Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -14,6 +14,7 @@ import random
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import time
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import requests
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import pandas as pd
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#Load prompts for randomization
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df = pd.read_csv('prompts.csv', header=None)
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@@ -23,6 +24,31 @@ prompt_values = df.values.flatten()
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with open('loras.json', 'r') as f:
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loras = json.load(f)
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# Initialize the base model
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dtype = torch.bfloat16
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device = "cuda" if torch.cuda.is_available() else "cpu"
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import time
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import requests
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import pandas as pd
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import tempfile
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#Load prompts for randomization
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df = pd.read_csv('prompts.csv', header=None)
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with open('loras.json', 'r') as f:
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loras = json.load(f)
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def download_and_cache_lora_images(loras):
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"""Download all lora images and replace URLs with local paths"""
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for lora in loras:
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if lora.get('image') and lora['image'].startswith('http'):
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try:
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response = requests.get(lora['image'], timeout=10)
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response.raise_for_status()
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# Create temp file
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temp_dir = tempfile.gettempdir()
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filename = f"lora_{hash(lora['image'])}.png"
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local_path = os.path.join(temp_dir, filename)
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with open(local_path, 'wb') as f:
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f.write(response.content)
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lora['image'] = local_path
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print(f"Downloaded image for {lora['title']}")
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except Exception as e:
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print(f"Failed to download image for {lora['title']}: {e}")
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lora['image'] = None
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return loras
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loras = download_and_cache_lora_images(loras)
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# Initialize the base model
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dtype = torch.bfloat16
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device = "cuda" if torch.cuda.is_available() else "cpu"
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