RAG-App: Agentic RAG Engine – Semantic Search, AI Agents
In this video, the channel WorldofAI introduces RAG-App, an open-source tool designed to build agentic RAG (Retrieval-Augmented Generation) AI agents. RAG-App allows users to chat with various file types, including PDFs, using different large language models such as Llama, OpenAI, and Gemini. The tool features a no-code interface, making it accessible for users to configure RAG chatbots that are private and fully local.
The video highlights the simplicity of setting up RAG-App, which can be deployed using Docker containers on any cloud infrastructure. The admin panel allows users to generate a chatbot over their data with full streaming support and file attachments. The tool also supports integrating custom tools into CRM systems or email, making it versatile for enterprise needs.
The demonstration includes the deployment process using Docker, configuring the chatbot with different models, and uploading a research paper to test the chatbot’s ability to reference and chunk the PDF. The chatbot successfully retrieves and summarizes information from the uploaded file, showcasing its capabilities.
The video also promotes WorldofAI Solutions, a team providing AI solutions for businesses and personal use cases, and encourages viewers to support the channel through Patreon and other means.
Overall, RAG-App is presented as a powerful and user-friendly tool for building customized AI agents and chatbots, suitable for both enterprise and personal use.