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Tabby is a self-hosted AI coding assistant, offering an open-source and on-premises alternative to GitHub Copilot. It boasts several key features:
Self-contained, with no need for a DBMS or cloud service.
OpenAPI interface, easy to integrate with existing infrastructure (e.g Cloud IDE).
Supports consumer-grade GPUs.
10/30/2024 Tabby v0.19.0 featuring recent shared threads on the main page to improve their discoverability.
07/09/2024 ?Announce Codestral integration in Tabby!
07/05/2024 Tabby v0.13.0 introduces Answer Engine, a central knowledge engine for internal engineering teams. It seamlessly integrates with dev team's internal data, delivering reliable and precise answers to empower developers.
06/13/2024 VSCode 1.7 marks a significant milestone with a versatile Chat experience throughout your coding experience. Come and they the latest chat in side-panel and editing via chat command!
06/10/2024 Latest ?blogpost drop on an enhanced code context understanding in Tabby!
06/06/2024 Tabby v0.12.0 release brings ?seamless integrations (Gitlab SSO, Self-hosted GitHub/GitLab, etc.), to flexible configurations (HTTP API integration) and expanded capabilities (repo-context in Code Browser)!
05/22/2024 Tabby VSCode 1.6 comes with multiple choices in inline completion, and the auto-generated commit messages?!
05/11/2024 v0.11.0 brings significant enterprise upgrades, including storage usage stats, ?GitHub & GitLab integration, ?Activities page, and the long-awaited ?Ask Tabby feature!
04/22/2024 v0.10.0 released, featuring the latest Reports tab with team-wise analytics for Tabby usage.
04/19/2024 Tabby now incorporates locally relevant snippets(declarations from local LSP, and recently modified code) for code completion!
04/17/2024 CodeGemma and CodeQwen model series have now been added to the official registry!
03/20/2024 v0.9 released, highlighting a full feature admin UI.
12/23/2023 Seamlessly deploy Tabby on any cloud with SkyServe ? from SkyPilot.
12/15/2023 v0.7.0 released with team management and secured access!
10/15/2023 RAG-based code completion is enabled by detail in v0.3.0?! Check out the blogpost explaining how Tabby utilizes repo-level context to get even smarter!
11/27/2023 v0.6.0 released!
11/09/2023 v0.5.5 released! With a redesign of UI + performance improvement.
10/24/2023 ⛳️ Major updates for Tabby IDE plugins across VSCode/Vim/IntelliJ!
10/04/2023 Check out the model directory for the latest models supported by Tabby.
09/18/2023 Apple's M1/M2 Metal inference support has landed in v0.1.1!
08/31/2023 Tabby's first stable release v0.0.1 ?.
08/28/2023 Experimental support for the CodeLlama 7B.
08/24/2023 Tabby is now on JetBrains Marketplace!
You can find our documentation here.
Installation
IDE/Editor Extensions
Configuration
The easiest way to start a Tabby server is by using the following Docker command:
docker run -it --gpus all -p 8080:8080 -v $HOME/.tabby:/data tabbyml/tabby serve --model StarCoder-1B --device cuda --chat-model Qwen2-1.5B-Instruct
For additional options (e.g inference type, parallelism), please refer to the documentation page.
Full guide at CONTRIBUTING.md;
git clone --recurse-submodules https://github.com/TabbyML/tabbycd tabby
If you have already cloned the repository, you could run the git submodule update --recursive --init
command to fetch all submodules.
Set up the Rust environment by following this tutorial.
Install the required dependencies:
# For MacOSbrew install protobuf# For Ubuntu / Debianapt install protobuf-compiler libopenblas-dev
Install useful tools:
# For Ubuntuapt install make sqlite3 graphviz
Now, you can build Tabby by running the command cargo build
.
... and don't forget to submit a Pull Request
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