from langchain.document_loaders import PyPDFLoader from langchain.text_splitter import RecursiveCharacterTextSplitter from langchain_openai import OpenAIEmbeddings, ChatOpenAI from langchain_community.vectorstores import Chroma from langchain.chains import RetrievalQA loader = PyPDFLoader("company_policy.pdf") documents = loader.load() splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200) chunks = splitter.split_documents(documents) embeddings = OpenAIEmbeddings() vectorstore = Chroma.from_documents(chunks, embeddings, persist_directory="./chroma_db") llm = ChatOpenAI(model_name="gpt-4", temperature=0) qa = RetrievalQA.from_chain_type( llm=llm, retriever=vectorstore.as_retriever(search_kwargs={"k": 4}), return_source_documents=True, ) result = qa.invoke({"query": "What is the refund policy?"}) print(result["result"])