Tencent has officially open-sourced the new document understanding and semantic retrieval framework WeKnora (Weina La). This is a smart Q&A solution specifically designed for complex and heterogeneous document scenarios, aiming to provide an efficient and controllable end-to-end process for enterprise-level document Q&A.
WeKnora adopts a modern modular design, building a complete document understanding and retrieval pipeline, covering core modules such as document processing, knowledge modeling, retrieval engine, reasoning generation, and interactive display. The document processing layer is responsible for parsing and preprocessing documents in various formats, converting unstructured content into structured data; the knowledge modeling layer constructs knowledge representations through technologies such as vectorization, chunking, knowledge graphs, and indexing; the retrieval engine layer integrates multiple retrieval strategies to achieve efficient and accurate content recall; the reasoning generation layer uses large language models to understand and generate the retrieved results; the interactive display layer provides an intuitive user interface and standard API interfaces.
WeKnora is built on large language models (LLMs), integrating technologies such as multi-modal preprocessing, semantic vector indexing, intelligent retrieval, and large model generation reasoning. Its technical highlights include a powerful multi-modal cognitive engine that can accurately parse mixed text and image content in PDFs, Word documents, and images, extract text, tables, and image semantic information, and combine OCR with cross-modal modeling technology to build a unified structured knowledge center. The modular RAG pipeline design supports free combination of retrieval strategies, large language models, and vector databases, seamlessly integrating with platforms like Ollama, flexibly switching mainstream models such as Qwen and DeepSeek, meeting the efficient customization needs of enterprise knowledge bases. Accurate reasoning and reliable decision-making guarantee include private deployment, deep understanding of multi-turn context, and full-chain visibility evaluation, providing reliable knowledge support for high-sensitive scenarios. In addition, WeKnora supports local deployment and Docker images, compatible with private clouds and offline environments, with an internal monitoring log system, providing full-chain observability to help operations staff efficiently manage.
WeKnora offers an out-of-the-box interactive experience, including one-click startup scripts and an intuitive Web UI interface, allowing non-technical users to quickly complete the deployment and application of document indexing and intelligent Q&A services.
WeKnora is widely applicable to various enterprise-level document Q&A scenarios, including enterprise knowledge management, research literature analysis, product technical support, legal compliance review, and medical knowledge assistance. It provides an intuitive and easy-to-use Web interface, supporting drag-and-drop upload of various documents, automatically recognizing document structure and extracting core knowledge, building indexes. The system also supports knowledge graph visualization, capable of transforming documents into knowledge graphs, displaying the relationships between different sections of the document, improving the relevance and breadth of search results.
WeKnora offers flexible deployment methods. For local deployment, it provides a complete Docker deployment solution, allowing users to quickly start services with simple commands. In addition, as a core technical framework of the WeChat Conversation Open Platform, WeKnora also supports no-code deployment, where users only need to upload knowledge to quickly deploy intelligent Q&A services within the WeChat ecosystem, achieving a "ask and answer immediately" experience. Through the WeChat Conversation Open Platform, WeKnora's intelligent Q&A capabilities can be seamlessly integrated into WeChat scenarios such as official accounts and mini programs, enhancing user interaction experiences.