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Ragna is an open-source RAG-based (Retrieval-Augmented Generation) AI orchestration framework designed to bridge the gap between AI research and production deployment. It provides a flexible and extensible platform that allows organizations to leverage the capabilities of large language models (LLMs) for a wide range of applications.

Ragna combines the strengths of retrieval models and generative models, enabling LLMs to access and utilize relevant information from document collections, resulting in more accurate and context-aware responses. With Ragna, you can seamlessly integrate LLMs, vector databases, tokenization strategies, and embedding models and experiment with different configurations to optimize performance and accuracy.

  • Open-Source and Transparent: Ragna promotes transparency and flexibility, allowing organizations to understand and customize the inner workings of the system according to their specific needs.
  • Scalable from Research to Production: Ragna provides a unified framework that supports both research and experimentation, as well as the deployment of production-ready applications, without the need for a complete code overhaul.
  • Modular and Extensible: Ragna allows you to mix and match different components and easily integrate new technologies as they emerge.
  • Efficient Document Retrieval: Ragna leverages vector databases and similarity search algorithms to efficiently retrieve the most relevant text passages from document collections, ensuring that LLMs have access to the necessary information to generate accurate responses.
  • Streamlined Development: Ragna offers a Python API for experimentation, a REST API for building web applications or integrating with third-party tools, and a fully-featured GUI, enabling a seamless development experience from prototyping to production.
  • Vendor Lock-in Avoidance: As an open-source solution, Ragna eliminates the risk of vendor lock-in, allowing organizations to leverage the power of AI without being tied to a single provider.
  • Collaborative and Community-Driven: Being an open-source project, Ragna fosters collaboration and knowledge-sharing within the AI community, leading to continuous improvement and innovation.