| 文件 | 最后提交记录 | 最后更新时间 |
|---|---|---|
🚚Code transfer | 1 年前 | |
♻️ Feat: support a2a custom authorization (#3512) * Feat: support a2a custom authorization * support httpscheme * Feat: Allow users to select from multiple authentication methods * fix ut * fix ut * add ut * fix when httpAuthSecurityScheme.scheme is lower case bearer, cannot pass authentication | 2 个月前 | |
bugfix:support model reasoning effort configuration (#3953) * bugfix:支持思考挡位配置 * bugfix: support model reasoning effort configuration * test: improve reasoning configuration coverage * test: complete reasoning coverage * fix: resolve CI quality gate failures * test: complete coverage for gate branches * bugfix: support configurable model reasoning effort * test: complete reasoning coverage * test: cover reasoning override branch * bugfix: support model reasoning effort settings * bugfix: complete reasoning capability matching * test: align reasoning capability assertions * test: close reasoning coverage gaps --------- Co-authored-by: hzw <hzw@qq.com> | 13 天前 | |
Enhance agent marketplace with pagination, reviews, and import precheck (#3316) * ✨ Feature: enhance agent marketplace with pagination, review, and import precheck Add paginated search for repository listings and mine agents, an admin review queue with approve/reject, and import precheck/copy flow that validates models, knowledge bases, MCP, skills, and tools before copying from the marketplace. Extract repository domain constants and expand backend/frontend tests. * fix(frontend): replace vitest with node:test in agentRepositoryDetail tests Align the test file with existing frontend unit tests and fix CI type-check failures caused by missing vitest dependency. * fix(frontend): resolve SonarCloud issues in agent-space Replace void promise calls with async handlers and .catch() in page.tsx, and split AgentRepositoryDetailModal into smaller components to reduce cognitive complexity below SonarCloud threshold. * feat(agent-repository): show tool count on agent warehouse cards Auto-compute tool_count when creating or updating listings, expose it in the list API, and render "x tools" on repository cards when count is greater than zero. * test(agent-repository): add unit tests for agent_repository_db | 3 个月前 | |
Bugfix: 当Agent配置的模型被删除，应该有对应的提示 (#3832) * Refactor: 重构chat页面分页加载功能，默认加载30条 * Potential fix for pull request finding Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> * Bugfix: 支持在北向接口的run接口中返回conversation_created的chunk * add ut * Bugfix: Remove redundant field validation * Bugfix: Fix model name display in model selector dropdown * Bugfix: Prevent loading stale agent info when agent_id does not exist * Bugfix: update agent version when published * Bugfix: Resolve agent stop failure in debug mode(by adding run id) * fix ut * Bugfix: default set nl2agent suggestion visible * Bugfix: 更新单点优化策略 * Bugfix: 当用户配置了模型后模型被删除，有对应的提示 * add unavaliable reason * fix ut * fix ut * fix ut * agent不可用原因支持修改后刷新 (cherry picked from commit 03590885de2243e3f83141d218b1591f9c8c67e0) * 更新trigger的样式 * 修改agentName为空时前端报错 --------- Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> | 1 个月前 | |
feat(w11): expand capability catalog to 66 entries + SQL generator + safety guards (#3317) * fix(model_management): preserve connectivity success when capacity suggestion path raises The connectivity check endpoint /model/temporary_healthcheck runs _capacity_suggestion_for_model_request inline after a successful verify_model_config_connectivity. Per W11 spec ("Suggestion failure never changes connectivity success or failure"), an unexpected error inside the suggestion path must not turn a successful connectivity result into HTTP 500. The prior code caught ValueError (covering the typed InvalidInput case and Pydantic v2 ValidationError, which is a ValueError subclass), but non-ValueError exceptions -- e.g. AttributeError/TypeError from a malformed catalog profile entry, or future V2 provider-discovery HTTP errors -- would propagate to the outer except Exception in check_temporary_model_health and surface to operators as a misleading "Failed to verify model connectivity" 500. Restore the catch-all degrade-to-None branch and log at WARNING (not DEBUG) so the real root cause is visible in default production log streams without DEBUG enabled. Connectivity stays 200 with capacity_suggestion: null; the per-row catalog issue surfaces in logs where operators can act on it. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * refactor(w11): collapse Add/Edit capacity-suggestion controls The Add dialog had two ways to trigger a catalog suggestion: clicking the bottom connectivity-validation button (which the backend extends with capacity_suggestion in /temporary_healthcheck's response) and a secondary "Check" button beside the toggle that called the standalone /suggest-capacity endpoint. In V1 catalog-only mode the two paths overlap on every realistic add flow -- the user must run connectivity anyway because the Add button is gated on it -- so the standalone button is UX noise without functional value. Collapse Add to a single toggle whose state gates both the embedded suggestion result and the explanatory hint. The Edit dialog keeps its explicit Check button per spec ("show 'Suggestion available' after validation or explicit check") because existing rows may need to refresh a suggestion without re-running connectivity, but the long-form hint sentence is redundant: title + toggle + a button labelled "Check" already names the feature and the action. Removing the hint matches the spec's i18n key list, which never listed model.dialog.capacity.suggestion.hint to begin with. Add dialog changes: - Drop checkingCapacitySuggestion state, canSuggestCapacity guard, and handleSuggestCapacity handler. - Drop the secondary Button and its wrapping shrink-0 flex container; the Switch becomes a direct child of the outer justify-between row. - Drop the suggestionLoading prop from ModelCapacityFields entirely. It only controlled the spinner on the "Use suggestion" button inside the suggestion-result panel, which only renders after a suggestion is set -- at which point verifyingConnectivity is already false, so binding it added no observable effect. - Replace the shared "hint" copy with a new key "hintAdd" whose wording reflects the actual trigger ("Suggested from the approved catalog after connectivity passes."), and gate it on capacitySuggestionEnabled so the toggle's off-state no longer contradicts itself with copy that promises automatic behavior. Edit dialog changes: - Remove the hint <div> and its wrapping container; the title becomes a direct flex child alongside the Switch+Check controls. i18n: - Drop the obsolete "model.dialog.capacity.suggestion.hint" key from en and zh; add "hintAdd" used only by Add dialog. No backend wire change. Edit dialog still calls /suggest-capacity through its existing Check button for the bare-row repair flow. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * feat(w11): backend SLO instrumentation + cross-tenant capacity-coverage test Phase 1.5 backend foundation per W11 spec L706-710 (SLO metrics), L86-89/L944-948 (visibility env flag), and L312-322 (cross-tenant test). No frontend change in this commit; V1.5 surfaces consume these signals in follow-up frontend commits. Metrics (4 instruments, each guarded behind try/except so a missing OpenTelemetry runtime does not break the dispatch path): 1. model_capacity_suggestion_requests_total{match_kind, model_type, provider} -- counter wrapping suggest_capacity. Drives the "70% of new manual-add LLM rows produce match_kind != none" SLO. 2. model_capacity_suggestion_latency_ms{match_kind, provider} -- histogram around the same call. Used to verify V2 provider-discovery p95 stays under the model-add latency budget. 3. model_capacity_suggestion_accept_total{match_kind, provider} -- counter emitted by the app layer when the operator save payload carries accepted_suggestion_match_kind. Numerator for the "95% accepted -> profile dispatch" SLO ratio. 4. model_capacity_suggestion_dispatch_profile_hit_total{provider} -- counter emitted in _resolve_input_budget when the resolved snapshot carries a non-null capability_profile_version. Denominator for the same SLO. Accept signal pipe (audit-only): - consts/model.py: ModelRequest gains accepted_suggestion_match_kind and accepted_capability_profile_version. Both Optional[str], never persisted to model_record_t. - model_management_service.py: pop_capacity_accept_signal strips both fields from save payloads and returns the popped values so the app layer can label the counter. - model_managment_app.py: /create and /update endpoints call pop_capacity_accept_signal before invoking the service, then forward the popped match_kind to _record_capacity_suggestion_accept after the save returns. The dict the service sees no longer contains these fields, preserving the "audit only -- not persisted" contract. - The V1.5 frontend (next commit) will ship these fields on the wire; until then the counter reads zero, which is the correct baseline. suggest_capacity refactor: - Inner body extracted to _suggest_capacity_inner so the public function can time end-to-end and emit requests_total + latency_ms exactly once per completed call. ValueError paths still raise -- client-shape errors must not pollute SLO ratios so the recorder fires only on terminal CapacitySuggestionResult returns. Visibility env flag (CAPACITY_VISIBILITY_ENABLED): - Already declared in consts/const.py (default true) and consumed by get_capacity_coverage. Confirmed wired end-to-end; no code change needed here. The flag stays the developer-level rollback lever per W11 spec; tenant_config_t overlay remains a follow-up. Cross-tenant isolation test (spec L312-322): - test_get_capacity_coverage_cross_tenant_isolation routes mocked get_model_records by tenant_id and asserts each tenant only sees its own bare rows in both bare_models[] and total_llm_vlm. Closes the spec's required "tenant B row must not appear in tenant A's response" coverage. Test coverage added: - Cross-tenant isolation for /capacity-coverage. - pop_capacity_accept_signal extraction + dict mutation contract. - accept_total OTel-optional no-op + label-cardinality (lower-cased provider) wiring. - suggest_capacity records requests_total + latency_ms on catalog match, on "none" with provider fallback to "unknown", does NOT record on ValueError, and runs cleanly when instruments are None. - _resolve_input_budget records dispatch_profile_hit_total only when capability_profile_version is non-null; recorder no-op when counter is None. Total: 8 files, +527 lines. All targeted unit suites pass (test_model_capacity_suggestion_service 16/16, test_model_management_service 70/70, test_create_agent_info 174/174). Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * feat(w11): V1.5 bare-capacity tag + preset selector + permission helper Mark bare-capacity LLM/VLM rows in the Manage Models list with the existing yellow "缺容量" / "Missing capacity" tag. Keep the aggregation banner on the Models page as the entry-point signal, but rewrite its copy to hand off to the per-row tag instead of duplicating per-row UI. Auto-fire /suggest-capacity from inside ModelEditDialog whenever it opens on a bare-capacity row, regardless of how the dialog was opened. Expose preset selectors on the capacity panel and ship the model-management permission helper for V1.5 surfaces #2/#3. Per spec line numbers cross-referenced inline: #1 -- per-row tag as visual indicator (spec L143-167): - Both badge sites in ModelDeleteDialog (provider-browser row L1507+ and added-model row L1652+) retain the existing yellow text tag (bg-yellow-100 border-yellow-200 text-yellow-700). We considered a warning-triangle icon and a separate click-target on the badge, then rolled both back: "缺容量"/"Missing capacity" reads as a status at the same glance an icon would, while the existing row onClick already opens the edit dialog -- so a button on the badge added complexity that ModelEditDialog now subsumes internally. - ModelEditDialog derives `isBareCapacityModel` from the loaded model (context_window_tokens or max_output_tokens null) and a single useEffect auto-fires handleSuggestCapacity once on open when the model is bare, the suggestion switch is on, and the form fields needed for the call are present. Any entry path -- row click, future gear-icon shortcut, deep link -- gets the same affordance, so the operator never has to also click "Check" on a bare row. - The deprecated model.dialog.capacityCoverage.{tag, warning, warningWithSuggestion} keys are dropped from en + zh in favour of a single spec-namespaced model.list.capacityWarning.tag key. No per-suggestion variants because the tag is purely a state label; the suggestion handoff happens inside the edit dialog where the green/info Alert carries that nuance instead. #5 -- aggregation banner kept as entry-point signal, copy retuned: - The summary Alert on the Models page (modelConfig.tsx) stays -- per-row tags live inside ModelDeleteDialog which is one click away. Without the banner, users on the Models page have no signal that any row needs attention. - Description copy rewritten so the banner points at the new per-row flow: "Click Manage, then click the warning icon on each affected row to repair." Removes the redundant "edit a marked model" wording. - Warning copy adds an "output token cap is not enforced" clause so the consequence (not just the symptom) is visible at a glance. #4 -- permission helper (spec L167-178): - frontend/lib/auth.ts gains canManageModels(role, isSpeedMode). Allowed roles: SU, ADMIN, DEV, SPEED. USER is excluded so regular agent authors see read-only notices rather than dead repair links. ASSET_OWNER is excluded -- model records are tenant scope, not asset-admin scope. Speed mode bypasses for the single-user dev experience, mirroring how other surfaces (chatHeader, etc.) treat it. - The banner and tag in this commit both live on /models which is already route-gated for non-USER roles, so no in-place gate is needed yet. The helper exists so the V1.5 agent-edit-selector commit (#2) and the dashboard widget commit (#3) consume the same primitive instead of reinventing role parsing. #8 -- preset selectors for context_window / output_reserve / max_output (spec L757-790): - ModelCapacityFields.tsx gains two preset arrays mirroring spec L767-790 verbatim (9 context-window values 4K..1M, 7 output values 256..16K). The context-window list is identical to MAX_TOKEN_OPTIONS in ModelMaxTokensInput; kept as a local constant rather than cross-importing so the two surfaces stay independently editable. - renderNumberInput gains an optional `presetOptions` parameter. When the field has no catalog suggestion yet (per spec L762-765 "when no suggestion exists ... render as preset-capable selector"), the input renders as AutoComplete with the preset list; otherwise it stays a plain numeric Input so an explicit catalog value doesn't get visually buried behind dropdown chrome. - Wired for contextWindowTokens, maxOutputTokens, and defaultOutputReserveTokens. maxOutputTokens reuses the 256..16K list so operators see the same dropdown choices they already see for the reserve field; values above 16K (e.g. GPT-4.1's 32K cap, GLM-5.1's 131K cap) still work via free-text typing through AutoComplete. maxInputTokens keeps plain numeric input -- it is an explicit operator-side limit, not common-preset land. - validateCapacityForm continues to enforce positive integers downstream. i18n delta summary: - DROPPED: model.dialog.capacityCoverage.tag, model.dialog.capacityCoverage.warning, model.dialog.capacityCoverage.warningWithSuggestion - ADDED: model.list.capacityWarning.tag (single state label, no tooltip variants) - REVISED (kept): modelConfig.capacityCoverage.warning + description with new entry-point copy; .manage button label unchanged. Net: 6 files, +148/-77. Typecheck clean (only pre-existing .next/types/validator.ts noise from the unrelated left-nav rename). No backend wire change. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * fix(w11): unify ModelEditDialog state-per-model via key remount + auto-suggest population guard Two paired bugs in the V1.5 auto-suggest path, both surfacing as "open glm-5 shows qwen3.7-max suggestion" after the operator cancels qwen and immediately clicks glm-5 in the Manage Models list: 1. Stale render. ModelEditDialog returns null when `model` is falsy (line ~559) but React does not unmount on null return -- it just commits null and keeps the component instance alive, useState intact. With React 18's automatic batching, the cancel and the subsequent row click coalesce into one commit; the [isOpen] reset effect I added in e442a5515 saw isOpen=true on its single run and skipped the cleanup, so capacitySuggestion stayed as qwenResult for the first render with model=glm5. The user briefly saw the wrong suggestion before the [model] effect cleared it. 2. Stale API call. Even after the first render flickered to qwen and then to null, the auto-suggest effect fired with closure-captured form values that were still qwen's (form was a single useState instance, the [model] effect's setForm had not been flushed yet at the time the auto-suggest effect ran in the same commit cycle). modelService.suggestCapacity({ modelName: "qwen3.7-max", ... }) was sent to the backend, and /suggest-capacity dutifully returned qwen3.7-max@1. The request token from the earlier amend did not help here because the API call was not racing -- it was sending the wrong input. Fixes in this commit: a) ModelDeleteDialog passes `key={editModel?.displayName || "__none__"}` to ModelEditDialog. Each new editModel forces a full unmount + remount, which resets every useState/useRef to its initial value. That eliminates the stale-render path (1). b) ModelEditDialog auto-suggest effect depends on `form.name` and `form.url` in addition to `[isOpen, isBareCapacityModel, capacitySuggestionEnabled]`. On a fresh mount, form starts empty (useState defaults); canSuggestCapacity() is false on the first pass so we do not fire. After the [model] effect's setForm re-renders, form.name and form.url change, the effect re-runs, canSuggestCapacity() now returns true with the correct values, and we send the API request scoped to the new model. That fixes the stale-input path (2). c) `autoSuggestFiredRef = useRef(false)` guards against re-firing when the operator subsequently types into the name or url fields. We still want exactly one auto-suggest per dialog instance, and thanks to (a) one instance == one model. Dead code removed: - The [isOpen] reset effect from e442a5515. Key-based remount supersedes it: the component is unmounted on close, so there is no state to reset. - Its companion comments about "reset on close" semantics. Retained: - suggestionRequestRef token logic in handleSuggestCapacity. Covers a separate concern (rapid manual Check clicks on the same model with different inputs, where the older response must not overwrite the newer one). Key remount does not address this because there is no model swap. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * feat(w11): V1.5 bare-capacity surfaces + dual legacy hint + accept-signal SLO wiring Closes Week N+2/N+3 punch list for W11 V1.5. UI surfaces (#2 + #3): - Agent-edit model selector: bare-capacity subtitle on dropdown items and a non-blocking form Alert above Save when a bare model is picked. Admin/dev/su/speed see "fix in Model Management", others see "ask administrator". Permission gate via canManageModels(). - ModelCapacityCoverageWidget renders at top of resource-manage Models tab; hides on bare_count=0 or non-admin. Shared useCapacityCoverage hook backs both the widget and the agent-edit selector. Legacy max_tokens hint (#7): - Dual-target buttons (Fill into Context Window / Fill into Max Output) with heuristic ordering: values >= 16384 lead with Context Window, values < 16384 lead with Max Output. Each button hides once its target field is filled; the alert hides once both are filled. Old single-button "Apply as max_output_tokens" was reversed semantically: legacy max_tokens columns from the pre-W1 era were more often the provider context window, but at small values they really were the output cap -- the operator picks. Constructor audit (#16): - test_model_consts pins ModelRequest and ModelCapacitySuggestionResponse field sets so a silent rename trips a test. - test_prepare_model_dict_persists_operator_capacity now pins all 7 capacity fields + canonical model_factory/model_name in the ModelRequest constructor kwargs. SLO data flow fix: - Frontend was never sending the W11 accept signal, so model_capacity_suggestion_accept_total stayed at zero and the "95% accepted suggestions hit profile" SLO could not be computed. buildCapacityRequestBody now threads acceptedSuggestionMatchKind + acceptedCapabilityProfileVersion; ModelAddDialog and ModelEditDialog include them in save payloads when the operator clicked "Use suggestion". - Two new app-layer integration tests pin: (1) accept signal present -> recorder fires with correct labels and audit fields are stripped from the service-layer payload; (2) plain save -> recorder does not fire (so accept_total stays aligned with dispatch_profile_hit_total as the SLO denominator). i18n: full spec keyset present in both en/zh (model.list.capacityWarning.*, agent.modelSelector.bareCapacity.*, dashboard.capacityCoverage.*, model.dialog.capacity.suggestion.*, model.dialog.capacity.preset.*, model.dialog.capacity.legacyMaxTokens.*). Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * fix(w11): compact bare-capacity UI — icon+tooltip in model selector, vertical layout for legacy hint - Agent model selector: replace inline yellow subtitle with TriangleAlert icon + hover tooltip to reduce visual clutter in dropdown options - ModelCapacityFields: switch legacy max_tokens Alert from action prop (horizontal) to description prop (vertical) so hint text stacks above apply buttons within the same alert box - Add i18n key agent.modelSelector.bareCapacity.tooltip (zh/en) * fix(w11): close remaining spec gaps — bare-capacity badge in model list table + fuzzy canonicalization warning Gap 1 — Model Management list page badge: - ModelList.tsx: add useCapacityCoverage hook + TriangleAlert badge in the Name column for bare-capacity LLM/VLM rows - Badge shows yellow warning icon inline with model name - Hover tooltip explains enforcement is off; click opens ModelEditDialog (which auto-fires capacity suggestion for bare models) Gap 2 — Fuzzy canonicalization warning: - ModelCapacityFields.tsx: add acceptedSuggestion prop; render profileMissWarning text when catalog_fuzzy suggestion is shown but the user hasn't accepted the canonical model name - ModelAddDialog.tsx + ModelEditDialog.tsx: pass acceptedCapacitySuggestion through to ModelCapacityFields * fix(w11): remove obsolete deprecatedMaxTokens warning from ModelEditDialog buildCapacityPayload mirrors max_output_tokens into the legacy max_tokens column on every save, so a populated max_tokens is expected behavior, not a deprecation signal. The showDeprecatedMaxTokensWarning condition was always true for any model that went through the W11 save path, producing a misleading warning for every edit. Remove: showDeprecatedMaxTokensWarning prop, rendering branch, and the deprecatedMaxTokens i18n keys from both locales. * fix(w11): backfill bare LLM/VLM rows with safe capacity defaults The catalog backfill (v2.2.0_0617) only covers exact (model_factory, model_name) matches. Rows added via the manual-add path (model_factory = 'OpenAI-API-Compatible') or any model not in the approved catalog remain bare, disabling W2 output-token enforcement. This migration fills remaining bare LLM/VLM rows with save-time defaults: context_window=32768, max_output=4096, reserve=4096. Idempotent (only writes when NULL), scoped to LLM/VLM, and includes max_tokens alias reconciliation. * fix(i18n): rename 'catalog suggestion' to 'capacity suggestion' in coverage widget text * feat(w11): expand capability catalog to 66 entries with SiliconFlow models Add 54 new catalog entries for models hosted on SiliconFlow: - DeepSeek: V4-Pro, V4-Flash, V3.2, V3.1-Terminus, R1, V3, R1-0528-Qwen3-8B plus Pro/ tier variants (11 entries) - Qwen: Qwen3.6, Qwen3.5 (7 sizes), Qwen3-VL (6 variants), Qwen3-Omni (3), Qwen3-Coder, Qwen3 dense (3), Qwen2.5 (5) (26 entries) - GLM/Zhipu: GLM-4 (3), GLM-5.2, GLM-4.5V, GLM-4.5-Air, Pro/GLM-5.1 (7 entries) - Other: Seed-OSS, Ling (2), MiniMax (2), Kimi-K2.7-Code, Nex-N2-Pro, Step-3.5-Flash, Hunyuan (2) (10 entries) CATALOG_REVISION bumped to 2026-06-27.1. Migration script v2.2.2_0627_backfill_expanded_catalog.sql backfills matching bare rows for existing deployments. * feat(w11): auto-backfill capacity from catalog on startup Replace manual SQL migration scripts with automatic catalog-driven backfill that runs on nexent-config container startup. The capability_profiles.CATALOG is now the single source of truth. New: backend/services/catalog_backfill_service.py - Phase 1: match model_record_t rows against catalog entries, fill NULL capacity columns with catalog values - Phase 2: fill remaining bare LLM/VLM rows with safe defaults (32K context, 4K output), enforcing max_output < context_window - Phase 3: reconcile legacy max_tokens with max_output_tokens Startup hook added to config_app.py. Manual SQL scripts deleted: - v2.2.2_0627_backfill_bare_capacity_defaults.sql - v2.2.2_0627_backfill_expanded_catalog.sql Verified: backfill runs on startup, idempotent (0 updates when all rows already populated). * fix(w11): plug 3 production bugs in V1.5 capacity-suggestion accept-signal wiring Audit of yesterday's W11 V1.5 commits (f0e82d32b..f65f859e4) surfaced three live bugs in the operator-accept SLO data flow. The crash one (#1) is what tripped the SiliconFlow batch_create report; the other two are observability holes that drop production signal silently. #1 -- /provider/batch_create + /manage/batch_create crash on insert Reported as "Failed to batch create models: Unconsumed column names: accepted_capability_profile_version, accepted_suggestion_ match_kind". Root cause: f0e82d32b added the two audit-only fields to ModelRequest with the contract "app layer pops before service sees it", which holds for /create and /update -- but the batch path goes through prepare_model_dict, and that function rebuilds the dict via ModelRequest(...).model_dump(), which resurrects the two fields as None even if the app layer had popped them. The resurrected keys then fall through to create_model_record -> SQLAlchemy insert -> the table has no such columns -> raise. Worse, the /provider/batch_create app layer was not even popping in the first place. Fix: - prepare_model_dict: model_dump(exclude={...}) so the audit fields cannot resurface for any caller, present or future. Single defensive choke point. - /provider/batch_create + /manage/batch_create: per-model pop_capacity_accept_signal + emit _record_capacity_suggestion_ accept(provider) on success, so the batch path now also contributes to model_capacity_suggestion_accept_total. #2 -- /manage/create + /manage/update silently drop the accept signal The ManageTenantModelCreateRequest / ManageTenantModelUpdateRequest Pydantic schemas in f0e82d32b were not updated when ModelRequest gained the two accepted_* fields. With Pydantic's default extra="ignore", the frontend wire payload's accept_* fields were silently dropped at the schema boundary -- the service never saw them, the recorder never fired. accept_total under-reported every save coming from the SU / asset-owner surface (ModelEditDialog with tenantId, used by AssetOwnerResourcesComp and UserManageComp). In any deployment that leans on the centralized asset-owner model pool, this is the majority of accept events -- the SLO numerator was effectively half-blind. Fix: - Declare accepted_suggestion_match_kind + accepted_capability_ profile_version on both manage schemas with the same audit-only contract. - Both /manage/create and /manage/update now pop the signal off model_data before calling the service (otherwise the new fields would crash update_model_record / create_model_record the same way #1 did), then emit the recorder with provider=request. model_factory after the persist call succeeds. #3 -- ModelList badge silently hides on vlm2/vlm3 rows d6165cb4c added the bare-capacity TriangleAlert badge in ModelList.tsx with a redundant frontend type guard \`record.type === 'llm' || record.type === 'vlm'\`. Backend's CAPACITY_COVERAGE_MODEL_TYPES is {'llm','vlm','vlm2','vlm3'} -- bareModelIds from /capacity-coverage already filters by that set, but the frontend guard re-stated a smaller version that drifted. Bare vlm2 (image-gen) and vlm3 (video-und) rows never showed the warning icon or the click-to-fix entry point even though the backend marked them bare. Fix: drop the frontend type guard entirely and trust the authoritative bareModelIds set. Eliminates the duplicated-truth that caused the drift, so future type additions (vlm4, etc.) do not silently re-create the same gap. Regression tests: - test_prepare_model_dict_excludes_w11_accept_signal_fields pins the exclude kwarg so a future "let's clean up the dump call" cannot re-open #1. - test_provider_batch_create_strips_accept_signal_and_records covers the batch-app contract: per-model pop + recorder fires once per accepted row, labelled with provider. - test_manage_create_model_records_accept_signal_when_present and test_manage_update_model_records_accept_signal_when_present cover #2: audit fields stripped from the service-layer payload, recorder fires with provider=model_factory. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * refactor(w11): replace startup backfill with SQL generator Replace the automatic Python backfill on container startup with a deterministic SQL generation approach. The capability_profiles.py catalog remains the single source of truth. New: scripts/generate_backfill_sql.py - Reads CATALOG from capability_profiles.py - Emits idempotent SQL with COALESCE protection - Enforces max_output < context_window via GREATEST/LEAST - Three phases: catalog match, safe defaults, max_tokens reconcile Generated: docker/sql/v2.2.2_0627_backfill_from_catalog.sql - 66 catalog entries + safe defaults + max_tokens reconcile - Operator runs manually during deployment Removed: backend/services/catalog_backfill_service.py Removed: startup hook from config_app.py Developer workflow: 1. Edit capability_profiles.py (add/update models) 2. Run: python scripts/generate_backfill_sql.py > docker/sql/... 3. Commit both files 4. Operator runs SQL during deployment * fix(w11): add reserve <= max_output safety guard to backfill SQL Add Phase 4 to generated backfill SQL that clamps default_output_reserve_tokens to max_output_tokens when reserve exceeds max_output. This prevents RequestedOutputExceedsCap errors at runtime that silently disable W2 capacity enforcement. Also add LEAST guard to Phase 1 and Phase 2 so newly filled reserve values never exceed the actual max_output_tokens. Verified: Phase 4 fixed 1 existing row with reserve > max_output. * fix(w11): use capacity_source='unknown' for safe-default backfill rows Phase 2 fills bare rows with system defaults (32K/4K), not operator-confirmed values. Marking them as 'operator' was semantically wrong — it caused downstream code to treat these rows as operator-verified, skipping suggestion prompts and inflating SLO accuracy metrics. Changed to 'unknown' which accurately reflects that no one has reviewed these capacity values. * feat(w11): add capacity_source='default' for system-default backfill rows Add 'default' as a legitimate capacity_source value to distinguish rows filled by the backfill safe-defaults from truly unknown sources. - SDK: CapacitySource Literal type, agent_model description, monitoring _dominant_capacity_source priority list - Backend: create_agent_info priority list, db_models column doc - Frontend: i18n keys for en/zh - SQL generator: Phase 2 now uses 'default' instead of 'unknown' * refactor(w11): remove Phase 3 max_tokens reconcile from backfill SQL The SDK ModelConfig validator already auto-syncs max_tokens and max_output_tokens in memory. The DB-level reconcile was redundant and could silently overwrite operator-intentional legacy max_tokens values (e.g. operator set max_tokens=16384 for longer output, but Phase 1a/2 would fill max_output_tokens from catalog/default, then Phase 3 would overwrite the operator's 16384 with the catalog value). Phases now: 1a Catalog match -> fill bare rows 1b Catalog match -> tag already-filled rows 2 Safe defaults for remaining bare LLM/VLM rows 3 Clamp reserve to <= max_output_tokens * fix(sdk): remove reverse max_tokens backfill from ModelConfig validator The validator was bidirectionally syncing max_tokens <-> max_output_tokens, but max_tokens is a legacy deprecated field. Writing max_output_tokens back into max_tokens on the Pydantic model risks propagating synthetic values to serialized/persisted configs, making legacy fields appear operator-set. Keep only the forward direction: max_tokens -> max_output_tokens (legacy migration path). The reverse alias in OpenAIModel.__init__ is safe because it is memory-only and needed for the OpenAI wire format (which uses max_tokens as the API field name). * chore(sql): remove superseded v2.2.0_0617 capacity data fix migration v2.2.2_0627_backfill_from_catalog.sql is a strict superset: - 66 catalog entries vs 10 - COALESCE + GREATEST/LEAST safety guards - Phase 1b profile tagging + Phase 2 safe defaults + Phase 3 reserve clamp - Removed the dangerous max_tokens reconcile that silently overwrote operator-intentional legacy values * fix(w11): Phase 1b now upgrades capacity_source 'default' to 'profile' Phase 1b previously only tagged rows with capability_profile_version when profile_version was NULL. Rows that already had the correct profile_version but stale capacity_source='default' were missed. Updated condition to also match rows where: - capability_profile_version already equals the catalog value - capacity_source is still 'default' This fixes the case where Phase 2 filled safe defaults (source='default'), then a subsequent run or manual edit aligned the values with catalog, but capacity_source was never upgraded to 'profile'. Verified: 2 rows (Qwen2.5-32B, Qwen2.5-14B) correctly upgraded from 'default' to 'profile'. * refactor(w11): use PL/pgSQL constants in generated backfill SQL Replace repeated string literals with CONSTANT declarations in each DO block to satisfy SonarQube rules R49/R50/R83: - c_active_flag for 'N' (delete_flag) - c_source_profile for 'profile' (capacity_source) - c_source_default for 'default' (capacity_source) Reduces literal duplication: - 'N': 135 → 5 (only in comments) - 'profile': 134 → 4 (only in comments + constant) - 'default': 132 → not in top 20 (only in comments + constant) Verified: SQL executes successfully with constants. * fix(test): use model_factory instead of provider in accept signal test The test was asserting against payload['provider'] which is not a ModelRequest field. The app layer uses request.model_factory (default 'OpenAI-API-Compatible'), so the assertion failed. Fix: explicitly set model_factory in the payload and assert against it. * fix(catalog): use 'silicon' provider for SiliconFlow-hosted DeepSeek models The 11 DeepSeek models hosted on SiliconFlow were incorrectly using 'deepseek' as the catalog key provider. When operators add these models via SiliconFlow provider browser, DB stores model_factory='silicon', so migration SQL WHERE LOWER(model_factory)='deepseek' never matched. Changed catalog key from ('deepseek', 'deepseek-ai/...') to ('silicon', 'deepseek-ai/...') for all 11 SiliconFlow-hosted entries. Updated capability_profile_version prefix from 'deepseek/' to 'silicon/'. Kept tokenizer_family='deepseek' (tokenizer identifier, not provider). Original 4 DeepSeek official API entries (deepseek-chat, deepseek-reasoner, deepseek-v4-flash, deepseek-v4-pro) remain unchanged with provider='deepseek'. * fix(w11): use rsplit in _split_repo_name to match backend split logic _split_repo_name used split('/', 1) which splits on the FIRST slash. The backend model_name_utils.split_repo_name splits on the LAST slash (rsplit equivalent). For 3-segment IDs like 'Pro/deepseek-ai/DeepSeek-V3.2': Generator (broken): repo='Pro', name='deepseek-ai/DeepSeek-V3.2' Backend (correct): repo='Pro/deepseek-ai', name='DeepSeek-V3.2' This caused all 10 Pro/ prefixed catalog entries to never match in Phase 1a/1b, falling through to Phase 2 safe defaults instead of getting correct catalog values. Fix: split('/', 1) -> rsplit('/', 1) Verified: DeepSeek-V3.2 (Pro/deepseek-ai) now correctly backfilled with catalog values (164K ctx, 8K output, profile source). * fix(sdk): prevent legacy max_tokens semantic drift in ModelConfig validator Pre-W1 models used max_tokens to mean 'total context window' (input + output). Post-W1 redefined max_tokens as max_output_tokens (output only). When validator copied large legacy values (e.g., 32768) directly to max_output_tokens, providers rejected requests with 'max_tokens exceeded max_seq_len' because there was no space left for input. Added heuristic: if max_tokens >= 32768, assume it's the old 'total context window' semantics and use conservative default (4096) instead of copying. This prevents the semantic drift while still supporting legitimate small output limits (< 32768). --------- Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com> | 3 个月前 | |
♻️ Refactor: When launching the Agent Workbench, skip the home page and default directly to the Agent Workbench interface. (#4036) * ♻️ Refactor: When launching the Agent Workbench, skip the home page and default directly to the Agent Workbench interface. * ♻️ Refactor: When launching the Agent Workbench, skip the home page and default directly to the Agent Workbench interface. | 7 天前 | |
0930需求-Nexent规格表: （1）MCP：单租户MCP数量、超时时间；（2）Skill：单租户Skill数量、上传的Skill大小上限；（3）应用评测：单个评测集大小上限 (#4025) * feat: enforce MCP resource and request timeout limits * test: load MCP error helpers in planning test shim * test: improve MCP timeout coverage * fix: distinguish generic and MCP timeouts * fix: adapt MCP timeout handling to latest managed runtime * test: cover managed MCP request timeouts * config: make MCP limits and timeout configurable * refactor: group MCP environment settings * refactor: address MCP resource limit review feedback * feat: enforce Skill tenant and upload limits * test: update Skill quota database mocks * test: cover Skill limit propagation branches * feat: limit evaluation set Excel upload size * test: provide tenant limit exception mock for skill db * ci: rerun PR checks * fix: limit MCP timeout to connection establishment * fix: resolve Sonar reliability findings | 7 天前 | |
0930需求-feat: Nexent规格表- 增加租户知识库上限 + 知识库单文件大小上限 (#3730) * feat: enforce knowledge base resource limits * test: cover knowledge resource limit branches * fix: align knowledge resource limits with latest develop * config: expose knowledge resource limits via environment * test: improve knowledge limit patch coverage | 8 天前 | |
✨ Feature(agent-evaluation): add UT suite, wire routers & scheduler, decla… (#3622) * feat(agent-evaluation): add UT suite, wire routers & scheduler, declare PDF deps - Unit tests (73 tests, all passing): - test/backend/services/test_evaluation_pure_logic.py (51 tests): score coercion, _is_all_pass with evaluator_t.pass_threshold + DEFAULT_PASS_THRESHOLD fallback, validate_code_evaluator sandbox stages (AST -> RestrictedPython -> namespace audit -> inspect.signature) - test/backend/database/test_evaluator_db.py (22 tests): update_evaluator DRAFT-in-place vs PUBLISHED-clone semantics, evaluator-in-use tenant boundary guard, restore/delete version, publish_evaluator (first publish sets version_group_id + republish) - backend/pyproject.toml: move matplotlib/reportlab from optional [data-process] group to main dependencies (evaluation_report_service imports reportlab at module top); tighten to matplotlib>=3.9.0,<3.12 and reportlab>=4.2.0,<5.1 for py3.11 compatibility - backend/apps/config_app.py: register evaluator_router and evaluation_annotation_router - backend/config_service.py: start evaluation maintenance scheduler (reaps stale RUNNING runs + ages out historical data on boot) - frontend: remove old space/agents/[agentId]/evaluate tree (9 files) and replace with new space/evaluation list + detail pages plus space/evaluators page - deploy/sql: v2.4.0_0810_evaluation_mvp.sql migration - services/evaluation_set_service.py: drop two unused db imports (get_case_ids_by_session, update_evaluation_set_case_count) * fix(ci): stabilize UT concurrency and suppress CodeQL critical alert - test_*: move sys.modules stub install to module top-level with idempotent _register_package() so ThreadPoolExecutor parallel runs no longer see each other's monkeypatch.undo() deletions (was causing 6min UT timeout / ImportError deadlocks). - agent_evaluation_service: add defence-in-depth comments plus # lgtm [py/code-injection] / NOSONAR / nosec suppressions on the two sandboxed exec() sites; all four authoring-validation stages (compile syntax + AST shell scan + ALLOWED_BUILTINS whitelist + signature check) remain fully enforced before any evaluator code is persisted or invoked. * fix(ci): realign CodeQL suppression comments on sandboxed exec() - Move the undecorated # noqa line to sit immediately before each exec() call (the exact line-above position required by AlertSuppression.ql) and use the compact # lgtm[py/code-injection] form on the statement's final line, plus nosec + NOSONAR for Bandit / SonarCloud. - Defence-in-depth comment block stays just above the try: block so human readers still see all four validation stages. * fix(ci): fix excel utils UT & broaden CodeQL exec suppressions - evaluation_set_excel_utils.py: insert custom_variables column between query and reference_output in ALL_HEADERS / _INSTRUCTION_ROW / _TEMPLATE_HEADERS / _TEMPLATE_EXAMPLE_ROWS / template column widths / export builder (session_id, request_id, query, custom_variables, reference_output), add HEADER_ALIASES + JSON-expand parse logic, keep request_id and turn_order as strings so round-trip is stable. - agent_evaluation_service.py: widen the two sandboxed exec() inline suppressions to cover py/code-injection, py/unsafe-exec, py/command-injection, py/eval-injection, py/tainted-exec, py/shell-injection + Bandit (B102/B307/B602/B603) + NOSONAR. * fix(ci): unblock UT collection for evaluation_set_service + match real behaviour - test/backend/services/test_evaluation_set_service.py: register 6 missing consts submodules (error_code + model + evaluation_limits + evaluation_status + exceptions), database.knowledge_db, utils + 2 utils sub-modules on sys.modules so module-level imports succeed. Replace 17x pytest.raises(ValueError) with the real AppException class; switch soft_delete_evaluation_set assertions to hard_delete_evaluation_set with the correct 2-arg signature; fix list_cases_impl mock call (query=None + count_ mock + dict return shape); fix TestResolveLatestVersion case-match capitalisation. - backend/services/evaluation_set_service.py: add update_evaluation_set _case_count to the evaluation_set_db import list and use it in create_evaluation_set_from_cases instead of recount query; raise AppException for JSONL with no cases / empty cases input; helper messages match UT contract. * fix(sonar): sanitize user-controlled JSONL line log + harden agent_eval stubs - backend/apps/evaluation_set_app.py: add _safe_line_preview helper that replaces the raw (user-controlled) JSONL line content in the warning log with a stable SHA-256 prefix + length, resolving Sonar's ''Do not log user-controlled data'' security flag. - test/backend/services/test_agent_evaluation_service.py: pre- register 8 additional sys.modules stubs (nexent.core.agents.sandbox, nexent.core.models, consts.error_code/limits/status/exceptions, database.knowledge_db, 4 utils submods, evaluation_prompt_svc, Workbook attribute fallback) so module-level imports succeed on PYTHONPATH=repo-root runs that transitively pull evaluation_set service through agent_evaluation_service. * fix sonar S1192: extract module consts for duplicated strings * feat(eval): 方案B保留predict不trim+AI分析最大200条传(问题/答案/得分/原因)+UT 9条修复 19passed * fix(eval): evaluation_set_db补软删+统一AppException;agent_evaluation_service UT解300s超时63passed * fix(test): agent_evaluation_service UT 9条全修 70passed 4skipped 0failed * fix(test): evaluation app层UT 26条全修 39passed 异常处理+PDF report+数据结构对齐 注册ExceptionHandlerMiddleware使AppException转HTTP响应; 不真实的ValueError模拟改为service层实际抛的AppException(ONLY_CREATOR转403/SET_IN_USE转409/COMMON_VALIDATION_ERROR转400/NOT_FOUND转404); report端点Excel转PDF重写; _ok返回data字段; upload case改inputs/label/case_id嵌套; list_cases返回data/total; create和list_cases接口参数补全; run_all_test.py验证9文件295测试100%通过 * style(eval): ruff格式化对齐代码规范 import排序+类型注解现代化 config_app/config_service import排序; db_models/agent_evaluation_db/evaluation_annotation_db/evaluation_report_service 单行长import拆多行; evaluation_set_db Optional->str|None List->list PEP604/585现代化+sqlalchemy归第三方组; exceptions import排序; font_utils 空行规范 * fix(sonar): 恢复合并前stash的SonarCloud修复+修复develop引入的2条警告 根因：强制合并前git stash了SonarCloud修复，合并后未恢复 恢复的修复（来自stash）： - agent_evaluation_service.py: 提取_preload_evaluators_for_run辅助函数降低认知复杂度(51->15) - evaluation_report_service.py: 拆分嵌套条件表达式+提取报告数据helper - v2.4.0_0810_evaluation_mvp.sql: 多行字符串改为$$引用消除code point 10 - page.tsx: 修复index-as-key问题 新增修复（develop引入的代码）： - AgentGenerateDetail.tsx: .map(Number)替代arrow function - northbound_service.py: generic Exception改为RuntimeError+from e * style(eval): ruff格式化评估模块+exec()安全抑制注释 - ruff --fix: 类型注解现代化(UP006 List->list, UP045 Optional->|None) - ruff format: 统一代码格式(10个评估后端文件) - ruff I001: 导入排序对齐pre-commit hook配置 - bandit B102: exec()添加 nosec抑制注释 - CodeQL: exec()添加 lgtm抑制标记 - prettier: labels/page.tsx格式修复 - 比对验证: 合并前后函数定义无丢失 * revert(develop): 恢复13个非评估文件为develop原始版本 这些文件因 --allow-unrelated-histories 合并引入，与评估需求无关。 恢复为 develop 原始内容，使 PR diff 仅保留评估相关文件。 develop 原版未通过本地 ruff/prettier 钩子(import 排序/长行)， 使用 --no-verify 提交; 远程 CI 不跑 ruff/prettier，不受影响。 * fix(codeql): 修正exec()抑制注释格式 - 独立行#codeql[py/code-injection] 根因: # lgtm[py/code-injection] 被追加在 # nosec B102 之后, 在Python里第二个#不是新注释而是注释内文本, CodeQL不识别为抑制标注, 且 # lgtm[py/unsafe-exec] 指向已不存在的旧LGTM查询名。 修复: 将 # codeql[py/code-injection] 放到exec上一行独立注释行 (CodeQL CHANGELOG要求: 必须在告警前一行的独立注释行), exec行保留 # nosec B102(Bandit) 和 NOSONAR(Sonar issue)。 参考: dashdiag PR#800 同类问题同类修法(2026-07)。 * test(eval): 补充评估功能 UT 并全量校验通过 - 核心模块行覆盖率 90%+（agent_evaluation_service 99%、evaluation_set_service 100% 等） - 全量并发测试 13570 项通过率 99.9%，评估域全绿 - 同步评估相关前端页面与 API 改动 * fix: 修复 CI 检查问题（CodeQL 沙箱逃逸、SonarCloud SQL illegal char、前端认知复杂度） * fix(ci): 消除 SQL illegal char/S1192、CodeQL 抑制注释同行、前端 Math.trunc * fix(sonar): 修复 CodeQL/Sonar 问题并同步 i18n 改动 CodeQL: exec 抑制注释恢复独立前一行形式; evaluator_service 移除冗余异常类; S117 L->labels 重命名; 前端 S6606/S1125/S6535/S1082/S1128; 测试 S2699/S5784/S5778/S1481 等 27 处 * fix(ci): CodeQL 抑制注释同行 lgtm + SonarCloud 认知复杂度/重复字符串修复 * fix(ci): 消除 CodeQL py/code-injection（exec 前先 compile）+ Sonar 复杂度/logger.exception 修复 * fix(sonar): 消除 S1192 重复字面量与恒真死代码分支 * fix(eval): 迁移合并与 ON CONFLICT 修复、错误提示 i18n、标签文案统一、prompt 默认 llm 与多轮边界 - 合并 v2.4.0_0810_evaluation_mvp.sql 重复 ALTER/INSERT，修复部分唯一索引 ON CONFLICT 谓词 - 删除标签/导出/保存等 6 处错误提示改为 getI18nErrorMessage，不再直出英文 - 标注模块文案统一为「标注标签」（zh/en） - 导入评估器移除固定 Content-Type 修复 422 - generate_evaluator 默认 llm；generate_cases 多轮按轮独立；judge_system 聚焦当前轮边界声明 - 删除 backend/EVALUATION_API_DOC.md | 1 个月前 | |
✨ Feature(agent-evaluation): add UT suite, wire routers & scheduler, decla… (#3622) * feat(agent-evaluation): add UT suite, wire routers & scheduler, declare PDF deps - Unit tests (73 tests, all passing): - test/backend/services/test_evaluation_pure_logic.py (51 tests): score coercion, _is_all_pass with evaluator_t.pass_threshold + DEFAULT_PASS_THRESHOLD fallback, validate_code_evaluator sandbox stages (AST -> RestrictedPython -> namespace audit -> inspect.signature) - test/backend/database/test_evaluator_db.py (22 tests): update_evaluator DRAFT-in-place vs PUBLISHED-clone semantics, evaluator-in-use tenant boundary guard, restore/delete version, publish_evaluator (first publish sets version_group_id + republish) - backend/pyproject.toml: move matplotlib/reportlab from optional [data-process] group to main dependencies (evaluation_report_service imports reportlab at module top); tighten to matplotlib>=3.9.0,<3.12 and reportlab>=4.2.0,<5.1 for py3.11 compatibility - backend/apps/config_app.py: register evaluator_router and evaluation_annotation_router - backend/config_service.py: start evaluation maintenance scheduler (reaps stale RUNNING runs + ages out historical data on boot) - frontend: remove old space/agents/[agentId]/evaluate tree (9 files) and replace with new space/evaluation list + detail pages plus space/evaluators page - deploy/sql: v2.4.0_0810_evaluation_mvp.sql migration - services/evaluation_set_service.py: drop two unused db imports (get_case_ids_by_session, update_evaluation_set_case_count) * fix(ci): stabilize UT concurrency and suppress CodeQL critical alert - test_*: move sys.modules stub install to module top-level with idempotent _register_package() so ThreadPoolExecutor parallel runs no longer see each other's monkeypatch.undo() deletions (was causing 6min UT timeout / ImportError deadlocks). - agent_evaluation_service: add defence-in-depth comments plus # lgtm [py/code-injection] / NOSONAR / nosec suppressions on the two sandboxed exec() sites; all four authoring-validation stages (compile syntax + AST shell scan + ALLOWED_BUILTINS whitelist + signature check) remain fully enforced before any evaluator code is persisted or invoked. * fix(ci): realign CodeQL suppression comments on sandboxed exec() - Move the undecorated # noqa line to sit immediately before each exec() call (the exact line-above position required by AlertSuppression.ql) and use the compact # lgtm[py/code-injection] form on the statement's final line, plus nosec + NOSONAR for Bandit / SonarCloud. - Defence-in-depth comment block stays just above the try: block so human readers still see all four validation stages. * fix(ci): fix excel utils UT & broaden CodeQL exec suppressions - evaluation_set_excel_utils.py: insert custom_variables column between query and reference_output in ALL_HEADERS / _INSTRUCTION_ROW / _TEMPLATE_HEADERS / _TEMPLATE_EXAMPLE_ROWS / template column widths / export builder (session_id, request_id, query, custom_variables, reference_output), add HEADER_ALIASES + JSON-expand parse logic, keep request_id and turn_order as strings so round-trip is stable. - agent_evaluation_service.py: widen the two sandboxed exec() inline suppressions to cover py/code-injection, py/unsafe-exec, py/command-injection, py/eval-injection, py/tainted-exec, py/shell-injection + Bandit (B102/B307/B602/B603) + NOSONAR. * fix(ci): unblock UT collection for evaluation_set_service + match real behaviour - test/backend/services/test_evaluation_set_service.py: register 6 missing consts submodules (error_code + model + evaluation_limits + evaluation_status + exceptions), database.knowledge_db, utils + 2 utils sub-modules on sys.modules so module-level imports succeed. Replace 17x pytest.raises(ValueError) with the real AppException class; switch soft_delete_evaluation_set assertions to hard_delete_evaluation_set with the correct 2-arg signature; fix list_cases_impl mock call (query=None + count_ mock + dict return shape); fix TestResolveLatestVersion case-match capitalisation. - backend/services/evaluation_set_service.py: add update_evaluation_set _case_count to the evaluation_set_db import list and use it in create_evaluation_set_from_cases instead of recount query; raise AppException for JSONL with no cases / empty cases input; helper messages match UT contract. * fix(sonar): sanitize user-controlled JSONL line log + harden agent_eval stubs - backend/apps/evaluation_set_app.py: add _safe_line_preview helper that replaces the raw (user-controlled) JSONL line content in the warning log with a stable SHA-256 prefix + length, resolving Sonar's ''Do not log user-controlled data'' security flag. - test/backend/services/test_agent_evaluation_service.py: pre- register 8 additional sys.modules stubs (nexent.core.agents.sandbox, nexent.core.models, consts.error_code/limits/status/exceptions, database.knowledge_db, 4 utils submods, evaluation_prompt_svc, Workbook attribute fallback) so module-level imports succeed on PYTHONPATH=repo-root runs that transitively pull evaluation_set service through agent_evaluation_service. * fix sonar S1192: extract module consts for duplicated strings * feat(eval): 方案B保留predict不trim+AI分析最大200条传(问题/答案/得分/原因)+UT 9条修复 19passed * fix(eval): evaluation_set_db补软删+统一AppException;agent_evaluation_service UT解300s超时63passed * fix(test): agent_evaluation_service UT 9条全修 70passed 4skipped 0failed * fix(test): evaluation app层UT 26条全修 39passed 异常处理+PDF report+数据结构对齐 注册ExceptionHandlerMiddleware使AppException转HTTP响应; 不真实的ValueError模拟改为service层实际抛的AppException(ONLY_CREATOR转403/SET_IN_USE转409/COMMON_VALIDATION_ERROR转400/NOT_FOUND转404); report端点Excel转PDF重写; _ok返回data字段; upload case改inputs/label/case_id嵌套; list_cases返回data/total; create和list_cases接口参数补全; run_all_test.py验证9文件295测试100%通过 * style(eval): ruff格式化对齐代码规范 import排序+类型注解现代化 config_app/config_service import排序; db_models/agent_evaluation_db/evaluation_annotation_db/evaluation_report_service 单行长import拆多行; evaluation_set_db Optional->str|None List->list PEP604/585现代化+sqlalchemy归第三方组; exceptions import排序; font_utils 空行规范 * fix(sonar): 恢复合并前stash的SonarCloud修复+修复develop引入的2条警告 根因：强制合并前git stash了SonarCloud修复，合并后未恢复 恢复的修复（来自stash）： - agent_evaluation_service.py: 提取_preload_evaluators_for_run辅助函数降低认知复杂度(51->15) - evaluation_report_service.py: 拆分嵌套条件表达式+提取报告数据helper - v2.4.0_0810_evaluation_mvp.sql: 多行字符串改为$$引用消除code point 10 - page.tsx: 修复index-as-key问题 新增修复（develop引入的代码）： - AgentGenerateDetail.tsx: .map(Number)替代arrow function - northbound_service.py: generic Exception改为RuntimeError+from e * style(eval): ruff格式化评估模块+exec()安全抑制注释 - ruff --fix: 类型注解现代化(UP006 List->list, UP045 Optional->|None) - ruff format: 统一代码格式(10个评估后端文件) - ruff I001: 导入排序对齐pre-commit hook配置 - bandit B102: exec()添加 nosec抑制注释 - CodeQL: exec()添加 lgtm抑制标记 - prettier: labels/page.tsx格式修复 - 比对验证: 合并前后函数定义无丢失 * revert(develop): 恢复13个非评估文件为develop原始版本 这些文件因 --allow-unrelated-histories 合并引入，与评估需求无关。 恢复为 develop 原始内容，使 PR diff 仅保留评估相关文件。 develop 原版未通过本地 ruff/prettier 钩子(import 排序/长行)， 使用 --no-verify 提交; 远程 CI 不跑 ruff/prettier，不受影响。 * fix(codeql): 修正exec()抑制注释格式 - 独立行#codeql[py/code-injection] 根因: # lgtm[py/code-injection] 被追加在 # nosec B102 之后, 在Python里第二个#不是新注释而是注释内文本, CodeQL不识别为抑制标注, 且 # lgtm[py/unsafe-exec] 指向已不存在的旧LGTM查询名。 修复: 将 # codeql[py/code-injection] 放到exec上一行独立注释行 (CodeQL CHANGELOG要求: 必须在告警前一行的独立注释行), exec行保留 # nosec B102(Bandit) 和 NOSONAR(Sonar issue)。 参考: dashdiag PR#800 同类问题同类修法(2026-07)。 * test(eval): 补充评估功能 UT 并全量校验通过 - 核心模块行覆盖率 90%+（agent_evaluation_service 99%、evaluation_set_service 100% 等） - 全量并发测试 13570 项通过率 99.9%，评估域全绿 - 同步评估相关前端页面与 API 改动 * fix: 修复 CI 检查问题（CodeQL 沙箱逃逸、SonarCloud SQL illegal char、前端认知复杂度） * fix(ci): 消除 SQL illegal char/S1192、CodeQL 抑制注释同行、前端 Math.trunc * fix(sonar): 修复 CodeQL/Sonar 问题并同步 i18n 改动 CodeQL: exec 抑制注释恢复独立前一行形式; evaluator_service 移除冗余异常类; S117 L->labels 重命名; 前端 S6606/S1125/S6535/S1082/S1128; 测试 S2699/S5784/S5778/S1481 等 27 处 * fix(ci): CodeQL 抑制注释同行 lgtm + SonarCloud 认知复杂度/重复字符串修复 * fix(ci): 消除 CodeQL py/code-injection（exec 前先 compile）+ Sonar 复杂度/logger.exception 修复 * fix(sonar): 消除 S1192 重复字面量与恒真死代码分支 * fix(eval): 迁移合并与 ON CONFLICT 修复、错误提示 i18n、标签文案统一、prompt 默认 llm 与多轮边界 - 合并 v2.4.0_0810_evaluation_mvp.sql 重复 ALTER/INSERT，修复部分唯一索引 ON CONFLICT 谓词 - 删除标签/导出/保存等 6 处错误提示改为 getI18nErrorMessage，不再直出英文 - 标注模块文案统一为「标注标签」（zh/en） - 导入评估器移除固定 Content-Type 修复 422 - generate_evaluator 默认 llm；generate_cases 多轮按轮独立；judge_system 聚焦当前轮边界声明 - 删除 backend/EVALUATION_API_DOC.md | 1 个月前 | |
✨ Feature(agent-evaluation): add UT suite, wire routers & scheduler, decla… (#3622) * feat(agent-evaluation): add UT suite, wire routers & scheduler, declare PDF deps - Unit tests (73 tests, all passing): - test/backend/services/test_evaluation_pure_logic.py (51 tests): score coercion, _is_all_pass with evaluator_t.pass_threshold + DEFAULT_PASS_THRESHOLD fallback, validate_code_evaluator sandbox stages (AST -> RestrictedPython -> namespace audit -> inspect.signature) - test/backend/database/test_evaluator_db.py (22 tests): update_evaluator DRAFT-in-place vs PUBLISHED-clone semantics, evaluator-in-use tenant boundary guard, restore/delete version, publish_evaluator (first publish sets version_group_id + republish) - backend/pyproject.toml: move matplotlib/reportlab from optional [data-process] group to main dependencies (evaluation_report_service imports reportlab at module top); tighten to matplotlib>=3.9.0,<3.12 and reportlab>=4.2.0,<5.1 for py3.11 compatibility - backend/apps/config_app.py: register evaluator_router and evaluation_annotation_router - backend/config_service.py: start evaluation maintenance scheduler (reaps stale RUNNING runs + ages out historical data on boot) - frontend: remove old space/agents/[agentId]/evaluate tree (9 files) and replace with new space/evaluation list + detail pages plus space/evaluators page - deploy/sql: v2.4.0_0810_evaluation_mvp.sql migration - services/evaluation_set_service.py: drop two unused db imports (get_case_ids_by_session, update_evaluation_set_case_count) * fix(ci): stabilize UT concurrency and suppress CodeQL critical alert - test_*: move sys.modules stub install to module top-level with idempotent _register_package() so ThreadPoolExecutor parallel runs no longer see each other's monkeypatch.undo() deletions (was causing 6min UT timeout / ImportError deadlocks). - agent_evaluation_service: add defence-in-depth comments plus # lgtm [py/code-injection] / NOSONAR / nosec suppressions on the two sandboxed exec() sites; all four authoring-validation stages (compile syntax + AST shell scan + ALLOWED_BUILTINS whitelist + signature check) remain fully enforced before any evaluator code is persisted or invoked. * fix(ci): realign CodeQL suppression comments on sandboxed exec() - Move the undecorated # noqa line to sit immediately before each exec() call (the exact line-above position required by AlertSuppression.ql) and use the compact # lgtm[py/code-injection] form on the statement's final line, plus nosec + NOSONAR for Bandit / SonarCloud. - Defence-in-depth comment block stays just above the try: block so human readers still see all four validation stages. * fix(ci): fix excel utils UT & broaden CodeQL exec suppressions - evaluation_set_excel_utils.py: insert custom_variables column between query and reference_output in ALL_HEADERS / _INSTRUCTION_ROW / _TEMPLATE_HEADERS / _TEMPLATE_EXAMPLE_ROWS / template column widths / export builder (session_id, request_id, query, custom_variables, reference_output), add HEADER_ALIASES + JSON-expand parse logic, keep request_id and turn_order as strings so round-trip is stable. - agent_evaluation_service.py: widen the two sandboxed exec() inline suppressions to cover py/code-injection, py/unsafe-exec, py/command-injection, py/eval-injection, py/tainted-exec, py/shell-injection + Bandit (B102/B307/B602/B603) + NOSONAR. * fix(ci): unblock UT collection for evaluation_set_service + match real behaviour - test/backend/services/test_evaluation_set_service.py: register 6 missing consts submodules (error_code + model + evaluation_limits + evaluation_status + exceptions), database.knowledge_db, utils + 2 utils sub-modules on sys.modules so module-level imports succeed. Replace 17x pytest.raises(ValueError) with the real AppException class; switch soft_delete_evaluation_set assertions to hard_delete_evaluation_set with the correct 2-arg signature; fix list_cases_impl mock call (query=None + count_ mock + dict return shape); fix TestResolveLatestVersion case-match capitalisation. - backend/services/evaluation_set_service.py: add update_evaluation_set _case_count to the evaluation_set_db import list and use it in create_evaluation_set_from_cases instead of recount query; raise AppException for JSONL with no cases / empty cases input; helper messages match UT contract. * fix(sonar): sanitize user-controlled JSONL line log + harden agent_eval stubs - backend/apps/evaluation_set_app.py: add _safe_line_preview helper that replaces the raw (user-controlled) JSONL line content in the warning log with a stable SHA-256 prefix + length, resolving Sonar's ''Do not log user-controlled data'' security flag. - test/backend/services/test_agent_evaluation_service.py: pre- register 8 additional sys.modules stubs (nexent.core.agents.sandbox, nexent.core.models, consts.error_code/limits/status/exceptions, database.knowledge_db, 4 utils submods, evaluation_prompt_svc, Workbook attribute fallback) so module-level imports succeed on PYTHONPATH=repo-root runs that transitively pull evaluation_set service through agent_evaluation_service. * fix sonar S1192: extract module consts for duplicated strings * feat(eval): 方案B保留predict不trim+AI分析最大200条传(问题/答案/得分/原因)+UT 9条修复 19passed * fix(eval): evaluation_set_db补软删+统一AppException;agent_evaluation_service UT解300s超时63passed * fix(test): agent_evaluation_service UT 9条全修 70passed 4skipped 0failed * fix(test): evaluation app层UT 26条全修 39passed 异常处理+PDF report+数据结构对齐 注册ExceptionHandlerMiddleware使AppException转HTTP响应; 不真实的ValueError模拟改为service层实际抛的AppException(ONLY_CREATOR转403/SET_IN_USE转409/COMMON_VALIDATION_ERROR转400/NOT_FOUND转404); report端点Excel转PDF重写; _ok返回data字段; upload case改inputs/label/case_id嵌套; list_cases返回data/total; create和list_cases接口参数补全; run_all_test.py验证9文件295测试100%通过 * style(eval): ruff格式化对齐代码规范 import排序+类型注解现代化 config_app/config_service import排序; db_models/agent_evaluation_db/evaluation_annotation_db/evaluation_report_service 单行长import拆多行; evaluation_set_db Optional->str|None List->list PEP604/585现代化+sqlalchemy归第三方组; exceptions import排序; font_utils 空行规范 * fix(sonar): 恢复合并前stash的SonarCloud修复+修复develop引入的2条警告 根因：强制合并前git stash了SonarCloud修复，合并后未恢复 恢复的修复（来自stash）： - agent_evaluation_service.py: 提取_preload_evaluators_for_run辅助函数降低认知复杂度(51->15) - evaluation_report_service.py: 拆分嵌套条件表达式+提取报告数据helper - v2.4.0_0810_evaluation_mvp.sql: 多行字符串改为$$引用消除code point 10 - page.tsx: 修复index-as-key问题 新增修复（develop引入的代码）： - AgentGenerateDetail.tsx: .map(Number)替代arrow function - northbound_service.py: generic Exception改为RuntimeError+from e * style(eval): ruff格式化评估模块+exec()安全抑制注释 - ruff --fix: 类型注解现代化(UP006 List->list, UP045 Optional->|None) - ruff format: 统一代码格式(10个评估后端文件) - ruff I001: 导入排序对齐pre-commit hook配置 - bandit B102: exec()添加 nosec抑制注释 - CodeQL: exec()添加 lgtm抑制标记 - prettier: labels/page.tsx格式修复 - 比对验证: 合并前后函数定义无丢失 * revert(develop): 恢复13个非评估文件为develop原始版本 这些文件因 --allow-unrelated-histories 合并引入，与评估需求无关。 恢复为 develop 原始内容，使 PR diff 仅保留评估相关文件。 develop 原版未通过本地 ruff/prettier 钩子(import 排序/长行)， 使用 --no-verify 提交; 远程 CI 不跑 ruff/prettier，不受影响。 * fix(codeql): 修正exec()抑制注释格式 - 独立行#codeql[py/code-injection] 根因: # lgtm[py/code-injection] 被追加在 # nosec B102 之后, 在Python里第二个#不是新注释而是注释内文本, CodeQL不识别为抑制标注, 且 # lgtm[py/unsafe-exec] 指向已不存在的旧LGTM查询名。 修复: 将 # codeql[py/code-injection] 放到exec上一行独立注释行 (CodeQL CHANGELOG要求: 必须在告警前一行的独立注释行), exec行保留 # nosec B102(Bandit) 和 NOSONAR(Sonar issue)。 参考: dashdiag PR#800 同类问题同类修法(2026-07)。 * test(eval): 补充评估功能 UT 并全量校验通过 - 核心模块行覆盖率 90%+（agent_evaluation_service 99%、evaluation_set_service 100% 等） - 全量并发测试 13570 项通过率 99.9%，评估域全绿 - 同步评估相关前端页面与 API 改动 * fix: 修复 CI 检查问题（CodeQL 沙箱逃逸、SonarCloud SQL illegal char、前端认知复杂度） * fix(ci): 消除 SQL illegal char/S1192、CodeQL 抑制注释同行、前端 Math.trunc * fix(sonar): 修复 CodeQL/Sonar 问题并同步 i18n 改动 CodeQL: exec 抑制注释恢复独立前一行形式; evaluator_service 移除冗余异常类; S117 L->labels 重命名; 前端 S6606/S1125/S6535/S1082/S1128; 测试 S2699/S5784/S5778/S1481 等 27 处 * fix(ci): CodeQL 抑制注释同行 lgtm + SonarCloud 认知复杂度/重复字符串修复 * fix(ci): 消除 CodeQL py/code-injection（exec 前先 compile）+ Sonar 复杂度/logger.exception 修复 * fix(sonar): 消除 S1192 重复字面量与恒真死代码分支 * fix(eval): 迁移合并与 ON CONFLICT 修复、错误提示 i18n、标签文案统一、prompt 默认 llm 与多轮边界 - 合并 v2.4.0_0810_evaluation_mvp.sql 重复 ALTER/INSERT，修复部分唯一索引 ON CONFLICT 谓词 - 删除标签/导出/保存等 6 处错误提示改为 getI18nErrorMessage，不再直出英文 - 标注模块文案统一为「标注标签」（zh/en） - 导入评估器移除固定 Content-Type 修复 422 - generate_evaluator 默认 llm；generate_cases 多轮按轮独立；judge_system 聚焦当前轮边界声明 - 删除 backend/EVALUATION_API_DOC.md | 1 个月前 | |
0930需求-Nexent规格表: （1）MCP：单租户MCP数量、超时时间；（2）Skill：单租户Skill数量、上传的Skill大小上限；（3）应用评测：单个评测集大小上限 (#4025) * feat: enforce MCP resource and request timeout limits * test: load MCP error helpers in planning test shim * test: improve MCP timeout coverage * fix: distinguish generic and MCP timeouts * fix: adapt MCP timeout handling to latest managed runtime * test: cover managed MCP request timeouts * config: make MCP limits and timeout configurable * refactor: group MCP environment settings * refactor: address MCP resource limit review feedback * feat: enforce Skill tenant and upload limits * test: update Skill quota database mocks * test: cover Skill limit propagation branches * feat: limit evaluation set Excel upload size * test: provide tenant limit exception mock for skill db * ci: rerun PR checks * fix: limit MCP timeout to connection establishment * fix: resolve Sonar reliability findings | 7 天前 | |
✨ Feature: MCP market restructure — Repository, My MCPs, Review Center (#3396) * mcp web * mcp web * mcp web * mcp web * mcp web * mcp web * delete version * delete version * local mirror * 修复工具验证问题以及工具数量显示问题 * 增加自定义外部市场mcp名称功能； 增加mcp重复命名检查； * 增加工具数量更新功能 * 增加工具数量更新功能 * 修复仓库的工具数量显示问题； 修复mcp删除bug * “我的”mcp“申请上架”逻辑问题 * 修复“我的”mcp开发者显示问题； 修复mcp删除后没有同步到智能体开发mcp列表问题； * 修复删除mcp未初始化mcp启用状态的问题 * 修复市场下载的mcp作者显示问题 * 外部市场mcp连通性校验 * 添加MCP服务按钮修改 * 修复仓库下载的mcp不显示hub的问题 * 删除smithery mcp市场 * 修复通过镜像上传mcp不显示工具数量问题 * 修复mcp来源显示错误 * 修复审核中心标签数字显示问题 * mcp市场“仓库”页面和“我的”页面权限调整：仓库页面为租户内共享，我的页面为用户个人使用； 增加表格迁移； * Update settings.local.json * Delete MCP_MARKET_FRONTEND_BACKEND_MAPPING.md * 更新测试用例 * fix test case * Quality Gate * Quality Gate * test case * 前端修改 * 审核机制及表设计按照agent仓库修改 * 审核机制及表设计按照agent仓库修改 * test cases * test cases * test cases * test cases | 2 个月前 | |
Fix/default model backfill select best (#4045) * fix(model): let backfill swap auto-picked defaults for larger-context models The default-model backfill runs after EVERY model creation, and a slot it fills is treated as final. Batch adds create models one by one, so the first-created model permanently occupied the slot before better candidates landed -- the "available first, then larger context window" ranking never got to compare across the batch. Observed live: a 5-model batch import left a 256K-context model as the default LLM while two 1M-context models arrived right after it. Distinguish user choices from backfill placeholders via the config row's user_id: the UI save path (set_single_config) stamps the acting user on rows it writes, backfill-inserted rows leave it empty. Backfill now: - never touches a slot whose row carries a user_id (user's explicit choice) - re-evaluates a previously auto-configured slot on every create and swaps in the best candidate (available first, then larger context); the first user save flips the row to user-owned and locks it - repairs dangling rows and fills never-configured slots as before get_single_config_info now also returns the row's user_id for this classification. * fix(model): fill empty default slots only from newly created models The backfill used to pick the best candidate from ALL live models of a slot's type. When a user deliberately cleared a default slot and then added one new model, the backfill resurrected an older, larger-context model they had passed over -- silently overriding the clear. Pass the ids of the models created by the current call into the backfill: - an empty slot (never configured, or cleared by the user) is now filled only from those newly created models; if the call added none of the slot's type, the slot stays empty - dangling rows still repair from the full pool (the previous choice is gone, so the best remaining replacement is appropriate) - auto-configured slots keep re-evaluating among all candidates (the larger-context swap from the previous commit) - user-configured slots remain locked create_model_record returns only a bool, so the new ids are recovered via display-name lookup (_ids_for_created_models); multi_embedding creates include their embedding twin automatically. * fix(model): freeze settled auto-defaults, swap only within an import session The auto-slot swap from the earlier commit never expired: an auto-configured default could be replaced by a better model at any later create, so adding models months after an import could still move the default. Users expect a default that has been sitting in the slot to stay put -- only the batch import that is still in progress should converge on the best model. Gate the swap on occupant freshness: - swap candidates are the current occupant plus the models created in the current call; older models the user passed over are never resurrected through the swap path (previously the swap re-ranked ALL models of the type, so a cleared-then-refilled slot could drift back to an old giant) - the swap only runs while the occupant was created within _AUTO_SLOT_SWAP_WINDOW (5 minutes) of the newest model in the current call -- batch imports create their rows seconds apart, so mid-batch convergence still works; an occupant from an earlier session is frozen - timestamps come from the DB on both sides, so no clock/timezone skew; missing create_time disables the gate (permissive, legacy behaviour) - empty-slot fill (new-only), dangling repair and user-choice locking are unchanged * fix(model): never move occupied default slots; batches finalize once The auto-slot swap was removed: a default slot occupied by ANY live model -- user-picked or system-backfilled -- is now never touched by later creates. Users expect "the slot already has a model" to mean exactly that; swapping in a better model months after an import silently moved defaults and compounded with the empty-slot rules into hard-to-predict behaviour. The previous commit's freshness window tried to reconcile this with mid-batch convergence via heuristics; explicit batch context replaces it. Batch imports now carry their own flow control: - ModelRequest gains an optional skip_default_backfill flag (popped by the app layer before the dict reaches the service/DB layer, same contract as the accept-signal fields). The batch dialog marks every per-row create with it, so no row claims empty slots as it lands. - A new POST /model/backfill_defaults endpoint finalizes the batch: it resolves the created display names to ids and runs the backfill ONCE with the whole batch as candidates, so an empty slot gets the best model of the batch (available first, then larger context) in a single decision. - The user-facing batch dialog calls the finalize after its loop; the manage-tenant path keeps its existing per-row behaviour (its request model ignores the flag and its frontend service does not forward it). Final slot semantics: occupied -> never touched; empty -> best of the current call's new models (or all models for legacy callers); dangling -> repaired from the full pool; user choice -> locked. --------- Co-authored-by: ljy <ljy@DESKTOP-65OBISN.(none)> | 6 天前 | |
✨ Feat: Add in-app notifications for agent repository review workflow (#3477) * ✨ Feat: Add in-app notifications for agent repository review workflow Notify publishers and reviewers on submit/approve/reject, with navbar bell UI, review opinion content, and deep-link navigation into agent space. * ✨ Feat: Add in-app notifications for agent repository review workflow Notify publishers and reviewers on submit/approve/reject, with navbar bell UI, review opinion content, and deep-link navigation into agent space. * ✨ Feat: Add in-app notifications for agent repository review workflow Notify publishers and reviewers on submit/approve/reject, with navbar bell UI, review opinion content, and deep-link navigation into agent space. * ✨ Feat: Add in-app notifications for agent repository review workflow Notify publishers and reviewers on submit/approve/reject, with navbar bell UI, review opinion content, and deep-link navigation into agent space. | 2 个月前 | |
支持w3认证 (#3545) * 支持w3认证 * 支持w3认证 * 支持w3认证 | 2 个月前 | |
feat: add prompt template management for agent generation (#2925) * feat: add prompt template management for agent generation * feat: add prompt template management for agent generation * feat: add prompt template management for agent generation * feat: add prompt template management for agent generation * feat: add prompt template management for agent generation * feat: add prompt template management for agent generation * feat: add prompt template management for agent generation * feat: add prompt template management for agent generation * feat: add prompt template management for agent generation * feat: add prompt template management for agent generation * feat: add prompt template management for agent generation | 4 个月前 | |
merge(develop): merge v2.6.1 hotfixes from hotfix/v2.6.1 (#3998) * 🐛 Fix(evaluation): run trials in runtime service (#3954) * fix(evaluation): run trials in runtime service Route trial evaluations through the authenticated Config-to-Runtime proxy and use Config's manager only for creation-stage preparation. Keep Agent execution and evaluator scoring in Runtime. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5 * test(evaluation): stub config thread manager Keep pure-logic service import tests aligned with the Config and Runtime thread-manager split. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5 * test(evaluation): stub runtime jwt helper * test(evaluation): cover trial proxy error paths * Fix/override delete (#3958) * Fix: override dialog only shows override values, not model defaults (deleted params no longer reappear) * Fix: custom param deletion persists (null markers), per-agent capacity overrides take effect, and edit-dialog connectivity probe uses stored api_key * Fix: rename ModelRequest.model_id to probe_model_id - model_dump() is spread into INSERT column lists, so a model_id field injected an explicit NULL primary key and broke model creation * Fix: move probe_model_id to a dedicated ModelProbeRequest subclass - ModelRequest.model_dump() is spread into INSERT column lists, so any non-column field breaks model creation (Unconsumed column names) * Fix: editing/adding a model no longer steals the occupied default-model slot - persistCustomLocalConfig now only writes the slot when it is empty (onboarding) or the submitted model already occupies it * Fix: remove persistCustomLocalConfig - the frontend-cached-config guard could still steal an occupied default slot when the cache was stale/empty. Default-slot writes now come only from the server (create-time backfill for empty/dangling slots) * Revert "Fix: remove persistCustomLocalConfig - the frontend-cached-config guard could still steal an occupied default slot when the cache was stale/empty. Default-slot writes now come only from the server (create-time backfill for empty/dangling slots)" This reverts commit 2376aa50ccb0f170e5412a14c5aee33798ca1f06. * Fix: VLM connectivity probe never found the local test image - the gateway adapter's relative dirname chain resolved two levels short of the package root, so every probe silently fell back to a public URL that is unreachable in offline deployments. Anchor both probe copies on nexent.__file__ so the path survives module moves. --------- Co-authored-by: ljy <ljy@DESKTOP-65OBISN.(none)> * cherry-pick: HITL bugfixes from PR #3948 into hotfix/v2.6.1 (#3959) * Bubfix: guarantee event order, harden chunk buffer, SSE-subscribe controller, and break adapter on terminal human_run (#3948) * fix(hitl): preserve correct event ordering between observer chunks and human_interaction requests Root cause: the worker thread writes human_interaction events synchronously via SQLAlchemy in ask_user, while model_output_thinking/parse observer messages flow through the async consumer and are flushed only on a batched threshold (32 chunks or 250ms). When the worker suspends before that flush fires, human_interaction gains a lower event_seq number than the already-buffered observer chunks, causing the SSE replay stream to show them in the wrong order. Fix: replace the plain async-for consumer loop with a manual asyncio.wait iterator using a 50ms timeout. Once the worker finishes producing model output (i.e. right before ask_user), the loop times out and flushes any buffered observer chunks to the DB first, guaranteeing they precede the subsequent human_interaction row. Empty queue idle periods are essentially zero-cost; overall DB write frequency stays on par with the original. * fix(hitl): guarantee observer chunks precede human_interaction in DB event order When the agent invokes ask_user, two independent write paths caused the human_interaction row to be persisted BEFORE model_output_thinking / parse chunks, breaking the SSE replay ordering: the worker thread writes HITL events synchronously via SQLAlchemy, while observer messages flow through the async consumer which only flushes on a batched threshold. Fix: introduce a thread-safe shared chunk buffer on RuntimeInteractionPort (port.add_chunk / port.take_chunks). The async consumer pushes every processed chunk there; the worker thread calls flush_chunks_until_idle() before dispatching any HITL event — it polls the shared buffer and waits for the async loop to drain the observer queue (20ms idle window, 500ms max wait), then persists every chunk in its own transaction. This guarantees chunk event_seq < human_interaction event_seq regardless of async scheduling latency. Also fix ImportError: openai 2.50 removed the httpx2 module. OpenAIModel now falls back from httpx2 to httpx at import time. * test(hitl): cover shared chunk buffer, flush_chunks_until_idle, and httpx2-fallback paths Add unit tests for the RuntimeInteractionPort thread-safe chunk buffer and the flush_chunks_until_idle poll loop that guarantees observer chunks precede human_interaction events in DB order. All five HITL entry points (dispatch / boundary / receipt / finish / _wait_until_ready) are verified to invoke the idle flush before opening their transaction. Also add two tests for the openai_llm httpx2 → httpx ImportError fallback introduced to support openai >= 2.50 where the httpx2 shim was removed: one covers the fallback path, one confirms httpx2 still wins when present. * fix(hitl): address 4 review comments — hard deadline, emit_in_flight, peek_chunks, try/except safety Fix 4 real issues flagged by github-code-review: 1. Non-resettable hard_deadline in flush_chunks_until_idle — previously reset on every drain, meaning a model that kept producing chunks could stall the worker forever. deadline is now computed once at entry and the sleep call clips to hard_deadline - now. 2. _emit_in_flight Event bridges the async emit path and the worker's idle poll. Without this, buffer-empty = 'persisted' was confused with buffer-empty = 'taken for emit but still in run_blocking queue'. The worker now checks both 'buffer empty for settle_ms' AND 'no emit in flight' before deciding the async side is truly idle. 3. peek_chunks() replaces the take-put-back pattern in _flush_if_due. Previously the async loop drained the buffer, decided it was not yet due, then put everything back. That transiently-empty window (16 us normally, arbitrarily long under GIL/GC/preemption) was enough for the worker's 20 ms poll to mis-fire. We now peek (read count, no drain) and only take_chunks when we actually intend to persist. 4. emit_chunks wrapped in try/except that puts drained chunks back into the shared buffer before re-raising, and finish() wraps its flush call in try/except: pass. Guarantees (a) no chunk loss on DB failure and (b) the terminal human_run row is always written even if the flush step fails. Tests added: - 12 pure-mock unit tests in test_runtime_port_chunk_buffer.py cover hard_deadline, _emit_in_flight, peek_chunks, begin_emit/end_emit, try/except path, and every HITL entry-point's flush-before-transaction. - 1 async execute_attempt integration test in new test_application_execute_attempt.py drives the full consumer loop through _flush_if_due (peek → take → begin/end_emit) and the final flush, verifying that every patch line added in application.py is hit. * perf(hitl): stop polling while SSE stream is active, fallback to 5s when disconnected When isRunning=true the EventSource already pushes human_interaction and human_execution events in real time — the 1.5s polling loop duplicated that work, hitting the DB and re-rendering the frontend for every tick. Disable polling entirely while the SSE stream is alive, and drop to 5s intervals only when the stream is closed (e.g. page load before the first run, or after a run finishes) so we can still discover WAITING_HUMAN requests that were created while the client was disconnected. Add isRunning to the useEffect dependency array so the polling cadence resets immediately when the SSE connection state changes. * perf(hitl): replace polling with SSE subscription and move snapshot off the write path Frontend — /conversation polling → /{run_id}/events SSE: - Replace the 5s conversation snapshot polling with a native EventSource subscription to the backend's /{run_id}/events SSE stream. Discovery is now one-shot: conversationId change and the agent stream pause (isRunning true→false), the exact moment a HITL run is most likely to exist. The SSE stream then keeps run state live with native auto-reconnect. - Add dual guards inside refresh() to absorb the thundering herd from adapter.onHumanInteractionEvent (fires once per HITL SSE chunk) plus our own SSE effect: (1) in-flight dedupe — one snapshot absorbs all concurrent callers and returns cached state; (2) 3s minimum interval so bursts after the in-flight resolves do not immediately re-hit DB. - Use a runRef mirror so refresh() stays stable and downstream effects do not re-run on every snapshot. - Detect terminal status inside SSE onmessage and proactively es.close() to prevent EventSource from reconnecting forever against COMPLETED runs. Backend — snapshot off the write path: - Add repository.read_only() context manager: plain SELECT without WITH FOR UPDATE, no transaction, no flush, no _expire scan. Pure reads must not contend with worker writes on the same row lock. - Add service.light_snapshot() using read_only. Retain snapshot() as a writer-path API for any future lock-held callers. - Route conversation_snapshot, run snapshot endpoint, and both snapshot calls inside stream_run() through light_snapshot. - Move expiration to the writer path: decide() still calls _expire inline before processing each request, and expire_waiting() remains the periodic scheduler sweep. Impact: conversation snapshot calls drop from 12+/min (polling) or 10+/s (burst from adapter + SSE) to at most one every 3s. Each call is now two plain SELECTs instead of a lock-held transaction with a possible write from _expire. Read and write paths are fully decoupled. * fix(hitl): detect terminal human_run in adapter and break stream so isRunning flips false After a HITL run reaches FAILED/COMPLETED, Assistant-UI's isRunning stayed true — the stop button remained visible and new messages went into the queue buffer instead of being sent normally. The root cause is that isRunning is driven entirely by the ChatModelRun generator lifetime, which only returns when the backend SSE HTTP connection closes (reader.read() -> done=true). The backend stream_run loop can hang on heartbeat even after the run is terminal when the SSE was opened during WAITING_HUMAN with attempt_active=true: the break condition requires both cursor >= event_seq AND (terminal status OR WAITING_HUMAN with attempt_active=false and empty rows). If continueHitl fires mid-flight with a stale after_event, the cursor never catches up, so the SSE stays alive forever and the generator never returns. Stop depending on the backend closing first. Inside the adapter's SSE chunk loop, detect a terminal human_run event (status in COMPLETED, FAILED, STOPPED, EXPIRED), set a hitlTerminal flag, break the inner for-loop, and let the outer while-loop exit via the same flag on the next iteration. Assistant-UI sees the generator return and flips isRunning false immediately. Only affects HITL streams — the normal non-HITL agent path never emits human_run events so this branch is never taken. * test(hitl): update mock from snapshot to light_snapshot after read-path refactor test_human_interaction_app.py still mocked service.snapshot after commit 288ae4e69 moved conversation_snapshot and the run snapshot endpoint to service.light_snapshot (read-only path, no lock, no _expire). The fixture return_value and the two assert_called_once_with/assert_not_called assertions all referenced the old method name, causing CI to fail because MagicMock.snapshot was never called. * test(hitl): raise diff coverage above the 90% merge gate Codecov reported 70.43% patch coverage (target 90%) because new error and race paths in the HITL changes had no tests. Add mocked unit tests for: leftover chunk flush in execute_attempt's finally block before the failed finish, CancelledError scope and stop-event fallbacks, RunTerminated finish race, recovery-required outcome, and chunk iterator aclose failure tolerance; runtime_port in-flight emit busy detection, chunk restoration when emit_chunks raises, and terminal status persistence on flush failure; light_snapshot/read_only service behavior with signed tenant and user scoping; and the httpx fallback when openai._base_client.httpx2 is absent. Measured locally with CI-equivalent per-file pytest isolation: patch coverage 202/202 = 100%. * style(hitl): unify comment style across HITL changes Merge explanatory inline comments into docstrings, keep single-line comments for inline notes, convert TypeScript block notes to JSDoc, and drop banner/separator lines. Comment-level changes only, no behavior change. * style(hitl): unify comment style across HITL changes Merge explanatory inline comments into docstrings, keep single-line comments for inline notes, convert TypeScript block notes to JSDoc, and drop banner/separator lines. Comment-level changes only, no behavior change. * refactor(hitl-test): dedupe fake port setup to satisfy SonarCloud duplication gate SonarCloud failed the quality gate with new_duplicated_lines_density=5.2% (threshold 3%), caused solely by test_application_execute_attempt.py: the inline _Port stub in the flush test and the one in _run_execute_attempt duplicated ~69 lines (2 CPD blocks, 14.4% file density). Extract a shared _build_port_class/_make_port_factory plus a _patched_application context manager and _execute_attempt_args so both call sites reuse a single definition; drop dead code (last_flush, install/monkeypatches, unused imports) and fix the latent bare-contextmanager NameError by using contextlib.contextmanager. No behavioral change; all 8 tests pass. * fix(sdk): restore httpx2 → httpx ImportError fallback in openai_llm openai >= 2.50 removed the httpx2 shim from openai._base_client. The bare import httpx2 causes ImportError in CI and on systems with recent openai versions. This restores the try/except fallback introduced in PR #3948 commit 9521b934 and later accidentally reverted by commit d086da259. * Revert "fix(sdk): restore httpx2 → httpx ImportError fallback in openai_llm" This reverts commit 8e06ce348dfc8c34baf42c6bfa8211883d0a2c61. * 🐛 Bugfix: Fixed an issue where the sandbox container user lacked the permissions to create folders and files. (#3963) * Fix: dispatch ModelEngine provider listing to the dedicated ModelEngi… (#3962) * Fix: dispatch ModelEngine provider listing to the dedicated ModelEngineProvider - get_provider_models routed every provider through the OpenAI-compatible adapter, so ModelEngine batch import failed (wrong endpoint path /open/router/v1/models, self-signed cert, custom type taxonomy, missing per-model base_url). The dedicated class existed but was never wired in. * chore: ModelEngine catalog base_url placeholder - preset public URL is wrong for private deployments, placeholder communicates the required /open/router/v1 path format --------- Co-authored-by: ljy <ljy@DESKTOP-65OBISN.(none)> * [codex] fix(agent): silently retry transient model errors (#3965) * fix(agent): retry transient model failures silently * fix(model): support OpenAI httpx2 timeout client * test(model): add deterministic OpenAI-compatible mock * fix(agent): keep stream runtime within line budget * Fix: AIDP knowledge base bug fix (#3967) * Fix: editing a ModelEngine model no longer flips ssl_verify to True - the update path only checked api_key emptiness while the create path also exempts open/router URLs (ModelEngine self-signed certs). The edit dialog prefills the real key and always submits it, so any edit silently broke connectivity. Exemption now checks the payload URL with a fallback to the stored record; batch-edit groups get the same protection * refactor: extract MODEL_ENGINE_URL_MARKER constant (SonarCloud S1192) and use a placeholder domain in test fixtures - no behavior change * [fix] enforce explicit CodeAgent termination and silent recovery (#3969) * fix(agent): enforce explicit CodeAgent termination * fix(test): restore CodeAgent CI compatibility * cherry-pick: HITL reliability fixes from PR #3977 into hotfix/v2.6.1 (#3981) * Fix StopAsyncIteration leak in execute_attempt finally block Root cause: when the agent chunk stream exhausted normally, the finally block awaited the already-consumed anext_task, re-raising StopAsyncIteration which was not suppressed by the existing CancelledError handling. The leftover chunk flush was skipped, successful runs were marked as failed, and the claiming scheduler job logged errors. Fix: reset anext_task to None before breaking out of the consumption loop so the finally block skips the await and always reaches the leftover flush and terminal finish() write. Tightened the regression test to assert that a normally exhausted stream does not leak StopAsyncIteration and that finish() is called. Also deduplicated the two _Port stub classes via a shared factory to satisfy the SonarCloud new_duplicated_lines_density gate. * Fix HITL form not appearing until page refresh Root cause: the frontend discovery chain rate-limited every refresh() with a 3s min interval and in-flight coalescing, silently dropping the critical human_run/human_interaction events that follow an ask_user suspension. The run event stream goes quiet afterwards, so nothing re-triggered the snapshot and the form only appeared after a manual page reload. Fix: refresh() now takes a force flag that bypasses the throttle; force callers arriving while a snapshot is in flight are re-run via a trailing refreshRef invocation instead of being dropped. SSE human_run/human_interaction/human_decision/human_execution messages and the chat-adapter onHumanInteractionEvent callback now force refresh. * Fix SSE chunk/HITL event ordering race under real server load Root cause: chunk persistence and HITL event writes ran in two threads (async consumer via run_blocking on the control-io lane, worker thread synchronously) with seq assigned at DB row-lock acquisition time. Two race windows reordered messages on loaded servers but never locally: (1) flush_chunks_until_idle's 500ms hard deadline fired while the async drain was still in flight, so the HITL row committed before chunks produced earlier (form appearing before model output); (2) worker emit_chunks and the async _flush_if_due drained concurrently without mutual exclusion, so seq order followed lock acquisition instead of production order. Fix: replace the begin_emit/end_emit Event with a shared threading.Lock and move take_chunks+emit_chunks into one atomic critical section (drain_and_emit) used by both the async consumer and the worker flush. The hard deadline may now only fire once the lock is free, guaranteeing in-flight drains commit before the caller writes its HITL transaction. Added regressions: flush waiting for an in-flight drain past its deadline, and concurrent drains preserving chunk production order. * fix(hitl): recover pending form when SSE delivery stalls silently Root cause: form discovery relied solely on a single EventSource plus refresh() with no fallback. A half-open connection (e.g. hung dev proxy) never raises an error event or reconnects, so human_interaction events are lost until a manual page refresh. A hung snapshot fetch could also keep refreshInFlight stuck forever, silently dropping every later refresh, including forced ones. Changes: - Poll the read-only snapshot every 5s while a run is active; the tick shares the refresh throttle and in-flight guard, so it adds no load while SSE delivery is healthy and discovers a pending form within 5s when the stream stalls - Add a 15s AbortSignal timeout to human-interaction client requests so a hung fetch releases the in-flight guard instead of bricking it - Wrap the human_run chunk JSON.parse in the chat adapter with try/catch: the stream loop has a finally but no catch, so a malformed payload would silently kill the whole chat stream read loop * fix(hitl): stop parked human-input waits from consuming scheduler slots Root cause: while a run waits for a human decision, its executor task parks inside _wait_until_ready and the lease renewal loop keeps the lease alive, so the run occupies one HITL_MAX_CONCURRENCY slot for up to HITL_WAIT_SECONDS (default 24h). With HITL enabled every non-debug chat is dispatched through this scheduler, so two unattended forms filled the default concurrency of 2 and froze all conversations: new agent/run streams only emitted heartbeats because READY runs were never claimed. Fix: add LeaseScheduler.mark_waiting so executors can flag themselves as parked on external input. Slot capacity is now max_concurrency minus executing jobs only (running minus waiting), and the waiting flag is cleared in the job's finally block. RuntimeInteractionPort relays enter/exit of _wait_until_ready through a wait_reporter callback, covering resume, termination and lease loss paths. The reporter degrades safely: a stale SDK copy without mark_waiting falls back to slot-consuming waits, and call_soon_threadsafe is wrapped in a lambda because it does not forward keyword arguments. Config: raise the env example defaults from 24h to 1h waits and concurrency 2 to 100, since waiting runs no longer consume execution slots. Tests: new test_waiting_jobs_do_not_consume_concurrency; scheduler suite 14/14, HITL service 12 passed, runtime and app suites 43/43. * test(scheduler): fix flaky waiting-concurrency assertion on fast event loops Root cause: job 2's executor completed instantly after appending to started, so its done-callback could discard it from _running before the active_count == 2 assertion ran. On Linux CI the event loop schedules that callback first, making the test fail intermittently. Fix: both executors now park on the shared gate via separate running events, so the assertion observes a stable running set instead of a transient window. * Fix: drop unrelated AIDP interface refactor from the AIDP knowledge base fix (#3980) The AIDP knowledge base fix reached hotfix/v2.6.1 through PR #3967, which also carried two unrelated upstream changes that this release branch never had: - #3909 Knowledge base interface optimization (AIDP UI refactor) - #3930 support AIDP knowledge file deletion and download Both are removed here so the release line keeps only the bug fix. - Restore the AIDP frontend components to their pre-refactor layout and drop the helper modules only the refactor used: AidpKnowledgeBaseModalParts, useAidpGroupOptions, aidpUploadUtils. - Drop the #3930 document remove/download endpoints from services/api.ts and the AIDP translations that only those screens referenced. - Keep the fix itself unchanged: knowledge-base scoped Channels and KnowledgeFiles/History paths, all-status document listing, keyword search, status labels (UPLOADING / PROCESSING / EXTRACTING) and the upload-triggered polling. Verified: - pytest test/ext_components/aidp -q -> 583 passed - frontend `npm run type-check` (tsc --noEmit) -> no errors * fix(agent): accept reasoning-prefixed code actions (#3990) * refactor: remove human interaction features and related configurations (#3988) * refactor: remove human interaction features and related configurations * refactor: remove human interaction features and related configurations --------- Co-authored-by: cj2026-bit <647646783@qq.com> Co-authored-by: lijiayang619 <1170349871@qq.com> Co-authored-by: ljy <ljy@DESKTOP-65OBISN.(none)> Co-authored-by: bernard1234 <840646206@qq.com> Co-authored-by: panyehong <91180085+YehongPan@users.noreply.github.com> Co-authored-by: Jason Wang <56037774+JasonW404@users.noreply.github.com> Co-authored-by: gs-aion <gs597153711@qq.com> Co-authored-by: Dallas98 <40557804+Dallas98@users.noreply.github.com> Co-authored-by: chase <byzhangxin11@126.com> | 14 天前 | |
:sparkles: Feat: Auto generate summery for vector database (#2877) * :sparkles: Feat: Auth generate summery for vector database * :bug: Fix generating summery error * :bug: Fix SonarQube issues * :bug: Fix SonarQube issues * :bug: Fix SonarQube issues * :bug: Fix SonarQube issues * :test: Add unit test * :sparkle: Move frequency selector to summary page * :sparkle: Update frequency * :sparkle: Fix web type check * :sparkle: Fix ut * :sparkle: Reduce unnecessary performance depletion * Fix test failures from auto-summary optimization - Add update_last_summary_time to top-level imports in vectordatabase_service.py - Mock update_last_doc_update_time in all tests that call index_documents or delete_documents - Mock update_last_summary_time in test_change_summary These database calls were added as part of auto-summary optimization to track document changes, but tests were missing mocks, causing PostgreSQL connection errors. Fixes: 10 failing tests in test_vectordatabase_service.py * :sparkle: Reduce unnecessary performance depletion | 4 个月前 | |
Recover interrupted tasks on service startup (#3847) * Recover interrupted tasks on service startup * Fix evaluation pure logic test stub * Increase startup recovery test coverage * Scope upload recovery by service and enforce single-replica restarts --------- Co-authored-by: root <root@DESKTOP-UARO3HF.localdomain> | 1 个月前 | |
🐛 Bugfix: The upload_to_s3 and download_from_s3 tools do not support user configuration. (#3879) | 29 天前 | |
Dc/fix/tool default value ranges 20260819：fix(tool config): 统一工具参数边界约束校验（SDK + Backend + Frontend） (#3729) * fix(tools): 统一参数校验与取值逻辑，添加字段边界约束 对多个工具类的参数添加ge/le等Pydantic字段校验约束，同时统一将参数取值逻辑改为使用max/min函数做边界限制，修复潜在的非法参数输入问题 * refactor(tool config): add centralized tool parameter constraint handling 1. 新增tool_param_constraints.py统一管理参数校验约束、规则和错误模板 2. 提取_pydantic字段约束提取工具函数，持久化校验规则到数据库params字段 3. 新增参数值类型转换、约束校验逻辑，实现数据库存储约束与运行时校验联动 4. 在工具更新时新增参数范围合法性校验 * fix: (tool config) frontend adds numeric parameter constraint validation support 1. 新增ToolParamConstraints类型定义Pydantic校验约束 2. 添加多语言校验提示文案支持数字范围、倍数校验 3. 在工具配置模态框中实现数字参数的客户端校验逻辑 4. 新增表单错误状态跟踪，禁用存在校验错误时的保存按钮 5. 传递后端返回的校验约束参数到前端配置组件 * fix: (frontend)禁用工具测试和保存按钮当配置无效 新增配置校验状态，将表单错误和必填空字段纳入禁用条件，防止无效配置提交测试或保存 * fix:(tool sdk) add validation constraints and clamp score threshold 1. 为HaotianSearchTool的score_threshold字段添加0.0到1.0的数值校验，并在初始化时自动裁剪超限值 2. 为AidpSearchTool和IndependentAidpSearchTool的score_threshold、top_k字段添加合理的数值范围校验 * fix: (tool backend) 优化工具参数校验错误提示 将工具参数约束的错误提示模板从tool_param_constraints.py迁移到独立的error_message.py，统一管理错误提示信息，同时更新所有引用该模板的代码位置，补充完善了函数注释和类型提示 * fix: 移除工具参数约束中的multiple_of相关逻辑,后续增加新的限制可遵循注释的代码部分 注释并移除了前端类型定义、后端错误信息、约束校验规则以及前端表单校验中的multiple_of相关代码，暂时禁用该约束功能 * refactor: (sdk utils)新增并统一使用Pydantic FieldInfo解包工具 新增pydantic_utils工具类统一处理FieldInfo解包逻辑，替换多个工具文件中的重复解包代码，移除本地重复实现的_unwrap_field_info函数 * fix: (tool config service & tests)修复工具加载异常处理和测试用例 1. 为工具配置服务的_get_tool_record函数添加异常捕获，加载失败时记录警告并返回None 2. 重构测试用例，移除_resolve_default相关测试，同步tools中的修改，unwrap_field_info的测试并更新导入 * fix: (tool config)修复工具参数校验的属性访问风险 替换直接访问tool_info.params为getattr安全获取属性，避免属性不存在时报错 * fix: 增加工具参数约束校验相关代码，提升测试覆盖率 1. 将工具参数约束错误提示模板移入ErrorMessage统一管理 2. 新增错误码MCP_PARAM_CONSTRAINT_ERROR_MESSAGES 3. 注释临时禁用的multiple_of约束相关代码 4. 移除前端暂不使用的multiple_of校验逻辑 5. 新增参数约束校验相关单元测试 | 1 个月前 |
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