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# Buster, the Mila cluster chatbot! | |
Buster is a chatbot that can answer questions about the Mila cluster. You can try it [here](https://huggingface.co/spaces/jerpint/buster). | |
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Where should I put my data when running a job? | |
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How do I run a job with 2 GPUs? | |
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It also works in french, although not as well: | |
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Comment est-ce que je lance une job avec 2 GPUs? | |
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If you ask a stupid question, you will get a stupid answer: | |
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What has more calories: a DGX A100 or a pasta salad? | |
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## How does Buster works? | |
First, we parsed the [Mila docs](https://docs.mila.quebec/index.html) into snippets. You can see exactly how in [`buster.docparser.get_all_documents`](https://github.com/jerpint/buster/blob/main/buster/docparser.py#L17). | |
The resulting snippets can be seen in [`buster/data/documents.csv`](https://github.com/jerpint/buster/blob/main/buster/data/documents.csv). | |
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, find the snippet from the doc with the highest cosine similarity to the question. | |
Finally, we craft the prompt: | |
- The most relevant snippet from the doc | |
- The engineering prompt: "Now answer the following question:" | |
- 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" | |