Update app.py

app.py

@@ -1,82 +1,50 @@
+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()
 
-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.
+# 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
 """
 
-# Try loading the model
 def get_available_model_name():
     """
-    Dynamically finds a working model from the user's account.
+    Dynamically finds a working Gemini model from the user's account.
     """
     try:
         available_models = []
@@ -85,10 +53,9 @@ 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 powerful models first
+        # Priority list: Try to find these specific models first
         preferred_order = [
             "models/gemini-1.5-flash",
             "models/gemini-1.5-pro",
@@ -96,49 +63,176 @@ def get_available_model_name():
             "models/gemini-1.0-pro"
         ]
         
-        # 1. Check if any preferred model is in the available list
+        # Check if any preferred model is available
         for preferred in preferred_order:
             if preferred in available_models:
-                logger.info(f"Selected Preferred Model: {preferred}")
                 return preferred
 
-        # 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
+        # If none of the preferred ones exist, use the first available
+        return available_models[0]
 
     except Exception as e:
-        logger.error(f"Error listing models: {e}")
         return None
 
-# ==========================================
-# 4. CHAT LOGIC
-# ==========================================
-def chat_response(message, history):
+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."
+    
     try:
-        if not api_key: return "⚠️ API Key Missing."
-        return model.generate_content(message).text
+        # 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
+        
     except Exception as e:
-        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**")
+        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>
+        """)
     
-    # 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?"
-        ]
-    )
+    # Main content
+    with gr.Row():
+        with gr.Column(scale=4):
+            chatbot = gr.Chatbot(
+                height=500,
+                bubble_full_width=False,
+                avatar_images=(None, "https://cdn-uploads.huggingface.co/production/uploads/6474405f90330355db146c76/dOtPhPMj5nk3SEceM_3Iq.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>
+    """)
+    
+    # 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)
 
+# Launch the app
 if __name__ == "__main__":
-    demo.queue().launch(server_name="0.0.0.0", server_port=7860)
+    demo.launch()