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https://github.com/bytedance/deer-flow.git
synced 2026-05-24 17:06:00 +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).
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@@ -11,6 +11,8 @@ from pydantic import BaseModel, ConfigDict, Field
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class McpOAuthConfig(BaseModel):
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"""OAuth configuration for an MCP server (HTTP/SSE transports)."""
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model_config = ConfigDict(extra="allow", frozen=True)
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enabled: bool = Field(default=True, description="Whether OAuth token injection is enabled")
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token_url: str = Field(description="OAuth token endpoint URL")
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grant_type: Literal["client_credentials", "refresh_token"] = Field(
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@@ -28,12 +30,13 @@ class McpOAuthConfig(BaseModel):
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default_token_type: str = Field(default="Bearer", description="Default token type when missing in token response")
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refresh_skew_seconds: int = Field(default=60, description="Refresh token this many seconds before expiry")
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extra_token_params: dict[str, str] = Field(default_factory=dict, description="Additional form params sent to token endpoint")
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model_config = ConfigDict(extra="allow")
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class McpServerConfig(BaseModel):
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"""Configuration for a single MCP server."""
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model_config = ConfigDict(extra="allow", frozen=True)
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enabled: bool = Field(default=True, description="Whether this MCP server is enabled")
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type: str = Field(default="stdio", description="Transport type: 'stdio', 'sse', or 'http'")
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command: str | None = Field(default=None, description="Command to execute to start the MCP server (for stdio type)")
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@@ -43,12 +46,13 @@ class McpServerConfig(BaseModel):
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headers: dict[str, str] = Field(default_factory=dict, description="HTTP headers to send (for sse or http type)")
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oauth: McpOAuthConfig | None = Field(default=None, description="OAuth configuration (for sse or http type)")
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description: str = Field(default="", description="Human-readable description of what this MCP server provides")
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model_config = ConfigDict(extra="allow")
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class SkillStateConfig(BaseModel):
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"""Configuration for a single skill's state."""
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model_config = ConfigDict(frozen=True)
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enabled: bool = Field(default=True, description="Whether this skill is enabled")
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@@ -64,7 +68,7 @@ class ExtensionsConfig(BaseModel):
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default_factory=dict,
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description="Map of skill name to state configuration",
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)
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model_config = ConfigDict(extra="allow", populate_by_name=True)
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model_config = ConfigDict(extra="allow", frozen=True, populate_by_name=True)
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@classmethod
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def resolve_config_path(cls, config_path: str | None = None) -> Path | None:
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@@ -195,62 +199,3 @@ class ExtensionsConfig(BaseModel):
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# Default to enable for public & custom skill
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return skill_category in ("public", "custom")
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return skill_config.enabled
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_extensions_config: ExtensionsConfig | None = None
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def get_extensions_config() -> ExtensionsConfig:
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"""Get the extensions config instance.
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Returns a cached singleton instance. Use `reload_extensions_config()` to reload
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from file, or `reset_extensions_config()` to clear the cache.
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Returns:
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The cached ExtensionsConfig instance.
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"""
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global _extensions_config
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if _extensions_config is None:
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_extensions_config = ExtensionsConfig.from_file()
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return _extensions_config
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def reload_extensions_config(config_path: str | None = None) -> ExtensionsConfig:
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"""Reload the extensions config from file and update the cached instance.
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This is useful when the config file has been modified and you want
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to pick up the changes without restarting the application.
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Args:
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config_path: Optional path to extensions config file. If not provided,
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uses the default resolution strategy.
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Returns:
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The newly loaded ExtensionsConfig instance.
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"""
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global _extensions_config
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_extensions_config = ExtensionsConfig.from_file(config_path)
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return _extensions_config
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def reset_extensions_config() -> None:
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"""Reset the cached extensions config instance.
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This clears the singleton cache, causing the next call to
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`get_extensions_config()` to reload from file. Useful for testing
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or when switching between different configurations.
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"""
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global _extensions_config
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_extensions_config = None
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def set_extensions_config(config: ExtensionsConfig) -> None:
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"""Set a custom extensions config instance.
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This allows injecting a custom or mock config for testing purposes.
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Args:
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config: The ExtensionsConfig instance to use.
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"""
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global _extensions_config
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_extensions_config = config
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