Update app.py

app.py

@@ -5,6 +5,7 @@ from TTS.api import TTS
 import librosa
 import numpy as np
 import os
+import spaces
 
 os.environ["COQUI_TOS_AGREED"] = "1"
 
@@ -12,16 +13,18 @@ processor = AutoProcessor.from_pretrained("facebook/musicgen-small")
 model_musicgen = MusicgenForConditionalGeneration.from_pretrained("facebook/musicgen-small")
 model_tts = TTS(model_name="tts_models/multilingual/multi-dataset/xtts_v2", progress_bar=False).to("cpu")
 
-def generate_music(text_prompt, audio_file=None, audio_mic=None, tts_text=None):
+@spaces.GPU()
+def generate_music(text_prompt, audio_file=None, tts_text=None):
     inputs = processor(text=text_prompt, padding=True, return_tensors="pt")
     max_duration_sec = 600
     min_duration_sec = 30
     max_new_tokens = int(max_duration_sec * model_musicgen.config.min_length)
     min_new_tokens = int(min_duration_sec * model_musicgen.config.min_length)
+    
     audio_values = model_musicgen.generate(**inputs.to("cpu"))
     music = audio_values.cpu().numpy()[0]
 
-    audio_prompt = audio_file or audio_mic
+    audio_prompt = audio_file
 
     if audio_prompt and tts_text:
         cloned_audio = model_tts.tts_with_vc(tts_text, speaker_wav=audio_prompt, language="es")
@@ -32,17 +35,21 @@ def generate_music(text_prompt, audio_file=None, audio_mic=None, tts_text=None):
         try:
             music_np = librosa.util.buf_to_float(music, n_bytes=2)
 
+            # Pad the shorter array
             if len(music_np) > len(cloned_audio):
-                padding = np.zeros(len(music_np) - len(cloned_audio))
-                cloned_audio = np.concatenate([cloned_audio, padding])
-            elif len(cloned_audio) > len(music_np):
-                padding = np.zeros(len(cloned_audio) - len(music_np))
-                music_np = np.concatenate([music_np, padding])
+                cloned_audio = np.pad(cloned_audio, (0, len(music_np) - len(cloned_audio)))
+            else:
+                music_np = np.pad(music_np, (0, len(cloned_audio) - len(music_np)))
 
             combined_audio = music_np + cloned_audio
-            return (44100, combined_audio)
-        except ImportError:
-            print("Error: Se requiere librosa para combinar audio. Instale con 'pip install librosa'")
+            
+            # Normalize and convert to int16
+            combined_audio = combined_audio / np.max(np.abs(combined_audio))
+            combined_audio_int16 = (combined_audio * 32767).astype(np.int16)
+
+            return (44100, combined_audio_int16)
+        except Exception as e:
+            print(f"Error combining audio: {e}")
             return (44100, music)
 
     return (44100, music)
@@ -59,4 +66,4 @@ iface = gr.Interface(
     description="Introduce una descripción de la música que deseas generar y opcionalmente un audio de voz para clonar con texto.",
 )
 
-iface.launch()
+iface.launch()