Youtu-GraphRAG - Tencent Youtu Labs Open Source Graph Retrieval Augmentation Generation Framework

What is Youtu-GraphRAG?

Youtu-GraphRAG is an open source graph retrieval augmentation generation framework from Tencent's Youtu Labs to help large language models handle complex Q&A tasks more accurately. By constructing a four-layer knowledge tree, the knowledge is disassembled into four levels: attributes, relations, keywords and communities, which realizes autonomous evolution and high-quality extraction of cross-domain knowledge. The framework upgrades the community detection technology and generates concise summaries combined with semantic understanding to improve the readability and accuracy of knowledge.Youtu-GraphRAG's intelligent iterative retrieval mechanism can break down a complex question into multiple sub-questions and retrieve them in parallel, and correct the results through an iterative reflection mechanism to significantly improve the accuracy and reliability of the answers. In six authoritative benchmark tests, it saves up to 90.71% of Token cost, and the accuracy of complex reasoning tasks is improved by up to 16.62%. The framework supports both Chinese and English languages, and is highly flexible and adaptable with no need for refactoring in cross-domain applications.

Features of Youtu-GraphRAG

• Efficient knowledge organization: By constructing a four-layer knowledge tree and disassembling the knowledge into four levels: attributes, relations, keywords, and communities, it realizes autonomous evolution and high-quality extraction of cross-domain knowledge, and improves the readability and accuracy of the knowledge.
• Intelligent Search Mechanism: Adopting intelligent iterative retrieval technology, it breaks down complex questions into multiple sub-questions to retrieve them in parallel, and corrects the results through an iterative reflection mechanism, significantly improving the accuracy and reliability of the answers.
• Cost optimizationThe highest Token cost savings of 90.71% in six authoritative benchmarks, effectively reducing the cost of use.
• Accuracy Improvement: Accuracy improvement of up to 16.62% for complex reasoning tasks, providing a more accurate solution for complex question and answer tasks.
• Multi-language support: Support Chinese and English bilingualism to meet the needs of use in different language environments.
• Highly flexible: It does not need to be reconfigured for cross-domain applications and is highly adaptable and flexible for a wide range of knowledge-intensive scenarios.
• Easy Deployment: Provide detailed deployment tutorials and open source code, developers can get the project code through GitHub, and use Docker to quickly deploy, reduce the threshold of use.

Core Benefits of Youtu-GraphRAG

• Graph-driven knowledge organization: Efficient knowledge management and retrieval is achieved by constructing a multi-layer knowledge graph that decomposes knowledge into layers of attributes, relationships, keywords and communities.
• complex reasoning: It can break down complex problems into multiple sub-problems to retrieve them in parallel, and correct the results through an iterative reflection mechanism to improve the accuracy and efficiency of complex reasoning tasks.
• cost-effectiveness: Outperforms in multiple benchmarks and saves up to 90.71% in Token costs, significantly reducing the cost of ownership.
• high accuracy: Up to 16.62% accuracy improvement for complex reasoning tasks, providing users with more accurate Q&A services.
• Multi-language support: Support Chinese and English bilingualism to meet the needs of use in different language environments.
• Domain Adaptation: Cross-domain applications without refactoring, highly flexible and adaptable for a wide range of knowledge-intensive scenarios.
• Rapid deployment: Provides detailed deployment tutorials and open source code, using Docker can be quickly deployed, reducing the threshold of use.

What is Youtu-GraphRAG's official website?

• Github repository:: https://github.com/TencentCloudADP/youtu-graphrag
• HuggingFace Model Library:: https://huggingface.co/datasets/Youtu-Graph/AnonyRAG
• arXiv Technical Paper:: https://arxiv.org/pdf/2508.19855

Who is Youtu-GraphRAG for?

• research worker: Engaged in research in the areas of natural language processing, knowledge graphs, and complex reasoning, utilizing the framework for academic research and experimentation.
• developers: Want to integrate efficient knowledge retrieval and complex reasoning functionality into projects, rapidly deploy and optimize application performance.
• business user: The need to build an enterprise knowledge base, intelligent customer service system or for document parsing, etc., to improve business efficiency and accuracy.
• data scientist: Process and analyze large amounts of structured or unstructured data, enhancing data analysis and decision support capabilities with the framework.
• technology enthusiast: Interested in the latest AI technologies and want to explore and learn about the application of cutting-edge technologies through hands-on experience.