id int64 0 190k | prompt stringlengths 21 13.4M | docstring stringlengths 1 12k ⌀ |
|---|---|---|
36,744 | from typing import Any, Callable, Dict, List, Optional, Tuple, cast
from llama_index.legacy.callbacks.schema import CBEventType, EventPayload
from llama_index.legacy.core.base_query_engine import BaseQueryEngine
from llama_index.legacy.core.response.schema import RESPONSE_TYPE
from llama_index.legacy.indices.query.quer... | Stop function for multi-step query combiner. |
36,745 | import logging
from typing import Callable, List, Optional, Sequence
from llama_index.legacy.async_utils import run_async_tasks
from llama_index.legacy.bridge.pydantic import BaseModel
from llama_index.legacy.callbacks.base import CallbackManager
from llama_index.legacy.callbacks.schema import CBEventType, EventPayload... | Combine multiple response from sub-engines. |
36,746 | import logging
from typing import Callable, List, Optional, Sequence
from llama_index.legacy.async_utils import run_async_tasks
from llama_index.legacy.bridge.pydantic import BaseModel
from llama_index.legacy.callbacks.base import CallbackManager
from llama_index.legacy.callbacks.schema import CBEventType, EventPayload... | Async combine multiple response from sub-engines. |
36,747 | import logging
from typing import Callable, List, Optional, Sequence
from llama_index.legacy.async_utils import run_async_tasks
from llama_index.legacy.bridge.pydantic import BaseModel
from llama_index.legacy.callbacks.base import CallbackManager
from llama_index.legacy.callbacks.schema import CBEventType, EventPayload... | Default node to metadata function. We use the node's text as the Tool description. |
36,748 | from string import Formatter
from typing import List
from llama_index.legacy.llms.base import BaseLLM
The provided code snippet includes necessary dependencies for implementing the `get_template_vars` function. Write a Python function `def get_template_vars(template_str: str) -> List[str]` to solve the following probl... | Get template variables from a template string. |
36,749 | from string import Formatter
from typing import List
from llama_index.legacy.llms.base import BaseLLM
class BaseLLM(ChainableMixin, BaseComponent):
"""LLM interface."""
callback_manager: CallbackManager = Field(
default_factory=CallbackManager, exclude=True
)
class Config:
arbitrary_t... | null |
36,750 | from contextlib import contextmanager
from typing import TYPE_CHECKING, Callable, Iterator
from llama_index.legacy.llms.huggingface import HuggingFaceLLM
from llama_index.legacy.llms.llama_cpp import LlamaCPP
from llama_index.legacy.llms.llm import LLM
class HuggingFaceLLM(CustomLLM):
"""HuggingFace LLM."""
m... | Prepare for using the LM format enforcer. This builds the processing function that will be injected into the LLM to activate the LM Format Enforcer. |
36,751 | from contextlib import contextmanager
from typing import TYPE_CHECKING, Callable, Iterator
from llama_index.legacy.llms.huggingface import HuggingFaceLLM
from llama_index.legacy.llms.llama_cpp import LlamaCPP
from llama_index.legacy.llms.llm import LLM
class HuggingFaceLLM(CustomLLM):
"""HuggingFace LLM."""
m... | Activate the LM Format Enforcer for the given LLM. with activate_lm_format_enforcer(llm, lm_format_enforcer_fn): llm.complete(...) |
36,752 | from typing import List
from llama_index.legacy.prompts.base import BasePromptTemplate
def get_empty_prompt_txt(prompt: BasePromptTemplate) -> str:
"""Get empty prompt text.
Substitute empty strings in parts of the prompt that have
not yet been filled out. Skip variables that have already
been partially... | Get biggest prompt. Oftentimes we need to fetch the biggest prompt, in order to be the most conservative about chunking text. This is a helper utility for that. |
36,753 | from llama_index.legacy.prompts.mixin import PromptDictType
PromptDictType = Dict[str, BasePromptTemplate]
The provided code snippet includes necessary dependencies for implementing the `display_prompt_dict` function. Write a Python function `def display_prompt_dict(prompts_dict: PromptDictType) -> None` to solve the... | Display prompt dict. Args: prompts_dict: prompt dict |
36,754 | from typing import Optional, Type, TypeVar
from llama_index.legacy.bridge.pydantic import BaseModel
from llama_index.legacy.output_parsers.base import OutputParserException
from llama_index.legacy.output_parsers.utils import parse_json_markdown
The provided code snippet includes necessary dependencies for implementing... | Convert a python format string to handlebars-style template. In python format string, single braces {} are used for variable substitution, and double braces {{}} are used for escaping actual braces (e.g. for JSON dict) In handlebars template, double braces {{}} are used for variable substitution, and single braces are ... |
36,755 | from typing import Optional, Type, TypeVar
from llama_index.legacy.bridge.pydantic import BaseModel
from llama_index.legacy.output_parsers.base import OutputParserException
from llama_index.legacy.output_parsers.utils import parse_json_markdown
def json_schema_to_guidance_output_template(
schema: dict,
key: Opt... | Convert a pydantic model to guidance output template. |
36,756 | from typing import Optional, Type, TypeVar
from llama_index.legacy.bridge.pydantic import BaseModel
from llama_index.legacy.output_parsers.base import OutputParserException
from llama_index.legacy.output_parsers.utils import parse_json_markdown
def wrap_json_markdown(text: str) -> str:
"""Wrap text in json markdown... | Convert a pydantic model to guidance output template wrapped in json markdown. |
36,757 | from typing import Optional, Type, TypeVar
from llama_index.legacy.bridge.pydantic import BaseModel
from llama_index.legacy.output_parsers.base import OutputParserException
from llama_index.legacy.output_parsers.utils import parse_json_markdown
Model = TypeVar("Model", bound=BaseModel)
class OutputParserException(Exce... | Parse output from guidance program. This is a temporary solution for parsing a pydantic object out of an executed guidance program. NOTE: right now we assume the output is the last markdown formatted json block NOTE: a better way is to extract via Program.variables, but guidance does not support extracting nested objec... |
36,758 | from typing import Any, Dict, List
from llama_index.legacy.bridge.langchain import BaseTool
from llama_index.legacy.bridge.pydantic import BaseModel, Field
from llama_index.legacy.core.base_query_engine import BaseQueryEngine
from llama_index.legacy.core.response.schema import RESPONSE_TYPE
from llama_index.legacy.sche... | Return a response with source node info. |
36,759 | from typing import Any, Optional
from llama_index.legacy.bridge.langchain import (
AgentExecutor,
AgentType,
BaseCallbackManager,
BaseLLM,
initialize_agent,
)
from llama_index.legacy.langchain_helpers.agents.toolkits import LlamaToolkit
def create_llama_agent(
toolkit: LlamaToolkit,
llm: Bas... | Load a chat llama agent given a Llama Toolkit and LLM. Args: toolkit: LlamaToolkit to use. llm: Language model to use as the agent. callback_manager: CallbackManager to use. Global callback manager is used if not provided. Defaults to None. agent_kwargs: Additional key word arguments to pass to the underlying agent **k... |
36,760 | from typing import Any, Dict, List, Optional
from llama_index.legacy.bridge.langchain import (
AIMessage,
BaseChatMemory,
BaseMessage,
HumanMessage,
)
from llama_index.legacy.bridge.langchain import BaseMemory as Memory
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.indices... | Get prompt input key. Copied over from langchain. |
36,761 | from typing import Callable, Optional
from llama_index.legacy.bridge.pydantic import BaseModel
from llama_index.legacy.callbacks.base import CallbackManager
from llama_index.legacy.prompts import BasePromptTemplate
from llama_index.legacy.prompts.default_prompt_selectors import (
DEFAULT_REFINE_PROMPT_SEL,
DEFA... | Get a response synthesizer. |
36,762 | import base64
import logging
from typing import List, Sequence
import requests
from llama_index.legacy.schema import ImageDocument
class ImageDocument(Document, ImageNode):
"""Data document containing an image."""
def class_name(cls) -> str:
return "ImageDocument"
def load_image_urls(image_urls: List... | null |
36,763 | import base64
import logging
from typing import List, Sequence
import requests
from llama_index.legacy.schema import ImageDocument
logger = logging.getLogger(__name__)
def encode_image(image_path: str) -> str:
with open(image_path, "rb") as image_file:
return base64.b64encode(image_file.read()).decode("utf-... | null |
36,764 | from typing import Any, Dict, Sequence, Tuple
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.constants import DEFAULT_CONTEXT_WINDOW, DEFAULT_NUM_OUTPUTS
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatResponse,
ChatResponseAsyncGen,
ChatResponseGen,
C... | null |
36,765 | from typing import Any, Dict, Sequence, Tuple
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.constants import DEFAULT_CONTEXT_WINDOW, DEFAULT_NUM_OUTPUTS
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatResponse,
ChatResponseAsyncGen,
ChatResponseGen,
C... | Convert messages to dicts. For use in ollama API |
36,766 | from http import HTTPStatus
from typing import Any, Dict, List, Sequence
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatResponse,
CompletionResponse,
)
from llama_index.legacy.schema import ImageDocument
class CompletionResponse(BaseModel):
"""
Completion response.
Fields:
... | null |
36,767 | from http import HTTPStatus
from typing import Any, Dict, List, Sequence
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatResponse,
CompletionResponse,
)
from llama_index.legacy.schema import ImageDocument
class ChatMessage(BaseModel):
"""Chat message."""
role: MessageRole = Messa... | null |
36,768 | from http import HTTPStatus
from typing import Any, Dict, List, Sequence
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatResponse,
CompletionResponse,
)
from llama_index.legacy.schema import ImageDocument
class ChatMessage(BaseModel):
"""Chat message."""
role: MessageRole = Messa... | null |
36,769 | from http import HTTPStatus
from typing import Any, Dict, List, Sequence
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatResponse,
CompletionResponse,
)
from llama_index.legacy.schema import ImageDocument
class ChatMessage(BaseModel):
"""Chat message."""
role: MessageRole = Messa... | null |
36,770 | from http import HTTPStatus
from typing import Any, Dict, List, Sequence
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatResponse,
CompletionResponse,
)
from llama_index.legacy.schema import ImageDocument
class ImageDocument(Document, ImageNode):
"""Data document containing an image."... | null |
36,771 | from http import HTTPStatus
from typing import Any, Dict, List, Optional, Sequence, Tuple
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.core.llms.types import (
ChatMessage,
ChatResponse,
ChatResponseAsyncGen,
ChatRe... | null |
36,772 | import json
import uuid
from typing import (
Any,
Callable,
Dict,
List,
Optional,
Sequence,
Tuple,
Union,
cast,
get_args,
)
import networkx
from llama_index.legacy.async_utils import run_jobs
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.callbacks i... | Add input to module deps inputs. |
36,773 | import json
import uuid
from typing import (
Any,
Callable,
Dict,
List,
Optional,
Sequence,
Tuple,
Union,
cast,
get_args,
)
import networkx
from llama_index.legacy.async_utils import run_jobs
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.callbacks i... | Add input to module deps inputs. |
36,774 | import json
import uuid
from typing import (
Any,
Callable,
Dict,
List,
Optional,
Sequence,
Tuple,
Union,
cast,
get_args,
)
import networkx
from llama_index.legacy.async_utils import run_jobs
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.callbacks i... | Print debug input. |
36,775 | import json
import uuid
from typing import (
Any,
Callable,
Dict,
List,
Optional,
Sequence,
Tuple,
Union,
cast,
get_args,
)
import networkx
from llama_index.legacy.async_utils import run_jobs
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.callbacks i... | Print debug input. |
36,776 | import json
import uuid
from typing import (
Any,
Callable,
Dict,
List,
Optional,
Sequence,
Tuple,
Union,
cast,
get_args,
)
import networkx
from llama_index.legacy.async_utils import run_jobs
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.callbacks i... | null |
36,777 | from inspect import signature
from typing import Any, Callable, Dict, Optional, Set, Tuple, cast
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr
from llama_index.legacy.callbacks.base import CallbackManager
from llama_index.legacy.core.query_pipeline.query_component import (
InputKeys,
OutputK... | Get parameters from function. Returns: Tuple[Set[str], Set[str]]: required and optional parameters |
36,778 | from inspect import signature
from typing import Any, Callable, Dict, Optional, Set, Tuple, cast
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr
from llama_index.legacy.callbacks.base import CallbackManager
from llama_index.legacy.core.query_pipeline.query_component import (
InputKeys,
OutputK... | Default agent input function. |
36,779 | import json
import re
from typing import Any, Generator, List, Optional
from llama_index.legacy.readers.base import BaseReader
from llama_index.legacy.schema import Document
import json
The provided code snippet includes necessary dependencies for implementing the `_depth_first_yield` function. Write a Python functio... | Do depth first yield of all of the leaf nodes of a JSON. Combines keys in the JSON tree using spaces. If levels_back is set to 0, prints all levels. If collapse_length is not None and the json_data is <= that number of characters, then we collapse it into one line. |
36,780 | import asyncio
import logging
import os
from typing import List, Optional
from llama_index.legacy.readers.base import BasePydanticReader
from llama_index.legacy.schema import Document
logger = logging.getLogger(__name__)
class Document(TextNode):
"""Generic interface for a data document.
This document connect... | Async read channel. Note: This is our hack to create a synchronous interface to the async discord.py API. We use the `asyncio` module to run this function with `asyncio.get_event_loop().run_until_complete`. |
36,781 | import logging
import re
from typing import TYPE_CHECKING, Any, List, Optional, Pattern
import numpy as np
_logger = logging.getLogger(__name__)
REDIS_REQUIRED_MODULES = [
{"name": "search", "ver": 20400},
{"name": "searchlight", "ver": 20400},
]
The provided code snippet includes necessary dependencies for im... | Check if the correct Redis modules are installed. |
36,782 | import logging
import re
from typing import TYPE_CHECKING, Any, List, Optional, Pattern
import numpy as np
The provided code snippet includes necessary dependencies for implementing the `get_redis_query` function. Write a Python function `def get_redis_query( return_fields: List[str], top_k: int = 20, vect... | Create a vector query for use with a SearchIndex. Args: return_fields (t.List[str]): A list of fields to return in the query results top_k (int, optional): The number of results to return. Defaults to 20. vector_field (str, optional): The name of the vector field in the index. Defaults to "vector". sort (bool, optional... |
36,783 | import logging
import re
from typing import TYPE_CHECKING, Any, List, Optional, Pattern
import numpy as np
def convert_bytes(data: Any) -> Any:
if isinstance(data, bytes):
return data.decode("ascii")
if isinstance(data, dict):
return dict(map(convert_bytes, data.items()))
if isinstance(data... | null |
36,784 | import logging
import re
from typing import TYPE_CHECKING, Any, List, Optional, Pattern
import numpy as np
def array_to_buffer(array: List[float], dtype: Any = np.float32) -> bytes:
return np.array(array).astype(dtype).tobytes() | null |
36,785 | import logging
import mimetypes
import multiprocessing
import os
import warnings
from datetime import datetime
from functools import reduce
from itertools import repeat
from pathlib import Path
from typing import Any, Callable, Dict, Generator, List, Optional, Type
from tqdm import tqdm
from llama_index.legacy.readers.... | Get some handy metadate from filesystem. Args: file_path: str: file path in str |
36,786 | import asyncio
import os
import time
from abc import ABC, abstractmethod
from typing import List, Tuple
from llama_index.legacy.readers.github_readers.github_api_client import (
GitBlobResponseModel,
GithubClient,
GitTreeResponseModel,
)
The provided code snippet includes necessary dependencies for impleme... | Log message if verbose is True. |
36,787 | import asyncio
import os
import time
from abc import ABC, abstractmethod
from typing import List, Tuple
from llama_index.legacy.readers.github_readers.github_api_client import (
GitBlobResponseModel,
GithubClient,
GitTreeResponseModel,
)
The provided code snippet includes necessary dependencies for impleme... | Get file extension. |
36,788 | import asyncio
import base64
import binascii
import logging
import os
import pathlib
import tempfile
from typing import Any, Callable, Dict, List, Optional, Tuple
from llama_index.legacy.readers.base import BaseReader
from llama_index.legacy.readers.file.base import DEFAULT_FILE_READER_CLS
from llama_index.legacy.reade... | Time a function. |
36,789 | import asyncio
import base64
import binascii
import logging
import os
import pathlib
import tempfile
from typing import Any, Callable, Dict, List, Optional, Tuple
from llama_index.legacy.readers.base import BaseReader
from llama_index.legacy.readers.file.base import DEFAULT_FILE_READER_CLS
from llama_index.legacy.reade... | Load data from a commit. |
36,790 | import asyncio
import base64
import binascii
import logging
import os
import pathlib
import tempfile
from typing import Any, Callable, Dict, List, Optional, Tuple
from llama_index.legacy.readers.base import BaseReader
from llama_index.legacy.readers.file.base import DEFAULT_FILE_READER_CLS
from llama_index.legacy.reade... | Load data from a branch. |
36,791 | from typing import Any, Dict, Type
from llama_index.legacy.readers.base import BasePydanticReader
from llama_index.legacy.readers.discord_reader import DiscordReader
from llama_index.legacy.readers.elasticsearch import ElasticsearchReader
from llama_index.legacy.readers.google_readers.gdocs import GoogleDocsReader
from... | null |
36,792 | from typing import Optional, Type
from llama_index.legacy.download.module import (
LLAMA_HUB_URL,
MODULE_TYPE,
download_llama_module,
track_download,
)
from llama_index.legacy.readers.base import BaseReader
LLAMA_HUB_URL = LLAMA_HUB_CONTENTS_URL + LLAMA_HUB_PATH
class MODULE_TYPE(str, Enum):
LO... | Download a single loader from the Loader Hub. Args: loader_class: The name of the loader class you want to download, such as `SimpleWebPageReader`. refresh_cache: If true, the local cache will be skipped and the loader will be fetched directly from the remote repo. use_gpt_index_import: If true, the loader files will u... |
36,793 | import logging
from typing import Any, Callable, Dict, List, Optional, Tuple
import requests
from llama_index.legacy.bridge.pydantic import PrivateAttr
from llama_index.legacy.readers.base import BasePydanticReader
from llama_index.legacy.schema import Document
The provided code snippet includes necessary dependencies... | Extract text from Substack blog post. |
36,794 | import logging
from typing import Any, List, Optional
from llama_index.legacy.readers.base import BaseReader
from llama_index.legacy.schema import Document
def escape_str(value: str) -> str:
BS = "\\"
must_escape = (BS, "'")
return (
"".join(f"{BS}{c}" if c in must_escape else c for c in value) if ... | null |
36,795 | import logging
from typing import Any, List, Optional
from llama_index.legacy.readers.base import BaseReader
from llama_index.legacy.schema import Document
def format_list_to_string(lst: List) -> str:
return "[" + ",".join(str(item) for item in lst) + "]" | null |
36,796 | from typing import List, Optional, Union
import numpy as np
from llama_index.legacy.readers.base import BaseReader
from llama_index.legacy.schema import Document
distance_metric_map = {
"l2": lambda a, b: np.linalg.norm(a - b, axis=1, ord=2),
"l1": lambda a, b: np.linalg.norm(a - b, axis=1, ord=1),
"max": l... | Naive search for nearest neighbors args: query_vector: Union[List, np.ndarray] data_vectors: np.ndarray limit (int): number of nearest neighbors distance_metric: distance function 'L2' for Euclidean, 'L1' for Nuclear, 'Max' l-infinity distance, 'cos' for cosine similarity, 'dot' for dot product returns: nearest_indices... |
36,797 | from typing import Dict, Type
from llama_index.legacy.node_parser.file.html import HTMLNodeParser
from llama_index.legacy.node_parser.file.json import JSONNodeParser
from llama_index.legacy.node_parser.file.markdown import MarkdownNodeParser
from llama_index.legacy.node_parser.file.simple_file import SimpleFileNodePars... | null |
36,798 | import logging
import uuid
from typing import List, Optional, Protocol, runtime_checkable
from llama_index.legacy.schema import (
BaseNode,
Document,
ImageDocument,
ImageNode,
NodeRelationship,
TextNode,
)
from llama_index.legacy.utils import truncate_text
logger = logging.getLogger(__name__)
cl... | Build nodes from splits. |
36,799 | import logging
from typing import Callable, List
from llama_index.legacy.node_parser.interface import TextSplitter
def split_text_keep_separator(text: str, separator: str) -> List[str]:
"""Split text with separator and keep the separator at the end of each split."""
parts = text.split(separator)
result = [s... | Split text by separator. |
36,800 | import logging
from typing import Callable, List
from llama_index.legacy.node_parser.interface import TextSplitter
The provided code snippet includes necessary dependencies for implementing the `split_by_char` function. Write a Python function `def split_by_char() -> Callable[[str], List[str]]` to solve the following ... | Split text by character. |
36,801 | import logging
from typing import Callable, List
from llama_index.legacy.node_parser.interface import TextSplitter
def split_by_sentence_tokenizer() -> Callable[[str], List[str]]:
import nltk
tokenizer = nltk.tokenize.PunktSentenceTokenizer()
# get the spans and then return the sentences
# using the ... | null |
36,802 | import logging
from typing import Callable, List
from llama_index.legacy.node_parser.interface import TextSplitter
def split_by_regex(regex: str) -> Callable[[str], List[str]]:
"""Split text by regex."""
import re
return lambda text: re.findall(regex, text)
The provided code snippet includes necessary depe... | Split text by phrase regex. This regular expression will split the sentences into phrases, where each phrase is a sequence of one or more non-comma, non-period, and non-semicolon characters, followed by an optional comma, period, or semicolon. The regular expression will also capture the delimiters themselves as separa... |
36,803 | from typing import Any, Dict, List, Optional, Sequence
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.callbacks.base import CallbackManager
from llama_index.legacy.callbacks.schema import CBEventType, EventPayload
from llama_index.legacy.node_parser.interface import NodeParser
from llama_i... | Add parent/child relationship between nodes. |
36,804 | from typing import Any, Dict, List, Optional, Sequence
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.callbacks.base import CallbackManager
from llama_index.legacy.callbacks.schema import CBEventType, EventPayload
from llama_index.legacy.node_parser.interface import NodeParser
from llama_i... | Get leaf nodes. |
36,805 | from typing import Any, Dict, List, Optional, Sequence
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.callbacks.base import CallbackManager
from llama_index.legacy.callbacks.schema import CBEventType, EventPayload
from llama_index.legacy.node_parser.interface import NodeParser
from llama_i... | Get root nodes. |
36,806 | from typing import Any, Callable, List, Optional
import pandas as pd
from llama_index.legacy.callbacks.base import CallbackManager
from llama_index.legacy.node_parser.relational.base_element import (
DEFAULT_SUMMARY_QUERY_STR,
BaseElementNodeParser,
Element,
)
from llama_index.legacy.schema import BaseNode,... | Convert HTML to dataframe. |
36,807 | from io import StringIO
from typing import Any, Callable, List, Optional
import pandas as pd
from llama_index.legacy.node_parser.relational.base_element import (
BaseElementNodeParser,
Element,
)
from llama_index.legacy.schema import BaseNode, TextNode
The provided code snippet includes necessary dependencies ... | Convert Markdown to dataframe. |
36,808 | import asyncio
import json
import logging
import time
from typing import Any, Dict, List, Optional, Tuple, Union, cast
from llama_index.legacy.agent.openai.utils import get_function_by_name
from llama_index.legacy.agent.types import BaseAgent
from llama_index.legacy.callbacks import (
CallbackManager,
CBEventTy... | From OpenAI thread messages. |
36,809 | import asyncio
import json
import logging
import time
from typing import Any, Dict, List, Optional, Tuple, Union, cast
from llama_index.legacy.agent.openai.utils import get_function_by_name
from llama_index.legacy.agent.types import BaseAgent
from llama_index.legacy.callbacks import (
CallbackManager,
CBEventTy... | Call a function and return the output as a string. |
36,810 | import asyncio
import json
import logging
import time
from typing import Any, Dict, List, Optional, Tuple, Union, cast
from llama_index.legacy.agent.openai.utils import get_function_by_name
from llama_index.legacy.agent.types import BaseAgent
from llama_index.legacy.callbacks import (
CallbackManager,
CBEventTy... | Call an async function and return the output as a string. |
36,811 | import asyncio
import json
import logging
import time
from typing import Any, Dict, List, Optional, Tuple, Union, cast
from llama_index.legacy.agent.openai.utils import get_function_by_name
from llama_index.legacy.agent.types import BaseAgent
from llama_index.legacy.callbacks import (
CallbackManager,
CBEventTy... | Process files. |
36,812 | import asyncio
import json
import logging
import uuid
from threading import Thread
from typing import Any, Dict, List, Optional, Tuple, Union, cast, get_args
from llama_index.legacy.agent.openai.utils import resolve_tool_choice
from llama_index.legacy.agent.types import (
BaseAgentWorker,
Task,
TaskStep,
... | Call a function and return the output as a string. |
36,813 | import asyncio
import json
import logging
import uuid
from threading import Thread
from typing import Any, Dict, List, Optional, Tuple, Union, cast, get_args
from llama_index.legacy.agent.openai.utils import resolve_tool_choice
from llama_index.legacy.agent.types import (
BaseAgentWorker,
Task,
TaskStep,
... | Call a function and return the output as a string. |
36,814 | from llama_index.legacy.agent.types import TaskStep
from llama_index.legacy.core.llms.types import MessageRole
from llama_index.legacy.llms.base import ChatMessage
from llama_index.legacy.memory import BaseMemory
class TaskStep(BaseModel):
"""Agent task step.
Represents a single input step within the executio... | Add user step to memory. |
36,815 | import re
from typing import Tuple
from llama_index.legacy.agent.react.types import (
ActionReasoningStep,
BaseReasoningStep,
ResponseReasoningStep,
)
from llama_index.legacy.output_parsers.utils import extract_json_str
from llama_index.legacy.types import BaseOutputParser
def extract_final_response(input_... | null |
36,816 | import re
from typing import Tuple
from llama_index.legacy.agent.react.types import (
ActionReasoningStep,
BaseReasoningStep,
ResponseReasoningStep,
)
from llama_index.legacy.output_parsers.utils import extract_json_str
from llama_index.legacy.types import BaseOutputParser
def extract_tool_use(input_text: s... | Parse an action reasoning step from the LLM output. |
36,817 | import asyncio
import uuid
from itertools import chain
from threading import Thread
from typing import (
Any,
AsyncGenerator,
Dict,
Generator,
List,
Optional,
Sequence,
Tuple,
cast,
)
from llama_index.legacy.agent.react.formatter import ReActChatFormatter
from llama_index.legacy.agen... | Add user step to memory. |
36,818 | import logging
from abc import abstractmethod
from typing import List, Optional, Sequence
from llama_index.legacy.agent.react.prompts import (
CONTEXT_REACT_CHAT_SYSTEM_HEADER,
REACT_CHAT_SYSTEM_HEADER,
)
from llama_index.legacy.agent.react.types import (
BaseReasoningStep,
ObservationReasoningStep,
)
f... | Tool. |
36,819 | import asyncio
import json
import logging
from abc import abstractmethod
from threading import Thread
from typing import Any, Dict, List, Optional, Tuple, Type, Union, cast, get_args
from llama_index.legacy.agent.openai.utils import get_function_by_name
from llama_index.legacy.agent.types import BaseAgent
from llama_in... | Call a function and return the output as a string. |
36,820 | import asyncio
import json
import logging
from abc import abstractmethod
from threading import Thread
from typing import Any, Dict, List, Optional, Tuple, Type, Union, cast, get_args
from llama_index.legacy.agent.openai.utils import get_function_by_name
from llama_index.legacy.agent.types import BaseAgent
from llama_in... | Call a function and return the output as a string. |
36,821 | import asyncio
import json
import logging
from abc import abstractmethod
from threading import Thread
from typing import Any, Dict, List, Optional, Tuple, Type, Union, cast, get_args
from llama_index.legacy.agent.openai.utils import get_function_by_name
from llama_index.legacy.agent.types import BaseAgent
from llama_in... | Resolve tool choice. If tool_choice is a function name string, return the appropriate dict. |
36,822 | from abc import abstractmethod
from collections import deque
from typing import Any, Deque, Dict, List, Optional, Union, cast
from llama_index.legacy.agent.types import (
BaseAgent,
BaseAgentWorker,
Task,
TaskStep,
TaskStepOutput,
)
from llama_index.legacy.bridge.pydantic import BaseModel, Field
fro... | Validate step from args. |
36,823 | import uuid
from typing import (
Any,
List,
Optional,
cast,
)
from llama_index.legacy.agent.types import (
BaseAgentWorker,
Task,
TaskStep,
TaskStepOutput,
)
from llama_index.legacy.bridge.pydantic import BaseModel, Field
from llama_index.legacy.callbacks import (
CallbackManager,
... | Get agent components. |
36,824 | import uuid
from typing import (
Any,
Dict,
List,
Optional,
Sequence,
Tuple,
cast,
)
from llama_index.legacy.agent.react.formatter import ReActChatFormatter
from llama_index.legacy.agent.react.output_parser import ReActOutputParser
from llama_index.legacy.agent.react.types import (
Actio... | Add user step to reasoning. Adds both text input and image input to reasoning. |
36,825 | import logging
import os
from string import Template
from typing import Any, Dict, List, Optional
from tenacity import retry, stop_after_attempt, wait_random_exponential
from llama_index.legacy.graph_stores.types import GraphStore
def hash_string_to_rank(string: str) -> int:
# get signed 64-bit hash value
sign... | null |
36,826 | import logging
import os
from string import Template
from typing import Any, Dict, List, Optional
from tenacity import retry, stop_after_attempt, wait_random_exponential
from llama_index.legacy.graph_stores.types import GraphStore
logger = logging.getLogger(__name__)
The provided code snippet includes necessary depend... | Prepare parameters for query. |
36,827 | import logging
import os
from string import Template
from typing import Any, Dict, List, Optional
from tenacity import retry, stop_after_attempt, wait_random_exponential
from llama_index.legacy.graph_stores.types import GraphStore
The provided code snippet includes necessary dependencies for implementing the `escape_s... | Escape String for NebulaGraph Query. |
36,828 | from llama_index.legacy.constants import DATA_KEY, TYPE_KEY
from llama_index.legacy.schema import (
BaseNode,
Document,
ImageDocument,
ImageNode,
IndexNode,
NodeRelationship,
RelatedNodeInfo,
TextNode,
)
TYPE_KEY = "__type__"
DATA_KEY = "__data__"
class BaseNode(BaseComponent):
de... | null |
36,829 | from llama_index.legacy.constants import DATA_KEY, TYPE_KEY
from llama_index.legacy.schema import (
BaseNode,
Document,
ImageDocument,
ImageNode,
IndexNode,
NodeRelationship,
RelatedNodeInfo,
TextNode,
)
def legacy_json_to_doc(doc_dict: dict) -> BaseNode:
"""Todo: Deprecated legacy s... | null |
36,830 | from enum import Enum
from typing import Dict, Type
from llama_index.legacy.storage.docstore.mongo_docstore import MongoDocumentStore
from llama_index.legacy.storage.docstore.simple_docstore import SimpleDocumentStore
from llama_index.legacy.storage.docstore.types import BaseDocumentStore
class SimpleDocumentStore(KVD... | null |
36,831 | from __future__ import annotations
import os
from decimal import Decimal
from typing import Any, Dict, List, Set, Tuple
from llama_index.legacy.storage.kvstore.types import DEFAULT_COLLECTION, BaseKVStore
def parse_schema(table: Any) -> Tuple[str, str]:
key_hash: str | None = None
key_range: str | None = None
... | null |
36,832 | from __future__ import annotations
import os
from decimal import Decimal
from typing import Any, Dict, List, Set, Tuple
from llama_index.legacy.storage.kvstore.types import DEFAULT_COLLECTION, BaseKVStore
def convert_float_to_decimal(obj: Any) -> Any:
if isinstance(obj, List):
return [convert_float_to_deci... | null |
36,833 | from __future__ import annotations
import os
from decimal import Decimal
from typing import Any, Dict, List, Set, Tuple
from llama_index.legacy.storage.kvstore.types import DEFAULT_COLLECTION, BaseKVStore
def convert_decimal_to_int_or_float(obj: Any) -> Any:
if isinstance(obj, List):
return [convert_decima... | null |
36,834 | import json
from typing import Any, Dict, List, Optional, Tuple, Type
from urllib.parse import urlparse
from llama_index.legacy.storage.kvstore.types import (
DEFAULT_BATCH_SIZE,
DEFAULT_COLLECTION,
BaseKVStore,
)
The provided code snippet includes necessary dependencies for implementing the `get_data_mode... | This part create a dynamic sqlalchemy model with a new table. |
36,835 | import json
from typing import Any, Dict, List, Optional, Tuple, Type
from urllib.parse import urlparse
from llama_index.legacy.storage.kvstore.types import (
DEFAULT_BATCH_SIZE,
DEFAULT_COLLECTION,
BaseKVStore,
)
def params_from_uri(uri: str) -> dict:
result = urlparse(uri)
database = result.path[... | null |
36,836 | from llama_index.legacy.constants import DATA_KEY, TYPE_KEY
from llama_index.legacy.data_structs.data_structs import IndexStruct
from llama_index.legacy.data_structs.registry import (
INDEX_STRUCT_TYPE_TO_INDEX_STRUCT_CLASS,
)
TYPE_KEY = "__type__"
DATA_KEY = "__data__"
class IndexStruct(DataClassJsonMixin):
... | null |
36,837 | from llama_index.legacy.constants import DATA_KEY, TYPE_KEY
from llama_index.legacy.data_structs.data_structs import IndexStruct
from llama_index.legacy.data_structs.registry import (
INDEX_STRUCT_TYPE_TO_INDEX_STRUCT_CLASS,
)
TYPE_KEY = "__type__"
DATA_KEY = "__data__"
class IndexStruct(DataClassJsonMixin):
... | null |
36,838 | import json
import logging
import sys
from typing import TYPE_CHECKING, Any, List, Optional
from urllib.parse import urlparse
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.llms import ChatMessage
from llama_index.legacy.storage.chat_store.base import BaseChatStore
def _message_to_dict(me... | null |
36,839 | import json
import logging
import sys
from typing import TYPE_CHECKING, Any, List, Optional
from urllib.parse import urlparse
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.llms import ChatMessage
from llama_index.legacy.storage.chat_store.base import BaseChatStore
def _dict_to_message(d:... | null |
36,840 | from llama_index.legacy.storage.chat_store.base import BaseChatStore
from llama_index.legacy.storage.chat_store.simple_chat_store import SimpleChatStore
RECOGNIZED_CHAT_STORES = {
SimpleChatStore.class_name(): SimpleChatStore,
}
class BaseChatStore(BaseComponent):
def class_name(cls) -> str:
"""Get cla... | Load a chat store from a dict. |
36,841 | import logging
from collections import Counter
from functools import partial
from typing import Any, Callable, Dict, List, Optional, cast
from llama_index.legacy.bridge.pydantic import PrivateAttr
from llama_index.legacy.schema import BaseNode, MetadataMode, TextNode
from llama_index.legacy.vector_stores.pinecone_utils... | Generate sparse vectors from a batch of contexts. NOTE: taken from https://www.pinecone.io/learn/hybrid-search-intro/. |
36,842 | import logging
from collections import Counter
from functools import partial
from typing import Any, Callable, Dict, List, Optional, cast
from llama_index.legacy.bridge.pydantic import PrivateAttr
from llama_index.legacy.schema import BaseNode, MetadataMode, TextNode
from llama_index.legacy.vector_stores.pinecone_utils... | Get default tokenizer. NOTE: taken from https://www.pinecone.io/learn/hybrid-search-intro/. |
36,843 | import logging
from collections import Counter
from functools import partial
from typing import Any, Callable, Dict, List, Optional, cast
from llama_index.legacy.bridge.pydantic import PrivateAttr
from llama_index.legacy.schema import BaseNode, MetadataMode, TextNode
from llama_index.legacy.vector_stores.pinecone_utils... | Convert from standard dataclass to pinecone filter dict. |
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