Build More Accurate AI Apps Through Fast Experimentation with Arize Phoenix, Langflow, and NVIDIA

The text discusses the challenges of building accurate AI apps, particularly in ensuring that they provide accurate answers to customers. The authors introduce a workflow for measuring accuracy using Arize Phoenix and Langflow, two open-source platforms developed by DataStax and NVIDIA respectively. The workflow involves creating a ground truth dataset, adding it to Arize Phoenix, designing a basic chatbot in Langflow, connecting Arize Phoenix to Langflow to measure accuracy, and adding a reranking model to improve the accuracy of the RAG chatbot. The authors demonstrate how to use these platforms to rapidly experiment with different AI design patterns, integrate capabilities from NVIDIA, and track over time how changes affect accuracy. By using this workflow, developers can build accurate AI apps that provide great experiences for their customers.

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