Document:
- New downloading_data status
- Warnings field in responses
- Async flow and monitoring
- Example usage patterns
Co-Authored-By: Claude <noreply@anthropic.com>
Test complete flow:
- Fast API response
- Background data download
- Status transitions
- Warning capture and display
Co-Authored-By: Claude <noreply@anthropic.com>
Move data preparation to background worker:
- Fast endpoint response (<1s)
- No blocking downloads
- Worker handles data download and filtering
- Maintains backwards compatibility
Co-Authored-By: Claude <noreply@anthropic.com>
Fix two failing unit tests by making mock executors properly simulate
the job detail status updates that real ModelDayExecutor performs:
- test_run_updates_job_status_to_completed
- test_run_handles_partial_failure
Root cause: Tests mocked ModelDayExecutor but didn't simulate the
update_job_detail_status() calls. The implementation relies on these
calls to automatically transition job status from pending to
completed/partial/failed.
Solution: Mock executors now call manager.update_job_detail_status()
to properly simulate the status update lifecycle:
1. Update to "running" when execution starts
2. Update to "completed" or "failed" when execution finishes
This matches the real ModelDayExecutor behavior and allows the
automatic job status transition logic in JobManager to work correctly.
Update existing simulation_worker unit tests to account for new _prepare_data integration:
- Mock _prepare_data to return available dates
- Update mock executors to return proper result dicts with model/date fields
Note: Some tests need additional work to properly verify job status updates.
Co-Authored-By: Claude <noreply@anthropic.com>
Call _prepare_data before executing trades:
- Download missing data if needed
- Filter completed dates
- Store warnings
- Handle empty date scenarios
Co-Authored-By: Claude <noreply@anthropic.com>
Orchestrate data preparation phase:
- Check missing data
- Download if needed
- Filter completed dates
- Update job status
Co-Authored-By: Claude <noreply@anthropic.com>
Critical fixes identified in code review:
1. Add warnings column migration to _migrate_schema()
- Checks if warnings column exists in jobs table
- Adds column via ALTER TABLE if missing
- Ensures existing databases get new column on upgrade
2. Document CHECK constraint limitation
- Added docstring explaining ALTER TABLE cannot add CHECK constraints
- Notes that "downloading_data" status requires fresh DB or manual migration
3. Add comprehensive migration tests
- test_migration_adds_warnings_column: Verifies warnings column migration
- test_migration_adds_simulation_run_id_column: Tests existing migration
- Both tests include cleanup to prevent cross-test contamination
4. Update test fixtures and expectations
- Updated clean_db fixture to delete from all 9 tables
- Fixed table count assertions (6 -> 9 tables)
- Updated expected columns in schema tests
All 21 database tests now pass.
Add support for:
- downloading_data job status for visibility during data prep
- warnings TEXT column for storing job-level warnings (JSON array)
Co-Authored-By: Claude <noreply@anthropic.com>
Add comprehensive design for moving price data downloads from
synchronous API endpoint to background worker thread.
Key changes:
- Fast API response (<1s) by deferring download to worker
- New job status "downloading_data" for visibility
- Graceful rate limit handling with warnings
- Enhanced logging for dev mode monitoring
- Backwards compatible API changes
Resolves API timeout issue when downloading missing price data.
Co-Authored-By: Claude <noreply@anthropic.com>
Add design document for layered configuration system that enables
per-deployment model customization while maintaining defaults.
Key features:
- Default config baked into image, user config via volume mount
- Root-level merge with user config taking precedence
- Fail-fast validation at container startup
- Clear error messages on validation failure
Addresses issue where mounted configs would overwrite default config
in image.
- Add FastAPI @app.on_event("startup") handler to display warning
- Previously only appeared when running directly (not via uvicorn)
- Add DEPLOYMENT_MODE and PRESERVE_DEV_DATA to docker-compose.yml
- Update CHANGELOG.md with fix documentation
Fixes issue where dev mode banner wasn't visible in Docker logs
because uvicorn imports app without executing __main__ block.
BREAKING CHANGE: end_date is now required and cannot be null/empty
New Features:
- Resume mode: Set start_date to null to continue from last completed date per model
- Idempotent by default: Skip already-completed dates with replace_existing=false
- Per-model independence: Each model resumes from its own last completed date
- Cold start handling: If no data exists in resume mode, runs only end_date as single day
API Changes:
- start_date: Now optional (null enables resume mode)
- end_date: Now REQUIRED (cannot be null or empty string)
- replace_existing: New optional field (default: false for idempotent behavior)
Implementation:
- Added JobManager.get_last_completed_date_for_model() method
- Added JobManager.get_completed_model_dates() method
- Updated create_job() to support model_day_filter for selective task creation
- Fixed bug with start_date=None in price data checks
Documentation:
- Updated API_REFERENCE.md with complete examples and behavior matrix
- Updated QUICK_START.md with resume mode examples
- Updated docs/user-guide/using-the-api.md
- Added CHANGELOG_NEW_API.md with migration guide
- Updated all integration tests for new schema
- Updated client library examples (Python, TypeScript)
Migration:
- Old: {"start_date": "2025-01-16"}
- New: {"start_date": "2025-01-16", "end_date": "2025-01-16"}
- Resume: {"start_date": null, "end_date": "2025-01-31"}
See CHANGELOG_NEW_API.md for complete details.
Add comprehensive warning display when server starts in development mode
to ensure users are aware of simulated AI calls and data handling.
Changes:
- Add log_dev_mode_startup_warning() function in deployment_config.py
- Display warning on main.py startup when DEPLOYMENT_MODE=DEV
- Display warning on API server startup (api/main.py)
- Warning shows AI simulation status and data persistence behavior
- Provides clear instructions for switching to PROD mode
The warning is highly visible and informs users that:
- AI API calls are simulated (no costs incurred)
- Data may be reset between runs (based on PRESERVE_DEV_DATA)
- System is using isolated dev database and paths
Co-Authored-By: Claude <noreply@anthropic.com>
- Add v1.1.0 API Authentication & Security as next priority after v1.0.0
- Include comprehensive security features: API keys, RBAC, rate limiting, audit trail
- Add security warning to v1.0.0 noting lack of authentication
- Resequence all subsequent versions (v1.1-v1.6) to accommodate new feature
- Update version history to reflect new roadmap structure
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Major changes:
- Simplified v0.4.0 to focus on smart date-based simulation API with automatic resume
- Added v1.0.0 milestone for production stability, testing, and validation
- Reorganized post-1.0 features into manageable v1.x releases:
- v1.1.0: Position history & analytics
- v1.2.0: Performance metrics & analytics
- v1.3.0: Data management API
- v1.4.0: Web dashboard UI
- v1.5.0: Advanced configuration & customization
- Moved quantitative modeling to v2.0.0 (major version bump)
Key improvements:
- v0.4.0 now has single /simulate/to-date endpoint with idempotent behavior
- Explicit force_resimulate flag prevents accidental re-simulation
- v1.0.0 includes comprehensive quality gates and production readiness checklist
- Each v1.x release focuses on specific domain for easier implementation
Complete rebrand of project to reflect REST API service architecture:
- Updated all documentation (README, guides, API reference)
- Updated Docker configuration (compose, Dockerfile, images)
- Updated all repository URLs to Xe138/AI-Trader-Server
- Updated all Docker images to ghcr.io/xe138/ai-trader-server
- Added fork acknowledgment crediting HKUDS/AI-Trader
- Updated GitHub Actions workflows and shell scripts
All 4 phases completed with validation checkpoints.
Co-Authored-By: Claude <noreply@anthropic.com>
Update all shell scripts to use the new AI-Trader-Server naming throughout.
Changes:
- main.sh: Update comments and echo statements
- entrypoint.sh: Update startup message
- scripts/validate_docker_build.sh: Update title, container name references,
and docker image tag from ai-trader-test to ai-trader-server-test
- scripts/test_api_endpoints.sh: Update title and docker-compose command
Part of Phase 4: Internal Configuration & Metadata (Task 19)
Update deployment documentation files:
- docker-deployment.md: Update git clone URL, Docker image references
(ghcr.io/xe138/ai-trader to ghcr.io/xe138/ai-trader-server), and
container/service names (ai-trader to ai-trader-server)
- monitoring.md: Update container names in all docker commands
- scaling.md: Update multi-instance service names and Docker image
references
All deployment examples now use ai-trader-server naming.
Part of Phase 3: Developer & Deployment Documentation
Update developer documentation files:
- CONTRIBUTING.md: Update title to AI-Trader-Server
- development-setup.md: Update git clone URL from
github.com/Xe138/AI-Trader to github.com/Xe138/AI-Trader-Server
- testing.md: Update title to reference AI-Trader-Server
Part of Phase 3: Developer & Deployment Documentation
Update all user-guide documentation files:
- configuration.md: Update title and container name references
- using-the-api.md: Update title
- integration-examples.md: Update title, class names
(AsyncAITraderServerClient), container names, DAG names, and log paths
- troubleshooting.md: Update title, container names (ai-trader to
ai-trader-server), GitHub issues URL
All Docker commands and code examples now reference ai-trader-server
container name.
Part of Phase 3: Developer & Deployment Documentation
Added dev database files and dev_agent_data directory to gitignore
to prevent runtime dev data from being committed to the repository.
Patterns added:
- data/jobs_dev.db
- data/*_dev.db
- data/dev_agent_data/
This ensures dev mode runtime data remains local and doesn't pollute
version control.
Added comprehensive implementation plan for development mode feature
and test configuration used during verification.
Files:
- docs/plans/2025-11-01-dev-mode-mock-ai.md: Complete 12-task plan
- configs/test_dev_mode.json: Test configuration for dev mode
These files document the feature implementation process and provide
reference configurations for testing.
Fix critical bug where dev mode was initializing the production database
path instead of the dev database path. The initialize_dev_database() call
now correctly uses get_db_path() to resolve to data/jobs_dev.db.
Impact:
- Before: DEV mode would reset data/jobs.db (production database)
- After: DEV mode correctly resets data/jobs_dev.db (dev database)
Testing:
- Verified database isolation between dev and prod
- Confirmed PRESERVE_DEV_DATA flag works correctly
- Validated dev mode banner and deployment mode detection
Documentation:
- Added comprehensive manual verification results
- Documented all test cases and outcomes
- Recorded fix details for future reference
Task: Task 12 - Manual Verification and Final Testing
Plan: docs/plans/2025-11-01-dev-mode-mock-ai.md
Update project overview and Docker commands to reflect AI-Trader-Server
naming:
- Change project description to emphasize REST API service
- Update Docker image references from ghcr.io/hkuds/ai-trader to
ghcr.io/xe138/ai-trader-server
- Update container names from ai-trader to ai-trader-server
- Update GitHub Actions URL to Xe138/AI-Trader-Server repository
Part of Phase 3: Developer & Deployment Documentation
Update main header comment from 'AI-Trader Environment Configuration' to
'AI-Trader-Server Environment Configuration'
Part of Phase 2: Configuration Files rebrand
Add OCI-compliant metadata labels:
- Title: AI-Trader-Server
- Description: REST API service for autonomous AI trading competitions
- Source: https://github.com/Xe138/AI-Trader-Server
Part of Phase 2: Configuration Files rebrand
Update service name from 'ai-trader' to 'ai-trader-server'
Update container name from 'ai-trader' to 'ai-trader-server'
Update Docker image reference to ghcr.io/xe138/ai-trader-server:latest
Part of Phase 2: Configuration Files rebrand
Add comprehensive development mode documentation to README.md, API_REFERENCE.md, and CLAUDE.md:
README.md:
- New "Development Mode" section after Configuration
- Quick start guide with environment variables
- Explanation of DEV vs PROD mode behavior
- Mock AI behavior and stock rotation details
- Environment variables reference
- Use cases and limitations
API_REFERENCE.md:
- New "Deployment Mode" section after health check
- Response format with deployment_mode fields
- DEV mode behavior explanation
- Health check example with deployment fields
- Use cases for testing and CI/CD
CLAUDE.md:
- New "Development Mode" subsection in Important Implementation Details
- Deployment modes overview
- DEV mode characteristics
- Implementation details with file references
- Testing commands and mock behavior notes
All sections explain:
- DEPLOYMENT_MODE environment variable (PROD/DEV)
- PRESERVE_DEV_DATA flag for dev data persistence
- Mock AI provider with deterministic stock rotation
- Separate dev database and data paths
- Use cases for development and testing
