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Author SHA1 Message Date
Luke Mino-Altherr
fa3749ced7 Add TypedDict types to scanner and bulk_ingest
Amp-Thread-ID: https://ampcode.com/threads/T-019c2af9-4d41-73e9-b38d-78d06bc28a3f
Co-authored-by: Amp <amp@ampcode.com>
2026-02-04 15:32:26 -08:00
Luke Mino-Altherr
16b5d9112b Fix path traversal validation to return 400 instead of 500
Catch ValueError from resolve_destination_from_tags in the upload
endpoint so that invalid path components like '..' return a 400
BAD_REQUEST error instead of falling through to the 500 handler.

Amp-Thread-ID: https://ampcode.com/threads/T-019c2af2-7c87-7263-88b0-9feca1c31b3c
Co-authored-by: Amp <amp@ampcode.com>
2026-02-04 15:24:51 -08:00
Luke Mino-Altherr
abeec3072b refactor(assets): extract scanner logic into service modules
- Create file_utils.py with shared file utilities:
  - get_mtime_ns() - extract mtime in nanoseconds from stat
  - get_size_and_mtime_ns() - get both size and mtime
  - verify_file_unchanged() - check file matches DB mtime/size
  - list_files_recursively() - recursive directory listing

- Create bulk_ingest.py for bulk operations:
  - BulkInsertResult dataclass
  - batch_insert_seed_assets() - batch insert with conflict handling
  - prune_orphaned_assets() - clean up orphaned assets

- Update scanner.py to use new service modules instead of
  calling database queries directly

- Update ingest.py to use shared get_size_and_mtime_ns()

- Export new functions from services/__init__.py

Amp-Thread-ID: https://ampcode.com/threads/T-019c2ae7-f701-716a-a0dd-1feb988732fb
Co-authored-by: Amp <amp@ampcode.com>
2026-02-04 15:17:31 -08:00
Luke Mino-Altherr
b23302f372 refactor(assets): consolidate duplicated query utilities and remove unused code
- Extract shared helpers to database/queries/common.py:
  - MAX_BIND_PARAMS, calculate_rows_per_statement, iter_chunks, iter_row_chunks
  - build_visible_owner_clause

- Remove duplicate _compute_filename_for_asset, consolidate in path_utils.py

- Remove unused get_asset_info_with_tags (duplicated get_asset_detail)

- Remove redundant __all__ from cache_state.py

- Make internal helpers private (_check_is_scalar)

Amp-Thread-ID: https://ampcode.com/threads/T-019c2ad9-9432-7451-94a8-79287dbbb19e
Co-authored-by: Amp <amp@ampcode.com>
2026-02-04 15:04:30 -08:00
Luke Mino-Altherr
adf6eb73fd refactor: eliminate manager layer, routes call services directly
- Delete app/assets/manager.py
- Move upload logic (upload_from_temp_path, create_from_hash) to ingest service
- Add HashMismatchError and DependencyMissingError to ingest service
- Add UploadResult schema for upload responses
- Update routes.py to import services directly and do schema conversion inline
- Add asset lookup/listing service functions to asset_management.py

Routes now call the service layer directly, removing an unnecessary
layer of indirection. The manager was only converting between service
dataclasses and Pydantic response schemas.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-04 14:50:11 -08:00
Luke Mino-Altherr
5259959fef refactor: require blake3 package directly in hashing module
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-03 20:42:11 -08:00
Luke Mino-Altherr
5474d8bf84 chore: consolidate service imports in manager.py
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-03 20:36:06 -08:00
Luke Mino-Altherr
9290e26e9f refactor: add explicit types to asset service functions
- Add typed result dataclasses: IngestResult, AddTagsResult,
  RemoveTagsResult, SetTagsResult, TagUsage
- Add UserMetadata type alias for user_metadata parameters
- Type helper functions with Session parameters
- Use TypedDicts at query layer to avoid circular imports
- Update manager.py and tests to use attribute access

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-03 20:32:14 -08:00
Luke Mino-Altherr
37ecc5b663 chore: remove obvious/self-documenting comments from assets package
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-03 20:14:11 -08:00
Luke Mino-Altherr
80d99e7b63 chore: remove module-level comments and docstrings from assets package
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-03 20:04:47 -08:00
Luke Mino-Altherr
d8cb122dfb chore: sort imports in assets package
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-03 20:02:52 -08:00
Luke Mino-Altherr
0f75def5b5 refactor: move scanner.py out of services to top-level assets module
Scanner is used externally by main.py and server.py for startup/maintenance,
not as part of the regular service layer. Moving it to app/assets/scanner.py
makes the public API clearer.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-03 19:56:29 -08:00
Luke Mino-Altherr
6b1f9f7755 refactor: convert asset tests to table-driven parametrized tests
- test_metadata.py: consolidate 7 filter type classes into parametrized tests
- test_asset.py: parametrize exists, get, and upsert test cases
- test_cache_state.py: parametrize upsert and delete scenarios
- test_crud.py: consolidate error response tests into single parametrized test
- test_list_filter.py: consolidate invalid query tests

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-03 19:50:16 -08:00
Luke Mino-Altherr
3311b13740 chore: remove unused re-exports from conftest.py
The helper functions are already imported directly from helpers.py
by all test files, so the backwards compatibility re-export is dead code.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-03 19:22:24 -08:00
Luke Mino-Altherr
bf7fbb6317 chore: remove unused get_utc_now import
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-03 18:47:11 -08:00
Luke Mino-Altherr
5571508e61 refactor: use query functions instead of direct ORM modifications in service layer
Add update_asset_info_name and update_asset_info_updated_at query functions
and update asset_management.py to use them instead of modifying ORM objects
directly. This ensures the service layer only uses explicit operations from
the queries package.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-03 18:44:23 -08:00
Luke Mino-Altherr
e3b8e512ca refactor: use explicit dataclasses instead of ORM objects in service layer
Replace dict/ORM object returns with explicit dataclasses to fix
DetachedInstanceError when accessing ORM attributes after session closes.

- Add app/assets/services/schemas.py with AssetData, AssetInfoData,
  AssetDetailResult, and RegisterAssetResult dataclasses
- Update asset_management.py and ingest.py to return dataclasses
- Update manager.py to use attribute access on dataclasses
- Fix created_new to be False in create_asset_from_hash (content exists)
- Add DependencyMissingError for better blake3 missing error handling
- Update tests to use attribute access instead of dict subscripting

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-03 18:39:07 -08:00
Luke Mino-Altherr
ea01cd665d fix: resolve test import errors and module collision in assets_test
Extract helper functions from conftest.py to a dedicated helpers.py module
to fix import resolution issues when pytest processes subdirectories.
Rename test_tags.py to test_tags_api.py to avoid module name collision
with queries/test_tags.py.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-03 14:57:52 -08:00
Luke Mino-Altherr
ccfc5dedd4 fix: handle missing blake3 module gracefully to prevent server crash
Make blake3 an optional import that fails gracefully at import time,
with a clear error message when hashing functions are actually called.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-03 14:46:33 -08:00
Luke Mino-Altherr
e9ca190098 refactor: remove try-finally wrapper in seed_assets by extracting helpers
Extract focused helper functions to eliminate the try-finally block that
wrapped ~50 lines just for logging. The new helpers (_collect_paths_for_roots,
_build_asset_specs, _insert_asset_specs) make seed_assets a simple linear flow.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-03 14:33:54 -08:00
Luke Mino-Altherr
ed60e93696 refactor: flatten nested try blocks and if statements in assets package
Extract helper functions to eliminate nested try-except blocks in scanner.py
and remove duplicated type-checking logic in asset_info.py. Simplify nested
conditionals in asset_management.py for clearer control flow.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-03 14:28:16 -08:00
Luke Mino-Altherr
fef2f01671 refactor: improve function naming for clarity and consistency
Rename functions to use clearer verb-based names:
- pick_best_live_path → select_best_live_path
- escape_like_prefix → escape_sql_like_string
- list_tree → list_files_recursively
- check_asset_file_fast → verify_asset_file_unchanged
- _seed_from_paths_batch → _batch_insert_assets_from_paths
- reconcile_cache_states_for_root → sync_cache_states_with_filesystem
- touch_asset_info_by_id → update_asset_info_access_time
- replace_asset_info_metadata_projection → set_asset_info_metadata
- expand_metadata_to_rows → convert_metadata_to_rows
- _rows_per_stmt → _calculate_rows_per_statement
- ensure_within_base → validate_path_within_base
- _cleanup_temp → _delete_temp_file_if_exists
- validate_hash_format → normalize_and_validate_hash
- get_relative_to_root_category_path_of_asset → get_asset_category_and_relative_path

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-03 14:20:36 -08:00
Luke Mino-Altherr
481a2fa263 refactor: rename functions to verb-based naming convention
Rename functions across app/assets/ to follow verb-based naming:
- is_scalar → check_is_scalar
- project_kv → expand_metadata_to_rows
- _visible_owner_clause → _build_visible_owner_clause
- _chunk_rows → _iter_row_chunks
- _at_least_one → _validate_at_least_one_field
- _tags_norm → _normalize_tags_field
- _ser_dt → _serialize_datetime
- _ser_updated → _serialize_updated_at
- _error_response → _build_error_response
- _validation_error_response → _build_validation_error_response
- file_sender → stream_file_chunks
- seed_assets_endpoint → seed_assets
- utcnow → get_utc_now
- _safe_sort_field → _validate_sort_field
- _safe_filename → _sanitize_filename
- fast_asset_file_check → check_asset_file_fast
- prefixes_for_root → get_prefixes_for_root
- blake3_hash → compute_blake3_hash
- blake3_hash_async → compute_blake3_hash_async
- _is_within → _check_is_within
- _rel → _compute_relative

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-03 13:58:14 -08:00
Luke Mino-Altherr
11ca1995a3 fix: remaining ruff linting errors in services tests
- Remove unused os imports in conftest.py and test_ingest.py
- Remove unused Tag import in test_asset_management.py
- Remove unused ensure_tags_exist import in test_ingest.py
- Fix unused info2 variable in test_asset_management.py

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-03 13:31:38 -08:00
Luke Mino-Altherr
4e02245012 fix: ruff linting errors and add comprehensive test coverage for asset queries
- Fix unused imports in routes.py, asset.py, manager.py, asset_management.py, ingest.py
- Fix whitespace issues in upload.py, asset_info.py, ingest.py
- Fix typo in manager.py (stray character after result["asset"])
- Fix broken import in test_metadata.py (project_kv moved to asset_info.py)
- Add fixture override in queries/conftest.py for unit test isolation

Add 48 new tests covering all previously untested query functions:
- asset.py: upsert_asset, bulk_insert_assets
- cache_state.py: upsert_cache_state, delete_cache_states_outside_prefixes,
  get_orphaned_seed_asset_ids, delete_assets_by_ids, get_cache_states_for_prefixes,
  bulk_set_needs_verify, delete_cache_states_by_ids, delete_orphaned_seed_asset,
  bulk_insert_cache_states_ignore_conflicts, get_cache_states_by_paths_and_asset_ids
- asset_info.py: insert_asset_info, get_or_create_asset_info,
  update_asset_info_timestamps, replace_asset_info_metadata_projection,
  bulk_insert_asset_infos_ignore_conflicts, get_asset_info_ids_by_ids
- tags.py: bulk_insert_tags_and_meta

Total: 119 tests pass (up from 71)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-03 13:21:12 -08:00
Luke Mino-Altherr
9f9db2c2c2 refactor: extract multipart upload parsing from routes
- Add app/assets/api/upload.py with parse_multipart_upload() for HTTP parsing
- Add ParsedUpload dataclass to schemas_in.py
- Add domain exceptions (AssetValidationError, AssetNotFoundError, HashMismatchError)
- Add manager.process_upload() with domain exceptions (no HTTP status codes)
- Routes map domain exceptions to HTTP responses
- Slim down upload_asset route to ~20 lines (was ~150)

Amp-Thread-ID: https://ampcode.com/threads/T-019c2519-abe1-738a-ad2e-29ece17c0e42
Co-authored-by: Amp <amp@ampcode.com>
2026-02-03 13:08:04 -08:00
Luke Mino-Altherr
e987bd268f Move get_comfy_models_folders to path_utils.py to avoid late import
Amp-Thread-ID: https://ampcode.com/threads/T-019c2510-33fa-7199-ae4b-bc31102277a7
Co-authored-by: Amp <amp@ampcode.com>
2026-02-03 13:08:04 -08:00
Luke Mino-Altherr
2eb100adf9 Refactor helpers.py: move functions to their respective modules
- Move scanner-only functions to scanner.py
- Move query-only functions (is_scalar, project_kv) to asset_info.py
- Move get_query_dict to routes.py
- Create path_utils.py service for path-related functions
- Reduce helpers.py to shared utilities only

Amp-Thread-ID: https://ampcode.com/threads/T-019c2510-33fa-7199-ae4b-bc31102277a7
Co-authored-by: Amp <amp@ampcode.com>
2026-02-03 13:08:04 -08:00
Luke Mino-Altherr
a02f160e20 Move hashing.py to services directory
Amp-Thread-ID: https://ampcode.com/threads/T-019c2510-33fa-7199-ae4b-bc31102277a7
Co-authored-by: Amp <amp@ampcode.com>
2026-02-03 13:08:04 -08:00
Luke Mino-Altherr
c3105b1174 refactor: move bulk_ops to queries and scanner service
- Delete bulk_ops.py, moving logic to appropriate layers
- Add bulk insert query functions:
  - queries/asset.bulk_insert_assets
  - queries/cache_state.bulk_insert_cache_states_ignore_conflicts
  - queries/cache_state.get_cache_states_by_paths_and_asset_ids
  - queries/asset_info.bulk_insert_asset_infos_ignore_conflicts
  - queries/asset_info.get_asset_info_ids_by_ids
  - queries/tags.bulk_insert_tags_and_meta
- Move seed_from_paths_batch orchestration to scanner._seed_from_paths_batch

Amp-Thread-ID: https://ampcode.com/threads/T-019c24fd-157d-776a-ad24-4f19cf5d3afe
Co-authored-by: Amp <amp@ampcode.com>
2026-02-03 13:08:04 -08:00
Luke Mino-Altherr
64d2f51dfc refactor: move scanner to services layer with pure query extraction
- Move app/assets/scanner.py to app/assets/services/scanner.py
- Extract pure queries from fast_db_consistency_pass:
  - get_cache_states_for_prefixes()
  - bulk_set_needs_verify()
  - delete_cache_states_by_ids()
  - delete_orphaned_seed_asset()
- Split prune_orphaned_assets into pure queries:
  - delete_cache_states_outside_prefixes()
  - get_orphaned_seed_asset_ids()
  - delete_assets_by_ids()
- Add reconcile_cache_states_for_root() service function
- Add prune_orphaned_assets() service function
- Remove function injection pattern
- Update imports in main.py, server.py, routes.py

Amp-Thread-ID: https://ampcode.com/threads/T-019c24f1-3385-701b-87e0-8b6bc87e841b
Co-authored-by: Amp <amp@ampcode.com>
2026-02-03 13:08:04 -08:00
Luke Mino-Altherr
fba4570e49 refactor: move in-function imports to top-level and remove keyword-only argument pattern
- Move imports from inside functions to module top-level in:
  - app/assets/database/queries/asset.py
  - app/assets/database/queries/asset_info.py
  - app/assets/database/queries/cache_state.py
  - app/assets/manager.py
  - app/assets/services/asset_management.py
  - app/assets/services/ingest.py

- Remove keyword-only argument markers (*,) from app/assets/ to match codebase conventions

Amp-Thread-ID: https://ampcode.com/threads/T-019c24eb-bfa2-727f-8212-8bc976048604
Co-authored-by: Amp <amp@ampcode.com>
2026-02-03 13:08:04 -08:00
Luke Mino-Altherr
15ee03f65c Refactor asset database: separate business logic from queries
Architecture changes:
- API Routes -> manager.py (thin adapter) -> services/ (business logic) -> queries/ (atomic DB ops)
- Services own session lifecycle via create_session()
- Queries accept Session as parameter, do single-table atomic operations

New app/assets/services/ layer:
- __init__.py - exports all service functions
- ingest.py - ingest_file_from_path(), register_existing_asset()
- asset_management.py - get_asset_detail(), update_asset_metadata(), delete_asset_reference(), set_asset_preview()
- tagging.py - apply_tags(), remove_tags(), list_tags()

Removed from queries/asset_info.py:
- ingest_fs_asset (moved to services/ingest.py as ingest_file_from_path)
- update_asset_info_full (moved to services/asset_management.py as update_asset_metadata)
- create_asset_info_for_existing_asset (moved to services/ingest.py as register_existing_asset)

Updated manager.py:
- Now a thin adapter that transforms API schemas to/from service calls
- Delegates all business logic to services layer
- No longer imports sqlalchemy.orm.Session or models directly

Test updates:
- Fixed test_cache_state.py import of pick_best_live_path (moved to helpers.py)
- Added comprehensive service layer tests (41 new tests)
- All 112 query + service tests pass

Amp-Thread-ID: https://ampcode.com/threads/T-019c24e2-7ae4-707f-ad19-c775ed8b82b5
Co-authored-by: Amp <amp@ampcode.com>
2026-02-03 13:08:04 -08:00
Luke Mino-Altherr
70a600baf0 chore: remove unused Asset import from manager.py
Amp-Thread-ID: https://ampcode.com/threads/T-019c24bb-475b-7442-9ff9-8288edea3345
Co-authored-by: Amp <amp@ampcode.com>
2026-02-03 13:08:04 -08:00
Luke Mino-Altherr
17ad7e393f refactor(assets): split queries.py into modular query modules
Split the ~1000 line app/assets/database/queries.py into focused modules:

- queries/asset.py - Asset entity queries (asset_exists_by_hash, get_asset_by_hash)
- queries/asset_info.py - AssetInfo queries (~15 functions)
- queries/cache_state.py - AssetCacheState queries (list_cache_states_by_asset_id,
  pick_best_live_path, prune_orphaned_assets, fast_db_consistency_pass)
- queries/tags.py - Tag queries (8 functions including ensure_tags_exist,
  add/remove tag functions, list_tags_with_usage)
- queries/__init__.py - Re-exports all public functions for backward compatibility

Also adds comprehensive unit tests using in-memory SQLite:
- tests-unit/assets_test/queries/conftest.py - Session fixture
- tests-unit/assets_test/queries/test_asset.py - 5 tests
- tests-unit/assets_test/queries/test_asset_info.py - 23 tests
- tests-unit/assets_test/queries/test_cache_state.py - 8 tests
- tests-unit/assets_test/queries/test_metadata.py - 12 tests for _apply_metadata_filter
- tests-unit/assets_test/queries/test_tags.py - 23 tests

All 71 unit tests pass. Existing integration tests unaffected.

Amp-Thread-ID: https://ampcode.com/threads/T-019c24bb-475b-7442-9ff9-8288edea3345
Co-authored-by: Amp <amp@ampcode.com>
2026-02-03 13:08:04 -08:00
256 changed files with 7648 additions and 12326 deletions

View File

@@ -1,127 +0,0 @@
# yaml-language-server: $schema=https://coderabbit.ai/integrations/schema.v2.json
language: "en-US"
early_access: false
tone_instructions: "Only comment on issues introduced by this PR's changes. Do not flag pre-existing problems in moved, re-indented, or reformatted code."
reviews:
profile: "chill"
request_changes_workflow: false
high_level_summary: false
poem: false
review_status: false
review_details: false
commit_status: true
collapse_walkthrough: true
changed_files_summary: false
sequence_diagrams: false
estimate_code_review_effort: false
assess_linked_issues: false
related_issues: false
related_prs: false
suggested_labels: false
auto_apply_labels: false
suggested_reviewers: false
auto_assign_reviewers: false
in_progress_fortune: false
enable_prompt_for_ai_agents: true
path_filters:
- "!comfy_api_nodes/apis/**"
- "!**/generated/*.pyi"
- "!.ci/**"
- "!script_examples/**"
- "!**/__pycache__/**"
- "!**/*.ipynb"
- "!**/*.png"
- "!**/*.bat"
path_instructions:
- path: "**"
instructions: |
IMPORTANT: Only comment on issues directly introduced by this PR's code changes.
Do NOT flag pre-existing issues in code that was merely moved, re-indented,
de-indented, or reformatted without logic changes. If code appears in the diff
only due to whitespace or structural reformatting (e.g., removing a `with:` block),
treat it as unchanged. Contributors should not feel obligated to address
pre-existing issues outside the scope of their contribution.
- path: "comfy/**"
instructions: |
Core ML/diffusion engine. Focus on:
- Backward compatibility (breaking changes affect all custom nodes)
- Memory management and GPU resource handling
- Performance implications in hot paths
- Thread safety for concurrent execution
- path: "comfy_api_nodes/**"
instructions: |
Third-party API integration nodes. Focus on:
- No hardcoded API keys or secrets
- Proper error handling for API failures (timeouts, rate limits, auth errors)
- Correct Pydantic model usage
- Security of user data passed to external APIs
- path: "comfy_extras/**"
instructions: |
Community-contributed extra nodes. Focus on:
- Consistency with node patterns (INPUT_TYPES, RETURN_TYPES, FUNCTION, CATEGORY)
- No breaking changes to existing node interfaces
- path: "comfy_execution/**"
instructions: |
Execution engine (graph execution, caching, jobs). Focus on:
- Caching correctness
- Concurrent execution safety
- Graph validation edge cases
- path: "nodes.py"
instructions: |
Core node definitions (2500+ lines). Focus on:
- Backward compatibility of NODE_CLASS_MAPPINGS
- Consistency of INPUT_TYPES return format
- path: "alembic_db/**"
instructions: |
Database migrations. Focus on:
- Migration safety and rollback support
- Data preservation during schema changes
auto_review:
enabled: true
auto_incremental_review: true
drafts: false
ignore_title_keywords:
- "WIP"
- "DO NOT REVIEW"
- "DO NOT MERGE"
finishing_touches:
docstrings:
enabled: false
unit_tests:
enabled: false
tools:
ruff:
enabled: false
pylint:
enabled: false
flake8:
enabled: false
gitleaks:
enabled: true
shellcheck:
enabled: false
markdownlint:
enabled: false
yamllint:
enabled: false
languagetool:
enabled: false
github-checks:
enabled: true
timeout_ms: 90000
ast-grep:
essential_rules: true
chat:
auto_reply: true
knowledge_base:
opt_out: false
learnings:
scope: "auto"

View File

@@ -7,8 +7,6 @@ on:
jobs:
send-webhook:
runs-on: ubuntu-latest
env:
DESKTOP_REPO_DISPATCH_TOKEN: ${{ secrets.DESKTOP_REPO_DISPATCH_TOKEN }}
steps:
- name: Send release webhook
env:
@@ -108,37 +106,3 @@ jobs:
--fail --silent --show-error
echo "✅ Release webhook sent successfully"
- name: Send repository dispatch to desktop
env:
DISPATCH_TOKEN: ${{ env.DESKTOP_REPO_DISPATCH_TOKEN }}
RELEASE_TAG: ${{ github.event.release.tag_name }}
RELEASE_URL: ${{ github.event.release.html_url }}
run: |
set -euo pipefail
if [ -z "${DISPATCH_TOKEN:-}" ]; then
echo "::error::DESKTOP_REPO_DISPATCH_TOKEN is required but not set."
exit 1
fi
PAYLOAD="$(jq -n \
--arg release_tag "$RELEASE_TAG" \
--arg release_url "$RELEASE_URL" \
'{
event_type: "comfyui_release_published",
client_payload: {
release_tag: $release_tag,
release_url: $release_url
}
}')"
curl -fsSL \
-X POST \
-H "Accept: application/vnd.github+json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DISPATCH_TOKEN}" \
https://api.github.com/repos/Comfy-Org/desktop/dispatches \
-d "$PAYLOAD"
echo "✅ Dispatched ComfyUI release ${RELEASE_TAG} to Comfy-Org/desktop"

2
.gitignore vendored
View File

@@ -11,7 +11,7 @@ extra_model_paths.yaml
/.vs
.vscode/
.idea/
venv*/
venv/
.venv/
/web/extensions/*
!/web/extensions/logging.js.example

View File

@@ -227,11 +227,11 @@ Put your VAE in: models/vae
AMD users can install rocm and pytorch with pip if you don't have it already installed, this is the command to install the stable version:
```pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm7.1```
```pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.4```
This is the command to install the nightly with ROCm 7.2 which might have some performance improvements:
This is the command to install the nightly with ROCm 7.1 which might have some performance improvements:
```pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/rocm7.2```
```pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/rocm7.1```
### AMD GPUs (Experimental: Windows and Linux), RDNA 3, 3.5 and 4 only.

View File

@@ -1,19 +1,36 @@
import logging
import uuid
import urllib.parse
import os
import contextlib
from aiohttp import web
import urllib.parse
import uuid
from typing import Any
from aiohttp import web
from pydantic import ValidationError
import app.assets.manager as manager
from app import user_manager
from app.assets.api import schemas_in
from app.assets.helpers import get_query_dict
from app.assets.scanner import seed_assets
import folder_paths
from app import user_manager
from app.assets.api import schemas_in, schemas_out
from app.assets.api.schemas_in import (
AssetValidationError,
UploadError,
)
from app.assets.api.upload import parse_multipart_upload
from app.assets.scanner import seed_assets as scanner_seed_assets
from app.assets.services import (
DependencyMissingError,
HashMismatchError,
apply_tags,
asset_exists,
create_from_hash,
delete_asset_reference,
get_asset_detail,
list_assets_page,
list_tags,
remove_tags,
resolve_asset_for_download,
update_asset_metadata,
upload_from_temp_path,
)
ROUTES = web.RouteTableDef()
USER_MANAGER: user_manager.UserManager | None = None
@@ -21,36 +38,78 @@ USER_MANAGER: user_manager.UserManager | None = None
# UUID regex (canonical hyphenated form, case-insensitive)
UUID_RE = r"[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12}"
def get_query_dict(request: web.Request) -> dict[str, Any]:
"""
Gets a dictionary of query parameters from the request.
'request.query' is a MultiMapping[str], needs to be converted to a dictionary to be validated by Pydantic.
"""
query_dict = {
key: request.query.getall(key)
if len(request.query.getall(key)) > 1
else request.query.get(key)
for key in request.query.keys()
}
return query_dict
# Note to any custom node developers reading this code:
# The assets system is not yet fully implemented, do not rely on the code in /app/assets remaining the same.
def register_assets_system(app: web.Application, user_manager_instance: user_manager.UserManager) -> None:
def register_assets_system(
app: web.Application, user_manager_instance: user_manager.UserManager
) -> None:
global USER_MANAGER
USER_MANAGER = user_manager_instance
app.add_routes(ROUTES)
def _error_response(status: int, code: str, message: str, details: dict | None = None) -> web.Response:
return web.json_response({"error": {"code": code, "message": message, "details": details or {}}}, status=status)
def _build_error_response(
status: int, code: str, message: str, details: dict | None = None
) -> web.Response:
return web.json_response(
{"error": {"code": code, "message": message, "details": details or {}}},
status=status,
)
def _validation_error_response(code: str, ve: ValidationError) -> web.Response:
return _error_response(400, code, "Validation failed.", {"errors": ve.json()})
def _build_validation_error_response(code: str, ve: ValidationError) -> web.Response:
return _build_error_response(400, code, "Validation failed.", {"errors": ve.json()})
def _validate_sort_field(requested: str | None) -> str:
if not requested:
return "created_at"
v = requested.lower()
if v in {"name", "created_at", "updated_at", "size", "last_access_time"}:
return v
return "created_at"
@ROUTES.head("/api/assets/hash/{hash}")
async def head_asset_by_hash(request: web.Request) -> web.Response:
hash_str = request.match_info.get("hash", "").strip().lower()
if not hash_str or ":" not in hash_str:
return _error_response(400, "INVALID_HASH", "hash must be like 'blake3:<hex>'")
return _build_error_response(
400, "INVALID_HASH", "hash must be like 'blake3:<hex>'"
)
algo, digest = hash_str.split(":", 1)
if algo != "blake3" or not digest or any(c for c in digest if c not in "0123456789abcdef"):
return _error_response(400, "INVALID_HASH", "hash must be like 'blake3:<hex>'")
exists = manager.asset_exists(asset_hash=hash_str)
if (
algo != "blake3"
or not digest
or any(c for c in digest if c not in "0123456789abcdef")
):
return _build_error_response(
400, "INVALID_HASH", "hash must be like 'blake3:<hex>'"
)
exists = asset_exists(hash_str)
return web.Response(status=200 if exists else 404)
@ROUTES.get("/api/assets")
async def list_assets(request: web.Request) -> web.Response:
async def list_assets_route(request: web.Request) -> web.Response:
"""
GET request to list assets.
"""
@@ -58,66 +117,124 @@ async def list_assets(request: web.Request) -> web.Response:
try:
q = schemas_in.ListAssetsQuery.model_validate(query_dict)
except ValidationError as ve:
return _validation_error_response("INVALID_QUERY", ve)
return _build_validation_error_response("INVALID_QUERY", ve)
payload = manager.list_assets(
sort = _validate_sort_field(q.sort)
order = (
"desc"
if (q.order or "desc").lower() not in {"asc", "desc"}
else q.order.lower()
)
result = list_assets_page(
owner_id=USER_MANAGER.get_request_user_id(request),
include_tags=q.include_tags,
exclude_tags=q.exclude_tags,
name_contains=q.name_contains,
metadata_filter=q.metadata_filter,
limit=q.limit,
offset=q.offset,
sort=q.sort,
order=q.order,
owner_id=USER_MANAGER.get_request_user_id(request),
sort=sort,
order=order,
)
summaries = [
schemas_out.AssetSummary(
id=item.info.id,
name=item.info.name,
asset_hash=item.asset.hash if item.asset else None,
size=int(item.asset.size_bytes)
if item.asset and item.asset.size_bytes
else None,
mime_type=item.asset.mime_type if item.asset else None,
tags=item.tags,
created_at=item.info.created_at,
updated_at=item.info.updated_at,
last_access_time=item.info.last_access_time,
)
for item in result.items
]
payload = schemas_out.AssetsList(
assets=summaries,
total=result.total,
has_more=(q.offset + len(summaries)) < result.total,
)
return web.json_response(payload.model_dump(mode="json", exclude_none=True))
@ROUTES.get(f"/api/assets/{{id:{UUID_RE}}}")
async def get_asset(request: web.Request) -> web.Response:
async def get_asset_route(request: web.Request) -> web.Response:
"""
GET request to get an asset's info as JSON.
"""
asset_info_id = str(uuid.UUID(request.match_info["id"]))
try:
result = manager.get_asset(
result = get_asset_detail(
asset_info_id=asset_info_id,
owner_id=USER_MANAGER.get_request_user_id(request),
)
if not result:
return _build_error_response(
404,
"ASSET_NOT_FOUND",
f"AssetInfo {asset_info_id} not found",
{"id": asset_info_id},
)
payload = schemas_out.AssetDetail(
id=result.info.id,
name=result.info.name,
asset_hash=result.asset.hash if result.asset else None,
size=int(result.asset.size_bytes)
if result.asset and result.asset.size_bytes is not None
else None,
mime_type=result.asset.mime_type if result.asset else None,
tags=result.tags,
user_metadata=result.info.user_metadata or {},
preview_id=result.info.preview_id,
created_at=result.info.created_at,
last_access_time=result.info.last_access_time,
)
except ValueError as e:
return _error_response(404, "ASSET_NOT_FOUND", str(e), {"id": asset_info_id})
return _build_error_response(
404, "ASSET_NOT_FOUND", str(e), {"id": asset_info_id}
)
except Exception:
logging.exception(
"get_asset failed for asset_info_id=%s, owner_id=%s",
asset_info_id,
USER_MANAGER.get_request_user_id(request),
)
return _error_response(500, "INTERNAL", "Unexpected server error.")
return web.json_response(result.model_dump(mode="json"), status=200)
return _build_error_response(500, "INTERNAL", "Unexpected server error.")
return web.json_response(payload.model_dump(mode="json"), status=200)
@ROUTES.get(f"/api/assets/{{id:{UUID_RE}}}/content")
async def download_asset_content(request: web.Request) -> web.Response:
# question: do we need disposition? could we just stick with one of these?
disposition = request.query.get("disposition", "attachment").lower().strip()
if disposition not in {"inline", "attachment"}:
disposition = "attachment"
try:
abs_path, content_type, filename = manager.resolve_asset_content_for_download(
result = resolve_asset_for_download(
asset_info_id=str(uuid.UUID(request.match_info["id"])),
owner_id=USER_MANAGER.get_request_user_id(request),
)
abs_path = result.abs_path
content_type = result.content_type
filename = result.download_name
except ValueError as ve:
return _error_response(404, "ASSET_NOT_FOUND", str(ve))
return _build_error_response(404, "ASSET_NOT_FOUND", str(ve))
except NotImplementedError as nie:
return _error_response(501, "BACKEND_UNSUPPORTED", str(nie))
return _build_error_response(501, "BACKEND_UNSUPPORTED", str(nie))
except FileNotFoundError:
return _error_response(404, "FILE_NOT_FOUND", "Underlying file not found on disk.")
return _build_error_response(
404, "FILE_NOT_FOUND", "Underlying file not found on disk."
)
quoted = (filename or "").replace("\r", "").replace("\n", "").replace('"', "'")
cd = f'{disposition}; filename="{quoted}"; filename*=UTF-8\'\'{urllib.parse.quote(filename)}'
cd = f"{disposition}; filename=\"{quoted}\"; filename*=UTF-8''{urllib.parse.quote(filename)}"
file_size = os.path.getsize(abs_path)
logging.info(
@@ -129,7 +246,7 @@ async def download_asset_content(request: web.Request) -> web.Response:
filename,
)
async def file_sender():
async def stream_file_chunks():
chunk_size = 64 * 1024
with open(abs_path, "rb") as f:
while True:
@@ -139,7 +256,7 @@ async def download_asset_content(request: web.Request) -> web.Response:
yield chunk
return web.Response(
body=file_sender(),
body=stream_file_chunks(),
content_type=content_type,
headers={
"Content-Disposition": cd,
@@ -149,16 +266,18 @@ async def download_asset_content(request: web.Request) -> web.Response:
@ROUTES.post("/api/assets/from-hash")
async def create_asset_from_hash(request: web.Request) -> web.Response:
async def create_asset_from_hash_route(request: web.Request) -> web.Response:
try:
payload = await request.json()
body = schemas_in.CreateFromHashBody.model_validate(payload)
except ValidationError as ve:
return _validation_error_response("INVALID_BODY", ve)
return _build_validation_error_response("INVALID_BODY", ve)
except Exception:
return _error_response(400, "INVALID_JSON", "Request body must be valid JSON.")
return _build_error_response(
400, "INVALID_JSON", "Request body must be valid JSON."
)
result = manager.create_asset_from_hash(
result = create_from_hash(
hash_str=body.hash,
name=body.name,
tags=body.tags,
@@ -166,228 +285,191 @@ async def create_asset_from_hash(request: web.Request) -> web.Response:
owner_id=USER_MANAGER.get_request_user_id(request),
)
if result is None:
return _error_response(404, "ASSET_NOT_FOUND", f"Asset content {body.hash} does not exist")
return web.json_response(result.model_dump(mode="json"), status=201)
return _build_error_response(
404, "ASSET_NOT_FOUND", f"Asset content {body.hash} does not exist"
)
payload_out = schemas_out.AssetCreated(
id=result.info.id,
name=result.info.name,
asset_hash=result.asset.hash,
size=int(result.asset.size_bytes) if result.asset.size_bytes else None,
mime_type=result.asset.mime_type,
tags=result.tags,
user_metadata=result.info.user_metadata or {},
preview_id=result.info.preview_id,
created_at=result.info.created_at,
last_access_time=result.info.last_access_time,
created_new=result.created_new,
)
return web.json_response(payload_out.model_dump(mode="json"), status=201)
def _delete_temp_file_if_exists(path: str | None) -> None:
if path and os.path.exists(path):
try:
os.remove(path)
except Exception:
pass
@ROUTES.post("/api/assets")
async def upload_asset(request: web.Request) -> web.Response:
"""Multipart/form-data endpoint for Asset uploads."""
if not (request.content_type or "").lower().startswith("multipart/"):
return _error_response(415, "UNSUPPORTED_MEDIA_TYPE", "Use multipart/form-data for uploads.")
reader = await request.multipart()
file_present = False
file_client_name: str | None = None
tags_raw: list[str] = []
provided_name: str | None = None
user_metadata_raw: str | None = None
provided_hash: str | None = None
provided_hash_exists: bool | None = None
file_written = 0
tmp_path: str | None = None
while True:
field = await reader.next()
if field is None:
break
fname = getattr(field, "name", "") or ""
if fname == "hash":
try:
s = ((await field.text()) or "").strip().lower()
except Exception:
return _error_response(400, "INVALID_HASH", "hash must be like 'blake3:<hex>'")
if s:
if ":" not in s:
return _error_response(400, "INVALID_HASH", "hash must be like 'blake3:<hex>'")
algo, digest = s.split(":", 1)
if algo != "blake3" or not digest or any(c for c in digest if c not in "0123456789abcdef"):
return _error_response(400, "INVALID_HASH", "hash must be like 'blake3:<hex>'")
provided_hash = f"{algo}:{digest}"
try:
provided_hash_exists = manager.asset_exists(asset_hash=provided_hash)
except Exception:
provided_hash_exists = None # do not fail the whole request here
elif fname == "file":
file_present = True
file_client_name = (field.filename or "").strip()
if provided_hash and provided_hash_exists is True:
# If client supplied a hash that we know exists, drain but do not write to disk
try:
while True:
chunk = await field.read_chunk(8 * 1024 * 1024)
if not chunk:
break
file_written += len(chunk)
except Exception:
return _error_response(500, "UPLOAD_IO_ERROR", "Failed to receive uploaded file.")
continue # Do not create temp file; we will create AssetInfo from the existing content
# Otherwise, store to temp for hashing/ingest
uploads_root = os.path.join(folder_paths.get_temp_directory(), "uploads")
unique_dir = os.path.join(uploads_root, uuid.uuid4().hex)
os.makedirs(unique_dir, exist_ok=True)
tmp_path = os.path.join(unique_dir, ".upload.part")
try:
with open(tmp_path, "wb") as f:
while True:
chunk = await field.read_chunk(8 * 1024 * 1024)
if not chunk:
break
f.write(chunk)
file_written += len(chunk)
except Exception:
try:
if os.path.exists(tmp_path or ""):
os.remove(tmp_path)
finally:
return _error_response(500, "UPLOAD_IO_ERROR", "Failed to receive and store uploaded file.")
elif fname == "tags":
tags_raw.append((await field.text()) or "")
elif fname == "name":
provided_name = (await field.text()) or None
elif fname == "user_metadata":
user_metadata_raw = (await field.text()) or None
# If client did not send file, and we are not doing a from-hash fast path -> error
if not file_present and not (provided_hash and provided_hash_exists):
return _error_response(400, "MISSING_FILE", "Form must include a 'file' part or a known 'hash'.")
if file_present and file_written == 0 and not (provided_hash and provided_hash_exists):
# Empty upload is only acceptable if we are fast-pathing from existing hash
try:
if tmp_path and os.path.exists(tmp_path):
os.remove(tmp_path)
finally:
return _error_response(400, "EMPTY_UPLOAD", "Uploaded file is empty.")
try:
spec = schemas_in.UploadAssetSpec.model_validate({
"tags": tags_raw,
"name": provided_name,
"user_metadata": user_metadata_raw,
"hash": provided_hash,
})
except ValidationError as ve:
try:
if tmp_path and os.path.exists(tmp_path):
os.remove(tmp_path)
finally:
return _validation_error_response("INVALID_BODY", ve)
# Validate models category against configured folders (consistent with previous behavior)
if spec.tags and spec.tags[0] == "models":
if len(spec.tags) < 2 or spec.tags[1] not in folder_paths.folder_names_and_paths:
if tmp_path and os.path.exists(tmp_path):
os.remove(tmp_path)
return _error_response(
400, "INVALID_BODY", f"unknown models category '{spec.tags[1] if len(spec.tags) >= 2 else ''}'"
)
parsed = await parse_multipart_upload(request, check_hash_exists=asset_exists)
except UploadError as e:
return _build_error_response(e.status, e.code, e.message)
owner_id = USER_MANAGER.get_request_user_id(request)
# Fast path: if a valid provided hash exists, create AssetInfo without writing anything
if spec.hash and provided_hash_exists is True:
try:
result = manager.create_asset_from_hash(
try:
spec = schemas_in.UploadAssetSpec.model_validate(
{
"tags": parsed.tags_raw,
"name": parsed.provided_name,
"user_metadata": parsed.user_metadata_raw,
"hash": parsed.provided_hash,
}
)
except ValidationError as ve:
_delete_temp_file_if_exists(parsed.tmp_path)
return _build_error_response(
400, "INVALID_BODY", f"Validation failed: {ve.json()}"
)
if spec.tags and spec.tags[0] == "models":
if (
len(spec.tags) < 2
or spec.tags[1] not in folder_paths.folder_names_and_paths
):
_delete_temp_file_if_exists(parsed.tmp_path)
category = spec.tags[1] if len(spec.tags) >= 2 else ""
return _build_error_response(
400, "INVALID_BODY", f"unknown models category '{category}'"
)
try:
# Fast path: if a valid provided hash exists, create AssetInfo without writing anything
if spec.hash and parsed.provided_hash_exists is True:
result = create_from_hash(
hash_str=spec.hash,
name=spec.name or (spec.hash.split(":", 1)[1]),
tags=spec.tags,
user_metadata=spec.user_metadata or {},
owner_id=owner_id,
)
except Exception:
logging.exception("create_asset_from_hash failed for hash=%s, owner_id=%s", spec.hash, owner_id)
return _error_response(500, "INTERNAL", "Unexpected server error.")
if result is None:
_delete_temp_file_if_exists(parsed.tmp_path)
return _build_error_response(
404, "ASSET_NOT_FOUND", f"Asset content {spec.hash} does not exist"
)
_delete_temp_file_if_exists(parsed.tmp_path)
else:
# Otherwise, we must have a temp file path to ingest
if not parsed.tmp_path or not os.path.exists(parsed.tmp_path):
return _build_error_response(
404,
"ASSET_NOT_FOUND",
"Provided hash not found and no file uploaded.",
)
if result is None:
return _error_response(404, "ASSET_NOT_FOUND", f"Asset content {spec.hash} does not exist")
# Drain temp if we accidentally saved (e.g., hash field came after file)
if tmp_path and os.path.exists(tmp_path):
with contextlib.suppress(Exception):
os.remove(tmp_path)
status = 200 if (not result.created_new) else 201
return web.json_response(result.model_dump(mode="json"), status=status)
# Otherwise, we must have a temp file path to ingest
if not tmp_path or not os.path.exists(tmp_path):
# The only case we reach here without a temp file is: client sent a hash that does not exist and no file
return _error_response(404, "ASSET_NOT_FOUND", "Provided hash not found and no file uploaded.")
try:
created = manager.upload_asset_from_temp_path(
spec,
temp_path=tmp_path,
client_filename=file_client_name,
owner_id=owner_id,
expected_asset_hash=spec.hash,
)
status = 201 if created.created_new else 200
return web.json_response(created.model_dump(mode="json"), status=status)
except ValueError as e:
if tmp_path and os.path.exists(tmp_path):
os.remove(tmp_path)
msg = str(e)
if "HASH_MISMATCH" in msg or msg.strip().upper() == "HASH_MISMATCH":
return _error_response(
400,
"HASH_MISMATCH",
"Uploaded file hash does not match provided hash.",
result = upload_from_temp_path(
temp_path=parsed.tmp_path,
name=spec.name,
tags=spec.tags,
user_metadata=spec.user_metadata or {},
client_filename=parsed.file_client_name,
owner_id=owner_id,
expected_hash=spec.hash,
)
return _error_response(400, "BAD_REQUEST", "Invalid inputs.")
except AssetValidationError as e:
_delete_temp_file_if_exists(parsed.tmp_path)
return _build_error_response(400, e.code, str(e))
except ValueError as e:
_delete_temp_file_if_exists(parsed.tmp_path)
return _build_error_response(400, "BAD_REQUEST", str(e))
except HashMismatchError as e:
_delete_temp_file_if_exists(parsed.tmp_path)
return _build_error_response(400, "HASH_MISMATCH", str(e))
except DependencyMissingError as e:
_delete_temp_file_if_exists(parsed.tmp_path)
return _build_error_response(503, "DEPENDENCY_MISSING", e.message)
except Exception:
if tmp_path and os.path.exists(tmp_path):
os.remove(tmp_path)
logging.exception("upload_asset_from_temp_path failed for tmp_path=%s, owner_id=%s", tmp_path, owner_id)
return _error_response(500, "INTERNAL", "Unexpected server error.")
_delete_temp_file_if_exists(parsed.tmp_path)
logging.exception("upload_asset failed for owner_id=%s", owner_id)
return _build_error_response(500, "INTERNAL", "Unexpected server error.")
payload = schemas_out.AssetCreated(
id=result.info.id,
name=result.info.name,
asset_hash=result.asset.hash,
size=int(result.asset.size_bytes) if result.asset.size_bytes else None,
mime_type=result.asset.mime_type,
tags=result.tags,
user_metadata=result.info.user_metadata or {},
preview_id=result.info.preview_id,
created_at=result.info.created_at,
last_access_time=result.info.last_access_time,
created_new=result.created_new,
)
status = 201 if result.created_new else 200
return web.json_response(payload.model_dump(mode="json"), status=status)
@ROUTES.put(f"/api/assets/{{id:{UUID_RE}}}")
async def update_asset(request: web.Request) -> web.Response:
async def update_asset_route(request: web.Request) -> web.Response:
asset_info_id = str(uuid.UUID(request.match_info["id"]))
try:
body = schemas_in.UpdateAssetBody.model_validate(await request.json())
except ValidationError as ve:
return _validation_error_response("INVALID_BODY", ve)
return _build_validation_error_response("INVALID_BODY", ve)
except Exception:
return _error_response(400, "INVALID_JSON", "Request body must be valid JSON.")
return _build_error_response(
400, "INVALID_JSON", "Request body must be valid JSON."
)
try:
result = manager.update_asset(
result = update_asset_metadata(
asset_info_id=asset_info_id,
name=body.name,
user_metadata=body.user_metadata,
owner_id=USER_MANAGER.get_request_user_id(request),
)
payload = schemas_out.AssetUpdated(
id=result.info.id,
name=result.info.name,
asset_hash=result.asset.hash if result.asset else None,
tags=result.tags,
user_metadata=result.info.user_metadata or {},
updated_at=result.info.updated_at,
)
except (ValueError, PermissionError) as ve:
return _error_response(404, "ASSET_NOT_FOUND", str(ve), {"id": asset_info_id})
return _build_error_response(
404, "ASSET_NOT_FOUND", str(ve), {"id": asset_info_id}
)
except Exception:
logging.exception(
"update_asset failed for asset_info_id=%s, owner_id=%s",
asset_info_id,
USER_MANAGER.get_request_user_id(request),
)
return _error_response(500, "INTERNAL", "Unexpected server error.")
return web.json_response(result.model_dump(mode="json"), status=200)
return _build_error_response(500, "INTERNAL", "Unexpected server error.")
return web.json_response(payload.model_dump(mode="json"), status=200)
@ROUTES.delete(f"/api/assets/{{id:{UUID_RE}}}")
async def delete_asset(request: web.Request) -> web.Response:
async def delete_asset_route(request: web.Request) -> web.Response:
asset_info_id = str(uuid.UUID(request.match_info["id"]))
delete_content = request.query.get("delete_content")
delete_content = True if delete_content is None else delete_content.lower() not in {"0", "false", "no"}
delete_content_param = request.query.get("delete_content")
delete_content = (
True
if delete_content_param is None
else delete_content_param.lower() not in {"0", "false", "no"}
)
try:
deleted = manager.delete_asset_reference(
deleted = delete_asset_reference(
asset_info_id=asset_info_id,
owner_id=USER_MANAGER.get_request_user_id(request),
delete_content_if_orphan=delete_content,
@@ -398,10 +480,12 @@ async def delete_asset(request: web.Request) -> web.Response:
asset_info_id,
USER_MANAGER.get_request_user_id(request),
)
return _error_response(500, "INTERNAL", "Unexpected server error.")
return _build_error_response(500, "INTERNAL", "Unexpected server error.")
if not deleted:
return _error_response(404, "ASSET_NOT_FOUND", f"AssetInfo {asset_info_id} not found.")
return _build_error_response(
404, "ASSET_NOT_FOUND", f"AssetInfo {asset_info_id} not found."
)
return web.Response(status=204)
@@ -416,11 +500,17 @@ async def get_tags(request: web.Request) -> web.Response:
query = schemas_in.TagsListQuery.model_validate(query_map)
except ValidationError as e:
return web.json_response(
{"error": {"code": "INVALID_QUERY", "message": "Invalid query parameters", "details": e.errors()}},
{
"error": {
"code": "INVALID_QUERY",
"message": "Invalid query parameters",
"details": e.errors(),
}
},
status=400,
)
result = manager.list_tags(
rows, total = list_tags(
prefix=query.prefix,
limit=query.limit,
offset=query.offset,
@@ -428,72 +518,108 @@ async def get_tags(request: web.Request) -> web.Response:
include_zero=query.include_zero,
owner_id=USER_MANAGER.get_request_user_id(request),
)
return web.json_response(result.model_dump(mode="json"))
tags = [
schemas_out.TagUsage(name=name, count=count, type=tag_type)
for (name, tag_type, count) in rows
]
payload = schemas_out.TagsList(
tags=tags, total=total, has_more=(query.offset + len(tags)) < total
)
return web.json_response(payload.model_dump(mode="json"))
@ROUTES.post(f"/api/assets/{{id:{UUID_RE}}}/tags")
async def add_asset_tags(request: web.Request) -> web.Response:
asset_info_id = str(uuid.UUID(request.match_info["id"]))
try:
payload = await request.json()
data = schemas_in.TagsAdd.model_validate(payload)
json_payload = await request.json()
data = schemas_in.TagsAdd.model_validate(json_payload)
except ValidationError as ve:
return _error_response(400, "INVALID_BODY", "Invalid JSON body for tags add.", {"errors": ve.errors()})
return _build_error_response(
400,
"INVALID_BODY",
"Invalid JSON body for tags add.",
{"errors": ve.errors()},
)
except Exception:
return _error_response(400, "INVALID_JSON", "Request body must be valid JSON.")
return _build_error_response(
400, "INVALID_JSON", "Request body must be valid JSON."
)
try:
result = manager.add_tags_to_asset(
result = apply_tags(
asset_info_id=asset_info_id,
tags=data.tags,
origin="manual",
owner_id=USER_MANAGER.get_request_user_id(request),
)
payload = schemas_out.TagsAdd(
added=result.added,
already_present=result.already_present,
total_tags=result.total_tags,
)
except (ValueError, PermissionError) as ve:
return _error_response(404, "ASSET_NOT_FOUND", str(ve), {"id": asset_info_id})
return _build_error_response(
404, "ASSET_NOT_FOUND", str(ve), {"id": asset_info_id}
)
except Exception:
logging.exception(
"add_tags_to_asset failed for asset_info_id=%s, owner_id=%s",
asset_info_id,
USER_MANAGER.get_request_user_id(request),
)
return _error_response(500, "INTERNAL", "Unexpected server error.")
return _build_error_response(500, "INTERNAL", "Unexpected server error.")
return web.json_response(result.model_dump(mode="json"), status=200)
return web.json_response(payload.model_dump(mode="json"), status=200)
@ROUTES.delete(f"/api/assets/{{id:{UUID_RE}}}/tags")
async def delete_asset_tags(request: web.Request) -> web.Response:
asset_info_id = str(uuid.UUID(request.match_info["id"]))
try:
payload = await request.json()
data = schemas_in.TagsRemove.model_validate(payload)
json_payload = await request.json()
data = schemas_in.TagsRemove.model_validate(json_payload)
except ValidationError as ve:
return _error_response(400, "INVALID_BODY", "Invalid JSON body for tags remove.", {"errors": ve.errors()})
return _build_error_response(
400,
"INVALID_BODY",
"Invalid JSON body for tags remove.",
{"errors": ve.errors()},
)
except Exception:
return _error_response(400, "INVALID_JSON", "Request body must be valid JSON.")
return _build_error_response(
400, "INVALID_JSON", "Request body must be valid JSON."
)
try:
result = manager.remove_tags_from_asset(
result = remove_tags(
asset_info_id=asset_info_id,
tags=data.tags,
owner_id=USER_MANAGER.get_request_user_id(request),
)
payload = schemas_out.TagsRemove(
removed=result.removed,
not_present=result.not_present,
total_tags=result.total_tags,
)
except ValueError as ve:
return _error_response(404, "ASSET_NOT_FOUND", str(ve), {"id": asset_info_id})
return _build_error_response(
404, "ASSET_NOT_FOUND", str(ve), {"id": asset_info_id}
)
except Exception:
logging.exception(
"remove_tags_from_asset failed for asset_info_id=%s, owner_id=%s",
asset_info_id,
USER_MANAGER.get_request_user_id(request),
)
return _error_response(500, "INTERNAL", "Unexpected server error.")
return _build_error_response(500, "INTERNAL", "Unexpected server error.")
return web.json_response(result.model_dump(mode="json"), status=200)
return web.json_response(payload.model_dump(mode="json"), status=200)
@ROUTES.post("/api/assets/seed")
async def seed_assets_endpoint(request: web.Request) -> web.Response:
async def seed_assets(request: web.Request) -> web.Response:
"""Trigger asset seeding for specified roots (models, input, output)."""
try:
payload = await request.json()
@@ -503,12 +629,12 @@ async def seed_assets_endpoint(request: web.Request) -> web.Response:
valid_roots = [r for r in roots if r in ("models", "input", "output")]
if not valid_roots:
return _error_response(400, "INVALID_BODY", "No valid roots specified")
return _build_error_response(400, "INVALID_BODY", "No valid roots specified")
try:
seed_assets(tuple(valid_roots))
scanner_seed_assets(tuple(valid_roots))
except Exception:
logging.exception("seed_assets failed for roots=%s", valid_roots)
return _error_response(500, "INTERNAL", "Seed operation failed")
logging.exception("scanner_seed_assets failed for roots=%s", valid_roots)
return _build_error_response(500, "INTERNAL", "Seed operation failed")
return web.json_response({"seeded": valid_roots}, status=200)

View File

@@ -1,4 +1,5 @@
import json
from dataclasses import dataclass
from typing import Any, Literal
from pydantic import (
@@ -10,6 +11,61 @@ from pydantic import (
model_validator,
)
class UploadError(Exception):
"""Error during upload parsing with HTTP status and code (used in HTTP layer only)."""
def __init__(self, status: int, code: str, message: str):
super().__init__(message)
self.status = status
self.code = code
self.message = message
class AssetValidationError(Exception):
"""Validation error in asset processing (invalid tags, metadata, etc.)."""
def __init__(self, code: str, message: str):
super().__init__(message)
self.code = code
class AssetNotFoundError(Exception):
"""Asset or asset content not found."""
def __init__(self, message: str):
super().__init__(message)
class HashMismatchError(Exception):
"""Uploaded file hash does not match provided hash."""
pass
class DependencyMissingError(Exception):
"""A required dependency is not installed."""
def __init__(self, message: str):
super().__init__(message)
self.message = message
@dataclass
class ParsedUpload:
"""Result of parsing a multipart upload request."""
file_present: bool
file_written: int
file_client_name: str | None
tmp_path: str | None
tags_raw: list[str]
provided_name: str | None
user_metadata_raw: str | None
provided_hash: str | None
provided_hash_exists: bool | None
class ListAssetsQuery(BaseModel):
include_tags: list[str] = Field(default_factory=list)
exclude_tags: list[str] = Field(default_factory=list)
@@ -21,7 +77,9 @@ class ListAssetsQuery(BaseModel):
limit: conint(ge=1, le=500) = 20
offset: conint(ge=0) = 0
sort: Literal["name", "created_at", "updated_at", "size", "last_access_time"] = "created_at"
sort: Literal["name", "created_at", "updated_at", "size", "last_access_time"] = (
"created_at"
)
order: Literal["asc", "desc"] = "desc"
@field_validator("include_tags", "exclude_tags", mode="before")
@@ -61,7 +119,7 @@ class UpdateAssetBody(BaseModel):
user_metadata: dict[str, Any] | None = None
@model_validator(mode="after")
def _at_least_one(self):
def _validate_at_least_one_field(self):
if self.name is None and self.user_metadata is None:
raise ValueError("Provide at least one of: name, user_metadata.")
return self
@@ -90,7 +148,7 @@ class CreateFromHashBody(BaseModel):
@field_validator("tags", mode="before")
@classmethod
def _tags_norm(cls, v):
def _normalize_tags_field(cls, v):
if v is None:
return []
if isinstance(v, list):
@@ -163,6 +221,7 @@ class UploadAssetSpec(BaseModel):
Files created via this endpoint are stored on disk using the **content hash** as the filename stem
and the original extension is preserved when available.
"""
model_config = ConfigDict(extra="ignore", str_strip_whitespace=True)
tags: list[str] = Field(..., min_length=1)
@@ -260,5 +319,7 @@ class UploadAssetSpec(BaseModel):
raise ValueError("first tag must be one of: models, input, output")
if root == "models":
if len(self.tags) < 2:
raise ValueError("models uploads require a category tag as the second tag")
raise ValueError(
"models uploads require a category tag as the second tag"
)
return self

View File

@@ -19,7 +19,7 @@ class AssetSummary(BaseModel):
model_config = ConfigDict(from_attributes=True)
@field_serializer("created_at", "updated_at", "last_access_time")
def _ser_dt(self, v: datetime | None, _info):
def _serialize_datetime(self, v: datetime | None, _info):
return v.isoformat() if v else None
@@ -40,7 +40,7 @@ class AssetUpdated(BaseModel):
model_config = ConfigDict(from_attributes=True)
@field_serializer("updated_at")
def _ser_updated(self, v: datetime | None, _info):
def _serialize_updated_at(self, v: datetime | None, _info):
return v.isoformat() if v else None
@@ -59,7 +59,7 @@ class AssetDetail(BaseModel):
model_config = ConfigDict(from_attributes=True)
@field_serializer("created_at", "last_access_time")
def _ser_dt(self, v: datetime | None, _info):
def _serialize_datetime(self, v: datetime | None, _info):
return v.isoformat() if v else None

165
app/assets/api/upload.py Normal file
View File

@@ -0,0 +1,165 @@
import os
import uuid
from aiohttp import web
import folder_paths
from app.assets.api.schemas_in import ParsedUpload, UploadError
def normalize_and_validate_hash(s: str) -> str:
"""
Validate and normalize a hash string.
Returns canonical 'blake3:<hex>' or raises UploadError.
"""
s = s.strip().lower()
if not s:
raise UploadError(400, "INVALID_HASH", "hash must be like 'blake3:<hex>'")
if ":" not in s:
raise UploadError(400, "INVALID_HASH", "hash must be like 'blake3:<hex>'")
algo, digest = s.split(":", 1)
if (
algo != "blake3"
or not digest
or any(c for c in digest if c not in "0123456789abcdef")
):
raise UploadError(400, "INVALID_HASH", "hash must be like 'blake3:<hex>'")
return f"{algo}:{digest}"
async def parse_multipart_upload(
request: web.Request,
check_hash_exists: callable,
) -> ParsedUpload:
"""
Parse a multipart/form-data upload request.
Args:
request: The aiohttp request
check_hash_exists: Callable(hash_str) -> bool to check if a hash exists
Returns:
ParsedUpload with parsed fields and temp file path
Raises:
UploadError: On validation or I/O errors
"""
if not (request.content_type or "").lower().startswith("multipart/"):
raise UploadError(
415, "UNSUPPORTED_MEDIA_TYPE", "Use multipart/form-data for uploads."
)
reader = await request.multipart()
file_present = False
file_client_name: str | None = None
tags_raw: list[str] = []
provided_name: str | None = None
user_metadata_raw: str | None = None
provided_hash: str | None = None
provided_hash_exists: bool | None = None
file_written = 0
tmp_path: str | None = None
while True:
field = await reader.next()
if field is None:
break
fname = getattr(field, "name", "") or ""
if fname == "hash":
try:
s = ((await field.text()) or "").strip().lower()
except Exception:
raise UploadError(
400, "INVALID_HASH", "hash must be like 'blake3:<hex>'"
)
if s:
provided_hash = normalize_and_validate_hash(s)
try:
provided_hash_exists = check_hash_exists(provided_hash)
except Exception:
provided_hash_exists = None # do not fail the whole request here
elif fname == "file":
file_present = True
file_client_name = (field.filename or "").strip()
if provided_hash and provided_hash_exists is True:
# If client supplied a hash that we know exists, drain but do not write to disk
try:
while True:
chunk = await field.read_chunk(8 * 1024 * 1024)
if not chunk:
break
file_written += len(chunk)
except Exception:
raise UploadError(
500, "UPLOAD_IO_ERROR", "Failed to receive uploaded file."
)
continue
uploads_root = os.path.join(folder_paths.get_temp_directory(), "uploads")
unique_dir = os.path.join(uploads_root, uuid.uuid4().hex)
os.makedirs(unique_dir, exist_ok=True)
tmp_path = os.path.join(unique_dir, ".upload.part")
try:
with open(tmp_path, "wb") as f:
while True:
chunk = await field.read_chunk(8 * 1024 * 1024)
if not chunk:
break
f.write(chunk)
file_written += len(chunk)
except Exception:
_delete_temp_file_if_exists(tmp_path)
raise UploadError(
500, "UPLOAD_IO_ERROR", "Failed to receive and store uploaded file."
)
elif fname == "tags":
tags_raw.append((await field.text()) or "")
elif fname == "name":
provided_name = (await field.text()) or None
elif fname == "user_metadata":
user_metadata_raw = (await field.text()) or None
if not file_present and not (provided_hash and provided_hash_exists):
raise UploadError(
400, "MISSING_FILE", "Form must include a 'file' part or a known 'hash'."
)
if (
file_present
and file_written == 0
and not (provided_hash and provided_hash_exists)
):
_delete_temp_file_if_exists(tmp_path)
raise UploadError(400, "EMPTY_UPLOAD", "Uploaded file is empty.")
return ParsedUpload(
file_present=file_present,
file_written=file_written,
file_client_name=file_client_name,
tmp_path=tmp_path,
tags_raw=tags_raw,
provided_name=provided_name,
user_metadata_raw=user_metadata_raw,
provided_hash=provided_hash,
provided_hash_exists=provided_hash_exists,
)
def _delete_temp_file_if_exists(tmp_path: str | None) -> None:
"""Safely remove a temp file if it exists."""
if tmp_path:
try:
if os.path.exists(tmp_path):
os.remove(tmp_path)
except Exception:
pass

View File

@@ -1,204 +0,0 @@
import os
import uuid
import sqlalchemy
from typing import Iterable
from sqlalchemy.orm import Session
from sqlalchemy.dialects import sqlite
from app.assets.helpers import utcnow
from app.assets.database.models import Asset, AssetCacheState, AssetInfo, AssetInfoTag, AssetInfoMeta
MAX_BIND_PARAMS = 800
def _chunk_rows(rows: list[dict], cols_per_row: int, max_bind_params: int) -> Iterable[list[dict]]:
if not rows:
return []
rows_per_stmt = max(1, max_bind_params // max(1, cols_per_row))
for i in range(0, len(rows), rows_per_stmt):
yield rows[i:i + rows_per_stmt]
def _iter_chunks(seq, n: int):
for i in range(0, len(seq), n):
yield seq[i:i + n]
def _rows_per_stmt(cols: int) -> int:
return max(1, MAX_BIND_PARAMS // max(1, cols))
def seed_from_paths_batch(
session: Session,
*,
specs: list[dict],
owner_id: str = "",
) -> dict:
"""Each spec is a dict with keys:
- abs_path: str
- size_bytes: int
- mtime_ns: int
- info_name: str
- tags: list[str]
- fname: Optional[str]
"""
if not specs:
return {"inserted_infos": 0, "won_states": 0, "lost_states": 0}
now = utcnow()
asset_rows: list[dict] = []
state_rows: list[dict] = []
path_to_asset: dict[str, str] = {}
asset_to_info: dict[str, dict] = {} # asset_id -> prepared info row
path_list: list[str] = []
for sp in specs:
ap = os.path.abspath(sp["abs_path"])
aid = str(uuid.uuid4())
iid = str(uuid.uuid4())
path_list.append(ap)
path_to_asset[ap] = aid
asset_rows.append(
{
"id": aid,
"hash": None,
"size_bytes": sp["size_bytes"],
"mime_type": None,
"created_at": now,
}
)
state_rows.append(
{
"asset_id": aid,
"file_path": ap,
"mtime_ns": sp["mtime_ns"],
}
)
asset_to_info[aid] = {
"id": iid,
"owner_id": owner_id,
"name": sp["info_name"],
"asset_id": aid,
"preview_id": None,
"user_metadata": {"filename": sp["fname"]} if sp["fname"] else None,
"created_at": now,
"updated_at": now,
"last_access_time": now,
"_tags": sp["tags"],
"_filename": sp["fname"],
}
# insert all seed Assets (hash=NULL)
ins_asset = sqlite.insert(Asset)
for chunk in _iter_chunks(asset_rows, _rows_per_stmt(5)):
session.execute(ins_asset, chunk)
# try to claim AssetCacheState (file_path)
# Insert with ON CONFLICT DO NOTHING, then query to find which paths were actually inserted
ins_state = (
sqlite.insert(AssetCacheState)
.on_conflict_do_nothing(index_elements=[AssetCacheState.file_path])
)
for chunk in _iter_chunks(state_rows, _rows_per_stmt(3)):
session.execute(ins_state, chunk)
# Query to find which of our paths won (were actually inserted)
winners_by_path: set[str] = set()
for chunk in _iter_chunks(path_list, MAX_BIND_PARAMS):
result = session.execute(
sqlalchemy.select(AssetCacheState.file_path)
.where(AssetCacheState.file_path.in_(chunk))
.where(AssetCacheState.asset_id.in_([path_to_asset[p] for p in chunk]))
)
winners_by_path.update(result.scalars().all())
all_paths_set = set(path_list)
losers_by_path = all_paths_set - winners_by_path
lost_assets = [path_to_asset[p] for p in losers_by_path]
if lost_assets: # losers get their Asset removed
for id_chunk in _iter_chunks(lost_assets, MAX_BIND_PARAMS):
session.execute(sqlalchemy.delete(Asset).where(Asset.id.in_(id_chunk)))
if not winners_by_path:
return {"inserted_infos": 0, "won_states": 0, "lost_states": len(losers_by_path)}
# insert AssetInfo only for winners
# Insert with ON CONFLICT DO NOTHING, then query to find which were actually inserted
winner_info_rows = [asset_to_info[path_to_asset[p]] for p in winners_by_path]
ins_info = (
sqlite.insert(AssetInfo)
.on_conflict_do_nothing(index_elements=[AssetInfo.asset_id, AssetInfo.owner_id, AssetInfo.name])
)
for chunk in _iter_chunks(winner_info_rows, _rows_per_stmt(9)):
session.execute(ins_info, chunk)
# Query to find which info rows were actually inserted (by matching our generated IDs)
all_info_ids = [row["id"] for row in winner_info_rows]
inserted_info_ids: set[str] = set()
for chunk in _iter_chunks(all_info_ids, MAX_BIND_PARAMS):
result = session.execute(
sqlalchemy.select(AssetInfo.id).where(AssetInfo.id.in_(chunk))
)
inserted_info_ids.update(result.scalars().all())
# build and insert tag + meta rows for the AssetInfo
tag_rows: list[dict] = []
meta_rows: list[dict] = []
if inserted_info_ids:
for row in winner_info_rows:
iid = row["id"]
if iid not in inserted_info_ids:
continue
for t in row["_tags"]:
tag_rows.append({
"asset_info_id": iid,
"tag_name": t,
"origin": "automatic",
"added_at": now,
})
if row["_filename"]:
meta_rows.append(
{
"asset_info_id": iid,
"key": "filename",
"ordinal": 0,
"val_str": row["_filename"],
"val_num": None,
"val_bool": None,
"val_json": None,
}
)
bulk_insert_tags_and_meta(session, tag_rows=tag_rows, meta_rows=meta_rows, max_bind_params=MAX_BIND_PARAMS)
return {
"inserted_infos": len(inserted_info_ids),
"won_states": len(winners_by_path),
"lost_states": len(losers_by_path),
}
def bulk_insert_tags_and_meta(
session: Session,
*,
tag_rows: list[dict],
meta_rows: list[dict],
max_bind_params: int,
) -> None:
"""Batch insert into asset_info_tags and asset_info_meta with ON CONFLICT DO NOTHING.
- tag_rows keys: asset_info_id, tag_name, origin, added_at
- meta_rows keys: asset_info_id, key, ordinal, val_str, val_num, val_bool, val_json
"""
if tag_rows:
ins_links = (
sqlite.insert(AssetInfoTag)
.on_conflict_do_nothing(index_elements=[AssetInfoTag.asset_info_id, AssetInfoTag.tag_name])
)
for chunk in _chunk_rows(tag_rows, cols_per_row=4, max_bind_params=max_bind_params):
session.execute(ins_links, chunk)
if meta_rows:
ins_meta = (
sqlite.insert(AssetInfoMeta)
.on_conflict_do_nothing(
index_elements=[AssetInfoMeta.asset_info_id, AssetInfoMeta.key, AssetInfoMeta.ordinal]
)
)
for chunk in _chunk_rows(meta_rows, cols_per_row=7, max_bind_params=max_bind_params):
session.execute(ins_meta, chunk)

View File

@@ -2,8 +2,8 @@ from __future__ import annotations
import uuid
from datetime import datetime
from typing import Any
from sqlalchemy import (
JSON,
BigInteger,
@@ -20,19 +20,21 @@ from sqlalchemy import (
)
from sqlalchemy.orm import Mapped, foreign, mapped_column, relationship
from app.assets.helpers import utcnow
from app.database.models import to_dict, Base
from app.assets.helpers import get_utc_now
from app.database.models import Base, to_dict
class Asset(Base):
__tablename__ = "assets"
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=lambda: str(uuid.uuid4()))
id: Mapped[str] = mapped_column(
String(36), primary_key=True, default=lambda: str(uuid.uuid4())
)
hash: Mapped[str | None] = mapped_column(String(256), nullable=True)
size_bytes: Mapped[int] = mapped_column(BigInteger, nullable=False, default=0)
mime_type: Mapped[str | None] = mapped_column(String(255))
created_at: Mapped[datetime] = mapped_column(
DateTime(timezone=False), nullable=False, default=utcnow
DateTime(timezone=False), nullable=False, default=get_utc_now
)
infos: Mapped[list[AssetInfo]] = relationship(
@@ -75,7 +77,9 @@ class AssetCacheState(Base):
__tablename__ = "asset_cache_state"
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
asset_id: Mapped[str] = mapped_column(String(36), ForeignKey("assets.id", ondelete="CASCADE"), nullable=False)
asset_id: Mapped[str] = mapped_column(
String(36), ForeignKey("assets.id", ondelete="CASCADE"), nullable=False
)
file_path: Mapped[str] = mapped_column(Text, nullable=False)
mtime_ns: Mapped[int | None] = mapped_column(BigInteger, nullable=True)
needs_verify: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
@@ -85,7 +89,9 @@ class AssetCacheState(Base):
__table_args__ = (
Index("ix_asset_cache_state_file_path", "file_path"),
Index("ix_asset_cache_state_asset_id", "asset_id"),
CheckConstraint("(mtime_ns IS NULL) OR (mtime_ns >= 0)", name="ck_acs_mtime_nonneg"),
CheckConstraint(
"(mtime_ns IS NULL) OR (mtime_ns >= 0)", name="ck_acs_mtime_nonneg"
),
UniqueConstraint("file_path", name="uq_asset_cache_state_file_path"),
)
@@ -99,15 +105,29 @@ class AssetCacheState(Base):
class AssetInfo(Base):
__tablename__ = "assets_info"
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=lambda: str(uuid.uuid4()))
id: Mapped[str] = mapped_column(
String(36), primary_key=True, default=lambda: str(uuid.uuid4())
)
owner_id: Mapped[str] = mapped_column(String(128), nullable=False, default="")
name: Mapped[str] = mapped_column(String(512), nullable=False)
asset_id: Mapped[str] = mapped_column(String(36), ForeignKey("assets.id", ondelete="RESTRICT"), nullable=False)
preview_id: Mapped[str | None] = mapped_column(String(36), ForeignKey("assets.id", ondelete="SET NULL"))
user_metadata: Mapped[dict[str, Any] | None] = mapped_column(JSON(none_as_null=True))
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=False), nullable=False, default=utcnow)
updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=False), nullable=False, default=utcnow)
last_access_time: Mapped[datetime] = mapped_column(DateTime(timezone=False), nullable=False, default=utcnow)
asset_id: Mapped[str] = mapped_column(
String(36), ForeignKey("assets.id", ondelete="RESTRICT"), nullable=False
)
preview_id: Mapped[str | None] = mapped_column(
String(36), ForeignKey("assets.id", ondelete="SET NULL")
)
user_metadata: Mapped[dict[str, Any] | None] = mapped_column(
JSON(none_as_null=True)
)
created_at: Mapped[datetime] = mapped_column(
DateTime(timezone=False), nullable=False, default=get_utc_now
)
updated_at: Mapped[datetime] = mapped_column(
DateTime(timezone=False), nullable=False, default=get_utc_now
)
last_access_time: Mapped[datetime] = mapped_column(
DateTime(timezone=False), nullable=False, default=get_utc_now
)
asset: Mapped[Asset] = relationship(
"Asset",
@@ -143,7 +163,9 @@ class AssetInfo(Base):
)
__table_args__ = (
UniqueConstraint("asset_id", "owner_id", "name", name="uq_assets_info_asset_owner_name"),
UniqueConstraint(
"asset_id", "owner_id", "name", name="uq_assets_info_asset_owner_name"
),
Index("ix_assets_info_owner_name", "owner_id", "name"),
Index("ix_assets_info_owner_id", "owner_id"),
Index("ix_assets_info_asset_id", "asset_id"),
@@ -196,7 +218,7 @@ class AssetInfoTag(Base):
)
origin: Mapped[str] = mapped_column(String(32), nullable=False, default="manual")
added_at: Mapped[datetime] = mapped_column(
DateTime(timezone=False), nullable=False, default=utcnow
DateTime(timezone=False), nullable=False, default=get_utc_now
)
asset_info: Mapped[AssetInfo] = relationship(back_populates="tag_links")
@@ -225,9 +247,7 @@ class Tag(Base):
overlaps="asset_info_links,tag_links,tags,asset_info",
)
__table_args__ = (
Index("ix_tags_tag_type", "tag_type"),
)
__table_args__ = (Index("ix_tags_tag_type", "tag_type"),)
def __repr__(self) -> str:
return f"<Tag {self.name}>"

View File

@@ -1,976 +0,0 @@
import os
import logging
import sqlalchemy as sa
from collections import defaultdict
from datetime import datetime
from typing import Iterable, Any
from sqlalchemy import select, delete, exists, func
from sqlalchemy.dialects import sqlite
from sqlalchemy.exc import IntegrityError
from sqlalchemy.orm import Session, contains_eager, noload
from app.assets.database.models import Asset, AssetInfo, AssetCacheState, AssetInfoMeta, AssetInfoTag, Tag
from app.assets.helpers import (
compute_relative_filename, escape_like_prefix, normalize_tags, project_kv, utcnow
)
from typing import Sequence
def visible_owner_clause(owner_id: str) -> sa.sql.ClauseElement:
"""Build owner visibility predicate for reads. Owner-less rows are visible to everyone."""
owner_id = (owner_id or "").strip()
if owner_id == "":
return AssetInfo.owner_id == ""
return AssetInfo.owner_id.in_(["", owner_id])
def pick_best_live_path(states: Sequence[AssetCacheState]) -> str:
"""
Return the best on-disk path among cache states:
1) Prefer a path that exists with needs_verify == False (already verified).
2) Otherwise, pick the first path that exists.
3) Otherwise return empty string.
"""
alive = [s for s in states if getattr(s, "file_path", None) and os.path.isfile(s.file_path)]
if not alive:
return ""
for s in alive:
if not getattr(s, "needs_verify", False):
return s.file_path
return alive[0].file_path
def apply_tag_filters(
stmt: sa.sql.Select,
include_tags: Sequence[str] | None = None,
exclude_tags: Sequence[str] | None = None,
) -> sa.sql.Select:
"""include_tags: every tag must be present; exclude_tags: none may be present."""
include_tags = normalize_tags(include_tags)
exclude_tags = normalize_tags(exclude_tags)
if include_tags:
for tag_name in include_tags:
stmt = stmt.where(
exists().where(
(AssetInfoTag.asset_info_id == AssetInfo.id)
& (AssetInfoTag.tag_name == tag_name)
)
)
if exclude_tags:
stmt = stmt.where(
~exists().where(
(AssetInfoTag.asset_info_id == AssetInfo.id)
& (AssetInfoTag.tag_name.in_(exclude_tags))
)
)
return stmt
def apply_metadata_filter(
stmt: sa.sql.Select,
metadata_filter: dict | None = None,
) -> sa.sql.Select:
"""Apply filters using asset_info_meta projection table."""
if not metadata_filter:
return stmt
def _exists_for_pred(key: str, *preds) -> sa.sql.ClauseElement:
return sa.exists().where(
AssetInfoMeta.asset_info_id == AssetInfo.id,
AssetInfoMeta.key == key,
*preds,
)
def _exists_clause_for_value(key: str, value) -> sa.sql.ClauseElement:
if value is None:
no_row_for_key = sa.not_(
sa.exists().where(
AssetInfoMeta.asset_info_id == AssetInfo.id,
AssetInfoMeta.key == key,
)
)
null_row = _exists_for_pred(
key,
AssetInfoMeta.val_json.is_(None),
AssetInfoMeta.val_str.is_(None),
AssetInfoMeta.val_num.is_(None),
AssetInfoMeta.val_bool.is_(None),
)
return sa.or_(no_row_for_key, null_row)
if isinstance(value, bool):
return _exists_for_pred(key, AssetInfoMeta.val_bool == bool(value))
if isinstance(value, (int, float)):
from decimal import Decimal
num = value if isinstance(value, Decimal) else Decimal(str(value))
return _exists_for_pred(key, AssetInfoMeta.val_num == num)
if isinstance(value, str):
return _exists_for_pred(key, AssetInfoMeta.val_str == value)
return _exists_for_pred(key, AssetInfoMeta.val_json == value)
for k, v in metadata_filter.items():
if isinstance(v, list):
ors = [_exists_clause_for_value(k, elem) for elem in v]
if ors:
stmt = stmt.where(sa.or_(*ors))
else:
stmt = stmt.where(_exists_clause_for_value(k, v))
return stmt
def asset_exists_by_hash(
session: Session,
*,
asset_hash: str,
) -> bool:
"""
Check if an asset with a given hash exists in database.
"""
row = (
session.execute(
select(sa.literal(True)).select_from(Asset).where(Asset.hash == asset_hash).limit(1)
)
).first()
return row is not None
def asset_info_exists_for_asset_id(
session: Session,
*,
asset_id: str,
) -> bool:
q = (
select(sa.literal(True))
.select_from(AssetInfo)
.where(AssetInfo.asset_id == asset_id)
.limit(1)
)
return (session.execute(q)).first() is not None
def get_asset_by_hash(
session: Session,
*,
asset_hash: str,
) -> Asset | None:
return (
session.execute(select(Asset).where(Asset.hash == asset_hash).limit(1))
).scalars().first()
def get_asset_info_by_id(
session: Session,
*,
asset_info_id: str,
) -> AssetInfo | None:
return session.get(AssetInfo, asset_info_id)
def list_asset_infos_page(
session: Session,
owner_id: str = "",
include_tags: Sequence[str] | None = None,
exclude_tags: Sequence[str] | None = None,
name_contains: str | None = None,
metadata_filter: dict | None = None,
limit: int = 20,
offset: int = 0,
sort: str = "created_at",
order: str = "desc",
) -> tuple[list[AssetInfo], dict[str, list[str]], int]:
base = (
select(AssetInfo)
.join(Asset, Asset.id == AssetInfo.asset_id)
.options(contains_eager(AssetInfo.asset), noload(AssetInfo.tags))
.where(visible_owner_clause(owner_id))
)
if name_contains:
escaped, esc = escape_like_prefix(name_contains)
base = base.where(AssetInfo.name.ilike(f"%{escaped}%", escape=esc))
base = apply_tag_filters(base, include_tags, exclude_tags)
base = apply_metadata_filter(base, metadata_filter)
sort = (sort or "created_at").lower()
order = (order or "desc").lower()
sort_map = {
"name": AssetInfo.name,
"created_at": AssetInfo.created_at,
"updated_at": AssetInfo.updated_at,
"last_access_time": AssetInfo.last_access_time,
"size": Asset.size_bytes,
}
sort_col = sort_map.get(sort, AssetInfo.created_at)
sort_exp = sort_col.desc() if order == "desc" else sort_col.asc()
base = base.order_by(sort_exp).limit(limit).offset(offset)
count_stmt = (
select(sa.func.count())
.select_from(AssetInfo)
.join(Asset, Asset.id == AssetInfo.asset_id)
.where(visible_owner_clause(owner_id))
)
if name_contains:
escaped, esc = escape_like_prefix(name_contains)
count_stmt = count_stmt.where(AssetInfo.name.ilike(f"%{escaped}%", escape=esc))
count_stmt = apply_tag_filters(count_stmt, include_tags, exclude_tags)
count_stmt = apply_metadata_filter(count_stmt, metadata_filter)
total = int((session.execute(count_stmt)).scalar_one() or 0)
infos = (session.execute(base)).unique().scalars().all()
id_list: list[str] = [i.id for i in infos]
tag_map: dict[str, list[str]] = defaultdict(list)
if id_list:
rows = session.execute(
select(AssetInfoTag.asset_info_id, Tag.name)
.join(Tag, Tag.name == AssetInfoTag.tag_name)
.where(AssetInfoTag.asset_info_id.in_(id_list))
.order_by(AssetInfoTag.added_at)
)
for aid, tag_name in rows.all():
tag_map[aid].append(tag_name)
return infos, tag_map, total
def fetch_asset_info_asset_and_tags(
session: Session,
asset_info_id: str,
owner_id: str = "",
) -> tuple[AssetInfo, Asset, list[str]] | None:
stmt = (
select(AssetInfo, Asset, Tag.name)
.join(Asset, Asset.id == AssetInfo.asset_id)
.join(AssetInfoTag, AssetInfoTag.asset_info_id == AssetInfo.id, isouter=True)
.join(Tag, Tag.name == AssetInfoTag.tag_name, isouter=True)
.where(
AssetInfo.id == asset_info_id,
visible_owner_clause(owner_id),
)
.options(noload(AssetInfo.tags))
.order_by(Tag.name.asc())
)
rows = (session.execute(stmt)).all()
if not rows:
return None
first_info, first_asset, _ = rows[0]
tags: list[str] = []
seen: set[str] = set()
for _info, _asset, tag_name in rows:
if tag_name and tag_name not in seen:
seen.add(tag_name)
tags.append(tag_name)
return first_info, first_asset, tags
def fetch_asset_info_and_asset(
session: Session,
*,
asset_info_id: str,
owner_id: str = "",
) -> tuple[AssetInfo, Asset] | None:
stmt = (
select(AssetInfo, Asset)
.join(Asset, Asset.id == AssetInfo.asset_id)
.where(
AssetInfo.id == asset_info_id,
visible_owner_clause(owner_id),
)
.limit(1)
.options(noload(AssetInfo.tags))
)
row = session.execute(stmt)
pair = row.first()
if not pair:
return None
return pair[0], pair[1]
def list_cache_states_by_asset_id(
session: Session, *, asset_id: str
) -> Sequence[AssetCacheState]:
return (
session.execute(
select(AssetCacheState)
.where(AssetCacheState.asset_id == asset_id)
.order_by(AssetCacheState.id.asc())
)
).scalars().all()
def touch_asset_info_by_id(
session: Session,
*,
asset_info_id: str,
ts: datetime | None = None,
only_if_newer: bool = True,
) -> None:
ts = ts or utcnow()
stmt = sa.update(AssetInfo).where(AssetInfo.id == asset_info_id)
if only_if_newer:
stmt = stmt.where(
sa.or_(AssetInfo.last_access_time.is_(None), AssetInfo.last_access_time < ts)
)
session.execute(stmt.values(last_access_time=ts))
def create_asset_info_for_existing_asset(
session: Session,
*,
asset_hash: str,
name: str,
user_metadata: dict | None = None,
tags: Sequence[str] | None = None,
tag_origin: str = "manual",
owner_id: str = "",
) -> AssetInfo:
"""Create or return an existing AssetInfo for an Asset identified by asset_hash."""
now = utcnow()
asset = get_asset_by_hash(session, asset_hash=asset_hash)
if not asset:
raise ValueError(f"Unknown asset hash {asset_hash}")
info = AssetInfo(
owner_id=owner_id,
name=name,
asset_id=asset.id,
preview_id=None,
created_at=now,
updated_at=now,
last_access_time=now,
)
try:
with session.begin_nested():
session.add(info)
session.flush()
except IntegrityError:
existing = (
session.execute(
select(AssetInfo)
.options(noload(AssetInfo.tags))
.where(
AssetInfo.asset_id == asset.id,
AssetInfo.name == name,
AssetInfo.owner_id == owner_id,
)
.limit(1)
)
).unique().scalars().first()
if not existing:
raise RuntimeError("AssetInfo upsert failed to find existing row after conflict.")
return existing
# metadata["filename"] hack
new_meta = dict(user_metadata or {})
computed_filename = None
try:
p = pick_best_live_path(list_cache_states_by_asset_id(session, asset_id=asset.id))
if p:
computed_filename = compute_relative_filename(p)
except Exception:
computed_filename = None
if computed_filename:
new_meta["filename"] = computed_filename
if new_meta:
replace_asset_info_metadata_projection(
session,
asset_info_id=info.id,
user_metadata=new_meta,
)
if tags is not None:
set_asset_info_tags(
session,
asset_info_id=info.id,
tags=tags,
origin=tag_origin,
)
return info
def set_asset_info_tags(
session: Session,
*,
asset_info_id: str,
tags: Sequence[str],
origin: str = "manual",
) -> dict:
desired = normalize_tags(tags)
current = set(
tag_name for (tag_name,) in (
session.execute(select(AssetInfoTag.tag_name).where(AssetInfoTag.asset_info_id == asset_info_id))
).all()
)
to_add = [t for t in desired if t not in current]
to_remove = [t for t in current if t not in desired]
if to_add:
ensure_tags_exist(session, to_add, tag_type="user")
session.add_all([
AssetInfoTag(asset_info_id=asset_info_id, tag_name=t, origin=origin, added_at=utcnow())
for t in to_add
])
session.flush()
if to_remove:
session.execute(
delete(AssetInfoTag)
.where(AssetInfoTag.asset_info_id == asset_info_id, AssetInfoTag.tag_name.in_(to_remove))
)
session.flush()
return {"added": to_add, "removed": to_remove, "total": desired}
def replace_asset_info_metadata_projection(
session: Session,
*,
asset_info_id: str,
user_metadata: dict | None = None,
) -> None:
info = session.get(AssetInfo, asset_info_id)
if not info:
raise ValueError(f"AssetInfo {asset_info_id} not found")
info.user_metadata = user_metadata or {}
info.updated_at = utcnow()
session.flush()
session.execute(delete(AssetInfoMeta).where(AssetInfoMeta.asset_info_id == asset_info_id))
session.flush()
if not user_metadata:
return
rows: list[AssetInfoMeta] = []
for k, v in user_metadata.items():
for r in project_kv(k, v):
rows.append(
AssetInfoMeta(
asset_info_id=asset_info_id,
key=r["key"],
ordinal=int(r["ordinal"]),
val_str=r.get("val_str"),
val_num=r.get("val_num"),
val_bool=r.get("val_bool"),
val_json=r.get("val_json"),
)
)
if rows:
session.add_all(rows)
session.flush()
def ingest_fs_asset(
session: Session,
*,
asset_hash: str,
abs_path: str,
size_bytes: int,
mtime_ns: int,
mime_type: str | None = None,
info_name: str | None = None,
owner_id: str = "",
preview_id: str | None = None,
user_metadata: dict | None = None,
tags: Sequence[str] = (),
tag_origin: str = "manual",
require_existing_tags: bool = False,
) -> dict:
"""
Idempotently upsert:
- Asset by content hash (create if missing)
- AssetCacheState(file_path) pointing to asset_id
- Optionally AssetInfo + tag links and metadata projection
Returns flags and ids.
"""
locator = os.path.abspath(abs_path)
now = utcnow()
if preview_id:
if not session.get(Asset, preview_id):
preview_id = None
out: dict[str, Any] = {
"asset_created": False,
"asset_updated": False,
"state_created": False,
"state_updated": False,
"asset_info_id": None,
}
# 1) Asset by hash
asset = (
session.execute(select(Asset).where(Asset.hash == asset_hash).limit(1))
).scalars().first()
if not asset:
vals = {
"hash": asset_hash,
"size_bytes": int(size_bytes),
"mime_type": mime_type,
"created_at": now,
}
res = session.execute(
sqlite.insert(Asset)
.values(**vals)
.on_conflict_do_nothing(index_elements=[Asset.hash])
)
if int(res.rowcount or 0) > 0:
out["asset_created"] = True
asset = (
session.execute(
select(Asset).where(Asset.hash == asset_hash).limit(1)
)
).scalars().first()
if not asset:
raise RuntimeError("Asset row not found after upsert.")
else:
changed = False
if asset.size_bytes != int(size_bytes) and int(size_bytes) > 0:
asset.size_bytes = int(size_bytes)
changed = True
if mime_type and asset.mime_type != mime_type:
asset.mime_type = mime_type
changed = True
if changed:
out["asset_updated"] = True
# 2) AssetCacheState upsert by file_path (unique)
vals = {
"asset_id": asset.id,
"file_path": locator,
"mtime_ns": int(mtime_ns),
}
ins = (
sqlite.insert(AssetCacheState)
.values(**vals)
.on_conflict_do_nothing(index_elements=[AssetCacheState.file_path])
)
res = session.execute(ins)
if int(res.rowcount or 0) > 0:
out["state_created"] = True
else:
upd = (
sa.update(AssetCacheState)
.where(AssetCacheState.file_path == locator)
.where(
sa.or_(
AssetCacheState.asset_id != asset.id,
AssetCacheState.mtime_ns.is_(None),
AssetCacheState.mtime_ns != int(mtime_ns),
)
)
.values(asset_id=asset.id, mtime_ns=int(mtime_ns))
)
res2 = session.execute(upd)
if int(res2.rowcount or 0) > 0:
out["state_updated"] = True
# 3) Optional AssetInfo + tags + metadata
if info_name:
try:
with session.begin_nested():
info = AssetInfo(
owner_id=owner_id,
name=info_name,
asset_id=asset.id,
preview_id=preview_id,
created_at=now,
updated_at=now,
last_access_time=now,
)
session.add(info)
session.flush()
out["asset_info_id"] = info.id
except IntegrityError:
pass
existing_info = (
session.execute(
select(AssetInfo)
.where(
AssetInfo.asset_id == asset.id,
AssetInfo.name == info_name,
(AssetInfo.owner_id == owner_id),
)
.limit(1)
)
).unique().scalar_one_or_none()
if not existing_info:
raise RuntimeError("Failed to update or insert AssetInfo.")
if preview_id and existing_info.preview_id != preview_id:
existing_info.preview_id = preview_id
existing_info.updated_at = now
if existing_info.last_access_time < now:
existing_info.last_access_time = now
session.flush()
out["asset_info_id"] = existing_info.id
norm = [t.strip().lower() for t in (tags or []) if (t or "").strip()]
if norm and out["asset_info_id"] is not None:
if not require_existing_tags:
ensure_tags_exist(session, norm, tag_type="user")
existing_tag_names = set(
name for (name,) in (session.execute(select(Tag.name).where(Tag.name.in_(norm)))).all()
)
missing = [t for t in norm if t not in existing_tag_names]
if missing and require_existing_tags:
raise ValueError(f"Unknown tags: {missing}")
existing_links = set(
tag_name
for (tag_name,) in (
session.execute(
select(AssetInfoTag.tag_name).where(AssetInfoTag.asset_info_id == out["asset_info_id"])
)
).all()
)
to_add = [t for t in norm if t in existing_tag_names and t not in existing_links]
if to_add:
session.add_all(
[
AssetInfoTag(
asset_info_id=out["asset_info_id"],
tag_name=t,
origin=tag_origin,
added_at=now,
)
for t in to_add
]
)
session.flush()
# metadata["filename"] hack
if out["asset_info_id"] is not None:
primary_path = pick_best_live_path(list_cache_states_by_asset_id(session, asset_id=asset.id))
computed_filename = compute_relative_filename(primary_path) if primary_path else None
current_meta = existing_info.user_metadata or {}
new_meta = dict(current_meta)
if user_metadata is not None:
for k, v in user_metadata.items():
new_meta[k] = v
if computed_filename:
new_meta["filename"] = computed_filename
if new_meta != current_meta:
replace_asset_info_metadata_projection(
session,
asset_info_id=out["asset_info_id"],
user_metadata=new_meta,
)
try:
remove_missing_tag_for_asset_id(session, asset_id=asset.id)
except Exception:
logging.exception("Failed to clear 'missing' tag for asset %s", asset.id)
return out
def update_asset_info_full(
session: Session,
*,
asset_info_id: str,
name: str | None = None,
tags: Sequence[str] | None = None,
user_metadata: dict | None = None,
tag_origin: str = "manual",
asset_info_row: Any = None,
) -> AssetInfo:
if not asset_info_row:
info = session.get(AssetInfo, asset_info_id)
if not info:
raise ValueError(f"AssetInfo {asset_info_id} not found")
else:
info = asset_info_row
touched = False
if name is not None and name != info.name:
info.name = name
touched = True
computed_filename = None
try:
p = pick_best_live_path(list_cache_states_by_asset_id(session, asset_id=info.asset_id))
if p:
computed_filename = compute_relative_filename(p)
except Exception:
computed_filename = None
if user_metadata is not None:
new_meta = dict(user_metadata)
if computed_filename:
new_meta["filename"] = computed_filename
replace_asset_info_metadata_projection(
session, asset_info_id=asset_info_id, user_metadata=new_meta
)
touched = True
else:
if computed_filename:
current_meta = info.user_metadata or {}
if current_meta.get("filename") != computed_filename:
new_meta = dict(current_meta)
new_meta["filename"] = computed_filename
replace_asset_info_metadata_projection(
session, asset_info_id=asset_info_id, user_metadata=new_meta
)
touched = True
if tags is not None:
set_asset_info_tags(
session,
asset_info_id=asset_info_id,
tags=tags,
origin=tag_origin,
)
touched = True
if touched and user_metadata is None:
info.updated_at = utcnow()
session.flush()
return info
def delete_asset_info_by_id(
session: Session,
*,
asset_info_id: str,
owner_id: str,
) -> bool:
stmt = sa.delete(AssetInfo).where(
AssetInfo.id == asset_info_id,
visible_owner_clause(owner_id),
)
return int((session.execute(stmt)).rowcount or 0) > 0
def list_tags_with_usage(
session: Session,
prefix: str | None = None,
limit: int = 100,
offset: int = 0,
include_zero: bool = True,
order: str = "count_desc",
owner_id: str = "",
) -> tuple[list[tuple[str, str, int]], int]:
counts_sq = (
select(
AssetInfoTag.tag_name.label("tag_name"),
func.count(AssetInfoTag.asset_info_id).label("cnt"),
)
.select_from(AssetInfoTag)
.join(AssetInfo, AssetInfo.id == AssetInfoTag.asset_info_id)
.where(visible_owner_clause(owner_id))
.group_by(AssetInfoTag.tag_name)
.subquery()
)
q = (
select(
Tag.name,
Tag.tag_type,
func.coalesce(counts_sq.c.cnt, 0).label("count"),
)
.select_from(Tag)
.join(counts_sq, counts_sq.c.tag_name == Tag.name, isouter=True)
)
if prefix:
escaped, esc = escape_like_prefix(prefix.strip().lower())
q = q.where(Tag.name.like(escaped + "%", escape=esc))
if not include_zero:
q = q.where(func.coalesce(counts_sq.c.cnt, 0) > 0)
if order == "name_asc":
q = q.order_by(Tag.name.asc())
else:
q = q.order_by(func.coalesce(counts_sq.c.cnt, 0).desc(), Tag.name.asc())
total_q = select(func.count()).select_from(Tag)
if prefix:
escaped, esc = escape_like_prefix(prefix.strip().lower())
total_q = total_q.where(Tag.name.like(escaped + "%", escape=esc))
if not include_zero:
total_q = total_q.where(
Tag.name.in_(select(AssetInfoTag.tag_name).group_by(AssetInfoTag.tag_name))
)
rows = (session.execute(q.limit(limit).offset(offset))).all()
total = (session.execute(total_q)).scalar_one()
rows_norm = [(name, ttype, int(count or 0)) for (name, ttype, count) in rows]
return rows_norm, int(total or 0)
def ensure_tags_exist(session: Session, names: Iterable[str], tag_type: str = "user") -> None:
wanted = normalize_tags(list(names))
if not wanted:
return
rows = [{"name": n, "tag_type": tag_type} for n in list(dict.fromkeys(wanted))]
ins = (
sqlite.insert(Tag)
.values(rows)
.on_conflict_do_nothing(index_elements=[Tag.name])
)
session.execute(ins)
def get_asset_tags(session: Session, *, asset_info_id: str) -> list[str]:
return [
tag_name for (tag_name,) in (
session.execute(
select(AssetInfoTag.tag_name).where(AssetInfoTag.asset_info_id == asset_info_id)
)
).all()
]
def add_tags_to_asset_info(
session: Session,
*,
asset_info_id: str,
tags: Sequence[str],
origin: str = "manual",
create_if_missing: bool = True,
asset_info_row: Any = None,
) -> dict:
if not asset_info_row:
info = session.get(AssetInfo, asset_info_id)
if not info:
raise ValueError(f"AssetInfo {asset_info_id} not found")
norm = normalize_tags(tags)
if not norm:
total = get_asset_tags(session, asset_info_id=asset_info_id)
return {"added": [], "already_present": [], "total_tags": total}
if create_if_missing:
ensure_tags_exist(session, norm, tag_type="user")
current = {
tag_name
for (tag_name,) in (
session.execute(
sa.select(AssetInfoTag.tag_name).where(AssetInfoTag.asset_info_id == asset_info_id)
)
).all()
}
want = set(norm)
to_add = sorted(want - current)
if to_add:
with session.begin_nested() as nested:
try:
session.add_all(
[
AssetInfoTag(
asset_info_id=asset_info_id,
tag_name=t,
origin=origin,
added_at=utcnow(),
)
for t in to_add
]
)
session.flush()
except IntegrityError:
nested.rollback()
after = set(get_asset_tags(session, asset_info_id=asset_info_id))
return {
"added": sorted(((after - current) & want)),
"already_present": sorted(want & current),
"total_tags": sorted(after),
}
def remove_tags_from_asset_info(
session: Session,
*,
asset_info_id: str,
tags: Sequence[str],
) -> dict:
info = session.get(AssetInfo, asset_info_id)
if not info:
raise ValueError(f"AssetInfo {asset_info_id} not found")
norm = normalize_tags(tags)
if not norm:
total = get_asset_tags(session, asset_info_id=asset_info_id)
return {"removed": [], "not_present": [], "total_tags": total}
existing = {
tag_name
for (tag_name,) in (
session.execute(
sa.select(AssetInfoTag.tag_name).where(AssetInfoTag.asset_info_id == asset_info_id)
)
).all()
}
to_remove = sorted(set(t for t in norm if t in existing))
not_present = sorted(set(t for t in norm if t not in existing))
if to_remove:
session.execute(
delete(AssetInfoTag)
.where(
AssetInfoTag.asset_info_id == asset_info_id,
AssetInfoTag.tag_name.in_(to_remove),
)
)
session.flush()
total = get_asset_tags(session, asset_info_id=asset_info_id)
return {"removed": to_remove, "not_present": not_present, "total_tags": total}
def remove_missing_tag_for_asset_id(
session: Session,
*,
asset_id: str,
) -> None:
session.execute(
sa.delete(AssetInfoTag).where(
AssetInfoTag.asset_info_id.in_(sa.select(AssetInfo.id).where(AssetInfo.asset_id == asset_id)),
AssetInfoTag.tag_name == "missing",
)
)
def set_asset_info_preview(
session: Session,
*,
asset_info_id: str,
preview_asset_id: str | None = None,
) -> None:
"""Set or clear preview_id and bump updated_at. Raises on unknown IDs."""
info = session.get(AssetInfo, asset_info_id)
if not info:
raise ValueError(f"AssetInfo {asset_info_id} not found")
if preview_asset_id is None:
info.preview_id = None
else:
# validate preview asset exists
if not session.get(Asset, preview_asset_id):
raise ValueError(f"Preview Asset {preview_asset_id} not found")
info.preview_id = preview_asset_id
info.updated_at = utcnow()
session.flush()

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from app.assets.database.queries.asset import (
asset_exists_by_hash,
bulk_insert_assets,
get_asset_by_hash,
upsert_asset,
)
from app.assets.database.queries.asset_info import (
asset_info_exists_for_asset_id,
bulk_insert_asset_infos_ignore_conflicts,
delete_asset_info_by_id,
fetch_asset_info_and_asset,
fetch_asset_info_asset_and_tags,
get_asset_info_by_id,
get_asset_info_ids_by_ids,
get_or_create_asset_info,
insert_asset_info,
list_asset_infos_page,
set_asset_info_metadata,
set_asset_info_preview,
update_asset_info_access_time,
update_asset_info_name,
update_asset_info_timestamps,
update_asset_info_updated_at,
)
from app.assets.database.queries.cache_state import (
CacheStateRow,
bulk_insert_cache_states_ignore_conflicts,
bulk_set_needs_verify,
delete_assets_by_ids,
delete_cache_states_by_ids,
delete_cache_states_outside_prefixes,
delete_orphaned_seed_asset,
get_cache_states_by_paths_and_asset_ids,
get_cache_states_for_prefixes,
get_orphaned_seed_asset_ids,
list_cache_states_by_asset_id,
upsert_cache_state,
)
from app.assets.database.queries.tags import (
AddTagsDict,
RemoveTagsDict,
SetTagsDict,
add_missing_tag_for_asset_id,
add_tags_to_asset_info,
bulk_insert_tags_and_meta,
ensure_tags_exist,
get_asset_tags,
list_tags_with_usage,
remove_missing_tag_for_asset_id,
remove_tags_from_asset_info,
set_asset_info_tags,
)
__all__ = [
"AddTagsDict",
"CacheStateRow",
"RemoveTagsDict",
"SetTagsDict",
"add_missing_tag_for_asset_id",
"add_tags_to_asset_info",
"asset_exists_by_hash",
"asset_info_exists_for_asset_id",
"bulk_insert_asset_infos_ignore_conflicts",
"bulk_insert_assets",
"bulk_insert_cache_states_ignore_conflicts",
"bulk_insert_tags_and_meta",
"bulk_set_needs_verify",
"delete_asset_info_by_id",
"delete_assets_by_ids",
"delete_cache_states_by_ids",
"delete_cache_states_outside_prefixes",
"delete_orphaned_seed_asset",
"ensure_tags_exist",
"fetch_asset_info_and_asset",
"fetch_asset_info_asset_and_tags",
"get_asset_by_hash",
"get_asset_info_by_id",
"get_asset_info_ids_by_ids",
"get_asset_tags",
"get_cache_states_by_paths_and_asset_ids",
"get_cache_states_for_prefixes",
"get_or_create_asset_info",
"get_orphaned_seed_asset_ids",
"insert_asset_info",
"list_asset_infos_page",
"list_cache_states_by_asset_id",
"list_tags_with_usage",
"remove_missing_tag_for_asset_id",
"remove_tags_from_asset_info",
"set_asset_info_metadata",
"set_asset_info_preview",
"set_asset_info_tags",
"update_asset_info_access_time",
"update_asset_info_name",
"update_asset_info_timestamps",
"update_asset_info_updated_at",
"upsert_asset",
"upsert_cache_state",
]

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import sqlalchemy as sa
from sqlalchemy import select
from sqlalchemy.dialects import sqlite
from sqlalchemy.orm import Session
from app.assets.database.models import Asset
from app.assets.database.queries.common import calculate_rows_per_statement, iter_chunks
def asset_exists_by_hash(
session: Session,
asset_hash: str,
) -> bool:
"""
Check if an asset with a given hash exists in database.
"""
row = (
session.execute(
select(sa.literal(True))
.select_from(Asset)
.where(Asset.hash == asset_hash)
.limit(1)
)
).first()
return row is not None
def get_asset_by_hash(
session: Session,
asset_hash: str,
) -> Asset | None:
return (
(session.execute(select(Asset).where(Asset.hash == asset_hash).limit(1)))
.scalars()
.first()
)
def upsert_asset(
session: Session,
asset_hash: str,
size_bytes: int,
mime_type: str | None = None,
) -> tuple[Asset, bool, bool]:
"""Upsert an Asset by hash. Returns (asset, created, updated)."""
vals = {"hash": asset_hash, "size_bytes": int(size_bytes)}
if mime_type:
vals["mime_type"] = mime_type
ins = (
sqlite.insert(Asset)
.values(**vals)
.on_conflict_do_nothing(index_elements=[Asset.hash])
)
res = session.execute(ins)
created = int(res.rowcount or 0) > 0
asset = (
session.execute(select(Asset).where(Asset.hash == asset_hash).limit(1))
.scalars()
.first()
)
if not asset:
raise RuntimeError("Asset row not found after upsert.")
updated = False
if not created:
changed = False
if asset.size_bytes != int(size_bytes) and int(size_bytes) > 0:
asset.size_bytes = int(size_bytes)
changed = True
if mime_type and asset.mime_type != mime_type:
asset.mime_type = mime_type
changed = True
if changed:
updated = True
return asset, created, updated
def bulk_insert_assets(
session: Session,
rows: list[dict],
) -> None:
"""Bulk insert Asset rows. Each dict should have: id, hash, size_bytes, mime_type, created_at."""
if not rows:
return
ins = sqlite.insert(Asset)
for chunk in iter_chunks(rows, calculate_rows_per_statement(5)):
session.execute(ins, chunk)

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from collections import defaultdict
from datetime import datetime
from decimal import Decimal
from typing import Sequence
import sqlalchemy as sa
from sqlalchemy import delete, exists, select
from sqlalchemy.dialects import sqlite
from sqlalchemy.exc import IntegrityError
from sqlalchemy.orm import Session, contains_eager, noload
from app.assets.database.models import (
Asset,
AssetInfo,
AssetInfoMeta,
AssetInfoTag,
Tag,
)
from app.assets.database.queries.common import (
MAX_BIND_PARAMS,
build_visible_owner_clause,
calculate_rows_per_statement,
iter_chunks,
)
from app.assets.helpers import escape_sql_like_string, get_utc_now, normalize_tags
def _check_is_scalar(v):
if v is None:
return True
if isinstance(v, bool):
return True
if isinstance(v, (int, float, Decimal, str)):
return True
return False
def _scalar_to_row(key: str, ordinal: int, value) -> dict:
"""Convert a scalar value to a typed projection row."""
if value is None:
return {
"key": key,
"ordinal": ordinal,
"val_str": None,
"val_num": None,
"val_bool": None,
"val_json": None,
}
if isinstance(value, bool):
return {"key": key, "ordinal": ordinal, "val_bool": bool(value)}
if isinstance(value, (int, float, Decimal)):
num = value if isinstance(value, Decimal) else Decimal(str(value))
return {"key": key, "ordinal": ordinal, "val_num": num}
if isinstance(value, str):
return {"key": key, "ordinal": ordinal, "val_str": value}
return {"key": key, "ordinal": ordinal, "val_json": value}
def convert_metadata_to_rows(key: str, value) -> list[dict]:
"""
Turn a metadata key/value into typed projection rows.
Returns list[dict] with keys:
key, ordinal, and one of val_str / val_num / val_bool / val_json (others None)
"""
if value is None:
return [_scalar_to_row(key, 0, None)]
if _check_is_scalar(value):
return [_scalar_to_row(key, 0, value)]
if isinstance(value, list):
if all(_check_is_scalar(x) for x in value):
return [_scalar_to_row(key, i, x) for i, x in enumerate(value)]
return [{"key": key, "ordinal": i, "val_json": x} for i, x in enumerate(value)]
return [{"key": key, "ordinal": 0, "val_json": value}]
def _apply_tag_filters(
stmt: sa.sql.Select,
include_tags: Sequence[str] | None = None,
exclude_tags: Sequence[str] | None = None,
) -> sa.sql.Select:
"""include_tags: every tag must be present; exclude_tags: none may be present."""
include_tags = normalize_tags(include_tags)
exclude_tags = normalize_tags(exclude_tags)
if include_tags:
for tag_name in include_tags:
stmt = stmt.where(
exists().where(
(AssetInfoTag.asset_info_id == AssetInfo.id)
& (AssetInfoTag.tag_name == tag_name)
)
)
if exclude_tags:
stmt = stmt.where(
~exists().where(
(AssetInfoTag.asset_info_id == AssetInfo.id)
& (AssetInfoTag.tag_name.in_(exclude_tags))
)
)
return stmt
def _apply_metadata_filter(
stmt: sa.sql.Select,
metadata_filter: dict | None = None,
) -> sa.sql.Select:
"""Apply filters using asset_info_meta projection table."""
if not metadata_filter:
return stmt
def _exists_for_pred(key: str, *preds) -> sa.sql.ClauseElement:
return sa.exists().where(
AssetInfoMeta.asset_info_id == AssetInfo.id,
AssetInfoMeta.key == key,
*preds,
)
def _exists_clause_for_value(key: str, value) -> sa.sql.ClauseElement:
if value is None:
no_row_for_key = sa.not_(
sa.exists().where(
AssetInfoMeta.asset_info_id == AssetInfo.id,
AssetInfoMeta.key == key,
)
)
null_row = _exists_for_pred(
key,
AssetInfoMeta.val_json.is_(None),
AssetInfoMeta.val_str.is_(None),
AssetInfoMeta.val_num.is_(None),
AssetInfoMeta.val_bool.is_(None),
)
return sa.or_(no_row_for_key, null_row)
if isinstance(value, bool):
return _exists_for_pred(key, AssetInfoMeta.val_bool == bool(value))
if isinstance(value, (int, float)):
num = value if isinstance(value, Decimal) else Decimal(str(value))
return _exists_for_pred(key, AssetInfoMeta.val_num == num)
if isinstance(value, str):
return _exists_for_pred(key, AssetInfoMeta.val_str == value)
return _exists_for_pred(key, AssetInfoMeta.val_json == value)
for k, v in metadata_filter.items():
if isinstance(v, list):
ors = [_exists_clause_for_value(k, elem) for elem in v]
if ors:
stmt = stmt.where(sa.or_(*ors))
else:
stmt = stmt.where(_exists_clause_for_value(k, v))
return stmt
def asset_info_exists_for_asset_id(
session: Session,
asset_id: str,
) -> bool:
q = (
select(sa.literal(True))
.select_from(AssetInfo)
.where(AssetInfo.asset_id == asset_id)
.limit(1)
)
return (session.execute(q)).first() is not None
def get_asset_info_by_id(
session: Session,
asset_info_id: str,
) -> AssetInfo | None:
return session.get(AssetInfo, asset_info_id)
def insert_asset_info(
session: Session,
asset_id: str,
owner_id: str,
name: str,
preview_id: str | None = None,
) -> AssetInfo | None:
"""Insert a new AssetInfo. Returns None if unique constraint violated."""
now = get_utc_now()
try:
with session.begin_nested():
info = AssetInfo(
owner_id=owner_id,
name=name,
asset_id=asset_id,
preview_id=preview_id,
created_at=now,
updated_at=now,
last_access_time=now,
)
session.add(info)
session.flush()
return info
except IntegrityError:
return None
def get_or_create_asset_info(
session: Session,
asset_id: str,
owner_id: str,
name: str,
preview_id: str | None = None,
) -> tuple[AssetInfo, bool]:
"""Get existing or create new AssetInfo. Returns (info, created)."""
info = insert_asset_info(
session,
asset_id=asset_id,
owner_id=owner_id,
name=name,
preview_id=preview_id,
)
if info:
return info, True
existing = (
session.execute(
select(AssetInfo)
.where(
AssetInfo.asset_id == asset_id,
AssetInfo.name == name,
AssetInfo.owner_id == owner_id,
)
.limit(1)
)
.unique()
.scalar_one_or_none()
)
if not existing:
raise RuntimeError("Failed to find AssetInfo after insert conflict.")
return existing, False
def update_asset_info_timestamps(
session: Session,
asset_info: AssetInfo,
preview_id: str | None = None,
) -> None:
"""Update timestamps and optionally preview_id on existing AssetInfo."""
now = get_utc_now()
if preview_id and asset_info.preview_id != preview_id:
asset_info.preview_id = preview_id
asset_info.updated_at = now
if asset_info.last_access_time < now:
asset_info.last_access_time = now
session.flush()
def list_asset_infos_page(
session: Session,
owner_id: str = "",
include_tags: Sequence[str] | None = None,
exclude_tags: Sequence[str] | None = None,
name_contains: str | None = None,
metadata_filter: dict | None = None,
limit: int = 20,
offset: int = 0,
sort: str = "created_at",
order: str = "desc",
) -> tuple[list[AssetInfo], dict[str, list[str]], int]:
base = (
select(AssetInfo)
.join(Asset, Asset.id == AssetInfo.asset_id)
.options(contains_eager(AssetInfo.asset), noload(AssetInfo.tags))
.where(build_visible_owner_clause(owner_id))
)
if name_contains:
escaped, esc = escape_sql_like_string(name_contains)
base = base.where(AssetInfo.name.ilike(f"%{escaped}%", escape=esc))
base = _apply_tag_filters(base, include_tags, exclude_tags)
base = _apply_metadata_filter(base, metadata_filter)
sort = (sort or "created_at").lower()
order = (order or "desc").lower()
sort_map = {
"name": AssetInfo.name,
"created_at": AssetInfo.created_at,
"updated_at": AssetInfo.updated_at,
"last_access_time": AssetInfo.last_access_time,
"size": Asset.size_bytes,
}
sort_col = sort_map.get(sort, AssetInfo.created_at)
sort_exp = sort_col.desc() if order == "desc" else sort_col.asc()
base = base.order_by(sort_exp).limit(limit).offset(offset)
count_stmt = (
select(sa.func.count())
.select_from(AssetInfo)
.join(Asset, Asset.id == AssetInfo.asset_id)
.where(build_visible_owner_clause(owner_id))
)
if name_contains:
escaped, esc = escape_sql_like_string(name_contains)
count_stmt = count_stmt.where(AssetInfo.name.ilike(f"%{escaped}%", escape=esc))
count_stmt = _apply_tag_filters(count_stmt, include_tags, exclude_tags)
count_stmt = _apply_metadata_filter(count_stmt, metadata_filter)
total = int((session.execute(count_stmt)).scalar_one() or 0)
infos = (session.execute(base)).unique().scalars().all()
id_list: list[str] = [i.id for i in infos]
tag_map: dict[str, list[str]] = defaultdict(list)
if id_list:
rows = session.execute(
select(AssetInfoTag.asset_info_id, Tag.name)
.join(Tag, Tag.name == AssetInfoTag.tag_name)
.where(AssetInfoTag.asset_info_id.in_(id_list))
.order_by(AssetInfoTag.added_at)
)
for aid, tag_name in rows.all():
tag_map[aid].append(tag_name)
return infos, tag_map, total
def fetch_asset_info_asset_and_tags(
session: Session,
asset_info_id: str,
owner_id: str = "",
) -> tuple[AssetInfo, Asset, list[str]] | None:
stmt = (
select(AssetInfo, Asset, Tag.name)
.join(Asset, Asset.id == AssetInfo.asset_id)
.join(AssetInfoTag, AssetInfoTag.asset_info_id == AssetInfo.id, isouter=True)
.join(Tag, Tag.name == AssetInfoTag.tag_name, isouter=True)
.where(
AssetInfo.id == asset_info_id,
build_visible_owner_clause(owner_id),
)
.options(noload(AssetInfo.tags))
.order_by(Tag.name.asc())
)
rows = (session.execute(stmt)).all()
if not rows:
return None
first_info, first_asset, _ = rows[0]
tags: list[str] = []
seen: set[str] = set()
for _info, _asset, tag_name in rows:
if tag_name and tag_name not in seen:
seen.add(tag_name)
tags.append(tag_name)
return first_info, first_asset, tags
def fetch_asset_info_and_asset(
session: Session,
asset_info_id: str,
owner_id: str = "",
) -> tuple[AssetInfo, Asset] | None:
stmt = (
select(AssetInfo, Asset)
.join(Asset, Asset.id == AssetInfo.asset_id)
.where(
AssetInfo.id == asset_info_id,
build_visible_owner_clause(owner_id),
)
.limit(1)
.options(noload(AssetInfo.tags))
)
row = session.execute(stmt)
pair = row.first()
if not pair:
return None
return pair[0], pair[1]
def update_asset_info_access_time(
session: Session,
asset_info_id: str,
ts: datetime | None = None,
only_if_newer: bool = True,
) -> None:
ts = ts or get_utc_now()
stmt = sa.update(AssetInfo).where(AssetInfo.id == asset_info_id)
if only_if_newer:
stmt = stmt.where(
sa.or_(
AssetInfo.last_access_time.is_(None), AssetInfo.last_access_time < ts
)
)
session.execute(stmt.values(last_access_time=ts))
def update_asset_info_name(
session: Session,
asset_info_id: str,
name: str,
) -> None:
"""Update the name of an AssetInfo."""
now = get_utc_now()
session.execute(
sa.update(AssetInfo)
.where(AssetInfo.id == asset_info_id)
.values(name=name, updated_at=now)
)
def update_asset_info_updated_at(
session: Session,
asset_info_id: str,
ts: datetime | None = None,
) -> None:
"""Update the updated_at timestamp of an AssetInfo."""
ts = ts or get_utc_now()
session.execute(
sa.update(AssetInfo).where(AssetInfo.id == asset_info_id).values(updated_at=ts)
)
def set_asset_info_metadata(
session: Session,
asset_info_id: str,
user_metadata: dict | None = None,
) -> None:
info = session.get(AssetInfo, asset_info_id)
if not info:
raise ValueError(f"AssetInfo {asset_info_id} not found")
info.user_metadata = user_metadata or {}
info.updated_at = get_utc_now()
session.flush()
session.execute(
delete(AssetInfoMeta).where(AssetInfoMeta.asset_info_id == asset_info_id)
)
session.flush()
if not user_metadata:
return
rows: list[AssetInfoMeta] = []
for k, v in user_metadata.items():
for r in convert_metadata_to_rows(k, v):
rows.append(
AssetInfoMeta(
asset_info_id=asset_info_id,
key=r["key"],
ordinal=int(r["ordinal"]),
val_str=r.get("val_str"),
val_num=r.get("val_num"),
val_bool=r.get("val_bool"),
val_json=r.get("val_json"),
)
)
if rows:
session.add_all(rows)
session.flush()
def delete_asset_info_by_id(
session: Session,
asset_info_id: str,
owner_id: str,
) -> bool:
stmt = sa.delete(AssetInfo).where(
AssetInfo.id == asset_info_id,
build_visible_owner_clause(owner_id),
)
return int((session.execute(stmt)).rowcount or 0) > 0
def set_asset_info_preview(
session: Session,
asset_info_id: str,
preview_asset_id: str | None = None,
) -> None:
"""Set or clear preview_id and bump updated_at. Raises on unknown IDs."""
info = session.get(AssetInfo, asset_info_id)
if not info:
raise ValueError(f"AssetInfo {asset_info_id} not found")
if preview_asset_id is None:
info.preview_id = None
else:
if not session.get(Asset, preview_asset_id):
raise ValueError(f"Preview Asset {preview_asset_id} not found")
info.preview_id = preview_asset_id
info.updated_at = get_utc_now()
session.flush()
def bulk_insert_asset_infos_ignore_conflicts(
session: Session,
rows: list[dict],
) -> None:
"""Bulk insert AssetInfo rows with ON CONFLICT DO NOTHING.
Each dict should have: id, owner_id, name, asset_id, preview_id,
user_metadata, created_at, updated_at, last_access_time
"""
if not rows:
return
ins = sqlite.insert(AssetInfo).on_conflict_do_nothing(
index_elements=[AssetInfo.asset_id, AssetInfo.owner_id, AssetInfo.name]
)
for chunk in iter_chunks(rows, calculate_rows_per_statement(9)):
session.execute(ins, chunk)
def get_asset_info_ids_by_ids(
session: Session,
info_ids: list[str],
) -> set[str]:
"""Query to find which AssetInfo IDs exist in the database."""
if not info_ids:
return set()
found: set[str] = set()
for chunk in iter_chunks(info_ids, MAX_BIND_PARAMS):
result = session.execute(select(AssetInfo.id).where(AssetInfo.id.in_(chunk)))
found.update(result.scalars().all())
return found

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import os
from typing import NamedTuple, Sequence
import sqlalchemy as sa
from sqlalchemy import select
from sqlalchemy.dialects import sqlite
from sqlalchemy.orm import Session
from app.assets.database.models import Asset, AssetCacheState, AssetInfo
from app.assets.database.queries.common import (
MAX_BIND_PARAMS,
calculate_rows_per_statement,
iter_chunks,
)
from app.assets.helpers import escape_sql_like_string
class CacheStateRow(NamedTuple):
"""Row from cache state query with joined asset data."""
state_id: int
file_path: str
mtime_ns: int | None
needs_verify: bool
asset_id: str
asset_hash: str | None
size_bytes: int
def list_cache_states_by_asset_id(
session: Session, *, asset_id: str
) -> Sequence[AssetCacheState]:
return (
(
session.execute(
select(AssetCacheState)
.where(AssetCacheState.asset_id == asset_id)
.order_by(AssetCacheState.id.asc())
)
)
.scalars()
.all()
)
def upsert_cache_state(
session: Session,
asset_id: str,
file_path: str,
mtime_ns: int,
) -> tuple[bool, bool]:
"""Upsert a cache state by file_path. Returns (created, updated)."""
vals = {
"asset_id": asset_id,
"file_path": file_path,
"mtime_ns": int(mtime_ns),
}
ins = (
sqlite.insert(AssetCacheState)
.values(**vals)
.on_conflict_do_nothing(index_elements=[AssetCacheState.file_path])
)
res = session.execute(ins)
created = int(res.rowcount or 0) > 0
if created:
return True, False
upd = (
sa.update(AssetCacheState)
.where(AssetCacheState.file_path == file_path)
.where(
sa.or_(
AssetCacheState.asset_id != asset_id,
AssetCacheState.mtime_ns.is_(None),
AssetCacheState.mtime_ns != int(mtime_ns),
)
)
.values(asset_id=asset_id, mtime_ns=int(mtime_ns))
)
res2 = session.execute(upd)
updated = int(res2.rowcount or 0) > 0
return False, updated
def delete_cache_states_outside_prefixes(
session: Session, valid_prefixes: list[str]
) -> int:
"""Delete cache states with file_path not matching any of the valid prefixes.
Args:
session: Database session
valid_prefixes: List of absolute directory prefixes that are valid
Returns:
Number of cache states deleted
"""
if not valid_prefixes:
return 0
def make_prefix_condition(prefix: str):
base = prefix if prefix.endswith(os.sep) else prefix + os.sep
escaped, esc = escape_sql_like_string(base)
return AssetCacheState.file_path.like(escaped + "%", escape=esc)
matches_valid_prefix = sa.or_(*[make_prefix_condition(p) for p in valid_prefixes])
result = session.execute(sa.delete(AssetCacheState).where(~matches_valid_prefix))
return result.rowcount
def get_orphaned_seed_asset_ids(session: Session) -> list[str]:
"""Get IDs of seed assets (hash is None) with no remaining cache states.
Returns:
List of asset IDs that are orphaned
"""
orphan_subq = (
sa.select(Asset.id)
.outerjoin(AssetCacheState, AssetCacheState.asset_id == Asset.id)
.where(Asset.hash.is_(None), AssetCacheState.id.is_(None))
)
return [row[0] for row in session.execute(orphan_subq).all()]
def delete_assets_by_ids(session: Session, asset_ids: list[str]) -> int:
"""Delete assets and their AssetInfos by ID.
Args:
session: Database session
asset_ids: List of asset IDs to delete
Returns:
Number of assets deleted
"""
if not asset_ids:
return 0
session.execute(sa.delete(AssetInfo).where(AssetInfo.asset_id.in_(asset_ids)))
result = session.execute(sa.delete(Asset).where(Asset.id.in_(asset_ids)))
return result.rowcount
def get_cache_states_for_prefixes(
session: Session,
prefixes: list[str],
) -> list[CacheStateRow]:
"""Get all cache states with paths matching any of the given prefixes.
Args:
session: Database session
prefixes: List of absolute directory prefixes to match
Returns:
List of cache state rows with joined asset data, ordered by asset_id, state_id
"""
if not prefixes:
return []
conds = []
for p in prefixes:
base = os.path.abspath(p)
if not base.endswith(os.sep):
base += os.sep
escaped, esc = escape_sql_like_string(base)
conds.append(AssetCacheState.file_path.like(escaped + "%", escape=esc))
rows = session.execute(
sa.select(
AssetCacheState.id,
AssetCacheState.file_path,
AssetCacheState.mtime_ns,
AssetCacheState.needs_verify,
AssetCacheState.asset_id,
Asset.hash,
Asset.size_bytes,
)
.join(Asset, Asset.id == AssetCacheState.asset_id)
.where(sa.or_(*conds))
.order_by(AssetCacheState.asset_id.asc(), AssetCacheState.id.asc())
).all()
return [
CacheStateRow(
state_id=row[0],
file_path=row[1],
mtime_ns=row[2],
needs_verify=row[3],
asset_id=row[4],
asset_hash=row[5],
size_bytes=int(row[6] or 0),
)
for row in rows
]
def bulk_set_needs_verify(session: Session, state_ids: list[int], value: bool) -> int:
"""Set needs_verify flag for multiple cache states.
Returns: Number of rows updated
"""
if not state_ids:
return 0
result = session.execute(
sa.update(AssetCacheState)
.where(AssetCacheState.id.in_(state_ids))
.values(needs_verify=value)
)
return result.rowcount
def delete_cache_states_by_ids(session: Session, state_ids: list[int]) -> int:
"""Delete cache states by their IDs.
Returns: Number of rows deleted
"""
if not state_ids:
return 0
result = session.execute(
sa.delete(AssetCacheState).where(AssetCacheState.id.in_(state_ids))
)
return result.rowcount
def delete_orphaned_seed_asset(session: Session, asset_id: str) -> bool:
"""Delete a seed asset (hash is None) and its AssetInfos.
Returns: True if asset was deleted, False if not found
"""
session.execute(sa.delete(AssetInfo).where(AssetInfo.asset_id == asset_id))
asset = session.get(Asset, asset_id)
if asset:
session.delete(asset)
return True
return False
def bulk_insert_cache_states_ignore_conflicts(
session: Session,
rows: list[dict],
) -> None:
"""Bulk insert cache state rows with ON CONFLICT DO NOTHING on file_path.
Each dict should have: asset_id, file_path, mtime_ns
"""
if not rows:
return
ins = sqlite.insert(AssetCacheState).on_conflict_do_nothing(
index_elements=[AssetCacheState.file_path]
)
for chunk in iter_chunks(rows, calculate_rows_per_statement(3)):
session.execute(ins, chunk)
def get_cache_states_by_paths_and_asset_ids(
session: Session,
path_to_asset: dict[str, str],
) -> set[str]:
"""Query cache states to find paths where our asset_id won the insert.
Args:
path_to_asset: Mapping of file_path -> asset_id we tried to insert
Returns:
Set of file_paths where our asset_id is present
"""
if not path_to_asset:
return set()
paths = list(path_to_asset.keys())
winners: set[str] = set()
for chunk in iter_chunks(paths, MAX_BIND_PARAMS):
result = session.execute(
select(AssetCacheState.file_path).where(
AssetCacheState.file_path.in_(chunk),
AssetCacheState.asset_id.in_([path_to_asset[p] for p in chunk]),
)
)
winners.update(result.scalars().all())
return winners

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"""Shared utilities for database query modules."""
from typing import Iterable
import sqlalchemy as sa
from app.assets.database.models import AssetInfo
MAX_BIND_PARAMS = 800
def calculate_rows_per_statement(cols: int) -> int:
"""Calculate how many rows can fit in one statement given column count."""
return max(1, MAX_BIND_PARAMS // max(1, cols))
def iter_chunks(seq, n: int):
"""Yield successive n-sized chunks from seq."""
for i in range(0, len(seq), n):
yield seq[i : i + n]
def iter_row_chunks(rows: list[dict], cols_per_row: int) -> Iterable[list[dict]]:
"""Yield chunks of rows sized to fit within bind param limits."""
if not rows:
return []
rows_per_stmt = max(1, MAX_BIND_PARAMS // max(1, cols_per_row))
for i in range(0, len(rows), rows_per_stmt):
yield rows[i : i + rows_per_stmt]
def build_visible_owner_clause(owner_id: str) -> sa.sql.ClauseElement:
"""Build owner visibility predicate for reads. Owner-less rows are visible to everyone."""
owner_id = (owner_id or "").strip()
if owner_id == "":
return AssetInfo.owner_id == ""
return AssetInfo.owner_id.in_(["", owner_id])

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from typing import Iterable, Sequence, TypedDict
import sqlalchemy as sa
from sqlalchemy import delete, func, select
from sqlalchemy.dialects import sqlite
from sqlalchemy.exc import IntegrityError
from sqlalchemy.orm import Session
from app.assets.database.models import AssetInfo, AssetInfoMeta, AssetInfoTag, Tag
from app.assets.database.queries.common import (
build_visible_owner_clause,
iter_row_chunks,
)
from app.assets.helpers import escape_sql_like_string, get_utc_now, normalize_tags
class AddTagsDict(TypedDict):
added: list[str]
already_present: list[str]
total_tags: list[str]
class RemoveTagsDict(TypedDict):
removed: list[str]
not_present: list[str]
total_tags: list[str]
class SetTagsDict(TypedDict):
added: list[str]
removed: list[str]
total: list[str]
def ensure_tags_exist(
session: Session, names: Iterable[str], tag_type: str = "user"
) -> None:
wanted = normalize_tags(list(names))
if not wanted:
return
rows = [{"name": n, "tag_type": tag_type} for n in list(dict.fromkeys(wanted))]
ins = (
sqlite.insert(Tag)
.values(rows)
.on_conflict_do_nothing(index_elements=[Tag.name])
)
session.execute(ins)
def get_asset_tags(session: Session, asset_info_id: str) -> list[str]:
return [
tag_name
for (tag_name,) in (
session.execute(
select(AssetInfoTag.tag_name).where(
AssetInfoTag.asset_info_id == asset_info_id
)
)
).all()
]
def set_asset_info_tags(
session: Session,
asset_info_id: str,
tags: Sequence[str],
origin: str = "manual",
) -> SetTagsDict:
desired = normalize_tags(tags)
current = set(
tag_name
for (tag_name,) in (
session.execute(
select(AssetInfoTag.tag_name).where(
AssetInfoTag.asset_info_id == asset_info_id
)
)
).all()
)
to_add = [t for t in desired if t not in current]
to_remove = [t for t in current if t not in desired]
if to_add:
ensure_tags_exist(session, to_add, tag_type="user")
session.add_all(
[
AssetInfoTag(
asset_info_id=asset_info_id,
tag_name=t,
origin=origin,
added_at=get_utc_now(),
)
for t in to_add
]
)
session.flush()
if to_remove:
session.execute(
delete(AssetInfoTag).where(
AssetInfoTag.asset_info_id == asset_info_id,
AssetInfoTag.tag_name.in_(to_remove),
)
)
session.flush()
return {"added": to_add, "removed": to_remove, "total": desired}
def add_tags_to_asset_info(
session: Session,
asset_info_id: str,
tags: Sequence[str],
origin: str = "manual",
create_if_missing: bool = True,
asset_info_row: AssetInfo | None = None,
) -> AddTagsDict:
if not asset_info_row:
info = session.get(AssetInfo, asset_info_id)
if not info:
raise ValueError(f"AssetInfo {asset_info_id} not found")
norm = normalize_tags(tags)
if not norm:
total = get_asset_tags(session, asset_info_id=asset_info_id)
return {"added": [], "already_present": [], "total_tags": total}
if create_if_missing:
ensure_tags_exist(session, norm, tag_type="user")
current = {
tag_name
for (tag_name,) in (
session.execute(
sa.select(AssetInfoTag.tag_name).where(
AssetInfoTag.asset_info_id == asset_info_id
)
)
).all()
}
want = set(norm)
to_add = sorted(want - current)
if to_add:
with session.begin_nested() as nested:
try:
session.add_all(
[
AssetInfoTag(
asset_info_id=asset_info_id,
tag_name=t,
origin=origin,
added_at=get_utc_now(),
)
for t in to_add
]
)
session.flush()
except IntegrityError:
nested.rollback()
after = set(get_asset_tags(session, asset_info_id=asset_info_id))
return {
"added": sorted(((after - current) & want)),
"already_present": sorted(want & current),
"total_tags": sorted(after),
}
def remove_tags_from_asset_info(
session: Session,
asset_info_id: str,
tags: Sequence[str],
) -> RemoveTagsDict:
info = session.get(AssetInfo, asset_info_id)
if not info:
raise ValueError(f"AssetInfo {asset_info_id} not found")
norm = normalize_tags(tags)
if not norm:
total = get_asset_tags(session, asset_info_id=asset_info_id)
return {"removed": [], "not_present": [], "total_tags": total}
existing = {
tag_name
for (tag_name,) in (
session.execute(
sa.select(AssetInfoTag.tag_name).where(
AssetInfoTag.asset_info_id == asset_info_id
)
)
).all()
}
to_remove = sorted(set(t for t in norm if t in existing))
not_present = sorted(set(t for t in norm if t not in existing))
if to_remove:
session.execute(
delete(AssetInfoTag).where(
AssetInfoTag.asset_info_id == asset_info_id,
AssetInfoTag.tag_name.in_(to_remove),
)
)
session.flush()
total = get_asset_tags(session, asset_info_id=asset_info_id)
return {"removed": to_remove, "not_present": not_present, "total_tags": total}
def add_missing_tag_for_asset_id(
session: Session,
asset_id: str,
origin: str = "automatic",
) -> None:
select_rows = (
sa.select(
AssetInfo.id.label("asset_info_id"),
sa.literal("missing").label("tag_name"),
sa.literal(origin).label("origin"),
sa.literal(get_utc_now()).label("added_at"),
)
.where(AssetInfo.asset_id == asset_id)
.where(
sa.not_(
sa.exists().where(
(AssetInfoTag.asset_info_id == AssetInfo.id)
& (AssetInfoTag.tag_name == "missing")
)
)
)
)
session.execute(
sqlite.insert(AssetInfoTag)
.from_select(
["asset_info_id", "tag_name", "origin", "added_at"],
select_rows,
)
.on_conflict_do_nothing(
index_elements=[AssetInfoTag.asset_info_id, AssetInfoTag.tag_name]
)
)
def remove_missing_tag_for_asset_id(
session: Session,
asset_id: str,
) -> None:
session.execute(
sa.delete(AssetInfoTag).where(
AssetInfoTag.asset_info_id.in_(
sa.select(AssetInfo.id).where(AssetInfo.asset_id == asset_id)
),
AssetInfoTag.tag_name == "missing",
)
)
def list_tags_with_usage(
session: Session,
prefix: str | None = None,
limit: int = 100,
offset: int = 0,
include_zero: bool = True,
order: str = "count_desc",
owner_id: str = "",
) -> tuple[list[tuple[str, str, int]], int]:
counts_sq = (
select(
AssetInfoTag.tag_name.label("tag_name"),
func.count(AssetInfoTag.asset_info_id).label("cnt"),
)
.select_from(AssetInfoTag)
.join(AssetInfo, AssetInfo.id == AssetInfoTag.asset_info_id)
.where(build_visible_owner_clause(owner_id))
.group_by(AssetInfoTag.tag_name)
.subquery()
)
q = (
select(
Tag.name,
Tag.tag_type,
func.coalesce(counts_sq.c.cnt, 0).label("count"),
)
.select_from(Tag)
.join(counts_sq, counts_sq.c.tag_name == Tag.name, isouter=True)
)
if prefix:
escaped, esc = escape_sql_like_string(prefix.strip().lower())
q = q.where(Tag.name.like(escaped + "%", escape=esc))
if not include_zero:
q = q.where(func.coalesce(counts_sq.c.cnt, 0) > 0)
if order == "name_asc":
q = q.order_by(Tag.name.asc())
else:
q = q.order_by(func.coalesce(counts_sq.c.cnt, 0).desc(), Tag.name.asc())
total_q = select(func.count()).select_from(Tag)
if prefix:
escaped, esc = escape_sql_like_string(prefix.strip().lower())
total_q = total_q.where(Tag.name.like(escaped + "%", escape=esc))
if not include_zero:
total_q = total_q.where(
Tag.name.in_(select(AssetInfoTag.tag_name).group_by(AssetInfoTag.tag_name))
)
rows = (session.execute(q.limit(limit).offset(offset))).all()
total = (session.execute(total_q)).scalar_one()
rows_norm = [(name, ttype, int(count or 0)) for (name, ttype, count) in rows]
return rows_norm, int(total or 0)
def bulk_insert_tags_and_meta(
session: Session,
tag_rows: list[dict],
meta_rows: list[dict],
) -> None:
"""Batch insert into asset_info_tags and asset_info_meta with ON CONFLICT DO NOTHING.
Args:
session: Database session
tag_rows: List of dicts with keys: asset_info_id, tag_name, origin, added_at
meta_rows: List of dicts with keys: asset_info_id, key, ordinal, val_str, val_num, val_bool, val_json
"""
if tag_rows:
ins_tags = sqlite.insert(AssetInfoTag).on_conflict_do_nothing(
index_elements=[AssetInfoTag.asset_info_id, AssetInfoTag.tag_name]
)
for chunk in iter_row_chunks(tag_rows, cols_per_row=4):
session.execute(ins_tags, chunk)
if meta_rows:
ins_meta = sqlite.insert(AssetInfoMeta).on_conflict_do_nothing(
index_elements=[
AssetInfoMeta.asset_info_id,
AssetInfoMeta.key,
AssetInfoMeta.ordinal,
]
)
for chunk in iter_row_chunks(meta_rows, cols_per_row=7):
session.execute(ins_meta, chunk)

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@@ -1,62 +0,0 @@
from typing import Iterable
import sqlalchemy
from sqlalchemy.orm import Session
from sqlalchemy.dialects import sqlite
from app.assets.helpers import normalize_tags, utcnow
from app.assets.database.models import Tag, AssetInfoTag, AssetInfo
def ensure_tags_exist(session: Session, names: Iterable[str], tag_type: str = "user") -> None:
wanted = normalize_tags(list(names))
if not wanted:
return
rows = [{"name": n, "tag_type": tag_type} for n in list(dict.fromkeys(wanted))]
ins = (
sqlite.insert(Tag)
.values(rows)
.on_conflict_do_nothing(index_elements=[Tag.name])
)
return session.execute(ins)
def add_missing_tag_for_asset_id(
session: Session,
*,
asset_id: str,
origin: str = "automatic",
) -> None:
select_rows = (
sqlalchemy.select(
AssetInfo.id.label("asset_info_id"),
sqlalchemy.literal("missing").label("tag_name"),
sqlalchemy.literal(origin).label("origin"),
sqlalchemy.literal(utcnow()).label("added_at"),
)
.where(AssetInfo.asset_id == asset_id)
.where(
sqlalchemy.not_(
sqlalchemy.exists().where((AssetInfoTag.asset_info_id == AssetInfo.id) & (AssetInfoTag.tag_name == "missing"))
)
)
)
session.execute(
sqlite.insert(AssetInfoTag)
.from_select(
["asset_info_id", "tag_name", "origin", "added_at"],
select_rows,
)
.on_conflict_do_nothing(index_elements=[AssetInfoTag.asset_info_id, AssetInfoTag.tag_name])
)
def remove_missing_tag_for_asset_id(
session: Session,
*,
asset_id: str,
) -> None:
session.execute(
sqlalchemy.delete(AssetInfoTag).where(
AssetInfoTag.asset_info_id.in_(sqlalchemy.select(AssetInfo.id).where(AssetInfo.asset_id == asset_id)),
AssetInfoTag.tag_name == "missing",
)
)

View File

@@ -1,75 +0,0 @@
from blake3 import blake3
from typing import IO
import os
import asyncio
DEFAULT_CHUNK = 8 * 1024 *1024 # 8MB
# NOTE: this allows hashing different representations of a file-like object
def blake3_hash(
fp: str | IO[bytes],
chunk_size: int = DEFAULT_CHUNK,
) -> str:
"""
Returns a BLAKE3 hex digest for ``fp``, which may be:
- a filename (str/bytes) or PathLike
- an open binary file object
If ``fp`` is a file object, it must be opened in **binary** mode and support
``read``, ``seek``, and ``tell``. The function will seek to the start before
reading and will attempt to restore the original position afterward.
"""
# duck typing to check if input is a file-like object
if hasattr(fp, "read"):
return _hash_file_obj(fp, chunk_size)
with open(os.fspath(fp), "rb") as f:
return _hash_file_obj(f, chunk_size)
async def blake3_hash_async(
fp: str | IO[bytes],
chunk_size: int = DEFAULT_CHUNK,
) -> str:
"""Async wrapper for ``blake3_hash_sync``.
Uses a worker thread so the event loop remains responsive.
"""
# If it is a path, open inside the worker thread to keep I/O off the loop.
if hasattr(fp, "read"):
return await asyncio.to_thread(blake3_hash, fp, chunk_size)
def _worker() -> str:
with open(os.fspath(fp), "rb") as f:
return _hash_file_obj(f, chunk_size)
return await asyncio.to_thread(_worker)
def _hash_file_obj(file_obj: IO, chunk_size: int = DEFAULT_CHUNK) -> str:
"""
Hash an already-open binary file object by streaming in chunks.
- Seeks to the beginning before reading (if supported).
- Restores the original position afterward (if tell/seek are supported).
"""
if chunk_size <= 0:
chunk_size = DEFAULT_CHUNK
# in case file object is already open and not at the beginning, track so can be restored after hashing
orig_pos = file_obj.tell()
try:
# seek to the beginning before reading
if orig_pos != 0:
file_obj.seek(0)
h = blake3()
while True:
chunk = file_obj.read(chunk_size)
if not chunk:
break
h.update(chunk)
return h.hexdigest()
finally:
# restore original position in file object, if needed
if orig_pos != 0:
file_obj.seek(orig_pos)

View File

@@ -1,52 +1,36 @@
import contextlib
import os
from decimal import Decimal
from aiohttp import web
from datetime import datetime, timezone
from pathlib import Path
from typing import Literal, Any
import folder_paths
from typing import Literal, Sequence
RootType = Literal["models", "input", "output"]
ALLOWED_ROOTS: tuple[RootType, ...] = ("models", "input", "output")
def get_query_dict(request: web.Request) -> dict[str, Any]:
def select_best_live_path(states: Sequence) -> str:
"""
Gets a dictionary of query parameters from the request.
'request.query' is a MultiMapping[str], needs to be converted to a dictionary to be validated by Pydantic.
Return the best on-disk path among cache states:
1) Prefer a path that exists with needs_verify == False (already verified).
2) Otherwise, pick the first path that exists.
3) Otherwise return empty string.
"""
query_dict = {
key: request.query.getall(key) if len(request.query.getall(key)) > 1 else request.query.get(key)
for key in request.query.keys()
}
return query_dict
alive = [
s
for s in states
if getattr(s, "file_path", None) and os.path.isfile(s.file_path)
]
if not alive:
return ""
for s in alive:
if not getattr(s, "needs_verify", False):
return s.file_path
return alive[0].file_path
def list_tree(base_dir: str) -> list[str]:
out: list[str] = []
base_abs = os.path.abspath(base_dir)
if not os.path.isdir(base_abs):
return out
for dirpath, _subdirs, filenames in os.walk(base_abs, topdown=True, followlinks=False):
for name in filenames:
out.append(os.path.abspath(os.path.join(dirpath, name)))
return out
def prefixes_for_root(root: RootType) -> list[str]:
if root == "models":
bases: list[str] = []
for _bucket, paths in get_comfy_models_folders():
bases.extend(paths)
return [os.path.abspath(p) for p in bases]
if root == "input":
return [os.path.abspath(folder_paths.get_input_directory())]
if root == "output":
return [os.path.abspath(folder_paths.get_output_directory())]
return []
ALLOWED_ROOTS: tuple[Literal["models", "input", "output"], ...] = (
"models",
"input",
"output",
)
def escape_like_prefix(s: str, escape: str = "!") -> tuple[str, str]:
def escape_sql_like_string(s: str, escape: str = "!") -> tuple[str, str]:
"""Escapes %, _ and the escape char itself in a LIKE prefix.
Returns (escaped_prefix, escape_char). Caller should append '%' and pass escape=escape_char to .like().
"""
@@ -54,173 +38,11 @@ def escape_like_prefix(s: str, escape: str = "!") -> tuple[str, str]:
s = s.replace("%", escape + "%").replace("_", escape + "_") # escape LIKE wildcards
return s, escape
def fast_asset_file_check(
*,
mtime_db: int | None,
size_db: int | None,
stat_result: os.stat_result,
) -> bool:
if mtime_db is None:
return False
actual_mtime_ns = getattr(stat_result, "st_mtime_ns", int(stat_result.st_mtime * 1_000_000_000))
if int(mtime_db) != int(actual_mtime_ns):
return False
sz = int(size_db or 0)
if sz > 0:
return int(stat_result.st_size) == sz
return True
def utcnow() -> datetime:
def get_utc_now() -> datetime:
"""Naive UTC timestamp (no tzinfo). We always treat DB datetimes as UTC."""
return datetime.now(timezone.utc).replace(tzinfo=None)
def get_comfy_models_folders() -> list[tuple[str, list[str]]]:
"""Build a list of (folder_name, base_paths[]) categories that are configured for model locations.
We trust `folder_paths.folder_names_and_paths` and include a category if
*any* of its base paths lies under the Comfy `models_dir`.
"""
targets: list[tuple[str, list[str]]] = []
models_root = os.path.abspath(folder_paths.models_dir)
for name, values in folder_paths.folder_names_and_paths.items():
paths, _exts = values[0], values[1] # NOTE: this prevents nodepacks that hackily edit folder_... from breaking ComfyUI
if any(os.path.abspath(p).startswith(models_root + os.sep) for p in paths):
targets.append((name, paths))
return targets
def resolve_destination_from_tags(tags: list[str]) -> tuple[str, list[str]]:
"""Validates and maps tags -> (base_dir, subdirs_for_fs)"""
root = tags[0]
if root == "models":
if len(tags) < 2:
raise ValueError("at least two tags required for model asset")
try:
bases = folder_paths.folder_names_and_paths[tags[1]][0]
except KeyError:
raise ValueError(f"unknown model category '{tags[1]}'")
if not bases:
raise ValueError(f"no base path configured for category '{tags[1]}'")
base_dir = os.path.abspath(bases[0])
raw_subdirs = tags[2:]
else:
base_dir = os.path.abspath(
folder_paths.get_input_directory() if root == "input" else folder_paths.get_output_directory()
)
raw_subdirs = tags[1:]
for i in raw_subdirs:
if i in (".", ".."):
raise ValueError("invalid path component in tags")
return base_dir, raw_subdirs if raw_subdirs else []
def ensure_within_base(candidate: str, base: str) -> None:
cand_abs = os.path.abspath(candidate)
base_abs = os.path.abspath(base)
try:
if os.path.commonpath([cand_abs, base_abs]) != base_abs:
raise ValueError("destination escapes base directory")
except Exception:
raise ValueError("invalid destination path")
def compute_relative_filename(file_path: str) -> str | None:
"""
Return the model's path relative to the last well-known folder (the model category),
using forward slashes, eg:
/.../models/checkpoints/flux/123/flux.safetensors -> "flux/123/flux.safetensors"
/.../models/text_encoders/clip_g.safetensors -> "clip_g.safetensors"
For non-model paths, returns None.
NOTE: this is a temporary helper, used only for initializing metadata["filename"] field.
"""
try:
root_category, rel_path = get_relative_to_root_category_path_of_asset(file_path)
except ValueError:
return None
p = Path(rel_path)
parts = [seg for seg in p.parts if seg not in (".", "..", p.anchor)]
if not parts:
return None
if root_category == "models":
# parts[0] is the category ("checkpoints", "vae", etc) drop it
inside = parts[1:] if len(parts) > 1 else [parts[0]]
return "/".join(inside)
return "/".join(parts) # input/output: keep all parts
def get_relative_to_root_category_path_of_asset(file_path: str) -> tuple[Literal["input", "output", "models"], str]:
"""Given an absolute or relative file path, determine which root category the path belongs to:
- 'input' if the file resides under `folder_paths.get_input_directory()`
- 'output' if the file resides under `folder_paths.get_output_directory()`
- 'models' if the file resides under any base path of categories returned by `get_comfy_models_folders()`
Returns:
(root_category, relative_path_inside_that_root)
For 'models', the relative path is prefixed with the category name:
e.g. ('models', 'vae/test/sub/ae.safetensors')
Raises:
ValueError: if the path does not belong to input, output, or configured model bases.
"""
fp_abs = os.path.abspath(file_path)
def _is_within(child: str, parent: str) -> bool:
try:
return os.path.commonpath([child, parent]) == parent
except Exception:
return False
def _rel(child: str, parent: str) -> str:
return os.path.relpath(os.path.join(os.sep, os.path.relpath(child, parent)), os.sep)
# 1) input
input_base = os.path.abspath(folder_paths.get_input_directory())
if _is_within(fp_abs, input_base):
return "input", _rel(fp_abs, input_base)
# 2) output
output_base = os.path.abspath(folder_paths.get_output_directory())
if _is_within(fp_abs, output_base):
return "output", _rel(fp_abs, output_base)
# 3) models (check deepest matching base to avoid ambiguity)
best: tuple[int, str, str] | None = None # (base_len, bucket, rel_inside_bucket)
for bucket, bases in get_comfy_models_folders():
for b in bases:
base_abs = os.path.abspath(b)
if not _is_within(fp_abs, base_abs):
continue
cand = (len(base_abs), bucket, _rel(fp_abs, base_abs))
if best is None or cand[0] > best[0]:
best = cand
if best is not None:
_, bucket, rel_inside = best
combined = os.path.join(bucket, rel_inside)
return "models", os.path.relpath(os.path.join(os.sep, combined), os.sep)
raise ValueError(f"Path is not within input, output, or configured model bases: {file_path}")
def get_name_and_tags_from_asset_path(file_path: str) -> tuple[str, list[str]]:
"""Return a tuple (name, tags) derived from a filesystem path.
Semantics:
- Root category is determined by `get_relative_to_root_category_path_of_asset`.
- The returned `name` is the base filename with extension from the relative path.
- The returned `tags` are:
[root_category] + parent folders of the relative path (in order)
For 'models', this means:
file '/.../ModelsDir/vae/test_tag/ae.safetensors'
-> root_category='models', some_path='vae/test_tag/ae.safetensors'
-> name='ae.safetensors', tags=['models', 'vae', 'test_tag']
Raises:
ValueError: if the path does not belong to input, output, or configured model bases.
"""
root_category, some_path = get_relative_to_root_category_path_of_asset(file_path)
p = Path(some_path)
parent_parts = [part for part in p.parent.parts if part not in (".", "..", p.anchor)]
return p.name, list(dict.fromkeys(normalize_tags([root_category, *parent_parts])))
def normalize_tags(tags: list[str] | None) -> list[str]:
"""
@@ -229,84 +51,3 @@ def normalize_tags(tags: list[str] | None) -> list[str]:
- Removing duplicates.
"""
return [t.strip().lower() for t in (tags or []) if (t or "").strip()]
def collect_models_files() -> list[str]:
out: list[str] = []
for folder_name, bases in get_comfy_models_folders():
rel_files = folder_paths.get_filename_list(folder_name) or []
for rel_path in rel_files:
abs_path = folder_paths.get_full_path(folder_name, rel_path)
if not abs_path:
continue
abs_path = os.path.abspath(abs_path)
allowed = False
for b in bases:
base_abs = os.path.abspath(b)
with contextlib.suppress(Exception):
if os.path.commonpath([abs_path, base_abs]) == base_abs:
allowed = True
break
if allowed:
out.append(abs_path)
return out
def is_scalar(v):
if v is None:
return True
if isinstance(v, bool):
return True
if isinstance(v, (int, float, Decimal, str)):
return True
return False
def project_kv(key: str, value):
"""
Turn a metadata key/value into typed projection rows.
Returns list[dict] with keys:
key, ordinal, and one of val_str / val_num / val_bool / val_json (others None)
"""
rows: list[dict] = []
def _null_row(ordinal: int) -> dict:
return {
"key": key, "ordinal": ordinal,
"val_str": None, "val_num": None, "val_bool": None, "val_json": None
}
if value is None:
rows.append(_null_row(0))
return rows
if is_scalar(value):
if isinstance(value, bool):
rows.append({"key": key, "ordinal": 0, "val_bool": bool(value)})
elif isinstance(value, (int, float, Decimal)):
num = value if isinstance(value, Decimal) else Decimal(str(value))
rows.append({"key": key, "ordinal": 0, "val_num": num})
elif isinstance(value, str):
rows.append({"key": key, "ordinal": 0, "val_str": value})
else:
rows.append({"key": key, "ordinal": 0, "val_json": value})
return rows
if isinstance(value, list):
if all(is_scalar(x) for x in value):
for i, x in enumerate(value):
if x is None:
rows.append(_null_row(i))
elif isinstance(x, bool):
rows.append({"key": key, "ordinal": i, "val_bool": bool(x)})
elif isinstance(x, (int, float, Decimal)):
num = x if isinstance(x, Decimal) else Decimal(str(x))
rows.append({"key": key, "ordinal": i, "val_num": num})
elif isinstance(x, str):
rows.append({"key": key, "ordinal": i, "val_str": x})
else:
rows.append({"key": key, "ordinal": i, "val_json": x})
return rows
for i, x in enumerate(value):
rows.append({"key": key, "ordinal": i, "val_json": x})
return rows
rows.append({"key": key, "ordinal": 0, "val_json": value})
return rows

View File

@@ -1,516 +0,0 @@
import os
import mimetypes
import contextlib
from typing import Sequence
from app.database.db import create_session
from app.assets.api import schemas_out, schemas_in
from app.assets.database.queries import (
asset_exists_by_hash,
asset_info_exists_for_asset_id,
get_asset_by_hash,
get_asset_info_by_id,
fetch_asset_info_asset_and_tags,
fetch_asset_info_and_asset,
create_asset_info_for_existing_asset,
touch_asset_info_by_id,
update_asset_info_full,
delete_asset_info_by_id,
list_cache_states_by_asset_id,
list_asset_infos_page,
list_tags_with_usage,
get_asset_tags,
add_tags_to_asset_info,
remove_tags_from_asset_info,
pick_best_live_path,
ingest_fs_asset,
set_asset_info_preview,
)
from app.assets.helpers import resolve_destination_from_tags, ensure_within_base
from app.assets.database.models import Asset
def _safe_sort_field(requested: str | None) -> str:
if not requested:
return "created_at"
v = requested.lower()
if v in {"name", "created_at", "updated_at", "size", "last_access_time"}:
return v
return "created_at"
def _get_size_mtime_ns(path: str) -> tuple[int, int]:
st = os.stat(path, follow_symlinks=True)
return st.st_size, getattr(st, "st_mtime_ns", int(st.st_mtime * 1_000_000_000))
def _safe_filename(name: str | None, fallback: str) -> str:
n = os.path.basename((name or "").strip() or fallback)
if n:
return n
return fallback
def asset_exists(*, asset_hash: str) -> bool:
"""
Check if an asset with a given hash exists in database.
"""
with create_session() as session:
return asset_exists_by_hash(session, asset_hash=asset_hash)
def list_assets(
*,
include_tags: Sequence[str] | None = None,
exclude_tags: Sequence[str] | None = None,
name_contains: str | None = None,
metadata_filter: dict | None = None,
limit: int = 20,
offset: int = 0,
sort: str = "created_at",
order: str = "desc",
owner_id: str = "",
) -> schemas_out.AssetsList:
sort = _safe_sort_field(sort)
order = "desc" if (order or "desc").lower() not in {"asc", "desc"} else order.lower()
with create_session() as session:
infos, tag_map, total = list_asset_infos_page(
session,
owner_id=owner_id,
include_tags=include_tags,
exclude_tags=exclude_tags,
name_contains=name_contains,
metadata_filter=metadata_filter,
limit=limit,
offset=offset,
sort=sort,
order=order,
)
summaries: list[schemas_out.AssetSummary] = []
for info in infos:
asset = info.asset
tags = tag_map.get(info.id, [])
summaries.append(
schemas_out.AssetSummary(
id=info.id,
name=info.name,
asset_hash=asset.hash if asset else None,
size=int(asset.size_bytes) if asset else None,
mime_type=asset.mime_type if asset else None,
tags=tags,
created_at=info.created_at,
updated_at=info.updated_at,
last_access_time=info.last_access_time,
)
)
return schemas_out.AssetsList(
assets=summaries,
total=total,
has_more=(offset + len(summaries)) < total,
)
def get_asset(
*,
asset_info_id: str,
owner_id: str = "",
) -> schemas_out.AssetDetail:
with create_session() as session:
res = fetch_asset_info_asset_and_tags(session, asset_info_id=asset_info_id, owner_id=owner_id)
if not res:
raise ValueError(f"AssetInfo {asset_info_id} not found")
info, asset, tag_names = res
preview_id = info.preview_id
return schemas_out.AssetDetail(
id=info.id,
name=info.name,
asset_hash=asset.hash if asset else None,
size=int(asset.size_bytes) if asset and asset.size_bytes is not None else None,
mime_type=asset.mime_type if asset else None,
tags=tag_names,
user_metadata=info.user_metadata or {},
preview_id=preview_id,
created_at=info.created_at,
last_access_time=info.last_access_time,
)
def resolve_asset_content_for_download(
*,
asset_info_id: str,
owner_id: str = "",
) -> tuple[str, str, str]:
with create_session() as session:
pair = fetch_asset_info_and_asset(session, asset_info_id=asset_info_id, owner_id=owner_id)
if not pair:
raise ValueError(f"AssetInfo {asset_info_id} not found")
info, asset = pair
states = list_cache_states_by_asset_id(session, asset_id=asset.id)
abs_path = pick_best_live_path(states)
if not abs_path:
raise FileNotFoundError
touch_asset_info_by_id(session, asset_info_id=asset_info_id)
session.commit()
ctype = asset.mime_type or mimetypes.guess_type(info.name or abs_path)[0] or "application/octet-stream"
download_name = info.name or os.path.basename(abs_path)
return abs_path, ctype, download_name
def upload_asset_from_temp_path(
spec: schemas_in.UploadAssetSpec,
*,
temp_path: str,
client_filename: str | None = None,
owner_id: str = "",
expected_asset_hash: str | None = None,
) -> schemas_out.AssetCreated:
"""
Create new asset or update existing asset from a temporary file path.
"""
try:
# NOTE: blake3 is not required right now, so this will fail if blake3 is not installed in local environment
import app.assets.hashing as hashing
digest = hashing.blake3_hash(temp_path)
except Exception as e:
raise RuntimeError(f"failed to hash uploaded file: {e}")
asset_hash = "blake3:" + digest
if expected_asset_hash and asset_hash != expected_asset_hash.strip().lower():
raise ValueError("HASH_MISMATCH")
with create_session() as session:
existing = get_asset_by_hash(session, asset_hash=asset_hash)
if existing is not None:
with contextlib.suppress(Exception):
if temp_path and os.path.exists(temp_path):
os.remove(temp_path)
display_name = _safe_filename(spec.name or (client_filename or ""), fallback=digest)
info = create_asset_info_for_existing_asset(
session,
asset_hash=asset_hash,
name=display_name,
user_metadata=spec.user_metadata or {},
tags=spec.tags or [],
tag_origin="manual",
owner_id=owner_id,
)
tag_names = get_asset_tags(session, asset_info_id=info.id)
session.commit()
return schemas_out.AssetCreated(
id=info.id,
name=info.name,
asset_hash=existing.hash,
size=int(existing.size_bytes) if existing.size_bytes is not None else None,
mime_type=existing.mime_type,
tags=tag_names,
user_metadata=info.user_metadata or {},
preview_id=info.preview_id,
created_at=info.created_at,
last_access_time=info.last_access_time,
created_new=False,
)
base_dir, subdirs = resolve_destination_from_tags(spec.tags)
dest_dir = os.path.join(base_dir, *subdirs) if subdirs else base_dir
os.makedirs(dest_dir, exist_ok=True)
src_for_ext = (client_filename or spec.name or "").strip()
_ext = os.path.splitext(os.path.basename(src_for_ext))[1] if src_for_ext else ""
ext = _ext if 0 < len(_ext) <= 16 else ""
hashed_basename = f"{digest}{ext}"
dest_abs = os.path.abspath(os.path.join(dest_dir, hashed_basename))
ensure_within_base(dest_abs, base_dir)
content_type = (
mimetypes.guess_type(os.path.basename(src_for_ext), strict=False)[0]
or mimetypes.guess_type(hashed_basename, strict=False)[0]
or "application/octet-stream"
)
try:
os.replace(temp_path, dest_abs)
except Exception as e:
raise RuntimeError(f"failed to move uploaded file into place: {e}")
try:
size_bytes, mtime_ns = _get_size_mtime_ns(dest_abs)
except OSError as e:
raise RuntimeError(f"failed to stat destination file: {e}")
with create_session() as session:
result = ingest_fs_asset(
session,
asset_hash=asset_hash,
abs_path=dest_abs,
size_bytes=size_bytes,
mtime_ns=mtime_ns,
mime_type=content_type,
info_name=_safe_filename(spec.name or (client_filename or ""), fallback=digest),
owner_id=owner_id,
preview_id=None,
user_metadata=spec.user_metadata or {},
tags=spec.tags,
tag_origin="manual",
require_existing_tags=False,
)
info_id = result["asset_info_id"]
if not info_id:
raise RuntimeError("failed to create asset metadata")
pair = fetch_asset_info_and_asset(session, asset_info_id=info_id, owner_id=owner_id)
if not pair:
raise RuntimeError("inconsistent DB state after ingest")
info, asset = pair
tag_names = get_asset_tags(session, asset_info_id=info.id)
created_result = schemas_out.AssetCreated(
id=info.id,
name=info.name,
asset_hash=asset.hash,
size=int(asset.size_bytes),
mime_type=asset.mime_type,
tags=tag_names,
user_metadata=info.user_metadata or {},
preview_id=info.preview_id,
created_at=info.created_at,
last_access_time=info.last_access_time,
created_new=result["asset_created"],
)
session.commit()
return created_result
def update_asset(
*,
asset_info_id: str,
name: str | None = None,
tags: list[str] | None = None,
user_metadata: dict | None = None,
owner_id: str = "",
) -> schemas_out.AssetUpdated:
with create_session() as session:
info_row = get_asset_info_by_id(session, asset_info_id=asset_info_id)
if not info_row:
raise ValueError(f"AssetInfo {asset_info_id} not found")
if info_row.owner_id and info_row.owner_id != owner_id:
raise PermissionError("not owner")
info = update_asset_info_full(
session,
asset_info_id=asset_info_id,
name=name,
tags=tags,
user_metadata=user_metadata,
tag_origin="manual",
asset_info_row=info_row,
)
tag_names = get_asset_tags(session, asset_info_id=asset_info_id)
result = schemas_out.AssetUpdated(
id=info.id,
name=info.name,
asset_hash=info.asset.hash if info.asset else None,
tags=tag_names,
user_metadata=info.user_metadata or {},
updated_at=info.updated_at,
)
session.commit()
return result
def set_asset_preview(
*,
asset_info_id: str,
preview_asset_id: str | None = None,
owner_id: str = "",
) -> schemas_out.AssetDetail:
with create_session() as session:
info_row = get_asset_info_by_id(session, asset_info_id=asset_info_id)
if not info_row:
raise ValueError(f"AssetInfo {asset_info_id} not found")
if info_row.owner_id and info_row.owner_id != owner_id:
raise PermissionError("not owner")
set_asset_info_preview(
session,
asset_info_id=asset_info_id,
preview_asset_id=preview_asset_id,
)
res = fetch_asset_info_asset_and_tags(session, asset_info_id=asset_info_id, owner_id=owner_id)
if not res:
raise RuntimeError("State changed during preview update")
info, asset, tags = res
result = schemas_out.AssetDetail(
id=info.id,
name=info.name,
asset_hash=asset.hash if asset else None,
size=int(asset.size_bytes) if asset and asset.size_bytes is not None else None,
mime_type=asset.mime_type if asset else None,
tags=tags,
user_metadata=info.user_metadata or {},
preview_id=info.preview_id,
created_at=info.created_at,
last_access_time=info.last_access_time,
)
session.commit()
return result
def delete_asset_reference(*, asset_info_id: str, owner_id: str, delete_content_if_orphan: bool = True) -> bool:
with create_session() as session:
info_row = get_asset_info_by_id(session, asset_info_id=asset_info_id)
asset_id = info_row.asset_id if info_row else None
deleted = delete_asset_info_by_id(session, asset_info_id=asset_info_id, owner_id=owner_id)
if not deleted:
session.commit()
return False
if not delete_content_if_orphan or not asset_id:
session.commit()
return True
still_exists = asset_info_exists_for_asset_id(session, asset_id=asset_id)
if still_exists:
session.commit()
return True
states = list_cache_states_by_asset_id(session, asset_id=asset_id)
file_paths = [s.file_path for s in (states or []) if getattr(s, "file_path", None)]
asset_row = session.get(Asset, asset_id)
if asset_row is not None:
session.delete(asset_row)
session.commit()
for p in file_paths:
with contextlib.suppress(Exception):
if p and os.path.isfile(p):
os.remove(p)
return True
def create_asset_from_hash(
*,
hash_str: str,
name: str,
tags: list[str] | None = None,
user_metadata: dict | None = None,
owner_id: str = "",
) -> schemas_out.AssetCreated | None:
canonical = hash_str.strip().lower()
with create_session() as session:
asset = get_asset_by_hash(session, asset_hash=canonical)
if not asset:
return None
info = create_asset_info_for_existing_asset(
session,
asset_hash=canonical,
name=_safe_filename(name, fallback=canonical.split(":", 1)[1]),
user_metadata=user_metadata or {},
tags=tags or [],
tag_origin="manual",
owner_id=owner_id,
)
tag_names = get_asset_tags(session, asset_info_id=info.id)
result = schemas_out.AssetCreated(
id=info.id,
name=info.name,
asset_hash=asset.hash,
size=int(asset.size_bytes),
mime_type=asset.mime_type,
tags=tag_names,
user_metadata=info.user_metadata or {},
preview_id=info.preview_id,
created_at=info.created_at,
last_access_time=info.last_access_time,
created_new=False,
)
session.commit()
return result
def add_tags_to_asset(
*,
asset_info_id: str,
tags: list[str],
origin: str = "manual",
owner_id: str = "",
) -> schemas_out.TagsAdd:
with create_session() as session:
info_row = get_asset_info_by_id(session, asset_info_id=asset_info_id)
if not info_row:
raise ValueError(f"AssetInfo {asset_info_id} not found")
if info_row.owner_id and info_row.owner_id != owner_id:
raise PermissionError("not owner")
data = add_tags_to_asset_info(
session,
asset_info_id=asset_info_id,
tags=tags,
origin=origin,
create_if_missing=True,
asset_info_row=info_row,
)
session.commit()
return schemas_out.TagsAdd(**data)
def remove_tags_from_asset(
*,
asset_info_id: str,
tags: list[str],
owner_id: str = "",
) -> schemas_out.TagsRemove:
with create_session() as session:
info_row = get_asset_info_by_id(session, asset_info_id=asset_info_id)
if not info_row:
raise ValueError(f"AssetInfo {asset_info_id} not found")
if info_row.owner_id and info_row.owner_id != owner_id:
raise PermissionError("not owner")
data = remove_tags_from_asset_info(
session,
asset_info_id=asset_info_id,
tags=tags,
)
session.commit()
return schemas_out.TagsRemove(**data)
def list_tags(
prefix: str | None = None,
limit: int = 100,
offset: int = 0,
order: str = "count_desc",
include_zero: bool = True,
owner_id: str = "",
) -> schemas_out.TagsList:
limit = max(1, min(1000, limit))
offset = max(0, offset)
with create_session() as session:
rows, total = list_tags_with_usage(
session,
prefix=prefix,
limit=limit,
offset=offset,
include_zero=include_zero,
order=order,
owner_id=owner_id,
)
tags = [schemas_out.TagUsage(name=name, count=count, type=tag_type) for (name, tag_type, count) in rows]
return schemas_out.TagsList(tags=tags, total=total, has_more=(offset + len(tags)) < total)

View File

@@ -1,263 +1,318 @@
import contextlib
import time
import logging
import os
import sqlalchemy
import time
from typing import Literal, TypedDict
import folder_paths
from app.database.db import create_session, dependencies_available
from app.assets.helpers import (
collect_models_files, compute_relative_filename, fast_asset_file_check, get_name_and_tags_from_asset_path,
list_tree,prefixes_for_root, escape_like_prefix,
RootType
from app.assets.database.queries import (
add_missing_tag_for_asset_id,
bulk_set_needs_verify,
delete_cache_states_by_ids,
delete_orphaned_seed_asset,
ensure_tags_exist,
get_cache_states_for_prefixes,
remove_missing_tag_for_asset_id,
)
from app.assets.database.tags import add_missing_tag_for_asset_id, ensure_tags_exist, remove_missing_tag_for_asset_id
from app.assets.database.bulk_ops import seed_from_paths_batch
from app.assets.database.models import Asset, AssetCacheState, AssetInfo
from app.assets.services.bulk_ingest import (
SeedAssetSpec,
batch_insert_seed_assets,
prune_orphaned_assets,
)
from app.assets.services.file_utils import (
get_mtime_ns,
list_files_recursively,
verify_file_unchanged,
)
from app.assets.services.path_utils import (
compute_relative_filename,
get_comfy_models_folders,
get_name_and_tags_from_asset_path,
)
from app.database.db import create_session, dependencies_available
class _StateInfo(TypedDict):
sid: int
fp: str
exists: bool
fast_ok: bool
needs_verify: bool
class _AssetAccumulator(TypedDict):
hash: str | None
size_db: int
states: list[_StateInfo]
RootType = Literal["models", "input", "output"]
def get_prefixes_for_root(root: RootType) -> list[str]:
if root == "models":
bases: list[str] = []
for _bucket, paths in get_comfy_models_folders():
bases.extend(paths)
return [os.path.abspath(p) for p in bases]
if root == "input":
return [os.path.abspath(folder_paths.get_input_directory())]
if root == "output":
return [os.path.abspath(folder_paths.get_output_directory())]
return []
def collect_models_files() -> list[str]:
out: list[str] = []
for folder_name, bases in get_comfy_models_folders():
rel_files = folder_paths.get_filename_list(folder_name) or []
for rel_path in rel_files:
abs_path = folder_paths.get_full_path(folder_name, rel_path)
if not abs_path:
continue
abs_path = os.path.abspath(abs_path)
allowed = False
for b in bases:
base_abs = os.path.abspath(b)
with contextlib.suppress(Exception):
if os.path.commonpath([abs_path, base_abs]) == base_abs:
allowed = True
break
if allowed:
out.append(abs_path)
return out
def sync_cache_states_with_filesystem(
session,
root: RootType,
collect_existing_paths: bool = False,
update_missing_tags: bool = False,
) -> set[str] | None:
"""Reconcile cache states with filesystem for a root.
- Toggle needs_verify per state using fast mtime/size check
- For hashed assets with at least one fast-ok state in this root: delete stale missing states
- For seed assets with all states missing: delete Asset and its AssetInfos
- Optionally add/remove 'missing' tags based on fast-ok in this root
- Optionally return surviving absolute paths
Args:
session: Database session
root: Root type to scan
collect_existing_paths: If True, return set of surviving file paths
update_missing_tags: If True, update 'missing' tags based on file status
Returns:
Set of surviving absolute paths if collect_existing_paths=True, else None
"""
prefixes = get_prefixes_for_root(root)
if not prefixes:
return set() if collect_existing_paths else None
rows = get_cache_states_for_prefixes(session, prefixes)
by_asset: dict[str, _AssetAccumulator] = {}
for row in rows:
acc = by_asset.get(row.asset_id)
if acc is None:
acc = {"hash": row.asset_hash, "size_db": row.size_bytes, "states": []}
by_asset[row.asset_id] = acc
fast_ok = False
try:
exists = True
fast_ok = verify_file_unchanged(
mtime_db=row.mtime_ns,
size_db=acc["size_db"],
stat_result=os.stat(row.file_path, follow_symlinks=True),
)
except FileNotFoundError:
exists = False
except OSError:
exists = False
acc["states"].append(
{
"sid": row.state_id,
"fp": row.file_path,
"exists": exists,
"fast_ok": fast_ok,
"needs_verify": row.needs_verify,
}
)
to_set_verify: list[int] = []
to_clear_verify: list[int] = []
stale_state_ids: list[int] = []
survivors: set[str] = set()
for aid, acc in by_asset.items():
a_hash = acc["hash"]
states = acc["states"]
any_fast_ok = any(s["fast_ok"] for s in states)
all_missing = all(not s["exists"] for s in states)
for s in states:
if not s["exists"]:
continue
if s["fast_ok"] and s["needs_verify"]:
to_clear_verify.append(s["sid"])
if not s["fast_ok"] and not s["needs_verify"]:
to_set_verify.append(s["sid"])
if a_hash is None:
if states and all_missing:
delete_orphaned_seed_asset(session, aid)
else:
for s in states:
if s["exists"]:
survivors.add(os.path.abspath(s["fp"]))
continue
if any_fast_ok:
for s in states:
if not s["exists"]:
stale_state_ids.append(s["sid"])
if update_missing_tags:
with contextlib.suppress(Exception):
remove_missing_tag_for_asset_id(session, asset_id=aid)
elif update_missing_tags:
with contextlib.suppress(Exception):
add_missing_tag_for_asset_id(session, asset_id=aid, origin="automatic")
for s in states:
if s["exists"]:
survivors.add(os.path.abspath(s["fp"]))
delete_cache_states_by_ids(session, stale_state_ids)
bulk_set_needs_verify(session, to_set_verify, value=True)
bulk_set_needs_verify(session, to_clear_verify, value=False)
return survivors if collect_existing_paths else None
def _sync_root_safely(root: RootType) -> set[str]:
"""Sync a single root's cache states with the filesystem.
Returns survivors (existing paths) or empty set on failure.
"""
try:
with create_session() as sess:
survivors = sync_cache_states_with_filesystem(
sess,
root,
collect_existing_paths=True,
update_missing_tags=True,
)
sess.commit()
return survivors or set()
except Exception as e:
logging.exception("fast DB scan failed for %s: %s", root, e)
return set()
def _prune_orphans_safely(prefixes: list[str]) -> int:
"""Prune orphaned assets outside the given prefixes.
Returns count pruned or 0 on failure.
"""
try:
with create_session() as sess:
count = prune_orphaned_assets(sess, prefixes)
sess.commit()
return count
except Exception as e:
logging.exception("orphan pruning failed: %s", e)
return 0
def _collect_paths_for_roots(roots: tuple[RootType, ...]) -> list[str]:
"""Collect all file paths for the given roots."""
paths: list[str] = []
if "models" in roots:
paths.extend(collect_models_files())
if "input" in roots:
paths.extend(list_files_recursively(folder_paths.get_input_directory()))
if "output" in roots:
paths.extend(list_files_recursively(folder_paths.get_output_directory()))
return paths
def _build_asset_specs(
paths: list[str],
existing_paths: set[str],
) -> tuple[list[SeedAssetSpec], set[str], int]:
"""Build asset specs from paths, returning (specs, tag_pool, skipped_count)."""
specs: list[SeedAssetSpec] = []
tag_pool: set[str] = set()
skipped = 0
for p in paths:
abs_p = os.path.abspath(p)
if abs_p in existing_paths:
skipped += 1
continue
try:
stat_p = os.stat(abs_p, follow_symlinks=False)
except OSError:
continue
if not stat_p.st_size:
continue
name, tags = get_name_and_tags_from_asset_path(abs_p)
specs.append(
{
"abs_path": abs_p,
"size_bytes": stat_p.st_size,
"mtime_ns": get_mtime_ns(stat_p),
"info_name": name,
"tags": tags,
"fname": compute_relative_filename(abs_p),
}
)
tag_pool.update(tags)
return specs, tag_pool, skipped
def _insert_asset_specs(specs: list[SeedAssetSpec], tag_pool: set[str]) -> int:
"""Insert asset specs into database, returning count of created infos."""
if not specs:
return 0
with create_session() as sess:
if tag_pool:
ensure_tags_exist(sess, tag_pool, tag_type="user")
result = batch_insert_seed_assets(sess, specs=specs, owner_id="")
sess.commit()
return result.inserted_infos
def seed_assets(roots: tuple[RootType, ...], enable_logging: bool = False) -> None:
"""
Scan the given roots and seed the assets into the database.
"""
"""Scan the given roots and seed the assets into the database."""
if not dependencies_available():
if enable_logging:
logging.warning("Database dependencies not available, skipping assets scan")
return
t_start = time.perf_counter()
created = 0
skipped_existing = 0
orphans_pruned = 0
paths: list[str] = []
try:
existing_paths: set[str] = set()
for r in roots:
try:
survivors: set[str] = _fast_db_consistency_pass(r, collect_existing_paths=True, update_missing_tags=True)
if survivors:
existing_paths.update(survivors)
except Exception as e:
logging.exception("fast DB scan failed for %s: %s", r, e)
try:
orphans_pruned = _prune_orphaned_assets(roots)
except Exception as e:
logging.exception("orphan pruning failed: %s", e)
existing_paths: set[str] = set()
for r in roots:
existing_paths.update(_sync_root_safely(r))
if "models" in roots:
paths.extend(collect_models_files())
if "input" in roots:
paths.extend(list_tree(folder_paths.get_input_directory()))
if "output" in roots:
paths.extend(list_tree(folder_paths.get_output_directory()))
all_prefixes = [os.path.abspath(p) for r in roots for p in get_prefixes_for_root(r)]
orphans_pruned = _prune_orphans_safely(all_prefixes)
specs: list[dict] = []
tag_pool: set[str] = set()
for p in paths:
abs_p = os.path.abspath(p)
if abs_p in existing_paths:
skipped_existing += 1
continue
try:
stat_p = os.stat(abs_p, follow_symlinks=False)
except OSError:
continue
# skip empty files
if not stat_p.st_size:
continue
name, tags = get_name_and_tags_from_asset_path(abs_p)
specs.append(
{
"abs_path": abs_p,
"size_bytes": stat_p.st_size,
"mtime_ns": getattr(stat_p, "st_mtime_ns", int(stat_p.st_mtime * 1_000_000_000)),
"info_name": name,
"tags": tags,
"fname": compute_relative_filename(abs_p),
}
)
for t in tags:
tag_pool.add(t)
# if no file specs, nothing to do
if not specs:
return
with create_session() as sess:
if tag_pool:
ensure_tags_exist(sess, tag_pool, tag_type="user")
paths = _collect_paths_for_roots(roots)
specs, tag_pool, skipped_existing = _build_asset_specs(paths, existing_paths)
created = _insert_asset_specs(specs, tag_pool)
result = seed_from_paths_batch(sess, specs=specs, owner_id="")
created += result["inserted_infos"]
sess.commit()
finally:
if enable_logging:
logging.info(
"Assets scan(roots=%s) completed in %.3fs (created=%d, skipped_existing=%d, orphans_pruned=%d, total_seen=%d)",
roots,
time.perf_counter() - t_start,
created,
skipped_existing,
orphans_pruned,
len(paths),
)
def _prune_orphaned_assets(roots: tuple[RootType, ...]) -> int:
"""Prune cache states outside configured prefixes, then delete orphaned seed assets."""
all_prefixes = [os.path.abspath(p) for r in roots for p in prefixes_for_root(r)]
if not all_prefixes:
return 0
def make_prefix_condition(prefix: str):
base = prefix if prefix.endswith(os.sep) else prefix + os.sep
escaped, esc = escape_like_prefix(base)
return AssetCacheState.file_path.like(escaped + "%", escape=esc)
matches_valid_prefix = sqlalchemy.or_(*[make_prefix_condition(p) for p in all_prefixes])
orphan_subq = (
sqlalchemy.select(Asset.id)
.outerjoin(AssetCacheState, AssetCacheState.asset_id == Asset.id)
.where(Asset.hash.is_(None), AssetCacheState.id.is_(None))
).scalar_subquery()
with create_session() as sess:
sess.execute(sqlalchemy.delete(AssetCacheState).where(~matches_valid_prefix))
sess.execute(sqlalchemy.delete(AssetInfo).where(AssetInfo.asset_id.in_(orphan_subq)))
result = sess.execute(sqlalchemy.delete(Asset).where(Asset.id.in_(orphan_subq)))
sess.commit()
return result.rowcount
def _fast_db_consistency_pass(
root: RootType,
*,
collect_existing_paths: bool = False,
update_missing_tags: bool = False,
) -> set[str] | None:
"""Fast DB+FS pass for a root:
- Toggle needs_verify per state using fast check
- For hashed assets with at least one fast-ok state in this root: delete stale missing states
- For seed assets with all states missing: delete Asset and its AssetInfos
- Optionally add/remove 'missing' tags based on fast-ok in this root
- Optionally return surviving absolute paths
"""
prefixes = prefixes_for_root(root)
if not prefixes:
return set() if collect_existing_paths else None
conds = []
for p in prefixes:
base = os.path.abspath(p)
if not base.endswith(os.sep):
base += os.sep
escaped, esc = escape_like_prefix(base)
conds.append(AssetCacheState.file_path.like(escaped + "%", escape=esc))
with create_session() as sess:
rows = (
sess.execute(
sqlalchemy.select(
AssetCacheState.id,
AssetCacheState.file_path,
AssetCacheState.mtime_ns,
AssetCacheState.needs_verify,
AssetCacheState.asset_id,
Asset.hash,
Asset.size_bytes,
)
.join(Asset, Asset.id == AssetCacheState.asset_id)
.where(sqlalchemy.or_(*conds))
.order_by(AssetCacheState.asset_id.asc(), AssetCacheState.id.asc())
)
).all()
by_asset: dict[str, dict] = {}
for sid, fp, mtime_db, needs_verify, aid, a_hash, a_size in rows:
acc = by_asset.get(aid)
if acc is None:
acc = {"hash": a_hash, "size_db": int(a_size or 0), "states": []}
by_asset[aid] = acc
fast_ok = False
try:
exists = True
fast_ok = fast_asset_file_check(
mtime_db=mtime_db,
size_db=acc["size_db"],
stat_result=os.stat(fp, follow_symlinks=True),
)
except FileNotFoundError:
exists = False
except OSError:
exists = False
acc["states"].append({
"sid": sid,
"fp": fp,
"exists": exists,
"fast_ok": fast_ok,
"needs_verify": bool(needs_verify),
})
to_set_verify: list[int] = []
to_clear_verify: list[int] = []
stale_state_ids: list[int] = []
survivors: set[str] = set()
for aid, acc in by_asset.items():
a_hash = acc["hash"]
states = acc["states"]
any_fast_ok = any(s["fast_ok"] for s in states)
all_missing = all(not s["exists"] for s in states)
for s in states:
if not s["exists"]:
continue
if s["fast_ok"] and s["needs_verify"]:
to_clear_verify.append(s["sid"])
if not s["fast_ok"] and not s["needs_verify"]:
to_set_verify.append(s["sid"])
if a_hash is None:
if states and all_missing: # remove seed Asset completely, if no valid AssetCache exists
sess.execute(sqlalchemy.delete(AssetInfo).where(AssetInfo.asset_id == aid))
asset = sess.get(Asset, aid)
if asset:
sess.delete(asset)
else:
for s in states:
if s["exists"]:
survivors.add(os.path.abspath(s["fp"]))
continue
if any_fast_ok: # if Asset has at least one valid AssetCache record, remove any invalid AssetCache records
for s in states:
if not s["exists"]:
stale_state_ids.append(s["sid"])
if update_missing_tags:
with contextlib.suppress(Exception):
remove_missing_tag_for_asset_id(sess, asset_id=aid)
elif update_missing_tags:
with contextlib.suppress(Exception):
add_missing_tag_for_asset_id(sess, asset_id=aid, origin="automatic")
for s in states:
if s["exists"]:
survivors.add(os.path.abspath(s["fp"]))
if stale_state_ids:
sess.execute(sqlalchemy.delete(AssetCacheState).where(AssetCacheState.id.in_(stale_state_ids)))
if to_set_verify:
sess.execute(
sqlalchemy.update(AssetCacheState)
.where(AssetCacheState.id.in_(to_set_verify))
.values(needs_verify=True)
)
if to_clear_verify:
sess.execute(
sqlalchemy.update(AssetCacheState)
.where(AssetCacheState.id.in_(to_clear_verify))
.values(needs_verify=False)
)
sess.commit()
return survivors if collect_existing_paths else None
if enable_logging:
logging.info(
"Assets scan(roots=%s) completed in %.3fs (created=%d, skipped_existing=%d, orphans_pruned=%d, total_seen=%d)",
roots,
time.perf_counter() - t_start,
created,
skipped_existing,
orphans_pruned,
len(paths),
)

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@@ -0,0 +1,91 @@
from app.assets.services.asset_management import (
asset_exists,
delete_asset_reference,
get_asset_by_hash,
get_asset_detail,
list_assets_page,
resolve_asset_for_download,
set_asset_preview,
update_asset_metadata,
)
from app.assets.services.bulk_ingest import (
BulkInsertResult,
batch_insert_seed_assets,
prune_orphaned_assets,
)
from app.assets.services.file_utils import (
get_mtime_ns,
get_size_and_mtime_ns,
list_files_recursively,
verify_file_unchanged,
)
from app.assets.services.ingest import (
DependencyMissingError,
HashMismatchError,
create_from_hash,
ingest_file_from_path,
register_existing_asset,
upload_from_temp_path,
)
from app.assets.services.schemas import (
AddTagsResult,
AssetData,
AssetDetailResult,
AssetInfoData,
AssetSummaryData,
DownloadResolutionResult,
IngestResult,
ListAssetsResult,
RegisterAssetResult,
RemoveTagsResult,
SetTagsResult,
TagUsage,
UploadResult,
UserMetadata,
)
from app.assets.services.tagging import (
apply_tags,
list_tags,
remove_tags,
)
__all__ = [
"AddTagsResult",
"AssetData",
"AssetDetailResult",
"AssetInfoData",
"AssetSummaryData",
"BulkInsertResult",
"DependencyMissingError",
"DownloadResolutionResult",
"HashMismatchError",
"IngestResult",
"ListAssetsResult",
"RegisterAssetResult",
"RemoveTagsResult",
"SetTagsResult",
"TagUsage",
"UploadResult",
"UserMetadata",
"apply_tags",
"asset_exists",
"batch_insert_seed_assets",
"create_from_hash",
"delete_asset_reference",
"get_asset_by_hash",
"get_asset_detail",
"get_mtime_ns",
"get_size_and_mtime_ns",
"ingest_file_from_path",
"list_assets_page",
"list_files_recursively",
"list_tags",
"prune_orphaned_assets",
"register_existing_asset",
"remove_tags",
"resolve_asset_for_download",
"set_asset_preview",
"update_asset_metadata",
"upload_from_temp_path",
"verify_file_unchanged",
]

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import contextlib
import mimetypes
import os
from typing import Sequence
from app.assets.database.models import Asset
from app.assets.database.queries import (
asset_exists_by_hash,
asset_info_exists_for_asset_id,
delete_asset_info_by_id,
fetch_asset_info_and_asset,
fetch_asset_info_asset_and_tags,
get_asset_by_hash as queries_get_asset_by_hash,
get_asset_info_by_id,
list_asset_infos_page,
list_cache_states_by_asset_id,
set_asset_info_metadata,
set_asset_info_preview,
set_asset_info_tags,
update_asset_info_access_time,
update_asset_info_name,
update_asset_info_updated_at,
)
from app.assets.helpers import select_best_live_path
from app.assets.services.path_utils import compute_filename_for_asset
from app.assets.services.schemas import (
AssetData,
AssetDetailResult,
AssetSummaryData,
DownloadResolutionResult,
ListAssetsResult,
UserMetadata,
extract_asset_data,
extract_info_data,
)
from app.database.db import create_session
def get_asset_detail(
asset_info_id: str,
owner_id: str = "",
) -> AssetDetailResult | None:
with create_session() as session:
result = fetch_asset_info_asset_and_tags(
session,
asset_info_id=asset_info_id,
owner_id=owner_id,
)
if not result:
return None
info, asset, tags = result
return AssetDetailResult(
info=extract_info_data(info),
asset=extract_asset_data(asset),
tags=tags,
)
def update_asset_metadata(
asset_info_id: str,
name: str | None = None,
tags: Sequence[str] | None = None,
user_metadata: UserMetadata = None,
tag_origin: str = "manual",
owner_id: str = "",
) -> AssetDetailResult:
with create_session() as session:
info = get_asset_info_by_id(session, asset_info_id=asset_info_id)
if not info:
raise ValueError(f"AssetInfo {asset_info_id} not found")
if info.owner_id and info.owner_id != owner_id:
raise PermissionError("not owner")
touched = False
if name is not None and name != info.name:
update_asset_info_name(session, asset_info_id=asset_info_id, name=name)
touched = True
computed_filename = compute_filename_for_asset(session, info.asset_id)
new_meta: dict | None = None
if user_metadata is not None:
new_meta = dict(user_metadata)
elif computed_filename:
current_meta = info.user_metadata or {}
if current_meta.get("filename") != computed_filename:
new_meta = dict(current_meta)
if new_meta is not None:
if computed_filename:
new_meta["filename"] = computed_filename
set_asset_info_metadata(
session, asset_info_id=asset_info_id, user_metadata=new_meta
)
touched = True
if tags is not None:
set_asset_info_tags(
session,
asset_info_id=asset_info_id,
tags=tags,
origin=tag_origin,
)
touched = True
if touched and user_metadata is None:
update_asset_info_updated_at(session, asset_info_id=asset_info_id)
result = fetch_asset_info_asset_and_tags(
session,
asset_info_id=asset_info_id,
owner_id=owner_id,
)
if not result:
raise RuntimeError("State changed during update")
info, asset, tag_list = result
detail = AssetDetailResult(
info=extract_info_data(info),
asset=extract_asset_data(asset),
tags=tag_list,
)
session.commit()
return detail
def delete_asset_reference(
asset_info_id: str,
owner_id: str,
delete_content_if_orphan: bool = True,
) -> bool:
with create_session() as session:
info_row = get_asset_info_by_id(session, asset_info_id=asset_info_id)
asset_id = info_row.asset_id if info_row else None
deleted = delete_asset_info_by_id(
session, asset_info_id=asset_info_id, owner_id=owner_id
)
if not deleted:
session.commit()
return False
if not delete_content_if_orphan or not asset_id:
session.commit()
return True
still_exists = asset_info_exists_for_asset_id(session, asset_id=asset_id)
if still_exists:
session.commit()
return True
# Orphaned asset - delete it and its files
states = list_cache_states_by_asset_id(session, asset_id=asset_id)
file_paths = [
s.file_path for s in (states or []) if getattr(s, "file_path", None)
]
asset_row = session.get(Asset, asset_id)
if asset_row is not None:
session.delete(asset_row)
session.commit()
# Delete files after commit
for p in file_paths:
with contextlib.suppress(Exception):
if p and os.path.isfile(p):
os.remove(p)
return True
def set_asset_preview(
asset_info_id: str,
preview_asset_id: str | None = None,
owner_id: str = "",
) -> AssetDetailResult:
with create_session() as session:
info_row = get_asset_info_by_id(session, asset_info_id=asset_info_id)
if not info_row:
raise ValueError(f"AssetInfo {asset_info_id} not found")
if info_row.owner_id and info_row.owner_id != owner_id:
raise PermissionError("not owner")
set_asset_info_preview(
session,
asset_info_id=asset_info_id,
preview_asset_id=preview_asset_id,
)
result = fetch_asset_info_asset_and_tags(
session, asset_info_id=asset_info_id, owner_id=owner_id
)
if not result:
raise RuntimeError("State changed during preview update")
info, asset, tags = result
detail = AssetDetailResult(
info=extract_info_data(info),
asset=extract_asset_data(asset),
tags=tags,
)
session.commit()
return detail
def asset_exists(asset_hash: str) -> bool:
with create_session() as session:
return asset_exists_by_hash(session, asset_hash=asset_hash)
def get_asset_by_hash(asset_hash: str) -> AssetData | None:
with create_session() as session:
asset = queries_get_asset_by_hash(session, asset_hash=asset_hash)
return extract_asset_data(asset)
def list_assets_page(
owner_id: str = "",
include_tags: Sequence[str] | None = None,
exclude_tags: Sequence[str] | None = None,
name_contains: str | None = None,
metadata_filter: dict | None = None,
limit: int = 20,
offset: int = 0,
sort: str = "created_at",
order: str = "desc",
) -> ListAssetsResult:
with create_session() as session:
infos, tag_map, total = list_asset_infos_page(
session,
owner_id=owner_id,
include_tags=include_tags,
exclude_tags=exclude_tags,
name_contains=name_contains,
metadata_filter=metadata_filter,
limit=limit,
offset=offset,
sort=sort,
order=order,
)
items: list[AssetSummaryData] = []
for info in infos:
items.append(
AssetSummaryData(
info=extract_info_data(info),
asset=extract_asset_data(info.asset),
tags=tag_map.get(info.id, []),
)
)
return ListAssetsResult(items=items, total=total)
def resolve_asset_for_download(
asset_info_id: str,
owner_id: str = "",
) -> DownloadResolutionResult:
with create_session() as session:
pair = fetch_asset_info_and_asset(
session, asset_info_id=asset_info_id, owner_id=owner_id
)
if not pair:
raise ValueError(f"AssetInfo {asset_info_id} not found")
info, asset = pair
states = list_cache_states_by_asset_id(session, asset_id=asset.id)
abs_path = select_best_live_path(states)
if not abs_path:
raise FileNotFoundError
update_asset_info_access_time(session, asset_info_id=asset_info_id)
session.commit()
ctype = (
asset.mime_type
or mimetypes.guess_type(info.name or abs_path)[0]
or "application/octet-stream"
)
download_name = info.name or os.path.basename(abs_path)
return DownloadResolutionResult(
abs_path=abs_path,
content_type=ctype,
download_name=download_name,
)

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import os
import uuid
from dataclasses import dataclass
from typing import TypedDict
from sqlalchemy.orm import Session
class SeedAssetSpec(TypedDict):
"""Spec for seeding an asset from filesystem."""
abs_path: str
size_bytes: int
mtime_ns: int
info_name: str
tags: list[str]
fname: str
from app.assets.database.queries import (
bulk_insert_asset_infos_ignore_conflicts,
bulk_insert_assets,
bulk_insert_cache_states_ignore_conflicts,
bulk_insert_tags_and_meta,
delete_assets_by_ids,
delete_cache_states_outside_prefixes,
get_asset_info_ids_by_ids,
get_cache_states_by_paths_and_asset_ids,
get_orphaned_seed_asset_ids,
)
from app.assets.helpers import get_utc_now
@dataclass
class BulkInsertResult:
"""Result of bulk asset insertion."""
inserted_infos: int
won_states: int
lost_states: int
def batch_insert_seed_assets(
session: Session,
specs: list[SeedAssetSpec],
owner_id: str = "",
) -> BulkInsertResult:
"""Seed assets from filesystem specs in batch.
Each spec is a dict with keys:
- abs_path: str
- size_bytes: int
- mtime_ns: int
- info_name: str
- tags: list[str]
- fname: Optional[str]
This function orchestrates:
1. Insert seed Assets (hash=NULL)
2. Claim cache states with ON CONFLICT DO NOTHING
3. Query to find winners (paths where our asset_id was inserted)
4. Delete Assets for losers (path already claimed by another asset)
5. Insert AssetInfo for winners
6. Insert tags and metadata for successfully inserted AssetInfos
Returns:
BulkInsertResult with inserted_infos, won_states, lost_states
"""
if not specs:
return BulkInsertResult(inserted_infos=0, won_states=0, lost_states=0)
now = get_utc_now()
asset_rows: list[dict] = []
state_rows: list[dict] = []
path_to_asset: dict[str, str] = {}
asset_to_info: dict[str, dict] = {}
path_list: list[str] = []
for sp in specs:
ap = os.path.abspath(sp["abs_path"])
aid = str(uuid.uuid4())
iid = str(uuid.uuid4())
path_list.append(ap)
path_to_asset[ap] = aid
asset_rows.append(
{
"id": aid,
"hash": None,
"size_bytes": sp["size_bytes"],
"mime_type": None,
"created_at": now,
}
)
state_rows.append(
{
"asset_id": aid,
"file_path": ap,
"mtime_ns": sp["mtime_ns"],
}
)
asset_to_info[aid] = {
"id": iid,
"owner_id": owner_id,
"name": sp["info_name"],
"asset_id": aid,
"preview_id": None,
"user_metadata": {"filename": sp["fname"]} if sp["fname"] else None,
"created_at": now,
"updated_at": now,
"last_access_time": now,
"_tags": sp["tags"],
"_filename": sp["fname"],
}
bulk_insert_assets(session, asset_rows)
bulk_insert_cache_states_ignore_conflicts(session, state_rows)
winners_by_path = get_cache_states_by_paths_and_asset_ids(session, path_to_asset)
all_paths_set = set(path_list)
losers_by_path = all_paths_set - winners_by_path
lost_assets = [path_to_asset[p] for p in losers_by_path]
if lost_assets:
delete_assets_by_ids(session, lost_assets)
if not winners_by_path:
return BulkInsertResult(
inserted_infos=0,
won_states=0,
lost_states=len(losers_by_path),
)
winner_info_rows = [asset_to_info[path_to_asset[p]] for p in winners_by_path]
db_info_rows = [
{
"id": row["id"],
"owner_id": row["owner_id"],
"name": row["name"],
"asset_id": row["asset_id"],
"preview_id": row["preview_id"],
"user_metadata": row["user_metadata"],
"created_at": row["created_at"],
"updated_at": row["updated_at"],
"last_access_time": row["last_access_time"],
}
for row in winner_info_rows
]
bulk_insert_asset_infos_ignore_conflicts(session, db_info_rows)
all_info_ids = [row["id"] for row in winner_info_rows]
inserted_info_ids = get_asset_info_ids_by_ids(session, all_info_ids)
tag_rows: list[dict] = []
meta_rows: list[dict] = []
if inserted_info_ids:
for row in winner_info_rows:
iid = row["id"]
if iid not in inserted_info_ids:
continue
for t in row["_tags"]:
tag_rows.append(
{
"asset_info_id": iid,
"tag_name": t,
"origin": "automatic",
"added_at": now,
}
)
if row["_filename"]:
meta_rows.append(
{
"asset_info_id": iid,
"key": "filename",
"ordinal": 0,
"val_str": row["_filename"],
"val_num": None,
"val_bool": None,
"val_json": None,
}
)
bulk_insert_tags_and_meta(session, tag_rows=tag_rows, meta_rows=meta_rows)
return BulkInsertResult(
inserted_infos=len(inserted_info_ids),
won_states=len(winners_by_path),
lost_states=len(losers_by_path),
)
def prune_orphaned_assets(session: Session, valid_prefixes: list[str]) -> int:
"""Prune cache states outside valid prefixes, then delete orphaned seed assets.
Args:
session: Database session
valid_prefixes: List of absolute directory prefixes that are valid
Returns:
Number of orphaned assets deleted
"""
delete_cache_states_outside_prefixes(session, valid_prefixes)
orphan_ids = get_orphaned_seed_asset_ids(session)
return delete_assets_by_ids(session, orphan_ids)

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import os
def get_mtime_ns(stat_result: os.stat_result) -> int:
"""Extract mtime in nanoseconds from a stat result."""
return getattr(
stat_result, "st_mtime_ns", int(stat_result.st_mtime * 1_000_000_000)
)
def get_size_and_mtime_ns(path: str, follow_symlinks: bool = True) -> tuple[int, int]:
"""Get file size in bytes and mtime in nanoseconds."""
st = os.stat(path, follow_symlinks=follow_symlinks)
return st.st_size, get_mtime_ns(st)
def verify_file_unchanged(
mtime_db: int | None,
size_db: int | None,
stat_result: os.stat_result,
) -> bool:
"""Check if a file is unchanged based on mtime and size.
Returns True if the file's mtime and size match the database values.
Returns False if mtime_db is None or values don't match.
"""
if mtime_db is None:
return False
actual_mtime_ns = get_mtime_ns(stat_result)
if int(mtime_db) != int(actual_mtime_ns):
return False
sz = int(size_db or 0)
if sz > 0:
return int(stat_result.st_size) == sz
return True
def list_files_recursively(base_dir: str) -> list[str]:
"""Recursively list all files in a directory."""
out: list[str] = []
base_abs = os.path.abspath(base_dir)
if not os.path.isdir(base_abs):
return out
for dirpath, _subdirs, filenames in os.walk(
base_abs, topdown=True, followlinks=False
):
for name in filenames:
out.append(os.path.abspath(os.path.join(dirpath, name)))
return out

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import asyncio
import os
from typing import IO
from blake3 import blake3
DEFAULT_CHUNK = 8 * 1024 * 1024
def compute_blake3_hash(
fp: str | IO[bytes],
chunk_size: int = DEFAULT_CHUNK,
) -> str:
if hasattr(fp, "read"):
return _hash_file_obj(fp, chunk_size)
with open(os.fspath(fp), "rb") as f:
return _hash_file_obj(f, chunk_size)
async def compute_compute_blake3_hash_async(
fp: str | IO[bytes],
chunk_size: int = DEFAULT_CHUNK,
) -> str:
if hasattr(fp, "read"):
return await asyncio.to_thread(compute_blake3_hash, fp, chunk_size)
def _worker() -> str:
with open(os.fspath(fp), "rb") as f:
return _hash_file_obj(f, chunk_size)
return await asyncio.to_thread(_worker)
def _hash_file_obj(file_obj: IO, chunk_size: int = DEFAULT_CHUNK) -> str:
if chunk_size <= 0:
chunk_size = DEFAULT_CHUNK
orig_pos = file_obj.tell()
try:
if orig_pos != 0:
file_obj.seek(0)
h = blake3()
while True:
chunk = file_obj.read(chunk_size)
if not chunk:
break
h.update(chunk)
return h.hexdigest()
finally:
if orig_pos != 0:
file_obj.seek(orig_pos)

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import contextlib
import logging
import mimetypes
import os
from typing import Sequence
from sqlalchemy import select
from sqlalchemy.orm import Session
import app.assets.services.hashing as hashing
from app.assets.database.models import Asset, AssetInfo, Tag
from app.assets.database.queries import (
add_tags_to_asset_info,
fetch_asset_info_and_asset,
get_asset_by_hash,
get_asset_tags,
get_or_create_asset_info,
remove_missing_tag_for_asset_id,
set_asset_info_metadata,
set_asset_info_tags,
update_asset_info_timestamps,
upsert_asset,
upsert_cache_state,
)
from app.assets.helpers import normalize_tags
from app.assets.services.file_utils import get_size_and_mtime_ns
from app.assets.services.path_utils import (
compute_filename_for_asset,
resolve_destination_from_tags,
validate_path_within_base,
)
from app.assets.services.schemas import (
IngestResult,
RegisterAssetResult,
UploadResult,
UserMetadata,
extract_asset_data,
extract_info_data,
)
from app.database.db import create_session
def ingest_file_from_path(
abs_path: str,
asset_hash: str,
size_bytes: int,
mtime_ns: int,
mime_type: str | None = None,
info_name: str | None = None,
owner_id: str = "",
preview_id: str | None = None,
user_metadata: UserMetadata = None,
tags: Sequence[str] = (),
tag_origin: str = "manual",
require_existing_tags: bool = False,
) -> IngestResult:
locator = os.path.abspath(abs_path)
asset_created = False
asset_updated = False
state_created = False
state_updated = False
asset_info_id: str | None = None
with create_session() as session:
if preview_id:
if not session.get(Asset, preview_id):
preview_id = None
asset, asset_created, asset_updated = upsert_asset(
session,
asset_hash=asset_hash,
size_bytes=size_bytes,
mime_type=mime_type,
)
state_created, state_updated = upsert_cache_state(
session,
asset_id=asset.id,
file_path=locator,
mtime_ns=mtime_ns,
)
if info_name:
info, info_created = get_or_create_asset_info(
session,
asset_id=asset.id,
owner_id=owner_id,
name=info_name,
preview_id=preview_id,
)
if info_created:
asset_info_id = info.id
else:
update_asset_info_timestamps(
session, asset_info=info, preview_id=preview_id
)
asset_info_id = info.id
norm = normalize_tags(list(tags))
if norm and asset_info_id:
if require_existing_tags:
_validate_tags_exist(session, norm)
add_tags_to_asset_info(
session,
asset_info_id=asset_info_id,
tags=norm,
origin=tag_origin,
create_if_missing=not require_existing_tags,
)
if asset_info_id:
_update_metadata_with_filename(
session,
asset_info_id=asset_info_id,
asset_id=asset.id,
info=info,
user_metadata=user_metadata,
)
try:
remove_missing_tag_for_asset_id(session, asset_id=asset.id)
except Exception:
logging.exception("Failed to clear 'missing' tag for asset %s", asset.id)
session.commit()
return IngestResult(
asset_created=asset_created,
asset_updated=asset_updated,
state_created=state_created,
state_updated=state_updated,
asset_info_id=asset_info_id,
)
def register_existing_asset(
asset_hash: str,
name: str,
user_metadata: UserMetadata = None,
tags: list[str] | None = None,
tag_origin: str = "manual",
owner_id: str = "",
) -> RegisterAssetResult:
with create_session() as session:
asset = get_asset_by_hash(session, asset_hash=asset_hash)
if not asset:
raise ValueError(f"No asset with hash {asset_hash}")
info, info_created = get_or_create_asset_info(
session,
asset_id=asset.id,
owner_id=owner_id,
name=name,
preview_id=None,
)
if not info_created:
tag_names = get_asset_tags(session, asset_info_id=info.id)
result = RegisterAssetResult(
info=extract_info_data(info),
asset=extract_asset_data(asset),
tags=tag_names,
created=False,
)
session.commit()
return result
new_meta = dict(user_metadata or {})
computed_filename = compute_filename_for_asset(session, asset.id)
if computed_filename:
new_meta["filename"] = computed_filename
if new_meta:
set_asset_info_metadata(
session,
asset_info_id=info.id,
user_metadata=new_meta,
)
if tags is not None:
set_asset_info_tags(
session,
asset_info_id=info.id,
tags=tags,
origin=tag_origin,
)
tag_names = get_asset_tags(session, asset_info_id=info.id)
session.refresh(info)
result = RegisterAssetResult(
info=extract_info_data(info),
asset=extract_asset_data(asset),
tags=tag_names,
created=True,
)
session.commit()
return result
def _validate_tags_exist(session: Session, tags: list[str]) -> None:
existing_tag_names = set(
name
for (name,) in session.execute(select(Tag.name).where(Tag.name.in_(tags))).all()
)
missing = [t for t in tags if t not in existing_tag_names]
if missing:
raise ValueError(f"Unknown tags: {missing}")
def _update_metadata_with_filename(
session: Session,
asset_info_id: str,
asset_id: str,
info: AssetInfo,
user_metadata: UserMetadata,
) -> None:
computed_filename = compute_filename_for_asset(session, asset_id)
current_meta = info.user_metadata or {}
new_meta = dict(current_meta)
if user_metadata:
for k, v in user_metadata.items():
new_meta[k] = v
if computed_filename:
new_meta["filename"] = computed_filename
if new_meta != current_meta:
set_asset_info_metadata(
session,
asset_info_id=asset_info_id,
user_metadata=new_meta,
)
def _sanitize_filename(name: str | None, fallback: str) -> str:
n = os.path.basename((name or "").strip() or fallback)
return n if n else fallback
class HashMismatchError(Exception):
pass
class DependencyMissingError(Exception):
def __init__(self, message: str):
self.message = message
super().__init__(message)
def upload_from_temp_path(
temp_path: str,
name: str | None = None,
tags: list[str] | None = None,
user_metadata: dict | None = None,
client_filename: str | None = None,
owner_id: str = "",
expected_hash: str | None = None,
) -> UploadResult:
try:
digest = hashing.compute_blake3_hash(temp_path)
except ImportError as e:
raise DependencyMissingError(str(e))
except Exception as e:
raise RuntimeError(f"failed to hash uploaded file: {e}")
asset_hash = "blake3:" + digest
if expected_hash and asset_hash != expected_hash.strip().lower():
raise HashMismatchError("Uploaded file hash does not match provided hash.")
with create_session() as session:
existing = get_asset_by_hash(session, asset_hash=asset_hash)
if existing is not None:
with contextlib.suppress(Exception):
if temp_path and os.path.exists(temp_path):
os.remove(temp_path)
display_name = _sanitize_filename(name or client_filename, fallback=digest)
result = register_existing_asset(
asset_hash=asset_hash,
name=display_name,
user_metadata=user_metadata or {},
tags=tags or [],
tag_origin="manual",
owner_id=owner_id,
)
return UploadResult(
info=result.info,
asset=result.asset,
tags=result.tags,
created_new=False,
)
base_dir, subdirs = resolve_destination_from_tags(tags)
dest_dir = os.path.join(base_dir, *subdirs) if subdirs else base_dir
os.makedirs(dest_dir, exist_ok=True)
src_for_ext = (client_filename or name or "").strip()
_ext = os.path.splitext(os.path.basename(src_for_ext))[1] if src_for_ext else ""
ext = _ext if 0 < len(_ext) <= 16 else ""
hashed_basename = f"{digest}{ext}"
dest_abs = os.path.abspath(os.path.join(dest_dir, hashed_basename))
validate_path_within_base(dest_abs, base_dir)
content_type = (
mimetypes.guess_type(os.path.basename(src_for_ext), strict=False)[0]
or mimetypes.guess_type(hashed_basename, strict=False)[0]
or "application/octet-stream"
)
try:
os.replace(temp_path, dest_abs)
except Exception as e:
raise RuntimeError(f"failed to move uploaded file into place: {e}")
try:
size_bytes, mtime_ns = get_size_and_mtime_ns(dest_abs)
except OSError as e:
raise RuntimeError(f"failed to stat destination file: {e}")
ingest_result = ingest_file_from_path(
asset_hash=asset_hash,
abs_path=dest_abs,
size_bytes=size_bytes,
mtime_ns=mtime_ns,
mime_type=content_type,
info_name=_sanitize_filename(name or client_filename, fallback=digest),
owner_id=owner_id,
preview_id=None,
user_metadata=user_metadata or {},
tags=tags,
tag_origin="manual",
require_existing_tags=False,
)
info_id = ingest_result.asset_info_id
if not info_id:
raise RuntimeError("failed to create asset metadata")
with create_session() as session:
pair = fetch_asset_info_and_asset(
session, asset_info_id=info_id, owner_id=owner_id
)
if not pair:
raise RuntimeError("inconsistent DB state after ingest")
info, asset = pair
tag_names = get_asset_tags(session, asset_info_id=info.id)
return UploadResult(
info=extract_info_data(info),
asset=extract_asset_data(asset),
tags=tag_names,
created_new=ingest_result.asset_created,
)
def create_from_hash(
hash_str: str,
name: str,
tags: list[str] | None = None,
user_metadata: dict | None = None,
owner_id: str = "",
) -> UploadResult | None:
canonical = hash_str.strip().lower()
with create_session() as session:
asset = get_asset_by_hash(session, asset_hash=canonical)
if not asset:
return None
result = register_existing_asset(
asset_hash=canonical,
name=_sanitize_filename(
name, fallback=canonical.split(":", 1)[1] if ":" in canonical else canonical
),
user_metadata=user_metadata or {},
tags=tags or [],
tag_origin="manual",
owner_id=owner_id,
)
return UploadResult(
info=result.info,
asset=result.asset,
tags=result.tags,
created_new=False,
)

View File

@@ -0,0 +1,184 @@
import os
from pathlib import Path
from typing import Literal
import folder_paths
from app.assets.helpers import normalize_tags
def get_comfy_models_folders() -> list[tuple[str, list[str]]]:
"""Build a list of (folder_name, base_paths[]) categories that are configured for model locations.
We trust `folder_paths.folder_names_and_paths` and include a category if
*any* of its base paths lies under the Comfy `models_dir`.
"""
targets: list[tuple[str, list[str]]] = []
models_root = os.path.abspath(folder_paths.models_dir)
for name, values in folder_paths.folder_names_and_paths.items():
paths, _exts = (
values[0],
values[1],
) # NOTE: this prevents nodepacks that hackily edit folder_... from breaking ComfyUI
if any(os.path.abspath(p).startswith(models_root + os.sep) for p in paths):
targets.append((name, paths))
return targets
def resolve_destination_from_tags(tags: list[str]) -> tuple[str, list[str]]:
"""Validates and maps tags -> (base_dir, subdirs_for_fs)"""
root = tags[0]
if root == "models":
if len(tags) < 2:
raise ValueError("at least two tags required for model asset")
try:
bases = folder_paths.folder_names_and_paths[tags[1]][0]
except KeyError:
raise ValueError(f"unknown model category '{tags[1]}'")
if not bases:
raise ValueError(f"no base path configured for category '{tags[1]}'")
base_dir = os.path.abspath(bases[0])
raw_subdirs = tags[2:]
else:
base_dir = os.path.abspath(
folder_paths.get_input_directory()
if root == "input"
else folder_paths.get_output_directory()
)
raw_subdirs = tags[1:]
for i in raw_subdirs:
if i in (".", ".."):
raise ValueError("invalid path component in tags")
return base_dir, raw_subdirs if raw_subdirs else []
def validate_path_within_base(candidate: str, base: str) -> None:
cand_abs = os.path.abspath(candidate)
base_abs = os.path.abspath(base)
try:
if os.path.commonpath([cand_abs, base_abs]) != base_abs:
raise ValueError("destination escapes base directory")
except Exception:
raise ValueError("invalid destination path")
def compute_relative_filename(file_path: str) -> str | None:
"""
Return the model's path relative to the last well-known folder (the model category),
using forward slashes, eg:
/.../models/checkpoints/flux/123/flux.safetensors -> "flux/123/flux.safetensors"
/.../models/text_encoders/clip_g.safetensors -> "clip_g.safetensors"
For non-model paths, returns None.
NOTE: this is a temporary helper, used only for initializing metadata["filename"] field.
"""
try:
root_category, rel_path = get_asset_category_and_relative_path(file_path)
except ValueError:
return None
p = Path(rel_path)
parts = [seg for seg in p.parts if seg not in (".", "..", p.anchor)]
if not parts:
return None
if root_category == "models":
# parts[0] is the category ("checkpoints", "vae", etc) drop it
inside = parts[1:] if len(parts) > 1 else [parts[0]]
return "/".join(inside)
return "/".join(parts) # input/output: keep all parts
def get_asset_category_and_relative_path(
file_path: str,
) -> tuple[Literal["input", "output", "models"], str]:
"""Given an absolute or relative file path, determine which root category the path belongs to:
- 'input' if the file resides under `folder_paths.get_input_directory()`
- 'output' if the file resides under `folder_paths.get_output_directory()`
- 'models' if the file resides under any base path of categories returned by `get_comfy_models_folders()`
Returns:
(root_category, relative_path_inside_that_root)
For 'models', the relative path is prefixed with the category name:
e.g. ('models', 'vae/test/sub/ae.safetensors')
Raises:
ValueError: if the path does not belong to input, output, or configured model bases.
"""
fp_abs = os.path.abspath(file_path)
def _check_is_within(child: str, parent: str) -> bool:
try:
return os.path.commonpath([child, parent]) == parent
except Exception:
return False
def _compute_relative(child: str, parent: str) -> str:
return os.path.relpath(
os.path.join(os.sep, os.path.relpath(child, parent)), os.sep
)
# 1) input
input_base = os.path.abspath(folder_paths.get_input_directory())
if _check_is_within(fp_abs, input_base):
return "input", _compute_relative(fp_abs, input_base)
# 2) output
output_base = os.path.abspath(folder_paths.get_output_directory())
if _check_is_within(fp_abs, output_base):
return "output", _compute_relative(fp_abs, output_base)
# 3) models (check deepest matching base to avoid ambiguity)
best: tuple[int, str, str] | None = None # (base_len, bucket, rel_inside_bucket)
for bucket, bases in get_comfy_models_folders():
for b in bases:
base_abs = os.path.abspath(b)
if not _check_is_within(fp_abs, base_abs):
continue
cand = (len(base_abs), bucket, _compute_relative(fp_abs, base_abs))
if best is None or cand[0] > best[0]:
best = cand
if best is not None:
_, bucket, rel_inside = best
combined = os.path.join(bucket, rel_inside)
return "models", os.path.relpath(os.path.join(os.sep, combined), os.sep)
raise ValueError(
f"Path is not within input, output, or configured model bases: {file_path}"
)
def compute_filename_for_asset(session, asset_id: str) -> str | None:
"""Compute the relative filename for an asset from its best live cache state path."""
from app.assets.database.queries import list_cache_states_by_asset_id
from app.assets.helpers import select_best_live_path
primary_path = select_best_live_path(
list_cache_states_by_asset_id(session, asset_id=asset_id)
)
return compute_relative_filename(primary_path) if primary_path else None
def get_name_and_tags_from_asset_path(file_path: str) -> tuple[str, list[str]]:
"""Return a tuple (name, tags) derived from a filesystem path.
Semantics:
- Root category is determined by `get_asset_category_and_relative_path`.
- The returned `name` is the base filename with extension from the relative path.
- The returned `tags` are:
[root_category] + parent folders of the relative path (in order)
For 'models', this means:
file '/.../ModelsDir/vae/test_tag/ae.safetensors'
-> root_category='models', some_path='vae/test_tag/ae.safetensors'
-> name='ae.safetensors', tags=['models', 'vae', 'test_tag']
Raises:
ValueError: if the path does not belong to input, output, or configured model bases.
"""
root_category, some_path = get_asset_category_and_relative_path(file_path)
p = Path(some_path)
parent_parts = [
part for part in p.parent.parts if part not in (".", "..", p.anchor)
]
return p.name, list(dict.fromkeys(normalize_tags([root_category, *parent_parts])))

View File

@@ -0,0 +1,126 @@
from dataclasses import dataclass
from datetime import datetime
from typing import Any, NamedTuple
from app.assets.database.models import Asset, AssetInfo
UserMetadata = dict[str, Any] | None
@dataclass(frozen=True)
class AssetData:
hash: str
size_bytes: int | None
mime_type: str | None
@dataclass(frozen=True)
class AssetInfoData:
id: str
name: str
user_metadata: UserMetadata
preview_id: str | None
created_at: datetime
updated_at: datetime
last_access_time: datetime | None
@dataclass(frozen=True)
class AssetDetailResult:
info: AssetInfoData
asset: AssetData | None
tags: list[str]
@dataclass(frozen=True)
class RegisterAssetResult:
info: AssetInfoData
asset: AssetData
tags: list[str]
created: bool
@dataclass(frozen=True)
class IngestResult:
asset_created: bool
asset_updated: bool
state_created: bool
state_updated: bool
asset_info_id: str | None
@dataclass(frozen=True)
class AddTagsResult:
added: list[str]
already_present: list[str]
total_tags: list[str]
@dataclass(frozen=True)
class RemoveTagsResult:
removed: list[str]
not_present: list[str]
total_tags: list[str]
@dataclass(frozen=True)
class SetTagsResult:
added: list[str]
removed: list[str]
total: list[str]
class TagUsage(NamedTuple):
name: str
tag_type: str
count: int
@dataclass(frozen=True)
class AssetSummaryData:
info: AssetInfoData
asset: AssetData | None
tags: list[str]
@dataclass(frozen=True)
class ListAssetsResult:
items: list[AssetSummaryData]
total: int
@dataclass(frozen=True)
class DownloadResolutionResult:
abs_path: str
content_type: str
download_name: str
@dataclass(frozen=True)
class UploadResult:
info: AssetInfoData
asset: AssetData
tags: list[str]
created_new: bool
def extract_info_data(info: AssetInfo) -> AssetInfoData:
return AssetInfoData(
id=info.id,
name=info.name,
user_metadata=info.user_metadata,
preview_id=info.preview_id,
created_at=info.created_at,
updated_at=info.updated_at,
last_access_time=info.last_access_time,
)
def extract_asset_data(asset: Asset | None) -> AssetData | None:
if asset is None:
return None
return AssetData(
hash=asset.hash,
size_bytes=asset.size_bytes,
mime_type=asset.mime_type,
)

View File

@@ -0,0 +1,89 @@
from app.assets.database.queries import (
add_tags_to_asset_info,
get_asset_info_by_id,
list_tags_with_usage,
remove_tags_from_asset_info,
)
from app.assets.services.schemas import AddTagsResult, RemoveTagsResult, TagUsage
from app.database.db import create_session
def apply_tags(
asset_info_id: str,
tags: list[str],
origin: str = "manual",
owner_id: str = "",
) -> AddTagsResult:
with create_session() as session:
info_row = get_asset_info_by_id(session, asset_info_id=asset_info_id)
if not info_row:
raise ValueError(f"AssetInfo {asset_info_id} not found")
if info_row.owner_id and info_row.owner_id != owner_id:
raise PermissionError("not owner")
data = add_tags_to_asset_info(
session,
asset_info_id=asset_info_id,
tags=tags,
origin=origin,
create_if_missing=True,
asset_info_row=info_row,
)
session.commit()
return AddTagsResult(
added=data["added"],
already_present=data["already_present"],
total_tags=data["total_tags"],
)
def remove_tags(
asset_info_id: str,
tags: list[str],
owner_id: str = "",
) -> RemoveTagsResult:
with create_session() as session:
info_row = get_asset_info_by_id(session, asset_info_id=asset_info_id)
if not info_row:
raise ValueError(f"AssetInfo {asset_info_id} not found")
if info_row.owner_id and info_row.owner_id != owner_id:
raise PermissionError("not owner")
data = remove_tags_from_asset_info(
session,
asset_info_id=asset_info_id,
tags=tags,
)
session.commit()
return RemoveTagsResult(
removed=data["removed"],
not_present=data["not_present"],
total_tags=data["total_tags"],
)
def list_tags(
prefix: str | None = None,
limit: int = 100,
offset: int = 0,
order: str = "count_desc",
include_zero: bool = True,
owner_id: str = "",
) -> tuple[list[TagUsage], int]:
limit = max(1, min(1000, limit))
offset = max(0, offset)
with create_session() as session:
rows, total = list_tags_with_usage(
session,
prefix=prefix,
limit=limit,
offset=offset,
include_zero=include_zero,
order=order,
owner_id=owner_id,
)
return [TagUsage(name, tag_type, count) for name, tag_type, count in rows], total

View File

@@ -1,107 +0,0 @@
from __future__ import annotations
from aiohttp import web
from typing import TYPE_CHECKING, TypedDict
if TYPE_CHECKING:
from comfy_api.latest._io_public import NodeReplace
from comfy_execution.graph_utils import is_link
import nodes
class NodeStruct(TypedDict):
inputs: dict[str, str | int | float | bool | tuple[str, int]]
class_type: str
_meta: dict[str, str]
def copy_node_struct(node_struct: NodeStruct, empty_inputs: bool = False) -> NodeStruct:
new_node_struct = node_struct.copy()
if empty_inputs:
new_node_struct["inputs"] = {}
else:
new_node_struct["inputs"] = node_struct["inputs"].copy()
new_node_struct["_meta"] = node_struct["_meta"].copy()
return new_node_struct
class NodeReplaceManager:
"""Manages node replacement registrations."""
def __init__(self):
self._replacements: dict[str, list[NodeReplace]] = {}
def register(self, node_replace: NodeReplace):
"""Register a node replacement mapping."""
self._replacements.setdefault(node_replace.old_node_id, []).append(node_replace)
def get_replacement(self, old_node_id: str) -> list[NodeReplace] | None:
"""Get replacements for an old node ID."""
return self._replacements.get(old_node_id)
def has_replacement(self, old_node_id: str) -> bool:
"""Check if a replacement exists for an old node ID."""
return old_node_id in self._replacements
def apply_replacements(self, prompt: dict[str, NodeStruct]):
connections: dict[str, list[tuple[str, str, int]]] = {}
need_replacement: set[str] = set()
for node_number, node_struct in prompt.items():
if "class_type" not in node_struct or "inputs" not in node_struct:
continue
class_type = node_struct["class_type"]
# need replacement if not in NODE_CLASS_MAPPINGS and has replacement
if class_type not in nodes.NODE_CLASS_MAPPINGS.keys() and self.has_replacement(class_type):
need_replacement.add(node_number)
# keep track of connections
for input_id, input_value in node_struct["inputs"].items():
if is_link(input_value):
conn_number = input_value[0]
connections.setdefault(conn_number, []).append((node_number, input_id, input_value[1]))
for node_number in need_replacement:
node_struct = prompt[node_number]
class_type = node_struct["class_type"]
replacements = self.get_replacement(class_type)
if replacements is None:
continue
# just use the first replacement
replacement = replacements[0]
new_node_id = replacement.new_node_id
# if replacement is not a valid node, skip trying to replace it as will only cause confusion
if new_node_id not in nodes.NODE_CLASS_MAPPINGS.keys():
continue
# first, replace node id (class_type)
new_node_struct = copy_node_struct(node_struct, empty_inputs=True)
new_node_struct["class_type"] = new_node_id
# TODO: consider replacing display_name in _meta as well for error reporting purposes; would need to query node schema
# second, replace inputs
if replacement.input_mapping is not None:
for input_map in replacement.input_mapping:
if "set_value" in input_map:
new_node_struct["inputs"][input_map["new_id"]] = input_map["set_value"]
elif "old_id" in input_map:
new_node_struct["inputs"][input_map["new_id"]] = node_struct["inputs"][input_map["old_id"]]
# finalize input replacement
prompt[node_number] = new_node_struct
# third, replace outputs
if replacement.output_mapping is not None:
# re-mapping outputs requires changing the input values of nodes that receive connections from this one
if node_number in connections:
for conns in connections[node_number]:
conn_node_number, conn_input_id, old_output_idx = conns
for output_map in replacement.output_mapping:
if output_map["old_idx"] == old_output_idx:
new_output_idx = output_map["new_idx"]
previous_input = prompt[conn_node_number]["inputs"][conn_input_id]
previous_input[1] = new_output_idx
def as_dict(self):
"""Serialize all replacements to dict."""
return {
k: [v.as_dict() for v in v_list]
for k, v_list in self._replacements.items()
}
def add_routes(self, routes):
@routes.get("/node_replacements")
async def get_node_replacements(request):
return web.json_response(self.as_dict())

View File

@@ -53,7 +53,7 @@ class SubgraphManager:
return entry_id, entry
async def load_entry_data(self, entry: SubgraphEntry):
with open(entry['path'], 'r', encoding='utf-8') as f:
with open(entry['path'], 'r') as f:
entry['data'] = f.read()
return entry

View File

@@ -1,44 +0,0 @@
#version 300 es
precision highp float;
uniform sampler2D u_image0;
uniform float u_float0; // Brightness slider -100..100
uniform float u_float1; // Contrast slider -100..100
in vec2 v_texCoord;
out vec4 fragColor;
const float MID_GRAY = 0.18; // 18% reflectance
// sRGB gamma 2.2 approximation
vec3 srgbToLinear(vec3 c) {
return pow(max(c, 0.0), vec3(2.2));
}
vec3 linearToSrgb(vec3 c) {
return pow(max(c, 0.0), vec3(1.0/2.2));
}
float mapBrightness(float b) {
return clamp(b / 100.0, -1.0, 1.0);
}
float mapContrast(float c) {
return clamp(c / 100.0 + 1.0, 0.0, 2.0);
}
void main() {
vec4 orig = texture(u_image0, v_texCoord);
float brightness = mapBrightness(u_float0);
float contrast = mapContrast(u_float1);
vec3 lin = srgbToLinear(orig.rgb);
lin = (lin - MID_GRAY) * contrast + brightness + MID_GRAY;
// Convert back to sRGB
vec3 result = linearToSrgb(clamp(lin, 0.0, 1.0));
fragColor = vec4(result, orig.a);
}

View File

@@ -1,72 +0,0 @@
#version 300 es
precision highp float;
uniform sampler2D u_image0;
uniform vec2 u_resolution;
uniform int u_int0; // Mode
uniform float u_float0; // Amount (0 to 100)
in vec2 v_texCoord;
out vec4 fragColor;
const int MODE_LINEAR = 0;
const int MODE_RADIAL = 1;
const int MODE_BARREL = 2;
const int MODE_SWIRL = 3;
const int MODE_DIAGONAL = 4;
const float AMOUNT_SCALE = 0.0005;
const float RADIAL_MULT = 4.0;
const float BARREL_MULT = 8.0;
const float INV_SQRT2 = 0.70710678118;
void main() {
vec2 uv = v_texCoord;
vec4 original = texture(u_image0, uv);
float amount = u_float0 * AMOUNT_SCALE;
if (amount < 0.000001) {
fragColor = original;
return;
}
// Aspect-corrected coordinates for circular effects
float aspect = u_resolution.x / u_resolution.y;
vec2 centered = uv - 0.5;
vec2 corrected = vec2(centered.x * aspect, centered.y);
float r = length(corrected);
vec2 dir = r > 0.0001 ? corrected / r : vec2(0.0);
vec2 offset = vec2(0.0);
if (u_int0 == MODE_LINEAR) {
// Horizontal shift (no aspect correction needed)
offset = vec2(amount, 0.0);
}
else if (u_int0 == MODE_RADIAL) {
// Outward from center, stronger at edges
offset = dir * r * amount * RADIAL_MULT;
offset.x /= aspect; // Convert back to UV space
}
else if (u_int0 == MODE_BARREL) {
// Lens distortion simulation (r² falloff)
offset = dir * r * r * amount * BARREL_MULT;
offset.x /= aspect; // Convert back to UV space
}
else if (u_int0 == MODE_SWIRL) {
// Perpendicular to radial (rotational aberration)
vec2 perp = vec2(-dir.y, dir.x);
offset = perp * r * amount * RADIAL_MULT;
offset.x /= aspect; // Convert back to UV space
}
else if (u_int0 == MODE_DIAGONAL) {
// 45° offset (no aspect correction needed)
offset = vec2(amount, amount) * INV_SQRT2;
}
float red = texture(u_image0, uv + offset).r;
float green = original.g;
float blue = texture(u_image0, uv - offset).b;
fragColor = vec4(red, green, blue, original.a);
}

View File

@@ -1,78 +0,0 @@
#version 300 es
precision highp float;
uniform sampler2D u_image0;
uniform float u_float0; // temperature (-100 to 100)
uniform float u_float1; // tint (-100 to 100)
uniform float u_float2; // vibrance (-100 to 100)
uniform float u_float3; // saturation (-100 to 100)
in vec2 v_texCoord;
out vec4 fragColor;
const float INPUT_SCALE = 0.01;
const float TEMP_TINT_PRIMARY = 0.3;
const float TEMP_TINT_SECONDARY = 0.15;
const float VIBRANCE_BOOST = 2.0;
const float SATURATION_BOOST = 2.0;
const float SKIN_PROTECTION = 0.5;
const float EPSILON = 0.001;
const vec3 LUMA_WEIGHTS = vec3(0.299, 0.587, 0.114);
void main() {
vec4 tex = texture(u_image0, v_texCoord);
vec3 color = tex.rgb;
// Scale inputs: -100/100 → -1/1
float temperature = u_float0 * INPUT_SCALE;
float tint = u_float1 * INPUT_SCALE;
float vibrance = u_float2 * INPUT_SCALE;
float saturation = u_float3 * INPUT_SCALE;
// Temperature (warm/cool): positive = warm, negative = cool
color.r += temperature * TEMP_TINT_PRIMARY;
color.b -= temperature * TEMP_TINT_PRIMARY;
// Tint (green/magenta): positive = green, negative = magenta
color.g += tint * TEMP_TINT_PRIMARY;
color.r -= tint * TEMP_TINT_SECONDARY;
color.b -= tint * TEMP_TINT_SECONDARY;
// Single clamp after temperature/tint
color = clamp(color, 0.0, 1.0);
// Vibrance with skin protection
if (vibrance != 0.0) {
float maxC = max(color.r, max(color.g, color.b));
float minC = min(color.r, min(color.g, color.b));
float sat = maxC - minC;
float gray = dot(color, LUMA_WEIGHTS);
if (vibrance < 0.0) {
// Desaturate: -100 → gray
color = mix(vec3(gray), color, 1.0 + vibrance);
} else {
// Boost less saturated colors more
float vibranceAmt = vibrance * (1.0 - sat);
// Branchless skin tone protection
float isWarmTone = step(color.b, color.g) * step(color.g, color.r);
float warmth = (color.r - color.b) / max(maxC, EPSILON);
float skinTone = isWarmTone * warmth * sat * (1.0 - sat);
vibranceAmt *= (1.0 - skinTone * SKIN_PROTECTION);
color = mix(vec3(gray), color, 1.0 + vibranceAmt * VIBRANCE_BOOST);
}
}
// Saturation
if (saturation != 0.0) {
float gray = dot(color, LUMA_WEIGHTS);
float satMix = saturation < 0.0
? 1.0 + saturation // -100 → gray
: 1.0 + saturation * SATURATION_BOOST; // +100 → 3x boost
color = mix(vec3(gray), color, satMix);
}
fragColor = vec4(clamp(color, 0.0, 1.0), tex.a);
}

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#version 300 es
precision highp float;
uniform sampler2D u_image0;
uniform float u_float0; // Blur radius (020, default ~5)
uniform float u_float1; // Edge threshold (0100, default ~30)
uniform int u_int0; // Step size (0/1 = every pixel, 2+ = skip pixels)
in vec2 v_texCoord;
out vec4 fragColor;
const int MAX_RADIUS = 20;
const float EPSILON = 0.0001;
// Perceptual luminance
float getLuminance(vec3 rgb) {
return dot(rgb, vec3(0.299, 0.587, 0.114));
}
vec4 bilateralFilter(vec2 uv, vec2 texelSize, int radius,
float sigmaSpatial, float sigmaColor)
{
vec4 center = texture(u_image0, uv);
vec3 centerRGB = center.rgb;
float invSpatial2 = -0.5 / (sigmaSpatial * sigmaSpatial);
float invColor2 = -0.5 / (sigmaColor * sigmaColor + EPSILON);
vec3 sumRGB = vec3(0.0);
float sumWeight = 0.0;
int step = max(u_int0, 1);
float radius2 = float(radius * radius);
for (int dy = -MAX_RADIUS; dy <= MAX_RADIUS; dy++) {
if (dy < -radius || dy > radius) continue;
if (abs(dy) % step != 0) continue;
for (int dx = -MAX_RADIUS; dx <= MAX_RADIUS; dx++) {
if (dx < -radius || dx > radius) continue;
if (abs(dx) % step != 0) continue;
vec2 offset = vec2(float(dx), float(dy));
float dist2 = dot(offset, offset);
if (dist2 > radius2) continue;
vec3 sampleRGB = texture(u_image0, uv + offset * texelSize).rgb;
// Spatial Gaussian
float spatialWeight = exp(dist2 * invSpatial2);
// Perceptual color distance (weighted RGB)
vec3 diff = sampleRGB - centerRGB;
float colorDist = dot(diff * diff, vec3(0.299, 0.587, 0.114));
float colorWeight = exp(colorDist * invColor2);
float w = spatialWeight * colorWeight;
sumRGB += sampleRGB * w;
sumWeight += w;
}
}
vec3 resultRGB = sumRGB / max(sumWeight, EPSILON);
return vec4(resultRGB, center.a); // preserve center alpha
}
void main() {
vec2 texelSize = 1.0 / vec2(textureSize(u_image0, 0));
float radiusF = clamp(u_float0, 0.0, float(MAX_RADIUS));
int radius = int(radiusF + 0.5);
if (radius == 0) {
fragColor = texture(u_image0, v_texCoord);
return;
}
// Edge threshold → color sigma
// Squared curve for better low-end control
float t = clamp(u_float1, 0.0, 100.0) / 100.0;
t *= t;
float sigmaColor = mix(0.01, 0.5, t);
// Spatial sigma tied to radius
float sigmaSpatial = max(radiusF * 0.75, 0.5);
fragColor = bilateralFilter(
v_texCoord,
texelSize,
radius,
sigmaSpatial,
sigmaColor
);
}

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#version 300 es
precision highp float;
uniform sampler2D u_image0;
uniform vec2 u_resolution;
uniform float u_float0; // grain amount [0.0 1.0] typical: 0.20.8
uniform float u_float1; // grain size [0.3 3.0] lower = finer grain
uniform float u_float2; // color amount [0.0 1.0] 0 = monochrome, 1 = RGB grain
uniform float u_float3; // luminance bias [0.0 1.0] 0 = uniform, 1 = shadows only
uniform int u_int0; // noise mode [0 or 1] 0 = smooth, 1 = grainy
in vec2 v_texCoord;
layout(location = 0) out vec4 fragColor0;
// High-quality integer hash (pcg-like)
uint pcg(uint v) {
uint state = v * 747796405u + 2891336453u;
uint word = ((state >> ((state >> 28u) + 4u)) ^ state) * 277803737u;
return (word >> 22u) ^ word;
}
// 2D -> 1D hash input
uint hash2d(uvec2 p) {
return pcg(p.x + pcg(p.y));
}
// Hash to float [0, 1]
float hashf(uvec2 p) {
return float(hash2d(p)) / float(0xffffffffu);
}
// Hash to float with offset (for RGB channels)
float hashf(uvec2 p, uint offset) {
return float(pcg(hash2d(p) + offset)) / float(0xffffffffu);
}
// Convert uniform [0,1] to roughly Gaussian distribution
// Using simple approximation: average of multiple samples
float toGaussian(uvec2 p) {
float sum = hashf(p, 0u) + hashf(p, 1u) + hashf(p, 2u) + hashf(p, 3u);
return (sum - 2.0) * 0.7; // Centered, scaled
}
float toGaussian(uvec2 p, uint offset) {
float sum = hashf(p, offset) + hashf(p, offset + 1u)
+ hashf(p, offset + 2u) + hashf(p, offset + 3u);
return (sum - 2.0) * 0.7;
}
// Smooth noise with better interpolation
float smoothNoise(vec2 p) {
vec2 i = floor(p);
vec2 f = fract(p);
// Quintic interpolation (less banding than cubic)
f = f * f * f * (f * (f * 6.0 - 15.0) + 10.0);
uvec2 ui = uvec2(i);
float a = toGaussian(ui);
float b = toGaussian(ui + uvec2(1u, 0u));
float c = toGaussian(ui + uvec2(0u, 1u));
float d = toGaussian(ui + uvec2(1u, 1u));
return mix(mix(a, b, f.x), mix(c, d, f.x), f.y);
}
float smoothNoise(vec2 p, uint offset) {
vec2 i = floor(p);
vec2 f = fract(p);
f = f * f * f * (f * (f * 6.0 - 15.0) + 10.0);
uvec2 ui = uvec2(i);
float a = toGaussian(ui, offset);
float b = toGaussian(ui + uvec2(1u, 0u), offset);
float c = toGaussian(ui + uvec2(0u, 1u), offset);
float d = toGaussian(ui + uvec2(1u, 1u), offset);
return mix(mix(a, b, f.x), mix(c, d, f.x), f.y);
}
void main() {
vec4 color = texture(u_image0, v_texCoord);
// Luminance (Rec.709)
float luma = dot(color.rgb, vec3(0.2126, 0.7152, 0.0722));
// Grain UV (resolution-independent)
vec2 grainUV = v_texCoord * u_resolution / max(u_float1, 0.01);
uvec2 grainPixel = uvec2(grainUV);
float g;
vec3 grainRGB;
if (u_int0 == 1) {
// Grainy mode: pure hash noise (no interpolation = no banding)
g = toGaussian(grainPixel);
grainRGB = vec3(
toGaussian(grainPixel, 100u),
toGaussian(grainPixel, 200u),
toGaussian(grainPixel, 300u)
);
} else {
// Smooth mode: interpolated with quintic curve
g = smoothNoise(grainUV);
grainRGB = vec3(
smoothNoise(grainUV, 100u),
smoothNoise(grainUV, 200u),
smoothNoise(grainUV, 300u)
);
}
// Luminance weighting (less grain in highlights)
float lumWeight = mix(1.0, 1.0 - luma, clamp(u_float3, 0.0, 1.0));
// Strength
float strength = u_float0 * 0.15;
// Color vs monochrome grain
vec3 grainColor = mix(vec3(g), grainRGB, clamp(u_float2, 0.0, 1.0));
color.rgb += grainColor * strength * lumWeight;
fragColor0 = vec4(clamp(color.rgb, 0.0, 1.0), color.a);
}

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#version 300 es
precision mediump float;
uniform sampler2D u_image0;
uniform vec2 u_resolution;
uniform int u_int0; // Blend mode
uniform int u_int1; // Color tint
uniform float u_float0; // Intensity
uniform float u_float1; // Radius
uniform float u_float2; // Threshold
in vec2 v_texCoord;
out vec4 fragColor;
const int BLEND_ADD = 0;
const int BLEND_SCREEN = 1;
const int BLEND_SOFT = 2;
const int BLEND_OVERLAY = 3;
const int BLEND_LIGHTEN = 4;
const float GOLDEN_ANGLE = 2.39996323;
const int MAX_SAMPLES = 48;
const vec3 LUMA = vec3(0.299, 0.587, 0.114);
float hash(vec2 p) {
p = fract(p * vec2(123.34, 456.21));
p += dot(p, p + 45.32);
return fract(p.x * p.y);
}
vec3 hexToRgb(int h) {
return vec3(
float((h >> 16) & 255),
float((h >> 8) & 255),
float(h & 255)
) * (1.0 / 255.0);
}
vec3 blend(vec3 base, vec3 glow, int mode) {
if (mode == BLEND_SCREEN) {
return 1.0 - (1.0 - base) * (1.0 - glow);
}
if (mode == BLEND_SOFT) {
return mix(
base - (1.0 - 2.0 * glow) * base * (1.0 - base),
base + (2.0 * glow - 1.0) * (sqrt(base) - base),
step(0.5, glow)
);
}
if (mode == BLEND_OVERLAY) {
return mix(
2.0 * base * glow,
1.0 - 2.0 * (1.0 - base) * (1.0 - glow),
step(0.5, base)
);
}
if (mode == BLEND_LIGHTEN) {
return max(base, glow);
}
return base + glow;
}
void main() {
vec4 original = texture(u_image0, v_texCoord);
float intensity = u_float0 * 0.05;
float radius = u_float1 * u_float1 * 0.012;
if (intensity < 0.001 || radius < 0.1) {
fragColor = original;
return;
}
float threshold = 1.0 - u_float2 * 0.01;
float t0 = threshold - 0.15;
float t1 = threshold + 0.15;
vec2 texelSize = 1.0 / u_resolution;
float radius2 = radius * radius;
float sampleScale = clamp(radius * 0.75, 0.35, 1.0);
int samples = int(float(MAX_SAMPLES) * sampleScale);
float noise = hash(gl_FragCoord.xy);
float angleOffset = noise * GOLDEN_ANGLE;
float radiusJitter = 0.85 + noise * 0.3;
float ca = cos(GOLDEN_ANGLE);
float sa = sin(GOLDEN_ANGLE);
vec2 dir = vec2(cos(angleOffset), sin(angleOffset));
vec3 glow = vec3(0.0);
float totalWeight = 0.0;
// Center tap
float centerMask = smoothstep(t0, t1, dot(original.rgb, LUMA));
glow += original.rgb * centerMask * 2.0;
totalWeight += 2.0;
for (int i = 1; i < MAX_SAMPLES; i++) {
if (i >= samples) break;
float fi = float(i);
float dist = sqrt(fi / float(samples)) * radius * radiusJitter;
vec2 offset = dir * dist * texelSize;
vec3 c = texture(u_image0, v_texCoord + offset).rgb;
float mask = smoothstep(t0, t1, dot(c, LUMA));
float w = 1.0 - (dist * dist) / (radius2 * 1.5);
w = max(w, 0.0);
w *= w;
glow += c * mask * w;
totalWeight += w;
dir = vec2(
dir.x * ca - dir.y * sa,
dir.x * sa + dir.y * ca
);
}
glow *= intensity / max(totalWeight, 0.001);
if (u_int1 > 0) {
glow *= hexToRgb(u_int1);
}
vec3 result = blend(original.rgb, glow, u_int0);
result += (noise - 0.5) * (1.0 / 255.0);
fragColor = vec4(clamp(result, 0.0, 1.0), original.a);
}

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#version 300 es
precision highp float;
uniform sampler2D u_image0;
uniform int u_int0; // Mode: 0=Master, 1=Reds, 2=Yellows, 3=Greens, 4=Cyans, 5=Blues, 6=Magentas, 7=Colorize
uniform int u_int1; // Color Space: 0=HSL, 1=HSB/HSV
uniform float u_float0; // Hue (-180 to 180)
uniform float u_float1; // Saturation (-100 to 100)
uniform float u_float2; // Lightness/Brightness (-100 to 100)
uniform float u_float3; // Overlap (0 to 100) - feathering between adjacent color ranges
in vec2 v_texCoord;
out vec4 fragColor;
// Color range modes
const int MODE_MASTER = 0;
const int MODE_RED = 1;
const int MODE_YELLOW = 2;
const int MODE_GREEN = 3;
const int MODE_CYAN = 4;
const int MODE_BLUE = 5;
const int MODE_MAGENTA = 6;
const int MODE_COLORIZE = 7;
// Color space modes
const int COLORSPACE_HSL = 0;
const int COLORSPACE_HSB = 1;
const float EPSILON = 0.0001;
//=============================================================================
// RGB <-> HSL Conversions
//=============================================================================
vec3 rgb2hsl(vec3 c) {
float maxC = max(max(c.r, c.g), c.b);
float minC = min(min(c.r, c.g), c.b);
float delta = maxC - minC;
float h = 0.0;
float s = 0.0;
float l = (maxC + minC) * 0.5;
if (delta > EPSILON) {
s = l < 0.5
? delta / (maxC + minC)
: delta / (2.0 - maxC - minC);
if (maxC == c.r) {
h = (c.g - c.b) / delta + (c.g < c.b ? 6.0 : 0.0);
} else if (maxC == c.g) {
h = (c.b - c.r) / delta + 2.0;
} else {
h = (c.r - c.g) / delta + 4.0;
}
h /= 6.0;
}
return vec3(h, s, l);
}
float hue2rgb(float p, float q, float t) {
t = fract(t);
if (t < 1.0/6.0) return p + (q - p) * 6.0 * t;
if (t < 0.5) return q;
if (t < 2.0/3.0) return p + (q - p) * (2.0/3.0 - t) * 6.0;
return p;
}
vec3 hsl2rgb(vec3 hsl) {
if (hsl.y < EPSILON) return vec3(hsl.z);
float q = hsl.z < 0.5
? hsl.z * (1.0 + hsl.y)
: hsl.z + hsl.y - hsl.z * hsl.y;
float p = 2.0 * hsl.z - q;
return vec3(
hue2rgb(p, q, hsl.x + 1.0/3.0),
hue2rgb(p, q, hsl.x),
hue2rgb(p, q, hsl.x - 1.0/3.0)
);
}
vec3 rgb2hsb(vec3 c) {
float maxC = max(max(c.r, c.g), c.b);
float minC = min(min(c.r, c.g), c.b);
float delta = maxC - minC;
float h = 0.0;
float s = (maxC > EPSILON) ? delta / maxC : 0.0;
float b = maxC;
if (delta > EPSILON) {
if (maxC == c.r) {
h = (c.g - c.b) / delta + (c.g < c.b ? 6.0 : 0.0);
} else if (maxC == c.g) {
h = (c.b - c.r) / delta + 2.0;
} else {
h = (c.r - c.g) / delta + 4.0;
}
h /= 6.0;
}
return vec3(h, s, b);
}
vec3 hsb2rgb(vec3 hsb) {
vec3 rgb = clamp(abs(mod(hsb.x * 6.0 + vec3(0.0, 4.0, 2.0), 6.0) - 3.0) - 1.0, 0.0, 1.0);
return hsb.z * mix(vec3(1.0), rgb, hsb.y);
}
//=============================================================================
// Color Range Weight Calculation
//=============================================================================
float hueDistance(float a, float b) {
float d = abs(a - b);
return min(d, 1.0 - d);
}
float getHueWeight(float hue, float center, float overlap) {
float baseWidth = 1.0 / 6.0;
float feather = baseWidth * overlap;
float d = hueDistance(hue, center);
float inner = baseWidth * 0.5;
float outer = inner + feather;
return 1.0 - smoothstep(inner, outer, d);
}
float getModeWeight(float hue, int mode, float overlap) {
if (mode == MODE_MASTER || mode == MODE_COLORIZE) return 1.0;
if (mode == MODE_RED) {
return max(
getHueWeight(hue, 0.0, overlap),
getHueWeight(hue, 1.0, overlap)
);
}
float center = float(mode - 1) / 6.0;
return getHueWeight(hue, center, overlap);
}
//=============================================================================
// Adjustment Functions
//=============================================================================
float adjustLightness(float l, float amount) {
return amount > 0.0
? l + (1.0 - l) * amount
: l + l * amount;
}
float adjustBrightness(float b, float amount) {
return clamp(b + amount, 0.0, 1.0);
}
float adjustSaturation(float s, float amount) {
return amount > 0.0
? s + (1.0 - s) * amount
: s + s * amount;
}
vec3 colorize(vec3 rgb, float hue, float sat, float light) {
float lum = dot(rgb, vec3(0.299, 0.587, 0.114));
float l = adjustLightness(lum, light);
vec3 hsl = vec3(fract(hue), clamp(sat, 0.0, 1.0), clamp(l, 0.0, 1.0));
return hsl2rgb(hsl);
}
//=============================================================================
// Main
//=============================================================================
void main() {
vec4 original = texture(u_image0, v_texCoord);
float hueShift = u_float0 / 360.0; // -180..180 -> -0.5..0.5
float satAmount = u_float1 / 100.0; // -100..100 -> -1..1
float lightAmount= u_float2 / 100.0; // -100..100 -> -1..1
float overlap = u_float3 / 100.0; // 0..100 -> 0..1
vec3 result;
if (u_int0 == MODE_COLORIZE) {
result = colorize(original.rgb, hueShift, satAmount, lightAmount);
fragColor = vec4(result, original.a);
return;
}
vec3 hsx = (u_int1 == COLORSPACE_HSL)
? rgb2hsl(original.rgb)
: rgb2hsb(original.rgb);
float weight = getModeWeight(hsx.x, u_int0, overlap);
if (u_int0 != MODE_MASTER && hsx.y < EPSILON) {
weight = 0.0;
}
if (weight > EPSILON) {
float h = fract(hsx.x + hueShift * weight);
float s = clamp(adjustSaturation(hsx.y, satAmount * weight), 0.0, 1.0);
float v = (u_int1 == COLORSPACE_HSL)
? clamp(adjustLightness(hsx.z, lightAmount * weight), 0.0, 1.0)
: clamp(adjustBrightness(hsx.z, lightAmount * weight), 0.0, 1.0);
vec3 adjusted = vec3(h, s, v);
result = (u_int1 == COLORSPACE_HSL)
? hsl2rgb(adjusted)
: hsb2rgb(adjusted);
} else {
result = original.rgb;
}
fragColor = vec4(result, original.a);
}

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#version 300 es
#pragma passes 2
precision highp float;
// Blur type constants
const int BLUR_GAUSSIAN = 0;
const int BLUR_BOX = 1;
const int BLUR_RADIAL = 2;
// Radial blur config
const int RADIAL_SAMPLES = 12;
const float RADIAL_STRENGTH = 0.0003;
uniform sampler2D u_image0;
uniform vec2 u_resolution;
uniform int u_int0; // Blur type (BLUR_GAUSSIAN, BLUR_BOX, BLUR_RADIAL)
uniform float u_float0; // Blur radius/amount
uniform int u_pass; // Pass index (0 = horizontal, 1 = vertical)
in vec2 v_texCoord;
layout(location = 0) out vec4 fragColor0;
float gaussian(float x, float sigma) {
return exp(-(x * x) / (2.0 * sigma * sigma));
}
void main() {
vec2 texelSize = 1.0 / u_resolution;
float radius = max(u_float0, 0.0);
// Radial (angular) blur - single pass, doesn't use separable
if (u_int0 == BLUR_RADIAL) {
// Only execute on first pass
if (u_pass > 0) {
fragColor0 = texture(u_image0, v_texCoord);
return;
}
vec2 center = vec2(0.5);
vec2 dir = v_texCoord - center;
float dist = length(dir);
if (dist < 1e-4) {
fragColor0 = texture(u_image0, v_texCoord);
return;
}
vec4 sum = vec4(0.0);
float totalWeight = 0.0;
float angleStep = radius * RADIAL_STRENGTH;
dir /= dist;
float cosStep = cos(angleStep);
float sinStep = sin(angleStep);
float negAngle = -float(RADIAL_SAMPLES) * angleStep;
vec2 rotDir = vec2(
dir.x * cos(negAngle) - dir.y * sin(negAngle),
dir.x * sin(negAngle) + dir.y * cos(negAngle)
);
for (int i = -RADIAL_SAMPLES; i <= RADIAL_SAMPLES; i++) {
vec2 uv = center + rotDir * dist;
float w = 1.0 - abs(float(i)) / float(RADIAL_SAMPLES);
sum += texture(u_image0, uv) * w;
totalWeight += w;
rotDir = vec2(
rotDir.x * cosStep - rotDir.y * sinStep,
rotDir.x * sinStep + rotDir.y * cosStep
);
}
fragColor0 = sum / max(totalWeight, 0.001);
return;
}
// Separable Gaussian / Box blur
int samples = int(ceil(radius));
if (samples == 0) {
fragColor0 = texture(u_image0, v_texCoord);
return;
}
// Direction: pass 0 = horizontal, pass 1 = vertical
vec2 dir = (u_pass == 0) ? vec2(1.0, 0.0) : vec2(0.0, 1.0);
vec4 color = vec4(0.0);
float totalWeight = 0.0;
float sigma = radius / 2.0;
for (int i = -samples; i <= samples; i++) {
vec2 offset = dir * float(i) * texelSize;
vec4 sample_color = texture(u_image0, v_texCoord + offset);
float weight;
if (u_int0 == BLUR_GAUSSIAN) {
weight = gaussian(float(i), sigma);
} else {
// BLUR_BOX
weight = 1.0;
}
color += sample_color * weight;
totalWeight += weight;
}
fragColor0 = color / totalWeight;
}

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#version 300 es
precision highp float;
uniform sampler2D u_image0;
in vec2 v_texCoord;
layout(location = 0) out vec4 fragColor0;
layout(location = 1) out vec4 fragColor1;
layout(location = 2) out vec4 fragColor2;
layout(location = 3) out vec4 fragColor3;
void main() {
vec4 color = texture(u_image0, v_texCoord);
// Output each channel as grayscale to separate render targets
fragColor0 = vec4(vec3(color.r), 1.0); // Red channel
fragColor1 = vec4(vec3(color.g), 1.0); // Green channel
fragColor2 = vec4(vec3(color.b), 1.0); // Blue channel
fragColor3 = vec4(vec3(color.a), 1.0); // Alpha channel
}

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#version 300 es
precision highp float;
// Levels Adjustment
// u_int0: channel (0=RGB, 1=R, 2=G, 3=B) default: 0
// u_float0: input black (0-255) default: 0
// u_float1: input white (0-255) default: 255
// u_float2: gamma (0.01-9.99) default: 1.0
// u_float3: output black (0-255) default: 0
// u_float4: output white (0-255) default: 255
uniform sampler2D u_image0;
uniform int u_int0;
uniform float u_float0;
uniform float u_float1;
uniform float u_float2;
uniform float u_float3;
uniform float u_float4;
in vec2 v_texCoord;
out vec4 fragColor;
vec3 applyLevels(vec3 color, float inBlack, float inWhite, float gamma, float outBlack, float outWhite) {
float inRange = max(inWhite - inBlack, 0.0001);
vec3 result = clamp((color - inBlack) / inRange, 0.0, 1.0);
result = pow(result, vec3(1.0 / gamma));
result = mix(vec3(outBlack), vec3(outWhite), result);
return result;
}
float applySingleChannel(float value, float inBlack, float inWhite, float gamma, float outBlack, float outWhite) {
float inRange = max(inWhite - inBlack, 0.0001);
float result = clamp((value - inBlack) / inRange, 0.0, 1.0);
result = pow(result, 1.0 / gamma);
result = mix(outBlack, outWhite, result);
return result;
}
void main() {
vec4 texColor = texture(u_image0, v_texCoord);
vec3 color = texColor.rgb;
float inBlack = u_float0 / 255.0;
float inWhite = u_float1 / 255.0;
float gamma = u_float2;
float outBlack = u_float3 / 255.0;
float outWhite = u_float4 / 255.0;
vec3 result;
if (u_int0 == 0) {
result = applyLevels(color, inBlack, inWhite, gamma, outBlack, outWhite);
}
else if (u_int0 == 1) {
result = color;
result.r = applySingleChannel(color.r, inBlack, inWhite, gamma, outBlack, outWhite);
}
else if (u_int0 == 2) {
result = color;
result.g = applySingleChannel(color.g, inBlack, inWhite, gamma, outBlack, outWhite);
}
else if (u_int0 == 3) {
result = color;
result.b = applySingleChannel(color.b, inBlack, inWhite, gamma, outBlack, outWhite);
}
else {
result = color;
}
fragColor = vec4(result, texColor.a);
}

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# GLSL Shader Sources
This folder contains the GLSL fragment shaders extracted from blueprint JSON files for easier editing and version control.
## File Naming Convention
`{Blueprint_Name}_{node_id}.frag`
- **Blueprint_Name**: The JSON filename with spaces/special chars replaced by underscores
- **node_id**: The GLSLShader node ID within the subgraph
## Usage
```bash
# Extract shaders from blueprint JSONs to this folder
python update_blueprints.py extract
# Patch edited shaders back into blueprint JSONs
python update_blueprints.py patch
```
## Workflow
1. Run `extract` to pull current shaders from JSONs
2. Edit `.frag` files
3. Run `patch` to update the blueprint JSONs
4. Test
5. Commit both `.frag` files and updated JSONs

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#version 300 es
precision highp float;
uniform sampler2D u_image0;
uniform vec2 u_resolution;
uniform float u_float0; // strength [0.0 2.0] typical: 0.31.0
in vec2 v_texCoord;
layout(location = 0) out vec4 fragColor0;
void main() {
vec2 texel = 1.0 / u_resolution;
// Sample center and neighbors
vec4 center = texture(u_image0, v_texCoord);
vec4 top = texture(u_image0, v_texCoord + vec2( 0.0, -texel.y));
vec4 bottom = texture(u_image0, v_texCoord + vec2( 0.0, texel.y));
vec4 left = texture(u_image0, v_texCoord + vec2(-texel.x, 0.0));
vec4 right = texture(u_image0, v_texCoord + vec2( texel.x, 0.0));
// Edge enhancement (Laplacian)
vec4 edges = center * 4.0 - top - bottom - left - right;
// Add edges back scaled by strength
vec4 sharpened = center + edges * u_float0;
fragColor0 = vec4(clamp(sharpened.rgb, 0.0, 1.0), center.a);
}

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#version 300 es
precision highp float;
uniform sampler2D u_image0;
uniform vec2 u_resolution;
uniform float u_float0; // amount [0.0 - 3.0] typical: 0.5-1.5
uniform float u_float1; // radius [0.5 - 10.0] blur radius in pixels
uniform float u_float2; // threshold [0.0 - 0.1] min difference to sharpen
in vec2 v_texCoord;
layout(location = 0) out vec4 fragColor0;
float gaussian(float x, float sigma) {
return exp(-(x * x) / (2.0 * sigma * sigma));
}
float getLuminance(vec3 color) {
return dot(color, vec3(0.2126, 0.7152, 0.0722));
}
void main() {
vec2 texel = 1.0 / u_resolution;
float radius = max(u_float1, 0.5);
float amount = u_float0;
float threshold = u_float2;
vec4 original = texture(u_image0, v_texCoord);
// Gaussian blur for the "unsharp" mask
int samples = int(ceil(radius));
float sigma = radius / 2.0;
vec4 blurred = vec4(0.0);
float totalWeight = 0.0;
for (int x = -samples; x <= samples; x++) {
for (int y = -samples; y <= samples; y++) {
vec2 offset = vec2(float(x), float(y)) * texel;
vec4 sample_color = texture(u_image0, v_texCoord + offset);
float dist = length(vec2(float(x), float(y)));
float weight = gaussian(dist, sigma);
blurred += sample_color * weight;
totalWeight += weight;
}
}
blurred /= totalWeight;
// Unsharp mask = original - blurred
vec3 mask = original.rgb - blurred.rgb;
// Luminance-based threshold with smooth falloff
float lumaDelta = abs(getLuminance(original.rgb) - getLuminance(blurred.rgb));
float thresholdScale = smoothstep(0.0, threshold, lumaDelta);
mask *= thresholdScale;
// Sharpen: original + mask * amount
vec3 sharpened = original.rgb + mask * amount;
fragColor0 = vec4(clamp(sharpened, 0.0, 1.0), original.a);
}

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#!/usr/bin/env python3
"""
Shader Blueprint Updater
Syncs GLSL shader files between this folder and blueprint JSON files.
File naming convention:
{Blueprint Name}_{node_id}.frag
Usage:
python update_blueprints.py extract # Extract shaders from JSONs to here
python update_blueprints.py patch # Patch shaders back into JSONs
python update_blueprints.py # Same as patch (default)
"""
import json
import logging
import sys
import re
from pathlib import Path
logging.basicConfig(level=logging.INFO, format='%(message)s')
logger = logging.getLogger(__name__)
GLSL_DIR = Path(__file__).parent
BLUEPRINTS_DIR = GLSL_DIR.parent
def get_blueprint_files():
"""Get all blueprint JSON files."""
return sorted(BLUEPRINTS_DIR.glob("*.json"))
def sanitize_filename(name):
"""Convert blueprint name to safe filename."""
return re.sub(r'[^\w\-]', '_', name)
def extract_shaders():
"""Extract all shaders from blueprint JSONs to this folder."""
extracted = 0
for json_path in get_blueprint_files():
blueprint_name = json_path.stem
try:
with open(json_path, 'r') as f:
data = json.load(f)
except (json.JSONDecodeError, IOError) as e:
logger.warning("Skipping %s: %s", json_path.name, e)
continue
# Find GLSLShader nodes in subgraphs
for subgraph in data.get('definitions', {}).get('subgraphs', []):
for node in subgraph.get('nodes', []):
if node.get('type') == 'GLSLShader':
node_id = node.get('id')
widgets = node.get('widgets_values', [])
# Find shader code (first string that looks like GLSL)
for widget in widgets:
if isinstance(widget, str) and widget.startswith('#version'):
safe_name = sanitize_filename(blueprint_name)
frag_name = f"{safe_name}_{node_id}.frag"
frag_path = GLSL_DIR / frag_name
with open(frag_path, 'w') as f:
f.write(widget)
logger.info(" Extracted: %s", frag_name)
extracted += 1
break
logger.info("\nExtracted %d shader(s)", extracted)
def patch_shaders():
"""Patch shaders from this folder back into blueprint JSONs."""
# Build lookup: blueprint_name -> [(node_id, shader_code), ...]
shader_updates = {}
for frag_path in sorted(GLSL_DIR.glob("*.frag")):
# Parse filename: {blueprint_name}_{node_id}.frag
parts = frag_path.stem.rsplit('_', 1)
if len(parts) != 2:
logger.warning("Skipping %s: invalid filename format", frag_path.name)
continue
blueprint_name, node_id_str = parts
try:
node_id = int(node_id_str)
except ValueError:
logger.warning("Skipping %s: invalid node_id", frag_path.name)
continue
with open(frag_path, 'r') as f:
shader_code = f.read()
if blueprint_name not in shader_updates:
shader_updates[blueprint_name] = []
shader_updates[blueprint_name].append((node_id, shader_code))
# Apply updates to JSON files
patched = 0
for json_path in get_blueprint_files():
blueprint_name = sanitize_filename(json_path.stem)
if blueprint_name not in shader_updates:
continue
try:
with open(json_path, 'r') as f:
data = json.load(f)
except (json.JSONDecodeError, IOError) as e:
logger.error("Error reading %s: %s", json_path.name, e)
continue
modified = False
for node_id, shader_code in shader_updates[blueprint_name]:
# Find the node and update
for subgraph in data.get('definitions', {}).get('subgraphs', []):
for node in subgraph.get('nodes', []):
if node.get('id') == node_id and node.get('type') == 'GLSLShader':
widgets = node.get('widgets_values', [])
if len(widgets) > 0 and widgets[0] != shader_code:
widgets[0] = shader_code
modified = True
logger.info(" Patched: %s (node %d)", json_path.name, node_id)
patched += 1
if modified:
with open(json_path, 'w') as f:
json.dump(data, f)
if patched == 0:
logger.info("No changes to apply.")
else:
logger.info("\nPatched %d shader(s)", patched)
def main():
if len(sys.argv) < 2:
command = "patch"
else:
command = sys.argv[1].lower()
if command == "extract":
logger.info("Extracting shaders from blueprints...")
extract_shaders()
elif command in ("patch", "update", "apply"):
logger.info("Patching shaders into blueprints...")
patch_shaders()
else:
logger.info(__doc__)
sys.exit(1)
if __name__ == "__main__":
main()

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{"revision": 0, "last_node_id": 29, "last_link_id": 0, "nodes": [{"id": 29, "type": "4c9d6ea4-b912-40e5-8766-6793a9758c53", "pos": [1970, -230], "size": [180, 86], "flags": {}, "order": 5, "mode": 0, "inputs": [{"label": "image", "localized_name": "images.image0", "name": "images.image0", "type": "IMAGE", "link": null}], "outputs": [{"label": "R", "localized_name": "IMAGE0", "name": "IMAGE0", "type": "IMAGE", "links": []}, {"label": "G", "localized_name": "IMAGE1", "name": "IMAGE1", "type": "IMAGE", "links": []}, {"label": "B", "localized_name": "IMAGE2", "name": "IMAGE2", "type": "IMAGE", "links": []}, {"label": "A", "localized_name": "IMAGE3", "name": "IMAGE3", "type": "IMAGE", "links": []}], "title": "Image Channels", "properties": {"proxyWidgets": []}, "widgets_values": []}], "links": [], "version": 0.4, "definitions": {"subgraphs": [{"id": "4c9d6ea4-b912-40e5-8766-6793a9758c53", "version": 1, "state": {"lastGroupId": 0, "lastNodeId": 28, "lastLinkId": 39, "lastRerouteId": 0}, "revision": 0, "config": {}, "name": "Image Channels", "inputNode": {"id": -10, "bounding": [1820, -185, 120, 60]}, "outputNode": {"id": -20, "bounding": [2460, -215, 120, 120]}, "inputs": [{"id": "3522932b-2d86-4a1f-a02a-cb29f3a9d7fe", "name": "images.image0", "type": "IMAGE", "linkIds": [39], "localized_name": "images.image0", "label": "image", "pos": [1920, -165]}], "outputs": [{"id": "605cb9c3-b065-4d9b-81d2-3ec331889b2b", "name": "IMAGE0", "type": "IMAGE", "linkIds": [26], "localized_name": "IMAGE0", "label": "R", "pos": [2480, -195]}, {"id": "fb44a77e-0522-43e9-9527-82e7465b3596", "name": "IMAGE1", "type": "IMAGE", "linkIds": [27], "localized_name": "IMAGE1", "label": "G", "pos": [2480, -175]}, {"id": "81460ee6-0131-402a-874f-6bf3001fc4ff", "name": "IMAGE2", "type": "IMAGE", "linkIds": [28], "localized_name": "IMAGE2", "label": "B", "pos": [2480, -155]}, {"id": "ae690246-80d4-4951-b1d9-9306d8a77417", "name": "IMAGE3", "type": "IMAGE", "linkIds": [29], "localized_name": "IMAGE3", "label": "A", "pos": [2480, -135]}], "widgets": [], "nodes": [{"id": 23, "type": "GLSLShader", "pos": [2000, -330], "size": [400, 172], "flags": {}, "order": 0, "mode": 0, "inputs": [{"label": "image", "localized_name": "images.image0", "name": "images.image0", "type": "IMAGE", "link": 39}, {"localized_name": "fragment_shader", "name": "fragment_shader", "type": "STRING", "widget": {"name": "fragment_shader"}, "link": null}, {"localized_name": "size_mode", "name": "size_mode", "type": "COMFY_DYNAMICCOMBO_V3", "widget": {"name": "size_mode"}, "link": null}, {"label": "image1", "localized_name": "images.image1", "name": "images.image1", "shape": 7, "type": "IMAGE", "link": null}], "outputs": [{"label": "R", "localized_name": "IMAGE0", "name": "IMAGE0", "type": "IMAGE", "links": [26]}, {"label": "G", "localized_name": "IMAGE1", "name": "IMAGE1", "type": "IMAGE", "links": [27]}, {"label": "B", "localized_name": "IMAGE2", "name": "IMAGE2", "type": "IMAGE", "links": [28]}, {"label": "A", "localized_name": "IMAGE3", "name": "IMAGE3", "type": "IMAGE", "links": [29]}], "properties": {"Node name for S&R": "GLSLShader"}, "widgets_values": ["#version 300 es\nprecision highp float;\n\nuniform sampler2D u_image0;\n\nin vec2 v_texCoord;\nlayout(location = 0) out vec4 fragColor0;\nlayout(location = 1) out vec4 fragColor1;\nlayout(location = 2) out vec4 fragColor2;\nlayout(location = 3) out vec4 fragColor3;\n\nvoid main() {\n vec4 color = texture(u_image0, v_texCoord);\n // Output each channel as grayscale to separate render targets\n fragColor0 = vec4(vec3(color.r), 1.0); // Red channel\n fragColor1 = vec4(vec3(color.g), 1.0); // Green channel\n fragColor2 = vec4(vec3(color.b), 1.0); // Blue channel\n fragColor3 = vec4(vec3(color.a), 1.0); // Alpha channel\n}\n", "from_input"]}], "groups": [], "links": [{"id": 39, "origin_id": -10, "origin_slot": 0, "target_id": 23, "target_slot": 0, "type": "IMAGE"}, {"id": 26, "origin_id": 23, "origin_slot": 0, "target_id": -20, "target_slot": 0, "type": "IMAGE"}, {"id": 27, "origin_id": 23, "origin_slot": 1, "target_id": -20, "target_slot": 1, "type": "IMAGE"}, {"id": 28, "origin_id": 23, "origin_slot": 2, "target_id": -20, "target_slot": 2, "type": "IMAGE"}, {"id": 29, "origin_id": 23, "origin_slot": 3, "target_id": -20, "target_slot": 3, "type": "IMAGE"}], "extra": {"workflowRendererVersion": "LG"}, "category": "Image Tools/Color adjust"}]}}

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{"revision": 0, "last_node_id": 15, "last_link_id": 0, "nodes": [{"id": 15, "type": "24d8bbfd-39d4-4774-bff0-3de40cc7a471", "pos": [-1490, 2040], "size": [400, 260], "flags": {}, "order": 0, "mode": 0, "inputs": [{"name": "prompt", "type": "STRING", "widget": {"name": "prompt"}, "link": null}, {"label": "reference images", "name": "images", "type": "IMAGE", "link": null}], "outputs": [{"name": "STRING", "type": "STRING", "links": null}], "title": "Prompt Enhance", "properties": {"proxyWidgets": [["-1", "prompt"]], "cnr_id": "comfy-core", "ver": "0.14.1"}, "widgets_values": [""]}], "links": [], "version": 0.4, "definitions": {"subgraphs": [{"id": "24d8bbfd-39d4-4774-bff0-3de40cc7a471", "version": 1, "state": {"lastGroupId": 0, "lastNodeId": 15, "lastLinkId": 14, "lastRerouteId": 0}, "revision": 0, "config": {}, "name": "Prompt Enhance", "inputNode": {"id": -10, "bounding": [-2170, 2110, 138.876953125, 80]}, "outputNode": {"id": -20, "bounding": [-640, 2110, 120, 60]}, "inputs": [{"id": "aeab7216-00e0-4528-a09b-bba50845c5a6", "name": "prompt", "type": "STRING", "linkIds": [11], "pos": [-2051.123046875, 2130]}, {"id": "7b73fd36-aa31-4771-9066-f6c83879994b", "name": "images", "type": "IMAGE", "linkIds": [14], "label": "reference images", "pos": [-2051.123046875, 2150]}], "outputs": [{"id": "c7b0d930-68a1-48d1-b496-0519e5837064", "name": "STRING", "type": "STRING", "linkIds": [13], "pos": [-620, 2130]}], "widgets": [], "nodes": [{"id": 11, "type": "GeminiNode", "pos": [-1560, 1990], "size": [470, 470], "flags": {}, "order": 0, "mode": 0, "inputs": [{"localized_name": "images", "name": "images", "shape": 7, "type": "IMAGE", "link": 14}, {"localized_name": "audio", "name": "audio", "shape": 7, "type": "AUDIO", "link": null}, {"localized_name": "video", "name": "video", "shape": 7, "type": "VIDEO", "link": null}, {"localized_name": "files", "name": "files", "shape": 7, "type": "GEMINI_INPUT_FILES", "link": null}, {"localized_name": "prompt", "name": "prompt", "type": "STRING", "widget": {"name": "prompt"}, "link": 11}, {"localized_name": "model", "name": "model", "type": "COMBO", "widget": {"name": "model"}, "link": null}, {"localized_name": "seed", "name": "seed", "type": "INT", "widget": {"name": "seed"}, "link": null}, {"localized_name": "system_prompt", "name": "system_prompt", "shape": 7, "type": "STRING", "widget": {"name": "system_prompt"}, "link": null}], "outputs": [{"localized_name": "STRING", "name": "STRING", "type": "STRING", "links": [13]}], "properties": {"cnr_id": "comfy-core", "ver": "0.14.1", "Node name for S&R": "GeminiNode"}, "widgets_values": ["", "gemini-3-pro-preview", 42, "randomize", "You are an expert in prompt writing.\nBased on the input, rewrite the user's input into a detailed prompt.\nincluding camera settings, lighting, composition, and style.\nReturn the prompt only"], "color": "#432", "bgcolor": "#653"}], "groups": [], "links": [{"id": 11, "origin_id": -10, "origin_slot": 0, "target_id": 11, "target_slot": 4, "type": "STRING"}, {"id": 13, "origin_id": 11, "origin_slot": 0, "target_id": -20, "target_slot": 0, "type": "STRING"}, {"id": 14, "origin_id": -10, "origin_slot": 1, "target_id": 11, "target_slot": 0, "type": "IMAGE"}], "extra": {"workflowRendererVersion": "LG"}, "category": "Text generation/Prompt enhance"}]}, "extra": {}}

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{"revision": 0, "last_node_id": 25, "last_link_id": 0, "nodes": [{"id": 25, "type": "621ba4e2-22a8-482d-a369-023753198b7b", "pos": [4610, -790], "size": [230, 58], "flags": {}, "order": 4, "mode": 0, "inputs": [{"label": "image", "localized_name": "images.image0", "name": "images.image0", "type": "IMAGE", "link": null}], "outputs": [{"label": "IMAGE", "localized_name": "IMAGE0", "name": "IMAGE0", "type": "IMAGE", "links": []}], "title": "Sharpen", "properties": {"proxyWidgets": [["24", "value"]]}, "widgets_values": []}], "links": [], "version": 0.4, "definitions": {"subgraphs": [{"id": "621ba4e2-22a8-482d-a369-023753198b7b", "version": 1, "state": {"lastGroupId": 0, "lastNodeId": 24, "lastLinkId": 36, "lastRerouteId": 0}, "revision": 0, "config": {}, "name": "Sharpen", "inputNode": {"id": -10, "bounding": [4090, -825, 120, 60]}, "outputNode": {"id": -20, "bounding": [5150, -825, 120, 60]}, "inputs": [{"id": "37011fb7-14b7-4e0e-b1a0-6a02e8da1fd7", "name": "images.image0", "type": "IMAGE", "linkIds": [34], "localized_name": "images.image0", "label": "image", "pos": [4190, -805]}], "outputs": [{"id": "e9182b3f-635c-4cd4-a152-4b4be17ae4b9", "name": "IMAGE0", "type": "IMAGE", "linkIds": [35], "localized_name": "IMAGE0", "label": "IMAGE", "pos": [5170, -805]}], "widgets": [], "nodes": [{"id": 24, "type": "PrimitiveFloat", "pos": [4280, -1240], "size": [270, 58], "flags": {}, "order": 0, "mode": 0, "inputs": [{"label": "strength", "localized_name": "value", "name": "value", "type": "FLOAT", "widget": {"name": "value"}, "link": null}], "outputs": [{"localized_name": "FLOAT", "name": "FLOAT", "type": "FLOAT", "links": [36]}], "properties": {"Node name for S&R": "PrimitiveFloat", "min": 0, "max": 3, "precision": 2, "step": 0.05}, "widgets_values": [0.5]}, {"id": 23, "type": "GLSLShader", "pos": [4570, -1240], "size": [370, 192], "flags": {}, "order": 1, "mode": 0, "inputs": [{"label": "image0", "localized_name": "images.image0", "name": "images.image0", "type": "IMAGE", "link": 34}, {"label": "image1", "localized_name": "images.image1", "name": "images.image1", "shape": 7, "type": "IMAGE", "link": null}, {"label": "u_float0", "localized_name": "floats.u_float0", "name": "floats.u_float0", "shape": 7, "type": "FLOAT", "link": 36}, {"label": "u_float1", "localized_name": "floats.u_float1", "name": "floats.u_float1", "shape": 7, "type": "FLOAT", "link": null}, {"label": "u_int0", "localized_name": "ints.u_int0", "name": "ints.u_int0", "shape": 7, "type": "INT", "link": null}, {"localized_name": "fragment_shader", "name": "fragment_shader", "type": "STRING", "widget": {"name": "fragment_shader"}, "link": null}, {"localized_name": "size_mode", "name": "size_mode", "type": "COMFY_DYNAMICCOMBO_V3", "widget": {"name": "size_mode"}, "link": null}], "outputs": [{"localized_name": "IMAGE0", "name": "IMAGE0", "type": "IMAGE", "links": [35]}, {"localized_name": "IMAGE1", "name": "IMAGE1", "type": "IMAGE", "links": null}, {"localized_name": "IMAGE2", "name": "IMAGE2", "type": "IMAGE", "links": null}, {"localized_name": "IMAGE3", "name": "IMAGE3", "type": "IMAGE", "links": null}], "properties": {"Node name for S&R": "GLSLShader"}, "widgets_values": ["#version 300 es\nprecision highp float;\n\nuniform sampler2D u_image0;\nuniform vec2 u_resolution;\nuniform float u_float0; // strength [0.0 2.0] typical: 0.31.0\n\nin vec2 v_texCoord;\nlayout(location = 0) out vec4 fragColor0;\n\nvoid main() {\n vec2 texel = 1.0 / u_resolution;\n \n // Sample center and neighbors\n vec4 center = texture(u_image0, v_texCoord);\n vec4 top = texture(u_image0, v_texCoord + vec2( 0.0, -texel.y));\n vec4 bottom = texture(u_image0, v_texCoord + vec2( 0.0, texel.y));\n vec4 left = texture(u_image0, v_texCoord + vec2(-texel.x, 0.0));\n vec4 right = texture(u_image0, v_texCoord + vec2( texel.x, 0.0));\n \n // Edge enhancement (Laplacian)\n vec4 edges = center * 4.0 - top - bottom - left - right;\n \n // Add edges back scaled by strength\n vec4 sharpened = center + edges * u_float0;\n \n fragColor0 = vec4(clamp(sharpened.rgb, 0.0, 1.0), center.a);\n}", "from_input"]}], "groups": [], "links": [{"id": 36, "origin_id": 24, "origin_slot": 0, "target_id": 23, "target_slot": 2, "type": "FLOAT"}, {"id": 34, "origin_id": -10, "origin_slot": 0, "target_id": 23, "target_slot": 0, "type": "IMAGE"}, {"id": 35, "origin_id": 23, "origin_slot": 0, "target_id": -20, "target_slot": 0, "type": "IMAGE"}], "extra": {"workflowRendererVersion": "LG"}, "category": "Image Tools/Sharpen"}]}}

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@@ -1 +0,0 @@
{"revision": 0, "last_node_id": 13, "last_link_id": 0, "nodes": [{"id": 13, "type": "cf95b747-3e17-46cb-8097-cac60ff9b2e1", "pos": [1120, 330], "size": [240, 58], "flags": {}, "order": 3, "mode": 0, "inputs": [{"localized_name": "video", "name": "video", "type": "VIDEO", "link": null}, {"name": "model_name", "type": "COMBO", "widget": {"name": "model_name"}, "link": null}], "outputs": [{"localized_name": "VIDEO", "name": "VIDEO", "type": "VIDEO", "links": []}], "title": "Video Upscale(GAN x4)", "properties": {"proxyWidgets": [["-1", "model_name"]], "cnr_id": "comfy-core", "ver": "0.14.1"}, "widgets_values": ["RealESRGAN_x4plus.safetensors"]}], "links": [], "version": 0.4, "definitions": {"subgraphs": [{"id": "cf95b747-3e17-46cb-8097-cac60ff9b2e1", "version": 1, "state": {"lastGroupId": 0, "lastNodeId": 13, "lastLinkId": 19, "lastRerouteId": 0}, "revision": 0, "config": {}, "name": "Video Upscale(GAN x4)", "inputNode": {"id": -10, "bounding": [550, 460, 120, 80]}, "outputNode": {"id": -20, "bounding": [1490, 460, 120, 60]}, "inputs": [{"id": "666d633e-93e7-42dc-8d11-2b7b99b0f2a6", "name": "video", "type": "VIDEO", "linkIds": [10], "localized_name": "video", "pos": [650, 480]}, {"id": "2e23a087-caa8-4d65-99e6-662761aa905a", "name": "model_name", "type": "COMBO", "linkIds": [19], "pos": [650, 500]}], "outputs": [{"id": "0c1768ea-3ec2-412f-9af6-8e0fa36dae70", "name": "VIDEO", "type": "VIDEO", "linkIds": [15], "localized_name": "VIDEO", "pos": [1510, 480]}], "widgets": [], "nodes": [{"id": 2, "type": "ImageUpscaleWithModel", "pos": [1110, 450], "size": [320, 46], "flags": {}, "order": 1, "mode": 0, "inputs": [{"localized_name": "upscale_model", "name": "upscale_model", "type": "UPSCALE_MODEL", "link": 1}, {"localized_name": "image", "name": "image", "type": "IMAGE", "link": 14}], "outputs": [{"localized_name": "IMAGE", "name": "IMAGE", "type": "IMAGE", "links": [13]}], "properties": {"cnr_id": "comfy-core", "ver": "0.10.0", "Node name for S&R": "ImageUpscaleWithModel"}}, {"id": 11, "type": "CreateVideo", "pos": [1110, 550], "size": [320, 78], "flags": {}, "order": 3, "mode": 0, "inputs": [{"localized_name": "images", "name": "images", "type": "IMAGE", "link": 13}, {"localized_name": "audio", "name": "audio", "shape": 7, "type": "AUDIO", "link": 16}, {"localized_name": "fps", "name": "fps", "type": "FLOAT", "widget": {"name": "fps"}, "link": 12}], "outputs": [{"localized_name": "VIDEO", "name": "VIDEO", "type": "VIDEO", "links": [15]}], "properties": {"cnr_id": "comfy-core", "ver": "0.10.0", "Node name for S&R": "CreateVideo"}, "widgets_values": [30]}, {"id": 10, "type": "GetVideoComponents", "pos": [1110, 330], "size": [320, 70], "flags": {}, "order": 2, "mode": 0, "inputs": [{"localized_name": "video", "name": "video", "type": "VIDEO", "link": 10}], "outputs": [{"localized_name": "images", "name": "images", "type": "IMAGE", "links": [14]}, {"localized_name": "audio", "name": "audio", "type": "AUDIO", "links": [16]}, {"localized_name": "fps", "name": "fps", "type": "FLOAT", "links": [12]}], "properties": {"cnr_id": "comfy-core", "ver": "0.10.0", "Node name for S&R": "GetVideoComponents"}}, {"id": 1, "type": "UpscaleModelLoader", "pos": [750, 450], "size": [280, 60], "flags": {}, "order": 0, "mode": 0, "inputs": [{"localized_name": "model_name", "name": "model_name", "type": "COMBO", "widget": {"name": "model_name"}, "link": 19}], "outputs": [{"localized_name": "UPSCALE_MODEL", "name": "UPSCALE_MODEL", "type": "UPSCALE_MODEL", "links": [1]}], "properties": {"cnr_id": "comfy-core", "ver": "0.10.0", "Node name for S&R": "UpscaleModelLoader", "models": [{"name": "RealESRGAN_x4plus.safetensors", "url": "https://huggingface.co/Comfy-Org/Real-ESRGAN_repackaged/resolve/main/RealESRGAN_x4plus.safetensors", "directory": "upscale_models"}]}, "widgets_values": ["RealESRGAN_x4plus.safetensors"]}], "groups": [], "links": [{"id": 1, "origin_id": 1, "origin_slot": 0, "target_id": 2, "target_slot": 0, "type": "UPSCALE_MODEL"}, {"id": 14, "origin_id": 10, "origin_slot": 0, "target_id": 2, "target_slot": 1, "type": "IMAGE"}, {"id": 13, "origin_id": 2, "origin_slot": 0, "target_id": 11, "target_slot": 0, "type": "IMAGE"}, {"id": 16, "origin_id": 10, "origin_slot": 1, "target_id": 11, "target_slot": 1, "type": "AUDIO"}, {"id": 12, "origin_id": 10, "origin_slot": 2, "target_id": 11, "target_slot": 2, "type": "FLOAT"}, {"id": 10, "origin_id": -10, "origin_slot": 0, "target_id": 10, "target_slot": 0, "type": "VIDEO"}, {"id": 15, "origin_id": 11, "origin_slot": 0, "target_id": -20, "target_slot": 0, "type": "VIDEO"}, {"id": 19, "origin_id": -10, "origin_slot": 1, "target_id": 1, "target_slot": 0, "type": "COMBO"}], "extra": {"workflowRendererVersion": "LG"}, "category": "Video generation and editing/Enhance video"}]}, "extra": {}}

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@@ -0,0 +1,13 @@
import pickle
load = pickle.load
class Empty:
pass
class Unpickler(pickle.Unpickler):
def find_class(self, module, name):
#TODO: safe unpickle
if module.startswith("pytorch_lightning"):
return Empty
return super().find_class(module, name)

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@@ -176,8 +176,6 @@ class InputTypeOptions(TypedDict):
"""COMBO type only. Specifies the configuration for a multi-select widget.
Available after ComfyUI frontend v1.13.4
https://github.com/Comfy-Org/ComfyUI_frontend/pull/2987"""
gradient_stops: NotRequired[list[list[float]]]
"""Gradient color stops for gradientslider display mode. Each stop is [offset, r, g, b] (``FLOAT``)."""
class HiddenInputTypeDict(TypedDict):

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@@ -4,25 +4,6 @@ import comfy.utils
import logging
def is_equal(x, y):
if torch.is_tensor(x) and torch.is_tensor(y):
return torch.equal(x, y)
elif isinstance(x, dict) and isinstance(y, dict):
if x.keys() != y.keys():
return False
return all(is_equal(x[k], y[k]) for k in x)
elif isinstance(x, (list, tuple)) and isinstance(y, (list, tuple)):
if type(x) is not type(y) or len(x) != len(y):
return False
return all(is_equal(a, b) for a, b in zip(x, y))
else:
try:
return x == y
except Exception:
logging.warning("comparison issue with COND")
return False
class CONDRegular:
def __init__(self, cond):
self.cond = cond
@@ -103,7 +84,7 @@ class CONDConstant(CONDRegular):
return self._copy_with(self.cond)
def can_concat(self, other):
if not is_equal(self.cond, other.cond):
if self.cond != other.cond:
return False
return True

View File

@@ -297,30 +297,6 @@ class ControlNet(ControlBase):
self.model_sampling_current = None
super().cleanup()
class QwenFunControlNet(ControlNet):
def get_control(self, x_noisy, t, cond, batched_number, transformer_options):
# Fun checkpoints are more sensitive to high strengths in the generic
# ControlNet merge path. Use a soft response curve so strength=1.0 stays
# unchanged while >1 grows more gently.
original_strength = self.strength
self.strength = math.sqrt(max(self.strength, 0.0))
try:
return super().get_control(x_noisy, t, cond, batched_number, transformer_options)
finally:
self.strength = original_strength
def pre_run(self, model, percent_to_timestep_function):
super().pre_run(model, percent_to_timestep_function)
self.set_extra_arg("base_model", model.diffusion_model)
def copy(self):
c = QwenFunControlNet(None, global_average_pooling=self.global_average_pooling, load_device=self.load_device, manual_cast_dtype=self.manual_cast_dtype)
c.control_model = self.control_model
c.control_model_wrapped = self.control_model_wrapped
self.copy_to(c)
return c
class ControlLoraOps:
class Linear(torch.nn.Module, comfy.ops.CastWeightBiasOp):
def __init__(self, in_features: int, out_features: int, bias: bool = True,
@@ -584,7 +560,6 @@ def load_controlnet_hunyuandit(controlnet_data, model_options={}):
def load_controlnet_flux_xlabs_mistoline(sd, mistoline=False, model_options={}):
model_config, operations, load_device, unet_dtype, manual_cast_dtype, offload_device = controlnet_config(sd, model_options=model_options)
control_model = comfy.ldm.flux.controlnet.ControlNetFlux(mistoline=mistoline, operations=operations, device=offload_device, dtype=unet_dtype, **model_config.unet_config)
sd = model_config.process_unet_state_dict(sd)
control_model = controlnet_load_state_dict(control_model, sd)
extra_conds = ['y', 'guidance']
control = ControlNet(control_model, load_device=load_device, manual_cast_dtype=manual_cast_dtype, extra_conds=extra_conds)
@@ -630,53 +605,6 @@ def load_controlnet_qwen_instantx(sd, model_options={}):
control = ControlNet(control_model, compression_ratio=1, latent_format=latent_format, concat_mask=concat_mask, load_device=load_device, manual_cast_dtype=manual_cast_dtype, extra_conds=extra_conds)
return control
def load_controlnet_qwen_fun(sd, model_options={}):
load_device = comfy.model_management.get_torch_device()
weight_dtype = comfy.utils.weight_dtype(sd)
unet_dtype = model_options.get("dtype", weight_dtype)
manual_cast_dtype = comfy.model_management.unet_manual_cast(unet_dtype, load_device)
operations = model_options.get("custom_operations", None)
if operations is None:
operations = comfy.ops.pick_operations(unet_dtype, manual_cast_dtype, disable_fast_fp8=True)
in_features = sd["control_img_in.weight"].shape[1]
inner_dim = sd["control_img_in.weight"].shape[0]
block_weight = sd["control_blocks.0.attn.to_q.weight"]
attention_head_dim = sd["control_blocks.0.attn.norm_q.weight"].shape[0]
num_attention_heads = max(1, block_weight.shape[0] // max(1, attention_head_dim))
model = comfy.ldm.qwen_image.controlnet.QwenImageFunControlNetModel(
control_in_features=in_features,
inner_dim=inner_dim,
num_attention_heads=num_attention_heads,
attention_head_dim=attention_head_dim,
num_control_blocks=5,
main_model_double=60,
injection_layers=(0, 12, 24, 36, 48),
operations=operations,
device=comfy.model_management.unet_offload_device(),
dtype=unet_dtype,
)
model = controlnet_load_state_dict(model, sd)
latent_format = comfy.latent_formats.Wan21()
control = QwenFunControlNet(
model,
compression_ratio=1,
latent_format=latent_format,
# Fun checkpoints already expect their own 33-channel context handling.
# Enabling generic concat_mask injects an extra mask channel at apply-time
# and breaks the intended fallback packing path.
concat_mask=False,
load_device=load_device,
manual_cast_dtype=manual_cast_dtype,
extra_conds=[],
)
return control
def convert_mistoline(sd):
return comfy.utils.state_dict_prefix_replace(sd, {"single_controlnet_blocks.": "controlnet_single_blocks."})
@@ -754,8 +682,6 @@ def load_controlnet_state_dict(state_dict, model=None, model_options={}):
return load_controlnet_qwen_instantx(controlnet_data, model_options=model_options)
elif "controlnet_x_embedder.weight" in controlnet_data:
return load_controlnet_flux_instantx(controlnet_data, model_options=model_options)
elif "control_blocks.0.after_proj.weight" in controlnet_data and "control_img_in.weight" in controlnet_data:
return load_controlnet_qwen_fun(controlnet_data, model_options=model_options)
elif "controlnet_blocks.0.linear.weight" in controlnet_data: #mistoline flux
return load_controlnet_flux_xlabs_mistoline(convert_mistoline(controlnet_data), mistoline=True, model_options=model_options)

View File

@@ -1,11 +1,12 @@
import math
import time
from functools import partial
from scipy import integrate
import torch
from torch import nn
import torchsde
from tqdm.auto import tqdm
from tqdm.auto import trange as trange_, tqdm
from . import utils
from . import deis
@@ -14,7 +15,34 @@ import comfy.model_patcher
import comfy.model_sampling
import comfy.memory_management
from comfy.utils import model_trange as trange
def trange(*args, **kwargs):
if comfy.memory_management.aimdo_allocator is None:
return trange_(*args, **kwargs)
pbar = trange_(*args, **kwargs, smoothing=1.0)
pbar._i = 0
pbar.set_postfix_str(" Model Initializing ... ")
_update = pbar.update
def warmup_update(n=1):
pbar._i += 1
if pbar._i == 1:
pbar.i1_time = time.time()
pbar.set_postfix_str(" Model Initialization complete! ")
elif pbar._i == 2:
#bring forward the effective start time based the the diff between first and second iteration
#to attempt to remove load overhead from the final step rate estimate.
pbar.start_t = pbar.i1_time - (time.time() - pbar.i1_time)
pbar.set_postfix_str("")
_update(n)
pbar.update = warmup_update
return pbar
def append_zero(x):
return torch.cat([x, x.new_zeros([1])])

View File

@@ -7,67 +7,6 @@ from comfy.ldm.modules.attention import optimized_attention
import comfy.model_management
from comfy.ldm.flux.layers import timestep_embedding
def get_silence_latent(length, device):
head = torch.tensor([[[ 0.5707, 0.0982, 0.6909, -0.5658, 0.6266, 0.6996, -0.1365, -0.1291,
-0.0776, -0.1171, -0.2743, -0.8422, -0.1168, 1.5539, -4.6936, 0.7436,
-1.1846, -0.2637, 0.6933, -6.7266, 0.0966, -0.1187, -0.3501, -1.1736,
0.0587, -2.0517, -1.3651, 0.7508, -0.2490, -1.3548, -0.1290, -0.7261,
1.1132, -0.3249, 0.2337, 0.3004, 0.6605, -0.0298, -0.1989, -0.4041,
0.2843, -1.0963, -0.5519, 0.2639, -1.0436, -0.1183, 0.0640, 0.4460,
-1.1001, -0.6172, -1.3241, 1.1379, 0.5623, -0.1507, -0.1963, -0.4742,
-2.4697, 0.5302, 0.5381, 0.4636, -0.1782, -0.0687, 1.0333, 0.4202],
[ 0.3040, -0.1367, 0.6200, 0.0665, -0.0642, 0.4655, -0.1187, -0.0440,
0.2941, -0.2753, 0.0173, -0.2421, -0.0147, 1.5603, -2.7025, 0.7907,
-0.9736, -0.0682, 0.1294, -5.0707, -0.2167, 0.3302, -0.1513, -0.8100,
-0.3894, -0.2884, -0.3149, 0.8660, -0.3817, -1.7061, 0.5824, -0.4840,
0.6938, 0.1859, 0.1753, 0.3081, 0.0195, 0.1403, -0.0754, -0.2091,
0.1251, -0.1578, -0.4968, -0.1052, -0.4554, -0.0320, 0.1284, 0.4974,
-1.1889, -0.0344, -0.8313, 0.2953, 0.5445, -0.6249, -0.1595, -0.0682,
-3.1412, 0.0484, 0.4153, 0.8260, -0.1526, -0.0625, 0.5366, 0.8473],
[ 5.3524e-02, -1.7534e-01, 5.4443e-01, -4.3501e-01, -2.1317e-03,
3.7200e-01, -4.0143e-03, -1.5516e-01, -1.2968e-01, -1.5375e-01,
-7.7107e-02, -2.0593e-01, -3.2780e-01, 1.5142e+00, -2.6101e+00,
5.8698e-01, -1.2716e+00, -2.4773e-01, -2.7933e-02, -5.0799e+00,
1.1601e-01, 4.0987e-01, -2.2030e-02, -6.6495e-01, -2.0995e-01,
-6.3474e-01, -1.5893e-01, 8.2745e-01, -2.2992e-01, -1.6816e+00,
5.4440e-01, -4.9579e-01, 5.5128e-01, 3.0477e-01, 8.3052e-02,
-6.1782e-02, 5.9036e-03, 2.9553e-01, -8.0645e-02, -1.0060e-01,
1.9144e-01, -3.8124e-01, -7.2949e-01, 2.4520e-02, -5.0814e-01,
2.3977e-01, 9.2943e-02, 3.9256e-01, -1.1993e+00, -3.2752e-01,
-7.2707e-01, 2.9476e-01, 4.3542e-01, -8.8597e-01, -4.1686e-01,
-8.5390e-02, -2.9018e+00, 6.4988e-02, 5.3945e-01, 9.1988e-01,
5.8762e-02, -7.0098e-02, 6.4772e-01, 8.9118e-01],
[-3.2225e-02, -1.3195e-01, 5.6411e-01, -5.4766e-01, -5.2170e-03,
3.1425e-01, -5.4367e-02, -1.9419e-01, -1.3059e-01, -1.3660e-01,
-9.0984e-02, -1.9540e-01, -2.5590e-01, 1.5440e+00, -2.6349e+00,
6.8273e-01, -1.2532e+00, -1.9810e-01, -2.2793e-02, -5.0506e+00,
1.8818e-01, 5.0109e-01, 7.3546e-03, -6.8771e-01, -3.0676e-01,
-7.3257e-01, -1.6687e-01, 9.2232e-01, -1.8987e-01, -1.7267e+00,
5.3355e-01, -5.3179e-01, 4.4953e-01, 2.8820e-01, 1.3012e-01,
-2.0943e-01, -1.1348e-01, 3.3929e-01, -1.5069e-01, -1.2919e-01,
1.8929e-01, -3.6166e-01, -8.0756e-01, 6.6387e-02, -5.8867e-01,
1.6978e-01, 1.0134e-01, 3.3877e-01, -1.2133e+00, -3.2492e-01,
-8.1237e-01, 3.8101e-01, 4.3765e-01, -8.0596e-01, -4.4531e-01,
-4.7513e-02, -2.9266e+00, 1.1741e-03, 4.5123e-01, 9.3075e-01,
5.3688e-02, -1.9621e-01, 6.4530e-01, 9.3870e-01]]], device=device).movedim(-1, 1)
silence_latent = torch.tensor([[[-1.3672e-01, -1.5820e-01, 5.8594e-01, -5.7422e-01, 3.0273e-02,
2.7930e-01, -2.5940e-03, -2.0703e-01, -1.6113e-01, -1.4746e-01,
-2.7710e-02, -1.8066e-01, -2.9688e-01, 1.6016e+00, -2.6719e+00,
7.7734e-01, -1.3516e+00, -1.9434e-01, -7.1289e-02, -5.0938e+00,
2.4316e-01, 4.7266e-01, 4.6387e-02, -6.6406e-01, -2.1973e-01,
-6.7578e-01, -1.5723e-01, 9.5312e-01, -2.0020e-01, -1.7109e+00,
5.8984e-01, -5.7422e-01, 5.1562e-01, 2.8320e-01, 1.4551e-01,
-1.8750e-01, -5.9814e-02, 3.6719e-01, -1.0059e-01, -1.5723e-01,
2.0605e-01, -4.3359e-01, -8.2812e-01, 4.5654e-02, -6.6016e-01,
1.4844e-01, 9.4727e-02, 3.8477e-01, -1.2578e+00, -3.3203e-01,
-8.5547e-01, 4.3359e-01, 4.2383e-01, -8.9453e-01, -5.0391e-01,
-5.6152e-02, -2.9219e+00, -2.4658e-02, 5.0391e-01, 9.8438e-01,
7.2754e-02, -2.1582e-01, 6.3672e-01, 1.0000e+00]]], device=device).movedim(-1, 1).repeat(1, 1, length)
silence_latent[:, :, :head.shape[-1]] = head
return silence_latent
def get_layer_class(operations, layer_name):
if operations is not None and hasattr(operations, layer_name):
return getattr(operations, layer_name)
@@ -244,7 +183,7 @@ class AceStepAttention(nn.Module):
else:
attn_bias = window_bias
attn_output = optimized_attention(query_states, key_states, value_states, self.num_heads, attn_bias, skip_reshape=True, low_precision_attention=False)
attn_output = optimized_attention(query_states, key_states, value_states, self.num_heads, attn_bias, skip_reshape=True)
attn_output = self.o_proj(attn_output)
return attn_output
@@ -738,7 +677,7 @@ class AttentionPooler(nn.Module):
def forward(self, x):
B, T, P, D = x.shape
x = self.embed_tokens(x)
special = comfy.model_management.cast_to(self.special_token, device=x.device, dtype=x.dtype).expand(B, T, 1, -1)
special = self.special_token.expand(B, T, 1, -1)
x = torch.cat([special, x], dim=2)
x = x.view(B * T, P + 1, D)
@@ -789,7 +728,7 @@ class FSQ(nn.Module):
self.register_buffer('implicit_codebook', implicit_codebook, persistent=False)
def bound(self, z):
levels_minus_1 = (comfy.model_management.cast_to(self._levels, device=z.device, dtype=z.dtype) - 1)
levels_minus_1 = (self._levels - 1).to(z.dtype)
scale = 2. / levels_minus_1
bracket = (levels_minus_1 * (torch.tanh(z) + 1) / 2.) + 0.5
@@ -804,8 +743,8 @@ class FSQ(nn.Module):
return codes_non_centered.float() * (2. / (self._levels.float() - 1)) - 1.
def codes_to_indices(self, zhat):
zhat_normalized = (zhat + 1.) / (2. / (comfy.model_management.cast_to(self._levels, device=zhat.device, dtype=zhat.dtype) - 1))
return (zhat_normalized * comfy.model_management.cast_to(self._basis, device=zhat.device, dtype=zhat.dtype)).sum(dim=-1).round().to(torch.int32)
zhat_normalized = (zhat + 1.) / (2. / (self._levels.to(zhat.dtype) - 1))
return (zhat_normalized * self._basis.to(zhat.dtype)).sum(dim=-1).round().to(torch.int32)
def forward(self, z):
orig_dtype = z.dtype
@@ -887,7 +826,7 @@ class ResidualFSQ(nn.Module):
x = self.project_in(x)
if hasattr(self, 'soft_clamp_input_value'):
sc_val = comfy.model_management.cast_to(self.soft_clamp_input_value, device=x.device, dtype=x.dtype)
sc_val = self.soft_clamp_input_value.to(x.dtype)
x = (x / sc_val).tanh() * sc_val
quantized_out = torch.tensor(0., device=x.device, dtype=x.dtype)
@@ -895,7 +834,7 @@ class ResidualFSQ(nn.Module):
all_indices = []
for layer, scale in zip(self.layers, self.scales):
scale = comfy.model_management.cast_to(scale, device=x.device, dtype=x.dtype)
scale = scale.to(residual.dtype)
quantized, indices = layer(residual / scale)
quantized = quantized * scale
@@ -1096,26 +1035,28 @@ class AceStepConditionGenerationModel(nn.Module):
audio_codes = torch.nn.functional.pad(audio_codes, (0, math.ceil(src_latents.shape[1] / 5) - audio_codes.shape[1]), "constant", 35847)
lm_hints_5Hz = self.tokenizer.quantizer.get_output_from_indices(audio_codes, dtype=text_hidden_states.dtype)
else:
lm_hints_5Hz, indices = self.tokenizer.tokenize(refer_audio_acoustic_hidden_states_packed)
assert False
# TODO ?
lm_hints = self.detokenizer(lm_hints_5Hz)
lm_hints = lm_hints[:, :src_latents.shape[1], :]
if is_covers is None or is_covers is True:
if is_covers is None:
src_latents = lm_hints
elif is_covers is False:
src_latents = refer_audio_acoustic_hidden_states_packed
else:
src_latents = torch.where(is_covers.unsqueeze(-1).unsqueeze(-1) > 0, lm_hints, src_latents)
context_latents = torch.cat([src_latents, chunk_masks.to(src_latents.dtype)], dim=-1)
return encoder_hidden, encoder_mask, context_latents
def forward(self, x, timestep, context, lyric_embed=None, refer_audio=None, audio_codes=None, is_covers=None, replace_with_null_embeds=False, **kwargs):
def forward(self, x, timestep, context, lyric_embed=None, refer_audio=None, audio_codes=None, **kwargs):
text_attention_mask = None
lyric_attention_mask = None
refer_audio_order_mask = None
attention_mask = None
chunk_masks = None
is_covers = None
src_latents = None
precomputed_lm_hints_25Hz = None
lyric_hidden_states = lyric_embed
@@ -1127,7 +1068,7 @@ class AceStepConditionGenerationModel(nn.Module):
if refer_audio_order_mask is None:
refer_audio_order_mask = torch.zeros((x.shape[0],), device=x.device, dtype=torch.long)
if src_latents is None:
if src_latents is None and is_covers is None:
src_latents = x
if chunk_masks is None:
@@ -1140,9 +1081,6 @@ class AceStepConditionGenerationModel(nn.Module):
src_latents, chunk_masks, is_covers, precomputed_lm_hints_25Hz=precomputed_lm_hints_25Hz, audio_codes=audio_codes
)
if replace_with_null_embeds:
enc_hidden[:] = self.null_condition_emb.to(enc_hidden)
out = self.decoder(hidden_states=x,
timestep=timestep,
timestep_r=timestep,

View File

@@ -179,8 +179,8 @@ class LLMAdapter(nn.Module):
if source_attention_mask.ndim == 2:
source_attention_mask = source_attention_mask.unsqueeze(1).unsqueeze(1)
x = self.in_proj(self.embed(target_input_ids))
context = source_hidden_states
x = self.in_proj(self.embed(target_input_ids, out_dtype=context.dtype))
position_ids = torch.arange(x.shape[1], device=x.device).unsqueeze(0)
position_ids_context = torch.arange(context.shape[1], device=x.device).unsqueeze(0)
position_embeddings = self.rotary_emb(x, position_ids)
@@ -195,20 +195,8 @@ class Anima(MiniTrainDIT):
super().__init__(*args, **kwargs)
self.llm_adapter = LLMAdapter(device=kwargs.get("device"), dtype=kwargs.get("dtype"), operations=kwargs.get("operations"))
def preprocess_text_embeds(self, text_embeds, text_ids, t5xxl_weights=None):
def preprocess_text_embeds(self, text_embeds, text_ids):
if text_ids is not None:
out = self.llm_adapter(text_embeds, text_ids)
if t5xxl_weights is not None:
out = out * t5xxl_weights
if out.shape[1] < 512:
out = torch.nn.functional.pad(out, (0, 0, 0, 512 - out.shape[1]))
return out
return self.llm_adapter(text_embeds, text_ids)
else:
return text_embeds
def forward(self, x, timesteps, context, **kwargs):
t5xxl_ids = kwargs.pop("t5xxl_ids", None)
if t5xxl_ids is not None:
context = self.preprocess_text_embeds(context, t5xxl_ids, t5xxl_weights=kwargs.pop("t5xxl_weights", None))
return super().forward(x, timesteps, context, **kwargs)

View File

@@ -3,6 +3,7 @@ from torch import Tensor, nn
from comfy.ldm.flux.layers import (
MLPEmbedder,
RMSNorm,
ModulationOut,
)
@@ -28,7 +29,7 @@ class Approximator(nn.Module):
super().__init__()
self.in_proj = operations.Linear(in_dim, hidden_dim, bias=True, dtype=dtype, device=device)
self.layers = nn.ModuleList([MLPEmbedder(hidden_dim, hidden_dim, dtype=dtype, device=device, operations=operations) for x in range( n_layers)])
self.norms = nn.ModuleList([operations.RMSNorm(hidden_dim, dtype=dtype, device=device) for x in range( n_layers)])
self.norms = nn.ModuleList([RMSNorm(hidden_dim, dtype=dtype, device=device, operations=operations) for x in range( n_layers)])
self.out_proj = operations.Linear(hidden_dim, out_dim, dtype=dtype, device=device)
@property

View File

@@ -152,7 +152,6 @@ class Chroma(nn.Module):
transformer_options={},
attn_mask: Tensor = None,
) -> Tensor:
transformer_options = transformer_options.copy()
patches_replace = transformer_options.get("patches_replace", {})
# running on sequences img
@@ -229,7 +228,6 @@ class Chroma(nn.Module):
transformer_options["total_blocks"] = len(self.single_blocks)
transformer_options["block_type"] = "single"
transformer_options["img_slice"] = [txt.shape[1], img.shape[1]]
for i, block in enumerate(self.single_blocks):
transformer_options["block_index"] = i
if i not in self.skip_dit:

View File

@@ -4,6 +4,8 @@ from functools import lru_cache
import torch
from torch import nn
from comfy.ldm.flux.layers import RMSNorm
class NerfEmbedder(nn.Module):
"""
@@ -143,7 +145,7 @@ class NerfGLUBlock(nn.Module):
# We now need to generate parameters for 3 matrices.
total_params = 3 * hidden_size_x**2 * mlp_ratio
self.param_generator = operations.Linear(hidden_size_s, total_params, dtype=dtype, device=device)
self.norm = operations.RMSNorm(hidden_size_x, dtype=dtype, device=device)
self.norm = RMSNorm(hidden_size_x, dtype=dtype, device=device, operations=operations)
self.mlp_ratio = mlp_ratio
@@ -176,7 +178,7 @@ class NerfGLUBlock(nn.Module):
class NerfFinalLayer(nn.Module):
def __init__(self, hidden_size, out_channels, dtype=None, device=None, operations=None):
super().__init__()
self.norm = operations.RMSNorm(hidden_size, dtype=dtype, device=device)
self.norm = RMSNorm(hidden_size, dtype=dtype, device=device, operations=operations)
self.linear = operations.Linear(hidden_size, out_channels, dtype=dtype, device=device)
def forward(self, x: torch.Tensor) -> torch.Tensor:
@@ -188,7 +190,7 @@ class NerfFinalLayer(nn.Module):
class NerfFinalLayerConv(nn.Module):
def __init__(self, hidden_size: int, out_channels: int, dtype=None, device=None, operations=None):
super().__init__()
self.norm = operations.RMSNorm(hidden_size, dtype=dtype, device=device)
self.norm = RMSNorm(hidden_size, dtype=dtype, device=device, operations=operations)
self.conv = operations.Conv2d(
in_channels=hidden_size,
out_channels=out_channels,

View File

@@ -335,7 +335,7 @@ class FinalLayer(nn.Module):
device=None, dtype=None, operations=None
):
super().__init__()
self.layer_norm = operations.LayerNorm(hidden_size, elementwise_affine=False, eps=1e-6)
self.layer_norm = nn.LayerNorm(hidden_size, elementwise_affine=False, eps=1e-6)
self.linear = operations.Linear(
hidden_size, spatial_patch_size * spatial_patch_size * temporal_patch_size * out_channels, bias=False, device=device, dtype=dtype
)
@@ -463,8 +463,6 @@ class Block(nn.Module):
extra_per_block_pos_emb: Optional[torch.Tensor] = None,
transformer_options: Optional[dict] = {},
) -> torch.Tensor:
residual_dtype = x_B_T_H_W_D.dtype
compute_dtype = emb_B_T_D.dtype
if extra_per_block_pos_emb is not None:
x_B_T_H_W_D = x_B_T_H_W_D + extra_per_block_pos_emb
@@ -514,7 +512,7 @@ class Block(nn.Module):
result_B_T_H_W_D = rearrange(
self.self_attn(
# normalized_x_B_T_HW_D,
rearrange(normalized_x_B_T_H_W_D.to(compute_dtype), "b t h w d -> b (t h w) d"),
rearrange(normalized_x_B_T_H_W_D, "b t h w d -> b (t h w) d"),
None,
rope_emb=rope_emb_L_1_1_D,
transformer_options=transformer_options,
@@ -524,7 +522,7 @@ class Block(nn.Module):
h=H,
w=W,
)
x_B_T_H_W_D = x_B_T_H_W_D + gate_self_attn_B_T_1_1_D.to(residual_dtype) * result_B_T_H_W_D.to(residual_dtype)
x_B_T_H_W_D = x_B_T_H_W_D + gate_self_attn_B_T_1_1_D * result_B_T_H_W_D
def _x_fn(
_x_B_T_H_W_D: torch.Tensor,
@@ -538,7 +536,7 @@ class Block(nn.Module):
)
_result_B_T_H_W_D = rearrange(
self.cross_attn(
rearrange(_normalized_x_B_T_H_W_D.to(compute_dtype), "b t h w d -> b (t h w) d"),
rearrange(_normalized_x_B_T_H_W_D, "b t h w d -> b (t h w) d"),
crossattn_emb,
rope_emb=rope_emb_L_1_1_D,
transformer_options=transformer_options,
@@ -557,7 +555,7 @@ class Block(nn.Module):
shift_cross_attn_B_T_1_1_D,
transformer_options=transformer_options,
)
x_B_T_H_W_D = result_B_T_H_W_D.to(residual_dtype) * gate_cross_attn_B_T_1_1_D.to(residual_dtype) + x_B_T_H_W_D
x_B_T_H_W_D = result_B_T_H_W_D * gate_cross_attn_B_T_1_1_D + x_B_T_H_W_D
normalized_x_B_T_H_W_D = _fn(
x_B_T_H_W_D,
@@ -565,8 +563,8 @@ class Block(nn.Module):
scale_mlp_B_T_1_1_D,
shift_mlp_B_T_1_1_D,
)
result_B_T_H_W_D = self.mlp(normalized_x_B_T_H_W_D.to(compute_dtype))
x_B_T_H_W_D = x_B_T_H_W_D + gate_mlp_B_T_1_1_D.to(residual_dtype) * result_B_T_H_W_D.to(residual_dtype)
result_B_T_H_W_D = self.mlp(normalized_x_B_T_H_W_D)
x_B_T_H_W_D = x_B_T_H_W_D + gate_mlp_B_T_1_1_D * result_B_T_H_W_D
return x_B_T_H_W_D
@@ -878,14 +876,6 @@ class MiniTrainDIT(nn.Module):
"extra_per_block_pos_emb": extra_pos_emb_B_T_H_W_D_or_T_H_W_B_D,
"transformer_options": kwargs.get("transformer_options", {}),
}
# The residual stream for this model has large values. To make fp16 compute_dtype work, we keep the residual stream
# in fp32, but run attention and MLP modules in fp16.
# An alternate method that clamps fp16 values "works" in the sense that it makes coherent images, but there is noticeable
# quality degradation and visual artifacts.
if x_B_T_H_W_D.dtype == torch.float16:
x_B_T_H_W_D = x_B_T_H_W_D.float()
for block in self.blocks:
x_B_T_H_W_D = block(
x_B_T_H_W_D,
@@ -894,6 +884,6 @@ class MiniTrainDIT(nn.Module):
**block_kwargs,
)
x_B_T_H_W_O = self.final_layer(x_B_T_H_W_D.to(crossattn_emb.dtype), t_embedding_B_T_D, adaln_lora_B_T_3D=adaln_lora_B_T_3D)
x_B_T_H_W_O = self.final_layer(x_B_T_H_W_D, t_embedding_B_T_D, adaln_lora_B_T_3D=adaln_lora_B_T_3D)
x_B_C_Tt_Hp_Wp = self.unpatchify(x_B_T_H_W_O)[:, :, :orig_shape[-3], :orig_shape[-2], :orig_shape[-1]]
return x_B_C_Tt_Hp_Wp

View File

@@ -5,9 +5,9 @@ import torch
from torch import Tensor, nn
from .math import attention, rope
import comfy.ops
import comfy.ldm.common_dit
# Fix import for some custom nodes, TODO: delete eventually.
RMSNorm = None
class EmbedND(nn.Module):
def __init__(self, dim: int, theta: int, axes_dim: list):
@@ -87,12 +87,20 @@ def build_mlp(hidden_size, mlp_hidden_dim, mlp_silu_act=False, yak_mlp=False, dt
operations.Linear(mlp_hidden_dim, hidden_size, bias=True, dtype=dtype, device=device),
)
class RMSNorm(torch.nn.Module):
def __init__(self, dim: int, dtype=None, device=None, operations=None):
super().__init__()
self.scale = nn.Parameter(torch.empty((dim), dtype=dtype, device=device))
def forward(self, x: Tensor):
return comfy.ldm.common_dit.rms_norm(x, self.scale, 1e-6)
class QKNorm(torch.nn.Module):
def __init__(self, dim: int, dtype=None, device=None, operations=None):
super().__init__()
self.query_norm = operations.RMSNorm(dim, dtype=dtype, device=device)
self.key_norm = operations.RMSNorm(dim, dtype=dtype, device=device)
self.query_norm = RMSNorm(dim, dtype=dtype, device=device, operations=operations)
self.key_norm = RMSNorm(dim, dtype=dtype, device=device, operations=operations)
def forward(self, q: Tensor, k: Tensor, v: Tensor) -> tuple:
q = self.query_norm(q)
@@ -161,7 +169,7 @@ class SiLUActivation(nn.Module):
class DoubleStreamBlock(nn.Module):
def __init__(self, hidden_size: int, num_heads: int, mlp_ratio: float, qkv_bias: bool = False, modulation=True, mlp_silu_act=False, proj_bias=True, yak_mlp=False, dtype=None, device=None, operations=None):
def __init__(self, hidden_size: int, num_heads: int, mlp_ratio: float, qkv_bias: bool = False, flipped_img_txt=False, modulation=True, mlp_silu_act=False, proj_bias=True, yak_mlp=False, dtype=None, device=None, operations=None):
super().__init__()
mlp_hidden_dim = int(hidden_size * mlp_ratio)
@@ -189,6 +197,8 @@ class DoubleStreamBlock(nn.Module):
self.txt_mlp = build_mlp(hidden_size, mlp_hidden_dim, mlp_silu_act=mlp_silu_act, yak_mlp=yak_mlp, dtype=dtype, device=device, operations=operations)
self.flipped_img_txt = flipped_img_txt
def forward(self, img: Tensor, txt: Tensor, vec: Tensor, pe: Tensor, attn_mask=None, modulation_dims_img=None, modulation_dims_txt=None, transformer_options={}):
if self.modulation:
img_mod1, img_mod2 = self.img_mod(vec)
@@ -196,9 +206,6 @@ class DoubleStreamBlock(nn.Module):
else:
(img_mod1, img_mod2), (txt_mod1, txt_mod2) = vec
transformer_patches = transformer_options.get("patches", {})
extra_options = transformer_options.copy()
# prepare image for attention
img_modulated = self.img_norm1(img)
img_modulated = apply_mod(img_modulated, (1 + img_mod1.scale), img_mod1.shift, modulation_dims_img)
@@ -217,23 +224,32 @@ class DoubleStreamBlock(nn.Module):
del txt_qkv
txt_q, txt_k = self.txt_attn.norm(txt_q, txt_k, txt_v)
q = torch.cat((txt_q, img_q), dim=2)
del txt_q, img_q
k = torch.cat((txt_k, img_k), dim=2)
del txt_k, img_k
v = torch.cat((txt_v, img_v), dim=2)
del txt_v, img_v
# run actual attention
attn = attention(q, k, v, pe=pe, mask=attn_mask, transformer_options=transformer_options)
del q, k, v
if self.flipped_img_txt:
q = torch.cat((img_q, txt_q), dim=2)
del img_q, txt_q
k = torch.cat((img_k, txt_k), dim=2)
del img_k, txt_k
v = torch.cat((img_v, txt_v), dim=2)
del img_v, txt_v
# run actual attention
attn = attention(q, k, v,
pe=pe, mask=attn_mask, transformer_options=transformer_options)
del q, k, v
if "attn1_output_patch" in transformer_patches:
extra_options["img_slice"] = [txt.shape[1], attn.shape[1]]
patch = transformer_patches["attn1_output_patch"]
for p in patch:
attn = p(attn, extra_options)
img_attn, txt_attn = attn[:, : img.shape[1]], attn[:, img.shape[1]:]
else:
q = torch.cat((txt_q, img_q), dim=2)
del txt_q, img_q
k = torch.cat((txt_k, img_k), dim=2)
del txt_k, img_k
v = torch.cat((txt_v, img_v), dim=2)
del txt_v, img_v
# run actual attention
attn = attention(q, k, v,
pe=pe, mask=attn_mask, transformer_options=transformer_options)
del q, k, v
txt_attn, img_attn = attn[:, : txt.shape[1]], attn[:, txt.shape[1]:]
txt_attn, img_attn = attn[:, : txt.shape[1]], attn[:, txt.shape[1]:]
# calculate the img bloks
img += apply_mod(self.img_attn.proj(img_attn), img_mod1.gate, None, modulation_dims_img)
@@ -312,9 +328,6 @@ class SingleStreamBlock(nn.Module):
else:
mod = vec
transformer_patches = transformer_options.get("patches", {})
extra_options = transformer_options.copy()
qkv, mlp = torch.split(self.linear1(apply_mod(self.pre_norm(x), (1 + mod.scale), mod.shift, modulation_dims)), [3 * self.hidden_size, self.mlp_hidden_dim_first], dim=-1)
q, k, v = qkv.view(qkv.shape[0], qkv.shape[1], 3, self.num_heads, -1).permute(2, 0, 3, 1, 4)
@@ -324,12 +337,6 @@ class SingleStreamBlock(nn.Module):
# compute attention
attn = attention(q, k, v, pe=pe, mask=attn_mask, transformer_options=transformer_options)
del q, k, v
if "attn1_output_patch" in transformer_patches:
patch = transformer_patches["attn1_output_patch"]
for p in patch:
attn = p(attn, extra_options)
# compute activation in mlp stream, cat again and run second linear layer
if self.yak_mlp:
mlp = self.mlp_act(mlp[..., self.mlp_hidden_dim_first // 2:]) * mlp[..., :self.mlp_hidden_dim_first // 2]

View File

@@ -29,34 +29,19 @@ def rope(pos: Tensor, dim: int, theta: int) -> Tensor:
return out.to(dtype=torch.float32, device=pos.device)
def _apply_rope1(x: Tensor, freqs_cis: Tensor):
x_ = x.to(dtype=freqs_cis.dtype).reshape(*x.shape[:-1], -1, 1, 2)
x_out = freqs_cis[..., 0] * x_[..., 0]
x_out.addcmul_(freqs_cis[..., 1], x_[..., 1])
return x_out.reshape(*x.shape).type_as(x)
def _apply_rope(xq: Tensor, xk: Tensor, freqs_cis: Tensor):
return apply_rope1(xq, freqs_cis), apply_rope1(xk, freqs_cis)
try:
import comfy.quant_ops
q_apply_rope = comfy.quant_ops.ck.apply_rope
q_apply_rope1 = comfy.quant_ops.ck.apply_rope1
def apply_rope(xq, xk, freqs_cis):
if comfy.model_management.in_training:
return _apply_rope(xq, xk, freqs_cis)
else:
return apply_rope1(xq, freqs_cis), apply_rope1(xk, freqs_cis)
def apply_rope1(x, freqs_cis):
if comfy.model_management.in_training:
return _apply_rope1(x, freqs_cis)
else:
return q_apply_rope1(x, freqs_cis)
apply_rope = comfy.quant_ops.ck.apply_rope
apply_rope1 = comfy.quant_ops.ck.apply_rope1
except:
logging.warning("No comfy kitchen, using old apply_rope functions.")
apply_rope = _apply_rope
apply_rope1 = _apply_rope1
def apply_rope1(x: Tensor, freqs_cis: Tensor):
x_ = x.to(dtype=freqs_cis.dtype).reshape(*x.shape[:-1], -1, 1, 2)
x_out = freqs_cis[..., 0] * x_[..., 0]
x_out.addcmul_(freqs_cis[..., 1], x_[..., 1])
return x_out.reshape(*x.shape).type_as(x)
def apply_rope(xq: Tensor, xk: Tensor, freqs_cis: Tensor):
return apply_rope1(xq, freqs_cis), apply_rope1(xk, freqs_cis)

View File

@@ -16,6 +16,7 @@ from .layers import (
SingleStreamBlock,
timestep_embedding,
Modulation,
RMSNorm
)
@dataclass
@@ -80,7 +81,7 @@ class Flux(nn.Module):
self.txt_in = operations.Linear(params.context_in_dim, self.hidden_size, bias=params.ops_bias, dtype=dtype, device=device)
if params.txt_norm:
self.txt_norm = operations.RMSNorm(params.context_in_dim, dtype=dtype, device=device)
self.txt_norm = RMSNorm(params.context_in_dim, dtype=dtype, device=device, operations=operations)
else:
self.txt_norm = None
@@ -142,7 +143,6 @@ class Flux(nn.Module):
attn_mask: Tensor = None,
) -> Tensor:
transformer_options = transformer_options.copy()
patches = transformer_options.get("patches", {})
patches_replace = transformer_options.get("patches_replace", {})
if img.ndim != 3 or txt.ndim != 3:
@@ -232,7 +232,6 @@ class Flux(nn.Module):
transformer_options["total_blocks"] = len(self.single_blocks)
transformer_options["block_type"] = "single"
transformer_options["img_slice"] = [txt.shape[1], img.shape[1]]
for i, block in enumerate(self.single_blocks):
transformer_options["block_index"] = i
if ("single_block", i) in blocks_replace:

View File

@@ -241,6 +241,7 @@ class HunyuanVideo(nn.Module):
self.num_heads,
mlp_ratio=params.mlp_ratio,
qkv_bias=params.qkv_bias,
flipped_img_txt=True,
dtype=dtype, device=device, operations=operations
)
for _ in range(params.depth)
@@ -304,7 +305,6 @@ class HunyuanVideo(nn.Module):
control=None,
transformer_options={},
) -> Tensor:
transformer_options = transformer_options.copy()
patches_replace = transformer_options.get("patches_replace", {})
initial_shape = list(img.shape)
@@ -378,14 +378,14 @@ class HunyuanVideo(nn.Module):
extra_txt_ids = torch.zeros((txt_ids.shape[0], txt_vision_states.shape[1], txt_ids.shape[-1]), device=txt_ids.device, dtype=txt_ids.dtype)
txt_ids = torch.cat((txt_ids, extra_txt_ids), dim=1)
ids = torch.cat((txt_ids, img_ids), dim=1)
ids = torch.cat((img_ids, txt_ids), dim=1)
pe = self.pe_embedder(ids)
img_len = img.shape[1]
if txt_mask is not None:
attn_mask_len = img_len + txt.shape[1]
attn_mask = torch.zeros((1, 1, attn_mask_len), dtype=img.dtype, device=img.device)
attn_mask[:, 0, :txt.shape[1]] = txt_mask
attn_mask[:, 0, img_len:] = txt_mask
else:
attn_mask = None
@@ -413,11 +413,10 @@ class HunyuanVideo(nn.Module):
if add is not None:
img += add
img = torch.cat((txt, img), 1)
img = torch.cat((img, txt), 1)
transformer_options["total_blocks"] = len(self.single_blocks)
transformer_options["block_type"] = "single"
transformer_options["img_slice"] = [txt.shape[1], img.shape[1]]
for i, block in enumerate(self.single_blocks):
transformer_options["block_index"] = i
if ("single_block", i) in blocks_replace:
@@ -436,9 +435,9 @@ class HunyuanVideo(nn.Module):
if i < len(control_o):
add = control_o[i]
if add is not None:
img[:, txt.shape[1]: img_len + txt.shape[1]] += add
img[:, : img_len] += add
img = img[:, txt.shape[1]: img_len + txt.shape[1]]
img = img[:, : img_len]
if ref_latent is not None:
img = img[:, ref_latent.shape[1]:]

View File

@@ -9,7 +9,6 @@ from comfy.ldm.lightricks.model import (
LTXVModel,
)
from comfy.ldm.lightricks.symmetric_patchifier import AudioPatchifier
from comfy.ldm.lightricks.embeddings_connector import Embeddings1DConnector
import comfy.ldm.common_dit
class CompressedTimestep:
@@ -218,7 +217,7 @@ class BasicAVTransformerBlock(nn.Module):
def forward(
self, x: Tuple[torch.Tensor, torch.Tensor], v_context=None, a_context=None, attention_mask=None, v_timestep=None, a_timestep=None,
v_pe=None, a_pe=None, v_cross_pe=None, a_cross_pe=None, v_cross_scale_shift_timestep=None, a_cross_scale_shift_timestep=None,
v_cross_gate_timestep=None, a_cross_gate_timestep=None, transformer_options=None, self_attention_mask=None,
v_cross_gate_timestep=None, a_cross_gate_timestep=None, transformer_options=None,
) -> Tuple[torch.Tensor, torch.Tensor]:
run_vx = transformer_options.get("run_vx", True)
run_ax = transformer_options.get("run_ax", True)
@@ -234,7 +233,7 @@ class BasicAVTransformerBlock(nn.Module):
vshift_msa, vscale_msa = (self.get_ada_values(self.scale_shift_table, vx.shape[0], v_timestep, slice(0, 2)))
norm_vx = comfy.ldm.common_dit.rms_norm(vx) * (1 + vscale_msa) + vshift_msa
del vshift_msa, vscale_msa
attn1_out = self.attn1(norm_vx, pe=v_pe, mask=self_attention_mask, transformer_options=transformer_options)
attn1_out = self.attn1(norm_vx, pe=v_pe, transformer_options=transformer_options)
del norm_vx
# video cross-attention
vgate_msa = self.get_ada_values(self.scale_shift_table, vx.shape[0], v_timestep, slice(2, 3))[0]
@@ -451,29 +450,6 @@ class LTXAVModel(LTXVModel):
operations=self.operations,
)
self.audio_embeddings_connector = Embeddings1DConnector(
split_rope=True,
double_precision_rope=True,
dtype=dtype,
device=device,
operations=self.operations,
)
self.video_embeddings_connector = Embeddings1DConnector(
split_rope=True,
double_precision_rope=True,
dtype=dtype,
device=device,
operations=self.operations,
)
def preprocess_text_embeds(self, context):
if context.shape[-1] == self.caption_channels * 2:
return context
out_vid = self.video_embeddings_connector(context)[0]
out_audio = self.audio_embeddings_connector(context)[0]
return torch.concat((out_vid, out_audio), dim=-1)
def _init_transformer_blocks(self, device, dtype, **kwargs):
"""Initialize transformer blocks for LTXAV."""
self.transformer_blocks = nn.ModuleList(
@@ -726,7 +702,7 @@ class LTXAVModel(LTXVModel):
return [(v_pe, av_cross_video_freq_cis), (a_pe, av_cross_audio_freq_cis)]
def _process_transformer_blocks(
self, x, context, attention_mask, timestep, pe, transformer_options={}, self_attention_mask=None, **kwargs
self, x, context, attention_mask, timestep, pe, transformer_options={}, **kwargs
):
vx = x[0]
ax = x[1]
@@ -770,7 +746,6 @@ class LTXAVModel(LTXVModel):
v_cross_gate_timestep=args["v_cross_gate_timestep"],
a_cross_gate_timestep=args["a_cross_gate_timestep"],
transformer_options=args["transformer_options"],
self_attention_mask=args.get("self_attention_mask"),
)
return out
@@ -791,7 +766,6 @@ class LTXAVModel(LTXVModel):
"v_cross_gate_timestep": av_ca_a2v_gate_noise_timestep,
"a_cross_gate_timestep": av_ca_v2a_gate_noise_timestep,
"transformer_options": transformer_options,
"self_attention_mask": self_attention_mask,
},
{"original_block": block_wrap},
)
@@ -813,7 +787,6 @@ class LTXAVModel(LTXVModel):
v_cross_gate_timestep=av_ca_a2v_gate_noise_timestep,
a_cross_gate_timestep=av_ca_v2a_gate_noise_timestep,
transformer_options=transformer_options,
self_attention_mask=self_attention_mask,
)
return [vx, ax]

View File

@@ -157,9 +157,11 @@ class Embeddings1DConnector(nn.Module):
self.num_learnable_registers = num_learnable_registers
if self.num_learnable_registers:
self.learnable_registers = nn.Parameter(
torch.empty(
torch.rand(
self.num_learnable_registers, inner_dim, dtype=dtype, device=device
)
* 2.0
- 1.0
)
def get_fractional_positions(self, indices_grid):
@@ -232,7 +234,7 @@ class Embeddings1DConnector(nn.Module):
return indices
def precompute_freqs_cis(self, indices_grid, spacing="exp", out_dtype=None):
def precompute_freqs_cis(self, indices_grid, spacing="exp"):
dim = self.inner_dim
n_elem = 2 # 2 because of cos and sin
freqs = self.precompute_freqs(indices_grid, spacing)
@@ -245,7 +247,7 @@ class Embeddings1DConnector(nn.Module):
)
else:
cos_freq, sin_freq = interleaved_freqs_cis(freqs, dim % n_elem)
return cos_freq.to(dtype=out_dtype), sin_freq.to(dtype=out_dtype), self.split_rope
return cos_freq.to(self.dtype), sin_freq.to(self.dtype), self.split_rope
def forward(
self,
@@ -286,7 +288,7 @@ class Embeddings1DConnector(nn.Module):
hidden_states.shape[1], dtype=torch.float32, device=hidden_states.device
)
indices_grid = indices_grid[None, None, :]
freqs_cis = self.precompute_freqs_cis(indices_grid, out_dtype=hidden_states.dtype)
freqs_cis = self.precompute_freqs_cis(indices_grid)
# 2. Blocks
for block_idx, block in enumerate(self.transformer_1d_blocks):

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