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737f100 7c8fa1c 737f100 7c8fa1c 737f100 7c8fa1c 737f100 7c8fa1c 737f100 7c8fa1c 737f100 7c8fa1c 737f100 7c8fa1c 737f100 7c8fa1c 737f100 7c8fa1c 737f100 7c8fa1c 737f100 7c8fa1c 737f100 7c8fa1c 737f100 63eda9e 737f100 7c8fa1c 737f100 7c8fa1c 737f100 7c8fa1c 737f100 7c8fa1c 737f100 7c8fa1c 737f100 7c8fa1c 737f100 7c8fa1c 737f100 7c8fa1c 737f100 7c8fa1c 737f100 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 | """Gradio UI for TorchReview Copilot."""
from __future__ import annotations
from html import escape
import gradio as gr
try:
from ..triage import get_default_engine
except ImportError:
from triage import get_default_engine
CSS = """
:root {
--paper: #f6f1e8;
--ink: #162521;
--accent: #d95d39;
--panel: #fffdf8;
--border: #d6c4b8;
--muted: #5f6f67;
--good: #2d7d62;
--warn: #b76516;
--high: #b23a48;
}
body, .gradio-container {
background:
radial-gradient(circle at top left, rgba(247, 197, 159, 0.35), transparent 35%),
linear-gradient(135deg, #f9f6ef 0%, #efe5d3 100%);
color: var(--ink);
font-family: Georgia, "Times New Roman", serif;
}
.gradio-container {
max-width: 1260px !important;
}
.hero-card,
.metric-card,
.subtle-card {
background: rgba(255, 253, 248, 0.95);
border: 1px solid var(--border);
border-radius: 20px;
box-shadow: 0 16px 40px rgba(22, 37, 33, 0.08);
}
.hero-card {
padding: 28px 30px;
margin-bottom: 12px;
}
.metric-card,
.subtle-card {
padding: 20px 22px;
}
.eyebrow {
text-transform: uppercase;
letter-spacing: 0.12em;
font-size: 12px;
color: var(--accent);
margin-bottom: 10px;
}
.hero-title {
font-size: 44px;
line-height: 1.05;
margin: 0 0 10px;
}
.hero-copy {
margin: 0;
font-size: 18px;
line-height: 1.55;
color: var(--muted);
}
.summary-title {
display: flex;
justify-content: space-between;
gap: 12px;
align-items: center;
margin-bottom: 14px;
}
.pill {
display: inline-block;
padding: 6px 12px;
border-radius: 999px;
font-size: 12px;
text-transform: uppercase;
letter-spacing: 0.08em;
background: #efe5d3;
}
.pill.low { color: var(--good); }
.pill.medium { color: var(--warn); }
.pill.high { color: var(--high); }
.summary-grid {
display: grid;
grid-template-columns: repeat(2, minmax(0, 1fr));
gap: 12px;
margin-top: 16px;
}
.summary-stat {
background: #fff7ef;
border-radius: 14px;
padding: 12px 14px;
border: 1px solid rgba(214, 196, 184, 0.8);
}
.summary-stat strong {
display: block;
font-size: 12px;
text-transform: uppercase;
letter-spacing: 0.08em;
color: var(--muted);
margin-bottom: 6px;
}
.radar-wrap {
display: grid;
gap: 12px;
}
.bar {
display: grid;
gap: 6px;
}
.bar-head {
display: flex;
justify-content: space-between;
font-size: 13px;
color: var(--muted);
}
.bar-track {
width: 100%;
height: 12px;
background: #f2e5d6;
border-radius: 999px;
overflow: hidden;
}
.bar-fill {
height: 100%;
border-radius: 999px;
}
.matched-box {
background: #fff7ef;
border: 1px solid rgba(214, 196, 184, 0.8);
border-radius: 16px;
padding: 14px;
}
.how-grid {
display: grid;
grid-template-columns: repeat(4, minmax(0, 1fr));
gap: 12px;
}
.how-step {
background: rgba(255, 253, 248, 0.9);
border: 1px solid var(--border);
border-radius: 18px;
padding: 16px;
}
@media (max-width: 900px) {
.hero-title {
font-size: 34px;
}
.summary-grid,
.how-grid {
grid-template-columns: 1fr;
}
}
"""
def _default_outputs() -> tuple[str, str, str, str, str]:
return (
"<div class='metric-card'><div class='eyebrow'>Awaiting Analysis</div><p class='hero-copy'>Paste Python code, add an optional traceback, or load one of the built-in examples.</p></div>",
"<div class='metric-card'><div class='eyebrow'>Live Triage Radar</div><p class='hero-copy'>Confidence bars will appear after the first analysis run.</p></div>",
"### Improvement Plan\nAnalyze a sample to generate syntax, edge-case, and scalability recommendations.",
"### Known Pattern Match\nThe nearest OpenEnv task will be highlighted here after inference runs.",
"### Model Notes\nBackend and extracted signal details will appear here.",
)
def _summary_html(result) -> str:
issue = escape(result.issue_label.title())
summary = escape(result.summary)
next_action = escape(result.suggested_next_action)
return f"""
<div class="metric-card">
<div class="summary-title">
<div>
<div class="eyebrow">TorchReview Verdict</div>
<h3 style="margin:0;font-size:30px;">{issue} Issue</h3>
</div>
<span class="pill {escape(result.repair_risk)}">{escape(result.repair_risk)} repair risk</span>
</div>
<p class="hero-copy">{summary}</p>
<div class="summary-grid">
<div class="summary-stat">
<strong>Reward Score</strong>
{result.reward_score:.0%}
</div>
<div class="summary-stat">
<strong>ML Quality</strong>
{result.ml_quality_score:.0%}
</div>
<div class="summary-stat">
<strong>Matched Pattern</strong>
{escape(result.matched_pattern.title)}
</div>
<div class="summary-stat">
<strong>Inference Backend</strong>
{escape(result.model_backend)}
</div>
<div class="summary-stat">
<strong>Lint Score</strong>
{result.lint_score:.0%}
</div>
<div class="summary-stat">
<strong>Complexity Penalty</strong>
{result.complexity_penalty:.0%}
</div>
<div class="summary-stat">
<strong>Next Action</strong>
{next_action}
</div>
</div>
</div>
"""
def _radar_html(result) -> str:
colors = {
"syntax": "#d95d39",
"logic": "#4f772d",
"performance": "#355070",
}
bars = []
for label, score in result.confidence_scores.items():
bars.append(
f"""
<div class="bar">
<div class="bar-head"><span>{escape(label.title())}</span><span>{score:.0%}</span></div>
<div class="bar-track">
<div class="bar-fill" style="width:{score * 100:.1f}%; background:{colors.get(label, '#d95d39')};"></div>
</div>
</div>
"""
)
return f"""
<div class="metric-card radar-wrap">
<div class="eyebrow">Live Triage Radar</div>
{''.join(bars)}
<div class="matched-box">
<strong>Nearest Known Pattern:</strong> {escape(result.matched_pattern.title)}<br>
<span style="color:#5f6f67;">{escape(result.matched_pattern.summary)}</span>
</div>
</div>
"""
def _plan_markdown(result) -> str:
plan_lines = "\n".join(f"{index + 1}. {step}" for index, step in enumerate(result.repair_plan))
return (
"### Improvement Plan\n"
f"**Primary issue:** `{result.issue_label}`\n\n"
f"{plan_lines}\n\n"
f"**Suggested next action:** {result.suggested_next_action}"
)
def _match_markdown(result) -> str:
return (
"### Known Pattern Match\n"
f"**Task:** `{result.matched_pattern.task_id}` \n"
f"**Title:** {result.matched_pattern.title} \n"
f"**Why it matched:** {result.matched_pattern.rationale} \n"
f"**Similarity:** {result.matched_pattern.similarity:.0%}"
)
def _model_markdown(result) -> str:
signal_lines = "\n".join(
f"- `{signal.name}` -> {signal.value} ({signal.impact}, weight {signal.weight:.2f}): {signal.evidence}"
for signal in result.extracted_signals
) or "- No strong static signals were extracted."
notes = "\n".join(f"- {item}" for item in result.inference_notes) or "- No additional backend notes."
return (
"### Model Notes\n"
f"- **Model backend:** `{result.model_backend}`\n"
f"- **Model id:** `{result.model_id}`\n"
f"- **Analysis time:** `{result.analysis_time_ms:.2f} ms`\n\n"
"### Reward Formula\n"
f"- `reward = (0.5 x {result.ml_quality_score:.2f}) + (0.3 x {result.lint_score:.2f}) - (0.2 x {result.complexity_penalty:.2f})`\n"
f"- **Final reward:** `{result.reward_score:.2f}`\n\n"
"### Extracted Signals\n"
f"{signal_lines}\n\n"
"### Backend Notes\n"
f"{notes}"
)
def analyze_inputs(code: str, traceback_text: str, context_window: str) -> tuple[str, str, str, str, str]:
"""Run the triage engine and format outputs for the Gradio UI."""
result = get_default_engine().triage(code or "", traceback_text or "", context_window or "")
return (
_summary_html(result),
_radar_html(result),
_plan_markdown(result),
_match_markdown(result),
_model_markdown(result),
)
def load_example(example_key: str) -> tuple[str, str, str, str, str, str, str, str, str]:
"""Populate the UI from a built-in example and immediately analyze it."""
example = get_default_engine().example_map()[example_key]
outputs = analyze_inputs(example.code, example.traceback_text, example.context_window)
header = (
f"### Example Scenario\n"
f"**{example.title}** \n"
f"{example.summary} \n"
f"Label target: `{example.label}`"
)
return (example.code, example.traceback_text, example.context_window, header, *outputs)
def build_demo() -> gr.Blocks:
"""Create the TorchReview Copilot Gradio application."""
examples = get_default_engine().example_map()
first_example = next(iter(examples.values()))
with gr.Blocks(title="TorchReview Copilot") as demo:
gr.HTML(
"""
<div class="hero-card">
<div class="eyebrow">Meta PyTorch OpenEnv Hackathon Demo</div>
<h1 class="hero-title">TorchReview Copilot</h1>
<p class="hero-copy">
AI-powered code review and improvement system using PyTorch to score code quality, surface bugs,
and generate a three-step improvement plan. OpenEnv stays underneath as the deterministic validation engine.
</p>
</div>
"""
)
with gr.Row():
with gr.Column(scale=6):
example_choice = gr.Radio(
choices=[(item.title, item.key) for item in examples.values()],
value=first_example.key,
label="Try a built-in failure scenario",
info="Switching examples updates the Live Triage Radar immediately.",
)
example_header = gr.Markdown()
code_input = gr.Code(
value=first_example.code,
language="python",
lines=18,
label="Python code under review",
)
traceback_input = gr.Textbox(
value=first_example.traceback_text,
lines=7,
label="Optional traceback / failing test output",
placeholder="Paste stack traces, assertion failures, or benchmark notes here.",
)
context_input = gr.Textbox(
value=first_example.context_window,
lines=4,
label="Context window",
placeholder="Describe expected behavior, constraints, or repository context.",
)
with gr.Row():
analyze_button = gr.Button("Analyze & Score Code", variant="primary")
clear_button = gr.Button("Clear Inputs", variant="secondary")
with gr.Column(scale=5):
summary_html = gr.HTML()
radar_html = gr.HTML()
plan_markdown = gr.Markdown()
match_markdown = gr.Markdown()
model_markdown = gr.Markdown()
gr.HTML(
"""
<div class="subtle-card" style="margin-top: 12px;">
<div class="eyebrow">How It Works</div>
<div class="how-grid">
<div class="how-step"><strong>Input</strong><br>Code plus optional traceback or benchmark signal.</div>
<div class="how-step"><strong>Processing</strong><br>Static checks extract parser, lint, complexity, and runtime clues.</div>
<div class="how-step"><strong>Model</strong><br>CodeBERTa embeddings run through PyTorch and score code quality against known OpenEnv patterns.</div>
<div class="how-step"><strong>Output</strong><br>Confidence radar, reward score, and a three-step improvement plan.</div>
</div>
</div>
"""
)
example_choice.change(
fn=load_example,
inputs=example_choice,
outputs=[code_input, traceback_input, context_input, example_header, summary_html, radar_html, plan_markdown, match_markdown, model_markdown],
show_progress="hidden",
)
analyze_button.click(
fn=analyze_inputs,
inputs=[code_input, traceback_input, context_input],
outputs=[summary_html, radar_html, plan_markdown, match_markdown, model_markdown],
show_progress="minimal",
)
clear_button.click(
fn=lambda: ("", "", "", "### Example Scenario\nChoose a built-in example or paste custom code.", *_default_outputs()),
inputs=None,
outputs=[code_input, traceback_input, context_input, example_header, summary_html, radar_html, plan_markdown, match_markdown, model_markdown],
show_progress="hidden",
)
demo.load(
fn=load_example,
inputs=example_choice,
outputs=[code_input, traceback_input, context_input, example_header, summary_html, radar_html, plan_markdown, match_markdown, model_markdown],
show_progress="hidden",
)
return demo
|