Handling greet type of questions without llm in RAG
I’m implementing a Retrieval-Augmented Generation (RAG) system for a chatbot that handles a variety of user queries. While RAG is primarily designed to provide informative responses by retrieving relevant documents and generating responses using a language model (LLM), I want to handle certain types of queries, like greetings and polite exchanges, without resorting to the LLM for efficiency and control.
I want the model to generate an exact number of tokens, no more, no less
Are there any tips or best practices to achieve this? I have tried few-shot prompting
are there any open source models which can perform this?
I have tried few-shot prompting it was not giving best results. Thank you in advance
How can i create AI to find how random numbers are being generated?
i’m trying to understand first if this is possible or not and if so then how can i begin to work on this, so what’s i’m trying to do is there is one game that gives us 2 numbers every time and we select one of those and it then tells us if it’s right answer or not. so i have lots of it’s old data of which number was true 0 or 1 in last 2k some turns.