In the era of information explosion, processing complex documents has always been a challenge for enterprises and researchers. Now, Tencent has open-sourced a new document understanding and retrieval tool based on large language models (LLMs), called WeKnora, aiming to help users efficiently extract and integrate information from various document formats such as PDF, Word, and images, and build a unified semantic view.
The biggest highlight of WeKnora is its powerful multimodal processing capability. It not only can extract structured content from different types of documents but also integrates these scattered pieces of information, providing users with a comprehensive and unified semantic perspective. With the strong understanding ability of LLMs, WeKnora can deeply understand the context of documents, achieving accurate question answering and smooth multi-turn conversations, greatly improving the efficiency and accuracy of information retrieval.
Additionally, WeKnora adopts a modular architecture, including core components such as document parsing, vectorization processing, retrieval engine, and large model reasoning. Each component can be flexibly configured and extended according to specific needs. This design makes it have broad application prospects, which can be used to build enterprise knowledge bases, research literature analysis assistants, medical knowledge assistants, legal regulations assistants, and even construct complex knowledge graphs, providing strong technical support for various industries.
Link: https://github.com/Tencent/WeKnora