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7 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
Daoyuan Li
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74392e1470
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Fix require_mention gating on whitespace-only bot_login/mention_login (#4055)
github.bot_login and trigger.mention_login were read raw in the require_mention precedence chain, so a whitespace-only value (e.g. " ") never fell through to the working fallback the chain documents - Python truthiness lets " " win an `or` chain over agent.name or the operator default. The third link (channels.github.default_mention_login) was already correctly normalized and pinned by test_operator_default_blank_string_treated_as_none; this closes the gap for the other two by normalizing GitHubTriggerConfig.mention_login and GitHubAgentConfig.bot_login once, at the config layer, via a field_validator mirroring the pattern already used elsewhere in the config package. |
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Zheng Feng
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dcb2e687d5
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feat(channels): add GitHub as a webhook-driven channel (#3754)
* feat(channels): add GitHub event-driven agents (#3754) Add a webhook-driven GitHub channel with fail-closed webhook routing, deterministic per-agent PR/issue threads, mention-gated trigger fan-out, GitHub App token injection for sandboxed gh/git commands, and backend/AGENTS.md documentation. * fix(llm-middleware): classify bare IndexError as transient Upstream chat providers occasionally return 200 OK with an empty generations list (observed against Volces "coding" on ark.cn-beijing.volces.com). When that happens, langchain_core.language_models.chat_models.ainvoke raises ``IndexError: list index out of range`` at ``llm_result.generations[0][0].message`` and kills the run. Treat a bare IndexError reaching the middleware as a transient upstream-payload glitch and route it through the existing retry/backoff path instead of failing the whole agent run. The retry budget and backoff schedule are unchanged. Adds three regression tests covering the classifier and both the recover-on-retry and exhausted-retries paths. * fix(runtime): ignore stale LLM fallback markers from prior runs When a run on a thread ends with the LLM-error-handling middleware emitting a `deerflow_error_fallback`-marked AIMessage (e.g. after the IndexError empty-generations classification fix lands), that message is persisted to the thread's checkpoint as part of the messages channel. LangGraph replays the full message history in `stream_mode="values"` chunks, so every subsequent run on the same thread re-streams the stale fallback marker — and the worker's chunk scanner faithfully picks it up, flipping `RunStatus.success` to `RunStatus.error` for runs that themselves had no LLM failure at all. Snapshot the set of pre-existing message ids from the pre-run checkpoint and thread it through `_extract_llm_error_fallback_message` / `_try_extract_from_message` as a filter. Markers on history messages are ignored; markers on fresh messages produced during this run still trip the error path. Falls back to an empty set when the checkpointer is absent or the snapshot can't be captured, preserving the prior behavior on first-run / no-state paths. Adds unit tests for the new filter (helper-level and `_collect_pre_existing_message_ids`) plus an integration test exercising the full `run_agent` path with a stale history checkpointer. * fix(channels): make github channel fire-and-forget to avoid httpx.ReadTimeout on long runs GitHub agent runs (clone -> edit -> test -> push -> PR) routinely exceed the langgraph_sdk default 300s read deadline. The manager's runs.wait call kept an HTTP stream open for the entire run lifetime, so the long run blew up with httpx.ReadTimeout and the outer except branch then released the dedupe key and emitted a false 'internal error' outbound. The GitHub channel's outbound send is log-only by design: agents post to the issue/PR via the gh CLI in the sandbox when they choose to comment or create a PR. There is nothing for the manager to ferry back, so the long-poll was pure overhead. This change adds ChannelRunPolicy.fire_and_forget (default False) and sets it True for the github channel. When fire_and_forget is True, _handle_chat dispatches via client.runs.create (short POST, returns once the run is pending) instead of client.runs.wait, and skips the response-extraction + outbound-publish block. ConflictError on a busy thread still trips the standard THREAD_BUSY_MESSAGE path so behavior on the busy case is preserved for any future non-github fire-and-forget channel. Other (non-github) channels are unchanged: their policy defaults fire_and_forget=False and they continue to dispatch via runs.wait. Adds 6 regression tests in tests/test_channels.py::TestGithubFireAndForget: - Default ChannelRunPolicy.fire_and_forget is False. - The github policy registers fire_and_forget=True. - github inbound calls runs.create, not runs.wait, with the right kwargs. - github inbound publishes no outbound on success. - ConflictError from runs.create still emits THREAD_BUSY_MESSAGE. - Non-github channels (slack) still dispatch via runs.wait. * test(lead-agent): accept user_id kwarg in skill-policy test stubs The two GitHub-channel tests added in #3754 stubbed _load_enabled_skills_for_tool_policy with a lambda that only accepted `available_skills` and `app_config`, but the real function (and its call site in agent.py) also passes `user_id`. This raised TypeError on every run, failing backend-unit-tests. Add `user_id=None` to match the three sibling stubs in the same file. * refactor(gateway): disambiguate context-key set names The two frozensets _INTERNAL_ONLY_CONTEXT_KEYS and _CONTEXT_ONLY_KEYS shared a confusable "CONTEXT_ONLY" token in different orders, and the first broke the _CONTEXT_<X>_KEYS pattern of its sibling _CONTEXT_CONFIGURABLE_KEYS. Rename to make the distinct axes explicit: _CONTEXT_INTERNAL_CALLER_KEYS - WHO: internal callers (scheduler) only _CONTEXT_RUNTIME_ONLY_KEYS - WHERE: runtime context only, never configurable Pure rename, no behavior change. |
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hataa
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b3c2cc42cf
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fix(agents): require config.yaml in resolve_agent_dir to skip memory-only directories (#3390) (#3481)
When memory is enabled, the first conversation with a legacy shared agent creates a per-user agent directory containing only memory.json (no config.yaml). On the second turn, resolve_agent_dir() returned this incomplete directory, causing load_agent_config() to fail with "Agent config not found". Require config.yaml to exist alongside the directory for both the per-user and legacy paths, so that memory-only directories fall through correctly. This aligns resolve_agent_dir with the existing config.yaml check in list_custom_agents. Refs: https://github.com/bytedance/deer-flow/issues/3390 |
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yangzheli
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59c4a3f0a4
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feat(agent): add custom-agent self-updates with user isolation (#2713)
* feat(agent): add update_agent tool for in-chat custom-agent self-updates (#2616) Custom agents had no built-in way to persist updates to their own SOUL.md / config.yaml from a normal chat — `setup_agent` was only bound during the bootstrap flow, so when the user asked the agent to refine its description or personality, the agent would shell out via bash/write_file and the edits landed in a temporary sandbox/tool workspace instead of `{base_dir}/agents/{agent_name}/`. Changes: - New `update_agent` builtin tool with partial-update semantics (only the fields you pass are written) and atomic temp-file + os.replace writes so a failed update never corrupts existing SOUL.md / config.yaml. - Lead agent now binds `update_agent` in the non-bootstrap path whenever `agent_name` is set in the runtime context. Default agent (no agent_name) and bootstrap flow are unchanged. - New `<self_update>` system-prompt section is injected for custom agents, instructing them to use `update_agent` — and explicitly NOT bash / write_file — to persist self-updates. - Tests: 11 new cases in `tests/test_update_agent_tool.py` covering validation (missing/invalid agent_name, unknown agent, no fields), partial updates (soul-only, description-only, skills=[] vs omitted), no-op detection, atomic-write safety, and AgentConfig round-tripping; plus 2 new cases in `tests/test_lead_agent_prompt.py` covering the self-update prompt section. - Docs: updated backend/CLAUDE.md builtin tools list and tools.mdx (en/zh) with the new tool description. * feat(agent): isolate custom agents per user Store custom agent definitions under the effective user, keep legacy agents readable until migration, and cover API/tool/migration behavior with tests. Co-authored-by: Cursor <cursoragent@cursor.com> * feat: consistent write/delete targets & add --user-id to migration --------- Co-authored-by: Cursor <cursoragent@cursor.com> |
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Hinotobi
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2176b2bbfc
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fix: validate bootstrap agent names before filesystem writes (#2274)
* fix: validate bootstrap agent names before filesystem writes * fix: tighten bootstrap agent-name validation |
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knukn
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f8fb8d6fb1
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feat/per agent skill filter (#1650)
* feat(agent): 为AgentConfig添加skills字段并更新lead_agent系统提示 在AgentConfig中添加skills字段以支持配置agent可用技能 更新lead_agent的系统提示模板以包含可用技能信息 * fix: resolve agent skill configuration edge cases and add tests * Update backend/packages/harness/deerflow/agents/lead_agent/prompt.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * refactor(agent): address PR review comments for skills configuration - Add detailed docstring to `skills` field in `AgentConfig` to clarify the semantics of `None` vs `[]`. - Add unit tests in `test_custom_agent.py` to verify `load_agent_config()` correctly parses omitted skills and explicit empty lists. - Fix `test_make_lead_agent_empty_skills_passed_correctly` to include `agent_name` in the runtime config, ensuring it exercises the real code path. * docs: 添加关于按代理过滤技能的配置说明 在配置示例文件和文档中添加说明，解释如何通过代理的config.yaml文件限制加载的技能 --------- Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> |
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DanielWalnut
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76803b826f
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refactor: split backend into harness (deerflow.*) and app (app.*) (#1131)
* refactor: extract shared utils to break harness→app cross-layer imports Move _validate_skill_frontmatter to src/skills/validation.py and CONVERTIBLE_EXTENSIONS + convert_file_to_markdown to src/utils/file_conversion.py. This eliminates the two reverse dependencies from client.py (harness layer) into gateway/routers/ (app layer), preparing for the harness/app package split. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * refactor: split backend/src into harness (deerflow.*) and app (app.*) Physically split the monolithic backend/src/ package into two layers: - **Harness** (`packages/harness/deerflow/`): publishable agent framework package with import prefix `deerflow.*`. Contains agents, sandbox, tools, models, MCP, skills, config, and all core infrastructure. - **App** (`app/`): unpublished application code with import prefix `app.*`. Contains gateway (FastAPI REST API) and channels (IM integrations). Key changes: - Move 13 harness modules to packages/harness/deerflow/ via git mv - Move gateway + channels to app/ via git mv - Rename all imports: src.* → deerflow.* (harness) / app.* (app layer) - Set up uv workspace with deerflow-harness as workspace member - Update langgraph.json, config.example.yaml, all scripts, Docker files - Add build-system (hatchling) to harness pyproject.toml - Add PYTHONPATH=. to gateway startup commands for app.* resolution - Update ruff.toml with known-first-party for import sorting - Update all documentation to reflect new directory structure Boundary rule enforced: harness code never imports from app. All 429 tests pass. Lint clean. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * chore: add harness→app boundary check test and update docs Add test_harness_boundary.py that scans all Python files in packages/harness/deerflow/ and fails if any `from app.*` or `import app.*` statement is found. This enforces the architectural rule that the harness layer never depends on the app layer. Update CLAUDE.md to document the harness/app split architecture, import conventions, and the boundary enforcement test. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat: add config versioning with auto-upgrade on startup When config.example.yaml schema changes, developers' local config.yaml files can silently become outdated. This adds a config_version field and auto-upgrade mechanism so breaking changes (like src.* → deerflow.* renames) are applied automatically before services start. - Add config_version: 1 to config.example.yaml - Add startup version check warning in AppConfig.from_file() - Add scripts/config-upgrade.sh with migration registry for value replacements - Add `make config-upgrade` target - Auto-run config-upgrade in serve.sh and start-daemon.sh before starting services - Add config error hints in service failure messages Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix comments * fix: update src.* import in test_sandbox_tools_security to deerflow.* Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: handle empty config and search parent dirs for config.example.yaml Address Copilot review comments on PR #1131: - Guard against yaml.safe_load() returning None for empty config files - Search parent directories for config.example.yaml instead of only looking next to config.yaml, fixing detection in common setups Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: correct skills root path depth and config_version type coercion - loader.py: fix get_skills_root_path() to use 5 parent levels (was 3) after harness split, file lives at packages/harness/deerflow/skills/ so parent×3 resolved to backend/packages/harness/ instead of backend/ - app_config.py: coerce config_version to int() before comparison in _check_config_version() to prevent TypeError when YAML stores value as string (e.g. config_version: "1") - tests: add regression tests for both fixes Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix: update test imports from src.* to deerflow.*/app.* after harness refactor Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> |