Update app.py

app.py

@@ -1,50 +1,82 @@
-import gradio as gr
 import google.generativeai as genai
+from dotenv import load_dotenv
+import logging
 import os
+import requests
+from bs4 import BeautifulSoup
+import time
 from datetime import datetime
+import gradio as gr
+
+# ==========================================
+# 1. SETUP & CONFIGURATION
+# ==========================================
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(message)s')
+logger = logging.getLogger(__name__)
+
+load_dotenv()
+api_key = os.getenv("GEMINI_API_KEY")
+
+# Emergency Fallback (If env fails)
+if not api_key:
+    # api_key = "PASTE_YOUR_KEY_HERE" 
+    pass
+
+try:
+    genai.configure(api_key=api_key)
+except Exception as e:
+    print(f"⚠️ Key Error: {e}")
+
+# ==========================================
+# 2. THE WEB SCRAPER (Working Perfectly)
+# ==========================================
+def fetch_nielit_live_data():
+    target_urls = [
+        "https://nielit.ac.in/",
+        "https://www.nielit.gov.in/chandigarh/index.php"
+    ]
+    
+    knowledge = f"### LIVE NIELIT DATA ({datetime.now().strftime('%Y-%m-%d')}) ###\n"
+    headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36'}
+    
+    print("⚡ SCANNING WEBSITES...")
+    
+    for url in target_urls:
+        try:
+            print(f"   Reading: {url}...")
+            resp = requests.get(url, headers=headers, timeout=10)
+            if resp.status_code == 200:
+                soup = BeautifulSoup(resp.content, 'html.parser')
+                for bad in soup(["script", "style", "nav", "footer"]):
+                    bad.extract()
+                text = ' '.join(soup.get_text(separator=' ', strip=True).split())
+                knowledge += f"\n--- SOURCE: {url} ---\n{text[:8000]}\n"
+        except:
+            pass # Skip failed sites to prevent crashes
+            
+    return knowledge
+
+# ==========================================
+# 3. INITIALIZATION
+# ==========================================
+print("\n🚀 STARTING BOT...")
+nielit_data = fetch_nielit_live_data()
 
-# Configure Gemini API
-GEMINI_API_KEY = os.environ.get("GEMINI_API_KEY")
-if GEMINI_API_KEY:
-    genai.configure(api_key=GEMINI_API_KEY)
-
-# NIELIT University Information
-NIELIT_INFO = """
-You are an AI assistant for NIELIT (National Institute of Electronics & Information Technology) Deemed to be University. 
-
-NIELIT UNIVERSITY INFORMATION:
-- NIELIT is an autonomous scientific society under the Ministry of Electronics and Information Technology (MeitY), Government of India
-- NIELIT has been conferred the status of "Deemed to be University" under Section 3 of the UGC Act, 1956
-- Offers various programs in IT, Electronics, and emerging technologies
-- Multiple centers across India including Delhi, Kolkata, Chennai, Calicut, Gorakhpur, Ajmer, Aurangabad, and more
-- Programs offered: B.Tech, M.Tech, MCA, PhD, and various certification courses
-- Focus areas: Artificial Intelligence, Machine Learning, Cybersecurity, IoT, Data Science, Cloud Computing, Blockchain
-- NIELIT also conducts CCC (Course on Computer Concepts), BCC, and other IT literacy programs
-- Conducts entrance exams for various programs
-
-KEY COURSES:
-1. B.Tech in Computer Science & Engineering
-2. M.Tech in various specializations (AI, Cybersecurity, Data Science, etc.)
-3. MCA (Master of Computer Applications)
-4. PhD programs in Computer Science and Electronics
-5. Certificate and Diploma courses (CCC, BCC, O Level, A Level, B Level, C Level)
-
-ADMISSIONS:
-- Admissions through entrance examinations
-- Online application process
-- Merit-based selection for various programs
-
-When answering questions:
-1. Be helpful, informative, and student-friendly
-2. Provide accurate information about NIELIT programs and services
-3. Guide students on admissions, courses, and career opportunities
-4. If you don't know specific current details (fees, dates, etc.), suggest visiting the official NIELIT website or contacting the admission office
-5. Be encouraging and supportive to prospective students
+system_prompt = f"""You are the **Official AI Assistant for NIELIT Ropar**.
+Your answers must be professional, academic, and based STRICTLY on the text below.
+
+### OFFICIAL DATA:
+{nielit_data}
+
+### RULES:
+1. If details (like specific fees) aren't in the text, say: "Please check the official website for the latest updates."
+2. Do not hallucinate.
 """
 
+# Try loading the model
 def get_available_model_name():
     """
-    Dynamically finds a working Gemini model from the user's account.
+    Dynamically finds a working model from the user's account.
     """
     try:
         available_models = []
@@ -53,9 +85,10 @@ def get_available_model_name():
                 available_models.append(m.name)
         
         if not available_models:
+            logger.error("No models found.")
             return None
 
-        # Priority list: Try to find these specific models first
+        # Priority list: Try to find these specific powerful models first
         preferred_order = [
             "models/gemini-1.5-flash",
             "models/gemini-1.5-pro",
@@ -63,176 +96,49 @@ def get_available_model_name():
             "models/gemini-1.0-pro"
         ]
         
-        # Check if any preferred model is available
+        # 1. Check if any preferred model is in the available list
         for preferred in preferred_order:
             if preferred in available_models:
+                logger.info(f"Selected Preferred Model: {preferred}")
                 return preferred
 
-        # If none of the preferred ones exist, use the first available
-        return available_models[0]
+        # 2. If none of the preferred ones exist, take the first available one
+        fallback = available_models[0]
+        logger.warning(f"Preferred models missing. Falling back to: {fallback}")
+        return fallback
 
     except Exception as e:
+        logger.error(f"Error listing models: {e}")
         return None
 
-def get_chatbot_response(message, history):
-    """Generate response using Gemini API"""
-    
-    if not GEMINI_API_KEY:
-        return "⚠️ Please set the GEMINI_API_KEY environment variable in Hugging Face Spaces settings."
-    
+# ==========================================
+# 4. CHAT LOGIC
+# ==========================================
+def chat_response(message, history):
     try:
-        # Get the best available model
-        model_name = get_available_model_name()
-        
-        if not model_name:
-            return "❌ No available Gemini models found for your API key.\n\n🔑 Please verify your API key at: https://aistudio.google.com/app/apikey\n\nMake sure you have access to Gemini models."
-        
-        # Initialize the model
-        model = genai.GenerativeModel(model_name)
-        
-        # Build conversation history
-        chat_history = []
-        for human, assistant in history:
-            chat_history.append({"role": "user", "parts": [human]})
-            chat_history.append({"role": "model", "parts": [assistant]})
-        
-        # Start chat with history
-        chat = model.start_chat(history=chat_history)
-        
-        # Create context-aware prompt
-        full_prompt = f"{NIELIT_INFO}\n\nStudent Query: {message}\n\nProvide a helpful and accurate response:"
-        
-        # Get response
-        response = chat.send_message(full_prompt)
-        
-        return response.text
-        
+        if not api_key: return "⚠️ API Key Missing."
+        return model.generate_content(message).text
     except Exception as e:
-        error_msg = str(e)
-        if "API_KEY_INVALID" in error_msg or "invalid" in error_msg.lower():
-            return f"❌ Invalid API Key Error: {error_msg}\n\n🔑 Please get a valid API key from: https://aistudio.google.com/app/apikey\n\nThen set it in Hugging Face Spaces: Settings → Repository secrets → GEMINI_API_KEY"
-        return f"❌ Error: {error_msg}\n\nModel used: {model_name if 'model_name' in locals() else 'unknown'}\n\nIf the error persists, please verify your API key is correct."
-
-# Custom CSS for NIELIT branding
-custom_css = """
-#header {
-    text-align: center;
-    background: linear-gradient(135deg, #1e3c72 0%, #2a5298 100%);
-    padding: 20px;
-    border-radius: 10px;
-    margin-bottom: 20px;
-}
-
-#header h1 {
-    color: white;
-    margin: 0;
-    font-size: 2em;
-}
-
-#header p {
-    color: #e0e0e0;
-    margin: 5px 0 0 0;
-}
-
-.message-wrap {
-    border-radius: 10px !important;
-}
-
-footer {
-    text-align: center;
-    margin-top: 20px;
-    color: #666;
-}
-"""
-
-# Predefined quick questions
-example_questions = [
-    "What programs does NIELIT University offer?",
-    "How can I apply for admission?",
-    "What is the CCC course?",
-    "Tell me about M.Tech programs",
-    "What are the career opportunities after NIELIT courses?",
-    "Information about PhD programs",
-]
-
-# Create Gradio interface
-with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
-    # Header
-    with gr.Row(elem_id="header"):
-        gr.HTML("""
-            <div>
-                <h1>🎓 NIELIT Deemed to be University</h1>
-                <p>AI-Powered Student Assistance Chatbot</p>
-            </div>
-        """)
-    
-    # Main content
-    with gr.Row():
-        with gr.Column(scale=4):
-            chatbot = gr.Chatbot(
-                height=500,
-                bubble_full_width=False,
-                avatar_images=(None, "bot.png"),
-                show_label=False
-            )
-            
-            with gr.Row():
-                msg = gr.Textbox(
-                    placeholder="Ask me anything about NIELIT University, programs, admissions...",
-                    show_label=False,
-                    scale=4,
-                    container=False
-                )
-                submit = gr.Button("Send", variant="primary", scale=1)
-            
-            clear = gr.Button("🗑️ Clear Chat")
-        
-        with gr.Column(scale=1):
-            gr.Markdown("### 💡 Quick Questions")
-            
-            for question in example_questions:
-                btn = gr.Button(question, size="sm")
-                btn.click(
-                    lambda q=question: q,
-                    outputs=msg
-                )
-            
-            gr.Markdown("---")
-            gr.Markdown("""
-            ### ℹ️ About
-            This chatbot provides information about:
-            - 📚 Academic Programs
-            - 📝 Admissions Process
-            - 🎯 Course Details
-            - 💼 Career Guidance
-            - 📞 Contact Information
-            
-            ### 🔗 Official Links
-            - [NIELIT Website](https://www.nielit.gov.in)
-            - [Student Portal](https://student.nielit.gov.in)
-            - [Admissions](https://nielit.gov.in/admissions)
-            """)
-    
-    # Footer
-    gr.HTML("""
-        <footer>
-            <p>Powered by Google Gemini AI | Developed for NIELIT Deemed to be University</p>
-            <p style="font-size: 0.9em; color: #999;">
-                For official information, please visit <a href="https://www.nielit.gov.in" target="_blank">www.nielit.gov.in</a>
-            </p>
-        </footer>
-    """)
+        return f"⚠️ Error: {str(e)}"
+
+# ==========================================
+# 5. UI (CRASH PROOF VERSION)
+# ==========================================
+# We use Blocks (Stable) instead of passing arguments to ChatInterface (Risky)
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 🎓 NIELIT Ropar AI Assistant")
+    gr.Markdown("Powered by **Gemini 1.5** + **Live Web Scraping**")
     
-    # Event handlers
-    def respond(message, chat_history):
-        bot_message = get_chatbot_response(message, chat_history)
-        chat_history.append((message, bot_message))
-        return "", chat_history
-    
-    msg.submit(respond, [msg, chatbot], [msg, chatbot])
-    submit.click(respond, [msg, chatbot], [msg, chatbot])
-    clear.click(lambda: None, None, chatbot, queue=False)
+    # Simple, arguments-free Interface to prevent TypeErrors
+    chat_interface = gr.ChatInterface(
+        fn=chat_response,
+        examples=[
+            "Does NIELIT Ropar have bus facility?",
+            "Who is the Head of Training?",
+            "What is the Fee structure?",
+            "Where is the campus located?"
+        ]
+    )
 
-# Launch the app
 if __name__ == "__main__":
-    demo.launch()
+    demo.queue().launch(server_name="0.0.0.0", server_port=7860)