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* feat: initial external model support * feat: support reference images for external models * fix: sorting lint error * chore: hide Reidentify button for external models * review: enable auto-install/remove fro external models * feat: show external mode name during install * review: model descriptions * review: implemented review comments * review: added optional seed control for external models * chore: fix linter warning * review: save api keys to a seperate file * docs: updated external model docs * chore: fix linter errors * fix: sync configured external starter models on startup * feat(ui): add provider-specific external generation nodes * feat: expose external panel schemas in model configs * feat(ui): drive external panels from panel schema * docs: sync app config docstring order * feat: add gemini 3.1 flash image preview starter model * feat: update gemini image model limits * fix: resolve TypeScript errors and move external provider config to api_keys.yaml 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. * feat: add resolution presets and imageConfig support for Gemini 3 models 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. * Remove unused external model fields and add provider-specific parameters - 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 * Chore Ruff check & format * Chore typegen * feat: full canvas workflow integration for external models - 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 * Chore typegen Linux seperator * feat: full canvas workflow integration for external models - Update buildExternalGraph test to include dimensions in mock params * Merge remote-tracking branch 'upstream/main' into external-models * Chore pnpm fix * add missing parameter * docs: add External Models guide with Gemini and OpenAI provider pages * fix(external-models): address PR review feedback - Gemini recall: write temperature, thinking_level, image_size to image metadata; wire external graph as metadata receiver; add recall handlers. - Canvas: gate regional guidance, inpaint mask, and control layer for external models. - Canvas: throw a clear error on outpainting for external models (was falling back to inpaint and hitting an API-side mask/image size mismatch). - Workflow editor: add ui_model_provider_id filter so OpenAI and Gemini nodes only list their own provider's models. - Workflow editor: silently drop seed when the selected model does not support it instead of raising a capability error. - Remove the legacy external_image_generation invocation and the graph-builder fallback; providers must register a dedicated node. - Regenerate schema.ts. - remove Gemini debug dumps to outputs/external_debug * fix(external-models): resolve TSC errors in metadata parsing and external graph - Export imageSizeChanged from paramsSlice (required by the new ImageSize recall handler). - Emit the external graph's metadata model entry via zModelIdentifierField since ExternalApiModelConfig is not part of the AnyModelConfig union. * chore: prettier format ModelIdentifierFieldInputComponent * fix: remove unsupported thinkingConfig from Gemini image models and restrict GPT Image models to txt2img * chore typegen * chore(docs): regenerate settings.json for external provider fields * fix(external): fix mask handling and mode support for external providers - Remove img2img and inpaint modes from Gemini models (Gemini has no bitmap mask or dedicated edit API; image editing works via reference images in the UI) - Fix DALL-E 2 inpainting: convert grayscale mask to RGBA with alpha channel transparency (OpenAI expects transparent=edit area) and convert init image to RGBA when mask is present * fix(external): update mode support and UI for external providers - Remove DALL-E 2 from starter models (deprecated, shutdown May 12 2026) - Enable img2img for GPT Image 1/1.5/1-mini (supports edits endpoint) - Set Gemini models to txt2img only (no mask/edit API; editing via ref images) - Hide mode/init_image/mask_image fields on Gemini node (not usable) - Hide mask_image field on OpenAI node (no model supports inpaint) * Chore typegen * fix(external): improve OpenAI node UX and disable cache by default - Hide OpenAI node's mode and init_image fields: OpenAI's API has no img2img/inpaint distinction (the edits endpoint is invoked automatically when reference images are provided). init_image is functionally identical to a reference image and was misleading users. - Default use_cache to False for external image generation nodes: external API calls are non-deterministic and incur usage costs. Cache hits returned stale image references that did not produce new gallery entries on repeat invokes. * fix(external): duplicate cached images on cache hit instead of skipping External image generation nodes use the standard invocation cache, but returning the cached output (with stale image_name references) on cache hits resulted in no new gallery entries — the Invoke button would spin indefinitely on repeat invokes with identical parameters. Override invoke_internal so that on cache hit, the cached images are loaded and re-saved as new gallery entries. The expensive API call is still skipped (cost saving), but the user sees a new image as expected. * Chore typegen + ruff * CHore ruff format * fix(external): restore OpenAI advanced settings on Remix recall Remix recall iterates through ImageMetadataHandlers but only Gemini's temperature handler was wired up — OpenAI's quality, background, and input_fidelity were stored in image metadata but never parsed back into the params slice. Add the three missing handlers so Remix restores these settings as expected. --------- Co-authored-by: Alexander Eichhorn <alex@eichhorn.dev> Co-authored-by: Alexander Eichhorn <alex@code-with.us> Co-authored-by: Lincoln Stein <lincoln.stein@gmail.com>
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title
| title |
|---|
| External Models |
:material-cloud-outline: External Models
External models let you generate images in Invoke by calling third-party image generation APIs instead of running a model locally. This is useful when:
- You don't have the GPU or VRAM to run a model locally.
- You want access to closed-source models (e.g. GPT Image, Gemini).
- You need a specific provider capability (very high resolutions, fast batches, bilingual text rendering, etc.).
External models appear in the model picker alongside locally installed models. Generations are routed to the provider's API, billed against your provider account, and the resulting images are imported back into Invoke like any other generation.
Supported Providers
- Google Gemini — Gemini 2.5 Flash Image, Gemini 3 Pro Image Preview, Gemini 3.1 Flash Image Preview
- OpenAI — GPT Image 1 / 1.5 / 1-mini, DALL·E 3, DALL·E 2
Configuring API Keys
External provider credentials are stored in a dedicated api_keys.yaml file alongside invokeai.yaml in your Invoke root directory.
# api_keys.yaml
external_gemini_api_key: "your-gemini-api-key"
external_openai_api_key: "your-openai-api-key"
# Optional: override the provider base URL (e.g. for a compatible proxy or regional endpoint)
external_gemini_base_url: "https://generativelanguage.googleapis.com"
external_openai_base_url: "https://api.openai.com"
Restart Invoke after editing api_keys.yaml so the new values are picked up.
!!! warning "Keep your keys private"
api_keys.yaml contains secrets. Do not commit it to version control and do not share it with other users of your machine.
Installing External Models
External models are listed in the starter models dialog under their provider. Install them like any other starter model — Invoke records a model reference but does not download weights (there are no weights to download).
Once installed, external models show up everywhere a model can be selected. Choose one, set the usual parameters (prompt, dimensions, num images, etc.), and invoke as normal.
Capabilities and Settings Visibility
Each external model declares its own capabilities — for example:
- Which generation modes it supports (
txt2img,img2img,inpaint). - Whether it accepts reference images, and how many.
- Which aspect ratios and resolutions it allows.
- Whether it supports a negative prompt, seed, or batch size > 1.
Invoke uses these capabilities to drive the UI: only the settings a given model actually supports will be shown in the parameters panel. If a field you expect is missing, it's because the selected model does not support it.
Costs and Rate Limits
External providers charge for each request. Check the provider's pricing page before running large batches. Rate-limit errors from the provider are surfaced in Invoke as generation failures — wait a moment and try again, or lower your concurrent batch size.