Update app.py

app.py

@@ -1,10 +1,21 @@
-import gradio as gr
-from detect import SimpleOfflineAccentClassifier
+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')
 
-def download_youtube_audio(url):
+@app.route('/analyze', methods=['POST'])
+def analyze():
     try:
+        video_url = request.form['url']
+        
+        # YouTube'dan ses indir
         ydl_opts = {
             'format': 'bestaudio/best',
             'postprocessors': [{
@@ -17,76 +28,22 @@ def download_youtube_audio(url):
         }
         
         with yt_dlp.YoutubeDL(ydl_opts) as ydl:
-            ydl.download([url])
-        
-        return 'temp_audio.wav'
-    except Exception as e:
-        return None
-
-def analyze_audio(audio_file, youtube_url):
-    if youtube_url:
-        audio_file = download_youtube_audio(youtube_url)
-        if not audio_file:
-            return "Failed to download YouTube audio."
-    
-    if not audio_file:
-        return "Please upload an audio file or provide a YouTube URL."
-    
-    try:
-        classifier = SimpleOfflineAccentClassifier()
-        result = classifier.predict_accent(audio_file)
-        
-        if result is None:
-            return "Audio file processing failed."
+            ydl.download([video_url])
         
-        output = f"Predicted Accent: {result['accent']}\n"
-        output += f"Confidence Score: {result['confidence']:.2%}\n\n"
-        output += "All Probabilities:\n"
+        # Ses dosyasını analiz et
+        result = classifier.predict_accent('temp_audio.wav')
         
-        sorted_probs = sorted(
-            result['all_probabilities'].items(), 
-            key=lambda x: x[1], 
-            reverse=True
-        )
+        # Geçici dosyayı temizle
+        if os.path.exists('temp_audio.wav'):
+            os.remove('temp_audio.wav')
         
-        for accent, prob in sorted_probs:
-            bar = "█" * int(prob * 20)
-            output += f"- {accent}: {prob:.2%} {bar}\n"
+        if result is None:
+            return jsonify({'error': 'voice analyze failed.'})
         
-        return output
+        return jsonify(result)
         
     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"
-            )
-            
-            youtube_url = gr.Textbox(
-                label="Or enter YouTube URL",
-                placeholder="https://www.youtube.com/watch?v=..."
-            )
-            
-            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, youtube_url],
-        outputs=output_text
-    )
+        return jsonify({'error': str(e)})
 
-# Launch the interface
-interface.launch(server_name="0.0.0.0", server_port=7860)
+if __name__ == '__main__':
+    app.run(debug=True, port=5000)