Source code for langchain.chains.retrieval

from __future__ import annotations

from typing import Any, Dict, Union

from langchain_core.retrievers import (
from langchain_core.runnables import Runnable, RunnablePassthrough

[docs]def create_retrieval_chain( retriever: Union[BaseRetriever, Runnable[dict, RetrieverOutput]], combine_docs_chain: Runnable[Dict[str, Any], str], ) -> Runnable: """Create retrieval chain that retrieves documents and then passes them on. Args: retriever: Retriever-like object that returns list of documents. Should either be a subclass of BaseRetriever or a Runnable that returns a list of documents. If a subclass of BaseRetriever, then it is expected that an `input` key be passed in - this is what is will be used to pass into the retriever. If this is NOT a subclass of BaseRetriever, then all the inputs will be passed into this runnable, meaning that runnable should take a dictionary as input. combine_docs_chain: Runnable that takes inputs and produces a string output. The inputs to this will be any original inputs to this chain, a new context key with the retrieved documents, and chat_history (if not present in the inputs) with a value of `[]` (to easily enable conversational retrieval. Returns: An LCEL Runnable. The Runnable return is a dictionary containing at the very least a `context` and `answer` key. Example: .. code-block:: python # pip install -U langchain langchain-community from langchain_community.chat_models import ChatOpenAI from langchain.chains.combine_documents import create_stuff_documents_chain from langchain.chains import create_retrieval_chain from langchain import hub retrieval_qa_chat_prompt = hub.pull("langchain-ai/retrieval-qa-chat") llm = ChatOpenAI() retriever = ... combine_docs_chain = create_stuff_documents_chain( llm, retrieval_qa_chat_prompt ) retrieval_chain = create_retrieval_chain(retriever, combine_docs_chain) chain.invoke({"input": "..."}) """ if not isinstance(retriever, BaseRetriever): retrieval_docs: Runnable[dict, RetrieverOutput] = retriever else: retrieval_docs = (lambda x: x["input"]) | retriever retrieval_chain = ( RunnablePassthrough.assign( context=retrieval_docs.with_config(run_name="retrieve_documents"), ).assign(answer=combine_docs_chain) ).with_config(run_name="retrieval_chain") return retrieval_chain