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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 persistent memory with retrieval and relevance ranking.
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.
Let AI query WAX balances, NFTs, prices, and transactions naturally.
Provide AI agents with persistent memory, knowledge retrieval, and feedback-driven learning.