Create components/chat.py

components/chat.py

@@ -0,0 +1,38 @@
+# src/components/chat.py
+import streamlit as st
+from langchain.schema import HumanMessage, AIMessage
+
+def format_chat_history(chat_history):
+    """Format chat history for QA system"""
+    formatted_history = []
+    for msg in chat_history[:-1]:
+        if isinstance(msg, HumanMessage):
+            formatted_history.append({"role": "user", "content": msg.content})
+        else:
+            formatted_history.append({"role": "assistant", "content": msg.content})
+    return formatted_history
+
+def display_chat_interface():
+    """Display chat interface component"""
+    st.markdown("### 💬 RFP Analysis Chat")
+    
+    for message in st.session_state.chat_history:
+        if isinstance(message, HumanMessage):
+            st.markdown(f"🧑‍💼 **You**: {message.content}")
+        else:
+            st.markdown(f"🤖 **Assistant**: {message.content}")
+    
+    if prompt := st.chat_input("Ask about the RFPs..."):
+        st.session_state.chat_history.append(HumanMessage(content=prompt))
+        
+        try:
+            with st.spinner("Analyzing documents..."):
+                formatted_history = format_chat_history(st.session_state.chat_history)
+                response = st.session_state.qa_system.invoke({
+                    "input": prompt,
+                    "chat_history": formatted_history
+                })
+            
+            st.session_state.chat_history.append(AIMessage(content=response["output"]))
+        except Exception as e:
+            st.error(f"Error generating response: {e}")