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dba2dae987f7-0 | langchain API Reference¶
langchain.adapters¶
Classes¶
adapters.openai.ChatCompletion()
Functions¶
adapters.openai.aenumerate(iterable[, start])
Async version of enumerate.
adapters.openai.convert_dict_to_message(_dict)
adapters.openai.convert_message_to_dict(message)
adapters.openai.convert_messages_for_finetuning(...)
Convert messages to a list of lists of dictionaries for fine-tuning.
adapters.openai.convert_openai_messages(messages)
Convert dictionaries representing OpenAI messages to LangChain format.
langchain.agents¶
Agent is a class that uses an LLM to choose a sequence of actions to take.
In Chains, a sequence of actions is hardcoded. In Agents,
a language model is used as a reasoning engine to determine which actions
to take and in which order.
Agents select and use Tools and Toolkits for actions.
Class hierarchy:
BaseSingleActionAgent --> LLMSingleActionAgent
OpenAIFunctionsAgent
XMLAgent
Agent --> <name>Agent # Examples: ZeroShotAgent, ChatAgent
BaseMultiActionAgent --> OpenAIMultiFunctionsAgent
Main helpers:
AgentType, AgentExecutor, AgentOutputParser, AgentExecutorIterator,
AgentAction, AgentFinish
Classes¶
agents.agent.Agent
Agent that calls the language model and deciding the action.
agents.agent.AgentExecutor
Agent that is using tools.
agents.agent.AgentOutputParser
Base class for parsing agent output into agent action/finish.
agents.agent.BaseMultiActionAgent
Base Multi Action Agent class.
agents.agent.BaseSingleActionAgent
Base Single Action Agent class.
agents.agent.ExceptionTool
Tool that just returns the query.
agents.agent.LLMSingleActionAgent
Base class for single action agents.
agents.agent.RunnableAgent
Agent powered by runnables. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-1 | agents.agent.RunnableAgent
Agent powered by runnables.
agents.agent_iterator.AgentExecutorIterator(...)
Iterator for AgentExecutor.
agents.agent_iterator.BaseAgentExecutorIterator()
Base class for AgentExecutorIterator.
agents.agent_toolkits.ainetwork.toolkit.AINetworkToolkit
Toolkit for interacting with AINetwork Blockchain.
agents.agent_toolkits.amadeus.toolkit.AmadeusToolkit
Toolkit for interacting with Office365.
agents.agent_toolkits.azure_cognitive_services.AzureCognitiveServicesToolkit
Toolkit for Azure Cognitive Services.
agents.agent_toolkits.base.BaseToolkit
Base Toolkit representing a collection of related tools.
agents.agent_toolkits.file_management.toolkit.FileManagementToolkit
Toolkit for interacting with a Local Files.
agents.agent_toolkits.github.toolkit.GitHubToolkit
GitHub Toolkit.
agents.agent_toolkits.gitlab.toolkit.GitLabToolkit
GitLab Toolkit.
agents.agent_toolkits.gmail.toolkit.GmailToolkit
Toolkit for interacting with Gmail.
agents.agent_toolkits.jira.toolkit.JiraToolkit
Jira Toolkit.
agents.agent_toolkits.json.toolkit.JsonToolkit
Toolkit for interacting with a JSON spec.
agents.agent_toolkits.multion.toolkit.MultionToolkit
Toolkit for interacting with the Browser Agent
agents.agent_toolkits.nla.tool.NLATool
Natural Language API Tool.
agents.agent_toolkits.nla.toolkit.NLAToolkit
Natural Language API Toolkit.
agents.agent_toolkits.office365.toolkit.O365Toolkit
Toolkit for interacting with Office 365.
agents.agent_toolkits.openapi.planner.RequestsDeleteToolWithParsing
A tool that sends a DELETE request and parses the response.
agents.agent_toolkits.openapi.planner.RequestsGetToolWithParsing
Requests GET tool with LLM-instructed extraction of truncated responses.
agents.agent_toolkits.openapi.planner.RequestsPatchToolWithParsing | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-2 | agents.agent_toolkits.openapi.planner.RequestsPatchToolWithParsing
Requests PATCH tool with LLM-instructed extraction of truncated responses.
agents.agent_toolkits.openapi.planner.RequestsPostToolWithParsing
Requests POST tool with LLM-instructed extraction of truncated responses.
agents.agent_toolkits.openapi.planner.RequestsPutToolWithParsing
Requests PUT tool with LLM-instructed extraction of truncated responses.
agents.agent_toolkits.openapi.spec.ReducedOpenAPISpec(...)
A reduced OpenAPI spec.
agents.agent_toolkits.openapi.toolkit.OpenAPIToolkit
Toolkit for interacting with an OpenAPI API.
agents.agent_toolkits.openapi.toolkit.RequestsToolkit
Toolkit for making REST requests.
agents.agent_toolkits.playwright.toolkit.PlayWrightBrowserToolkit
Toolkit for PlayWright browser tools.
agents.agent_toolkits.powerbi.toolkit.PowerBIToolkit
Toolkit for interacting with Power BI dataset.
agents.agent_toolkits.spark_sql.toolkit.SparkSQLToolkit
Toolkit for interacting with Spark SQL.
agents.agent_toolkits.sql.toolkit.SQLDatabaseToolkit
Toolkit for interacting with SQL databases.
agents.agent_toolkits.vectorstore.toolkit.VectorStoreInfo
Information about a VectorStore.
agents.agent_toolkits.vectorstore.toolkit.VectorStoreRouterToolkit
Toolkit for routing between Vector Stores.
agents.agent_toolkits.vectorstore.toolkit.VectorStoreToolkit
Toolkit for interacting with a Vector Store.
agents.agent_toolkits.zapier.toolkit.ZapierToolkit
Zapier Toolkit.
agents.agent_types.AgentType(value[, names, ...])
Enumerator with the Agent types.
agents.chat.base.ChatAgent
Chat Agent.
agents.chat.output_parser.ChatOutputParser
Output parser for the chat agent.
agents.conversational.base.ConversationalAgent
An agent that holds a conversation in addition to using tools.
agents.conversational.output_parser.ConvoOutputParser | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-3 | agents.conversational.output_parser.ConvoOutputParser
Output parser for the conversational agent.
agents.conversational_chat.base.ConversationalChatAgent
An agent designed to hold a conversation in addition to using tools.
agents.conversational_chat.output_parser.ConvoOutputParser
Output parser for the conversational agent.
agents.mrkl.base.ChainConfig(action_name, ...)
Configuration for chain to use in MRKL system.
agents.mrkl.base.MRKLChain
[Deprecated] Chain that implements the MRKL system.
agents.mrkl.base.ZeroShotAgent
Agent for the MRKL chain.
agents.mrkl.output_parser.MRKLOutputParser
MRKL Output parser for the chat agent.
agents.openai_functions_agent.agent_token_buffer_memory.AgentTokenBufferMemory
Memory used to save agent output AND intermediate steps.
agents.openai_functions_agent.base.OpenAIFunctionsAgent
An Agent driven by OpenAIs function powered API.
agents.openai_functions_multi_agent.base.OpenAIMultiFunctionsAgent
An Agent driven by OpenAIs function powered API.
agents.output_parsers.json.JSONAgentOutputParser
Parses tool invocations and final answers in XML format.
agents.output_parsers.openai_functions.OpenAIFunctionsAgentOutputParser
Parses a message into agent action/finish.
agents.output_parsers.react_json_single_input.ReActJsonSingleInputOutputParser
Parses ReAct-style LLM calls that have a single tool input in json format.
agents.output_parsers.react_single_input.ReActSingleInputOutputParser
Parses ReAct-style LLM calls that have a single tool input.
agents.output_parsers.self_ask.SelfAskOutputParser
Parses self-ask style LLM calls.
agents.output_parsers.xml.XMLAgentOutputParser
Parses tool invocations and final answers in XML format. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-4 | Parses tool invocations and final answers in XML format.
agents.react.base.DocstoreExplorer(docstore)
Class to assist with exploration of a document store.
agents.react.base.ReActChain
[Deprecated] Chain that implements the ReAct paper.
agents.react.base.ReActDocstoreAgent
Agent for the ReAct chain.
agents.react.base.ReActTextWorldAgent
Agent for the ReAct TextWorld chain.
agents.react.output_parser.ReActOutputParser
Output parser for the ReAct agent.
agents.schema.AgentScratchPadChatPromptTemplate
Chat prompt template for the agent scratchpad.
agents.self_ask_with_search.base.SelfAskWithSearchAgent
Agent for the self-ask-with-search paper.
agents.self_ask_with_search.base.SelfAskWithSearchChain
[Deprecated] Chain that does self-ask with search.
agents.structured_chat.base.StructuredChatAgent
Structured Chat Agent.
agents.structured_chat.output_parser.StructuredChatOutputParser
Output parser for the structured chat agent.
agents.structured_chat.output_parser.StructuredChatOutputParserWithRetries
Output parser with retries for the structured chat agent.
agents.tools.InvalidTool
Tool that is run when invalid tool name is encountered by agent.
agents.xml.base.XMLAgent
Agent that uses XML tags.
Functions¶
agents.agent_iterator.rebuild_callback_manager_on_set(...)
Decorator to force setters to rebuild callback mgr
agents.agent_toolkits.conversational_retrieval.openai_functions.create_conversational_retrieval_agent(...)
A convenience method for creating a conversational retrieval agent.
agents.agent_toolkits.conversational_retrieval.tool.create_retriever_tool(...)
Create a tool to do retrieval of documents.
agents.agent_toolkits.csv.base.create_csv_agent(...)
Create csv agent by loading to a dataframe and using pandas agent.
agents.agent_toolkits.json.base.create_json_agent(...) | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-5 | agents.agent_toolkits.json.base.create_json_agent(...)
Construct a json agent from an LLM and tools.
agents.agent_toolkits.openapi.base.create_openapi_agent(...)
Construct an OpenAPI agent from an LLM and tools.
agents.agent_toolkits.openapi.planner.create_openapi_agent(...)
Instantiate OpenAI API planner and controller for a given spec.
agents.agent_toolkits.openapi.spec.reduce_openapi_spec(spec)
Simplify/distill/minify a spec somehow.
agents.agent_toolkits.pandas.base.create_pandas_dataframe_agent(llm, df)
Construct a pandas agent from an LLM and dataframe.
agents.agent_toolkits.powerbi.base.create_pbi_agent(llm)
Construct a Power BI agent from an LLM and tools.
agents.agent_toolkits.powerbi.chat_base.create_pbi_chat_agent(llm)
Construct a Power BI agent from a Chat LLM and tools.
agents.agent_toolkits.python.base.create_python_agent(...)
Construct a python agent from an LLM and tool.
agents.agent_toolkits.spark.base.create_spark_dataframe_agent(llm, df)
Construct a Spark agent from an LLM and dataframe.
agents.agent_toolkits.spark_sql.base.create_spark_sql_agent(...)
Construct a Spark SQL agent from an LLM and tools.
agents.agent_toolkits.sql.base.create_sql_agent(...)
Construct an SQL agent from an LLM and tools.
agents.agent_toolkits.vectorstore.base.create_vectorstore_agent(...)
Construct a VectorStore agent from an LLM and tools.
agents.agent_toolkits.vectorstore.base.create_vectorstore_router_agent(...)
Construct a VectorStore router agent from an LLM and tools.
agents.agent_toolkits.xorbits.base.create_xorbits_agent(...)
Construct a xorbits agent from an LLM and dataframe.
agents.format_scratchpad.log.format_log_to_str(...)
Construct the scratchpad that lets the agent continue its thought process. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-6 | Construct the scratchpad that lets the agent continue its thought process.
agents.format_scratchpad.log_to_messages.format_log_to_messages(...)
Construct the scratchpad that lets the agent continue its thought process.
agents.format_scratchpad.openai_functions.format_to_openai_functions(...)
Format intermediate steps.
agents.format_scratchpad.xml.format_xml(...)
agents.initialize.initialize_agent(tools, llm)
Load an agent executor given tools and LLM.
agents.load_tools.get_all_tool_names()
Get a list of all possible tool names.
agents.load_tools.load_huggingface_tool(...)
Loads a tool from the HuggingFace Hub.
agents.load_tools.load_tools(tool_names[, ...])
Load tools based on their name.
agents.loading.load_agent(path, **kwargs)
Unified method for loading an agent from LangChainHub or local fs.
agents.loading.load_agent_from_config(config)
Load agent from Config Dict.
agents.utils.validate_tools_single_input(...)
Validate tools for single input.
langchain.agents.format_scratchpad¶
Logic for formatting intermediate steps into an agent scratchpad.
Intermediate steps refers to the list of (AgentAction, observation) tuples
that result from previous iterations of the agent.
Depending on the prompting strategy you are using, you may want to format these
differently before passing them into the LLM.
Functions¶
agents.format_scratchpad.log.format_log_to_str(...)
Construct the scratchpad that lets the agent continue its thought process.
agents.format_scratchpad.log_to_messages.format_log_to_messages(...)
Construct the scratchpad that lets the agent continue its thought process.
agents.format_scratchpad.openai_functions.format_to_openai_functions(...)
Format intermediate steps.
agents.format_scratchpad.xml.format_xml(...)
langchain.agents.output_parsers¶
Parsing utils to go from string to AgentAction or Agent Finish. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-7 | Parsing utils to go from string to AgentAction or Agent Finish.
AgentAction means that an action should be taken.
This contains the name of the tool to use, the input to pass to that tool,
and a log variable (which contains a log of the agent’s thinking).
AgentFinish means that a response should be given.
This contains a return_values dictionary. This usually contains a
single output key, but can be extended to contain more.
This also contains a log variable (which contains a log of the agent’s thinking).
Classes¶
agents.output_parsers.json.JSONAgentOutputParser
Parses tool invocations and final answers in XML format.
agents.output_parsers.openai_functions.OpenAIFunctionsAgentOutputParser
Parses a message into agent action/finish.
agents.output_parsers.react_json_single_input.ReActJsonSingleInputOutputParser
Parses ReAct-style LLM calls that have a single tool input in json format.
agents.output_parsers.react_single_input.ReActSingleInputOutputParser
Parses ReAct-style LLM calls that have a single tool input.
agents.output_parsers.self_ask.SelfAskOutputParser
Parses self-ask style LLM calls.
agents.output_parsers.xml.XMLAgentOutputParser
Parses tool invocations and final answers in XML format.
langchain.cache¶
Warning
Beta Feature!
Cache provides an optional caching layer for LLMs.
Cache is useful for two reasons:
It can save you money by reducing the number of API calls you make to the LLM
provider if you’re often requesting the same completion multiple times.
It can speed up your application by reducing the number of API calls you make
to the LLM provider.
Cache directly competes with Memory. See documentation for Pros and Cons.
Class hierarchy: | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-8 | Cache directly competes with Memory. See documentation for Pros and Cons.
Class hierarchy:
BaseCache --> <name>Cache # Examples: InMemoryCache, RedisCache, GPTCache
Classes¶
cache.CassandraCache([session, keyspace, ...])
Cache that uses Cassandra / Astra DB as a backend.
cache.CassandraSemanticCache(session, ...[, ...])
Cache that uses Cassandra as a vector-store backend for semantic (i.e.
cache.FullLLMCache(**kwargs)
SQLite table for full LLM Cache (all generations).
cache.GPTCache([init_func])
Cache that uses GPTCache as a backend.
cache.InMemoryCache()
Cache that stores things in memory.
cache.MomentoCache(cache_client, cache_name, *)
Cache that uses Momento as a backend.
cache.RedisCache(redis_, *[, ttl])
Cache that uses Redis as a backend.
cache.RedisSemanticCache(redis_url, embedding)
Cache that uses Redis as a vector-store backend.
cache.SQLAlchemyCache(engine, cache_schema)
Cache that uses SQAlchemy as a backend.
cache.SQLiteCache([database_path])
Cache that uses SQLite as a backend.
Functions¶
langchain.callbacks¶
Callback handlers allow listening to events in LangChain.
Class hierarchy:
BaseCallbackHandler --> <name>CallbackHandler # Example: AimCallbackHandler
Classes¶
callbacks.aim_callback.AimCallbackHandler([...])
Callback Handler that logs to Aim.
callbacks.aim_callback.BaseMetadataCallbackHandler()
This class handles the metadata and associated function states for callbacks.
callbacks.argilla_callback.ArgillaCallbackHandler(...)
Callback Handler that logs into Argilla.
callbacks.arize_callback.ArizeCallbackHandler([...])
Callback Handler that logs to Arize.
callbacks.arthur_callback.ArthurCallbackHandler(...) | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-9 | Callback Handler that logs to Arize.
callbacks.arthur_callback.ArthurCallbackHandler(...)
Callback Handler that logs to Arthur platform.
callbacks.base.AsyncCallbackHandler()
Async callback handler that can be used to handle callbacks from langchain.
callbacks.base.BaseCallbackHandler()
Base callback handler that can be used to handle callbacks from langchain.
callbacks.base.BaseCallbackManager(handlers)
Base callback manager that handles callbacks from 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.clearml_callback.ClearMLCallbackHandler([...])
Callback Handler that logs to ClearML.
callbacks.comet_ml_callback.CometCallbackHandler([...])
Callback Handler that logs to Comet.
callbacks.confident_callback.DeepEvalCallbackHandler(metrics)
Callback Handler that logs into deepeval.
callbacks.context_callback.ContextCallbackHandler([...])
Callback Handler that records transcripts to the Context service.
callbacks.file.FileCallbackHandler(filename)
Callback Handler that writes to a file.
callbacks.flyte_callback.FlyteCallbackHandler()
This callback handler that is used within a Flyte task.
callbacks.human.HumanApprovalCallbackHandler(...)
Callback for manually validating values.
callbacks.human.HumanRejectedException
Exception to raise when a person manually review and rejects a value.
callbacks.infino_callback.InfinoCallbackHandler([...])
Callback Handler that logs to Infino.
callbacks.labelstudio_callback.LabelStudioCallbackHandler([...])
Label Studio callback handler.
callbacks.labelstudio_callback.LabelStudioMode(value)
callbacks.llmonitor_callback.LLMonitorCallbackHandler([...]) | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-10 | callbacks.llmonitor_callback.LLMonitorCallbackHandler([...])
Initializes the LLMonitorCallbackHandler. #### Parameters: - app_id: The app id of the app you want to report to. Defaults to None, which means that LLMONITOR_APP_ID will be used. - api_url: The url of the LLMonitor API. Defaults to None, which means that either LLMONITOR_API_URL environment variable or https://app.llmonitor.com will be used.
callbacks.llmonitor_callback.UserContextManager(user_id)
callbacks.manager.AsyncCallbackManager(handlers)
Async callback manager that handles callbacks from LangChain.
callbacks.manager.AsyncCallbackManagerForChainGroup(...)
Initialize callback manager.
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 that handles callbacks from langchain.
callbacks.manager.CallbackManagerForChainGroup(...)
Initialize callback manager.
callbacks.manager.CallbackManagerForChainRun(*, ...)
Callback manager for chain run.
callbacks.manager.CallbackManagerForLLMRun(*, ...)
Callback manager for LLM run.
callbacks.manager.CallbackManagerForRetrieverRun(*, ...)
Callback manager for retriever run. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-11 | 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.mlflow_callback.MlflowCallbackHandler([...])
Callback Handler that logs metrics and artifacts to mlflow server.
callbacks.mlflow_callback.MlflowLogger(**kwargs)
Callback Handler that logs metrics and artifacts to mlflow server.
callbacks.openai_info.OpenAICallbackHandler()
Callback Handler that tracks OpenAI info.
callbacks.promptlayer_callback.PromptLayerCallbackHandler([...])
Callback handler for promptlayer.
callbacks.sagemaker_callback.SageMakerCallbackHandler(run)
Callback Handler that logs prompt artifacts and metrics to SageMaker Experiments.
callbacks.stdout.StdOutCallbackHandler([color])
Callback Handler that prints to std out.
callbacks.streaming_aiter.AsyncIteratorCallbackHandler()
Callback handler that returns an async iterator.
callbacks.streaming_aiter_final_only.AsyncFinalIteratorCallbackHandler(*)
Callback handler that returns an async iterator.
callbacks.streaming_stdout.StreamingStdOutCallbackHandler()
Callback handler for streaming.
callbacks.streaming_stdout_final_only.FinalStreamingStdOutCallbackHandler(*)
Callback handler for streaming in agents.
callbacks.streamlit.mutable_expander.ChildRecord(...)
The child record as a NamedTuple.
callbacks.streamlit.mutable_expander.ChildType(value)
The enumerator of the child type.
callbacks.streamlit.mutable_expander.MutableExpander(...)
A Streamlit expander that can be renamed and dynamically expanded/collapsed.
callbacks.streamlit.streamlit_callback_handler.LLMThought(...)
A thought in the LLM's thought stream.
callbacks.streamlit.streamlit_callback_handler.LLMThoughtLabeler()
Generates markdown labels for LLMThought containers. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-12 | Generates markdown labels for LLMThought containers.
callbacks.streamlit.streamlit_callback_handler.LLMThoughtState(value)
Enumerator of the LLMThought state.
callbacks.streamlit.streamlit_callback_handler.StreamlitCallbackHandler(...)
A callback handler that writes to a Streamlit app.
callbacks.streamlit.streamlit_callback_handler.ToolRecord(...)
The tool record as a NamedTuple.
callbacks.tracers.base.BaseTracer(**kwargs)
Base interface for tracers.
callbacks.tracers.base.TracerException
Base class for exceptions in tracers module.
callbacks.tracers.evaluation.EvaluatorCallbackHandler(...)
A tracer that runs a run evaluator whenever a run is persisted.
callbacks.tracers.langchain.LangChainTracer([...])
An implementation of the SharedTracer that POSTS to the langchain endpoint.
callbacks.tracers.langchain_v1.LangChainTracerV1(...)
An implementation of the SharedTracer that POSTS to the langchain endpoint.
callbacks.tracers.log_stream.LogEntry
callbacks.tracers.log_stream.LogStreamCallbackHandler(*)
callbacks.tracers.log_stream.RunLog(*ops, state)
callbacks.tracers.log_stream.RunLogPatch(*ops)
callbacks.tracers.log_stream.RunState
callbacks.tracers.run_collector.RunCollectorCallbackHandler([...])
A tracer that collects all nested runs in a list.
callbacks.tracers.schemas.BaseRun
Base class for Run.
callbacks.tracers.schemas.ChainRun
Class for ChainRun.
callbacks.tracers.schemas.LLMRun
Class for LLMRun.
callbacks.tracers.schemas.Run
Run schema for the V2 API in the Tracer.
callbacks.tracers.schemas.ToolRun
Class for ToolRun.
callbacks.tracers.schemas.TracerSession
TracerSessionV1 schema for the V2 API.
callbacks.tracers.schemas.TracerSessionBase
Base class for TracerSession. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-13 | callbacks.tracers.schemas.TracerSessionBase
Base class for TracerSession.
callbacks.tracers.schemas.TracerSessionV1
TracerSessionV1 schema.
callbacks.tracers.schemas.TracerSessionV1Base
Base class for TracerSessionV1.
callbacks.tracers.schemas.TracerSessionV1Create
Create class for TracerSessionV1.
callbacks.tracers.stdout.ConsoleCallbackHandler(...)
Tracer that prints to the console.
callbacks.tracers.stdout.FunctionCallbackHandler(...)
Tracer that calls a function with a single str parameter.
callbacks.tracers.wandb.RunProcessor(...)
Handles the conversion of a LangChain Runs into a WBTraceTree.
callbacks.tracers.wandb.WandbRunArgs
Arguments for the WandbTracer.
callbacks.tracers.wandb.WandbTracer([run_args])
Callback Handler that logs to Weights and Biases.
callbacks.trubrics_callback.TrubricsCallbackHandler([...])
Callback handler for Trubrics.
callbacks.utils.BaseMetadataCallbackHandler()
This class handles the metadata and associated function states for callbacks.
callbacks.wandb_callback.WandbCallbackHandler([...])
Callback Handler that logs to Weights and Biases.
callbacks.whylabs_callback.WhyLabsCallbackHandler(...)
Callback Handler for logging to WhyLabs.
Functions¶
callbacks.aim_callback.import_aim()
Import the aim python package and raise an error if it is not installed.
callbacks.clearml_callback.import_clearml()
Import the clearml python package and raise an error if it is not installed.
callbacks.comet_ml_callback.import_comet_ml()
Import comet_ml and raise an error if it is not installed.
callbacks.context_callback.import_context()
Import the getcontext package.
callbacks.flyte_callback.analyze_text(text)
Analyze text using textstat and spacy. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-14 | Analyze text using textstat and spacy.
callbacks.flyte_callback.import_flytekit()
Import flytekit and flytekitplugins-deck-standard.
callbacks.infino_callback.import_infino()
Import the infino client.
callbacks.labelstudio_callback.get_default_label_configs(mode)
callbacks.llmonitor_callback.identify(user_id)
callbacks.manager.atrace_as_chain_group(...)
Get an async callback manager for a chain group in a context manager.
callbacks.manager.collect_runs()
Collect all run traces in context.
callbacks.manager.env_var_is_set(env_var)
Check if an environment variable is set.
callbacks.manager.get_openai_callback()
Get the OpenAI callback handler in a context manager.
callbacks.manager.trace_as_chain_group(...)
Get a callback manager for a chain group in a context manager.
callbacks.manager.tracing_enabled([session_name])
Get the Deprecated LangChainTracer in a context manager.
callbacks.manager.tracing_v2_enabled([...])
Instruct LangChain to log all runs in context to LangSmith.
callbacks.manager.wandb_tracing_enabled([...])
Get the WandbTracer in a context manager.
callbacks.mlflow_callback.analyze_text(text)
Analyze text using textstat and spacy.
callbacks.mlflow_callback.construct_html_from_prompt_and_generation(...)
Construct an html element from a prompt and a generation.
callbacks.mlflow_callback.import_mlflow()
Import the mlflow python package and raise an error if it is not installed.
callbacks.openai_info.get_openai_token_cost_for_model(...)
Get the cost in USD for a given model and number of tokens.
callbacks.openai_info.standardize_model_name(...)
Standardize the model name to a format that can be used in the OpenAI API.
callbacks.sagemaker_callback.save_json(data, ...)
Save dict to local file path. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-15 | callbacks.sagemaker_callback.save_json(data, ...)
Save dict to local file path.
callbacks.tracers.evaluation.wait_for_all_evaluators()
Wait for all tracers to finish.
callbacks.tracers.langchain.get_client()
Get the client.
callbacks.tracers.langchain.log_error_once(...)
Log an error once.
callbacks.tracers.langchain.wait_for_all_tracers()
Wait for all tracers to finish.
callbacks.tracers.langchain_v1.get_headers()
Get the headers for the LangChain API.
callbacks.tracers.schemas.RunTypeEnum()
RunTypeEnum.
callbacks.tracers.stdout.elapsed(run)
Get the elapsed time of a run.
callbacks.tracers.stdout.try_json_stringify(...)
Try to stringify an object to JSON.
callbacks.utils.flatten_dict(nested_dict[, ...])
Flattens a nested dictionary into a flat dictionary.
callbacks.utils.hash_string(s)
Hash a string using sha1.
callbacks.utils.import_pandas()
Import the pandas python package and raise an error if it is not installed.
callbacks.utils.import_spacy()
Import the spacy python package and raise an error if it is not installed.
callbacks.utils.import_textstat()
Import the textstat python package and raise an error if it is not installed.
callbacks.utils.load_json(json_path)
Load json file to a string.
callbacks.wandb_callback.analyze_text(text)
Analyze text using textstat and spacy.
callbacks.wandb_callback.construct_html_from_prompt_and_generation(...)
Construct an html element from a prompt and a generation.
callbacks.wandb_callback.import_wandb()
Import the wandb python package and raise an error if it is not installed.
callbacks.wandb_callback.load_json_to_dict(...)
Load json file to a dictionary.
callbacks.whylabs_callback.import_langkit([...]) | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-16 | Load json file to a dictionary.
callbacks.whylabs_callback.import_langkit([...])
Import the langkit python package and raise an error if it is not installed.
langchain.chains¶
Chains are easily reusable components linked together.
Chains encode a sequence of calls to components like models, document retrievers,
other Chains, etc., and provide a simple interface to this sequence.
The Chain interface makes it easy to create apps that are:
Stateful: add Memory to any Chain to give it state,
Observable: pass Callbacks to a Chain to execute additional functionality,
like logging, outside the main sequence of component calls,
Composable: combine Chains with other components, including other Chains.
Class hierarchy:
Chain --> <name>Chain # Examples: LLMChain, MapReduceChain, RouterChain
Classes¶
chains.api.base.APIChain
Chain that makes API calls and summarizes the responses to answer a question.
chains.api.openapi.chain.OpenAPIEndpointChain
Chain interacts with an OpenAPI endpoint using natural language.
chains.api.openapi.requests_chain.APIRequesterChain
Get the request parser.
chains.api.openapi.requests_chain.APIRequesterOutputParser
Parse the request and error tags.
chains.api.openapi.response_chain.APIResponderChain
Get the response parser.
chains.api.openapi.response_chain.APIResponderOutputParser
Parse the response and error tags.
chains.base.Chain
Abstract base class for creating structured sequences of calls to components.
chains.combine_documents.base.AnalyzeDocumentChain
Chain that splits documents, then analyzes it in pieces.
chains.combine_documents.base.BaseCombineDocumentsChain
Base interface for chains combining documents.
chains.combine_documents.map_reduce.MapReduceDocumentsChain
Combining documents by mapping a chain over them, then combining results.
chains.combine_documents.map_rerank.MapRerankDocumentsChain
Combining documents by mapping a chain over them, then reranking results. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-17 | Combining documents by mapping a chain over them, then reranking results.
chains.combine_documents.reduce.AsyncCombineDocsProtocol(...)
Interface for the combine_docs method.
chains.combine_documents.reduce.CombineDocsProtocol(...)
Interface for the combine_docs method.
chains.combine_documents.reduce.ReduceDocumentsChain
Combine documents by recursively reducing them.
chains.combine_documents.refine.RefineDocumentsChain
Combine documents by doing a first pass and then refining on more documents.
chains.combine_documents.stuff.StuffDocumentsChain
Chain that combines documents by stuffing into context.
chains.constitutional_ai.base.ConstitutionalChain
Chain for applying constitutional principles.
chains.constitutional_ai.models.ConstitutionalPrinciple
Class for a constitutional principle.
chains.conversation.base.ConversationChain
Chain to have a conversation and load context from memory.
chains.conversational_retrieval.base.BaseConversationalRetrievalChain
Chain for chatting with an index.
chains.conversational_retrieval.base.ChatVectorDBChain
Chain for chatting with a vector database.
chains.conversational_retrieval.base.ConversationalRetrievalChain
Chain for having a conversation based on retrieved documents.
chains.elasticsearch_database.base.ElasticsearchDatabaseChain
Chain for interacting with Elasticsearch Database.
chains.flare.base.FlareChain
Chain that combines a retriever, a question generator, and a response generator.
chains.flare.base.QuestionGeneratorChain
Chain that generates questions from uncertain spans.
chains.flare.prompts.FinishedOutputParser
Output parser that checks if the output is finished.
chains.graph_qa.arangodb.ArangoGraphQAChain
Chain for question-answering against a graph by generating AQL statements.
chains.graph_qa.base.GraphQAChain
Chain for question-answering against a graph.
chains.graph_qa.cypher.GraphCypherQAChain | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-18 | chains.graph_qa.cypher.GraphCypherQAChain
Chain for question-answering against a graph by generating Cypher statements.
chains.graph_qa.falkordb.FalkorDBQAChain
Chain for question-answering against a graph by generating Cypher statements.
chains.graph_qa.hugegraph.HugeGraphQAChain
Chain for question-answering against a graph by generating gremlin statements.
chains.graph_qa.kuzu.KuzuQAChain
Chain for question-answering against a graph by generating Cypher statements for Kùzu.
chains.graph_qa.nebulagraph.NebulaGraphQAChain
Chain for question-answering against a graph by generating nGQL statements.
chains.graph_qa.neptune_cypher.NeptuneOpenCypherQAChain
Chain for question-answering against a Neptune graph by generating openCypher statements.
chains.graph_qa.sparql.GraphSparqlQAChain
Chain for question-answering against an RDF or OWL graph by generating SPARQL statements.
chains.hyde.base.HypotheticalDocumentEmbedder
Generate hypothetical document for query, and then embed that.
chains.llm.LLMChain
Chain to run queries against LLMs.
chains.llm_bash.base.LLMBashChain
Chain that interprets a prompt and executes bash operations.
chains.llm_bash.prompt.BashOutputParser
Parser for bash output.
chains.llm_checker.base.LLMCheckerChain
Chain for question-answering with self-verification.
chains.llm_math.base.LLMMathChain
Chain that interprets a prompt and executes python code to do math.
chains.llm_requests.LLMRequestsChain
Chain that requests a URL and then uses an LLM to parse results. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-19 | Chain that requests a URL and then uses an LLM to parse results.
chains.llm_summarization_checker.base.LLMSummarizationCheckerChain
Chain for question-answering with self-verification.
chains.llm_symbolic_math.base.LLMSymbolicMathChain
Chain that interprets a prompt and executes python code to do symbolic math.
chains.mapreduce.MapReduceChain
Map-reduce chain.
chains.moderation.OpenAIModerationChain
Pass input through a moderation endpoint.
chains.natbot.base.NatBotChain
Implement an LLM driven browser.
chains.natbot.crawler.Crawler()
A crawler for web pages.
chains.natbot.crawler.ElementInViewPort
A typed dictionary containing information about elements in the viewport.
chains.openai_functions.citation_fuzzy_match.FactWithEvidence
Class representing a single statement.
chains.openai_functions.citation_fuzzy_match.QuestionAnswer
A question and its answer as a list of facts each one should have a source.
chains.openai_functions.openapi.SimpleRequestChain
Chain for making a simple request to an API endpoint.
chains.openai_functions.qa_with_structure.AnswerWithSources
An answer to the question, with sources.
chains.prompt_selector.BasePromptSelector
Base class for prompt selectors.
chains.prompt_selector.ConditionalPromptSelector
Prompt collection that goes through conditionals.
chains.qa_generation.base.QAGenerationChain
Base class for question-answer generation chains.
chains.qa_with_sources.base.BaseQAWithSourcesChain
Question answering chain with sources over documents.
chains.qa_with_sources.base.QAWithSourcesChain
Question answering with sources over documents.
chains.qa_with_sources.loading.LoadingCallable(...)
Interface for loading the combine documents chain.
chains.qa_with_sources.retrieval.RetrievalQAWithSourcesChain
Question-answering with sources over an index. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-20 | Question-answering with sources over an index.
chains.qa_with_sources.vector_db.VectorDBQAWithSourcesChain
Question-answering with sources over a vector database.
chains.query_constructor.base.StructuredQueryOutputParser
Output parser that parses a structured query.
chains.query_constructor.ir.Comparator(value)
Enumerator of the comparison operators.
chains.query_constructor.ir.Comparison
A comparison to a value.
chains.query_constructor.ir.Expr
Base class for all expressions.
chains.query_constructor.ir.FilterDirective
A filtering expression.
chains.query_constructor.ir.Operation
A logical operation over other directives.
chains.query_constructor.ir.Operator(value)
Enumerator of the operations.
chains.query_constructor.ir.StructuredQuery
A structured query.
chains.query_constructor.ir.Visitor()
Defines interface for IR translation using visitor pattern.
chains.query_constructor.schema.AttributeInfo
Information about a data source attribute.
chains.retrieval_qa.base.BaseRetrievalQA
Base class for question-answering chains.
chains.retrieval_qa.base.RetrievalQA
Chain for question-answering against an index.
chains.retrieval_qa.base.VectorDBQA
Chain for question-answering against a vector database.
chains.router.base.MultiRouteChain
Use a single chain to route an input to one of multiple candidate chains.
chains.router.base.Route(destination, ...)
Create new instance of Route(destination, next_inputs)
chains.router.base.RouterChain
Chain that outputs the name of a destination chain and the inputs to it.
chains.router.embedding_router.EmbeddingRouterChain
Chain that uses embeddings to route between options.
chains.router.llm_router.LLMRouterChain
A router chain that uses an LLM chain to perform routing.
chains.router.llm_router.RouterOutputParser
Parser for output of router chain in the multi-prompt chain.
chains.router.multi_prompt.MultiPromptChain | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-21 | chains.router.multi_prompt.MultiPromptChain
A multi-route chain that uses an LLM router chain to choose amongst prompts.
chains.router.multi_retrieval_qa.MultiRetrievalQAChain
A multi-route chain that uses an LLM router chain to choose amongst retrieval qa chains.
chains.sequential.SequentialChain
Chain where the outputs of one chain feed directly into next.
chains.sequential.SimpleSequentialChain
Simple chain where the outputs of one step feed directly into next.
chains.sql_database.query.SQLInput
Input for a SQL Chain.
chains.sql_database.query.SQLInputWithTables
Input for a SQL Chain.
chains.transform.TransformChain
Chain that transforms the chain output.
Functions¶
chains.example_generator.generate_example(...)
Return another example given a list of examples for a prompt.
chains.graph_qa.cypher.construct_schema(...)
Filter the schema based on included or excluded types
chains.graph_qa.cypher.extract_cypher(text)
Extract Cypher code from a text.
chains.graph_qa.falkordb.extract_cypher(text)
Extract Cypher code from a text.
chains.graph_qa.neptune_cypher.extract_cypher(text)
Extract Cypher code from text using Regex.
chains.graph_qa.neptune_cypher.trim_query(query)
chains.graph_qa.neptune_cypher.use_simple_prompt(llm)
Decides whether to use the simple prompt
chains.loading.load_chain(path, **kwargs)
Unified method for loading a chain from LangChainHub or local fs.
chains.loading.load_chain_from_config(...)
Load chain from Config Dict.
chains.openai_functions.base.convert_python_function_to_openai_function(...)
Convert a Python function to an OpenAI function-calling API compatible dict.
chains.openai_functions.base.convert_to_openai_function(...)
Convert a raw function/class to an OpenAI function. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-22 | Convert a raw function/class to an OpenAI function.
chains.openai_functions.base.create_openai_fn_chain(...)
Create an LLM chain that uses OpenAI functions.
chains.openai_functions.base.create_structured_output_chain(...)
Create an LLMChain that uses an OpenAI function to get a structured output.
chains.openai_functions.citation_fuzzy_match.create_citation_fuzzy_match_chain(llm)
Create a citation fuzzy match chain.
chains.openai_functions.extraction.create_extraction_chain(...)
Creates a chain that extracts information from a passage.
chains.openai_functions.extraction.create_extraction_chain_pydantic(...)
Creates a chain that extracts information from a passage using pydantic schema.
chains.openai_functions.openapi.get_openapi_chain(spec)
Create a chain for querying an API from a OpenAPI spec.
chains.openai_functions.openapi.openapi_spec_to_openai_fn(spec)
Convert a valid OpenAPI spec to the JSON Schema format expected for OpenAI
chains.openai_functions.qa_with_structure.create_qa_with_sources_chain(llm)
Create a question answering chain that returns an answer with sources.
chains.openai_functions.qa_with_structure.create_qa_with_structure_chain(...)
Create a question answering chain that returns an answer with sources
chains.openai_functions.tagging.create_tagging_chain(...)
Creates a chain that extracts information from a passage
chains.openai_functions.tagging.create_tagging_chain_pydantic(...)
Creates a chain that extracts information from a passage
chains.openai_functions.utils.get_llm_kwargs(...)
Returns the kwargs for the LLMChain constructor.
chains.prompt_selector.is_chat_model(llm)
Check if the language model is a chat model.
chains.prompt_selector.is_llm(llm)
Check if the language model is a LLM.
chains.qa_with_sources.loading.load_qa_with_sources_chain(llm)
Load a question answering with sources chain. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-23 | Load a question answering with sources chain.
chains.query_constructor.base.load_query_constructor_chain(...)
Load a query constructor chain.
chains.query_constructor.parser.get_parser([...])
Returns a parser for the query language.
chains.query_constructor.parser.v_args(...)
Dummy decorator for when lark is not installed.
chains.sql_database.query.create_sql_query_chain(llm, db)
Create a chain that generates SQL queries.
langchain.chat_loaders¶
Chat Loaders load chat messages from common communications platforms.
Load chat messages from various
communications platforms such as Facebook Messenger, Telegram, and
WhatsApp. The loaded chat messages can be used for fine-tuning models.
Class hierarchy:
BaseChatLoader --> <name>ChatLoader # Examples: WhatsAppChatLoader, IMessageChatLoader
Main helpers:
ChatSession
Classes¶
chat_loaders.base.BaseChatLoader()
Base class for chat loaders.
chat_loaders.facebook_messenger.FolderFacebookMessengerChatLoader(path)
Load Facebook Messenger chat data from a folder.
chat_loaders.facebook_messenger.SingleFileFacebookMessengerChatLoader(path)
Load Facebook Messenger chat data from a single file.
chat_loaders.gmail.GMailLoader(creds[, n, ...])
Load data from GMail.
chat_loaders.imessage.IMessageChatLoader([path])
Load chat sessions from the iMessage chat.db SQLite file.
chat_loaders.slack.SlackChatLoader(path)
Load Slack conversations from a dump zip file.
chat_loaders.telegram.TelegramChatLoader(path)
Load telegram conversations to LangChain chat messages.
chat_loaders.whatsapp.WhatsAppChatLoader(path)
Load WhatsApp conversations from a dump zip file or directory.
Functions¶
chat_loaders.utils.map_ai_messages(...)
Convert messages from the specified 'sender' to AI messages.
chat_loaders.utils.map_ai_messages_in_session(...) | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-24 | chat_loaders.utils.map_ai_messages_in_session(...)
Convert messages from the specified 'sender' to AI messages.
chat_loaders.utils.merge_chat_runs(chat_sessions)
Merge chat runs together.
chat_loaders.utils.merge_chat_runs_in_session(...)
Merge chat runs together in a chat session.
langchain.chat_models¶
Chat Models are a variation on language models.
While Chat Models use language models under the hood, the interface they expose
is a bit different. Rather than expose a “text in, text out” API, they expose
an interface where “chat messages” are the inputs and outputs.
Class hierarchy:
BaseLanguageModel --> BaseChatModel --> <name> # Examples: ChatOpenAI, ChatGooglePalm
Main helpers:
AIMessage, BaseMessage, HumanMessage
Classes¶
chat_models.anthropic.ChatAnthropic
Anthropic chat large language models.
chat_models.anyscale.ChatAnyscale
Anyscale Chat large language models.
chat_models.azure_openai.AzureChatOpenAI
Azure OpenAI Chat Completion API.
chat_models.azureml_endpoint.AzureMLChatOnlineEndpoint
AzureML Chat models API.
chat_models.azureml_endpoint.LlamaContentFormatter()
Content formatter for LLaMA.
chat_models.baidu_qianfan_endpoint.QianfanChatEndpoint
Baidu Qianfan chat models.
chat_models.base.BaseChatModel
Base class for Chat models.
chat_models.base.SimpleChatModel
Simple Chat Model.
chat_models.bedrock.BedrockChat
Create a new model by parsing and validating input data from keyword arguments.
chat_models.bedrock.ChatPromptAdapter()
Adapter class to prepare the inputs from Langchain to prompt format that Chat model expects.
chat_models.ernie.ErnieBotChat
ERNIE-Bot large language model.
chat_models.fake.FakeListChatModel
Fake ChatModel for testing purposes. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-25 | chat_models.fake.FakeListChatModel
Fake ChatModel for testing purposes.
chat_models.fake.FakeMessagesListChatModel
Create a new model by parsing and validating input data from keyword arguments.
chat_models.fireworks.ChatFireworks
Fireworks Chat models.
chat_models.google_palm.ChatGooglePalm
Google PaLM Chat models API.
chat_models.google_palm.ChatGooglePalmError
Error with the Google PaLM API.
chat_models.human.HumanInputChatModel
ChatModel which returns user input as the response.
chat_models.javelin_ai_gateway.ChatJavelinAIGateway
Javelin AI Gateway chat models API.
chat_models.javelin_ai_gateway.ChatParams
Parameters for the Javelin AI Gateway LLM.
chat_models.jinachat.JinaChat
Jina AI Chat models API.
chat_models.konko.ChatKonko
ChatKonko Chat large language models API.
chat_models.litellm.ChatLiteLLM
Create a new model by parsing and validating input data from keyword arguments.
chat_models.litellm.ChatLiteLLMException
Error with the LiteLLM I/O library
chat_models.minimax.MiniMaxChat
Wrapper around Minimax large language models.
chat_models.mlflow_ai_gateway.ChatMLflowAIGateway
MLflow AI Gateway chat models API.
chat_models.mlflow_ai_gateway.ChatParams
Parameters for the MLflow AI Gateway LLM.
chat_models.ollama.ChatOllama
Ollama locally runs large language models.
chat_models.openai.ChatOpenAI
OpenAI Chat large language models API.
chat_models.promptlayer_openai.PromptLayerChatOpenAI
PromptLayer and OpenAI Chat large language models API.
chat_models.vertexai.ChatVertexAI
Vertex AI Chat large language models API.
Functions¶ | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-26 | chat_models.vertexai.ChatVertexAI
Vertex AI Chat large language models API.
Functions¶
chat_models.anthropic.convert_messages_to_prompt_anthropic(...)
Format a list of messages into a full prompt for the Anthropic model
chat_models.baidu_qianfan_endpoint.convert_message_to_dict(message)
chat_models.fireworks.acompletion_with_retry(llm, *)
Use tenacity to retry the async completion call.
chat_models.fireworks.acompletion_with_retry_streaming(llm, *)
Use tenacity to retry the completion call for streaming.
chat_models.fireworks.completion_with_retry(llm, *)
Use tenacity to retry the completion call.
chat_models.fireworks.convert_dict_to_message(_dict)
Convert a dict response to a message.
chat_models.google_palm.achat_with_retry(...)
Use tenacity to retry the async completion call.
chat_models.google_palm.chat_with_retry(llm, ...)
Use tenacity to retry the completion call.
chat_models.jinachat.acompletion_with_retry(...)
Use tenacity to retry the async completion call.
chat_models.litellm.acompletion_with_retry(llm)
Use tenacity to retry the async completion call.
chat_models.openai.acompletion_with_retry(llm)
Use tenacity to retry the async completion call.
langchain.docstore¶
Docstores are classes to store and load Documents.
The Docstore is a simplified version of the Document Loader.
Class hierarchy:
Docstore --> <name> # Examples: InMemoryDocstore, Wikipedia
Main helpers:
Document, AddableMixin
Classes¶
docstore.arbitrary_fn.DocstoreFn(lookup_fn)
Langchain Docstore via arbitrary lookup function.
docstore.base.AddableMixin()
Mixin class that supports adding texts.
docstore.base.Docstore() | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-27 | Mixin class that supports adding texts.
docstore.base.Docstore()
Interface to access to place that stores documents.
docstore.in_memory.InMemoryDocstore([_dict])
Simple in memory docstore in the form of a dict.
docstore.wikipedia.Wikipedia()
Wrapper around wikipedia API.
langchain.document_loaders¶
Document Loaders are classes to load Documents.
Document Loaders are usually used to load a lot of Documents in a single run.
Class hierarchy:
BaseLoader --> <name>Loader # Examples: TextLoader, UnstructuredFileLoader
Main helpers:
Document, <name>TextSplitter
Classes¶
document_loaders.acreom.AcreomLoader(path[, ...])
Load acreom vault from a directory.
document_loaders.airbyte.AirbyteCDKLoader(...)
Load with an Airbyte source connector implemented using the CDK.
document_loaders.airbyte.AirbyteGongLoader(...)
Load from Gong using an Airbyte source connector.
document_loaders.airbyte.AirbyteHubspotLoader(...)
Load from Hubspot using an Airbyte source connector.
document_loaders.airbyte.AirbyteSalesforceLoader(...)
Load from Salesforce using an Airbyte source connector.
document_loaders.airbyte.AirbyteShopifyLoader(...)
Load from Shopify using an Airbyte source connector.
document_loaders.airbyte.AirbyteStripeLoader(...)
Load from Stripe using an Airbyte source connector.
document_loaders.airbyte.AirbyteTypeformLoader(...)
Load from Typeform using an Airbyte source connector.
document_loaders.airbyte.AirbyteZendeskSupportLoader(...)
Load from Zendesk Support using an Airbyte source connector.
document_loaders.airbyte_json.AirbyteJSONLoader(...)
Load local Airbyte json files.
document_loaders.airtable.AirtableLoader(...) | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-28 | Load local Airbyte json files.
document_loaders.airtable.AirtableLoader(...)
Load the Airtable tables.
document_loaders.apify_dataset.ApifyDatasetLoader
Load datasets from Apify web scraping, crawling, and data extraction platform.
document_loaders.arcgis_loader.ArcGISLoader(layer)
Load records from an ArcGIS FeatureLayer.
document_loaders.arxiv.ArxivLoader(query[, ...])
Load a query result from Arxiv.
document_loaders.assemblyai.AssemblyAIAudioTranscriptLoader(...)
Loader for AssemblyAI audio transcripts.
document_loaders.assemblyai.TranscriptFormat(value)
Transcript format to use for the document loader.
document_loaders.async_html.AsyncHtmlLoader(...)
Load HTML asynchronously.
document_loaders.azlyrics.AZLyricsLoader([...])
Load AZLyrics webpages.
document_loaders.azure_blob_storage_container.AzureBlobStorageContainerLoader(...)
Load from Azure Blob Storage container.
document_loaders.azure_blob_storage_file.AzureBlobStorageFileLoader(...)
Load from Azure Blob Storage files.
document_loaders.base.BaseBlobParser()
Abstract interface for blob parsers.
document_loaders.base.BaseLoader()
Interface for Document Loader.
document_loaders.base_o365.O365BaseLoader
Create a new model by parsing and validating input data from keyword arguments.
document_loaders.bibtex.BibtexLoader(...[, ...])
Load a bibtex file.
document_loaders.bigquery.BigQueryLoader(query)
Load from the Google Cloud Platform BigQuery.
document_loaders.bilibili.BiliBiliLoader(...)
Load BiliBili video transcripts.
document_loaders.blackboard.BlackboardLoader(...)
Load a Blackboard course.
document_loaders.blob_loaders.file_system.FileSystemBlobLoader(path, *)
Load blobs in the local file system. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-29 | Load blobs in the local file system.
document_loaders.blob_loaders.schema.Blob
Blob represents raw data by either reference or value.
document_loaders.blob_loaders.schema.BlobLoader()
Abstract interface for blob loaders implementation.
document_loaders.blob_loaders.youtube_audio.YoutubeAudioLoader(...)
Load YouTube urls as audio file(s).
document_loaders.blockchain.BlockchainDocumentLoader(...)
Load elements from a blockchain smart contract.
document_loaders.blockchain.BlockchainType(value)
Enumerator of the supported blockchains.
document_loaders.brave_search.BraveSearchLoader(...)
Load with Brave Search engine.
document_loaders.browserless.BrowserlessLoader(...)
Load webpages with Browserless /content endpoint.
document_loaders.chatgpt.ChatGPTLoader(log_file)
Load conversations from exported ChatGPT data.
document_loaders.chromium.AsyncChromiumLoader(urls)
Scrape HTML pages from URLs using a headless instance of the Chromium.
document_loaders.college_confidential.CollegeConfidentialLoader([...])
Load College Confidential webpages.
document_loaders.concurrent.ConcurrentLoader(...)
Load and pars Documents concurrently.
document_loaders.confluence.ConfluenceLoader(url)
Load Confluence pages.
document_loaders.confluence.ContentFormat(value)
Enumerator of the content formats of Confluence page.
document_loaders.conllu.CoNLLULoader(file_path)
Load CoNLL-U files.
document_loaders.csv_loader.CSVLoader(file_path)
Load a CSV file into a list of Documents.
document_loaders.csv_loader.UnstructuredCSVLoader(...)
Load CSV files using Unstructured.
document_loaders.cube_semantic.CubeSemanticLoader(...)
Load Cube semantic layer metadata.
document_loaders.datadog_logs.DatadogLogsLoader(...)
Load Datadog logs.
document_loaders.dataframe.BaseDataFrameLoader(...) | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-30 | Load Datadog logs.
document_loaders.dataframe.BaseDataFrameLoader(...)
Initialize with dataframe object.
document_loaders.dataframe.DataFrameLoader(...)
Load Pandas DataFrame.
document_loaders.diffbot.DiffbotLoader(...)
Load Diffbot json file.
document_loaders.directory.DirectoryLoader(...)
Load from a directory.
document_loaders.discord.DiscordChatLoader(...)
Load Discord chat logs.
document_loaders.docugami.DocugamiLoader
Load from Docugami.
document_loaders.dropbox.DropboxLoader
Load files from Dropbox.
document_loaders.duckdb_loader.DuckDBLoader(query)
Load from DuckDB.
document_loaders.email.OutlookMessageLoader(...)
Loads Outlook Message files using extract_msg.
document_loaders.email.UnstructuredEmailLoader(...)
Load email files using Unstructured.
document_loaders.embaas.BaseEmbaasLoader
Base loader for Embaas document extraction API.
document_loaders.embaas.EmbaasBlobLoader
Load Embaas blob.
document_loaders.embaas.EmbaasDocumentExtractionParameters
Parameters for the embaas document extraction API.
document_loaders.embaas.EmbaasDocumentExtractionPayload
Payload for the Embaas document extraction API.
document_loaders.embaas.EmbaasLoader
Load from Embaas.
document_loaders.epub.UnstructuredEPubLoader(...)
Load EPub files using Unstructured.
document_loaders.etherscan.EtherscanLoader(...)
Load transactions from Ethereum mainnet.
document_loaders.evernote.EverNoteLoader(...)
Load from EverNote.
document_loaders.excel.UnstructuredExcelLoader(...)
Load Microsoft Excel files using Unstructured.
document_loaders.facebook_chat.FacebookChatLoader(path)
Load Facebook Chat messages directory dump. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-31 | document_loaders.facebook_chat.FacebookChatLoader(path)
Load Facebook Chat messages directory dump.
document_loaders.fauna.FaunaLoader(query, ...)
Load from FaunaDB.
document_loaders.figma.FigmaFileLoader(...)
Load Figma file.
document_loaders.gcs_directory.GCSDirectoryLoader(...)
Load from GCS directory.
document_loaders.gcs_file.GCSFileLoader(...)
Load from GCS file.
document_loaders.generic.GenericLoader(...)
Generic Document Loader.
document_loaders.geodataframe.GeoDataFrameLoader(...)
Load geopandas Dataframe.
document_loaders.git.GitLoader(repo_path[, ...])
Load Git repository files.
document_loaders.gitbook.GitbookLoader(web_page)
Load GitBook data.
document_loaders.github.BaseGitHubLoader
Load GitHub repository Issues.
document_loaders.github.GitHubIssuesLoader
Load issues of a GitHub repository.
document_loaders.googledrive.GoogleDriveLoader
Load Google Docs from Google Drive.
document_loaders.gutenberg.GutenbergLoader(...)
Load from Gutenberg.org.
document_loaders.helpers.FileEncoding(...)
File encoding as the NamedTuple.
document_loaders.hn.HNLoader([web_path, ...])
Load Hacker News data.
document_loaders.html.UnstructuredHTMLLoader(...)
Load HTML files using Unstructured.
document_loaders.html_bs.BSHTMLLoader(file_path)
Load HTML files and parse them with beautiful soup.
document_loaders.hugging_face_dataset.HuggingFaceDatasetLoader(path)
Load from Hugging Face Hub datasets.
document_loaders.ifixit.IFixitLoader(web_path)
Load iFixit repair guides, device wikis and answers.
document_loaders.image.UnstructuredImageLoader(...)
Load PNG and JPG files using Unstructured.
document_loaders.image_captions.ImageCaptionLoader(...) | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-32 | document_loaders.image_captions.ImageCaptionLoader(...)
Load image captions.
document_loaders.imsdb.IMSDbLoader([...])
Load IMSDb webpages.
document_loaders.iugu.IuguLoader(resource[, ...])
Load from IUGU.
document_loaders.joplin.JoplinLoader([...])
Load notes from Joplin.
document_loaders.json_loader.JSONLoader(...)
Load a JSON file using a jq schema.
document_loaders.larksuite.LarkSuiteDocLoader(...)
Load from LarkSuite (FeiShu).
document_loaders.markdown.UnstructuredMarkdownLoader(...)
Load Markdown files using Unstructured.
document_loaders.mastodon.MastodonTootsLoader(...)
Load the Mastodon 'toots'.
document_loaders.max_compute.MaxComputeLoader(...)
Load from Alibaba Cloud MaxCompute table.
document_loaders.mediawikidump.MWDumpLoader(...)
Load MediaWiki dump from an XML file.
document_loaders.merge.MergedDataLoader(loaders)
Merge documents from a list of loaders
document_loaders.mhtml.MHTMLLoader(file_path)
Parse MHTML files with BeautifulSoup.
document_loaders.modern_treasury.ModernTreasuryLoader(...)
Load from Modern Treasury.
document_loaders.mongodb.MongodbLoader(...)
Load MongoDB documents.
document_loaders.news.NewsURLLoader(urls[, ...])
Load news articles from URLs using Unstructured.
document_loaders.notebook.NotebookLoader(path)
Load Jupyter notebook (.ipynb) files.
document_loaders.notion.NotionDirectoryLoader(path)
Load Notion directory dump.
document_loaders.notiondb.NotionDBLoader(...)
Load from Notion DB.
document_loaders.nuclia.NucliaLoader(path, ...)
Load from any file type using Nuclia Understanding API. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-33 | Load from any file type using Nuclia Understanding API.
document_loaders.obs_directory.OBSDirectoryLoader(...)
Load from Huawei OBS directory.
document_loaders.obs_file.OBSFileLoader(...)
Load from the Huawei OBS file.
document_loaders.obsidian.ObsidianLoader(path)
Load Obsidian files from directory.
document_loaders.odt.UnstructuredODTLoader(...)
Load OpenOffice ODT files using Unstructured.
document_loaders.onedrive.OneDriveLoader
Load from Microsoft OneDrive.
document_loaders.onedrive_file.OneDriveFileLoader
Load a file from Microsoft OneDrive.
document_loaders.open_city_data.OpenCityDataLoader(...)
Load from Open City.
document_loaders.org_mode.UnstructuredOrgModeLoader(...)
Load Org-Mode files using Unstructured.
document_loaders.parsers.audio.OpenAIWhisperParser([...])
Transcribe and parse audio files.
document_loaders.parsers.audio.OpenAIWhisperParserLocal([...])
Transcribe and parse audio files with OpenAI Whisper model.
document_loaders.parsers.docai.DocAIParser(*)
Initializes the parser.
document_loaders.parsers.docai.DocAIParsingResults(...)
A dataclass to store DocAI parsing results.
document_loaders.parsers.generic.MimeTypeBasedParser(...)
Parser that uses mime-types to parse a blob.
document_loaders.parsers.grobid.GrobidParser(...)
Load article PDF files using Grobid.
document_loaders.parsers.grobid.ServerUnavailableException
Exception raised when the Grobid server is unavailable.
document_loaders.parsers.html.bs4.BS4HTMLParser(*)
Pparse HTML files using Beautiful Soup.
document_loaders.parsers.language.code_segmenter.CodeSegmenter(code)
Abstract class for the code segmenter.
document_loaders.parsers.language.javascript.JavaScriptSegmenter(code)
Code segmenter for JavaScript. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-34 | Code segmenter for JavaScript.
document_loaders.parsers.language.language_parser.LanguageParser([...])
Parse using the respective programming language syntax.
document_loaders.parsers.language.python.PythonSegmenter(code)
Code segmenter for Python.
document_loaders.parsers.msword.MsWordParser()
document_loaders.parsers.pdf.AmazonTextractPDFParser([...])
Send PDF files to Amazon Textract and parse them.
document_loaders.parsers.pdf.DocumentIntelligenceParser(...)
Loads a PDF with Azure Document Intelligence (formerly Forms Recognizer) and chunks at character level.
document_loaders.parsers.pdf.PDFMinerParser()
Parse PDF using PDFMiner.
document_loaders.parsers.pdf.PDFPlumberParser([...])
Parse PDF with PDFPlumber.
document_loaders.parsers.pdf.PyMuPDFParser([...])
Parse PDF using PyMuPDF.
document_loaders.parsers.pdf.PyPDFParser([...])
Load PDF using pypdf and chunk at character level.
document_loaders.parsers.pdf.PyPDFium2Parser()
Parse PDF with PyPDFium2.
document_loaders.parsers.txt.TextParser()
Parser for text blobs.
document_loaders.pdf.AmazonTextractPDFLoader(...)
Load PDF files from a local file system, HTTP or S3.
document_loaders.pdf.BasePDFLoader(file_path, *)
Base Loader class for PDF files.
document_loaders.pdf.DocumentIntelligenceLoader(...)
Loads a PDF with Azure Document Intelligence
document_loaders.pdf.MathpixPDFLoader(file_path)
Load PDF files using Mathpix service.
document_loaders.pdf.OnlinePDFLoader(...[, ...])
Load online PDF.
document_loaders.pdf.PDFMinerLoader(file_path, *)
Load PDF files using PDFMiner.
document_loaders.pdf.PDFMinerPDFasHTMLLoader(...)
Load PDF files as HTML content using PDFMiner. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-35 | Load PDF files as HTML content using PDFMiner.
document_loaders.pdf.PDFPlumberLoader(file_path)
Load PDF files using pdfplumber.
document_loaders.pdf.PyMuPDFLoader(file_path, *)
Load PDF files using PyMuPDF.
document_loaders.pdf.PyPDFDirectoryLoader(path)
Load a directory with PDF files using pypdf and chunks at character level.
document_loaders.pdf.PyPDFLoader(file_path)
Load PDF using `pypdf and chunks at character level.
document_loaders.pdf.PyPDFium2Loader(...[, ...])
Load PDF using pypdfium2 and chunks at character level.
document_loaders.pdf.UnstructuredPDFLoader(...)
Load PDF files using Unstructured.
document_loaders.polars_dataframe.PolarsDataFrameLoader(...)
Load Polars DataFrame.
document_loaders.powerpoint.UnstructuredPowerPointLoader(...)
Load Microsoft PowerPoint files using Unstructured.
document_loaders.psychic.PsychicLoader(...)
Load from Psychic.dev.
document_loaders.pubmed.PubMedLoader(query)
Load from the PubMed biomedical library.
document_loaders.pyspark_dataframe.PySparkDataFrameLoader([...])
Load PySpark DataFrames.
document_loaders.python.PythonLoader(file_path)
Load Python files, respecting any non-default encoding if specified.
document_loaders.readthedocs.ReadTheDocsLoader(path)
Load ReadTheDocs documentation directory.
document_loaders.recursive_url_loader.RecursiveUrlLoader(url)
Load all child links from a URL page.
document_loaders.reddit.RedditPostsLoader(...)
Load Reddit posts.
document_loaders.roam.RoamLoader(path)
Load Roam files from a directory.
document_loaders.rocksetdb.ColumnNotFoundError(...)
Column not found error.
document_loaders.rocksetdb.RocksetLoader(...) | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-36 | Column not found error.
document_loaders.rocksetdb.RocksetLoader(...)
Load from a Rockset database.
document_loaders.rss.RSSFeedLoader([urls, ...])
Load news articles from RSS feeds using Unstructured.
document_loaders.rst.UnstructuredRSTLoader(...)
Load RST files using Unstructured.
document_loaders.rtf.UnstructuredRTFLoader(...)
Load RTF files using Unstructured.
document_loaders.s3_directory.S3DirectoryLoader(bucket)
Load from Amazon AWS S3 directory.
document_loaders.s3_file.S3FileLoader(...[, ...])
Load from Amazon AWS S3 file.
document_loaders.sharepoint.SharePointLoader
Load from SharePoint.
document_loaders.sitemap.SitemapLoader(web_path)
Load a sitemap and its URLs.
document_loaders.slack_directory.SlackDirectoryLoader(...)
Load from a Slack directory dump.
document_loaders.snowflake_loader.SnowflakeLoader(...)
Load from Snowflake API.
document_loaders.spreedly.SpreedlyLoader(...)
Load from Spreedly API.
document_loaders.srt.SRTLoader(file_path)
Load .srt (subtitle) files.
document_loaders.stripe.StripeLoader(resource)
Load from Stripe API.
document_loaders.telegram.TelegramChatApiLoader([...])
Load Telegram chat json directory dump.
document_loaders.telegram.TelegramChatFileLoader(path)
Load from Telegram chat dump.
document_loaders.tencent_cos_directory.TencentCOSDirectoryLoader(...)
Load from Tencent Cloud COS directory.
document_loaders.tencent_cos_file.TencentCOSFileLoader(...)
Load from Tencent Cloud COS file.
document_loaders.tensorflow_datasets.TensorflowDatasetLoader(...)
Load from TensorFlow Dataset.
document_loaders.text.TextLoader(file_path)
Load text file. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-37 | document_loaders.text.TextLoader(file_path)
Load text file.
document_loaders.tomarkdown.ToMarkdownLoader(...)
Load HTML using 2markdown API.
document_loaders.toml.TomlLoader(source)
Load TOML files.
document_loaders.trello.TrelloLoader(client, ...)
Load cards from a Trello board.
document_loaders.tsv.UnstructuredTSVLoader(...)
Load TSV files using Unstructured.
document_loaders.twitter.TwitterTweetLoader(...)
Load Twitter tweets.
document_loaders.unstructured.UnstructuredAPIFileIOLoader(file)
Load files using Unstructured API.
document_loaders.unstructured.UnstructuredAPIFileLoader([...])
Load files using Unstructured API.
document_loaders.unstructured.UnstructuredBaseLoader([...])
Base Loader that uses Unstructured.
document_loaders.unstructured.UnstructuredFileIOLoader(file)
Load files using Unstructured.
document_loaders.unstructured.UnstructuredFileLoader(...)
Load files using Unstructured.
document_loaders.url.UnstructuredURLLoader(urls)
Load files from remote URLs using Unstructured.
document_loaders.url_playwright.PlaywrightEvaluator()
Abstract base class for all evaluators.
document_loaders.url_playwright.PlaywrightURLLoader(urls)
Load HTML pages with Playwright and parse with Unstructured.
document_loaders.url_playwright.UnstructuredHtmlEvaluator([...])
Evaluates the page HTML content using the unstructured library.
document_loaders.url_selenium.SeleniumURLLoader(urls)
Load HTML pages with Selenium and parse with Unstructured.
document_loaders.weather.WeatherDataLoader(...)
Load weather data with Open Weather Map API.
document_loaders.web_base.WebBaseLoader([...])
Load HTML pages using urllib and parse them with `BeautifulSoup'.
document_loaders.whatsapp_chat.WhatsAppChatLoader(path)
Load WhatsApp messages text file. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-38 | Load WhatsApp messages text file.
document_loaders.wikipedia.WikipediaLoader(query)
Load from Wikipedia.
document_loaders.word_document.Docx2txtLoader(...)
Load DOCX file using docx2txt and chunks at character level.
document_loaders.word_document.UnstructuredWordDocumentLoader(...)
Load Microsof Word file using Unstructured.
document_loaders.xml.UnstructuredXMLLoader(...)
Load XML file using Unstructured.
document_loaders.xorbits.XorbitsLoader(...)
Load Xorbits DataFrame.
document_loaders.youtube.GoogleApiClient([...])
Generic Google API Client.
document_loaders.youtube.GoogleApiYoutubeLoader(...)
Load all Videos from a YouTube Channel.
document_loaders.youtube.YoutubeLoader(video_id)
Load YouTube transcripts.
Functions¶
document_loaders.base_o365.fetch_mime_types(...)
document_loaders.chatgpt.concatenate_rows(...)
Combine message information in a readable format ready to be used.
document_loaders.facebook_chat.concatenate_rows(row)
Combine message information in a readable format ready to be used.
document_loaders.helpers.detect_file_encodings(...)
Try to detect the file encoding.
document_loaders.notebook.concatenate_cells(...)
Combine cells information in a readable format ready to be used.
document_loaders.notebook.remove_newlines(x)
Recursively remove newlines, no matter the data structure they are stored in.
document_loaders.parsers.registry.get_parser(...)
Get a parser by parser name.
document_loaders.rocksetdb.default_joiner(docs)
Default joiner for content columns.
document_loaders.telegram.concatenate_rows(row)
Combine message information in a readable format ready to be used.
document_loaders.telegram.text_to_docs(text)
Convert a string or list of strings to a list of Documents with metadata.
document_loaders.unstructured.get_elements_from_api([...])
Retrieve a list of elements from the Unstructured API. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-39 | Retrieve a list of elements from the Unstructured API.
document_loaders.unstructured.satisfies_min_unstructured_version(...)
Check if the installed Unstructured version exceeds the minimum version for the feature in question.
document_loaders.unstructured.validate_unstructured_version(...)
Raise an error if the Unstructured version does not exceed the specified minimum.
document_loaders.whatsapp_chat.concatenate_rows(...)
Combine message information in a readable format ready to be used.
langchain.document_transformers¶
Document Transformers are classes to transform Documents.
Document Transformers usually used to transform a lot of Documents in a single run.
Class hierarchy:
BaseDocumentTransformer --> <name> # Examples: DoctranQATransformer, DoctranTextTranslator
Main helpers:
Document
Classes¶
document_transformers.beautiful_soup_transformer.BeautifulSoupTransformer()
Transform HTML content by extracting specific tags and removing unwanted ones.
document_transformers.doctran_text_extract.DoctranPropertyExtractor(...)
Extract properties from text documents using doctran.
document_transformers.doctran_text_qa.DoctranQATransformer([...])
Extract QA from text documents using doctran.
document_transformers.doctran_text_translate.DoctranTextTranslator([...])
Translate text documents using doctran.
document_transformers.embeddings_redundant_filter.EmbeddingsClusteringFilter
Perform K-means clustering on document vectors.
document_transformers.embeddings_redundant_filter.EmbeddingsRedundantFilter
Filter that drops redundant documents by comparing their embeddings.
document_transformers.html2text.Html2TextTransformer([...])
Replace occurrences of a particular search pattern with a replacement string
document_transformers.long_context_reorder.LongContextReorder
Lost in the middle: Performance degrades when models must access relevant information in the middle of long contexts. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-40 | document_transformers.nuclia_text_transform.NucliaTextTransformer(nua)
The Nuclia Understanding API splits into paragraphs and sentences, identifies entities, provides a summary of the text and generates embeddings for all sentences.
document_transformers.openai_functions.OpenAIMetadataTagger
Extract metadata tags from document contents using OpenAI functions.
Functions¶
document_transformers.embeddings_redundant_filter.get_stateful_documents(...)
Convert a list of documents to a list of documents with state.
document_transformers.openai_functions.create_metadata_tagger(...)
Create a DocumentTransformer that uses an OpenAI function chain to automatically
langchain.embeddings¶
Embedding models are wrappers around embedding models
from different APIs and services.
Embedding models can be LLMs or not.
Class hierarchy:
Embeddings --> <name>Embeddings # Examples: OpenAIEmbeddings, HuggingFaceEmbeddings
Classes¶
embeddings.aleph_alpha.AlephAlphaAsymmetricSemanticEmbedding
Aleph Alpha's asymmetric semantic embedding.
embeddings.aleph_alpha.AlephAlphaSymmetricSemanticEmbedding
The symmetric version of the Aleph Alpha's semantic embeddings.
embeddings.awa.AwaEmbeddings
Embedding documents and queries with Awa DB.
embeddings.baidu_qianfan_endpoint.QianfanEmbeddingsEndpoint
Baidu Qianfan Embeddings embedding models.
embeddings.bedrock.BedrockEmbeddings
Bedrock embedding models.
embeddings.cache.CacheBackedEmbeddings(...)
Interface for caching results from embedding models.
embeddings.clarifai.ClarifaiEmbeddings
Clarifai embedding models.
embeddings.cohere.CohereEmbeddings
Cohere embedding models.
embeddings.dashscope.DashScopeEmbeddings
DashScope embedding models.
embeddings.deepinfra.DeepInfraEmbeddings | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-41 | DashScope embedding models.
embeddings.deepinfra.DeepInfraEmbeddings
Deep Infra's embedding inference service.
embeddings.edenai.EdenAiEmbeddings
EdenAI embedding.
embeddings.elasticsearch.ElasticsearchEmbeddings(...)
Elasticsearch embedding models.
embeddings.embaas.EmbaasEmbeddings
Embaas's embedding service.
embeddings.embaas.EmbaasEmbeddingsPayload
Payload for the Embaas embeddings API.
embeddings.ernie.ErnieEmbeddings
Ernie Embeddings V1 embedding models.
embeddings.fake.DeterministicFakeEmbedding
Fake embedding model that always returns the same embedding vector for the same text.
embeddings.fake.FakeEmbeddings
Fake embedding model.
embeddings.google_palm.GooglePalmEmbeddings
Google's PaLM Embeddings APIs.
embeddings.gpt4all.GPT4AllEmbeddings
GPT4All embedding models.
embeddings.gradient_ai.GradientEmbeddings
Gradient.ai Embedding models.
embeddings.gradient_ai.TinyAsyncGradientEmbeddingClient([...])
A helper tool to embed Gradient.
embeddings.huggingface.HuggingFaceBgeEmbeddings
HuggingFace BGE sentence_transformers embedding models.
embeddings.huggingface.HuggingFaceEmbeddings
HuggingFace sentence_transformers embedding models.
embeddings.huggingface.HuggingFaceInferenceAPIEmbeddings
Embed texts using the HuggingFace API.
embeddings.huggingface.HuggingFaceInstructEmbeddings
Wrapper around sentence_transformers embedding models.
embeddings.huggingface_hub.HuggingFaceHubEmbeddings
HuggingFaceHub embedding models.
embeddings.javelin_ai_gateway.JavelinAIGatewayEmbeddings
Wrapper around embeddings LLMs in the Javelin AI Gateway.
embeddings.jina.JinaEmbeddings
Jina embedding models. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-42 | embeddings.jina.JinaEmbeddings
Jina embedding models.
embeddings.llamacpp.LlamaCppEmbeddings
llama.cpp embedding models.
embeddings.llm_rails.LLMRailsEmbeddings
LLMRails embedding models.
embeddings.localai.LocalAIEmbeddings
LocalAI embedding models.
embeddings.minimax.MiniMaxEmbeddings
MiniMax's embedding service.
embeddings.mlflow_gateway.MlflowAIGatewayEmbeddings
Wrapper around embeddings LLMs in the MLflow AI Gateway.
embeddings.modelscope_hub.ModelScopeEmbeddings
ModelScopeHub embedding models.
embeddings.mosaicml.MosaicMLInstructorEmbeddings
MosaicML embedding service.
embeddings.nlpcloud.NLPCloudEmbeddings
NLP Cloud embedding models.
embeddings.octoai_embeddings.OctoAIEmbeddings
OctoAI Compute Service embedding models.
embeddings.ollama.OllamaEmbeddings
Ollama locally runs large language models.
embeddings.openai.OpenAIEmbeddings
OpenAI embedding models.
embeddings.sagemaker_endpoint.EmbeddingsContentHandler()
Content handler for LLM class.
embeddings.sagemaker_endpoint.SagemakerEndpointEmbeddings
Custom Sagemaker Inference Endpoints.
embeddings.self_hosted.SelfHostedEmbeddings
Custom embedding models on self-hosted remote hardware.
embeddings.self_hosted_hugging_face.SelfHostedHuggingFaceEmbeddings
HuggingFace embedding models on self-hosted remote hardware.
embeddings.self_hosted_hugging_face.SelfHostedHuggingFaceInstructEmbeddings
HuggingFace InstructEmbedding models on self-hosted remote hardware.
embeddings.spacy_embeddings.SpacyEmbeddings
Embeddings by SpaCy models.
embeddings.tensorflow_hub.TensorflowHubEmbeddings
TensorflowHub embedding models. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-43 | embeddings.tensorflow_hub.TensorflowHubEmbeddings
TensorflowHub embedding models.
embeddings.vertexai.VertexAIEmbeddings
Google Cloud VertexAI embedding models.
embeddings.xinference.XinferenceEmbeddings([...])
Wrapper around xinference embedding models.
Functions¶
embeddings.dashscope.embed_with_retry(...)
Use tenacity to retry the embedding call.
embeddings.google_palm.embed_with_retry(...)
Use tenacity to retry the completion call.
embeddings.localai.async_embed_with_retry(...)
Use tenacity to retry the embedding call.
embeddings.localai.embed_with_retry(...)
Use tenacity to retry the embedding call.
embeddings.minimax.embed_with_retry(...)
Use tenacity to retry the completion call.
embeddings.openai.async_embed_with_retry(...)
Use tenacity to retry the embedding call.
embeddings.openai.embed_with_retry(...)
Use tenacity to retry the embedding call.
embeddings.self_hosted_hugging_face.load_embedding_model(...)
Load the embedding model.
langchain.evaluation¶
Evaluation chains for grading LLM and Chain outputs.
This module contains off-the-shelf evaluation chains for grading the output of
LangChain primitives such as language models and chains.
Loading an evaluator
To load an evaluator, you can use the load_evaluators or
load_evaluator functions with the
names of the evaluators to load.
from langchain.evaluation import load_evaluator
evaluator = load_evaluator("qa")
evaluator.evaluate_strings(
prediction="We sold more than 40,000 units last week",
input="How many units did we sell last week?",
reference="We sold 32,378 units",
)
The evaluator must be one of EvaluatorType.
Datasets
To load one of the LangChain HuggingFace datasets, you can use the load_dataset function with the | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-44 | name of the dataset to load.
from langchain.evaluation import load_dataset
ds = load_dataset("llm-math")
Some common use cases for evaluation include:
Grading the accuracy of a response against ground truth answers: QAEvalChain
Comparing the output of two models: PairwiseStringEvalChain or LabeledPairwiseStringEvalChain when there is additionally a reference label.
Judging the efficacy of an agent’s tool usage: TrajectoryEvalChain
Checking whether an output complies with a set of criteria: CriteriaEvalChain or LabeledCriteriaEvalChain when there is additionally a reference label.
Computing semantic difference between a prediction and reference: EmbeddingDistanceEvalChain or between two predictions: PairwiseEmbeddingDistanceEvalChain
Measuring the string distance between a prediction and reference StringDistanceEvalChain or between two predictions PairwiseStringDistanceEvalChain
Low-level API
These evaluators implement one of the following interfaces:
StringEvaluator: Evaluate a prediction string against a reference label and/or input context.
PairwiseStringEvaluator: Evaluate two prediction strings against each other. Useful for scoring preferences, measuring similarity between two chain or llm agents, or comparing outputs on similar inputs.
AgentTrajectoryEvaluator Evaluate the full sequence of actions taken by an agent.
These interfaces enable easier composability and usage within a higher level evaluation framework.
Classes¶
evaluation.agents.trajectory_eval_chain.TrajectoryEval
A named tuple containing the score and reasoning for a trajectory.
evaluation.agents.trajectory_eval_chain.TrajectoryEvalChain
A chain for evaluating ReAct style agents.
evaluation.agents.trajectory_eval_chain.TrajectoryOutputParser
Trajectory output parser.
evaluation.comparison.eval_chain.LabeledPairwiseStringEvalChain
A chain for comparing two outputs, such as the outputs
evaluation.comparison.eval_chain.PairwiseStringEvalChain | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-45 | evaluation.comparison.eval_chain.PairwiseStringEvalChain
A chain for comparing two outputs, such as the outputs
evaluation.comparison.eval_chain.PairwiseStringResultOutputParser
A parser for the output of the PairwiseStringEvalChain.
evaluation.criteria.eval_chain.Criteria(value)
A Criteria to evaluate.
evaluation.criteria.eval_chain.CriteriaEvalChain
LLM Chain for evaluating runs against criteria.
evaluation.criteria.eval_chain.CriteriaResultOutputParser
A parser for the output of the CriteriaEvalChain.
evaluation.criteria.eval_chain.LabeledCriteriaEvalChain
Criteria evaluation chain that requires references.
evaluation.embedding_distance.base.EmbeddingDistance(value)
Embedding Distance Metric.
evaluation.embedding_distance.base.EmbeddingDistanceEvalChain
Use embedding distances to score semantic difference between a prediction and reference.
evaluation.embedding_distance.base.PairwiseEmbeddingDistanceEvalChain
Use embedding distances to score semantic difference between two predictions.
evaluation.exact_match.base.ExactMatchStringEvaluator(*)
Compute an exact match between the prediction and the reference.
evaluation.parsing.base.JsonEqualityEvaluator([...])
Evaluates whether the prediction is equal to the reference after
evaluation.parsing.base.JsonValidityEvaluator(...)
Evaluates whether the prediction is valid JSON.
evaluation.qa.eval_chain.ContextQAEvalChain
LLM Chain for evaluating QA w/o GT based on context
evaluation.qa.eval_chain.CotQAEvalChain
LLM Chain for evaluating QA using chain of thought reasoning.
evaluation.qa.eval_chain.QAEvalChain
LLM Chain for evaluating question answering.
evaluation.qa.generate_chain.QAGenerateChain
LLM Chain for generating examples for question answering.
evaluation.regex_match.base.RegexMatchStringEvaluator(*)
Compute a regex match between the prediction and the reference.
evaluation.schema.AgentTrajectoryEvaluator()
Interface for evaluating agent trajectories.
evaluation.schema.EvaluatorType(value[, ...])
The types of the evaluators. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-46 | evaluation.schema.EvaluatorType(value[, ...])
The types of the evaluators.
evaluation.schema.LLMEvalChain
A base class for evaluators that use an LLM.
evaluation.schema.PairwiseStringEvaluator()
Compare the output of two models (or two outputs of the same model).
evaluation.schema.StringEvaluator()
Grade, tag, or otherwise evaluate predictions relative to their inputs and/or reference labels.
evaluation.string_distance.base.PairwiseStringDistanceEvalChain
Compute string edit distances between two predictions.
evaluation.string_distance.base.StringDistance(value)
Distance metric to use.
evaluation.string_distance.base.StringDistanceEvalChain
Compute string distances between the prediction and the reference.
Functions¶
evaluation.comparison.eval_chain.resolve_pairwise_criteria(...)
Resolve the criteria for the pairwise evaluator.
evaluation.criteria.eval_chain.resolve_criteria(...)
Resolve the criteria to evaluate.
evaluation.loading.load_dataset(uri)
Load a dataset from the LangChainDatasets on HuggingFace.
evaluation.loading.load_evaluator(evaluator, *)
Load the requested evaluation chain specified by a string.
evaluation.loading.load_evaluators(evaluators, *)
Load evaluators specified by a list of evaluator types.
langchain.graphs¶
Graphs provide a natural language interface to graph databases.
Classes¶
graphs.arangodb_graph.ArangoGraph(db)
ArangoDB wrapper for graph operations.
graphs.falkordb_graph.FalkorDBGraph(database)
FalkorDB wrapper for graph operations.
graphs.graph_document.GraphDocument
Represents a graph document consisting of nodes and relationships.
graphs.graph_document.Node
Represents a node in a graph with associated properties.
graphs.graph_document.Relationship
Represents a directed relationship between two nodes in a graph.
graphs.hugegraph.HugeGraph([username, ...])
HugeGraph wrapper for graph operations | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-47 | HugeGraph wrapper for graph operations
graphs.kuzu_graph.KuzuGraph(db[, database])
Kùzu wrapper for graph operations.
graphs.memgraph_graph.MemgraphGraph(url, ...)
Memgraph wrapper for graph operations.
graphs.nebula_graph.NebulaGraph(space[, ...])
NebulaGraph wrapper for graph operations NebulaGraph inherits methods from Neo4jGraph to bring ease to the user space.
graphs.neo4j_graph.Neo4jGraph(url, username, ...)
Neo4j wrapper for graph operations.
graphs.neptune_graph.NeptuneGraph(host[, ...])
Neptune wrapper for graph operations.
graphs.neptune_graph.NeptuneQueryException(...)
A class to handle queries that fail to execute
graphs.networkx_graph.KnowledgeTriple(...)
A triple in the graph.
graphs.networkx_graph.NetworkxEntityGraph([graph])
Networkx wrapper for entity graph operations.
graphs.rdf_graph.RdfGraph([source_file, ...])
RDFlib wrapper for graph operations.
Functions¶
graphs.arangodb_graph.get_arangodb_client([...])
Get the Arango DB client from credentials.
graphs.networkx_graph.get_entities(entity_str)
Extract entities from entity string.
graphs.networkx_graph.parse_triples(...)
Parse knowledge triples from the knowledge string.
langchain.hub¶
Push and pull to the LangChain Hub.
Functions¶
hub.pull(owner_repo_commit, *[, api_url, ...])
Pulls an object from the hub and returns it as a LangChain object.
hub.push(repo_full_name, object, *[, ...])
Pushes an object to the hub and returns the URL it can be viewed at in a browser.
langchain.indexes¶
Code to support various indexing workflows.
Provides code to:
Create knowledge graphs from data. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-48 | Code to support various indexing workflows.
Provides code to:
Create knowledge graphs from data.
Support indexing workflows from LangChain data loaders to vectorstores.
For indexing workflows, this code is used to avoid writing duplicated content
into the vectostore and to avoid over-writing content if it’s unchanged.
Importantly, this keeps on working even if the content being written is derived
via a set of transformations from some source content (e.g., indexing children
documents that were derived from parent documents by chunking.)
Classes¶
indexes.base.RecordManager(namespace)
An abstract base class representing the interface for a record manager.
indexes.graph.GraphIndexCreator
Functionality to create graph index.
indexes.vectorstore.VectorStoreIndexWrapper
Wrapper around a vectorstore for easy access.
indexes.vectorstore.VectorstoreIndexCreator
Logic for creating indexes.
Functions¶
langchain.llms¶
LLM classes provide
access to the large language model (LLM) APIs and services.
Class hierarchy:
BaseLanguageModel --> BaseLLM --> LLM --> <name> # Examples: AI21, HuggingFaceHub, OpenAI
Main helpers:
LLMResult, PromptValue,
CallbackManagerForLLMRun, AsyncCallbackManagerForLLMRun,
CallbackManager, AsyncCallbackManager,
AIMessage, BaseMessage
Classes¶
llms.ai21.AI21
AI21 large language models.
llms.ai21.AI21PenaltyData
Parameters for AI21 penalty data.
llms.aleph_alpha.AlephAlpha
Aleph Alpha large language models.
llms.amazon_api_gateway.AmazonAPIGateway
Amazon API Gateway to access LLM models hosted on AWS.
llms.amazon_api_gateway.ContentHandlerAmazonAPIGateway()
Adapter to prepare the inputs from Langchain to a format that LLM model expects.
llms.anthropic.Anthropic | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-49 | llms.anthropic.Anthropic
Anthropic large language models.
llms.anyscale.Anyscale
Anyscale Service models.
llms.aviary.Aviary
Aviary hosted models.
llms.aviary.AviaryBackend(backend_url, bearer)
Aviary backend.
llms.azureml_endpoint.AzureMLEndpointClient(...)
AzureML Managed Endpoint client.
llms.azureml_endpoint.AzureMLOnlineEndpoint
Azure ML Online Endpoint models.
llms.azureml_endpoint.ContentFormatterBase()
Transform request and response of AzureML endpoint to match with required schema.
llms.azureml_endpoint.DollyContentFormatter()
Content handler for the Dolly-v2-12b model
llms.azureml_endpoint.GPT2ContentFormatter()
Content handler for GPT2
llms.azureml_endpoint.HFContentFormatter()
Content handler for LLMs from the HuggingFace catalog.
llms.azureml_endpoint.LlamaContentFormatter()
Content formatter for LLaMa
llms.azureml_endpoint.OSSContentFormatter()
Deprecated: Kept for backwards compatibility
llms.baidu_qianfan_endpoint.QianfanLLMEndpoint
Baidu Qianfan hosted open source or customized models.
llms.bananadev.Banana
Banana large language models.
llms.base.BaseLLM
Base LLM abstract interface.
llms.base.LLM
Base LLM abstract class.
llms.baseten.Baseten
Baseten models.
llms.beam.Beam
Beam API for gpt2 large language model.
llms.bedrock.Bedrock
Bedrock models.
llms.bedrock.BedrockBase
Create a new model by parsing and validating input data from keyword arguments.
llms.bedrock.LLMInputOutputAdapter() | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-50 | llms.bedrock.LLMInputOutputAdapter()
Adapter class to prepare the inputs from Langchain to a format that LLM model expects.
llms.bittensor.NIBittensorLLM
NIBittensorLLM is created by Neural Internet (https://neuralinternet.ai/), powered by Bittensor, a decentralized network full of different AI models.
llms.cerebriumai.CerebriumAI
CerebriumAI large language models.
llms.chatglm.ChatGLM
ChatGLM LLM service.
llms.clarifai.Clarifai
Clarifai large language models.
llms.cohere.Cohere
Cohere large language models.
llms.ctransformers.CTransformers
C Transformers LLM models.
llms.ctranslate2.CTranslate2
CTranslate2 language model.
llms.databricks.Databricks
Databricks serving endpoint or a cluster driver proxy app for LLM.
llms.deepinfra.DeepInfra
DeepInfra models.
llms.deepsparse.DeepSparse
Neural Magic DeepSparse LLM interface.
llms.edenai.EdenAI
Wrapper around edenai models.
llms.fake.FakeListLLM
Fake LLM for testing purposes.
llms.fake.FakeStreamingListLLM
Fake streaming list LLM for testing purposes.
llms.fireworks.Fireworks
Fireworks models.
llms.forefrontai.ForefrontAI
ForefrontAI large language models.
llms.google_palm.GooglePalm
Google PaLM models.
llms.gooseai.GooseAI
GooseAI large language models.
llms.gpt4all.GPT4All
GPT4All language models.
llms.gradient_ai.GradientLLM
Gradient.ai LLM Endpoints. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-51 | llms.gradient_ai.GradientLLM
Gradient.ai LLM Endpoints.
llms.huggingface_endpoint.HuggingFaceEndpoint
HuggingFace Endpoint models.
llms.huggingface_hub.HuggingFaceHub
HuggingFaceHub models.
llms.huggingface_pipeline.HuggingFacePipeline
HuggingFace Pipeline API.
llms.huggingface_text_gen_inference.HuggingFaceTextGenInference
HuggingFace text generation API.
llms.human.HumanInputLLM
It returns user input as the response.
llms.javelin_ai_gateway.JavelinAIGateway
Wrapper around completions LLMs in the Javelin AI Gateway.
llms.javelin_ai_gateway.Params
Parameters for the Javelin AI Gateway LLM.
llms.koboldai.KoboldApiLLM
Kobold API language model.
llms.llamacpp.LlamaCpp
llama.cpp model.
llms.manifest.ManifestWrapper
HazyResearch's Manifest library.
llms.minimax.Minimax
Wrapper around Minimax large language models.
llms.minimax.MinimaxCommon
Create a new model by parsing and validating input data from keyword arguments.
llms.mlflow_ai_gateway.MlflowAIGateway
Wrapper around completions LLMs in the MLflow AI Gateway.
llms.mlflow_ai_gateway.Params
Parameters for the MLflow AI Gateway LLM.
llms.modal.Modal
Modal large language models.
llms.mosaicml.MosaicML
MosaicML LLM service.
llms.nlpcloud.NLPCloud
NLPCloud large language models.
llms.octoai_endpoint.OctoAIEndpoint
OctoAI LLM Endpoints.
llms.ollama.Ollama
Ollama locally runs large language models. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-52 | llms.ollama.Ollama
Ollama locally runs large language models.
llms.opaqueprompts.OpaquePrompts
An LLM wrapper that uses OpaquePrompts to sanitize prompts.
llms.openai.AzureOpenAI
Azure-specific OpenAI large language models.
llms.openai.BaseOpenAI
Base OpenAI large language model class.
llms.openai.OpenAI
OpenAI large language models.
llms.openai.OpenAIChat
OpenAI Chat large language models.
llms.openllm.IdentifyingParams
Parameters for identifying a model as a typed dict.
llms.openllm.OpenLLM
OpenLLM, supporting both in-process model instance and remote OpenLLM servers.
llms.openlm.OpenLM
OpenLM models.
llms.petals.Petals
Petals Bloom models.
llms.pipelineai.PipelineAI
PipelineAI large language models.
llms.predibase.Predibase
Use your Predibase models with Langchain.
llms.predictionguard.PredictionGuard
Prediction Guard large language models.
llms.promptlayer_openai.PromptLayerOpenAI
PromptLayer OpenAI large language models.
llms.promptlayer_openai.PromptLayerOpenAIChat
Wrapper around OpenAI large language models.
llms.replicate.Replicate
Replicate models.
llms.rwkv.RWKV
RWKV language models.
llms.sagemaker_endpoint.ContentHandlerBase()
A handler class to transform input from LLM to a format that SageMaker endpoint expects.
llms.sagemaker_endpoint.LLMContentHandler()
Content handler for LLM class.
llms.sagemaker_endpoint.SagemakerEndpoint
Sagemaker Inference Endpoint models.
llms.self_hosted.SelfHostedPipeline
Model inference on self-hosted remote hardware. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-53 | Model inference on self-hosted remote hardware.
llms.self_hosted_hugging_face.SelfHostedHuggingFaceLLM
HuggingFace Pipeline API to run on self-hosted remote hardware.
llms.stochasticai.StochasticAI
StochasticAI large language models.
llms.symblai_nebula.Nebula
Nebula Service models.
llms.textgen.TextGen
text-generation-webui models.
llms.titan_takeoff.TitanTakeoff
Create a new model by parsing and validating input data from keyword arguments.
llms.tongyi.Tongyi
Tongyi Qwen large language models.
llms.vertexai.VertexAI
Google Vertex AI large language models.
llms.vertexai.VertexAIModelGarden
Large language models served from Vertex AI Model Garden.
llms.vllm.VLLM
VLLM language model.
llms.vllm.VLLMOpenAI
vLLM OpenAI-compatible API client
llms.writer.Writer
Writer large language models.
llms.xinference.Xinference
Wrapper for accessing Xinference's large-scale model inference service.
Functions¶
llms.aviary.get_completions(model, prompt[, ...])
Get completions from Aviary models.
llms.aviary.get_models()
List available models
llms.base.create_base_retry_decorator(...[, ...])
Create a retry decorator for a given LLM and provided list of error types.
llms.base.get_prompts(params, prompts)
Get prompts that are already cached.
llms.base.update_cache(existing_prompts, ...)
Update the cache and get the LLM output.
llms.cohere.acompletion_with_retry(llm, **kwargs)
Use tenacity to retry the completion call. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-54 | Use tenacity to retry the completion call.
llms.cohere.completion_with_retry(llm, **kwargs)
Use tenacity to retry the completion call.
llms.databricks.get_default_api_token()
Gets the default Databricks personal access token.
llms.databricks.get_default_host()
Gets the default Databricks workspace hostname.
llms.databricks.get_repl_context()
Gets the notebook REPL context if running inside a Databricks notebook.
llms.fireworks.acompletion_with_retry(llm, *)
Use tenacity to retry the completion call.
llms.fireworks.acompletion_with_retry_streaming(llm, *)
Use tenacity to retry the completion call for streaming.
llms.fireworks.completion_with_retry(llm, *)
Use tenacity to retry the completion call.
llms.google_palm.generate_with_retry(llm, ...)
Use tenacity to retry the completion call.
llms.koboldai.clean_url(url)
Remove trailing slash and /api from url if present.
llms.loading.load_llm(file)
Load LLM from file.
llms.loading.load_llm_from_config(config)
Load LLM from Config Dict.
llms.openai.acompletion_with_retry(llm[, ...])
Use tenacity to retry the async completion call.
llms.openai.completion_with_retry(llm[, ...])
Use tenacity to retry the completion call.
llms.openai.update_token_usage(keys, ...)
Update token usage.
llms.symblai_nebula.completion_with_retry(...)
Use tenacity to retry the completion call.
llms.symblai_nebula.make_request(self, ...)
Generate text from the model.
llms.tongyi.generate_with_retry(llm, **kwargs) | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-55 | llms.tongyi.generate_with_retry(llm, **kwargs)
Use tenacity to retry the completion call.
llms.tongyi.stream_generate_with_retry(llm, ...)
Use tenacity to retry the completion call.
llms.utils.enforce_stop_tokens(text, stop)
Cut off the text as soon as any stop words occur.
llms.vertexai.acompletion_with_retry(llm, *args)
Use tenacity to retry the completion call.
llms.vertexai.completion_with_retry(llm, *args)
Use tenacity to retry the completion call.
llms.vertexai.is_codey_model(model_name)
Returns True if the model name is a Codey model.
llms.vertexai.stream_completion_with_retry(...)
Use tenacity to retry the completion call.
langchain.load¶
Serialization and deserialization.
Classes¶
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.
Functions¶
load.dump.default(obj)
Return a default value for a Serializable object or a SerializedNotImplemented object.
load.dump.dumpd(obj)
Return a json dict representation of an object.
load.dump.dumps(obj, *[, pretty])
Return a json string representation of an object.
load.load.load(obj, *[, secrets_map, ...])
Revive a LangChain class from a JSON object.
load.load.loads(text, *[, secrets_map, ...])
Revive a LangChain class from a JSON string. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-56 | Revive a LangChain class from a JSON string.
load.serializable.to_json_not_implemented(obj)
Serialize a "not implemented" object.
langchain.memory¶
Memory maintains Chain state, incorporating context from past runs.
Class hierarchy for Memory:
BaseMemory --> BaseChatMemory --> <name>Memory # Examples: ZepMemory, MotorheadMemory
Main helpers:
BaseChatMessageHistory
Chat Message History stores the chat message history in different stores.
Class hierarchy for ChatMessageHistory:
BaseChatMessageHistory --> <name>ChatMessageHistory # Example: ZepChatMessageHistory
Main helpers:
AIMessage, BaseMessage, HumanMessage
Classes¶
memory.buffer.ConversationBufferMemory
Buffer for storing conversation memory.
memory.buffer.ConversationStringBufferMemory
Buffer for storing conversation memory.
memory.buffer_window.ConversationBufferWindowMemory
Buffer for storing conversation memory inside a limited size window.
memory.chat_memory.BaseChatMemory
Abstract base class for chat memory.
memory.chat_message_histories.cassandra.CassandraChatMessageHistory(...)
Chat message history that stores history in Cassandra.
memory.chat_message_histories.cosmos_db.CosmosDBChatMessageHistory(...)
Chat message history backed by Azure CosmosDB.
memory.chat_message_histories.dynamodb.DynamoDBChatMessageHistory(...)
Chat message history that stores history in AWS DynamoDB.
memory.chat_message_histories.file.FileChatMessageHistory(...)
Chat message history that stores history in a local file.
memory.chat_message_histories.firestore.FirestoreChatMessageHistory(...)
Chat message history backed by Google Firestore.
memory.chat_message_histories.in_memory.ChatMessageHistory
In memory implementation of chat message history.
memory.chat_message_histories.momento.MomentoChatMessageHistory(...)
Chat message history cache that uses Momento as a backend.
memory.chat_message_histories.mongodb.MongoDBChatMessageHistory(...) | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-57 | memory.chat_message_histories.mongodb.MongoDBChatMessageHistory(...)
Chat message history that stores history in MongoDB.
memory.chat_message_histories.postgres.PostgresChatMessageHistory(...)
Chat message history stored in a Postgres database.
memory.chat_message_histories.redis.RedisChatMessageHistory(...)
Chat message history stored in a Redis database.
memory.chat_message_histories.rocksetdb.RocksetChatMessageHistory(...)
Uses Rockset to store chat messages.
memory.chat_message_histories.sql.BaseMessageConverter()
The class responsible for converting BaseMessage to your SQLAlchemy model.
memory.chat_message_histories.sql.DefaultMessageConverter(...)
The default message converter for SQLChatMessageHistory.
memory.chat_message_histories.sql.SQLChatMessageHistory(...)
Chat message history stored in an SQL database.
memory.chat_message_histories.streamlit.StreamlitChatMessageHistory([key])
Chat message history that stores messages in Streamlit session state.
memory.chat_message_histories.xata.XataChatMessageHistory(...)
Chat message history stored in a Xata database.
memory.chat_message_histories.zep.ZepChatMessageHistory(...)
Chat message history that uses Zep as a backend.
memory.combined.CombinedMemory
Combining multiple memories' data together.
memory.entity.BaseEntityStore
Abstract base class for Entity store.
memory.entity.ConversationEntityMemory
Entity extractor & summarizer memory.
memory.entity.InMemoryEntityStore
In-memory Entity store.
memory.entity.RedisEntityStore
Redis-backed Entity store.
memory.entity.SQLiteEntityStore
SQLite-backed Entity store
memory.kg.ConversationKGMemory
Knowledge graph conversation memory.
memory.motorhead_memory.MotorheadMemory
Chat message memory backed by Motorhead service.
memory.readonly.ReadOnlySharedMemory
A memory wrapper that is read-only and cannot be changed.
memory.simple.SimpleMemory | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-58 | A memory wrapper that is read-only and cannot be changed.
memory.simple.SimpleMemory
Simple memory for storing context or other information that shouldn't ever change between prompts.
memory.summary.ConversationSummaryMemory
Conversation summarizer to chat memory.
memory.summary.SummarizerMixin
Mixin for summarizer.
memory.summary_buffer.ConversationSummaryBufferMemory
Buffer with summarizer for storing conversation memory.
memory.token_buffer.ConversationTokenBufferMemory
Conversation chat memory with token limit.
memory.vectorstore.VectorStoreRetrieverMemory
VectorStoreRetriever-backed memory.
memory.zep_memory.ZepMemory
Persist your chain history to the Zep Memory Server.
Functions¶
memory.chat_message_histories.sql.create_message_model(...)
Create a message model for a given table name.
memory.utils.get_prompt_input_key(inputs, ...)
Get the prompt input key.
langchain.model_laboratory¶
Experiment with different models.
Classes¶
model_laboratory.ModelLaboratory(chains[, names])
Experiment with different models.
langchain.output_parsers¶
OutputParser classes parse the output of an LLM call.
Class hierarchy:
BaseLLMOutputParser --> BaseOutputParser --> <name>OutputParser # ListOutputParser, PydanticOutputParser
Main helpers:
Serializable, Generation, PromptValue
Classes¶
output_parsers.boolean.BooleanOutputParser
Parse the output of an LLM call to a boolean.
output_parsers.combining.CombiningOutputParser
Combine multiple output parsers into one.
output_parsers.datetime.DatetimeOutputParser
Parse the output of an LLM call to a datetime.
output_parsers.enum.EnumOutputParser
Parse an output that is one of a set of values.
output_parsers.fix.OutputFixingParser
Wraps a parser and tries to fix parsing errors.
output_parsers.json.SimpleJsonOutputParser | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-59 | output_parsers.json.SimpleJsonOutputParser
Parse the output of an LLM call to a JSON object.
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.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.pydantic.PydanticOutputParser
Parse an output using a pydantic model.
output_parsers.rail_parser.GuardrailsOutputParser
Parse the output of an LLM call using Guardrails.
output_parsers.regex.RegexParser
Parse the output of an LLM call using a regex.
output_parsers.regex_dict.RegexDictParser
Parse the output of an LLM call into a Dictionary using a regex.
output_parsers.retry.RetryOutputParser
Wraps a parser and tries to fix parsing errors.
output_parsers.retry.RetryWithErrorOutputParser
Wraps a parser and tries to fix parsing errors.
output_parsers.structured.ResponseSchema
A schema for a response from a structured output parser.
output_parsers.structured.StructuredOutputParser
Parse the output of an LLM call to a structured output.
output_parsers.xml.XMLOutputParser | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-60 | output_parsers.xml.XMLOutputParser
Parse an output using xml format.
Functions¶
output_parsers.json.parse_and_check_json_markdown(...)
Parse a JSON string from a Markdown string and check that it contains the expected keys.
output_parsers.json.parse_json_markdown(...)
Parse a JSON string from a Markdown string.
output_parsers.json.parse_partial_json(s, *)
output_parsers.loading.load_output_parser(config)
Load an output parser.
langchain.prompts¶
Prompt is the input to the model.
Prompt is often constructed
from multiple components. Prompt classes and functions make constructing
and working with prompts easy.
Class hierarchy:
BasePromptTemplate --> PipelinePromptTemplate
StringPromptTemplate --> PromptTemplate
FewShotPromptTemplate
FewShotPromptWithTemplates
BaseChatPromptTemplate --> AutoGPTPrompt
ChatPromptTemplate --> AgentScratchPadChatPromptTemplate
BaseMessagePromptTemplate --> MessagesPlaceholder
BaseStringMessagePromptTemplate --> ChatMessagePromptTemplate
HumanMessagePromptTemplate
AIMessagePromptTemplate
SystemMessagePromptTemplate
PromptValue --> StringPromptValue
ChatPromptValue
Classes¶
prompts.base.StringPromptTemplate
String prompt that exposes the format method, returning a prompt.
prompts.base.StringPromptValue
String prompt value.
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
A prompt template for chat models.
prompts.chat.ChatPromptValue
Chat prompt value.
prompts.chat.ChatPromptValueConcrete | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-61 | prompts.chat.ChatPromptValue
Chat prompt value.
prompts.chat.ChatPromptValueConcrete
Chat prompt value which explicitly lists out the message types it accepts.
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.example_selector.base.BaseExampleSelector()
Interface for selecting examples to include in prompts.
prompts.example_selector.length_based.LengthBasedExampleSelector
Select examples based on length.
prompts.example_selector.ngram_overlap.NGramOverlapExampleSelector
Select and order examples based on ngram overlap score (sentence_bleu score).
prompts.example_selector.semantic_similarity.MaxMarginalRelevanceExampleSelector
ExampleSelector that selects examples based on Max Marginal Relevance.
prompts.example_selector.semantic_similarity.SemanticSimilarityExampleSelector
Example selector that selects examples based on SemanticSimilarity.
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.pipeline.PipelinePromptTemplate
A prompt template for composing multiple prompt templates together.
prompts.prompt.Prompt
alias of PromptTemplate
prompts.prompt.PromptTemplate
A prompt template for a language model.
Functions¶
prompts.base.check_valid_template(template, ...)
Check that template string is valid.
prompts.base.jinja2_formatter(template, **kwargs)
Format a template using jinja2.
prompts.base.validate_jinja2(template, ...)
Validate that the input variables are valid for the template.
prompts.example_selector.ngram_overlap.ngram_overlap_score(...) | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-62 | prompts.example_selector.ngram_overlap.ngram_overlap_score(...)
Compute ngram overlap score of source and example as sentence_bleu score.
prompts.example_selector.semantic_similarity.sorted_values(values)
Return a list of values in dict sorted by key.
prompts.loading.load_prompt(path)
Unified method for loading a prompt from LangChainHub or local fs.
prompts.loading.load_prompt_from_config(config)
Load prompt from Config Dict.
langchain.retrievers¶
Retriever class returns Documents given a text query.
It is more general than a vector store. A retriever does not need to be able to
store documents, only to return (or retrieve) it. Vector stores can be used as
the backbone of a retriever, but there are other types of retrievers as well.
Class hierarchy:
BaseRetriever --> <name>Retriever # Examples: ArxivRetriever, MergerRetriever
Main helpers:
Document, Serializable, Callbacks,
CallbackManagerForRetrieverRun, AsyncCallbackManagerForRetrieverRun
Classes¶
retrievers.arxiv.ArxivRetriever
Arxiv retriever.
retrievers.azure_cognitive_search.AzureCognitiveSearchRetriever
Azure Cognitive Search service retriever.
retrievers.bm25.BM25Retriever
BM25 retriever without Elasticsearch.
retrievers.chaindesk.ChaindeskRetriever
Chaindesk API retriever.
retrievers.chatgpt_plugin_retriever.ChatGPTPluginRetriever
ChatGPT plugin retriever.
retrievers.contextual_compression.ContextualCompressionRetriever
Retriever that wraps a base retriever and compresses the results.
retrievers.databerry.DataberryRetriever
Databerry API retriever.
retrievers.docarray.DocArrayRetriever | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-63 | Databerry API retriever.
retrievers.docarray.DocArrayRetriever
DocArray Document Indices retriever.
retrievers.docarray.SearchType(value[, ...])
Enumerator of the types of search to perform.
retrievers.document_compressors.base.BaseDocumentCompressor
Base class for document compressors.
retrievers.document_compressors.base.DocumentCompressorPipeline
Document compressor that uses a pipeline of Transformers.
retrievers.document_compressors.chain_extract.LLMChainExtractor
Document compressor that uses an LLM chain to extract the relevant parts of documents.
retrievers.document_compressors.chain_extract.NoOutputParser
Parse outputs that could return a null string of some sort.
retrievers.document_compressors.chain_filter.LLMChainFilter
Filter that drops documents that aren't relevant to the query.
retrievers.document_compressors.cohere_rerank.CohereRerank
Document compressor that uses Cohere Rerank API.
retrievers.document_compressors.embeddings_filter.EmbeddingsFilter
Document compressor that uses embeddings to drop documents unrelated to the query.
retrievers.elastic_search_bm25.ElasticSearchBM25Retriever
Elasticsearch retriever that uses BM25.
retrievers.ensemble.EnsembleRetriever
Retriever that ensembles the multiple retrievers.
retrievers.google_cloud_enterprise_search.GoogleCloudEnterpriseSearchRetriever
Google Cloud Enterprise Search API retriever.
retrievers.kay.KayAiRetriever
Retriever for Kay.ai datasets.
retrievers.kendra.AdditionalResultAttribute
Additional result attribute.
retrievers.kendra.AdditionalResultAttributeValue
Value of an additional result attribute.
retrievers.kendra.AmazonKendraRetriever
Amazon Kendra Index retriever.
retrievers.kendra.DocumentAttribute
Document attribute. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-64 | Amazon Kendra Index retriever.
retrievers.kendra.DocumentAttribute
Document attribute.
retrievers.kendra.DocumentAttributeValue
Value of a document attribute.
retrievers.kendra.Highlight
Information that highlights the key words in the excerpt.
retrievers.kendra.QueryResult
Amazon Kendra Query API search result.
retrievers.kendra.QueryResultItem
Query API result item.
retrievers.kendra.ResultItem
Base class of a result item.
retrievers.kendra.RetrieveResult
Amazon Kendra Retrieve API search result.
retrievers.kendra.RetrieveResultItem
Retrieve API result item.
retrievers.kendra.TextWithHighLights
Text with highlights.
retrievers.knn.KNNRetriever
KNN retriever.
retrievers.llama_index.LlamaIndexGraphRetriever
LlamaIndex graph data structure retriever.
retrievers.llama_index.LlamaIndexRetriever
LlamaIndex retriever.
retrievers.merger_retriever.MergerRetriever
Retriever that merges the results of multiple retrievers.
retrievers.metal.MetalRetriever
Metal API retriever.
retrievers.milvus.MilvusRetriever
Milvus API retriever.
retrievers.multi_query.LineList
List of lines.
retrievers.multi_query.LineListOutputParser
Output parser for a list of lines.
retrievers.multi_query.MultiQueryRetriever
Given a query, use an LLM to write a set of queries.
retrievers.multi_vector.MultiVectorRetriever
Retrieve from a set of multiple embeddings for the same document.
retrievers.parent_document_retriever.ParentDocumentRetriever
Retrieve small chunks then retrieve their parent documents. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-65 | Retrieve small chunks then retrieve their parent documents.
retrievers.pinecone_hybrid_search.PineconeHybridSearchRetriever
Pinecone Hybrid Search retriever.
retrievers.pubmed.PubMedRetriever
PubMed API retriever.
retrievers.re_phraser.RePhraseQueryRetriever
Given a query, use an LLM to re-phrase it.
retrievers.remote_retriever.RemoteLangChainRetriever
LangChain API retriever.
retrievers.self_query.base.SelfQueryRetriever
Retriever that uses a vector store and an LLM to generate the vector store queries.
retrievers.self_query.chroma.ChromaTranslator()
Translate Chroma internal query language elements to valid filters.
retrievers.self_query.dashvector.DashvectorTranslator()
Logic for converting internal query language elements to valid filters.
retrievers.self_query.deeplake.DeepLakeTranslator()
Translate DeepLake internal query language elements to valid filters.
retrievers.self_query.elasticsearch.ElasticsearchTranslator()
Translate Elasticsearch internal query language elements to valid filters.
retrievers.self_query.milvus.MilvusTranslator()
Translate Milvus internal query language elements to valid filters.
retrievers.self_query.myscale.MyScaleTranslator([...])
Translate MyScale internal query language elements to valid filters.
retrievers.self_query.opensearch.OpenSearchTranslator()
Translate OpenSearch internal query domain-specific language elements to valid filters.
retrievers.self_query.pinecone.PineconeTranslator()
Translate Pinecone internal query language elements to valid filters.
retrievers.self_query.qdrant.QdrantTranslator(...)
Translate Qdrant internal query language elements to valid filters.
retrievers.self_query.redis.RedisTranslator(schema)
Translate
retrievers.self_query.supabase.SupabaseVectorTranslator() | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-66 | Translate
retrievers.self_query.supabase.SupabaseVectorTranslator()
Translate Langchain filters to Supabase PostgREST filters.
retrievers.self_query.timescalevector.TimescaleVectorTranslator()
Translate the internal query language elements to valid filters.
retrievers.self_query.vectara.VectaraTranslator()
Translate Vectara internal query language elements to valid filters.
retrievers.self_query.weaviate.WeaviateTranslator()
Translate Weaviate internal query language elements to valid filters.
retrievers.svm.SVMRetriever
SVM retriever.
retrievers.tfidf.TFIDFRetriever
TF-IDF retriever.
retrievers.time_weighted_retriever.TimeWeightedVectorStoreRetriever
Retriever that combines embedding similarity with recency in retrieving values.
retrievers.vespa_retriever.VespaRetriever
Vespa retriever.
retrievers.weaviate_hybrid_search.WeaviateHybridSearchRetriever
Weaviate hybrid search retriever.
retrievers.web_research.LineList
List of questions.
retrievers.web_research.QuestionListOutputParser
Output parser for a list of numbered questions.
retrievers.web_research.SearchQueries
Search queries to research for the user's goal.
retrievers.web_research.WebResearchRetriever
Google Search API retriever.
retrievers.wikipedia.WikipediaRetriever
Wikipedia API retriever.
retrievers.zep.ZepRetriever
Zep long-term memory store retriever.
retrievers.zilliz.ZillizRetriever
Zilliz API retriever.
Functions¶
retrievers.bm25.default_preprocessing_func(text)
retrievers.document_compressors.chain_extract.default_get_input(...)
Return the compression chain input. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-67 | retrievers.document_compressors.chain_extract.default_get_input(...)
Return the compression chain input.
retrievers.document_compressors.chain_filter.default_get_input(...)
Return the compression chain input.
retrievers.kendra.clean_excerpt(excerpt)
Clean an excerpt from Kendra.
retrievers.kendra.combined_text(item)
Combine a ResultItem title and excerpt into a single string.
retrievers.knn.create_index(contexts, embeddings)
Create an index of embeddings for a list of contexts.
retrievers.milvus.MilvusRetreiver(*args, ...)
Deprecated MilvusRetreiver.
retrievers.pinecone_hybrid_search.create_index(...)
Create an index from a list of contexts.
retrievers.pinecone_hybrid_search.hash_text(text)
Hash a text using SHA256.
retrievers.self_query.deeplake.can_cast_to_float(string)
Check if a string can be cast to a float.
retrievers.self_query.milvus.process_value(value)
retrievers.self_query.vectara.process_value(value)
retrievers.svm.create_index(contexts, embeddings)
Create an index of embeddings for a list of contexts.
retrievers.zilliz.ZillizRetreiver(*args, ...)
Deprecated ZillizRetreiver.
langchain.runnables¶
Classes¶
runnables.openai_functions.OpenAIFunction
A function description for ChatOpenAI
runnables.openai_functions.OpenAIFunctionsRouter
A runnable that routes to the selected function.
langchain.schema¶
Schemas are the LangChain Base Classes and Interfaces.
Classes¶
schema.agent.AgentAction
A full description of an action for an ActionAgent to execute.
schema.agent.AgentActionMessageLog | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-68 | schema.agent.AgentActionMessageLog
Create a new model by parsing and validating input data from keyword arguments.
schema.agent.AgentFinish
The final return value of an ActionAgent.
schema.cache.BaseCache()
Base interface for cache.
schema.chat.ChatSession
Chat Session represents a single conversation, channel, or other group of messages.
schema.chat_history.BaseChatMessageHistory()
Abstract base class for storing chat message history.
schema.document.BaseDocumentTransformer()
Abstract base class for document transformation systems.
schema.document.Document
Class for storing a piece of text and associated metadata.
schema.embeddings.Embeddings()
Interface for embedding models.
schema.exceptions.LangChainException
General LangChain exception.
schema.language_model.BaseLanguageModel
Abstract base class for interfacing with language models.
schema.memory.BaseMemory
Abstract base class for memory in Chains.
schema.messages.AIMessage
A Message from an AI.
schema.messages.AIMessageChunk
A Message chunk from an AI.
schema.messages.BaseMessage
The base abstract Message class.
schema.messages.BaseMessageChunk
A Message chunk, which can be concatenated with other Message chunks.
schema.messages.ChatMessage
A Message that can be assigned an arbitrary speaker (i.e.
schema.messages.ChatMessageChunk
A Chat Message chunk.
schema.messages.FunctionMessage
A Message for passing the result of executing a function back to a model.
schema.messages.FunctionMessageChunk
A Function Message chunk.
schema.messages.HumanMessage
A Message from a human.
schema.messages.HumanMessageChunk
A Human Message chunk.
schema.messages.SystemMessage
A Message for priming AI behavior, usually passed in as the first of a sequence of input messages.
schema.messages.SystemMessageChunk
A System Message chunk.
schema.output.ChatGeneration
A single chat generation output.
schema.output.ChatGenerationChunk
A ChatGeneration chunk, which can be concatenated with other | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-69 | schema.output.ChatGenerationChunk
A ChatGeneration chunk, which can be concatenated with other
schema.output.ChatResult
Class that contains all results for a single chat model call.
schema.output.Generation
A single text generation output.
schema.output.GenerationChunk
A Generation chunk, which can be concatenated with other Generation chunks.
schema.output.LLMResult
Class that contains all results for a batched LLM call.
schema.output.RunInfo
Class that contains metadata for a single execution of a Chain or model.
schema.output_parser.BaseCumulativeTransformOutputParser
Base class for an output parser that can handle streaming input.
schema.output_parser.BaseGenerationOutputParser
Base class to parse the output of an LLM call.
schema.output_parser.BaseLLMOutputParser
Abstract base class for parsing the outputs of a model.
schema.output_parser.BaseOutputParser
Base class to parse the output of an LLM call.
schema.output_parser.BaseTransformOutputParser
Base class for an output parser that can handle streaming input.
schema.output_parser.NoOpOutputParser
alias of StrOutputParser
schema.output_parser.OutputParserException(error)
Exception that output parsers should raise to signify a parsing error.
schema.output_parser.StrOutputParser
OutputParser that parses LLMResult into the top likely string.
schema.prompt.PromptValue
Base abstract class for inputs to any language model.
schema.prompt_template.BasePromptTemplate
Base class for all prompt templates, returning a prompt.
schema.retriever.BaseRetriever
Abstract base class for a Document retrieval system.
schema.runnable.base.Runnable()
A Runnable is a unit of work that can be invoked, batched, streamed, or transformed.
schema.runnable.base.RunnableBinding
A runnable that delegates calls to another runnable with a set of kwargs.
schema.runnable.base.RunnableBranch
A Runnable that selects which branch to run based on a condition. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-70 | A Runnable that selects which branch to run based on a condition.
schema.runnable.base.RunnableEach
A runnable that delegates calls to another runnable with each element of the input sequence.
schema.runnable.base.RunnableGenerator(transform)
A runnable that runs a generator function.
schema.runnable.base.RunnableLambda(func[, ...])
A runnable that runs a callable.
schema.runnable.base.RunnableMap
A runnable that runs a mapping of runnables in parallel, and returns a mapping of their outputs.
schema.runnable.base.RunnableSequence
A sequence of runnables, where the output of each is the input of the next.
schema.runnable.base.RunnableWithFallbacks
A Runnable that can fallback to other Runnables if it fails.
schema.runnable.config.RunnableConfig
Configuration for a Runnable.
schema.runnable.passthrough.RunnableAssign
A runnable that assigns key-value pairs to Dict[str, Any] inputs.
schema.runnable.passthrough.RunnablePassthrough
A runnable that passes through the input.
schema.runnable.retry.RunnableRetry
Retry a Runnable if it fails.
schema.runnable.router.RouterInput
A Router input.
schema.runnable.router.RouterRunnable
A runnable that routes to a set of runnables based on Input['key'].
schema.runnable.utils.AddableDict
Dictionary that can be added to another dictionary.
schema.runnable.utils.GetLambdaSource()
schema.runnable.utils.IsFunctionArgDict()
schema.runnable.utils.IsLocalDict(name, keys)
schema.runnable.utils.SupportsAdd(*args, ...)
schema.storage.BaseStore()
Abstract interface for a key-value store.
schema.vectorstore.VectorStore()
Interface for vector store.
schema.vectorstore.VectorStoreRetriever
Base Retriever class for VectorStore.
Functions¶
schema.messages.get_buffer_string(messages) | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-71 | Functions¶
schema.messages.get_buffer_string(messages)
Convert sequence of Messages to strings and concatenate them into one string.
schema.messages.messages_from_dict(messages)
Convert a sequence of messages from dicts to Message objects.
schema.messages.messages_to_dict(messages)
Convert a sequence of Messages to a list of dictionaries.
schema.prompt_template.format_document(doc, ...)
Format a document into a string based on a prompt template.
schema.runnable.base.coerce_to_runnable(thing)
schema.runnable.config.acall_func_with_variable_args(...)
Call function that may optionally accept a run_manager and/or config.
schema.runnable.config.call_func_with_variable_args(...)
Call function that may optionally accept a run_manager and/or config.
schema.runnable.config.ensure_config([config])
schema.runnable.config.get_async_callback_manager_for_config(config)
schema.runnable.config.get_callback_manager_for_config(config)
schema.runnable.config.get_config_list(...)
Helper method to get a list of configs from a single config or a list of configs, useful for subclasses overriding batch() or abatch().
schema.runnable.config.get_executor_for_config(config)
schema.runnable.config.patch_config(config, *)
schema.runnable.passthrough.aidentity(x)
schema.runnable.passthrough.identity(x)
schema.runnable.utils.aadd(addables)
schema.runnable.utils.accepts_config(callable)
schema.runnable.utils.accepts_run_manager(...)
schema.runnable.utils.add(addables)
schema.runnable.utils.gated_coro(semaphore, coro)
schema.runnable.utils.gather_with_concurrency(n, ...)
schema.runnable.utils.get_function_first_arg_dict_keys(func)
schema.runnable.utils.get_lambda_source(func)
Get the source code of a lambda function.
schema.runnable.utils.indent_lines_after_first(...)
Indent all lines of text after the first line.
langchain.smith¶ | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-72 | Indent all lines of text after the first line.
langchain.smith¶
LangSmith utilities.
This module provides utilities for connecting to LangSmith. For more information on LangSmith, see the LangSmith documentation.
Evaluation
LangSmith helps you evaluate Chains and other language model application components using a number of LangChain evaluators.
An example of this is shown below, assuming you’ve created a LangSmith dataset called <my_dataset_name>:
from langsmith import Client
from langchain.chat_models import ChatOpenAI
from langchain.chains import LLMChain
from langchain.smith import RunEvalConfig, run_on_dataset
# Chains may have memory. Passing in a constructor function lets the
# evaluation framework avoid cross-contamination between runs.
def construct_chain():
llm = ChatOpenAI(temperature=0)
chain = LLMChain.from_string(
llm,
"What's the answer to {your_input_key}"
)
return chain
# Load off-the-shelf evaluators via config or the EvaluatorType (string or enum)
evaluation_config = RunEvalConfig(
evaluators=[
"qa", # "Correctness" against a reference answer
"embedding_distance",
RunEvalConfig.Criteria("helpfulness"),
RunEvalConfig.Criteria({
"fifth-grader-score": "Do you have to be smarter than a fifth grader to answer this question?"
}),
]
)
client = Client()
run_on_dataset(
client,
"<my_dataset_name>",
construct_chain,
evaluation=evaluation_config,
)
You can also create custom evaluators by subclassing the
StringEvaluator
or LangSmith’s RunEvaluator classes.
from typing import Optional
from langchain.evaluation import StringEvaluator
class MyStringEvaluator(StringEvaluator): | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-73 | from langchain.evaluation import StringEvaluator
class MyStringEvaluator(StringEvaluator):
@property
def requires_input(self) -> bool:
return False
@property
def requires_reference(self) -> bool:
return True
@property
def evaluation_name(self) -> str:
return "exact_match"
def _evaluate_strings(self, prediction, reference=None, input=None, **kwargs) -> dict:
return {"score": prediction == reference}
evaluation_config = RunEvalConfig(
custom_evaluators = [MyStringEvaluator()],
)
run_on_dataset(
client,
"<my_dataset_name>",
construct_chain,
evaluation=evaluation_config,
)
Primary Functions
arun_on_dataset: Asynchronous function to evaluate a chain, agent, or other LangChain component over a dataset.
run_on_dataset: Function to evaluate a chain, agent, or other LangChain component over a dataset.
RunEvalConfig: Class representing the configuration for running evaluation. You can select evaluators by EvaluatorType or config, or you can pass in custom_evaluators
Classes¶
smith.evaluation.config.EvalConfig
Configuration for a given run evaluator.
smith.evaluation.config.RunEvalConfig
Configuration for a run evaluation.
smith.evaluation.progress.ProgressBarCallback(total)
A simple progress bar for the console.
smith.evaluation.runner_utils.InputFormatError
Raised when the input format is invalid.
smith.evaluation.runner_utils.TestResult
A dictionary of the results of a single test run.
smith.evaluation.string_run_evaluator.ChainStringRunMapper
Extract items to evaluate from the run object from a chain.
smith.evaluation.string_run_evaluator.LLMStringRunMapper
Extract items to evaluate from the run object.
smith.evaluation.string_run_evaluator.StringExampleMapper | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-74 | smith.evaluation.string_run_evaluator.StringExampleMapper
Map an example, or row in the dataset, to the inputs of an evaluation.
smith.evaluation.string_run_evaluator.StringRunEvaluatorChain
Evaluate Run and optional examples.
smith.evaluation.string_run_evaluator.StringRunMapper
Extract items to evaluate from the run object.
smith.evaluation.string_run_evaluator.ToolStringRunMapper
Map an input to the tool.
Functions¶
smith.evaluation.name_generation.random_name([...])
Generate a random name.
smith.evaluation.runner_utils.arun_on_dataset(...)
Run the Chain or language model on a dataset and store traces to the specified project name.
smith.evaluation.runner_utils.run_on_dataset(...)
Run the Chain or language model on a dataset and store traces to the specified project name.
langchain.storage¶
Implementations of key-value stores and storage helpers.
Module provides implementations of various key-value stores that conform
to a simple key-value interface.
The primary goal of these storages is to support implementation of caching.
Classes¶
storage.encoder_backed.EncoderBackedStore(...)
Wraps a store with key and value encoders/decoders.
storage.exceptions.InvalidKeyException
Raised when a key is invalid; e.g., uses incorrect characters.
storage.file_system.LocalFileStore(root_path)
BaseStore interface that works on the local file system.
storage.in_memory.InMemoryStore()
In-memory implementation of the BaseStore using a dictionary.
storage.redis.RedisStore(*[, client, ...])
BaseStore implementation using Redis as the underlying store.
langchain.text_splitter¶
Text Splitters are classes for splitting text.
Class hierarchy:
BaseDocumentTransformer --> TextSplitter --> <name>TextSplitter # Example: CharacterTextSplitter
RecursiveCharacterTextSplitter --> <name>TextSplitter | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-75 | RecursiveCharacterTextSplitter --> <name>TextSplitter
Note: MarkdownHeaderTextSplitter does not derive from TextSplitter.
Main helpers:
Document, Tokenizer, Language, LineType, HeaderType
Classes¶
text_splitter.CharacterTextSplitter([...])
Splitting text that looks at characters.
text_splitter.HeaderType
Header type as typed dict.
text_splitter.Language(value[, names, ...])
Enum of the programming languages.
text_splitter.LatexTextSplitter(**kwargs)
Attempts to split the text along Latex-formatted layout elements.
text_splitter.LineType
Line type as typed dict.
text_splitter.MarkdownHeaderTextSplitter(...)
Splitting markdown files based on specified headers.
text_splitter.MarkdownTextSplitter(**kwargs)
Attempts to split the text along Markdown-formatted headings.
text_splitter.NLTKTextSplitter([separator, ...])
Splitting text using NLTK package.
text_splitter.PythonCodeTextSplitter(**kwargs)
Attempts to split the text along Python syntax.
text_splitter.RecursiveCharacterTextSplitter([...])
Splitting text by recursively look at characters.
text_splitter.SentenceTransformersTokenTextSplitter([...])
Splitting text to tokens using sentence model tokenizer.
text_splitter.SpacyTextSplitter([separator, ...])
Splitting text using Spacy package.
text_splitter.TextSplitter(chunk_size, ...)
Interface for splitting text into chunks.
text_splitter.TokenTextSplitter([...])
Splitting text to tokens using model tokenizer.
text_splitter.Tokenizer(chunk_overlap, ...)
Functions¶
text_splitter.split_text_on_tokens(*, text, ...)
Split incoming text and return chunks using tokenizer.
langchain.tools¶ | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-76 | Split incoming text and return chunks using tokenizer.
langchain.tools¶
Tools are classes that an Agent uses to interact with the world.
Each tool has a description. Agent uses the description to choose the right
tool for the job.
Class hierarchy:
ToolMetaclass --> BaseTool --> <name>Tool # Examples: AIPluginTool, BaseGraphQLTool
<name> # Examples: BraveSearch, HumanInputRun
Main helpers:
CallbackManagerForToolRun, AsyncCallbackManagerForToolRun
Classes¶
tools.ainetwork.app.AINAppOps
Create a new model by parsing and validating input data from keyword arguments.
tools.ainetwork.app.AppOperationType(value)
tools.ainetwork.app.AppSchema
Create a new model by parsing and validating input data from keyword arguments.
tools.ainetwork.base.AINBaseTool
Base class for the AINetwork tools.
tools.ainetwork.base.OperationType(value[, ...])
tools.ainetwork.owner.AINOwnerOps
Create a new model by parsing and validating input data from keyword arguments.
tools.ainetwork.owner.RuleSchema
Create a new model by parsing and validating input data from keyword arguments.
tools.ainetwork.rule.AINRuleOps
Create a new model by parsing and validating input data from keyword arguments.
tools.ainetwork.rule.RuleSchema
Create a new model by parsing and validating input data from keyword arguments.
tools.ainetwork.transfer.AINTransfer
Create a new model by parsing and validating input data from keyword arguments.
tools.ainetwork.transfer.TransferSchema
Create a new model by parsing and validating input data from keyword arguments.
tools.ainetwork.value.AINValueOps
Create a new model by parsing and validating input data from keyword arguments.
tools.ainetwork.value.ValueSchema
Create a new model by parsing and validating input data from keyword arguments. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-77 | Create a new model by parsing and validating input data from keyword arguments.
tools.amadeus.base.AmadeusBaseTool
Base Tool for Amadeus.
tools.amadeus.closest_airport.AmadeusClosestAirport
Tool for finding the closest airport to a particular location.
tools.amadeus.closest_airport.ClosestAirportSchema
Schema for the AmadeusClosestAirport tool.
tools.amadeus.flight_search.AmadeusFlightSearch
Tool for searching for a single flight between two airports.
tools.amadeus.flight_search.FlightSearchSchema
Schema for the AmadeusFlightSearch tool.
tools.arxiv.tool.ArxivQueryRun
Tool that searches the Arxiv API.
tools.azure_cognitive_services.form_recognizer.AzureCogsFormRecognizerTool
Tool that queries the Azure Cognitive Services Form Recognizer API.
tools.azure_cognitive_services.image_analysis.AzureCogsImageAnalysisTool
Tool that queries the Azure Cognitive Services Image Analysis API.
tools.azure_cognitive_services.speech2text.AzureCogsSpeech2TextTool
Tool that queries the Azure Cognitive Services Speech2Text API.
tools.azure_cognitive_services.text2speech.AzureCogsText2SpeechTool
Tool that queries the Azure Cognitive Services Text2Speech API.
tools.base.BaseTool
Interface LangChain tools must implement.
tools.base.SchemaAnnotationError
Raised when 'args_schema' is missing or has an incorrect type annotation.
tools.base.StructuredTool
Tool that can operate on any number of inputs.
tools.base.Tool
Tool that takes in function or coroutine directly.
tools.base.ToolException
An optional exception that tool throws when execution error occurs.
tools.bing_search.tool.BingSearchResults
Tool that queries the Bing Search API and gets back json.
tools.bing_search.tool.BingSearchRun
Tool that queries the Bing search API.
tools.brave_search.tool.BraveSearch | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-78 | Tool that queries the Bing search API.
tools.brave_search.tool.BraveSearch
Tool that queries the BraveSearch.
tools.dataforseo_api_search.tool.DataForSeoAPISearchResults
Tool that queries the DataForSeo Google Search API and get back json.
tools.dataforseo_api_search.tool.DataForSeoAPISearchRun
Tool that queries the DataForSeo Google search API.
tools.ddg_search.tool.DuckDuckGoSearchResults
Tool that queries the DuckDuckGo search API and gets back json.
tools.ddg_search.tool.DuckDuckGoSearchRun
Tool that queries the DuckDuckGo search API.
tools.edenai.audio_speech_to_text.EdenAiSpeechToTextTool
Tool that queries the Eden AI Speech To Text API.
tools.edenai.audio_text_to_speech.EdenAiTextToSpeechTool
Tool that queries the Eden AI Text to speech API.
tools.edenai.edenai_base_tool.EdenaiTool
the base tool for all the EdenAI Tools .
tools.edenai.image_explicitcontent.EdenAiExplicitImageTool
Tool that queries the Eden AI Explicit image detection.
tools.edenai.image_objectdetection.EdenAiObjectDetectionTool
Tool that queries the Eden AI Object detection API.
tools.edenai.ocr_identityparser.EdenAiParsingIDTool
Tool that queries the Eden AI Identity parsing API.
tools.edenai.ocr_invoiceparser.EdenAiParsingInvoiceTool
Tool that queries the Eden AI Invoice parsing API.
tools.edenai.text_moderation.EdenAiTextModerationTool
Tool that queries the Eden AI Explicit text detection.
tools.eleven_labs.models.ElevenLabsModel(value)
Models available for Eleven Labs Text2Speech. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-79 | Models available for Eleven Labs Text2Speech.
tools.eleven_labs.text2speech.ElevenLabsModel(value)
Models available for Eleven Labs Text2Speech.
tools.eleven_labs.text2speech.ElevenLabsText2SpeechTool
Tool that queries the Eleven Labs Text2Speech API.
tools.file_management.copy.CopyFileTool
Tool that copies a file.
tools.file_management.copy.FileCopyInput
Input for CopyFileTool.
tools.file_management.delete.DeleteFileTool
Tool that deletes a file.
tools.file_management.delete.FileDeleteInput
Input for DeleteFileTool.
tools.file_management.file_search.FileSearchInput
Input for FileSearchTool.
tools.file_management.file_search.FileSearchTool
Tool that searches for files in a subdirectory that match a regex pattern.
tools.file_management.list_dir.DirectoryListingInput
Input for ListDirectoryTool.
tools.file_management.list_dir.ListDirectoryTool
Tool that lists files and directories in a specified folder.
tools.file_management.move.FileMoveInput
Input for MoveFileTool.
tools.file_management.move.MoveFileTool
Tool that moves a file.
tools.file_management.read.ReadFileInput
Input for ReadFileTool.
tools.file_management.read.ReadFileTool
Tool that reads a file.
tools.file_management.utils.BaseFileToolMixin
Mixin for file system tools.
tools.file_management.utils.FileValidationError
Error for paths outside the root directory.
tools.file_management.write.WriteFileInput
Input for WriteFileTool.
tools.file_management.write.WriteFileTool
Tool that writes a file to disk.
tools.github.tool.GitHubAction
Tool for interacting with the GitHub API.
tools.gitlab.tool.GitLabAction
Tool for interacting with the GitLab API.
tools.gmail.base.GmailBaseTool
Base class for Gmail tools.
tools.gmail.create_draft.CreateDraftSchema
Input for CreateDraftTool. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-80 | tools.gmail.create_draft.CreateDraftSchema
Input for CreateDraftTool.
tools.gmail.create_draft.GmailCreateDraft
Tool that creates a draft email for Gmail.
tools.gmail.get_message.GmailGetMessage
Tool that gets a message by ID from Gmail.
tools.gmail.get_message.SearchArgsSchema
Input for GetMessageTool.
tools.gmail.get_thread.GetThreadSchema
Input for GetMessageTool.
tools.gmail.get_thread.GmailGetThread
Tool that gets a thread by ID from Gmail.
tools.gmail.search.GmailSearch
Tool that searches for messages or threads in Gmail.
tools.gmail.search.Resource(value[, names, ...])
Enumerator of Resources to search.
tools.gmail.search.SearchArgsSchema
Input for SearchGmailTool.
tools.gmail.send_message.GmailSendMessage
Tool that sends a message to Gmail.
tools.gmail.send_message.SendMessageSchema
Input for SendMessageTool.
tools.golden_query.tool.GoldenQueryRun
Tool that adds the capability to query using the Golden API and get back JSON.
tools.google_places.tool.GooglePlacesSchema
Input for GooglePlacesTool.
tools.google_places.tool.GooglePlacesTool
Tool that queries the Google places API.
tools.google_search.tool.GoogleSearchResults
Tool that queries the Google Search API and gets back json.
tools.google_search.tool.GoogleSearchRun
Tool that queries the Google search API.
tools.google_serper.tool.GoogleSerperResults
Tool that queries the Serper.dev Google Search API and get back json.
tools.google_serper.tool.GoogleSerperRun
Tool that queries the Serper.dev Google search API.
tools.graphql.tool.BaseGraphQLTool
Base tool for querying a GraphQL API.
tools.human.tool.HumanInputRun
Tool that asks user for input.
tools.ifttt.IFTTTWebhook
IFTTT Webhook.
tools.jira.tool.JiraAction
Tool that queries the Atlassian Jira API. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-81 | tools.jira.tool.JiraAction
Tool that queries the Atlassian Jira API.
tools.json.tool.JsonGetValueTool
Tool for getting a value in a JSON spec.
tools.json.tool.JsonListKeysTool
Tool for listing keys in a JSON spec.
tools.json.tool.JsonSpec
Base class for JSON spec.
tools.metaphor_search.tool.MetaphorSearchResults
Tool that queries the Metaphor Search API and gets back json.
tools.multion.create_session.CreateSessionSchema
Input for CreateSessionTool.
tools.multion.create_session.MultionCreateSession
Tool that creates a new Multion Browser Window with provided fields.
tools.multion.update_session.MultionUpdateSession
Tool that updates an existing Multion Browser Window with provided fields.
tools.multion.update_session.UpdateSessionSchema
Input for UpdateSessionTool.
tools.nuclia.tool.NUASchema
Input for Nuclia Understanding API.
tools.nuclia.tool.NucliaUnderstandingAPI
Tool to process files with the Nuclia Understanding API.
tools.office365.base.O365BaseTool
Base class for the Office 365 tools.
tools.office365.create_draft_message.CreateDraftMessageSchema
Input for SendMessageTool.
tools.office365.create_draft_message.O365CreateDraftMessage
Tool for creating a draft email in Office 365.
tools.office365.events_search.O365SearchEvents
Class for searching calendar events in Office 365
tools.office365.events_search.SearchEventsInput
Input for SearchEmails Tool.
tools.office365.messages_search.O365SearchEmails
Class for searching email messages in Office 365
tools.office365.messages_search.SearchEmailsInput
Input for SearchEmails Tool.
tools.office365.send_event.O365SendEvent
Tool for sending calendar events in Office 365.
tools.office365.send_event.SendEventSchema
Input for CreateEvent Tool. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-82 | tools.office365.send_event.SendEventSchema
Input for CreateEvent Tool.
tools.office365.send_message.O365SendMessage
Tool for sending an email in Office 365.
tools.office365.send_message.SendMessageSchema
Input for SendMessageTool.
tools.openapi.utils.api_models.APIOperation
A model for a single API operation.
tools.openapi.utils.api_models.APIProperty
A model for a property in the query, path, header, or cookie params.
tools.openapi.utils.api_models.APIPropertyBase
Base model for an API property.
tools.openapi.utils.api_models.APIPropertyLocation(value)
The location of the property.
tools.openapi.utils.api_models.APIRequestBody
A model for a request body.
tools.openapi.utils.api_models.APIRequestBodyProperty
A model for a request body property.
tools.openweathermap.tool.OpenWeatherMapQueryRun
Tool that queries the OpenWeatherMap API.
tools.playwright.base.BaseBrowserTool
Base class for browser tools.
tools.playwright.click.ClickTool
Tool for clicking on an element with the given CSS selector.
tools.playwright.click.ClickToolInput
Input for ClickTool.
tools.playwright.current_page.CurrentWebPageTool
Tool for getting the URL of the current webpage.
tools.playwright.extract_hyperlinks.ExtractHyperlinksTool
Extract all hyperlinks on the page.
tools.playwright.extract_hyperlinks.ExtractHyperlinksToolInput
Input for ExtractHyperlinksTool.
tools.playwright.extract_text.ExtractTextTool
Tool for extracting all the text on the current webpage.
tools.playwright.get_elements.GetElementsTool
Tool for getting elements in the current web page matching a CSS selector.
tools.playwright.get_elements.GetElementsToolInput
Input for GetElementsTool.
tools.playwright.navigate.NavigateTool
Tool for navigating a browser to a URL.
tools.playwright.navigate.NavigateToolInput
Input for NavigateToolInput.
tools.playwright.navigate_back.NavigateBackTool | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-83 | Input for NavigateToolInput.
tools.playwright.navigate_back.NavigateBackTool
Navigate back to the previous page in the browser history.
tools.plugin.AIPlugin
AI Plugin Definition.
tools.plugin.AIPluginTool
Tool for getting the OpenAPI spec for an AI Plugin.
tools.plugin.AIPluginToolSchema
Schema for AIPluginTool.
tools.plugin.ApiConfig
API Configuration.
tools.powerbi.tool.InfoPowerBITool
Tool for getting metadata about a PowerBI Dataset.
tools.powerbi.tool.ListPowerBITool
Tool for getting tables names.
tools.powerbi.tool.QueryPowerBITool
Tool for querying a Power BI Dataset.
tools.pubmed.tool.PubmedQueryRun
Tool that searches the PubMed API.
tools.python.tool.PythonAstREPLTool
A tool for running python code in a REPL.
tools.python.tool.PythonInputs
Create a new model by parsing and validating input data from keyword arguments.
tools.python.tool.PythonREPLTool
A tool for running python code in a REPL.
tools.requests.tool.BaseRequestsTool
Base class for requests tools.
tools.requests.tool.RequestsDeleteTool
Tool for making a DELETE request to an API endpoint.
tools.requests.tool.RequestsGetTool
Tool for making a GET request to an API endpoint.
tools.requests.tool.RequestsPatchTool
Tool for making a PATCH request to an API endpoint.
tools.requests.tool.RequestsPostTool
Tool for making a POST request to an API endpoint.
tools.requests.tool.RequestsPutTool
Tool for making a PUT request to an API endpoint.
tools.scenexplain.tool.SceneXplainInput
Input for SceneXplain.
tools.scenexplain.tool.SceneXplainTool
Tool that explains images.
tools.searchapi.tool.SearchAPIResults
Tool that queries the SearchApi.io search API and returns JSON.
tools.searchapi.tool.SearchAPIRun | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-84 | tools.searchapi.tool.SearchAPIRun
Tool that queries the SearchApi.io search API.
tools.searx_search.tool.SearxSearchResults
Tool that queries a Searx instance and gets back json.
tools.searx_search.tool.SearxSearchRun
Tool that queries a Searx instance.
tools.shell.tool.ShellInput
Commands for the Bash Shell tool.
tools.shell.tool.ShellTool
Tool to run shell commands.
tools.sleep.tool.SleepInput
Input for CopyFileTool.
tools.sleep.tool.SleepTool
Tool that adds the capability to sleep.
tools.spark_sql.tool.BaseSparkSQLTool
Base tool for interacting with Spark SQL.
tools.spark_sql.tool.InfoSparkSQLTool
Tool for getting metadata about a Spark SQL.
tools.spark_sql.tool.ListSparkSQLTool
Tool for getting tables names.
tools.spark_sql.tool.QueryCheckerTool
Use an LLM to check if a query is correct.
tools.spark_sql.tool.QuerySparkSQLTool
Tool for querying a Spark SQL.
tools.sql_database.tool.BaseSQLDatabaseTool
Base tool for interacting with a SQL database.
tools.sql_database.tool.InfoSQLDatabaseTool
Tool for getting metadata about a SQL database.
tools.sql_database.tool.ListSQLDatabaseTool
Tool for getting tables names.
tools.sql_database.tool.QuerySQLCheckerTool
Use an LLM to check if a query is correct.
tools.sql_database.tool.QuerySQLDataBaseTool
Tool for querying a SQL database.
tools.steamship_image_generation.tool.ModelName(value)
Supported Image Models for generation.
tools.steamship_image_generation.tool.SteamshipImageGenerationTool
Tool used to generate images from a text-prompt.
tools.vectorstore.tool.BaseVectorStoreTool
Base class for tools that use a VectorStore.
tools.vectorstore.tool.VectorStoreQATool
Tool for the VectorDBQA chain. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-85 | tools.vectorstore.tool.VectorStoreQATool
Tool for the VectorDBQA chain.
tools.vectorstore.tool.VectorStoreQAWithSourcesTool
Tool for the VectorDBQAWithSources chain.
tools.wikipedia.tool.WikipediaQueryRun
Tool that searches the Wikipedia API.
tools.wolfram_alpha.tool.WolframAlphaQueryRun
Tool that queries using the Wolfram Alpha SDK.
tools.yahoo_finance_news.YahooFinanceNewsTool
Tool that searches financial news on Yahoo Finance.
tools.youtube.search.YouTubeSearchTool
Tool that queries YouTube.
tools.zapier.tool.ZapierNLAListActions
Returns a list of all exposed (enabled) actions associated with
tools.zapier.tool.ZapierNLARunAction
Executes an action that is identified by action_id, must be exposed
Functions¶
tools.ainetwork.utils.authenticate([network])
Authenticate using the AIN Blockchain
tools.amadeus.utils.authenticate()
Authenticate using the Amadeus API
tools.azure_cognitive_services.utils.detect_file_src_type(...)
Detect if the file is local or remote.
tools.azure_cognitive_services.utils.download_audio_from_url(...)
Download audio from url to local.
tools.base.create_schema_from_function(...)
Create a pydantic schema from a function's signature.
tools.base.tool(*args[, return_direct, ...])
Make tools out of functions, can be used with or without arguments.
tools.ddg_search.tool.DuckDuckGoSearchTool(...)
Deprecated.
tools.file_management.utils.get_validated_relative_path(...)
Resolve a relative path, raising an error if not within the root directory.
tools.file_management.utils.is_relative_to(...)
Check if path is relative to root.
tools.gmail.utils.build_resource_service([...])
Build a Gmail service.
tools.gmail.utils.clean_email_body(body)
Clean email body.
tools.gmail.utils.get_gmail_credentials([...]) | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-86 | Clean email body.
tools.gmail.utils.get_gmail_credentials([...])
Get credentials.
tools.gmail.utils.import_google()
Import google libraries.
tools.gmail.utils.import_googleapiclient_resource_builder()
Import googleapiclient.discovery.build function.
tools.gmail.utils.import_installed_app_flow()
Import InstalledAppFlow class.
tools.interaction.tool.StdInInquireTool(...)
Tool for asking the user for input.
tools.office365.utils.authenticate()
Authenticate using the Microsoft Grah API
tools.office365.utils.clean_body(body)
Clean body of a message or event.
tools.playwright.base.lazy_import_playwright_browsers()
Lazy import playwright browsers.
tools.playwright.utils.aget_current_page(browser)
Asynchronously get the current page of the browser.
tools.playwright.utils.create_async_playwright_browser([...])
Create an async playwright browser.
tools.playwright.utils.create_sync_playwright_browser([...])
Create a playwright browser.
tools.playwright.utils.get_current_page(browser)
Get the current page of the browser.
tools.playwright.utils.run_async(coro)
Run an async coroutine.
tools.plugin.marshal_spec(txt)
Convert the yaml or json serialized spec to a dict.
tools.python.tool.sanitize_input(query)
Sanitize input to the python REPL.
tools.render.format_tool_to_openai_function(tool)
Format tool into the OpenAI function API.
tools.render.render_text_description(tools)
Render the tool name and description in plain text.
tools.render.render_text_description_and_args(tools)
Render the tool name, description, and args in plain text.
tools.steamship_image_generation.utils.make_image_public(...)
Upload a block to a signed URL and return the public URL.
langchain.tools.render¶
Different methods for rendering Tools to be passed to LLMs. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-87 | langchain.tools.render¶
Different methods for rendering Tools to be passed to LLMs.
Depending on the LLM you are using and the prompting strategy you are using,
you may want Tools to be rendered in a different way.
This module contains various ways to render tools.
Functions¶
tools.render.format_tool_to_openai_function(tool)
Format tool into the OpenAI function API.
tools.render.render_text_description(tools)
Render the tool name and description in plain text.
tools.render.render_text_description_and_args(tools)
Render the tool name, description, and args in plain text.
langchain.utilities¶
Utilities are the integrations with third-part systems and packages.
Other LangChain classes use Utilities to interact with third-part systems
and packages.
Classes¶
utilities.alpha_vantage.AlphaVantageAPIWrapper
Wrapper for AlphaVantage API for Currency Exchange Rate.
utilities.apify.ApifyWrapper
Wrapper around Apify.
utilities.arxiv.ArxivAPIWrapper
Wrapper around ArxivAPI.
utilities.awslambda.LambdaWrapper
Wrapper for AWS Lambda SDK.
utilities.bash.BashProcess([strip_newlines, ...])
Wrapper class for starting subprocesses.
utilities.bibtex.BibtexparserWrapper
Wrapper around bibtexparser.
utilities.bing_search.BingSearchAPIWrapper
Wrapper for Bing Search API.
utilities.brave_search.BraveSearchWrapper
Wrapper around the Brave search engine.
utilities.dalle_image_generator.DallEAPIWrapper
Wrapper for OpenAI's DALL-E Image Generator.
utilities.dataforseo_api_search.DataForSeoAPIWrapper
Wrapper around the DataForSeo API.
utilities.duckduckgo_search.DuckDuckGoSearchAPIWrapper
Wrapper for DuckDuckGo Search API.
utilities.github.GitHubAPIWrapper
Wrapper for GitHub API. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-88 | utilities.github.GitHubAPIWrapper
Wrapper for GitHub API.
utilities.gitlab.GitLabAPIWrapper
Wrapper for GitLab API.
utilities.golden_query.GoldenQueryAPIWrapper
Wrapper for Golden.
utilities.google_places_api.GooglePlacesAPIWrapper
Wrapper around Google Places API.
utilities.google_search.GoogleSearchAPIWrapper
Wrapper for Google Search API.
utilities.google_serper.GoogleSerperAPIWrapper
Wrapper around the Serper.dev Google Search API.
utilities.graphql.GraphQLAPIWrapper
Wrapper around GraphQL API.
utilities.jira.JiraAPIWrapper
Wrapper for Jira API.
utilities.max_compute.MaxComputeAPIWrapper(client)
Interface for querying Alibaba Cloud MaxCompute tables.
utilities.metaphor_search.MetaphorSearchAPIWrapper
Wrapper for Metaphor Search API.
utilities.openapi.HTTPVerb(value[, names, ...])
Enumerator of the HTTP verbs.
utilities.openapi.OpenAPISpec()
OpenAPI Model that removes mis-formatted parts of the spec.
utilities.openweathermap.OpenWeatherMapAPIWrapper
Wrapper for OpenWeatherMap API using PyOWM.
utilities.portkey.Portkey()
Portkey configuration.
utilities.powerbi.PowerBIDataset
Create PowerBI engine from dataset ID and credential or token.
utilities.pubmed.PubMedAPIWrapper
Wrapper around PubMed API.
utilities.python.PythonREPL
Simulates a standalone Python REPL.
utilities.redis.TokenEscaper([escape_chars_re])
Escape punctuation within an input string.
utilities.requests.Requests
Wrapper around requests to handle auth and async.
utilities.requests.RequestsWrapper
alias of TextRequestsWrapper
utilities.requests.TextRequestsWrapper
Lightweight wrapper around requests library.
utilities.scenexplain.SceneXplainAPIWrapper
Wrapper for SceneXplain API.
utilities.searchapi.SearchApiAPIWrapper
Wrapper around SearchApi API.
utilities.searx_search.SearxResults(data) | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-89 | Wrapper around SearchApi API.
utilities.searx_search.SearxResults(data)
Dict like wrapper around search api results.
utilities.searx_search.SearxSearchWrapper
Wrapper for Searx API.
utilities.serpapi.HiddenPrints()
Context manager to hide prints.
utilities.serpapi.SerpAPIWrapper
Wrapper around SerpAPI.
utilities.spark_sql.SparkSQL([...])
SparkSQL is a utility class for interacting with Spark SQL.
utilities.sql_database.SQLDatabase(engine[, ...])
SQLAlchemy wrapper around a database.
utilities.tensorflow_datasets.TensorflowDatasets
Access to the TensorFlow Datasets.
utilities.twilio.TwilioAPIWrapper
Messaging Client using Twilio.
utilities.wikipedia.WikipediaAPIWrapper
Wrapper around WikipediaAPI.
utilities.wolfram_alpha.WolframAlphaAPIWrapper
Wrapper for Wolfram Alpha.
utilities.zapier.ZapierNLAWrapper
Wrapper for Zapier NLA.
Functions¶
utilities.opaqueprompts.desanitize(...)
Restore the original sensitive data from the sanitized text.
utilities.opaqueprompts.sanitize(input)
Sanitize input string or dict of strings by replacing sensitive data with placeholders. It returns the sanitized input string or dict of strings and the secure context as a dict following the format: { "sanitized_input": <sanitized input string or dict of strings>, "secure_context": <secure context> }.
utilities.powerbi.fix_table_name(table)
Add single quotes around table names that contain spaces.
utilities.powerbi.json_to_md(json_contents)
Converts a JSON object to a markdown table.
utilities.redis.check_redis_module_exist(...)
Check if the correct Redis modules are installed.
utilities.redis.get_client(redis_url, **kwargs)
Get a redis client from the connection url given.
utilities.sql_database.truncate_word(...[, ...]) | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-90 | utilities.sql_database.truncate_word(...[, ...])
Truncate a string to a certain number of words, based on the max string length.
utilities.vertexai.init_vertexai([project, ...])
Init vertexai.
utilities.vertexai.raise_vertex_import_error([...])
Raise ImportError related to Vertex SDK being not available.
langchain.utils¶
Utility functions for LangChain.
These functions do not depend on any other LangChain module.
Classes¶
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.atee
alias of Tee
utils.formatting.StrictFormatter()
A subclass of formatter that checks for extra keys.
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.openai_functions.FunctionDescription
Representation of a callable function to the OpenAI API.
Functions¶
utils.aiter.py_anext(iterator[, default])
Pure-Python implementation of anext() for testing purposes.
utils.aiter.tee_peer(iterator, buffer, ...)
An individual iterator of a tee()
utils.env.get_from_dict_or_env(data, key, ...)
Get a value from a dictionary or an environment variable.
utils.env.get_from_env(key, env_key[, default])
Get a value from a dictionary or an environment variable.
utils.html.extract_sub_links(raw_html, url, *)
Extract all links from a raw html string and convert into absolute paths.
utils.html.find_all_links(raw_html, *[, pattern])
utils.input.get_bolded_text(text) | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-91 | utils.input.get_bolded_text(text)
Get bolded text.
utils.input.get_color_mapping(items[, ...])
Get mapping for items to a support color.
utils.input.get_colored_text(text, color)
Get colored text.
utils.input.print_text(text[, color, end, file])
Print text with highlighting and no end characters.
utils.iter.batch_iterate(size, iterable)
Utility batching function.
utils.iter.tee_peer(iterator, buffer, peers, ...)
An individual iterator of a tee()
utils.json_schema.dereference_refs(schema_obj, *)
Try to substitute $refs in JSON Schema.
utils.loading.try_load_from_hub(path, ...)
Load configuration from hub.
utils.math.cosine_similarity(X, Y)
Row-wise cosine similarity between two equal-width matrices.
utils.math.cosine_similarity_top_k(X, Y[, ...])
Row-wise cosine similarity with optional top-k and score threshold filtering.
utils.openai_functions.convert_pydantic_to_openai_function(...)
utils.pydantic.get_pydantic_major_version()
Get the major version of Pydantic.
utils.strings.comma_list(items)
Convert a list to a comma-separated string.
utils.strings.stringify_dict(data)
Stringify a dictionary.
utils.strings.stringify_value(val)
Stringify a value.
utils.utils.build_extra_kwargs(extra_kwargs, ...)
Build extra kwargs from values and extra_kwargs.
utils.utils.check_package_version(package[, ...])
Check the version of a package.
utils.utils.get_pydantic_field_names(...)
Get field names, including aliases, for a pydantic class.
utils.utils.guard_import(module_name, *[, ...])
Dynamically imports a module and raises a helpful exception if the module is not installed.
utils.utils.mock_now(dt_value) | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-92 | utils.utils.mock_now(dt_value)
Context manager for mocking out datetime.now() in unit tests.
utils.utils.raise_for_status_with_text(response)
Raise an error with the response text.
utils.utils.xor_args(*arg_groups)
Validate specified keyword args are mutually exclusive.
langchain.vectorstores¶
Vector store stores embedded data and performs vector search.
One of the most common ways to store and search over unstructured data is to
embed it and store the resulting embedding vectors, and then query the store
and retrieve the data that are ‘most similar’ to the embedded query.
Class hierarchy:
VectorStore --> <name> # Examples: Annoy, FAISS, Milvus
BaseRetriever --> VectorStoreRetriever --> <name>Retriever # Example: VespaRetriever
Main helpers:
Embeddings, Document
Classes¶
vectorstores.alibabacloud_opensearch.AlibabaCloudOpenSearch(...)
Alibaba Cloud OpenSearch vector store.
vectorstores.alibabacloud_opensearch.AlibabaCloudOpenSearchSettings(...)
Alibaba Cloud Opensearch client configuration.
vectorstores.analyticdb.AnalyticDB(...[, ...])
AnalyticDB (distributed PostgreSQL) vector store.
vectorstores.annoy.Annoy(embedding_function, ...)
Annoy vector store.
vectorstores.atlas.AtlasDB(name[, ...])
Atlas vector store.
vectorstores.awadb.AwaDB([table_name, ...])
AwaDB vector store.
vectorstores.azuresearch.AzureSearch(...[, ...])
Azure Cognitive Search vector store.
vectorstores.azuresearch.AzureSearchVectorStoreRetriever
Retriever that uses Azure Cognitive Search.
vectorstores.bageldb.Bagel([cluster_name, ...])
BagelDB.ai vector store. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-93 | BagelDB.ai vector store.
vectorstores.cassandra.Cassandra(embedding, ...)
Wrapper around Apache Cassandra(R) for vector-store workloads.
vectorstores.chroma.Chroma([...])
ChromaDB vector store.
vectorstores.clarifai.Clarifai([user_id, ...])
Clarifai AI vector store.
vectorstores.clickhouse.Clickhouse(embedding)
ClickHouse VectorSearch vector store.
vectorstores.clickhouse.ClickhouseSettings
ClickHouse client configuration.
vectorstores.dashvector.DashVector(...)
DashVector vector store.
vectorstores.deeplake.DeepLake([...])
Activeloop Deep Lake vector store.
vectorstores.dingo.Dingo(embedding, text_key, *)
Dingo vector store.
vectorstores.docarray.base.DocArrayIndex(...)
Base class for DocArray based vector stores.
vectorstores.docarray.hnsw.DocArrayHnswSearch(...)
HnswLib storage using DocArray package.
vectorstores.docarray.in_memory.DocArrayInMemorySearch(...)
In-memory DocArray storage for exact search.
vectorstores.elastic_vector_search.ElasticKnnSearch(...)
[Deprecated] [DEPRECATED] Elasticsearch with k-nearest neighbor search (k-NN) vector store.
vectorstores.elastic_vector_search.ElasticVectorSearch(...)
ElasticVectorSearch uses the brute force method of searching on vectors.
vectorstores.elasticsearch.ApproxRetrievalStrategy([...])
Approximate retrieval strategy using the HNSW algorithm.
vectorstores.elasticsearch.BaseRetrievalStrategy()
Base class for Elasticsearch retrieval strategies.
vectorstores.elasticsearch.ElasticsearchStore(...)
Elasticsearch vector store.
vectorstores.elasticsearch.ExactRetrievalStrategy()
Exact retrieval strategy using the script_score query.
vectorstores.elasticsearch.SparseRetrievalStrategy([...])
Sparse retrieval strategy using the text_expansion processor. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-94 | Sparse retrieval strategy using the text_expansion processor.
vectorstores.epsilla.Epsilla(client, embeddings)
Wrapper around Epsilla vector database.
vectorstores.faiss.FAISS(embedding_function, ...)
Meta Faiss vector store.
vectorstores.hologres.Hologres(...[, ndims, ...])
Hologres API vector store.
vectorstores.hologres.HologresWrapper(...)
Hologres API wrapper.
vectorstores.lancedb.LanceDB(connection, ...)
LanceDB vector store.
vectorstores.llm_rails.LLMRails([...])
Implementation of Vector Store using LLMRails (https://llmrails.com/).
vectorstores.llm_rails.LLMRailsRetriever
Create a new model by parsing and validating input data from keyword arguments.
vectorstores.llm_rails.ModelChoices(value[, ...])
vectorstores.marqo.Marqo(client, index_name)
Marqo vector store.
vectorstores.matching_engine.MatchingEngine(...)
Google Vertex AI Matching Engine vector store.
vectorstores.meilisearch.Meilisearch(embedding)
Meilisearch vector store.
vectorstores.milvus.Milvus(embedding_function)
Milvus vector store.
vectorstores.mongodb_atlas.MongoDBAtlasVectorSearch(...)
MongoDB Atlas Vector Search vector store.
vectorstores.myscale.MyScale(embedding[, config])
MyScale vector store.
vectorstores.myscale.MyScaleSettings
MyScale client configuration.
vectorstores.neo4j_vector.Neo4jVector(...[, ...])
Neo4j vector index.
vectorstores.neo4j_vector.SearchType(value)
Enumerator of the Distance strategies.
vectorstores.nucliadb.NucliaDB(...[, ...])
NucliaDB vector store. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-95 | NucliaDB vector store.
vectorstores.opensearch_vector_search.OpenSearchVectorSearch(...)
Amazon OpenSearch Vector Engine vector store.
vectorstores.pgembedding.BaseModel(**kwargs)
Base model for all SQL stores.
vectorstores.pgembedding.CollectionStore(...)
Collection store.
vectorstores.pgembedding.EmbeddingStore(**kwargs)
Embedding store.
vectorstores.pgembedding.PGEmbedding(...[, ...])
Postgres with the pg_embedding extension as a vector store.
vectorstores.pgembedding.QueryResult()
Result from a query.
vectorstores.pgvector.BaseModel(**kwargs)
Base model for the SQL stores.
vectorstores.pgvector.DistanceStrategy(value)
Enumerator of the Distance strategies.
vectorstores.pgvector.PGVector(...[, ...])
Postgres/PGVector vector store.
vectorstores.pinecone.Pinecone(index, ...[, ...])
Pinecone vector store.
vectorstores.qdrant.Qdrant(client, ...[, ...])
Qdrant vector store.
vectorstores.qdrant.QdrantException
Qdrant related exceptions.
vectorstores.redis.base.Redis(redis_url, ...)
Wrapper around Redis vector database.
vectorstores.redis.base.RedisVectorStoreRetriever
Retriever for Redis VectorStore.
vectorstores.redis.filters.RedisFilter()
vectorstores.redis.filters.RedisFilterExpression([...])
A RedisFilterExpression is a logical expression of RedisFilterFields.
vectorstores.redis.filters.RedisFilterField(field)
vectorstores.redis.filters.RedisFilterOperator(value)
vectorstores.redis.filters.RedisNum(field)
A RedisFilterField representing a numeric field in a Redis index.
vectorstores.redis.filters.RedisTag(field)
A RedisTag is a RedisFilterField representing a tag in a Redis index.
vectorstores.redis.filters.RedisText(field) | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-96 | vectorstores.redis.filters.RedisText(field)
A RedisText is a RedisFilterField representing a text field in a Redis index.
vectorstores.redis.schema.FlatVectorField
Create a new model by parsing and validating input data from keyword arguments.
vectorstores.redis.schema.HNSWVectorField
Create a new model by parsing and validating input data from keyword arguments.
vectorstores.redis.schema.NumericFieldSchema
Create a new model by parsing and validating input data from keyword arguments.
vectorstores.redis.schema.RedisDistanceMetric(value)
vectorstores.redis.schema.RedisField
Create a new model by parsing and validating input data from keyword arguments.
vectorstores.redis.schema.RedisModel
Create a new model by parsing and validating input data from keyword arguments.
vectorstores.redis.schema.RedisVectorField
Create a new model by parsing and validating input data from keyword arguments.
vectorstores.redis.schema.TagFieldSchema
Create a new model by parsing and validating input data from keyword arguments.
vectorstores.redis.schema.TextFieldSchema
Create a new model by parsing and validating input data from keyword arguments.
vectorstores.rocksetdb.Rockset(client, ...)
Rockset vector store.
vectorstores.scann.ScaNN(embedding, index, ...)
ScaNN vector store.
vectorstores.singlestoredb.SingleStoreDB(...)
SingleStore DB vector store.
vectorstores.singlestoredb.SingleStoreDBRetriever
Retriever for SingleStoreDB vector stores.
vectorstores.sklearn.BaseSerializer(persist_path)
Base class for serializing data.
vectorstores.sklearn.BsonSerializer(persist_path)
Serializes data in binary json using the bson python package.
vectorstores.sklearn.JsonSerializer(persist_path)
Serializes data in json using the json package from python standard library.
vectorstores.sklearn.ParquetSerializer(...)
Serializes data in Apache Parquet format using the pyarrow package. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-97 | Serializes data in Apache Parquet format using the pyarrow package.
vectorstores.sklearn.SKLearnVectorStore(...)
Simple in-memory vector store based on the scikit-learn library NearestNeighbors implementation.
vectorstores.sklearn.SKLearnVectorStoreException
Exception raised by SKLearnVectorStore.
vectorstores.sqlitevss.SQLiteVSS(table, ...)
Wrapper around SQLite with vss extension as a vector database.
vectorstores.starrocks.StarRocks(embedding)
StarRocks vector store.
vectorstores.starrocks.StarRocksSettings
StarRocks client configuration.
vectorstores.supabase.SupabaseVectorStore(...)
Supabase Postgres vector store.
vectorstores.tair.Tair(embedding_function, ...)
Tair vector store.
vectorstores.tencentvectordb.ConnectionParams(...)
Tencent vector DB Connection params.
vectorstores.tencentvectordb.IndexParams(...)
Tencent vector DB Index params.
vectorstores.tencentvectordb.TencentVectorDB(...)
Initialize wrapper around the tencent vector database.
vectorstores.tigris.Tigris(client, ...)
Tigris vector store.
vectorstores.timescalevector.TimescaleVector(...)
VectorStore implementation using the timescale vector client to store vectors in Postgres.
vectorstores.typesense.Typesense(...[, ...])
Typesense vector store.
vectorstores.usearch.USearch(embedding, ...)
USearch vector store.
vectorstores.utils.DistanceStrategy(value[, ...])
Enumerator of the Distance strategies for calculating distances between vectors.
vectorstores.vald.Vald(embedding[, host, ...])
Wrapper around Vald vector database.
vectorstores.vearch.Vearch(embedding_function)
Initialize vearch vector store flag 1 for cluster,0 for standalone
vectorstores.vectara.Vectara([...]) | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-98 | vectorstores.vectara.Vectara([...])
Vectara API vector store.
vectorstores.vectara.VectaraRetriever
Retriever class for Vectara.
vectorstores.weaviate.Weaviate(client, ...)
Weaviate vector store.
vectorstores.xata.XataVectorStore(api_key, ...)
Xata vector store.
vectorstores.zep.CollectionConfig(name, ...)
Configuration for a Zep Collection.
vectorstores.zep.ZepVectorStore(...[, ...])
Zep vector store.
vectorstores.zilliz.Zilliz(embedding_function)
Zilliz vector store.
Functions¶
vectorstores.alibabacloud_opensearch.create_metadata(fields)
Create metadata from fields.
vectorstores.annoy.dependable_annoy_import()
Import annoy if available, otherwise raise error.
vectorstores.clickhouse.has_mul_sub_str(s, *args)
Check if a string contains multiple substrings.
vectorstores.faiss.dependable_faiss_import([...])
Import faiss if available, otherwise raise error.
vectorstores.myscale.has_mul_sub_str(s, *args)
Check if a string contains multiple substrings.
vectorstores.neo4j_vector.check_if_not_null(...)
vectorstores.neo4j_vector.sort_by_index_name(...)
Sort first element to match the index_name if exists
vectorstores.qdrant.sync_call_fallback(method)
Decorator to call the synchronous method of the class if the async method is not implemented.
vectorstores.redis.base.check_index_exists(...)
Check if Redis index exists.
vectorstores.redis.filters.check_operator_misuse(func)
vectorstores.redis.schema.read_schema(...)
vectorstores.scann.dependable_scann_import()
Import scann if available, otherwise raise error.
vectorstores.scann.normalize(x)
Normalize vectors to unit length. | https://api.python.langchain.com/en/latest/api_reference.html |
dba2dae987f7-99 | vectorstores.scann.normalize(x)
Normalize vectors to unit length.
vectorstores.starrocks.debug_output(s)
Print a debug message if DEBUG is True.
vectorstores.starrocks.get_named_result(...)
Get a named result from a query.
vectorstores.starrocks.has_mul_sub_str(s, *args)
Check if a string has multiple substrings.
vectorstores.usearch.dependable_usearch_import()
Import usearch if available, otherwise raise error.
vectorstores.utils.filter_complex_metadata(...)
Filter out metadata types that are not supported for a vector store.
vectorstores.utils.maximal_marginal_relevance(...)
Calculate maximal marginal relevance. | https://api.python.langchain.com/en/latest/api_reference.html |
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