id int64 0 190k | prompt stringlengths 21 13.4M | docstring stringlengths 1 12k ⌀ |
|---|---|---|
28,030 | from __future__ import annotations
from typing import Any, Dict, Union
from langchain_core.retrievers import (
BaseRetriever,
RetrieverOutput,
)
from langchain_core.runnables import Runnable, RunnablePassthrough
RetrieverOutput = List[Document]
class BaseRetriever(RunnableSerializable[RetrieverInput, Retriev... | Create retrieval chain that retrieves documents and then passes them on. Args: retriever: Retriever-like object that returns list of documents. Should either be a subclass of BaseRetriever or a Runnable that returns a list of documents. If a subclass of BaseRetriever, then it is expected that an `input` key be passed i... |
28,031 | from __future__ import annotations
import warnings
from pathlib import Path
from typing import Any, Dict, List, Optional
from langchain_core.callbacks import CallbackManagerForChainRun
from langchain_core.language_models import BaseLanguageModel
from langchain_core.prompts.prompt import PromptTemplate
from langchain_co... | null |
28,032 | from typing import List
from langchain_core.language_models import BaseLanguageModel
from langchain_core.prompts.few_shot import FewShotPromptTemplate
from langchain_core.prompts.prompt import PromptTemplate
from langchain.chains.llm import LLMChain
TEST_GEN_TEMPLATE_SUFFIX = "Add another example."
class FewShotPrompt... | Return another example given a list of examples for a prompt. |
28,033 | from typing import Any, List, Optional, Type, Union
from langchain_core.language_models import BaseLanguageModel
from langchain_core.messages import HumanMessage, SystemMessage
from langchain_core.output_parsers import BaseLLMOutputParser
from langchain_core.output_parsers.openai_functions import (
OutputFunctionsP... | Create a question answering chain that returns an answer with sources. Args: llm: Language model to use for the chain. verbose: Whether to print the details of the chain **kwargs: Keyword arguments to pass to `create_qa_with_structure_chain`. Returns: Chain (LLMChain) that can be used to answer questions with citations... |
28,034 | from typing import Any, Optional
from langchain_core.language_models import BaseLanguageModel
from langchain_core.output_parsers.openai_functions import (
JsonOutputFunctionsParser,
PydanticOutputFunctionsParser,
)
from langchain_core.prompts import ChatPromptTemplate
from langchain.chains.base import Chain
fro... | Creates a chain that extracts information from a passage based on a schema. Args: schema: The schema of the entities to extract. llm: The language model to use. Returns: Chain (LLMChain) that can be used to extract information from a passage. |
28,035 | from typing import Any, Optional
from langchain_core.language_models import BaseLanguageModel
from langchain_core.output_parsers.openai_functions import (
JsonOutputFunctionsParser,
PydanticOutputFunctionsParser,
)
from langchain_core.prompts import ChatPromptTemplate
from langchain.chains.base import Chain
fro... | Creates a chain that extracts information from a passage based on a pydantic schema. Args: pydantic_schema: The pydantic schema of the entities to extract. llm: The language model to use. Returns: Chain (LLMChain) that can be used to extract information from a passage. |
28,036 | from __future__ import annotations
import json
import re
from collections import defaultdict
from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Tuple, Union
import requests
from langchain_community.chat_models import ChatOpenAI
from langchain_community.utilities.openapi import OpenAPISpec
from langc... | null |
28,037 | from __future__ import annotations
import json
import re
from collections import defaultdict
from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Tuple, Union
import requests
from langchain_community.chat_models import ChatOpenAI
from langchain_community.utilities.openapi import OpenAPISpec
from langc... | Create a chain for querying an API from a OpenAPI spec. Args: spec: OpenAPISpec or url/file/text string corresponding to one. llm: language model, should be an OpenAI function-calling model, e.g. `ChatOpenAI(model="gpt-3.5-turbo-0613")`. prompt: Main prompt template to use. request_chain: Chain for taking the functions... |
28,038 | from typing import Any, Dict
The provided code snippet includes necessary dependencies for implementing the `_resolve_schema_references` function. Write a Python function `def _resolve_schema_references(schema: Any, definitions: Dict[str, Any]) -> Any` to solve the following problem:
Resolves the $ref keys in a JSON s... | Resolves the $ref keys in a JSON schema object using the provided definitions. |
28,039 | from typing import Any, Dict
def _convert_schema(schema: dict) -> dict:
props = {k: {"title": k, **v} for k, v in schema["properties"].items()}
return {
"type": "object",
"properties": props,
"required": schema.get("required", []),
} | null |
28,040 | from typing import Any, Dict
The provided code snippet includes necessary dependencies for implementing the `get_llm_kwargs` function. Write a Python function `def get_llm_kwargs(function: dict) -> dict` to solve the following problem:
Returns the kwargs for the LLMChain constructor. Args: function: The function to us... | Returns the kwargs for the LLMChain constructor. Args: function: The function to use. Returns: The kwargs for the LLMChain constructor. |
28,041 | from typing import Iterator, List
from langchain_core.language_models import BaseLanguageModel
from langchain_core.messages import HumanMessage, SystemMessage
from langchain_core.output_parsers.openai_functions import PydanticOutputFunctionsParser
from langchain_core.prompts.chat import ChatPromptTemplate, HumanMessage... | Create a citation fuzzy match chain. Args: llm: Language model to use for the chain. Returns: Chain (LLMChain) that can be used to answer questions with citations. |
28,042 | from typing import (
Any,
Callable,
Dict,
Optional,
Sequence,
Type,
Union,
)
from langchain_core._api import deprecated
from langchain_core.language_models import BaseLanguageModel
from langchain_core.output_parsers import (
BaseLLMOutputParser,
)
from langchain_core.output_parsers.opena... | [Legacy] Create an LLMChain that uses an OpenAI function to get a structured output. Args: output_schema: Either a dictionary or pydantic.BaseModel class. If a dictionary is passed in, it's assumed to already be a valid JsonSchema. For best results, pydantic.BaseModels should have docstrings describing what the schema ... |
28,043 | from typing import Any, List, Optional
from langchain_core.language_models import BaseLanguageModel
from langchain_core.output_parsers.openai_functions import (
JsonKeyOutputFunctionsParser,
PydanticAttrOutputFunctionsParser,
)
from langchain_core.prompts import BasePromptTemplate, ChatPromptTemplate
from langc... | Creates a chain that extracts information from a passage. Args: schema: The schema of the entities to extract. llm: The language model to use. prompt: The prompt to use for extraction. verbose: Whether to run in verbose mode. In verbose mode, some intermediate logs will be printed to the console. Defaults to the global... |
28,044 | from typing import Any, List, Optional
from langchain_core.language_models import BaseLanguageModel
from langchain_core.output_parsers.openai_functions import (
JsonKeyOutputFunctionsParser,
PydanticAttrOutputFunctionsParser,
)
from langchain_core.prompts import BasePromptTemplate, ChatPromptTemplate
from langc... | Creates a chain that extracts information from a passage using pydantic schema. Args: pydantic_schema: The pydantic schema of the entities to extract. llm: The language model to use. prompt: The prompt to use for extraction. verbose: Whether to run in verbose mode. In verbose mode, some intermediate logs will be printe... |
28,045 | from __future__ import annotations
from typing import Any, Callable, List, Optional, Protocol, Tuple
from langchain_core.callbacks import Callbacks
from langchain_core.documents import Document
from langchain_core.pydantic_v1 import Extra
from langchain.chains.combine_documents.base import BaseCombineDocumentsChain
Th... | Split Documents into subsets that each meet a cumulative length constraint. Args: docs: The full list of Documents. length_func: Function for computing the cumulative length of a set of Documents. token_max: The maximum cumulative length of any subset of Documents. **kwargs: Arbitrary additional keyword params to pass ... |
28,046 | from __future__ import annotations
from typing import Any, Callable, List, Optional, Protocol, Tuple
from langchain_core.callbacks import Callbacks
from langchain_core.documents import Document
from langchain_core.pydantic_v1 import Extra
from langchain.chains.combine_documents.base import BaseCombineDocumentsChain
cla... | Execute a collapse function on a set of documents and merge their metadatas. Args: docs: A list of Documents to combine. combine_document_func: A function that takes in a list of Documents and optionally addition keyword parameters and combines them into a single string. **kwargs: Arbitrary additional keyword params to... |
28,047 | from __future__ import annotations
from typing import Any, Callable, List, Optional, Protocol, Tuple
from langchain_core.callbacks import Callbacks
from langchain_core.documents import Document
from langchain_core.pydantic_v1 import Extra
from langchain.chains.combine_documents.base import BaseCombineDocumentsChain
cla... | Execute a collapse function on a set of documents and merge their metadatas. Args: docs: A list of Documents to combine. combine_document_func: A function that takes in a list of Documents and optionally addition keyword parameters and combines them into a single string. **kwargs: Arbitrary additional keyword params to... |
28,048 | from typing import Any, Dict, List, Optional, Tuple
from langchain_core.callbacks import Callbacks
from langchain_core.documents import Document
from langchain_core.language_models import LanguageModelLike
from langchain_core.output_parsers import BaseOutputParser, StrOutputParser
from langchain_core.prompts import Bas... | Create a chain for passing a list of Documents to a model. Args: llm: Language model. prompt: Prompt template. Must contain input variable "context", which will be used for passing in the formatted documents. output_parser: Output parser. Defaults to StrOutputParser. document_prompt: Prompt used for formatting each doc... |
28,049 | from __future__ import annotations
from typing import Any, Dict, List, Tuple
from langchain_core.callbacks import Callbacks
from langchain_core.documents import Document
from langchain_core.prompts import BasePromptTemplate, format_document
from langchain_core.prompts.prompt import PromptTemplate
from langchain_core.py... | null |
28,050 | from abc import ABC, abstractmethod
from typing import Any, Dict, List, Optional, Tuple, Type
from langchain_core.callbacks import (
AsyncCallbackManagerForChainRun,
CallbackManagerForChainRun,
)
from langchain_core.documents import Document
from langchain_core.prompts import BasePromptTemplate, PromptTemplate
... | null |
28,051 | from typing import Any, Dict, List, Optional, TypedDict, Union
from langchain_community.utilities.sql_database import SQLDatabase
from langchain_core.language_models import BaseLanguageModel
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import BasePromptTemplate
from langchain_co... | Create a chain that generates SQL queries. *Security Note*: This chain generates SQL queries for the given database. The SQLDatabase class provides a get_table_info method that can be used to get column information as well as sample data from the table. To mitigate risk of leaking sensitive data, limit permissions to r... |
28,052 | import inspect
import json
import logging
import warnings
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Any, Dict, List, Optional, Type, Union, cast
import yaml
from langchain_core._api import deprecated
from langchain_core.callbacks import (
AsyncCallbackManager,
AsyncCallback... | null |
28,053 | from __future__ import annotations
from langchain_core.language_models import LanguageModelLike
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import BasePromptTemplate
from langchain_core.retrievers import RetrieverLike, RetrieverOutputLike
from langchain_core.runnables import Ru... | Create a chain that takes conversation history and returns documents. If there is no `chat_history`, then the `input` is just passed directly to the retriever. If there is `chat_history`, then the prompt and LLM will be used to generate a search query. That search query is then passed to the retriever. Args: llm: Langu... |
28,054 | from __future__ import annotations
import warnings
from typing import Any, Dict, List, Optional
from langchain_core.callbacks import CallbackManagerForChainRun
from langchain_core.language_models import BaseLanguageModel
from langchain_core.prompts import PromptTemplate
from langchain_core.pydantic_v1 import Extra, roo... | null |
28,055 | import datetime
import warnings
from typing import Any, Literal, Optional, Sequence, Union
from langchain_core.utils import check_package_version
from typing_extensions import TypedDict
from langchain.chains.query_constructor.ir import (
Comparator,
Comparison,
FilterDirective,
Operation,
Operator,
... | Dummy decorator for when lark is not installed. |
28,056 | import datetime
import warnings
from typing import Any, Literal, Optional, Sequence, Union
from langchain_core.utils import check_package_version
from typing_extensions import TypedDict
from langchain.chains.query_constructor.ir import (
Comparator,
Comparison,
FilterDirective,
Operation,
Operator,
... | Returns a parser for the query language. Args: allowed_comparators: Optional[Sequence[Comparator]] allowed_operators: Optional[Sequence[Operator]] Returns: Lark parser for the query language. |
28,057 | from __future__ import annotations
import json
from typing import Any, Callable, List, Optional, Sequence, Tuple, Union, cast
from langchain_core.exceptions import OutputParserException
from langchain_core.language_models import BaseLanguageModel
from langchain_core.output_parsers import BaseOutputParser
from langchain... | Fix invalid filter directive. Args: filter: Filter directive to fix. allowed_comparators: allowed comparators. Defaults to all comparators. allowed_operators: allowed operators. Defaults to all operators. allowed_attributes: allowed attributes. Defaults to all attributes. Returns: Fixed filter directive. |
28,058 | from __future__ import annotations
import json
from typing import Any, Callable, List, Optional, Sequence, Tuple, Union, cast
from langchain_core.exceptions import OutputParserException
from langchain_core.language_models import BaseLanguageModel
from langchain_core.output_parsers import BaseOutputParser
from langchain... | Load a query constructor chain. Args: llm: BaseLanguageModel to use for the chain. document_contents: The contents of the document to be queried. attribute_info: Sequence of attributes in the document. examples: Optional list of examples to use for the chain. allowed_comparators: Sequence of allowed comparators. Defaul... |
28,059 | from __future__ import annotations
import json
from typing import Any, Callable, List, Optional, Sequence, Tuple, Union, cast
from langchain_core.exceptions import OutputParserException
from langchain_core.language_models import BaseLanguageModel
from langchain_core.output_parsers import BaseOutputParser
from langchain... | Load a query constructor runnable chain. Args: llm: BaseLanguageModel to use for the chain. document_contents: Description of the page contents of the document to be queried. attribute_info: Sequence of attributes in the document. examples: Optional list of examples to use for the chain. allowed_comparators: Sequence o... |
28,060 | from __future__ import annotations
from abc import ABC, abstractmethod
from enum import Enum
from typing import Any, List, Optional, Sequence, Union
from langchain_core.pydantic_v1 import BaseModel
The provided code snippet includes necessary dependencies for implementing the `_to_snake_case` function. Write a Python ... | Convert a name into snake_case. |
28,061 | from __future__ import annotations
import asyncio
from typing import Any, Callable, Dict, Optional, Sequence, cast
from langchain_core.documents import Document
from langchain_core.language_models import BaseLanguageModel
from langchain_core.output_parsers import BaseOutputParser
from langchain_core.prompts import Prom... | Return the compression chain input. |
28,062 | from __future__ import annotations
import asyncio
from typing import Any, Callable, Dict, Optional, Sequence, cast
from langchain_core.documents import Document
from langchain_core.language_models import BaseLanguageModel
from langchain_core.output_parsers import BaseOutputParser
from langchain_core.prompts import Prom... | null |
28,063 | from typing import Any, Callable, Dict, Optional, Sequence
from langchain_core.documents import Document
from langchain_core.language_models import BaseLanguageModel
from langchain_core.prompts import BasePromptTemplate, PromptTemplate
from langchain.callbacks.manager import Callbacks
from langchain.chains import LLMCh... | null |
28,064 | from typing import Any, Callable, Dict, Optional, Sequence
from langchain_core.documents import Document
from langchain_core.language_models import BaseLanguageModel
from langchain_core.prompts import BasePromptTemplate, PromptTemplate
from langchain.callbacks.manager import Callbacks
from langchain.chains import LLMCh... | Return the compression chain input. |
28,065 | import asyncio
import logging
from typing import List, Optional, Sequence
from langchain_core.callbacks import (
AsyncCallbackManagerForRetrieverRun,
CallbackManagerForRetrieverRun,
)
from langchain_core.documents import Document
from langchain_core.language_models import BaseLanguageModel
from langchain_core.o... | null |
28,066 | import datetime
from copy import deepcopy
from typing import Any, Dict, List, Optional, Tuple
from langchain_core.callbacks import CallbackManagerForRetrieverRun
from langchain_core.documents import Document
from langchain_core.pydantic_v1 import Field
from langchain_core.retrievers import BaseRetriever
from langchain_... | Get the hours passed between two datetimes. |
28,067 | from typing import Tuple, Union
from langchain.chains.query_constructor.ir import (
Comparator,
Comparison,
Operation,
Operator,
StructuredQuery,
Visitor,
)
The provided code snippet includes necessary dependencies for implementing the `process_value` function. Write a Python function `def proc... | Convert a value to a string and add single quotes if it is a string. |
28,068 | import re
from typing import Any, Callable, Dict, Tuple
from langchain.chains.query_constructor.ir import (
Comparator,
Comparison,
Operation,
Operator,
StructuredQuery,
Visitor,
)
The provided code snippet includes necessary dependencies for implementing the `_DEFAULT_COMPOSER` function. Write... | Default composer for logical operators. Args: op_name: Name of the operator. Returns: Callable that takes a list of arguments and returns a string. |
28,069 | import re
from typing import Any, Callable, Dict, Tuple
from langchain.chains.query_constructor.ir import (
Comparator,
Comparison,
Operation,
Operator,
StructuredQuery,
Visitor,
)
The provided code snippet includes necessary dependencies for implementing the `_FUNCTION_COMPOSER` function. Writ... | Composer for functions. Args: op_name: Name of the function. Returns: Callable that takes a list of arguments and returns a string. |
28,070 | import logging
from typing import Any, Dict, List, Optional, Sequence, Tuple, Type, Union
from langchain_community.vectorstores import (
AstraDB,
Chroma,
DashVector,
DeepLake,
Dingo,
ElasticsearchStore,
Milvus,
MongoDBAtlasVectorSearch,
MyScale,
OpenSearchVectorSearch,
PGVect... | Get the translator class corresponding to the vector store class. |
28,071 | from typing import Tuple, Union
from langchain.chains.query_constructor.ir import (
Comparator,
Comparison,
Operation,
Operator,
StructuredQuery,
Visitor,
)
The provided code snippet includes necessary dependencies for implementing the `can_cast_to_float` function. Write a Python function `def ... | Check if a string can be cast to a float. |
28,072 | from typing import Tuple, Union
from langchain.chains.query_constructor.ir import (
Comparator,
Comparison,
Operation,
Operator,
StructuredQuery,
Visitor,
)
The provided code snippet includes necessary dependencies for implementing the `process_value` function. Write a Python function `def proc... | Convert a value to a string and add double quotes if it is a string. It required for comparators involving strings. Args: value: The value to convert. comparator: The comparator. Returns: The converted value as a string. |
28,073 | from __future__ import annotations
from abc import abstractmethod
from typing import Any, Dict, List, Optional
from langchain_core.load.dump import dumpd
from langchain_core.load.load import load
from langchain_core.load.serializable import Serializable
from langchain_core.messages import BaseMessage, get_buffer_string... | null |
28,074 | import random
adjectives = [
"abandoned",
"aching",
"advanced",
"ample",
"artistic",
"back",
"best",
"bold",
"brief",
"clear",
"cold",
"complicated",
"cooked",
"crazy",
"crushing",
"damp",
"dear",
"definite",
"dependable",
"diligent",
"... | Generate a random name. |
28,075 | from __future__ import annotations
import concurrent.futures
import dataclasses
import functools
import inspect
import logging
import uuid
from datetime import datetime, timezone
from enum import Enum
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
List,
Optional,
Tuple,
Union,
... | Validate that the example inputs are valid for the model. |
28,076 | from __future__ import annotations
import concurrent.futures
import dataclasses
import functools
import inspect
import logging
import uuid
from datetime import datetime, timezone
from enum import Enum
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
List,
Optional,
Tuple,
Union,
... | Configure the evaluators to run on the results of the chain. |
28,077 | from __future__ import annotations
import concurrent.futures
import dataclasses
import functools
import inspect
import logging
import uuid
from datetime import datetime, timezone
from enum import Enum
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
List,
Optional,
Tuple,
Union,
... | null |
28,078 | from __future__ import annotations
import concurrent.futures
import dataclasses
import functools
import inspect
import logging
import uuid
from datetime import datetime, timezone
from enum import Enum
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
List,
Optional,
Tuple,
Union,
... | null |
28,079 | from __future__ import annotations
import concurrent.futures
import dataclasses
import functools
import inspect
import logging
import uuid
from datetime import datetime, timezone
from enum import Enum
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
List,
Optional,
Tuple,
Union,
... | null |
28,080 | from __future__ import annotations
import concurrent.futures
import dataclasses
import functools
import inspect
import logging
import uuid
from datetime import datetime, timezone
from enum import Enum
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
List,
Optional,
Tuple,
Union,
... | null |
28,081 | from typing import Any, Optional, Sequence
from langchain_core._api import deprecated
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.language_models import BaseLanguageModel
from langchain_core.tools import BaseTool
from langchain.agents.agent import AgentExecutor
from langchain.agents.age... | Load an agent executor given tools and LLM. Args: tools: List of tools this agent has access to. llm: Language model to use as the agent. agent: Agent type to use. If None and agent_path is also None, will default to AgentType.ZERO_SHOT_REACT_DESCRIPTION. callback_manager: CallbackManager to use. Global callback manage... |
28,082 | from typing import List, Tuple
from langchain_core.agents import AgentAction
class AgentAction(Serializable):
"""A full description of an action for an ActionAgent to execute."""
tool: str
"""The name of the Tool to execute."""
tool_input: Union[str, dict]
"""The input to pass in to the Tool."""
... | Format the intermediate steps as XML. Args: intermediate_steps: The intermediate steps. Returns: The intermediate steps as XML. |
28,083 | import json
from typing import List, Sequence, Tuple
from langchain_core.agents import AgentAction, AgentActionMessageLog
from langchain_core.messages import AIMessage, BaseMessage, FunctionMessage
def _convert_agent_action_to_messages(
agent_action: AgentAction, observation: str
) -> List[BaseMessage]:
"""Conv... | Convert (AgentAction, tool output) tuples into FunctionMessages. Args: intermediate_steps: Steps the LLM has taken to date, along with observations Returns: list of messages to send to the LLM for the next prediction |
28,084 | from typing import List, Tuple
from langchain_core.agents import AgentAction
from langchain_core.messages import AIMessage, BaseMessage, HumanMessage
class AgentAction(Serializable):
"""A full description of an action for an ActionAgent to execute."""
tool: str
"""The name of the Tool to execute."""
t... | Construct the scratchpad that lets the agent continue its thought process. |
28,085 | import json
from typing import List, Sequence, Tuple
from langchain_core.agents import AgentAction
from langchain_core.messages import (
AIMessage,
BaseMessage,
ToolMessage,
)
from langchain.agents.output_parsers.openai_tools import OpenAIToolAgentAction
def _create_tool_message(
agent_action: OpenAIToo... | Convert (AgentAction, tool output) tuples into FunctionMessages. Args: intermediate_steps: Steps the LLM has taken to date, along with observations Returns: list of messages to send to the LLM for the next prediction |
28,086 | from typing import List, Tuple
from langchain_core.agents import AgentAction
class AgentAction(Serializable):
"""A full description of an action for an ActionAgent to execute."""
tool: str
"""The name of the Tool to execute."""
tool_input: Union[str, dict]
"""The input to pass in to the Tool."""
... | Construct the scratchpad that lets the agent continue its thought process. |
28,087 | import json
from json import JSONDecodeError
from typing import List, Union
from langchain_core.agents import AgentAction, AgentActionMessageLog, AgentFinish
from langchain_core.exceptions import OutputParserException
from langchain_core.messages import (
AIMessage,
BaseMessage,
)
from langchain_core.outputs im... | Parse an AI message potentially containing tool_calls. |
28,088 | from typing import Sequence
from langchain_core.tools import BaseTool
class BaseTool(RunnableSerializable[Union[str, Dict], Any]):
"""Interface LangChain tools must implement."""
def __init_subclass__(cls, **kwargs: Any) -> None:
"""Create the definition of the new tool class."""
super().__ini... | Validate tools for single input. |
28,089 | from __future__ import annotations
from typing import Optional, Sequence
from langchain_core.language_models import BaseLanguageModel
from langchain_core.prompts import BasePromptTemplate
from langchain_core.runnables import Runnable, RunnablePassthrough
from langchain_core.tools import BaseTool
from langchain.agents i... | Create an agent that uses ReAct prompting. Args: llm: LLM to use as the agent. tools: Tools this agent has access to. prompt: The prompt to use. See Prompt section below for more. output_parser: AgentOutputParser for parse the LLM output. tools_renderer: This controls how the tools are converted into a string and then ... |
28,090 | import json
import logging
from pathlib import Path
from typing import Any, List, Optional, Union
import yaml
from langchain_core._api import deprecated
from langchain_core.language_models import BaseLanguageModel
from langchain_core.tools import Tool
from langchain_core.utils.loading import try_load_from_hub
from lang... | Unified method for loading an agent from LangChainHub or local fs. Args: path: Path to the agent file. **kwargs: Additional keyword arguments passed to the agent executor. Returns: An agent executor. |
28,091 | import json
from json import JSONDecodeError
from typing import Any, List, Optional, Sequence, Tuple, Union
from langchain_core._api import deprecated
from langchain_core.agents import AgentAction, AgentActionMessageLog, AgentFinish
from langchain_core.callbacks import BaseCallbackManager, Callbacks
from langchain_core... | Parse an AI message. |
28,092 | from typing import Sequence
from langchain_core.language_models import BaseLanguageModel
from langchain_core.prompts.chat import ChatPromptTemplate
from langchain_core.runnables import Runnable, RunnablePassthrough
from langchain_core.tools import BaseTool
from langchain_core.utils.function_calling import convert_to_op... | Create an agent that uses OpenAI tools. Args: llm: LLM to use as the agent. tools: Tools this agent has access to. prompt: The prompt to use. See Prompt section below for more on the expected input variables. Returns: A Runnable sequence representing an agent. It takes as input all the same input variables as the promp... |
28,093 | from typing import Sequence
from langchain_core.language_models import BaseLanguageModel
from langchain_core.prompts.chat import ChatPromptTemplate
from langchain_core.runnables import Runnable, RunnablePassthrough
from langchain_core.tools import BaseTool
from langchain.agents.format_scratchpad import format_log_to_me... | Create an agent that uses JSON to format its logic, build for Chat Models. Args: llm: LLM to use as the agent. tools: Tools this agent has access to. prompt: The prompt to use. See Prompt section below for more. stop_sequence: Adds a stop token of "Observation:" to avoid hallucinates. Default is True. You may to set th... |
28,094 | import re
from typing import Any, List, Optional, Sequence, Tuple
from langchain_core._api import deprecated
from langchain_core.agents import AgentAction
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.language_models import BaseLanguageModel
from langchain_core.prompts import BasePromptTe... | Create an agent aimed at supporting tools with multiple inputs. Args: llm: LLM to use as the agent. tools: Tools this agent has access to. prompt: The prompt to use. See Prompt section below for more. tools_renderer: This controls how the tools are converted into a string and then passed into the LLM. Default is `rende... |
28,095 | from typing import Any, List, Sequence, Tuple, Union
from langchain_core._api import deprecated
from langchain_core.agents import AgentAction, AgentFinish
from langchain_core.callbacks import Callbacks
from langchain_core.language_models import BaseLanguageModel
from langchain_core.prompts.base import BasePromptTemplat... | Create an agent that uses XML to format its logic. Args: llm: LLM to use as the agent. tools: Tools this agent has access to. prompt: The prompt to use, must have input keys `tools`: contains descriptions for each tool. `agent_scratchpad`: contains previous agent actions and tool outputs. tools_renderer: This controls ... |
28,096 | from typing import Any, Sequence, Union
from langchain_community.utilities.google_serper import GoogleSerperAPIWrapper
from langchain_community.utilities.searchapi import SearchApiAPIWrapper
from langchain_community.utilities.serpapi import SerpAPIWrapper
from langchain_core._api import deprecated
from langchain_core.l... | Create an agent that uses self-ask with search prompting. Args: llm: LLM to use as the agent. tools: List of tools. Should just be of length 1, with that tool having name `Intermediate Answer` prompt: The prompt to use, must have input key `agent_scratchpad` which will contain agent actions and tool outputs. Returns: A... |
28,097 | from typing import Any, List, Optional
from langchain_core.language_models import BaseLanguageModel
from langchain_core.memory import BaseMemory
from langchain_core.messages import SystemMessage
from langchain_core.prompts.chat import MessagesPlaceholder
from langchain.agents.agent import AgentExecutor
from langchain... | A convenience method for creating a conversational retrieval agent. Args: llm: The language model to use, should be ChatOpenAI tools: A list of tools the agent has access to remember_intermediate_steps: Whether the agent should remember intermediate steps or not. Intermediate steps refer to prior action/observation pai... |
28,098 | from typing import Any, Dict, Optional
from langchain_core.language_models import BaseLanguageModel
from langchain.agents.agent import AgentExecutor
from langchain.agents.agent_toolkits.vectorstore.prompt import PREFIX, ROUTER_PREFIX
from langchain.agents.agent_toolkits.vectorstore.toolkit import (
VectorStoreRoute... | Construct a VectorStore agent from an LLM and tools. Args: llm (BaseLanguageModel): LLM that will be used by the agent toolkit (VectorStoreToolkit): Set of tools for the agent callback_manager (Optional[BaseCallbackManager], optional): Object to handle the callback [ Defaults to None. ] prefix (str, optional): The pref... |
28,099 | from typing import Any, Dict, Optional
from langchain_core.language_models import BaseLanguageModel
from langchain.agents.agent import AgentExecutor
from langchain.agents.agent_toolkits.vectorstore.prompt import PREFIX, ROUTER_PREFIX
from langchain.agents.agent_toolkits.vectorstore.toolkit import (
VectorStoreRoute... | Construct a VectorStore router agent from an LLM and tools. Args: llm (BaseLanguageModel): LLM that will be used by the agent toolkit (VectorStoreRouterToolkit): Set of tools for the agent which have routing capability with multiple vector stores callback_manager (Optional[BaseCallbackManager], optional): Object to han... |
28,100 | from typing import Any, List, Optional, Sequence, Tuple, Type, Union
from langchain_core._api import deprecated
from langchain_core.agents import AgentAction, AgentFinish
from langchain_core.callbacks import BaseCallbackManager, Callbacks
from langchain_core.language_models import BaseLanguageModel
from langchain_core.... | Create an agent that uses OpenAI function calling. Args: llm: LLM to use as the agent. Should work with OpenAI function calling, so either be an OpenAI model that supports that or a wrapper of a different model that adds in equivalent support. tools: Tools this agent has access to. prompt: The prompt to use. See Prompt... |
28,101 | from __future__ import annotations
import json
from json import JSONDecodeError
from time import sleep
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Sequence, Tuple, Union
from langchain_core.agents import AgentAction, AgentFinish
from langchain_core.callbacks import CallbackManager
from langchain_core.l... | null |
28,102 | from __future__ import annotations
import json
from json import JSONDecodeError
from time import sleep
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Sequence, Tuple, Union
from langchain_core.agents import AgentAction, AgentFinish
from langchain_core.callbacks import CallbackManager
from langchain_core.l... | null |
28,103 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,104 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,105 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,106 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,107 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,108 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,109 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,110 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,111 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,112 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,113 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,114 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,115 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,116 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,117 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,118 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,119 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,120 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,121 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,122 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,123 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,124 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,125 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,126 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,127 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,128 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
28,129 | import warnings
from typing import Any, Dict, List, Optional, Callable, Tuple
from mypy_extensions import Arg, KwArg
from langchain_core.tools import Tool
from langchain_core.language_models import BaseLanguageModel
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.callbacks import Callbacks
... | null |
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