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stock-agent/README.md
Gahow Wang 7350d6286c feat(ui): split client into Live and Strategy pages and wire new routes 
Rebuilds the client into Live (watchlist with charts, fundamentals, news,
quant analysis) and Strategy (backtest runner / precomputed results) pages,
adds the corresponding /api/stocks/:symbol/chart|fundamentals|related|quant
and /api/strategies endpoints, and updates project tooling.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-19 23:21:03 +08:00

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Personal Stock Agent

统一个人股票监控 MVP，支持 A股、港股、美股自选股，按日生成监控报告。数据接口固定使用 IPADS Responses API，密钥从 .env 的 IPADS_API_KEY 读取。

Run

npm install
npm run dev

Frontend: http://127.0.0.1:5173

Backend: http://127.0.0.1:8787

LAN access:

HOST=0.0.0.0 CLIENT_PORT=5174 PORT=8787 npm run dev

Open http://gahow-pc.ipads-lab.se.sjtu.edu.cn:5174 from another device on the same network.

IPADS API

配置文件：

IPADS_API_KEY=your_api_key

固定服务端配置：

base_url = "http://tianx.ipads-lab.se.sjtu.edu.cn:8319/v1"
wire_api = "responses"
env_key = "IPADS_API_KEY"

The backend calls:

POST http://tianx.ipads-lab.se.sjtu.edu.cn:8319/v1/responses
Authorization: Bearer ${IPADS_API_KEY}

The response output text must be JSON matching the stock snapshot schema used by the agent. If IPADS_API_KEY is blank, the app uses deterministic demo data so the dashboard remains usable.

Features

  • Add/remove watchlist symbols such as 600519, 000001.SZ, 00700.HK, AAPL, MSFT.US.
  • Normalize symbols into A股、港股、美股 markets.
  • Generate a daily report with earnings timing, peer stocks, valuation discount/premium, related news, and buy-watch/hold/avoid recommendations.
  • Refreshes the cached daily report every 24 hours while the backend process is running.
  • View each watchlist stock with locally cached D/W/M/Y K-line chart data, zoom controls, MA5/MA20/MA60, RSI14, MACD, volume, and cached financial statements. US K-line and quote/research fields use Nasdaq as the fixed data source and target at least 5 years of verified daily OHLCV history when available.
  • Cache related market context such as sector, liquidity, volatility, drawdown, relative strength, capital flow, sentiment, and risk flags.
  • Run an agent-backed quantitative analysis across technical, valuation, growth, quality, liquidity, sentiment, and risk factors to classify each stock as buy-watch/hold/avoid.
  • Add tags to every watchlist stock and filter the watchlist by tag.
  • In configured provider mode, prompts require verified data and do not permit approximate or fabricated values; missing data is surfaced instead of being filled with synthetic values.
  • K-line cache updates incrementally: once 5 years of daily bars exist locally, refreshes request only the latest missing window and merge by date.

Local cache

Persistent app data defaults to ./data and can be moved with:

STOCK_AGENT_DATA_DIR=/path/to/stock-agent-data

The backend stores watchlist data in watchlist.json and per-stock cached snapshot/K-line/financial data under cache/.