generate.py: p.ip_adapter_masks was reinitialized inside the per-adapter loop, discarding all but the last adapter's masks; move it beside the other accumulators. process.py: req.params is dict|None, so a null params body crashed .items() in post_preprocess/post_mask. api.py: split(':') without maxsplit broke auth/auth-file entries whose password contains a colon. gallery.py: allowed_paths stored quote(path) but the membership check and path guards use the raw path, causing duplicate accumulation and an ineffective whitelist; also drop the unused FastAPI import (pylint W0611 surfaced when this file is linted).
Co-Authored-By: Claude <noreply@anthropic.com>
Surface YoloRestorer.restore() as a standalone operation: a Detailer
postprocessing script in the Process tab and a thin /sdapi/v1/detail
endpoint, neither requiring a base generation pass.
- modules/postprocess/yolo.py: YoloRestorer.make_processing() builds the
synthetic Img2Img processing object both entry points feed to restore(),
resolving the seed so the inpaint passes are reproducible
- modules/api/process.py: post_detail handler exposes the full detailer
parameter set and returns the detailed image plus optional annotations
as base64
- scripts/postprocessing_detailer.py: reuses shared.yolo.ui('extras') and
runs through make_processing()
- modules/postprocessing.py: run_extras takes a per-script script_args
dict, also letting the extras API drive other scripts such as Remove
background; omitting it leaves existing callers unchanged
- modules/api/models.py: ReqDetail / ResDetail
- modules/processing_info.py: guard create_infotext's Image/Hires CFG
reporting against an unset (None) cfg_image, matching the is-not-None
checks the other cfg_image readers use; the detailer inpaint pass runs
with it unset
- test/test-detailer-api.py: covers both paths; effect tests measure the
diff inside the detected region with extreme isolated parameter values,
and the suite disables model quantization for the run and restores the
original settings afterward
Tag dictionaries are lookup data, not model weights — place them
alongside cache.json and metadata.json in the data/ folder instead
of inside the models directory.
Move all caption/interrogate/tagger/VQA API code out of the monolithic
endpoints.py and models.py into a new self-contained modules/api/caption.py,
following the loras.py / nudenet.py self-registering pattern.
- Move 15 Pydantic models (ReqCaption, ResCaption, ReqVQA, ResVQA,
ReqTagger, ResTagger, dispatch union types, etc.) from models.py
- Move 11 handler functions from endpoints.py
- Deduplicate ~150 lines via shared _do_openclip, _do_tagger, _do_vqa
core functions called by both direct and dispatch endpoints
- Add register_api() that registers all 8 caption routes
- Add promptgen field to ResVLMPrompts (bug fix: handler returned it
but response model silently dropped it)
- Improve all endpoint docstrings and Field descriptions for API docs
Add comprehensive caption/interrogate API with documentation:
- GET /sdapi/v1/interrogate: List available interrogation models
- POST /sdapi/v1/interrogate: Interrogate with OpenCLIP/BLIP/DeepDanbooru
- POST /sdapi/v1/vqa: Caption with Vision-Language Models (VLM)
- GET /sdapi/v1/vqa: List available VLM models
- POST /sdapi/v1/vqa/batch: Batch caption multiple images
- POST /sdapi/v1/tagger: Tag images with WaifuDiffusion/DeepBooru
Updates:
- Add detailed docstrings with usage examples
- Fix analyze_image response parsing for Gradio update dicts
- Add request/response models for all endpoints
- Remove /sdapi/v1/face-restorers route from api.py
- Remove get_restorers() function from endpoints.py
- Remove gfpgan_visibility, codeformer_visibility, codeformer_weight
fields from ReqProcess model
- Remove GFPGAN and CodeFormer entries from run_extras() signature
and create_args_for_run dict in postprocessing.py