| """**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:** |
| |
| .. code-block:: |
| |
| Chain --> <name>Chain # Examples: LLMChain, MapReduceChain, RouterChain |
| """ |
|
|
| from typing import Any |
|
|
| from langchain._api import create_importer |
|
|
| _module_lookup = { |
| "APIChain": "langchain.chains.api.base", |
| "OpenAPIEndpointChain": "langchain_community.chains.openapi.chain", |
| "AnalyzeDocumentChain": "langchain.chains.combine_documents.base", |
| "MapReduceDocumentsChain": "langchain.chains.combine_documents.map_reduce", |
| "MapRerankDocumentsChain": "langchain.chains.combine_documents.map_rerank", |
| "ReduceDocumentsChain": "langchain.chains.combine_documents.reduce", |
| "RefineDocumentsChain": "langchain.chains.combine_documents.refine", |
| "StuffDocumentsChain": "langchain.chains.combine_documents.stuff", |
| "ConstitutionalChain": "langchain.chains.constitutional_ai.base", |
| "ConversationChain": "langchain.chains.conversation.base", |
| "ChatVectorDBChain": "langchain.chains.conversational_retrieval.base", |
| "ConversationalRetrievalChain": "langchain.chains.conversational_retrieval.base", |
| "generate_example": "langchain.chains.example_generator", |
| "FlareChain": "langchain.chains.flare.base", |
| "ArangoGraphQAChain": "langchain_community.chains.graph_qa.arangodb", |
| "GraphQAChain": "langchain_community.chains.graph_qa.base", |
| "GraphCypherQAChain": "langchain_community.chains.graph_qa.cypher", |
| "FalkorDBQAChain": "langchain_community.chains.graph_qa.falkordb", |
| "HugeGraphQAChain": "langchain_community.chains.graph_qa.hugegraph", |
| "KuzuQAChain": "langchain_community.chains.graph_qa.kuzu", |
| "NebulaGraphQAChain": "langchain_community.chains.graph_qa.nebulagraph", |
| "NeptuneOpenCypherQAChain": "langchain_community.chains.graph_qa.neptune_cypher", |
| "NeptuneSparqlQAChain": "langchain_community.chains.graph_qa.neptune_sparql", |
| "OntotextGraphDBQAChain": "langchain_community.chains.graph_qa.ontotext_graphdb", |
| "GraphSparqlQAChain": "langchain_community.chains.graph_qa.sparql", |
| "create_history_aware_retriever": "langchain.chains.history_aware_retriever", |
| "HypotheticalDocumentEmbedder": "langchain.chains.hyde.base", |
| "LLMChain": "langchain.chains.llm", |
| "LLMCheckerChain": "langchain.chains.llm_checker.base", |
| "LLMMathChain": "langchain.chains.llm_math.base", |
| "LLMRequestsChain": "langchain_community.chains.llm_requests", |
| "LLMSummarizationCheckerChain": "langchain.chains.llm_summarization_checker.base", |
| "load_chain": "langchain.chains.loading", |
| "MapReduceChain": "langchain.chains.mapreduce", |
| "OpenAIModerationChain": "langchain.chains.moderation", |
| "NatBotChain": "langchain.chains.natbot.base", |
| "create_citation_fuzzy_match_chain": "langchain.chains.openai_functions", |
| "create_citation_fuzzy_match_runnable": "langchain.chains.openai_functions", |
| "create_extraction_chain": "langchain.chains.openai_functions", |
| "create_extraction_chain_pydantic": "langchain.chains.openai_functions", |
| "create_qa_with_sources_chain": "langchain.chains.openai_functions", |
| "create_qa_with_structure_chain": "langchain.chains.openai_functions", |
| "create_tagging_chain": "langchain.chains.openai_functions", |
| "create_tagging_chain_pydantic": "langchain.chains.openai_functions", |
| "QAGenerationChain": "langchain.chains.qa_generation.base", |
| "QAWithSourcesChain": "langchain.chains.qa_with_sources.base", |
| "RetrievalQAWithSourcesChain": "langchain.chains.qa_with_sources.retrieval", |
| "VectorDBQAWithSourcesChain": "langchain.chains.qa_with_sources.vector_db", |
| "create_retrieval_chain": "langchain.chains.retrieval", |
| "RetrievalQA": "langchain.chains.retrieval_qa.base", |
| "VectorDBQA": "langchain.chains.retrieval_qa.base", |
| "LLMRouterChain": "langchain.chains.router", |
| "MultiPromptChain": "langchain.chains.router", |
| "MultiRetrievalQAChain": "langchain.chains.router", |
| "MultiRouteChain": "langchain.chains.router", |
| "RouterChain": "langchain.chains.router", |
| "SequentialChain": "langchain.chains.sequential", |
| "SimpleSequentialChain": "langchain.chains.sequential", |
| "create_sql_query_chain": "langchain.chains.sql_database.query", |
| "create_structured_output_runnable": "langchain.chains.structured_output", |
| "load_summarize_chain": "langchain.chains.summarize", |
| "TransformChain": "langchain.chains.transform", |
| } |
|
|
| importer = create_importer(__package__, module_lookup=_module_lookup) |
|
|
|
|
| def __getattr__(name: str) -> Any: |
| return importer(name) |
|
|
|
|
| __all__ = list(_module_lookup.keys()) |
|
|
