Upload custom_handler_diffsketcher.py with huggingface_hub
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custom_handler_diffsketcher.py
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from typing import Dict, Any
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import torch
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import base64
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import io
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import os
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import json
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from PIL import Image
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class EndpointHandler:
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def __init__(self, path=""):
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# Initialize device
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self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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print(f"Initializing diffsketcher handler on {self.device}")
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def __call__(self, data: Dict[str, Any]) -> Dict[str, str]:
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# Extract prompt from the input data
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prompt = data.get("prompt", "")
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if not prompt and "prompts" in data:
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prompts = data.get("prompts", [""])
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prompt = prompts[0] if prompts else ""
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# Generate a placeholder SVG
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svg = f'<svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><text x="50%" y="50%" dominant-baseline="middle" text-anchor="middle" font-size="20">diffsketcher: {prompt}</text></svg>'
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# Create a placeholder image
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image = Image.new('RGB', (512, 512), color = (100, 100, 100))
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# Convert the image to base64
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buffered = io.BytesIO()
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image.save(buffered, format="PNG")
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img_str = base64.b64encode(buffered.getvalue()).decode()
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# Return the results
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return {
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"svg": svg,
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"image": img_str
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}
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