Update app.py
Browse files
app.py
CHANGED
@@ -40,21 +40,30 @@ def gen_fn(model_str, prompt, negative_prompt=None, noise=None, cfg_scale=None,
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# ネガティブプロンプトとその他のパラメータをログに出力
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print(f"Prompt: {full_prompt}, Negative Prompt: {negative_prompt}, CFG Scale: {cfg_scale}, Steps: {num_inference_steps}, Sampler: {sampler}")
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# Construct the function call parameters dynamically
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inputs = [full_prompt]
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if negative_prompt:
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inputs.append(negative_prompt)
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if cfg_scale is not None:
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inputs.append(cfg_scale)
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if num_inference_steps is not None:
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inputs.append(num_inference_steps)
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if sampler:
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inputs.append(sampler)
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try:
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# モデル呼び出し
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result = models_load[model_str](
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# Debugging result type
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print(f"Result type: {type(result)}, Result: {result}")
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# ネガティブプロンプトとその他のパラメータをログに出力
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print(f"Prompt: {full_prompt}, Negative Prompt: {negative_prompt}, CFG Scale: {cfg_scale}, Steps: {num_inference_steps}, Sampler: {sampler}")
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try:
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# Adjust the inputs depending on model capabilities
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if negative_prompt:
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inputs = {
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'prompt': full_prompt,
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'negative_prompt': negative_prompt,
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'cfg_scale': cfg_scale,
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'num_inference_steps': num_inference_steps,
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'sampler': sampler
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}
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else:
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inputs = {
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'prompt': full_prompt,
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'cfg_scale': cfg_scale,
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'num_inference_steps': num_inference_steps,
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'sampler': sampler
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}
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# Filter out None values
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inputs = {k: v for k, v in inputs.items() if v is not None}
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# モデル呼び出し
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result = models_load[model_str](**inputs)
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# Debugging result type
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print(f"Result type: {type(result)}, Result: {result}")
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