Fausto Ivan Zamora Arias

Improving LLMs CAG with accumulative knowledge using RabbitMQ, Ollama and Gemma3 Why RabbitMQ ? Thinking about an LLM that will receive a lot of messages from everywhere means that you need to keep track of its messages and responses so the context could be understood on the whole conversation. Remember that it can't be just a stream every time; sometimes users would appear after days or months, and the sense of knowing the person should be stored. Now, storing is just one part of the solution for retaining context. We all have heard about RAG and CAG, but what happens if I need to store the information in real-time? You know, users keep sending messages. So the saving and retrieving messages would be blocking the AI's response time. Therefore, I figured why not use a queue system that notifies a consumer about new messages, stores them in a DB, so t...

 So I had this friend who was pretty upset because every time he wanted to do an offer on Opensea a bot took it , and as you could imagine it was "blazing fast". Which made me think, as someone who do computers for a living, how to make an NFT bot which makes offers and buys NFTs in real time? Well I dont know much about NFTs, but I love programming crasy experiments, so I decided to use NodeJs and ask the AIs how to do it, to be fair vibe coding but a story to tell. So I started by looking into ChatGPT , which sugested some alternatives but not a direct script, you know it seems like it learned to just give hints on crypto stuff.  Then I asked DeepSeek which was way more efficient on code and an actual division of buying and offering. Well what did I found ? First is the Ethers library    which is a library to manage etherium and ilk , which means the way you create a wallet instance  this.provider = new ethers.provide...