Update app.py

app.py

@@ -5,26 +5,25 @@ from langchain_huggingface import HuggingFaceEndpoint
 from langchain_core.prompts import PromptTemplate
 from langchain_core.output_parsers import StrOutputParser
 from transformers import pipeline
-from config import NASA_API_KEY  # Import the NASA API key
+from config import NASA_API_KEY  # Ensure this file exists with your NASA API Key
 
+# Model settings
 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):
-    llm = HuggingFaceEndpoint(
+    return HuggingFaceEndpoint(
         repo_id=model_id,
         max_new_tokens=max_new_tokens,
         temperature=temperature,
-        token=os.getenv("HF_TOKEN")  # Hugging Face token from environment variable
+        token=os.getenv("HF_TOKEN")  # Hugging Face API Token
     )
-    return llm
 
+# Function to get NASA Astronomy Picture of the Day
 def get_nasa_apod():
-    """
-    Fetch NASA Astronomy Picture of the Day (APOD).
-    """
     url = f"https://api.nasa.gov/planetary/apod?api_key={NASA_API_KEY}"
     response = requests.get(url)
     if response.status_code == 200:
@@ -33,35 +32,27 @@ 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):
-    """
-    Analyze sentiment of user input.
-    """
     result = sentiment_analyzer(user_text)[0]
     return result['label']
 
+# Function to predict user intent
 def predict_action(user_text):
-    """
-    Predicts user's intent based on input.
-    """
     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):
-    """
-    Generates a follow-up question to continue the conversation.
-    """
     prompt_text = (
         f"Based on the user's message: '{user_text}', suggest a natural follow-up question "
         "to keep the conversation engaging."
     )
-
     hf = get_llm_hf_inference(max_new_tokens=64, temperature=0.7)
-    chat = hf.invoke(input=prompt_text)
-    
-    return chat.strip()
+    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)
@@ -81,7 +72,6 @@ def get_response(system_message, chat_history, user_text, max_new_tokens=256):
     prompt = PromptTemplate.from_template(
         "[INST] {system_message}\n\nCurrent Conversation:\n{chat_history}\n\nUser: {user_text}.\n [/INST]\nAI:"
     )
-
     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("AI:")[-1]
@@ -97,67 +87,53 @@ def get_response(system_message, chat_history, user_text, max_new_tokens=256):
 
     return response, follow_up, chat_history, None
 
-# Streamlit UI Setup
+# --- Streamlit UI Setup ---
 st.set_page_config(page_title="NASA ChatBot", page_icon="🚀")
 
-st.title("🚀 HAL")
-# Chat Display with Updated Styling
-st.markdown("<div class='container'>", unsafe_allow_html=True)
+st.title("🚀 HAL - Your NASA AI Assistant")
+st.markdown("🌌 *Ask me about space, NASA, and beyond!*")
 
-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>Bot:</strong> {message['content']}</div>", unsafe_allow_html=True)
+# 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?"}]
 
-st.markdown("</div>", unsafe_allow_html=True)
+# Sidebar for chat reset
+if st.sidebar.button("Reset Chat"):
+    st.session_state.chat_history = [{"role": "assistant", "content": "Hello! How can I assist you today?"}]
+    st.experimental_rerun()
 
-# Custom CSS for chat styling
+# Chat Display Styling
 st.markdown("""
     <style>
-    /* Style for chat messages */
     .user-msg {
         background-color: #0078D7; /* Dark Blue */
-        color: white; /* White text for contrast */
+        color: white;
         padding: 10px;
         border-radius: 10px;
         margin-bottom: 5px;
         width: fit-content;
         max-width: 80%;
     }
-
     .assistant-msg {
         background-color: #333333; /* Dark Gray */
-        color: white; /* White text for contrast */
+        color: white;
         padding: 10px;
         border-radius: 10px;
         margin-bottom: 5px;
         width: fit-content;
         max-width: 80%;
     }
-
-    /* Center messages for better appearance */
     .container {
         display: flex;
         flex-direction: column;
         align-items: flex-start;
     }
-
-    /* Adjust messages on mobile */
     @media (max-width: 600px) {
-        .user-msg, .assistant-msg { 
-            font-size: 16px;
-            max-width: 100%;
-        }
+        .user-msg, .assistant-msg { font-size: 16px; max-width: 100%; }
     }
     </style>
 """, unsafe_allow_html=True)
 
-# Initialize chat history
-# Initialize chat history in session state
-if "chat_history" not in st.session_state:
-    st.session_state.chat_history = [{"role": "assistant", "content": "Hello! How can I assist you today?"}]
-
 # Chat Display
 st.markdown("<div class='container'>", unsafe_allow_html=True)
 
@@ -169,21 +145,7 @@ for message in st.session_state.chat_history:
 
 st.markdown("</div>", unsafe_allow_html=True)
 
-
-
-# Sidebar for chat reset
-if st.sidebar.button("Reset Chat"):
-    st.session_state.chat_history = [{"role": "assistant", "content": "Hello! How can I assist you today?"}]
-    st.experimental_rerun()
-
-# Chat display
-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>Bot:</strong> {message['content']}</div>", unsafe_allow_html=True)
-
-# User input
+# User Input Section
 user_input = st.text_area("Type your message:", height=100)
 
 if st.button("Send"):
@@ -201,7 +163,7 @@ if st.button("Send"):
         if image_url:
             st.image(image_url, caption="NASA Image of the Day")
 
-        # Follow-up options
+        # Follow-up question suggestions
         follow_up_options = [follow_up, "Explain differently", "Give me an example"]
         selected_option = st.radio("What would you like to do next?", follow_up_options)