Update app.py

app.py

@@ -1,261 +1,236 @@
 import gradio as gr
-from chatbot import Chatbot
-import json
+import pandas as pd
+import numpy as np
+from course_recommender import CourseRecommender
+from database_connection import DatabaseConnection
+import os
 
-# Initialize chatbot
-chatbot = Chatbot()
+# Initialize the recommender system
+recommender = CourseRecommender()
+db_connection = DatabaseConnection()
 
-def chat_interface(message, history):
-    """Handle chat interface with Gradio"""
-    if not message.strip():
-        return "Please enter a message."
-    
-    # Get response from chatbot
-    response = chatbot.get_response(message)
+# Global variables to store current recommendations
+current_recommendations = []
+current_user_input = {}
+
+def get_course_recommendations(stanine, gwa, strand, hobbies):
+    """Get course recommendations based on user input"""
+    global current_recommendations, current_user_input
     
-    # Format the response for display (removed confidence)
-    if response['status'] == 'success':
-        formatted_response = response['answer']
-    else:
-        formatted_response = response['answer']
+    # Validate inputs
+    if not stanine or not gwa or not strand or not hobbies:
+        return "Please fill in all fields", "", ""
     
-    return formatted_response
+    try:
+        stanine = int(stanine)
+        gwa = float(gwa)
+        
+        if stanine < 1 or stanine > 9:
+            return "Stanine must be between 1-9", "", ""
+        
+        if gwa < 75 or gwa > 100:
+            return "GWA must be between 75-100", "", ""
+        
+        if strand not in ["STEM", "ABM", "HUMSS", "GAS", "TVL"]:
+            return "Strand must be one of: STEM, ABM, HUMSS, GAS, TVL", "", ""
+        
+        # Store current user input
+        current_user_input = {
+            'stanine': stanine,
+            'gwa': gwa,
+            'strand': strand,
+            'hobbies': hobbies
+        }
+        
+        # Get recommendations
+        recommendations = recommender.predict_course(stanine, gwa, strand, hobbies)
+        current_recommendations = recommendations
+        
+        # Format recommendations
+        result_text = "🎓 Course Recommendations:\n\n"
+        for i, (course, confidence) in enumerate(recommendations, 1):
+            confidence_percent = confidence * 100
+            result_text += f"{i}. {course} (Confidence: {confidence_percent:.1f}%)\n"
+        
+        # Show top recommendation
+        top_course = recommendations[0][0] if recommendations else "No recommendations"
+        confidence = recommendations[0][1] * 100 if recommendations else 0
+        
+        return result_text, top_course, f"{confidence:.1f}%"
+        
+    except ValueError as e:
+        return f"Invalid input: {str(e)}", "", ""
+    except Exception as e:
+        return f"Error getting recommendations: {str(e)}", "", ""
 
-def get_system_info():
-    """Get system information"""
-    faq_count = chatbot.get_qa_count()
-    database_url = chatbot.database_url
+def rate_recommendation(rating):
+    """Rate the current recommendation (like/dislike)"""
+    global current_recommendations, current_user_input
+    
+    if not current_recommendations or not current_user_input:
+        return "No recommendations to rate. Please get recommendations first."
     
-    # Test database connection
     try:
-        import requests
-        response = requests.get(f"{database_url}/faqs", params={'question': 'test'}, timeout=5)
-        if response.status_code == 200:
-            db_status = "Connected"
+        # Convert rating to numeric
+        rating_value = 1 if rating == "👍 Like" else 0
+        
+        # Get the top recommendation
+        top_course = current_recommendations[0][0]
+        
+        # Add feedback to database
+        success = recommender.add_feedback(
+            course=top_course,
+            stanine=current_user_input['stanine'],
+            gwa=current_user_input['gwa'],
+            strand=current_user_input['strand'],
+            rating=rating_value,
+            hobbies=current_user_input['hobbies']
+        )
+        
+        if success:
+            return f"✅ Thank you for your feedback! Your rating for '{top_course}' has been recorded."
         else:
-            db_status = f"Error ({response.status_code})"
-    except:
-        db_status = "Unavailable"
-    
-    return f"System Status: Active\nFAQ Pairs Loaded: {faq_count}\nDatabase: {db_status}\nCourse Recommender: Ready"
+            return "❌ Failed to record feedback. Please try again."
+            
+    except Exception as e:
+        return f"Error recording feedback: {str(e)}"
 
-def get_course_recommendations(stanine, gwa, strand, hobbies):
-    """Get course recommendations"""
-    return chatbot.get_course_recommendations(stanine, gwa, strand, hobbies)
+def train_model():
+    """Train the model with current data"""
+    try:
+        accuracy = recommender.train_model(use_database=True)
+        return f"✅ Model trained successfully! Accuracy: {accuracy:.3f}"
+    except Exception as e:
+        return f"❌ Error training model: {str(e)}"
 
 # Create Gradio interface
-with gr.Blocks(
-    title="AI Chatbot",
-    theme=gr.themes.Soft(),
-    css="""
-    .gradio-container {
-        max-width: 800px !important;
-        margin: auto !important;
-    }
-    .chat-message {
-        padding: 10px;
-        margin: 5px 0;
-        border-radius: 10px;
-    }
-    """
-) as demo:
-    
-    gr.Markdown(
-        """
-        # 🤖 AI Student Assistant
+def create_interface():
+    with gr.Blocks(title="Course AI Recommender", theme=gr.themes.Soft()) as demo:
+        gr.Markdown("""
+        # 🎓 Course AI Machine Learning Recommender
         
-        Get answers to your questions and personalized course recommendations!
+        Get personalized course recommendations based on your academic profile and interests!
+        """)
         
-        **Features:**
-        - FAQ Chat: Get instant answers from our knowledge base
-        - Course Recommendations: Get personalized course suggestions based on your profile
-        """
-    )
-    
-    with gr.Tabs():
-        with gr.TabItem("💬 FAQ Chat"):
-            with gr.Row():
-                with gr.Column(scale=3):
-                    chatbot_interface = gr.Chatbot(
-                        label="FAQ Chat",
-                        height=400,
-                        show_label=True,
-                        container=True,
-                        bubble_full_width=False
-                    )
-                    
-                    with gr.Row():
-                        msg = gr.Textbox(
-                            placeholder="Type your question here...",
-                            show_label=False,
-                            scale=4,
-                            container=False
-                        )
-                        submit_btn = gr.Button("Send", variant="primary", scale=1)
+        with gr.Row():
+            with gr.Column(scale=1):
+                gr.Markdown("### 📝 Your Profile")
                 
-                with gr.Column(scale=1):
-                    gr.Markdown("### System Info")
-                    system_info = gr.Textbox(
-                        value=get_system_info(),
-                        label="Status",
-                        interactive=False,
-                        lines=4
-                    )
-                    
-                    refresh_btn = gr.Button("Refresh Status", variant="secondary")
-                    
-                    gr.Markdown("### FAQ Instructions")
-                    gr.Markdown(
-                        """
-                        **How to use:**
-                        1. Type your question in the text box
-                        2. Click Send or press Enter
-                        3. Get AI-powered answers from FAQ database
-                        
-                        **Tips:**
-                        - Ask specific questions for better results
-                        - Try rephrasing if you don't get a good match
-                        """
-                    )
-        
-        with gr.TabItem("🎯 Course Recommendations"):
-            with gr.Row():
-                with gr.Column(scale=2):
-                    gr.Markdown("### 📝 Student Profile")
-                    
-                    stanine_input = gr.Textbox(
-                        value="5",
-                        label="Stanine (1-9)",
-                        placeholder="Enter a number between 1 and 9",
-                        info="Your stanine score from standardized tests"
-                    )
-
-                    gwa_input = gr.Textbox(
-                        value="85",
-                        label="GWA (75-100)",
-                        placeholder="Enter a number between 75 and 100",
-                        info="Your General Weighted Average"
-                    )
-                    
-                    strand_input = gr.Dropdown(
-                        choices=["STEM", "ABM", "HUMSS", "GAS", "TVL"],
-                        label="Senior High School Strand",
-                        info="Select your SHS strand (TVL uses hobbies to infer track)"
-                    )
-                    
-                    hobbies_input = gr.Textbox(
-                        label="Hobbies & Interests",
-                        placeholder="e.g., programming, gaming, business, teaching...",
-                        lines=3,
-                        info="Describe your interests and hobbies"
-                    )
-                    
-                    recommend_btn = gr.Button("Get Recommendations", variant="primary", size="lg")
+                stanine_input = gr.Slider(
+                    minimum=1, maximum=9, step=1, value=5,
+                    label="Stanine Score (1-9)",
+                    info="Your stanine score from standardized tests"
+                )
                 
-                with gr.Column(scale=3):
-                    gr.Markdown("### 🎯 Your Course Recommendations")
-                    recommendations_output = gr.Markdown(
-                        value="Enter your profile details and click 'Get Recommendations' to see personalized course suggestions.",
-                        label="Recommendations"
-                    )
-                    
-                    gr.Markdown("### 📚 Available Courses")
-                    gr.Markdown(
-                        """
-                        **CASTECH**
-                        - BSA: Bachelor of Science in Agriculture
-                        - BSFish: Bachelor of Science in Fisheries
-                        - BSFoodTech: Bachelor of Science in Food Technology
-
-                        **CFA**
-                        - BSFo: Bachelor of Science in Forestry
-                        - BSAgFo: Bachelor of Science in Agroforestry
-
-                        **CBEE**
-                        - BSHM: Bachelor of Science in Hospitality Management
-                        - BSEntrep: Bachelor of Science in Entrepreneurship
-                        - BSAgribus: Bachelor of Science in Agriculture Business
-                        - BSAgEcon: Bachelor of Science in Agricultural Economics
-
-                        **CAS**
-                        - BSBio: Bachelor of Science in Biology
-                        - BSMath: Bachelor of Science in Mathematics
-                        - BAELS: Bachelor of Arts in English Language Studies
-                        - BSDevComm: Bachelor of Science in Development Communication
-
-                        **COECS**
-                        - BSABE: Agricultural and Biosystems Engineering
-                        - BSGE: Geodetic Engineering
-                        - BSCE: Civil Engineering
-                        - BSCpE: Computer Engineering
-                        - BSIT: Information Technology
-
-                        **COED**
-                        - BTLEd: Technology and Livelihood Education
-                        - BSED: Secondary Education
-                        - BEED: Elementary Education
-                        - BPE: Physical Education
-
-                        **CVM**
-                        - DVM: Doctor of Veterinary Medicine
-                        """
-                    )
-    
-    # Event handlers
-    def user(user_message, history):
-        return "", history + [[user_message, None]]
-    
-    def bot(history):
-        user_message = history[-1][0]
-        bot_message = chat_interface(user_message, history)
-        history[-1][1] = bot_message
-        return history
-    
-    def refresh_system_info():
-        return get_system_info()
-    
-    # Connect FAQ Chat events
-    submit_btn.click(
-        fn=user,
-        inputs=[msg, chatbot_interface],
-        outputs=[msg, chatbot_interface],
-        queue=False
-    ).then(
-        fn=bot,
-        inputs=chatbot_interface,
-        outputs=chatbot_interface,
-        queue=True
-    )
-    
-    msg.submit(
-        fn=user,
-        inputs=[msg, chatbot_interface],
-        outputs=[msg, chatbot_interface],
-        queue=False
-    ).then(
-        fn=bot,
-        inputs=chatbot_interface,
-        outputs=chatbot_interface,
-        queue=True
-    )
-    
-    # Connect Course Recommendation events
-    recommend_btn.click(
-        fn=get_course_recommendations,
-        inputs=[stanine_input, gwa_input, strand_input, hobbies_input],
-        outputs=recommendations_output
-    )
+                gwa_input = gr.Slider(
+                    minimum=75, maximum=100, step=0.1, value=85,
+                    label="GWA (75-100)",
+                    info="Your Grade Weighted Average"
+                )
+                
+                strand_input = gr.Dropdown(
+                    choices=["STEM", "ABM", "HUMSS", "GAS", "TVL"],
+                    value="STEM",
+                    label="Academic Strand",
+                    info="Your current academic strand"
+                )
+                
+                hobbies_input = gr.Textbox(
+                    label="Hobbies & Interests",
+                    placeholder="e.g., Programming, Reading, Sports, Music",
+                    info="List your hobbies and interests (comma-separated)"
+                )
+                
+                get_recommendations_btn = gr.Button("🎯 Get Recommendations", variant="primary")
+                
+                train_model_btn = gr.Button("🤖 Train Model", variant="secondary")
+            
+            with gr.Column(scale=1):
+                gr.Markdown("### 🎓 Recommendations")
+                
+                recommendations_output = gr.Textbox(
+                    label="Course Recommendations",
+                    lines=8,
+                    interactive=False
+                )
+                
+                top_course_output = gr.Textbox(
+                    label="Top Recommendation",
+                    interactive=False
+                )
+                
+                confidence_output = gr.Textbox(
+                    label="Confidence Score",
+                    interactive=False
+                )
+                
+                gr.Markdown("### 👍 Rate Your Recommendation")
+                
+                rating_buttons = gr.Radio(
+                    choices=["👍 Like", "👎 Dislike"],
+                    label="How do you rate this recommendation?",
+                    interactive=True
+                )
+                
+                rate_btn = gr.Button("Submit Rating", variant="secondary")
+                
+                rating_feedback = gr.Textbox(
+                    label="Rating Feedback",
+                    interactive=False
+                )
+        
+        # Event handlers
+        get_recommendations_btn.click(
+            fn=get_course_recommendations,
+            inputs=[stanine_input, gwa_input, strand_input, hobbies_input],
+            outputs=[recommendations_output, top_course_output, confidence_output]
+        )
+        
+        rate_btn.click(
+            fn=rate_recommendation,
+            inputs=[rating_buttons],
+            outputs=[rating_feedback]
+        )
+        
+        train_model_btn.click(
+            fn=train_model,
+            outputs=[gr.Textbox(label="Training Status", interactive=False)]
+        )
+        
+        # Add some example inputs
+        gr.Markdown("""
+        ### 💡 Example Inputs
+        
+        **For STEM students:**
+        - Stanine: 7-9, GWA: 85-95, Strand: STEM, Hobbies: Programming, Mathematics, Science
+        
+        **For ABM students:**
+        - Stanine: 6-8, GWA: 80-90, Strand: ABM, Hobbies: Business, Leadership, Economics
+        
+        **For HUMSS students:**
+        - Stanine: 5-8, GWA: 78-88, Strand: HUMSS, Hobbies: Literature, History, Writing
+        """)
     
-    refresh_btn.click(
-        fn=refresh_system_info,
-        outputs=system_info
-    )
+    return demo
 
+# Initialize the interface
 if __name__ == "__main__":
+    # Try to load existing model
+    try:
+        recommender.load_model()
+        print("✅ Loaded existing model")
+    except:
+        print("⚠️ No existing model found. Training with basic data...")
+        try:
+            recommender.train_model(use_database=False)
+            print("✅ Model trained with basic data")
+        except Exception as e:
+            print(f"❌ Error training model: {e}")
+    
+    # Create and launch interface
+    demo = create_interface()
     demo.launch(
         server_name="0.0.0.0",
         server_port=7860,
-        share=False,
-        show_error=True,
-        quiet=False
-    )
+        share=True
+    )