Removed noisy debug print statements that were added during
troubleshooting. The context injection is now working correctly
and no longer needs diagnostic output.
Cleaned up:
- Entry point logging
- Before/after injection logging
- Tool name and args logging
This commit implements Task 1 from the schema migration plan:
- Trade tools (buy/sell) now write to actions table instead of old positions table
- Added trading_day_id parameter to buy/sell functions
- Updated ContextInjector to inject trading_day_id
- Updated RuntimeConfigManager to include TRADING_DAY_ID in config
- Removed P&L calculation from trade functions (now done at trading_days level)
- Added tests verifying correct behavior with new schema
Changes:
- agent_tools/tool_trade.py: Modified _buy_impl and _sell_impl to write to actions table
- agent/context_injector.py: Added trading_day_id parameter and injection logic
- api/model_day_executor.py: Updated to read trading_day_id from runtime config
- api/runtime_manager.py: Added trading_day_id to config initialization
- tests/unit/test_trade_tools_new_schema.py: New tests for new schema compliance
All tests passing.
Root cause: AI models were hallucinating signature/job_id/today_date values
and passing them in tool calls. The ContextInjector was checking
"if param not in request.args" before injecting, which failed when AI
provided (incorrect) values.
Fix: Always override context parameters, never trust AI-provided values.
Evidence from logs:
- ContextInjector had correct values (self.signature=gpt-5, job_id=6dabd9e6...)
- But AI was passing signature=None or hallucinated values like "fundamental-bot-v1"
- After injection, args showed the AI's (wrong) values, not the interceptor's
This ensures runtime context is ALWAYS injected regardless of what the AI sends.
Fixes #TBD
Log ContextInjector instance ID and attribute values at entry to __call__()
to diagnose why attributes appear as None during tool invocation despite
being set correctly during set_context().
This will reveal whether:
- Multiple ContextInjector instances exist
- Attributes are being overwritten/cleared
- Wrong instance is being invoked
Complete rewrite of position management in MCP trade tools:
**Trade Tools (agent_tools/tool_trade.py)**
- Replace file-based position.jsonl reads with SQLite queries
- Add get_current_position_from_db() to query positions and holdings tables
- Rewrite buy() and sell() to write directly to database
- Calculate portfolio value and P&L metrics in tools
- Accept job_id and session_id parameters via ContextInjector
- Return errors with proper context for debugging
- Use deployment-aware database path resolution
**Context Injection (agent/context_injector.py)**
- Add job_id and session_id to constructor
- Inject job_id and session_id into buy/sell tool calls
- Support optional parameters (None in standalone mode)
**BaseAgent (agent/base_agent/base_agent.py)**
- Read JOB_ID from runtime config
- Pass job_id to ContextInjector during initialization
- Enable automatic context injection for API mode
**ModelDayExecutor (api/model_day_executor.py)**
- Add _initialize_starting_position() method
- Create initial position record before agent runs
- Load initial_cash from config
- Update context_injector.session_id after session creation
- Link positions to sessions automatically
**Architecture Changes:**
- Eliminates file-based position tracking entirely
- Single source of truth: SQLite database
- Positions automatically linked to trading sessions
- Concurrent execution safe (no file system conflicts)
- Deployment mode aware (prod vs dev databases)
This completes the migration to database-only position storage.
File-based position.jsonl is no longer used or created.
Fixes context injection errors in concurrent simulations.
The interceptor __call__ method must be async and follow the proper
signature: async __call__(request, handler) -> result
Previous implementation was synchronous and had wrong signature, causing
'object function can't be used in await expression' error.
Resolves issue where MCP trade tools couldn't access SIGNATURE and TODAY_DATE
during concurrent API simulations, causing "SIGNATURE environment variable is
not set" errors.
Problem:
- MCP services run as separate HTTP processes
- Multiple simulations execute concurrently via ThreadPoolExecutor
- Environment variables from executor process not accessible to MCP services
Solution:
- Add ContextInjector that implements ToolCallInterceptor
- Automatically injects signature and today_date into buy/sell tool calls
- Trade tools accept optional parameters, falling back to config/env
- BaseAgent creates interceptor and updates today_date per session
Changes:
- agent/context_injector.py: New interceptor for context injection
- agent/base_agent/base_agent.py: Create and use ContextInjector
- agent_tools/tool_trade.py: Add optional signature/today_date parameters
Benefits:
- Supports concurrent multi-model simulations
- Maintains backward compatibility with CLI mode
- AI model unaware of injected parameters
