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