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__init__.py — langchain Source File

Architecture documentation for __init__.py, a python file in the langchain codebase. 2 imports, 0 dependents.

File python AgentOrchestration ClassicChains 2 imports 1 functions

Entity Profile

Dependency Diagram

graph LR
  78ebb5f9_0b46_e00a_5ed1_7ed28f701dbc["__init__.py"]
  feec1ec4_6917_867b_d228_b134d0ff8099["typing"]
  78ebb5f9_0b46_e00a_5ed1_7ed28f701dbc --> feec1ec4_6917_867b_d228_b134d0ff8099
  e4596b95_ed91_0e47_96dd_7e987bc14a69["langchain_classic._api"]
  78ebb5f9_0b46_e00a_5ed1_7ed28f701dbc --> e4596b95_ed91_0e47_96dd_7e987bc14a69
  style 78ebb5f9_0b46_e00a_5ed1_7ed28f701dbc fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

"""**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.
"""

from typing import Any

from langchain_classic._api import create_importer

_module_lookup = {
    "APIChain": "langchain_classic.chains.api.base",
    "OpenAPIEndpointChain": "langchain_community.chains.openapi.chain",
    "AnalyzeDocumentChain": "langchain_classic.chains.combine_documents.base",
    "MapReduceDocumentsChain": "langchain_classic.chains.combine_documents.map_reduce",
    "MapRerankDocumentsChain": "langchain_classic.chains.combine_documents.map_rerank",
    "ReduceDocumentsChain": "langchain_classic.chains.combine_documents.reduce",
    "RefineDocumentsChain": "langchain_classic.chains.combine_documents.refine",
    "StuffDocumentsChain": "langchain_classic.chains.combine_documents.stuff",
    "ConstitutionalChain": "langchain_classic.chains.constitutional_ai.base",
    "ConversationChain": "langchain_classic.chains.conversation.base",
    "ChatVectorDBChain": "langchain_classic.chains.conversational_retrieval.base",
    "ConversationalRetrievalChain": (
        "langchain_classic.chains.conversational_retrieval.base"
    ),
    "generate_example": "langchain_classic.chains.example_generator",
    "FlareChain": "langchain_classic.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_classic.chains.history_aware_retriever"
    ),
    "HypotheticalDocumentEmbedder": "langchain_classic.chains.hyde.base",
    "LLMChain": "langchain_classic.chains.llm",
    "LLMCheckerChain": "langchain_classic.chains.llm_checker.base",
    "LLMMathChain": "langchain_classic.chains.llm_math.base",
    "LLMRequestsChain": "langchain_community.chains.llm_requests",
    "LLMSummarizationCheckerChain": (
        "langchain_classic.chains.llm_summarization_checker.base"
    ),
    "load_chain": "langchain_classic.chains.loading",
    "MapReduceChain": "langchain_classic.chains.mapreduce",
    "OpenAIModerationChain": "langchain_classic.chains.moderation",
    "NatBotChain": "langchain_classic.chains.natbot.base",
    "create_citation_fuzzy_match_chain": "langchain_classic.chains.openai_functions",
    "create_citation_fuzzy_match_runnable": "langchain_classic.chains.openai_functions",
    "create_extraction_chain": "langchain_classic.chains.openai_functions",
    "create_extraction_chain_pydantic": "langchain_classic.chains.openai_functions",
    "create_qa_with_sources_chain": "langchain_classic.chains.openai_functions",
    "create_qa_with_structure_chain": "langchain_classic.chains.openai_functions",
    "create_tagging_chain": "langchain_classic.chains.openai_functions",
    "create_tagging_chain_pydantic": "langchain_classic.chains.openai_functions",
    "QAGenerationChain": "langchain_classic.chains.qa_generation.base",
    "QAWithSourcesChain": "langchain_classic.chains.qa_with_sources.base",
    "RetrievalQAWithSourcesChain": "langchain_classic.chains.qa_with_sources.retrieval",
    "VectorDBQAWithSourcesChain": "langchain_classic.chains.qa_with_sources.vector_db",
    "create_retrieval_chain": "langchain_classic.chains.retrieval",
    "RetrievalQA": "langchain_classic.chains.retrieval_qa.base",
    "VectorDBQA": "langchain_classic.chains.retrieval_qa.base",
    "LLMRouterChain": "langchain_classic.chains.router",
    "MultiPromptChain": "langchain_classic.chains.router",
    "MultiRetrievalQAChain": "langchain_classic.chains.router",
    "MultiRouteChain": "langchain_classic.chains.router",
    "RouterChain": "langchain_classic.chains.router",
    "SequentialChain": "langchain_classic.chains.sequential",
    "SimpleSequentialChain": "langchain_classic.chains.sequential",
    "create_sql_query_chain": "langchain_classic.chains.sql_database.query",
    "create_structured_output_runnable": "langchain_classic.chains.structured_output",
    "load_summarize_chain": "langchain_classic.chains.summarize",
    "TransformChain": "langchain_classic.chains.transform",
}

importer = create_importer(__package__, module_lookup=_module_lookup)


def __getattr__(name: str) -> Any:
    return importer(name)


__all__ = list(_module_lookup.keys())

Domain

Subdomains

Functions

Dependencies

  • langchain_classic._api
  • typing

Source

Frequently Asked Questions

What does __init__.py do?
__init__.py is a source file in the langchain codebase, written in python. It belongs to the AgentOrchestration domain, ClassicChains subdomain.
What functions are defined in __init__.py?
__init__.py defines 1 function(s): __getattr__.
What does __init__.py depend on?
__init__.py imports 2 module(s): langchain_classic._api, typing.
Where is __init__.py in the architecture?
__init__.py is located at libs/langchain/langchain_classic/chains/__init__.py (domain: AgentOrchestration, subdomain: ClassicChains, directory: libs/langchain/langchain_classic/chains).

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