langchain の API リファレンス

langchain (langchain-ai/langchain) の公開 API 400 件 —— クラス 127、関数 57、メソッド 216。実際のソースを静的解析して抽出した正確なシグネチャを掲載しています。

種別	件数
クラス	127
関数	57
メソッド	216

API 一覧

funclibs.core.langchain_core._api.beta_decorator.emit_warning() -> None

Emit the warning.

funclibs.core.langchain_core._api.beta_decorator.finalize(_:Callable[..., Any], new_doc:str) -> T

Finalize the annotation of a class.

funclibs.core.langchain_core._api.beta_decorator.surface_langchain_beta_warnings() -> None

Unmute LangChain beta warnings.

func

libs.core.langchain_core._api.beta_decorator.warn_beta(*message:str='', *name:str='', *obj_type:str='', *addendum:str='') -> None

Display a standardized beta annotation.

funclibs.core.langchain_core._api.beta_decorator.warn_if_direct_instance(self:Any, *args:Any, **kwargs:Any) -> Any

Warn that the class is in beta.

funclibs.core.langchain_core._api.deprecation.emit_warning() -> None

Emit the warning.

funclibs.core.langchain_core._api.deprecation.finalize(_:Callable[..., Any], new_doc:str) -> T

Finalize the deprecation of a class.

funclibs.core.langchain_core._api.deprecation.surface_langchain_deprecation_warnings() -> None

Unmute LangChain deprecation warnings.

funclibs.core.langchain_core._api.deprecation.warn_if_direct_instance(self:Any, *args:Any, **kwargs:Any) -> Any

Warn that the class is in beta.

funclibs.core.langchain_core._security._policy.validate_hostname(hostname:str, policy:SSRFPolicy) -> None

Validate a hostname against the SSRF policy.

funclibs.core.langchain_core._security._policy.validate_resolved_ip(ip_str:str, policy:SSRFPolicy) -> None

Validate a resolved IP address against the SSRF policy.

funclibs.core.langchain_core._security._policy.validate_url_sync(url:str, policy:SSRFPolicy=DEFAULT_SSRF_POLICY) -> None

Synchronous URL validation (no DNS resolution).

func

libs.core.langchain_core._security._ssrf_protection.is_safe_url(url:str | AnyHttpUrl, *allow_private:bool=False, *allow_http:bool=True) -> bool

Non-throwing version of `validate_safe_url`.

func

libs.core.langchain_core._security._ssrf_protection.validate_safe_url(url:str | AnyHttpUrl, *allow_private:bool=False, *allow_http:bool=True) -> str

Validate a URL for SSRF protection.

func

libs.core.langchain_core._security._transport.ssrf_safe_client(policy:SSRFPolicy=DEFAULT_SSRF_POLICY, **kwargs:object) -> httpx.Client

Create an `httpx.Client` with SSRF protection.

classlibs.core.langchain_core.agents.AgentAction

Represents a request to execute an action by an agent.

methodlibs.core.langchain_core.agents.AgentAction.get_lc_namespace() -> list[str]

Get the namespace of the LangChain object.

methodlibs.core.langchain_core.agents.AgentAction.is_lc_serializable() -> bool

`AgentAction` is serializable.

classlibs.core.langchain_core.agents.AgentFinish

Final return value of an `ActionAgent`.

methodlibs.core.langchain_core.agents.AgentFinish.get_lc_namespace() -> list[str]

Get the namespace of the LangChain object.

methodlibs.core.langchain_core.agents.AgentFinish.is_lc_serializable() -> bool

Return `True` as this class is serializable.

methodlibs.core.langchain_core.agents.AgentFinish.messages() -> Sequence[BaseMessage]

Messages that correspond to this observation.

classlibs.core.langchain_core.agents.AgentStep

Result of running an `AgentAction`.

methodlibs.core.langchain_core.agents.AgentStep.messages() -> Sequence[BaseMessage]

Messages that correspond to this observation.

classlibs.core.langchain_core.caches.BaseCache

Interface for a caching layer for LLMs and Chat models.

methodlibs.core.langchain_core.caches.BaseCache.aclear(**kwargs:Any) -> None

Async clear cache that can take additional keyword arguments.

methodlibs.core.langchain_core.caches.BaseCache.alookup(prompt:str, llm_string:str) -> RETURN_VAL_TYPE | None

Async look up based on `prompt` and `llm_string`.

methodlibs.core.langchain_core.caches.BaseCache.clear(**kwargs:Any) -> None

Clear cache that can take additional keyword arguments.

methodlibs.core.langchain_core.caches.BaseCache.lookup(prompt:str, llm_string:str) -> RETURN_VAL_TYPE | None

Look up based on `prompt` and `llm_string`.

methodlibs.core.langchain_core.caches.BaseCache.update(prompt:str, llm_string:str, return_val:RETURN_VAL_TYPE) -> None

Update cache based on `prompt` and `llm_string`.

classlibs.core.langchain_core.caches.InMemoryCache

Cache that stores things in memory.

methodlibs.core.langchain_core.caches.InMemoryCache.aclear(**kwargs:Any) -> None

Async clear cache.

methodlibs.core.langchain_core.caches.InMemoryCache.alookup(prompt:str, llm_string:str) -> RETURN_VAL_TYPE | None

Async look up based on `prompt` and `llm_string`.

methodlibs.core.langchain_core.caches.InMemoryCache.clear(**kwargs:Any) -> None

Clear cache.

methodlibs.core.langchain_core.caches.InMemoryCache.lookup(prompt:str, llm_string:str) -> RETURN_VAL_TYPE | None

Look up based on `prompt` and `llm_string`.

methodlibs.core.langchain_core.caches.InMemoryCache.update(prompt:str, llm_string:str, return_val:RETURN_VAL_TYPE) -> None

Update cache based on `prompt` and `llm_string`.

classlibs.core.langchain_core.callbacks.base.AsyncCallbackHandler

Base async callback handler.

method

libs.core.langchain_core.callbacks.base.AsyncCallbackHandler.on_agent_action(action:AgentAction, *run_id:UUID, *parent_run_id:UUID | None=None, *tags:list[str] | None=None, **kwargs:Any) -> None

Run on agent action.

method

libs.core.langchain_core.callbacks.base.AsyncCallbackHandler.on_agent_finish(finish:AgentFinish, *run_id:UUID, *parent_run_id:UUID | None=None, *tags:list[str] | None=None, **kwargs:Any) -> None

Run on the agent end.

method

libs.core.langchain_core.callbacks.base.AsyncCallbackHandler.on_chain_end(outputs:dict[str, Any], *run_id:UUID, *parent_run_id:UUID | None=None, *tags:list[str] | None=None, **kwargs:Any) -> None

Run when a chain ends running.

method

libs.core.langchain_core.callbacks.base.AsyncCallbackHandler.on_chain_error(error:BaseException, *run_id:UUID, *parent_run_id:UUID | None=None, *tags:list[str] | None=None, **kwargs:Any) -> None

Run when chain errors.

method

libs.core.langchain_core.callbacks.base.AsyncCallbackHandler.on_llm_end(response:LLMResult, *run_id:UUID, *parent_run_id:UUID | None=None, *tags:list[str] | None=None, **kwargs:Any) -> None

Run when the model ends running.

method

libs.core.langchain_core.callbacks.base.AsyncCallbackHandler.on_llm_error(error:BaseException, *run_id:UUID, *parent_run_id:UUID | None=None, *tags:list[str] | None=None, **kwargs:Any) -> None

Run when LLM errors.

method

libs.core.langchain_core.callbacks.base.AsyncCallbackHandler.on_retriever_end(documents:Sequence[Document], *run_id:UUID, *parent_run_id:UUID | None=None, *tags:list[str] | None=None, **kwargs:Any) -> None

Run on the retriever end.

method

libs.core.langchain_core.callbacks.base.AsyncCallbackHandler.on_retriever_error(error:BaseException, *run_id:UUID, *parent_run_id:UUID | None=None, *tags:list[str] | None=None, **kwargs:Any) -> None

Run on retriever error.

method

libs.core.langchain_core.callbacks.base.AsyncCallbackHandler.on_retry(retry_state:RetryCallState, *run_id:UUID, *parent_run_id:UUID | None=None, **kwargs:Any) -> Any

Run on a retry event.

method

libs.core.langchain_core.callbacks.base.AsyncCallbackHandler.on_text(text:str, *run_id:UUID, *parent_run_id:UUID | None=None, *tags:list[str] | None=None, **kwargs:Any) -> None

Run on an arbitrary text.

method

libs.core.langchain_core.callbacks.base.AsyncCallbackHandler.on_tool_end(output:Any, *run_id:UUID, *parent_run_id:UUID | None=None, *tags:list[str] | None=None, **kwargs:Any) -> None

Run when the tool ends running.

method

libs.core.langchain_core.callbacks.base.AsyncCallbackHandler.on_tool_error(error:BaseException, *run_id:UUID, *parent_run_id:UUID | None=None, *tags:list[str] | None=None, **kwargs:Any) -> None

Run when tool errors.

classlibs.core.langchain_core.callbacks.base.BaseCallbackHandler

Base callback handler.

methodlibs.core.langchain_core.callbacks.base.BaseCallbackHandler.ignore_agent() -> bool

Whether to ignore agent callbacks.

methodlibs.core.langchain_core.callbacks.base.BaseCallbackHandler.ignore_chain() -> bool

Whether to ignore chain callbacks.

methodlibs.core.langchain_core.callbacks.base.BaseCallbackHandler.ignore_chat_model() -> bool

Whether to ignore chat model callbacks.

methodlibs.core.langchain_core.callbacks.base.BaseCallbackHandler.ignore_custom_event() -> bool

Ignore custom event.

methodlibs.core.langchain_core.callbacks.base.BaseCallbackHandler.ignore_llm() -> bool

Whether to ignore LLM callbacks.

methodlibs.core.langchain_core.callbacks.base.BaseCallbackHandler.ignore_retriever() -> bool

Whether to ignore retriever callbacks.

methodlibs.core.langchain_core.callbacks.base.BaseCallbackHandler.ignore_retry() -> bool

Whether to ignore retry callbacks.

classlibs.core.langchain_core.callbacks.base.BaseCallbackManager

Base callback manager.

method

libs.core.langchain_core.callbacks.base.BaseCallbackManager.add_handler(handler:BaseCallbackHandler, inherit:bool=True) -> None

Add a handler to the callback manager.

method

libs.core.langchain_core.callbacks.base.BaseCallbackManager.add_metadata(metadata:dict[str, Any], inherit:bool=True) -> None

Add metadata to the callback manager.

methodlibs.core.langchain_core.callbacks.base.BaseCallbackManager.add_tags(tags:list[str], inherit:bool=True) -> None

Add tags to the callback manager.

methodlibs.core.langchain_core.callbacks.base.BaseCallbackManager.copy() -> Self

Return a copy of the callback manager.

methodlibs.core.langchain_core.callbacks.base.BaseCallbackManager.is_async() -> bool

Whether the callback manager is async.

methodlibs.core.langchain_core.callbacks.base.BaseCallbackManager.remove_handler(handler:BaseCallbackHandler) -> None

Remove a handler from the callback manager.

methodlibs.core.langchain_core.callbacks.base.BaseCallbackManager.remove_metadata(keys:list[str]) -> None

Remove metadata from the callback manager.

methodlibs.core.langchain_core.callbacks.base.BaseCallbackManager.remove_tags(tags:list[str]) -> None

Remove tags from the callback manager.

classlibs.core.langchain_core.callbacks.base.CallbackManagerMixin

Mixin for callback manager.

classlibs.core.langchain_core.callbacks.base.ChainManagerMixin

Mixin for chain callbacks.

method

libs.core.langchain_core.callbacks.base.ChainManagerMixin.on_agent_action(action:AgentAction, *run_id:UUID, *parent_run_id:UUID | None=None, **kwargs:Any) -> Any

Run on agent action.

method

libs.core.langchain_core.callbacks.base.ChainManagerMixin.on_agent_finish(finish:AgentFinish, *run_id:UUID, *parent_run_id:UUID | None=None, **kwargs:Any) -> Any

Run on the agent end.

method

libs.core.langchain_core.callbacks.base.ChainManagerMixin.on_chain_end(outputs:dict[str, Any], *run_id:UUID, *parent_run_id:UUID | None=None, **kwargs:Any) -> Any

Run when chain ends running.

method

libs.core.langchain_core.callbacks.base.ChainManagerMixin.on_chain_error(error:BaseException, *run_id:UUID, *parent_run_id:UUID | None=None, **kwargs:Any) -> Any

Run when chain errors.

classlibs.core.langchain_core.callbacks.base.LLMManagerMixin

Mixin for LLM callbacks.

method

libs.core.langchain_core.callbacks.base.LLMManagerMixin.on_llm_end(response:LLMResult, *run_id:UUID, *parent_run_id:UUID | None=None, *tags:list[str] | None=None, **kwargs:Any) -> Any

Run when LLM ends running.

method

libs.core.langchain_core.callbacks.base.LLMManagerMixin.on_llm_error(error:BaseException, *run_id:UUID, *parent_run_id:UUID | None=None, *tags:list[str] | None=None, **kwargs:Any) -> Any

Run when LLM errors.

classlibs.core.langchain_core.callbacks.base.RetrieverManagerMixin

Mixin for `Retriever` callbacks.

method

libs.core.langchain_core.callbacks.base.RetrieverManagerMixin.on_retriever_end(documents:Sequence[Document], *run_id:UUID, *parent_run_id:UUID | None=None, **kwargs:Any) -> Any

Run when `Retriever` ends running.

method

libs.core.langchain_core.callbacks.base.RetrieverManagerMixin.on_retriever_error(error:BaseException, *run_id:UUID, *parent_run_id:UUID | None=None, **kwargs:Any) -> Any

Run when `Retriever` errors.

classlibs.core.langchain_core.callbacks.base.RunManagerMixin

Mixin for run manager.

method

libs.core.langchain_core.callbacks.base.RunManagerMixin.on_retry(retry_state:RetryCallState, *run_id:UUID, *parent_run_id:UUID | None=None, **kwargs:Any) -> Any

Run on a retry event.

method

libs.core.langchain_core.callbacks.base.RunManagerMixin.on_text(text:str, *run_id:UUID, *parent_run_id:UUID | None=None, **kwargs:Any) -> Any

Run on an arbitrary text.

classlibs.core.langchain_core.callbacks.base.ToolManagerMixin

Mixin for tool callbacks.

method

libs.core.langchain_core.callbacks.base.ToolManagerMixin.on_tool_end(output:Any, *run_id:UUID, *parent_run_id:UUID | None=None, **kwargs:Any) -> Any

Run when the tool ends running.

method

libs.core.langchain_core.callbacks.base.ToolManagerMixin.on_tool_error(error:BaseException, *run_id:UUID, *parent_run_id:UUID | None=None, **kwargs:Any) -> Any

Run when tool errors.

classlibs.core.langchain_core.callbacks.file.FileCallbackHandler

Callback handler that writes to a file.

methodlibs.core.langchain_core.callbacks.file.FileCallbackHandler.close() -> None

Close the file if it's open.

methodlibs.core.langchain_core.callbacks.file.FileCallbackHandler.on_chain_end(outputs:dict[str, Any], **kwargs:Any) -> None

Print that we finished a chain.

method

libs.core.langchain_core.callbacks.file.FileCallbackHandler.on_chain_start(serialized:dict[str, Any], inputs:dict[str, Any], **kwargs:Any) -> None

Print that we are entering a chain.

method

libs.core.langchain_core.callbacks.file.FileCallbackHandler.on_text(text:str, color:str | None=None, end:str='', **kwargs:Any) -> None

Handle text output.

classlibs.core.langchain_core.callbacks.manager.AsyncCallbackManagerForChainGroup

Async callback manager for the chain group.

method

libs.core.langchain_core.callbacks.manager.AsyncCallbackManagerForChainGroup.on_chain_end(outputs:dict[str, Any] | Any, **kwargs:Any) -> None

Run when traced chain group ends.

method

libs.core.langchain_core.callbacks.manager.AsyncCallbackManagerForChainGroup.on_chain_error(error:BaseException, **kwargs:Any) -> None

Run when chain errors.

classlibs.core.langchain_core.callbacks.manager.AsyncCallbackManagerForChainRun

Async callback manager for chain run.

method

libs.core.langchain_core.callbacks.manager.AsyncCallbackManagerForChainRun.on_agent_action(action:AgentAction, **kwargs:Any) -> None

Run when agent action is received.

method

libs.core.langchain_core.callbacks.manager.AsyncCallbackManagerForChainRun.on_agent_finish(finish:AgentFinish, **kwargs:Any) -> None

Run when agent finish is received.

method

libs.core.langchain_core.callbacks.manager.AsyncCallbackManagerForChainRun.on_chain_end(outputs:dict[str, Any] | Any, **kwargs:Any) -> None

Run when a chain ends running.

method

libs.core.langchain_core.callbacks.manager.AsyncCallbackManagerForChainRun.on_chain_error(error:BaseException, **kwargs:Any) -> None

Run when chain errors.

classlibs.core.langchain_core.callbacks.manager.AsyncCallbackManagerForLLMRun

Async callback manager for LLM run.

method

libs.core.langchain_core.callbacks.manager.AsyncCallbackManagerForLLMRun.on_llm_end(response:LLMResult, **kwargs:Any) -> None

Run when LLM ends running.

method

libs.core.langchain_core.callbacks.manager.AsyncCallbackManagerForLLMRun.on_llm_error(error:BaseException, **kwargs:Any) -> None

Run when LLM errors.

classlibs.core.langchain_core.callbacks.manager.AsyncCallbackManagerForRetrieverRun

Async callback manager for retriever run.

method

libs.core.langchain_core.callbacks.manager.AsyncCallbackManagerForRetrieverRun.on_retriever_end(documents:Sequence[Document], **kwargs:Any) -> None

Run when the retriever ends running.

method

libs.core.langchain_core.callbacks.manager.AsyncCallbackManagerForRetrieverRun.on_retriever_error(error:BaseException, **kwargs:Any) -> None

Run when retriever errors.

classlibs.core.langchain_core.callbacks.manager.AsyncCallbackManagerForToolRun

Async callback manager for tool run.

methodlibs.core.langchain_core.callbacks.manager.AsyncCallbackManagerForToolRun.on_tool_end(output:Any, **kwargs:Any) -> None

Async run when the tool ends running.

method

libs.core.langchain_core.callbacks.manager.AsyncCallbackManagerForToolRun.on_tool_error(error:BaseException, **kwargs:Any) -> None

Run when tool errors.

classlibs.core.langchain_core.callbacks.manager.AsyncParentRunManager

Async parent run manager.

methodlibs.core.langchain_core.callbacks.manager.AsyncParentRunManager.get_child(tag:str | None=None) -> AsyncCallbackManager

Get a child callback manager.

classlibs.core.langchain_core.callbacks.manager.AsyncRunManager

Async run manager.

methodlibs.core.langchain_core.callbacks.manager.AsyncRunManager.get_sync() -> RunManager

Get the equivalent sync `RunManager`.

methodlibs.core.langchain_core.callbacks.manager.AsyncRunManager.on_retry(retry_state:RetryCallState, **kwargs:Any) -> None

Async run when a retry is received.

methodlibs.core.langchain_core.callbacks.manager.AsyncRunManager.on_text(text:str, **kwargs:Any) -> None

Run when a text is received.

classlibs.core.langchain_core.callbacks.manager.BaseRunManager

Base class for run manager (a bound callback manager).

classlibs.core.langchain_core.callbacks.manager.CallbackManager

Callback manager for LangChain.

method

libs.core.langchain_core.callbacks.manager.CallbackManager.on_llm_start(serialized:dict[str, Any], prompts:list[str], run_id:UUID | None=None, **kwargs:Any) -> list[CallbackManagerForLLMRun]

Run when LLM starts running.

classlibs.core.langchain_core.callbacks.manager.CallbackManagerForChainGroup

Callback manager for the chain group.

method

libs.core.langchain_core.callbacks.manager.CallbackManagerForChainGroup.on_chain_end(outputs:dict[str, Any] | Any, **kwargs:Any) -> None

Run when traced chain group ends.

method

libs.core.langchain_core.callbacks.manager.CallbackManagerForChainGroup.on_chain_error(error:BaseException, **kwargs:Any) -> None

Run when chain errors.

classlibs.core.langchain_core.callbacks.manager.CallbackManagerForChainRun

Callback manager for chain run.

method

libs.core.langchain_core.callbacks.manager.CallbackManagerForChainRun.on_agent_action(action:AgentAction, **kwargs:Any) -> None

Run when agent action is received.

method

libs.core.langchain_core.callbacks.manager.CallbackManagerForChainRun.on_agent_finish(finish:AgentFinish, **kwargs:Any) -> None

Run when agent finish is received.

method

libs.core.langchain_core.callbacks.manager.CallbackManagerForChainRun.on_chain_end(outputs:dict[str, Any] | Any, **kwargs:Any) -> None

Run when chain ends running.

method

libs.core.langchain_core.callbacks.manager.CallbackManagerForChainRun.on_chain_error(error:BaseException, **kwargs:Any) -> None

Run when chain errors.

classlibs.core.langchain_core.callbacks.manager.CallbackManagerForLLMRun

Callback manager for LLM run.

methodlibs.core.langchain_core.callbacks.manager.CallbackManagerForLLMRun.on_llm_end(response:LLMResult, **kwargs:Any) -> None

Run when LLM ends running.

method

libs.core.langchain_core.callbacks.manager.CallbackManagerForLLMRun.on_llm_error(error:BaseException, **kwargs:Any) -> None

Run when LLM errors.

classlibs.core.langchain_core.callbacks.manager.CallbackManagerForRetrieverRun

Callback manager for retriever run.

method

libs.core.langchain_core.callbacks.manager.CallbackManagerForRetrieverRun.on_retriever_end(documents:Sequence[Document], **kwargs:Any) -> None

Run when retriever ends running.

method

libs.core.langchain_core.callbacks.manager.CallbackManagerForRetrieverRun.on_retriever_error(error:BaseException, **kwargs:Any) -> None

Run when retriever errors.

classlibs.core.langchain_core.callbacks.manager.CallbackManagerForToolRun

Callback manager for tool run.

methodlibs.core.langchain_core.callbacks.manager.CallbackManagerForToolRun.on_tool_end(output:Any, **kwargs:Any) -> None

Run when the tool ends running.

method

libs.core.langchain_core.callbacks.manager.CallbackManagerForToolRun.on_tool_error(error:BaseException, **kwargs:Any) -> None

Run when tool errors.

classlibs.core.langchain_core.callbacks.manager.ParentRunManager

Synchronous parent run manager.

methodlibs.core.langchain_core.callbacks.manager.ParentRunManager.get_child(tag:str | None=None) -> CallbackManager

Get a child callback manager.

classlibs.core.langchain_core.callbacks.manager.RunManager

Synchronous run manager.

methodlibs.core.langchain_core.callbacks.manager.RunManager.on_retry(retry_state:RetryCallState, **kwargs:Any) -> None

Run when a retry is received.

methodlibs.core.langchain_core.callbacks.manager.RunManager.on_text(text:str, **kwargs:Any) -> None

Run when a text is received.

func

libs.core.langchain_core.callbacks.manager.adispatch_custom_event(name:str, data:Any, *config:RunnableConfig | None=None) -> None

Dispatch an adhoc event to the handlers.

func

libs.core.langchain_core.callbacks.manager.ahandle_event(handlers:list[BaseCallbackHandler], event_name:str, ignore_condition_name:str | None, *args:Any, **kwargs:Any) -> None

Async generic event handler for `AsyncCallbackManager`.

func

libs.core.langchain_core.callbacks.manager.dispatch_custom_event(name:str, data:Any, *config:RunnableConfig | None=None) -> None

Dispatch an adhoc event.

func

libs.core.langchain_core.callbacks.manager.handle_event(handlers:list[BaseCallbackHandler], event_name:str, ignore_condition_name:str | None, *args:Any, **kwargs:Any) -> None

Generic event handler for `CallbackManager`.

classlibs.core.langchain_core.callbacks.stdout.StdOutCallbackHandler

Callback handler that prints to std out.

method

libs.core.langchain_core.callbacks.stdout.StdOutCallbackHandler.on_agent_action(action:AgentAction, color:str | None=None, **kwargs:Any) -> Any

Run on agent action.

method

libs.core.langchain_core.callbacks.stdout.StdOutCallbackHandler.on_agent_finish(finish:AgentFinish, color:str | None=None, **kwargs:Any) -> None

Run on the agent end.

method

libs.core.langchain_core.callbacks.stdout.StdOutCallbackHandler.on_chain_end(outputs:dict[str, Any], **kwargs:Any) -> None

Print out that we finished a chain.

method

libs.core.langchain_core.callbacks.stdout.StdOutCallbackHandler.on_chain_start(serialized:dict[str, Any], inputs:dict[str, Any], **kwargs:Any) -> None

Print out that we are entering a chain.

method

libs.core.langchain_core.callbacks.stdout.StdOutCallbackHandler.on_text(text:str, color:str | None=None, end:str='', **kwargs:Any) -> None

Run when the agent ends.

classlibs.core.langchain_core.callbacks.streaming_stdout.StreamingStdOutCallbackHandler

Callback handler for streaming.

method

libs.core.langchain_core.callbacks.streaming_stdout.StreamingStdOutCallbackHandler.on_agent_action(action:AgentAction, **kwargs:Any) -> Any

Run on agent action.

method

libs.core.langchain_core.callbacks.streaming_stdout.StreamingStdOutCallbackHandler.on_agent_finish(finish:AgentFinish, **kwargs:Any) -> None

Run on the agent end.

method

libs.core.langchain_core.callbacks.streaming_stdout.StreamingStdOutCallbackHandler.on_chain_end(outputs:dict[str, Any], **kwargs:Any) -> None

Run when a chain ends running.

method

libs.core.langchain_core.callbacks.streaming_stdout.StreamingStdOutCallbackHandler.on_chain_error(error:BaseException, **kwargs:Any) -> None

Run when chain errors.

method

libs.core.langchain_core.callbacks.streaming_stdout.StreamingStdOutCallbackHandler.on_chain_start(serialized:dict[str, Any], inputs:dict[str, Any], **kwargs:Any) -> None

Run when a chain starts running.

method

libs.core.langchain_core.callbacks.streaming_stdout.StreamingStdOutCallbackHandler.on_chat_model_start(serialized:dict[str, Any], messages:list[list[BaseMessage]], **kwargs:Any) -> None

Run when LLM starts running.

method

libs.core.langchain_core.callbacks.streaming_stdout.StreamingStdOutCallbackHandler.on_llm_end(response:LLMResult, **kwargs:Any) -> None

Run when LLM ends running.

method

libs.core.langchain_core.callbacks.streaming_stdout.StreamingStdOutCallbackHandler.on_llm_error(error:BaseException, **kwargs:Any) -> None

Run when LLM errors.

method

libs.core.langchain_core.callbacks.streaming_stdout.StreamingStdOutCallbackHandler.on_llm_new_token(token:str | list[str | dict[str, Any]], **kwargs:Any) -> None

Run on new LLM token.

method

libs.core.langchain_core.callbacks.streaming_stdout.StreamingStdOutCallbackHandler.on_llm_start(serialized:dict[str, Any], prompts:list[str], **kwargs:Any) -> None

Run when LLM starts running.

method

libs.core.langchain_core.callbacks.streaming_stdout.StreamingStdOutCallbackHandler.on_text(text:str, **kwargs:Any) -> None

Run on an arbitrary text.

method

libs.core.langchain_core.callbacks.streaming_stdout.StreamingStdOutCallbackHandler.on_tool_end(output:Any, **kwargs:Any) -> None

Run when tool ends running.

method

libs.core.langchain_core.callbacks.streaming_stdout.StreamingStdOutCallbackHandler.on_tool_error(error:BaseException, **kwargs:Any) -> None

Run when tool errors.

method

libs.core.langchain_core.callbacks.streaming_stdout.StreamingStdOutCallbackHandler.on_tool_start(serialized:dict[str, Any], input_str:str, **kwargs:Any) -> None

Run when the tool starts running.

func

libs.core.langchain_core.callbacks.usage.get_usage_metadata_callback(name:str='usage_metadata_callback') -> Generator[UsageMetadataCallbackHandler, None, None]

Get usage metadata callback.

methodlibs.core.langchain_core.chat_history.InMemoryChatMessageHistory.aadd_messages(messages:Sequence[BaseMessage]) -> None

Async add messages to the store.

methodlibs.core.langchain_core.chat_history.InMemoryChatMessageHistory.aclear() -> None

Async clear all messages from the store.

methodlibs.core.langchain_core.chat_history.InMemoryChatMessageHistory.add_message(message:BaseMessage) -> None

Add a self-created message to the store.

methodlibs.core.langchain_core.chat_history.InMemoryChatMessageHistory.aget_messages() -> list[BaseMessage]

Async version of getting messages.

methodlibs.core.langchain_core.chat_history.InMemoryChatMessageHistory.clear() -> None

Clear all messages from the store.

classlibs.core.langchain_core.chat_loaders.BaseChatLoader

Base class for chat loaders.

methodlibs.core.langchain_core.chat_loaders.BaseChatLoader.lazy_load() -> Iterator[ChatSession]

Lazy load the chat sessions.

methodlibs.core.langchain_core.chat_loaders.BaseChatLoader.load() -> list[ChatSession]

Eagerly load the chat sessions into memory.

classlibs.core.langchain_core.chat_sessions.ChatSession

Chat Session.

classlibs.core.langchain_core.cross_encoders.BaseCrossEncoder

Interface for cross encoder models.

methodlibs.core.langchain_core.cross_encoders.BaseCrossEncoder.score(text_pairs:list[tuple[str, str]]) -> list[float]

Score pairs' similarity.

classlibs.core.langchain_core.document_loaders.base.BaseBlobParser

Abstract interface for blob parsers.

methodlibs.core.langchain_core.document_loaders.base.BaseBlobParser.lazy_parse(blob:Blob) -> Iterator[Document]

Lazy parsing interface.

classlibs.core.langchain_core.document_loaders.base.BaseLoader

Interface for document loader.

methodlibs.core.langchain_core.document_loaders.base.BaseLoader.alazy_load() -> AsyncIterator[Document]

A lazy loader for `Document`.

methodlibs.core.langchain_core.document_loaders.base.BaseLoader.aload() -> list[Document]

Load data into `Document` objects.

methodlibs.core.langchain_core.document_loaders.base.BaseLoader.lazy_load() -> Iterator[Document]

A lazy loader for `Document`.

methodlibs.core.langchain_core.document_loaders.base.BaseLoader.load() -> list[Document]

Load data into `Document` objects.

method

libs.core.langchain_core.document_loaders.base.BaseLoader.load_and_split(text_splitter:TextSplitter | None=None) -> list[Document]

Load `Document` and split into chunks.

methodlibs.core.langchain_core.documents.base.Blob.as_bytes() -> bytes

Read data as bytes.

methodlibs.core.langchain_core.documents.base.Blob.as_bytes_io() -> Generator[BytesIO | BufferedReader, None, None]

Read data as a byte stream.

methodlibs.core.langchain_core.documents.base.Blob.as_string() -> str

Read data as a string.

methodlibs.core.langchain_core.documents.base.Blob.check_blob_is_valid(values:dict[str, Any]) -> Any

Verify that either data or path is provided.

classlibs.core.langchain_core.documents.base.Document

Class for storing a piece of text and associated metadata.

methodlibs.core.langchain_core.documents.base.Document.get_lc_namespace() -> list[str]

Get the namespace of the LangChain object.

methodlibs.core.langchain_core.documents.base.Document.is_lc_serializable() -> bool

Return `True` as this class is serializable.

classlibs.core.langchain_core.documents.compressor.BaseDocumentCompressor

Base class for document compressors.

method

libs.core.langchain_core.documents.transformers.BaseDocumentTransformer.transform_documents(documents:Sequence[Document], **kwargs:Any) -> Sequence[Document]

Transform a list of documents.

classlibs.core.langchain_core.embeddings.embeddings.Embeddings

Interface for embedding models.

methodlibs.core.langchain_core.embeddings.embeddings.Embeddings.aembed_documents(texts:list[str]) -> list[list[float]]

Asynchronous Embed search docs.

methodlibs.core.langchain_core.embeddings.embeddings.Embeddings.aembed_query(text:str) -> list[float]

Asynchronous Embed query text.

methodlibs.core.langchain_core.embeddings.embeddings.Embeddings.embed_documents(texts:list[str]) -> list[list[float]]

Embed search docs.

methodlibs.core.langchain_core.embeddings.embeddings.Embeddings.embed_query(text:str) -> list[float]

Embed query text.

classlibs.core.langchain_core.embeddings.fake.FakeEmbeddings

Fake embedding model for unit testing purposes.

classlibs.core.langchain_core.example_selectors.length_based.LengthBasedExampleSelector

Select examples based on length.

method

libs.core.langchain_core.example_selectors.length_based.LengthBasedExampleSelector.aadd_example(example:dict[str, str]) -> None

Async add new example to list.

method

libs.core.langchain_core.example_selectors.length_based.LengthBasedExampleSelector.add_example(example:dict[str, str]) -> None

Add new example to list.

funclibs.core.langchain_core.example_selectors.semantic_similarity.sorted_values(values:dict[str, str]) -> list[str]

Return a list of values in dict sorted by key.

classlibs.core.langchain_core.exceptions.ErrorCode

Error codes.

classlibs.core.langchain_core.exceptions.LangChainException

General LangChain exception.

classlibs.core.langchain_core.exceptions.TracerException

Base class for exceptions in tracers module.

funclibs.core.langchain_core.globals.get_debug() -> bool

Get the value of the `debug` global setting.

funclibs.core.langchain_core.globals.get_llm_cache() -> Optional['BaseCache']

Get the value of the `llm_cache` global setting.

funclibs.core.langchain_core.globals.get_verbose() -> bool

Get the value of the `verbose` global setting.

funclibs.core.langchain_core.globals.set_debug(value:bool) -> None

Set a new value for the `debug` global setting.

funclibs.core.langchain_core.globals.set_llm_cache(value:Optional['BaseCache']) -> None

Set a new LLM cache, overwriting the previous value, if any.

funclibs.core.langchain_core.globals.set_verbose(value:bool) -> None

Set a new value for the `verbose` global setting.

classlibs.core.langchain_core.indexing.api.IndexingException

Raised when an indexing operation fails.

classlibs.core.langchain_core.indexing.base.DeleteResponse

A generic response for delete operation.

methodlibs.core.langchain_core.indexing.base.DocumentIndex.adelete(ids:list[str] | None=None, **kwargs:Any) -> DeleteResponse

Delete by IDs or other criteria.

methodlibs.core.langchain_core.indexing.base.DocumentIndex.aget(ids:Sequence[str], **kwargs:Any) -> list[Document]

Get documents by id.

methodlibs.core.langchain_core.indexing.base.DocumentIndex.aupsert(items:Sequence[Document], **kwargs:Any) -> UpsertResponse

Add or update documents in the `VectorStore`.

methodlibs.core.langchain_core.indexing.base.DocumentIndex.delete(ids:list[str] | None=None, **kwargs:Any) -> DeleteResponse

Delete by IDs or other criteria.

methodlibs.core.langchain_core.indexing.base.DocumentIndex.get(ids:Sequence[str], **kwargs:Any) -> list[Document]

Get documents by id.

methodlibs.core.langchain_core.indexing.base.DocumentIndex.upsert(items:Sequence[Document], **kwargs:Any) -> UpsertResponse

Upsert documents into the index.

classlibs.core.langchain_core.indexing.base.InMemoryRecordManager

An in-memory record manager for testing purposes.

methodlibs.core.langchain_core.indexing.base.InMemoryRecordManager.adelete_keys(keys:Sequence[str]) -> None

Async delete specified records from the database.

methodlibs.core.langchain_core.indexing.base.InMemoryRecordManager.delete_keys(keys:Sequence[str]) -> None

Delete specified records from the database.

methodlibs.core.langchain_core.indexing.base.InMemoryRecordManager.exists(keys:Sequence[str]) -> list[bool]

Check if the provided keys exist in the database.

method

libs.core.langchain_core.indexing.base.InMemoryRecordManager.update(keys:Sequence[str], *group_ids:Sequence[str | None] | None=None, *time_at_least:float | None=None) -> None

Upsert records into the database.

methodlibs.core.langchain_core.indexing.base.RecordManager.delete_keys(keys:Sequence[str]) -> None

Delete specified records from the database.

methodlibs.core.langchain_core.indexing.base.RecordManager.exists(keys:Sequence[str]) -> list[bool]

Check if the provided keys exist in the database.

method

libs.core.langchain_core.indexing.base.RecordManager.update(keys:Sequence[str], *group_ids:Sequence[str | None] | None=None, *time_at_least:float | None=None) -> None

Upsert records into the database.

classlibs.core.langchain_core.indexing.base.UpsertResponse

A generic response for upsert operations.

classlibs.core.langchain_core.indexing.in_memory.InMemoryDocumentIndex

In memory document index.

method

libs.core.langchain_core.indexing.in_memory.InMemoryDocumentIndex.delete(ids:list[str] | None=None, **kwargs:Any) -> DeleteResponse

Delete by IDs.

method

libs.core.langchain_core.indexing.in_memory.InMemoryDocumentIndex.upsert(items:Sequence[Document], **kwargs:Any) -> UpsertResponse

Upsert documents into the index.

func

libs.core.langchain_core.language_models._compat_bridge.amessage_to_events(msg:BaseMessage, *message_id:str | None=None) -> AsyncIterator[MessagesData]

Async variant of `message_to_events`.

classlibs.core.langchain_core.language_models.base.LangSmithParams

LangSmith parameters for tracing.

funclibs.core.langchain_core.language_models.base.get_tokenizer() -> Any

Get a GPT-2 tokenizer instance.

classlibs.core.langchain_core.language_models.chat_model_stream.SyncTextProjection

String-specialized sync projection.

methodlibs.core.langchain_core.language_models.chat_model_stream.SyncTextProjection.push(delta:str) -> None

Append a text delta.

classlibs.core.langchain_core.language_models.chat_models.BaseChatModel

Base class for chat models.

methodlibs.core.langchain_core.language_models.chat_models.BaseChatModel.OutputType() -> Any

Get the output type for this `Runnable`.

methodlibs.core.langchain_core.language_models.chat_models.BaseChatModel.asdict() -> builtins.dict[str, Any]

Return a dictionary representation of the chat model.

methodlibs.core.langchain_core.language_models.chat_models.BaseChatModel.dict(**_kwargs:Any) -> builtins.dict[str, Any]

DEPRECATED - use `asdict()` instead.

func

libs.core.langchain_core.language_models.chat_models.agenerate_from_stream(stream:AsyncIterator[ChatGenerationChunk]) -> ChatResult

Async generate from a stream.

func

libs.core.langchain_core.language_models.chat_models.generate_from_stream(stream:Iterator[ChatGenerationChunk]) -> ChatResult

Generate from a stream.

classlibs.core.langchain_core.language_models.fake.FakeListLLM

Fake LLM for testing purposes.

classlibs.core.langchain_core.language_models.fake.FakeListLLMError

Fake error for testing purposes.

classlibs.core.langchain_core.language_models.fake.FakeStreamingListLLM

Fake streaming list LLM for testing purposes.

classlibs.core.langchain_core.language_models.fake_chat_models.FakeChatModel

Fake Chat Model wrapper for testing purposes.

classlibs.core.langchain_core.language_models.fake_chat_models.FakeListChatModel

Fake chat model for testing purposes.

classlibs.core.langchain_core.language_models.fake_chat_models.FakeListChatModelError

Fake error for testing purposes.

classlibs.core.langchain_core.language_models.fake_chat_models.FakeMessagesListChatModel

Fake chat model for testing purposes.

classlibs.core.langchain_core.language_models.llms.BaseLLM

Base LLM abstract interface.

methodlibs.core.langchain_core.language_models.llms.BaseLLM.OutputType() -> type[str]

Get the output type for this `Runnable`.

methodlibs.core.langchain_core.language_models.llms.BaseLLM.asdict() -> builtins.dict[str, Any]

Return a dictionary representation of the LLM.

methodlibs.core.langchain_core.language_models.llms.BaseLLM.dict(**_kwargs:Any) -> builtins.dict[str, Any]

DEPRECATED - use `asdict()` instead.

methodlibs.core.langchain_core.language_models.llms.BaseLLM.save(file_path:Path | str) -> None

Save the LLM.

classlibs.core.langchain_core.language_models.llms.LLM

Simple interface for implementing a custom LLM.

funclibs.core.langchain_core.load.dump.default(obj:Any) -> Any

Return a default value for an object.

funclibs.core.langchain_core.load.dump.dumpd(obj:Any) -> Any

Return a dict representation of an object.

funclibs.core.langchain_core.load.dump.dumps(obj:Any, *pretty:bool=False, **kwargs:Any) -> str

Return a JSON string representation of an object.

classlibs.core.langchain_core.load.load.Reviver

Reviver for JSON objects.

classlibs.core.langchain_core.load.serializable.BaseSerialized

Base class for serialized objects.

classlibs.core.langchain_core.load.serializable.Serializable

Serializable base class.

methodlibs.core.langchain_core.load.serializable.Serializable.get_lc_namespace() -> list[str]

Get the namespace of the LangChain object.

methodlibs.core.langchain_core.load.serializable.Serializable.is_lc_serializable() -> bool

Is this class serializable?

methodlibs.core.langchain_core.load.serializable.Serializable.to_json() -> SerializedConstructor | SerializedNotImplemented

Serialize the object to JSON.

methodlibs.core.langchain_core.load.serializable.Serializable.to_json_not_implemented() -> SerializedNotImplemented

Serialize a "not implemented" object.

classlibs.core.langchain_core.load.serializable.SerializedConstructor

Serialized constructor.

classlibs.core.langchain_core.load.serializable.SerializedNotImplemented

Serialized not implemented.

classlibs.core.langchain_core.load.serializable.SerializedSecret

Serialized secret.

funclibs.core.langchain_core.load.serializable.to_json_not_implemented(obj:object) -> SerializedNotImplemented

Serialize a "not implemented" object.

funclibs.core.langchain_core.load.serializable.try_neq_default(value:Any, key:str, model:BaseModel) -> bool

Try to determine if a value is different from the default.

classlibs.core.langchain_core.messages.ai.AIMessage

Message from an AI.

methodlibs.core.langchain_core.messages.ai.AIMessage.lc_attributes() -> dict[str, Any]

Attributes to be serialized.

methodlibs.core.langchain_core.messages.ai.AIMessage.pretty_repr(html:bool=False) -> str

Return a pretty representation of the message for display.

classlibs.core.langchain_core.messages.ai.AIMessageChunk

Message chunk from an AI (yielded when streaming).

methodlibs.core.langchain_core.messages.ai.AIMessageChunk.init_server_tool_calls() -> Self

Initialize server tool calls.

methodlibs.core.langchain_core.messages.ai.AIMessageChunk.init_tool_calls() -> Self

Initialize tool calls from tool call chunks.

classlibs.core.langchain_core.messages.ai.InputTokenDetails

Breakdown of input token counts.

classlibs.core.langchain_core.messages.ai.OutputTokenDetails

Breakdown of output token counts.

classlibs.core.langchain_core.messages.ai.UsageMetadata

Usage metadata for a message, such as token counts.

func

libs.core.langchain_core.messages.ai.add_ai_message_chunks(left:AIMessageChunk, *others:AIMessageChunk) -> AIMessageChunk

Add multiple `AIMessageChunk`s together.

funclibs.core.langchain_core.messages.ai.add_usage(left:UsageMetadata | None, right:UsageMetadata | None) -> UsageMetadata

Recursively add two UsageMetadata objects.

func

libs.core.langchain_core.messages.ai.subtract_usage(left:UsageMetadata | None, right:UsageMetadata | None) -> UsageMetadata

Recursively subtract two `UsageMetadata` objects.

classlibs.core.langchain_core.messages.base.BaseMessage

Base abstract message class.

methodlibs.core.langchain_core.messages.base.BaseMessage.get_lc_namespace() -> list[str]

Get the namespace of the LangChain object.

methodlibs.core.langchain_core.messages.base.BaseMessage.is_lc_serializable() -> bool

`BaseMessage` is serializable.

methodlibs.core.langchain_core.messages.base.BaseMessage.pretty_print() -> None

Print a pretty representation of the message.

methodlibs.core.langchain_core.messages.base.BaseMessage.pretty_repr(html:bool=False) -> str

Get a pretty representation of the message.

funclibs.core.langchain_core.messages.base.get_msg_title_repr(title:str, *bold:bool=False) -> str

Get a title representation for a message.

func

libs.core.langchain_core.messages.base.merge_content(first_content:str | list[str | dict[Any, Any]], *contents:str | list[str | dict[Any, Any]]) -> str | list[str | dict[Any, Any]]

Merge multiple message contents.

funclibs.core.langchain_core.messages.base.message_to_dict(message:BaseMessage) -> dict[str, Any]

Convert a Message to a dictionary.

classlibs.core.langchain_core.messages.chat.ChatMessage

Message that can be assigned an arbitrary speaker (i.e.

classlibs.core.langchain_core.messages.chat.ChatMessageChunk

Chat Message chunk.

classlibs.core.langchain_core.messages.content.AudioContentBlock

Audio data.

classlibs.core.langchain_core.messages.content.Citation

Annotation for citing data from a document.

classlibs.core.langchain_core.messages.content.ImageContentBlock

Image data.

classlibs.core.langchain_core.messages.content.InvalidToolCall

Allowance for errors made by LLM.

classlibs.core.langchain_core.messages.content.NonStandardAnnotation

Provider-specific annotation format.

classlibs.core.langchain_core.messages.content.NonStandardContentBlock

Provider-specific content data.

classlibs.core.langchain_core.messages.content.ReasoningContentBlock

Reasoning output from a LLM.

classlibs.core.langchain_core.messages.content.ServerToolCall

Tool call that is executed server-side.

classlibs.core.langchain_core.messages.content.ServerToolResult

Result of a server-side tool call.

classlibs.core.langchain_core.messages.content.TextContentBlock

Text output from a LLM.

classlibs.core.langchain_core.messages.content.ToolCall

Represents an AI's request to call a tool.

classlibs.core.langchain_core.messages.content.ToolCallChunk

A chunk of a tool call (yielded when streaming).

classlibs.core.langchain_core.messages.content.VideoContentBlock

Video data.

func

libs.core.langchain_core.messages.content.create_citation(*url:str | None=None, *title:str | None=None, *start_index:int | None=None, *end_index:int | None=None, *cited_text:str | None=None, *id:str | None=None, **kwargs:Any) -> Citation

Create a `Citation`.

func

libs.core.langchain_core.messages.content.create_non_standard_block(value:dict[str, Any], *id:str | None=None, *index:int | str | None=None) -> NonStandardContentBlock

Create a `NonStandardContentBlock`.

func

libs.core.langchain_core.messages.content.create_reasoning_block(reasoning:str | None=None, id:str | None=None, index:int | str | None=None, **kwargs:Any) -> ReasoningContentBlock

Create a `ReasoningContentBlock`.

func

libs.core.langchain_core.messages.content.create_text_block(text:str, *id:str | None=None, *annotations:list[Annotation] | None=None, *index:int | str | None=None, **kwargs:Any) -> TextContentBlock

Create a `TextContentBlock`.

func

libs.core.langchain_core.messages.content.create_tool_call(name:str, args:dict[str, Any], *id:str | None=None, *index:int | str | None=None, **kwargs:Any) -> ToolCall

Create a `ToolCall`.

classlibs.core.langchain_core.messages.function.FunctionMessageChunk

Function Message chunk.

classlibs.core.langchain_core.messages.human.HumanMessage

Message from the user.

classlibs.core.langchain_core.messages.human.HumanMessageChunk

Human Message chunk.

classlibs.core.langchain_core.messages.modifier.RemoveMessage

Message responsible for deleting other messages.

classlibs.core.langchain_core.messages.system.SystemMessage

Message for priming AI behavior.

classlibs.core.langchain_core.messages.system.SystemMessageChunk

System Message chunk.

classlibs.core.langchain_core.messages.tool.ToolCall

Represents an AI's request to call a tool.

classlibs.core.langchain_core.messages.tool.ToolCallChunk

A chunk of a tool call (yielded when streaming).

classlibs.core.langchain_core.messages.tool.ToolMessageChunk

Tool Message chunk.

classlibs.core.langchain_core.messages.tool.ToolOutputMixin

Mixin for objects that tools can return directly.

func

libs.core.langchain_core.messages.tool.default_tool_chunk_parser(raw_tool_calls:list[dict[str, Any]]) -> list[ToolCallChunk]

Best-effort parsing of tool chunks.

func

libs.core.langchain_core.messages.tool.default_tool_parser(raw_tool_calls:list[dict[str, Any]]) -> tuple[list[ToolCall], list[InvalidToolCall]]

Best-effort parsing of tools.

func

libs.core.langchain_core.messages.tool.invalid_tool_call(*name:str | None=None, *args:str | None=None, *id:str | None=None, *error:str | None=None) -> InvalidToolCall

Create an invalid tool call.

funclibs.core.langchain_core.messages.tool.tool_call(*name:str, *args:dict[str, Any], *id:str | None) -> ToolCall

Create a tool call.

func

libs.core.langchain_core.messages.tool.tool_call_chunk(*name:str | None=None, *args:str | None=None, *id:str | None=None, *index:int | None=None) -> ToolCallChunk

Create a tool call chunk.

funclibs.core.langchain_core.messages.utils.message_chunk_to_message(chunk:BaseMessage) -> BaseMessage

Convert a message chunk to a `Message`.

classlibs.core.langchain_core.output_parsers.base.BaseGenerationOutputParser

Base class to parse the output of an LLM call.

methodlibs.core.langchain_core.output_parsers.base.BaseGenerationOutputParser.InputType() -> Any

Return the input type for the parser.

methodlibs.core.langchain_core.output_parsers.base.BaseGenerationOutputParser.OutputType() -> type[T]

Return the output type for the parser.

classlibs.core.langchain_core.output_parsers.base.BaseOutputParser

Base class to parse the output of an LLM call.

methodlibs.core.langchain_core.output_parsers.base.BaseOutputParser.InputType() -> Any

Return the input type for the parser.

methodlibs.core.langchain_core.output_parsers.base.BaseOutputParser.OutputType() -> type[T]

Return the output type for the parser.

methodlibs.core.langchain_core.output_parsers.base.BaseOutputParser.asdict(**kwargs:Any) -> builtins.dict[str, Any]

Return a dictionary representation of the output parser.

methodlibs.core.langchain_core.output_parsers.base.BaseOutputParser.dict(**kwargs:Any) -> builtins.dict[str, Any]

DEPRECATED - use `asdict()` instead.

methodlibs.core.langchain_core.output_parsers.base.BaseOutputParser.parse(text:str) -> T

Parse a single string model output into some structure.

classlibs.core.langchain_core.output_parsers.json.JsonOutputParser

Parse the output of an LLM call to a JSON object.

methodlibs.core.langchain_core.output_parsers.json.JsonOutputParser.parse(text:str) -> Any

Parse the output of an LLM call to a JSON object.

classlibs.core.langchain_core.output_parsers.list.ListOutputParser

Parse the output of a model to a list.

methodlibs.core.langchain_core.output_parsers.list.ListOutputParser.parse(text:str) -> list[str]

Parse the output of an LLM call.

methodlibs.core.langchain_core.output_parsers.list.ListOutputParser.parse_iter(text:str) -> Iterator[re.Match[str]]

Parse the output of an LLM call.

classlibs.core.langchain_core.output_parsers.list.MarkdownListOutputParser

Parse a Markdown list.

methodlibs.core.langchain_core.output_parsers.list.MarkdownListOutputParser.parse(text:str) -> list[str]

Parse the output of an LLM call.

classlibs.core.langchain_core.output_parsers.list.NumberedListOutputParser

Parse a numbered list.

methodlibs.core.langchain_core.output_parsers.list.NumberedListOutputParser.parse(text:str) -> list[str]

Parse the output of an LLM call.

funclibs.core.langchain_core.output_parsers.list.droplastn(iter:Iterator[T], n:int) -> Iterator[T]

Drop the last `n` elements of an iterator.

classlibs.core.langchain_core.output_parsers.openai_functions.JsonOutputFunctionsParser

Parse an output as the JSON object.

methodlibs.core.langchain_core.output_parsers.openai_functions.JsonOutputFunctionsParser.parse(text:str) -> Any

Parse the output of an LLM call to a JSON object.

classlibs.core.langchain_core.output_parsers.openai_functions.OutputFunctionsParser

Parse an output that is one of sets of values.

classlibs.core.langchain_core.output_parsers.openai_functions.PydanticOutputFunctionsParser

Parse an output as a Pydantic object.

method

libs.core.langchain_core.output_parsers.openai_functions.PydanticOutputFunctionsParser.validate_schema(values:dict[str, Any]) -> Any

Validate the Pydantic schema.

classlibs.core.langchain_core.output_parsers.openai_tools.JsonOutputKeyToolsParser

Parse tools from OpenAI response.

classlibs.core.langchain_core.output_parsers.openai_tools.JsonOutputToolsParser

Parse tools from OpenAI response.

classlibs.core.langchain_core.output_parsers.openai_tools.PydanticToolsParser

Parse tools from OpenAI response.

func

libs.core.langchain_core.output_parsers.openai_tools.parse_tool_call(raw_tool_call:dict[str, Any], *partial:bool=False, *strict:bool=False, *return_id:bool=True) -> dict[str, Any] | None

Parse a single tool call.

func

libs.core.langchain_core.output_parsers.openai_tools.parse_tool_calls(raw_tool_calls:list[dict[str, Any]], *partial:bool=False, *strict:bool=False, *return_id:bool=True) -> list[dict[str, Any]]

Parse a list of tool calls.

classlibs.core.langchain_core.output_parsers.pydantic.PydanticOutputParser

Parse an output using a Pydantic model.

methodlibs.core.langchain_core.output_parsers.pydantic.PydanticOutputParser.OutputType() -> type[TBaseModel]

Return the Pydantic model.

methodlibs.core.langchain_core.output_parsers.pydantic.PydanticOutputParser.parse(text:str) -> TBaseModel

Parse the output of an LLM call to a Pydantic object.

classlibs.core.langchain_core.output_parsers.string.StrOutputParser

Extract text content from model outputs as a string.

methodlibs.core.langchain_core.output_parsers.string.StrOutputParser.is_lc_serializable() -> bool

`StrOutputParser` is serializable.

methodlibs.core.langchain_core.output_parsers.string.StrOutputParser.parse(text:str) -> str

Returns the input text with no changes.

classlibs.core.langchain_core.output_parsers.xml.XMLOutputParser

Parse an output using xml format.

methodlibs.core.langchain_core.output_parsers.xml.XMLOutputParser.parse(text:str) -> dict[str, str | list[Any]]

Parse the output of an LLM call.

funclibs.core.langchain_core.output_parsers.xml.nested_element(path:list[str], elem:ET.Element) -> Any

Get nested element from path.

classlibs.core.langchain_core.outputs.chat_generation.ChatGeneration

A single chat generation output.

classlibs.core.langchain_core.outputs.chat_generation.ChatGenerationChunk

`ChatGeneration` chunk.

classlibs.core.langchain_core.outputs.generation.Generation

A single text generation output.

methodlibs.core.langchain_core.outputs.generation.Generation.get_lc_namespace() -> list[str]

Get the namespace of the LangChain object.

methodlibs.core.langchain_core.outputs.generation.Generation.is_lc_serializable() -> bool

Return `True` as this class is serializable.

classlibs.core.langchain_core.outputs.llm_result.LLMResult

A container for results of an LLM call.

methodlibs.core.langchain_core.outputs.llm_result.LLMResult.flatten() -> list[LLMResult]

Flatten generations into a single list.

classlibs.core.langchain_core.prompt_values.ChatPromptValue

Chat prompt value.

methodlibs.core.langchain_core.prompt_values.ChatPromptValue.get_lc_namespace() -> list[str]

Get the namespace of the LangChain object.

methodlibs.core.langchain_core.prompt_values.ChatPromptValue.to_messages() -> list[BaseMessage]

Return prompt as a list of messages.

methodlibs.core.langchain_core.prompt_values.ChatPromptValue.to_string() -> str

Return prompt as string.

classlibs.core.langchain_core.prompt_values.ImagePromptValue

Image prompt value.

methodlibs.core.langchain_core.prompt_values.ImagePromptValue.to_messages() -> list[BaseMessage]

Return prompt (image URL) as messages.

methodlibs.core.langchain_core.prompt_values.ImagePromptValue.to_string() -> str

Return prompt (image URL) as string.

classlibs.core.langchain_core.prompt_values.ImageURL

Image URL for multimodal model inputs (OpenAI format).

classlibs.core.langchain_core.prompt_values.PromptValue

Base abstract class for inputs to any language model.

methodlibs.core.langchain_core.prompt_values.PromptValue.get_lc_namespace() -> list[str]

Get the namespace of the LangChain object.

methodlibs.core.langchain_core.prompt_values.PromptValue.is_lc_serializable() -> bool

Return `True` as this class is serializable.

methodlibs.core.langchain_core.prompt_values.PromptValue.to_messages() -> list[BaseMessage]

Return prompt as a list of messages.

methodlibs.core.langchain_core.prompt_values.PromptValue.to_string() -> str

Return prompt value as string.

classlibs.core.langchain_core.prompt_values.StringPromptValue

String prompt value.

methodlibs.core.langchain_core.prompt_values.StringPromptValue.get_lc_namespace() -> list[str]

Get the namespace of the LangChain object.

methodlibs.core.langchain_core.prompt_values.StringPromptValue.to_messages() -> list[BaseMessage]

Return prompt as messages.

methodlibs.core.langchain_core.prompt_values.StringPromptValue.to_string() -> str

Return prompt as string.

classlibs.core.langchain_core.prompts.chat.AIMessagePromptTemplate

AI message prompt template.

classlibs.core.langchain_core.prompts.chat.BaseChatPromptTemplate

Base class for chat prompt templates.

methodlibs.core.langchain_core.prompts.chat.BaseChatPromptTemplate.aformat(**kwargs:Any) -> str

Async format the chat template into a string.

methodlibs.core.langchain_core.prompts.chat.BaseChatPromptTemplate.aformat_messages(**kwargs:Any) -> list[BaseMessage]

Async format kwargs into a list of messages.

methodlibs.core.langchain_core.prompts.chat.BaseChatPromptTemplate.aformat_prompt(**kwargs:Any) -> ChatPromptValue

Async format prompt.

methodlibs.core.langchain_core.prompts.chat.BaseChatPromptTemplate.format(**kwargs:Any) -> str

Format the chat template into a string.

methodlibs.core.langchain_core.prompts.chat.BaseChatPromptTemplate.format_messages(**kwargs:Any) -> list[BaseMessage]

Format kwargs into a list of messages.

methodlibs.core.langchain_core.prompts.chat.BaseChatPromptTemplate.format_prompt(**kwargs:Any) -> ChatPromptValue

Format prompt.

methodlibs.core.langchain_core.prompts.chat.BaseChatPromptTemplate.pretty_print() -> None

Print a human-readable representation.

methodlibs.core.langchain_core.prompts.chat.BaseChatPromptTemplate.pretty_repr(html:bool=False) -> str

Human-readable representation.

classlibs.core.langchain_core.prompts.chat.ChatMessagePromptTemplate

Chat message prompt template.

methodlibs.core.langchain_core.prompts.chat.ChatMessagePromptTemplate.aformat(**kwargs:Any) -> BaseMessage

Async format the prompt template.

methodlibs.core.langchain_core.prompts.chat.ChatMessagePromptTemplate.format(**kwargs:Any) -> BaseMessage

Format the prompt template.

この情報について

掲載しているシグネチャは langchain-ai/langchain の公開ソースコードを Python の ast モジュールで静的解析し、引数名・デフォルト値・型注釈・戻り値型をそのまま抽出したものです。実装コードは保存していません。詳しくは仕組みの解説をご覧ください。

収録ライブラリ一覧（全 805 件）へ戻る