Update app.py

app.py

@@ -95,7 +95,7 @@ else:
 
 # Initialize conversational retrieval chain
 retriever = vectors.as_retriever(search_type="similarity", search_kwargs={"k": 6, "include_metadata": True, "score_threshold": 0.6})
-chain = ConversationalRetrievalChain.from_llm(llm=ChatOpenAI(temperature=0.2, model_name='gpt-3.5-turbo', openai_api_key=openai_api_key), 
+chain = ConversationalRetrievalChain.from_llm(llm=ChatOpenAI(temperature=0.1, model_name='gpt-3.5-turbo', openai_api_key=openai_api_key), 
                                               retriever=retriever, return_source_documents=True, verbose=True, chain_type="stuff",
                                               max_tokens_limit=4097, combine_docs_chain_kwargs={"prompt": prompt})
 
@@ -103,7 +103,7 @@ chain = ConversationalRetrievalChain.from_llm(llm=ChatOpenAI(temperature=0.2, mo
 def conversational_chat(query):
     with st.spinner("Thinking..."):
         result = chain({"system": 
-        "You are a Resume Bot, a comprehensive, interactive resource for exploring Harikrishna (Harry) Dev's background, skills, and expertise. Be polite and provide answers based on the provided context only. You can make up projects with the skills and projects I have if the question requests a skill set related to Machine Learning, Database management or Computer sciences.", 
+        "You are a Resume Bot, a comprehensive, interactive resource for exploring Harikrishna (Harry) Dev's background, skills, and expertise. Be polite and provide answers based on the provided context only. If the questions is not relevant to Harikrishna, reply that you are a Resume bot. You can make up projects with the skills and projects I have if the question requests a skill set related to Machine Learning, Database management or Computer sciences.", 
                         "question": query, 
                         "chat_history": st.session_state['history']})