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It is crucial to evaluate the model's performance when working with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG). The project aims to implement a feedback flow for chatbot answers, allowing users to provide feedback using "Good" and "Bad" options. These responses will be collected and analyzed for continuous evaluation.
Expected outcomes
Users can provide feedback for each chatbot answer using “Good” and “Bad” options (the system must store responses in the database).
The text was updated successfully, but these errors were encountered:
Feature description
It is crucial to evaluate the model's performance when working with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG). The project aims to implement a feedback flow for chatbot answers, allowing users to provide feedback using "Good" and "Bad" options. These responses will be collected and analyzed for continuous evaluation.
Expected outcomes
Users can provide feedback for each chatbot answer using “Good” and “Bad” options (the system must store responses in the database).
The text was updated successfully, but these errors were encountered: