mirror of
https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-03-22 05:32:12 -03:00
4bff17aa1a
- Expanded the prompt.json file with new configurations for KSampler, CheckpointLoaderSimple, and various CLIPTextEncode nodes. - Introduced additional Lora management features, including a new Lora Stacker and improved trigger word handling. - Enhanced the loras_widget.js to log the generated prompt when saving recipes directly, aiding in debugging and user feedback. - Improved overall structure and organization of the prompt configurations for better maintainability.
63 lines
2.0 KiB
Python
63 lines
2.0 KiB
Python
#!/usr/bin/env python3
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"""Simple test script for the workflow parser"""
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import json
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import os
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import sys
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from pathlib import Path
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# Get project path
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project_path = Path(__file__).parent.parent.parent
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refs_path = project_path / "refs"
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prompt_path = refs_path / "prompt.json"
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output_path = refs_path / "output.json"
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print(f"Loading workflow from {prompt_path}")
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print(f"Expected output from {output_path}")
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# Load the workflow JSON
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with open(prompt_path, 'r', encoding='utf-8') as f:
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workflow_json = json.load(f)
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# Load the expected output
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with open(output_path, 'r', encoding='utf-8') as f:
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expected_output = json.load(f)
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print("\nExpected output:")
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print(json.dumps(expected_output, indent=2))
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# Manually extract important parameters to verify our understanding
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sampler_node_id = "3"
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sampler_node = workflow_json.get(sampler_node_id, {})
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print("\nSampler node:")
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print(json.dumps(sampler_node, indent=2))
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# Extract seed, steps, cfg
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seed = sampler_node.get("inputs", {}).get("seed")
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steps = sampler_node.get("inputs", {}).get("steps")
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cfg = sampler_node.get("inputs", {}).get("cfg")
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print(f"\nExtracted parameters:")
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print(f"seed: {seed}")
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print(f"steps: {steps}")
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print(f"cfg_scale: {cfg}")
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# Extract positive prompt - this requires following node references
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positive_ref = sampler_node.get("inputs", {}).get("positive", [])
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if isinstance(positive_ref, list) and len(positive_ref) == 2:
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positive_node_id, slot_index = positive_ref
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positive_node = workflow_json.get(positive_node_id, {})
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print(f"\nPositive node ({positive_node_id}):")
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print(json.dumps(positive_node, indent=2))
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# Follow the reference to the text value
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text_ref = positive_node.get("inputs", {}).get("text", [])
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if isinstance(text_ref, list) and len(text_ref) == 2:
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text_node_id, slot_index = text_ref
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text_node = workflow_json.get(text_node_id, {})
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print(f"\nText node ({text_node_id}):")
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print(json.dumps(text_node, indent=2))
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print("\nTest completed.") |