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Tags: LLM tools
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25–48 of 66 · Most stars

Rapid-MLX is an open-source (Apache 2.0) OpenAI- and Anthropic-compatible LLM inference server for Apple Silicon, built on MLX, focused on reliable tool calling for coding agents. Up to 4× faster than Apple's MLX (mlx-lm) on the same weights.

  • apple-silicon
  • local-llm
  • macos
  • mlx

一个多模态多模型通用型的全局全能 AI 查询生成桌面悬浮助手应用

한국 문서를 읽고·고치고·새로 쓰는 AI 문서 도구 — HWP·HWPX·PDF·오피스·스캔(OCR)을 Markdown으로, 신구대조·서식 보존 편집·Markdown→HWPX 작성·HWP→HWPX 변환·양식 채우기·공문서 검수까지. 라이브러리·CLI·MCP | Read, diff, edit, write and convert Korean documents (HWP, HWPX, PDF, Office, scans) — library, CLI and MCP server

  • cli
  • document-parser
  • hancom
  • hwp

TranslatedPagekin (formerly AI Novel Writer): free, open-source AI novel writing app for long novels and web fiction. Imitate, continue, rewrite; import writing skills. Local-first, no model bundled. Windows & macOS. Pagekin, a free AI novel writing app, covers everything from settings and blueprints to the main text, review, and final draft. It supports deconstructing and imitating, continuing, and rewriting, and can import writing Skills (such as removing the "AI flavor"). You must configure the model yourself; your works stay local.

OCRFlux is a lightweight yet powerful multimodal toolkit that significantly advances PDF-to-Markdown conversion, excelling in complex layout handling, complicated table parsing and cross-page content merging.

This includes the original implementation of SELF-RAG: Learning to Retrieve, Generate and Critique through self-reflection by Akari Asai, Zeqiu Wu, Yizhong Wang, Avirup Sil, and Hannaneh Hajishirzi.

Claude Code is an agentic coding tool that lives in your terminal, understands your codebase, and helps you code faster by executing routine tasks, explaining complex code, and handling git workflows - all through natural language commands. All original source code is the property of Anthropic.

Own the flow: one open-source AI platform for your knowledge, models and channels – web, WhatsApp, email, Outlook, Nextcloud & ownCloud. Local and cloud models side by side, with the cost on every answer.

37 tok/s from Qwen3-Next-80B (48 GB) on a 32 GB laptop, 24 without drafts vs 2.8 for llama.cpp; reading 62 vs 16 tok/s. Faster than llama.cpp on all 13 models compared in Q4_K_M. LLMs bigger than your RAM, pure C, CPU or GPU.

  • avx2
  • c
  • cpu-inference
  • gguf