DataStax, the company that powers generative AI applications with real-time, scalable data, today announced a new integration with LangChain, the most popular orchestration framework for developing applications with large language models (LLMs). The integration makes it easy to add Astra DB – the real-time database for developers building production Gen AI applications – or Apache Cassandra, as a new vector source in the LangChain framework.
As many companies implement retrieval augmented generation (RAG) – the process of providing context from outside data sources to deliver more accurate LLM query responses – into their generative AI applications, they require a vector store that gives them real-time updates with zero latency on critical, real-life production workloads.
Generative AI applications built with RAG stacks require a vector-enabled database and an orchestration framework like LangChain, to provide memory or context to LLMs for accurate and relevant answers. Developers use LangChain as the leading AI-first toolkit to connect their application to different data sources.
The new integration lets developers leverage the power of the Astra DB vector database for their LLM, AI assistant, and real-time generative AI projects through the LangChain plugin architecture for vector stores. Together, Astra DB and LangChain help developers to take advantage of framework features like vector similarity search, semantic caching, term-based search, LLM-response caching, and data injection from Astra DB (or Cassandra) into prompt templates.
In a RAG application, the model receives supplementary data or context from various sources — most often a database that can store vectors, said Harrison Chase, CEO, LangChain. Building a generative AI app requires a robust, powerful database, and we ensure our users have access to the best options on the market via our simple plugin architecture. With integrations like DataStax's LangChain connector, incorporating Astra DB or Apache Cassandra as a vector store becomes a seamless and intuitive process.
“Developers at startups and enterprises alike are using LangChain to build generative AI apps, so a deep native integration is a must-have,” said Ed Anuff, CPO, DataStax. “The ability for developers to easily use Astra DB as their vector database of choice, directly from LangChain, streamlines the process of building the personalized AI applications that companies need. In fact, we’re already seeing customers benefit from our joint technologies as healthcare AI company, Skypoint, is using Astra DB and LangChain to power its generative AI healthcare model.”
To learn more, join the live webinar on October 26 at 9am PT, where LangChain founder and CEO, Harrison Chase, and SkyPoint founder and CEO, Tisson Mathew, discuss their experience building production RAG applications.
About DataStax
DataStax is the company that powers generative AI applications with real-time, scalable data with production-ready vector data tools that generative AI applications need, and seamless integration with developers’ stacks of choice. The Astra DB vector database provides developers with elegant APIs, powerful real-time data pipelines, and complete ecosystem integrations to quickly build and deploy production-level AI applications. With DataStax, any enterprise can mobilize real-time data to quickly build smart, high-growth AI applications at unlimited scale, on any cloud. Hundreds of the world’s leading enterprises, including Audi, Bud Financial, Capital One, SkyPoint Cloud, Verizon, VerSe Innovation, and many more rely on DataStax to deliver real-time AI. Learn more at DataStax.com.
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