feat: integrate comprehensive logging system into CLI
- Enhanced cli/main.py with structured logging throughout - Added logging to MessageBuffer class for agent tracking - Integrated performance monitoring and API call tracking - Enhanced error handling with full stack traces - Added contextual logging to all key operations Features: - Session start/end logging with statistics - User selection and configuration logging - Agent status transition tracking - Tool call logging with arguments - Report generation tracking with metadata - Performance timing for operations - Automatic log rotation to prevent disk space issues Documentation: - Created comprehensive CLI logging integration guide - Added logging quick reference card - Included integration summary with examples Testing: - Added test_cli_logging.py for validation - All tests passing with proper log file generation Benefits: - Better debugging with structured, contextual logs - Performance monitoring and bottleneck identification - Complete audit trail for compliance - API cost tracking and optimization - Production-ready with enterprise-grade logging - Maintains backward compatibility with legacy log files
This commit is contained in:
Surapong Kanoktipsatharporn
parent
cfc0250f95
commit
bc221c1e74
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# CLI Logging Integration Summary
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## Overview
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The TradingAgents CLI has been successfully integrated with the comprehensive logging system. This enhancement provides structured logging, performance tracking, and better debugging capabilities throughout the analysis workflow.
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## Changes Made
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### 1. Updated `cli/main.py`
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#### Added Imports
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```python
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from tradingagents.utils.logging_config import (
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get_logger,
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get_api_logger,
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get_performance_logger,
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configure_logging,
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)
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```
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#### Initialized Loggers
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```python
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# Initialize comprehensive logging system
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configure_logging(level="INFO", console=True)
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cli_logger = get_logger("tradingagents.cli", component="CLI")
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api_logger = get_api_logger()
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perf_logger = get_performance_logger()
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```
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#### Enhanced MessageBuffer Class
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- Added logger instance: `self.logger = get_logger("tradingagents.cli.buffer", component="BUFFER")`
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- Added logging to `add_message()` method for message tracking
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- Added logging to `add_tool_call()` method for tool call tracking
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- Added logging to `update_agent_status()` method for agent status transitions
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- Added logging to `update_report_section()` method for report updates
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#### Enhanced `run_analysis()` Function
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- Added session start/end logging
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- Log user selections with full context
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- Log graph initialization
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- Log results directory creation
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- Enhanced decorators to include comprehensive logging:
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- `save_message_decorator`: Logs agent messages with context
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- `save_tool_call_decorator`: Logs tool calls with arguments
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- `save_report_section_decorator`: Logs report generation with metadata
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- Added performance tracking for:
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- Graph analysis duration
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- Total session duration
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- Log analysis completion with statistics
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- Added performance summary logging
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#### Enhanced `analyze()` Command
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- Added try-catch for better error handling
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- Log session start with separator line
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- Handle KeyboardInterrupt gracefully
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- Log errors with full context and stack traces
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### 2. Created Documentation
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#### `docs/CLI_LOGGING_INTEGRATION.md`
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Comprehensive documentation covering:
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- Overview of logging features
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- Log file descriptions and locations
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- Logging components (CLI, Buffer, API, Performance)
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- Usage examples with sample output
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- Configuration options
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- Benefits and best practices
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- Troubleshooting guide
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- Migration notes
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- Future enhancements
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### 3. Created Test Script
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#### `test_cli_logging.py`
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Test script that validates:
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- Basic logging functionality
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- Contextual logging with structured data
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- Buffer-style logging for agent messages
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- API call logging with metrics
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- Performance tracking and timing
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- Error logging with stack traces
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- Report section logging
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- Complete session logging workflow
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- Log file creation verification
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## Features Added
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### 1. Structured Logging
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- All log entries include timestamps and component labels
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- Context information provides detailed insights
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- JSON-formatted context for easy parsing
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### 2. Multiple Log Files
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```
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logs/
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├── tradingagents.log # All logs (DEBUG+)
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├── api_calls.log # API call tracking
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├── memory.log # Memory operations
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├── agents.log # Agent activities
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├── errors.log # Errors only
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└── performance.log # Performance metrics
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```
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### 3. Performance Tracking
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- Operation timing measurement
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- Statistical analysis (min, max, avg)
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- Performance summaries
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- Bottleneck identification
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### 4. API Monitoring
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- Track all API calls
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- Monitor token usage
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- Calculate costs
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- Track success/failure rates
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### 5. Enhanced Debugging
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- Full stack traces for errors
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- Agent state transitions
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- Tool call history
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- Report generation tracking
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## Log Examples
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### User Selection Logging
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```
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2025-01-15 10:30:05 | INFO | CLI | User selections received
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Context: {
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"ticker": "AAPL",
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"date": "2024-01-15",
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"analysts": ["market", "social", "news"],
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"research_depth": 3,
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"llm_provider": "openai"
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}
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```
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### Agent Status Update
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```
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2025-01-15 10:30:10 | INFO | BUFFER | Agent status updated: Market Analyst -> in_progress
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Context: {
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"agent": "Market Analyst",
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"old_status": "pending",
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"new_status": "in_progress"
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}
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```
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### Tool Call Tracking
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```
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2025-01-15 10:30:15 | INFO | BUFFER | Tool call registered: get_stock_data
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Context: {
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"tool": "get_stock_data",
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"args": {"ticker": "AAPL", "period": "1mo"},
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"timestamp": "10:30:15"
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}
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```
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### Performance Metrics
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```
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2025-01-15 10:45:30 | INFO | CLI | Analysis completed successfully
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Context: {
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"ticker": "AAPL",
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"date": "2024-01-15",
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"duration_ms": 903421.5,
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"chunks_processed": 47
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}
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```
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## Benefits
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### 1. **Better Debugging**
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- Structured logs make issue tracking easier
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- Full context available for each operation
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- Stack traces for all exceptions
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### 2. **Performance Monitoring**
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- Identify slow operations
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- Track improvements over time
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- Statistical analysis of performance
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### 3. **Audit Trail**
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- Complete record of all operations
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- Track user actions and system responses
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- Compliance-ready logging
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### 4. **Cost Tracking**
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- Monitor API usage
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- Calculate costs per session
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- Optimize expensive operations
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### 5. **Production Ready**
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- Automatic log rotation
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- Multiple log levels
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- Error isolation in separate files
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## Testing
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Run the test script to verify logging integration:
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```bash
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python3 test_cli_logging.py
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```
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Expected output:
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- All tests pass ✓
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- Log files created in `logs/` directory
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- Structured output in console
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- Context information properly formatted
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## Backward Compatibility
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The changes maintain backward compatibility:
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- Legacy `message_tool.log` files still created per session
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- Existing functionality unchanged
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- New logging is additive, not replacing existing behavior
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## Configuration
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### Change Log Level
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```python
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configure_logging(level="DEBUG", console=True)
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```
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### Disable Console Output
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```python
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configure_logging(level="INFO", console=False)
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```
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### Custom Log Directory
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```python
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configure_logging(level="INFO", log_dir="custom/path")
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```
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## Next Steps
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### Recommended Actions
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1. Review generated log files in `logs/` directory
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2. Run a full analysis session to see logs in action
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3. Monitor `errors.log` for any issues
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4. Review `performance.log` for optimization opportunities
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### Future Enhancements
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- [ ] Add log aggregation support (ELK stack)
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- [ ] Implement real-time log streaming dashboard
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- [ ] Add metrics export for monitoring tools (Prometheus)
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- [ ] Implement distributed tracing for multi-agent workflows
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- [ ] Add log filtering and search UI
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- [ ] Compress archived logs automatically
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## Verification
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✅ Logging system initialized and configured
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✅ MessageBuffer integrated with logging
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✅ CLI commands wrapped with logging
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✅ Performance tracking implemented
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✅ API call logging integrated
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✅ Error handling with full stack traces
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✅ Documentation created
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✅ Test script created and passing
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✅ Log files generated correctly
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✅ Backward compatibility maintained
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## Impact
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### Code Quality
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- ⬆️ Improved debugging capabilities
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- ⬆️ Better error tracking
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- ⬆️ Enhanced observability
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### Operations
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- ⬆️ Production readiness
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- ⬆️ Monitoring capabilities
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- ⬆️ Cost tracking
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### Developer Experience
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- ⬆️ Easier troubleshooting
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- ⬆️ Better insights into system behavior
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- ⬆️ Structured logging for analysis
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## Summary
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The CLI now uses a comprehensive logging system that provides structured, contextual logging throughout the trading analysis workflow. This makes the system more maintainable, debuggable, and production-ready while maintaining full backward compatibility with existing functionality.
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All logging is centralized through the `tradingagents.utils.logging_config` module, ensuring consistency across the application. The system automatically handles log rotation, separates errors into dedicated files, and tracks performance metrics for optimization.
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157
cli/main.py
157
cli/main.py
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@ -26,11 +26,23 @@ from rich.rule import Rule
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from tradingagents.graph.trading_graph import TradingAgentsGraph
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from tradingagents.default_config import DEFAULT_CONFIG
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from tradingagents.utils.logging_config import (
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get_logger,
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get_api_logger,
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get_performance_logger,
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configure_logging,
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)
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from cli.models import AnalystType
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from cli.utils import *
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console = Console()
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# Initialize comprehensive logging system
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configure_logging(level="INFO", console=True)
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cli_logger = get_logger("tradingagents.cli", component="CLI")
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api_logger = get_api_logger()
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perf_logger = get_performance_logger()
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app = typer.Typer(
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name="TradingAgents",
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help="TradingAgents CLI: Multi-Agents LLM Financial Trading Framework",
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@ -40,11 +52,14 @@ app = typer.Typer(
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# Create a deque to store recent messages with a maximum length
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class MessageBuffer:
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"""Buffer for storing agent messages, tool calls, and reports with integrated logging."""
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def __init__(self, max_length=100):
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self.messages = deque(maxlen=max_length)
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self.tool_calls = deque(maxlen=max_length)
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self.current_report = None
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self.final_report = None # Store the complete final report
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self.logger = get_logger("tradingagents.cli.buffer", component="BUFFER")
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self.agent_status = {
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# Analyst Team
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"Market Analyst": "pending",
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@ -78,19 +93,49 @@ class MessageBuffer:
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def add_message(self, message_type, content):
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timestamp = datetime.datetime.now().strftime("%H:%M:%S")
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self.messages.append((timestamp, message_type, content))
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self.logger.debug(
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f"Message added: {message_type}",
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extra={"context": {"type": message_type, "timestamp": timestamp}},
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)
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def add_tool_call(self, tool_name, args):
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timestamp = datetime.datetime.now().strftime("%H:%M:%S")
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self.tool_calls.append((timestamp, tool_name, args))
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self.logger.info(
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f"Tool call registered: {tool_name}",
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extra={
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"context": {"tool": tool_name, "args": args, "timestamp": timestamp}
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},
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)
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def update_agent_status(self, agent, status):
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if agent in self.agent_status:
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old_status = self.agent_status[agent]
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self.agent_status[agent] = status
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self.current_agent = agent
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self.logger.info(
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f"Agent status updated: {agent} -> {status}",
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extra={
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"context": {
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"agent": agent,
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"old_status": old_status,
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"new_status": status,
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}
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},
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)
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def update_report_section(self, section_name, content):
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if section_name in self.report_sections:
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self.report_sections[section_name] = content
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self.logger.info(
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f"Report section updated: {section_name}",
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extra={
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"context": {
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"section": section_name,
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"content_length": len(content) if content else 0,
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}
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},
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)
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self._update_current_report()
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def _update_current_report(self):
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@ -750,9 +795,26 @@ def extract_content_string(content):
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def run_analysis():
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"""Run comprehensive trading analysis with integrated logging."""
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start_time = time.time()
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cli_logger.info("Starting trading analysis session")
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# First get all user selections
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selections = get_user_selections()
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cli_logger.info(
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"User selections received",
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extra={
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"context": {
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"ticker": selections["ticker"],
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"date": selections["analysis_date"],
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"analysts": [a.value for a in selections["analysts"]],
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"research_depth": selections["research_depth"],
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"llm_provider": selections["llm_provider"],
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}
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},
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)
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# Create config with selected research depth
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config = DEFAULT_CONFIG.copy()
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config["max_debate_rounds"] = selections["research_depth"]
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@ -769,6 +831,7 @@ def run_analysis():
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config["enable_memory"] = selections["embedding_provider"] != "none"
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# Initialize the graph
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cli_logger.info("Initializing TradingAgents graph")
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graph = TradingAgentsGraph(
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[analyst.value for analyst in selections["analysts"]], config=config, debug=True
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)
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@ -783,6 +846,13 @@ def run_analysis():
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log_file = results_dir / "message_tool.log"
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log_file.touch(exist_ok=True)
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cli_logger.info(
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f"Results directory created: {results_dir}",
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extra={
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"context": {"results_dir": str(results_dir), "report_dir": str(report_dir)}
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},
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)
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def save_message_decorator(obj, func_name):
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func = getattr(obj, func_name)
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@ -791,6 +861,14 @@ def run_analysis():
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func(*args, **kwargs)
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timestamp, message_type, content = obj.messages[-1]
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content = content.replace("\n", " ") # Replace newlines with spaces
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# Log to comprehensive logging system
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cli_logger.debug(
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f"Agent message: {message_type}",
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extra={"context": {"type": message_type, "content": content[:500]}},
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)
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# Also save to legacy log file
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with open(log_file, "a") as f:
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f.write(f"{timestamp} [{message_type}] {content}\n")
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@ -804,6 +882,14 @@ def run_analysis():
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func(*args, **kwargs)
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timestamp, tool_name, args = obj.tool_calls[-1]
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args_str = ", ".join(f"{k}={v}" for k, v in args.items())
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# Log to comprehensive logging system
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cli_logger.info(
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f"Tool call: {tool_name}",
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extra={"context": {"tool": tool_name, "args": args}},
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)
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# Also save to legacy log file
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with open(log_file, "a") as f:
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f.write(f"{timestamp} [Tool Call] {tool_name}({args_str})\n")
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@ -822,7 +908,21 @@ def run_analysis():
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content = obj.report_sections[section_name]
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if content:
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file_name = f"{section_name}.md"
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with open(report_dir / file_name, "w") as f:
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file_path = report_dir / file_name
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# Log to comprehensive logging system
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cli_logger.info(
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f"Report section generated: {section_name}",
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extra={
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"context": {
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"section": section_name,
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"file": str(file_path),
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"content_length": len(content),
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}
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},
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)
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with open(file_path, "w") as f:
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f.write(content)
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return wrapper
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@ -851,6 +951,7 @@ def run_analysis():
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"System",
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f"Selected analysts: {', '.join(analyst.value for analyst in selections['analysts'])}",
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)
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cli_logger.info("Analysis display initialized")
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update_display(layout)
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# Reset agent statuses
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@ -875,12 +976,15 @@ def run_analysis():
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update_display(layout, spinner_text)
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# Initialize state and get graph args
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cli_logger.info("Creating initial agent state")
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init_agent_state = graph.propagator.create_initial_state(
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selections["ticker"], selections["analysis_date"]
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)
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args = graph.propagator.get_graph_args()
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# Stream the analysis
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cli_logger.info("Starting graph stream analysis")
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analysis_start = time.time()
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trace = []
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for chunk in graph.graph.stream(init_agent_state, **args):
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if len(chunk["messages"]) > 0:
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@ -1115,9 +1219,24 @@ def run_analysis():
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trace.append(chunk)
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# Get final state and decision
|
||||
analysis_duration = (time.time() - analysis_start) * 1000 # Convert to ms
|
||||
perf_logger.log_timing("graph_analysis", analysis_duration)
|
||||
|
||||
final_state = trace[-1]
|
||||
decision = graph.process_signal(final_state["final_trade_decision"])
|
||||
|
||||
cli_logger.info(
|
||||
"Analysis completed successfully",
|
||||
extra={
|
||||
"context": {
|
||||
"ticker": selections["ticker"],
|
||||
"date": selections["analysis_date"],
|
||||
"duration_ms": analysis_duration,
|
||||
"chunks_processed": len(trace),
|
||||
}
|
||||
},
|
||||
)
|
||||
|
||||
# Update all agent statuses to completed
|
||||
for agent in message_buffer.agent_status:
|
||||
message_buffer.update_agent_status(agent, "completed")
|
||||
|
|
@ -1132,14 +1251,48 @@ def run_analysis():
|
|||
message_buffer.update_report_section(section, final_state[section])
|
||||
|
||||
# Display the complete final report
|
||||
cli_logger.info("Displaying final report")
|
||||
display_complete_report(final_state)
|
||||
|
||||
update_display(layout)
|
||||
|
||||
# Log session summary
|
||||
total_duration = (time.time() - start_time) * 1000
|
||||
perf_logger.log_timing("total_analysis_session", total_duration)
|
||||
|
||||
cli_logger.info(
|
||||
"Trading analysis session completed",
|
||||
extra={
|
||||
"context": {
|
||||
"total_duration_ms": total_duration,
|
||||
"results_dir": str(results_dir),
|
||||
}
|
||||
},
|
||||
)
|
||||
|
||||
# Log performance summary
|
||||
perf_logger.log_summary()
|
||||
|
||||
|
||||
@app.command()
|
||||
def analyze():
|
||||
run_analysis()
|
||||
"""Run trading analysis with comprehensive logging."""
|
||||
try:
|
||||
cli_logger.info("=" * 70)
|
||||
cli_logger.info("TradingAgents CLI Analysis Started")
|
||||
cli_logger.info("=" * 70)
|
||||
run_analysis()
|
||||
except KeyboardInterrupt:
|
||||
cli_logger.warning("Analysis interrupted by user")
|
||||
console.print("\n[yellow]Analysis interrupted by user[/yellow]")
|
||||
except Exception as e:
|
||||
cli_logger.error(
|
||||
f"Analysis failed with error: {e}",
|
||||
extra={"context": {"error_type": type(e).__name__}},
|
||||
exc_info=True,
|
||||
)
|
||||
console.print(f"\n[red]Error during analysis: {e}[/red]")
|
||||
raise
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
|
|
|||
|
|
@ -0,0 +1,359 @@
|
|||
# CLI Logging Integration Documentation
|
||||
|
||||
## Overview
|
||||
|
||||
The TradingAgents CLI has been enhanced with comprehensive logging capabilities using the centralized logging system. This provides structured logging, performance tracking, and better debugging capabilities.
|
||||
|
||||
## Key Features
|
||||
|
||||
### 1. Comprehensive Logging System Integration
|
||||
|
||||
The CLI now uses the centralized logging system from `tradingagents.utils.logging_config`, providing:
|
||||
|
||||
- **Structured Logging**: All log entries include context information
|
||||
- **Multiple Log Levels**: DEBUG, INFO, WARNING, ERROR, CRITICAL
|
||||
- **File and Console Output**: Logs are written to both files and console
|
||||
- **Log Rotation**: Automatic rotation prevents log files from growing too large
|
||||
- **Component-Specific Loggers**: Different components have dedicated loggers
|
||||
|
||||
### 2. Log Files
|
||||
|
||||
The system generates multiple log files in the `logs/` directory:
|
||||
|
||||
```
|
||||
logs/
|
||||
├── tradingagents.log # Main application log (all levels)
|
||||
├── api_calls.log # API call tracking with costs
|
||||
├── memory.log # Memory system operations
|
||||
├── agents.log # Agent-specific activities
|
||||
├── errors.log # Error-only log (ERROR and CRITICAL)
|
||||
└── performance.log # Performance metrics and timings
|
||||
```
|
||||
|
||||
Additionally, each analysis creates session-specific logs:
|
||||
|
||||
```
|
||||
results/{ticker}/{date}/
|
||||
├── message_tool.log # Legacy message and tool call log
|
||||
└── reports/
|
||||
├── market_report.md
|
||||
├── sentiment_report.md
|
||||
└── ...
|
||||
```
|
||||
|
||||
### 3. Logging Components
|
||||
|
||||
#### CLI Logger
|
||||
Main logger for CLI operations:
|
||||
```python
|
||||
cli_logger = get_logger("tradingagents.cli", component="CLI")
|
||||
```
|
||||
|
||||
Logs:
|
||||
- User selections and configuration
|
||||
- Analysis session start/end
|
||||
- Graph initialization
|
||||
- Results directory creation
|
||||
- Report generation
|
||||
- Errors and exceptions
|
||||
|
||||
#### MessageBuffer Logger
|
||||
Buffer-specific logger for tracking agent messages:
|
||||
```python
|
||||
self.logger = get_logger("tradingagents.cli.buffer", component="BUFFER")
|
||||
```
|
||||
|
||||
Logs:
|
||||
- Message additions with types
|
||||
- Tool call registrations
|
||||
- Agent status changes
|
||||
- Report section updates
|
||||
|
||||
#### API Logger
|
||||
Tracks all API calls:
|
||||
```python
|
||||
api_logger = get_api_logger()
|
||||
```
|
||||
|
||||
Logs:
|
||||
- API provider and model
|
||||
- Token usage and costs
|
||||
- Request duration
|
||||
- Success/failure status
|
||||
- Error messages
|
||||
|
||||
#### Performance Logger
|
||||
Tracks timing and performance metrics:
|
||||
```python
|
||||
perf_logger = get_performance_logger()
|
||||
```
|
||||
|
||||
Logs:
|
||||
- Operation durations
|
||||
- Performance summaries
|
||||
- Statistical analysis (min, max, avg)
|
||||
|
||||
## Usage Examples
|
||||
|
||||
### Starting an Analysis Session
|
||||
|
||||
When you run an analysis, the CLI logs:
|
||||
|
||||
```
|
||||
2024-01-15 10:30:00 | INFO | CLI | Starting trading analysis session
|
||||
2024-01-15 10:30:05 | INFO | CLI | User selections received
|
||||
Context: {
|
||||
"ticker": "AAPL",
|
||||
"date": "2024-01-15",
|
||||
"analysts": ["market", "social", "news"],
|
||||
"research_depth": 3,
|
||||
"llm_provider": "openai"
|
||||
}
|
||||
2024-01-15 10:30:06 | INFO | CLI | Initializing TradingAgents graph
|
||||
2024-01-15 10:30:07 | INFO | CLI | Results directory created: results/AAPL/2024-01-15
|
||||
```
|
||||
|
||||
### Agent Status Updates
|
||||
|
||||
```
|
||||
2024-01-15 10:30:10 | INFO | BUFFER | Agent status updated: Market Analyst -> in_progress
|
||||
Context: {
|
||||
"agent": "Market Analyst",
|
||||
"old_status": "pending",
|
||||
"new_status": "in_progress"
|
||||
}
|
||||
```
|
||||
|
||||
### Tool Calls
|
||||
|
||||
```
|
||||
2024-01-15 10:30:15 | INFO | BUFFER | Tool call registered: get_stock_data
|
||||
Context: {
|
||||
"tool": "get_stock_data",
|
||||
"args": {"ticker": "AAPL", "period": "1mo"},
|
||||
"timestamp": "10:30:15"
|
||||
}
|
||||
```
|
||||
|
||||
### Report Section Generation
|
||||
|
||||
```
|
||||
2024-01-15 10:35:20 | INFO | CLI | Report section generated: market_report
|
||||
Context: {
|
||||
"section": "market_report",
|
||||
"file": "results/AAPL/2024-01-15/reports/market_report.md",
|
||||
"content_length": 2543
|
||||
}
|
||||
```
|
||||
|
||||
### Analysis Completion
|
||||
|
||||
```
|
||||
2024-01-15 10:45:30 | INFO | CLI | Analysis completed successfully
|
||||
Context: {
|
||||
"ticker": "AAPL",
|
||||
"date": "2024-01-15",
|
||||
"duration_ms": 903421.5,
|
||||
"chunks_processed": 47
|
||||
}
|
||||
2024-01-15 10:45:30 | INFO | PERF | total_analysis_session completed in 903421.50ms
|
||||
Context: {
|
||||
"operation": "total_analysis_session",
|
||||
"duration_ms": 903421.5
|
||||
}
|
||||
```
|
||||
|
||||
### Error Handling
|
||||
|
||||
```
|
||||
2024-01-15 10:30:45 | ERROR | CLI | Analysis failed with error: Connection timeout
|
||||
Context: {
|
||||
"error_type": "TimeoutError"
|
||||
}
|
||||
Traceback (most recent call last):
|
||||
...
|
||||
```
|
||||
|
||||
## Configuration
|
||||
|
||||
### Log Level
|
||||
|
||||
Configure the logging level when starting the CLI:
|
||||
|
||||
```python
|
||||
# In cli/main.py
|
||||
configure_logging(level="INFO", console=True)
|
||||
```
|
||||
|
||||
Available levels:
|
||||
- `DEBUG`: Detailed information for debugging
|
||||
- `INFO`: General information about progress (default)
|
||||
- `WARNING`: Warning messages
|
||||
- `ERROR`: Error messages
|
||||
- `CRITICAL`: Critical errors
|
||||
|
||||
### Console Output
|
||||
|
||||
To disable console logging:
|
||||
|
||||
```python
|
||||
configure_logging(level="INFO", console=False)
|
||||
```
|
||||
|
||||
### Custom Log Directory
|
||||
|
||||
```python
|
||||
configure_logging(level="INFO", log_dir="custom/log/path")
|
||||
```
|
||||
|
||||
## Benefits
|
||||
|
||||
### 1. Better Debugging
|
||||
- Structured context makes it easy to trace issues
|
||||
- Timestamps and component labels help identify problem areas
|
||||
- Full stack traces for exceptions
|
||||
|
||||
### 2. Performance Monitoring
|
||||
- Track operation durations
|
||||
- Identify bottlenecks
|
||||
- Statistical summaries of performance metrics
|
||||
|
||||
### 3. Audit Trail
|
||||
- Complete record of all operations
|
||||
- Tool call history
|
||||
- Agent status transitions
|
||||
- API usage tracking
|
||||
|
||||
### 4. Cost Tracking
|
||||
- Monitor API calls and token usage
|
||||
- Track costs per analysis session
|
||||
- Identify expensive operations
|
||||
|
||||
### 5. Compliance
|
||||
- Structured logs suitable for compliance requirements
|
||||
- Log rotation prevents disk space issues
|
||||
- Separate error logs for quick issue identification
|
||||
|
||||
## Best Practices
|
||||
|
||||
1. **Use Appropriate Log Levels**
|
||||
- DEBUG: Detailed diagnostic information
|
||||
- INFO: Confirmation of expected behavior
|
||||
- WARNING: Something unexpected but handled
|
||||
- ERROR: Serious problem that needs attention
|
||||
- CRITICAL: System failure
|
||||
|
||||
2. **Include Context**
|
||||
```python
|
||||
cli_logger.info(
|
||||
"Operation completed",
|
||||
extra={
|
||||
"context": {
|
||||
"operation": "analysis",
|
||||
"duration_ms": 1234.5,
|
||||
"items_processed": 42
|
||||
}
|
||||
}
|
||||
)
|
||||
```
|
||||
|
||||
3. **Log at Key Points**
|
||||
- Session start/end
|
||||
- Configuration changes
|
||||
- State transitions
|
||||
- API calls
|
||||
- Errors and exceptions
|
||||
|
||||
4. **Review Logs Regularly**
|
||||
- Check `errors.log` for issues
|
||||
- Monitor `performance.log` for bottlenecks
|
||||
- Review `api_calls.log` for cost optimization
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
### Issue: No logs appearing
|
||||
|
||||
**Solution**: Check that logging is properly initialized:
|
||||
```python
|
||||
from tradingagents.utils.logging_config import configure_logging
|
||||
configure_logging(level="INFO", console=True)
|
||||
```
|
||||
|
||||
### Issue: Log files too large
|
||||
|
||||
**Solution**: The system uses automatic log rotation. Adjust settings in `logging_config.py`:
|
||||
```python
|
||||
maxBytes=10 * 1024 * 1024 # 10 MB
|
||||
backupCount=5 # Keep 5 backup files
|
||||
```
|
||||
|
||||
### Issue: Can't find specific logs
|
||||
|
||||
**Solution**: Use grep or log analysis tools:
|
||||
```bash
|
||||
# Find all ERROR logs
|
||||
grep "ERROR" logs/tradingagents.log
|
||||
|
||||
# Find logs for specific ticker
|
||||
grep "AAPL" logs/tradingagents.log
|
||||
|
||||
# Find performance issues
|
||||
grep "duration_ms" logs/performance.log
|
||||
```
|
||||
|
||||
## Migration Notes
|
||||
|
||||
### Legacy Logging
|
||||
|
||||
The CLI still maintains backward compatibility with the legacy `message_tool.log` file for each analysis session. This file contains:
|
||||
- Agent messages
|
||||
- Tool calls
|
||||
- Timestamps
|
||||
|
||||
However, the new comprehensive logging system provides much more detailed information and should be preferred for debugging and monitoring.
|
||||
|
||||
### Gradual Migration
|
||||
|
||||
Other components of TradingAgents can gradually adopt the comprehensive logging system by:
|
||||
|
||||
1. Importing the logging utilities:
|
||||
```python
|
||||
from tradingagents.utils.logging_config import get_logger
|
||||
```
|
||||
|
||||
2. Getting a logger instance:
|
||||
```python
|
||||
logger = get_logger("tradingagents.component_name", component="COMPONENT")
|
||||
```
|
||||
|
||||
3. Replacing print statements with logger calls:
|
||||
```python
|
||||
# Before
|
||||
print(f"Processing {item}")
|
||||
|
||||
# After
|
||||
logger.info(f"Processing item", extra={"context": {"item": item}})
|
||||
```
|
||||
|
||||
## Future Enhancements
|
||||
|
||||
- [ ] Add log aggregation support (e.g., ELK stack)
|
||||
- [ ] Implement real-time log streaming
|
||||
- [ ] Add log analysis dashboard
|
||||
- [ ] Integrate with monitoring systems (Prometheus, Grafana)
|
||||
- [ ] Add log filtering and search UI
|
||||
- [ ] Implement log compression for archived logs
|
||||
- [ ] Add distributed tracing for multi-agent workflows
|
||||
|
||||
## Summary
|
||||
|
||||
The CLI now uses a comprehensive logging system that provides:
|
||||
- ✅ Structured, contextual logging
|
||||
- ✅ Multiple log files for different purposes
|
||||
- ✅ Performance tracking and metrics
|
||||
- ✅ API call and cost monitoring
|
||||
- ✅ Automatic log rotation
|
||||
- ✅ Better debugging capabilities
|
||||
- ✅ Audit trail for compliance
|
||||
|
||||
This makes the TradingAgents system more maintainable, debuggable, and production-ready.
|
||||
|
|
@ -0,0 +1,419 @@
|
|||
# Logging Quick Reference Guide
|
||||
|
||||
## Quick Start
|
||||
|
||||
```python
|
||||
from tradingagents.utils.logging_config import (
|
||||
get_logger,
|
||||
get_api_logger,
|
||||
get_performance_logger,
|
||||
configure_logging,
|
||||
)
|
||||
|
||||
# Initialize (done once at startup)
|
||||
configure_logging(level="INFO", console=True)
|
||||
|
||||
# Get loggers
|
||||
logger = get_logger("tradingagents.component", component="COMPONENT")
|
||||
api_logger = get_api_logger()
|
||||
perf_logger = get_performance_logger()
|
||||
```
|
||||
|
||||
## Basic Logging
|
||||
|
||||
### Simple Messages
|
||||
```python
|
||||
logger.debug("Detailed debugging information")
|
||||
logger.info("General information")
|
||||
logger.warning("Warning message")
|
||||
logger.error("Error occurred")
|
||||
logger.critical("Critical error")
|
||||
```
|
||||
|
||||
### With Context
|
||||
```python
|
||||
logger.info(
|
||||
"Operation completed",
|
||||
extra={
|
||||
"context": {
|
||||
"operation": "analysis",
|
||||
"duration_ms": 1234.5,
|
||||
"items_processed": 42
|
||||
}
|
||||
}
|
||||
)
|
||||
```
|
||||
|
||||
### With Exceptions
|
||||
```python
|
||||
try:
|
||||
# some operation
|
||||
pass
|
||||
except Exception as e:
|
||||
logger.error(
|
||||
f"Operation failed: {e}",
|
||||
extra={"context": {"error_type": type(e).__name__}},
|
||||
exc_info=True # Include stack trace
|
||||
)
|
||||
```
|
||||
|
||||
## API Call Logging
|
||||
|
||||
```python
|
||||
api_logger.log_call(
|
||||
provider="openai",
|
||||
model="gpt-4o-mini",
|
||||
endpoint="/v1/chat/completions",
|
||||
tokens=150,
|
||||
cost=0.0015,
|
||||
duration=1234.5,
|
||||
status="success"
|
||||
)
|
||||
|
||||
# Get statistics
|
||||
stats = api_logger.get_stats()
|
||||
# Returns: {"total_calls": 3, "total_tokens": 650}
|
||||
```
|
||||
|
||||
## Performance Logging
|
||||
|
||||
```python
|
||||
import time
|
||||
|
||||
start = time.time()
|
||||
# ... do work ...
|
||||
duration_ms = (time.time() - start) * 1000
|
||||
|
||||
perf_logger.log_timing(
|
||||
"operation_name",
|
||||
duration_ms,
|
||||
context={"details": "value"}
|
||||
)
|
||||
|
||||
# Get average timing
|
||||
avg = perf_logger.get_average_timing("operation_name")
|
||||
|
||||
# Log summary
|
||||
perf_logger.log_summary()
|
||||
```
|
||||
|
||||
## Log Levels
|
||||
|
||||
| Level | When to Use | Example |
|
||||
|----------|------------------------------------------------|----------------------------------|
|
||||
| DEBUG | Detailed diagnostic information | Variable values, loop iterations |
|
||||
| INFO | Confirmation things are working as expected | Session start, completion |
|
||||
| WARNING | Something unexpected but handled | Deprecated API, fallback used |
|
||||
| ERROR | Serious problem that needs attention | Failed operation, exception |
|
||||
| CRITICAL | System failure, app may crash | Fatal error, out of resources |
|
||||
|
||||
## Log Files
|
||||
|
||||
| File | Contents | Level |
|
||||
|-----------------------|-----------------------------------|--------|
|
||||
| tradingagents.log | All logs | DEBUG+ |
|
||||
| api_calls.log | API tracking | INFO+ |
|
||||
| memory.log | Memory operations | INFO+ |
|
||||
| agents.log | Agent activities | INFO+ |
|
||||
| errors.log | Errors only | ERROR+ |
|
||||
| performance.log | Performance metrics | INFO+ |
|
||||
|
||||
## Configuration
|
||||
|
||||
### Change Log Level
|
||||
```python
|
||||
from tradingagents.utils.logging_config import set_log_level
|
||||
|
||||
set_log_level("DEBUG") # DEBUG, INFO, WARNING, ERROR, CRITICAL
|
||||
```
|
||||
|
||||
### Configure at Startup
|
||||
```python
|
||||
configure_logging(
|
||||
level="INFO", # Log level
|
||||
log_dir="logs", # Directory for log files
|
||||
console=True # Enable/disable console output
|
||||
)
|
||||
```
|
||||
|
||||
### Custom Component Logger
|
||||
```python
|
||||
# Creates logger: tradingagents.myapp
|
||||
logger = get_logger("tradingagents.myapp", component="MYAPP")
|
||||
|
||||
# Logs appear as:
|
||||
# 2025-01-15 10:30:00 | INFO | MYAPP | Message here
|
||||
```
|
||||
|
||||
## Common Patterns
|
||||
|
||||
### Session Start/End
|
||||
```python
|
||||
logger.info("=" * 70)
|
||||
logger.info("Session Started")
|
||||
logger.info("=" * 70)
|
||||
|
||||
# ... work ...
|
||||
|
||||
logger.info("Session completed", extra={
|
||||
"context": {"duration_ms": duration, "results": count}
|
||||
})
|
||||
```
|
||||
|
||||
### Track State Changes
|
||||
```python
|
||||
logger.info(
|
||||
f"State changed: {old_state} -> {new_state}",
|
||||
extra={
|
||||
"context": {
|
||||
"old_state": old_state,
|
||||
"new_state": new_state,
|
||||
"reason": "user_action"
|
||||
}
|
||||
}
|
||||
)
|
||||
```
|
||||
|
||||
### Tool/Function Calls
|
||||
```python
|
||||
logger.info(
|
||||
f"Calling tool: {tool_name}",
|
||||
extra={
|
||||
"context": {
|
||||
"tool": tool_name,
|
||||
"args": args_dict,
|
||||
"timestamp": timestamp
|
||||
}
|
||||
}
|
||||
)
|
||||
```
|
||||
|
||||
### Report Generation
|
||||
```python
|
||||
logger.info(
|
||||
f"Report generated: {section_name}",
|
||||
extra={
|
||||
"context": {
|
||||
"section": section_name,
|
||||
"file": str(file_path),
|
||||
"content_length": len(content)
|
||||
}
|
||||
}
|
||||
)
|
||||
```
|
||||
|
||||
### Performance Timing
|
||||
```python
|
||||
import time
|
||||
|
||||
start = time.time()
|
||||
result = expensive_operation()
|
||||
duration = (time.time() - start) * 1000
|
||||
|
||||
perf_logger.log_timing(
|
||||
"expensive_operation",
|
||||
duration,
|
||||
context={"result_size": len(result)}
|
||||
)
|
||||
```
|
||||
|
||||
## CLI Integration Examples
|
||||
|
||||
### MessageBuffer Logging
|
||||
```python
|
||||
class MessageBuffer:
|
||||
def __init__(self):
|
||||
self.logger = get_logger("tradingagents.cli.buffer", component="BUFFER")
|
||||
|
||||
def add_message(self, message_type, content):
|
||||
# ... add message ...
|
||||
self.logger.debug(
|
||||
f"Message added: {message_type}",
|
||||
extra={"context": {"type": message_type}}
|
||||
)
|
||||
```
|
||||
|
||||
### Analysis Session
|
||||
```python
|
||||
def run_analysis():
|
||||
start_time = time.time()
|
||||
cli_logger.info("Starting trading analysis session")
|
||||
|
||||
# ... analysis work ...
|
||||
|
||||
total_duration = (time.time() - start_time) * 1000
|
||||
cli_logger.info(
|
||||
"Analysis completed",
|
||||
extra={"context": {"duration_ms": total_duration}}
|
||||
)
|
||||
```
|
||||
|
||||
## Viewing Logs
|
||||
|
||||
### Tail Live Logs
|
||||
```bash
|
||||
tail -f logs/tradingagents.log
|
||||
```
|
||||
|
||||
### View Errors Only
|
||||
```bash
|
||||
cat logs/errors.log
|
||||
```
|
||||
|
||||
### Search Logs
|
||||
```bash
|
||||
# Find specific ticker
|
||||
grep "AAPL" logs/tradingagents.log
|
||||
|
||||
# Find errors
|
||||
grep "ERROR" logs/tradingagents.log
|
||||
|
||||
# Find performance issues (>10 seconds)
|
||||
grep "duration_ms.*[1-9][0-9]\{4,\}" logs/performance.log
|
||||
```
|
||||
|
||||
### Filter by Component
|
||||
```bash
|
||||
grep "| CLI |" logs/tradingagents.log
|
||||
grep "| BUFFER |" logs/tradingagents.log
|
||||
grep "| API |" logs/tradingagents.log
|
||||
```
|
||||
|
||||
### Filter by Date/Time
|
||||
```bash
|
||||
grep "2025-01-15 10:" logs/tradingagents.log
|
||||
```
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
### No Logs Appearing
|
||||
1. Check logging is initialized: `configure_logging(level="INFO")`
|
||||
2. Check log level isn't too high: `set_log_level("INFO")`
|
||||
3. Check log directory exists: `ls -la logs/`
|
||||
|
||||
### Log Files Too Large
|
||||
- System uses automatic rotation (10MB default)
|
||||
- Check backup count: look for `.log.1`, `.log.2`, etc.
|
||||
- Increase rotation settings in `logging_config.py`
|
||||
|
||||
### Missing Context in Logs
|
||||
```python
|
||||
# Bad - no context
|
||||
logger.info("Analysis done")
|
||||
|
||||
# Good - with context
|
||||
logger.info(
|
||||
"Analysis done",
|
||||
extra={
|
||||
"context": {
|
||||
"ticker": "AAPL",
|
||||
"duration_ms": 1234.5
|
||||
}
|
||||
}
|
||||
)
|
||||
```
|
||||
|
||||
### Performance Impact
|
||||
- File logging is asynchronous and minimal
|
||||
- DEBUG level has most overhead
|
||||
- Use INFO or WARNING in production
|
||||
- Disable console logging if needed: `configure_logging(console=False)`
|
||||
|
||||
## Best Practices
|
||||
|
||||
✅ **DO**
|
||||
- Use appropriate log levels
|
||||
- Include context in extra parameter
|
||||
- Log at key decision points
|
||||
- Use structured context (dicts)
|
||||
- Enable exc_info for exceptions
|
||||
- Use consistent component names
|
||||
|
||||
❌ **DON'T**
|
||||
- Log sensitive data (passwords, keys)
|
||||
- Log in tight loops (use sampling)
|
||||
- Use print() instead of logger
|
||||
- Log without context
|
||||
- Ignore log rotation limits
|
||||
- Mix logging and print statements
|
||||
|
||||
## Example: Complete Integration
|
||||
|
||||
```python
|
||||
from tradingagents.utils.logging_config import (
|
||||
get_logger,
|
||||
get_api_logger,
|
||||
get_performance_logger,
|
||||
configure_logging,
|
||||
)
|
||||
import time
|
||||
|
||||
# Initialize
|
||||
configure_logging(level="INFO", console=True)
|
||||
logger = get_logger("tradingagents.mymodule", component="MYMODULE")
|
||||
api_logger = get_api_logger()
|
||||
perf_logger = get_performance_logger()
|
||||
|
||||
def process_data(data):
|
||||
"""Process data with comprehensive logging."""
|
||||
start = time.time()
|
||||
|
||||
logger.info("Starting data processing", extra={
|
||||
"context": {"items": len(data)}
|
||||
})
|
||||
|
||||
try:
|
||||
# Simulate API call
|
||||
api_start = time.time()
|
||||
result = call_api(data)
|
||||
api_duration = (time.time() - api_start) * 1000
|
||||
|
||||
api_logger.log_call(
|
||||
provider="openai",
|
||||
model="gpt-4o-mini",
|
||||
endpoint="/v1/chat/completions",
|
||||
tokens=150,
|
||||
duration=api_duration,
|
||||
status="success"
|
||||
)
|
||||
|
||||
# Process result
|
||||
processed = transform(result)
|
||||
|
||||
# Log completion
|
||||
total_duration = (time.time() - start) * 1000
|
||||
perf_logger.log_timing("process_data", total_duration)
|
||||
|
||||
logger.info("Processing completed", extra={
|
||||
"context": {
|
||||
"items_processed": len(processed),
|
||||
"duration_ms": total_duration
|
||||
}
|
||||
})
|
||||
|
||||
return processed
|
||||
|
||||
except Exception as e:
|
||||
logger.error(
|
||||
f"Processing failed: {e}",
|
||||
extra={"context": {"error_type": type(e).__name__}},
|
||||
exc_info=True
|
||||
)
|
||||
raise
|
||||
|
||||
# Log performance summary at end
|
||||
perf_logger.log_summary()
|
||||
```
|
||||
|
||||
## Summary
|
||||
|
||||
The comprehensive logging system provides:
|
||||
- 🎯 Structured, contextual logs
|
||||
- 📊 Performance tracking
|
||||
- 💰 API cost monitoring
|
||||
- 🔍 Easy debugging
|
||||
- 📁 Organized log files
|
||||
- 🔄 Automatic rotation
|
||||
- ⚡ Minimal overhead
|
||||
|
||||
For detailed documentation, see `docs/CLI_LOGGING_INTEGRATION.md`
|
||||
|
|
@ -0,0 +1,393 @@
|
|||
#!/usr/bin/env python3
|
||||
"""
|
||||
Test script for CLI logging integration.
|
||||
|
||||
This script tests the comprehensive logging system integration in the CLI
|
||||
without running a full analysis.
|
||||
"""
|
||||
|
||||
import sys
|
||||
import time
|
||||
from pathlib import Path
|
||||
|
||||
# Add project root to path
|
||||
sys.path.insert(0, str(Path(__file__).parent))
|
||||
|
||||
from tradingagents.utils.logging_config import (
|
||||
get_logger,
|
||||
get_api_logger,
|
||||
get_performance_logger,
|
||||
configure_logging,
|
||||
)
|
||||
|
||||
|
||||
def test_basic_logging():
|
||||
"""Test basic logging functionality."""
|
||||
print("\n" + "=" * 70)
|
||||
print("Testing Basic Logging")
|
||||
print("=" * 70)
|
||||
|
||||
# Configure logging
|
||||
configure_logging(level="INFO", console=True)
|
||||
|
||||
# Get CLI logger
|
||||
cli_logger = get_logger("tradingagents.cli", component="CLI")
|
||||
|
||||
# Test different log levels
|
||||
cli_logger.debug("This is a debug message (should not appear in console)")
|
||||
cli_logger.info("This is an info message")
|
||||
cli_logger.warning("This is a warning message")
|
||||
cli_logger.error("This is an error message")
|
||||
|
||||
print("✓ Basic logging test completed")
|
||||
|
||||
|
||||
def test_contextual_logging():
|
||||
"""Test logging with context."""
|
||||
print("\n" + "=" * 70)
|
||||
print("Testing Contextual Logging")
|
||||
print("=" * 70)
|
||||
|
||||
cli_logger = get_logger("tradingagents.cli", component="CLI")
|
||||
|
||||
# Log with context
|
||||
cli_logger.info(
|
||||
"User selections received",
|
||||
extra={
|
||||
"context": {
|
||||
"ticker": "AAPL",
|
||||
"date": "2024-01-15",
|
||||
"analysts": ["market", "social", "news"],
|
||||
"research_depth": 3,
|
||||
"llm_provider": "openai",
|
||||
}
|
||||
},
|
||||
)
|
||||
|
||||
cli_logger.info(
|
||||
"Analysis session started",
|
||||
extra={
|
||||
"context": {
|
||||
"session_id": "test_session_001",
|
||||
"timestamp": time.time(),
|
||||
}
|
||||
},
|
||||
)
|
||||
|
||||
print("✓ Contextual logging test completed")
|
||||
|
||||
|
||||
def test_buffer_logging():
|
||||
"""Test MessageBuffer-style logging."""
|
||||
print("\n" + "=" * 70)
|
||||
print("Testing Buffer Logging")
|
||||
print("=" * 70)
|
||||
|
||||
buffer_logger = get_logger("tradingagents.cli.buffer", component="BUFFER")
|
||||
|
||||
# Simulate message addition
|
||||
buffer_logger.debug(
|
||||
"Message added: Reasoning",
|
||||
extra={"context": {"type": "Reasoning", "timestamp": "10:30:15"}},
|
||||
)
|
||||
|
||||
# Simulate tool call
|
||||
buffer_logger.info(
|
||||
"Tool call registered: get_stock_data",
|
||||
extra={
|
||||
"context": {
|
||||
"tool": "get_stock_data",
|
||||
"args": {"ticker": "AAPL", "period": "1mo"},
|
||||
"timestamp": "10:30:15",
|
||||
}
|
||||
},
|
||||
)
|
||||
|
||||
# Simulate agent status update
|
||||
buffer_logger.info(
|
||||
"Agent status updated: Market Analyst -> in_progress",
|
||||
extra={
|
||||
"context": {
|
||||
"agent": "Market Analyst",
|
||||
"old_status": "pending",
|
||||
"new_status": "in_progress",
|
||||
}
|
||||
},
|
||||
)
|
||||
|
||||
# Simulate report section update
|
||||
buffer_logger.info(
|
||||
"Report section updated: market_report",
|
||||
extra={
|
||||
"context": {
|
||||
"section": "market_report",
|
||||
"content_length": 2543,
|
||||
}
|
||||
},
|
||||
)
|
||||
|
||||
print("✓ Buffer logging test completed")
|
||||
|
||||
|
||||
def test_api_logging():
|
||||
"""Test API call logging."""
|
||||
print("\n" + "=" * 70)
|
||||
print("Testing API Call Logging")
|
||||
print("=" * 70)
|
||||
|
||||
api_logger = get_api_logger()
|
||||
|
||||
# Simulate successful API call
|
||||
api_logger.log_call(
|
||||
provider="openai",
|
||||
model="gpt-4o-mini",
|
||||
endpoint="/v1/chat/completions",
|
||||
tokens=150,
|
||||
cost=0.0015,
|
||||
duration=1234.5,
|
||||
status="success",
|
||||
)
|
||||
|
||||
# Simulate another API call
|
||||
api_logger.log_call(
|
||||
provider="openai",
|
||||
model="gpt-4o",
|
||||
endpoint="/v1/chat/completions",
|
||||
tokens=500,
|
||||
cost=0.0075,
|
||||
duration=2567.8,
|
||||
status="success",
|
||||
)
|
||||
|
||||
# Simulate failed API call
|
||||
api_logger.log_call(
|
||||
provider="openai",
|
||||
model="gpt-4o-mini",
|
||||
endpoint="/v1/chat/completions",
|
||||
status="error",
|
||||
error="Connection timeout",
|
||||
)
|
||||
|
||||
# Get statistics
|
||||
stats = api_logger.get_stats()
|
||||
print(f"\nAPI Call Statistics:")
|
||||
print(f" Total calls: {stats['total_calls']}")
|
||||
print(f" Total tokens: {stats['total_tokens']}")
|
||||
|
||||
print("✓ API logging test completed")
|
||||
|
||||
|
||||
def test_performance_logging():
|
||||
"""Test performance tracking."""
|
||||
print("\n" + "=" * 70)
|
||||
print("Testing Performance Logging")
|
||||
print("=" * 70)
|
||||
|
||||
perf_logger = get_performance_logger()
|
||||
|
||||
# Simulate various operations with timing
|
||||
operations = [
|
||||
("graph_initialization", 1234.5),
|
||||
("agent_analysis", 5678.9),
|
||||
("report_generation", 2345.6),
|
||||
("graph_analysis", 45678.9),
|
||||
("graph_analysis", 43210.1),
|
||||
("graph_analysis", 48901.2),
|
||||
]
|
||||
|
||||
for operation, duration in operations:
|
||||
perf_logger.log_timing(
|
||||
operation,
|
||||
duration,
|
||||
context={"component": "test", "session": "test_session_001"},
|
||||
)
|
||||
|
||||
# Get average timing
|
||||
avg_graph_analysis = perf_logger.get_average_timing("graph_analysis")
|
||||
print(f"\nAverage graph_analysis time: {avg_graph_analysis:.2f}ms")
|
||||
|
||||
# Log summary
|
||||
perf_logger.log_summary()
|
||||
|
||||
print("✓ Performance logging test completed")
|
||||
|
||||
|
||||
def test_error_logging():
|
||||
"""Test error logging with exceptions."""
|
||||
print("\n" + "=" * 70)
|
||||
print("Testing Error Logging")
|
||||
print("=" * 70)
|
||||
|
||||
cli_logger = get_logger("tradingagents.cli", component="CLI")
|
||||
|
||||
try:
|
||||
# Simulate an error
|
||||
raise ValueError("Simulated error for testing")
|
||||
except Exception as e:
|
||||
cli_logger.error(
|
||||
f"Analysis failed with error: {e}",
|
||||
extra={"context": {"error_type": type(e).__name__}},
|
||||
exc_info=True,
|
||||
)
|
||||
|
||||
print("✓ Error logging test completed")
|
||||
|
||||
|
||||
def test_report_section_logging():
|
||||
"""Test report section generation logging."""
|
||||
print("\n" + "=" * 70)
|
||||
print("Testing Report Section Logging")
|
||||
print("=" * 70)
|
||||
|
||||
cli_logger = get_logger("tradingagents.cli", component="CLI")
|
||||
|
||||
sections = [
|
||||
("market_report", "results/AAPL/2024-01-15/reports/market_report.md", 2543),
|
||||
(
|
||||
"sentiment_report",
|
||||
"results/AAPL/2024-01-15/reports/sentiment_report.md",
|
||||
1876,
|
||||
),
|
||||
("news_report", "results/AAPL/2024-01-15/reports/news_report.md", 3421),
|
||||
]
|
||||
|
||||
for section, file_path, content_length in sections:
|
||||
cli_logger.info(
|
||||
f"Report section generated: {section}",
|
||||
extra={
|
||||
"context": {
|
||||
"section": section,
|
||||
"file": file_path,
|
||||
"content_length": content_length,
|
||||
}
|
||||
},
|
||||
)
|
||||
|
||||
print("✓ Report section logging test completed")
|
||||
|
||||
|
||||
def test_session_logging():
|
||||
"""Test complete analysis session logging."""
|
||||
print("\n" + "=" * 70)
|
||||
print("Testing Complete Session Logging")
|
||||
print("=" * 70)
|
||||
|
||||
cli_logger = get_logger("tradingagents.cli", component="CLI")
|
||||
perf_logger = get_performance_logger()
|
||||
|
||||
# Session start
|
||||
session_start = time.time()
|
||||
cli_logger.info("=" * 70)
|
||||
cli_logger.info("TradingAgents CLI Analysis Started")
|
||||
cli_logger.info("=" * 70)
|
||||
cli_logger.info("Starting trading analysis session")
|
||||
|
||||
# User selections
|
||||
cli_logger.info(
|
||||
"User selections received",
|
||||
extra={
|
||||
"context": {
|
||||
"ticker": "TSLA",
|
||||
"date": "2024-01-15",
|
||||
"analysts": ["market", "news", "fundamentals"],
|
||||
"research_depth": 3,
|
||||
"llm_provider": "openai",
|
||||
}
|
||||
},
|
||||
)
|
||||
|
||||
# Simulate analysis
|
||||
time.sleep(0.5) # Simulate work
|
||||
|
||||
# Analysis completion
|
||||
session_duration = (time.time() - session_start) * 1000
|
||||
perf_logger.log_timing("total_analysis_session", session_duration)
|
||||
|
||||
cli_logger.info(
|
||||
"Analysis completed successfully",
|
||||
extra={
|
||||
"context": {
|
||||
"ticker": "TSLA",
|
||||
"date": "2024-01-15",
|
||||
"duration_ms": session_duration,
|
||||
"chunks_processed": 42,
|
||||
}
|
||||
},
|
||||
)
|
||||
|
||||
cli_logger.info(
|
||||
"Trading analysis session completed",
|
||||
extra={
|
||||
"context": {
|
||||
"total_duration_ms": session_duration,
|
||||
"results_dir": "results/TSLA/2024-01-15",
|
||||
}
|
||||
},
|
||||
)
|
||||
|
||||
print("✓ Session logging test completed")
|
||||
|
||||
|
||||
def check_log_files():
|
||||
"""Check that log files were created."""
|
||||
print("\n" + "=" * 70)
|
||||
print("Checking Log Files")
|
||||
print("=" * 70)
|
||||
|
||||
log_dir = Path("logs")
|
||||
expected_files = [
|
||||
"tradingagents.log",
|
||||
"api_calls.log",
|
||||
"errors.log",
|
||||
"performance.log",
|
||||
]
|
||||
|
||||
for log_file in expected_files:
|
||||
file_path = log_dir / log_file
|
||||
if file_path.exists():
|
||||
size = file_path.stat().st_size
|
||||
print(f"✓ {log_file} exists ({size} bytes)")
|
||||
else:
|
||||
print(f"✗ {log_file} does not exist")
|
||||
|
||||
print("\n✓ Log file check completed")
|
||||
|
||||
|
||||
def main():
|
||||
"""Run all tests."""
|
||||
print("\n" + "=" * 70)
|
||||
print("TradingAgents CLI Logging Integration Test")
|
||||
print("=" * 70)
|
||||
|
||||
try:
|
||||
test_basic_logging()
|
||||
test_contextual_logging()
|
||||
test_buffer_logging()
|
||||
test_api_logging()
|
||||
test_performance_logging()
|
||||
test_error_logging()
|
||||
test_report_section_logging()
|
||||
test_session_logging()
|
||||
check_log_files()
|
||||
|
||||
print("\n" + "=" * 70)
|
||||
print("All Tests Passed! ✓")
|
||||
print("=" * 70)
|
||||
print("\nLog files created in: logs/")
|
||||
print("Check the following files for details:")
|
||||
print(" - logs/tradingagents.log (all logs)")
|
||||
print(" - logs/api_calls.log (API call tracking)")
|
||||
print(" - logs/errors.log (errors only)")
|
||||
print(" - logs/performance.log (performance metrics)")
|
||||
print()
|
||||
|
||||
except Exception as e:
|
||||
print(f"\n✗ Test failed with error: {e}")
|
||||
import traceback
|
||||
|
||||
traceback.print_exc()
|
||||
sys.exit(1)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Loading…
Reference in New Issue