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I was really fascinated by Gemini 1.5 pro, though it was a bit slow and sort of 70% accurate in my use case.

I have a huge 500k~ tokens and complex niche codebase that I've worked on for many years, largely alone. There are parts of it I wish to refactor but I struggle because it I've become blind to my own code. It also sometimes feels lonely in a way. If it was a game I could at least show my friends, but this project is too abstract.

Gemini missed the mark a few times, especially when asking about more complex things but overall it was useful. That it got things wrong is sort of ok because I knew the codebase well enough to spot those mistakes.

Gemini 1.5 pro gave me a glimpse into what it was like having "someone" understand your whole codebase, hint at areas to improve, etc. A bit like a true copilot or coworker, but for a dream hobby project.



How do you proceed to use it this way ? Did you have to write custom code to call the API with your codebase ? Can you give some example questions for which the LLM gave you useful insights and/or made you save time ?


I just used https://aistudio.google.com/, no api or anything.

My project "Nattlua" is a typed version of Lua like Typescript is to Javascript.

Some example questions that would give me new insight:

- Asking what the codebase is without supplying the readme. (though it might know because the codebase is public already)

- Asking it to generate complex type code based on existing tests and examples and without.

- Asking for places to refactor, the most fun one. Sometimes the exact solution provided is wrong, but often it's a good start.


How does it compare to others products in your use case?


I feel it was worse than gpt4 at coding at a low level (getting syntax right, forgetting small details, etc)

But I can write code so those can be fixed. At a higher level it's OK, but the most valuable thing is being able to have my codebase in its context. No other public LLM currently as far as I know can do that.




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