Update app.py

app.py

@@ -63,137 +63,4 @@ def generate_follow_up(user_text):
         f"Given the user's question: '{user_text}', generate a single friendly follow-up question. "
         "Make it short, conversational, and natural—like a human would ask. "
         "Example: If the user asks 'What is a quark?', respond with something like "
-        "'Would you like to learn about the six types of quarks?' "
-        "Do NOT include phrases like 'A natural follow-up question could be'."
-    )
-
-    hf = get_llm_hf_inference(max_new_tokens=32, temperature=0.7)
-    return hf.invoke(input=prompt_text).strip()
-
-def get_response(system_message, chat_history, user_text, max_new_tokens=256):
-    """
-    Generates HAL's response, making it more conversational and engaging.
-    """
-    sentiment = analyze_sentiment(user_text)
-    action = predict_action(user_text)
-
-    if action == "nasa_info":
-        nasa_url, nasa_title, nasa_explanation = get_nasa_apod()
-        response = f"**{nasa_title}**\n\n{nasa_explanation}"
-        chat_history.append({'role': 'user', 'content': user_text})
-        chat_history.append({'role': 'assistant', 'content': response})
-        
-        follow_up = generate_follow_up(user_text)
-        chat_history.append({'role': 'assistant', 'content': follow_up})
-        return response, follow_up, chat_history, nasa_url
-
-    hf = get_llm_hf_inference(max_new_tokens=max_new_tokens, temperature=0.9)
-
-    prompt = PromptTemplate.from_template(
-        (
-            "[INST] {system_message}"
-            "\nCurrent Conversation:\n{chat_history}\n\n"
-            "\nUser: {user_text}.\n [/INST]"
-            "\nAI: Keep responses conversational and engaging. Start with a friendly phrase like "
-            "'Certainly!', 'Of course!', or 'Great question!' before answering."
-            " Keep responses concise but engaging."
-            "\nHAL:"
-        )
-    )
-
-    chat = prompt | hf.bind(skip_prompt=True) | StrOutputParser(output_key='content')
-    response = chat.invoke(input=dict(system_message=system_message, user_text=user_text, chat_history=chat_history))
-    response = response.split("HAL:")[-1].strip()
-
-    chat_history.append({'role': 'user', 'content': user_text})
-    chat_history.append({'role': 'assistant', 'content': response})
-
-    follow_up = generate_follow_up(user_text)
-    chat_history.append({'role': 'assistant', 'content': follow_up})
-
-    return response, follow_up, chat_history, None
-
-# --- Chat UI ---
-st.title("🚀 HAL - Your NASA AI Assistant")
-st.markdown("🌌 *Ask me about space, NASA, and beyond!*")
-
-# Sidebar: Reset Chat
-if st.sidebar.button("Reset Chat"):
-    st.session_state.chat_history = [{"role": "assistant", "content": "Hello! How can I assist you today?"}]
-    st.session_state.response_ready = False
-    st.session_state.follow_up = ""
-    st.session_state.last_topic = ""
-    st.rerun()  # ✅ Correct method to reset the app in newer Streamlit versions
-
-
-# Custom Chat Styling
-st.markdown("""
-    <style>
-    .user-msg {
-        background-color: #0078D7;
-        color: white;
-        padding: 10px;
-        border-radius: 10px;
-        margin-bottom: 5px;
-        width: fit-content;
-        max-width: 80%;
-    }
-    .assistant-msg {
-        background-color: #333333;
-        color: white;
-        padding: 10px;
-        border-radius: 10px;
-        margin-bottom: 5px;
-        width: fit-content;
-        max-width: 80%;
-    }
-    .container {
-        display: flex;
-        flex-direction: column;
-        align-items: flex-start;
-    }
-    @media (max-width: 600px) {
-        .user-msg, .assistant-msg { font-size: 16px; max-width: 100%; }
-    }
-    </style>
-""", unsafe_allow_html=True)
-
-# --- Chat History Display (Ensures All Messages Are Visible) ---
-st.markdown("<div class='container'>", unsafe_allow_html=True)
-
-for message in st.session_state.chat_history:
-    if message["role"] == "user":
-        st.markdown(f"<div class='user-msg'><strong>You:</strong> {message['content']}</div>", unsafe_allow_html=True)
-    else:
-        st.markdown(f"<div class='assistant-msg'><strong>HAL:</strong> {message['content']}</div>", unsafe_allow_html=True)
-
-st.markdown("</div>", unsafe_allow_html=True)
-
-# --- Single Input Box for Both Initial and Follow-Up Messages ---
-user_input = st.chat_input("Type your message here...")  # Uses Enter to submit
-
-if user_input:
-    # Save user message in chat history
-    st.session_state.chat_history.append({'role': 'user', 'content': user_input})  
-
-    # Generate HAL's response
-    response, follow_up, st.session_state.chat_history, image_url = get_response(
-        system_message="You are a helpful AI assistant.",
-        user_text=user_input,
-        chat_history=st.session_state.chat_history
-    )
-
-    st.session_state.chat_history.append({'role': 'assistant', 'content': response})
-
-    st.markdown(f"<div class='assistant-msg'><strong>HAL:</strong> {response}</div>", unsafe_allow_html=True)
-
-    if image_url:
-        st.image(image_url, caption="NASA Image of the Day")
-
-    st.session_state.follow_up = follow_up
-    st.session_state.response_ready = True  # Enables follow-up response cycle
-
-if st.session_state.response_ready and st.session_state.follow_up:
-    st.session_state.chat_history.append({'role': 'assistant', 'content': st.session_state.follow_up})
-    st.markdown(f"<div class='assistant-msg'><strong>HAL:</strong> {st.session_state.follow_up}</div>", unsafe_allow_html=True)
-    st.session_state.response_ready = False
+        "'Would