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8 Commits
| Author | SHA1 | Message | Date | |
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hataa
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266883b3dd
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fix(subagents): inherit summarization middleware and harden step capture (#3875 Phase 3) (#4009)
Phase 3 of #3875 — subagents previously inherited none of the lead's context-compaction, so a deep-research subagent (max_turns up to 150) could accumulate >1M cumulative input before max_turns/timeout/token_budget engaged, even after Phase 2's budget capped the pathological tail. - Gate the subagent runtime chain on the SAME ``app_config.summarization.enabled`` switch the lead reads (per maintainer guidance in #3875), via the shared ``create_summarization_middleware`` factory. One config covers both chains; no separate ``subagents.summarization`` field. No-op when summarization is off (factory returns None). - ``skip_memory_flush=True`` on the subagent path: the factory otherwise attaches ``memory_flush_hook`` (when memory.enabled), which flushes pre-compaction messages into durable memory keyed by thread_id. Subagents share the parent's thread_id, so without skipping the hook a subagent's internal turns would pollute the PARENT thread's durable memory (#3875 Phase 3 review point). - Harden ``capture_new_step_messages`` to tolerate history contraction: summarization rewrites the messages channel via ``RemoveMessage(id=REMOVE_ALL_MESSAGES)``, shrinking len(messages) below the step-capture cursor. Without a reset, every step appended after the compaction point was dropped until length overtook the stale cursor (#3845 interaction, maintainer validation point (a)). Cursor now resets to the new tail; id/content dedup prevents re-emitting pre-compaction steps. - Couple the DEFAULT token-budget ceiling to ``summarization.enabled`` (#3875 Phase 3 review point): 1M when compaction is on, 2M when off (preserves Phase 2's deliberate headroom for summarization-off deep-research runs that can exceed 1M). A user-set budget (global or per-agent) always wins regardless of the switch. Flagged tunable. The summarization middleware does not implement ``consume_stop_reason``, so the Phase 2 guard-cap stop-reason channel is unaffected. Refs: https://github.com/bytedance/deer-flow/issues/3875 |
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hataa
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c9fb9768d4
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fix(subagents): unify guardrail caps on additive stop_reason + add token_budget (#3875 Phase 2) (#3980)
Phase 2 of #3875. Two guardrail axes can end a subagent run early — the turn budget (GraphRecursionError) and the token budget (TokenBudgetMiddleware) — and both now surface *why* through one additive `subagent_stop_reason` field instead of a status enum. This completes and course-corrects Phase 1 (#3949), which shipped the turn-budget cap as a `max_turns_reached` status enum. The agreed Phase 2 design replaces that enum with an optional `stop_reason` field (token_capped | turn_capped | loop_capped): a new enum value would break v1 consumers, while an additive field is ignored by older frontends and ledger readers. `max_turns_reached` and SubagentStatus.MAX_TURNS_REACHED are removed. - subagents.token_budget config (default enabled, 2,000,000 tokens, warn 0.7) with per-agent override; TokenBudgetMiddleware is now attached in build_subagent_runtime_middlewares so the cost-ceiling backstop engages for every subagent. The hard-stop does not raise — it strips tool_calls and lets the run finish with a final answer, recording the cap on a per-run consume_stop_reason() accessor. - executor.py: on normal completion it reads consume_stop_reason() and stamps completed + token_capped when the budget fired; on GraphRecursionError it recovers the last AIMessage partial (completed + turn_capped) or, if nothing usable survived, failed + turn_capped. SubagentResult gains stop_reason. - status_contract.py / contracts/subagent_status_contract.json (v2) / frontend subtask-result.ts: additive subagent_stop_reason field, pinned by test_status_values_match_contract / test_stop_reason_values_match_contract. - task_tool.py + delegation_ledger.py: drop the max_turns_reached paths; the ledger captures stop_reason and renders model-facing "capped" guidance so the lead reuses a capped completion knowingly. The 2,000,000-token default is deliberately loose (tighten to taste) — it would have roughly halved the reported 4.4M burn while leaving legitimate deep-research runs (max_turns=150) room. Subagent summarization is a follow-up. |
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DanielWalnut
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05be7ea688
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fix(subagents): raise general-purpose max_turns to 150 and default timeout to 30min (#3610)
* fix(subagents): raise general-purpose max_turns to 150 and default timeout to 30min Deep-research subtasks failed out of the box with GraphRecursionError (Recursion limit of 100 reached): the built-in general-purpose subagent caps at max_turns=100. Raise it to 150 and bump the default subagent timeout from 900s (15min) to 1800s (30min) so the extra turns have time to run instead of shifting the failure to a timeout. The lead agent recursion_limit (100) is unchanged; the failures are subagent-only. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> * docs(subagents): clarify lead recursion_limit is independent of subagent max_turns Add comments at both lead recursion_limit=100 sites (gateway services + channel manager) explaining the lead's LangGraph super-step budget is separate from subagent depth, so the two 100s are not conflated. Comment-only, no behavior change. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> * docs(subagents): clarify built-in vs custom timeout scope; pin bash max_turns in test Review follow-ups: (1) clarify SubagentConfig docstring + global timeout field/comment that the 1800 default applies to built-in subagents (custom agents keep their own timeout_seconds); (2) pin bash.max_turns==60 in the defaults regression test so the config.example.yaml doc cannot drift; (3) rename test_default_timeout_preserved_when_no_config -> test_explicit_global_timeout_propagates_to_general_purpose since it intentionally exercises an explicit non-default 900. No runtime behavior change. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com> |
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KiteEater
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4ead2c6b19
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fix(config): reset config-backed singletons on hot reload (#2588)
* Fix stale config singletons on reload * fix(config): update checkpointer imports after runtime move * Fix config reload singleton mutation on validation failure --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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Xinmin Zeng
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30d619de08
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feat(subagents): support per-subagent skill loading and custom subagent types (#2253)
* feat(subagents): support per-subagent skill loading and custom subagent types (#2230) Add per-subagent skill configuration and custom subagent type registration, aligned with Codex's role-based config layering and per-session skill injection. Backend: - SubagentConfig gains `skills` field (None=all, []=none, list=whitelist) - New CustomSubagentConfig for user-defined subagent types in config.yaml - SubagentsAppConfig gains `custom_agents` section and `get_skills_for()` - Registry resolves custom agents with three-layer config precedence - SubagentExecutor loads skills per-session as conversation items (Codex pattern) - task_tool no longer appends skills to system_prompt - Lead agent system prompt dynamically lists all registered subagent types - setup_agent tool accepts optional skills parameter - Gateway agents API transparently passes skills in CRUD operations Frontend: - Agent/CreateAgentRequest/UpdateAgentRequest types include skills field - Agent card displays skills as badges alongside tool_groups Config: - config.example.yaml documents custom_agents and per-agent skills override Tests: - 40 new tests covering all skill config, custom agents, and registry logic - Existing tests updated for new get_skills_prompt_section signature Closes #2230 * fix: address review feedback on skills PR - Remove stale get_skills_prompt_section monkeypatches from test_task_tool_core_logic.py (task_tool no longer imports this function after skill injection moved to executor) - Add key prefixes (tg:/sk:) to agent-card badges to prevent React key collisions between tool_groups and skills * fix(ci): resolve lint and test failures - Format agent-card.tsx with prettier (lint-frontend) - Remove stale "Skills Appendix" system_prompt assertion — skills are now loaded per-session by SubagentExecutor, not appended to system_prompt * fix(ci): sort imports in test_subagent_skills_config.py (ruff I001) * fix(ci): use nullish coalescing in agent-card badge condition (eslint) * fix: address review feedback on skills PR - Use model_fields_set in AgentUpdateRequest to distinguish "field omitted" from "explicitly set to null" — fixes skills=None ambiguity where None means "inherit all" but was treated as "don't change" - Move lazy import of get_subagent_config outside loop in _build_available_subagents_description to avoid repeated import overhead --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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Javen Fang
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ac04f2704f
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feat(subagents): allow model override per subagent in config.yaml (#2064)
* feat(subagents): allow model override per subagent in config.yaml Wire the existing SubagentConfig.model field to config.yaml so users can assign different models to different subagent types. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * test(subagents): cover model override in SubagentsAppConfig + registry Addresses review feedback on #2064: - registry.py: update stale inline comment — the block now applies timeout, max_turns AND model overrides, not just timeout. - test_subagent_timeout_config.py: add coverage for model override resolution across SubagentOverrideConfig, SubagentsAppConfig (get_model_for + load), and registry.get_subagent_config: - per-agent model override is applied to registry-returned config - omitted `model` keeps the builtin value - explicit `model: null` in config.yaml is equivalent to omission - model override on one agent does not affect other agents - model override preserves all other fields (name, description, timeout_seconds, max_turns) - model override does not mutate BUILTIN_SUBAGENTS Copilot's suggestion (3) "setting model to 'inherit' forces inheritance" is skipped intentionally: there is no 'inherit' sentinel in the current implementation — model is `str | None`, and None already means "inherit from parent". Adding a sentinel would be a new feature, not test coverage for this PR. Tests run locally: 51 passed (37 existing + 14 new / expanded). * test(subagents): reject empty-string model at config load time Addresses WillemJiang's review comment on #2064 (empty-string edge case): - subagents_config.py: add `min_length=1` to the `model` field on SubagentOverrideConfig. `model: ""` in config.yaml would otherwise bypass the `is not None` check and reach create_chat_model(name="") as a confusing runtime error. This is symmetric with the existing `ge=1` guards on timeout_seconds / max_turns, so the validation style stays consistent across all three override fields. - test_subagent_timeout_config.py: add test_rejects_empty_model mirroring the existing test_rejects_zero / test_rejects_negative cases; update the docstring on test_model_accepts_any_string (now test_model_accepts_any_non_empty_string) to reflect the new guard. Not addressing the first comment (validating `model` against the `models:` section at load time) in this PR. `SubagentsAppConfig` is scoped to the `subagents:` block and cannot see the sibling `models:` section, so proper cross-section validation needs a second pass or a structural change that is out of scope here — and the current behavior is consistent with how timeout_seconds / max_turns work today. Happy to track this as a follow-up issue covering cross-section validation uniformly for all three fields. Tests run locally: 52 passed in this file; 1847 passed, 18 skipped across the full backend suite. Ruff check + format clean. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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Markus Corazzione
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0ffe5a73c1
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chroe(config):Increase subagent max-turn limits (#1852) | ||
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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> |