Setting up and configuring Retrieval-Augmented Generation (RAG) applications in enterprise environments can be a complicated process. Enterprises often struggle with understanding the complexities involved, particularly when dealing with the variations of different cloud platforms and the need for ensuring robust security.
OpenAI’s custom Generative Pretrained Transformers (GPTs) offer options that can simplify the configuration process, but these are frequently hosted on third-party cloud services, which can potentially raise data privacy and compliance issues. While convenient, these hosted solutions may not provide the level of data and infrastructure control that some enterprises demand.
RAGApp, a streamlined solution for enterprises wanting to deploy RAG applications on their cloud platforms, may offer a resolution. Built on LlamaIndex and used effectively with Docker, RAGApp simplifies the deployment process to make it as easy as executing a single command. RAGApp also offers a flexible configurable Admin UI that can be accessed via a web browser. This flexibility allows the use of hosted AI models from providers like OpenAI or Gemini, or even local models through Ollama.
RAGApp offers an array of features to ease the deployment process. The application offers three main endpoints — an Admin UI, which facilitates configuration, a Chat UI, and an API, both of which become functional once the application is set up. To ensure secure usage, RAGApp does not include built-in authentication but requires users to secure the application through their own cloud environment’s features, such as Kubernetes Ingress Controller. Moreover, the application supports deployment with Docker Compose, enabling the use of several AI models and simplified integration with local Ollama instances.
In conclusion, RAGApp offers an effective and practical solution for businesses looking to deploy RAG applications in their cloud infrastructure. By leveraging Docker and offering a simple user interface for configuration, RAGApp simplifies the deployment process. Furthermore, it gives enterprises the flexibility to choose their preferred AI models. This all makes RAGApp an ideal tool for businesses venturing into building their Agentic RAG applications in their enterprise as simply as using GPTs.
