DEVOPSdigest

DataStax announced a new integration with LangChain, an 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.

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.”