langchain-core: 0.2.30

langchain-core defines the base abstractions for the LangChain ecosystem.

The interfaces for core components like chat models, LLMs, vector stores, retrievers, and more are defined here. The universal invocation protocol (Runnables) along with a syntax for combining components (LangChain Expression Language) are also defined here.

No third-party integrations are defined here. The dependencies are kept purposefully very lightweight.

agents

agents.AgentAction	Represents a request to execute an action by an agent.
agents.AgentActionMessageLog	Representation of an action to be executed by an agent.
agents.AgentFinish	Final return value of an ActionAgent.
agents.AgentStep	Result of running an AgentAction.

beta

beta.runnables.context.Context()	Context for a runnable.
beta.runnables.context.ContextGet
beta.runnables.context.ContextSet
beta.runnables.context.PrefixContext([prefix])	Context for a runnable with a prefix.

caches

caches.BaseCache()	Interface for a caching layer for LLMs and Chat models.
caches.InMemoryCache(*[, maxsize])	Cache that stores things in memory.

callbacks

callbacks.base.AsyncCallbackHandler()	Async callback handler for LangChain.
callbacks.base.BaseCallbackHandler()	Base callback handler for LangChain.
callbacks.base.BaseCallbackManager(handlers)	Base callback manager for LangChain.
callbacks.base.CallbackManagerMixin()	Mixin for callback manager.
callbacks.base.ChainManagerMixin()	Mixin for chain callbacks.
callbacks.base.LLMManagerMixin()	Mixin for LLM callbacks.
callbacks.base.RetrieverManagerMixin()	Mixin for Retriever callbacks.
callbacks.base.RunManagerMixin()	Mixin for run manager.
callbacks.base.ToolManagerMixin()	Mixin for tool callbacks.
callbacks.file.FileCallbackHandler(filename)	Callback Handler that writes to a file.
callbacks.manager.AsyncCallbackManager(handlers)	Async callback manager that handles callbacks from LangChain.
callbacks.manager.AsyncCallbackManagerForChainGroup(...)	Async callback manager for the chain group.
callbacks.manager.AsyncCallbackManagerForChainRun(*, ...)	Async callback manager for chain run.
callbacks.manager.AsyncCallbackManagerForLLMRun(*, ...)	Async callback manager for LLM run.
callbacks.manager.AsyncCallbackManagerForRetrieverRun(*, ...)	Async callback manager for retriever run.
callbacks.manager.AsyncCallbackManagerForToolRun(*, ...)	Async callback manager for tool run.
callbacks.manager.AsyncParentRunManager(*, ...)	Async Parent Run Manager.
callbacks.manager.AsyncRunManager(*, run_id, ...)	Async Run Manager.
callbacks.manager.BaseRunManager(*, run_id, ...)	Base class for run manager (a bound callback manager).
callbacks.manager.CallbackManager(handlers)	Callback manager for LangChain.
callbacks.manager.CallbackManagerForChainGroup(...)	Callback manager for the chain group.
callbacks.manager.CallbackManagerForChainRun(*, ...)	Callback manager for chain run.
callbacks.manager.CallbackManagerForLLMRun(*, ...)	Callback manager for LLM run.
callbacks.manager.CallbackManagerForRetrieverRun(*, ...)	Callback manager for retriever run.
callbacks.manager.CallbackManagerForToolRun(*, ...)	Callback manager for tool run.
callbacks.manager.ParentRunManager(*, ...[, ...])	Sync Parent Run Manager.
callbacks.manager.RunManager(*, run_id, ...)	Sync Run Manager.
callbacks.stdout.StdOutCallbackHandler([color])	Callback Handler that prints to std out.
callbacks.streaming_stdout.StreamingStdOutCallbackHandler()	Callback handler for streaming.

chat_history

chat_history.BaseChatMessageHistory()	Abstract base class for storing chat message history.
chat_history.InMemoryChatMessageHistory	In memory implementation of chat message history.

chat_loaders

chat_loaders.BaseChatLoader()

Base class for chat loaders.

chat_sessions

chat_sessions.ChatSession

Chat Session represents a single conversation, channel, or other group of messages.

document_loaders

document_loaders.base.BaseBlobParser()	Abstract interface for blob parsers.
document_loaders.base.BaseLoader()	Interface for Document Loader.
document_loaders.blob_loaders.BlobLoader()	Abstract interface for blob loaders implementation.

documents

documents.base.BaseMedia	Use to represent media content.
documents.base.Blob	Blob represents raw data by either reference or value.
documents.base.Document	Class for storing a piece of text and associated metadata.
documents.compressor.BaseDocumentCompressor	Base class for document compressors.
documents.transformers.BaseDocumentTransformer()	Abstract base class for document transformation.

embeddings

embeddings.embeddings.Embeddings()	Interface for embedding models.
embeddings.fake.DeterministicFakeEmbedding	Deterministic fake embedding model for unit testing purposes.
embeddings.fake.FakeEmbeddings	Fake embedding model for unit testing purposes.

example_selectors

example_selectors.base.BaseExampleSelector()	Interface for selecting examples to include in prompts.
example_selectors.length_based.LengthBasedExampleSelector	Select examples based on length.
example_selectors.semantic_similarity.MaxMarginalRelevanceExampleSelector	Select examples based on Max Marginal Relevance.
example_selectors.semantic_similarity.SemanticSimilarityExampleSelector	Select examples based on semantic similarity.

exceptions

exceptions.LangChainException	General LangChain exception.
exceptions.OutputParserException(error[, ...])	Exception that output parsers should raise to signify a parsing error.
exceptions.TracerException	Base class for exceptions in tracers module.

globals

graph_vectorstores

graph_vectorstores.base.GraphVectorStore(...)
graph_vectorstores.base.GraphVectorStoreRetriever	Retriever class for GraphVectorStore.
graph_vectorstores.base.Node	Node in the GraphVectorStore.
graph_vectorstores.links.Link(kind, ...)	A link to/from a tag of a given tag.

indexing

indexing.api.IndexingResult	Return a detailed a breakdown of the result of the indexing operation.
indexing.base.DeleteResponse	A generic response for delete operation.
indexing.base.DocumentIndex
indexing.base.InMemoryRecordManager(namespace)	An in-memory record manager for testing purposes.
indexing.base.RecordManager(namespace)	Abstract base class representing the interface for a record manager.
indexing.base.UpsertResponse	A generic response for upsert operations.
indexing.in_memory.InMemoryDocumentIndex

language_models

language_models.base.BaseLanguageModel	Abstract base class for interfacing with language models.
language_models.chat_models.BaseChatModel	Base class for chat models.
language_models.chat_models.LangSmithParams	LangSmith parameters for tracing.
language_models.chat_models.SimpleChatModel	Simplified implementation for a chat model to inherit from.
language_models.fake.FakeListLLM	Fake LLM for testing purposes.
language_models.fake.FakeStreamingListLLM	Fake streaming list LLM for testing purposes.
language_models.fake_chat_models.FakeChatModel	Fake Chat Model wrapper for testing purposes.
language_models.fake_chat_models.FakeListChatModel	Fake ChatModel for testing purposes.
language_models.fake_chat_models.FakeMessagesListChatModel	Fake ChatModel for testing purposes.
language_models.fake_chat_models.GenericFakeChatModel	Generic fake chat model that can be used to test the chat model interface.
language_models.fake_chat_models.ParrotFakeChatModel	Generic fake chat model that can be used to test the chat model interface.
language_models.llms.BaseLLM	Base LLM abstract interface.
language_models.llms.LLM	Simple interface for implementing a custom LLM.

load

load.load.Reviver([secrets_map, ...])	Reviver for JSON objects.
load.serializable.BaseSerialized	Base class for serialized objects.
load.serializable.Serializable	Serializable base class.
load.serializable.SerializedConstructor	Serialized constructor.
load.serializable.SerializedNotImplemented	Serialized not implemented.
load.serializable.SerializedSecret	Serialized secret.

memory

memory.BaseMemory

Abstract base class for memory in Chains.

messages

messages.ai.AIMessage	Message from an AI.
messages.ai.AIMessageChunk	Message chunk from an AI.
messages.ai.UsageMetadata	Usage metadata for a message, such as token counts.
messages.base.BaseMessage	Base abstract message class.
messages.base.BaseMessageChunk	Message chunk, which can be concatenated with other Message chunks.
messages.chat.ChatMessage	Message that can be assigned an arbitrary speaker (i.e.
messages.chat.ChatMessageChunk	Chat Message chunk.
messages.function.FunctionMessage	Message for passing the result of executing a tool back to a model.
messages.function.FunctionMessageChunk	Function Message chunk.
messages.human.HumanMessage	Message from a human.
messages.human.HumanMessageChunk	Human Message chunk.
messages.modifier.RemoveMessage
messages.system.SystemMessage	Message for priming AI behavior.
messages.system.SystemMessageChunk	System Message chunk.
messages.tool.InvalidToolCall	Allowance for errors made by LLM.
messages.tool.ToolCall	Represents a request to call a tool.
messages.tool.ToolCallChunk	A chunk of a tool call (e.g., as part of a stream).
messages.tool.ToolMessage	Message for passing the result of executing a tool back to a model.
messages.tool.ToolMessageChunk	Tool Message chunk.

output_parsers

output_parsers.base.BaseGenerationOutputParser	Base class to parse the output of an LLM call.
output_parsers.base.BaseLLMOutputParser()	Abstract base class for parsing the outputs of a model.
output_parsers.base.BaseOutputParser	Base class to parse the output of an LLM call.
output_parsers.json.JsonOutputParser	Parse the output of an LLM call to a JSON object.
output_parsers.json.SimpleJsonOutputParser	alias of JsonOutputParser
output_parsers.list.CommaSeparatedListOutputParser	Parse the output of an LLM call to a comma-separated list.
output_parsers.list.ListOutputParser	Parse the output of an LLM call to a list.
output_parsers.list.MarkdownListOutputParser	Parse a Markdown list.
output_parsers.list.NumberedListOutputParser	Parse a numbered list.
output_parsers.openai_functions.JsonKeyOutputFunctionsParser	Parse an output as the element of the Json object.
output_parsers.openai_functions.JsonOutputFunctionsParser	Parse an output as the Json object.
output_parsers.openai_functions.OutputFunctionsParser	Parse an output that is one of sets of values.
output_parsers.openai_functions.PydanticAttrOutputFunctionsParser	Parse an output as an attribute of a pydantic object.
output_parsers.openai_functions.PydanticOutputFunctionsParser	Parse an output as a pydantic object.
output_parsers.openai_tools.JsonOutputKeyToolsParser	Parse tools from OpenAI response.
output_parsers.openai_tools.JsonOutputToolsParser	Parse tools from OpenAI response.
output_parsers.openai_tools.PydanticToolsParser	Parse tools from OpenAI response.
output_parsers.pydantic.PydanticOutputParser	Parse an output using a pydantic model.
output_parsers.string.StrOutputParser	OutputParser that parses LLMResult into the top likely string.
output_parsers.transform.BaseCumulativeTransformOutputParser	Base class for an output parser that can handle streaming input.
output_parsers.transform.BaseTransformOutputParser	Base class for an output parser that can handle streaming input.
output_parsers.xml.XMLOutputParser	Parse an output using xml format.

outputs

outputs.chat_generation.ChatGeneration	A single chat generation output.
outputs.chat_generation.ChatGenerationChunk	ChatGeneration chunk, which can be concatenated with other ChatGeneration chunks.
outputs.chat_result.ChatResult	Use to represent the result of a chat model call with a single prompt.
outputs.generation.Generation	A single text generation output.
outputs.generation.GenerationChunk	Generation chunk, which can be concatenated with other Generation chunks.
outputs.llm_result.LLMResult	A container for results of an LLM call.
outputs.run_info.RunInfo	Class that contains metadata for a single execution of a Chain or model.

prompt_values

prompt_values.ChatPromptValue	Chat prompt value.
prompt_values.ChatPromptValueConcrete	Chat prompt value which explicitly lists out the message types it accepts.
prompt_values.ImagePromptValue	Image prompt value.
prompt_values.ImageURL	Image URL.
prompt_values.PromptValue	Base abstract class for inputs to any language model.
prompt_values.StringPromptValue	String prompt value.

prompts

prompts.base.BasePromptTemplate	Base class for all prompt templates, returning a prompt.
prompts.chat.AIMessagePromptTemplate	AI message prompt template.
prompts.chat.BaseChatPromptTemplate	Base class for chat prompt templates.
prompts.chat.BaseMessagePromptTemplate	Base class for message prompt templates.
prompts.chat.BaseStringMessagePromptTemplate	Base class for message prompt templates that use a string prompt template.
prompts.chat.ChatMessagePromptTemplate	Chat message prompt template.
prompts.chat.ChatPromptTemplate	Prompt template for chat models.
prompts.chat.HumanMessagePromptTemplate	Human message prompt template.
prompts.chat.MessagesPlaceholder	Prompt template that assumes variable is already list of messages.
prompts.chat.SystemMessagePromptTemplate	System message prompt template.
prompts.few_shot.FewShotChatMessagePromptTemplate	Chat prompt template that supports few-shot examples.
prompts.few_shot.FewShotPromptTemplate	Prompt template that contains few shot examples.
prompts.few_shot_with_templates.FewShotPromptWithTemplates	Prompt template that contains few shot examples.
prompts.image.ImagePromptTemplate	Image prompt template for a multimodal model.
prompts.pipeline.PipelinePromptTemplate	Prompt template for composing multiple prompt templates together.
prompts.prompt.PromptTemplate	Prompt template for a language model.
prompts.string.StringPromptTemplate	String prompt that exposes the format method, returning a prompt.
prompts.structured.StructuredPrompt

rate_limiters

rate_limiters.BaseRateLimiter(*args, **kwargs)
rate_limiters.InMemoryRateLimiter(*[, ...])

retrievers

retrievers.BaseRetriever	Abstract base class for a Document retrieval system.
retrievers.LangSmithRetrieverParams	LangSmith parameters for tracing.

runnables

runnables.base.Runnable()	A unit of work that can be invoked, batched, streamed, transformed and composed.
runnables.base.RunnableBinding	Wrap a Runnable with additional functionality.
runnables.base.RunnableBindingBase	Runnable that delegates calls to another Runnable with a set of kwargs.
runnables.base.RunnableEach	Runnable that delegates calls to another Runnable with each element of the input sequence.
runnables.base.RunnableEachBase	Runnable that delegates calls to another Runnable with each element of the input sequence.
runnables.base.RunnableGenerator(transform)	Runnable that runs a generator function.
runnables.base.RunnableLambda(func[, afunc, ...])	RunnableLambda converts a python callable into a Runnable.
runnables.base.RunnableMap	alias of RunnableParallel
runnables.base.RunnableParallel	Runnable that runs a mapping of Runnables in parallel, and returns a mapping of their outputs.
runnables.base.RunnableSequence	Sequence of Runnables, where the output of each is the input of the next.
runnables.base.RunnableSerializable	Runnable that can be serialized to JSON.
runnables.branch.RunnableBranch	Runnable that selects which branch to run based on a condition.
runnables.config.ContextThreadPoolExecutor([...])	ThreadPoolExecutor that copies the context to the child thread.
runnables.config.EmptyDict	Empty dict type.
runnables.config.RunnableConfig	Configuration for a Runnable.
runnables.configurable.DynamicRunnable	Serializable Runnable that can be dynamically configured.
runnables.configurable.RunnableConfigurableAlternatives	Runnable that can be dynamically configured.
runnables.configurable.RunnableConfigurableFields	Runnable that can be dynamically configured.
runnables.configurable.StrEnum(value[, ...])	String enum.
runnables.fallbacks.RunnableWithFallbacks	Runnable that can fallback to other Runnables if it fails.
runnables.graph.Branch(condition, ends)	Branch in a graph.
runnables.graph.CurveStyle(value[, names, ...])	Enum for different curve styles supported by Mermaid
runnables.graph.Edge(source, target[, data, ...])	Edge in a graph.
runnables.graph.Graph(nodes, ...)	Graph of nodes and edges.
runnables.graph.LabelsDict	Dictionary of labels for nodes and edges in a graph.
runnables.graph.MermaidDrawMethod(value[, ...])	Enum for different draw methods supported by Mermaid
runnables.graph.Node(id, name, data, metadata)	Node in a graph.
runnables.graph.NodeStyles([default, first, ...])	Schema for Hexadecimal color codes for different node types.
runnables.graph.Stringifiable(*args, **kwargs)
runnables.graph_ascii.AsciiCanvas(cols, lines)	Class for drawing in ASCII.
runnables.graph_ascii.VertexViewer(name)	Class to define vertex box boundaries that will be accounted for during graph building by grandalf.
runnables.graph_png.PngDrawer([fontname, labels])	Helper class to draw a state graph into a PNG file.
runnables.history.RunnableWithMessageHistory	Runnable that manages chat message history for another Runnable.
runnables.passthrough.RunnableAssign	Runnable that assigns key-value pairs to Dict[str, Any] inputs.
runnables.passthrough.RunnablePassthrough	Runnable to passthrough inputs unchanged or with additional keys.
runnables.passthrough.RunnablePick	Runnable that picks keys from Dict[str, Any] inputs.
runnables.retry.RunnableRetry	Retry a Runnable if it fails.
runnables.router.RouterInput	Router input.
runnables.router.RouterRunnable	Runnable that routes to a set of Runnables based on Input['key'].
runnables.schema.BaseStreamEvent	Streaming event.
runnables.schema.CustomStreamEvent	Custom stream event created by the user.
runnables.schema.EventData	Data associated with a streaming event.
runnables.schema.StandardStreamEvent	A standard stream event that follows LangChain convention for event data.
runnables.utils.AddableDict	Dictionary that can be added to another dictionary.
runnables.utils.ConfigurableField(id[, ...])	Field that can be configured by the user.
runnables.utils.ConfigurableFieldMultiOption(id, ...)	Field that can be configured by the user with multiple default values.
runnables.utils.ConfigurableFieldSingleOption(id, ...)	Field that can be configured by the user with a default value.
runnables.utils.ConfigurableFieldSpec(id, ...)	Field that can be configured by the user.
runnables.utils.FunctionNonLocals()	Get the nonlocal variables accessed of a function.
runnables.utils.GetLambdaSource()	Get the source code of a lambda function.
runnables.utils.IsFunctionArgDict()	Check if the first argument of a function is a dict.
runnables.utils.IsLocalDict(name, keys)	Check if a name is a local dict.
runnables.utils.NonLocals()	Get nonlocal variables accessed.
runnables.utils.SupportsAdd(*args, **kwargs)	Protocol for objects that support addition.

stores

stores.BaseStore()	Abstract interface for a key-value store.
stores.InMemoryBaseStore()	In-memory implementation of the BaseStore using a dictionary.
stores.InMemoryByteStore()	In-memory store for bytes.
stores.InMemoryStore()	In-memory store for any type of data.
stores.InvalidKeyException	Raised when a key is invalid; e.g., uses incorrect characters.

structured_query

structured_query.Comparator(value[, names, ...])	Enumerator of the comparison operators.
structured_query.Comparison	Comparison to a value.
structured_query.Expr	Base class for all expressions.
structured_query.FilterDirective	Filtering expression.
structured_query.Operation	Logical operation over other directives.
structured_query.Operator(value[, names, ...])	Enumerator of the operations.
structured_query.StructuredQuery	Structured query.
structured_query.Visitor()	Defines interface for IR translation using a visitor pattern.

sys_info

tools

tools.base.BaseTool	Interface LangChain tools must implement.
tools.base.BaseToolkit	Base Toolkit representing a collection of related tools.
tools.base.InjectedToolArg()	Annotation for a Tool arg that is not meant to be generated by a model.
tools.base.SchemaAnnotationError	Raised when 'args_schema' is missing or has an incorrect type annotation.
tools.base.ToolException	Optional exception that tool throws when execution error occurs.
tools.retriever.RetrieverInput	Input to the retriever.
tools.simple.Tool	Tool that takes in function or coroutine directly.
tools.structured.StructuredTool	Tool that can operate on any number of inputs.

tracers

tracers.base.AsyncBaseTracer(*[, _schema_format])	Async Base interface for tracers.
tracers.base.BaseTracer(*[, _schema_format])	Base interface for tracers.
tracers.evaluation.EvaluatorCallbackHandler(...)	Tracer that runs a run evaluator whenever a run is persisted.
tracers.event_stream.RunInfo	Information about a run.
tracers.langchain.LangChainTracer([...])	Implementation of the SharedTracer that POSTS to the LangChain endpoint.
tracers.log_stream.LogEntry	A single entry in the run log.
tracers.log_stream.LogStreamCallbackHandler(*)	Tracer that streams run logs to a stream.
tracers.log_stream.RunLog(*ops, state)	Run log.
tracers.log_stream.RunLogPatch(*ops)	Patch to the run log.
tracers.log_stream.RunState	State of the run.
tracers.root_listeners.AsyncRootListenersTracer(*, ...)	Async Tracer that calls listeners on run start, end, and error.
tracers.root_listeners.RootListenersTracer(*, ...)	Tracer that calls listeners on run start, end, and error.
tracers.run_collector.RunCollectorCallbackHandler([...])	Tracer that collects all nested runs in a list.
tracers.schemas.Run	Run schema for the V2 API in the Tracer.
tracers.stdout.ConsoleCallbackHandler(**kwargs)	Tracer that prints to the console.
tracers.stdout.FunctionCallbackHandler(...)	Tracer that calls a function with a single str parameter.

utils

utils.aiter.NoLock()	Dummy lock that provides the proper interface but no protection.
utils.aiter.Tee(iterable[, n, lock])	Create n separate asynchronous iterators over iterable.
utils.aiter.aclosing(thing)	Async context manager for safely finalizing an asynchronously cleaned-up resource such as an async generator, calling its aclose() method.
utils.aiter.atee	alias of Tee
utils.formatting.StrictFormatter()	Formatter that checks for extra keys.
utils.function_calling.FunctionDescription	Representation of a callable function to send to an LLM.
utils.function_calling.ToolDescription	Representation of a callable function to the OpenAI API.
utils.iter.NoLock()	Dummy lock that provides the proper interface but no protection.
utils.iter.Tee(iterable[, n, lock])	Create n separate asynchronous iterators over iterable
utils.iter.safetee	alias of Tee
utils.mustache.ChevronError	Custom exception for Chevron errors.

vectorstores

vectorstores.base.VectorStore()	Interface for vector store.
vectorstores.base.VectorStoreRetriever	Base Retriever class for VectorStore.
vectorstores.in_memory.InMemoryVectorStore(...)	In-memory implementation of VectorStore using a dictionary.