MemexNG-Semantic History Search 제작자: Durga Gairhe

AI-powered semantic search for your browsing history — 100% private, fully local. Find any page you've read by describing it naturally, without exact keywords.

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MemexNG — Semantic History Search

Find anything you've ever read. MemexNG brings AI-powered semantic search to your browsing history — completely private and fully local. Instead of searching with exact keywords, simply describe what you remember.

🔍 Semantic Search

Find pages by meaning, not exact words:
- "that article about AI privacy risks"
- "React authentication tutorial"
- "video about local LLMs"
- "CSS animation performance guide"
Uses on-device AI embeddings to understand the meaning behind your searches.

🧠 Ask Questions About What You've Read

Use natural language to search and summarize information from your browsing history:
- Retrieve relevant pages
- Surface matching excerpts
- Provide cited answers with clickable source references
- Rediscover forgotten research
Every answer includes clickable source references.

⚡ Fast & Lightweight

Instant popup search
Fast HNSW vector search
Optimized for large histories
Dark / light / system theme

🔒 100% Private — No Cloud

Data never leaves your device
No servers, no telemetry, no accounts
No tracking, no analytics
Works fully offline after model download

🏷️ Features

Semantic history search
AI natural language queries
Local vector search index
Reading list & annotations
Omnibox search
Domain filtering & relevance controls
Indexed page statistics
Configurable privacy controls

🛡 Permissions

<all_urls> — page content extraction for indexing
storage / unlimitedStorage — stores your local search index
activeTab — reads current page when indexing
history — optional browsing history indexing
offscreen — runs AI embedding generation efficiently
All processing happens locally on your device.

🧩 Open Source

Built with Transformers.js, ONNX Runtime Web, Mozilla Readability, Voy vector search, React + TypeScript.
MemexNG — Your History, Augmented.

개발자 의견

Built with WXT v0.19 + Vite 6. Uses @huggingface/transformers (ONNX Runtime Web) for on-device text embeddings and voy-search (WebAssembly) for vector similarity search. All ML inference runs locally via WebAssembly — no external APIs. The fixMv2Background Rollup plugin inlines all ES module imports into background.js for Firefox MV2 compatibility. Readability.js is used for article extraction.

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MemexNG-Semantic History Search 제작자: Durga Gairhe

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