Update app.py

app.py

@@ -382,7 +382,256 @@ class GradioInterface:
         print("🌐 Initializing Enhanced Gradio interface...")
         # Initialize AI config and pipeline properly
         self.ai_config = AIConfig(safe_mode=True)
-        # Add other initialization code here
+        self.pipeline = ContentAdaptationPipeline(self.ai_config)
+        self.session_stats = {
+            "adaptations": 0,
+            "start_time": datetime.now(),
+            "profiles_used": {},
+            "total_processing_time": 0.0
+        }
+    
+    def adapt_content_interface(self, content, profile_name, interests_text, complexity):
+        """Main interface function for content adaptation"""
+        
+        if not content or not content.strip():
+            return (
+                "<div style='padding: 20px; background: #fff3cd; border-radius: 10px;'>"
+                "<h4>⚠️ Input Required</h4>"
+                "<p>Please enter some educational content to adapt for different learning styles.</p>"
+                "</div>",
+                "", "", ""
+            )
+        
+        try:
+            # Convert profile name to key
+            profile_map = {
+                "🎯 Visual Structure": "visual_structure",
+                "🔬 Directed Hyperfocus": "hyperfocus_directed", 
+                "🌸 Sensory Adaptation": "sensory_adaptation",
+                "🎮 Special Interests": "special_interests"
+            }
+            
+            profile_key = profile_map.get(profile_name, "visual_structure")
+            interests = [i.strip() for i in interests_text.split(',') if i.strip()]
+            
+            # Perform adaptation
+            result = self.pipeline.adapt_content(
+                content=content.strip(),
+                profile_key=profile_key,
+                interests=interests,
+                complexity=complexity
+            )
+            
+            # Update session stats
+            self._update_session_stats(result)
+            
+            # Format outputs for interface
+            adapted_html = result['adapted_content']
+            
+            gamification_info = self._format_gamification_output(result['gamification'])
+            processing_info = self._format_processing_output(result)
+            stats_info = self._format_stats_output()
+            
+            return adapted_html, gamification_info, processing_info, stats_info
+            
+        except Exception as e:
+            error_msg = f"❌ Adaptation error: {str(e)}"
+            print(f"Interface error: {e}")
+            
+            return (
+                f"<div style='padding: 20px; background: #f8d7da; border-radius: 10px;'>"
+                f"<h4>❌ Processing Error</h4>"
+                f"<p>An error occurred during content adaptation: {str(e)}</p>"
+                f"<p><em>Please try again with different content or settings.</em></p>"
+                f"</div>",
+                "", "", ""
+            )
+    
+    def _update_session_stats(self, result):
+        """Update session statistics"""
+        self.session_stats["adaptations"] += 1
+        
+        profile_used = result.get("profile_used", "unknown")
+        if profile_used in self.session_stats["profiles_used"]:
+            self.session_stats["profiles_used"][profile_used] += 1
+        else:
+            self.session_stats["profiles_used"][profile_used] = 1
+        
+        self.session_stats["total_processing_time"] += result.get("processing_time", 0)
+    
+    def _format_gamification_output(self, gamification):
+        """Format gamification information for display"""
+        
+        level = gamification.get("current_level", 1)
+        xp = gamification.get("xp_points", 0)
+        progress = gamification.get("progress_percentage", 0)
+        achievements = len(gamification.get("achievements", []))
+        
+        return (
+            f"🎮 Level {level} | ⭐ {xp:,} XP | 📈 {progress}% to next level | "
+            f"🏆 {achievements} achievements unlocked"
+        )
+    
+    def _format_processing_output(self, result):
+        """Format processing information for display"""
+        
+        processing_time = result.get("processing_time", 0)
+        ai_status = "🧠 AI Model" if result.get("gemma3_used", False) else "🎭 Enhanced Simulation"
+        profile = result.get("profile_used", "unknown").replace("_", " ").title()
+        success = "✅ Success" if result.get("success", False) else "⚠️ Fallback"
+        
+        return (
+            f"⚡ {processing_time:.2f}s processing | {ai_status} | "
+            f"🎯 {profile} profile | {success}"
+        )
+    
+    def _format_stats_output(self):
+        """Format session statistics for display"""
+        
+        total_adaptations = self.session_stats["adaptations"]
+        session_time = (datetime.now() - self.session_stats["start_time"]).total_seconds() / 60
+        avg_processing = (
+            self.session_stats["total_processing_time"] / total_adaptations 
+            if total_adaptations > 0 else 0
+        )
+        
+        most_used_profile = "None"
+        if self.session_stats["profiles_used"]:
+            most_used_profile = max(
+                self.session_stats["profiles_used"].items(), 
+                key=lambda x: x[1]
+            )[0].replace("_", " ").title()
+        
+        return (
+            f"📊 Session: {total_adaptations} adaptations | "
+            f"⏱️ {session_time:.1f}min active | "
+            f"⚡ {avg_processing:.2f}s avg | "
+            f"🎯 Most used: {most_used_profile}"
+        )
+    
+    def get_system_status(self):
+        """Get current system status with API info"""
+        
+        model_status = "🧠 AI Model Active" if not self.ai_config.simulation_mode else "🎭 Simulation Mode"
+        device_info = "🚀 GPU" if torch.cuda.is_available() else "💻 CPU"
+        
+        # Determine base URL for API
+        base_url = "http://localhost:8000" if "SPACE_ID" not in os.environ else "https://your-space.hf.space"
+        
+        return f"""
+## 🔧 System Status
+**AI Engine:** {model_status}  
+**Device:** {device_info}  
+**Profiles:** 4 neurodiverse learning profiles available  
+**Features:** Content adaptation, gamification, analytics  
+**Session:** {self.session_stats['adaptations']} adaptations completed  
+
+## 🔌 API Integration
+**API Status:** ✅ Active and ready  
+**Base URL:** `{base_url}`  
+**Documentation:** `{base_url}/docs`  
+**Health Check:** `{base_url}/health`  
+
+**Available Endpoints:**
+- `POST /adapt` - Content adaptation
+- `GET /profiles` - List profiles  
+- `GET /examples` - Usage examples
+- `GET /health` - Health check
+
+## 🎯 Profile System
+- 🎯 **Visual Structure:** Clear organization and hierarchy
+- 🔬 **Directed Hyperfocus:** Technical depth and detail
+- 🌸 **Sensory Adaptation:** Calm and accessible design
+- 🎮 **Special Interests:** Gamification and motivation
+
+## ✨ Capabilities
+✅ Real-time content adaptation  
+✅ Multiple complexity levels  
+✅ Interest-based personalization  
+✅ Accessibility features  
+✅ Progress tracking and gamification  
+✅ **REST API for external access**  
+✅ **Gradio web interface**  
+        """
+    
+    def get_api_examples_display(self):
+        """Get API examples for display in Gradio"""
+        
+        base_url = "http://localhost:8000" if "SPACE_ID" not in os.environ else "https://your-space.hf.space"
+        
+        return f"""
+## 🔌 API Usage Examples
+
+### Python Example
+```python
+import requests
+
+url = "{base_url}/adapt"
+data = {{
+    "content": "Your educational content here...",
+    "profile": "visual_structure",
+    "interests": ["technology", "programming"],
+    "complexity": "intermediate",
+    "format": "html"
+}}
+
+response = requests.post(url, json=data)
+result = response.json()
+
+print("Adapted:", result["adapted_content"])
+print("Gamification:", result["gamification"])
+```
+
+### JavaScript Example
+```javascript
+const response = await fetch('{base_url}/adapt', {{
+    method: 'POST',
+    headers: {{ 'Content-Type': 'application/json' }},
+    body: JSON.stringify({{
+        content: 'Your educational content...',
+        profile: 'visual_structure',
+        interests: ['technology'],
+        complexity: 'intermediate'
+    }})
+}});
+
+const result = await response.json();
+console.log('Adapted:', result.adapted_content);
+```
+
+### cURL Example
+```bash
+curl -X POST "{base_url}/adapt" \\
+  -H "Content-Type: application/json" \\
+  -d '{{
+    "content": "AI is transforming education...",
+    "profile": "visual_structure",
+    "interests": ["technology", "AI"],
+    "complexity": "intermediate"
+  }}'
+```
+
+### Available Profiles
+- `visual_structure` - Clear organization and hierarchy
+- `hyperfocus_directed` - Technical depth and detail  
+- `sensory_adaptation` - Calm and accessible design
+- `special_interests` - Gamification and motivation
+
+### Response Format
+```json
+{{
+  "adapted_content": "Enhanced HTML content...",
+  "gamification": {{
+    "current_level": 15,
+    "xp_points": 1250,
+    "achievements": ["Explorer", "Scholar"]
+  }},
+  "processing_time": 0.45,
+  "profile_used": "visual_structure",
+  "success": true
+}}
+```
+        """
     
     def create_interface(self):
         """Create the main Gradio interface with API integration"""
@@ -392,7 +641,7 @@ class GradioInterface:
             theme=gr.themes.Soft()
         ) as interface:
             
-            # Main Header with API info - Fixed: proper string handling
+            # Main Header with API info
             header_html = """
 <div style="text-align: center; background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); color: white; padding: 2.5rem; border-radius: 20px; margin-bottom: 2rem;">
     <h1 style="margin: 0; font-size: 2.5em;">🧠 InclusiveEdu</h1>
@@ -408,82 +657,6 @@ class GradioInterface:
             
             gr.HTML(header_html)
             
-            # Main content sections
-            with gr.Row():
-                with gr.Column(scale=1):
-                    gr.Markdown("## 📝 Content Input & Settings")
-                    
-                    content_input = gr.Textbox(
-                        label="Educational Content",
-                        placeholder="Enter the educational content you want to adapt...",
-                        lines=8,
-                        max_lines=12
-                    )
-                    
-                    with gr.Row():
-                        profile_dropdown = gr.Dropdown(
-                            label="🎯 Neurodiverse Learning Profile",
-                            choices=[
-                                "🎯 Visual Structure",
-                                "🔬 Directed Hyperfocus", 
-                                "🌸 Sensory Adaptation",
-                                "🎮 Special Interests"
-                            ],
-                            value="🎯 Visual Structure"
-                        )
-                        
-                        complexity_dropdown = gr.Dropdown(
-                            label="📊 Content Complexity",
-                            choices=[
-                                "beginner",
-                                "intermediate", 
-                                "advanced"
-                            ],
-                            value="intermediate"
-                        )
-                    
-                    interests_input = gr.Textbox(
-                        label="🎯 Personal Interests (comma-separated)",
-                        placeholder="technology, science, programming, art...",
-                        value="technology, learning, science"
-                    )
-                    
-                    adapt_button = gr.Button(
-                        "🚀 Adapt Content", 
-                        variant="primary"
-                    )
-                
-                with gr.Column(scale=1):
-                    gr.Markdown("## ✨ Adapted Learning Content")
-                    
-                    adapted_output = gr.HTML(
-                        label="Neurodiverse Adapted Content"
-                    )
-                    
-                    # Status outputs
-                    with gr.Row():
-                        gamification_output = gr.Textbox(
-                            label="🎮 Gamification & Progress",
-                            lines=2,
-                            interactive=False
-                        )
-                        
-                        processing_output = gr.Textbox(
-                            label="⚡ Processing Information",
-                            lines=2,
-                            interactive=False
-                        )
-                    
-                    stats_output = gr.Textbox(
-                        label="📊 Session Statistics",
-                        lines=2,
-                        interactive=False
-                    )
-            
-            # Additional sections would go here...
-            
-        return interface
-            
             # Main Interface Layout
             with gr.Row():
                 # Input Section
@@ -662,7 +835,7 @@ class GradioInterface:
             )
             
             # Enhanced Footer with API Information
-            gr.HTML(f"""
+            footer_html = f"""
             <div style="margin-top: 50px; padding: 30px; background: #f8f9fa; border-radius: 20px; text-align: center;">
                 
                 <h3 style="color: #495057; margin-top: 0;">🧠 InclusiveEdu - Empowering Every Learner</h3>
@@ -721,7 +894,9 @@ class GradioInterface:
                     Optimized for cloud deployment
                 </small>
             </div>
-            """)
+            """
+            
+            gr.HTML(footer_html)
         
         return interface