Deploying Retrieval-Augmented Generation (RAG) applications in enterprise environments can be complex. Many enterprises struggle with the intricacies of setting up and configuring these applications, especially when dealing with the nuances of different cloud infrastructures and ensuring security.
Existing solutions attempt to address these challenges. OpenAI’s custom GPTs offer a streamlined configuration experience, but they are typically hosted on third-party cloud services, raising concerns about data privacy and compliance. While these hosted solutions are convenient, they may not meet the needs of enterprises that require more control over their data and infrastructure.
RAGApp is a straightforward solution for enterprises looking to deploy Agentic RAG applications in their cloud environments. Using Docker, RAGApp simplifies the deployment process, making it as easy as running a single command. Built on LlamaIndex, RAGApp can be configured via an Admin UI accessible through a web browser. This flexibility allows enterprises to use hosted AI models from providers like OpenAI or Gemini, as well as local models via Ollama.
The capabilities of RAGApp are demonstrated through its features. The application provides three main endpoints: an Admin UI, a Chat UI, and an API. The Admin UI allows users to configure the RAGApp, while the Chat UI and API become functional once the app is set up. For security, RAGApp does not include built-in authentication, requiring users to secure the application paths through their cloud environment’s features, such as an Ingress Controller in Kubernetes. Additionally, RAGApp supports deployment with Docker Compose, enabling the use of different AI models and facilitating integration with local instances of Ollama.
In conclusion, RAGApp offers a practical and effective solution for enterprises looking to deploy RAG applications in their cloud infrastructure. By leveraging Docker and providing a user-friendly configuration interface, RAGApp simplifies the deployment process and gives enterprises the flexibility to choose their preferred AI models.
Niharika is a Technical consulting intern at Marktechpost. She is a third year undergraduate, currently pursuing her B.Tech from Indian Institute of Technology(IIT), Kharagpur. She is a highly enthusiastic individual with a keen interest in Machine learning, Data science and AI and an avid reader of the latest developments in these fields.
