Model Releases
local semantic file search for Linux (Rust, llama.cpp, EmbeddingGemma 2)
indexes PDFs, Office files, scans, screenshots, audio and video, and finds them by content. A query like 'when did they decide to freeze hiring' opens the recording at that second. * EmbeddingGemma 2
indexes PDFs, Office files, scans, screenshots, audio and video, and finds them by content. A query like "when did they decide to freeze hiring" opens the recording at that second. * EmbeddingGemma 2 embeds text, images, video frames and 30 s audio windows into one vector space, run in-process via llama.cpp (CUDA, Vulkan or CPU). Ranking is hybrid: vector similarity plus SQLite FTS5 for exact strings. OCR is PaddleOCR. Engine in Rust, app in GTK 4. No LLM, no network after the model download. On an i5 laptop with Iris Xe: right file first on 95% of a small test set, ~4 ms keyword results, ~0.17 s semantic search, Vulkan indexing ~3x faster than CPU. Missing: audio transcription, packages, Wayland shortcut on older desktops. MIT: https://github.com/pdstn12/Recall Inspired by DigUp, a macOS app by Abdur Rahim. https://i.redd.it/7jvvwjndvquh1.gif submitted by /u/somthing_tn [link] [comments]
Related
- Open-source Mac app that runs EmbeddingGemma 2 locally to search your files by what’s in them
- Introducing EmbeddingGemma 2: A best-in-class open model for natively multimodal embeddings | Google
Source: r/LocalLLaMA | 2026-10-11