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# Source code for langchain.chains.qa_with_sources.retrieval

    """Question-answering with sources over an index."""

    from typing import Any, Dict, List

    from langchain_core.callbacks import (
        AsyncCallbackManagerForChainRun,
        CallbackManagerForChainRun,
    )
    from langchain_core.documents import Document
    from langchain_core.pydantic_v1 import Field
    from langchain_core.retrievers import BaseRetriever

    from langchain.chains.combine_documents.stuff import StuffDocumentsChain
    from langchain.chains.qa_with_sources.base import BaseQAWithSourcesChain

    class RetrievalQAWithSourcesChain(BaseQAWithSourcesChain):
        """Question-answering with sources over an index."""

        retriever: BaseRetriever = Field(exclude=True)
        """Index to connect to."""
        reduce_k_below_max_tokens: bool = False
        """Reduce the number of results to return from store based on tokens limit"""
        max_tokens_limit: int = 3375
        """Restrict the docs to return from store based on tokens,
        enforced only for StuffDocumentChain and if reduce_k_below_max_tokens is to true"""

        def _reduce_tokens_below_limit(self, docs: List[Document]) -> List[Document]:
            num_docs = len(docs)

            if self.reduce_k_below_max_tokens and isinstance(
                self.combine_documents_chain, StuffDocumentsChain
            ):
                tokens = [
                    self.combine_documents_chain.llm_chain._get_num_tokens(doc.page_content)
                    for doc in docs
                ]
                token_count = sum(tokens[:num_docs])
                while token_count > self.max_tokens_limit:
                    num_docs -= 1
                    token_count -= tokens[num_docs]

            return docs[:num_docs]

        def _get_docs(
            self, inputs: Dict[str, Any], *, run_manager: CallbackManagerForChainRun
        ) -> List[Document]:
            question = inputs[self.question_key]
            docs = self.retriever.invoke(
                question, config={"callbacks": run_manager.get_child()}
            )
            return self._reduce_tokens_below_limit(docs)

        async def _aget_docs(
            self, inputs: Dict[str, Any], *, run_manager: AsyncCallbackManagerForChainRun
        ) -> List[Document]:
            question = inputs[self.question_key]
            docs = await self.retriever.ainvoke(
                question, config={"callbacks": run_manager.get_child()}
            )
            return self._reduce_tokens_below_limit(docs)

        @property
        def _chain_type(self) -> str:
            """Return the chain type."""
            return "retrieval_qa_with_sources_chain"