* fix(subagents): scale max_turns into the graph's super-step budget
max_turns was handed to LangGraph as recursion_limit, but the two count
different things. recursion_limit counts super-steps, one per graph node,
and create_agent compiles a node for every middleware lifecycle hook, so
one turn costs before_model + model + after_model + tools nodes — seven to
eight through the subagent chain. The built-in general-purpose agent's
max_turns=150 therefore bought about 18 tool-using turns before failing as
turn_capped, and every middleware added to the chain shrank the effective
budget again.
Resolve the limit from the chain each subagent was actually assembled with
(subagents/turn_budget.py) instead of passing the turn count through, so
raising max_turns buys the turns it names.
No config keys or defaults changed; existing max_turns values now grant
their full budget, bounded as before by subagents.timeout_seconds and
subagents.token_budget.
* fix(subagents): warn when a counted hook can jump the agent loop
Review follow-up. The per-turn cost is a flat multiplier over the straight
before_model -> model -> tools loop. A hook that declares can_jump_to and
returns {"jump_to": ...} re-enters the loop without traversing tools,
spending another before_model + model + after_model pass that buys no tool
result, so the resolved limit becomes a lower bound rather than an exact
budget — silently re-creating the short budget this translation fixes.
Measured against a compiled graph: with one jumping after_model hook,
three tool turns need the resolved limit plus one jump pass, and the run
raises GraphRecursionError at the resolved limit.
How often a jump fires is data-dependent and unbounded, so it cannot be
folded into the arithmetic. find_jumping_hooks reports the condition off
the same __can_jump_to__ attribute the factory reads, and the executor
warns when a counted hook declares one. Nothing in today's subagent chain
does, so this changes no budget.
* fix(subagents): detect jumps declared on agent-level hooks too
Review follow-up. find_jumping_hooks exempted before_agent/after_agent on
the grounds that a jump out of them lands in the loop the budget already
pays for. That does not hold on langchain 1.3.14:
- after_agent jumps re-enter the loop after it finished, and the hook runs
again on the next exit, so the extra passes are unbounded. Even
jump_to "end" is routed to exit_node, the head of the after_agent chain,
so it reruns the chain; destinations are no safe filter.
- a before_agent hook that stages a tool call and jumps to tools runs a
tools step no model turn paid for. It is O(1), but the resolved limit
has zero headroom, so one step caps the last turn.
The detector now scans every hook pair the factory wires jump edges for.
The compiled-graph pin is parametrized over after_model->model,
after_agent->model, after_agent->end and before_agent->tools, each raising
GraphRecursionError at the resolved limit and completing once the jump's
cost is added. No middleware in the subagent chain declares a jump on any
hook, so this changes no budget.
* 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>
* fix(subagents): consolidate system_prompt and skills into single SystemMessage
Some LLM APIs (vLLM, Xinference, Chinese LLM providers) reject multiple
system messages with \”System message must be at the beginning.\” The
subagent executor was sending separate SystemMessages for the configured
system_prompt and each loaded skill, which caused failures when calling
task tool with sub-agents.
Merge system_prompt and all skill content into one SystemMessage in the
initial state, and pass system_prompt=None to create_agent() so the
factory doesn't prepend a second one.
Fixes#2693
* fix(subagents): update SubagentConfig.system_prompt to str | None and add astream regression test
Agent-Logs-Url: https://github.com/bytedance/deer-flow/sessions/2ee03a26-e19b-4106-abc5-c76a2906383b
Co-authored-by: WillemJiang <219644+WillemJiang@users.noreply.github.com>
* fixed the lint error
* fix the lint error in the backend
* fix the unit test error of test_subagent_executor
---------
Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
* fix(subagents): use model override for tools and middleware
* fix(config): resolve effective subagent model
* fix(subagents): defer app config loading
* fix(subagents): fully defer config.yaml load in executor __init__
The previous attempt only relocated the explicit get_app_config() call,
but left resolve_subagent_model_name(...) running eagerly in __init__.
That helper has its own internal get_app_config() fallback, which still
fired when both app_config and parent_model were None and
config.model == "inherit" — exactly the path unit tests hit, breaking
21 tests in CI with FileNotFoundError: config.yaml.
Skip the eager resolve in __init__ when it would require loading the
config file, and defer to _create_agent (which already has the
app_config or get_app_config() fallback).
* 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>
* 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>
