| 文件 | 最后提交记录 | 最后更新时间 |
|---|---|---|
✨feat:Add metadata parameter mechanism and fix prompt injection issues (#3738) * feat:新增metadata参数机制，支持对话传参和A2A子智能体传递以及北向接口适配 * bugfix:修复智能体生成提示词误注入知识库描述 * bugfix:去掉initl.sql新增语句 * test:add utest * test::add test * test:add test * test:add test * bugfix:add error message * bugfix:fix error message | 1 个月前 | |
🧪test：add e2e test baseline&fix some bugs (#4065) * test:baseline cases * test:add local test process * doc:add test deploy guide * bugfiix:优化测试流程 * bugfix：修复测试用例 * doc:轻量化bugfix的spec设计和测试用例设计 * test:修复测试用例 * test:修复D1测试用例 * test: 修复 D3 用例脚本并记录失败归因 * test: 移除 D3 变更记录，仅保留测试修复 * fix(test-e2e): make D5 tests portable and isolate evaluation workloads * fix(test-e2e): repair Windows case contracts and D4 journeys * feat(test-e2e): launch repository daily from a pinned branch * test:修复D4读取config问题 * test:修复测试用例，删掉过期用例 * test：修复测试用例 * test:修复测试用例 * doc：测试规范修改 * test：增加外部记忆mock服务 * test：测试用例修复 * fix(prompt): reject blank task descriptions before SSE generation * fix(agent): return 404 for missing discovery resources * fix(agent): validate relationships before update writes * fix(model): preserve provider error status on provider create A provider failure (e.g. an upstream connection_failed) was raised as HTTPException(502) by create_provider_models_for_tenant, but the generic except Exception handlers in the service and the app layer swallowed it and re-wrapped it, so /model/provider/create answered 500 with the real status only surviving as text in the message body (API-049). - service: re-raise HTTPException instead of wrapping it - app: pass HTTPException through on /provider/create and /manage/provider/create - schema: reject a blank provider with 422 at the boundary - tests: regression coverage for both behaviours * fix: correct conversation access and stopped-turn regressions * fix: enforce tenant isolation and edit permissions for agent relations * fix: enforce tenant isolation and edit permissions for agent relations1 * 🐛 Fix tag projection crash on first-attempt ES write failure Problem: project_document_assignments() dereferenced the prior ledger state without a None guard in its generic exception handler. On a document's first-ever projection attempt there is no ledger row yet, so an ES write failure crashed with AttributeError before the failed state was persisted. The failure then became invisible: no retry_count, no next_attempt_at, retry_pending_document_projections() never picked the document up, and tag-filtered retrieval silently ignored the document until its tags were re-saved. Fix: Treat a missing prior state as retry_count 0 in the failure handler ((current or {}).get("retry_count")), so first-attempt failures record a retryable failed state with correct exponential backoff. Added a regression unit test for the no-prior-state failure path (previously only the existing-state path was covered). Also added one blank line after the import block to satisfy the repo ruff pre-commit hook on this file (pre-existing I001). Verification: - test/backend/services/test_tag_document_projection.py 28/28 passed, incl. new test_first_attempt_failure_records_retryable_state - Neighboring regression: test_tag_management_service.py and test_tag_document_batch_status.py, 53/53 passed - ruff (E,F,I,W hook rule set) clean on the touched backend file - Matches the state-machine expectations of e2e case API-AUTO-357B84F01BA6D321 (daily run 2026-10-09) * Fix A2A publication smoke scope and remove Mock dependency * fix(a2a): execute the version recorded by A2A publication * [WIP] Fix accepted semantic repair stream commits (#4057) * feat(audit): add security audit logging to backend management APIs (#4055) * feat: 为模型管理接口添加安全审计日志记录 实现了模型创建、更新、删除、批量操作等接口的安全审计日志功能，过滤了敏感凭证信息，确保审计日志安全合规。新增了审计安全字段过滤工具函数，补充了对应的测试用例验证审计日志的正确性和安全性。 * feat: 为多个接口添加安全审计日志记录 为agent和agent_repository相关的API接口添加安全审计事件记录，包括代理更新、图标上传、删除、导出、导入、版本发布/回滚/更新/删除等操作，同时补充对应的测试用例验证审计日志的正确性，确保敏感数据不被记录。 * feat: 为MCP和技能相关接口添加上下文安全审计日志 为tool、mcp、remote_mcp、skill模块的所有关键增删改接口添加安全审计日志，记录操作人、资源信息等关键字段，同时避免记录敏感信息如凭证、密钥等。新增对应的测试用例验证审计日志的正确性，确保敏感数据不会被泄露。 * feat: 添加安全审计日志并限制审计详情列表长度 在多个服务端点添加安全审计日志，记录关键操作信息 同时统一审计详情列表的长度限制为20，防止日志被恶意payload撑爆 * feat: 为配置相关接口添加安全审计日志记录 为 config_sync_app 和 memory_config_app 的配置操作接口添加安全审计事件记录，记录操作人、租户、操作类型和相关字段信息，同时更新测试用例验证审计日志的正确性，确保敏感配置值不被记录。 * test: 为上传测试用例添加 http_request 参数默认值 为测试用例中的 upload_files 调用添加 http_request=None 参数，避免测试时可能出现的未定义错误 * chore: bootstrap semantic repair stream fix draft * fix(agent): commit accepted streamed code action repairs * test(agent): verify repaired streams in deployed runtime and browser * test(agent): clarify deployed repair assertion failures --------- Co-authored-by: charmingchi1 <71816192+charmingchi1@users.noreply.github.com> * fix: repair agent repository e2e cases and API-type MCP health check (#4061) * fix: repair four failing e2e cases (API-086, API-063, PW-MCP-CONTAINER-01, PW-MCP-MARKET-01) * fix: skip MCP protocol handshake for API-type MCP health check * fix(test-e2e): align runtime contracts and strengthen local test diagnostics * fix(test-e2e): reconcile standalone semantic repair tests with formal cases * test:修改workflow * test:修复测试用例 * fix: preserve manual titles and metadata-free A2A calls * test: repair D1-D5 runtime contracts and execution evidence * test: repair daily assertions and remove excluded cases * fix: guard MCP tag refresh and repair daily test isolation * test：修复测试用例 * test:修复测试用例 * test:修复测试用例 --------- Co-authored-by: panyehong <2655992392@qq.com> Co-authored-by: xuyaqist <xuyaqist@gmail.com> Co-authored-by: chase <byzhangxin11@126.com> Co-authored-by: cj2026-bit <647646783@qq.com> Co-authored-by: Jason Wang <56037774+JasonW404@users.noreply.github.com> Co-authored-by: charmingchi1 <71816192+charmingchi1@users.noreply.github.com> Co-authored-by: MoeexT <yuwancumian666@outlook.com> | 5 天前 | |
fix(agent): export filename uses display name + unique copy name suffix (#4064) * fix(agent): export agent with display name as zip filename Use the agent display name (falling back to name) for export zip filenames, and encode Content-Disposition with RFC 5987 so non-ASCII names survive browser downloads. Extract the filename on the frontend from the encoded header. Verified: unit tests for header encoding/parsing and API-level export checks in the local cluster. * fix(agent): generate unique copy name suffix on agent copy * fix(agent): deduplicate agent name on create via update API * test(e2e): cover agent copy unique-name and availability contract Add bugfix record AGENT-COPY-DUP-20261012, update API-058 to the fixed auto-suffix dedup contract, and add D4 journey PW-AGENT-COPY-01 that copies an agent twice through the repository UI and asserts unique identifiers and availability. * test(e2e): assert agent export uses display-name filename Add bugfix record AGENT-EXPORT-NAME-20261012, update API-066 to require the display-name ZIP export path, and extend the D3 scenario to bind a skill before export and assert the RFC 5987 encoded Content-Disposition filename. * test(e2e): parse bare agent list array in copy journey /api/agent/list returns a bare JSON array; the copy journey and the shared page object unwrapped payload.data, so every poll resolved to an empty list and the case failed before its assertions ran. Parse the array first and keep the wrapped shape as a fallback. Also align case.yaml expected_results with the three spec assertions and remap acceptance bindings accordingly. | 4 天前 | |
✨ Feature: Development of Agent Workbench Features (#4010) * ✨ Feature: Development of Agent Workbench Features * ✨ Feature: Development of Agent Workbench Features * ✨ Feature: Development of Agent Workbench Features * 🐛 Bugfix: The upload_to_s3 and download_from_s3 tools do not support user configuration. * feat:add-workbench * 工作台知识库选择依据aidp开关 * feat:工作台前端风格统一优化 * fix(workbench): restore chat modes and tenant model selection * fix(workbench): restore header and system skills * fix(workbench): hide built-in skills from composer * fix(workbench): restore managed agent invocation * fix(workbench): authorize hidden system agent for HITL * fix(workbench): persist creation history and retry branches * test(workbench): align legacy Skill API mocks with creation history * feat(workbench): separate chat entrypoints and refine creation UX * fix: restore workbench attachment reuse and landing layout * feat(workbench): gate workbench with deployment flag * feat(workbench): gate workbench with deployment flag * feat(workbench): Resolved conflicts and fixed an issue where historical sessions became unavailable after deleting and recreating the agent. * feat(workbench): Fix frontend pipeline build issues. * test(workbench): fix unit test isolation * test(workbench): raise patch coverage above threshold * refactor(workbench): consolidate database migration * fix(workbench): align reasoning defaults and skill card actions * test(workbench): use complete Agent fixture for reasoning defaults --------- Co-authored-by: dongjibao2001 <332722455@qq.com> | 23 天前 | |
fix: scheduled tasks display on new chat page (#3515) * feat: implement turn resource handling and selection in agent workflow * feat: implement turn resource handling and selection in agent workflow * feat: add automation proposal parsing and rendering in conversation threads | 2 个月前 | |
🧪test：add e2e test baseline&fix some bugs (#4065) * test:baseline cases * test:add local test process * doc:add test deploy guide * bugfiix:优化测试流程 * bugfix：修复测试用例 * doc:轻量化bugfix的spec设计和测试用例设计 * test:修复测试用例 * test:修复D1测试用例 * test: 修复 D3 用例脚本并记录失败归因 * test: 移除 D3 变更记录，仅保留测试修复 * fix(test-e2e): make D5 tests portable and isolate evaluation workloads * fix(test-e2e): repair Windows case contracts and D4 journeys * feat(test-e2e): launch repository daily from a pinned branch * test:修复D4读取config问题 * test:修复测试用例，删掉过期用例 * test：修复测试用例 * test:修复测试用例 * doc：测试规范修改 * test：增加外部记忆mock服务 * test：测试用例修复 * fix(prompt): reject blank task descriptions before SSE generation * fix(agent): return 404 for missing discovery resources * fix(agent): validate relationships before update writes * fix(model): preserve provider error status on provider create A provider failure (e.g. an upstream connection_failed) was raised as HTTPException(502) by create_provider_models_for_tenant, but the generic except Exception handlers in the service and the app layer swallowed it and re-wrapped it, so /model/provider/create answered 500 with the real status only surviving as text in the message body (API-049). - service: re-raise HTTPException instead of wrapping it - app: pass HTTPException through on /provider/create and /manage/provider/create - schema: reject a blank provider with 422 at the boundary - tests: regression coverage for both behaviours * fix: correct conversation access and stopped-turn regressions * fix: enforce tenant isolation and edit permissions for agent relations * fix: enforce tenant isolation and edit permissions for agent relations1 * 🐛 Fix tag projection crash on first-attempt ES write failure Problem: project_document_assignments() dereferenced the prior ledger state without a None guard in its generic exception handler. On a document's first-ever projection attempt there is no ledger row yet, so an ES write failure crashed with AttributeError before the failed state was persisted. The failure then became invisible: no retry_count, no next_attempt_at, retry_pending_document_projections() never picked the document up, and tag-filtered retrieval silently ignored the document until its tags were re-saved. Fix: Treat a missing prior state as retry_count 0 in the failure handler ((current or {}).get("retry_count")), so first-attempt failures record a retryable failed state with correct exponential backoff. Added a regression unit test for the no-prior-state failure path (previously only the existing-state path was covered). Also added one blank line after the import block to satisfy the repo ruff pre-commit hook on this file (pre-existing I001). Verification: - test/backend/services/test_tag_document_projection.py 28/28 passed, incl. new test_first_attempt_failure_records_retryable_state - Neighboring regression: test_tag_management_service.py and test_tag_document_batch_status.py, 53/53 passed - ruff (E,F,I,W hook rule set) clean on the touched backend file - Matches the state-machine expectations of e2e case API-AUTO-357B84F01BA6D321 (daily run 2026-10-09) * Fix A2A publication smoke scope and remove Mock dependency * fix(a2a): execute the version recorded by A2A publication * [WIP] Fix accepted semantic repair stream commits (#4057) * feat(audit): add security audit logging to backend management APIs (#4055) * feat: 为模型管理接口添加安全审计日志记录 实现了模型创建、更新、删除、批量操作等接口的安全审计日志功能，过滤了敏感凭证信息，确保审计日志安全合规。新增了审计安全字段过滤工具函数，补充了对应的测试用例验证审计日志的正确性和安全性。 * feat: 为多个接口添加安全审计日志记录 为agent和agent_repository相关的API接口添加安全审计事件记录，包括代理更新、图标上传、删除、导出、导入、版本发布/回滚/更新/删除等操作，同时补充对应的测试用例验证审计日志的正确性，确保敏感数据不被记录。 * feat: 为MCP和技能相关接口添加上下文安全审计日志 为tool、mcp、remote_mcp、skill模块的所有关键增删改接口添加安全审计日志，记录操作人、资源信息等关键字段，同时避免记录敏感信息如凭证、密钥等。新增对应的测试用例验证审计日志的正确性，确保敏感数据不会被泄露。 * feat: 添加安全审计日志并限制审计详情列表长度 在多个服务端点添加安全审计日志，记录关键操作信息 同时统一审计详情列表的长度限制为20，防止日志被恶意payload撑爆 * feat: 为配置相关接口添加安全审计日志记录 为 config_sync_app 和 memory_config_app 的配置操作接口添加安全审计事件记录，记录操作人、租户、操作类型和相关字段信息，同时更新测试用例验证审计日志的正确性，确保敏感配置值不被记录。 * test: 为上传测试用例添加 http_request 参数默认值 为测试用例中的 upload_files 调用添加 http_request=None 参数，避免测试时可能出现的未定义错误 * chore: bootstrap semantic repair stream fix draft * fix(agent): commit accepted streamed code action repairs * test(agent): verify repaired streams in deployed runtime and browser * test(agent): clarify deployed repair assertion failures --------- Co-authored-by: charmingchi1 <71816192+charmingchi1@users.noreply.github.com> * fix: repair agent repository e2e cases and API-type MCP health check (#4061) * fix: repair four failing e2e cases (API-086, API-063, PW-MCP-CONTAINER-01, PW-MCP-MARKET-01) * fix: skip MCP protocol handshake for API-type MCP health check * fix(test-e2e): align runtime contracts and strengthen local test diagnostics * fix(test-e2e): reconcile standalone semantic repair tests with formal cases * test:修改workflow * test:修复测试用例 * fix: preserve manual titles and metadata-free A2A calls * test: repair D1-D5 runtime contracts and execution evidence * test: repair daily assertions and remove excluded cases * fix: guard MCP tag refresh and repair daily test isolation * test：修复测试用例 * test:修复测试用例 * test:修复测试用例 --------- Co-authored-by: panyehong <2655992392@qq.com> Co-authored-by: xuyaqist <xuyaqist@gmail.com> Co-authored-by: chase <byzhangxin11@126.com> Co-authored-by: cj2026-bit <647646783@qq.com> Co-authored-by: Jason Wang <56037774+JasonW404@users.noreply.github.com> Co-authored-by: charmingchi1 <71816192+charmingchi1@users.noreply.github.com> Co-authored-by: MoeexT <yuwancumian666@outlook.com> | 5 天前 | |
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> | 25 天前 | |
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> | 25 天前 | |
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> | 25 天前 | |
🧪test：add e2e test baseline&fix some bugs (#4065) * test:baseline cases * test:add local test process * doc:add test deploy guide * bugfiix:优化测试流程 * bugfix：修复测试用例 * doc:轻量化bugfix的spec设计和测试用例设计 * test:修复测试用例 * test:修复D1测试用例 * test: 修复 D3 用例脚本并记录失败归因 * test: 移除 D3 变更记录，仅保留测试修复 * fix(test-e2e): make D5 tests portable and isolate evaluation workloads * fix(test-e2e): repair Windows case contracts and D4 journeys * feat(test-e2e): launch repository daily from a pinned branch * test:修复D4读取config问题 * test:修复测试用例，删掉过期用例 * test：修复测试用例 * test:修复测试用例 * doc：测试规范修改 * test：增加外部记忆mock服务 * test：测试用例修复 * fix(prompt): reject blank task descriptions before SSE generation * fix(agent): return 404 for missing discovery resources * fix(agent): validate relationships before update writes * fix(model): preserve provider error status on provider create A provider failure (e.g. an upstream connection_failed) was raised as HTTPException(502) by create_provider_models_for_tenant, but the generic except Exception handlers in the service and the app layer swallowed it and re-wrapped it, so /model/provider/create answered 500 with the real status only surviving as text in the message body (API-049). - service: re-raise HTTPException instead of wrapping it - app: pass HTTPException through on /provider/create and /manage/provider/create - schema: reject a blank provider with 422 at the boundary - tests: regression coverage for both behaviours * fix: correct conversation access and stopped-turn regressions * fix: enforce tenant isolation and edit permissions for agent relations * fix: enforce tenant isolation and edit permissions for agent relations1 * 🐛 Fix tag projection crash on first-attempt ES write failure Problem: project_document_assignments() dereferenced the prior ledger state without a None guard in its generic exception handler. On a document's first-ever projection attempt there is no ledger row yet, so an ES write failure crashed with AttributeError before the failed state was persisted. The failure then became invisible: no retry_count, no next_attempt_at, retry_pending_document_projections() never picked the document up, and tag-filtered retrieval silently ignored the document until its tags were re-saved. Fix: Treat a missing prior state as retry_count 0 in the failure handler ((current or {}).get("retry_count")), so first-attempt failures record a retryable failed state with correct exponential backoff. Added a regression unit test for the no-prior-state failure path (previously only the existing-state path was covered). Also added one blank line after the import block to satisfy the repo ruff pre-commit hook on this file (pre-existing I001). Verification: - test/backend/services/test_tag_document_projection.py 28/28 passed, incl. new test_first_attempt_failure_records_retryable_state - Neighboring regression: test_tag_management_service.py and test_tag_document_batch_status.py, 53/53 passed - ruff (E,F,I,W hook rule set) clean on the touched backend file - Matches the state-machine expectations of e2e case API-AUTO-357B84F01BA6D321 (daily run 2026-10-09) * Fix A2A publication smoke scope and remove Mock dependency * fix(a2a): execute the version recorded by A2A publication * [WIP] Fix accepted semantic repair stream commits (#4057) * feat(audit): add security audit logging to backend management APIs (#4055) * feat: 为模型管理接口添加安全审计日志记录 实现了模型创建、更新、删除、批量操作等接口的安全审计日志功能，过滤了敏感凭证信息，确保审计日志安全合规。新增了审计安全字段过滤工具函数，补充了对应的测试用例验证审计日志的正确性和安全性。 * feat: 为多个接口添加安全审计日志记录 为agent和agent_repository相关的API接口添加安全审计事件记录，包括代理更新、图标上传、删除、导出、导入、版本发布/回滚/更新/删除等操作，同时补充对应的测试用例验证审计日志的正确性，确保敏感数据不被记录。 * feat: 为MCP和技能相关接口添加上下文安全审计日志 为tool、mcp、remote_mcp、skill模块的所有关键增删改接口添加安全审计日志，记录操作人、资源信息等关键字段，同时避免记录敏感信息如凭证、密钥等。新增对应的测试用例验证审计日志的正确性，确保敏感数据不会被泄露。 * feat: 添加安全审计日志并限制审计详情列表长度 在多个服务端点添加安全审计日志，记录关键操作信息 同时统一审计详情列表的长度限制为20，防止日志被恶意payload撑爆 * feat: 为配置相关接口添加安全审计日志记录 为 config_sync_app 和 memory_config_app 的配置操作接口添加安全审计事件记录，记录操作人、租户、操作类型和相关字段信息，同时更新测试用例验证审计日志的正确性，确保敏感配置值不被记录。 * test: 为上传测试用例添加 http_request 参数默认值 为测试用例中的 upload_files 调用添加 http_request=None 参数，避免测试时可能出现的未定义错误 * chore: bootstrap semantic repair stream fix draft * fix(agent): commit accepted streamed code action repairs * test(agent): verify repaired streams in deployed runtime and browser * test(agent): clarify deployed repair assertion failures --------- Co-authored-by: charmingchi1 <71816192+charmingchi1@users.noreply.github.com> * fix: repair agent repository e2e cases and API-type MCP health check (#4061) * fix: repair four failing e2e cases (API-086, API-063, PW-MCP-CONTAINER-01, PW-MCP-MARKET-01) * fix: skip MCP protocol handshake for API-type MCP health check * fix(test-e2e): align runtime contracts and strengthen local test diagnostics * fix(test-e2e): reconcile standalone semantic repair tests with formal cases * test:修改workflow * test:修复测试用例 * fix: preserve manual titles and metadata-free A2A calls * test: repair D1-D5 runtime contracts and execution evidence * test: repair daily assertions and remove excluded cases * fix: guard MCP tag refresh and repair daily test isolation * test：修复测试用例 * test:修复测试用例 * test:修复测试用例 --------- Co-authored-by: panyehong <2655992392@qq.com> Co-authored-by: xuyaqist <xuyaqist@gmail.com> Co-authored-by: chase <byzhangxin11@126.com> Co-authored-by: cj2026-bit <647646783@qq.com> Co-authored-by: Jason Wang <56037774+JasonW404@users.noreply.github.com> Co-authored-by: charmingchi1 <71816192+charmingchi1@users.noreply.github.com> Co-authored-by: MoeexT <yuwancumian666@outlook.com> | 5 天前 | |
feat(audit): add security audit logging to backend management APIs (#4055) * feat: 为模型管理接口添加安全审计日志记录 实现了模型创建、更新、删除、批量操作等接口的安全审计日志功能，过滤了敏感凭证信息，确保审计日志安全合规。新增了审计安全字段过滤工具函数，补充了对应的测试用例验证审计日志的正确性和安全性。 * feat: 为多个接口添加安全审计日志记录 为agent和agent_repository相关的API接口添加安全审计事件记录，包括代理更新、图标上传、删除、导出、导入、版本发布/回滚/更新/删除等操作，同时补充对应的测试用例验证审计日志的正确性，确保敏感数据不被记录。 * feat: 为MCP和技能相关接口添加上下文安全审计日志 为tool、mcp、remote_mcp、skill模块的所有关键增删改接口添加安全审计日志，记录操作人、资源信息等关键字段，同时避免记录敏感信息如凭证、密钥等。新增对应的测试用例验证审计日志的正确性，确保敏感数据不会被泄露。 * feat: 添加安全审计日志并限制审计详情列表长度 在多个服务端点添加安全审计日志，记录关键操作信息 同时统一审计详情列表的长度限制为20，防止日志被恶意payload撑爆 * feat: 为配置相关接口添加安全审计日志记录 为 config_sync_app 和 memory_config_app 的配置操作接口添加安全审计事件记录，记录操作人、租户、操作类型和相关字段信息，同时更新测试用例验证审计日志的正确性，确保敏感配置值不被记录。 * test: 为上传测试用例添加 http_request 参数默认值 为测试用例中的 upload_files 调用添加 http_request=None 参数，避免测试时可能出现的未定义错误 | 7 天前 | |
🐛 Bugfix: Move AIDP-related synchronous calls to a managed thread to avoid blocking other interfaces. (#4054) | 8 天前 | |
✨ Support api-key management (#3745) * ✨ Support api-key management 🐛 Bugfix: users with dev/user role can only see their api-keys when creating them. * 🧪 Add test files | 1 个月前 | |
feat(logging):Security Audit Logging (#4015) * feat: 添加安全审计服务并在关键操作记录审计日志 新增 audit_service 服务用于记录安全审计事件，在用户注册、登录、登出、密码修改、OAuth/ CAS 相关操作、令牌管理、账户撤销等关键安全操作中记录审计日志，同时新增对应测试用例确保审计功能正常工作。 * feat: 为 API 密钥操作添加上下文安全审计日志 在 API 密钥应用和北向应用中，为刷新、撤销 API 密钥以及批量创建 API 用户等操作添加安全审计日志记录，仅记录非敏感的目标用户信息、操作人信息和请求标识，避免泄露明文 API 密钥。同时新增对应的测试用例验证审计日志的正确性和安全性。 * feat: 为用户、租户、邀请和群组操作添加安全审计日志 在多个API端点（用户、租户、邀请、群组相关的创建、更新、删除等操作）中添加了安全审计日志记录，同时新增了对应的测试用例来验证审计日志的正确性。 | 19 天前 | |
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 | |
0930需求-Nexent规格表：完善租户资源限制错误码、429响应及中英文提示 (#3966) * fix: standardize tenant resource limit errors * fix: roll back rejected tenant user registrations * fix: stabilize tenant limit test imports * test: import HTTPStatus in northbound tests * test: cover tenant resource limit error paths * config: make tenant resource limits configurable | 26 天前 | |
feat(logging):Security Audit Logging (#4015) * feat: 添加安全审计服务并在关键操作记录审计日志 新增 audit_service 服务用于记录安全审计事件，在用户注册、登录、登出、密码修改、OAuth/ CAS 相关操作、令牌管理、账户撤销等关键安全操作中记录审计日志，同时新增对应测试用例确保审计功能正常工作。 * feat: 为 API 密钥操作添加上下文安全审计日志 在 API 密钥应用和北向应用中，为刷新、撤销 API 密钥以及批量创建 API 用户等操作添加安全审计日志记录，仅记录非敏感的目标用户信息、操作人信息和请求标识，避免泄露明文 API 密钥。同时新增对应的测试用例验证审计日志的正确性和安全性。 * feat: 为用户、租户、邀请和群组操作添加安全审计日志 在多个API端点（用户、租户、邀请、群组相关的创建、更新、删除等操作）中添加了安全审计日志记录，同时新增了对应的测试用例来验证审计日志的正确性。 | 19 天前 | |
✨ Feature: Development of Agent Workbench Features (#4010) * ✨ Feature: Development of Agent Workbench Features * ✨ Feature: Development of Agent Workbench Features * ✨ Feature: Development of Agent Workbench Features * 🐛 Bugfix: The upload_to_s3 and download_from_s3 tools do not support user configuration. * feat:add-workbench * 工作台知识库选择依据aidp开关 * feat:工作台前端风格统一优化 * fix(workbench): restore chat modes and tenant model selection * fix(workbench): restore header and system skills * fix(workbench): hide built-in skills from composer * fix(workbench): restore managed agent invocation * fix(workbench): authorize hidden system agent for HITL * fix(workbench): persist creation history and retry branches * test(workbench): align legacy Skill API mocks with creation history * feat(workbench): separate chat entrypoints and refine creation UX * fix: restore workbench attachment reuse and landing layout * feat(workbench): gate workbench with deployment flag * feat(workbench): gate workbench with deployment flag * feat(workbench): Resolved conflicts and fixed an issue where historical sessions became unavailable after deleting and recreating the agent. * feat(workbench): Fix frontend pipeline build issues. * test(workbench): fix unit test isolation * test(workbench): raise patch coverage above threshold * refactor(workbench): consolidate database migration * fix(workbench): align reasoning defaults and skill card actions * test(workbench): use complete Agent fixture for reasoning defaults --------- Co-authored-by: dongjibao2001 <332722455@qq.com> | 23 天前 | |
feat(audit): add security audit logging to backend management APIs (#4055) * feat: 为模型管理接口添加安全审计日志记录 实现了模型创建、更新、删除、批量操作等接口的安全审计日志功能，过滤了敏感凭证信息，确保审计日志安全合规。新增了审计安全字段过滤工具函数，补充了对应的测试用例验证审计日志的正确性和安全性。 * feat: 为多个接口添加安全审计日志记录 为agent和agent_repository相关的API接口添加安全审计事件记录，包括代理更新、图标上传、删除、导出、导入、版本发布/回滚/更新/删除等操作，同时补充对应的测试用例验证审计日志的正确性，确保敏感数据不被记录。 * feat: 为MCP和技能相关接口添加上下文安全审计日志 为tool、mcp、remote_mcp、skill模块的所有关键增删改接口添加安全审计日志，记录操作人、资源信息等关键字段，同时避免记录敏感信息如凭证、密钥等。新增对应的测试用例验证审计日志的正确性，确保敏感数据不会被泄露。 * feat: 添加安全审计日志并限制审计详情列表长度 在多个服务端点添加安全审计日志，记录关键操作信息 同时统一审计详情列表的长度限制为20，防止日志被恶意payload撑爆 * feat: 为配置相关接口添加安全审计日志记录 为 config_sync_app 和 memory_config_app 的配置操作接口添加安全审计事件记录，记录操作人、租户、操作类型和相关字段信息，同时更新测试用例验证审计日志的正确性，确保敏感配置值不被记录。 * test: 为上传测试用例添加 http_request 参数默认值 为测试用例中的 upload_files 调用添加 http_request=None 参数，避免测试时可能出现的未定义错误 | 7 天前 | |
🧪test：add e2e test baseline&fix some bugs (#4065) * test:baseline cases * test:add local test process * doc:add test deploy guide * bugfiix:优化测试流程 * bugfix：修复测试用例 * doc:轻量化bugfix的spec设计和测试用例设计 * test:修复测试用例 * test:修复D1测试用例 * test: 修复 D3 用例脚本并记录失败归因 * test: 移除 D3 变更记录，仅保留测试修复 * fix(test-e2e): make D5 tests portable and isolate evaluation workloads * fix(test-e2e): repair Windows case contracts and D4 journeys * feat(test-e2e): launch repository daily from a pinned branch * test:修复D4读取config问题 * test:修复测试用例，删掉过期用例 * test：修复测试用例 * test:修复测试用例 * doc：测试规范修改 * test：增加外部记忆mock服务 * test：测试用例修复 * fix(prompt): reject blank task descriptions before SSE generation * fix(agent): return 404 for missing discovery resources * fix(agent): validate relationships before update writes * fix(model): preserve provider error status on provider create A provider failure (e.g. an upstream connection_failed) was raised as HTTPException(502) by create_provider_models_for_tenant, but the generic except Exception handlers in the service and the app layer swallowed it and re-wrapped it, so /model/provider/create answered 500 with the real status only surviving as text in the message body (API-049). - service: re-raise HTTPException instead of wrapping it - app: pass HTTPException through on /provider/create and /manage/provider/create - schema: reject a blank provider with 422 at the boundary - tests: regression coverage for both behaviours * fix: correct conversation access and stopped-turn regressions * fix: enforce tenant isolation and edit permissions for agent relations * fix: enforce tenant isolation and edit permissions for agent relations1 * 🐛 Fix tag projection crash on first-attempt ES write failure Problem: project_document_assignments() dereferenced the prior ledger state without a None guard in its generic exception handler. On a document's first-ever projection attempt there is no ledger row yet, so an ES write failure crashed with AttributeError before the failed state was persisted. The failure then became invisible: no retry_count, no next_attempt_at, retry_pending_document_projections() never picked the document up, and tag-filtered retrieval silently ignored the document until its tags were re-saved. Fix: Treat a missing prior state as retry_count 0 in the failure handler ((current or {}).get("retry_count")), so first-attempt failures record a retryable failed state with correct exponential backoff. Added a regression unit test for the no-prior-state failure path (previously only the existing-state path was covered). Also added one blank line after the import block to satisfy the repo ruff pre-commit hook on this file (pre-existing I001). Verification: - test/backend/services/test_tag_document_projection.py 28/28 passed, incl. new test_first_attempt_failure_records_retryable_state - Neighboring regression: test_tag_management_service.py and test_tag_document_batch_status.py, 53/53 passed - ruff (E,F,I,W hook rule set) clean on the touched backend file - Matches the state-machine expectations of e2e case API-AUTO-357B84F01BA6D321 (daily run 2026-10-09) * Fix A2A publication smoke scope and remove Mock dependency * fix(a2a): execute the version recorded by A2A publication * [WIP] Fix accepted semantic repair stream commits (#4057) * feat(audit): add security audit logging to backend management APIs (#4055) * feat: 为模型管理接口添加安全审计日志记录 实现了模型创建、更新、删除、批量操作等接口的安全审计日志功能，过滤了敏感凭证信息，确保审计日志安全合规。新增了审计安全字段过滤工具函数，补充了对应的测试用例验证审计日志的正确性和安全性。 * feat: 为多个接口添加安全审计日志记录 为agent和agent_repository相关的API接口添加安全审计事件记录，包括代理更新、图标上传、删除、导出、导入、版本发布/回滚/更新/删除等操作，同时补充对应的测试用例验证审计日志的正确性，确保敏感数据不被记录。 * feat: 为MCP和技能相关接口添加上下文安全审计日志 为tool、mcp、remote_mcp、skill模块的所有关键增删改接口添加安全审计日志，记录操作人、资源信息等关键字段，同时避免记录敏感信息如凭证、密钥等。新增对应的测试用例验证审计日志的正确性，确保敏感数据不会被泄露。 * feat: 添加安全审计日志并限制审计详情列表长度 在多个服务端点添加安全审计日志，记录关键操作信息 同时统一审计详情列表的长度限制为20，防止日志被恶意payload撑爆 * feat: 为配置相关接口添加安全审计日志记录 为 config_sync_app 和 memory_config_app 的配置操作接口添加安全审计事件记录，记录操作人、租户、操作类型和相关字段信息，同时更新测试用例验证审计日志的正确性，确保敏感配置值不被记录。 * test: 为上传测试用例添加 http_request 参数默认值 为测试用例中的 upload_files 调用添加 http_request=None 参数，避免测试时可能出现的未定义错误 * chore: bootstrap semantic repair stream fix draft * fix(agent): commit accepted streamed code action repairs * test(agent): verify repaired streams in deployed runtime and browser * test(agent): clarify deployed repair assertion failures --------- Co-authored-by: charmingchi1 <71816192+charmingchi1@users.noreply.github.com> * fix: repair agent repository e2e cases and API-type MCP health check (#4061) * fix: repair four failing e2e cases (API-086, API-063, PW-MCP-CONTAINER-01, PW-MCP-MARKET-01) * fix: skip MCP protocol handshake for API-type MCP health check * fix(test-e2e): align runtime contracts and strengthen local test diagnostics * fix(test-e2e): reconcile standalone semantic repair tests with formal cases * test:修改workflow * test:修复测试用例 * fix: preserve manual titles and metadata-free A2A calls * test: repair D1-D5 runtime contracts and execution evidence * test: repair daily assertions and remove excluded cases * fix: guard MCP tag refresh and repair daily test isolation * test：修复测试用例 * test:修复测试用例 * test:修复测试用例 --------- Co-authored-by: panyehong <2655992392@qq.com> Co-authored-by: xuyaqist <xuyaqist@gmail.com> Co-authored-by: chase <byzhangxin11@126.com> Co-authored-by: cj2026-bit <647646783@qq.com> Co-authored-by: Jason Wang <56037774+JasonW404@users.noreply.github.com> Co-authored-by: charmingchi1 <71816192+charmingchi1@users.noreply.github.com> Co-authored-by: MoeexT <yuwancumian666@outlook.com> | 5 天前 | |
fix(auth): handle session expiry with 401 responses across model management (#3766) * feat(gateway): add DashScope VLM adapter for audio via vlm slot - Add DashScopeVLMAdapter in modality/vlm, registered as ("dashscope", "vlm"); image/video protocols are inherited unchanged from OpenAIVLMAdapter - Encode audio as input_audio with a full data-URL: DashScope's OpenAI-compatible mode rejects audio_url and misreads raw base64 as a URL - Export DashScopeVLMAdapter from modality/__init__ - Drop vlm4 from provider-catalog health check types (audio models now covered by the adapter-based vlm health check) * test(gateway): add DashScopeVLMAdapter unit tests - Cover registration under the dashscope factory and the factory attribute - Cover the audio message path (input_audio with a full data-URL) and the video fallback that delegates to the generic OpenAI form * test(gateway): adapt tokenpony catalog test to probe fallback The refactored VLM branch no longer lets the provider catalog fail a check; a catalog error now falls through to a real adapter probe so valid-but- unlisted models (audio/omni) are not marked unavailable. Align the tokenpony vlm3 test with the new semantics: catalog error is confirmed, the real probe runs, and its result is returned. * test(gateway): cover vlm factory inference fallback in prepare_model_dict The new VLM branch infers model_factory from the base URL; when inference yields nothing the original factory must be kept. Add a prepare_model_dict case where _infer_model_factory returns None and assert the vlm3 factory is left unchanged, closing the uncovered branch. * fix(auth): handle session expiry with 401 responses across model management - Add TokenExpiredError subclassing UnauthorizedError plus a global FastAPI handler mapping it to a 401 JSON response with code TOKEN_EXPIRED - Raise TokenExpiredError from auth_utils for missing/invalid/expired session tokens; RBAC permission-denied keeps raising UnauthorizedError and is intentionally not redirected - Catch TokenExpiredError in model management endpoints (create/suggest/ capacity/provider/batch) and return 401 instead of generic errors - Handle 401 in frontend modelService.ts by redirecting through handleSessionExpired() instead of showing generic failure messages * fix(test): register TokenExpiredError in auth_utils exception mocks The new TokenExpiredError subclasses UnauthorizedError but was missing from the consts.exceptions mock, so auth_utils imported a MagicMock and every raise failed with 'exceptions must derive from BaseException'. Bind the real class in both the import list and the mock re-export list so the auth_utils tests pass again. * fix(test): cover TokenExpiredError 401 paths across app endpoints Add unit tests asserting every app endpoint guarded by token auth maps an expired token to 401: - app_factory: TokenExpiredError exception handler (TOKEN_EXPIRED code) - config_sync, conversation_share, knowledge_summary, monitoring, datamate, prompt_template, tool_config: per-endpoint 401 assertions - conversation_management: create/list/rename/delete/history/sources/ knowledge-scope/title endpoints - quota: tenant + platform quota endpoints - vectordatabase: all auth-guarded index/document/chunk/hybrid endpoints - model_managment: all /model CRUD, healthcheck, and manage endpoints - auth_utils: get_aksk_config / invalid timestamp / unexpected error TokenExpiredError raise paths --------- Co-authored-by: jeffwu <meetjeff.wu@gmail.com> | 1 个月前 | |
✨ Feature: Development of Agent Workbench Features (#4010) * ✨ Feature: Development of Agent Workbench Features * ✨ Feature: Development of Agent Workbench Features * ✨ Feature: Development of Agent Workbench Features * 🐛 Bugfix: The upload_to_s3 and download_from_s3 tools do not support user configuration. * feat:add-workbench * 工作台知识库选择依据aidp开关 * feat:工作台前端风格统一优化 * fix(workbench): restore chat modes and tenant model selection * fix(workbench): restore header and system skills * fix(workbench): hide built-in skills from composer * fix(workbench): restore managed agent invocation * fix(workbench): authorize hidden system agent for HITL * fix(workbench): persist creation history and retry branches * test(workbench): align legacy Skill API mocks with creation history * feat(workbench): separate chat entrypoints and refine creation UX * fix: restore workbench attachment reuse and landing layout * feat(workbench): gate workbench with deployment flag * feat(workbench): gate workbench with deployment flag * feat(workbench): Resolved conflicts and fixed an issue where historical sessions became unavailable after deleting and recreating the agent. * feat(workbench): Fix frontend pipeline build issues. * test(workbench): fix unit test isolation * test(workbench): raise patch coverage above threshold * refactor(workbench): consolidate database migration * fix(workbench): align reasoning defaults and skill card actions * test(workbench): use complete Agent fixture for reasoning defaults --------- Co-authored-by: dongjibao2001 <332722455@qq.com> | 23 天前 | |
♻️ Refactor(data-process): replace Ray with Celery prefork (#3888) * refactor(data-process): replace Ray with Celery prefork Run parsing in process-local Celery prefork children, keep orchestration and forwarding on thread workers, and remove the Ray runtime, dependency, and deployment surface. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(data-process): preserve sync parser result metadata * fix(data-process): wait for parser readiness in result backend * fix(data-process): tolerate lightweight worker app doubles * test(model): mock authentication for temporary healthcheck * Revert "test(model): mock authentication for temporary healthcheck" This reverts commit 9aa8d45b8eb9b8248b731957d23d851936e03608. * test(data-process): configure Celery URLs in isolated tests * test(data-process): cover prefork task boundaries * test(data-process): isolate prefork coverage from redis backend * test(data-process): cover lazy prefork branches * fix(data-process): complete celery prefork migration review fixes * test(data-process): align prefork tests with current APIs * fix(data-process): avoid logging user-controlled image paths * test(data-process): isolate router tests from celery bootstrap * test(model): provide auth for temporary healthcheck * test(data-process): stub redis chunk loader in router test * test(data-process): cover parser cancellation and lifecycle helpers * test(data-process): re-export process_sync from tasks module Keep the synchronous parse entry point reachable through the tasks module so coverage and isolation tests can patch one import site. Use a redundant-alias re-export to satisfy F401. * 🧪 Test: restore stubbed sys.modules after app router fixture Problem: the stub_modules fixture in test_data_process_app.py assigned stub modules directly to sys.modules without restoring them, so the stubs leaked into every later test file sharing the same pytest process. Running test_data_process_app.py before test_data_process_service.py failed all 52 service tests in setUp with AttributeError: '_CeleryAppStub' object has no attribute 'reset_mock'. The leak was invisible to CI because run_all_test.py runs each test file in its own subprocess. Fix: replace the six direct sys.modules assignments with monkeypatch.setitem so the real modules are restored when the fixture tears down. Behavior during each test is unchanged. Verification: - pytest test/backend/app/test_data_process_app.py test/backend/services/test_data_process_service.py -> 76 passed (was 24 passed / 52 failed) - each file alone: 24 passed / 52 passed (no regression) - wider combo (app + services + tasks + worker + coverage): app+services now pass together; the remaining failures are a pre-existing module-level mock leak in test_data_process_service.py that exists on develop and is out of scope here. | 9 天前 | |
fix(auth): handle session expiry with 401 responses across model management (#3766) * feat(gateway): add DashScope VLM adapter for audio via vlm slot - Add DashScopeVLMAdapter in modality/vlm, registered as ("dashscope", "vlm"); image/video protocols are inherited unchanged from OpenAIVLMAdapter - Encode audio as input_audio with a full data-URL: DashScope's OpenAI-compatible mode rejects audio_url and misreads raw base64 as a URL - Export DashScopeVLMAdapter from modality/__init__ - Drop vlm4 from provider-catalog health check types (audio models now covered by the adapter-based vlm health check) * test(gateway): add DashScopeVLMAdapter unit tests - Cover registration under the dashscope factory and the factory attribute - Cover the audio message path (input_audio with a full data-URL) and the video fallback that delegates to the generic OpenAI form * test(gateway): adapt tokenpony catalog test to probe fallback The refactored VLM branch no longer lets the provider catalog fail a check; a catalog error now falls through to a real adapter probe so valid-but- unlisted models (audio/omni) are not marked unavailable. Align the tokenpony vlm3 test with the new semantics: catalog error is confirmed, the real probe runs, and its result is returned. * test(gateway): cover vlm factory inference fallback in prepare_model_dict The new VLM branch infers model_factory from the base URL; when inference yields nothing the original factory must be kept. Add a prepare_model_dict case where _infer_model_factory returns None and assert the vlm3 factory is left unchanged, closing the uncovered branch. * fix(auth): handle session expiry with 401 responses across model management - Add TokenExpiredError subclassing UnauthorizedError plus a global FastAPI handler mapping it to a 401 JSON response with code TOKEN_EXPIRED - Raise TokenExpiredError from auth_utils for missing/invalid/expired session tokens; RBAC permission-denied keeps raising UnauthorizedError and is intentionally not redirected - Catch TokenExpiredError in model management endpoints (create/suggest/ capacity/provider/batch) and return 401 instead of generic errors - Handle 401 in frontend modelService.ts by redirecting through handleSessionExpired() instead of showing generic failure messages * fix(test): register TokenExpiredError in auth_utils exception mocks The new TokenExpiredError subclasses UnauthorizedError but was missing from the consts.exceptions mock, so auth_utils imported a MagicMock and every raise failed with 'exceptions must derive from BaseException'. Bind the real class in both the import list and the mock re-export list so the auth_utils tests pass again. * fix(test): cover TokenExpiredError 401 paths across app endpoints Add unit tests asserting every app endpoint guarded by token auth maps an expired token to 401: - app_factory: TokenExpiredError exception handler (TOKEN_EXPIRED code) - config_sync, conversation_share, knowledge_summary, monitoring, datamate, prompt_template, tool_config: per-endpoint 401 assertions - conversation_management: create/list/rename/delete/history/sources/ knowledge-scope/title endpoints - quota: tenant + platform quota endpoints - vectordatabase: all auth-guarded index/document/chunk/hybrid endpoints - model_managment: all /model CRUD, healthcheck, and manage endpoints - auth_utils: get_aksk_config / invalid timestamp / unexpected error TokenExpiredError raise paths --------- Co-authored-by: jeffwu <meetjeff.wu@gmail.com> | 1 个月前 | |
✨ Add FastAPI application factory and unit tests: Implemented a new app_factory module for creating FastAPI applications with common configurations and exception handling. Added comprehensive unit tests to validate the functionality of the create_app and register_exception_handlers functions. | 7 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 | 2 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> | 25 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 | 18 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 | 2 个月前 | |
feat(audit): add security audit logging to backend management APIs (#4055) * feat: 为模型管理接口添加安全审计日志记录 实现了模型创建、更新、删除、批量操作等接口的安全审计日志功能，过滤了敏感凭证信息，确保审计日志安全合规。新增了审计安全字段过滤工具函数，补充了对应的测试用例验证审计日志的正确性和安全性。 * feat: 为多个接口添加安全审计日志记录 为agent和agent_repository相关的API接口添加安全审计事件记录，包括代理更新、图标上传、删除、导出、导入、版本发布/回滚/更新/删除等操作，同时补充对应的测试用例验证审计日志的正确性，确保敏感数据不被记录。 * feat: 为MCP和技能相关接口添加上下文安全审计日志 为tool、mcp、remote_mcp、skill模块的所有关键增删改接口添加安全审计日志，记录操作人、资源信息等关键字段，同时避免记录敏感信息如凭证、密钥等。新增对应的测试用例验证审计日志的正确性，确保敏感数据不会被泄露。 * feat: 添加安全审计日志并限制审计详情列表长度 在多个服务端点添加安全审计日志，记录关键操作信息 同时统一审计详情列表的长度限制为20，防止日志被恶意payload撑爆 * feat: 为配置相关接口添加安全审计日志记录 为 config_sync_app 和 memory_config_app 的配置操作接口添加安全审计事件记录，记录操作人、租户、操作类型和相关字段信息，同时更新测试用例验证审计日志的正确性，确保敏感配置值不被记录。 * test: 为上传测试用例添加 http_request 参数默认值 为测试用例中的 upload_files 调用添加 http_request=None 参数，避免测试时可能出现的未定义错误 | 7 天前 | |
feat(logging):Security Audit Logging (#4015) * feat: 添加安全审计服务并在关键操作记录审计日志 新增 audit_service 服务用于记录安全审计事件，在用户注册、登录、登出、密码修改、OAuth/ CAS 相关操作、令牌管理、账户撤销等关键安全操作中记录审计日志，同时新增对应测试用例确保审计功能正常工作。 * feat: 为 API 密钥操作添加上下文安全审计日志 在 API 密钥应用和北向应用中，为刷新、撤销 API 密钥以及批量创建 API 用户等操作添加安全审计日志记录，仅记录非敏感的目标用户信息、操作人信息和请求标识，避免泄露明文 API 密钥。同时新增对应的测试用例验证审计日志的正确性和安全性。 * feat: 为用户、租户、邀请和群组操作添加安全审计日志 在多个API端点（用户、租户、邀请、群组相关的创建、更新、删除等操作）中添加了安全审计日志记录，同时新增了对应的测试用例来验证审计日志的正确性。 | 19 天前 | |
✨ Support full thread management (#3917) * 📃 Merge cursor rules into universal AGENTS.md and skills * ✨ Support full thread management * ✨ Support full thread management phase2 * 🧪 Add test files * 🧪 Add test files * 🧪 Add test files * ✨ Thread management fulfilling platform constraint * 🧪 Add test files * 🧪 Add thread interface * 🧪 Add test files | 1 个月前 | |
feat(agent): add verification configuration for agents and update related components (#3174) * feat(agent): add verification configuration for agents and update related components * feat(model): update model type labels and add monitoring dashboard translations | 3 个月前 | |
🧪 Add global test configuration and common fixtures for improved test, refactor test files to use pytest and improve mock handling - Converted unittest test cases to pytest format across multiple test files. - Simplified mock setups using pytest-mock for better readability and maintainability. - Removed unnecessary imports and legacy code to streamline test execution. - Enhanced test coverage for utility functions in various modules. | 8 个月前 | |
feat(logging):Security Audit Logging (#4015) * feat: 添加安全审计服务并在关键操作记录审计日志 新增 audit_service 服务用于记录安全审计事件，在用户注册、登录、登出、密码修改、OAuth/ CAS 相关操作、令牌管理、账户撤销等关键安全操作中记录审计日志，同时新增对应测试用例确保审计功能正常工作。 * feat: 为 API 密钥操作添加上下文安全审计日志 在 API 密钥应用和北向应用中，为刷新、撤销 API 密钥以及批量创建 API 用户等操作添加安全审计日志记录，仅记录非敏感的目标用户信息、操作人信息和请求标识，避免泄露明文 API 密钥。同时新增对应的测试用例验证审计日志的正确性和安全性。 * feat: 为用户、租户、邀请和群组操作添加安全审计日志 在多个API端点（用户、租户、邀请、群组相关的创建、更新、删除等操作）中添加了安全审计日志记录，同时新增了对应的测试用例来验证审计日志的正确性。 | 19 天前 | |
♻️ Refactor phase 1: agent_service / vectordatabase_service / skill_service (#3843) * refactor(core): slim agent skill and knowledge services Extract reusable service boundaries, preserve deleted-model availability, and consolidate knowledge-base permission, list, and deletion flows. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5.6-sol * ♻️ Refactor phase 1: agent_service / vectordatabase_service / skill_service * ♻️ Refactor phase 1: agent_service / vectordatabase_service / skill_service * 🧪 Add test files * fix(agent): preserve repository naming after develop rebase * ♻️ Refactor phase 1: agent_service / vectordatabase_service / skill_service * 🧪 Add test files | 1 个月前 | |
feat(audit): add security audit logging to backend management APIs (#4055) * feat: 为模型管理接口添加安全审计日志记录 实现了模型创建、更新、删除、批量操作等接口的安全审计日志功能，过滤了敏感凭证信息，确保审计日志安全合规。新增了审计安全字段过滤工具函数，补充了对应的测试用例验证审计日志的正确性和安全性。 * feat: 为多个接口添加安全审计日志记录 为agent和agent_repository相关的API接口添加安全审计事件记录，包括代理更新、图标上传、删除、导出、导入、版本发布/回滚/更新/删除等操作，同时补充对应的测试用例验证审计日志的正确性，确保敏感数据不被记录。 * feat: 为MCP和技能相关接口添加上下文安全审计日志 为tool、mcp、remote_mcp、skill模块的所有关键增删改接口添加安全审计日志，记录操作人、资源信息等关键字段，同时避免记录敏感信息如凭证、密钥等。新增对应的测试用例验证审计日志的正确性，确保敏感数据不会被泄露。 * feat: 添加安全审计日志并限制审计详情列表长度 在多个服务端点添加安全审计日志，记录关键操作信息 同时统一审计详情列表的长度限制为20，防止日志被恶意payload撑爆 * feat: 为配置相关接口添加安全审计日志记录 为 config_sync_app 和 memory_config_app 的配置操作接口添加安全审计事件记录，记录操作人、租户、操作类型和相关字段信息，同时更新测试用例验证审计日志的正确性，确保敏感配置值不被记录。 * test: 为上传测试用例添加 http_request 参数默认值 为测试用例中的 upload_files 调用添加 http_request=None 参数，避免测试时可能出现的未定义错误 | 7 天前 | |
feat(audit): add security audit logging to backend management APIs (#4055) * feat: 为模型管理接口添加安全审计日志记录 实现了模型创建、更新、删除、批量操作等接口的安全审计日志功能，过滤了敏感凭证信息，确保审计日志安全合规。新增了审计安全字段过滤工具函数，补充了对应的测试用例验证审计日志的正确性和安全性。 * feat: 为多个接口添加安全审计日志记录 为agent和agent_repository相关的API接口添加安全审计事件记录，包括代理更新、图标上传、删除、导出、导入、版本发布/回滚/更新/删除等操作，同时补充对应的测试用例验证审计日志的正确性，确保敏感数据不被记录。 * feat: 为MCP和技能相关接口添加上下文安全审计日志 为tool、mcp、remote_mcp、skill模块的所有关键增删改接口添加安全审计日志，记录操作人、资源信息等关键字段，同时避免记录敏感信息如凭证、密钥等。新增对应的测试用例验证审计日志的正确性，确保敏感数据不会被泄露。 * feat: 添加安全审计日志并限制审计详情列表长度 在多个服务端点添加安全审计日志，记录关键操作信息 同时统一审计详情列表的长度限制为20，防止日志被恶意payload撑爆 * feat: 为配置相关接口添加安全审计日志记录 为 config_sync_app 和 memory_config_app 的配置操作接口添加安全审计事件记录，记录操作人、租户、操作类型和相关字段信息，同时更新测试用例验证审计日志的正确性，确保敏感配置值不被记录。 * test: 为上传测试用例添加 http_request 参数默认值 为测试用例中的 upload_files 调用添加 http_request=None 参数，避免测试时可能出现的未定义错误 | 7 天前 | |
🐛 Bugfix: memories, multimodal embeddings 500 es error, security, skills (#3577) * 🐛 Bugfix: Memory status fix 🐛 Bugfix: Cannot choose multimodal processed knowledge base in tool configuration 🐛 Bugfix: Patch several security issues on interfaces 🐛 Bugfix: Official skill not found when missing allowed-tools * 🐛 Bugfix: Knowledge base created by embedding model (using same) throwing 500 elasticsearch error * 🧪 Add test files * 🧪 Add test files * 🧪 Add test files * 🐛 Bugfix: knowledge base search skill frontend * ♻️ Fix uncontrolled data used in path expression | 2 个月前 | |
♻️ refactor model service (#4088) * refactor: consolidate model management services * test: update Management architecture checks for model modules | 3 天前 | |
fix: let tenant admins manage models of their own tenant (#4043) #4008 closed a horizontal-privilege hole on /model/manage/* by restricting the endpoints to the SU role. The whitelist did not distinguish a cross-tenant call from one naming the caller's own tenant, so ADMIN users lost the whole Models tab on /resource-manage: manage/list returned 403 and the page rendered an empty table with no error, because the create, update, delete, healthcheck and provider endpoints share the same guard. The page always sends the caller's own tenant_id (UserManageComp falls back to user.tenantId for non-SU), so rejecting ADMIN blocked no cross-tenant access -- it only broke tenant admins managing their own models. Replace the role whitelist with a role + tenant scope check: SU may target any tenant, ADMIN only the tenant its token belongs to, and every other role is rejected as before. ADMIN and SU share the same model:* permission seeds, so the role itself still has to be checked -- permissions alone cannot separate them. The existing ADMIN cross-tenant test kept passing because it used a foreign tenant_id, which is why the regression went uncaught. Add own-tenant coverage for list and update, plus a DEV case proving require(model:read) is not sufficient on its own to reach the manage surface. Co-authored-by: jeffwu <meetjeff.wu@gmail.com> Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com> | 17 天前 | |
Configure monitoring dashboard role access (#3928) Co-authored-by: hhhhsc <name> | 1 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> | 25 天前 | |
feat(logging):Security Audit Logging (#4015) * feat: 添加安全审计服务并在关键操作记录审计日志 新增 audit_service 服务用于记录安全审计事件，在用户注册、登录、登出、密码修改、OAuth/ CAS 相关操作、令牌管理、账户撤销等关键安全操作中记录审计日志，同时新增对应测试用例确保审计功能正常工作。 * feat: 为 API 密钥操作添加上下文安全审计日志 在 API 密钥应用和北向应用中，为刷新、撤销 API 密钥以及批量创建 API 用户等操作添加安全审计日志记录，仅记录非敏感的目标用户信息、操作人信息和请求标识，避免泄露明文 API 密钥。同时新增对应的测试用例验证审计日志的正确性和安全性。 * feat: 为用户、租户、邀请和群组操作添加安全审计日志 在多个API端点（用户、租户、邀请、群组相关的创建、更新、删除等操作）中添加了安全审计日志记录，同时新增了对应的测试用例来验证审计日志的正确性。 | 19 天前 | |
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> | 25 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 | 19 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 | |
feat(logging):Security Audit Logging (#4015) * feat: 添加安全审计服务并在关键操作记录审计日志 新增 audit_service 服务用于记录安全审计事件，在用户注册、登录、登出、密码修改、OAuth/ CAS 相关操作、令牌管理、账户撤销等关键安全操作中记录审计日志，同时新增对应测试用例确保审计功能正常工作。 * feat: 为 API 密钥操作添加上下文安全审计日志 在 API 密钥应用和北向应用中，为刷新、撤销 API 密钥以及批量创建 API 用户等操作添加安全审计日志记录，仅记录非敏感的目标用户信息、操作人信息和请求标识，避免泄露明文 API 密钥。同时新增对应的测试用例验证审计日志的正确性和安全性。 * feat: 为用户、租户、邀请和群组操作添加安全审计日志 在多个API端点（用户、租户、邀请、群组相关的创建、更新、删除等操作）中添加了安全审计日志记录，同时新增了对应的测试用例来验证审计日志的正确性。 | 19 天前 | |
feat(logging):Security Audit Logging (#4015) * feat: 添加安全审计服务并在关键操作记录审计日志 新增 audit_service 服务用于记录安全审计事件，在用户注册、登录、登出、密码修改、OAuth/ CAS 相关操作、令牌管理、账户撤销等关键安全操作中记录审计日志，同时新增对应测试用例确保审计功能正常工作。 * feat: 为 API 密钥操作添加上下文安全审计日志 在 API 密钥应用和北向应用中，为刷新、撤销 API 密钥以及批量创建 API 用户等操作添加安全审计日志记录，仅记录非敏感的目标用户信息、操作人信息和请求标识，避免泄露明文 API 密钥。同时新增对应的测试用例验证审计日志的正确性和安全性。 * feat: 为用户、租户、邀请和群组操作添加安全审计日志 在多个API端点（用户、租户、邀请、群组相关的创建、更新、删除等操作）中添加了安全审计日志记录，同时新增了对应的测试用例来验证审计日志的正确性。 | 19 天前 | |
♻️ Refactor phase 1: agent_service / vectordatabase_service / skill_service (#3843) * refactor(core): slim agent skill and knowledge services Extract reusable service boundaries, preserve deleted-model availability, and consolidate knowledge-base permission, list, and deletion flows. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5.6-sol * ♻️ Refactor phase 1: agent_service / vectordatabase_service / skill_service * ♻️ Refactor phase 1: agent_service / vectordatabase_service / skill_service * 🧪 Add test files * fix(agent): preserve repository naming after develop rebase * ♻️ Refactor phase 1: agent_service / vectordatabase_service / skill_service * 🧪 Add test files | 1 个月前 | |
🧪test：add e2e test baseline&fix some bugs (#4065) * test:baseline cases * test:add local test process * doc:add test deploy guide * bugfiix:优化测试流程 * bugfix：修复测试用例 * doc:轻量化bugfix的spec设计和测试用例设计 * test:修复测试用例 * test:修复D1测试用例 * test: 修复 D3 用例脚本并记录失败归因 * test: 移除 D3 变更记录，仅保留测试修复 * fix(test-e2e): make D5 tests portable and isolate evaluation workloads * fix(test-e2e): repair Windows case contracts and D4 journeys * feat(test-e2e): launch repository daily from a pinned branch * test:修复D4读取config问题 * test:修复测试用例，删掉过期用例 * test：修复测试用例 * test:修复测试用例 * doc：测试规范修改 * test：增加外部记忆mock服务 * test：测试用例修复 * fix(prompt): reject blank task descriptions before SSE generation * fix(agent): return 404 for missing discovery resources * fix(agent): validate relationships before update writes * fix(model): preserve provider error status on provider create A provider failure (e.g. an upstream connection_failed) was raised as HTTPException(502) by create_provider_models_for_tenant, but the generic except Exception handlers in the service and the app layer swallowed it and re-wrapped it, so /model/provider/create answered 500 with the real status only surviving as text in the message body (API-049). - service: re-raise HTTPException instead of wrapping it - app: pass HTTPException through on /provider/create and /manage/provider/create - schema: reject a blank provider with 422 at the boundary - tests: regression coverage for both behaviours * fix: correct conversation access and stopped-turn regressions * fix: enforce tenant isolation and edit permissions for agent relations * fix: enforce tenant isolation and edit permissions for agent relations1 * 🐛 Fix tag projection crash on first-attempt ES write failure Problem: project_document_assignments() dereferenced the prior ledger state without a None guard in its generic exception handler. On a document's first-ever projection attempt there is no ledger row yet, so an ES write failure crashed with AttributeError before the failed state was persisted. The failure then became invisible: no retry_count, no next_attempt_at, retry_pending_document_projections() never picked the document up, and tag-filtered retrieval silently ignored the document until its tags were re-saved. Fix: Treat a missing prior state as retry_count 0 in the failure handler ((current or {}).get("retry_count")), so first-attempt failures record a retryable failed state with correct exponential backoff. Added a regression unit test for the no-prior-state failure path (previously only the existing-state path was covered). Also added one blank line after the import block to satisfy the repo ruff pre-commit hook on this file (pre-existing I001). Verification: - test/backend/services/test_tag_document_projection.py 28/28 passed, incl. new test_first_attempt_failure_records_retryable_state - Neighboring regression: test_tag_management_service.py and test_tag_document_batch_status.py, 53/53 passed - ruff (E,F,I,W hook rule set) clean on the touched backend file - Matches the state-machine expectations of e2e case API-AUTO-357B84F01BA6D321 (daily run 2026-10-09) * Fix A2A publication smoke scope and remove Mock dependency * fix(a2a): execute the version recorded by A2A publication * [WIP] Fix accepted semantic repair stream commits (#4057) * feat(audit): add security audit logging to backend management APIs (#4055) * feat: 为模型管理接口添加安全审计日志记录 实现了模型创建、更新、删除、批量操作等接口的安全审计日志功能，过滤了敏感凭证信息，确保审计日志安全合规。新增了审计安全字段过滤工具函数，补充了对应的测试用例验证审计日志的正确性和安全性。 * feat: 为多个接口添加安全审计日志记录 为agent和agent_repository相关的API接口添加安全审计事件记录，包括代理更新、图标上传、删除、导出、导入、版本发布/回滚/更新/删除等操作，同时补充对应的测试用例验证审计日志的正确性，确保敏感数据不被记录。 * feat: 为MCP和技能相关接口添加上下文安全审计日志 为tool、mcp、remote_mcp、skill模块的所有关键增删改接口添加安全审计日志，记录操作人、资源信息等关键字段，同时避免记录敏感信息如凭证、密钥等。新增对应的测试用例验证审计日志的正确性，确保敏感数据不会被泄露。 * feat: 添加安全审计日志并限制审计详情列表长度 在多个服务端点添加安全审计日志，记录关键操作信息 同时统一审计详情列表的长度限制为20，防止日志被恶意payload撑爆 * feat: 为配置相关接口添加安全审计日志记录 为 config_sync_app 和 memory_config_app 的配置操作接口添加安全审计事件记录，记录操作人、租户、操作类型和相关字段信息，同时更新测试用例验证审计日志的正确性，确保敏感配置值不被记录。 * test: 为上传测试用例添加 http_request 参数默认值 为测试用例中的 upload_files 调用添加 http_request=None 参数，避免测试时可能出现的未定义错误 * chore: bootstrap semantic repair stream fix draft * fix(agent): commit accepted streamed code action repairs * test(agent): verify repaired streams in deployed runtime and browser * test(agent): clarify deployed repair assertion failures --------- Co-authored-by: charmingchi1 <71816192+charmingchi1@users.noreply.github.com> * fix: repair agent repository e2e cases and API-type MCP health check (#4061) * fix: repair four failing e2e cases (API-086, API-063, PW-MCP-CONTAINER-01, PW-MCP-MARKET-01) * fix: skip MCP protocol handshake for API-type MCP health check * fix(test-e2e): align runtime contracts and strengthen local test diagnostics * fix(test-e2e): reconcile standalone semantic repair tests with formal cases * test:修改workflow * test:修复测试用例 * fix: preserve manual titles and metadata-free A2A calls * test: repair D1-D5 runtime contracts and execution evidence * test: repair daily assertions and remove excluded cases * fix: guard MCP tag refresh and repair daily test isolation * test：修复测试用例 * test:修复测试用例 * test:修复测试用例 --------- Co-authored-by: panyehong <2655992392@qq.com> Co-authored-by: xuyaqist <xuyaqist@gmail.com> Co-authored-by: chase <byzhangxin11@126.com> Co-authored-by: cj2026-bit <647646783@qq.com> Co-authored-by: Jason Wang <56037774+JasonW404@users.noreply.github.com> Co-authored-by: charmingchi1 <71816192+charmingchi1@users.noreply.github.com> Co-authored-by: MoeexT <yuwancumian666@outlook.com> | 5 天前 | |
fix(auth): handle session expiry with 401 responses across model management (#3766) * feat(gateway): add DashScope VLM adapter for audio via vlm slot - Add DashScopeVLMAdapter in modality/vlm, registered as ("dashscope", "vlm"); image/video protocols are inherited unchanged from OpenAIVLMAdapter - Encode audio as input_audio with a full data-URL: DashScope's OpenAI-compatible mode rejects audio_url and misreads raw base64 as a URL - Export DashScopeVLMAdapter from modality/__init__ - Drop vlm4 from provider-catalog health check types (audio models now covered by the adapter-based vlm health check) * test(gateway): add DashScopeVLMAdapter unit tests - Cover registration under the dashscope factory and the factory attribute - Cover the audio message path (input_audio with a full data-URL) and the video fallback that delegates to the generic OpenAI form * test(gateway): adapt tokenpony catalog test to probe fallback The refactored VLM branch no longer lets the provider catalog fail a check; a catalog error now falls through to a real adapter probe so valid-but- unlisted models (audio/omni) are not marked unavailable. Align the tokenpony vlm3 test with the new semantics: catalog error is confirmed, the real probe runs, and its result is returned. * test(gateway): cover vlm factory inference fallback in prepare_model_dict The new VLM branch infers model_factory from the base URL; when inference yields nothing the original factory must be kept. Add a prepare_model_dict case where _infer_model_factory returns None and assert the vlm3 factory is left unchanged, closing the uncovered branch. * fix(auth): handle session expiry with 401 responses across model management - Add TokenExpiredError subclassing UnauthorizedError plus a global FastAPI handler mapping it to a 401 JSON response with code TOKEN_EXPIRED - Raise TokenExpiredError from auth_utils for missing/invalid/expired session tokens; RBAC permission-denied keeps raising UnauthorizedError and is intentionally not redirected - Catch TokenExpiredError in model management endpoints (create/suggest/ capacity/provider/batch) and return 401 instead of generic errors - Handle 401 in frontend modelService.ts by redirecting through handleSessionExpired() instead of showing generic failure messages * fix(test): register TokenExpiredError in auth_utils exception mocks The new TokenExpiredError subclasses UnauthorizedError but was missing from the consts.exceptions mock, so auth_utils imported a MagicMock and every raise failed with 'exceptions must derive from BaseException'. Bind the real class in both the import list and the mock re-export list so the auth_utils tests pass again. * fix(test): cover TokenExpiredError 401 paths across app endpoints Add unit tests asserting every app endpoint guarded by token auth maps an expired token to 401: - app_factory: TokenExpiredError exception handler (TOKEN_EXPIRED code) - config_sync, conversation_share, knowledge_summary, monitoring, datamate, prompt_template, tool_config: per-endpoint 401 assertions - conversation_management: create/list/rename/delete/history/sources/ knowledge-scope/title endpoints - quota: tenant + platform quota endpoints - vectordatabase: all auth-guarded index/document/chunk/hybrid endpoints - model_managment: all /model CRUD, healthcheck, and manage endpoints - auth_utils: get_aksk_config / invalid timestamp / unexpected error TokenExpiredError raise paths --------- Co-authored-by: jeffwu <meetjeff.wu@gmail.com> | 1 个月前 | |
feat(audit): add security audit logging to backend management APIs (#4055) * feat: 为模型管理接口添加安全审计日志记录 实现了模型创建、更新、删除、批量操作等接口的安全审计日志功能，过滤了敏感凭证信息，确保审计日志安全合规。新增了审计安全字段过滤工具函数，补充了对应的测试用例验证审计日志的正确性和安全性。 * feat: 为多个接口添加安全审计日志记录 为agent和agent_repository相关的API接口添加安全审计事件记录，包括代理更新、图标上传、删除、导出、导入、版本发布/回滚/更新/删除等操作，同时补充对应的测试用例验证审计日志的正确性，确保敏感数据不被记录。 * feat: 为MCP和技能相关接口添加上下文安全审计日志 为tool、mcp、remote_mcp、skill模块的所有关键增删改接口添加安全审计日志，记录操作人、资源信息等关键字段，同时避免记录敏感信息如凭证、密钥等。新增对应的测试用例验证审计日志的正确性，确保敏感数据不会被泄露。 * feat: 添加安全审计日志并限制审计详情列表长度 在多个服务端点添加安全审计日志，记录关键操作信息 同时统一审计详情列表的长度限制为20，防止日志被恶意payload撑爆 * feat: 为配置相关接口添加安全审计日志记录 为 config_sync_app 和 memory_config_app 的配置操作接口添加安全审计事件记录，记录操作人、租户、操作类型和相关字段信息，同时更新测试用例验证审计日志的正确性，确保敏感配置值不被记录。 * test: 为上传测试用例添加 http_request 参数默认值 为测试用例中的 upload_files 调用添加 http_request=None 参数，避免测试时可能出现的未定义错误 | 7 天前 | |
feat(audit): add security audit logging to backend management APIs (#4055) * feat: 为模型管理接口添加安全审计日志记录 实现了模型创建、更新、删除、批量操作等接口的安全审计日志功能，过滤了敏感凭证信息，确保审计日志安全合规。新增了审计安全字段过滤工具函数，补充了对应的测试用例验证审计日志的正确性和安全性。 * feat: 为多个接口添加安全审计日志记录 为agent和agent_repository相关的API接口添加安全审计事件记录，包括代理更新、图标上传、删除、导出、导入、版本发布/回滚/更新/删除等操作，同时补充对应的测试用例验证审计日志的正确性，确保敏感数据不被记录。 * feat: 为MCP和技能相关接口添加上下文安全审计日志 为tool、mcp、remote_mcp、skill模块的所有关键增删改接口添加安全审计日志，记录操作人、资源信息等关键字段，同时避免记录敏感信息如凭证、密钥等。新增对应的测试用例验证审计日志的正确性，确保敏感数据不会被泄露。 * feat: 添加安全审计日志并限制审计详情列表长度 在多个服务端点添加安全审计日志，记录关键操作信息 同时统一审计详情列表的长度限制为20，防止日志被恶意payload撑爆 * feat: 为配置相关接口添加安全审计日志记录 为 config_sync_app 和 memory_config_app 的配置操作接口添加安全审计事件记录，记录操作人、租户、操作类型和相关字段信息，同时更新测试用例验证审计日志的正确性，确保敏感配置值不被记录。 * test: 为上传测试用例添加 http_request 参数默认值 为测试用例中的 upload_files 调用添加 http_request=None 参数，避免测试时可能出现的未定义错误 | 7 天前 | |
feat(audit): add security audit logging to backend management APIs (#4055) * feat: 为模型管理接口添加安全审计日志记录 实现了模型创建、更新、删除、批量操作等接口的安全审计日志功能，过滤了敏感凭证信息，确保审计日志安全合规。新增了审计安全字段过滤工具函数，补充了对应的测试用例验证审计日志的正确性和安全性。 * feat: 为多个接口添加安全审计日志记录 为agent和agent_repository相关的API接口添加安全审计事件记录，包括代理更新、图标上传、删除、导出、导入、版本发布/回滚/更新/删除等操作，同时补充对应的测试用例验证审计日志的正确性，确保敏感数据不被记录。 * feat: 为MCP和技能相关接口添加上下文安全审计日志 为tool、mcp、remote_mcp、skill模块的所有关键增删改接口添加安全审计日志，记录操作人、资源信息等关键字段，同时避免记录敏感信息如凭证、密钥等。新增对应的测试用例验证审计日志的正确性，确保敏感数据不会被泄露。 * feat: 添加安全审计日志并限制审计详情列表长度 在多个服务端点添加安全审计日志，记录关键操作信息 同时统一审计详情列表的长度限制为20，防止日志被恶意payload撑爆 * feat: 为配置相关接口添加安全审计日志记录 为 config_sync_app 和 memory_config_app 的配置操作接口添加安全审计事件记录，记录操作人、租户、操作类型和相关字段信息，同时更新测试用例验证审计日志的正确性，确保敏感配置值不被记录。 * test: 为上传测试用例添加 http_request 参数默认值 为测试用例中的 upload_files 调用添加 http_request=None 参数，避免测试时可能出现的未定义错误 | 7 天前 | |
feat: refactor label system (#3809) * fix(tag-mgmt): register legacy exception handlers + fix filter endpoint sync + add value usage index - backend/apps/app_factory.py: register handlers for legacy domain exceptions (UnauthorizedError->401, ForbiddenError->403, LimitExceededError->429, ValidationError->400, NotFoundException->404, DuplicateError->409, TagManagementConflictError->409, SignatureValidationError->401) so they no longer fall through to the generic 500 handler. Verified live: unauthenticated tag endpoints now return 401 instead of 500. - backend/apps/tag_management_app.py: convert filter_resource_tag_assignments from async/await to sync/_run to match the synchronous TagManagementDB.filter_authorized_resource_ids (which returns a dict, not a coroutine). Fixes TypeError -> HTTP 500 on the filter endpoint. - deploy/sql: add partial index idx_resource_tag_assignment_value (tenant_id, value_id, delete_flag) WHERE delete_flag='N' via new migration v2.5.4_0820_tag_value_usage_index.sql and init.sql. Benchmark at capacity limits (100 defs / 100k values / 50k assignments) showed value-usage-count was a 102ms Seq Scan; with the index it becomes a 1.28ms Index Only Scan. Idempotent (IF NOT EXISTS). * feat(tag-mgmt): unified tag management for KB/agent/MCP/skill resources - Add tenant-scoped tag libraries, definitions, values and assignments - Wire tag chips and filters into knowledge base, agent and MCP pages - Add document tag projection ledger with provider sync - Clean up assignments when KB/agent/MCP/skill resources are deleted - Add preflight and migration scripts v2.5.0-v2.5.3 - Cache assignment reads on list pages to avoid per-row HTTP requests * fix(tag-mgmt): migrate tag assignment entries and enable tag search for mine agents * feat(tag-mgmt): complete unified tag assignment flows * feat(tag-management): unify repository tag filters * feat(tag-management): localize and search agent tags * feat(tag-management): unify repository tag filtering * fix(tag-management): migrate legacy agent categories * fix(tag-management): restore rebased tag UI * feat(tag-management): support no-value tags * fix(tag-management): unblock CI checks * chore(sonar): exclude mirrored tag SQL from CPD * test(tag-management): raise patch coverage * fix(tag-management): address review feedback * fix: migrate tag services after management split | 1 个月前 | |
feat: refactor label system (#3809) * fix(tag-mgmt): register legacy exception handlers + fix filter endpoint sync + add value usage index - backend/apps/app_factory.py: register handlers for legacy domain exceptions (UnauthorizedError->401, ForbiddenError->403, LimitExceededError->429, ValidationError->400, NotFoundException->404, DuplicateError->409, TagManagementConflictError->409, SignatureValidationError->401) so they no longer fall through to the generic 500 handler. Verified live: unauthenticated tag endpoints now return 401 instead of 500. - backend/apps/tag_management_app.py: convert filter_resource_tag_assignments from async/await to sync/_run to match the synchronous TagManagementDB.filter_authorized_resource_ids (which returns a dict, not a coroutine). Fixes TypeError -> HTTP 500 on the filter endpoint. - deploy/sql: add partial index idx_resource_tag_assignment_value (tenant_id, value_id, delete_flag) WHERE delete_flag='N' via new migration v2.5.4_0820_tag_value_usage_index.sql and init.sql. Benchmark at capacity limits (100 defs / 100k values / 50k assignments) showed value-usage-count was a 102ms Seq Scan; with the index it becomes a 1.28ms Index Only Scan. Idempotent (IF NOT EXISTS). * feat(tag-mgmt): unified tag management for KB/agent/MCP/skill resources - Add tenant-scoped tag libraries, definitions, values and assignments - Wire tag chips and filters into knowledge base, agent and MCP pages - Add document tag projection ledger with provider sync - Clean up assignments when KB/agent/MCP/skill resources are deleted - Add preflight and migration scripts v2.5.0-v2.5.3 - Cache assignment reads on list pages to avoid per-row HTTP requests * fix(tag-mgmt): migrate tag assignment entries and enable tag search for mine agents * feat(tag-mgmt): complete unified tag assignment flows * feat(tag-management): unify repository tag filters * feat(tag-management): localize and search agent tags * feat(tag-management): unify repository tag filtering * fix(tag-management): migrate legacy agent categories * fix(tag-management): restore rebased tag UI * feat(tag-management): support no-value tags * fix(tag-management): unblock CI checks * chore(sonar): exclude mirrored tag SQL from CPD * test(tag-management): raise patch coverage * fix(tag-management): address review feedback * fix: migrate tag services after management split | 1 个月前 | |
feat: refactor label system (#3809) * fix(tag-mgmt): register legacy exception handlers + fix filter endpoint sync + add value usage index - backend/apps/app_factory.py: register handlers for legacy domain exceptions (UnauthorizedError->401, ForbiddenError->403, LimitExceededError->429, ValidationError->400, NotFoundException->404, DuplicateError->409, TagManagementConflictError->409, SignatureValidationError->401) so they no longer fall through to the generic 500 handler. Verified live: unauthenticated tag endpoints now return 401 instead of 500. - backend/apps/tag_management_app.py: convert filter_resource_tag_assignments from async/await to sync/_run to match the synchronous TagManagementDB.filter_authorized_resource_ids (which returns a dict, not a coroutine). Fixes TypeError -> HTTP 500 on the filter endpoint. - deploy/sql: add partial index idx_resource_tag_assignment_value (tenant_id, value_id, delete_flag) WHERE delete_flag='N' via new migration v2.5.4_0820_tag_value_usage_index.sql and init.sql. Benchmark at capacity limits (100 defs / 100k values / 50k assignments) showed value-usage-count was a 102ms Seq Scan; with the index it becomes a 1.28ms Index Only Scan. Idempotent (IF NOT EXISTS). * feat(tag-mgmt): unified tag management for KB/agent/MCP/skill resources - Add tenant-scoped tag libraries, definitions, values and assignments - Wire tag chips and filters into knowledge base, agent and MCP pages - Add document tag projection ledger with provider sync - Clean up assignments when KB/agent/MCP/skill resources are deleted - Add preflight and migration scripts v2.5.0-v2.5.3 - Cache assignment reads on list pages to avoid per-row HTTP requests * fix(tag-mgmt): migrate tag assignment entries and enable tag search for mine agents * feat(tag-mgmt): complete unified tag assignment flows * feat(tag-management): unify repository tag filters * feat(tag-management): localize and search agent tags * feat(tag-management): unify repository tag filtering * fix(tag-management): migrate legacy agent categories * fix(tag-management): restore rebased tag UI * feat(tag-management): support no-value tags * fix(tag-management): unblock CI checks * chore(sonar): exclude mirrored tag SQL from CPD * test(tag-management): raise patch coverage * fix(tag-management): address review feedback * fix: migrate tag services after management split | 1 个月前 | |
feat: refactor label system (#3809) * fix(tag-mgmt): register legacy exception handlers + fix filter endpoint sync + add value usage index - backend/apps/app_factory.py: register handlers for legacy domain exceptions (UnauthorizedError->401, ForbiddenError->403, LimitExceededError->429, ValidationError->400, NotFoundException->404, DuplicateError->409, TagManagementConflictError->409, SignatureValidationError->401) so they no longer fall through to the generic 500 handler. Verified live: unauthenticated tag endpoints now return 401 instead of 500. - backend/apps/tag_management_app.py: convert filter_resource_tag_assignments from async/await to sync/_run to match the synchronous TagManagementDB.filter_authorized_resource_ids (which returns a dict, not a coroutine). Fixes TypeError -> HTTP 500 on the filter endpoint. - deploy/sql: add partial index idx_resource_tag_assignment_value (tenant_id, value_id, delete_flag) WHERE delete_flag='N' via new migration v2.5.4_0820_tag_value_usage_index.sql and init.sql. Benchmark at capacity limits (100 defs / 100k values / 50k assignments) showed value-usage-count was a 102ms Seq Scan; with the index it becomes a 1.28ms Index Only Scan. Idempotent (IF NOT EXISTS). * feat(tag-mgmt): unified tag management for KB/agent/MCP/skill resources - Add tenant-scoped tag libraries, definitions, values and assignments - Wire tag chips and filters into knowledge base, agent and MCP pages - Add document tag projection ledger with provider sync - Clean up assignments when KB/agent/MCP/skill resources are deleted - Add preflight and migration scripts v2.5.0-v2.5.3 - Cache assignment reads on list pages to avoid per-row HTTP requests * fix(tag-mgmt): migrate tag assignment entries and enable tag search for mine agents * feat(tag-mgmt): complete unified tag assignment flows * feat(tag-management): unify repository tag filters * feat(tag-management): localize and search agent tags * feat(tag-management): unify repository tag filtering * fix(tag-management): migrate legacy agent categories * fix(tag-management): restore rebased tag UI * feat(tag-management): support no-value tags * fix(tag-management): unblock CI checks * chore(sonar): exclude mirrored tag SQL from CPD * test(tag-management): raise patch coverage * fix(tag-management): address review feedback * fix: migrate tag services after management split | 1 个月前 | |
Feat: bundled default agents (#3899) * 调整mcp添加mcp和编辑页面，与mcp配置页面保持一致； mcp容器化启动点击后就展示日志，配置页面和仓库页面都修改； 修复mcp服务更新后，无法刷新工具的问题； * mcp仓库增加分页； fix test case * fix test case * fix test case * Update custom.json * 修复本地镜像上传部署日志显示问题 * fix bug * fix bug * add test case * add test case * 删除mcp市场 * 优化前端页面 * Update custom.json * Normalize custom locale file endings * Fix MCP registry endpoint typing * Remove obsolete MCP registry frontend code * 修改本地镜像上传MCP错误提示 * 修复mcp提交审核后不及时显示问题 * 修复api转mcp服务切换租户添加会导致原有工具列表被清空的问题 * 修复API转MCP后工具列表未同步 * 恢复工具手动刷新逻辑 * 避免API转MCP工具因扫描失败被隐藏 * docs(agents): define bundled official agent design Document industry-specific official agent packages, reserved platform templates, startup synchronization, repository visibility, and tenant copy permissions. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * docs(agents): add bundled agent implementation plan Break the approved industry-specific official agent design into test-first backend, repository, frontend, and deployment tasks. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * docs(agents): add Chinese design and plan Provide Chinese versions of the approved bundled official agent design and implementation plan. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * feat(agents): add official bundle sync foundation Support multi-profile official agent bundles with safe ZIP loading and idempotent synchronization into the reserved platform repository. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * feat(agents): expose official listings in repository Merge selected official listings into repository reads, keep platform templates read-only through tenant scoping, and trigger synchronization at startup or through the deployment script. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * feat(agents): mark official listings in clients Show official repository entries as read-only templates in the UI and inject selected bundle directories into Docker and Kubernetes deployments. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * feat(deploy): select official agent profiles offline Allow offline package builds to retain only explicitly selected official agent profiles and emit the runtime official-agent configuration. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agents): isolate bundle skill validation Resolve official bundle skill entries with a local model so repository service test doubles and runtime imports cannot corrupt the Pydantic forward reference. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * feat(deploy): sync official agents during installation Run official agent synchronization after Docker and Kubernetes deployments become ready, while retaining startup synchronization as an idempotent fallback. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * feat(deploy): let users select agent categories Fetch the official agent catalog during installation, scan its category directories, and persist the user's multi-category selection for Docker and Kubernetes deployment. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * feat(agents): install official repository dependencies Route official repository imports through tenant-level MCP, Skill, and knowledge-base preparation while preserving ordinary imports. Add ZIP and directory bundle loading and retain the current Agent service with only the required skill-link helpers. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agents): resolve bundles by repository agent name Use the official repository name as the bundle directory key and restore the normal listing content value. Keep bundle lookup aligned with the contract that the bundle folder and root Agent name are identical. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * feat(deploy): separate official agent deployment Move official Agent resource selection and synchronization out of the main Nexent installation flow. Add a standalone Docker/Kubernetes/local deployment entry, keep official repository visibility independent of startup profiles, and preserve tenant-level installation for user copies. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * chore(deploy): mark official agent entry executable Allow the standalone official Agent deployment entry to run directly in Git-based deployment environments. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(deploy): accept host paths for official agents Copy local official Agent resources through the running config container and explicitly synchronize the mounted container directory. Remove the conflicting read-only submount so Windows host paths can be used after Nexent is deployed. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(deploy): preserve container paths in git bash Disable MSYS path conversion for Docker and Kubernetes sync arguments so mounted Linux paths are not rewritten into Windows paths. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(repository): resolve official listings during import Allow repository prechecks and imports to fall back to the reserved official tenant so shared official listings can be copied by business tenants. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(repository): report official import requirements Build official repository precheck items from the mounted bundle so copy dialogs show model, knowledge base, MCP, Skill, and tool availability instead of an empty list. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agents): keep official bundle keys stable Store the Bundle directory key in official repository listings and repair existing official records during synchronization so prechecks and imports reload the correct mounted Bundle. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agents): resolve bundles inside profiles Allow official installation and precheck to locate directory, JSON, and ZIP bundles nested under selected profile directories. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agents): ignore skill archives during bundle scan Keep Skill ZIP payloads from being misclassified as standalone official Agent bundles during profile synchronization. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agents): diagnose official bundle lookup Log the resolved official bundle path and validation target so runtime lookup failures can be distinguished from missing mounted resources. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(deploy): pin official bundle path in container Override host-local OFFICIAL_AGENTS_PATH values from backend/.env with the mounted container path so repository prechecks can resolve official bundles. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * feat(repository): choose tenant models during official copy Show tenant-configured language and embedding models in the repository copy dialog and pass the selected IDs through the official install path. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(repository): preserve official flag for model selection Expose the publisher tenant in repository summaries and use it as a fallback so official copy dialogs always show tenant model selectors. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(repository): preserve publisher on summary listings Restore the publisher tenant on lightweight repository records so official listings reach the copy dialog with the official flag. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agents): apply official skill resolutions Honor the copy dialog choice to reuse an existing tenant Skill or create a renamed Skill when installing an official agent. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(official-agents): ensure dependencies before reuse Prepare official knowledge bases and other dependencies even when the root agent already exists, so partial installs can be repaired instead of being skipped. Add runtime logs for official repository routing and bundle dependency counts. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agents): honor skill conflict resolutions Evaluate official Skill reuse or rename choices before raising duplicate errors, so dependency preparation can continue to knowledge base creation and Agent import. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(official-agents): repair reused knowledge references Update existing official Agent tool instances after resolving a tenant knowledge base, so earlier partial installs no longer keep the bundle-local kb key. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(official-agents): isolate user agent copies Treat official dependencies as tenant-scoped while keeping copied Agents user-scoped. Create a uniquely named visible copy when another user already owns the bundle's root Agent. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(official-agents): share tenant knowledge bases Make official knowledge bases visible to every group in the tenant while keeping them read-only, and show bundle knowledge base display names instead of logical placeholders during import precheck. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * feat(official-agents): label copies by email Use the current account email in copied official Agent and Skill display names while retaining private technical identifiers for tenant uniqueness. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent-repository): hide official publisher label Hide the publisher text below the official badge for official Agent listings while preserving author display for regular listings. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent-repository): reuse existing official embeddings Hide embedding model selection when all official knowledge bases already exist in the tenant and let the backend reuse their configured models. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent-repository): block official copy without embeddings Show a clear tenant embedding-model requirement and prevent official knowledge-base installation from starting when no usable embedding model is configured. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent-repository): validate official kb embedding model Treat an official knowledge base as reusable only when its tenant embedding model still exists and is available, while leaving ordinary repository imports unchanged. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * chore(deploy): remove official profile env setting Keep profile selection in the standalone official-agent deployment flow instead of the main environment template. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * chore(deploy): remove legacy official profile variable Keep official agent profile selection exclusively in the standalone deployment script. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * chore(k8s): remove unused market backend config Remove the obsolete external market backend address from Kubernetes deployment values and rendering. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * chore(docs): remove bundled agent plans from code repo Keep bundled default agent design documents in the centralized nexent-doc archive instead of the business repository. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent-import): use migrated agent management service Replace stale services.agent_service imports in the official agent installer with the migrated agent management entry points so repository imports can complete after the agent service refactor. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent-import): use migrated knowledge base service Replace the removed vectordatabase_service import in official agent knowledge-base installation with the migrated knowledge-base and model management services. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent-repository): refresh mine agents after copy Switch to the mine tab and refresh its query after a repository copy succeeds so the created or reused Agent is immediately visible. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(official-agents): label copied agents with user email Append the current user's email to official Agent display names for both new installs and idempotent retries. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent-import): import model status enum Allow repository import precheck to evaluate tenant model availability without raising a NameError. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(official-agents): create unique copies on name conflicts Match ordinary repository imports by always creating official Agent copies and generating tenant-scoped unique names while preserving tenant dependency reuse. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * feat(official-agents): add default marketplace tags Populate category tags in official agent bundle metadata so synchronized repository listings and local marketplace submissions have default labels. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(official-agents): preserve default tags on import Apply official Bundle category tags to the newly imported tenant Agent after resolving tenant-specific tag values. Keep ordinary repository imports unchanged. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(official-agents): remove forced default tags Keep official Agent tags empty so users choose from the tenant tag definitions when applying for listing. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(tags): allow tenant users to read tag definitions Keep tag library mutations restricted to management roles while allowing authenticated tenant users to load tag choices for repository listing forms. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent-repository): render tag limit in hint Pass the tag limit to the localized hint so the UI renders the numeric value instead of the raw interpolation placeholder. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * test: align regression tests with migrated services Update stale mocks, assertions, and service paths after the management-service migration. Cover official agent knowledge-base reuse, skill resolution, MCP headers, tag reads, and asynchronous tool refresh. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * docs: add official agent deployment guide Document online, local, offline, Docker, and Kubernetes deployment of official Agent bundles, including profile selection, synchronization, verification, and troubleshooting. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * docs: document agent export bundle conversion Add the conversion workflow from Nexent-exported Agent JSON or ZIP to a profile-scoped official bundle, including Skill and knowledge-base seed handling. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * test: mock tenant MCP endpoint in tool tests Patch the tenant-scoped local MCP endpoint used by get_all_mcp_tools instead of the obsolete base URL mock. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * docs: remove official agent deployment guide Withdraw the deployment guide from the feature branch as requested. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * test: cover official agent synchronization Add unit coverage for source-agent materialization, repository upsert, and failure isolation during official bundle synchronization. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * test: cover official repository import flow Exercise official listing fallback lookup, bundle precheck, installation outcomes, and download accounting branches. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * test: cover official agent bundle loading Exercise profile validation, safe archive handling, skill and knowledge-base loading, and directory bundle synchronization paths. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * test: stub model parameter filter for official agent tests Keep the isolated consts.model test module compatible with the naming service import chain used in CI. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * test: cover official agent service edge cases Add coverage for bundle discovery, nested archives, resource loading failures, partial KB repair, and existing-agent installation paths. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * test: cover tenant MCP routing branches Exercise tenant refresh skips, app construction fallbacks, router authorization and lazy initialization, and MCP startup cleanup paths. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * test: cover repository import precheck branches Test embedding model availability and official knowledge-base name fallback during repository import prechecks. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * test: cover official agent bundle defaults Verify official bundle card fields derive from the root agent and fall back to safe defaults when metadata is absent. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(mcp): avoid duplicate tool cleanup on delete Clean up MCP tools exactly once during deletion and use the shared outer-apis name for OpenAPI services. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * chore(deploy): remove obsolete agent TUI branches Align common.sh with develop after official agent deployment was separated from the main installation flow. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * chore(official-agents): keep local snapshots out of remote Stop tracking the two local official agent snapshots while preserving the files for local deployment and testing. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * chore(agents): remove unused attachment fallback Revert the unrelated MinIO bucket fallback that is not used by official agent installation. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * chore(deploy): remove redundant official agent directory setup Keep official agent directory creation in the standalone deployment flow and restore deploy.sh to develop behavior. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * chore(deploy): remove obsolete official agent env example Restore the environment example after official agent deployment moved to the standalone flow. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * chore(deploy): remove official agent helm wiring Restore Kubernetes deployment templates to develop and keep official agent installation outside the main Nexent deployment flow. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * chore(offline): remove obsolete official agent packaging Restore offline package generation to develop and remove the unused official-agent profile filtering path. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * feat(agent): manage official agent visibility Add tenant-scoped visibility overrides and super-admin management APIs for official agent templates. Provide resource-management UI with visibility switch and global template deletion while preserving tenant copies. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * refactor(agent): remove tenant visibility controls Keep official-agent management global and remove the tenant visibility table, migration, switch, and filtering. Super admins can still delete official templates while tenant copies and dependencies remain untouched. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent): restrict official agent management to super admins Use the authenticated global role for official agent management APIs and hide the management control from non-super-admin users. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent): confirm official agent deletion in modal Replace the inline confirmation with a descriptive modal before deleting the official template and bundle files. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent): resolve official knowledge base conflicts Allow official agent imports to reuse or create a tenant knowledge base when names collide, and pass the selected resolution through the repository copy flow. Keep ordinary repository imports on the existing index-name path and add regression coverage. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent): separate knowledge base resolution panel Render official knowledge base reuse or create-new choices as a sibling panel to skill conflicts and model selection. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent): align knowledge base conflict styling Match the official knowledge base conflict panel to the skill conflict layout with white cards and separate titles and options. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent): show accurate dependency status Prefer repository requirement reason codes over generic activation labels so existing knowledge bases with unavailable embedding models are not shown as unactivated. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent): show knowledge base copy name Display the expected copy name beside the create-new knowledge base option, matching the skill conflict experience. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent): remove copy name parentheses Display the knowledge base copy name without surrounding parentheses in the repository import dialog. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent): treat duplicate skills as resolvable Keep duplicate skills in the dedicated reuse-or-rename panel instead of also classifying them as unavailable dependencies. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent): show duplicate knowledge bases as conflicts Keep same-name knowledge bases in the abnormal dependency section with a conflict label, matching duplicate skill behavior while preserving reuse-or-create choices. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent): avoid duplicate knowledge base status Exclude knowledge bases requiring conflict resolution from the available dependency section so they appear only in the conflict section. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent): align official import arguments Use the authenticated tenant and user context when importing official agents instead of passing unsupported arguments to import_agent_impl. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(deploy): support Unicode official agent profiles Allow official agent profile directory names such as Chinese names while retaining path traversal protection. Add coverage for Unicode profile parsing. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(deploy): support nested official agent profiles Add a profile-root option so Hub layouts such as AgentsHub/行业智能体/金融 can be selected without treating the nested directory as a Git repository URL. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(deploy): limit Hub checkout to selected profiles Skip whole-repository Git LFS checkout and sparsely materialize only the selected profile paths. This prevents unrelated unavailable LFS objects from blocking official agent deployment. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(deploy): materialize sparse official agent checkout Update the worktree explicitly after configuring sparse checkout for no-checkout Hub clones, so nested Unicode profiles are available to the synchronization step. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent-sync): avoid logging expected missing agents Use a non-raising agent lookup during official bundle synchronization so first-time provisioning does not emit database error logs. Preserve the existing raising lookup for callers that require strict lookup semantics and add coverage for both paths. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(deploy): preserve official profile directories Copy selected profile contents into an explicit profile directory in the target mount so synchronization can resolve paths such as /mnt/nexent/official-agents/金融. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent-repository): hide official take-down action from admins Keep official agent management in the super-admin resource page and prevent tenant administrators from seeing the ordinary repository take-down action on official listings. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(official-agents): preserve container paths in sync script Clean selected profiles before copying and disable MSYS path conversion so Windows Git Bash does not leave stale nested bundles behind. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(official-agents): convert Git Bash copy sources Keep container paths protected from MSYS conversion while converting temporary local sources to Docker-readable Windows paths. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(official-agents): publish Nexent as repository author Use Nexent as the marketplace author for official bundles without changing the source agent snapshot metadata. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent-repository): restore official listing badge Render the official badge in the unified agent repository card while preserving the existing version badge and listing behavior. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent-repository): hide activation for name conflicts Keep skill and knowledge base name conflicts in the resolution flow instead of offering an activation action. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent-repository): prioritize dependency name conflicts Detect skill duplicates by their precheck reason and show knowledge base conflicts before availability errors, so conflicting resources do not expose activation actions. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent-repository): show conflict reason without activation Use the conflict-prioritized reason label in the non-action status branch so duplicate knowledge bases are not shown as unavailable. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * test(agent-repository): update knowledge resolution coverage Align repository and official-agent tests with knowledge-base resolution payloads and the embedding availability checks introduced by official imports. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * test(agent-repository): cover official management branches Add coverage for repository fallback errors, official listing management, bundle deletion, and invalid official bundle paths. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * chore(official-agents): exclude document writing snapshot Remove the document writing official agent snapshot from version control while preserving the local deployment asset. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * docs(deployment): add official agent deployment guide Document independent official-agent deployment from Agent Hub, local directories, and offline archives, including profile selection, verification, and troubleshooting. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * docs(deployment): document official agent deletion Refine the official-agent guide to match the Chinese documentation style and explain super-admin template deletion, preserved tenant copies, and post-deletion verification. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * docs(deployment): align official agent page style Remove the page navigation block so the official-agent deployment guide follows the existing deployment documentation style. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * docs(deployment): remove page metadata Keep the official-agent deployment guide consistent with deployment documents that use a plain Markdown heading. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * docs(config): document official agent variables Add the official-agent resource path and optional profile fallback to the environment template while keeping profile selection in the independent deployment command. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * refactor(mcp): move tenant URL builder to utils Keep MCP configuration constants in consts while moving tenant-scoped URL construction into a utility module. Update all production callers and the focused test to use the new location. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * refactor(agent): unify official identity under system IDs Use one system tenant and user identity for official agent synchronization and repository visibility. Keep deprecated aliases for compatibility while updating frontend detection and tests. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent): use system identity for official agents Replace the separate official tenant and user identifiers with the shared system identity and update all related repository, sync, frontend, and test references. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * docs(deployment): reorder official agent sections Place profile redeployment guidance before troubleshooting and keep the section numbering sequential. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * refactor(agent): sync official bundles through local API Replace the backend script entrypoint with a loopback-only synchronization API and make Docker and Kubernetes deployment scripts call it from inside the config container. Keep synchronization business logic in the service layer. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent): avoid MSYS path conversion in sync request Use the service default official-agent directory instead of passing the container path through docker exec curl, which MSYS rewrites on Windows Git Bash. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent-sync): prevent user-controlled bundle paths Remove the base_dir query parameter from the internal synchronization API so bundle loading always uses the configured container path. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent-sync): resolve profiles from mounted directories Avoid concatenating the selected profile directly into a filesystem path and cover Unicode profile directory resolution. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex * fix(agent-sync): scan configured root before filtering profiles Avoid recursively traversing a directory derived from user-selected profile input by scanning the configured bundle root once and filtering descendants by their top-level profile. Co-authored-by: Codex <noreply@openai.com> Generated-by: gpt-5-codex | 19 天前 | |
feat(logging):Security Audit Logging (#4015) * feat: 添加安全审计服务并在关键操作记录审计日志 新增 audit_service 服务用于记录安全审计事件，在用户注册、登录、登出、密码修改、OAuth/ CAS 相关操作、令牌管理、账户撤销等关键安全操作中记录审计日志，同时新增对应测试用例确保审计功能正常工作。 * feat: 为 API 密钥操作添加上下文安全审计日志 在 API 密钥应用和北向应用中，为刷新、撤销 API 密钥以及批量创建 API 用户等操作添加安全审计日志记录，仅记录非敏感的目标用户信息、操作人信息和请求标识，避免泄露明文 API 密钥。同时新增对应的测试用例验证审计日志的正确性和安全性。 * feat: 为用户、租户、邀请和群组操作添加安全审计日志 在多个API端点（用户、租户、邀请、群组相关的创建、更新、删除等操作）中添加了安全审计日志记录，同时新增了对应的测试用例来验证审计日志的正确性。 | 19 天前 | |
♻️ 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. | 18 天前 | |
✨ Support full thread management (#3917) * 📃 Merge cursor rules into universal AGENTS.md and skills * ✨ Support full thread management * ✨ Support full thread management phase2 * 🧪 Add test files * 🧪 Add test files * 🧪 Add test files * ✨ Thread management fulfilling platform constraint * 🧪 Add test files * 🧪 Add thread interface * 🧪 Add test files | 1 个月前 | |
feat(audit): add security audit logging to backend management APIs (#4055) * feat: 为模型管理接口添加安全审计日志记录 实现了模型创建、更新、删除、批量操作等接口的安全审计日志功能，过滤了敏感凭证信息，确保审计日志安全合规。新增了审计安全字段过滤工具函数，补充了对应的测试用例验证审计日志的正确性和安全性。 * feat: 为多个接口添加安全审计日志记录 为agent和agent_repository相关的API接口添加安全审计事件记录，包括代理更新、图标上传、删除、导出、导入、版本发布/回滚/更新/删除等操作，同时补充对应的测试用例验证审计日志的正确性，确保敏感数据不被记录。 * feat: 为MCP和技能相关接口添加上下文安全审计日志 为tool、mcp、remote_mcp、skill模块的所有关键增删改接口添加安全审计日志，记录操作人、资源信息等关键字段，同时避免记录敏感信息如凭证、密钥等。新增对应的测试用例验证审计日志的正确性，确保敏感数据不会被泄露。 * feat: 添加安全审计日志并限制审计详情列表长度 在多个服务端点添加安全审计日志，记录关键操作信息 同时统一审计详情列表的长度限制为20，防止日志被恶意payload撑爆 * feat: 为配置相关接口添加安全审计日志记录 为 config_sync_app 和 memory_config_app 的配置操作接口添加安全审计事件记录，记录操作人、租户、操作类型和相关字段信息，同时更新测试用例验证审计日志的正确性，确保敏感配置值不被记录。 * test: 为上传测试用例添加 http_request 参数默认值 为测试用例中的 upload_files 调用添加 http_request=None 参数，避免测试时可能出现的未定义错误 | 7 天前 | |
feat(logging):Security Audit Logging (#4015) * feat: 添加安全审计服务并在关键操作记录审计日志 新增 audit_service 服务用于记录安全审计事件，在用户注册、登录、登出、密码修改、OAuth/ CAS 相关操作、令牌管理、账户撤销等关键安全操作中记录审计日志，同时新增对应测试用例确保审计功能正常工作。 * feat: 为 API 密钥操作添加上下文安全审计日志 在 API 密钥应用和北向应用中，为刷新、撤销 API 密钥以及批量创建 API 用户等操作添加安全审计日志记录，仅记录非敏感的目标用户信息、操作人信息和请求标识，避免泄露明文 API 密钥。同时新增对应的测试用例验证审计日志的正确性和安全性。 * feat: 为用户、租户、邀请和群组操作添加安全审计日志 在多个API端点（用户、租户、邀请、群组相关的创建、更新、删除等操作）中添加了安全审计日志记录，同时新增了对应的测试用例来验证审计日志的正确性。 | 19 天前 | |
0930需求-Nexent规格表：完善租户资源限制错误码、429响应及中英文提示 (#3966) * fix: standardize tenant resource limit errors * fix: roll back rejected tenant user registrations * fix: stabilize tenant limit test imports * test: import HTTPStatus in northbound tests * test: cover tenant resource limit error paths * config: make tenant resource limits configurable | 26 天前 | |
feat(logging):Security Audit Logging (#4015) * feat: 添加安全审计服务并在关键操作记录审计日志 新增 audit_service 服务用于记录安全审计事件，在用户注册、登录、登出、密码修改、OAuth/ CAS 相关操作、令牌管理、账户撤销等关键安全操作中记录审计日志，同时新增对应测试用例确保审计功能正常工作。 * feat: 为 API 密钥操作添加上下文安全审计日志 在 API 密钥应用和北向应用中，为刷新、撤销 API 密钥以及批量创建 API 用户等操作添加安全审计日志记录，仅记录非敏感的目标用户信息、操作人信息和请求标识，避免泄露明文 API 密钥。同时新增对应的测试用例验证审计日志的正确性和安全性。 * feat: 为用户、租户、邀请和群组操作添加安全审计日志 在多个API端点（用户、租户、邀请、群组相关的创建、更新、删除等操作）中添加了安全审计日志记录，同时新增了对应的测试用例来验证审计日志的正确性。 | 19 天前 | |
feat(audit): add security audit logging to backend management APIs (#4055) * feat: 为模型管理接口添加安全审计日志记录 实现了模型创建、更新、删除、批量操作等接口的安全审计日志功能，过滤了敏感凭证信息，确保审计日志安全合规。新增了审计安全字段过滤工具函数，补充了对应的测试用例验证审计日志的正确性和安全性。 * feat: 为多个接口添加安全审计日志记录 为agent和agent_repository相关的API接口添加安全审计事件记录，包括代理更新、图标上传、删除、导出、导入、版本发布/回滚/更新/删除等操作，同时补充对应的测试用例验证审计日志的正确性，确保敏感数据不被记录。 * feat: 为MCP和技能相关接口添加上下文安全审计日志 为tool、mcp、remote_mcp、skill模块的所有关键增删改接口添加安全审计日志，记录操作人、资源信息等关键字段，同时避免记录敏感信息如凭证、密钥等。新增对应的测试用例验证审计日志的正确性，确保敏感数据不会被泄露。 * feat: 添加安全审计日志并限制审计详情列表长度 在多个服务端点添加安全审计日志，记录关键操作信息 同时统一审计详情列表的长度限制为20，防止日志被恶意payload撑爆 * feat: 为配置相关接口添加安全审计日志记录 为 config_sync_app 和 memory_config_app 的配置操作接口添加安全审计事件记录，记录操作人、租户、操作类型和相关字段信息，同时更新测试用例验证审计日志的正确性，确保敏感配置值不被记录。 * test: 为上传测试用例添加 http_request 参数默认值 为测试用例中的 upload_files 调用添加 http_request=None 参数，避免测试时可能出现的未定义错误 | 7 天前 | |
import ali and volc stt model (#2934) * improve codecov * implement asr * import ali qwen realtime tts model * import volc realtime tts model * improve code readability * improve code readability * add test files * improve code readability and maintainability by adding comments and improving variable names. * improve test files * improve test files * improve test files * add test code for ali voice model to improve coverage * add test code for ali voice model to improve coverage * add test code for voice model to improve coverage * add test code for voice model to improve coverage * add test code for voice model to improve coverage * add test code for voice model to improve coverage * add test code for voice model to improve coverage * add test code for voice model to improve coverage * add test code for voice model to improve coverage * add test code for voice model to improve coverage * add test code for voice model to improve coverage * save stt only * add test files * add user guide for voice model and Modify the prompt in the base_utl input box of the voice model | 5 个月前 |
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