Understanding Agent Orchestration with OpenAI in 300 Lines of Code

Understanding Agent Orchestration with OpenAI in 300 Lines of Code

When using large language models, achieving stable performance usually only requires a good prompt and the right tools. However, dealing with many unique processes can become tricky. To address this, OpenAI published a blog post on their official website titled “Orchestrating Agents: Routines and Handoffs”, which introduces the concepts of Routines and Handoffs. The code … Read more

Understanding MCP and Its Integration with auto-coder.chat

Understanding MCP and Its Integration with auto-coder.chat

What is MCP What is MCP (Model Context Protocol)? There are many complex explanations online, so I will try to clarify it here. To understand a process or technology, we first look at the problems it aims to solve and its evolution. To enable models to not only output text (including images, audio, and video) … Read more

MCP vs Function Calling: More Than Just Simple Function Calls

MCP vs Function Calling: More Than Just Simple Function Calls

In the field of Artificial Intelligence (AI), large language models (LLMs) are developing at a revolutionary speed, excelling in tasks such as writing, coding, and Q&A. However, to truly integrate these AI models into our daily lives and workflows, they need to interact effectively with the outside world. Function Calling and MCP (Model Context Protocol) … Read more

Reject Module in Large Model RAG

Reject Module in Large Model RAG

To effectively implement <span>RAG</span>, there are indeed many aspects that need refinement, and today we will learn about the Reject Module. Official Explanation In the RAG (Retrieval-Augmented Generation) model, the Reject Module is an important component designed to enhance the robustness of the generation model when facing irrelevant queries or information. Plain Explanation A simple … Read more