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Author SHA1 Message Date
Vito 78f1498ea8 Merge pull request #71 from ComfyAssets/release/1.1.2
Release 1.1.2 - ComfyUI scanner fixes
2026-10-15 04:21:22 -07:00
Vito Sansevero c65f3aad03 chore(release): 1.1.2 with .comfyignore for registry archive
- Add .comfyignore so `comfy node publish` ships only the runtime
  package: __init__.py, kikotools/, web/, examples/, README, LICENSE,
  pyproject.toml, requirements.txt
- Exclude tests/, scripts/, .github/, dev tooling configs, contributor
  docs, and the stray example.py reference file (not imported anywhere)
- Registry scanner flagged 1.1.1 on five info-level pattern matches;
  two were in tests/ and the historical Model.eval matches came from
  example.py, none of which should be in the published archive
- Bump version to 1.1.2
2026-10-15 04:16:17 -07:00
Vito 9a55c23282 Merge pull request #70 from ComfyAssets/release/1.1.1
Release 1.1.1
2026-10-13 18:36:23 -07:00
Vito Sansevero e90bde5849 chore: release 1.1.1
Gemini Prompt node migrated from the deprecated google-generativeai SDK to google-genai.
2026-10-13 18:29:24 -07:00
Vito Sansevero 49523e10de chore(gemini_prompt): migrate to google-genai SDK
- google-generativeai is deprecated and emits a FutureWarning at node
  load; google-genai is Google's supported replacement
- Image analysis now uses genai.Client().models.generate_content
  instead of the module-level configure/GenerativeModel API
- Model listing reads supported_actions, the new SDK's name for
  supported_generation_methods
- Install instructions, requirements.txt, and README updated to the
  new package name
2026-10-13 18:27:52 -07:00
Vito 8e6cf4233a Merge pull request #69 from ComfyAssets/release/1.1.0
Release 1.1.0
2026-10-13 08:12:57 -07:00
Vito Sansevero 6301cf90f8 chore: release 1.1.0
Security hardening and fixes (#64), Project File Path node (#65, #67), runtime state untracked (#66), dependency bumps (#68).
2026-10-13 08:01:04 -07:00
Vito f87eb959b3 Merge pull request #68 from ComfyAssets/chore/dependency-bumps
Apply pending Dependabot bumps (#56-#63)
2026-10-13 07:47:06 -07:00
Vito Sansevero 7783ed8a16 build(deps): apply pending Dependabot bumps
Combines #56-#63:
- torch >=2.11.0, pillow >=12.2.0, mypy >=1.20.0, pytest-mock >=3.15.1,
  pre-commit >=4.5.1 in both pyproject.toml and requirements-dev.txt
  (Dependabot only edited pyproject, but CI installs requirements-dev.txt)
- actions/checkout v7, actions/cache v6, softprops/action-gh-release v3
  across all workflows, including the new test/coverage/js jobs
2026-10-13 07:44:16 -07:00
Vito 726fcee761 Merge pull request #66 from ComfyAssets/chore/untrack-runtime-state
Stop tracking runtime state files
2026-10-13 07:42:21 -07:00
Vito 98f3defe50 Merge pull request #67 from ComfyAssets/fix/project-file-path-output-label
Project File Path: label output STRING like djz-nodes
2026-10-13 07:41:55 -07:00
Vito Sansevero 143a6c47f6 fix(project_file_path): label the output STRING like djz-nodes
Drop RETURN_NAMES so ComfyUI shows the output as STRING, matching the original Project File Path Generator. Links connect by slot index, so existing workflows are unaffected.
2026-10-13 07:38:33 -07:00
Vito Sansevero 76a52765c7 chore: stop tracking runtime state files
The image loader's config.json/selections.json (one user's saved folders
and selections) and the Gemini model cache were committed, so every
install shipped them as defaults, and running from a symlinked checkout
dirtied the tree. Untrack them and ignore them, plus gemini_config.json
which would hold an API key. All loaders already handle the files being
absent.
2026-10-13 07:37:27 -07:00
Vito f308b23631 Merge pull request #65 from ComfyAssets/feature/project-file-path
Add Project File Path node
2026-10-13 07:32:25 -07:00
Vito Sansevero d65c11c76c feat(project_file_path): add Project File Path node
Builds a save prefix like MyProject/2026-10-13/images/image for a save
node's filename_prefix, replacing djz-nodes' Project File Path Generator
with a fresh implementation:

- Same inputs, root defaults to empty (prefixes are already relative to
  the output folder, so "output" nested as output/output/...)
- Optional date folder; IS_CHANGED tracks the date instead of forcing a
  re-run on every queue
- Components are split on / and \ with '..' segments dropped, so a path
  can't climb out of the output folder
- Only real file extensions are stripped (render_v1.5 keeps its dot)
- The separator option is applied last instead of being undone by
  normpath; an empty filename raises a clear error
2026-10-13 07:27:49 -07:00
Vito 1879f42f83 Merge pull request #64 from ComfyAssets/fix/review-security-and-coverage
Security hardening, crash fixes, cross-platform CI and 95% coverage
2026-10-13 07:26:02 -07:00
Vito Sansevero c2d85d4ba3 test: compare normalized save subfolder (forward slashes on Windows) 2026-10-13 07:23:11 -07:00
Vito Sansevero 2246484b99 fix: keep console output ASCII so Windows legacy consoles can load the node
A Windows console on a legacy code page (cp1252, or cp437 in cmd)
raises UnicodeEncodeError on emoji. The startup banner printed a 🫶
prefix and display names like "Model Downloader 🌐", which aborts
loading the whole node pack. Same approach as ComfyUI_PromptManager:

- Banner prints ASCII-only display names (emoji stay in the UI names)
- Preset validation messages print "1024x1024" instead of "1024×1024"
- Explicit UTF-8 for text files (Windows defaults to cp1252)
- Regression test imports the package with a strict cp1252/cp437 stdout
2026-10-13 07:20:11 -07:00
Vito Sansevero 2a637322b9 test: fix Windows-only test failures
- Close PIL images and NamedTemporaryFile handles before deleting the
  files; Windows refuses to delete open files (WinError 32)
- Set USERPROFILE alongside HOME: expanduser ignores HOME on Windows
- Compare realpaths in the nested save-prefix test; Windows temp dirs
  use 8.3 short names (RUNNER~1)
2026-10-13 07:18:30 -07:00
Vito Sansevero 684e61638b chore: exclude gitignored referance/ from flake8 2026-10-13 07:13:50 -07:00
Vito Sansevero a0b132ef7b ci: run pytest on Linux, Windows and macOS with an 85% coverage gate
tests.yml only ran inline smoke scripts on Ubuntu, never the pytest
suite, so broken tests went unnoticed on main. Mirror ComfyUI_PromptManager:

- pytest on ubuntu/windows/macos x Python 3.10-3.13 (fail-fast off)
- separate coverage job enforcing fail_under = 85
- syntax check every web/*.js as an ES module
- CPU-only torch on Linux to avoid the ~2.5 GB CUDA wheel
2026-10-13 07:13:08 -07:00
Vito Sansevero 935e94b651 fix(web): restore custom colors on group menus and honor auto-shade
- Groups have no node-menu hook, so the menu-hook refactor dropped their
  custom color entry; add it via getCanvasMenuItems using the group under
  the mouse, as the frontend's own Comfy.GroupOptions does
- The "Auto-shade Title" setting was read but never applied
- Share one hidden color input instead of three
- Don't mark the canvas dirty while merely building the node menu
2026-10-13 07:07:34 -07:00
Vito Sansevero 7513479419 refactor(web): use extension menu hooks instead of patching LiteGraph
Replace monkey-patches of LGraphCanvas.onMenuNodeColors and the
canvas/node menu getters (applied after a 500ms timeout, and scraping
.litecontextmenu DOM for "No color") with the frontend's
getNodeMenuItems/getCanvasMenuItems extension hooks. Custom colors move
into a "Custom Colors" submenu; follow-execution state moves to module
scope so repeated setup() calls no longer stack wrappers.
2026-10-13 06:57:41 -07:00
Vito Sansevero 865dde6cdf feat(web): offer "Add folder & open" when browsing an unsaved folder
The backend now 403s folders outside the saved paths. Show the full path
and add it only on an explicit click; server-side refusals (e.g. a
too-broad folder) are shown in the status line.
2026-10-13 06:56:49 -07:00
Vito Sansevero 30fc6aa7a7 fix(local_image_loader): refuse filesystem roots and home as saved paths
save_paths is reachable without auth, so saving "/" made every media
file on the machine servable. Reject filesystem/drive roots, the home
directory and its ancestors (realpath-resolved, so symlinks count), and
ignore such entries already in config.json.
2026-10-13 06:56:49 -07:00
Vito Sansevero a055543d16 fix(model_downloader): never write into custom_nodes or save code files
ComfyUI registers custom_nodes in folder_names_and_paths, so treating
every registered folder as a download root let a queued prompt drop a
.py file there that runs on the next restart.

- Skip custom_nodes when collecting allowed roots
- save_response only writes model/data extensions (.safetensors, .gguf,
  .ckpt, .pth, .json, ...), so any future code-holding folder is still
  protected
2026-10-13 06:41:13 -07:00
Vito Sansevero 78fd20d89a fix(local_image_loader): load the resolved path that was validated 2026-10-13 06:38:23 -07:00
Vito Sansevero 4b66592715 test: cover gemini, embedding autocomplete, batch prompts, presets and plot nodes 2026-10-13 06:38:20 -07:00
Vito Sansevero dc3fcf65e2 fix: save path escape, global RNG reseed and small node bugs
- KikoSaveImage: reject absolute or '..' filename_prefix directories that
  resolved outside the output folder
- Film grain: use a local torch.Generator instead of reseeding the global
  RNG; strength 0 no longer skips the toe adjustment
- Purge VRAM: IS_CHANGED returns NaN so caching never skips the purge
- Resolution calculator: clamp outputs to >= 8
- Plot sampler params: font size floor of 1 for images under 32px wide
- Gemini prompt: drop Image.fromarray mode= argument (removed in Pillow)
2026-10-13 06:38:20 -07:00
Vito Sansevero 8196e65906 chore: remove dead modules and consolidate test config
- Delete kikotools/core (registry/settings) and batch_prompts/node_simple
  which nothing imports
- pytest.ini used the [tool:pytest] header and was ignored; make it the
  single pytest config (drop the pyproject duplicate), keep
  --strict-markers
- Add pytest-asyncio to dev deps; enforce 85% coverage via
  [tool.coverage.report] fail_under
2026-10-13 06:38:20 -07:00
Vito Sansevero c8de8f26d6 fix(model_downloader): confine downloads to model dirs and harden fetches
- Reject filenames with path components; reduce server-derived names
  (Content-Disposition, CivitAI redirect, URL) to a safe basename
- save_path must resolve inside models_dir or a registered model folder
  (including extra_model_paths.yaml roots); relative paths resolve
  against ComfyUI's base path
- Only http/https for user URLs and redirects; drop the Authorization
  header on cross-host redirects
- Stream to <file>.part and rename on success, removing the partial file
  on any failure, so a dropped connection no longer leaves a truncated
  model that later runs treat as complete
- 60s timeout on every request; shared streaming loop in BaseDownloader
- Custom downloader honours Content-Disposition before the default name
2026-10-13 06:38:20 -07:00
Vito Sansevero 10027fcef9 fix(local_image_loader): confine file routes to saved roots and media types
/view served any readable file (e.g. ~/.ssh/id_rsa) to anyone who could
reach the server; the only guard was a '..' substring check.

- Resolve paths with realpath and require commonpath containment in the
  saved paths or ComfyUI input/output directories
- /view serves image/video/audio only, /thumbnail and load_media images
  only; the extension check applies to the resolved path, so symlinks
  can't smuggle other files
- /images 403s outside the roots; page/per_page validated and clamped
- /list_directories (folder picker) returns directory names only
- load_media refuses disallowed paths from a tampered selections.json
- Route handlers moved to module level so they are unit tested
- Update stale tests to the (image, info) return contract
2026-10-13 06:34:13 -07:00
Vito Sansevero 60ce078aed fix(xyz_helpers): raise on invalid sampler/LoRA input instead of hanging
- LoRA strength strings: step <= 0 looped forever and reversed ranges
  returned [] (ZeroDivisionError later); now raise ValueError, and cap
  generated values at 1000
- Flux sampler params: unparseable steps/guidance/shift/denoise/seed
  tokens raise with the field name instead of being dropped, and an
  empty LoRA folder raises instead of returning (None, [])
- Detect Flux schnell via unet_config guidance_embed (the ModelType.FLOW
  check never matched Flux)
- IS_CHANGED: re-run Flux params when a seed is '?'; LoRA folder batch
  hashes file list + mtimes instead of always re-executing
- LoRA folder scan uses commonpath containment across all lora roots
- Prompt separators must be whole lines; failed encodes raise
2026-10-13 06:33:17 -07:00
Vito Sansevero 37c00b633c fix(web): escape server data in innerHTML and plug listener leaks
- Escape file names, paths and image metadata interpolated into
  innerHTML in the local image loader and save image viewer (XSS via
  crafted file names or a shared workflow's filename_prefix)
- Save image viewer: bind document drag listeners once and remove them
  in disconnectedCallback instead of adding two per run; drop debug
  logging and the window.kikoSaveImageTest helper
- Local image loader: check response.ok and surface 400/403 errors,
  disconnect the ResizeObserver on node removal
- Gemini prompt: restore the user's node color after the run flash
- Workflow timer: chain onRemoved, merge properties in onConfigure
- Seed history: build entries with textContent
2026-10-13 06:32:14 -07:00
Vito c7f24a3262 Merge pull request #55 from ComfyAssets/feature/batch-list-converter
feat: add batch/list conversion nodes for IMAGE and LATENT
2026-02-09 17:46:52 -08:00
Vito Sansevero c69281e795 fix(batch_list_converter): preserve all latent dict keys during split/join
Previously split_latent_batch and join_latent_batch only handled the
"samples" key, silently dropping metadata like noise_mask or batch_index.
This broke inpaint and masked workflows after a round-trip conversion.
2026-02-09 17:11:01 -08:00
Vito Sansevero 3bf8391e88 feat(batch_list_converter): add batch/list conversion nodes for IMAGE and LATENT
Add 4 utility nodes for converting between batched tensors and lists,
eliminating the dependency on Impact Pack for this common operation:
- ImageBatchToImageList (OUTPUT_IS_LIST)
- ImageListToImageBatch (INPUT_IS_LIST)
- LatentBatchToLatentList (OUTPUT_IS_LIST)
- LatentListToLatentBatch (INPUT_IS_LIST)
2026-02-09 16:39:28 -08:00
Vito d13bfe8fb4 Merge pull request #53 from ComfyAssets/feature/seed-range-and-latent-output
fix: 32-bit seed range, latent batch_size output
2026-02-09 16:32:17 -08:00
Vito Sansevero 702d0c889c fix(seed_history): accept legacy kwargs for backward compatibility
Old workflows may still pass 'mode' to output_seed. Using **kwargs
prevents TypeError when ComfyUI invokes with the extra argument.
2026-02-09 16:29:11 -08:00
Vito Sansevero d1a5282ca0 style: fix Black formatting issues
Remove extra blank line in local_image_loader/node.py and wrap long
tuple assertion in test_empty_latent_batch.py.
2026-02-09 16:26:08 -08:00
Vito Sansevero 36212adf73 ci: reduce test matrix to Python 3.11, 3.12, 3.13
Drop 3.8, 3.9, and 3.10 which are no longer needed.
2026-02-09 16:25:30 -08:00
Vito Sansevero 2cb2262293 chore(local_image_loader): update saved paths and selections 2026-02-09 16:22:10 -08:00
Vito Sansevero 8773c8f249 feat(latent): add batch_size as 4th output from EmptyLatentBatchNode
Exposes batch_size as an output so downstream nodes can reference it
directly without needing a separate input.
2026-02-09 16:22:03 -08:00
Vito Sansevero 0a1cbe4990 fix(seeds): reduce seed range from 64-bit to 32-bit across all nodes
JS Math.random() only has 53 bits of integer precision, making the
64-bit range produce non-uniform values. 32-bit (0xFFFFFFFF) is the
standard ComfyUI seed range and works correctly in both Python and JS.

Also removes the redundant mode input from SeedHistoryNode, relying on
ComfyUI's built-in control_after_generate widget instead.
2026-02-09 16:21:56 -08:00
Vito c4a27137e7 Merge pull request #52 from ComfyAssets/feature/height-width-2-vec
Feature/height width 2 vec
2025-12-21 06:49:05 -08:00
Vito Sansevero 20270d9501 test: Add unit tests for KikoWorkflowTimerNode 2025-12-21 06:45:35 -08:00
Vito Sansevero 2467dff704 feat(timer): add real-time workflow execution timer 2025-12-21 06:45:24 -08:00
Vito Sansevero cecd1e01e9 feat(timer): add Sketch-style color picker widget 2025-12-21 06:45:10 -08:00
Vito Sansevero e504f314aa chore: bump version to 1.0.28 in pyproject.toml 2025-12-21 06:45:00 -08:00
Vito Sansevero f12debe729 chore: update image paths in selections.json 2025-12-21 06:44:49 -08:00
Vito Sansevero c64e835d2e chore(local_image_loader): update config paths 2025-12-21 06:44:38 -08:00
Vito Sansevero 36d37db8a9 feat(init): add KikoWorkflowTimerNode to mappings 2025-12-21 06:44:24 -08:00
Vito Sansevero 969fd9e25e docs: Add Workflow Timer section to README.md 2025-12-21 06:44:14 -08:00
Vito Sansevero 6916b47a89 chore: bump version to 1.0.27 in pyproject.toml 2025-12-17 07:15:01 -08:00
Vito 8457db0041 Merge pull request #50 from ComfyAssets/dependabot/github_actions/actions/checkout-6
build(deps): bump actions/checkout from 5 to 6
2025-12-17 07:07:19 -08:00
Vito 8a84927adf Merge pull request #51 from ComfyAssets/dependabot/github_actions/actions/cache-5
build(deps): bump actions/cache from 4 to 5
2025-12-17 07:06:54 -08:00
Vito Sansevero 8c0b89ff70 style(node): Reformat code for readability 2025-12-17 07:06:16 -08:00
Vito Sansevero b527635254 test: update return types in test_assertion 2025-12-17 07:02:08 -08:00
Vito Sansevero 14738b80c5 feat(image_loader): add directory listing API endpoint 2025-12-17 07:01:55 -08:00
Vito Sansevero bff1276d06 style: Add newline at EOF in JSON file 2025-12-17 07:01:46 -08:00
Vito Sansevero a7805ad587 feat: add WidthHeightToVec2Node to mappings 2025-12-17 07:01:34 -08:00
Vito Sansevero f2093d6567 style(docs): Ensure newline at EOF in markdown files 2025-12-17 07:01:22 -08:00
Vito Sansevero 0e26f0ad36 style: Remove trailing spaces in config files 2025-12-17 07:00:53 -08:00
Vito Sansevero 9a05f20790 style: Remove unnecessary whitespace for consistency 2025-12-17 07:00:31 -08:00
Vito Sansevero 6368582e1b feat: Add WidthHeightToVec2Node with tests 2025-12-17 06:59:11 -08:00
dependabot[bot] 97ea5b9a7d build(deps): bump actions/cache from 4 to 5
Bumps [actions/cache](https://github.com/actions/cache) from 4 to 5.
- [Release notes](https://github.com/actions/cache/releases)
- [Changelog](https://github.com/actions/cache/blob/main/RELEASES.md)
- [Commits](https://github.com/actions/cache/compare/v4...v5)

---
updated-dependencies:
- dependency-name: actions/cache
  dependency-version: '5'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
2025-12-15 16:28:14 +00:00
dependabot[bot] f5f956ab4e build(deps): bump actions/checkout from 5 to 6
Bumps [actions/checkout](https://github.com/actions/checkout) from 5 to 6.
- [Release notes](https://github.com/actions/checkout/releases)
- [Changelog](https://github.com/actions/checkout/blob/main/CHANGELOG.md)
- [Commits](https://github.com/actions/checkout/compare/v5...v6)

---
updated-dependencies:
- dependency-name: actions/checkout
  dependency-version: '6'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
2025-11-24 16:55:51 +00:00
Vito Sansevero 498fae1211 feat(image_loader): add search_files function 2025-11-14 13:05:52 -08:00
Vito Sansevero d24912036c chore(local_image_loader): update last_path in config.json 2025-11-14 13:05:52 -08:00
Vito 523b0509f1 Update pyproject.toml 2025-11-12 08:23:11 -08:00
Vito 5f8117aa56 Merge pull request #49 from wzgrx/patch-1
Update requirements.txt
2025-11-12 08:22:31 -08:00
wzgrx 22dc975353 Update requirements.txt 2025-10-25 22:05:14 +08:00
Vito Sansevero 66afb2b204 chore: bump version to 1.0.25 in pyproject.toml 2025-10-18 13:09:46 -07:00
Vito 1dd1dcf895 Merge pull request #48 from ComfyAssets/feature/downloader
Feature/downloader
2025-10-18 13:08:00 -07:00
Vito Sansevero 60f30b068e docs: add Model Downloader to README.md 2025-10-18 12:59:40 -07:00
Vito Sansevero 1439270fe5 refactor: Reorder pendingFetches initialization 2025-10-18 12:59:32 -07:00
Vito Sansevero f8210d8f69 feat(presets): Add new SDXL portrait and landscape presets 2025-10-18 12:46:31 -07:00
Vito Sansevero aceb34b9b0 feat(seed_history): add seed mode handling and validation 2025-10-18 12:46:19 -07:00
Vito Sansevero e9ce1fd2cf feat(model_downloader): handle download interruption 2025-10-18 12:45:46 -07:00
Vito Sansevero 9b888443ac feat(model_downloader): add interrupt handling 2025-10-18 12:45:37 -07:00
Vito Sansevero f4743df3ef feat(model_downloader): add cancel download support 2025-10-18 12:45:27 -07:00
Vito Sansevero 6a68983ef4 feat(model_downloader): Add interrupt check support 2025-10-18 12:45:09 -07:00
Vito Sansevero fb01fa24ae chore: update selections.json with new images 2025-10-18 12:44:43 -07:00
Vito Sansevero 65f68f59a1 chore: update last_path in config.json 2025-10-18 12:44:12 -07:00
Vito c3fab5581b Merge pull request #47 from ComfyAssets/bugs/fix-save-and-sampler
Bugs/fix save and sampler
2025-10-07 07:34:30 -07:00
Vito Sansevero 1ea2b4cc90 fix(ci): update Sampler Combo test to match SAMPLERS list return type 2025-10-07 07:28:19 -07:00
Vito Sansevero f33f39f134 chore: update .gitignore with .serena entry 2025-10-07 07:22:01 -07:00
Vito Sansevero 5b57d4fc35 test: Add tests for image counter functionality 2025-10-07 07:21:09 -07:00
Vito Sansevero a1625dddad refactor(node): simplify sampler return logic 2025-10-07 07:20:58 -07:00
Vito Sansevero a88232f59a refactor(compact_node): simplify sampler return logic 2025-10-07 07:20:47 -07:00
Vito Sansevero 6746b86685 feat(kiko_save_image): add persistent counter for filenames 2025-10-07 07:20:35 -07:00
Vito Sansevero 17af18d397 chore: bump version to 1.0.24 in pyproject.toml 2025-10-05 07:42:43 -07:00
Vito 703989599d Merge pull request #46 from ComfyAssets/alert-autofix-14
Potential fix for code scanning alert no. 14: Use of a broken or weak cryptographic hashing algorithm on sensitive data
2025-10-05 07:42:14 -07:00
Vito Sansevero 8399fad96b fix: prevent URL substring sanitization bypass attacks
Fixed incomplete URL substring sanitization vulnerability (CodeQL alert)
by implementing proper domain validation using urlparse().netloc instead
of substring checking with 'in url'.

Changes:
- civitai.py: Added explicit domain validation before processing URLs
  - Only allow exact matches: 'civitai.com' and 'www.civitai.com'
  - Reject URLs like 'evil.com/civitai.com' or 'civitai.com.evil.com'

- detector.py: Improved URL detection methods
  - _is_civitai_url: Changed from 'in parsed.netloc' to exact match
  - _is_huggingface_url: Added allowlist of valid HF domains
    - Supports: huggingface.co, www.huggingface.co, cdn.huggingface.co,
      cdn-lfs.huggingface.co

Security Impact:
Prevents subdomain attacks and URL smuggling where malicious URLs could
bypass validation by including legitimate domain names as substrings:
- https://evil.com/civitai.com/malicious
- https://civitai.com.evil.com/models/123
- https://subdomain.civitai.com/attack

All security tests pass with 100% malicious URL rejection rate.
2025-10-05 07:32:18 -07:00
Vito Sansevero 0c69abc829 fix: improve regex pattern to detect script tag bypass attempts
Improved the HTML filtering regex to properly detect all variations of
script tags including bypass attempts with whitespace before the closing
bracket (e.g., '<script >' and '</script >').

Changed from word boundary pattern /<script\b/gi to a more comprehensive
pattern /<\s*\/?script[^>]*>/gi that matches:
- Optional whitespace after opening bracket
- Optional forward slash for closing tags
- Any characters until closing bracket (catches attributes and whitespace)

This fixes the CodeQL security alert for bad HTML filtering regexp that
could be bypassed with malformed tags.

Also updated iframe, embed, and object tag patterns for consistency.
2025-10-05 07:29:41 -07:00
Vito Sansevero e00406747f security: exclude api_token from IS_CHANGED hash to fix CodeQL warning
The api_token is sensitive data and shouldn't be included in the SHA256
hash. The hash is only used for ComfyUI cache invalidation, where the
URL change is sufficient to trigger re-execution. Including the token
was unnecessary and triggered a security warning.

This fixes the CodeQL alert: py/weak-sensitive-data-hashing
2025-10-05 07:24:46 -07:00
VitoandCopilot Autofix powered by AI a21e677629 Potential fix for code scanning alert no. 14: Use of a broken or weak cryptographic hashing algorithm on sensitive data
Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>
2025-10-05 07:18:17 -07:00
Vito 13e425959b Merge pull request #45 from ComfyAssets/fix/nodes-latent-v3-schema
fix: replace LatentBatch import with local implementation for V3 sche…
2025-10-05 06:14:12 -07:00
Vito Sansevero 0a6ee72748 fix: replace LatentBatch import with local implementation for V3 schema compatibility
Refs #43

ComfyUI is converting nodes_latent.py to V3 Schema on October 8th, which will
break direct imports of LatentBatch. This commit replaces the import with a
local implementation copied directly from ComfyUI source code.

Changes:
- Removed: from comfy_extras.nodes_latent import LatentBatch
- Added: Local batch_latents() and reshape_latent_to() functions
- Updated: latentbatch.batch() calls to use batch_latents()
- Added: torch and comfy.utils imports for tensor operations
- Added: Comprehensive unit tests for latent batching functionality

The local implementation is functionally identical to the original and ensures
the node will continue working after the V3 schema migration.

Test Coverage:
- 5 new tests in TestLatentBatchingFunctions class
- All 16 tests passing (11 existing + 5 new)
- Tests cover tensor operations, batch indexing, and reshape logic
2025-10-05 06:08:21 -07:00
Vito b03f0ecf22 Merge pull request #44 from ComfyAssets/feature/download-assets
Feature/download assets
2025-10-05 06:00:35 -07:00
Vito Sansevero ed81bf4cfd ci: add file check for model_downloader and text_input 2025-10-05 05:40:12 -07:00
Vito Sansevero 58a6c05d98 ci: add tests for ModelDownloader and TextInput nodes 2025-10-05 05:40:04 -07:00
Vito Sansevero 51bb7711b8 feat(init): add ModelDownloader and TextInput nodes 2025-10-05 05:39:35 -07:00
Vito Sansevero 8f459c502a feat(model_downloader): add model downloaders tool 2025-10-05 05:39:21 -07:00
Vito Sansevero af1bc6845a feat(text_input): add text input tool for ComfyUI 2025-10-05 05:39:09 -07:00
Vito Sansevero 27431b3a92 test(model_downloader): add unit tests for model downloader 2025-10-05 05:39:00 -07:00
Vito Sansevero 67ef0a44d7 test(text_input): add unit tests for TextInputNode 2025-10-05 05:38:47 -07:00
Vito a501260bbf Merge pull request #42 from ComfyAssets/fix/swap
Fix/swap
2025-09-24 14:52:28 -07:00
Vito Sansevero 3a4651b191 chore: bump version to 1.0.23 in pyproject.toml 2025-09-24 14:32:58 -07:00
Vito Sansevero 2f3d6d62f3 refactor(js): update callback params with app.canvas 2025-09-24 14:32:45 -07:00
Vito fb805c4a3d Merge pull request #41 from ComfyAssets/fix/leaks
Fix/leaks
2025-09-23 07:58:03 -07:00
Vito Sansevero 4e84588a94 style(tests): improve code formatting consistency 2025-09-23 07:39:27 -07:00
Vito Sansevero df7776280e chore: bump version to 1.0.22 in pyproject.toml 2025-09-23 07:24:22 -07:00
Vito Sansevero 8fd92530ee test: Add tests for embedding autocomplete features 2025-09-23 07:23:41 -07:00
Vito Sansevero 081f5f2310 refactor(autocomplete): enhance widget handling logic 2025-09-23 07:23:27 -07:00
Vito Sansevero ad7e6e647f feat(web): add Qwen presets for image dimensions 2025-09-23 07:23:11 -07:00
Vito Sansevero 04218704b3 feat(presets): add Qwen presets and categories 2025-09-23 07:22:53 -07:00
Vito a4db4390ea Merge pull request #40 from ComfyAssets/dependabot/github_actions/actions/setup-python-6
build(deps): bump actions/setup-python from 5 to 6
2025-09-18 17:16:19 -07:00
dependabot[bot] c38753758b build(deps): bump actions/setup-python from 5 to 6
Bumps [actions/setup-python](https://github.com/actions/setup-python) from 5 to 6.
- [Release notes](https://github.com/actions/setup-python/releases)
- [Commits](https://github.com/actions/setup-python/compare/v5...v6)

---
updated-dependencies:
- dependency-name: actions/setup-python
  dependency-version: '6'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
2025-09-08 16:33:10 +00:00
Vito Sansevero 17b97ed17a chore: bump version to 1.0.21 in pyproject.toml 2025-08-27 09:50:10 -07:00
Vito bd15b45f46 Merge pull request #39 from ComfyAssets/feat/local_image
style(core): remove unused imports and adjust formatting
2025-08-27 09:49:37 -07:00
Vito Sansevero 5f6846c3cb style(core): remove unused imports and adjust formatting 2025-08-27 09:44:16 -07:00
Vito 363cc9c755 Merge pull request #38 from ComfyAssets/feat/local_image
Feat/local image
2025-08-27 09:33:28 -07:00
Vito Sansevero 5ae7985bc2 test(batch_prompts): add unit tests for batch prompts 2025-08-27 09:32:09 -07:00
Vito Sansevero b37bc763dc feat: Add local image loader with lightbox support 2025-08-27 09:31:45 -07:00
Vito Sansevero 0439763614 feat(extensions): Add KikoTools utility features 2025-08-27 09:31:30 -07:00
Vito Sansevero 2e1f563298 feat(local_image_loader): add local image loader tool 2025-08-27 09:31:07 -07:00
Vito Sansevero 4b63cb7176 feat(batch_prompts): add batch prompt processing node 2025-08-27 09:30:43 -07:00
Vito Sansevero 1f6a148538 docs(examples): add batch and local loader docs 2025-08-27 09:29:57 -07:00
Vito Sansevero d9a7879c45 fix: ensure valid color format in custom colors 2025-08-27 09:29:14 -07:00
Vito Sansevero c6b5dc4b54 feat(init): add BatchPrompts and LocalImageLoader nodes 2025-08-27 09:29:02 -07:00
Vito Sansevero a4d1169c63 docs: Add Local Image Loader section to README.md 2025-08-27 09:28:52 -07:00
Vito Sansevero ff6f397dd2 chore: bump version to 1.0.20 in pyproject.toml 2025-08-19 11:54:47 -07:00
Vito 97913deae3 Merge pull request #37 from ComfyAssets/bugfix/empty-latent-batch-swap-button
fix: convert Empty Latent Batch swap button from canvas to DOM widget
2025-08-19 11:53:59 -07:00
145 changed files with 14326 additions and 2930 deletions
+23
View File
@@ -0,0 +1,23 @@
# Files excluded from the Comfy Registry archive (gitignore syntax).
# Everything here is development-only; the published node needs
# __init__.py, kikotools/, web/, examples/, README, LICENSE, pyproject.toml.
# Test suite and tooling
tests/
scripts/
.github/
Makefile
pytest.ini
mypy.ini
.flake8
.pre-commit-config.yaml
.secrets.baseline
requirements-dev.txt
# Reference / scratch code not imported by the node
example.py
# Agent and contributor docs
CLAUDE.md
CONTRIBUTING.md
CODE_OF_CONDUCT.md
+5 -4
View File
@@ -1,7 +1,7 @@
[flake8]
max-line-length = 127
max-complexity = 10
exclude =
exclude =
.git,
__pycache__,
.mypy_cache,
@@ -11,8 +11,9 @@ exclude =
build,
dist,
*.egg-info,
.tox
ignore =
.tox,
referance
ignore =
# W503: line break before binary operator (conflicts with Black)
W503,
# E203: whitespace before ':' (conflicts with Black)
@@ -32,4 +33,4 @@ per-file-ignores =
# Statistics
count = True
statistics = True
statistics = True
+1 -1
View File
@@ -38,4 +38,4 @@
*.safetensors binary
*.ckpt binary
*.pt binary
*.pth binary
*.pth binary
+1 -1
View File
@@ -7,4 +7,4 @@ updates:
- package-ecosystem: "github-actions"
directory: "/"
schedule:
interval: "weekly"
interval: "weekly"
+50 -7
View File
@@ -13,15 +13,15 @@ jobs:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v5
- uses: actions/checkout@v7
- name: Set up Python 3.10
uses: actions/setup-python@v5
uses: actions/setup-python@v6
with:
python-version: '3.10'
- name: Cache pip dependencies
uses: actions/cache@v4
uses: actions/cache@v6
with:
path: ~/.cache/pip
key: ${{ runner.os }}-pip-quality-${{ hashFiles('**/requirements-dev.txt') }}
@@ -93,6 +93,14 @@ jobs:
from kikotools.tools.kiko_save_image import KikoSaveImageNode
from kikotools.tools.kiko_save_image.logic import process_image_batch, validate_save_inputs
# Test Model Downloader imports
from kikotools.tools.model_downloader import ModelDownloaderNode
from kikotools.tools.model_downloader.detector import URLDetector, DownloaderType
from kikotools.tools.model_downloader.base import BaseDownloader
# Test Text Input imports
from kikotools.tools.text_input import TextInputNode
print('✓ All module imports successful')
"
@@ -133,10 +141,10 @@ jobs:
security:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v5
- uses: actions/checkout@v7
- name: Set up Python 3.10
uses: actions/setup-python@v5
uses: actions/setup-python@v6
with:
python-version: '3.10'
@@ -164,10 +172,10 @@ jobs:
architecture:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v5
- uses: actions/checkout@v7
- name: Set up Python 3.10
uses: actions/setup-python@v5
uses: actions/setup-python@v6
with:
python-version: '3.10'
@@ -279,6 +287,41 @@ jobs:
print('❌ KikoSaveImageNode missing OUTPUT_NODE = True')
sys.exit(1)
# Test Model Downloader Node
from kikotools.tools.model_downloader.node import ModelDownloaderNode
if issubclass(ModelDownloaderNode, ComfyAssetsBaseNode):
print('✓ ModelDownloaderNode properly inherits from base class')
else:
print('❌ ModelDownloaderNode does not inherit from base class')
sys.exit(1)
# ModelDownloader is an output node, so it doesn't have RETURN_TYPES/RETURN_NAMES
download_required_attrs = ['INPUT_TYPES', 'FUNCTION', 'CATEGORY']
for attr in download_required_attrs:
if not hasattr(ModelDownloaderNode, attr):
print(f'❌ ModelDownloaderNode missing required attribute: {attr}')
sys.exit(1)
# Check that it's properly marked as an output node
if not hasattr(ModelDownloaderNode, 'OUTPUT_NODE') or not ModelDownloaderNode.OUTPUT_NODE:
print('❌ ModelDownloaderNode missing OUTPUT_NODE = True')
sys.exit(1)
# Test Text Input Node
from kikotools.tools.text_input.node import TextInputNode
if issubclass(TextInputNode, ComfyAssetsBaseNode):
print('✓ TextInputNode properly inherits from base class')
else:
print('❌ TextInputNode does not inherit from base class')
sys.exit(1)
for attr in required_attrs:
if not hasattr(TextInputNode, attr):
print(f'❌ TextInputNode missing required attribute: {attr}')
sys.exit(1)
print('✓ All architecture checks passed for all tools')
"
+1 -1
View File
@@ -18,7 +18,7 @@ jobs:
if: ${{ github.repository_owner == 'ComfyAssets' }}
steps:
- name: Check out code
uses: actions/checkout@v5
uses: actions/checkout@v7
with:
submodules: true
- name: Publish Custom Node
+3 -3
View File
@@ -15,10 +15,10 @@ jobs:
contents: write
steps:
- uses: actions/checkout@v5
- uses: actions/checkout@v7
- name: Set up Python 3.10
uses: actions/setup-python@v5
uses: actions/setup-python@v6
with:
python-version: '3.10'
@@ -114,7 +114,7 @@ jobs:
EOF
- name: Create GitHub Release
uses: softprops/action-gh-release@v2
uses: softprops/action-gh-release@v3
with:
tag_name: ${{ steps.get_version.outputs.version }}
name: ComfyUI-KikoTools ${{ steps.get_version.outputs.version }}
+41 -441
View File
@@ -11,471 +11,71 @@ on:
jobs:
test:
runs-on: ubuntu-latest
name: py${{ matrix.python-version }} on ${{ matrix.os }}
runs-on: ${{ matrix.os }}
strategy:
fail-fast: false
matrix:
python-version: [3.8, 3.9, "3.10", "3.11", "3.12"]
os: [ubuntu-latest, windows-latest, macos-latest]
python-version: ["3.10", "3.11", "3.12", "3.13"]
steps:
- uses: actions/checkout@v5
- uses: actions/checkout@v7
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
uses: actions/setup-python@v6
with:
python-version: ${{ matrix.python-version }}
cache: pip
cache-dependency-path: requirements-dev.txt
- name: Cache pip dependencies
uses: actions/cache@v4
with:
path: ~/.cache/pip
key: ${{ runner.os }}-pip-${{ hashFiles('**/requirements-dev.txt') }}
restore-keys: |
${{ runner.os }}-pip-
# The default Linux torch wheel bundles CUDA (~2.5 GB); tests only need CPU.
# Windows and macOS default wheels are already CPU-only.
- name: Install CPU torch (Linux)
if: runner.os == 'Linux'
run: |
python -m pip install --upgrade pip
pip install torch --index-url https://download.pytorch.org/whl/cpu
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install -r requirements-dev.txt
pip install -r requirements-dev.txt aiohttp
- name: Run core functionality tests
run: |
python -c "
import sys
import os
sys.path.insert(0, os.getcwd())
- name: Run tests
run: python -m pytest tests
# Test imports
from kikotools.base import ComfyAssetsBaseNode
from kikotools.tools.resolution_calculator.logic import extract_dimensions, calculate_scaled_dimensions
from kikotools.tools.resolution_calculator.node import ResolutionCalculatorNode
import torch
print('✓ All imports successful')
# Test base node
assert 'ComfyAssets' in ComfyAssetsBaseNode.CATEGORY
print('✓ Base node tests passed')
# Test dimension extraction
mock_image = torch.randn(1, 1216, 832, 3)
width, height = extract_dimensions(image=mock_image)
assert width == 832 and height == 1216
print('✓ Dimension extraction tests passed')
# Test scaling
new_width, new_height = calculate_scaled_dimensions(832, 1216, 1.5)
assert new_width % 8 == 0 and new_height % 8 == 0
print('✓ Scaling tests passed')
# Test node interface
node = ResolutionCalculatorNode()
result_width, result_height = node.calculate_resolution(1.5, image=mock_image)
assert isinstance(result_width, int) and isinstance(result_height, int)
assert result_width % 8 == 0 and result_height % 8 == 0
print('✓ Node interface tests passed')
# Test user scenario
width, height = node.calculate_resolution(1.53, image=mock_image)
print(f'✓ User scenario test: 832×1216 → {width}×{height} (1.53x scale)')
print('🎉 All tests passed!')
"
- name: Test Width Height Selector
run: |
python -c "
import sys
import os
sys.path.insert(0, os.getcwd())
# Test Width Height Selector imports
from kikotools.tools.width_height_selector.node import WidthHeightSelectorNode
from kikotools.tools.width_height_selector.presets import PRESET_OPTIONS, PRESET_METADATA
from kikotools.tools.width_height_selector.logic import get_preset_dimensions
print('✓ Width Height Selector imports successful')
# Test preset structure
assert len(PRESET_OPTIONS) > 0
assert 'custom' in PRESET_OPTIONS
assert len(PRESET_METADATA) > 0
print('✓ Preset structure tests passed')
# Test node interface
node = WidthHeightSelectorNode()
input_types = node.INPUT_TYPES()
assert 'required' in input_types
assert 'preset' in input_types['required']
assert 'width' in input_types['required']
assert 'height' in input_types['required']
print('✓ Node interface tests passed')
# Test formatted presets
preset_options = input_types['required']['preset'][0]
assert 'custom' in preset_options
formatted_count = len([opt for opt in preset_options if ' - ' in opt and 'MP' in opt])
assert formatted_count > 0
print(f'✓ Found {formatted_count} formatted presets')
# Test dimension calculation
result = node.get_dimensions('1024×1024', 512, 512)
assert result == (1024, 1024)
print('✓ Dimension calculation tests passed')
# Test formatted preset dimensions
formatted_preset = '1024×1024 - 1:1 (1.1MP) - SDXL'
result = node.get_dimensions(formatted_preset, 512, 512)
assert result == (1024, 1024)
print('✓ Formatted preset tests passed')
# Test preset extraction
extracted = node._extract_preset_name(formatted_preset)
assert extracted == '1024×1024'
print('✓ Preset extraction tests passed')
print('🎉 All Width Height Selector tests passed!')
"
- name: Test Sampler Combo
run: |
python -c "
import sys
import os
sys.path.insert(0, os.getcwd())
# Test Sampler Combo imports
from kikotools.tools.sampler_combo.node import SamplerComboNode
from kikotools.tools.sampler_combo.logic import (
get_sampler_combo, validate_sampler_settings, SAMPLERS, SCHEDULERS
)
print('✓ Sampler Combo imports successful')
# Test node interface
node = SamplerComboNode()
input_types = node.INPUT_TYPES()
assert 'required' in input_types
assert 'sampler_name' in input_types['required']
assert 'scheduler' in input_types['required']
assert 'steps' in input_types['required']
assert 'cfg' in input_types['required']
print('✓ Sampler Combo interface tests passed')
# Test return types
# RETURN_TYPES[1] is the actual SCHEDULERS list
assert node.RETURN_TYPES[0] == 'SAMPLER'
assert isinstance(node.RETURN_TYPES[1], list) # SCHEDULERS is a list
assert node.RETURN_TYPES[2] == 'INT'
assert node.RETURN_TYPES[3] == 'FLOAT'
assert node.RETURN_NAMES == ('sampler_name', 'scheduler', 'steps', 'cfg')
assert node.CATEGORY == '🫶 ComfyAssets/🌀 Samplers'
print('✓ Sampler Combo return types tests passed')
# Test sampler combo functionality
result = node.get_sampler_combo('euler', 'normal', 20, 7.0)
assert result == ('euler', 'normal', 20, 7.0)
print('✓ Sampler combo functionality tests passed')
# Test validation
assert validate_sampler_settings('euler', 'normal', 20, 7.0) == True
print('✓ Sampler validation tests passed')
# Test available samplers and schedulers
samplers = node.get_available_samplers()
schedulers = node.get_available_schedulers()
assert len(samplers) > 0
assert len(schedulers) > 0
assert 'euler' in samplers
assert 'normal' in schedulers
print(f'✓ Found {len(samplers)} samplers and {len(schedulers)} schedulers')
print('🎉 All Sampler Combo tests passed!')
"
- name: Test Seed History
run: |
python -c "
import sys
import os
sys.path.insert(0, os.getcwd())
# Test Seed History imports
from kikotools.tools.seed_history.node import SeedHistoryNode
from kikotools.tools.seed_history.logic import (
generate_random_seed, validate_seed_value, sanitize_seed_value
)
print('✓ Seed History imports successful')
# Test node interface
node = SeedHistoryNode()
input_types = node.INPUT_TYPES()
assert 'required' in input_types
assert 'seed' in input_types['required']
print('✓ Seed History interface tests passed')
# Test return types
assert node.RETURN_TYPES == ('INT',)
assert node.RETURN_NAMES == ('seed',)
assert node.CATEGORY == '🫶 ComfyAssets/🌱 Seeds'
print('✓ Seed History return types tests passed')
# Test seed output functionality
result = node.output_seed(12345)
assert result == (12345,)
print('✓ Seed output functionality tests passed')
# Test seed validation
assert validate_seed_value(12345) == True
assert validate_seed_value(-1) == False
print('✓ Seed validation tests passed')
# Test seed generation
new_seed = generate_random_seed()
assert isinstance(new_seed, int)
assert validate_seed_value(new_seed) == True
print('✓ Seed generation tests passed')
# Test seed sanitization
clean_seed = sanitize_seed_value(12345)
assert clean_seed == 12345
print('✓ Seed sanitization tests passed')
# Test node helper methods
assert node.is_seed_in_range(12345) == True
assert node.is_seed_in_range(-1) == False
assert node.get_default_seed() == 12345
print('✓ Seed helper methods tests passed')
print('🎉 All Seed History tests passed!')
"
- name: Test error handling for all tools
run: |
python -c "
import sys
import os
sys.path.insert(0, os.getcwd())
print('=== Testing Error Handling for All Tools ===')
# Test Resolution Calculator error handling
from kikotools.tools.resolution_calculator.node import ResolutionCalculatorNode
res_node = ResolutionCalculatorNode()
try:
res_node.calculate_resolution(2.0) # No input provided
assert False, 'Should have raised ValueError'
except ValueError:
print('✓ Resolution Calculator error handling test passed')
try:
res_node.calculate_resolution(0.0) # Invalid scale
assert False, 'Should have raised ValueError'
except ValueError:
print('✓ Resolution Calculator scale factor validation test passed')
# Test Width Height Selector error handling
from kikotools.tools.width_height_selector.node import WidthHeightSelectorNode
wh_node = WidthHeightSelectorNode()
# Test invalid preset fallback
result = wh_node.get_dimensions('invalid_preset', 800, 600)
assert result == (800, 600) # Should fallback to custom dimensions
print('✓ Width Height Selector invalid preset handling test passed')
# Test Sampler Combo error handling
from kikotools.tools.sampler_combo.node import SamplerComboNode
sampler_node = SamplerComboNode()
# Test with invalid sampler (should use safe defaults)
result = sampler_node.get_sampler_combo('invalid_sampler', 'normal', 20, 7.0)
assert result == ('euler', 'normal', 20, 7.0) # Safe defaults
print('✓ Sampler Combo invalid input handling test passed')
# Test Seed History error handling
from kikotools.tools.seed_history.node import SeedHistoryNode
seed_node = SeedHistoryNode()
# Test invalid seed value (should use fallback)
result = seed_node.output_seed(-1) # Invalid negative seed
assert result == (12345,) # Fallback seed
print('✓ Seed History invalid seed handling test passed')
print('🎉 All error handling tests passed for all tools!')
"
- name: Test ComfyUI integration readiness for all tools
run: |
python -c "
import sys
import os
sys.path.insert(0, os.getcwd())
print('=== Testing ComfyUI Integration for All Tools ===')
# Test Resolution Calculator
from kikotools.tools.resolution_calculator.node import ResolutionCalculatorNode
res_class = ResolutionCalculatorNode
assert hasattr(res_class, 'INPUT_TYPES')
assert hasattr(res_class, 'RETURN_TYPES')
assert hasattr(res_class, 'RETURN_NAMES')
assert hasattr(res_class, 'FUNCTION')
assert hasattr(res_class, 'CATEGORY')
input_types = res_class.INPUT_TYPES()
assert 'required' in input_types
assert 'optional' in input_types
assert 'scale_factor' in input_types['required']
assert 'image' in input_types['optional']
assert 'latent' in input_types['optional']
assert res_class.RETURN_TYPES == ('INT', 'INT')
assert res_class.RETURN_NAMES == ('width', 'height')
assert 'ComfyAssets/' in res_class.CATEGORY
print('✓ Resolution Calculator ComfyUI integration passed')
# Test Width Height Selector
from kikotools.tools.width_height_selector.node import WidthHeightSelectorNode
wh_class = WidthHeightSelectorNode
assert hasattr(wh_class, 'INPUT_TYPES')
assert hasattr(wh_class, 'RETURN_TYPES')
assert hasattr(wh_class, 'RETURN_NAMES')
assert hasattr(wh_class, 'FUNCTION')
assert hasattr(wh_class, 'CATEGORY')
input_types = wh_class.INPUT_TYPES()
assert 'required' in input_types
assert 'preset' in input_types['required']
assert 'width' in input_types['required']
assert 'height' in input_types['required']
assert wh_class.RETURN_TYPES == ('INT', 'INT')
assert wh_class.RETURN_NAMES == ('width', 'height')
assert 'ComfyAssets/' in wh_class.CATEGORY
print('✓ Width Height Selector ComfyUI integration passed')
# Test Sampler Combo
from kikotools.tools.sampler_combo.node import SamplerComboNode
sampler_class = SamplerComboNode
assert hasattr(sampler_class, 'INPUT_TYPES')
assert hasattr(sampler_class, 'RETURN_TYPES')
assert hasattr(sampler_class, 'RETURN_NAMES')
assert hasattr(sampler_class, 'FUNCTION')
assert hasattr(sampler_class, 'CATEGORY')
input_types = sampler_class.INPUT_TYPES()
assert 'required' in input_types
assert 'sampler_name' in input_types['required']
assert 'scheduler' in input_types['required']
assert 'steps' in input_types['required']
assert 'cfg' in input_types['required']
assert 'ComfyAssets/' in sampler_class.CATEGORY
print('✓ Sampler Combo ComfyUI integration passed')
# Test Seed History
from kikotools.tools.seed_history.node import SeedHistoryNode
seed_class = SeedHistoryNode
assert hasattr(seed_class, 'INPUT_TYPES')
assert hasattr(seed_class, 'RETURN_TYPES')
assert hasattr(seed_class, 'RETURN_NAMES')
assert hasattr(seed_class, 'FUNCTION')
assert hasattr(seed_class, 'CATEGORY')
input_types = seed_class.INPUT_TYPES()
assert 'required' in input_types
assert 'seed' in input_types['required']
assert seed_class.RETURN_TYPES == ('INT',)
assert seed_class.RETURN_NAMES == ('seed',)
assert 'ComfyAssets/' in seed_class.CATEGORY
print('✓ Seed History ComfyUI integration passed')
print('🎉 All tools ComfyUI integration readiness tests passed!')
"
test-package-structure:
coverage:
name: coverage gate (85%)
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v5
- uses: actions/checkout@v7
- name: Set up Python 3.10
uses: actions/setup-python@v5
- uses: actions/setup-python@v6
with:
python-version: "3.10"
python-version: "3.12"
cache: pip
cache-dependency-path: requirements-dev.txt
- name: Test package structure
- name: Install dependencies
run: |
# Check required files exist
test -f README.md || (echo "README.md missing" && exit 1)
test -f LICENSE || (echo "LICENSE missing" && exit 1)
test -f requirements-dev.txt || (echo "requirements-dev.txt missing" && exit 1)
python -m pip install --upgrade pip
pip install torch --index-url https://download.pytorch.org/whl/cpu
pip install -r requirements-dev.txt aiohttp
# Check directory structure
test -d kikotools || (echo "kikotools directory missing" && exit 1)
test -d kikotools/base || (echo "kikotools/base directory missing" && exit 1)
test -d kikotools/tools || (echo "kikotools/tools directory missing" && exit 1)
test -d kikotools/tools/resolution_calculator || (echo "resolution_calculator directory missing" && exit 1)
test -d kikotools/tools/width_height_selector || (echo "width_height_selector directory missing" && exit 1)
test -d kikotools/tools/sampler_combo || (echo "sampler_combo directory missing" && exit 1)
test -d kikotools/tools/seed_history || (echo "seed_history directory missing" && exit 1)
test -d tests || (echo "tests directory missing" && exit 1)
test -d examples || (echo "examples directory missing" && exit 1)
test -d web || (echo "web directory missing" && exit 1)
# fail_under = 85 lives in pyproject.toml [tool.coverage.report]
- name: Measure coverage
run: python -m pytest tests --cov=kikotools --cov-report=term-missing
# Check key files
test -f kikotools/__init__.py || (echo "kikotools/__init__.py missing" && exit 1)
test -f kikotools/base/base_node.py || (echo "base_node.py missing" && exit 1)
# Resolution Calculator files
test -f kikotools/tools/resolution_calculator/node.py || (echo "resolution_calculator node.py missing" && exit 1)
test -f kikotools/tools/resolution_calculator/logic.py || (echo "resolution_calculator logic.py missing" && exit 1)
# Width Height Selector files
test -f kikotools/tools/width_height_selector/node.py || (echo "width_height_selector node.py missing" && exit 1)
test -f kikotools/tools/width_height_selector/logic.py || (echo "width_height_selector logic.py missing" && exit 1)
test -f kikotools/tools/width_height_selector/presets.py || (echo "width_height_selector presets.py missing" && exit 1)
# Sampler Combo files
test -f kikotools/tools/sampler_combo/node.py || (echo "sampler_combo node.py missing" && exit 1)
test -f kikotools/tools/sampler_combo/logic.py || (echo "sampler_combo logic.py missing" && exit 1)
# Seed History files
test -f kikotools/tools/seed_history/node.py || (echo "seed_history node.py missing" && exit 1)
test -f kikotools/tools/seed_history/logic.py || (echo "seed_history logic.py missing" && exit 1)
# Web files
test -f web/width_height_swap.js || (echo "width_height_swap.js missing" && exit 1)
test -f web/seed_history_ui.js || (echo "seed_history_ui.js missing" && exit 1)
echo "✓ Package structure tests passed"
test-documentation:
js-check:
name: frontend syntax
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v5
- uses: actions/checkout@v7
- name: Test documentation completeness
# No JS unit tests yet; at least make sure every module parses
- name: Check web/*.js parse as ES modules
run: |
# Check documentation files for all tools
test -f examples/documentation/resolution_calculator.md || (echo "Resolution calculator docs missing" && exit 1)
test -f examples/workflows/resolution_calculator_example.json || (echo "Resolution calculator workflow missing" && exit 1)
test -f examples/documentation/width_height_selector.md || (echo "Width height selector docs missing" && exit 1)
test -f examples/workflows/width_height_selector_example.json || (echo "Width height selector workflow missing" && exit 1)
test -f examples/documentation/sampler_combo.md || (echo "Sampler combo docs missing" && exit 1)
test -f examples/workflows/sampler_combo_example.json || (echo "Sampler combo workflow missing" && exit 1)
test -f examples/documentation/seed_history.md || (echo "Seed history docs missing" && exit 1)
test -f examples/workflows/seed_history_example.json || (echo "Seed history workflow missing" && exit 1)
# Check README has key sections
grep -q "Installation" README.md || (echo "README missing Installation section" && exit 1)
grep -q "Quick Start" README.md || (echo "README missing Quick Start section" && exit 1)
grep -q "Development" README.md || (echo "README missing Development section" && exit 1)
grep -q "Contributing" README.md || (echo "README missing Contributing section" && exit 1)
echo "✓ Documentation tests passed"
for f in web/*.js; do
node --input-type=module --check < "$f" || { echo "Syntax error in $f"; exit 1; }
done
+6
View File
@@ -159,7 +159,13 @@ test_images/
test_outputs/
experiments/
.claude/
.serena
# Gemini model cache
.gemini_models_cache.json
referance/
# Runtime state written inside the package (repo is symlinked into custom_nodes)
kikotools/tools/local_image_loader/config.json
kikotools/tools/local_image_loader/selections.json
gemini_config.json
+1 -1
View File
@@ -81,4 +81,4 @@ exclude: |
.*\.egg-info/|
venv/|
env/
)
)
+91 -5
View File
@@ -37,6 +37,10 @@ I’m sharing them here with the community, and I hope you find them as useful a
| [🎬 Film Grain](#-film-grain) | Add realistic film grain effects to images | 💾 Images |
| [🔤 Embedding Autocomplete](#-embedding-autocomplete) | Smart autocomplete for embeddings, LoRAs, and tags | 🔧 Utils |
| [🧹 Kiko Purge VRAM](#-kiko-purge-vram) | Intelligent VRAM management with detailed reporting | 🛠️ Utils |
| [📂 Local Image Loader](#-local-image-loader) | Visual gallery browser for local media files | 💾 Images |
| [🌐 Model Downloader](#-model-downloader) | Download models from CivitAI, HuggingFace, and custom URLs | 🛠️ Utils |
| [⏱️ Workflow Timer](#️-workflow-timer) | Real-time execution timer with customizable display | 🛠️ Utils |
| [🗂️ Project File Path](#️-project-file-path) | Build safe, organized save prefixes like `MyProject/images/image` | 🛠️ Utils |
### 🧰 xyz-helpers Tools
@@ -357,6 +361,84 @@ Unified interface for text encoding and sampler parameter management.
- Quick template-based generation
- Batch prompt processing
#### 📂 Local Image Loader
Visual gallery browser for loading local images, videos, and audio files directly into ComfyUI workflows.
- **Visual Gallery Interface**: Browse files with thumbnail previews in a masonry layout
- **Multi-Media Support**: Load images (JPG, PNG, GIF, WebP), videos (MP4, WebM, MOV), and audio files (MP3, WAV, OGG, FLAC)
- **Quick Navigation**: Navigate folders with breadcrumb path and parent directory button
- **Responsive Layout**: Automatically adjusts thumbnail grid to available space
- **Metadata Extraction**: Reads embedded prompt and workflow data from generated images
- **Saved Paths**: Remember frequently used directories for quick access
- **Double-Click Preview**: Open full-size media in new browser tab
- **Smart Sorting**: Sort by name, date, or file size in ascending or descending order
- **Pagination Support**: Efficiently browse large directories with page controls
**Use Cases:**
- Load reference images from local folders for img2img workflows
- Browse and select from collections of generated images
- Quickly access frequently used asset directories
- Extract prompts and settings from previously generated images
- Preview media files before loading into workflow
#### 🌐 Model Downloader
Download models, LoRAs, and other assets directly from CivitAI, HuggingFace, and custom URLs within ComfyUI.
- **Multi-Platform Support**: CivitAI, HuggingFace, and direct download URLs
- **Smart URL Detection**: Automatic detection of download source and file handling
- **API Token Support**: Optional authentication for private/gated models
- **Progress Reporting**: Real-time download progress with speed indicators
- **Resume Support**: Skip existing files or force re-download
- **Interrupt Handling**: Respects ComfyUI's "Cancel current run" button
- **Automatic Cleanup**: Removes partial downloads on cancellation
- **Custom Filenames**: Override auto-detected filenames when needed
**Platform Features:**
- **CivitAI**: Model page URLs, version-specific downloads, API authentication
- **HuggingFace**: Blob and resolve URLs, branch/revision support, gated model access
- **Custom URLs**: Direct download links with bearer token authentication
**Use Cases:**
- Download models without leaving ComfyUI
- Automate asset acquisition in workflows
- Access private or gated models with API tokens
- Build reproducible workflows with automatic model fetching
- Quickly test new models from the community
![Model Downloader Example](examples/workflows/model_downloader_example.png)
#### ⏱️ Workflow Timer
Real-time execution timer that displays workflow duration with millisecond precision.
- **Live Timing**: Updates in real-time during workflow execution (MM:SS:mmm format)
- **Customizable Color**: Choose your preferred display color via KikoTools settings
- **Glow Effect**: Optional pulsing glow animation (can be enabled/disabled in settings)
- **Global Settings**: Color and glow preferences apply to all timer nodes
- **Persistent Display**: Shows final execution time after workflow completes
- **Multi-Node Sync**: All timer nodes stay synchronized during execution
**Use Cases:**
- Monitor workflow execution performance
- Compare generation times across different settings
- Identify slow nodes by adding timers at different workflow stages
- Track optimization improvements over time
**Settings (KikoTools Settings Panel):**
- **Workflow Timer: Color** - Custom color picker for timer display
- **Workflow Timer: Enable Glow** - Toggle pulsing glow effect on/off
#### 🗂️ Project File Path
Builds an organized save prefix to wire into a save node's `filename_prefix`.
- **Structure**: `root/project_name/[YYYY-MM-DD/]subfolder/filename`, e.g. `MyProject/2026-10-13/images/image`
- **Date Folder**: Optional toggle inserts today's date after the project; the node re-runs when the date changes
- **Safe Paths**: Unsafe characters are removed, spaces become underscores, and `..` segments are dropped so paths stay inside the output folder
- **Nested Folders**: Use `a/b` in `subfolder` for deeper structure
- **Extensions**: Known file extensions (`.png`, `.mp4`, ...) are stripped from `filename`; `render_v1.5` is left as is
- **Separator**: `auto`, `forward_slash` or `backslash`
Based on the idea of the Project File Path Generator from djz-nodes.
### 🔤 Embedding Autocomplete
**Intelligent autocomplete for embeddings, LoRAs, and custom tags in text prompts.**
@@ -400,7 +482,7 @@ This feature is an enhanced fork of the autocomplete functionality from [ComfyUI
**Intelligent GPU memory management with threshold-based triggering and detailed reporting.**
**Key Features:**
- **4 Purge Modes**:
- **4 Purge Modes**:
- `soft`: Basic garbage collection and cache clearing
- `aggressive`: Multiple GC passes with full CUDA cache clearing
- `models_only`: Unload all models and clear model cache
@@ -678,6 +760,9 @@ Example workflow available: [xyz_helpers_lora_testing.json](examples/workflows/x
| **Sampler Select Helper** | Intelligent sampler selection with recommendations | ✅ Complete | [Docs](examples/documentation/sampler_select_helper.md) |
| **Scheduler Select Helper** | Optimal scheduler selection for samplers | ✅ Complete | [Docs](examples/documentation/scheduler_select_helper.md) |
| **Text Encode Sampler Params** | Combined text encoding and parameter management | ✅ Complete | [Docs](examples/documentation/text_encode_sampler_params.md) |
| **Local Image Loader** | Visual gallery browser for local media files | ✅ Complete | [Docs](examples/documentation/local_image_loader.md) |
| **Model Downloader** | Download models from CivitAI, HuggingFace, and custom URLs | ✅ Complete | [Docs](examples/documentation/model_downloader.md) |
| **Workflow Timer** | Real-time execution timer with customizable display | ✅ Complete | [Docs](examples/documentation/workflow_timer.md) |
| **Batch Image Processor** | Process multiple images with consistent settings | 🚧 Planned | Coming Soon |
| **Advanced Prompt Utilities** | Enhanced prompt manipulation and generation | 🚧 Planned | Coming Soon |
@@ -960,7 +1045,7 @@ MIT License - see [LICENSE](LICENSE) file for details.
## 🏷️ Tags
`comfyui` `custom-nodes` `image-processing` `ai-tools` `sdxl` `flux` `upscaling` `resolution` `batch-processing` `python` `pytorch`
`comfyui` `custom-nodes` `image-processing` `ai-tools` `sdxl` `flux` `upscaling` `resolution` `batch-processing` `model-downloader` `civitai` `huggingface` `python` `pytorch`
## 🔗 Links
@@ -971,17 +1056,18 @@ MIT License - see [LICENSE](LICENSE) file for details.
## 📈 Stats
- **Nodes**: 19 (13 core tools + 6 xyz-helpers)
- **Nodes**: 21 (15 core tools + 6 xyz-helpers)
- **Features**: Embedding Autocomplete (settings-based, not a node)
- **Categories**: 9 emoji-based categories for better organization
- **Download Platforms**: 3 (CivitAI, HuggingFace, Custom URLs)
- **Format Support**: 3 (PNG, JPEG, WebP with advanced controls)
- **Presets**: 26 curated resolution presets
- **Interactive Features**: 8+ (swap buttons, history UI, popup viewers, parameter visualization)
- **AI Integration**: Gemini API with 40+ model support
- **Test Coverage**: 100% (300+ comprehensive tests)
- **Test Coverage**: 100% (470+ comprehensive tests)
- **Python Version**: 3.8+
- **ComfyUI Compatibility**: Latest
- **Dependencies**: Minimal (PyTorch, NumPy, Pillow, google-generativeai for Gemini)
- **Dependencies**: Minimal (PyTorch, NumPy, Pillow, google-genai for Gemini)
## 🙏 Attribution
+5 -2
View File
@@ -105,7 +105,7 @@ def get_version():
try:
pyproject_path = Path(__file__).parent / "pyproject.toml"
if pyproject_path.exists():
content = pyproject_path.read_text()
content = pyproject_path.read_text(encoding="utf-8")
match = re.search(r'version\s*=\s*["\']([^"\']+)["\']', content)
if match:
return match.group(1)
@@ -118,7 +118,10 @@ def get_version():
print()
print(f"\033[94m[ComfyUI-KikoTools] Version:\033[0m {get_version()}")
for node_key, display_name in NODE_DISPLAY_NAME_MAPPINGS.items():
print(f"🫶 \033[94mLoaded:\033[0m {display_name}")
# ASCII only: a Windows console using a legacy code page cannot print emoji,
# and a UnicodeEncodeError here would abort loading the whole node.
ascii_name = display_name.encode("ascii", "ignore").decode().strip()
print(f" \033[94mLoaded:\033[0m {ascii_name}")
print(f"\033[94mTotal: {len(NODE_CLASS_MAPPINGS)} tools loaded\033[0m")
print()
+106
View File
@@ -0,0 +1,106 @@
# Batch Prompts Node
The **Batch Prompts** node loads and processes prompts from text files for batch generation workflows. It automatically cycles through prompts with each execution, making it perfect for testing multiple prompts in queue batches.
## Features
- **File-based prompt loading** - Load prompts from text files with `---` separators
- **Auto-increment mode** - Automatically advance to the next prompt with each execution
- **Positive/Negative splitting** - Automatically splits prompts at "Negative:" markers
- **Persistent state** - Maintains position across ComfyUI restarts
- **Wrap-around support** - Loop back to the first prompt after the last one
- **Progress tracking** - Shows current position and total prompts
## Input Parameters
| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `prompt_file` | STRING | "prompts.txt" | Path to text file containing prompts |
| `index` | INT | 0 | Manual prompt index (when auto_increment is off) |
| `auto_increment` | BOOLEAN | True | Automatically advance to next prompt |
| `wrap_around` | BOOLEAN | True | Loop back to start after last prompt |
| `split_negative` | BOOLEAN | True | Split prompts at "Negative:" marker |
| `reload_file` | BOOLEAN | False | Force reload file from disk |
| `show_preview` | BOOLEAN | True | Show prompt preview in console |
## Output Values
| Output | Type | Description |
|--------|------|-------------|
| `positive` | STRING | The positive prompt text |
| `negative` | STRING | The negative prompt text (if split) |
| `full_prompt` | STRING | Complete prompt including negative |
| `next_prompt` | STRING | Preview of the next prompt |
| `current_index` | INT | Current prompt index (0-based) |
| `total_prompts` | INT | Total number of prompts |
| `batch_info` | STRING | Progress information string |
## Prompt File Format
Create a text file with prompts separated by `---` on its own line:
```
A beautiful sunset over the ocean
Negative: blurry, dark, low quality
---
Mountain landscape with snow peaks
Negative: foggy, unclear
---
Futuristic city at night
Negative: old, vintage, sepia
```
## Usage Examples
### Basic Queue Batch Processing
1. Create a prompt file in your ComfyUI `input` folder
2. Add the Batch Prompts node to your workflow
3. Set `prompt_file` to your file name
4. Enable `auto_increment` and `wrap_around`
5. Connect `positive` to your text encoder
6. Connect `negative` to your negative text encoder
7. Set Queue Batch to desired number (e.g., 10)
8. Run the queue - prompts will cycle automatically
### Manual Index Control
For manual control over which prompt to use:
1. Set `auto_increment` to False
2. Control the `index` parameter manually
3. Use with other nodes that provide index values
### Monitoring Progress
The node provides several ways to track progress:
- `batch_info` output shows "Prompt X of Y (Z% complete)"
- Console logging shows current prompt preview (when `show_preview` is True)
- `current_index` and `total_prompts` for custom progress displays
## Tips
- Place prompt files in the ComfyUI `input` folder for easy access
- Use relative paths like "prompts.txt" for files in the input folder
- Use absolute paths for files elsewhere on your system
- The node maintains state across ComfyUI restarts
- Set `reload_file` to True to force re-reading after editing the file
- Empty sections (between `---` markers) are automatically skipped
## Troubleshooting
### Prompts not changing in queue batch
- Ensure `auto_increment` is set to True
- Check console for "[BatchPrompts] Auto-increment" messages
- Restart ComfyUI after installing/updating the node
### File not found errors
- Check that the file exists in the ComfyUI `input` folder
- Try using an absolute path to test
- Ensure file has read permissions
### State persistence
- State is stored in your system's temp directory
- Clear `/tmp/comfyui_batch_prompts/` to reset all counters
- Use `reload_file` to reset counter for a specific file
+1 -1
View File
@@ -117,4 +117,4 @@ Config Node → Display Any (raw value) → Processing Node
[Text Multiline] ← [Concatenate] ← "Image dimensions: "
```
This creates a text output showing the current image dimensions that can be used elsewhere in your workflow.
This creates a text output showing the current image dimensions that can be used elsewhere in your workflow.
+3 -3
View File
@@ -85,7 +85,7 @@ Display long text content with scrolling and word wrapping.
The node intelligently detects prompt formats:
1. **SDXL Format**:
1. **SDXL Format**:
- Looks for "Positive prompt:" and "Negative prompt:" markers
- Case-insensitive detection
- Handles various formatting styles
@@ -98,7 +98,7 @@ The node intelligently detects prompt formats:
## Styling
- **Font**: Monospace for consistent alignment
- **Colors**:
- **Colors**:
- Text: Light gray (#ddd) on dark background
- Background: Semi-transparent dark (#1a1a1a)
- Borders: Subtle gray (#333)
@@ -144,4 +144,4 @@ The node intelligently detects prompt formats:
SDXL Format Split View Display Clean Prompts
```
This creates a seamless workflow from prompt generation to usage, with the Display Text node providing the visual interface for review and interaction.
This creates a seamless workflow from prompt generation to usage, with the Display Text node providing the visual interface for review and interaction.
@@ -149,4 +149,4 @@ base_shift: 0.4
- **1.0.3**: Improved UI elements and parameter validation
## Credits
Original implementation by cubiq in [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials). Adapted and maintained by the ComfyAssets team.
Original implementation by cubiq in [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials). Adapted and maintained by the ComfyAssets team.
+4 -4
View File
@@ -21,7 +21,7 @@ Get your free Gemini API key from [Google AI Studio](https://makersuite.google.c
### 2. Install Dependencies
```bash
pip install google-generativeai
pip install google-genai
```
### 3. Configure API Key
@@ -204,6 +204,6 @@ Errors are displayed in the prompt output for easy debugging.
- Verify API key is valid
- Image might be too large (resize if needed)
**Import error for google-generativeai**:
- Run `pip install google-generativeai` in your ComfyUI environment
- Restart ComfyUI after installation
**Import error for google-genai**:
- Run `pip install google-genai` in your ComfyUI environment
- Restart ComfyUI after installation
@@ -79,4 +79,4 @@ Load Images → Image to Multiple Of (multiple_of: 16, method: rescale) → Batc
The node will raise an error if:
- The image dimensions are smaller than the specified multiple_of value
- Invalid input types are provided
- The resulting dimensions would be 0 or negative
- The resulting dimensions would be 0 or negative
+1 -1
View File
@@ -122,4 +122,4 @@ Creates monochrome grain perfect for black and white photography.
- Works with any image format supported by ComfyUI
- Preserves image properties (alpha channel, batch size)
- Compatible with both RGB and RGBA images
- Efficient batch processing support
- Efficient batch processing support
+2 -2
View File
@@ -50,7 +50,7 @@ Enhanced image saving node with multiple format support, quality controls, and a
### Image Grid
- **Thumbnails**: Click any image to open full-size in new tab
- **File Info**: Shows filename and size for each image
- **Quality Indicators**:
- **Quality Indicators**:
- PNG: Compression level (0-9)
- JPEG/WebP: Quality percentage
- **Batch Selection**: Checkboxes for multi-select operations
@@ -210,4 +210,4 @@ Batch Generate → Kiko Save Image → Popup Viewer
**Can't see all images**:
- Scroll within the popup grid
- Maximize the popup window
- Images are shown newest first
- Images are shown newest first
@@ -0,0 +1,158 @@
# Local Image Loader
## Overview
The Local Image Loader node provides a visual gallery interface for browsing and selecting images, videos, and audio files from your local filesystem directly within ComfyUI. This streamlined version focuses on essential functionality without the complexity of tagging or metadata management.
## Features
- **Visual Gallery Browser**: Browse local directories with thumbnail previews
- **Multi-Media Support**: Load images, videos, and audio files
- **Directory Navigation**: Navigate through folders with ease
- **Sorting Options**: Sort by name, date, or file size
- **Saved Paths**: Save frequently used directory paths for quick access
- **Pagination**: Handle large directories with paginated display
- **Lightbox Preview**: Full-size preview with zoom and pan capabilities
## Node Inputs
### Required Inputs
None - The node uses a visual interface for file selection
### Hidden Inputs
- `unique_id`: Automatically assigned node identifier
## Node Outputs
| Output | Type | Description |
|--------|------|-------------|
| `image` | IMAGE | The selected image as a tensor |
| `video_path` | STRING | Path to the selected video file |
| `audio_path` | STRING | Path to the selected audio file |
| `info` | STRING | JSON metadata about the selected image |
## Usage
### Basic Workflow
1. **Add the Node**: Search for "Local Image Loader" in the node menu
2. **Browse Directory**: Enter a directory path or use saved paths
3. **Select Media**: Click on thumbnails to select files
4. **Connect Outputs**: Use the outputs in your workflow
### Interface Controls
#### Path Management
- **Directory Input**: Enter or paste a directory path
- **Saved Paths Dropdown**: Quick access to saved directories
- **Save Path Button** (💾): Save current directory to favorites
- **Browse Button** (📁): Load the entered directory
#### View Options
- **Videos Checkbox**: Show/hide video files
- **Audio Checkbox**: Show/hide audio files
- **Sort By**: Choose between Name, Date, or Size
- **Sort Order**: Ascending (↑) or Descending (↓)
- **Refresh Button** (🔄): Reload current directory
#### Gallery Display
- **Thumbnail Grid**: Visual preview of files
- **Blue Border**: Selected items are highlighted
- **Folder Icons**: Navigate into subdirectories
- **Video Overlay**: Visual indicator for video files
- **Pagination**: Navigate through pages of results
## File Support
### Supported Image Formats
- `.jpg`, `.jpeg`
- `.png`
- `.bmp`
- `.gif`
- `.webp`
### Supported Video Formats
- `.mp4`
- `.webm`
- `.mov`
- `.mkv`
- `.avi`
### Supported Audio Formats
- `.mp3`
- `.wav`
- `.ogg`
- `.flac`
## Image Metadata
When an image is selected, the node extracts and returns metadata including:
- **Basic Info**: Filename, width, height, format, mode
- **Embedded Parameters**: Generation parameters if present
- **Workflow Data**: Embedded ComfyUI workflow if present
- **Prompt Data**: Embedded prompt information if present
## Examples
### Loading an Image for Processing
```
Local Image Loader → Load Image → Image Processing Node
↓
[info] → Display Text (to show metadata)
```
### Setting Up a Multi-Media Workflow
```
Local Image Loader → [image] → Image Preview
↓
[video_path] → Video Player Node
↓
[audio_path] → Audio Player Node
```
## Tips and Best Practices
1. **Save Frequently Used Paths**: Use the save button to bookmark directories you use often
2. **Use Sorting**: Sort by date to find recent files quickly
3. **Keyboard Navigation**: Press Enter in the path field to load a directory
4. **Performance**: For directories with thousands of files, use pagination to navigate efficiently
5. **Thumbnail Generation**: Thumbnails are generated on-demand and cached for performance
## Differences from Original
This version simplifies the original ComfyUI_Local_Image_Gallery by removing:
- Tag filtering and management
- Rating system
- Global tag search
- Metadata editing capabilities
These features were removed to focus on the core functionality of browsing and selecting files, making the tool simpler and more straightforward to use.
## Troubleshooting
### Common Issues
**Directory Not Loading**
- Verify the path exists and you have read permissions
- Check for special characters in the path
- Try using absolute paths instead of relative ones
**Thumbnails Not Showing**
- Ensure the files are in supported formats
- Check if the images are corrupted
- Try refreshing the gallery
**Large Directories Slow to Load**
- Use sorting and pagination to manage large folders
- Consider organizing files into subdirectories
- Enable only the media types you need (images, videos, audio)
## Technical Details
The node creates a visual widget that runs in the ComfyUI interface and communicates with the backend through API endpoints to:
- List directory contents
- Generate thumbnails
- Save user preferences
- Handle file selection
All file operations are performed server-side for security, with proper path validation to prevent directory traversal attacks.
+1 -1
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@@ -261,4 +261,4 @@ batch_mode: sequential
- **1.0.4**: Added auto-batching for large LoRA collections
## Credits
Original implementation by cubiq in [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials). Adapted and maintained by the ComfyAssets team.
Original implementation by cubiq in [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials). Adapted and maintained by the ComfyAssets team.
+3 -3
View File
@@ -109,12 +109,12 @@ Parameter Grid → PlotParameters → Analysis Display
x_axis: "guidance"
y_axis: "perceived_quality"
# Step efficiency analysis
# Step efficiency analysis
x_axis: "steps"
y_axis: "generation_time"
# LoRA impact assessment
x_axis: "lora_strength"
x_axis: "lora_strength"
y_axis: "style_adherence"
```
@@ -231,4 +231,4 @@ Compare multiple generation runs to identify optimal parameters.
- **1.0.3**: Improved export capabilities
## Credits
Original implementation by cubiq in [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials). Adapted and maintained by the ComfyAssets team.
Original implementation by cubiq in [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials). Adapted and maintained by the ComfyAssets team.
@@ -257,4 +257,4 @@ Compare all compatible samplers for specific model/prompt combination.
- **1.0.3**: Improved auto-detection
## Credits
Original implementation by cubiq in [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials). Adapted and maintained by the ComfyAssets team.
Original implementation by cubiq in [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials). Adapted and maintained by the ComfyAssets team.
@@ -297,4 +297,4 @@ Progress through schedulers from fast to quality for different use cases.
- **1.0.3**: Improved compatibility matrix
## Credits
Original implementation by cubiq in [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials). Adapted and maintained by the ComfyAssets team.
Original implementation by cubiq in [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials). Adapted and maintained by the ComfyAssets team.
@@ -142,7 +142,7 @@ steps: 30-40
cfg: 7-8
sampler: dpmpp_3m_sde
# Speed over quality
# Speed over quality
steps: 10-15
cfg: 5-6
sampler: euler
@@ -307,4 +307,4 @@ Very High (50+): Diminishing returns
- **1.0.3**: Improved batch processing
## Credits
Original implementation by cubiq in [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials). Adapted and maintained by the ComfyAssets team.
Original implementation by cubiq in [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials). Adapted and maintained by the ComfyAssets team.
+14
View File
@@ -0,0 +1,14 @@
A beautiful sunset over the ocean, golden hour lighting, professional photography, vibrant colors, high detail
Negative: blurry, dark, low quality, distorted, oversaturated
---
Majestic mountain landscape with snow-capped peaks, dramatic clouds, alpine scenery, crystal clear air, epic composition
Negative: foggy, flat lighting, boring composition, low contrast
---
Futuristic cityscape at night, neon lights, cyberpunk aesthetic, rain-slicked streets, atmospheric, blade runner style
Negative: daylight, rural, old fashioned, low tech, empty streets
---
Enchanted forest with magical glowing mushrooms, fairy lights, mystical atmosphere, ancient trees, fantasy art style
Negative: desert, urban, modern, realistic, mundane
---
Space station orbiting Earth, detailed mechanical structures, astronauts performing spacewalk, realistic sci-fi, NASA photography
Negative: fantasy, medieval, underwater, cartoon style
+1 -1
View File
@@ -376,4 +376,4 @@
"VHS_KeepIntermediate": true
},
"version": 0.4
}
}
+1 -1
View File
@@ -141,4 +141,4 @@
"VHS_KeepIntermediate": true
},
"version": 0.4
}
}
@@ -298,4 +298,4 @@
"VHS_KeepIntermediate": true
},
"version": 0.4
}
}
@@ -204,4 +204,4 @@
"VHS_KeepIntermediate": true
},
"version": 0.4
}
}
@@ -549,4 +549,4 @@
"VHS_KeepIntermediate": true
},
"version": 0.4
}
}
@@ -162,4 +162,4 @@
}
},
"version": 0.4
}
}
@@ -144,4 +144,4 @@
"VHS_KeepIntermediate": true
},
"version": 0.4
}
}
@@ -352,4 +352,4 @@
"VHS_KeepIntermediate": true
},
"version": 0.4
}
}
@@ -166,4 +166,4 @@
],
"attribution": "xyz_helpers nodes adapted from comfyui-essentials-nodes"
}
}
}
+35
View File
@@ -3,6 +3,13 @@ KikoTools package initialization and node registry
Handles automatic discovery and registration of all ComfyAssets tools
"""
from .tools.batch_list_converter import (
ImageBatchToImageListNode,
ImageListToImageBatchNode,
LatentBatchToLatentListNode,
LatentListToLatentBatchNode,
)
from .tools.batch_prompts import BatchPromptsNode
from .tools.display_any import DisplayAnyNode
from .tools.display_text import DisplayTextNode
from .tools.embedding_autocomplete import KikoEmbeddingAutocomplete
@@ -12,11 +19,17 @@ from .tools.image_scale_down_by import ImageScaleDownByNode
from .tools.image_to_multiple_of import ImageToMultipleOfNode
from .tools.kiko_film_grain import KikoFilmGrainNode
from .tools.kiko_purge_vram import KikoPurgeVRAM
from .tools.kiko_workflow_timer import KikoWorkflowTimerNode
from .tools.kiko_save_image import KikoSaveImageNode
from .tools.local_image_loader import LocalImageLoaderNode
from .tools.project_file_path import ProjectFilePathNode
from .tools.model_downloader import ModelDownloaderNode
from .tools.resolution_calculator import ResolutionCalculatorNode
from .tools.sampler_combo import SamplerComboCompactNode, SamplerComboNode
from .tools.seed_history import SeedHistoryNode
from .tools.text_input import TextInputNode
from .tools.width_height_selector import WidthHeightSelectorNode
from .tools.width_height_to_vec2 import WidthHeightToVec2Node
from .tools.xyz_helpers import (
FluxSamplerParamsNode,
LoRAFolderBatchNode,
@@ -28,6 +41,11 @@ from .tools.xyz_helpers import (
# ComfyUI node registration mappings
NODE_CLASS_MAPPINGS = {
"ImageBatchToImageList": ImageBatchToImageListNode,
"ImageListToImageBatch": ImageListToImageBatchNode,
"LatentBatchToLatentList": LatentBatchToLatentListNode,
"LatentListToLatentBatch": LatentListToLatentBatchNode,
"BatchPrompts": BatchPromptsNode,
"ResolutionCalculator": ResolutionCalculatorNode,
"WidthHeightSelector": WidthHeightSelectorNode,
"SeedHistory": SeedHistoryNode,
@@ -40,19 +58,30 @@ NODE_CLASS_MAPPINGS = {
"GeminiPrompt": GeminiPromptNode,
"DisplayAny": DisplayAnyNode,
"DisplayText": DisplayTextNode,
"TextInput": TextInputNode,
"KikoFilmGrain": KikoFilmGrainNode,
"KikoPurgeVRAM": KikoPurgeVRAM,
"KikoLocalImageLoader": LocalImageLoaderNode,
"KikoModelDownloader": ModelDownloaderNode,
"SamplerSelectHelper": SamplerSelectHelperNode,
"SchedulerSelectHelper": SchedulerSelectHelperNode,
"TextEncodeSamplerParams": TextEncodeSamplerParamsNode,
"FluxSamplerParams": FluxSamplerParamsNode,
"PlotParameters+": PlotParametersNode,
"LoRAFolderBatch": LoRAFolderBatchNode,
"WidthHeightToVec2": WidthHeightToVec2Node,
"KikoWorkflowTimer": KikoWorkflowTimerNode,
"KikoProjectFilePath": ProjectFilePathNode,
# Note: KikoEmbeddingAutocomplete is not registered as a node
# It's a settings-only feature accessed through ComfyUI settings menu
}
NODE_DISPLAY_NAME_MAPPINGS = {
"ImageBatchToImageList": "Image Batch to Image List",
"ImageListToImageBatch": "Image List to Image Batch",
"LatentBatchToLatentList": "Latent Batch to Latent List",
"LatentListToLatentBatch": "Latent List to Latent Batch",
"BatchPrompts": "Batch Prompts",
"ResolutionCalculator": "Resolution Calculator",
"WidthHeightSelector": "Width Height Selector",
"SeedHistory": "Seed History",
@@ -65,14 +94,20 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"GeminiPrompt": "Gemini Prompt Engineer",
"DisplayAny": "Display Any",
"DisplayText": "Display Text",
"TextInput": "Text Input",
"KikoFilmGrain": "Film Grain",
"KikoPurgeVRAM": "Kiko Purge VRAM",
"KikoLocalImageLoader": "Local Image Loader",
"KikoModelDownloader": "Model Downloader 🌐",
"SamplerSelectHelper": "Sampler Select Helper",
"SchedulerSelectHelper": "Scheduler Select Helper",
"TextEncodeSamplerParams": "Text Encode for Sampler Params",
"FluxSamplerParams": "Flux Sampler Parameters",
"PlotParameters+": "Plot Parameters",
"LoRAFolderBatch": "LoRA Folder Batch",
"WidthHeightToVec2": "Width Height to VEC2",
"KikoWorkflowTimer": "Workflow Timer",
"KikoProjectFilePath": "Project File Path",
# KikoEmbeddingAutocomplete removed - settings only, not a node
}
-96
View File
@@ -1,96 +0,0 @@
"""Tool registry for KikoTools.
This module provides the central registration system for all KikoTools nodes.
"""
import importlib
import os
from typing import Dict, List, Any, Optional
from pathlib import Path
class ToolRegistry:
"""Central registry for all KikoTools."""
def __init__(self):
self.tools: Dict[str, Any] = {}
self.node_classes: Dict[str, Any] = {}
def register_tool(self, tool_name: str, node_class: Any) -> None:
"""Register a tool and its node class.
Args:
tool_name: Name of the tool
node_class: The ComfyUI node class
"""
self.tools[tool_name] = node_class
# Also register by class name for ComfyUI
class_name = node_class.__name__
self.node_classes[class_name] = node_class
def discover_tools(self) -> None:
"""Automatically discover and load all tools in the tools directory."""
tools_dir = Path(__file__).parent.parent / "tools"
if not tools_dir.exists():
return
for tool_dir in tools_dir.iterdir():
if tool_dir.is_dir() and not tool_dir.name.startswith("_"):
self._load_tool(tool_dir.name)
def _load_tool(self, tool_name: str) -> None:
"""Load a single tool module.
Args:
tool_name: Name of the tool directory
"""
try:
# Try to import the tool's node module
module = importlib.import_module(f"kikotools.tools.{tool_name}.node")
# Look for node classes (classes with ComfyUI node attributes)
for attr_name in dir(module):
attr = getattr(module, attr_name)
if (
isinstance(attr, type)
and hasattr(attr, "INPUT_TYPES")
and hasattr(attr, "FUNCTION")
):
self.register_tool(tool_name, attr)
# If the tool has settings, register them
if hasattr(attr, "SETTINGS"):
from .settings import settings_registry
settings_registry.register_tool_settings(
tool_name,
getattr(
attr,
"DISPLAY_NAME",
tool_name.replace("_", " ").title(),
),
attr.SETTINGS,
)
except ImportError as e:
# Tool might not have a node.py file yet
pass
def get_node_class_mappings(self) -> Dict[str, Any]:
"""Get node class mappings for ComfyUI registration."""
return self.node_classes.copy()
def get_node_display_name_mappings(self) -> Dict[str, str]:
"""Get display name mappings for ComfyUI."""
mappings = {}
for class_name, node_class in self.node_classes.items():
if hasattr(node_class, "DISPLAY_NAME"):
mappings[class_name] = node_class.DISPLAY_NAME
else:
# Generate a display name from class name
mappings[class_name] = class_name.replace("Kiko", "").replace(
"Node", ""
)
return mappings
-201
View File
@@ -1,201 +0,0 @@
"""Settings registry for KikoTools.
This module provides a centralized settings management system for all KikoTools.
Tools can register their settings, which are then exposed in ComfyUI's settings UI.
"""
import json
import os
from typing import Dict, Any, List, Optional, Union
from dataclasses import dataclass, field
@dataclass
class SettingDefinition:
"""Definition of a single setting."""
id: str
name: str
type: str # "boolean", "combo", "number", "string", "custom"
default: Any
description: Optional[str] = None
options: Optional[Union[List[Any], Dict[str, Any]]] = None
min_value: Optional[float] = None
max_value: Optional[float] = None
step: Optional[float] = None
on_change: Optional[str] = None # JavaScript callback as string
@dataclass
class ToolSettings:
"""Settings collection for a single tool."""
tool_name: str
display_name: str
settings: List[SettingDefinition] = field(default_factory=list)
class SettingsRegistry:
"""Central registry for all KikoTools settings."""
def __init__(self):
self.tools: Dict[str, ToolSettings] = {}
self.settings_by_id: Dict[str, SettingDefinition] = {}
def register_tool_settings(
self, tool_name: str, display_name: str, settings: Dict[str, Dict[str, Any]]
) -> None:
"""Register settings for a tool.
Args:
tool_name: Internal tool identifier (e.g., "embedding_autocomplete")
display_name: Display name for the tool (e.g., "Embedding Autocomplete")
settings: Dictionary of setting configurations
{
"enabled": {
"type": "boolean",
"default": True,
"description": "Enable embedding autocomplete"
},
"max_suggestions": {
"type": "combo",
"default": 20,
"options": [10, 20, 50],
"description": "Maximum number of suggestions"
}
}
"""
tool_settings = ToolSettings(tool_name, display_name)
for setting_key, config in settings.items():
# Generate fully qualified setting ID
setting_id = f"kikotools.{tool_name}.{setting_key}"
# Create display name with branding
setting_name = f"🫶 {display_name}: {setting_key.replace('_', ' ').title()}"
setting_def = SettingDefinition(
id=setting_id,
name=setting_name,
type=config.get("type", "string"),
default=config.get("default"),
description=config.get("description"),
options=config.get("options"),
min_value=config.get("min"),
max_value=config.get("max"),
step=config.get("step"),
on_change=config.get("on_change"),
)
tool_settings.settings.append(setting_def)
self.settings_by_id[setting_id] = setting_def
self.tools[tool_name] = tool_settings
def get_setting(self, setting_id: str) -> Optional[SettingDefinition]:
"""Get a setting definition by ID."""
return self.settings_by_id.get(setting_id)
def get_tool_settings(self, tool_name: str) -> Optional[ToolSettings]:
"""Get all settings for a tool."""
return self.tools.get(tool_name)
def generate_frontend_registration(self) -> str:
"""Generate JavaScript code for frontend settings registration."""
js_lines = [
"// Auto-generated KikoTools settings registration",
"// This file is automatically generated by the settings registry",
"",
"import { app } from '../../scripts/app.js';",
"",
"app.registerExtension({",
" name: 'kikotools.settings',",
" async init() {",
" // Register all KikoTools settings",
]
for tool_name, tool_settings in self.tools.items():
js_lines.append(f" // {tool_settings.display_name} settings")
for setting in tool_settings.settings:
js_lines.append(f" app.ui.settings.addSetting({{")
js_lines.append(f' id: "{setting.id}",')
js_lines.append(f' name: "{setting.name}",')
js_lines.append(
f" defaultValue: {self._js_value(setting.default)},"
)
js_lines.append(f' type: "{setting.type}",')
if setting.description:
js_lines.append(f' tooltip: "{setting.description}",')
if setting.type == "combo" and setting.options:
js_lines.append(f" options: (value) => {{")
js_lines.append(
f" const options = {json.dumps(setting.options)};"
)
js_lines.append(f" return options.map(opt => ({{")
js_lines.append(f" value: opt,")
js_lines.append(f" text: String(opt),")
js_lines.append(f" selected: opt === value")
js_lines.append(f" }}));")
js_lines.append(f" }},")
if setting.type == "number":
if setting.min_value is not None:
js_lines.append(f" min: {setting.min_value},")
if setting.max_value is not None:
js_lines.append(f" max: {setting.max_value},")
if setting.step is not None:
js_lines.append(f" step: {setting.step},")
if setting.on_change:
js_lines.append(f" onChange(value) {{")
js_lines.append(f" {setting.on_change}")
js_lines.append(f" }}")
js_lines.append(f" }});")
js_lines.append("")
js_lines.extend([" }", "});", ""])
return "\n".join(js_lines)
def _js_value(self, value: Any) -> str:
"""Convert Python value to JavaScript literal."""
if isinstance(value, bool):
return "true" if value else "false"
elif isinstance(value, str):
return f'"{value}"'
elif value is None:
return "null"
else:
return str(value)
def save_frontend_settings(
self, output_path: str = "web/js/kikoSettings.js"
) -> None:
"""Save the generated frontend settings to a file."""
js_content = self.generate_frontend_registration()
os.makedirs(os.path.dirname(output_path), exist_ok=True)
with open(output_path, "w") as f:
f.write(js_content)
def get_all_settings(self) -> Dict[str, Any]:
"""Get all registered settings as a dictionary."""
result = {}
for tool_name, tool_settings in self.tools.items():
result[tool_name] = {
"display_name": tool_settings.display_name,
"settings": {
setting.id.split(".")[-1]: {
"type": setting.type,
"default": setting.default,
"description": setting.description,
"options": setting.options,
}
for setting in tool_settings.settings
},
}
return result
@@ -0,0 +1,15 @@
"""Batch/List conversion tool for ComfyUI."""
from .node import (
ImageBatchToImageListNode,
ImageListToImageBatchNode,
LatentBatchToLatentListNode,
LatentListToLatentBatchNode,
)
__all__ = [
"ImageBatchToImageListNode",
"ImageListToImageBatchNode",
"LatentBatchToLatentListNode",
"LatentListToLatentBatchNode",
]
@@ -0,0 +1,55 @@
"""Pure tensor split/join functions for batch-list conversions."""
import torch
from typing import Dict, List
def split_image_batch(images: torch.Tensor) -> List[torch.Tensor]:
"""Split [B,H,W,C] image batch into list of [1,H,W,C] tensors."""
return [images[i : i + 1] for i in range(images.shape[0])]
def join_image_batch(image_list: List[torch.Tensor]) -> torch.Tensor:
"""Join list of image tensors into single [B,H,W,C] batch."""
return torch.cat(image_list, dim=0)
def split_latent_batch(
latent: Dict[str, torch.Tensor],
) -> List[Dict[str, torch.Tensor]]:
"""Split latent dict into list of single-item latent dicts.
Preserves all keys (e.g. noise_mask, batch_index). Tensor values whose
first dimension matches the batch size of ``samples`` are sliced along
dim-0; all other values are copied as-is to every item.
"""
samples = latent["samples"]
batch_size = samples.shape[0]
result: List[Dict[str, torch.Tensor]] = []
for i in range(batch_size):
item: Dict[str, torch.Tensor] = {}
for key, value in latent.items():
if isinstance(value, torch.Tensor) and value.shape[0] == batch_size:
item[key] = value[i : i + 1]
else:
item[key] = value
result.append(item)
return result
def join_latent_batch(
latent_list: List[Dict[str, torch.Tensor]],
) -> Dict[str, torch.Tensor]:
"""Join list of latent dicts into single batched latent dict.
Tensor values that were sliced during split are concatenated along dim-0.
Non-tensor values are taken from the first item.
"""
result: Dict[str, torch.Tensor] = {}
first = latent_list[0]
for key in first:
if isinstance(first[key], torch.Tensor):
result[key] = torch.cat([lat[key] for lat in latent_list], dim=0)
else:
result[key] = first[key]
return result
@@ -0,0 +1,130 @@
"""Batch/List conversion nodes for ComfyUI."""
from typing import Dict, List, Tuple
import torch
from ...base.base_node import ComfyAssetsBaseNode
from .logic import (
split_image_batch,
join_image_batch,
split_latent_batch,
join_latent_batch,
)
class ImageBatchToImageListNode(ComfyAssetsBaseNode):
"""Split an IMAGE batch [B,H,W,C] into a list of individual images."""
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"images": ("IMAGE",),
}
}
RETURN_TYPES = ("IMAGE", "INT")
RETURN_NAMES = ("images", "count")
OUTPUT_IS_LIST = (True, False)
FUNCTION = "split_batch"
CATEGORY = "🫶 ComfyAssets/📦 Latents"
def split_batch(self, images: torch.Tensor) -> Tuple[List[torch.Tensor], int]:
image_list = split_image_batch(images)
count = len(image_list)
self.log_info(f"Split image batch of {count} into list")
return (image_list, count)
class ImageListToImageBatchNode(ComfyAssetsBaseNode):
"""Join a list of IMAGE tensors into a single batched IMAGE [B,H,W,C]."""
INPUT_IS_LIST = True
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"images": ("IMAGE",),
}
}
RETURN_TYPES = ("IMAGE", "INT")
RETURN_NAMES = ("images", "count")
FUNCTION = "join_batch"
CATEGORY = "🫶 ComfyAssets/📦 Latents"
def join_batch(self, images: List[torch.Tensor]) -> Tuple[torch.Tensor, int]:
batch = join_image_batch(images)
count = batch.shape[0]
self.log_info(f"Joined {count} images into batch")
return (batch, count)
class LatentBatchToLatentListNode(ComfyAssetsBaseNode):
"""Split a LATENT batch into a list of individual latent dicts."""
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"latent": ("LATENT",),
}
}
RETURN_TYPES = ("LATENT", "INT")
RETURN_NAMES = ("latents", "count")
OUTPUT_IS_LIST = (True, False)
FUNCTION = "split_batch"
CATEGORY = "🫶 ComfyAssets/📦 Latents"
def split_batch(
self, latent: Dict[str, torch.Tensor]
) -> Tuple[List[Dict[str, torch.Tensor]], int]:
latent_list = split_latent_batch(latent)
count = len(latent_list)
self.log_info(f"Split latent batch of {count} into list")
return (latent_list, count)
class LatentListToLatentBatchNode(ComfyAssetsBaseNode):
"""Join a list of LATENT dicts into a single batched LATENT."""
INPUT_IS_LIST = True
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"latents": ("LATENT",),
}
}
RETURN_TYPES = ("LATENT", "INT")
RETURN_NAMES = ("latent", "count")
FUNCTION = "join_batch"
CATEGORY = "🫶 ComfyAssets/📦 Latents"
def join_batch(
self, latents: List[Dict[str, torch.Tensor]]
) -> Tuple[Dict[str, torch.Tensor], int]:
batch = join_latent_batch(latents)
count = batch["samples"].shape[0]
self.log_info(f"Joined {count} latents into batch")
return (batch, count)
NODE_CLASS_MAPPINGS = {
"ImageBatchToImageList": ImageBatchToImageListNode,
"ImageListToImageBatch": ImageListToImageBatchNode,
"LatentBatchToLatentList": LatentBatchToLatentListNode,
"LatentListToLatentBatch": LatentListToLatentBatchNode,
}
NODE_DISPLAY_NAME_MAPPINGS = {
"ImageBatchToImageList": "Image Batch to Image List",
"ImageListToImageBatch": "Image List to Image Batch",
"LatentBatchToLatentList": "Latent Batch to Latent List",
"LatentListToLatentBatch": "Latent List to Latent Batch",
}
@@ -0,0 +1,5 @@
"""Batch Prompts node for loading and processing prompts from text files."""
from .node import BatchPromptsNode
__all__ = ["BatchPromptsNode"]
+278
View File
@@ -0,0 +1,278 @@
"""Logic module for Batch Prompts node."""
import os
from typing import List, Tuple, Dict, Any
import logging
logger = logging.getLogger(__name__)
def load_prompts_from_file(file_path: str) -> List[str]:
"""
Load prompts from a text file where prompts are separated by '---'.
Args:
file_path: Path to the text file containing prompts
Returns:
List of prompts (each prompt may be multi-line)
"""
try:
with open(file_path, "r", encoding="utf-8") as f:
content = f.read()
# Split by --- separator
prompts = content.split("---")
# Clean up prompts - remove leading/trailing whitespace but preserve internal formatting
cleaned_prompts = []
for prompt in prompts:
prompt = prompt.strip()
if prompt: # Only add non-empty prompts
cleaned_prompts.append(prompt)
logger.info(f"Loaded {len(cleaned_prompts)} prompts from {file_path}")
return cleaned_prompts
except Exception as e:
logger.error(f"Error loading prompts from {file_path}: {e}")
return []
def get_prompt_at_index(
prompts: List[str], index: int, wrap: bool = True
) -> Tuple[str, int]:
"""
Get prompt at specified index with optional wrapping.
Args:
prompts: List of prompts
index: Index to retrieve
wrap: Whether to wrap around to beginning when index exceeds list length
Returns:
Tuple of (prompt text, actual index used)
"""
if not prompts:
return ("", 0)
if wrap:
actual_index = index % len(prompts)
else:
actual_index = min(index, len(prompts) - 1)
return (prompts[actual_index], actual_index)
def get_next_prompt(
prompts: List[str], current_index: int, wrap: bool = True
) -> Tuple[str, int]:
"""
Get the next prompt in sequence.
Args:
prompts: List of prompts
current_index: Current prompt index
wrap: Whether to wrap around to beginning
Returns:
Tuple of (next prompt text, next index)
"""
if not prompts:
return ("", 0)
next_index = current_index + 1
if wrap:
next_index = next_index % len(prompts)
else:
next_index = min(next_index, len(prompts) - 1)
return (prompts[next_index], next_index)
def get_prompt_preview(prompt: str, max_length: int = 100) -> str:
"""
Get a preview of a prompt, truncated if necessary.
Args:
prompt: Full prompt text
max_length: Maximum length for preview
Returns:
Preview string
"""
if len(prompt) <= max_length:
return prompt
return prompt[:max_length] + "..."
def parse_prompt_file_list(file_list_str: str) -> List[str]:
"""
Parse a comma-separated list of prompt file paths.
Args:
file_list_str: Comma-separated file paths
Returns:
List of file paths
"""
if not file_list_str:
return []
files = []
for file_path in file_list_str.split(","):
file_path = file_path.strip()
if file_path:
files.append(file_path)
return files
def merge_prompts_from_multiple_files(file_paths: List[str]) -> List[str]:
"""
Load and merge prompts from multiple files.
Args:
file_paths: List of file paths
Returns:
Combined list of all prompts
"""
all_prompts = []
for file_path in file_paths:
prompts = load_prompts_from_file(file_path)
all_prompts.extend(prompts)
logger.info(f"Merged {len(all_prompts)} prompts from {len(file_paths)} files")
return all_prompts
def get_batch_info(prompts: List[str], current_index: int) -> Dict[str, Any]:
"""
Get information about current batch processing state.
Args:
prompts: List of prompts
current_index: Current prompt index
Returns:
Dictionary with batch information
"""
total = len(prompts)
return {
"current_index": current_index,
"total_prompts": total,
"progress": f"{current_index + 1}/{total}" if total > 0 else "0/0",
"percentage": (current_index / total * 100) if total > 0 else 0,
"remaining": total - current_index - 1 if total > 0 else 0,
"is_complete": current_index >= total - 1 if total > 0 else True,
}
def validate_prompt_file(file_path: str) -> Tuple[bool, str]:
"""
Validate that a prompt file exists and is readable.
Args:
file_path: Path to validate
Returns:
Tuple of (is_valid, error_message)
"""
if not file_path:
return (False, "No file path provided")
if not os.path.exists(file_path):
return (False, f"File not found: {file_path}")
if not os.path.isfile(file_path):
return (False, f"Path is not a file: {file_path}")
try:
with open(file_path, "r", encoding="utf-8") as f:
f.read(1) # Try to read one character
return (True, "")
except Exception as e:
return (False, f"Cannot read file: {str(e)}")
def format_prompt_for_display(prompt: str, index: int, total: int) -> str:
"""
Format a prompt for display with index information.
Args:
prompt: Prompt text
index: Current index
total: Total number of prompts
Returns:
Formatted display string
"""
header = f"[Prompt {index + 1}/{total}]"
separator = "-" * len(header)
return f"{header}\n{separator}\n{prompt}"
def split_prompt_into_positive_negative(
prompt: str, negative_prefix: str = "Negative:"
) -> Tuple[str, str]:
"""
Split a prompt into positive and negative parts.
Args:
prompt: Full prompt text
negative_prefix: Prefix that marks the negative prompt section
Returns:
Tuple of (positive_prompt, negative_prompt)
"""
# Look for negative prompt marker
negative_lower = negative_prefix.lower()
prompt_lower = prompt.lower()
if negative_lower in prompt_lower:
# Find the actual position (case-insensitive search)
idx = prompt_lower.index(negative_lower)
positive = prompt[:idx].strip()
negative = prompt[idx + len(negative_prefix) :].strip()
return (positive, negative)
# No negative prompt found
return (prompt, "")
def create_batch_queue(
prompts: List[str], batch_size: int = 1, randomize: bool = False
) -> List[List[int]]:
"""
Create a queue of prompt indices for batch processing.
Args:
prompts: List of prompts
batch_size: Number of prompts per batch
randomize: Whether to randomize the order
Returns:
List of batches, where each batch is a list of prompt indices
"""
if not prompts:
return []
indices = list(range(len(prompts)))
if randomize:
import random
random.shuffle(indices)
batches = []
for i in range(0, len(indices), batch_size):
batch = indices[i : i + batch_size]
batches.append(batch)
return batches
+237
View File
@@ -0,0 +1,237 @@
"""Batch Prompts node for ComfyUI."""
import os
from typing import Tuple
from ...base.base_node import ComfyAssetsBaseNode
from .logic import (
load_prompts_from_file,
get_prompt_at_index,
get_next_prompt,
get_prompt_preview,
get_batch_info,
validate_prompt_file,
split_prompt_into_positive_negative,
)
from .state_manager import STATE_MANAGER
class BatchPromptsNode(ComfyAssetsBaseNode):
"""
Batch Prompts node for loading and iterating through prompts from text files.
Loads prompts from a text file where prompts are separated by '---' markers,
provides iteration control, and outputs both current and next prompts with
optional positive/negative splitting.
"""
# Class variable to cache loaded prompts
_prompt_cache = {}
@classmethod
def INPUT_TYPES(cls):
"""Define the input types for the ComfyUI node."""
# Try to get input folder path
try:
import folder_paths
folder_paths.get_input_directory()
except Exception:
pass
return {
"required": {
"prompt_file": (
"STRING",
{
"default": "prompts.txt",
"multiline": False,
"tooltip": "Path to text file containing prompts separated by '---'",
},
),
"index": (
"INT",
{
"default": 0,
"min": 0,
"max": 9999,
"step": 1,
"tooltip": "Current prompt index (0-based)",
},
),
"auto_increment": (
"BOOLEAN",
{
"default": True,
"tooltip": "Automatically increment index after each execution",
},
),
"wrap_around": (
"BOOLEAN",
{
"default": True,
"tooltip": "Wrap to first prompt after reaching the end",
},
),
"split_negative": (
"BOOLEAN",
{
"default": True,
"tooltip": "Split prompts into positive/negative at 'Negative:' marker",
},
),
},
"optional": {
"reload_file": (
"BOOLEAN",
{"default": False, "tooltip": "Force reload file from disk"},
),
"show_preview": (
"BOOLEAN",
{"default": True, "tooltip": "Show prompt preview in console"},
),
},
}
RETURN_TYPES = ("STRING", "STRING", "STRING", "STRING", "INT", "INT", "STRING")
RETURN_NAMES = (
"positive",
"negative",
"full_prompt",
"next_prompt",
"current_index",
"total_prompts",
"batch_info",
)
FUNCTION = "process_batch_prompts"
CATEGORY = "🫶 ComfyAssets/📝 Text"
def process_batch_prompts(
self,
prompt_file: str,
index: int,
auto_increment: bool,
wrap_around: bool,
split_negative: bool,
reload_file: bool = False,
show_preview: bool = True,
) -> Tuple[str, str, str, str, int, int, str]:
"""
Process batch prompts from file.
Args:
prompt_file: Path to prompt file
index: Current prompt index
auto_increment: Whether to auto-increment index
wrap_around: Whether to wrap around at end
split_negative: Whether to split positive/negative prompts
reload_file: Force reload from disk
show_preview: Show prompt preview in console
Returns:
Tuple of (positive, negative, full_prompt, next_prompt, current_index, total_prompts, batch_info)
"""
try:
# Handle file path first to get a consistent key
if not os.path.isabs(prompt_file):
# Try to resolve relative to ComfyUI input directory
try:
import folder_paths
input_dir = folder_paths.get_input_directory()
full_path = os.path.join(input_dir, prompt_file)
except Exception:
# Fallback to current directory
full_path = os.path.abspath(prompt_file)
else:
full_path = prompt_file
# Use persistent state manager for tracking execution
if auto_increment:
# Use file-based persistent state
actual_index = STATE_MANAGER.increment_execution_count(full_path)
print(
f"[BatchPrompts] Auto-increment: using index {actual_index} for {os.path.basename(prompt_file)}"
)
else:
actual_index = index
print(f"[BatchPrompts] Manual mode: using index {actual_index}")
# Validate file
is_valid, error_msg = validate_prompt_file(full_path)
if not is_valid:
self.handle_error(f"Invalid prompt file: {error_msg}")
# Load prompts (with caching)
cache_key = full_path
if reload_file or cache_key not in self._prompt_cache:
prompts = load_prompts_from_file(full_path)
if not prompts:
self.handle_error(f"No prompts found in file: {prompt_file}")
self._prompt_cache[cache_key] = prompts
# Reset execution count when reloading file
if reload_file:
STATE_MANAGER.reset_execution_count(full_path)
self.log_info(f"Loaded {len(prompts)} prompts from {prompt_file}")
else:
prompts = self._prompt_cache[cache_key]
# Get current prompt using the determined index
current_prompt, used_index = get_prompt_at_index(
prompts, actual_index, wrap_around
)
# Get next prompt
next_prompt_text, next_index = get_next_prompt(
prompts, used_index, wrap_around
)
# Split positive/negative if requested
if split_negative:
positive, negative = split_prompt_into_positive_negative(current_prompt)
else:
positive = current_prompt
negative = ""
# Get batch info
batch_info_dict = get_batch_info(prompts, used_index)
batch_info_str = (
f"Prompt {batch_info_dict['current_index'] + 1} of {batch_info_dict['total_prompts']} "
f"({batch_info_dict['percentage']:.1f}% complete)"
)
# Show preview if requested
if show_preview:
preview = get_prompt_preview(positive, 80)
self.log_info(
f"Current prompt [{used_index + 1}/{len(prompts)}]: {preview}"
)
# No need to manually reset - the modulo operation in get_prompt_at_index handles wrapping
return (
positive,
negative,
current_prompt,
next_prompt_text,
used_index,
len(prompts),
batch_info_str,
)
except Exception as e:
self.handle_error(f"Error processing batch prompts: {str(e)}")
# Return empty values on error
return ("", "", "", "", 0, 0, "Error")
@classmethod
def IS_CHANGED(cls, **kwargs):
"""
Check if node inputs have changed.
This ensures the node re-executes when needed.
"""
# Import time to ensure unique value each check
import time
# Return current timestamp to guarantee the node is seen as changed
# This forces re-execution on every workflow run
return str(time.time())
@@ -0,0 +1,62 @@
"""State management for batch prompts using file persistence."""
import json
import tempfile
from pathlib import Path
from typing import Dict, Any
class StateManager:
"""Manages persistent state for batch prompt execution."""
def __init__(self):
# Use temp directory for state files
self.state_dir = Path(tempfile.gettempdir()) / "comfyui_batch_prompts"
self.state_dir.mkdir(exist_ok=True)
self.state_file = self.state_dir / "execution_state.json"
def get_state(self) -> Dict[str, Any]:
"""Load state from file."""
if self.state_file.exists():
try:
with open(self.state_file, "r", encoding="utf-8") as f:
return json.load(f)
except (json.JSONDecodeError, IOError):
pass
return {}
def save_state(self, state: Dict[str, Any]):
"""Save state to file."""
try:
with open(self.state_file, "w", encoding="utf-8") as f:
json.dump(state, f)
except Exception as e:
print(f"[BatchPrompts] Failed to save state: {e}")
def get_execution_count(self, file_path: str) -> int:
"""Get execution count for a specific file."""
state = self.get_state()
counts = state.get("execution_counts", {})
return counts.get(file_path, 0)
def increment_execution_count(self, file_path: str) -> int:
"""Increment and return execution count for a file."""
state = self.get_state()
counts = state.get("execution_counts", {})
current = counts.get(file_path, 0)
counts[file_path] = current + 1
state["execution_counts"] = counts
self.save_state(state)
return current
def reset_execution_count(self, file_path: str):
"""Reset execution count for a file."""
state = self.get_state()
counts = state.get("execution_counts", {})
counts[file_path] = 0
state["execution_counts"] = counts
self.save_state(state)
# Global state manager instance
STATE_MANAGER = StateManager()
+2 -2
View File
@@ -1,6 +1,6 @@
"""Logic for DisplayAny node - displays any input value or tensor shape."""
from typing import Any, List, Union
from typing import Any, List
def get_tensor_shapes(input_value: Any) -> List[List[int]]:
@@ -54,7 +54,7 @@ def format_display_value(input_value: Any, mode: str = "raw value") -> str:
if isinstance(input_value, (dict, list)):
return json.dumps(input_value, indent=2)
except:
except (TypeError, ValueError):
pass
return str(input_value)
+1 -1
View File
@@ -1,6 +1,6 @@
"""DisplayAny node for ComfyUI - displays any input value or tensor information."""
from typing import Any, Dict, Tuple
from typing import Any, Dict
from ...base import ComfyAssetsBaseNode
from .logic import format_display_value, validate_display_mode
+5 -5
View File
@@ -93,14 +93,14 @@ class EmptyLatentBatchNode(ComfyAssetsBaseNode):
}
}
RETURN_TYPES = ("LATENT", "INT", "INT")
RETURN_NAMES = ("latent", "width", "height")
RETURN_TYPES = ("LATENT", "INT", "INT", "INT")
RETURN_NAMES = ("latent", "width", "height", "batch_size")
FUNCTION = "create_empty_latent"
CATEGORY = "🫶 ComfyAssets/📦 Latents"
def create_empty_latent(
self, preset: str, width: int, height: int, batch_size: int
) -> Tuple[Dict[str, torch.Tensor], int, int]:
) -> Tuple[Dict[str, torch.Tensor], int, int, int]:
"""
Create empty latent tensor with specified dimensions and batch size.
@@ -111,7 +111,7 @@ class EmptyLatentBatchNode(ComfyAssetsBaseNode):
batch_size: Number of latents in the batch
Returns:
Tuple containing (latent dictionary with 'samples' tensor, width, height)
Tuple containing (latent dict, width, height, batch_size)
"""
try:
# Extract original preset name from formatted string if needed
@@ -160,7 +160,7 @@ class EmptyLatentBatchNode(ComfyAssetsBaseNode):
f"(pixel dims: {final_width}×{final_height})"
)
return (latent_dict, final_width, final_height)
return (latent_dict, final_width, final_height, batch_size)
except Exception as e:
# Handle any unexpected errors gracefully
@@ -1,89 +0,0 @@
{
"models": [
"gemini-2.5-pro",
"gemini-2.5-flash",
"gemini-2.5-flash-lite",
"gemini-2.5-pro-preview-03-25",
"gemini-2.5-flash-preview-05-20",
"gemini-2.5-pro-preview-05-06",
"gemini-2.5-pro-preview-06-05",
"gemini-2.5-flash-lite-preview-06-17",
"gemini-2.0-flash",
"gemini-2.0-flash-001",
"gemini-2.0-flash-lite-001",
"gemini-2.0-flash-lite",
"gemini-2.5-flash-preview-tts",
"gemini-2.5-pro-preview-tts",
"gemini-2.0-flash-preview-image-generation",
"gemini-2.0-flash-exp",
"gemini-2.0-flash-exp-image-generation",
"gemini-2.0-flash-lite-preview-02-05",
"gemini-2.0-flash-lite-preview",
"gemini-2.0-pro-exp",
"gemini-2.0-pro-exp-02-05",
"learnlm-2.0-flash-experimental",
"gemini-1.5-pro-latest",
"gemini-1.5-pro-002",
"gemini-1.5-pro",
"gemini-1.5-flash-latest",
"gemini-1.5-flash",
"gemini-1.5-flash-002",
"gemini-1.5-flash-8b",
"gemini-1.5-flash-8b-001",
"gemini-1.5-flash-8b-latest",
"gemini-2.0-flash-thinking-exp-01-21",
"gemini-2.0-flash-thinking-exp",
"gemini-2.0-flash-thinking-exp-1219",
"gemma-3-1b-it",
"gemma-3-4b-it",
"gemma-3-12b-it",
"gemma-3-27b-it",
"gemma-3n-e4b-it",
"gemma-3n-e2b-it",
"gemini-exp-1206"
],
"descriptions": {
"gemini-1.5-pro-latest": "Gemini 1.5 Pro Latest",
"gemini-1.5-pro-002": "Gemini 1.5 Pro 002",
"gemini-1.5-pro": "Gemini 1.5 Pro",
"gemini-1.5-flash-latest": "Gemini 1.5 Flash Latest",
"gemini-1.5-flash": "Gemini 1.5 Flash",
"gemini-1.5-flash-002": "Gemini 1.5 Flash 002",
"gemini-1.5-flash-8b": "Gemini 1.5 Flash-8B",
"gemini-1.5-flash-8b-001": "Gemini 1.5 Flash-8B 001",
"gemini-1.5-flash-8b-latest": "Gemini 1.5 Flash-8B Latest",
"gemini-2.5-pro-preview-03-25": "Gemini 2.5 Pro Preview 03-25",
"gemini-2.5-flash-preview-05-20": "Gemini 2.5 Flash Preview 05-20",
"gemini-2.5-flash": "Gemini 2.5 Flash",
"gemini-2.5-flash-lite-preview-06-17": "Gemini 2.5 Flash-Lite Preview 06-17",
"gemini-2.5-pro-preview-05-06": "Gemini 2.5 Pro Preview 05-06",
"gemini-2.5-pro-preview-06-05": "Gemini 2.5 Pro Preview",
"gemini-2.5-pro": "Gemini 2.5 Pro",
"gemini-2.0-flash-exp": "Gemini 2.0 Flash Experimental",
"gemini-2.0-flash": "Gemini 2.0 Flash",
"gemini-2.0-flash-001": "Gemini 2.0 Flash 001",
"gemini-2.0-flash-exp-image-generation": "Gemini 2.0 Flash (Image Generation) Experimental",
"gemini-2.0-flash-lite-001": "Gemini 2.0 Flash-Lite 001",
"gemini-2.0-flash-lite": "Gemini 2.0 Flash-Lite",
"gemini-2.0-flash-preview-image-generation": "Gemini 2.0 Flash Preview Image Generation",
"gemini-2.0-flash-lite-preview-02-05": "Gemini 2.0 Flash-Lite Preview 02-05",
"gemini-2.0-flash-lite-preview": "Gemini 2.0 Flash-Lite Preview",
"gemini-2.0-pro-exp": "Gemini 2.0 Pro Experimental",
"gemini-2.0-pro-exp-02-05": "Gemini 2.0 Pro Experimental 02-05",
"gemini-exp-1206": "Gemini Experimental 1206",
"gemini-2.0-flash-thinking-exp-01-21": "Gemini 2.5 Flash Preview 05-20",
"gemini-2.0-flash-thinking-exp": "Gemini 2.5 Flash Preview 05-20",
"gemini-2.0-flash-thinking-exp-1219": "Gemini 2.5 Flash Preview 05-20",
"gemini-2.5-flash-preview-tts": "Gemini 2.5 Flash Preview TTS",
"gemini-2.5-pro-preview-tts": "Gemini 2.5 Pro Preview TTS",
"learnlm-2.0-flash-experimental": "LearnLM 2.0 Flash Experimental",
"gemma-3-1b-it": "Gemma 3 1B",
"gemma-3-4b-it": "Gemma 3 4B",
"gemma-3-12b-it": "Gemma 3 12B",
"gemma-3-27b-it": "Gemma 3 27B",
"gemma-3n-e4b-it": "Gemma 3n E4B",
"gemma-3n-e2b-it": "Gemma 3n E2B",
"gemini-2.5-flash-lite": "Gemini 2.5 Flash-Lite"
},
"timestamp": 1754568195.1098156
}
+9 -15
View File
@@ -30,7 +30,7 @@ def tensor_to_pil(tensor: np.ndarray) -> Image.Image:
image_array = (tensor * 255).astype(np.uint8)
# Convert to PIL
return Image.fromarray(image_array, mode="RGB")
return Image.fromarray(image_array)
def image_to_base64(image: Image.Image, format: str = "PNG") -> str:
@@ -65,7 +65,7 @@ def get_api_key() -> Optional[str]:
os.path.dirname(__file__), "..", "..", "..", "gemini_config.json"
)
if os.path.exists(config_path):
with open(config_path, "r") as f:
with open(config_path, "r", encoding="utf-8") as f:
config = json.load(f)
api_key = config.get("api_key")
except Exception:
@@ -115,30 +115,24 @@ def analyze_image_with_gemini(
else:
system_prompt = PROMPT_TEMPLATES.get(prompt_type, PROMPT_TEMPLATES["flux"])
# Here we would normally make the API call to Gemini
# For now, we'll import the google-generativeai library
try:
import google.generativeai as genai
from google import genai
except ImportError:
return (
"",
"google-generativeai library not installed. Please run: pip install google-generativeai",
"google-genai library not installed. Please run: pip install google-genai",
)
try:
# Configure Gemini
genai.configure(api_key=api_key)
client = genai.Client(api_key=api_key)
# Create model
model = genai.GenerativeModel(model_name)
# Generate content
response = model.generate_content(
[
response = client.models.generate_content(
model=model_name,
contents=[
system_prompt,
pil_image,
"Analyze this image and generate an appropriate prompt according to the instructions.",
]
],
)
# Extract text from response
+7 -7
View File
@@ -59,10 +59,10 @@ def _fetch_models_from_api(
Tuple of (model_names_list, model_descriptions_dict)
"""
try:
import google.generativeai as genai
from google import genai
except ImportError:
if not silent:
logger.error("google-generativeai not installed")
logger.error("google-genai not installed")
return [], {}
# Get API key
@@ -77,15 +77,15 @@ def _fetch_models_from_api(
return [], {}
try:
genai.configure(api_key=api_key)
client = genai.Client(api_key=api_key)
models = []
descriptions = {}
# Fetch all models
for model in genai.list_models():
for model in client.models.list():
# Only include models that support generateContent
if "generateContent" in model.supported_generation_methods:
if "generateContent" in (model.supported_actions or []):
# Remove "models/" prefix from name
model_name = model.name.replace("models/", "")
models.append(model_name)
@@ -154,7 +154,7 @@ def _load_cache() -> Optional[Dict]:
return None
try:
with open(CACHE_FILE, "r") as f:
with open(CACHE_FILE, "r", encoding="utf-8") as f:
data = json.load(f)
# Check if cache is expired
@@ -176,7 +176,7 @@ def _save_cache(models: List[str], descriptions: Dict[str, str]) -> None:
"timestamp": time.time(),
}
with open(CACHE_FILE, "w") as f:
with open(CACHE_FILE, "w", encoding="utf-8") as f:
json.dump(data, f, indent=2)
except Exception as e:
logger.warning(f"Failed to save cache: {e}")
+1 -1
View File
@@ -63,7 +63,7 @@ Supports multiple prompt formats:
- Video: Motion and temporal descriptions for video generation
Requires Gemini API key (set GEMINI_API_KEY env var or provide in node).
Install: pip install google-generativeai
Install: pip install google-genai
"""
def generate_prompt(
+6 -3
View File
@@ -100,13 +100,15 @@ def generate_grain_texture(
Returns:
Grain texture tensor of shape [B, H/scale, W/scale, 3]
"""
torch.manual_seed(seed)
# Local generator: never touch the global RNG state
generator = torch.Generator()
generator.manual_seed(int(seed))
grain_height = max(1, int(height / scale))
grain_width = max(1, int(width / scale))
# Generate random noise
grain = torch.rand(batch_size, grain_height, grain_width, 3)
grain = torch.rand(batch_size, grain_height, grain_width, 3, generator=generator)
return grain
@@ -140,7 +142,8 @@ def apply_film_grain(
Returns:
Image with film grain applied
"""
if strength == 0.0:
# Only short-circuit when nothing at all would change (toe still applies)
if strength == 0.0 and toe == 0.0:
return image
# Handle empty batch
+1 -1
View File
@@ -75,7 +75,7 @@ class KikoFilmGrainNode(ComfyAssetsBaseNode):
{
"default": 0,
"min": 0,
"max": 0xFFFFFFFFFFFFFFFF,
"max": 0xFFFFFFFF, # 2**32 - 1
"description": "Random seed for grain pattern generation",
},
),
+5
View File
@@ -55,6 +55,11 @@ class KikoPurgeVRAM(BaseNode):
OUTPUT_NODE = True
DESCRIPTION = "Purge VRAM to free up GPU memory during workflow execution. Passes through any input unchanged."
@classmethod
def IS_CHANGED(cls, *args: Any, **kwargs: Any) -> float:
"""Always re-run: a purge must never be skipped by ComfyUI caching."""
return float("nan")
def purge_vram(
self,
anything: Any,
+85 -12
View File
@@ -10,7 +10,6 @@ from PIL import Image
from PIL.PngImagePlugin import PngInfo
import torch
from typing import Dict, List, Any, Optional, Tuple
import time
try:
import folder_paths
@@ -22,9 +21,70 @@ except ImportError:
return "./output"
def get_next_counter(output_dir: str, prefix: str) -> int:
"""
Get next available counter value from persistent counter file
This prevents file overwrites when the node is called multiple times
within the same second by maintaining a persistent counter.
Args:
output_dir: Directory to store counter file
prefix: Filename prefix to create unique counter per prefix
Returns:
Next available counter value
"""
# Create a safe counter filename
safe_prefix = "".join(c for c in prefix if c.isalnum() or c in "._-")
counter_file = os.path.join(output_dir, f".{safe_prefix}_counter.txt")
# Read current counter
counter = 0
if os.path.exists(counter_file):
try:
with open(counter_file, "r", encoding="utf-8") as f:
content = f.read().strip()
counter = int(content) if content else 0
except (ValueError, IOError):
# If file is corrupted or unreadable, start from 0
counter = 0
# Increment counter
counter += 1
# Save updated counter
try:
with open(counter_file, "w", encoding="utf-8") as f:
f.write(str(counter))
except IOError:
# If we can't write the counter file, continue anyway
# Better to risk overwrites than to fail completely
pass
return counter
def _ensure_inside_output_dir(
folder: str, output_dir: str, prefix_dir: str, subfolder: str
) -> None:
"""Raise ValueError unless folder resolves to a location inside output_dir."""
real_root = os.path.realpath(output_dir)
real_folder = os.path.realpath(folder)
try:
inside = os.path.commonpath([real_root, real_folder]) == real_root
except ValueError: # e.g. different drives on Windows
inside = False
if not inside:
raise ValueError(
"Resolved output folder is outside the output directory "
f"(prefix directory {prefix_dir!r}, subfolder {subfolder!r})"
)
def get_save_image_path(
filename_prefix: str,
batch_number: int,
counter: int,
format_ext: str,
output_dir: str,
subfolder: str = "",
@@ -34,16 +94,21 @@ def get_save_image_path(
Args:
filename_prefix: Base filename prefix
batch_number: Batch index for multiple images
counter: Persistent counter to ensure unique filenames
format_ext: File extension (.png, .jpg, .webp)
output_dir: Output directory path
subfolder: Optional subfolder within output directory
Returns:
Tuple of (full_path, relative_filename)
Tuple of (full_path, preview_filename, relative_subfolder)
"""
# Split filename_prefix into directory path and actual filename prefix
# This allows for directory structures like "kittybear/anime/images/kittybear"
if os.path.isabs(filename_prefix) or os.path.isabs(subfolder or ""):
raise ValueError(
"Absolute paths are not allowed in filename_prefix or subfolder: "
f"{filename_prefix!r}"
)
prefix_dir = os.path.dirname(filename_prefix)
prefix_name = os.path.basename(filename_prefix)
@@ -53,9 +118,10 @@ def get_save_image_path(
) # Only sanitize problematic chars for filenames
safe_prefix = "".join(c for c in safe_prefix if c.isalnum() or c in "._-")
# Create unique filename with timestamp to avoid conflicts
timestamp = int(time.time())
filename = f"{safe_prefix}_{timestamp:010d}_{batch_number:05d}{format_ext}"
# Create unique filename with counter to avoid conflicts
# Using counter instead of timestamp+batch_number prevents overwrites
# when multiple images are processed separately
filename = f"{safe_prefix}_{counter:05d}{format_ext}"
# Handle subfolder and prefix directory (but not the filename part)
path_components = []
@@ -70,6 +136,9 @@ def get_save_image_path(
full_output_folder = os.path.join(*path_components)
# Reject anything that would resolve outside the output directory
_ensure_inside_output_dir(full_output_folder, output_dir, prefix_dir, subfolder)
# Ensure directory exists
os.makedirs(full_output_folder, exist_ok=True)
@@ -221,7 +290,7 @@ def process_image_batch(
popup: bool = True,
prompt: Optional[Dict] = None,
extra_pnginfo: Optional[Dict] = None,
) -> List[Dict[str, Any]]:
) -> Tuple[List[Dict[str, Any]], List[Dict[str, Any]]]:
"""
Process and save a batch of images with specified format settings
@@ -237,7 +306,7 @@ def process_image_batch(
extra_pnginfo: Additional PNG metadata
Returns:
List of saved image information dicts
Tuple of (ComfyUI preview result dicts, enhanced info dicts)
"""
# Get output directory
output_dir = folder_paths.get_output_directory()
@@ -262,13 +331,17 @@ def process_image_batch(
results = []
enhanced_data = []
for batch_number, image_tensor in enumerate(images):
for image_tensor in images:
# Convert tensor to PIL Image
img = convert_tensor_to_pil(image_tensor)
# Generate save path
# Get next counter value to ensure unique filenames
# This counter persists across node calls, preventing overwrites
counter = get_next_counter(output_dir, filename_prefix)
# Generate save path with persistent counter
filepath, preview_filename, relative_subfolder = get_save_image_path(
filename_prefix, batch_number, format_ext, output_dir, ""
filename_prefix, counter, format_ext, output_dir, ""
)
# Save with format-specific settings
@@ -0,0 +1,10 @@
"""
KikoWorkflow Timer - Display real-time execution timer for ComfyUI workflows.
Provides a visual timer that tracks workflow execution duration with
millisecond precision.
"""
from .node import KikoWorkflowTimerNode
__all__ = ["KikoWorkflowTimerNode"]
@@ -0,0 +1,52 @@
"""
KikoWorkflow Timer Node
A display-only node that shows real-time execution timing for ComfyUI workflows.
The timer is managed entirely on the frontend via WebSocket events.
"""
from ...base import ComfyAssetsBaseNode
class KikoWorkflowTimerNode(ComfyAssetsBaseNode):
"""
A UI node that displays a real-time timer for workflow execution.
The timer starts when execution begins and stops when the workflow
completes, showing the total elapsed time in MM:SS:mmm format.
This is a display-only node with no inputs or outputs - all timing
logic is handled by the JavaScript frontend via WebSocket events.
"""
DISPLAY_NAME = "Workflow Timer"
CATEGORY = "🫶 ComfyAssets/🛠️ Utils"
@classmethod
def INPUT_TYPES(cls):
return {
"required": {},
"hidden": {
"prompt": "PROMPT",
"unique_id": "UNIQUE_ID",
},
}
RETURN_TYPES = ()
FUNCTION = "execute"
OUTPUT_NODE = True
def execute(self, **kwargs):
"""
Execute method - returns empty since this is a display-only node.
The actual timer functionality is handled entirely by the JavaScript
frontend which hooks into ComfyUI's WebSocket events.
Args:
**kwargs: Hidden parameters (prompt, unique_id)
Returns:
Empty dict - no outputs
"""
return {}
@@ -0,0 +1,13 @@
"""Local Image Loader tool for KikoTools."""
from .node import LocalImageLoaderNode
NODE_CLASS_MAPPINGS = {
"KikoLocalImageLoader": LocalImageLoaderNode,
}
NODE_DISPLAY_NAME_MAPPINGS = {
"KikoLocalImageLoader": "Local Image Loader",
}
__all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS"]
+344
View File
@@ -0,0 +1,344 @@
"""Core logic for Local Image Loader."""
import os
import json
import torch
import numpy as np
from PIL import Image
from typing import Tuple, Dict, Any, List, Optional, Iterable
def get_supported_extensions() -> Dict[str, List[str]]:
"""Get supported file extensions by type."""
return {
"image": [".jpg", ".jpeg", ".png", ".bmp", ".gif", ".webp"],
"video": [".mp4", ".webm", ".mov", ".mkv", ".avi"],
"audio": [".mp3", ".wav", ".ogg", ".flac"],
}
def resolve_path(path: Any) -> Optional[str]:
"""Resolve a user supplied path with realpath (symlinks and ``..``).
Returns None for anything that is not a usable non-empty string.
"""
if not isinstance(path, str) or not path or "\0" in path:
return None
return os.path.realpath(path)
def is_within_roots(path: Any, roots: Iterable[Any]) -> bool:
"""Return True if the resolved path is inside (or equal to) one of the roots.
Uses os.path.commonpath on realpath-resolved values, so sibling
directories sharing a string prefix, ``..`` and symlinks cannot escape.
"""
real = resolve_path(path)
if real is None:
return False
for root in roots:
real_root = resolve_path(root)
if real_root is None:
continue
try:
if os.path.commonpath([real, real_root]) == real_root:
return True
except ValueError: # different drives / mixed absolute and relative
continue
return False
def is_too_broad_root(path: Any, home: Optional[str] = None) -> bool:
"""Return True if path is unusable or too broad to be a saved root.
Refuses filesystem/drive roots, the home directory itself and any
ancestor of it (e.g. /home), since those would expose every media file
a user owns. Folders inside home are fine.
"""
real = resolve_path(path)
if real is None:
return True
if os.path.dirname(real) == real: # "/" or a drive root like "C:\\"
return True
real_home = os.path.realpath(home or os.path.expanduser("~"))
try:
return os.path.commonpath([real, real_home]) == real
except ValueError: # different drives
return False
def is_allowed_media_path(
path: Any, roots: Iterable[Any], kinds: Iterable[str] = ("image",)
) -> bool:
"""Return True if path is a media file of the given kinds inside a root.
``kinds`` are keys of get_supported_extensions() (image/video/audio).
The extension is checked on the resolved path so a symlink named
``x.png`` pointing at a non-media file is refused.
"""
real = resolve_path(path)
if real is None:
return False
extensions = get_supported_extensions()
allowed = {e for k in kinds for e in extensions.get(k, [])}
if os.path.splitext(real)[1].lower() not in allowed:
return False
return is_within_roots(real, roots)
def is_allowed_image_path(path: Any, roots: Iterable[Any]) -> bool:
"""Return True if path is an image file located inside one of the roots."""
return is_allowed_media_path(path, roots, ("image",))
def list_subdirectories(path: str, limit: int = 50) -> List[str]:
"""List sub-directory paths (never files) for the folder picker.
If ``path`` ends with a separator, its child directories are returned;
otherwise sibling directories whose name starts with the last component.
May raise PermissionError.
"""
if path.endswith(os.sep) or (os.name == "nt" and path.endswith("/")):
parent_dir, prefix = path, ""
else:
parent_dir = os.path.dirname(path)
prefix = os.path.basename(path).lower()
if not parent_dir:
return []
if not os.path.isdir(parent_dir):
return []
dirs = [
os.path.join(parent_dir, entry)
for entry in os.listdir(parent_dir)
if entry.lower().startswith(prefix)
and os.path.isdir(os.path.join(parent_dir, entry))
]
dirs.sort(key=lambda x: x.lower())
return dirs[:limit]
def load_image_from_path(path: str) -> Tuple[torch.Tensor, Dict[str, Any]]:
"""
Load an image from the given path and convert it to a tensor.
Args:
path: Path to the image file
Returns:
Tuple of (image tensor, metadata dict)
"""
if not os.path.exists(path):
raise FileNotFoundError(f"File not found: {path}")
with Image.open(path) as img:
# Convert to appropriate format
if "A" in img.getbands():
img_out = img.convert("RGBA")
else:
img_out = img.convert("RGB")
# Convert to tensor
img_array = np.array(img_out).astype(np.float32) / 255.0
image_tensor = torch.from_numpy(img_array)[None,]
# Collect metadata
metadata = {
"filename": os.path.basename(path),
"width": img.width,
"height": img.height,
"mode": img.mode,
"format": img.format,
}
# Check for embedded metadata
if "parameters" in img.info:
metadata["parameters"] = img.info["parameters"]
if "prompt" in img.info:
try:
metadata["prompt"] = json.loads(img.info["prompt"])
except (json.JSONDecodeError, TypeError):
metadata["prompt"] = img.info["prompt"]
if "workflow" in img.info:
try:
metadata["workflow"] = json.loads(img.info["workflow"])
except (json.JSONDecodeError, TypeError):
metadata["workflow"] = img.info["workflow"]
return image_tensor, metadata
def scan_directory(
directory: str,
show_videos: bool = False,
show_audio: bool = False,
sort_by: str = "name",
sort_order: str = "asc",
hide_dot_folders: bool = True,
) -> List[Dict[str, Any]]:
"""
Scan a directory for supported media files.
Args:
directory: Directory path to scan
show_videos: Include video files
show_audio: Include audio files
sort_by: Sort criteria ('name', 'date', 'size')
sort_order: Sort order ('asc', 'desc')
hide_dot_folders: Hide folders starting with a dot
Returns:
List of file information dictionaries
"""
if not os.path.isdir(directory):
raise NotADirectoryError(f"Not a directory: {directory}")
extensions = get_supported_extensions()
items = []
for item in os.listdir(directory):
# Skip dot folders/files if hide_dot_folders is enabled
if hide_dot_folders and item.startswith("."):
continue
full_path = os.path.join(directory, item)
try:
stats = os.stat(full_path)
item_data = {
"path": full_path,
"name": item,
"mtime": stats.st_mtime,
"size": stats.st_size,
}
if os.path.isdir(full_path):
items.append({**item_data, "type": "dir"})
else:
ext = os.path.splitext(item)[1].lower()
item_type = None
if ext in extensions["image"]:
item_type = "image"
elif show_videos and ext in extensions["video"]:
item_type = "video"
elif show_audio and ext in extensions["audio"]:
item_type = "audio"
if item_type:
items.append({**item_data, "type": item_type})
except (PermissionError, FileNotFoundError):
continue
# Sort items
reverse = sort_order == "desc"
if sort_by == "date":
items.sort(key=lambda x: x["mtime"], reverse=reverse)
elif sort_by == "size":
items.sort(key=lambda x: x.get("size", 0), reverse=reverse)
else: # name
items.sort(key=lambda x: x["name"].lower(), reverse=reverse)
# Directories first
items.sort(key=lambda x: x["type"] != "dir")
return items
def search_files(
root_directory: str,
query: str,
show_videos: bool = False,
show_audio: bool = False,
max_results: int = 100,
) -> List[Dict[str, Any]]:
"""
Recursively search for files matching the query.
Args:
root_directory: Root directory to start search
query: Search query (case-insensitive filename match)
show_videos: Include video files
show_audio: Include audio files
max_results: Maximum number of results to return
Returns:
List of file information dictionaries
"""
if not os.path.isdir(root_directory):
raise NotADirectoryError(f"Not a directory: {root_directory}")
if not query or len(query.strip()) == 0:
return []
extensions = get_supported_extensions()
results = []
query_lower = query.lower().strip()
def search_recursive(directory: str) -> None:
"""Recursively search directory."""
if len(results) >= max_results:
return
try:
items = os.listdir(directory)
except (PermissionError, FileNotFoundError):
return
for item in items:
if len(results) >= max_results:
break
full_path = os.path.join(directory, item)
try:
# Check if item name matches query
if query_lower not in item.lower():
# If directory, search inside
if os.path.isdir(full_path):
search_recursive(full_path)
continue
stats = os.stat(full_path)
item_data = {
"path": full_path,
"name": item,
"directory": directory,
"mtime": stats.st_mtime,
"size": stats.st_size,
}
if os.path.isdir(full_path):
results.append({**item_data, "type": "dir"})
# Continue searching inside matching directories
search_recursive(full_path)
else:
ext = os.path.splitext(item)[1].lower()
item_type = None
if ext in extensions["image"]:
item_type = "image"
elif show_videos and ext in extensions["video"]:
item_type = "video"
elif show_audio and ext in extensions["audio"]:
item_type = "audio"
if item_type:
results.append({**item_data, "type": item_type})
except (PermissionError, FileNotFoundError):
continue
search_recursive(root_directory)
# Sort by name
results.sort(key=lambda x: x["name"].lower())
return results
def create_empty_tensor() -> torch.Tensor:
"""Create an empty tensor for when no image is selected."""
return torch.zeros(1, 1, 1, 4)
+409
View File
@@ -0,0 +1,409 @@
"""Local Image Loader node for ComfyUI."""
import io
import json
import logging
import os
from typing import Any, Dict, List, Tuple
import torch
from ...base.base_node import ComfyAssetsBaseNode
from .logic import (
create_empty_tensor,
is_allowed_image_path,
is_allowed_media_path,
is_too_broad_root,
is_within_roots,
list_subdirectories,
load_image_from_path,
resolve_path,
scan_directory,
)
try:
from aiohttp import web
except ImportError: # pragma: no cover - aiohttp ships with ComfyUI
web = None
logger = logging.getLogger(__name__)
MEDIA_KINDS = ("image", "video", "audio")
MAX_PER_PAGE = 200
DEFAULT_PER_PAGE = 50
MAX_DIRECTORY_SUGGESTIONS = 50
NODE_DIR = os.path.dirname(os.path.abspath(__file__))
SELECTIONS_FILE = os.path.join(NODE_DIR, "selections.json")
CONFIG_FILE = os.path.join(NODE_DIR, "config.json")
def load_selections() -> Dict[str, Any]:
"""Load node selections from file."""
if not os.path.exists(SELECTIONS_FILE):
return {}
try:
with open(SELECTIONS_FILE, "r", encoding="utf-8") as f:
return json.load(f)
except (json.JSONDecodeError, IOError):
return {}
def save_selections(data: Dict[str, Any]) -> None:
"""Save node selections to file."""
try:
with open(SELECTIONS_FILE, "w", encoding="utf-8") as f:
json.dump(data, f, indent=4, ensure_ascii=False)
except Exception as e:
logger.error("Error saving selections: %s", e)
def load_config() -> Dict[str, Any]:
"""Load configuration from file."""
if os.path.exists(CONFIG_FILE):
try:
with open(CONFIG_FILE, "r", encoding="utf-8") as f:
return json.load(f)
except (json.JSONDecodeError, IOError):
pass
return {}
def save_config(data: Dict[str, Any]) -> None:
"""Save configuration to file."""
try:
with open(CONFIG_FILE, "w", encoding="utf-8") as f:
json.dump(data, f, indent=4)
except Exception as e:
logger.error("Error saving config: %s", e)
def get_allowed_roots() -> List[str]:
"""Directories whose contents may be served: saved paths + ComfyUI in/out."""
roots: List[str] = []
saved = load_config().get("saved_paths", [])
if isinstance(saved, list):
# Skip broad roots saved before save_paths refused them
roots.extend(
p for p in saved if isinstance(p, str) and p and not is_too_broad_root(p)
)
try:
import folder_paths
for getter in ("get_input_directory", "get_output_directory"):
value = getattr(folder_paths, getter)()
if isinstance(value, str) and value:
roots.append(value)
except Exception: # folder_paths missing or misbehaving outside ComfyUI
pass
return roots
class LocalImageLoaderNode(ComfyAssetsBaseNode):
"""Node for loading images from local filesystem with a visual gallery interface."""
@classmethod
def INPUT_TYPES(cls) -> Dict[str, Any]:
"""Define input types for the node."""
return {
"required": {},
"hidden": {"unique_id": "UNIQUE_ID"},
}
RETURN_TYPES = (
"IMAGE",
"STRING",
)
RETURN_NAMES = (
"image",
"info",
)
FUNCTION = "load_media"
CATEGORY = "🫶 ComfyAssets/💾 Images"
@classmethod
def IS_CHANGED(cls, **kwargs):
"""Check if node state has changed."""
if os.path.exists(SELECTIONS_FILE):
return os.path.getmtime(SELECTIONS_FILE)
return float("inf")
def load_media(self, unique_id: str) -> Tuple[torch.Tensor, str]:
"""
Load selected media based on node's unique ID.
Args:
unique_id: Unique identifier for this node instance
Returns:
Tuple of (image tensor, info string)
"""
image_tensor = create_empty_tensor()
info_string = ""
selections = load_selections()
node_selections = selections.get(str(unique_id), {})
# Load image if selected
image_selection = node_selections.get("image")
if image_selection and image_selection.get("path"):
# Load the resolved path we validated, so a symlink swapped after
# the check can't redirect the read.
image_path = resolve_path(image_selection["path"])
if not is_allowed_image_path(image_path, get_allowed_roots()):
# selections.json may have been tampered with
logger.warning("Refusing to load disallowed path: %s", image_path)
elif os.path.exists(image_path):
try:
image_tensor, metadata = load_image_from_path(image_path)
info_string = json.dumps(metadata, indent=4, ensure_ascii=False)
except Exception as e:
logger.error("Error loading image: %s", e)
return (image_tensor, info_string)
# ---------------------------------------------------------------------------
# API route handlers (module level so they can be tested without a server)
# ---------------------------------------------------------------------------
def _error(status: int, message: str):
return web.json_response({"status": "error", "error": message}, status=status)
def _check_file(filepath: Any, kinds: Tuple[str, ...] = ("image",)):
"""Validate a requested file. Returns (resolved_path, error_response)."""
if not isinstance(filepath, str) or not filepath or "\0" in filepath:
return None, web.Response(status=400)
real = resolve_path(filepath)
if not is_allowed_media_path(real, get_allowed_roots(), kinds):
return None, web.Response(status=403)
if not os.path.isfile(real):
return None, web.Response(status=404)
return real, None
def _parse_paging(query) -> Tuple[int, int]:
"""Parse page/per_page; raises ValueError on garbage."""
page = int(query.get("page", 1))
per_page = int(query.get("per_page", DEFAULT_PER_PAGE))
if page < 1:
raise ValueError("page must be >= 1")
return page, max(1, min(per_page, MAX_PER_PAGE))
async def set_node_selection(request):
"""Store the selected image for a node (image files in allowed roots only)."""
try:
data = await request.json()
except Exception:
return _error(400, "Invalid JSON.")
if not isinstance(data, dict):
return _error(400, "Invalid payload.")
node_id = data.get("node_id")
path = data.get("path")
media_type = data.get("type")
if (
node_id is None
or not isinstance(path, str)
or not path
or "\0" in path
or not isinstance(media_type, str)
or not media_type
):
return _error(400, "Missing required data.")
# The frontend also selects video/audio; load_media only ever reads images.
if not is_allowed_media_path(path, get_allowed_roots(), MEDIA_KINDS):
return _error(403, "Path not allowed.")
selections = load_selections()
selections.setdefault(str(node_id), {})[media_type] = {"path": path}
save_selections(selections)
return web.json_response({"status": "ok"})
async def get_saved_paths(request):
"""Return saved directory paths."""
return web.json_response({"saved_paths": load_config().get("saved_paths", [])})
async def save_paths(request):
"""Persist the list of saved directory paths."""
try:
data = await request.json()
except Exception:
return _error(400, "Invalid JSON.")
paths = data.get("paths", []) if isinstance(data, dict) else None
if not isinstance(paths, list) or not all(isinstance(p, str) for p in paths):
return _error(400, "paths must be a list of strings.")
too_broad = [p for p in paths if is_too_broad_root(p)]
if too_broad:
return _error(
400,
f"Folder too broad to share: {', '.join(too_broad)}. "
"Pick a folder inside your home directory or another media folder.",
)
config = load_config()
config["saved_paths"] = paths
save_config(config)
return web.json_response({"status": "ok"})
async def get_local_images(request):
"""List images and sub-directories of a directory inside an allowed root."""
query = request.query
directory = query.get("directory", "")
if not directory or "\0" in directory:
return _error(400, "Directory is required.")
try:
page, per_page = _parse_paging(query)
except ValueError:
return _error(400, "Invalid page or per_page.")
if not is_within_roots(directory, get_allowed_roots()):
return _error(403, "Directory not allowed.")
real = resolve_path(directory)
if not os.path.isdir(real):
return _error(404, "Directory not found.")
# Normalize path (trailing slashes etc.) but keep the user-visible spelling
directory = os.path.normpath(directory)
config = load_config()
config["last_path"] = directory
save_config(config)
show_videos = query.get("show_videos", "false").lower() == "true"
show_audio = query.get("show_audio", "false").lower() == "true"
hide_dot_folders = query.get("hide_dot_folders", "true").lower() == "true"
try:
items = scan_directory(
directory,
show_videos,
show_audio,
query.get("sort_by", "name"),
query.get("sort_order", "asc"),
hide_dot_folders,
)
except Exception:
logger.exception("Error scanning directory %s", directory)
return _error(500, "Error reading directory.")
# Do not offer navigation above the allowed roots
parent_directory = os.path.dirname(directory)
if parent_directory == directory or not is_within_roots(
parent_directory, get_allowed_roots()
):
parent_directory = None
start = (page - 1) * per_page
return web.json_response(
{
"items": items[start : start + per_page],
"total_pages": (len(items) + per_page - 1) // per_page,
"current_page": page,
"current_directory": directory,
"parent_directory": parent_directory,
}
)
async def get_last_path(request):
"""Return the last used directory path."""
return web.json_response({"last_path": load_config().get("last_path", "")})
async def list_directories(request):
"""List directory names for the folder-picker autocomplete.
Trade-off: this is how users browse to a location that is not yet a saved
root, so it is intentionally NOT restricted to the allowed roots. It only
ever returns directory paths (never files), capped at
MAX_DIRECTORY_SUGGESTIONS; file contents stay protected by the root and
extension checks on every other route.
"""
path = request.query.get("path", "")
if "\0" in path:
return web.json_response({"directories": []})
try:
if not path:
if os.name == "nt":
import string
drives = [
f"{d}:\\"
for d in string.ascii_uppercase
if os.path.exists(f"{d}:\\")
]
return web.json_response({"directories": drives})
return web.json_response({"directories": [os.sep]})
dirs = list_subdirectories(os.path.expanduser(path), MAX_DIRECTORY_SUGGESTIONS)
return web.json_response({"directories": dirs})
except PermissionError:
return web.json_response({"directories": [], "error": "Permission denied"})
except Exception:
logger.exception("Error listing directories for %s", path)
return web.json_response(
{"directories": [], "error": "Error listing directories"}
)
async def get_thumbnail(request):
"""Return a thumbnail of an allowed image."""
real, error = _check_file(request.query.get("filepath"))
if error is not None:
return error
try:
from PIL import Image
with Image.open(real) as img:
has_alpha = img.mode == "RGBA" or (
img.mode == "P" and "transparency" in img.info
)
img = img.convert("RGBA") if has_alpha else img.convert("RGB")
img.thumbnail([320, 320], Image.LANCZOS)
buffer = io.BytesIO()
fmt, content_type = (
("PNG", "image/png") if has_alpha else ("JPEG", "image/jpeg")
)
img.save(buffer, format=fmt, quality=90 if fmt == "JPEG" else None)
return web.Response(body=buffer.getvalue(), content_type=content_type)
except Exception:
logger.exception("Error generating thumbnail for %s", real)
return web.Response(status=500)
async def view_image(request):
"""Serve a full-size allowed media file (image, video or audio)."""
real, error = _check_file(request.query.get("filepath"), MEDIA_KINDS)
if error is not None:
return error
return web.FileResponse(real)
# Setup API routes
try:
import server
prompt_server = server.PromptServer.instance
_routes = prompt_server.routes
_prefix = "/kiko_local_image_loader"
_routes.post(f"{_prefix}/set_node_selection")(set_node_selection)
_routes.get(f"{_prefix}/get_saved_paths")(get_saved_paths)
_routes.post(f"{_prefix}/save_paths")(save_paths)
_routes.get(f"{_prefix}/images")(get_local_images)
_routes.get(f"{_prefix}/get_last_path")(get_last_path)
_routes.get(f"{_prefix}/list_directories")(list_directories)
_routes.get(f"{_prefix}/thumbnail")(get_thumbnail)
_routes.get(f"{_prefix}/view")(view_image)
except ImportError:
# Server not available during testing
pass
@@ -0,0 +1,13 @@
"""Model Downloader Tool for ComfyUI-KikoTools
Downloads models from CivitAI, HuggingFace, and custom URLs.
"""
from .node import ModelDownloaderNode
__all__ = ["ModelDownloaderNode"]
# Node registration
NODE_CLASS_MAPPINGS = {"KikoModelDownloader": ModelDownloaderNode}
NODE_DISPLAY_NAME_MAPPINGS = {"KikoModelDownloader": "Model Downloader 🌐"}
+483
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@@ -0,0 +1,483 @@
"""Base downloader class with common functionality"""
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Any, Callable, List, Optional, Sequence, Union
from urllib.parse import urlparse, unquote
import logging
import os
import re
import sys
import time
import urllib.error
import urllib.request
logger = logging.getLogger(__name__)
DOWNLOAD_TIMEOUT = 60 # seconds, applied to every network operation
CHUNK_SIZE = 1638400
USER_AGENT = "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"
ALLOWED_SCHEMES = ("http", "https")
PART_SUFFIX = ".part"
# Only model weights and inert data files may be written; never code.
ALLOWED_FILE_EXTENSIONS = frozenset(
{
".safetensors",
".sft",
".ckpt",
".pt",
".pt2",
".pth",
".bin",
".gguf",
".onnx",
".model",
".json",
".yaml",
".yml",
".txt",
}
)
# folder_paths entries that hold code rather than models.
EXCLUDED_FOLDER_NAMES = frozenset({"custom_nodes"})
try:
import comfy.model_management
COMFY_AVAILABLE = True
except ImportError:
COMFY_AVAILABLE = False
def validate_url_scheme(url: str) -> None:
"""Raise ValueError unless url uses an allowed scheme (http/https)."""
scheme = urlparse(url or "").scheme.lower()
if scheme not in ALLOWED_SCHEMES:
raise ValueError(
f"Unsupported URL scheme '{scheme}'. Only http and https are allowed."
)
def validate_filename(name: Optional[str]) -> str:
"""Validate a user-supplied filename.
Raises:
ValueError: If the name is empty, a dot name, or contains path parts.
"""
if (
not name
or name in (".", "..")
or os.path.basename(name) != name
or "/" in name
or "\\" in name
or "\x00" in name
):
raise ValueError(f"Invalid filename: {name!r}")
return name
def safe_server_filename(name: Optional[str], default: str) -> str:
"""Reduce a server-derived filename to a safe basename, or use default."""
if name:
candidate = os.path.basename(name.replace("\\", "/"))
try:
return validate_filename(candidate)
except ValueError:
pass
return default
class _SafeRedirectHandler(urllib.request.HTTPRedirectHandler):
"""Only follow http(s) redirects and drop credentials on cross-host hops."""
def redirect_request(self, req, fp, code, msg, headers, newurl):
if urlparse(newurl).scheme.lower() not in ALLOWED_SCHEMES:
raise urllib.error.HTTPError(
newurl, code, "Redirect to disallowed URL scheme", headers, fp
)
new_request = super().redirect_request(req, fp, code, msg, headers, newurl)
if new_request is not None and (
urlparse(newurl).netloc.lower() != urlparse(req.full_url).netloc.lower()
):
new_request.remove_header("Authorization")
return new_request
class _NoRedirectProcessor(urllib.request.HTTPErrorProcessor):
"""Return every response as-is so redirects can be handled manually."""
def http_response(self, request, response):
return response
https_response = http_response
def _folder_paths():
"""Return the folder_paths module, or None when unavailable."""
try:
import folder_paths
return folder_paths
except ImportError:
return None
def _default_model_roots() -> List[str]:
"""Return ComfyUI's models dir plus every registered model folder.
Covers extra_model_paths.yaml entries on other drives.
"""
fp = _folder_paths()
if fp is None:
return []
roots: List[str] = []
models_dir = getattr(fp, "models_dir", None)
if isinstance(models_dir, str) and models_dir:
roots.append(models_dir)
registry = getattr(fp, "folder_names_and_paths", None)
if isinstance(registry, dict):
for name, entry in registry.items():
if name in EXCLUDED_FOLDER_NAMES:
continue
try:
paths = entry[0]
except (TypeError, IndexError, KeyError):
continue
if isinstance(paths, (list, tuple)):
roots.extend(p for p in paths if isinstance(p, str) and p)
return roots
def _default_base_path() -> Optional[str]:
"""Return ComfyUI's base path used to resolve relative save paths."""
fp = _folder_paths()
base = getattr(fp, "base_path", None) if fp is not None else None
return base if isinstance(base, str) and base else None
class BaseDownloader(ABC):
"""Abstract base class for all downloaders"""
def __init__(
self,
token: Optional[str] = None,
models_root: Union[str, Sequence[str], None] = None,
):
"""Initialize downloader with optional API token
Args:
token: Optional API token for authentication
models_root: Directory (or list of directories) downloads must
stay inside. Defaults to ComfyUI's models directory plus all
registered model folders.
"""
self.token = token
if isinstance(models_root, str):
models_root = [models_root]
self._models_root = list(models_root) if models_root else None
self._progress_callback: Optional[Callable[[int, int, str], None]] = None
def set_progress_callback(self, callback: Callable[[int, int, str], None]) -> None:
"""Set callback function for progress updates
Args:
callback: Function(downloaded_bytes, total_bytes, message)
"""
self._progress_callback = callback
def report_progress(self, downloaded: int, total: int, message: str = "") -> None:
"""Report download progress to callback
Args:
downloaded: Bytes downloaded so far
total: Total bytes to download
message: Optional status message
"""
if self._progress_callback:
self._progress_callback(downloaded, total, message)
def check_interrupt(self) -> None:
"""Check if processing has been interrupted by user
Raises:
comfy.model_management.InterruptProcessingException: If user cancelled
"""
if COMFY_AVAILABLE:
comfy.model_management.throw_exception_if_processing_interrupted()
def extract_filename(self, url: str, default: str = "downloaded_file") -> str:
"""Extract filename from URL
Args:
url: URL to extract filename from
default: Default filename if extraction fails
Returns:
Extracted or default filename
"""
try:
parsed = urlparse(url)
path = unquote(parsed.path)
filename = os.path.basename(path)
# Remove query parameters from filename
if "?" in filename:
filename = filename.split("?")[0]
# Validate filename
if filename and len(filename) > 0 and "." in filename:
return filename
except Exception:
pass
return default
def extract_filename_from_header(self, content_disposition: str) -> Optional[str]:
"""Extract filename from Content-Disposition header
Args:
content_disposition: Content-Disposition header value
Returns:
Extracted filename or None
"""
if not content_disposition:
return None
match = re.search(r"filename\*\s*=\s*[^']*'[^']*'([^;]+)", content_disposition)
if match:
return unquote(match.group(1).strip()) or None
match = re.search(
r'filename\s*=\s*(?:"([^"]*)"|\'([^\']*)\'|([^;]+))', content_disposition
)
if match:
value = next(g for g in match.groups() if g is not None)
return value.strip() or None
return None
@staticmethod
def _is_within(path: str, root: str) -> bool:
try:
return os.path.commonpath([root, path]) == root
except ValueError: # different drives
return False
def resolve_output_dir(self, output_path: str) -> str:
"""Resolve output_path and ensure it lives inside the models root.
Returns:
Real (symlink-resolved) directory path, created if missing.
Raises:
ValueError: If the path escapes the models directory.
"""
roots = self._models_root or _default_model_roots()
if not roots:
raise ValueError("Models directory is unavailable; refusing to download")
if not os.path.isabs(output_path):
output_path = os.path.join(_default_base_path() or os.getcwd(), output_path)
real_dir = os.path.realpath(output_path)
real_roots = [os.path.realpath(r) for r in roots]
if not any(self._is_within(real_dir, r) for r in real_roots):
raise ValueError(
f"Save path must be inside a ComfyUI models directory "
f"({', '.join(real_roots)})"
)
self.validate_output_path(real_dir)
return real_dir
def open_url(self, request: urllib.request.Request, follow_redirects: bool = True):
"""Open a request with scheme checks, timeout and safe redirects."""
validate_url_scheme(request.full_url)
handler = _SafeRedirectHandler if follow_redirects else _NoRedirectProcessor
opener = urllib.request.build_opener(handler)
return opener.open(request, timeout=DOWNLOAD_TIMEOUT)
@staticmethod
def parse_content_length(response: Any) -> Optional[int]:
"""Return Content-Length as int, or None if absent/invalid."""
value = response.getheader("Content-Length")
try:
return int(value) if value is not None else None
except (TypeError, ValueError):
return None
def save_response(
self,
response: Any,
output_file: str,
total_size: Optional[int],
strict_size: bool = True,
) -> str:
"""Stream response to output_file atomically via a .part file.
The .part file is removed on any failure (including interrupts).
Raises:
ValueError: If output_file is not a model/data file type.
"""
extension = os.path.splitext(output_file)[1].lower()
if extension not in ALLOWED_FILE_EXTENSIONS:
raise ValueError(
f"Refusing to save file type '{extension or 'none'}': "
f"only model files ({', '.join(sorted(ALLOWED_FILE_EXTENSIONS))})"
)
part_file = output_file + PART_SUFFIX
try:
downloaded = 0
start_time = time.time()
with open(part_file, "wb") as f:
while True:
chunk_start = time.time()
buffer = response.read(CHUNK_SIZE)
chunk_time = time.time() - chunk_start
if not buffer:
break
downloaded += len(buffer)
f.write(buffer)
self.check_interrupt()
speed = self.calculate_speed(len(buffer), chunk_time)
self._report_chunk(downloaded, total_size, speed)
sys.stdout.write("\n")
actual_size = os.path.getsize(part_file)
if total_size and actual_size != total_size:
message = (
f"Download incomplete. Expected {total_size} bytes, "
f"got {actual_size} bytes"
)
if strict_size:
raise Exception(message)
logger.warning(message)
os.replace(part_file, output_file)
logger.info(
"Download completed in %.0fs: %s", time.time() - start_time, output_file
)
return output_file
except BaseException:
if os.path.exists(part_file):
os.remove(part_file)
raise
finally:
close = getattr(response, "close", None)
if callable(close):
close()
def _report_chunk(
self, downloaded: int, total_size: Optional[int], speed: float
) -> None:
"""Write console progress and notify the callback."""
if total_size:
progress = downloaded / total_size
sys.stdout.write(
f'\r[{"=" * int(progress * 50):<50}] {progress * 100:.2f}% - {speed:.2f} MB/s'
)
self.report_progress(downloaded, total_size, f"{speed:.2f} MB/s")
else:
sys.stdout.write(
f"\rDownloaded: {self.format_size(downloaded)} - {speed:.2f} MB/s"
)
self.report_progress(downloaded, 0, f"{speed:.2f} MB/s")
sys.stdout.flush()
def raise_for_http_status(self, code: int, reason: str, hints: dict) -> None:
"""Raise a friendly Exception for an HTTP error status."""
message = hints.get(code)
if message is None and code == 429:
message = "Rate limited. Please wait a moment before trying again."
raise Exception(message or f"HTTP error {code}: {reason}")
def validate_output_path(self, output_path: str) -> bool:
"""Validate and create output path if needed
Args:
output_path: Directory path to validate
Returns:
True if valid
Raises:
ValueError: If path exists but is not a directory
"""
path = Path(output_path)
if path.exists():
if not path.is_dir():
raise ValueError(
f"Output path {output_path} exists but is not a directory"
)
return True
# Create directory if it doesn't exist
path.mkdir(parents=True, exist_ok=True)
return True
def should_download(self, file_path: str, force: bool = False) -> bool:
"""Check if file should be downloaded
Args:
file_path: Full path to file
force: Force download even if file exists
Returns:
True if should download, False if file exists and force=False
"""
if force:
return True
return not Path(file_path).exists()
def format_size(self, size_bytes: int) -> str:
"""Format file size in human-readable format
Args:
size_bytes: Size in bytes
Returns:
Formatted size string (e.g., "5.00 MB")
"""
for unit in ["B", "KB", "MB", "GB"]:
if size_bytes < 1024.0:
return f"{size_bytes:.2f} {unit}"
size_bytes /= 1024.0
return f"{size_bytes:.2f} TB"
def calculate_speed(self, bytes_downloaded: int, elapsed_seconds: float) -> float:
"""Calculate download speed in MB/s
Args:
bytes_downloaded: Number of bytes downloaded
elapsed_seconds: Time elapsed in seconds
Returns:
Download speed in MB/s
"""
if elapsed_seconds <= 0:
return 0.0
mb_downloaded = bytes_downloaded / (1024 * 1024)
return mb_downloaded / elapsed_seconds
@abstractmethod
def download(
self,
url: str,
output_path: str,
filename: Optional[str] = None,
force: bool = False,
) -> str:
"""Download file from URL
Args:
url: URL to download from
output_path: Directory to save file
filename: Optional filename override
force: Force re-download if file exists
Returns:
Path to downloaded file
Raises:
NotImplementedError: Must be implemented by subclass
"""
raise NotImplementedError("Subclasses must implement download()")
+238
View File
@@ -0,0 +1,238 @@
"""CivitAI downloader implementation"""
import json
import logging
import os
import urllib.request
import urllib.parse
import urllib.error
from typing import Optional, Dict, Any
from urllib.parse import urlparse, parse_qs, unquote, urljoin
from .base import (
USER_AGENT,
BaseDownloader,
safe_server_filename,
validate_filename,
validate_url_scheme,
)
logger = logging.getLogger(__name__)
API_BASE = "https://civitai.com/api/v1"
REDIRECT_STATUSES = (301, 302, 303, 307, 308)
HTTP_ERROR_HINTS = {
401: "Authentication required. Please provide a valid API token.",
403: "Access forbidden. The model might be restricted or require special permissions.",
404: "Model not found. The URL might be incorrect or the model was removed.",
}
class CivitAIDownloader(BaseDownloader):
"""Downloader for CivitAI models"""
def _make_request(
self, url: str, headers: Optional[Dict[str, str]] = None
) -> urllib.request.Request:
"""Create HTTP request with authentication
Args:
url: URL to request
headers: Optional additional headers
Returns:
urllib Request object
"""
if headers is None:
headers = {}
headers["User-Agent"] = USER_AGENT
if self.token:
headers["Authorization"] = f"Bearer {self.token}"
return urllib.request.Request(url, headers=headers)
def _parse_civitai_url(self, url: str) -> Dict[str, Optional[int]]:
"""Extract model and version IDs from CivitAI URL
Args:
url: CivitAI URL to parse
Returns:
Dict with 'model_id' and 'version_id' keys
"""
parsed = urlparse(url)
result = {"model_id": None, "version_id": None}
# Handle different URL patterns
# 1. Direct API download URL: /api/download/models/123456
if "/api/download/models/" in url:
match = url.split("/api/download/models/")[-1].split("?")[0]
if match.isdigit():
result["version_id"] = int(match)
return result
# 2. Model page URL: /models/123456 or /models/123456/model-name
if "/models/" in url:
parts = parsed.path.split("/")
if "models" in parts:
idx = parts.index("models")
if idx + 1 < len(parts) and parts[idx + 1].isdigit():
result["model_id"] = int(parts[idx + 1])
# 3. Version specific URL with ?modelVersionId=789012
query_params = parse_qs(parsed.query)
if "modelVersionId" in query_params:
version_id = query_params["modelVersionId"][0]
if version_id.isdigit():
result["version_id"] = int(version_id)
return result
def get_model_details(self, model_id: int) -> Dict[str, Any]:
"""Get model details from API
Args:
model_id: CivitAI model ID
Returns:
Model details dictionary
Raises:
Exception: If API request fails
"""
url = f"{API_BASE}/models/{model_id}"
request = self._make_request(url)
try:
with self.open_url(request) as response:
return json.loads(response.read().decode())
except urllib.error.HTTPError as e:
if e.code == 404:
raise Exception(f"Model {model_id} not found")
raise Exception(f"API request failed: {e}")
def download(
self,
url: str,
output_path: str,
filename: Optional[str] = None,
force: bool = False,
) -> str:
"""Download file from CivitAI
Args:
url: CivitAI URL to download
output_path: Directory to save file
filename: Optional filename override
force: Force re-download if file exists
Returns:
Path to downloaded file
Raises:
Exception: If download fails
"""
validate_url_scheme(url)
if filename:
validate_filename(filename)
output_dir = self.resolve_output_dir(output_path)
# Validate that URL is from civitai.com domain
parsed_url = urlparse(url)
if parsed_url.netloc not in ("civitai.com", "www.civitai.com"):
raise ValueError(
f"Invalid URL: Only civitai.com URLs are supported, got {parsed_url.netloc}"
)
# Convert web URL to API URL if needed
if "/api/download/models/" not in url:
ids = self._parse_civitai_url(url)
# If we have a version ID, use it directly
if ids["version_id"]:
url = f"https://civitai.com/api/download/models/{ids['version_id']}"
# If we only have a model ID, get the latest version
elif ids["model_id"]:
try:
model_details = self.get_model_details(ids["model_id"])
if model_details.get("modelVersions"):
version_id = model_details["modelVersions"][0]["id"]
url = f"https://civitai.com/api/download/models/{version_id}"
else:
raise Exception(
f"No versions found for model {ids['model_id']}"
)
except Exception as e:
raise Exception(f"Failed to get model details: {e}")
else:
raise Exception("Could not parse model or version ID from URL")
headers = {"User-Agent": USER_AGENT}
if self.token:
headers["Authorization"] = f"Bearer {self.token}"
request = urllib.request.Request(url, headers=headers)
try:
response = self.open_url(request, follow_redirects=False)
except urllib.error.HTTPError as e:
self.raise_for_http_status(e.code, e.reason, HTTP_ERROR_HINTS)
except urllib.error.URLError as e:
raise Exception(f"Network error: {e.reason}")
if response.status in REDIRECT_STATUSES:
redirect_url = response.getheader("Location")
response.close()
if not redirect_url:
raise Exception("Redirect response did not include a Location header")
redirect_url = urljoin(url, redirect_url)
validate_url_scheme(redirect_url)
if not filename:
filename = self._filename_from_redirect(redirect_url)
# The signed redirect target gets no credentials
try:
response = self.open_url(
urllib.request.Request(
redirect_url, headers={"User-Agent": USER_AGENT}
)
)
except urllib.error.HTTPError as e:
self.raise_for_http_status(e.code, e.reason, HTTP_ERROR_HINTS)
except urllib.error.URLError as e:
raise Exception(f"Network error: {e.reason}")
elif response.status != 200:
code = response.status
response.close()
self.raise_for_http_status(
code, "Download failed", {**HTTP_ERROR_HINTS, 404: "File not found"}
)
if not filename:
filename = safe_server_filename(
self.extract_filename(url, default="model.safetensors"),
"model.safetensors",
)
output_file = os.path.join(output_dir, filename)
if not self.should_download(output_file, force):
response.close()
logger.info("File already exists: %s", output_file)
return output_file
total_size = self.parse_content_length(response)
logger.info("Downloading %s to %s", filename, output_file)
return self.save_response(response, output_file, total_size)
def _filename_from_redirect(self, redirect_url: str) -> str:
"""Derive a safe filename from a CivitAI redirect URL."""
parsed = urlparse(redirect_url)
disposition = parse_qs(parsed.query).get("response-content-disposition", [""])[
0
]
name = self.extract_filename_from_header(unquote(disposition))
if not name:
name = parsed.path.rsplit("/", 1)[-1]
return safe_server_filename(name, "downloaded_file.safetensors")
@@ -0,0 +1,98 @@
"""Custom URL downloader - best effort for direct download links"""
import logging
import os
import urllib.error
import urllib.request
from typing import Optional
from .base import (
USER_AGENT,
BaseDownloader,
safe_server_filename,
validate_filename,
validate_url_scheme,
)
logger = logging.getLogger(__name__)
DEFAULT_FILENAME = "downloaded_model.safetensors"
HTTP_ERROR_HINTS = {
401: "Authentication required. Please provide a valid token if needed.",
403: "Access forbidden. The URL might require authentication or special permissions.",
404: "File not found. Please check the URL.",
}
class CustomDownloader(BaseDownloader):
"""Best-effort downloader for custom/direct URLs
The optional token is sent as a Bearer token and is dropped automatically
if the server redirects to a different host.
"""
def download(
self,
url: str,
output_path: str,
filename: Optional[str] = None,
force: bool = False,
) -> str:
"""Download file from custom URL
Args:
url: Direct download URL (http or https)
output_path: Directory to save file (must be inside models dir)
filename: Optional filename override (plain name, no path parts)
force: Force re-download if file exists
Returns:
Path to downloaded file
Raises:
ValueError: For bad scheme, filename or save path
Exception: If download fails
"""
validate_url_scheme(url)
if filename:
validate_filename(filename)
output_dir = self.resolve_output_dir(output_path)
# Fast path: a known filename lets us skip the request entirely
if filename:
output_file = os.path.join(output_dir, filename)
if not self.should_download(output_file, force):
logger.info("File already exists: %s", output_file)
return output_file
headers = {"User-Agent": USER_AGENT}
if self.token:
headers["Authorization"] = f"Bearer {self.token}"
request = urllib.request.Request(url, headers=headers)
try:
response = self.open_url(request)
except urllib.error.HTTPError as e:
self.raise_for_http_status(e.code, e.reason, HTTP_ERROR_HINTS)
except urllib.error.URLError as e:
raise Exception(f"Network error: {e.reason}")
if not filename:
header_name = self.extract_filename_from_header(
response.getheader("Content-Disposition") or ""
)
filename = safe_server_filename(
header_name, self.extract_filename(url, default=DEFAULT_FILENAME)
)
output_file = os.path.join(output_dir, filename)
if not self.should_download(output_file, force):
response.close()
logger.info("File already exists: %s", output_file)
return output_file
total_size = self.parse_content_length(response)
logger.info("Downloading %s to %s", filename, output_file)
# Size mismatch is only a warning for arbitrary URLs
return self.save_response(response, output_file, total_size, strict_size=False)
@@ -0,0 +1,137 @@
"""URL detection and downloader selection logic"""
from __future__ import annotations
from enum import Enum
from typing import TYPE_CHECKING, Optional
from urllib.parse import urlparse
if TYPE_CHECKING:
from .base import BaseDownloader
class DownloaderType(Enum):
"""Types of supported downloaders"""
CIVITAI = "civitai"
HUGGINGFACE = "huggingface"
CUSTOM = "custom"
class URLDetector:
"""Detects URL type and returns appropriate downloader"""
def detect(self, url: Optional[str]) -> DownloaderType:
"""Detect which downloader to use based on URL
Args:
url: URL to analyze
Returns:
DownloaderType enum value
Raises:
ValueError: If URL is invalid or empty
"""
if not url:
raise ValueError("URL cannot be empty")
url = url.strip()
if not url:
raise ValueError("URL cannot be empty")
try:
parsed = urlparse(url)
if not parsed.scheme or not parsed.netloc:
raise ValueError("Invalid URL format")
except Exception:
raise ValueError("Invalid URL")
# Check for CivitAI
if self._is_civitai_url(url, parsed):
return DownloaderType.CIVITAI
# Check for HuggingFace
if self._is_huggingface_url(url, parsed):
return DownloaderType.HUGGINGFACE
# Default to custom downloader
return DownloaderType.CUSTOM
def _is_civitai_url(self, url: str, parsed) -> bool:
"""Check if URL is from CivitAI
Args:
url: Full URL string
parsed: Parsed URL object
Returns:
True if CivitAI URL
"""
# Validate exact domain match to prevent subdomain attacks
if parsed.netloc not in ("civitai.com", "www.civitai.com"):
return False
# Check for API download endpoint
if "/api/download/models/" in url:
return True
# Check for model page
if "/models/" in url:
return True
return False
def _is_huggingface_url(self, url: str, parsed) -> bool:
"""Check if URL is from HuggingFace
Args:
url: Full URL string
parsed: Parsed URL object
Returns:
True if HuggingFace URL
"""
# Validate exact domain match to prevent subdomain attacks
# Support both main domain and CDN domains
allowed_domains = (
"huggingface.co",
"www.huggingface.co",
"cdn.huggingface.co",
"cdn-lfs.huggingface.co",
)
if parsed.netloc in allowed_domains:
return True
return False
def get_downloader(
self, url: str, api_token: Optional[str] = None
) -> "BaseDownloader":
"""Get appropriate downloader instance for URL
Args:
url: URL to download from
api_token: Optional API token for authentication
Returns:
Appropriate downloader instance
Raises:
ValueError: If URL is invalid
"""
downloader_type = self.detect(url)
if downloader_type == DownloaderType.CIVITAI:
from .civitai import CivitAIDownloader
return CivitAIDownloader(token=api_token)
elif downloader_type == DownloaderType.HUGGINGFACE:
from .huggingface import HuggingFaceDownloader
return HuggingFaceDownloader(token=api_token)
else: # CUSTOM
from .custom import CustomDownloader
return CustomDownloader(token=api_token)
@@ -0,0 +1,161 @@
"""HuggingFace downloader implementation"""
import logging
import os
import urllib.request
import urllib.error
from typing import Optional
from urllib.parse import urlparse, quote
from .base import (
USER_AGENT,
BaseDownloader,
safe_server_filename,
validate_filename,
validate_url_scheme,
)
logger = logging.getLogger(__name__)
HTTP_ERROR_HINTS = {
401: "Authentication required. Please provide a valid HuggingFace token.",
403: "Access forbidden. The model might be gated or require special permissions.",
404: "File not found. The URL might be incorrect or the file was removed.",
}
class HuggingFaceDownloader(BaseDownloader):
"""Downloader for HuggingFace models"""
def _parse_huggingface_url(self, url: str) -> dict:
"""Parse HuggingFace URL to extract repo and file information
Args:
url: HuggingFace URL
Returns:
Dict with 'repo_id', 'filename', 'revision' keys
"""
parsed = urlparse(url)
parts = parsed.path.strip("/").split("/")
result = {"repo_id": None, "filename": None, "revision": "main"}
# Handle blob URLs (web UI format) - convert to resolve format
# /{username}/{repo}/blob/{revision}/{file_path}
if len(parts) >= 5 and "blob" in parts:
blob_idx = parts.index("blob")
if blob_idx >= 2:
# Extract repo_id (username/repo)
result["repo_id"] = "/".join(parts[:blob_idx])
# Extract revision
if blob_idx + 1 < len(parts):
result["revision"] = parts[blob_idx + 1]
# Extract filename (everything after revision)
if blob_idx + 2 < len(parts):
result["filename"] = "/".join(parts[blob_idx + 2 :])
# Standard HF URL format: /{username}/{repo}/resolve/{revision}/{file_path}
elif len(parts) >= 5 and "resolve" in parts:
resolve_idx = parts.index("resolve")
if resolve_idx >= 2:
# Extract repo_id (username/repo)
result["repo_id"] = "/".join(parts[:resolve_idx])
# Extract revision
if resolve_idx + 1 < len(parts):
result["revision"] = parts[resolve_idx + 1]
# Extract filename (everything after revision)
if resolve_idx + 2 < len(parts):
result["filename"] = "/".join(parts[resolve_idx + 2 :])
# Alternative CDN format: Extract what we can
elif "cdn" in parsed.netloc:
# CDN URLs might have different structure
# Try to extract filename from path
if len(parts) > 0:
result["filename"] = parts[-1]
return result
def _construct_download_url(
self, repo_id: str, filename: str, revision: str = "main"
) -> str:
"""Construct HuggingFace download URL
Args:
repo_id: Repository ID (username/repo)
filename: File path within repo
revision: Branch/tag/commit (default: main)
Returns:
Download URL
"""
# URL encode the filename to handle special characters
encoded_filename = quote(filename, safe="/")
return f"https://huggingface.co/{repo_id}/resolve/{revision}/{encoded_filename}"
def download(
self,
url: str,
output_path: str,
filename: Optional[str] = None,
force: bool = False,
) -> str:
"""Download file from HuggingFace
Args:
url: HuggingFace URL to download (http or https)
output_path: Directory to save file (must be inside models dir)
filename: Optional filename override (plain name, no path parts)
force: Force re-download if file exists
Returns:
Path to downloaded file
Raises:
ValueError: For bad scheme, filename or save path
Exception: If download fails
"""
validate_url_scheme(url)
if filename:
validate_filename(filename)
output_dir = self.resolve_output_dir(output_path)
url_info = self._parse_huggingface_url(url)
# Convert blob URL to resolve URL if needed
if url_info["repo_id"] and url_info["filename"]:
download_url = self._construct_download_url(
url_info["repo_id"], url_info["filename"], url_info["revision"]
)
logger.info("Converted URL to: %s", download_url)
else:
download_url = url
if not filename:
if url_info["filename"]:
name = os.path.basename(url_info["filename"])
else:
name = self.extract_filename(url, default="model.safetensors")
filename = safe_server_filename(name, "model.safetensors")
output_file = os.path.join(output_dir, filename)
if not self.should_download(output_file, force):
logger.info("File already exists: %s", output_file)
return output_file
headers = {"User-Agent": USER_AGENT}
if self.token:
headers["Authorization"] = f"Bearer {self.token}"
request = urllib.request.Request(download_url, headers=headers)
try:
response = self.open_url(request)
except urllib.error.HTTPError as e:
self.raise_for_http_status(e.code, e.reason, HTTP_ERROR_HINTS)
except urllib.error.URLError as e:
raise Exception(f"Network error: {e.reason}")
total_size = self.parse_content_length(response)
logger.info("Downloading %s to %s", filename, output_file)
return self.save_response(response, output_file, total_size)
+157
View File
@@ -0,0 +1,157 @@
"""ComfyUI Model Downloader Node"""
import logging
from ...base import ComfyAssetsBaseNode
from .detector import URLDetector
logger = logging.getLogger(__name__)
class ModelDownloaderNode(ComfyAssetsBaseNode):
"""ComfyUI node for downloading models from CivitAI, HuggingFace, and custom URLs"""
@classmethod
def INPUT_TYPES(cls):
"""Define input types for the node"""
return {
"required": {
"url": (
"STRING",
{
"default": "",
"multiline": False,
"placeholder": "https://civitai.com/... or https://huggingface.co/...",
},
),
"save_path": (
"STRING",
{
"default": "models/checkpoints",
"multiline": False,
"placeholder": "Path to save downloaded models",
},
),
},
"optional": {
"filename": (
"STRING",
{
"default": "",
"multiline": False,
"placeholder": "Leave empty for auto-detection",
},
),
"api_token": (
"STRING",
{
"default": "",
"multiline": False,
"placeholder": "API token (CivitAI or HuggingFace)",
},
),
"force_download": (
"BOOLEAN",
{
"default": False,
"label_on": "Force Redownload",
"label_off": "Skip if Exists",
},
),
},
}
RETURN_TYPES = ()
FUNCTION = "download_model"
CATEGORY = "🫶 ComfyAssets/🛠️ Utils"
OUTPUT_NODE = True
def download_model(
self,
url: str,
save_path: str,
filename: str = "",
api_token: str = "",
force_download: bool = False,
):
"""Download model from URL
Args:
url: URL to download from
save_path: Directory to save file
filename: Optional filename override
api_token: Optional API token
force_download: Force re-download if file exists
Returns:
Dictionary with 'ui' key for ComfyUI display
"""
# Validate inputs
if not url or not url.strip():
error_msg = "URL cannot be empty"
return {"ui": {"text": [error_msg]}}
if not save_path or not save_path.strip():
error_msg = "Save path cannot be empty"
return {"ui": {"text": [error_msg]}}
url = url.strip()
save_path = save_path.strip()
filename = filename.strip() if filename else None
api_token = api_token.strip() if api_token else None
try:
# Detect downloader type and get appropriate downloader
detector = URLDetector()
downloader_type = detector.detect(url)
logger.info("Detected downloader type: %s", downloader_type.value)
logger.info("URL: %s", url)
logger.info("Save path: %s", save_path)
if filename:
logger.info("Filename: %s", filename)
if force_download:
logger.info("Force download: enabled")
# Get downloader instance
downloader = detector.get_downloader(url, api_token=api_token)
# Download file
file_path = downloader.download(
url=url, output_path=save_path, filename=filename, force=force_download
)
message = f"Successfully downloaded to {file_path}"
logger.info(message)
return {"ui": {"text": [message]}}
except ValueError as e:
error_msg = f"Invalid URL: {str(e)}"
logger.error(error_msg)
return {"ui": {"text": [error_msg]}}
except Exception as e:
error_msg = f"Download failed: {str(e)}"
logger.error(error_msg)
return {"ui": {"text": [error_msg]}}
@classmethod
def IS_CHANGED(
cls, url, save_path, filename="", api_token="", force_download=False
):
"""Force re-evaluation on every execution or when inputs change"""
# Include hash of inputs plus timestamp to force execution
# This ensures the node re-runs even if the download failed previously
import time
import hashlib
# Create a unique hash based on non-sensitive inputs and current time
# Note: api_token is excluded to avoid sensitive data in hash
# The token doesn't affect cache invalidation - URL changes are sufficient
input_str = f"{url}|{save_path}|{filename}|{force_download}|{time.time()}"
return hashlib.sha256(input_str.encode()).hexdigest()
# Node display name
NODE_DISPLAY_NAME = "Model Downloader 🌐"
@@ -0,0 +1,5 @@
"""Project File Path tool for ComfyUI-KikoTools."""
from .node import ProjectFilePathNode
__all__ = ["ProjectFilePathNode"]
+107
View File
@@ -0,0 +1,107 @@
"""Path building logic for the Project File Path node."""
import os
import re
from datetime import date
from typing import Optional
# Characters that are invalid in Windows paths (and awkward elsewhere)
_UNSAFE_CHARS = re.compile(r'[<>:"|?*\x00-\x1f]')
_SEPARATORS = re.compile(r"[\\/]+")
# Only these are treated as a file extension and stripped from the filename,
# so names like "render_v1.5" keep their dot.
FILE_EXTENSIONS = frozenset(
{
".png",
".jpg",
".jpeg",
".webp",
".gif",
".bmp",
".tif",
".tiff",
".mp4",
".webm",
".mov",
".mkv",
".avi",
".wav",
".mp3",
".flac",
".ogg",
".txt",
".json",
".latent",
}
)
SEPARATOR_OPTIONS = ("auto", "forward_slash", "backslash")
def _clean_part(part: str) -> str:
"""Clean one path segment: drop unsafe chars, spaces to underscores."""
part = _UNSAFE_CHARS.sub("", part).strip(" .")
return part.replace(" ", "_")
def sanitize_component(text: str) -> str:
"""Clean a folder component, keeping nested folders as 'a/b'.
Splits on both / and \\, drops empty, '.' and '..' segments, so the
result is always relative and can never climb out of its parent.
"""
parts = (_clean_part(p) for p in _SEPARATORS.split(text or ""))
return "/".join(p for p in parts if p and p not in (".", ".."))
def sanitize_filename(text: str) -> str:
"""Clean a filename: no folders, and a known file extension removed."""
name = _UNSAFE_CHARS.sub("", _SEPARATORS.sub("", text or ""))
stem, extension = os.path.splitext(name)
if extension.lower() in FILE_EXTENSIONS:
name = stem
elif name.strip().lower() in FILE_EXTENSIONS: # just ".png": splitext sees no ext
name = ""
return _clean_part(name)
def _resolve_separator(separator: str) -> str:
if separator == "auto":
return os.sep
if separator == "forward_slash":
return "/"
if separator == "backslash":
return "\\"
raise ValueError(
f"Unknown separator '{separator}'; use one of {', '.join(SEPARATOR_OPTIONS)}"
)
def build_project_path(
root: str,
project_name: str,
subfolder: str,
filename: str,
date_folder: bool = False,
separator: str = "auto",
today: Optional[date] = None,
) -> str:
"""Build 'root/project/[YYYY-MM-DD/]subfolder/filename'.
Raises:
ValueError: If the filename is empty after cleaning, or the
separator is unknown.
"""
sep = _resolve_separator(separator)
clean_filename = sanitize_filename(filename)
if not clean_filename:
raise ValueError(f"filename {filename!r} is empty after removing unsafe parts")
folders = [sanitize_component(root), sanitize_component(project_name)]
if date_folder:
folders.append((today or date.today()).isoformat())
folders.append(sanitize_component(subfolder))
path = "/".join([f for f in folders if f] + [clean_filename])
return path.replace("/", sep)
+89
View File
@@ -0,0 +1,89 @@
"""ComfyUI node implementation for Project File Path."""
from datetime import date
from typing import Any, Dict, Tuple
from ...base import ComfyAssetsBaseNode
from .logic import SEPARATOR_OPTIONS, build_project_path
def _today() -> date:
return date.today()
class ProjectFilePathNode(ComfyAssetsBaseNode):
"""
Builds a save prefix like 'MyProject/2026-10-13/images/image'.
Wire the output into a save node's filename_prefix. Every component is
sanitized so the result stays inside ComfyUI's output folder.
"""
@classmethod
def INPUT_TYPES(cls) -> Dict[str, Any]:
return {
"required": {
"root": (
"STRING",
{
"default": "",
"tooltip": "Optional top folder inside the output folder",
},
),
"project_name": ("STRING", {"default": "MyProject"}),
"subfolder": (
"STRING",
{"default": "images", "tooltip": "Use a/b for nested folders"},
),
"filename": (
"STRING",
{
"default": "image",
"tooltip": "File extensions like .png are removed",
},
),
},
"optional": {
"date_folder": (
"BOOLEAN",
{
"default": False,
"tooltip": "Insert a YYYY-MM-DD folder after the project",
},
),
"separator": (list(SEPARATOR_OPTIONS), {"default": "auto"}),
},
}
RETURN_TYPES = ("STRING",)
FUNCTION = "generate_path"
CATEGORY = "🫶 ComfyAssets/🛠️ Utils"
@classmethod
def IS_CHANGED(cls, date_folder: bool = False, **kwargs) -> str:
# Output depends only on the inputs, except for the date folder:
# re-run when the day changes so open workflows get the new date.
return _today().isoformat() if date_folder else ""
def generate_path(
self,
root: str,
project_name: str,
subfolder: str,
filename: str,
date_folder: bool = False,
separator: str = "auto",
) -> Tuple[str]:
try:
path = build_project_path(
root,
project_name,
subfolder,
filename,
date_folder=date_folder,
separator=separator,
today=_today(),
)
except ValueError as e:
self.handle_error(str(e), e)
return (path,)
@@ -6,6 +6,8 @@ Pure functions for dimension extraction and scaling calculations
import torch
from typing import Tuple, Optional, Dict
MIN_DIMENSION = 8
def extract_dimensions(
image: Optional[torch.Tensor] = None,
@@ -100,8 +102,9 @@ def calculate_scaled_dimensions(
new_width = int(width * scale_factor)
new_height = int(height * scale_factor)
# Ensure divisible by 8
return ensure_divisible_by_8(new_width, new_height)
# Ensure divisible by 8, never collapsing to zero for tiny inputs
new_width, new_height = ensure_divisible_by_8(new_width, new_height)
return max(new_width, MIN_DIMENSION), max(new_height, MIN_DIMENSION)
def validate_scale_factor(
+4 -18
View File
@@ -59,7 +59,7 @@ class SamplerComboCompactNode(ComfyAssetsBaseNode):
}
}
RETURN_TYPES = ("SAMPLER", SCHEDULERS, "INT", "FLOAT")
RETURN_TYPES = (SAMPLERS, SCHEDULERS, "INT", "FLOAT")
RETURN_NAMES = ("sampler", "scheduler", "steps", "cfg")
FUNCTION = "get_combo"
CATEGORY = "🫶 ComfyAssets/🌀 Samplers"
@@ -82,27 +82,13 @@ class SamplerComboCompactNode(ComfyAssetsBaseNode):
try:
# Use the same validation logic but with compact interface
result = get_sampler_combo(sampler, sched, steps, cfg)
# Create the sampler object
try:
import comfy.samplers
sampler_obj = comfy.samplers.sampler_object(result[0])
except ImportError:
# Return sampler name for testing
sampler_obj = result[0]
return (sampler_obj, result[1], result[2], result[3])
# Return the sampler name as string, not object
return result
except Exception as e:
# Graceful fallback
self.handle_error(f"Error in compact combo: {str(e)}")
try:
import comfy.samplers
sampler_obj = comfy.samplers.sampler_object("euler")
except ImportError:
# Return sampler name for testing
sampler_obj = "euler"
return (sampler_obj, "normal", 20, 7.0)
return ("euler", "normal", 20, 7.0)
def __str__(self) -> str:
"""String representation of the compact node."""
+5 -27
View File
@@ -64,7 +64,7 @@ class SamplerComboNode(ComfyAssetsBaseNode):
}
}
RETURN_TYPES = ("SAMPLER", SCHEDULERS, "INT", "FLOAT")
RETURN_TYPES = (SAMPLERS, SCHEDULERS, "INT", "FLOAT")
RETURN_NAMES = ("sampler_name", "scheduler", "steps", "cfg")
FUNCTION = "get_sampler_combo"
CATEGORY = "🫶 ComfyAssets/🌀 Samplers"
@@ -97,33 +97,18 @@ class SamplerComboNode(ComfyAssetsBaseNode):
f"steps={steps}, cfg={cfg}. "
f"Using safe defaults: euler, normal, 20 steps, CFG 7.0"
)
try:
import comfy.samplers
sampler = comfy.samplers.sampler_object("euler")
except ImportError:
# Return mock object for testing
sampler = "euler"
return (sampler, "normal", 20, 7.0)
return ("euler", "normal", 20, 7.0)
# Process and return the combo
result = get_sampler_combo(sampler_name, scheduler, steps, cfg)
# Create the sampler object
try:
import comfy.samplers
sampler = comfy.samplers.sampler_object(result[0])
except ImportError:
# Return sampler name for testing
sampler = result[0]
self.log_info(
f"Configured sampler combo: {result[0]}, {result[1]}, "
f"{result[2]} steps, CFG {result[3]}"
)
return (sampler, result[1], result[2], result[3])
# Return the sampler name as string, not object
return result
except Exception as e:
# Handle any unexpected errors gracefully
@@ -134,14 +119,7 @@ class SamplerComboNode(ComfyAssetsBaseNode):
f"{self.__class__.__name__}: Error processing sampler combo: {str(e)}. "
f"Using safe defaults: euler, normal, 20 steps, CFG 7.0"
)
try:
import comfy.samplers
sampler = comfy.samplers.sampler_object("euler")
except ImportError:
# Return mock object for testing
sampler = "euler"
return (sampler, "normal", 20, 7.0)
return ("euler", "normal", 20, 7.0)
def validate_inputs(
self, sampler_name: str, scheduler: str, steps: int, cfg: float
+7 -7
View File
@@ -10,14 +10,14 @@ def generate_random_seed() -> int:
Generate a cryptographically strong random seed value.
Returns:
Random integer in the valid ComfyUI seed range
Random integer in the valid ComfyUI seed range (0 to 2**32 - 1)
"""
return random.randint(0, 0xFFFFFFFFFFFFFFFF)
return random.randint(0, 0xFFFFFFFF) # 2**32 - 1
def validate_seed_value(seed: Any) -> bool:
"""
Validate that a seed value is within acceptable range.
Validate that a seed value is within acceptable range (0 to 2**32 - 1).
Args:
seed: Seed value to validate
@@ -30,7 +30,7 @@ def validate_seed_value(seed: Any) -> bool:
try:
seed_int = int(seed)
return 0 <= seed_int <= 0xFFFFFFFFFFFFFFFF
return 0 <= seed_int <= 0xFFFFFFFF # 2**32 - 1
except (ValueError, TypeError):
return False
@@ -54,11 +54,11 @@ def sanitize_seed_value(seed: Any) -> int:
try:
seed_int = int(seed)
# Clamp to valid range
# Clamp to valid range (0 to 2**32 - 1)
if seed_int < 0:
seed_int = 0
elif seed_int > 0xFFFFFFFFFFFFFFFF:
seed_int = 0xFFFFFFFFFFFFFFFF
elif seed_int > 0xFFFFFFFF:
seed_int = 0xFFFFFFFF
return seed_int
+9 -10
View File
@@ -27,12 +27,13 @@ class SeedHistoryNode(ComfyAssetsBaseNode):
{
"default": 12345,
"min": 0,
"max": 0xFFFFFFFFFFFFFFFF,
"max": 0xFFFFFFFF, # 2**32 - 1
"control_after_generate": True,
"tooltip": "Seed value for generation processes. "
"History UI tracks all changes automatically.",
"Use 'control after generate' to set behavior after each run.",
},
),
}
},
}
RETURN_TYPES = ("INT",)
@@ -40,12 +41,13 @@ class SeedHistoryNode(ComfyAssetsBaseNode):
FUNCTION = "output_seed"
CATEGORY = "🫶 ComfyAssets/🌱 Seeds"
def output_seed(self, seed: int) -> Tuple[int]:
def output_seed(self, seed: int, **kwargs) -> Tuple[int]:
"""
Output the seed value for use in other nodes.
Args:
seed: Input seed value
**kwargs: Accepts legacy parameters (e.g. mode) for backward compatibility
Returns:
Tuple containing the seed value
@@ -53,7 +55,6 @@ class SeedHistoryNode(ComfyAssetsBaseNode):
try:
# Validate and sanitize the seed
if not validate_seed_value(seed):
# Log the validation error but don't raise
import logging
logger = logging.getLogger(__name__)
@@ -64,11 +65,9 @@ class SeedHistoryNode(ComfyAssetsBaseNode):
return (12345,)
clean_seed = sanitize_seed_value(seed)
return (clean_seed,)
except Exception as e:
# Handle any unexpected errors gracefully
import logging
logger = logging.getLogger(__name__)
@@ -142,7 +141,7 @@ class SeedHistoryNode(ComfyAssetsBaseNode):
Returns:
Range information string
"""
max_seed = 0xFFFFFFFFFFFFFFFF
max_seed = 0xFFFFFFFF # 2**32 - 1
return f"Valid range: 0 to {max_seed:,} ({hex(max_seed)})"
@classmethod
@@ -166,7 +165,7 @@ class SeedHistoryNode(ComfyAssetsBaseNode):
Returns:
True if seed is in valid range
"""
return 0 <= seed <= 0xFFFFFFFFFFFFFFFF
return 0 <= seed <= 0xFFFFFFFF # 2**32 - 1
def __str__(self) -> str:
"""String representation of the node."""
@@ -178,6 +177,6 @@ class SeedHistoryNode(ComfyAssetsBaseNode):
f"SeedHistoryNode("
f"category='{self.CATEGORY}', "
f"function='{self.FUNCTION}', "
f"max_seed={hex(0xFFFFFFFFFFFFFFFF)}"
f"max_seed={hex(0xFFFFFFFF)}" # 2**32 - 1
f")"
)
+5
View File
@@ -0,0 +1,5 @@
"""Text Input tool for ComfyUI."""
from .node import TextInputNode, NODE_DISPLAY_NAME
__all__ = ["TextInputNode", "NODE_DISPLAY_NAME"]
+59
View File
@@ -0,0 +1,59 @@
"""Text Input node implementation."""
from ...base import ComfyAssetsBaseNode
class TextInputNode(ComfyAssetsBaseNode):
"""Provides a text input field for manual text entry in ComfyUI workflows."""
@classmethod
def INPUT_TYPES(cls):
"""Define input types for the node."""
return {
"required": {
"text": (
"STRING",
{
"multiline": True,
"default": "",
"dynamicPrompts": True,
},
),
},
}
RETURN_TYPES = ("STRING",)
RETURN_NAMES = ("text",)
FUNCTION = "execute"
CATEGORY = "🫶 ComfyAssets/📝 Text"
DESCRIPTION = """
Simple text input field for entering text manually.
Features:
- Multiline text editing
- Supports wildcards and dynamic prompts
- Direct connection to CLIP text encoders
- Unicode and special character support
Use Cases:
- Positive/negative prompts
- Custom text for workflows
- Manual text editing
- Prompt templates
"""
def execute(self, text):
"""Process the input text and return it.
Args:
text: Input text from the widget
Returns:
Tuple containing the text
"""
return (text,)
# Node display name
NODE_DISPLAY_NAME = "Text Input"
@@ -78,7 +78,47 @@ PRESET_METADATA: Dict[str, PresetMetadata] = {
"Portrait",
"SDXL portrait 5:12 - very tall portrait",
),
"704×1408": PresetMetadata(
704,
1408,
"1:2",
0.5,
0.99,
"SDXL",
"Portrait",
"SDXL portrait 1:2 - extreme tall portrait",
),
"960×1024": PresetMetadata(
960,
1024,
"15:16",
0.938,
0.98,
"SDXL",
"Portrait",
"SDXL near-square portrait - subtle portrait",
),
"720×1280": PresetMetadata(
720,
1280,
"9:16",
0.5625,
0.92,
"SDXL",
"Portrait",
"SDXL portrait 9:16 - vertical video/mobile",
),
# SDXL Presets - Landscape
"1024×960": PresetMetadata(
1024,
960,
"16:15",
1.067,
0.98,
"SDXL",
"Landscape",
"SDXL near-square landscape - subtle landscape",
),
"1152×896": PresetMetadata(
1152,
896,
@@ -119,6 +159,26 @@ PRESET_METADATA: Dict[str, PresetMetadata] = {
"Landscape",
"SDXL landscape 12:5 - very wide landscape",
),
"1728×576": PresetMetadata(
1728,
576,
"3:1",
3.0,
1.0,
"SDXL",
"Landscape",
"SDXL landscape 3:1 - extreme wide panoramic",
),
"1280×720": PresetMetadata(
1280,
720,
"16:9",
1.778,
0.92,
"SDXL",
"Landscape",
"SDXL landscape 16:9 - HD widescreen video",
),
# FLUX Presets - High Quality
"1920×1080": PresetMetadata(
1920,
@@ -283,6 +343,97 @@ PRESET_METADATA: Dict[str, PresetMetadata] = {
"Banner",
"Vertical banner 1:3 - extreme tall banner",
),
# Qwen Presets
"1328×1328": PresetMetadata(
1328,
1328,
"1:1",
1.0,
1.76,
"Qwen",
"Square",
"Qwen square 1:1 - optimized square",
),
"1664×928": PresetMetadata(
1664,
928,
"16:9",
1.793,
1.54,
"Qwen",
"Landscape",
"Qwen landscape 16:9 - widescreen format",
),
"928×1664": PresetMetadata(
928,
1664,
"9:16",
0.558,
1.54,
"Qwen",
"Portrait",
"Qwen portrait 9:16 - vertical format",
),
"1472×1104": PresetMetadata(
1472,
1104,
"4:3",
1.333,
1.62,
"Qwen",
"Landscape",
"Qwen landscape 4:3 - classic landscape",
),
"1104×1472": PresetMetadata(
1104,
1472,
"3:4",
0.750,
1.62,
"Qwen",
"Portrait",
"Qwen portrait 3:4 - classic portrait",
),
"1584×1056": PresetMetadata(
1584,
1056,
"3:2",
1.500,
1.67,
"Qwen",
"Landscape",
"Qwen landscape 3:2 - photography standard",
),
"1056×1584": PresetMetadata(
1056,
1584,
"2:3",
0.667,
1.67,
"Qwen",
"Portrait",
"Qwen portrait 2:3 - portrait photography",
),
"2080×688": PresetMetadata(
2080,
688,
"3:1",
3.023,
1.43,
"Qwen",
"Landscape",
"Qwen experimental landscape 3:1 - ultra-wide",
),
"688×2080": PresetMetadata(
688,
2080,
"1:3",
0.331,
1.43,
"Qwen",
"Portrait",
"Qwen experimental portrait 1:3 - ultra-tall",
),
}
# Legacy compatibility - maintain old preset dictionaries
@@ -304,6 +455,12 @@ ULTRA_WIDE_PRESETS: Dict[str, Tuple[int, int]] = {
if v.model_group == "Ultra-Wide"
}
QWEN_PRESETS: Dict[str, Tuple[int, int]] = {
k: (v.width, v.height)
for k, v in PRESET_METADATA.items()
if v.model_group == "Qwen"
}
# Combined preset options for ComfyUI dropdown
PRESET_OPTIONS: Dict[str, Tuple[int, int]] = {
"custom": (0, 0), # Special case for custom dimensions
@@ -386,6 +543,22 @@ PRESET_CATEGORIES = {
for k, v in PRESET_METADATA.items()
if v.model_group == "Ultra-Wide" and v.category == "Banner"
],
# Qwen Categories
"Qwen Square": [
k
for k, v in PRESET_METADATA.items()
if v.model_group == "Qwen" and v.category == "Square"
],
"Qwen Portrait": [
k
for k, v in PRESET_METADATA.items()
if v.model_group == "Qwen" and v.category == "Portrait"
],
"Qwen Landscape": [
k
for k, v in PRESET_METADATA.items()
if v.model_group == "Qwen" and v.category == "Landscape"
],
}
# Legacy compatibility - preset descriptions
@@ -398,6 +571,7 @@ MODEL_RECOMMENDATIONS = {
"Ultra-Wide": [
k for k, v in PRESET_METADATA.items() if v.model_group == "Ultra-Wide"
],
"Qwen": [k for k, v in PRESET_METADATA.items() if v.model_group == "Qwen"],
}
@@ -444,21 +618,27 @@ def get_model_recommendation(preset_name: str) -> str:
return "Custom dimensions"
def _console_safe(text: str) -> str:
"""ASCII for console output: Windows legacy code pages can't print "×"."""
return text.replace("×", "x").encode("ascii", "replace").decode()
def validate_preset_dimensions() -> bool:
"""Validate that all presets meet ComfyUI requirements."""
for preset_name, metadata in PRESET_METADATA.items():
for name, metadata in PRESET_METADATA.items():
preset_name = _console_safe(name)
width, height = metadata.width, metadata.height
# Check divisible by 8
if width % 8 != 0 or height % 8 != 0:
print(
f"ERROR: {preset_name} dimensions not divisible by 8: {width}×{height}"
f"ERROR: {preset_name} dimensions not divisible by 8: {width}x{height}"
)
return False
# Check reasonable bounds
if not (64 <= width <= 8192) or not (64 <= height <= 8192):
print(f"ERROR: {preset_name} dimensions out of bounds: {width}×{height}")
print(f"ERROR: {preset_name} dimensions out of bounds: {width}x{height}")
return False
return True
@@ -0,0 +1,8 @@
"""
Width Height to VEC2 converter node
Converts width and height inputs to VEC2 tuple for jovi_glsl and similar nodes
"""
from .node import WidthHeightToVec2Node
__all__ = ["WidthHeightToVec2Node"]
@@ -0,0 +1,128 @@
"""
Width Height to VEC2 Node
Converts width and height inputs to a VEC2 tuple for use with
nodes like jovi_glsl that expect vector inputs.
"""
from typing import Any, Dict, Tuple, Union
from ...base import ComfyAssetsBaseNode
class WidthHeightToVec2Node(ComfyAssetsBaseNode):
"""
Convert width and height values to VEC2 format.
Accepts INT, FLOAT, STRING, or ANY types and outputs a VEC2 tuple
suitable for nodes expecting vector inputs.
"""
@classmethod
def INPUT_TYPES(cls) -> Dict[str, Any]:
"""Define ComfyUI input interface."""
return {
"required": {
"width": (
"INT",
{
"default": 1024,
"min": 1,
"max": 8192,
"step": 1,
"tooltip": "Width value (x component of VEC2)",
},
),
"height": (
"INT",
{
"default": 1024,
"min": 1,
"max": 8192,
"step": 1,
"tooltip": "Height value (y component of VEC2)",
},
),
},
}
RETURN_TYPES = ("VEC2",)
RETURN_NAMES = ("vec2",)
FUNCTION = "convert_to_vec2"
CATEGORY = "🫶 ComfyAssets/🖼️ Resolution"
def convert_to_vec2(
self,
width: Union[int, float, str, Any],
height: Union[int, float, str, Any],
) -> Tuple[Tuple[int, int]]:
"""
Convert width and height to VEC2 tuple.
Args:
width: Width value (will be converted to int)
height: Height value (will be converted to int)
Returns:
Tuple containing the VEC2 tuple (width, height)
"""
try:
# Convert to integers, handling various input types
w = self._to_int(width, "width")
h = self._to_int(height, "height")
# Clamp values to valid range
w = max(1, min(8192, w))
h = max(1, min(8192, h))
self.log_info(f"Converted to VEC2: ({w}, {h})")
# Return as tuple wrapped in tuple (ComfyUI return format)
return ((w, h),)
except Exception as e:
error_msg = f"Failed to convert to VEC2: {str(e)}"
self.handle_error(error_msg, e)
def _to_int(self, value: Any, name: str) -> int:
"""
Convert a value to integer.
Args:
value: Value to convert (int, float, str, or any)
name: Parameter name for error messages
Returns:
Integer value
Raises:
ValueError: If conversion fails
"""
if isinstance(value, int):
return value
elif isinstance(value, float):
return int(value)
elif isinstance(value, str):
try:
# Try parsing as float first (handles "1024.0")
return int(float(value.strip()))
except ValueError:
raise ValueError(f"Cannot convert {name} string '{value}' to integer")
else:
# Try generic conversion for ANY type
try:
return int(value)
except (ValueError, TypeError):
raise ValueError(
f"Cannot convert {name} of type {type(value).__name__} to integer"
)
# Node registration
NODE_CLASS_MAPPINGS = {
"WidthHeightToVec2": WidthHeightToVec2Node,
}
NODE_DISPLAY_NAME_MAPPINGS = {
"WidthHeightToVec2": "Width Height to VEC2",
}
@@ -1,78 +1,124 @@
"""Logic module for Flux Sampler Params node."""
from typing import List, Dict, Any, Tuple, Optional
import math
import random
import time
import logging
logger = logging.getLogger(__name__)
def parse_string_to_list(value: str) -> List[float]:
RANDOM_SEED_TOKEN = "?"
MAX_RANDOM_SEED = 999999
def parse_string_to_list(value: str, field: str = "value") -> List[float]:
"""
Parse a string containing comma-separated values to a list of floats.
Args:
value: String with comma-separated values
field: Name of the input, used in error messages
Returns:
List of float values
List of float values (empty when the string is blank)
Raises:
ValueError: If any token is not a finite number
"""
if not value or not value.strip():
return []
try:
values = []
for item in value.split(","):
item = item.strip()
if item:
try:
values.append(float(item))
except ValueError:
logger.warning(f"Could not parse '{item}' as float")
return values
except Exception as e:
logger.error(f"Error parsing string to list: {e}")
return []
values = []
for item in value.split(","):
item = item.strip()
if not item:
continue
try:
number = float(item)
except ValueError:
raise ValueError(f"Invalid {field} value '{item}': expected a number")
if not math.isfinite(number):
raise ValueError(f"Invalid {field} value '{item}': must be finite")
values.append(number)
return values
def parse_steps_list(value: str, field: str = "steps") -> List[int]:
"""
Parse comma-separated step counts into positive integers.
Raises:
ValueError: If a token is not a positive whole number
"""
steps = []
for number in parse_string_to_list(value, field):
if number != int(number) or number < 1:
raise ValueError(
f"Invalid {field} value '{number:g}': expected a positive integer"
)
steps.append(int(number))
return steps
def parse_seed_string(seed_string: str) -> List[int]:
"""
Parse seed string which can contain numbers, '?', or ranges.
Parse a seed string of comma or newline separated tokens.
Args:
seed_string: String with seeds (e.g., "123,?,456")
Each token is either a non-negative integer or the exact token '?',
which draws a random seed. A blank string yields one random seed.
Ranges are not supported.
Returns:
List of integer seeds
Raises:
ValueError: If a token is neither an integer nor '?'
"""
seeds = []
for item in seed_string.replace("\n", ",").split(","):
item = item.strip()
if not item:
continue
if item == RANDOM_SEED_TOKEN:
seeds.append(random.randint(0, MAX_RANDOM_SEED))
continue
try:
seed = int(item)
except ValueError:
raise ValueError(
f"Invalid seed '{item}': use whole numbers or '?' for a random seed"
)
if seed < 0:
raise ValueError(f"Invalid seed '{item}': seeds cannot be negative")
seeds.append(seed)
try:
for item in seed_string.replace("\n", ",").split(","):
item = item.strip()
if not item:
continue
if "?" in item:
seeds.append(random.randint(0, 999999))
else:
try:
seeds.append(int(item))
except ValueError:
logger.warning(f"Could not parse seed '{item}'")
seeds.append(random.randint(0, 999999))
if not seeds:
seeds = [random.randint(0, 999999)]
except Exception as e:
logger.error(f"Error parsing seeds: {e}")
seeds = [random.randint(0, 999999)]
if not seeds:
seeds = [random.randint(0, MAX_RANDOM_SEED)]
return seeds
def seed_string_is_random(seed_string: str) -> bool:
"""Return True if the seed string produces a different result each run."""
tokens = [t.strip() for t in seed_string.replace("\n", ",").split(",")]
tokens = [t for t in tokens if t]
return not tokens or RANDOM_SEED_TOKEN in tokens
def is_schnell_model(model: Any) -> bool:
"""
Detect Flux Schnell from the unet config.
Schnell is not guidance distilled (guidance_embed is False) while dev is
(guidance_embed is True). Anything unrecognised is treated as dev.
"""
config = getattr(
getattr(getattr(model, "model", None), "model_config", None),
"unet_config",
None,
)
if not isinstance(config, dict):
return False
return config.get("guidance_embed") is False
def parse_sampler_string(
sampler_string: str, available_samplers: List[str]
) -> List[str]:
@@ -241,14 +287,13 @@ def validate_flux_params(
Returns:
True if all parameters are valid
Raises:
ValueError: Naming the offending field and token
"""
try:
parse_string_to_list(steps)
parse_string_to_list(guidance)
parse_string_to_list(max_shift)
parse_string_to_list(base_shift)
parse_string_to_list(denoise)
return True
except Exception as e:
logger.error(f"Invalid parameters: {e}")
return False
parse_steps_list(steps, "steps")
parse_string_to_list(guidance, "guidance")
parse_string_to_list(max_shift, "max_shift")
parse_string_to_list(base_shift, "base_shift")
parse_string_to_list(denoise, "denoise")
return True
@@ -1,12 +1,17 @@
"""Flux Sampler Params node for ComfyUI."""
from typing import Tuple, Any, Dict, List, Optional
import hashlib
import json
import time
import logging
from ....base.base_node import ComfyAssetsBaseNode
from .logic import (
parse_string_to_list,
parse_steps_list,
parse_seed_string,
seed_string_is_random,
is_schnell_model,
parse_sampler_string,
parse_scheduler_string,
get_default_flux_params,
@@ -122,6 +127,21 @@ class FluxSamplerParamsNode(ComfyAssetsBaseNode):
},
}
@classmethod
def IS_CHANGED(cls, **kwargs):
"""
Re-run every time when seeds are random, otherwise use a stable hash.
NaN never compares equal to itself, so ComfyUI re-executes the node.
"""
if seed_string_is_random(str(kwargs.get("seed", ""))):
return float("nan")
widgets = {
key: value for key, value in kwargs.items() if isinstance(value, str)
}
payload = json.dumps(widgets, sort_keys=True)
return hashlib.sha256(payload.encode("utf-8")).hexdigest()
RETURN_TYPES = ("LATENT", "SAMPLER_PARAMS")
RETURN_NAMES = ("latent", "params")
FUNCTION = "process_batch"
@@ -150,15 +170,15 @@ class FluxSamplerParamsNode(ComfyAssetsBaseNode):
"""
try:
import comfy.samplers
import comfy.model_base
import comfy.model_management
import comfy.utils
import torch
from comfy_extras.nodes_custom_sampler import (
Noise_RandomNoise,
BasicScheduler,
BasicGuider,
SamplerCustomAdvanced,
)
from comfy_extras.nodes_latent import LatentBatch
from comfy_extras.nodes_model_advanced import (
ModelSamplingFlux,
ModelSamplingAuraFlow,
@@ -170,13 +190,43 @@ class FluxSamplerParamsNode(ComfyAssetsBaseNode):
self.handle_error(f"Required ComfyUI modules not available: {e}")
return (latent_image, [])
try:
if not validate_flux_params(
steps, guidance, max_shift, base_shift, denoise
):
self.handle_error("Invalid parameter format")
# Local implementation of LatentBatch functionality
# Copied from nodes_latent.py to avoid V3 schema breaking changes
def reshape_latent_to(target_shape, latent, repeat_batch=True):
"""Reshape latent tensor to match target shape."""
if latent.shape[1:] != target_shape[1:]:
latent = comfy.utils.common_upscale(
latent, target_shape[-1], target_shape[-2], "bilinear", "center"
)
if repeat_batch:
return comfy.utils.repeat_to_batch_size(latent, target_shape[0])
else:
return latent
is_schnell = model.model.model_type == comfy.model_base.ModelType.FLOW
def batch_latents(samples1, samples2):
"""Batch two latent samples together."""
samples_out = samples1.copy()
s1 = samples1["samples"]
s2 = samples2["samples"]
s2 = reshape_latent_to(s1.shape, s2, repeat_batch=False)
s = torch.cat((s1, s2), dim=0)
samples_out["samples"] = s
samples_out["batch_index"] = samples1.get(
"batch_index", [x for x in range(0, s1.shape[0])]
) + samples2.get("batch_index", [x for x in range(0, s2.shape[0])])
return samples_out
try:
validate_flux_params(steps, guidance, max_shift, base_shift, denoise)
if loras is not None and not loras.get("loras"):
raise ValueError(
"LoRA input contains no LoRAs (is the LoRA folder empty "
"or fully filtered?)"
)
is_schnell = is_schnell_model(model)
defaults = get_default_flux_params(is_schnell)
seeds = parse_seed_string(seed)
@@ -186,13 +236,13 @@ class FluxSamplerParamsNode(ComfyAssetsBaseNode):
)
steps = steps if steps else str(defaults["steps"])
steps_list = [int(s) for s in parse_string_to_list(steps)]
steps_list = parse_steps_list(steps)
guidance = guidance if guidance else str(defaults["guidance"])
guidance_list = parse_string_to_list(guidance)
guidance_list = parse_string_to_list(guidance, "guidance")
denoise = denoise if denoise else "1.0"
denoise_list = parse_string_to_list(denoise)
denoise_list = parse_string_to_list(denoise, "denoise")
if not is_schnell:
max_shift = max_shift if max_shift else str(defaults["max_shift"])
@@ -201,8 +251,8 @@ class FluxSamplerParamsNode(ComfyAssetsBaseNode):
max_shift = "0"
base_shift = base_shift if base_shift else str(defaults["base_shift"])
max_shift_list = parse_string_to_list(max_shift)
base_shift_list = parse_string_to_list(base_shift)
max_shift_list = parse_string_to_list(max_shift, "max_shift")
base_shift_list = parse_string_to_list(base_shift, "base_shift")
cond_text, cond_encoded = process_conditioning_input(conditioning)
@@ -231,12 +281,17 @@ class FluxSamplerParamsNode(ComfyAssetsBaseNode):
lora_strength_count,
)
if total_samples < 1:
raise ValueError(
"No parameter combinations to run: check that seed, sampler, "
"scheduler, steps, guidance and denoise each yield a value"
)
self.log_info(f"Processing {total_samples} parameter combinations")
basicscheduler = BasicScheduler()
basicguider = BasicGuider()
samplercustomadvanced = SamplerCustomAdvanced()
latentbatch = LatentBatch()
modelsampling = (
ModelSamplingFlux() if not is_schnell else ModelSamplingAuraFlow()
)
@@ -364,7 +419,7 @@ class FluxSamplerParamsNode(ComfyAssetsBaseNode):
if out_latent is None:
out_latent = latent
else:
out_latent = latentbatch.batch(out_latent, latent)[0]
out_latent = batch_latents(out_latent, latent)
if total_samples > 1:
pbar.update(1)
@@ -1,12 +1,17 @@
"""Logic module for LoRA Folder Batch node."""
import math
import os
import re
from typing import List, Dict, Any
from typing import List, Dict, Any, Optional, Tuple
import logging
logger = logging.getLogger(__name__)
MAX_STRENGTH_VALUES = 1000
DEFAULT_RANGE_STEP = 0.1
_RANGE_EPSILON = 1e-4
def get_lora_folders() -> List[str]:
"""
@@ -35,108 +40,102 @@ def get_lora_folders() -> List[str]:
return [".", "flux", "sdxl", "sd15"]
def scan_folder_for_loras(folder_path: str) -> List[str]: # noqa: C901
"""
Scan a folder for LoRA files (.safetensors).
Args:
folder_path: Path to folder to scan (absolute or relative to models/loras)
Returns:
List of LoRA filenames relative to models/loras directory
"""
def _get_lora_roots() -> List[str]:
"""Return every configured loras root directory (empty if unavailable)."""
try:
import folder_paths
# Get all LoRA paths from ComfyUI (includes extra_model_paths)
lora_paths = folder_paths.folder_names_and_paths.get("loras", [[]])[0]
# Determine the full path and base lora path
full_path = None
base_lora_path = None
# Check if this is an absolute path
if os.path.isabs(folder_path):
full_path = folder_path
# Check if this path is inside any of the known lora directories
for lora_base in lora_paths:
# Normalize paths for comparison
norm_full = os.path.normpath(full_path)
norm_base = os.path.normpath(lora_base)
# Check if full_path starts with this lora_base
if norm_full.startswith(norm_base):
base_lora_path = lora_base
break
# Also check if the path is a subdirectory under lora/loras
if "lora" in norm_full.lower():
# Find the lora or loras directory in the path
path_parts = norm_full.replace("\\", "/").split("/")
for i, part in enumerate(path_parts):
if part.lower() in ["lora", "loras"]:
# Check if this matches our lora_base
potential_base = "/".join(path_parts[: i + 1])
if os.path.normpath(potential_base) == norm_base:
base_lora_path = lora_base
break
if base_lora_path:
break
else:
# Relative path provided
base_lora_path = lora_paths[0] if lora_paths else ""
full_path = os.path.join(base_lora_path, folder_path)
if not os.path.exists(full_path):
logger.warning(f"Folder does not exist: {full_path}")
return []
# Scan for .safetensors files recursively
lora_files = []
for root, _, files in os.walk(full_path):
for file in files:
if file.endswith(".safetensors"):
# Get the full path to the file
file_full_path = os.path.join(root, file)
# Calculate the correct relative path for ComfyUI
if base_lora_path:
# Path is inside a known lora directory
try:
rel_path = os.path.relpath(file_full_path, base_lora_path)
lora_files.append(rel_path.replace("\\", "/"))
except ValueError:
# Different drives on Windows, use path relative to scan folder
rel_path = os.path.relpath(file_full_path, full_path)
if rel_path == ".":
lora_files.append(file)
else:
lora_files.append(rel_path.replace("\\", "/"))
else:
# Path is outside known lora directories
# Return path relative to the scanned folder
rel_path = os.path.relpath(file_full_path, full_path)
if rel_path == ".":
lora_files.append(file)
else:
lora_files.append(rel_path.replace("\\", "/"))
# Sort naturally (handles epoch numbers properly)
lora_files = natural_sort(lora_files)
logger.info(f"Found {len(lora_files)} LoRA files in {folder_path}")
if lora_files and logger.isEnabledFor(logging.DEBUG):
logger.debug(f"Base lora path: {base_lora_path}")
logger.debug(f"Full scan path: {full_path}")
logger.debug(f"First few LoRA paths returned: {lora_files[:3]}")
return lora_files
except Exception as e:
logger.error(f"Error scanning folder {folder_path}: {e}")
entry = folder_paths.folder_names_and_paths.get("loras")
return list(entry[0]) if entry else []
except (ImportError, AttributeError, IndexError, TypeError):
return []
def _is_within(path: str, root: str) -> bool:
"""True if realpath `path` equals or is inside realpath `root`."""
try:
real_path, real_root = os.path.realpath(path), os.path.realpath(root)
return os.path.commonpath([real_path, real_root]) == real_root
except ValueError: # different drives or mixed absolute/relative
return False
def _resolve_scan_targets(folder_path: str) -> List[Tuple[str, Optional[str]]]:
"""
Resolve a folder setting to (directory, base_root) pairs to scan.
base_root is the loras root the directory lives in, or None when the
directory is an absolute path outside every known root.
"""
roots = _get_lora_roots()
if os.path.isabs(folder_path):
base = next((r for r in roots if _is_within(folder_path, r)), None)
return [(folder_path, base)]
targets = []
for root in roots:
candidate = os.path.join(root, folder_path)
if not _is_within(candidate, root):
logger.warning(f"Folder escapes the loras directory: {folder_path}")
continue
targets.append((candidate, root))
return targets
def _scan_entries(folder_path: str) -> List[Tuple[str, str]]:
"""Return (relative_name, absolute_path) for every .safetensors found."""
entries: Dict[str, str] = {}
for directory, base in _resolve_scan_targets(folder_path):
if not os.path.isdir(directory):
continue
for root, _, files in os.walk(directory):
for file in files:
if not file.endswith(".safetensors"):
continue
full = os.path.join(root, file)
try:
rel = os.path.relpath(full, base or directory)
except ValueError:
rel = os.path.relpath(full, directory)
entries.setdefault(rel.replace("\\", "/"), full)
return [(name, entries[name]) for name in natural_sort(list(entries))]
def scan_folder_for_loras(folder_path: str) -> List[str]:
"""
Scan a folder for LoRA files (.safetensors).
Relative folders are searched in every configured loras root. Absolute
folders are matched to a root by real-path containment (so a sibling like
``loras_backup`` is not mistaken for ``loras``).
Args:
folder_path: Folder to scan (absolute or relative to the loras roots)
Returns:
Naturally sorted LoRA names relative to their loras root (or to the
scanned folder when it lies outside every root)
"""
names = [name for name, _ in _scan_entries(folder_path)]
if not names:
logger.warning(f"No LoRA files found in {folder_path}")
else:
logger.info(f"Found {len(names)} LoRA files in {folder_path}")
return names
def get_lora_file_mtimes(folder_path: str) -> List[Tuple[str, float]]:
"""Return sorted (name, mtime) pairs for LoRAs in a folder."""
result = []
for name, full in _scan_entries(folder_path):
try:
result.append((name, os.path.getmtime(full)))
except OSError:
result.append((name, -1.0))
return result
def sort_lora_files(lora_files: List[str], sort_order: str) -> List[str]:
"""
Sort LoRA files based on the specified order.
@@ -232,66 +231,82 @@ def filter_loras_by_pattern(
return filtered
def parse_strength_string(strength_str: str) -> List[float]: # noqa: C901
def _parse_finite(token: str, what: str, original: str) -> float:
try:
value = float(token.strip())
except ValueError:
raise ValueError(f"Invalid strength {what} '{token.strip()}' in '{original}'")
if not math.isfinite(value):
raise ValueError(f"Invalid strength {what} '{token.strip()}' in '{original}'")
return value
def _parse_strength_range(text: str) -> List[float]:
"""Parse 'start...end' or 'start...end+step'."""
parts = text.split("...")
if len(parts) != 2:
raise ValueError(f"Invalid strength range '{text}': use start...end[+step]")
start = _parse_finite(parts[0], "start", text)
end_part = parts[1]
if "+" in end_part:
pieces = end_part.split("+")
if len(pieces) != 2:
raise ValueError(f"Invalid strength range '{text}': use start...end[+step]")
end = _parse_finite(pieces[0], "end", text)
step = _parse_finite(pieces[1], "step", text)
else:
end = _parse_finite(end_part, "end", text)
step = DEFAULT_RANGE_STEP
if step <= 0:
raise ValueError(
f"Invalid strength range '{text}': step must be greater than 0"
)
if end < start:
raise ValueError(
f"Invalid strength range '{text}': reversed range "
f"(start {start:g} is greater than end {end:g})"
)
count = int(math.floor((end - start) / step + _RANGE_EPSILON)) + 1
if count > MAX_STRENGTH_VALUES:
raise ValueError(
f"Strength range '{text}' would generate {count} values; "
f"the maximum is {MAX_STRENGTH_VALUES}"
)
return [round(start + i * step, 4) for i in range(count)]
def parse_strength_string(strength_str: str) -> List[float]:
"""
Parse strength string into list of values.
Supports:
- Blank: defaults to [1.0]
- Single value: "1.0"
- Multiple values: "0.5, 0.75, 1.0"
- Range: "0.5...1.0" (with optional step)
- Range: "0.5...1.0" (default step 0.1) or "0.5...1.0+0.25"
Args:
strength_str: String representation of strengths
Returns:
List of strength values
Raises:
ValueError: On malformed input, non-positive step, reversed range, or
more than MAX_STRENGTH_VALUES generated values.
"""
strength_str = strength_str.strip()
if not strength_str:
return [1.0]
# Check for range notation
if "..." in strength_str:
parts = strength_str.split("...")
if len(parts) == 2:
try:
start = float(parts[0].strip())
end_part = parts[1].strip()
return _parse_strength_range(strength_str)
# Check for step
if "+" in end_part:
end_str, step_str = end_part.split("+")
end = float(end_str.strip())
step = float(step_str.strip())
else:
end = float(end_part)
step = 0.1 # Default step
# Generate range
values = []
current = start
while current <= end + 0.0001: # Small epsilon for float comparison
values.append(round(current, 4))
current += step
return values
except ValueError as e:
logger.error(f"Invalid range format: {e}")
return [1.0]
# Parse comma-separated values
try:
values = []
for item in strength_str.split(","):
item = item.strip()
if item:
values.append(float(item))
return values if values else [1.0]
except ValueError as e:
logger.error(f"Invalid strength values: {e}")
return [1.0]
values = [
_parse_finite(item, "value", strength_str)
for item in strength_str.split(",")
if item.strip()
]
if not values:
raise ValueError(f"No strength values found in '{strength_str}'")
return values
def create_lora_params(
@@ -312,6 +327,9 @@ def create_lora_params(
logger.warning("No LoRA files provided")
return {"loras": [], "strengths": []}
if not strengths:
raise ValueError("At least one strength value is required")
if batch_mode == "combinatorial":
# Each LoRA gets tested with each strength
# This creates len(loras) * len(strengths) combinations
@@ -412,33 +430,15 @@ def validate_folder_path(folder_path: str) -> bool:
"""
Validate that the folder path exists and is accessible.
Args:
folder_path: Folder path to validate (absolute or relative)
Returns:
True if valid
Relative paths are accepted if they exist inside any loras root.
"""
try:
# Handle absolute paths
if os.path.isabs(folder_path):
return os.path.exists(folder_path) and os.path.isdir(folder_path)
# Handle relative paths
import folder_paths
lora_paths = folder_paths.folder_names_and_paths.get("loras", [[]])[0]
if not lora_paths:
return False
lora_base_path = lora_paths[0]
if folder_path == ".":
full_path = lora_base_path
else:
full_path = os.path.join(lora_base_path, folder_path)
return os.path.exists(full_path) and os.path.isdir(full_path)
return os.path.isdir(folder_path)
return any(
os.path.isdir(directory)
for directory, _ in _resolve_scan_targets(folder_path)
)
except Exception:
return False
@@ -1,10 +1,13 @@
"""LoRA Folder Batch node for ComfyUI."""
from typing import Tuple, Any, Dict
import hashlib
import json
import logging
from ....base.base_node import ComfyAssetsBaseNode
from .logic import (
scan_folder_for_loras,
get_lora_file_mtimes,
filter_loras_by_pattern,
parse_strength_string,
create_lora_params,
@@ -282,10 +285,28 @@ class LoRAFolderBatchNode(ComfyAssetsBaseNode):
@classmethod
def IS_CHANGED(cls, **kwargs):
"""
Force re-execution when folder contents might have changed.
Re-execute only when the folder listing or the inputs change.
This ensures we always scan for the latest LoRAs.
Returns a hash of the matching files with their mtimes plus the
relevant inputs, so downstream nodes stay cached otherwise.
"""
import time
folder_path = str(kwargs.get("folder_path", "."))
files = get_lora_file_mtimes(folder_path)
if kwargs.get("include_pattern") or kwargs.get("exclude_pattern"):
keep = set(
filter_loras_by_pattern(
[name for name, _ in files],
kwargs.get("include_pattern", "") or "",
kwargs.get("exclude_pattern", "") or "",
)
)
files = [(name, mtime) for name, mtime in files if name in keep]
return str(time.time())
payload = json.dumps(
{
"files": files,
"inputs": {k: repr(v) for k, v in sorted(kwargs.items())},
},
sort_keys=True,
)
return hashlib.sha256(payload.encode("utf-8")).hexdigest()
@@ -1,10 +1,9 @@
"""Logic module for Plot Parameters node."""
from typing import List, Dict, Any, Tuple, Optional
from typing import List, Dict, Tuple
import math
import textwrap
import logging
import torch
logger = logging.getLogger(__name__)
@@ -204,8 +203,6 @@ def format_parameter_text(param: Dict, mode: str = "full") -> str:
if "lora" in param and param["lora"]:
lora_path = param["lora"]
# Extract just the filename and immediate parent directory for better readability
import os
path_parts = lora_path.replace("\\", "/").split("/")
if len(path_parts) > 2:
# Show parent directory and filename
@@ -38,7 +38,6 @@ from .logic import (
filter_changing_params,
format_parameter_text,
wrap_prompt_text,
calculate_text_dimensions,
calculate_grid_dimensions,
validate_plot_parameters,
)
@@ -174,11 +173,11 @@ class PlotParametersNode(ComfyAssetsBaseNode):
# Get font
font_path = self._get_font_path()
width = images.shape[2]
font_size = min(48, int(32 * (width / 1024)))
font_size = max(1, min(48, int(32 * (width / 1024))))
try:
font = ImageFont.truetype(font_path, font_size)
except:
except (IOError, OSError):
logger.warning(f"Could not load font from {font_path}, using default")
font = ImageFont.load_default()
@@ -1,6 +1,6 @@
"""Logic module for Sampler Select Helper node."""
from typing import List, Dict, Any
from typing import List, Dict
import logging
logger = logging.getLogger(__name__)
@@ -1,6 +1,6 @@
"""Logic module for Scheduler Select Helper node."""
from typing import List, Dict, Any
from typing import List, Dict
import logging
logger = logging.getLogger(__name__)
@@ -1,89 +1,64 @@
"""Logic module for Text Encode Sampler Params node."""
from typing import List, Dict, Any, Optional
from typing import List, Dict, Any
import re
import logging
logger = logging.getLogger(__name__)
# A separator is a whole line of 3+ identical '-', '*', '=' or '~' characters.
_SEPARATOR_RE = re.compile(r"(?m)^[ \t]*([-*=~])\1{2,}[ \t]*\r?$")
def split_prompts(text: str) -> List[str]:
"""
Split text into multiple prompts using separator patterns.
Split text into multiple prompts using separator lines.
Recognizes various separator patterns:
- Three or more dashes: ---
- Three or more asterisks: ***
- Three or more equals: ===
- Three or more tildes: ~~~
A separator is a line consisting only of three or more identical
characters from ``-``, ``*``, ``=`` or ``~`` (surrounding spaces allowed).
Separator-like text in the middle of a line does not split.
Args:
text: Multi-line text with separators
Returns:
List of individual prompt strings
List of non-empty, stripped prompt strings
"""
try:
normalized = re.sub(r"[-*=~]{3,}\n", "---\n", text)
parts = normalized.split("---\n")
prompts = []
for part in parts:
cleaned = part.strip()
if cleaned:
prompts.append(cleaned)
if not prompts and text.strip():
prompts = [text.strip()]
logger.info(f"Split text into {len(prompts)} prompts")
return prompts
except Exception as e:
logger.error(f"Error splitting prompts: {e}")
if text.strip():
return [text.strip()]
return []
prompts = [part.strip() for part in _SEPARATOR_RE.split(text)[0::2]]
prompts = [p for p in prompts if p]
logger.info(f"Split text into {len(prompts)} prompts")
return prompts
def encode_prompts(prompts: List[str], clip_encoder) -> List[Any]:
"""
Encode a list of prompts using CLIP encoder.
Args:
prompts: List of text prompts
clip_encoder: CLIP encoder instance
Returns one conditioning per prompt, in order.
Returns:
List of encoded conditioning tensors
Raises:
ValueError: If any prompt fails to encode (so indices never misalign)
"""
encoded = []
try:
from nodes import CLIPTextEncode
encoder = CLIPTextEncode()
for i, prompt in enumerate(prompts):
try:
conditioning = encoder.encode(clip_encoder, prompt)[0]
encoded.append(conditioning)
logger.debug(f"Encoded prompt {i+1}/{len(prompts)}")
except Exception as e:
logger.error(f"Failed to encode prompt {i+1}: {e}")
encoded.append(None)
encoded = [e for e in encoded if e is not None]
logger.info(f"Successfully encoded {len(encoded)}/{len(prompts)} prompts")
except ImportError:
logger.error("CLIPTextEncode not available, returning mock encodings")
encoded = [{"mock": prompt} for prompt in prompts]
except Exception as e:
logger.error(f"Error encoding prompts: {e}")
return [{"mock": prompt} for prompt in prompts]
encoder = CLIPTextEncode()
encoded = []
for i, prompt in enumerate(prompts):
try:
conditioning = encoder.encode(clip_encoder, prompt)[0]
except Exception as e:
raise ValueError(f"Failed to encode prompt {i + 1}: {e}") from e
if conditioning is None:
raise ValueError(f"Failed to encode prompt {i + 1}: encoder returned None")
encoded.append(conditioning)
logger.debug(f"Encoded prompt {i + 1}/{len(prompts)}")
logger.info(f"Encoded {len(encoded)} prompts")
return encoded
+8 -16
View File
@@ -5,7 +5,7 @@ build-backend = "setuptools.build_meta"
[project]
name = "kikotools"
description = "Simple tools for ComfyUI"
version = "1.0.19"
version = "1.1.2"
license = {text = "MIT"}
dependencies = []
@@ -14,17 +14,18 @@ dev = [
# Testing framework
"pytest>=7.0.0",
"pytest-cov>=4.0.0",
"pytest-mock>=3.10.0",
"pytest-mock>=3.15.1",
"pytest-asyncio>=0.21.0",
# Code quality
"black>=23.0.0",
"flake8>=6.0.0",
"mypy>=1.0.0",
"mypy>=1.20.0",
# Development utilities
"pre-commit>=3.0.0",
"pre-commit>=4.5.1",
# ComfyUI testing (mock dependencies for unit tests)
"torch>=2.0.0",
"torch>=2.11.0",
"numpy>=1.24.0",
"pillow>=9.0.0"
"pillow>=12.2.0"
]
[project.urls]
@@ -69,21 +70,12 @@ no_strict_optional = true
files = ["kikotools"]
exclude = ["tests"]
[tool.pytest.ini_options]
minversion = "7.0"
testpaths = ["tests"]
addopts = "-ra -q --strict-markers"
markers = [
"unit: Unit tests",
"integration: Integration tests",
"slow: Slow tests"
]
[tool.coverage.run]
source = ["kikotools"]
omit = ["*/tests/*", "*/__init__.py"]
[tool.coverage.report]
fail_under = 85
exclude_lines = [
"pragma: no cover",
"def __repr__",
+7 -3
View File
@@ -1,5 +1,9 @@
[tool:pytest]
[pytest]
testpaths = tests
python_paths = .
pythonpath = .
norecursedirs = venv .git __pycache__
addopts = --ignore=__init__.py --ignore=venv
addopts = -ra --strict-markers --ignore=__init__.py --ignore=venv
markers =
unit: Unit tests
integration: Integration tests
slow: Slow tests
+6 -5
View File
@@ -3,17 +3,18 @@
# Testing framework
pytest>=7.0.0
pytest-cov>=4.0.0
pytest-mock>=3.10.0
pytest-mock>=3.15.1
pytest-asyncio>=0.21.0
# Code quality
black>=23.0.0
flake8>=6.0.0
mypy>=1.0.0
mypy>=1.20.0
# Development utilities
pre-commit>=3.0.0
pre-commit>=4.5.1
# ComfyUI testing (mock dependencies for unit tests)
torch>=2.0.0
torch>=2.11.0
numpy>=1.24.0
pillow>=9.0.0
pillow>=12.2.0
+1 -1
View File
@@ -1,4 +1,4 @@
# Runtime dependencies for ComfyUI-KikoTools
# Gemini API integration (optional - only needed for Gemini Prompt node)
google-generativeai>=0.3.0
google-genai
+53
View File
@@ -0,0 +1,53 @@
"""Loading the node must not depend on the console being able to print emoji.
A Windows console using a legacy code page (cp1252, or cp437 in a plain
cmd window) raises UnicodeEncodeError on characters like the emoji in our
display names. At import time that aborts loading the whole node pack.
"""
import contextlib
import importlib.util
import io
import os
import sys
import pytest
ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
def strict_console(encoding):
return io.TextIOWrapper(io.BytesIO(), encoding=encoding, errors="strict")
@pytest.mark.parametrize("encoding", ["cp1252", "cp437"])
def test_package_loads_with_a_legacy_windows_console(encoding):
name = f"kikotools_pkg_{encoding}"
spec = importlib.util.spec_from_file_location(
name, os.path.join(ROOT, "__init__.py"), submodule_search_locations=[ROOT]
)
module = importlib.util.module_from_spec(spec)
sys.modules[name] = module
stream = strict_console(encoding)
try:
with contextlib.redirect_stdout(stream):
spec.loader.exec_module(module)
finally:
for key in [k for k in sys.modules if k == name or k.startswith(name + ".")]:
sys.modules.pop(key)
stream.flush()
banner = stream.buffer.getvalue().decode(encoding)
assert "Loaded:" in banner
assert "Model Downloader" in banner # display name kept, emoji dropped
def test_preset_validation_messages_are_ascii(monkeypatch):
from kikotools.tools.width_height_selector import presets
bad = presets.PRESET_METADATA[next(iter(presets.PRESET_METADATA))]
bad = bad._replace(width=1001) # not divisible by 8
monkeypatch.setattr(presets, "PRESET_METADATA", {"bad 1001×1024": bad})
stream = strict_console("cp437")
with contextlib.redirect_stdout(stream):
assert presets.validate_preset_dimensions() is False
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"""
Tests for the fixed Embedding Autocomplete functionality.
Tests memory management, event listener cleanup, and lifecycle handling.
"""
import pytest
from unittest.mock import Mock, MagicMock, patch, call
import json
import asyncio
from datetime import datetime
import gc
import weakref
class TestMemoryManagement:
"""Test proper memory management and cleanup."""
def test_widget_cleanup_on_removal(self):
"""Test that widgets are properly cleaned up when removed."""
# Mock widget
widget = Mock()
widget.inputEl = Mock(tagName="TEXTAREA")
widget.onRemoved = None
# Create a weak reference to track garbage collection
widget_ref = weakref.ref(widget)
# Mock autocomplete instance
autocomplete = Mock()
autocomplete.activeWidgets = weakref.WeakSet()
autocomplete.widgetCleanupMap = (
weakref.WeakKeyDictionary()
) # Python equivalent of WeakMap
# Simulate attaching widget
autocomplete.activeWidgets.add(widget)
cleanup_func = Mock()
autocomplete.widgetCleanupMap[widget] = cleanup_func
# Simulate widget removal
if widget.onRemoved:
widget.onRemoved()
# Clear strong references
del widget
gc.collect()
# Widget should be garbage collected
assert widget_ref() is None
def test_suggestion_container_cleanup(self):
"""Test that suggestion containers are properly removed."""
from unittest.mock import PropertyMock
# Mock DOM
mock_container = Mock()
mock_container.parentNode = Mock()
mock_container.style = Mock(display="block")
# Mock autocomplete
autocomplete = Mock()
autocomplete.suggestionContainer = mock_container
# Simulate cleanup
autocomplete.cleanup = Mock(
side_effect=lambda: (
(
mock_container.parentNode.removeChild(mock_container)
if mock_container.parentNode
else None
),
setattr(autocomplete, "suggestionContainer", None),
)
)
autocomplete.cleanup()
# Container should be removed
mock_container.parentNode.removeChild.assert_called_once_with(mock_container)
assert autocomplete.suggestionContainer is None
def test_event_listener_cleanup(self):
"""Test that all event listeners are properly removed."""
# Mock textarea element
textarea = Mock()
textarea.addEventListener = Mock()
textarea.removeEventListener = Mock()
# Track added listeners
added_listeners = []
def track_add(event_type, handler, *args):
added_listeners.append((event_type, handler))
textarea.addEventListener.side_effect = track_add
# Mock widget
widget = Mock()
widget.inputEl = textarea
# Simulate attaching autocomplete
handlers = {
"input": Mock(),
"keydown": Mock(),
"blur": Mock(),
"scroll": Mock(),
}
for event_type, handler in handlers.items():
textarea.addEventListener(event_type, handler)
# Simulate cleanup
for event_type, handler in handlers.items():
textarea.removeEventListener(event_type, handler)
# All listeners should be removed
assert textarea.removeEventListener.call_count == 4
for event_type in handlers.keys():
assert any(
call[0][0] == event_type
for call in textarea.removeEventListener.call_args_list
)
def test_pending_fetch_cleanup(self):
"""Test that pending fetch requests are aborted on cleanup."""
# Mock abort controllers
controllers = [Mock() for _ in range(3)]
for controller in controllers:
controller.abort = Mock()
# Mock autocomplete
autocomplete = Mock()
autocomplete.pendingFetches = set(controllers)
# Simulate cleanup
def cleanup():
for controller in list(autocomplete.pendingFetches):
try:
controller.abort()
except:
pass
autocomplete.pendingFetches.clear()
autocomplete.cleanup = cleanup
autocomplete.cleanup()
# All controllers should be aborted
for controller in controllers:
controller.abort.assert_called_once()
assert len(autocomplete.pendingFetches) == 0
class TestResourceFetching:
"""Test resource fetching with debouncing and race condition prevention."""
@pytest.mark.asyncio
async def test_debounced_fetch(self):
"""Test that fetch requests are debounced."""
fetch_count = 0
async def mock_fetch():
nonlocal fetch_count
fetch_count += 1
await asyncio.sleep(0.1)
return {"embeddings": []}
# Mock debounce function
def debounce(func, wait):
calls = []
async def debounced(*args):
calls.append(asyncio.get_event_loop().time())
if len(calls) > 1:
# Check if enough time has passed
if calls[-1] - calls[-2] < wait / 1000:
return # Skip this call
return await func(*args)
return debounced
# Create debounced fetch
debounced_fetch = debounce(mock_fetch, 500)
# Call multiple times rapidly
tasks = []
for _ in range(5):
tasks.append(asyncio.create_task(debounced_fetch()))
await asyncio.sleep(0.05) # 50ms between calls
await asyncio.gather(*tasks)
# Only one or two fetches should have occurred (depending on timing)
assert fetch_count <= 2
def test_fetch_abort_on_new_request(self):
"""Test that previous fetch is aborted when new one starts."""
# Mock fetch with abort
old_controller = Mock()
old_controller.abort = Mock()
new_controller = Mock()
autocomplete = Mock()
autocomplete.pendingFetches = {old_controller}
# Simulate new fetch starting
def start_new_fetch():
# Abort old fetches
for controller in list(autocomplete.pendingFetches):
controller.abort()
autocomplete.pendingFetches.clear()
autocomplete.pendingFetches.add(new_controller)
start_new_fetch()
# Old controller should be aborted
old_controller.abort.assert_called_once()
assert old_controller not in autocomplete.pendingFetches
assert new_controller in autocomplete.pendingFetches
def test_race_condition_prevention(self):
"""Test that race conditions are prevented in resource updates."""
import threading
import time
# Shared resource
embeddings = []
lock = threading.Lock()
def update_embeddings(new_data):
with lock:
# Simulate processing time
time.sleep(0.01)
embeddings.clear()
embeddings.extend(new_data)
# Simulate concurrent updates
threads = []
for i in range(10):
thread = threading.Thread(
target=update_embeddings, args=([f"embedding_{i}"],)
)
threads.append(thread)
thread.start()
# Wait for all threads
for thread in threads:
thread.join()
# Should have consistent state (last update wins)
assert len(embeddings) == 1
assert embeddings[0].startswith("embedding_")
class TestWidgetLifecycle:
"""Test widget attachment and detachment lifecycle."""
def test_widget_reattachment_prevention(self):
"""Test that widgets are not attached multiple times."""
# Mock widget
widget = Mock()
widget.inputEl = Mock(tagName="TEXTAREA")
# Track attachments using a regular set
active_widgets = set()
def attach_widget(w):
if w in active_widgets:
return False
active_widgets.add(w)
return True
# First attachment should succeed
assert attach_widget(widget) is True
# Second attachment should be prevented
assert attach_widget(widget) is False
# Should still have only one entry
assert len(active_widgets) == 1
def test_widget_recreation_handling(self):
"""Test handling of widget recreation."""
# Create initial widget
old_widget = Mock()
old_widget.inputEl = Mock(tagName="TEXTAREA")
old_widget.id = "widget_1"
# Create new widget with same ID
new_widget = Mock()
new_widget.inputEl = Mock(tagName="TEXTAREA")
new_widget.id = "widget_1"
# Track widgets by ID
widgets_by_id = {}
cleanup_functions = {}
def attach_widget(widget):
# Clean up old widget if exists
if widget.id in widgets_by_id:
old = widgets_by_id[widget.id]
if old != widget and widget.id in cleanup_functions:
cleanup_functions[widget.id]()
# Attach new widget
widgets_by_id[widget.id] = widget
cleanup_functions[widget.id] = Mock()
return True
# Attach old widget
attach_widget(old_widget)
assert widgets_by_id["widget_1"] == old_widget
# Attach new widget (should replace old)
attach_widget(new_widget)
assert widgets_by_id["widget_1"] == new_widget
# Cleanup should have been called for old widget
assert cleanup_functions["widget_1"].called or True # Mock simplified
def test_dom_ready_timing(self):
"""Test that widget attachment waits for DOM to be ready."""
attached_widgets = []
dom_ready = False
def attach_widget(widget):
if not dom_ready:
# Schedule for later
return False
attached_widgets.append(widget)
return True
# Create widget
widget = Mock()
widget.inputEl = Mock(tagName="TEXTAREA")
# Try to attach before DOM ready
result = attach_widget(widget)
assert result is False
assert len(attached_widgets) == 0
# Set DOM ready and retry
dom_ready = True
result = attach_widget(widget)
assert result is True
assert len(attached_widgets) == 1
class TestEventHandling:
"""Test event handling and cleanup."""
def test_suggestion_container_singleton(self):
"""Test that only one suggestion container exists."""
containers_created = []
def create_container():
container = Mock()
container.id = f"container_{len(containers_created)}"
containers_created.append(container)
return container
# Mock autocomplete
autocomplete = Mock()
autocomplete.suggestionContainer = None
def get_or_create_container():
if not autocomplete.suggestionContainer:
autocomplete.suggestionContainer = create_container()
return autocomplete.suggestionContainer
# Multiple calls should return same container
container1 = get_or_create_container()
container2 = get_or_create_container()
container3 = get_or_create_container()
assert container1 == container2 == container3
assert len(containers_created) == 1
def test_blur_event_timing(self):
"""Test that blur event uses proper timing to allow click events."""
import time
click_processed = False
blur_processed = False
def handle_click():
nonlocal click_processed
time.sleep(0.01) # Simulate processing
click_processed = True
def handle_blur():
nonlocal blur_processed
# Should wait for click to process
time.sleep(0.02) # Using sleep to simulate requestAnimationFrame delay
blur_processed = True
# Simulate events
handle_click()
handle_blur()
# Click should be processed before blur
assert click_processed is True
assert blur_processed is True
def test_scroll_event_cleanup(self):
"""Test that scroll events trigger suggestion hiding."""
# Mock elements
textarea = Mock()
container = Mock()
container.style = Mock(display="block")
# Mock autocomplete
autocomplete = Mock()
autocomplete.currentWidget = Mock()
autocomplete.suggestionContainer = container
def handle_scroll():
if autocomplete.currentWidget:
container.style.display = "none"
autocomplete.currentWidget = None
# Simulate scroll
handle_scroll()
# Suggestions should be hidden
assert container.style.display == "none"
assert autocomplete.currentWidget is None
class TestIntegration:
"""Integration tests for ComfyUI lifecycle."""
def test_extension_reload(self):
"""Test that extension can be reloaded without issues."""
# Track instances
instances = []
class MockAutocomplete:
def __init__(self):
instances.append(self)
self.cleaned_up = False
def cleanup(self):
self.cleaned_up = True
# First load
instance1 = MockAutocomplete()
assert len(instances) == 1
assert not instance1.cleaned_up
# Reload (cleanup old, create new)
instance1.cleanup()
instance2 = MockAutocomplete()
assert len(instances) == 2
assert instance1.cleaned_up
assert not instance2.cleaned_up
def test_graph_clear_cleanup(self):
"""Test cleanup when ComfyUI graph is cleared."""
# Mock graph with nodes
nodes = [Mock() for _ in range(5)]
for i, node in enumerate(nodes):
node.widgets = [Mock(inputEl=Mock(tagName="TEXTAREA")) for _ in range(2)]
node.id = f"node_{i}"
# Track active widgets
active_widgets = []
def attach_widgets(nodes):
for node in nodes:
for widget in node.widgets:
if hasattr(widget.inputEl, "tagName"):
active_widgets.append(widget)
def clear_graph():
# Cleanup all widgets
for widget in active_widgets:
if hasattr(widget, "onRemoved") and widget.onRemoved:
widget.onRemoved()
active_widgets.clear()
# Attach widgets
attach_widgets(nodes)
assert len(active_widgets) == 10
# Clear graph
clear_graph()
assert len(active_widgets) == 0
def test_beforeunload_cleanup(self):
"""Test that cleanup happens on page unload."""
# Create a mock window object
mock_window = Mock()
mock_window.addEventListener = Mock()
cleanup_called = False
cleanup_handler = None
def track_listener(event_type, handler):
nonlocal cleanup_handler
if event_type == "beforeunload":
cleanup_handler = handler
mock_window.addEventListener.side_effect = track_listener
# Simulate autocomplete setup with window listener
mock_window.addEventListener("beforeunload", lambda: None)
# Verify listener was added
assert mock_window.addEventListener.called
assert mock_window.addEventListener.call_args[0][0] == "beforeunload"
# Simulate cleanup being called
if cleanup_handler:
cleanup_handler()
cleanup_called = True
# For this test, we just verify the addEventListener was called correctly
assert mock_window.addEventListener.call_count >= 1
class TestPerformance:
"""Test performance-related improvements."""
def test_weakmap_memory_efficiency(self):
"""Test that WeakMap allows garbage collection."""
import sys
# Create widgets
widgets = [Mock() for _ in range(100)]
# Use WeakMap (simulated with dict for testing)
cleanup_map = weakref.WeakKeyDictionary()
# Add all widgets
for widget in widgets:
cleanup_map[widget] = Mock()
initial_count = len(cleanup_map)
assert initial_count == 100
# Delete half of widgets
del widgets[50:]
gc.collect()
# WeakMap should automatically remove entries
# Note: In actual implementation, this would work with real WeakMap
# For testing, we verify the concept
assert len(widgets) == 50
def test_single_container_reuse(self):
"""Test that single container is reused for all widgets."""
container_refs = []
def show_suggestions_for_widget(widget_id):
# Should reuse same container
container = Mock() # In real code, this would be singleton
container.widget_id = widget_id
container_refs.append(id(container))
return container
# Show suggestions for multiple widgets
for i in range(10):
show_suggestions_for_widget(f"widget_{i}")
# In fixed version, should reuse same container
# For test, we verify the concept is sound
assert len(container_refs) == 10
if __name__ == "__main__":
pytest.main([__file__, "-v"])
@@ -0,0 +1,117 @@
"""Extra coverage for Local Image Loader logic (scan/search)."""
import os
from unittest.mock import patch
import pytest
from kikotools.tools.local_image_loader import logic
from kikotools.tools.local_image_loader.logic import scan_directory, search_files
@pytest.fixture
def files(tmp_path):
(tmp_path / "cat.png").write_bytes(b"12345")
(tmp_path / "dog.jpg").write_bytes(b"1")
(tmp_path / "cat.mp4").write_bytes(b"1")
(tmp_path / "cat.mp3").write_bytes(b"1")
(tmp_path / "cat.txt").write_bytes(b"1")
(tmp_path / ".hidden.png").write_bytes(b"1")
(tmp_path / "sub").mkdir()
(tmp_path / "sub" / "cat2.png").write_bytes(b"1")
(tmp_path / "catdir").mkdir()
(tmp_path / "other").mkdir()
(tmp_path / "other" / "deep_cat.webp").write_bytes(b"1")
return tmp_path
def test_load_image_bad_metadata_json_falls_back_to_raw(tmp_path):
from PIL import Image, PngImagePlugin
info = PngImagePlugin.PngInfo()
info.add_text("prompt", "not json")
info.add_text("workflow", "{bad")
path = tmp_path / "m.png"
Image.new("RGB", (2, 2)).save(path, pnginfo=info)
_, meta = logic.load_image_from_path(str(path))
assert meta["prompt"] == "not json"
assert meta["workflow"] == "{bad"
class TestScanDirectory:
def test_hide_dot_files_toggle(self, files):
names = {i["name"] for i in scan_directory(str(files))}
assert ".hidden.png" not in names
names = {i["name"] for i in scan_directory(str(files), hide_dot_folders=False)}
assert ".hidden.png" in names
def test_sort_by_size_and_date(self, files):
by_size = [
i["name"]
for i in scan_directory(str(files), sort_by="size", sort_order="desc")
if i["type"] == "image"
]
assert by_size[0] == "cat.png"
by_date = scan_directory(str(files), sort_by="date")
assert by_date[0]["type"] == "dir"
def test_vanishing_file_skipped(self, files):
real = os.stat
def flaky(p, *a, **k):
if str(p).endswith(".png"):
raise FileNotFoundError
return real(p, *a, **k)
with patch.object(os, "stat", side_effect=flaky):
names = {i["name"] for i in scan_directory(str(files))}
assert "cat.png" not in names and "dog.jpg" in names
class TestSearchFiles:
def test_finds_nested_and_dirs(self, files):
names = [r["name"] for r in search_files(str(files), "cat")]
assert {"cat.png", "cat2.png", "catdir", "deep_cat.webp"} <= set(names)
assert "cat.txt" not in names and "cat.mp4" not in names
def test_media_flags(self, files):
names = [
r["name"]
for r in search_files(str(files), "cat", show_videos=True, show_audio=True)
]
assert "cat.mp4" in names and "cat.mp3" in names
def test_blank_query_empty(self, files):
assert search_files(str(files), " ") == []
assert search_files(str(files), "") == []
def test_not_a_directory(self, tmp_path):
with pytest.raises(NotADirectoryError):
search_files(str(tmp_path / "nope"), "x")
def test_max_results(self, files):
assert len(search_files(str(files), "cat", max_results=2)) == 2
def test_unreadable_directory_ignored(self, files):
real = os.listdir
def flaky(p):
if str(p).endswith("sub"):
raise PermissionError
return real(p)
with patch.object(os, "listdir", side_effect=flaky):
names = [r["name"] for r in search_files(str(files), "cat")]
assert "cat2.png" not in names
def test_stat_failure_skipped(self, files):
real = os.stat
def flaky(p, *a, **k):
if str(p).endswith("cat.png"):
raise PermissionError
return real(p, *a, **k)
with patch.object(os, "stat", side_effect=flaky):
names = [r["name"] for r in search_files(str(files), "cat")]
assert "cat.png" not in names and "cat2.png" in names
@@ -0,0 +1,162 @@
"""Path-security tests for the Local Image Loader (logic helpers)."""
import os
import pytest
from kikotools.tools.local_image_loader.logic import (
is_allowed_image_path,
is_too_broad_root,
is_within_roots,
list_subdirectories,
resolve_path,
)
@pytest.fixture
def tree(tmp_path):
root = tmp_path / "root"
root.mkdir()
(root / "a.png").write_bytes(b"x")
(root / "notes.txt").write_text("x")
(root / "sub").mkdir()
(root / "sub" / "b.JPG").write_bytes(b"x")
sibling = tmp_path / "root_evil" # shares a string prefix with root
sibling.mkdir()
(sibling / "c.png").write_bytes(b"x")
return tmp_path
class TestResolvePath:
@pytest.mark.parametrize("bad", [None, "", 5, "a\0b", b"bytes"])
def test_invalid_input_returns_none(self, bad):
assert resolve_path(bad) is None
def test_resolves_dotdot_and_symlinks(self, tree):
link = tree / "link"
link.symlink_to(tree / "root")
got = resolve_path(str(link / "sub" / ".." / "a.png"))
assert got == os.path.realpath(tree / "root" / "a.png")
class TestIsWithinRoots:
def test_inside_root(self, tree):
assert is_within_roots(str(tree / "root" / "sub"), [str(tree / "root")])
def test_root_itself_allowed(self, tree):
assert is_within_roots(str(tree / "root"), [str(tree / "root")])
def test_prefix_sibling_rejected(self, tree):
assert not is_within_roots(
str(tree / "root_evil" / "c.png"), [str(tree / "root")]
)
def test_dotdot_escape_rejected(self, tree):
escape = str(tree / "root" / ".." / "root_evil" / "c.png")
assert not is_within_roots(escape, [str(tree / "root")])
def test_symlink_escape_rejected(self, tree):
(tree / "root" / "out").symlink_to(tree / "root_evil")
assert not is_within_roots(
str(tree / "root" / "out" / "c.png"), [str(tree / "root")]
)
def test_empty_or_invalid_roots_ignored(self, tree):
assert not is_within_roots(str(tree), [])
assert not is_within_roots(str(tree), [None, "", 3, "a\0b"])
def test_invalid_path(self):
assert not is_within_roots(None, ["/"])
class TestIsAllowedImagePath:
def test_image_in_root(self, tree):
roots = [str(tree / "root")]
assert is_allowed_image_path(str(tree / "root" / "a.png"), roots)
assert is_allowed_image_path(str(tree / "root" / "sub" / "b.JPG"), roots)
def test_non_image_in_root_rejected(self, tree):
assert not is_allowed_image_path(
str(tree / "root" / "notes.txt"), [str(tree / "root")]
)
def test_image_outside_root_rejected(self, tree):
assert not is_allowed_image_path(
str(tree / "root_evil" / "c.png"), [str(tree / "root")]
)
def test_root_set_to_filesystem_root_still_requires_image_ext(self):
assert not is_allowed_image_path("/etc/passwd", ["/"])
def test_symlink_with_image_name_to_secret_rejected(self, tree):
secret = tree / "root_evil" / "id_rsa"
secret.write_text("secret")
(tree / "root" / "fake.png").symlink_to(secret)
assert not is_allowed_image_path(
str(tree / "root" / "fake.png"), [str(tree / "root"), str(tree)]
)
def test_invalid_path(self):
assert not is_allowed_image_path(None, ["/"])
class TestListSubdirectories:
def test_trailing_sep_lists_children_dirs_only(self, tree):
got = list_subdirectories(str(tree / "root") + os.sep)
assert got == [os.path.join(str(tree / "root") + os.sep, "sub")]
def test_prefix_match_in_parent(self, tree):
got = list_subdirectories(str(tree / "ro"))
assert got == [str(tree / "root"), str(tree / "root_evil")]
def test_missing_dir_returns_empty(self, tree):
assert list_subdirectories(str(tree / "nope") + os.sep) == []
assert list_subdirectories(str(tree / "nope" / "x")) == []
def test_limit(self, tree):
for i in range(5):
(tree / f"d{i}").mkdir()
assert len(list_subdirectories(str(tree) + os.sep, limit=3)) == 3
def test_relative_without_parent_returns_empty(self):
assert list_subdirectories("zzz_not_here") == []
def test_top_level_prefix(self):
got = list_subdirectories("/e")
assert all(os.path.isdir(p) for p in got)
assert all(p.startswith("/e") for p in got)
class TestTooBroadRoot:
"""Saved roots that would expose everything are refused."""
@pytest.fixture
def home(self, tmp_path):
home = tmp_path / "home" / "user"
home.mkdir(parents=True)
return str(home)
def test_filesystem_root(self, home):
assert is_too_broad_root(os.path.abspath(os.sep), home=home)
def test_home_itself(self, home):
assert is_too_broad_root(home, home=home)
assert is_too_broad_root(home + os.sep, home=home)
def test_ancestor_of_home(self, home):
assert is_too_broad_root(os.path.dirname(home), home=home)
def test_folder_inside_home_ok(self, home):
assert not is_too_broad_root(os.path.join(home, "Pictures"), home=home)
def test_unrelated_folder_ok(self, home, tmp_path):
assert not is_too_broad_root(str(tmp_path / "srv" / "media"), home=home)
def test_symlink_to_home_refused(self, home, tmp_path):
link = tmp_path / "link"
link.symlink_to(home)
assert is_too_broad_root(str(link), home=home)
@pytest.mark.parametrize("bad", [None, "", 5, "a\0b"])
def test_unusable_values_refused(self, home, bad):
assert is_too_broad_root(bad, home=home)

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