* fix(kimi): resolve Kimi Code API 403 errors and User-Agent restrictions
Kimi Code subscription keys require a whitelisted coding-agent User-Agent to avoid access_terminated_error 403s. This adds User-Agent probing and caching for Kimi Code endpoints.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(kimi): omit temperature for kimi-for-coding API calls
Kimi Code rejects any non-default temperature with HTTP 400, which broke deep research probes and low-temp LLM rounds.
Co-authored-by: Cursor <cursoragent@cursor.com>
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
Adding a new endpoint only auto-set the global default chat endpoint when
none was configured (`if not settings.get("default_endpoint_id")`). When the
existing default pointed at an endpoint the user had since disabled, it was
never reassigned, so features that read the raw `default_endpoint_id` setting
(notably Memory → Tidy) failed with "No default model configured — set one in
Settings" even though an enabled endpoint existed.
Reassign the default when the configured endpoint is missing/disabled, via a
new pure `_default_endpoint_needs_assignment` helper. Adds unit coverage for
the helper plus route-level regression tests for the disabled/enabled cases.
Fixes#3586
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* feat: add NVIDIA as an AI provider (integrate.api.nvidia.com)
* feat: add NVIDIA option to provider settings dropdown and aliases
* test: add NVIDIA provider detection and endpoint tests
* Add NVIDIA to _HOST_TO_CURATED and expand non-chat model filtering
- nvidia.com -> 'nvidia' curated key for proper provider routing
- _NON_CHAT_PREFIXES: bge, snowflake/arctic-embed, nvidia/nv-embed
- _NON_CHAT_CONTAINS: content-safety, -safety, -reward, nvclip,
kosmos, fuyu, deplot, vila, neva, gliner, riva, -parse,
-embedqa, -nemoretriever
* Expand non-chat model filtering for NVIDIA embedding/guard/video models
Add _NON_CHAT_PREFIXES: embed, recurrent
Add _NON_CHAT_CONTAINS: topic-control, guard, calibration,
ai-synthetic-video, cosmos-reason2
Catches remaining unfiltered non-chat models from NVIDIA catalog:
embedding (llama-nemotron-embed, embed-qa), guard (llama-guard,
nemoguard-topic-control), calibration (ising-calibration),
video (ai-synthetic-video-detector, cosmos-reason2),
recurrent (recurrentgemma-2b)
* Filter non-chat models in _probe_endpoint via _is_chat_model()
Previously _is_chat_model() was only used in the per-model probe
and _first_chat_model(), so non-chat models still appeared in the
model picker even though they were filtered in those specific paths.
Applying the filter at _probe_endpoint() return ensures non-chat
models (embeddings, safety guards, reward, calibration, video
detectors, CLIP, VLM, translation, parsing, recurrent, etc.) never
enter cached_models and never appear in the picker.
* Fix _NON_CHAT_CONTAINS to catch org-prefixed embedding models
Prefix checks (mid.startswith) miss models with org prefixes like
baai/bge-m3, nvidia/embed-qa-4, google/recurrentgemma-2b, etc.
Adding the same terms to _NON_CHAT_CONTAINS ensures they are caught
regardless of the org prefix.
Adds: embed, bge, recurrent, starcoder, gemma-2b
* fix(model-routes): drop collision-prone substrings from global non-chat filter
The NVIDIA PR added several substrings to the shared _NON_CHAT_PREFIXES
and _NON_CHAT_CONTAINS tuples. These are intended to filter out
embedding, retrieval, safety, and vision models from NVIDIA's catalog
that are not chat-completions-capable. However, four of the added
substrings collide with legitimate chat models served by other providers:
- gemma-2b matches google/gemma-2b-it (instruct chat model)
- starcoder matches bigcode/starcoder2-15b (code completion model)
- recurrent matches google/recurrentgemma-2b (language model)
- guard matches meta-llama/Llama-Guard-3-8B (safety classifier)
Removing these four from the global tuples keeps the NVIDIA-specific
filtering intact (safety, embedding, retrieval, and vision models are
still caught by other tokens such as content-safety, -safety, -reward,
embed, bge, -embedqa, -nemoretriever, nvclip, deplot, etc.) while
preventing false negatives for instruct/code models on other providers.
Tests added for gemma-2b-it, google/gemma-2b-it, and
bigcode/starcoder2-15b-instruct asserting they are recognized as chat
models.
Co-authored-by: Kenny Van de Maele <kenny@kvandemaele.be>
* fix(nvidia): remove duplicate bge/embed tokens from _NON_CHAT_CONTAINS
Tokens already present in _NON_CHAT_PREFIXES, making the CONTAINS
entries redundant since the prefix check runs first.
Co-authored-by: Kenny Van de Maele <kenny@kvandemaele.be>
* fix(nvidia): move bge to CONTAINS, add llama-guard, remove stray blanks
Co-authored-by: Kenny Van de Maele <kenny@kvandemaele.be>
* style: fix indentation of groq and xai test cases in test_provider_endpoints.py
---------
Co-authored-by: Kenny Van de Maele <kenny@kvandemaele.be>
Add focused tests for the z.ai/api/coding path override:
- _match_provider_curated: 5 tests verifying coding vs base key
- _probe_endpoint: 3 tests verifying model preservation, curated
append on partial response, and base-zai exclusion
Rebased onto dev per reviewer request.
Fixes#2230
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: Alexandre Teixeira <111787685+alteixeira20@users.noreply.github.com>
GET /api/models swallowed any non-HTTPException raised while checking
whether the caller is authenticated (bare except Exception: pass), so a
broken auth_manager or an exception from get_current_user silently
granted the full model list to an anonymous caller instead of rejecting
the request. Now any unexpected exception logs and returns HTTP 500.
Split out of #2360 per reviewer request to keep the deny-list and the
auth-gate fix as separate, single-purpose PRs.
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
* feat: Add ChatGPT Subscription support and related features
- Introduced a new provider option for ChatGPT Subscription in the endpoint selection UI.
- Implemented OAuth flow for ChatGPT Subscription sign-in, including polling for authorization status.
- Updated admin interface to handle ChatGPT Subscription, including disabling API key input and providing user guidance.
- Enhanced cost tracking logic to differentiate between subscription and non-subscription endpoints.
- Added new slash commands for managing skills, including listing, searching, and invoking skills.
- Implemented caching for skill catalog to optimize performance.
- Updated tests to cover new ChatGPT Subscription functionality and ensure proper endpoint probing.
- Refactored existing code to accommodate new features and improve maintainability.
* refactor: share provider device-flow setup
- reuse one device-flow backend for Copilot and ChatGPT Subscription
- add one frontend device-flow helper for Settings and /setup
- put GitHub Copilot back into Add Models, now as a dropdown option
- make provider selection just select; clicking Add starts sign-in
- stop ChatGPT Subscription setup from opening auth tabs automatically
- make /setup copilot and /setup chatgpt-subscription work from chat
- show ChatGPT Subscription in the /setup suggestions
- show the real error message when setup fails
- add focused tests for the shared flow and setup UI
* feat(chatgpt-subscription): harden credential lifecycle and streamline auth UX
Backend:
- Resolve runtime bearer for provider-auth endpoints at probe time via a
shared _resolve_probe_key() that delegates to resolve_endpoint_runtime,
applied across all probe/refresh call sites.
- Skip live completion probes and health pings for discovery-only providers
(centralized behind _is_discovery_only_provider) — the Codex/Responses API
has no such endpoints, so status is derived from cached models.
- Never persist the short lived ChatGPT bearer to the plaintext sessions
table; proactively clear any stale bearer left by an earlier code path.
- Revoke orphaned ProviderAuthSession credentials when the last endpoint
backing them is deleted (_delete_orphaned_provider_auth), surfaced via
cleared_provider_auth in the delete response.
Frontend (admin.js):
- Auto-start the device-auth flow on provider selection so the authorization
panel (code + Authorize) shows immediately instead of behind a "Sign in" click.
- Remove the redundant top button for device auth providers, move retry
into the panel via an inline "Try again".
- Drop the self-evident hint text and add an execCommand clipboard fallback so
Copy works in non-secure (HTTP/LAN) contexts.
* fix: harden chatgpt subscription provider
* chore: remove PR media from branch
* Fix chatgpt subscription recovery and token handling
---------
Co-authored-by: 5p00kyy <admin@5p00ky.dev>
_ping_endpoint() probes the bare base URL for non-Ollama endpoints.
OpenAI-compatible servers like llama-swap return 404 on the /v1 prefix
but 200 on /v1/models, causing endpoints to appear offline despite being
fully functional.
Add a /models fallback when the base URL returns a non-auth 4xx.
Auth failures (401/403) are treated as definitive — probing /models
would just repeat the same rejection.
Fixes#3181
Co-authored-by: michaelxer <michaelxer@users.noreply.github.com>
Updates endpoint/model-route test HTTP mocks to accept the verify keyword argument passed by endpoint probing code. Restores one focused part of the Python CI baseline tracked in #2580.
* fix: support large proxy model endpoint refresh
Large OpenAI-compatible proxy endpoints can expose hundreds of models and make /v1/models slow. Treating those endpoints like local model servers caused model picker opens and background probes to repeatedly hit /models, producing timeouts and making otherwise usable endpoints appear offline.
Make model endpoint discovery cached-first for normal UI usage, add explicit proxy/API classification and refresh policy fields, exclude proxy/API endpoints from aggressive local probing, and preserve cached models when refresh fails.
Manual Test/Add/Refresh actions still fetch the full model list with longer timeouts so users can intentionally import large proxy model lists without blocking normal model picker usage.
* fix: preserve endpoint ping status semantics
In Docker, a model-endpoint URL pointing at loopback (e.g. the LM Studio
default http://localhost:1234/v1) targets the Odysseus container itself, not
the host running the server, so the probe gets a connection error and the
endpoint is rejected with a misleading 'No models found for that provider/key'.
Rewrite loopback to host.docker.internal (which compose already maps to
host-gateway) for the probe and the saved URL, mirroring the existing Ollama
handling. Gated on actually being in a container with the gateway reachable, so
native installs and gateway-less deploys are untouched.
Fixes#25
Co-authored-by: Claude <noreply@anthropic.com>
KYDNO