Update app.py

app.py

@@ -1,49 +1,59 @@
-from flask import Flask, render_template, request, jsonify
-import yt_dlp
-import os
-from detect import SimpleOfflineAccentClassifier
-
-app = Flask(__name__)
-classifier = SimpleOfflineAccentClassifier()
-
-@app.route('/')
-def home():
-    return render_template('index.html')
-
-@app.route('/analyze', methods=['POST'])
-def analyze():
-    try:
-        video_url = request.form['url']
-        
-        # YouTube'dan ses indir
-        ydl_opts = {
-            'format': 'bestaudio/best',
-            'postprocessors': [{
-                'key': 'FFmpegExtractAudio',
-                'preferredcodec': 'wav',
-            }],
-            'outtmpl': 'temp_audio',
-            'quiet': True,
-            'no_warnings': True
-        }
-        
-        with yt_dlp.YoutubeDL(ydl_opts) as ydl:
-            ydl.download([video_url])
-        
-        # Ses dosyasını analiz et
-        result = classifier.predict_accent('temp_audio.wav')
-        
-        # Geçici dosyayı temizle
-        if os.path.exists('temp_audio.wav'):
-            os.remove('temp_audio.wav')
-        
-        if result is None:
-            return jsonify({'error': 'voice analyze failed.'})
-        
-        return jsonify(result)
-        
-    except Exception as e:
-        return jsonify({'error': str(e)})
-
-if __name__ == '__main__':
-    app.run(debug=True, port=5000)
+import gradio as gr
+from detect import SimpleOfflineAccentClassifier
+
+def analyze_audio(audio_file):
+    if audio_file is None:
+        return "Please upload an audio file."
+    
+    try:
+        classifier = SimpleOfflineAccentClassifier()
+        result = classifier.predict_accent(audio_file)
+        
+        if result is None:
+            return "Audio file processing failed."
+        
+        output = f"Predicted Accent: {result['accent']}\n"
+        output += f"Confidence Score: {result['confidence']:.2%}\n\n"
+        output += "All Probabilities:\n"
+        
+        sorted_probs = sorted(
+            result['all_probabilities'].items(), 
+            key=lambda x: x[1], 
+            reverse=True
+        )
+        
+        for accent, prob in sorted_probs:
+            bar = "█" * int(prob * 20)
+            output += f"- {accent}: {prob:.2%} {bar}\n"
+        
+        return output
+        
+    except Exception as e:
+        return f"Error occurred: {str(e)}"
+
+# Create Gradio interface
+with gr.Blocks() as interface:
+    gr.Markdown("# AI Accent Classifier")
+    
+    with gr.Row():
+        with gr.Column():
+            audio_input = gr.Audio(
+                label="Upload Audio File",
+                type="filepath"
+            )
+            
+            classify_btn = gr.Button("Analyze Accent")
+        
+        with gr.Column():
+            output_text = gr.Markdown(
+                label="Analysis Results",
+                value="Analysis results will appear here..."
+            )
+    
+    classify_btn.click(
+        fn=analyze_audio,
+        inputs=audio_input,
+        outputs=output_text
+    )
+
+interface.launch()