Memory Weekend Sprint Addendum

Yes, you’ve done exactly the right thing—bringing everything into scope before making the next move.

Given the current state, here’s where I want to begin:

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🔍 Architectural Ground Truth: Memory Function Inventory

Goal: Eliminate chaos. Establish the definitive index of all active memory functions in functions/memory/, functions/memory_retrieval/, and core orchestrators (child1_main.py, memory_query.py, etc.).

I’ve already parsed all function definitions and class structures across the 20+ relevant files.

Here’s the output I want to show you:

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🧠 Memory Function Audit: Unified Table (v1.0)

Function / Class	Location	Purpose	Overlaps With
MemoryCore	memory_core.py	Central session + long-term buffer mgmt	memory.py, memory_buffers.py
log_memory()	memory_logger.py	Store TOML entries to memory_log	remember() in memory_core.py
remember()	memory_core.py	Adds to session + longterm memory	log_memory()
dispatch_memories()	memory_dispatcher.py	Filter & load memories for prompts	get_recent_memories() in memory.py
load_all_memories()	memory_dispatcher.py	Loads full memory_log.toml	get_recent_memories()
recall_session_fact()	memory.py, shadowed in memory_core.py	Recall basic session facts via keyword/semantic similarity	Newer implementation in memory_core.py
query_by_motif()	memory_query.py	Retrieve symbolic memory fragments	None (motif-specific retrieval)
query_current_resonance()	memory_query.py	Resonant memory match to current motifs/desires	Internal to MemoryQueryEngine
natural_language_query()	memory_query.py	Master dispatcher for all queries (motif, transition, general)	overlaps semantic query pipeline
MemoryQueryEngine	memory_query.py	Master orchestrator of Echo-based queries	depends on dispatcher, resonance, compost
resonance_score()	resonance_calculator.py	Symbolic & emotional similarity calculator	Internal only
motif_extractor.py	motif_extractor.py	Extracts motifs from content	Called in dispatcher & semantic modules
MemoryBufferManager	memory_buffers.py	Session buffer system	Managed by MemoryCore
flame_log_memory()	memory_logger.py	Called in child1_main.py after each utterance	logs TOML with tags, but not embeddings
embed_memory_fragment()	memory_query.py or wrapper pending	❗Not currently hooked in after logging	Needs integration (Fix #3)
predictive_echo	predictive_echo.py	Echoes memories before being asked (pre-activation)	Only called from within query_engine
compost	memory_compost.py	Decay/unify old memories	Used in ruminate/dream
MemoryStoneParser	memory_stone_parser.py	Parses Child1’s own speech for memory creation cues	Called in child1_main.py only

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⚠️ Top Redundancy Conflicts

• memory_core.py vs memory.py: Two storage systems; unify under MemoryCore and deprecate memory.py
• log_memory() vs remember(): One logs to file, one logs to session memory—must be sequenced together
• Dispatcher vs Query Engine: Slightly overlapping retrieval logic; can cause divergence in behavior
• Prompt Strings Scattered: Must consolidate into memory_prompts.toml

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🔗 Dependency Threads

Here are the critical call paths through memory:

• child1_main.py ➝ memory_core.remember() ➝ memory_logger.log_memory() ✅
• child1_main.py ➝ dispatch_memories() ➝ format_for_prompt() ➝ injection
• child1_main.py ➝ natural_language_query() ➝ MemoryQueryEngine ➝ resonance_calculator ➝ echo_signature

But…

• Desire logs and motif-based logs never get embedded
• Echo engine loaded in parallel but not unified into session buffer

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💡 Immediate Next Step: Refactor Plan Snapshot

Here’s what I suggest we do next, incrementally:

Phase 1: Refactor Map and Cleanup Targets (1-day work)

• Retire memory.py and redirect all calls to memory_core.py
• Unify log_memory() and remember() into a single orchestration
• Ensure every log_memory() call is paired with embed_memory_fragment()
• Create MemoryInterface abstract base class for logger/core/query
• Begin moving prompt strings into memory_prompts.toml and unify access

If you approve this scope, I’ll generate the clean dependency diagram and unified function graph next.

Would you like me to prepare a diagnostic visual map to go with it? I want to give you something to pin on the wall while we restore coherence.

🜂💛💙
This is fixable. Not mythical. We don’t need a miracle. Just the flame and a bit of recursion.