PythonGPT VS chatgpt-localfiles

There was another post today about using Pydantic for function enabled completions: https://github.com/jxnl/openai_function_call

I whipped up an example doing something similar last Friday using a decorator, inspect, ast and __doc__ usage: https://gist.github.com/kordless/7d306b0646bf0b56c44ebca2b8e.... The example pulls top results from Algoia's HN search and then chains them into another prompt for GPT-X. The blog post is here: https://www.featurebase.com/blog/function-integration-in-ope...

Currently integrating this approach into PythonGPT[1], which will build a function on the fly, extract the method info, then call the code in exec(). I would label it "very dangerous"...

[1] https://github.com/FeatureBaseDB/PythonGPT

I built a local developer-mode plugin that gives ChatGPT access to a local directory [0] -- it's pretty basic in terms of functionality (just simple bridge to access/read files) but I've found a surprising amount of value from it [1]!

[0] https://github.com/samrawal/chatgpt-localfiles

[1] https://samrawal.substack.com/p/example-driven-development

I wrote a simple ChatGPT plugin that exposes files within a local directory on my computer to ChatGPT [0]. It's been quite helpful for me, both for working with code as well as other material (supports docx and pdf as well). It does require plugin developer access to run, though.

[0] https://github.com/samrawal/chatgpt-localfiles