ComfyUI-Lora-Manager/docs/load-image-metadata.md

Load Image Metadata (LoraManager)

Load a source image and reuse its prompts, local models, LoRAs, and sampling settings. The node lives under Lora Manager → loaders. Restart ComfyUI after installing this change and refresh the page. This Python node needs no Vue widget build.

Wiring a checkpoint workflow

1. Upload/select an image in Load Image Metadata (LoraManager).
2. Convert ckpt_name on Checkpoint Loader (LoraManager) to an input and connect model_name. Leave its randomization control fixed.
3. Connect the checkpoint's MODEL and CLIP to Lora Loader (LoraManager). Connect the metadata node's lora_stack to that loader. Leave its LoRA widget empty unless you intentionally want additional LoRAs.
4. Connect the LoRA loader's CLIP to two CLIP Text Encode nodes. Connect metadata positive and negative to their text inputs, and their conditioning outputs to KSampler. Connect the LoRA loader's MODEL to KSampler.
5. Convert KSampler's seed, steps, cfg, sampler_name, scheduler, and denoise widgets to inputs and connect the corresponding metadata outputs.
6. For text-to-image, connect width/height to an appropriate Empty Latent node. For img2img, encode the image output with the appropriate VAE instead.
7. Connect KSampler's samples and the checkpoint's VAE to VAE Decode, then Save Image.
8. Connect readable_report to a text display node for prompts, sampling settings, model/LoRA names, local resolution status and warnings. The original report output remains notes followed by formatted JSON; it is not a pure JSON string.

model_name, sampler_name, and scheduler use COMBO outputs for converted dropdown inputs in current ComfyUI. model_name contains the matching local checkpoint or diffusion-model filename. The report identifies the resolved type; connect it to the appropriate loader. Lookup searches both categories regardless of how the original metadata labels the model.

For a diffusion-model workflow, connect model_name to Unet Loader (LoraManager) and select the correct text encoder(s), VAE, latent node and architecture-specific conditioning separately. These settings do not reconstruct an entire workflow or guarantee pixel-identical reproduction.

Selection and overrides

prefer_saved_image_metadata is enabled by default. It prefers the saved A1111-style generation parameters (including ComfyUI exports in that format) over the workflow. The report identifies this source; sampler_node_id is ignored in this mode when valid saved parameters are available. If saved parameters are absent or malformed, the node tries workflow metadata and reports any parsing failure.

Disable the flag to prefer workflow extraction. Only active samplers are eligible: muted/bypassed sampler nodes and samplers inside muted/bypassed subgraph instances are excluded. This uses the saved UI workflow's mode flags when available, including nested subgraphs, and any modes in the API graph. Explicitly selecting an inactive sampler produces an error report and the usual saved-parameter/default recovery; it never extracts that inactive stage.

With one supported active sampler, leave sampler_node_id blank. With several, enter its original node ID. Reports list candidate IDs when selection is ambiguous. Native subgraphs in API prompt metadata use colon-qualified paths: 1481:1783 means node 1783 inside subgraph instance 1481. Nested paths such as 10:20:30 are supported; slash notation (1481/1783) is also accepted. A container ID (1481) or leaf ID (1783) is accepted only if it identifies one sampler. An exact sampler ID takes precedence over abbreviated matching.

Selection follows that sampler's graph, rather than mixing branches. Supported sampling nodes include KSampler, KSamplerAdvanced and SamplerCustomAdvanced with standard RandomNoise, CFGGuider/BasicGuider, BasicScheduler and KSamplerSelect components. BasicGuider's CFG is 1; its architecture-specific lack of negative conditioning is reported. Known Image Saver parameter/selector outputs and rgthree seed values can be read without executing those nodes.

Detail Daemon's underlying sampler name is recovered, but its sampling effects are explicitly unsupported. Other custom model/conditioning nodes can still require defaults or overrides. If a requested stage cannot be read and global image parameters are used instead, the report explicitly says those parameters cannot verify the selected stage. Subgraph traversal requires the expanded API prompt; UI-workflow-only subgraph definitions are not expanded or executed.

Extraction errors do not stop this node. If an API prompt uses unsupported samplers, the node first tries the image's saved generation parameters. Any remaining unavailable or invalid extracted fields use the SDXL starter defaults; valid extracted fields are preserved. readable_report starts with ❌ ERROR and explains each recovery or substitution. This also applies to existing nodes saved with missing_settings=strict; that legacy option no longer blocks extraction recovery. New nodes default to use_defaults.

The report uses emoji section markers (🖼️ image, 📦 model, ⚙️ sampling, 🧩 LoRAs, ➕/➖ prompts) and ❌/⚠️/ℹ️ status markers. It is plain text, so colors depend on the connected display node. Missing/ambiguous local files still appear in missing_files. An empty model output requires selecting a local model manually. Invalid explicit overrides and unreadable image files remain execution errors.

overrides_json replaces extracted values, for example:

{
  "scheduler": "normal",
  "model_name": "portraits/model.safetensors",
  "seed": 12345,
  "loras": [["styles/ink.safetensors", 0.7, 0.3]]
}

Supported keys: positive, negative, model_name, seed, steps, cfg, sampler_name, scheduler, width, height, denoise, loras. LoRA entries are [name, model_strength, clip_strength]; "loras": [] explicitly clears the extracted stack. Legacy checkpoint_name and unet_name override keys remain accepted as aliases for model_name; supply only one model key. Exact relative or absolute local business paths disambiguate duplicate basenames. Matching falls back to a unique filename or extensionless filename, then an exact unique catalog file_name or model_name alias. Version dots are preserved when stripping known file extensions. It never downloads or fuzzy-matches models, and stale entries whose files no longer exist are excluded.

Images with no metadata automatically use a bottle-inspired SDXL starter preset, even with an existing saved strict setting: a glass-bottle/galaxy landscape prompt, negative text, watermark, seed 0, 20 steps, CFG 7, Euler/normal, 1024×1024 and denoise 1, with no LoRAs. These settings are clearly identified as synthetic defaults in both reports. Source image pixels and mask are unchanged. Overrides take precedence. The node selects sd_xl_base_1.0.safetensors only when uniquely indexed; otherwise choose an SDXL checkpoint manually or supply model_name. Malformed or unsupported metadata also recovers with an explicit ERROR report.

Supported metadata and limits

• PNG API prompt metadata; JPEG/WebP EXIF parameter comments; ComfyUI WebP prompt:/workflow: EXIF fields.
• Standard KSampler, core checkpoint/UNet/LoRA loaders, LoRA Manager checkpoint, UNet, LoRA/text loaders and LoRA stacks. LoRA application order and separate model/CLIP strengths are preserved, including intentional repeated entries. Different LoRA chains on model and prompt CLIP branches require an explicit stack override rather than being silently merged.
• Literal CLIPTextEncode text and supported primitive value connections. Prompt polarity comes from sampler wiring, never from words such as “ugly”.
• A1111/Forge generation text with explicit sampler alias mappings. Recognized LoRA directives become stack entries and are removed from prompt text. Literal tags in ComfyUI encoder text remain literal; graph loaders determine its stack.
• A1111 Automatic/absent schedules do not reliably identify a ComfyUI schedule. The node substitutes normal and reports the missing information as an ERROR; an explicit override can select a different schedule.
• UI-workflow-only fallback supports known core widget layouts, with a report warning. Saved widgets can differ from executed values (for example a seed randomized after generation). Custom widget layouts are not guessed.
• KSamplerAdvanced partial/noise settings require an explicit denoise override; this is an intentional approximation, not a reconstruction of those controls.
• Distinct SDXL/Flux encoder prompts, combined/regional/zeroed conditioning, arbitrary custom nodes, dynamic wildcards and unsupported custom sampling components are not automatically reconstructed. Supply explicit overrides or retain the original workflow for those cases.
• Width/height come from a recognized latent source or fall back to source-image dimensions; resized/upscaled images can therefore need dimension overrides.
• VAE, text encoder choice, CLIP skip, ControlNet and architecture-specific conditioning still need the appropriate nodes. No embedded code is executed and no external metadata service is contacted.

LoRA Manager must have indexed the required models. Library resolution includes its configured extra folders and preserves business paths through symlinks.

Extraction without a local catalog

The parser extracts names before attempting local resolution. In recovery mode, report includes source_resources with original model names, LoRA names and strengths, and embedded resource hashes even when none are installed. The model output sockets remain empty and the resolved stack excludes missing files.

Combined sampler labels such as Euler a SGM Uniform, Euler Normal and er_sde simple are split into sampler and scheduler. Multiline parameter blocks and their nested JSON resource lists are supported. If prompt LoRA tags are absent, one hash-name entry and one weighted resource can be matched offline; multiple entries require an explicit mapping rather than guessing from order. A single resource also disambiguates duplicated identical prompt tags.

The Model field in A1111-style metadata does not distinguish checkpoints from standalone diffusion models. The node searches both indexed categories by name, then reports the matched type. Local model type and filename cannot be verified without an indexed library. Multiple equally good matches are reported as ambiguous; specify a relative path through model_name to disambiguate.

“Image contains no supported generation metadata”

For older versions, this means extraction failed before any library lookup. The current node uses the starter preset when metadata is entirely absent. The error identifies the actual server file, its format, byte size and metadata keys. PNG text chunks are read both before and after pixel data. If no generation metadata remains, upload the original saved file: clipboard copies and re-encoded/exported images may lose it. use_defaults supplies replacement settings; it does not recover the original prompts or seed.

Missing local resources

missing_files is a text output listing unresolved checkpoints/UNets and LoRAs. LoRA entries include both model and CLIP weights and the resolution failure. It is empty when all requested resources resolve. Missing and ambiguous LoRAs are excluded from lora_stack, including in strict mode, so downstream loaders receive only resolved files. Valid entries keep their original order and weights. Unresolved model-name sockets are empty: select a model manually or override its name before connecting that socket to a loader.

Output layout and upgrade

The outputs start with image, mask, positive, negative, model_name, lora_stack, lora_stack_text, followed by the sampling settings and reports. lora_stack_text lists each resolved stack path with model and CLIP weights in application order. It is empty for an empty stack; unresolved files appear only in missing_files, with their requested weights.

This replaces the former separate checkpoint/UNet sockets and renames lost_list to missing_files. Restart ComfyUI, refresh, and recreate existing instances of this node; reconnect the model and stack outputs to avoid stale saved slot indices. Sampling and report output indices remain unchanged. No Vue build is required.