LLM locaux
vLLM
A high-throughput and memory-efficient inference and serving engine for LLMs
★ 93,1 k étoilesApache-2.0
Voir le guide →webclaw est un projet de LLM locaux open source, créé par 0xMassi (0xMassi/webclaw sur GitHub). Il compte 2 366 étoiles sur GitHub et 235 forks, il est publié sous la licence AGPL-3.0 et a été mis à jour pour la dernière fois sur GitHub le 23 septembre 2026.
Fast Rust scraper that turns web pages into clean data for LLMs.
Get the Rust-built binary or build from source.
Give it a URL to scrape or crawl.
Get clean markdown or structured data back.
Pipe results to agents via CLI, API, or MCP.
Fast extraction with low resource use.
Runs on your machine, no cloud required.
Clean page conversion for LLMs.
Follow links across whole sites.
Integrate extraction into any stack.
Give AI agents direct scraping tools.
Download the source and move into the project folder.
git clone https://github.com/0xMassi/webclaw.git
cd webclawEvery project documents its own setup; start with install requirements.
cat README.md | head -60Follow the project's launch command — Docker, pip, npm, or a binary release.
# see README for the exact launch commandIt is local-first and open source, so no per-page API fees.
Commercial use is allowed, but network use of modified versions requires sharing source.
Check the docs for rendering capabilities.
Yes, agents can call it through the Model Context Protocol.
Only if building from source; binaries avoid that.
A high-throughput and memory-efficient inference and serving engine for LLMs
High-performance In-browser LLM Inference Engine
Quantization, kernels, runtime and inference engine for mobiles, wearables, smart home and robots
Early proposal and implementation for connecting LLMs to web pages.
Run local LLMs like Llama and DeepSeek right inside your web browser.
Alibaba's lightweight, blazing-fast inference engine for on-device LLMs and edge AI.
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A high-throughput and memory-efficient inference and serving engine for LLMs
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LLM Agent Framework in ComfyUI includes MCP sever, Omost,GPT-sovits, ChatTTS,GOT-OCR2.0, and FLUX prompt nodes,access to Feishu,discord,and adapts to all llm…
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Run controllable pre-trained AI models locally, written in Rust.
动手学Ollama，CPU玩转大模型部署，在线阅读地址：https://datawhalechina.github.io/handy-ollama/
Let any LLM actually watch a video — frames plus transcript, run locally.
Gratuit et ouvert : récupérez le code source, mettez une étoile au dépôt et commencez à créer.