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# Open-Assistant
<h1 align="center">
Open-Assistant
</h1>
Open Assistant is a project meant to give everyone access to a great chat based
large language model.
<p align="center">
<img width="60%" hight="100%" src="https://github.com/LAION-AI/Open-Assistant/blob/main/assets/logo.png"/>
</p>
Table of Contents
=======================
* [What is Open Assistant?](#what-is-open-assistant)
* [Do you want to try it out?](#do-you-want-to-try-it-out)
* [The Plan](#the-plan)
* [The Vision](#the-vision)
* [How can you help?](#how-can-you-help)
* [I’m in! Now what?](#i'm-in-now-what)
---
What is Open Assistant?
------
_Open Assistant is a project meant to give everyone access to a great chat based
large language model._
We believe that by doing this we will create a revolution in innovation in
language. In the same way that stable-diffusion helped the world make art and
@@ -14,7 +36,7 @@ If you are interested in taking a look at the current state of the project, you
can set up an entire stack needed to run **Open-Assistant**, including the
website, backend, and associated dependent services.
To start the demo, run this in the root directory of the repository:
##### To start the demo, run this in the root directory of the repository:
```sh
docker compose up --build
@@ -23,10 +45,10 @@ docker compose up --build
Then, navigate to `http://localhost:3000` (It may take some time to boot up) and
interact with the website.
**Note:** When logging in via email, navigate to `http://localhost:1080` to get
> **Note:** When logging in via email, navigate to `http://localhost:1080` to get
the magic email login link.
**Note:** If you would like to run this in a standardized development
> **Note:** If you would like to run this in a standardized development
environment (a
["devcontainer"](https://code.visualstudio.com/docs/devcontainers/containers))
using
@@ -37,8 +59,7 @@ provided [`.devcontainer`](.devcontainer/) folder.
## The Plan
We want to get to an initial MVP as fast as possible, by following the 3-steps
outlined in the InstructGPT paper.
##### We want to get to an initial MVP as fast as possible, by following the 3-steps outlined in the InstructGPT paper.
1. Collect high-quality human generated Instruction-Fulfillment samples
(prompt + response), goal >50k. We design a crowdsourced process to collect