Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -82,57 +82,6 @@ def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, guidan
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if lora_id:
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pipe.unload_lora_weights()
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# def query(lora_id, prompt, steps=28, cfg_scale=3.5, randomize_seed=True, seed=-1, width=1024, height=1024):
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# if prompt == "" or prompt == None:
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# return None
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# if lora_id.strip() == "" or lora_id == None:
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# lora_id = "black-forest-labs/FLUX.1-dev"
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# key = random.randint(0, 999)
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# API_URL = "https://api-inference.huggingface.co/models/"+ lora_id.strip()
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# API_TOKEN = random.choice([os.getenv("HF_READ_TOKEN")])
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# headers = {"Authorization": f"Bearer {API_TOKEN}"}
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# # prompt = GoogleTranslator(source='ru', target='en').translate(prompt)
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# # print(f'\033[1mGeneration {key} translation:\033[0m {prompt}')
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# prompt = f"{prompt} | ultra detail, ultra elaboration, ultra quality, perfect."
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# # print(f'\033[1mGeneration {key}:\033[0m {prompt}')
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# # If seed is -1, generate a random seed and use it
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# if randomize_seed:
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# seed = random.randint(1, 4294967296)
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# payload = {
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# "inputs": prompt,
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# "steps": steps,
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# "cfg_scale": cfg_scale,
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# "seed": seed,
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# "parameters": {
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# "width": width, # Pass the width to the API
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# "height": height # Pass the height to the API
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# }
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# }
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# response = requests.post(API_URL, headers=headers, json=payload, timeout=timeout)
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# if response.status_code != 200:
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# print(f"Error: Failed to get image. Response status: {response.status_code}")
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# print(f"Response content: {response.text}")
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# if response.status_code == 503:
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# raise gr.Error(f"{response.status_code} : The model is being loaded")
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# raise gr.Error(f"{response.status_code}")
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# try:
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# image_bytes = response.content
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# image = Image.open(io.BytesIO(image_bytes))
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# print(f'\033[1mGeneration {key} completed!\033[0m ({prompt})')
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# return image, seed, seed
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# except Exception as e:
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# print(f"Error when trying to open the image: {e}")
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# return None
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examples = [
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if lora_id:
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pipe.unload_lora_weights()
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examples = [
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