Interesting to see that the semantic chunking in the tools library is a wrapper around GPT-4. Asks GPT for the python code and executes it: https://github.com/NeumTry/NeumAI/blob/main/neumai-tools/neu...
I assume that in a not so distant future, a malware scanner will detect this and disallow one to run this locally.
Generally we have found that recursive chunking and character chunking tend to be short sighted.
Why not capture a few strategies that the LLM returns as code that can be properly audited (and ran locally improving the overall performance)?
The idea of auditing the strategy is interesting. The flow that we have used for the semantic chunkers up to date has been along these lines where we : 1) Use the utility to generate the code snippets (and do some manual inspection) 2) Test the code snippets against some sample text 3) Validate the results