How to Train on Other Documentation

This AI can use any documentation, but first it needs to be prepared for similarity search.

video-example-of-how-to-do-it

Start by going to /scripts/ folder.

If you open this file you will see that it uses RST files from the folder to create a index.faiss and index.pkl.

It currently uses OPEN_AI to create vector store, so make sure your documentation is not too big. Pandas cost me around 3-4$.

You can usually find documentation on github in docs/ folder for most open-source projects.

Name it inputs/
Put all your .rst/.md files in there
The search is recursive, so you don't need to flatten them

If there are no .rst/.md files just convert whatever you find to txt and feed it. (don't forget to change the extension in script)

And write your OpenAI API key inside OPENAI_API_KEY=<your-api-key>

python ingest.py ingest

It will tell you how much it will cost

Once you run it will use new context that is relevant to your documentation Make sure you select default in the dropdown in the UI

Customization

You can learn more about options while running ingest.py by running:

python ingest.py --help

Options
ingest	Runs 'ingest' function converting documentation to to Faiss plus Index format
--dir TEXT	List of paths to directory for index creation. E.g. --dir inputs --dir inputs2 [default: inputs]
--file TEXT	File paths to use (Optional; overrides directory) E.g. --files inputs/1.md --files inputs/2.md
--recursive / --no-recursive	Whether to recursively search in subdirectories [default: recursive]
--limit INTEGER	Maximum number of files to read
--formats TEXT	List of required extensions (list with .) Currently supported: .rst, .md, .pdf, .docx, .csv, .epub, .html [default: .rst, .md]
--exclude / --no-exclude	Whether to exclude hidden files (dotfiles) [default: exclude]
-y, --yes	Whether to skip price confirmation
--sample / --no-sample	Whether to output sample of the first 5 split documents. [default: no-sample]
--token-check / --no-token-check	Whether to group small documents and split large. Improves semantics. [default: token-check]
--min_tokens INTEGER	Minimum number of tokens to not group. [default: 150]
--max_tokens INTEGER	Maximum number of tokens to not split. [default: 2000]

convert	Creates documentation in .md format from source code
--dir TEXT	Path to a directory with source code. E.g. --dir inputs [default: inputs]
--formats TEXT	Source code language from which to create documentation. Supports py, js and java. E.g. --formats py [default: py]