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Browse files- app.py +7 -6
- requirements.txt +2 -0
app.py
CHANGED
@@ -7,6 +7,7 @@ from datetime import datetime
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import time
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import logging
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import traceback # For better error reporting
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#os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
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#logger = logging.getLogger()
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@@ -46,7 +47,7 @@ def load_fn(models):
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for model in models:
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if model not in models_load.keys():
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try:
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m = gr.load(f'models/{model}')
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models_load.update({model: m})
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models_load[model] = m # Store in dictionary
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@@ -121,8 +122,8 @@ def gen_fn(model_str, prompt):
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# Execute the model's processing with a timeout
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#future = executor.submit(models_load[model_str], f"{prompt}")
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#response = future.result(timeout=150) # Wait for result with timeout
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response = models_load.get(model_str, lambda txt: None)(f'{prompt}')
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if isinstance(response, gr.Image):
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return response
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elif isinstance(response, tuple):
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return None
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@@ -219,9 +220,9 @@ textarea{ position: absolute; font-size: 1em !important; padding: 4px;
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demo.queue()
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demo.queue = False
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demo.config["queue"] = False
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demo.launch(max_threads=40)
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import time
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import logging
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import traceback # For better error reporting
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from PIL import Image
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#os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
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#logger = logging.getLogger()
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for model in models:
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if model not in models_load.keys():
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try:
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m = gr.load(f'models/{model}', examples=None)
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models_load.update({model: m})
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models_load[model] = m # Store in dictionary
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# Execute the model's processing with a timeout
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#future = executor.submit(models_load[model_str], f"{prompt}")
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#response = future.result(timeout=150) # Wait for result with timeout
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response = models_load.get(model_str, lambda txt: None).fn(f'{prompt}')
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if isinstance(response, gr.Image) or isinstance(response, Image.Image):
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return response
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elif isinstance(response, tuple):
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return None
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demo.queue()
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#demo.queue = False
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#demo.config["queue"] = False
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demo.launch(max_threads=40, ssr_mode=False)
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requirements.txt
ADDED
@@ -0,0 +1,2 @@
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pydantic==2.10.6
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huggingface_hub==0.25.2
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