Update app.py

app.py

@@ -8,10 +8,52 @@ from langchain_core.prompts import PromptTemplate
 from langchain_core.output_parsers import StrOutputParser
 from transformers import pipeline
 
-# Must be the very first command!
+# Must be the first Streamlit command!
 st.set_page_config(page_title="HAL - NASA ChatBot", page_icon="🚀")
 
-# Appearance adjustments (if any) could be added here as well
+# Appearance settings (optional): you can modify these as needed
+user_bg_color = "#0078D7"
+assistant_bg_color = "#333333"
+text_color = "#FFFFFF"
+font_choice = "sans serif"
+
+# Inject custom CSS for appearance
+custom_css = f"""
+<style>
+    .user-msg {{
+        background-color: {user_bg_color};
+        color: {text_color};
+        padding: 10px;
+        border-radius: 10px;
+        margin-bottom: 5px;
+        width: fit-content;
+        max-width: 80%;
+        font-family: {font_choice};
+    }}
+    .assistant-msg {{
+        background-color: {assistant_bg_color};
+        color: {text_color};
+        padding: 10px;
+        border-radius: 10px;
+        margin-bottom: 5px;
+        width: fit-content;
+        max-width: 80%;
+        font-family: {font_choice};
+    }}
+    .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>
+"""
+st.markdown(custom_css, unsafe_allow_html=True)
 
 # Initialize session state variables
 if "chat_history" not in st.session_state:
@@ -21,9 +63,17 @@ if "response_ready" not in st.session_state:
 if "follow_up" not in st.session_state:
     st.session_state.follow_up = ""
 if "saved_conversations" not in st.session_state:
-    st.session_state.saved_conversations = {}  # Dictionary: conv_id -> chat_history
+    st.session_state.saved_conversations = {}  # dict mapping conv_id -> chat_history
 
-# --- Set Up Model & API Functions ---
+# Set up keys from environment variables
+HF_TOKEN = os.getenv("HF_TOKEN")
+if not HF_TOKEN:
+    raise ValueError("HF_TOKEN environment variable not set.")
+NASA_API_KEY = os.getenv("NASA_API_KEY")
+if not NASA_API_KEY:
+    raise ValueError("NASA_API_KEY environment variable not set.")
+
+# --- Model & API functions ---
 model_id = "mistralai/Mistral-7B-Instruct-v0.3"
 sentiment_analyzer = pipeline(
     "sentiment-analysis",
@@ -36,34 +86,31 @@ def get_llm_hf_inference(model_id=model_id, max_new_tokens=128, temperature=0.7)
         repo_id=model_id,
         max_new_tokens=max_new_tokens,
         temperature=temperature,
-        token=os.getenv("HF_TOKEN"),
+        token=HF_TOKEN,
         task="text-generation"
     )
 
 def get_nasa_apod():
-    url = f"https://api.nasa.gov/planetary/apod?api_key={os.getenv('NASA_API_KEY')}"
+    url = f"https://api.nasa.gov/planetary/apod?api_key={NASA_API_KEY}"
     response = requests.get(url)
     if response.status_code == 200:
         data = response.json()
         return data.get("url", ""), data.get("title", ""), data.get("explanation", "")
     else:
-        return "", "NASA Data Unavailable", "I couldn't fetch data from NASA right now. Please try again later."
+        return "", "NASA Data Unavailable", "I couldn't fetch data from NASA right now."
 
 def analyze_sentiment(user_text):
     result = sentiment_analyzer(user_text)[0]
     return result['label']
 
 def predict_action(user_text):
-    if "NASA" in user_text or "space" in user_text:
-        return "nasa_info"
-    return "general_query"
+    return "nasa_info" if ("nasa" in user_text.lower() or "space" in user_text.lower()) else "general_query"
 
 def generate_follow_up(user_text):
     prompt_text = (
-        f"Based on the user's question: '{user_text}', generate two concise, friendly follow-up questions "
-        "that invite further discussion. For example, one variant might ask, "
-        "'Would you like to know more about the six types of quarks?' and another might ask, "
-        "'Would you like to explore another aspect of quantum physics?'. Do not include extra commentary."
+        f"Based on the user's question: '{user_text}', generate two concise, friendly follow-up questions that invite further discussion. "
+        "For example, one could be 'Would you like to know more about the six types of quarks?' and another 'Would you like to explore another aspect of quantum physics?'. "
+        "Return only the questions, separated by a newline."
     )
     hf = get_llm_hf_inference(max_new_tokens=80, temperature=0.9)
     output = hf.invoke(input=prompt_text).strip()
@@ -84,6 +131,7 @@ def get_response(system_message, chat_history, user_text, max_new_tokens=256):
             style_instruction = match.group(2).strip().capitalize()
             style_instruction = f" Please respond in the voice of {style_instruction}."
     
+    # Handle NASA queries separately
     if action == "nasa_info":
         nasa_url, nasa_title, nasa_explanation = get_nasa_apod()
         response = f"**{nasa_title}**\n\n{nasa_explanation}"
@@ -92,7 +140,7 @@ def get_response(system_message, chat_history, user_text, max_new_tokens=256):
         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)
     filtered_history = ""
     for message in chat_history:
@@ -101,60 +149,51 @@ def get_response(system_message, chat_history, user_text, max_new_tokens=256):
         filtered_history += f"{message['role']}: {message['content']}\n"
     
     style_clause = style_instruction if style_instruction else ""
-    
     prompt = PromptTemplate.from_template(
         (
             "[INST] {system_message}\n\nCurrent Conversation:\n{chat_history}\n\n"
             "User: {user_text}.\n [/INST]\n"
-            "AI: Please answer the user's question in depth in a friendly, conversational tone, starting with a phrase like "
-            "'Certainly!', 'Of course!', or 'Great question!'." + style_clause +
+            "AI: Please provide a detailed, in-depth answer in a friendly, conversational tone. "
+            "Begin with a phrase like 'Certainly!', 'Of course!', or 'Great question!'." + style_clause +
             "\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=filtered_history))
     response = response.split("HAL:")[-1].strip()
-    
     if not response:
         response = "Certainly, here is an in-depth explanation: [Fallback explanation]."
-    
     chat_history.append({'role': 'user', 'content': user_text})
     chat_history.append({'role': 'assistant', 'content': response})
-    
     if sentiment == "NEGATIVE" and not user_text.strip().endswith("?"):
         response = "I'm sorry you're feeling this way. I'm here to help. What can I do to assist you further?"
         chat_history[-1]['content'] = response
-    
     follow_up = generate_follow_up(user_text)
     chat_history.append({'role': 'assistant', 'content': follow_up})
-    
     return response, follow_up, chat_history, None
 
-# --- Sidebar: Saved Conversations ---
-#st.sidebar.header("Saved Conversations")
-#if st.sidebar.button("Save Current Conversation"):
-    #conv_id = f"Conv {len(st.session_state.saved_conversations) + 1}"
-    # Save a copy of the current conversation history
-    #st.session_state.saved_conversations[conv_id] = st.session_state.chat_history.copy()
-    #st.sidebar.success(f"Conversation saved as {conv_id}.")
-
-# Display saved conversation links
-#if st.session_state.saved_conversations:
-    #for conv_id in st.session_state.saved_conversations:
-        #if st.sidebar.button(f"Load {conv_id}"):
-            #st.session_state.chat_history = st.session_state.saved_conversations[conv_id].copy()
-            #st.sidebar.info(f"Loaded {conv_id}.")
-
-# --- Chat UI Rendering ---
+# --- Sidebar: Save/Load Conversations ---
+st.sidebar.header("Saved Conversations")
+if st.sidebar.button("Save Current Conversation"):
+    conv_id = f"Conv {len(st.session_state.saved_conversations) + 1}"
+    st.session_state.saved_conversations[conv_id] = st.session_state.chat_history.copy()
+    st.sidebar.success(f"Conversation saved as {conv_id}.")
+    
+if st.session_state.saved_conversations:
+    for conv_id in st.session_state.saved_conversations:
+        if st.sidebar.button(f"Load {conv_id}"):
+            st.session_state.chat_history = st.session_state.saved_conversations[conv_id].copy()
+            st.sidebar.info(f"Loaded {conv_id}.")
+
+# --- Main Chat UI ---
 st.title("🚀 HAL - Your NASA AI Assistant")
 st.markdown("🌌 *Ask me about space, NASA, and beyond!*")
 
-#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.experimental_rerun()
+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.experimental_rerun()
 
 st.markdown("<div class='container'>", unsafe_allow_html=True)
 for message in st.session_state.chat_history: