Source code for langchain_community.retrievers.remote_retriever

from typing import List, Optional

import aiohttp
import requests
from langchain_core.callbacks import (
    AsyncCallbackManagerForRetrieverRun,
    CallbackManagerForRetrieverRun,
)
from langchain_core.documents import Document
from langchain_core.retrievers import BaseRetriever


[docs]class RemoteLangChainRetriever(BaseRetriever): """`LangChain API` retriever.""" url: str """URL of the remote LangChain API.""" headers: Optional[dict] = None """Headers to use for the request.""" input_key: str = "message" """Key to use for the input in the request.""" response_key: str = "response" """Key to use for the response in the request.""" page_content_key: str = "page_content" """Key to use for the page content in the response.""" metadata_key: str = "metadata" """Key to use for the metadata in the response.""" def _get_relevant_documents( self, query: str, *, run_manager: CallbackManagerForRetrieverRun ) -> List[Document]: response = requests.post( self.url, json={self.input_key: query}, headers=self.headers ) result = response.json() return [ Document( page_content=r[self.page_content_key], metadata=r[self.metadata_key] ) for r in result[self.response_key] ] async def _aget_relevant_documents( self, query: str, *, run_manager: AsyncCallbackManagerForRetrieverRun ) -> List[Document]: async with aiohttp.ClientSession() as session: async with session.request( "POST", self.url, headers=self.headers, json={self.input_key: query} ) as response: result = await response.json() return [ Document( page_content=r[self.page_content_key], metadata=r[self.metadata_key] ) for r in result[self.response_key] ]