About YES/NO.EVENTS

Overview

YES/NO.EVENTS is a professional-grade trading terminal for Polymarket prediction markets. It combines a Bloomberg Terminal-style interface with natural language AI trading capabilities.

Key Features

• 100+ API Functions - Full Polymarket integration (CLOB, Gamma, Data, Polyrouter)
• Local AI - Edge detection via Ollama (llama3.2), no API costs
• Real-time Streaming - WebSocket price updates and trade feeds
• Quant Tools - Monte Carlo, Kelly Criterion, momentum scanner
• Pre-computed Data - 31 days of Elon tweet analytics

Installation

Requirements

• Python 3.12+
• macOS, Linux, or WSL
• ~100MB disk space

Step 1: Clone Repository

# Clone the repository
git clone https://github.com/your-repo/yesno-events.git
cd yesno-events

Step 2: Create Virtual Environment

# Create and activate venv
python3.12 -m venv .venv
source .venv/bin/activate

Step 3: Install Dependencies

# Install required packages
pip install py-clob-client textual rich pyyaml numpy scikit-learn

# Make scripts executable
chmod +x *.sh

Step 4: Verify Installation

# Test the trading module
python -c "import trading; print('OK')"

# Run tests
./run_tests.sh

Optional: Enable AI Edge Detection

# Install Ollama (macOS)
brew install ollama

# Start Ollama server
ollama serve

# Pull the model
ollama pull llama3.2

Quick Start

Launch Terminal UI

./yesno.sh

Launch Web Dashboard

./run.sh
# Open http://localhost:8888

Launch Trading Cockpit

python cockpit_web.py
# Open http://localhost:8891

CLI Commands

# Scan markets
./trade.sh scan

# Find EV opportunities
./trade.sh ev

# Monte Carlo simulation
./quant.sh mc 450 72

# Search markets
./search.sh markets "bitcoin"

Project Structure

dashboard4all/
├── app.py              # TUI terminal (Textual) - 6,752 lines
├── dashboard4all.py    # Web dashboard - 12,779 lines
├── trading.py          # API layer - 3,812 lines
├── cockpit_web.py      # Trading cockpit (port 8891)
├── claude_trader.py    # Natural language trading CLI
├── rtds_client.py      # WebSocket real-time streaming
├── quant.py            # Monte Carlo, Kelly criterion
├── search.py           # TF-IDF vector search
├── tracker.py          # Tweet calendar aggregation
│
├── *.sh                # Shell wrappers
│
├── data/
│   ├── .trading_config.json  # API credentials
│   ├── markets.db            # SQLite market cache
│   └── cache/                # API response cache
│
├── docs/               # Documentation
├── tests/              # Test suite
├── calendar/           # Event tracking
├── strategies/         # Strategy templates
│
└── projects/           # Standalone packages
    ├── claude-trader/  # Natural language trading
    ├── poly-terminal/  # TUI package
    ├── poly-web/       # Web package
    └── poly-calendar/  # Calendar package

CLI Reference

trade.sh - Market Operations

quant.sh - Quantitative Models

tracker.sh - Tweet Tracking

search.sh - Vector Search

API Integration

The platform integrates with 6 data sources:

Python Usage

from trading import *

# Search markets
markets = polyrouter_search("bitcoin")

# Get market price
price = get_clob_price(market_id)

# Get orderbook
book = get_orderbook(market_id)

# Place order (requires credentials)
result = place_order(market_id, "BUY", price=0.35, size=10)

Configuration

Trading Credentials

To enable trading, create data/.trading_config.json:

{
  "private_key": "0x...",
  "api_key": "...",
  "api_secret": "...",
  "passphrase": "...",
  "funder": "0x..."
}

TUI Settings

TUI settings are stored in data/.yesno_config.json:

{
  "theme": "dark",
  "refresh_rate": 30,
  "default_view": "markets"
}

Keyboard Shortcuts (TUI)

Navigation

Trading