* feat: add configurable shift parameter for Z-Image sigma schedule
Add a shift (mu) override to the Z-Image denoise invocation and expose
it in the UI. When left blank, shift is auto-calculated from image
dimensions (existing behavior). Users can override to fine-tune the
timestep schedule, with an inline X button to reset back to auto.
* refactor: switch Z-Image sigma schedule from exponential to linear time shift
Use shift directly as a linear multiplier instead of exp(mu), giving
more predictable and uniform control over the timestep schedule.
Auto-calculated values are converted via exp(mu) to preserve identical
default behavior.
* feat: recall Z-Image shift parameter from metadata
Write z_image_shift into graph metadata and add a ZImageShift recall
handler so the shift override can be restored from previously generated
images. Auto-mode (null) is omitted from metadata to avoid persisting a
stale value.
---------
Co-authored-by: Lincoln Stein <lincoln.stein@gmail.com>
openapi-typescript computes enum types from `const` usage in
discriminated unions rather than from the enum definition itself,
dropping values that only appear in some union members (e.g. "anima"
from BaseModelType). Add a post-processing step that patches generated
string enum types to match the actual OpenAPI schema definitions.
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: Alexander Eichhorn <alex@eichhorn.dev>
* fix(ui): replace all hardcoded frontend strings with i18n translation keys
Remove fallback/defaultValue strings from t() calls, replace hardcoded
English text in labels, tooltips, aria-labels, placeholders and JSX content
with proper t() calls, and add ~50 missing keys to en.json. Fix incorrect
i18n key paths in CanvasObjectImage.ts and a Zoom button aria-label bug
in CanvasToolbarScale.tsx.
* chore pnpm run fix
---------
Co-authored-by: Lincoln Stein <lincoln.stein@gmail.com>
* feat(frontend): suppress tooltips on touch devices
* fix(frontend): change selector to role="tooltip" because .chakra-tooltip does not match
* chore(frontend): lint:prettier
* feat: add Anima model support
* schema
* image to image
* regional guidance
* loras
* last fixes
* tests
* fix attributions
* fix attributions
* refactor to use diffusers reference
* fix an additional lora type
* some adjustments to follow flux 2 paper implementation
* use t5 from model manager instead of downloading
* make lora identification more reliable
* fix: resolve lint errors in anima module
Remove unused variable, fix import ordering, inline dict() call,
and address minor lint issues across anima-related files.
* Chore Ruff format again
* fix regional guidance error
* fix(anima): validate unexpected keys after strict=False checkpoint loading
Capture the load_state_dict result and raise RuntimeError on unexpected
keys (indicating a corrupted or incompatible checkpoint), while logging
a warning for missing keys (expected for inv_freq buffers regenerated
at runtime).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(anima): make model loader submodel fields required instead of Optional
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(anima): add Classification.Prototype to LoRA loaders, fix exception types
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(anima): fix replace-all in key conversion, warn on DoRA+LoKR, unify grouping functions
- Use key.replace(old, new, 1) in _convert_kohya_unet_key and _convert_kohya_te_key to avoid replacing multiple occurrences
- Upgrade DoRA+LoKR dora_scale strip from logger.debug to logger.warning since it represents data loss
- Replace _group_kohya_keys and _group_by_layer with a single _group_keys_by_layer function parameterized by extra_suffixes, with _KOHYA_KNOWN_SUFFIXES and _PEFT_EXTRA_SUFFIXES constants
- Add test_empty_state_dict_returns_empty_model to verify empty input produces a model with no layers
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(anima): add safety cap for Qwen3 sequence length to prevent OOM
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(anima): add denoising range validation, fix closure capture, add edge case tests
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(anima): add T5 to metadata, fix dead code, decouple scheduler type guard
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(anima): update VAE field description for required field
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* chore: regenerate frontend types after upstream merge
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* chore: ruff format anima_denoise.py
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix(anima): add T5 encoder metadata recall handler
The T5 encoder was added to generation metadata but had no recall
handler, so it wasn't restored when recalling from metadata.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* chore(frontend): add regression test for buildAnimaGraph
Add tests for CFG gating (negative conditioning omitted when cfgScale <= 1)
and basic graph structure (model loader, text encoder, denoise nodes).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* only show 0.6b for anima
* dont show 0.6b for other models
* schema
* Anima preview 3
* fix ci
---------
Co-authored-by: Your Name <you@example.com>
Co-authored-by: kappacommit <samwolfe40@gmail.com>
Co-authored-by: Alexander Eichhorn <alex@eichhorn.dev>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Lincoln Stein <lincoln.stein@gmail.com>
* feat: Add canvas-workflow integration feature
This commit implements a new feature that allows users to run workflows
directly from the unified canvas. Users can now:
- Access a "Run Workflow" option from the canvas layer context menu
- Select a workflow with image parameters from a modal dialog
- Customize workflow parameters (non-image fields)
- Execute the workflow with the current canvas layer as input
- Have the result automatically added back to the canvas
Key changes:
- Added canvasWorkflowIntegrationSlice for state management
- Created CanvasWorkflowIntegrationModal and related UI components
- Added context menu item to raster layers
- Integrated workflow execution with canvas image extraction
- Added modal to global modal isolator
This integration enhances the canvas by allowing users to leverage
custom workflows for advanced image processing directly within the
canvas workspace.
Implements feature request for deeper workflow-canvas integration.
* refactor(ui): simplify canvas workflow integration field rendering
- Extract WorkflowFieldRenderer component for individual field rendering
- Add WorkflowFormPreview component to handle workflow parameter display
- Remove workflow compatibility filtering - allow all workflows
- Simplify workflow selector to use flattened workflow list
- Add comprehensive field type support (String, Integer, Float, Boolean, Enum, Scheduler, Board, Model, Image, Color)
- Implement image field selection UI with radio
* feat(ui): add canvas-workflow-integration logging namespace
* feat(ui): add workflow filtering for canvas-workflow integration
- Add useFilteredWorkflows hook to filter workflows with ImageField inputs
- Add workflowHasImageField utility to check for ImageField in Form Builder
- Only show workflows that have Form Builder with at least one ImageField
- Add loading state while filtering workflows
- Improve error messages to clarify Form Builder requirement
- Update modal description to mention Form Builder and parameter adjustment
- Add fallback error message for workflows without Form Builder
* feat(ui): add persistence and migration for canvas workflow integration state
- Add _version field (v1) to canvasWorkflowIntegrationState for future migrations
- Add persistConfig with migration function to handle version upgrades
- Add persistDenylist to exclude transient state (isOpen, isProcessing, sourceEntityIdentifier)
- Use es-toolkit isPlainObject and tsafe assert for type-safe migration
- Persist selectedWorkflowId and fieldValues across sessions
* pnpm fix imports
* fix(ui): handle workflow errors in canvas staging area and improve form UX
- Clear processing state when workflow execution fails at enqueue time
or during invocation, so the modal doesn't get stuck
- Optimistically update listAllQueueItems cache on queue item status
changes so the staging area immediately exits on failure
- Clear processing state on invocation_error for canvas workflow origin
- Auto-select the only unfilled ImageField in workflow form
- Fix image field overflow and thumbnail sizing in workflow form
* feat(ui): add canvas_output node and entry-based staging area
Add a dedicated `canvas_output` backend invocation node that explicitly
marks which images go to the canvas staging area, replacing the fragile
board-based heuristic. Each `canvas_output` node produces a separate
navigable entry in the staging area, allowing workflows with multiple
outputs to be individually previewed and accepted.
Key changes:
- New `CanvasOutputInvocation` backend node (canvas.py)
- Entry-based staging area model where each output image is a separate
navigable entry with flat next/prev cycling across all items
- Frontend execute hook uses `canvas_output` type detection instead of
board field heuristic, with proper board field value translation
- Workflow filtering requires both Form Builder and canvas_output node
- Updated QueueItemPreviewMini and StagingAreaItemsList for entries
- Tests for entry-based navigation, multi-output, and race conditions
* Chore pnp run fix
* Chore eslint fix
* Remove unused useOutputImageDTO export to fix knip lint
* Update invokeai/frontend/web/src/features/controlLayers/components/CanvasWorkflowIntegration/useCanvasWorkflowIntegrationExecute.tsx
Co-authored-by: dunkeroni <dunkeroni@gmail.com>
* move UI text to en.json
* fix conflicts merge with main
* generate schema
* Chore typegen
---------
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Lincoln Stein <lincoln.stein@gmail.com>
Co-authored-by: dunkeroni <dunkeroni@gmail.com>
Klein 9B Base (undistilled) and Klein 9B (distilled) have identical
architectures and cannot be distinguished from the state dict alone.
Use a filename heuristic ("base" in the name) to detect the Base
variant for checkpoint, GGUF, and diffusers format models.
Also fixes the incorrect guidance_embeds-based detection for diffusers
format, since both variants have guidance_embeds=False.
* feat: add support for OneTrainer BFL Flux LoRA format
Newer versions of OneTrainer export Flux LoRAs using BFL internal key
names (double_blocks, single_blocks, img_attn, etc.) with a
'transformer.' prefix and split QKV projections (qkv.0/1/2, linear1.0/1/2/3).
This format was not recognized by any existing detector.
Add detection and conversion for this format, merging split QKV and
linear1 layers into MergedLayerPatch instances for the fused BFL model.
* chore ruff
OneTrainer exports Z-Image LoRAs with 'transformer.layers.' key prefix
instead of 'diffusion_model.layers.'. Add this prefix (and the
PEFT-wrapped 'base_model.model.transformer.layers.' variant) to the
Z-Image LoRA probe so these models are correctly identified and loaded.
- Add missing aspect ratios (4:5, 5:4, 8:1, 4:1, 1:4, 1:8) to type
system for external model support
- Sync canvas bbox when external model resolution preset is selected
- Use params preset dimensions in buildExternalGraph to prevent
"unsupported aspect ratio" errors
- Lock all bbox controls (resize handles, aspect ratio select,
width/height sliders, swap/optimal buttons) for external models
with fixed dimension presets
- Disable denoise strength slider for external models (not applicable)
- Sync bbox aspect ratio changes back to paramsSlice for external models
- Initialize bbox dimensions when switching to an external model
* Added If node
* Added stricter type checking on inputs
* feat(nodes): make if-node type checks cardinality-aware without loosening global AnyField
* chore: typegen
* Initial plan
* Warn user when credentials have expired in multiuser mode
Agent-Logs-Url: https://github.com/lstein/InvokeAI/sessions/f0947cda-b15c-475d-b7f4-2d553bdf2cd6
Co-authored-by: lstein <111189+lstein@users.noreply.github.com>
* Address code review: avoid multiple localStorage reads in base query
Agent-Logs-Url: https://github.com/lstein/InvokeAI/sessions/f0947cda-b15c-475d-b7f4-2d553bdf2cd6
Co-authored-by: lstein <111189+lstein@users.noreply.github.com>
* bugfix(multiuser): ask user to log back in when authentication token expires
* feat: sliding window session expiry with token refresh
Backend:
- SlidingWindowTokenMiddleware refreshes JWT on each mutating request
(POST/PUT/PATCH/DELETE), returning a new token in X-Refreshed-Token
response header. GET requests don't refresh (they're often background
fetches that shouldn't reset the inactivity timer).
- CORS expose_headers updated to allow X-Refreshed-Token.
Frontend:
- dynamicBaseQuery picks up X-Refreshed-Token from responses and
updates localStorage so subsequent requests use the fresh expiry.
- 401 handler only triggers sessionExpiredLogout when a token was
actually sent (not for unauthenticated background requests).
- ProtectedRoute polls localStorage every 5s and listens for storage
events to detect token removal (e.g. manual deletion, other tabs).
Result: session expires after TOKEN_EXPIRATION_NORMAL (1 day) of
inactivity, not a fixed time after login. Any user-initiated action
resets the clock.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* chore(backend): ruff
* fix: address review feedback on auth token handling
Bug fixes:
- ProtectedRoute: only treat 401 errors as session expiry, not
transient 500/network errors that should not force logout
- Token refresh: use explicit remember_me claim in JWT instead of
inferring from remaining lifetime, preventing silent downgrade of
7-day tokens to 1-day when <24h remains
- TokenData: add remember_me field, set during login
Tests (6 new):
- Mutating requests (POST/PUT/DELETE) return X-Refreshed-Token
- GET requests do not return X-Refreshed-Token
- Unauthenticated requests do not return X-Refreshed-Token
- Remember-me token refreshes to 7-day duration even near expiry
- Normal token refreshes to 1-day duration
- remember_me claim preserved through refresh cycle
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* chore(backend): ruff
---------
Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: lstein <111189+lstein@users.noreply.github.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: Jonathan <34005131+JPPhoto@users.noreply.github.com>
* feat: add bulk reidentify action for models (#8951)
Add a "Reidentify Models" bulk action to the model manager, allowing
users to re-probe multiple models at once instead of one by one.
- Backend: POST /api/v2/models/i/bulk_reidentify endpoint with partial
failure handling (returns succeeded/failed lists)
- Frontend: bulk reidentify mutation, confirmation modal with warning
about custom settings reset, toast notifications for all outcomes
- i18n: new translation keys for bulk reidentify UI strings
* fix typgen
* Fix bulk reidentify failing for models without trigger_phrases
The bulk reidentify endpoint was directly assigning trigger_phrases
without checking if the config type supports it, causing an
AttributeError for ControlNet models. Added the same hasattr guard
used by the individual reidentify endpoint. Also restored the
missing path preservation that the individual endpoint has.
- Remove negative_prompt, steps, guidance, reference_image_weights,
reference_image_modes from external model nodes (unused by any provider)
- Remove supports_negative_prompt, supports_steps, supports_guidance
from ExternalModelCapabilities
- Add provider_options dict to ExternalGenerationRequest for
provider-specific parameters
- Add OpenAI-specific fields: quality, background, input_fidelity
- Add Gemini-specific fields: temperature, thinking_level
- Add new OpenAI starter models: GPT Image 1.5, GPT Image 1 Mini,
DALL-E 3, DALL-E 2
- Fix OpenAI provider to use output_format (GPT Image) vs
response_format (DALL-E) and send model ID in requests
- Add fixed aspect ratio sizes for OpenAI models (bucketing)
- Add ExternalProviderRateLimitError with retry logic for 429 responses
- Add provider-specific UI components in ExternalSettingsAccordion
- Simplify ParamSteps/ParamGuidance by removing dead external overrides
- Update all backend and frontend tests
Add combined resolution preset selector for external models that maps
aspect ratio + image size to fixed dimensions. Gemini 3 Pro and 3.1 Flash
now send imageConfig (aspectRatio + imageSize) via generationConfig instead
of text-based aspect ratio hints used by Gemini 2.5 Flash.
Backend: ExternalResolutionPreset model, resolution_presets capability field,
image_size on ExternalGenerationRequest, and Gemini provider imageConfig logic.
Frontend: ExternalSettingsAccordion with combo resolution select, dimension
slider disabling for fixed-size models, and panel schema constraint wiring
for Steps/Guidance/Seed controls.
Add 'external', 'external_image_generator', and 'external_api' to Zod
enum schemas (zBaseModelType, zModelType, zModelFormat) to match the
generated OpenAPI types. Remove redundant union workarounds from
component prop types and Record definitions.
Fix type errors in ModelEdit (react-hook-form Control invariance),
parsing.tsx (model identifier narrowing), buildExternalGraph (edge
typing), and ModelSettings import/export buttons.
Move external_gemini_base_url and external_openai_base_url into
api_keys.yaml alongside the API keys so all external provider config
lives in one dedicated file, separate from invokeai.yaml.
