Crypto Market Agent

Live: crypto-market-agent.vercel.app

An alternative investment analytics platform for cryptocurrency market data. Explore historical rankings by market cap, run AI-powered queries, and analyze sector dynamics through interactive dashboards.

Features

• Quarterly Snapshots — Top N coins by market cap across quarters (2020+)
• AI Chat Agent — Conversational interface powered by GPT-4o with tool-calling for natural language crypto queries
• Correlation Matrix — Price correlation heatmaps across assets
• Risk Metrics — Sharpe ratio, Sortino ratio, max drawdown, VaR (95%/99%)
• Sector Rotation — Aggregated performance by sector (Layer 1, DeFi, Meme, AI, RWA, etc.)
• CSV Export — Download filtered datasets for further analysis

Tech Stack

Layer	Technologies
Backend	Python 3.10, FastAPI, OpenAI GPT-4o, Pandas, NumPy
Frontend	React 18, TypeScript, Vite, Tailwind CSS, Recharts
Data	CoinGecko Pro API, Joblib caching
Deployment	Railway (backend), Vercel (frontend)

Getting Started

Prerequisites

• Python 3.10+
• Node.js 18+
• CoinGecko Pro API key
• OpenAI API key

Environment Variables

Create a .env file in the project root:

OPENAI_API_KEY=sk-...
COINGECKO_API_KEY=your-key
ALLOWED_ORIGINS=http://localhost:5173   # comma-separated origins for CORS
BASE_URL=http://localhost:8000          # used for CSV download links

Backend

python -m venv priceandmc
source priceandmc/bin/activate
pip install -r requirements.txt
uvicorn src.api.server:app --reload --port 8000

API docs available at http://localhost:8000/docs.

Frontend

cd frontend
npm install
npm run dev

Opens at http://localhost:5173. Vite proxies /api requests to the backend.

CLI Agent

python -m src.main

Interactive REPL — type crypto questions, reset to clear history, quit to exit.

Project Structure

src/
  main.py              # CLI entry point
  api/server.py        # FastAPI REST API
  agent/agent.py       # AI agent with tool-calling loop
  agent/tools.py       # Tools exposed to GPT-4o
  data/coingecko_client.py  # CoinGecko API client with caching
  data/analytics.py    # Correlation, risk metrics, sector analysis
  data/date_utils.py   # Quarter boundary utilities
frontend/
  src/pages/           # Dashboard, Explorer, Correlation, Risk, Sectors
  src/components/      # Charts, tables, filters, AI chat widget
  src/api/             # API client
database/              # Joblib-cached snapshots

API Endpoints

Endpoint	Description
GET /api/top-coins	Top N coins at quarter boundaries (filterable)
GET /api/top-coins/export	CSV download
GET /api/coin/{id}	Single coin snapshot at a date
GET /api/coin/{id}/history	Time-series data (quarterly/monthly/yearly)
GET /api/analytics/correlation	Price correlation matrix
GET /api/analytics/risk-metrics	Sharpe, Sortino, drawdown, VaR
GET /api/analytics/sectors	Sector performance aggregation
GET /api/quarters	Available quarter dates
GET /api/sectors	Token categories
POST /api/chat	AI agent conversation

Deployment

Backend deploys on Railway via Nixpacks (see Procfile and railway.json).

Frontend deploys on Vercel (see frontend/vercel.json). Set VITE_API_URL to your backend URL in Vercel environment settings.

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/your-feature)
3. Commit your changes (git commit -m 'Add your feature')
4. Push to the branch (git push origin feature/your-feature)
5. Open a Pull Request

License

MIT