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Author SHA1 Message Date
Will Miao f8d98934ad feat(ui): set preview via drag and drop on model cards (#1034) 2026-08-14 13:01:10 +08:00
Will Miao 303cca0d85 fix(download): accept newer CivitAI file types for primary file selection
Downloads failed with "No suitable file found in metadata" for models whose
only file uses newer CivitAI file types (e.g. 'Enhancement LoRA' for
Anima/AIR image-editing LoRAs) because the primary-file allowlist only
covered legacy types.

- unify the weights-type allowlist as MODEL_WEIGHT_FILE_TYPES
  (py/utils/constants.py) and apply it across download, recipe and
  metadata-refresh lookups
- mirror CivitAI's getPrimaryFile() semantics: prefer weights-type primary,
  fall back to weights files, then trust CivitAI's primary flag (excluding
  non-downloadable artifacts like Config/Archive/Workflow)
- mirror the allowlist in the frontend via shared isModelWeightFile() helper
- add regression tests for the Enhancement LoRA primary-file download,
  primary-flag fallback and weights-over-non-weights-primary preference
2026-08-12 21:14:23 +08:00
Will Miao c2f16784b3 fix(metadata): keep identity selectors from leaking unselected prompts 2026-08-12 19:44:43 +08:00
Will Miao 5bc6d8286c fix(metadata): exclude scalar fields from conditioning provenance inputs 2026-08-12 19:18:46 +08:00
Luna_K 3f8381ffee Fix prompt tracking through conditioning transforms 2026-08-12 19:16:30 +08:00
Will Miao 1ca99294c9 feat(delete): shorten undo window to 20s and make undo toast dismissible 2026-08-12 19:15:03 +08:00
Will Miao 680f0a57f5 fix(update): resolve template path when updating to a different base model (#1059)
Version-tab updates reused the current version's folder, so updating a LoRA
to a version with a different base model (e.g. Illustrious -> Anima) ignored
the download path template and landed in the old version's directory.

When the target version's base model differs from the current local version
and a path template is configured, re-resolve the template under the same
model root. The backend keeps an explicitly provided root when
use_save_dir_as_root is set, so regular downloads still use the default root.
2026-08-12 18:45:54 +08:00
Will Miao 94e3f54571 feat(workflow): exclude text-capable nodes with connected text from send targets
CLIP Text Encode and friends whose text widget is backed by a connected
input cannot have their text changed via the widget (execution reads the
linked input), so sending to them was a silent no-op.

- Registry: compute text_widget_connected capability from the widget's
  backing input link state; has_text_widget drops to false when wired;
  include the flag in the registration fingerprint so link changes
  re-register the affected nodes
- Registry: hook link connect/disconnect (graph events on new litegraph,
  onAfterChange fallback for classic) on root and subgraphs, plus
  subgraph-created for future subgraphs
- applyWidgetUpdate: skip inject_text when the target widget is connected
  and self-heal the registry instead of writing a value that is ignored
- Web UI: drop text_widget_connected nodes from prompt/embedding send
  candidates; show a Mark as -> Send Prompt Target hint toast when no
  candidates remain (new uiHelpers.workflow.noPromptTargets key, synced
  to all locales; zh-CN/zh-TW translated)
- Extract shared resolveTextWidget() used by both the candidate-set
  logic and the write path so the two cannot drift apart
- Tests: workflow registry connection-state registration, subgraph
  handling, fingerprint re-registration, inject_text write/skip paths,
  setup link-change hooks; uiHelpers candidate filtering and hint toast
2026-08-12 16:50:07 +08:00
Will Miao 5c2b2aedcc fix(i18n): complete recipe delete undo warning translations
Translate modals.deleteRecipe.recoverableWarning in all 9 non-English
locales (de, es, fr, he, ja, ko, ru, zh-CN, zh-TW)
2026-08-11 21:20:54 +08:00
Will Miao ebc31fb963 fix(i18n): translate recipe delete undo warning
Move the recipe delete modal's undo warning into modals.deleteRecipe.
recoverableWarning instead of hardcoded English; sync placeholders into
all 9 non-English locales
2026-08-11 21:18:36 +08:00
Will Miao 9659df6ad9 refactor(delete): make undo unconditional, remove undo toggle and button delay
- Remove delete_undo_enabled setting (backend default, frontend state,
  settings modal UI, 10 locales); staged deletes with 30s undo are now
  the only delete path and stale settings keys are silently ignored
- Remove the 1500ms delete-button arm delay (armDeleteButton) from all
  delete modals; misclicks are recoverable via the undo toast
- Delete modal always shows the recoverable warning
- Log the first staged file path in staging log lines for easier support
2026-08-11 21:15:59 +08:00
Will Miao 04d131e9dc docs(delete): correct same-volume guarantee after symlink fix 2026-08-11 19:01:44 +08:00
Will Miao 78fe6282c7 test(delete): symlink and restart regression for staged deletes 2026-08-11 19:00:28 +08:00
Will Miao 0c00ee22fc fix(delete): stage model deletes into the model folder (avoid EXDEV) 2026-08-11 18:48:03 +08:00
Will Miao 5fd4946b1f fix(delete): track staged batches in-process; reconcile at startup 2026-08-11 18:36:30 +08:00
Will Miao f1d3ac0cdc fix(metadata): fill local file facts when self-heal recreates sidecar
Refresh after manual .metadata.json deletion rebuilds the payload without
file_name/size/modified, which are required by BaseModelMetadata.from_dict.
The recreated sidecar then fails to parse and the scanner skips the model.

- load_metadata_payload fills missing file facts from os.stat
- hydrate_model_data restores every missing key from the cache snapshot
  only when the sidecar is missing entirely (disk stays authoritative
  otherwise), preferring the cached import timestamp for modified
- save_metadata fills file facts on write so no write path can produce
  an unparseable sidecar
2026-08-11 14:57:23 +08:00
Will Miao e2c45905f0 test(recipe): await background resort deterministically in pagination tests 2026-08-11 14:09:24 +08:00
Will Miao b2c68e6a65 feat(delete): add undo toasts and harden delete modals 2026-08-11 14:09:10 +08:00
Will Miao eb0f6dd3b6 feat(settings): add delete_undo_enabled toggle 2026-08-11 14:08:55 +08:00
Will Miao 0bf87f9092 chore(i18n): add undo-delete and delete-confirmation strings 2026-08-11 14:08:41 +08:00
Will Miao 1da2433bb2 feat(delete): add undo-delete endpoint and purge scheduling 2026-08-11 14:08:28 +08:00
Will Miao 2d6cf545b9 feat(delete): stage model and recipe deletes for 30s undo 2026-08-11 14:08:15 +08:00
Will Miao 6a259a14fa feat(nodes): flag missing local models at queue and load time (#1057) 2026-08-10 12:31:36 +08:00
Will Miao 41e1fd1e1f feat(download): expose aria2 disk write failure root cause at INFO level
Promote aria2 stderr lines that indicate disk write failures (e.g. the
'cause: No space left on device' line following 'Write disk cache flush
failure') from DEBUG to INFO so the root cause is visible in default logs,
including Windows-specific phrases (file locked by another process, sharing
violation). The same line is rate-limited to one INFO report per 60s window
and the report map is pruned on insert so repeated failures cannot spam the
log or grow memory. All other stderr output stays at DEBUG.
2026-08-10 09:45:13 +08:00
Will Miao 95fb3c7fc9 feat(recipes): add prompt-aware duplicate detection toggle 2026-08-10 00:07:14 +08:00
Will Miao 8237e5f9ea feat(ui): mark repair recipe data entries as deprecated
Add (Deprecated) label suffix to the three context menu entries for
repairing recipe data (global, bulk, single) ahead of their removal.
2026-08-09 15:50:02 +08:00
Will Miao aa75986178 fix(ui): hide context menu separator with no visible items 2026-08-09 15:44:10 +08:00
Will Miao b887922055 fix(i18n): translate rematch metadata strings 2026-08-09 15:33:24 +08:00
Will Miao 68fa0f29c7 feat(recipes): report rematch results with aggregate logs and toast feedback 2026-08-09 14:37:23 +08:00
Will Miao d9d362c9c9 fix(download): self-heal aria2 transfers lost on daemon restart 2026-08-09 12:48:36 +08:00
Will Miao d0bc4be0dc chore(skill): harden lora-manager-e2e for sandboxed E2E 2026-08-09 11:31:04 +08:00
Will Miao 420530f532 feat(ui): add global, bulk and per-recipe rematch actions 2026-08-09 11:31:00 +08:00
Will Miao 3001f0f0ef feat(recipes): add recipe rematch API endpoints 2026-08-09 11:30:50 +08:00
Will Miao b2a1307d23 feat(recipes): add recipe rematch WebSocket progress channel 2026-08-09 11:30:46 +08:00
Will Miao 64da845a58 feat(recipes): add local-only recipe rematch to scanner 2026-08-09 11:30:43 +08:00
Will Miao 27027c4497 refactor(recipes): reuse shared local hash cache in create-from-example 2026-08-08 22:45:29 +08:00
Will Miao 86c85c08ec feat(recipes): pass local hash cache to remote and url recipe imports 2026-08-08 22:13:19 +08:00
Will Miao 196c8ffc3e feat(recipes): match civitai image hash sections against local hash cache 2026-08-08 22:12:47 +08:00
Will Miao cfc95ee02a feat(recipes): pass local hash cache through analysis recipe parsing 2026-08-08 22:11:50 +08:00
Will Miao 479fa36997 feat(recipes): add version-cached local hash cache builder 2026-08-08 22:04:09 +08:00
Will Miao 3e1216e9bc feat(recipes): add cache version counter to model scanners 2026-08-08 21:57:36 +08:00
Will Miao 007883b7d1 fix(recipes): backfill lora cache item by autov2/autov3 hash too 2026-08-08 21:51:34 +08:00
Will Miao dc9200a12c fix(recipes): match recipe-format lora cache item by autov2/autov3 hash 2026-08-08 21:50:33 +08:00
Will Miao d2f955266d fix(types): resolve pre-existing basedpyright errors in tests
Fix ~790 basedpyright errors across the test suite:
- Type stub subclasses of real production classes with super().__init__()
- Add missing generic type arguments and Dict[str, Any] annotations
- Add None guards before subscript/member access
- Adapt tests to production API changes (removed dead handlers,
  PersistentModelCache.get_default, _i18n_filter_added location)
2026-08-08 20:12:59 +08:00
Will Miao 8e724538bd fix(types): resolve pre-existing basedpyright errors in py/ and standalone.py
Fix ~950 basedpyright errors across the backend:
- Convert ineffective # type: ignore comments to # pyright: ignore[rule]
- Add missing generic type arguments (Dict[str, Any], list[Any], ...)
- Annotate dynamic dict literals and runtime-initialized attributes
- Widen CivitAI provider tuple signatures in recipe parsers
- Remove dead LoraRoutes handlers calling nonexistent LoraService methods
- Suppress unavoidable ServiceRegistry import cycles (basedpyright counts
  function-local imports as cycle edges)
2026-08-08 20:12:52 +08:00
Will Miao 6fcdeb799d feat(metadata): resolve AutoV3 at download time without waiting for backfill
- Read AutoV3 directly from the downloaded file's own file_info hashes
  (no SHA256 cross-matching against version_info.files, so the value is
  captured even when the API omits SHA256)
- Extract normalize_autov3() validation helper shared with the
  sha256-matching autov3_from_civitai_files path
- Fall back to the embedded safetensors header hash at download
  completion; mark '' (checked-unavailable) so the startup backfill
  query (autov3 IS NULL) never revisits the row
- Clear archive-level AutoV3 for zip-extracted models so per-file
  header resolution applies to every extracted model
2026-08-08 15:20:43 +08:00
Will Miao 97b9b1f62b feat(metadata): add CivitAI AutoV3 hash support across all storage layers
- Three-state autov3 field (not-checked / checked-unavailable / 12-hex value)
  in .metadata.json sidecars, in-memory ModelHashIndex, and SQLite
  (models.autov3 column + autov3_index table) with column-presence migration
- Background self-terminating backfill for legacy rows: per-model-type
  concurrency guard, executor-offloaded I/O, Civitai-first resolution
  (SHA256-matched version file) falling back to the embedded safetensors
  header hash
- Civitai-first propagation on metadata refresh, scan, and download paths;
  reject the empty-string SHA256 placeholder and strip OneTrainer 0x prefix
- List API hash filters and hash index lookups accept 12-char AutoV3
- Cap safetensors header reads at 64 MiB to prevent crafted-file allocation
- Prevent stale AutoV3 mappings on file replacement while preserving them on
  same-file re-registration (lazy-hash completion)
2026-08-08 14:30:34 +08:00
Will Miao 4bf9a4b640 refactor(download): rename locationStep id to downloadLocationStep
The download modal's step shared the 'locationStep' id with the import
modal, so getElementById('locationStep') could resolve to the wrong
element depending on template include order. The import flow relied on
an injected display:block !important rule to work around it.

Rename the download modal's step id and update all references so each
modal owns a unique step id.
2026-08-08 08:50:36 +08:00
Will Miao c5088772e8 fix(ui): pin import modal action buttons with sticky footer
Make the import modal a flex column with a scrollable step area so the
Back/Import buttons stay visible on short viewports (1080p / 150% zoom)
instead of being cut off at the bottom of the scroll flow.

Also reset step scroll positions via class since 'locationStep' has a
duplicate id in the download modal template.
2026-08-08 08:49:20 +08:00
Will Miao 56acefbd6c feat(autocomplete): search loras within active filters of LoRA Manager page
Add /af and /noaf toggle commands (plus /activefilters aliases) to the
loras autocomplete widget. When enabled (default off), suggestions are
matched within the active filters (folder, base model, tags, auto-tags,
license, tag logic) persisted by the LoRA Manager page in localStorage,
keeping the match pool consistent with the list endpoint, including the
global show_only_sfw setting.

Backend: /lm/{prefix}/relative-paths accepts the filter query params and
pre-filters the scanner cache with ModelFilterSet. The presence of the
recursive param signals the filter pipeline to run even without concrete
filters so global settings stay in parity with the list endpoint.
2026-08-07 20:07:34 +08:00
Will Miao 5ab06c4aae docs: rename "Standalone Web UI" to "LoRA Manager Web UI" in AGENTS.md 2026-08-07 17:57:01 +08:00
Will Miao c11f4b5c68 feat(ui): widen filter panel and preset name limit 2026-08-07 16:53:14 +08:00
Will Miao 86376284f4 fix(ui): clamp filter panel height to viewport 2026-08-07 16:53:04 +08:00
Will Miao 2b8a2fc7d8 feat(filters): remove preset count limit 2026-08-07 16:52:53 +08:00
Will Miao f26e1b41c8 fix(i18n): translate zh-TW api key placeholder 2026-08-07 16:25:40 +08:00
Will Miao c1671af99f feat(downloads): translate batch download summary strings 2026-08-07 16:23:55 +08:00
Will Miao ac7707d0f6 fix(cards): clear model-card min-width on the item element itself 2026-08-07 16:09:51 +08:00
Will Miao 381cd710a2 feat(recipes): translate recipes layout setting strings 2026-08-07 15:36:30 +08:00
Will Miao ad0d18cb79 chore: ignore .playwright-mcp working directory 2026-08-07 15:33:43 +08:00
Will Miao 7980ee77d0 perf(recipes): batch preview dimension reads via asyncio.gather 2026-08-07 15:31:13 +08:00
Will Miao 916b8bb327 fix(recipes): skip stale scroller re-enable on deferred layout switch 2026-08-07 14:03:13 +08:00
Will Miao 87e3d4dea9 feat(recipes): wire recipes layout switch event and rebuild 2026-08-07 12:49:30 +08:00
Will Miao 76a913f5e0 feat(recipes): complete MasonryScroller public API parity with VirtualScroller 2026-08-07 12:40:28 +08:00
Will Miao d8c192e647 feat(recipes): branch masonry scroller instantiation for recipes page 2026-08-07 12:38:17 +08:00
Will Miao c453437620 feat(recipes): add MasonryScroller with column-based virtual scrolling 2026-08-07 12:31:13 +08:00
Will Miao 720fa6d909 feat(recipes): expose preview width/height in recipe listing API 2026-08-07 11:59:26 +08:00
Will Miao b4f71089f4 feat(recipes): add recipes_layout setting (grid|masonry) with i18n 2026-08-07 11:49:12 +08:00
Will Miao 83e6657ead feat(recipes): add get_image_dimensions helper with LRU cache 2026-08-07 11:47:28 +08:00
Will Miao 7ea6df4111 feat(downloads): default to latest version when URL lacks modelVersionId
Auto-select the first (newest) version for URLs without an explicit
modelVersionId, matching the existing batch flow, so users can proceed
to location/download without manually picking a version.
2026-08-07 11:24:45 +08:00
Will Miao d9ab92602a feat(downloads): show failure summary modal for single downloads too 2026-08-07 10:49:14 +08:00
pixelpaws 5ffadaed31 Merge pull request #1054 from willmiao/feat/gemini-provider
feat(llm): add Gemini as a preset AI provider
2026-08-07 10:30:45 +08:00
Will Miao 24f5f7df5d feat(llm): add Gemini as a preset AI provider 2026-08-07 10:27:51 +08:00
Will Miao daf01fb1d6 feat(downloads): show batch download summary with failure details and retry 2026-08-07 10:23:17 +08:00
Will Miao 0f11b6def9 fix(recipes): allow recipes storage path on a different drive (Windows)
os.path.commonpath raises ValueError for paths on different Windows
drives. Treat that as no common root so cross-drive recipes migrations
succeed instead of failing with 'Invalid recipes path change'.
2026-08-06 22:18:24 +08:00
Will Miao 7df83f44b8 feat(SaveImageLM): add add_loras_to_prompt toggle to restore legacy lora syntax line in metadata 2026-08-06 15:58:18 +08:00
Will Miao 169fa7bed6 fix(vue-widgets): resolve pre-existing typecheck errors 2026-08-06 15:33:02 +08:00
Will Miao 027b504fe8 refactor(autocomplete): remove unused custom_words and embeddings modelTypes 2026-08-06 15:28:58 +08:00
Will Miao 186ef4da78 refactor(ui): group example image download actions into a submenu
Move the 'Download Missing' / 'Re-process All' example image actions
under a single 'Download Example Images' submenu item in the single-model
and bulk context menus, matching the existing send-to-workflow submenu
pattern. Shorten the submenu labels and update all locale translations.
2026-08-03 21:18:05 +08:00
pixelpaws dc674098e7 Merge pull request #1050 from willmiao/fix/recipes-bulk-content-rating
fix(recipes): enable bulk content rating for selected recipes
2026-08-03 20:58:24 +08:00
Will Miao 9087b4b07c feat(example-images): add missing-only download path and skip existing files
Split the single-model and bulk context menu actions into 'Download
Missing Example Images' (regular endpoint, skips already-processed
models) and 'Re-process Example Images' (force endpoint, retries
failed models).

- start_download accepts model_hashes so a selected subset can be
  processed with the progress-aware skip logic; explicitly targeted
  models bypass the failed/processed model-level guards so per-image
  gaps are filled
- pre-download existence check in the processor skips network requests
  for image files already on disk across all download paths
- force download retries previously failed models and clears their
  failed status on success
- add i18n keys for the new menu items across all locales
2026-08-03 20:52:46 +08:00
Will Miao 8e45c22d7a fix(recipes): enable bulk content rating for selected recipes 2026-08-03 19:31:58 +08:00
Will Miao 191c4e03cd feat(metadata-overwrite): support wired MODEL input on model field
The model field now accepts either a manual string or a MODEL connection.
When wired, the model name is extracted from the patcher's
cached_patcher_init (registered by core loaders load_checkpoint_guess_config
and load_diffusion_model, preserved through LoRA clones) and converted to a
ComfyUI-style relative name via config model roots.

- model input declared as "STRING,MODEL" with widgetType STRING, so the
  text widget and the dual-type connection slot coexist; non-STRING/MODEL
  links are rejected by frontend and backend type validation
- UNETLoaderLM GGUF branch now registers a custom cached_patcher_init reload
  factory so GGUF models participate in name extraction and ModelPatcher
  deepclone/dynamic machinery
- shared collect_overwrite_params() helper keeps the node and the metadata
  extractor conversion logic in sync; extraction failures are logged instead
  of silently dropping the overwrite
2026-08-03 16:44:03 +08:00
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---
name: lora-manager-e2e
description: End-to-end testing and validation for LoRa Manager features. Use when performing automated E2E validation of LoRa Manager standalone mode, including starting/restarting the server, using Chrome DevTools MCP to interact with the web UI at http://127.0.0.1:8188/loras, and verifying frontend-to-backend functionality. Covers workflow validation, UI interaction testing, and integration testing between the standalone Python backend and the browser frontend.
description: End-to-end testing and validation for LoRa Manager features. Use when performing automated E2E validation of LoRa Manager standalone mode in a SANDBOXED, disposable configuration: check the port, start/restart the standalone server on a free port, use Chrome DevTools MCP to interact with the web UI (http://127.0.0.1:{PORT}/loras), and verify frontend-to-backend functionality. Covers workflow validation, UI interaction testing, and integration testing between the standalone Python backend and the browser frontend. Trigger keywords: E2E, standalone, Chrome DevTools MCP, lora-manager-e2e, sandbox.
---
# LoRa Manager E2E Testing
This skill provides workflows and utilities for end-to-end testing of LoRa Manager using Chrome DevTools MCP.
## Conventions Used in This Document
- **`{PORT}`**: The server port. The default candidate is `8188`, but **`8188` is commonly occupied by a live ComfyUI process** and MUST NOT be assumed to be free. Always check availability first (see [Port Selection](#port-selection)) and use a free port (e.g. `8199`) for the E2E run. Substitute the actual port for every `{PORT}` in the commands below.
- **`<repo-root>`**: The repository/worktree root. Always run commands from the repo or worktree root; never assume a specific absolute path (paths such as `/home/<user>/...` differ per machine). The E2E scripts resolve the project root themselves, but fixture/settings paths are relative to `<repo-root>`.
## SANDBOX (MANDATORY)
> **Read this section before running anything.** Every E2E run MUST target a throwaway sandbox, never the real user data. A fresh subagent that skips this section WILL permanently mutate real user recipes.
1. **Portable settings**: create `<repo-root>/settings.json` (gitignored) with `"use_portable_settings": true` plus sandboxed `folder_paths` (lora/checkpoint roots) and `recipes_path`. This keeps the configuration inside the repo instead of the real user config dir (`~/.config/ComfyUI-LoRA-Manager/settings.json`).
2. **Sandboxed paths**: point `folder_paths` / `recipes_path` / `example_images_path` at disposable dirs — e.g. under `/tmp/opencode/<plan-name>-e2e/` (or worktree-local dirs). NEVER point the E2E at the real library (`~/models/...`), real recipe dir, or real settings.
3. **Never touch the real config**: the real user config at `~/.config/ComfyUI-LoRA-Manager/settings.json` and the real recipe dir must remain byte-identical before and after the run.
4. **Record real-data protection proof** before starting and after finishing:
```bash
# BEFORE: snapshot real config + recipe library state
sha256sum ~/.config/ComfyUI-LoRA-Manager/settings.json > /tmp/opencode/<plan>-e2e/settings.before.sha256
ls ~/models/recipes/*.recipe.json 2>/dev/null | wc -l > /tmp/opencode/<plan>-e2e/recipes-count.before.txt
find ~/models/recipes -name '*.recipe.json' -newermt "$(date -Iseconds)" | head # expect empty after run
# AFTER: record again, then diff the two snapshots. Any change = the run leaked into real data.
```
Also confirm `<repo-root>/git status` stays clean for `settings.json`/`cache/` (both are gitignored).
### Portable Settings Example
```json
{
"use_portable_settings": true,
"folder_paths": {
"loras": ["/tmp/opencode/<plan>-e2e/models/loras"],
"checkpoints": ["/tmp/opencode/<plan>-e2e/models/checkpoints"],
"unet": ["/tmp/opencode/<plan>-e2e/models/checkpoints"],
"diffusers": []
},
"recipes_path": "/tmp/opencode/<plan>-e2e/recipes",
"example_images_path": "/tmp/opencode/<plan>-e2e/example_images"
}
```
The scanner computes and persists model hashes during the library scan, so the sandbox model dirs just need the model files + `.metadata.json` sidecars (see [Fixture + Fresh-State Guidance](#fixture--fresh-state-guidance)).
## Time Budgets & Abort Guidance
A fresh subagent should complete a sandboxed standalone E2E **in well under 30 minutes**. Budget each phase:
| Phase | Expected duration | Abort if |
| --- | --- | --- |
| Port check + sandbox setup | < 2 min | — |
| Server start (detached) + readiness | < 30 s | > 60 s (2x) → stop |
| Chrome DevTools MCP connect | < 1 min | > 2 min → stop |
| Per entry-point run (after fixtures ready) | < 5 min | > 10 min (2x) → stop |
| Fixture reset + cache clear between runs | < 1 min | > 2 min → stop |
**Abort rule**: if a phase exceeds ~2x its budget, OR any single tool call fails/retries 3+ times in a row, **STOP**. Do not loop or retry blindly. Report `BLOCKED` with: the phase, the last observed state (server PID + `ss -tlnp` output, page snapshot, last API response), and the suspected cause. Record the partial state as evidence; a clean BLOCKED report is more valuable than an hour of retries.
## Prerequisites
- LoRa Manager project cloned and dependencies installed (`pip install -r requirements.txt`)
- LoRa Manager project cloned and dependencies installed (`pip install -r requirements.txt`) — run everything from `<repo-root>`
- Chrome browser available for debugging
- Chrome DevTools MCP connected
- `ss` (or `lsof`/`netstat`) available for port checks: `ss -tlnp`
## Quick Start Workflow
## Port Selection
### 1. Start LoRa Manager Standalone
```python
# Use the provided script to start the server
python .agents/skills/lora-manager-e2e/scripts/start_server.py --port 8188
```
Or manually:
```bash
cd /home/miao/workspace/ComfyUI/custom_nodes/ComfyUI-Lora-Manager
python standalone.py --port 8188
```
Wait for server ready message before proceeding.
### 2. Open Chrome Debug Mode
`8188` is only the *default candidate*. Verify it is actually free before every run:
```bash
# Chrome with remote debugging on port 9222
google-chrome --remote-debugging-port=9222 --user-data-dir=/tmp/chrome-lora-manager http://127.0.0.1:8188/loras
# Is anything listening on 8188?
ss -tlnp | grep ':8188' || echo "8188 is free"
```
### 3. Connect Chrome DevTools MCP
- If a process holds `8188` (e.g. a live ComfyUI — pid 6575 on this machine), pick a different free port, e.g. `8199`:
```bash
ss -tlnp | grep ':8199' || echo "8199 is free"
```
- **Never** kill a process you did not start for this E2E. The live ComfyUI is off-limits. Pick a free port instead.
- Use your chosen port for **all** subsequent commands (server, Chrome launch, browser URLs).
Ensure the MCP server is connected to Chrome at `http://localhost:9222`.
## Quick Start Workflow (sandboxed)
### 4. Navigate and Interact
### 1. Prepare the sandbox
```bash
cd <repo-root> # ALWAYS run from the repo/worktree root
mkdir -p /tmp/opencode/<plan>-e2e/models/{loras,checkpoints}
mkdir -p /tmp/opencode/<plan>-e2e/{recipes,example_images,recipes-before}
# write <repo-root>/settings.json per the portable-settings example above
# record real-data protection proof (see SANDBOX section)
```
### 2. Check port availability
```bash
ss -tlnp | grep ':{PORT}' || echo "port {PORT} is free"
```
If `{PORT}` is occupied by an unrelated process, pick a free one and use it everywhere below. When in doubt use `8199`.
### 3. Start LoRa Manager Standalone (detached)
The standalone server **dies with the shell unless launched fully detached** — a plain background `&` from the bash tool is killed when the tool call returns. Launch via the helper script:
```bash
python .agents/skills/lora-manager-e2e/scripts/start_server.py --port {PORT} --wait --timeout 30 --detach
```
Or manually (equivalent detached form):
```bash
setsid nohup python standalone.py --port {PORT} --host 127.0.0.1 < /dev/null \
>> /tmp/opencode/<plan>-e2e/server.log 2>&1 &
echo "started" # record the printed/pidfile PID for cleanup
```
Verify it is listening **before** proceeding (readiness poll is not a substitute for this):
```bash
ss -tlnp | grep ':{PORT}'
```
Record the server PID for cleanup: the helper script writes it to `/tmp/lora-manager-e2e-server-{PORT}.pid`; a manual `setsid` launch has no pidfile, so capture it explicitly (e.g. from `ss -tlnp`).
### 4. Open Chrome Debug Mode
```bash
# Chrome with remote debugging on port 9222 (note the {PORT} URL)
google-chrome --remote-debugging-port=9222 --user-data-dir=/tmp/chrome-lora-manager http://127.0.0.1:{PORT}/loras
```
### 5. Connect Chrome DevTools MCP
Ensure the MCP server is connected to Chrome at `http://localhost:9222`. Verify with `list_pages` — if it fails with "browser is already running", see [Chrome DevTools MCP Troubleshooting](#chrome-devtools-mcp-troubleshooting).
### 6. Navigate and Interact
Use Chrome DevTools MCP tools to:
- Take snapshots: `take_snapshot`
@@ -56,7 +154,7 @@ Use Chrome DevTools MCP tools to:
```python
# Navigate to LoRA list page
navigate_page(type="url", url="http://127.0.0.1:8188/loras")
navigate_page(type="url", url="http://127.0.0.1:{PORT}/loras")
# Wait for page to load
wait_for(text="LoRAs", timeout=10000)
@@ -68,9 +166,10 @@ snapshot = take_snapshot()
### Pattern: Restart Server for Configuration Changes
```python
# Stop current server (if running)
# Start with new configuration
python .agents/skills/lora-manager-e2e/scripts/start_server.py --port 8188 --restart
# Stop current server (if running), start with new configuration.
# --restart only kills the E2E server this script started before (via its pidfile);
# it refuses to blindly kill unrelated processes on the port.
python .agents/skills/lora-manager-e2e/scripts/start_server.py --port {PORT} --restart --wait --detach
# Wait and refresh browser
navigate_page(type="reload", ignoreCache=True)
@@ -130,24 +229,96 @@ click(uid="modal-submit-button")
wait_for(text="Success", timeout=5000)
```
## Fixture + Fresh-State Guidance
For rematch/repair E2E runs, seed the **sandboxed** `recipes_path` with hand-written fixture recipes. Rules (validated by the task-8 E2E):
1. **Filename constraint**: each file MUST be named `f"{id}.recipe.json"` **and** the in-JSON `id` field MUST equal the filename. Discovery accepts any `*.recipe.json`, but persistence resolves the path via `get_recipe_json_path` and `_save_recipe_persistently` returns `False` on a mismatch → the fixture would be counted as an error.
- `recipe-a.recipe.json` → in-JSON `"id": "recipe-a"`
2. **File format**: mirror an existing recipe JSON — top-level `id`, `file_path`, `title`, `loras`, `fingerprint`, `gen_params`; lora entries per the persistence conventions (`hash`, `file_name`, `modelVersionId`, `isDeleted`, ...).
3. **Companion image**: each recipe needs an image (e.g. a `.webp` generated with PIL) referenced by `file_path`, used for EXIF verification (`ExifUtils.append_recipe_metadata` writes a `"Recipe metadata: ..."` marker; a freshly generated `.webp` with no marker is the clean "untouched" control).
4. **autov3 three-state contract**: for L3 (autov3-only, renamed-file) fixtures the local model's `.metadata.json` sidecar MUST have the `autov3` key **ABSENT** (the "unchecked" state), NOT `""` — `""` is the TERMINAL "checked but unavailable" state that L3 deliberately skips. The scanner computes + persists `autov3` from the file header during the normal library scan (`model_scanner.py` `_process_model_file`), so the live L3 match resolves through the local autov3/hash cache; the computed-autov3 branch for unchecked items is covered by the unit suite.
5. **Fixture design for a rematch run** (mirrors the task-8 E2E):
- `recipe-a`: lora entry `isDeleted=True`, `hash` = 12-char autov3 computed from the local model (`calculate_autov3`, `py/utils/file_utils.py`), whose local model file was RENAMED after the recipe was written so `file_name` differs (proves L3 match without filename).
- `recipe-b`: parser-convention checkpoint entry (uses `id`, no `modelVersionId`) matching a local checkpoint via L2 — the local checkpoint's `.metadata.json` MUST carry civitai version data with that `id` so `version_index` contains it (L2 cannot match otherwise).
- `recipe-c`: healthy recipe (no deleted entries) → must remain untouched.
### Fresh state between entry-point runs
Each entry point (global / per-recipe / selection-bulk) must start from the same deleted state. Between runs:
```bash
# 1. Reset fixtures to the before-state snapshot (copy back from recipes-before/)
cp /tmp/opencode/<plan>-e2e/recipes-before/*.recipe.json /tmp/opencode/<plan>-e2e/recipes/
# 2. Clear the recipe/FTS caches so the stale in-memory/library state is gone
rm -f <repo-root>/cache/recipe/*.sqlite
rm -rf <repo-root>/cache/fts/*
# 3. Restart the server (fresh process, fresh scan)
python .agents/skills/lora-manager-e2e/scripts/start_server.py --port {PORT} --restart --wait --timeout 30 --detach
# 4. Re-verify server listening + reload the browser page
```
## Server Lifecycle
- **Detached launch is mandatory**: the standalone server dies with the shell unless launched via `setsid` (or the helper script's `--detach`). Use `setsid nohup python standalone.py --port {PORT} --host 127.0.0.1 ... < /dev/null &`.
- **Verify with `ss -tlnp`** after every (re)start; do not proceed on a blind "server starting" message.
- **Never kill pre-existing processes** — only kill the E2E server PID you started (`start_server.py --restart` kills only PIDs it manages via its pidfile). The live ComfyUI or a stale QA Chrome must never be killed as part of cleanup unless explicitly identified as such (see Chrome troubleshooting).
- **Record your PID for cleanup**: note the PID printed/pidfile, and stop exactly that PID at the end (`kill <PID>`, then confirm with `ss -tlnp` that `{PORT}` is released).
## Chrome DevTools MCP Troubleshooting
### Stale profile lock ("browser is already running" / `list_pages` fails)
A Chrome profile can be held by a stale Chrome from a prior MCP session, which makes `list_pages` fail with "browser is already running":
1. Identify the stale Chrome — it owns the profile dir in `--user-data-dir` (e.g. `~/.config/chrome-dev-profile`). Find its process:
```bash
ps -ef | grep -i '[c]hrome.*user-data-dir'
```
2. Confirm it is a QA Chrome from a completed task (its parent is an old MCP/browser process, it is NOT the live ComfyUI server, and it is NOT your current MCP instance).
3. Kill ONLY that stale Chrome:
```bash
kill <stale-chrome-pid>
```
Never kill the live server or unrelated processes.
4. Retry `list_pages`. The current MCP will spawn a fresh browser.
### Screenshot-write restrictions
The chrome-devtools MCP may refuse to write into paths outside its configured workspace roots (e.g. the worktree `.omo/evidence/...` canonicalizing to an unmapped path). Workaround:
```bash
# 1. Save the screenshot to /tmp via the MCP
# take_screenshot(filePath="/tmp/<plan>-e2e/recipe-b-after.png", format="png")
# 2. Copy it into the evidence dir from the shell
mkdir -p <repo-root>/.omo/evidence/screenshots
cp /tmp/<plan>-e2e/recipe-b-after.png <repo-root>/.omo/evidence/screenshots/
```
## Cancellation Testing (KNOWN GAP)
Testing the rematch-cancel path E2E requires a run long enough to cancel mid-flight. A tiny 3-recipe fixture set completes in **seconds** — too fast to reliably cancel. The cancel path is currently **unit-covered only** (`rematch_all_recipes` cancellation tests); do not block an E2E run on cancel-path verification. If you must attempt it, you would need an artificially large/deferred fixture set to create a cancellable window — treat this as a research task, not part of the standard E2E.
## Available Scripts
### scripts/start_server.py
Starts or restarts the LoRa Manager standalone server.
Starts or restarts the LoRa Manager standalone server for E2E testing.
```bash
python scripts/start_server.py [--port PORT] [--restart] [--wait]
python scripts/start_server.py [--port PORT] [--restart] [--wait] [--timeout SECONDS] [--detach]
```
Options:
- `--port`: Server port (default: 8188)
- `--restart`: Kill existing server before starting
- `--wait`: Wait for server to be ready before exiting
- `--port`: Server port (default: 8188). The script exits early with a clear message if the port is already in use by an unrelated process.
- `--restart`: Kill the E2E server this script previously managed (tracked via `/tmp/lora-manager-e2e-server-{PORT}.pid`) before starting. If unrelated processes still hold the port after that, the script reports them and aborts instead of killing them.
- `--wait`: Wait for the server to be ready before exiting.
- `--timeout`: Readiness wait timeout in seconds (default: 30).
- `--detach`: Launch the server fully detached (`setsid`-style, survives shell death — REQUIRED for E2E). Default off: a normal background process that dies with the shell.
### scripts/wait_for_server.py
Polls server until ready or timeout.
Polls the server until ready or timeout.
```bash
python scripts/wait_for_server.py [--port PORT] [--timeout SECONDS]
@@ -196,6 +367,7 @@ results = performance_stop_trace()
## Cleanup
Always ensure proper cleanup after tests:
1. Stop the standalone server
2. Close browser pages (keep at least one open)
3. Clear temporary data if needed
1. Stop the standalone server: `kill <recorded-pid>` (only the PID you started), then confirm `ss -tlnp | grep ':{PORT}'` is empty.
2. Close browser pages (keep at least one open).
3. Remove the sandbox: `rm -rf /tmp/opencode/<plan>-e2e` and `<repo-root>/settings.json` + `<repo-root>/cache` (both gitignored).
4. Re-run the real-data protection check from the SANDBOX section and record the result in your evidence.
@@ -2,11 +2,13 @@
Quick reference for common MCP commands used in LoRa Manager E2E testing.
> **Port convention**: `{PORT}` is the port chosen for the E2E run (default candidate `8188`, but only if actually free — see the SKILL.md Port Selection section; use e.g. `8199` when `8188` is occupied by a live ComfyUI). Always run against the **sandboxed** standalone server, never a live instance.
## Navigation
```python
# Navigate to LoRA list page
navigate_page(type="url", url="http://127.0.0.1:8188/loras")
navigate_page(type="url", url="http://127.0.0.1:{PORT}/loras")
# Reload page with cache clear
navigate_page(type="reload", ignoreCache=True)
@@ -179,7 +181,7 @@ pages = list_pages()
select_page(pageId=0, bringToFront=True)
# Create new page
new_page(url="http://127.0.0.1:8188/loras")
new_page(url="http://127.0.0.1:{PORT}/loras")
# Close page (keep at least one open!)
close_page(pageId=1)
@@ -261,7 +263,7 @@ drag(from_uid="draggable-item", to_uid="drop-zone")
### Verify LoRA Cards Loaded
```python
navigate_page(type="url", url="http://127.0.0.1:8188/loras")
navigate_page(type="url", url="http://127.0.0.1:{PORT}/loras")
wait_for(text="LoRAs", timeout=10000)
# Check if cards loaded
@@ -322,3 +324,37 @@ navigate_page(type="reload")
errors = list_console_messages(types=["error"])
assert len(errors) == 0, f"Console errors: {errors}"
```
## Troubleshooting
### Stale profile lock ("browser is already running" / `list_pages` fails)
A Chrome profile held by a stale Chrome from a prior MCP session makes `list_pages`
fail with "browser is already running". Fix:
1. Find the stale Chrome that owns the profile dir (e.g. `~/.config/chrome-dev-profile`):
```bash
ps -ef | grep -i '[c]hrome.*user-data-dir'
```
2. Confirm it is a QA Chrome from a completed task (NOT the live ComfyUI server, NOT
your current MCP instance).
3. Kill ONLY that stale Chrome (`kill <stale-pid>`), then retry `list_pages`.
### Screenshot-write restrictions
The MCP may refuse to write into paths outside its configured workspace roots
(e.g. `.omo/evidence/screenshots/` under a worktree that canonicalizes to an unmapped
path). Save the screenshot to `/tmp` via the MCP, then copy it into the evidence dir:
```bash
# MCP: take_screenshot(filePath="/tmp/<plan>-e2e/recipe-b-after.png", format="png")
# Shell:
mkdir -p <repo-root>/.omo/evidence/screenshots
cp /tmp/<plan>-e2e/recipe-b-after.png <repo-root>/.omo/evidence/screenshots/
```
### Time budgets & abort rule
See SKILL.md "Time Budgets & Abort Guidance": if a phase exceeds ~2x its budget or a
tool call retries 3+ times in a row, STOP and report BLOCKED with the last observed
state (server PID + `ss -tlnp`, page snapshot, last API response). Do not loop.
@@ -2,6 +2,14 @@
This document provides detailed test scenarios for end-to-end validation of LoRa Manager features.
> **Run preconditions (from SKILL.md)**: every run uses the **sandboxed** standalone
> server on a free port `{PORT}` (default candidate `8188`, only if actually free — pick
> e.g. `8199` when `8188` is occupied by a live ComfyUI). Fixtures live in the sandboxed
> `recipes_path` as `f"{id}.recipe.json"` files with matching in-JSON `id`; the real user
> config and real library are never touched (record protection proof before/after).
> Abort if a phase exceeds ~2x its budget or a tool call retries 3+ times (SKILL.md
> "Time Budgets & Abort Guidance").
## Table of Contents
1. [LoRA List Page](#lora-list-page)
@@ -19,7 +27,7 @@ This document provides detailed test scenarios for end-to-end validation of LoRa
**Objective**: Verify the LoRA list page loads correctly and displays models.
**Steps**:
1. Navigate to `http://127.0.0.1:8188/loras`
1. Navigate to `http://127.0.0.1:{PORT}/loras`
2. Wait for page title "LoRAs" to appear
3. Take snapshot to verify:
- Header with "LoRAs" title is visible
@@ -134,7 +142,7 @@ evaluate_script(function="""
**Objective**: Verify recipes page loads and displays recipes.
**Steps**:
1. Navigate to `http://127.0.0.1:8188/recipes`
1. Navigate to `http://127.0.0.1:{PORT}/recipes`
2. Wait for "Recipes" title
3. Take snapshot
@@ -176,7 +184,7 @@ evaluate_script(function="""
**Objective**: Verify settings page displays correctly.
**Steps**:
1. Navigate to `http://127.0.0.1:8188/settings`
1. Navigate to `http://127.0.0.1:{PORT}/settings`
2. Wait for "Settings" title
3. Take snapshot
@@ -190,7 +198,7 @@ evaluate_script(function="""
1. Navigate to settings page
2. Change a setting (e.g., default view mode)
3. Save settings
4. Restart server: `python scripts/start_server.py --restart --wait`
4. Restart server: `python scripts/start_server.py --port {PORT} --restart --wait --timeout 30 --detach`
5. Refresh browser page
6. Navigate to settings
@@ -8,186 +8,208 @@ This script shows how to:
3. Verify functionality end-to-end
Note: This is a template. Actual execution requires Chrome DevTools MCP.
Port: pick a FREE port for the run — 8188 is commonly occupied by a live
ComfyUI (see the skill's Port Selection section). Set PORT below to e.g. 8199
when 8188 is taken. Always run against a SANDBOXED standalone server.
"""
import subprocess
import sys
import time
# Choose the E2E port. 8188 is only the default candidate; use 8199 (or any
# free port checked with `ss -tlnp`) when 8188 is occupied by a live ComfyUI.
PORT = "8188"
def run_test():
"""Run example E2E test flow."""
print("=" * 60)
print("LoRa Manager E2E Test Example")
print("=" * 60)
# Step 1: Start server
# Step 1: Start server (detached so it survives the shell)
print("\n[1/5] Starting LoRa Manager standalone server...")
result = subprocess.run(
[sys.executable, "start_server.py", "--port", "8188", "--wait", "--timeout", "30"],
[sys.executable, "start_server.py", "--port", PORT, "--wait", "--timeout", "30", "--detach"],
capture_output=True,
text=True
text=True,
)
if result.returncode != 0:
print(f"Failed to start server: {result.stderr}")
return 1
print("Server ready!")
# Step 2: Open Chrome (manual step - show command)
print("\n[2/5] Open Chrome with debug mode:")
print("google-chrome --remote-debugging-port=9222 --user-data-dir=/tmp/chrome-lora-manager http://127.0.0.1:8188/loras")
print(
f"google-chrome --remote-debugging-port=9222 "
f"--user-data-dir=/tmp/chrome-lora-manager http://127.0.0.1:{PORT}/loras"
)
print("(In actual test, this would be automated via MCP)")
# Step 3: Navigate and verify page load
print("\n[3/5] Page Load Verification:")
print("""
print(
f"""
MCP Commands to execute:
1. navigate_page(type="url", url="http://127.0.0.1:8188/loras")
1. navigate_page(type="url", url="http://127.0.0.1:{PORT}/loras")
2. wait_for(text="LoRAs", timeout=10000)
3. snapshot = take_snapshot()
""")
"""
)
# Step 4: Test search functionality
print("\n[4/5] Search Functionality Test:")
print("""
print(
"""
MCP Commands to execute:
1. fill(uid="search-input", value="test")
2. press_key(key="Enter")
3. wait_for(text="Results", timeout=5000)
4. result = evaluate_script(function="""
4. result = evaluate_script(function=`
() => {
const cards = document.querySelectorAll('.lora-card');
return { count: cards.length };
}
""")
""")
`)
"""
)
# Step 5: Verify API
print("\n[5/5] API Verification:")
print("""
print(
"""
MCP Commands to execute:
1. api_result = evaluate_script(function="""
1. api_result = evaluate_script(function=`
async () => {
const response = await fetch('/loras/api/list');
const data = await response.json();
return { count: data.length, status: response.status };
}
""")
`)
2. Verify api_result['status'] == 200
""")
"""
)
print("\n" + "=" * 60)
print("Test flow completed!")
print("=" * 60)
return 0
def example_restart_flow():
"""Example: Testing configuration change that requires restart."""
print("\n" + "=" * 60)
print("Example: Server Restart Flow")
print("=" * 60)
print("""
print(
f"""
Scenario: Change setting and verify after restart
Steps:
1. Navigate to settings page
- navigate_page(type="url", url="http://127.0.0.1:8188/settings")
- navigate_page(type="url", url="http://127.0.0.1:{PORT}/settings")
2. Change a setting (e.g., theme)
- fill(uid="theme-select", value="dark")
- click(uid="save-settings-button")
3. Restart server
- subprocess.run([python, "start_server.py", "--restart", "--wait"])
- subprocess.run([python, "start_server.py", "--port", "{PORT}", "--restart", "--wait", "--detach"])
4. Refresh browser
- navigate_page(type="reload", ignoreCache=True)
- wait_for(text="LoRAs", timeout=15000)
5. Verify setting persisted
- navigate_page(type="url", url="http://127.0.0.1:8188/settings")
- navigate_page(type="url", url="http://127.0.0.1:{PORT}/settings")
- theme = evaluate_script(function="() => document.querySelector('#theme-select').value")
- assert theme == "dark"
""")
"""
)
def example_modal_interaction():
"""Example: Testing modal dialog interaction."""
print("\n" + "=" * 60)
print("Example: Modal Dialog Interaction")
print("=" * 60)
print("""
print(
"""
Scenario: Add new LoRA via modal
Steps:
1. Open modal
- click(uid="add-lora-button")
- wait_for(text="Add LoRA", timeout=3000)
2. Fill form
- fill_form(elements=[
{"uid": "lora-name", "value": "Test Character"},
{"uid": "lora-path", "value": "/models/test.safetensors"},
])
3. Submit
- click(uid="modal-submit-button")
4. Verify success
- wait_for(text="Successfully added", timeout=5000)
- snapshot = take_snapshot()
""")
"""
)
def example_network_monitoring():
"""Example: Network request monitoring."""
print("\n" + "=" * 60)
print("Example: Network Request Monitoring")
print("=" * 60)
print("""
print(
f"""
Scenario: Verify API calls during user interaction
Steps:
1. Clear network log (implicit on navigation)
- navigate_page(type="url", url="http://127.0.0.1:8188/loras")
- navigate_page(type="url", url="http://127.0.0.1:{PORT}/loras")
2. Perform action that triggers API call
- fill(uid="search-input", value="character")
- press_key(key="Enter")
3. List network requests
- requests = list_network_requests(resourceTypes=["xhr", "fetch"])
4. Find search API call
- search_requests = [r for r in requests if "/api/search" in r.get("url", "")]
- assert len(search_requests) > 0, "Search API was not called"
5. Get request details
- if search_requests:
details = get_network_request(reqid=search_requests[0]["reqid"])
- Verify request method, response status, etc.
""")
"""
)
if __name__ == "__main__":
print("LoRa Manager E2E Test Examples\n")
print("This script demonstrates E2E testing patterns.\n")
print("Note: Actual execution requires Chrome DevTools MCP connection.\n")
run_test()
example_restart_flow()
example_modal_interaction()
example_network_monitoring()
print("\n" + "=" * 60)
print("All examples shown!")
print("=" * 60)
@@ -1,15 +1,78 @@
#!/usr/bin/env python3
"""
Start or restart LoRa Manager standalone server for E2E testing.
Backward-compatible CLI: --port, --restart, --wait, --timeout all work as before.
New options: --detach (setsid-style fully detached launch, survives shell death).
Safety rules implemented here:
- Never kill processes the script did not start. The script tracks the PIDs it
manages in a pidfile (/tmp/lora-manager-e2e-server-{PORT}.pid).
- If the port is held by an unrelated process (e.g. a live ComfyUI) the script
reports the conflict and exits early instead of killing it.
- --restart only kills managed PIDs; if unrelated processes still hold the port
afterwards, the script reports them and aborts.
"""
from __future__ import annotations
import argparse
import os
import signal
import socket
import subprocess
import sys
import time
import socket
import signal
import os
PIDFILE_PREFIX = "/tmp/lora-manager-e2e-server"
def pidfile_path(port: int) -> str:
"""Path of the pidfile that records PIDs this script started for a port."""
return f"{PIDFILE_PREFIX}-{port}.pid"
def read_managed_pids(port: int) -> list[int]:
"""Read PIDs this script previously managed for the port (may be stale)."""
path = pidfile_path(port)
if not os.path.exists(path):
return []
try:
with open(path, "r", encoding="utf-8") as fh:
return [int(line.strip()) for line in fh if line.strip().isdigit()]
except (OSError, ValueError):
return []
def write_managed_pids(port: int, pids: list[int]) -> None:
"""Record PIDs this script manages for the port."""
try:
with open(pidfile_path(port), "w", encoding="utf-8") as fh:
for pid in pids:
fh.write(f"{pid}\n")
except OSError as exc:
print(f"Warning: could not write pidfile for port {port}: {exc}")
def clear_managed_pids(port: int) -> None:
"""Remove the pidfile for the port (no longer managed)."""
path = pidfile_path(port)
try:
if os.path.exists(path):
os.remove(path)
except OSError as exc:
print(f"Warning: could not remove pidfile {path}: {exc}")
def process_alive(pid: int) -> bool:
"""Return True if a process with the given pid exists."""
try:
os.kill(pid, 0)
return True
except ProcessLookupError:
return False
except PermissionError:
return True # exists but owned by someone else
def find_server_process(port: int) -> list[int]:
@@ -19,7 +82,7 @@ def find_server_process(port: int) -> list[int]:
["lsof", "-ti", f":{port}"],
capture_output=True,
text=True,
check=False
check=False,
)
if result.returncode == 0 and result.stdout.strip():
return [int(pid) for pid in result.stdout.strip().split("\n") if pid]
@@ -30,7 +93,7 @@ def find_server_process(port: int) -> list[int]:
["netstat", "-tlnp"],
capture_output=True,
text=True,
check=False
check=False,
)
pids = []
for line in result.stdout.split("\n"):
@@ -49,30 +112,48 @@ def find_server_process(port: int) -> list[int]:
return []
def kill_server(port: int) -> None:
"""Kill processes using the specified port."""
pids = find_server_process(port)
def describe_processes(pids: list[int]) -> str:
"""Human-readable description of a pid list (pid + command line)."""
descriptions = []
for pid in pids:
cmdline = ""
try:
with open(f"/proc/{pid}/cmdline", "rb") as fh:
raw = fh.read().replace(b"\x00", b" ").decode("utf-8", "replace")
cmdline = raw.strip()
except OSError:
pass
descriptions.append(f"pid {pid}{' (' + cmdline + ')' if cmdline else ''}")
return ", ".join(descriptions) if descriptions else "none"
def kill_pids(pids: list[int], what: str) -> None:
"""Send SIGTERM (then SIGKILL) to the given PIDs, only after reporting."""
for pid in pids:
print(f"Sent SIGTERM to {what} pid {pid}")
try:
os.kill(pid, signal.SIGTERM)
print(f"Sent SIGTERM to process {pid}")
except ProcessLookupError:
pass
# Wait for processes to terminate
time.sleep(1)
deadline = time.time() + 5
while time.time() < deadline:
if not any(process_alive(pid) for pid in pids):
break
time.sleep(0.2)
# Force kill if still running
pids = find_server_process(port)
for pid in pids:
try:
os.kill(pid, signal.SIGKILL)
print(f"Sent SIGKILL to process {pid}")
except ProcessLookupError:
pass
if process_alive(pid):
try:
os.kill(pid, signal.SIGKILL)
print(f"Sent SIGKILL to {what} pid {pid}")
except ProcessLookupError:
pass
def is_server_ready(port: int, timeout: float = 0.5) -> bool:
def is_server_ready(port: int, timeout: float = 2.0) -> bool:
"""Check if server is accepting connections."""
try:
with socket.create_connection(("127.0.0.1", port), timeout=timeout):
@@ -84,9 +165,15 @@ def is_server_ready(port: int, timeout: float = 0.5) -> bool:
def wait_for_server(port: int, timeout: int = 30) -> bool:
"""Wait for server to become ready."""
start = time.time()
last_report = 0.0
while time.time() - start < timeout:
if is_server_ready(port):
return True
# Report progress every ~5s so a slow boot is visible, not silent.
elapsed = time.time() - start
if elapsed - last_report >= 5:
print(f" ...still waiting ({int(elapsed)}s/{timeout}s)")
last_report = elapsed
time.sleep(0.5)
return False
@@ -99,68 +186,148 @@ def main() -> int:
"--port",
type=int,
default=8188,
help="Server port (default: 8188)"
help="Server port (default: 8188)",
)
parser.add_argument(
"--restart",
action="store_true",
help="Kill existing server before starting"
help="Kill the E2E server previously managed by this script for the port "
"(tracked via pidfile) before starting; refuse to kill unrelated processes",
)
parser.add_argument(
"--wait",
action="store_true",
help="Wait for server to be ready before exiting"
help="Wait for server to be ready before exiting",
)
parser.add_argument(
"--timeout",
type=int,
default=30,
help="Timeout for waiting (default: 30)"
help="Timeout for waiting (default: 30)",
)
parser.add_argument(
"--detach",
action="store_true",
help="Launch the server fully detached (setsid-style) so it survives shell "
"death. REQUIRED for E2E: a plain background process dies with the shell",
)
args = parser.parse_args()
# Get project root (parent of .agents directory)
script_dir = os.path.dirname(os.path.abspath(__file__))
skill_dir = os.path.dirname(script_dir)
project_root = os.path.dirname(os.path.dirname(os.path.dirname(skill_dir)))
# Restart if requested
managed_pids = read_managed_pids(args.port)
# Restart if requested: kill ONLY managed PIDs.
if args.restart:
print(f"Killing existing server on port {args.port}...")
kill_server(args.port)
alive_managed = [pid for pid in managed_pids if process_alive(pid)]
if alive_managed:
print(
f"Killing E2E server previously started by this script on port "
f"{args.port} ({describe_processes(alive_managed)})..."
)
kill_pids(alive_managed, "managed E2E server")
else:
print(
f"No live managed E2E server for port {args.port} "
f"(pidfile: {pidfile_path(args.port)})"
)
time.sleep(1)
# Check if already running
if is_server_ready(args.port):
print(f"Server already running on port {args.port}")
return 0
# Refuse to kill anything the script did not manage.
remaining = find_server_process(args.port)
if remaining:
print(
f"ERROR: port {args.port} is still held by process(es) this script "
f"did not start: {describe_processes(remaining)}."
)
print(
"These may be unrelated (e.g. a live ComfyUI). The script will NOT "
"kill them. Pick a different --port, or stop them manually if you "
"are certain they are stale E2E servers."
)
return 2
clear_managed_pids(args.port)
# Port conflict check before starting: never blind-kill.
port_pids = find_server_process(args.port)
if port_pids:
alive_managed = [pid for pid in port_pids if pid in managed_pids]
unmanaged = [pid for pid in port_pids if pid not in managed_pids]
if alive_managed and not unmanaged:
print(
f"Server already running on port {args.port} "
f"({describe_processes(alive_managed)}, started by this script). "
f"Use --restart to recycle it."
)
return 0
print(
f"ERROR: port {args.port} is already in use by process(es): "
f"{describe_processes(port_pids)}."
)
print(
"This is likely an unrelated process (e.g. a live ComfyUI holding 8188). "
"The script will NOT kill it. Pick a free port with --port, e.g. 8199."
)
return 2
# Start server
print(f"Starting LoRa Manager standalone server on port {args.port}...")
cmd = [sys.executable, "standalone.py", "--port", str(args.port)]
# Start in background
process = subprocess.Popen(
cmd,
cwd=project_root,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
start_new_session=True
)
print(f"Server process started with PID {process.pid}")
cmd = [
sys.executable,
"standalone.py",
"--host",
"127.0.0.1",
"--port",
str(args.port),
]
if args.detach:
# Fully detached launch: new session (setsid), no controlling terminal,
# stdin from /dev/null, stdout/stderr to a log file. Survives the shell.
log_dir = os.path.join(script_dir, "logs")
os.makedirs(log_dir, exist_ok=True)
log_path = os.path.join(log_dir, f"server-{args.port}.log")
with open(log_path, "ab") as log_fh:
process = subprocess.Popen(
cmd,
cwd=project_root,
stdin=subprocess.DEVNULL,
stdout=log_fh,
stderr=subprocess.STDOUT,
start_new_session=True,
close_fds=True,
)
print(f"Detached server process started with PID {process.pid} (setsid)")
print(f"Log: {log_path}")
else:
# Plain background process (legacy behavior): dies with the shell.
process = subprocess.Popen(
cmd,
cwd=project_root,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
start_new_session=True,
)
print(f"Server process started with PID {process.pid}")
print(
"NOTE: not detached — this process dies when the launching shell exits. "
"For E2E use --detach."
)
write_managed_pids(args.port, [process.pid])
# Wait for ready if requested
if args.wait:
print(f"Waiting for server to be ready (timeout: {args.timeout}s)...")
if wait_for_server(args.port, args.timeout):
print(f"Server ready at http://127.0.0.1:{args.port}/loras")
return 0
else:
print(f"Timeout waiting for server")
return 1
print(f"Timeout waiting for server on port {args.port}")
return 1
print(f"Server starting at http://127.0.0.1:{args.port}/loras")
return 0
@@ -1,15 +1,20 @@
#!/usr/bin/env python3
"""
Wait for LoRa Manager server to become ready.
Timeout is configurable via --timeout (default 30s); the script polls the port
until the server accepts connections or the timeout expires.
"""
from __future__ import annotations
import argparse
import socket
import sys
import time
def is_server_ready(port: int, timeout: float = 0.5) -> bool:
def is_server_ready(port: int, timeout: float = 2.0) -> bool:
"""Check if server is accepting connections."""
try:
with socket.create_connection(("127.0.0.1", port), timeout=timeout):
@@ -21,9 +26,15 @@ def is_server_ready(port: int, timeout: float = 0.5) -> bool:
def wait_for_server(port: int, timeout: int = 30) -> bool:
"""Wait for server to become ready."""
start = time.time()
last_report = 0.0
while time.time() - start < timeout:
if is_server_ready(port):
return True
# Report progress every ~5s so a slow boot is visible, not silent.
elapsed = time.time() - start
if elapsed - last_report >= 5:
print(f" ...still waiting ({int(elapsed)}s/{timeout}s)")
last_report = elapsed
time.sleep(0.5)
return False
@@ -36,25 +47,24 @@ def main() -> int:
"--port",
type=int,
default=8188,
help="Server port (default: 8188)"
help="Server port (default: 8188)",
)
parser.add_argument(
"--timeout",
type=int,
default=30,
help="Timeout in seconds (default: 30)"
help="Timeout in seconds (default: 30)",
)
args = parser.parse_args()
print(f"Waiting for server on port {args.port} (timeout: {args.timeout}s)...")
if wait_for_server(args.port, args.timeout):
print(f"Server ready at http://127.0.0.1:{args.port}/loras")
return 0
else:
print(f"Timeout: Server not ready after {args.timeout}s")
return 1
print(f"Timeout: Server not ready after {args.timeout}s")
return 1
if __name__ == "__main__":
+1
View File
@@ -25,6 +25,7 @@ model_cache/
reasonix.toml
.reasonix/
.codegraph/
.playwright-mcp/
# Vue widgets development cache (but keep build output)
vue-widgets/node_modules/
+202
View File
@@ -0,0 +1,202 @@
---
slug: undo-delete-staging
status: drafting
intent: clear
review_required: false
pending-action: write .omo/plans/undo-delete-staging.md
approach: "Option B: delayed physical deletion with Undo. Backend: same-volume rename to per-root staging dir (.lm-pending-delete/) [updated 2026-08: model staging moved to a SIBLING dir inside each deleted model's own folder — see 'Symlink fix (2026-08)' under Decisions] + manifest JSON (batch_id, expires_at, staged->original map) + purge (30s TTL timer + startup sweep + opportunistic) + undo-delete endpoint + settings toggle 'skip undo'. Small files (recipes: JSON+preview) copy to global staging under settings dir instead of rename. Frontend: extend toast system with action button + 30s countdown; delete flows (single model / recipe / bulk / duplicates) consume batch_id from delete response and show Undo toast; expired undo -> 'undo expired' toast. Plus confirm-modal friction (C-friction, NO type-to-confirm): delete button delay-activation 1.5s + modal shows file size 'will free X GB' + Cancel gets initial focus. i18n keys + sync_translation_keys.py."
---
# Draft: undo-delete-staging
## Components (topology ledger)
<!-- Lock the SHAPE before depth. One row per top-level component that can succeed or fail independently. -->
<!-- id | outcome (one line) | status: active|deferred | evidence path -->
- backend staging module (stage/purge/undo + manifest + per-volume dir resolution) | new module, active | pending exploration: model_lifecycle_service.py delete_model / delete_model_artifacts
- delete endpoints return batch_id (model/recipe/bulk/duplicates) | active | pending exploration: handlers + response shapes
- undo-delete HTTP endpoint + route registration | active | pending exploration: route registrar pattern
- purge scheduling (30s timer + startup sweep + opportunistic) | active | pending exploration: app on_startup hooks
- settings toggle "skip undo window" | active | pending exploration: settings service read pattern
- frontend toast extension (action button + countdown) | active | pending exploration: showToast impl
- frontend delete flows consume batch_id + Undo toast | active | pending exploration: call sites
- confirm-modal friction (delay-activate + size display + cancel focus) | active | pending exploration: modal focus behavior
- i18n keys + sync_translation_keys.py | active | known
## Open assumptions (announced defaults)
<!-- Record any default you adopt instead of asking, so the user can veto it at the gate. -->
<!-- assumption | adopted default | rationale | reversible? -->
- Undo window TTL = 30s | 30s balances space-freeing intent vs accident recovery | yes (constant)
- Staging dir name: `.lm-pending-delete/` under each model root; recipes: `{settings_dir}/.lm-pending-delete/` | hidden, same-volume [updated 2026-08: same-volume is now guaranteed by sibling staging inside the model's own folder, not by the root location], consistent | yes
- Staging failure falls back to existing hard delete | user intent is delete; staging is best-effort; hard delete likely fails identically under same conditions | yes
- Purge on startup uses expires_at (not purge-all) so a <30s restart with live tab can still undo | robust, matches client-side timer | yes
- Settings toggle label: "Delete permanently immediately (skip undo window)" | power users freeing space | yes
- C-friction: delete button enabled after 1.5s + modal shows freed size; NO type-to-confirm (user vetoed) | user explicitly rejected type-to-confirm | n/a
- Bulk/duplicates delete: one batch id for whole action, one undo restores all | simplest consistent semantics | yes
## Findings (cited - path:lines)
### Backend
- `delete_model_artifacts` (py/services/model_lifecycle_service.py:19-48) = physical delete via os.remove; patterns: main file + `{name}.metadata.json` + PREVIEW_EXTENSIONS (py/utils/constants.py:22-37). ALSO called by ModelScanner.bulk_delete_models (py/services/model_scanner.py:2221) - single swap point covers bulk models.
- `ModelLifecycleService.delete_model` (model_lifecycle_service.py:101-154): fetches `cached_entry` (111-116) - SNAPSHOT available for cache restore; after delete: cache.raw_data removal + resort + bump_cache_version (136-143), `_hash_index.remove_by_path` (145-146), `_sync_update_for_model` (148; update-service only, no recipe JSON rewrites - recipe refs are hash-based, re-resolve on restore), `_persist_current_cache` (150-152), returns `{"success": True, "deleted_files": [...]}` (154).
- Handler `delete_model` (py/routes/handlers/model_handlers.py:478-492): POST /api/lm/{prefix}/delete; response passthrough; `_broadcast_models_changed()` (57-74) after success; 400 `{"success":false,"error"}`; 500 plain text.
- Recipe delete: handler (recipe_handlers.py:1422-1438) DELETE /api/lm/recipe/{recipe_id} -> persistence_service.delete_recipe (py/services/recipes/persistence_service.py:193-209): os.remove(recipe_json_path) + os.remove(image_path) (204-206), recipe_scanner.remove_recipe (208), returns `{"success": true, "message": ...}`. PersistenceResult dataclass (20-25).
- Bulk models: POST /api/lm/{prefix}/bulk-delete (model_route_registrar.py:39) -> handler (model_handlers.py:974-994) -> lifecycle_service.bulk_delete_models (model_lifecycle_service.py:308-318) -> scanner.bulk_delete_models (model_scanner.py:2181-2269) which calls delete_model_artifacts per file (2221) + `_batch_update_cache_for_deleted_models` (2271-2335); response `{"success","status","total_deleted","total_attempted","cache_updated","results"}` (2254-2269).
- Bulk recipes: POST /api/lm/recipes/bulk-delete (recipe_route_registrar.py:50) -> handler (recipe_handlers.py:1554-1573) -> persistence_service.bulk_delete (persistence_service.py:439-482): per-id os.remove x2 (464-466), recipe_scanner.bulk_remove (472); response `{"success","deleted","failed","total_deleted","total_failed"}` (474-482).
- Duplicates: NO dedicated delete endpoints (find-only: GET /api/lm/{prefix}/find-duplicates model_route_registrar.py:59, GET /api/lm/recipes/find-duplicates recipe_route_registrar.py:49). Duplicate deletion reuses bulk-delete endpoints.
- Startup hooks: lora_manager.py:183-187 `app.on_startup.append(lambda app: cls._initialize_services())` (ComfyUI mode, app = PromptServer.instance.app at :78); standalone.py:370-374 same (StandaloneLoraManager.add_routes). Background tasks: `asyncio.create_task(name=...)` (lora_manager.py:224-239; recipe_handlers.py:793). Singleton+asyncio.Lock pattern: model_scanner.py:40-63.
- Settings: DEFAULT_SETTINGS (py/services/settings_manager.py:57-119), `get(key, default)` (1390-1392), get_settings_manager() (2215-2228), reset_settings_manager() (2231). Typed-bool getter example: get_skip_previously_downloaded_model_versions (1253-1262). Handlers: base_model_routes.py:70, base_recipe_routes.py:54.
- Model roots: ModelScanner.get_model_roots base NotImplementedError (model_scanner.py:1073-1075); impls lora_scanner.py:31-45, checkpoint_scanner.py:428-441, embedding_scanner.py:24-36. `_find_root_for_file(file_path)` (model_scanner.py:1108-1124) returns containing root - for per-root staging dir computation [updated 2026-08: staging no longer uses the containing root; batches are siblings inside the model's own folder]. Business-path rule (AGENTS.md): use os.path.abspath, never realpath, for staging/undo routing.
- Cache restore methods: ModelCache has raw_data + resort (conftest mocks: tests/conftest.py:144-154); ModelHashIndex.add_entry(sha256, file_path, autov3) (py/services/model_hash_index.py:16); RecipeScanner.add_recipe(recipe_data) (recipe_scanner.py:2136) -> recipe_cache.add_recipe (recipe_cache.py:64). No single-file incremental model rescan - use snapshot restore instead of rescan.
- Route registrar: model_route_registrar.py:177 add_route(method, path, handler), :180 add_prefixed_route - undo endpoint can be a non-prefixed route via add_route.
- Tests: tests/services/test_model_lifecycle_service.py (inline tmp_path files, per-test stub scanners ScannerForDelete/VersionAwareScanner etc); conftest MockScanner/MockCache/MockHashIndex (tests/conftest.py:134-212); integration fixtures tests/integration/conftest.py; lifecycle hook tests tests/routes/test_lora_manager_lifecycle.py:177-178, tests/standalone/test_standalone_server.py:83-84.
### Frontend
- 5 delete call sites:
a) Single model: static/js/utils/modalUtils.js confirmDelete (27-42) -> getModelApiClient().deleteModel(path); ignores return.
b) Recipe single: static/js/components/RecipeCard.js confirmDeleteRecipe (405-449) - RAW fetch DELETE /api/lm/recipe/{id}, checks only response.ok, showToast toast.recipes.deletedSuccessfully, state.virtualScroller.removeItemByFilePath.
c) Bulk: static/js/managers/BulkManager.js confirmBulkDelete (633-672) -> getActiveApiClient() (134-142) -> bulkDeleteModels(filePaths); reads result.cancelled/success/deleted_count/error.
d) Recipe duplicates: static/js/components/DuplicatesManager.js confirmDeleteDuplicates (457-494) - RAW fetch POST /api/lm/recipes/bulk-delete, reads data.success/data.total_deleted, exitDuplicateMode().
e) Model duplicates: static/js/components/ModelDuplicatesManager.js confirmDeleteDuplicates (710-776) - RAW fetch POST /api/lm/{type}/bulk-delete, reads data.total_deleted, then resetAndReload(true) + find-duplicates re-check.
Bonus: static/js/components/shared/ModelVersionsTab.js:1136-1144 client.deleteModel (ignores return).
- API clients: BaseModelApiClient.deleteModel (static/js/api/baseModelApi.js:184-216) returns true/false, shows its own toasts, does removeItemByFilePath inside; bulkDeleteModels (1591-1642) returns {success, deleted_count, failed_count, errors} or {success:false, cancelled:true}; RecipeSidebarApiClient.bulkDeleteModels (recipeApi.js:623-664) returns {success, deleted_count: total_deleted, ...}. Endpoint map apiConfig.js:56,64.
- Toast: showToast(key, params={}, type='info', fallback=null) (static/js/utils/uiHelpers.js:136-193) - textContent only, NO action/button support; durations 2000/5000ms; CSS static/css/components/toast.css (.toast flex gap:12px - button can be added). Closest action pattern: bannerService.registerBanner actions array + onRegister (static/js/managers/BannerService.js; used uiHelpers.js:18-57).
- i18n: locales/en.json delete keys (1303-1314 bulkDelete, 1945-1948 recipes, 1987-1991 models, 2124-2130 duplicates, 2166-2170 toast.api); t()/interpolate (static/js/i18n/index.js:193-248); translate wrapper (utils/i18nHelpers.js:13-23); sync script scripts/sync_translation_keys.py (en reference, [TODO: Translate] placeholders).
- Refresh after undo: recipes -> window.recipeManager.loadRecipes(true) (recipes.js:359; used by FilterManager.js:752 etc) or refreshRecipes (recipeApi.js:308); models -> resetAndReload(true) from modelApiFactory (used by ModelDuplicatesManager.js:740).
- Size for modal: card.dataset.file_size (ModelCard.js:467), formatFileSize (ModelModal.js:615).
- Tests: tests/frontend/utils/uiHelpers.dom.test.js (toast), api/recipeApi.bulk.test.js, components/duplicatesManager.test.js, components/modelDuplicatesManager.test.js, pages/*Page.test.js, i18n tests tests/i18n/test_i18n.py.
## Decisions (with rationale)
1. Same-volume rename staging for model files (atomic, no copy cost for multi-GB files); cross-volume rename forbidden. [CORRECTED 2026-08: "same-volume because under the containing root" was only true for plain directories — nested symlinked subdirs could cross volumes. Superseded by sibling staging: `.lm-pending-delete/<batch_id>/` inside the deleted model's own folder makes stage/undo same-device by construction; see "Symlink fix (2026-08)" below.]
2. Copy-to-global-staging for recipes (small files; avoids recipe JSON vs preview image cross-volume problem).
3. Manifest JSON files are the only state - no DB changes. Manifest includes model cached_entry snapshot for exact cache restore (no rescan needed).
4. Undo endpoint returns restored paths; expired batch -> 404-style error -> frontend 'undo expired' toast.
5. Skip-undo setting honored server-side (no batch_id in response -> no undo toast client-side).
6. Staging failure falls back to existing hard delete (best-effort undo, never blocks delete).
7. Undo window TTL = 30s constant (PENDING_DELETE_TTL_SECONDS); startup sweep uses expires_at (survives restart; browser-tab timer survives).
8. Purge triple-trigger: per-batch asyncio timer task + on_startup sweep + opportunistic purge at each stage/undo.
9. Frontend: new showActionToast (keep showToast signature untouched; extract shared createToastElement/appendToast internals); undo click -> shared handleUndoDelete(batchId, refreshFn); full list refresh after undo (recipes: window.recipeManager.loadRecipes(true); models: resetAndReload(true)).
10. C-friction wave (NO type-to-confirm - user vetoed): delete buttons delay-activate 1.5s after modal open, initial focus on Cancel, model delete modal gains "permanently deleted from disk" warning + file size display (card.dataset.file_size + formatFileSize).
11. Model cache restore on undo: append snapshot to cache.raw_data (dedupe by file_path) + resort + bump_cache_version + _persist_current_cache + _hash_index.add_entry + _broadcast_models_changed. Recipe restore: copy back files + recipe_scanner.add_recipe(recipe_data loaded from restored JSON).
### Symlink fix (2026-08)
Post-execution addendum (plan `.omo/plans/undo-delete-symlink-fix.md`, commits 5fd4946b / 0c00ee22):
12. Model staging moved from `<model_root>/.lm-pending-delete/<batch_id>/` to `<model_dir>/.lm-pending-delete/<batch_id>/` (sibling of the model artifacts, inside the deleted model's own folder). Stage/undo renames are same-device BY CONSTRUCTION — EXDEV is impossible even when the business path traverses nested symlinks to other volumes (the decision-1 "containing root" guarantee covered only plain directories). EXDEV remains possible only for cross-volume merges, which keep the batch_ids-array fallback. Accepted edge: deleting the model's whole FOLDER during the 30s window destroys that batch (undo returns 404). Batch discovery uses an in-memory registry (`_known_batch_dirs`) with a startup reconciliation scan (`purge_expired(scan_roots=True)`) covering restarts and crash leftovers. Recipe batches unchanged (copy-based settings-dir staging with the `_restore_file` EXDEV fallback).
## Scope IN
- Model single delete (model_handlers delete_model / model_lifecycle_service)
- Recipe delete (recipe_handlers delete_recipe / persistence_service)
- Bulk delete (models scanner + recipes persistence) + duplicates (reuse bulk endpoints)
- Undo endpoint POST /api/lm/undo-delete (models + recipes, one batch space)
- Purge: timer + startup sweep + opportunistic
- Settings toggle delete_undo_enabled + settings page checkbox
- Frontend: showActionToast + all 5 delete flows + shared undo handler
- C-friction modal changes (delay-activate + cancel focus + warning copy + size display)
- i18n keys + sync_translation_keys.py
- Backend + frontend tests
## Scope OUT (Must NOT have)
- NO type-to-confirm / hold-to-confirm friction (user vetoed)
- NO OS trash integration (send2trash) in this iteration
- NO persistent recycle-bin UI (no trash browsing page)
- NO changes to exclude/unexclude flow
- NO DB migrations
- NO new dependencies (no send2trash)
- NO changes to download flows
- NO recipe-JSON rewriting on model undo (hash-based refs re-resolve themselves)
## Open questions
None - all implementation details resolved by exploration. Design decisions settled in conversation (B+C, no type-to-confirm).
## Approval gate
status: approved
<!-- Approach approved -> rerun scaffold without --draft-only, run Metis gap analysis, APPEND todo batches, fill TL;DR last, run structural self-check, then Phase 4 handoff. -->
## Review round state (ulw-plan-review-round-state-contract)
```json
{
"transition": "replace",
"phase": "review_round_initialized",
"applies_when": ["retry_after_plan_change"],
"atomic": true,
"review_required": true,
"plan_path": ".omo/plans/undo-delete-staging.md",
"plan_sha256": "8cf7c9be38a76d8ef1fb832aba043d6d7e82b60465b1bf28c6eafa7045117adc",
"review_round_id": "rr-undo-del-20260811-006",
"round_status": "active",
"pending-action": "review .omo/plans/undo-delete-staging.md",
"review": {
"momus": { "status": "pending", "workspace_root": "/mnt/data/reinstall-backup-2026-04-12/data/workspace/ComfyUI/custom_nodes/ComfyUI-Lora-Manager", "runtime_home": null, "target": ".omo/plans/undo-delete-staging.md", "round_id": "rr-undo-del-20260811-006", "plan_sha256": "8cf7c9be38a76d8ef1fb832aba043d6d7e82b60465b1bf28c6eafa7045117adc", "launch_id": null, "session": null, "result": null },
"independent": { "status": "pending", "workspace_root": "/mnt/data/reinstall-backup-2026-04-12/data/workspace/ComfyUI/custom_nodes/ComfyUI-Lora-Manager", "runtime_home": null, "target": ".omo/plans/undo-delete-staging.md", "round_id": "rr-undo-del-20260811-006", "plan_sha256": "8cf7c9be38a76d8ef1fb832aba043d6d7e82b60465b1bf28c6eafa7045117adc", "launch_id": null, "session": null, "result": null }
}
}
```
## Review results + fix/retry ledger
### Round 1 (rr-undo-del-20260811-001, plan sha256 6c52bf99...)
- momus: APPROVE (non-blocking notes: todo1+7 duplicate DEFAULT_SETTINGS key -> fixed todo 7 to verify-only; "batch_ids" plural in todos 8/9 acceptance -> fixed; purge OSError note -> folded into todo 1 purge semantics)
- independent (oracle): CHANGES_REQUESTED
- BLOCKING S1: scanner walks would index .lm-pending-delete staged files as ghost entries -> fixed: todo 1 now mandates scanner walk exclusion at model_scanner.py:706/:867/:1404/_process_model_file + acceptance (o) scanner-visibility test
- BLOCKING S2: manifest lacks model_type, undo could restore into wrong cache/hash index -> fixed: manifest now carries model_type + todo 5 resolves per-type scanner via registrar pattern + acceptance (b) checkpoint-batch test
- S3 merged-batch expires_at re-anchor -> fixed: merge_batches re-anchors now+TTL in todo 1 + todo 3/4 assertions
- S4 manifest-less dir policy -> fixed: quarantine to <batch_id>.orphaned, never delete (todo 1 + acceptance g)
- S5 partial-undo retry semantics -> fixed: per-entry restored flag write-through + retry test (acceptance e)
- S6 purge locked-file failure semantics -> fixed: skip file, keep batch, never rmtree past errors (todo 1 + acceptance i)
- T8 undo-after-restart test -> fixed: todo 5 acceptance (f)
- T9 recipe undo -> re-delete test -> fixed: todo 5 acceptance (h)
- T7 rescan-stale-entry test -> fixed: todo 5 acceptance (g)
- Route registration pinned to shared routes class per mode (NOT per-model-type registrar which registers 3x) -> fixed: todo 5 now creates py/routes/pending_delete_routes.py registered once in lora_manager.py:170-172 + standalone.py:356-358 + duplicate-route test (e)
- Version-index staleness on single-delete undo -> fixed: todo 5 follows bulk cache-update pattern incl. rebuild_version_index (model_scanner.py:2324)
- Cancelled-bulk batch_id frontend handling -> fixed: todo 9 shows action toast on cancelled+staged-subset
- Single-instance assumption -> added to Scope OUT
- Occupied-refusal loss UX -> accepted-intent documented in success criteria + modal copy
### Round 2 (rr-undo-del-20260811-002, plan sha256 f3d52235...)
- momus: APPROVE (all 12 round-1 fixes verified present; zero dead references; non-blocking nits only)
- independent (oracle): CHANGES_REQUESTED
- BLOCK-1: merge_batches file-movement semantics unspecified (silent data-loss vector) -> fixed: todo 1 now specifies move-into-winner-dir + entry re-point + loser-dirs-removed-only-when-empty + abort-on-move-failure (all batches intact) + merge inside service lock + acceptance (k) file-survival assertions + acceptance (l) merge-failure abort test
- BLOCK-2: same-file parallel edits within waves (todo 5 vs 6 on lora_manager.py; todo 8 vs 9 on baseModelApi.js) -> fixed: waves/matrix now serialize 5->6 and 8->9 with explicit reasons; matrix updated
- Recommended: checkpoint_scanner.py:331 exclusion -> fixed (todo 1 + acceptance p); S5 pre-check skips restored:true entries -> fixed (todo 1); _tags_count restore on undo -> fixed (todo 5 + acceptance j); undo-blind flows documented (ModelVersionsTab + misc_handlers:2456) -> fixed (todo 8 note + Scope OUT); merge-failure no-merge fallback contract (batch_ids array) -> fixed (todos 3/4/9)
### Round 3 (rr-undo-del-20260811-003, plan sha256 8f2dfd46...)
- momus: APPROVE (all round-2 fixes verified present + spot-checked refs; no new contradictions)
- independent (oracle): CHANGES_REQUESTED
- BLOCKING A: merged batches never timer-purged after re-anchor (winner's original timer no-ops at old expiry; no fresh timer for re-anchored expiry; idle server -> merged batch lingers, violating "30s purge" success criterion; affects EVERY bulk delete) -> fixed: todo 1 merge_batches now ARMS A FRESH PURGE TIMER for the winner with re-anchored expiry + acceptance (q) fresh-timer test + purge_expired must enumerate ALL scanner types' roots (explicit in todo 1)
- BLOCKING B: dependency matrix contradicted same-file policy for todos 8/9<->11 (5 shared files) and 12<->11 -> fixed: todo 11 now "Blocked by: 8, 9 (same files...)"; todo 12 blocked by 11 (sync after 11); wave text updated (11, then 12 AFTER 11); "Can parallelize with" columns corrected
- BLOCKING C: frontend batch_ids sequential-undo fallback has NO test + merge->undo loser-restore + merge->purge assertions missing -> fixed: todo 9 acceptance now tests the batch_ids fallback path; todo 1 acceptance now has (k2)/(k3)
- Notes folded: sub-second toast-tail expiry race accepted; EXDEV fallback = NORMAL path for cross-volume bulks [annotated 2026-08: after the sibling-staging fix, EXDEV can only arise during cross-volume MERGES, never during single stage/undo renames]
### Round 4 (rr-undo-del-20260811-004, plan sha256 179e7ff7...)
- momus: APPROVE (round-3 fixes verified; one non-blocking nit: todo 11 inline "Blocked by: —" stale -> fixed to "8, 9")
- independent (oracle): CHANGES_REQUESTED
- BLOCKING GAP-1 (NEW, introduced by round-3 fix): todo 8 handleUndoDelete always-refresh/always-toast contract contradicted todo 9's sequential loop "exactly ONE final refresh" -> fixed: handleUndoDelete(batchId, refreshFn, {showToast, refresh}) suppression options; todo 9 loop uses suppressed calls + one final refresh/toast; acceptance extended (loop failure mid-way -> stop + error toast + no final refresh; 404 body discrimination expired vs occupied)
- BLOCKING GAP-2: no cross-type purge enumeration test -> fixed: todo 1 acceptance (r) purges expired batches across lora root + checkpoint root + recipe staging dir in one call
- Non-blocking folded: GAP-3 404-copy discrimination -> fixed in todo 8 (d); GAP-4 merge partial-failure rollback direction (move back + restore manifests, extended (l) asserts sequential constituent undo still restores everything) -> fixed in todo 1; GAP-5 post-restart timer-loss residual gap documented -> fixed in todo 6; GAP-6 usage_stats.py:424 walk added to exclusion mandate + todo 5 acceptance (k) embeddings undo test
### Round 5 (rr-undo-del-20260811-005, plan sha256 dfaa39ea...)
- momus: APPROVE (all round-4 fixes verified; no new contradictions)
- independent (oracle): CHANGES_REQUESTED
- BLOCK-1: lock-ordering deadlock ambiguity (asyncio.Lock not re-entrant: opportunistic purge_expired called while stage/undo hold the lock would deadlock on first use) -> fixed: todo 1 now has explicit LOCK HIERARCHY (lock acquired ONLY by stage/merge/undo/purge_batch; purge_expired is lock-free and must be called BEFORE lock acquisition); todo 6 (c) updated with the same rule + acceptance (u) lock-no-deadlock test
- BLOCK-2: purge edge semantics unspecified -> fixed: purge_batch treats missing staged files (partially-restored batches) as already-purged (FileNotFoundError silent no-op); sweep skips `.orphaned`-suffixed dirs (quarantine is terminal); acceptance (s) partially-restored purge + (t) quarantine-terminal tests
- Non-blocking folded: todo 2/3 test-file collision -> todo 3's bulk tests moved to tests/services/test_model_scanner.py; todo 9 (d) DuplicatesManager refreshFn stated explicitly (recipes loadRecipes / models resetAndReload); modal-copy + bulk-count trade-offs acknowledged in success criteria; acceptance (r) extended with embeddings root
### Round 6 (rr-undo-del-20260811-006, plan sha256 8cf7c9be...)
- momus: APPROVE (all round-5 fixes verified; no new contradictions; references verified)
- independent (oracle): APPROVE — no blocking issues; all round-5 items fixed with working, tested solutions; no new race/data-loss/consistency defects
- Deferred optional improvements (non-blocking, recorded for executor awareness; plan file left untouched to preserve the approved digest):
1. Tag-count asymmetry: single delete_model never decrements _tags_count (lifecycle 101-154), bulk does (scanner 2297-2303); undo re-increment is exact for bulk, over-counts for single until rescan (cosmetic, self-healing). Optional fix riding in todo 2: decrement tags in the single-delete path to mirror bulk.
2. Todo 5 factual nit: ModelCache.resort() already rebuilds the version index — explicit rebuild in undo is belt-and-braces, no action needed.
3. Todo 8 premise nit: ModelVersionsTab call ignores deleteModel's return entirely — nothing breaks, no adaptation needed.
4. Todo 3's pytest command includes test_model_lifecycle_service.py which todo 2 edits in the same wave — run that file's tests after todo 2 lands.
5. merge_batches with a missing/quarantined constituent id: any sane fallback (abort -> batch_ids, or skip missing) acceptable — files stay staged either way.
## Review lifecycle
- rounds: 6 (rr-undo-del-20260811-001..006); final round both lanes APPROVE
- final live-plan validation: sha256 = 8cf7c9be38a76d8ef1fb832aba043d6d7e82b60465b1bf28c6eafa7045117adc — MATCHES approved round-6 digest
- status: APPROVED — ready for execution handoff ($start-work undo-delete-staging)
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+3 -3
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@@ -31,7 +31,7 @@ COVERAGE_FILE=coverage/backend/.coverage pytest \
--cov-report=xml:coverage/backend/coverage.xml
```
### Frontend Development (Standalone Web UI)
### Frontend Development (LoRA Manager Web UI)
```bash
npm install
@@ -154,9 +154,9 @@ npm run test:coverage # Generate coverage report
## Frontend UI Architecture
### 1. Standalone Web UI
### 1. LoRA Manager Web UI
- Location: `./static/` and `./templates/`
- Tech: Vanilla JS + CSS, served by standalone server
- Tech: Vanilla JS + CSS, served by the hosting server (ComfyUI app in plugin mode, `standalone.py` in standalone mode)
- Tests via npm in root directory
### 2. ComfyUI Custom Node Widgets
+4
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@@ -39,6 +39,7 @@ These fields are present in all model metadata files.
| `metadata_source` | string\|null | ❌ No | ✅ Yes | Last provider that supplied metadata (see below) |
| `last_checked_at` | float | ❌ No (default: `0`) | ✅ Yes | Unix timestamp of last metadata check |
| `hash_status` | string | ❌ No (default: `"completed"`) | ✅ Yes | Hash calculation status: `"pending"`, `"calculating"`, `"completed"`, `"failed"` |
| `autov3` | string\|null | ❌ No | ✅ Yes | CivitAI AutoV3 hash (first 12 chars, lowercase hex) sourced from the safetensors embedded metadata (`sshs_model_hash` / `modelspec.hash_sha256`). **Absent** = not yet checked (may be backfilled later); **`null`** = checked but unavailable (header has no recognized hash); **12-char hex string** = value |
---
@@ -287,6 +288,7 @@ These fields are automatically synchronized with the filesystem:
- `preview_url` — Updated if preview file is moved/removed
- `sha256` — Updated during hash calculation (when `hash_status="pending"`)
- `hash_status` — Updated during hash calculation
- `autov3` — Set when metadata is first created (from safetensors header); may be backfilled later for entries where it is absent
- `last_checked_at` — Timestamp of scan
- `metadata_source` — Set based on metadata provider
@@ -345,6 +347,7 @@ These fields can be edited by users at any time through the Lora Manager UI or b
| `metadata_source` | `null` |
| `last_checked_at` | `0` |
| `hash_status` | `"completed"` |
| `autov3` | absent (not checked) or `null` (checked, no value) |
| `usage_tips` | `"{}"` (LoRA only) |
| `model_type` | `"checkpoint"` or `"embedding"` (not present in LoRA models) |
@@ -354,6 +357,7 @@ These fields can be edited by users at any time through the Lora Manager UI or b
| Version | Date | Changes |
|---------|------|---------|
| 1.1 | 2026-08 | Added `autov3` field (CivitAI AutoV3 hash with three-state semantics) |
| 1.0 | 2026-03 | Initial schema documentation |
---
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@@ -186,6 +186,16 @@
"cancelled": "Repair cancelled. {count} recipes were repaired.",
"error": "Recipe repair failed: {message}"
},
"rematchRecipes": {
"label": "Rematch recipes to local models",
"loading": "Rematching recipes to local models...",
"success": "Matched {entries} entries across {recipes} recipes",
"successErrors": "Matched {entries} entries across {recipes} recipes, {failures} failed",
"allFailed": "Rematch failed for {failures} of {total} recipes",
"noMatch": "No local match found for {entries} entries in {recipes} recipes",
"cancelled": "Rematch cancelled. {recipes} recipes updated ({entries} entries).",
"error": "Recipe rematch failed: {message}"
},
"manageExcludedModels": {
"label": "Manage Excluded Models"
},
@@ -449,6 +459,12 @@
"compact": "7 (1080p), 8 (2K), 10 (4K)"
},
"displayDensityWarning": "Warning: Higher densities may cause performance issues on systems with limited resources.",
"recipesLayout": "Recipes Layout",
"recipesLayoutHelp": "Choose how recipe cards are arranged: a uniform grid or a masonry (Pinterest-style) layout that preserves each image's aspect ratio.",
"recipesLayoutOptions": {
"grid": "Grid",
"masonry": "Masonry"
},
"showFolderSidebar": "Show Folder Sidebar",
"showFolderSidebarHelp": "Toggle the folder navigation sidebar on model pages. When disabled, the sidebar and hover area stay hidden.",
"cardInfoDisplay": "Card Info Display",
@@ -678,6 +694,7 @@
"deepseek": "DeepSeek",
"groq": "Groq",
"openrouter": "OpenRouter",
"google": "Gemini",
"opencode-go": "OpenCode Go",
"custom": "Custom (OpenAI-compatible)"
},
@@ -761,6 +778,7 @@
"copyAll": "Copy Selected Syntax",
"refreshAll": "Refresh Selected Metadata",
"repairMetadata": "Repair Metadata for Selected",
"rematchMetadata": "Rematch Selected to Local Models",
"reimportMetadata": "Re-import from Source",
"checkUpdates": "Check Updates for Selected",
"moveAll": "Move Selected to Folder",
@@ -773,6 +791,8 @@
"deleteAll": "Delete Selected",
"downloadMissingLoras": "Download Missing LoRAs",
"downloadExamples": "Download Example Images",
"downloadMissingExamples": "Download Missing",
"reprocessExamples": "Re-process All",
"clear": "Clear Selection",
"skipMetadataRefreshCount": "Skip ({count} models)",
"resumeMetadataRefreshCount": "Resume ({count} models)",
@@ -808,10 +828,13 @@
"sendToWorkflowReplace": "Send to Workflow (Replace)",
"openExamples": "Open Examples Folder",
"downloadExamples": "Download Example Images",
"downloadMissingExamples": "Download Missing",
"reprocessExamples": "Re-process All",
"replacePreview": "Replace Preview",
"setContentRating": "Set Content Rating",
"moveToFolder": "Move to Folder",
"repairMetadata": "Repair metadata",
"rematchMetadata": "Rematch to local models",
"reimportMetadata": "Re-import from Source",
"excludeModel": "Exclude Model",
"restoreModel": "Restore Model",
@@ -912,8 +935,16 @@
},
"duplicates": {
"found": "Found {count} duplicate groups",
"noGroups": "No duplicate groups found with the current matching basis",
"keepLatest": "Keep Latest Versions",
"deleteSelected": "Delete Selected"
"deleteSelected": "Delete Selected",
"includePromptLabel": "Include prompt in matching",
"basis": {
"loraCombo": "Matched by: LoRA combination",
"loraComboAndPrompt": "Matched by: LoRA combination + prompt",
"hintLoraCombo": "Recipes with the same LoRAs at identical strengths are grouped.",
"hintPromptIncluded": "Recipes are grouped only when they use the same LoRAs at identical strengths AND have the same prompt."
}
},
"contextMenu": {
"copyRecipe": {
@@ -1246,8 +1277,13 @@
}
},
"deleteModel": {
"freesSpace": "Frees {size}",
"title": "Delete Model",
"message": "Are you sure you want to delete this model and all associated files?"
"message": "Are you sure you want to delete this model and all associated files?",
"recoverableWarning": "This will permanently delete the file after 20 seconds unless you undo."
},
"deleteRecipe": {
"recoverableWarning": "This action can be undone for 20 seconds."
},
"excludeModel": {
"title": "Exclude Model",
@@ -1577,6 +1613,21 @@
"downloadCsv": "Download CSV",
"columnModelName": "Model Name",
"columnError": "Error"
},
"downloadBatchSummary": {
"title": "Batch Download Summary",
"statSuccess": "Success",
"statFailed": "Failed",
"statTotal": "Total",
"successMessage": "All {count} models downloaded successfully",
"completedWithErrors": "Completed with errors",
"failed": "Download failed",
"failedItems": "Failed Items ({count})",
"columnName": "Model Name",
"columnError": "Error",
"close": "Close",
"copyReport": "Copy Report",
"retryFailed": "Retry Failed ({count})"
}
},
"modelTags": {
@@ -1675,6 +1726,7 @@
"recipeReplaced": "Recipe replaced in workflow",
"recipeFailedToSend": "Failed to send recipe to workflow",
"noMatchingNodes": "No compatible nodes available in the current workflow",
"noPromptTargets": "No compatible prompt targets in the workflow.\nRight-click a node in ComfyUI → Mark as → Send Prompt Target",
"noTargetNodeSelected": "No target node selected",
"modelUpdated": "Model updated in workflow",
"modelFailed": "Failed to update model node",
@@ -1925,6 +1977,12 @@
"repairBulkComplete": "Repair complete: {repaired} repaired, {skipped} skipped (of {total})",
"repairBulkSkipped": "No repair needed for any of the {total} selected recipes",
"repairBulkFailed": "Failed to repair selected recipes: {message}",
"rematchComplete": "Matched {entries} entries across {recipes} recipes",
"rematchCompleteErrors": "Matched {entries} entries across {recipes} recipes, {failures} failed",
"rematchAllFailed": "Rematch failed for {failures} of {total} selected recipes",
"rematchUnmatched": "No local match found for {entries} entries in {recipes} recipes",
"rematchSkipped": "No rematch needed for any of the {total} selected recipes",
"rematchFailed": "Failed to rematch selected recipes: {message}",
"reimporting": "Re-importing recipe from source...",
"reimportSuccess": "Recipe re-imported successfully",
"reimportBulkComplete": "Re-import complete: {completed} re-imported, {failed} failed (of {total})",
@@ -2033,7 +2091,6 @@
"presetNameTooLong": "Preset name must be {max} characters or less",
"presetNameInvalidChars": "Preset name contains invalid characters",
"presetNameExists": "A preset with this name already exists",
"maxPresetsReached": "Maximum {max} presets allowed. Delete one to add more.",
"presetNotFound": "Preset not found",
"invalidPreset": "Invalid preset data",
"deletePresetFailed": "Failed to delete preset",
@@ -2062,6 +2119,14 @@
"updateFailed": "Failed to update trigger words",
"copyFailed": "Copy failed"
},
"undo": {
"action": "Undo",
"deleted": "Deleted {name}",
"deletedBulk": "Deleted {count} item(s)",
"expired": "Undo window expired. The item was permanently deleted.",
"failed": "Undo failed: {error}",
"restored": "Item restored"
},
"virtual": {
"loadFailed": "Failed to load items",
"loadMoreFailed": "Failed to load more items",
@@ -2125,6 +2190,7 @@
"fileRenameFailed": "Failed to rename file: {error}",
"previewUpdated": "Preview updated successfully",
"previewUploadFailed": "Failed to upload preview image",
"previewDropInvalid": "Unsupported file type: {name}. Drop an image or MP4 video instead.",
"refreshComplete": "{action} complete",
"refreshFailed": "Failed to {action} {type}s",
"metadataRefreshed": "Metadata refreshed successfully",
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@@ -1,9 +1,13 @@
# pyright: reportImportCycles=false
# Lazy (function-local) imports still count as static edges in basedpyright's
# reportImportCycles, so the ServiceRegistry singleton pattern necessarily forms
# import cycles. Breaking them would require an architectural refactor.
import os
import platform
import posixpath
import threading
from pathlib import Path
import folder_paths # type: ignore
import folder_paths # pyright: ignore[reportMissingImports]
from typing import Any, Dict, Iterable, List, Mapping, Optional, Set, Tuple
import logging
import json
@@ -90,7 +94,7 @@ def _resolve_valid_default_root(
def _normalize_folder_paths_for_comparison(
folder_paths: Mapping[str, Iterable[str]],
folder_paths: Mapping[str, Any],
) -> Dict[str, Set[str]]:
"""Normalize folder paths for comparison across libraries."""
@@ -482,7 +486,7 @@ class Config:
import ctypes
FILE_ATTRIBUTE_REPARSE_POINT = 0x400
attrs = ctypes.windll.kernel32.GetFileAttributesW(str(path)) # type: ignore[attr-defined]
attrs = ctypes.windll.kernel32.GetFileAttributesW(str(path)) # pyright: ignore[reportAttributeAccessIssue]
return attrs != -1 and (attrs & FILE_ATTRIBUTE_REPARSE_POINT)
except Exception as e:
logger.error(f"Error checking Windows reparse point: {e}")
@@ -491,7 +495,7 @@ class Config:
logger.error(f"Error checking link status for {path}: {e}")
return False
def _entry_is_symlink(self, entry: os.DirEntry) -> bool:
def _entry_is_symlink(self, entry: os.DirEntry[str]) -> bool:
"""Check if a directory entry is a symlink, including Windows junctions."""
if entry.is_symlink():
return True
@@ -500,7 +504,7 @@ class Config:
import ctypes
FILE_ATTRIBUTE_REPARSE_POINT = 0x400
attrs = ctypes.windll.kernel32.GetFileAttributesW(entry.path) # type: ignore[attr-defined]
attrs = ctypes.windll.kernel32.GetFileAttributesW(entry.path) # pyright: ignore[reportAttributeAccessIssue]
return attrs != -1 and (attrs & FILE_ATTRIBUTE_REPARSE_POINT)
except Exception:
pass
@@ -1126,8 +1130,8 @@ class Config:
def _apply_library_paths(
self,
folder_paths: Mapping[str, Iterable[str]],
extra_folder_paths: Optional[Mapping[str, Iterable[str]]] = None,
folder_paths: Mapping[str, Any],
extra_folder_paths: Optional[Mapping[str, Any]] = None,
recipes_path: str = "",
) -> None:
self._path_mappings.clear()
@@ -1432,12 +1436,13 @@ class Config:
# ('_lm_config_cache') that is NEVER removed from sys.modules (its key does
# NOT start with 'py.'), so it survives re-imports of py.* modules.
_CONFIG_SENTINEL = "_lm_config_cache"
config: Config
if _CONFIG_SENTINEL in _sys.modules:
# Re-import: reuse the existing singleton from the sentinel.
config: Config = _sys.modules[_CONFIG_SENTINEL].config # type: ignore[valid-type]
config = _sys.modules[_CONFIG_SENTINEL].config
else:
config: Config = Config()
config = Config()
# Register the sentinel so re-imports of py.config find us.
_sentinel_mod = _types.ModuleType(_CONFIG_SENTINEL)
_sentinel_mod.config = config
setattr(_sentinel_mod, "config", config)
_sys.modules[_CONFIG_SENTINEL] = _sentinel_mod
+18 -1
View File
@@ -14,7 +14,7 @@ standalone_mode = (
if not standalone_mode:
setup_logging()
from server import PromptServer # type: ignore
from server import PromptServer # pyright: ignore[reportMissingImports]
from .config import config
from .services.model_service_factory import (
@@ -25,10 +25,12 @@ from .routes.recipe_routes import RecipeRoutes
from .routes.stats_routes import StatsRoutes
from .routes.update_routes import UpdateRoutes
from .routes.misc_routes import MiscRoutes
from .routes.pending_delete_routes import PendingDeleteRoutes
from .routes.preview_routes import PreviewRoutes
from .routes.example_images_routes import ExampleImagesRoutes
from .services.service_registry import ServiceRegistry
from .services.settings_manager import get_settings_manager
from .services.pending_delete_service import get_pending_delete_service
from .utils.example_images_migration import ExampleImagesMigration
from .services.websocket_manager import ws_manager
from .services.example_images_cleanup_service import ExampleImagesCleanupService
@@ -170,6 +172,7 @@ class LoraManager:
RecipeRoutes.setup_routes(app)
UpdateRoutes.setup_routes(app)
MiscRoutes.setup_routes(app)
PendingDeleteRoutes.setup_routes(app)
ExampleImagesRoutes.setup_routes(app, ws_manager=ws_manager)
PreviewRoutes.setup_routes(app)
@@ -245,6 +248,20 @@ class LoraManager:
cls._run_post_initialization_tasks(init_tasks), name="post_init_tasks"
)
# Startup sweep: purge pending-delete batches that expired during a
# previous run. Non-blocking (fire-and-forget); purge_expired only
# removes already-expired batches, so a staged undo that survived a
# restart stays restorable. scan_roots=True runs the reconciliation
# pass first so leftover batches (the in-process registry is empty
# after a restart) are re-discovered on disk. Covers both plugin
# and standalone modes (StandaloneLoraManager reuses this
# classmethod).
pending_delete_service = await get_pending_delete_service()
asyncio.create_task(
pending_delete_service.purge_expired(scan_roots=True),
name="pending_delete_startup_sweep",
)
logger.debug(
"LoRA Manager: All services initialized and background tasks scheduled"
)
+2 -2
View File
@@ -22,7 +22,7 @@ if not standalone_mode:
logger.info("ComfyUI Metadata Collector initialized")
def get_metadata(prompt_id=None): # type: ignore[no-redef]
def get_metadata(prompt_id=None): # pyright: ignore[reportRedeclaration]
"""Helper function to get metadata from the registry"""
registry = MetadataRegistry()
return registry.get_metadata(prompt_id)
@@ -31,6 +31,6 @@ else:
def init():
logger.info("ComfyUI Metadata Collector disabled in standalone mode")
def get_metadata(prompt_id=None): # type: ignore[no-redef]
def get_metadata(prompt_id=None): # pyright: ignore[reportRedeclaration]
"""Dummy implementation for standalone mode"""
return {}
+1 -1
View File
@@ -16,7 +16,7 @@ class MetadataHook:
execution = None
try:
# Try direct import first
import execution # type: ignore
import execution # pyright: ignore[reportMissingImports]
except ImportError:
# Try to locate from system modules
for module_name in sys.modules:
+11 -1
View File
@@ -1,5 +1,6 @@
import time
from nodes import NODE_CLASS_MAPPINGS # type: ignore
from typing import Any
from nodes import NODE_CLASS_MAPPINGS # pyright: ignore[reportMissingImports, reportAttributeAccessIssue]
from .node_extractors import NODE_EXTRACTORS, GenericNodeExtractor
from .constants import METADATA_CATEGORIES, IMAGES, OVERWRITE
@@ -9,6 +10,15 @@ class MetadataRegistry:
_instance = None
current_prompt_id: Any = None
current_prompt: Any = None
metadata: dict[str, Any] = {}
prompt_metadata: dict[str, Any] = {}
executed_nodes: set[str] = set()
node_cache: dict[str, Any] = {}
max_prompt_history: int = 3
metadata_categories: list[str] = METADATA_CATEGORIES
def __new__(cls):
if cls._instance is None:
cls._instance = super().__new__(cls)
+70 -29
View File
@@ -2,7 +2,8 @@ import json
import os
import re
from .constants import CLIP_SKIP_SENTINEL, MODELS, PROMPTS, SAMPLING, LORAS, SIZE, IMAGES, IS_SAMPLER, OVERWRITE, METADATA_OVERWRITE_FIELDS
from .constants import MODELS, PROMPTS, SAMPLING, LORAS, SIZE, IMAGES, IS_SAMPLER, OVERWRITE
from .overwrite_utils import collect_overwrite_params
def _store_checkpoint_metadata(metadata, node_id, model_name):
@@ -39,7 +40,7 @@ class GenericNodeExtractor(NodeMetadataExtractor):
* ``MODEL`` output: common input fields (ckpt_name, unet_name, etc.)
are checked for a model file name and stored as checkpoint metadata.
* ``CONDITIONING`` output: common text input fields are checked for
prompt text and stored as prompt metadata.
prompt text, and conditioning inputs are tracked through transforms.
"""
# Input field names that carry a model path in loader-style nodes.
@@ -72,7 +73,7 @@ class GenericNodeExtractor(NodeMetadataExtractor):
_store_checkpoint_metadata(metadata, node_id, name)
return
# — CONDITIONING encoder detection (CLIPTextEncode, Flux, custom)
# — CONDITIONING encoder / transform detection
if "CONDITIONING" in return_types or any("CONDITIONING" in str(t) for t in return_types):
text = None
for field in GenericNodeExtractor._TEXT_FIELDS:
@@ -80,12 +81,14 @@ class GenericNodeExtractor(NodeMetadataExtractor):
if val and isinstance(val, str) and val.strip():
text = val.strip()
break
if text:
prompt_data = metadata.setdefault(PROMPTS, {})
prompt_data[node_id] = {
"text": text,
"node_id": node_id,
}
input_conditionings = _collect_conditioning_inputs(inputs)
if text or input_conditionings:
prompt_metadata = _ensure_prompt_metadata(metadata, node_id)
if text:
prompt_metadata["text"] = text
if input_conditionings:
prompt_metadata["orig_conditionings"] = input_conditionings
@staticmethod
def update(node_id, outputs, metadata, return_types=None):
@@ -97,11 +100,26 @@ class GenericNodeExtractor(NodeMetadataExtractor):
return
if node_id not in metadata.get(PROMPTS, {}):
return
if outputs and isinstance(outputs, list) and len(outputs) > 0:
if isinstance(outputs[0], tuple) and len(outputs[0]) > 0:
cond = outputs[0][0]
if cond is not None:
metadata[PROMPTS][node_id]["conditioning"] = cond
output_tuple = _first_output_tuple(outputs)
if not output_tuple or len(output_tuple) < 1:
return
conditioning_index = _first_conditioning_index(return_types)
if conditioning_index is None or len(output_tuple) <= conditioning_index:
return
output_conditioning = output_tuple[conditioning_index]
if output_conditioning is None:
return
prompt_metadata = metadata[PROMPTS][node_id]
prompt_metadata["conditioning"] = output_conditioning
_record_conditioning_source(
metadata,
node_id,
output_conditioning,
prompt_metadata.get("orig_conditionings", []),
)
class CheckpointLoaderExtractor(NodeMetadataExtractor):
@staticmethod
@@ -416,6 +434,34 @@ def _first_output_tuple(outputs):
return None
def _first_conditioning_index(return_types):
"""Return the index of the first CONDITIONING output slot, or None."""
if not return_types:
return None
for index, return_type in enumerate(return_types):
if "CONDITIONING" in str(return_type):
return index
return None
def _collect_conditioning_inputs(inputs):
"""Collect conditioning object inputs (``conditioning*`` keys).
Primitive values (None, str, int, float, bool) are excluded so scalar
fields like ``conditioning_strength`` are not mistaken for conditioning
objects during provenance tracking.
"""
if not inputs:
return []
return [
value
for input_name, value in inputs.items()
if input_name.startswith("conditioning")
and value is not None
and not isinstance(value, (str, int, float, bool))
]
def _record_conditioning_source(
metadata, node_id, output_conditioning, input_conditionings
):
@@ -428,6 +474,14 @@ def _record_conditioning_source(
if not sources:
return
# Identity-preserving selectors return one of their inputs unchanged:
# only that input contributed to the output, so record it alone instead
# of treating every input as a combination source.
for conditioning in sources:
if id(conditioning) == id(output_conditioning):
sources = [conditioning]
break
prompt_metadata = _ensure_prompt_metadata(metadata, node_id)
prompt_metadata.setdefault("conditioning_sources", []).append(
{
@@ -507,13 +561,7 @@ class ConditioningCombineExtractor(NodeMetadataExtractor):
if not inputs:
return
input_conditionings = []
for input_name in inputs:
if (
input_name.startswith("conditioning")
and inputs[input_name] is not None
):
input_conditionings.append(inputs[input_name])
input_conditionings = _collect_conditioning_inputs(inputs)
if input_conditionings:
prompt_metadata = _ensure_prompt_metadata(metadata, node_id)
@@ -1233,14 +1281,7 @@ class MetadataOverwriteExtractor(NodeMetadataExtractor):
if not inputs:
return
overwrite_params = {}
for key in METADATA_OVERWRITE_FIELDS:
value = inputs.get(key)
if key == "clip_skip":
if value != CLIP_SKIP_SENTINEL:
overwrite_params[key] = value
elif value: # truthy — only overwrite when user provided a real value
overwrite_params[key] = value
overwrite_params = collect_overwrite_params(inputs)
if overwrite_params:
metadata.setdefault(OVERWRITE, {})
+42
View File
@@ -0,0 +1,42 @@
"""Shared helpers for Metadata Overwrite node metadata collection.
Used by both the MetadataOverwriteLM node (execution time) and the
MetadataOverwriteExtractor (hook time) so the conversion/filtering logic
cannot drift between the two paths.
"""
import logging
from typing import Any, Dict
from ..utils.utils import model_patcher_to_name
from .constants import CLIP_SKIP_SENTINEL, METADATA_OVERWRITE_FIELDS
logger = logging.getLogger(__name__)
def collect_overwrite_params(values: Dict[str, Any]) -> Dict[str, Any]:
"""Convert node input values into non-default overwrite parameters.
For most fields, a falsy value (empty string, 0) means "not set" and is
skipped. clip_skip uses a dedicated sentinel (-25) so that a wired value
of 0 is preserved. The ``model`` field accepts either a manual string or
a wired MODEL (ModelPatcher) connection; in the latter case the source
model name is extracted from the patcher's ``cached_patcher_init`` and
stored as a ComfyUI-style relative path.
"""
result: Dict[str, Any] = {}
for key in METADATA_OVERWRITE_FIELDS:
value = values.get(key)
if key == "model" and not isinstance(value, str):
value = model_patcher_to_name(value)
if value is None:
logger.warning(
"Could not extract model name from wired MODEL input "
"(no cached_patcher_init); model metadata overwrite skipped"
)
if key == "clip_skip":
if value != CLIP_SKIP_SENTINEL:
result[key] = value
elif value:
result[key] = value
return result
+2 -2
View File
@@ -43,7 +43,7 @@ SCANNER_GETTER_NAMES = tuple(SCANNER_TYPE_MAP.keys())
async def _find_model_entry(
model_path: str,
) -> tuple[object, object, str | None] | tuple[None, None, None]:
) -> tuple[Any, object, str | None] | tuple[None, None, None]:
"""Iterate all scanners and return the first (scanner, entry, getter_name)
that owns *model_path*. Returns ``(None, None, None)`` when no scanner
claims it.
@@ -73,7 +73,7 @@ async def _find_model_entry(
async def _find_scanner_for_model(
model_path: str,
) -> tuple[object, object] | tuple[None, None]:
) -> tuple[Any, object] | tuple[None, None]:
"""Find the (scanner, cache_entry) responsible for *model_path*."""
scanner, entry, _ = await _find_model_entry(model_path)
return scanner, entry
+11 -7
View File
@@ -1,7 +1,8 @@
import logging
from typing import List, Tuple
import comfy.sd # type: ignore
import folder_paths # type: ignore
import os
from typing import Any, List, Tuple
import comfy.sd # pyright: ignore[reportMissingImports]
import folder_paths # pyright: ignore[reportMissingImports]
from ..utils.utils import get_checkpoint_info_absolute, _format_model_name_for_comfyui
logger = logging.getLogger(__name__)
@@ -18,9 +19,9 @@ class CheckpointLoaderLM:
CATEGORY = "Lora Manager/loaders"
@classmethod
def INPUT_TYPES(s):
def INPUT_TYPES(cls):
# Get list of checkpoint names from scanner (includes extra folder paths)
checkpoint_names = s._get_checkpoint_names()
checkpoint_names = cls._get_checkpoint_names()
return {
"required": {
"ckpt_name": (
@@ -58,7 +59,10 @@ class CheckpointLoaderLM:
for item in cache.raw_data:
if item.get("sub_type") == "checkpoint":
file_path = item.get("file_path", "")
if file_path:
# Only offer models that still exist on disk so ComfyUI
# flags missing checkpoints at queue time via
# "value not in list" (the scanner cache can be stale).
if file_path and os.path.exists(file_path):
# Format using relative path with OS-native separator
formatted_name = _format_model_name_for_comfyui(
file_path, model_roots
@@ -89,7 +93,7 @@ class CheckpointLoaderLM:
logger.error(f"Error getting checkpoint names: {e}")
return []
def load_checkpoint(self, ckpt_name: str) -> Tuple:
def load_checkpoint(self, ckpt_name: str) -> Tuple[Any, Any, Any]:
"""Load a checkpoint by name, supporting extra folder paths
Args:
+8 -2
View File
@@ -15,6 +15,7 @@ from .utils import (
any_type,
apply_lora_syntax_format,
get_loras_list,
validate_lora_entries,
)
logger = logging.getLogger(__name__)
@@ -42,6 +43,11 @@ class CreateHookLoraLM:
"optional": FlexibleOptionalInputType(any_type),
}
@classmethod
def VALIDATE_INPUTS(cls, loras=None):
"""Queue-time validation: reject missing local LoRAs before execution."""
return validate_lora_entries({"loras": loras}) or True
RETURN_TYPES = ("HOOKS", "STRING", "STRING")
RETURN_NAMES = ("HOOKS", "trigger_words", "active_loras")
FUNCTION = "create_hook"
@@ -57,8 +63,8 @@ class CreateHookLoraLM:
del text # used by the frontend widget only
# Lazy imports: comfy is not available in CI/test environment at module level
import comfy.hooks # type: ignore # noqa: C0415
import comfy.utils # type: ignore # noqa: C0415
import comfy.hooks # pyright: ignore[reportMissingImports] # noqa: C0415
import comfy.utils # pyright: ignore[reportMissingImports] # noqa: C0415
prev_hooks: comfy.hooks.HookGroup | None = kwargs.get("prev_hooks")
+8 -2
View File
@@ -1,8 +1,8 @@
import importlib
import logging
import comfy.sd # type: ignore
import comfy.utils # type: ignore
import comfy.sd # pyright: ignore[reportMissingImports]
import comfy.utils # pyright: ignore[reportMissingImports]
from ..utils.utils import get_lora_info_absolute
from .utils import (
@@ -14,6 +14,7 @@ from .utils import (
get_loras_list,
nunchaku_load_lora,
parse_lora_syntax,
validate_lora_entries,
)
logger = logging.getLogger(__name__)
@@ -142,6 +143,11 @@ class LoraLoaderLM:
"optional": FlexibleOptionalInputType(any_type),
}
@classmethod
def VALIDATE_INPUTS(cls, loras=None):
"""Queue-time validation: reject missing local LoRAs before execution."""
return validate_lora_entries({"loras": loras}) or True
RETURN_TYPES = ("MODEL", "CLIP", "STRING", "STRING")
RETURN_NAMES = ("MODEL", "CLIP", "trigger_words", "loaded_loras")
FUNCTION = "load_loras"
+6
View File
@@ -9,6 +9,7 @@ and tracks the last used combination for reuse.
import logging
import os
from ..utils.utils import get_lora_info
from .utils import validate_lora_entries
logger = logging.getLogger(__name__)
@@ -31,6 +32,11 @@ class LoraRandomizerLM:
},
}
@classmethod
def VALIDATE_INPUTS(cls, loras=None):
"""Queue-time validation: reject missing local LoRAs before execution."""
return validate_lora_entries({"loras": loras}) or True
RETURN_TYPES = ("LORA_STACK",)
RETURN_NAMES = ("LORA_STACK",)
+1 -1
View File
@@ -73,7 +73,7 @@ class LoraStackCombinerLM:
stack = inspect.stack()
if len(stack) > 2 and stack[2].function == "get_input_info":
optional_inputs = _LoraStackOptionalInputs(optional_inputs) # type: ignore[assignment]
optional_inputs = _LoraStackOptionalInputs(optional_inputs) # pyright: ignore[reportAssignmentType]
return {
"required": {},
+6 -1
View File
@@ -1,6 +1,6 @@
import os
from ..utils.utils import get_lora_info
from .utils import FlexibleOptionalInputType, any_type, apply_lora_syntax_format, extract_lora_name, get_loras_list
from .utils import FlexibleOptionalInputType, any_type, apply_lora_syntax_format, extract_lora_name, get_loras_list, validate_lora_entries
import logging
@@ -22,6 +22,11 @@ class LoraStackerLM:
"optional": FlexibleOptionalInputType(any_type),
}
@classmethod
def VALIDATE_INPUTS(cls, loras=None):
"""Queue-time validation: reject missing local LoRAs before execution."""
return validate_lora_entries({"loras": loras}) or True
RETURN_TYPES = ("LORA_STACK", "STRING", "STRING")
RETURN_NAMES = ("LORA_STACK", "trigger_words", "active_loras")
FUNCTION = "stack_loras"
+14 -15
View File
@@ -9,10 +9,8 @@ but users may wire 0 to express "no clip skip / default".
from typing import Any
from ..metadata_collector.constants import (
CLIP_SKIP_SENTINEL as _CLIP_SKIP_SENTINEL,
METADATA_OVERWRITE_FIELDS,
)
from ..metadata_collector.constants import CLIP_SKIP_SENTINEL as _CLIP_SKIP_SENTINEL
from ..metadata_collector.overwrite_utils import collect_overwrite_params
class MetadataOverwriteLM:
@@ -87,12 +85,16 @@ class MetadataOverwriteLM:
},
),
"model": (
"STRING",
"STRING,MODEL",
{
"default": "",
"widgetType": "STRING",
"tooltip": (
"The checkpoint or diffusion model (UNet) used "
"for generation. Only overwrites when non-empty."
"for generation. Fill in the name manually or "
"connect a MODEL output — the model name is then "
"extracted automatically. Only overwrites when "
"non-empty."
),
},
),
@@ -158,13 +160,10 @@ class MetadataOverwriteLM:
For most fields, a falsy value (empty string, 0) means "not set"
and is skipped. clip_skip uses a dedicated sentinel (-25) so that
a wired value of 0 is preserved and reaches the metadata pipeline.
The ``model`` field accepts either a manual string or a wired MODEL
(ModelPatcher) connection; in the latter case the underlying model
name is extracted from the patcher's ``cached_patcher_init`` and
stored as a ComfyUI-style relative path.
"""
result: dict[str, Any] = {}
for key in METADATA_OVERWRITE_FIELDS:
value = kwargs.get(key)
if key == "clip_skip":
if value != _CLIP_SKIP_SENTINEL:
result[key] = value
elif value:
result[key] = value
return (result,)
return (collect_overwrite_params(kwargs),)
+12 -13
View File
@@ -15,15 +15,15 @@ import os
import re
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Optional, Tuple, Union
from typing import Any, Dict, List, Optional, Tuple, Union, cast
import comfy.utils # type: ignore
import folder_paths # type: ignore
import comfy.utils # pyright: ignore[reportMissingImports]
import folder_paths # pyright: ignore[reportMissingImports]
import torch
import torch.nn as nn
from safetensors import safe_open
from nunchaku.lora.flux.nunchaku_converter import (
from nunchaku.lora.flux.nunchaku_converter import ( # pyright: ignore[reportMissingTypeStubs]
pack_lowrank_weight,
unpack_lowrank_weight,
)
@@ -87,10 +87,6 @@ def _rename_layer_underscore_layer_name(old_name: str) -> str:
return new_name
def _is_indexable_module(module):
return isinstance(module, (nn.ModuleList, nn.Sequential, list, tuple))
def _get_module_by_name(model: nn.Module, name: str) -> Optional[nn.Module]:
if not name:
return model
@@ -100,7 +96,7 @@ def _get_module_by_name(model: nn.Module, name: str) -> Optional[nn.Module]:
continue
if hasattr(module, part):
module = getattr(module, part)
elif part.isdigit() and _is_indexable_module(module):
elif part.isdigit() and isinstance(module, (nn.ModuleList, nn.Sequential, list, tuple)):
try:
module = module[int(part)]
except (IndexError, TypeError):
@@ -267,7 +263,9 @@ def _handle_proj_out_split(lora_dict: Dict[str, Dict[str, torch.Tensor]], base_k
return result, consumed
def _apply_lora_to_module(module: nn.Module, a_tensor: torch.Tensor, b_tensor: torch.Tensor, module_name: str, model: nn.Module) -> None:
def _apply_lora_to_module(module: Any, a_tensor: torch.Tensor, b_tensor: torch.Tensor, module_name: str, model: Any) -> None:
# These modules are dynamic torch containers; monkey-patched attributes
# below are set at runtime, so the module/model types are deliberately Any.
if not hasattr(module, "in_features") or not hasattr(module, "out_features"):
raise ValueError(f"{module_name}: unsupported module without in/out features")
if a_tensor.shape[1] != module.in_features or b_tensor.shape[0] != module.out_features:
@@ -336,7 +334,7 @@ def _apply_lora_to_module(module: nn.Module, a_tensor: torch.Tensor, b_tensor: t
raise ValueError(f"{module_name}: unsupported module type {type(module)}")
def reset_lora_v2(model: nn.Module) -> None:
def reset_lora_v2(model: Any) -> None:
slots = getattr(model, "_lora_slots", None)
if not slots:
return
@@ -344,6 +342,7 @@ def reset_lora_v2(model: nn.Module) -> None:
module = _get_module_by_name(model, name)
if module is None:
continue
module = cast(Any, module)
module_type = info.get("type", "nunchaku")
if module_type == "nunchaku":
base_rank = info["base_rank"]
@@ -371,7 +370,7 @@ def reset_lora_v2(model: nn.Module) -> None:
def compose_loras_v2(model: nn.Module, lora_configs: List[Tuple[Union[str, Path, Dict[str, torch.Tensor]], float]], apply_awq_mod: bool = True) -> bool:
del apply_awq_mod # retained for interface compatibility
reset_lora_v2(model)
aggregated_weights: Dict[str, List[Dict[str, object]]] = defaultdict(list)
aggregated_weights: Dict[str, List[Dict[str, Any]]] = defaultdict(list)
saw_supported_format = False
unresolved_targets = 0
@@ -471,7 +470,7 @@ def compose_loras_v2(model: nn.Module, lora_configs: List[Tuple[Union[str, Path,
class ComfyQwenImageWrapperLM(nn.Module):
def __init__(self, model: nn.Module, config=None, apply_awq_mod: bool = True):
super().__init__()
self.model = model
self.model: Any = model
self.config = {} if config is None else config
self.dtype = next(model.parameters()).dtype
self.loras: List[Tuple[Union[str, Path, Dict[str, torch.Tensor]], float]] = []
+2 -2
View File
@@ -67,7 +67,7 @@ class PromptLM:
stack = inspect.stack()
if len(stack) > 2 and stack[2].function == "get_input_info":
optional_inputs = _PromptOptionalInputs(optional_inputs) # type: ignore[assignment]
optional_inputs = _PromptOptionalInputs(optional_inputs) # pyright: ignore[reportAssignmentType]
return {
"required": {
@@ -126,7 +126,7 @@ class PromptLM:
else:
prompt = expanded_text
from nodes import CLIPTextEncode # type: ignore
from nodes import CLIPTextEncode # pyright: ignore[reportMissingImports, reportAttributeAccessIssue]
conditioning = CLIPTextEncode().encode(clip, prompt)[0]
return (conditioning, prompt)
+22 -9
View File
@@ -5,7 +5,7 @@ import time
import uuid
from typing import Any, Dict, Optional
import numpy as np
import folder_paths # type: ignore
import folder_paths # pyright: ignore[reportMissingImports]
from ..services.service_registry import ServiceRegistry
from ..metadata_collector.metadata_processor import MetadataProcessor
from ..metadata_collector import get_metadata
@@ -13,7 +13,7 @@ from ..utils.constants import CARD_PREVIEW_WIDTH
from ..utils.exif_utils import ExifUtils
from ..utils.utils import calculate_recipe_fingerprint, sanitize_folder_name
from PIL import Image, PngImagePlugin
import piexif
import piexif # pyright: ignore[reportMissingTypeStubs]
import logging
# Civitai-compatible sampler name mapping: ComfyUI internal → A1111 display name
@@ -252,6 +252,13 @@ class SaveImageLM:
"tooltip": "When enabled, embeds generation parameters into the saved image metadata. Disable to skip writing generation metadata.",
},
),
"add_loras_to_prompt": (
"BOOLEAN",
{
"default": False,
"tooltip": "When enabled, appends the LoRA syntax line (e.g. <lora:name:strength>) after the positive prompt in the saved metadata.",
},
),
"add_counter_to_filename": (
"BOOLEAN",
{
@@ -348,7 +355,7 @@ class SaveImageLM:
type_lower = model_type.lower() if model_type else "other"
return f"urn:air:{slug}:{type_lower}:civitai:{model_id}@{version_id}"
def format_metadata(self, metadata_dict: dict) -> str:
def format_metadata(self, metadata_dict: dict[str, Any], add_loras_to_prompt: bool = False) -> str:
"""Format metadata as A1111-compatible parameters string with Hashes JSON and Civitai resources."""
if not metadata_dict: return ""
@@ -389,7 +396,7 @@ class SaveImageLM:
ckpt_display_name = os.path.splitext(os.path.basename(checkpoint))[0]
# Resolve LoRA hash and Civitai data from local cache
loras_data: list[dict] = []
loras_data: list[dict[str, Any]] = []
for lora_name, strength in lora_entries:
lora_hash, lora_civitai, lora_base_model = self._resolve_model_cache_entry(
"lora_scanner", lora_name
@@ -411,9 +418,9 @@ class SaveImageLM:
hashes[f"LORA:{lora['name']}"] = lora["hash"][:10].upper()
# Build Civitai resources JSON array
civitai_resources: list[dict] = []
civitai_resources: list[dict[str, Any]] = []
if ckpt_civitai.get("id", 0) > 0:
ckpt_resource: dict = {}
ckpt_resource: dict[str, Any] = {}
ckpt_type = (ckpt_civitai.get("model") or {}).get("type", "Checkpoint")
model_id = ckpt_civitai.get("modelId", 0)
version_id = ckpt_civitai.get("id", 0)
@@ -432,7 +439,7 @@ class SaveImageLM:
lora_civitai = lora["civitai"]
if not lora_civitai or lora_civitai.get("id", 0) <= 0:
continue
lora_resource: dict = {"weight": lora["strength"]}
lora_resource: dict[str, Any] = {"weight": lora["strength"]}
lora_type = (lora_civitai.get("model") or {}).get("type", "LORA")
model_id = lora_civitai.get("modelId", 0)
version_id = lora_civitai.get("id", 0)
@@ -458,7 +465,10 @@ class SaveImageLM:
scheduler_name = scheduler_mapping.get(scheduler, scheduler) if scheduler else None
# Build output lines
lines = [prompt] if prompt else [""]
prompt_line = prompt if prompt else ""
if add_loras_to_prompt and loras_text:
prompt_line = f"{prompt_line}\n{loras_text}" if prompt_line else loras_text
lines = [prompt_line] if prompt_line else [""]
if negative_prompt:
lines.append(f"Negative prompt: {negative_prompt}")
@@ -793,6 +803,7 @@ class SaveImageLM:
save_with_metadata=True,
add_counter_to_filename=True,
save_as_recipe=False,
add_loras_to_prompt=False,
):
"""Save images with metadata"""
results = []
@@ -801,7 +812,7 @@ class SaveImageLM:
raw_metadata = get_metadata()
metadata_dict = MetadataProcessor.to_dict(raw_metadata, id)
metadata = self.format_metadata(metadata_dict)
metadata = self.format_metadata(metadata_dict, add_loras_to_prompt)
# Process filename_prefix with pattern substitution
filename_prefix = self.format_filename(filename_prefix, metadata_dict)
@@ -943,6 +954,7 @@ class SaveImageLM:
save_with_metadata=True,
add_counter_to_filename=True,
save_as_recipe=False,
add_loras_to_prompt=False,
):
"""Process and save image with metadata"""
# Make sure the output directory exists
@@ -974,6 +986,7 @@ class SaveImageLM:
save_with_metadata,
add_counter_to_filename,
save_as_recipe,
add_loras_to_prompt,
)
return {
+31 -7
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@@ -1,12 +1,27 @@
import logging
import os
from typing import List, Tuple
import comfy.sd # type: ignore
from typing import Any, List, Tuple
import comfy.sd # pyright: ignore[reportMissingImports]
from ..utils.utils import get_checkpoint_info_absolute, _format_model_name_for_comfyui
logger = logging.getLogger(__name__)
def _reload_gguf_unet(
unet_path: str, weight_dtype: str, disable_dynamic: bool = False
) -> object:
"""Reload a GGUF diffusion model from disk (cached_patcher_init factory).
Mirrors the GGUF branch of UNETLoaderLM.load_unet so ModelPatcher
deepclone/dynamic machinery can rebuild GGUF models with the correct
GGMLOps. ``disable_dynamic`` is accepted for signature compatibility
with core ComfyUI loaders.
"""
loader = UNETLoaderLM()
model, = loader._load_gguf_unet(unet_path, unet_path, weight_dtype)
return model
class UNETLoaderLM:
"""UNET Loader with support for extra folder paths
@@ -19,9 +34,9 @@ class UNETLoaderLM:
CATEGORY = "Lora Manager/loaders"
@classmethod
def INPUT_TYPES(s):
def INPUT_TYPES(cls):
# Get list of unet names from scanner (includes extra folder paths)
unet_names = s._get_unet_names()
unet_names = cls._get_unet_names()
return {
"required": {
"unet_name": (
@@ -59,7 +74,10 @@ class UNETLoaderLM:
for item in cache.raw_data:
if item.get("sub_type") == "diffusion_model":
file_path = item.get("file_path", "")
if file_path:
# Only offer models that still exist on disk so ComfyUI
# flags missing diffusion models at queue time via
# "value not in list" (the scanner cache can be stale).
if file_path and os.path.exists(file_path):
# Format using relative path with OS-native separator
formatted_name = _format_model_name_for_comfyui(
file_path, model_roots
@@ -90,7 +108,7 @@ class UNETLoaderLM:
logger.error(f"Error getting unet names: {e}")
return []
def load_unet(self, unet_name: str, weight_dtype: str) -> Tuple:
def load_unet(self, unet_name: str, weight_dtype: str) -> Tuple[Any, ...]:
"""Load a diffusion model by name, supporting extra folder paths
Args:
@@ -133,7 +151,7 @@ class UNETLoaderLM:
def _load_gguf_unet(
self, unet_path: str, unet_name: str, weight_dtype: str
) -> Tuple:
) -> Tuple[Any, ...]:
"""Load a GGUF format diffusion model
Args:
@@ -196,6 +214,12 @@ class UNETLoaderLM:
# Wrap with GGUFModelPatcher
model = GGUFModelPatcher.clone(model)
# Register a reload factory so the MODEL carries its source path
# (cached_patcher_init) like core ComfyUI loaders do — required
# for model-name extraction downstream and for ModelPatcher
# deepclone/dynamic machinery.
model.cached_patcher_init = (_reload_gguf_unet, (unet_path, weight_dtype))
return (model,)
except Exception as e:
+159 -3
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@@ -1,3 +1,6 @@
from typing import Any
class AnyType(str):
"""A special class that is always equal in not equal comparisons. Credit to pythongosssss"""
@@ -6,7 +9,7 @@ class AnyType(str):
# Credit to Regis Gaughan, III (rgthree)
class FlexibleOptionalInputType(dict):
class FlexibleOptionalInputType(dict[str, Any]):
"""A special class to make flexible nodes that pass data to our python handlers.
Enables both flexible/dynamic input types (like for Any Switch) or a dynamic number of inputs
@@ -23,6 +26,7 @@ class FlexibleOptionalInputType(dict):
"""
def __init__(self, type):
super().__init__()
self.type = type
def __getitem__(self, key):
@@ -40,7 +44,8 @@ import re
import logging
import copy
import sys
import folder_paths # type: ignore
import asyncio
import folder_paths # pyright: ignore[reportMissingImports]
logger = logging.getLogger(__name__)
@@ -70,7 +75,7 @@ def extract_lora_name(lora_path):
return apply_lora_syntax_format(name_no_ext)
def parse_lora_syntax(text: str) -> list[dict]:
def parse_lora_syntax(text: str) -> list[dict[str, Any]]:
"""Parse <lora:name:strength> syntax from text input into a list of dicts.
Each entry contains: name, model_strength, clip_strength.
@@ -107,6 +112,157 @@ def get_loras_list(kwargs):
return []
_LORA_EXTENSIONS = (".safetensors", ".ckpt", ".pt", ".bin")
def _strip_lora_extension(name: str) -> str:
"""Strip a known LoRA model extension from a name (case-insensitive)."""
lowered = name.lower()
for ext in _LORA_EXTENSIONS:
if lowered.endswith(ext):
return name[: -len(ext)]
return name
def _find_missing_loras(names: list[str]) -> list[str]:
"""Return the names that cannot be resolved to an existing local LoRA file.
Mirrors the matching semantics of ``get_lora_info_absolute``
(py/utils/utils.py): after stripping the extension, a name matches a cached
LoRA when it equals the cached file name or the ``folder/file`` path. As a
fallback, a name containing a folder that only matches by basename resolves
to the first basename match (same behavior as the runtime resolver). Raw
absolute paths that exist on disk are always considered available.
The scanner cache is fetched once for all names; the cache may be stale, so
resolved paths are additionally verified with ``os.path.isfile``.
"""
if not names:
return []
async def _check() -> list[str]:
from ..services.service_registry import ServiceRegistry
scanner = await ServiceRegistry.get_lora_scanner()
# The scanner cache may not be hydrated yet (startup, library path
# change). An empty cache is not authoritative — treat it as "cannot
# verify" and skip validation instead of flagging every active LoRA
# as missing.
if getattr(scanner, "_cache", None) is None or getattr(
scanner, "_is_initializing", False
):
return []
cache = await scanner.get_cached_data()
lookup = {}
basename_candidates = {}
for item in cache.raw_data:
file_path = item.get("file_path")
if not file_path:
continue
file_name = item.get("file_name", "")
folder = item.get("folder", "")
file_name_no_ext = _strip_lora_extension(file_name)
path_name_no_ext = (
f"{folder}/{file_name_no_ext}".replace("\\", "/")
if folder
else file_name_no_ext
)
lookup.setdefault(file_name_no_ext, file_path)
lookup.setdefault(path_name_no_ext, file_path)
basename_candidates.setdefault(file_name_no_ext, []).append(
(folder, file_path)
)
missing = []
for name in names:
if not name:
continue
normalized = name.replace("\\", "/")
# Raw absolute paths (outside the library) are usable as-is.
if os.path.isfile(normalized):
continue
no_ext = _strip_lora_extension(normalized)
file_path = lookup.get(no_ext)
if file_path is None and "/" in no_ext:
# A name with a folder that matches only by basename resolves
# at runtime like get_lora_info_absolute's fallback does:
# prefer a candidate whose folder prefixes the name, else the
# first basename match.
folder, basename = no_ext.rsplit("/", 1)
candidates = basename_candidates.get(basename, [])
file_path = next(
(
fp
for fld, fp in candidates
if fld and no_ext.startswith(fld + "/")
),
None,
)
if file_path is None and candidates:
file_path = candidates[0][1]
if file_path is None or not os.path.isfile(file_path):
missing.append(name)
return missing
try:
# Check if we're already in an event loop
loop = asyncio.get_running_loop()
# If we're in a running loop, run the async check in a separate thread
import concurrent.futures
def run_in_thread():
new_loop = asyncio.new_event_loop()
asyncio.set_event_loop(new_loop)
try:
return new_loop.run_until_complete(_check())
finally:
new_loop.close()
with concurrent.futures.ThreadPoolExecutor() as executor:
future = executor.submit(run_in_thread)
return future.result()
except RuntimeError:
# No event loop is running, we can use asyncio.run()
return asyncio.run(_check())
def validate_lora_entries(kwargs):
"""Validate active LoRA widget entries against the local library.
Used by node ``VALIDATE_INPUTS`` implementations so ComfyUI rejects the
prompt at queue time (``custom_validation_failed``) when an active entry
references a LoRA that is not available locally mirroring how built-in
loader nodes flag missing models before execution starts.
Returns:
None when every active entry resolves to an existing local file,
otherwise a descriptive error string listing the missing LoRAs.
Verification failures (e.g. scanner not ready) are treated as valid
so queueing is never blocked by validation machinery itself.
"""
# Missing/empty loras input is always valid; skip get_loras_list so it
# does not log a warning for the None case on every queue.
if not kwargs.get("loras"):
return None
loras = get_loras_list(kwargs)
active_names = []
for lora in loras:
if not isinstance(lora, dict):
continue
if not lora.get("active", False):
continue
active_names.append(apply_lora_syntax_format(str(lora.get("name") or "")))
try:
missing = _find_missing_loras(active_names)
except Exception:
logger.exception("Failed to validate LoRA entries against the local library")
return None
if not missing:
return None
return "Missing LoRA(s) in local library: " + ", ".join(missing)
def load_state_dict_in_safetensors(path, device="cpu", filter_prefix=""):
"""Simplified version of load_state_dict_in_safetensors that just loads from a local path"""
import safetensors.torch
+6 -1
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@@ -1,7 +1,7 @@
import os
from ..utils.utils import get_lora_info_absolute
from ..config import config
from .utils import FlexibleOptionalInputType, any_type, get_loras_list
from .utils import FlexibleOptionalInputType, any_type, get_loras_list, validate_lora_entries
import logging
logger = logging.getLogger(__name__)
@@ -35,6 +35,11 @@ class WanVideoLoraSelectLM:
"optional": FlexibleOptionalInputType(any_type),
}
@classmethod
def VALIDATE_INPUTS(cls, loras=None):
"""Queue-time validation: reject missing local LoRAs before execution."""
return validate_lora_entries({"loras": loras}) or True
RETURN_TYPES = ("WANVIDLORA", "STRING", "STRING")
RETURN_NAMES = ("lora", "trigger_words", "active_loras")
FUNCTION = "process_loras"
+31 -9
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@@ -1,3 +1,7 @@
# pyright: reportImportCycles=false
# Lazy (function-local) imports still count as static edges in basedpyright's
# reportImportCycles, so the ServiceRegistry singleton pattern necessarily forms
# import cycles. Breaking them would require an architectural refactor.
"""Base classes for recipe parsers."""
import json
@@ -7,7 +11,7 @@ import re
from typing import Dict, List, Any, Optional, Tuple
from abc import ABC, abstractmethod
from ..config import config
from ..utils.constants import VALID_LORA_TYPES, VALID_CHECKPOINT_SUB_TYPES
from ..utils.constants import MODEL_WEIGHT_FILE_TYPES, VALID_LORA_TYPES, VALID_CHECKPOINT_SUB_TYPES
from ..utils.civitai_utils import rewrite_preview_url
logger = logging.getLogger(__name__)
@@ -38,7 +42,7 @@ class RecipeMetadataParser(ABC):
pass
@staticmethod
async def populate_lora_from_civitai(lora_entry: Dict[str, Any], civitai_info_tuple: Tuple[Dict[str, Any], Optional[str]],
async def populate_lora_from_civitai(lora_entry: Dict[str, Any], civitai_info_tuple: Tuple[Dict[str, Any] | None, str | None] | Dict[str, Any],
recipe_scanner=None, base_model_counts=None, hash_value=None) -> Optional[Dict[str, Any]]:
"""
Populate a lora entry with information from Civitai API response
@@ -151,9 +155,9 @@ class RecipeMetadataParser(ABC):
# Process file information if available
if 'files' in civitai_info:
# Find the primary model file (type="Model" and primary=true) in the files list
# Find the primary model file (weights-type and primary=true) in the files list
model_file = next((file for file in civitai_info.get('files', [])
if file.get('type') == 'Model' and file.get('primary') == True), None)
if file.get('type') in MODEL_WEIGHT_FILE_TYPES and file.get('primary') == True), None)
if model_file:
# Get size
@@ -175,10 +179,18 @@ class RecipeMetadataParser(ABC):
lora_entry['localPath'] = local_path
lora_entry['file_name'] = os.path.splitext(os.path.basename(local_path))[0]
# Get thumbnail from local preview if available
# Get thumbnail from local preview if available.
# Match the cache item by local path first (get_path_by_hash
# cascade: 10-char autov2 / 12-char autov3), then by hash.
lora_cache = await lora_scanner.get_cached_data()
lora_item = next((item for item in lora_cache.raw_data
if item['sha256'].lower() == lora_entry['hash'].lower()), None)
h = (lora_entry.get("hash") or "").lower()
lora_item = next((item for item in lora_cache.raw_data
if (item.get("file_path") or "") == local_path), None)
if lora_item is None:
lora_item = next((item for item in lora_cache.raw_data
if (item.get("sha256") or "").lower() == h
or (item.get("autov3") or "").lower() == h
or (item.get("sha256") or "")[:10].lower() == h), None)
if lora_item and 'preview_url' in lora_item:
lora_entry['thumbnailUrl'] = config.get_preview_static_url(lora_item['preview_url'])
except Exception as e:
@@ -194,7 +206,7 @@ class RecipeMetadataParser(ABC):
return lora_entry
@staticmethod
async def populate_checkpoint_from_civitai(checkpoint: Dict[str, Any], civitai_info: Dict[str, Any]) -> Dict[str, Any]:
async def populate_checkpoint_from_civitai(checkpoint: Dict[str, Any], civitai_info: Dict[str, Any] | Tuple[Dict[str, Any] | None, str | None] | None) -> Dict[str, Any]:
"""
Populate checkpoint information from Civitai API response
@@ -249,11 +261,21 @@ class RecipeMetadataParser(ABC):
checkpoint['id'] = civitai_data.get('id', 0)
if 'files' in civitai_data:
# Prefer the file CivitAI marked primary; fall back to any
# weights-type file (providers without primary flags).
model_file = next(
(
file
for file in civitai_data.get('files', [])
if file.get('type') == 'Model'
if file.get('type') in MODEL_WEIGHT_FILE_TYPES
and file.get('primary') is True
),
None,
) or next(
(
file
for file in civitai_data.get('files', [])
if file.get('type') in MODEL_WEIGHT_FILE_TYPES
),
None,
)
+4
View File
@@ -1,3 +1,7 @@
# pyright: reportImportCycles=false
# Lazy (function-local) imports still count as static edges in basedpyright's
# reportImportCycles, so the ServiceRegistry singleton pattern necessarily forms
# import cycles. Breaking them would require an architectural refactor.
import logging
import json
import os
+3 -1
View File
@@ -1,6 +1,7 @@
"""Factory for creating recipe metadata parsers."""
import logging
from typing import Any
from .parsers import (
RecipeFormatParser,
ComfyMetadataParser,
@@ -31,7 +32,8 @@ class RecipeParserFactory:
# First, try CivitaiApiMetadataParser for dict input
if isinstance(metadata, dict):
try:
if CivitaiApiMetadataParser().is_metadata_matching(metadata):
user_comment: Any = metadata
if CivitaiApiMetadataParser().is_metadata_matching(user_comment):
return CivitaiApiMetadataParser()
except Exception as e:
logger.debug(f"CivitaiApiMetadataParser check failed: {e}")
+1 -1
View File
@@ -52,7 +52,7 @@ class AutomaticMetadataParser(RecipeMetadataParser):
negative_and_params = ""
# Initialize metadata
metadata = {
metadata: Dict[str, Any] = {
"prompt": prompt,
"loras": []
}
+117 -56
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@@ -4,7 +4,7 @@ import json
import logging
from typing import Dict, Any, Union
from ..base import RecipeMetadataParser
from ..constants import GEN_PARAM_KEYS
from ..constants import GEN_PARAM_KEYS, VALID_LORA_TYPES
from ...services.metadata_service import get_default_metadata_provider
from ...config import config
@@ -14,15 +14,16 @@ logger = logging.getLogger(__name__)
class CivitaiApiMetadataParser(RecipeMetadataParser):
"""Parser for Civitai image metadata format"""
def is_metadata_matching(self, metadata) -> bool:
def is_metadata_matching(self, user_comment) -> bool:
"""Check if the metadata matches the Civitai image metadata format
Args:
metadata: The metadata from the image (dict)
user_comment: The metadata from the image (dict)
Returns:
bool: True if this parser can handle the metadata
"""
metadata = user_comment
if not metadata or not isinstance(metadata, dict):
return False
@@ -73,7 +74,7 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
return False
async def parse_metadata( # type: ignore[override]
async def parse_metadata( # pyright: ignore[reportIncompatibleMethodOverride]
self, user_comment, recipe_scanner=None, civitai_client=None,
local_cache: dict[str, Any] | None = None,
) -> Dict[str, Any]:
@@ -89,8 +90,7 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
Returns:
Dict containing parsed recipe data
"""
metadata: Dict[str, Any] = user_comment # type: ignore[assignment]
metadata = user_comment
metadata: Dict[str, Any] = user_comment
try:
# Get metadata provider instead of using civitai_client directly
metadata_provider = await get_default_metadata_provider()
@@ -116,7 +116,7 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
metadata = inner_meta
# Initialize result structure
result = {
result: Dict[str, Any] = {
"base_model": None,
"loras": [],
"model": None,
@@ -125,10 +125,10 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
}
# Track already added LoRAs to prevent duplicates
added_loras = {} # key: model_version_id or hash, value: index in result["loras"]
added_loras: Dict[str, Any] = {} # key: model_version_id or hash, value: index in result["loras"]
# Extract hash information from hashes field for LoRA matching
lora_hashes = {}
lora_hashes: Dict[str, Any] = {}
if "hashes" in metadata and isinstance(metadata["hashes"], dict):
for key, hash_value in metadata["hashes"].items():
key_str = str(key)
@@ -184,7 +184,7 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
if model_info:
result["base_model"] = model_info.get("baseModel", "")
base_model_counts = {}
base_model_counts: Dict[str, int] = {}
# Process standard resources array
if "resources" in metadata and isinstance(metadata["resources"], list):
@@ -196,7 +196,7 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
# identification because it has an explicit type field and hash,
# unlike modelVersionIds which is a flat list with no type info.
if resource_type == "model":
checkpoint_entry = {
checkpoint_entry: Dict[str, Any] = {
"id": 0,
"modelId": 0,
"name": resource.get("name", "Unknown Model"),
@@ -216,7 +216,8 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
# Try to look up base model from the checkpoint hash
cp_hash = checkpoint_entry.get("hash")
if cp_hash and metadata_provider:
local_cached = local_cache.get(cp_hash) if local_cache else None
# local_cache keys are stored lowercase
local_cached = local_cache.get(cp_hash.lower()) if local_cache else None
if local_cached:
self._populate_entry_from_cache(
checkpoint_entry, local_cached
@@ -294,8 +295,15 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
# Try to get info from Civitai if hash is available
if lora_hash and metadata_provider:
local_cached = local_cache.get(lora_hash) if local_cache else None
# local_cache keys are stored lowercase
local_cached = local_cache.get(lora_hash.lower()) if local_cache else None
if local_cached:
cached_type = self._cache_item_model_type(local_cached)
if cached_type and cached_type not in VALID_LORA_TYPES:
logger.debug(
f"Skipping non-LoRA cache item for hash {lora_hash}"
)
continue
self._populate_entry_from_cache(
lora_entry, local_cached
)
@@ -304,6 +312,12 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
added_loras[str(lora_entry["id"])] = len(
result["loras"]
)
# Mirror base.py:150-151 counts for API-path loras
bm = local_cached.get("base_model") or ""
if bm:
base_model_counts[bm] = base_model_counts.get(
bm, 0
) + 1
else:
try:
civitai_info = (
@@ -649,30 +663,47 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
}
if metadata_provider:
try:
civitai_info = await metadata_provider.get_model_by_hash(
lora_hash
)
populated_entry = await self.populate_lora_from_civitai(
lora_entry,
civitai_info,
recipe_scanner,
base_model_counts,
lora_hash,
)
if populated_entry is None:
# local_cache keys are stored lowercase
local_cached = local_cache.get(lora_hash.lower()) if local_cache else None
if local_cached:
cached_type = self._cache_item_model_type(local_cached)
if cached_type and cached_type not in VALID_LORA_TYPES:
logger.debug(
f"Skipping non-LoRA cache item for hash {lora_hash}"
)
continue
lora_entry = populated_entry
self._populate_entry_from_cache(lora_entry, local_cached)
# Mirror base.py:150-151 counts for API-path loras
bm = local_cached.get("base_model") or ""
if bm:
base_model_counts[bm] = base_model_counts.get(bm, 0) + 1
if "id" in lora_entry and lora_entry["id"]:
added_loras[str(lora_entry["id"])] = len(result["loras"])
except Exception as e:
logger.error(
f"Error fetching Civitai info for LoRA hash {lora_hash}: {e}"
)
else:
try:
civitai_info = await metadata_provider.get_model_by_hash(
lora_hash
)
populated_entry = await self.populate_lora_from_civitai(
lora_entry,
civitai_info,
recipe_scanner,
base_model_counts,
lora_hash,
)
if populated_entry is None:
continue
lora_entry = populated_entry
if "id" in lora_entry and lora_entry["id"]:
added_loras[str(lora_entry["id"])] = len(result["loras"])
except Exception as e:
logger.error(
f"Error fetching Civitai info for LoRA hash {lora_hash}: {e}"
)
added_loras[lora_hash] = len(result["loras"])
result["loras"].append(lora_entry)
@@ -711,32 +742,51 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
# Try to get info from Civitai if hash is available
if lora_entry["hash"] and metadata_provider:
try:
civitai_info = await metadata_provider.get_model_by_hash(
lora_hash
)
populated_entry = await self.populate_lora_from_civitai(
lora_entry,
civitai_info,
recipe_scanner,
base_model_counts,
lora_hash,
)
if populated_entry is None:
# local_cache keys are stored lowercase
local_cached = local_cache.get(lora_hash.lower()) if local_cache else None
if local_cached:
cached_type = self._cache_item_model_type(local_cached)
if cached_type and cached_type not in VALID_LORA_TYPES:
logger.debug(
f"Skipping non-LoRA cache item for hash {lora_hash}"
)
lora_index += 1
continue # Skip invalid LoRA types
lora_entry = populated_entry
continue # Skip non-LoRA cache items
self._populate_entry_from_cache(lora_entry, local_cached)
# Mirror base.py:150-151 counts for API-path loras
bm = local_cached.get("base_model") or ""
if bm:
base_model_counts[bm] = base_model_counts.get(bm, 0) + 1
# If we have a version ID from Civitai, track it for deduplication
if "id" in lora_entry and lora_entry["id"]:
added_loras[str(lora_entry["id"])] = len(result["loras"])
except Exception as e:
logger.error(
f"Error fetching Civitai info for LoRA hash {lora_entry['hash']}: {e}"
)
else:
try:
civitai_info = await metadata_provider.get_model_by_hash(
lora_hash
)
populated_entry = await self.populate_lora_from_civitai(
lora_entry,
civitai_info,
recipe_scanner,
base_model_counts,
lora_hash,
)
if populated_entry is None:
lora_index += 1
continue # Skip invalid LoRA types
lora_entry = populated_entry
# If we have a version ID from Civitai, track it for deduplication
if "id" in lora_entry and lora_entry["id"]:
added_loras[str(lora_entry["id"])] = len(result["loras"])
except Exception as e:
logger.error(
f"Error fetching Civitai info for LoRA hash {lora_entry['hash']}: {e}"
)
# Track by hash if we have it
if lora_hash:
@@ -795,3 +845,14 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
base_model = cache_item.get("base_model", "")
if base_model:
entry["baseModel"] = base_model
@staticmethod
def _cache_item_model_type(cache_item: dict[str, Any]) -> str:
"""Lowercased civitai.model.type of a cache item, or '' when unknown."""
civ = cache_item.get("civitai")
if not isinstance(civ, dict):
return ""
model_info = civ.get("model")
if not isinstance(model_info, dict):
return ""
return (model_info.get("type") or "").lower()
+1 -1
View File
@@ -30,7 +30,7 @@ class MetaFormatParser(RecipeMetadataParser):
prompt = parts[0].strip()
# Initialize metadata
metadata = {"prompt": prompt, "loras": []}
metadata: Dict[str, Any] = {"prompt": prompt, "loras": []}
# Extract negative prompt and parameters if available
if len(parts) > 1:
+10 -2
View File
@@ -91,7 +91,15 @@ class RecipeFormatParser(RecipeMetadataParser):
exists_locally = lora_scanner.has_hash(lora['hash'])
if exists_locally:
lora_cache = await lora_scanner.get_cached_data()
lora_item = next((item for item in lora_cache.raw_data if item['sha256'].lower() == lora['hash'].lower()), None)
# Cascade match: full sha256, stored autov3, or autov2 (sha256[:10]).
h = (lora.get('hash') or '').lower()
lora_item = next(
(item for item in lora_cache.raw_data
if (item.get("sha256") or "").lower() == h
or (item.get("autov3") or "").lower() == h
or (item.get("sha256") or "")[:10].lower() == h),
None
)
if lora_item:
lora_entry['existsLocally'] = True
lora_entry['inLibrary'] = True
@@ -148,7 +156,7 @@ class RecipeFormatParser(RecipeMetadataParser):
checkpoint_data = recipe_metadata.get('checkpoint') or {}
if isinstance(checkpoint_data, dict) and checkpoint_data:
version_id = checkpoint_data.get('modelVersionId') or checkpoint_data.get('id')
checkpoint_entry = {
checkpoint_entry: Dict[str, Any] = {
'id': version_id or 0,
'modelId': checkpoint_data.get('modelId', 0),
'name': checkpoint_data.get('name', 'Unknown Checkpoint'),
+9 -8
View File
@@ -2,7 +2,7 @@ from __future__ import annotations
import logging
from abc import ABC, abstractmethod
from typing import TYPE_CHECKING, Callable, Dict, Mapping
from typing import TYPE_CHECKING, Awaitable, Callable, Dict, Mapping
import jinja2
from aiohttp import web
@@ -30,6 +30,7 @@ from ..services.websocket_progress_callback import (
WebSocketProgressCallback,
)
from ..utils.exif_utils import ExifUtils
from ..utils.constants import MODEL_WEIGHT_FILE_TYPES
from ..utils.metadata_manager import MetadataManager
from .model_route_registrar import COMMON_ROUTE_DEFINITIONS, ModelRouteRegistrar
from .handlers.model_handlers import (
@@ -84,7 +85,7 @@ class BaseModelRoutes(ABC):
self.metadata_progress_callback = WebSocketBroadcastCallback()
self._handler_set: ModelHandlerSet | None = None
self._handler_mapping: Dict[str, Callable[[web.Request], web.StreamResponse]] | None = None
self._handler_mapping: Dict[str, Callable[[web.Request], Awaitable[web.Response]]] | None = None
self._preview_service = PreviewAssetService(
metadata_manager=MetadataManager,
@@ -131,7 +132,7 @@ class BaseModelRoutes(ABC):
self._handler_set = None
self._handler_mapping = None
def _ensure_handler_mapping(self) -> Mapping[str, Callable[[web.Request], web.StreamResponse]]:
def _ensure_handler_mapping(self) -> Mapping[str, Callable[[web.Request], Awaitable[web.StreamResponse]]]:
if self._handler_mapping is None:
handler_set = self._create_handler_set()
self._handler_set = handler_set
@@ -220,7 +221,7 @@ class BaseModelRoutes(ABC):
)
@property
def route_handlers(self) -> Mapping[str, Callable[[web.Request], web.StreamResponse]]:
def route_handlers(self) -> Mapping[str, Callable[[web.Request], Awaitable[web.StreamResponse]]]:
return self._ensure_handler_mapping()
def setup_routes(self, app: web.Application, prefix: str) -> None:
@@ -237,7 +238,7 @@ class BaseModelRoutes(ABC):
"""Setup model-specific routes."""
raise NotImplementedError
def _parse_specific_params(self, request: web.Request) -> Dict:
def _parse_specific_params(self, request: web.Request) -> Dict[str, Any]:
"""Parse model-specific parameters - to be overridden by subclasses."""
return {}
@@ -251,9 +252,9 @@ class BaseModelRoutes(ABC):
def _find_model_file(self, files):
"""Find the appropriate model file from the files list - can be overridden by subclasses."""
return next((file for file in files if file.get("type") in ("Model", "Diffusion Model") and file.get("primary") is True), None)
return next((file for file in files if file.get("type") in MODEL_WEIGHT_FILE_TYPES and file.get("primary") is True), None)
def get_handler(self, name: str) -> Callable[[web.Request], web.StreamResponse]:
def get_handler(self, name: str) -> Callable[[web.Request], Awaitable[web.StreamResponse]]:
"""Expose handlers for subclasses or tests."""
return self._ensure_handler_mapping()[name]
@@ -285,7 +286,7 @@ class BaseModelRoutes(ABC):
)
return self.model_lifecycle_service
def _make_handler_proxy(self, name: str) -> Callable[[web.Request], web.StreamResponse]:
def _make_handler_proxy(self, name: str) -> Callable[[web.Request], Awaitable[web.StreamResponse]]:
async def proxy(request: web.Request) -> web.StreamResponse:
try:
handler = self.get_handler(name)
+13 -9
View File
@@ -4,7 +4,7 @@ from __future__ import annotations
import logging
import os
from typing import Callable, Mapping
from typing import Awaitable, Callable, Mapping
import jinja2
from aiohttp import web
@@ -61,7 +61,9 @@ class BaseRecipeRoutes:
self._i18n_registered = False
self._startup_hooks_registered = False
self._handler_set: RecipeHandlerSet | None = None
self._handler_mapping: dict[str, Callable] | None = None
self._handler_mapping: Mapping[
str, Callable[[web.Request], Awaitable[web.StreamResponse]]
] | None = None
async def attach_dependencies(self, app: web.Application | None = None) -> None:
"""Resolve shared services from the registry."""
@@ -84,7 +86,9 @@ class BaseRecipeRoutes:
app.on_startup.append(self.attach_dependencies)
self._startup_hooks_registered = True
def to_route_mapping(self) -> Mapping[str, Callable]:
def to_route_mapping(
self,
) -> Mapping[str, Callable[[web.Request], Awaitable[web.StreamResponse]]]:
"""Return a mapping of handler name to coroutine for registrar binding."""
if self._handler_mapping is None:
@@ -124,17 +128,17 @@ class BaseRecipeRoutes:
or os.environ.get("HF_HUB_DISABLE_TELEMETRY", "0") == "0"
)
if not standalone_mode:
from ..metadata_collector import get_metadata # type: ignore[import-not-found]
from ..metadata_collector.metadata_processor import ( # type: ignore[import-not-found]
from ..metadata_collector import get_metadata # pyright: ignore[reportMissingImports]
from ..metadata_collector.metadata_processor import ( # pyright: ignore[reportMissingImports]
MetadataProcessor,
)
from ..metadata_collector.metadata_registry import ( # type: ignore[import-not-found]
from ..metadata_collector.metadata_registry import ( # pyright: ignore[reportMissingImports]
MetadataRegistry,
)
else: # pragma: no cover - optional dependency path
get_metadata = None # type: ignore[assignment]
MetadataProcessor = None # type: ignore[assignment]
MetadataRegistry = None # type: ignore[assignment]
get_metadata = None # pyright: ignore[reportAssignmentType]
MetadataProcessor = None # pyright: ignore[reportAssignmentType]
MetadataRegistry = None # pyright: ignore[reportAssignmentType]
analysis_service = RecipeAnalysisService(
exif_utils=ExifUtils,
+9 -9
View File
@@ -1,5 +1,5 @@
import logging
from typing import Dict, List, Set
from typing import Any, Dict, List, Set
from aiohttp import web
from .base_model_routes import BaseModelRoutes
@@ -28,13 +28,13 @@ class CheckpointRoutes(BaseModelRoutes):
# Attach service dependencies
self.attach_service(self.service)
def setup_routes(self, app: web.Application):
def setup_routes(self, app: web.Application, prefix: str = "checkpoints"):
"""Setup Checkpoint routes"""
# Schedule service initialization on app startup
app.on_startup.append(lambda _: self.initialize_services())
# Setup common routes with 'checkpoints' prefix (includes page route)
super().setup_routes(app, 'checkpoints')
super().setup_routes(app, prefix)
def setup_specific_routes(self, registrar: ModelRouteRegistrar, prefix: str):
"""Setup Checkpoint-specific routes"""
@@ -53,9 +53,9 @@ class CheckpointRoutes(BaseModelRoutes):
"""Get expected model types string for error messages"""
return "Checkpoint"
def _parse_specific_params(self, request: web.Request) -> Dict:
def _parse_specific_params(self, request: web.Request) -> Dict[str, Any]:
"""Parse Checkpoint-specific parameters"""
params: Dict = {}
params: Dict[str, Any] = {}
if 'checkpoint_hash' in request.query:
params['hash_filters'] = {'single_hash': request.query['checkpoint_hash'].lower()}
@@ -70,7 +70,7 @@ class CheckpointRoutes(BaseModelRoutes):
"""Get detailed information for a specific checkpoint by name"""
try:
name = request.match_info.get('name', '')
checkpoint_info = await self.service.get_model_info_by_name(name)
checkpoint_info = await self.service.get_model_info_by_name(name) # pyright: ignore[reportAttributeAccessIssue]
if checkpoint_info:
return web.json_response(checkpoint_info)
@@ -89,7 +89,7 @@ class CheckpointRoutes(BaseModelRoutes):
roots.extend(config.checkpoints_roots or [])
roots.extend(config.extra_checkpoints_roots or [])
# Remove duplicates while preserving order
seen: set = set()
seen: set[str] = set()
unique_roots: List[str] = []
for root in roots:
if root and root not in seen:
@@ -114,7 +114,7 @@ class CheckpointRoutes(BaseModelRoutes):
roots.extend(config.unet_roots or [])
roots.extend(config.extra_unet_roots or [])
# Remove duplicates while preserving order
seen: set = set()
seen: set[str] = set()
unique_roots: List[str] = []
for root in roots:
if root and root not in seen:
+4 -4
View File
@@ -26,13 +26,13 @@ class EmbeddingRoutes(BaseModelRoutes):
# Attach service dependencies
self.attach_service(self.service)
def setup_routes(self, app: web.Application):
def setup_routes(self, app: web.Application, prefix: str = "embeddings"):
"""Setup Embedding routes"""
# Schedule service initialization on app startup
app.on_startup.append(lambda _: self.initialize_services())
# Setup common routes with 'embeddings' prefix (includes page route)
super().setup_routes(app, 'embeddings')
super().setup_routes(app, prefix)
def setup_specific_routes(self, registrar: ModelRouteRegistrar, prefix: str):
"""Setup Embedding-specific routes"""
@@ -51,7 +51,7 @@ class EmbeddingRoutes(BaseModelRoutes):
"""Get detailed information for a specific embedding by name"""
try:
name = request.match_info.get('name', '')
embedding_info = await self.service.get_model_info_by_name(name)
embedding_info = await self.service.get_model_info_by_name(name) # pyright: ignore[reportAttributeAccessIssue]
if embedding_info:
return web.json_response(embedding_info)
+8 -4
View File
@@ -1,7 +1,7 @@
from __future__ import annotations
import logging
from typing import Callable, Mapping
from typing import Any, Awaitable, Callable, Mapping
from aiohttp import web
@@ -35,7 +35,7 @@ class ExampleImagesRoutes:
*,
ws_manager,
download_manager: DownloadManager | None = None,
processor=ExampleImagesProcessor,
processor: Any = ExampleImagesProcessor,
file_manager=ExampleImagesFileManager,
cleanup_service: ExampleImagesCleanupService | None = None,
) -> None:
@@ -46,7 +46,9 @@ class ExampleImagesRoutes:
self._file_manager = file_manager
self._cleanup_service = cleanup_service or ExampleImagesCleanupService()
self._handler_set: ExampleImagesHandlerSet | None = None
self._handler_mapping: Mapping[str, Callable[[web.Request], web.StreamResponse]] | None = None
self._handler_mapping: Mapping[
str, Callable[[web.Request], Awaitable[web.StreamResponse]]
] | None = None
@classmethod
def setup_routes(cls, app: web.Application, *, ws_manager) -> None:
@@ -61,7 +63,9 @@ class ExampleImagesRoutes:
registrar = ExampleImagesRouteRegistrar(app)
registrar.register_routes(self.to_route_mapping())
def to_route_mapping(self) -> Mapping[str, Callable[[web.Request], web.StreamResponse]]:
def to_route_mapping(
self,
) -> Mapping[str, Callable[[web.Request], Awaitable[web.StreamResponse]]]:
"""Return the registrar-compatible mapping of handler names to callables."""
if self._handler_mapping is None:
@@ -3,7 +3,7 @@ from __future__ import annotations
import logging
from dataclasses import dataclass
from typing import Callable, Mapping
from typing import Awaitable, Callable, Mapping
from aiohttp import web
@@ -170,7 +170,7 @@ class ExampleImagesHandlerSet:
management: ExampleImagesManagementHandler
files: ExampleImagesFileHandler
def to_route_mapping(self) -> Mapping[str, Callable[[web.Request], web.StreamResponse]]:
def to_route_mapping(self) -> Mapping[str, Callable[[web.Request], Awaitable[web.StreamResponse]]]:
"""Flatten handler methods into the registrar mapping."""
return {
+53 -45
View File
@@ -276,7 +276,7 @@ def _collect_comfyui_session_logs(
) -> dict[str, Any]:
if log_entries is None:
try:
import app.logger as comfy_logger
import app.logger as comfy_logger # pyright: ignore[reportMissingImports]
log_entries = list(comfy_logger.get_logs() or [])
except Exception as exc: # pragma: no cover - environment dependent
@@ -422,10 +422,10 @@ class PromptServerProtocol(Protocol):
"""Subset of PromptServer used by the handlers."""
instance: "PromptServerProtocol"
sockets: dict # maps clientId (sid) → WebSocketResponse
sockets: dict[str, Any] # maps clientId (sid) → WebSocketResponse
def send_sync(
self, event: str, payload: dict | None = None, sid: str | None = None
self, event: str, payload: dict[str, Any] | None = None, sid: str | None = None
) -> None: # pragma: no cover - protocol
...
@@ -443,7 +443,12 @@ class UsageStatsFactory(Protocol):
class MetadataProviderProtocol(Protocol):
async def get_model_versions(
self, model_id: int
) -> dict | None: # pragma: no cover - protocol
) -> dict[str, Any] | None: # pragma: no cover - protocol
...
async def get_user_models(
self, username: str, cursor: str | None = None
) -> Any: # pragma: no cover - protocol
...
@@ -466,16 +471,16 @@ class MetadataArchiveManagerProtocol(Protocol):
class BackupServiceProtocol(Protocol):
async def create_snapshot(
self, *, snapshot_type: str = "manual", persist: bool = False
) -> dict: # pragma: no cover - protocol
) -> dict[str, Any]: # pragma: no cover - protocol
...
async def restore_snapshot(self, archive_path: str) -> dict: # pragma: no cover - protocol
async def restore_snapshot(self, archive_path: str) -> dict[str, Any]: # pragma: no cover - protocol
...
def get_status(self) -> dict: # pragma: no cover - protocol
def get_status(self) -> dict[str, Any]: # pragma: no cover - protocol
...
def get_available_snapshots(self) -> list[dict]: # pragma: no cover - protocol
def get_available_snapshots(self) -> list[dict[str, Any]]: # pragma: no cover - protocol
...
@@ -491,7 +496,7 @@ class NodeRegistry:
def __init__(self) -> None:
self._lock = asyncio.Lock()
# sid → {unique_id → node_info}
self._tab_nodes: Dict[str, Dict[str, dict]] = {}
self._tab_nodes: Dict[str, Dict[str, dict[str, Any]]] = {}
self._ready = asyncio.Event()
self._waiting_clients: set[str] = set()
@@ -504,7 +509,7 @@ class NodeRegistry:
# Helpers to build one node dict (extracted so it's reused for each tab)
# ------------------------------------------------------------------
@staticmethod
def _build_node_dict(node: dict) -> dict:
def _build_node_dict(node: dict[str, Any]) -> dict[str, Any]:
node_id = node["node_id"]
graph_id = str(node["graph_id"])
unique_id = f"{graph_id}:{node_id}"
@@ -513,11 +518,11 @@ class NodeRegistry:
bgcolor = node.get("bgcolor") or DEFAULT_NODE_COLOR
raw_capabilities = node.get("capabilities")
capabilities: dict = {}
capabilities: dict[str, Any] = {}
if isinstance(raw_capabilities, dict):
capabilities = dict(raw_capabilities)
raw_widget_names: list | None = node.get("widget_names")
raw_widget_names: list[Any] | None = node.get("widget_names")
if not isinstance(raw_widget_names, list):
capability_widget_names = capabilities.get("widget_names")
raw_widget_names = (
@@ -565,9 +570,9 @@ class NodeRegistry:
# ------------------------------------------------------------------
# Public API
# ------------------------------------------------------------------
async def register_nodes(self, sid: str, nodes: list[dict]) -> None:
async def register_nodes(self, sid: str, nodes: list[dict[str, Any]]) -> None:
"""Register/replace the node list for a single ComfyUI tab (identified by *sid*)."""
tab_nodes: dict[str, dict] = {}
tab_nodes: dict[str, dict[str, Any]] = {}
for node in nodes:
nd = self._build_node_dict(node)
tab_nodes[nd["unique_id"]] = nd
@@ -602,7 +607,7 @@ class NodeRegistry:
except asyncio.TimeoutError:
return False
async def get_merged_registry(self, active_sids: set[str] | None = None) -> dict:
async def get_merged_registry(self, active_sids: set[str] | None = None) -> dict[str, Any]:
"""Return the union of all known tab nodes, pruning any tab that is no
longer connected."""
async with self._lock:
@@ -619,8 +624,8 @@ class NodeRegistry:
len(stale_sids), stale_sids,
)
merged: dict[str, dict] = {}
tab_info: dict[str, dict] = {}
merged: dict[str, dict[str, Any]] = {}
tab_info: dict[str, dict[str, Any]] = {}
for sid, nodes in self._tab_nodes.items():
tab_info[sid] = {
"node_count": len(nodes),
@@ -653,7 +658,7 @@ class SupportersHandler:
def __init__(self, logger: logging.Logger | None = None) -> None:
self._logger = logger or logging.getLogger(__name__)
def _load_supporters(self) -> dict:
def _load_supporters(self) -> dict[str, Any]:
"""Load supporters data from JSON file."""
try:
current_file = os.path.abspath(__file__)
@@ -1229,10 +1234,8 @@ class DoctorHandler:
settings_snapshot = _sanitize_sensitive_data(
getattr(self._settings, "settings", {}) or {}
)
startup_messages_getter = getattr(self._settings, "get_startup_messages", None)
startup_messages = (
list(startup_messages_getter()) if callable(startup_messages_getter) else []
)
startup_messages_getter: Any = getattr(self._settings, "get_startup_messages", None)
startup_messages = list(startup_messages_getter()) if startup_messages_getter else []
environment = {
"app_version": app_version,
@@ -1439,7 +1442,7 @@ class SettingsHandler:
*,
settings_service=None,
metadata_provider_updater: Callable[
[], Awaitable[None]
[], Awaitable[Any]
] = update_metadata_providers,
downloader_factory: Callable[
[], Awaitable[DownloaderProtocol]
@@ -1484,8 +1487,8 @@ class SettingsHandler:
settings_file = getattr(self._settings, "settings_file", None)
if settings_file:
response_data["settings_file"] = settings_file
messages_getter = getattr(self._settings, "get_startup_messages", None)
messages = list(messages_getter()) if callable(messages_getter) else []
messages_getter: Any = getattr(self._settings, "get_startup_messages", None)
messages = list(messages_getter()) if messages_getter else []
return web.json_response(
{
"success": True,
@@ -2005,11 +2008,11 @@ async def _noop_backup_service() -> None:
@dataclass
class ServiceRegistryAdapter:
get_lora_scanner: Callable[[], Awaitable]
get_checkpoint_scanner: Callable[[], Awaitable]
get_embedding_scanner: Callable[[], Awaitable]
get_downloaded_version_history_service: Callable[[], Awaitable]
get_backup_service: Callable[[], Awaitable] = _noop_backup_service
get_lora_scanner: Callable[[], Awaitable[Any]]
get_checkpoint_scanner: Callable[[], Awaitable[Any]]
get_embedding_scanner: Callable[[], Awaitable[Any]]
get_downloaded_version_history_service: Callable[[], Awaitable[Any]]
get_backup_service: Callable[[], Awaitable[Any]] = _noop_backup_service
class ModelLibraryHandler:
@@ -2050,8 +2053,8 @@ class ModelLibraryHandler:
return await self._service_registry.get_downloaded_version_history_service()
@staticmethod
def _with_downloaded_flag(versions: list[dict]) -> list[dict]:
enriched: list[dict] = []
def _with_downloaded_flag(versions: list[dict[str, Any]]) -> list[dict[str, Any]]:
enriched: list[dict[str, Any]] = []
for version in versions:
entry = dict(version)
entry.setdefault("hasBeenDownloaded", True)
@@ -2244,7 +2247,7 @@ class ModelLibraryHandler:
checkpoint_scanner = await self._service_registry.get_checkpoint_scanner()
embedding_scanner = await self._service_registry.get_embedding_scanner()
results: list[dict] = []
results: list[dict[str, Any]] = []
for model_id in model_ids:
lora_versions = await lora_scanner.get_model_versions_by_id(model_id)
if lora_versions:
@@ -2353,7 +2356,7 @@ class ModelLibraryHandler:
)
try:
model_version_id = int(data.get("modelVersionId"))
model_version_id = int(data.get("modelVersionId")) # pyright: ignore[reportArgumentType]
except (TypeError, ValueError):
return web.json_response(
{"success": False, "error": "Parameter modelVersionId must be an integer"},
@@ -2465,10 +2468,11 @@ class ModelLibraryHandler:
"checkpoint": checkpoint_scanner,
"embedding": embedding_scanner,
}
scanner = scanner_map.get(found_type)
scanner = scanner_map.get(found_type or "")
if scanner:
persist = getattr(scanner, "_persist_current_cache", None)
if callable(persist):
scanner.bump_cache_version()
persist: Any = getattr(scanner, "_persist_current_cache", None)
if persist:
await persist()
history_service = await self._get_download_history_service()
@@ -2649,13 +2653,13 @@ class ModelLibraryHandler:
}
lora_type_aliases = {model_type.lower() for model_type in VALID_LORA_TYPES}
type_scanner_map: Dict[str, object | None] = {
type_scanner_map: Dict[str, Any] = {
**{alias: lora_scanner for alias in lora_type_aliases},
"checkpoint": checkpoint_scanner,
"textualinversion": embedding_scanner,
}
versions: list[dict] = []
versions: list[dict[str, Any]] = []
history_service = await self._get_download_history_service()
model_ids: list[int] = []
model_count = 0
@@ -2707,6 +2711,8 @@ class ModelLibraryHandler:
tags_value = model.get("tags")
tags = tags_value if isinstance(tags_value, list) else []
model_id = model.get("id")
if model_id is None:
continue
try:
model_id_int = int(model_id)
except (TypeError, ValueError):
@@ -2722,6 +2728,8 @@ class ModelLibraryHandler:
continue
version_id = version.get("id")
if version_id is None:
continue
try:
version_id_int = int(version_id)
except (TypeError, ValueError):
@@ -2783,7 +2791,7 @@ class MetadataArchiveHandler:
] = get_metadata_archive_manager,
settings_service=None,
metadata_provider_updater: Callable[
[], Awaitable[None]
[], Awaitable[Any]
] = update_metadata_providers,
) -> None:
self._metadata_archive_manager_factory = metadata_archive_manager_factory
@@ -2930,7 +2938,7 @@ class BackupHandler:
if request.content_type.startswith("multipart/"):
reader = await request.multipart()
field = await reader.next()
field: Any = await reader.next()
uploaded = False
while field is not None:
if getattr(field, "filename", None):
@@ -3549,7 +3557,7 @@ class NodeRegistryHandler:
except (TypeError, ValueError):
parsed_node_id = node_identifier
payload: dict = {
payload: dict[str, Any] = {
"id": parsed_node_id,
"value": value,
"mode": mode,
@@ -3673,7 +3681,7 @@ class NodeRegistryHandler:
except (TypeError, ValueError):
parsed_node_id = node_identifier
payload: dict = {
payload: dict[str, Any] = {
"id": parsed_node_id,
"value": value,
"mode": mode,
@@ -3740,8 +3748,8 @@ class MiscHandlerSet:
doctor: DoctorHandler,
example_workflows: ExampleWorkflowsHandler,
base_model: BaseModelHandlerSet,
hf_handler: HfHandler | None = None,
agent_handler: AgentHandler | None = None,
hf_handler: Any = None,
agent_handler: Any = None,
) -> None:
self.health = health
self.settings = settings
+119 -19
View File
@@ -51,6 +51,29 @@ LICENSE_FIELDS = (
)
_broadcast_models_changed_tasks: set = set()
def _broadcast_models_changed() -> None:
"""Notify connected clients that the local model library changed.
The ComfyUI graph page listens for this event to invalidate its cached
model availability data (loras widget missing-model cues / error flags)
without waiting for the cache TTL to expire.
"""
try:
from ...services.websocket_manager import ws_manager
task = asyncio.create_task(ws_manager.broadcast({"type": "models_changed"}))
# Keep a reference so the task is not garbage-collected mid-await.
_broadcast_models_changed_tasks.add(task)
task.add_done_callback(_broadcast_models_changed_tasks.discard)
except Exception:
logging.getLogger(__name__).debug(
"Failed to broadcast models_changed", exc_info=True
)
class ModelPageView:
"""Render the HTML view for model listings."""
@@ -71,7 +94,7 @@ class ModelPageView:
self._server_i18n = server_i18n
self._logger = logger
def _load_supporters(self) -> dict:
def _load_supporters(self) -> dict[str, Any]:
"""Load supporters data from JSON file."""
try:
current_file = os.path.abspath(__file__)
@@ -152,7 +175,7 @@ class ModelPageView:
self._template_env.filters["t"] = (
self._server_i18n.create_template_filter()
)
self._template_env._i18n_filter_added = True # type: ignore[attr-defined]
self._template_env._i18n_filter_added = True # pyright: ignore[reportAttributeAccessIssue]
from ...services.llm_service import PROVIDER_PRESETS
@@ -199,7 +222,7 @@ class ModelListingHandler:
self,
*,
service,
parse_specific_params: Callable[[web.Request], Dict],
parse_specific_params: Callable[[web.Request], Dict[str, Any]],
logger: logging.Logger,
) -> None:
self._service = service
@@ -287,7 +310,7 @@ class ModelListingHandler:
)
return web.json_response({"error": str(exc)}, status=500)
def _parse_common_params(self, request: web.Request) -> Dict:
def _parse_common_params(self, request: web.Request) -> Dict[str, Any]:
page = int(request.query.get("page", "1"))
page_size = min(int(request.query.get("page_size", "20")), 100)
sort_by = request.query.get("sort_by", "name")
@@ -460,6 +483,7 @@ class ModelManagementHandler:
return web.Response(text="Model path is required", status=400)
result = await self._lifecycle_service.delete_model(file_path)
_broadcast_models_changed()
return web.json_response(result)
except ValueError as exc:
return web.json_response({"success": False, "error": str(exc)}, status=400)
@@ -658,7 +682,7 @@ class ModelManagementHandler:
try:
reader = await request.multipart()
field = await reader.next()
field: Any = await reader.next()
if field is None or field.name != "preview_file":
raise ValueError("Expected 'preview_file' field")
content_type = field.headers.get("Content-Type", "image/png")
@@ -700,7 +724,7 @@ class ModelManagementHandler:
{
"success": True,
"preview_url": config.get_preview_static_url(
result["preview_path"]
str(result["preview_path"])
),
"preview_nsfw_level": result["preview_nsfw_level"],
}
@@ -781,7 +805,7 @@ class ModelManagementHandler:
result = await self._preview_service.replace_preview(
model_path=model_path,
preview_data=preview_data,
preview_data=preview_bytes,
content_type=content_type,
original_filename=original_filename,
nsfw_level=nsfw_level,
@@ -793,7 +817,7 @@ class ModelManagementHandler:
{
"success": True,
"preview_url": config.get_preview_static_url(
result["preview_path"]
str(result["preview_path"])
),
"preview_nsfw_level": result["preview_nsfw_level"],
}
@@ -931,6 +955,8 @@ class ModelManagementHandler:
file_path=file_path, new_file_name=new_file_name
)
_broadcast_models_changed()
return web.json_response(
{
**result,
@@ -959,6 +985,7 @@ class ModelManagementHandler:
)
result = await self._lifecycle_service.bulk_delete_models(file_paths)
_broadcast_models_changed()
return web.json_response(result)
except ValueError as exc:
return web.json_response({"success": False, "error": str(exc)}, status=400)
@@ -1061,6 +1088,7 @@ class ModelQueryHandler:
await self._service.scan_models(
force_refresh=True, rebuild_cache=full_rebuild
)
_broadcast_models_changed()
if self._service.scanner.is_cancelled():
return web.json_response(
{
@@ -1488,8 +1516,73 @@ class ModelQueryHandler:
search = request.query.get("search", "").strip()
limit = min(int(request.query.get("limit", "15")), 100)
offset = max(0, int(request.query.get("offset", "0")))
folder = request.query.get("folder")
recursive = request.query.get("recursive", "true").lower() == "true"
base_models = list(request.query.getall("base_model", []))
model_types = list(request.query.getall("model_type", []))
tag_filters: Dict[str, str] = {}
for tag in request.query.getall("tag_include", []):
if tag:
tag_filters[tag] = "include"
for tag in request.query.getall("tag_exclude", []):
if tag:
tag_filters[tag] = "exclude"
auto_tag_filters: Dict[str, str] = {}
for tag in request.query.getall("auto_tag_include", []):
if tag:
auto_tag_filters[tag] = "include"
for tag in request.query.getall("auto_tag_exclude", []):
if tag:
auto_tag_filters[tag] = "exclude"
tag_logic = request.query.get("tag_logic", "any").lower()
if tag_logic not in ("any", "all"):
tag_logic = "any"
credit_required = request.query.get("credit_required")
if credit_required is not None:
credit_required = credit_required.lower() not in ("false", "0", "")
allow_selling_generated_content = request.query.get(
"allow_selling_generated_content"
)
if allow_selling_generated_content is not None:
allow_selling_generated_content = (
allow_selling_generated_content.lower() not in ("false", "0", "")
)
# The presence of the recursive param (always sent by the loras
# widget when filter mode is on) signals that the filter pipeline
# must run even when no concrete filter is set, so global settings
# like show_only_sfw stay consistent with the list endpoint.
apply_filters = (
"recursive" in request.query
or folder is not None
or bool(base_models)
or bool(model_types)
or bool(tag_filters)
or bool(auto_tag_filters)
or credit_required is not None
or allow_selling_generated_content is not None
)
matching_paths = await self._service.search_relative_paths(
search, limit, offset
search,
limit,
offset,
folder=folder,
recursive=recursive,
base_models=base_models,
model_types=model_types,
tags=tag_filters,
auto_tags=auto_tag_filters,
tag_logic=tag_logic,
credit_required=credit_required,
allow_selling_generated_content=allow_selling_generated_content,
apply_filters=apply_filters,
)
return web.json_response(
{"success": True, "relative_paths": matching_paths}
@@ -1995,7 +2088,7 @@ class ModelCivitaiHandler:
settings_service: SettingsManager,
ws_manager: WebSocketManager,
logger: logging.Logger,
metadata_provider_factory: Callable[[], Awaitable],
metadata_provider_factory: Callable[[], Awaitable[Any]],
validate_model_type: Callable[[str], bool],
expected_model_types: Callable[[], str],
find_model_file: Callable[
@@ -2060,7 +2153,7 @@ class ModelCivitaiHandler:
downloaded_version_ids = set(
await history_service.get_downloaded_version_ids(
self._service.model_type,
model_id,
int(model_id),
)
)
except Exception as exc: # pragma: no cover - defensive logging
@@ -2170,6 +2263,8 @@ class ModelMoveHandler:
result = await self._move_service.move_model(
file_path, target_path, use_default_paths=use_default_paths
)
if result.get("success"):
_broadcast_models_changed()
status = 200 if result.get("success") else 500
return web.json_response(result, status=status)
except Exception as exc:
@@ -2189,6 +2284,8 @@ class ModelMoveHandler:
result = await self._move_service.move_models_bulk(
file_paths, target_path, use_default_paths=use_default_paths
)
if result.get("success"):
_broadcast_models_changed()
return web.json_response(result)
except Exception as exc:
self._logger.error("Error moving models in bulk: %s", exc, exc_info=True)
@@ -2234,6 +2331,7 @@ class ModelAutoOrganizeHandler:
progress_callback=self._progress_callback,
exclusion_patterns=exclusion_patterns,
)
_broadcast_models_changed()
return web.json_response(result.to_dict())
except AutoOrganizeInProgressError:
return web.json_response(
@@ -2337,8 +2435,8 @@ class ModelUpdateHandler:
self._logger.error("Failed to fetch license info: %s", exc, exc_info=True)
return web.json_response({"success": False, "error": str(exc)}, status=500)
updated: List[Dict[str, str]] = []
errors: List[Dict[str, str]] = []
updated: List[Dict[str, Any]] = []
errors: List[Dict[str, Any]] = []
for model_id in model_ids:
license_payload = license_map.get(model_id)
if not license_payload:
@@ -2351,6 +2449,7 @@ class ModelUpdateHandler:
model_section = civitai_section.get("model")
if not isinstance(model_section, Mapping):
model_section = {}
model_section = dict(model_section)
model_section.update(resolved_payload)
civitai_section["model"] = model_section
metadata_payload["civitai"] = civitai_section
@@ -2366,7 +2465,7 @@ class ModelUpdateHandler:
)
errors.append({"filePath": metadata_path, "error": str(exc)})
response_payload = {"success": True, "updated": updated}
response_payload: Dict[str, Any] = {"success": True, "updated": updated}
missing_model_ids = [mid for mid in model_ids if mid not in license_map]
if missing_model_ids:
response_payload["missingModelIds"] = missing_model_ids
@@ -2715,6 +2814,7 @@ class ModelUpdateHandler:
civitai_payload = metadata_payload.get("civitai")
if not isinstance(civitai_payload, Mapping):
civitai_payload = {}
civitai_payload = dict(civitai_payload)
model_payload = civitai_payload.get("model")
if not isinstance(model_payload, Mapping):
@@ -2759,7 +2859,7 @@ class ModelUpdateHandler:
return aggregated
def _extract_target_model_ids(self, payload: Dict) -> Optional[List[int]]:
def _extract_target_model_ids(self, payload: Dict[str, Any]) -> Optional[List[int]]:
if not isinstance(payload, Mapping):
return None
@@ -2787,7 +2887,7 @@ class ModelUpdateHandler:
return {}
to_dict = getattr(metadata, "to_dict", None)
if callable(to_dict):
if to_dict:
try:
return to_dict()
except Exception:
@@ -2798,7 +2898,7 @@ class ModelUpdateHandler:
return {}
async def _read_json(self, request: web.Request) -> Dict:
async def _read_json(self, request: web.Request) -> Dict[str, Any]:
if not request.can_read_body:
return {}
try:
@@ -2830,7 +2930,7 @@ class ModelUpdateHandler:
record,
*,
version_context: Optional[Dict[int, Dict[str, Any]]] = None,
) -> Dict:
) -> Dict[str, Any]:
context = version_context or {}
# Check user setting for hiding early access versions
hide_early_access = False
@@ -2859,7 +2959,7 @@ class ModelUpdateHandler:
@staticmethod
def _serialize_version(
version, context: Optional[Dict[str, Any]]
) -> Dict:
) -> Dict[str, Any]:
context = context or {}
preview_override = context.get("preview_override")
preview_url = (
@@ -0,0 +1,323 @@
"""Handler for the pending-delete undo endpoint.
Restores a staged delete batch (models or recipes) via
``PendingDeleteService.undo`` and then repairs the affected library caches:
the model cache entry is restored from the manifest's ``model_snapshot``
(including the version index and hash index), tag counts are re-incremented,
and the recipe cache is re-populated via ``RecipeScanner.add_recipe``.
The per-type scanner is resolved from the manifest's ``model_type`` page value
through the SAME ServiceRegistry getters the model route registrars use
(lora/checkpoint/embedding) - never a hardcoded lora scanner.
"""
from __future__ import annotations
import inspect
import json
import logging
import os
import re
from typing import Any, Awaitable, Callable, Dict, List, Optional, Set, cast
from aiohttp import web
from ...services.pending_delete_service import get_pending_delete_service
from .model_handlers import _broadcast_models_changed
logger = logging.getLogger(__name__)
# Manifest ``model_type`` page values -> ServiceRegistry scanner getter names.
# The model route registrars resolve per-type scanners via these getters
# (lora_routes / checkpoint_routes / embedding_routes); undo must do the same
# so the CORRECT cache is restored for the deleted model's type.
_MODEL_TYPE_GETTER_NAMES: Dict[str, str] = {
"loras": "get_lora_scanner",
"checkpoints": "get_checkpoint_scanner",
"embeddings": "get_embedding_scanner",
}
# Staged batch ids are ``uuid.uuid4().hex`` (32 lowercase hex chars). The id is
# joined into filesystem paths by ``_find_batch_dir``, so reject anything that
# does not match this exact shape (blocks path-traversal via batch_id).
_BATCH_ID_RE = re.compile(r"^[0-9a-f]{32}$")
class PendingDeleteHandler:
"""Handle undo requests for staged model/recipe deletions."""
def __init__(
self,
*,
service_factory: Callable[[], Awaitable[Any]] = get_pending_delete_service,
scanner_getter: Optional[Callable[[str], Awaitable[Any]]] = None,
recipe_scanner_getter: Optional[Callable[[], Awaitable[Any]]] = None,
) -> None:
self._service_factory: Callable[[], Awaitable[Any]] = service_factory
self._scanner_getter: Callable[[str], Awaitable[Any]] = (
scanner_getter or self._resolve_scanner
)
self._recipe_scanner_getter: Callable[[], Awaitable[Any]] = (
recipe_scanner_getter or self._resolve_recipe_scanner
)
@staticmethod
async def _resolve_scanner(model_type: str) -> Any:
"""Resolve the per-type scanner for a manifest ``model_type``.
The getter is looked up on the ServiceRegistry module namespace at call
time so tests (and the registry stubs) can patch it.
"""
from ...services import service_registry
getter_name = _MODEL_TYPE_GETTER_NAMES.get(model_type)
if getter_name is None:
raise ValueError(f"Unknown model type: {model_type}")
getter = getattr(service_registry.ServiceRegistry, getter_name, None)
if not callable(getter):
raise ValueError(f"No scanner getter for model type: {model_type}")
scanner = await cast(Callable[[], Awaitable[Any]], getter)()
if scanner is None:
raise ValueError(f"No scanner registered for model type: {model_type}")
return scanner
@staticmethod
async def _resolve_recipe_scanner() -> Any:
"""Resolve the recipe scanner via the ServiceRegistry module namespace."""
from ...services import service_registry
getter = getattr(service_registry.ServiceRegistry, "get_recipe_scanner", None)
if not callable(getter):
raise ValueError("Recipe scanner getter unavailable")
scanner = await cast(Callable[[], Awaitable[Any]], getter)()
if scanner is None:
raise ValueError("No recipe scanner registered")
return scanner
async def undo_delete(self, request: web.Request) -> web.Response:
"""Restore a staged batch and its library cache entry.
Body: ``{"batch_id": str}``. On success returns
``{"success": True, "restored": [<original paths>], "kind": kind}``.
Expired/unknown batches and occupied target paths -> 404.
"""
try:
data = await request.json()
except Exception:
return web.json_response(
{"success": False, "error": "Invalid JSON body"}, status=400
)
if not isinstance(data, dict):
return web.json_response(
{"success": False, "error": "Invalid JSON body"}, status=400
)
batch_id = data.get("batch_id")
if not batch_id or not isinstance(batch_id, str):
return web.json_response(
{"success": False, "error": "batch_id is required"}, status=400
)
if not _BATCH_ID_RE.fullmatch(batch_id):
# batch_id is joined into a path by _find_batch_dir - restrict to
# the exact staged-id shape so traversal payloads get 400.
return web.json_response(
{"success": False, "error": "Invalid batch_id"}, status=400
)
service = await self._service_factory()
try:
# Read the manifest BEFORE undo: undo() removes the batch dir.
manifest = await self._read_staged_manifest(service, batch_id)
result = await service.undo(batch_id)
except ValueError as exc:
return web.json_response({"success": False, "error": str(exc)}, status=404)
except Exception as exc:
logger.error("Unexpected error undoing batch %s: %s", batch_id, exc, exc_info=True)
return web.json_response({"success": False, "error": str(exc)}, status=500)
kind = result.get("kind")
try:
if kind == "model":
if manifest is not None:
await self._restore_model_cache(manifest)
else:
# undo() raises when the manifest is missing, so this only
# happens defensively - files are restored regardless.
logger.warning(
"Manifest missing after undo of %s; skipping cache restore",
batch_id,
)
_broadcast_models_changed()
elif kind == "recipe":
# Recipe undo is client-refresh only: re-add to the scanner
# cache, no models_changed broadcast.
if manifest is not None:
await self._restore_recipe_cache(result, manifest)
else:
logger.warning(
"Manifest missing after undo of %s; skipping cache restore",
batch_id,
)
except Exception as exc:
# Files are already restored; only the cache restoration failed.
logger.error(
"Cache restoration failed after undo of %s: %s",
batch_id,
exc,
exc_info=True,
)
return web.json_response({"success": False, "error": str(exc)}, status=500)
return web.json_response(
{
"success": True,
"restored": result.get("restored", []),
"kind": kind,
}
)
@staticmethod
async def _read_staged_manifest(
service: Any, batch_id: str
) -> Optional[Dict[str, Any]]:
"""Locate and read the batch manifest while it still exists on disk."""
batch_dir = await service._find_batch_dir(batch_id)
if not batch_dir:
return None
manifest_path = os.path.join(batch_dir, "manifest.json")
try:
with open(manifest_path, "r", encoding="utf-8") as handle:
payload = json.load(handle)
except (OSError, json.JSONDecodeError) as exc:
logger.debug("Failed to read manifest for batch %s: %s", batch_id, exc)
return None
return payload if isinstance(payload, dict) else None
async def _restore_model_cache(self, manifest: Dict[str, Any]) -> None:
"""Re-add every deleted model's cache entry from the manifest.
Each main-file entry carries the deleted model's ``snapshot`` (added at
stage time), so a merged bulk manifest holds ALL snapshots - undo must
restore every one, not just the top-level winner's. Old-format
manifests without entry snapshots fall back to the top-level
``model_snapshot`` (backward compat / single-delete path).
"""
model_type = manifest.get("model_type")
if not model_type or not isinstance(model_type, str):
raise ValueError(f"Manifest carries no model_type: {manifest.get('batch_id')}")
scanner = await self._scanner_getter(model_type)
# Collect one snapshot per distinct file_path from the entry snapshots.
snapshots: List[Dict[str, Any]] = []
seen: Set[str] = set()
for entry in manifest.get("entries") or []:
snapshot = entry.get("snapshot")
if not isinstance(snapshot, dict):
continue
file_path = snapshot.get("file_path")
if not file_path or not isinstance(file_path, str):
continue
if file_path in seen:
continue
seen.add(file_path)
snapshots.append(snapshot)
if not snapshots:
# Backward compat: pre-F3 manifests carry only the top-level
# model_snapshot (single-delete path, unchanged behavior).
top = manifest.get("model_snapshot")
if isinstance(top, dict) and top.get("file_path"):
snapshots = [top]
else:
logger.warning(
"Manifest %s has no restorable model snapshot; skipping cache restore",
manifest.get("batch_id"),
)
return
cache = await scanner.get_cached_data()
if cache is None:
logger.warning(
"Scanner cache unavailable for %s; skipping cache restore", model_type
)
return
for snapshot in snapshots:
file_path = str(snapshot["file_path"])
# A rescan between delete and undo may have re-added a stale entry
# for this path - drop it so exactly one (the snapshot) remains.
cache.raw_data = [
item for item in cache.raw_data if item.get("file_path") != file_path
]
# Restore tag counts (mirror of the bulk-delete decrement in
# _batch_update_cache_for_deleted_models: undo re-increments).
tags = snapshot.get("tags")
if isinstance(tags, list):
for tag in tags:
if not isinstance(tag, str) or not tag:
continue
scanner._tags_count[tag] = scanner._tags_count.get(tag, 0) + 1
cache.raw_data.append(dict(snapshot))
# Re-register the path in the hash index (add_entry guards a
# missing sha256 internally; still guard defensively here).
sha256 = snapshot.get("sha256") or ""
autov3 = snapshot.get("autov3")
hash_index = getattr(scanner, "_hash_index", None)
if hash_index is not None and sha256 and file_path:
hash_index.add_entry(sha256, file_path, autov3)
# Follow the bulk-delete cache-update pattern ONCE after all entries,
# including the explicit version-index rebuild so the version index
# does not go stale.
cache.rebuild_version_index()
await cache.resort()
scanner.bump_cache_version()
persist = getattr(scanner, "_persist_current_cache", None)
if callable(persist):
result = persist()
if inspect.isawaitable(result):
await result
async def _restore_recipe_cache(
self, result: Dict[str, Any], manifest: Dict[str, Any]
) -> None:
"""Re-add a restored recipe via ``RecipeScanner.add_recipe``.
The recipe JSON embeds the full recipe_data (incl. id/file_path);
``add_recipe`` only READS the ``_json_path_map`` so the forced frontend
refresh self-heals any transient path-map gap.
"""
restored = result.get("restored") or []
json_path = next(
(p for p in restored if isinstance(p, str) and p.endswith(".json")),
None,
)
if not json_path or not os.path.exists(json_path):
# Defensive fallback to the manifest's recipe_snapshot file_path.
snapshot = manifest.get("recipe_snapshot") or {}
fallback = snapshot.get("file_path")
if fallback and os.path.exists(fallback):
json_path = fallback
else:
logger.warning(
"Restored recipe JSON not found in %s; skipping cache restore",
restored,
)
return
try:
with open(json_path, "r", encoding="utf-8") as handle:
recipe_data = json.load(handle)
except (OSError, json.JSONDecodeError) as exc:
logger.warning("Failed to load restored recipe JSON %s: %s", json_path, exc)
return
if not isinstance(recipe_data, dict):
return
recipe_scanner = await self._recipe_scanner_getter()
await recipe_scanner.add_recipe(recipe_data)
__all__ = ["PendingDeleteHandler"]
+314 -54
View File
@@ -10,7 +10,7 @@ import asyncio
import tempfile
from dataclasses import dataclass
from pathlib import Path
from typing import Any, Awaitable, Callable, Dict, List, Mapping, Optional
from typing import Any, Awaitable, Callable, Dict, List, Mapping, Optional, Tuple
from aiohttp import web
@@ -44,6 +44,22 @@ EnsureDependenciesCallable = Callable[[], Awaitable[None]]
RecipeScannerGetter = Callable[[], Any]
CivitaiClientGetter = Callable[[], Any]
# Cap concurrent preview-dimension reads across requests. With a cold LRU
# cache one page can touch up to page_size image files; 16 balances SSD and
# HDD throughput without starving the event loop.
_DIMS_READ_SEMAPHORE = asyncio.Semaphore(16)
async def _read_preview_dims(path: str) -> Optional[Tuple[int, int]]:
"""Read preview dimensions off the event loop under the concurrency cap.
PIL I/O runs in a worker thread so it never blocks the event loop, and the
semaphore bounds how many files are opened at once even when many list
requests land together.
"""
async with _DIMS_READ_SEMAPHORE:
return await asyncio.to_thread(ExifUtils.get_image_dimensions, path)
@dataclass(frozen=True)
class RecipeHandlerSet:
@@ -96,6 +112,11 @@ class RecipeHandlerSet:
"repair_recipe": self.management.repair_recipe,
"repair_recipes_bulk": self.management.repair_recipes_bulk,
"get_repair_progress": self.management.get_repair_progress,
"rematch_recipes": self.management.rematch_recipes,
"cancel_rematch": self.management.cancel_rematch,
"rematch_recipe": self.management.rematch_recipe,
"rematch_recipes_bulk": self.management.rematch_recipes_bulk,
"get_rematch_progress": self.management.get_rematch_progress,
"start_batch_import": self.batch_import.start_batch_import,
"get_batch_import_progress": self.batch_import.get_batch_import_progress,
"cancel_batch_import": self.batch_import.cancel_batch_import,
@@ -246,7 +267,8 @@ class RecipeListingHandler:
recursive=recursive,
)
for item in result.get("items", []):
items = result.get("items", [])
for item in items:
file_path = item.get("file_path")
if file_path:
item["file_url"] = self.format_recipe_file_url(file_path)
@@ -255,6 +277,26 @@ class RecipeListingHandler:
item.setdefault("loras", [])
item.setdefault("base_model", "")
# Batch preview dimension reads with asyncio.gather. The previous
# loop awaited asyncio.to_thread once per item, so a page_size=100
# request submitted 100 sequential thread calls (50-300ms cold-page
# latency). gather runs them concurrently while the semaphore caps
# disk opens; dimensions stay omitted (not null) when a preview has
# no readable size (video, missing file).
to_read = [
(i, item.get("file_path"))
for i, item in enumerate(items)
if item.get("file_path")
]
if to_read:
dims_list = await asyncio.gather(
*(_read_preview_dims(path) for _, path in to_read)
)
for (idx, _), dims in zip(to_read, dims_list):
if dims:
item = items[idx]
item["width"], item["height"] = dims
return web.json_response(result)
except Exception as exc:
self._logger.error("Error retrieving recipes: %s", exc, exc_info=True)
@@ -538,7 +580,12 @@ class RecipeQueryHandler:
if recipe_scanner is None:
raise RuntimeError("Recipe scanner unavailable")
fingerprint_groups = await recipe_scanner.find_all_duplicate_recipes()
include_prompt = (
request.query.get("include_prompt", "false").lower() in ("1", "true")
)
fingerprint_groups = await recipe_scanner.find_all_duplicate_recipes(
include_prompt=include_prompt
)
url_groups = await recipe_scanner.find_duplicate_recipes_by_source()
response_data = []
@@ -571,6 +618,7 @@ class RecipeQueryHandler:
response_data.append(
{
"type": "fingerprint",
"key": f"g-{len(response_data) + 1}",
"fingerprint": fingerprint,
"count": len(recipes),
"recipes": recipes,
@@ -606,6 +654,7 @@ class RecipeQueryHandler:
response_data.append(
{
"type": "source_path",
"key": f"g-{len(response_data) + 1}",
"fingerprint": url,
"count": len(recipes),
"recipes": recipes,
@@ -850,6 +899,159 @@ class RecipeManagementHandler:
self._logger.error("Error repairing single recipe: %s", exc, exc_info=True)
return web.json_response({"success": False, "error": str(exc)}, status=500)
async def rematch_recipes(self, request: web.Request) -> web.Response:
try:
await self._ensure_dependencies_ready()
recipe_scanner = self._recipe_scanner_getter()
if recipe_scanner is None:
return web.json_response(
{"success": False, "error": "Recipe scanner unavailable"},
status=503,
)
# Mutual exclusion: a global rematch cannot start while a rematch
# OR a repair is already running — both mutate recipes under the
# same mutation lock.
if (
self._ws_manager.is_recipe_rematch_running()
or self._ws_manager.is_recipe_repair_running()
):
return web.json_response(
{"success": False, "error": "Recipe rematch already in progress"},
status=409,
)
recipe_scanner.reset_cancellation()
async def progress_callback(data):
await self._ws_manager.broadcast_recipe_rematch_progress(data)
# Run in background to avoid timeout
async def run_rematch():
try:
await recipe_scanner.rematch_all_recipes(
progress_callback=progress_callback
)
except Exception as e:
self._logger.error(
f"Error in recipe rematch task: {e}", exc_info=True
)
await self._ws_manager.broadcast_recipe_rematch_progress(
{"status": "error", "error": str(e)}
)
finally:
# Keep the final status for a while so the UI can see it
await asyncio.sleep(5)
self._ws_manager.cleanup_recipe_rematch_progress()
asyncio.create_task(run_rematch())
return web.json_response(
{"success": True, "message": "Recipe rematch started"}
)
except Exception as exc:
self._logger.error("Error starting recipe rematch: %s", exc, exc_info=True)
return web.json_response({"success": False, "error": str(exc)}, status=500)
async def cancel_rematch(self, request: web.Request) -> web.Response:
try:
await self._ensure_dependencies_ready()
recipe_scanner = self._recipe_scanner_getter()
if recipe_scanner is None:
return web.json_response(
{"success": False, "error": "Recipe scanner unavailable"},
status=503,
)
recipe_scanner.cancel_task()
return web.json_response(
{"success": True, "message": "Cancellation requested"}
)
except Exception as exc:
self._logger.error("Error cancelling recipe rematch: %s", exc, exc_info=True)
return web.json_response({"success": False, "error": str(exc)}, status=500)
async def rematch_recipes_bulk(self, request: web.Request) -> web.Response:
"""Rematch deleted resources for multiple recipes by their IDs.
Accepts a JSON body with a "recipe_ids" array. The per-recipe loop is
delegated to the scanner's rematch_recipes_bulk; this handler only
parses the request and returns the scanner's summary.
"""
try:
await self._ensure_dependencies_ready()
recipe_scanner = self._recipe_scanner_getter()
if recipe_scanner is None:
return web.json_response(
{"success": False, "error": "Recipe scanner unavailable"},
status=503,
)
# A bulk rematch must not queue behind a running global rematch's
# mutation lock.
if self._ws_manager.is_recipe_rematch_running():
return web.json_response(
{"success": False, "error": "Recipe rematch already in progress"},
status=409,
)
data = await request.json()
recipe_ids = data.get("recipe_ids", [])
if not recipe_ids:
return web.json_response(
{"success": False, "error": "recipe_ids are required"},
status=400,
)
result = await recipe_scanner.rematch_recipes_bulk(recipe_ids)
return web.json_response(result)
except Exception as exc:
self._logger.error(
"Error performing bulk rematch: %s", exc, exc_info=True
)
return web.json_response(
{"success": False, "error": str(exc)}, status=500
)
async def rematch_recipe(self, request: web.Request) -> web.Response:
try:
await self._ensure_dependencies_ready()
recipe_scanner = self._recipe_scanner_getter()
if recipe_scanner is None:
return web.json_response(
{"success": False, "error": "Recipe scanner unavailable"},
status=503,
)
# Reject per-recipe rematches while a global run is in progress so
# they do not queue behind the mutation lock.
if self._ws_manager.is_recipe_rematch_running():
return web.json_response(
{"success": False, "error": "Recipe rematch already in progress"},
status=409,
)
recipe_id = request.match_info["recipe_id"]
result = await recipe_scanner.rematch_recipe_by_id(recipe_id)
return web.json_response(result)
except RecipeNotFoundError as exc:
return web.json_response({"success": False, "error": str(exc)}, status=404)
except Exception as exc:
self._logger.error("Error rematching single recipe: %s", exc, exc_info=True)
return web.json_response({"success": False, "error": str(exc)}, status=500)
async def get_rematch_progress(self, request: web.Request) -> web.Response:
try:
progress = self._ws_manager.get_recipe_rematch_progress()
if progress:
return web.json_response({"success": True, "progress": progress})
return web.json_response(
{"success": False, "message": "No rematch in progress"}, status=404
)
except Exception as exc:
self._logger.error("Error getting rematch progress: %s", exc, exc_info=True)
return web.json_response({"success": False, "error": str(exc)}, status=500)
async def reimport_recipe(self, request: web.Request) -> web.Response:
"""Delete a recipe and re-import it from its source URL.
@@ -1045,10 +1247,10 @@ class RecipeManagementHandler:
*,
image_url: str,
name: str,
lora_entries: list,
checkpoint_entry: dict,
gen_params_request: dict,
tags: list,
lora_entries: list[Any],
checkpoint_entry: Dict[str, Any] | None,
gen_params_request: Dict[str, Any] | None,
tags: list[Any],
base_model: str,
source_path: str,
) -> web.Response:
@@ -1081,6 +1283,12 @@ class RecipeManagementHandler:
_original_image_url,
) = await self._download_remote_media(image_url)
# Build a version-cached map of local model hashes to cache items so
# CivitaiApiMetadataParser can skip CivitAI API calls for models that
# exist on disk. Built once and shared by every parse pass below.
local_cache = await recipe_scanner.build_local_hash_cache()
from ...recipes.parsers.civitai_image import CivitaiApiMetadataParser
# Extract embedded EXIF metadata (offloaded to thread pool in this call)
embedded_gen_params = {}
parsed_embedded = None
@@ -1102,9 +1310,16 @@ class RecipeManagementHandler:
)
)
if parser:
parsed_embedded = await parser.parse_metadata(
raw_embedded, recipe_scanner=recipe_scanner
)
if isinstance(parser, CivitaiApiMetadataParser):
parsed_embedded = await parser.parse_metadata(
raw_embedded,
recipe_scanner=recipe_scanner,
local_cache=local_cache,
)
else:
parsed_embedded = await parser.parse_metadata(
raw_embedded, recipe_scanner=recipe_scanner
)
if parsed_embedded and "gen_params" in parsed_embedded:
embedded_gen_params = parsed_embedded["gen_params"]
else:
@@ -1135,9 +1350,16 @@ class RecipeManagementHandler:
civitai_inner_meta
)
if parser:
civitai_parsed = await parser.parse_metadata(
civitai_inner_meta, recipe_scanner=recipe_scanner
)
if isinstance(parser, CivitaiApiMetadataParser):
civitai_parsed = await parser.parse_metadata(
civitai_inner_meta,
recipe_scanner=recipe_scanner,
local_cache=local_cache,
)
else:
civitai_parsed = await parser.parse_metadata(
civitai_inner_meta, recipe_scanner=recipe_scanner
)
if civitai_parsed and "gen_params" in civitai_parsed:
# Merge: API gen_params override EXIF at field level,
# EXIF fills in fields the API doesn't have.
@@ -1641,7 +1863,7 @@ class RecipeManagementHandler:
if not provider:
return ""
version_info = await provider.get_model_version_info(version_id)
version_info = await provider.get_model_version_info(str(version_id))
if isinstance(version_info, tuple):
version_info = version_info[0]
@@ -1761,6 +1983,12 @@ class RecipeManagementHandler:
await self._download_remote_media(image_url)
)
# Build a version-cached map of local model hashes to cache items so
# CivitaiApiMetadataParser can skip CivitAI API calls for models that
# exist on disk. Built once and shared by every parse pass below.
local_cache = await recipe_scanner.build_local_hash_cache()
from ...recipes.parsers.civitai_image import CivitaiApiMetadataParser
# Extract embedded EXIF metadata
embedded_gen_params = {}
parsed_embedded = None
@@ -1782,9 +2010,16 @@ class RecipeManagementHandler:
)
)
if parser:
parsed_embedded = await parser.parse_metadata(
raw_embedded, recipe_scanner=recipe_scanner
)
if isinstance(parser, CivitaiApiMetadataParser):
parsed_embedded = await parser.parse_metadata(
raw_embedded,
recipe_scanner=recipe_scanner,
local_cache=local_cache,
)
else:
parsed_embedded = await parser.parse_metadata(
raw_embedded, recipe_scanner=recipe_scanner
)
if parsed_embedded and "gen_params" in parsed_embedded:
embedded_gen_params = parsed_embedded["gen_params"]
finally:
@@ -1822,9 +2057,16 @@ class RecipeManagementHandler:
)
)
if parser:
parsed_embedded = await parser.parse_metadata(
raw_orig, recipe_scanner=recipe_scanner
)
if isinstance(parser, CivitaiApiMetadataParser):
parsed_embedded = await parser.parse_metadata(
raw_orig,
recipe_scanner=recipe_scanner,
local_cache=local_cache,
)
else:
parsed_embedded = await parser.parse_metadata(
raw_orig, recipe_scanner=recipe_scanner
)
if (
parsed_embedded
and "gen_params" in parsed_embedded
@@ -1858,9 +2100,16 @@ class RecipeManagementHandler:
civitai_inner_meta
)
if parser:
civitai_parsed = await parser.parse_metadata(
civitai_inner_meta, recipe_scanner=recipe_scanner
)
if isinstance(parser, CivitaiApiMetadataParser):
civitai_parsed = await parser.parse_metadata(
civitai_inner_meta,
recipe_scanner=recipe_scanner,
local_cache=local_cache,
)
else:
civitai_parsed = await parser.parse_metadata(
civitai_inner_meta, recipe_scanner=recipe_scanner
)
if civitai_parsed and "gen_params" in civitai_parsed:
# Merge: API gen_params override EXIF at field level,
# EXIF fills in fields the API doesn't have.
@@ -2072,33 +2321,44 @@ class RecipeManagementHandler:
parsed_input = {**image_data, **inner_meta}
parsed_input.pop("meta", None)
# Build a local cache of {hash cache_item} so the parser can
# skip CivitAI API calls for models that exist on disk.
local_cache: Dict[str, Dict[str, Any]] = {}
lora_scanner = getattr(recipe_scanner, "_lora_scanner", None)
if lora_scanner and model_hash:
try:
parent_cache_data = await lora_scanner.get_cached_data()
for item in getattr(parent_cache_data, "raw_data", []):
if item.get("sha256", "").lower() == model_hash.lower():
local_cache[model_hash.lower()] = item
# Compute AutoV3 so the parser can also match on
# that hash type (CivitAI metadata resources use
# AutoV3).
file_path = item.get("file_path")
if file_path and os.path.exists(file_path):
try:
from ...utils.file_utils import (
calculate_autov3,
)
autov3 = calculate_autov3(file_path)
if autov3:
local_cache[autov3.lower()] = item
except Exception:
pass
break
except Exception:
pass
# Build the shared local hash cache so the parser can skip CivitAI
# API calls for models that exist on disk.
local_cache: Dict[str, Dict[str, Any]] = (
await recipe_scanner.build_local_hash_cache()
)
# Bounded supplement for un-backfilled parents. The shared builder
# never computes autov3; when the parent model exists on disk but
# its cached entry has no stored AutoV3, compute it for that single
# file and register the AutoV3 key so the parser can also match on
# that hash type (CivitAI metadata resources use AutoV3). This runs
# whenever the parent is found with an empty autov3, independent of
# whether the sha256 key is already present in the shared cache.
if model_hash:
lora_scanner = getattr(recipe_scanner, "_lora_scanner", None)
if lora_scanner:
try:
parent_cache_data = await lora_scanner.get_cached_data()
for item in getattr(parent_cache_data, "raw_data", []):
if item.get("sha256", "").lower() == model_hash.lower():
autov3 = (item.get("autov3") or "").lower()
if not autov3:
file_path = item.get("file_path")
if file_path and os.path.exists(file_path):
try:
from ...utils.file_utils import (
calculate_autov3,
)
autov3 = (
calculate_autov3(file_path) or ""
).lower()
except Exception:
pass
if autov3:
local_cache[autov3] = item
break
except Exception:
pass
parser = self._analysis_service._recipe_parser_factory.create_parser(
parsed_input
@@ -2130,10 +2390,10 @@ class RecipeManagementHandler:
parent_model_id: int | None = None
parent_version_name: str | None = None
parent_model_name: str | None = None
# Prefer sha256 key; fall back to any cached entry.
# Resolve the parent strictly by its sha256 key. There is no
# arbitrary fallback: with a full-library cache, picking any entry
# would corrupt the isDeleted reconciliation below.
parent_item = local_cache.get(model_hash.lower()) if model_hash else None
if parent_item is None and local_cache:
parent_item = next(iter(local_cache.values()))
if parent_item:
civ = parent_item.get("civitai") or {}
if isinstance(civ, dict):
@@ -2349,7 +2609,7 @@ class RecipeAnalysisHandler:
content_type = request.headers.get("Content-Type", "")
if "multipart/form-data" in content_type:
reader = await request.multipart()
field = await reader.next()
field: Any = await reader.next()
if field is None or field.name != "image":
raise RecipeValidationError("No image field found")
image_chunks = bytearray()
+6 -71
View File
@@ -1,8 +1,8 @@
import asyncio
import logging
from aiohttp import web
from typing import Dict
from server import PromptServer # type: ignore
from typing import Any, Dict
from server import PromptServer # pyright: ignore[reportMissingImports]
from .base_model_routes import BaseModelRoutes
from .model_route_registrar import ModelRouteRegistrar
@@ -31,13 +31,13 @@ class LoraRoutes(BaseModelRoutes):
# Attach service dependencies
self.attach_service(self.service)
def setup_routes(self, app: web.Application):
def setup_routes(self, app: web.Application, prefix: str = "loras"):
"""Setup LoRA routes"""
# Schedule service initialization on app startup
app.on_startup.append(lambda _: self.initialize_services())
# Setup common routes with 'loras' prefix (includes page route)
super().setup_routes(app, "loras")
super().setup_routes(app, prefix)
def setup_specific_routes(self, registrar: ModelRouteRegistrar, prefix: str):
"""Setup LoRA-specific routes"""
@@ -73,7 +73,7 @@ class LoraRoutes(BaseModelRoutes):
"POST", "/api/lm/{prefix}/get_trigger_words", prefix, self.get_trigger_words
)
def _parse_specific_params(self, request: web.Request) -> Dict:
def _parse_specific_params(self, request: web.Request) -> Dict[str, Any]:
"""Parse LoRA-specific parameters"""
params = {}
@@ -119,25 +119,6 @@ class LoraRoutes(BaseModelRoutes):
logger.error(f"Error getting letter counts: {e}")
return web.json_response({"success": False, "error": str(e)}, status=500)
async def get_lora_notes(self, request: web.Request) -> web.Response:
"""Get notes for a specific LoRA file"""
try:
lora_name = request.query.get("name")
if not lora_name:
return web.Response(text="Lora file name is required", status=400)
notes = await self.service.get_lora_notes(lora_name)
if notes is not None:
return web.json_response({"success": True, "notes": notes})
else:
return web.json_response(
{"success": False, "error": "LoRA not found in cache"}, status=404
)
except Exception as e:
logger.error(f"Error getting lora notes: {e}", exc_info=True)
return web.json_response({"success": False, "error": str(e)}, status=500)
async def get_lora_trigger_words(self, request: web.Request) -> web.Response:
"""Get trigger words for a specific LoRA file"""
try:
@@ -168,52 +149,6 @@ class LoraRoutes(BaseModelRoutes):
logger.error(f"Error getting lora usage tips by path: {e}", exc_info=True)
return web.json_response({"success": False, "error": str(e)}, status=500)
async def get_lora_preview_url(self, request: web.Request) -> web.Response:
"""Get the static preview URL for a LoRA file"""
try:
lora_name = request.query.get("name")
if not lora_name:
return web.Response(text="Lora file name is required", status=400)
preview_url = await self.service.get_lora_preview_url(lora_name)
if preview_url:
return web.json_response({"success": True, "preview_url": preview_url})
else:
return web.json_response(
{
"success": False,
"error": "No preview URL found for the specified lora",
},
status=404,
)
except Exception as e:
logger.error(f"Error getting lora preview URL: {e}", exc_info=True)
return web.json_response({"success": False, "error": str(e)}, status=500)
async def get_lora_civitai_url(self, request: web.Request) -> web.Response:
"""Get the Civitai URL for a LoRA file"""
try:
lora_name = request.query.get("name")
if not lora_name:
return web.Response(text="Lora file name is required", status=400)
result = await self.service.get_lora_civitai_url(lora_name)
if result["civitai_url"]:
return web.json_response({"success": True, **result})
else:
return web.json_response(
{
"success": False,
"error": "No Civitai data found for the specified lora",
},
status=404,
)
except Exception as e:
logger.error(f"Error getting lora Civitai URL: {e}", exc_info=True)
return web.json_response({"success": False, "error": str(e)}, status=500)
async def get_random_loras(self, request: web.Request) -> web.Response:
"""Get random LoRAs based on filters and strength ranges"""
try:
@@ -337,7 +272,7 @@ class LoraRoutes(BaseModelRoutes):
graph_identifier = entry.get("graph_id")
try:
parsed_node_id = int(node_identifier)
parsed_node_id = int(node_identifier) # pyright: ignore[reportArgumentType]
except (TypeError, ValueError):
parsed_node_id = node_identifier
+2 -2
View File
@@ -5,7 +5,7 @@ miscellaneous endpoints share a consistent registration flow.
"""
from dataclasses import dataclass
from typing import Callable, Iterable, Mapping
from typing import Any, Callable, Iterable, Mapping
from aiohttp import web
@@ -147,7 +147,7 @@ class MiscRouteRegistrar:
handler_lookup[definition.handler_name],
)
def _bind(self, method: str, path: str, handler: Callable) -> None:
def _bind(self, method: str, path: str, handler: Callable[..., Any]) -> None:
add_method_name = self._METHOD_MAP[method.upper()]
add_method = getattr(self._app.router, add_method_name)
add_method(path, handler)
+1 -1
View File
@@ -7,7 +7,7 @@ import os
from typing import Awaitable, Callable, Mapping
from aiohttp import web
from server import PromptServer # type: ignore
from server import PromptServer # pyright: ignore[reportMissingImports]
from ..services.metadata_service import (
get_metadata_archive_manager,
+4 -4
View File
@@ -3,7 +3,7 @@
from __future__ import annotations
from dataclasses import dataclass
from typing import Callable, Iterable, Mapping
from typing import Any, Callable, Iterable, Mapping
from aiohttp import web
@@ -174,15 +174,15 @@ class ModelRouteRegistrar:
handler_lookup[definition.handler_name],
)
def add_route(self, method: str, path: str, handler: Callable) -> None:
def add_route(self, method: str, path: str, handler: Callable[..., Any]) -> None:
self._bind_route(method, path, handler)
def add_prefixed_route(
self, method: str, path_template: str, prefix: str, handler: Callable
self, method: str, path_template: str, prefix: str, handler: Callable[..., Any]
) -> None:
self._bind_route(method, path_template.replace("{prefix}", prefix), handler)
def _bind_route(self, method: str, path: str, handler: Callable) -> None:
def _bind_route(self, method: str, path: str, handler: Callable[..., Any]) -> None:
add_method_name = self._METHOD_MAP[method.upper()]
add_method = getattr(self._app.router, add_method_name)
add_method(path, handler)
+25
View File
@@ -0,0 +1,25 @@
"""Route controller for the pending-delete undo endpoint."""
from __future__ import annotations
from aiohttp import web
from .handlers.pending_delete_handler import PendingDeleteHandler
class PendingDeleteRoutes:
"""Shared route controller mirroring MiscRoutes/UpdateRoutes.
Registered ONCE per mode (py/lora_manager.py, standalone.py); NEVER through
the per-model-type ModelRouteRegistrar, which is instantiated per model
type and would register this non-prefixed route three times.
"""
@staticmethod
def setup_routes(app: web.Application) -> None:
"""Register the shared undo-delete endpoint."""
handler = PendingDeleteHandler()
_ = app.router.add_post("/api/lm/undo-delete", handler.undo_delete)
__all__ = ["PendingDeleteRoutes"]
+7 -2
View File
@@ -3,7 +3,7 @@
from __future__ import annotations
from dataclasses import dataclass
from typing import Callable, Mapping
from typing import Any, Callable, Mapping
from aiohttp import web
@@ -61,6 +61,11 @@ ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
RouteDefinition("POST", "/api/lm/recipe/{recipe_id}/repair", "repair_recipe"),
RouteDefinition("POST", "/api/lm/recipes/repair-bulk", "repair_recipes_bulk"),
RouteDefinition("GET", "/api/lm/recipes/repair-progress", "get_repair_progress"),
RouteDefinition("POST", "/api/lm/recipes/rematch", "rematch_recipes"),
RouteDefinition("POST", "/api/lm/recipes/rematch-bulk", "rematch_recipes_bulk"),
RouteDefinition("POST", "/api/lm/recipe/{recipe_id}/rematch", "rematch_recipe"),
RouteDefinition("POST", "/api/lm/recipes/cancel-rematch", "cancel_rematch"),
RouteDefinition("GET", "/api/lm/recipes/rematch-progress", "get_rematch_progress"),
RouteDefinition("POST", "/api/lm/recipes/batch-import/start", "start_batch_import"),
RouteDefinition(
"GET", "/api/lm/recipes/batch-import/progress", "get_batch_import_progress"
@@ -105,7 +110,7 @@ class RecipeRouteRegistrar:
handler = handler_lookup[definition.handler_name]
self._bind_route(definition.method, definition.path, handler)
def _bind_route(self, method: str, path: str, handler: Callable) -> None:
def _bind_route(self, method: str, path: str, handler: Callable[..., Any]) -> None:
add_method_name = self._METHOD_MAP[method.upper()]
add_method = getattr(self._app.router, add_method_name)
add_method(path, handler)
+11 -10
View File
@@ -40,10 +40,11 @@ class StatsRoutes:
"""Route handlers for Statistics page and API endpoints"""
def __init__(self):
self.lora_scanner = None
self.checkpoint_scanner = None
self.embedding_scanner = None
self.usage_stats = None
self.lora_scanner: Any = None
self.checkpoint_scanner: Any = None
self.embedding_scanner: Any = None
self.usage_stats: Any = None
self._i18n_filter_added = False
self.template_env = jinja2.Environment(
loader=jinja2.FileSystemLoader(config.templates_path),
autoescape=True
@@ -95,9 +96,9 @@ class StatsRoutes:
server_i18n.set_locale(user_language)
# 为模板环境添加i18n过滤器
if not hasattr(self.template_env, '_i18n_filter_added'):
if not self._i18n_filter_added:
self.template_env.filters['t'] = server_i18n.create_template_filter()
self.template_env._i18n_filter_added = True
self._i18n_filter_added = True
template = self.template_env.get_template('statistics.html')
rendered = template.render(
@@ -549,7 +550,7 @@ class StatsRoutes:
'error': str(e)
}, status=500)
def _count_unused_models(self, models: List[Dict], usage_data: Dict) -> int:
def _count_unused_models(self, models: List[Dict[str, Any]], usage_data: Dict[str, Any]) -> int:
"""Count models that have never been used"""
used_hashes = set(usage_data.keys())
unused_count = 0
@@ -560,7 +561,7 @@ class StatsRoutes:
return unused_count
def _get_top_used_models(self, usage_data: Dict, model_map: Dict, limit: int) -> List[Dict]:
def _get_top_used_models(self, usage_data: Dict[str, Any], model_map: Dict[str, Any], limit: int) -> List[Dict[str, Any]]:
"""Get top used models with their metadata"""
sorted_usage = sorted(usage_data.items(), key=lambda x: x[1].get('total', 0), reverse=True)
@@ -578,7 +579,7 @@ class StatsRoutes:
return top_models
def _get_usage_timeline(self, usage_data: Dict, days: int) -> List[Dict]:
def _get_usage_timeline(self, usage_data: Dict[str, Any], days: int) -> List[Dict[str, Any]]:
"""Get usage timeline for the past N days"""
timeline = []
today = datetime.now()
@@ -614,7 +615,7 @@ class StatsRoutes:
return list(reversed(timeline)) # Oldest to newest
def _format_size(self, size_bytes: int) -> str:
def _format_size(self, size_bytes: float) -> str:
"""Format file size in human readable format"""
for unit in ['B', 'KB', 'MB', 'GB', 'TB']:
if size_bytes < 1024.0:
+16 -13
View File
@@ -6,7 +6,7 @@ import shutil
import tempfile
import asyncio
from aiohttp import web, ClientError
from typing import Dict, List
from typing import Any, Dict, List, cast
from ..utils.settings_paths import ensure_settings_file
from ..services.downloader import get_downloader
@@ -467,9 +467,10 @@ class UpdateRoutes:
if not success:
logger.error(f"Failed to fetch release info: {data}")
return False, ""
zip_url = data.get("zipball_url")
version = data.get("tag_name", "unknown")
release_payload = cast(dict[str, Any], data)
zip_url = release_payload.get("zipball_url", "")
version = release_payload.get("tag_name", "unknown")
# Download ZIP to temporary file
with tempfile.NamedTemporaryFile(delete=False, suffix=".zip") as tmp_zip:
@@ -580,9 +581,10 @@ class UpdateRoutes:
logger.warning("Failed to fetch GitHub commit: %s", data)
return "main", [], 0, ""
commit_sha = data.get('sha', '')[:7]
commit_message = data.get('commit', {}).get('message', '')
commit_date = data.get('commit', {}).get('committer', {}).get('date', '')[:10]
commit_payload = cast(dict[str, Any], data)
commit_sha = commit_payload.get('sha', '')[:7]
commit_message = commit_payload.get('commit', {}).get('message', '')
commit_date = commit_payload.get('commit', {}).get('committer', {}).get('date', '')[:10]
version = f"main-{commit_sha}"
changelog = [commit_message] if commit_message else []
@@ -598,10 +600,11 @@ class UpdateRoutes:
custom_headers={'Accept': 'application/vnd.github+json'}
)
if c_ok:
if c_data.get('status') in ('ahead', 'diverged'):
behind_by = c_data.get('ahead_by', 0)
compare_payload = cast(dict[str, Any], c_data)
if compare_payload.get('status') in ('ahead', 'diverged'):
behind_by = compare_payload.get('ahead_by', 0)
else:
behind_by = c_data.get('behind_by', 0)
behind_by = compare_payload.get('behind_by', 0)
return version, changelog, behind_by, commit_date
@@ -706,7 +709,7 @@ class UpdateRoutes:
logger.info(f"Successfully updated to {new_version}")
return True, new_version
except git.exc.GitError as e:
except git.exc.GitError as e: # pyright: ignore[reportAttributeAccessIssue]
logger.error(f"Git error during update: {e}")
return False, ""
except Exception as e:
@@ -767,7 +770,7 @@ class UpdateRoutes:
return git_info
@staticmethod
async def _get_remote_version() -> tuple[str, List[str], List[Dict]]:
async def _get_remote_version() -> tuple[str, List[str], List[Dict[str, Any]]]:
"""
Fetch remote version from GitHub
Returns:
@@ -789,7 +792,7 @@ class UpdateRoutes:
# Parse releases
releases = []
for i, release in enumerate(data):
for i, release in enumerate(cast(list[dict[str, Any]], data)):
version = release.get('tag_name', '')
if not version.startswith('v'):
version = f"v{version}"
+1 -1
View File
@@ -117,7 +117,7 @@ def _render_prompt(template: str, variables: Dict[str, Any]) -> str:
Uses simple regex substitution no Jinja2 dependency needed.
"""
def replace(match: re.Match) -> str:
def replace(match: re.Match[str]) -> str:
key = match.group(1).strip()
value = variables.get(key, "")
if isinstance(value, (dict, list)):
+1 -1
View File
@@ -295,7 +295,7 @@ class PostProcessor:
normalises every tag to lowercase for case-insensitive dedup.
"""
merged: List[str] = []
seen: set = set()
seen: set[str] = set()
for tag in list(existing) + list(new):
t = tag.strip().lower()
if t and t not in seen:
+1 -1
View File
@@ -49,7 +49,7 @@ _FRONTMATTER_RE = re.compile(
)
def _parse_skill_file(path: Path) -> tuple[dict, str]:
def _parse_skill_file(path: Path) -> tuple[dict[str, Any], str]:
"""Read a prompt definition file (``prompt.md`` or legacy ``SKILL.md``) and
return (frontmatter_dict, body_text).
@@ -9,7 +9,7 @@ from __future__ import annotations
import html as html_module
import re
from typing import List, Tuple
from typing import Any, List, Tuple
_REPO_URL_PATTERN = re.compile(r"https?://huggingface\.co/([^/]+/[^/]+)")
@@ -18,10 +18,10 @@ _REPO_URL_PATTERN = re.compile(r"https?://huggingface\.co/([^/]+/[^/]+)")
def extract_simple_markdown_images(
markdown_text: str,
repo: str,
existing_urls: set | None = None,
existing_urls: set[str] | None = None,
default_width: int = 512,
default_height: int = 512,
) -> list[dict]:
) -> list[dict[str, Any]]:
"""Extract standalone markdown images from the README body.
Matches ``![alt](url)`` on lines that are NOT part of a markdown table
@@ -36,8 +36,8 @@ def extract_simple_markdown_images(
return []
base_url = f"https://huggingface.co/{repo}/resolve/main"
images: list[dict] = []
seen_urls: set = set(existing_urls) if existing_urls else set()
images: list[dict[str, Any]] = []
seen_urls: set[str] = set(existing_urls) if existing_urls else set()
# Collect lines that are NOT inside fenced code blocks
lines = markdown_text.split("\n")
@@ -86,10 +86,10 @@ def extract_simple_markdown_images(
def extract_html_img_tags(
markdown_text: str,
repo: str,
existing_urls: set | None = None,
existing_urls: set[str] | None = None,
default_width: int = 512,
default_height: int = 512,
) -> list[dict]:
) -> list[dict[str, Any]]:
"""Extract image URLs from HTML ``<img src=\"...\">`` tags in the README.
Many HF collection repos (e.g. ``deadman44/Z-Image_LoRA``) use raw HTML
@@ -103,8 +103,8 @@ def extract_html_img_tags(
return []
base_url = f"https://huggingface.co/{repo}/resolve/main"
images: list[dict] = []
seen_urls: set = set(existing_urls) if existing_urls else set()
images: list[dict[str, Any]] = []
seen_urls: set[str] = set(existing_urls) if existing_urls else set()
for m in re.finditer(
r'<img\s[^>]*src=\"([^\"]+)\"',
@@ -175,7 +175,7 @@ def extract_gallery_images(
repo: str,
default_width: int = 512,
default_height: int = 512,
) -> List[dict]:
) -> List[dict[str, Any]]:
"""Extract widget/gallery images from the YAML frontmatter of a HF README.
Args:
@@ -196,7 +196,7 @@ def extract_gallery_images(
if not frontmatter:
return []
images: List[dict] = []
images: List[dict[str, Any]] = []
base_url = f"https://huggingface.co/{repo}/resolve/main"
w = default_width or 512
h = default_height or 512
@@ -258,7 +258,7 @@ def extract_gallery_images(
text = raw_text
if url:
image: dict = {
image: dict[str, Any] = {
"url": url,
"type": "image",
"nsfwLevel": 0,
@@ -276,10 +276,10 @@ def extract_gallery_images(
def extract_gallery_table_images(
markdown_text: str,
repo: str,
existing_urls: set | None = None,
existing_urls: set[str] | None = None,
default_width: int = 512,
default_height: int = 512,
) -> list[dict]:
) -> list[dict[str, Any]]:
"""Extract images from ``| Preview | Prompt |`` markdown gallery tables.
Many HF READMEs include a sample-gallery table in the body (outside
@@ -295,8 +295,8 @@ def extract_gallery_table_images(
return []
base_url = f"https://huggingface.co/{repo}/resolve/main"
images: list[dict] = []
seen_urls: set = set(existing_urls) if existing_urls else set()
images: list[dict[str, Any]] = []
seen_urls: set[str] = set(existing_urls) if existing_urls else set()
lines = markdown_text.split("\n")
n = len(lines)
i = 0
@@ -514,7 +514,7 @@ def _strip_standalone_images(text: str) -> str:
URL was stripped entirely, making it impossible for the LLM to return
a ``preview_url`` for repos that use HTML ``<img>`` tags exclusively.
"""
def _img_to_md(match: re.Match) -> str:
def _img_to_md(match: re.Match[str]) -> str:
"""Convert an ``<img>`` tag to markdown image syntax ``![alt](src)``."""
tag = match.group(0)
src_m = re.search(r'src="([^"]+)"', tag) or re.search(r"src='([^']+)'", tag)
@@ -942,7 +942,7 @@ def _strip_badge_images(text: str) -> str:
"twitter", "colab", "gradio", "space",
)
def _should_remove(m: re.Match) -> str:
def _should_remove(m: re.Match[str]) -> str:
alt = (m.group(1) or "").lower()
for kw in badge_keywords:
if kw in alt:
+146 -18
View File
@@ -1,3 +1,7 @@
# pyright: reportImportCycles=false
# Lazy (function-local) imports still count as static edges in basedpyright's
# reportImportCycles, so the ServiceRegistry singleton pattern necessarily forms
# import cycles. Breaking them would require an architectural refactor.
from __future__ import annotations
import asyncio
@@ -7,6 +11,7 @@ import os
import secrets
import shutil
import socket
import time
from dataclasses import dataclass
from datetime import datetime
from pathlib import Path
@@ -20,10 +25,43 @@ from .settings_manager import get_settings_manager
logger = logging.getLogger(__name__)
# Maximum times the download poll loop will re-schedule a transfer after it
# is lost (daemon restart / RPC outage) before failing the download.
MAX_TRANSFER_RECOVERY_ATTEMPTS = 2
# stderr lines matching these markers indicate a disk write failure inside
# aria2 (piece cache flush or raw file write). They are promoted to INFO so
# the root cause (disk full, permission denied, file locked by another
# process, ...) is visible in the default logs; all other stderr output stays
# at DEBUG to avoid noise.
_DISK_WRITE_ERROR_MARKERS = (
# aria2 wrapper messages (write disk cache flush path)
"write disk cache flush failure",
"error when trying to flush write cache",
"failed to write into the file",
"failed to open the file",
"failed to seek the file",
# underlying root-cause phrases reported via "cause: ..." (POSIX + Windows)
"no space left on device",
"not enough space on the disk",
"input/output error",
"permission denied",
"access is denied",
"disk quota exceeded",
"used by another process",
"sharing violation",
)
# Minimum interval between INFO-level reports of the same stderr line so a
# repeated failure (e.g. aria2 retrying against a full disk) does not spam
# the log.
STDERR_ERROR_REPORT_INTERVAL = 60.0
def _try_certifi_ca_path() -> str | None:
"""Return the certifi CA bundle path if available, else None."""
try:
import certifi # type: ignore[import-untyped]
import certifi # pyright: ignore[reportMissingTypeStubs]
path = certifi.where()
if os.path.isfile(path):
@@ -81,10 +119,12 @@ class Aria2Downloader:
self._rpc_session: Optional[aiohttp.ClientSession] = None
self._rpc_session_lock = asyncio.Lock()
self._process_lock = asyncio.Lock()
self._register_lock = asyncio.Lock()
self._transfers: Dict[str, Aria2Transfer] = {}
self._poll_interval = 0.5
self._state_store = Aria2TransferStateStore()
self._stderr_reader_task: Optional[asyncio.Task] = None
self._stderr_reader_task: Optional[asyncio.Task[Any]] = None
self._stderr_error_report: Dict[str, float] = {}
@property
def is_running(self) -> bool:
@@ -99,26 +139,58 @@ class Aria2Downloader:
progress_callback=None,
headers: Optional[Dict[str, str]] = None,
) -> Tuple[bool, str]:
"""Download a file using aria2 RPC and wait for completion."""
"""Download a file using aria2 RPC and wait for completion.
The poll loop is self-healing: when the in-memory transfer entry
disappears (e.g. another download restarted the daemon and
``close()`` cleared ``_transfers``) or the RPC becomes unreachable,
the transfer is re-scheduled with ``continue=true`` so the download
resumes from the on-disk ``.aria2`` control file. Recovery is bounded
by ``MAX_TRANSFER_RECOVERY_ATTEMPTS``.
"""
await self._ensure_process()
save_path = os.path.abspath(save_path)
transfer = self._transfers.get(download_id)
if transfer is None or os.path.abspath(transfer.save_path) != save_path:
gid = await self._schedule_download(
url,
save_path,
download_id=download_id,
headers=headers,
)
transfer = Aria2Transfer(gid=gid, save_path=save_path)
self._transfers[download_id] = transfer
async with self._register_lock:
transfer = self._transfers.get(download_id)
if transfer is None or os.path.abspath(transfer.save_path) != save_path:
transfer = await self._register_transfer(
url,
save_path,
download_id=download_id,
headers=headers,
)
recovery_attempts = 0
try:
while True:
status = await self._get_status_with_retry(download_id)
try:
status = await self._get_status_with_retry(download_id)
except Aria2Error:
status = None
if status is None:
return False, "aria2 download not found"
if recovery_attempts >= MAX_TRANSFER_RECOVERY_ATTEMPTS:
return False, "aria2 download not found"
recovery_attempts += 1
logger.warning(
"aria2 transfer %s lost; re-scheduling with resume "
"(attempt %d/%d)",
download_id,
recovery_attempts,
MAX_TRANSFER_RECOVERY_ATTEMPTS,
)
await asyncio.sleep(1.0)
await self._ensure_process()
async with self._register_lock:
transfer = await self._register_transfer(
url,
save_path,
download_id=download_id,
headers=headers,
)
continue
snapshot = self._build_progress_snapshot(status)
if progress_callback is not None:
@@ -135,7 +207,9 @@ class Aria2Downloader:
await asyncio.sleep(self._poll_interval)
finally:
self._transfers.pop(download_id, None)
current = self._transfers.get(download_id)
if current is not None and current.gid == transfer.gid:
self._transfers.pop(download_id, None)
async def _get_status_with_retry(
self, download_id: str, *, max_retries: int = 4, retry_delay: float = 3.0
@@ -190,7 +264,7 @@ class Aria2Downloader:
download_id,
)
options: Dict[str, str] = {
options: Dict[str, Any] = {
"dir": save_dir,
"out": out_name,
"continue": "true",
@@ -238,6 +312,25 @@ class Aria2Downloader:
)
return gid
async def _register_transfer(
self,
url: str,
save_path: str,
*,
download_id: str,
headers: Optional[Dict[str, str]] = None,
) -> Aria2Transfer:
"""Schedule a download and track it in the in-memory transfer registry."""
gid = await self._schedule_download(
url,
save_path,
download_id=download_id,
headers=headers,
)
transfer = Aria2Transfer(gid=gid, save_path=os.path.abspath(save_path))
self._transfers[download_id] = transfer
return transfer
async def get_status(self, download_id: str) -> Optional[Dict[str, Any]]:
"""Return the raw aria2 status payload for a known download."""
@@ -385,16 +478,51 @@ class Aria2Downloader:
blocks, which freezes the entire ``aria2c`` process including its
RPC handler. This background task reads lines from stderr as they
arrive and forwards them to Python's logger.
Lines that indicate a disk write failure (e.g. the "cause: No space
left on device" line that follows "Write disk cache flush failure")
are promoted to INFO so the root cause is visible without enabling
debug logging; every other line stays at DEBUG to avoid noise.
"""
try:
assert self._process is not None and self._process.stderr is not None
async for line in self._process.stderr:
text = line.decode("utf-8", errors="replace").rstrip()
if text:
logger.debug("aria2 stderr: %s", text)
if self._is_disk_write_error(text):
self._report_stderr_error(text)
else:
logger.debug("aria2 stderr: %s", text)
except Exception:
pass
@staticmethod
def _is_disk_write_error(text: str) -> bool:
lowered = text.lower()
return any(marker in lowered for marker in _DISK_WRITE_ERROR_MARKERS)
def _report_stderr_error(self, text: str) -> None:
"""INFO-log a disk write failure line, rate-limited per line text.
aria2 re-emits the same error chain on every poll/retry while the
underlying condition persists; only the first occurrence within
``STDERR_ERROR_REPORT_INTERVAL`` seconds is promoted to INFO.
"""
now = time.monotonic()
last = self._stderr_error_report.get(text)
if last is not None and now - last < STDERR_ERROR_REPORT_INTERVAL:
logger.debug("aria2 stderr (repeated disk write error): %s", text)
return
# Drop entries older than the window so the map stays bounded even
# during a long disk-full episode (piece indexes change per line).
self._stderr_error_report = {
line: timestamp
for line, timestamp in self._stderr_error_report.items()
if now - timestamp < STDERR_ERROR_REPORT_INTERVAL
}
self._stderr_error_report[text] = now
logger.info("aria2 disk write failure: %s", text)
async def _dispatch_progress(self, callback, snapshot: DownloadProgress) -> None:
try:
result = callback(snapshot, snapshot)
+3 -3
View File
@@ -8,7 +8,7 @@ from filename, base_model, and CivitAI version name — no manual tagging requir
from __future__ import annotations
import re
from typing import Dict, List, Set
from typing import Any, Dict, List, Set
# ── Tag category definitions ──────────────────────────────────────────
# Each category maps a display label to a regex pattern.
@@ -52,7 +52,7 @@ AUTO_TAG_GROUPS = {
DEFAULT_ENABLED_GROUPS = {"mode", "video"}
def _collect_sources(model_data: Dict) -> List[str]:
def _collect_sources(model_data: Dict[str, Any]) -> List[str]:
"""Collect all text sources from model data for tag matching."""
sources: List[str] = []
@@ -73,7 +73,7 @@ def _collect_sources(model_data: Dict) -> List[str]:
return sources
def extract_auto_tags(model_data: Dict) -> List[str]:
def extract_auto_tags(model_data: Dict[str, Any]) -> List[str]:
"""Extract auto-detected tags from model metadata.
Uses a two-layer approach:
+144
View File
@@ -0,0 +1,144 @@
# pyright: reportImportCycles=false
# Lazy (function-local) imports still count as static edges in basedpyright's
# reportImportCycles, so the ServiceRegistry singleton pattern necessarily forms
# import cycles. Breaking them would require an architectural refactor.
"""Backfill the AutoV3 checked state for models loaded from a persisted snapshot.
The SQLite persistent cache predates the AutoV3 feature, so entries hydrated
from it have a NULL ``autov3`` column (the "not checked yet" state). This
service computes the embedded AutoV3 hash for each such model once per
process and persists it through the scanner's single write path
(:meth:`ModelScanner.update_autov3_for_model`), marking every visited row so a
subsequent run finds nothing left to do.
Three-state contract honored here:
- ``NULL`` (sqlite) / absent (dict) = not checked yet backfill computes it
- ``''`` (sqlite/dict) / JSON null = checked, no value available never recompute
- 12-char lowercase hex = value never recompute
"""
from __future__ import annotations
import asyncio
import json
import logging
import os
import threading
from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING: # pragma: no cover - type-check only; runtime imports are local
from .model_scanner import ModelScanner
logger = logging.getLogger(__name__)
def _resolve_autov3(file_path: str) -> str:
"""Resolve the AutoV3 hash for a model file.
Prefers the Civitai AutoV3 reported for the file whose SHA256 matches
(the authoritative value for recipe matching); falls back to the embedded
safetensors header hash. Returns ``''`` when neither is available.
"""
try:
metadata_path = f"{os.path.splitext(file_path)[0]}.metadata.json"
if os.path.exists(metadata_path):
with open(metadata_path, "r", encoding="utf-8") as handle:
payload = json.load(handle)
if isinstance(payload, dict):
from ..utils.models import autov3_from_civitai_files # local import avoids cycles
sha256 = (payload.get("sha256") or "").lower()
civitai_autov3 = autov3_from_civitai_files(payload.get("civitai"), sha256)
if civitai_autov3:
return civitai_autov3
except Exception:
pass
from ..utils.file_utils import calculate_autov3 # local import avoids cycles
return calculate_autov3(file_path) or ""
class Autov3BackfillService:
"""Compute and persist AutoV3 hashes for models missing a checked state."""
_instance: Optional["Autov3BackfillService"] = None
_instance_lock = threading.Lock()
def __init__(self) -> None:
# Re-entrancy guard per model type: scanners for different model types
# initialize concurrently (lora_manager.py), so a global guard would
# silently skip every type but the first to start. Each model type
# runs its own backfill; a duplicate trigger for the same type no-ops.
self._running_types: set[str] = set()
@classmethod
def get_instance(cls) -> "Autov3BackfillService":
"""Return the process-wide singleton instance."""
if cls._instance is None:
with cls._instance_lock:
if cls._instance is None:
cls._instance = cls()
return cls._instance
async def backfill(self, scanner: "ModelScanner") -> int:
"""Compute AutoV3 for every un-checked model of ``scanner.model_type``.
Each candidate file is read once via :func:`~py.utils.file_utils.calculate_autov3`
(cheap: safetensors header only) and the result is persisted through
``scanner.update_autov3_for_model``. Files that no longer exist on
disk are skipped they are intentionally NOT marked, because scanner
cleanup removes the stale row later.
Returns:
The number of models successfully updated. Never raises; on any
failure a warning is logged and ``0`` is returned. A duplicate
trigger for a model type that is already being backfilled returns
``0`` immediately; different model types run concurrently.
"""
model_type = scanner.model_type
if model_type in self._running_types:
return 0
self._running_types.add(model_type)
try:
# Local imports avoid import cycles at module load time.
from .persistent_model_cache import get_persistent_cache
from ..utils.file_utils import calculate_autov3
persistent = getattr(scanner, "_persistent_cache", None) or get_persistent_cache()
paths = persistent.get_models_missing_autov3(model_type)
loop = asyncio.get_running_loop()
count = 0
for path in paths:
# A file that no longer exists must not be marked; scanner
# cleanup removes the stale row later. The existence check and
# hash resolution run in the executor so the loop stays
# responsive to API requests while the backfill iterates a
# large library.
if not await loop.run_in_executor(None, os.path.exists, path):
continue
autov3 = await loop.run_in_executor(None, _resolve_autov3, path)
if await scanner.update_autov3_for_model(model_type, path, autov3):
count += 1
if paths:
logger.info(
"AutoV3 backfill: updated %d/%d models for %s",
count,
len(paths),
model_type,
)
else:
# Steady state after the first run: nothing left to backfill.
logger.debug("AutoV3 backfill: nothing to process for %s", model_type)
return count
except Exception as exc:
logger.warning(
"AutoV3 backfill failed for %s: %s",
getattr(scanner, "model_type", "?"),
exc,
)
return 0
finally:
self._running_types.discard(model_type)
+4
View File
@@ -1,3 +1,7 @@
# pyright: reportImportCycles=false
# Lazy (function-local) imports still count as static edges in basedpyright's
# reportImportCycles, so the ServiceRegistry singleton pattern necessarily forms
# import cycles. Breaking them would require an architectural refactor.
from __future__ import annotations
import asyncio
+146 -67
View File
@@ -2,7 +2,7 @@ from abc import ABC, abstractmethod
import asyncio
import re
import random
from typing import Any, Dict, List, Optional, Type, Union, TYPE_CHECKING
from typing import Any, Awaitable, Dict, List, Optional, Type, Union, TYPE_CHECKING, cast
import logging
import os
import time
@@ -70,24 +70,24 @@ class BaseModelService(ABC):
page: int,
page_size: int,
sort_by: str = "name",
folder: str = None,
folder_include: list = None,
folder_exclude: list = None,
search: str = None,
folder: str | None = None,
folder_include: list[str] | None = None,
folder_exclude: list[str] | None = None,
search: str | None = None,
fuzzy_search: bool = False,
base_models: list = None,
model_types: list = None,
base_models: list[str] | None = None,
model_types: list[str] | None = None,
tags: Optional[Dict[str, str]] = None,
auto_tags: Optional[Dict[str, str]] = None,
search_options: dict = None,
hash_filters: dict = None,
search_options: dict[str, Any] | None = None,
hash_filters: dict[str, Any] | None = None,
favorites_only: bool = False,
update_available_only: bool = False,
credit_required: Optional[bool] = None,
allow_selling_generated_content: Optional[bool] = None,
tag_logic: str = "any",
**kwargs,
) -> Dict:
) -> Dict[str, Any]:
"""Get paginated and filtered model data"""
overall_start = time.perf_counter()
@@ -178,8 +178,8 @@ class BaseModelService(ABC):
ufs = self.settings.get("version_grouping", "same_base")
group_by_base = ufs == "same_base"
model_groups: Dict[Any, List[Dict]] = {}
ungrouped_standalone: List[Dict] = []
model_groups: Dict[Any, List[Dict[str, Any]]] = {}
ungrouped_standalone: List[Dict[str, Any]] = []
for item in sorted_data:
mid = self._extract_group_key(item)
if mid is None:
@@ -249,7 +249,7 @@ class BaseModelService(ABC):
filter_duration = time.perf_counter() - t1
post_filter_count = len(filtered_data)
annotated_for_filter: Optional[List[Dict]] = None
annotated_for_filter: Optional[List[Dict[str, Any]]] = None
t2 = time.perf_counter()
if update_available_only:
annotated_for_filter = await self._annotate_update_flags(filtered_data)
@@ -296,11 +296,11 @@ class BaseModelService(ABC):
page: int,
page_size: int,
sort_by: str = "name",
search: str = None,
search: str | None = None,
fuzzy_search: bool = False,
search_options: dict = None,
search_options: dict[str, Any] | None = None,
**kwargs,
) -> Dict:
) -> Dict[str, Any]:
"""Get paginated excluded model data."""
excluded_paths = list(self.scanner.get_excluded_models())
excluded_entries: List[Dict[str, Any]] = []
@@ -326,7 +326,7 @@ class BaseModelService(ABC):
]
persist_current_cache = getattr(self.scanner, "_persist_current_cache", None)
if callable(persist_current_cache):
await persist_current_cache()
await cast(Awaitable[Any], persist_current_cache())
excluded_entries = self._sort_entries(excluded_entries, sort_by)
@@ -444,39 +444,50 @@ class BaseModelService(ABC):
return entry
async def _apply_hash_filters(
self, data: List[Dict], hash_filters: Dict
) -> List[Dict]:
"""Apply hash-based filtering"""
self, data: List[Dict[str, Any]], hash_filters: Dict[str, Any]
) -> List[Dict[str, Any]]:
"""Apply hash-based filtering (SHA256 and AutoV3)."""
def matches_hash_set(item: Dict[str, Any], hash_set: set[str]) -> bool:
"""Check whether an item matches any hash in the set.
Compares the item's ``sha256`` field and its non-empty ``autov3``
field, both case-insensitively.
"""
if item.get("sha256", "").lower() in hash_set:
return True
autov3 = item.get("autov3", "")
return bool(autov3) and autov3.lower() in hash_set
single_hash = hash_filters.get("single_hash")
multiple_hashes = hash_filters.get("multiple_hashes")
if single_hash:
# Filter by single hash
single_hash = single_hash.lower()
# Filter by single hash (SHA256 or AutoV3)
return [
item for item in data if item.get("sha256", "").lower() == single_hash
item for item in data if matches_hash_set(item, {single_hash.lower()})
]
elif multiple_hashes:
# Filter by multiple hashes
hash_set = set(hash.lower() for hash in multiple_hashes)
return [item for item in data if item.get("sha256", "").lower() in hash_set]
# Filter by multiple hashes (SHA256 or AutoV3)
hash_set = {hash.lower() for hash in multiple_hashes}
return [item for item in data if matches_hash_set(item, hash_set)]
return data
async def _apply_common_filters(
self,
data: List[Dict],
folder: str = None,
folder_include: list = None,
folder_exclude: list = None,
base_models: list = None,
model_types: list = None,
data: List[Dict[str, Any]],
folder: str | None = None,
folder_include: list[str] | None = None,
folder_exclude: list[str] | None = None,
base_models: list[str] | None = None,
model_types: list[str] | None = None,
tags: Optional[Dict[str, str]] = None,
auto_tags: Optional[Dict[str, str]] = None,
favorites_only: bool = False,
search_options: dict = None,
search_options: dict[str, Any] | None = None,
tag_logic: str = "any",
) -> List[Dict]:
) -> List[Dict[str, Any]]:
"""Apply common filters that work across all model types"""
normalized_options = self.search_strategy.normalize_options(search_options)
criteria = FilterCriteria(
@@ -495,24 +506,24 @@ class BaseModelService(ABC):
async def _apply_search_filters(
self,
data: List[Dict],
data: List[Dict[str, Any]],
search: str,
fuzzy_search: bool,
search_options: dict,
) -> List[Dict]:
search_options: dict[str, Any] | None,
) -> List[Dict[str, Any]]:
"""Apply search filtering"""
normalized_options = self.search_strategy.normalize_options(search_options)
return self.search_strategy.apply(
data, search, normalized_options, fuzzy_search
)
async def _apply_specific_filters(self, data: List[Dict], **kwargs) -> List[Dict]:
async def _apply_specific_filters(self, data: List[Dict[str, Any]], **kwargs) -> List[Dict[str, Any]]:
"""Apply model-specific filters - to be overridden by subclasses if needed"""
return data
async def _apply_credit_required_filter(
self, data: List[Dict], credit_required: bool
) -> List[Dict]:
self, data: List[Dict[str, Any]], credit_required: bool
) -> List[Dict[str, Any]]:
"""Apply credit required filtering based on license_flags.
Args:
@@ -542,8 +553,8 @@ class BaseModelService(ABC):
return filtered_data
async def _apply_allow_selling_filter(
self, data: List[Dict], allow_selling: bool
) -> List[Dict]:
self, data: List[Dict[str, Any]], allow_selling: bool
) -> List[Dict[str, Any]]:
"""Apply allow selling generated content filtering based on license_flags.
Args:
@@ -575,8 +586,8 @@ class BaseModelService(ABC):
async def _annotate_update_flags(
self,
items: List[Dict],
) -> List[Dict]:
items: List[Dict[str, Any]],
) -> List[Dict[str, Any]]:
"""Attach an update_available flag to each response item.
Items without a civitai model id default to False.
@@ -591,7 +602,7 @@ class BaseModelService(ABC):
item["update_available"] = False
return annotated
id_to_items: Dict[int, List[Dict]] = {}
id_to_items: Dict[int, List[Dict[str, Any]]] = {}
ordered_ids: List[int] = []
for item in annotated:
model_id = self._extract_model_id(item)
@@ -628,7 +639,7 @@ class BaseModelService(ABC):
record_method = getattr(self.update_service, "get_records_bulk", None)
if callable(record_method):
try:
records = await record_method(self.model_type, ordered_ids)
records = await cast(Awaitable[Any], record_method(self.model_type, ordered_ids))
resolved = {
model_id: record.has_update(hide_early_access=hide_early_access)
for model_id, record in records.items()
@@ -648,11 +659,11 @@ class BaseModelService(ABC):
bulk_method = getattr(self.update_service, "has_updates_bulk", None)
if callable(bulk_method):
try:
resolved = await bulk_method(
resolved = await cast(Awaitable[Any], bulk_method(
self.model_type,
ordered_ids,
hide_early_access=hide_early_access,
)
))
except Exception as exc:
logger.error(
"Failed to resolve update status in bulk for %s models (%s): %s",
@@ -714,7 +725,7 @@ class BaseModelService(ABC):
return annotated
@staticmethod
def _extract_hf_group_key(item: Dict) -> Optional[str]:
def _extract_hf_group_key(item: Dict[str, Any]) -> Optional[str]:
"""Extract `hf:{owner}/{repo}` from item's ``hf_url``, or None."""
hf_url = item.get("hf_url") if isinstance(item, dict) else None
if not hf_url or not isinstance(hf_url, str):
@@ -727,7 +738,7 @@ class BaseModelService(ABC):
return f"hf:{m.group(1)}"
@staticmethod
def _extract_group_key(item: Dict) -> Union[int, str, None]:
def _extract_group_key(item: Dict[str, Any]) -> Union[int, str, None]:
"""Return the group identity key: CivitAI modelId (int) or HF repo (str).
Preference order:
@@ -741,7 +752,7 @@ class BaseModelService(ABC):
return BaseModelService._extract_hf_group_key(item)
@staticmethod
def _extract_model_id(item: Dict) -> Optional[int]:
def _extract_model_id(item: Dict[str, Any]) -> Optional[int]:
civitai = item.get("civitai") if isinstance(item, dict) else None
if not isinstance(civitai, dict):
return None
@@ -754,7 +765,7 @@ class BaseModelService(ABC):
return None
@staticmethod
def _extract_version_id(item: Dict) -> Optional[int]:
def _extract_version_id(item: Dict[str, Any]) -> Optional[int]:
civitai = item.get("civitai") if isinstance(item, dict) else None
if not isinstance(civitai, dict):
return None
@@ -767,7 +778,7 @@ class BaseModelService(ABC):
return None
@staticmethod
def _extract_base_model(item: Dict) -> Optional[str]:
def _extract_base_model(item: Dict[str, Any]) -> Optional[str]:
value = item.get("base_model")
if value is None:
return None
@@ -819,7 +830,7 @@ class BaseModelService(ABC):
return highest_by_base
def _paginate(self, data: List[Dict], page: int, page_size: int) -> Dict:
def _paginate(self, data: List[Dict[str, Any]], page: int, page_size: int) -> Dict[str, Any]:
"""Apply pagination to filtered data"""
total_items = len(data)
start_idx = (page - 1) * page_size
@@ -834,7 +845,7 @@ class BaseModelService(ABC):
}
@abstractmethod
async def format_response(self, model_data: Dict) -> Optional[Dict]:
async def format_response(self, model_data: Dict[str, Any]) -> Optional[Dict[str, Any]]:
"""Format model data for API response - must be implemented by subclasses.
Subclasses should return None for corrupted entries so the handler
@@ -843,17 +854,17 @@ class BaseModelService(ABC):
pass
# Common service methods that delegate to scanner
async def get_top_tags(self, limit: int = 20) -> List[Dict]:
async def get_top_tags(self, limit: int = 20) -> List[Dict[str, Any]]:
"""Get top tags sorted by frequency"""
return await self.scanner.get_top_tags(limit)
async def search_tags(
self, query: str, limit: int = 50
) -> List[Dict]:
) -> List[Dict[str, Any]]:
"""Search tags by substring, sorted by frequency"""
return await self.scanner.search_tags(query, limit)
async def get_base_models(self, limit: int = 20) -> List[Dict]:
async def get_base_models(self, limit: int = 20) -> List[Dict[str, Any]]:
"""Get base models sorted by frequency"""
return await self.scanner.get_base_models(limit)
@@ -920,7 +931,7 @@ class BaseModelService(ABC):
"""Get model root directories"""
return self.scanner.get_model_roots()
def filter_civitai_data(self, data: Dict, minimal: bool = False) -> Dict:
def filter_civitai_data(self, data: Dict[str, Any], minimal: bool = False) -> Dict[str, Any]:
"""Filter relevant fields from CivitAI data"""
if not data:
return {}
@@ -946,7 +957,7 @@ class BaseModelService(ABC):
)
return {k: data[k] for k in fields if k in data}
async def get_folder_tree(self, model_root: str) -> Dict:
async def get_folder_tree(self, model_root: str) -> Dict[str, Any]:
"""Get hierarchical folder tree for a specific model root"""
cache = await self.scanner.get_cached_data()
@@ -975,7 +986,7 @@ class BaseModelService(ABC):
return tree
async def get_unified_folder_tree(self) -> Dict:
async def get_unified_folder_tree(self) -> Dict[str, Any]:
"""Get unified folder tree across all model roots"""
cache = await self.scanner.get_cached_data()
@@ -1004,7 +1015,7 @@ class BaseModelService(ABC):
return unified_tree
async def get_model_notes(self, model_name: str) -> Optional[dict]:
async def get_model_notes(self, model_name: str) -> Optional[dict[str, Any]]:
"""Get notes and file_path for a specific model file.
Supports both simple names (``OWSMianne_ANIMA_V1``) and full-path
@@ -1136,7 +1147,7 @@ class BaseModelService(ABC):
return {"civitai_url": None, "model_id": None, "version_id": None}
async def get_model_metadata(self, file_path: str) -> Optional[Dict]:
async def get_model_metadata(self, file_path: str) -> Optional[Dict[str, Any]]:
"""Load full metadata for a single model.
Listing/search endpoints return lightweight cache entries; this method performs
@@ -1232,7 +1243,7 @@ class BaseModelService(ABC):
return True
@staticmethod
def _relative_path_sort_key(relative_path: str, include_terms: List[str]) -> tuple:
def _relative_path_sort_key(relative_path: str, include_terms: List[str]) -> tuple[int, int, int, str]:
"""Sort paths by how well they satisfy the include tokens.
Sorts based on path without extension for consistent ordering.
@@ -1259,19 +1270,87 @@ class BaseModelService(ABC):
)
async def search_relative_paths(
self, search_term: str, limit: int = 15, offset: int = 0
self,
search_term: str,
limit: int = 15,
offset: int = 0,
*,
folder: Optional[str] = None,
folder_include: Optional[list[str]] = None,
folder_exclude: Optional[list[str]] = None,
base_models: Optional[list[str]] = None,
model_types: Optional[list[str]] = None,
tags: Optional[dict[str, str]] = None,
auto_tags: Optional[dict[str, str]] = None,
tag_logic: str = "any",
credit_required: Optional[bool] = None,
allow_selling_generated_content: Optional[bool] = None,
recursive: bool = True,
apply_filters: bool = False,
) -> List[str]:
"""Search model relative file paths for autocomplete functionality"""
"""Search model relative file paths for autocomplete functionality.
Optional filter kwargs mirror the filters used by the list endpoint
(/api/lm/{prefix}/list). When no filter kwargs are provided the
behavior is identical to plain token-based path matching.
"""
cache = await self.scanner.get_cached_data()
include_terms, exclude_terms = self._parse_search_tokens(search_term)
data = cache.raw_data
has_filters = any(
[
apply_filters,
folder is not None,
folder_include,
folder_exclude,
base_models,
model_types,
tags,
auto_tags,
credit_required is not None,
allow_selling_generated_content is not None,
]
)
if has_filters:
# Auto-tags are not stored in the scanner cache — they are computed
# on the fly. Pre-compute them only when an auto-tag filter is
# active to avoid mutating cache entries unnecessarily.
if auto_tags:
from .auto_tag_service import extract_auto_tags
for item in data:
if not item.get("auto_tags"):
item["auto_tags"] = extract_auto_tags(item)
criteria = FilterCriteria(
folder=folder,
folder_include=folder_include,
folder_exclude=folder_exclude,
base_models=base_models,
model_types=model_types,
tags=tags,
auto_tags=auto_tags,
search_options={"recursive": recursive},
tag_logic=tag_logic,
)
data = self.filter_set.apply(data, criteria)
if credit_required is not None:
data = await self._apply_credit_required_filter(
data, credit_required
)
if allow_selling_generated_content is not None:
data = await self._apply_allow_selling_filter(
data, allow_selling_generated_content
)
matching_paths = []
# Get model roots for path calculation
model_roots = self.scanner.get_model_roots()
# Collect all matching paths first (needed for proper sorting and offset)
for model in cache.raw_data:
for model in data:
file_path = model.get("file_path", "")
if not file_path:
continue
+30 -2
View File
@@ -59,6 +59,7 @@ class CacheEntryValidator:
'notes': ('', False),
'usage_tips': ('', False),
'hash_status': ('completed', False),
'autov3': (None, False),
}
@classmethod
@@ -119,8 +120,13 @@ class CacheEntryValidator:
if is_required:
errors.append(f"Required field '{field_name}' is missing or None")
if auto_repair:
working_entry[field_name] = cls._get_default_copy(default_value)
repaired = True
# A missing optional field whose default is None is already
# semantically equal to its default (e.g. autov3: absent
# means "not checked") — writing None back is a no-op, not
# a repair.
if default_value is not None:
working_entry[field_name] = cls._get_default_copy(default_value)
repaired = True
continue
# Validate field type and value
@@ -175,6 +181,15 @@ class CacheEntryValidator:
# that invalidates the entry, but we also don't mark it repaired.
pass
# Normalize autov3 to lowercase if needed (optional field, never stripped).
autov3 = working_entry.get('autov3')
if isinstance(autov3, str) and autov3:
normalized_autov3 = autov3.lower()
if normalized_autov3 != autov3:
if auto_repair:
working_entry['autov3'] = normalized_autov3
repaired = True
# Determine if entry is valid
# Entry is valid if no critical required field errors remain after repair
# Critical fields are file_path and sha256
@@ -242,6 +257,19 @@ class CacheEntryValidator:
"""
expected_type = type(default_value)
# Special case: autov3 is optional with a three-state contract.
# None = not checked, "" = checked but unavailable, otherwise a
# 12-character hex string (case-insensitive here; normalized to
# lowercase separately).
if field_name == 'autov3':
if value is None or value == "":
return None
if not isinstance(value, str):
return f"Field 'autov3' should be string or None, got {type(value).__name__}"
if len(value) != 12 or any(c not in '0123456789abcdefABCDEF' for c in value):
return "Field 'autov3' should be a 12-character hex string"
return None
# Special handling for numeric types
if expected_type == int:
if not isinstance(value, (int, float)):
+36 -8
View File
@@ -1,3 +1,7 @@
# pyright: reportImportCycles=false
# Lazy (function-local) imports still count as static edges in basedpyright's
# reportImportCycles, so the ServiceRegistry singleton pattern necessarily forms
# import cycles. Breaking them would require an architectural refactor.
import asyncio
import json
import logging
@@ -6,10 +10,10 @@ from datetime import datetime
from typing import Any, Dict, List, Optional
from ..utils.models import CheckpointMetadata
from ..utils.file_utils import find_preview_file, normalize_path
from ..utils.file_utils import find_preview_file, normalize_path, calculate_autov3
from ..utils.metadata_manager import MetadataManager
from ..config import config
from .model_scanner import ModelScanner
from .model_scanner import ModelScanner, _is_excluded_dir
from .model_hash_index import ModelHashIndex
logger = logging.getLogger(__name__)
@@ -62,6 +66,11 @@ class CheckpointScanner(ModelScanner):
# Find preview image
preview_url = find_preview_file(base_name, dir_path)
# AutoV3 reads only the safetensors header, so it is cheap even for
# large checkpoints; record the checked state at creation time ("" =
# checked but unavailable).
autov3 = calculate_autov3(real_path)
# Create metadata WITHOUT calculating hash
metadata = CheckpointMetadata(
file_name=base_name,
@@ -77,6 +86,7 @@ class CheckpointScanner(ModelScanner):
sub_type="checkpoint",
from_civitai=False, # Mark as local model since no hash yet
hash_status="pending", # Mark hash as pending
autov3=autov3 or "",
)
# Save the created metadata
@@ -120,7 +130,11 @@ class CheckpointScanner(ModelScanner):
# that queries get_hash_by_filename first) will miss on every
# lookup and keep calling back into this method, creating a
# tight loop that never populates the index.
self._hash_index.add_entry(metadata.sha256.lower(), file_path)
self._hash_index.add_entry(
metadata.sha256.lower(),
file_path,
getattr(metadata, "autov3", None) or None,
)
return metadata.sha256
async with self._hash_calculation_lock:
@@ -132,7 +146,11 @@ class CheckpointScanner(ModelScanner):
and metadata.hash_status == "completed"
and metadata.sha256
):
self._hash_index.add_entry(metadata.sha256.lower(), file_path)
self._hash_index.add_entry(
metadata.sha256.lower(),
file_path,
getattr(metadata, "autov3", None) or None,
)
return metadata.sha256
task = self._hash_calculation_tasks.get(real_path)
@@ -185,7 +203,11 @@ class CheckpointScanner(ModelScanner):
if metadata.hash_status == "completed" and metadata.sha256:
# Populate the in-memory hash index even for pre-computed
# hashes, mirroring the fix in calculate_hash_for_model.
self._hash_index.add_entry(metadata.sha256.lower(), file_path)
self._hash_index.add_entry(
metadata.sha256.lower(),
file_path,
getattr(metadata, "autov3", None) or None,
)
return metadata.sha256
# Update status to calculating
@@ -202,7 +224,11 @@ class CheckpointScanner(ModelScanner):
await MetadataManager.save_metadata(file_path, metadata)
# Update hash index
self._hash_index.add_entry(sha256.lower(), file_path)
self._hash_index.add_entry(
sha256.lower(),
file_path,
getattr(metadata, "autov3", None) or None,
)
# Update the in-memory cache entry so that subsequent
# _persist_current_cache / _save_persistent_cache calls
@@ -216,6 +242,7 @@ class CheckpointScanner(ModelScanner):
if entry.get("file_path") == file_path:
entry["sha256"] = sha256.lower()
entry["hash_status"] = "completed"
self.bump_cache_version()
break
logger.info(f"Hash calculated for checkpoint: {file_path}")
@@ -301,7 +328,8 @@ class CheckpointScanner(ModelScanner):
if not os.path.exists(root_path):
continue
for dirpath, _dirnames, filenames in os.walk(root_path):
for dirpath, dirnames, filenames in os.walk(root_path):
dirnames[:] = [d for d in dirnames if not _is_excluded_dir(d)]
for filename in filenames:
if not filename.endswith(".metadata.json"):
continue
@@ -405,7 +433,7 @@ class CheckpointScanner(ModelScanner):
roots.extend(config.extra_checkpoints_roots or [])
roots.extend(config.extra_unet_roots or [])
# Remove duplicates while preserving order
seen: set = set()
seen: set[str] = set()
unique_roots: List[str] = []
for root in roots:
if root not in seen:
+28 -28
View File
@@ -1,6 +1,6 @@
import os
import logging
from typing import Dict, Optional
from typing import Any, Dict, Optional
from .base_model_service import BaseModelService
from .auto_tag_service import extract_auto_tags
@@ -21,58 +21,58 @@ class CheckpointService(BaseModelService):
"""
super().__init__("checkpoint", scanner, CheckpointMetadata, update_service=update_service)
async def format_response(self, checkpoint_data: Dict) -> Optional[Dict]:
async def format_response(self, model_data: Dict[str, Any]) -> Optional[Dict[str, Any]]:
"""Format Checkpoint data for API response.
Returns None when the entry is missing critical fields (corrupted cache
row), so the handler layer can filter it out. See issue #730.
"""
# Guard against corrupted cache entries missing critical fields
file_path = checkpoint_data.get("file_path")
file_path = model_data.get("file_path")
if not file_path or not isinstance(file_path, str):
logger.warning(
"Skipping corrupted checkpoint entry (missing file_path): %s",
checkpoint_data.get("file_name", "<unknown>"),
model_data.get("file_name", "<unknown>"),
)
return None
# Get sub_type from cache entry (new canonical field)
sub_type = checkpoint_data.get("sub_type", "checkpoint")
sub_type = model_data.get("sub_type", "checkpoint")
file_name = checkpoint_data.get("file_name") or ""
model_name = checkpoint_data.get("model_name") or file_name
folder = checkpoint_data.get("folder") or ""
file_name = model_data.get("file_name") or ""
model_name = model_data.get("model_name") or file_name
folder = model_data.get("folder") or ""
return {
"model_name": model_name,
"file_name": file_name,
"preview_url": config.get_preview_static_url(checkpoint_data.get("preview_url", "")),
"preview_nsfw_level": checkpoint_data.get("preview_nsfw_level", 0),
"base_model": checkpoint_data.get("base_model", ""),
"preview_url": config.get_preview_static_url(model_data.get("preview_url", "")),
"preview_nsfw_level": model_data.get("preview_nsfw_level", 0),
"base_model": model_data.get("base_model", ""),
"folder": folder,
"sha256": checkpoint_data.get("sha256", ""),
"sha256": model_data.get("sha256", ""),
"file_path": file_path.replace(os.sep, "/"),
"file_size": checkpoint_data.get("size", 0),
"modified": checkpoint_data.get("modified", ""),
"tags": checkpoint_data.get("tags", []),
"from_civitai": checkpoint_data.get("from_civitai", True),
"usage_count": checkpoint_data.get("usage_count", 0),
"notes": checkpoint_data.get("notes", ""),
"file_size": model_data.get("size", 0),
"modified": model_data.get("modified", ""),
"tags": model_data.get("tags", []),
"from_civitai": model_data.get("from_civitai", True),
"usage_count": model_data.get("usage_count", 0),
"notes": model_data.get("notes", ""),
"sub_type": sub_type,
"favorite": checkpoint_data.get("favorite", False),
"exclude": bool(checkpoint_data.get("exclude", False)),
"update_available": bool(checkpoint_data.get("update_available", False)),
"skip_metadata_refresh": bool(checkpoint_data.get("skip_metadata_refresh", False)),
"civitai": self.filter_civitai_data(checkpoint_data.get("civitai", {}), minimal=True),
"auto_tags": checkpoint_data.get("auto_tags") or extract_auto_tags(checkpoint_data),
"version_count": checkpoint_data.get("version_count"),
"hf_url": checkpoint_data.get("hf_url", ""),
"favorite": model_data.get("favorite", False),
"exclude": bool(model_data.get("exclude", False)),
"update_available": bool(model_data.get("update_available", False)),
"skip_metadata_refresh": bool(model_data.get("skip_metadata_refresh", False)),
"civitai": self.filter_civitai_data(model_data.get("civitai", {}), minimal=True),
"auto_tags": model_data.get("auto_tags") or extract_auto_tags(model_data),
"version_count": model_data.get("version_count"),
"hf_url": model_data.get("hf_url", ""),
}
def find_duplicate_hashes(self) -> Dict:
def find_duplicate_hashes(self) -> Dict[str, Any]:
"""Find Checkpoints with duplicate SHA256 hashes"""
return self.scanner._hash_index.get_duplicate_hashes()
def find_duplicate_filenames(self) -> Dict:
def find_duplicate_filenames(self) -> Dict[str, Any]:
"""Find Checkpoints with conflicting filenames"""
return self.scanner._hash_index.get_duplicate_filenames()
+41 -36
View File
@@ -1,8 +1,12 @@
# pyright: reportImportCycles=false
# Lazy (function-local) imports still count as static edges in basedpyright's
# reportImportCycles, so the ServiceRegistry singleton pattern necessarily forms
# import cycles. Breaking them would require an architectural refactor.
import json
import logging
import asyncio
from copy import deepcopy
from typing import Optional, Dict, Tuple, List
from typing import Any, Optional, Dict, Tuple, List, cast
from .model_metadata_provider import CivArchiveModelMetadataProvider, ModelMetadataProviderManager
from .downloader import get_downloader
from .errors import RateLimitError
@@ -37,8 +41,8 @@ class CivArchiveClient:
async def _request_json(
self,
path: str,
params: Optional[Dict[str, str]] = None
) -> Tuple[Optional[Dict], Optional[str]]:
params: Optional[Dict[str, Any]] = None
) -> Tuple[Optional[Dict[str, Any]], Optional[str]]:
"""Call CivArchive API and return JSON payload"""
success, payload = await self._make_request(path, params=params)
if not success:
@@ -52,12 +56,12 @@ class CivArchiveClient:
self,
path: str,
*,
params: Optional[Dict[str, str]] = None,
) -> Tuple[bool, Dict | str]:
params: Optional[Dict[str, Any]] = None,
) -> Tuple[bool, Dict[str, Any] | str]:
"""Wrapper around downloader.make_request that surfaces rate limits."""
downloader = await get_downloader()
kwargs: Dict[str, Dict[str, str]] = {}
kwargs: Dict[str, Dict[str, Any]] = {}
if params:
safe_params = {str(key): str(value) for key, value in params.items() if value is not None}
if safe_params:
@@ -73,10 +77,11 @@ class CivArchiveClient:
if payload.provider is None:
payload.provider = "civarchive_api"
raise payload
return success, payload
# RateLimitError is always raised above, so the returned payload is a dict or str.
return success, cast(Dict[str, Any] | str, payload)
@staticmethod
def _normalize_payload(payload: Dict) -> Dict:
def _normalize_payload(payload: Dict[str, Any]) -> Dict[str, Any]:
"""Unwrap CivArchive responses that wrap content under a data key"""
if not isinstance(payload, dict):
return {}
@@ -86,12 +91,12 @@ class CivArchiveClient:
return payload
@staticmethod
def _split_context(payload: Dict) -> Tuple[Dict, Dict, List[Dict]]:
def _split_context(payload: Dict[str, Any]) -> Tuple[Dict[str, Any], Dict[str, Any], List[Dict[str, Any]]]:
"""Separate version payload from surrounding model context"""
data = CivArchiveClient._normalize_payload(payload)
context: Dict = {}
fallback_files: List[Dict] = []
version: Dict = {}
context: Dict[str, Any] = {}
fallback_files: List[Dict[str, Any]] = []
version: Dict[str, Any] = {}
for key, value in data.items():
if key in {"version", "model"}:
@@ -115,7 +120,7 @@ class CivArchiveClient:
return context, version, fallback_files
@staticmethod
def _ensure_list(value) -> List:
def _ensure_list(value: Any) -> List[Any]:
if isinstance(value, list):
return value
if value is None:
@@ -123,7 +128,7 @@ class CivArchiveClient:
return [value]
@staticmethod
def _build_model_info(context: Dict) -> Dict:
def _build_model_info(context: Dict[str, Any]) -> Dict[str, Any]:
tags = context.get("tags")
if not isinstance(tags, list):
tags = list(tags) if isinstance(tags, (set, tuple)) else ([] if tags is None else [tags])
@@ -136,7 +141,7 @@ class CivArchiveClient:
}
@staticmethod
def _build_creator_info(context: Dict) -> Dict:
def _build_creator_info(context: Dict[str, Any]) -> Dict[str, Any]:
username = context.get("creator_username") or context.get("username") or ""
image = context.get("creator_image") or context.get("creator_avatar") or ""
creator: Dict[str, Optional[str]] = {
@@ -150,7 +155,7 @@ class CivArchiveClient:
return creator
@staticmethod
def _transform_file_entry(file_data: Dict) -> Dict:
def _transform_file_entry(file_data: Dict[str, Any]) -> Dict[str, Any]:
mirrors = file_data.get("mirrors") or []
if not isinstance(mirrors, list):
mirrors = [mirrors]
@@ -165,7 +170,7 @@ class CivArchiveClient:
if not name and available_mirror:
name = available_mirror.get("filename")
transformed: Dict = {
transformed: Dict[str, Any] = {
"id": file_data.get("id"),
"sizeKB": file_data.get("sizeKB"),
"name": name,
@@ -216,23 +221,23 @@ class CivArchiveClient:
def _transform_files(
self,
files: Optional[List[Dict]],
fallback_files: Optional[List[Dict]] = None
) -> List[Dict]:
candidates: List[Dict] = []
files: Optional[List[Dict[str, Any]]],
fallback_files: Optional[List[Dict[str, Any]]] = None
) -> List[Dict[str, Any]]:
candidates: List[Dict[str, Any]] = []
if isinstance(files, list) and files:
candidates = files
elif isinstance(fallback_files, list):
candidates = fallback_files
transformed_files: List[Dict] = []
transformed_files: List[Dict[str, Any]] = []
for file_data in candidates:
if isinstance(file_data, dict):
transformed_files.append(self._transform_file_entry(file_data))
# Sort: .safetensors first, .ckpt second, others last
# so the backend fallback (no file_params) prefers safetensors
def _sort_key(f: Dict) -> int:
def _sort_key(f: Dict[str, Any]) -> int:
fname = f.get("name") or ""
if isinstance(fname, str):
lower = fname.lower()
@@ -247,10 +252,10 @@ class CivArchiveClient:
def _transform_version(
self,
context: Dict,
version: Dict,
fallback_files: Optional[List[Dict]] = None
) -> Optional[Dict]:
context: Dict[str, Any],
version: Dict[str, Any],
fallback_files: Optional[List[Dict[str, Any]]] = None
) -> Optional[Dict[str, Any]]:
if not version:
return None
@@ -291,7 +296,7 @@ class CivArchiveClient:
return version_copy
async def _resolve_version_from_files(self, payload: Dict) -> Optional[Dict]:
async def _resolve_version_from_files(self, payload: Dict[str, Any]) -> Optional[Dict[str, Any]]:
"""Fallback to fetch version data when only file metadata is available"""
data = self._normalize_payload(payload)
files = data.get("files") or payload.get("files") or []
@@ -323,7 +328,7 @@ class CivArchiveClient:
return resolved
return None
async def get_model_by_hash(self, model_hash: str) -> Tuple[Optional[Dict], Optional[str]]:
async def get_model_by_hash(self, model_hash: str) -> Tuple[Optional[Dict[str, Any]], Optional[str]]:
"""Find model by SHA256 hash value using CivArchive API"""
try:
payload, error = await self._request_json(f"/sha256/{model_hash.lower()}")
@@ -332,12 +337,12 @@ class CivArchiveClient:
return None, "Model not found"
return None, error
context, version_data, fallback_files = self._split_context(payload)
context, version_data, fallback_files = self._split_context(cast(Dict[str, Any], payload))
transformed = self._transform_version(context, version_data, fallback_files)
if transformed:
return transformed, None
resolved = await self._resolve_version_from_files(payload)
resolved = await self._resolve_version_from_files(cast(Dict[str, Any], payload))
if resolved:
return resolved, None
@@ -350,7 +355,7 @@ class CivArchiveClient:
logger.error(f"Error fetching CivArchive model by hash {model_hash[:10]}: {e}")
return None, str(e)
async def get_model_versions(self, model_id: str) -> Optional[Dict]:
async def get_model_versions(self, model_id: str) -> Optional[Dict[str, Any]]:
"""Get all versions of a model using CivArchive API"""
try:
payload, error = await self._request_json(f"/models/{model_id}")
@@ -364,7 +369,7 @@ class CivArchiveClient:
context, version_data, fallback_files = self._split_context(payload)
versions_meta = data.get("versions") or []
transformed_versions: List[Dict] = []
transformed_versions: List[Dict[str, Any]] = []
for meta in versions_meta:
if not isinstance(meta, dict):
continue
@@ -381,7 +386,7 @@ class CivArchiveClient:
if primary_version:
transformed_versions.insert(0, primary_version)
ordered_versions: List[Dict] = []
ordered_versions: List[Dict[str, Any]] = []
seen_ids = set()
for version in transformed_versions:
version_id = version.get("id")
@@ -402,7 +407,7 @@ class CivArchiveClient:
logger.error(f"Error fetching CivArchive model versions for {model_id}: {e}")
return None
async def get_model_version(self, model_id: int = None, version_id: int = None) -> Optional[Dict]:
async def get_model_version(self, model_id: int | str | None = None, version_id: int | str | None = None) -> Optional[Dict[str, Any]]:
"""Get specific model version using CivArchive API
Args:
@@ -459,7 +464,7 @@ class CivArchiveClient:
logger.error(f"Error fetching CivArchive model version via API {model_id}/{version_id}: {e}")
return None
async def get_model_version_info(self, version_id: str) -> Tuple[Optional[Dict], Optional[str]]:
async def get_model_version_info(self, version_id: str) -> Tuple[Optional[Dict[str, Any]], Optional[str]]:
""" Fetch model version metadata using a known bogus model lookup
CivArchive lacks a direct version lookup API, this uses a workaround (which we handle in the main model request now)
+1 -1
View File
@@ -283,7 +283,7 @@ class CivitaiBaseModelService:
return None
if isinstance(result, str):
data = json.loads(result)
data: Any = json.loads(result)
else:
data = result
+49 -37
View File
@@ -1,10 +1,14 @@
# pyright: reportImportCycles=false
# Lazy (function-local) imports still count as static edges in basedpyright's
# reportImportCycles, so the ServiceRegistry singleton pattern necessarily forms
# import cycles. Breaking them would require an architectural refactor.
import asyncio
import copy
import logging
import os
import time
from collections import OrderedDict
from typing import Any, Optional, Dict, Tuple, List, Sequence
from typing import Any, Optional, Dict, Tuple, List, Sequence, cast
from .connectivity_guard import (
OFFLINE_FRIENDLY_MESSAGE,
is_expected_offline_error,
@@ -17,6 +21,7 @@ from .model_metadata_provider import (
from .downloader import get_downloader
from .errors import RateLimitError, ResourceNotFoundError
from ..utils.civitai_utils import resolve_license_payload
from ..utils.constants import MODEL_WEIGHT_FILE_TYPES
logger = logging.getLogger(__name__)
@@ -58,7 +63,7 @@ class CivitaiClient:
# Uses OrderedDict with LRU eviction at MAX_CACHE_ENTRIES to prevent
# unbounded growth in long-running server processes.
self._version_info_cache: OrderedDict[
str, Tuple[Optional[Dict], Optional[str]]
str, Tuple[Optional[Dict[str, Any]], Optional[str]]
] = OrderedDict()
self._MAX_CACHE_ENTRIES = 500
@@ -72,7 +77,7 @@ class CivitaiClient:
*,
use_auth: bool = False,
**kwargs,
) -> Tuple[bool, Dict | str]:
) -> Tuple[bool, Dict[str, Any] | str]:
"""Wrapper around downloader.make_request that surfaces rate limits,
with retry for transient server errors (5xx, Cloudflare 524, network flakiness)."""
@@ -86,7 +91,8 @@ class CivitaiClient:
**kwargs,
)
if success:
return True, result
# RateLimitError is raised below; a successful result is dict or str.
return True, cast(Dict[str, Any] | str, result)
if isinstance(result, RateLimitError):
if result.provider is None:
@@ -126,7 +132,7 @@ class CivitaiClient:
return False, "Unexpected error in _make_request"
@staticmethod
def _remove_comfy_metadata(model_version: Optional[Dict]) -> None:
def _remove_comfy_metadata(model_version: Optional[Dict[str, Any]]) -> None:
"""Remove Comfy-specific metadata from model version images."""
if not isinstance(model_version, dict):
return
@@ -173,7 +179,7 @@ class CivitaiClient:
async def get_model_by_hash(
self, model_hash: str
) -> Tuple[Optional[Dict], Optional[str]]:
) -> Tuple[Optional[Dict[str, Any]], Optional[str]]:
try:
success, version = await self._make_request(
"GET",
@@ -220,7 +226,7 @@ class CivitaiClient:
# Ensure directory exists
os.makedirs(os.path.dirname(save_path), exist_ok=True)
with open(save_path, "wb") as f:
f.write(content)
f.write(content if isinstance(content, bytes) else content.encode("utf-8"))
return True
return False
except Exception as e:
@@ -275,7 +281,7 @@ class CivitaiClient:
return True
return False
async def get_model_versions(self, model_id: str) -> Optional[Dict]:
async def get_model_versions(self, model_id: str) -> Optional[Dict[str, Any]]:
"""Get all versions of a model with local availability info"""
try:
success, result = await self._make_request(
@@ -283,7 +289,7 @@ class CivitaiClient:
f"{self.base_url}/models/{model_id}",
use_auth=True,
)
if success:
if success and isinstance(result, dict):
# Also return model type along with versions
return {
"modelVersions": result.get("modelVersions", []),
@@ -317,7 +323,7 @@ class CivitaiClient:
async def get_model_versions_bulk(
self, model_ids: Sequence[int]
) -> Optional[Dict[int, Dict]]:
) -> Optional[Dict[int, Dict[str, Any]]]:
"""Fetch model metadata for multiple ids using the batch API."""
deduped: Dict[int, None] = {}
@@ -347,13 +353,13 @@ class CivitaiClient:
if not isinstance(items, list):
return {}
payload: Dict[int, Dict] = {}
payload: Dict[int, Dict[str, Any]] = {}
for item in items:
if not isinstance(item, dict):
continue
model_id = item.get("id")
try:
normalized_id = int(model_id)
normalized_id = int(cast(Any, model_id))
except (TypeError, ValueError):
continue
payload[normalized_id] = {
@@ -373,8 +379,8 @@ class CivitaiClient:
return None
async def get_model_version(
self, model_id: int = None, version_id: int = None
) -> Optional[Dict]:
self, model_id: int | None = None, version_id: int | None = None
) -> Optional[Dict[str, Any]]:
"""Get specific model version with additional metadata."""
try:
if model_id is None and version_id is not None:
@@ -392,7 +398,7 @@ class CivitaiClient:
logger.error(f"Error fetching model version: {e}")
return None
async def _get_version_by_id_only(self, version_id: int) -> Optional[Dict]:
async def _get_version_by_id_only(self, version_id: int) -> Optional[Dict[str, Any]]:
version = await self._fetch_version_by_id(version_id)
if version is None:
return None
@@ -411,7 +417,7 @@ class CivitaiClient:
async def _get_version_with_model_id(
self, model_id: int, version_id: Optional[int]
) -> Optional[Dict]:
) -> Optional[Dict[str, Any]]:
model_data = await self._fetch_model_data(model_id)
if not model_data:
return None
@@ -464,20 +470,20 @@ class CivitaiClient:
self._remove_comfy_metadata(version)
return version
async def _fetch_model_data(self, model_id: int) -> Optional[Dict]:
async def _fetch_model_data(self, model_id: int) -> Optional[Dict[str, Any]]:
success, data = await self._make_request(
"GET",
f"{self.base_url}/models/{model_id}",
use_auth=True,
)
if success:
if success and isinstance(data, dict):
return data
if is_expected_offline_error(data):
return None
logger.warning(f"Failed to fetch model data for model {model_id}")
return None
async def _fetch_version_by_id(self, version_id: Optional[int]) -> Optional[Dict]:
async def _fetch_version_by_id(self, version_id: Optional[int]) -> Optional[Dict[str, Any]]:
if version_id is None:
return None
@@ -486,7 +492,7 @@ class CivitaiClient:
f"{self.base_url}/model-versions/{version_id}",
use_auth=True,
)
if success:
if success and isinstance(version, dict):
return version
if is_expected_offline_error(version):
return None
@@ -494,7 +500,7 @@ class CivitaiClient:
logger.warning(f"Failed to fetch version by id {version_id}")
return None
async def _fetch_version_by_hash(self, model_hash: Optional[str]) -> Optional[Dict]:
async def _fetch_version_by_hash(self, model_hash: Optional[str]) -> Optional[Dict[str, Any]]:
if not model_hash:
return None
@@ -503,7 +509,7 @@ class CivitaiClient:
f"{self.base_url}/model-versions/by-hash/{model_hash}",
use_auth=True,
)
if success:
if success and isinstance(version, dict):
return version
if is_expected_offline_error(version):
return None
@@ -512,8 +518,8 @@ class CivitaiClient:
return None
def _select_target_version(
self, model_data: Dict, model_id: int, version_id: Optional[int]
) -> Optional[Dict]:
self, model_data: Dict[str, Any], model_id: int, version_id: Optional[int]
) -> Optional[Dict[str, Any]]:
model_versions = model_data.get("modelVersions", [])
if not model_versions:
logger.warning(f"No model versions found for model {model_id}")
@@ -532,18 +538,24 @@ class CivitaiClient:
return model_versions[0]
def _extract_primary_model_hash(self, version_entry: Dict) -> Optional[str]:
def _extract_primary_model_hash(self, version_entry: Dict[str, Any]) -> Optional[str]:
# Prefer the generic "Model" file (most reliable version identity);
# fall back to any other weights-type primary.
for file_info in version_entry.get("files", []):
if file_info.get("type") == "Model" and file_info.get("primary"):
hashes = file_info.get("hashes", {})
model_hash = hashes.get("SHA256")
model_hash = (file_info.get("hashes", {}) or {}).get("SHA256")
if model_hash:
return model_hash
for file_info in version_entry.get("files", []):
if file_info.get("type") in MODEL_WEIGHT_FILE_TYPES and file_info.get("primary"):
model_hash = (file_info.get("hashes", {}) or {}).get("SHA256")
if model_hash:
return model_hash
return None
def _build_version_from_model_data(
self, version_entry: Dict, model_id: int, model_data: Dict
) -> Dict:
self, version_entry: Dict[str, Any], model_id: int, model_data: Dict[str, Any]
) -> Dict[str, Any]:
version = copy.deepcopy(version_entry)
version.pop("index", None)
version["modelId"] = model_id
@@ -555,7 +567,7 @@ class CivitaiClient:
}
return version
def _enrich_version_with_model_data(self, version: Dict, model_data: Dict) -> None:
def _enrich_version_with_model_data(self, version: Dict[str, Any], model_data: Dict[str, Any]) -> None:
model_info = version.get("model")
if not isinstance(model_info, dict):
model_info = {}
@@ -571,7 +583,7 @@ class CivitaiClient:
async def get_model_version_info(
self, version_id: str
) -> Tuple[Optional[Dict], Optional[str]]:
) -> Tuple[Optional[Dict[str, Any]], Optional[str]]:
"""Fetch model version metadata from Civitai
Args:
@@ -596,7 +608,7 @@ class CivitaiClient:
logger.debug("Resolving Civitai model version info: %s", url)
success, result = await self._make_request("GET", url, use_auth=True)
if success:
if success and isinstance(result, dict):
logger.debug("Successfully fetched model version info for: %s", version_id)
self._remove_comfy_metadata(result)
self._version_info_cache[version_id] = (result, None)
@@ -626,7 +638,7 @@ class CivitaiClient:
async def get_image_info(
self, image_id: str, source_url: str | None = None
) -> Optional[Dict]:
) -> Optional[Dict[str, Any]]:
"""Fetch image information from Civitai API
Args:
@@ -659,7 +671,7 @@ class CivitaiClient:
)
return None
if result and "items" in result and isinstance(result["items"], list):
if isinstance(result, dict) and "items" in result and isinstance(result["items"], list):
items = result["items"]
for item in items:
@@ -699,7 +711,7 @@ class CivitaiClient:
async def get_model_versions_by_hashes(
self, hashes: List[str]
) -> Optional[List[Dict]]:
) -> Optional[List[Dict[str, Any]]]:
"""Fetch full version details for up to 100 SHA256 hashes via the batch endpoint.
Uses POST /api/v1/model-versions/by-hash which returns full version
@@ -716,7 +728,7 @@ class CivitaiClient:
return []
BATCH_SIZE = 100
all_versions: List[Dict] = []
all_versions: List[Dict[str, Any]] = []
for start in range(0, len(hashes), BATCH_SIZE):
batch = hashes[start : start + BATCH_SIZE]
@@ -736,7 +748,7 @@ class CivitaiClient:
continue
if isinstance(result, list):
all_versions.extend(result)
all_versions.extend(cast(Any, result))
else:
logger.debug(
"Unexpected by-hash response type: %s", type(result)
+2 -1
View File
@@ -18,7 +18,7 @@ class DownloadCoordinator:
self,
*,
ws_manager,
download_manager_factory: Callable[[], Awaitable],
download_manager_factory: Callable[[], Awaitable[Any]],
) -> None:
self._ws_manager = ws_manager
self._download_manager_factory = download_manager_factory
@@ -83,6 +83,7 @@ class DownloadCoordinator:
save_dir=payload.get("model_root"),
relative_path=payload.get("relative_path", ""),
use_default_paths=payload.get("use_default_paths", False),
use_save_dir_as_root=payload.get("use_save_dir_as_root", False),
progress_callback=progress_callback,
download_id=download_id,
source=payload.get("source"),
+199 -110
View File
@@ -1,3 +1,7 @@
# pyright: reportImportCycles=false
# Lazy (function-local) imports still count as static edges in basedpyright's
# reportImportCycles, so the ServiceRegistry singleton pattern necessarily forms
# import cycles. Breaking them would require an architectural refactor.
import copy
import logging
import os
@@ -8,17 +12,18 @@ import zipfile
from concurrent.futures import ThreadPoolExecutor
from collections import OrderedDict
import uuid
from typing import Dict, List, Optional, Set, Tuple
from typing import Any, Dict, List, Optional, Set, Tuple, cast
from urllib.parse import urlparse
from ..utils.models import LoraMetadata, CheckpointMetadata, EmbeddingMetadata
from ..utils.constants import (
CARD_PREVIEW_WIDTH,
DIFFUSION_MODEL_BASE_MODELS,
MODEL_WEIGHT_FILE_TYPES,
SUPPORTED_DOWNLOAD_SKIP_BASE_MODELS,
VALID_LORA_TYPES,
)
from ..utils.civitai_utils import normalize_civitai_download_url, rewrite_preview_url
from ..utils.file_utils import calculate_sha256
from ..utils.file_utils import calculate_sha256, calculate_autov3
from ..utils.preview_selection import resolve_mature_threshold, select_preview_media
from ..utils.utils import sanitize_folder_name
from ..utils.exif_utils import ExifUtils
@@ -42,6 +47,11 @@ CIVITAI_DOWNLOAD_URL_PREFIXES = (
)
# File types that are never the intended download target even when CivitAI
# marks them primary — configs/archives/workflows are auxiliary artifacts.
NON_DOWNLOADABLE_PRIMARY_TYPES = ("Config", "Archive", "Workflow", "Training Data")
class DownloadManager:
_instance = None
_lock = asyncio.Lock()
@@ -121,7 +131,7 @@ class DownloadManager:
"delay": 0,
}
)
except DownloadInProgressError:
except DownloadInProgressError: # pyright: ignore[reportPossiblyUnboundVariable]
logger.info(
"Skipping automatic example images download for %s; another example images download is already running",
model_hash,
@@ -170,7 +180,7 @@ class DownloadManager:
logger.error("aria2 download failed for %s: %s", download_url, exc)
return False, str(exc)
download_kwargs = {
download_kwargs: Dict[str, Any] = {
"progress_callback": progress_callback,
"use_auth": use_auth,
}
@@ -204,16 +214,17 @@ class DownloadManager:
async def download_from_civitai(
self,
model_id: int = None,
model_version_id: int = None,
save_dir: str = None,
model_id: int | None = None,
model_version_id: int | None = None,
save_dir: str | None = None,
relative_path: str = "",
progress_callback=None,
use_default_paths: bool = False,
download_id: str = None,
source: str = None,
file_params: Dict = None,
) -> Dict:
download_id: str | None = None,
source: str | None = None,
file_params: Dict[str, Any] | None = None,
use_save_dir_as_root: bool = False,
) -> Dict[str, Any]:
"""Download model from Civitai with task tracking and concurrency control
Args:
@@ -253,6 +264,7 @@ class DownloadManager:
"save_dir": save_dir,
"relative_path": relative_path,
"use_default_paths": bool(use_default_paths),
"use_save_dir_as_root": bool(use_save_dir_as_root),
"source": source,
"file_params": copy.deepcopy(file_params) if file_params is not None else None,
"progress": 0,
@@ -283,6 +295,7 @@ class DownloadManager:
use_default_paths,
source,
file_params,
use_save_dir_as_root,
)
)
@@ -309,14 +322,15 @@ class DownloadManager:
async def _download_with_semaphore(
self,
task_id: str,
model_id: int,
model_version_id: int,
save_dir: str,
model_id: int | None,
model_version_id: int | None,
save_dir: str | None,
relative_path: str,
progress_callback=None,
use_default_paths: bool = False,
source: str = None,
file_params: Dict = None,
source: str | None = None,
file_params: Dict[str, Any] | None = None,
use_save_dir_as_root: bool = False,
):
"""Execute download with semaphore to limit concurrency"""
# Update status to waiting
@@ -380,7 +394,8 @@ class DownloadManager:
# Use original download implementation
try:
# Check for cancellation before starting
if asyncio.current_task().cancelled():
current_task = asyncio.current_task()
if current_task is not None and current_task.cancelled():
raise asyncio.CancelledError()
result = await self._execute_original_download(
@@ -396,6 +411,7 @@ class DownloadManager:
),
source,
file_params,
use_save_dir_as_root=use_save_dir_as_root,
)
# Update status based on result
@@ -484,11 +500,11 @@ class DownloadManager:
# Schedule cleanup of download record after delay
asyncio.create_task(self._cleanup_download_record(task_id))
def _start_background_download_task(self, download_id: str, coroutine) -> asyncio.Task:
def _start_background_download_task(self, download_id: str, coroutine) -> asyncio.Task[Any]:
task = asyncio.create_task(coroutine)
self._download_tasks[download_id] = task
def _cleanup_done_task(done_task: asyncio.Task) -> None:
def _cleanup_done_task(done_task: asyncio.Task[Any]) -> None:
current_task = self._download_tasks.get(download_id)
if current_task is done_task:
self._download_tasks.pop(download_id, None)
@@ -530,7 +546,7 @@ class DownloadManager:
async def _cleanup_cancelled_download_files(
self,
download_id: str,
download_info: Optional[Dict],
download_info: Optional[Dict[str, Any]],
) -> None:
target_files = set()
persisted = await self._aria2_state_store.get(download_id)
@@ -603,19 +619,20 @@ class DownloadManager:
self,
download_id: str,
*,
extra: Optional[Dict] = None,
extra: Optional[Dict[str, Any]] = None,
) -> None:
info = self._active_downloads.get(download_id)
if not info:
return
payload = {
payload: Dict[str, Any] = {
"download_id": download_id,
"model_id": info.get("model_id"),
"model_version_id": info.get("model_version_id"),
"save_dir": info.get("save_dir"),
"relative_path": info.get("relative_path", ""),
"use_default_paths": bool(info.get("use_default_paths", False)),
"use_save_dir_as_root": bool(info.get("use_save_dir_as_root", False)),
"source": info.get("source"),
"file_params": copy.deepcopy(info.get("file_params")),
"transfer_backend": info.get("transfer_backend", "aria2"),
@@ -631,13 +648,14 @@ class DownloadManager:
await self._aria2_state_store.upsert(download_id, payload)
def _build_restored_download_info(self, record: Dict, save_path: str) -> Dict:
def _build_restored_download_info(self, record: Dict[str, Any], save_path: str) -> Dict[str, Any]:
return {
"model_id": record.get("model_id"),
"model_version_id": record.get("model_version_id"),
"save_dir": record.get("save_dir"),
"relative_path": record.get("relative_path", ""),
"use_default_paths": bool(record.get("use_default_paths", False)),
"use_save_dir_as_root": bool(record.get("use_save_dir_as_root", False)),
"source": record.get("source"),
"file_params": copy.deepcopy(record.get("file_params")),
"progress": record.get("progress", 0),
@@ -653,8 +671,8 @@ class DownloadManager:
def _is_same_aria2_download_request(
self,
current_info: Optional[Dict],
persisted_record: Dict,
current_info: Optional[Dict[str, Any]],
persisted_record: Dict[str, Any],
) -> bool:
if not isinstance(current_info, dict):
return False
@@ -666,13 +684,15 @@ class DownloadManager:
return current_version_id == persisted_version_id
def _build_download_urls_from_file_info(self, file_info: Dict, source: str = None) -> List[str]:
def _build_download_urls_from_file_info(self, file_info: Dict[str, Any], source: str | None = None) -> List[str]:
mirrors = file_info.get("mirrors") or []
download_urls: List[str] = []
if mirrors:
for mirror in mirrors:
if mirror.get("deletedAt") is None and mirror.get("url"):
download_urls.append(normalize_civitai_download_url(mirror["url"]))
normalized_url = normalize_civitai_download_url(mirror["url"])
if normalized_url:
download_urls.append(normalized_url)
if source == "civarchive" and len(download_urls) > 1:
civitai_urls = [
@@ -688,7 +708,9 @@ class DownloadManager:
if not download_urls:
download_url = file_info.get("downloadUrl")
if download_url:
download_urls.append(normalize_civitai_download_url(download_url))
normalized_url = normalize_civitai_download_url(download_url)
if normalized_url:
download_urls.append(normalized_url)
return download_urls
@@ -696,8 +718,8 @@ class DownloadManager:
self,
*,
model_type: str,
version_info: Dict,
file_info: Dict,
version_info: Dict[str, Any],
file_info: Dict[str, Any],
save_path: str,
):
if model_type == "checkpoint":
@@ -706,7 +728,7 @@ class DownloadManager:
return EmbeddingMetadata.from_civitai_info(version_info, file_info, save_path)
return LoraMetadata.from_civitai_info(version_info, file_info, save_path)
def _resolve_save_path_from_persisted_record(self, record: Dict) -> Optional[str]:
def _resolve_save_path_from_persisted_record(self, record: Dict[str, Any]) -> Optional[str]:
save_path = record.get("save_path") or record.get("file_path")
if isinstance(save_path, str) and save_path:
return os.path.abspath(save_path)
@@ -728,7 +750,7 @@ class DownloadManager:
return os.path.abspath(os.path.join(save_dir, file_name))
async def _resume_restored_aria2_download(self, download_id: str, record: Dict) -> Dict:
async def _resume_restored_aria2_download(self, download_id: str, record: Dict[str, Any]) -> Dict[str, Any]:
try:
if download_id in self._active_downloads:
self._active_downloads[download_id]["status"] = "downloading"
@@ -842,7 +864,7 @@ class DownloadManager:
self,
previous_download_id: str,
new_download_id: str,
persisted_record: Dict,
persisted_record: Dict[str, Any],
save_path: str,
) -> None:
aria2_downloader = await get_aria2_downloader()
@@ -938,7 +960,7 @@ class DownloadManager:
except Exception:
status_payload = None
if status_payload is not None:
if status_payload is not None and isinstance(gid, str):
remote_status = status_payload.get("status", "")
if remote_status in {"active", "waiting", "paused"}:
await aria2_downloader.restore_transfer(download_id, gid, save_path)
@@ -992,6 +1014,7 @@ class DownloadManager:
bool(restored.get("use_default_paths", False)),
restored.get("source"),
restored.get("file_params"),
bool(restored.get("use_save_dir_as_root", False)),
)
)
continue
@@ -1115,17 +1138,18 @@ class DownloadManager:
async def _execute_original_download(
self,
model_id,
model_version_id,
save_dir,
relative_path,
model_id: int | None,
model_version_id: int | None,
save_dir: str | None,
relative_path: str,
progress_callback,
use_default_paths,
download_id=None,
transfer_backend="python",
source=None,
file_params=None,
):
use_default_paths: bool,
download_id: str | None = None,
transfer_backend: str = "python",
source: str | None = None,
file_params: Dict[str, Any] | None = None,
use_save_dir_as_root: bool = False,
) -> Dict[str, Any]:
"""Wrapper for original download_from_civitai implementation"""
try:
# Check if model version already exists in library
@@ -1172,7 +1196,7 @@ class DownloadManager:
# Get version info based on the provided identifier
version_info = await metadata_provider.get_model_version(
model_id, model_version_id
cast(int, model_id), cast(int, model_version_id)
)
if not version_info:
@@ -1183,7 +1207,7 @@ class DownloadManager:
)
metadata_provider = await get_default_metadata_provider()
version_info = await metadata_provider.get_model_version(
model_id, model_version_id
cast(int, model_id), cast(int, model_version_id)
)
if not version_info:
@@ -1353,41 +1377,48 @@ class DownloadManager:
# Handle use_default_paths
if use_default_paths:
settings_manager = get_settings_manager()
# Set save_dir based on model type
if model_type == "checkpoint":
if is_diffusion_model:
default_path = settings_manager.get("default_unet_root")
error_msg = "Default unet root path not set in settings"
else:
default_path = settings_manager.get("default_checkpoint_root")
error_msg = "Default checkpoint root path not set in settings"
if not default_path:
return {
"success": False,
"error": error_msg,
}
save_dir = default_path
elif model_type == "lora":
default_path = settings_manager.get("default_lora_root")
if not default_path:
return {
"success": False,
"error": "Default lora root path not set in settings",
}
save_dir = default_path
elif model_type == "embedding":
default_path = settings_manager.get("default_embedding_root")
if not default_path:
return {
"success": False,
"error": "Default embedding root path not set in settings",
}
save_dir = default_path
# With use_save_dir_as_root, an explicitly provided save_dir is kept
# as the base root and the path template is resolved underneath it.
# Otherwise fall back to the configured default root, which keeps the
# classic "download to default root" behavior for regular downloads.
if not save_dir or not use_save_dir_as_root:
# Set save_dir based on model type
if model_type == "checkpoint":
if is_diffusion_model:
default_path = settings_manager.get("default_unet_root")
error_msg = "Default unet root path not set in settings"
else:
default_path = settings_manager.get("default_checkpoint_root")
error_msg = "Default checkpoint root path not set in settings"
if not default_path:
return {
"success": False,
"error": error_msg,
}
save_dir = default_path
elif model_type == "lora":
default_path = settings_manager.get("default_lora_root")
if not default_path:
return {
"success": False,
"error": "Default lora root path not set in settings",
}
save_dir = default_path
elif model_type == "embedding":
default_path = settings_manager.get("default_embedding_root")
if not default_path:
return {
"success": False,
"error": "Default embedding root path not set in settings",
}
save_dir = default_path
# Calculate relative path using template
relative_path = self._calculate_relative_path(version_info, model_type)
# Update save directory with relative path if provided
if not save_dir:
return {"success": False, "error": "No save directory specified"}
if relative_path:
base_save_dir = save_dir
save_dir = os.path.join(save_dir, relative_path)
@@ -1475,7 +1506,7 @@ class DownloadManager:
f
for f in files
if f.get("primary")
and f.get("type") in ("Model", "Negative", "Diffusion Model", "UNet")
and f.get("type") in MODEL_WEIGHT_FILE_TYPES
),
None,
)
@@ -1515,21 +1546,52 @@ class DownloadManager:
# Fallback to primary file if no match found
if not file_info:
logger.debug("[download] Looking for primary file as fallback")
# Prefer a weights-type file CivitAI marked primary; then any
# weights-type file (providers without primary flags, e.g.
# civarchive); then trust CivitAI's primary flag regardless of
# type — newer types like 'Enhancement LoRA' are valid primary
# files. Weights files are preferred over non-weights primary
# files so a Config/Archive primary never replaces a Model.
file_info = next(
(
f
for f in files
if f.get("primary") and f.get("type") in ("Model", "Negative", "Diffusion Model", "UNet")
if f.get("primary") and f.get("type") in MODEL_WEIGHT_FILE_TYPES
),
None,
)
if file_info:
logger.debug(
"[download] Fallback primary file selected: id=%s, name=%s",
"[download] Fallback primary file selected (primary + weights): id=%s, name=%s",
file_info.get("id"), file_info.get("name"),
)
else:
logger.debug("[download] No primary file found in fallback lookup")
file_info = next(
(f for f in files if f.get("type") in MODEL_WEIGHT_FILE_TYPES),
None,
)
if file_info:
logger.debug(
"[download] Fallback primary file selected (weights type, no primary flag): id=%s, name=%s",
file_info.get("id"), file_info.get("name"),
)
else:
file_info = next(
(
f
for f in files
if f.get("primary")
and f.get("type") not in NON_DOWNLOADABLE_PRIMARY_TYPES
),
None,
)
if file_info:
logger.debug(
"[download] Fallback primary file selected (trusting CivitAI primary flag): id=%s, name=%s, type=%s",
file_info.get("id"), file_info.get("name"), file_info.get("type"),
)
else:
logger.debug("[download] No primary file found in fallback lookup")
if not file_info:
return {"success": False, "error": "No suitable file found in metadata"}
@@ -1561,6 +1623,11 @@ class DownloadManager:
version_info, file_info, save_path
)
logger.info(f"Creating EmbeddingMetadata for {file_name}")
else:
return {
"success": False,
"error": f'Unsupported model type "{model_type}"',
}
# 6. Start download process
if transfer_backend == "aria2" and download_id:
@@ -1580,7 +1647,7 @@ class DownloadManager:
},
)
execute_kwargs = {
execute_kwargs: Dict[str, Any] = {
"download_urls": download_urls,
"save_dir": save_dir,
"metadata": metadata,
@@ -1627,7 +1694,8 @@ class DownloadManager:
)
# If early_access_msg exists and download failed, replace error message
if "early_access_msg" in locals() and not result.get("success", False):
early_access_msg = locals().get("early_access_msg")
if early_access_msg and not result.get("success", False):
result["error"] = early_access_msg
return result
@@ -1652,7 +1720,7 @@ class DownloadManager:
self,
model_type: str,
model_id_value,
version_info: Dict,
version_info: Dict[str, Any],
fallback_version_id=None,
file_path: str | None = None,
) -> None:
@@ -1683,8 +1751,8 @@ class DownloadManager:
try:
await history_service.mark_downloaded(
model_type,
int(version_id),
model_id=int(resolved_model_id) if resolved_model_id is not None else None,
int(cast(Any, version_id)),
model_id=int(cast(Any, resolved_model_id)) if resolved_model_id is not None else None,
source="download",
file_path=file_path,
)
@@ -1701,7 +1769,7 @@ class DownloadManager:
self,
model_type: str,
model_id_value,
version_info: Dict,
version_info: Dict[str, Any],
fallback_version_id=None,
) -> None:
"""Ensure update tracking reflects a newly downloaded version."""
@@ -1725,7 +1793,7 @@ class DownloadManager:
if isinstance(model_info, dict):
resolved_model_id = model_info.get("id")
try:
resolved_model_id = int(resolved_model_id)
resolved_model_id = int(cast(Any, resolved_model_id))
except (TypeError, ValueError):
logger.debug(
"Skipping update sync; invalid model id: %s", resolved_model_id
@@ -1736,7 +1804,7 @@ class DownloadManager:
if version_id is None:
version_id = fallback_version_id
try:
version_id = int(version_id)
version_id = int(cast(Any, version_id))
except (TypeError, ValueError):
logger.debug(
"Skipping update sync; invalid version id for model %s: %s",
@@ -1773,7 +1841,7 @@ class DownloadManager:
for entry in local_versions or []:
vid = entry.get("versionId")
try:
version_ids.add(int(vid))
version_ids.add(int(cast(Any, vid)))
except (TypeError, ValueError):
continue
@@ -1795,7 +1863,7 @@ class DownloadManager:
)
def _calculate_relative_path(
self, version_info: Dict, model_type: str = "lora"
self, version_info: Dict[str, Any], model_type: str = "lora"
) -> str:
"""Calculate relative path using template from settings
@@ -1871,21 +1939,22 @@ class DownloadManager:
download_urls: List[str],
save_dir: str,
metadata,
version_info: Dict,
version_info: Dict[str, Any],
relative_path: str,
progress_callback=None,
model_type: str = "lora",
download_id: str = None,
download_id: str | None = None,
transfer_backend: Optional[str] = None,
) -> Dict:
) -> Dict[str, Any]:
"""Execute the actual download process including preview images and model files"""
metadata_entries: List = []
metadata_entries: List[Any] = []
metadata_files_for_cleanup: List[str] = []
extracted_paths: List[str] = []
metadata_path = ""
preview_targets: List[str] = []
preview_path: str | None = None
preview_nsfw_level = 0
save_path: str | None = None
transfer_backend = (transfer_backend or self._get_model_download_backend()).lower()
try:
resolved, save_path = await self._resolve_download_target_path(
@@ -1933,9 +2002,9 @@ class DownloadManager:
mature_threshold=mature_threshold,
)
preview_url = selected_image.get("url") if selected_image else None
preview_url = cast(Optional[str], selected_image.get("url")) if selected_image else None
media_type = (
(selected_image.get("type") or "").lower() if selected_image else ""
cast(str, selected_image.get("type") or "").lower() if selected_image else ""
)
def _extension_from_url(url: str, fallback: str) -> str:
@@ -1959,9 +2028,10 @@ class DownloadManager:
preview_url, media_type="video"
)
attempt_urls: List[str] = []
if rewritten:
if rewritten and rewritten_url:
attempt_urls.append(rewritten_url)
attempt_urls.append(preview_url)
if preview_url:
attempt_urls.append(preview_url)
seen_attempts = set()
for attempt in attempt_urls:
@@ -1978,7 +2048,7 @@ class DownloadManager:
rewritten_url, rewritten = rewrite_preview_url(
preview_url, media_type="image"
)
if rewritten:
if rewritten and rewritten_url:
preview_ext = _extension_from_url(preview_url, ".png")
preview_path = os.path.splitext(save_path)[0] + preview_ext
success, _ = await downloader.download_file(
@@ -2004,7 +2074,9 @@ class DownloadManager:
)
if success:
with open(temp_path, "wb") as temp_file_handle:
temp_file_handle.write(content)
temp_file_handle.write(
content if isinstance(content, bytes) else content.encode("utf-8")
)
preview_path = (
os.path.splitext(save_path)[0] + ".webp"
)
@@ -2056,6 +2128,8 @@ class DownloadManager:
last_error = None
for download_url in download_urls:
download_url = normalize_civitai_download_url(download_url)
if download_url is None:
continue
use_auth = download_url.startswith(CIVITAI_DOWNLOAD_URL_PREFIXES)
if transfer_backend == "aria2" and download_id:
await self._persist_aria2_state(
@@ -2160,6 +2234,10 @@ class DownloadManager:
"error": f"Zip archive does not contain any supported model files ({supported_text})",
}
actual_file_paths = extracted_paths
# The archive entry's AutoV3 (if any) describes the zip itself,
# not the extracted models; clear it so per-file header
# resolution applies to every extracted model.
metadata.autov3 = None
try:
os.remove(save_path)
except OSError as exc:
@@ -2235,7 +2313,7 @@ class DownloadManager:
entry, normalized_file_path, adjust_root
)
if adjusted_entry is not None:
entry = adjusted_entry
entry = cast(Any, adjusted_entry)
metadata_entries[index] = entry
metadata_file_path = (
@@ -2355,11 +2433,11 @@ class DownloadManager:
async def _build_metadata_entries(
self, base_metadata, file_paths: List[str]
) -> List:
) -> List[Any]:
if not file_paths:
return []
entries: List = []
entries: List[Any] = []
for index, file_path in enumerate(file_paths):
entry = base_metadata if index == 0 else copy.deepcopy(base_metadata)
# Update file paths without modifying size and modified timestamps
@@ -2374,6 +2452,16 @@ class DownloadManager:
sha256 = await calculate_sha256(file_path)
if sha256:
entry.sha256 = sha256.lower()
# AutoV3: the Civitai-reported value for the downloaded file (set
# by from_civitai_info) takes precedence. Only the un-checked
# state (None) triggers a header read; '' (checked-unavailable)
# is never re-read, honoring the three-state contract so rows
# marked at download time stay untouched by later passes.
if entry.autov3 is None:
autov3 = await asyncio.get_running_loop().run_in_executor(
None, calculate_autov3, file_path
)
entry.autov3 = (autov3 or "").lower()
entries.append(entry)
return entries
@@ -2392,7 +2480,7 @@ class DownloadManager:
return destination
def _distribute_preview_to_entries(
self, preview_path: str, entries: List
self, preview_path: str, entries: List[Any]
) -> List[str]:
if not preview_path or not entries:
return []
@@ -2451,7 +2539,7 @@ class DownloadManager:
progress_callback, normalized_snapshot, rounded_progress
)
async def cancel_download(self, download_id: str) -> Dict:
async def cancel_download(self, download_id: str) -> Dict[str, Any]:
"""Cancel an active download by download_id
Args:
@@ -2533,7 +2621,7 @@ class DownloadManager:
self._download_tasks.pop(download_id, None)
await self._aria2_state_store.remove(download_id)
async def skip_download(self, download_id: str) -> Dict:
async def skip_download(self, download_id: str) -> Dict[str, Any]:
"""Skip a download while preserving all partial files on disk.
Removes all in-memory tracking (asyncio task, semaphore, active/pause
@@ -2616,7 +2704,7 @@ class DownloadManager:
# Preserve aria2 state store entry so the partial download
# info survives restarts and can be resumed later
async def pause_download(self, download_id: str) -> Dict:
async def pause_download(self, download_id: str) -> Dict[str, Any]:
"""Pause an active download without losing progress."""
await self._restore_persisted_downloads()
@@ -2663,7 +2751,7 @@ class DownloadManager:
return {"success": True, "message": "Download paused successfully"}
async def resume_download(self, download_id: str) -> Dict:
async def resume_download(self, download_id: str) -> Dict[str, Any]:
"""Resume a previously paused download."""
await self._restore_persisted_downloads()
@@ -2680,7 +2768,7 @@ class DownloadManager:
self._pause_events[download_id] = pause_control
self._active_downloads[download_id] = self._build_restored_download_info(
persisted,
os.path.abspath(save_path),
os.path.abspath(cast(str, save_path)),
)
if pause_control.is_set():
@@ -2724,6 +2812,7 @@ class DownloadManager:
bool(persisted.get("use_default_paths", False)),
persisted.get("source"),
persisted.get("file_params"),
bool(persisted.get("use_save_dir_as_root", False)),
),
)
except Exception as exc:
@@ -2807,7 +2896,7 @@ class DownloadManager:
elif asyncio.iscoroutine(result):
await result
async def get_active_downloads(self) -> Dict:
async def get_active_downloads(self) -> Dict[str, Any]:
"""Get information about all active downloads
Returns:
@@ -1,3 +1,7 @@
# pyright: reportImportCycles=false
# Lazy (function-local) imports still count as static edges in basedpyright's
# reportImportCycles, so the ServiceRegistry singleton pattern necessarily forms
# import cycles. Breaking them would require an architectural refactor.
from __future__ import annotations
import asyncio
+13 -8
View File
@@ -1,3 +1,7 @@
# pyright: reportImportCycles=false
# Lazy (function-local) imports still count as static edges in basedpyright's
# reportImportCycles, so the ServiceRegistry singleton pattern necessarily forms
# import cycles. Breaking them would require an architectural refactor.
"""
Unified download manager for all HTTP/HTTPS downloads in the application.
@@ -20,7 +24,7 @@ from dataclasses import dataclass
from datetime import datetime, timedelta
from email.utils import parsedate_to_datetime
from urllib.parse import urlparse
from typing import Optional, Dict, Tuple, Callable, Union, Awaitable
from typing import Optional, Dict, Tuple, Callable, Union, Awaitable, Any, cast
from ..services.settings_manager import get_settings_manager
from .connectivity_guard import (
OFFLINE_COOLDOWN_ERROR,
@@ -204,6 +208,7 @@ class Downloader:
# Double check after acquiring lock
if self._session is None or self._should_refresh_session():
await self._create_session()
assert self._session is not None
return self._session
@property
@@ -231,7 +236,7 @@ class Downloader:
)
try:
timeout_value = float(raw_value)
timeout_value = float(cast(Any, raw_value))
except (TypeError, ValueError):
timeout_value = default_timeout
@@ -243,7 +248,7 @@ class Downloader:
raw_value = os.environ.get("COMFYUI_DOWNLOAD_MAX_RETRIES")
try:
retries = int(raw_value)
retries = int(cast(Any, raw_value))
except (TypeError, ValueError):
retries = default_retries
@@ -320,7 +325,7 @@ class Downloader:
# CA coverage across different Python environments (especially
# embedded/compatibility Python builds).
try:
import certifi # type: ignore[import-untyped]
import certifi # pyright: ignore[reportMissingTypeStubs]
ca_path = certifi.where()
ssl_context = ssl.create_default_context(cafile=ca_path)
@@ -330,7 +335,7 @@ class Downloader:
logger.debug("SSL: certifi unavailable; using system default CA bundle")
# Optimize TCP connection parameters
connector_kwargs = dict(
connector_kwargs: Dict[str, Any] = dict(
ssl=ssl_context,
limit=8, # Concurrent connections
ttl_dns_cache=300, # DNS cache timeout
@@ -890,7 +895,7 @@ class Downloader:
use_auth: bool = False,
custom_headers: Optional[Dict[str, str]] = None,
return_headers: bool = False,
) -> Tuple[bool, Union[bytes, str], Optional[Dict]]:
) -> Tuple[bool, Union[bytes, str], Optional[Dict[str, Any]]]:
"""
Download a file to memory (for small files like preview images)
@@ -976,7 +981,7 @@ class Downloader:
url: str,
use_auth: bool = False,
custom_headers: Optional[Dict[str, str]] = None,
) -> Tuple[bool, Union[Dict, str]]:
) -> Tuple[bool, Union[Dict[str, Any], str]]:
"""
Get response headers without downloading the full content
@@ -1036,7 +1041,7 @@ class Downloader:
use_auth: bool = False,
custom_headers: Optional[Dict[str, str]] = None,
**kwargs,
) -> Tuple[bool, Union[Dict, str]]:
) -> Tuple[bool, Union[Dict[str, Any], str, RateLimitError]]:
"""
Make a generic HTTP request and return JSON response
+1 -1
View File
@@ -27,7 +27,7 @@ class EmbeddingScanner(ModelScanner):
roots.extend(config.embeddings_roots or [])
roots.extend(config.extra_embeddings_roots or [])
# Remove duplicates while preserving order
seen: set = set()
seen: set[str] = set()
unique_roots: List[str] = []
for root in roots:
if root and root not in seen:
+28 -28
View File
@@ -1,6 +1,6 @@
import os
import logging
from typing import Dict, Optional
from typing import Any, Dict, Optional
from .base_model_service import BaseModelService
from .auto_tag_service import extract_auto_tags
@@ -21,58 +21,58 @@ class EmbeddingService(BaseModelService):
"""
super().__init__("embedding", scanner, EmbeddingMetadata, update_service=update_service)
async def format_response(self, embedding_data: Dict) -> Optional[Dict]:
async def format_response(self, model_data: Dict[str, Any]) -> Optional[Dict[str, Any]]:
"""Format Embedding data for API response.
Returns None when the entry is missing critical fields (corrupted cache
row), so the handler layer can filter it out. See issue #730.
"""
# Guard against corrupted cache entries missing critical fields
file_path = embedding_data.get("file_path")
file_path = model_data.get("file_path")
if not file_path or not isinstance(file_path, str):
logger.warning(
"Skipping corrupted embedding entry (missing file_path): %s",
embedding_data.get("file_name", "<unknown>"),
model_data.get("file_name", "<unknown>"),
)
return None
# Get sub_type from cache entry (new canonical field)
sub_type = embedding_data.get("sub_type", "embedding")
sub_type = model_data.get("sub_type", "embedding")
file_name = embedding_data.get("file_name") or ""
model_name = embedding_data.get("model_name") or file_name
folder = embedding_data.get("folder") or ""
file_name = model_data.get("file_name") or ""
model_name = model_data.get("model_name") or file_name
folder = model_data.get("folder") or ""
return {
"model_name": model_name,
"file_name": file_name,
"preview_url": config.get_preview_static_url(embedding_data.get("preview_url", "")),
"preview_nsfw_level": embedding_data.get("preview_nsfw_level", 0),
"base_model": embedding_data.get("base_model", ""),
"preview_url": config.get_preview_static_url(model_data.get("preview_url", "")),
"preview_nsfw_level": model_data.get("preview_nsfw_level", 0),
"base_model": model_data.get("base_model", ""),
"folder": folder,
"sha256": embedding_data.get("sha256", ""),
"sha256": model_data.get("sha256", ""),
"file_path": file_path.replace(os.sep, "/"),
"file_size": embedding_data.get("size", 0),
"modified": embedding_data.get("modified", ""),
"tags": embedding_data.get("tags", []),
"from_civitai": embedding_data.get("from_civitai", True),
# "usage_count": embedding_data.get("usage_count", 0), # TODO: Enable when embedding usage tracking is implemented
"notes": embedding_data.get("notes", ""),
"file_size": model_data.get("size", 0),
"modified": model_data.get("modified", ""),
"tags": model_data.get("tags", []),
"from_civitai": model_data.get("from_civitai", True),
# "usage_count": model_data.get("usage_count", 0), # TODO: Enable when embedding usage tracking is implemented
"notes": model_data.get("notes", ""),
"sub_type": sub_type,
"favorite": embedding_data.get("favorite", False),
"exclude": bool(embedding_data.get("exclude", False)),
"update_available": bool(embedding_data.get("update_available", False)),
"skip_metadata_refresh": bool(embedding_data.get("skip_metadata_refresh", False)),
"civitai": self.filter_civitai_data(embedding_data.get("civitai", {}), minimal=True),
"auto_tags": embedding_data.get("auto_tags") or extract_auto_tags(embedding_data),
"version_count": embedding_data.get("version_count"),
"hf_url": embedding_data.get("hf_url", ""),
"favorite": model_data.get("favorite", False),
"exclude": bool(model_data.get("exclude", False)),
"update_available": bool(model_data.get("update_available", False)),
"skip_metadata_refresh": bool(model_data.get("skip_metadata_refresh", False)),
"civitai": self.filter_civitai_data(model_data.get("civitai", {}), minimal=True),
"auto_tags": model_data.get("auto_tags") or extract_auto_tags(model_data),
"version_count": model_data.get("version_count"),
"hf_url": model_data.get("hf_url", ""),
}
def find_duplicate_hashes(self) -> Dict:
def find_duplicate_hashes(self) -> Dict[str, Any]:
"""Find Embeddings with duplicate SHA256 hashes"""
return self.scanner._hash_index.get_duplicate_hashes()
def find_duplicate_filenames(self) -> Dict:
def find_duplicate_filenames(self) -> Dict[str, Any]:
"""Find Embeddings with conflicting filenames"""
return self.scanner._hash_index.get_duplicate_filenames()
@@ -35,7 +35,7 @@ class CleanupResult:
def to_dict(self) -> Dict[str, object]:
"""Convert the dataclass to a serialisable dictionary."""
data = {
data: Dict[str, object] = {
"success": self.success,
"checked_folders": self.checked_folders,
"moved_empty_folders": self.moved_empty_folders,
+5
View File
@@ -201,6 +201,11 @@ PROVIDER_PRESETS: Dict[str, Dict[str, Any]] = {
"api_base": "https://openrouter.ai/api/v1",
"requires_key": True,
},
"google": {
"name": "Gemini",
"api_base": "https://generativelanguage.googleapis.com/v1beta/openai",
"requires_key": True,
},
"opencode-go": {
"name": "OpenCode Go",
"api_base": "https://opencode.ai/zen/go/v1",
+14 -4
View File
@@ -1,10 +1,12 @@
# pyright: reportImportCycles=false
# Lazy (function-local) imports still count as static edges in basedpyright's
# reportImportCycles, so the ServiceRegistry singleton pattern necessarily forms
# import cycles. Breaking them would require an architectural refactor.
import logging
from typing import List
from ..utils.models import LoraMetadata
from ..config import config
from .model_scanner import ModelScanner
from .model_hash_index import ModelHashIndex # Changed from LoraHashIndex to ModelHashIndex
import sys
logger = logging.getLogger(__name__)
@@ -15,8 +17,10 @@ class LoraScanner(ModelScanner):
def __init__(self):
# Define supported file extensions
file_extensions = {'.safetensors'}
# Initialize parent class with ModelHashIndex
from .model_hash_index import ModelHashIndex
super().__init__(
model_type="lora",
model_class=LoraMetadata,
@@ -26,11 +30,13 @@ class LoraScanner(ModelScanner):
def get_model_roots(self) -> List[str]:
"""Get lora root directories (including extra paths)"""
from ..config import config
roots: List[str] = []
roots.extend(config.loras_roots or [])
roots.extend(config.extra_loras_roots or [])
# Remove duplicates while preserving order
seen: set = set()
seen: set[str] = set()
unique_roots: List[str] = []
for root in roots:
if root and root not in seen:
@@ -68,8 +74,12 @@ class LoraScanner(ModelScanner):
test_hash = next(iter(self._hash_index._hash_to_path.keys()))
test_path = self._hash_index.get_path(test_hash)
logger.debug(f"\nTest lookup by hash: {test_hash[:8]}... -> {test_path}")
if test_path is None:
return
# Also test reverse lookup
test_hash_result = self._hash_index.get_hash(test_path)
if test_hash_result is None:
return
logger.debug(f"Test reverse lookup: {test_path} -> {test_hash_result[:8]}...\n\n")
+41 -41
View File
@@ -1,7 +1,7 @@
import logging
import json
import os
from typing import Dict, List, Optional
from typing import Any, Dict, List, Optional
from .base_model_service import BaseModelService
from .model_query import resolve_sub_type
@@ -24,7 +24,7 @@ class LoraService(BaseModelService):
"""
super().__init__("lora", scanner, LoraMetadata, update_service=update_service)
async def format_response(self, lora_data: Dict) -> Optional[Dict]:
async def format_response(self, model_data: Dict[str, Any]) -> Optional[Dict[str, Any]]:
"""Format LoRA data for API response.
Returns None when the entry is missing critical fields (corrupted cache
@@ -32,56 +32,56 @@ class LoraService(BaseModelService):
whole listing request. See issue #730.
"""
# Guard against corrupted cache entries missing critical fields
file_path = lora_data.get("file_path")
file_path = model_data.get("file_path")
if not file_path or not isinstance(file_path, str):
logger.warning(
"Skipping corrupted LoRA entry (missing file_path): %s",
lora_data.get("file_name", "<unknown>"),
model_data.get("file_name", "<unknown>"),
)
return None
# Resolve sub_type using priority: sub_type > model_type > civitai.model.type > default
# Normalize to lowercase for consistent API responses
sub_type = resolve_sub_type(lora_data).lower()
sub_type = resolve_sub_type(model_data).lower()
file_name = lora_data.get("file_name") or ""
model_name = lora_data.get("model_name") or file_name
folder = lora_data.get("folder") or ""
file_name = model_data.get("file_name") or ""
model_name = model_data.get("model_name") or file_name
folder = model_data.get("folder") or ""
return {
"model_name": model_name,
"file_name": file_name,
"preview_url": config.get_preview_static_url(
lora_data.get("preview_url", "")
model_data.get("preview_url", "")
),
"preview_nsfw_level": lora_data.get("preview_nsfw_level", 0),
"base_model": lora_data.get("base_model", ""),
"preview_nsfw_level": model_data.get("preview_nsfw_level", 0),
"base_model": model_data.get("base_model", ""),
"folder": folder,
"sha256": lora_data.get("sha256", ""),
"sha256": model_data.get("sha256", ""),
"file_path": file_path.replace(os.sep, "/"),
"file_size": lora_data.get("size", 0),
"modified": lora_data.get("modified", ""),
"tags": lora_data.get("tags", []),
"from_civitai": lora_data.get("from_civitai", True),
"usage_count": lora_data.get("usage_count", 0),
"usage_tips": lora_data.get("usage_tips", ""),
"notes": lora_data.get("notes", ""),
"favorite": lora_data.get("favorite", False),
"exclude": bool(lora_data.get("exclude", False)),
"update_available": bool(lora_data.get("update_available", False)),
"file_size": model_data.get("size", 0),
"modified": model_data.get("modified", ""),
"tags": model_data.get("tags", []),
"from_civitai": model_data.get("from_civitai", True),
"usage_count": model_data.get("usage_count", 0),
"usage_tips": model_data.get("usage_tips", ""),
"notes": model_data.get("notes", ""),
"favorite": model_data.get("favorite", False),
"exclude": bool(model_data.get("exclude", False)),
"update_available": bool(model_data.get("update_available", False)),
"skip_metadata_refresh": bool(
lora_data.get("skip_metadata_refresh", False)
model_data.get("skip_metadata_refresh", False)
),
"sub_type": sub_type,
"civitai": self.filter_civitai_data(
lora_data.get("civitai", {}), minimal=True
model_data.get("civitai", {}), minimal=True
),
"auto_tags": lora_data.get("auto_tags") or extract_auto_tags(lora_data),
"version_count": lora_data.get("version_count"),
"hf_url": lora_data.get("hf_url", ""),
"auto_tags": model_data.get("auto_tags") or extract_auto_tags(model_data),
"version_count": model_data.get("version_count"),
"hf_url": model_data.get("hf_url", ""),
}
async def _apply_specific_filters(self, data: List[Dict], **kwargs) -> List[Dict]:
async def _apply_specific_filters(self, data: List[Dict[str, Any]], **kwargs) -> List[Dict[str, Any]]:
"""Apply LoRA-specific filters"""
# Handle first_letter filter for LoRAs
first_letter = kwargs.get("first_letter")
@@ -152,7 +152,7 @@ class LoraService(BaseModelService):
return data
def _filter_by_first_letter(self, data: List[Dict], letter: str) -> List[Dict]:
def _filter_by_first_letter(self, data: List[Dict[str, Any]], letter: str) -> List[Dict[str, Any]]:
"""Filter data by first letter of model name
Special handling:
@@ -307,7 +307,7 @@ class LoraService(BaseModelService):
return None
@staticmethod
def get_recommended_strength_from_lora_data(lora_data: Dict) -> Optional[float]:
def get_recommended_strength_from_lora_data(lora_data: Dict[str, Any]) -> Optional[float]:
"""Parse usage_tips JSON and extract recommended model strength."""
try:
usage_tips = lora_data.get("usage_tips", "")
@@ -320,7 +320,7 @@ class LoraService(BaseModelService):
@staticmethod
def get_recommended_clip_strength_from_lora_data(
lora_data: Dict,
lora_data: Dict[str, Any],
) -> Optional[float]:
"""Parse usage_tips JSON and extract recommended clip strength."""
try:
@@ -332,7 +332,7 @@ class LoraService(BaseModelService):
except (json.JSONDecodeError, TypeError, AttributeError):
return None
async def get_lora_metadata_by_filename(self, filename: str) -> Optional[Dict]:
async def get_lora_metadata_by_filename(self, filename: str) -> Optional[Dict[str, Any]]:
"""Return cached raw metadata for a LoRA matching the given filename."""
cache = await self.scanner.get_cached_data(force_refresh=False)
@@ -357,11 +357,11 @@ class LoraService(BaseModelService):
return None
def find_duplicate_hashes(self) -> Dict:
def find_duplicate_hashes(self) -> Dict[str, Any]:
"""Find LoRAs with duplicate SHA256 hashes"""
return self.scanner._hash_index.get_duplicate_hashes()
def find_duplicate_filenames(self) -> Dict:
def find_duplicate_filenames(self) -> Dict[str, Any]:
"""Find LoRAs with conflicting filenames"""
return self.scanner._hash_index.get_duplicate_filenames()
@@ -373,8 +373,8 @@ class LoraService(BaseModelService):
use_same_clip_strength: bool = True,
clip_strength_min: float = 0.0,
clip_strength_max: float = 1.0,
locked_loras: Optional[List[Dict]] = None,
pool_config: Optional[Dict] = None,
locked_loras: Optional[List[Dict[str, Any]]] = None,
pool_config: Optional[Dict[str, Any]] = None,
count_mode: str = "fixed",
count_min: int = 3,
count_max: int = 7,
@@ -382,7 +382,7 @@ class LoraService(BaseModelService):
recommended_strength_scale_min: float = 0.5,
recommended_strength_scale_max: float = 1.0,
seed: Optional[int] = None,
) -> List[Dict]:
) -> List[Dict[str, Any]]:
"""
Get random LoRAs with specified strength ranges.
@@ -513,8 +513,8 @@ class LoraService(BaseModelService):
return result_loras
async def _apply_pool_filters(
self, available_loras: List[Dict], pool_config: Dict
) -> List[Dict]:
self, available_loras: List[Dict[str, Any]], pool_config: Dict[str, Any]
) -> List[Dict[str, Any]]:
"""
Apply pool_config filters to available LoRAs.
@@ -671,8 +671,8 @@ class LoraService(BaseModelService):
return available_loras
async def get_cycler_list(
self, pool_config: Optional[Dict] = None, sort_by: str = "filename"
) -> List[Dict]:
self, pool_config: Optional[Dict[str, Any]] = None, sort_by: str = "filename"
) -> List[Dict[str, Any]]:
"""
Get filtered and sorted LoRA list for cycling.
+5 -1
View File
@@ -1,3 +1,7 @@
# pyright: reportImportCycles=false
# Lazy (function-local) imports still count as static edges in basedpyright's
# reportImportCycles, so the ServiceRegistry singleton pattern necessarily forms
# import cycles. Breaking them would require an architectural refactor.
import os
import logging
from .model_metadata_provider import (
@@ -170,7 +174,7 @@ def _wrap_provider_with_rate_limit(provider_name: str | None, provider: ModelMet
return RateLimitRetryingProvider(provider, label=provider_name)
async def get_metadata_provider(provider_name: str = None):
async def get_metadata_provider(provider_name: str | None = None):
"""Get a specific metadata provider or default provider with rate-limit handling."""
provider_manager = await ModelMetadataProviderManager.get_instance()
+20 -7
View File
@@ -6,25 +6,26 @@ import json
import logging
import os
from datetime import datetime
from typing import Any, Awaitable, Callable, Dict, Iterable, Optional
from typing import Any, Awaitable, Callable, Dict, Iterable, Optional, Protocol
from ..services.settings_manager import SettingsManager
from ..utils.civitai_utils import resolve_license_payload
from ..utils.model_utils import determine_base_model
from ..utils.models import autov3_from_civitai_files
from .connectivity_guard import OFFLINE_FRIENDLY_MESSAGE, is_expected_offline_error
from .errors import RateLimitError
logger = logging.getLogger(__name__)
class MetadataProviderProtocol:
class MetadataProviderProtocol(Protocol):
"""Subset of metadata provider interface consumed by the sync service."""
async def get_model_by_hash(self, sha256: str) -> tuple[Optional[Dict[str, Any]], Optional[str]]:
async def get_model_by_hash(self, model_hash: str) -> tuple[Optional[Dict[str, Any]], Optional[str]]:
...
async def get_model_version(
self, model_id: int, model_version_id: Optional[int]
self, model_id: Any = None, version_id: Any = None
) -> Optional[Dict[str, Any]]:
...
@@ -38,8 +39,8 @@ class MetadataSyncService:
metadata_manager,
preview_service,
settings: SettingsManager,
default_metadata_provider_factory: Callable[[], Awaitable[MetadataProviderProtocol]],
metadata_provider_selector: Callable[[str], Awaitable[MetadataProviderProtocol]],
default_metadata_provider_factory: Callable[..., Awaitable[MetadataProviderProtocol]],
metadata_provider_selector: Callable[..., Awaitable[MetadataProviderProtocol]],
) -> None:
self._metadata_manager = metadata_manager
self._preview_service = preview_service
@@ -152,6 +153,18 @@ class MetadataSyncService:
civitai_metadata.get("baseModel")
)
# Civitai-first AutoV3 propagation: the freshly fetched version
# metadata may report an AutoV3 for the file whose SHA256 matches the
# local model. Persist it now so recipe matching sees it immediately —
# no full rescan or restart required (the header is never re-read to
# upgrade the checked-unavailable '' state).
sha256_value = (local_metadata.get("sha256") or "").lower()
civitai_autov3 = autov3_from_civitai_files(
local_metadata.get("civitai"), sha256_value
)
if civitai_autov3:
local_metadata["autov3"] = civitai_autov3
await self._preview_service.ensure_preview_for_metadata(
metadata_path, local_metadata, civitai_metadata.get("images", [])
)
@@ -479,7 +492,7 @@ class MetadataSyncService:
if not file_paths:
raise ValueError("No file paths provided for verification")
results = {
results: Dict[str, Any] = {
"verified_as_duplicates": True,
"mismatched_files": [],
"new_hash_map": {},
+21 -16
View File
@@ -31,17 +31,22 @@ DISPLAY_NAME_MODES = {"model_name", "file_name"}
class ModelCache:
"""Cache structure for model data with extensible sorting."""
raw_data: List[Dict]
raw_data: List[Dict[str, Any]]
folders: List[str]
version_index: Dict[int, Dict] = field(default_factory=dict)
version_index: Dict[int, Dict[str, Any]] = field(default_factory=dict)
model_id_index: Dict[int, List[Dict[str, Any]]] = field(default_factory=dict)
name_display_mode: str = "model_name"
_lock: Any = field(init=False, repr=False, default=None)
# Cache for last sort: (sort_key, order, seed) -> sorted list
_last_sort: Tuple[Optional[str], str, Optional[str]] = field(
init=False, repr=False, default=(None, "asc", None)
)
_last_sorted_data: List[Dict[str, Any]] = field(
init=False, repr=False, default_factory=list
)
def __post_init__(self):
self._lock = asyncio.Lock()
# Cache for last sort: (sort_key, order, seed) -> sorted list
self._last_sort: Tuple[Optional[str], str, Optional[str]] = (None, "asc", None)
self._last_sorted_data: List[Dict] = []
self._normalize_raw_data()
self.name_display_mode = self._normalize_display_mode(self.name_display_mode)
# Default sort on init
@@ -64,7 +69,7 @@ class ModelCache:
return ""
return str(value)
def _normalize_item(self, item: Dict) -> None:
def _normalize_item(self, item: Dict[str, Any]) -> None:
"""Ensure core metadata fields are present and string typed."""
if not isinstance(item, dict):
@@ -80,7 +85,7 @@ class ModelCache:
for item in self.raw_data:
self._normalize_item(item)
def _get_display_name(self, item: Dict) -> str:
def _get_display_name(self, item: Dict[str, Any]) -> str:
"""Return the value used for name-based sorting based on display settings."""
if self.name_display_mode == "file_name":
@@ -114,7 +119,7 @@ class ModelCache:
for item in self.raw_data:
self.add_to_version_index(item)
def add_to_version_index(self, item: Dict) -> None:
def add_to_version_index(self, item: Dict[str, Any]) -> None:
"""Register a cache item in the version/model indexes if possible."""
civitai_data = item.get('civitai') if isinstance(item, dict) else None
@@ -143,7 +148,7 @@ class ModelCache:
else:
versions.append(descriptor)
def remove_from_version_index(self, item: Dict) -> None:
def remove_from_version_index(self, item: Dict[str, Any]) -> None:
"""Remove a cache item from the version/model indexes if present."""
civitai_data = item.get('civitai') if isinstance(item, dict) else None
@@ -177,7 +182,7 @@ class ModelCache:
def _build_version_descriptor(
self,
item: Dict,
item: Dict[str, Any],
civitai_data: Dict[str, Any],
version_id: int,
) -> Optional[Dict[str, Any]]:
@@ -204,8 +209,8 @@ class ModelCache:
async def resort(self):
"""Resort cached data according to last sort mode if set"""
async with self._lock:
if self._last_sort[0] is not None:
sort_key, order, seed = self._last_sort
sort_key, order, seed = self._last_sort
if sort_key is not None:
sorted_data = self._sort_data(self.raw_data, sort_key, order, seed)
self._last_sorted_data = sorted_data
# Update folder list
@@ -219,7 +224,7 @@ class ModelCache:
self.folders = sorted(list(all_folders), key=lambda x: x.lower())
self.rebuild_version_index()
def _sort_data(self, data: List[Dict], sort_key: str, order: str, seed: Optional[str] = None) -> List[Dict]:
def _sort_data(self, data: List[Dict[str, Any]], sort_key: str, order: str, seed: Optional[str] = None) -> List[Dict[str, Any]]:
"""Sort data by sort_key and order"""
start_time = time.perf_counter()
reverse = (order == 'desc')
@@ -293,7 +298,7 @@ class ModelCache:
logger.debug("ModelCache._sort_data(%s, %s) for %d items took %.3fs", sort_key, order, len(data), duration)
return result
async def get_sorted_data(self, sort_key: str = 'name', order: str = 'asc', seed: Optional[str] = None) -> List[Dict]:
async def get_sorted_data(self, sort_key: str = 'name', order: str = 'asc', seed: Optional[str] = None) -> List[Dict[str, Any]]:
"""Get sorted data by sort_key and order, using cache if possible"""
async with self._lock:
cache_key = (sort_key, order, seed)
@@ -321,8 +326,8 @@ class ModelCache:
self.name_display_mode = normalized
if self._last_sort[0] == 'name':
sort_key, order, seed = self._last_sort
sort_key, order, seed = self._last_sort
if sort_key == 'name':
self._last_sorted_data = self._sort_data(self.raw_data, sort_key, order, seed)
async def update_preview_url(self, file_path: str, preview_url: str, preview_nsfw_level: int) -> bool:
+3 -1
View File
@@ -41,7 +41,7 @@ class AutoOrganizeResult:
def to_dict(self) -> Dict[str, Any]:
"""Convert result to dictionary"""
result = {
result: Dict[str, Any] = {
'success': self.status != 'error',
'status': self.status,
'message': f'Auto-organize {self.operation_type} completed: {self.success_count} moved, {self.skipped_count} skipped, {self.failure_count} failed out of {self.total} total',
@@ -418,6 +418,8 @@ class ModelFileService:
"""Calculate the target directory for a model"""
if is_flat_structure:
file_path = model.get('file_path')
if not isinstance(file_path, str):
return None
current_dir = os.path.dirname(file_path)
# Check if already in root directory
+53 -4
View File
@@ -8,11 +8,12 @@ class ModelHashIndex:
self._hash_to_path: Dict[str, str] = {}
self._filename_to_hash: Dict[str, str] = {}
self._autov2_to_path: Dict[str, str] = {}
self._autov3_to_path: Dict[str, str] = {}
# New data structures for tracking duplicates
self._duplicate_hashes: Dict[str, List[str]] = {} # sha256 -> list of paths
self._duplicate_filenames: Dict[str, List[str]] = {} # filename -> list of paths
def add_entry(self, sha256: str, file_path: str) -> None:
def add_entry(self, sha256: str, file_path: str, autov3: Optional[str] = None) -> None:
"""Add or update hash index entry"""
if not sha256 or not file_path:
return
@@ -33,9 +34,14 @@ class ModelHashIndex:
self._duplicate_hashes.setdefault(sha256, []).append(file_path)
# Track duplicates by filename - FIXED LOGIC
is_re_registration = False
existing_hash: Optional[str] = None
if filename in self._filename_to_hash:
existing_hash = self._filename_to_hash[filename]
existing_path = self._hash_to_path.get(existing_hash)
# Same path registered again (e.g. a file replaced in place with
# new content) — used below to drop its stale autov3 mapping.
is_re_registration = existing_path == file_path
# If this is a different file with the same filename
if existing_path and existing_path != file_path:
@@ -67,12 +73,36 @@ class ModelHashIndex:
# AutoV2 = first 10 chars of SHA256
if len(sha256) >= 10:
self._autov2_to_path[sha256[:10]] = file_path
# AutoV3 is an independent hash (not derived from SHA256), stored as-is.
# Drop stale mappings for a path when it is re-registered with a NEW
# sha256 (file replaced in place) or with an explicit new autov3 value
# (correction). Re-registering the SAME file with the same sha256 and
# no autov3 (e.g. lazy-hash completion) must never clear its existing
# mapping. First-time registrations stay O(1).
if autov3:
autov3 = autov3.lower()
if is_re_registration and (existing_hash != sha256 or autov3):
stale_autov3_keys = [
key for key, mapped_path in self._autov3_to_path.items()
if mapped_path == file_path and key != autov3
]
for key in stale_autov3_keys:
del self._autov3_to_path[key]
if autov3:
self._autov3_to_path[autov3] = file_path
def add_autov3(self, autov3: str, file_path: str) -> None:
"""Add or update an AutoV3-only index entry (used when only AutoV3 is known)"""
if not autov3:
return
autov3 = autov3.lower()
self._autov3_to_path[autov3] = file_path
def _get_filename_from_path(self, file_path: str) -> str:
"""Extract filename without extension from path"""
return os.path.splitext(os.path.basename(file_path))[0]
def remove_by_path(self, file_path: str, hash_val: str = None) -> None:
def remove_by_path(self, file_path: str, hash_val: Optional[str] = None) -> None:
"""Remove entry by file path"""
filename = self._get_filename_from_path(file_path)
@@ -167,6 +197,11 @@ class ModelHashIndex:
for k in autov2_keys_to_remove:
del self._autov2_to_path[k]
# Remove from AutoV3 index
autov3_keys_to_remove = [k for k, v in self._autov3_to_path.items() if v == file_path]
for k in autov3_keys_to_remove:
del self._autov3_to_path[k]
def remove_by_hash(self, sha256: str) -> None:
"""Remove entry by hash"""
sha256 = sha256.lower()
@@ -189,6 +224,11 @@ class ModelHashIndex:
autov2_key = sha256[:10]
if autov2_key in self._autov2_to_path:
del self._autov2_to_path[autov2_key]
# Remove AutoV3 entries pointing to any removed path
autov3_keys_to_remove = [k for k, v in self._autov3_to_path.items() if v in paths_to_remove]
for k in autov3_keys_to_remove:
del self._autov3_to_path[k]
# Update filename-to-hash and duplicate filenames for all paths
for path_to_remove in paths_to_remove:
@@ -209,22 +249,26 @@ class ModelHashIndex:
del self._duplicate_filenames[fname]
def has_hash(self, hash_value: str) -> bool:
"""Check if hash exists in index (SHA256 or AutoV2)"""
"""Check if hash exists in index (SHA256, AutoV2, or AutoV3)"""
normalized = hash_value.lower()
if normalized in self._hash_to_path:
return True
if len(normalized) == 10:
return normalized in self._autov2_to_path
if len(normalized) == 12:
return normalized in self._autov3_to_path
return False
def get_path(self, hash_value: str) -> Optional[str]:
"""Get file path for a hash (SHA256 or AutoV2)"""
"""Get file path for a hash (SHA256, AutoV2, or AutoV3)"""
normalized = hash_value.lower()
path = self._hash_to_path.get(normalized)
if path is not None:
return path
if len(normalized) == 10:
return self._autov2_to_path.get(normalized)
if len(normalized) == 12:
return self._autov3_to_path.get(normalized)
return None
def get_hash(self, file_path: str) -> Optional[str]:
@@ -243,6 +287,7 @@ class ModelHashIndex:
self._hash_to_path.clear()
self._filename_to_hash.clear()
self._autov2_to_path.clear()
self._autov3_to_path.clear()
self._duplicate_hashes.clear()
self._duplicate_filenames.clear()
@@ -253,6 +298,10 @@ class ModelHashIndex:
def get_all_filenames(self) -> Set[str]:
"""Get all filenames in the index"""
return set(self._filename_to_hash.keys())
def get_all_autov3(self) -> Dict[str, str]:
"""Get a snapshot of all AutoV3 hashes mapped to their file paths"""
return dict(self._autov3_to_path)
def get_duplicate_hashes(self) -> Dict[str, List[str]]:
"""Get dictionary of duplicate hashes and their paths"""
+36 -9
View File
@@ -4,9 +4,10 @@ from __future__ import annotations
import logging
import os
from typing import Any, Awaitable, Callable, Dict, Iterable, List, Mapping, Optional, TYPE_CHECKING
from typing import Any, Awaitable, Callable, Dict, Iterable, List, Mapping, Optional, TYPE_CHECKING, cast
from ..services.service_registry import ServiceRegistry
from ..services.pending_delete_service import get_pending_delete_service
from ..utils.constants import PREVIEW_EXTENSIONS
from ..utils.metadata_manager import MetadataManager
@@ -87,8 +88,8 @@ class ModelLifecycleService:
scanner,
metadata_manager,
metadata_loader: Callable[[str], Awaitable[Dict[str, object]]],
recipe_scanner_factory: Callable[[], Awaitable] | None = None,
update_service: "ModelUpdateService" | None = None,
recipe_scanner_factory: Callable[[], Awaitable[Any]] | None = None,
update_service: Optional["ModelUpdateService"] = None,
) -> None:
self._scanner = scanner
self._metadata_manager = metadata_manager
@@ -129,15 +130,33 @@ class ModelLifecycleService:
target_dir = os.path.dirname(file_path)
base_name = os.path.basename(file_path)
file_name, main_extension = os.path.splitext(base_name)
deleted_files = await delete_model_artifacts(
target_dir, file_name, main_extension=main_extension
# Stage the delete into the pending-delete service when undo is
# enabled; a successful stage renames the artifacts away, otherwise
# fall back to the direct hard delete.
pending_delete_service = await get_pending_delete_service()
batch_id = await pending_delete_service.stage_model_delete(
scanner=self._scanner,
target_dir=target_dir,
file_name=file_name,
main_extension=main_extension,
original_file_path=file_path,
cached_entry=cached_entry,
)
deleted_files: List[str] = []
if batch_id is None:
deleted_files = await delete_model_artifacts(
target_dir, file_name, main_extension=main_extension
)
if cache:
cache.raw_data = [
item for item in cache.raw_data if item.get("file_path") != file_path
]
await cache.resort()
bump_cache_version = getattr(self._scanner, "bump_cache_version", None)
if callable(bump_cache_version):
bump_cache_version()
if hasattr(self._scanner, "_hash_index") and self._scanner._hash_index:
self._scanner._hash_index.remove_by_path(file_path)
@@ -146,9 +165,13 @@ class ModelLifecycleService:
persist_current_cache = getattr(self._scanner, "_persist_current_cache", None)
if callable(persist_current_cache):
await persist_current_cache()
await cast(Awaitable[Any], persist_current_cache())
return {"success": True, "deleted_files": deleted_files}
return {
"success": True,
"deleted_files": deleted_files,
"batch_id": batch_id,
}
@staticmethod
def _extract_model_id_from_payload(payload: Any) -> Optional[int]:
@@ -244,6 +267,9 @@ class ModelLifecycleService:
item for item in cache.raw_data if item["file_path"] != file_path
]
await cache.resort()
bump_cache_version = getattr(self._scanner, "bump_cache_version", None)
if callable(bump_cache_version):
bump_cache_version()
excluded = getattr(self._scanner, "_excluded_models", None)
if isinstance(excluded, list):
@@ -252,7 +278,7 @@ class ModelLifecycleService:
persist_current_cache = getattr(self._scanner, "_persist_current_cache", None)
if callable(persist_current_cache):
await persist_current_cache()
await cast(Awaitable[Any], persist_current_cache())
message = f"Model {os.path.basename(file_path)} excluded"
return {"success": True, "message": message}
@@ -357,7 +383,8 @@ class ModelLifecycleService:
if os.path.exists(metadata_path):
metadata = await self._metadata_loader(metadata_path)
hash_value = metadata.get("sha256") if isinstance(metadata, dict) else None
raw_hash = metadata.get("sha256") if isinstance(metadata, dict) else None
hash_value = raw_hash if isinstance(raw_hash, str) else None
renamed_files: List[str] = []
new_metadata_path: Optional[str] = None
+52 -52
View File
@@ -10,7 +10,7 @@ from .errors import RateLimitError, ResourceNotFoundError
try:
from bs4 import BeautifulSoup
except ImportError as exc:
BeautifulSoup = None # type: ignore[assignment]
BeautifulSoup = None # pyright: ignore[reportAssignmentType]
_BS4_IMPORT_ERROR = exc
else:
_BS4_IMPORT_ERROR = None
@@ -18,7 +18,7 @@ else:
try:
import aiosqlite
except ImportError as exc:
aiosqlite = None # type: ignore[assignment]
aiosqlite = None # pyright: ignore[reportAssignmentType]
_AIOSQLITE_IMPORT_ERROR = exc
else:
_AIOSQLITE_IMPORT_ERROR = None
@@ -105,24 +105,24 @@ class ModelMetadataProvider(ABC):
"""Base abstract class for all model metadata providers"""
@abstractmethod
async def get_model_by_hash(self, model_hash: str) -> Tuple[Optional[Dict], Optional[str]]:
async def get_model_by_hash(self, model_hash: str) -> Tuple[Optional[Dict[str, Any]], Optional[str]]:
"""Find model by hash value"""
pass
@abstractmethod
async def get_model_versions(self, model_id: str) -> Optional[Dict]:
async def get_model_versions(self, model_id: str) -> Optional[Dict[str, Any]]:
"""Get all versions of a model with their details"""
pass
async def get_model_versions_bulk(
self, model_ids: Sequence[int]
) -> Optional[Dict[int, Dict]]:
) -> Optional[Dict[int, Dict[str, Any]]]:
"""Fetch model versions for multiple model ids when supported."""
raise NotImplementedError
async def get_model_versions_by_hashes(
self, hashes: List[str]
) -> Optional[List[Dict]]:
) -> Optional[List[Dict[str, Any]]]:
"""Fetch full version details for multiple SHA256 hashes.
Used specifically to retrieve ``usageControl`` which is only
@@ -133,17 +133,17 @@ class ModelMetadataProvider(ABC):
raise NotImplementedError
@abstractmethod
async def get_model_version(self, model_id: int = None, version_id: int = None) -> Optional[Dict]:
async def get_model_version(self, model_id: Optional[int] = None, version_id: Optional[int] = None) -> Optional[Dict[str, Any]]:
"""Get specific model version with additional metadata"""
pass
@abstractmethod
async def get_model_version_info(self, version_id: str) -> Tuple[Optional[Dict], Optional[str]]:
async def get_model_version_info(self, version_id: str) -> Tuple[Optional[Dict[str, Any]], Optional[str]]:
"""Fetch model version metadata"""
pass
@abstractmethod
async def get_user_models(self, username: str, cursor: Optional[str] = None) -> Optional[Dict]:
async def get_user_models(self, username: str, cursor: Optional[str] = None) -> Optional[Dict[str, Any]]:
"""Fetch one page of models owned by the specified user.
Returns ``{"items": [...], "nextCursor": <str|None>}`` on success,
@@ -161,29 +161,29 @@ class CivitaiModelMetadataProvider(ModelMetadataProvider):
def __init__(self, civitai_client):
self.client = civitai_client
async def get_model_by_hash(self, model_hash: str) -> Tuple[Optional[Dict], Optional[str]]:
async def get_model_by_hash(self, model_hash: str) -> Tuple[Optional[Dict[str, Any]], Optional[str]]:
return await self.client.get_model_by_hash(model_hash)
async def get_model_versions(self, model_id: str) -> Optional[Dict]:
async def get_model_versions(self, model_id: str) -> Optional[Dict[str, Any]]:
return await self.client.get_model_versions(model_id)
async def get_model_versions_bulk(
self, model_ids: Sequence[int]
) -> Optional[Dict[int, Dict]]:
) -> Optional[Dict[int, Dict[str, Any]]]:
return await self.client.get_model_versions_bulk(model_ids)
async def get_model_versions_by_hashes(
self, hashes: List[str]
) -> Optional[List[Dict]]:
) -> Optional[List[Dict[str, Any]]]:
return await self.client.get_model_versions_by_hashes(hashes)
async def get_model_version(self, model_id: int = None, version_id: int = None) -> Optional[Dict]:
async def get_model_version(self, model_id: Optional[int] = None, version_id: Optional[int] = None) -> Optional[Dict[str, Any]]:
return await self.client.get_model_version(model_id, version_id)
async def get_model_version_info(self, version_id: str) -> Tuple[Optional[Dict], Optional[str]]:
async def get_model_version_info(self, version_id: str) -> Tuple[Optional[Dict[str, Any]], Optional[str]]:
return await self.client.get_model_version_info(version_id)
async def get_user_models(self, username: str, cursor: Optional[str] = None) -> Optional[Dict]:
async def get_user_models(self, username: str, cursor: Optional[str] = None) -> Optional[Dict[str, Any]]:
return await self.client.get_user_models(username, cursor)
async def get_creator_model_count(self, username: str) -> Optional[int]:
@@ -195,19 +195,19 @@ class CivArchiveModelMetadataProvider(ModelMetadataProvider):
def __init__(self, civarchive_client):
self.client = civarchive_client
async def get_model_by_hash(self, model_hash: str) -> Tuple[Optional[Dict], Optional[str]]:
async def get_model_by_hash(self, model_hash: str) -> Tuple[Optional[Dict[str, Any]], Optional[str]]:
return await self.client.get_model_by_hash(model_hash)
async def get_model_versions(self, model_id: str) -> Optional[Dict]:
async def get_model_versions(self, model_id: str) -> Optional[Dict[str, Any]]:
return await self.client.get_model_versions(model_id)
async def get_model_version(self, model_id: int = None, version_id: int = None) -> Optional[Dict]:
async def get_model_version(self, model_id: Optional[int] = None, version_id: Optional[int] = None) -> Optional[Dict[str, Any]]:
return await self.client.get_model_version(model_id, version_id)
async def get_model_version_info(self, version_id: str) -> Tuple[Optional[Dict], Optional[str]]:
async def get_model_version_info(self, version_id: str) -> Tuple[Optional[Dict[str, Any]], Optional[str]]:
return await self.client.get_model_version_info(version_id)
async def get_user_models(self, username: str, cursor: Optional[str] = None) -> Optional[Dict]:
async def get_user_models(self, username: str, cursor: Optional[str] = None) -> Optional[Dict[str, Any]]:
"""Not supported by CivArchive provider"""
return None
@@ -218,7 +218,7 @@ class SQLiteModelMetadataProvider(ModelMetadataProvider):
self.db_path = db_path
self._aiosqlite = _require_aiosqlite()
async def get_model_by_hash(self, model_hash: str) -> Tuple[Optional[Dict], Optional[str]]:
async def get_model_by_hash(self, model_hash: str) -> Tuple[Optional[Dict[str, Any]], Optional[str]]:
"""Find model by hash value from SQLite database"""
async with self._aiosqlite.connect(self.db_path) as db:
# Look up in model_files table to get model_id and version_id
@@ -243,7 +243,7 @@ class SQLiteModelMetadataProvider(ModelMetadataProvider):
result = await self._get_version_with_model_data(db, model_id, version_id)
return result, None if result else "Error retrieving model data"
async def get_model_versions(self, model_id: str) -> Optional[Dict]:
async def get_model_versions(self, model_id: str) -> Optional[Dict[str, Any]]:
"""Get all versions of a model from SQLite database"""
async with self._aiosqlite.connect(self.db_path) as db:
db.row_factory = self._aiosqlite.Row
@@ -299,7 +299,7 @@ class SQLiteModelMetadataProvider(ModelMetadataProvider):
'name': model_name
}
async def get_model_version(self, model_id: int = None, version_id: int = None) -> Optional[Dict]:
async def get_model_version(self, model_id: Optional[int] = None, version_id: Optional[int] = None) -> Optional[Dict[str, Any]]:
"""Get specific model version with additional metadata from SQLite database"""
if not model_id and not version_id:
return None
@@ -339,7 +339,7 @@ class SQLiteModelMetadataProvider(ModelMetadataProvider):
# Now we have both model_id and version_id, get the full data
return await self._get_version_with_model_data(db, model_id, version_id)
async def get_model_version_info(self, version_id: str) -> Tuple[Optional[Dict], Optional[str]]:
async def get_model_version_info(self, version_id: str) -> Tuple[Optional[Dict[str, Any]], Optional[str]]:
"""Fetch model version metadata from SQLite database"""
async with self._aiosqlite.connect(self.db_path) as db:
db.row_factory = self._aiosqlite.Row
@@ -358,11 +358,11 @@ class SQLiteModelMetadataProvider(ModelMetadataProvider):
version_data = await self._get_version_with_model_data(db, model_id, version_id)
return version_data, None
async def get_user_models(self, username: str, cursor: Optional[str] = None) -> Optional[Dict]:
async def get_user_models(self, username: str, cursor: Optional[str] = None) -> Optional[Dict[str, Any]]:
"""Listing models by username is not supported for archive database"""
return None
async def _get_version_with_model_data(self, db, model_id, version_id) -> Optional[Dict]:
async def _get_version_with_model_data(self, db, model_id, version_id) -> Optional[Dict[str, Any]]:
"""Helper to build version data with model information"""
# Get version details
version_query = "SELECT name, base_model, data FROM model_versions WHERE id = ? AND model_id = ?"
@@ -485,7 +485,7 @@ class FallbackMetadataProvider(ModelMetadataProvider):
jitter_ratio=self._rate_limit_jitter_ratio,
)
async def get_model_by_hash(self, model_hash: str) -> Tuple[Optional[Dict], Optional[str]]:
async def get_model_by_hash(self, model_hash: str) -> Tuple[Optional[Dict[str, Any]], Optional[str]]:
for provider, label in self._iter_providers():
try:
result, error = await self._call_with_rate_limit(
@@ -507,7 +507,7 @@ class FallbackMetadataProvider(ModelMetadataProvider):
continue
return None, "Model not found"
async def get_model_versions(self, model_id: str) -> Optional[Dict]:
async def get_model_versions(self, model_id: str) -> Optional[Dict[str, Any]]:
not_found_confirmed = False
for provider, label in self._iter_providers():
try:
@@ -538,7 +538,7 @@ class FallbackMetadataProvider(ModelMetadataProvider):
continue
return None
async def get_model_version(self, model_id: int = None, version_id: int = None) -> Optional[Dict]:
async def get_model_version(self, model_id: Optional[int] = None, version_id: Optional[int] = None) -> Optional[Dict[str, Any]]:
for provider, label in self._iter_providers():
try:
result = await self._call_with_rate_limit(
@@ -561,7 +561,7 @@ class FallbackMetadataProvider(ModelMetadataProvider):
continue
return None
async def get_model_version_info(self, version_id: str) -> Tuple[Optional[Dict], Optional[str]]:
async def get_model_version_info(self, version_id: str) -> Tuple[Optional[Dict[str, Any]], Optional[str]]:
for provider, label in self._iter_providers():
try:
result, error = await self._call_with_rate_limit(
@@ -585,7 +585,7 @@ class FallbackMetadataProvider(ModelMetadataProvider):
async def get_model_versions_by_hashes(
self, hashes: List[str]
) -> Optional[List[Dict]]:
) -> Optional[List[Dict[str, Any]]]:
for provider, label in self._iter_providers():
try:
result = await self._call_with_rate_limit(
@@ -613,7 +613,7 @@ class FallbackMetadataProvider(ModelMetadataProvider):
continue
return None
async def get_user_models(self, username: str, cursor: Optional[str] = None) -> Optional[Dict]:
async def get_user_models(self, username: str, cursor: Optional[str] = None) -> Optional[Dict[str, Any]]:
for provider, label in self._iter_providers():
try:
result = await self._call_with_rate_limit(
@@ -681,14 +681,14 @@ class RateLimitRetryingProvider(ModelMetadataProvider):
def __getattr__(self, item):
return getattr(self._provider, item)
async def get_model_by_hash(self, model_hash: str) -> Tuple[Optional[Dict], Optional[str]]:
async def get_model_by_hash(self, model_hash: str) -> Tuple[Optional[Dict[str, Any]], Optional[str]]:
return await self._rate_limit_helper.run(
self._label,
self._provider.get_model_by_hash,
model_hash,
)
async def get_model_versions(self, model_id: str) -> Optional[Dict]:
async def get_model_versions(self, model_id: str) -> Optional[Dict[str, Any]]:
return await self._rate_limit_helper.run(
self._label,
self._provider.get_model_versions,
@@ -698,7 +698,7 @@ class RateLimitRetryingProvider(ModelMetadataProvider):
async def get_model_versions_bulk(
self,
model_ids: Sequence[int],
) -> Optional[Dict[int, Dict]]:
) -> Optional[Dict[int, Dict[str, Any]]]:
return await self._rate_limit_helper.run(
self._label,
self._provider.get_model_versions_bulk,
@@ -707,14 +707,14 @@ class RateLimitRetryingProvider(ModelMetadataProvider):
async def get_model_versions_by_hashes(
self, hashes: List[str]
) -> Optional[List[Dict]]:
) -> Optional[List[Dict[str, Any]]]:
return await self._rate_limit_helper.run(
self._label,
self._provider.get_model_versions_by_hashes,
hashes,
)
async def get_model_version(self, model_id: int = None, version_id: int = None) -> Optional[Dict]:
async def get_model_version(self, model_id: Optional[int] = None, version_id: Optional[int] = None) -> Optional[Dict[str, Any]]:
return await self._rate_limit_helper.run(
self._label,
self._provider.get_model_version,
@@ -722,14 +722,14 @@ class RateLimitRetryingProvider(ModelMetadataProvider):
version_id,
)
async def get_model_version_info(self, version_id: str) -> Tuple[Optional[Dict], Optional[str]]:
async def get_model_version_info(self, version_id: str) -> Tuple[Optional[Dict[str, Any]], Optional[str]]:
return await self._rate_limit_helper.run(
self._label,
self._provider.get_model_version_info,
version_id,
)
async def get_user_models(self, username: str, cursor: Optional[str] = None) -> Optional[Dict]:
async def get_user_models(self, username: str, cursor: Optional[str] = None) -> Optional[Dict[str, Any]]:
return await self._rate_limit_helper.run(
self._label,
self._provider.get_user_models,
@@ -762,12 +762,12 @@ class ModelMetadataProviderManager:
if is_default or self.default_provider is None:
self.default_provider = name
async def get_model_by_hash(self, model_hash: str, provider_name: str = None) -> Tuple[Optional[Dict], Optional[str]]:
async def get_model_by_hash(self, model_hash: str, provider_name: Optional[str] = None) -> Tuple[Optional[Dict[str, Any]], Optional[str]]:
"""Find model by hash using specified or default provider"""
provider = self._get_provider(provider_name)
return await provider.get_model_by_hash(model_hash)
async def get_model_versions(self, model_id: str, provider_name: str = None) -> Optional[Dict]:
async def get_model_versions(self, model_id: str, provider_name: Optional[str] = None) -> Optional[Dict[str, Any]]:
"""Get model versions using specified or default provider"""
provider = self._get_provider(provider_name)
return await provider.get_model_versions(model_id)
@@ -775,8 +775,8 @@ class ModelMetadataProviderManager:
async def get_model_versions_bulk(
self,
model_ids: Sequence[int],
provider_name: str = None,
) -> Optional[Dict[int, Dict]]:
provider_name: Optional[str] = None,
) -> Optional[Dict[int, Dict[str, Any]]]:
"""Fetch model versions for multiple model ids when supported by provider."""
provider = self._get_provider(provider_name)
try:
@@ -784,12 +784,12 @@ class ModelMetadataProviderManager:
except NotImplementedError:
return None
async def get_model_version(self, model_id: int = None, version_id: int = None, provider_name: str = None) -> Optional[Dict]:
async def get_model_version(self, model_id: Optional[int] = None, version_id: Optional[int] = None, provider_name: Optional[str] = None) -> Optional[Dict[str, Any]]:
"""Get specific model version using specified or default provider"""
provider = self._get_provider(provider_name)
return await provider.get_model_version(model_id, version_id)
async def get_model_version_info(self, version_id: str, provider_name: str = None) -> Tuple[Optional[Dict], Optional[str]]:
async def get_model_version_info(self, version_id: str, provider_name: Optional[str] = None) -> Tuple[Optional[Dict[str, Any]], Optional[str]]:
"""Fetch model version info using specified or default provider"""
provider = self._get_provider(provider_name)
return await provider.get_model_version_info(version_id)
@@ -797,8 +797,8 @@ class ModelMetadataProviderManager:
async def get_model_versions_by_hashes(
self,
hashes: List[str],
provider_name: str = None,
) -> Optional[List[Dict]]:
provider_name: Optional[str] = None,
) -> Optional[List[Dict[str, Any]]]:
provider = self._get_provider(provider_name)
try:
return await provider.get_model_versions_by_hashes(hashes)
@@ -808,19 +808,19 @@ class ModelMetadataProviderManager:
async def get_user_models(
self,
username: str,
provider_name: str = None,
provider_name: Optional[str] = None,
cursor: Optional[str] = None,
) -> Optional[Dict]:
) -> Optional[Dict[str, Any]]:
"""Fetch one page of models owned by the specified user"""
provider = self._get_provider(provider_name)
return await provider.get_user_models(username, cursor)
async def get_creator_model_count(self, username: str, provider_name: str = None) -> Optional[int]:
async def get_creator_model_count(self, username: str, provider_name: Optional[str] = None) -> Optional[int]:
"""Best-effort published model count for the specified user"""
provider = self._get_provider(provider_name)
return await provider.get_creator_model_count(username)
def _get_provider(self, provider_name: str = None) -> ModelMetadataProvider:
def _get_provider(self, provider_name: Optional[str] = None) -> ModelMetadataProvider:
"""Get provider by name or default provider"""
if provider_name:
if provider_name not in self.providers:
+2 -1
View File
@@ -12,6 +12,7 @@ from typing import (
Tuple,
Protocol,
Callable,
cast,
)
from ..utils.constants import NSFW_LEVELS
@@ -309,7 +310,7 @@ class ModelFilterSet:
else:
include_tags.add(normalized)
else:
include_tags = {tag.strip().lower() for tag in tag_filters if tag}
include_tags = {tag.strip().lower() for tag in cast(Iterable[Any], tag_filters) if tag}
if include_tags:
tag_logic = criteria.tag_logic.lower() if criteria.tag_logic else "any"

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