superlocalmemory

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AI agent memory with mathematical foundations. Store, recall, search, and manage memories locally. Local data root; optional networked features have separate behavior.

AI & Automation 199 stars 34 forks Updated today AGPL-3.0

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# SuperLocalMemory AI agent memory with a local data root. Five candidate producers (semantic, BM25, temporal, spreading-activation, Hopfield) fuse via RRF, with an entity-graph post-fusion score enhancement — all with mathematical similarity scoring. Mode A operates without sending memory content to a cloud model provider; optional connectors, backup, and proxy providers are explicit choices with separate behavior. ## Installation ```bash pip install superlocalmemory # or npm install -g superlocalmemory ``` ## Quick Start ```bash slm remember "Alice works at Google as a Staff Engineer" --json slm recall "Who is Alice?" --json slm status --json ``` ## Commands All data-returning commands support `--json` for structured agent-native output. ### Memory Operations ```bash slm remember "<content>" --json # Store a memory slm remember "<content>" --tags "a,b" --json slm recall "<query>" --json # Semantic search slm recall "<query>" --limit 5 --json slm list --json -n 20 # List recent memories slm forget "<query>" --json # Preview matches (add --yes to delete) slm forget "<query>" --json --yes # Delete matching memories slm delete <fact_id> --json --yes # Delete specific memory by ID slm update <fact_id> "<content>" --json # Update a memory ``` ### Diagnostics ```bash slm status --json # System status (mode, profile, DB) slm health --json # Math lay...

Details

Author
qualixar
Repository
qualixar/superlocalmemory
Created
5 months ago
Last Updated
today
Language
Python
License
AGPL-3.0

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