Forward unrecognized OpenAI-compatible generateKwargs keys through extraBody while reserving documented provider control keys such as modelsPath.\n\nVerification:\n- cd mateclaw-server && mvn -pl . test -Dtest=OpenAiCompatibleChatModelBuilderTest,ModelDiscoveryServiceTestPromptTest\n- cd mateclaw-ui && node --max-old-space-size=6144 ./node_modules/vue-tsc/bin/vue-tsc.js --noEmit
Apply a Reactor inter-frame idle timeout at the streaming chat chokepoint so half-open provider body streams surface through the normal retry/failover path. Also keep the HTTP timeout documentation accurate and cover the behavior with focused tests.
Custom (user-added) providers were hard-coded supportModelDiscovery=false in
createCustomProvider, so self-hosted OpenAI-compatible endpoints (vLLM /
Xinference / LocalAI / gateways) never surfaced the 'discover models' button —
users had to add every model id by hand.
- ModelProtocol: add per-protocol supportsSelfConfiguredDiscovery() + resolve()
helper (single source of truth for chat-model class and capability flags).
baseUrl+apiKey protocols (openai-compatible, dashscope-native, gemini-native,
anthropic-messages) => true; OAuth protocols => false. The flag is deliberately
narrower than 'can ever discover' (built-in ChatGPT-OAuth still discovers via
its OAuth session); javadoc warns against reusing it to gate the button.
- createCustomProvider: default supportModelDiscovery from the resolved protocol
instead of always false. Existing rows are unaffected (no migration).
- OpenAiModelsPath: new single source of truth for the models-listing path,
honoring an optional 'modelsPath' generateKwargs override (mirrors the existing
'completionsPath' override) for endpoints behind a reverse proxy / non-standard
prefix (e.g. /openai/v1/models) that would otherwise 404 on /v1/models.
Shared by BOTH discovery (ModelDiscoveryService) and the failover liveness
probe (OpenAiCompatibleListModelsProbe) so an override can't make a provider
discoverable yet still marked unhealthy by a probe hitting the wrong path.
- Tests: ModelProtocolTest (capability table + resolve fallback), OpenAiModelsPathTest
(path branch table + vendor cases + modelsPath override), and custom-provider
discovery-default assertions. Path-resolution coverage consolidated into
OpenAiModelsPathTest (was split across the discovery + probe test files).
- Docs: zh/en models.md note custom-provider discovery + modelsPath override.
Refs matevip/mateclaw#519
Lets an employee pin an ordered fallback chain of (provider, model) entries; the same provider may appear multiple times with different models. Build-time dedup keys on exact (provider, model).
Add GET /api/v1/channels/webchat/wiki/pages mirroring /skills, so
downstream integrators can build a [[slug]] picker UI that points the
LLM at specific wiki pages. The picker token format is the universal
Obsidian/Wikipedia wikilink convention; the LLM consumes [[slug]] via
the existing wiki_read_page(slug=...) tool, so no agent-runtime changes
are needed.
- AgentBindingResolver.getBoundKbIds(agentId): three-state mirror of
getBoundSkillIds. null = no rows (fall through to workspace-wide KBs),
Set.of() = explicitly scoped to zero KBs, non-empty = explicit scope.
- WebChatController.listWikiPages: API Key + visitorToken auth chain,
agentId workspace anti-escalation, visibility excludes pageType=
synthesis (LLM intermediate artifacts), 100-page cap forces keyword
filter, response carries only display-level metadata.
- WebChatWikiPageView DTO: kbId/kbName/slug/title/summary/pageType;
content/embedding/sourceRawIds deliberately stay admin-console-only.
- WikiTool.wiki_read_page @Tool description: document the [[slug]]
convention so the LLM treats each token as a wiki-page reference.
- WebChatWikiPageListTest: 8 cases covering happy path, keyword filter,
synthesis exclusion, anti-escalation, auth failures, cap behavior,
and the no-binding → workspace-wide fallback.
Closes#381.
openAiCompatibleClientBuilder() was creating a new java.net.http.HttpClient
per request. Each instance spawns a selector thread and connection pool that
are never closed, exhausting the OS thread limit under frequent model-test
calls (e.g. DeepSeek provider).
Elevate the HttpClient to a static singleton so all OpenAI-compatible
provider requests share one connection pool and one selector thread.
Closesmatevip/mateclaw#328
Add KingbaseES support as an opt-in profile: dedicated migration tree, bilingual seed data, runtime DbType detection (KINGBASE_ES / POSTGRE_SQL), and JDBC URL handling in the datasource manager.
The vision/video sidecar dropdown filtered candidates through the built-in
capability heuristics, so provider-compatible models whose custom names match
no known prefix (and carry no declared modalities) were hidden and could not be
selected as a sidecar — even when they natively support the modality.
- listByType now returns every enabled chat model, annotating each row with a
transient modalityCapable flag and sorting known-capable rows first, instead
of hard-filtering recognized models only.
- MultimodalRouter honours an explicitly configured sidecar model instead of
dropping it when the heuristics don't recognize it; a wrong pick degrades
gracefully through the caption path rather than silently disabling routing.
- ModelPicker gains an optional capability badge; the sidecar UI tags
recognized vision models while keeping every enabled model selectable.
Closes#174
Model identifiers like 'Qwen/Qwen3-Embedding-8B' or
'Pro/deepseek-ai/DeepSeek-V3' carry forward slashes that Spring MVC
decodes from %2F before path matching, so even with the frontend's
encodeURIComponent the request never reaches the handler and 404s out.
The two affected endpoints take modelId as a request param instead:
DELETE /{providerId}/models/{modelId} -> DELETE /{providerId}/models?modelId=...
POST /{providerId}/models/{modelId}/test -> POST /{providerId}/models/test?modelId=...
modelApi.removeProviderModel / testModel in the UI follow suit, passing
the id via axios params so axios handles the URL encoding consistently.
providerId stays as a path variable — provider ids are kebab-case and
never contain slashes.
Closes#175
ModelConfigController.testEmbedding() previously caught and stringified
the exception's getMessage() into the response body without writing
anything to the server log. Operators investigating an Embedding test
failure saw only the truncated client-side message — root causes like
the DashScope-native vs OpenAI-compat routing bug (#166) or the
requireApiKey gap (#167) were invisible server-side.
Add @Slf4j to the controller and log.error the full stack trace
alongside the failing modelId, so future Embedding test regressions are
diagnosable from the server log without redeploying with debug
breakpoints.
Closes#169
ModelConfigService.validateModel() flagged a duplicate when re-adding a
manually-typed (provider, modelName) pair that happened to match a row
with deleted=1 in mate_model_config. The user-visible symptom: adding
'dashscope/qwen3-plus' fails with 'model identifier already exists',
yet the management page shows no such model.
The project itself runs hard-delete via deleteById(), so the user-facing
delete path doesn't create deleted=1 rows. The stale rows come from
schema migrations (V44, V81) that intentionally tombstone bogus catalog
entries — for instance V81 sets deleted=1 on the non-existent
'qwen3-plus' (id=1000000172) so it stays out of routing but preserves
the id for audit. ModelConfigEntity has no @TableLogic, and the project
has no global logic-delete-field config, so LambdaQueryWrapper queries
do not auto-append the deleted filter; the migration tombstones leak
into the validate-model query.
Add an explicit .eq(getDeleted, 0) to the uniqueness check so migration
tombstones don't block legitimate re-adds.
Follow-up: several other queries in ModelConfigService share the same
oversight (list/get methods), and a future migration could drop the
tombstones entirely to align with the V20 hard-delete posture.
Closes#168
The native DashScope provider exposes both chat and embedding models, but
DASHSCOPE_NATIVE_ALLOW_PREFIXES only listed chat families
(qwen-/qwen2-/qwen3-/deepseek-/baichuan/yi-/llama). When a user manually
added text-embedding-v1/v2/v3/v4 to the dashscope provider,
assertModelIdAcceptable() rejected the id because no allow prefix matched.
Add 'text-embedding-' to the allow-list and broaden the doc comment from
"native chat protocol" to "native protocol (chat or embedding)" so the
intent is clear.
Discovery probing is chat-based and will still mark embedding entries
probeOk=false; surfacing them as discoverable embedding suggestions is a
separate follow-up.
Closes#167
EmbeddingModelFactory.buildOpenAi() hard-failed on any provider whose API
key was empty or unusable, so keyless providers like Ollama and OpenCode
(declared with requireApiKey=false) could pass the chat connectivity test
but bounce when the same provider's embedding model was tested.
Mirror the chat path in OpenAiCompatibleChatModelBuilder.buildOpenAiApi:
- If requireApiKey is not explicitly false, an unusable key still throws.
- If requireApiKey == false, the key check is skipped and an empty string
is passed to OpenAiApi.builder() so no Authorization: Bearer header is
attached to the outgoing request.
Closes#166
EmbeddingModelFactory used EmbeddingProtocol.fromProviderId() to pick the
embedding protocol, which substring-matches 'dashscope' / 'qwen' / 'aliyun'
in the providerId. The dashscope-compat provider carries 'dashscope' in its
id but runs in OpenAI compatible mode (chatModel='OpenAIChatModel',
baseUrl='https://dashscope.aliyuncs.com/compatible-mode/v1'). Routing it to
DASHSCOPE_EMBEDDING made DashScopeApi build its native path against the
compat base, producing 404s on every embedding call.
Switch to the chatModel column instead — the same signal ModelProtocol
.fromChatModel() uses for the chat path. chatModel='DashScopeChatModel'
takes the native protocol; everything else (including dashscope-compat)
takes OpenAI-compatible.
EmbeddingProtocol.fromProviderId() is retained for reference but is no
longer called; future callers should follow the chatModel pattern.
