Explore innovative applications based on Redis in Golang. This article details how to build a document vector indexing and retrieval system (RAG). In-depth analysis of the RAG technical framework, covering key aspects such as system architecture and project operation. The project has been open sourced to provide valuable reference for developers. Come and click to read and learn more about RAG...

In the AI ​​era, large model knowledge bases face database query problems, such as incorrect results and instability. Introducing knowledge graphs has become a new idea, which is like a bridge between natural language and databases. It can define entities and relationships, standardize terms, optimize query paths, and integrate across databases. Want to learn more about what knowledge graphs...

Explore efficient interaction methods for large AI models. This article explains the RACEF prompt word framework in detail. It is a structured tool to improve AI interaction effects. It consists of five key parts, such as restatement and supplementation, and is applicable to a variety of complex tasks. Learn about its application scenarios, compatible models, and advantages and disadvantages....

In-depth analysis of the differences between n8n and Dify in the fields of workflow automation and AI applications! Two open source star tools, n8n focuses on general workflow automation, and Dify focuses on AI-driven development. Compare their core functions, applicable scenarios, etc. in detail. Learn about the application of open source big models in them and interpret what open source big...

In-depth analysis of the status of big model technology in 2025, focusing on technical principles from RAG to CoT. Discuss AI Agent implementation problems, such as data vectorization information loss faced by RAG retrieval enhancement generation technology. Detailed explanation of big model architecture and core components, revealing the secrets behind big model technology. Click to read and...

Explore the NVIDIA team's agent-based AI technology practices, focusing on analyzing its innovations in the field of large models. The article explains RAG technology in depth and reveals the principles and architecture of large model technology. For example, how AI sales assistants optimize workflows, how code review optimization copes with challenges, etc. It presents you with cutting-edge...

Explore new breakthroughs in integrating images into knowledge bases! RAG technology continues to innovate, and traditional methods face bottlenecks when processing multimodal data. Cohere Embed v4 brings a solution with advantages such as multimodal support and long context processing. Learn about the principles of RAG technology and see how it works with Gemini Flash 2.5 to achieve...

OpenAI's large language model enhanced fine-tuning is now available! With just a few dozen samples, the model can be upgraded from an average level to an expert level. Whether it is converting instructions into code or extracting the essence of messy text, excellent results can be achieved through model fine-tuning technology. RFT is now open to verified organizations. Want to learn more?...

Explore the truth behind AI Agent and analyze its current status in the field of large language models. Sun Xin, vice president of Gartner, discusses in depth that domestic AI Agent is at its peak but faces many constraints, and companies should explore it with caution. Detailed explanation of the current status and principles of large model technology to help you gain insight into industry...

In-depth analysis of building a responsible large language model solution, covering mitigation measures at the data, model, and security system levels. In particular, the application of RAG technology is introduced, and the principle of RAG technology is explained in detail. It reveals how to reduce potential hazards and improve model security. Click to read for more details!