yuxinyou125的博客

原创 A2A 和 MCP：Oauth2 认证与授权

https://stytch.com/blog/mcp-authentication-and-authorization-servers/There are two primary ways to implement the authorization server within the MCP architecture:

原创 AI Engineering: AI 工程路线图

原创 Redis 应用案例： 在LLM中的应用

The most common use case is caching the responses for common inputs. Caching allows the application to store responses for frequently asked questions or common queries so that the application can bring the response to the customer.Rate limiting is a techni

原创 Applied LLMs Mastery 2024：应用LLM路线图

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原创 Lesson 1: The Evolution of UX to AX (AI Agent Experience) 智能体体验

For decades, User Experience (UX) has been at the center of digital design, ensuring that human users can seamlessly interact with applications, websites, and software. However, as AI agents—such as virtual assistants, recommendation engines, and automated

原创 Lesson 2: Understanding AI Agents as Users

参考引用：AI agents fall into , each with . Siri, Google Assistant, Alexa, ChatGPT-powered assistants. Understanding natural language queries and retrieving relevant information. Voice or text-based interactions with API-backed data sources.✅✅✅✅。

原创 Lesson 3: The AI Agent Journey：智能体旅程

智能体体验地图✅ .✅ .

原创 客户旅程映射图：战略工具

建议采用模块化与可组合的软件架构构建此类智能体。：AI智能体可分为六种类型，包括反射型、目标导向型、学习型、效用导向型、分层型及协作型智能体，每种类型均针对特定场景与应用场景设计。数字化领导者应深入理解AI智能体的商业潜力，同时系统性地评估其潜在应用场景、风险矩阵及应对策略，以确保技术的成功实施。：多个智能体协同作业，能够解决单一智能体难以处理的复杂任务，提供更具适应性、可扩展性及稳健性的解决方案。：AI智能体依托优化算法、自然语言处理（NLP）及知识表示等AI技术，实现对环境的感知、导航与动态适应。

原创 Agentic AI

creating。

原创 Grafana Stack: 运营数据和分析数据

Grafana is an open-source observability platform that brings together logs, traces, and metrics into dashboards. Grafana is the front end to several tools we will be using:Spring Boot 3 Observability

原创 docker ollama 导入模型文件

注意：.ollama 文件夹是存放模型文件，来自与docker ollam:/root/.ollama 目录下。

原创 LLM：过滤掉COT思考过程