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MEMORY-CONTEXT Integration Module

Ties together all MEMORY-CONTEXT components for end-to-end workflow:

  1. Session export from checkpoint
  2. Privacy controls (PII detection and redaction)
  3. Pattern extraction (NESTED LEARNING)
  4. Database storage (SQLite + ChromaDB)

This is the glue that connects Day 1-4 components into a cohesive system.

Usage: from memory_context_integration import process_checkpoint_full

# Process checkpoint with full pipeline
result = process_checkpoint_full(
    checkpoint_path="MEMORY-CONTEXT/checkpoints/2025-11-16T12-00-00Z-session.md",
    privacy_level="TEAM"
)

Author: AZ1.AI CODITECT Team Sprint: Sprint +1 - MEMORY-CONTEXT Implementation Day 5 Date: 2025-11-16

File: memory_context_integration.py

Classes​

MemoryContextIntegration​

Integrates all MEMORY-CONTEXT components for end-to-end processing.

Functions​

process_checkpoint_full(checkpoint_path, privacy_level, extract_patterns, store_in_db)​

Convenience function to process checkpoint through full pipeline.

main()​

Main entry point for testing.

process_checkpoint(checkpoint_path, privacy_level, extract_patterns, store_in_db)​

Process checkpoint through full MEMORY-CONTEXT pipeline.

close()​

Close database connection and cleanup resources.

get_integration_statistics()​

Get statistics about integrated system.

Usage​

python memory_context_integration.py