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Add ultra-fast on-device memory retrieval for AI agents on Apple Silicon.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Wax" yet — see the docs or source repo.
I’m building a local AI agent in Swift on Apple Silicon. Explain how to integrate Wax as a single-file memory layer for conversation storage, semantic retrieval, and RAG, and provide integration steps plus a sample code structure.
A Swift-focused integration plan with architecture, data flow, core code structure, and retrieval call examples.
Design a fully offline, serverless, no-external-API RAG architecture using Wax for a knowledge assistant on macOS. Cover document ingestion, indexing, querying, context assembly, and performance optimization.
An offline RAG architecture proposal with key modules, workflow details, and Apple Silicon optimization tips.
I want to evaluate whether Wax fits my AI app. Provide an evaluation checklist comparing an on-device single-file memory layer with a cloud vector database in latency, privacy, deployment complexity, and maintenance cost.
A structured evaluation checklist and comparison summary to decide on an on-device memory retrieval approach.
Give AI agents local long-term memory with private hybrid retrieval.
Give AI agents persistent memory with retrieval and relevance ranking.
Free persistent memory for AI agents with storage and semantic search.
Give AI coding agents persistent local shared memory across agents.
Add governed cross-agent memory with retrieval and sync for coding agents.
Give AI agents persistent, verifiable memory with blockchain-backed integrity proofs.