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docs: Mention support for other languages #684

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12 changes: 7 additions & 5 deletions README.md
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Expand Up @@ -16,7 +16,7 @@

envd (`ɪnˈvdɪ`) is a **machine learning development environment** for data science and AI/ML engineering teams.

🐍 **No Docker, only Python** - Focus on writing Python code, we will take care of Docker and development environment setup.
🐍 **No Docker** - Focus on writing Python/R/Julia code, we will take care of Docker and development environment setup.

🖨️ **Built-in Jupyter/VSCode** - First-class support for Jupyter and VSCode remote extension.

Expand All @@ -32,9 +32,9 @@ It is still too difficult to configure development environments and reproduce re

`envd` is a **machine learning development environment** for data science and AI/ML engineering teams. Environments built with `envd` provide the following features out-of-the-box:

🐍 **Life is short, use Python[^1]**
🐍 **Life is short, use Python[^1]/R/Julia**

Development environments are full of Dockerfiles, bash scripts, Kubernetes YAML manifests, and many other clunky files that are always breaking. `envd` builds are isolated and clean. You can write simple instructions in Python, instead of Bash / Makefile / Dockerfile / ...
Development environments are full of Dockerfiles, bash scripts, Kubernetes YAML manifests, and many other clunky files that are always breaking. `envd` builds are isolated and clean. You can write simple instructions in Python/R/Julia, instead of Bash / Makefile / Dockerfile / ...

![envd](./docs/images/envd.png)

Expand Down Expand Up @@ -92,8 +92,8 @@ You can reproduce the same dev environment, on your laptop, public cloud VMs, or

We’re focused on helping data scientists and teams that develop AI/ML models. And they may suffer from:

- building the development environments with Python, CUDA, Docker, SSH, and so on. Do you have a complicated Dockerfile or build script that sets up all your dev environments, but is always breaking?
- Updating the environment. Do you always need to ask infrastructure engineers how to add a new python package in the Dockerfile?
- building the development environments with Python/R/Julia, CUDA, Docker, SSH, and so on. Do you have a complicated Dockerfile or build script that sets up all your dev environments, but is always breaking?
- Updating the environment. Do you always need to ask infrastructure engineers how to add a new Python/R/Julia package in the Dockerfile?
- Managing environments and machines. Do you always forget which machines are used for the specific project, because you handle multiple projects concurrently?

---
Expand Down Expand Up @@ -154,6 +154,8 @@ def build():
shell("zsh")
```

*Note that we use Python here as an example but please check out examples for other languages such as R and Julia [here](https://github.com/tensorchord/envd/tree/main/examples).*

Then please run the command below to set up a new environment:

```
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