mirror of
https://github.com/Xe138/AI-Trader.git
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Bill
fb9583b374
Major architecture transformation from batch-only to API service with
database persistence for Windmill integration.
## REST API Implementation
- POST /simulate/trigger - Start simulation jobs
- GET /simulate/status/{job_id} - Monitor job progress
- GET /results - Query results with filters (job_id, date, model)
- GET /health - Service health checks
## Database Layer
- SQLite persistence with 6 tables (jobs, job_details, positions,
holdings, reasoning_logs, tool_usage)
- Foreign key constraints with cascade deletes
- Replaces JSONL file storage
## Backend Components
- JobManager: Job lifecycle management with concurrency control
- RuntimeConfigManager: Thread-safe isolated runtime configs
- ModelDayExecutor: Single model-day execution engine
- SimulationWorker: Date-sequential, model-parallel orchestration
## Testing
- 102 unit and integration tests (85% coverage)
- Database: 98% coverage
- Job manager: 98% coverage
- API endpoints: 81% coverage
- Pydantic models: 100% coverage
- TDD approach throughout
## Docker Deployment
- Dual-mode: API server (persistent) + batch (one-time)
- Health checks with 30s interval
- Volume persistence for database and logs
- Separate entrypoints for each mode
## Validation Tools
- scripts/validate_docker_build.sh - Build validation
- scripts/test_api_endpoints.sh - Complete API testing
- scripts/test_batch_mode.sh - Batch mode validation
- DOCKER_API.md - Deployment guide
- TESTING_GUIDE.md - Testing procedures
## Configuration
- API_PORT environment variable (default: 8080)
- Backwards compatible with existing configs
- FastAPI, uvicorn, pydantic>=2.0 dependencies
Co-Authored-By: AI Assistant <noreply@example.com>
94 lines
2.9 KiB
YAML
94 lines
2.9 KiB
YAML
services:
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# Batch mode: Run one-time simulations with config file
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ai-trader-batch:
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image: ghcr.io/xe138/ai-trader:latest
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# Uncomment to build locally instead of pulling:
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# build: .
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container_name: ai-trader-batch
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volumes:
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- ${VOLUME_PATH:-.}/data:/app/data
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- ${VOLUME_PATH:-.}/logs:/app/logs
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- ${VOLUME_PATH:-.}/configs:/app/configs
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environment:
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# AI Model API Configuration
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- OPENAI_API_BASE=${OPENAI_API_BASE}
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- OPENAI_API_KEY=${OPENAI_API_KEY}
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# Data Source Configuration
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- ALPHAADVANTAGE_API_KEY=${ALPHAADVANTAGE_API_KEY}
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- JINA_API_KEY=${JINA_API_KEY}
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# System Configuration
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- RUNTIME_ENV_PATH=/app/data/runtime_env.json
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# MCP Service Ports (fixed internally)
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- MATH_HTTP_PORT=8000
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- SEARCH_HTTP_PORT=8001
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- TRADE_HTTP_PORT=8002
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- GETPRICE_HTTP_PORT=8003
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# Agent Configuration
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- AGENT_MAX_STEP=${AGENT_MAX_STEP:-30}
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ports:
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# Format: "HOST:CONTAINER" - container ports are fixed, host ports configurable via .env
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- "${MATH_HTTP_PORT:-8000}:8000"
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- "${SEARCH_HTTP_PORT:-8001}:8001"
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- "${TRADE_HTTP_PORT:-8002}:8002"
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- "${GETPRICE_HTTP_PORT:-8003}:8003"
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- "${WEB_HTTP_PORT:-8888}:8888"
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restart: "no" # Batch jobs should not auto-restart
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profiles:
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- batch # Only start with: docker-compose --profile batch up
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# API mode: REST API server for Windmill integration
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ai-trader-api:
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image: ghcr.io/xe138/ai-trader:latest
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# Uncomment to build locally instead of pulling:
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# build: .
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container_name: ai-trader-api
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entrypoint: ["./entrypoint-api.sh"]
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volumes:
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- ${VOLUME_PATH:-.}/data:/app/data
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- ${VOLUME_PATH:-.}/logs:/app/logs
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- ${VOLUME_PATH:-.}/configs:/app/configs
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environment:
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# AI Model API Configuration
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- OPENAI_API_BASE=${OPENAI_API_BASE}
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- OPENAI_API_KEY=${OPENAI_API_KEY}
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# Data Source Configuration
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- ALPHAADVANTAGE_API_KEY=${ALPHAADVANTAGE_API_KEY}
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- JINA_API_KEY=${JINA_API_KEY}
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# System Configuration
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- RUNTIME_ENV_PATH=/app/data/runtime_env.json
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# MCP Service Ports (fixed internally)
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- MATH_HTTP_PORT=8000
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- SEARCH_HTTP_PORT=8001
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- TRADE_HTTP_PORT=8002
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- GETPRICE_HTTP_PORT=8003
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# API Configuration
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- API_PORT=${API_PORT:-8080}
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# Agent Configuration
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- AGENT_MAX_STEP=${AGENT_MAX_STEP:-30}
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ports:
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# MCP service ports (internal)
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- "${MATH_HTTP_PORT:-8000}:8000"
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- "${SEARCH_HTTP_PORT:-8001}:8001"
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- "${TRADE_HTTP_PORT:-8002}:8002"
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- "${GETPRICE_HTTP_PORT:-8003}:8003"
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# API server port (primary interface)
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- "${API_PORT:-8080}:8080"
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# Web dashboard
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- "${WEB_HTTP_PORT:-8888}:8888"
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restart: unless-stopped # Keep API server running
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healthcheck:
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test: ["CMD", "curl", "-f", "http://localhost:8080/health"]
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interval: 30s
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timeout: 10s
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retries: 3
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start_period: 40s
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