README.md

metadata

title: AI Trading Fusion - BitNet Transformer
emoji: 📈
colorFrom: blue
colorTo: green
sdk: docker
pinned: false

trading-cli

A full-screen TUI AI trading application powered by FinBERT sentiment analysis and Alpaca paper trading. ┌─────────────────────────────────────────────────────────┐ │ TRADING CLI - Paper Trading Mode Cash: $98,234.50 │ ├─────────────────────────────────────────────────────────┤ │ [1] Dashboard [2] Watchlist [3] Portfolio │ │ [4] Trades [5] Sentiment [6] Config [q] Quit │ ├─────────────────────────────────────────────────────────┤ │ MARKET STATUS: ● OPEN Last Updated: 14:23:45 EST │ └─────────────────────────────────────────────────────────┘

Features

Feature	Details
Full-screen TUI	Textual-based, single command launch
FinBERT sentiment	Local inference, ProsusAI/finbert
Paper trading	Alpaca paper API (or built-in demo mode)
Live prices	Alpaca market data + yfinance fallback
Hybrid signals	0.6 × technical + 0.4 × sentiment
Persistent state	SQLite (trades, watchlist, sentiment cache)
Demo mode	Works without any API keys

---

Quick Start

1. Install uv (if not already installed)

curl -LsSf https://astral.sh/uv/install.sh | sh

2. Clone and install

git clone https://github.com/luohoa97/ai-trading.git
cd ai-trading
uv sync

3. Run

uv run trading-cli

On first launch, FinBERT (~500 MB) downloads from HuggingFace and is cached locally. The app starts in Demo Mode automatically if no Alpaca keys are configured.

Alpaca Paper Trading Setup (optional)

1. Sign up at alpaca.markets — free, no credit card needed
2. Generate paper trading API keys in the Alpaca dashboard
3. Open Config in the app (6), enter your keys, press Ctrl+S

The app always uses paper trading endpoints — no real money is ever at risk.

Configuration

Config file: ~/.config/trading-cli/config.toml

alpaca_api_key    = "PKxxxxxxxxxxxx"
alpaca_api_secret = "xxxxxxxxxxxxxxxxxxxxxxxxxxxx"
alpaca_paper      = true
 
# Risk management
risk_pct        = 0.02    # 2% of portfolio per trade
max_drawdown    = 0.15    # halt trading at 15% drawdown
stop_loss_pct   = 0.05    # 5% stop-loss per position
max_positions   = 10
 
# Signal thresholds (hybrid score: -1 to +1)
signal_buy_threshold  =  0.5
signal_sell_threshold = -0.3

# Poll intervals (seconds)
poll_interval_prices    = 30
poll_interval_news      = 900
poll_interval_signals   = 300
poll_interval_positions = 60

---

Keyboard Shortcuts

Key	Action
1–6	Switch screens
q / Ctrl+C	Quit
r	Refresh current screen
a	Add symbol (Watchlist)
d	Delete selected symbol (Watchlist)
x	Close position (Portfolio)
e	Export trades to CSV (Trades)
f	Focus filter (Trades)
Enter	Submit symbol / confirm action
Ctrl+S	Save config (Config screen)

---

Screens

1 — Dashboard: Account balance, market status, live positions, real-time signal log. 2 — Watchlist: Add/remove symbols. See live prices, sentiment score, and BUY/SELL/HOLD signal per symbol. 3 — Portfolio: Full position detail from Alpaca. Press x to close a position via market order. 4 — Trades: Scrollable history with Alpaca order_id. Press e to export CSV. 5 — Sentiment: Type any symbol, press Enter — see FinBERT scores per headline and an aggregated gauge. 6 — Config: Edit API keys, thresholds, risk limits, toggle auto-trading.

Trading Strategy

Signal = 0.6 × technical + 0.4 × sentiment | Component | Calculation | |---|---| | technical_score | 0.5 × SMA crossover (20/50) + 0.5 × RSI(14) | | sentiment_score | FinBERT weighted average on latest news | | BUY | hybrid > +0.50 | | SELL | hybrid < −0.30 | In manual mode (default), signals appear in the log for review. In auto-trading mode (Config → toggle), market orders are submitted automatically.

Project Structure

trading_cli/
├── __main__.py           # Entry point: uv run trading-cli
├── app.py                # Textual App, workers, screen routing
├── config.py             # Load/save ~/.config/trading-cli/config.toml
├── screens/
│   ├── dashboard.py      # Screen 1 — main dashboard
│   ├── watchlist.py      # Screen 2 — symbol watchlist
│   ├── portfolio.py      # Screen 3 — positions & P&L
│   ├── trades.py         # Screen 4 — trade history
│   ├── sentiment.py      # Screen 5 — FinBERT analysis
│   └── config_screen.py  # Screen 6 — settings editor
├── widgets/
│   ├── positions_table.py  # Reusable P&L table
│   ├── signal_log.py       # Scrolling signal feed
│   └── sentiment_gauge.py  # Visual [-1, +1] gauge
├── sentiment/
│   ├── finbert.py          # Singleton model, batch inference, cache
│   └── aggregator.py       # Score aggregation + gauge renderer
├── strategy/
│   ├── signals.py          # SMA + RSI + sentiment hybrid signal
│   └── risk.py             # Position sizing, stop-loss, drawdown
├── execution/
│   └── alpaca_client.py    # Real AlpacaClient + MockAlpacaClient
└── data/
    ├── market.py           # OHLCV via Alpaca / yfinance
    ├── news.py             # Headlines via Alpaca News / yfinance
    └── db.py               # SQLite schema + all queries

---

Database

Location: ~/.config/trading-cli/trades.db | Table | Contents | |---|---| | trades | Every executed order with Alpaca order_id | | signals | Every generated signal (executed or not) | | watchlist | Monitored symbols | | sentiment_cache | MD5(headline) → label + score | | price_history | OHLCV bars per symbol |

Development

# Run app
uv run trading-cli
 
# Live logs
tail -f ~/.config/trading-cli/app.log
 
# Reset state
rm ~/.config/trading-cli/trades.db
rm ~/.config/trading-cli/config.toml
```# ai-trading