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# Production RAG pipeline from langchain_openai import OpenAIEmbeddings from langchain_pinecone import PineconeVectorStore from langchain_anthropic import ChatAnthropic from langchain.chains import RetrievalQA llm = ChatAnthropic(model="claude-sonnet-4-6") vectorstore = PineconeVectorStore( embedding=OpenAIEmbeddings( model="text-embedding-3-large" ) ) # Grounded, accurate responses chain = RetrievalQA.from_chain_type( llm=llm, retriever=vectorstore.as_retriever( search_kwargs={"k": 8} ), )