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# Buster, the QA documentation chatbot! | |
Buster is a question-answering chatbot that can be tuned to specific documentations. You can try it [here](https://huggingface.co/spaces/jerpint/buster), where it will answer questions about [🤗 Transformers](https://huggingface.co/docs/transformers/index). | |
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## How does Buster work? | |
First, we parsed the documentation into snippets. For each snippet, we obtain an embedding by using the [OpenAI API](https://beta.openai.com/docs/guides/embeddings/what-are-embeddings). | |
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](https://beta.openai.com/docs/api-reference/completions), and display the answer to the user! | |
### Currently used models | |
- For embeddings: "text-embedding-ada-002" | |
- For completion: "text-davinci-003" | |
### Livestream | |
For more information, you can watch the livestream where explain how buster works in detail! | |
- [Livestream recording](https://youtu.be/LB5g-AhfPG8) | |
- [Livestream notebook](https://colab.research.google.com/drive/1CosxSNod48KrkyBn5_vkeleb7u0CrBa6) | |