Managing RAG Studio

Manage the entire lifecycle of LLMs with the help of RAG Studio, empowering you to optimize AI workloads while enhancing the accuracy and efficiency of your models.

RAG Studio Overview
Retrieval-Augmented Generation (RAG) Studio is a no-code application for creating RAG chatbots that combine the power of retrieval and generation to provide accurate and efficient responses.
Key features for RAG Studio
RAG Studio allows you to create an application with a conversational interface (chatbot) that can be used to converse with a connected large language model, and comes with the functionality to enable retrieval-augemented generation to improve the performance and accuracy of the model’s responses.
Launching RAG Studio within a project
RAG Studio is compatible with Cloudera AI Inference service, AWS Bedrock, Azure OpenAI, and Open AI enabling you to select different LLM and embedding models tailored to your specific needs.
Configuring RAG Studio
After launching RAG Studio, an initial configuration is required, with optional settings available for additional customization. Without this configuration, the Studio will not be able to access any AI models.