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36 lines
1.5 KiB
36 lines
1.5 KiB
# Using Large Language Models with Grist
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In this experimental Grist feature, originally developed by Alex Hall,
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you can hook up an AI model such as OpenAI's Codex to write formulas for
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you. Here's how.
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First, you need an API key. You'll have best results currently with an
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OpenAI model. Visit https://openai.com/api/ and prepare a key, then
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store it in an environment variable `OPENAI_API_KEY`.
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Alternatively, there are many non-proprietary models hosted on Hugging Face.
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At the time of writing, none can compare with OpenAI for use with Grist.
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Things can change quickly in the world of AI though. So instead of OpenAI,
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you can visit https://huggingface.co/ and prepare a key, then
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store it in an environment variable `HUGGINGFACE_API_KEY`.
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That's all the configuration needed!
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Currently it is only a backend feature, we are still working on the UI for it.
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## Trying other models
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The model used will default to `text-davinci-002` for OpenAI. You can
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get better results by setting an environment variable `COMPLETION_MODEL` to
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`code-davinci-002` if you have access to that model.
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The model used will default to `NovelAI/genji-python-6B` for
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Hugging Face. There's no particularly great model for this application,
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but you can try other models by setting an environment variable
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`COMPLETION_MODEL` to `codeparrot/codeparrot` or
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`NinedayWang/PolyCoder-2.7B` or similar.
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If you are hosting a model yourself, host it as Hugging Face does,
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and use `COMPLETION_URL` rather than `COMPLETION_MODEL` to
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point to the model on your own server rather than Hugging Face.
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