mirror of https://github.com/bytedance/deer-flow.git synced 2026-05-06 16:58:24 +00:00

greatmengqi 3e6a34297d 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).

2026-04-26 21:45:02 +08:00

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Authentication Upgrade Guide

DeerFlow 内置了认证模块。本文档面向从无认证版本升级的用户。

核心概念

认证模块采用始终强制策略：

首次启动时自动创建 admin 账号，随机密码打印到控制台日志
认证从一开始就是强制的，无竞争窗口
历史对话（升级前创建的 thread）自动迁移到 admin 名下

升级步骤

1. 更新代码

git pull origin main
cd backend && make install

2. 首次启动

make dev

控制台会输出：

============================================================
  Admin account created on first boot
  Email:    admin@deerflow.dev
  Password: aB3xK9mN_pQ7rT2w
  Change it after login: Settings → Account
============================================================

如果未登录就重启了服务，不用担心——只要 setup 未完成，每次启动都会重置密码并重新打印到控制台。

3. 登录

访问 http://localhost:2026/login，使用控制台输出的邮箱和密码登录。

4. 修改密码

登录后进入 Settings → Account → Change Password。

5. 添加用户（可选）

其他用户通过 /login 页面注册，自动获得 user 角色。每个用户只能看到自己的对话。

安全机制

机制	说明
JWT HttpOnly Cookie	Token 不暴露给 JavaScript，防止 XSS 窃取
CSRF Double Submit Cookie	所有 POST/PUT/DELETE 请求需携带 `X-CSRF-Token`
bcrypt 密码哈希	密码不以明文存储
多租户隔离	用户只能访问自己的 thread
HTTPS 自适应	检测 `x-forwarded-proto`，自动设置 `Secure` cookie 标志

常见操作

忘记密码

cd backend

# 重置 admin 密码
python -m app.gateway.auth.reset_admin

# 重置指定用户密码
python -m app.gateway.auth.reset_admin --email user@example.com

会输出新的随机密码。

完全重置

删除用户数据库，重启后自动创建新 admin：

rm -f backend/.deer-flow/users.db
# 重启服务，控制台输出新密码

数据存储

文件	内容
`.deer-flow/users.db`	SQLite 用户数据库（密码哈希、角色）
`.env` 中的 `AUTH_JWT_SECRET`	JWT 签名密钥（未设置时自动生成临时密钥，重启后 session 失效）

生产环境建议

# 生成持久化 JWT 密钥，避免重启后所有用户需重新登录
python -c "import secrets; print(secrets.token_urlsafe(32))"
# 将输出添加到 .env：
# AUTH_JWT_SECRET=<生成的密钥>

API 端点

端点	方法	说明
`/api/v1/auth/login/local`	POST	邮箱密码登录（OAuth2 form）
`/api/v1/auth/register`	POST	注册新用户（user 角色）
`/api/v1/auth/logout`	POST	登出（清除 cookie）
`/api/v1/auth/me`	GET	获取当前用户信息
`/api/v1/auth/change-password`	POST	修改密码
`/api/v1/auth/setup-status`	GET	检查 admin 是否存在

兼容性

标准模式（make dev）：完全兼容，admin 自动创建
Gateway 模式（make dev-pro）：完全兼容
Docker 部署：完全兼容，.deer-flow/users.db 需持久化卷挂载
IM 渠道（Feishu/Slack/Telegram）：通过 LangGraph SDK 通信，不经过认证层
DeerFlowClient（嵌入式）：不经过 HTTP，不受认证影响

故障排查

症状	原因	解决
启动后没看到密码	admin 已存在（非首次启动）	用 `reset_admin` 重置，或删 `users.db`
登录后 POST 返回 403	CSRF token 缺失	确认前端已更新
重启后需要重新登录	`AUTH_JWT_SECRET` 未持久化	在 `.env` 中设置固定密钥

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