Update app.py

app.py

@@ -27,6 +27,18 @@ ANSWER:
 """
 CUSTOM_QUESTION_PROMPT = PromptTemplate.from_template(custom_template)
 
+prompt_template = """<s>[INST]
+You will answer from the provided files stored in knowledge base
+CONTEXT: {context}
+CHAT HISTORY: {chat_history}
+QUESTION: {question}
+ANSWER:
+</s>[INST]
+
+"""
+
+prompt = PromptTemplate(template=prompt_template,
+                        input_variables=['context', 'question', 'chat_history'])
 # Function to extract text from documents
 def get_document_text(uploaded_files):
     documents = []
@@ -62,15 +74,17 @@ def get_vectorstore(chunks):
 
 # Create a conversational chain
 def get_conversationchain(vectorstore):
-    llm = ChatOpenAI(temperature=0.4, model_name='gpt-4o-mini')
+    llm = ChatOpenAI(temperature=0.5, model_name='gpt-4o-mini')
     memory = ConversationBufferMemory(memory_key='chat_history', return_messages=True)
-    return ConversationalRetrievalChain.from_llm(
+    conversation_chain = ConversationalRetrievalChain.from_llm(
         llm=llm,
-        retriever=vectorstore.as_retriever(),
+        retriever=vectorstore.as_retriever(search_type="similarity",search_kwargs={"k": 20}),
         condense_question_prompt=CUSTOM_QUESTION_PROMPT,
-        memory=memory
+        memory=memory,  
+        combine_docs_chain_kwargs={'prompt': prompt}
     )
-
+    return conversation_chain
+    
 # Handle user questions and update chat history
 def handle_question(question):
     if not st.session_state.conversation: