Skip to content
This repository has been archived by the owner on May 28, 2024. It is now read-only.

Commit

Permalink
Remove aviary.anyscale.com references from README (#145)
Browse files Browse the repository at this point in the history
  • Loading branch information
ArturNiederfahrenhorst committed Mar 26, 2024
1 parent 6b86748 commit a36a602
Showing 1 changed file with 3 additions and 30 deletions.
33 changes: 3 additions & 30 deletions README.md
Original file line number Diff line number Diff line change
@@ -1,8 +1,9 @@
# RayLLM - LLMs on Ray

[![Build status](https://badge.buildkite.com/d6d7af987d1db222827099a953410c4e212b32e8199ca513be.svg?branch=master)](https://buildkite.com/anyscale/aviary-docker)
The hosted Aviary Explorer is not available anymore.
Visit [Anyscale](https://temp.endpoints.anyscale.com) to experience models served with RayLLM models.

Try it now: [🦜🔍 Ray Aviary Explorer 🦜🔍](http://aviary.anyscale.com/)
[![Build status](https://badge.buildkite.com/d6d7af987d1db222827099a953410c4e212b32e8199ca513be.svg?branch=master)](https://buildkite.com/anyscale/aviary-docker)

RayLLM (formerly known as Aviary) is an LLM serving solution that makes it easy to deploy and manage
a variety of open source LLMs, built on [Ray Serve](https://docs.ray.io/en/latest/serve/index.html). It does this by:
Expand Down Expand Up @@ -234,34 +235,6 @@ pip install "rayllm[frontend] @ git+https://github.com/ray-project/ray-llm.git"
The backend dependencies are heavy weight, and quite large. We recommend using the official
`anyscale/ray-llm` image. Installing the backend manually is not a supported usecase.

## Running Aviary Explorer locally

The frontend is a [Gradio](https://gradio.app/) interface that allows you to interact
with the models in the backend through a web interface.
The Gradio app is served using [Ray Serve](https://docs.ray.io/en/latest/serve/index.html).

To run the Aviary Explorer locally, you need to set the following environment variable:

```shell
export ENDPOINT_URL=<hostname of the backend, eg. 'http://localhost:8000'>
```

Once you have set these environment variables, you can run the frontend with the
following command:

```shell
serve run rayllm.frontend.app:app --non-blocking
```

You will be able to access it at `http://localhost:8000/frontend` in your browser.

To just use the Gradio frontend without Ray Serve, you can start it
with `python rayllm/frontend/app.py`. In that case, the Gradio interface should be accessible at `http://localhost:7860` in your browser.
If running the frontend yourself is not an option, you can still use
[our hosted version](http://aviary.anyscale.com/) for your experiments.

Note that the frontend will not dynamically update the list of models should they change in the backend. In order for the frontend to update, you will need to restart it.

### Usage stats collection

Ray collects basic, non-identifiable usage statistics to help us improve the project.
Expand Down

0 comments on commit a36a602

Please sign in to comment.