Update QnA.py

QnA.py

@@ -1,16 +1,20 @@
-from langchain.chains import RetrievalQA
+from langchain.chains.combine_documents import create_stuff_documents_chain
+from langchain_core.prompts import ChatPromptTemplate
+from langchain.chains import create_retrieval_chain
+
 #from Api_Key import google_plam
-from langchain.llms import GooglePalm
+from langchain_groq import ChatGroq
 import os
 from dotenv import load_dotenv
 load_dotenv()
-os.getenv("GOOGLE_API_KEY")
-google_plam = os.getenv("GOOGLE_API_KEY")
-
 
-def Q_A(vectorstore,question):
-    google_llm = GooglePalm(google_api_key=google_plam, temperature=0.5)
-    qa = RetrievalQA.from_chain_type(llm=google_llm, chain_type="stuff", retriever=vectorstore.as_retriever())
-    answer = qa.run(question)
 
-    return answer
+def Q_A(vectorstore,question,API_KEY):
+    os.environ["GROQ_API_KEY"] = API_KEY
+    llm_groq = ChatGroq(model="llama3-8b-8192")
+    # Create a retriever
+    retriever = vectorstore.as_retriever(search_type = 'similarity',search_kwargs = {'k':2},)
+    question_answer_chain = create_stuff_documents_chain(llm_groq, prompt_template_to_analyze_resume())
+    chain = create_retrieval_chain(retriever, question_answer_chain)
+    result = chain.invoke({'input':question})
+    return result['answer']