Migration Phase 5: Web interface implementation

app.py

@@ -4,38 +4,22 @@ from dotenv import load_dotenv
 from agent.graph import app
 from agent.state import AgentState
 
+
 load_dotenv()
 
-st.set_page_config(page_title="AutoStream AI Sales Assistant", page_icon="🎬", layout="centered")
 
-# Custom CSS for minimalist, cooler UI
+st.set_page_config(page_title="AutoStream AI Sales Assistant", page_icon="🤖", layout="centered")
+
+
 st.markdown("""
 <style>
     .stChatFloatingInputContainer {
         bottom: 20px;
     }
-    .main {
-        background-color: #0E1117;
-    }
-    h1 {
-        color: #E2E8F0;
-        font-family: 'Helvetica Neue', Helvetica, Arial, sans-serif;
-        font-weight: 700;
-        text-align: center;
-        margin-bottom: 2rem;
-    }
-    .subtitle {
-        color: #94A3B8;
-        text-align: center;
-        margin-bottom: 2rem;
-        font-size: 1.1rem;
-    }
-    .stAlert {
-        border-radius: 8px;
-    }
 </style>
 """, unsafe_allow_html=True)
 
+
 if "messages" not in st.session_state:
     st.session_state.messages = []
 
@@ -51,43 +35,54 @@ if "messages" not in st.session_state:
         response=""
     )
 
+
     st.session_state.messages.append({"role": "assistant", "content": "Hello! I'm the AutoStream assistant. I can answer questions about our features and pricing. How can I help you today?"})
 
-st.markdown("<h1>🎬 AutoStream Assistant</h1>", unsafe_allow_html=True)
-st.markdown("<div class='subtitle'>Ask about features and pricing, or sign up for a plan instantly!</div>", unsafe_allow_html=True)
 
 if not os.environ.get("OPENAI_API_KEY"):
-    st.info("ℹ️ OPENAI_API_KEY is not set. The system will fall back to a local Qwen model and HuggingFace embeddings.")
+    st.warning("⚠️ OPENAI_API_KEY is not set. Please set it in your environment to use the agent.")
+
+st.title("🤖 AutoStream AI Sales Assistant")
+st.markdown("Ask me about AutoStream features and pricing, or sign up for a plan!")
+
 
 for message in st.session_state.messages:
     with st.chat_message(message["role"]):
         st.markdown(message["content"])
 
+
 if prompt := st.chat_input("What would you like to know?"):
 
     st.session_state.messages.append({"role": "user", "content": prompt})
     with st.chat_message("user"):
         st.markdown(prompt)
 
+
     st.session_state.agent_state["current_message"] = prompt
 
+
     with st.chat_message("assistant"):
         with st.spinner("Thinking..."):
             try:
+
                 result_state = app.invoke(st.session_state.agent_state)
                 st.session_state.agent_state = result_state
 
                 response = result_state["response"]
 
+
                 st.session_state.agent_state["conversation_history"].append({"role": "user", "content": prompt})
                 st.session_state.agent_state["conversation_history"].append({"role": "assistant", "content": response})
 
+
                 if len(st.session_state.agent_state["conversation_history"]) > 12:
                     st.session_state.agent_state["conversation_history"] = st.session_state.agent_state["conversation_history"][-12:]
 
+
                 st.markdown(response)
 
-                with st.expander("Agent Reasoning & State", expanded=False):
+
+                with st.expander("Agent Reasoning & State"):
                     st.write(f"**Detected Intent:** `{result_state.get('detected_intent', 'UNKNOWN')}`")
                     if result_state.get("retrieved_documents") and result_state.get("detected_intent") in ["PRODUCT_QUERY", "PRICING_QUERY"]:
                         st.write(f"**RAG Retrieval:** Found {len(result_state['retrieved_documents'])} relevant knowledge chunks.")
@@ -104,4 +99,5 @@ if prompt := st.chat_input("What would you like to know?"):
                 response = f"An error occurred: {str(e)}"
                 st.error(response)
 
+
     st.session_state.messages.append({"role": "assistant", "content": response})