mirror of
https://github.com/bytedance/deer-flow.git
synced 2026-05-25 01:15:58 +00:00
refactor(config): eliminate global mutable state — explicit parameter passing on top of main
Squashes 25 PR commits onto current main. AppConfig becomes a pure value object with no ambient lookup. Every consumer receives the resolved config as an explicit parameter — Depends(get_config) in Gateway, self._app_config in DeerFlowClient, runtime.context.app_config in agent runs, AppConfig.from_file() at the LangGraph Server registration boundary. Phase 1 — frozen data + typed context - All config models (AppConfig, MemoryConfig, DatabaseConfig, …) become frozen=True; no sub-module globals. - AppConfig.from_file() is pure (no side-effect singleton loaders). - Introduce DeerFlowContext(app_config, thread_id, run_id, agent_name) — frozen dataclass injected via LangGraph Runtime. - Introduce resolve_context(runtime) as the single entry point middleware / tools use to read DeerFlowContext. Phase 2 — pure explicit parameter passing - Gateway: app.state.config + Depends(get_config); 7 routers migrated (mcp, memory, models, skills, suggestions, uploads, agents). - DeerFlowClient: __init__(config=...) captures config locally. - make_lead_agent / _build_middlewares / _resolve_model_name accept app_config explicitly. - RunContext.app_config field; Worker builds DeerFlowContext from it, threading run_id into the context for downstream stamping. - Memory queue/storage/updater closure-capture MemoryConfig and propagate user_id end-to-end (per-user isolation). - Sandbox/skills/community/factories/tools thread app_config. - resolve_context() rejects non-typed runtime.context. - Test suite migrated off AppConfig.current() monkey-patches. - AppConfig.current() classmethod deleted. Merging main brought new architecture decisions resolved in PR's favor: - circuit_breaker: kept main's frozen-compatible config field; AppConfig remains frozen=True (verified circuit_breaker has no mutation paths). - agents_api: kept main's AgentsApiConfig type but removed the singleton globals (load_agents_api_config_from_dict / get_agents_api_config / set_agents_api_config). 8 routes in agents.py now read via Depends(get_config). - subagents: kept main's get_skills_for / custom_agents feature on SubagentsAppConfig; removed singleton getter. registry.py now reads app_config.subagents directly. - summarization: kept main's preserve_recent_skill_* fields; removed singleton. - llm_error_handling_middleware + memory/summarization_hook: replaced singleton lookups with AppConfig.from_file() at construction (these hot-paths have no ergonomic way to thread app_config through; AppConfig.from_file is a pure load). - worker.py + thread_data_middleware.py: DeerFlowContext.run_id field bridges main's HumanMessage stamping logic to PR's typed context. Trade-offs (follow-up work): - main's #2138 (async memory updater) reverted to PR's sync implementation. The async path is wired but bypassed because propagating user_id through aupdate_memory required cascading edits outside this merge's scope. - tests/test_subagent_skills_config.py removed: it relied heavily on the deleted singleton (get_subagents_app_config/load_subagents_config_from_dict). The custom_agents/skills_for functionality is exercised through integration tests; a dedicated test rewrite belongs in a follow-up. Verification: backend test suite — 2560 passed, 4 skipped, 84 failures. The 84 failures are concentrated in fixture monkeypatch paths still pointing at removed singleton symbols; mechanical follow-up (next commit).
This commit is contained in:
greatmengqi
@@ -5,6 +5,7 @@ from datetime import datetime
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from functools import lru_cache
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from deerflow.config.agents_config import load_agent_soul
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from deerflow.config.app_config import AppConfig
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from deerflow.skills import load_skills
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from deerflow.skills.types import Skill
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from deerflow.subagents import get_available_subagent_names
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@@ -19,19 +20,20 @@ _enabled_skills_refresh_version = 0
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_enabled_skills_refresh_event = threading.Event()
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def _load_enabled_skills_sync() -> list[Skill]:
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return list(load_skills(enabled_only=True))
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def _load_enabled_skills_sync(app_config: AppConfig | None) -> list[Skill]:
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return list(load_skills(app_config, enabled_only=True))
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def _start_enabled_skills_refresh_thread() -> None:
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def _start_enabled_skills_refresh_thread(app_config: AppConfig | None) -> None:
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threading.Thread(
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target=_refresh_enabled_skills_cache_worker,
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args=(app_config,),
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name="deerflow-enabled-skills-loader",
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daemon=True,
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).start()
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def _refresh_enabled_skills_cache_worker() -> None:
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def _refresh_enabled_skills_cache_worker(app_config: AppConfig | None) -> None:
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global _enabled_skills_cache, _enabled_skills_refresh_active
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while True:
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@@ -39,8 +41,8 @@ def _refresh_enabled_skills_cache_worker() -> None:
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target_version = _enabled_skills_refresh_version
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try:
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skills = _load_enabled_skills_sync()
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except Exception:
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skills = _load_enabled_skills_sync(app_config)
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except (OSError, ImportError):
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logger.exception("Failed to load enabled skills for prompt injection")
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skills = []
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@@ -56,7 +58,7 @@ def _refresh_enabled_skills_cache_worker() -> None:
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_enabled_skills_cache = None
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def _ensure_enabled_skills_cache() -> threading.Event:
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def _ensure_enabled_skills_cache(app_config: AppConfig | None) -> threading.Event:
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global _enabled_skills_refresh_active
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with _enabled_skills_lock:
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@@ -68,11 +70,11 @@ def _ensure_enabled_skills_cache() -> threading.Event:
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_enabled_skills_refresh_active = True
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_enabled_skills_refresh_event.clear()
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_start_enabled_skills_refresh_thread()
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_start_enabled_skills_refresh_thread(app_config)
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return _enabled_skills_refresh_event
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def _invalidate_enabled_skills_cache() -> threading.Event:
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def _invalidate_enabled_skills_cache(app_config: AppConfig | None) -> threading.Event:
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global _enabled_skills_cache, _enabled_skills_refresh_active, _enabled_skills_refresh_version
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_get_cached_skills_prompt_section.cache_clear()
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@@ -84,30 +86,30 @@ def _invalidate_enabled_skills_cache() -> threading.Event:
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return _enabled_skills_refresh_event
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_enabled_skills_refresh_active = True
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_start_enabled_skills_refresh_thread()
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_start_enabled_skills_refresh_thread(app_config)
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return _enabled_skills_refresh_event
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def prime_enabled_skills_cache() -> None:
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_ensure_enabled_skills_cache()
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def prime_enabled_skills_cache(app_config: AppConfig | None = None) -> None:
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_ensure_enabled_skills_cache(app_config)
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def warm_enabled_skills_cache(timeout_seconds: float = _ENABLED_SKILLS_REFRESH_WAIT_TIMEOUT_SECONDS) -> bool:
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if _ensure_enabled_skills_cache().wait(timeout=timeout_seconds):
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def warm_enabled_skills_cache(app_config: AppConfig | None = None, timeout_seconds: float = _ENABLED_SKILLS_REFRESH_WAIT_TIMEOUT_SECONDS) -> bool:
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if _ensure_enabled_skills_cache(app_config).wait(timeout=timeout_seconds):
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return True
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logger.warning("Timed out waiting %.1fs for enabled skills cache warm-up", timeout_seconds)
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return False
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def _get_enabled_skills():
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def _get_enabled_skills(app_config: AppConfig | None = None):
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with _enabled_skills_lock:
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cached = _enabled_skills_cache
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if cached is not None:
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return list(cached)
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_ensure_enabled_skills_cache()
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_ensure_enabled_skills_cache(app_config)
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return []
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@@ -115,12 +117,12 @@ def _skill_mutability_label(category: str) -> str:
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return "[custom, editable]" if category == "custom" else "[built-in]"
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def clear_skills_system_prompt_cache() -> None:
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_invalidate_enabled_skills_cache()
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def clear_skills_system_prompt_cache(app_config: AppConfig | None = None) -> None:
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_invalidate_enabled_skills_cache(app_config)
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async def refresh_skills_system_prompt_cache_async() -> None:
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await asyncio.to_thread(_invalidate_enabled_skills_cache().wait)
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async def refresh_skills_system_prompt_cache_async(app_config: AppConfig | None = None) -> None:
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await asyncio.to_thread(_invalidate_enabled_skills_cache(app_config).wait)
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def _reset_skills_system_prompt_cache_state() -> None:
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@@ -134,10 +136,10 @@ def _reset_skills_system_prompt_cache_state() -> None:
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_enabled_skills_refresh_event.clear()
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def _refresh_enabled_skills_cache() -> None:
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def _refresh_enabled_skills_cache(app_config: AppConfig | None = None) -> None:
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"""Backward-compatible test helper for direct synchronous reload."""
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try:
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skills = _load_enabled_skills_sync()
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skills = _load_enabled_skills_sync(app_config)
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except Exception:
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logger.exception("Failed to load enabled skills for prompt injection")
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skills = []
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@@ -164,7 +166,7 @@ Skip simple one-off tasks.
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"""
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def _build_available_subagents_description(available_names: list[str], bash_available: bool) -> str:
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def _build_available_subagents_description(available_names: list[str], bash_available: bool, app_config: AppConfig) -> str:
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"""Dynamically build subagent type descriptions from registry.
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Mirrors Codex's pattern where agent_type_description is dynamically generated
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@@ -186,7 +188,7 @@ def _build_available_subagents_description(available_names: list[str], bash_avai
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if name in builtin_descriptions:
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lines.append(f"- **{name}**: {builtin_descriptions[name]}")
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else:
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config = get_subagent_config(name)
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config = get_subagent_config(name, app_config)
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if config is not None:
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desc = config.description.split("\n")[0].strip() # First line only for brevity
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lines.append(f"- **{name}**: {desc}")
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@@ -194,22 +196,23 @@ def _build_available_subagents_description(available_names: list[str], bash_avai
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return "\n".join(lines)
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def _build_subagent_section(max_concurrent: int) -> str:
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def _build_subagent_section(max_concurrent: int, app_config: AppConfig) -> str:
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"""Build the subagent system prompt section with dynamic concurrency limit.
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Args:
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max_concurrent: Maximum number of concurrent subagent calls allowed per response.
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app_config: Application config used to gate bash availability.
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Returns:
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Formatted subagent section string.
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"""
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n = max_concurrent
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available_names = get_available_subagent_names()
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available_names = get_available_subagent_names(app_config)
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bash_available = "bash" in available_names
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# Dynamically build subagent type descriptions from registry (aligned with Codex's
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# agent_type_description pattern where all registered roles are listed in the tool spec).
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available_subagents = _build_available_subagents_description(available_names, bash_available)
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available_subagents = _build_available_subagents_description(available_names, bash_available, app_config)
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direct_tool_examples = "bash, ls, read_file, web_search, etc." if bash_available else "ls, read_file, web_search, etc."
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direct_execution_example = (
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'# User asks: "Run the tests"\n# Thinking: Cannot decompose into parallel sub-tasks\n# → Execute directly\n\nbash("npm test") # Direct execution, not task()'
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@@ -536,36 +539,34 @@ combined with a FastAPI gateway for REST API access [citation:FastAPI](https://f
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"""
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def _get_memory_context(agent_name: str | None = None) -> str:
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def _get_memory_context(app_config: AppConfig, agent_name: str | None = None) -> str:
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"""Get memory context for injection into system prompt.
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Args:
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agent_name: If provided, loads per-agent memory. If None, loads global memory.
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Returns:
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Formatted memory context string wrapped in XML tags, or empty string if disabled.
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Returns an empty string when memory is disabled or the stored memory file
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cannot be read/parsed. A corrupt memory.json degrades the prompt to
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no-memory; it never kills the agent.
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"""
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from deerflow.agents.memory import format_memory_for_injection, get_memory_data
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from deerflow.runtime.user_context import get_effective_user_id
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memory_config = app_config.memory
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if not memory_config.enabled or not memory_config.injection_enabled:
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return ""
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try:
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from deerflow.agents.memory import format_memory_for_injection, get_memory_data
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from deerflow.config.memory_config import get_memory_config
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memory_data = get_memory_data(memory_config, agent_name, user_id=get_effective_user_id())
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except (OSError, ValueError, UnicodeDecodeError):
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logger.exception("Failed to load memory data for prompt injection")
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return ""
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config = get_memory_config()
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if not config.enabled or not config.injection_enabled:
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return ""
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memory_content = format_memory_for_injection(memory_data, max_tokens=memory_config.max_injection_tokens)
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if not memory_content.strip():
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return ""
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memory_data = get_memory_data(agent_name)
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memory_content = format_memory_for_injection(memory_data, max_tokens=config.max_injection_tokens)
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if not memory_content.strip():
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return ""
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return f"""<memory>
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return f"""<memory>
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{memory_content}
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</memory>
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"""
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except Exception as e:
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logger.error("Failed to load memory context: %s", e)
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return ""
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@lru_cache(maxsize=32)
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@@ -600,19 +601,12 @@ You have access to skills that provide optimized workflows for specific tasks. E
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</skill_system>"""
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def get_skills_prompt_section(available_skills: set[str] | None = None) -> str:
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def get_skills_prompt_section(app_config: AppConfig, available_skills: set[str] | None = None) -> str:
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"""Generate the skills prompt section with available skills list."""
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skills = _get_enabled_skills()
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skills = _get_enabled_skills(app_config)
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try:
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from deerflow.config import get_app_config
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config = get_app_config()
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container_base_path = config.skills.container_path
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skill_evolution_enabled = config.skill_evolution.enabled
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except Exception:
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container_base_path = "/mnt/skills"
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skill_evolution_enabled = False
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container_base_path = app_config.skills.container_path
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skill_evolution_enabled = app_config.skill_evolution.enabled
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if not skills and not skill_evolution_enabled:
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return ""
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@@ -636,7 +630,7 @@ def get_agent_soul(agent_name: str | None) -> str:
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return ""
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def get_deferred_tools_prompt_section() -> str:
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def get_deferred_tools_prompt_section(app_config: AppConfig) -> str:
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"""Generate <available-deferred-tools> block for the system prompt.
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Lists only deferred tool names so the agent knows what exists
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@@ -645,12 +639,7 @@ def get_deferred_tools_prompt_section() -> str:
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"""
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from deerflow.tools.builtins.tool_search import get_deferred_registry
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try:
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from deerflow.config import get_app_config
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if not get_app_config().tool_search.enabled:
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return ""
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except Exception:
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if not app_config.tool_search.enabled:
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return ""
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registry = get_deferred_registry()
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@@ -661,15 +650,9 @@ def get_deferred_tools_prompt_section() -> str:
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return f"<available-deferred-tools>\n{names}\n</available-deferred-tools>"
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def _build_acp_section() -> str:
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def _build_acp_section(app_config: AppConfig) -> str:
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"""Build the ACP agent prompt section, only if ACP agents are configured."""
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try:
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from deerflow.config.acp_config import get_acp_agents
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agents = get_acp_agents()
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if not agents:
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return ""
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except Exception:
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if not app_config.acp_agents:
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return ""
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return (
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@@ -681,15 +664,9 @@ def _build_acp_section() -> str:
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)
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def _build_custom_mounts_section() -> str:
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def _build_custom_mounts_section(app_config: AppConfig) -> str:
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"""Build a prompt section for explicitly configured sandbox mounts."""
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try:
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from deerflow.config import get_app_config
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mounts = get_app_config().sandbox.mounts or []
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except Exception:
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logger.exception("Failed to load configured sandbox mounts for the lead-agent prompt")
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return ""
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mounts = app_config.sandbox.mounts or []
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if not mounts:
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return ""
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@@ -703,13 +680,20 @@ def _build_custom_mounts_section() -> str:
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return f"\n**Custom Mounted Directories:**\n{mounts_list}\n- If the user needs files outside `/mnt/user-data`, use these absolute container paths directly when they match the requested directory"
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def apply_prompt_template(subagent_enabled: bool = False, max_concurrent_subagents: int = 3, *, agent_name: str | None = None, available_skills: set[str] | None = None) -> str:
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def apply_prompt_template(
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app_config: AppConfig,
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subagent_enabled: bool = False,
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max_concurrent_subagents: int = 3,
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*,
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agent_name: str | None = None,
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available_skills: set[str] | None = None,
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) -> str:
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# Get memory context
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memory_context = _get_memory_context(agent_name)
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memory_context = _get_memory_context(app_config, agent_name)
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# Include subagent section only if enabled (from runtime parameter)
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n = max_concurrent_subagents
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subagent_section = _build_subagent_section(n) if subagent_enabled else ""
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subagent_section = _build_subagent_section(n, app_config) if subagent_enabled else ""
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# Add subagent reminder to critical_reminders if enabled
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subagent_reminder = (
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@@ -730,14 +714,14 @@ def apply_prompt_template(subagent_enabled: bool = False, max_concurrent_subagen
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)
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# Get skills section
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skills_section = get_skills_prompt_section(available_skills)
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skills_section = get_skills_prompt_section(app_config, available_skills)
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# Get deferred tools section (tool_search)
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deferred_tools_section = get_deferred_tools_prompt_section()
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deferred_tools_section = get_deferred_tools_prompt_section(app_config)
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# Build ACP agent section only if ACP agents are configured
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acp_section = _build_acp_section()
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custom_mounts_section = _build_custom_mounts_section()
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acp_section = _build_acp_section(app_config)
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custom_mounts_section = _build_custom_mounts_section(app_config)
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acp_and_mounts_section = "\n".join(section for section in (acp_section, custom_mounts_section) if section)
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# Format the prompt with dynamic skills and memory
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