add chatbot functionality

app.py

@@ -9,6 +9,8 @@ from langchain.prompts import PromptTemplate
 from langchain.chains.question_answering import load_qa_chain
 import streamlit as st
 
+from config import *
+
 confluence_api_key = os.environ["CONFLUENCE_API_KEY"]
 
 if "GOOGLE_API_KEY" not in os.environ:
@@ -34,27 +36,43 @@ llm = ChatGoogleGenerativeAI(model="gemini-1.5-flash-latest")
 vector_store = FAISS.from_texts(chunks, embedding=embeddings)
 vector_store.save_local("faiss_index")
 
-def get_response(query):
+#chat_history = []
+
+def get_response(query, chat_history):
     prompt_template = """
-        Answer the question as detailed as possible from the provided context, make sure to provide all the details, if the answer is not in
-        provided context just say, "answer is not available in the context", don't provide the wrong answer\n\n
+        Answer the question as detailed as possible based on the conversation history and the provided context, make sure to provide all the details, if the answer is not in
+        provided context just say, "I am not able to help. Please contact Platform Support Team at platform_support@email.com", don't provide the wrong answer\n\n
+        Conversation History:\n {chat_history}\n
         Context:\n {context}?\n
         Question: \n{question}\n
 
         Answer:
     """
-    prompt = PromptTemplate(template=prompt_template, input_variables=["context", "question"])
+    prompt = PromptTemplate(template=prompt_template, input_variables=["chat_history", "context", "question"])
     chain = load_qa_chain(llm, chain_type="stuff", prompt=prompt)
     db = FAISS.load_local("faiss_index", embeddings, allow_dangerous_deserialization=True)
     docs = db.similarity_search(query)
-    response =  chain({"input_documents" : docs, "question": query}, return_only_outputs = True)
+    response =  chain({"input_documents" : docs, "question": query, "chat_history": chat_history}, return_only_outputs = True)
     return response["output_text"]
 
 
 if __name__ == '__main__':
     st.set_page_config("Chat with Confluence Page")
     st.header("Chat with Confluence Page using AI")
+    
+    if "messages" not in st.session_state:
+        st.session_state.messages = []
 
-    question = st.text_input("Ask questions related to login and registration")
-    answer = get_response(question)
-    st.write("Reply: ", answer)
+    for message in st.session_state.messages:
+        with st.chat_message(message["role"]):
+            st.markdown(message["content"])
+    
+    if question := st.chat_input("Ask questions related to login and registration"):
+        st.session_state.messages.append({"role": "user", "content": question})
+        with st.chat_message("user"):
+            st.markdown(question)
+        
+        with st.chat_message("assistant"):
+            answer = get_response(question, st.session_state.messages)
+            st.write(answer)
+        st.session_state.messages.append({"role": "assistant", "content": answer})