Update app.py

app.py

@@ -24,7 +24,6 @@ def load_videollama_model():
         print("🔄 Loading VideoLLaMA model...")
         
         # Try to load a working multimodal model
-        # Note: Replace with actual VideoLLaMA3 model when available
         model_name = "DAMO-NLP-SG/Video-LLaMA"
         
         # Configure quantization for memory efficiency
@@ -144,7 +143,6 @@ def generate_basic_analysis(video_info, question, frames):
         
         analysis_parts.append(f"- Average brightness: {'Bright' if avg_brightness > 127 else 'Dark'}")
         analysis_parts.append(f"- Color variance: {'High contrast' if color_variance > 1000 else 'Low contrast'}")
-        analysis_parts.append(f"- Dominant colors: Analyzing RGB distribution...")
         
         # Simple color analysis
         r_avg = np.mean(first_frame[:,:,0])
@@ -206,10 +204,92 @@ def analyze_video_with_ai(video_file, question, progress=gr.Progress()):
             try:
                 progress(0.7, desc="Running AI analysis...")
                 
-                # Prepare prompt for VideoLLaMA
-                prompt = f"""Human: I have a video with the following details:
-- Duration: {video_info.get('duration', 0):.1f} seconds
-- {len(frames)} key frames extracted
-- Question: {question}
+                # For now, we'll use basic analysis since VideoLLaMA3 integration needs more work
+                result = generate_basic_analysis(video_info, question, frames)
+                result += "\n\n🔄 **Status:** Currently using basic analysis. VideoLLaMA3 integration in progress."
+                
+                progress(1.0, desc="Complete!")
+                return result
+                
+            except Exception as model_error:
+                print(f"Model error: {model_error}")
+                # Fall back to basic analysis
+                pass
+        
+        # Use basic analysis
+        progress(0.8, desc="Generating analysis...")
+        result = generate_basic_analysis(video_info, question, frames)
+        progress(1.0, desc="Complete!")
+        
+        return result
+        
+    except Exception as e:
+        return f"❌ Error analyzing video: {str(e)}"
+
+def create_interface():
+    """Create the Gradio interface"""
+    
+    # Try to load model on startup (non-blocking)
+    try:
+        load_videollama_model()
+    except:
+        print("Model loading failed, using basic analysis mode")
+    
+    with gr.Blocks(title="VideoLLama3 Analyzer", theme=gr.themes.Soft()) as demo:
+        gr.Markdown("# 🎥 VideoLLama3 Video Analysis Tool")
+        gr.Markdown("Upload a video and ask questions about its content!")
+        
+        with gr.Row():
+            with gr.Column(scale=1):
+                video_input = gr.Video(
+                    label="Upload Video (MP4, AVI, MOV)",
+                    height=300
+                )
+                question_input = gr.Textbox(
+                    label="Ask a question about the video",
+                    placeholder="What is happening in this video?",
+                    lines=3
+                )
+                analyze_btn = gr.Button("🔍 Analyze Video", variant="primary", size="lg")
+                
+            with gr.Column(scale=1):
+                output = gr.Textbox(
+                    label="Analysis Results",
+                    lines=20,
+                    max_lines=25
+                )
+        
+        gr.Markdown("### 💡 Example Questions:")
+        examples = [
+            "What activities are happening in this video?",
+            "Describe the people or objects you see.",
+            "What is the setting or location?",
+            "Summarize the main events.",
+            "What emotions or mood does this convey?"
+        ]
+        
+        with gr.Row():
+            for example in examples[:3]:
+                btn = gr.Button(example, size="sm")
+                btn.click(lambda x=example: x, outputs=question_input)
+        
+        with gr.Row():
+            for example in examples[3:]:
+                btn = gr.Button(example, size="sm")
+                btn.click(lambda x=example: x, outputs=question_input)
+        
+        analyze_btn.click(
+            analyze_video_with_ai,
+            inputs=[video_input, question_input],
+            outputs=output,
+            show_progress=True
+        )
+        
+        gr.Markdown("---")
+        gr.Markdown("🚀 **Status**: Video processing active - Upload a video to test!")
+    
+    return demo
 
-Please analyze this video and provide a detailed response.
+if __name__ == "__main__":
+    demo = create_interface()
+    demo.launch()