Update app.py

app.py

@@ -1,51 +1,83 @@
 import os
-from langchain_huggingface import HuggingFaceEndpoint
+import requests
 import streamlit as st
+from langchain_huggingface import HuggingFaceEndpoint
 from langchain_core.prompts import PromptTemplate
 from langchain_core.output_parsers import StrOutputParser
-import requests
-from config import NASA_API_KEY  # Import the NASA API key from the configuration file
+from transformers import pipeline
+from config import NASA_API_KEY  # Ensure this file exists with your NASA API Key
+
+# 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
+
+if "follow_up" not in st.session_state:
+    st.session_state.follow_up = ""  # Stores follow-up question
+
+# --- Set Up Model & API Functions ---
 model_id = "mistralai/Mistral-7B-Instruct-v0.3"
 
+# Initialize sentiment analysis pipeline
+sentiment_analyzer = pipeline("sentiment-analysis")
+
 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
 
 def get_nasa_apod():
-    """
-    Fetch the Astronomy Picture of the Day (APOD) from the NASA API.
-    """
     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 f"Title: {data['title']}\nExplanation: {data['explanation']}\nURL: {data['url']}"
+        return data.get("url", ""), data.get("title", ""), data.get("explanation", "")
     else:
-        return "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. Please try again later."
+
+def analyze_sentiment(user_text):
+    result = sentiment_analyzer(user_text)[0]
+    return result['label']
 
-def get_response(system_message, chat_history, user_text, 
-                 eos_token_id=['User'], max_new_tokens=256, get_llm_hf_kws={}):
+def predict_action(user_text):
     if "NASA" in user_text or "space" in user_text:
-        nasa_response = get_nasa_apod()
+        return "nasa_info"
+    return "general_query"
+
+def generate_follow_up(user_text):
+    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)
+    return hf.invoke(input=prompt_text).strip()
+
+def get_response(system_message, chat_history, user_text, max_new_tokens=256):
+    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': nasa_response})
-        return nasa_response, chat_history
+        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=0.1)
 
     prompt = PromptTemplate.from_template(
-        (
-            "[INST] {system_message}"
-            "\nCurrent Conversation:\n{chat_history}\n\n"
-            "\nUser: {user_text}.\n [/INST]"
-            "\nAI:"
-        )
+        "[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))
@@ -53,31 +85,91 @@ def get_response(system_message, chat_history, user_text,
 
     chat_history.append({'role': 'user', 'content': user_text})
     chat_history.append({'role': 'assistant', 'content': response})
-    return response, chat_history
 
-# Streamlit setup
-st.set_page_config(page_title="HuggingFace ChatBot", page_icon="🤗")
-st.title("NASA Personal Assistant")
-st.markdown(f"*This chatbot uses {model_id} and NASA's APIs to provide information and responses.*")
+    if sentiment == "NEGATIVE":
+        response += "\n😞 I'm sorry to hear that. How can I assist you further?"
 
-# Initialize 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?"}]
-    
-# Sidebar for settings
+    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.experimental_rerun()
+
+# 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
+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...")  # Only ONE chat_input()
 
-# Main chat interface
-user_input = st.chat_input(placeholder="Type your message here...")
 if user_input:
-    response, st.session_state.chat_history = get_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,
-        max_new_tokens=128
+        chat_history=st.session_state.chat_history
     )
-    # Display messages
-    for message in st.session_state.chat_history:
-        st.chat_message(message["role"]).write(message["content"])
 
+    # Display HAL's response
+    st.markdown(f"<div class='assistant-msg'><strong>HAL:</strong> {response}</div>", unsafe_allow_html=True)
+
+    # Display NASA image if available
+    if image_url:
+        st.image(image_url, caption="NASA Image of the Day")
+
+    # Store follow-up question in session state
+    st.session_state.follow_up = follow_up
+    st.session_state.response_ready = True  # Enables follow-up response cycle
+
+# Display follow-up question inside chat if available
+if st.session_state.response_ready and 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)
+
+    # Reset response state so user can type next input
+    st.session_state.response_ready = False