Update app.py

app.py

@@ -10,7 +10,7 @@ from datetime import datetime
 
 app = Flask(__name__)
 
-# Mock GoogleGenAI class (replace with actual SDK if available)
+# Mock GoogleGenAI class
 class GoogleGenAI:
     def __init__(self, config):
         self.api_key = config['apiKey']
@@ -65,7 +65,8 @@ async def generate_music():
         config = data.get('config', {
             'temperature': 1.1,
             'topK': 40,
-            'guidance': 4.0
+            'guidance': 4.0,
+            'slowed_factor': 1.0
         })
 
         if not prompts:
@@ -82,20 +83,29 @@ async def generate_music():
 
         collected_chunks = []
         total_duration = 0
-        target_duration = 600  # 10 minutes in seconds
+        target_duration = 60  # 1 minute
 
         async def mock_generate_chunks():
             nonlocal collected_chunks, total_duration
-            chunk_duration = 2  # seconds
-            samples_per_chunk = int(sample_rate * chunk_duration * 2)  # stereo, 16-bit
+            slowed_factor = config.get('slowed_factor', 1.0)
+            chunk_duration = 2 * slowed_factor
+            samples_per_chunk = int(sample_rate * chunk_duration * 2)  # Stereo, 16-bit
+            base_freq = 440  # Base frequency (A4)
             while total_duration < target_duration:
-                chunk = np.random.randint(-32768, 32768, samples_per_chunk, dtype=np.int16)
+                # Vary frequency based on prompt weights
+                total_weight = sum(p['weight'] for p in weighted_prompts)
+                freq_modifier = sum(p['weight'] * (ord(p['text'][0]) % 10) / 10 for p in weighted_prompts) / total_weight
+                freq = base_freq * (1 + freq_modifier * 0.5)  # Adjust frequency slightly per style
+                t = np.linspace(0, chunk_duration, samples_per_chunk, False)
+                # Simple sine wave with amplitude modulation for "slowed" effect
+                amplitude = 0.5 if slowed_factor < 1 else 1.0
+                chunk = (amplitude * 32767 * np.sin(2 * np.pi * freq * t / sample_rate)).astype(np.int16)
                 encoded_chunk = base64.b64encode(chunk.tobytes()).decode('utf-8')
                 decoded_chunk = decode(encoded_chunk)
                 collected_chunks.append(decoded_chunk)
                 total_duration += chunk_duration
                 yield {'serverContent': {'audioChunks': [{'data': encoded_chunk}]}}
-                await asyncio.sleep(0.1)  # Simulate network delay
+                await asyncio.sleep(0.1 * slowed_factor)
             yield {'close': True}
 
         session = await ai.live.music.connect({
@@ -128,7 +138,7 @@ async def generate_music():
 
         output = BytesIO(wav_blob)
         timestamp = datetime.now().isoformat().replace(':', '-')
-        filename = f"prompt-dj-music-10min-{timestamp}.wav"
+        filename = f"prompt-dj-music-1min-{timestamp}.wav"
 
         return send_file(
             output,
@@ -141,4 +151,4 @@ async def generate_music():
         return jsonify({'error': str(e)}), 500
 
 if __name__ == '__main__':
-    app.run(host='0.0.0.0', port=5000)
+    app.run(host='0.0.0.0', port=7860)