Register AWS Polly as an audio provider with SigV4 request signing,
speech engine discovery, and API-key validation for managed provider
flows.
Add Lemonade as a self-hosted OpenAI-compatible provider, expand
static model discovery to audio registries, and support Azure OpenAI
deployment discovery from resource endpoints.
Sanitize sensitive provider-specific AWS fields in API responses and
update related tests and release notes.
* fix(sse): preserve Responses API hosted tools in Codex executor
normalizeCodexTools was dropping every non-function tool, which stripped
Codex CLI's built-in image_generation tool (and other hosted tools like
web_search / file_search) before they reached OpenAI. Add a whitelist
and structural check so they pass through, while keeping unknown types
filtered locally with a debug log.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* feat(sse): route DALL-E-style image generation through Codex hosted tool
Adds a Codex branch to the /v1/images/generations handler so DALL-E-style
requests with `model: codex/*` (or `cx/*`) are translated into /responses
calls with the `image_generation` hosted tool, then unpacked back into
OpenAI image response shape. Enables OpenWebUI and other clients that hit
the legacy images endpoint to drive Codex image generation.
Also defaults `store: false` in the Codex executor whenever an
`image_generation` tool is present — the Codex backend rejects store=true
with hosted image generation ("Store must be set to false").
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* feat(sse): forward size/quality from DALL-E body to Codex image_generation tool
The Codex image-gen shim was ignoring `size` and `quality` from the incoming
/v1/images/generations body, so OpenWebUI's size and quality selectors had
no effect. Forward both into the hosted tool config, mapping DALL-E's
`standard`/`hd` to the image_generation tool's `medium`/`high` so legacy
clients keep working.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* feat(providers): add Petals and Nous Research provider support
Register Nous Research as an OpenAI-compatible gateway with remote
model discovery and validation against chat completions.
Add Petals provider metadata, default config, validation, and a
specialized executor that maps OpenAI-style requests to the public
generate endpoint. Also allow optional API keys and configurable base
URLs for Petals in the dashboard and provider schemas.
Expand provider model and catalog tests to cover both integrations.
* fix(resilience): sync queue updates and clear stale discovery caches
Await runtime request queue updates so limiter settings and auto-enabled
API key protections are recomputed when resilience settings change.
Preserve cancelled batch state for in-flight work by marking input files
processed without generating output artifacts, and replace cached synced
models with an empty set when remote discovery returns no models so the
providers route falls back to the local catalog instead of stale cache.
---------
Co-authored-by: Payne <trader-payne@users.noreply.github.com>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Co-authored-by: diegosouzapw <diegosouzapw@users.noreply.github.com>
* fix(claude): preserve tool_result adjacency in native and CC-compatible paths
* feat(providers): add Petals and Nous Research provider support
Register Nous Research as an OpenAI-compatible gateway with remote
model discovery and validation against chat completions.
Add Petals provider metadata, default config, validation, and a
specialized executor that maps OpenAI-style requests to the public
generate endpoint. Also allow optional API keys and configurable base
URLs for Petals in the dashboard and provider schemas.
Expand provider model and catalog tests to cover both integrations.
* fix(resilience): sync queue updates and clear stale discovery caches
Await runtime request queue updates so limiter settings and auto-enabled
API key protections are recomputed when resilience settings change.
Preserve cancelled batch state for in-flight work by marking input files
processed without generating output artifacts, and replace cached synced
models with an empty set when remote discovery returns no models so the
providers route falls back to the local catalog instead of stale cache.
---------
Co-authored-by: congvc <congvc-dev@gmail.com>
Co-authored-by: diegosouzapw <diegosouzapw@users.noreply.github.com>
Register Empower and Poe as managed OpenAI-compatible providers with
static metadata, example models, and remote model catalog support.
Add Poe-specific credential validation against its balance endpoint and
tighten Zed credential imports by skipping unsupported entries and
deduplicating provider-token pairs before saving.
Add Runway as a managed API key provider with a static video model
catalog, dashboard metadata, and provider model route support.
Implement Runway-specific URL normalization, auth headers, credential
validation, and video generation handling for both text-to-video and
image-to-video flows, including task polling and output normalization.
Extend unit coverage for Runway validation, managed catalog exposure,
registry discovery, and end-to-end video handler behavior.
Expand the provider catalog with GitLab Duo PAT and OAuth support,
NLP Cloud, and new OpenAI-compatible gateways including Azure AI
Foundry, Bedrock, DataRobot, watsonx, OCI, SAP, Modal, Reka,
Clarifai, and Chutes.
Add specialized GitLab and NLP Cloud executors, provider-specific
URL normalization and validation flows, managed catalog/model
discovery updates, and dashboard metadata for the new providers.
Extend search support with You.com, including request building,
response normalization, validation coverage, and route/schema
registration.
Add Amazon Q as a Kiro-compatible OAuth provider across execution,
token refresh, usage reporting, dashboard connection flows, and model
catalog exposure.
Add Voyage AI embedding and rerank catalogs plus Jina AI rerank support,
including local model catalog handling, API key validation, provider
metadata, and rerank error reporting updates.
Refresh built-in GitHub Copilot and Kiro model registries to match the
current supported lineup and extend test coverage for the new provider
paths.
Register GLHF, CablyAI, TheB.AI, and FenayAI across the provider
registry, managed provider catalog, and provider metadata so they can be
configured like other API key-backed integrations.
Extend the provider models route to fetch remote model catalogs for these
gateways and add unit coverage for catalog resolution and managed
provider handling. Increase unit test concurrency to keep the expanded
test suite faster to run.
Treat LM Studio, vLLM, Llamafile, Triton, Docker Model Runner,
XInference, and oobabooga as managed local providers with default
base URLs and passthrough model discovery.
Avoid sending empty bearer headers during validation, model discovery,
and execution so self-hosted endpoints work without API keys while
still honoring custom base URLs and localized dashboard hints.
Introduce a custom CLI tools card that generates OpenAI-compatible
env vars and JSON config, and add a cost overview tab with pricing
source visibility.
Add persisted custom eval suites with authenticated CRUD routes and
validation, plus new translator stream transformation tooling and
richer live monitor routing details.
Improve localization coverage across dashboard flows and add unit
tests for custom CLI config, pricing sources, eval suites, and
stream transformation.
Store eval executions with target metadata, expose aggregated scorecard
and recent run history endpoints, and return dashboard-ready eval data
including target options and API key metadata.
Also require management auth for eval read endpoints and preserve
per-case latency, errors, and output snippets so historical results are
more reliable and easier to inspect.
Unify audit access under the logs experience and add richer active
request visibility with sanitized client and provider payload previews.
Expose provider warnings from upstream responses in compliance audit
logs, surface learned rate-limit header data in health monitoring, and
add MCP cache stats and cache flush tools with test coverage.
Also add local provider catalog support for SD WebUI and ComfyUI,
include video generation in endpoint docs and UI, add eval run storage
migrations, and refresh docs and translations to match the expanded
feature set.
The provider registry used PascalCase header keys (e.g. "Anthropic-Version")
while the Claude Code client path in base.ts sets lowercase keys
("anthropic-version"). Since JS object keys are case-sensitive, both keys
coexist in the headers object. When fetch() sends them, HTTP treats them
as duplicates and concatenates the values ("2023-06-01, 2023-06-01"),
causing Anthropic's API to reject the request with a 400 error.
Normalize all Anthropic-specific header keys to lowercase to match the
convention used in executors and the upstream API.
- Stream release: wrap stream body with TransformStream to release
account semaphore only when stream is fully consumed (Thread 1)
- Key scope: remove model from semaphore key — was per-account-per-model,
now truly per-account to match PR motivation (Thread 2)
- Test location: move accountSemaphore.test.ts to tests/unit/ per style guide (Thread 3)
- Fix flaky timestamp assertions in semaphore tests
- DB 마이그레이션 028: provider_connections.max_concurrent 컬럼 추가
- AccountSemaphore: 계정별 FIFO 세마포어 (acquire/release/timeout/block)
- chatCore.ts: 요청 파이프라인에 선제적 cap enforcement 통합
- providers.ts: maxConround-trip round-trip 저장/조회, cleanNulls() 보정
- API: provider limits route에서 maxConcurrent GET/PUT 지원
- UI: provider 연결 상세 페이지 account native cap 입력 필드 + hint
- UI: ResilienceTab combo concurrency 라벨 구분 (combo vs account)
- i18n: en/ko 번역 키 추가
- schemas.ts: maxConcurrent 음수 검증 + null 허용
- 테스트: semaphore 6개, DB round-trip + validation 6개
Reject invalid API keys even when authentication is optional and add
OPTIONS handlers for batch and file routes to support CORS preflights.
Also recover orphaned batches stuck in finalizing after restarts,
include finalizing in pending batch queries, preserve multipart upload
content handling, and fetch remote vision images as data URIs for
Anthropic requests.
* feat(vision-bridge): add automatic image description fallback for non-vision models
Implements VisionBridgeGuardrail (priority 5) that intercepts image-bearing
requests to non-vision models, extracts descriptions via a configurable
vision model (default: gpt-4o-mini), and replaces images with text before
forwarding. Fails open on any error.
- Add VisionBridgeGuardrail class extending BaseGuardrail
- Add visionBridgeHelpers: extractImageParts, callVisionModel, replaceImageParts, resolveImageAsDataUri
- Add visionBridgeDefaults with configurable settings
- Register VisionBridgeGuardrail in GuardrailRegistry at priority 5
- Add 51 unit tests covering all spec scenarios (VB-S01 through VB-S10)
- Dependency injection for getSettings and callVisionModel (testable without SQLite)
Closesdiegosouzapw/OmniRoute#1424
* fix(vision-bridge): resolve Anthropic API, parallel processing, provider keys, structuredClone
- create createSettingsApiHarness function with temp directory setup
- add beforeEach/afterEach hooks for storage reset between tests
- add after hook for cleanup
- use dynamic imports after env setup to ensure proper initialization
