Santa Clara, Calif. &ndash; February 20, 2024 &ndash; <a href="https://www.datastax.com/">DataStax</a>, the Gen AI data company, today announced its out-of-the-box <a href="https://www.datastax.com/guides/what-is-retrieval-augmented-generation">retrieval augmented generation</a> (RAG) solution, RAGStack, is now generally available powered by LlamaIndex as an open source framework, in addition to LangChain.&nbsp; DataStax RAGStack for LlamaIndex is also the first partner to support an integration (currently in public preview) with LlamaIndex&rsquo;s LlamaParse, which gives developers using <a href="https://www.datastax.com/products/datastax-astra">Astra DB</a> a simple API to efficiently parse and transform complex PDFs into vectors in minutes.&nbsp;&nbsp;
&nbsp;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&rsquo;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.&nbsp;
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&reg;, 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.&nbsp;
&ldquo;We are excited to be working with DataStax to streamline the implementation process of RAG techniques,&rdquo; said Jerry Liu, co-founder and CEO of LlamaIndex. &ldquo;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.&rdquo;
"At Imprompt, we're pioneering digital interaction with our 'Chat-to-Everything&rsquo; platform, seamlessly integrating with Astra DB from DataStax as our primary vector store,&rdquo; said Jeff Schneider, CEO at Imprompt. &ldquo;With RAGStack powered by LlamaIndex, we enhance enterprise offerings while prioritizing privacy. Our integration with RAGStack enables secure data exchange, powering innovation for global enterprises."
&ldquo;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,&rdquo; said Davor Bonaci, CTO and executive vice president, DataStax. &ldquo;By incorporating LlamaIndex into RAGStack, we are providing developers with a comprehensive GenAI stack that simplifies the complexities of RAG implementation, while offering long-term support and compatibility assurance.&rdquo;
To learn more about the integration, join the live &ldquo;how to&rdquo; event on March 12 at 10 a.m. PT with LlamaIndex and Imprompt &ndash; sign up <a href="https://www.crowdcast.io/c/w8si7ykqrs8a">here</a> for details. To get started, check out the notebook examples of how to use <a href="https://docs.datastax.com/en/ragstack/docs/examples/llama-astra.html">LlamaIndex</a> and <a href="https://docs.datastax.com/en/ragstack/docs/examples/llama-parse-astra.html">LlamaParse</a> with Astra DB.&nbsp;
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Additional Resources
<ul>
<li style="font-weight: 400;" aria-level="1"><a href="https://www.youtube.com/watch?v=yLRgWfH0g7o">How to power a NoSQL assistant with gen AI</a></li>
<li style="font-weight: 400;" aria-level="1"><a href="https://www.datastax.com/use-cases/vector-search-llm-generative-ai">Vector Search for LLM and Generative AI Applications</a></li>
<li style="font-weight: 400;" aria-level="1"><a href="https://www.datastax.com/resources/whitepaper/vector-search-for-generative-ai-apps?filter=%7B%7D">Whitepaper: Vector Search for Generative AI Apps</a></li>
</ul>
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About DataStax
<a href="https://www.datastax.com/">DataStax</a>, the GenAI data company, helps developers and companies successfully create a bold new world through GenAI. We offer a one-stop Generative AI Stack with everything needed for a faster, easier, path to production for relevant and responsive GenAI apps. DataStax delivers a RAG-first developer experience, with first-class integrations into leading AI ecosystem partners, so we work out with developers&rsquo; existing stacks of choice. Anyone can quickly build smart, high-growth AI applications at unlimited scale, on any cloud. Hundreds of the world&rsquo;s leading enterprises, including Audi, Bud Financial, Capital One, SkyPoint Cloud, and many more rely on DataStax to deliver GenAI. Learn more at <a href="https://www.datastax.com/">DataStax.com</a>.&nbsp;
&copy; 2024 DataStax Inc., All Rights Reserved. DataStax is a registered trademark of DataStax, Inc. and its subsidiaries in the United States and/or other countries.&nbsp;
Apache, Apache Cassandra, and Cassandra, are either registered trademarks or trademarks of the Apache Software Foundation or its subsidiaries in Canada, the United States, and/or other countries.
 
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