Create qa_chain.py

qa_chain.py

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+from langchain_openai import ChatOpenAI
+from langchain.chains import create_retrieval_chain
+from langchain.chains.combine_documents import create_stuff_documents_chain
+from langchain_core.prompts import ChatPromptTemplate
+
+def manabQA(retriever, question):    
+    os.environ["OPENAI_API_KEY"] = os.getenv("OPENAI_API_KEY")
+    # Step 1: Initialize GPT-4o-mini LLM
+    llm = ChatOpenAI(model="gpt-4o-mini", temperature=0)
+    
+    # Step 2: Create system prompt for QA
+    system_prompt = (
+        "You are a helpful assistant. Use the following context to answer the question. "
+        "If you don't know the answer, say so.\n\n"
+        "{context}"
+    )
+    prompt = ChatPromptTemplate.from_messages([
+        ("system", system_prompt),
+        ("human", "{input}")
+    ])
+    
+    # Step 3: Create document chain and full retrieval chain
+    question_answer_chain = create_stuff_documents_chain(llm, prompt)
+    qa_chain = create_retrieval_chain(retriever, question_answer_chain)
+    
+    # Step 4: Ask a question
+    response = qa_chain.invoke({"input": question})
+    return response