MuninnDB adds Dream Engine for LLM memory consolidation with vault isolation

MuninnDB has added a Dream Engine feature for LLM memory consolidation, modeled after sleep consolidation in the brain. The open-source tool is written in Go and includes Ebbinghaus decay, Hebbian association learning, and vector search capabilities.

How the Dream Engine works

The consolidation pipeline runs between sessions and performs several operations:

• Lowers the deduplication cosine threshold from 0.95 to 0.85
• Flags near-duplicate clusters
• Passes ambiguous cases to an LLM for semantic review
• Automatically merges clear duplicates

You can run it with a dry-run option: muninn dream --dry-run. Sample output shows: "No changes were written. Dream completed in 0s default scanned 107 engrams (merged 9) legal-docs 1 engrams (protected, skipped)"

Vault trust tiers for data isolation

The system implements data protection through vault trust tiers:

• Legal vaults: Skipped entirely, never sent to any LLM
• Work/personal: Ollama or Anthropic only
• Global/projects: Any configured provider

Development status and architecture

The author has shipped Phase 0 with configurable deduplication and dry-run CLI. The next phase (PR #2) will add LLM consolidation, bidirectional stability, and a dream journal feature.

The tool runs locally on consumer hardware - the author mentions using an RTX 5070 Ti with Ollama. The architecture is detailed in a technical writeup that explores neuroscience parallels.