refactor: implement database-only position tracking with lazy context injection

This commit migrates the system to database-only position storage,
eliminating file-based position.jsonl dependencies and fixing
ContextInjector initialization timing issues.

Key Changes:

1. ContextInjector Lifecycle Refactor:
   - Remove ContextInjector creation from BaseAgent.__init__()
   - Add BaseAgent.set_context() method for post-initialization injection
   - Update ModelDayExecutor to create ContextInjector with correct trading day date
   - Ensures ContextInjector receives actual trading date instead of init_date
   - Includes session_id injection for proper database linking

2. Database Position Functions:
   - Implement get_today_init_position_from_db() for querying previous positions
   - Implement add_no_trade_record_to_db() for no-trade day handling
   - Both functions query SQLite directly (positions + holdings tables)
   - Handle first trading day case with initial cash return
   - Include comprehensive error handling and logging

3. System Integration:
   - Update get_agent_system_prompt() to use database queries
   - Update _handle_trading_result() to write no-trade records to database
   - Remove dependencies on position.jsonl file reading/writing
   - Use deployment_config for automatic prod/dev database resolution

Data Flow:
- ModelDayExecutor creates runtime config and trading session
- Agent initialized without context
- ContextInjector created with (signature, date, job_id, session_id)
- Context injected via set_context()
- System prompt queries database for yesterday's position
- Trade tools write directly to database
- No-trade handler creates database records

Fixes:
- ContextInjector no longer receives None values
- No FileNotFoundError for missing position.jsonl files
- Database is single source of truth for position tracking
- Session linking maintained across all position records

Design: docs/plans/2025-02-11-database-position-tracking-design.md

api/model_day_executor.py

@@ -129,12 +129,18 @@ class ModelDayExecutor:
             # Set environment variable for agent to use isolated config
             os.environ["RUNTIME_ENV_PATH"] = self.runtime_config_path
 
-            # Initialize agent
+            # Initialize agent (without context)
             agent = await self._initialize_agent()
 
-            # Update context injector with session_id
-            if hasattr(agent, 'context_injector') and agent.context_injector:
-                agent.context_injector.session_id = session_id
+            # Create and inject context with correct values
+            from agent.context_injector import ContextInjector
+            context_injector = ContextInjector(
+                signature=self.model_sig,
+                today_date=self.date,  # Current trading day
+                job_id=self.job_id,
+                session_id=session_id
+            )
+            agent.set_context(context_injector)
 
             # Run trading session
             logger.info(f"Running trading session for {self.model_sig} on {self.date}")