https://github.com/ovh/shai
shai is a coding agent, your pair programming buddy that lives in the terminal. Written in rust with love <3
https://github.com/ovh/shai
agentic-ai ai cli coding-assistant
Last synced: about 2 months ago
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shai is a coding agent, your pair programming buddy that lives in the terminal. Written in rust with love <3
- Host: GitHub
- URL: https://github.com/ovh/shai
- Owner: ovh
- License: apache-2.0
- Created: 2025-07-16T13:31:16.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-08-02T08:17:32.000Z (4 months ago)
- Last Synced: 2025-08-02T10:40:57.282Z (4 months ago)
- Topics: agentic-ai, ai, cli, coding-assistant
- Language: Rust
- Homepage:
- Size: 2.7 MB
- Stars: 101
- Watchers: 4
- Forks: 8
- Open Issues: 22
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Authors: AUTHORS
Awesome Lists containing this project
- awesome-repositories - ovh/shai - shai is a coding agent, your pair programming buddy that lives in the terminal. Written in rust with love <3 (Rust)
- awesome-AI-driven-development - SHAI - a coding agent, your pair programming buddy that lives in the terminal. Written in rust with love <3 (Terminal & CLI Agents)
README
# SHAI
shai is a coding agent, your pair programming buddy that lives in the terminal. Written in rust with love <3
## Install
### install latest stable release
Install the latest release with the following command:
```
curl -fsSL https://raw.githubusercontent.com/ovh/shai/main/install.sh | sh
```
the `shai` binary will be installed in `$HOME/.local/bin`
### install ``nightly`` version
Install the last [``unstable``](https://github.com/ovh/shai/releases/tag/unstable) version with the following command:
```bash
curl -fsSL https://raw.githubusercontent.com/ovh/shai/main/install.sh | SHAI_RELEASE=unstable sh
```
the `shai` binary will be installed in `$HOME/.local/bin`
## Configure a provider and Run!
By default `shai` uses OVHcloud as an anonymous user meaning you will be rate limited! If you want to sign in with your account or select another provider, run:
```
shai auth
```
Once you have a provider set up, you can run shai:
```
shai
```
## Run Headless
Shai can also run in headless mode without user interface. In that case simply pipe a prompt into shai, it will stream event in the stderr:
```
echo "make me a hello world in main.py" | shai
```
you can also instruct shai to return the entire conversation as a trace once it is done:
```
echo "make me a hello world in main.py" | shai 2>/dev/null --trace
```
this is handy because you can chain `shai` calls:
```
echo "make me a hello world in main.py" | shai --trace | shai "now run it!"
```
## Project context file
You can create a `SHAI.md` file at the root of your project containing any information you want Shai to know about the project (architecture, build steps, important directories, etc.). Shai will automatically load this file as additional context.
## Custom Agent (with MCP)
Instead of a single global configuration, you can create custom agent in a separate configuration.
`example.config` contains an example of a custom configuration with an stdio MCP server configured.
Place this file in `~/.config/shai/agents/example.config`, you can then list the agents available with:
```
shai agent list
```
you can run shai with this specific agent with the `agent` subcommand:
```
shai example
```
## shell assistant
shai can also act as a shell assistant in case a command failed and will propose you a fix. This works by injecting command hook while monitoring your terminal output. Your last terminal output along with the last command and error code will be sent for analysis to the llm provider. To start hooking your shell with shai simply type:
```
$ shai on
```
for instance:
To stop shai from monitoring your shell you can type:
```
$ shai off
```
## Build The Project
Simply build the project with `cargo`
```
git clone git@github.com:ovh/shai.git
cd shai
cargo build --release
```
## Compatible OVHCloud endpoints
OVHCloud provides compatible LLM endpoints for using shai with tools. Start by creating a [_Public Cloud_ project in your OVHCloud account](https://www.ovh.com/manager/#/public-cloud), then head to _AI Endpoints_ and retreive your API key. After setting it in shai, you can:
- choose [one of the models with function calling feature](https://endpoints.ai.cloud.ovh.net/catalog) (e.g., [gpt-oss-120b](https://endpoints.ai.cloud.ovh.net/models/gpt-oss-120b), [gpt-oss-20b](https://endpoints.ai.cloud.ovh.net/models/gpt-oss-20b), [Mistral-Small-3.2-24B-Instruct-2506](https://endpoints.ai.cloud.ovh.net/models/mistral-small-3-2-24b-instruct-2506)) for best performance ;
- choose any other model forcing structured output (`/set so` option).