WeKnora - Tencent WeChat Open Source Document Understanding and Semantic Retrieval Framework

What is WeKnora?

WeKnora is Tencent WeChat team's open source large language model (LLM)-based document understanding and semantic retrieval framework, designed for structurally complex, heterogeneous document scenarios, using modular architecture, integration of multimodal preprocessing, semantic vector indexing, intelligent recall and large model generative reasoning, to build up a highly efficient and controllable document Q&A process. The core retrieval process is based on the RAG (Retrieval-Augmented Generation) mechanism, which combines contextually relevant fragments with language models to achieve higher quality semantic answers.

Features of WeKnora

• multimodal cognitive engineAccurately parses mixed-text content in PDF, Word, images and other formats to extract semantic information from text, tables and images.
• Modular RAG assembly line design: It supports free combination of search strategies, large language models and vector databases, and flexibly adapts to a variety of application scenarios.
• Precision Reasoning and Trusted Decision Assurance: Combines private deployment, multiple rounds of deep contextual understanding with full-link visual assessment to ensure Q&A accuracy and reliability.
• Flexibility to adapt to multiple production environments: Supports localized deployment and Docker images, compatible with private cloud and offline environments to meet different user needs.
• Out-of-the-box interactive experience: Provide one-click startup scripts and an intuitive Web UI interface to lower the threshold of use and enhance the user experience.

WeKnora's core strengths

• Deep multimodal understandingIt can accurately parse documents in multiple formats, extract semantic information from text, tables and images, and realize in-depth understanding of complex documents.
• Efficient Semantic Retrieval: Advanced semantic vector indexing technology is used to quickly find the most relevant document fragments to the query, improving retrieval efficiency and accuracy.
• Intelligent Q&A Generation: Combined with large language model generative reasoning, it provides context-aware intelligent Q&A and generates high-quality semantic answers.
• Modular Architecture: It supports free combination of search strategies, large language model and vector database, which is convenient for users to configure and expand flexibly according to their needs.
• Private deployment: Supports localized deployment and Docker images, compatible with private cloud and offline environments, ensuring data security and privacy.
• usability: Provide one-click startup scripts and an intuitive Web UI interface to lower the threshold of use and realize out-of-the-box usage.

What is WeKnora's official website

• Project website:: https://weknora.weixin.qq.com/
• GitHub repository:: https://github.com/Tencent/WeKnora

Who WeKnora is for

• Enterprise Knowledge Management Team: It is used to build and manage the internal knowledge base of an organization, quickly retrieve and extract key information, and enhance the efficiency of knowledge sharing.
• Intelligent Customer Service Developers: Integrate into the customer service system to quickly get information from product manuals, FAQs and other documents to improve the speed and quality of customer service response.
• Legal and financial professionals: Assist in analyzing complex legal documents, contracts, financial reports, and other documents to improve efficiency and accuracy.
• Academic researchers: Helps to speed up the research process by providing quick access to and understanding of a large number of academic papers and research reports.
• Educators and students: Used to build an intelligent learning system, students can quickly access the knowledge points in the textbook by asking questions to improve their learning efficiency.
• multi-source heterogeneous information processor: For scenarios where information needs to be integrated from different sources and documents in different formats and processed intelligently, such as data analysts and intelligence analysts.