@datastax/ragstack-ai
Advanced tools
RAGStack is an out-of-the-box solution simplifying Retrieval Augmented Generation (RAG) in GenAI apps.
Looking for the Python version? Check out RAGStack for Python.
RAGStack includes the best open-source for implementing RAG, giving developers a comprehensive Gen AI Stack leveraging LangChainJS and more. RAGStack leverages the LangChain ecosystem and is fully compatible with LangSmith for monitoring your AI deployments.
For each open-source project included in RAGStack, we select a version lineup and then test the combination for compatibility, performance, and security. Our extensive test suite ensures that RAGStack components work well together so you can confidently deploy them in production.
RAGStack uses the Astra DB Serverless (Vector) database, which provides a highly performant and scalable vector store for RAG workloads like question answering, semantic search, and semantic caching.
Install @datastax/ragstack-ai via the CLI:
npx @datastax/ragstack-ai-cli install
RAGStack is based on LangChainJS, checkout the LangChainJS documentation to get started with the code.
FAQs
DataStax RAGStack for Javascript/Typescript
The npm package @datastax/ragstack-ai receives a total of 6 weekly downloads. As such, @datastax/ragstack-ai popularity was classified as not popular.
We found that @datastax/ragstack-ai demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 6 open source maintainers collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Research
Security News
Socket’s threat research team has detected six malicious npm packages typosquatting popular libraries to insert SSH backdoors.
Security News
MITRE's 2024 CWE Top 25 highlights critical software vulnerabilities like XSS, SQL Injection, and CSRF, reflecting shifts due to a refined ranking methodology.
Security News
In this segment of the Risky Business podcast, Feross Aboukhadijeh and Patrick Gray discuss the challenges of tracking malware discovered in open source softare.