AGInt Memory Integration

Overview

AGInt (Augmentic Intelligence) has been integrated with the memory_agent system to store its cognitive loop operations and decision-making processes in persistent memory under the stm/mindx_agint folder structure.

Memory Structure

Agent-Specific Organization

AGInt memories are organized under the mindx_agint agent-specific directory:

/home/hacker/mindX/data/memory/stm/mindx_agint/
├── cycles/          # Cognitive cycle operations
├── steps/           # Individual step executions
├── completion/      # Overall completion logs
└── errors/          # Error logs and exceptions

Memory Categories

• cycles: Logs each cognitive cycle start and completion
• steps: Logs individual P-O-D-A (Perception, Orientation, Decision, Action) steps
• completion: Logs overall AGInt completion status
• errors: Logs any errors or exceptions during execution

Implementation Details

Memory Logging Functions

The following functions have been added to mindx_backend_service/main_service.py:

1. _log_agint_cycle_start(): Logs cycle initiation
2. _log_agint_cycle_completion(): Logs cycle completion with metrics
3. _log_agint_step(): Logs individual step execution
4. _log_agint_completion(): Logs overall completion
5. _log_agint_error(): Logs errors and exceptions

Integration Points

Memory logging is integrated at key points in the AGInt cognitive loop:

• Cycle Start: When each cognitive cycle begins
• Step Execution: During each P-O-D-A step
• Cycle Completion: When each cycle finishes
• Overall Completion: When the entire AGInt process completes
• Error Handling: When exceptions occur

Memory Data Structure

Each memory entry contains:

{
  "timestamp_utc": "2025-09-19T23:16:49.424841",
  "memory_type": "STM",
  "category": "mindx_agint/cycles",
  "metadata": {
    "agent": "mindx_agint",
    "component": "cognitive_loop"
  },
  "data": {
    "cycle": 1,
    "max_cycles": 5,
    "directive": "evolve test_file.py",
    "autonomous_mode": false,
    "timestamp": 1692565000.0,
    "status": "started",
    "phase": "cycle_start"
  }
}

Usage

Automatic Logging

Memory logging happens automatically when AGInt is executed through the API endpoint:

POST /commands/agint/stream
{
  "directive": "evolve test_file.py",
  "max_cycles": 5,
  "autonomous_mode": false
}

Manual Testing

You can test the memory integration directly:

from agents.memory_agent import MemoryAgent

memory_agent = MemoryAgent()
result = await memory_agent.save_memory('STM', 'mindx_agint/cycles', data, metadata)

Benefits

1. Persistent Memory: AGInt operations are stored for analysis and learning
2. Agent-Specific Organization: Clean separation from other agent memories
3. Rich Metadata: Detailed information about each operation
4. Scalable Structure: Easy to extend for additional logging categories
5. Debugging Support: Comprehensive logs for troubleshooting

File Naming Convention

Memory files follow the pattern:

{timestamp}_{random_id}.{agent}_{category}.mem.json

Example:

20250919161649_424801.mindx_agint_cycles.mem.json

Integration Status

✅ Completed:

• Memory agent integration
• Agent-specific directory structure
• Memory logging functions
• Integration with AGInt cognitive loop
• Basic testing and verification

🔄 In Progress:

• Stream-based memory logging during API calls
• Error handling and recovery
• Memory cleanup and archival

Future Enhancements

1. Memory Analysis: Tools to analyze AGInt decision patterns
2. Learning Integration: Use memory data for improving AGInt performance
3. Memory Archival: Automatic cleanup of old memory files
4. Real-time Monitoring: Live memory usage dashboards
5. Cross-Agent Memory: Sharing relevant memories between agents