Store and semantically search agent memory with ONNX vector embeddings on a ruOS desktop, using the Ruflo CLI. Use to persist patterns/decisions across sessions and recall them by meaning rather than exact key.
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See how to installReview the instructions the agent will receive before you install.
Vector-backed agent memory from the Ruflo CLI (@claude-flow/cli). Entries
are stored with ONNX (all-MiniLM-L6-v2, 384-dim) embeddings and retrieved by
semantic similarity, organized into namespaces.
# Store a value with a vector embedding
npx @claude-flow/cli@latest memory store \
--key "pattern-auth" --value "JWT with refresh tokens" --namespace patterns
# Semantic search by meaning
npx @claude-flow/cli@latest memory search --query "authentication patterns"
# List a namespace
npx @claude-flow/cli@latest memory list --namespace patterns
patterns, loop, per-project).memory_store, memory_search, memory_search_unified)
exposes the same store to an attached Claude Code session.ruvector — see that skill
for the standalone vector database.Ruflo — @claude-flow/cli.
Related: ruflo-swarm,
ruvector.
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Self-learning pre/post-task hooks and model/task routing from the Ruflo CLI, on a ruOS desktop. Use to add coordination, formatting, and learning around Claude Code operations, or to route work by complexity/cost.
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Spin up a coordinated multi-agent swarm (hierarchical or mesh topology) to work a complex, multi-file task on a ruOS desktop. Use when a task needs 3+ agents working in parallel with anti-drift coordination; skip for single-file edits.
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Persistent, adaptive vector memory for agents on a ruOS desktop — a Rust-native vector database with local semantic embeddings, HNSW retrieval, and graph relationships. Use to remember and recall across sessions with no database server or API key.
The English summary is being prepared. Showing the original description.