ac99c1342d
- backend/.env.example: AI 网关地址 129.146.203.203 → 129.146.26.249； MariaDB 注释段更新为生产实际（garmin 专用账号 @ 127.0.0.1:3306，socket 已不用） - README: 生产数据层/数据库说明改为 Oracle 新机本地 MariaDB 10.3 - docs/REQUIREMENTS: 部署目标 NAS → Oracle 新机；公网方式 frp 隧道 → gunicorn 直绑 8123 - docs/ARCHITECTURE: 部署架构改为真实生产栈（Flask+gunicorn+MariaDB+SPA）
64 lines
2.6 KiB
Plaintext
64 lines
2.6 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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# --- 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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