code
stringlengths 1
1.05M
| repo_name
stringlengths 6
83
| path
stringlengths 3
242
| language
stringclasses 222
values | license
stringclasses 20
values | size
int64 1
1.05M
|
|---|---|---|---|---|---|
import { onContentUpdated } from 'vitepress';
import { computed, shallowRef } from 'vue';
import { getHeaders } from '../composables/outline';
import { useData } from './data';
export function useLocalNav() {
const { theme, frontmatter } = useData();
const headers = shallowRef([]);
const hasLocalNav = computed(() => {
return headers.value.length > 0;
});
onContentUpdated(() => {
headers.value = getHeaders(frontmatter.value.outline ?? theme.value.outline);
});
return {
headers,
hasLocalNav
};
}
|
2301_80257615/MateChat
|
docs/theme-default/composables/local-nav.js
|
JavaScript
|
mit
| 563
|
import { ref, watch } from 'vue';
import { useRoute } from 'vitepress';
export function useNav() {
const isScreenOpen = ref(false);
function openScreen() {
isScreenOpen.value = true;
window.addEventListener('resize', closeScreenOnTabletWindow);
}
function closeScreen() {
isScreenOpen.value = false;
window.removeEventListener('resize', closeScreenOnTabletWindow);
}
function toggleScreen() {
isScreenOpen.value ? closeScreen() : openScreen();
}
/**
* Close screen when the user resizes the window wider than tablet size.
*/
function closeScreenOnTabletWindow() {
window.outerWidth >= 768 && closeScreen();
}
const route = useRoute();
watch(() => route.path, closeScreen);
return {
isScreenOpen,
openScreen,
closeScreen,
toggleScreen
};
}
|
2301_80257615/MateChat
|
docs/theme-default/composables/nav.js
|
JavaScript
|
mit
| 885
|
import { onMounted, onUnmounted, onUpdated } from 'vue';
import { throttleAndDebounce } from '../support/utils';
// cached list of anchor elements from resolveHeaders
const resolvedHeaders = [];
export function resolveTitle(theme) {
return (
(typeof theme.outline === 'object' && !Array.isArray(theme.outline) && theme.outline.label) ||
theme.outlineTitle ||
''
);
}
export function getHeaders(range) {
const headers = [...document.querySelectorAll('.vp-doc :where(h1,h2,h3,h4,h5,h6)')]
.filter((el) => el.id && el.hasChildNodes())
.map((el) => {
const level = Number(el.tagName[1]);
return {
element: el,
title: serializeHeader(el),
link: el.id,
level,
};
});
return resolveHeaders(headers, range);
}
function serializeHeader(h) {
let ret = '';
for (const node of h.childNodes) {
if (node.nodeType === 1) {
if (
node.classList.contains('VPBadge') ||
node.classList.contains('header-anchor') ||
node.classList.contains('ignore-header')
) {
continue;
}
ret += node.textContent;
} else if (node.nodeType === 3) {
ret += node.textContent;
}
}
return ret.trim();
}
export function resolveHeaders(headers, range) {
if (range === false) {
return [];
}
const levelsRange =
(typeof range === 'object' && !Array.isArray(range) ? range.level : range) || 2;
const [high, low] =
typeof levelsRange === 'number'
? [levelsRange, levelsRange]
: levelsRange === 'deep'
? [2, 6]
: levelsRange;
return buildTree(headers, high, low);
}
export function useActiveAnchor(container) {
const onScroll = throttleAndDebounce(setActiveLink, 100);
let prevActiveLink = null;
onMounted(() => {
requestAnimationFrame(setActiveLink);
window.addEventListener('scroll', onScroll);
});
onUpdated(() => {
// sidebar update means a route change
activateLink(location.hash);
});
onUnmounted(() => {
window.removeEventListener('scroll', onScroll);
});
function setActiveLink() {
const scrollY = window.scrollY;
const innerHeight = window.innerHeight;
const offsetHeight = document.body.offsetHeight;
const isBottom = Math.abs(scrollY + innerHeight - offsetHeight) < 1;
const headers = resolvedHeaders
.map(({ element, link }) => ({
link,
top: getAbsoluteTop(element),
}))
.filter(({ top }) => !Number.isNaN(top))
.sort((a, b) => a.top - b.top);
// no headers available for active link
if (!headers.length) {
activateLink(null);
return;
}
// page top
if (scrollY < 1) {
activateLink(null);
return;
}
// page bottom - highlight last link
if (isBottom) {
activateLink(headers[headers.length - 1].link);
return;
}
// find the last header above the top of viewport
let activeLink = null;
for (const { link, top } of headers) {
if (top > scrollY + 4) {
break;
}
activeLink = link;
}
activateLink(activeLink);
}
function activateLink(hash) {
if (prevActiveLink) {
prevActiveLink.classList.remove('active');
}
if (hash == null) {
prevActiveLink = null;
} else {
prevActiveLink = container.value.querySelector(`.content-nav #nav-${hash}`);
}
const activeLink = prevActiveLink;
if (activeLink) {
activeLink.classList.add('active');
}
}
}
function getAbsoluteTop(element) {
let offsetTop = 0;
while (element !== document.body) {
if (element === null) {
// child element is:
// - not attached to the DOM (display: none)
// - set to fixed position (not scrollable)
// - body or html element (null offsetParent)
return NaN;
}
offsetTop += element.offsetTop;
element = element.offsetParent;
}
return offsetTop;
}
function buildTree(data, min, max) {
resolvedHeaders.length = 0;
const result = [];
const stack = [];
data.forEach((item) => {
const node = { ...item, children: [] };
let parent = stack[stack.length - 1];
while (parent && parent.level >= node.level) {
stack.pop();
parent = stack[stack.length - 1];
}
if (node.element.classList.contains('ignore-header') || (parent && 'shouldIgnore' in parent)) {
stack.push({ level: node.level, shouldIgnore: true });
return;
}
if (node.level > max || node.level < min) return;
resolvedHeaders.push({ element: node.element, link: node.link });
if (parent) parent.children.push(node);
else result.push(node);
stack.push(node);
});
return result;
}
|
2301_80257615/MateChat
|
docs/theme-default/composables/outline.js
|
JavaScript
|
mit
| 4,667
|
import { computed } from 'vue';
import { useData } from './data';
import { isActive } from '../../shared';
import { getSidebar, getFlatSideBarLinks } from '../support/sidebar';
export function usePrevNext() {
const { page, theme, frontmatter } = useData();
return computed(() => {
const sidebar = getSidebar(theme.value.sidebar, page.value.relativePath);
const links = getFlatSideBarLinks(sidebar);
// ignore inner-page links with hashes
const candidates = uniqBy(links, (link) => link.link.replace(/[?#].*$/, ''));
const index = candidates.findIndex((link) => {
return isActive(page.value.relativePath, link.link);
});
const hidePrev = (theme.value.docFooter?.prev === false && !frontmatter.value.prev) ||
frontmatter.value.prev === false;
const hideNext = (theme.value.docFooter?.next === false && !frontmatter.value.next) ||
frontmatter.value.next === false;
return {
prev: hidePrev
? undefined
: {
text: (typeof frontmatter.value.prev === 'string'
? frontmatter.value.prev
: typeof frontmatter.value.prev === 'object'
? frontmatter.value.prev.text
: undefined) ??
candidates[index - 1]?.docFooterText ??
candidates[index - 1]?.text,
link: (typeof frontmatter.value.prev === 'object'
? frontmatter.value.prev.link
: undefined) ?? candidates[index - 1]?.link
},
next: hideNext
? undefined
: {
text: (typeof frontmatter.value.next === 'string'
? frontmatter.value.next
: typeof frontmatter.value.next === 'object'
? frontmatter.value.next.text
: undefined) ??
candidates[index + 1]?.docFooterText ??
candidates[index + 1]?.text,
link: (typeof frontmatter.value.next === 'object'
? frontmatter.value.next.link
: undefined) ?? candidates[index + 1]?.link
}
};
});
}
function uniqBy(array, keyFn) {
const seen = new Set();
return array.filter((item) => {
const k = keyFn(item);
return seen.has(k) ? false : seen.add(k);
});
}
|
2301_80257615/MateChat
|
docs/theme-default/composables/prev-next.js
|
JavaScript
|
mit
| 2,580
|
import { useMediaQuery } from '@vueuse/core';
import { computed, onMounted, onUnmounted, ref, watch, watchEffect, watchPostEffect } from 'vue';
import { isActive } from '../../shared';
import { hasActiveLink as containsActiveLink, getSidebar, getSidebarGroups } from '../support/sidebar';
import { useData } from './data';
export function useSidebar() {
const { frontmatter, page, theme } = useData();
const is960 = useMediaQuery('(min-width: 960px)');
const isOpen = ref(false);
const _sidebar = computed(() => {
const sidebarConfig = theme.value.sidebar;
const relativePath = page.value.relativePath;
return sidebarConfig ? getSidebar(sidebarConfig, relativePath) : [];
});
const sidebar = ref(_sidebar.value);
watch(_sidebar, (next, prev) => {
if (JSON.stringify(next) !== JSON.stringify(prev))
sidebar.value = _sidebar.value;
});
const hasSidebar = computed(() => {
return (frontmatter.value.sidebar !== false &&
sidebar.value.length > 0 &&
frontmatter.value.layout !== 'home');
});
const leftAside = computed(() => {
if (hasAside)
return frontmatter.value.aside == null
? theme.value.aside === 'left'
: frontmatter.value.aside === 'left';
return false;
});
const hasAside = computed(() => {
if (frontmatter.value.layout === 'home')
return false;
if (frontmatter.value.aside != null)
return !!frontmatter.value.aside;
return theme.value.aside !== false;
});
const isSidebarEnabled = computed(() => hasSidebar.value && is960.value);
const sidebarGroups = computed(() => {
return hasSidebar.value ? getSidebarGroups(sidebar.value) : [];
});
function open() {
isOpen.value = true;
}
function close() {
isOpen.value = false;
}
function toggle() {
isOpen.value ? close() : open();
}
return {
isOpen,
sidebar,
sidebarGroups,
hasSidebar,
hasAside,
leftAside,
isSidebarEnabled,
open,
close,
toggle
};
}
/**
* a11y: cache the element that opened the Sidebar (the menu button) then
* focus that button again when Menu is closed with Escape key.
*/
export function useCloseSidebarOnEscape(isOpen, close) {
let triggerElement;
watchEffect(() => {
triggerElement = isOpen.value
? document.activeElement
: undefined;
});
onMounted(() => {
window.addEventListener('keyup', onEscape);
});
onUnmounted(() => {
window.removeEventListener('keyup', onEscape);
});
function onEscape(e) {
if (e.key === 'Escape' && isOpen.value) {
close();
triggerElement?.focus();
}
}
}
export function useSidebarControl(item) {
const { page, hash } = useData();
const collapsed = ref(false);
const collapsible = computed(() => {
return item.value.collapsed != null;
});
const isLink = computed(() => {
return !!item.value.link;
});
const isActiveLink = ref(false);
const updateIsActiveLink = () => {
isActiveLink.value = isActive(page.value.relativePath, item.value.link);
};
watch([page, item, hash], updateIsActiveLink);
onMounted(updateIsActiveLink);
const hasActiveLink = computed(() => {
if (isActiveLink.value) {
return true;
}
return item.value.items
? containsActiveLink(page.value.relativePath, item.value.items)
: false;
});
const hasChildren = computed(() => {
return !!(item.value.items && item.value.items.length);
});
watchEffect(() => {
collapsed.value = !!(collapsible.value && item.value.collapsed);
});
watchPostEffect(() => {
;
(isActiveLink.value || hasActiveLink.value) && (collapsed.value = false);
});
function toggle() {
if (collapsible.value) {
collapsed.value = !collapsed.value;
}
}
return {
collapsed,
collapsible,
isLink,
isActiveLink,
hasActiveLink,
hasChildren,
toggle
};
}
|
2301_80257615/MateChat
|
docs/theme-default/composables/sidebar.js
|
JavaScript
|
mit
| 4,287
|
import { onMounted, onUnmounted } from 'vue';
import { throttleAndDebounce } from '../support/utils';
/**
* Defines grid configuration for each sponsor size in tuple.
*
* [Screen width, Column size]
*
* It sets grid size on matching screen size. For example, `[768, 5]` will
* set 5 columns when screen size is bigger or equal to 768px.
*
* Column will set only when item size is bigger than the column size. For
* example, even we define 5 columns, if we only have 1 sponsor yet, we would
* like to show it in 1 column to make it stand out.
*/
const GridSettings = {
xmini: [[0, 2]],
mini: [],
small: [
[920, 6],
[768, 5],
[640, 4],
[480, 3],
[0, 2]
],
medium: [
[960, 5],
[832, 4],
[640, 3],
[480, 2]
],
big: [
[832, 3],
[640, 2]
]
};
export function useSponsorsGrid({ el, size = 'medium' }) {
const onResize = throttleAndDebounce(manage, 100);
onMounted(() => {
manage();
window.addEventListener('resize', onResize);
});
onUnmounted(() => {
window.removeEventListener('resize', onResize);
});
function manage() {
adjustSlots(el.value, size);
}
}
function adjustSlots(el, size) {
const tsize = el.children.length;
const asize = el.querySelectorAll('.vp-sponsor-grid-item:not(.empty)').length;
const grid = setGrid(el, size, asize);
manageSlots(el, grid, tsize, asize);
}
function setGrid(el, size, items) {
const settings = GridSettings[size];
const screen = window.innerWidth;
let grid = 1;
settings.some(([breakpoint, value]) => {
if (screen >= breakpoint) {
grid = items < value ? items : value;
return true;
}
});
setGridData(el, grid);
return grid;
}
function setGridData(el, value) {
el.dataset.vpGrid = String(value);
}
function manageSlots(el, grid, tsize, asize) {
const diff = tsize - asize;
const rem = asize % grid;
const drem = rem === 0 ? rem : grid - rem;
neutralizeSlots(el, drem - diff);
}
function neutralizeSlots(el, count) {
if (count === 0) {
return;
}
count > 0 ? addSlots(el, count) : removeSlots(el, count * -1);
}
function addSlots(el, count) {
for (let i = 0; i < count; i++) {
const slot = document.createElement('div');
slot.classList.add('vp-sponsor-grid-item', 'empty');
el.append(slot);
}
}
function removeSlots(el, count) {
for (let i = 0; i < count; i++) {
el.removeChild(el.lastElementChild);
}
}
|
2301_80257615/MateChat
|
docs/theme-default/composables/sponsor-grid.js
|
JavaScript
|
mit
| 2,596
|
import './styles/fonts.css';
import './styles/global.scss';
import Layout from './components/Layout.vue';
export * from './without-fonts';
export { Layout };
import { ThemeServiceInit, infinityTheme, galaxyTheme } from 'devui-theme';
import { ThemeKey } from './components/datas/type';
// 默认使用无限主题
export const themeServiceInstance = ThemeServiceInit(
{
infinityTheme,
galaxyTheme,
},
'infinityTheme',
);
if (typeof localStorage !== 'undefined' && localStorage.getItem('theme') === ThemeKey.Galaxy) {
themeServiceInstance.applyTheme(galaxyTheme);
}
|
2301_80257615/MateChat
|
docs/theme-default/index.js
|
JavaScript
|
mit
| 583
|
@media (prefers-reduced-motion: reduce) {
*,
::before,
::after {
animation-delay: -1ms !important;
animation-duration: 1ms !important;
animation-iteration-count: 1 !important;
background-attachment: initial !important;
scroll-behavior: auto !important;
transition-duration: 0s !important;
transition-delay: 0s !important;
}
}
*,
::before,
::after {
box-sizing: border-box;
}
html {
line-height: 1.4;
font-size: 16px;
-webkit-text-size-adjust: 100%;
}
html.dark {
color-scheme: dark;
}
body {
margin: 0;
width: 100%;
min-width: 320px;
min-height: 100vh;
line-height: 24px;
font-family: var(--vp-font-family-base);
font-size: 16px;
font-weight: 400;
color: var(--vp-c-text-1);
font-synthesis: style;
text-rendering: optimizeLegibility;
-webkit-font-smoothing: antialiased;
-moz-osx-font-smoothing: grayscale;
}
main {
display: block;
}
h1,
h2,
h3,
h4,
h5,
h6 {
margin: 0;
line-height: 24px;
font-size: 16px;
font-weight: 400;
}
p {
margin: 0;
}
strong,
b {
font-weight: 600;
}
/**
* Avoid 300ms click delay on touch devices that support the `touch-action`
* CSS property.
*
* In particular, unlike most other browsers, IE11+Edge on Windows 10 on
* touch devices and IE Mobile 10-11 DON'T remove the click delay when
* `<meta name="viewport" content="width=device-width">` is present.
* However, they DO support removing the click delay via
* `touch-action: manipulation`.
*
* See:
* - http://v4-alpha.getbootstrap.com/content/reboot/#click-delay-optimization-for-touch
* - http://caniuse.com/#feat=css-touch-action
* - http://patrickhlauke.github.io/touch/tests/results/#suppressing-300ms-delay
*/
a,
area,
button,
[role='button'],
input,
label,
select,
summary,
textarea {
touch-action: manipulation;
}
a {
color: inherit;
text-decoration: inherit;
}
ol,
ul {
list-style: none;
margin: 0;
padding: 0;
}
blockquote {
margin: 0;
}
body pre,
body code,
body kbd,
body samp {
font-family: var(--vp-font-family-mono);
}
img,
svg,
video,
canvas,
audio,
iframe,
embed,
object {
display: block;
}
figure {
margin: 0;
}
img,
video {
max-width: 100%;
height: auto;
}
button,
input,
optgroup,
select,
textarea {
border: 0;
padding: 0;
line-height: inherit;
color: inherit;
}
button {
padding: 0;
font-family: inherit;
background-color: transparent;
background-image: none;
}
button:enabled,
[role='button']:enabled {
cursor: pointer;
}
button:focus,
button:focus-visible {
outline: 1px dotted;
outline: 4px auto -webkit-focus-ring-color;
}
button:focus:not(:focus-visible) {
outline: none !important;
}
input:focus,
textarea:focus,
select:focus {
outline: none;
}
table {
border-collapse: collapse;
}
input {
background-color: transparent;
}
input:-ms-input-placeholder,
textarea:-ms-input-placeholder {
color: var(--vp-c-text-3);
}
input::-ms-input-placeholder,
textarea::-ms-input-placeholder {
color: var(--vp-c-text-3);
}
input::placeholder,
textarea::placeholder {
color: var(--vp-c-text-3);
}
input::-webkit-outer-spin-button,
input::-webkit-inner-spin-button {
-webkit-appearance: none;
margin: 0;
}
input[type='number'] {
-moz-appearance: textfield;
}
textarea {
resize: vertical;
}
select {
-webkit-appearance: none;
}
fieldset {
margin: 0;
padding: 0;
}
h1,
h2,
h3,
h4,
h5,
h6,
li,
p {
overflow-wrap: break-word;
}
vite-error-overlay {
z-index: 9999;
}
mjx-container {
overflow-x: auto;
}
mjx-container > svg {
display: inline-block;
margin: auto;
}
|
2301_80257615/MateChat
|
docs/theme-default/styles/base.css
|
CSS
|
mit
| 3,568
|
.custom-block {
border: 1px solid transparent;
border-radius: 8px;
padding: 16px 16px 8px;
line-height: 24px;
font-size: var(--vp-custom-block-font-size);
color: var(--vp-c-text-2);
}
.custom-block.info {
border-color: var(--vp-custom-block-info-border);
color: var(--vp-custom-block-info-text);
background-color: var(--vp-custom-block-info-bg);
}
.custom-block.info a,
.custom-block.info code {
color: var(--vp-c-brand-1);
}
.custom-block.info a:hover,
.custom-block.info a:hover > code {
color: var(--vp-c-brand-2);
}
.custom-block.info code {
background-color: var(--vp-custom-block-info-code-bg);
}
.custom-block.note {
border-color: var(--vp-custom-block-note-border);
color: var(--vp-custom-block-note-text);
background-color: var(--vp-custom-block-note-bg);
}
.custom-block.note a,
.custom-block.note code {
color: var(--vp-c-brand-1);
}
.custom-block.note a:hover,
.custom-block.note a:hover > code {
color: var(--vp-c-brand-2);
}
.custom-block.note code {
background-color: var(--vp-custom-block-note-code-bg);
}
.custom-block.tip {
border-color: var(--vp-custom-block-tip-border);
color: var(--vp-custom-block-tip-text);
background-color: var(--vp-custom-block-tip-bg);
}
.custom-block.tip a,
.custom-block.tip code {
color: var(--vp-c-tip-1);
}
.custom-block.tip a:hover,
.custom-block.tip a:hover > code {
color: var(--vp-c-tip-2);
}
.custom-block.tip code {
background-color: var(--vp-custom-block-tip-code-bg);
}
.custom-block.important {
border-color: var(--vp-custom-block-important-border);
color: var(--vp-custom-block-important-text);
background-color: var(--vp-custom-block-important-bg);
}
.custom-block.important a,
.custom-block.important code {
color: var(--vp-c-important-1);
}
.custom-block.important a:hover,
.custom-block.important a:hover > code {
color: var(--vp-c-important-2);
}
.custom-block.important code {
background-color: var(--vp-custom-block-important-code-bg);
}
.custom-block.warning {
border-color: var(--vp-custom-block-warning-border);
color: var(--vp-custom-block-warning-text);
background-color: var(--vp-custom-block-warning-bg);
}
.custom-block.warning a,
.custom-block.warning code {
color: var(--vp-c-warning-1);
}
.custom-block.warning a:hover,
.custom-block.warning a:hover > code {
color: var(--vp-c-warning-2);
}
.custom-block.warning code {
background-color: var(--vp-custom-block-warning-code-bg);
}
.custom-block.danger {
border-color: var(--vp-custom-block-danger-border);
color: var(--vp-custom-block-danger-text);
background-color: var(--vp-custom-block-danger-bg);
}
.custom-block.danger a,
.custom-block.danger code {
color: var(--vp-c-danger-1);
}
.custom-block.danger a:hover,
.custom-block.danger a:hover > code {
color: var(--vp-c-danger-2);
}
.custom-block.danger code {
background-color: var(--vp-custom-block-danger-code-bg);
}
.custom-block.caution {
border-color: var(--vp-custom-block-caution-border);
color: var(--vp-custom-block-caution-text);
background-color: var(--vp-custom-block-caution-bg);
}
.custom-block.caution a,
.custom-block.caution code {
color: var(--vp-c-caution-1);
}
.custom-block.caution a:hover,
.custom-block.caution a:hover > code {
color: var(--vp-c-caution-2);
}
.custom-block.caution code {
background-color: var(--vp-custom-block-caution-code-bg);
}
.custom-block.details {
border-color: var(--vp-custom-block-details-border);
color: var(--vp-custom-block-details-text);
background-color: var(--vp-custom-block-details-bg);
}
.custom-block.details a {
color: var(--vp-c-brand-1);
}
.custom-block.details a:hover,
.custom-block.details a:hover > code {
color: var(--vp-c-brand-2);
}
.custom-block.details code {
background-color: var(--vp-custom-block-details-code-bg);
}
.custom-block-title {
font-weight: 600;
}
.custom-block p + p {
margin: 8px 0;
}
.custom-block.details summary {
margin: 0 0 8px;
font-weight: 700;
cursor: pointer;
user-select: none;
}
.custom-block.details summary + p {
margin: 8px 0;
}
.custom-block a {
color: inherit;
font-weight: 600;
text-decoration: underline;
text-underline-offset: 2px;
transition: opacity 0.25s;
}
.custom-block a:hover {
opacity: 0.75;
}
.custom-block code {
font-size: var(--vp-custom-block-code-font-size);
}
.custom-block.custom-block th,
.custom-block.custom-block blockquote > p {
font-size: var(--vp-custom-block-font-size);
color: inherit;
}
|
2301_80257615/MateChat
|
docs/theme-default/styles/components/custom-block.css
|
CSS
|
mit
| 4,480
|
.vp-code-group {
margin-top: 16px;
}
.vp-code-group .tabs {
position: relative;
display: flex;
margin-right: -24px;
margin-left: -24px;
padding: 0 12px;
background-color: var(--vp-code-tab-bg);
overflow-x: auto;
overflow-y: hidden;
box-shadow: inset 0 -1px var(--vp-code-tab-divider);
}
@media (min-width: 640px) {
.vp-code-group .tabs {
margin-right: 0;
margin-left: 0;
border-radius: 8px 8px 0 0;
}
}
.vp-code-group .tabs input {
position: fixed;
opacity: 0;
pointer-events: none;
}
.vp-code-group .tabs label {
position: relative;
display: inline-block;
border-bottom: 1px solid transparent;
padding: 0 12px;
line-height: 48px;
font-size: 14px;
font-weight: 500;
color: var(--vp-code-tab-text-color);
white-space: nowrap;
cursor: pointer;
transition: color 0.25s;
}
.vp-code-group .tabs label::after {
position: absolute;
right: 8px;
bottom: -1px;
left: 8px;
z-index: 1;
height: 2px;
border-radius: 2px;
content: '';
background-color: transparent;
transition: background-color 0.25s;
}
.vp-code-group label:hover {
color: var(--vp-code-tab-hover-text-color);
}
.vp-code-group input:checked + label {
color: var(--vp-code-tab-active-text-color);
}
.vp-code-group input:checked + label::after {
background-color: var(--vp-code-tab-active-bar-color);
}
.vp-code-group div[class*='language-'],
.vp-block {
display: none;
margin-top: 0 !important;
border-top-left-radius: 0 !important;
border-top-right-radius: 0 !important;
}
.vp-code-group div[class*='language-'].active,
.vp-block.active {
display: block;
}
.vp-block {
padding: 20px 24px;
}
|
2301_80257615/MateChat
|
docs/theme-default/styles/components/vp-code-group.css
|
CSS
|
mit
| 1,656
|
.dark .vp-code span {
color: var(--shiki-dark, inherit);
}
html:not(.dark) .vp-code span {
color: var(--shiki-light, inherit);
}
|
2301_80257615/MateChat
|
docs/theme-default/styles/components/vp-code.css
|
CSS
|
mit
| 134
|
/**
* Headings
* -------------------------------------------------------------------------- */
.vp-doc h1,
.vp-doc h2,
.vp-doc h3,
.vp-doc h4,
.vp-doc h5,
.vp-doc h6 {
position: relative;
font-weight: 600;
outline: none;
}
.vp-doc h1 {
letter-spacing: -0.02em;
line-height: 40px;
font-size: 28px;
}
.vp-doc h2 {
margin: 48px 0 16px;
border-top: 1px solid var(--vp-c-divider);
padding-top: 24px;
letter-spacing: -0.02em;
line-height: 32px;
font-size: 24px;
}
.vp-doc h3 {
margin: 32px 0 0;
letter-spacing: -0.01em;
line-height: 28px;
font-size: 20px;
}
.vp-doc h4 {
margin: 24px 0 0;
letter-spacing: -0.01em;
line-height: 24px;
font-size: 18px;
}
.vp-doc .header-anchor {
display: none;
}
@media (min-width: 768px) {
.vp-doc h1 {
letter-spacing: -0.02em;
line-height: 40px;
font-size: 32px;
}
}
/**
* Paragraph and inline elements
* -------------------------------------------------------------------------- */
.vp-doc p,
.vp-doc summary {
margin: 16px 0;
}
.vp-doc p {
line-height: 28px;
}
.vp-doc blockquote {
margin: 16px 0;
border-left: 2px solid var(--vp-c-divider);
padding-left: 16px;
transition: border-color 0.5s;
color: var(--vp-c-text-2);
}
.vp-doc blockquote > p {
margin: 0;
font-size: 16px;
transition: color 0.5s;
}
.vp-doc a {
font-weight: 500;
color: var(--vp-c-brand-1);
text-decoration: underline;
text-underline-offset: 2px;
transition:
color 0.25s,
opacity 0.25s;
}
.vp-doc a:hover {
color: var(--vp-c-brand-2);
}
.vp-doc strong {
font-weight: 600;
}
/**
* Lists
* -------------------------------------------------------------------------- */
.vp-doc ul,
.vp-doc ol {
padding-left: 1.25rem;
margin: 16px 0;
}
.vp-doc ul {
list-style: disc;
}
.vp-doc ol {
list-style: decimal;
}
.vp-doc li + li {
margin-top: 8px;
}
.vp-doc li > ol,
.vp-doc li > ul {
margin: 8px 0 0;
}
/**
* Table
* -------------------------------------------------------------------------- */
.vp-doc table {
display: block;
border-collapse: collapse;
margin: 20px 0;
overflow-x: auto;
}
.vp-doc tr {
background-color: var(--vp-c-bg);
border-top: 1px solid var(--vp-c-divider);
transition: background-color 0.5s;
}
.vp-doc tr:nth-child(2n) {
background-color: var(--vp-c-bg-soft);
}
.vp-doc th,
.vp-doc td {
border: 1px solid var(--vp-c-divider);
padding: 8px 16px;
}
.vp-doc th {
text-align: left;
font-size: 14px;
font-weight: 600;
color: var(--vp-c-text-2);
background-color: var(--vp-c-bg-soft);
}
.vp-doc td {
font-size: 14px;
}
/**
* Decorational elements
* -------------------------------------------------------------------------- */
.vp-doc hr {
margin: 16px 0;
border: none;
border-top: 1px solid var(--vp-c-divider);
}
/**
* Custom Block
* -------------------------------------------------------------------------- */
.vp-doc .custom-block {
margin: 16px 0;
}
.vp-doc .custom-block p {
margin: 8px 0;
line-height: 24px;
}
.vp-doc .custom-block p:first-child {
margin: 0;
}
.vp-doc .custom-block div[class*='language-'] {
margin: 8px 0;
border-radius: 8px;
}
.vp-doc .custom-block div[class*='language-'] code {
font-weight: 400;
background-color: transparent;
}
.vp-doc .custom-block .vp-code-group .tabs {
margin: 0;
border-radius: 8px 8px 0 0;
}
/**
* Code
* -------------------------------------------------------------------------- */
/* inline code */
.vp-doc :not(pre, h1, h2, h3, h4, h5, h6) > code {
font-size: var(--vp-code-font-size);
color: var(--vp-code-color);
}
.vp-doc :not(pre) > code {
border-radius: 4px;
padding: 3px 6px;
background-color: var(--vp-code-bg);
transition:
color 0.25s,
background-color 0.5s;
}
.vp-doc a > code {
color: var(--vp-code-link-color);
}
.vp-doc a:hover > code {
color: var(--vp-code-link-hover-color);
}
.vp-doc h1 > code,
.vp-doc h2 > code,
.vp-doc h3 > code,
.vp-doc h4 > code {
font-size: 0.9em;
}
.vp-doc div[class*='language-'],
.vp-block {
border-radius: 8px;
position: relative;
margin: 16px 0px;
background-color: var(--vp-code-block-bg);
overflow-x: auto;
transition: background-color 0.5s;
}
@media (min-width: 640px) {
.vp-doc div[class*='language-'],
.vp-block {
border-radius: 8px;
margin: 16px 0;
}
}
@media (max-width: 639px) {
.vp-doc li div[class*='language-'] {
border-radius: 8px 0 0 8px;
}
}
.vp-doc div[class*='language-'] + div[class*='language-'],
.vp-doc div[class$='-api'] + div[class*='language-'],
.vp-doc div[class*='language-'] + div[class$='-api'] > div[class*='language-'] {
margin-top: -8px;
}
.vp-doc [class*='language-'] pre,
.vp-doc [class*='language-'] code {
/*rtl:ignore*/
direction: ltr;
/*rtl:ignore*/
text-align: left;
white-space: pre;
word-spacing: normal;
word-break: normal;
word-wrap: normal;
-moz-tab-size: 4;
-o-tab-size: 4;
tab-size: 4;
-webkit-hyphens: none;
-moz-hyphens: none;
-ms-hyphens: none;
hyphens: none;
}
.vp-doc [class*='language-'] pre {
position: relative;
z-index: 1;
margin: 0;
padding: 20px 0;
background: transparent;
overflow-x: auto;
}
.vp-doc [class*='language-'] code {
display: block;
padding: 0 24px;
width: fit-content;
min-width: 100%;
line-height: var(--vp-code-line-height);
font-size: var(--vp-code-font-size);
color: var(--vp-code-block-color);
transition: color 0.5s;
}
.vp-doc [class*='language-'] code .highlighted {
background-color: var(--vp-code-line-highlight-color);
transition: background-color 0.5s;
margin: 0 -24px;
padding: 0 24px;
width: calc(100% + 2 * 24px);
display: inline-block;
}
.vp-doc [class*='language-'] code .highlighted.error {
background-color: var(--vp-code-line-error-color);
}
.vp-doc [class*='language-'] code .highlighted.warning {
background-color: var(--vp-code-line-warning-color);
}
.vp-doc [class*='language-'] code .diff {
transition: background-color 0.5s;
margin: 0 -24px;
padding: 0 24px;
width: calc(100% + 2 * 24px);
display: inline-block;
}
.vp-doc [class*='language-'] code .diff::before {
position: absolute;
left: 10px;
}
.vp-doc [class*='language-'] .has-focused-lines .line:not(.has-focus) {
filter: blur(0.095rem);
opacity: 0.4;
transition:
filter 0.35s,
opacity 0.35s;
}
.vp-doc [class*='language-'] .has-focused-lines .line:not(.has-focus) {
opacity: 0.7;
transition:
filter 0.35s,
opacity 0.35s;
}
.vp-doc [class*='language-']:hover .has-focused-lines .line:not(.has-focus) {
filter: blur(0);
opacity: 1;
}
.vp-doc [class*='language-'] code .diff.remove {
background-color: var(--vp-code-line-diff-remove-color);
opacity: 0.7;
}
.vp-doc [class*='language-'] code .diff.remove::before {
content: '-';
color: var(--vp-code-line-diff-remove-symbol-color);
}
.vp-doc [class*='language-'] code .diff.add {
background-color: var(--vp-code-line-diff-add-color);
}
.vp-doc [class*='language-'] code .diff.add::before {
content: '+';
color: var(--vp-code-line-diff-add-symbol-color);
}
.vp-doc div[class*='language-'].line-numbers-mode {
/*rtl:ignore*/
padding-left: 32px;
}
.vp-doc .line-numbers-wrapper {
position: absolute;
top: 0;
bottom: 0;
/*rtl:ignore*/
left: 0;
z-index: 3;
/*rtl:ignore*/
border-right: 1px solid var(--vp-code-block-divider-color);
padding-top: 20px;
width: 32px;
text-align: center;
font-family: var(--vp-font-family-mono);
line-height: var(--vp-code-line-height);
font-size: var(--vp-code-font-size);
color: var(--vp-code-line-number-color);
transition:
border-color 0.5s,
color 0.5s;
}
.vp-doc [class*='language-'] > button.copy {
/*rtl:ignore*/
direction: ltr;
position: absolute;
top: 12px;
/*rtl:ignore*/
right: 12px;
z-index: 3;
border: 1px solid var(--vp-code-copy-code-border-color);
border-radius: 4px;
width: 40px;
height: 40px;
background-color: var(--vp-code-copy-code-bg);
opacity: 0;
cursor: pointer;
background-image: var(--vp-icon-copy);
background-position: 50%;
background-size: 20px;
background-repeat: no-repeat;
transition:
border-color 0.25s,
background-color 0.25s,
opacity 0.25s;
}
.vp-doc [class*='language-']:hover > button.copy,
.vp-doc [class*='language-'] > button.copy:focus {
opacity: 1;
}
.vp-doc [class*='language-'] > button.copy:hover,
.vp-doc [class*='language-'] > button.copy.copied {
border-color: var(--vp-code-copy-code-hover-border-color);
background-color: var(--vp-code-copy-code-hover-bg);
}
.vp-doc [class*='language-'] > button.copy.copied,
.vp-doc [class*='language-'] > button.copy:hover.copied {
/*rtl:ignore*/
border-radius: 0 4px 4px 0;
background-color: var(--vp-code-copy-code-hover-bg);
background-image: var(--vp-icon-copied);
}
.vp-doc [class*='language-'] > button.copy.copied::before,
.vp-doc [class*='language-'] > button.copy:hover.copied::before {
position: relative;
top: -1px;
/*rtl:ignore*/
transform: translateX(calc(-100% - 1px));
display: flex;
justify-content: center;
align-items: center;
border: 1px solid var(--vp-code-copy-code-hover-border-color);
/*rtl:ignore*/
border-right: 0;
border-radius: 4px 0 0 4px;
padding: 0 10px;
width: fit-content;
height: 40px;
text-align: center;
font-size: 12px;
font-weight: 500;
color: var(--vp-code-copy-code-active-text);
background-color: var(--vp-code-copy-code-hover-bg);
white-space: nowrap;
content: var(--vp-code-copy-copied-text-content);
}
.vp-doc [class*='language-'] > span.lang {
position: absolute;
top: 2px;
/*rtl:ignore*/
right: 8px;
z-index: 2;
font-size: 12px;
font-weight: 500;
user-select: none;
color: var(--vp-code-lang-color);
transition:
color 0.4s,
opacity 0.4s;
}
.vp-doc [class*='language-']:hover > button.copy + span.lang,
.vp-doc [class*='language-'] > button.copy:focus + span.lang {
opacity: 0;
}
/**
* Component: Team
* -------------------------------------------------------------------------- */
.vp-doc .VPTeamMembers {
margin-top: 24px;
}
.vp-doc .VPTeamMembers.small.count-1 .container {
margin: 0 !important;
max-width: calc((100% - 24px) / 2) !important;
}
.vp-doc .VPTeamMembers.small.count-2 .container,
.vp-doc .VPTeamMembers.small.count-3 .container {
max-width: 100% !important;
}
.vp-doc .VPTeamMembers.medium.count-1 .container {
margin: 0 !important;
max-width: calc((100% - 24px) / 2) !important;
}
/**
* External links
* -------------------------------------------------------------------------- */
/* prettier-ignore */
:is(.vp-external-link-icon, .vp-doc a[href*='://'], .vp-doc a[target='_blank']):not(.no-icon)::after {
display: inline-block;
margin-top: -1px;
margin-left: 4px;
width: 11px;
height: 11px;
background: currentColor;
color: var(--vp-c-text-3);
flex-shrink: 0;
--icon: url("data:image/svg+xml, %3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 24 24' %3E%3Cpath d='M0 0h24v24H0V0z' fill='none' /%3E%3Cpath d='M9 5v2h6.59L4 18.59 5.41 20 17 8.41V15h2V5H9z' /%3E%3C/svg%3E");
-webkit-mask-image: var(--icon);
mask-image: var(--icon);
}
.vp-external-link-icon::after {
content: '';
}
/* prettier-ignore */
.external-link-icon-enabled :is(.vp-doc a[href*='://'], .vp-doc a[target='_blank'])::after {
content: '';
color: currentColor;
}
|
2301_80257615/MateChat
|
docs/theme-default/styles/components/vp-doc.css
|
CSS
|
mit
| 11,390
|
/* webfont-marker-begin */
@import url('https://fonts.googleapis.com/css2?family=Inter:ital,opsz,wght@0,14..32,100..900;1,14..32,100..900&display=swap');
/* webfont-marker-end */
@font-face {
font-family: Inter;
font-style: normal;
font-weight: 100 900;
font-display: swap;
src: url('../fonts/inter-roman-cyrillic-ext.woff2') format('woff2');
unicode-range: U+0460-052F, U+1C80-1C88, U+20B4, U+2DE0-2DFF, U+A640-A69F,
U+FE2E-FE2F;
}
@font-face {
font-family: Inter;
font-style: normal;
font-weight: 100 900;
font-display: swap;
src: url('../fonts/inter-roman-cyrillic.woff2') format('woff2');
unicode-range: U+0301, U+0400-045F, U+0490-0491, U+04B0-04B1, U+2116;
}
@font-face {
font-family: Inter;
font-style: normal;
font-weight: 100 900;
font-display: swap;
src: url('../fonts/inter-roman-greek-ext.woff2') format('woff2');
unicode-range: U+1F00-1FFF;
}
@font-face {
font-family: Inter;
font-style: normal;
font-weight: 100 900;
font-display: swap;
src: url('../fonts/inter-roman-greek.woff2') format('woff2');
unicode-range: U+0370-0377, U+037A-037F, U+0384-038A, U+038C, U+038E-03A1,
U+03A3-03FF;
}
@font-face {
font-family: Inter;
font-style: normal;
font-weight: 100 900;
font-display: swap;
src: url('../fonts/inter-roman-vietnamese.woff2') format('woff2');
unicode-range: U+0102-0103, U+0110-0111, U+0128-0129, U+0168-0169, U+01A0-01A1,
U+01AF-01B0, U+0300-0301, U+0303-0304, U+0308-0309, U+0323, U+0329,
U+1EA0-1EF9, U+20AB;
}
@font-face {
font-family: Inter;
font-style: normal;
font-weight: 100 900;
font-display: swap;
src: url('../fonts/inter-roman-latin-ext.woff2') format('woff2');
unicode-range: U+0100-02AF, U+0304, U+0308, U+0329, U+1E00-1E9F, U+1EF2-1EFF,
U+2020, U+20A0-20AB, U+20AD-20C0, U+2113, U+2C60-2C7F, U+A720-A7FF;
}
@font-face {
font-family: Inter;
font-style: normal;
font-weight: 100 900;
font-display: swap;
src: url('../fonts/inter-roman-latin.woff2') format('woff2');
unicode-range: U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA,
U+02DC, U+0304, U+0308, U+0329, U+2000-206F, U+2074, U+20AC, U+2122, U+2191,
U+2193, U+2212, U+2215, U+FEFF, U+FFFD;
}
@font-face {
font-family: Inter;
font-style: italic;
font-weight: 100 900;
font-display: swap;
src: url('../fonts/inter-italic-cyrillic-ext.woff2') format('woff2');
unicode-range: U+0460-052F, U+1C80-1C88, U+20B4, U+2DE0-2DFF, U+A640-A69F,
U+FE2E-FE2F;
}
@font-face {
font-family: Inter;
font-style: italic;
font-weight: 100 900;
font-display: swap;
src: url('../fonts/inter-italic-cyrillic.woff2') format('woff2');
unicode-range: U+0301, U+0400-045F, U+0490-0491, U+04B0-04B1, U+2116;
}
@font-face {
font-family: Inter;
font-style: italic;
font-weight: 100 900;
font-display: swap;
src: url('../fonts/inter-italic-greek-ext.woff2') format('woff2');
unicode-range: U+1F00-1FFF;
}
@font-face {
font-family: Inter;
font-style: italic;
font-weight: 100 900;
font-display: swap;
src: url('../fonts/inter-italic-greek.woff2') format('woff2');
unicode-range: U+0370-0377, U+037A-037F, U+0384-038A, U+038C, U+038E-03A1,
U+03A3-03FF;
}
@font-face {
font-family: Inter;
font-style: italic;
font-weight: 100 900;
font-display: swap;
src: url('../fonts/inter-italic-vietnamese.woff2') format('woff2');
unicode-range: U+0102-0103, U+0110-0111, U+0128-0129, U+0168-0169, U+01A0-01A1,
U+01AF-01B0, U+0300-0301, U+0303-0304, U+0308-0309, U+0323, U+0329,
U+1EA0-1EF9, U+20AB;
}
@font-face {
font-family: Inter;
font-style: italic;
font-weight: 100 900;
font-display: swap;
src: url('../fonts/inter-italic-latin-ext.woff2') format('woff2');
unicode-range: U+0100-02AF, U+0304, U+0308, U+0329, U+1E00-1E9F, U+1EF2-1EFF,
U+2020, U+20A0-20AB, U+20AD-20C0, U+2113, U+2C60-2C7F, U+A720-A7FF;
}
@font-face {
font-family: Inter;
font-style: italic;
font-weight: 100 900;
font-display: swap;
src: url('../fonts/inter-italic-latin.woff2') format('woff2');
unicode-range: U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA,
U+02DC, U+0304, U+0308, U+0329, U+2000-206F, U+2074, U+20AC, U+2122, U+2191,
U+2193, U+2212, U+2215, U+FEFF, U+FFFD;
}
@font-face {
font-family: 'Punctuation SC';
font-weight: 400;
src: local('PingFang SC Regular'), local('Noto Sans CJK SC'),
local('Microsoft YaHei');
unicode-range: U+201C, U+201D, U+2018, U+2019, U+2E3A, U+2014, U+2013, U+2026,
U+00B7, U+007E, U+002F;
}
@font-face {
font-family: 'Punctuation SC';
font-weight: 500;
src: local('PingFang SC Medium'), local('Noto Sans CJK SC'),
local('Microsoft YaHei');
unicode-range: U+201C, U+201D, U+2018, U+2019, U+2E3A, U+2014, U+2013, U+2026,
U+00B7, U+007E, U+002F;
}
@font-face {
font-family: 'Punctuation SC';
font-weight: 600;
src: local('PingFang SC Semibold'), local('Noto Sans CJK SC Bold'),
local('Microsoft YaHei Bold');
unicode-range: U+201C, U+201D, U+2018, U+2019, U+2E3A, U+2014, U+2013, U+2026,
U+00B7, U+007E, U+002F;
}
@font-face {
font-family: 'Punctuation SC';
font-weight: 700;
src: local('PingFang SC Semibold'), local('Noto Sans CJK SC Bold'),
local('Microsoft YaHei Bold');
unicode-range: U+201C, U+201D, U+2018, U+2019, U+2E3A, U+2014, U+2013, U+2026,
U+00B7, U+007E, U+002F;
}
/* Generate the subsetted fonts using: `pyftsubset <file>.woff2 --unicodes="<range>" --output-file="inter-<style>-<subset>.woff2" --flavor=woff2` */
|
2301_80257615/MateChat
|
docs/theme-default/styles/fonts.css
|
CSS
|
mit
| 5,523
|
@import 'devui-theme/styles-var/devui-var.scss';
html {
scrollbar-width: thin;
scrollbar-color: transparent transparent;
overflow-y: scroll; //这是为了兼容ie8，不支持:root, vw
}
html:hover {
scrollbar-color: $devui-line transparent;
}
body[ui-theme='galaxy-theme'] #content-slider-tabs {
--devui-base-bg: #3f3f3f;
ul {
background-color: #1a1a1c99 !important;
}
}
body[ui-theme='galaxy-theme'] #icon-container {
background-color: #1a1a1c99 !important;
}
body {
background-color: $devui-base-bg;
}
.devui-scrollbar::-webkit-scrollbar {
width: 8px;
height: 8px;
}
.devui-scrollbar::-webkit-scrollbar-track {
background-color: transparent;
}
.devui-scrollbar::-webkit-scrollbar-thumb {
border-radius: 8px;
background-color: $devui-line;
}
.devui-scrollbar::-webkit-scrollbar-thumb:hover {
background-color: $devui-placeholder;
}
.devui-scroll-overlay {
overflow: auto;
}
.devui-scroll-overlay::-webkit-scrollbar-thumb {
background-color: transparent;
}
.devui-scroll-overlay:hover::-webkit-scrollbar-thumb {
background-color: $devui-line;
}
.devui-scroll-overlay:hover::-webkit-scrollbar-thumb:hover {
background-color: $devui-placeholder;
}
.devui-text-ellipsis {
overflow: hidden;
white-space: nowrap;
text-overflow: ellipsis;
}
button.copy {
display: none;
}
// 以下13行是防止滚动条显示与隐藏时页面抖动
:root {
overflow-y: auto;
overflow-x: hidden;
}
:root body {
position: absolute;
}
#app {
width: 100vw;
overflow: hidden;
}
|
2301_80257615/MateChat
|
docs/theme-default/styles/global.scss
|
SCSS
|
mit
| 1,527
|
[class^='vpi-'],
[class*=' vpi-'],
.vp-icon {
width: 1em;
height: 1em;
}
[class^='vpi-'].bg,
[class*=' vpi-'].bg,
.vp-icon.bg {
background-size: 100% 100%;
background-color: transparent;
}
[class^='vpi-']:not(.bg),
[class*=' vpi-']:not(.bg),
.vp-icon:not(.bg) {
-webkit-mask: var(--icon) no-repeat;
mask: var(--icon) no-repeat;
-webkit-mask-size: 100% 100%;
mask-size: 100% 100%;
background-color: currentColor;
color: inherit;
}
/* internal icons - used under ISC from https://lucide.dev/ */
.vpi-align-left {
--icon: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' fill='none' stroke='currentColor' stroke-linecap='round' stroke-linejoin='round' stroke-width='2' viewBox='0 0 24 24'%3E%3Cpath d='M21 6H3M15 12H3M17 18H3'/%3E%3C/svg%3E");
}
.vpi-arrow-right,
.vpi-arrow-down,
.vpi-arrow-left,
.vpi-arrow-up {
--icon: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' fill='none' stroke='currentColor' stroke-linecap='round' stroke-linejoin='round' stroke-width='2' viewBox='0 0 24 24'%3E%3Cpath d='M5 12h14M12 5l7 7-7 7'/%3E%3C/svg%3E");
}
.vpi-chevron-right,
.vpi-chevron-down,
.vpi-chevron-left,
.vpi-chevron-up {
--icon: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' fill='none' stroke='currentColor' stroke-linecap='round' stroke-linejoin='round' stroke-width='2' viewBox='0 0 24 24'%3E%3Cpath d='m9 18 6-6-6-6'/%3E%3C/svg%3E");
}
.vpi-chevron-down,
.vpi-arrow-down {
transform: rotate(90deg);
}
.vpi-chevron-left,
.vpi-arrow-left {
transform: rotate(180deg);
}
.vpi-chevron-up,
.vpi-arrow-up {
transform: rotate(-90deg);
}
.vpi-square-pen {
--icon: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' fill='none' stroke='currentColor' stroke-linecap='round' stroke-linejoin='round' stroke-width='2' viewBox='0 0 24 24'%3E%3Cpath d='M12 3H5a2 2 0 0 0-2 2v14a2 2 0 0 0 2 2h14a2 2 0 0 0 2-2v-7'/%3E%3Cpath d='M18.375 2.625a2.121 2.121 0 1 1 3 3L12 15l-4 1 1-4Z'/%3E%3C/svg%3E");
}
.vpi-plus {
--icon: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' fill='none' stroke='currentColor' stroke-linecap='round' stroke-linejoin='round' stroke-width='2' viewBox='0 0 24 24'%3E%3Cpath d='M5 12h14M12 5v14'/%3E%3C/svg%3E");
}
.vpi-sun {
--icon: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' fill='none' stroke='currentColor' stroke-linecap='round' stroke-linejoin='round' stroke-width='2' viewBox='0 0 24 24'%3E%3Ccircle cx='12' cy='12' r='4'/%3E%3Cpath d='M12 2v2M12 20v2M4.93 4.93l1.41 1.41M17.66 17.66l1.41 1.41M2 12h2M20 12h2M6.34 17.66l-1.41 1.41M19.07 4.93l-1.41 1.41'/%3E%3C/svg%3E");
}
.vpi-moon {
--icon: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' fill='none' stroke='currentColor' stroke-linecap='round' stroke-linejoin='round' stroke-width='2' viewBox='0 0 24 24'%3E%3Cpath d='M12 3a6 6 0 0 0 9 9 9 9 0 1 1-9-9Z'/%3E%3C/svg%3E");
}
.vpi-more-horizontal {
--icon: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' fill='none' stroke='currentColor' stroke-linecap='round' stroke-linejoin='round' stroke-width='2' viewBox='0 0 24 24'%3E%3Ccircle cx='12' cy='12' r='1'/%3E%3Ccircle cx='19' cy='12' r='1'/%3E%3Ccircle cx='5' cy='12' r='1'/%3E%3C/svg%3E");
}
.vpi-languages {
--icon: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' fill='none' stroke='currentColor' stroke-linecap='round' stroke-linejoin='round' stroke-width='2' viewBox='0 0 24 24'%3E%3Cpath d='m5 8 6 6M4 14l6-6 2-3M2 5h12M7 2h1M22 22l-5-10-5 10M14 18h6'/%3E%3C/svg%3E");
}
.vpi-heart {
--icon: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' fill='none' stroke='currentColor' stroke-linecap='round' stroke-linejoin='round' stroke-width='2' viewBox='0 0 24 24'%3E%3Cpath d='M19 14c1.49-1.46 3-3.21 3-5.5A5.5 5.5 0 0 0 16.5 3c-1.76 0-3 .5-4.5 2-1.5-1.5-2.74-2-4.5-2A5.5 5.5 0 0 0 2 8.5c0 2.3 1.5 4.05 3 5.5l7 7Z'/%3E%3C/svg%3E");
}
.vpi-search {
--icon: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' fill='none' stroke='currentColor' stroke-linecap='round' stroke-linejoin='round' stroke-width='2' viewBox='0 0 24 24'%3E%3Ccircle cx='11' cy='11' r='8'/%3E%3Cpath d='m21 21-4.3-4.3'/%3E%3C/svg%3E");
}
.vpi-layout-list {
--icon: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' fill='none' stroke='currentColor' stroke-linecap='round' stroke-linejoin='round' stroke-width='2' viewBox='0 0 24 24'%3E%3Crect width='7' height='7' x='3' y='3' rx='1'/%3E%3Crect width='7' height='7' x='3' y='14' rx='1'/%3E%3Cpath d='M14 4h7M14 9h7M14 15h7M14 20h7'/%3E%3C/svg%3E");
}
.vpi-delete {
--icon: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' fill='none' stroke='currentColor' stroke-linecap='round' stroke-linejoin='round' stroke-width='2' viewBox='0 0 24 24'%3E%3Cpath d='M20 5H9l-7 7 7 7h11a2 2 0 0 0 2-2V7a2 2 0 0 0-2-2ZM18 9l-6 6M12 9l6 6'/%3E%3C/svg%3E");
}
.vpi-corner-down-left {
--icon: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' fill='none' stroke='currentColor' stroke-linecap='round' stroke-linejoin='round' stroke-width='2' viewBox='0 0 24 24'%3E%3Cpath d='m9 10-5 5 5 5'/%3E%3Cpath d='M20 4v7a4 4 0 0 1-4 4H4'/%3E%3C/svg%3E");
}
:root {
/* clipboard */
--vp-icon-copy: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' fill='none' stroke='rgba(128,128,128,1)' stroke-linecap='round' stroke-linejoin='round' stroke-width='2' viewBox='0 0 24 24'%3E%3Crect width='8' height='4' x='8' y='2' rx='1' ry='1'/%3E%3Cpath d='M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2'/%3E%3C/svg%3E");
/* clipboard-copy */
--vp-icon-copied: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' fill='none' stroke='rgba(128,128,128,1)' stroke-linecap='round' stroke-linejoin='round' stroke-width='2' viewBox='0 0 24 24'%3E%3Crect width='8' height='4' x='8' y='2' rx='1' ry='1'/%3E%3Cpath d='M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2'/%3E%3Cpath d='m9 14 2 2 4-4'/%3E%3C/svg%3E");
}
|
2301_80257615/MateChat
|
docs/theme-default/styles/icons.css
|
CSS
|
mit
| 6,037
|
.visually-hidden {
position: absolute;
width: 1px;
height: 1px;
white-space: nowrap;
clip: rect(0 0 0 0);
clip-path: inset(50%);
overflow: hidden;
}
|
2301_80257615/MateChat
|
docs/theme-default/styles/utils.css
|
CSS
|
mit
| 163
|
/**
* Colors: Solid
* -------------------------------------------------------------------------- */
:root {
--vp-c-white: #ffffff;
--vp-c-black: #000000;
--vp-c-neutral: var(--vp-c-black);
--vp-c-neutral-inverse: var(--vp-c-white);
}
.dark {
--vp-c-neutral: var(--vp-c-white);
--vp-c-neutral-inverse: var(--vp-c-black);
}
/**
* Colors: Palette
*
* The primitive colors used for accent colors. These colors are referenced
* by functional colors such as "Text", "Background", or "Brand".
*
* Each colors have exact same color scale system with 3 levels of solid
* colors with different brightness, and 1 soft color.
*
* - `XXX-1`: The most solid color used mainly for colored text. It must
* satisfy the contrast ratio against when used on top of `XXX-soft`.
*
* - `XXX-2`: The color used mainly for hover state of the button.
*
* - `XXX-3`: The color for solid background, such as bg color of the button.
* It must satisfy the contrast ratio with pure white (#ffffff) text on
* top of it.
*
* - `XXX-soft`: The color used for subtle background such as custom container
* or badges. It must satisfy the contrast ratio when putting `XXX-1` colors
* on top of it.
*
* The soft color must be semi transparent alpha channel. This is crucial
* because it allows adding multiple "soft" colors on top of each other
* to create a accent, such as when having inline code block inside
* custom containers.
* -------------------------------------------------------------------------- */
:root {
--vp-c-gray-1: #dddde3;
--vp-c-gray-2: #e4e4e9;
--vp-c-gray-3: #ebebef;
--vp-c-gray-soft: rgba(142, 150, 170, 0.14);
--vp-c-indigo-1: #3451b2;
--vp-c-indigo-2: #3a5ccc;
--vp-c-indigo-3: #5672cd;
--vp-c-indigo-soft: rgba(100, 108, 255, 0.14);
--vp-c-purple-1: #6f42c1;
--vp-c-purple-2: #7e4cc9;
--vp-c-purple-3: #8e5cd9;
--vp-c-purple-soft: rgba(159, 122, 234, 0.14);
--vp-c-green-1: #18794e;
--vp-c-green-2: #299764;
--vp-c-green-3: #30a46c;
--vp-c-green-soft: rgba(16, 185, 129, 0.14);
--vp-c-yellow-1: #915930;
--vp-c-yellow-2: #946300;
--vp-c-yellow-3: #9f6a00;
--vp-c-yellow-soft: rgba(234, 179, 8, 0.14);
--vp-c-red-1: #b8272c;
--vp-c-red-2: #d5393e;
--vp-c-red-3: #e0575b;
--vp-c-red-soft: rgba(244, 63, 94, 0.14);
--vp-c-sponsor: #db2777;
}
.dark {
--vp-c-gray-1: #515c67;
--vp-c-gray-2: #414853;
--vp-c-gray-3: #32363f;
--vp-c-gray-soft: rgba(101, 117, 133, 0.16);
--vp-c-indigo-1: #a8b1ff;
--vp-c-indigo-2: #5c73e7;
--vp-c-indigo-3: #3e63dd;
--vp-c-indigo-soft: rgba(100, 108, 255, 0.16);
--vp-c-purple-1: #c8abfa;
--vp-c-purple-2: #a879e6;
--vp-c-purple-3: #8e5cd9;
--vp-c-purple-soft: rgba(159, 122, 234, 0.16);
--vp-c-green-1: #3dd68c;
--vp-c-green-2: #30a46c;
--vp-c-green-3: #298459;
--vp-c-green-soft: rgba(16, 185, 129, 0.16);
--vp-c-yellow-1: #f9b44e;
--vp-c-yellow-2: #da8b17;
--vp-c-yellow-3: #a46a0a;
--vp-c-yellow-soft: rgba(234, 179, 8, 0.16);
--vp-c-red-1: #f66f81;
--vp-c-red-2: #f14158;
--vp-c-red-3: #b62a3c;
--vp-c-red-soft: rgba(244, 63, 94, 0.16);
}
/**
* Colors: Background
*
* - `bg`: The bg color used for main screen.
*
* - `bg-alt`: The alternative bg color used in places such as "sidebar",
* or "code block".
*
* - `bg-elv`: The elevated bg color. This is used at parts where it "floats",
* such as "dialog".
*
* - `bg-soft`: The bg color to slightly distinguish some components from
* the page. Used for things like "carbon ads" or "table".
* -------------------------------------------------------------------------- */
:root {
--vp-c-bg: #ffffff;
--vp-c-bg-alt: #f6f6f7;
--vp-c-bg-elv: #ffffff;
--vp-c-bg-soft: #f6f6f7;
}
.dark {
--vp-c-bg: #1b1b1f;
--vp-c-bg-alt: #161618;
--vp-c-bg-elv: #202127;
--vp-c-bg-soft: #202127;
}
/**
* Colors: Borders
*
* - `divider`: This is used for separators. This is used to divide sections
* within the same components, such as having separator on "h2" heading.
*
* - `border`: This is designed for borders on interactive components.
* For example this should be used for a button outline.
*
* - `gutter`: This is used to divide components in the page. For example
* the header and the lest of the page.
* -------------------------------------------------------------------------- */
:root {
--vp-c-border: #c2c2c4;
--vp-c-divider: #e2e2e3;
--vp-c-gutter: #e2e2e3;
}
.dark {
--vp-c-border: #3c3f44;
--vp-c-divider: #2e2e32;
--vp-c-gutter: #000000;
}
/**
* Colors: Text
*
* - `text-1`: Used for primary text.
*
* - `text-2`: Used for muted texts, such as "inactive menu" or "info texts".
*
* - `text-3`: Used for subtle texts, such as "placeholders" or "caret icon".
* -------------------------------------------------------------------------- */
:root {
--vp-c-text-1: rgba(60, 60, 67);
--vp-c-text-2: rgba(60, 60, 67, 0.78);
--vp-c-text-3: rgba(60, 60, 67, 0.56);
}
.dark {
--vp-c-text-1: rgba(255, 255, 245, 0.86);
--vp-c-text-2: rgba(235, 235, 245, 0.6);
--vp-c-text-3: rgba(235, 235, 245, 0.38);
}
/**
* Colors: Function
*
* - `default`: The color used purely for subtle indication without any
* special meanings attached to it such as bg color for menu hover state.
*
* - `brand`: Used for primary brand colors, such as link text, button with
* brand theme, etc.
*
* - `tip`: Used to indicate useful information. The default theme uses the
* brand color for this by default.
*
* - `warning`: Used to indicate warning to the users. Used in custom
* container, badges, etc.
*
* - `danger`: Used to show error, or dangerous message to the users. Used
* in custom container, badges, etc.
*
* To understand the scaling system, refer to "Colors: Palette" section.
* -------------------------------------------------------------------------- */
:root {
--vp-c-default-1: var(--vp-c-gray-1);
--vp-c-default-2: var(--vp-c-gray-2);
--vp-c-default-3: var(--vp-c-gray-3);
--vp-c-default-soft: var(--vp-c-gray-soft);
--vp-c-brand-1: var(--vp-c-indigo-1);
--vp-c-brand-2: var(--vp-c-indigo-2);
--vp-c-brand-3: var(--vp-c-indigo-3);
--vp-c-brand-soft: var(--vp-c-indigo-soft);
/* DEPRECATED: Use `--vp-c-brand-1` instead. */
--vp-c-brand: var(--vp-c-brand-1);
--vp-c-tip-1: var(--vp-c-brand-1);
--vp-c-tip-2: var(--vp-c-brand-2);
--vp-c-tip-3: var(--vp-c-brand-3);
--vp-c-tip-soft: var(--vp-c-brand-soft);
--vp-c-note-1: var(--vp-c-brand-1);
--vp-c-note-2: var(--vp-c-brand-2);
--vp-c-note-3: var(--vp-c-brand-3);
--vp-c-note-soft: var(--vp-c-brand-soft);
--vp-c-success-1: var(--vp-c-green-1);
--vp-c-success-2: var(--vp-c-green-2);
--vp-c-success-3: var(--vp-c-green-3);
--vp-c-success-soft: var(--vp-c-green-soft);
--vp-c-important-1: var(--vp-c-purple-1);
--vp-c-important-2: var(--vp-c-purple-2);
--vp-c-important-3: var(--vp-c-purple-3);
--vp-c-important-soft: var(--vp-c-purple-soft);
--vp-c-warning-1: var(--vp-c-yellow-1);
--vp-c-warning-2: var(--vp-c-yellow-2);
--vp-c-warning-3: var(--vp-c-yellow-3);
--vp-c-warning-soft: var(--vp-c-yellow-soft);
--vp-c-danger-1: var(--vp-c-red-1);
--vp-c-danger-2: var(--vp-c-red-2);
--vp-c-danger-3: var(--vp-c-red-3);
--vp-c-danger-soft: var(--vp-c-red-soft);
--vp-c-caution-1: var(--vp-c-red-1);
--vp-c-caution-2: var(--vp-c-red-2);
--vp-c-caution-3: var(--vp-c-red-3);
--vp-c-caution-soft: var(--vp-c-red-soft);
}
/**
* Typography
* -------------------------------------------------------------------------- */
:root {
--vp-font-family-base: 'Inter', ui-sans-serif, system-ui, sans-serif,
'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol', 'Noto Color Emoji';
--vp-font-family-mono: ui-monospace, 'Menlo', 'Monaco', 'Consolas',
'Liberation Mono', 'Courier New', monospace;
font-optical-sizing: auto;
}
:root:where(:lang(zh)) {
--vp-font-family-base: 'Punctuation SC', 'Inter', ui-sans-serif, system-ui,
sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol',
'Noto Color Emoji';
}
/**
* Shadows
* -------------------------------------------------------------------------- */
:root {
--vp-shadow-1: 0 1px 2px rgba(0, 0, 0, 0.04), 0 1px 2px rgba(0, 0, 0, 0.06);
--vp-shadow-2: 0 3px 12px rgba(0, 0, 0, 0.07), 0 1px 4px rgba(0, 0, 0, 0.07);
--vp-shadow-3: 0 12px 32px rgba(0, 0, 0, 0.1), 0 2px 6px rgba(0, 0, 0, 0.08);
--vp-shadow-4: 0 14px 44px rgba(0, 0, 0, 0.12), 0 3px 9px rgba(0, 0, 0, 0.12);
--vp-shadow-5: 0 18px 56px rgba(0, 0, 0, 0.16), 0 4px 12px rgba(0, 0, 0, 0.16);
}
/**
* Z-indexes
* -------------------------------------------------------------------------- */
:root {
--vp-z-index-footer: 10;
--vp-z-index-local-nav: 20;
--vp-z-index-nav: 30;
--vp-z-index-layout-top: 40;
--vp-z-index-backdrop: 50;
--vp-z-index-sidebar: 60;
}
@media (min-width: 960px) {
:root {
--vp-z-index-sidebar: 25;
}
}
/**
* Layouts
* -------------------------------------------------------------------------- */
:root {
--vp-layout-max-width: 1440px;
}
/**
* Component: Header Anchor
* -------------------------------------------------------------------------- */
:root {
--vp-header-anchor-symbol: '#';
}
/**
* Component: Code
* -------------------------------------------------------------------------- */
:root {
--vp-code-line-height: 1.7;
--vp-code-font-size: 0.875em;
--vp-code-color: var(--vp-c-brand-1);
--vp-code-link-color: var(--vp-c-brand-1);
--vp-code-link-hover-color: var(--vp-c-brand-2);
--vp-code-bg: var(--vp-c-default-soft);
--vp-code-block-color: var(--vp-c-text-2);
--vp-code-block-bg: var(--vp-c-bg-alt);
--vp-code-block-divider-color: var(--vp-c-gutter);
--vp-code-lang-color: var(--vp-c-text-3);
--vp-code-line-highlight-color: var(--vp-c-default-soft);
--vp-code-line-number-color: var(--vp-c-text-3);
--vp-code-line-diff-add-color: var(--vp-c-success-soft);
--vp-code-line-diff-add-symbol-color: var(--vp-c-success-1);
--vp-code-line-diff-remove-color: var(--vp-c-danger-soft);
--vp-code-line-diff-remove-symbol-color: var(--vp-c-danger-1);
--vp-code-line-warning-color: var(--vp-c-warning-soft);
--vp-code-line-error-color: var(--vp-c-danger-soft);
--vp-code-copy-code-border-color: var(--vp-c-divider);
--vp-code-copy-code-bg: var(--vp-c-bg-soft);
--vp-code-copy-code-hover-border-color: var(--vp-c-divider);
--vp-code-copy-code-hover-bg: var(--vp-c-bg);
--vp-code-copy-code-active-text: var(--vp-c-text-2);
--vp-code-copy-copied-text-content: 'Copied';
--vp-code-tab-divider: var(--vp-code-block-divider-color);
--vp-code-tab-text-color: var(--vp-c-text-2);
--vp-code-tab-bg: var(--vp-code-block-bg);
--vp-code-tab-hover-text-color: var(--vp-c-text-1);
--vp-code-tab-active-text-color: var(--vp-c-text-1);
--vp-code-tab-active-bar-color: var(--vp-c-brand-1);
}
/**
* Component: Button
* -------------------------------------------------------------------------- */
:root {
--vp-button-brand-border: transparent;
--vp-button-brand-text: var(--vp-c-white);
--vp-button-brand-bg: var(--vp-c-brand-3);
--vp-button-brand-hover-border: transparent;
--vp-button-brand-hover-text: var(--vp-c-white);
--vp-button-brand-hover-bg: var(--vp-c-brand-2);
--vp-button-brand-active-border: transparent;
--vp-button-brand-active-text: var(--vp-c-white);
--vp-button-brand-active-bg: var(--vp-c-brand-1);
--vp-button-alt-border: transparent;
--vp-button-alt-text: var(--vp-c-text-1);
--vp-button-alt-bg: var(--vp-c-default-3);
--vp-button-alt-hover-border: transparent;
--vp-button-alt-hover-text: var(--vp-c-text-1);
--vp-button-alt-hover-bg: var(--vp-c-default-2);
--vp-button-alt-active-border: transparent;
--vp-button-alt-active-text: var(--vp-c-text-1);
--vp-button-alt-active-bg: var(--vp-c-default-1);
--vp-button-sponsor-border: var(--vp-c-text-2);
--vp-button-sponsor-text: var(--vp-c-text-2);
--vp-button-sponsor-bg: transparent;
--vp-button-sponsor-hover-border: var(--vp-c-sponsor);
--vp-button-sponsor-hover-text: var(--vp-c-sponsor);
--vp-button-sponsor-hover-bg: transparent;
--vp-button-sponsor-active-border: var(--vp-c-sponsor);
--vp-button-sponsor-active-text: var(--vp-c-sponsor);
--vp-button-sponsor-active-bg: transparent;
}
/**
* Component: Custom Block
* -------------------------------------------------------------------------- */
:root {
--vp-custom-block-font-size: 14px;
--vp-custom-block-code-font-size: 13px;
--vp-custom-block-info-border: transparent;
--vp-custom-block-info-text: var(--vp-c-text-1);
--vp-custom-block-info-bg: var(--vp-c-default-soft);
--vp-custom-block-info-code-bg: var(--vp-c-default-soft);
--vp-custom-block-note-border: transparent;
--vp-custom-block-note-text: var(--vp-c-text-1);
--vp-custom-block-note-bg: var(--vp-c-default-soft);
--vp-custom-block-note-code-bg: var(--vp-c-default-soft);
--vp-custom-block-tip-border: transparent;
--vp-custom-block-tip-text: var(--vp-c-text-1);
--vp-custom-block-tip-bg: var(--vp-c-tip-soft);
--vp-custom-block-tip-code-bg: var(--vp-c-tip-soft);
--vp-custom-block-important-border: transparent;
--vp-custom-block-important-text: var(--vp-c-text-1);
--vp-custom-block-important-bg: var(--vp-c-important-soft);
--vp-custom-block-important-code-bg: var(--vp-c-important-soft);
--vp-custom-block-warning-border: transparent;
--vp-custom-block-warning-text: var(--vp-c-text-1);
--vp-custom-block-warning-bg: var(--vp-c-warning-soft);
--vp-custom-block-warning-code-bg: var(--vp-c-warning-soft);
--vp-custom-block-danger-border: transparent;
--vp-custom-block-danger-text: var(--vp-c-text-1);
--vp-custom-block-danger-bg: var(--vp-c-danger-soft);
--vp-custom-block-danger-code-bg: var(--vp-c-danger-soft);
--vp-custom-block-caution-border: transparent;
--vp-custom-block-caution-text: var(--vp-c-text-1);
--vp-custom-block-caution-bg: var(--vp-c-caution-soft);
--vp-custom-block-caution-code-bg: var(--vp-c-caution-soft);
--vp-custom-block-details-border: var(--vp-custom-block-info-border);
--vp-custom-block-details-text: var(--vp-custom-block-info-text);
--vp-custom-block-details-bg: var(--vp-custom-block-info-bg);
--vp-custom-block-details-code-bg: var(--vp-custom-block-info-code-bg);
}
/**
* Component: Input
* -------------------------------------------------------------------------- */
:root {
--vp-input-border-color: var(--vp-c-border);
--vp-input-bg-color: var(--vp-c-bg-alt);
--vp-input-switch-bg-color: var(--vp-c-default-soft);
}
/**
* Component: Nav
* -------------------------------------------------------------------------- */
:root {
--vp-nav-height: 64px;
--vp-nav-bg-color: var(--vp-c-bg);
--vp-nav-screen-bg-color: var(--vp-c-bg);
--vp-nav-logo-height: 24px;
}
.hide-nav {
--vp-nav-height: 0px;
}
.hide-nav .VPSidebar {
--vp-nav-height: 22px;
}
/**
* Component: Local Nav
* -------------------------------------------------------------------------- */
:root {
--vp-local-nav-bg-color: var(--vp-c-bg);
}
/**
* Component: Sidebar
* -------------------------------------------------------------------------- */
:root {
--vp-sidebar-width: 272px;
--vp-sidebar-bg-color: var(--vp-c-bg-alt);
}
/**
* Colors Backdrop
* -------------------------------------------------------------------------- */
:root {
--vp-backdrop-bg-color: rgba(0, 0, 0, 0.6);
}
/**
* Component: Home
* -------------------------------------------------------------------------- */
:root {
--vp-home-hero-name-color: var(--vp-c-brand-1);
--vp-home-hero-name-background: transparent;
--vp-home-hero-image-background-image: none;
--vp-home-hero-image-filter: none;
}
/**
* Component: Badge
* -------------------------------------------------------------------------- */
:root {
--vp-badge-info-border: transparent;
--vp-badge-info-text: var(--vp-c-text-2);
--vp-badge-info-bg: var(--vp-c-default-soft);
--vp-badge-tip-border: transparent;
--vp-badge-tip-text: var(--vp-c-tip-1);
--vp-badge-tip-bg: var(--vp-c-tip-soft);
--vp-badge-warning-border: transparent;
--vp-badge-warning-text: var(--vp-c-warning-1);
--vp-badge-warning-bg: var(--vp-c-warning-soft);
--vp-badge-danger-border: transparent;
--vp-badge-danger-text: var(--vp-c-danger-1);
--vp-badge-danger-bg: var(--vp-c-danger-soft);
}
/**
* Component: Carbon Ads
* -------------------------------------------------------------------------- */
:root {
--vp-carbon-ads-text-color: var(--vp-c-text-1);
--vp-carbon-ads-poweredby-color: var(--vp-c-text-2);
--vp-carbon-ads-bg-color: var(--vp-c-bg-soft);
--vp-carbon-ads-hover-text-color: var(--vp-c-brand-1);
--vp-carbon-ads-hover-poweredby-color: var(--vp-c-text-1);
}
/**
* Component: Local Search
* -------------------------------------------------------------------------- */
:root {
--vp-local-search-bg: var(--vp-c-bg);
--vp-local-search-result-bg: var(--vp-c-bg);
--vp-local-search-result-border: var(--vp-c-divider);
--vp-local-search-result-selected-bg: var(--vp-c-bg);
--vp-local-search-result-selected-border: var(--vp-c-brand-1);
--vp-local-search-highlight-bg: var(--vp-c-brand-1);
--vp-local-search-highlight-text: var(--vp-c-neutral-inverse);
}
|
2301_80257615/MateChat
|
docs/theme-default/styles/vars.css
|
CSS
|
mit
| 17,362
|
// adapted from https://stackoverflow.com/a/46432113/11613622
export class LRUCache {
max;
cache;
constructor(max = 10) {
this.max = max;
this.cache = new Map();
}
get(key) {
let item = this.cache.get(key);
if (item !== undefined) {
// refresh key
this.cache.delete(key);
this.cache.set(key, item);
}
return item;
}
set(key, val) {
// refresh key
if (this.cache.has(key))
this.cache.delete(key);
// evict oldest
else if (this.cache.size === this.max)
this.cache.delete(this.first());
this.cache.set(key, val);
}
first() {
return this.cache.keys().next().value;
}
clear() {
this.cache.clear();
}
}
|
2301_80257615/MateChat
|
docs/theme-default/support/lru.js
|
JavaScript
|
mit
| 809
|
import { ensureStartingSlash } from './utils';
import { isActive } from '../../shared';
/**
* Get the `Sidebar` from sidebar option. This method will ensure to get correct
* sidebar config from `MultiSideBarConfig` with various path combinations such
* as matching `guide/` and `/guide/`. If no matching config was found, it will
* return empty array.
*/
export function getSidebar(_sidebar, path) {
if (Array.isArray(_sidebar))
return addBase(_sidebar);
if (_sidebar == null)
return [];
path = ensureStartingSlash(path);
const dir = Object.keys(_sidebar)
.sort((a, b) => {
return b.split('/').length - a.split('/').length;
})
.find((dir) => {
// make sure the multi sidebar key starts with slash too
return path.startsWith(ensureStartingSlash(dir));
});
const sidebar = dir ? _sidebar[dir] : [];
return Array.isArray(sidebar)
? addBase(sidebar)
: addBase(sidebar.items, sidebar.base);
}
/**
* Get or generate sidebar group from the given sidebar items.
*/
export function getSidebarGroups(sidebar) {
const groups = [];
let lastGroupIndex = 0;
for (const index in sidebar) {
const item = sidebar[index];
if (item.items) {
lastGroupIndex = groups.push(item);
continue;
}
if (!groups[lastGroupIndex]) {
groups.push({ items: [] });
}
groups[lastGroupIndex].items.push(item);
lastGroupIndex++;
}
return groups;
}
export function getFlatSideBarLinks(sidebar) {
const links = [];
function recursivelyExtractLinks(items) {
for (const item of items) {
if (item.text && item.link) {
links.push({
text: item.text,
link: item.link,
docFooterText: item.docFooterText
});
}
if (item.items) {
recursivelyExtractLinks(item.items);
}
}
}
recursivelyExtractLinks(sidebar);
return links;
}
/**
* Check if the given sidebar item contains any active link.
*/
export function hasActiveLink(path, items) {
if (Array.isArray(items)) {
return items.some((item) => hasActiveLink(path, item));
}
return isActive(path, items.link)
? true
: items.items
? hasActiveLink(path, items.items)
: false;
}
function addBase(items, _base) {
return [...items].map((_item) => {
const item = { ..._item };
const base = item.base || _base;
if (base && item.link)
item.link = base + item.link;
if (item.items)
item.items = addBase(item.items, base);
return item;
});
}
|
2301_80257615/MateChat
|
docs/theme-default/support/sidebar.js
|
JavaScript
|
mit
| 2,776
|
import { useData } from '../composables/data';
/**
* @param themeObject Can be an object with `translations` and `locales` properties
*/
export function createSearchTranslate(defaultTranslations) {
const { localeIndex, theme } = useData();
function translate(key) {
const keyPath = key.split('.');
const themeObject = theme.value.search?.options;
const isObject = themeObject && typeof themeObject === 'object';
const locales = (isObject && themeObject.locales?.[localeIndex.value]?.translations) ||
null;
const translations = (isObject && themeObject.translations) || null;
let localeResult = locales;
let translationResult = translations;
let defaultResult = defaultTranslations;
const lastKey = keyPath.pop();
for (const k of keyPath) {
let fallbackResult = null;
const foundInFallback = defaultResult?.[k];
if (foundInFallback) {
fallbackResult = defaultResult = foundInFallback;
}
const foundInTranslation = translationResult?.[k];
if (foundInTranslation) {
fallbackResult = translationResult = foundInTranslation;
}
const foundInLocale = localeResult?.[k];
if (foundInLocale) {
fallbackResult = localeResult = foundInLocale;
}
// Put fallback into unresolved results
if (!foundInFallback) {
defaultResult = fallbackResult;
}
if (!foundInTranslation) {
translationResult = fallbackResult;
}
if (!foundInLocale) {
localeResult = fallbackResult;
}
}
return (localeResult?.[lastKey] ??
translationResult?.[lastKey] ??
defaultResult?.[lastKey] ??
'');
}
return translate;
}
|
2301_80257615/MateChat
|
docs/theme-default/support/translation.js
|
JavaScript
|
mit
| 1,937
|
import { withBase } from 'vitepress';
import { useData } from '../composables/data';
import { isExternal, treatAsHtml } from '../../shared';
import { LocaleKey } from '../components/datas/type';
export function throttleAndDebounce(fn, delay) {
let timeoutId;
let called = false;
return () => {
if (timeoutId) clearTimeout(timeoutId);
if (!called) {
fn();
(called = true) && setTimeout(() => (called = false), delay);
} else timeoutId = setTimeout(fn, delay);
};
}
export function ensureStartingSlash(path) {
return /^\//.test(path) ? path : `/${path}`;
}
export function normalizeLink(url) {
const { pathname, search, hash, protocol } = new URL(url, 'http://a.com');
if (isExternal(url) || url.startsWith('#') || !protocol.startsWith('http') || !treatAsHtml(pathname)) return url;
const { site } = useData();
const normalizedPath =
pathname.endsWith('/') || pathname.endsWith('.html')
? url
: url.replace(/(?:(^\.+)\/)?.*$/, `$1${pathname.replace(/(\.md)?$/, site.value.cleanUrls ? '' : '.html')}${search}${hash}`);
return withBase(normalizedPath);
}
export function getLocaleUrlPrefix(origin) {
let url = origin;
if (typeof localStorage !== 'undefined' && localStorage.getItem('locale') === LocaleKey.en) {
url = '/en' + origin;
}
return url;
}
|
2301_80257615/MateChat
|
docs/theme-default/support/utils.js
|
JavaScript
|
mit
| 1,320
|
import './styles/vars.css';
import './styles/base.css';
import './styles/icons.css';
import './styles/utils.css';
import './styles/components/custom-block.css';
import './styles/components/vp-code.css';
import './styles/components/vp-code-group.css';
import './styles/components/vp-doc.css';
export { useSidebar } from './composables/sidebar';
export { useLocalNav } from './composables/local-nav';
|
2301_80257615/MateChat
|
docs/theme-default/without-fonts.js
|
JavaScript
|
mit
| 400
|
import { defineConfig } from 'vite';
import path from 'node:path';
export default defineConfig({
resolve: {
alias: {
'@matechat/core': path.resolve(__dirname, '../packages/components'),
},
},
});
|
2301_80257615/MateChat
|
docs/vite.config.ts
|
TypeScript
|
mit
| 215
|
<!DOCTYPE html>
<html lang="">
<head>
<meta charset="UTF-8">
<link rel="icon" href="/favicon.ico">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>MetaChat Playground</title>
</head>
<body>
<div id="app"></div>
<script type="module" src="/src/main.ts"></script>
</body>
</html>
|
2301_80257615/MateChat
|
playground/index.html
|
HTML
|
mit
| 340
|
<template>
<McLayout class="container">
<McHeader :title="'MateChat'" :logoImg="'https://matechat.gitcode.com/logo.svg'">
<template #operationArea>
<div class="operations">
<i class="icon-helping"></i>
</div>
</template>
</McHeader>
<McLayoutContent v-if="startPage"
style="display: flex; flex-direction: column; align-items: center; justify-content: center; gap: 12px">
<McIntroduction :logoImg="'https://matechat.gitcode.com/logo2x.svg'" :title="'MateChat'"
:subTitle="'Hi，欢迎使用 MateChat'" :description="description"></McIntroduction>
<McPrompt :list="introPrompt.list" :direction="introPrompt.direction" class="intro-prompt"
@itemClick="onSubmit($event.label)"></McPrompt>
</McLayoutContent>
<McLayoutContent v-else>
<template v-for="(msg, idx) in messages" :key="idx">
<McBubble v-if="msg.from === 'user'" :content="msg.content" :align="'right'"
:avatarConfig="{ imgSrc: 'https://matechat.gitcode.com/png/demo/userAvatar.svg' }">
</McBubble>
<McBubble v-else :content="msg.content" :avatarConfig="{ imgSrc: 'https://matechat.gitcode.com/logo.svg' }">
</McBubble>
</template>
</McLayoutContent>
<div class="shortcut" style="display: flex; align-items: center; gap: 8px">
<McPrompt v-if="!startPage" :list="simplePrompt" :direction="'horizontal'" style="flex: 1"
@itemClick="onSubmit($event.label)"></McPrompt>
<d-button style="margin-left: auto" icon="add" shape="circle" title="新建对话" size="sm" @click="
startPage = true;
messages = [];
" />
</div>
<McLayoutSender>
<McInput :value="inputValue" :maxLength="2000" @change="(e) => (inputValue = e)" @submit="onSubmit">
<template #extra>
<div class="input-foot-wrapper">
<div class="input-foot-left">
<span v-for="(item, index) in inputFootIcons" :key="index">
<i :class="item.icon"></i>
{{ item.text }}
</span>
<span class="input-foot-dividing-line"></span>
<span class="input-foot-maxlength">{{ inputValue.length }}/2000</span>
</div>
<div class="input-foot-right">
<d-button icon="op-clearup" shape="round" :disabled="!inputValue" @click="inputValue = ''">清空输入</d-button>
</div>
</div>
</template>
</McInput>
</McLayoutSender>
</McLayout>
</template>
<script setup lang="ts">
import { ref } from 'vue';
const description = [
'MateChat 可以辅助研发人员编码、查询知识和相关作业信息、编写文档等。',
'作为AI模型，MateChat 提供的答案可能不总是确定或准确的，但您的反馈可以帮助 MateChat 做的更好。',
];
const introPrompt = {
direction: 'horizontal',
list: [
{
value: 'quickSort',
label: '帮我写一个快速排序',
iconConfig: { name: 'icon-info-o', color: '#5e7ce0' },
desc: '使用 js 实现一个快速排序',
},
{
value: 'helpMd',
label: '你可以帮我做些什么？',
iconConfig: { name: 'icon-star', color: 'rgb(255, 215, 0)' },
desc: '了解当前大模型可以帮你做的事',
},
{
value: 'bindProjectSpace',
label: '怎么绑定项目空间',
iconConfig: { name: 'icon-priority', color: '#3ac295' },
desc: '如何绑定云空间中的项目',
},
],
};
const simplePrompt = [
{
value: 'quickSort',
iconConfig: { name: 'icon-info-o', color: '#5e7ce0' },
label: '帮我写一个快速排序',
},
{
value: 'helpMd',
iconConfig: { name: 'icon-star', color: 'rgb(255, 215, 0)' },
label: '你可以帮我做些什么？',
},
];
const startPage = ref(true);
const inputValue = ref('');
const inputFootIcons = [
{ icon: 'icon-at', text: '智能体' },
{ icon: 'icon-standard', text: '词库' },
{ icon: 'icon-add', text: '附件' },
];
const messages = ref([
{
from: 'user',
content: '你好',
},
{
from: 'model',
content: '你好，我是 MateChat',
id: 'init-msg',
},
]);
const onSubmit = (evt) => {
startPage.value = false;
// 用户发送消息
messages.value.push({
from: 'user',
content: evt,
});
setTimeout(() => {
// 模型返回消息
messages.value.push({
from: 'model',
content: evt,
});
}, 200);
};
</script>
<style>
.container {
width: 1000px;
margin: 0 auto;
height: 100vh;
padding: 20px;
gap: 8px;
background: #fff;
}
.input-foot-wrapper {
display: flex;
justify-content: space-between;
align-items: center;
width: 100%;
height: 100%;
margin-right: 8px;
.input-foot-left {
display: flex;
align-items: center;
gap: 8px;
span {
font-size: var(--devui-font-size-sm);
color: var(--devui-text);
cursor: pointer;
}
.input-foot-dividing-line {
width: 1px;
height: 14px;
background-color: var(--devui-line);
}
.input-foot-maxlength {
font-size: var(--devui-font-size-sm);
color: var(--devui-aide-text);
}
}
.input-foot-right {
&>*:not(:first-child) {
margin-left: 8px;
}
}
}
</style>
|
2301_80257615/MateChat
|
playground/src/App.vue
|
Vue
|
mit
| 5,301
|
<template>
<div ref="markdownCardRef" class="mc-markdown-render" v-html="markedHtml"></div>
</template>
<script setup lang="ts">
import markdownit from 'markdown-it';
import hljs from 'highlight.js';
import { computed } from 'vue';
const props = defineProps({
content: {
type: String,
default: '',
},
});
const mdt = markdownit({
breaks: true,
linkify: true,
html: true,
highlight: (str, lang) => {
if (lang && hljs.getLanguage(lang)) {
try {
return hljs.highlight(str, { language: lang }).value;
} catch (_) {}
}
return ''; // use external default escaping
},
});
const markedHtml = computed(() => {
return mdt.render(props.content);
});
</script>
<style lang="scss" scoped>
.mc-markdown-render {
overflow-x: auto;
:deep(p) {
margin: 0 !important;
}
}
</style>
|
2301_80257615/MateChat
|
playground/src/RenderMarkdown.vue
|
Vue
|
mit
| 835
|
/* color palette from <https://github.com/vuejs/theme> */
:root {
--vt-c-white: #ffffff;
--vt-c-white-soft: #f8f8f8;
--vt-c-white-mute: #f2f2f2;
--vt-c-black: #181818;
--vt-c-black-soft: #222222;
--vt-c-black-mute: #282828;
--vt-c-indigo: #2c3e50;
--vt-c-divider-light-1: rgba(60, 60, 60, 0.29);
--vt-c-divider-light-2: rgba(60, 60, 60, 0.12);
--vt-c-divider-dark-1: rgba(84, 84, 84, 0.65);
--vt-c-divider-dark-2: rgba(84, 84, 84, 0.48);
--vt-c-text-light-1: var(--vt-c-indigo);
--vt-c-text-light-2: rgba(60, 60, 60, 0.66);
--vt-c-text-dark-1: var(--vt-c-white);
--vt-c-text-dark-2: rgba(235, 235, 235, 0.64);
}
/* semantic color variables for this project */
:root {
--color-background: var(--vt-c-white);
--color-background-soft: var(--vt-c-white-soft);
--color-background-mute: var(--vt-c-white-mute);
--color-border: var(--vt-c-divider-light-2);
--color-border-hover: var(--vt-c-divider-light-1);
--color-heading: var(--vt-c-text-light-1);
--color-text: var(--vt-c-text-light-1);
--section-gap: 160px;
}
@media (prefers-color-scheme: dark) {
:root {
--color-background: var(--vt-c-black);
--color-background-soft: var(--vt-c-black-soft);
--color-background-mute: var(--vt-c-black-mute);
--color-border: var(--vt-c-divider-dark-2);
--color-border-hover: var(--vt-c-divider-dark-1);
--color-heading: var(--vt-c-text-dark-1);
--color-text: var(--vt-c-text-dark-2);
}
}
*,
*::before,
*::after {
box-sizing: border-box;
margin: 0;
font-weight: normal;
}
body {
min-height: 100vh;
color: var(--color-text);
background: var(--color-background);
transition:
color 0.5s,
background-color 0.5s;
line-height: 1.6;
font-family:
Inter,
-apple-system,
BlinkMacSystemFont,
'Segoe UI',
Roboto,
Oxygen,
Ubuntu,
Cantarell,
'Fira Sans',
'Droid Sans',
'Helvetica Neue',
sans-serif;
font-size: 15px;
text-rendering: optimizeLegibility;
-webkit-font-smoothing: antialiased;
-moz-osx-font-smoothing: grayscale;
}
|
2301_80257615/MateChat
|
playground/src/assets/base.css
|
CSS
|
mit
| 2,067
|
@import './base.css';
#app {
max-width: 1280px;
margin: 0 auto;
padding: 2rem;
font-weight: normal;
}
a,
.green {
text-decoration: none;
color: hsla(160, 100%, 37%, 1);
transition: 0.4s;
padding: 3px;
}
@media (hover: hover) {
a:hover {
background-color: hsla(160, 100%, 37%, 0.2);
}
}
@media (min-width: 1024px) {
body {
display: flex;
place-items: center;
}
#app {
display: grid;
grid-template-columns: 1fr 1fr;
padding: 0 2rem;
}
}
|
2301_80257615/MateChat
|
playground/src/assets/main.css
|
CSS
|
mit
| 492
|
<template>
<svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" fill="currentColor">
<path
d="M15 4a1 1 0 1 0 0 2V4zm0 11v-1a1 1 0 0 0-1 1h1zm0 4l-.707.707A1 1 0 0 0 16 19h-1zm-4-4l.707-.707A1 1 0 0 0 11 14v1zm-4.707-1.293a1 1 0 0 0-1.414 1.414l1.414-1.414zm-.707.707l-.707-.707.707.707zM9 11v-1a1 1 0 0 0-.707.293L9 11zm-4 0h1a1 1 0 0 0-1-1v1zm0 4H4a1 1 0 0 0 1.707.707L5 15zm10-9h2V4h-2v2zm2 0a1 1 0 0 1 1 1h2a3 3 0 0 0-3-3v2zm1 1v6h2V7h-2zm0 6a1 1 0 0 1-1 1v2a3 3 0 0 0 3-3h-2zm-1 1h-2v2h2v-2zm-3 1v4h2v-4h-2zm1.707 3.293l-4-4-1.414 1.414 4 4 1.414-1.414zM11 14H7v2h4v-2zm-4 0c-.276 0-.525-.111-.707-.293l-1.414 1.414C5.42 15.663 6.172 16 7 16v-2zm-.707 1.121l3.414-3.414-1.414-1.414-3.414 3.414 1.414 1.414zM9 12h4v-2H9v2zm4 0a3 3 0 0 0 3-3h-2a1 1 0 0 1-1 1v2zm3-3V3h-2v6h2zm0-6a3 3 0 0 0-3-3v2a1 1 0 0 1 1 1h2zm-3-3H3v2h10V0zM3 0a3 3 0 0 0-3 3h2a1 1 0 0 1 1-1V0zM0 3v6h2V3H0zm0 6a3 3 0 0 0 3 3v-2a1 1 0 0 1-1-1H0zm3 3h2v-2H3v2zm1-1v4h2v-4H4zm1.707 4.707l.586-.586-1.414-1.414-.586.586 1.414 1.414z"
/>
</svg>
</template>
|
2301_80257615/MateChat
|
playground/src/components/icons/IconCommunity.vue
|
Vue
|
mit
| 1,054
|
<template>
<svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" fill="currentColor">
<path
d="M10 3.22l-.61-.6a5.5 5.5 0 0 0-7.666.105 5.5 5.5 0 0 0-.114 7.665L10 18.78l8.39-8.4a5.5 5.5 0 0 0-.114-7.665 5.5 5.5 0 0 0-7.666-.105l-.61.61z"
/>
</svg>
</template>
|
2301_80257615/MateChat
|
playground/src/components/icons/IconSupport.vue
|
Vue
|
mit
| 288
|
<!-- This icon is from <https://github.com/Templarian/MaterialDesign>, distributed under Apache 2.0 (https://www.apache.org/licenses/LICENSE-2.0) license-->
<template>
<svg
xmlns="http://www.w3.org/2000/svg"
xmlns:xlink="http://www.w3.org/1999/xlink"
aria-hidden="true"
role="img"
class="iconify iconify--mdi"
width="24"
height="24"
preserveAspectRatio="xMidYMid meet"
viewBox="0 0 24 24"
>
<path
d="M20 18v-4h-3v1h-2v-1H9v1H7v-1H4v4h16M6.33 8l-1.74 4H7v-1h2v1h6v-1h2v1h2.41l-1.74-4H6.33M9 5v1h6V5H9m12.84 7.61c.1.22.16.48.16.8V18c0 .53-.21 1-.6 1.41c-.4.4-.85.59-1.4.59H4c-.55 0-1-.19-1.4-.59C2.21 19 2 18.53 2 18v-4.59c0-.32.06-.58.16-.8L4.5 7.22C4.84 6.41 5.45 6 6.33 6H7V5c0-.55.18-1 .57-1.41C7.96 3.2 8.44 3 9 3h6c.56 0 1.04.2 1.43.59c.39.41.57.86.57 1.41v1h.67c.88 0 1.49.41 1.83 1.22l2.34 5.39z"
fill="currentColor"
></path>
</svg>
</template>
|
2301_80257615/MateChat
|
playground/src/components/icons/IconTooling.vue
|
Vue
|
mit
| 913
|
import './assets/base.css';
import 'vue-devui/style.css';
import '@devui-design/icons/icomoon/devui-icon.css';
import { createApp } from 'vue';
import DevUI from 'vue-devui';
import 'vue-devui/style.css';
import '@devui-design/icons/icomoon/devui-icon.css';
import App from './App.vue';
import MateChat from '@matechat/core';
const app = createApp(App)
app.use(DevUI)
app.use(MateChat)
app.mount('#app');
import { ThemeServiceInit, infinityTheme } from 'devui-theme';
// 使用无限主题
ThemeServiceInit({ infinityTheme }, 'infinityTheme');
|
2301_80257615/MateChat
|
playground/src/main.ts
|
TypeScript
|
mit
| 548
|
<template>
<div class="container">
<McInput
ref="inputRef"
v-mention="isVisible"
:trigger="[{ key: '/', onlyInputStart: true }, '@']"
:onSearchChange="onSearchChange"
:value="inputValue"
:maxLength="2000"
@change="onInputChange"
>
<template #mention>
<McList :data="options" :inputEl="inputRef" enableShortKey @select="onListSelect"></McList>
</template>
</McInput>
</div>
</template>
<script setup lang="ts">
import { ref } from 'vue';
const inputRef = ref();
const inputValue = ref('');
const isVisible = ref(false);
const options = ref(new Array(6).fill(0).map((item, i) => ({ label: `Option ${i + 1}`, value: i + 1 })));
let triggerIndex: number;
let cursorIndex: number;
let currentTrigger: string;
const onSearchChange = (e) => {
triggerIndex = e.triggerIndex;
cursorIndex = e.cursorIndex;
currentTrigger = e.trigger;
};
const onListSelect = (e) => {
inputValue.value = inputValue.value.slice(0, triggerIndex) + currentTrigger + e.label + inputValue.value.slice(cursorIndex);
};
const onInputChange = (e) => {
inputValue.value = e;
};
</script>
<style scoped lang="scss">
.container {
display: flex;
flex-direction: column;
justify-content: flex-end;
padding: 20px;
width: 500px;
height: 600px;
}
</style>
|
2301_80257615/MateChat
|
playground/src/mention-demo.vue
|
Vue
|
mit
| 1,316
|
import quickSortMd from './quicksort.md?raw';
import helpMd from './help.md?raw';
export const introPrompt = {
direction: 'horizontal',
list: [
{
value: 'quickSort',
label: '帮我写一个快速排序',
icon: 'icon-info-o',
color: 'rgb(255, 215, 0)',
desc: '使用 js 快速实现一个可用的快速排序',
},
{
value: 'helpMd',
label: '你可以帮我做些什么？',
icon: 'icon-star',
color: 'rgb(255, 215, 0)',
desc: '了解当前大模型可以帮你做的事',
},
{
value: 'helpMd',
label: '你可以帮我做些什么？',
icon: 'icon-star',
color: 'rgb(255, 215, 0)',
desc: '了解当前大模型可以帮你做的事',
},
],
};
export const guessQuestions = [
{ label: '怎么绑定项目空间' },
{ label: '最近执行流水线列表' },
{ label: '帮我写一个快速排序' },
{ label: '使用 js 格式化时间' },
];
export const simplePrompt = [
{
value: 'quickSort',
icon: 'icon-info-o',
color: 'rgb(255, 215, 0)',
label: '帮我写一个快速排序',
},
{
value: 'helpMd',
icon: 'icon-star',
color: 'rgb(255, 215, 0)',
label: '你可以帮我做些什么？',
},
];
export const mockAnswer = {
quickSort: quickSortMd,
helpMd: helpMd,
};
|
2301_80257615/MateChat
|
playground/src/mock.constants.ts
|
TypeScript
|
mit
| 1,340
|
<template>
<Prompt
class="p10"
:title="prompts.title"
:color="prompts.color"
:icon="prompts.icon"
:list="prompts.list"
:direction="'horizontal'"
@itemClick="onItemClick($event)"
></Prompt>
<Prompt
class="p10"
:title="prompts.title"
:color="prompts.color"
:icon="prompts.icon"
:list="prompts.list"
:direction="'vertical'"
@itemClick="onItemClick($event)"
></Prompt>
<Prompt
class="p10"
:title="promptsSub.title"
:color="promptsSub.color"
:icon="promptsSub.icon"
:list="promptsSub.list"
:direction="'horizontal'"
@itemClick="onItemClick($event)"
></Prompt>
<Prompt class="p10" :list="listText" :direction="'horizontal'" @itemClick="onItemClick($event)"></Prompt>
<Prompt class="p10" :list="listIcon" :direction="'horizontal'" @itemClick="onItemClick($event)"></Prompt>
<Prompt class="p10" :list="listDesc" :direction="'horizontal'" @itemClick="onItemClick($event)"></Prompt>
</template>
<script setup lang="ts">
import Prompt from '@matechat/core/Prompt/Prompt.vue';
const prompts = {
title: 'Inspirational Sparks and Marvelous Tips',
icon: 'like',
color: 'rgb(24, 144, 255)',
direction: 'horizontal',
list: [
{
value: '1',
label: 'Ignite Your Creativity',
icon: 'icon-info-o',
color: 'rgb(255, 215, 0)',
desc: 'Got any sparks for a new project?',
},
{
value: '2',
label: 'Uncover Background Info',
icon: 'icon-star',
color: 'rgb(255, 215, 0)',
desc: 'Help me understand the background of this topic.',
},
],
};
const promptsSub = {
title: 'Inspirational Sparks and Marvelous Tips',
icon: 'like',
color: 'rgb(24, 144, 255)',
direction: 'horizontal',
list: [
{
value: '1',
label: 'Ignite Your Creativity',
icon: 'icon-info-o',
color: 'rgb(255, 215, 0)',
subList: [
{
value: '1',
label: 'Ignite Your Creativity',
icon: 'icon-info-o',
color: 'rgb(255, 215, 0)',
desc: 'Got any sparks for a new project?',
},
{
value: '2',
label: 'Uncover Background Info',
icon: 'icon-star',
color: 'rgb(255, 215, 0)',
desc: 'Help me understand the background of this topic.',
},
],
},
{
value: '2',
label: 'Uncover Background Info',
icon: 'icon-star',
color: 'rgb(255, 215, 0)',
subList: [
{
value: '1',
label: 'Ignite Your Creativity',
icon: 'icon-info-o',
color: 'rgb(255, 215, 0)',
desc: 'Got any sparks for a new project?',
},
{
value: '2',
label: 'Uncover Background Info',
icon: 'icon-star',
color: 'rgb(255, 215, 0)',
desc: 'Help me understand the background of this topic.',
},
],
},
],
};
const listText = [
{
value: '1',
label: 'Ignite Your Creativity',
},
{
value: '2',
label: 'Ignite Your XXX',
},
];
const listIcon = [
{
value: '1',
icon: 'icon-info-o',
color: 'rgb(255, 215, 0)',
},
{
value: '2',
icon: 'icon-star',
color: 'rgb(255, 215, 0)',
},
];
const listDesc = [
{
value: '1',
desc: 'icon-info-o',
},
{
value: '2',
desc: 'icon-star',
},
];
function onItemClick(item) {
console.log(item);
}
</script>
<style scoped lang="scss">
@import 'devui-theme/styles-var/devui-var.scss';
.p10 {
padding: 10px;
}
</style>
|
2301_80257615/MateChat
|
playground/src/testPrompt.vue
|
Vue
|
mit
| 3,554
|
import { defineConfig } from 'vite';
import vue from '@vitejs/plugin-vue';
import vueJsx from '@vitejs/plugin-vue-jsx';
import path from 'node:path';
console.log(path.resolve(__dirname, '../packages/components/dist'))
// https://vite.dev/config/
export default defineConfig({
plugins: [vue(), vueJsx()],
resolve: {
alias: {
'@matechat/core': path.resolve(__dirname, '../packages/components'),
'@': path.resolve(__dirname, 'src'),
},
},
optimizeDeps: { exclude: ['fsevents'] },
});
|
2301_80257615/MateChat
|
playground/vite.config.ts
|
TypeScript
|
mit
| 511
|
import path from 'node:path';
import vue from '@vitejs/plugin-vue';
import vueJsx from '@vitejs/plugin-vue-jsx';
import fs from 'fs-extra';
import { build, defineConfig } from 'vite';
import {
buildLibOutputDir,
buildLibOutputIndexDtsFile,
buildLibOutputIndexFile,
componentIndexFile,
componentsDir,
ignoreDirs,
} from './const.js';
import { resolveFilesInfo } from './utils.js';
async function buildComponents() {
const filesInfo = resolveFilesInfo(componentsDir, ['node_modules', 'dist']);
for (let i = 0; i < filesInfo.length; i++) {
await buildSingle(filesInfo[i]);
}
autoImportCss();
copyIndex();
generateIndexDts();
}
async function buildSingle(itemFile) {
await build(
defineConfig({
configFile: false,
publicDir: false,
plugins: [vue(), vueJsx()],
build: {
rollupOptions: {
external: [
'vue',
'@floating-ui/dom',
'@vue/shared',
'lodash-es',
/@matechat\/core/,
'markdown-it',
'highlight.js',
'xss',
],
},
lib: {
entry: itemFile.indexPath,
name: 'index',
fileName: 'index',
formats: ['es'],
},
outDir: path.resolve(buildLibOutputDir, `./${itemFile.name}`),
},
}),
);
}
// 自动引入index.css
function autoImportCss() {
const ignore = [...ignoreDirs, 'Locale'];
const itemDirs = fs
.readdirSync(buildLibOutputDir)
.filter(
(itemDir) =>
fs.statSync(path.resolve(buildLibOutputDir, itemDir)).isDirectory() &&
!ignore.includes(itemDir),
)
.map((itemDir) => ({
indexPath: path.resolve(buildLibOutputDir, itemDir, 'index.js'),
}));
for (const itemDir of itemDirs) {
const fileContent = fs.readFileSync(itemDir.indexPath);
const outputFileContent = `import "./index.css";\n${fileContent}`;
fs.outputFile(itemDir.indexPath, outputFileContent, 'utf-8');
}
}
// 复制components/index.ts的内容到dist/index.js
function copyIndex() {
const fileContent = fs.readFileSync(componentIndexFile, 'utf-8');
fs.ensureFileSync(buildLibOutputIndexFile);
fs.outputFileSync(buildLibOutputIndexFile, fileContent, 'utf-8');
}
// 生成index.d.ts
function generateIndexDts() {
const fileStr = `import type { App } from 'vue';
declare function install(app: App): void
declare const _default: {
install: typeof install;
};
export default _default;`;
fs.outputFileSync(buildLibOutputIndexDtsFile, fileStr, 'utf8');
}
buildComponents();
|
2301_80257615/MateChat
|
scripts/build-component.js
|
JavaScript
|
mit
| 2,584
|
import path from 'path';
import { fileURLToPath } from 'url';
import { dirname } from 'path';
const __filename = fileURLToPath(import.meta.url);
const __dirname = dirname(__filename);
export const indexFileName = 'index.ts';
export const ignoreDirs = ['PopperTrigger', 'node_modules', 'dist'];
export const componentsDir = path.resolve(__dirname, '../packages/components');
export const componentIndexFile = path.resolve(componentsDir, `./${indexFileName}`);
export const buildLibOutputDir = path.resolve(__dirname, '../packages/components/dist');
export const buildLibOutputIndexFile = path.resolve(buildLibOutputDir, './mate-chat.js');
export const buildLibOutputIndexDtsFile = path.resolve(buildLibOutputDir, './index.d.ts');
|
2301_80257615/MateChat
|
scripts/const.js
|
JavaScript
|
mit
| 731
|
import fs from 'fs-extra';
import { ignoreDirs, componentsDir, componentIndexFile } from './const.js';
import { resolveFilesInfo, parseExport, createIndexTemplate } from './utils.js';
function generateComponent() {
const exportModules = [];
const filesInfo = resolveFilesInfo(componentsDir, ignoreDirs);
filesInfo.forEach((item) => {
exportModules.push(parseExport(item));
});
const template = createIndexTemplate(exportModules);
fs.writeFile(componentIndexFile, template, 'utf-8');
}
generateComponent();
|
2301_80257615/MateChat
|
scripts/generate-component.js
|
JavaScript
|
mit
| 527
|
import path from 'path';
import fs from 'fs-extra';
import { fileURLToPath } from 'url';
import { dirname } from 'path';
const __filename = fileURLToPath(import.meta.url);
const __dirname = dirname(__filename);
const release = () => {
const packageSourceFile = path.resolve(__dirname, '../packages/components/package.json');
const packageTargetFile = path.resolve(__dirname, '../packages/components/dist/package.json');
const readmeSourceFile = path.resolve(__dirname, '../packages/components/README.md');
const readmeTargetFile = path.resolve(__dirname, '../packages/components/dist/README.md');
fs.copySync(packageSourceFile, packageTargetFile);
fs.copySync(readmeSourceFile, readmeTargetFile);
};
release();
|
2301_80257615/MateChat
|
scripts/release.js
|
JavaScript
|
mit
| 727
|
import path from 'path';
import fs from 'fs-extra';
import traverse from '@babel/traverse';
import babelParser from '@babel/parser';
import { indexFileName } from './const.js';
export function resolveFilesInfo(targetDir, ignoreDirs = []) {
return fs
.readdirSync(targetDir)
.filter((itemDir) => fs.statSync(path.resolve(targetDir, itemDir)).isDirectory() && !ignoreDirs.includes(itemDir))
.map((itemDir) => ({ name: itemDir, indexPath: path.resolve(targetDir, itemDir, indexFileName) }));
}
export function parseExport(fileInfo) {
const fileContent = fs.readFileSync(fileInfo.indexPath, 'utf-8');
const ast = babelParser.parse(fileContent, {
sourceType: 'module',
plugins: ['typescript'],
});
const exportNames = [];
const installer = 'Mc' + fileInfo.name;
traverse.default(ast, {
ExportNamedDeclaration({ node }) {
if (node.specifiers.length) {
node.specifiers.forEach((specifier) => {
exportNames.push(specifier.local.name);
});
} else if (node.declaration) {
if (node.declaration.declarations) {
node.declaration.declarations.forEach((dec) => {
exportNames.push(dec.id.name);
});
} else if (node.declaration.id) {
exportNames.push(node.declaration.id.name);
}
}
},
});
return { installer, exportNames, dirName: fileInfo.name };
}
export function createIndexTemplate(exportModules) {
const exportComponents = [];
const imports = [];
const installs = [];
exportModules.forEach((item) => {
const { installer, exportNames, dirName } = item;
const importStr = `import { ${exportNames.join(', ')} } from './${dirName}';`;
imports.push(importStr);
installs.push(installer);
exportComponents.push(...exportNames);
});
const template = `\
${imports.join('\n')}
const installs = [
${installs.join(',\n ')}
];
export {
${exportComponents.join(',\n ')}
};
export default {
install(app) {
installs.forEach((p) => app.use(p));
}
};
`;
return template;
}
|
2301_80257615/MateChat
|
scripts/utils.js
|
JavaScript
|
mit
| 2,059
|
<script>
export default {
onLaunch: function() {
console.log('App Launch')
},
onShow: function() {
console.log('App Show')
},
onHide: function() {
console.log('App Hide')
}
}
</script>
<style>
/*每个页面公共css */
</style>
|
2301_80750063/Test1
|
App.vue
|
Vue
|
unknown
| 254
|
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<script>
var coverSupport = 'CSS' in window && typeof CSS.supports === 'function' && (CSS.supports('top: env(a)') ||
CSS.supports('top: constant(a)'))
document.write(
'<meta name="viewport" content="width=device-width, user-scalable=no, initial-scale=1.0, maximum-scale=1.0, minimum-scale=1.0' +
(coverSupport ? ', viewport-fit=cover' : '') + '" />')
</script>
<title></title>
<!--preload-links-->
<!--app-context-->
</head>
<body>
<div id="app"><!--app-html--></div>
<script type="module" src="/main.js"></script>
</body>
</html>
|
2301_80750063/Test1
|
index.html
|
HTML
|
unknown
| 672
|
import App from './App'
// #ifndef VUE3
import Vue from 'vue'
import './uni.promisify.adaptor'
Vue.config.productionTip = false
App.mpType = 'app'
const app = new Vue({
...App
})
app.$mount()
// #endif
// #ifdef VUE3
import { createSSRApp } from 'vue'
export function createApp() {
const app = createSSRApp(App)
return {
app
}
}
// #endif
|
2301_80750063/Test1
|
main.js
|
JavaScript
|
unknown
| 352
|
<template>
<view class="content">
<image class="logo" src="/static/logo.png"></image>
<view class="text-area">
<text class="title">{{title}}</text>
</view>
</view>
</template>
<script>
export default {
data() {
return {
title: 'Hellounify'
}
},
onLoad() {
},
methods: {
}
}
</script>
<style>
.content {
display: flex;
flex-direction: column;
align-items: center;
justify-content: center;
}
.logo {
height: 200rpx;
width: 200rpx;
margin-top: 200rpx;
margin-left: auto;
margin-right: auto;
margin-bottom: 50rpx;
}
.text-area {
display: flex;
justify-content: center;
}
.title {
font-size: 36rpx;
color: #8f8f94;
}
</style>
|
2301_80750063/Test1
|
pages/index/index.vue
|
Vue
|
unknown
| 699
|
uni.addInterceptor({
returnValue (res) {
if (!(!!res && (typeof res === "object" || typeof res === "function") && typeof res.then === "function")) {
return res;
}
return new Promise((resolve, reject) => {
res.then((res) => {
if (!res) return resolve(res)
return res[0] ? reject(res[0]) : resolve(res[1])
});
});
},
});
|
2301_80750063/Test1
|
uni.promisify.adaptor.js
|
JavaScript
|
unknown
| 373
|
/**
* 这里是uni-app内置的常用样式变量
*
* uni-app 官方扩展插件及插件市场（https://ext.dcloud.net.cn）上很多三方插件均使用了这些样式变量
* 如果你是插件开发者，建议你使用scss预处理，并在插件代码中直接使用这些变量（无需 import 这个文件），方便用户通过搭积木的方式开发整体风格一致的App
*
*/
/**
* 如果你是App开发者（插件使用者），你可以通过修改这些变量来定制自己的插件主题，实现自定义主题功能
*
* 如果你的项目同样使用了scss预处理，你也可以直接在你的 scss 代码中使用如下变量，同时无需 import 这个文件
*/
/* 颜色变量 */
/* 行为相关颜色 */
$uni-color-primary: #007aff;
$uni-color-success: #4cd964;
$uni-color-warning: #f0ad4e;
$uni-color-error: #dd524d;
/* 文字基本颜色 */
$uni-text-color:#333;//基本色
$uni-text-color-inverse:#fff;//反色
$uni-text-color-grey:#999;//辅助灰色，如加载更多的提示信息
$uni-text-color-placeholder: #808080;
$uni-text-color-disable:#c0c0c0;
/* 背景颜色 */
$uni-bg-color:#ffffff;
$uni-bg-color-grey:#f8f8f8;
$uni-bg-color-hover:#f1f1f1;//点击状态颜色
$uni-bg-color-mask:rgba(0, 0, 0, 0.4);//遮罩颜色
/* 边框颜色 */
$uni-border-color:#c8c7cc;
/* 尺寸变量 */
/* 文字尺寸 */
$uni-font-size-sm:12px;
$uni-font-size-base:14px;
$uni-font-size-lg:16px;
/* 图片尺寸 */
$uni-img-size-sm:20px;
$uni-img-size-base:26px;
$uni-img-size-lg:40px;
/* Border Radius */
$uni-border-radius-sm: 2px;
$uni-border-radius-base: 3px;
$uni-border-radius-lg: 6px;
$uni-border-radius-circle: 50%;
/* 水平间距 */
$uni-spacing-row-sm: 5px;
$uni-spacing-row-base: 10px;
$uni-spacing-row-lg: 15px;
/* 垂直间距 */
$uni-spacing-col-sm: 4px;
$uni-spacing-col-base: 8px;
$uni-spacing-col-lg: 12px;
/* 透明度 */
$uni-opacity-disabled: 0.3; // 组件禁用态的透明度
/* 文章场景相关 */
$uni-color-title: #2C405A; // 文章标题颜色
$uni-font-size-title:20px;
$uni-color-subtitle: #555555; // 二级标题颜色
$uni-font-size-subtitle:26px;
$uni-color-paragraph: #3F536E; // 文章段落颜色
$uni-font-size-paragraph:15px;
|
2301_80750063/Test1
|
uni.scss
|
SCSS
|
unknown
| 2,217
|
<!doctype html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<link rel="icon" type="image/svg+xml" href="/vite.svg" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>canvas-editor</title>
</head>
<body>
<div id="app"></div>
<script type="module" src="/src/main.ts"></script>
</body>
</html>
|
2301_80689990/canvas-editor
|
index.html
|
HTML
|
unknown
| 360
|
<template>
<div class="app" @keydown="handleKeyDown" tabindex="0">
<header class="app-header">
<h1>我的画布</h1>
<div class="toolbar">
<button
@click="undoAction"
:disabled="!canvasStore.canUndo"
class="undo-btn"
title="撤销 (Ctrl/Cmd+Z)"
>
撤销
</button>
<button
@click="redoAction"
:disabled="!canvasStore.canRedo"
class="redo-btn"
title="重做 (Ctrl/Cmd+Shift+Z / Ctrl/Cmd+Y)"
>
重做
</button>
<button @click="addRectangle">矩形</button>
<button @click="addCircle">圆形</button>
<button @click="addTriangle">三角形</button>
<button @click="addText" class="text-btn">文本</button>
<button @click="triggerImageUpload" class="image-btn">
图片
</button>
<input
type="file"
ref="fileInput"
accept="image/png,image/jpeg,image/jpg"
@change="handleImageUpload"
style="display: none"
>
<button @click="resetView" class="view-btn">重置</button>
<div class="zoom-info">
{{ Math.round(viewport.scale * 100) }}%
</div>
<button
@click="deleteSelected"
:disabled="!hasSelection"
class="delete-btn"
>
删除
</button>
</div>
</header>
<main class="app-main">
<CanvasRenderer />
<Toolbar />
</main>
</div>
</template>
<script setup lang="ts">
import { ref, computed, onMounted } from 'vue';
import CanvasRenderer from './components/CanvasRenderer.vue';
import Toolbar from './components/Toolbar.vue';
import { useCanvasStore } from './stores/canvas';
import type {
RectangleElement,
CircleElement,
TriangleElement,
TextElement,
ImageElement
} from './types/canvas';
const canvasStore = useCanvasStore();
const fileInput = ref<HTMLInputElement>();
// 触发文件选择
const triggerImageUpload = (): void => {
fileInput.value?.click();
};
// 处理图片上传
const handleImageUpload = (event: Event): void => {
const target = event.target as HTMLInputElement;
const file = target.files?.[0];
if (!file) return;
if (!file.type.startsWith('image/')) {
console.error('请选择图片文件！');
return;
}
if (file.size > 5 * 1024 * 1024) {
console.error('图片大小不能超过5MB！');
return;
}
const reader = new FileReader();
reader.onload = (e) => {
const result = e.target?.result as string;
if (result) {
addImageElement(result);
}
};
reader.onerror = () => {
console.error('图片读取失败，请重试！');
};
reader.readAsDataURL(file);
target.value = '';
};
// 生成唯一ID的辅助函数
const generateId = (): string => 'element_' + Date.now() + '_' + Math.random().toString(36).substr(2, 9);
// 添加图片元素到画布
const addImageElement = (src: string): void => {
const img = new Image();
img.onload = () => {
// 计算初始尺寸（刚上传到画布时的尺寸）
const initialWidth = img.width > 300 ? 300 : img.width;
const initialHeight = img.width > 300 ? (img.height * 300) / img.width : img.height;
const newImage: ImageElement = {
id: generateId(),
type: 'image',
x: 100,
y: 100,
width: initialWidth, // 使用初始尺寸
height: initialHeight,
originalWidth: img.width,
originalHeight: img.height,
initialWidth: initialWidth, // 保存初始尺寸
initialHeight: initialHeight,
src,
filter: 'none',
opacity: 1,
borderWidth: 0,
borderColor: '#000000',
selected: false,
zIndex: 0
};
canvasStore.addElement(newImage);
};
img.onerror = () => console.error('图片加载失败');
img.src = src;
};
// 计算属性：视口状态
const viewport = computed(() => canvasStore.viewport);
// 计算属性：是否有选中的元素
const hasSelection = computed((): boolean => {
return canvasStore.selectedElements().length > 0;
});
// 添加矩形的方法
const addRectangle = (): void => {
const newRectangle: RectangleElement = {
id: generateId(),
type: 'rectangle',
x: 100,
y: 100,
width: 200,
height: 150,
background: '#ff6b6b',
borderWidth: 0,
borderColor: '#000000',
selected: false,
zIndex: 0
};
canvasStore.addElement(newRectangle);
};
// 添加圆形的方法
const addCircle = (): void => {
const newCircle: CircleElement = {
id: generateId(),
type: 'circle',
x: 150,
y: 150,
width: 120,
height: 120,
background: '#4ecdc4',
borderWidth: 0,
borderColor: '#000000',
selected: false,
zIndex: 0
};
canvasStore.addElement(newCircle);
};
// 添加三角形的方法
const addTriangle = (): void => {
const newTriangle: TriangleElement = {
id: generateId(),
type: 'triangle',
x: 200,
y: 200,
width: 150,
height: 130,
background: '#45b7d1',
borderWidth: 0,
borderColor: '#000000',
selected: false,
zIndex: 0
};
canvasStore.addElement(newTriangle);
};
// 新增：添加文本元素
const addText = (): void => {
const newText: TextElement = {
id: generateId(),
type: 'text',
x: 250,
y: 250,
width: 120,
height: 40,
selected: false,
zIndex: 0,
content: '双击编辑文本',
fontSize: 16,
fontFamily: 'Arial',
color: '#000000',
background: 'transparent',
bold: false,
italic: false,
underline: false,
textAlign: 'left',
strikethrough: false, // 默认无删除线
};
canvasStore.addElement(newText);
};
// 重置视图
const resetView = (): void => {
canvasStore.resetViewport();
};
// 删除选中的元素
const deleteSelected = (): void => {
if (hasSelection.value) {
canvasStore.deleteSelectedElements();
}
};
// --- ⚡ 撤销/重做操作 ⚡ ---
const undoAction = (): void => {
const success = canvasStore.undo();
if (!success) {
console.warn('无法撤销：撤销栈为空');
}
};
const redoAction = (): void => {
const success = canvasStore.redo();
if (!success) {
console.warn('无法重做：重做栈为空');
}
};
// --- ✨ 样式切换辅助函数 (之前缺失的部分) ✨ ---
const toggleTextStyle = (property: 'bold' | 'italic' | 'underline'): void => {
const selected = canvasStore.selectedElements();
selected.forEach(element => {
// 只有文本元素才响应这些快捷键
if (element.type === 'text') {
// 强制类型断言，告诉 TS 这是一个 TextElement
const textElement = element as TextElement;
// 取反当前状态 (true -> false, false -> true)
const newValue = !textElement[property];
// 更新 Store
canvasStore.updateElement(element.id, {
[property]: newValue
});
}
});
};
// 键盘事件处理
const handleKeyDown = (event: KeyboardEvent): void => {
// 边界处理：快捷键冲突 - 检查是否在输入框中
const activeElement = document.activeElement;
const isInputFocused = activeElement?.tagName === 'INPUT' || activeElement?.tagName === 'TEXTAREA';
if (isInputFocused) {
return;
}
const isMetaOrCtrl = event.metaKey || event.ctrlKey;
// 撤销 (Ctrl+Z)
if (isMetaOrCtrl && event.key.toLowerCase() === 'z' && !event.shiftKey) {
event.preventDefault();
undoAction();
}
// 重做 (Ctrl+Shift+Z 或 Ctrl+Y)
else if (isMetaOrCtrl && ((event.key.toLowerCase() === 'z' && event.shiftKey) || event.key.toLowerCase() === 'y')) {
event.preventDefault();
redoAction();
}
// Delete 键或 Backspace 键删除选中元素
if ((event.key === 'Delete' || event.key === 'Backspace') && hasSelection.value) {
event.preventDefault();
deleteSelected();
}
// Ctrl+C 复制
if (isMetaOrCtrl && event.key === 'c') {
event.preventDefault();
const success = canvasStore.copySelectedElements();
if (success) console.log('复制成功');
}
// Ctrl+V 粘贴
if (isMetaOrCtrl && event.key === 'v') {
event.preventDefault();
const success = canvasStore.pasteElements();
if (success) console.log('粘贴成功');
}
// Ctrl+B 加粗
if (isMetaOrCtrl && (event.key === 'b' || event.key === 'B')) {
event.preventDefault();
toggleTextStyle('bold');
}
// Ctrl+I 斜体
if (isMetaOrCtrl && (event.key === 'i' || event.key === 'I')) {
event.preventDefault();
toggleTextStyle('italic');
}
// Ctrl+U 下划线
if (isMetaOrCtrl && (event.key === 'u' || event.key === 'U')) {
event.preventDefault();
toggleTextStyle('underline');
}
// Ctrl + +/- 缩放
if (isMetaOrCtrl && (event.key === '=' || event.key === '+' || event.key === 'Equal')) {
event.preventDefault();
if (hasSelection.value) canvasStore.scaleSelectedElements(1.1);
}
if (isMetaOrCtrl && event.key === '-') {
event.preventDefault();
if (hasSelection.value) canvasStore.scaleSelectedElements(0.9);
}
};
onMounted(() => {
canvasStore.loadFromLocalStorage();
canvasStore.loadClipboardFromLocalStorage();
});
</script>
<style>
/* 重置默认样式 */
* {
margin: 0;
padding: 0;
box-sizing: border-box;
}
html, body {
width: 100%;
height: 100%;
overflow: hidden;
}
#app {
width: 100%;
height: 100%;
}
.app {
width: 100%;
height: 100vh;
display: flex;
flex-direction: column;
padding-bottom: 0;
outline: none;
}
.app-header {
padding: 0rem 1rem;
background: white;
display: flex;
justify-content: space-between;
align-items: center;
flex-shrink: 0;
}
.app-header h1 {
font-size: 2.5rem;
margin: 10px;
}
.app-main {
flex: 1;
overflow: hidden;
margin: 0 20px 20px 20px;
background: white;
border-radius: 8px;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
}
.toolbar {
display: flex;
gap: 10px;
}
/* 通用按钮样式 */
.toolbar button {
padding: 0.5rem 1rem;
background: #4a90e2;
color: white;
border: none;
border-radius: 4px;
cursor: pointer;
transition: all 0.2s;
outline: none; /* 移除点击时的黑框 */
}
.toolbar button:focus {
outline: none; /* 移除焦点时的黑框 */
box-shadow: 0 0 0 2px rgba(255, 255, 255, 0.3); /* 添加自定义焦点样式 */
}
.toolbar button:hover:not(:disabled) {
background: #357abd;
transform: translateY(-1px);
}
/* --- 撤销/重做按钮样式 --- */
.undo-btn, .redo-btn {
padding: 0.5rem 1rem;
border: none;
border-radius: 4px;
cursor: pointer;
transition: all 0.2s;
display: flex;
align-items: center;
gap: 4px;
outline: none; /* 移除点击时的黑框 */
}
.undo-btn:focus,
.redo-btn:focus {
outline: none; /* 移除焦点时的黑框 */
box-shadow: 0 0 0 2px rgba(255, 255, 255, 0.3); /* 添加自定义焦点样式 */
}
.undo-btn {
background: #4a90e2;
color: white;
}
.undo-btn:hover:not(:disabled) {
background: #357abd;
transform: translateY(-1px);
}
.redo-btn {
background: #2ecc71;
color: white;
}
.redo-btn:hover:not(:disabled) {
background: #27ae60;
transform: translateY(-1px);
}
.undo-btn:disabled,
.redo-btn:disabled {
opacity: 0.5;
cursor: not-allowed;
transform: none;
}
.undo-btn .icon, .redo-btn .icon {
font-size: 16px;
}
.view-btn {
background: #27ae60 !important;
margin-left: 10px;
}
.view-btn:hover {
background: #219653 !important;
}
.image-btn {
background: #e67e22 !important;
}
.image-btn:hover {
background: #d35400 !important;
}
.zoom-info {
padding: 0.5rem 1rem;
background: #34495e;
color: white;
border-radius: 4px;
font-size: 14px;
font-family: monospace;
display: flex;
align-items: center;
justify-content: center;
min-width: 60px;
text-align: center;
}
.toolbar button:disabled {
background: #cccccc;
cursor: not-allowed;
opacity: 0.6;
}
.text-btn {
background: #9b59b6 !important;
}
.text-btn:hover {
background: #8e44ad !important;
}
.delete-btn {
background: #e74c3c !important;
margin-left: 10px;
}
.delete-btn:hover:not(:disabled) {
background: #c0392b !important;
}
</style>
|
2301_80689990/canvas-editor
|
src/App.vue
|
Vue
|
unknown
| 12,278
|
<template>
<div class="canvas-container">
<canvas ref="canvasRef"></canvas>
</div>
</template>
<script setup lang="ts">
import { onMounted, onUnmounted, ref, watch } from 'vue';
import { useCanvasStore } from '../stores/canvas';
import { Application, Graphics, Container, Rectangle, Texture, Sprite, Text, TextStyle, TextMetrics } from 'pixi.js';
import { filters } from 'pixi.js';
import type { CanvasElement, TextElement, ImageElement, RectangleElement, CircleElement, TriangleElement } from '../types/canvas';
const { ColorMatrixFilter, BlurFilter } = filters;
const canvasRef = ref<HTMLCanvasElement>();
const canvasStore = useCanvasStore();
let app: Application;
/** 新增：worldLayer（会缩放的世界层）与 uiLayer（不缩放的 UI 层） */
let worldLayer: Container;
let uiLayer: Container;
let selectionGraphics: Graphics;
let lastTextClickTime = 0;
const SCALE_HANDLE_SIZE = 8;
const SCALE_HANDLE_FILL = 0x4a90e2;
const SCALE_HANDLE_STROKE = 0xffffff;
onMounted(() => {
if (!canvasRef.value) return;
app = new Application({
view: canvasRef.value,
width: canvasRef.value.clientWidth,
height: canvasRef.value.clientHeight,
backgroundColor: 0xffffff,
resolution: window.devicePixelRatio || 1,
autoDensity: true
});
// 初始化世界层与 UI 层
worldLayer = new Container();
uiLayer = new Container();
// uiLayer 不随缩放变化
uiLayer.scale.set(1);
uiLayer.position.set(0, 0);
// 把两个层加入 stage（worldLayer 在下面，uiLayer 在上层）
app.stage.addChild(worldLayer);
app.stage.addChild(uiLayer);
// selectionGraphics 放到 uiLayer（不随缩放）
selectionGraphics = new Graphics();
uiLayer.addChild(selectionGraphics);
window.addEventListener('resize', handleResize);
handleResize();
renderElements();
setupCanvasInteractions();
});
const getScaleCursor = (handle: string): string => {
switch (handle) {
case 'nw': case 'se': return 'nwse-resize';
case 'ne': case 'sw': return 'nesw-resize';
case 'n': case 's': return 'ns-resize';
case 'e': case 'w': return 'ew-resize';
default: return 'default';
}
};
const setupCanvasInteractions = () => {
if (!app) return;
app.stage.eventMode = 'static';
app.stage.hitArea = app.screen;
app.stage.on('wheel', (event) => {
event.preventDefault();
const wheelEvent = event.data.originalEvent as unknown as WheelEvent;
canvasStore.zoom(wheelEvent.deltaY, wheelEvent.clientX, wheelEvent.clientY);
});
app.stage.on('pointerdown', (event) => {
const mouseEvent = event.data.originalEvent as unknown as MouseEvent;
// 中键或 Ctrl+左键平移
if (mouseEvent.button === 1 || (mouseEvent.ctrlKey && mouseEvent.button === 0)) {
event.stopPropagation();
const pos = event.data.global;
canvasStore.startPan(pos.x, pos.y);
if (app.renderer.view.style) app.renderer.view.style.cursor = 'grabbing';
}
// 左键点击空白处：框选
else if (mouseEvent.button === 0 && event.target === app.stage) {
const pos = event.data.global;
if (!canvasStore.dragState.isDragging && !canvasStore.viewport.isPanning) {
if (!mouseEvent.shiftKey) canvasStore.clearSelection();
// 传递屏幕坐标给 Store，Store 会转为世界坐标
canvasStore.startSelection(pos.x, pos.y);
if (app.renderer.view.style) app.renderer.view.style.cursor = 'crosshair';
renderSelectionBox();
}
}
});
app.stage.on('pointermove', (event) => {
const pos = event.data.global;
if (canvasStore.scaleState.isScaling) {
canvasStore.updateScale(pos.x, pos.y);
if (app.renderer.view.style) app.renderer.view.style.cursor = getScaleCursor(canvasStore.scaleState.scaleHandle);
} else if (canvasStore.dragState.isDragging) {
canvasStore.updateDrag(pos.x, pos.y);
if (app.renderer.view.style) app.renderer.view.style.cursor = 'grabbing';
} else if (canvasStore.viewport.isPanning) {
canvasStore.updatePan(pos.x, pos.y);
if (app.renderer.view.style) app.renderer.view.style.cursor = 'grabbing';
} else if (canvasStore.selectionBox.isSelecting) {
canvasStore.updateSelection(pos.x, pos.y);
renderSelectionBox();
if (app.renderer.view.style) app.renderer.view.style.cursor = 'crosshair';
} else if (event.target !== app.stage) {
if (app.renderer.view.style) app.renderer.view.style.cursor = 'grab';
} else {
if (app.renderer.view.style) app.renderer.view.style.cursor = 'default';
}
});
const onPointerUp = (): void => {
if (canvasStore.scaleState.isScaling) {
canvasStore.endScale();
if (app.renderer.view.style) app.renderer.view.style.cursor = 'default';
}
if (canvasStore.selectionBox.isSelecting) {
canvasStore.endSelection();
clearSelectionBox();
if (app.renderer.view.style) app.renderer.view.style.cursor = 'default';
}
canvasStore.endDrag();
canvasStore.endPan();
if (app.renderer.view.style) app.renderer.view.style.cursor = 'default';
};
app.stage.on('pointerup', onPointerUp);
app.stage.on('pointerupoutside', onPointerUp);
};
watch(() => [canvasStore.elements, canvasStore.viewport], () => renderElements(), { deep: true });
const handleResize = () => {
if (!app || !canvasRef.value) return;
const parent = canvasRef.value.parentElement;
if (parent) app.renderer.resize(parent.clientWidth, parent.clientHeight);
};
// ✨✨ 优化：框选渲染 - 视觉线条粗细修正 ✨✨
const renderSelectionBox = () => {
if (!selectionGraphics || !canvasStore.selectionBox.isSelecting) return;
const { startX, startY, currentX, currentY } = canvasStore.selectionBox;
// 关键修复：selectionBox存储的是世界坐标，但uiLayer不随缩放，需要转换为屏幕坐标
const x1 = startX * canvasStore.viewport.scale + canvasStore.viewport.x;
const y1 = startY * canvasStore.viewport.scale + canvasStore.viewport.y;
const x2 = currentX * canvasStore.viewport.scale + canvasStore.viewport.x;
const y2 = currentY * canvasStore.viewport.scale + canvasStore.viewport.y;
const x = Math.min(x1, x2);
const y = Math.min(y1, y2);
const width = Math.abs(x2 - x1);
const height = Math.abs(y2 - y1);
selectionGraphics.clear();
// 关键：线条粗细显示一致（UI 层已不缩放）
const lineWidth = 2;
selectionGraphics.lineStyle(lineWidth, 0x4a90e2, 0.8);
selectionGraphics.beginFill(0x4a90e2, 0.1);
selectionGraphics.drawRect(x, y, width, height);
selectionGraphics.endFill();
};
const clearSelectionBox = () => selectionGraphics && selectionGraphics.clear();
const renderElements = () => {
if (!app) return;
// ✅ 不再清空整个 stage，改为只清空 worldLayer（所有会缩放的元素）
worldLayer.removeChildren();
worldLayer.x = canvasStore.viewport.x;
worldLayer.y = canvasStore.viewport.y;
worldLayer.scale.set(canvasStore.viewport.scale);
const sortedElements = [...canvasStore.elements].sort((a, b) => (a.zIndex || 0) - (b.zIndex || 0));
sortedElements.forEach(element => {
let graphics;
if ('type' in element) {
const typedElement = element as { type: string };
switch (typedElement.type) {
case 'rectangle': graphics = createRectangle(element as RectangleElement); break;
case 'circle': graphics = createCircle(element as CircleElement); break;
case 'triangle': graphics = createTriangle(element as TriangleElement); break;
case 'text': graphics = createText(element as TextElement); break;
case 'image': graphics = createImage(element as ImageElement); break;
default: console.warn('未知元素:', typedElement.type);
}
}
if (graphics) worldLayer.addChild(graphics);
});
// selectionGraphics 位于 uiLayer（不随缩放），直接绘制或清空
if (selectionGraphics) {
if (canvasStore.selectionBox.isSelecting) renderSelectionBox();
else selectionGraphics.clear();
}
};
const hexToNumber = (hex: string) => {
if (!hex || typeof hex !== 'string') return 0;
return parseInt(hex.replace('#', ''), 16);
}
// --- 元素创建函数 ---
const createImage = (element: ImageElement): Container => {
const container = new Container();
const DEFAULT_SIZE = 200;
const w = element.width ?? DEFAULT_SIZE;
const h = element.height ?? DEFAULT_SIZE;
const sprite = Sprite.from(element.src);
sprite.width = w;
sprite.height = h;
sprite.alpha = element.opacity ?? 1;
container.addChild(sprite as any);
if (element.borderWidth > 0) {
const border = new Graphics().lineStyle(element.borderWidth, hexToNumber(element.borderColor)).drawRect(0, 0, w, h);
container.addChild(border as any);
}
applyFilter(sprite, element.filter || '无滤镜');
if (element.selected) {
const highlight = new Graphics().lineStyle(3 / canvasStore.viewport.scale, 0x4a90e2).drawRect(-2, -2, w + 4, h + 4);
container.addChild(highlight as any);
drawScaleHandles(container, 0, 0, w, h, element.id);
}
container.x = element.x;
container.y = element.y;
container.hitArea = new Rectangle(-5, -5, w + 10, h + 10);
setupInteractive(container, element);
return container;
};
const applyFilter = (sprite: Sprite, name: string): void => {
sprite.filters = [];
const m = new ColorMatrixFilter();
switch (name) {
case '灰度': m.grayscale(1, false); sprite.filters = [m]; break;
case '复古': m.sepia(false); sprite.filters = [m]; break;
case '反色': m.negative(false); sprite.filters = [m]; break;
case '高饱和': m.saturate(2, false); sprite.filters = [m]; break;
case '去饱和': m.saturate(0, false); sprite.filters = [m]; break;
case '色相180°': m.hue(180, false); sprite.filters = [m]; break;
case '提亮': m.brightness(1.3, false); sprite.filters = [m]; break;
case '高对比': m.contrast(1.5, false); sprite.filters = [m]; break;
case '模糊': sprite.filters = [new BlurFilter(8)]; break;
}
};
const createRectangle = (element: CanvasElement): Container => {
const container = new Container();
const g = new Graphics();
if ('background' in element) {
g.beginFill(hexToNumber(element.background));
}
if ('borderWidth' in element && element.borderWidth > 0 && 'borderColor' in element) {
g.lineStyle(element.borderWidth, hexToNumber(element.borderColor));
}
g.drawRect(0, 0, element.width, element.height);
g.endFill();
if (element.selected) {
g.lineStyle(3 / canvasStore.viewport.scale, 0x4a90e2).drawRect(-2, -2, element.width + 4, element.height + 4);
drawScaleHandles(container, 0, 0, element.width, element.height, element.id);
}
container.addChild(g as any);
container.x = element.x;
container.y = element.y;
container.hitArea = new Rectangle(-5, -5, element.width + 10, element.height + 10);
setupInteractive(container, element);
return container;
};
const createCircle = (element: CanvasElement): Container => {
const container = new Container();
const g = new Graphics();
const rx = element.width / 2, ry = element.height / 2;
if ('background' in element) {
g.beginFill(hexToNumber(element.background));
}
if ('borderWidth' in element && element.borderWidth > 0 && 'borderColor' in element) {
g.lineStyle(element.borderWidth, hexToNumber(element.borderColor));
}
g.drawEllipse(rx, ry, rx, ry);
g.endFill();
if (element.selected) {
g.lineStyle(3 / canvasStore.viewport.scale, 0x4a90e2).drawEllipse(rx, ry, rx + 2, ry + 2);
drawScaleHandles(container, 0, 0, element.width, element.height, element.id);
}
container.addChild(g as any);
container.x = element.x;
container.y = element.y;
container.hitArea = new Rectangle(-5, -5, element.width + 10, element.height + 10);
setupInteractive(container, element);
return container;
};
const createTriangle = (element: CanvasElement): Container => {
const container = new Container();
const g = new Graphics();
const w = element.width, h = element.height;
if ('background' in element) {
g.beginFill(hexToNumber(element.background));
}
if ('borderWidth' in element && 'borderColor' in element) {
g.lineStyle(element.borderWidth, hexToNumber(element.borderColor));
}
g.moveTo(w/2, 0).lineTo(0, h).lineTo(w, h).lineTo(w/2, 0);
g.endFill();
if (element.selected) {
g.lineStyle(3 / canvasStore.viewport.scale, 0x4a90e2);
g.moveTo(w/2, -3).lineTo(-3, h+3).lineTo(w+3, h+3).lineTo(w/2, -3);
drawScaleHandles(container, 0, 0, w, h, element.id);
}
container.addChild(g as any);
container.x = element.x;
container.y = element.y;
container.hitArea = new Rectangle(-5, -5, w + 10, h + 10);
setupInteractive(container, element);
return container;
};
const createText = (element: any) => {
const container = new Container();
const graphics = new Graphics();
// 1. 初始化样式
const style = new TextStyle({
fontFamily: element.fontFamily || 'Arial, Helvetica, sans-serif',
fontSize: Number(element.fontSize) || 16,
fill: element.color || '#000000',
fontWeight: element.bold ? 'bold' : 'normal',
fontStyle: element.italic ? 'italic' : 'normal',
align: element.textAlign || 'left',
wordWrap: true,
wordWrapWidth: Number(element.width) || 200,
breakWords: true,
padding: 10,
trim: true,
textBaseline: 'middle'
});
// 2. 创建文本对象
const textSprite = new Text(element.content, style);
textSprite.style = style;
textSprite.text = element.content;
try {
(textSprite as any).updateText && (textSprite as any).updateText();
} catch (e) {
}
// 手动处理对齐
if (element.textAlign === 'center') {
textSprite.anchor.set(0.5, 0);
textSprite.x = element.width / 2;
} else if (element.textAlign === 'right') {
textSprite.anchor.set(1, 0);
textSprite.x = element.width;
} else {
textSprite.anchor.set(0, 0);
textSprite.x = 0;
}
textSprite.y = 0;
// 3. 绘制背景
if (element.background && element.background !== 'transparent') {
graphics.beginFill(hexToNumber(element.background));
} else {
graphics.beginFill(0x000000, 0);
}
graphics.drawRect(0, 0, element.width, element.height);
graphics.endFill();
// 4. 选中状态高亮
if (element.selected) {
graphics.lineStyle(2 / canvasStore.viewport.scale, 0x4a90e2);
graphics.drawRect(-2, -2, element.width + 4, element.height + 4);
drawScaleHandles(container, 0, 0, element.width, element.height, element.id);
}
// 5. 组装
container.addChild(graphics as any);
container.addChild(textSprite as any);
// ... (省略装饰线逻辑，保持不变，因为你之前的代码装饰线逻辑已经是好的) ...
// ✨✨ 手动绘制线条 (修复多行渲染 & 消失Bug) ✨✨
const drawStrikethrough = element.strikethrough;
const drawUnderline = !drawStrikethrough && element.underline;
if (drawStrikethrough || drawUnderline) {
const lineGraphics = new Graphics();
const lineColor = hexToNumber(element.color);
lineGraphics.lineStyle(2, lineColor);
const metrics = TextMetrics.measureText(element.content, style, element.wordWrap);
const lineHeight = metrics.lineHeight;
metrics.lines.forEach((lineText, i) => {
const lineWidth = TextMetrics.measureText(lineText, style, element.wordWrap).width;
let lineXOffset = 0;
if (element.textAlign === 'center') {
lineXOffset = (element.width - lineWidth) / 2;
} else if (element.textAlign === 'right') {
lineXOffset = element.width - lineWidth;
}
const finalStartX = lineXOffset;
const finalEndX = finalStartX + lineWidth;
const lineTopY = textSprite.y + i * lineHeight;
if (drawStrikethrough) {
const strikeY = lineTopY + lineHeight * 0.55;
lineGraphics.moveTo(finalStartX, strikeY);
lineGraphics.lineTo(finalEndX, strikeY);
} else if (drawUnderline) {
const underlineY = lineTopY + lineHeight * 0.92;
lineGraphics.moveTo(finalStartX, underlineY);
lineGraphics.lineTo(finalEndX, underlineY);
}
});
container.addChild(lineGraphics);
}
// 位置与交互
container.x = element.x;
container.y = element.y;
container.eventMode = 'static';
container.cursor = 'text';
container.hitArea = new Rectangle(0, 0, element.width, element.height);
container.on('pointerdown', (event) => {
event.stopPropagation();
const currentTime = Date.now();
if (currentTime - lastTextClickTime < 300) {
startTextEdit(element); // 双击编辑
lastTextClickTime = 0;
return;
}
lastTextClickTime = currentTime;
const pos = event.data.global;
if ((event.data.originalEvent as unknown as KeyboardEvent).shiftKey) {
canvasStore.toggleElementSelection(element.id);
} else {
if (!element.selected) canvasStore.selectElement(element.id);
}
canvasStore.bringToFront();
container.scale.set(1.05);
setTimeout(() => container.scale.set(1.0), 150);
// ✅ 关键：把屏幕坐标转换为世界坐标后再 startDrag（统一世界坐标）
const world = canvasStore.screenToWorld(pos.x, pos.y);
canvasStore.startDrag(element.id, world.x, world.y);
});
return container;
};
const setupInteractive = (container: Container, element: any) => {
container.eventMode = 'static';
container.cursor = 'pointer';
container.on('pointerover', () => container.cursor = 'grab');
container.on('pointerout', () => container.cursor = 'pointer');
container.on('pointerdown', (e) => {
e.stopPropagation();
container.cursor = 'grabbing';
const global = e.data.global;
if ((e.data.originalEvent as unknown as KeyboardEvent).shiftKey) canvasStore.toggleElementSelection(element.id);
else if (!element.selected) canvasStore.selectElement(element.id);
canvasStore.bringToFront();
container.scale.set(1.05);
setTimeout(() => container.scale.set(1.0), 150);
// ✅ 关键：统一传入世界坐标（screen -> world）
const world = canvasStore.screenToWorld(global.x, global.y);
canvasStore.startDrag(element.id, world.x, world.y);
});
container.on('pointerup', () => container.cursor = 'grab');
};
// ✨✨ 优化：缩放手柄 - 视觉大小修正 ✨✨
const drawScaleHandles = (container: Container, x: number, y: number, w: number, h: number, id: string) => {
const handles = [
{ id: 'nw', x: x, y: y, c: 'nwse-resize' },
{ id: 'n', x: x + w/2, y: y, c: 'ns-resize' },
{ id: 'ne', x: x + w, y: y, c: 'nesw-resize' },
{ id: 'e', x: x + w, y: y + h/2, c: 'ew-resize' },
{ id: 'se', x: x + w, y: y + h, c: 'nwse-resize' },
{ id: 's', x: x + w/2, y: y + h, c: 'ns-resize' },
{ id: 'sw', x: x, y: y + h, c: 'nesw-resize' },
{ id: 'w', x: x, y: y + h/2, c: 'ew-resize' }
];
handles.forEach(hdl => {
const g = new Graphics();
// 关键：除以 scale，确保手柄视觉大小不变
const size = SCALE_HANDLE_SIZE / canvasStore.viewport.scale;
g.beginFill(SCALE_HANDLE_FILL).lineStyle(1 / canvasStore.viewport.scale, SCALE_HANDLE_STROKE);
g.drawRect(hdl.x - size/2, hdl.y - size/2, size, size);
g.endFill();
g.eventMode = 'static';
g.cursor = hdl.c;
g.on('pointerdown', (e) => {
e.stopPropagation();
e.data.originalEvent.preventDefault();
// startScale 在 store 端期望屏幕坐标（startX,startY），因此我们传入屏幕坐标
canvasStore.startScale(id, hdl.id, e.data.global.x, e.data.global.y);
});
container.addChild(g as any);
});
};
const startTextEdit = (element: any) => {
const parent = app.view.parentElement;
if (!parent) return;
const textarea = document.createElement('textarea');
const scale = canvasStore.viewport.scale;
const x = element.x * scale + canvasStore.viewport.x;
const y = element.y * scale + canvasStore.viewport.y;
textarea.value = element.content;
textarea.style.position = 'absolute';
textarea.style.left = `${x}px`;
textarea.style.top = `${y}px`;
textarea.style.width = `${element.width * scale}px`;
textarea.style.height = `${element.height * scale}px`;
textarea.style.fontSize = `${element.fontSize * scale}px`;
textarea.style.fontFamily = element.fontFamily;
textarea.style.color = element.color;
textarea.style.textAlign = element.textAlign;
textarea.style.fontWeight = element.bold ? 'bold' : 'normal';
textarea.style.fontStyle = element.italic ? 'italic' : 'normal';
textarea.style.textDecoration = element.strikethrough ? 'line-through' : (element.underline ? 'underline' : 'none');
textarea.style.background = element.background === 'transparent' ? 'rgba(255,255,255,0.8)' : element.background;
textarea.style.border = '1px dashed #4a90e2';
textarea.style.outline = 'none';
textarea.style.padding = '0';
textarea.style.margin = '0';
textarea.style.resize = 'none';
textarea.style.zIndex = '1000';
const finish = (): void => {
if (textarea.value !== element.content) {
canvasStore.updateElement(element.id, { content: textarea.value });
}
if (textarea.parentNode) textarea.parentNode.removeChild(textarea);
};
textarea.onblur = finish;
textarea.onkeydown = (e) => {
if (e.key === 'Enter' && !e.shiftKey) {
e.preventDefault();
finish();
}
if (e.key === 'Escape') textarea.remove();
e.stopPropagation();
};
parent.appendChild(textarea);
setTimeout(() => { textarea.focus(); textarea.select(); }, 10);
};
onUnmounted(() => {
if (app) app.destroy(true, { children: true, texture: true, baseTexture: true });
window.removeEventListener('resize', handleResize);
});
</script>
<style scoped>
.canvas-container {
width: 100%;
height: 100%;
background: #f5f5f5;
position: relative;
overflow: hidden;
}
canvas {
display: block;
width: 100%;
height: 100%;
}
</style>
|
2301_80689990/canvas-editor
|
src/components/CanvasRenderer.vue
|
Vue
|
unknown
| 22,008
|
<script setup lang="ts">
import { ref } from 'vue'
defineProps<{ msg: string }>()
const count = ref(0)
</script>
<template>
<h1>{{ msg }}</h1>
<div class="card">
<button type="button" @click="count++">count is {{ count }}</button>
<p>
Edit
<code>components/HelloWorld.vue</code> to test HMR
</p>
</div>
<p>
Check out
<a href="https://vuejs.org/guide/quick-start.html#local" target="_blank"
>create-vue</a
>, the official Vue + Vite starter
</p>
<p>
Learn more about IDE Support for Vue in the
<a
href="https://vuejs.org/guide/scaling-up/tooling.html#ide-support"
target="_blank"
>Vue Docs Scaling up Guide</a
>.
</p>
<p class="read-the-docs">Click on the Vite and Vue logos to learn more</p>
</template>
<style scoped>
.read-the-docs {
color: #888;
}
</style>
|
2301_80689990/canvas-editor
|
src/components/HelloWorld.vue
|
Vue
|
unknown
| 856
|
<template>
<div
v-if="hasSelection"
class="toolbar"
ref="toolbarRef"
:style="toolbarStyle"
>
<div class="toolbar-handle" @mousedown="startDrag">
⠿ 拖拽移动
</div>
<div class="toolbar-section">
<h3>属性设置</h3>
<div v-if="selectedTypes.includes('text')" class="text-properties">
<div class="toolbar-item">
<label>内容:</label>
<input
type="text"
v-model="selectedContent"
@input="updateSelectedElementsOptimized('content', selectedContent)"
@focus="disableGlobalKeys"
@blur="enableGlobalKeys"
>
</div>
<div class="toolbar-row">
<div class="toolbar-item">
<label>字号:</label>
<input
type="number"
min="12"
v-model="selectedFontSize"
@input="updateSelectedElementsOptimized('fontSize', selectedFontSize)"
@focus="disableGlobalKeys"
@blur="enableGlobalKeys"
>
</div>
<div class="toolbar-item">
<label>字体:</label>
<select
v-model="selectedFontFamily"
@change="updateSelectedElementsOptimized('fontFamily', selectedFontFamily)"
style="width: 100px; height: 30px;"
>
<option value="Arial">Arial</option>
<option value="Times New Roman">Times New Roman</option>
<option value="SimSun">宋体</option>
<option value="Microsoft YaHei">微软雅黑</option>
<option value="SimHei">黑体</option>
</select>
</div>
</div>
<div class="toolbar-item">
<label>颜色:</label>
<input
type="color"
v-model="selectedTextColor"
@input="updateSelectedElementsOptimized('color', selectedTextColor)"
>
</div>
<div class="toolbar-item style-buttons">
<button
:class="{ active: selectedBold }"
@click="updateSelectedElementsOptimized('bold', !selectedBold)"
title="加粗 (Ctrl+B)"
>
B
</button>
<button
:class="{ active: selectedItalic }"
@click="updateSelectedElementsOptimized('italic', !selectedItalic)"
title="斜体 (Ctrl+I)"
>
<span style="display:inline-block; transform: skewX(-12deg); font-family: Arial;">
I
</span>
</button>
<button
:class="{ active: selectedUnderline }"
@click="updateSelectedElementsOptimized('underline', !selectedUnderline)"
title="下划线 (Ctrl+U)"
>
U
</button>
<button
:class="{ active: selectedStrikethrough }"
@click="updateSelectedElementsOptimized('strikethrough', !selectedStrikethrough)"
title="删除线"
style="text-decoration: line-through;"
>
S
</button>
</div>
<div class="toolbar-item style-buttons">
<button :class="{ active: selectedTextAlign === 'left' }" @click="updateSelectedElementsOptimized('textAlign', 'left')">左</button>
<button :class="{ active: selectedTextAlign === 'center' }" @click="updateSelectedElementsOptimized('textAlign', 'center')">中</button>
<button :class="{ active: selectedTextAlign === 'right' }" @click="updateSelectedElementsOptimized('textAlign', 'right')">右</button>
</div>
<hr class="divider">
</div>
<div class="toolbar-item">
<label>背景色:</label>
<div style="display: flex; gap: 5px; align-items: center;">
<input
type="color"
v-model="displayBackgroundColor"
>
<button
@click="setBackgroundTransparent"
class="small-btn"
:class="{ active: selectedBackground === 'transparent' }"
title="设为透明"
>
透明
</button>
</div>
</div>
<div class="toolbar-item">
<label>边框色:</label>
<input
type="color"
v-model="selectedBorderColor"
@input="updateSelectedElementsOptimized('borderColor', selectedBorderColor)"
>
<span class="color-value">{{ selectedBorderColor }}</span>
</div>
<div class="toolbar-item">
<label>边框宽度:</label>
<input
type="range"
min="0"
max="10"
v-model="selectedBorderWidth"
@input="updateSelectedElementsOptimized('borderWidth', parseInt(selectedBorderWidth.toString()))"
>
<span>{{ selectedBorderWidth }}px</span>
</div>
<div class="toolbar-item" v-if="selectedTypes.includes('image')">
<label>滤镜:</label>
<select v-model="selectedFilter"
@input="updateSelectedElementsOptimized('filter', ($event.target as HTMLSelectElement).value)">
<option value="无滤镜">无滤镜</option>
<option value="灰度">灰度</option>
<option value="复古">复古</option>
<option value="反色">反色</option>
<option value="提亮">提亮</option>
<option value="高对比">高对比</option>
<option value="高饱和">高饱和</option>
<option value="去饱和">去饱和</option>
<option value="色相180°">色相180°</option>
<option value="模糊">模糊</option>
</select>
</div>
<div class="toolbar-item" v-if="showImageProperties">
<label>透明度:</label>
<input
type="range"
min="0"
max="1"
step="0.05"
:value="selectedOpacity"
@input="onOpacityInput"
>
<span>{{ Math.round(selectedOpacity * 100) }}%</span>
</div>
<div class="toolbar-actions" v-if="showImageProperties">
<button class="reset-btn" @click="resetImageSize">重置尺寸</button>
</div>
<div class="toolbar-row">
<div class="toolbar-item">
<label>X:</label>
<input
type="number"
v-model="selectedX"
@input="updateSelectedElementsOptimized('x', parseInt(selectedX.toString()) || 0)"
@focus="disableGlobalKeys"
@blur="enableGlobalKeys"
ref="xInput"
>
</div>
<div class="toolbar-item">
<label>Y:</label>
<input
type="number"
v-model="selectedY"
@input="updateSelectedElementsOptimized('y', parseInt(selectedY.toString()) || 0)"
@focus="disableGlobalKeys"
@blur="enableGlobalKeys"
ref="yInput"
>
</div>
</div>
<div class="toolbar-row">
<div class="toolbar-item">
<label>宽度:</label>
<input
type="number"
min="10"
v-model="selectedWidth"
@input="updateSelectedElementsOptimized('width', Math.max(1, parseInt(selectedWidth.toString()) || 100))"
@focus="disableGlobalKeys"
@blur="enableGlobalKeys"
ref="widthInput"
>
</div>
<div class="toolbar-item">
<label>高度:</label>
<input
type="number"
min="10"
v-model="selectedHeight"
@input="updateSelectedElementsOptimized('height', Math.max(1, parseInt(selectedHeight.toString()) || 100))"
@focus="disableGlobalKeys"
@blur="enableGlobalKeys"
ref="heightInput"
>
</div>
</div>
<div class="toolbar-actions">
<button @click="copySelected" class="copy-btn" :disabled="!hasSelection">
复制 (Ctrl+C)
</button>
<button @click="pasteElements" class="paste-btn" :disabled="!canPaste">
粘贴 (Ctrl+V)
</button>
<button @click="deleteSelected" class="delete-btn">
删除
</button>
<button @click="clearSelection" class="clear-btn">
取消
</button>
</div>
<div class="selection-info">
<p>已选中 {{ selectedCount }} 个元素</p>
<p v-if="selectedTypes.length > 0">类型: {{ selectedTypes.join(', ') }}</p>
</div>
</div>
</div>
</template>
<script setup lang="ts">
import { ref, watch, computed, onMounted, onUnmounted } from 'vue';
import { useCanvasStore } from '../stores/canvas';
import type { TextElement } from '../types/canvas';
// 防抖和节流函数
const debounce = <T extends (...args: any[]) => void>(func: T, delay: number) => {
let timeoutId: ReturnType<typeof setTimeout>;
return (...args: Parameters<T>) => {
clearTimeout(timeoutId);
timeoutId = setTimeout(() => func(...args), delay);
};
};
const throttle = <T extends (...args: any[]) => void>(func: T, limit: number) => {
let inThrottle: boolean;
return (...args: Parameters<T>) => {
if (!inThrottle) {
func(...args);
inThrottle = true;
setTimeout(() => inThrottle = false, limit);
}
};
};
const canvasStore = useCanvasStore();
const toolbarRef = ref<HTMLElement>();
// 图片专属表单数据
const selectedOpacity = ref<number>(1);
const selectedFilter = ref('');
// 输入框引用
const xInput = ref<HTMLInputElement>();
const yInput = ref<HTMLInputElement>();
const widthInput = ref<HTMLInputElement>();
const heightInput = ref<HTMLInputElement>();
const isDragging = ref(false);
const dragOffset = ref({ x: 0, y: 0 });
const loadToolbarPosition = () => {
const saved = localStorage.getItem('toolbar-position');
if (saved) return JSON.parse(saved);
return { x: 20, y: 80 };
};
const saveToolbarPosition = (position: { x: number; y: number }) => {
localStorage.setItem('toolbar-position', JSON.stringify(position));
};
const toolbarPosition = ref(loadToolbarPosition());
const globalKeysEnabled = ref(true);
const toolbarStyle = computed(() => ({
left: `${toolbarPosition.value.x}px`,
top: `${toolbarPosition.value.y}px`
}));
// 计算属性
const hasSelection = computed(() => canvasStore.selectedElements().length > 0);
const selectedCount = computed(() => canvasStore.selectedElements().length);
const selectedElements = computed(() => canvasStore.selectedElements());
const canPaste = computed(() => canvasStore.clipboard.length > 0);
const selectedTypes = computed(() => [...new Set(selectedElements.value.map(el => el.type))]);
const showImageProperties = computed(() => selectedElements.value.some((el: { type: string }) => el.type === 'image'));
// 表单数据
const selectedBackground = ref('#ffffff');
const selectedBorderColor = ref('#000000');
const selectedBorderWidth = ref(0);
const selectedX = ref(0);
const selectedY = ref(0);
const selectedWidth = ref(100);
const selectedHeight = ref(100);
// 文本专属数据
const selectedContent = ref('');
const selectedFontSize = ref(16);
const selectedFontFamily = ref('Arial');
const selectedTextColor = ref('#000000');
const selectedBold = ref(false);
const selectedItalic = ref(false);
const selectedUnderline = ref(false);
const selectedStrikethrough = ref(false);
const selectedTextAlign = ref('left');
// 计算属性：解决背景色输入框不支持 transparent 的问题
const displayBackgroundColor = computed({
get: () => {
return selectedBackground.value === 'transparent' ? '#ffffff' : selectedBackground.value;
},
set: (val) => {
selectedBackground.value = val;
updateSelectedElementsOptimized('background', val);
}
});
// 方法定义
const disableGlobalKeys = () => { globalKeysEnabled.value = false; };
const enableGlobalKeys = () => { globalKeysEnabled.value = true; };
const onOpacityInput = (e: Event) => {
const val = parseFloat((e.target as HTMLInputElement).value);
selectedOpacity.value = val;
updateSelectedElementsOptimized('opacity', val);
};
const resetImageSize = () => {
const img = canvasStore.selectedElements().find((el: { type: string }) => el.type === 'image');
if (!img) return;
const w = (img as any).initialWidth || (img as any).width || 200;
const h = (img as any).initialHeight || (img as any).height || 200;
updateSelectedElements('width', w);
updateSelectedElements('height', h);
selectedWidth.value = w;
selectedHeight.value = h;
};
// 拖拽逻辑
const startDrag = (event: MouseEvent) => {
event.preventDefault();
isDragging.value = true;
if (toolbarRef.value) {
const rect = toolbarRef.value.getBoundingClientRect();
dragOffset.value = { x: event.clientX - rect.left, y: event.clientY - rect.top };
}
document.addEventListener('mousemove', handleDrag);
document.addEventListener('mouseup', stopDrag);
};
const handleDrag = (event: MouseEvent) => {
if (!isDragging.value) return;
const newX = event.clientX - dragOffset.value.x;
const newY = event.clientY - dragOffset.value.y;
const maxX = window.innerWidth - 300;
const maxY = window.innerHeight - 400;
toolbarPosition.value = { x: Math.max(0, Math.min(newX, maxX)), y: Math.max(0, Math.min(newY, maxY)) };
};
const stopDrag = () => {
isDragging.value = false;
saveToolbarPosition(toolbarPosition.value);
document.removeEventListener('mousemove', handleDrag);
document.removeEventListener('mouseup', stopDrag);
};
const handleResize = () => {
const maxX = window.innerWidth - 300;
const maxY = window.innerHeight - 400;
if (toolbarPosition.value.x > maxX || toolbarPosition.value.y > maxY) {
toolbarPosition.value = { x: Math.min(toolbarPosition.value.x, maxX), y: Math.min(toolbarPosition.value.y, maxY) };
saveToolbarPosition(toolbarPosition.value);
}
};
// 监听选中元素变化
watch(selectedElements, (newElements) => {
const img = newElements.find((el: { type: string }) => el.type === 'image');
selectedFilter.value = img ? (img.filter ?? '无滤镜') : '无滤镜';
selectedOpacity.value = img ? (img.opacity ?? 1) : 1;
if (newElements.length) {
const firstElement = newElements[0];
selectedBackground.value = firstElement.background ?? '#ffffff';
selectedBorderColor.value = firstElement.borderColor ?? '#000000';
selectedBorderWidth.value = firstElement.borderWidth ?? 0;
selectedX.value = firstElement.x;
selectedY.value = firstElement.y;
selectedWidth.value = firstElement.width;
selectedHeight.value = firstElement.height;
if (newElements.length === 1 && firstElement.type === 'text') {
const textEl = firstElement as TextElement;
selectedContent.value = textEl.content || '';
selectedFontSize.value = textEl.fontSize || 16;
selectedFontFamily.value = textEl.fontFamily || 'Arial';
selectedTextColor.value = textEl.color || '#000000';
selectedBold.value = textEl.bold || false;
selectedItalic.value = textEl.italic || false;
selectedUnderline.value = textEl.underline || false;
selectedStrikethrough.value = textEl.strikethrough || false;
selectedTextAlign.value = textEl.textAlign || 'left';
}
} else {
selectedBackground.value = '#ffffff';
selectedBorderColor.value = '#000000';
selectedBorderWidth.value = 0;
selectedX.value = 0;
selectedY.value = 0;
selectedWidth.value = 0;
selectedHeight.value = 0;
}
}, { immediate: true, deep: true });
// 更新方法
const updateSelectedElements = (property: string, value: any) => {
if (property === 'filter' && value === '') value = '无滤镜';
if (property === 'width' || property === 'height') {
const minSize = 10;
value = Math.max(minSize, parseInt(value) || minSize);
if (property === 'width') selectedWidth.value = value;
else if (property === 'height') selectedHeight.value = value;
}
const selectedIds = canvasStore.selectedElements().map(el => el.id);
selectedIds.forEach(id => {
canvasStore.updateElement(id, { [property]: value });
});
};
const setBackgroundTransparent = () => {
selectedBackground.value = 'transparent';
updateSelectedElementsOptimized('background', 'transparent');
};
// 核心修复函数：处理字体大小类型转换
const updateSelectedElementsOptimized = (property: string, value: any) => {
if (property === 'background' && value !== 'transparent') {
selectedBackground.value = value;
}
// ✨✨ 核心修复：字号必须转为数字 ✨✨
if (property === 'fontSize') {
const size = parseInt(String(value));
if (isNaN(size) || size < 10) return;
debounceUpdate(property, size);
return;
}
// ✨✨ 核心修复：边框宽度必须转为数字 ✨✨
if (property === 'borderWidth') {
const width = parseInt(String(value));
if (isNaN(width) || width < 0) return;
throttleUpdate(property, width);
return;
}
if (['opacity'].includes(property)) throttleUpdate(property, value);
else if (['x', 'y', 'width', 'height'].includes(property)) debounceUpdate(property, value);
else immediateUpdate(property, value);
};
const immediateUpdate = (property: string, value: any) => updateSelectedElements(property, value);
const throttleUpdate = throttle((property: string, value: any) => updateSelectedElements(property, value), 50);
const debounceUpdate = debounce((property: string, value: any) => updateSelectedElements(property, value), 100);
const deleteSelected = () => canvasStore.deleteSelectedElements();
const clearSelection = () => canvasStore.clearSelection();
const copySelected = () => canvasStore.copySelectedElements();
const pasteElements = () => canvasStore.pasteElements();
onMounted(() => window.addEventListener('resize', handleResize));
onUnmounted(() => {
document.removeEventListener('mousemove', handleDrag);
document.removeEventListener('mouseup', stopDrag);
window.removeEventListener('resize', handleResize);
});
</script>
<style scoped>
.toolbar {
position: fixed;
background: white;
border: 1px solid #e0e0e0;
border-radius: 8px;
padding: 0;
box-shadow: 0 4px 12px rgba(0, 0, 0, 0.1);
min-width: 280px;
z-index: 1000;
cursor: default;
user-select: none;
}
.toolbar-handle {
padding: 12px 16px;
background: #f8f9fa;
border-bottom: 1px solid #e0e0e0;
cursor: grab;
font-size: 14px;
color: #666;
border-radius: 8px 8px 8px 8px;
display: flex;
align-items: center;
justify-content: space-between;
}
.toolbar-handle::before { font-size: 16px; margin-right: 8px; }
.toolbar-handle:active { cursor: grabbing; background: #dee2e6; }
.toolbar-section { padding: 16px; }
.toolbar-section h3 { margin: 0 0 16px 0; font-size: 16px; border-bottom: 1px solid #eee; padding-bottom: 8px; }
.toolbar-item { display: flex; align-items: center; margin-bottom: 12px; gap: 8px; }
.toolbar-item label { min-width: 80px; font-size: 14px; color: #666; }
.toolbar-item input[type="color"] { width: 40px; height: 30px; border: 1px solid #ddd; cursor: pointer; }
.toolbar-item input[type="range"] { flex: 1; }
.toolbar-item input[type="number"], .toolbar-item input[type="text"] { width: 70px; padding: 4px 8px; border: 1px solid #ddd; border-radius: 4px; }
.toolbar-row { display: flex; gap: 12px; }
.toolbar-actions { display: flex; gap: 8px; margin-top: 16px; padding-top: 16px; border-top: 1px solid #eee; transform: translateY(0); }
.toolbar-actions button { flex: 1; padding: 8px; border: none; border-radius: 4px; cursor: pointer; color: white; margin-bottom: 8px; }
.delete-btn { background: #e74c3c; }
.copy-btn { background: #3498db; }
.paste-btn { background: #2ecc71; }
.clear-btn { background: #95a5a6; }
.reset-btn { background: #f39c12 !important; }
.reset-btn:hover, .reset-btn:active { background: #e67e22 !important; }
.selection-info { margin-top: 12px; font-size: 12px; color: #666; border-top: 1px solid #eee; padding-top: 8px; }
/* 文本样式按钮 */
.style-buttons { display: flex; gap: 4px; }
.style-buttons button { flex: 1; padding: 6px; background: #f8f9fa; border: 1px solid #ddd; border-radius: 4px; cursor: pointer; font-weight: bold; color: #333; }
.style-buttons button.active { background: #4a90e2; color: white; border-color: #357abd; }
.divider { border: 0; border-top: 1px solid #eee; margin: 12px 0; }
.small-btn { padding: 2px 6px; font-size: 12px; background: #f1f1f1; border: 1px solid #ccc; border-radius: 4px; cursor: pointer; }
.small-btn.active { background: #e0e0e0; color: #999; border-style: dashed; }
</style>
|
2301_80689990/canvas-editor
|
src/components/Toolbar.vue
|
Vue
|
unknown
| 20,694
|
import { createApp } from 'vue'
import { createPinia } from 'pinia' // 导入pinia
import './style.css'
import App from './App.vue'
const app = createApp(App)
const pinia = createPinia()
app.use(pinia) // 使用pinia
app.mount('#app')
|
2301_80689990/canvas-editor
|
src/main.ts
|
TypeScript
|
unknown
| 239
|
// 新增：拖拽状态类型
interface DragState {
isDragging: boolean;
dragElementId: string;
startX: number;
startY: number;
elementStartX: number;
elementStartY: number;
selectedIds: string[]; // 所有选中的元素ID
elementStartPositions: { [key: string]: { x: number, y: number } }; // 所有元素的初始位置
}
// 在 canvas.ts 中添加缩放状态接口
interface ScaleState {
isScaling: boolean;
scaleHandle: string; // 'nw' | 'ne' | 'sw' | 'se' | 'n' | 'e' | 's' | 'w'
elementId: string;
startX: number;
startY: number;
elementStartX: number;
elementStartY: number;
elementStartWidth: number;
elementStartHeight: number;
scaleMultiple: boolean; // 是否同时缩放多个元素
selectedIds: string[];
elementStartPositions: { [key: string]: { x: number, y: number, width: number, height: number } };
}
// 用于移动操作的元素位置接口
interface ElementPosition {
id: string;
x: number;
y: number;
}
type OperationData = {
// 整体画布状态（用于全局撤销/重做）
elements?: CanvasElement[];
// 特定元素操作（用于局部撤销/重做）
elementId?: string;
before?: Partial<CanvasElement> | CanvasElement[] | ElementPosition[]; // 操作前状态
after?: Partial<CanvasElement> | CanvasElement[] | ElementPosition[]; // 操作后状态
};
export interface CanvasOperation {
id: string; // 操作 ID
type: 'add' | 'delete' | 'move' | 'resize' | 'update' | 'clear' | 'batch'; // 操作类型
timestamp: number; // 时间戳
description: string; // 操作描述
data: OperationData; // 操作数据
}
// 1.1 数据结构定义：HistoryState 接口
export interface HistoryState {
undoStack: CanvasOperation[]; // 撤销栈
redoStack: CanvasOperation[]; // 重做栈
maxHistory: number; // 最大历史条数
isRecording: boolean; // 记录开关
}
// 1. 导入必要的工具
import { defineStore } from 'pinia';
import { ref, computed } from 'vue';
import type { CanvasElement } from '../types/canvas';
// 2. 创建仓库
export const useCanvasStore = defineStore('canvas', () => {
// 1.3 撤销：从撤销栈取出最后一条操作，恢复到操作前状态，移入重做栈
const undo = (): boolean => {
if (historyState.value.undoStack.length === 0) {
console.warn('撤销栈为空，无法撤销。')
return false
}
const operation = historyState.value.undoStack.pop() as CanvasOperation
// 4.2 ① 暂停记录
pauseRecording()
try {
console.log(`[undo] ${operation.description} (${operation.type})`)
const { before, after } = operation.data
switch (operation.type) {
case 'add': {
// 新增撤销：删除对应元素
const elementId = operation.data.elementId;
const idsToDel = elementId ? [elementId] : (after as CanvasElement[]).map(e => e.id)
elements.value = elements.value.filter(el => !idsToDel.includes(el.id))
break
}
case 'delete': {
// 删除撤销：只保留真值元素
const toRestore = (Array.isArray(before) ? before : [before])
.filter((b): b is CanvasElement => b != null)
if (toRestore.length) elements.value.push(...deepClone(toRestore))
break
}
case 'update':
case 'move':
case 'resize':
case 'batch': {
// 批量或单个：用 before 快照覆盖
const arr = Array.isArray(before) ? before : [before]
arr.forEach(b => {
if (b) {
const target = elements.value.find(el => el.id === b.id)
if (target) Object.assign(target, deepClone(b))
}
})
break
}
case 'clear': {
// 清空撤销：整份恢复
elements.value = deepClone(before as CanvasElement[])
break
}
default:
console.warn(`[undo] 未知类型: ${operation.type}`)
break
}
// 移入重做栈
historyState.value.redoStack.push(operation)
// 收尾
clearSelection()
saveToLocalStorage()
return true
} catch (e) {
// 4.2 异常捕获 & 回滚
console.error('[undo] 失败:', e)
historyState.value.undoStack.push(operation) // 还回去
return false
} finally {
// 4.2 恢复记录
resumeRecording()
}
}
// const undo = () => {
// if (historyState.value.undoStack.length === 0) {
// console.warn('撤销栈为空，无法撤销。');
// return false;
// }
// const operation = historyState.value.undoStack.pop() as CanvasOperation;
// // 1. 暂停记录，防止撤销操作本身被记录
// pauseRecording();
// try {
// console.log(`执行撤销操作: ${operation.description} (类型: ${operation.type})`);
// // 使用操作前状态 (operation.data.before) 恢复元素状态
// const elementId = operation.data.elementId;
// const beforeState = operation.data.before;
// const afterState = operation.data.after; // 记录当前状态（操作后的状态），用于重做
// switch (operation.type) {
// case 'add':
// // 新增操作的撤销：删除被新增的元素
// if (elementId) {
// elements.value = elements.value.filter(el => el.id !== elementId);
// } else if (Array.isArray(afterState)) {
// // 批量添加的撤销：删除所有新增的元素（afterState即为新增的元素列表）
// const idsToDelete = afterState.map(el => el.id);
// elements.value = elements.value.filter(el => !idsToDelete.includes(el.id));
// }
// break;
// case 'delete':
// // 删除操作的撤销：恢复被删除的元素 (beforeState即为被删除的元素列表)
// if (Array.isArray(beforeState)) {
// // 批量删除的撤销：恢复所有被删除的元素
// elements.value.push(...deepClone(beforeState));
// } else if (beforeState && elementId) {
// // 单个删除的撤销：恢复单个元素
// elements.value.push(deepClone(beforeState) as CanvasElement);
// }
// break;
// case 'update':
// case 'move':
// case 'resize':
// case 'batch': // 批量更新/移动/缩放
// // 更新/移动/缩放的撤销：恢复元素操作前的状态
// if (Array.isArray(beforeState)) {
// // 批量操作的撤销 (beforeState是包含多个元素的数组)
// beforeState.forEach(b => {
// const target = elements.value.find(el => el.id === b.id);
// if (target) {
// Object.assign(target, b);
// }
// });
// } else if (beforeState && elementId) {
// // 单个操作的撤销
// const target = elements.value.find(el => el.id === elementId);
// if (target) {
// Object.assign(target, beforeState);
// }
// }
// break;
// case 'clear':
// // 清空操作的撤销：恢复所有被清空的元素
// if (Array.isArray(beforeState)) {
// elements.value = deepClone(beforeState);
// }
// break;
// default:
// console.warn(`未知操作类型 "${operation.type}"，无法撤销。`);
// break;
// }
// // 2. 将操作移入重做栈，用于重做
// // 确保重做栈中的操作数据是“撤销前”的状态（即操作原本的“之后”状态）
// historyState.value.redoStack.push(operation);
// // 清除选择状态，防止撤销后操作的元素仍然处于选中状态
// clearSelection();
// saveToLocalStorage();
// return true;
// } catch (e) {
// console.error('执行撤销逻辑时发生错误:', e);
// // 失败后将操作推回 undo 栈（但不恢复记录）
// historyState.value.undoStack.push(operation);
// return false;
// } finally {
// // 3. 恢复记录
// resumeRecording();
// }
// };
// 1.3 重做：从重做栈取出操作，重新执行该操作，将操作移回撤销栈
const redo = (): boolean => {
if (historyState.value.redoStack.length === 0) {
console.warn('重做栈为空，无法重做。')
return false
}
const operation = historyState.value.redoStack.pop() as CanvasOperation
// 4.2 ① 暂停记录
pauseRecording()
try {
console.log(`[redo] ${operation.description} (${operation.type})`)
const { before, after } = operation.data
switch (operation.type) {
case 'add': {
// 新增重做：把 after 里的元素重新 push
const toAdd = Array.isArray(after) ? after : [after]
elements.value.push(...deepClone(toAdd).filter((a): a is CanvasElement => a != null))
break
}
case 'delete': {
// 删除重做：再次删掉 before 里的元素
const idsToDel = (Array.isArray(before) ? before : [before])
.filter((b): b is CanvasElement => b != null)
.map(b => b.id)
elements.value = elements.value.filter(el => !idsToDel.includes(el.id))
break
}
case 'update':
case 'move':
case 'resize':
case 'batch': {
const arr = (Array.isArray(after) ? after : [after])
.filter((a): a is CanvasElement => a != null)
for (const a of arr) {
const target = elements.value.find(el => el.id === a.id)
if (target) Object.assign(target, deepClone(a))
}
break
}
case 'clear': {
// 清空重做：再次清空
elements.value = []
break
}
default:
console.warn(`[redo] 未知类型: ${operation.type}`)
break
}
// 移回撤销栈
historyState.value.undoStack.push(operation)
// 收尾
clearSelection()
saveToLocalStorage()
return true
} catch (e) {
// 4.2 ② 异常捕获 & 回滚
console.error('[redo] 失败:', e)
historyState.value.redoStack.push(operation) // 还回去
return false
} finally {
// 4.2 ① 必恢复记录
resumeRecording()
}
}
// const redo = () => {
// if (historyState.value.redoStack.length === 0) {
// console.warn('重做栈为空，无法重做。');
// return false;
// }
// const operation = historyState.value.redoStack.pop() as CanvasOperation;
// // 1. 暂停记录，防止重做操作本身被记录
// pauseRecording();
// try {
// console.log(`执行重做操作: ${operation.description} (类型: ${operation.type})`);
// // 使用操作后状态 (operation.data.after) 恢复元素状态
// const elementId = operation.data.elementId;
// const beforeState = operation.data.before; // 记录当前状态（操作前的状态），用于撤销
// const afterState = operation.data.after;
// switch (operation.type) {
// case 'add':
// // 新增操作的重做：重新添加元素 (afterState即为新增的元素)
// if (Array.isArray(afterState)) {
// elements.value.push(...deepClone(afterState));
// } else if (afterState) {
// elements.value.push(deepClone(afterState) as CanvasElement);
// }
// break;
// case 'delete':
// // 删除操作的重做：重新删除元素 (beforeState即为被删除的元素列表)
// if (Array.isArray(beforeState)) {
// const idsToDelete = beforeState.map(el => el.id);
// elements.value = elements.value.filter(el => !idsToDelete.includes(el.id));
// } else if (beforeState && elementId) {
// elements.value = elements.value.filter(el => el.id !== elementId);
// }
// break;
// case 'update':
// case 'move':
// case 'resize':
// case 'batch':
// // 更新/移动/缩放的重做：应用元素操作后的状态 (afterState)
// if (Array.isArray(afterState)) {
// // 批量操作的重做
// afterState.forEach(a => {
// const target = elements.value.find(el => el.id === a.id);
// if (target) {
// Object.assign(target, a);
// }
// });
// } else if (afterState && elementId) {
// // 单个操作的重做
// const target = elements.value.find(el => el.id === elementId);
// if (target) {
// Object.assign(target, afterState);
// }
// }
// break;
// case 'clear':
// // 清空操作的重做：清空所有元素
// elements.value = [];
// break;
// default:
// console.warn(`未知操作类型 "${operation.type}"，无法重做。`);
// break;
// }
// // 2. 将操作移回撤销栈
// historyState.value.undoStack.push(operation);
// // 重新保存本地状态
// clearSelection();
// saveToLocalStorage();
// return true;
// } catch (e) {
// console.error('执行重做逻辑时发生错误:', e);
// // 失败后将操作推回 redo 栈（但不恢复记录）
// historyState.value.redoStack.push(operation);
// return false;
// } finally {
// // 3. 恢复记录
// resumeRecording();
// }
// };
// 1.3 clearHistory：清空所有操作记录
const clearHistory = (): void => {
historyState.value.undoStack = [];
historyState.value.redoStack = [];
console.log('历史记录已清空。');
};
// 1.2 recordOperation：将操作记录存入撤销栈，限制栈最大长度，新增操作时清空重做栈
const recordOperation = (operation: CanvasOperation): void => {
if (!historyState.value.isRecording) {
console.warn(`记录已暂停，操作 "${operation.description}" 未被记录。`);
return;
}
// 1. 新增操作时清空重做栈
if (historyState.value.redoStack.length > 0) {
historyState.value.redoStack = [];
console.log(`清空重做栈，当前新操作: ${operation.description}`);
}
// 2. 将新操作存入撤销栈
historyState.value.undoStack.push(operation);
// 3. 限制栈最大长度
const max = historyState.value.maxHistory;
if (historyState.value.undoStack.length > max) {
// 移除最旧的（栈底的）操作
historyState.value.undoStack.shift();
console.log(`撤销栈超出最大限制 (${max})，移除最旧记录。`);
}
console.log(`记录操作成功: ${operation.description} (Undo 栈: ${historyState.value.undoStack.length})`);
};
// 1.2 pauseRecording：暂停操作记录
const pauseRecording = (): void => {
historyState.value.isRecording = false;
console.log('操作记录已暂停。');
};
// 1.2 resumeRecording：恢复操作记录
const resumeRecording = (): void => {
historyState.value.isRecording = true;
console.log('操作记录已恢复。');
};
// 1.2 getHistoryInfo：返回当前可撤销 / 可重做状态（布尔值）
const getHistoryInfo = (): { canUndo: boolean; canRedo: boolean } => {
return {
canUndo: historyState.value.undoStack.length > 0,
canRedo: historyState.value.redoStack.length > 0,
};
};
// 1.2 createOperation：创建标准化操作记录，自动生成唯一 ID、填充时间戳
const createOperation = (
type: CanvasOperation['type'],
description: string,
data: OperationData
): CanvasOperation => {
return {
id: generateId(), // 假设 generateId 已经存在并可用
type,
timestamp: Date.now(),
description,
data: deepClone(data) as OperationData, // 使用深拷贝保证数据的独立性
};
};
//深拷贝
const deepClone = <T>(obj: T): T => {
if (obj === null || typeof obj !== 'object') {
return obj;
}
if (Array.isArray(obj)) {
return obj.map(item => deepClone(item)) as T;
}
const cloned = {} as T;
for (const key in obj) {
if (Object.prototype.hasOwnProperty.call(obj, key)) {
cloned[key] = deepClone(obj[key]);
}
}
return cloned;
};
// 1.1 新增：历史记录状态对象
const historyState = ref<HistoryState>({
undoStack: [],
redoStack: [],
maxHistory: 50, // 默认最大记录条数
isRecording: true // 默认开启记录
});
// 在 useCanvasStore 函数中添加缩放状态
const scaleState = ref<ScaleState>({
isScaling: false,
scaleHandle: '',
elementId: '',
startX: 0,
startY: 0,
elementStartX: 0,
elementStartY: 0,
elementStartWidth: 0,
elementStartHeight: 0,
scaleMultiple: false,
selectedIds: [],
elementStartPositions: {}
});
// 这里写仓库的具体内容
const elements = ref<CanvasElement[]>([]);
const dragState = ref<DragState>({
isDragging: false,
dragElementId: '',
startX: 0,
startY: 0,
elementStartX: 0,
elementStartY: 0,
selectedIds: [] as string[],
elementStartPositions: {} as { [key: string]: { x: number, y: number } }
});
// 新增：视口状态（画布视图）
const viewport = ref({
x: 0, // 画布偏移X
y: 0, // 画布偏移Y
scale: 1, // 缩放比例
isPanning: false, // 是否正在平移
panStart: { x: 0, y: 0 } // 平移起始点
});
// 在现有的状态后添加框选状态
const selectionBox = ref({
isSelecting: false,
startX: 0,
startY: 0,
currentX: 0,
currentY: 0
});
// 元素添加配置：可配置的偏移量和默认位置
const elementAddConfig = ref({
defaultOffset: 10, // 默认偏移量（可配置）
defaultPosition: { x: 100, y: 100 }, // 默认基准位置
maxSameTypeCount: 1000 // 防止计数溢出
});
// 元素添加历史记录：按类型分别记录最后位置和计数
const elementAddHistory = ref<{
[key: string]: {
lastAddedPosition: { x: number, y: number },
sameTypeCount: number,
lastAddedTime: number // 记录最后添加时间，用于错误处理
}
}>({});
// 添加框选方法
const startSelection = (startX: number, startY: number): void => {
// 关键修复：将传入的屏幕坐标转换为世界坐标，确保与元素坐标系统一致
const worldStartX = (startX - viewport.value.x) / viewport.value.scale;
const worldStartY = (startY - viewport.value.y) / viewport.value.scale;
selectionBox.value = {
isSelecting: true,
startX: worldStartX,
startY: worldStartY,
currentX: worldStartX,
currentY: worldStartY
};
};
const updateSelection = (currentX: number, currentY: number): void => {
if (!selectionBox.value.isSelecting) return;
// 关键修复：将传入的屏幕坐标转换为世界坐标
const worldCurrentX = (currentX - viewport.value.x) / viewport.value.scale;
const worldCurrentY = (currentY - viewport.value.y) / viewport.value.scale;
selectionBox.value.currentX = worldCurrentX;
selectionBox.value.currentY = worldCurrentY;
};
const endSelection = (): void => {
if (!selectionBox.value.isSelecting) return;
// 计算选择框的范围
const startX = Math.min(selectionBox.value.startX, selectionBox.value.currentX);
const startY = Math.min(selectionBox.value.startY, selectionBox.value.currentY);
const endX = Math.max(selectionBox.value.startX, selectionBox.value.currentX);
const endY = Math.max(selectionBox.value.startY, selectionBox.value.currentY);
const width = endX - startX;
const height = endY - startY;
// 如果选择框太小，认为是点击而不是框选
if (width < 5 && height < 5) {
selectionBox.value.isSelecting = false;
return;
}
// 查找在选择框内的元素
const selectedIds: string[] = [];
elements.value.forEach(element => {
// 计算元素的边界（考虑视口变换）
const elementLeft = element.x;
const elementTop = element.y;
const elementRight = element.x + element.width;
const elementBottom = element.y + element.height;
// 检查元素是否与选择框相交
const isIntersecting = !(
elementRight < startX ||
elementLeft > endX ||
elementBottom < startY ||
elementTop > endY
);
if (isIntersecting) {
selectedIds.push(element.id);
}
});
// 更新选中状态
if (selectedIds.length > 0) {
// 先取消所有选择
elements.value.forEach(element => {
element.selected = false;
});
// 选中在选择框内的元素
selectedIds.forEach(id => {
const element = elements.value.find(el => el.id === id);
if (element) {
element.selected = true;
}
});
saveToLocalStorage();
}
selectionBox.value.isSelecting = false;
};
// 元素类型识别和验证函数
const validateElementType = (element: CanvasElement): boolean => {
// 验证元素类型是否有效
const validTypes = ['rectangle', 'circle', 'triangle', 'text', 'image'];
if (!validTypes.includes(element.type)) {
console.warn(`无效的元素类型: ${element.type}`);
return false;
}
// 验证元素位置是否有效
if (typeof element.x !== 'number' || typeof element.y !== 'number' ||
isNaN(element.x) || isNaN(element.y)) {
console.warn(`无效的元素位置: x=${element.x}, y=${element.y}`);
return false;
}
return true;
};
// 获取同类型元素最后位置信息
const getLastPositionOfSameType = (elementType: string): { x: number, y: number } | null => {
const history = elementAddHistory.value[elementType];
if (history && history.lastAddedPosition) {
// 检查位置数据是否有效（防止错误数据）
if (typeof history.lastAddedPosition.x === 'number' &&
typeof history.lastAddedPosition.y === 'number' &&
!isNaN(history.lastAddedPosition.x) && !isNaN(history.lastAddedPosition.y)) {
return history.lastAddedPosition;
}
}
return null;
};
// 计算新元素位置（基于绝对定位）
const calculateNewPosition = (elementType: string): { x: number, y: number } => {
const lastPosition = getLastPositionOfSameType(elementType);
if (lastPosition) {
// 存在上一个同类型元素：向右下偏移
const offset = elementAddConfig.value.defaultOffset;
return {
x: lastPosition.x + offset,
y: lastPosition.y + offset
};
} else {
// 首个该类型元素：使用默认基准位置
return {
x: elementAddConfig.value.defaultPosition.x,
y: elementAddConfig.value.defaultPosition.y
};
}
};
// 更新元素添加历史记录
const updateElementHistory = (elementType: string, position: { x: number, y: number }): void => {
if (!elementAddHistory.value[elementType]) {
// 创建新的历史记录
elementAddHistory.value[elementType] = {
lastAddedPosition: position,
sameTypeCount: 1,
lastAddedTime: Date.now()
};
} else {
// 更新现有历史记录
elementAddHistory.value[elementType].lastAddedPosition = position;
elementAddHistory.value[elementType].sameTypeCount++;
elementAddHistory.value[elementType].lastAddedTime = Date.now();
// 防止计数溢出
if (elementAddHistory.value[elementType].sameTypeCount > elementAddConfig.value.maxSameTypeCount) {
elementAddHistory.value[elementType].sameTypeCount = 1;
}
}
};
// 添加元素的方法（完善的类型识别和偏移机制）
const addElement = (element: CanvasElement): void => {
// 预先生成ID，保证操作记录和实际元素 ID 一致
const newElementId = generateId();
element.id = newElementId; // 赋予ID
// ⚡ 关键步骤：在添加到数组之前，先更新选中状态 ⚡
// 确保取消选中所有其他元素
elements.value.forEach(el => el.selected = false);
// 设置新元素为选中状态
element.selected = true;
try {
// 1. 验证元素类型和位置 (保持不变)
if (!validateElementType(element)) {
console.error('元素验证失败，无法添加');
return;
}
// 2. 计算新元素位置 (保持不变)
const newPosition = calculateNewPosition(element.type);
element.x = newPosition.x;
element.y = newPosition.y;
// 3. 记录操作：在元素添加到数组之前
if (historyState.value.isRecording) {
const operation = createOperation(
'add',
`添加了 ${element.type} 元素`,
{
elementId: newElementId,
before: undefined, // 添加操作没有操作前状态
after: deepClone(element), // 记录新增元素的完整状态 (包括已选中的状态)
}
);
recordOperation(operation);
}
// 4. 更新元素添加历史记录 (保持不变)
updateElementHistory(element.type, newPosition);
// 5. 添加元素到数组 (保持不变)
elements.value.push(element);
// 6. 保存到本地存储 (保持不变)
saveToLocalStorage();
console.log(`添加${element.type}元素成功，位置: (${element.x}, ${element.y})`);
resetPasteState(); // 添加新元素后重置粘贴计数
} catch (error) {
console.error('添加元素时发生错误:', error);
// ... 错误处理逻辑保持不变
saveToLocalStorage();
}
};
// const addElement = (element: CanvasElement) => {
// try {
// // 1. 验证元素类型和位置
// if (!validateElementType(element)) {
// console.error('元素验证失败，无法添加');
// return;
// }
// // 2. 计算新元素位置（基于绝对定位）
// const newPosition = calculateNewPosition(element.type, element.x, element.y);
// // 3. 更新元素位置
// element.x = newPosition.x;
// element.y = newPosition.y;
// // 4. 更新元素添加历史记录
// updateElementHistory(element.type, newPosition);
// // 5. 添加元素到数组
// elements.value.push(element);
// // 6. 保存到本地存储
// saveToLocalStorage();
// console.log(`添加${element.type}元素成功，位置: (${element.x}, ${element.y})`);
// } catch (error) {
// console.error('添加元素时发生错误:', error);
// // 错误处理：回退到默认位置
// element.x = elementAddConfig.value.defaultPosition.x;
// element.y = elementAddConfig.value.defaultPosition.y;
// elements.value.push(element);
// saveToLocalStorage();
// }
// };
// 更新元素添加配置的方法
const updateElementAddConfig = (newConfig: Partial<typeof elementAddConfig.value>): void => {
try {
Object.assign(elementAddConfig.value, newConfig);
console.log('元素添加配置已更新:', elementAddConfig.value);
} catch (error) {
console.error('更新元素添加配置时发生错误:', error);
}
};
// 重置元素添加历史记录
const resetElementAddHistory = (elementType?: string): void => {
try {
if (elementType) {
// 重置特定类型的元素历史
delete elementAddHistory.value[elementType];
console.log(`已重置${elementType}类型的元素添加历史`);
} else {
// 重置所有类型的元素历史
elementAddHistory.value = {};
console.log('已重置所有类型的元素添加历史');
}
} catch (error) {
console.error('重置元素添加历史时发生错误:', error);
}
};
// 获取元素添加统计信息
const getElementAddStats = (): { [key: string]: { count: number, lastAdded: number } } => {
const stats: { [key: string]: { count: number, lastAdded: number } } = {};
Object.keys(elementAddHistory.value).forEach(type => {
const history = elementAddHistory.value[type];
if (history) {
stats[type] = {
count: history.sameTypeCount,
lastAdded: history.lastAddedTime
};
}
});
return stats;
};
// 新增：选择单个元素
const selectElement = (id: string): void => {
// 先取消所有元素的选中状态
elements.value.forEach(element => {
element.selected = false;
});
// 选中指定元素
const element = elements.value.find(el => el.id === id);
if (element) {
element.selected = true;
}
saveToLocalStorage();
};
// 新增：取消所有选择
const clearSelection = (): void => {
elements.value.forEach(element => {
element.selected = false;
});
saveToLocalStorage();
};
// 新增：切换元素选择状态（用于多选）
const toggleElementSelection = (id: string): void => {
const element = elements.value.find(el => el.id === id);
if (element) {
element.selected = !element.selected;
}
saveToLocalStorage();
};
// 新增：获取选中的元素
const selectedElements = (): CanvasElement[] => {
return elements.value.filter(element => element.selected);
};
// 新增：开始拖拽
const startDrag = (elementId: string, startX: number, startY: number): void => {
// const element = elements.value.find(el => el.id === elementId);
const selectedIds = selectedElements().map(el => el.id);
// if (element) {
// dragState.value = {
// isDragging: true,
// dragElementId: elementId,
// startX,
// startY,
// elementStartX: element.x,
// elementStartY: element.y
// };
// }
// 如果没有任何元素被选中，就选中当前点击的元素
if (selectedIds.length === 0) {
selectElement(elementId);
selectedIds.push(elementId);
}
// 记录所有选中元素的初始位置
const elementStartPositions: { [key: string]: { x: number, y: number } } = {};
selectedIds.forEach(id => {
const el = elements.value.find(e => e.id === id);
if (el) {
elementStartPositions[id] = { x: el.x, y: el.y };
}
});
// 关键修复：将传入的世界坐标转换为屏幕坐标，确保与updateDrag中的坐标系统一致
const screenStartX = startX * viewport.value.scale + viewport.value.x;
const screenStartY = startY * viewport.value.scale + viewport.value.y;
dragState.value = {
isDragging: true,
dragElementId: elementId, // 仍然记录最初拖动的元素
startX: screenStartX,
startY: screenStartY,
elementStartX: 0, // 不再使用单个元素的位置
elementStartY: 0,
selectedIds, // 新增：记录所有选中的元素ID
elementStartPositions // 新增：记录所有选中元素的初始位置
};
};
// 开始缩放
const startScale = (elementId: string, handle: string, startX: number, startY: number): void => {
const element = elements.value.find(el => el.id === elementId);
if (!element) return;
const selectedElementsList = selectedElements();
const selectedIds = selectedElementsList.map(el => el.id);
// 记录所有选中元素的初始位置和尺寸
const elementStartPositions: { [key: string]: { x: number, y: number, width: number, height: number } } = {};
// 如果有多选且当前元素被选中，则缩放所有选中的元素
if (selectedIds.length > 1 && selectedIds.includes(elementId)) {
selectedIds.forEach(id => {
const el = elements.value.find(e => e.id === id);
if (el) {
elementStartPositions[id] = {
x: el.x,
y: el.y,
width: el.width,
height: el.height
};
}
});
} else {
// 只缩放当前元素
selectedIds.forEach(id => {
if (id === elementId) {
elementStartPositions[id] = {
x: element.x,
y: element.y,
width: element.width,
height: element.height
};
}
});
}
scaleState.value = {
isScaling: true,
scaleHandle: handle,
elementId,
startX,
startY,
elementStartX: element.x,
elementStartY: element.y,
elementStartWidth: element.width,
elementStartHeight: element.height,
scaleMultiple: selectedIds.length > 1,
selectedIds: selectedIds.includes(elementId) ? selectedIds : [elementId],
elementStartPositions
};
};
// 更新缩放
const updateScale = (currentX: number, currentY: number): void => {
if (!scaleState.value.isScaling) return;
// 关键修复：将屏幕坐标差值转换为世界坐标差值，考虑缩放比例
const deltaX = (currentX - scaleState.value.startX) / viewport.value.scale;
const deltaY = (currentY - scaleState.value.startY) / viewport.value.scale;
const handle = scaleState.value.scaleHandle;
// 计算缩放比例（基于初始尺寸）
const minWidth = 10; // 最小宽度
const minHeight = 10; // 最小高度
// 处理每个选中的元素
scaleState.value.selectedIds.forEach(id => {
const element = elements.value.find(el => el.id === id);
const startPos = scaleState.value.elementStartPositions[id];
if (!element || !startPos) return;
let newX = startPos.x;
let newY = startPos.y;
let newWidth = startPos.width;
let newHeight = startPos.height;
// 根据控制柄位置计算新的位置和尺寸
switch (handle) {
case 'nw': // 左上
newX = startPos.x + deltaX;
newY = startPos.y + deltaY;
newWidth = Math.max(minWidth, startPos.width - deltaX);
newHeight = Math.max(minHeight, startPos.height - deltaY);
break;
case 'ne': // 右上
newY = startPos.y + deltaY;
newWidth = Math.max(minWidth, startPos.width + deltaX);
newHeight = Math.max(minHeight, startPos.height - deltaY);
break;
case 'sw': // 左下
newX = startPos.x + deltaX;
newWidth = Math.max(minWidth, startPos.width - deltaX);
newHeight = Math.max(minHeight, startPos.height + deltaY);
break;
case 'se': // 右下
newWidth = Math.max(minWidth, startPos.width + deltaX);
newHeight = Math.max(minHeight, startPos.height + deltaY);
break;
case 'n': // 上
newY = startPos.y + deltaY;
newHeight = Math.max(minHeight, startPos.height - deltaY);
break;
case 's': // 下
newHeight = Math.max(minHeight, startPos.height + deltaY);
break;
case 'e': // 右
newWidth = Math.max(minWidth, startPos.width + deltaX);
break;
case 'w': // 左
newX = startPos.x + deltaX;
newWidth = Math.max(minWidth, startPos.width - deltaX);
break;
}
// 应用新的位置和尺寸
element.x = newX;
element.y = newY;
element.width = newWidth;
element.height = newHeight;
});
};
// 结束缩放
const endScale = (): void => {
if (!scaleState.value.isScaling) return;
if (historyState.value.isRecording) {
// 1. 提取缩放前的元素状态 (在 startScale 中记录)
const selectedIds = scaleState.value.selectedIds;
const beforeState = selectedIds.map(id => {
const startPos = scaleState.value.elementStartPositions[id];
if (startPos) {
return {
id: id,
x: startPos.x,
y: startPos.y,
width: startPos.width,
height: startPos.height,
};
}
return undefined;
}).filter((x): x is { id: string, x: number, y: number, width: number, height: number } => x !== undefined);
// 2. 提取缩放后的元素状态
const afterState = selectedIds.map(id => {
const el = elements.value.find(e => e.id === id);
return el ? { id: id, x: el.x, y: el.y, width: el.width, height: el.height } : undefined;
}).filter((x): x is { id: string, x: number, y: number, width: number, height: number } => x !== undefined);
// 3. 记录操作
const operation = createOperation(
'resize',
`缩放了 ${selectedIds.length} 个元素`,
{
before: beforeState,
after: afterState
}
);
recordOperation(operation);
}
scaleState.value.isScaling = false;
saveToLocalStorage();
resetPasteState(); // 缩放结束时重置粘贴计数
};
// const endScale = () => {
// if (scaleState.value.isScaling) {
// scaleState.value.isScaling = false;
// saveToLocalStorage();
// }
// };
// 按比例缩放选中元素
const scaleSelectedElements = (scaleFactor: number): void => {
const selected = selectedElements();
if (selected.length === 0) return;
const minSize = 10; // 最小尺寸限制
selected.forEach(element => {
const newWidth = Math.max(minSize, element.width * scaleFactor);
const newHeight = Math.max(minSize, element.height * scaleFactor);
updateElement(element.id, {
width: newWidth,
height: newHeight
});
});
};
// 新增：更新拖拽位置
const updateDrag = (currentX: number, currentY: number): void => {
if (!dragState.value.isDragging) return;
// 关键优化：将屏幕坐标差值转换为世界坐标差值，考虑缩放比例
const deltaX = (currentX - dragState.value.startX) / viewport.value.scale;
const deltaY = (currentY - dragState.value.startY) / viewport.value.scale;
// 移动所有选中的元素
dragState.value.selectedIds.forEach(id => {
const element = elements.value.find(el => el.id === id);
const startPos = dragState.value.elementStartPositions[id];
if (element && startPos) {
element.x = startPos.x + deltaX;
element.y = startPos.y + deltaY;
}
});
};
// 结束拖拽
const endDrag = (): void => {
if (!dragState.value.isDragging) return;
if (historyState.value.isRecording) {
// 1. 提取拖拽前的元素状态 (在 startDrag 中记录)
const selectedIds = dragState.value.selectedIds;
const beforeState = selectedIds.map(id => {
const startPos = dragState.value.elementStartPositions[id];
if (startPos) {
return {
id: id,
x: startPos.x,
y: startPos.y,
};
}
return undefined;
}).filter((x): x is { id: string, x: number, y: number } => x !== undefined);
// 2. 提取拖拽后的元素状态
const afterState = selectedIds.map(id => {
const el = elements.value.find(e => e.id === id);
return el ? { id: id, x: el.x, y: el.y } : undefined;
}).filter((x): x is { id: string, x: number, y: number } => x !== undefined);
// 3. 记录操作
const operation = createOperation(
'move',
`移动了 ${selectedIds.length} 个元素`,
{
before: beforeState,
after: afterState
}
);
recordOperation(operation);
}
dragState.value.isDragging = false;
saveToLocalStorage(); // 拖拽结束时保存
resetPasteState(); // 拖拽结束时重置粘贴计数
};
// const endDrag = () => {
// if (dragState.value.isDragging) {
// dragState.value.isDragging = false;
// saveToLocalStorage(); // 拖拽结束时保存
// }
// };
// 新增：画布平移方法
const startPan = (startX: number, startY: number): void => {
viewport.value.isPanning = true;
viewport.value.panStart = { x: startX, y: startY };
};
const updatePan = (currentX: number, currentY: number): void => {
if (!viewport.value.isPanning) return;
const deltaX = currentX - viewport.value.panStart.x;
const deltaY = currentY - viewport.value.panStart.y;
viewport.value.x += deltaX;
viewport.value.y += deltaY;
viewport.value.panStart = { x: currentX, y: currentY };
};
const endPan = (): void => {
viewport.value.isPanning = false;
};
// 新增：画布缩放方法
const zoom = (delta: number, centerX?: number, centerY?: number): void => {
const zoomFactor = delta > 0 ? 1.1 : 0.9; // 滚轮向上放大，向下缩小
const oldScale = viewport.value.scale;
const newScale = Math.max(0.1, Math.min(5, viewport.value.scale * zoomFactor));
// 限制缩放范围
// 如果有中心点，基于中心点缩放
if (centerX !== undefined && centerY !== undefined) {
const worldX = (centerX - viewport.value.x) / oldScale;
const worldY = (centerY - viewport.value.y) / oldScale;
viewport.value.x = centerX - worldX * newScale;
viewport.value.y = centerY - worldY * newScale;
}
viewport.value.scale = newScale;
};
// 新增：重置视图
const resetViewport = (): void => {
viewport.value = {
x: 0,
y: 0,
scale: 1,
isPanning: false,
panStart: { x: 0, y: 0 }
};
};
// 持久化
const saveToLocalStorage = (): void => {
const state = {
elements: elements.value,
viewport: {
x: viewport.value.x,
y: viewport.value.y,
scale: viewport.value.scale
}
};
localStorage.setItem('canvas-state', JSON.stringify(state));
};
const loadFromLocalStorage = (): void => {
const saved = localStorage.getItem('canvas-state');
if (saved) {
const state = JSON.parse(saved);
elements.value = state.elements || [];
if (state.viewport) {
viewport.value.x = state.viewport.x || 0;
viewport.value.y = state.viewport.y || 0;
viewport.value.scale = state.viewport.scale || 1;
}
}
};
// 更新元素 (Update Element)
const updateElement = (id: string, updates: Partial<CanvasElement>): void => {
const element = elements.value.find(el => el.id === id);
if (!element) return;
if (historyState.value.isRecording) {
// 1. 记录元素更新前的完整状态
const beforeState = deepClone(element);
// 2. 执行更新
Object.assign(element, updates);
// 3. 记录元素更新后的完整状态
const afterState = deepClone(element);
// 4. 将操作记录存入撤销栈
const operation = createOperation(
'update',
`更新了元素 ${id} 的属性`,
{
elementId: id,
before: beforeState,
after: afterState
}
);
recordOperation(operation);
} else {
// 如果记录暂停，则直接更新
Object.assign(element, updates);
}
saveToLocalStorage();
// 如果修改了位置或尺寸，则重置粘贴计数
if (updates.x !== undefined || updates.y !== undefined || updates.width !== undefined || updates.height !== undefined) {
resetPasteState();
}
};
// const updateElement = (id: string, updates: Partial<CanvasElement>) => {
// const element = elements.value.find(el => el.id === id);
// if (element) {
// Object.assign(element, updates);
// saveToLocalStorage();
// }
// };
// 新增：剪贴板状态
const clipboard = ref<CanvasElement[]>([]);
// 新增：粘贴状态（用于连续粘贴的偏移量控制）
const pasteState = ref({
pasteCount: 0, // 粘贴次数
lastPastePosition: { x: 0, y: 0 }, // 最后一次粘贴的位置
originalBoundingBox: { minX: 0, minY: 0, maxX: 0, maxY: 0, centerX: 0, centerY: 0 } // 原始包围盒
});
// 新增：复制选中的元素到剪贴板
const copySelectedElements = (): boolean => {
const selected = selectedElements();
if (selected.length === 0) {
console.warn('没有选中的元素可以复制');
return false;
}
// 检查是否复制了相同的元素（防止重复复制相同内容）
const selectedIds = selected.map(el => el.id).sort().join(',');
const lastCopiedIds = clipboard.value.map(el => el.id).sort().join(',');
if (selectedIds === lastCopiedIds) {
console.log('复制了相同的元素，剪贴板内容保持不变');
return true; // 仍然返回成功，但内容不变
}
try {
// 深拷贝选中的元素，并清除选中状态
clipboard.value = selected.map(element => ({
...JSON.parse(JSON.stringify(element)),
selected: false,
id: generateId() // 为复制的元素生成新的ID
}));
// 记录原始包围盒信息，用于连续粘贴
pasteState.value.originalBoundingBox = calculateBoundingBox(selected);
pasteState.value.pasteCount = 0; // 重置粘贴计数
// 保存剪贴板状态到本地存储
saveClipboardToLocalStorage();
console.log(`复制了 ${selected.length} 个元素到剪贴板`);
console.log(`原始包围盒: (${pasteState.value.originalBoundingBox.minX}, ${pasteState.value.originalBoundingBox.minY}) - (${pasteState.value.originalBoundingBox.maxX}, ${pasteState.value.originalBoundingBox.maxY})`);
return true;
} catch (error) {
console.error('复制元素时发生错误:', error);
return false;
}
};
// 新增：计算元素组的包围盒（最小矩形边界）
const calculateBoundingBox = (elements: CanvasElement[]): { minX: number, minY: number, maxX: number, maxY: number, width: number, height: number, centerX: number, centerY: number } => {
if (elements.length === 0) {
return { minX: 0, minY: 0, maxX: 0, maxY: 0, width: 0, height: 0, centerX: 0, centerY: 0 };
}
let minX = Infinity;
let minY = Infinity;
let maxX = -Infinity;
let maxY = -Infinity;
elements.forEach(element => {
minX = Math.min(minX, element.x);
minY = Math.min(minY, element.y);
maxX = Math.max(maxX, element.x + element.width);
maxY = Math.max(maxY, element.y + element.height);
});
const width = maxX - minX;
const height = maxY - minY;
const centerX = minX + width / 2;
const centerY = minY + height / 2;
return { minX, minY, maxX, maxY, width, height, centerX, centerY };
};
// 新增：计算视口中心的世界坐标
const getViewportCenter = (): { x: number, y: number } => {
// 假设画布大小为 800x600，可以根据实际情况调整
const canvasWidth = 800;
const canvasHeight = 600;
// 计算视口中心的世界坐标
const viewportCenterX = (-viewport.value.x + canvasWidth / 2) / viewport.value.scale;
const viewportCenterY = (-viewport.value.y + canvasHeight / 2) / viewport.value.scale;
return { x: viewportCenterX, y: viewportCenterY };
};
// 新增：检查元素是否在画布边界内
const isElementInCanvasBounds = (element: CanvasElement): boolean => {
// 定义画布边界（可以根据实际需求调整）
const canvasBounds = {
minX: -1000,
minY: -1000,
maxX: 2000,
maxY: 2000
};
return element.x >= canvasBounds.minX &&
element.y >= canvasBounds.minY &&
element.x + element.width <= canvasBounds.maxX &&
element.y + element.height <= canvasBounds.maxY;
};
// 新增：粘贴剪贴板中的元素到画布，保持相对位置关系
// 粘贴剪贴板中的元素到画布，保持相对位置关系
const pasteElements = (offsetX: number = 10, offsetY: number = 10): boolean => {
if (clipboard.value.length === 0) {
console.warn('剪贴板为空，无法粘贴');
return false;
}
// 检查剪贴板数据是否有效
if (!Array.isArray(clipboard.value) || clipboard.value.some(el => !el || !el.type)) {
console.error('剪贴板数据无效，无法粘贴');
clipboard.value = [];
saveClipboardToLocalStorage();
return false;
}
try {
// 计算剪贴板中元素的包围盒
const clipboardBoundingBox = calculateBoundingBox(clipboard.value);
// 计算粘贴位置（基于当前选中元素或视口中心）
const selectedElementsList = selectedElements();
let targetX = 0;
let targetY = 0;
let pasteStrategy = '';
if (selectedElementsList.length > 0) {
// 策略1：如果有选中的元素，基于选中元素的包围盒中心粘贴
const selectedBoundingBox = calculateBoundingBox(selectedElementsList);
targetX = selectedBoundingBox.centerX;
targetY = selectedBoundingBox.centerY;
pasteStrategy = '基于选中元素中心';
} else {
// 策略2：如果没有选中的元素，基于视口中心粘贴
const viewportCenter = getViewportCenter();
targetX = viewportCenter.x;
targetY = viewportCenter.y;
pasteStrategy = '基于视口中心';
}
// 固定偏移量机制：每次粘贴都向右下偏移10px
const fixedOffsetX = offsetX;
const fixedOffsetY = offsetY;
// 应用固定偏移量
targetX += fixedOffsetX;
targetY += fixedOffsetY;
const newElements: CanvasElement[] = [];
let outOfBoundsCount = 0;
// 粘贴所有剪贴板中的元素，保持相对位置关系
clipboard.value.forEach(element => {
// 计算元素相对于包围盒中心的偏移量
const elementRelativeX = element.x - clipboardBoundingBox.centerX;
const elementRelativeY = element.y - clipboardBoundingBox.centerY;
// 应用相同的偏移量到目标位置
const newX = targetX + elementRelativeX;
const newY = targetY + elementRelativeY;
// 注意：这里需要确保 newElement 是一个深拷贝，避免对 clipboard.value 的引用污染
const newElement: CanvasElement = {
...deepClone(element), // 确保是深拷贝
x: newX,
y: newY,
id: generateId() // 为每个粘贴的元素生成新的ID
};
// 验证元素数据完整性
if (!newElement.type || !newElement.id) {
console.warn('跳过无效的剪贴板元素');
return;
}
// 检查元素是否在画布边界内
if (!isElementInCanvasBounds(newElement)) {
console.warn(`元素 ${newElement.id} 超出画布边界，已调整位置`);
outOfBoundsCount++;
// 可以在这里添加边界调整逻辑
}
newElements.push(newElement);
});
if (newElements.length === 0) {
console.warn('没有有效的元素可以粘贴');
return false;
}
// 1. **执行操作：批量添加新元素**
elements.value.push(...newElements);
// 2. 清除所有选中状态，然后选中刚刚粘贴的元素
clearSelection();
newElements.forEach(element => {
element.selected = true;
});
// 3. **记录操作**
if (historyState.value.isRecording) {
const operation = createOperation(
'add', // 使用 'add' 类型，因为其撤销逻辑是删除元素
`粘贴了 ${newElements.length} 个元素`,
{
before: undefined,
after: newElements.map(el => deepClone(el)), // 记录粘贴后所有元素的完整状态
}
);
recordOperation(operation);
}
// 4. 更新粘贴状态
pasteState.value.pasteCount = pasteState.value.pasteCount + 1;
pasteState.value.lastPastePosition = { x: targetX, y: targetY };
saveToLocalStorage();
// 详细的日志输出，便于调试
const newBoundingBox = calculateBoundingBox(newElements);
console.log(`粘贴了 ${newElements.length} 个元素，保持相对位置关系`);
console.log(`粘贴策略: ${pasteStrategy}`);
console.log(`粘贴次数: ${pasteState.value.pasteCount}`);
console.log(`固定偏移量: (${fixedOffsetX}, ${fixedOffsetY})`);
console.log(`原始包围盒: (${clipboardBoundingBox.minX}, ${clipboardBoundingBox.minY}) - (${clipboardBoundingBox.maxX}, ${clipboardBoundingBox.maxY})`);
console.log(`目标位置: (${targetX}, ${targetY})`);
console.log(`新包围盒: (${newBoundingBox.minX}, ${newBoundingBox.minY}) - (${newBoundingBox.maxX}, ${newBoundingBox.maxY})`);
if (outOfBoundsCount > 0) {
console.warn(`${outOfBoundsCount} 个元素超出画布边界`);
}
return true;
} catch (error) {
console.error('粘贴元素时发生错误:', error);
return false;
}
};
// const pasteElements = (offsetX: number = 10, offsetY: number = 10) => {
// if (clipboard.value.length === 0) {
// console.warn('剪贴板为空，无法粘贴');
// return false;
// }
// // 检查剪贴板数据是否有效
// if (!Array.isArray(clipboard.value) || clipboard.value.some(el => !el || !el.type)) {
// console.error('剪贴板数据无效，无法粘贴');
// clipboard.value = [];
// saveClipboardToLocalStorage();
// return false;
// }
// try {
// // 计算剪贴板中元素的包围盒
// const clipboardBoundingBox = calculateBoundingBox(clipboard.value);
// // 计算粘贴位置（基于当前选中元素或视口中心）
// const selectedElementsList = selectedElements();
// let targetX = 0;
// let targetY = 0;
// let pasteStrategy = '';
// if (selectedElementsList.length > 0) {
// // 策略1：如果有选中的元素，基于选中元素的包围盒中心粘贴
// const selectedBoundingBox = calculateBoundingBox(selectedElementsList);
// targetX = selectedBoundingBox.centerX;
// targetY = selectedBoundingBox.centerY;
// pasteStrategy = '基于选中元素中心';
// } else {
// // 策略2：如果没有选中的元素，基于视口中心粘贴
// const viewportCenter = getViewportCenter();
// targetX = viewportCenter.x;
// targetY = viewportCenter.y;
// pasteStrategy = '基于视口中心';
// }
// // 连续粘贴的偏移量累加机制
// const pasteCount = pasteState.value.pasteCount;
// const cumulativeOffsetX = offsetX * (pasteCount + 1);
// const cumulativeOffsetY = offsetY * (pasteCount + 1);
// // 应用累加的偏移量
// targetX += cumulativeOffsetX;
// targetY += cumulativeOffsetY;
// const newElements: CanvasElement[] = [];
// let outOfBoundsCount = 0;
// // 粘贴所有剪贴板中的元素，保持相对位置关系
// clipboard.value.forEach(element => {
// // 计算元素相对于包围盒中心的偏移量
// const elementRelativeX = element.x - clipboardBoundingBox.centerX;
// const elementRelativeY = element.y - clipboardBoundingBox.centerY;
// // 应用相同的偏移量到目标位置
// const newX = targetX + elementRelativeX;
// const newY = targetY + elementRelativeY;
// const newElement = {
// ...JSON.parse(JSON.stringify(element)),
// x: newX,
// y: newY,
// id: generateId() // 为每个粘贴的元素生成新的ID
// };
// // 验证元素数据完整性
// if (!newElement.type || !newElement.id) {
// console.warn('跳过无效的剪贴板元素');
// return;
// }
// // 检查元素是否在画布边界内
// if (!isElementInCanvasBounds(newElement)) {
// console.warn(`元素 ${newElement.id} 超出画布边界，已调整位置`);
// outOfBoundsCount++;
// // 可以在这里添加边界调整逻辑
// }
// newElements.push(newElement);
// });
// if (newElements.length === 0) {
// console.warn('没有有效的元素可以粘贴');
// return false;
// }
// // 批量添加新元素
// elements.value.push(...newElements);
// // 清除所有选中状态，然后选中刚刚粘贴的元素
// clearSelection();
// newElements.forEach(element => {
// element.selected = true;
// });
// // 更新粘贴状态
// pasteState.value.pasteCount = pasteCount + 1;
// pasteState.value.lastPastePosition = { x: targetX, y: targetY };
// saveToLocalStorage();
// // 详细的日志输出，便于调试
// const newBoundingBox = calculateBoundingBox(newElements);
// console.log(`粘贴了 ${newElements.length} 个元素，保持相对位置关系`);
// console.log(`粘贴策略: ${pasteStrategy}`);
// console.log(`粘贴次数: ${pasteState.value.pasteCount}`);
// console.log(`默认偏移量: (${offsetX}, ${offsetY})`);
// console.log(`累加偏移量: (${cumulativeOffsetX}, ${cumulativeOffsetY})`);
// console.log(`原始包围盒: (${clipboardBoundingBox.minX}, ${clipboardBoundingBox.minY}) - (${clipboardBoundingBox.maxX}, ${clipboardBoundingBox.maxY})`);
// console.log(`目标位置: (${targetX}, ${targetY})`);
// console.log(`新包围盒: (${newBoundingBox.minX}, ${newBoundingBox.minY}) - (${newBoundingBox.maxX}, ${newBoundingBox.maxY})`);
// if (outOfBoundsCount > 0) {
// console.warn(`${outOfBoundsCount} 个元素超出画布边界`);
// }
// return true;
// } catch (error) {
// console.error('粘贴元素时发生错误:', error);
// return false;
// }
// };
// 新增：保存剪贴板状态到本地存储
const saveClipboardToLocalStorage = (): void => {
localStorage.setItem('canvas-clipboard', JSON.stringify(clipboard.value));
};
// 新增：从本地存储加载剪贴板状态
const loadClipboardFromLocalStorage = (): void => {
const saved = localStorage.getItem('canvas-clipboard');
if (saved) {
try {
clipboard.value = JSON.parse(saved);
} catch (error) {
console.error('加载剪贴板数据失败:', error);
clipboard.value = [];
}
}
};
// 新增：生成唯一ID的辅助函数
const generateId = (): string => 'element_' + Date.now() + '_' + Math.random().toString(36).substr(2, 9);
const resetPasteState = (): void => {
if (pasteState.value.pasteCount > 0) {
pasteState.value.pasteCount = 0;
console.log('元素被修改或移动，粘贴计数已重置。');
}
};
// 在现有的方法后面添加删除方法
// 删除选中的元素
const deleteSelectedElements = (): void => {
const selected = selectedElements();
if (selected.length === 0) {
return;
}
// 1. 记录操作前被删除元素的完整状态 (深拷贝)
// 在执行删除操作之前获取快照，是正确的。
let operation: CanvasOperation | null = null;
if (historyState.value.isRecording) {
operation = createOperation(
'delete',
`删除了 ${selected.length} 个元素`,
{
// 记录被删除元素的快照，用于撤销
before: selected.map(el => deepClone(el)),
after: undefined // 删除操作的 'after' 状态是 undefined/null
}
);
}
// 2. 执行删除操作 (无论是否记录历史，都要执行)
const selectedIds = selected.map(el => el.id);
elements.value = elements.value.filter(element => !selectedIds.includes(element.id));
// 3. 将操作记录存入撤销栈 (如果操作已创建)
if (operation) { // 检查 operation 是否在第 1 步被创建
recordOperation(operation);
}
// ⚠️ 注意：您原来的代码中有一个 else 块，这导致如果 isRecording=false，
// elements.value 会被修改，但不会保存到本地。
// 4. 执行其他收尾工作 (始终执行)
saveToLocalStorage();
resetPasteState();
};
// const deleteSelectedElements = () => {
// // 获取所有选中的元素ID
// const selectedIds = selectedElements().map(el => el.id);
// // 过滤掉选中的元素
// elements.value = elements.value.filter(element => !selectedIds.includes(element.id));
// saveToLocalStorage();
// };
// 新增：将选中元素提升到最前面
const bringToFront = (): boolean => {
const selected = selectedElements();
if (selected.length === 0) {
console.warn('没有选中的元素可以提升层级');
return false;
}
// 获取当前最大的zIndex值
const maxZIndex = Math.max(...elements.value.map(el => el.zIndex || 0));
// 为每个选中的元素设置新的zIndex值（比当前最大值大1）
selected.forEach(element => {
element.zIndex = maxZIndex + 1;
});
saveToLocalStorage();
console.log(`已将 ${selected.length} 个元素提升到最前面，新zIndex: ${maxZIndex + 1}`);
return true;
};
// 在 canvas.ts 中添加自动扩展机制
const AUTO_EXPAND_AMOUNT = 1000; // 每次扩展1000像素
const checkAndExpandViewport = () => {
// 获取当前所有元素的边界
const bounds = getElementsBounds();
const canvasSize = getCanvasSize();
// 计算当前视口在世界坐标中的位置
const worldViewport = getViewportWorldRect();
// 检查是否需要扩展各个方向
if (worldViewport.x + worldViewport.width > bounds.maxX - 500) {
// 向右扩展
expandBounds('right', AUTO_EXPAND_AMOUNT);
}
if (worldViewport.y + worldViewport.height > bounds.maxY - 500) {
// 向下扩展
expandBounds('down', AUTO_EXPAND_AMOUNT);
}
if (worldViewport.x < bounds.minX + 500) {
// 向左扩展
expandBounds('left', AUTO_EXPAND_AMOUNT);
}
if (worldViewport.y < bounds.minY + 500) {
// 向上扩展
expandBounds('up', AUTO_EXPAND_AMOUNT);
}
};
const expandBounds = (direction: 'left' | 'right' | 'up' | 'down', amount: number) => {
const bounds = canvasStore.viewport.bounds;
switch (direction) {
case 'left':
bounds.minX -= amount;
bounds.width += amount;
break;
case 'right':
bounds.maxX += amount;
bounds.width += amount;
break;
case 'up':
bounds.minY -= amount;
bounds.height += amount;
break;
case 'down':
bounds.maxY += amount;
bounds.height += amount;
break;
}
// 更新所有相关元素
updateScrollbars();
};
// 新增：屏幕坐标转换为世界坐标
const screenToWorld = (screenX: number, screenY: number): { x: number, y: number } => {
// 考虑视口偏移和缩放
const worldX = (screenX - viewport.value.x) / viewport.value.scale;
const worldY = (screenY - viewport.value.y) / viewport.value.scale;
return { x: worldX, y: worldY };
};
return {
elements,
dragState,
scaleState, // 新增：缩放状态
viewport, // 新增
selectionBox, // 新增
clipboard, // 新增：剪贴板状态
elementAddConfig, // 新增：元素添加配置
elementAddHistory, // 新增：元素添加历史记录
historyState, // 💡 新增：历史记录状态对象
undo,
redo,
resetPasteState,
clearHistory,
// 💡 新增：操作记录核心方法
createOperation,
recordOperation,
pauseRecording,
resumeRecording,
getHistoryInfo,
deepClone, // 💡 新增：深拷贝辅助函数
addElement,
selectElement,
clearSelection,
toggleElementSelection,
selectedElements,
startDrag,
updateDrag,
endDrag,
// 新增的缩放方法
startScale,
updateScale,
endScale,
scaleSelectedElements, // 按比例缩放选中元素
startPan, // 新增
updatePan, // 新增
endPan, // 新增
zoom, // 新增
resetViewport, // 新增
updateElement, // 确保有这个
deleteSelectedElements, // 新增
startSelection, // 新增
updateSelection, // 新增
endSelection, // 新增
copySelectedElements, // 新增：复制方法
pasteElements, // 新增：粘贴方法
bringToFront, // 新增：层级提升方法
updateElementAddConfig, // 新增：更新元素添加配置
resetElementAddHistory, // 新增：重置元素添加历史记录
getElementAddStats, // 新增：获取元素添加统计信息
loadFromLocalStorage,
loadClipboardFromLocalStorage, // 新增：加载剪贴板数据
screenToWorld, // 新增：屏幕坐标转世界坐标
canUndo: computed(() => historyState.value.undoStack.length > 0),
canRedo: computed(() => historyState.value.redoStack.length > 0),
};
});
|
2301_80689990/canvas-editor
|
src/stores/canvas.ts
|
TypeScript
|
unknown
| 65,325
|
:root {
font-family: system-ui, Avenir, Helvetica, Arial, sans-serif;
line-height: 1.5;
font-weight: 400;
color-scheme: light dark;
color: rgba(255, 255, 255, 0.87);
background-color: #242424;
font-synthesis: none;
text-rendering: optimizeLegibility;
-webkit-font-smoothing: antialiased;
-moz-osx-font-smoothing: grayscale;
}
a {
font-weight: 500;
color: #646cff;
text-decoration: inherit;
}
a:hover {
color: #535bf2;
}
body {
margin: 0;
display: flex;
place-items: center;
min-width: 320px;
min-height: 100vh;
}
h1 {
font-size: 3.2em;
line-height: 1.1;
}
button {
border-radius: 8px;
border: 1px solid transparent;
padding: 0.6em 1.2em;
font-size: 1em;
font-weight: 500;
font-family: inherit;
background-color: #1a1a1a;
cursor: pointer;
transition: border-color 0.25s;
}
button:hover {
border-color: #646cff;
}
button:focus,
button:focus-visible {
outline: 4px auto -webkit-focus-ring-color;
}
.card {
padding: 2em;
}
#app {
max-width: 1280px;
margin: 0 auto;
padding: 0;
text-align: center;
}
@media (prefers-color-scheme: light) {
:root {
color: #213547;
background-color: #ffffff;
}
a:hover {
color: #747bff;
}
button {
background-color: #f9f9f9;
}
}
|
2301_80689990/canvas-editor
|
src/style.css
|
CSS
|
unknown
| 1,270
|
// 定义基础接口
export interface BaseElement {
id: string; // 唯一标识
type: string; // 元素类型
x: number; // x坐标
y: number; // y坐标
width: number; // 宽度
height: number; // 高度
selected: boolean; // 选中状态
zIndex: number; // 层级控制属性
}
// 定义矩形特有接口（继承基础接口）
export interface RectangleElement extends BaseElement {
type: 'rectangle';
background: string;
borderWidth: number;
borderColor: string;
}
// 圆形元素接口
export interface CircleElement extends BaseElement {
type: 'circle';
background: string;
borderWidth: number;
borderColor: string;
}
// 三角形元素接口
export interface TriangleElement extends BaseElement {
type: 'triangle';
background: string;
borderWidth: number;
borderColor: string;
}
// ✨✨ 文本元素接口 (确认 strikethrough 存在) ✨✨
export interface TextElement extends BaseElement {
type: 'text';
content: string;
fontSize: number;
fontFamily: string;
color: string;
background: string;
bold: boolean;
italic: boolean;
underline: boolean;
strikethrough: boolean; // 👈 必须有这个
textAlign: 'left' | 'center' | 'right';
}
// 图片元素接口
export interface ImageElement extends BaseElement {
type: 'image';
src: string;
originalWidth: number;
originalHeight: number;
initialWidth: number; // 上传到画布时的初始宽度
initialHeight: number; // 上传到画布时的初始高度
filter?: string;
opacity: number;
borderWidth: number;
borderColor: string;
}
export interface SelectionBoxState {
isSelecting: boolean;
startX: number;
startY: number;
currentX: number;
currentY: number;
}
// 更新联合类型
export type CanvasElement = RectangleElement | CircleElement | TriangleElement | TextElement | ImageElement;
|
2301_80689990/canvas-editor
|
src/types/canvas.ts
|
TypeScript
|
unknown
| 1,856
|
import { defineConfig } from 'vite'
import vue from '@vitejs/plugin-vue'
import { resolve } from 'path'
// https://vite.dev/config/
export default defineConfig({
plugins: [vue()],
resolve: {
alias: {
'@': resolve(__dirname, 'src')
}
}
})
|
2301_80689990/canvas-editor
|
vite.config.ts
|
TypeScript
|
unknown
| 259
|
#!/bin/bash
# 定义下载地址和文件名
DOWNLOAD_URL="https://cangjie-lang.cn/v1/files/auth/downLoad?nsId=142267&fileName=Cangjie-0.53.13-linux_x64.tar.gz&objectKey=6719f1eb3af6947e3c6af327"
FILE_NAME="Cangjie-0.53.13-linux_x64.tar.gz"
# 检查 cangjie 工具链是否已安装
echo "确保 cangjie 工具链已安装..."
if ! command -v cjc -v &> /dev/null
then
echo "cangjie工具链 未安装，尝试进行安装..."
# 下载文件
echo "Downloading Cangjie compiler..."
curl -L -o "$FILE_NAME" "$DOWNLOAD_URL"
# 检查下载是否成功
if [ $? -eq 0 ]; then
echo "Download completed successfully."
else
echo "Download failed."
exit 1
fi
# 解压文件
echo "Extracting $FILE_NAME..."
tar -xvf "$FILE_NAME"
# 检查解压是否成功
if [ $? -eq 0 ]; then
echo "Extraction completed successfully."
else
echo "Extraction failed."
exit 1
fi
# 检查 envsetup.sh 是否存在并进行 source
if [[ -f "cangjie/envsetup.sh" ]]; then
echo "envsetup.sh found!"
source cangjie/envsetup.sh
else
echo "envsetup.sh not found!"
exit 1
fi
fi
# 检查 openEuler 防火墙状态
echo "检查 openEuler 防火墙状态..."
if systemctl status firewalld | grep "active (running)" &> /dev/null; then
echo "防火墙已开启，尝试开放 21 端口..."
firewall-cmd --zone=public --add-port=21/tcp --permanent
firewall-cmd --reload
echo "21 端口已开放。"
else
echo "防火墙未开启，无需开放端口。"
fi
# 编译ftp_server
echo "正在编译 ftp_server..."
cjpm build
# 检查编译是否成功
if [ $? -eq 0 ]; then
echo "编译成功."
else
echo "编译失败."
exit 1
fi
# 运行 ftp_server
echo "正在启动 ftp 服务器..."
cjpm run
|
2301_80220344/Cangjie-Examples
|
FTP/run-ftp.sh
|
Shell
|
apache-2.0
| 1,967
|
<!DOCTYPE html>
<html lang="cn">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Document</title>
</head>
<body>
<div>Hello Cangjie!</div>
<p></p>
<script>
let xhr = new XMLHttpRequest()
xhr.open("POST", "/Hello", true)
xhr.onreadystatechange = () => {
if(xhr.readyState == 4 && xhr.status == 200){
let res = JSON.parse(xhr.responseText)
document.body.innerHTML += `<div>${res.msg}</div>`
}
}
xhr.send(JSON.stringify({
name: "Chen",
age: 999
}))
</script>
</body>
</html>
|
2301_80220344/Cangjie-Examples
|
HTTPServer/index.html
|
HTML
|
apache-2.0
| 687
|
{"cells":[{"cell_type":"markdown","metadata":{"id":"AB155B13302D459CBAAABA327849B76D","jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"# 说明\n特征工程部分照搬社区的baseline未作改动，仅仅进行了模型的部分参数调整和基于stacking的模型融合。\n另外，由于是输出概率，后续按照回归去做，故删除了不平衡样本的处理，一开始当成分类去做，最高只能到0.8+，按照回归轻松0.9+\n参数仅做了简单的调整，非最优，线下0.9361018703876826，线上验证0.93536922"},{"cell_type":"markdown","metadata":{"id":"C325760DBE164B398588C602C8C376BC","jupyter":{},"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"source":"# 查看数据"},{"cell_type":"code","execution_count":1,"metadata":{"collapsed":false,"id":"0A028E17E34B4CFEABE9DFF956D89741","jupyter":{},"scrolled":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"outputs":[],"source":"import pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns\n\nplt.rcParams['font.sans-serif'] = ['SimHei']\nplt.rcParams['axes.unicode_minus'] = False"},{"cell_type":"code","execution_count":2,"metadata":{"collapsed":false,"id":"001F87A7D41644E4BA2EA25513B0D1B3","jupyter":{},"scrolled":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"outputs":[],"source":"train=pd.read_csv(r'/home/mw/input/data9803/train_set.csv')\ntest=pd.read_csv('/home/mw/input/data9803/test_set.csv')"},{"cell_type":"code","execution_count":3,"metadata":{"collapsed":false,"id":"B8C543716B964973872549E7B4DFDFAA","jupyter":{},"scrolled":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"outputs":[],"source":"data = pd.concat([train.drop(['y'],axis=1),test],axis=0).reset_index(drop=True)"},{"cell_type":"code","execution_count":4,"metadata":{"id":"D7CE94A95A2544AE808C26A4B1901BA7","jupyter":{},"scrolled":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true,"collapsed":false},"outputs":[{"output_type":"stream","text":"job : ['management' 'technician' 'admin.' 'services' 'retired' 'student'\n 'blue-collar' 'unknown' 'entrepreneur' 'housemaid' 'self-employed'\n 'unemployed']\nmarital : ['married' 'divorced' 'single']\neducation : ['tertiary' 'primary' 'secondary' 'unknown']\ndefault : ['no' 'yes']\nhousing : ['yes' 'no']\nloan : ['no' 'yes']\ncontact : ['unknown' 'cellular' 'telephone']\nmonth : ['may' 'apr' 'jul' 'jun' 'nov' 'aug' 'jan' 'feb' 'dec' 'oct' 'sep' 'mar']\npoutcome : ['unknown' 'other' 'failure' 'success']\n","name":"stdout"}],"source":"# 对object型数据查看unique\nstr_features = []\nnum_features=[]\nfor col in train.columns:\n if train[col].dtype=='object':\n str_features.append(col)\n print(col,': ',train[col].unique())\n if train[col].dtype=='int64' and col not in ['ID','y']:\n num_features.append(col)"},{"cell_type":"markdown","metadata":{"id":"29CB9E135078402DBE2F479858631C1D","jupyter":{},"mdEditEnable":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"source":"# 特征工程"},{"cell_type":"code","execution_count":6,"metadata":{"collapsed":true,"id":"928046C510F54165A50D2FFBEFB4A5B5","jupyter":{},"scrolled":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"outputs":[],"source":"from scipy.stats import chi2_contingency # 数值型特征检验，检验特征与标签的关系\nfrom scipy.stats import f_oneway,ttest_ind # 分类型特征检验，检验特征与标签的关系"},{"cell_type":"code","execution_count":7,"metadata":{"collapsed":true,"id":"B5098300108B4CB784E1E1D8A1A7AF40","jupyter":{},"scrolled":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"outputs":[],"source":"#----------数据集处理--------------#\nfrom sklearn.model_selection import train_test_split # 划分训练集和验证集\nfrom sklearn.model_selection import KFold,StratifiedKFold # k折交叉\nfrom imblearn.combine import SMOTETomek,SMOTEENN # 综合采样\nfrom imblearn.over_sampling import SMOTE # 过采样\nfrom imblearn.under_sampling import RandomUnderSampler # 欠采样\n\n#----------数据处理--------------#\nfrom sklearn.preprocessing import StandardScaler # 标准化\nfrom sklearn.preprocessing import OneHotEncoder # 热独编码\nfrom sklearn.preprocessing import OrdinalEncoder"},{"cell_type":"markdown","metadata":{"id":"AB4FDF679736489B86708802E2B4E05B","jupyter":{},"mdEditEnable":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"source":"## 特征处理"},{"cell_type":"markdown","metadata":{"id":"B76FEED533744B93AD63ED6825716E5C","jupyter":{},"mdEditEnable":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"source":"**连续变量即数值化数据做标准化处理**"},{"cell_type":"code","execution_count":8,"metadata":{"collapsed":true,"id":"DD0BE0C3EF0D4755A0F255565CA064B3","jupyter":{},"scrolled":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"outputs":[],"source":"# 异常值处理\ndef outlier_processing(dfx):\n df = dfx.copy()\n q1 = df.quantile(q=0.25)\n q3 = df.quantile(q=0.75)\n iqr = q3 - q1\n Umin = q1 - 1.5*iqr\n Umax = q3 + 1.5*iqr \n df[df>Umax] = df[df<=Umax].max()\n df[df<Umin] = df[df>=Umin].min()\n return df"},{"cell_type":"code","execution_count":9,"metadata":{"collapsed":true,"id":"353D496D273C4456A8EF7C663D1C81C1","jupyter":{},"scrolled":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"outputs":[],"source":"train['age']=outlier_processing(train['age'])\ntrain['day']=outlier_processing(train['day'])\ntrain['duration']=outlier_processing(train['duration'])\ntrain['campaign']=outlier_processing(train['campaign'])\n\n\ntest['age']=outlier_processing(test['age'])\ntest['day']=outlier_processing(test['day'])\ntest['duration']=outlier_processing(test['duration'])\ntest['campaign']=outlier_processing(test['campaign'])"},{"cell_type":"code","execution_count":10,"metadata":{"id":"605C7188AA404524AA2B935E363D1E6C","jupyter":{},"scrolled":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n"," .dataframe tbody tr th:only-of-type {\n"," vertical-align: middle;\n"," }\n","\n"," .dataframe tbody tr th {\n"," vertical-align: top;\n"," }\n","\n"," .dataframe thead th {\n"," text-align: right;\n"," }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n"," <thead>\n"," <tr style=\"text-align: right;\">\n"," <th></th>\n"," <th>age</th>\n"," <th>balance</th>\n"," <th>day</th>\n"," <th>duration</th>\n"," <th>campaign</th>\n"," <th>pdays</th>\n"," <th>previous</th>\n"," </tr>\n"," </thead>\n"," <tbody>\n"," <tr>\n"," <th>count</th>\n"," <td>25317.000000</td>\n"," <td>25317.000000</td>\n"," <td>25317.000000</td>\n"," <td>25317.000000</td>\n"," <td>25317.000000</td>\n"," <td>25317.000000</td>\n"," <td>25317.000000</td>\n"," </tr>\n"," <tr>\n"," <th>mean</th>\n"," <td>40.859502</td>\n"," <td>1357.555082</td>\n"," <td>15.835289</td>\n"," <td>234.235138</td>\n"," <td>2.391437</td>\n"," <td>40.248766</td>\n"," <td>0.591737</td>\n"," </tr>\n"," <tr>\n"," <th>std</th>\n"," <td>10.387365</td>\n"," <td>2999.822811</td>\n"," <td>8.319480</td>\n"," <td>175.395559</td>\n"," <td>1.599851</td>\n"," <td>100.213541</td>\n"," <td>2.568313</td>\n"," </tr>\n"," <tr>\n"," <th>min</th>\n"," <td>18.000000</td>\n"," <td>-8019.000000</td>\n"," <td>1.000000</td>\n"," <td>0.000000</td>\n"," <td>1.000000</td>\n"," <td>-1.000000</td>\n"," <td>0.000000</td>\n"," </tr>\n"," <tr>\n"," <th>25%</th>\n"," <td>33.000000</td>\n"," <td>73.000000</td>\n"," <td>8.000000</td>\n"," <td>103.000000</td>\n"," <td>1.000000</td>\n"," <td>-1.000000</td>\n"," <td>0.000000</td>\n"," </tr>\n"," <tr>\n"," <th>50%</th>\n"," <td>39.000000</td>\n"," <td>448.000000</td>\n"," <td>16.000000</td>\n"," <td>181.000000</td>\n"," <td>2.000000</td>\n"," <td>-1.000000</td>\n"," <td>0.000000</td>\n"," </tr>\n"," <tr>\n"," <th>75%</th>\n"," <td>48.000000</td>\n"," <td>1435.000000</td>\n"," <td>21.000000</td>\n"," <td>317.000000</td>\n"," <td>3.000000</td>\n"," <td>-1.000000</td>\n"," <td>0.000000</td>\n"," </tr>\n"," <tr>\n"," <th>max</th>\n"," <td>70.000000</td>\n"," <td>102127.000000</td>\n"," <td>31.000000</td>\n"," <td>638.000000</td>\n"," <td>6.000000</td>\n"," <td>854.000000</td>\n"," <td>275.000000</td>\n"," </tr>\n"," </tbody>\n","</table>\n","</div>"],"text/plain":[" age balance day duration campaign \\\n","count 25317.000000 25317.000000 25317.000000 25317.000000 25317.000000 \n","mean 40.859502 1357.555082 15.835289 234.235138 2.391437 \n","std 10.387365 2999.822811 8.319480 175.395559 1.599851 \n","min 18.000000 -8019.000000 1.000000 0.000000 1.000000 \n","25% 33.000000 73.000000 8.000000 103.000000 1.000000 \n","50% 39.000000 448.000000 16.000000 181.000000 2.000000 \n","75% 48.000000 1435.000000 21.000000 317.000000 3.000000 \n","max 70.000000 102127.000000 31.000000 638.000000 6.000000 \n","\n"," pdays previous \n","count 25317.000000 25317.000000 \n","mean 40.248766 0.591737 \n","std 100.213541 2.568313 \n","min -1.000000 0.000000 \n","25% -1.000000 0.000000 \n","50% -1.000000 0.000000 \n","75% -1.000000 0.000000 \n","max 854.000000 275.000000 "]},"execution_count":10,"metadata":{},"output_type":"execute_result"}],"source":"train[num_features].describe()"},{"cell_type":"markdown","metadata":{"id":"FA30A072639C418283A5F9FF7BB70A5A","jupyter":{},"mdEditEnable":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"source":"**分类变量做编码处理**"},{"cell_type":"code","execution_count":11,"metadata":{"collapsed":true,"id":"B843C59639844E1A872AECAFE7926878","jupyter":{},"scrolled":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"outputs":[],"source":"dummy_train=train.join(pd.get_dummies(train[str_features])).drop(str_features,axis=1).drop(['ID','y'],axis=1)\ndummy_test=test.join(pd.get_dummies(test[str_features])).drop(str_features,axis=1).drop(['ID'],axis=1)"},{"cell_type":"markdown","metadata":{"id":"F2EA03BA7FAA45FF85F2CEDA21AB2F25","jupyter":{},"mdEditEnable":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"source":"## 统计检验与特征筛选 \n\n\n**连续变量-连续变量 相关分析**\n\n**连续变量-分类变量 T检验/方差分析**\n\n**分类变量-分类变量 卡方检验**"},{"cell_type":"markdown","metadata":{"id":"500456AC13CA4815858E06D09EE17A9E","jupyter":{},"mdEditEnable":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"source":"**对类别标签（离散变量）用卡方检验分析重要性**\n\n卡方检验认为显著水平大于95%是差异性显著的，这里即看p值是否是p>0.05，若p>0.05，则说明特征不会呈现差异性"},{"cell_type":"code","execution_count":12,"metadata":{"id":"40798A95334C4A85812FCB8A3CE6DD75","jupyter":{},"scrolled":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":["job 卡方检验p值: 0.0000\n","marital 卡方检验p值: 0.0000\n","education 卡方检验p值: 0.0000\n","default 卡方检验p值: 0.0001\n","housing 卡方检验p值: 0.0000\n","loan 卡方检验p值: 0.0000\n","contact 卡方检验p值: 0.0000\n","month 卡方检验p值: 0.0000\n","poutcome 卡方检验p值: 0.0000\n"]}],"source":"for col in str_features:\n obs=pd.crosstab(train['y'],\n train[col],\n rownames=['y'],\n colnames=[col])\n chi2, p, dof, expect = chi2_contingency(obs)\n print(\"{} 卡方检验p值: {:.4f}\".format(col,p))"},{"cell_type":"markdown","metadata":{"id":"30A24D4C89AF4BDAA0115FDF8F7C12E5","jupyter":{},"mdEditEnable":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"source":"**对连续变量做方差分析进行特征筛选**\n"},{"cell_type":"code","execution_count":13,"metadata":{"id":"43185B05C4AB48628437C4224F86F348","jupyter":{},"scrolled":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":["scores_: [ 13.38856992 84.16396612 25.76507245 4405.56959938 193.97418155\n"," 296.33099313 199.09942912]\n","pvalues_: [2.53676251e-04 4.89124305e-20 3.88332900e-07 0.00000000e+00\n"," 6.26768275e-44 4.93591331e-66 4.86613654e-45]\n","selected index: [0 1 2 3 4 5 6]\n"]}],"source":"from sklearn.feature_selection import SelectKBest,f_classif\n\nf,p=f_classif(train[num_features],train['y'])\nk = f.shape[0] - (p > 0.05).sum()\nselector = SelectKBest(f_classif, k=k)\nselector.fit(train[num_features],train['y'])\n\nprint('scores_:',selector.scores_)\nprint('pvalues_:',selector.pvalues_)\nprint('selected index:',selector.get_support(True))"},{"cell_type":"code","execution_count":14,"metadata":{"collapsed":true,"id":"5AC3B3DFF3134BDC83E167086A48540B","jupyter":{},"scrolled":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"outputs":[],"source":"# 标准化，返回值为标准化后的数据\nstandardScaler=StandardScaler()\nss=standardScaler.fit(dummy_train.loc[:,num_features])\ndummy_train.loc[:,num_features]=ss.transform(dummy_train.loc[:,num_features])\ndummy_test.loc[:,num_features]=ss.transform(dummy_test.loc[:,num_features])"},{"cell_type":"code","execution_count":15,"metadata":{"collapsed":true,"id":"EEEA48883D2E4FA58FB392991E531C86","jupyter":{},"scrolled":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"outputs":[],"source":"X=dummy_train\ny=train['y']"},{"cell_type":"markdown","metadata":{"id":"A16ACA2680A243C0880DE1F19CFB6AAD","jupyter":{},"mdEditEnable":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"source":"**因为后续是进行回归而非分类，个人认为没有必要进行不平衡处理，故此部分就注释掉了**"},{"cell_type":"code","execution_count":16,"metadata":{"collapsed":true,"id":"AFE7C8F818B148178A42245BBF4C8878","jupyter":{},"scrolled":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"outputs":[],"source":"# X_train,X_valid,y_train,y_valid=train_test_split(X,y,test_size=0.2,random_state=2020)"},{"cell_type":"code","execution_count":17,"metadata":{"collapsed":true,"id":"046EFE395ED34BFCAD11F2721BBE40FD","jupyter":{},"scrolled":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"outputs":[],"source":"# smote_tomek = SMOTETomek(random_state=2020)\n# X_resampled, y_resampled = smote_tomek.fit_resample(X, y)"},{"cell_type":"markdown","metadata":{"id":"13F7B7216054465D9437CEB872026BC3","jupyter":{},"mdEditEnable":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"source":"# 数据建模"},{"cell_type":"code","execution_count":19,"metadata":{"id":"0E1FC19C7DF74042B6F1A9F5527AA4AE","jupyter":{},"scrolled":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"outputs":[{"name":"stderr","output_type":"stream","text":["E:\\Anaconda3\\lib\\site-packages\\dask\\dataframe\\utils.py:13: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n"," import pandas.util.testing as tm\n"]}],"source":"#----------建模工具--------------#\nfrom sklearn.model_selection import GridSearchCV\nfrom sklearn.pipeline import Pipeline\nfrom sklearn.model_selection import KFold,RepeatedKFold\nimport lightgbm as lgb\nfrom sklearn.ensemble import RandomForestRegressor\nimport xgboost as xgb\nfrom xgboost import XGBRegressor\nfrom sklearn.linear_model import BayesianRidge\nfrom catboost import CatBoostRegressor, Pool\nfrom lightgbm import LGBMRegressor\n#----------模型评估工具----------#\nfrom sklearn.metrics import confusion_matrix # 混淆矩阵\nfrom sklearn.metrics import classification_report\nfrom sklearn.metrics import recall_score,f1_score\nfrom sklearn.metrics import roc_auc_score\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.metrics import roc_curve,auc\nfrom sklearn.metrics import roc_auc_score"},{"cell_type":"markdown","metadata":{"id":"D59F8B42DDB34650B81C23D56AE0BB43","jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"## 模型建立和参数调整"},{"cell_type":"markdown","metadata":{"id":"B6C0DDA8DA53482ABA9E2EE753DB105D","jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"### 基于GridSearchCV的随机森林参数调整"},{"cell_type":"code","execution_count":45,"metadata":{"id":"4451159F5E62465CB52012889AD801B2","jupyter":{},"scrolled":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":["Fitting 3 folds for each of 3 candidates, totalling 9 fits\n","{'max_features': 11, 'min_samples_leaf': 1, 'n_estimators': 1700}\n"]}],"source":"# 随机森林\n# param = {'n_estimators':[1500,1700,2000],\n# 'max_features':[7,11,15]\n# }\n# gs = GridSearchCV(estimator=RandomForestRegressor(), param_grid=param, cv=3, scoring=\"neg_mean_squared_error\", n_jobs=-1, verbose=10) \n# gs.fit(X_resampled,y_resampled)\n# print(gs.best_params_) \n"},{"cell_type":"markdown","metadata":{"id":"821CD114AA87471B9188366261086B72","jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"### 基于五折交叉验证的随机森林"},{"cell_type":"code","execution_count":46,"metadata":{"id":"46ED98A1821C450E85F2338B49A197C6","jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":["0.929373220326099\n"]}],"source":"n_fold = 5\nfolds = KFold(n_splits=n_fold, shuffle=True, random_state=2022)\noof_rf = np.zeros(len(X))\nprediction_rf = np.zeros(len(dummy_test))\nfor fold_n, (train_index, valid_index) in enumerate(folds.split(X)):\n X_train, X_valid = X.iloc[train_index], X.iloc[valid_index]\n y_train, y_valid = y[train_index], y[valid_index]\n# smote_tomek = SMOTETomek(random_state=2022)\n# X_resampled, y_resampled = smote_tomek.fit_resample(X_train, y_train)\n model_rf = RandomForestRegressor(max_features=11,min_samples_leaf=1,n_estimators=1700,random_state=2022).fit(X_train,y_train)\n y_pred_valid = model_rf.predict(X_valid)\n y_pred = model_rf.predict(dummy_test)\n oof_rf[valid_index] = y_pred_valid.reshape(-1, )\n prediction_rf += y_pred\nprediction_rf /= n_fold \nprint(roc_auc_score(y, oof_rf))\n#0.929373220326099"},{"cell_type":"markdown","metadata":{"id":"A03808ADDE7A4AC4AEFDC87F09A5A017","jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"### 基于GridSearchCV的XGB参数调整"},{"cell_type":"code","execution_count":123,"metadata":{"id":"A26971BEEF684860B739522723029593","jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":["Fitting 3 folds for each of 3 candidates, totalling 9 fits\n","{'colsample_bytree': 0.6, 'learning_rate': 0.05, 'max_depth': 3, 'n_estimators': 800, 'subsample': 0.8}\n"]}],"source":"# param = {'max_depth': [3],\n# 'learning_rate': [0.01],\n# 'subsample':[0.8],\n# 'colsample_bytree':[0.6],\n# 'n_estimators': [8000]\n\n# }\n# gs = GridSearchCV(estimator=XGBRegressor(), param_grid=param, cv=3, scoring=\"neg_mean_squared_error\", n_jobs=-1, verbose=10) \n# gs.fit(X,y)\n# print(gs.best_params_) \n"},{"cell_type":"markdown","metadata":{"id":"7AF59354E891478D8154F963C5EDE251","jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"### 基于五折交叉验证的XGB"},{"cell_type":"code","execution_count":126,"metadata":{"id":"C0C60825A129420F8F4C983DEC926AC6","jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":["[0]\tvalidation_0-auc:0.86541\n","[1]\tvalidation_0-auc:0.88478\n","[2]\tvalidation_0-auc:0.89516\n","[3]\tvalidation_0-auc:0.90166\n","[4]\tvalidation_0-auc:0.90600\n","[5]\tvalidation_0-auc:0.90680\n","[6]\tvalidation_0-auc:0.90747\n","[7]\tvalidation_0-auc:0.90969\n","[8]\tvalidation_0-auc:0.90979\n","[9]\tvalidation_0-auc:0.90992\n","[10]\tvalidation_0-auc:0.91239\n"]},{"name":"stderr","output_type":"stream","text":["E:\\Anaconda3\\lib\\site-packages\\xgboost\\sklearn.py:797: UserWarning: `eval_metric` in `fit` method is deprecated for better compatibility with scikit-learn, use `eval_metric` in constructor or`set_params` instead.\n"," UserWarning,\n","E:\\Anaconda3\\lib\\site-packages\\xgboost\\sklearn.py:797: UserWarning: `early_stopping_rounds` in `fit` method is deprecated for better compatibility with scikit-learn, use `early_stopping_rounds` in constructor or`set_params` instead.\n"," UserWarning,\n"]},{"name":"stdout","output_type":"stream","text":"[11]\tvalidation_0-auc:0.91302\n[12]\tvalidation_0-auc:0.91294\n[13]\tvalidation_0-auc:0.91220\n[14]\tvalidation_0-auc:0.91338\n[15]\tvalidation_0-auc:0.91288\n[16]\tvalidation_0-auc:0.91278\n[17]\tvalidation_0-auc:0.91364\n[18]\tvalidation_0-auc:0.91342\n[19]\tvalidation_0-auc:0.91408\n[20]\tvalidation_0-auc:0.91458\n[21]\tvalidation_0-auc:0.91514\n[22]\tvalidation_0-auc:0.91541\n[23]\tvalidation_0-auc:0.91541\n[24]\tvalidation_0-auc:0.91533\n[25]\tvalidation_0-auc:0.91583\n[26]\tvalidation_0-auc:0.91574\n[27]\tvalidation_0-auc:0.91588\n[28]\tvalidation_0-auc:0.91624\n[29]\tvalidation_0-auc:0.91635\n[30]\tvalidation_0-auc:0.91886\n[31]\tvalidation_0-auc:0.91898\n[32]\tvalidation_0-auc:0.91876\n[33]\tvalidation_0-auc:0.91921\n[34]\tvalidation_0-auc:0.91927\n[35]\tvalidation_0-auc:0.91894\n[36]\tvalidation_0-auc:0.91962\n[37]\tvalidation_0-auc:0.91952\n[38]\tvalidation_0-auc:0.91979\n[39]\tvalidation_0-auc:0.91998\n[40]\tvalidation_0-auc:0.92026\n[41]\tvalidation_0-auc:0.92031\n[42]\tvalidation_0-auc:0.92050\n[43]\tvalidation_0-auc:0.92028\n[44]\tvalidation_0-auc:0.92069\n[45]\tvalidation_0-auc:0.92116\n[46]\tvalidation_0-auc:0.92123\n[47]\tvalidation_0-auc:0.92150\n[48]\tvalidation_0-auc:0.92170\n[49]\tvalidation_0-auc:0.92155\n[50]\tvalidation_0-auc:0.92219\n[51]\tvalidation_0-auc:0.92242\n[52]\tvalidation_0-auc:0.92279\n[53]\tvalidation_0-auc:0.92275\n[54]\tvalidation_0-auc:0.92314\n[55]\tvalidation_0-auc:0.92312\n[56]\tvalidation_0-auc:0.92295\n[57]\tvalidation_0-auc:0.92310\n[58]\tvalidation_0-auc:0.92318\n[59]\tvalidation_0-auc:0.92353\n[60]\tvalidation_0-auc:0.92354\n[61]\tvalidation_0-auc:0.92378\n[62]\tvalidation_0-auc:0.92391\n[63]\tvalidation_0-auc:0.92395\n[64]\tvalidation_0-auc:0.92396\n[65]\tvalidation_0-auc:0.92381\n[66]\tvalidation_0-auc:0.92382\n[67]\tvalidation_0-auc:0.92389\n[68]\tvalidation_0-auc:0.92386\n[69]\tvalidation_0-auc:0.92375\n[70]\tvalidation_0-auc:0.92381\n[71]\tvalidation_0-auc:0.92370\n[72]\tvalidation_0-auc:0.92367\n[73]\tvalidation_0-auc:0.92388\n[74]\tvalidation_0-auc:0.92374\n[75]\tvalidation_0-auc:0.92375\n[76]\tvalidation_0-auc:0.92374\n[77]\tvalidation_0-auc:0.92368\n[78]\tvalidation_0-auc:0.92361\n[79]\tvalidation_0-auc:0.92382\n[80]\tvalidation_0-auc:0.92401\n[81]\tvalidation_0-auc:0.92394\n[82]\tvalidation_0-auc:0.92405\n[83]\tvalidation_0-auc:0.92407\n[84]\tvalidation_0-auc:0.92416\n[85]\tvalidation_0-auc:0.92399\n[86]\tvalidation_0-auc:0.92386\n[87]\tvalidation_0-auc:0.92389\n[88]\tvalidation_0-auc:0.92388\n[89]\tvalidation_0-auc:0.92398\n[90]\tvalidation_0-auc:0.92403\n[91]\tvalidation_0-auc:0.92402\n[92]\tvalidation_0-auc:0.92398\n[93]\tvalidation_0-auc:0.92399\n[94]\tvalidation_0-auc:0.92403\n[95]\tvalidation_0-auc:0.92406\n[96]\tvalidation_0-auc:0.92393\n[97]\tvalidation_0-auc:0.92406\n[98]\tvalidation_0-auc:0.92400\n[99]\tvalidation_0-auc:0.92407\n[100]\tvalidation_0-auc:0.92414\n[101]\tvalidation_0-auc:0.92435\n[102]\tvalidation_0-auc:0.92449\n[103]\tvalidation_0-auc:0.92457\n[104]\tvalidation_0-auc:0.92450\n[105]\tvalidation_0-auc:0.92462\n[106]\tvalidation_0-auc:0.92475\n[107]\tvalidation_0-auc:0.92476\n[108]\tvalidation_0-auc:0.92494\n[109]\tvalidation_0-auc:0.92495\n[110]\tvalidation_0-auc:0.92496\n[111]\tvalidation_0-auc:0.92491\n[112]\tvalidation_0-auc:0.92489\n[113]\tvalidation_0-auc:0.92490\n[114]\tvalidation_0-auc:0.92495\n[115]\tvalidation_0-auc:0.92502\n[116]\tvalidation_0-auc:0.92507\n[117]\tvalidation_0-auc:0.92516\n[118]\tvalidation_0-auc:0.92516\n[119]\tvalidation_0-auc:0.92521\n[120]\tvalidation_0-auc:0.92523\n[121]\tvalidation_0-auc:0.92526\n[122]\tvalidation_0-auc:0.92533\n[123]\tvalidation_0-auc:0.92537\n[124]\tvalidation_0-auc:0.92531\n[125]\tvalidation_0-auc:0.92532\n[126]\tvalidation_0-auc:0.92532\n[127]\tvalidation_0-auc:0.92531\n[128]\tvalidation_0-auc:0.92527\n[129]\tvalidation_0-auc:0.92527\n[130]\tvalidation_0-auc:0.92525\n[131]\tvalidation_0-auc:0.92551\n[132]\tvalidation_0-auc:0.92549\n[133]\tvalidation_0-auc:0.92551\n[134]\tvalidation_0-auc:0.92545\n[135]\tvalidation_0-auc:0.92550\n[136]\tvalidation_0-auc:0.92551\n[137]\tvalidation_0-auc:0.92559\n[138]\tvalidation_0-auc:0.92562\n[139]\tvalidation_0-auc:0.92567\n[140]\tvalidation_0-auc:0.92566\n[141]\tvalidation_0-auc:0.92566\n[142]\tvalidation_0-auc:0.92566\n[143]\tvalidation_0-auc:0.92568\n[144]\tvalidation_0-auc:0.92566\n[145]\tvalidation_0-auc:0.92564\n[146]\tvalidation_0-auc:0.92560\n[147]\tvalidation_0-auc:0.92582\n[148]\tvalidation_0-auc:0.92579\n[149]\tvalidation_0-auc:0.92579\n[150]\tvalidation_0-auc:0.92577\n[151]\tvalidation_0-auc:0.92571\n[152]\tvalidation_0-auc:0.92571\n[153]\tvalidation_0-auc:0.92576\n[154]\tvalidation_0-auc:0.92572\n[155]\tvalidation_0-auc:0.92571\n[156]\tvalidation_0-auc:0.92577\n[157]\tvalidation_0-auc:0.92572\n[158]\tvalidation_0-auc:0.92567\n[159]\tvalidation_0-auc:0.92570\n[160]\tvalidation_0-auc:0.92565\n[161]\tvalidation_0-auc:0.92559\n[162]\tvalidation_0-auc:0.92562\n[163]\tvalidation_0-auc:0.92565\n[164]\tvalidation_0-auc:0.92568\n[165]\tvalidation_0-auc:0.92568\n[166]\tvalidation_0-auc:0.92568\n[167]\tvalidation_0-auc:0.92564\n[168]\tvalidation_0-auc:0.92559\n[169]\tvalidation_0-auc:0.92557\n[170]\tvalidation_0-auc:0.92553\n[171]\tvalidation_0-auc:0.92550\n[172]\tvalidation_0-auc:0.92549\n[173]\tvalidation_0-auc:0.92552\n[174]\tvalidation_0-auc:0.92548\n[175]\tvalidation_0-auc:0.92545\n[176]\tvalidation_0-auc:0.92547\n[177]\tvalidation_0-auc:0.92549\n[178]\tvalidation_0-auc:0.92554\n[179]\tvalidation_0-auc:0.92566\n[180]\tvalidation_0-auc:0.92571\n[181]\tvalidation_0-auc:0.92586\n[182]\tvalidation_0-auc:0.92585\n[183]\tvalidation_0-auc:0.92594\n[184]\tvalidation_0-auc:0.92594\n[185]\tvalidation_0-auc:0.92605\n[186]\tvalidation_0-auc:0.92598\n[187]\tvalidation_0-auc:0.92597\n[188]\tvalidation_0-auc:0.92598\n[189]\tvalidation_0-auc:0.92595\n[190]\tvalidation_0-auc:0.92608\n[191]\tvalidation_0-auc:0.92609\n[192]\tvalidation_0-auc:0.92613\n[193]\tvalidation_0-auc:0.92609\n[194]\tvalidation_0-auc:0.92614\n[195]\tvalidation_0-auc:0.92613\n[196]\tvalidation_0-auc:0.92614\n[197]\tvalidation_0-auc:0.92629\n[198]\tvalidation_0-auc:0.92626\n[199]\tvalidation_0-auc:0.92622\n[200]\tvalidation_0-auc:0.92622\n[201]\tvalidation_0-auc:0.92626\n[202]\tvalidation_0-auc:0.92644\n[203]\tvalidation_0-auc:0.92647\n[204]\tvalidation_0-auc:0.92645\n[205]\tvalidation_0-auc:0.92653\n[206]\tvalidation_0-auc:0.92667\n[207]\tvalidation_0-auc:0.92681\n[208]\tvalidation_0-auc:0.92674\n[209]\tvalidation_0-auc:0.92684\n[210]\tvalidation_0-auc:0.92689\n[211]\tvalidation_0-auc:0.92691\n[212]\tvalidation_0-auc:0.92691\n[213]\tvalidation_0-auc:0.92689\n[214]\tvalidation_0-auc:0.92687\n[215]\tvalidation_0-auc:0.92692\n[216]\tvalidation_0-auc:0.92687\n[217]\tvalidation_0-auc:0.92686\n[218]\tvalidation_0-auc:0.92686\n[219]\tvalidation_0-auc:0.92686\n[220]\tvalidation_0-auc:0.92706\n[221]\tvalidation_0-auc:0.92705\n[222]\tvalidation_0-auc:0.92707\n[223]\tvalidation_0-auc:0.92706\n[224]\tvalidation_0-auc:0.92705\n[225]\tvalidation_0-auc:0.92712\n[226]\tvalidation_0-auc:0.92727\n[227]\tvalidation_0-auc:0.92725\n[228]\tvalidation_0-auc:0.92726\n[229]\tvalidation_0-auc:0.92727\n[230]\tvalidation_0-auc:0.92721\n[231]\tvalidation_0-auc:0.92724\n[232]\tvalidation_0-auc:0.92739\n[233]\tvalidation_0-auc:0.92746\n[234]\tvalidation_0-auc:0.92753\n[235]\tvalidation_0-auc:0.92754\n[236]\tvalidation_0-auc:0.92756\n[237]\tvalidation_0-auc:0.92759\n[238]\tvalidation_0-auc:0.92761\n[239]\tvalidation_0-auc:0.92756\n[240]\tvalidation_0-auc:0.92754\n[241]\tvalidation_0-auc:0.92750\n[242]\tvalidation_0-auc:0.92749\n[243]\tvalidation_0-auc:0.92757\n[244]\tvalidation_0-auc:0.92760\n[245]\tvalidation_0-auc:0.92760\n[246]\tvalidation_0-auc:0.92765\n[247]\tvalidation_0-auc:0.92765\n[248]\tvalidation_0-auc:0.92761\n[249]\tvalidation_0-auc:0.92768\n[250]\tvalidation_0-auc:0.92766\n[251]\tvalidation_0-auc:0.92768\n[252]\tvalidation_0-auc:0.92772\n[253]\tvalidation_0-auc:0.92772\n[254]\tvalidation_0-auc:0.92770\n[255]\tvalidation_0-auc:0.92763\n[256]\tvalidation_0-auc:0.92771\n[257]\tvalidation_0-auc:0.92775\n[258]\tvalidation_0-auc:0.92776\n[259]\tvalidation_0-auc:0.92776\n[260]\tvalidation_0-auc:0.92780\n[261]\tvalidation_0-auc:0.92783\n[262]\tvalidation_0-auc:0.92784\n[263]\tvalidation_0-auc:0.92785\n[264]\tvalidation_0-auc:0.92788\n[265]\tvalidation_0-auc:0.92792\n[266]\tvalidation_0-auc:0.92791\n[267]\tvalidation_0-auc:0.92791\n[268]\tvalidation_0-auc:0.92787\n[269]\tvalidation_0-auc:0.92785\n[270]\tvalidation_0-auc:0.92797\n[271]\tvalidation_0-auc:0.92796\n[272]\tvalidation_0-auc:0.92795\n[273]\tvalidation_0-auc:0.92802\n[274]\tvalidation_0-auc:0.92811\n[275]\tvalidation_0-auc:0.92809\n[276]\tvalidation_0-auc:0.92810\n[277]\tvalidation_0-auc:0.92811\n[278]\tvalidation_0-auc:0.92813\n[279]\tvalidation_0-auc:0.92813\n[280]\tvalidation_0-auc:0.92807\n[281]\tvalidation_0-auc:0.92811\n[282]\tvalidation_0-auc:0.92816\n[283]\tvalidation_0-auc:0.92821\n[284]\tvalidation_0-auc:0.92821\n[285]\tvalidation_0-auc:0.92824\n[286]\tvalidation_0-auc:0.92829\n[287]\tvalidation_0-auc:0.92833\n[288]\tvalidation_0-auc:0.92832\n[289]\tvalidation_0-auc:0.92830\n[290]\tvalidation_0-auc:0.92833\n[291]\tvalidation_0-auc:0.92835\n[292]\tvalidation_0-auc:0.92842\n[293]\tvalidation_0-auc:0.92843\n[294]\tvalidation_0-auc:0.92844\n[295]\tvalidation_0-auc:0.92845\n[296]\tvalidation_0-auc:0.92845\n[297]\tvalidation_0-auc:0.92849\n[298]\tvalidation_0-auc:0.92851\n[299]\tvalidation_0-auc:0.92853\n[300]\tvalidation_0-auc:0.92854\n[301]\tvalidation_0-auc:0.92853\n[302]\tvalidation_0-auc:0.92851\n[303]\tvalidation_0-auc:0.92865\n[304]\tvalidation_0-auc:0.92865\n[305]\tvalidation_0-auc:0.92867\n[306]\tvalidation_0-auc:0.92865\n[307]\tvalidation_0-auc:0.92871\n[308]\tvalidation_0-auc:0.92869\n[309]\tvalidation_0-auc:0.92866\n[310]\tvalidation_0-auc:0.92865\n[311]\tvalidation_0-auc:0.92862\n[312]\tvalidation_0-auc:0.92863\n[313]\tvalidation_0-auc:0.92867\n[314]\tvalidation_0-auc:0.92865\n[315]\tvalidation_0-auc:0.92884\n[316]\tvalidation_0-auc:0.92883\n[317]\tvalidation_0-auc:0.92881\n[318]\tvalidation_0-auc:0.92880\n[319]\tvalidation_0-auc:0.92878\n[320]\tvalidation_0-auc:0.92880\n[321]\tvalidation_0-auc:0.92886\n[322]\tvalidation_0-auc:0.92889\n[323]\tvalidation_0-auc:0.92890\n[324]\tvalidation_0-auc:0.92891\n[325]\tvalidation_0-auc:0.92893\n[326]\tvalidation_0-auc:0.92892\n[327]\tvalidation_0-auc:0.92893\n[328]\tvalidation_0-auc:0.92889\n[329]\tvalidation_0-auc:0.92894\n[330]\tvalidation_0-auc:0.92895\n[331]\tvalidation_0-auc:0.92903\n[332]\tvalidation_0-auc:0.92903\n[333]\tvalidation_0-auc:0.92908\n[334]\tvalidation_0-auc:0.92909\n[335]\tvalidation_0-auc:0.92909\n[336]\tvalidation_0-auc:0.92908\n[337]\tvalidation_0-auc:0.92917\n[338]\tvalidation_0-auc:0.92921\n[339]\tvalidation_0-auc:0.92921\n[340]\tvalidation_0-auc:0.92923\n[341]\tvalidation_0-auc:0.92923\n[342]\tvalidation_0-auc:0.92923\n[343]\tvalidation_0-auc:0.92924\n[344]\tvalidation_0-auc:0.92920\n[345]\tvalidation_0-auc:0.92924\n[346]\tvalidation_0-auc:0.92926\n[347]\tvalidation_0-auc:0.92928\n[348]\tvalidation_0-auc:0.92928\n[349]\tvalidation_0-auc:0.92934\n[350]\tvalidation_0-auc:0.92936\n[351]\tvalidation_0-auc:0.92934\n[352]\tvalidation_0-auc:0.92933\n[353]\tvalidation_0-auc:0.92932\n[354]\tvalidation_0-auc:0.92930\n[355]\tvalidation_0-auc:0.92932\n[356]\tvalidation_0-auc:0.92934\n[357]\tvalidation_0-auc:0.92937\n[358]\tvalidation_0-auc:0.92937\n[359]\tvalidation_0-auc:0.92939\n[360]\tvalidation_0-auc:0.92937\n[361]\tvalidation_0-auc:0.92939\n[362]\tvalidation_0-auc:0.92936\n[363]\tvalidation_0-auc:0.92933\n[364]\tvalidation_0-auc:0.92934\n[365]\tvalidation_0-auc:0.92934\n[366]\tvalidation_0-auc:0.92936\n[367]\tvalidation_0-auc:0.92940\n[368]\tvalidation_0-auc:0.92945\n[369]\tvalidation_0-auc:0.92943\n[370]\tvalidation_0-auc:0.92946\n[371]\tvalidation_0-auc:0.92945\n[372]\tvalidation_0-auc:0.92938\n[373]\tvalidation_0-auc:0.92936\n[374]\tvalidation_0-auc:0.92937\n[375]\tvalidation_0-auc:0.92940\n[376]\tvalidation_0-auc:0.92943\n[377]\tvalidation_0-auc:0.92942\n[378]\tvalidation_0-auc:0.92947\n[379]\tvalidation_0-auc:0.92947\n[380]\tvalidation_0-auc:0.92946\n[381]\tvalidation_0-auc:0.92946\n[382]\tvalidation_0-auc:0.92946\n[383]\tvalidation_0-auc:0.92947\n[384]\tvalidation_0-auc:0.92953\n[385]\tvalidation_0-auc:0.92951\n[386]\tvalidation_0-auc:0.92959\n[387]\tvalidation_0-auc:0.92959\n[388]\tvalidation_0-auc:0.92964\n[389]\tvalidation_0-auc:0.92967\n[390]\tvalidation_0-auc:0.92967\n[391]\tvalidation_0-auc:0.92967\n[392]\tvalidation_0-auc:0.92966\n[393]\tvalidation_0-auc:0.92964\n[394]\tvalidation_0-auc:0.92959\n[395]\tvalidation_0-auc:0.92960\n[396]\tvalidation_0-auc:0.92964\n[397]\tvalidation_0-auc:0.92969\n[398]\tvalidation_0-auc:0.92969\n[399]\tvalidation_0-auc:0.92969\n[400]\tvalidation_0-auc:0.92970\n[401]\tvalidation_0-auc:0.92967\n[402]\tvalidation_0-auc:0.92969\n[403]\tvalidation_0-auc:0.92971\n[404]\tvalidation_0-auc:0.92974\n[405]\tvalidation_0-auc:0.92977\n[406]\tvalidation_0-auc:0.92975\n[407]\tvalidation_0-auc:0.92974\n[408]\tvalidation_0-auc:0.92972\n[409]\tvalidation_0-auc:0.92972\n[410]\tvalidation_0-auc:0.92974\n[411]\tvalidation_0-auc:0.92974\n[412]\tvalidation_0-auc:0.92971\n[413]\tvalidation_0-auc:0.92967\n[414]\tvalidation_0-auc:0.92969\n[415]\tvalidation_0-auc:0.92965\n[416]\tvalidation_0-auc:0.92963\n[417]\tvalidation_0-auc:0.92966\n[418]\tvalidation_0-auc:0.92968\n[419]\tvalidation_0-auc:0.92968\n[420]\tvalidation_0-auc:0.92968\n[421]\tvalidation_0-auc:0.92965\n[422]\tvalidation_0-auc:0.92964\n[423]\tvalidation_0-auc:0.92964\n[424]\tvalidation_0-auc:0.92965\n[425]\tvalidation_0-auc:0.92965\n[426]\tvalidation_0-auc:0.92966\n[427]\tvalidation_0-auc:0.92967\n[428]\tvalidation_0-auc:0.92967\n[429]\tvalidation_0-auc:0.92968\n[430]\tvalidation_0-auc:0.92970\n[431]\tvalidation_0-auc:0.92971\n[432]\tvalidation_0-auc:0.92971\n[433]\tvalidation_0-auc:0.92971\n[434]\tvalidation_0-auc:0.92974\n[435]\tvalidation_0-auc:0.92977\n[436]\tvalidation_0-auc:0.92979\n[437]\tvalidation_0-auc:0.92978\n[438]\tvalidation_0-auc:0.92981\n[439]\tvalidation_0-auc:0.92986\n[440]\tvalidation_0-auc:0.92987\n[441]\tvalidation_0-auc:0.92990\n[442]\tvalidation_0-auc:0.92990\n[443]\tvalidation_0-auc:0.92990\n[444]\tvalidation_0-auc:0.92988\n[445]\tvalidation_0-auc:0.92992\n[446]\tvalidation_0-auc:0.92991\n[447]\tvalidation_0-auc:0.92998\n[448]\tvalidation_0-auc:0.92999\n[449]\tvalidation_0-auc:0.92996\n[450]\tvalidation_0-auc:0.92999\n[451]\tvalidation_0-auc:0.92998\n[452]\tvalidation_0-auc:0.92997\n[453]\tvalidation_0-auc:0.93000\n[454]\tvalidation_0-auc:0.93001\n[455]\tvalidation_0-auc:0.93004\n[456]\tvalidation_0-auc:0.93004\n[457]\tvalidation_0-auc:0.93005\n[458]\tvalidation_0-auc:0.93004\n[459]\tvalidation_0-auc:0.93008\n[460]\tvalidation_0-auc:0.93008\n[461]\tvalidation_0-auc:0.93006\n[462]\tvalidation_0-auc:0.93003\n[463]\tvalidation_0-auc:0.93003\n[464]\tvalidation_0-auc:0.93001\n[465]\tvalidation_0-auc:0.93003\n[466]\tvalidation_0-auc:0.93000\n[467]\tvalidation_0-auc:0.93004\n[468]\tvalidation_0-auc:0.93003\n[469]\tvalidation_0-auc:0.93003\n[470]\tvalidation_0-auc:0.93001\n[471]\tvalidation_0-auc:0.93000\n[472]\tvalidation_0-auc:0.93004\n[473]\tvalidation_0-auc:0.93001\n[474]\tvalidation_0-auc:0.93002\n[475]\tvalidation_0-auc:0.93003\n[476]\tvalidation_0-auc:0.93005\n[477]\tvalidation_0-auc:0.93005\n[478]\tvalidation_0-auc:0.93004\n[479]\tvalidation_0-auc:0.93003\n[480]\tvalidation_0-auc:0.93001\n[481]\tvalidation_0-auc:0.93000\n[482]\tvalidation_0-auc:0.93000\n[483]\tvalidation_0-auc:0.92998\n[484]\tvalidation_0-auc:0.92997\n[485]\tvalidation_0-auc:0.92998\n[486]\tvalidation_0-auc:0.92998\n[487]\tvalidation_0-auc:0.92996\n[488]\tvalidation_0-auc:0.92991\n[489]\tvalidation_0-auc:0.92993\n[490]\tvalidation_0-auc:0.92996\n[491]\tvalidation_0-auc:0.92994\n[492]\tvalidation_0-auc:0.92994\n[493]\tvalidation_0-auc:0.92995\n[494]\tvalidation_0-auc:0.92993\n[495]\tvalidation_0-auc:0.92992\n[496]\tvalidation_0-auc:0.92998\n[497]\tvalidation_0-auc:0.92996\n[498]\tvalidation_0-auc:0.92997\n[499]\tvalidation_0-auc:0.92997\n[500]\tvalidation_0-auc:0.92997\n[501]\tvalidation_0-auc:0.92996\n[502]\tvalidation_0-auc:0.92999\n[503]\tvalidation_0-auc:0.93002\n[504]\tvalidation_0-auc:0.93002\n[505]\tvalidation_0-auc:0.93005\n[506]\tvalidation_0-auc:0.93006\n[507]\tvalidation_0-auc:0.93002\n[508]\tvalidation_0-auc:0.93002\n[509]\tvalidation_0-auc:0.93004\n[510]\tvalidation_0-auc:0.93003\n[511]\tvalidation_0-auc:0.93000\n[512]\tvalidation_0-auc:0.93001\n[513]\tvalidation_0-auc:0.93001\n[514]\tvalidation_0-auc:0.93001\n[515]\tvalidation_0-auc:0.92996\n[516]\tvalidation_0-auc:0.92994\n[517]\tvalidation_0-auc:0.92993\n[518]\tvalidation_0-auc:0.92993\n[519]\tvalidation_0-auc:0.92993\n[520]\tvalidation_0-auc:0.92994\n[521]\tvalidation_0-auc:0.92996\n[522]\tvalidation_0-auc:0.92995\n[523]\tvalidation_0-auc:0.92996\n[524]\tvalidation_0-auc:0.93004\n[525]\tvalidation_0-auc:0.92999\n[526]\tvalidation_0-auc:0.93000\n[527]\tvalidation_0-auc:0.93002\n[528]\tvalidation_0-auc:0.93001\n[529]\tvalidation_0-auc:0.93002\n[530]\tvalidation_0-auc:0.93005\n[531]\tvalidation_0-auc:0.93004\n[532]\tvalidation_0-auc:0.93003\n[533]\tvalidation_0-auc:0.93004\n[534]\tvalidation_0-auc:0.93006\n[535]\tvalidation_0-auc:0.93007\n[536]\tvalidation_0-auc:0.93006\n[537]\tvalidation_0-auc:0.93006\n[538]\tvalidation_0-auc:0.93007\n[539]\tvalidation_0-auc:0.93010\n[540]\tvalidation_0-auc:0.93010\n[541]\tvalidation_0-auc:0.93011\n[542]\tvalidation_0-auc:0.93011\n[543]\tvalidation_0-auc:0.93013\n[544]\tvalidation_0-auc:0.93019\n[545]\tvalidation_0-auc:0.93019\n[546]\tvalidation_0-auc:0.93023\n[547]\tvalidation_0-auc:0.93033\n[548]\tvalidation_0-auc:0.93034\n[549]\tvalidation_0-auc:0.93031\n[550]\tvalidation_0-auc:0.93030\n[551]\tvalidation_0-auc:0.93028\n[552]\tvalidation_0-auc:0.93032\n[553]\tvalidation_0-auc:0.93031\n[554]\tvalidation_0-auc:0.93029\n[555]\tvalidation_0-auc:0.93021\n[556]\tvalidation_0-auc:0.93024\n[557]\tvalidation_0-auc:0.93020\n[558]\tvalidation_0-auc:0.93021\n[559]\tvalidation_0-auc:0.93024\n[560]\tvalidation_0-auc:0.93023\n[561]\tvalidation_0-auc:0.93020\n[562]\tvalidation_0-auc:0.93024\n[563]\tvalidation_0-auc:0.93023\n[564]\tvalidation_0-auc:0.93025\n[565]\tvalidation_0-auc:0.93024\n[566]\tvalidation_0-auc:0.93020\n[567]\tvalidation_0-auc:0.93016\n[568]\tvalidation_0-auc:0.93014\n[569]\tvalidation_0-auc:0.93022\n[570]\tvalidation_0-auc:0.93015\n[571]\tvalidation_0-auc:0.93018\n[572]\tvalidation_0-auc:0.93015\n[573]\tvalidation_0-auc:0.93016\n[574]\tvalidation_0-auc:0.93015\n[575]\tvalidation_0-auc:0.93013\n[576]\tvalidation_0-auc:0.93013\n[577]\tvalidation_0-auc:0.93013\n[578]\tvalidation_0-auc:0.93008\n[579]\tvalidation_0-auc:0.92997\n[580]\tvalidation_0-auc:0.92997\n[581]\tvalidation_0-auc:0.92997\n[582]\tvalidation_0-auc:0.92994\n[583]\tvalidation_0-auc:0.92996\n[584]\tvalidation_0-auc:0.92995\n[585]\tvalidation_0-auc:0.92998\n[586]\tvalidation_0-auc:0.92996\n[587]\tvalidation_0-auc:0.92996\n[588]\tvalidation_0-auc:0.92992\n[589]\tvalidation_0-auc:0.92992\n[590]\tvalidation_0-auc:0.92994\n[591]\tvalidation_0-auc:0.92993\n[592]\tvalidation_0-auc:0.92995\n[593]\tvalidation_0-auc:0.92996\n[594]\tvalidation_0-auc:0.92994\n[595]\tvalidation_0-auc:0.92999\n[596]\tvalidation_0-auc:0.92997\n[597]\tvalidation_0-auc:0.93000\n[598]\tvalidation_0-auc:0.92999\n[599]\tvalidation_0-auc:0.93000\n[600]\tvalidation_0-auc:0.93001\n[601]\tvalidation_0-auc:0.92998\n[602]\tvalidation_0-auc:0.93001\n[603]\tvalidation_0-auc:0.93000\n[604]\tvalidation_0-auc:0.93000\n[605]\tvalidation_0-auc:0.93000\n[606]\tvalidation_0-auc:0.92997\n[607]\tvalidation_0-auc:0.92996\n[608]\tvalidation_0-auc:0.92995\n[609]\tvalidation_0-auc:0.92996\n[610]\tvalidation_0-auc:0.92994\n[611]\tvalidation_0-auc:0.92993\n[612]\tvalidation_0-auc:0.92994\n[613]\tvalidation_0-auc:0.92993\n[614]\tvalidation_0-auc:0.93001\n[615]\tvalidation_0-auc:0.93001\n[616]\tvalidation_0-auc:0.92999\n[617]\tvalidation_0-auc:0.92999\n[618]\tvalidation_0-auc:0.92998\n[619]\tvalidation_0-auc:0.93000\n[620]\tvalidation_0-auc:0.92997\n[621]\tvalidation_0-auc:0.92996\n[622]\tvalidation_0-auc:0.92995\n[623]\tvalidation_0-auc:0.92993\n[624]\tvalidation_0-auc:0.92996\n[625]\tvalidation_0-auc:0.92995\n[626]\tvalidation_0-auc:0.92995\n[627]\tvalidation_0-auc:0.92994\n[628]\tvalidation_0-auc:0.92993\n[629]\tvalidation_0-auc:0.92994\n[630]\tvalidation_0-auc:0.92994\n[631]\tvalidation_0-auc:0.92999\n[632]\tvalidation_0-auc:0.92998\n[633]\tvalidation_0-auc:0.92999\n[634]\tvalidation_0-auc:0.92997\n[635]\tvalidation_0-auc:0.92999\n[636]\tvalidation_0-auc:0.93000\n[637]\tvalidation_0-auc:0.93003\n[638]\tvalidation_0-auc:0.93004\n[639]\tvalidation_0-auc:0.93003\n[640]\tvalidation_0-auc:0.93003\n[641]\tvalidation_0-auc:0.92998\n[642]\tvalidation_0-auc:0.92994\n[643]\tvalidation_0-auc:0.92996\n[644]\tvalidation_0-auc:0.92996\n[645]\tvalidation_0-auc:0.92995\n[646]\tvalidation_0-auc:0.92992\n[647]\tvalidation_0-auc:0.92993\n[0]\tvalidation_0-auc:0.86701\n[1]\tvalidation_0-auc:0.87891\n[2]\tvalidation_0-auc:0.89505\n[3]\tvalidation_0-auc:0.90440\n[4]\tvalidation_0-auc:0.90702\n[5]\tvalidation_0-auc:0.90887\n[6]\tvalidation_0-auc:0.90934\n[7]\tvalidation_0-auc:0.91298\n[8]\tvalidation_0-auc:0.91290\n[9]\tvalidation_0-auc:0.91572\n[10]\tvalidation_0-auc:0.91688\n"},{"name":"stderr","output_type":"stream","text":["E:\\Anaconda3\\lib\\site-packages\\xgboost\\sklearn.py:797: UserWarning: `eval_metric` in `fit` method is deprecated for better compatibility with scikit-learn, use `eval_metric` in constructor or`set_params` instead.\n"," UserWarning,\n","E:\\Anaconda3\\lib\\site-packages\\xgboost\\sklearn.py:797: UserWarning: `early_stopping_rounds` in `fit` method is deprecated for better compatibility with scikit-learn, use `early_stopping_rounds` in constructor or`set_params` instead.\n"," UserWarning,\n"]},{"name":"stdout","output_type":"stream","text":"[11]\tvalidation_0-auc:0.91640\n[12]\tvalidation_0-auc:0.91649\n[13]\tvalidation_0-auc:0.91567\n[14]\tvalidation_0-auc:0.91686\n[15]\tvalidation_0-auc:0.91657\n[16]\tvalidation_0-auc:0.91638\n[17]\tvalidation_0-auc:0.91766\n[18]\tvalidation_0-auc:0.91773\n[19]\tvalidation_0-auc:0.91769\n[20]\tvalidation_0-auc:0.91741\n[21]\tvalidation_0-auc:0.91777\n[22]\tvalidation_0-auc:0.91795\n[23]\tvalidation_0-auc:0.91779\n[24]\tvalidation_0-auc:0.91799\n[25]\tvalidation_0-auc:0.91792\n[26]\tvalidation_0-auc:0.91767\n[27]\tvalidation_0-auc:0.91750\n[28]\tvalidation_0-auc:0.91767\n[29]\tvalidation_0-auc:0.91753\n[30]\tvalidation_0-auc:0.91849\n[31]\tvalidation_0-auc:0.91840\n[32]\tvalidation_0-auc:0.91850\n[33]\tvalidation_0-auc:0.91938\n[34]\tvalidation_0-auc:0.91975\n[35]\tvalidation_0-auc:0.91945\n[36]\tvalidation_0-auc:0.91969\n[37]\tvalidation_0-auc:0.91947\n[38]\tvalidation_0-auc:0.91946\n[39]\tvalidation_0-auc:0.91965\n[40]\tvalidation_0-auc:0.92008\n[41]\tvalidation_0-auc:0.92049\n[42]\tvalidation_0-auc:0.92055\n[43]\tvalidation_0-auc:0.92052\n[44]\tvalidation_0-auc:0.92039\n[45]\tvalidation_0-auc:0.92074\n[46]\tvalidation_0-auc:0.92098\n[47]\tvalidation_0-auc:0.92105\n[48]\tvalidation_0-auc:0.92125\n[49]\tvalidation_0-auc:0.92137\n[50]\tvalidation_0-auc:0.92198\n[51]\tvalidation_0-auc:0.92203\n[52]\tvalidation_0-auc:0.92201\n[53]\tvalidation_0-auc:0.92221\n[54]\tvalidation_0-auc:0.92233\n[55]\tvalidation_0-auc:0.92231\n[56]\tvalidation_0-auc:0.92225\n[57]\tvalidation_0-auc:0.92228\n[58]\tvalidation_0-auc:0.92240\n[59]\tvalidation_0-auc:0.92259\n[60]\tvalidation_0-auc:0.92284\n[61]\tvalidation_0-auc:0.92299\n[62]\tvalidation_0-auc:0.92302\n[63]\tvalidation_0-auc:0.92323\n[64]\tvalidation_0-auc:0.92317\n[65]\tvalidation_0-auc:0.92309\n[66]\tvalidation_0-auc:0.92307\n[67]\tvalidation_0-auc:0.92310\n[68]\tvalidation_0-auc:0.92310\n[69]\tvalidation_0-auc:0.92314\n[70]\tvalidation_0-auc:0.92313\n[71]\tvalidation_0-auc:0.92299\n[72]\tvalidation_0-auc:0.92299\n[73]\tvalidation_0-auc:0.92307\n[74]\tvalidation_0-auc:0.92291\n[75]\tvalidation_0-auc:0.92332\n[76]\tvalidation_0-auc:0.92338\n[77]\tvalidation_0-auc:0.92343\n[78]\tvalidation_0-auc:0.92346\n[79]\tvalidation_0-auc:0.92357\n[80]\tvalidation_0-auc:0.92361\n[81]\tvalidation_0-auc:0.92361\n[82]\tvalidation_0-auc:0.92361\n[83]\tvalidation_0-auc:0.92369\n[84]\tvalidation_0-auc:0.92362\n[85]\tvalidation_0-auc:0.92363\n[86]\tvalidation_0-auc:0.92362\n[87]\tvalidation_0-auc:0.92371\n[88]\tvalidation_0-auc:0.92363\n[89]\tvalidation_0-auc:0.92372\n[90]\tvalidation_0-auc:0.92375\n[91]\tvalidation_0-auc:0.92381\n[92]\tvalidation_0-auc:0.92383\n[93]\tvalidation_0-auc:0.92385\n[94]\tvalidation_0-auc:0.92390\n[95]\tvalidation_0-auc:0.92394\n[96]\tvalidation_0-auc:0.92397\n[97]\tvalidation_0-auc:0.92401\n[98]\tvalidation_0-auc:0.92404\n[99]\tvalidation_0-auc:0.92399\n[100]\tvalidation_0-auc:0.92407\n[101]\tvalidation_0-auc:0.92416\n[102]\tvalidation_0-auc:0.92409\n[103]\tvalidation_0-auc:0.92418\n[104]\tvalidation_0-auc:0.92412\n[105]\tvalidation_0-auc:0.92404\n[106]\tvalidation_0-auc:0.92411\n[107]\tvalidation_0-auc:0.92412\n[108]\tvalidation_0-auc:0.92424\n[109]\tvalidation_0-auc:0.92416\n[110]\tvalidation_0-auc:0.92418\n[111]\tvalidation_0-auc:0.92417\n[112]\tvalidation_0-auc:0.92417\n[113]\tvalidation_0-auc:0.92422\n[114]\tvalidation_0-auc:0.92434\n[115]\tvalidation_0-auc:0.92428\n[116]\tvalidation_0-auc:0.92439\n[117]\tvalidation_0-auc:0.92440\n[118]\tvalidation_0-auc:0.92439\n[119]\tvalidation_0-auc:0.92445\n[120]\tvalidation_0-auc:0.92448\n[121]\tvalidation_0-auc:0.92457\n[122]\tvalidation_0-auc:0.92461\n[123]\tvalidation_0-auc:0.92462\n[124]\tvalidation_0-auc:0.92455\n[125]\tvalidation_0-auc:0.92466\n[126]\tvalidation_0-auc:0.92471\n[127]\tvalidation_0-auc:0.92470\n[128]\tvalidation_0-auc:0.92474\n[129]\tvalidation_0-auc:0.92473\n[130]\tvalidation_0-auc:0.92470\n[131]\tvalidation_0-auc:0.92488\n[132]\tvalidation_0-auc:0.92487\n[133]\tvalidation_0-auc:0.92488\n[134]\tvalidation_0-auc:0.92483\n[135]\tvalidation_0-auc:0.92490\n[136]\tvalidation_0-auc:0.92490\n[137]\tvalidation_0-auc:0.92486\n[138]\tvalidation_0-auc:0.92487\n[139]\tvalidation_0-auc:0.92490\n[140]\tvalidation_0-auc:0.92493\n[141]\tvalidation_0-auc:0.92494\n[142]\tvalidation_0-auc:0.92493\n[143]\tvalidation_0-auc:0.92497\n[144]\tvalidation_0-auc:0.92494\n[145]\tvalidation_0-auc:0.92499\n[146]\tvalidation_0-auc:0.92500\n[147]\tvalidation_0-auc:0.92503\n[148]\tvalidation_0-auc:0.92504\n[149]\tvalidation_0-auc:0.92502\n[150]\tvalidation_0-auc:0.92504\n[151]\tvalidation_0-auc:0.92505\n[152]\tvalidation_0-auc:0.92503\n[153]\tvalidation_0-auc:0.92507\n[154]\tvalidation_0-auc:0.92503\n[155]\tvalidation_0-auc:0.92501\n[156]\tvalidation_0-auc:0.92505\n[157]\tvalidation_0-auc:0.92505\n[158]\tvalidation_0-auc:0.92508\n[159]\tvalidation_0-auc:0.92512\n[160]\tvalidation_0-auc:0.92510\n[161]\tvalidation_0-auc:0.92509\n[162]\tvalidation_0-auc:0.92515\n[163]\tvalidation_0-auc:0.92522\n[164]\tvalidation_0-auc:0.92521\n[165]\tvalidation_0-auc:0.92523\n[166]\tvalidation_0-auc:0.92522\n[167]\tvalidation_0-auc:0.92522\n[168]\tvalidation_0-auc:0.92519\n[169]\tvalidation_0-auc:0.92518\n[170]\tvalidation_0-auc:0.92518\n[171]\tvalidation_0-auc:0.92527\n[172]\tvalidation_0-auc:0.92524\n[173]\tvalidation_0-auc:0.92529\n[174]\tvalidation_0-auc:0.92532\n[175]\tvalidation_0-auc:0.92534\n[176]\tvalidation_0-auc:0.92535\n[177]\tvalidation_0-auc:0.92539\n[178]\tvalidation_0-auc:0.92545\n[179]\tvalidation_0-auc:0.92551\n[180]\tvalidation_0-auc:0.92545\n[181]\tvalidation_0-auc:0.92545\n[182]\tvalidation_0-auc:0.92543\n[183]\tvalidation_0-auc:0.92548\n[184]\tvalidation_0-auc:0.92553\n[185]\tvalidation_0-auc:0.92548\n[186]\tvalidation_0-auc:0.92552\n[187]\tvalidation_0-auc:0.92553\n[188]\tvalidation_0-auc:0.92552\n[189]\tvalidation_0-auc:0.92552\n[190]\tvalidation_0-auc:0.92558\n[191]\tvalidation_0-auc:0.92556\n[192]\tvalidation_0-auc:0.92560\n[193]\tvalidation_0-auc:0.92560\n[194]\tvalidation_0-auc:0.92565\n[195]\tvalidation_0-auc:0.92567\n[196]\tvalidation_0-auc:0.92569\n[197]\tvalidation_0-auc:0.92571\n[198]\tvalidation_0-auc:0.92573\n[199]\tvalidation_0-auc:0.92574\n[200]\tvalidation_0-auc:0.92574\n[201]\tvalidation_0-auc:0.92580\n[202]\tvalidation_0-auc:0.92588\n[203]\tvalidation_0-auc:0.92586\n[204]\tvalidation_0-auc:0.92590\n[205]\tvalidation_0-auc:0.92597\n[206]\tvalidation_0-auc:0.92600\n[207]\tvalidation_0-auc:0.92598\n[208]\tvalidation_0-auc:0.92595\n[209]\tvalidation_0-auc:0.92598\n[210]\tvalidation_0-auc:0.92593\n[211]\tvalidation_0-auc:0.92597\n[212]\tvalidation_0-auc:0.92592\n[213]\tvalidation_0-auc:0.92590\n[214]\tvalidation_0-auc:0.92599\n[215]\tvalidation_0-auc:0.92599\n[216]\tvalidation_0-auc:0.92600\n[217]\tvalidation_0-auc:0.92602\n[218]\tvalidation_0-auc:0.92607\n[219]\tvalidation_0-auc:0.92610\n[220]\tvalidation_0-auc:0.92611\n[221]\tvalidation_0-auc:0.92613\n[222]\tvalidation_0-auc:0.92614\n[223]\tvalidation_0-auc:0.92619\n[224]\tvalidation_0-auc:0.92618\n[225]\tvalidation_0-auc:0.92618\n[226]\tvalidation_0-auc:0.92627\n[227]\tvalidation_0-auc:0.92625\n[228]\tvalidation_0-auc:0.92629\n[229]\tvalidation_0-auc:0.92630\n[230]\tvalidation_0-auc:0.92633\n[231]\tvalidation_0-auc:0.92636\n[232]\tvalidation_0-auc:0.92639\n[233]\tvalidation_0-auc:0.92637\n[234]\tvalidation_0-auc:0.92645\n[235]\tvalidation_0-auc:0.92645\n[236]\tvalidation_0-auc:0.92644\n[237]\tvalidation_0-auc:0.92646\n[238]\tvalidation_0-auc:0.92644\n[239]\tvalidation_0-auc:0.92647\n[240]\tvalidation_0-auc:0.92650\n[241]\tvalidation_0-auc:0.92648\n[242]\tvalidation_0-auc:0.92646\n[243]\tvalidation_0-auc:0.92651\n[244]\tvalidation_0-auc:0.92653\n[245]\tvalidation_0-auc:0.92651\n[246]\tvalidation_0-auc:0.92654\n[247]\tvalidation_0-auc:0.92659\n[248]\tvalidation_0-auc:0.92656\n[249]\tvalidation_0-auc:0.92658\n[250]\tvalidation_0-auc:0.92658\n[251]\tvalidation_0-auc:0.92662\n[252]\tvalidation_0-auc:0.92663\n[253]\tvalidation_0-auc:0.92663\n[254]\tvalidation_0-auc:0.92663\n[255]\tvalidation_0-auc:0.92664\n[256]\tvalidation_0-auc:0.92664\n[257]\tvalidation_0-auc:0.92671\n[258]\tvalidation_0-auc:0.92672\n[259]\tvalidation_0-auc:0.92673\n[260]\tvalidation_0-auc:0.92671\n[261]\tvalidation_0-auc:0.92672\n[262]\tvalidation_0-auc:0.92675\n[263]\tvalidation_0-auc:0.92680\n[264]\tvalidation_0-auc:0.92680\n[265]\tvalidation_0-auc:0.92679\n[266]\tvalidation_0-auc:0.92679\n[267]\tvalidation_0-auc:0.92683\n[268]\tvalidation_0-auc:0.92686\n[269]\tvalidation_0-auc:0.92685\n[270]\tvalidation_0-auc:0.92684\n[271]\tvalidation_0-auc:0.92685\n[272]\tvalidation_0-auc:0.92683\n[273]\tvalidation_0-auc:0.92686\n[274]\tvalidation_0-auc:0.92688\n[275]\tvalidation_0-auc:0.92688\n[276]\tvalidation_0-auc:0.92687\n[277]\tvalidation_0-auc:0.92690\n[278]\tvalidation_0-auc:0.92693\n[279]\tvalidation_0-auc:0.92693\n[280]\tvalidation_0-auc:0.92693\n[281]\tvalidation_0-auc:0.92693\n[282]\tvalidation_0-auc:0.92692\n[283]\tvalidation_0-auc:0.92699\n[284]\tvalidation_0-auc:0.92703\n[285]\tvalidation_0-auc:0.92702\n[286]\tvalidation_0-auc:0.92700\n[287]\tvalidation_0-auc:0.92701\n[288]\tvalidation_0-auc:0.92703\n[289]\tvalidation_0-auc:0.92703\n[290]\tvalidation_0-auc:0.92703\n[291]\tvalidation_0-auc:0.92702\n[292]\tvalidation_0-auc:0.92701\n[293]\tvalidation_0-auc:0.92699\n[294]\tvalidation_0-auc:0.92699\n[295]\tvalidation_0-auc:0.92698\n[296]\tvalidation_0-auc:0.92698\n[297]\tvalidation_0-auc:0.92699\n[298]\tvalidation_0-auc:0.92704\n[299]\tvalidation_0-auc:0.92705\n[300]\tvalidation_0-auc:0.92706\n[301]\tvalidation_0-auc:0.92708\n[302]\tvalidation_0-auc:0.92710\n[303]\tvalidation_0-auc:0.92711\n[304]\tvalidation_0-auc:0.92715\n[305]\tvalidation_0-auc:0.92718\n[306]\tvalidation_0-auc:0.92714\n[307]\tvalidation_0-auc:0.92716\n[308]\tvalidation_0-auc:0.92713\n[309]\tvalidation_0-auc:0.92713\n[310]\tvalidation_0-auc:0.92714\n[311]\tvalidation_0-auc:0.92715\n[312]\tvalidation_0-auc:0.92712\n[313]\tvalidation_0-auc:0.92710\n[314]\tvalidation_0-auc:0.92709\n[315]\tvalidation_0-auc:0.92717\n[316]\tvalidation_0-auc:0.92715\n[317]\tvalidation_0-auc:0.92716\n[318]\tvalidation_0-auc:0.92717\n[319]\tvalidation_0-auc:0.92718\n[320]\tvalidation_0-auc:0.92717\n[321]\tvalidation_0-auc:0.92722\n[322]\tvalidation_0-auc:0.92718\n[323]\tvalidation_0-auc:0.92720\n[324]\tvalidation_0-auc:0.92722\n[325]\tvalidation_0-auc:0.92718\n[326]\tvalidation_0-auc:0.92717\n[327]\tvalidation_0-auc:0.92715\n[328]\tvalidation_0-auc:0.92715\n[329]\tvalidation_0-auc:0.92716\n[330]\tvalidation_0-auc:0.92721\n[331]\tvalidation_0-auc:0.92721\n[332]\tvalidation_0-auc:0.92722\n[333]\tvalidation_0-auc:0.92721\n[334]\tvalidation_0-auc:0.92722\n[335]\tvalidation_0-auc:0.92725\n[336]\tvalidation_0-auc:0.92726\n[337]\tvalidation_0-auc:0.92724\n[338]\tvalidation_0-auc:0.92724\n[339]\tvalidation_0-auc:0.92722\n[340]\tvalidation_0-auc:0.92724\n[341]\tvalidation_0-auc:0.92728\n[342]\tvalidation_0-auc:0.92727\n[343]\tvalidation_0-auc:0.92725\n[344]\tvalidation_0-auc:0.92724\n[345]\tvalidation_0-auc:0.92732\n[346]\tvalidation_0-auc:0.92736\n[347]\tvalidation_0-auc:0.92735\n[348]\tvalidation_0-auc:0.92736\n[349]\tvalidation_0-auc:0.92732\n[350]\tvalidation_0-auc:0.92732\n[351]\tvalidation_0-auc:0.92734\n[352]\tvalidation_0-auc:0.92735\n[353]\tvalidation_0-auc:0.92732\n[354]\tvalidation_0-auc:0.92731\n[355]\tvalidation_0-auc:0.92735\n[356]\tvalidation_0-auc:0.92737\n[357]\tvalidation_0-auc:0.92745\n[358]\tvalidation_0-auc:0.92742\n[359]\tvalidation_0-auc:0.92741\n[360]\tvalidation_0-auc:0.92737\n[361]\tvalidation_0-auc:0.92732\n[362]\tvalidation_0-auc:0.92736\n[363]\tvalidation_0-auc:0.92736\n[364]\tvalidation_0-auc:0.92735\n[365]\tvalidation_0-auc:0.92739\n[366]\tvalidation_0-auc:0.92738\n[367]\tvalidation_0-auc:0.92741\n[368]\tvalidation_0-auc:0.92740\n[369]\tvalidation_0-auc:0.92742\n[370]\tvalidation_0-auc:0.92743\n[371]\tvalidation_0-auc:0.92744\n[372]\tvalidation_0-auc:0.92745\n[373]\tvalidation_0-auc:0.92747\n[374]\tvalidation_0-auc:0.92749\n[375]\tvalidation_0-auc:0.92749\n[376]\tvalidation_0-auc:0.92748\n[377]\tvalidation_0-auc:0.92752\n[378]\tvalidation_0-auc:0.92749\n[379]\tvalidation_0-auc:0.92753\n[380]\tvalidation_0-auc:0.92754\n[381]\tvalidation_0-auc:0.92751\n[382]\tvalidation_0-auc:0.92752\n[383]\tvalidation_0-auc:0.92752\n[384]\tvalidation_0-auc:0.92752\n[385]\tvalidation_0-auc:0.92754\n[386]\tvalidation_0-auc:0.92755\n[387]\tvalidation_0-auc:0.92755\n[388]\tvalidation_0-auc:0.92754\n[389]\tvalidation_0-auc:0.92753\n[390]\tvalidation_0-auc:0.92754\n[391]\tvalidation_0-auc:0.92753\n[392]\tvalidation_0-auc:0.92753\n[393]\tvalidation_0-auc:0.92755\n[394]\tvalidation_0-auc:0.92755\n[395]\tvalidation_0-auc:0.92753\n[396]\tvalidation_0-auc:0.92752\n[397]\tvalidation_0-auc:0.92752\n[398]\tvalidation_0-auc:0.92755\n[399]\tvalidation_0-auc:0.92755\n[400]\tvalidation_0-auc:0.92756\n[401]\tvalidation_0-auc:0.92758\n[402]\tvalidation_0-auc:0.92757\n[403]\tvalidation_0-auc:0.92755\n[404]\tvalidation_0-auc:0.92756\n[405]\tvalidation_0-auc:0.92756\n[406]\tvalidation_0-auc:0.92751\n[407]\tvalidation_0-auc:0.92756\n[408]\tvalidation_0-auc:0.92756\n[409]\tvalidation_0-auc:0.92756\n[410]\tvalidation_0-auc:0.92753\n[411]\tvalidation_0-auc:0.92753\n[412]\tvalidation_0-auc:0.92751\n[413]\tvalidation_0-auc:0.92752\n[414]\tvalidation_0-auc:0.92753\n[415]\tvalidation_0-auc:0.92751\n[416]\tvalidation_0-auc:0.92752\n[417]\tvalidation_0-auc:0.92750\n[418]\tvalidation_0-auc:0.92752\n[419]\tvalidation_0-auc:0.92751\n[420]\tvalidation_0-auc:0.92752\n[421]\tvalidation_0-auc:0.92751\n[422]\tvalidation_0-auc:0.92751\n[423]\tvalidation_0-auc:0.92753\n[424]\tvalidation_0-auc:0.92756\n[425]\tvalidation_0-auc:0.92755\n[426]\tvalidation_0-auc:0.92757\n[427]\tvalidation_0-auc:0.92760\n[428]\tvalidation_0-auc:0.92760\n[429]\tvalidation_0-auc:0.92761\n[430]\tvalidation_0-auc:0.92759\n[431]\tvalidation_0-auc:0.92764\n[432]\tvalidation_0-auc:0.92763\n[433]\tvalidation_0-auc:0.92761\n[434]\tvalidation_0-auc:0.92764\n[435]\tvalidation_0-auc:0.92766\n[436]\tvalidation_0-auc:0.92768\n[437]\tvalidation_0-auc:0.92767\n[438]\tvalidation_0-auc:0.92766\n[439]\tvalidation_0-auc:0.92763\n[440]\tvalidation_0-auc:0.92767\n[441]\tvalidation_0-auc:0.92767\n[442]\tvalidation_0-auc:0.92766\n[443]\tvalidation_0-auc:0.92766\n[444]\tvalidation_0-auc:0.92762\n[445]\tvalidation_0-auc:0.92760\n[446]\tvalidation_0-auc:0.92759\n[447]\tvalidation_0-auc:0.92760\n[448]\tvalidation_0-auc:0.92761\n[449]\tvalidation_0-auc:0.92758\n[450]\tvalidation_0-auc:0.92760\n[451]\tvalidation_0-auc:0.92760\n[452]\tvalidation_0-auc:0.92762\n[453]\tvalidation_0-auc:0.92764\n[454]\tvalidation_0-auc:0.92765\n[455]\tvalidation_0-auc:0.92767\n[456]\tvalidation_0-auc:0.92767\n[457]\tvalidation_0-auc:0.92772\n[458]\tvalidation_0-auc:0.92776\n[459]\tvalidation_0-auc:0.92776\n[460]\tvalidation_0-auc:0.92777\n[461]\tvalidation_0-auc:0.92780\n[462]\tvalidation_0-auc:0.92779\n[463]\tvalidation_0-auc:0.92777\n[464]\tvalidation_0-auc:0.92781\n[465]\tvalidation_0-auc:0.92781\n[466]\tvalidation_0-auc:0.92783\n[467]\tvalidation_0-auc:0.92781\n[468]\tvalidation_0-auc:0.92779\n[469]\tvalidation_0-auc:0.92783\n[470]\tvalidation_0-auc:0.92782\n[471]\tvalidation_0-auc:0.92785\n[472]\tvalidation_0-auc:0.92782\n[473]\tvalidation_0-auc:0.92780\n[474]\tvalidation_0-auc:0.92781\n[475]\tvalidation_0-auc:0.92781\n[476]\tvalidation_0-auc:0.92780\n[477]\tvalidation_0-auc:0.92783\n[478]\tvalidation_0-auc:0.92782\n[479]\tvalidation_0-auc:0.92782\n[480]\tvalidation_0-auc:0.92786\n[481]\tvalidation_0-auc:0.92785\n[482]\tvalidation_0-auc:0.92786\n[483]\tvalidation_0-auc:0.92786\n[484]\tvalidation_0-auc:0.92785\n[485]\tvalidation_0-auc:0.92784\n[486]\tvalidation_0-auc:0.92784\n[487]\tvalidation_0-auc:0.92783\n[488]\tvalidation_0-auc:0.92782\n[489]\tvalidation_0-auc:0.92781\n[490]\tvalidation_0-auc:0.92780\n[491]\tvalidation_0-auc:0.92778\n[492]\tvalidation_0-auc:0.92781\n[493]\tvalidation_0-auc:0.92785\n[494]\tvalidation_0-auc:0.92782\n[495]\tvalidation_0-auc:0.92783\n[496]\tvalidation_0-auc:0.92786\n[497]\tvalidation_0-auc:0.92785\n[498]\tvalidation_0-auc:0.92784\n[499]\tvalidation_0-auc:0.92785\n[500]\tvalidation_0-auc:0.92784\n[501]\tvalidation_0-auc:0.92784\n[502]\tvalidation_0-auc:0.92787\n[503]\tvalidation_0-auc:0.92792\n[504]\tvalidation_0-auc:0.92793\n[505]\tvalidation_0-auc:0.92796\n[506]\tvalidation_0-auc:0.92795\n[507]\tvalidation_0-auc:0.92796\n[508]\tvalidation_0-auc:0.92796\n[509]\tvalidation_0-auc:0.92797\n[510]\tvalidation_0-auc:0.92793\n[511]\tvalidation_0-auc:0.92794\n[512]\tvalidation_0-auc:0.92793\n[513]\tvalidation_0-auc:0.92794\n[514]\tvalidation_0-auc:0.92793\n[515]\tvalidation_0-auc:0.92797\n[516]\tvalidation_0-auc:0.92797\n[517]\tvalidation_0-auc:0.92798\n[518]\tvalidation_0-auc:0.92798\n[519]\tvalidation_0-auc:0.92797\n[520]\tvalidation_0-auc:0.92795\n[521]\tvalidation_0-auc:0.92795\n[522]\tvalidation_0-auc:0.92798\n[523]\tvalidation_0-auc:0.92798\n[524]\tvalidation_0-auc:0.92795\n[525]\tvalidation_0-auc:0.92791\n[526]\tvalidation_0-auc:0.92788\n[527]\tvalidation_0-auc:0.92785\n[528]\tvalidation_0-auc:0.92785\n[529]\tvalidation_0-auc:0.92786\n[530]\tvalidation_0-auc:0.92789\n[531]\tvalidation_0-auc:0.92786\n[532]\tvalidation_0-auc:0.92785\n[533]\tvalidation_0-auc:0.92786\n[534]\tvalidation_0-auc:0.92786\n[535]\tvalidation_0-auc:0.92784\n[536]\tvalidation_0-auc:0.92783\n[537]\tvalidation_0-auc:0.92784\n[538]\tvalidation_0-auc:0.92783\n[539]\tvalidation_0-auc:0.92784\n[540]\tvalidation_0-auc:0.92783\n[541]\tvalidation_0-auc:0.92789\n[542]\tvalidation_0-auc:0.92792\n[543]\tvalidation_0-auc:0.92792\n[544]\tvalidation_0-auc:0.92792\n[545]\tvalidation_0-auc:0.92790\n[546]\tvalidation_0-auc:0.92788\n[547]\tvalidation_0-auc:0.92782\n[548]\tvalidation_0-auc:0.92781\n[549]\tvalidation_0-auc:0.92778\n[550]\tvalidation_0-auc:0.92778\n[551]\tvalidation_0-auc:0.92778\n[552]\tvalidation_0-auc:0.92776\n[553]\tvalidation_0-auc:0.92775\n[554]\tvalidation_0-auc:0.92771\n[555]\tvalidation_0-auc:0.92772\n[556]\tvalidation_0-auc:0.92770\n[557]\tvalidation_0-auc:0.92772\n[558]\tvalidation_0-auc:0.92772\n[559]\tvalidation_0-auc:0.92771\n[560]\tvalidation_0-auc:0.92768\n[561]\tvalidation_0-auc:0.92768\n[562]\tvalidation_0-auc:0.92768\n[563]\tvalidation_0-auc:0.92768\n[564]\tvalidation_0-auc:0.92769\n[565]\tvalidation_0-auc:0.92774\n[566]\tvalidation_0-auc:0.92779\n[567]\tvalidation_0-auc:0.92778\n[568]\tvalidation_0-auc:0.92781\n[569]\tvalidation_0-auc:0.92779\n[570]\tvalidation_0-auc:0.92776\n[571]\tvalidation_0-auc:0.92774\n[572]\tvalidation_0-auc:0.92772\n[573]\tvalidation_0-auc:0.92772\n[574]\tvalidation_0-auc:0.92771\n[575]\tvalidation_0-auc:0.92771\n[576]\tvalidation_0-auc:0.92775\n[577]\tvalidation_0-auc:0.92776\n[578]\tvalidation_0-auc:0.92776\n[579]\tvalidation_0-auc:0.92776\n[580]\tvalidation_0-auc:0.92776\n[581]\tvalidation_0-auc:0.92774\n[582]\tvalidation_0-auc:0.92770\n[583]\tvalidation_0-auc:0.92775\n[584]\tvalidation_0-auc:0.92769\n[585]\tvalidation_0-auc:0.92768\n[586]\tvalidation_0-auc:0.92770\n[587]\tvalidation_0-auc:0.92772\n[588]\tvalidation_0-auc:0.92772\n[589]\tvalidation_0-auc:0.92774\n[590]\tvalidation_0-auc:0.92772\n[591]\tvalidation_0-auc:0.92772\n[592]\tvalidation_0-auc:0.92771\n[593]\tvalidation_0-auc:0.92770\n[594]\tvalidation_0-auc:0.92769\n[595]\tvalidation_0-auc:0.92770\n[596]\tvalidation_0-auc:0.92769\n[597]\tvalidation_0-auc:0.92765\n[598]\tvalidation_0-auc:0.92763\n[599]\tvalidation_0-auc:0.92762\n[600]\tvalidation_0-auc:0.92761\n[601]\tvalidation_0-auc:0.92763\n[602]\tvalidation_0-auc:0.92763\n[603]\tvalidation_0-auc:0.92762\n[604]\tvalidation_0-auc:0.92758\n[605]\tvalidation_0-auc:0.92756\n[606]\tvalidation_0-auc:0.92757\n[607]\tvalidation_0-auc:0.92757\n[608]\tvalidation_0-auc:0.92756\n[609]\tvalidation_0-auc:0.92754\n[610]\tvalidation_0-auc:0.92753\n[611]\tvalidation_0-auc:0.92751\n[612]\tvalidation_0-auc:0.92757\n[613]\tvalidation_0-auc:0.92757\n[614]\tvalidation_0-auc:0.92760\n[615]\tvalidation_0-auc:0.92761\n[616]\tvalidation_0-auc:0.92760\n[617]\tvalidation_0-auc:0.92766\n[0]\tvalidation_0-auc:0.86082\n[1]\tvalidation_0-auc:0.87954\n[2]\tvalidation_0-auc:0.89021\n[3]\tvalidation_0-auc:0.88417\n[4]\tvalidation_0-auc:0.88310\n[5]\tvalidation_0-auc:0.90295\n[6]\tvalidation_0-auc:0.90830\n[7]\tvalidation_0-auc:0.90873\n[8]\tvalidation_0-auc:0.90841\n[9]\tvalidation_0-auc:0.91263\n[10]\tvalidation_0-auc:0.91663\n[11]\tvalidation_0-auc:0.91804\n"},{"name":"stderr","output_type":"stream","text":["E:\\Anaconda3\\lib\\site-packages\\xgboost\\sklearn.py:797: UserWarning: `eval_metric` in `fit` method is deprecated for better compatibility with scikit-learn, use `eval_metric` in constructor or`set_params` instead.\n"," UserWarning,\n","E:\\Anaconda3\\lib\\site-packages\\xgboost\\sklearn.py:797: UserWarning: `early_stopping_rounds` in `fit` method is deprecated for better compatibility with scikit-learn, use `early_stopping_rounds` in constructor or`set_params` instead.\n"," UserWarning,\n"]},{"name":"stdout","output_type":"stream","text":"[12]\tvalidation_0-auc:0.92002\n[13]\tvalidation_0-auc:0.92045\n[14]\tvalidation_0-auc:0.92028\n[15]\tvalidation_0-auc:0.92117\n[16]\tvalidation_0-auc:0.92060\n[17]\tvalidation_0-auc:0.92007\n[18]\tvalidation_0-auc:0.92012\n[19]\tvalidation_0-auc:0.92056\n[20]\tvalidation_0-auc:0.92115\n[21]\tvalidation_0-auc:0.92272\n[22]\tvalidation_0-auc:0.92302\n[23]\tvalidation_0-auc:0.92345\n[24]\tvalidation_0-auc:0.92380\n[25]\tvalidation_0-auc:0.92478\n[26]\tvalidation_0-auc:0.92474\n[27]\tvalidation_0-auc:0.92540\n[28]\tvalidation_0-auc:0.92551\n[29]\tvalidation_0-auc:0.92551\n[30]\tvalidation_0-auc:0.92604\n[31]\tvalidation_0-auc:0.92591\n[32]\tvalidation_0-auc:0.92639\n[33]\tvalidation_0-auc:0.92736\n[34]\tvalidation_0-auc:0.92697\n[35]\tvalidation_0-auc:0.92699\n[36]\tvalidation_0-auc:0.92696\n[37]\tvalidation_0-auc:0.92697\n[38]\tvalidation_0-auc:0.92672\n[39]\tvalidation_0-auc:0.92667\n[40]\tvalidation_0-auc:0.92712\n[41]\tvalidation_0-auc:0.92706\n[42]\tvalidation_0-auc:0.92704\n[43]\tvalidation_0-auc:0.92712\n[44]\tvalidation_0-auc:0.92666\n[45]\tvalidation_0-auc:0.92658\n[46]\tvalidation_0-auc:0.92653\n[47]\tvalidation_0-auc:0.92649\n[48]\tvalidation_0-auc:0.92651\n[49]\tvalidation_0-auc:0.92647\n[50]\tvalidation_0-auc:0.92653\n[51]\tvalidation_0-auc:0.92679\n[52]\tvalidation_0-auc:0.92676\n[53]\tvalidation_0-auc:0.92684\n[54]\tvalidation_0-auc:0.92712\n[55]\tvalidation_0-auc:0.92728\n[56]\tvalidation_0-auc:0.92727\n[57]\tvalidation_0-auc:0.92732\n[58]\tvalidation_0-auc:0.92721\n[59]\tvalidation_0-auc:0.92728\n[60]\tvalidation_0-auc:0.92753\n[61]\tvalidation_0-auc:0.92751\n[62]\tvalidation_0-auc:0.92750\n[63]\tvalidation_0-auc:0.92753\n[64]\tvalidation_0-auc:0.92756\n[65]\tvalidation_0-auc:0.92754\n[66]\tvalidation_0-auc:0.92760\n[67]\tvalidation_0-auc:0.92749\n[68]\tvalidation_0-auc:0.92738\n[69]\tvalidation_0-auc:0.92746\n[70]\tvalidation_0-auc:0.92767\n[71]\tvalidation_0-auc:0.92795\n[72]\tvalidation_0-auc:0.92798\n[73]\tvalidation_0-auc:0.92780\n[74]\tvalidation_0-auc:0.92772\n[75]\tvalidation_0-auc:0.92786\n[76]\tvalidation_0-auc:0.92789\n[77]\tvalidation_0-auc:0.92800\n[78]\tvalidation_0-auc:0.92822\n[79]\tvalidation_0-auc:0.92836\n[80]\tvalidation_0-auc:0.92846\n[81]\tvalidation_0-auc:0.92868\n[82]\tvalidation_0-auc:0.92875\n[83]\tvalidation_0-auc:0.92887\n[84]\tvalidation_0-auc:0.92901\n[85]\tvalidation_0-auc:0.92906\n[86]\tvalidation_0-auc:0.92900\n[87]\tvalidation_0-auc:0.92919\n[88]\tvalidation_0-auc:0.92927\n[89]\tvalidation_0-auc:0.92970\n[90]\tvalidation_0-auc:0.92981\n[91]\tvalidation_0-auc:0.92983\n[92]\tvalidation_0-auc:0.92990\n[93]\tvalidation_0-auc:0.93004\n[94]\tvalidation_0-auc:0.93023\n[95]\tvalidation_0-auc:0.93021\n[96]\tvalidation_0-auc:0.93024\n[97]\tvalidation_0-auc:0.93021\n[98]\tvalidation_0-auc:0.93031\n[99]\tvalidation_0-auc:0.93070\n[100]\tvalidation_0-auc:0.93070\n[101]\tvalidation_0-auc:0.93074\n[102]\tvalidation_0-auc:0.93070\n[103]\tvalidation_0-auc:0.93078\n[104]\tvalidation_0-auc:0.93084\n[105]\tvalidation_0-auc:0.93085\n[106]\tvalidation_0-auc:0.93093\n[107]\tvalidation_0-auc:0.93099\n[108]\tvalidation_0-auc:0.93100\n[109]\tvalidation_0-auc:0.93098\n[110]\tvalidation_0-auc:0.93103\n[111]\tvalidation_0-auc:0.93102\n[112]\tvalidation_0-auc:0.93098\n[113]\tvalidation_0-auc:0.93099\n[114]\tvalidation_0-auc:0.93110\n[115]\tvalidation_0-auc:0.93120\n[116]\tvalidation_0-auc:0.93124\n[117]\tvalidation_0-auc:0.93125\n[118]\tvalidation_0-auc:0.93125\n[119]\tvalidation_0-auc:0.93126\n[120]\tvalidation_0-auc:0.93118\n[121]\tvalidation_0-auc:0.93100\n[122]\tvalidation_0-auc:0.93099\n[123]\tvalidation_0-auc:0.93095\n[124]\tvalidation_0-auc:0.93089\n[125]\tvalidation_0-auc:0.93086\n[126]\tvalidation_0-auc:0.93080\n[127]\tvalidation_0-auc:0.93080\n[128]\tvalidation_0-auc:0.93080\n[129]\tvalidation_0-auc:0.93093\n[130]\tvalidation_0-auc:0.93098\n[131]\tvalidation_0-auc:0.93100\n[132]\tvalidation_0-auc:0.93099\n[133]\tvalidation_0-auc:0.93100\n[134]\tvalidation_0-auc:0.93098\n[135]\tvalidation_0-auc:0.93103\n[136]\tvalidation_0-auc:0.93130\n[137]\tvalidation_0-auc:0.93132\n[138]\tvalidation_0-auc:0.93144\n[139]\tvalidation_0-auc:0.93147\n[140]\tvalidation_0-auc:0.93146\n[141]\tvalidation_0-auc:0.93156\n[142]\tvalidation_0-auc:0.93160\n[143]\tvalidation_0-auc:0.93161\n[144]\tvalidation_0-auc:0.93164\n[145]\tvalidation_0-auc:0.93167\n[146]\tvalidation_0-auc:0.93171\n[147]\tvalidation_0-auc:0.93173\n[148]\tvalidation_0-auc:0.93172\n[149]\tvalidation_0-auc:0.93169\n[150]\tvalidation_0-auc:0.93164\n[151]\tvalidation_0-auc:0.93171\n[152]\tvalidation_0-auc:0.93168\n[153]\tvalidation_0-auc:0.93167\n[154]\tvalidation_0-auc:0.93169\n[155]\tvalidation_0-auc:0.93170\n[156]\tvalidation_0-auc:0.93171\n[157]\tvalidation_0-auc:0.93173\n[158]\tvalidation_0-auc:0.93180\n[159]\tvalidation_0-auc:0.93190\n[160]\tvalidation_0-auc:0.93205\n[161]\tvalidation_0-auc:0.93202\n[162]\tvalidation_0-auc:0.93211\n[163]\tvalidation_0-auc:0.93213\n[164]\tvalidation_0-auc:0.93217\n[165]\tvalidation_0-auc:0.93216\n[166]\tvalidation_0-auc:0.93220\n[167]\tvalidation_0-auc:0.93239\n[168]\tvalidation_0-auc:0.93237\n[169]\tvalidation_0-auc:0.93246\n[170]\tvalidation_0-auc:0.93248\n[171]\tvalidation_0-auc:0.93244\n[172]\tvalidation_0-auc:0.93249\n[173]\tvalidation_0-auc:0.93253\n[174]\tvalidation_0-auc:0.93261\n[175]\tvalidation_0-auc:0.93262\n[176]\tvalidation_0-auc:0.93257\n[177]\tvalidation_0-auc:0.93257\n[178]\tvalidation_0-auc:0.93250\n[179]\tvalidation_0-auc:0.93250\n[180]\tvalidation_0-auc:0.93253\n[181]\tvalidation_0-auc:0.93249\n[182]\tvalidation_0-auc:0.93252\n[183]\tvalidation_0-auc:0.93247\n[184]\tvalidation_0-auc:0.93252\n[185]\tvalidation_0-auc:0.93250\n[186]\tvalidation_0-auc:0.93255\n[187]\tvalidation_0-auc:0.93254\n[188]\tvalidation_0-auc:0.93253\n[189]\tvalidation_0-auc:0.93256\n[190]\tvalidation_0-auc:0.93268\n[191]\tvalidation_0-auc:0.93275\n[192]\tvalidation_0-auc:0.93281\n[193]\tvalidation_0-auc:0.93279\n[194]\tvalidation_0-auc:0.93285\n[195]\tvalidation_0-auc:0.93295\n[196]\tvalidation_0-auc:0.93298\n[197]\tvalidation_0-auc:0.93303\n[198]\tvalidation_0-auc:0.93302\n[199]\tvalidation_0-auc:0.93316\n[200]\tvalidation_0-auc:0.93316\n[201]\tvalidation_0-auc:0.93319\n[202]\tvalidation_0-auc:0.93325\n[203]\tvalidation_0-auc:0.93320\n[204]\tvalidation_0-auc:0.93326\n[205]\tvalidation_0-auc:0.93321\n[206]\tvalidation_0-auc:0.93333\n[207]\tvalidation_0-auc:0.93339\n[208]\tvalidation_0-auc:0.93337\n[209]\tvalidation_0-auc:0.93341\n[210]\tvalidation_0-auc:0.93339\n[211]\tvalidation_0-auc:0.93338\n[212]\tvalidation_0-auc:0.93340\n[213]\tvalidation_0-auc:0.93344\n[214]\tvalidation_0-auc:0.93348\n[215]\tvalidation_0-auc:0.93346\n[216]\tvalidation_0-auc:0.93343\n[217]\tvalidation_0-auc:0.93342\n[218]\tvalidation_0-auc:0.93347\n[219]\tvalidation_0-auc:0.93349\n[220]\tvalidation_0-auc:0.93349\n[221]\tvalidation_0-auc:0.93350\n[222]\tvalidation_0-auc:0.93350\n[223]\tvalidation_0-auc:0.93359\n[224]\tvalidation_0-auc:0.93359\n[225]\tvalidation_0-auc:0.93363\n[226]\tvalidation_0-auc:0.93368\n[227]\tvalidation_0-auc:0.93375\n[228]\tvalidation_0-auc:0.93377\n[229]\tvalidation_0-auc:0.93376\n[230]\tvalidation_0-auc:0.93378\n[231]\tvalidation_0-auc:0.93388\n[232]\tvalidation_0-auc:0.93389\n[233]\tvalidation_0-auc:0.93389\n[234]\tvalidation_0-auc:0.93385\n[235]\tvalidation_0-auc:0.93394\n[236]\tvalidation_0-auc:0.93399\n[237]\tvalidation_0-auc:0.93407\n[238]\tvalidation_0-auc:0.93407\n[239]\tvalidation_0-auc:0.93407\n[240]\tvalidation_0-auc:0.93406\n[241]\tvalidation_0-auc:0.93412\n[242]\tvalidation_0-auc:0.93411\n[243]\tvalidation_0-auc:0.93424\n[244]\tvalidation_0-auc:0.93422\n[245]\tvalidation_0-auc:0.93421\n[246]\tvalidation_0-auc:0.93422\n[247]\tvalidation_0-auc:0.93431\n[248]\tvalidation_0-auc:0.93426\n[249]\tvalidation_0-auc:0.93423\n[250]\tvalidation_0-auc:0.93425\n[251]\tvalidation_0-auc:0.93431\n[252]\tvalidation_0-auc:0.93434\n[253]\tvalidation_0-auc:0.93439\n[254]\tvalidation_0-auc:0.93439\n[255]\tvalidation_0-auc:0.93443\n[256]\tvalidation_0-auc:0.93445\n[257]\tvalidation_0-auc:0.93448\n[258]\tvalidation_0-auc:0.93445\n[259]\tvalidation_0-auc:0.93446\n[260]\tvalidation_0-auc:0.93451\n[261]\tvalidation_0-auc:0.93451\n[262]\tvalidation_0-auc:0.93457\n[263]\tvalidation_0-auc:0.93454\n[264]\tvalidation_0-auc:0.93453\n[265]\tvalidation_0-auc:0.93455\n[266]\tvalidation_0-auc:0.93453\n[267]\tvalidation_0-auc:0.93452\n[268]\tvalidation_0-auc:0.93454\n[269]\tvalidation_0-auc:0.93458\n[270]\tvalidation_0-auc:0.93458\n[271]\tvalidation_0-auc:0.93452\n[272]\tvalidation_0-auc:0.93454\n[273]\tvalidation_0-auc:0.93454\n[274]\tvalidation_0-auc:0.93451\n[275]\tvalidation_0-auc:0.93456\n[276]\tvalidation_0-auc:0.93463\n[277]\tvalidation_0-auc:0.93470\n[278]\tvalidation_0-auc:0.93471\n[279]\tvalidation_0-auc:0.93477\n[280]\tvalidation_0-auc:0.93481\n[281]\tvalidation_0-auc:0.93486\n[282]\tvalidation_0-auc:0.93486\n[283]\tvalidation_0-auc:0.93487\n[284]\tvalidation_0-auc:0.93488\n[285]\tvalidation_0-auc:0.93484\n[286]\tvalidation_0-auc:0.93486\n[287]\tvalidation_0-auc:0.93485\n[288]\tvalidation_0-auc:0.93489\n[289]\tvalidation_0-auc:0.93488\n[290]\tvalidation_0-auc:0.93488\n[291]\tvalidation_0-auc:0.93489\n[292]\tvalidation_0-auc:0.93490\n[293]\tvalidation_0-auc:0.93490\n[294]\tvalidation_0-auc:0.93494\n[295]\tvalidation_0-auc:0.93497\n[296]\tvalidation_0-auc:0.93502\n[297]\tvalidation_0-auc:0.93499\n[298]\tvalidation_0-auc:0.93497\n[299]\tvalidation_0-auc:0.93499\n[300]\tvalidation_0-auc:0.93500\n[301]\tvalidation_0-auc:0.93502\n[302]\tvalidation_0-auc:0.93500\n[303]\tvalidation_0-auc:0.93501\n[304]\tvalidation_0-auc:0.93501\n[305]\tvalidation_0-auc:0.93504\n[306]\tvalidation_0-auc:0.93499\n[307]\tvalidation_0-auc:0.93504\n[308]\tvalidation_0-auc:0.93502\n[309]\tvalidation_0-auc:0.93505\n[310]\tvalidation_0-auc:0.93511\n[311]\tvalidation_0-auc:0.93517\n[312]\tvalidation_0-auc:0.93527\n[313]\tvalidation_0-auc:0.93532\n[314]\tvalidation_0-auc:0.93530\n[315]\tvalidation_0-auc:0.93529\n[316]\tvalidation_0-auc:0.93532\n[317]\tvalidation_0-auc:0.93537\n[318]\tvalidation_0-auc:0.93537\n[319]\tvalidation_0-auc:0.93537\n[320]\tvalidation_0-auc:0.93536\n[321]\tvalidation_0-auc:0.93537\n[322]\tvalidation_0-auc:0.93540\n[323]\tvalidation_0-auc:0.93536\n[324]\tvalidation_0-auc:0.93536\n[325]\tvalidation_0-auc:0.93536\n[326]\tvalidation_0-auc:0.93538\n[327]\tvalidation_0-auc:0.93542\n[328]\tvalidation_0-auc:0.93544\n[329]\tvalidation_0-auc:0.93544\n[330]\tvalidation_0-auc:0.93550\n[331]\tvalidation_0-auc:0.93550\n[332]\tvalidation_0-auc:0.93550\n[333]\tvalidation_0-auc:0.93549\n[334]\tvalidation_0-auc:0.93550\n[335]\tvalidation_0-auc:0.93547\n[336]\tvalidation_0-auc:0.93551\n[337]\tvalidation_0-auc:0.93554\n[338]\tvalidation_0-auc:0.93553\n[339]\tvalidation_0-auc:0.93554\n[340]\tvalidation_0-auc:0.93552\n[341]\tvalidation_0-auc:0.93553\n[342]\tvalidation_0-auc:0.93554\n[343]\tvalidation_0-auc:0.93552\n[344]\tvalidation_0-auc:0.93552\n[345]\tvalidation_0-auc:0.93551\n[346]\tvalidation_0-auc:0.93553\n[347]\tvalidation_0-auc:0.93552\n[348]\tvalidation_0-auc:0.93555\n[349]\tvalidation_0-auc:0.93555\n[350]\tvalidation_0-auc:0.93557\n[351]\tvalidation_0-auc:0.93558\n[352]\tvalidation_0-auc:0.93557\n[353]\tvalidation_0-auc:0.93564\n[354]\tvalidation_0-auc:0.93565\n[355]\tvalidation_0-auc:0.93567\n[356]\tvalidation_0-auc:0.93575\n[357]\tvalidation_0-auc:0.93579\n[358]\tvalidation_0-auc:0.93579\n[359]\tvalidation_0-auc:0.93584\n[360]\tvalidation_0-auc:0.93582\n[361]\tvalidation_0-auc:0.93586\n[362]\tvalidation_0-auc:0.93591\n[363]\tvalidation_0-auc:0.93586\n[364]\tvalidation_0-auc:0.93586\n[365]\tvalidation_0-auc:0.93587\n[366]\tvalidation_0-auc:0.93588\n[367]\tvalidation_0-auc:0.93587\n[368]\tvalidation_0-auc:0.93585\n[369]\tvalidation_0-auc:0.93588\n[370]\tvalidation_0-auc:0.93585\n[371]\tvalidation_0-auc:0.93585\n[372]\tvalidation_0-auc:0.93587\n[373]\tvalidation_0-auc:0.93587\n[374]\tvalidation_0-auc:0.93586\n[375]\tvalidation_0-auc:0.93584\n[376]\tvalidation_0-auc:0.93585\n[377]\tvalidation_0-auc:0.93591\n[378]\tvalidation_0-auc:0.93591\n[379]\tvalidation_0-auc:0.93595\n[380]\tvalidation_0-auc:0.93594\n[381]\tvalidation_0-auc:0.93594\n[382]\tvalidation_0-auc:0.93594\n[383]\tvalidation_0-auc:0.93599\n[384]\tvalidation_0-auc:0.93600\n[385]\tvalidation_0-auc:0.93602\n[386]\tvalidation_0-auc:0.93600\n[387]\tvalidation_0-auc:0.93600\n[388]\tvalidation_0-auc:0.93604\n[389]\tvalidation_0-auc:0.93607\n[390]\tvalidation_0-auc:0.93612\n[391]\tvalidation_0-auc:0.93611\n[392]\tvalidation_0-auc:0.93612\n[393]\tvalidation_0-auc:0.93615\n[394]\tvalidation_0-auc:0.93614\n[395]\tvalidation_0-auc:0.93615\n[396]\tvalidation_0-auc:0.93615\n[397]\tvalidation_0-auc:0.93614\n[398]\tvalidation_0-auc:0.93615\n[399]\tvalidation_0-auc:0.93617\n[400]\tvalidation_0-auc:0.93618\n[401]\tvalidation_0-auc:0.93621\n[402]\tvalidation_0-auc:0.93621\n[403]\tvalidation_0-auc:0.93623\n[404]\tvalidation_0-auc:0.93621\n[405]\tvalidation_0-auc:0.93620\n[406]\tvalidation_0-auc:0.93621\n[407]\tvalidation_0-auc:0.93626\n[408]\tvalidation_0-auc:0.93624\n[409]\tvalidation_0-auc:0.93622\n[410]\tvalidation_0-auc:0.93622\n[411]\tvalidation_0-auc:0.93625\n[412]\tvalidation_0-auc:0.93627\n[413]\tvalidation_0-auc:0.93628\n[414]\tvalidation_0-auc:0.93631\n[415]\tvalidation_0-auc:0.93630\n[416]\tvalidation_0-auc:0.93629\n[417]\tvalidation_0-auc:0.93640\n[418]\tvalidation_0-auc:0.93636\n[419]\tvalidation_0-auc:0.93645\n[420]\tvalidation_0-auc:0.93643\n[421]\tvalidation_0-auc:0.93643\n[422]\tvalidation_0-auc:0.93642\n[423]\tvalidation_0-auc:0.93640\n[424]\tvalidation_0-auc:0.93642\n[425]\tvalidation_0-auc:0.93643\n[426]\tvalidation_0-auc:0.93645\n[427]\tvalidation_0-auc:0.93644\n[428]\tvalidation_0-auc:0.93644\n[429]\tvalidation_0-auc:0.93645\n[430]\tvalidation_0-auc:0.93643\n[431]\tvalidation_0-auc:0.93644\n[432]\tvalidation_0-auc:0.93652\n[433]\tvalidation_0-auc:0.93652\n[434]\tvalidation_0-auc:0.93657\n[435]\tvalidation_0-auc:0.93658\n[436]\tvalidation_0-auc:0.93664\n[437]\tvalidation_0-auc:0.93662\n[438]\tvalidation_0-auc:0.93661\n[439]\tvalidation_0-auc:0.93663\n[440]\tvalidation_0-auc:0.93659\n[441]\tvalidation_0-auc:0.93660\n[442]\tvalidation_0-auc:0.93661\n[443]\tvalidation_0-auc:0.93664\n[444]\tvalidation_0-auc:0.93661\n[445]\tvalidation_0-auc:0.93661\n[446]\tvalidation_0-auc:0.93659\n[447]\tvalidation_0-auc:0.93658\n[448]\tvalidation_0-auc:0.93659\n[449]\tvalidation_0-auc:0.93660\n[450]\tvalidation_0-auc:0.93658\n[451]\tvalidation_0-auc:0.93659\n[452]\tvalidation_0-auc:0.93663\n[453]\tvalidation_0-auc:0.93665\n[454]\tvalidation_0-auc:0.93666\n[455]\tvalidation_0-auc:0.93666\n[456]\tvalidation_0-auc:0.93668\n[457]\tvalidation_0-auc:0.93669\n[458]\tvalidation_0-auc:0.93669\n[459]\tvalidation_0-auc:0.93666\n[460]\tvalidation_0-auc:0.93669\n[461]\tvalidation_0-auc:0.93673\n[462]\tvalidation_0-auc:0.93672\n[463]\tvalidation_0-auc:0.93672\n[464]\tvalidation_0-auc:0.93671\n[465]\tvalidation_0-auc:0.93671\n[466]\tvalidation_0-auc:0.93672\n[467]\tvalidation_0-auc:0.93670\n[468]\tvalidation_0-auc:0.93670\n[469]\tvalidation_0-auc:0.93669\n[470]\tvalidation_0-auc:0.93669\n[471]\tvalidation_0-auc:0.93670\n[472]\tvalidation_0-auc:0.93671\n[473]\tvalidation_0-auc:0.93672\n[474]\tvalidation_0-auc:0.93676\n[475]\tvalidation_0-auc:0.93676\n[476]\tvalidation_0-auc:0.93680\n[477]\tvalidation_0-auc:0.93677\n[478]\tvalidation_0-auc:0.93678\n[479]\tvalidation_0-auc:0.93680\n[480]\tvalidation_0-auc:0.93677\n[481]\tvalidation_0-auc:0.93678\n[482]\tvalidation_0-auc:0.93679\n[483]\tvalidation_0-auc:0.93679\n[484]\tvalidation_0-auc:0.93681\n[485]\tvalidation_0-auc:0.93685\n[486]\tvalidation_0-auc:0.93685\n[487]\tvalidation_0-auc:0.93685\n[488]\tvalidation_0-auc:0.93687\n[489]\tvalidation_0-auc:0.93687\n[490]\tvalidation_0-auc:0.93684\n[491]\tvalidation_0-auc:0.93681\n[492]\tvalidation_0-auc:0.93683\n[493]\tvalidation_0-auc:0.93681\n[494]\tvalidation_0-auc:0.93684\n[495]\tvalidation_0-auc:0.93683\n[496]\tvalidation_0-auc:0.93686\n[497]\tvalidation_0-auc:0.93685\n[498]\tvalidation_0-auc:0.93687\n[499]\tvalidation_0-auc:0.93686\n[500]\tvalidation_0-auc:0.93687\n[501]\tvalidation_0-auc:0.93688\n[502]\tvalidation_0-auc:0.93685\n[503]\tvalidation_0-auc:0.93684\n[504]\tvalidation_0-auc:0.93687\n[505]\tvalidation_0-auc:0.93687\n[506]\tvalidation_0-auc:0.93687\n[507]\tvalidation_0-auc:0.93687\n[508]\tvalidation_0-auc:0.93688\n[509]\tvalidation_0-auc:0.93688\n[510]\tvalidation_0-auc:0.93687\n[511]\tvalidation_0-auc:0.93686\n[512]\tvalidation_0-auc:0.93688\n[513]\tvalidation_0-auc:0.93692\n[514]\tvalidation_0-auc:0.93691\n[515]\tvalidation_0-auc:0.93693\n[516]\tvalidation_0-auc:0.93692\n[517]\tvalidation_0-auc:0.93694\n[518]\tvalidation_0-auc:0.93693\n[519]\tvalidation_0-auc:0.93695\n[520]\tvalidation_0-auc:0.93693\n[521]\tvalidation_0-auc:0.93695\n[522]\tvalidation_0-auc:0.93696\n[523]\tvalidation_0-auc:0.93694\n[524]\tvalidation_0-auc:0.93694\n[525]\tvalidation_0-auc:0.93692\n[526]\tvalidation_0-auc:0.93691\n[527]\tvalidation_0-auc:0.93697\n[528]\tvalidation_0-auc:0.93698\n[529]\tvalidation_0-auc:0.93695\n[530]\tvalidation_0-auc:0.93696\n[531]\tvalidation_0-auc:0.93697\n[532]\tvalidation_0-auc:0.93694\n[533]\tvalidation_0-auc:0.93693\n[534]\tvalidation_0-auc:0.93691\n[535]\tvalidation_0-auc:0.93694\n[536]\tvalidation_0-auc:0.93693\n[537]\tvalidation_0-auc:0.93695\n[538]\tvalidation_0-auc:0.93697\n[539]\tvalidation_0-auc:0.93697\n[540]\tvalidation_0-auc:0.93696\n[541]\tvalidation_0-auc:0.93691\n[542]\tvalidation_0-auc:0.93693\n[543]\tvalidation_0-auc:0.93694\n[544]\tvalidation_0-auc:0.93693\n[545]\tvalidation_0-auc:0.93691\n[546]\tvalidation_0-auc:0.93691\n[547]\tvalidation_0-auc:0.93694\n[548]\tvalidation_0-auc:0.93699\n[549]\tvalidation_0-auc:0.93700\n[550]\tvalidation_0-auc:0.93698\n[551]\tvalidation_0-auc:0.93697\n[552]\tvalidation_0-auc:0.93698\n[553]\tvalidation_0-auc:0.93698\n[554]\tvalidation_0-auc:0.93698\n[555]\tvalidation_0-auc:0.93699\n[556]\tvalidation_0-auc:0.93699\n[557]\tvalidation_0-auc:0.93701\n[558]\tvalidation_0-auc:0.93699\n[559]\tvalidation_0-auc:0.93700\n[560]\tvalidation_0-auc:0.93700\n[561]\tvalidation_0-auc:0.93701\n[562]\tvalidation_0-auc:0.93701\n[563]\tvalidation_0-auc:0.93700\n[564]\tvalidation_0-auc:0.93701\n[565]\tvalidation_0-auc:0.93701\n[566]\tvalidation_0-auc:0.93703\n[567]\tvalidation_0-auc:0.93706\n[568]\tvalidation_0-auc:0.93706\n[569]\tvalidation_0-auc:0.93710\n[570]\tvalidation_0-auc:0.93712\n[571]\tvalidation_0-auc:0.93712\n[572]\tvalidation_0-auc:0.93711\n[573]\tvalidation_0-auc:0.93709\n[574]\tvalidation_0-auc:0.93711\n[575]\tvalidation_0-auc:0.93707\n[576]\tvalidation_0-auc:0.93706\n[577]\tvalidation_0-auc:0.93707\n[578]\tvalidation_0-auc:0.93708\n[579]\tvalidation_0-auc:0.93708\n[580]\tvalidation_0-auc:0.93707\n[581]\tvalidation_0-auc:0.93706\n[582]\tvalidation_0-auc:0.93708\n[583]\tvalidation_0-auc:0.93706\n[584]\tvalidation_0-auc:0.93706\n[585]\tvalidation_0-auc:0.93703\n[586]\tvalidation_0-auc:0.93707\n[587]\tvalidation_0-auc:0.93704\n[588]\tvalidation_0-auc:0.93705\n[589]\tvalidation_0-auc:0.93703\n[590]\tvalidation_0-auc:0.93703\n[591]\tvalidation_0-auc:0.93704\n[592]\tvalidation_0-auc:0.93703\n[593]\tvalidation_0-auc:0.93705\n[594]\tvalidation_0-auc:0.93702\n[595]\tvalidation_0-auc:0.93699\n[596]\tvalidation_0-auc:0.93697\n[597]\tvalidation_0-auc:0.93697\n[598]\tvalidation_0-auc:0.93698\n[599]\tvalidation_0-auc:0.93697\n[600]\tvalidation_0-auc:0.93697\n[601]\tvalidation_0-auc:0.93707\n[602]\tvalidation_0-auc:0.93709\n[603]\tvalidation_0-auc:0.93705\n[604]\tvalidation_0-auc:0.93704\n[605]\tvalidation_0-auc:0.93703\n[606]\tvalidation_0-auc:0.93702\n[607]\tvalidation_0-auc:0.93704\n[608]\tvalidation_0-auc:0.93702\n[609]\tvalidation_0-auc:0.93702\n[610]\tvalidation_0-auc:0.93705\n[611]\tvalidation_0-auc:0.93706\n[612]\tvalidation_0-auc:0.93706\n[613]\tvalidation_0-auc:0.93707\n[614]\tvalidation_0-auc:0.93707\n[615]\tvalidation_0-auc:0.93706\n[616]\tvalidation_0-auc:0.93707\n[617]\tvalidation_0-auc:0.93705\n[618]\tvalidation_0-auc:0.93712\n[619]\tvalidation_0-auc:0.93709\n[620]\tvalidation_0-auc:0.93712\n[621]\tvalidation_0-auc:0.93711\n[622]\tvalidation_0-auc:0.93708\n[623]\tvalidation_0-auc:0.93708\n[624]\tvalidation_0-auc:0.93707\n[625]\tvalidation_0-auc:0.93706\n[626]\tvalidation_0-auc:0.93705\n[627]\tvalidation_0-auc:0.93705\n[628]\tvalidation_0-auc:0.93705\n[629]\tvalidation_0-auc:0.93705\n[630]\tvalidation_0-auc:0.93706\n[631]\tvalidation_0-auc:0.93705\n[632]\tvalidation_0-auc:0.93707\n[633]\tvalidation_0-auc:0.93706\n[634]\tvalidation_0-auc:0.93706\n[635]\tvalidation_0-auc:0.93705\n[636]\tvalidation_0-auc:0.93700\n[637]\tvalidation_0-auc:0.93701\n[638]\tvalidation_0-auc:0.93700\n[639]\tvalidation_0-auc:0.93702\n[640]\tvalidation_0-auc:0.93702\n[641]\tvalidation_0-auc:0.93703\n[642]\tvalidation_0-auc:0.93705\n[643]\tvalidation_0-auc:0.93708\n[644]\tvalidation_0-auc:0.93708\n[645]\tvalidation_0-auc:0.93709\n[646]\tvalidation_0-auc:0.93710\n[647]\tvalidation_0-auc:0.93707\n[648]\tvalidation_0-auc:0.93710\n[649]\tvalidation_0-auc:0.93710\n[650]\tvalidation_0-auc:0.93708\n[651]\tvalidation_0-auc:0.93708\n[652]\tvalidation_0-auc:0.93708\n[653]\tvalidation_0-auc:0.93710\n[654]\tvalidation_0-auc:0.93711\n[655]\tvalidation_0-auc:0.93713\n[656]\tvalidation_0-auc:0.93710\n[657]\tvalidation_0-auc:0.93708\n[658]\tvalidation_0-auc:0.93706\n[659]\tvalidation_0-auc:0.93719\n[660]\tvalidation_0-auc:0.93719\n[661]\tvalidation_0-auc:0.93717\n[662]\tvalidation_0-auc:0.93716\n[663]\tvalidation_0-auc:0.93716\n[664]\tvalidation_0-auc:0.93714\n[665]\tvalidation_0-auc:0.93717\n[666]\tvalidation_0-auc:0.93716\n[667]\tvalidation_0-auc:0.93718\n[668]\tvalidation_0-auc:0.93722\n[669]\tvalidation_0-auc:0.93721\n[670]\tvalidation_0-auc:0.93721\n[671]\tvalidation_0-auc:0.93719\n[672]\tvalidation_0-auc:0.93720\n[673]\tvalidation_0-auc:0.93720\n[674]\tvalidation_0-auc:0.93719\n[675]\tvalidation_0-auc:0.93723\n[676]\tvalidation_0-auc:0.93722\n[677]\tvalidation_0-auc:0.93721\n[678]\tvalidation_0-auc:0.93721\n[679]\tvalidation_0-auc:0.93719\n[680]\tvalidation_0-auc:0.93720\n[681]\tvalidation_0-auc:0.93720\n[682]\tvalidation_0-auc:0.93722\n[683]\tvalidation_0-auc:0.93722\n[684]\tvalidation_0-auc:0.93721\n[685]\tvalidation_0-auc:0.93721\n[686]\tvalidation_0-auc:0.93721\n[687]\tvalidation_0-auc:0.93722\n[688]\tvalidation_0-auc:0.93723\n[689]\tvalidation_0-auc:0.93724\n[690]\tvalidation_0-auc:0.93724\n[691]\tvalidation_0-auc:0.93720\n[692]\tvalidation_0-auc:0.93721\n[693]\tvalidation_0-auc:0.93722\n[694]\tvalidation_0-auc:0.93724\n[695]\tvalidation_0-auc:0.93723\n[696]\tvalidation_0-auc:0.93722\n[697]\tvalidation_0-auc:0.93722\n[698]\tvalidation_0-auc:0.93734\n[699]\tvalidation_0-auc:0.93733\n[700]\tvalidation_0-auc:0.93735\n[701]\tvalidation_0-auc:0.93735\n[702]\tvalidation_0-auc:0.93735\n[703]\tvalidation_0-auc:0.93735\n[704]\tvalidation_0-auc:0.93734\n[705]\tvalidation_0-auc:0.93733\n[706]\tvalidation_0-auc:0.93731\n[707]\tvalidation_0-auc:0.93729\n[708]\tvalidation_0-auc:0.93729\n[709]\tvalidation_0-auc:0.93732\n[710]\tvalidation_0-auc:0.93731\n[711]\tvalidation_0-auc:0.93731\n[712]\tvalidation_0-auc:0.93731\n[713]\tvalidation_0-auc:0.93732\n[714]\tvalidation_0-auc:0.93734\n[715]\tvalidation_0-auc:0.93733\n[716]\tvalidation_0-auc:0.93734\n[717]\tvalidation_0-auc:0.93734\n[718]\tvalidation_0-auc:0.93733\n[719]\tvalidation_0-auc:0.93733\n[720]\tvalidation_0-auc:0.93734\n[721]\tvalidation_0-auc:0.93734\n[722]\tvalidation_0-auc:0.93736\n[723]\tvalidation_0-auc:0.93737\n[724]\tvalidation_0-auc:0.93738\n[725]\tvalidation_0-auc:0.93738\n[726]\tvalidation_0-auc:0.93739\n[727]\tvalidation_0-auc:0.93737\n[728]\tvalidation_0-auc:0.93738\n[729]\tvalidation_0-auc:0.93738\n[730]\tvalidation_0-auc:0.93736\n[731]\tvalidation_0-auc:0.93735\n[732]\tvalidation_0-auc:0.93734\n[733]\tvalidation_0-auc:0.93733\n[734]\tvalidation_0-auc:0.93735\n[735]\tvalidation_0-auc:0.93736\n[736]\tvalidation_0-auc:0.93734\n[737]\tvalidation_0-auc:0.93735\n[738]\tvalidation_0-auc:0.93737\n[739]\tvalidation_0-auc:0.93735\n[740]\tvalidation_0-auc:0.93732\n[741]\tvalidation_0-auc:0.93731\n[742]\tvalidation_0-auc:0.93735\n[743]\tvalidation_0-auc:0.93734\n[744]\tvalidation_0-auc:0.93732\n[745]\tvalidation_0-auc:0.93730\n[746]\tvalidation_0-auc:0.93730\n[747]\tvalidation_0-auc:0.93732\n[748]\tvalidation_0-auc:0.93733\n[749]\tvalidation_0-auc:0.93733\n[750]\tvalidation_0-auc:0.93734\n[751]\tvalidation_0-auc:0.93733\n[752]\tvalidation_0-auc:0.93731\n[753]\tvalidation_0-auc:0.93731\n[754]\tvalidation_0-auc:0.93732\n[755]\tvalidation_0-auc:0.93731\n[756]\tvalidation_0-auc:0.93732\n[757]\tvalidation_0-auc:0.93733\n[758]\tvalidation_0-auc:0.93733\n[759]\tvalidation_0-auc:0.93736\n[760]\tvalidation_0-auc:0.93739\n[761]\tvalidation_0-auc:0.93736\n[762]\tvalidation_0-auc:0.93740\n[763]\tvalidation_0-auc:0.93742\n[764]\tvalidation_0-auc:0.93740\n[765]\tvalidation_0-auc:0.93739\n[766]\tvalidation_0-auc:0.93739\n[767]\tvalidation_0-auc:0.93737\n[768]\tvalidation_0-auc:0.93737\n[769]\tvalidation_0-auc:0.93739\n[770]\tvalidation_0-auc:0.93741\n[771]\tvalidation_0-auc:0.93741\n[772]\tvalidation_0-auc:0.93739\n[773]\tvalidation_0-auc:0.93740\n[774]\tvalidation_0-auc:0.93741\n[775]\tvalidation_0-auc:0.93741\n[776]\tvalidation_0-auc:0.93738\n[777]\tvalidation_0-auc:0.93737\n[778]\tvalidation_0-auc:0.93738\n[779]\tvalidation_0-auc:0.93737\n[780]\tvalidation_0-auc:0.93738\n[781]\tvalidation_0-auc:0.93737\n[782]\tvalidation_0-auc:0.93737\n[783]\tvalidation_0-auc:0.93736\n[784]\tvalidation_0-auc:0.93734\n[785]\tvalidation_0-auc:0.93735\n[786]\tvalidation_0-auc:0.93736\n[787]\tvalidation_0-auc:0.93737\n[788]\tvalidation_0-auc:0.93736\n[789]\tvalidation_0-auc:0.93734\n[790]\tvalidation_0-auc:0.93736\n[791]\tvalidation_0-auc:0.93735\n[792]\tvalidation_0-auc:0.93734\n[793]\tvalidation_0-auc:0.93735\n[794]\tvalidation_0-auc:0.93735\n[795]\tvalidation_0-auc:0.93733\n[796]\tvalidation_0-auc:0.93732\n[797]\tvalidation_0-auc:0.93734\n[798]\tvalidation_0-auc:0.93733\n[799]\tvalidation_0-auc:0.93729\n[800]\tvalidation_0-auc:0.93729\n[801]\tvalidation_0-auc:0.93729\n[802]\tvalidation_0-auc:0.93729\n[803]\tvalidation_0-auc:0.93727\n[804]\tvalidation_0-auc:0.93727\n[805]\tvalidation_0-auc:0.93726\n[806]\tvalidation_0-auc:0.93727\n[807]\tvalidation_0-auc:0.93726\n[808]\tvalidation_0-auc:0.93723\n[809]\tvalidation_0-auc:0.93723\n[810]\tvalidation_0-auc:0.93724\n[811]\tvalidation_0-auc:0.93725\n[812]\tvalidation_0-auc:0.93724\n[813]\tvalidation_0-auc:0.93722\n[814]\tvalidation_0-auc:0.93720\n[815]\tvalidation_0-auc:0.93719\n[816]\tvalidation_0-auc:0.93720\n[817]\tvalidation_0-auc:0.93720\n[818]\tvalidation_0-auc:0.93721\n[819]\tvalidation_0-auc:0.93719\n[820]\tvalidation_0-auc:0.93720\n[821]\tvalidation_0-auc:0.93717\n[822]\tvalidation_0-auc:0.93718\n[823]\tvalidation_0-auc:0.93716\n[824]\tvalidation_0-auc:0.93717\n[825]\tvalidation_0-auc:0.93713\n[826]\tvalidation_0-auc:0.93716\n[827]\tvalidation_0-auc:0.93716\n[828]\tvalidation_0-auc:0.93715\n[829]\tvalidation_0-auc:0.93714\n[830]\tvalidation_0-auc:0.93714\n[831]\tvalidation_0-auc:0.93713\n[832]\tvalidation_0-auc:0.93710\n[833]\tvalidation_0-auc:0.93710\n[834]\tvalidation_0-auc:0.93709\n[835]\tvalidation_0-auc:0.93706\n[836]\tvalidation_0-auc:0.93703\n[837]\tvalidation_0-auc:0.93701\n[838]\tvalidation_0-auc:0.93700\n[839]\tvalidation_0-auc:0.93701\n[840]\tvalidation_0-auc:0.93697\n[841]\tvalidation_0-auc:0.93700\n[842]\tvalidation_0-auc:0.93700\n[843]\tvalidation_0-auc:0.93699\n[844]\tvalidation_0-auc:0.93700\n[845]\tvalidation_0-auc:0.93699\n[846]\tvalidation_0-auc:0.93699\n[847]\tvalidation_0-auc:0.93699\n[848]\tvalidation_0-auc:0.93699\n[849]\tvalidation_0-auc:0.93699\n[850]\tvalidation_0-auc:0.93699\n[851]\tvalidation_0-auc:0.93698\n[852]\tvalidation_0-auc:0.93700\n[853]\tvalidation_0-auc:0.93700\n[854]\tvalidation_0-auc:0.93700\n[855]\tvalidation_0-auc:0.93698\n[856]\tvalidation_0-auc:0.93699\n[857]\tvalidation_0-auc:0.93699\n[858]\tvalidation_0-auc:0.93696\n[859]\tvalidation_0-auc:0.93696\n[860]\tvalidation_0-auc:0.93694\n[861]\tvalidation_0-auc:0.93691\n[862]\tvalidation_0-auc:0.93694\n[863]\tvalidation_0-auc:0.93695\n[0]\tvalidation_0-auc:0.87061\n[1]\tvalidation_0-auc:0.89799\n[2]\tvalidation_0-auc:0.89406\n[3]\tvalidation_0-auc:0.88494\n[4]\tvalidation_0-auc:0.88084\n[5]\tvalidation_0-auc:0.90076\n[6]\tvalidation_0-auc:0.90776\n[7]\tvalidation_0-auc:0.90517\n[8]\tvalidation_0-auc:0.90161\n"},{"name":"stderr","output_type":"stream","text":["E:\\Anaconda3\\lib\\site-packages\\xgboost\\sklearn.py:797: UserWarning: `eval_metric` in `fit` method is deprecated for better compatibility with scikit-learn, use `eval_metric` in constructor or`set_params` instead.\n"," UserWarning,\n","E:\\Anaconda3\\lib\\site-packages\\xgboost\\sklearn.py:797: UserWarning: `early_stopping_rounds` in `fit` method is deprecated for better compatibility with scikit-learn, use `early_stopping_rounds` in constructor or`set_params` instead.\n"," UserWarning,\n"]},{"name":"stdout","output_type":"stream","text":"[9]\tvalidation_0-auc:0.90911\n[10]\tvalidation_0-auc:0.91437\n[11]\tvalidation_0-auc:0.91579\n[12]\tvalidation_0-auc:0.91731\n[13]\tvalidation_0-auc:0.91850\n[14]\tvalidation_0-auc:0.91759\n[15]\tvalidation_0-auc:0.91874\n[16]\tvalidation_0-auc:0.91750\n[17]\tvalidation_0-auc:0.91686\n[18]\tvalidation_0-auc:0.91712\n[19]\tvalidation_0-auc:0.91780\n[20]\tvalidation_0-auc:0.91763\n[21]\tvalidation_0-auc:0.91862\n[22]\tvalidation_0-auc:0.91930\n[23]\tvalidation_0-auc:0.91870\n[24]\tvalidation_0-auc:0.91875\n[25]\tvalidation_0-auc:0.91975\n[26]\tvalidation_0-auc:0.91984\n[27]\tvalidation_0-auc:0.92001\n[28]\tvalidation_0-auc:0.92029\n[29]\tvalidation_0-auc:0.92005\n[30]\tvalidation_0-auc:0.92083\n[31]\tvalidation_0-auc:0.92096\n[32]\tvalidation_0-auc:0.92150\n[33]\tvalidation_0-auc:0.92204\n[34]\tvalidation_0-auc:0.92178\n[35]\tvalidation_0-auc:0.92211\n[36]\tvalidation_0-auc:0.92255\n[37]\tvalidation_0-auc:0.92264\n[38]\tvalidation_0-auc:0.92287\n[39]\tvalidation_0-auc:0.92265\n[40]\tvalidation_0-auc:0.92270\n[41]\tvalidation_0-auc:0.92273\n[42]\tvalidation_0-auc:0.92261\n[43]\tvalidation_0-auc:0.92279\n[44]\tvalidation_0-auc:0.92307\n[45]\tvalidation_0-auc:0.92333\n[46]\tvalidation_0-auc:0.92327\n[47]\tvalidation_0-auc:0.92306\n[48]\tvalidation_0-auc:0.92284\n[49]\tvalidation_0-auc:0.92313\n[50]\tvalidation_0-auc:0.92357\n[51]\tvalidation_0-auc:0.92386\n[52]\tvalidation_0-auc:0.92382\n[53]\tvalidation_0-auc:0.92401\n[54]\tvalidation_0-auc:0.92423\n[55]\tvalidation_0-auc:0.92426\n[56]\tvalidation_0-auc:0.92409\n[57]\tvalidation_0-auc:0.92443\n[58]\tvalidation_0-auc:0.92448\n[59]\tvalidation_0-auc:0.92436\n[60]\tvalidation_0-auc:0.92447\n[61]\tvalidation_0-auc:0.92473\n[62]\tvalidation_0-auc:0.92479\n[63]\tvalidation_0-auc:0.92467\n[64]\tvalidation_0-auc:0.92455\n[65]\tvalidation_0-auc:0.92472\n[66]\tvalidation_0-auc:0.92485\n[67]\tvalidation_0-auc:0.92480\n[68]\tvalidation_0-auc:0.92490\n[69]\tvalidation_0-auc:0.92515\n[70]\tvalidation_0-auc:0.92521\n[71]\tvalidation_0-auc:0.92522\n[72]\tvalidation_0-auc:0.92528\n[73]\tvalidation_0-auc:0.92549\n[74]\tvalidation_0-auc:0.92526\n[75]\tvalidation_0-auc:0.92546\n[76]\tvalidation_0-auc:0.92533\n[77]\tvalidation_0-auc:0.92556\n[78]\tvalidation_0-auc:0.92560\n[79]\tvalidation_0-auc:0.92574\n[80]\tvalidation_0-auc:0.92585\n[81]\tvalidation_0-auc:0.92602\n[82]\tvalidation_0-auc:0.92600\n[83]\tvalidation_0-auc:0.92601\n[84]\tvalidation_0-auc:0.92601\n[85]\tvalidation_0-auc:0.92615\n[86]\tvalidation_0-auc:0.92614\n[87]\tvalidation_0-auc:0.92613\n[88]\tvalidation_0-auc:0.92625\n[89]\tvalidation_0-auc:0.92643\n[90]\tvalidation_0-auc:0.92642\n[91]\tvalidation_0-auc:0.92644\n[92]\tvalidation_0-auc:0.92641\n[93]\tvalidation_0-auc:0.92639\n[94]\tvalidation_0-auc:0.92641\n[95]\tvalidation_0-auc:0.92647\n[96]\tvalidation_0-auc:0.92639\n[97]\tvalidation_0-auc:0.92657\n[98]\tvalidation_0-auc:0.92681\n[99]\tvalidation_0-auc:0.92684\n[100]\tvalidation_0-auc:0.92683\n[101]\tvalidation_0-auc:0.92680\n[102]\tvalidation_0-auc:0.92683\n[103]\tvalidation_0-auc:0.92686\n[104]\tvalidation_0-auc:0.92698\n[105]\tvalidation_0-auc:0.92705\n[106]\tvalidation_0-auc:0.92708\n[107]\tvalidation_0-auc:0.92725\n[108]\tvalidation_0-auc:0.92721\n[109]\tvalidation_0-auc:0.92734\n[110]\tvalidation_0-auc:0.92738\n[111]\tvalidation_0-auc:0.92748\n[112]\tvalidation_0-auc:0.92740\n[113]\tvalidation_0-auc:0.92757\n[114]\tvalidation_0-auc:0.92754\n[115]\tvalidation_0-auc:0.92756\n[116]\tvalidation_0-auc:0.92755\n[117]\tvalidation_0-auc:0.92770\n[118]\tvalidation_0-auc:0.92765\n[119]\tvalidation_0-auc:0.92760\n[120]\tvalidation_0-auc:0.92764\n[121]\tvalidation_0-auc:0.92767\n[122]\tvalidation_0-auc:0.92764\n[123]\tvalidation_0-auc:0.92758\n[124]\tvalidation_0-auc:0.92763\n[125]\tvalidation_0-auc:0.92770\n[126]\tvalidation_0-auc:0.92767\n[127]\tvalidation_0-auc:0.92771\n[128]\tvalidation_0-auc:0.92772\n[129]\tvalidation_0-auc:0.92793\n[130]\tvalidation_0-auc:0.92795\n[131]\tvalidation_0-auc:0.92792\n[132]\tvalidation_0-auc:0.92798\n[133]\tvalidation_0-auc:0.92803\n[134]\tvalidation_0-auc:0.92806\n[135]\tvalidation_0-auc:0.92801\n[136]\tvalidation_0-auc:0.92814\n[137]\tvalidation_0-auc:0.92812\n[138]\tvalidation_0-auc:0.92809\n[139]\tvalidation_0-auc:0.92812\n[140]\tvalidation_0-auc:0.92827\n[141]\tvalidation_0-auc:0.92843\n[142]\tvalidation_0-auc:0.92839\n[143]\tvalidation_0-auc:0.92844\n[144]\tvalidation_0-auc:0.92859\n[145]\tvalidation_0-auc:0.92868\n[146]\tvalidation_0-auc:0.92869\n[147]\tvalidation_0-auc:0.92865\n[148]\tvalidation_0-auc:0.92867\n[149]\tvalidation_0-auc:0.92866\n[150]\tvalidation_0-auc:0.92867\n[151]\tvalidation_0-auc:0.92880\n[152]\tvalidation_0-auc:0.92881\n[153]\tvalidation_0-auc:0.92886\n[154]\tvalidation_0-auc:0.92887\n[155]\tvalidation_0-auc:0.92883\n[156]\tvalidation_0-auc:0.92885\n[157]\tvalidation_0-auc:0.92882\n[158]\tvalidation_0-auc:0.92883\n[159]\tvalidation_0-auc:0.92893\n[160]\tvalidation_0-auc:0.92901\n[161]\tvalidation_0-auc:0.92903\n[162]\tvalidation_0-auc:0.92911\n[163]\tvalidation_0-auc:0.92920\n[164]\tvalidation_0-auc:0.92924\n[165]\tvalidation_0-auc:0.92923\n[166]\tvalidation_0-auc:0.92924\n[167]\tvalidation_0-auc:0.92935\n[168]\tvalidation_0-auc:0.92937\n[169]\tvalidation_0-auc:0.92936\n[170]\tvalidation_0-auc:0.92935\n[171]\tvalidation_0-auc:0.92938\n[172]\tvalidation_0-auc:0.92935\n[173]\tvalidation_0-auc:0.92939\n[174]\tvalidation_0-auc:0.92940\n[175]\tvalidation_0-auc:0.92944\n[176]\tvalidation_0-auc:0.92940\n[177]\tvalidation_0-auc:0.92936\n[178]\tvalidation_0-auc:0.92935\n[179]\tvalidation_0-auc:0.92932\n[180]\tvalidation_0-auc:0.92930\n[181]\tvalidation_0-auc:0.92927\n[182]\tvalidation_0-auc:0.92933\n[183]\tvalidation_0-auc:0.92927\n[184]\tvalidation_0-auc:0.92942\n[185]\tvalidation_0-auc:0.92942\n[186]\tvalidation_0-auc:0.92946\n[187]\tvalidation_0-auc:0.92953\n[188]\tvalidation_0-auc:0.92955\n[189]\tvalidation_0-auc:0.92954\n[190]\tvalidation_0-auc:0.92968\n[191]\tvalidation_0-auc:0.92970\n[192]\tvalidation_0-auc:0.92981\n[193]\tvalidation_0-auc:0.92979\n[194]\tvalidation_0-auc:0.92980\n[195]\tvalidation_0-auc:0.92983\n[196]\tvalidation_0-auc:0.92986\n[197]\tvalidation_0-auc:0.92986\n[198]\tvalidation_0-auc:0.92984\n[199]\tvalidation_0-auc:0.92985\n[200]\tvalidation_0-auc:0.92982\n[201]\tvalidation_0-auc:0.92986\n[202]\tvalidation_0-auc:0.92984\n[203]\tvalidation_0-auc:0.92984\n[204]\tvalidation_0-auc:0.92986\n[205]\tvalidation_0-auc:0.92989\n[206]\tvalidation_0-auc:0.92991\n[207]\tvalidation_0-auc:0.92988\n[208]\tvalidation_0-auc:0.92987\n[209]\tvalidation_0-auc:0.92984\n[210]\tvalidation_0-auc:0.92984\n[211]\tvalidation_0-auc:0.92982\n[212]\tvalidation_0-auc:0.92982\n[213]\tvalidation_0-auc:0.92980\n[214]\tvalidation_0-auc:0.92990\n[215]\tvalidation_0-auc:0.92992\n[216]\tvalidation_0-auc:0.93002\n[217]\tvalidation_0-auc:0.93000\n[218]\tvalidation_0-auc:0.92999\n[219]\tvalidation_0-auc:0.92997\n[220]\tvalidation_0-auc:0.92997\n[221]\tvalidation_0-auc:0.92999\n[222]\tvalidation_0-auc:0.92999\n[223]\tvalidation_0-auc:0.93006\n[224]\tvalidation_0-auc:0.93002\n[225]\tvalidation_0-auc:0.93004\n[226]\tvalidation_0-auc:0.93007\n[227]\tvalidation_0-auc:0.93007\n[228]\tvalidation_0-auc:0.93007\n[229]\tvalidation_0-auc:0.93011\n[230]\tvalidation_0-auc:0.93018\n[231]\tvalidation_0-auc:0.93021\n[232]\tvalidation_0-auc:0.93020\n[233]\tvalidation_0-auc:0.93018\n[234]\tvalidation_0-auc:0.93016\n[235]\tvalidation_0-auc:0.93014\n[236]\tvalidation_0-auc:0.93017\n[237]\tvalidation_0-auc:0.93014\n[238]\tvalidation_0-auc:0.93017\n[239]\tvalidation_0-auc:0.93014\n[240]\tvalidation_0-auc:0.93023\n[241]\tvalidation_0-auc:0.93023\n[242]\tvalidation_0-auc:0.93019\n[243]\tvalidation_0-auc:0.93020\n[244]\tvalidation_0-auc:0.93019\n[245]\tvalidation_0-auc:0.93016\n[246]\tvalidation_0-auc:0.93017\n[247]\tvalidation_0-auc:0.93018\n[248]\tvalidation_0-auc:0.93019\n[249]\tvalidation_0-auc:0.93023\n[250]\tvalidation_0-auc:0.93023\n[251]\tvalidation_0-auc:0.93023\n[252]\tvalidation_0-auc:0.93024\n[253]\tvalidation_0-auc:0.93024\n[254]\tvalidation_0-auc:0.93029\n[255]\tvalidation_0-auc:0.93031\n[256]\tvalidation_0-auc:0.93029\n[257]\tvalidation_0-auc:0.93026\n[258]\tvalidation_0-auc:0.93030\n[259]\tvalidation_0-auc:0.93027\n[260]\tvalidation_0-auc:0.93034\n[261]\tvalidation_0-auc:0.93038\n[262]\tvalidation_0-auc:0.93032\n[263]\tvalidation_0-auc:0.93030\n[264]\tvalidation_0-auc:0.93031\n[265]\tvalidation_0-auc:0.93035\n[266]\tvalidation_0-auc:0.93035\n[267]\tvalidation_0-auc:0.93039\n[268]\tvalidation_0-auc:0.93039\n[269]\tvalidation_0-auc:0.93037\n[270]\tvalidation_0-auc:0.93038\n[271]\tvalidation_0-auc:0.93047\n[272]\tvalidation_0-auc:0.93052\n[273]\tvalidation_0-auc:0.93054\n[274]\tvalidation_0-auc:0.93054\n[275]\tvalidation_0-auc:0.93052\n[276]\tvalidation_0-auc:0.93050\n[277]\tvalidation_0-auc:0.93052\n[278]\tvalidation_0-auc:0.93052\n[279]\tvalidation_0-auc:0.93059\n[280]\tvalidation_0-auc:0.93067\n[281]\tvalidation_0-auc:0.93068\n[282]\tvalidation_0-auc:0.93069\n[283]\tvalidation_0-auc:0.93072\n[284]\tvalidation_0-auc:0.93065\n[285]\tvalidation_0-auc:0.93063\n[286]\tvalidation_0-auc:0.93063\n[287]\tvalidation_0-auc:0.93065\n[288]\tvalidation_0-auc:0.93066\n[289]\tvalidation_0-auc:0.93065\n[290]\tvalidation_0-auc:0.93071\n[291]\tvalidation_0-auc:0.93067\n[292]\tvalidation_0-auc:0.93064\n[293]\tvalidation_0-auc:0.93062\n[294]\tvalidation_0-auc:0.93060\n[295]\tvalidation_0-auc:0.93062\n[296]\tvalidation_0-auc:0.93064\n[297]\tvalidation_0-auc:0.93063\n[298]\tvalidation_0-auc:0.93070\n[299]\tvalidation_0-auc:0.93069\n[300]\tvalidation_0-auc:0.93070\n[301]\tvalidation_0-auc:0.93072\n[302]\tvalidation_0-auc:0.93073\n[303]\tvalidation_0-auc:0.93081\n[304]\tvalidation_0-auc:0.93079\n[305]\tvalidation_0-auc:0.93078\n[306]\tvalidation_0-auc:0.93075\n[307]\tvalidation_0-auc:0.93079\n[308]\tvalidation_0-auc:0.93077\n[309]\tvalidation_0-auc:0.93076\n[310]\tvalidation_0-auc:0.93083\n[311]\tvalidation_0-auc:0.93086\n[312]\tvalidation_0-auc:0.93084\n[313]\tvalidation_0-auc:0.93088\n[314]\tvalidation_0-auc:0.93088\n[315]\tvalidation_0-auc:0.93085\n[316]\tvalidation_0-auc:0.93086\n[317]\tvalidation_0-auc:0.93092\n[318]\tvalidation_0-auc:0.93093\n[319]\tvalidation_0-auc:0.93095\n[320]\tvalidation_0-auc:0.93096\n[321]\tvalidation_0-auc:0.93094\n[322]\tvalidation_0-auc:0.93094\n[323]\tvalidation_0-auc:0.93099\n[324]\tvalidation_0-auc:0.93095\n[325]\tvalidation_0-auc:0.93100\n[326]\tvalidation_0-auc:0.93099\n[327]\tvalidation_0-auc:0.93098\n[328]\tvalidation_0-auc:0.93101\n[329]\tvalidation_0-auc:0.93099\n[330]\tvalidation_0-auc:0.93101\n[331]\tvalidation_0-auc:0.93106\n[332]\tvalidation_0-auc:0.93111\n[333]\tvalidation_0-auc:0.93110\n[334]\tvalidation_0-auc:0.93114\n[335]\tvalidation_0-auc:0.93117\n[336]\tvalidation_0-auc:0.93118\n[337]\tvalidation_0-auc:0.93120\n[338]\tvalidation_0-auc:0.93117\n[339]\tvalidation_0-auc:0.93122\n[340]\tvalidation_0-auc:0.93123\n[341]\tvalidation_0-auc:0.93121\n[342]\tvalidation_0-auc:0.93119\n[343]\tvalidation_0-auc:0.93122\n[344]\tvalidation_0-auc:0.93122\n[345]\tvalidation_0-auc:0.93121\n[346]\tvalidation_0-auc:0.93120\n[347]\tvalidation_0-auc:0.93121\n[348]\tvalidation_0-auc:0.93120\n[349]\tvalidation_0-auc:0.93117\n[350]\tvalidation_0-auc:0.93121\n[351]\tvalidation_0-auc:0.93124\n[352]\tvalidation_0-auc:0.93122\n[353]\tvalidation_0-auc:0.93122\n[354]\tvalidation_0-auc:0.93123\n[355]\tvalidation_0-auc:0.93126\n[356]\tvalidation_0-auc:0.93129\n[357]\tvalidation_0-auc:0.93130\n[358]\tvalidation_0-auc:0.93132\n[359]\tvalidation_0-auc:0.93134\n[360]\tvalidation_0-auc:0.93136\n[361]\tvalidation_0-auc:0.93135\n[362]\tvalidation_0-auc:0.93137\n[363]\tvalidation_0-auc:0.93141\n[364]\tvalidation_0-auc:0.93143\n[365]\tvalidation_0-auc:0.93141\n[366]\tvalidation_0-auc:0.93146\n[367]\tvalidation_0-auc:0.93144\n[368]\tvalidation_0-auc:0.93144\n[369]\tvalidation_0-auc:0.93145\n[370]\tvalidation_0-auc:0.93147\n[371]\tvalidation_0-auc:0.93145\n[372]\tvalidation_0-auc:0.93145\n[373]\tvalidation_0-auc:0.93147\n[374]\tvalidation_0-auc:0.93146\n[375]\tvalidation_0-auc:0.93145\n[376]\tvalidation_0-auc:0.93148\n[377]\tvalidation_0-auc:0.93150\n[378]\tvalidation_0-auc:0.93152\n[379]\tvalidation_0-auc:0.93150\n[380]\tvalidation_0-auc:0.93150\n[381]\tvalidation_0-auc:0.93150\n[382]\tvalidation_0-auc:0.93148\n[383]\tvalidation_0-auc:0.93146\n[384]\tvalidation_0-auc:0.93147\n[385]\tvalidation_0-auc:0.93146\n[386]\tvalidation_0-auc:0.93147\n[387]\tvalidation_0-auc:0.93145\n[388]\tvalidation_0-auc:0.93144\n[389]\tvalidation_0-auc:0.93144\n[390]\tvalidation_0-auc:0.93147\n[391]\tvalidation_0-auc:0.93146\n[392]\tvalidation_0-auc:0.93147\n[393]\tvalidation_0-auc:0.93145\n[394]\tvalidation_0-auc:0.93143\n[395]\tvalidation_0-auc:0.93144\n[396]\tvalidation_0-auc:0.93144\n[397]\tvalidation_0-auc:0.93147\n[398]\tvalidation_0-auc:0.93147\n[399]\tvalidation_0-auc:0.93152\n[400]\tvalidation_0-auc:0.93150\n[401]\tvalidation_0-auc:0.93152\n[402]\tvalidation_0-auc:0.93151\n[403]\tvalidation_0-auc:0.93153\n[404]\tvalidation_0-auc:0.93153\n[405]\tvalidation_0-auc:0.93153\n[406]\tvalidation_0-auc:0.93154\n[407]\tvalidation_0-auc:0.93155\n[408]\tvalidation_0-auc:0.93157\n[409]\tvalidation_0-auc:0.93155\n[410]\tvalidation_0-auc:0.93156\n[411]\tvalidation_0-auc:0.93157\n[412]\tvalidation_0-auc:0.93157\n[413]\tvalidation_0-auc:0.93154\n[414]\tvalidation_0-auc:0.93155\n[415]\tvalidation_0-auc:0.93155\n[416]\tvalidation_0-auc:0.93155\n[417]\tvalidation_0-auc:0.93156\n[418]\tvalidation_0-auc:0.93154\n[419]\tvalidation_0-auc:0.93157\n[420]\tvalidation_0-auc:0.93155\n[421]\tvalidation_0-auc:0.93155\n[422]\tvalidation_0-auc:0.93155\n[423]\tvalidation_0-auc:0.93153\n[424]\tvalidation_0-auc:0.93151\n[425]\tvalidation_0-auc:0.93151\n[426]\tvalidation_0-auc:0.93152\n[427]\tvalidation_0-auc:0.93150\n[428]\tvalidation_0-auc:0.93149\n[429]\tvalidation_0-auc:0.93146\n[430]\tvalidation_0-auc:0.93148\n[431]\tvalidation_0-auc:0.93148\n[432]\tvalidation_0-auc:0.93149\n[433]\tvalidation_0-auc:0.93148\n[434]\tvalidation_0-auc:0.93145\n[435]\tvalidation_0-auc:0.93144\n[436]\tvalidation_0-auc:0.93147\n[437]\tvalidation_0-auc:0.93150\n[438]\tvalidation_0-auc:0.93152\n[439]\tvalidation_0-auc:0.93152\n[440]\tvalidation_0-auc:0.93152\n[441]\tvalidation_0-auc:0.93150\n[442]\tvalidation_0-auc:0.93152\n[443]\tvalidation_0-auc:0.93152\n[444]\tvalidation_0-auc:0.93151\n[445]\tvalidation_0-auc:0.93152\n[446]\tvalidation_0-auc:0.93152\n[447]\tvalidation_0-auc:0.93151\n[448]\tvalidation_0-auc:0.93149\n[449]\tvalidation_0-auc:0.93147\n[450]\tvalidation_0-auc:0.93149\n[451]\tvalidation_0-auc:0.93150\n[452]\tvalidation_0-auc:0.93152\n[453]\tvalidation_0-auc:0.93152\n[454]\tvalidation_0-auc:0.93152\n[455]\tvalidation_0-auc:0.93152\n[456]\tvalidation_0-auc:0.93153\n[457]\tvalidation_0-auc:0.93153\n[458]\tvalidation_0-auc:0.93155\n[459]\tvalidation_0-auc:0.93154\n[460]\tvalidation_0-auc:0.93153\n[461]\tvalidation_0-auc:0.93154\n[462]\tvalidation_0-auc:0.93154\n[463]\tvalidation_0-auc:0.93153\n[464]\tvalidation_0-auc:0.93152\n[465]\tvalidation_0-auc:0.93157\n[466]\tvalidation_0-auc:0.93158\n[467]\tvalidation_0-auc:0.93156\n[468]\tvalidation_0-auc:0.93155\n[469]\tvalidation_0-auc:0.93156\n[470]\tvalidation_0-auc:0.93152\n[471]\tvalidation_0-auc:0.93150\n[472]\tvalidation_0-auc:0.93153\n[473]\tvalidation_0-auc:0.93154\n[474]\tvalidation_0-auc:0.93156\n[475]\tvalidation_0-auc:0.93157\n[476]\tvalidation_0-auc:0.93160\n[477]\tvalidation_0-auc:0.93162\n[478]\tvalidation_0-auc:0.93162\n[479]\tvalidation_0-auc:0.93158\n[480]\tvalidation_0-auc:0.93158\n[481]\tvalidation_0-auc:0.93160\n[482]\tvalidation_0-auc:0.93161\n[483]\tvalidation_0-auc:0.93158\n[484]\tvalidation_0-auc:0.93161\n[485]\tvalidation_0-auc:0.93162\n[486]\tvalidation_0-auc:0.93163\n[487]\tvalidation_0-auc:0.93164\n[488]\tvalidation_0-auc:0.93163\n[489]\tvalidation_0-auc:0.93164\n[490]\tvalidation_0-auc:0.93164\n[491]\tvalidation_0-auc:0.93163\n[492]\tvalidation_0-auc:0.93164\n[493]\tvalidation_0-auc:0.93164\n[494]\tvalidation_0-auc:0.93164\n[495]\tvalidation_0-auc:0.93164\n[496]\tvalidation_0-auc:0.93162\n[497]\tvalidation_0-auc:0.93162\n[498]\tvalidation_0-auc:0.93158\n[499]\tvalidation_0-auc:0.93156\n[500]\tvalidation_0-auc:0.93158\n[501]\tvalidation_0-auc:0.93156\n[502]\tvalidation_0-auc:0.93155\n[503]\tvalidation_0-auc:0.93153\n[504]\tvalidation_0-auc:0.93151\n[505]\tvalidation_0-auc:0.93148\n[506]\tvalidation_0-auc:0.93148\n[507]\tvalidation_0-auc:0.93148\n[508]\tvalidation_0-auc:0.93149\n[509]\tvalidation_0-auc:0.93154\n[510]\tvalidation_0-auc:0.93157\n[511]\tvalidation_0-auc:0.93156\n[512]\tvalidation_0-auc:0.93153\n[513]\tvalidation_0-auc:0.93155\n[514]\tvalidation_0-auc:0.93157\n[515]\tvalidation_0-auc:0.93157\n[516]\tvalidation_0-auc:0.93156\n[517]\tvalidation_0-auc:0.93154\n[518]\tvalidation_0-auc:0.93156\n[519]\tvalidation_0-auc:0.93156\n[520]\tvalidation_0-auc:0.93154\n[521]\tvalidation_0-auc:0.93151\n[522]\tvalidation_0-auc:0.93154\n[523]\tvalidation_0-auc:0.93152\n[524]\tvalidation_0-auc:0.93151\n[525]\tvalidation_0-auc:0.93150\n[526]\tvalidation_0-auc:0.93153\n[527]\tvalidation_0-auc:0.93153\n[528]\tvalidation_0-auc:0.93155\n[529]\tvalidation_0-auc:0.93155\n[530]\tvalidation_0-auc:0.93156\n[531]\tvalidation_0-auc:0.93156\n[532]\tvalidation_0-auc:0.93154\n[533]\tvalidation_0-auc:0.93153\n[534]\tvalidation_0-auc:0.93152\n[535]\tvalidation_0-auc:0.93153\n[536]\tvalidation_0-auc:0.93151\n[537]\tvalidation_0-auc:0.93150\n[538]\tvalidation_0-auc:0.93150\n[539]\tvalidation_0-auc:0.93151\n[540]\tvalidation_0-auc:0.93153\n[541]\tvalidation_0-auc:0.93151\n[542]\tvalidation_0-auc:0.93150\n[543]\tvalidation_0-auc:0.93152\n[544]\tvalidation_0-auc:0.93155\n[545]\tvalidation_0-auc:0.93154\n[546]\tvalidation_0-auc:0.93154\n[547]\tvalidation_0-auc:0.93154\n[548]\tvalidation_0-auc:0.93155\n[549]\tvalidation_0-auc:0.93153\n[550]\tvalidation_0-auc:0.93151\n[551]\tvalidation_0-auc:0.93151\n[552]\tvalidation_0-auc:0.93151\n[553]\tvalidation_0-auc:0.93150\n[554]\tvalidation_0-auc:0.93152\n[555]\tvalidation_0-auc:0.93152\n[556]\tvalidation_0-auc:0.93151\n[557]\tvalidation_0-auc:0.93150\n[558]\tvalidation_0-auc:0.93149\n[559]\tvalidation_0-auc:0.93149\n[560]\tvalidation_0-auc:0.93150\n[561]\tvalidation_0-auc:0.93149\n[562]\tvalidation_0-auc:0.93150\n[563]\tvalidation_0-auc:0.93152\n[564]\tvalidation_0-auc:0.93150\n[565]\tvalidation_0-auc:0.93148\n[566]\tvalidation_0-auc:0.93147\n[567]\tvalidation_0-auc:0.93147\n[568]\tvalidation_0-auc:0.93148\n[569]\tvalidation_0-auc:0.93146\n[570]\tvalidation_0-auc:0.93148\n[571]\tvalidation_0-auc:0.93147\n[572]\tvalidation_0-auc:0.93150\n[573]\tvalidation_0-auc:0.93150\n[574]\tvalidation_0-auc:0.93149\n[575]\tvalidation_0-auc:0.93147\n[576]\tvalidation_0-auc:0.93148\n[577]\tvalidation_0-auc:0.93149\n[578]\tvalidation_0-auc:0.93150\n[579]\tvalidation_0-auc:0.93153\n[580]\tvalidation_0-auc:0.93153\n[581]\tvalidation_0-auc:0.93153\n[582]\tvalidation_0-auc:0.93153\n[583]\tvalidation_0-auc:0.93151\n[584]\tvalidation_0-auc:0.93152\n[585]\tvalidation_0-auc:0.93152\n[586]\tvalidation_0-auc:0.93151\n[587]\tvalidation_0-auc:0.93151\n[0]\tvalidation_0-auc:0.86942\n[1]\tvalidation_0-auc:0.89070\n[2]\tvalidation_0-auc:0.88742\n[3]\tvalidation_0-auc:0.87897\n[4]\tvalidation_0-auc:0.87720\n[5]\tvalidation_0-auc:0.90129\n[6]\tvalidation_0-auc:0.90854\n[7]\tvalidation_0-auc:0.90787\n[8]\tvalidation_0-auc:0.90431\n[9]\tvalidation_0-auc:0.91046\n"},{"name":"stderr","output_type":"stream","text":["E:\\Anaconda3\\lib\\site-packages\\xgboost\\sklearn.py:797: UserWarning: `eval_metric` in `fit` method is deprecated for better compatibility with scikit-learn, use `eval_metric` in constructor or`set_params` instead.\n"," UserWarning,\n","E:\\Anaconda3\\lib\\site-packages\\xgboost\\sklearn.py:797: UserWarning: `early_stopping_rounds` in `fit` method is deprecated for better compatibility with scikit-learn, use `early_stopping_rounds` in constructor or`set_params` instead.\n"," UserWarning,\n"]},{"name":"stdout","output_type":"stream","text":"[10]\tvalidation_0-auc:0.91408\n[11]\tvalidation_0-auc:0.91608\n[12]\tvalidation_0-auc:0.91840\n[13]\tvalidation_0-auc:0.91914\n[14]\tvalidation_0-auc:0.91867\n[15]\tvalidation_0-auc:0.91971\n[16]\tvalidation_0-auc:0.91925\n[17]\tvalidation_0-auc:0.91914\n[18]\tvalidation_0-auc:0.91887\n[19]\tvalidation_0-auc:0.91968\n[20]\tvalidation_0-auc:0.91991\n[21]\tvalidation_0-auc:0.92078\n[22]\tvalidation_0-auc:0.92122\n[23]\tvalidation_0-auc:0.92099\n[24]\tvalidation_0-auc:0.92052\n[25]\tvalidation_0-auc:0.92125\n[26]\tvalidation_0-auc:0.92111\n[27]\tvalidation_0-auc:0.92123\n[28]\tvalidation_0-auc:0.92137\n[29]\tvalidation_0-auc:0.92094\n[30]\tvalidation_0-auc:0.92228\n[31]\tvalidation_0-auc:0.92244\n[32]\tvalidation_0-auc:0.92273\n[33]\tvalidation_0-auc:0.92338\n[34]\tvalidation_0-auc:0.92305\n[35]\tvalidation_0-auc:0.92392\n[36]\tvalidation_0-auc:0.92400\n[37]\tvalidation_0-auc:0.92406\n[38]\tvalidation_0-auc:0.92395\n[39]\tvalidation_0-auc:0.92397\n[40]\tvalidation_0-auc:0.92420\n[41]\tvalidation_0-auc:0.92421\n[42]\tvalidation_0-auc:0.92402\n[43]\tvalidation_0-auc:0.92400\n[44]\tvalidation_0-auc:0.92413\n[45]\tvalidation_0-auc:0.92423\n[46]\tvalidation_0-auc:0.92447\n[47]\tvalidation_0-auc:0.92430\n[48]\tvalidation_0-auc:0.92398\n[49]\tvalidation_0-auc:0.92396\n[50]\tvalidation_0-auc:0.92421\n[51]\tvalidation_0-auc:0.92446\n[52]\tvalidation_0-auc:0.92457\n[53]\tvalidation_0-auc:0.92460\n[54]\tvalidation_0-auc:0.92465\n[55]\tvalidation_0-auc:0.92436\n[56]\tvalidation_0-auc:0.92416\n[57]\tvalidation_0-auc:0.92396\n[58]\tvalidation_0-auc:0.92380\n[59]\tvalidation_0-auc:0.92358\n[60]\tvalidation_0-auc:0.92393\n[61]\tvalidation_0-auc:0.92403\n[62]\tvalidation_0-auc:0.92413\n[63]\tvalidation_0-auc:0.92405\n[64]\tvalidation_0-auc:0.92395\n[65]\tvalidation_0-auc:0.92396\n[66]\tvalidation_0-auc:0.92405\n[67]\tvalidation_0-auc:0.92405\n[68]\tvalidation_0-auc:0.92409\n[69]\tvalidation_0-auc:0.92443\n[70]\tvalidation_0-auc:0.92456\n[71]\tvalidation_0-auc:0.92462\n[72]\tvalidation_0-auc:0.92468\n[73]\tvalidation_0-auc:0.92493\n[74]\tvalidation_0-auc:0.92498\n[75]\tvalidation_0-auc:0.92528\n[76]\tvalidation_0-auc:0.92526\n[77]\tvalidation_0-auc:0.92547\n[78]\tvalidation_0-auc:0.92553\n[79]\tvalidation_0-auc:0.92548\n[80]\tvalidation_0-auc:0.92569\n[81]\tvalidation_0-auc:0.92601\n[82]\tvalidation_0-auc:0.92591\n[83]\tvalidation_0-auc:0.92587\n[84]\tvalidation_0-auc:0.92597\n[85]\tvalidation_0-auc:0.92615\n[86]\tvalidation_0-auc:0.92632\n[87]\tvalidation_0-auc:0.92656\n[88]\tvalidation_0-auc:0.92666\n[89]\tvalidation_0-auc:0.92697\n[90]\tvalidation_0-auc:0.92710\n[91]\tvalidation_0-auc:0.92701\n[92]\tvalidation_0-auc:0.92718\n[93]\tvalidation_0-auc:0.92717\n[94]\tvalidation_0-auc:0.92717\n[95]\tvalidation_0-auc:0.92716\n[96]\tvalidation_0-auc:0.92717\n[97]\tvalidation_0-auc:0.92720\n[98]\tvalidation_0-auc:0.92732\n[99]\tvalidation_0-auc:0.92731\n[100]\tvalidation_0-auc:0.92720\n[101]\tvalidation_0-auc:0.92712\n[102]\tvalidation_0-auc:0.92720\n[103]\tvalidation_0-auc:0.92729\n[104]\tvalidation_0-auc:0.92741\n[105]\tvalidation_0-auc:0.92764\n[106]\tvalidation_0-auc:0.92777\n[107]\tvalidation_0-auc:0.92792\n[108]\tvalidation_0-auc:0.92775\n[109]\tvalidation_0-auc:0.92791\n[110]\tvalidation_0-auc:0.92793\n[111]\tvalidation_0-auc:0.92793\n[112]\tvalidation_0-auc:0.92795\n[113]\tvalidation_0-auc:0.92805\n[114]\tvalidation_0-auc:0.92810\n[115]\tvalidation_0-auc:0.92821\n[116]\tvalidation_0-auc:0.92824\n[117]\tvalidation_0-auc:0.92831\n[118]\tvalidation_0-auc:0.92825\n[119]\tvalidation_0-auc:0.92831\n[120]\tvalidation_0-auc:0.92838\n[121]\tvalidation_0-auc:0.92856\n[122]\tvalidation_0-auc:0.92856\n[123]\tvalidation_0-auc:0.92855\n[124]\tvalidation_0-auc:0.92871\n[125]\tvalidation_0-auc:0.92876\n[126]\tvalidation_0-auc:0.92868\n[127]\tvalidation_0-auc:0.92875\n[128]\tvalidation_0-auc:0.92889\n[129]\tvalidation_0-auc:0.92896\n[130]\tvalidation_0-auc:0.92899\n[131]\tvalidation_0-auc:0.92897\n[132]\tvalidation_0-auc:0.92891\n[133]\tvalidation_0-auc:0.92894\n[134]\tvalidation_0-auc:0.92898\n[135]\tvalidation_0-auc:0.92894\n[136]\tvalidation_0-auc:0.92892\n[137]\tvalidation_0-auc:0.92889\n[138]\tvalidation_0-auc:0.92894\n[139]\tvalidation_0-auc:0.92900\n[140]\tvalidation_0-auc:0.92910\n[141]\tvalidation_0-auc:0.92937\n[142]\tvalidation_0-auc:0.92950\n[143]\tvalidation_0-auc:0.92964\n[144]\tvalidation_0-auc:0.92968\n[145]\tvalidation_0-auc:0.92971\n[146]\tvalidation_0-auc:0.92975\n[147]\tvalidation_0-auc:0.92972\n[148]\tvalidation_0-auc:0.92979\n[149]\tvalidation_0-auc:0.92981\n[150]\tvalidation_0-auc:0.92982\n[151]\tvalidation_0-auc:0.92986\n[152]\tvalidation_0-auc:0.92980\n[153]\tvalidation_0-auc:0.92990\n[154]\tvalidation_0-auc:0.92995\n[155]\tvalidation_0-auc:0.92993\n[156]\tvalidation_0-auc:0.92994\n[157]\tvalidation_0-auc:0.92991\n[158]\tvalidation_0-auc:0.92994\n[159]\tvalidation_0-auc:0.92994\n[160]\tvalidation_0-auc:0.93000\n[161]\tvalidation_0-auc:0.93001\n[162]\tvalidation_0-auc:0.93004\n[163]\tvalidation_0-auc:0.93009\n[164]\tvalidation_0-auc:0.93014\n[165]\tvalidation_0-auc:0.93012\n[166]\tvalidation_0-auc:0.93010\n[167]\tvalidation_0-auc:0.93019\n[168]\tvalidation_0-auc:0.93031\n[169]\tvalidation_0-auc:0.93033\n[170]\tvalidation_0-auc:0.93034\n[171]\tvalidation_0-auc:0.93036\n[172]\tvalidation_0-auc:0.93038\n[173]\tvalidation_0-auc:0.93040\n[174]\tvalidation_0-auc:0.93042\n[175]\tvalidation_0-auc:0.93044\n[176]\tvalidation_0-auc:0.93048\n[177]\tvalidation_0-auc:0.93045\n[178]\tvalidation_0-auc:0.93049\n[179]\tvalidation_0-auc:0.93055\n[180]\tvalidation_0-auc:0.93065\n[181]\tvalidation_0-auc:0.93067\n[182]\tvalidation_0-auc:0.93074\n[183]\tvalidation_0-auc:0.93073\n[184]\tvalidation_0-auc:0.93071\n[185]\tvalidation_0-auc:0.93073\n[186]\tvalidation_0-auc:0.93074\n[187]\tvalidation_0-auc:0.93081\n[188]\tvalidation_0-auc:0.93080\n[189]\tvalidation_0-auc:0.93081\n[190]\tvalidation_0-auc:0.93085\n[191]\tvalidation_0-auc:0.93093\n[192]\tvalidation_0-auc:0.93098\n[193]\tvalidation_0-auc:0.93096\n[194]\tvalidation_0-auc:0.93104\n[195]\tvalidation_0-auc:0.93117\n[196]\tvalidation_0-auc:0.93116\n[197]\tvalidation_0-auc:0.93124\n[198]\tvalidation_0-auc:0.93122\n[199]\tvalidation_0-auc:0.93124\n[200]\tvalidation_0-auc:0.93128\n[201]\tvalidation_0-auc:0.93132\n[202]\tvalidation_0-auc:0.93134\n[203]\tvalidation_0-auc:0.93137\n[204]\tvalidation_0-auc:0.93143\n[205]\tvalidation_0-auc:0.93141\n[206]\tvalidation_0-auc:0.93153\n[207]\tvalidation_0-auc:0.93158\n[208]\tvalidation_0-auc:0.93164\n[209]\tvalidation_0-auc:0.93162\n[210]\tvalidation_0-auc:0.93161\n[211]\tvalidation_0-auc:0.93164\n[212]\tvalidation_0-auc:0.93167\n[213]\tvalidation_0-auc:0.93167\n[214]\tvalidation_0-auc:0.93163\n[215]\tvalidation_0-auc:0.93165\n[216]\tvalidation_0-auc:0.93172\n[217]\tvalidation_0-auc:0.93167\n[218]\tvalidation_0-auc:0.93171\n[219]\tvalidation_0-auc:0.93177\n[220]\tvalidation_0-auc:0.93179\n[221]\tvalidation_0-auc:0.93183\n[222]\tvalidation_0-auc:0.93190\n[223]\tvalidation_0-auc:0.93192\n[224]\tvalidation_0-auc:0.93195\n[225]\tvalidation_0-auc:0.93197\n[226]\tvalidation_0-auc:0.93204\n[227]\tvalidation_0-auc:0.93211\n[228]\tvalidation_0-auc:0.93212\n[229]\tvalidation_0-auc:0.93212\n[230]\tvalidation_0-auc:0.93210\n[231]\tvalidation_0-auc:0.93213\n[232]\tvalidation_0-auc:0.93214\n[233]\tvalidation_0-auc:0.93213\n[234]\tvalidation_0-auc:0.93214\n[235]\tvalidation_0-auc:0.93217\n[236]\tvalidation_0-auc:0.93214\n[237]\tvalidation_0-auc:0.93220\n[238]\tvalidation_0-auc:0.93236\n[239]\tvalidation_0-auc:0.93234\n[240]\tvalidation_0-auc:0.93234\n[241]\tvalidation_0-auc:0.93237\n[242]\tvalidation_0-auc:0.93241\n[243]\tvalidation_0-auc:0.93255\n[244]\tvalidation_0-auc:0.93254\n[245]\tvalidation_0-auc:0.93257\n[246]\tvalidation_0-auc:0.93257\n[247]\tvalidation_0-auc:0.93256\n[248]\tvalidation_0-auc:0.93256\n[249]\tvalidation_0-auc:0.93253\n[250]\tvalidation_0-auc:0.93250\n[251]\tvalidation_0-auc:0.93254\n[252]\tvalidation_0-auc:0.93257\n[253]\tvalidation_0-auc:0.93259\n[254]\tvalidation_0-auc:0.93263\n[255]\tvalidation_0-auc:0.93272\n[256]\tvalidation_0-auc:0.93269\n[257]\tvalidation_0-auc:0.93273\n[258]\tvalidation_0-auc:0.93275\n[259]\tvalidation_0-auc:0.93281\n[260]\tvalidation_0-auc:0.93281\n[261]\tvalidation_0-auc:0.93277\n[262]\tvalidation_0-auc:0.93278\n[263]\tvalidation_0-auc:0.93283\n[264]\tvalidation_0-auc:0.93279\n[265]\tvalidation_0-auc:0.93298\n[266]\tvalidation_0-auc:0.93299\n[267]\tvalidation_0-auc:0.93298\n[268]\tvalidation_0-auc:0.93300\n[269]\tvalidation_0-auc:0.93306\n[270]\tvalidation_0-auc:0.93307\n[271]\tvalidation_0-auc:0.93308\n[272]\tvalidation_0-auc:0.93307\n[273]\tvalidation_0-auc:0.93304\n[274]\tvalidation_0-auc:0.93305\n[275]\tvalidation_0-auc:0.93313\n[276]\tvalidation_0-auc:0.93328\n[277]\tvalidation_0-auc:0.93330\n[278]\tvalidation_0-auc:0.93335\n[279]\tvalidation_0-auc:0.93338\n[280]\tvalidation_0-auc:0.93337\n[281]\tvalidation_0-auc:0.93340\n[282]\tvalidation_0-auc:0.93347\n[283]\tvalidation_0-auc:0.93351\n[284]\tvalidation_0-auc:0.93355\n[285]\tvalidation_0-auc:0.93350\n[286]\tvalidation_0-auc:0.93351\n[287]\tvalidation_0-auc:0.93353\n[288]\tvalidation_0-auc:0.93353\n[289]\tvalidation_0-auc:0.93355\n[290]\tvalidation_0-auc:0.93355\n[291]\tvalidation_0-auc:0.93359\n[292]\tvalidation_0-auc:0.93361\n[293]\tvalidation_0-auc:0.93363\n[294]\tvalidation_0-auc:0.93367\n[295]\tvalidation_0-auc:0.93368\n[296]\tvalidation_0-auc:0.93368\n[297]\tvalidation_0-auc:0.93368\n[298]\tvalidation_0-auc:0.93369\n[299]\tvalidation_0-auc:0.93369\n[300]\tvalidation_0-auc:0.93365\n[301]\tvalidation_0-auc:0.93369\n[302]\tvalidation_0-auc:0.93371\n[303]\tvalidation_0-auc:0.93371\n[304]\tvalidation_0-auc:0.93372\n[305]\tvalidation_0-auc:0.93374\n[306]\tvalidation_0-auc:0.93373\n[307]\tvalidation_0-auc:0.93371\n[308]\tvalidation_0-auc:0.93371\n[309]\tvalidation_0-auc:0.93375\n[310]\tvalidation_0-auc:0.93381\n[311]\tvalidation_0-auc:0.93387\n[312]\tvalidation_0-auc:0.93394\n[313]\tvalidation_0-auc:0.93395\n[314]\tvalidation_0-auc:0.93398\n[315]\tvalidation_0-auc:0.93399\n[316]\tvalidation_0-auc:0.93399\n[317]\tvalidation_0-auc:0.93405\n[318]\tvalidation_0-auc:0.93404\n[319]\tvalidation_0-auc:0.93406\n[320]\tvalidation_0-auc:0.93405\n[321]\tvalidation_0-auc:0.93406\n[322]\tvalidation_0-auc:0.93407\n[323]\tvalidation_0-auc:0.93404\n[324]\tvalidation_0-auc:0.93408\n[325]\tvalidation_0-auc:0.93409\n[326]\tvalidation_0-auc:0.93410\n[327]\tvalidation_0-auc:0.93410\n[328]\tvalidation_0-auc:0.93416\n[329]\tvalidation_0-auc:0.93417\n[330]\tvalidation_0-auc:0.93417\n[331]\tvalidation_0-auc:0.93413\n[332]\tvalidation_0-auc:0.93420\n[333]\tvalidation_0-auc:0.93425\n[334]\tvalidation_0-auc:0.93435\n[335]\tvalidation_0-auc:0.93437\n[336]\tvalidation_0-auc:0.93437\n[337]\tvalidation_0-auc:0.93435\n[338]\tvalidation_0-auc:0.93438\n[339]\tvalidation_0-auc:0.93439\n[340]\tvalidation_0-auc:0.93439\n[341]\tvalidation_0-auc:0.93436\n[342]\tvalidation_0-auc:0.93434\n[343]\tvalidation_0-auc:0.93439\n[344]\tvalidation_0-auc:0.93440\n[345]\tvalidation_0-auc:0.93440\n[346]\tvalidation_0-auc:0.93439\n[347]\tvalidation_0-auc:0.93446\n[348]\tvalidation_0-auc:0.93448\n[349]\tvalidation_0-auc:0.93448\n[350]\tvalidation_0-auc:0.93450\n[351]\tvalidation_0-auc:0.93449\n[352]\tvalidation_0-auc:0.93448\n[353]\tvalidation_0-auc:0.93450\n[354]\tvalidation_0-auc:0.93451\n[355]\tvalidation_0-auc:0.93458\n[356]\tvalidation_0-auc:0.93456\n[357]\tvalidation_0-auc:0.93456\n[358]\tvalidation_0-auc:0.93454\n[359]\tvalidation_0-auc:0.93456\n[360]\tvalidation_0-auc:0.93454\n[361]\tvalidation_0-auc:0.93452\n[362]\tvalidation_0-auc:0.93453\n[363]\tvalidation_0-auc:0.93456\n[364]\tvalidation_0-auc:0.93453\n[365]\tvalidation_0-auc:0.93455\n[366]\tvalidation_0-auc:0.93466\n[367]\tvalidation_0-auc:0.93468\n[368]\tvalidation_0-auc:0.93466\n[369]\tvalidation_0-auc:0.93463\n[370]\tvalidation_0-auc:0.93470\n[371]\tvalidation_0-auc:0.93471\n[372]\tvalidation_0-auc:0.93471\n[373]\tvalidation_0-auc:0.93472\n[374]\tvalidation_0-auc:0.93477\n[375]\tvalidation_0-auc:0.93480\n[376]\tvalidation_0-auc:0.93484\n[377]\tvalidation_0-auc:0.93484\n[378]\tvalidation_0-auc:0.93483\n[379]\tvalidation_0-auc:0.93484\n[380]\tvalidation_0-auc:0.93486\n[381]\tvalidation_0-auc:0.93485\n[382]\tvalidation_0-auc:0.93484\n[383]\tvalidation_0-auc:0.93484\n[384]\tvalidation_0-auc:0.93486\n[385]\tvalidation_0-auc:0.93487\n[386]\tvalidation_0-auc:0.93486\n[387]\tvalidation_0-auc:0.93483\n[388]\tvalidation_0-auc:0.93485\n[389]\tvalidation_0-auc:0.93483\n[390]\tvalidation_0-auc:0.93485\n[391]\tvalidation_0-auc:0.93483\n[392]\tvalidation_0-auc:0.93483\n[393]\tvalidation_0-auc:0.93482\n[394]\tvalidation_0-auc:0.93487\n[395]\tvalidation_0-auc:0.93487\n[396]\tvalidation_0-auc:0.93488\n[397]\tvalidation_0-auc:0.93487\n[398]\tvalidation_0-auc:0.93487\n[399]\tvalidation_0-auc:0.93488\n[400]\tvalidation_0-auc:0.93494\n[401]\tvalidation_0-auc:0.93497\n[402]\tvalidation_0-auc:0.93498\n[403]\tvalidation_0-auc:0.93499\n[404]\tvalidation_0-auc:0.93501\n[405]\tvalidation_0-auc:0.93504\n[406]\tvalidation_0-auc:0.93508\n[407]\tvalidation_0-auc:0.93506\n[408]\tvalidation_0-auc:0.93504\n[409]\tvalidation_0-auc:0.93504\n[410]\tvalidation_0-auc:0.93503\n[411]\tvalidation_0-auc:0.93504\n[412]\tvalidation_0-auc:0.93504\n[413]\tvalidation_0-auc:0.93507\n[414]\tvalidation_0-auc:0.93511\n[415]\tvalidation_0-auc:0.93512\n[416]\tvalidation_0-auc:0.93516\n[417]\tvalidation_0-auc:0.93517\n[418]\tvalidation_0-auc:0.93516\n[419]\tvalidation_0-auc:0.93519\n[420]\tvalidation_0-auc:0.93515\n[421]\tvalidation_0-auc:0.93512\n[422]\tvalidation_0-auc:0.93513\n[423]\tvalidation_0-auc:0.93513\n[424]\tvalidation_0-auc:0.93516\n[425]\tvalidation_0-auc:0.93514\n[426]\tvalidation_0-auc:0.93514\n[427]\tvalidation_0-auc:0.93513\n[428]\tvalidation_0-auc:0.93518\n[429]\tvalidation_0-auc:0.93517\n[430]\tvalidation_0-auc:0.93517\n[431]\tvalidation_0-auc:0.93517\n[432]\tvalidation_0-auc:0.93520\n[433]\tvalidation_0-auc:0.93521\n[434]\tvalidation_0-auc:0.93522\n[435]\tvalidation_0-auc:0.93522\n[436]\tvalidation_0-auc:0.93518\n[437]\tvalidation_0-auc:0.93523\n[438]\tvalidation_0-auc:0.93524\n[439]\tvalidation_0-auc:0.93527\n[440]\tvalidation_0-auc:0.93528\n[441]\tvalidation_0-auc:0.93527\n[442]\tvalidation_0-auc:0.93531\n[443]\tvalidation_0-auc:0.93535\n[444]\tvalidation_0-auc:0.93535\n[445]\tvalidation_0-auc:0.93535\n[446]\tvalidation_0-auc:0.93536\n[447]\tvalidation_0-auc:0.93539\n[448]\tvalidation_0-auc:0.93542\n[449]\tvalidation_0-auc:0.93542\n[450]\tvalidation_0-auc:0.93543\n[451]\tvalidation_0-auc:0.93543\n[452]\tvalidation_0-auc:0.93547\n[453]\tvalidation_0-auc:0.93551\n[454]\tvalidation_0-auc:0.93550\n[455]\tvalidation_0-auc:0.93553\n[456]\tvalidation_0-auc:0.93554\n[457]\tvalidation_0-auc:0.93553\n[458]\tvalidation_0-auc:0.93554\n[459]\tvalidation_0-auc:0.93559\n[460]\tvalidation_0-auc:0.93560\n[461]\tvalidation_0-auc:0.93557\n[462]\tvalidation_0-auc:0.93559\n[463]\tvalidation_0-auc:0.93561\n[464]\tvalidation_0-auc:0.93563\n[465]\tvalidation_0-auc:0.93564\n[466]\tvalidation_0-auc:0.93565\n[467]\tvalidation_0-auc:0.93563\n[468]\tvalidation_0-auc:0.93565\n[469]\tvalidation_0-auc:0.93563\n[470]\tvalidation_0-auc:0.93567\n[471]\tvalidation_0-auc:0.93565\n[472]\tvalidation_0-auc:0.93566\n[473]\tvalidation_0-auc:0.93569\n[474]\tvalidation_0-auc:0.93570\n[475]\tvalidation_0-auc:0.93568\n[476]\tvalidation_0-auc:0.93572\n[477]\tvalidation_0-auc:0.93572\n[478]\tvalidation_0-auc:0.93573\n[479]\tvalidation_0-auc:0.93573\n[480]\tvalidation_0-auc:0.93574\n[481]\tvalidation_0-auc:0.93573\n[482]\tvalidation_0-auc:0.93576\n[483]\tvalidation_0-auc:0.93577\n[484]\tvalidation_0-auc:0.93580\n[485]\tvalidation_0-auc:0.93579\n[486]\tvalidation_0-auc:0.93582\n[487]\tvalidation_0-auc:0.93583\n[488]\tvalidation_0-auc:0.93582\n[489]\tvalidation_0-auc:0.93582\n[490]\tvalidation_0-auc:0.93581\n[491]\tvalidation_0-auc:0.93586\n[492]\tvalidation_0-auc:0.93584\n[493]\tvalidation_0-auc:0.93587\n[494]\tvalidation_0-auc:0.93589\n[495]\tvalidation_0-auc:0.93589\n[496]\tvalidation_0-auc:0.93589\n[497]\tvalidation_0-auc:0.93590\n[498]\tvalidation_0-auc:0.93590\n[499]\tvalidation_0-auc:0.93589\n[500]\tvalidation_0-auc:0.93591\n[501]\tvalidation_0-auc:0.93589\n[502]\tvalidation_0-auc:0.93589\n[503]\tvalidation_0-auc:0.93591\n[504]\tvalidation_0-auc:0.93594\n[505]\tvalidation_0-auc:0.93590\n[506]\tvalidation_0-auc:0.93593\n[507]\tvalidation_0-auc:0.93592\n[508]\tvalidation_0-auc:0.93594\n[509]\tvalidation_0-auc:0.93598\n[510]\tvalidation_0-auc:0.93597\n[511]\tvalidation_0-auc:0.93594\n[512]\tvalidation_0-auc:0.93593\n[513]\tvalidation_0-auc:0.93589\n[514]\tvalidation_0-auc:0.93591\n[515]\tvalidation_0-auc:0.93592\n[516]\tvalidation_0-auc:0.93591\n[517]\tvalidation_0-auc:0.93591\n[518]\tvalidation_0-auc:0.93591\n[519]\tvalidation_0-auc:0.93591\n[520]\tvalidation_0-auc:0.93589\n[521]\tvalidation_0-auc:0.93588\n[522]\tvalidation_0-auc:0.93588\n[523]\tvalidation_0-auc:0.93595\n[524]\tvalidation_0-auc:0.93595\n[525]\tvalidation_0-auc:0.93598\n[526]\tvalidation_0-auc:0.93598\n[527]\tvalidation_0-auc:0.93599\n[528]\tvalidation_0-auc:0.93595\n[529]\tvalidation_0-auc:0.93594\n[530]\tvalidation_0-auc:0.93597\n[531]\tvalidation_0-auc:0.93594\n[532]\tvalidation_0-auc:0.93594\n[533]\tvalidation_0-auc:0.93595\n[534]\tvalidation_0-auc:0.93594\n[535]\tvalidation_0-auc:0.93594\n[536]\tvalidation_0-auc:0.93594\n[537]\tvalidation_0-auc:0.93593\n[538]\tvalidation_0-auc:0.93592\n[539]\tvalidation_0-auc:0.93596\n[540]\tvalidation_0-auc:0.93595\n[541]\tvalidation_0-auc:0.93596\n[542]\tvalidation_0-auc:0.93597\n[543]\tvalidation_0-auc:0.93596\n[544]\tvalidation_0-auc:0.93603\n[545]\tvalidation_0-auc:0.93605\n[546]\tvalidation_0-auc:0.93606\n[547]\tvalidation_0-auc:0.93603\n[548]\tvalidation_0-auc:0.93604\n[549]\tvalidation_0-auc:0.93602\n[550]\tvalidation_0-auc:0.93604\n[551]\tvalidation_0-auc:0.93604\n[552]\tvalidation_0-auc:0.93606\n[553]\tvalidation_0-auc:0.93605\n[554]\tvalidation_0-auc:0.93606\n[555]\tvalidation_0-auc:0.93607\n[556]\tvalidation_0-auc:0.93607\n[557]\tvalidation_0-auc:0.93608\n[558]\tvalidation_0-auc:0.93607\n[559]\tvalidation_0-auc:0.93608\n[560]\tvalidation_0-auc:0.93609\n[561]\tvalidation_0-auc:0.93608\n[562]\tvalidation_0-auc:0.93609\n[563]\tvalidation_0-auc:0.93609\n[564]\tvalidation_0-auc:0.93610\n[565]\tvalidation_0-auc:0.93609\n[566]\tvalidation_0-auc:0.93608\n[567]\tvalidation_0-auc:0.93611\n[568]\tvalidation_0-auc:0.93611\n[569]\tvalidation_0-auc:0.93612\n[570]\tvalidation_0-auc:0.93609\n[571]\tvalidation_0-auc:0.93610\n[572]\tvalidation_0-auc:0.93613\n[573]\tvalidation_0-auc:0.93613\n[574]\tvalidation_0-auc:0.93614\n[575]\tvalidation_0-auc:0.93616\n[576]\tvalidation_0-auc:0.93616\n[577]\tvalidation_0-auc:0.93615\n[578]\tvalidation_0-auc:0.93618\n[579]\tvalidation_0-auc:0.93619\n[580]\tvalidation_0-auc:0.93617\n[581]\tvalidation_0-auc:0.93617\n[582]\tvalidation_0-auc:0.93617\n[583]\tvalidation_0-auc:0.93616\n[584]\tvalidation_0-auc:0.93623\n[585]\tvalidation_0-auc:0.93625\n[586]\tvalidation_0-auc:0.93628\n[587]\tvalidation_0-auc:0.93629\n[588]\tvalidation_0-auc:0.93630\n[589]\tvalidation_0-auc:0.93628\n[590]\tvalidation_0-auc:0.93625\n[591]\tvalidation_0-auc:0.93625\n[592]\tvalidation_0-auc:0.93623\n[593]\tvalidation_0-auc:0.93625\n[594]\tvalidation_0-auc:0.93626\n[595]\tvalidation_0-auc:0.93626\n[596]\tvalidation_0-auc:0.93626\n[597]\tvalidation_0-auc:0.93627\n[598]\tvalidation_0-auc:0.93624\n[599]\tvalidation_0-auc:0.93626\n[600]\tvalidation_0-auc:0.93624\n[601]\tvalidation_0-auc:0.93622\n[602]\tvalidation_0-auc:0.93622\n[603]\tvalidation_0-auc:0.93626\n[604]\tvalidation_0-auc:0.93627\n[605]\tvalidation_0-auc:0.93624\n[606]\tvalidation_0-auc:0.93627\n[607]\tvalidation_0-auc:0.93628\n[608]\tvalidation_0-auc:0.93626\n[609]\tvalidation_0-auc:0.93629\n[610]\tvalidation_0-auc:0.93631\n[611]\tvalidation_0-auc:0.93631\n[612]\tvalidation_0-auc:0.93637\n[613]\tvalidation_0-auc:0.93638\n[614]\tvalidation_0-auc:0.93639\n[615]\tvalidation_0-auc:0.93640\n[616]\tvalidation_0-auc:0.93639\n[617]\tvalidation_0-auc:0.93639\n[618]\tvalidation_0-auc:0.93638\n[619]\tvalidation_0-auc:0.93639\n[620]\tvalidation_0-auc:0.93641\n[621]\tvalidation_0-auc:0.93642\n[622]\tvalidation_0-auc:0.93640\n[623]\tvalidation_0-auc:0.93638\n[624]\tvalidation_0-auc:0.93637\n[625]\tvalidation_0-auc:0.93638\n[626]\tvalidation_0-auc:0.93645\n[627]\tvalidation_0-auc:0.93648\n[628]\tvalidation_0-auc:0.93646\n[629]\tvalidation_0-auc:0.93646\n[630]\tvalidation_0-auc:0.93646\n[631]\tvalidation_0-auc:0.93645\n[632]\tvalidation_0-auc:0.93646\n[633]\tvalidation_0-auc:0.93647\n[634]\tvalidation_0-auc:0.93649\n[635]\tvalidation_0-auc:0.93650\n[636]\tvalidation_0-auc:0.93650\n[637]\tvalidation_0-auc:0.93654\n[638]\tvalidation_0-auc:0.93655\n[639]\tvalidation_0-auc:0.93657\n[640]\tvalidation_0-auc:0.93658\n[641]\tvalidation_0-auc:0.93657\n[642]\tvalidation_0-auc:0.93656\n[643]\tvalidation_0-auc:0.93656\n[644]\tvalidation_0-auc:0.93654\n[645]\tvalidation_0-auc:0.93653\n[646]\tvalidation_0-auc:0.93652\n[647]\tvalidation_0-auc:0.93651\n[648]\tvalidation_0-auc:0.93652\n[649]\tvalidation_0-auc:0.93654\n[650]\tvalidation_0-auc:0.93655\n[651]\tvalidation_0-auc:0.93654\n[652]\tvalidation_0-auc:0.93653\n[653]\tvalidation_0-auc:0.93652\n[654]\tvalidation_0-auc:0.93652\n[655]\tvalidation_0-auc:0.93652\n[656]\tvalidation_0-auc:0.93650\n[657]\tvalidation_0-auc:0.93649\n[658]\tvalidation_0-auc:0.93649\n[659]\tvalidation_0-auc:0.93650\n[660]\tvalidation_0-auc:0.93651\n[661]\tvalidation_0-auc:0.93650\n[662]\tvalidation_0-auc:0.93649\n[663]\tvalidation_0-auc:0.93649\n[664]\tvalidation_0-auc:0.93650\n[665]\tvalidation_0-auc:0.93648\n[666]\tvalidation_0-auc:0.93649\n[667]\tvalidation_0-auc:0.93648\n[668]\tvalidation_0-auc:0.93653\n[669]\tvalidation_0-auc:0.93653\n[670]\tvalidation_0-auc:0.93654\n[671]\tvalidation_0-auc:0.93656\n[672]\tvalidation_0-auc:0.93652\n[673]\tvalidation_0-auc:0.93652\n[674]\tvalidation_0-auc:0.93652\n[675]\tvalidation_0-auc:0.93654\n[676]\tvalidation_0-auc:0.93653\n[677]\tvalidation_0-auc:0.93653\n[678]\tvalidation_0-auc:0.93652\n[679]\tvalidation_0-auc:0.93655\n[680]\tvalidation_0-auc:0.93655\n[681]\tvalidation_0-auc:0.93655\n[682]\tvalidation_0-auc:0.93656\n[683]\tvalidation_0-auc:0.93656\n[684]\tvalidation_0-auc:0.93654\n[685]\tvalidation_0-auc:0.93654\n[686]\tvalidation_0-auc:0.93655\n[687]\tvalidation_0-auc:0.93654\n[688]\tvalidation_0-auc:0.93654\n[689]\tvalidation_0-auc:0.93653\n[690]\tvalidation_0-auc:0.93653\n[691]\tvalidation_0-auc:0.93653\n[692]\tvalidation_0-auc:0.93652\n[693]\tvalidation_0-auc:0.93651\n[694]\tvalidation_0-auc:0.93653\n[695]\tvalidation_0-auc:0.93655\n[696]\tvalidation_0-auc:0.93656\n[697]\tvalidation_0-auc:0.93656\n[698]\tvalidation_0-auc:0.93654\n[699]\tvalidation_0-auc:0.93656\n[700]\tvalidation_0-auc:0.93657\n[701]\tvalidation_0-auc:0.93656\n[702]\tvalidation_0-auc:0.93655\n[703]\tvalidation_0-auc:0.93655\n[704]\tvalidation_0-auc:0.93660\n[705]\tvalidation_0-auc:0.93662\n[706]\tvalidation_0-auc:0.93661\n[707]\tvalidation_0-auc:0.93659\n[708]\tvalidation_0-auc:0.93660\n[709]\tvalidation_0-auc:0.93657\n[710]\tvalidation_0-auc:0.93655\n[711]\tvalidation_0-auc:0.93654\n[712]\tvalidation_0-auc:0.93653\n[713]\tvalidation_0-auc:0.93654\n[714]\tvalidation_0-auc:0.93655\n[715]\tvalidation_0-auc:0.93654\n[716]\tvalidation_0-auc:0.93655\n[717]\tvalidation_0-auc:0.93656\n[718]\tvalidation_0-auc:0.93656\n[719]\tvalidation_0-auc:0.93657\n[720]\tvalidation_0-auc:0.93654\n[721]\tvalidation_0-auc:0.93655\n[722]\tvalidation_0-auc:0.93653\n[723]\tvalidation_0-auc:0.93654\n[724]\tvalidation_0-auc:0.93655\n[725]\tvalidation_0-auc:0.93658\n[726]\tvalidation_0-auc:0.93659\n[727]\tvalidation_0-auc:0.93659\n[728]\tvalidation_0-auc:0.93658\n[729]\tvalidation_0-auc:0.93657\n[730]\tvalidation_0-auc:0.93656\n[731]\tvalidation_0-auc:0.93653\n[732]\tvalidation_0-auc:0.93652\n[733]\tvalidation_0-auc:0.93651\n[734]\tvalidation_0-auc:0.93651\n[735]\tvalidation_0-auc:0.93651\n[736]\tvalidation_0-auc:0.93650\n[737]\tvalidation_0-auc:0.93648\n[738]\tvalidation_0-auc:0.93652\n[739]\tvalidation_0-auc:0.93651\n[740]\tvalidation_0-auc:0.93651\n[741]\tvalidation_0-auc:0.93650\n[742]\tvalidation_0-auc:0.93649\n[743]\tvalidation_0-auc:0.93652\n[744]\tvalidation_0-auc:0.93652\n[745]\tvalidation_0-auc:0.93651\n[746]\tvalidation_0-auc:0.93652\n[747]\tvalidation_0-auc:0.93652\n[748]\tvalidation_0-auc:0.93652\n[749]\tvalidation_0-auc:0.93651\n[750]\tvalidation_0-auc:0.93651\n[751]\tvalidation_0-auc:0.93649\n[752]\tvalidation_0-auc:0.93648\n[753]\tvalidation_0-auc:0.93648\n[754]\tvalidation_0-auc:0.93651\n[755]\tvalidation_0-auc:0.93651\n[756]\tvalidation_0-auc:0.93651\n[757]\tvalidation_0-auc:0.93651\n[758]\tvalidation_0-auc:0.93652\n[759]\tvalidation_0-auc:0.93653\n[760]\tvalidation_0-auc:0.93655\n[761]\tvalidation_0-auc:0.93654\n[762]\tvalidation_0-auc:0.93652\n[763]\tvalidation_0-auc:0.93652\n[764]\tvalidation_0-auc:0.93655\n[765]\tvalidation_0-auc:0.93654\n[766]\tvalidation_0-auc:0.93655\n[767]\tvalidation_0-auc:0.93652\n[768]\tvalidation_0-auc:0.93653\n[769]\tvalidation_0-auc:0.93654\n[770]\tvalidation_0-auc:0.93653\n[771]\tvalidation_0-auc:0.93653\n[772]\tvalidation_0-auc:0.93654\n[773]\tvalidation_0-auc:0.93653\n[774]\tvalidation_0-auc:0.93653\n[775]\tvalidation_0-auc:0.93657\n[776]\tvalidation_0-auc:0.93656\n[777]\tvalidation_0-auc:0.93658\n[778]\tvalidation_0-auc:0.93659\n[779]\tvalidation_0-auc:0.93659\n[780]\tvalidation_0-auc:0.93658\n[781]\tvalidation_0-auc:0.93657\n[782]\tvalidation_0-auc:0.93654\n[783]\tvalidation_0-auc:0.93654\n[784]\tvalidation_0-auc:0.93651\n[785]\tvalidation_0-auc:0.93652\n[786]\tvalidation_0-auc:0.93652\n[787]\tvalidation_0-auc:0.93653\n[788]\tvalidation_0-auc:0.93652\n[789]\tvalidation_0-auc:0.93654\n[790]\tvalidation_0-auc:0.93655\n[791]\tvalidation_0-auc:0.93654\n[792]\tvalidation_0-auc:0.93652\n[793]\tvalidation_0-auc:0.93656\n[794]\tvalidation_0-auc:0.93654\n[795]\tvalidation_0-auc:0.93653\n[796]\tvalidation_0-auc:0.93655\n[797]\tvalidation_0-auc:0.93658\n[798]\tvalidation_0-auc:0.93657\n[799]\tvalidation_0-auc:0.93656\n[800]\tvalidation_0-auc:0.93654\n[801]\tvalidation_0-auc:0.93653\n[802]\tvalidation_0-auc:0.93653\n[803]\tvalidation_0-auc:0.93653\n[804]\tvalidation_0-auc:0.93652\n[805]\tvalidation_0-auc:0.93650\n0.9326219985474677\n"}],"source":"n_fold = 5\nfolds = KFold(n_splits=n_fold, shuffle=True, random_state=2022)\noof_xgb = np.zeros(len(X))\nprediction_xgb = np.zeros(len(dummy_test))\nfor fold_n, (train_index, valid_index) in enumerate(folds.split(X)):\n X_train, X_valid = X.iloc[train_index], X.iloc[valid_index]\n y_train, y_valid = y[train_index], y[valid_index]\n# smote_tomek = SMOTETomek(random_state=2022)\n# X_resampled, y_resampled = smote_tomek.fit_resample(X_train, y_train)\n eval_set = [(X_valid, y_valid)]\n model_xgb = XGBRegressor(\n max_depth=9,learning_rate=0.01,n_estimators=10000,colsample_bytree=0.6,subsample=0.8,random_state=2022\n ).fit(X_train,y_train,early_stopping_rounds=100, eval_metric=\"auc\",eval_set=eval_set, verbose=True)\n y_pred_valid = model_xgb.predict(X_valid)\n y_pred = model_xgb.predict(dummy_test)\n oof_xgb[valid_index] = y_pred_valid.reshape(-1, )\n prediction_xgb += y_pred\nprediction_xgb /= n_fold \nprint(roc_auc_score(y, oof_xgb))\n# 0.9326219985474677"},{"cell_type":"markdown","metadata":{"id":"D03CB6619D8B44B08E990ED3EA01C61D","jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"### 基于GridSearchCV的LGBM参数调整"},{"cell_type":"code","execution_count":65,"metadata":{"id":"082D0D1C79D14C0BB07870203B74F5F8","jupyter":{},"scrolled":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":["{'colsample_bytree': 0.8, 'learning_rate': 0.01, 'max_depth': 30, 'n_estimators': 10000, 'num_leaves': 59, 'subsample': 0.7}\n"]}],"source":"# param = {'max_depth': [30],\n# 'learning_rate': [0.01],\n# 'num_leaves': [59],\n# 'subsample': [0.7],\n# 'colsample_bytree': [0.8],\n# 'n_estimators': [10000]}\n# gs = GridSearchCV(estimator=LGBMRegressor(), param_grid=param, cv=5, scoring=\"neg_mean_squared_error\", n_jobs=-1) \n# gs.fit(X_resampled,y_resampled)\n# print(gs.best_params_) \n"},{"cell_type":"markdown","metadata":{"id":"23ADF0543B77452A8DCC799C0582D474","jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"### 基于五折交叉验证的LGBM"},{"cell_type":"code","execution_count":115,"metadata":{"id":"D2313DA33FCA4D7EA5F3C32DD98D6BBA","jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"outputs":[{"name":"stderr","output_type":"stream","text":["E:\\Anaconda3\\lib\\site-packages\\lightgbm\\sklearn.py:726: UserWarning: 'early_stopping_rounds' argument is deprecated and will be removed in a future release of LightGBM. Pass 'early_stopping()' callback via 'callbacks' argument instead.\n"," _log_warning(\"'early_stopping_rounds' argument is deprecated and will be removed in a future release of LightGBM. \"\n","E:\\Anaconda3\\lib\\site-packages\\lightgbm\\sklearn.py:736: UserWarning: 'verbose' argument is deprecated and will be removed in a future release of LightGBM. Pass 'log_evaluation()' callback via 'callbacks' argument instead.\n"," _log_warning(\"'verbose' argument is deprecated and will be removed in a future release of LightGBM. \"\n"]},{"name":"stdout","output_type":"stream","text":["[50]\ttraining's auc: 0.94085\ttraining's l2: 0.0788925\tvalid_1's auc: 0.925864\tvalid_1's l2: 0.0818997\n","[100]\ttraining's auc: 0.944802\ttraining's l2: 0.0672695\tvalid_1's auc: 0.928742\tvalid_1's l2: 0.0719714\n","[150]\ttraining's auc: 0.948559\ttraining's l2: 0.0607984\tvalid_1's auc: 0.930343\tvalid_1's l2: 0.0672457\n","[200]\ttraining's auc: 0.951549\ttraining's l2: 0.056876\tvalid_1's auc: 0.931374\tvalid_1's l2: 0.0649636\n","[250]\ttraining's auc: 0.954385\ttraining's l2: 0.054275\tvalid_1's auc: 0.931987\tvalid_1's l2: 0.0639735\n","[300]\ttraining's auc: 0.957015\ttraining's l2: 0.0521878\tvalid_1's auc: 0.932396\tvalid_1's l2: 0.0634468\n","[350]\ttraining's auc: 0.960145\ttraining's l2: 0.0503487\tvalid_1's auc: 0.93328\tvalid_1's l2: 0.0630066\n","[400]\ttraining's auc: 0.962937\ttraining's l2: 0.0486323\tvalid_1's auc: 0.93371\tvalid_1's l2: 0.062822\n","[450]\ttraining's auc: 0.965233\ttraining's l2: 0.0471381\tvalid_1's auc: 0.933886\tvalid_1's l2: 0.0627358\n","[500]\ttraining's auc: 0.96724\ttraining's l2: 0.0458021\tvalid_1's auc: 0.934201\tvalid_1's l2: 0.0626506\n","[550]\ttraining's auc: 0.969189\ttraining's l2: 0.0445553\tvalid_1's auc: 0.934529\tvalid_1's l2: 0.0624507\n","[600]\ttraining's auc: 0.970941\ttraining's l2: 0.0434685\tvalid_1's auc: 0.93459\tvalid_1's l2: 0.0623492\n","[650]\ttraining's auc: 0.972602\ttraining's l2: 0.0424998\tvalid_1's auc: 0.934349\tvalid_1's l2: 0.0622475\n","[700]\ttraining's auc: 0.974021\ttraining's l2: 0.041611\tvalid_1's auc: 0.934276\tvalid_1's l2: 0.0621712\n","[750]\ttraining's auc: 0.975347\ttraining's l2: 0.0408109\tvalid_1's auc: 0.933644\tvalid_1's l2: 0.0622134\n","[800]\ttraining's auc: 0.976582\ttraining's l2: 0.0400338\tvalid_1's auc: 0.933249\tvalid_1's l2: 0.0622394\n"]},{"name":"stderr","output_type":"stream","text":["E:\\Anaconda3\\lib\\site-packages\\lightgbm\\sklearn.py:726: UserWarning: 'early_stopping_rounds' argument is deprecated and will be removed in a future release of LightGBM. Pass 'early_stopping()' callback via 'callbacks' argument instead.\n"," _log_warning(\"'early_stopping_rounds' argument is deprecated and will be removed in a future release of LightGBM. \"\n","E:\\Anaconda3\\lib\\site-packages\\lightgbm\\sklearn.py:736: UserWarning: 'verbose' argument is deprecated and will be removed in a future release of LightGBM. Pass 'log_evaluation()' callback via 'callbacks' argument instead.\n"," _log_warning(\"'verbose' argument is deprecated and will be removed in a future release of LightGBM. \"\n"]},{"name":"stdout","output_type":"stream","text":["[50]\ttraining's auc: 0.9402\ttraining's l2: 0.07935\tvalid_1's auc: 0.932536\tvalid_1's l2: 0.0801626\n","[100]\ttraining's auc: 0.943739\ttraining's l2: 0.0676194\tvalid_1's auc: 0.934496\tvalid_1's l2: 0.0702667\n","[150]\ttraining's auc: 0.947848\ttraining's l2: 0.061121\tvalid_1's auc: 0.936416\tvalid_1's l2: 0.065416\n","[200]\ttraining's auc: 0.950776\ttraining's l2: 0.0572456\tvalid_1's auc: 0.937341\tvalid_1's l2: 0.0630831\n","[250]\ttraining's auc: 0.953983\ttraining's l2: 0.0545583\tvalid_1's auc: 0.938133\tvalid_1's l2: 0.0619445\n","[300]\ttraining's auc: 0.956913\ttraining's l2: 0.0523396\tvalid_1's auc: 0.93872\tvalid_1's l2: 0.0612938\n","[350]\ttraining's auc: 0.959894\ttraining's l2: 0.0504202\tvalid_1's auc: 0.939454\tvalid_1's l2: 0.0609051\n","[400]\ttraining's auc: 0.962519\ttraining's l2: 0.0487443\tvalid_1's auc: 0.939785\tvalid_1's l2: 0.0607129\n","[450]\ttraining's auc: 0.964735\ttraining's l2: 0.0473303\tvalid_1's auc: 0.939786\tvalid_1's l2: 0.0606189\n","[500]\ttraining's auc: 0.966875\ttraining's l2: 0.0459614\tvalid_1's auc: 0.940058\tvalid_1's l2: 0.0605379\n","[550]\ttraining's auc: 0.968779\ttraining's l2: 0.0447104\tvalid_1's auc: 0.94022\tvalid_1's l2: 0.0605152\n","[600]\ttraining's auc: 0.97058\ttraining's l2: 0.0435918\tvalid_1's auc: 0.940533\tvalid_1's l2: 0.0604589\n","[650]\ttraining's auc: 0.972085\ttraining's l2: 0.0426417\tvalid_1's auc: 0.940571\tvalid_1's l2: 0.0604517\n","[700]\ttraining's auc: 0.973432\ttraining's l2: 0.0417863\tvalid_1's auc: 0.940672\tvalid_1's l2: 0.0604522\n","[750]\ttraining's auc: 0.974732\ttraining's l2: 0.0409048\tvalid_1's auc: 0.940905\tvalid_1's l2: 0.0603683\n","[800]\ttraining's auc: 0.975899\ttraining's l2: 0.0401361\tvalid_1's auc: 0.940962\tvalid_1's l2: 0.0603816\n","[850]\ttraining's auc: 0.976931\ttraining's l2: 0.0394491\tvalid_1's auc: 0.940966\tvalid_1's l2: 0.0603915\n","[900]\ttraining's auc: 0.977929\ttraining's l2: 0.0387792\tvalid_1's auc: 0.94085\tvalid_1's l2: 0.0604162\n","[950]\ttraining's auc: 0.978862\ttraining's l2: 0.0381312\tvalid_1's auc: 0.940734\tvalid_1's l2: 0.0604662\n"]},{"name":"stderr","output_type":"stream","text":["E:\\Anaconda3\\lib\\site-packages\\lightgbm\\sklearn.py:726: UserWarning: 'early_stopping_rounds' argument is deprecated and will be removed in a future release of LightGBM. Pass 'early_stopping()' callback via 'callbacks' argument instead.\n"," _log_warning(\"'early_stopping_rounds' argument is deprecated and will be removed in a future release of LightGBM. \"\n","E:\\Anaconda3\\lib\\site-packages\\lightgbm\\sklearn.py:736: UserWarning: 'verbose' argument is deprecated and will be removed in a future release of LightGBM. Pass 'log_evaluation()' callback via 'callbacks' argument instead.\n"," _log_warning(\"'verbose' argument is deprecated and will be removed in a future release of LightGBM. \"\n"]},{"name":"stdout","output_type":"stream","text":["[50]\ttraining's auc: 0.941654\ttraining's l2: 0.0795005\tvalid_1's auc: 0.922594\tvalid_1's l2: 0.0787988\n","[100]\ttraining's auc: 0.945571\ttraining's l2: 0.0677357\tvalid_1's auc: 0.92527\tvalid_1's l2: 0.0696453\n","[150]\ttraining's auc: 0.949356\ttraining's l2: 0.0611459\tvalid_1's auc: 0.926724\tvalid_1's l2: 0.0655987\n","[200]\ttraining's auc: 0.952608\ttraining's l2: 0.0570597\tvalid_1's auc: 0.928057\tvalid_1's l2: 0.0637265\n","[250]\ttraining's auc: 0.955616\ttraining's l2: 0.0543341\tvalid_1's auc: 0.928873\tvalid_1's l2: 0.0630037\n","[300]\ttraining's auc: 0.95832\ttraining's l2: 0.0522183\tvalid_1's auc: 0.929336\tvalid_1's l2: 0.0626532\n","[350]\ttraining's auc: 0.961151\ttraining's l2: 0.0503588\tvalid_1's auc: 0.930429\tvalid_1's l2: 0.0623272\n","[400]\ttraining's auc: 0.963634\ttraining's l2: 0.0487219\tvalid_1's auc: 0.93069\tvalid_1's l2: 0.0622242\n","[450]\ttraining's auc: 0.965829\ttraining's l2: 0.0472595\tvalid_1's auc: 0.930543\tvalid_1's l2: 0.0621943\n","[500]\ttraining's auc: 0.967929\ttraining's l2: 0.0459291\tvalid_1's auc: 0.930614\tvalid_1's l2: 0.0621045\n","[550]\ttraining's auc: 0.969991\ttraining's l2: 0.0446926\tvalid_1's auc: 0.930791\tvalid_1's l2: 0.0620086\n","[600]\ttraining's auc: 0.971611\ttraining's l2: 0.0436567\tvalid_1's auc: 0.930556\tvalid_1's l2: 0.0619909\n","[650]\ttraining's auc: 0.973089\ttraining's l2: 0.0427368\tvalid_1's auc: 0.930451\tvalid_1's l2: 0.0619711\n","[700]\ttraining's auc: 0.974456\ttraining's l2: 0.0418338\tvalid_1's auc: 0.930732\tvalid_1's l2: 0.0618934\n","[750]\ttraining's auc: 0.975701\ttraining's l2: 0.0409687\tvalid_1's auc: 0.93121\tvalid_1's l2: 0.0617997\n","[800]\ttraining's auc: 0.976774\ttraining's l2: 0.04021\tvalid_1's auc: 0.931229\tvalid_1's l2: 0.0618136\n","[850]\ttraining's auc: 0.977858\ttraining's l2: 0.0394732\tvalid_1's auc: 0.931142\tvalid_1's l2: 0.061852\n","[900]\ttraining's auc: 0.978878\ttraining's l2: 0.0387557\tvalid_1's auc: 0.930934\tvalid_1's l2: 0.0618529\n","[950]\ttraining's auc: 0.979878\ttraining's l2: 0.0380331\tvalid_1's auc: 0.930689\tvalid_1's l2: 0.0618732\n"]},{"name":"stderr","output_type":"stream","text":["E:\\Anaconda3\\lib\\site-packages\\lightgbm\\sklearn.py:726: UserWarning: 'early_stopping_rounds' argument is deprecated and will be removed in a future release of LightGBM. Pass 'early_stopping()' callback via 'callbacks' argument instead.\n"," _log_warning(\"'early_stopping_rounds' argument is deprecated and will be removed in a future release of LightGBM. \"\n","E:\\Anaconda3\\lib\\site-packages\\lightgbm\\sklearn.py:736: UserWarning: 'verbose' argument is deprecated and will be removed in a future release of LightGBM. Pass 'log_evaluation()' callback via 'callbacks' argument instead.\n"," _log_warning(\"'verbose' argument is deprecated and will be removed in a future release of LightGBM. \"\n"]},{"name":"stdout","output_type":"stream","text":["[50]\ttraining's auc: 0.938779\ttraining's l2: 0.0783692\tvalid_1's auc: 0.929724\tvalid_1's l2: 0.0849279\n","[100]\ttraining's auc: 0.943638\ttraining's l2: 0.0667337\tvalid_1's auc: 0.932269\tvalid_1's l2: 0.074493\n","[150]\ttraining's auc: 0.94752\ttraining's l2: 0.0603255\tvalid_1's auc: 0.933807\tvalid_1's l2: 0.0694419\n","[200]\ttraining's auc: 0.950881\ttraining's l2: 0.056408\tvalid_1's auc: 0.93552\tvalid_1's l2: 0.0669414\n","[250]\ttraining's auc: 0.95406\ttraining's l2: 0.0536874\tvalid_1's auc: 0.935899\tvalid_1's l2: 0.0658231\n","[300]\ttraining's auc: 0.957231\ttraining's l2: 0.05144\tvalid_1's auc: 0.936191\tvalid_1's l2: 0.0651672\n","[350]\ttraining's auc: 0.960257\ttraining's l2: 0.0495814\tvalid_1's auc: 0.936883\tvalid_1's l2: 0.064655\n","[400]\ttraining's auc: 0.962809\ttraining's l2: 0.0479463\tvalid_1's auc: 0.937101\tvalid_1's l2: 0.0644035\n","[450]\ttraining's auc: 0.965109\ttraining's l2: 0.0464814\tvalid_1's auc: 0.937094\tvalid_1's l2: 0.0642898\n","[500]\ttraining's auc: 0.967202\ttraining's l2: 0.0451684\tvalid_1's auc: 0.937229\tvalid_1's l2: 0.0641968\n","[550]\ttraining's auc: 0.969275\ttraining's l2: 0.0439568\tvalid_1's auc: 0.937514\tvalid_1's l2: 0.0640906\n","[600]\ttraining's auc: 0.971103\ttraining's l2: 0.0428949\tvalid_1's auc: 0.937774\tvalid_1's l2: 0.0639556\n","[650]\ttraining's auc: 0.972795\ttraining's l2: 0.0419193\tvalid_1's auc: 0.938085\tvalid_1's l2: 0.0638854\n","[700]\ttraining's auc: 0.974376\ttraining's l2: 0.0409977\tvalid_1's auc: 0.938299\tvalid_1's l2: 0.0637705\n","[750]\ttraining's auc: 0.975719\ttraining's l2: 0.0401733\tvalid_1's auc: 0.938254\tvalid_1's l2: 0.0638389\n","[800]\ttraining's auc: 0.976952\ttraining's l2: 0.039378\tvalid_1's auc: 0.938171\tvalid_1's l2: 0.0638989\n","[850]\ttraining's auc: 0.977996\ttraining's l2: 0.0386485\tvalid_1's auc: 0.93817\tvalid_1's l2: 0.0639324\n","[900]\ttraining's auc: 0.978923\ttraining's l2: 0.0380388\tvalid_1's auc: 0.938106\tvalid_1's l2: 0.0639588\n"]},{"name":"stderr","output_type":"stream","text":["E:\\Anaconda3\\lib\\site-packages\\lightgbm\\sklearn.py:726: UserWarning: 'early_stopping_rounds' argument is deprecated and will be removed in a future release of LightGBM. Pass 'early_stopping()' callback via 'callbacks' argument instead.\n"," _log_warning(\"'early_stopping_rounds' argument is deprecated and will be removed in a future release of LightGBM. \"\n","E:\\Anaconda3\\lib\\site-packages\\lightgbm\\sklearn.py:736: UserWarning: 'verbose' argument is deprecated and will be removed in a future release of LightGBM. Pass 'log_evaluation()' callback via 'callbacks' argument instead.\n"," _log_warning(\"'verbose' argument is deprecated and will be removed in a future release of LightGBM. \"\n"]},{"name":"stdout","output_type":"stream","text":["[50]\ttraining's auc: 0.941106\ttraining's l2: 0.0789061\tvalid_1's auc: 0.916192\tvalid_1's l2: 0.0814378\n","[100]\ttraining's auc: 0.945514\ttraining's l2: 0.0669373\tvalid_1's auc: 0.919579\tvalid_1's l2: 0.0723827\n","[150]\ttraining's auc: 0.949487\ttraining's l2: 0.0604246\tvalid_1's auc: 0.921699\tvalid_1's l2: 0.068301\n","[200]\ttraining's auc: 0.953036\ttraining's l2: 0.0563975\tvalid_1's auc: 0.922555\tvalid_1's l2: 0.0664568\n","[250]\ttraining's auc: 0.955869\ttraining's l2: 0.0536905\tvalid_1's auc: 0.923021\tvalid_1's l2: 0.0656804\n","[300]\ttraining's auc: 0.958501\ttraining's l2: 0.0515648\tvalid_1's auc: 0.923196\tvalid_1's l2: 0.0654114\n","[350]\ttraining's auc: 0.961319\ttraining's l2: 0.0497304\tvalid_1's auc: 0.924204\tvalid_1's l2: 0.0651377\n","[400]\ttraining's auc: 0.963981\ttraining's l2: 0.0480409\tvalid_1's auc: 0.924832\tvalid_1's l2: 0.0648762\n","[450]\ttraining's auc: 0.96626\ttraining's l2: 0.0466098\tvalid_1's auc: 0.925281\tvalid_1's l2: 0.0647658\n","[500]\ttraining's auc: 0.968523\ttraining's l2: 0.0452797\tvalid_1's auc: 0.925673\tvalid_1's l2: 0.0647242\n","[550]\ttraining's auc: 0.970423\ttraining's l2: 0.0440425\tvalid_1's auc: 0.926443\tvalid_1's l2: 0.0646256\n","[600]\ttraining's auc: 0.972048\ttraining's l2: 0.0429566\tvalid_1's auc: 0.926666\tvalid_1's l2: 0.064639\n","[650]\ttraining's auc: 0.97356\ttraining's l2: 0.0419683\tvalid_1's auc: 0.926761\tvalid_1's l2: 0.0646741\n","[700]\ttraining's auc: 0.974844\ttraining's l2: 0.0411034\tvalid_1's auc: 0.926648\tvalid_1's l2: 0.0647594\n","[750]\ttraining's auc: 0.976116\ttraining's l2: 0.0402927\tvalid_1's auc: 0.92654\tvalid_1's l2: 0.0648155\n","0.9342991211145983\n"]}],"source":"n_fold = 5\nfolds = KFold(n_splits=n_fold, shuffle=True,random_state=1314)\nparams = {\n 'learning_rate':0.01,\n 'subsample': 0.7,\n 'num_leaves': 59,\n 'n_estimators':1500,\n 'max_depth': 30,\n 'colsample_bytree': 0.8,\n 'verbose': -1,\n 'seed': 2022,\n 'n_jobs': -1\n}\n\noof_lgb = np.zeros(len(X))\npredictions_lgb = np.zeros(len(dummy_test))\nfor fold_n, (train_index, valid_index) in enumerate(folds.split(X)):\n X_train, X_valid = X.iloc[train_index], X.iloc[valid_index]\n y_train, y_valid = y[train_index], y[valid_index]\n# smote_tomek = SMOTETomek(random_state=2022)\n# X_resampled, y_resampled = smote_tomek.fit_resample(X_train, y_train)\n model = lgb.LGBMRegressor(**params)\n model.fit(X_train, y_train,\n eval_set=[(X_train, y_train), (X_valid, y_valid)],\n eval_metric='auc',\n verbose=50, early_stopping_rounds=200)\n y_pred_valid = model.predict(X_valid)\n y_pred = model.predict(dummy_test, num_iteration=model.best_iteration_)\n oof_lgb[valid_index] = y_pred_valid.reshape(-1, )\n predictions_lgb += y_pred\npredictions_lgb /= n_fold\nprint(roc_auc_score(y, oof_lgb))\n# 0.9342991211145983"},{"cell_type":"markdown","metadata":{"id":"1D0CF99ED0F04505ADAF99D733B04257","jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"### 基于GridSearchCV的catboost参数调整"},{"cell_type":"code","execution_count":1,"metadata":{"collapsed":true,"id":"40143CE0A1F7461A9D5AAFEB614609B5","jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"outputs":[],"source":"\n# param = {'depth': [7,9,11],\n# 'learning_rate': [0.01],\n# 'iterations': [8000]}\n# gs = GridSearchCV(estimator=CatBoostRegressor(), param_grid=param, cv=3, scoring=\"neg_mean_squared_error\", n_jobs=-1) \n# gs.fit(X_resampled,y_resampled)\n# print(gs.best_params_) "},{"cell_type":"markdown","metadata":{"id":"0E595CF0D95341E69AB1154B1849F14E","jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"### 基于五折交叉验证的catboost"},{"cell_type":"code","execution_count":67,"metadata":{"id":"3A557EC583C0481488702DC367D10F53","jupyter":{},"scrolled":false,"slideshow":{"slide_type":"slide"},"tags":[],"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":["0:\tlearn: 0.3201355\ttest: 0.3215319\tbest: 0.3215319 (0)\ttotal: 55.1ms\tremaining: 22m 57s\n","1000:\tlearn: 0.2210492\ttest: 0.2482059\tbest: 0.2482059 (1000)\ttotal: 34.7s\tremaining: 13m 51s\n","Stopped by overfitting detector (300 iterations wait)\n","\n","bestTest = 0.2468782072\n","bestIteration = 1477\n","\n","Shrink model to first 1478 iterations.\n","0:\tlearn: 0.3208935\ttest: 0.3185105\tbest: 0.3185105 (0)\ttotal: 69.5ms\tremaining: 28m 57s\n","1000:\tlearn: 0.2206024\ttest: 0.2464808\tbest: 0.2464751 (998)\ttotal: 37.8s\tremaining: 15m 5s\n","2000:\tlearn: 0.1971871\ttest: 0.2454924\tbest: 0.2454188 (1725)\ttotal: 1m 13s\tremaining: 14m 5s\n","Stopped by overfitting detector (300 iterations wait)\n","\n","bestTest = 0.2454188002\n","bestIteration = 1725\n","\n","Shrink model to first 1726 iterations.\n","0:\tlearn: 0.3214860\ttest: 0.3161403\tbest: 0.3161403 (0)\ttotal: 42ms\tremaining: 17m 30s\n","1000:\tlearn: 0.2210140\ttest: 0.2480678\tbest: 0.2480521 (995)\ttotal: 36.2s\tremaining: 14m 27s\n","Stopped by overfitting detector (300 iterations wait)\n","\n","bestTest = 0.24699407\n","bestIteration = 1556\n","\n","Shrink model to first 1557 iterations.\n","0:\tlearn: 0.3186885\ttest: 0.3274174\tbest: 0.3274174 (0)\ttotal: 54ms\tremaining: 22m 30s\n","1000:\tlearn: 0.2202664\ttest: 0.2525361\tbest: 0.2525361 (1000)\ttotal: 36.4s\tremaining: 14m 32s\n","Stopped by overfitting detector (300 iterations wait)\n","\n","bestTest = 0.2515410448\n","bestIteration = 1603\n","\n","Shrink model to first 1604 iterations.\n","0:\tlearn: 0.3209030\ttest: 0.3185929\tbest: 0.3185929 (0)\ttotal: 75.6ms\tremaining: 31m 29s\n","1000:\tlearn: 0.2212537\ttest: 0.2523067\tbest: 0.2523067 (1000)\ttotal: 34.7s\tremaining: 13m 51s\n","Stopped by overfitting detector (300 iterations wait)\n","\n","bestTest = 0.250998901\n","bestIteration = 1618\n","\n","Shrink model to first 1619 iterations.\n"]}],"source":"# 本地交叉验证\nn_fold = 5\nfolds = KFold(n_splits=n_fold, shuffle=True, random_state=1314)\n\noof_cat = np.zeros(len(X))\nprediction_cat = np.zeros(len(dummy_test))\nfor fold_n, (train_index, valid_index) in enumerate(folds.split(X)):\n X_train, X_valid = X.iloc[train_index], X.iloc[valid_index]\n y_train, y_valid = y[train_index], y[valid_index]\n# smote_tomek = SMOTETomek(random_state=2022)\n# X_resampled, y_resampled = smote_tomek.fit_resample(X_train, y_train)\n train_pool = Pool(X_train, y_train)\n eval_pool = Pool(X_valid, y_valid)\n cbt_model = CatBoostRegressor(iterations=25000, # 注：baseline 提到的分数是用 iterations=60000 得到的，但运行时间有点久\n learning_rate=0.01, # 注：事实上好几个 property 在 lr=0.1 时收敛巨慢。后面可以考虑调大\n# eval_metric='SMAPE',\n depth=9,\n use_best_model=True,\n random_seed=2022,\n logging_level='Verbose',\n #task_type='GPU',\n devices='0',\n gpu_ram_part=0.5,\n early_stopping_rounds=300)\n \n cbt_model.fit(train_pool,\n eval_set=eval_pool,\n verbose=1000)\n\n y_pred_valid = cbt_model.predict(X_valid)\n y_pred_c = cbt_model.predict(dummy_test)\n oof_cat[valid_index] = y_pred_valid.reshape(-1, )\n prediction_cat += y_pred_c\nprediction_cat /= n_fold \n"},{"cell_type":"code","execution_count":68,"metadata":{"id":"27A63B61DB094FCF95CEEB6A1E3ADC5A","jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":["0.935264298588153\n"]}],"source":"print(roc_auc_score(y, oof_cat))\n# 0.935264298588153"},{"cell_type":"markdown","metadata":{"id":"9470A77D276E418F9CB2ACD8D18E6F68","jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"### 基于stacking的模型融合"},{"cell_type":"code","execution_count":71,"metadata":{"id":"4A24F209D61E47E7A27F4A26D6687B89","jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":["fold 0\n","fold 1\n","fold 2\n","fold 3\n","fold 4\n","fold 5\n","fold 6\n","fold 7\n","fold 8\n","fold 9\n","CV score: 0.06156606\n"]}],"source":"# from sklearn.linear_model import Bayesian\nfrom sklearn.metrics import mean_squared_error,mean_absolute_error,make_scorer\n\n# 将多个模型的结果进行stacking（叠加）\ntrain_stack = np.vstack([oof_rf,oof_lgb,oof_cat,oof_xgb]).transpose()\ntest_stack = np.vstack([prediction_rf,prediction_lgb,prediction_cat,prediction_xgb]).transpose()\n#贝叶斯分类器也使用交叉验证的方法，5折，重复2次\nfolds_stack = RepeatedKFold(n_splits=5, n_repeats=2, random_state=2018)\noof_stack = np.zeros(train_stack.shape[0])\npredictions = np.zeros(test_stack.shape[0])\n \nfor fold_, (trn_idx, val_idx) in enumerate(folds_stack.split(train_stack,y)):\n print(\"fold {}\".format(fold_))\n trn_data, trn_y = train_stack[trn_idx], y.iloc[trn_idx].values\n val_data, val_y = train_stack[val_idx], y.iloc[val_idx].values#\n \n clf_3 = BayesianRidge()\n clf_3.fit(trn_data, trn_y)\n \n oof_stack[val_idx] = clf_3.predict(val_data)#对验证集有一个预测，用于后面计算模型的偏差\n predictions += clf_3.predict(test_stack) / 10#对测试集的预测，除以10是因为5折交叉验证重复了2次\n \nmean_squared_error(y.values, oof_stack)#计算出模型在训练集上的均方误差\nprint(\"CV score: {:<8.8f}\".format(mean_squared_error(y.values, oof_stack)))"},{"cell_type":"code","execution_count":72,"metadata":{"id":"33AB2F850236462DB7F0DFE549A2C559","jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":["0.9361018703876826\n"]}],"source":"print(roc_auc_score(y, oof_stack))\n# 0.9361018703876826"},{"cell_type":"markdown","metadata":{"id":"1D7C809913E14DD79D1E399F519EDC1C","jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"source":"# 保存结果"},{"cell_type":"code","execution_count":73,"metadata":{"collapsed":true,"id":"BC37DA49289D45C2951D2FFDC91043BA","jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"trusted":true},"outputs":[],"source":"test['pred'] = predictions\ntest[['ID', 'pred']].to_csv(r'C:\\Users\\hepei\\Desktop\\比赛代码\\练习赛\\客户购买预测\\结果\\sub.csv', index=None, encoding=\"utf-8\")"}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python","nbconvert_exporter":"python","file_extension":".py","version":"3.5.2","pygments_lexer":"ipython3"}},"nbformat":4,"nbformat_minor":2}
|
2301_80733725/DVLab
|
Baseline客户购买预测.ipynb
|
Jupyter Notebook
|
unknown
| 165,004
|
#!/bin/bash
# 定义下载地址和文件名
DOWNLOAD_URL="https://cangjie-lang.cn/v1/files/auth/downLoad?nsId=142267&fileName=Cangjie-0.53.13-linux_x64.tar.gz&objectKey=6719f1eb3af6947e3c6af327"
FILE_NAME="Cangjie-0.53.13-linux_x64.tar.gz"
# 检查 cangjie 工具链是否已安装
echo "确保 cangjie 工具链已安装..."
if ! command -v cjc -v &> /dev/null
then
echo "cangjie工具链 未安装，尝试进行安装..."
# 下载文件
echo "Downloading Cangjie compiler..."
curl -L -o "$FILE_NAME" "$DOWNLOAD_URL"
# 检查下载是否成功
if [ $? -eq 0 ]; then
echo "Download completed successfully."
else
echo "Download failed."
exit 1
fi
# 解压文件
echo "Extracting $FILE_NAME..."
tar -xvf "$FILE_NAME"
# 检查解压是否成功
if [ $? -eq 0 ]; then
echo "Extraction completed successfully."
else
echo "Extraction failed."
exit 1
fi
# 检查 envsetup.sh 是否存在并进行 source
if [[ -f "cangjie/envsetup.sh" ]]; then
echo "envsetup.sh found!"
source cangjie/envsetup.sh
else
echo "envsetup.sh not found!"
exit 1
fi
fi
# 检查 openEuler 防火墙状态
echo "检查 openEuler 防火墙状态..."
if systemctl status firewalld | grep "active (running)" &> /dev/null; then
echo "防火墙已开启，尝试开放 21 端口..."
firewall-cmd --zone=public --add-port=21/tcp --permanent
firewall-cmd --reload
echo "21 端口已开放。"
else
echo "防火墙未开启，无需开放端口。"
fi
# 编译ftp_server
echo "正在编译 ftp_server..."
cjpm build
# 检查编译是否成功
if [ $? -eq 0 ]; then
echo "编译成功."
else
echo "编译失败."
exit 1
fi
# 运行 ftp_server
echo "正在启动 ftp 服务器..."
cjpm run
|
2301_80674151/Cangjie-Examples_9958
|
FTP/run-ftp.sh
|
Shell
|
apache-2.0
| 1,967
|
<!DOCTYPE html>
<html lang="cn">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Document</title>
</head>
<body>
<div>Hello Cangjie!</div>
<p></p>
<script>
let xhr = new XMLHttpRequest()
xhr.open("POST", "/Hello", true)
xhr.onreadystatechange = () => {
if(xhr.readyState == 4 && xhr.status == 200){
let res = JSON.parse(xhr.responseText)
document.body.innerHTML += `<div>${res.msg}</div>`
}
}
xhr.send(JSON.stringify({
name: "Chen",
age: 999
}))
</script>
</body>
</html>
|
2301_80674151/Cangjie-Examples_9958
|
HTTPServer/index.html
|
HTML
|
apache-2.0
| 687
|
#!/bin/bash
# 定义下载地址和文件名
DOWNLOAD_URL="https://cangjie-lang.cn/v1/files/auth/downLoad?nsId=142267&fileName=Cangjie-0.53.13-linux_x64.tar.gz&objectKey=6719f1eb3af6947e3c6af327"
FILE_NAME="Cangjie-0.53.13-linux_x64.tar.gz"
# 检查 cangjie 工具链是否已安装
echo "确保 cangjie 工具链已安装..."
if ! command -v cjc -v &> /dev/null
then
echo "cangjie工具链 未安装，尝试进行安装..."
# 下载文件
echo "Downloading Cangjie compiler..."
curl -L -o "$FILE_NAME" "$DOWNLOAD_URL"
# 检查下载是否成功
if [ $? -eq 0 ]; then
echo "Download completed successfully."
else
echo "Download failed."
exit 1
fi
# 解压文件
echo "Extracting $FILE_NAME..."
tar -xvf "$FILE_NAME"
# 检查解压是否成功
if [ $? -eq 0 ]; then
echo "Extraction completed successfully."
else
echo "Extraction failed."
exit 1
fi
# 检查 envsetup.sh 是否存在并进行 source
if [[ -f "cangjie/envsetup.sh" ]]; then
echo "envsetup.sh found!"
source cangjie/envsetup.sh
else
echo "envsetup.sh not found!"
exit 1
fi
fi
# 检查 openEuler 防火墙状态
echo "检查 openEuler 防火墙状态..."
if systemctl status firewalld | grep "active (running)" &> /dev/null; then
echo "防火墙已开启，尝试开放 21 端口..."
firewall-cmd --zone=public --add-port=21/tcp --permanent
firewall-cmd --reload
echo "21 端口已开放。"
else
echo "防火墙未开启，无需开放端口。"
fi
# 编译ftp_server
echo "正在编译 ftp_server..."
cjpm build
# 检查编译是否成功
if [ $? -eq 0 ]; then
echo "编译成功."
else
echo "编译失败."
exit 1
fi
# 运行 ftp_server
echo "正在启动 ftp 服务器..."
cjpm run
|
2301_80674151/Cangjie-Examples
|
FTP/run-ftp.sh
|
Shell
|
apache-2.0
| 1,967
|
<!DOCTYPE html>
<html lang="cn">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Document</title>
</head>
<body>
<div>Hello Cangjie!</div>
<p></p>
<script>
let xhr = new XMLHttpRequest()
xhr.open("POST", "/Hello", true)
xhr.onreadystatechange = () => {
if(xhr.readyState == 4 && xhr.status == 200){
let res = JSON.parse(xhr.responseText)
document.body.innerHTML += `<div>${res.msg}</div>`
}
}
xhr.send(JSON.stringify({
name: "Chen",
age: 999
}))
</script>
</body>
</html>
|
2301_80674151/Cangjie-Examples
|
HTTPServer/index.html
|
HTML
|
apache-2.0
| 687
|
#答案生成模块
import openai
import json
from typing import List, Dict
from config import OPENAI_API_KEY, DEEPSEEK_API_KEY, XINGHE_API_KEY, XINGHE_BASE_URL, OPENAI_MODEL, DEEPSEEK_MODEL, XINGHE_MODEL
from model_status import model_status
import requests
from prompt_templates import prompt_templates
from knowledge_enhancer import zhiyuan_enhancer
from performance_timer import global_timer, APITimer
class AnswerGenerator:
def __init__(self, openai_api_key=OPENAI_API_KEY, deepseek_api_key=DEEPSEEK_API_KEY, xinghe_api_key=XINGHE_API_KEY, gemini_api_key="AIzaSyB1lMryiHH_V_7-OVT4eyuLBrHbLsigRCs"):
self.openai_client = openai.OpenAI(api_key=openai_api_key)
self.deepseek_client = openai.OpenAI(api_key=deepseek_api_key, base_url="https://api.deepseek.com/v1")
self.xinghe_client = openai.OpenAI(api_key=xinghe_api_key, base_url=XINGHE_BASE_URL)
self.gemini_api_key = gemini_api_key
self.gemini_url = "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent"
def generate(self, question: str, classification: Dict, retrieved_docs: List[Dict], context: List[Dict], preferred_model: str = None) -> str:
"""生成回答，支持指定模型。如果不指定，则按顺序尝试：星河大模型、Gemini、OpenAI、DeepSeek、本地模板。"""
# 如果是问候语，直接返回简单回复，不进行知识增强
if classification.get('label') == 'greeting':
return self._generate_greeting_response(question)
context_info = self._build_context_info(context)
knowledge_info = self._build_knowledge_info(retrieved_docs)
# 使用新的提示词模板系统
multimodal_prompt = prompt_templates.get_multimodal_prompt(
classification['label'],
question,
knowledge_info,
context_info
)
# 如果指定了模型，尝试使用该模型，失败则回退到本地方案
if preferred_model:
try:
return self._generate_with_specific_model(preferred_model, question, classification, knowledge_info, context_info, multimodal_prompt)
except Exception as e:
error_msg = str(e)
print(f"指定模型 {preferred_model} 调用失败，回退到本地备用方案: {error_msg}")
# 回退到本地备用方案
print("使用本地备用回答生成")
with APITimer("本地模板生成"):
model_status.update_status('fallback', True)
model_status.switch_model('fallback')
fallback_answer = self._generate_fallback_answer(question, classification, retrieved_docs)
# 使用智源研究院知识增强回答
enhanced_answer = zhiyuan_enhancer.enhance_answer_with_knowledge(question, fallback_answer, classification)
# 添加模型信息和计时器信息
global_timer.add_info("使用模型", f"本地备用方案 (原选择: {self._get_model_display_name(preferred_model)})")
enhanced_answer = f"## 🤖 使用模型: 本地备用方案\n\n> ⚠️ 注意：您选择的 **{self._get_model_display_name(preferred_model)}** 暂时不可用，已自动切换到本地备用方案。\n\n{enhanced_answer}"
return enhanced_answer
# 否则按顺序尝试各个模型
# 1. 优先使用星河大模型
if model_status.status['xinghe']['available']:
try:
# 使用提示词模板系统
prompt_data = prompt_templates.format_prompt(
classification['label'],
question,
knowledge_info,
context_info
)
with APITimer("星河大模型API"):
response = self.xinghe_client.chat.completions.create(
model=XINGHE_MODEL,
messages=[
{"role": "system", "content": prompt_data["system"]},
{"role": "user", "content": prompt_data["user"]}
],
max_tokens=2000,
temperature=0.7
)
model_status.update_status('xinghe', True)
model_status.switch_model('xinghe')
answer = response.choices[0].message.content
# 使用智源研究院知识增强回答
with APITimer("星河知识增强"):
enhanced_answer = zhiyuan_enhancer.enhance_answer_with_knowledge(question, answer, classification)
# 添加模型信息和计时器信息
global_timer.add_info("使用模型", f"星河大模型 ({model_status.status['xinghe']['model']})")
enhanced_answer = f"## 🤖 使用模型: 星河大模型 ({model_status.status['xinghe']['model']})\n\n{enhanced_answer}"
return enhanced_answer
except Exception as e:
error_msg = str(e)
print(f"星河大模型API调用失败: {error_msg}")
model_status.update_status('xinghe', False, error_msg)
global_timer.add_info("星河错误", error_msg[:100])
# 2. 使用Gemini
try:
gemini_payload = {
"contents": [
{"parts": [
{"text": multimodal_prompt}
]}
]
}
headers = {
"Content-Type": "application/json",
"X-goog-api-key": self.gemini_api_key
}
with APITimer("Gemini模型API"):
resp = requests.post(self.gemini_url, json=gemini_payload, headers=headers, timeout=30)
if resp.status_code == 200:
data = resp.json()
# Gemini返回格式兼容Markdown
if "candidates" in data and data["candidates"]:
content = data["candidates"][0]["content"]["parts"][0]["text"]
model_status.update_status('gemini', True)
model_status.switch_model('gemini')
# 使用智源研究院知识增强回答
with APITimer("Gemini知识增强"):
enhanced_answer = zhiyuan_enhancer.enhance_answer_with_knowledge(question, content, classification)
# 添加模型信息和计时器信息
global_timer.add_info("使用模型", "Gemini")
enhanced_answer = f"## 🤖 使用模型: Gemini\n\n{enhanced_answer}"
return enhanced_answer
else:
raise Exception("Gemini无有效回答")
else:
raise Exception(f"Gemini API错误: {resp.status_code} {resp.text}")
except Exception as e:
error_msg = str(e)
print(f"Gemini API调用失败: {error_msg}")
model_status.update_status('gemini', False, error_msg)
global_timer.add_info("Gemini错误", error_msg[:100])
# 3. 尝试使用OpenAI
if model_status.status['openai']['available']:
try:
# 使用提示词模板系统
prompt_data = prompt_templates.format_prompt(
classification['label'],
question,
knowledge_info,
context_info
)
with APITimer("OpenAI模型API"):
response = self.openai_client.chat.completions.create(
model=OPENAI_MODEL,
messages=[
{"role": "system", "content": prompt_data["system"]},
{"role": "user", "content": prompt_data["user"]}
],
max_tokens=2000,
temperature=0.7
)
model_status.update_status('openai', True)
model_status.switch_model('openai')
answer = response.choices[0].message.content
# 使用智源研究院知识增强回答
with APITimer("OpenAI知识增强"):
enhanced_answer = zhiyuan_enhancer.enhance_answer_with_knowledge(question, answer, classification)
# 添加模型信息和计时器信息
global_timer.add_info("使用模型", f"OpenAI ({model_status.status['openai']['model']})")
enhanced_answer = f"## 🤖 使用模型: OpenAI ({model_status.status['openai']['model']})\n\n{enhanced_answer}"
return enhanced_answer
except Exception as e:
error_msg = str(e)
print(f"OpenAI API调用失败: {error_msg}")
model_status.update_status('openai', False, error_msg)
global_timer.add_info("OpenAI错误", error_msg[:100])
# 4. 尝试使用DeepSeek
if model_status.status['deepseek']['available']:
try:
# 使用提示词模板系统
prompt_data = prompt_templates.format_prompt(
classification['label'],
question,
knowledge_info,
context_info
)
with APITimer("DeepSeek模型API"):
response = self.deepseek_client.chat.completions.create(
model=DEEPSEEK_MODEL,
messages=[
{"role": "system", "content": prompt_data["system"]},
{"role": "user", "content": prompt_data["user"]}
],
max_tokens=2000,
temperature=0.7
)
model_status.update_status('deepseek', True)
model_status.switch_model('deepseek')
answer = response.choices[0].message.content
# 使用智源研究院知识增强回答
with APITimer("DeepSeek知识增强"):
enhanced_answer = zhiyuan_enhancer.enhance_answer_with_knowledge(question, answer, classification)
# 添加模型信息和计时器信息
global_timer.add_info("使用模型", f"DeepSeek ({model_status.status['deepseek']['model']})")
enhanced_answer = f"## 🤖 使用模型: DeepSeek ({model_status.status['deepseek']['model']})\n\n{enhanced_answer}"
return enhanced_answer
except Exception as e2:
error_msg = str(e2)
print(f"DeepSeek API调用失败: {error_msg}")
model_status.update_status('deepseek', False, error_msg)
global_timer.add_info("DeepSeek错误", error_msg[:100])
# 5. 本地模板
print("使用本地备用回答生成")
with APITimer("本地模板生成"):
model_status.update_status('fallback', True)
model_status.switch_model('fallback')
fallback_answer = self._generate_fallback_answer(question, classification, retrieved_docs)
# 使用智源研究院知识增强回答
enhanced_answer = zhiyuan_enhancer.enhance_answer_with_knowledge(question, fallback_answer, classification)
# 添加模型信息和计时器信息
global_timer.add_info("使用模型", "本地备用方案")
enhanced_answer = f"## 🤖 使用模型: 本地备用方案\n\n{enhanced_answer}"
return enhanced_answer
def _generate_with_specific_model(self, model_name: str, question: str, classification: Dict, knowledge_info: str, context_info: str, multimodal_prompt: str) -> str:
"""使用指定的模型生成回答"""
# 星河大模型
if model_name == 'xinghe':
# 即使状态为不可用，也尝试调用（可能是状态更新不及时）
try:
prompt_data = prompt_templates.format_prompt(
classification['label'],
question,
knowledge_info,
context_info
)
with APITimer("星河大模型API"):
response = self.xinghe_client.chat.completions.create(
model=XINGHE_MODEL,
messages=[
{"role": "system", "content": prompt_data["system"]},
{"role": "user", "content": prompt_data["user"]}
],
max_tokens=2000,
temperature=0.7
)
model_status.update_status('xinghe', True)
model_status.switch_model('xinghe')
answer = response.choices[0].message.content
with APITimer("星河知识增强"):
enhanced_answer = zhiyuan_enhancer.enhance_answer_with_knowledge(question, answer, classification)
global_timer.add_info("使用模型", f"星河大模型 ({model_status.status['xinghe']['model']})")
enhanced_answer = f"## 🤖 使用模型: 星河大模型 ({model_status.status['xinghe']['model']})\n\n{enhanced_answer}"
return enhanced_answer
except Exception as e:
error_msg = str(e)
print(f"星河大模型API调用失败: {error_msg}")
model_status.update_status('xinghe', False, error_msg)
raise Exception(f"星河大模型调用失败: {error_msg}")
# Gemini模型
elif model_name == 'gemini':
try:
gemini_payload = {
"contents": [
{"parts": [
{"text": multimodal_prompt}
]}
]
}
headers = {
"Content-Type": "application/json",
"X-goog-api-key": self.gemini_api_key
}
with APITimer("Gemini模型API"):
resp = requests.post(self.gemini_url, json=gemini_payload, headers=headers, timeout=30)
if resp.status_code == 200:
data = resp.json()
if "candidates" in data and data["candidates"]:
content = data["candidates"][0]["content"]["parts"][0]["text"]
model_status.update_status('gemini', True)
model_status.switch_model('gemini')
with APITimer("Gemini知识增强"):
enhanced_answer = zhiyuan_enhancer.enhance_answer_with_knowledge(question, content, classification)
global_timer.add_info("使用模型", "Gemini")
enhanced_answer = f"## 🤖 使用模型: Gemini\n\n{enhanced_answer}"
return enhanced_answer
else:
raise Exception("Gemini无有效回答")
else:
raise Exception(f"Gemini API错误: {resp.status_code} {resp.text}")
except Exception as e:
error_msg = str(e)
print(f"Gemini API调用失败: {error_msg}")
model_status.update_status('gemini', False, error_msg)
raise Exception(f"Gemini模型调用失败: {error_msg}")
# OpenAI模型
elif model_name == 'openai':
# 即使状态为不可用，也尝试调用（可能是状态更新不及时）
try:
prompt_data = prompt_templates.format_prompt(
classification['label'],
question,
knowledge_info,
context_info
)
with APITimer("OpenAI模型API"):
response = self.openai_client.chat.completions.create(
model=OPENAI_MODEL,
messages=[
{"role": "system", "content": prompt_data["system"]},
{"role": "user", "content": prompt_data["user"]}
],
max_tokens=2000,
temperature=0.7
)
model_status.update_status('openai', True)
model_status.switch_model('openai')
answer = response.choices[0].message.content
with APITimer("OpenAI知识增强"):
enhanced_answer = zhiyuan_enhancer.enhance_answer_with_knowledge(question, answer, classification)
global_timer.add_info("使用模型", f"OpenAI ({model_status.status['openai']['model']})")
enhanced_answer = f"## 🤖 使用模型: OpenAI ({model_status.status['openai']['model']})\n\n{enhanced_answer}"
return enhanced_answer
except Exception as e:
error_msg = str(e)
print(f"OpenAI API调用失败: {error_msg}")
model_status.update_status('openai', False, error_msg)
raise Exception(f"OpenAI模型调用失败: {error_msg}")
# DeepSeek模型
elif model_name == 'deepseek':
# 即使状态为不可用，也尝试调用（可能是状态更新不及时）
try:
prompt_data = prompt_templates.format_prompt(
classification['label'],
question,
knowledge_info,
context_info
)
with APITimer("DeepSeek模型API"):
response = self.deepseek_client.chat.completions.create(
model=DEEPSEEK_MODEL,
messages=[
{"role": "system", "content": prompt_data["system"]},
{"role": "user", "content": prompt_data["user"]}
],
max_tokens=2000,
temperature=0.7
)
model_status.update_status('deepseek', True)
model_status.switch_model('deepseek')
answer = response.choices[0].message.content
with APITimer("DeepSeek知识增强"):
enhanced_answer = zhiyuan_enhancer.enhance_answer_with_knowledge(question, answer, classification)
global_timer.add_info("使用模型", f"DeepSeek ({model_status.status['deepseek']['model']})")
enhanced_answer = f"## 🤖 使用模型: DeepSeek ({model_status.status['deepseek']['model']})\n\n{enhanced_answer}"
return enhanced_answer
except Exception as e:
error_msg = str(e)
print(f"DeepSeek API调用失败: {error_msg}")
model_status.update_status('deepseek', False, error_msg)
raise Exception(f"DeepSeek模型调用失败: {error_msg}")
else:
raise Exception(f"未知的模型名称: {model_name}")
def _get_model_display_name(self, model_name: str) -> str:
"""获取模型的显示名称"""
model_names = {
'xinghe': '星河大模型',
'gemini': 'Gemini',
'openai': 'OpenAI',
'deepseek': 'DeepSeek'
}
return model_names.get(model_name, model_name)
def _generate_greeting_response(self, question: str) -> str:
"""生成问候语回复"""
greeting_responses = [
"""# 👋 你好！
很高兴见到你！我是你的Rust编程学习助手。
## 🦀 我能为你做什么？
**Rust知识解答**：
- 解释Rust概念和语法
- 提供代码示例和最佳实践
- 协助调试和错误解决
- 回答编程相关问题
## 💡 开始学习
有什么Rust相关的问题想要了解吗？比如：
- "什么是所有权？"
- "如何使用Vec？"
- "生命周期是什么？"
随时提问，我会尽力帮助你！""",
"""# 🌟 欢迎！
你好！我是专业的Rust编程助手。
## 🚀 服务特色
**智能问答**：基于星河大模型的专业回答
**知识增强**：结合智源研究院最新研究成果
**多模态输出**：支持代码高亮、图表、表格
**在线编程**：Monaco Editor集成，支持代码运行
## 🎯 开始探索
准备好开始你的Rust学习之旅了吗？有什么问题尽管问我！""",
"""# 🦀 Hello Rust!
很高兴认识你！我是你的Rust学习伙伴。
## 💪 我的能力
- **概念解释**：深入浅出地解释Rust概念
- **代码示例**：提供实用的代码示例
- **错误调试**：帮助解决编译和运行时问题
- **最佳实践**：分享Rust编程的最佳实践
## 🔥 立即开始
有什么Rust问题想要了解？我在这里等你！"""
]
# 根据问题内容选择不同的回复
question_lower = question.lower()
if 'hello' in question_lower or 'hi' in question_lower:
return greeting_responses[0]
elif '你好' in question_lower:
return greeting_responses[1]
else:
return greeting_responses[2]
def _build_context_info(self, context: List[Dict]) -> str:
"""构建上下文信息"""
if not context:
return ""
context_info = "**对话历史：**\n"
for i, turn in enumerate(context[-3:], 1): # 只保留最近3轮
context_info += f"{i}. 问：{turn['question']}\n 答：{turn['answer'][:100]}...\n\n"
return context_info
def _build_knowledge_info(self, docs: List[Dict]) -> str:
"""构建知识库信息"""
if not docs:
return "**相关知识点：** 未找到相关知识\n"
knowledge_info = "**相关知识点：**\n"
for doc in docs:
knowledge_info += f"- **{doc['topic']}**：{doc['content']}\n"
if 'code' in doc:
knowledge_info += f" ```rust\n {doc['code']}\n ```\n"
return knowledge_info
def _is_non_rust_question(self, question: str) -> bool:
"""判断是否为非Rust相关问题"""
question_lower = question.lower()
# 定义Rust相关关键词
rust_keywords = [
'rust', '生命周期', '所有权', '借用', '可变', '不可变', 'trait', 'struct', 'enum',
'match', 'option', 'result', '迭代器', '闭包', '宏', '模块', 'cargo', '编译',
'错误', '调试', '内存', '安全', '并发', '异步', 'future', 'pin', 'unsafe'
]
# 定义通用问候语
greetings = ['你好', 'hello', 'hi', '您好', '早上好', '下午好', '晚上好', '嗨']
# 如果是问候语，直接返回True
if any(greeting in question_lower for greeting in greetings):
return True
# 检查是否包含Rust相关关键词
has_rust_keywords = any(keyword in question_lower for keyword in rust_keywords)
# 如果没有Rust关键词，可能是非Rust问题
return not has_rust_keywords
def _generate_general_response(self, question: str) -> str:
"""生成通用回答（非Rust相关问题）"""
question_lower = question.lower()
# 问候语回答
if any(greeting in question_lower for greeting in ['你好', 'hello', 'hi', '您好', '早上好', '下午好', '晚上好', '嗨']):
return """## 您好！ 👋
很高兴见到您！我是**Rust知识解释智能体**，专门帮助您学习Rust编程语言。
### 🤖 我能为您做什么？
- **概念解释**：解释Rust的核心概念，如所有权、生命周期等
- **用法指导**：提供代码示例和最佳实践
- **错误调试**：帮助解决编译和运行时错误
- **语言对比**：比较Rust与其他编程语言的异同
- **学习建议**：提供Rust学习路径和资源推荐
### 💡 试试这些Rust相关问题：
- "Rust的所有权是什么？"
- "如何使用迭代器？"
- "这个编译错误怎么解决？"
- "Rust和C++有什么区别？"
- "如何学习Rust？"
### 🚀 开始探索Rust世界
请在下方输入您的Rust相关问题，我会为您提供详细的解答！
### 🔧 代码编辑器
想要实践代码？点击这里进入 <a href="http://127.0.0.1:5000/code_editor" target="_blank"><b>代码编辑器</b></a> 进行在线编程练习！"""
# 其他非Rust问题的回答
return f"""## 关于"{question}"的回复 🤔
我注意到您的问题可能不是关于Rust编程的。我是**Rust知识解释智能体**，专门帮助用户学习Rust编程语言。
### 🎯 我的专长领域
- **Rust编程概念**：所有权、生命周期、借用检查器等
- **Rust语法和用法**：变量、函数、结构体、枚举等
- **Rust错误调试**：编译错误、运行时错误等
- **Rust最佳实践**：代码组织、性能优化等
### 💡 如果您想了解Rust，可以试试：
- "Rust是什么？"
- "Rust适合什么项目？"
- "如何开始学习Rust？"
- "Rust有什么特点？"
### 🔗 其他资源
如果您需要其他方面的帮助，建议您：
- 使用专门的搜索引擎
- 访问相关领域的专业网站
- 咨询相关领域的专家
我很乐意继续为您提供Rust编程方面的帮助！ 🦀"""
def _generate_fallback_answer(self, question: str, classification: Dict, retrieved_docs: List[Dict]) -> str:
"""生成备用回答（当API调用失败时）"""
question_lower = question.lower()
# 根据问题类型生成不同的回答
if classification['label'] == 'definition':
return self._generate_definition_fallback(question)
elif classification['label'] == 'usage':
return self._generate_usage_fallback(question)
elif classification['label'] == 'error_debug':
return self._generate_error_debug_fallback(question)
elif classification['label'] == 'comparison':
return self._generate_comparison_fallback(question)
else:
return self._generate_faq_fallback(question)
def _generate_definition_fallback(self, question: str) -> str:
"""生成定义类问题的备用回答，代码练习和综合案例根据用户问题动态生成"""
# 动态生成代码练习题
code_ex1 = f"练习1：请编写一个函数，演示“{question}”相关的基本用法。"
code_ex2 = f"练习2：请实现一个结构体或算法，体现“{question}”的核心特性。"
# 动态生成综合案例
case_req = f"案例要求：设计一个小项目，要求充分体现“{question}”的实际应用场景。"
case_steps = f"实现步骤：1. 明确项目目标和输入输出；2. 设计主要数据结构和函数；3. 实现核心功能；4. 编写测试用例验证。"
return f"""
<div class=\"system-section\">
<div class=\"system-section-title\"><i class=\"fas fa-book\"></i> 概念定义</div>
<ol class=\"system-section-list\">
<li><strong>{question.replace('是什么', '').replace('？', '').replace('什么意思', '')}</strong>是Rust编程语言中的一个重要概念。</li>
<li>这是Rust的核心特性之一</li>
<li>确保内存安全和线程安全</li>
<li>编译时检查，运行时零开销</li>
<li>提供强大的抽象能力</li>
</ol>
<div class=\"system-section-title\"><i class=\"fas fa-code\"></i> 代码练习</div>
<ol class=\"system-section-list\">
<li>{code_ex1}</li>
<li>{code_ex2}</li>
</ol>
<div class=\"system-section-title\"><i class=\"fas fa-lightbulb\"></i> 综合案例</div>
<ol class=\"system-section-list\">
<li>{case_req}</li>
<li>{case_steps}</li>
</ol>
<div class=\"system-section-title\"><i class=\"fas fa-edit\"></i> 实践练习</div>
<p>想要实践这些代码练习？点击这里进入 <a href="http://127.0.0.1:5000/code_editor" target="_blank"><b>代码编辑器</b></a> 进行在线编程！</p>
</div>
"""
def _generate_usage_fallback(self, question: str) -> str:
"""生成用法类问题的备用回答"""
return f"""## 基本用法
以下是**{question.replace('怎么', '').replace('如何', '').replace('使用', '').replace('？', '')}**的基本用法：
### 代码示例
```rust
fn main() {{
// 基本用法示例
let result = example_function();
println!("结果: {{}}", result);
}}
fn example_function() -> i32 {{
42
}}
```
### 参数说明
- param1: 第一个参数的作用
- param2: 第二个参数的作用
### 最佳实践
1. 遵循Rust的命名约定
2. 使用适当的错误处理
3. 考虑性能影响
4. 编写清晰的文档
### 常见用法
- 基本语法
- 函数调用
- 错误处理
- 模块组织
### 🔧 实践练习
想要运行这些代码示例？点击这里进入 <a href="http://127.0.0.1:5000/code_editor" target="_blank"><b>代码编辑器</b></a> 进行在线编程练习！"""
def _generate_error_debug_fallback(self, question: str) -> str:
"""生成错误调试类问题的备用回答"""
return f"""## 错误分析
您遇到的**{question.replace('错误', '').replace('问题', '').replace('？', '')}**通常是由于以下原因：
### 常见原因
- 借用检查器规则违反
- 生命周期不匹配
- 类型不匹配
- 所有权问题
### 解决方案
```rust
// 错误代码示例
let mut v = vec![1, 2, 3];
let first = &v[0];
v.push(4); // 编译错误
// 正确代码
let mut v = vec![1, 2, 3];
v.push(4);
let first = &v[0]; // 正确
```
### 调试技巧
1. 仔细阅读编译器错误信息
2. 使用 `cargo check` 进行静态检查
3. 逐步简化代码定位问题
4. 查看官方文档和示例
### 预防措施
- 理解所有权规则
- 注意生命周期
- 合理使用借用
- 编写测试代码
### 🔧 调试练习
想要实践这些调试技巧？点击这里进入 <a href="http://127.0.0.1:5000/code_editor" target="_blank"><b>代码编辑器</b></a> 进行在线调试练习！"""
def _generate_comparison_fallback(self, question: str) -> str:
"""生成对比类问题的备用回答"""
return f"""## 对比分析
**{question.replace('区别', '').replace('不同', '').replace('比较', '').replace('？', '')}**的主要差异：
### 核心差异
| 特性 | Rust | 其他语言 |
|------|------|----------|
| 内存管理 | 所有权系统 | 垃圾回收/手动管理 |
| 并发安全 | 编译时检查 | 运行时检查 |
| 性能 | 零开销抽象 | 可能有运行时开销 |
| 学习曲线 | 较陡峭 | 相对平缓 |
### 代码对比
```rust
// Rust 示例
let s = String::from("hello");
// 所有权自动管理
```
```cpp
// C++ 示例
std::string s = "hello";
// 需要手动管理内存
```
### 适用场景
- **Rust**: 系统编程、性能敏感应用、安全关键系统
- **其他**: 快速原型、脚本编程、通用应用开发
### 选择建议
- 需要内存安全：选择Rust
- 需要快速开发：选择其他语言
- 需要高性能：Rust是很好的选择
### 🔧 实践对比
想要亲自体验Rust的特性？点击这里进入 <a href="http://127.0.0.1:5000/code_editor" target="_blank"><b>代码编辑器</b></a> 进行在线编程实践！"""
def _generate_faq_fallback(self, question: str) -> str:
"""生成FAQ类问题的备用回答"""
return f"""## 问题解答
关于**{question.replace('？', '')}**的详细解答：
### 背景说明
这是一个常见的问题，涉及到Rust的学习路径和最佳实践。
### 实践建议
1. 从官方文档开始学习
2. 多做练习项目
3. 参与社区讨论
4. 阅读优秀代码
### 学习资源
- [Rust官方文档](https://doc.rust-lang.org/)
- [Rust Book](https://doc.rust-lang.org/book/)
- [Rust by Example](https://doc.rust-lang.org/rust-by-example/)
- [Rust社区](https://users.rust-lang.org/)
### 扩展阅读
- 所有权系统详解
- 生命周期管理
- 错误处理最佳实践
- 并发编程模式
### 学习路径
1. 基础语法
2. 所有权和借用
3. 错误处理
4. 高级特性
5. 项目实践
### 🔧 开始实践
想要开始Rust编程实践？点击这里进入 <a href="http://127.0.0.1:5000/code_editor" target="_blank"><b>代码编辑器</b></a> 进行在线编程学习！"""
|
2301_80743186/rust-agent-code
|
answer_generator.py
|
Python
|
unknown
| 32,937
|
#Web应用主入口
from flask import Flask, render_template, request, jsonify, session, redirect, url_for
from main import KnowledgeExplanationAgent
from config import FLASK_SECRET_KEY, DEFAULT_USERS, DEBUG_MODE
from model_status import model_status
from multimodal_enhancer import multimodal_enhancer
from knowledge_enhancer import zhiyuan_enhancer
import json
import os
import threading
from functools import wraps
from tempfile import NamedTemporaryFile
import subprocess
# 导入性能计时器
from performance_timer import global_timer, StepTimer, APITimer
app = Flask(__name__)
app.config['SECRET_KEY'] = FLASK_SECRET_KEY
# 初始化知识解释智能体
agent = KnowledgeExplanationAgent()
def preload_resources():
"""
预加载模型和FAISS索引，避免用户第一个问题时的延迟
"""
try:
print("开始预加载资源...")
# 预加载retriever资源
if hasattr(agent, 'retriever') and hasattr(agent.retriever, '_ensure_resources_loaded'):
print("正在预加载检索器模型和FAISS索引...")
agent.retriever._ensure_resources_loaded()
print("检索器资源预加载完成")
else:
print("检索器不存在或没有_ensure_resources_loaded方法")
# 这里可以添加其他需要预加载的资源
print("所有资源预加载完成")
except Exception as e:
print(f"预加载资源时出错: {str(e)}")
def login_required(f):
"""登录验证装饰器"""
@wraps(f)
def decorated_function(*args, **kwargs):
if 'user_id' not in session:
return redirect(url_for('login'))
return f(*args, **kwargs)
return decorated_function
@app.route('/')
def index():
"""重定向到登录页面"""
return redirect(url_for('login'))
@app.route('/login', methods=['GET', 'POST'])
def login():
"""登录页面"""
if request.method == 'POST':
data = request.get_json()
username = data.get('username')
password = data.get('password')
if username in DEFAULT_USERS and DEFAULT_USERS[username]['password'] == password:
session['user_id'] = username
session['user_role'] = DEFAULT_USERS[username]['role']
session['user_name'] = DEFAULT_USERS[username]['name']
return jsonify({'status': 'success', 'redirect': '/dashboard'})
else:
return jsonify({'status': 'error', 'message': '用户名或密码错误'}), 401
return render_template('login.html')
@app.route('/logout')
def logout():
"""登出"""
session.clear()
return redirect(url_for('login'))
@app.route('/dashboard')
@login_required
def dashboard():
"""主页面（需要登录）"""
return render_template('index.html', user=session)
@app.route('/code_editor')
@login_required
def code_editor():
return render_template('code_editor.html', user=session)
@app.route('/api/chat', methods=['POST'])
@login_required
def chat():
"""聊天API接口"""
try:
data = request.get_json()
user_id = session.get('user_id', 'anonymous')
message = data.get('message', '').strip()
preferred_model = data.get('model', None) # 获取用户选择的模型
if not message:
return jsonify({
'status': 'error',
'message': '消息不能为空'
}), 400
# 重置性能计时器
global_timer.reset()
with StepTimer("完整问答流程"):
# 调用知识解释智能体处理问题
with StepTimer("智能体处理问题"):
result = agent.process_question(user_id, message, preferred_model=preferred_model)
# 保存并打印性能报告
global_timer.save_report(message, result.get('content', ''))
global_timer.print_summary()
return jsonify(result)
except Exception as e:
# 即使出错也要保存性能报告
try:
global_timer.save_report(message or "", f"错误: {str(e)}")
except:
pass
return jsonify({
'status': 'error',
'message': f'服务器错误: {str(e)}'
}), 500
@app.route('/api/status')
def status():
"""系统状态检查"""
return jsonify({
'status': 'success',
'message': '系统运行正常',
'version': '1.0.0',
'model_status': model_status.get_status_summary()
})
@app.route('/api/export', methods=['POST'])
def export_chat():
"""导出聊天记录"""
try:
data = request.get_json()
chat_history = data.get('history', [])
# 生成导出文件
export_data = {
'timestamp': data.get('timestamp'),
'user_id': data.get('user_id'),
'history': chat_history
}
return jsonify({
'status': 'success',
'data': export_data
})
except Exception as e:
return jsonify({
'status': 'error',
'message': f'导出失败: {str(e)}'
}), 500
@app.route('/api/knowledge', methods=['GET'])
def get_knowledge():
"""获取知识库信息"""
try:
# 这里可以返回知识库统计信息
return jsonify({
'status': 'success',
'data': {
'total_docs': len(agent.retriever.knowledge_base),
'categories': ['definition', 'usage', 'error_debug', 'comparison', 'faq']
}
})
except Exception as e:
return jsonify({
'status': 'error',
'message': f'获取知识库信息失败: {str(e)}'
}), 500
@app.route('/api/session/<session_id>', methods=['GET'])
def get_session(session_id):
"""获取会话信息"""
try:
context = agent.context_manager.get_context(session_id)
summary = agent.context_manager.get_session_summary(session_id)
return jsonify({
'status': 'success',
'data': {
'context': context,
'summary': summary
}
})
except Exception as e:
return jsonify({
'status': 'error',
'message': f'获取会话信息失败: {str(e)}'
}), 500
@app.route('/api/session/<session_id>', methods=['DELETE'])
def clear_session(session_id):
"""清空会话"""
try:
agent.context_manager.clear_context(session_id)
return jsonify({
'status': 'success',
'message': '会话已清空'
})
except Exception as e:
return jsonify({
'status': 'error',
'message': f'清空会话失败: {str(e)}'
}), 500
@app.route('/api/storage/stats', methods=['GET'])
@login_required
def get_storage_stats():
"""获取存储统计信息"""
try:
stats = agent.context_manager.get_storage_stats()
return jsonify({
'status': 'success',
'stats': stats
})
except Exception as e:
return jsonify({
'status': 'error',
'message': f'获取存储统计失败: {str(e)}'
}), 500
@app.route('/api/render', methods=['POST'])
def render_markdown():
"""渲染Markdown为HTML"""
try:
data = request.get_json()
markdown_content = data.get('markdown', '')
if not markdown_content:
return jsonify({
'status': 'error',
'message': 'Markdown内容不能为空'
}), 400
# 使用多模态增强器
enhanced_content = multimodal_enhancer.enhance_content(markdown_content)
return jsonify({
'status': 'success',
'html': enhanced_content['enhanced_html'],
'code_blocks': enhanced_content['code_blocks'],
'mermaid_diagrams': enhanced_content['mermaid_diagrams'],
'tables': enhanced_content['tables']
})
except Exception as e:
return jsonify({
'status': 'error',
'message': f'渲染失败: {str(e)}'
}), 500
@app.route('/api/multimodal/styles')
def get_multimodal_styles():
"""获取多模态增强样式"""
try:
css_styles = multimodal_enhancer.generate_css_styles()
return jsonify({
'status': 'success',
'css': css_styles
})
except Exception as e:
return jsonify({
'status': 'error',
'message': f'获取样式失败: {str(e)}'
}), 500
@app.route('/api/multimodal/scripts')
def get_multimodal_scripts():
"""获取多模态增强脚本"""
try:
js_functions = multimodal_enhancer.generate_js_functions()
return jsonify({
'status': 'success',
'javascript': js_functions
})
except Exception as e:
return jsonify({
'status': 'error',
'message': f'获取脚本失败: {str(e)}'
}), 500
@app.route('/api/zhiyuan/stats', methods=['GET'])
@login_required
def get_zhiyuan_stats():
"""获取智源研究院知识统计"""
try:
stats = zhiyuan_enhancer.get_knowledge_statistics()
return jsonify({
'status': 'success',
'stats': stats
})
except Exception as e:
return jsonify({
'status': 'error',
'message': f'获取统计信息失败: {str(e)}'
}), 500
@app.route('/api/run_rust_code', methods=['POST'])
@login_required
def run_rust_code():
"""运行Rust代码并返回结果"""
try:
data = request.get_json()
code = data.get('code', '')
if not code:
return jsonify({'status': 'error', 'message': '代码不能为空'}), 400
# 写入临时文件
with NamedTemporaryFile('w', encoding='utf-8', suffix='.rs', delete=False) as f:
f.write(code)
rust_file = f.name
exe_file = rust_file[:-3] + '.exe'
# 编译
compile_proc = subprocess.run(['rustc', rust_file, '-o', exe_file], capture_output=True, text=True, timeout=10)
if compile_proc.returncode != 0:
return jsonify({'status': 'error', 'message': '编译错误', 'stderr': compile_proc.stderr})
# 运行
run_proc = subprocess.run([exe_file], capture_output=True, text=True, timeout=5)
return jsonify({'status': 'success', 'stdout': run_proc.stdout, 'stderr': run_proc.stderr})
except subprocess.TimeoutExpired:
return jsonify({'status': 'error', 'message': '运行超时'}), 500
except Exception as e:
return jsonify({'status': 'error', 'message': f'运行失败: {str(e)}'}), 500
@app.route('/api/analyze_rust_code', methods=['POST'])
@login_required
def analyze_rust_code():
"""调用大模型分析Rust代码，返回分析结果"""
from answer_generator import AnswerGenerator
try:
data = request.get_json()
code = data.get('code', '')
examples_raw = data.get('examples', '')
if not code:
return jsonify({'status': 'error', 'message': '代码不能为空'}), 400
# 解析 examples
try:
examples = json.loads(examples_raw) if examples_raw else {}
except Exception as e:
examples = {}
code_practice = examples.get('code_practice', '')
comprehensive_case = examples.get('comprehensive_case', '')
# 构造更详细的分析prompt
prompt = f"""
你是一个专业的Rust编程题目批改与优化专家。请根据下方的【题目内容】和【用户提交代码】，完成如下分析：
【题目内容】
{code_practice}\n{comprehensive_case}
【用户提交代码】
```rust
{code}
```
请严格按照以下结构输出：
1. **题目归属判断**：判断该代码最有可能是针对哪一道题目（请给出题号和题目标题/内容，若无法判断请说明原因）。
2. **正确性分析**：判断代码是否正确，若有错误请详细指出并给出修改建议。
3. **优化建议**：从风格、性能、安全性等角度给出具体可操作的优化建议。
4. **完美代码示例**：给出针对该题目的最优/标准Rust代码（用```rust代码块包裹）。
5. **正向反馈**：指出该代码的优点、亮点或值得肯定的地方，鼓励用户继续学习。
请用分点详细说明，内容要简明、专业、鼓励性强。
"""
ag = AnswerGenerator()
# 直接用Gemini API分析
try:
gemini_payload = {
"contents": [
{"parts": [
{"text": prompt}
]}
]
}
headers = {
"Content-Type": "application/json",
"X-goog-api-key": ag.gemini_api_key
}
import requests
resp = requests.post(ag.gemini_url, json=gemini_payload, headers=headers, timeout=30)
if resp.status_code == 200:
data = resp.json()
if "candidates" in data and data["candidates"]:
content = data["candidates"][0]["content"]["parts"][0]["text"]
return jsonify({'status': 'success', 'result': content})
else:
raise Exception("Gemini无有效分析结果")
else:
raise Exception(f"Gemini API错误: {resp.status_code} {resp.text}")
except Exception as e:
return jsonify({'status': 'error', 'message': f'大模型分析失败: {str(e)}'})
except Exception as e:
return jsonify({'status': 'error', 'message': f'服务器错误: {str(e)}'})
@app.errorhandler(404)
def not_found(error):
return jsonify({
'status': 'error',
'message': '接口不存在'
}), 404
@app.errorhandler(500)
def internal_error(error):
return jsonify({
'status': 'error',
'message': '服务器内部错误'
}), 500
if __name__ == '__main__':
# 确保静态文件目录存在
os.makedirs('static/css', exist_ok=True)
os.makedirs('static/js', exist_ok=True)
os.makedirs('templates', exist_ok=True)
print("启动Rust知识解释智能体Web服务...")
print("访问地址: http://localhost:5000")
print("API文档: http://localhost:5000/api/status")
# 异步预加载资源，避免阻塞应用启动
preload_thread = threading.Thread(target=preload_resources)
preload_thread.daemon = True # 设置为守护线程，主线程结束时自动终止
preload_thread.start()
app.run(debug=DEBUG_MODE, host='0.0.0.0', port=5000)
|
2301_80743186/rust-agent-code
|
app.py
|
Python
|
unknown
| 14,856
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
性能测试脚本 - 用于测量semantic_retriever.py的性能指标
可以在代码修改前后运行，对比性能变化
"""
import time
import json
import os
from typing import Dict, List, Tuple
from semantic_retriever import SemanticRetriever
def test_retrieval_performance(retriever: SemanticRetriever, test_questions: List[str], iterations: int = 5) -> Dict:
"""
测试检索性能
Args:
retriever: 语义检索实例
test_questions: 测试问题列表
iterations: 每个问题重复测试的次数
Returns:
Dict: 包含性能指标的字典
"""
print(f"\n开始测试检索性能（每个问题重复{iterations}次）...")
results = {
"question_times": [],
"total_time": 0,
"average_time_per_question": 0
}
total_start_time = time.time()
for i, question in enumerate(test_questions):
question_total_time = 0
print(f"测试问题 {i+1}/{len(test_questions)}: '{question}'")
for j in range(iterations):
start_time = time.time()
retrieved_docs = retriever.retrieve(question, top_k=3)
end_time = time.time()
elapsed = (end_time - start_time) * 1000 # 转换为毫秒
question_total_time += elapsed
print(f" 迭代 {j+1}/{iterations}: {elapsed:.2f}ms, 返回文档数: {len(retrieved_docs)}")
avg_time = question_total_time / iterations
results["question_times"].append({
"question": question,
"average_time_ms": avg_time,
"total_time_ms": question_total_time
})
print(f" 平均时间: {avg_time:.2f}ms")
total_end_time = time.time()
total_time_ms = (total_end_time - total_start_time) * 1000
avg_time_per_question = total_time_ms / (len(test_questions) * iterations)
results["total_time"] = total_time_ms
results["average_time_per_question"] = avg_time_per_question
print(f"\n总测试时间: {total_time_ms:.2f}ms")
print(f"平均每个问题检索时间: {avg_time_per_question:.2f}ms")
return results
def test_initialization_performance(kb_path: str = 'rust_knowledge_base/rust_docs_sample.json', iterations: int = 3) -> Dict:
"""
测试初始化性能
Args:
kb_path: 知识库路径
iterations: 重复测试的次数
Returns:
Dict: 包含性能指标的字典
"""
print(f"\n开始测试初始化性能（重复{iterations}次）...")
results = {
"init_times": [],
"total_time": 0,
"average_time": 0
}
total_start_time = time.time()
for i in range(iterations):
print(f"初始化迭代 {i+1}/{iterations}...")
start_time = time.time()
# 创建新的检索器实例
retriever = SemanticRetriever(kb_path)
end_time = time.time()
elapsed = (end_time - start_time) * 1000 # 转换为毫秒
results["init_times"].append(elapsed)
print(f" 初始化时间: {elapsed:.2f}ms, 知识库文档数: {len(retriever.knowledge_base)}")
total_end_time = time.time()
total_time_ms = (total_end_time - total_start_time) * 1000
avg_time = total_time_ms / iterations
results["total_time"] = total_time_ms
results["average_time"] = avg_time
print(f"\n总初始化时间: {total_time_ms:.2f}ms")
print(f"平均初始化时间: {avg_time:.2f}ms")
return results
def test_embedding_generation(retriever: SemanticRetriever, texts: List[str]) -> Dict:
"""
测试嵌入向量生成性能
Args:
retriever: 语义检索实例
texts: 测试文本列表
Returns:
Dict: 包含性能指标的字典
"""
if not retriever.model:
print("模型未初始化，跳过嵌入向量生成测试")
return {"error": "Model not initialized"}
print(f"\n开始测试嵌入向量生成性能...")
# 测试单个短文本
short_text = "这是一个简短的测试文本"
start_time = time.time()
short_embedding = retriever.model.encode([short_text])
short_time = (time.time() - start_time) * 1000
# 测试多个文本
start_time = time.time()
embeddings = retriever.model.encode(texts)
batch_time = (time.time() - start_time) * 1000
avg_time_per_text = batch_time / len(texts)
# 正确处理numpy数组的维度获取
embedding_dimension = embeddings.shape[1] if embeddings.size > 0 else 0
results = {
"short_text_time_ms": short_time,
"batch_test": {
"total_texts": len(texts),
"total_time_ms": batch_time,
"average_time_per_text_ms": avg_time_per_text,
"embedding_dimension": embedding_dimension
}
}
print(f"单个短文本嵌入时间: {short_time:.2f}ms")
print(f"批量文本嵌入 ({len(texts)}个文本): 总时间 {batch_time:.2f}ms, 平均每文本 {avg_time_per_text:.2f}ms")
print(f"嵌入向量维度: {embedding_dimension}")
return results
def run_comprehensive_benchmark(kb_path: str = 'rust_knowledge_base/rust_docs_sample.json', iterations: int = 3) -> Dict:
"""
运行综合性能基准测试
Args:
kb_path: 知识库路径
iterations: 重复测试次数
Returns:
Dict: 包含所有性能测试结果的字典
"""
print("=" * 60)
print("开始综合性能基准测试")
print(f"测试配置: 知识库='{kb_path}', 迭代次数={iterations}")
print("=" * 60)
# 记录开始时间
overall_start_time = time.time()
# 初始化测试
init_results = test_initialization_performance(kb_path, iterations)
# 创建一个检索器实例用于后续测试
print("\n创建检索器实例用于后续测试...")
retriever = SemanticRetriever(kb_path)
# 准备测试问题和文本
test_questions = [
"什么是Rust的所有权？",
"如何在Rust中声明可变变量？",
"解释一下Rust的生命周期概念",
"Rust中的借用规则是什么？",
"如何处理Rust中的错误？"
]
# 从知识库中提取一些文本用于嵌入测试
test_texts = [doc.get('content', '')[:200] for doc in retriever.knowledge_base[:5]]
# 嵌入生成测试
embedding_results = test_embedding_generation(retriever, test_texts)
# 检索性能测试
retrieval_results = test_retrieval_performance(retriever, test_questions, iterations)
# 记录结束时间
overall_end_time = time.time()
overall_time_ms = (overall_end_time - overall_start_time) * 1000
# 汇总结果
results = {
"timestamp": time.strftime("%Y-%m-%d %H:%M:%S"),
"overall_test_time_ms": overall_time_ms,
"initialization": init_results,
"embedding_generation": embedding_results,
"retrieval": retrieval_results
}
# 保存结果到文件
output_file = f"performance_benchmark_{int(time.time())}.json"
with open(output_file, 'w', encoding='utf-8') as f:
json.dump(results, f, ensure_ascii=False, indent=2)
print("\n" + "=" * 60)
print(f"性能测试完成，结果已保存到 {output_file}")
print(f"总测试时间: {overall_time_ms:.2f}ms")
print("=" * 60)
# 打印关键性能指标摘要
print("\n性能指标摘要:")
print(f"1. 初始化时间: {init_results['average_time']:.2f}ms")
if 'batch_test' in embedding_results:
print(f"2. 文本嵌入时间: {embedding_results['batch_test']['average_time_per_text_ms']:.2f}ms/文本")
print(f"3. 问题检索时间: {retrieval_results['average_time_per_question']:.2f}ms/问题")
return results
def compare_benchmark_files(file1: str, file2: str) -> None:
"""
比较两个基准测试结果文件
Args:
file1: 第一个基准测试文件路径
file2: 第二个基准测试文件路径
"""
if not os.path.exists(file1) or not os.path.exists(file2):
print(f"错误: 找不到文件 {file1} 或 {file2}")
return
with open(file1, 'r', encoding='utf-8') as f1, open(file2, 'r', encoding='utf-8') as f2:
results1 = json.load(f1)
results2 = json.load(f2)
print("\n" + "=" * 70)
print(f"性能对比: {file1} vs {file2}")
print("=" * 70)
# 比较初始化时间
init1 = results1['initialization']['average_time']
init2 = results2['initialization']['average_time']
init_diff = ((init2 - init1) / init1) * 100
print(f"初始化时间: {init1:.2f}ms → {init2:.2f}ms ({init_diff:+.2f}%)")
# 比较嵌入时间
if 'batch_test' in results1['embedding_generation'] and 'batch_test' in results2['embedding_generation']:
emb1 = results1['embedding_generation']['batch_test']['average_time_per_text_ms']
emb2 = results2['embedding_generation']['batch_test']['average_time_per_text_ms']
emb_diff = ((emb2 - emb1) / emb1) * 100
print(f"文本嵌入时间: {emb1:.2f}ms → {emb2:.2f}ms ({emb_diff:+.2f}%)")
# 比较检索时间
ret1 = results1['retrieval']['average_time_per_question']
ret2 = results2['retrieval']['average_time_per_question']
ret_diff = ((ret2 - ret1) / ret1) * 100
print(f"问题检索时间: {ret1:.2f}ms → {ret2:.2f}ms ({ret_diff:+.2f}%)")
# 比较总时间
total1 = results1['overall_test_time_ms']
total2 = results2['overall_test_time_ms']
total_diff = ((total2 - total1) / total1) * 100
print(f"总测试时间: {total1:.2f}ms → {total2:.2f}ms ({total_diff:+.2f}%)")
# 总结
print("\n" + "=" * 70)
if ret_diff < 0:
print(f"性能提升: 检索速度提高了 {-ret_diff:.2f}%")
else:
print(f"性能下降: 检索速度降低了 {ret_diff:.2f}%")
print("=" * 70)
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser(description='Semantic Retriever 性能测试工具')
parser.add_argument('--compare', nargs=2, metavar=('FILE1', 'FILE2'),
help='比较两个性能测试结果文件')
parser.add_argument('--iterations', type=int, default=3,
help='测试迭代次数（默认：3）')
parser.add_argument('--kb-path', default='rust_knowledge_base/rust_docs_sample.json',
help='知识库文件路径')
args = parser.parse_args()
if args.compare:
compare_benchmark_files(args.compare[0], args.compare[1])
else:
run_comprehensive_benchmark(args.kb_path, args.iterations)
|
2301_80743186/rust-agent-code
|
benchmark_semantic_retriever.py
|
Python
|
unknown
| 10,901
|
# 配置文件
import os
# API密钥配置
OPENAI_API_KEY = ""
DEEPSEEK_API_KEY = "sk-6b9a1c1845294019acc98577326b3e9a"
# Gemini API Key
GEMINI_API_KEY = ""
# 星河大模型 API 配置
XINGHE_API_KEY = "bce-v3/ALTAK-GC9TQ2g1jvMelu6uIKMMX/e07d1814829c9e121bb3091b803f860c824e9238"
XINGHE_BASE_URL = "https://qianfan.baidubce.com/v2"
# 模型配置
OPENAI_MODEL = "gpt-3.5-turbo"
DEEPSEEK_MODEL = "deepseek-chat"
XINGHE_MODEL = "ernie-4.5-turbo-vl" # 星河大模型名称
# 应用配置
FLASK_SECRET_KEY = '4c04b4599e28ed1ce04231ae9694cf00c02a9d600bae80051631607a4c537626'
DEBUG_MODE = True
# 默认用户配置
DEFAULT_USERS = {
'admin': {'password': '123456', 'role': 'admin', 'name': '管理员'},
'student': {'password': '123456', 'role': 'student', 'name': '学生'},
'teacher': {'password': '123456', 'role': 'teacher', 'name': '教师'}
}
# 知识库配置
KNOWLEDGE_BASE_PATH = 'rust_knowledge_base/rust_docs_sample.json'
# 问题分类标签
QUESTION_LABELS = ["greeting", "definition", "usage", "error_debug", "comparison", "faq"]
# 从环境变量读取API密钥（如果存在）
if os.getenv('OPENAI_API_KEY'):
OPENAI_API_KEY = os.getenv('OPENAI_API_KEY')
if os.getenv('DEEPSEEK_API_KEY'):
DEEPSEEK_API_KEY = os.getenv('DEEPSEEK_API_KEY')
if os.getenv('GEMINI_API_KEY'):
GEMINI_API_KEY = os.getenv('GEMINI_API_KEY')
if os.getenv('XINGHE_API_KEY'):
XINGHE_API_KEY = os.getenv('XINGHE_API_KEY')
|
2301_80743186/rust-agent-code
|
config.py
|
Python
|
unknown
| 1,448
|
#上下文管理模块
import json
import time
import os
from typing import List, Dict, Optional
from datetime import datetime
class ContextManager:
def __init__(self, max_context_length: int = 5, storage_dir: str = "chat_sessions"):
self.sessions = {}
self.max_context_length = max_context_length
self.storage_dir = storage_dir
self._ensure_storage_dir()
self._load_all_sessions()
def get_context(self, session_id: str) -> List[Dict]:
"""获取会话上下文"""
if session_id not in self.sessions:
return []
session = self.sessions[session_id]
return session.get('context', [])
def update_context(self, session_id: str, question: str, answer: str, classification: Dict):
"""更新会话上下文"""
if session_id not in self.sessions:
self.sessions[session_id] = {
'created_at': datetime.now().isoformat(),
'last_updated': datetime.now().isoformat(),
'context': [],
'question_count': 0,
'question_types': []
}
session = self.sessions[session_id]
# 添加新的对话轮次
turn = {
'timestamp': datetime.now().isoformat(),
'question': question,
'answer': answer,
'classification': classification,
'turn_id': len(session['context']) + 1
}
session['context'].append(turn)
session['last_updated'] = datetime.now().isoformat()
session['question_count'] += 1
session['question_types'].append(classification['label'])
# 限制上下文长度
if len(session['context']) > self.max_context_length:
session['context'] = session['context'][-self.max_context_length:]
# 保存到文件
self._save_session(session_id)
# 更新会话统计
self._update_session_stats(session_id)
def get_session_summary(self, session_id: str) -> Dict:
"""获取会话摘要"""
if session_id not in self.sessions:
return {}
session = self.sessions[session_id]
context = session.get('context', [])
# 统计问题类型
type_counts = {}
for turn in context:
label = turn['classification']['label']
type_counts[label] = type_counts.get(label, 0) + 1
# 生成摘要
summary = {
'session_id': session_id,
'created_at': session['created_at'],
'last_updated': session['last_updated'],
'total_turns': len(context),
'question_types': type_counts,
'current_topic': self._extract_current_topic(context),
'learning_progress': self._assess_learning_progress(context)
}
return summary
def _extract_current_topic(self, context: List[Dict]) -> str:
"""提取当前学习主题"""
if not context:
return "未开始"
# 简单的主题提取逻辑
recent_questions = [turn['question'] for turn in context[-3:]]
question_text = " ".join(recent_questions).lower()
# 关键词匹配
topics = {
'生命周期': ['生命周期', 'lifetime', '作用域'],
'所有权': ['所有权', 'ownership', 'move'],
'借用': ['借用', 'borrow', '引用'],
'错误处理': ['错误', 'error', 'panic', 'result'],
'迭代器': ['迭代器', 'iterator', 'for'],
'模块': ['模块', 'module', 'use', 'mod']
}
for topic, keywords in topics.items():
if any(keyword in question_text for keyword in keywords):
return topic
return "综合学习"
def _assess_learning_progress(self, context: List[Dict]) -> Dict:
"""评估学习进度"""
if not context:
return {'level': 'beginner', 'confidence': 0.0}
# 基于问题类型和复杂度评估
type_scores = {
'definition': 1,
'usage': 2,
'error_debug': 3,
'comparison': 4,
'faq': 1
}
total_score = 0
for turn in context:
label = turn['classification']['label']
total_score += type_scores.get(label, 1)
avg_score = total_score / len(context)
if avg_score >= 3.5:
level = 'advanced'
confidence = min(0.9, avg_score / 5.0)
elif avg_score >= 2.0:
level = 'intermediate'
confidence = min(0.8, avg_score / 3.0)
else:
level = 'beginner'
confidence = min(0.7, avg_score / 2.0)
return {
'level': level,
'confidence': confidence,
'score': avg_score
}
def _update_session_stats(self, session_id: str):
"""更新会话统计信息"""
session = self.sessions[session_id]
# 计算会话时长
created_at = datetime.fromisoformat(session['created_at'])
last_updated = datetime.fromisoformat(session['last_updated'])
duration = (last_updated - created_at).total_seconds()
session['duration_seconds'] = duration
session['avg_turn_interval'] = duration / session['question_count'] if session['question_count'] > 0 else 0
def clear_context(self, session_id: str):
"""清除会话上下文"""
if session_id in self.sessions:
self.sessions[session_id]['context'] = []
self.sessions[session_id]['last_updated'] = datetime.now().isoformat()
# 保存到文件
self._save_session(session_id)
def get_all_sessions(self) -> Dict:
"""获取所有会话信息"""
return {
session_id: self.get_session_summary(session_id)
for session_id in self.sessions.keys()
}
def save_sessions(self, file_path: str):
"""保存会话数据到文件"""
with open(file_path, 'w', encoding='utf-8') as f:
json.dump(self.sessions, f, ensure_ascii=False, indent=2)
def load_sessions(self, file_path: str):
"""从文件加载会话数据"""
try:
with open(file_path, 'r', encoding='utf-8') as f:
self.sessions = json.load(f)
except FileNotFoundError:
print(f"会话文件 {file_path} 不存在，使用空会话")
self.sessions = {}
def _ensure_storage_dir(self):
"""确保存储目录存在"""
if not os.path.exists(self.storage_dir):
os.makedirs(self.storage_dir)
def _save_session(self, session_id: str):
"""保存单个会话到文件"""
if session_id in self.sessions:
session_file = os.path.join(self.storage_dir, f"{session_id}.json")
try:
with open(session_file, 'w', encoding='utf-8') as f:
json.dump(self.sessions[session_id], f, ensure_ascii=False, indent=2)
except Exception as e:
print(f"保存会话 {session_id} 失败: {e}")
def _load_all_sessions(self):
"""加载所有会话文件"""
if not os.path.exists(self.storage_dir):
return
for filename in os.listdir(self.storage_dir):
if filename.endswith('.json'):
session_id = filename[:-5] # 移除.json后缀
session_file = os.path.join(self.storage_dir, filename)
try:
with open(session_file, 'r', encoding='utf-8') as f:
self.sessions[session_id] = json.load(f)
except Exception as e:
print(f"加载会话 {session_id} 失败: {e}")
def delete_session(self, session_id: str):
"""删除会话文件和内存数据"""
# 删除内存中的数据
if session_id in self.sessions:
del self.sessions[session_id]
# 删除文件
session_file = os.path.join(self.storage_dir, f"{session_id}.json")
if os.path.exists(session_file):
try:
os.remove(session_file)
except Exception as e:
print(f"删除会话文件 {session_id} 失败: {e}")
def get_storage_stats(self) -> Dict:
"""获取存储统计信息"""
if not os.path.exists(self.storage_dir):
return {"total_sessions": 0, "total_size": 0, "storage_dir": self.storage_dir}
total_sessions = 0
total_size = 0
for filename in os.listdir(self.storage_dir):
if filename.endswith('.json'):
total_sessions += 1
file_path = os.path.join(self.storage_dir, filename)
total_size += os.path.getsize(file_path)
return {
"total_sessions": total_sessions,
"total_size": total_size,
"total_size_mb": round(total_size / (1024 * 1024), 2),
"storage_dir": self.storage_dir
}
|
2301_80743186/rust-agent-code
|
context_manager.py
|
Python
|
unknown
| 9,351
|
#对话管理模块
class DialogueManager:
def __init__(self):
self.sessions = {}
def get_context(self, user_id):
return self.sessions.get(user_id, [])
def append_turn(self, user_id, question, answer):
if user_id not in self.sessions:
self.sessions[user_id] = []
self.sessions[user_id].append({'question': question, 'answer': answer})
|
2301_80743186/rust-agent-code
|
dialogue_manager.py
|
Python
|
unknown
| 393
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Rust知识库扩充工具
自动从公开资源和模板生成Rust知识库条目
"""
import json
import os
import random
import time
# import requests # 可选，目前未使用
from typing import List, Dict
import re
class RustKnowledgeBaseExpander:
def __init__(self, output_path='rust_knowledge_base/rust_docs_expanded.json'):
self.output_path = output_path
self.existing_knowledge = []
self.new_entries = []
self.categories = ["definition", "usage", "error_debug", "comparison", "faq"]
self.difficulties = ["beginner", "intermediate", "advanced"]
# Rust主题分类和相关子主题
self.rust_topics = {
"所有权与生命周期": ["所有权系统", "借用规则", "生命周期参数", "移动语义", "复制语义", "引用计数"],
"基础类型": ["标量类型", "复合类型", "元组", "数组", "切片", "字符串"],
"函数与闭包": ["函数定义", "函数参数", "返回值", "闭包", "高阶函数", "递归"],
"结构体与枚举": ["结构体定义", "方法实现", "枚举类型", "模式匹配", "Option类型", "Result类型"],
"特质系统": ["特质定义", "默认实现", "特质边界", "关联类型", "特质对象", "孤儿规则"],
"泛型编程": ["泛型函数", "泛型类型", "泛型特质", "泛型约束", "类型参数", "单态化"],
"模块系统": ["模块定义", "可见性", "use声明", "pub关键字", "super和self", "包管理"],
"错误处理": ["Result类型", "?操作符", "panic宏", "错误传播", "自定义错误", "错误转换"],
"集合类型": ["Vec动态数组", "HashMap哈希表", "HashSet集合", "BTreeMap有序映射", "BTreeSet有序集合", "迭代器"],
"智能指针": ["Box智能指针", "Rc引用计数", "Arc原子引用", "RefCell内部可变性", "Cell类型", "Weak引用"],
"并发编程": ["线程创建", "消息传递", "互斥锁", "读写锁", "原子类型", "线程安全"],
"异步编程": ["async/await", "Future特质", "异步运行时", "异步任务", "并发控制", "流处理"],
"不安全Rust": ["unsafe关键字", "原始指针", "FFI接口", "内联汇编", "全局变量", "内存布局"],
"宏系统": ["声明宏", "过程宏", "derive宏", "属性宏", "函数式宏", "宏展开"],
"测试与基准": ["单元测试", "集成测试", "文档测试", "基准测试", "测试属性", "测试工具"],
"性能优化": ["零成本抽象", "内存优化", "算法优化", "并发优化", "编译优化", "分析工具"],
"Rust生态": ["Cargo工具", "crates.io", "标准库", "第三方库", "开发工具", "社区实践"],
"高级特性": ["无栈协程", "类型族", "常量泛型", "稳定ABI", "内联汇编", "链接优化"]
}
# 代码模板
self.code_templates = {
"definition": [
"// 定义{topic}\n{code}",
"// {topic}的基本实现\n{code}",
"// {topic}的核心概念示例\n{code}"
],
"usage": [
"// 使用{topic}\n{code}",
"// {topic}的常见用法\n{code}",
"// {topic}的实际应用示例\n{code}"
],
"error_debug": [
"// {topic}的错误示例\n{code}\n// 修复方法: {fix}",
"// 错误代码\n{code}\n// 正确版本\n{correct}",
"// 编译错误: {error}\n{code}"
],
"comparison": [
"// Rust中的{topic}\n{rust_code}\n\n// 其他语言中的类似实现\n// {other_language}:\n// {other_code}",
"// {topic}在Rust vs {other_language}\n\n// Rust:\n{rust_code}\n\n// {other_language}:\n// {other_code}"
],
"faq": [
"// 如何在Rust中实现{topic}？\n{code}",
"// {topic}的最佳实践\n{code}",
"// 处理{topic}的推荐方法\n{code}"
]
}
def load_existing_knowledge(self, existing_path='rust_knowledge_base/rust_docs_sample.json'):
"""加载现有的知识库文件"""
if os.path.exists(existing_path):
try:
with open(existing_path, 'r', encoding='utf-8') as f:
self.existing_knowledge = json.load(f)
print(f"成功加载现有知识库，共{len(self.existing_knowledge)}条记录")
return True
except Exception as e:
print(f"加载现有知识库失败: {e}")
return False
def generate_entry_from_template(self, entry_id: str, category: str, difficulty: str) -> Dict:
"""从模板生成知识条目"""
# 随机选择主题和子主题
main_topic = random.choice(list(self.rust_topics.keys()))
sub_topic = random.choice(self.rust_topics[main_topic])
# 根据类别和难度生成内容
if category == "definition":
content = f"Rust中的{sub_topic}是{main_topic}的重要组成部分。{sub_topic}用于{self._generate_description(category, sub_topic)}。"
code = self._generate_code_snippet(category, sub_topic, difficulty)
elif category == "usage":
content = f"在Rust中使用{sub_topic}的方法：{self._generate_description(category, sub_topic)}。{self._generate_usage_examples(sub_topic, difficulty)}。"
code = self._generate_code_snippet(category, sub_topic, difficulty)
elif category == "error_debug":
content = f"常见的{sub_topic}错误及解决方案：{self._generate_description(category, sub_topic)}。{self._generate_error_fix(sub_topic)}。"
code = self._generate_code_snippet(category, sub_topic, difficulty)
elif category == "comparison":
other_language = random.choice(["C++", "Python", "Go", "JavaScript"])
content = f"Rust与{other_language}中的{sub_topic}对比：{self._generate_description(category, sub_topic)}。{self._generate_language_comparison(sub_topic, other_language)}。"
code = self._generate_code_snippet(category, sub_topic, difficulty, other_language)
elif category == "faq":
content = f"关于Rust中{sub_topic}的常见问题：{self._generate_description(category, sub_topic)}。{self._generate_faq_answer(sub_topic)}。"
code = self._generate_code_snippet(category, sub_topic, difficulty)
# 生成标签
tags = [main_topic, sub_topic]
# 根据内容添加一些相关标签
if "所有权" in content:
tags.append("所有权")
if "生命周期" in content:
tags.append("生命周期")
if "借用" in content:
tags.append("借用")
if "并发" in content:
tags.append("并发")
if "异步" in content:
tags.append("异步")
# 确保标签不重复且数量适中
tags = list(set(tags))[:5] # 最多5个标签
# 选择合适的代码模板
code_template = random.choice(self.code_templates[category])
# 创建参数字典，始终包含topic
params = {'topic': sub_topic}
# 根据模板字符串中需要的参数，添加相应的值
if '{code}' in code_template:
params['code'] = code
if '{error}' in code_template:
params['error'] = code.get('error', code) if isinstance(code, dict) else code
if '{fix}' in code_template:
params['fix'] = code.get('fix', '修复相关错误') if isinstance(code, dict) else '修复相关错误'
if '{correct}' in code_template:
params['correct'] = code.get('correct', '// 正确代码示例') if isinstance(code, dict) else '// 正确代码示例'
if '{rust_code}' in code_template:
params['rust_code'] = code.get('rust', code) if isinstance(code, dict) else code
if '{other_language}' in code_template:
params['other_language'] = code.get('other_language', 'C++') if isinstance(code, dict) else 'C++'
if '{other_code}' in code_template:
params['other_code'] = code.get('other_code', '// 其他语言代码示例') if isinstance(code, dict) else '// 其他语言代码示例'
# 格式化模板
filled_code = code_template.format(**params)
return {
"id": entry_id,
"title": sub_topic,
"content": content,
"code": filled_code,
"tags": tags,
"category": category,
"difficulty": difficulty
}
def _generate_description(self, category: str, topic: str) -> str:
"""生成描述文本"""
descriptions = {
"definition": f"{topic}是Rust语言的基础概念，它提供了{self._get_topic_feature(topic)}的能力",
"usage": f"正确使用{topic}可以提高代码的{self._get_benefit(topic)}",
"error_debug": f"常见的错误包括{self._get_common_errors(topic)}",
"comparison": f"Rust的{topic}实现更加安全高效",
"faq": f"这个问题经常被Rust初学者问到"
}
return descriptions.get(category, "这是一个重要的Rust概念")
def _generate_code_snippet(self, category: str, topic: str, difficulty: str, other_language: str = "C++") -> str:
"""生成代码片段"""
# 根据主题和类别生成相应的代码片段
if topic == "所有权系统":
return "let s1 = String::from(\"hello\");\nlet s2 = s1; // s1的所有权移动到s2\n// println!(\"{}\", s1); // 错误：s1不再有效"
elif topic == "借用规则":
return "let mut s = String::from(\"hello\");\nlet r1 = &s; // 不可变借用\nlet r2 = &s; // 不可变借用\n// let r3 = &mut s; // 错误：不能同时有可变和不可变借用"
elif topic == "生命周期参数":
return "fn longest<'a>(x: &'a str, y: &'a str) -> &'a str {\n if x.len() > y.len() { x } else { y }\n}"
elif topic == "结构体定义":
return "struct User {\n name: String,\n age: u32,\n active: bool,\n}\n\nlet user = User {\n name: String::from(\"Alice\"),\n age: 30,\n active: true,\n};"
elif topic == "错误处理" and category == "error_debug":
return {
"error": "fn read_file() {\n let file = File::open(\"hello.txt\"); // 缺少错误处理\n let mut contents = String::new();\n file.read_to_string(&mut contents); // 错误\n}",
"correct": "use std::fs::File;\nuse std::io::{self, Read};\n\nfn read_file() -> io::Result<String> {\n let mut file = File::open(\"hello.txt\")?;\n let mut contents = String::new();\n file.read_to_string(&mut contents)?;\n Ok(contents)\n}",
"fix": "使用?操作符进行错误传播"
}
elif topic == "并发编程" and category == "comparison":
return {
"rust": "use std::thread;\nuse std::sync::mpsc;\n\nfn main() {\n let (tx, rx) = mpsc::channel();\n \n thread::spawn(move || {\n tx.send(String::from(\"hello\")).unwrap();\n });\n \n let received = rx.recv().unwrap();\n println!(\"Got: {}\", received);\n}",
"other_language": other_language,
"other_code": "// C++版本\n#include <thread>\n#include <iostream>\n#include <string>\n\nint main() {\n std::thread t([]{\n std::cout << \"hello\" << std::endl;\n });\n t.join();\n return 0;\n}"
}
elif topic == "闭包":
return "// 闭包定义\nlet add_one = |x: i32| -> i32 { x + 1 };\nlet result = add_one(5); // 结果是6\n\n// 更简洁的语法\nlet multiply = |x, y| x * y;\nlet product = multiply(3, 4); // 结果是12"
elif topic == "泛型函数":
return "// 泛型函数定义\nf<T>(x: T, y: T) -> T where T: std::ops::Add<Output = T> {\n x + y\n}\n\n// 使用泛型函数\nlet sum_i32 = add(5, 10); // i32类型\nlet sum_f64 = add(3.14, 2.71); // f64类型"
elif topic == "特质定义":
return "// 特质定义\ntrait Animal {\n fn name(&self) -> &str;\n \n // 默认实现\n fn speak(&self) -> String {\n format!(\"{} makes a sound\", self.name())\n }\n}\n\n// 实现特质\nstruct Dog { name: String }\nimpl Animal for Dog {\n fn name(&self) -> &str { &self.name }\n fn speak(&self) -> String {\n format!(\"{} barks\", self.name())\n }\n}"
else:
# 为其他主题生成通用代码
return self._generate_generic_code(topic, difficulty)
def _generate_generic_code(self, topic: str, difficulty: str) -> str:
"""生成通用代码片段"""
if difficulty == "beginner":
return f"// {topic}的基础示例\nfn main() {{\n println!(\"Hello, {topic}!\");\n}}"
elif difficulty == "intermediate":
return f"// {topic}的中级示例\nfn process_{topic.lower().replace(' ', '_')}() -> Result<(), Box<dyn std::error::Error>> {{\n // 实现{topic}的逻辑\n Ok(())\n}}\n\nfn main() {{\n if let Err(e) = process_{topic.lower().replace(' ', '_')}() {{\n eprintln!(\"Error: {{}}\", e);\n }}\n}}"
else: # advanced
# 先选择特性
sync_feature = random.choice(['Mutex', 'Arc', 'RwLock'])
data_feature = random.choice(['Mutex', 'Arc'])
# 然后构建字符串
code = f"// {topic}的高级示例\nuse std::sync::{sync_feature};\nuse std::thread;\n\n"
code += f"fn advanced_{topic.lower().replace(' ', '_')}() {{\n // 复杂的{topic}实现\n let data = {data_feature}::new(vec![1, 2, 3]);\n // 多线程或其他高级特性\n}}\n\n"
code += f"fn main() {{\n advanced_{topic.lower().replace(' ', '_')}();\n}}"
return code
def _get_topic_feature(self, topic: str) -> str:
"""获取主题特性描述"""
features = [
"内存安全", "并发控制", "类型安全", "零成本抽象", "高性能",
"错误处理", "代码复用", "模块化", "可扩展性", "可读性"
]
return random.choice(features)
def _get_benefit(self, topic: str) -> str:
"""获取使用主题的好处"""
benefits = [
"安全性", "性能", "可维护性", "可读性", "可扩展性",
"代码复用", "错误预防", "运行效率", "开发效率", "可靠性"
]
return random.choice(benefits)
def _get_common_errors(self, topic: str) -> str:
"""获取常见错误描述"""
errors = [
"生命周期不匹配", "借用规则违反", "类型错误", "空指针解引用",
"数据竞争", "资源泄漏", "无限递归", "溢出", "死锁", "错误处理不当"
]
return random.choice(errors)
def _generate_usage_examples(self, topic: str, difficulty: str) -> str:
"""生成使用示例描述"""
examples = [
f"在实际项目中，{topic}常用于处理{self._get_use_case(topic)}",
f"{topic}的典型应用场景包括{self._get_use_case(topic)}",
f"推荐在{self._get_situation(topic)}时使用{topic}"
]
return random.choice(examples)
def _generate_error_fix(self, topic: str) -> str:
"""生成错误修复方法"""
fixes = [
"检查生命周期注解", "遵循借用规则", "正确使用智能指针",
"添加适当的类型约束", "实现错误处理逻辑", "优化内存使用"
]
return random.choice(fixes)
def _generate_language_comparison(self, topic: str, other_language: str) -> str:
"""生成语言对比描述"""
comparisons = [
f"Rust的{topic}比{other_language}更安全",
f"Rust在{topic}方面提供了编译时检查，而{other_language}依赖运行时",
f"Rust的{topic}实现兼顾了安全和性能，{other_language}在这方面有所取舍"
]
return random.choice(comparisons)
def _generate_faq_answer(self, topic: str) -> str:
"""生成FAQ答案"""
answers = [
f"要实现{topic}，建议遵循Rust的最佳实践",
f"{topic}的关键在于理解Rust的所有权模型",
f"对于{topic}，推荐使用标准库中的{self._get_recommended_feature(topic)}"
]
return random.choice(answers)
def _get_use_case(self, topic: str) -> str:
"""获取使用场景"""
use_cases = [
"复杂数据结构", "并发程序", "系统编程", "Web后端",
"命令行工具", "游戏开发", "嵌入式系统", "高性能计算"
]
return random.choice(use_cases)
def _get_situation(self, topic: str) -> str:
"""获取适用情况"""
situations = [
"需要高性能", "对安全性要求高", "处理复杂数据",
"并发编程", "系统级开发", "跨平台应用"
]
return random.choice(situations)
def _get_recommended_feature(self, topic: str) -> str:
"""获取推荐特性"""
features = [
"标准集合类型", "智能指针", "并发原语", "错误处理机制",
"特质系统", "泛型", "异步运行时", "宏系统"
]
return random.choice(features)
def fetch_from_rust_docs(self, topic: str) -> Dict:
"""尝试从Rust官方文档获取内容（可选增强功能）"""
# 这是一个占位函数，可以扩展为实际的API调用
# 由于Rust官方文档可能没有开放API，可以考虑使用其他公开资源
return {}
def generate_knowledge_base(self, target_count: int = 500):
"""生成指定数量的知识条目"""
# 确定需要生成的新条目数量
existing_count = len(self.existing_knowledge)
if existing_count >= target_count:
print(f"现有知识库已有{existing_count}条记录，已满足目标数量{target_count}")
return
new_count = target_count - existing_count
print(f"需要生成{new_count}条新的知识条目")
# 生成新条目
for i in range(new_count):
# 生成唯一ID
entry_id = f"k{i + existing_count + 1:03d}"
# 随机选择类别和难度，但保持一定的分布
category_weights = {
"definition": 0.3,
"usage": 0.3,
"error_debug": 0.2,
"comparison": 0.1,
"faq": 0.1
}
category = random.choices(
list(category_weights.keys()),
weights=list(category_weights.values())
)[0]
# 根据类别调整难度分布
if category in ["definition", "usage"]:
difficulty_weights = {"beginner": 0.4, "intermediate": 0.5, "advanced": 0.1}
else:
difficulty_weights = {"beginner": 0.2, "intermediate": 0.5, "advanced": 0.3}
difficulty = random.choices(
list(difficulty_weights.keys()),
weights=list(difficulty_weights.values())
)[0]
# 生成条目
entry = self.generate_entry_from_template(entry_id, category, difficulty)
self.new_entries.append(entry)
# 显示进度
if (i + 1) % 50 == 0:
print(f"已生成{i + 1}/{new_count}条记录")
# 避免生成过快
time.sleep(0.01)
print(f"成功生成{len(self.new_entries)}条新的知识条目")
def combine_and_save(self):
"""合并现有条目和新条目并保存"""
# 合并所有条目
combined_knowledge = self.existing_knowledge + self.new_entries
# 确保ID唯一
seen_ids = set()
unique_knowledge = []
for entry in combined_knowledge:
if entry["id"] not in seen_ids:
seen_ids.add(entry["id"])
unique_knowledge.append(entry)
# 按ID排序
unique_knowledge.sort(key=lambda x: x["id"])
# 保存到文件
os.makedirs(os.path.dirname(self.output_path), exist_ok=True)
with open(self.output_path, 'w', encoding='utf-8') as f:
json.dump(unique_knowledge, f, ensure_ascii=False, indent=2)
print(f"成功保存扩充后的知识库到{self.output_path}")
print(f"最终知识库包含{len(unique_knowledge)}条记录")
# 统计各类别的分布
category_count = {}
difficulty_count = {}
for entry in unique_knowledge:
category = entry.get("category", "unknown")
difficulty = entry.get("difficulty", "unknown")
category_count[category] = category_count.get(category, 0) + 1
difficulty_count[difficulty] = difficulty_count.get(difficulty, 0) + 1
print("\n类别分布:")
for cat, count in category_count.items():
print(f" {cat}: {count}")
print("\n难度分布:")
for diff, count in difficulty_count.items():
print(f" {diff}: {count}")
def validate_knowledge_base(self, file_path=None):
"""验证知识库格式是否正确"""
path_to_check = file_path or self.output_path
if not os.path.exists(path_to_check):
print(f"文件不存在: {path_to_check}")
return False
try:
with open(path_to_check, 'r', encoding='utf-8') as f:
knowledge = json.load(f)
if not isinstance(knowledge, list):
print("错误：知识库必须是一个数组")
return False
required_fields = ["id", "title", "content", "code", "tags", "category", "difficulty"]
seen_ids = set()
invalid_entries = []
for i, entry in enumerate(knowledge):
# 检查必需字段
missing_fields = [field for field in required_fields if field not in entry]
if missing_fields:
invalid_entries.append((i, f"缺少必需字段: {', '.join(missing_fields)}"))
continue
# 检查ID唯一性
if entry["id"] in seen_ids:
invalid_entries.append((i, f"ID重复: {entry['id']}"))
seen_ids.add(entry["id"])
# 检查字段类型
if not isinstance(entry["tags"], list):
invalid_entries.append((i, "tags必须是数组类型"))
if invalid_entries:
print(f"发现{len(invalid_entries)}个无效条目:")
for idx, error in invalid_entries:
print(f" 条目{idx}: {error}")
return False
print(f"知识库验证成功，共{len(knowledge)}条有效记录")
return True
except json.JSONDecodeError as e:
print(f"JSON格式错误: {e}")
return False
except Exception as e:
print(f"验证过程中发生错误: {e}")
return False
def main():
print("=== Rust知识库扩充工具 ===")
print("此工具将帮助您自动扩充Rust知识库，无需手动输入\n")
# 创建扩充器实例
expander = RustKnowledgeBaseExpander()
# 加载现有知识库
expander.load_existing_knowledge()
# 设置目标数量
target_count = 500 # 默认目标500条
# 生成新条目
expander.generate_knowledge_base(target_count)
# 合并并保存
expander.combine_and_save()
# 验证生成的知识库
expander.validate_knowledge_base()
print("\n=== 知识库扩充完成 ===")
print("您可以在config.py中修改KNOWLEDGE_BASE_PATH指向新的知识库文件")
print("或者将生成的文件复制到rust_knowledge_base/rust_docs_sample.json替换原有文件")
if __name__ == "__main__":
main()
|
2301_80743186/rust-agent-code
|
expand_knowledge_base.py
|
Python
|
unknown
| 24,904
|
# 知识增强模块 - 集成智源研究院数据
import requests
import json
import os
from typing import Dict, List, Optional
from datetime import datetime, timedelta
import hashlib
from performance_timer import global_timer, APITimer, StepTimer
class ZhiyuanKnowledgeEnhancer:
"""智源研究院知识增强器"""
def __init__(self):
self.cache_dir = "zhiyuan_cache"
self.cache_duration = timedelta(hours=24) # 缓存24小时
self.api_endpoints = {
"papers": "https://api.zhiyuan.com/papers", # 论文数据
"datasets": "https://api.zhiyuan.com/datasets", # 数据集
"models": "https://api.zhiyuan.com/models", # 模型
"news": "https://api.zhiyuan.com/news" # 新闻动态
}
self._ensure_cache_dir()
def _ensure_cache_dir(self):
"""确保缓存目录存在"""
if not os.path.exists(self.cache_dir):
os.makedirs(self.cache_dir)
def _get_cache_key(self, query: str, category: str) -> str:
"""生成缓存键"""
return hashlib.md5(f"{query}_{category}".encode()).hexdigest()
def _is_cache_valid(self, cache_file: str) -> bool:
"""检查缓存是否有效"""
if not os.path.exists(cache_file):
return False
file_time = datetime.fromtimestamp(os.path.getmtime(cache_file))
return datetime.now() - file_time < self.cache_duration
def _load_from_cache(self, cache_file: str) -> Optional[Dict]:
"""从缓存加载数据"""
try:
with open(cache_file, 'r', encoding='utf-8') as f:
return json.load(f)
except:
return None
def _save_to_cache(self, cache_file: str, data: Dict):
"""保存数据到缓存"""
try:
with open(cache_file, 'w', encoding='utf-8') as f:
json.dump(data, f, ensure_ascii=False, indent=2)
except Exception as e:
print(f"缓存保存失败: {e}")
def search_rust_knowledge(self, query: str, category: str = "all") -> Dict:
"""搜索Rust相关知识"""
cache_key = self._get_cache_key(query, category)
cache_file = os.path.join(self.cache_dir, f"{cache_key}.json")
# 检查缓存
if self._is_cache_valid(cache_file):
cached_data = self._load_from_cache(cache_file)
if cached_data:
print(f"使用缓存数据: {query}")
return cached_data
# 从智源研究院获取数据
knowledge_data = self._fetch_zhiyuan_data(query, category)
# 保存到缓存
if knowledge_data:
self._save_to_cache(cache_file, knowledge_data)
return knowledge_data
def _fetch_zhiyuan_data(self, query: str, category: str) -> Dict:
"""从智源研究院获取数据"""
try:
# 模拟智源研究院API调用（实际使用时需要真实的API）
rust_knowledge = self._get_rust_knowledge_base()
# 根据查询内容匹配相关知识
matched_knowledge = self._match_knowledge(query, rust_knowledge)
return {
"status": "success",
"query": query,
"category": category,
"knowledge": matched_knowledge,
"source": "智源研究院",
"timestamp": datetime.now().isoformat()
}
except Exception as e:
print(f"智源研究院数据获取失败: {e}")
return {
"status": "error",
"message": str(e),
"knowledge": []
}
def _get_rust_knowledge_base(self) -> Dict:
"""获取Rust知识库（基于智源研究院的研究成果）"""
return {
"papers": [
{
"title": "Rust语言内存安全机制研究",
"authors": ["智源研究院", "清华大学"],
"year": 2023,
"abstract": "本文深入分析了Rust语言的所有权系统和借用检查器，提出了内存安全的新理论框架。",
"keywords": ["Rust", "内存安全", "所有权", "借用检查器"],
"url": "https://zhiyuan.com/papers/rust-memory-safety"
},
{
"title": "并发编程语言对比研究：Rust vs Go vs C++",
"authors": ["智源研究院", "中科院"],
"year": 2023,
"abstract": "对比分析了Rust、Go和C++在并发编程方面的优劣，为开发者选择提供参考。",
"keywords": ["Rust", "并发编程", "性能对比", "Go", "C++"],
"url": "https://zhiyuan.com/papers/concurrent-languages"
},
{
"title": "Rust生态系统发展现状与趋势分析",
"authors": ["智源研究院"],
"year": 2024,
"abstract": "分析了Rust生态系统的发展现状，包括Cargo包管理器、社区发展等。",
"keywords": ["Rust", "生态系统", "Cargo", "社区"],
"url": "https://zhiyuan.com/papers/rust-ecosystem"
}
],
"datasets": [
{
"name": "Rust代码质量评估数据集",
"description": "包含10万个Rust项目的代码质量评估数据",
"size": "2.5GB",
"format": "JSON",
"url": "https://zhiyuan.com/datasets/rust-code-quality"
},
{
"name": "Rust性能基准测试数据集",
"description": "Rust与其他语言性能对比的基准测试数据",
"size": "1.8GB",
"format": "CSV",
"url": "https://zhiyuan.com/datasets/rust-benchmarks"
}
],
"models": [
{
"name": "Rust代码生成模型",
"description": "基于Transformer的Rust代码自动生成模型",
"parameters": "7B",
"accuracy": "92.3%",
"url": "https://zhiyuan.com/models/rust-codegen"
},
{
"name": "Rust漏洞检测模型",
"description": "使用深度学习检测Rust代码中的潜在漏洞",
"parameters": "3B",
"accuracy": "89.7%",
"url": "https://zhiyuan.com/models/rust-vuln-detection"
}
],
"news": [
{
"title": "Rust 1.75.0发布：性能优化与安全增强",
"date": "2024-01-15",
"summary": "新版本在编译速度和内存使用方面有显著改进",
"url": "https://zhiyuan.com/news/rust-1-75-0"
},
{
"title": "智源研究院开源Rust机器学习框架",
"date": "2024-01-10",
"summary": "为Rust生态系统贡献了新的机器学习工具",
"url": "https://zhiyuan.com/news/rust-ml-framework"
}
]
}
def _match_knowledge(self, query: str, knowledge_base: Dict) -> List[Dict]:
"""根据查询匹配相关知识"""
matched_items = []
query_lower = query.lower()
# Rust核心概念到论文主题的映射
concept_to_paper_mapping = {
# 所有权和借用相关概念 -> 内存安全论文
"引用": ["Rust语言内存安全机制研究"],
"不可变引用": ["Rust语言内存安全机制研究"],
"可变引用": ["Rust语言内存安全机制研究"],
"借用": ["Rust语言内存安全机制研究"],
"所有权": ["Rust语言内存安全机制研究"],
"生命周期": ["Rust语言内存安全机制研究"],
"借用检查器": ["Rust语言内存安全机制研究"],
"内存安全": ["Rust语言内存安全机制研究"],
# 并发相关概念 -> 并发编程论文
"并发": ["并发编程语言对比研究：Rust vs Go vs C++"],
"异步": ["并发编程语言对比研究：Rust vs Go vs C++"],
"线程": ["并发编程语言对比研究：Rust vs Go vs C++"],
# 生态系统相关概念 -> 生态系统论文
"cargo": ["Rust生态系统发展现状与趋势分析"],
"包管理": ["Rust生态系统发展现状与趋势分析"],
"生态系统": ["Rust生态系统发展现状与趋势分析"],
"社区": ["Rust生态系统发展现状与趋势分析"]
}
# 匹配论文
for paper in knowledge_base["papers"]:
matched = False
relevance = 0.0
# 方法1: 直接关键词匹配
if any(keyword.lower() in query_lower for keyword in paper["keywords"]):
matched = True
relevance = self._calculate_relevance(query, paper["keywords"])
# 方法2: 通过概念映射匹配
for concept, paper_titles in concept_to_paper_mapping.items():
if concept in query_lower and paper["title"] in paper_titles:
matched = True
# 概念匹配的相关性稍低，但仍然是相关的
relevance = max(relevance, 0.6)
# 方法3: 如果查询包含"rust"且论文标题包含"Rust"，给予基础相关性
if "rust" in query_lower and "rust" in paper["title"].lower():
matched = True
relevance = max(relevance, 0.5)
if matched:
matched_items.append({
"type": "paper",
"title": paper["title"],
"abstract": paper["abstract"],
"relevance": relevance,
"url": paper["url"]
})
# 匹配数据集
for dataset in knowledge_base["datasets"]:
if "rust" in query_lower and any(word in query_lower for word in ["数据", "数据集", "质量", "性能"]):
matched_items.append({
"type": "dataset",
"name": dataset["name"],
"description": dataset["description"],
"relevance": 0.8,
"url": dataset["url"]
})
# 匹配模型
for model in knowledge_base["models"]:
if "rust" in query_lower and any(word in query_lower for word in ["模型", "生成", "检测", "AI"]):
matched_items.append({
"type": "model",
"name": model["name"],
"description": model["description"],
"relevance": 0.7,
"url": model["url"]
})
# 按相关性排序
matched_items.sort(key=lambda x: x["relevance"], reverse=True)
return matched_items[:5] # 返回前5个最相关的结果
def _calculate_relevance(self, query: str, keywords: List[str]) -> float:
"""计算相关性分数"""
query_words = set(query.lower().split())
keyword_words = set([kw.lower() for kw in keywords])
intersection = len(query_words & keyword_words)
union = len(query_words | keyword_words)
return intersection / union if union > 0 else 0.0
def enhance_answer_with_knowledge(self, question: str, answer: str, classification: Dict) -> str:
"""使用智源研究院知识增强回答"""
try:
# 检查缓存
cache_key = self._get_cache_key(question + answer, "enhanced")
cache_file = os.path.join(self.cache_dir, f"{cache_key}.json")
if self._is_cache_valid(cache_file):
cached_result = self._load_from_cache(cache_file)
if cached_result:
global_timer.add_info("知识增强", "使用缓存")
return cached_result
with StepTimer("知识增强完整流程"):
# 检查是否为问候语，如果是则跳过知识增强
if classification.get('label') == 'greeting':
global_timer.add_info("知识增强", "问候语，跳过")
return answer
# 检查问题是否包含Rust相关关键词
question_lower = question.lower()
rust_keywords = [
'rust', '生命周期', '所有权', '借用', '可变', '不可变', 'trait', 'struct', 'enum',
'match', 'option', 'result', '迭代器', '闭包', '宏', '模块', 'cargo', '编译',
'错误', '调试', '内存', '安全', '并发', '异步', 'future', 'pin', 'unsafe',
'引用', '指针', '智能指针', 'box', 'rc', 'arc', 'refcell', 'cell', 'weak',
'vec', 'hashmap', 'hashset', 'btreemap', 'btreeset', '字符串', '切片',
'函数', '方法', '闭包', '泛型', '类型', '变量', '常量', '静态变量'
]
# 如果问题不包含任何Rust相关关键词，跳过知识增强
if not any(keyword in question_lower for keyword in rust_keywords):
global_timer.add_info("知识增强", "非Rust问题，跳过")
return answer
# 搜索相关知识
with APITimer("知识搜索"):
knowledge_data = self.search_rust_knowledge(question, classification.get('label', 'all'))
global_timer.add_info("知识搜索结果", len(knowledge_data.get("knowledge", [])))
if knowledge_data.get("status") == "success" and knowledge_data.get("knowledge"):
# 构建增强的回答
with StepTimer("构建增强回答"):
enhanced_answer = self._build_enhanced_answer(answer, knowledge_data["knowledge"])
# 缓存结果
self._save_to_cache(cache_file, enhanced_answer)
return enhanced_answer
else:
return answer
except Exception as e:
print(f"知识增强失败: {e}")
global_timer.add_info("知识增强错误", str(e)[:100])
return answer
def _build_enhanced_answer(self, original_answer: str, knowledge_items: List[Dict]) -> str:
"""构建增强的回答"""
if not knowledge_items:
return original_answer
# 添加智源研究院知识增强部分
enhancement_section = "\n\n## 🧠 智源研究院知识增强\n"
enhancement_section += "基于智源研究院的最新研究成果，为您提供更深入的专业见解：\n\n"
for item in knowledge_items[:3]: # 只显示前3个最相关的
if item["type"] == "paper":
enhancement_section += f"### 📄 相关研究论文\n\n"
# 添加可点击的标题链接
paper_url = item.get('url', '#')
enhancement_section += f"**[{item['title']}]({paper_url})**\n\n"
enhancement_section += f"{item['abstract']}\n\n"
enhancement_section += f"<div style='margin-top: 8px; padding: 8px; background: #f0f7ff; border-left: 3px solid #3498db; border-radius: 4px;'>\n"
enhancement_section += f"<small>📌 <strong>来源：</strong>智源研究院 | <strong>相关性：</strong>{item['relevance']:.1%} | "
enhancement_section += f"<a href='{paper_url}' target='_blank' style='color: #3498db; text-decoration: none;'>🔗 查看详情</a></small>\n"
enhancement_section += f"</div>\n\n"
elif item["type"] == "dataset":
enhancement_section += f"### 📊 相关数据集\n\n"
dataset_url = item.get('url', '#')
enhancement_section += f"**[{item['name']}]({dataset_url})**\n\n"
enhancement_section += f"{item['description']}\n\n"
enhancement_section += f"<div style='margin-top: 8px; padding: 8px; background: #f0f7ff; border-left: 3px solid #3498db; border-radius: 4px;'>\n"
enhancement_section += f"<small>📌 <strong>来源：</strong>智源研究院 | <strong>相关性：</strong>{item['relevance']:.1%} | "
enhancement_section += f"<a href='{dataset_url}' target='_blank' style='color: #3498db; text-decoration: none;'>🔗 查看详情</a></small>\n"
enhancement_section += f"</div>\n\n"
elif item["type"] == "model":
enhancement_section += f"### 🤖 相关AI模型\n\n"
model_url = item.get('url', '#')
enhancement_section += f"**[{item['name']}]({model_url})**\n\n"
enhancement_section += f"{item['description']}\n\n"
enhancement_section += f"<div style='margin-top: 8px; padding: 8px; background: #f0f7ff; border-left: 3px solid #3498db; border-radius: 4px;'>\n"
enhancement_section += f"<small>📌 <strong>来源：</strong>智源研究院 | <strong>相关性：</strong>{item['relevance']:.1%} | "
enhancement_section += f"<a href='{model_url}' target='_blank' style='color: #3498db; text-decoration: none;'>🔗 查看详情</a></small>\n"
enhancement_section += f"</div>\n\n"
enhancement_section += "### 🔗 更多资源\n"
enhancement_section += "- [智源研究院官网](https://zhiyuan.com)\n"
enhancement_section += "- [Rust研究专题](https://zhiyuan.com/rust-research)\n"
enhancement_section += "- [开源项目](https://github.com/zhiyuan-ai)\n"
return original_answer + enhancement_section
def get_knowledge_statistics(self) -> Dict:
"""获取知识库统计信息"""
try:
knowledge_base = self._get_rust_knowledge_base()
return {
"papers_count": len(knowledge_base["papers"]),
"datasets_count": len(knowledge_base["datasets"]),
"models_count": len(knowledge_base["models"]),
"news_count": len(knowledge_base["news"]),
"last_updated": datetime.now().isoformat(),
"cache_size": self._get_cache_size()
}
except Exception as e:
return {"error": str(e)}
def _get_cache_size(self) -> str:
"""获取缓存大小"""
try:
total_size = 0
for filename in os.listdir(self.cache_dir):
filepath = os.path.join(self.cache_dir, filename)
if os.path.isfile(filepath):
total_size += os.path.getsize(filepath)
if total_size < 1024:
return f"{total_size} B"
elif total_size < 1024 * 1024:
return f"{total_size / 1024:.1f} KB"
else:
return f"{total_size / (1024 * 1024):.1f} MB"
except:
return "未知"
# 创建全局实例
zhiyuan_enhancer = ZhiyuanKnowledgeEnhancer()
|
2301_80743186/rust-agent-code
|
knowledge_enhancer.py
|
Python
|
unknown
| 20,017
|
#知识检索模块
import json
import os
class KnowledgeRetriever:
def __init__(self, kb_path='rust_knowledge_base/rust_docs_sample.json'):
self.kb_path = kb_path
if os.path.exists(self.kb_path):
with open(self.kb_path, 'r', encoding='utf-8') as f:
self.docs = json.load(f)
else:
self.docs = []
def retrieve(self, question, topk=3):
# 简单关键词匹配，返回相关文档
results = []
for doc in self.docs:
if any(word in doc['content'] for word in question.split()):
results.append(doc)
return results[:topk] if results else self.docs[:topk]
|
2301_80743186/rust-agent-code
|
knowledge_retriever.py
|
Python
|
unknown
| 684
|
#主模块import json
import os
from question_classifier import QuestionClassifier
from semantic_retriever import SemanticRetriever
from answer_generator import AnswerGenerator
from performance_timer import global_timer, StepTimer, APITimer
from multimodal_renderer import MultimodalRenderer
from context_manager import ContextManager
import json
class KnowledgeExplanationAgent:
def __init__(self):
self.classifier = QuestionClassifier()
self.retriever = SemanticRetriever()
self.generator = AnswerGenerator()
self.renderer = MultimodalRenderer()
self.context_manager = ContextManager()
def process_question(self, user_id, question, session_id=None, preferred_model=None):
"""处理用户问题的完整流程"""
try:
# M1: 问题分类
with StepTimer("问题分类"):
classification = self.classifier.classify(question)
global_timer.add_info("问题类型", classification['label'])
print(f"问题分类: {classification}")
# # M2: 语义检索（可选，当前知识库为空可跳过或返回空列表）
# retrieved_docs = [] # 暂不使用知识库
# M2: 语义检索
with StepTimer("语义检索"):
retrieved_docs = self.retriever.retrieve(question, classification['label'])
global_timer.add_info("检索结果数量", len(retrieved_docs))
# M5: 上下文管理
with StepTimer("获取上下文"):
context = self.context_manager.get_context(session_id or user_id)
# M3: 回答生成
with StepTimer("回答生成"):
answer_markdown = self.generator.generate(
question=question,
classification=classification,
retrieved_docs=retrieved_docs,
context=context,
preferred_model=preferred_model
)
# M4: 更新上下文（记录对话历史）
with StepTimer("更新上下文"):
self.context_manager.update_context(
session_id or user_id,
question,
answer_markdown,
classification
)
# 只返回Markdown内容，不做多模态HTML渲染
return {
'status': 'success',
'classification': classification,
'answer_markdown': answer_markdown
}
except Exception as e:
return {
'status': 'error',
'message': f'处理问题时出错: {str(e)}'
}
if __name__ == "__main__":
agent = KnowledgeExplanationAgent()
print("=== 知识解释智能体系统 ===")
print("支持的问题类型: definition, usage, error_debug, comparison, faq")
print("输入 'exit' 退出\n")
while True:
user_id = input("用户ID: ")
if user_id.lower() == 'exit':
break
question = input("问题: ")
if question.lower() == 'exit':
break
result = agent.process_question(user_id, question)
if result['status'] == 'success':
print(f"\n=== 处理结果 ===")
print(f"问题类型: {result['classification']['label']}")
print(f"置信度: {result['classification']['confidence']:.3f}")
print(f"\n=== 生成的回答 ===")
print(result['answer_markdown'])
else:
print(f"错误: {result['message']}")
print("\n" + "="*50 + "\n")
|
2301_80743186/rust-agent-code
|
main.py
|
Python
|
unknown
| 3,784
|
# 模型状态监控模块
import time
from typing import Dict, List
class ModelStatus:
def __init__(self):
self.status = {
'xinghe': {
'available': True,
'last_check': time.time(),
'error_count': 0,
'model': 'ernie-bot-turbo'
},
'openai': {
'available': True,
'last_check': time.time(),
'error_count': 0,
'model': 'gpt-3.5-turbo'
},
'deepseek': {
'available': True,
'last_check': time.time(),
'error_count': 0,
'model': 'deepseek-chat'
},
'fallback': {
'available': True,
'last_check': time.time(),
'error_count': 0,
'model': 'local-fallback'
}
}
self.current_model = 'xinghe'
def update_status(self, model: str, success: bool, error_message: str = None):
"""更新模型状态"""
if model in self.status:
self.status[model]['last_check'] = time.time()
if success:
self.status[model]['available'] = True
self.status[model]['error_count'] = 0
else:
self.status[model]['error_count'] += 1
if self.status[model]['error_count'] >= 3:
self.status[model]['available'] = False
def get_available_models(self) -> List[str]:
"""获取可用的模型列表"""
return [model for model, info in self.status.items() if info['available']]
def get_current_model(self) -> str:
"""获取当前使用的模型"""
return self.current_model
def switch_model(self, model: str):
"""切换模型"""
if model in self.status and self.status[model]['available']:
self.current_model = model
return True
return False
def get_status_summary(self) -> Dict:
"""获取状态摘要"""
return {
'current_model': self.current_model,
'available_models': self.get_available_models(),
'status': self.status
}
def reset_status(self):
"""重置所有模型状态"""
for model in self.status:
self.status[model]['available'] = True
self.status[model]['error_count'] = 0
self.status[model]['last_check'] = time.time()
self.current_model = 'xinghe'
# 全局状态实例
model_status = ModelStatus()
|
2301_80743186/rust-agent-code
|
model_status.py
|
Python
|
unknown
| 2,628
|
# 多模态增强器
import re
import json
from typing import Dict, List, Any, Optional
class MultimodalEnhancer:
def __init__(self):
self.mermaid_counter = 0
def _normalize_markdown_codeblock(self, text: str) -> str:
"""还原被转义的markdown代码块前缀"""
import re
# 先还原mermaid和rust等带语言的
text = re.sub(r'\\+`{3}\s*mermaid', '```mermaid', text)
text = re.sub(r'\\+`{3}\s*rust', '```rust', text)
# 再还原普通代码块
text = re.sub(r'\\+`{3}', '```', text)
return text
def enhance_content(self, content: str) -> Dict[str, Any]:
"""增强内容，提取多模态元素"""
# 先去除markdown代码块前缀的多余转义
content = self._normalize_markdown_codeblock(content)
enhanced = {
'text_content': content,
'code_blocks': [],
'mermaid_diagrams': [],
'tables': [],
'images': [],
'enhanced_html': content
}
# 提取代码块
enhanced['code_blocks'] = self._extract_code_blocks(content)
# 提取Mermaid图表
enhanced['mermaid_diagrams'] = self._extract_mermaid_diagrams(content)
# 提取表格
enhanced['tables'] = self._extract_tables(content)
# 生成增强的HTML
enhanced['enhanced_html'] = self._generate_enhanced_html(content, enhanced)
return enhanced
def _extract_code_blocks(self, content: str) -> List[Dict[str, str]]:
"""提取代码块"""
code_blocks = []
pattern = r'```(\w+)?\n(.*?)```'
matches = re.finditer(pattern, content, re.DOTALL)
for match in matches:
language = match.group(1) or 'text'
code = match.group(2).strip()
code_blocks.append({
'language': language,
'code': code,
'id': f'code-{len(code_blocks)}'
})
return code_blocks
def _extract_mermaid_diagrams(self, content: str) -> List[Dict[str, str]]:
"""提取Mermaid图表"""
mermaid_diagrams = []
pattern = r'```mermaid\s*\n(.*?)```'
matches = re.finditer(pattern, content, re.DOTALL)
for match in matches:
diagram_code = match.group(1).strip()
self.mermaid_counter += 1
mermaid_diagrams.append({
'id': f'mermaid-{self.mermaid_counter}',
'code': diagram_code,
'type': self._detect_mermaid_type(diagram_code)
})
return mermaid_diagrams
def _detect_mermaid_type(self, diagram_code: str) -> str:
"""检测Mermaid图表类型"""
if 'graph' in diagram_code or 'flowchart' in diagram_code:
return 'flowchart'
elif 'sequenceDiagram' in diagram_code:
return 'sequence'
elif 'classDiagram' in diagram_code:
return 'class'
elif 'stateDiagram' in diagram_code:
return 'state'
elif 'gantt' in diagram_code:
return 'gantt'
elif 'pie' in diagram_code:
return 'pie'
else:
return 'unknown'
def _extract_tables(self, content: str) -> List[Dict[str, Any]]:
"""提取Markdown表格"""
tables = []
pattern = r'\|.*\|\n\|[\s\-:|]+\|\n(\|.*\|\n)*'
matches = re.finditer(pattern, content)
for match in matches:
table_text = match.group(0)
table_data = self._parse_markdown_table(table_text)
tables.append({
'id': f'table-{len(tables)}',
'data': table_data,
'html': self._table_to_html(table_data)
})
return tables
def _parse_markdown_table(self, table_text: str) -> List[List[str]]:
"""解析Markdown表格"""
lines = table_text.strip().split('\n')
table_data = []
for line in lines:
if line.startswith('|') and line.endswith('|'):
# 移除首尾的|并分割
cells = [cell.strip() for cell in line[1:-1].split('|')]
table_data.append(cells)
return table_data
def _table_to_html(self, table_data: List[List[str]]) -> str:
"""将表格数据转换为HTML"""
if not table_data:
return ""
html = '<table class="enhanced-table">\n'
for i, row in enumerate(table_data):
if i == 0:
html += ' <thead>\n <tr>\n'
for cell in row:
html += f' <th>{cell}</th>\n'
html += ' </tr>\n </thead>\n <tbody>\n'
else:
html += ' <tr>\n'
for cell in row:
html += f' <td>{cell}</td>\n'
html += ' </tr>\n'
html += ' </tbody>\n</table>'
return html
def _generate_enhanced_html(self, content: str, enhanced: Dict[str, Any]) -> str:
"""生成增强的HTML内容（美化代码块和mermaid图表，并分块分段，p标签仅包裹纯文本）"""
html_content = content
# 1. 标题美化
html_content = re.sub(r'^### (.*)$', r'<h3 style="margin: 18px 0 8px 0; font-size: 1.1em; color: #2d3748;">\1</h3>', html_content, flags=re.MULTILINE)
html_content = re.sub(r'^## (.*)$', r'<h2 style="margin: 28px 0 12px 0; font-size: 1.3em; color: #2563eb;">\1</h2>', html_content, flags=re.MULTILINE)
html_content = re.sub(r'^# (.*)$', r'<h1 style="margin: 36px 0 16px 0; font-size: 1.6em; color: #1a202c;">\1</h1>', html_content, flags=re.MULTILINE)
# 2. Mermaid图表
def mermaid_repl(match):
code = match.group(1).strip()
return (
'<div class="mermaid-container" style="margin: 24px 0;">\n'
' <div class="mermaid-header" style="padding: 8px 16px; background: #f0fdf4; border-bottom: 1px solid #c6f6d5;">\n'
' <span class="diagram-type" style="color: #38a169; font-weight: bold;">关系图</span>\n'
' </div>\n'
' <div class="mermaid-content" style="padding: 18px; background: #f9fafb; text-align: center;">\n'
f' <div class="mermaid">{self._escape_html(code)}</div>\n'
' </div>\n'
'</div>'
)
html_content = re.sub(r'```mermaid\s*\n([\s\S]*?)\n```', mermaid_repl, html_content, flags=re.DOTALL)
# 3. 代码块
def code_repl(match):
lang = match.group(1) or 'text'
code = match.group(2).strip()
return (
'<div class="code-block" style="margin: 24px 0;">\n'
' <div class="code-header" style="display: flex; align-items: center; justify-content: space-between; background: #f7fafc; padding: 8px 16px; border-bottom: 1px solid #e2e8f0;">\n'
f' <span class="language-tag" style="color: #3182ce; font-weight: bold;">{lang}</span>\n'
' <button class="copy-btn" style="background: #edf2f7; border: none; border-radius: 4px; padding: 2px 10px; cursor: pointer;">复制</button>\n'
' </div>\n'
' <pre style="margin: 0; background: #f9fafb;"><code class="language-' + lang + '">' + self._escape_html(code) + '</code></pre>\n'
'</div>'
)
html_content = re.sub(r'```(\w+)?\s*\n([\s\S]*?)\n```', code_repl, html_content, flags=re.DOTALL)
# 4. 列表美化
html_content = re.sub(r'^\s*[-\*] (.*)$', r'<ul><li>\1</li></ul>', html_content, flags=re.MULTILINE)
html_content = re.sub(r'^\s*\d+\. (.*)$', r'<ol><li>\1</li></ol>', html_content, flags=re.MULTILINE)
html_content = re.sub(r'(</ul>)\s*<ul>', '', html_content) # 合并相邻ul
html_content = re.sub(r'(</ol>)\s*<ol>', '', html_content)
# 5. 表格美化（简单处理）
html_content = re.sub(r'^\|(.+?)\|$', r'<div class="table-block">|\1|</div>', html_content, flags=re.MULTILINE)
# 6. 只对纯文本行用<p>包裹
lines = html_content.split('\n')
new_lines = []
for line in lines:
lstr = line.strip()
if not lstr:
continue
# 只包裹非HTML标签开头和结尾的纯文本
if not (lstr.startswith('<') and lstr.endswith('>')):
new_lines.append(f'<p>{lstr}</p>')
else:
new_lines.append(line)
html_content = '\n'.join(new_lines)
return html_content
def _escape_html(self, text: str) -> str:
"""转义HTML特殊字符"""
return text.replace('&', '&').replace('<', '<').replace('>', '>').replace('"', '"').replace("'", ''')
def generate_css_styles(self) -> str:
"""生成增强样式"""
return """
/* 多模态增强样式 */
.enhanced-table {
width: 100%;
border-collapse: collapse;
margin: 15px 0;
background: white;
border-radius: 8px;
overflow: hidden;
box-shadow: 0 2px 8px rgba(0,0,0,0.1);
}
.enhanced-table th,
.enhanced-table td {
padding: 12px 15px;
text-align: left;
border-bottom: 1px solid #eee;
}
.enhanced-table th {
background: #f8f9fa;
font-weight: 600;
color: #2c3e50;
}
.enhanced-table tr:hover {
background: #f8f9fa;
}
.code-block {
margin: 15px 0;
border-radius: 8px;
overflow: hidden;
box-shadow: 0 2px 8px rgba(0,0,0,0.1);
}
.code-header {
display: flex;
justify-content: space-between;
align-items: center;
padding: 8px 15px;
background: #2d3748;
color: white;
}
.language-tag {
font-size: 0.9rem;
font-weight: 500;
}
.copy-btn {
background: #4a5568;
color: white;
border: none;
padding: 4px 8px;
border-radius: 4px;
font-size: 0.8rem;
cursor: pointer;
transition: background 0.2s;
}
.copy-btn:hover {
background: #718096;
}
.code-block pre {
margin: 0;
padding: 15px;
background: #2d3748;
color: #e2e8f0;
overflow-x: auto;
}
.mermaid-container {
margin: 20px 0;
border: 1px solid #e2e8f0;
border-radius: 8px;
overflow: hidden;
background: white;
}
.mermaid-header {
padding: 10px 15px;
background: #f7fafc;
border-bottom: 1px solid #e2e8f0;
}
.diagram-type {
font-size: 0.9rem;
font-weight: 500;
color: #4a5568;
}
.mermaid-content {
padding: 20px;
text-align: center;
}
/* 响应式设计 */
@media (max-width: 768px) {
.enhanced-table {
font-size: 0.9rem;
}
.enhanced-table th,
.enhanced-table td {
padding: 8px 10px;
}
.code-block pre {
padding: 10px;
font-size: 0.85rem;
}
}
"""
def generate_js_functions(self) -> str:
"""生成JavaScript函数"""
return """
// 复制代码功能
function copyCode(codeId) {
const codeBlock = document.getElementById(codeId);
const code = codeBlock.querySelector('code').textContent;
navigator.clipboard.writeText(code).then(() => {
const btn = codeBlock.querySelector('.copy-btn');
const originalText = btn.textContent;
btn.textContent = '已复制!';
btn.style.background = '#48bb78';
setTimeout(() => {
btn.textContent = originalText;
btn.style.background = '#4a5568';
}, 2000);
}).catch(err => {
console.error('复制失败:', err);
alert('复制失败，请手动复制');
});
}
// 初始化Mermaid图表
function initMermaid() {
if (typeof mermaid !== 'undefined') {
mermaid.initialize({
startOnLoad: true,
theme: 'default',
flowchart: {
useMaxWidth: true,
htmlLabels: true
}
});
}
}
// 页面加载完成后初始化
document.addEventListener('DOMContentLoaded', function() {
initMermaid();
});
"""
# 创建全局实例
multimodal_enhancer = MultimodalEnhancer()
|
2301_80743186/rust-agent-code
|
multimodal_enhancer.py
|
Python
|
unknown
| 12,323
|
#多模态渲染模块
import re
from typing import Dict, List
class MultimodalRenderer:
def __init__(self):
self.css_styles = self._get_css_styles()
def render(self, markdown_content: str) -> str:
"""将Markdown内容渲染为HTML"""
html = self._markdown_to_html(markdown_content)
return self._wrap_with_template(html)
def _markdown_to_html(self, markdown: str) -> str:
"""Markdown转HTML的核心逻辑"""
html = markdown
# 处理标题
html = re.sub(r'^### (.*$)', r'<h3>\1</h3>', html, flags=re.MULTILINE)
html = re.sub(r'^## (.*$)', r'<h2>\1</h2>', html, flags=re.MULTILINE)
html = re.sub(r'^# (.*$)', r'<h1>\1</h1>', html, flags=re.MULTILINE)
# 处理粗体
html = re.sub(r'\*\*(.*?)\*\*', r'<strong>\1</strong>', html)
# 处理斜体
html = re.sub(r'\*(.*?)\*', r'<em>\1</em>', html)
# 处理代码块
html = re.sub(
r'```rust\n(.*?)\n```',
r'<pre class="code-block rust"><code>\1</code></pre>',
html,
flags=re.DOTALL
)
html = re.sub(
r'```(.*?)\n(.*?)\n```',
r'<pre class="code-block \1"><code>\2</code></pre>',
html,
flags=re.DOTALL
)
# 处理行内代码
html = re.sub(r'`(.*?)`', r'<code class="inline-code">\1</code>', html)
# 处理列表
html = re.sub(r'^\d+\. (.*$)', r'<li>\1</li>', html, flags=re.MULTILINE)
html = re.sub(r'^- (.*$)', r'<li>\1</li>', html, flags=re.MULTILINE)
# 处理段落
html = re.sub(r'\n\n([^<].*?)\n\n', r'<p>\1</p>', html, flags=re.DOTALL)
# 处理Mermaid图表
html = re.sub(
r'```mermaid\n(.*?)\n```',
r'<div class="mermaid">\1</div>',
html,
flags=re.DOTALL
)
# 处理换行
html = html.replace('\n', '<br>')
return html
def _wrap_with_template(self, content: str) -> str:
"""包装HTML模板"""
return f"""
<!DOCTYPE html>
<html lang="zh-CN">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Rust知识解释</title>
<script src="https://cdn.jsdelivr.net/npm/mermaid/dist/mermaid.min.js"></script>
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/prism/1.29.0/themes/prism.min.css">
<script src="https://cdnjs.cloudflare.com/ajax/libs/prism/1.29.0/components/prism-core.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/prism/1.29.0/plugins/autoloader/prism-autoloader.min.js"></script>
<style>
{self.css_styles}
</style>
</head>
<body>
<div class="container">
<div class="content">
{content}
</div>
</div>
<script>
mermaid.initialize({{ startOnLoad: true }});
Prism.highlightAll();
</script>
</body>
</html>
"""
def _get_css_styles(self) -> str:
"""获取CSS样式"""
return """
body {
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
line-height: 1.6;
color: #333;
max-width: 800px;
margin: 0 auto;
padding: 20px;
background-color: #f8f9fa;
}
.container {
background: white;
border-radius: 8px;
box-shadow: 0 2px 10px rgba(0,0,0,0.1);
overflow: hidden;
}
.content {
padding: 30px;
}
h1, h2, h3 {
color: #2c3e50;
margin-top: 30px;
margin-bottom: 15px;
}
h1 {
font-size: 2em;
border-bottom: 3px solid #3498db;
padding-bottom: 10px;
}
h2 {
font-size: 1.5em;
border-bottom: 2px solid #ecf0f1;
padding-bottom: 8px;
}
h3 {
font-size: 1.2em;
color: #34495e;
}
p {
margin-bottom: 15px;
text-align: justify;
}
.code-block {
background: #f8f9fa;
border: 1px solid #e9ecef;
border-radius: 6px;
padding: 15px;
margin: 15px 0;
overflow-x: auto;
font-family: 'Fira Code', 'Monaco', 'Consolas', monospace;
font-size: 14px;
line-height: 1.4;
}
.inline-code {
background: #f1f3f4;
padding: 2px 6px;
border-radius: 4px;
font-family: 'Fira Code', monospace;
font-size: 0.9em;
color: #d73a49;
}
.mermaid {
text-align: center;
margin: 20px 0;
padding: 20px;
background: #f8f9fa;
border-radius: 6px;
}
li {
margin-bottom: 8px;
}
strong {
color: #2c3e50;
font-weight: 600;
}
em {
color: #7f8c8d;
font-style: italic;
}
@media (max-width: 768px) {
body {
padding: 10px;
}
.content {
padding: 20px;
}
h1 {
font-size: 1.5em;
}
h2 {
font-size: 1.3em;
}
}
"""
def save_html(self, markdown_content: str, file_path: str):
"""保存渲染后的HTML到文件"""
html_content = self.render(markdown_content)
with open(file_path, 'w', encoding='utf-8') as f:
f.write(html_content)
|
2301_80743186/rust-agent-code
|
multimodal_renderer.py
|
Python
|
unknown
| 6,008
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
性能分析工具 - 用于测量 SemanticRetriever 的各个操作耗时
"""
import time
import json
import numpy as np
from semantic_retriever import SemanticRetriever
def measure_time(func, *args, **kwargs):
"""
测量函数执行时间
Args:
func: 要执行的函数
*args: 函数参数
**kwargs: 函数关键字参数
Returns:
tuple: (函数返回值, 执行时间(毫秒))
"""
start_time = time.time()
result = func(*args, **kwargs)
end_time = time.time()
elapsed_time = (end_time - start_time) * 1000 # 转换为毫秒
return result, elapsed_time
def run_performance_analysis():
"""
运行完整的性能分析测试
"""
print("=" * 80)
print("SemanticRetriever 性能分析工具")
print("此工具用于测量各个关键操作的耗时，帮助优化性能")
print("=" * 80)
# 测试配置
config = {
'kb_path': 'rust_knowledge_base/rust_docs_sample.json',
'test_questions': [
"什么是所有权？",
"如何处理借用检查器错误？",
"Rust和C++的主要区别是什么？",
"生命周期参数的作用是什么？",
"如何声明可变变量？"
],
'top_k_values': [1, 3, 5],
'iterations': 3 # 每个操作执行的次数，取平均值
}
print(f"测试配置: {json.dumps(config, ensure_ascii=False, indent=2)}")
print("\n开始性能测试...\n")
# 1. 初始化时间
print("[测试1] 初始化时间测量")
retriever, init_time = measure_time(SemanticRetriever, config['kb_path'])
print(f"初始化完成，耗时: {init_time:.2f} ms")
# 2. 资源加载时间（确保加载所有资源）
print("\n[测试2] 资源加载时间测量")
_, resource_load_time = measure_time(retriever._ensure_resources_loaded)
print(f"资源加载完成，耗时: {resource_load_time:.2f} ms")
# 3. 知识库大小
print(f"\n知识库信息: {len(retriever.knowledge_base)} 条记录")
if hasattr(retriever, 'index') and retriever.index is not None:
print(f"FAISS索引维度: {retriever.index.d}")
# 4. 分词性能测试
print("\n[测试3] 分词性能测试")
test_texts = [
"Rust是一种系统编程语言，注重安全性、并发和内存效率。",
"The borrow checker ensures memory safety without garbage collection.",
"可变变量可以通过mut关键字声明。mutable variables can be declared with mut keyword."
]
tokenize_times = []
for text in test_texts:
_, tokenize_time = measure_time(retriever._tokenize_text, text)
tokens = retriever._tokenize_text(text)
tokenize_times.append(tokenize_time)
print(f"文本: {text[:30]}... | 分词数: {len(tokens)} | 耗时: {tokenize_time:.2f} ms")
print(f"平均分词时间: {np.mean(tokenize_times):.2f} ms")
# 5. 嵌入向量生成性能
print("\n[测试4] 嵌入向量生成性能")
embedding_times = []
for text in test_texts:
_, embed_time = measure_time(retriever._get_embedding, text)
embedding_times.append(embed_time)
print(f"文本: {text[:30]}... | 耗时: {embed_time:.2f} ms")
print(f"平均嵌入时间: {np.mean(embedding_times):.2f} ms")
# 6. 检索性能测试
print("\n[测试5] 检索性能测试")
retrieval_results = {}
for question in config['test_questions']:
question_results = {}
for top_k in config['top_k_values']:
iteration_times = []
iteration_results = []
for i in range(config['iterations']):
results, retrieve_time = measure_time(
retriever.retrieve,
question=question,
top_k=top_k,
debug=False
)
iteration_times.append(retrieve_time)
iteration_results.append(len(results))
avg_time = np.mean(iteration_times)
question_results[top_k] = {
'avg_time': avg_time,
'min_time': np.min(iteration_times),
'max_time': np.max(iteration_times),
'avg_results': np.mean(iteration_results)
}
print(f"问题: '{question}' | top_k={top_k} | 平均时间: {avg_time:.2f} ms | \\n" +
f" 最小值: {np.min(iteration_times):.2f} ms | 最大值: {np.max(iteration_times):.2f} ms | 平均结果数: {np.mean(iteration_results):.1f}")
retrieval_results[question] = question_results
# 7. 缓存效率测试
print("\n[测试6] 缓存效率测试")
# 清除缓存
if hasattr(retriever, 'token_cache'):
retriever.token_cache.clear()
if hasattr(retriever, 'embedding_cache'):
retriever.embedding_cache.clear()
# 第一次执行
first_time = []
for question in config['test_questions'][:2]: # 只测试前两个问题
_, time1 = measure_time(retriever.retrieve, question=question, top_k=3)
first_time.append(time1)
avg_first_time = np.mean(first_time)
# 第二次执行（应该使用缓存）
second_time = []
for question in config['test_questions'][:2]:
_, time2 = measure_time(retriever.retrieve, question=question, top_k=3)
second_time.append(time2)
avg_second_time = np.mean(second_time)
cache_improvement = (1 - avg_second_time / avg_first_time) * 100 if avg_first_time > 0 else 0
print(f"第一次检索平均时间: {avg_first_time:.2f} ms")
print(f"第二次检索平均时间: {avg_second_time:.2f} ms")
print(f"缓存带来的性能提升: {cache_improvement:.1f}%")
# 8. 缓存大小统计
if hasattr(retriever, 'token_cache'):
print(f"分词缓存大小: {len(retriever.token_cache)} 条")
if hasattr(retriever, 'embedding_cache'):
print(f"嵌入向量缓存大小: {len(retriever.embedding_cache)} 条")
# 生成综合报告
print("\n" + "=" * 80)
print("综合性能报告")
print("=" * 80)
report = {
'init_time_ms': init_time,
'resource_load_time_ms': resource_load_time,
'avg_tokenize_time_ms': np.mean(tokenize_times),
'avg_embedding_time_ms': np.mean(embedding_times),
'cache_improvement_percent': cache_improvement,
'retrieval_performance': retrieval_results
}
print(json.dumps(report, ensure_ascii=False, indent=2))
# 保存报告到文件
timestamp = time.strftime("%Y%m%d_%H%M%S")
report_file = f"performance_report_{timestamp}.json"
try:
with open(report_file, 'w', encoding='utf-8') as f:
json.dump(report, f, ensure_ascii=False, indent=2)
print(f"\n报告已保存到: {report_file}")
except Exception as e:
print(f"\n警告: 保存报告失败: {str(e)}")
print("\n性能分析完成！")
print("建议在代码修改前后各运行一次，比较性能差异。")
if __name__ == "__main__":
run_performance_analysis()
|
2301_80743186/rust-agent-code
|
performance_analyzer.py
|
Python
|
unknown
| 7,284
|
import time
import json
import os
from datetime import datetime
from contextlib import contextmanager
class PerformanceTimer:
"""
性能计时器，用于记录各个环节的执行时间
"""
def __init__(self):
self.reset()
def reset(self):
"""重置所有计时数据"""
self.start_time = time.time()
self.steps = {}
self.api_calls = {}
self.info = {}
self.question = ""
self.answer = ""
def start_step(self, step_name):
"""开始记录一个步骤的时间"""
self.steps[step_name] = {
'start': time.time(),
'end': None,
'duration': None
}
def end_step(self, step_name):
"""结束记录一个步骤的时间"""
if step_name in self.steps:
self.steps[step_name]['end'] = time.time()
self.steps[step_name]['duration'] = self.steps[step_name]['end'] - self.steps[step_name]['start']
def start_api_call(self, api_name):
"""开始记录一个API调用的时间"""
self.api_calls[api_name] = {
'start': time.time(),
'end': None,
'duration': None
}
def end_api_call(self, api_name):
"""结束记录一个API调用的时间"""
if api_name in self.api_calls:
self.api_calls[api_name]['end'] = time.time()
self.api_calls[api_name]['duration'] = self.api_calls[api_name]['end'] - self.api_calls[api_name]['start']
def add_info(self, key, value):
"""添加额外信息"""
self.info[key] = value
def get_total_time(self):
"""获取总执行时间"""
return time.time() - self.start_time
def print_summary(self):
"""打印性能摘要"""
print("\n===== 性能报告 =====")
print(f"总执行时间: {self.get_total_time():.2f} 秒")
print("\n步骤执行时间:")
for step_name, step_data in sorted(self.steps.items(), key=lambda x: x[1]['duration'] or 0, reverse=True):
duration = step_data['duration'] or 0
percentage = (duration / self.get_total_time()) * 100 if self.get_total_time() > 0 else 0
print(f" {step_name}: {duration:.2f} 秒 ({percentage:.1f}%)")
print("\nAPI调用时间:")
for api_name, api_data in sorted(self.api_calls.items(), key=lambda x: x[1]['duration'] or 0, reverse=True):
duration = api_data['duration'] or 0
percentage = (duration / self.get_total_time()) * 100 if self.get_total_time() > 0 else 0
print(f" {api_name}: {duration:.2f} 秒 ({percentage:.1f}%)")
if self.info:
print("\n额外信息:")
for key, value in self.info.items():
print(f" {key}: {value}")
print("====================\n")
def save_report(self, question, answer):
"""保存性能报告到文件"""
self.question = question
self.answer = answer
# 创建报告目录
report_dir = "performance_reports"
if not os.path.exists(report_dir):
os.makedirs(report_dir)
# 生成报告文件名
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S_%f")[:-3]
filename = os.path.join(report_dir, f"report_{timestamp}.json")
# 准备报告数据
report_data = {
'timestamp': datetime.now().isoformat(),
'total_time': self.get_total_time(),
'steps': {k: {'duration': v['duration']} for k, v in self.steps.items() if v['duration'] is not None},
'api_calls': {k: {'duration': v['duration']} for k, v in self.api_calls.items() if v['duration'] is not None},
'info': self.info,
'question': question,
'answer_preview': answer[:200] + "..." if len(answer) > 200 else answer
}
# 保存报告
with open(filename, 'w', encoding='utf-8') as f:
json.dump(report_data, f, ensure_ascii=False, indent=2)
print(f"性能报告已保存到: {filename}")
class StepTimer:
"""
步骤计时器上下文管理器
"""
def __init__(self, step_name):
self.step_name = step_name
def __enter__(self):
global_timer.start_step(self.step_name)
return self
def __exit__(self, exc_type, exc_val, exc_tb):
global_timer.end_step(self.step_name)
return False
class APITimer:
"""
API调用计时器上下文管理器
"""
def __init__(self, api_name):
self.api_name = api_name
def __enter__(self):
global_timer.start_api_call(self.api_name)
return self
def __exit__(self, exc_type, exc_val, exc_tb):
global_timer.end_api_call(self.api_name)
return False
# 创建全局计时器实例
global_timer = PerformanceTimer()
|
2301_80743186/rust-agent-code
|
performance_timer.py
|
Python
|
unknown
| 4,983
|
#个性化模块
class Personalization:
def __init__(self):
# 假设有简单的用户画像数据
self.user_profiles = {
'1001': {'level': 'beginner', 'name': '小明'},
'1002': {'level': 'advanced', 'name': '小红'},
}
def get_user_profile(self, user_id):
# 默认初学者
return self.user_profiles.get(user_id, {'level': 'beginner', 'name': '未知'})
|
2301_80743186/rust-agent-code
|
personalization.py
|
Python
|
unknown
| 430
|
# 提示词模板系统
from typing import Dict, List, Any
import json
class PromptTemplateSystem:
def __init__(self):
self.templates = self._initialize_templates()
def _initialize_templates(self) -> Dict[str, Dict[str, str]]:
"""初始化所有提示词模板"""
return {
"definition": {
"system": """你是一个专业的Rust编程知识解释智能体，专门负责概念定义类问题的回答。
你的回答必须严格按照以下层次结构输出：
# 📚 概念定义
**核心定义**：简洁明了的定义
**重要特征**：列出3-5个关键特征
## 🎯 核心要点
- **要点1**：详细说明
- **要点2**：详细说明
- **要点3**：详细说明
## 💻 示例代码
\`\`\`rust
// 完整可运行的示例代码
\`\`\`
## 🔄 概念关系图
\`\`\`mermaid
// 展示概念间关系的流程图
\`\`\`
## 🔗 相关概念
- **概念1**：简要说明
- **概念2**：简要说明
- **概念3**：简要说明
## 📖 学习建议
1. **第一步**：建议
2. **第二步**：建议
3. **第三步**：建议
---
## 📝 代码练习
请根据下述用户问题，生成2个与该问题紧密相关的简单Rust编程题，题目要具体、可操作，适合初学者练习，且必须与用户问题高度相关，不要泛泛而谈。
- 练习1：
- 练习2：
## 🏆 综合案例
请根据下述用户问题，生成1个与该问题紧密相关的综合项目案例，需包含：
- 案例要求：简明描述项目目标和功能需求，必须与用户问题高度相关
- 实现步骤：详细列出实现该项目的主要步骤，步骤要清晰、可操作
用户问题：{question}
要求：
- 使用中文回答
- 严格按照上述层次结构输出
- 每个层次都要有明确的标题和图标
- 代码块使用```rust标记
- 图表使用mermaid语法
- 确保所有内容都在界面范围内显示""",
"user": """请为以下Rust概念提供详细解释：
**问题**：{question}
**相关知识点**：
{knowledge_info}
**对话历史**：
{context_info}
请生成包含文字解释、代码示例和图示的完整回答。"""
},
"usage": {
"system": """你是一个专业的Rust编程知识解释智能体，专门负责用法说明类问题的回答。
你的回答必须严格按照以下层次结构输出：
# 🚀 基本用法
**语法说明**：核心语法和用法
**使用场景**：适用的情况和条件
## 📝 语法详解
- **语法点1**：详细说明
- **语法点2**：详细说明
- **语法点3**：详细说明
## 💻 代码示例
\`\`\`rust
// 完整可运行的示例代码
\`\`\`
## ⚙️ 参数说明
| 参数 | 类型 | 说明 | 示例 |
|------|------|------|------|
| 参数1 | 类型1 | 说明1 | 示例1 |
| 参数2 | 类型2 | 说明2 | 示例2 |
## 🔄 使用流程图
\`\`\`mermaid
// 展示使用步骤的流程图
\`\`\`
## 💡 最佳实践
1. **实践1**：详细建议
2. **实践2**：详细建议
3. **实践3**：详细建议
## 🎯 常见用法
- **用法1**：典型应用场景
- **用法2**：典型应用场景
- **用法3**：典型应用场景
要求：
- 使用中文回答
- 严格按照上述层次结构输出
- 每个层次都要有明确的标题和图标
- 代码块使用```rust标记
- 图表使用mermaid语法
- 确保所有内容都在界面范围内显示""",
"user": """请为以下Rust用法问题提供详细说明：
**问题**：{question}
**相关知识点**：
{knowledge_info}
**对话历史**：
{context_info}
请生成包含文字解释、代码示例和图示的完整回答。"""
},
"error_debug": {
"system": """你是一个专业的Rust编程知识解释智能体，专门负责错误调试类问题的回答。
你的回答必须严格按照以下层次结构输出：
# 🚨 错误分析
**错误类型**：具体的错误类型
**错误原因**：详细的原因分析
## 🔍 错误详情
- **错误信息**：完整的错误信息
- **错误位置**：错误发生的具体位置
- **错误影响**：错误可能造成的影响
## ❌ 错误代码示例
\`\`\`rust
// 导致错误的代码
\`\`\`
## ✅ 正确解决方案
\`\`\`rust
// 修复后的正确代码
\`\`\`
## 🔄 修复流程图
\`\`\`mermaid
// 展示错误修复步骤的流程图
\`\`\`
## 🛡️ 预防措施
1. **预防1**：具体的预防方法
2. **预防2**：具体的预防方法
3. **预防3**：具体的预防方法
## 🔧 调试技巧
- **技巧1**：调试方法和工具
- **技巧2**：调试方法和工具
- **技巧3**：调试方法和工具
## 📚 相关资源
- **文档链接**：相关官方文档
- **工具推荐**：调试工具推荐
- **学习资源**：深入学习资源
要求：
- 使用中文回答
- 严格按照上述层次结构输出
- 每个层次都要有明确的标题和图标
- 代码块使用```rust标记
- 图表使用mermaid语法
- 确保所有内容都在界面范围内显示""",
"user": """请为以下Rust错误调试问题提供详细解决方案：
**问题**：{question}
**相关知识点**：
{knowledge_info}
**对话历史**：
{context_info}
请生成包含文字解释、代码示例和图示的完整回答。"""
},
"comparison": {
"system": """你是一个专业的Rust编程知识解释智能体，专门负责概念对比类问题的回答。
你的回答必须严格按照以下层次结构输出：
# ⚖️ 对比概述
**对比对象**：明确要对比的概念或技术
**对比维度**：从哪些角度进行对比
## 📊 对比维度
- **维度1**：性能对比
- **维度2**：安全性对比
- **维度3**：易用性对比
- **维度4**：适用场景对比
## 🔍 详细差异分析
| 特性 | 选项A | 选项B | 说明 |
|------|-------|-------|------|
| 特性1 | 表现1 | 表现2 | 差异说明 |
| 特性2 | 表现1 | 表现2 | 差异说明 |
| 特性3 | 表现1 | 表现2 | 差异说明 |
## 💻 代码对比示例
### 选项A的实现
\`\`\`rust
// 选项A的代码示例
\`\`\`
### 选项B的实现
\`\`\`rust
// 选项B的代码示例
\`\`\`
## 🔄 对比关系图
\`\`\`mermaid
// 展示对比关系的图表
\`\`\`
## 🎯 适用场景
### 选择选项A的场景
- **场景1**：具体说明
- **场景2**：具体说明
- **场景3**：具体说明
### 选择选项B的场景
- **场景1**：具体说明
- **场景2**：具体说明
- **场景3**：具体说明
## 💡 选择建议
1. **建议1**：具体建议
2. **建议2**：具体建议
3. **建议3**：具体建议
## 📚 深入学习
- **资源1**：相关学习资源
- **资源2**：相关学习资源
- **资源3**：相关学习资源
要求：
- 使用中文回答
- 严格按照上述层次结构输出
- 每个层次都要有明确的标题和图标
- 代码块使用```rust标记
- 图表使用mermaid语法
- 确保所有内容都在界面范围内显示""",
"user": """请为以下Rust概念对比问题提供详细分析：
**问题**：{question}
**相关知识点**：
{knowledge_info}
**对话历史**：
{context_info}
请生成包含文字解释、代码示例和图示的完整回答。"""
},
"greeting": {
"system": """你是一个友好的Rust编程知识解释智能体，专门负责问候语类问题的回答。
你的回答必须简洁友好，包含以下内容：
# 👋 问候回应
**友好回应**：热情友好的问候回复
**服务介绍**：简要介绍你能提供的Rust学习帮助
## 🦀 Rust学习助手
**我能帮助你**：
- 解答Rust编程问题
- 解释Rust概念和语法
- 提供代码示例和最佳实践
- 协助调试和错误解决
## 💡 开始学习
**建议**：鼓励用户开始提问Rust相关问题
要求：
- 使用中文回答
- 保持友好和热情的语气
- 简洁明了，不要过于冗长
- 鼓励用户提问Rust相关问题""",
"user": """用户问候：{question}
请给出友好的回应，并简要介绍你能提供的Rust学习帮助。"""
},
"faq": {
"system": """你是一个专业的Rust编程知识解释智能体，专门负责常见问题类问题的回答。
你的回答必须严格按照以下层次结构输出：
# ❓ 问题解答
**直接回答**：简洁明了的答案
**核心要点**：回答的关键要点
## 📖 背景说明
**问题背景**：问题的产生背景和原因
**重要性**：为什么这个问题很重要
## 💡 详细解释
- **要点1**：详细说明
- **要点2**：详细说明
- **要点3**：详细说明
## 💻 实践示例
\`\`\`rust
// 相关的代码示例
\`\`\`
## 🔄 解决流程图
\`\`\`mermaid
// 展示问题解决步骤的流程图
\`\`\`
## 🎯 实践建议
1. **建议1**：具体的实践建议
2. **建议2**：具体的实践建议
3. **建议3**：具体的实践建议
## 📚 学习资源
| 资源类型 | 推荐内容 | 链接/说明 |
|----------|----------|-----------|
| 官方文档 | 相关文档 | 链接或说明 |
| 教程视频 | 推荐教程 | 链接或说明 |
| 实践项目 | 练习项目 | 链接或说明 |
## 🚀 扩展阅读
- **进阶主题1**：相关进阶内容
- **进阶主题2**：相关进阶内容
- **进阶主题3**：相关进阶内容
## 🔗 相关链接
- **链接1**：相关资源链接
- **链接2**：相关资源链接
- **链接3**：相关资源链接
要求：
- 使用中文回答
- 严格按照上述层次结构输出
- 每个层次都要有明确的标题和图标
- 代码块使用```rust标记
- 图表使用mermaid语法
- 确保所有内容都在界面范围内显示""",
"user": """请为以下Rust常见问题提供详细解答：
**问题**：{question}
**相关知识点**：
{knowledge_info}
**对话历史**：
{context_info}
请生成包含文字解释、代码示例和图示的完整回答。"""
}
}
def get_template(self, question_type: str) -> Dict[str, str]:
"""获取指定问题类型的提示词模板"""
return self.templates.get(question_type, self.templates["faq"])
def format_prompt(self, question_type: str, question: str, knowledge_info: str = "", context_info: str = "") -> Dict[str, str]:
"""格式化提示词模板"""
template = self.get_template(question_type)
formatted_user = template["user"].format(
question=question,
knowledge_info=knowledge_info or "未找到相关知识",
context_info=context_info or "无对话历史"
)
return {
"system": template["system"],
"user": formatted_user
}
def get_multimodal_prompt(self, question_type: str, question: str, knowledge_info: str = "", context_info: str = "") -> str:
"""获取多模态输出的完整提示词"""
template = self.get_template(question_type)
multimodal_system = template["system"] + """
**多模态输出要求**：
- 文字解释：清晰的概念说明和步骤描述
- 代码示例：完整的Rust代码，使用```rust标记
- 图示说明：使用mermaid语法创建流程图、关系图或时序图
- 表格对比：使用Markdown表格进行对比分析
- 列表总结：使用有序或无序列表总结要点
**图示类型建议**：
- 概念关系图：展示概念间的关联
- 流程图：展示操作步骤
- 时序图：展示执行顺序
- 类图：展示结构关系
- 状态图：展示状态转换
**实践链接**：
在每个回答的最后，添加一个实践练习部分，包含指向代码编辑器的链接：
### 🔧 实践练习
想要实践这些代码示例？点击这里进入 <a href="http://127.0.0.1:5000/code_editor" target="_blank"><b>代码编辑器</b></a> 进行在线编程练习！"""
formatted_user = template["user"].format(
question=question,
knowledge_info=knowledge_info or "未找到相关知识",
context_info=context_info or "无对话历史"
)
return f"{multimodal_system}\n\n{formatted_user}"
# 创建全局实例
prompt_templates = PromptTemplateSystem()
|
2301_80743186/rust-agent-code
|
prompt_templates.py
|
Python
|
unknown
| 12,483
|
#问题分类模块
import openai
import json
import requests
from config import OPENAI_API_KEY, DEEPSEEK_API_KEY, XINGHE_API_KEY, XINGHE_BASE_URL, OPENAI_MODEL, DEEPSEEK_MODEL, XINGHE_MODEL, QUESTION_LABELS
from model_status import model_status
class QuestionClassifier:
def __init__(self, openai_api_key=OPENAI_API_KEY, deepseek_api_key=DEEPSEEK_API_KEY, xinghe_api_key=XINGHE_API_KEY, gemini_api_key="AIzaSyB1lMryiHH_V_7-OVT4eyuLBrHbLsigRCs"):
self.openai_client = openai.OpenAI(api_key=openai_api_key)
self.deepseek_client = openai.OpenAI(api_key=deepseek_api_key, base_url="https://api.deepseek.com/v1")
self.xinghe_client = openai.OpenAI(api_key=xinghe_api_key, base_url=XINGHE_BASE_URL)
self.gemini_api_key = gemini_api_key
self.gemini_url = "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent"
self.labels = QUESTION_LABELS
def classify(self, question):
"""分类用户问题"""
system_prompt = """你是一个Rust编程问题分类专家。请将用户的问题分类为以下6种类型之一：
1. greeting - 问候语类：打招呼、问候、寒暄等
示例："你好"、"Hello"、"早上好"、"Hi"、"你好吗？"
2. definition - 概念定义类：询问Rust概念、术语的定义和含义
示例："生命周期是什么？"、"所有权是什么意思？"
3. usage - 用法说明类：询问如何使用某个功能、语法或API
示例："如何使用迭代器？"、"怎么声明可变变量？"
4. error_debug - 错误调试类：询问编译错误、运行时错误或调试问题
示例："这个编译错误怎么解决？"、"为什么会出现借用检查器错误？"
5. comparison - 语言/概念对比类：比较Rust与其他语言或概念的异同
示例："Rust和C++有什么区别？"、"生命周期和垃圾回收有什么不同？"
6. faq - 常见问题类：一般性的Rust学习问题或最佳实践
示例："Rust适合什么项目？"、"如何学习Rust？"
请返回JSON格式：{"label": "分类标签", "confidence": 置信度(0-1)}"""
# 1. 优先使用星河大模型
if model_status.status['xinghe']['available']:
try:
response = self.xinghe_client.chat.completions.create(
model=XINGHE_MODEL,
messages=[
{"role": "system", "content": system_prompt},
{"role": "user", "content": f"请分类这个问题：{question}"}
],
max_tokens=100,
temperature=0.1
)
result_text = response.choices[0].message.content.strip()
# 尝试解析JSON
try:
result = json.loads(result_text)
if result['label'] not in self.labels:
result['label'] = 'faq' # 默认分类
model_status.update_status('xinghe', True)
return result
except json.JSONDecodeError:
# 如果JSON解析失败，使用简单规则分类
model_status.update_status('xinghe', False, "JSON解析失败")
return self._rule_based_classify(question)
except Exception as e:
print(f"星河大模型分类API调用失败: {e}")
model_status.update_status('xinghe', False, str(e))
# 2. 使用Gemini
try:
gemini_payload = {
"contents": [
{"parts": [
{"text": f"{system_prompt}\n\n请分类这个问题：{question}"}
]}
]
}
headers = {
"Content-Type": "application/json",
"X-goog-api-key": self.gemini_api_key
}
resp = requests.post(self.gemini_url, json=gemini_payload, headers=headers, timeout=20)
if resp.status_code == 200:
data = resp.json()
if "candidates" in data and data["candidates"]:
result_text = data["candidates"][0]["content"]["parts"][0]["text"].strip()
# 尝试解析JSON
try:
result = json.loads(result_text)
if result['label'] not in self.labels:
result['label'] = 'faq' # 默认分类
model_status.update_status('gemini', True)
return result
except json.JSONDecodeError:
# 如果JSON解析失败，使用简单规则分类
model_status.update_status('gemini', False, "JSON解析失败")
return self._rule_based_classify(question)
else:
raise Exception("Gemini无有效回答")
else:
raise Exception(f"Gemini API错误: {resp.status_code} {resp.text}")
except Exception as e:
print(f"Gemini分类API调用失败: {e}")
model_status.update_status('gemini', False, str(e))
# 3. 尝试使用OpenAI
if model_status.status['openai']['available']:
try:
response = self.openai_client.chat.completions.create(
model=OPENAI_MODEL,
messages=[
{"role": "system", "content": system_prompt},
{"role": "user", "content": f"请分类这个问题：{question}"}
],
max_tokens=100,
temperature=0.1
)
result_text = response.choices[0].message.content.strip()
# 尝试解析JSON
try:
result = json.loads(result_text)
if result['label'] not in self.labels:
result['label'] = 'faq' # 默认分类
model_status.update_status('openai', True)
return result
except json.JSONDecodeError:
# 如果JSON解析失败，使用简单规则分类
model_status.update_status('openai', False, "JSON解析失败")
return self._rule_based_classify(question)
except Exception as e:
print(f"OpenAI分类API调用失败: {e}")
model_status.update_status('openai', False, str(e))
# 4. 尝试使用DeepSeek
if model_status.status['deepseek']['available']:
try:
response = self.deepseek_client.chat.completions.create(
model=DEEPSEEK_MODEL,
messages=[
{"role": "system", "content": system_prompt},
{"role": "user", "content": f"请分类这个问题：{question}"}
],
max_tokens=100,
temperature=0.1
)
result_text = response.choices[0].message.content.strip()
# 尝试解析JSON
try:
result = json.loads(result_text)
if result['label'] not in self.labels:
result['label'] = 'faq' # 默认分类
model_status.update_status('deepseek', True)
return result
except json.JSONDecodeError:
# 如果JSON解析失败，使用简单规则分类
model_status.update_status('deepseek', False, "JSON解析失败")
return self._rule_based_classify(question)
except Exception as e2:
print(f"DeepSeek分类API调用失败: {e2}")
model_status.update_status('deepseek', False, str(e2))
# 5. 使用规则分类作为最终备用方案
print("使用本地规则分类作为备用方案")
model_status.update_status('fallback', True)
return self._rule_based_classify(question)
def _rule_based_classify(self, question):
"""基于规则的备用分类方法"""
question_lower = question.lower()
# 定义关键词规则
greeting_keywords = ['你好', 'hello', 'hi', '早上好', '下午好', '晚上好', '你好吗', 'how are you', 'good morning', 'good afternoon', 'good evening']
definition_keywords = ['是什么', '什么意思', '定义', '概念', '术语']
usage_keywords = ['怎么', '如何', '使用', '用法', '语法']
error_keywords = ['错误', '编译', '运行', '调试', '问题', '失败']
comparison_keywords = ['区别', '不同', '比较', 'vs', '对比']
# 首先检查问候语
if any(keyword in question_lower for keyword in greeting_keywords):
return {"label": "greeting", "confidence": 0.9}
elif any(keyword in question_lower for keyword in definition_keywords):
return {"label": "definition", "confidence": 0.8}
elif any(keyword in question_lower for keyword in usage_keywords):
return {"label": "usage", "confidence": 0.8}
elif any(keyword in question_lower for keyword in error_keywords):
return {"label": "error_debug", "confidence": 0.8}
elif any(keyword in question_lower for keyword in comparison_keywords):
return {"label": "comparison", "confidence": 0.8}
else:
return {"label": "faq", "confidence": 0.6}
|
2301_80743186/rust-agent-code
|
question_classifier.py
|
Python
|
unknown
| 9,778
|
# 语义检索模块，目前只更改了test_system里面的
# 采用paraphrase-multilingual-MiniLM-L12-v2
import json
import os
import re
from typing import List, Dict
import faiss
import numpy as np
from sentence_transformers import SentenceTransformer
import logging
from performance_timer import global_timer, StepTimer
# 配置日志（默认设置为WARNING级别以减少性能影响）
logging.basicConfig(level=logging.WARNING, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
# 尝试导入jieba进行中文分词
try:
import jieba
import logging as jieba_logging
JIEBA_AVAILABLE = True
# 禁用jieba的日志输出以提高性能
jieba_logging.basicConfig(level=logging.ERROR)
except ImportError:
print("警告: jieba库未安装，将使用简单分词方法，对中文支持有限")
JIEBA_AVAILABLE = False
# 下载faiss，numpy，sentence_transformers：pip install faiss-cpu numpy sentence-transformers
class SemanticRetriever:
def __init__(self, kb_path='rust_knowledge_base/rust_docs_sample.json'):
self.kb_path = kb_path
self.knowledge_base = []
self.index = None
self.model = None
# 添加缓存机制
self.token_cache = {}
self.embedding_cache = {}
# 延迟加载标志
self._kb_loaded = False
self._model_loaded = False
self._index_built = False
def _ensure_resources_loaded(self):
"""
确保所有必要的资源都已加载
"""
if not self._kb_loaded:
self.knowledge_base = self._load_knowledge_base()
self._kb_loaded = True
if not self._model_loaded:
self._init_model()
self._model_loaded = True
if not self._index_built and self._kb_loaded and self._model_loaded:
self._build_faiss_index()
self._index_built = True
def _init_model(self):
"""
初始化嵌入模型
"""
try:
# 初始化嵌入模型
# 优先尝试使用本地D盘的多语言模型
local_model_path = 'D:/paraphrase-multilingual-MiniLM-L12-v2'
if os.path.exists(local_model_path):
print(f"使用本地多语言模型: {local_model_path}")
self.model = SentenceTransformer(local_model_path)
else:
# 如果本地模型不存在，使用模型名称让系统自动下载并缓存
print("使用模型名称，系统将自动查找缓存或下载多语言模型")
self.model = SentenceTransformer('paraphrase-multilingual-MiniLM-L12-v2')
# 禁用jieba的DEBUG输出
if JIEBA_AVAILABLE:
import jieba
jieba.setLogLevel(20) # 设置为INFO级别，隐藏DEBUG输出
except Exception as e:
logger.error(f"初始化嵌入模型失败: {str(e)}")
print(f"警告: 初始化嵌入模型失败: {str(e)}")
self.model = None
def _load_knowledge_base(self) -> List[Dict]: # 知识库加载并标准化
"""加载知识库并转换为统一格式"""
if os.path.exists(self.kb_path):
with open(self.kb_path, 'r', encoding='utf-8') as f:
raw_docs = json.load(f)
# 转换格式以匹配代码期望的结构
converted_docs = []
for i, doc in enumerate(raw_docs):
# 优先使用知识库中已有的tags：如果存在且非空，直接使用；否则自动提取
if 'tags' in doc and doc['tags']: # 检查tags字段存在且不为空（空列表/空字符串都不满足）
tags = doc['tags']
# 可选：对已有tags做简单清洗（去重、过滤短词，保持数据一致性）
tags = list(dict.fromkeys([t.strip() for t in tags if len(t.strip()) > 1]))[:10]
else:
# 无已有tags，自动从内容提取关键词作为标签
tags = []
if 'content' in doc:
# 简单的关键词提取，实际项目中可以使用更复杂的NLP方法
content_words = doc['content'].lower().split()
# 过滤掉常见停用词和短词
common_stopwords = set(
['的', '了', '和', '是', '在', '有', '我', '他', '她', '它', '这', '那', '为', '与', '而',
'就', '都', '但', '及', '于', '要', '把', '将', '被', '也', '更', '还', '你', '您', '们'])
keywords = [word.strip('.,;!?\n') for word in content_words if
word not in common_stopwords and len(word) > 2]
# 去重并取前10个关键词作为标签
tags = list(dict.fromkeys(keywords))[:10]
# 优先使用知识库中已有的category：如果存在且非"unknown"，直接使用；否则自动分类
category = doc.get('category', 'unknown') # 先读取已有category，默认unknown
if category == 'unknown' or not category: # 仅当category为unknown或空时，执行自动分类
title_lower = doc.get('title', '').lower()
content_lower = doc.get('content', '').lower()
# 简单的分类规则
if any(word in title_lower or word in content_lower for word in
['什么是', '什么', '定义', '概念', '介绍']):
category = 'definition'
elif any(word in title_lower or word in content_lower for word in
['如何', '使用', '用法', '怎么', '步骤']):
category = 'usage'
elif any(word in title_lower or word in content_lower for word in
['错误', '问题', 'debug', '修复', '解决']):
category = 'error_debug'
elif any(word in title_lower or word in content_lower for word in
['比较', '区别', 'vs', 'vs.', '对比']):
category = 'comparison'
else:
category = 'faq' # 默认归为常见问题
# 标准化文档格式（统一字段）
converted_doc = {
"id": f"k{i + 1:03d}",
"topic": doc.get("title", ""), # 使用title作为topic
"content": doc.get("content", ""),
"tags": tags, # 优先用已有tags，无则自动提取
"category": category, # 优先用已有category，无则自动分类
"code": doc.get("code", "")
}
converted_docs.append(converted_doc)
print(
f"知识库加载完成，共{len(converted_docs)}条记录，平均每文档标签数: {sum(len(doc['tags']) for doc in converted_docs) / len(converted_docs):.1f}")
return converted_docs
else:
# 若知识库文件不存在，返回默认知识库
return [
{
"id": "k001",
"topic": "生命周期",
"content": "Rust的生命周期用于确保引用始终有效。生命周期是引用保持有效的作用域。",
"tags": ["生命周期", "引用", "作用域"],
"category": "definition",
"code": "fn longest<'a>(x: &'a str, y: &'a str) -> &'a str {\n if x.len() > y.len() { x } else { y }\n}"
},
{
"id": "k002",
"topic": "所有权",
"content": "Rust的所有权系统是内存安全的核心。每个值都有一个所有者，当所有者离开作用域时，值会被丢弃。",
"tags": ["所有权", "内存管理", "作用域"],
"category": "definition",
"code": "let s1 = String::from(\"hello\");\nlet s2 = s1; // s1的所有权移动到s2"
},
{
"id": "k003",
"topic": "可变变量",
"content": "使用mut关键字声明可变变量，允许修改变量的值。",
"tags": ["变量", "mut", "可变性"],
"category": "usage",
"code": "let mut x = 5;\nx = 10; // 可以修改"
},
{
"id": "k004",
"topic": "借用检查器错误",
"content": "借用检查器错误通常是由于违反了Rust的借用规则导致的。常见错误包括同时存在可变和不可变借用。",
"tags": ["借用检查器", "错误", "调试"],
"category": "error_debug",
"code": "let mut v = vec![1, 2, 3];\nlet first = &v[0];\nv.push(4); // 错误：同时存在可变和不可变借用"
},
{
"id": "k005",
"topic": "Rust vs C++",
"content": "Rust和C++都是系统编程语言，但Rust通过所有权系统提供内存安全，而C++需要手动管理内存。",
"tags": ["Rust", "C++", "比较"],
"category": "comparison",
"code": "// Rust: 自动内存管理\nlet s = String::from(\"hello\");\n// C++: 手动内存管理\n// std::string s = \"hello\";"
}
]
def _build_faiss_index(self): # 构建 FAISS 向量索引
"""
构建FAISS向量索引，使用更高效的索引类型，并支持索引持久化
"""
if not self.knowledge_base or not self.model: # 若知识库或模型为空，直接返回
return
# 索引文件路径
index_path = os.path.splitext(self.kb_path)[0] + '_index.faiss'
# 尝试从文件加载索引，避免重复构建
if os.path.exists(index_path) and not self._index_built:
try:
self.index = faiss.read_index(index_path)
print(f"从文件加载FAISS索引: {index_path}")
self._index_built = True
return
except Exception as e:
print(f"加载FAISS索引失败，将重新构建: {str(e)}")
# 使用缓存机制生成嵌入向量
embeddings = []
for doc in self.knowledge_base:
# 组合关键信息：主题 + 分类 + 标签 + 内容 + 代码
# 将标签转换为空格分隔的字符串
tags_str = " ".join(doc.get('tags', [])) # 标签转为空格分隔的字符串
# 构建完整文本（包含所有关键字段）
combined_text = (
f"主题: {doc['topic']} "
f"分类: {doc['category']} "
f"标签: {tags_str} "
f"内容: {doc['content']}"
)
# 如果有代码也加入
if doc.get('code'):
combined_text += f" 代码: {doc['code']}"
# 使用缓存的嵌入向量
embedding = self._get_embedding(combined_text)
if embedding is not None:
embeddings.append(embedding)
embeddings = np.array(embeddings).astype(np.float32)
print(f"生成嵌入向量类型: {type(embeddings)}, 形状: {embeddings.shape}")
# 根据文档数量选择合适的索引类型
dimension = embeddings.shape[1]
total_docs = len(embeddings)
if total_docs > 1000:
# 对于大数据集，使用IVF索引加速搜索
nlist = min(100, total_docs // 10)
quantizer = faiss.IndexFlatIP(dimension)
self.index = faiss.IndexIVFFlat(quantizer, dimension, nlist, faiss.METRIC_INNER_PRODUCT)
self.index.train(embeddings)
else:
# 对于小数据集，使用Flat索引保证准确性
self.index = faiss.IndexFlatIP(dimension)
# 添加向量到索引
self.index.add(embeddings)
# 尝试保存索引到文件
try:
faiss.write_index(self.index, index_path)
print(f"FAISS索引已保存到文件: {index_path}")
except Exception as e:
logger.warning(f"保存FAISS索引失败: {str(e)}")
print(f"警告: 保存FAISS索引失败: {str(e)}")
print(f"FAISS索引构建完成，共 {total_docs} 个文档")
def _tokenize_text(self, text: str) -> List[str]: # 文本分词
"""
对文本进行分词，支持中英文，并使用缓存避免重复计算
"""
# 检查缓存
if text in self.token_cache:
return self.token_cache[text]
# 去除空白字符和特殊字符
text = re.sub(r'\s+|[,.!?;\n]', ' ', text.lower().strip())
# 检查文本中是否包含中文字符
if JIEBA_AVAILABLE and re.search(r'[\u4e00-\u9fff]', text):
# 使用jieba分词处理中文
result = list(jieba.cut(text))
else:
# 英文分词（按空格）+ 简单中文分词（按字）
# 提取所有汉字作为单独的词
chinese_chars = re.findall(r'[\u4e00-\u9fff]', text)
# 提取英文单词
english_words = re.findall(r'[a-zA-Z]+', text)
# 合并结果
result = chinese_chars + english_words
# 存入缓存
self.token_cache[text] = result
return result
def _get_embedding(self, text: str):
"""
获取文本的嵌入向量，并使用缓存避免重复计算
"""
# 检查缓存
if text in self.embedding_cache:
return self.embedding_cache[text]
# 确保模型已加载
if not self._model_loaded:
self._init_model()
self._model_loaded = True
if not self.model:
return None
# 生成嵌入向量
embedding = self.model.encode([text], normalize_embeddings=True)[0]
# 存入缓存
self.embedding_cache[text] = embedding
return embedding
def _calculate_comprehensive_score(self, vector_score: float, doc: Dict, question: str, question_type: str, question_tokens: set = None) -> float: #综合评分计算
"""
计算综合评分，结合向量相似度和关键词匹配
"""
# 向量相似度分数（已在向量检索时计算）
vector_score_contribution = vector_score * 0.5 # 向量相似度权重0.5
# 关键词匹配分数计算
# 1. 提取文档的关键信息：主题、分类、标签、内容、代码
doc_keywords = set()
# 提取主题中的关键词
if doc.get('topic'):
doc_keywords.update(self._tokenize_text(doc['topic']))
# 提取分类中的关键词
if doc.get('category'):
doc_keywords.update(self._tokenize_text(doc['category']))
# 提取标签作为关键词
if doc.get('tags'):
for tag in doc['tags']:
doc_keywords.update(self._tokenize_text(tag))
# 提取内容中的关键词（取前100个字符进行分词）
if doc.get('content'):
content_preview = doc['content'][:100]
doc_keywords.update(self._tokenize_text(content_preview))
# 提取代码中的关键词（如果有）
if doc.get('code'):
# 从代码中提取标识符（变量名、函数名等）
code_identifiers = set(re.findall(r'[a-zA-Z_][a-zA-Z0-9_]*', doc['code']))
doc_keywords.update(code_identifiers)
# 对问题进行分词（使用预计算的分词结果，如果提供）
if question_tokens is None:
question_keywords = set(self._tokenize_text(question))
else:
question_keywords = question_tokens
# 计算关键词匹配比例
keyword_match_score = 0.0
if question_keywords:
# 计算交集的大小（共同关键词的数量）
common_keywords = question_keywords.intersection(doc_keywords)
keyword_match_score = len(common_keywords) / len(question_keywords)
# 关键词匹配分数贡献（权重0.5）
keyword_match_contribution = keyword_match_score * 0.5
# 类型匹配加分（可选，根据question_type）
type_match_bonus = 0.0
if question_type and doc.get('category') == question_type:
type_match_bonus = 0.1 # 类型匹配加0.1分
# 综合得分
score = vector_score_contribution + keyword_match_contribution + type_match_bonus
return min(1.0, score) # 确保不超过1.0
def retrieve(self, question: str, question_type: str = None, top_k: int = 3, debug: bool = False) -> List[Dict]:
"""
语义检索相关文档 - 使用向量检索
"""
try:
with StepTimer("语义检索完整流程"):
# 确保所有资源已加载
with StepTimer("加载资源"):
self._ensure_resources_loaded()
if not self.index:
print("FAISS索引未初始化")
return []
# 使用缓存获取查询向量
with StepTimer("生成查询向量"):
query_embedding = self._get_embedding(question)
if query_embedding is None:
return []
query_embedding = np.array([query_embedding]).astype(np.float32)
# 动态计算搜索范围 - 优化搜索范围以提高性能
total_docs = len(self.knowledge_base)
# 减少搜索范围，从0.1减少到0.05，提高性能
search_k = max(top_k * 5, min(int(total_docs * 0.05), total_docs))
with StepTimer("FAISS检索"):
scores, indices = self.index.search(query_embedding, search_k)
if debug:
print(f"检索问题: '{question}'")
print(f"搜索到 {len(indices[0])} 个候选结果")
with StepTimer("结果过滤与排序"):
results = []
# 提前对问题进行分词（使用jieba，若可用），供后续标题匹配使用
question_tokens = set(self._tokenize_text(question))
# 限制处理的候选文档数量，避免不必要的计算
max_candidates = min(search_k, 20)
for i, (score, idx) in enumerate(zip(scores[0][:max_candidates], indices[0][:max_candidates])):
if idx < len(self.knowledge_base):
doc = self.knowledge_base[idx]
# 计算综合评分，传入预计算的问题分词结果以避免重复计算
final_score = self._calculate_comprehensive_score(score, doc, question, question_type, question_tokens)
# 核心：增加基于jieba分词的标题匹配逻辑
# 即使综合评分略低，但标题与问题高度相关，也纳入结果
is_relevant = False
# 原过滤条件：分数>0.35
if final_score > 0.35:
is_relevant = True
# 放宽条件：分数>0.25且标题与问题高度相关（依赖jieba分词结果）
elif final_score > 0.25:
# 对文档标题进行分词（使用jieba，若可用）
topic_tokens = set(self._tokenize_text(doc.get('topic', '')))
# 计算标题分词与问题分词的重叠比例，超过50%则认为高度相关
if topic_tokens and len(question_tokens & topic_tokens) / len(topic_tokens) > 0.5:
if debug:
print(f"DEBUG: 标题高度相关（分词匹配），破格录取: {doc.get('topic', '无标题')}")
is_relevant = True
# 类型匹配条件（保持不变）
category_match = (not question_type or
doc.get('category') == question_type or
question_type == "unknown")
# 满足相关性和类型匹配则加入结果
if is_relevant and category_match:
results.append({
**doc,
'score': float(final_score)
})
# 提前结束如果已收集足够文档
if len(results) >= top_k:
break
# 按分数排序
results.sort(key=lambda x: x['score'], reverse=True)
global_timer.add_info("检索到文档数", len(results))
if results:
global_timer.add_info("最高相似度得分", max(results, key=lambda x: x['score'])['score'])
if debug:
print(f"返回 {len(results)} 个最终结果")
return results
except Exception as e:
print(f"检索失败: {e}")
global_timer.add_info("检索错误", str(e)[:100])
return []
# """语义检索相关文档"""
# # 向量检索模式（优先）
# if self.model and self.index:
# try:
# return self._vector_retrieve(question, question_type, top_k)
# except Exception as e:
# print(f"向量检索失败: {str(e)}")
# print("切换到备用检索方法: 关键词匹配")
# else:
# print("模型或索引未初始化，使用备用检索方法: 关键词匹配")
# # 备用关键词匹配模式
# return self._keyword_retrieve(question, question_type, top_k)
# def _vector_retrieve(self, question: str, question_type: str = None, top_k: int = 3) -> List[Dict]:
# """使用向量检索相关文档"""
# # 将问题转换为向量
# query_embedding = self.model.encode([question], normalize_embeddings=True).astype(np.float32)
#
# # 使用FAISS进行相似度搜索 - 增加搜索范围
# # search_k = min(top_k * 3, len(self.knowledge_base))
# total_docs = len(self.knowledge_base)
# search_k = min(total_docs, top_k * 10)
# scores, indices = self.index.search(query_embedding, search_k)
#
# print(f"检索问题: '{question}'")
# print(f"搜索到 {len(indices[0])} 个候选结果")
#
# results = []
# for i, (score, idx) in enumerate(zip(scores[0], indices[0])):
# if idx < len(self.knowledge_base):
# doc = self.knowledge_base[idx]
#
# # 计算综合评分
# final_score = self._calculate_comprehensive_score(score, doc, question, question_type)
#
# # 降低阈值并优化过滤逻辑
# # 1. 首先降低阈值到0.2，让更多文档能被检索到
# # 2. 对于特定情况可以进一步放宽限制
# is_relevant = False
#
# # 基本条件：分数超过阈值
# if final_score > 0.2:
# is_relevant = True
# # 如果问题和文档标题有较多重叠，即使分数略低也考虑
# elif final_score > 0.15:
# question_tokens = set(self._tokenize_text(question))
# topic_tokens = set(self._tokenize_text(doc.get('topic', '')))
# if topic_tokens and len(question_tokens & topic_tokens) / len(topic_tokens) > 0.5:
# print(f"DEBUG: 标题高度相关，破格录取: {doc.get('topic', '无标题')}")
# is_relevant = True
#
# # 分类匹配可以适当放宽
# category_match = not question_type or doc.get('category') == question_type or question_type == "unknown"
#
# if is_relevant and category_match:
# results.append({
# **doc,
# 'score': float(final_score)
# })
#
# # 如果已经收集到足够的文档，提前结束
# if len(results) >= top_k:
# break
#
# # 按分数排序
# results.sort(key=lambda x: x['score'], reverse=True)
# print(f"返回 {len(results)} 个最终结果")
# return results
#
# def _keyword_retrieve(self, question: str, question_type: str = None, top_k: int = 3) -> List[Dict]:
# """备用关键词检索方法"""
# results = []
#
# for doc in self.knowledge_base:
# score = 0
#
# # 基于问题类型的过滤
# if question_type and doc.get('category') == question_type:
# score += 0.5
#
# # 关键词匹配（使用改进的分词方法）
# question_tokens = set(self._tokenize_text(question))
# content_tokens = set(self._tokenize_text(doc['content']))
# tag_tokens = set()
# for tag in doc.get('tags', []):
# tag_tokens.update(self._tokenize_text(tag))
#
# # 计算匹配度
# content_match = len(question_tokens & content_tokens) / len(question_tokens) if question_tokens else 0
# tag_match = len(question_tokens & tag_tokens) / len(question_tokens) if question_tokens else 0
#
# score += content_match * 0.3 + tag_match * 0.2
#
# if score > 0:
# results.append({
# **doc,
# 'score': score
# })
#
# # 按分数排序并返回top_k
# results.sort(key=lambda x: x['score'], reverse=True)
# return results[:top_k]
def add_document(self, doc: Dict):
"""
添加新文档到知识库
"""
# 确保资源已加载
self._ensure_resources_loaded()
if 'id' not in doc:
doc['id'] = f"k{len(self.knowledge_base) + 1:03d}"
self.knowledge_base.append(doc)
# 保存到文件
try:
with open(self.kb_path, 'w', encoding='utf-8') as f:
json.dump(self.knowledge_base, f, ensure_ascii=False, indent=2)
print(f"成功添加文档: {doc.get('topic', '无标题')}")
except Exception as e:
print(f"警告: 保存文档到文件失败: {str(e)}")
# 重新构建索引（仅当向量检索模式可用时）
try:
if self.model:
# 清除相关缓存以确保数据一致性
self._index_built = False
self.embedding_cache.clear()
self._build_faiss_index()
except Exception as e:
print(f"警告: 重建FAISS索引失败: {str(e)}")
if __name__ == "__main__":
print("开始测试语义检索模块...")
# 创建检索器实例，默认不使用调试模式
retriever = SemanticRetriever()
# 测试问题
test_questions = [
"变量如何声明？",
"什么是可变变量？",
"如何定义函数？"
]
# 启用调试模式进行测试
for question in test_questions:
print(f"\n=== 测试问题: {question} ===")
results = retriever.retrieve(question, top_k=2, debug=True)
for i, result in enumerate(results):
print(f"{i + 1}. 主题: {result['topic']}, 分数: {result['score']:.4f}")
print(f" 内容: {result['content']}")
print()
|
2301_80743186/rust-agent-code
|
semantic_retriever.py
|
Python
|
unknown
| 28,895
|
# 语义检索模块，目前只更改了test_system里面的
import json
import os
from typing import List, Dict
import faiss
import numpy as np
from sentence_transformers import SentenceTransformer
# 下载faiss，numpy，sentence_transformers：pip install faiss-cpu numpy sentence-transformers
class SemanticRetriever:
def init(self, kb_path='rust_knowledge_base/rust_docs_sample.json'):
self.kb_path = kb_path
self.knowledge_base = self._load_knowledge_base()
# 初始化嵌入模型和FAISS索引
self.model = SentenceTransformer('D:/all-MiniLM-L6-v2') # 暂存在这里
self.index = None
self._build_faiss_index()
def _load_knowledge_base(self) -> List[Dict]:
"""加载知识库并转换为统一格式"""
if os.path.exists(self.kb_path):
with open(self.kb_path, 'r', encoding='utf-8') as f:
raw_docs = json.load(f)
# 转换格式以匹配代码期望的结构
converted_docs = []
for i, doc in enumerate(raw_docs):
converted_doc = {
"id": f"k{i + 1:03d}",
"topic": doc.get("title", ""), # 使用title作为topic
"content": doc.get("content", ""),
"tags": [], # 您的JSON中没有tags，设为空列表
"category": "unknown", # 默认分类
"code": doc.get("code", "")
}
converted_docs.append(converted_doc)
return converted_docs
else:
# 默认知识库（保持原样）
return [
{
"id": "k001",
"topic": "生命周期",
"content": "Rust的生命周期用于确保引用始终有效。生命周期是引用保持有效的作用域。",
"tags": ["生命周期", "引用", "作用域"],
"category": "definition",
"code": "fn longest<'a>(x: &'a str, y: &'a str) -> &'a str {\n if x.len() > y.len() { x } else { y }\n}"
},
{
"id": "k002",
"topic": "所有权",
"content": "Rust的所有权系统是内存安全的核心。每个值都有一个所有者，当所有者离开作用域时，值会被丢弃。",
"tags": ["所有权", "内存管理", "作用域"],
"category": "definition",
"code": "let s1 = String::from(\"hello\");\nlet s2 = s1; // s1的所有权移动到s2"
},
{
"id": "k003",
"topic": "可变变量",
"content": "使用mut关键字声明可变变量，允许修改变量的值。",
"tags": ["变量", "mut", "可变性"],
"category": "usage",
"code": "let mut x = 5;\nx = 10; // 可以修改"
},
{
"id": "k004",
"topic": "借用检查器错误",
"content": "借用检查器错误通常是由于违反了Rust的借用规则导致的。常见错误包括同时存在可变和不可变借用。",
"tags": ["借用检查器", "错误", "调试"],
"category": "error_debug",
"code": "let mut v = vec![1, 2, 3];\nlet first = &v[0];\nv.push(4); // 错误：同时存在可变和不可变借用"
},
{
"id": "k005",
"topic": "Rust vs C++",
"content": "Rust和C++都是系统编程语言，但Rust通过所有权系统提供内存安全，而C++需要手动管理内存。",
"tags": ["Rust", "C++", "比较"],
"category": "comparison",
"code": "// Rust: 自动内存管理\nlet s = String::from(\"hello\");\n// C++: 手动内存管理\n// std::string s = \"hello\";"
}
]
def _build_faiss_index(self):
"""构建FAISS向量索引"""
if not self.knowledge_base:
return
# 优化文本组合策略
texts = []
for doc in self.knowledge_base:
# 多种文本组合方式，增加信息密度
combined_texts = [
# 方式1：标题+内容
f"{doc['topic']} {doc['content']}",
# 方式2：标题重复强调 + 内容
f"{doc['topic']} {doc['topic']} {doc['content']}",
# 方式3：纯内容
doc['content']
]
# 选择最长的文本（通常包含最多信息）
best_text = max(combined_texts, key=len)
texts.append(best_text)
# 生成嵌入向量
embeddings = self.model.encode(texts, normalize_embeddings=True)
print(f"生成嵌入向量类型: {type(embeddings)}, 形状: {embeddings.shape}")
# 创建FAISS索引
dimension = embeddings.shape[1]
self.index = faiss.IndexFlatIP(dimension) # 使用内积相似度
# 添加向量到索引
self.index.add(embeddings.astype(np.float32))
print(f"FAISS索引构建完成，共 {len(self.knowledge_base)} 个文档")
def _calculate_comprehensive_score(self, vector_score: float, doc: Dict, question: str,
question_type: str) -> float:
"""计算综合评分"""
# 将向量相似度分数归一化到[0,1]范围
normalized_vector_score = max(0, min(1, vector_score))
# 关键词匹配
question_words = set(question.lower().split())
content_words = set(doc['content'].lower().split())
tag_words = set([tag.lower() for tag in doc.get('tags', [])])
# 计算匹配度
content_match = len(question_words & content_words) / len(question_words) if question_words else 0
tag_match = len(question_words & tag_words) / len(question_words) if question_words else 0
# 计算问题类型匹配
type_match = 0.15 if question_type and doc.get('category') == question_type else 0
# 综合评分 = 向量相似度(0.7) + 内容匹配(0.1) + 标签匹配(0.05) + 类型匹配(0.15)
# 总加和不超过1.0
score = (
normalized_vector_score * 0.7 + # 向量相似度占比最大
content_match * 0.1 + # 内容匹配
tag_match * 0.05 + # 标签匹配
type_match * 0.15 # 类型匹配
)
return min(1.0, score) # 确保不超过1.0
def retrieve(self, question: str, question_type: str = None, top_k: int = 3) -> List[Dict]:
"""语义检索相关文档 - 使用向量检索"""
if not self.index:
print("FAISS索引未初始化")
return []
# 将问题转换为向量
query_embedding = self.model.encode([question], normalize_embeddings=True).astype(np.float32)
# 使用FAISS进行相似度搜索 - 增加搜索范围
search_k = min(top_k * 3, len(self.knowledge_base))
scores, indices = self.index.search(query_embedding, search_k)
print(f"检索问题: '{question}'")
print(f"搜索到 {len(indices[0])} 个候选结果")
results = []
for i, (score, idx) in enumerate(zip(scores[0], indices[0])):
if idx < len(self.knowledge_base):
doc = self.knowledge_base[idx]
# 计算综合评分
final_score = self._calculate_comprehensive_score(score, doc, question, question_type)
# 基于问题类型的过滤和最低分数阈值
if (final_score > 0.3 and
(not question_type or doc.get('category') == question_type or question_type == "unknown")):
results.append({
**doc,
'score': float(final_score)
})
# 如果已经收集到足够的文档，提前结束
if len(results) >= top_k:
break
# 按分数排序
results.sort(key=lambda x: x['score'], reverse=True)
print(f"返回 {len(results)} 个最终结果")
return results
def add_document(self, doc: Dict):
"""添加新文档到知识库"""
if 'id' not in doc:
doc['id'] = f"k{len(self.knowledge_base) + 1:03d}"
self.knowledge_base.append(doc)
# 保存到文件
with open(self.kb_path, 'w', encoding='utf-8') as f:
json.dump(self.knowledge_base, f, ensure_ascii=False, indent=2)
# 重新构建索引
self._build_faiss_index()
if name == "main":
print("开始测试语义检索模块...")
retriever = SemanticRetriever()
# 更全面的测试问题
test_questions = [
"如何声明变量？",
"mut关键字有什么用？",
"怎样定义一个函数？",
"Rust中的所有权是什么？",
"生命周期怎么用？"
]
for question in test_questions:
print(f"\n{'=' * 50}")
results = retriever.retrieve(question, top_k=2)
print(f"=== 检索分析: {question} ===")
if not results:
print("未找到相关结果")
continue
print(f"找到 {len(results)} 个相关文档:")
for i, result in enumerate(results):
print(f"{i + 1}. [{result['score']:.3f}] {result['topic']}")
# 分析分数分布
scores = [r['score'] for r in results]
if scores:
print(f"分数范围: {min(scores):.3f} - {max(scores):.3f}")
print(f"平均分数: {sum(scores) / len(scores):.3f}")
for i, result in enumerate(results):
print(f"\n{i + 1}. 主题: {result['topic']}")
print(f" 分数: {result['score']:.4f}")
print(f" 内容: {result['content'][:100]}...")
if result.get('code'):
print(f" 代码: {result['code'][:50]}...")
|
2301_80743186/rust-agent-code
|
semantic_retriever_old.py
|
Python
|
unknown
| 10,355
|
# 简单测试问候语功能
from answer_generator import AnswerGenerator
# 测试问候语回复
ag = AnswerGenerator()
response = ag._generate_greeting_response("你好")
print("问候语回复生成成功，长度:", len(response))
print("包含中文:", "你好" in response)
print("包含Rust:", "Rust" in response)
|
2301_80743186/rust-agent-code
|
simple_test.py
|
Python
|
unknown
| 323
|
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Rust知识解释智能体Web应用启动脚本
"""
import os
import sys
import subprocess
from pathlib import Path
def check_dependencies():
"""检查依赖包是否已安装"""
required_packages = ['flask', 'openai']
missing_packages = []
for package in required_packages:
try:
__import__(package)
except ImportError:
missing_packages.append(package)
if missing_packages:
print(f"❌ 缺少依赖包: {', '.join(missing_packages)}")
print("请运行以下命令安装依赖:")
print("pip install -r requirements.txt")
return False
return True
def check_files():
"""检查必要文件是否存在"""
required_files = [
'app.py',
'main.py',
'question_classifier.py',
'semantic_retriever.py',
'answer_generator.py',
'multimodal_renderer.py',
'context_manager.py',
'templates/index.html',
'static/css/style.css',
'static/js/app.js'
]
missing_files = []
for file_path in required_files:
if not Path(file_path).exists():
missing_files.append(file_path)
if missing_files:
print(f"❌ 缺少文件: {', '.join(missing_files)}")
return False
return True
def create_directories():
"""创建必要的目录"""
directories = ['static/css', 'static/js', 'templates']
for directory in directories:
Path(directory).mkdir(parents=True, exist_ok=True)
def main():
"""主函数"""
print("🚀 Rust知识解释智能体Web应用启动器")
print("=" * 50)
# 检查依赖
print("📦 检查依赖包...")
if not check_dependencies():
sys.exit(1)
print("✅ 依赖包检查通过")
# 检查文件
print("📁 检查文件完整性...")
if not check_files():
print("❌ 文件检查失败，请确保所有文件都存在")
sys.exit(1)
print("✅ 文件检查通过")
# 创建目录
print("📂 创建必要目录...")
create_directories()
print("✅ 目录创建完成")
# 启动应用
print("\n🎯 启动Web应用...")
print("📱 访问地址: http://localhost:5001")
print("🔧 API状态: http://localhost:5001/api/status")
print("⏹️ 按 Ctrl+C 停止服务")
print("=" * 50)
try:
# 导入并运行Flask应用
from app import app
app.run(debug=True, host='0.0.0.0', port=5001)
except KeyboardInterrupt:
print("\n👋 服务已停止")
except Exception as e:
print(f"❌ 启动失败: {e}")
sys.exit(1)
if __name__ == "__main__":
main()
|
2301_80743186/rust-agent-code
|
start_web.py
|
Python
|
unknown
| 2,771
|
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Rust知识解释智能体Web应用启动脚本（带登录功能）
"""
import os
import sys
import subprocess
from pathlib import Path
def check_dependencies():
"""检查依赖包是否已安装"""
required_packages = ['flask', 'openai']
missing_packages = []
for package in required_packages:
try:
__import__(package)
except ImportError:
missing_packages.append(package)
if missing_packages:
print(f"缺少依赖包: {', '.join(missing_packages)}")
print("请运行以下命令安装依赖:")
print("pip install -r requirements.txt")
return False
return True
def check_files():
"""检查必要文件是否存在"""
required_files = [
'app.py',
'main.py',
'question_classifier.py',
'semantic_retriever.py',
'answer_generator.py',
'multimodal_renderer.py',
'context_manager.py',
'templates/login.html',
'templates/index.html',
'static/css/auth.css',
'static/css/style.css',
'static/js/auth.js',
'static/js/app.js'
]
missing_files = []
for file_path in required_files:
if not Path(file_path).exists():
missing_files.append(file_path)
if missing_files:
print(f"缺少文件: {', '.join(missing_files)}")
return False
return True
def create_directories():
"""创建必要的目录"""
directories = ['static/css', 'static/js', 'templates']
for directory in directories:
Path(directory).mkdir(parents=True, exist_ok=True)
def show_default_users():
"""显示默认用户信息"""
print("\n默认用户账户:")
print("=" * 40)
print("管理员: admin / 123456")
print("学生: student / 123456")
print("教师: teacher / 123456")
print("=" * 40)
def main():
"""主函数"""
print("Rust知识解释智能体Web应用启动器（带登录功能）")
print("=" * 60)
# 检查依赖
print("检查依赖包...")
if not check_dependencies():
sys.exit(1)
print("依赖包检查通过")
# 检查文件
print("检查文件完整性...")
if not check_files():
print("文件检查失败，请确保所有文件都存在")
sys.exit(1)
print("文件检查通过")
# 创建目录
print("创建必要目录...")
create_directories()
print("目录创建完成")
# 显示默认用户
show_default_users()
# 启动应用
print("\n启动Web应用...")
print("登录页面: http://localhost:5001/login")
print("主页面: http://localhost:5001/dashboard")
print("API状态: http://localhost:5001/api/status")
print("按 Ctrl+C 停止服务")
print("=" * 60)
try:
# 导入并运行Flask应用
from app import app
app.run(debug=True, host='0.0.0.0', port=5001)
except KeyboardInterrupt:
print("\n服务已停止")
except Exception as e:
print(f"启动失败: {e}")
sys.exit(1)
if __name__ == "__main__":
main()
|
2301_80743186/rust-agent-code
|
start_with_auth.py
|
Python
|
unknown
| 3,202
|
/* 认证页面样式 */
* {
margin: 0;
padding: 0;
box-sizing: border-box;
}
:root {
--primary-color: #3498db;
--secondary-color: #2ecc71;
--accent-color: #e74c3c;
--text-color: #2c3e50;
--light-text: #7f8c8d;
--bg-color: #f8f9fa;
--card-bg: #ffffff;
--border-color: #ecf0f1;
--shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
--shadow-hover: 0 8px 15px rgba(0, 0, 0, 0.15);
--border-radius: 12px;
--transition: all 0.3s ease;
}
/*body {*/
/* font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, 'Helvetica Neue', Arial, sans-serif;*/
/* background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);*/
/* min-height: 100vh;*/
/* display: flex;*/
/* align-items: center;*/
/* justify-content: center;*/
/* padding: 20px;*/
/*}*/
body {
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, 'Helvetica Neue', Arial, sans-serif;
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); /* 保留原背景 */
min-height: 100vh;
display: flex;
align-items: center; /* 保持垂直居中（不改动） */
justify-content: flex-end; /* 核心修改：水平靠右对齐 */
padding: 20px; /* 保留基础内边距 */
padding-right: 150px; /* 关键：卡片与右侧间距100px（按需调整） */
padding-left: 20px; /* 左侧留小间距，避免小屏幕贴边 */
}
.auth-container {
width: 100%;
max-width: 450px; /* 保留原最大宽度，缩放基于此值 */
animation: fadeInUp 2s ease;
margin-left: 0; /* 关键：删除左侧负边距，避免卡片向右偏移 */
}
.auth-container {
width: 100%;
max-width: 450px;
animation: fadeInUp 0.8s ease;
}
.auth-card {
background: var(--card-bg);
border-radius: var(--border-radius);
box-shadow: var(--shadow-hover);
overflow: hidden;
position: relative;
}
/* 头部样式 */
.auth-header {
text-align: center;
padding: 40px 30px 30px;
background: linear-gradient(135deg, var(--primary-color), #2980b9);
color: white;
}
.auth-header h1 {
font-size: 1.8rem;
font-weight: 700;
margin-bottom: 10px;
text-shadow: 0 2px 4px rgba(0, 0, 0, 0.3);
}
.auth-header p {
font-size: 1rem;
opacity: 0.9;
font-weight: 300;
}
/* 表单样式 */
.auth-form {
padding: 30px;
}
.form-group {
margin-bottom: 20px;
}
.form-group label {
display: block;
margin-bottom: 8px;
font-weight: 500;
color: var(--text-color);
font-size: 0.95rem;
}
.form-group label i {
margin-right: 8px;
color: var(--primary-color);
}
.form-group input {
width: 100%;
padding: 12px 15px;
border: 2px solid var(--border-color);
border-radius: 8px;
font-size: 1rem;
transition: var(--transition);
background: var(--bg-color);
}
.form-group input:focus {
outline: none;
border-color: var(--primary-color);
box-shadow: 0 0 0 3px rgba(52, 152, 219, 0.1);
background: white;
}
/* 密码输入框 */
.password-input {
position: relative;
}
.toggle-password {
position: absolute;
right: 12px;
top: 50%;
transform: translateY(-50%);
background: none;
border: none;
color: var(--light-text);
cursor: pointer;
padding: 5px;
transition: var(--transition);
}
.toggle-password:hover {
color: var(--primary-color);
}
/* 复选框样式 */
.checkbox-label {
display: flex;
align-items: center;
cursor: pointer;
font-size: 0.9rem;
color: var(--light-text);
}
.checkbox-label input[type="checkbox"] {
width: auto;
margin-right: 10px;
accent-color: var(--primary-color);
}
.terms-link {
color: var(--primary-color);
text-decoration: none;
}
.terms-link:hover {
text-decoration: underline;
}
/* 按钮样式 */
.auth-btn {
width: 100%;
padding: 14px 20px;
border: none;
border-radius: 8px;
font-size: 1rem;
font-weight: 600;
cursor: pointer;
transition: var(--transition);
display: flex;
align-items: center;
justify-content: center;
gap: 8px;
margin-bottom: 15px;
}
.login-btn {
background: var(--primary-color);
color: white;
}
.login-btn:hover {
background: #2980b9;
transform: translateY(-2px);
box-shadow: var(--shadow-hover);
}
.register-btn {
background: var(--bg-color);
color: var(--text-color);
border: 2px solid var(--border-color);
}
.register-btn:hover {
background: var(--secondary-color);
color: white;
border-color: var(--secondary-color);
transform: translateY(-2px);
}
.register-submit-btn {
background: var(--secondary-color);
color: white;
}
.register-submit-btn:hover {
background: #27ae60;
transform: translateY(-2px);
box-shadow: var(--shadow-hover);
}
.login-back-btn {
background: var(--bg-color);
color: var(--text-color);
border: 2px solid var(--border-color);
}
.login-back-btn:hover {
background: var(--primary-color);
color: white;
border-color: var(--primary-color);
transform: translateY(-2px);
}
/* 分割线 */
.auth-divider {
text-align: center;
margin: 20px 0;
position: relative;
}
.auth-divider::before {
content: '';
position: absolute;
top: 50%;
left: 0;
right: 0;
height: 1px;
background: var(--border-color);
}
.auth-divider span {
background: var(--card-bg);
padding: 0 15px;
color: var(--light-text);
font-size: 0.9rem;
}
/* 默认用户提示 */
.default-users {
padding: 20px 30px;
background: var(--bg-color);
border-top: 1px solid var(--border-color);
}
.default-users h4 {
color: var(--text-color);
margin-bottom: 15px;
font-size: 1rem;
display: flex;
align-items: center;
gap: 8px;
}
.user-list {
display: flex;
flex-direction: column;
gap: 8px;
}
.user-item {
font-size: 0.9rem;
color: var(--light-text);
padding: 8px 12px;
background: white;
border-radius: 6px;
border: 1px solid var(--border-color);
}
.user-item strong {
color: var(--text-color);
}
/* 状态消息 */
.status-message {
position: absolute;
top: 20px;
right: 20px;
padding: 12px 20px;
border-radius: 8px;
font-size: 0.9rem;
font-weight: 500;
z-index: 1000;
animation: slideInRight 0.3s ease;
}
.status-message.success {
background: #d4edda;
color: #155724;
border: 1px solid #c3e6cb;
}
.status-message.error {
background: #f8d7da;
color: #721c24;
border: 1px solid #f5c6cb;
}
.status-message.info {
background: #d1ecf1;
color: #0c5460;
border: 1px solid #bee5eb;
}
/* 响应式设计 */
@media (max-width: 480px) {
.auth-container {
max-width: 100%;
}
.auth-header {
padding: 30px 20px 20px;
}
.auth-header h1 {
font-size: 1.5rem;
}
.auth-form {
padding: 20px;
}
.default-users {
padding: 15px 20px;
}
}
/* 动画 */
@keyframes fadeInUp {
from {
opacity: 0;
transform: translateY(30px);
}
to {
opacity: 1;
transform: translateY(0);
}
}
@keyframes slideInRight {
from {
opacity: 0;
transform: translateX(30px);
}
to {
opacity: 1;
transform: translateX(0);
}
}
/* 表单切换动画 */
.auth-form {
transition: var(--transition);
}
.auth-form.hidden {
opacity: 0;
transform: translateX(-20px);
pointer-events: none;
}
.auth-form.visible {
opacity: 1;
transform: translateX(0);
pointer-events: all;
}
|
2301_80743186/rust-agent-code
|
static/css/auth.css
|
CSS
|
unknown
| 7,631
|
/* 全局样式 */
* {
margin: 0;
padding: 0;
box-sizing: border-box;
}
:root {
--primary-color: #3498db;
--secondary-color: #2ecc71;
--accent-color: #e74c3c;
--text-color: #2c3e50;
--light-text: #7f8c8d;
--bg-color: #f8f9fa;
--card-bg: #ffffff;
--border-color: #ecf0f1;
--shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
--shadow-hover: 0 8px 15px rgba(0, 0, 0, 0.15);
--border-radius: 12px;
--transition: all 0.3s ease;
}
body, html {
height: 100%;
width: 100%;
}
body {
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, 'Helvetica Neue', Arial, sans-serif;
background: #f0f0f0;
min-height: 100vh;
color: var(--text-color);
line-height: 1.6;
}
/* 容器布局 */
.container {
max-width: none;
width: 100vw;
min-height: 100vh;
height: 100vh;
margin: 0;
padding: 0;
display: flex;
flex-direction: column;
}
/* 头部样式 */
.header {
text-align: center;
margin-bottom: 30px;
animation: fadeInDown 0.8s ease;
}
.header h1 {
font-size: 2.5rem;
font-weight: 700;
color: #1976d2;
margin-bottom: 10px;
text-shadow: 0 2px 4px rgba(0, 0, 0, 0.3);
}
.header p {
font-size: 1.1rem;
color: #1976d2;
font-weight: 300;
}
/* 主要内容区域 */
.main-content {
display: flex;
flex: 1 1 auto;
height: 100%;
min-height: 0;
}
/* 侧边栏 */
.sidebar {
position: fixed;
left: 0;
top: 0;
bottom: 0;
width: 270px;
z-index: 100;
height: 100vh;
overflow-y: auto;
border-radius: 0;
box-shadow: var(--shadow);
background: var(--card-bg);
padding: 25px 20px 25px 20px;
}
.sidebar h3 {
color: var(--primary-color);
margin-bottom: 20px;
font-size: 1.3rem;
border-bottom: 2px solid var(--border-color);
padding-bottom: 10px;
}
.sidebar-actions {
margin-top: 25px;
display: flex;
flex-direction: column;
gap: 10px;
}
.action-btn {
padding: 10px 15px;
background: var(--bg-color);
border: 1px solid var(--border-color);
border-radius: 8px;
color: var(--text-color);
font-size: 0.9rem;
cursor: pointer;
transition: var(--transition);
display: flex;
align-items: center;
gap: 8px;
}
.action-btn:hover {
background: var(--primary-color);
color: white;
border-color: var(--primary-color);
}
/* 用户信息 */
.user-info {
margin-bottom: 25px;
}
.user-info label {
display: block;
margin-bottom: 8px;
font-weight: 500;
color: var(--text-color);
}
.current-user {
background: var(--bg-color);
padding: 12px 15px;
border-radius: 8px;
border: 2px solid var(--border-color);
margin-bottom: 15px;
}
.current-user strong {
display: block;
color: var(--primary-color);
font-size: 1.1rem;
margin-bottom: 5px;
}
.user-role {
background: var(--primary-color);
color: white;
padding: 4px 8px;
border-radius: 12px;
font-size: 0.8rem;
font-weight: 500;
}
.user-status {
display: flex;
align-items: center;
gap: 8px;
margin-top: 10px;
font-size: 0.9rem;
color: var(--light-text);
}
.status-dot {
width: 8px;
height: 8px;
border-radius: 50%;
background: var(--light-text);
}
.status-dot.online {
background: var(--secondary-color);
box-shadow: 0 0 0 2px rgba(46, 204, 113, 0.2);
}
.user-info input {
width: 100%;
padding: 12px 15px;
border: 2px solid var(--border-color);
border-radius: 8px;
font-size: 1rem;
transition: var(--transition);
}
.user-info input:focus {
outline: none;
border-color: var(--primary-color);
box-shadow: 0 0 0 3px rgba(52, 152, 219, 0.1);
}
.user-actions {
margin-bottom: 25px;
}
.logout-btn {
background: var(--accent-color) !important;
color: white !important;
border-color: var(--accent-color) !important;
}
.logout-btn:hover {
background: #c0392b !important;
border-color: #c0392b !important;
}
/* 模型选择器 */
.model-selector {
margin-bottom: 25px;
padding: 15px;
background: linear-gradient(135deg, #f8f9fa 0%, #e9ecef 100%);
border-radius: var(--border-radius);
border: 1px solid var(--border-color);
}
.model-selector h4 {
margin-bottom: 15px;
color: var(--text-color);
font-size: 1.1rem;
display: flex;
align-items: center;
gap: 8px;
}
.model-selector h4 i {
color: var(--primary-color);
}
.model-options {
display: flex;
flex-direction: column;
gap: 10px;
}
.model-option {
display: flex;
align-items: center;
padding: 12px;
background: white;
border: 2px solid var(--border-color);
border-radius: 8px;
cursor: pointer;
transition: var(--transition);
position: relative;
}
.model-option:hover {
border-color: var(--primary-color);
background: #f0f7ff;
transform: translateX(3px);
box-shadow: 0 2px 8px rgba(52, 152, 219, 0.15);
}
.model-option input[type="radio"] {
margin-right: 12px;
width: 18px;
height: 18px;
cursor: pointer;
accent-color: var(--primary-color);
}
.model-option input[type="radio"]:checked + .model-name {
color: var(--primary-color);
font-weight: 600;
}
.model-option input[type="radio"]:checked ~ .model-desc {
color: var(--primary-color);
}
.model-option:has(input[type="radio"]:checked) {
border-color: var(--primary-color);
background: linear-gradient(135deg, #e3f2fd 0%, #f0f7ff 100%);
box-shadow: 0 2px 8px rgba(52, 152, 219, 0.2);
}
.model-name {
flex: 1;
display: flex;
align-items: center;
gap: 8px;
font-size: 0.95rem;
font-weight: 500;
color: var(--text-color);
transition: var(--transition);
}
.model-name i {
font-size: 1rem;
color: var(--primary-color);
}
.model-desc {
/* font-size: 0.8rem; */
font-size: 0.7rem;
color: var(--light-text);
transition: var(--transition);
}
/* 问题类型指示器 */
.question-types {
margin-bottom: 25px;
}
.question-types h4 {
margin-bottom: 15px;
color: var(--text-color);
font-size: 1.1rem;
}
.type-indicator {
display: flex;
flex-wrap: wrap;
gap: 8px;
}
.type-tag {
padding: 6px 12px;
border-radius: 20px;
font-size: 0.85rem;
font-weight: 500;
background: var(--bg-color);
color: var(--light-text);
border: 1px solid var(--border-color);
transition: var(--transition);
}
.type-tag.active {
background: var(--primary-color);
color: white;
border-color: var(--primary-color);
}
/* 聊天区域 */
.chat-area {
margin-left: 270px;
flex: 1 1 0;
min-width: 0;
max-width: calc(100vw - 270px);
height: 100vh;
display: flex;
flex-direction: column;
/* animation: fadeInRight 0.8s ease; */
}
/* 聊天头部 */
.chat-header {
padding: 20px 25px;
border-bottom: 1px solid var(--border-color);
background: linear-gradient(135deg, var(--primary-color), #2980b9);
color: white;
border-radius: var(--border-radius) var(--border-radius) 0 0;
}
.chat-header h3 {
font-size: 1.3rem;
margin-bottom: 5px;
}
.chat-header p {
opacity: 0.9;
font-size: 0.95rem;
}
/* 消息列表 */
.messages {
flex: 1 1 auto;
overflow-y: auto;
overflow-x: hidden;
padding-bottom: 16px;
padding-left: 20px;
padding-right: 20px;
}
.message {
margin-bottom: 20px;
animation: fadeInUp 0.5s ease;
}
.message.user {
text-align: right;
background: none !important;
box-shadow: none !important;
color: #222;
}
.message.assistant {
text-align: left;
}
.message-content {
background: #fff !important;
color: var(--text-color);
border-radius: 10px;
padding: 16px 18px;
box-shadow: 0 2px 8px rgba(0,0,0,0.04);
font-size: 1rem;
word-break: break-word;
word-wrap: break-word;
overflow-wrap: break-word;
max-width: 100%;
overflow-x: auto;
margin-bottom: 6px;
}
.message.user .message-content {
background: #f5f6fa !important;
color: #222 !important;
border-bottom-right-radius: 5px;
}
.message.assistant .message-content {
background: var(--bg-color);
color: var(--text-color);
border: 1px solid var(--border-color);
border-bottom-left-radius: 5px;
}
.message-time {
font-size: 0.8rem;
color: var(--light-text);
margin-top: 5px;
opacity: 0.7;
border: none;
background: none;
box-shadow: none;
}
/* 输入区域 */
.input-area {
position: sticky;
bottom: 0;
left: 0;
width: 100%;
background: var(--card-bg);
box-shadow: 0 -2px 8px rgba(0,0,0,0.04);
z-index: 10;
padding: 12px 20px 8px 20px;
}
.input-container {
display: flex;
gap: 15px;
align-items: flex-end;
}
.input-container textarea {
flex: 1;
padding: 15px;
border: 2px solid var(--border-color);
border-radius: 12px;
font-size: 1rem;
font-family: inherit;
resize: none;
min-height: 50px;
max-height: 120px;
transition: var(--transition);
}
.input-container textarea:focus {
outline: none;
border-color: var(--primary-color);
box-shadow: 0 0 0 3px rgba(52, 152, 219, 0.1);
}
.send-btn {
padding: 15px 25px;
background: var(--primary-color);
color: white;
border: none;
border-radius: 12px;
font-size: 1rem;
font-weight: 600;
cursor: pointer;
transition: var(--transition);
display: flex;
align-items: center;
gap: 8px;
}
.send-btn:hover {
background: #2980b9;
transform: translateY(-2px);
box-shadow: var(--shadow-hover);
}
.send-btn:disabled {
background: var(--light-text);
cursor: not-allowed;
transform: none;
box-shadow: none;
}
/* 加载动画 */
.loading {
display: flex;
align-items: center;
gap: 8px;
color: var(--light-text);
font-style: italic;
}
.spinner {
width: 20px;
height: 20px;
border: 2px solid var(--border-color);
border-top: 2px solid var(--primary-color);
border-radius: 50%;
animation: spin 1s linear infinite;
}
/* 状态指示器 */
.status-indicator {
display: flex;
align-items: center;
gap: 10px;
margin-bottom: 15px;
padding: 10px 15px;
background: var(--bg-color);
border-radius: 8px;
border-left: 4px solid var(--secondary-color);
}
.status-indicator.error {
border-left-color: var(--accent-color);
background: #fdf2f2;
}
.status-indicator.success {
border-left-color: var(--secondary-color);
background: #f0f9ff;
}
/* 响应式设计 */
@media (max-width: 900px) {
.sidebar {
position: fixed;
left: 0;
top: 0;
width: 200px;
padding: 15px 8px 15px 8px;
z-index: 200;
transform: translateX(-100%);
transition: transform 0.3s;
}
.sidebar.active {
transform: translateX(0);
}
.chat-area {
margin-left: 0;
}
/* 移动端模型选择器优化 */
.model-selector {
padding: 12px;
margin-bottom: 20px;
}
.model-selector h4 {
font-size: 1rem;
margin-bottom: 12px;
}
.model-option {
padding: 10px;
font-size: 0.9rem;
}
.model-name {
font-size: 0.9rem;
}
.model-desc {
font-size: 0.75rem;
}
}
/* 动画 */
@keyframes fadeInDown {
from {
opacity: 0;
transform: translateY(-30px);
}
to {
opacity: 1;
transform: translateY(0);
}
}
@keyframes fadeInLeft {
from {
opacity: 0;
transform: translateX(-30px);
}
to {
opacity: 1;
transform: translateX(0);
}
}
@keyframes fadeInRight {
from {
opacity: 0;
transform: translateX(30px);
}
to {
opacity: 1;
transform: translateX(0);
}
}
@keyframes fadeInUp {
from {
opacity: 0;
transform: translateY(20px);
}
to {
opacity: 1;
transform: translateY(0);
}
}
@keyframes spin {
0% { transform: rotate(0deg); }
100% { transform: rotate(360deg); }
}
/* 滚动条样式 */
.messages::-webkit-scrollbar {
width: 6px;
}
.messages::-webkit-scrollbar-track {
background: var(--bg-color);
border-radius: 3px;
}
.messages::-webkit-scrollbar-thumb {
background: var(--border-color);
border-radius: 3px;
}
.messages::-webkit-scrollbar-thumb:hover {
background: var(--light-text);
}
/* 代码块样式 */
.code-block {
margin: 15px 0;
border-radius: 8px;
overflow: hidden;
box-shadow: 0 2px 8px rgba(0,0,0,0.1);
max-width: 100%;
}
.code-header {
display: flex;
justify-content: space-between;
align-items: center;
padding: 8px 15px;
background: #2d3748;
color: white;
}
.language-tag {
font-size: 0.9rem;
font-weight: 500;
}
.copy-btn {
background: #4a5568;
color: white;
border: none;
padding: 4px 8px;
border-radius: 4px;
font-size: 0.8rem;
cursor: pointer;
transition: background 0.2s;
}
.copy-btn:hover {
background: #718096;
}
.code-block pre {
margin: 0;
padding: 15px;
background: #1e1e1e;
color: #d4d4d4;
overflow-x: auto;
font-family: 'Fira Code', 'Monaco', 'Consolas', monospace;
font-size: 0.9rem;
line-height: 1.6;
max-width: 100%;
word-break: break-all;
white-space: pre-wrap;
}
.code-block code {
background: none;
color: #d4d4d4;
padding: 0;
border-radius: 0;
font-size: inherit;
font-weight: 400;
text-shadow: none;
}
/* 确保代码高亮后的文字清晰可见 */
.code-block code.hljs {
color: #d4d4d4 !important;
background: transparent !important;
}
.code-block .hljs-keyword {
color: #569cd6 !important;
}
.code-block .hljs-string {
color: #ce9178 !important;
}
.code-block .hljs-comment {
color: #6a9955 !important;
}
.code-block .hljs-function {
color: #dcdcaa !important;
}
.code-block .hljs-number {
color: #b5cea8 !important;
}
.code-block .hljs-type {
color: #4ec9b0 !important;
}
/* 覆盖 Prism.js 的默认样式，解决代码显示模糊问题 */
.code-block code[class*="language-"],
.code-block pre[class*="language-"] {
color: #d4d4d4 !important;
/* background: #1e1e1e !important; */
background: #2d3748 !important;
text-shadow: none !important; /* 移除导致模糊的阴影 */
font-family: 'Fira Code', 'Monaco', 'Consolas', monospace !important;
font-size: 0.9rem !important;
line-height: 1.6 !important;
}
/* 覆盖 Prism.js 的 token 颜色 */
.code-block .token.cdata,
.code-block .token.comment,
.code-block .token.doctype,
.code-block .token.prolog {
color: #6a9955 !important; /* 注释 - 绿色 */
}
.code-block .token.punctuation {
color: #d4d4d4 !important; /* 标点符号 */
}
.code-block .token.boolean,
.code-block .token.constant,
.code-block .token.deleted,
.code-block .token.number,
.code-block .token.property,
.code-block .token.symbol,
.code-block .token.tag {
color: #569cd6 !important; /* 关键字 - 蓝色 */
}
.code-block .token.attr-name,
.code-block .token.builtin,
.code-block .token.char,
.code-block .token.inserted,
.code-block .token.selector,
.code-block .token.string {
color: #ce9178 !important; /* 字符串 - 橙色 */
}
.code-block .token.entity,
.code-block .token.operator,
.code-block .token.url {
color: #d4d4d4 !important;
background: transparent !important;
}
.code-block .token.atrule,
.code-block .token.attr-value,
.code-block .token.keyword {
color: #569cd6 !important; /* 关键字 - 蓝色 */
}
.code-block .token.class-name,
.code-block .token.function {
color: #dcdcaa !important; /* 函数 - 黄色 */
}
.code-block .token.important,
.code-block .token.regex,
.code-block .token.variable {
color: #ce9178 !important; /* 变量 - 橙色 */
}
/* 确保选中时的背景色清晰 */
.code-block code[class*="language-"]::selection,
.code-block code[class*="language-"]::-moz-selection,
.code-block pre[class*="language-"]::selection,
.code-block pre[class*="language-"]::-moz-selection {
text-shadow: none !important;
background: #264f78 !important; /* 选中时的背景色 */
color: #ffffff !important;
}
.code-block p {
margin: 0.8px !important; /* 仅代码块内的<p>生效 */
}
.inline-code {
background: #f7fafc;
color: #e53e3e;
padding: 2px 4px;
border-radius: 4px;
font-family: 'Fira Code', 'Monaco', 'Consolas', monospace;
font-size: 0.9em;
}
/* 图表容器 */
.mermaid-container {
margin: 20px 0;
border: 1px solid var(--border-color);
border-radius: 8px;
overflow: hidden;
background: white;
max-width: 100%;
}
.mermaid-header {
padding: 10px 15px;
background: #f7fafc;
border-bottom: 1px solid var(--border-color);
}
.diagram-type {
font-size: 0.9rem;
font-weight: 500;
color: #4a5568;
}
.mermaid-content {
padding: 20px;
text-align: center;
overflow-x: auto;
}
.mermaid {
display: inline-block;
max-width: 100%;
}
.mermaid-error {
color: #e53e3e;
padding: 10px;
background: #fed7d7;
border-radius: 4px;
font-size: 0.9rem;
}
/* 工具提示 */
.tooltip {
position: relative;
display: inline-block;
}
.tooltip .tooltiptext {
visibility: hidden;
width: 200px;
background-color: var(--text-color);
color: white;
text-align: center;
border-radius: 6px;
padding: 8px;
position: absolute;
z-index: 1;
bottom: 125%;
left: 50%;
margin-left: -100px;
opacity: 0;
transition: opacity 0.3s;
font-size: 0.85rem;
}
.tooltip:hover .tooltiptext {
visibility: visible;
opacity: 1;
}
.sidebar-toggle {
display: none;
position: fixed;
top: 18px;
left: 18px;
z-index: 300;
background: var(--primary-color);
color: #fff;
border: none;
border-radius: 8px;
padding: 10px 14px;
font-size: 1.3rem;
cursor: pointer;
box-shadow: var(--shadow);
transition: background 0.2s;
}
.sidebar-toggle:hover {
background: var(--secondary-color);
}
@media (max-width: 900px) {
.sidebar-toggle {
display: block;
}
}
/* 表格样式 */
.enhanced-table {
width: 100%;
border-collapse: collapse;
margin: 15px 0;
background: white;
border-radius: 8px;
overflow: hidden;
box-shadow: 0 2px 8px rgba(0,0,0,0.1);
max-width: 100%;
}
.enhanced-table th,
.enhanced-table td {
padding: 12px 15px;
text-align: left;
border-bottom: 1px solid #eee;
word-wrap: break-word;
max-width: 200px;
}
.enhanced-table th {
background: #f8f9fa;
font-weight: 600;
color: #2c3e50;
}
.enhanced-table tr:hover {
background: #f8f9fa;
}
/* 消息内容样式增强 */
.message-content h1,
.message-content h2,
.message-content h3 {
margin: 25px 0 15px 0;
color: var(--text-color);
font-weight: 600;
}
.message-content h1 {
font-size: 2rem;
border-bottom: 3px solid var(--primary-color);
padding-bottom: 8px;
margin-top: 0;
position: relative;
}
.message-content h1::before {
content: '';
position: absolute;
left: 0;
bottom: -3px;
width: 50px;
height: 3px;
background: var(--secondary-color);
}
.message-content h2 {
font-size: 1.6rem;
border-bottom: 2px solid var(--border-color);
padding-bottom: 5px;
margin-top: 30px;
position: relative;
padding-left: 15px;
}
.message-content h2::before {
content: '';
position: absolute;
left: 0;
top: 50%;
transform: translateY(-50%);
width: 4px;
height: 20px;
background: var(--primary-color);
border-radius: 2px;
}
.message-content h3 {
font-size: 1.4rem;
margin-top: 25px;
color: var(--primary-color);
border-left: 3px solid var(--secondary-color);
padding-left: 12px;
}
.message-content p {
margin: 15px 0;
line-height: 1.7;
color: #4a5568;
}
.message-content ul,
.message-content ol {
margin: 15px 0;
padding-left: 25px;
}
.message-content li {
margin: 8px 0;
line-height: 1.6;
color: #4a5568;
}
/* 层次化列表样式 */
.message-content ul li {
position: relative;
padding-left: 5px;
}
.message-content ul li::before {
content: '•';
color: var(--primary-color);
font-weight: bold;
position: absolute;
left: -15px;
}
/* 去除对ul li的所有特殊渲染，恢复为原生li小圆点 */
.message-content ul li,
.message-content ul li::before {
all: unset;
display: list-item;
color: inherit;
font-size: inherit;
font-weight: inherit;
margin: 0;
padding: 0;
}
/* 去除对消息内容中有序列表li的特殊样式，恢复原生数字 */
.message-content ol li,
.message-content ol li::before {
all: unset;
display: list-item;
color: inherit;
font-size: inherit;
font-weight: inherit;
margin: 0;
padding: 0;
}
.message-content strong {
color: var(--primary-color);
font-weight: 700;
background: linear-gradient(120deg, rgba(52, 152, 219, 0.1) 0%, rgba(52, 152, 219, 0.1) 100%);
padding: 2px 6px;
border-radius: 4px;
}
.message-content a {
color: var(--primary-color);
text-decoration: none;
border-bottom: 1px dotted var(--primary-color);
transition: all 0.3s ease;
}
.message-content a:hover {
color: var(--secondary-color);
border-bottom: 1px solid var(--secondary-color);
background: rgba(46, 204, 113, 0.1);
padding: 2px 4px;
border-radius: 4px;
}
/* 层次化内容容器 */
.message-content > div {
margin: 20px 0;
padding: 15px;
border-radius: 8px;
background: rgba(248, 249, 250, 0.5);
border-left: 4px solid var(--primary-color);
}
/* 层次化内容容器样式 */
.content-section {
margin: 25px 0;
padding: 20px;
border-radius: 12px;
background: linear-gradient(135deg, rgba(255, 255, 255, 0.9) 0%, rgba(248, 249, 250, 0.9) 100%);
box-shadow: 0 4px 15px rgba(0, 0, 0, 0.08);
border: 1px solid rgba(52, 152, 219, 0.1);
transition: all 0.3s ease;
}
.content-section:hover {
transform: translateY(-2px);
box-shadow: 0 8px 25px rgba(0, 0, 0, 0.12);
}
.main-section {
border-left: 6px solid var(--primary-color);
background: linear-gradient(135deg, rgba(52, 152, 219, 0.05) 0%, rgba(255, 255, 255, 0.95) 100%);
}
.sub-section {
border-left: 4px solid var(--secondary-color);
margin-left: 20px;
background: linear-gradient(135deg, rgba(46, 204, 113, 0.05) 0%, rgba(255, 255, 255, 0.95) 100%);
}
.section-title {
margin: 0 0 20px 0 !important;
padding: 0 !important;
border: none !important;
font-size: 1.8rem !important;
color: var(--primary-color) !important;
font-weight: 700 !important;
text-shadow: 0 1px 2px rgba(0, 0, 0, 0.1);
}
.sub-section .section-title {
font-size: 1.5rem !important;
color: var(--secondary-color) !important;
}
.section-subtitle {
margin: 20px 0 15px 0 !important;
padding: 0 !important;
border: none !important;
font-size: 1.3rem !important;
color: #2c3e50 !important;
font-weight: 600 !important;
border-bottom: 2px solid #ecf0f1 !important;
padding-bottom: 8px !important;
}
/* 层次化间距 */
.content-section > p:first-child {
margin-top: 0;
}
.content-section > p:last-child {
margin-bottom: 0;
}
/* 图标样式 */
.message-content h1::after,
.message-content h2::after {
content: attr(data-icon);
margin-left: 10px;
font-size: 0.8em;
opacity: 0.7;
}
/* 系统回复内容统一样式 */
.system-section {
border: 1.5px solid var(--border-color);
border-radius: 10px;
background: var(--card-bg);
margin: 24px 0;
padding: 18px 22px 18px 22px;
box-shadow: var(--shadow);
transition: var(--transition);
}
.system-section-title {
font-size: 1.15em;
font-weight: bold;
color: var(--primary-color);
margin-bottom: 12px;
display: flex;
align-items: center;
gap: 8px;
}
.system-section-title i {
color: var(--primary-color);
font-size: 1.1em;
}
.system-section-list {
margin-left: 22px;
margin-bottom: 0;
}
.system-section-list li {
margin-bottom: 8px;
line-height: 1.7;
font-size: 1em;
color: var(--text-color);
}
/* Mermaid关系图容器自适应更大，始终居中且最大化显示 */
.mermaid-container, .mermaid {
width: 100vw !important;
min-height: 70vh !important;
max-width: none !important;
overflow: auto !important;
background: #fff;
margin: 0 auto 24px auto;
display: flex !important;
justify-content: center;
align-items: center;
box-sizing: border-box;
}
.mermaid svg {
width: 90vw !important;
height: 70vh !important;
max-width: none !important;
display: block;
margin: 0 auto;
}
|
2301_80743186/rust-agent-code
|
static/css/style.css
|
CSS
|
unknown
| 24,969
|
// 知识解释智能体前端应用
class KnowledgeAgentApp {
constructor() {
this.currentUserId = '';
this.sessionId = '';
this.isLoading = false;
this.selectedModel = 'xinghe'; // 默认选择星河大模型
this.init();
}
init() {
this.bindEvents();
this.loadUserSession();
this.updateQuestionTypes();
this.showWelcomeMessage();
// 显示用户登录状态
this.showUserStatus();
// 加载多模态增强功能
this.loadMultimodalEnhancements();
}
bindEvents() {
// 用户ID输入
const userIdInput = document.getElementById('userId');
if (userIdInput) {
userIdInput.addEventListener('change', (e) => {
this.currentUserId = e.target.value;
this.sessionId = `session_${this.currentUserId}_${Date.now()}`;
this.saveUserSession();
});
}
// 消息输入
const messageInput = document.getElementById('messageInput');
const sendBtn = document.getElementById('sendBtn');
if (messageInput) {
messageInput.addEventListener('keypress', (e) => {
if (e.key === 'Enter' && !e.shiftKey) {
e.preventDefault();
this.sendMessage();
}
});
// 自动调整高度
messageInput.addEventListener('input', () => {
this.adjustTextareaHeight(messageInput);
});
}
if (sendBtn) {
sendBtn.addEventListener('click', () => {
this.sendMessage();
});
}
// 模型选择器事件
const modelOptions = document.querySelectorAll('input[name="model"]');
modelOptions.forEach(option => {
option.addEventListener('change', (e) => {
this.selectedModel = e.target.value;
this.showStatus(`已切换到: ${this.getModelName(this.selectedModel)}`, 'success');
});
});
// 清空聊天记录
const clearBtn = document.getElementById('clearChat');
if (clearBtn) {
clearBtn.addEventListener('click', () => {
this.clearChat();
});
}
// 导出聊天记录
const exportBtn = document.getElementById('exportChat');
if (exportBtn) {
exportBtn.addEventListener('click', () => {
this.exportChat();
});
}
}
async sendMessage() {
const messageInput = document.getElementById('messageInput');
const message = messageInput.value.trim();
if (!message) return;
// 添加用户消息
this.addMessage(message, 'user');
messageInput.value = '';
this.adjustTextareaHeight(messageInput);
// 显示加载状态
this.setLoading(true);
try {
// 调用后端API
const response = await this.callBackendAPI(message);
if (response.status === 'success') {
// 统一使用 renderEnhancedMarkdown 渲染，保持与新消息和历史消息一致的渲染效果
// 自动提取代码练习和综合案例并存入localStorage（只提取题目和步骤）
let code_practice = '';
let comprehensive_case = '';
// 提取代码练习两个题目
const codePracticeMatch = response.answer_markdown.match(/(代码练习[\s\S]*?)(?=(#|##|###|\*\*|🏆|\u{1F3C6}|综合案例|$))/u);
if (codePracticeMatch) {
// 匹配所有“练习1：...”和“练习2：...”
const exs = Array.from(codePracticeMatch[0].matchAll(/练习[12]：(.+?)(?=\n|$)/g));
code_practice = exs.map(e => e[0]).join('\n');
}
// 提取综合案例的案例要求和实现步骤
const comprehensiveCaseMatch = response.answer_markdown.match(/(综合案例[\s\S]*)/u);
if (comprehensiveCaseMatch) {
// 匹配“案例要求：...”和“实现步骤：...”
const req = comprehensiveCaseMatch[0].match(/案例要求：([\s\S]*?)(?=实现步骤|$)/);
const steps = comprehensiveCaseMatch[0].match(/实现步骤：([\s\S]*)/);
comprehensive_case = '';
if (req) comprehensive_case += '案例要求：' + req[1].trim() + '\n';
if (steps) comprehensive_case += '实现步骤：' + steps[1].trim();
}
// 调试：直接存储大模型原始内容，确保分析界面能读取
// 去除“实践练习”部分（支持多种格式）
let answerForAnalysis = response.answer_markdown
// Markdown标题格式（匹配### 实践练习等，兼容表情但不强制匹配）
.replace(/### ?[\s\S]*?(实践练习|调试练习|实践对比|开始实践)[\s\S]*?(?=\n###|\n##|\n#|$)/g, '')
// HTML格式（如fallback回答）
.replace(/<div class="system-section-title">.*?(实践练习|调试练习|实践对比|开始实践).*?<\/div>[\s\S]*?<\/p>/g, '');
localStorage.setItem('rust_examples', JSON.stringify({ code_practice: answerForAnalysis, comprehensive_case: answerForAnalysis }));
console.log('已存入rust_examples:', { code_practice: answerForAnalysis, comprehensive_case: answerForAnalysis });
// 直接传递 markdown 文本，让 addMessage 统一使用 renderEnhancedMarkdown 渲染
this.addMessage(response.answer_markdown, 'assistant', response.classification);
this.updateQuestionTypeIndicator(response.classification.label);
this.showStatus(`问题类型: ${response.classification.label} | 置信度: ${(response.classification.confidence * 100).toFixed(1)}%`, 'success');
} else {
this.addMessage(`抱歉，处理您的问题时出现错误：${response.message}`, 'assistant');
this.showStatus('处理失败', 'error');
}
} catch (error) {
console.error('API调用错误:', error);
this.addMessage('抱歉，网络连接出现问题，请稍后重试。', 'assistant');
this.showStatus('网络错误', 'error');
} finally {
this.setLoading(false);
}
}
async callBackendAPI(message) {
try {
const response = await fetch('/api/chat', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify({
user_id: this.currentUserId || 'anonymous',
message: message,
model: this.selectedModel // 发送选择的模型
})
});
if (!response.ok) {
throw new Error(`HTTP error! status: ${response.status}`);
}
const data = await response.json();
return data;
} catch (error) {
console.error('API调用错误:', error);
// 如果API调用失败，回退到模拟响应
return this.getMockResponse(message);
}
}
getMockResponse(message) {
return new Promise((resolve) => {
setTimeout(() => {
const mockResponse = {
status: 'success',
classification: {
label: this.detectQuestionType(message),
confidence: 0.85 + Math.random() * 0.15
},
answer_markdown: this.generateMockAnswer(message),
rendered_html: '<div>Mock HTML</div>',
context_length: Math.floor(Math.random() * 5) + 1
};
resolve(mockResponse);
}, 1000);
});
}
detectQuestionType(message) {
const lowerMessage = message.toLowerCase();
if (lowerMessage.includes('是什么') || lowerMessage.includes('定义') || lowerMessage.includes('概念')) {
return 'definition';
} else if (lowerMessage.includes('怎么') || lowerMessage.includes('如何') || lowerMessage.includes('使用')) {
return 'usage';
} else if (lowerMessage.includes('错误') || lowerMessage.includes('问题') || lowerMessage.includes('调试')) {
return 'error_debug';
} else if (lowerMessage.includes('区别') || lowerMessage.includes('不同') || lowerMessage.includes('比较')) {
return 'comparison';
} else {
return 'faq';
}
}
generateMockAnswer(question) {
const answers = {
definition: `## 概念定义
**${question.replace('是什么', '').replace('？', '')}**是Rust编程语言中的一个重要概念。
## 核心要点
- 这是Rust的核心特性之一
- 确保内存安全和线程安全
- 编译时检查，运行时零开销
## 示例代码
\`\`\`rust
// 示例代码
fn example() {
println!("这是一个示例");
}
\`\`\`
## 相关概念
- 所有权系统
- 借用检查器
- 生命周期管理`,
usage: `## 基本用法
以下是**${question.replace('怎么', '').replace('如何', '').replace('使用', '').replace('？', '')}**的基本用法：
## 代码示例
\`\`\`rust
fn main() {
// 基本用法示例
let result = example_function();
println!("结果: {}", result);
}
fn example_function() -> i32 {
42
}
\`\`\`
## 参数说明
- param1: 第一个参数的作用
- param2: 第二个参数的作用
## 最佳实践
1. 遵循Rust的命名约定
2. 使用适当的错误处理
3. 考虑性能影响`,
error_debug: `## 错误分析
您遇到的**${question.replace('错误', '').replace('问题', '').replace('？', '')}**通常是由于以下原因：
## 常见原因
- 借用检查器规则违反
- 生命周期不匹配
- 类型不匹配
## 解决方案
\`\`\`rust
// 错误代码
let mut v = vec![1, 2, 3];
let first = &v[0];
v.push(4); // 编译错误
// 正确代码
let mut v = vec![1, 2, 3];
v.push(4);
let first = &v[0]; // 正确
\`\`\`
## 调试技巧
1. 仔细阅读编译器错误信息
2. 使用 cargo check 进行静态检查
3. 逐步简化代码定位问题`,
comparison: `## 对比分析
**${question.replace('区别', '').replace('不同', '').replace('比较', '').replace('？', '')}**的主要差异：
## 核心差异
| 特性 | Rust | 其他语言 |
|------|------|----------|
| 内存管理 | 所有权系统 | 垃圾回收/手动管理 |
| 并发安全 | 编译时检查 | 运行时检查 |
| 性能 | 零开销抽象 | 可能有运行时开销 |
## 代码对比
\`\`\`rust
// Rust 示例
let s = String::from("hello");
// 所有权自动管理
\`\`\`
\`\`\`cpp
// C++ 示例
std::string s = "hello";
// 需要手动管理内存
\`\`\`
## 适用场景
- **Rust**: 系统编程、性能敏感应用
- **其他**: 快速原型、脚本编程`,
faq: `## 问题解答
关于**${question.replace('？', '')}**的详细解答：
## 背景说明
这是一个常见的问题，涉及到Rust的学习路径和最佳实践。
## 实践建议
1. 从官方文档开始学习
2. 多做练习项目
3. 参与社区讨论
## 学习资源
- [Rust官方文档](https://doc.rust-lang.org/)
- [Rust Book](https://doc.rust-lang.org/book/)
- [Rust by Example](https://doc.rust-lang.org/rust-by-example/)
## 扩展阅读
- 所有权系统详解
- 生命周期管理
- 错误处理最佳实践`
};
const questionType = this.detectQuestionType(question);
return answers[questionType] || answers.faq;
}
addMessage(content, sender, classification = null) {
const messagesContainer = document.querySelector('.messages');
const messageDiv = document.createElement('div');
messageDiv.className = `message ${sender}`;
const time = new Date().toLocaleTimeString();
let messageContent = content;
// 如果是助手消息，使用多模态渲染
if (sender === 'assistant') {
if (content.includes('<div class="code-block"') || content.includes('<div class="mermaid-container"')) {
messageContent = content;
} else {
messageContent = this.renderEnhancedMarkdown(content);
}
}
messageDiv.innerHTML = `
<div class="message-content">
${messageContent}
${classification ? `<div class="message-meta">
<small>类型: ${classification.label} | 置信度: ${(classification.confidence * 100).toFixed(1)}%</small>
</div>` : ''}
</div>
<div class="message-time">${time}</div>
`;
messagesContainer.appendChild(messageDiv);
messagesContainer.scrollTop = messagesContainer.scrollHeight;
if (sender === 'assistant') {
// 立即处理消息内容（代码高亮和Mermaid渲染）
this.processMessageContent(messageDiv);
}
}
renderEnhancedMarkdown(markdown) {
// 1. 用 marked 解析所有 Markdown
let html = marked.parse(markdown);
// 2. 处理 Mermaid 图表
html = html.replace(/```mermaid\s*\n([\s\S]*?)\n```/g, (match, code) => {
const id = `mermaid-${Date.now()}-${Math.random().toString(36).substr(2, 9)}`;
return `<div class="mermaid-container" id="${id}">
<div class="mermaid-header">
<span class="diagram-type">流程图</span>
</div>
<div class="mermaid-content">
<div class="mermaid" data-mermaid="${encodeURIComponent(code)}">
${code}
</div>
</div>
</div>`;
});
// 3. 处理 Rust 代码块
html = html.replace(/<pre><code class="language-rust">([\s\S]*?)<\/code><\/pre>/g, (match, code) => {
const id = `code-${Date.now()}-${Math.random().toString(36).substr(2, 9)}`;
return `<div class="code-block" data-language="rust" id="${id}">
<div class="code-header">
<span class="language-tag">rust</span>
<button class="copy-btn" onclick="copyCode('${id}')">复制</button>
</div>
<pre><code class="language-rust">${this.escapeHtml(code)}</code></pre>
</div>`;
});
// 4. 其他代码块
html = html.replace(/<pre><code class="language-([\w-]+)">([\s\S]*?)<\/code><\/pre>/g, (match, lang, code) => {
if (lang === 'rust') return match; // rust已处理
const id = `code-${Date.now()}-${Math.random().toString(36).substr(2, 9)}`;
return `<div class="code-block" data-language="${lang}" id="${id}">
<div class="code-header">
<span class="language-tag">${lang}</span>
<button class="copy-btn" onclick="copyCode('${id}')">复制</button>
</div>
<pre><code class="language-${lang}">${this.escapeHtml(code)}</code></pre>
</div>`;
});
// 5. 包裹到主容器
if (!html.includes('content-section')) {
html = `<div class="content-section main-section">${html}</div>`;
}
html += '</div>';
return html;
}
escapeHtml(text) {
const div = document.createElement('div');
div.textContent = text;
return div.innerHTML;
}
processMessageContent(messageDiv) {
// 处理代码高亮
const codeBlocks = messageDiv.querySelectorAll('pre code');
codeBlocks.forEach(block => {
if (window.hljs) {
hljs.highlightElement(block);
}
});
// 处理Mermaid图表 - 立即渲染
const mermaidDivs = messageDiv.querySelectorAll('.mermaid');
mermaidDivs.forEach((div, index) => {
if (window.mermaid) {
// 获取原始代码
const mermaidCode = div.getAttribute('data-mermaid')
? decodeURIComponent(div.getAttribute('data-mermaid'))
: div.textContent.trim();
if (!mermaidCode) return;
// 生成唯一ID
const mermaidId = `mermaid-${Date.now()}-${index}-${Math.random().toString(36).substr(2, 9)}`;
// 立即渲染Mermaid图表
mermaid.render(mermaidId, mermaidCode)
.then(({ svg }) => {
div.innerHTML = svg;
// Mermaid渲染后，svg已插入，添加缩放拖拽
const svgElem = div.querySelector('svg');
if (svgElem && window.svgPanZoom) {
const panZoomInstance = svgPanZoom(svgElem, {
zoomEnabled: true,
controlIconsEnabled: true,
fit: true,
center: true,
minZoom: 0.2,
maxZoom: 20
});
// 自动放大到合适的大小
panZoomInstance.zoom(2);
}
})
.catch(error => {
console.error('Mermaid渲染失败:', error);
div.innerHTML = `<div class="mermaid-error">图表渲染失败: ${error.message}</div>`;
});
}
});
}
renderMarkdown(markdown) {
// 简单的Markdown渲染（备用方法）
let html = markdown
// 标题
.replace(/^### (.*$)/gm, '<h3>$1</h3>')
.replace(/^## (.*$)/gm, '<h2>$1</h2>')
.replace(/^# (.*$)/gm, '<h1>$1</h1>')
// 粗体
.replace(/\*\*(.*?)\*\*/g, '<strong>$1</strong>')
// 代码块
.replace(/```rust\n([\s\S]*?)\n```/g, '<pre class="code-block"><code>$1</code></pre>')
.replace(/```([\s\S]*?)```/g, '<pre class="code-block"><code>$1</code></pre>')
// 行内代码
.replace(/`(.*?)`/g, '<code class="inline-code">$1</code>')
// 列表
.replace(/^\d+\. (.*$)/gm, '<li>$1</li>')
.replace(/^- (.*$)/gm, '<li>$1</li>')
// 链接
.replace(/\[(.*?)\]\((.*?)\)/g, '<a href="$2" target="_blank">$1</a>')
// 换行
.replace(/\n/g, '<br>');
// 处理列表
html = html.replace(/(<li>.*<\/li>)/gs, '<ul>$1</ul>');
return html;
}
setLoading(loading) {
this.isLoading = loading;
const sendBtn = document.getElementById('sendBtn');
const messageInput = document.getElementById('messageInput');
if (loading) {
sendBtn.disabled = true;
sendBtn.innerHTML = '<div class="spinner"></div> 处理中...';
messageInput.disabled = true;
} else {
sendBtn.disabled = false;
sendBtn.innerHTML = '发送';
messageInput.disabled = false;
}
}
showStatus(message, type = 'info') {
const statusContainer = document.querySelector('.status-indicator');
if (statusContainer) {
statusContainer.className = `status-indicator ${type}`;
statusContainer.innerHTML = `
<span>${type === 'error' ? '❌' : type === 'success' ? '✅' : 'ℹ️'}</span>
<span>${message}</span>
`;
statusContainer.style.display = 'flex';
// 3秒后自动隐藏
setTimeout(() => {
statusContainer.style.display = 'none';
}, 3000);
}
}
updateQuestionTypes() {
const types = ['definition', 'usage', 'error_debug', 'comparison', 'faq'];
const container = document.querySelector('.type-indicator');
if (container) {
container.innerHTML = types.map(type =>
`<span class="type-tag" data-type="${type}">${this.getTypeLabel(type)}</span>`
).join('');
}
}
updateQuestionTypeIndicator(activeType) {
const tags = document.querySelectorAll('.type-tag');
tags.forEach(tag => {
tag.classList.remove('active');
if (tag.dataset.type === activeType) {
tag.classList.add('active');
}
});
}
getTypeLabel(type) {
const labels = {
definition: '定义',
usage: '用法',
error_debug: '调试',
comparison: '对比',
faq: 'FAQ'
};
return labels[type] || type;
}
getModelName(model) {
const names = {
xinghe: '星河大模型',
gemini: 'Gemini',
openai: 'OpenAI',
deepseek: 'DeepSeek'
};
return names[model] || model;
}
adjustTextareaHeight(textarea) {
textarea.style.height = 'auto';
textarea.style.height = Math.min(textarea.scrollHeight, 120) + 'px';
}
showWelcomeMessage() {
const userName = this.currentUserId || '用户';
const welcomeMessage = `
## 欢迎使用Rust知识解释智能体！ 🤖
您好，**${userName}**！我是您的专属Rust编程助手，可以帮助您：
### 🎯 支持的问题类型
- **定义类**: "生命周期是什么？"
- **用法类**: "如何使用迭代器？"
- **调试类**: "这个编译错误怎么解决？"
- **对比类**: "Rust和C++有什么区别？"
- **FAQ类**: "Rust适合什么项目？"
### 💡 使用建议
1. 提出具体的Rust相关问题
2. 我会根据问题类型提供个性化解答
3. 支持多轮对话和上下文理解
4. 享受智能化的编程学习体验
### 🚀 开始提问
请在下方输入您的Rust相关问题，我会为您提供详细的解答！
`;
this.addMessage(welcomeMessage, 'assistant');
}
clearChat() {
const messagesContainer = document.querySelector('.messages');
messagesContainer.innerHTML = '';
this.showWelcomeMessage();
this.showStatus('聊天记录已清空', 'success');
}
exportChat() {
const messages = document.querySelectorAll('.message');
let exportText = 'Rust知识解释智能体 - 聊天记录\n';
exportText += '='.repeat(50) + '\n\n';
messages.forEach(message => {
const sender = message.classList.contains('user') ? '用户' : '智能体';
const content = message.querySelector('.message-content').textContent;
const time = message.querySelector('.message-time').textContent;
exportText += `[${time}] ${sender}:\n${content}\n\n`;
});
const blob = new Blob([exportText], { type: 'text/plain;charset=utf-8' });
const url = URL.createObjectURL(blob);
const a = document.createElement('a');
a.href = url;
a.download = `rust-chat-${new Date().toISOString().slice(0, 10)}.txt`;
a.click();
URL.revokeObjectURL(url);
this.showStatus('聊天记录已导出', 'success');
}
async clearChat() {
if (!this.currentUserId) return;
if (confirm('确定要清空所有聊天记录吗？此操作不可恢复。')) {
try {
const response = await fetch(`/api/session/${this.currentUserId}`, {
method: 'DELETE'
});
if (response.ok) {
// 清空前端消息显示
const messagesContainer = document.querySelector('.messages');
if (messagesContainer) {
messagesContainer.innerHTML = '';
}
this.showStatus('聊天记录已清空', 'success');
} else {
this.showStatus('清空失败', 'error');
}
} catch (error) {
console.error('清空聊天记录失败:', error);
this.showStatus('清空失败', 'error');
}
}
}
loadUserSession() {
// 从页面中获取用户ID
const userIdInput = document.getElementById('userId');
if (userIdInput && userIdInput.value) {
this.currentUserId = userIdInput.value;
this.sessionId = `session_${this.currentUserId}_${Date.now()}`;
} else {
// 如果没有用户ID，尝试从当前用户信息中获取
const currentUserElement = document.querySelector('.current-user strong');
if (currentUserElement) {
this.currentUserId = currentUserElement.textContent;
this.sessionId = `session_${this.currentUserId}_${Date.now()}`;
}
}
// 加载历史对话
this.loadChatHistory();
}
saveUserSession() {
if (this.currentUserId) {
localStorage.setItem('rustAgentUserId', this.currentUserId);
}
}
async loadChatHistory() {
if (!this.currentUserId) return;
try {
const response = await fetch(`/api/session/${this.currentUserId}`);
if (response.ok) {
const data = await response.json();
if (data.status === 'success' && data.data.context.length > 0) {
// 清空当前消息
const messagesContainer = document.querySelector('.messages');
if (messagesContainer) {
messagesContainer.innerHTML = '';
}
// 加载历史消息
data.data.context.forEach(turn => {
// 添加用户消息
this.addMessage(turn.question, 'user');
// 添加助手消息
this.addMessage(turn.answer, 'assistant', turn.classification);
});
// 滚动到底部
this.scrollToBottom();
this.showStatus(`已加载 ${data.data.context.length} 条历史消息`, 'success');
}
}
} catch (error) {
console.error('加载历史消息失败:', error);
}
}
showUserStatus() {
if (this.currentUserId) {
this.showStatus(`欢迎回来，${this.currentUserId}！系统已就绪`, 'success');
}
}
async loadMultimodalEnhancements() {
try {
// 加载多模态样式
const stylesResponse = await fetch('/api/multimodal/styles');
if (stylesResponse.ok) {
const stylesData = await stylesResponse.json();
if (stylesData.status === 'success') {
document.getElementById('multimodal-styles').textContent = stylesData.css;
}
}
// 加载多模态脚本
const scriptsResponse = await fetch('/api/multimodal/scripts');
if (scriptsResponse.ok) {
const scriptsData = await scriptsResponse.json();
if (scriptsData.status === 'success') {
document.getElementById('multimodal-scripts').textContent = scriptsData.javascript;
}
}
} catch (error) {
console.error('加载多模态增强功能失败:', error);
}
}
async renderMultimodalContent(markdownContent) {
try {
const response = await fetch('/api/render', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify({
markdown: markdownContent
})
});
if (response.ok) {
const data = await response.json();
if (data.status === 'success') {
// 处理Mermaid图表
this.processMermaidDiagrams(data.mermaid_diagrams);
// 处理代码高亮
this.processCodeBlocks(data.code_blocks);
return data.html;
}
}
} catch (error) {
console.error('多模态渲染失败:', error);
}
// 如果多模态渲染失败，回退到普通Markdown渲染
return this.renderMarkdown(markdownContent);
}
processMermaidDiagrams(diagrams) {
if (!diagrams || diagrams.length === 0) return;
// 延迟处理Mermaid图表，确保DOM已更新
setTimeout(() => {
diagrams.forEach(diagram => {
const container = document.getElementById(diagram.id);
if (container) {
mermaid.render(diagram.id, diagram.code).then(({ svg }) => {
container.innerHTML = svg;
// Mermaid渲染后，svg已插入，添加缩放拖拽
const svgElem = container.querySelector('svg');
if (svgElem && window.svgPanZoom) {
const panZoomInstance = svgPanZoom(svgElem, {
zoomEnabled: true,
controlIconsEnabled: true,
fit: true,
center: true,
minZoom: 0.2,
maxZoom: 10
});
// 自动放大到5倍
panZoomInstance.zoom(5);
}
}).catch(error => {
console.error('Mermaid渲染失败:', error);
container.innerHTML = `<div class="mermaid-error">图表渲染失败: ${error.message}</div>`;
});
}
});
}, 100);
}
scrollToBottom() {
const messagesContainer = document.querySelector('.messages');
if (messagesContainer) {
messagesContainer.scrollTop = messagesContainer.scrollHeight;
}
}
processCodeBlocks(codeBlocks) {
if (!codeBlocks || codeBlocks.length === 0) return;
// 延迟处理代码高亮，确保DOM已更新
setTimeout(() => {
codeBlocks.forEach(block => {
const container = document.getElementById(block.id);
if (container) {
const codeElement = container.querySelector('code');
if (codeElement) {
hljs.highlightElement(codeElement);
}
}
});
}, 100);
}
}
// 登出功能
function logout() {
if (confirm('确定要退出登录吗？')) {
window.location.href = '/logout';
}
}
// 复制代码功能
function copyCode(codeId) {
const codeBlock = document.getElementById(codeId);
if (!codeBlock) return;
const code = codeBlock.querySelector('code');
if (!code) return;
const textToCopy = code.textContent;
navigator.clipboard.writeText(textToCopy).then(() => {
const btn = codeBlock.querySelector('.copy-btn');
if (btn) {
const originalText = btn.textContent;
btn.textContent = '已复制!';
btn.style.background = '#48bb78';
setTimeout(() => {
btn.textContent = originalText;
btn.style.background = '#4a5568';
}, 2000);
}
}).catch(err => {
console.error('复制失败:', err);
alert('复制失败，请手动复制');
});
}
// 页面加载完成后初始化应用
document.addEventListener('DOMContentLoaded', () => {
window.app = new KnowledgeAgentApp();
});
// Markdown渲染+代码高亮+Mermaid渲染
function renderMarkdown(mdText) {
return marked.parse(mdText, {
highlight: function(code, lang) {
if (lang && hljs.getLanguage(lang)) {
return hljs.highlight(code, { language: lang }).value;
}
return code;
}
});
}
function renderMessage(mdText, container) {
// 1. 渲染Markdown
container.innerHTML = renderMarkdown(mdText);
// 2. 代码高亮
container.querySelectorAll('pre code').forEach((block) => {
hljs.highlightElement(block);
});
// 3. Mermaid 渲染
container.querySelectorAll('code.language-mermaid').forEach((block) => {
const parent = block.parentElement;
const mermaidDiv = document.createElement('div');
mermaidDiv.className = 'mermaid';
mermaidDiv.innerHTML = block.textContent;
parent.replaceWith(mermaidDiv);
});
if (window.mermaid) {
mermaid.init(undefined, container.querySelectorAll('.mermaid'));
}
}
// 移动端导航栏展开/收起
window.addEventListener('DOMContentLoaded', function() {
const sidebarToggle = document.getElementById('sidebarToggle');
const sidebar = document.querySelector('.sidebar');
if (sidebarToggle && sidebar) {
sidebarToggle.addEventListener('click', function() {
sidebar.classList.toggle('active');
});
// 点击主内容区时自动收起侧边栏（移动端）
document.querySelector('.chat-area')?.addEventListener('click', function() {
if (window.innerWidth <= 900) {
sidebar.classList.remove('active');
}
});
}
});
|
2301_80743186/rust-agent-code
|
static/js/app.js
|
JavaScript
|
unknown
| 34,578
|
// 认证页面JavaScript
class AuthApp {
constructor() {
this.defaultUsers = {
'admin': { password: '123456', role: 'admin', name: '管理员' },
'student': { password: '123456', role: 'student', name: '学生' },
'teacher': { password: '123456', role: 'teacher', name: '教师' }
};
this.init();
}
init() {
this.bindEvents();
this.loadSavedCredentials();
}
bindEvents() {
// 登录表单提交
const loginForm = document.getElementById('loginForm');
if (loginForm) {
loginForm.addEventListener('submit', (e) => {
e.preventDefault();
this.handleLogin();
});
}
// 注册表单提交
const registerForm = document.getElementById('registerForm');
if (registerForm) {
registerForm.addEventListener('submit', (e) => {
e.preventDefault();
this.handleRegister();
});
}
// 回车键提交
document.addEventListener('keypress', (e) => {
if (e.key === 'Enter') {
const activeForm = document.querySelector('.auth-form:not([style*="display: none"])');
if (activeForm) {
const submitBtn = activeForm.querySelector('button[type="submit"]');
if (submitBtn) {
submitBtn.click();
}
}
}
});
}
async handleLogin() {
const username = document.getElementById('username').value.trim();
const password = document.getElementById('password').value;
const rememberMe = document.getElementById('rememberMe').checked;
// 验证输入
if (!username || !password) {
this.showStatus('请填写用户名和密码', 'error');
return;
}
try {
// 调用后端登录API
const response = await fetch('/login', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify({
username: username,
password: password
})
});
const data = await response.json();
if (data.status === 'success') {
// 保存用户信息到本地存储（用于记住我功能）
if (rememberMe) {
const userInfo = {
username: username,
role: this.defaultUsers[username]?.role || 'user',
name: this.defaultUsers[username]?.name || username,
loginTime: new Date().toISOString()
};
localStorage.setItem('rustAgentUser', JSON.stringify(userInfo));
}
this.showStatus('登录成功，正在跳转...', 'success');
// 延迟跳转
setTimeout(() => {
window.location.href = data.redirect || '/dashboard';
}, 1000);
} else {
this.showStatus(data.message || '登录失败', 'error');
}
} catch (error) {
console.error('登录请求失败:', error);
// 如果API调用失败，回退到前端验证
if (this.validateUser(username, password)) {
this.showStatus('登录成功，正在跳转...', 'success');
setTimeout(() => {
window.location.href = '/dashboard';
}, 1000);
} else {
this.showStatus('用户名或密码错误', 'error');
}
}
}
handleRegister() {
const username = document.getElementById('regUsername').value.trim();
const email = document.getElementById('regEmail').value.trim();
const password = document.getElementById('regPassword').value;
const confirmPassword = document.getElementById('regConfirmPassword').value;
const agreeTerms = document.getElementById('agreeTerms').checked;
// 验证输入
if (!username || !email || !password || !confirmPassword) {
this.showStatus('请填写所有必填字段', 'error');
return;
}
if (password !== confirmPassword) {
this.showStatus('两次输入的密码不一致', 'error');
return;
}
if (password.length < 6) {
this.showStatus('密码长度至少6位', 'error');
return;
}
if (!agreeTerms) {
this.showStatus('请同意服务条款和隐私政策', 'error');
return;
}
// 检查用户名是否已存在
if (this.defaultUsers[username]) {
this.showStatus('用户名已存在', 'error');
return;
}
// 模拟注册成功
this.showStatus('注册成功！请使用新账户登录', 'success');
// 清空表单
document.getElementById('registerForm').reset();
// 切换到登录页面
setTimeout(() => {
this.showLogin();
}, 1500);
}
validateUser(username, password) {
const user = this.defaultUsers[username];
return user && user.password === password;
}
showStatus(message, type = 'info') {
const statusElement = document.getElementById('statusMessage');
if (statusElement) {
statusElement.textContent = message;
statusElement.className = `status-message ${type}`;
statusElement.style.display = 'block';
// 3秒后自动隐藏
setTimeout(() => {
statusElement.style.display = 'none';
}, 3000);
}
}
loadSavedCredentials() {
const savedUser = localStorage.getItem('rustAgentUser') || sessionStorage.getItem('rustAgentUser');
if (savedUser) {
try {
const userInfo = JSON.parse(savedUser);
document.getElementById('username').value = userInfo.username;
document.getElementById('rememberMe').checked = true;
} catch (e) {
console.error('解析保存的用户信息失败:', e);
}
}
}
}
// 全局函数
function showRegister() {
const loginForm = document.getElementById('loginForm');
const registerForm = document.getElementById('registerForm');
if (loginForm && registerForm) {
loginForm.style.display = 'none';
registerForm.style.display = 'block';
registerForm.classList.add('visible');
}
}
function showLogin() {
const loginForm = document.getElementById('loginForm');
const registerForm = document.getElementById('registerForm');
if (loginForm && registerForm) {
registerForm.style.display = 'none';
loginForm.style.display = 'block';
loginForm.classList.add('visible');
}
}
function togglePassword() {
const passwordInput = document.getElementById('password');
const toggleBtn = document.querySelector('.toggle-password i');
if (passwordInput.type === 'password') {
passwordInput.type = 'text';
toggleBtn.className = 'fas fa-eye-slash';
} else {
passwordInput.type = 'password';
toggleBtn.className = 'fas fa-eye';
}
}
function toggleRegPassword() {
const passwordInput = document.getElementById('regPassword');
const toggleBtn = document.querySelector('#regPassword + .toggle-password i');
if (passwordInput.type === 'password') {
passwordInput.type = 'text';
toggleBtn.className = 'fas fa-eye-slash';
} else {
passwordInput.type = 'password';
toggleBtn.className = 'fas fa-eye';
}
}
function toggleRegConfirmPassword() {
const passwordInput = document.getElementById('regConfirmPassword');
const toggleBtn = document.querySelector('#regConfirmPassword + .toggle-password i');
if (passwordInput.type === 'password') {
passwordInput.type = 'text';
toggleBtn.className = 'fas fa-eye-slash';
} else {
passwordInput.type = 'password';
toggleBtn.className = 'fas fa-eye';
}
}
// 页面加载完成后初始化
document.addEventListener('DOMContentLoaded', () => {
window.authApp = new AuthApp();
});
|
2301_80743186/rust-agent-code
|
static/js/auth.js
|
JavaScript
|
unknown
| 8,578
|
<!DOCTYPE html>
<html lang="zh-CN">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Rust代码分析 - Rust知识解释智能体</title>
<link rel="stylesheet" href="{{ url_for('static', filename='css/style.css') }}">
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css">
<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/highlight.js@11.8.0/styles/github.min.css">
<style>
body {
margin: 0;
padding: 0;
min-height: 100vh;
background: #f5f6fa;
font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
}
.layout {
display: flex;
min-height: 100vh;
}
.sidebar {
width: 420px;
background: #fff;
border-radius: 0 18px 18px 0;
box-shadow: 2px 0 16px rgba(52,152,219,0.08);
padding: 32px 24px 24px 24px;
display: flex;
flex-direction: column;
align-items: flex-start;
z-index: 2;
}
.sidebar h3 {
margin-top: 0;
color: #222;
font-size: 1.2rem;
display: flex;
align-items: center;
gap: 8px;
}
.sidebar .task-list {
margin-top: 24px;
width: 100%;
overflow-y: auto;
flex: 1;
}
.sidebar .task-list::-webkit-scrollbar {
width: 6px;
background: #f0f0f0;
}
.sidebar .task-list::-webkit-scrollbar-thumb {
background: #e0e6ed;
border-radius: 3px;
}
.main-content {
flex: 1;
display: flex;
justify-content: center;
align-items: flex-start;
padding: 48px 0;
}
.editor-card {
background: #fff;
border-radius: 18px;
box-shadow: 0 4px 24px rgba(52,152,219,0.10);
padding: 48px 60px 36px 36px; /* 缩小padding */
max-width: 1100px; /* 缩小最大宽度 */
width: 100%;
display: flex;
flex-direction: column;
align-items: center;
margin-left:300px; /* 缩小左边距 */
}
.editor-title {
font-size: 1.3rem;
color: #222;
font-weight: bold;
margin-bottom: 0;
display: flex;
align-items: center;
gap: 8px;
}
.blue-underline {
width: 200px;
height: 4px;
background: #4f8cff;
border-radius: 2px;
margin: 10px 0 24px 0;
}
#monaco-editor {
width: 100%;
min-height: 400px;
max-height:50vh;
border-radius: 10px;
border: 1.5px solid #e0e6ed;
box-shadow: 0 2px 8px rgba(52,152,219,0.08);
margin-bottom: 24px;
background: #181c24;
max-width: 1300px; /* 提高最大宽度 */
}
.button-group {
display: flex;
justify-content: center;
align-items: center;
gap: 18px;
margin-bottom: 18px;
width: 100%;
max-width: 1300px; /* 提高最大宽度 */
}
.submit-btn, .run-btn {
background: linear-gradient(90deg, #4f8cff 0%, #27ae60 100%);
color: #fff;
border: none;
border-radius: 14px;
padding: 12px 36px;
font-size: 1.08rem;
font-weight: 700;
cursor: pointer;
box-shadow: 0 2px 8px rgba(52,152,219,0.10);
transition: all 0.18s cubic-bezier(.4,1.3,.6,1);
margin: 0;
display: flex;
align-items: center;
gap: 8px;
letter-spacing: 0.5px;
}
.submit-btn:hover, .run-btn:hover {
background: linear-gradient(90deg, #27ae60 0%, #4f8cff 100%);
}
.run-result, .analysis-result {
background: #f8f9fa;
border-radius: 8px;
padding: 12px 10px;
min-height: 40px;
font-size: 0.98rem;
color: #222;
box-shadow: 0 2px 8px rgba(0,0,0,0.04);
white-space: pre-wrap;
word-break: break-all;
width: 100%;
margin-bottom: 0;
}
@media (max-width: 1000px) {
.sidebar { display: none; }
.main-content { padding: 12px 0; }
.editor-card { max-width: 98vw; padding: 16px 4vw; }
}
@media (max-width: 600px) {
.editor-title { font-size: 1.05rem; }
.blue-underline { width: 120px; }
.editor-card { padding: 8px 2vw; }
}
</style>
<script src="https://unpkg.com/monaco-editor@0.34.1/min/vs/loader.js"></script>
<script src="https://unpkg.com/mermaid@10.9.0/dist/mermaid.min.js"></script>
</head>
<body>
<div class="layout">
<div class="sidebar" id="examplesSidebar">
<button onclick="window.location.href='/dashboard'" style="margin-bottom: 18px; background: #4f8cff; color: #fff; border: none; border-radius: 8px; padding: 8px 22px; font-size: 1rem; font-weight: 600; cursor: pointer; box-shadow: 0 2px 8px rgba(52,152,219,0.10); transition: all 0.18s;">
← 返回问答界面
</button>
<h3><i class="fas fa-tasks"></i> 编程任务</h3>
<div class="task-list" id="examplesContent">
<p>从问答界面获取的例题和案例将显示在这里。</p>
</div>
</div>
<div class="main-content">
<div class="editor-card">
<div class="editor-title">
<i class="fas fa-code"></i> Rust 代码分析与在线运行
</div>
<div class="blue-underline"></div>
<div id="monaco-editor"></div>
<div class="button-group">
<button type="button" class="run-btn" id="runRustBtn"><i class="fas fa-play"></i> 运行</button>
<button type="button" class="submit-btn" id="analyzeBtn"><i class="fas fa-paper-plane"></i> 提交分析</button>
</div>
<div id="runResult" class="run-result" style="display:none;"></div>
<div id="analysisResult" class="analysis-result">分析结果将在此处展示</div>
</div>
</div>
</div>
<script src="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/js/all.min.js"></script>
<script src="https://cdn.jsdelivr.net/npm/marked/marked.min.js"></script>
<script>
let monacoEditor;
require.config({ paths: { 'vs': 'https://unpkg.com/monaco-editor@0.34.1/min/vs' }});
require(['vs/editor/editor.main'], function() {
monacoEditor = monaco.editor.create(document.getElementById('monaco-editor'), {
value: '// 在此输入您的Rust代码\nfn main() {\n println!("Hello, Rust!");\n}',
language: 'rust',
theme: 'vs-dark',
fontSize: 16,
minimap: { enabled: false },
automaticLayout: true
});
fetchAndDisplayExamples();
});
async function fetchAndDisplayExamples() {
// 优先从localStorage读取rust_examples
let examples = localStorage.getItem('rust_examples');
const container = document.getElementById('examplesContent');
function beautifyContent(raw) {
if (!raw) return '<div style="color:#888;">暂无编程任务。</div>';
let html = '';
// 练习部分
const exerciseMatches = Array.from(raw.matchAll(/练习[0-9]+[\s\S]*?(?=(练习[0-9]+|综合案例|$))/g));
exerciseMatches.forEach((match, idx) => {
let block = match[0].trim();
let lines = block.split('\n').filter(l => l.trim());
let title = lines[0] || `练习${idx+1}`;
let body = lines.slice(1).join('\n');
html += `<div class="task-card" style="background:#f8f9fa;border-radius:12px;padding:18px 18px 14px 18px;margin-bottom:18px;border:1.5px solid #e0e6ed;box-shadow:0 2px 8px #4f8cff11;">
<div class="task-title" style="font-weight:bold;color:#1976d2;font-size:1.13rem;margin-bottom:10px;letter-spacing:1px;">${title}</div>
<pre style="color:#234;font-size:1.08rem;line-height:1.85;background:#f4f6fb;border-radius:8px;border:none;margin:0;padding:12px 14px 10px 14px;white-space:pre-wrap;">${body}</pre>
</div>`;
});
// 综合案例部分
const caseMatch = raw.match(/综合案例[\s\S]*/);
if (caseMatch) {
let block = caseMatch[0].trim();
let lines = block.split('\n').filter(l => l.trim());
let title = lines[0] || '综合案例';
let body = lines.slice(1).join('\n');
html += `<div class="task-card" style="background:#fffbe6;border-radius:12px;padding:18px 18px 14px 18px;margin-bottom:18px;border:1.5px solid #ffe58f;box-shadow:0 2px 8px #faad1411;">
<div class="task-title" style="font-weight:bold;color:#faad14;font-size:1.13rem;margin-bottom:10px;letter-spacing:1px;">${title}</div>
<pre style="color:#8c6d1f;font-size:1.08rem;line-height:1.85;background:#fffdf3;border-radius:8px;border:none;margin:0;padding:12px 14px 10px 14px;white-space:pre-wrap;">${body}</pre>
</div>`;
}
return html || '<div style="color:#888;">暂无编程任务。</div>';
}
if (examples) {
try {
examples = JSON.parse(examples);
let content = examples.code_practice || '';
// 只展示“代码练习”及其后内容
let codePracticeIndex = content.indexOf('代码练习');
if (codePracticeIndex !== -1) {
content = content.substring(codePracticeIndex);
}
container.innerHTML = beautifyContent(content);
} catch(e) {
container.innerHTML = '<p style="color:#e74c3c;">编程任务加载失败</p>';
}
} else {
try {
const response = await fetch('/api/get_examples');
const data = await response.json();
if (data.status === 'success' && (data.data.examples.length > 0 || data.data.comprehensive_case)) {
let content = '';
if (data.data.examples.length > 0) {
content += data.data.examples.join('\n');
}
if (data.data.comprehensive_case) {
content += '\n' + data.data.comprehensive_case;
}
container.innerHTML = beautifyContent(content);
} else {
container.innerHTML = '<div style="text-align: center; color: #999; padding: 20px;"><i class="fas fa-info-circle"></i><br>当前没有相关的编程任务</div>';
}
} catch (error) {
console.error('获取编程任务失败:', error);
container.innerHTML = '<div style="text-align: center; color: #e74c3c; padding: 20px;"><i class="fas fa-exclamation-triangle"></i><br>加载编程任务失败，请稍后重试</div>';
}
}
}
// 运行按钮事件
document.addEventListener('DOMContentLoaded', function() {
const runBtn = document.getElementById('runRustBtn');
const runResultDiv = document.getElementById('runResult');
if (runBtn) {
runBtn.addEventListener('click', async function() {
runResultDiv.style.display = 'block';
runResultDiv.innerHTML = '<div style=\'font-weight:bold;color:#fff;background:#222;padding:6px 12px 4px 12px;border-radius:8px 8px 0 0;font-size:1rem;\'>运行结果</div>' +
'<pre id=\'runResultBox\' style=\'background:#181c24;color:#e8eaf6;padding:16px 14px 14px 14px;border-radius:0 0 8px 8px;margin:0;font-size:1.05rem;overflow-x:auto;\'>正在运行...</pre>';
const code = monacoEditor.getValue();
try {
const resp = await fetch('/api/run_rust_code', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({ code })
});
const data = await resp.json();
const resultBox = document.getElementById('runResultBox');
if (data.status === 'success') {
resultBox.textContent = (data.stdout && data.stdout.trim() ? data.stdout : '[无输出]') + (data.stderr ? ('\n[stderr]\n' + data.stderr) : '');
} else {
resultBox.textContent = (data.message || '运行失败') + (data.stderr ? ('\n' + data.stderr) : '');
}
} catch (e) {
const resultBox = document.getElementById('runResultBox');
resultBox.textContent = '运行出错: ' + e;
}
});
}
});
// 分析按钮事件
document.getElementById('analyzeBtn').onclick = async function() {
const analysisDiv = document.getElementById('analysisResult');
analysisDiv.innerHTML = '<span style="color:#888;">正在分析，请稍候...</span>';
const code = monacoEditor.getValue();
let examples = localStorage.getItem('rust_examples');
try {
const resp = await fetch('/api/analyze_rust_code', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({ code, examples })
});
const data = await resp.json();
if (data.status === 'success') {
let result = data.result || '';
// 每一块用小卡片包裹，标题为“1. 题目归属判断”等
function beautifyAnalysisSections(md) {
// 优化分块正则，支持多种常见大项标题格式
// 支持：### 1.、### 1、、### 一、、#### 1.、1. 、1、 、一、
const sectionRegex = /^(###|####)?\s*((\d+|[一二三四五六七八九十]+)[\.、])\s*[^\n]*$/gm;
let indices = [];
let match;
while ((match = sectionRegex.exec(md)) !== null) {
indices.push({ idx: match.index, title: match[0] });
}
let parts = [];
if (indices.length === 0) {
// 没有分块，整体渲染
let content = mdToOrderedList(md);
return `<div class='analysis-section-card' style='background:#fff;border-radius:8px;padding:18px 16px 14px 16px;margin-bottom:18px;border:1.5px solid #e0e6ed;box-shadow:0 2px 8px #4f8cff08;'>
<div class='analysis-section-title' style='font-weight:bold;color:#1976d2;font-size:1.08rem;margin-bottom:10px;'>代码分析结果</div>
<div class='analysis-section-content'>${content}</div>
</div>`;
}
for (let i = 0; i < indices.length; i++) {
let start = indices[i].idx;
let end = (i + 1 < indices.length) ? indices[i + 1].idx : md.length;
let sectionMd = md.slice(start, end).trim();
// 提取标题文本（保留数字和内容）
let titleLine = indices[i].title;
let titleText = titleLine.replace(/^(###|####)?\s*/, '');
// 去掉标题行再渲染内容，并去除内容中重复出现的标题（如1.题目归属判断等）
let sectionContentMd = sectionMd.replace(titleLine, '').trim();
// 去除内容开头的“1.题目归属判断”、“1、题目归属判断”、“一、题目归属判断”、“1. 正确性分析”、“**正确性分析**:”等
sectionContentMd = sectionContentMd.replace(/^(\s*[\d一二三四五六七八九十]+[\.、])?\s*(\*\*|__)?[\u4e00-\u9fa5A-Za-z0-9_（）()]+([:：\.]|\*\*|__)*\s*/u, '');
// 只对每个分块内容做分条转有序列表
let content = mdToOrderedList(sectionContentMd);
parts.push(`<div class='analysis-section-card' style='background:#fff;border-radius:8px;padding:18px 16px 14px 16px;margin-bottom:18px;border:1.5px solid #e0e6ed;box-shadow:0 2px 8px #4f8cff08;'>
<div class='analysis-section-title' style='font-weight:bold;color:#1976d2;font-size:1.08rem;margin-bottom:10px;'>${titleText}</div>
<div class='analysis-section-content'>${content}</div>
</div>`);
}
// 只返回分块卡片拼接
return parts.join('');
}
// 分点转有序列表函数，提升到外部作用域
function mdToOrderedList(md) {
const lines = md.split(/\r?\n/);
let inList = false;
let html = '';
let listBuffer = [];
for (let line of lines) {
if (/^([*\-•]|\d+[\.、])\s+/.test(line)) {
inList = true;
listBuffer.push(line.replace(/^([*\-•]|\d+[\.、])\s+/, ''));
} else {
if (inList) {
html += '<ol style="margin:0 0 0 22px;padding:0 0 0 8px;">' + listBuffer.map(item => `<li>${item}</li>`).join('') + '</ol>';
listBuffer = [];
inList = false;
}
html += line ? `<div>${line}</div>` : '<br>';
}
}
if (inList && listBuffer.length > 0) {
html += '<ol style="margin:0 0 0 22px;padding:0 0 0 8px;">' + listBuffer.map(item => `<li>${item}</li>`).join('') + '</ol>';
}
return html;
}
analysisDiv.innerHTML = beautifyAnalysisSections(result);
} else {
analysisDiv.innerHTML = '<span style="color:#e74c3c;">' + (data.message || '分析失败') + '</span>';
}
} catch (e) {
analysisDiv.innerHTML = '<span style="color:#e74c3c;">分析出错: ' + e + '</span>';
}
};
</script>
</body>
</html>
|
2301_80743186/rust-agent-code
|
templates/code_editor.html
|
HTML
|
unknown
| 19,290
|
<!DOCTYPE html>
<html lang="zh-CN">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Rust知识解释智能体</title>
<link rel="stylesheet" href="{{ url_for('static', filename='css/style.css') }}">
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/prism/1.29.0/themes/prism.min.css">
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css">
<script src="https://cdnjs.cloudflare.com/ajax/libs/prism/1.29.0/components/prism-core.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/prism/1.29.0/plugins/autoloader/prism-autoloader.min.js"></script>
<script src="https://cdn.jsdelivr.net/npm/mermaid/dist/mermaid.min.js"></script>
<!-- Markdown 渲染 -->
<script src="https://cdn.jsdelivr.net/npm/marked/marked.min.js"></script>
<!-- 代码高亮 -->
<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/highlight.js@11.8.0/styles/github.min.css">
<script src="https://cdn.jsdelivr.net/npm/highlight.js@11.8.0/lib/highlight.min.js"></script>
<script src="https://cdn.jsdelivr.net/npm/highlight.js@11.8.0/lib/languages/rust.min.js"></script>
<!-- 多模态增强样式 -->
<style id="multimodal-styles"></style>
</head>
<body>
<div class="container">
<!-- 移动端汉堡菜单按钮 -->
<button class="sidebar-toggle" id="sidebarToggle" aria-label="展开/收起导航栏">
<i class="fas fa-bars"></i>
</button>
<!-- 头部 -->
<header class="header">
<h1><i class="fas fa-robot"></i> Rust知识解释智能体</h1>
<p>智能问答 · 多轮对话 · 个性化讲解 · 多模态展示</p>
</header>
<!-- 主要内容区域 -->
<main class="main-content">
<!-- 侧边栏 -->
<aside class="sidebar">
<h3><i class="fas fa-user"></i> 用户信息</h3>
<div class="user-info">
<label>当前用户</label>
<div class="current-user">
<strong>{{ user.user_name }}</strong>
<span class="user-role">{{ user.user_role }}</span>
</div>
<input type="text" id="userId" value="{{ user.user_id }}" style="display: none;">
<div class="user-status">
<span class="status-dot online"></span>
<span>已登录</span>
</div>
</div>
<div class="user-actions">
<button onclick="logout()" class="action-btn logout-btn">
<i class="fas fa-sign-out-alt"></i> 退出登录
</button>
</div>
<div class="model-selector">
<h4><i class="fas fa-brain"></i> 选择AI模型</h4>
<div class="model-options">
<label class="model-option">
<input type="radio" name="model" value="xinghe" checked>
<span class="model-name">
<i class="fas fa-star"></i> 星河大模型
</span>
<span class="model-desc">默认推荐</span>
</label>
<label class="model-option">
<input type="radio" name="model" value="gemini">
<span class="model-name">
<i class="fas fa-gem"></i> Gemini
</span>
<span class="model-desc">Google AI</span>
</label>
<label class="model-option">
<input type="radio" name="model" value="openai">
<span class="model-name">
<i class="fas fa-robot"></i> OpenAI
</span>
<span class="model-desc">GPT模型</span>
</label>
<label class="model-option">
<input type="radio" name="model" value="deepseek">
<span class="model-name">
<i class="fas fa-rocket"></i> DeepSeek
</span>
<span class="model-desc">国产大模型</span>
</label>
</div>
</div>
<div class="question-types">
<h4><i class="fas fa-tags"></i> 问题类型</h4>
<div class="type-indicator">
<span class="type-tag" data-type="definition">定义</span>
<span class="type-tag" data-type="usage">用法</span>
<span class="type-tag" data-type="error_debug">调试</span>
<span class="type-tag" data-type="comparison">对比</span>
<span class="type-tag" data-type="faq">FAQ</span>
</div>
</div>
<div class="sidebar-actions">
<button id="codeAnalysis" class="action-btn" onclick="window.location.href='http://127.0.0.1:5000/code_editor'">
<i class="fas fa-code"></i> 例题练习
</button>
<button id="clearChat" class="action-btn">
<i class="fas fa-trash"></i> 清空聊天
</button>
<button id="exportChat" class="action-btn">
<i class="fas fa-download"></i> 导出记录
</button>
</div>
<div class="status-indicator" style="display: none;">
<span>ℹ️</span>
<span>系统就绪</span>
</div>
</aside>
<!-- 聊天区域 -->
<section class="chat-area">
<!-- 聊天头部 -->
<div class="chat-header">
<h3><i class="fas fa-comments"></i> 智能对话</h3>
<p>与AI助手进行Rust编程知识交流</p>
</div>
<!-- 消息列表 -->
<div class="messages">
<!-- 消息将在这里动态添加 -->
</div>
<!-- 输入区域 -->
<div class="input-area">
<div class="input-container">
<textarea
id="messageInput"
placeholder="请输入您的Rust相关问题... (按Enter发送，Shift+Enter换行)"
rows="1"
></textarea>
<button id="sendBtn" class="send-btn">
<i class="fas fa-paper-plane"></i>
发送
</button>
</div>
</div>
</section>
</main>
</div>
<!-- JavaScript -->
<script src="{{ url_for('static', filename='js/app.js') }}"></script>
<!-- 多模态增强脚本 -->
<script id="multimodal-scripts"></script>
<!-- 初始化Mermaid -->
<script>
mermaid.initialize({
startOnLoad: true,
theme: 'default',
flowchart: {
useMaxWidth: true,
htmlLabels: true
}
});
</script>
<!-- svg-pan-zoom CDN，必须在app.js后引入 -->
<script src="https://cdn.jsdelivr.net/npm/svg-pan-zoom@3.6.1/dist/svg-pan-zoom.min.js"></script>
</body>
</html>
|
2301_80743186/rust-agent-code
|
templates/index.html
|
HTML
|
unknown
| 7,946
|
<!DOCTYPE html>
<html lang="zh-CN">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>登录 - Rust知识解释智能体</title>
<link rel="stylesheet" href="{{ url_for('static', filename='css/auth.css') }}">
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css">
</head>
<body>
<div class="auth-container">
<div class="auth-card">
<!-- 头部 -->
<div class="auth-header">
<h1><i class="fas fa-robot"></i> Rust知识解释智能体</h1>
<p>智能问答 · 多轮对话 · 个性化讲解</p>
</div>
<!-- 登录表单 -->
<form id="loginForm" class="auth-form">
<div class="form-group">
<label for="username">
<i class="fas fa-user"></i> 用户名
</label>
<input
type="text"
id="username"
name="username"
placeholder="请输入用户名"
value="admin"
required
>
</div>
<div class="form-group">
<label for="password">
<i class="fas fa-lock"></i> 密码
</label>
<div class="password-input">
<input
type="password"
id="password"
name="password"
placeholder="请输入密码"
value="123456"
required
>
<button type="button" class="toggle-password" onclick="togglePassword()">
<i class="fas fa-eye"></i>
</button>
</div>
</div>
<div class="form-group">
<label class="checkbox-label">
<input type="checkbox" id="rememberMe" checked>
<span class="checkmark"></span>
记住我
</label>
</div>
<button type="submit" class="auth-btn login-btn">
<i class="fas fa-sign-in-alt"></i>
登录
</button>
<div class="auth-divider">
<span>或者</span>
</div>
<button type="button" class="auth-btn register-btn" onclick="showRegister()">
<i class="fas fa-user-plus"></i>
注册新账户
</button>
</form>
<!-- 注册表单 -->
<form id="registerForm" class="auth-form" style="display: none;">
<div class="form-group">
<label for="regUsername">
<i class="fas fa-user"></i> 用户名
</label>
<input
type="text"
id="regUsername"
name="username"
placeholder="请输入用户名"
required
>
</div>
<div class="form-group">
<label for="regEmail">
<i class="fas fa-envelope"></i> 邮箱
</label>
<input
type="email"
id="regEmail"
name="email"
placeholder="请输入邮箱"
required
>
</div>
<div class="form-group">
<label for="regPassword">
<i class="fas fa-lock"></i> 密码
</label>
<div class="password-input">
<input
type="password"
id="regPassword"
name="password"
placeholder="请输入密码"
required
>
<button type="button" class="toggle-password" onclick="toggleRegPassword()">
<i class="fas fa-eye"></i>
</button>
</div>
</div>
<div class="form-group">
<label for="regConfirmPassword">
<i class="fas fa-lock"></i> 确认密码
</label>
<div class="password-input">
<input
type="password"
id="regConfirmPassword"
name="confirmPassword"
placeholder="请再次输入密码"
required
>
<button type="button" class="toggle-password" onclick="toggleRegConfirmPassword()">
<i class="fas fa-eye"></i>
</button>
</div>
</div>
<div class="form-group">
<label class="checkbox-label">
<input type="checkbox" id="agreeTerms" required>
<span class="checkmark"></span>
我同意 <a href="#" class="terms-link">服务条款</a> 和 <a href="#" class="terms-link">隐私政策</a>
</label>
</div>
<button type="submit" class="auth-btn register-submit-btn">
<i class="fas fa-user-plus"></i>
注册
</button>
<div class="auth-divider">
<span>或者</span>
</div>
<button type="button" class="auth-btn login-back-btn" onclick="showLogin()">
<i class="fas fa-sign-in-alt"></i>
返回登录
</button>
</form>
<!-- 默认用户提示 -->
<div class="default-users">
<h4><i class="fas fa-info-circle"></i> 默认用户</h4>
<div class="user-list">
<div class="user-item">
<strong>管理员:</strong> admin / 123456
</div>
<div class="user-item">
<strong>学生:</strong> student / 123456
</div>
<div class="user-item">
<strong>教师:</strong> teacher / 123456
</div>
</div>
</div>
<!-- 状态提示 -->
<div id="statusMessage" class="status-message" style="display: none;"></div>
</div>
</div>
<script src="{{ url_for('static', filename='js/auth.js') }}"></script>
</body>
</html>
|
2301_80743186/rust-agent-code
|
templates/login.html
|
HTML
|
unknown
| 7,285
|
<!DOCTYPE html>
<html lang="zh-CN">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Rust知识解释</title>
<script src="https://cdn.jsdelivr.net/npm/mermaid/dist/mermaid.min.js"></script>
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/prism/1.29.0/themes/prism.min.css">
<script src="https://cdnjs.cloudflare.com/ajax/libs/prism/1.29.0/components/prism-core.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/prism/1.29.0/plugins/autoloader/prism-autoloader.min.js"></script>
<style>
body {
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
line-height: 1.6;
color: #333;
max-width: 800px;
margin: 0 auto;
padding: 20px;
background-color: #f8f9fa;
}
.container {
background: white;
border-radius: 8px;
box-shadow: 0 2px 10px rgba(0,0,0,0.1);
overflow: hidden;
}
.content {
padding: 30px;
}
h1, h2, h3 {
color: #2c3e50;
margin-top: 30px;
margin-bottom: 15px;
}
h1 {
font-size: 2em;
border-bottom: 3px solid #3498db;
padding-bottom: 10px;
}
h2 {
font-size: 1.5em;
border-bottom: 2px solid #ecf0f1;
padding-bottom: 8px;
}
h3 {
font-size: 1.2em;
color: #34495e;
}
p {
margin-bottom: 15px;
text-align: justify;
}
.code-block {
background: #f8f9fa;
border: 1px solid #e9ecef;
border-radius: 6px;
padding: 15px;
margin: 15px 0;
overflow-x: auto;
font-family: 'Fira Code', 'Monaco', 'Consolas', monospace;
font-size: 14px;
line-height: 1.4;
}
.inline-code {
background: #f1f3f4;
padding: 2px 6px;
border-radius: 4px;
font-family: 'Fira Code', monospace;
font-size: 0.9em;
color: #d73a49;
}
.mermaid {
text-align: center;
margin: 20px 0;
padding: 20px;
background: #f8f9fa;
border-radius: 6px;
}
li {
margin-bottom: 8px;
}
strong {
color: #2c3e50;
font-weight: 600;
}
em {
color: #7f8c8d;
font-style: italic;
}
@media (max-width: 768px) {
body {
padding: 10px;
}
.content {
padding: 20px;
}
h1 {
font-size: 1.5em;
}
h2 {
font-size: 1.3em;
}
}
</style>
</head>
<body>
<div class="container">
<div class="content">
<br><h1>Rust生命周期详解</h1><br><br><h2>概念定义</h2><br><strong>生命周期</strong>是Rust中引用保持有效的作用域。<br><br><h2>示例代码</h2><br><pre class="code-block rust"><code>fn longest<'a>(x: &'a str, y: &'a str) -> &'a str {<br> if x.len() > y.len() { x } else { y }<br>}</code></pre><br><br><h2>流程图</h2><br><pre class="code-block mermaid"><code>graph TD<br> A[创建引用] --> B[生命周期开始]<br> B --> C[使用引用]<br> C --> D[生命周期结束]<br> D --> E[引用失效]</code></pre><br><br><h2>关键要点</h2><br><li>生命周期确保引用安全</li><br><li>编译器自动推断生命周期</li><br><li>显式标注用于复杂情况</li><br>
</div>
</div>
<script>
mermaid.initialize({ startOnLoad: true });
Prism.highlightAll();
</script>
</body>
</html>
|
2301_80743186/rust-agent-code
|
test_output.html
|
HTML
|
unknown
| 4,149
|
import tkinter as tk
from tkinter import ttk
class ColumnSelector:
def __init__(self, parent, columns, column_types, title, callback):
self.callback = callback
self.selected_columns = []
self.window = tk.Toplevel(parent)
self.window.title(title)
self.window.geometry('300x400')
# 创建说明标签
ttk.Label(self.window, text="选择需要处理的列：").pack(pady=10)
# 创建列表框和滚动条
frame = ttk.Frame(self.window)
frame.pack(fill=tk.BOTH, expand=True, padx=10)
scrollbar = ttk.Scrollbar(frame)
scrollbar.pack(side=tk.RIGHT, fill=tk.Y)
self.listbox = tk.Listbox(frame, selectmode=tk.MULTIPLE, yscrollcommand=scrollbar.set)
self.listbox.pack(side=tk.LEFT, fill=tk.BOTH, expand=True)
scrollbar.config(command=self.listbox.yview)
# 添加列名到列表框
for col in columns:
col_type = column_types[col]
self.listbox.insert(tk.END, f"{col} ({col_type})")
# 创建按钮框架
button_frame = ttk.Frame(self.window)
button_frame.pack(fill=tk.X, padx=10, pady=10)
ttk.Button(button_frame, text="确定", command=self.on_confirm).pack(side=tk.LEFT, padx=10)
ttk.Button(button_frame, text="取消", command=self.window.destroy).pack(side=tk.LEFT)
def on_confirm(self):
# 获取选中的列名（去除类型信息）
self.selected_columns = [self.listbox.get(i).split(' (')[0]
for i in self.listbox.curselection()]
self.callback(self.selected_columns)
self.window.destroy()
class ParameterDialog:
def __init__(self, parent, params, title, callback):
self.callback = callback
self.params = params
self.values = {}
self.window = tk.Toplevel(parent)
self.window.title(title)
self.window.geometry('400x300')
# 创建主框架
main_frame = ttk.Frame(self.window)
main_frame.pack(fill=tk.BOTH, expand=True, padx=10, pady=10)
# 创建参数输入区域
for param_name, param_info in params.items():
frame = ttk.Frame(main_frame)
frame.pack(fill=tk.X, pady=5)
ttk.Label(frame, text=param_info['label']).pack(side=tk.LEFT)
if param_info['type'] == 'choice':
var = tk.StringVar(value=param_info['default'])
combo = ttk.Combobox(frame, textvariable=var, values=param_info['choices'])
combo.pack(side=tk.RIGHT, fill=tk.X, expand=True)
self.values[param_name] = var
elif param_info['type'] == 'int':
var = tk.IntVar(value=param_info['default'])
spin = ttk.Spinbox(frame, from_=param_info['min'], to=param_info['max'],
textvariable=var)
spin.pack(side=tk.RIGHT, fill=tk.X, expand=True)
self.values[param_name] = var
elif param_info['type'] == 'str':
var = tk.StringVar(value=param_info['default'])
entry = ttk.Entry(frame, textvariable=var)
entry.pack(side=tk.RIGHT, fill=tk.X, expand=True)
self.values[param_name] = var
# 创建按钮区域
button_frame = ttk.Frame(self.window)
button_frame.pack(fill=tk.X, padx=10, pady=10)
ttk.Button(button_frame, text="确定", command=self.on_confirm).pack(side=tk.LEFT, padx=10)
ttk.Button(button_frame, text="取消", command=self.window.destroy).pack(side=tk.LEFT)
def on_confirm(self):
result = {param_name: var.get() for param_name, var in self.values.items()}
self.callback(result)
self.window.destroy()
|
2301_80863610/Undoom
|
Excel格式化工具/src/components.py
|
Python
|
unknown
| 3,799
|
import pandas as pd
import numpy as np
import logging
from datetime import datetime
class DataHandler:
def __init__(self):
self.df = None
self.operation_history = []
self.redo_history = []
def load_excel(self, file_path):
"""加载Excel文件并验证格式"""
try:
file_ext = file_path.lower().split('.')[-1]
if file_ext not in ['xlsx', 'xls']:
raise ValueError('不支持的文件格式，请使用.xlsx或.xls格式的Excel文件')
self.df = pd.read_excel(file_path)
return self.df
except Exception as e:
logging.error(f'加载Excel文件失败: {str(e)}')
raise
def save_excel(self, file_path):
"""保存Excel文件"""
try:
self.df.to_excel(file_path, index=False)
logging.info(f'文件已保存: {file_path}')
except Exception as e:
logging.error(f'保存Excel文件失败: {str(e)}')
raise
def get_statistics(self):
"""获取数据统计信息"""
return {
'row_count': len(self.df),
'column_count': len(self.df.columns),
'null_count': self.df.isnull().sum().sum()
}
def get_column_types(self):
"""获取列数据类型"""
return self.df.dtypes
def remove_spaces(self, columns):
"""删除指定列的空格"""
for col in columns:
if self.df[col].dtype == object:
self.df[col] = self.df[col].str.strip()
return self.df
def normalize_case(self, case_type, columns):
"""统一大小写"""
for col in columns:
if self.df[col].dtype == object:
if case_type == 'lower':
self.df[col] = self.df[col].str.lower()
elif case_type == 'upper':
self.df[col] = self.df[col].str.upper()
elif case_type == 'title':
self.df[col] = self.df[col].str.title()
return self.df
def format_numbers(self, decimal_places, columns):
"""格式化数字"""
for col in columns:
if pd.api.types.is_numeric_dtype(self.df[col]):
self.df[col] = self.df[col].round(decimal_places)
return self.df
def format_dates(self, date_format, columns):
"""格式化日期"""
for col in columns:
if pd.api.types.is_datetime64_any_dtype(self.df[col]):
self.df[col] = self.df[col].dt.strftime(date_format)
return self.df
def remove_special_chars(self, pattern, columns):
"""删除特殊字符"""
for col in columns:
if self.df[col].dtype == object:
self.df[col] = self.df[col].str.replace(pattern, '', regex=True)
return self.df
def fill_empty_values(self, method, value=None, columns=None):
"""填充空值"""
if columns is None:
columns = self.df.columns
for col in columns:
if method == 'value':
self.df[col].fillna(value, inplace=True)
elif method == 'mean':
if pd.api.types.is_numeric_dtype(self.df[col]):
self.df[col].fillna(self.df[col].mean(), inplace=True)
elif method == 'median':
if pd.api.types.is_numeric_dtype(self.df[col]):
self.df[col].fillna(self.df[col].median(), inplace=True)
elif method == 'mode':
self.df[col].fillna(self.df[col].mode()[0], inplace=True)
elif method == 'ffill':
self.df[col].fillna(method='ffill', inplace=True)
elif method == 'bfill':
self.df[col].fillna(method='bfill', inplace=True)
return self.df
def remove_empty_rows(self):
"""删除空行
删除所有单元格都为空值（包括NaN、None、空字符串）的行
"""
try:
# 检查每个单元格是否为空（包括NaN、None和空字符串）
is_empty = self.df.apply(lambda x: x.isna() | (x.astype(str).str.strip() == ''))
# 找出所有单元格都为空的行
empty_rows = is_empty.all(axis=1)
# 删除空行
self.df = self.df[~empty_rows]
logging.info(f'已删除 {empty_rows.sum()} 个空行')
return self.df
except Exception as e:
logging.error(f'删除空行失败: {str(e)}')
raise
|
2301_80863610/Undoom
|
Excel格式化工具/src/data_handler.py
|
Python
|
unknown
| 4,592
|
import tkinter as tk
from tkinter import ttk, filedialog, messagebox
import logging
import os
from datetime import datetime
from data_handler import DataHandler
from components import ColumnSelector, ParameterDialog
# 配置日志
logging.basicConfig(
filename='excel_cleaner.log',
level=logging.INFO,
format='%(asctime)s - %(levelname)s - %(message)s'
)
class ExcelCleaner:
def __init__(self):
self.window = tk.Tk()
self.window.title("Excel数据格式化工具")
self.window.geometry("1200x800")
self.window.configure(bg='#f0f0f0')
# 初始化数据处理器
self.data_handler = DataHandler()
self.current_file = None
# 创建主界面
self.create_gui()
def create_gui(self):
# 创建主框架
main_frame = ttk.Frame(self.window)
main_frame.pack(fill=tk.BOTH, expand=True, padx=10, pady=5)
# 左侧工具面板
left_panel = ttk.LabelFrame(main_frame, text="工具面板", padding=10)
left_panel.pack(side=tk.LEFT, fill=tk.Y, padx=5, pady=5)
# 文件操作区域
self.create_file_frame(left_panel)
# 数据处理操作区域
self.create_operation_frame(left_panel)
# 右侧预览区域
right_panel = ttk.LabelFrame(main_frame, text="数据预览", padding=10)
right_panel.pack(side=tk.LEFT, fill=tk.BOTH, expand=True, padx=5, pady=5)
# 创建预览表格
self.create_preview_table(right_panel)
# 创建状态栏
self.status_var = tk.StringVar()
self.status_var.set("就绪")
status_bar = ttk.Label(self.window, textvariable=self.status_var, relief=tk.SUNKEN)
status_bar.pack(side=tk.BOTTOM, fill=tk.X)
def create_file_frame(self, parent):
file_frame = ttk.LabelFrame(parent, text="文件操作", padding=5)
file_frame.pack(fill=tk.X, pady=5)
ttk.Button(file_frame, text="打开文件", command=self.open_file).pack(fill=tk.X, pady=2)
ttk.Button(file_frame, text="保存文件", command=self.save_file).pack(fill=tk.X, pady=2)
def create_operation_frame(self, parent):
op_frame = ttk.LabelFrame(parent, text="数据处理", padding=5)
op_frame.pack(fill=tk.X, pady=5)
operations = [
("删除空格", self.remove_spaces),
("统一大小写", self.normalize_case),
("格式化数字", self.format_numbers),
("格式化日期", self.format_dates),
("删除特殊字符", self.remove_special_chars),
("填充空值", self.fill_empty_values),
("删除空行", self.remove_empty_rows)
]
for op_name, op_func in operations:
ttk.Button(op_frame, text=op_name, command=op_func).pack(fill=tk.X, pady=2)
def create_preview_table(self, parent):
# 创建表格框架
table_frame = ttk.Frame(parent)
table_frame.pack(fill=tk.BOTH, expand=True)
# 创建水平和垂直滚动条
h_scrollbar = ttk.Scrollbar(table_frame, orient=tk.HORIZONTAL)
v_scrollbar = ttk.Scrollbar(table_frame)
h_scrollbar.pack(side=tk.BOTTOM, fill=tk.X)
v_scrollbar.pack(side=tk.RIGHT, fill=tk.Y)
# 创建表格
self.preview_table = ttk.Treeview(table_frame,
yscrollcommand=v_scrollbar.set,
xscrollcommand=h_scrollbar.set)
self.preview_table.pack(fill=tk.BOTH, expand=True)
# 配置滚动条
h_scrollbar.config(command=self.preview_table.xview)
v_scrollbar.config(command=self.preview_table.yview)
def update_preview(self):
# 清空现有数据
for item in self.preview_table.get_children():
self.preview_table.delete(item)
if self.data_handler.df is not None:
# 设置列
self.preview_table['columns'] = list(self.data_handler.df.columns)
self.preview_table['show'] = 'headings'
# 设置列标题
for column in self.data_handler.df.columns:
self.preview_table.heading(column, text=column)
self.preview_table.column(column, width=100)
# 添加数据（限制显示前100行）
for idx, row in self.data_handler.df.head(100).iterrows():
self.preview_table.insert('', tk.END, values=list(row))
# 更新状态栏
stats = self.data_handler.get_statistics()
self.status_var.set(
f"总行数: {stats['row_count']} | 总列数: {stats['column_count']} | "
f"空值数: {stats['null_count']}")
def open_file(self):
try:
file_path = filedialog.askopenfilename(
filetypes=[("Excel文件", "*.xlsx;*.xls")]
)
if file_path:
self.current_file = file_path
self.data_handler.load_excel(file_path)
self.update_preview()
messagebox.showinfo("成功", "文件加载成功！")
except Exception as e:
messagebox.showerror("错误", str(e))
def save_file(self):
if self.data_handler.df is None:
messagebox.showwarning("警告", "没有数据可保存！")
return
try:
file_path = filedialog.asksaveasfilename(
defaultextension=".xlsx",
filetypes=[("Excel文件", "*.xlsx")]
)
if file_path:
self.data_handler.save_excel(file_path)
messagebox.showinfo("成功", "文件保存成功！")
except Exception as e:
messagebox.showerror("错误", str(e))
def remove_spaces(self):
if self.data_handler.df is None:
messagebox.showwarning("警告", "请先加载数据！")
return
def on_columns_selected(columns):
try:
self.data_handler.remove_spaces(columns)
self.update_preview()
messagebox.showinfo("成功", "空格删除成功！")
except Exception as e:
messagebox.showerror("错误", str(e))
ColumnSelector(self.window,
self.data_handler.df.columns,
self.data_handler.get_column_types(),
"选择要删除空格的列",
on_columns_selected)
def normalize_case(self):
if self.data_handler.df is None:
messagebox.showwarning("警告", "请先加载数据！")
return
params = {
'case_type': {
'label': '大小写类型',
'type': 'choice',
'choices': ['lower', 'upper', 'title'],
'default': 'lower'
}
}
def on_params_set(params_values):
def on_columns_selected(columns):
try:
self.data_handler.normalize_case(params_values['case_type'], columns)
self.update_preview()
messagebox.showinfo("成功", "大小写转换成功！")
except Exception as e:
messagebox.showerror("错误", str(e))
ColumnSelector(self.window,
self.data_handler.df.columns,
self.data_handler.get_column_types(),
"选择要转换大小写的列",
on_columns_selected)
ParameterDialog(self.window, params, "设置大小写转换参数", on_params_set)
def format_numbers(self):
if self.data_handler.df is None:
messagebox.showwarning("警告", "请先加载数据！")
return
params = {
'decimal_places': {
'label': '小数位数',
'type': 'int',
'min': 0,
'max': 10,
'default': 2
}
}
def on_params_set(params_values):
def on_columns_selected(columns):
try:
self.data_handler.format_numbers(params_values['decimal_places'], columns)
self.update_preview()
messagebox.showinfo("成功", "数字格式化成功！")
except Exception as e:
messagebox.showerror("错误", str(e))
ColumnSelector(self.window,
self.data_handler.df.columns,
self.data_handler.get_column_types(),
"选择要格式化的数字列",
on_columns_selected)
ParameterDialog(self.window, params, "设置数字格式化参数", on_params_set)
def format_dates(self):
if self.data_handler.df is None:
messagebox.showwarning("警告", "请先加载数据！")
return
params = {
'date_format': {
'label': '日期格式',
'type': 'choice',
'choices': ['%Y-%m-%d', '%Y/%m/%d', '%Y年%m月%d日'],
'default': '%Y-%m-%d'
}
}
def on_params_set(params_values):
def on_columns_selected(columns):
try:
self.data_handler.format_dates(params_values['date_format'], columns)
self.update_preview()
messagebox.showinfo("成功", "日期格式化成功！")
except Exception as e:
messagebox.showerror("错误", str(e))
ColumnSelector(self.window,
self.data_handler.df.columns,
self.data_handler.get_column_types(),
"选择要格式化的日期列",
on_columns_selected)
ParameterDialog(self.window, params, "设置日期格式化参数", on_params_set)
def remove_special_chars(self):
if self.data_handler.df is None:
messagebox.showwarning("警告", "请先加载数据！")
return
params = {
'pattern': {
'label': '要删除的字符模式',
'type': 'str',
'default': '[^\w\s]'
}
}
def on_params_set(params_values):
def on_columns_selected(columns):
try:
self.data_handler.remove_special_chars(params_values['pattern'], columns)
self.update_preview()
messagebox.showinfo("成功", "特殊字符删除成功！")
except Exception as e:
messagebox.showerror("错误", str(e))
ColumnSelector(self.window,
self.data_handler.df.columns,
self.data_handler.get_column_types(),
"选择要处理的列",
on_columns_selected)
ParameterDialog(self.window, params, "设置特殊字符删除参数", on_params_set)
def fill_empty_values(self):
if self.data_handler.df is None:
messagebox.showwarning("警告", "请先加载数据！")
return
def remove_empty_rows(self):
if self.data_handler.df is None:
messagebox.showwarning("警告", "请先加载数据！")
return
try:
self.data_handler.remove_empty_rows()
self.update_preview()
messagebox.showinfo("成功", "空行删除成功！")
except Exception as e:
messagebox.showerror("错误", str(e))
params = {
'method': {
'label': '填充方法',
'type': 'choice',
'choices': ['value', 'mean', 'median', 'mode', 'ffill', 'bfill'],
'default': 'value'
},
'value': {
'label': '填充值（仅用于固定值填充）',
'type': 'str',
'default': '0'
}
}
def on_params_set(params_values):
def on_columns_selected(columns):
try:
self.data_handler.fill_empty_values(
method=params_values['method'],
value=params_values['value'],
columns=columns
)
self.update_preview()
messagebox.showinfo("成功", "空值填充成功！")
except Exception as e:
messagebox.showerror("错误", str(e))
ColumnSelector(self.window,
self.data_handler.df.columns,
self.data_handler.get_column_types(),
"选择要填充的列",
on_columns_selected)
ParameterDialog(self.window, params, "设置空值填充参数", on_params_set)
def run(self):
self.window.mainloop()
if __name__ == '__main__':
app = ExcelCleaner()
app.run()
|
2301_80863610/Undoom
|
Excel格式化工具/src/main.py
|
Python
|
unknown
| 13,218
|
import pandas as pd
import numpy as np
from tkinter import *
from tkinter import ttk, filedialog, messagebox
import os
from tkinter.scrolledtext import ScrolledText
import threading
from queue import Queue
import logging
from datetime import datetime
# 配置日志
logging.basicConfig(
filename='excel_cleaner.log',
level=logging.INFO,
format='%(asctime)s - %(levelname)s - %(message)s'
)
# 模拟 DataHandler, ColumnSelector, ParameterDialog 类
class DataHandler:
def __init__(self):
self.df = None
self.operation_history = []
self.redo_history = []
def load_excel(self, file_path):
self.df = pd.read_excel(file_path)
return self.df
def save_excel(self, file_path):
self.df.to_excel(file_path, index=False)
def get_statistics(self):
return {
'row_count': len(self.df),
'column_count': len(self.df.columns)
}
def get_column_types(self):
return self.df.dtypes
def remove_spaces(self, columns):
for col in columns:
if self.df[col].dtype == object:
self.df[col] = self.df[col].str.strip()
return self.df
def normalize_case(self, case_type, columns):
for col in columns:
if self.df[col].dtype == object:
if case_type == 'lower':
self.df[col] = self.df[col].str.lower()
elif case_type == 'upper':
self.df[col] = self.df[col].str.upper()
elif case_type == 'title':
self.df[col] = self.df[col].str.title()
return self.df
def format_numbers(self, decimal_places, columns):
for col in columns:
if pd.api.types.is_numeric_dtype(self.df[col]):
self.df[col] = self.df[col].round(decimal_places)
return self.df
def format_dates(self, date_format, columns):
for col in columns:
if pd.api.types.is_datetime64_any_dtype(self.df[col]):
self.df[col] = self.df[col].dt.strftime(date_format)
return self.df
def remove_special_chars(self, pattern, columns):
for col in columns:
if self.df[col].dtype == object:
self.df[col] = self.df[col].str.replace(pattern, '', regex=True)
return self.df
def fill_empty_values(self, method, value=None, columns=None):
if columns is None:
columns = self.df.columns
for col in columns:
if method == 'value':
self.df[col].fillna(value, inplace=True)
elif method == 'mean':
self.df[col].fillna(self.df[col].mean(), inplace=True)
elif method == 'median':
self.df[col].fillna(self.df[col].median(), inplace=True)
elif method == 'mode':
self.df[col].fillna(self.df[col].mode()[0], inplace=True)
elif method == 'ffill':
self.df[col].fillna(method='ffill', inplace=True)
elif method == 'bfill':
self.df[col].fillna(method='bfill', inplace=True)
return self.df
class ColumnSelector:
def __init__(self, parent, columns, column_types, title, callback):
self.callback = callback
self.selected_columns = []
self.window = Toplevel(parent)
self.window.title(title)
ttk.Label(self.window, text="选择列：").pack(pady=10)
self.listbox = Listbox(self.window, selectmode=MULTIPLE)
for col in columns:
self.listbox.insert(END, col)
self.listbox.pack(fill=BOTH, expand=True, padx=10, pady=10)
button_frame = ttk.Frame(self.window)
button_frame.pack(fill=X, padx=10, pady=10)
ttk.Button(button_frame, text="确定", command=self.on_confirm).pack(side=LEFT, padx=10)
ttk.Button(button_frame, text="取消", command=self.window.destroy).pack(side=LEFT)
def on_confirm(self):
self.selected_columns = [self.listbox.get(i) for i in self.listbox.curselection()]
self.callback(self.selected_columns)
self.window.destroy()
class ParameterDialog:
def __init__(self, parent, params, title, callback):
self.callback = callback
self.params = params
self.values = {}
self.window = Toplevel(parent)
self.window.title(title)
for param_name, param_info in params.items():
ttk.Label(self.window, text=param_info['label']).pack(pady=5)
if param_info['type'] == 'choice':
var = StringVar()
var.set(param_info['default'])
ttk.Combobox(self.window, textvariable=var, values=param_info['choices']).pack(fill=X, padx=10)
self.values[param_name] = var
elif param_info['type'] == 'int':
var = IntVar()
var.set(param_info['default'])
ttk.Spinbox(self.window, from_=param_info['min'], to=param_info['max'], textvariable=var).pack(fill=X, padx=10)
self.values[param_name] = var
elif param_info['type'] == 'str':
var = StringVar()
var.set(param_info['default'])
ttk.Entry(self.window, textvariable=var).pack(fill=X, padx=10)
self.values[param_name] = var
button_frame = ttk.Frame(self.window)
button_frame.pack(fill=X, padx=10, pady=10)
ttk.Button(button_frame, text="确定", command=self.on_confirm).pack(side=LEFT, padx=10)
ttk.Button(button_frame, text="取消", command=self.window.destroy).pack(side=LEFT)
def on_confirm(self):
result = {param_name: var.get() for param_name, var in self.values.items()}
self.callback(result)
self.window.destroy()
class ExcelCleaner:
def __init__(self):
self.window = Tk()
self.window.title("Excel数据格式化批处理工具")
self.window.geometry("1000x800")
self.window.configure(bg='#f0f0f0')
# 初始化数据处理器
self.data_handler = DataHandler()
self.processing_queue = Queue()
# 设置样式
self.setup_styles()
# 创建菜单栏
self.create_menu()
# 创建主框架
main_frame = ttk.Frame(self.window)
main_frame.pack(fill=BOTH, expand=True, padx=10, pady=5)
# 左侧工具面板
left_panel = ttk.LabelFrame(main_frame, text="工具面板", padding=10)
left_panel.pack(side=LEFT, fill=Y, padx=5, pady=5)
# 文件操作区域
self.create_file_frame(left_panel)
# 清洗操作区域
self.create_clean_frame(left_panel)
# 右侧主要内容区域
right_panel = ttk.Frame(main_frame)
right_panel.pack(side=LEFT, fill=BOTH, expand=True, padx=5)
# 预览区域
self.create_preview_frame(right_panel)
# 状态栏
self.create_status_bar()
# 进度条
self.create_progress_bar()
# 绑定快捷键
self.bind_shortcuts()
def setup_styles(self):
style = ttk.Style()
style.theme_use('clam')
# 配置按钮样式
style.configure(
"Tool.TButton",
padding=5,
font=('微软雅黑', 10),
background='#e1e1e1',
foreground='#333333'
)
# 配置标签样式
style.configure(
"Title.TLabel",
font=('微软雅黑', 12, 'bold'),
background='#f0f0f0',
foreground='#333333'
)
# 配置框架样式
style.configure(
"Card.TLabelframe",
background='#ffffff',
padding=10
)
# 配置树形视图样式
style.configure(
"Preview.Treeview",
font=('微软雅黑', 10),
rowheight=25
)
# 配置进度条样式
style.configure(
"Progress.Horizontal.TProgressbar",
troughcolor='#f0f0f0',
background='#4CAF50',
thickness=10
)
def create_progress_bar(self):
self.progress_var = DoubleVar()
self.progress_bar = ttk.Progressbar(
self.window,
style="Progress.Horizontal.TProgressbar",
variable=self.progress_var,
maximum=100
)
self.progress_bar.pack(fill=X, padx=5, pady=2)
def bind_shortcuts(self):
self.window.bind('<Control-o>', lambda e: self.select_file())
self.window.bind('<Control-s>', lambda e: self.save_file())
self.window.bind('<Control-z>', lambda e: self.undo())
self.window.bind('<Control-y>', lambda e: self.redo())
self.window.bind('<F1>', lambda e: self.show_help())
def process_in_background(self, func, *args, **kwargs):
"""在后台线程中处理耗时操作"""
def wrapper():
try:
self.progress_var.set(0)
self.status_var.set("正在处理...")
self.window.update()
# 执行操作
result = func(*args, **kwargs)
# 更新UI
self.window.after(0, self.update_ui_after_processing, result)
except Exception as e:
logging.error(f"处理错误: {str(e)}")
self.window.after(0, self.show_error, str(e))
finally:
self.window.after(0, self.progress_var.set, 100)
self.window.after(0, self.status_var.set, "处理完成")
# 启动后台线程
thread = threading.Thread(target=wrapper)
thread.daemon = True
thread.start()
def update_ui_after_processing(self, result):
"""处理完成后更新UI"""
if isinstance(result, tuple):
self.data_handler.df = result[0]
if len(result) > 1:
removed_rows = result[1]
self.status_var.set(f"已删除 {removed_rows} 行数据")
elif isinstance(result, pd.DataFrame):
self.data_handler.df = result
if result is not None:
self.update_preview()
def show_error(self, error_msg):
"""显示错误消息"""
messagebox.showerror("错误", f"处理过程中出现错误：{error_msg}")
self.status_var.set("处理失败")
def select_file(self):
file_path = filedialog.askopenfilename(
filetypes=[("Excel files", "*.xlsx *.xls")]
)
if file_path:
self.process_in_background(self.data_handler.load_excel, file_path)
def save_file(self):
if self.data_handler.df is not None:
file_path = filedialog.asksaveasfilename(
defaultextension=".xlsx",
filetypes=[("Excel files", "*.xlsx")]
)
if file_path:
self.process_in_background(self.data_handler.save_excel, file_path)
def undo(self):
"""撤销上一步操作"""
if self.data_handler.operation_history:
last_operation = self.data_handler.operation_history.pop()
self.data_handler.df = last_operation['previous_state'].copy()
self.update_preview()
self.status_var.set("已撤销上一步操作")
def redo(self):
"""重做上一步操作"""
if hasattr(self.data_handler, 'redo_history') and self.data_handler.redo_history:
last_operation = self.data_handler.redo_history.pop()
self.data_handler.df = last_operation['next_state'].copy()
self.data_handler.operation_history.append(last_operation)
self.update_preview()
self.status_var.set("已重做上一步操作")
def add_operation_to_history(self, operation_name, previous_state, next_state):
"""添加操作到历史记录"""
self.data_handler.operation_history.append({
'name': operation_name,
'previous_state': previous_state.copy(),
'next_state': next_state.copy()
})
# 清空重做历史
if hasattr(self.data_handler, 'redo_history'):
self.data_handler.redo_history.clear()
def remove_duplicates(self):
if self.data_handler.df is not None:
previous_state = self.data_handler.df.copy()
self.data_handler.df = self.data_handler.df.drop_duplicates()
removed_rows = len(previous_state) - len(self.data_handler.df)
self.add_operation_to_history("删除重复行", previous_state, self.data_handler.df.copy())
self.update_preview()
self.status_var.set(f"已删除 {removed_rows} 行重复数据")
def remove_empty_rows(self):
if self.data_handler.df is not None:
previous_state = self.data_handler.df.copy()
self.data_handler.df = self.data_handler.df.dropna(how='all')
removed_rows = len(previous_state) - len(self.data_handler.df)
self.add_operation_to_history("删除空行", previous_state, self.data_handler.df.copy())
self.update_preview()
self.status_var.set(f"已删除 {removed_rows} 行空数据")
def remove_spaces(self):
if self.data_handler.df is not None:
def on_columns_selected(columns):
self.process_in_background(
self.data_handler.remove_spaces,
columns=columns
)
ColumnSelector(
self.window,
list(self.data_handler.df.columns),
self.data_handler.get_column_types(),
title="选择要去除空格的列",
callback=on_columns_selected
)
def normalize_case(self):
if self.data_handler.df is not None:
def on_params_set(params):
def on_columns_selected(columns):
self.process_in_background(
self.data_handler.normalize_case,
case_type=params["case_type"],
columns=columns
)
ColumnSelector(
self.window,
list(self.data_handler.df.columns),
self.data_handler.get_column_types(),
title="选择要统一大小写的列",
callback=on_columns_selected
)
params = {
"case_type": {
"type": "choice",
"label": "大小写格式",
"default": "lower",
"choices": ["lower", "upper", "title"]
}
}
ParameterDialog(
self.window,
params,
title="选择大小写格式",
callback=on_params_set
)
def format_numbers(self):
if self.data_handler.df is not None:
def on_params_set(params):
def on_columns_selected(columns):
self.process_in_background(
self.data_handler.format_numbers,
decimal_places=params["decimal_places"],
columns=columns
)
ColumnSelector(
self.window,
list(self.data_handler.df.columns),
self.data_handler.get_column_types(),
title="选择要格式化的数值列",
callback=on_columns_selected
)
params = {
"decimal_places": {
"type": "int",
"label": "小数位数",
"default": 2,
"min": 0,
"max": 10
}
}
ParameterDialog(
self.window,
params,
title="设置数值格式",
callback=on_params_set
)
def format_dates(self):
if self.data_handler.df is not None:
def on_params_set(params):
def on_columns_selected(columns):
self.process_in_background(
self.data_handler.format_dates,
date_format=params["date_format"],
columns=columns
)
ColumnSelector(
self.window,
list(self.data_handler.df.columns),
self.data_handler.get_column_types(),
title="选择要格式化的日期列",
callback=on_columns_selected
)
params = {
"date_format": {
"type": "choice",
"label": "日期格式",
"default": "%Y-%m-%d",
"choices": [
"%Y-%m-%d",
"%Y/%m/%d",
"%d-%m-%Y",
"%m/%d/%Y"
]
}
}
ParameterDialog(
self.window,
params,
title="选择日期格式",
callback=on_params_set
)
def remove_special_chars(self):
if self.data_handler.df is not None:
def on_params_set(params):
def on_columns_selected(columns):
self.process_in_background(
self.data_handler.remove_special_chars,
pattern=params["pattern"],
columns=columns
)
ColumnSelector(
self.window,
list(self.data_handler.df.columns),
self.data_handler.get_column_types(),
title="选择要处理的列",
callback=on_columns_selected
)
params = {
"pattern": {
"type": "str",
"label": "正则表达式",
"default": r'[^\w\s]'
}
}
ParameterDialog(
self.window,
params,
title="设置正则表达式",
callback=on_params_set
)
def fill_empty_values(self):
if self.data_handler.df is not None:
def on_params_set(params):
def on_columns_selected(columns):
value = params.get("value")
if params["method"] == "value" and value:
try:
# 尝试转换为数值
value = float(value) if '.' in value else int(value)
except ValueError:
pass
self.process_in_background(
self.data_handler.fill_empty_values,
method=params["method"],
value=value,
columns=columns
)
ColumnSelector(
self.window,
list(self.data_handler.df.columns),
self.data_handler.get_column_types(),
title="选择要填充的列",
callback=on_columns_selected
)
params = {
"method": {
"type": "choice",
"label": "填充方式",
"default": "mean",
"choices": ["mean", "median", "mode", "ffill", "bfill", "value"]
},
"value": {
"type": "str",
"label": "填充值",
"default": ""
}
}
ParameterDialog(
self.window,
params,
title="选择填充方式",
callback=on_params_set
)
def analyze_data(self):
if self.data_handler.df is not None:
analysis_window = Toplevel(self.window)
analysis_window.title("数据分析")
analysis_window.geometry("600x400")
stats_text = ScrolledText(analysis_window, wrap=WORD, width=70, height=20)
stats_text.pack(padx=10, pady=10, fill=BOTH, expand=True)
stats = []
stats.append("数据基本信息：")
stats.append("-" * 50)
stats.append(f"总行数：{len(self.data_handler.df)}")
stats.append(f"总列数：{len(self.data_handler.df.columns)}")
stats.append("\n数值列统计：")
stats.append("-" * 50)
numeric_stats = self.data_handler.df.describe()
stats.append(str(numeric_stats))
stats.append("\n空值统计：")
stats.append("-" * 50)
null_counts = self.data_handler.df.isnull().sum()
stats.append(str(null_counts))
stats_text.insert(END, "\n".join(stats))
stats_text.configure(state='disabled')
def visualize_data(self):
if self.data_handler.df is not None:
try:
import matplotlib.pyplot as plt
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
# 设置中文字体
plt.rcParams['font.sans-serif'] = ['SimHei'] # 用来正常显示中文标签
plt.rcParams['axes.unicode_minus'] = False # 用来正常显示负号
viz_window = Toplevel(self.window)
viz_window.title("数据可视化")
viz_window.geometry("800x600")
options_frame = ttk.Frame(viz_window)
options_frame.pack(fill=X, padx=10, pady=5)
ttk.Label(options_frame, text="图表类型：").pack(side=LEFT)
chart_type = StringVar(value="bar")
ttk.Radiobutton(options_frame, text="柱状图", variable=chart_type, value="bar").pack(side=LEFT)
ttk.Radiobutton(options_frame, text="折线图", variable=chart_type, value="line").pack(side=LEFT)
ttk.Radiobutton(options_frame, text="散点图", variable=chart_type, value="scatter").pack(side=LEFT)
# 添加列选择
ttk.Label(options_frame, text=" 选择列：").pack(side=LEFT)
column_var = StringVar()
numeric_columns = list(self.data_handler.df.select_dtypes(include=[np.number]).columns)
if not numeric_columns:
messagebox.showwarning("警告", "没有可用的数值列进行可视化")
return
column_combo = ttk.Combobox(options_frame, textvariable=column_var, values=numeric_columns)
column_combo.pack(side=LEFT)
column_combo.set(numeric_columns[0])
fig, ax = plt.subplots(figsize=(10, 6))
canvas = FigureCanvasTkAgg(fig, master=viz_window)
canvas.get_tk_widget().pack(fill=BOTH, expand=True, padx=10, pady=5)
def update_chart():
try:
ax.clear()
chart_style = chart_type.get()
selected_column = column_var.get()
if not selected_column:
messagebox.showwarning("警告", "请选择要可视化的列")
return
if chart_style == "bar":
self.data_handler.df[selected_column].plot(kind='bar', ax=ax)
ax.set_title(f"{selected_column} 柱状图")
elif chart_style == "line":
self.data_handler.df[selected_column].plot(kind='line', ax=ax)
ax.set_title(f"{selected_column} 折线图")
else: # scatter
if len(numeric_columns) >= 2:
x_col = selected_column
y_col = next(col for col in numeric_columns if col != x_col)
self.data_handler.df.plot(kind='scatter', x=x_col, y=y_col, ax=ax)
ax.set_title(f"{x_col} vs {y_col} 散点图")
else:
messagebox.showwarning("警告", "需要至少两个数值列才能创建散点图")
return
plt.tight_layout()
canvas.draw()
except Exception as e:
messagebox.showerror("错误", f"绘图时发生错误：{str(e)}")
ttk.Button(options_frame, text="更新图表", command=update_chart).pack(side=LEFT, padx=10)
update_chart()
except ImportError:
messagebox.showwarning("警告", "请安装matplotlib库以使用可视化功能")
def run(self):
self.window.mainloop()
def create_menu(self):
menubar = Menu(self.window)
self.window.config(menu=menubar)
# 文件菜单
file_menu = Menu(menubar, tearoff=0)
menubar.add_cascade(label="文件", menu=file_menu)
file_menu.add_command(label="打开 (Ctrl+O)", command=self.select_file)
file_menu.add_command(label="保存 (Ctrl+S)", command=self.save_file)
file_menu.add_separator()
file_menu.add_command(label="退出", command=self.window.quit)
# 编辑菜单
edit_menu = Menu(menubar, tearoff=0)
menubar.add_cascade(label="编辑", menu=edit_menu)
edit_menu.add_command(label="撤销 (Ctrl+Z)", command=self.undo)
edit_menu.add_command(label="重做 (Ctrl+Y)", command=self.redo)
# 视图菜单
view_menu = Menu(menubar, tearoff=0)
menubar.add_cascade(label="视图", menu=view_menu)
view_menu.add_checkbutton(label="显示状态栏", command=self.toggle_status_bar)
# 帮助菜单
help_menu = Menu(menubar, tearoff=0)
menubar.add_cascade(label="帮助", menu=help_menu)
help_menu.add_command(label="使用说明 (F1)", command=self.show_help)
help_menu.add_command(label="关于", command=self.show_about)
def create_file_frame(self, parent):
file_frame = ttk.LabelFrame(parent, text="文件操作", padding=10, style="Card.TLabelframe")
file_frame.pack(fill=X, pady=(0, 10))
# 文件选择
self.file_path = StringVar()
ttk.Label(file_frame, text="Excel文件：", style="Title.TLabel").pack(anchor=W)
ttk.Entry(file_frame, textvariable=self.file_path, width=30).pack(fill=X, pady=5)
button_frame = ttk.Frame(file_frame)
button_frame.pack(fill=X)
ttk.Button(button_frame, text="浏览", command=self.select_file, style="Tool.TButton").pack(side=LEFT, padx=2)
ttk.Button(button_frame, text="保存", command=self.save_file, style="Tool.TButton").pack(side=LEFT, padx=2)
def create_clean_frame(self, parent):
clean_frame = ttk.LabelFrame(parent, text="数据清洗", padding=10, style="Card.TLabelframe")
clean_frame.pack(fill=BOTH, expand=True)
operations = [
("删除重复行", self.remove_duplicates),
("删除空行", self.remove_empty_rows),
("去除空格", self.remove_spaces),
("统一大小写", self.normalize_case),
("数值格式化", self.format_numbers),
("日期格式化", self.format_dates),
("删除特殊字符", self.remove_special_chars),
("填充空值", self.fill_empty_values),
("数据分析", self.analyze_data),
("数据可视化", self.visualize_data)
]
for text, command in operations:
btn = ttk.Button(clean_frame, text=text, command=command, style="Tool.TButton")
btn.pack(fill=X, pady=2)
def create_preview_frame(self, parent):
preview_frame = ttk.LabelFrame(parent, text="数据预览", padding=10, style="Card.TLabelframe")
preview_frame.pack(fill=BOTH, expand=True)
# 创建带滚动条的树形视图
tree_frame = ttk.Frame(preview_frame)
tree_frame.pack(fill=BOTH, expand=True)
# 创建水平滚动条
h_scrollbar = ttk.Scrollbar(tree_frame, orient=HORIZONTAL)
h_scrollbar.pack(side=BOTTOM, fill=X)
# 创建垂直滚动条
v_scrollbar = ttk.Scrollbar(tree_frame)
v_scrollbar.pack(side=RIGHT, fill=Y)
# 创建树形视图
self.tree = ttk.Treeview(
tree_frame,
style="Preview.Treeview",
xscrollcommand=h_scrollbar.set,
yscrollcommand=v_scrollbar.set
)
self.tree.pack(fill=BOTH, expand=True)
# 配置滚动条
h_scrollbar.config(command=self.tree.xview)
v_scrollbar.config(command=self.tree.yview)
# 创建统计信息面板
stats_frame = ttk.Frame(preview_frame)
stats_frame.pack(fill=X, pady=(10, 0))
self.stats_label = ttk.Label(stats_frame, text="", style="Title.TLabel")
self.stats_label.pack(side=LEFT)
def create_status_bar(self):
self.status_var = StringVar()
self.status_bar = ttk.Label(
self.window,
textvariable=self.status_var,
relief=SUNKEN,
padding=(5, 2)
)
self.status_bar.pack(fill=X, padx=5, pady=2)
def toggle_status_bar(self):
# 切换状态栏显示/隐藏
if self.status_bar.winfo_viewable():
self.status_bar.pack_forget()
else:
self.status_bar.pack(fill=X, padx=5, pady=2)
def update_preview(self):
# 清空现有数据
for item in self.tree.get_children():
self.tree.delete(item)
if self.data_handler.df is not None:
df = self.data_handler.df
# 设置列
self.tree["columns"] = list(df.columns)
self.tree["show"] = "headings"
for column in df.columns:
self.tree.heading(column, text=column)
self.tree.column(column, width=100, anchor='center')
# 添加数据（仅显示前100行）
for i, row in df.head(100).iterrows():
self.tree.insert("", END, values=list(row))
# 更新统计标签
stats = self.data_handler.get_statistics()
self.stats_label.config(
text=f"行数: {stats['row_count']} | 列数: {stats['column_count']}"
)
# 更新状态栏
self.status_var.set(
f"当前加载文件: {os.path.basename(self.file_path.get())} | "
f"行数: {stats['row_count']} | 列数: {stats['column_count']}"
)
else:
self.status_var.set("请先加载文件")
def show_help(self):
help_text = """
Excel数据格式化批处理工具使用说明：
1. 文件操作：
- 点击"浏览"选择Excel文件
- 点击"保存"保存处理后的文件
2. 数据清洗功能：
- 删除重复行：删除完全重复的数据行
- 删除空行：删除全为空值的行
- 去除空格：删除文本中的首尾空格
- 统一大小写：统一文本的大小写格式
- 数值格式化：统一数值的小数位数
- 日期格式化：统一日期的显示格式
- 删除特殊字符：清除文本中的特殊字符
- 填充空值：使用多种方式填充缺失值
3. 数据分析：
- 查看基本统计信息
- 空值分析
- 数据分布可视化
4. 快捷键：
- Ctrl+O：打开文件
- Ctrl+S：保存文件
- Ctrl+Z：撤销
- Ctrl+Y：重做
- F1：显示帮助
"""
help_window = Toplevel(self.window)
help_window.title("使用说明")
help_window.geometry("600x400")
help_text_widget = ScrolledText(help_window, wrap=WORD, width=70, height=20)
help_text_widget.pack(padx=10, pady=10, fill=BOTH, expand=True)
help_text_widget.insert(END, help_text)
help_text_widget.configure(state='disabled')
def show_about(self):
about_text = """
Excel数据格式化批处理工具
功能特点：
- 支持多种数据清洗操作
- 实时预览数据变化
- 数据分析和可视化
- 后台处理，避免卡顿
- 撤销/重做功能
- 友好的图形界面
"""
messagebox.showinfo("关于", about_text)
if __name__ == "__main__":
try:
app = ExcelCleaner()
app.run()
except Exception as e:
logging.error(f"程序运行错误: {str(e)}")
messagebox.showerror("错误", f"程序运行出错：{str(e)}")
# 优化的代码，运行即出现GUI界面
|
2301_80863610/Undoom
|
Excel格式化工具/test.py
|
Python
|
unknown
| 33,323
|
#!/bin/bash
# 定义下载地址和文件名
DOWNLOAD_URL="https://cangjie-lang.cn/v1/files/auth/downLoad?nsId=142267&fileName=Cangjie-0.53.13-linux_x64.tar.gz&objectKey=6719f1eb3af6947e3c6af327"
FILE_NAME="Cangjie-0.53.13-linux_x64.tar.gz"
# 检查 cangjie 工具链是否已安装
echo "确保 cangjie 工具链已安装..."
if ! command -v cjc -v &> /dev/null
then
echo "cangjie工具链 未安装，尝试进行安装..."
# 下载文件
echo "Downloading Cangjie compiler..."
curl -L -o "$FILE_NAME" "$DOWNLOAD_URL"
# 检查下载是否成功
if [ $? -eq 0 ]; then
echo "Download completed successfully."
else
echo "Download failed."
exit 1
fi
# 解压文件
echo "Extracting $FILE_NAME..."
tar -xvf "$FILE_NAME"
# 检查解压是否成功
if [ $? -eq 0 ]; then
echo "Extraction completed successfully."
else
echo "Extraction failed."
exit 1
fi
# 检查 envsetup.sh 是否存在并进行 source
if [[ -f "cangjie/envsetup.sh" ]]; then
echo "envsetup.sh found!"
source cangjie/envsetup.sh
else
echo "envsetup.sh not found!"
exit 1
fi
fi
# 检查 openEuler 防火墙状态
echo "检查 openEuler 防火墙状态..."
if systemctl status firewalld | grep "active (running)" &> /dev/null; then
echo "防火墙已开启，尝试开放 21 端口..."
firewall-cmd --zone=public --add-port=21/tcp --permanent
firewall-cmd --reload
echo "21 端口已开放。"
else
echo "防火墙未开启，无需开放端口。"
fi
# 编译ftp_server
echo "正在编译 ftp_server..."
cjpm build
# 检查编译是否成功
if [ $? -eq 0 ]; then
echo "编译成功."
else
echo "编译失败."
exit 1
fi
# 运行 ftp_server
echo "正在启动 ftp 服务器..."
cjpm run
|
2301_80674151/Cangjie-Examples_4666
|
FTP/run-ftp.sh
|
Shell
|
apache-2.0
| 1,967
|