Update app.py

app.py

@@ -5,7 +5,8 @@ import os
 import random
 import torch
 
-IS_DUPLICATE = not os.getenv('SPACE_ID', '').startswith('hexgrad/')
+# IS_DUPLICATE = not os.getenv('SPACE_ID', '').startswith('hexgrad/')
+IS_DUPLICATE = False
 CUDA_AVAILABLE = torch.cuda.is_available()
 if not IS_DUPLICATE:
     import kokoro
@@ -20,7 +21,7 @@ pipelines = {lang_code: KPipeline(lang_code=lang_code, model=False) for lang_cod
 def forward_gpu(ps, ref_s, speed):
     return models[True](ps, ref_s, speed)
 
-def generate_first(text, voice='af_heart', speed=1, use_gpu=CUDA_AVAILABLE):
+def generate_first(text, voice='ef_dora', speed=1, use_gpu=CUDA_AVAILABLE):
     text = text if CHAR_LIMIT is None else text.strip()[:CHAR_LIMIT]
     pipeline = pipelines[voice[0]]
     pack = pipeline.load_voice(voice)
@@ -43,16 +44,16 @@ def generate_first(text, voice='af_heart', speed=1, use_gpu=CUDA_AVAILABLE):
     return None, ''
 
 # Arena API
-def predict(text, voice='af_heart', speed=1):
+def predict(text, voice='ef_dora', speed=1):
     return generate_first(text, voice, speed, use_gpu=False)[0]
 
-def tokenize_first(text, voice='af_heart'):
+def tokenize_first(text, voice='ef_dora'):
     pipeline = pipelines[voice[0]]
     for _, ps, _ in pipeline(text, voice):
         return ps
     return ''
 
-def generate_all(text, voice='af_heart', speed=1, use_gpu=CUDA_AVAILABLE):
+def generate_all(text, voice='ef_dora', speed=1, use_gpu=CUDA_AVAILABLE):
     text = text if CHAR_LIMIT is None else text.strip()[:CHAR_LIMIT]
     pipeline = pipelines[voice[0]]
     pack = pipeline.load_voice(voice)
@@ -136,25 +137,26 @@ with gr.Blocks() as stream_tab:
         gr.DuplicateButton()
 
 BANNER_TEXT = '''
-[***Kokoro*** **is an open-weight TTS model with 82 million parameters.**](https://huggingface.co/hexgrad/Kokoro-82M)
+[***Kokoro*** **es un modelo TTS de peso abierto con 82 millones de parámetros.**](https://huggingface.co/hexgrad/Kokoro-82M)
 
-This demo only showcases English, but you can directly use the model to access other languages.
+Esta demo solo muestra voces en español, pero puedes usar el modelo directamente para acceder a otros idiomas.
 '''
-API_OPEN = os.getenv('SPACE_ID') != 'hexgrad/Kokoro-TTS'
+#API_OPEN = os.getenv('SPACE_ID') != 'hexgrad/Kokoro-TTS'
+API_OPEN = false
 API_NAME = None if API_OPEN else False
 with gr.Blocks() as app:
     with gr.Row():
         gr.Markdown(BANNER_TEXT, container=True)
     with gr.Row():
         with gr.Column():
-            text = gr.Textbox(label='Input Text', info=f"Up to ~500 characters per Generate, or {'∞' if CHAR_LIMIT is None else CHAR_LIMIT} characters per Stream")
+            text = gr.Textbox(label='Input Text', info=f"hasta ~500 characteres por Generacion, o {'∞' if CHAR_LIMIT is None else CHAR_LIMIT} characters per Stream")
             with gr.Row():
-                voice = gr.Dropdown(list(CHOICES.items()), value='af_heart', label='Voice', info='Quality and availability vary by language')
+                voice = gr.Dropdown(list(CHOICES.items()), value='ef_dora', label='Voice', info='La calidad varia segun los lenguages')
                 use_gpu = gr.Dropdown(
                     [('ZeroGPU 🚀', True), ('CPU 🐌', False)],
                     value=CUDA_AVAILABLE,
                     label='Hardware',
-                    info='GPU is usually faster, but has a usage quota',
+                    info='GPU es mas rapido, pero esta limitado',
                     interactive=CUDA_AVAILABLE
                 )
             speed = gr.Slider(minimum=0.5, maximum=2, value=1, step=0.1, label='Speed')