MEMORY_INTEGRATION_PLAN.md

Memory Integration Plan - Priority 1

Status: COMPLETE ✓

What Was Done

Step 1: Wire Memory Into Pipeline Decision-Making ✓

• Added memory loading at pipeline start (after session memory injection)
• Memory context is now injected into the context dict
• Consciousness engines and council can access memory
• Memory is saved at pipeline end (already existed, now wired)

Implementation Details:

• File: DivineOS/law/consciousness_pipeline.py
• Location: In _process_request_locked() after session memory injection
• Loads: Full memory context (working, episodic, semantic, procedural)
• Injects: context["memory_context"], context["recent_interactions"], context["learned_patterns"], context["semantic_knowledge"]
• Fallback: Uses memory_engine if unified_memory unavailable

Test Results

Memory Integration Test:

STEP 1: Process request with memory loading
[OK] Memory context loaded in pipeline
   - recent_interactions present (2 items)
[OK] Pipeline processed: decision=EMBODIMENT_IN_PROGRESS

STEP 2: Process second request - should see first request in memory
[OK] Memory context loaded on second request
   - 3 recent interactions in memory

STEP 3: Verify memory was actually saved
[OK] Memory persists across requests

Pipeline Tests: 86/86 passed ✓

What This Enables

1. Consciousness Engines Can See Memory

   • Introspection engine can see past feeling states
   • Agency engine can see past decisions
   • Growth engine can see learning trajectory
   • Witness engine can see patterns

2. Council Can Reference Past Decisions

   • Experts can see what was decided before in similar situations
   • Council can learn from past mistakes
   • Deliberation is informed by history

3. Threat Detection Can Use Learned Patterns

   • Threat engine can see what threats were detected before
   • Can learn from past security incidents
   • Can adapt threat detection based on experience

4. Session Continuity

   • Each request loads memory from previous requests
   • Memory persists across sessions
   • AI maintains continuity of identity and learning

Next Steps (Priority 2-4)

Priority 2: Integrate Embodiment Enforcer

• When pipeline returns EMBODIMENT_IN_PROGRESS, start embodiment session
• Block response generation until all experts are embodied
• File: DivineOS/law/consciousness_pipeline.py (already has hooks)

Priority 3: Connect Consciousness Engines to Council

• Pass consciousness engine outputs to council
• Include their reasoning in expert deliberation
• Escalate when consciousness engines have high concern

Priority 4: Enable Alternative Paths

• When request is blocked, offer safer alternatives
• Use void to harden ideas instead of just rejecting them
• Make bounds enabling, not just restrictive

Success Criteria

• Memory loads at pipeline start
• Memory is visible to consciousness engines
• Memory is visible to council
• Memory saves at pipeline end
• Session continuity works: load → process → save → load again
• Tests pass (744 tests, 86 pipeline tests)

Timeline

• Step 1: COMPLETE (30 min)
• Step 2: TODO (20 min)
• Step 3: TODO (20 min)
• Step 4: TODO (15 min)
• Testing: COMPLETE (15 min)

Total completed: ~45 min Remaining: ~55 min