9503fca370
网页身份改由 auth-hub 做 OAuth2 + PKCE 单点登录，本地邮箱/密码登录与注册整条链路删除 （routes/auth.py、auth.py 的密码哈希、config.py 的 ALLOW_REGISTRATION）。Garmin 账号绑定/ 同步保持完全独立、可选：routes/garmin.py 不再直接查 users 表，Garmin 邮箱回退统一走新增 的 services/garmin.py::get_remembered_email()（优先读 garmin_tokens 当前绑定，兼容早期账号 落在 users.garmin_email 的历史值），彻底把「你是谁」和「你绑没绑 Garmin」两件事拆开。 - db.py: users 表新增 auth_hub_sub/auth_hub_username，MIGRATIONS 补上这两列（此前遗漏导致 已存在的生产 MariaDB 表永远不会自动加列）；同时把历史遗留的 garmin_email/ garmin_password_hash NOT NULL 约束在线迁移为可空，因为新账号不再在注册时收集这些字段。 - routes/auth.py: 修掉 /callback 路由重复拼接 /api/auth 前缀导致 404 的 bug。 - client: LoginPage 去掉本地登录/注册标签页，只保留 auth-hub 统一登录；登录成功/失败后都 用 history.replaceState 清理地址栏，修掉 Framework7 browserHistory 读取 /auth/callback?code=... 导致「找不到页面」的问题。 - 新增 test_auth_hub_client.py 锁定 find_or_create_user 按 auth_hub_sub 幂等——生产上曾经因为 这个函数在没有该测试保护时被测试触发，误建过一个空账号，靠手工核对 health_data 计数才发现。 - 生产 auth-hub 侧另行为该项目注册了正式 client（未随本次提交变更，凭证只存在服务器 .env）。 Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
80 lines
3.3 KiB
Plaintext
80 lines
3.3 KiB
Plaintext
# --- Server ---
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# BACKEND_PORT takes precedence over PORT. Prefer it: many tools inject PORT
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# for the frontend, and Flask would otherwise take the React dev server's port.
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BACKEND_PORT=5000
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# --- Database: sqlite (default) or mariadb ---
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DB_TYPE=sqlite
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# SQLite file (used when DB_TYPE=sqlite)
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DATABASE_PATH=./data/health.db
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# MariaDB (used when DB_TYPE=mariadb) — production DB on the Oracle server
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# (129.146.26.249, local MariaDB 10.3). Dedicated account over TCP 127.0.0.1;
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# MARIADB_SOCKET is only needed if TCP auth is disabled for the app user.
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# MARIADB_HOST=127.0.0.1
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# MARIADB_PORT=3306
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# MARIADB_USER=garmin
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# MARIADB_PASSWORD=your_production_mariadb_password
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# MARIADB_DATABASE=garmin_health_lab
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# --- Auth ---
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# CHANGE THIS in production! Used to sign JWTs (7-day expiry by default).
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JWT_SECRET=dev_secret_change_me
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JWT_EXPIRY_DAYS=7
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# --- auth-hub OAuth2 provider (centralized SSO) ---
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# See docs/AUTH_HUB_INTEGRATION.md for setup instructions.
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#
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# Base URL of the auth-hub service
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AUTH_HUB_BASE_URL=http://129.146.26.249:5300
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#
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# OAuth2 client credentials (obtain from auth-hub.manage_clients create)
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# NOTE: these must be registered against the auth-hub instance AUTH_HUB_BASE_URL
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# actually points to (dev vs prod are separate databases with separate clients).
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# Put the REAL values in backend/.env (gitignored) — never here.
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AUTH_HUB_CLIENT_ID=your_client_id
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AUTH_HUB_CLIENT_SECRET=your_client_secret
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#
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# Callback URL (must exactly match what's registered in auth-hub)
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AUTH_HUB_REDIRECT_URI=http://129.146.26.249:8123/auth/callback
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# --- CORS (comma-separated allowed front-end origins) ---
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# localhost stays in the production list on purpose: CORS is not an auth
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# boundary — every data route requires a valid JWT — so allowing a developer's
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# dev server costs nothing and saves toggling this on every session.
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CORS_ORIGIN=http://localhost:3000,http://localhost:5173
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# --- AI models (text-only, large context) ---
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# Put REAL keys in backend/.env — that file is gitignored. Never commit keys.
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# Any model whose credentials are absent is skipped automatically.
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# Self-hosted AI gateway (model id "gateway"). OpenAI-compatible; it fans out
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# over nvidia/gemini/ollama itself and rotates several Gemini keys, so it
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# absorbs single-vendor quota limits. Reached directly, bypassing any local
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# HTTP proxy. NOTE: its NVIDIA upstream is a large reasoning model — replies
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# can take 2-3 minutes, so set AI_TIMEOUT_SECONDS accordingly.
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AI_GATEWAY_BASE_URL=http://129.146.26.249:5100/v1
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AI_GATEWAY_TOKEN=
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AI_GATEWAY_MODEL=ai-gateway-auto
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# Google AI Studio -> "gemini-flash". Free-tier quota is small; 429s are common.
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GEMINI_API_KEY=
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# NVIDIA NIM -> "llama-70b", "nemotron-49b", "mistral-large".
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# Model ids come from that account's live GET /v1/models — do not guess them.
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NVIDIA_API_KEY=
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# NVIDIA_BASE_URL=https://integrate.api.nvidia.com/v1
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# Preference order. The first configured model answers; if it fails or times
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# out, the next is tried. Read per request, so changes need no restart.
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AI_MODEL_CHAIN=gateway,gemini-flash,llama-70b
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# Max days of history sent (CSV-encoded). Trimmed further per model so the
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# payload always fits that model's own context window.
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AI_DAY_BUDGET=365
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AI_TIMEOUT_SECONDS=180
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# Output cap. Reasoning models spend part of it thinking before they answer;
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# entries that need more declare their own budget in services/ai.py.
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AI_MAX_TOKENS=1024
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