Source code for langchain.chains.combine_documents.refine
"""Combine documents by doing a first pass and then refining on more documents."""
from __future__ import annotations
from typing import Any, Dict, List, Tuple
from langchain.callbacks.manager import Callbacks
from langchain.chains.combine_documents.base import (
    BaseCombineDocumentsChain,
)
from langchain.chains.llm import LLMChain
from langchain.docstore.document import Document
from langchain.prompts.prompt import PromptTemplate
from langchain.pydantic_v1 import Extra, Field, root_validator
from langchain.schema import BasePromptTemplate, format_document
def _get_default_document_prompt() -> PromptTemplate:
    return PromptTemplate(input_variables=["page_content"], template="{page_content}")
[docs]class RefineDocumentsChain(BaseCombineDocumentsChain):
    """Combine documents by doing a first pass and then refining on more documents.
    This algorithm first calls `initial_llm_chain` on the first document, passing
    that first document in with the variable name `document_variable_name`, and
    produces a new variable with the variable name `initial_response_name`.
    Then, it loops over every remaining document. This is called the "refine" step.
    It calls `refine_llm_chain`,
    passing in that document with the variable name `document_variable_name`
    as well as the previous response with the variable name `initial_response_name`.
    Example:
        .. code-block:: python
            from langchain.chains import RefineDocumentsChain, LLMChain
            from langchain.prompts import PromptTemplate
            from langchain.llms import OpenAI
            # This controls how each document will be formatted. Specifically,
            # it will be passed to `format_document` - see that function for more
            # details.
            document_prompt = PromptTemplate(