Update app.py

app.py

@@ -5,7 +5,8 @@ import os
 import random
 import torch
 
-CHAR_LIMIT = None
+IS_DUPLICATE = not os.getenv('SPACE_ID', 'hivecorp/keets2').startswith('hexgrad/')
+CHAR_LIMIT = None if IS_DUPLICATE else 5000
 
 CUDA_AVAILABLE = torch.cuda.is_available()
 models = {gpu: KModel().to('cuda' if gpu else 'cpu').eval() for gpu in [False] + ([True] if CUDA_AVAILABLE else [])}
@@ -18,7 +19,7 @@ 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):
-    text = text
+    text = text if CHAR_LIMIT is None else text.strip()[:CHAR_LIMIT]
     pipeline = pipelines[voice[0]]
     pack = pipeline.load_voice(voice)
     use_gpu = use_gpu and CUDA_AVAILABLE
@@ -49,7 +50,7 @@ def tokenize_first(text, voice='af_heart'):
     return words  # Return a list of words
 
 def generate_all(text, voice='af_heart', speed=1, use_gpu=CUDA_AVAILABLE):
-    text = text
+    text = text if CHAR_LIMIT is None else text.strip()[:CHAR_LIMIT]
     pipeline = pipelines[voice[0]]
     pack = pipeline.load_voice(voice)
     use_gpu = use_gpu and CUDA_AVAILABLE
@@ -189,7 +190,7 @@ with gr.Blocks() as app:
         with gr.Column():
             gr.TabbedInterface([generate_tab], ['Generate'])
     random_btn.click(fn=get_random_text, inputs=[voice], outputs=[text], api_name=API_NAME)
-    generate_btn.click(fn=generate_all, inputs=[text, voice, speed, use_gpu], outputs=[out_audio, out_ps], api_name=API_NAME)
+    generate_btn.click(fn=generate_first, inputs=[text, voice, speed, use_gpu], outputs=[out_audio, out_ps], api_name=API_NAME)
     tokenize_btn.click(fn=tokenize_first, inputs=[text, voice], outputs=[out_ps], api_name=API_NAME)
     predict_btn.click(fn=predict, inputs=[text, voice, speed], outputs=[out_audio], api_name=API_NAME)