Codex Local
131a8bc5fb
ComfyUI at /ai/ComfyUI with SDXL models Short messages (<30 chars) skip RAG = faster response Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
53 lines
1.9 KiB
Python
Executable File
53 lines
1.9 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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KXKM Image Generation — SDXL Lightning via diffusers
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Replaces ComfyUI for /imagine command.
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Usage: python3 scripts/generate_image.py --prompt "cyberpunk cat" --output /tmp/img.png
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Output: JSON on last line {"status":"completed","seed":123,"path":"/tmp/img.png"}
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"""
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import argparse, json, os, sys, time, random
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument("--prompt", required=True)
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parser.add_argument("--output", default="/tmp/kxkm-imagine.png")
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parser.add_argument("--seed", type=int, default=-1)
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parser.add_argument("--steps", type=int, default=4)
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parser.add_argument("--width", type=int, default=1024)
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parser.add_argument("--height", type=int, default=1024)
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args = parser.parse_args()
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seed = args.seed if args.seed >= 0 else random.randint(0, 2**32)
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t0 = time.time()
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try:
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import torch
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from diffusers import StableDiffusionXLPipeline, EulerDiscreteScheduler
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model_id = "stabilityai/sdxl-turbo"
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pipe = StableDiffusionXLPipeline.from_pretrained(
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model_id, torch_dtype=torch.float16, variant="fp16"
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).to("cuda")
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pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config)
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generator = torch.Generator("cuda").manual_seed(seed)
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image = pipe(
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prompt=args.prompt,
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num_inference_steps=args.steps,
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guidance_scale=0.0,
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width=args.width,
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height=args.height,
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generator=generator,
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).images[0]
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image.save(args.output)
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duration = round(time.time() - t0, 1)
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print(json.dumps({"status": "completed", "seed": seed, "path": args.output, "duration": duration}))
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except Exception as e:
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print(json.dumps({"status": "failed", "error": str(e)[:200]}))
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sys.exit(1)
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if __name__ == "__main__":
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main()
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