Visualize your RAG Data — Evaluate your Retrieval-Augmented Generation System with Ragas

Visualize your RAG Data — Evaluate your Retrieval-Augmented Generation System with Ragas

How to use UMAP dimensionality reduction for Embeddings to show multiple evaluation Questions and their relationships to source documents with Ragas, OpenAI, Langchain and ChromaDB

Retrieval-Augmented Generation (RAG) adds a retrieval step to the workflow of an LLM, enabling it to query relevant data from additional sources like private documents when responding to questions and queries [1]. This workflow does not require costly training or fine-tuning of LLMs …

chatgpt data data science dimensionality documents editors pick embeddings evaluation langchain large language models llm machine learning multiple openai questions rag relationships retrieval retrieval-augmented show umap workflow