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https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-03-21 21:22:11 -03:00
feat: add checkpoint metadata to EXIF recipe data
Add support for storing checkpoint information in image EXIF metadata. The checkpoint data is simplified and includes fields like model ID, version, name, hash, and base model. This allows for better tracking of AI model checkpoints used in image generation workflows.
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@@ -140,6 +140,28 @@ class ExifUtils:
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if metadata:
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# Remove any existing recipe metadata
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metadata = ExifUtils.remove_recipe_metadata(metadata)
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# Prepare checkpoint data
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checkpoint_data = recipe_data.get("checkpoint") or {}
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simplified_checkpoint = None
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if isinstance(checkpoint_data, dict) and checkpoint_data:
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simplified_checkpoint = {
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"type": checkpoint_data.get("type", "checkpoint"),
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"modelId": checkpoint_data.get("modelId", 0),
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"modelVersionId": checkpoint_data.get("modelVersionId")
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or checkpoint_data.get("id", 0),
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"modelName": checkpoint_data.get(
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"modelName", checkpoint_data.get("name", "")
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),
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"modelVersionName": checkpoint_data.get(
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"modelVersionName", checkpoint_data.get("version", "")
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),
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"hash": checkpoint_data.get("hash", "").lower()
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if checkpoint_data.get("hash")
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else "",
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"file_name": checkpoint_data.get("file_name", ""),
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"baseModel": checkpoint_data.get("baseModel", ""),
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}
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# Prepare simplified loras data
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simplified_loras = []
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@@ -160,7 +182,8 @@ class ExifUtils:
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'base_model': recipe_data.get('base_model', ''),
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'loras': simplified_loras,
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'gen_params': recipe_data.get('gen_params', {}),
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'tags': recipe_data.get('tags', [])
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'tags': recipe_data.get('tags', []),
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**({'checkpoint': simplified_checkpoint} if simplified_checkpoint else {})
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}
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# Convert to JSON string
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@@ -359,4 +382,4 @@ class ExifUtils:
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return f.read(), os.path.splitext(image_data)[1]
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except Exception:
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return image_data, '.jpg' # Last resort fallback
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return image_data, '.jpg'
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return image_data, '.jpg'
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61
tests/utils/test_exif_utils.py
Normal file
61
tests/utils/test_exif_utils.py
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@@ -0,0 +1,61 @@
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import json
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from py.utils.exif_utils import ExifUtils
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def test_append_recipe_metadata_includes_checkpoint(monkeypatch, tmp_path):
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captured = {}
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monkeypatch.setattr(
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ExifUtils, "extract_image_metadata", staticmethod(lambda _path: None)
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)
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def fake_update_image_metadata(image_path, metadata):
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captured["path"] = image_path
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captured["metadata"] = metadata
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return image_path
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monkeypatch.setattr(
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ExifUtils, "update_image_metadata", staticmethod(fake_update_image_metadata)
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)
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checkpoint = {
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"type": "checkpoint",
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"modelId": 827184,
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"modelVersionId": 2167369,
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"modelName": "WAI-illustrious-SDXL",
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"modelVersionName": "v15.0",
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"hash": "ABC123",
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"file_name": "WAI-illustrious-SDXL",
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"baseModel": "Illustrious",
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}
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recipe_data = {
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"title": "Semi-realism",
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"base_model": "Illustrious",
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"loras": [],
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"tags": [],
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"checkpoint": checkpoint,
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}
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image_path = tmp_path / "image.webp"
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image_path.write_bytes(b"")
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ExifUtils.append_recipe_metadata(str(image_path), recipe_data)
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assert captured["path"] == str(image_path)
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assert captured["metadata"].startswith("Recipe metadata: ")
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payload = json.loads(captured["metadata"].split("Recipe metadata: ", 1)[1])
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assert payload["checkpoint"] == {
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"type": "checkpoint",
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"modelId": 827184,
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"modelVersionId": 2167369,
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"modelName": "WAI-illustrious-SDXL",
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"modelVersionName": "v15.0",
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"hash": "abc123",
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"file_name": "WAI-illustrious-SDXL",
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"baseModel": "Illustrious",
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}
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assert payload["base_model"] == "Illustrious"
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