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feat: enhance metadata processing and extraction for Efficient nodes with improved prompt handling and conditioning outputs.
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@@ -233,17 +233,25 @@ class MetadataProcessor:
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pos_conditioning = metadata[PROMPTS][sampler_id].get("pos_conditioning")
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neg_conditioning = metadata[PROMPTS][sampler_id].get("neg_conditioning")
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# Try to match conditioning objects with those stored by CLIPTextEncodeExtractor
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for prompt_node_id, prompt_data in metadata[PROMPTS].items():
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if "conditioning" not in prompt_data:
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continue
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# For nodes with single conditioning output
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if "conditioning" in prompt_data:
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if pos_conditioning is not None and id(prompt_data["conditioning"]) == id(pos_conditioning):
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result["prompt"] = prompt_data.get("text", "")
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if pos_conditioning is not None and id(prompt_data["conditioning"]) == id(pos_conditioning):
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result["prompt"] = prompt_data.get("text", "")
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if neg_conditioning is not None and id(prompt_data["conditioning"]) == id(neg_conditioning):
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result["negative_prompt"] = prompt_data.get("text", "")
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if neg_conditioning is not None and id(prompt_data["conditioning"]) == id(neg_conditioning):
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result["negative_prompt"] = prompt_data.get("text", "")
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# For nodes with separate pos_conditioning and neg_conditioning outputs (like TSC_EfficientLoader)
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if "positive_encoded" in prompt_data:
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if pos_conditioning is not None and id(prompt_data["positive_encoded"]) == id(pos_conditioning):
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result["prompt"] = prompt_data.get("positive_text", "")
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if "negative_encoded" in prompt_data:
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if neg_conditioning is not None and id(prompt_data["negative_encoded"]) == id(neg_conditioning):
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result["negative_prompt"] = prompt_data.get("negative_text", "")
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return result
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