Update src/streamlit_app.py

src/streamlit_app.py

@@ -115,15 +115,32 @@ agent = create_deep_agent(
     system_prompt=research_instructions,
 )
 
-# --- Streamlit Chat UI ---
-st.title("🧠 Deep Research Agent")
-st.caption(f"Running on: **{provider}** backend")
-
+# Initialize chat history
+if "messages" not in st.session_state:
+    st.session_state["messages"] = [
+        {"role": "assistant", "content": "Hello! I’m your Deep Research Agent. What would you like to explore today?"}
+    ]
+
+# Display chat history
+for msg in st.session_state.messages:
+    with st.chat_message(msg["role"]):
+        st.markdown(msg["content"])
+
+# --- Chat Input ---
 if prompt := st.chat_input("Ask your research question..."):
+    # Save user message
+    st.session_state.messages.append({"role": "user", "content": prompt})
     st.chat_message("user").write(prompt)
+
+    # Process assistant response
     with st.chat_message("assistant"):
         st_callback = StreamlitCallbackHandler(st.container())
-        response = agent.invoke({"messages": [{"role": "user", "content": prompt}]},{"callbacks": [st_callback]})
-        displayed_response = response["messages"][-1].content
-        #output = response.get("output", str(response))
-        st.write(displayed_response)
+        response = agent.invoke(
+            {"messages": st.session_state.messages},
+            {"callbacks": [st_callback]},
+        )
+
+        # Extract and display assistant reply
+        reply = response["messages"][-1].content
+        st.markdown(reply)
+        st.session_state.messages.append({"role": "assistant", "content": reply})