{"repo":"tenstorrent/tt-studio","free":true,"listed":false,"github":"https://github.com/tenstorrent/tt-studio","clone":"git clone https://github.com/tenstorrent/tt-studio.git","description":"The Tenstorrent Studio (TT-Studio) is an easy to use web interface for running AI models on Tenstorrent hardware. It handles all the technical setup automatically and gives you a simple GUI to deploy models, chat with models, and more.","language":"Python","stars":49,"topics":["backend-service","chat-application","react","ui-components","accelerator","ai-agents","tenstorrent","device-detection","device-management","device-manager"],"license":"Apache-2.0","category":"chat-messaging","readme_excerpt":"TT-Studio A web UI for deploying and chatting with AI models on Tenstorrent hardware. It wraps TT Inference Server packaging and TT-Metal execution behind a Django + React + agent stack. No Tenstorrent hardware? You can still use it — point it at remote endpoints running on cards elsewhere. --- Table of Contents - Before you start - Quickstart - Documentation - Community & License --- Before you start You'll need: - Python 3.8+ and Docker installed - Your user in the docker group so you don't need sudo — sudo usermod -aG docker $USER , then log out and back in - A Hugging Face token for any gated models you want to run (Llama, etc.) - First time on Tenstorrent hardware? Do the Getting Started Guide first. Full prerequisites are in the detailed setup guide. --- Quickstart run.py handles the rest — the tt-inference-server artifact, your .env , the right Docker overlays for your hardware, and all the containers. It asks for your Hugging Face token along the way. When it finishes, open http://localhost:3000 . A few flags are worth knowing: - python3 run.py --dev — development mode: mounts your local source so the backend and frontend hot-reload as you edit. - python3 run.py --purge-all — tear everything down and wipe the persistent volume and .env for a clean slate. (Use --stop instead to stop the containers but keep your data.) - python3 run.py --report-bug — bundle your logs into a ZIP and open a pre-filled GitHub issue (also offered automatically if setup errors out). - python","default_branch":null,"files":null,"tree":[],"storefront":"/r/tenstorrent","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/tenstorrent/tt-studio/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}