Update app.py

app.py

@@ -7,13 +7,22 @@ from langchain_core.output_parsers import StrOutputParser
 from transformers import pipeline
 from config import NASA_API_KEY  # Ensure this file exists with your NASA API Key
 
-# Model settings
+# Set up Streamlit UI
+st.set_page_config(page_title="HAL - NASA ChatBot", page_icon="🚀")
+
+# --- Ensure Session State Variables are Initialized ---
+if "chat_history" not in st.session_state:
+    st.session_state.chat_history = [{"role": "assistant", "content": "Hello! How can I assist you today?"}]
+
+if "response_ready" not in st.session_state:
+    st.session_state.response_ready = False  # Tracks whether HAL has responded
+
+# --- Set Up Model & API Functions ---
 model_id = "mistralai/Mistral-7B-Instruct-v0.3"
 
 # Initialize sentiment analysis pipeline
 sentiment_analyzer = pipeline("sentiment-analysis")
 
-# Function to initialize Hugging Face model
 def get_llm_hf_inference(model_id=model_id, max_new_tokens=128, temperature=0.1):
     return HuggingFaceEndpoint(
         repo_id=model_id,
@@ -22,7 +31,6 @@ def get_llm_hf_inference(model_id=model_id, max_new_tokens=128, temperature=0.1)
         token=os.getenv("HF_TOKEN")  # Hugging Face API Token
     )
 
-# Function to get NASA Astronomy Picture of the Day
 def get_nasa_apod():
     url = f"https://api.nasa.gov/planetary/apod?api_key={NASA_API_KEY}"
     response = requests.get(url)
@@ -32,18 +40,15 @@ def get_nasa_apod():
     else:
         return "", "NASA Data Unavailable", "I couldn't fetch data from NASA right now. Please try again later."
 
-# Function to analyze sentiment of user input
 def analyze_sentiment(user_text):
     result = sentiment_analyzer(user_text)[0]
     return result['label']
 
-# Function to predict user intent
 def predict_action(user_text):
     if "NASA" in user_text or "space" in user_text:
         return "nasa_info"
     return "general_query"
 
-# Function to generate a follow-up question
 def generate_follow_up(user_text):
     prompt_text = (
         f"Based on the user's message: '{user_text}', suggest a natural follow-up question "
@@ -52,7 +57,6 @@ def generate_follow_up(user_text):
     hf = get_llm_hf_inference(max_new_tokens=64, temperature=0.7)
     return hf.invoke(input=prompt_text).strip()
 
-# Function to process user input and generate a response
 def get_response(system_message, chat_history, user_text, max_new_tokens=256):
     sentiment = analyze_sentiment(user_text)
     action = predict_action(user_text)
@@ -87,26 +91,21 @@ def get_response(system_message, chat_history, user_text, max_new_tokens=256):
 
     return response, follow_up, chat_history, None
 
-# --- Streamlit UI Setup ---
-st.set_page_config(page_title="NASA ChatBot", page_icon="🚀")
-
+# --- Chat UI ---
 st.title("🚀 HAL - Your NASA AI Assistant")
 st.markdown("🌌 *Ask me about space, NASA, and beyond!*")
 
-# Ensure chat history is initialized
-if "chat_history" not in st.session_state:
-    st.session_state.chat_history = [{"role": "assistant", "content": "Hello! How can I assist you today?"}]
-
-# Sidebar for chat reset
+# 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.experimental_rerun()
 
-# Chat Display Styling
+# Custom Chat Styling
 st.markdown("""
     <style>
     .user-msg {
-        background-color: #0078D7; /* Dark Blue */
+        background-color: #0078D7;
         color: white;
         padding: 10px;
         border-radius: 10px;
@@ -115,7 +114,7 @@ st.markdown("""
         max-width: 80%;
     }
     .assistant-msg {
-        background-color: #333333; /* Dark Gray */
+        background-color: #333333;
         color: white;
         padding: 10px;
         border-radius: 10px;
@@ -134,56 +133,47 @@ st.markdown("""
     </style>
 """, unsafe_allow_html=True)
 
-# Chat Display
+# Chat History Display
 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)
 
-# User Input Section
+# --- Input & Button Handling ---
 user_input = st.text_area("Type your message:", height=100)
 
-if st.button("Send"):
-    if user_input:
-        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
-        )
+send_button_placeholder = st.empty()
 
-        # Display response
-        st.markdown(f"<div class='assistant-msg'><strong>HAL:</strong> {response}</div>", unsafe_allow_html=True)
+if not st.session_state.response_ready:
+    if send_button_placeholder.button("Send"):
+        if user_input:
+            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
+            )
 
-        # Display NASA image if available
-        if image_url:
-            st.image(image_url, caption="NASA Image of the Day")
+            st.markdown(f"<div class='assistant-msg'><strong>HAL:</strong> {response}</div>", unsafe_allow_html=True)
 
-        # Display a conversational follow-up message
-        st.markdown(f"<div class='assistant-msg'><strong>HAL:</strong> {follow_up}</div>", unsafe_allow_html=True)
+            if image_url:
+                st.image(image_url, caption="NASA Image of the Day")
 
-        # Provide a text box for the user's next response
-        next_input = st.text_input("HAL is waiting for your response...")
+            st.session_state.response_ready = True  # Hide Send button after response
 
-# If the user enters a follow-up message
-if next_input:
-    response, _, st.session_state.chat_history, _ = get_response(
-        system_message="You are a helpful AI assistant.",
-        user_text=next_input,
-        chat_history=st.session_state.chat_history
-    )
-    st.markdown(f"<div class='assistant-msg'><strong>HAL:</strong> {response}</div>", unsafe_allow_html=True)
+# Conversational Follow-up
+if st.session_state.response_ready:
+    st.markdown(f"<div class='assistant-msg'><strong>HAL:</strong> {follow_up}</div>", unsafe_allow_html=True)
 
+    next_input = st.text_input("HAL is waiting for your response...")
 
-        if st.button("Continue"):
-            if selected_option:
-                response, _, st.session_state.chat_history, _ = get_response(
-                    system_message="You are a helpful AI assistant.",
-                    user_text=selected_option,
-                    chat_history=st.session_state.chat_history
-                )
-                st.markdown(f"<div class='assistant-msg'><strong>HAL:</strong> {response}</div>", unsafe_allow_html=True)
+    if next_input:
+        response, _, st.session_state.chat_history, _ = get_response(
+            system_message="You are a helpful AI assistant.",
+            user_text=next_input,
+            chat_history=st.session_state.chat_history
+        )
+        st.markdown(f"<div class='assistant-msg'><strong>HAL:</strong> {response}</div>", unsafe_allow_html=True)
+        st.session_state.response_ready = False  # Allow new input