Quote:
Originally Posted by OriginalContentGuy
[You must be logged in to view images. Log in or Register.]
Ekco, I watched your video about your embedded machine learning personal assistant. And while it's definitely attention grabbing, I really want to know what your actual workflow looks like with this tool. What are your early insights and/or first impressions about your experience? Also did you code it yourself?
|
https://github.com/Ekco-S64QTN6/ollama_rag_agent
it's 100% vibe coded and i have no idea what i'm doing, this is my first time even looking at python and i'm using Gemini mainly to teach me concepts and explain things as we go, and for the code i let Gemini, DeepSeek and Chatgpt argue/code review each other pipe that back into Gemini and have it explain to me like "structurally where should this go in the main loop" i ask what's best practices a lot.
it's a lot of "let's add tts to it?" "llms don't have persistent memory how do we go about adding that?" "walk me through installing PostgreSQL" "hey this single file is getting really long can we break this out into multiple files" and me going Ooooh so that's what refactoring code means..etc..etc
it's inefficient anyone who actually knows this stuff could have done it in 1/100th the time and it's probably the worst way ever to actually try and learn something
my early insights/first impressions are it's just a glorified autocorrect (LLMs) that you can attach some other tools to like in my case letting it run commands and scripts, talk, display system info like neofetch does and in theory actually index and parse the documents i have in the data folder locally so i can ask it questions
[You must be logged in to view images. Log in or Register.]