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DataStax and LlamaIndex Simplify RAG Application Development for GenAI Developers

DataStax

Developers Can Now Utilize DataStax RAGStack and LlamaIndex Integration to Build GenAI Applications, Including a Preview of LlamaParse

DataStax launches RAGStack, powered by LlamaIndex and LangChain, now generally available. It’s the first to integrate with LlamaParse, offering developers an efficient PDF parsing API for Astra DB users.

LlamaIndex is a framework for ingesting, indexing, and querying data for building generative AI applications and addresses the ingestion pipelines needed for enterprise-ready RAG. LlamaParse is LlamaIndex’s new offering that targets enterprise developers building RAG over complex PDFs; it enables clean extraction of tables by running recursive retrieval, promising more accurate parsing of the complex documents often found in business.

Out-of-the-box RAG solutions are in high demand, so this integration is a significant milestone for our enterprise developers seeking to implement generative AI applications

Davor Bonaci, CTO and executive vice president, DataStax

RAGStack with LlamaIndex offers a comprehensive solution tailored to address the challenges encountered by enterprise developers in implementing RAG solutions. Key benefits include a curated Python distribution available on PyPI, ensuring smooth integration with Astra DB, DataStax Enterprise (DSE), and Apache Cassandra®, and a live RAGStack test matrix and proven GenAI app templates. The inclusion of LlamaIndex enhanced indexing and parsing capabilities enables users to use LlamaIndex alone, or in combination with LangChain and their ecosystem including LangServe, LangChain Templates, and LangSmith.

“We are excited to be working with DataStax to streamline the implementation process of RAG techniques,” said Jerry Liu, co-founder and CEO of LlamaIndex. “Together, we’re reshaping the RAG landscape by offering a simplified journey for not only enterprises but also developers looking to put GenAI applications into production with ease. This collaboration embodies our commitment to simplicity, innovation, and limitless possibilities.”

“At Imprompt, we’re pioneering digital interaction with our ‘Chat-to-Everything’ platform, seamlessly integrating with Astra DB from DataStax as our primary vector store,” said Jeff Schneider, CEO at Imprompt.”

“Out-of-the-box RAG solutions are in high demand, so this integration is a significant milestone for our enterprise developers seeking to implement generative AI applications,” said Davor Bonaci, CTO and executive vice president, DataStax.”

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