AI-Trader/CHANGELOG.md

Changelog

All notable changes to the AI-Trader project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

Unreleased

0.2.0 - 2025-10-30

Added

• Complete Docker deployment support with containerization
• Docker Compose orchestration for easy local deployment
• Multi-stage Dockerfile with Python 3.10-slim base image
• Automated CI/CD pipeline via GitHub Actions for release builds
• Docker images published to GitHub Container Registry (ghcr.io)
• Comprehensive Docker documentation (docs/DOCKER.md)
• Release process documentation (docs/RELEASING.md)
• CLAUDE.md repository guidance for development
• Docker deployment section in main README
• Environment variable configuration via docker-compose
• Sequential startup script (entrypoint.sh) for data fetch, MCP services, and trading agent
• Volume mounts for data and logs persistence
• Pre-built image support from ghcr.io/hkuds/ai-trader

Changed

• Updated .env.example with Docker-specific configuration and paths
• Updated .gitignore to exclude git worktrees directory
• Removed deprecated version tag from docker-compose.yml

Fixed

• Docker Compose configuration now follows modern best practices (version-less)

0.1.0 - Initial Release

Added

• AI trading competition platform for NASDAQ 100 stocks
• Support for multiple AI models (GPT, Claude, Qwen, DeepSeek, Gemini)
• MCP (Model Context Protocol) toolchain integration
  • Mathematical calculation tools
  • Market intelligence search via Jina AI
  • Trading execution tools
  • Price query tools
• Historical replay architecture with anti-look-ahead controls
• Alpha Vantage API integration for price data
• Autonomous AI decision-making with zero human intervention
• Real-time performance analytics and leaderboard
• Position tracking and trading logs
• Web-based performance dashboard
• Complete NASDAQ 100 stock universe support
• Initial capital: $10,000 per AI model
• Configurable date range for backtesting
• Multi-model concurrent trading support
• Automatic data fetching and merging
• Comprehensive README with quick start guide

Technical Details

• Python 3.10+ support
• LangChain framework integration
• FastMCP for MCP service implementation
• JSONL format for position and log storage
• Weekday-only trading simulation
• Configurable agent parameters (max_steps, max_retries, initial_cash)

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Release Notes Template

For future releases, use this template:

## [X.Y.Z] - YYYY-MM-DD

### Added
- New features

### Changed
- Changes to existing functionality

### Deprecated
- Soon-to-be removed features

### Removed
- Removed features

### Fixed
- Bug fixes

### Security
- Security improvements

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