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DataStax releases a number of updates to better facilitate RAG implementation

DataStax is making a number of improvements to its development platform that will allow developers to more easily implement retrieval augmented generation (RAG) in their generative AI applications. 

“The Generative AI stack is a big and complex ball of technology that many are working to get their arms around. We’re focused on helping developers stay true to their roots so they can do what they do best: build and develop, rather than worrying about application infrastructure. We’re delivering a cutting-edge, end-to-end stack to make this a lot easier,” said Ed Anuff, chief product officer at DataStax.

The company is releasing Langflow 1.0, the newest version of the visual framework for building RAG applications, which DataStax acquired back in April. This update includes dozens of integrations with other generative AI tools, including LangChain, LangSmith, OpenAI, Hugging Face, and Mistral. It also includes a cloud-hosted version of Langflow within DataStax Cloud and access to LangSmith’s observability capabilities. 

DataStax also announced RAGStack 1.0. RAGStack is an out-of-the-box solution that includes various tools needed to implement RAG. 

RAGStack 1.0 includes support for Langflow, a knowledge graph designed for generative AI, ColBERT powered by Astra DB, Text2SQL and Text2CQL, and Vectorize, which is a tool that lets developers choose their embedding service. 

The company will be demoing these new updates at its RAG++ event in San Francisco tonight.

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The post DataStax releases a number of updates to better facilitate RAG implementation appeared first on SD Times.



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