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AI-Trader/CHANGELOG.md
Bill 849e7bffa2 refactor: remove unnecessary RUNTIME_ENV_PATH environment variable 
Simplifies deployment configuration by removing the RUNTIME_ENV_PATH
environment variable, which is no longer needed for API mode.

Changes:
- Remove RUNTIME_ENV_PATH from docker-compose.yml
- Remove RUNTIME_ENV_PATH from .env.example
- Update CLAUDE.md to reflect API-managed runtime configs
- Update README.md to remove RUNTIME_ENV_PATH from config examples
- Update CHANGELOG.md with this simplification

Technical details:
- API mode dynamically creates isolated runtime config files via
  RuntimeConfigManager (data/runtime_env_{job_id}_{model}_{date}.json)
- tools/general_tools.py already handles missing RUNTIME_ENV_PATH
  gracefully, returning empty dict and warning on writes
- No functional impact - all tests pass without this variable set
- Reduces configuration complexity for new deployments

Breaking change: None - variable was vestigial from batch mode era
2025-10-31 14:37:00 -04:00

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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

Changed

  • Simplified Configuration - Removed RUNTIME_ENV_PATH environment variable
    • No longer needed in docker-compose.yml or .env.example
    • API mode dynamically manages runtime configs via RuntimeConfigManager
    • Legacy tools gracefully handle missing RUNTIME_ENV_PATH
    • Reduces configuration complexity for new deployments

0.3.0 - 2025-10-31

Added - API Service Transformation

  • REST API Service - Complete FastAPI implementation for external orchestration
    • POST /simulate/trigger - Trigger simulation jobs with config, date range, and models
    • GET /simulate/status/{job_id} - Query job progress and execution details
    • GET /results - Retrieve simulation results with filtering (job_id, date, model)
    • GET /health - Service health check with database connectivity verification
  • SQLite Database - Complete persistence layer replacing JSONL files
    • Jobs table - Job metadata and lifecycle tracking
    • Job details table - Per model-day execution status
    • Positions table - Trading position records with P&L
    • Holdings table - Portfolio holdings breakdown
    • Reasoning logs table - AI decision reasoning history
    • Tool usage table - MCP tool usage statistics
  • Backend Components
    • JobManager - Job lifecycle management with concurrent job prevention
    • RuntimeConfigManager - Isolated runtime configs for thread-safe execution
    • ModelDayExecutor - Single model-day execution engine
    • SimulationWorker - Job orchestration with date-sequential, model-parallel execution
  • Comprehensive Test Suite
    • 102 unit and integration tests (85% coverage)
    • 19 database tests (98% coverage)
    • 23 job manager tests (98% coverage)
    • 10 model executor tests (84% coverage)
    • 20 API endpoint tests (81% coverage)
    • 20 Pydantic model tests (100% coverage)
    • 10 runtime manager tests (89% coverage)
  • Docker Deployment - Persistent REST API service
    • API-only deployment (batch mode removed for simplicity)
    • Single docker-compose service (ai-trader)
    • Health check configuration (30s interval, 3 retries)
    • Volume persistence for SQLite database and logs
    • Configurable API_PORT for flexible deployment
    • System dependencies (curl, procps) for health checks and debugging
  • Validation & Testing Tools
    • scripts/validate_docker_build.sh - Docker build and startup validation with port awareness
    • scripts/test_api_endpoints.sh - Complete API endpoint testing suite with port awareness
    • TESTING_GUIDE.md - Comprehensive testing procedures and troubleshooting (including port conflicts)
  • Documentation
    • DOCKER_API.md - API deployment guide with examples
    • TESTING_GUIDE.md - Validation procedures and troubleshooting
    • API endpoint documentation with request/response examples
    • Windmill integration patterns and examples

Changed

  • Architecture - Transformed from batch-only to API-first service with database persistence
  • Data Storage - Migrated from JSONL files to SQLite relational database
  • Deployment - Simplified to single API-only Docker service
  • Configuration - Added configurable API_PORT environment variable (default: 8080, customizable for port conflicts)
  • Requirements - Added fastapi>=0.120.0, uvicorn[standard]>=0.27.0, pydantic>=2.0.0
  • Docker Compose - Single service (ai-trader) instead of dual-mode
  • Dockerfile - Added system dependencies (curl, procps) and port 8080 exposure
  • .env.example - Enhanced API server configuration with port conflict documentation
  • Entrypoint - Unified entrypoint.sh with proper signal handling (exec uvicorn)

Technical Implementation

  • Test-Driven Development - All components written with tests first
  • Mock-based Testing - Avoid heavy dependencies in unit tests
  • Pydantic V2 - Type-safe request/response validation
  • Foreign Key Constraints - Database referential integrity with cascade deletes
  • Thread-safe Execution - Isolated runtime configs per model-day
  • Background Job Execution - ThreadPoolExecutor for parallel model execution
  • Automatic Status Transitions - Job status updates based on model-day completion

Performance & Quality

  • Code Coverage - 85% overall (84.63% measured)
    • Database layer: 98%
    • Job manager: 98%
    • Pydantic models: 100%
    • Runtime manager: 89%
    • Model executor: 84%
    • FastAPI app: 81%
  • Test Execution - 102 tests in ~2.5 seconds
  • Zero Test Failures - All tests passing (threading tests excluded)

Integration Ready

  • Windmill.dev - HTTP-based integration with polling support
  • External Orchestration - RESTful API for workflow automation
  • Monitoring - Health checks and status tracking
  • Persistence - SQLite database survives container restarts

Breaking Changes

  • Batch Mode Removed - All simulations now run through REST API
    • Simplifies deployment and eliminates dual-mode complexity
    • Focus on API-first architecture for external orchestration
    • Migration: Use POST /simulate/trigger endpoint instead of batch execution

0.2.0 - 2025-10-31

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
  • Automatic draft release creation with version tagging
  • Docker images published to GitHub Container Registry (ghcr.io)
  • Comprehensive Docker documentation (docs/DOCKER.md)
  • Release process documentation (docs/RELEASING.md)
  • Data cache reuse design documentation (docs/DESIGN_DATA_CACHE_REUSE.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/xe138/ai-trader
  • Configurable volume path for persistent data
  • Configurable web interface host port
  • Automated merged.jsonl creation during price fetching
  • API key registration URLs in .env.example

Changed

  • Updated .env.example with Docker-specific configuration, API key URLs, and paths
  • Updated .gitignore to exclude git worktrees directory
  • Removed deprecated version tag from docker-compose.yml
  • Updated repository URLs to Xe138/AI-Trader fork
  • Docker Compose now uses pre-built image by default
  • Simplified Docker config file selection with convention over configuration
  • Fixed internal ports with configurable host ports
  • Separated data scripts from volume mount directory
  • Reduced log flooding during data fetch
  • OPENAI_API_BASE can now be left empty in configuration

Fixed

  • Docker Compose configuration now follows modern best practices (version-less)
  • Prevent restart loop on missing API keys with proper validation
  • Docker tag generation now converts repository owner to lowercase
  • Validate GITHUB_REF is a tag in docker-release workflow
  • Correct Dockerfile FROM AS casing
  • Module import errors for MCP services resolved with PYTHONPATH
  • Prevent price data overwrite on container restart
  • Merge script now writes to current directory for volume compatibility

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)

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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