create_extraction_chain() — langchain Function Reference

Architecture documentation for the create_extraction_chain() function in extraction.py from the langchain codebase.

Function python AgentOrchestration ClassicChains calls 1

Entity Profile

AgentOrchestration→ ClassicChains→ create_extraction_chain() — langchain Function Reference

Dependency Diagram

graph TD
  ed29345b_184d_c631_895a_47d9341de245["create_extraction_chain()"]
  f3ae89de_9c39_fe1b_3ede_79ea9e0ed4fe["extraction.py"]
  ed29345b_184d_c631_895a_47d9341de245 -->|defined in| f3ae89de_9c39_fe1b_3ede_79ea9e0ed4fe
  d96ba5e6_9d3c_8107_e3e7_4c1c7394f868["_get_extraction_function()"]
  ed29345b_184d_c631_895a_47d9341de245 -->|calls| d96ba5e6_9d3c_8107_e3e7_4c1c7394f868
  style ed29345b_184d_c631_895a_47d9341de245 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/langchain/langchain_classic/chains/openai_functions/extraction.py lines 76–107

def create_extraction_chain(
    schema: dict,
    llm: BaseLanguageModel,
    prompt: BasePromptTemplate | None = None,
    tags: list[str] | None = None,
    verbose: bool = False,  # noqa: FBT001,FBT002
) -> Chain:
    """Creates a chain that extracts information from a passage.

    Args:
        schema: The schema of the entities to extract.
        llm: The language model to use.
        prompt: The prompt to use for extraction.
        tags: Optional list of tags to associate with the chain.
        verbose: Whether to run in verbose mode. In verbose mode, some intermediate
            logs will be printed to the console.

    Returns:
        Chain that can be used to extract information from a passage.
    """
    function = _get_extraction_function(schema)
    extraction_prompt = prompt or ChatPromptTemplate.from_template(_EXTRACTION_TEMPLATE)
    output_parser = JsonKeyOutputFunctionsParser(key_name="info")
    llm_kwargs = get_llm_kwargs(function)
    return LLMChain(
        llm=llm,
        prompt=extraction_prompt,
        llm_kwargs=llm_kwargs,
        output_parser=output_parser,
        tags=tags,
        verbose=verbose,
    )