= "What did the president say about Justice Breyer"chain({"input_documents": docs, "question": query}, return_only_outputs=True)    {'output_text': ' The president thanked Justice Breyer for his service.\nSOURCES: 30-pl'}PreviousText splitting by headerNextRAG using local modelsPrepare DataQuickstartThe stuff ChainThe map_reduce ChainThe refine ChainThe map-rerank ChainDocument QA with sourcesCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.
Here we walk through how to use LangChain for question answering over a list of documents. Under the hood we'll be using our Document chains.
Here we walk through how to use LangChain for question answering over a list of documents. Under the hood we'll be using our Document chains. ->: = "What did the president say about Justice Breyer"chain({"input_documents": docs, "question": query}, return_only_outputs=True)    {'output_text': ' The president thanked Justice Breyer for his service.\nSOURCES: 30-pl'}PreviousText splitting by headerNextRAG using local modelsPrepare DataQuickstartThe stuff ChainThe map_reduce ChainThe refine ChainThe map-rerank ChainDocument QA with sourcesCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.