mirror of
https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-09-29 15:04:09 -03:00
feat(recipes): preserve embedded ComfyUI workflow on remote imports
CivitAI serves a re-encoded, metadata-free optimized rendition as the recipe preview, so the ComfyUI workflow embedded in the original image was dropped: imported recipes reported has_workflow=false and never offered "Send Workflow to ComfyUI" even when the source image carried one. Recover the workflow from the original rendition and carry it to the save step as data, so the stored preview stays the small optimized image: - ExifUtils: embed a caller-supplied workflow during optimize_image's single encode pass, and add embed_workflow() to patch WebP EXIF in place (used by the verbatim skip_optimize branch and as a safety net). - RecipePersistenceService.save_recipe: embed metadata["workflow"] before detecting has_workflow. - analyze_remote_image: return the workflow recovered from the original rendition it already downloads for EXIF parsing. - RecipeManagementHandler: add _fetch_original_media() and workflow helpers; _do_import_from_url reuses them, and _do_import_remote_recipe fetches the original only when CivitAI reports a ComfyUI payload (meta.comfy) so workflow-less images pay no extra bandwidth. - Batch URL imports and the import modal forward the recovered workflow. Verified against the reported image: has_workflow flips from false to true and the recovered workflow matches the original (25 nodes, same graph id).
This commit is contained in:
Will Miao
@@ -1284,6 +1284,21 @@ class RecipeManagementHandler:
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_original_image_url,
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) = await self._download_remote_media(image_url)
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# CivitAI's optimized rendition is re-encoded and metadata-free, so an
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# embedded ComfyUI workflow only exists in the original. Fetch it
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# lazily: unlike the URL import path (which needs the original for
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# metadata parsing anyway), this path would download it purely for the
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# workflow, so it is skipped unless the API reports one.
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original_workflow = None
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if _original_image_url and self._meta_indicates_comfy_workflow(
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civitai_meta_raw
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):
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_raw_original, original_workflow = await self._fetch_original_media(
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_original_image_url
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)
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if original_workflow:
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metadata["workflow"] = original_workflow
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# Build a version-cached map of local model hashes to cache items so
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# CivitaiApiMetadataParser can skip CivitAI API calls for models that
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# exist on disk. Built once and shared by every parse pass below.
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@@ -2090,6 +2105,90 @@ class RecipeManagementHandler:
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except FileNotFoundError:
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pass
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def _read_embedded_workflow(self, image_path: Optional[str]) -> Optional[str]:
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"""Return a ComfyUI workflow embedded in ``image_path``, if any.
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``ExifUtils.extract_image_metadata`` stops at the generation
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parameters, so the UI-format workflow has to be read through the
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structured metadata reader. Failures map to ``None``.
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"""
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if not image_path or not os.path.exists(image_path):
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return None
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try:
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metadata = ExifUtils._load_structured_metadata(image_path)
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except Exception as exc:
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self._logger.debug(
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"Failed to read embedded workflow from %s: %s", image_path, exc
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)
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return None
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workflow = metadata.get("workflow") if isinstance(metadata, dict) else None
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return workflow if isinstance(workflow, str) and workflow else None
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@staticmethod
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def _meta_indicates_comfy_workflow(civitai_meta_raw: Any) -> bool:
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"""Whether CivitAI reports an embedded ComfyUI workflow for an image.
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``meta.comfy`` is the payload CivitAI captured from the original image,
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so its presence is the signal that fetching the original is worth the
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bandwidth when the caller does not already need it for metadata
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parsing.
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"""
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if not isinstance(civitai_meta_raw, dict):
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return False
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inner = civitai_meta_raw.get("meta")
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if isinstance(inner, dict) and inner.get("comfy"):
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return True
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return bool(civitai_meta_raw.get("comfy"))
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async def _fetch_original_media(
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self, original_image_url: Optional[str]
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) -> tuple[Optional[str], Optional[str]]:
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"""Download the original rendition and read its embedded media.
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CivitAI's optimized renditions are re-encoded and carry no metadata, so
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the original is the only source for embedded generation metadata and
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for the UI-format ComfyUI workflow (the raw extractor's fallback chain
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ends at ``workflow`` only when no prompt is present).
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Returns ``(raw_metadata, workflow)``; either element is ``None`` when
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unavailable. Failures never raise — imports keep working with the
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optimized rendition when the original cannot be fetched.
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"""
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if not original_image_url:
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return None, None
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with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as temp_file:
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temp_path = temp_file.name
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try:
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downloader = await self._downloader_factory()
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success, _result = await downloader.download_file(
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original_image_url, temp_path, use_auth=False
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)
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if not success:
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self._logger.warning(
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"Failed to download original rendition: %s", original_image_url
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)
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return None, None
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raw_metadata = await asyncio.to_thread(
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ExifUtils.extract_image_metadata, temp_path
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)
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workflow = await asyncio.to_thread(
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self._read_embedded_workflow, temp_path
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)
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return raw_metadata, workflow
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except Exception as exc:
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self._logger.warning(
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"Failed to read original rendition %s: %s", original_image_url, exc
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)
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return None, None
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finally:
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try:
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if os.path.exists(temp_path):
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os.unlink(temp_path)
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except OSError:
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pass
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def _safe_int(self, value: Any) -> int:
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try:
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return int(value)
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@@ -2295,6 +2394,7 @@ class RecipeManagementHandler:
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"Failed to extract embedded metadata: %s", exc
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)
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original_workflow: Optional[str] = None
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if not parsed_embedded and original_image_url:
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self._logger.debug(
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"Optimized image has no embedded metadata, "
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@@ -2302,48 +2402,32 @@ class RecipeManagementHandler:
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original_image_url,
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)
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try:
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downloader = await self._downloader_factory()
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with tempfile.NamedTemporaryFile(
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suffix=".png", delete=False
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) as tmp:
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orig_tmp_path = tmp.name
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try:
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success, _ = await downloader.download_file(
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original_image_url, orig_tmp_path, use_auth=False
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)
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if success:
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raw_orig = await asyncio.to_thread(
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ExifUtils.extract_image_metadata, orig_tmp_path
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raw_orig, original_workflow = await self._fetch_original_media(
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original_image_url
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)
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diagnostics["exif_present"] = bool(raw_orig) or bool(
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diagnostics.get("exif_present")
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)
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if raw_orig:
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parser = (
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self._analysis_service._recipe_parser_factory.create_parser(
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raw_orig
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)
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diagnostics["exif_present"] = bool(raw_orig)
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if raw_orig:
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parser = (
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self._analysis_service._recipe_parser_factory.create_parser(
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raw_orig
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)
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)
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if parser:
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diagnostics["exif_parser"] = parser.__class__.__name__
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if isinstance(parser, CivitaiApiMetadataParser):
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parsed_embedded = await parser.parse_metadata(
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raw_orig,
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recipe_scanner=recipe_scanner,
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local_cache=local_cache,
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)
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if parser:
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diagnostics["exif_parser"] = parser.__class__.__name__
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if isinstance(parser, CivitaiApiMetadataParser):
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parsed_embedded = await parser.parse_metadata(
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raw_orig,
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recipe_scanner=recipe_scanner,
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local_cache=local_cache,
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)
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else:
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parsed_embedded = await parser.parse_metadata(
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raw_orig, recipe_scanner=recipe_scanner
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)
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if (
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parsed_embedded
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and "gen_params" in parsed_embedded
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):
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embedded_gen_params = parsed_embedded[
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"gen_params"
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]
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finally:
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if os.path.exists(orig_tmp_path):
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os.unlink(orig_tmp_path)
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else:
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parsed_embedded = await parser.parse_metadata(
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raw_orig, recipe_scanner=recipe_scanner
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)
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if parsed_embedded and "gen_params" in parsed_embedded:
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embedded_gen_params = parsed_embedded["gen_params"]
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except Exception as exc:
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self._logger.warning(
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"Failed to extract metadata from original image: %s", exc
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@@ -2391,6 +2475,8 @@ class RecipeManagementHandler:
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"gen_params": embedded_gen_params or {},
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"source_path": image_url,
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}
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if original_workflow:
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metadata["workflow"] = original_workflow
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# Extract preview_nsfw_level from the CivitAI API response
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# (injected into civitai_meta_raw by _download_remote_media).
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