Update app.py

app.py

@@ -54,6 +54,15 @@ ai = GoogleGenAI({
 model = 'lyria-realtime-exp'
 sample_rate = 48000
 
+# Genre-specific parameters
+GENRE_PARAMS = {
+    "Synthwave": {"base_freq": 220, "mod_freq": 2, "amplitude": 0.7},  # Lower freq, pulsing
+    "Dreamwave": {"base_freq": 110, "mod_freq": 0.5, "amplitude": 0.5},  # Softer, slower
+    "Chillsynth": {"base_freq": 165, "mod_freq": 1, "amplitude": 0.6},  # Mid-range, smooth
+    "Lovewave": {"base_freq": 130, "mod_freq": 0.8, "amplitude": 0.4},  # Warm, gentle
+    "slowed": {"base_freq": 55, "mod_freq": 0.2, "amplitude": 0.3}  # Very low, slow
+}
+
 @app.route('/generate', methods=['POST'])
 async def generate_music():
     try:
@@ -90,16 +99,16 @@ async def generate_music():
             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)
+            t = np.linspace(0, chunk_duration, samples_per_chunk, False)
             while total_duration < target_duration:
-                # Vary frequency based on prompt weights
+                # Weighted average of genre parameters
                 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)
+                base_freq = sum(p['weight'] * GENRE_PARAMS.get(p['text'], GENRE_PARAMS["Synthwave"])['base_freq'] for p in weighted_prompts) / total_weight
+                mod_freq = sum(p['weight'] * GENRE_PARAMS.get(p['text'], GENRE_PARAMS["Synthwave"])['mod_freq'] for p in weighted_prompts) / total_weight
+                amplitude = sum(p['weight'] * GENRE_PARAMS.get(p['text'], GENRE_PARAMS["Synthwave"])['amplitude'] for p in weighted_prompts) / total_weight
+                amplitude *= 0.5 if slowed_factor < 1 else 1.0  # Reduce amplitude for slowed effect
+                # Generate modulated sine wave
+                chunk = (amplitude * 32767 * np.sin(2 * np.pi * (base_freq + mod_freq * np.sin(2 * np.pi * 0.1 * t)) * 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)