metadata

title: Buster
emoji: 🤖
colorFrom: red
colorTo: blue
sdk: gradio
app_file: buster/apps/gradio_app.py
python_version: 3.10.8
pinned: false

Buster, the QA documentation chatbot!

Buster is a question-answering chatbot that can be tuned to any source of documentations.

Demo

You can try out our live demo here, where it will answer questions about a bunch of libraries we've already scraped, including 🤗 Transformers.

Quickstart

Here is a quick guide to help you deploy buster on your own dataset!

First step, install buster locally. Note that buster requires python>=3.10.

git clone https://github.com/jerpint/buster.git
pip install -e .

Then, go to the examples folder. We've attached a sample stackoverflow.csv file to help you get started. You will convert the .csv to a documents.db file.

buster_csv_parser stackoverflow.csv --output-filepath documents.db

This will generate the embeddings and save them locally. Finally, run

gradio gradio_app.py

This will launch the gradio app locally, which you should be able to view on localhost

How does Buster work?

First, we parsed the documentation into snippets. For each snippet, we obtain an embedding by using the OpenAI API.

Then, when a user asks a question, we compute its embedding, and find the snippets from the doc with the highest cosine similarity to the question.

Finally, we craft the prompt:

The most relevant snippets from the doc.
The engineering prompt.
The user's question.

We send the prompt to the OpenAI API, and display the answer to the user!

Currently available models

For embeddings: "text-embedding-ada-002"
For completion: We support both "text-davinci-003" and "gpt-3.5-turbo"

Livestream

For more information, you can watch the livestream where explain how buster works in detail!