Fixed critical bug where ModelDayExecutor._initialize_agent() created
a BaseAgent but never called agent.initialize(), leaving self.model=None.
This caused 'NoneType' object has no attribute 'bind' error when
run_trading_session() tried to create the langchain agent.
Changes:
- Made _initialize_agent() async
- Added await agent.initialize() call
- Updated call site to await async function
Now properly initializes MCP client, tools, and AI model before
executing trading sessions, matching the working CLI mode pattern.
- Add _create_trading_session() method to create session records
- Add async _store_reasoning_logs() to store conversation with AI summaries
- Add async _update_session_summary() to generate overall session summary
- Modify execute() -> execute_async() with async workflow
- Add execute_sync() wrapper and keep execute() as sync entry point
- Update _write_results_to_db() to accept and use session_id parameter
- Modify positions INSERT to include session_id foreign key
- Remove old reasoning_logs code block (obsolete schema)
- Add comprehensive unit tests for all new functionality
All tests pass. Session-based reasoning storage now integrated.
- Fix async call in model_day_executor.py by wrapping with asyncio.run()
Resolves RuntimeWarning where run_trading_session coroutine was never awaited
- Remove register_agent() call in API mode to prevent file-based position storage
Position data is now stored exclusively in SQLite database (jobs.db)
- Update test mocks to use AsyncMock for async run_trading_session method
This fixes production deployment issues:
1. Trading sessions now execute properly (async bug)
2. No position files created, database-only storage
3. All tests pass
Closes issue with no trades being executed in production
