ViDoRAG is a novel multimodal retrieval-augmented generation framework developed by Alibaba's Natural Language Processing team, designed for complex reasoning tasks involving visually rich documents. This framework significantly improves the robustness and accuracy of generative models through dynamic iterative reasoning agents and a Gaussian Mixture Model (GMM)-driven multimodal retrieval strategy. Key advantages of ViDoRAG include efficient handling of visual and textual information, support for multi-hop reasoning, and high scalability. The framework is suitable for scenarios requiring information retrieval and generation from large-scale documents, such as intelligent question answering, document analysis, and content creation. Its open-source nature and flexible, modular design make it a valuable tool for researchers and developers in the multimodal generation field.