qa_chain.py

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