(core) Porting back AI formula backend

Summary: This is a backend part for the formula AI.

Test Plan: New tests

Reviewers: paulfitz

Reviewed By: paulfitz

Subscribers: cyprien

Differential Revision: https://phab.getgrist.com/D3786

documentation/llm.md

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