Focused on software development, sharing source code and tutorials for various systems.
This guide walks through integrating Spring AI 2.0 into a Spring Boot application, covering Maven dependency setup, model configuration, ChatClient usage for synchronous and streaming calls, Redis‑backed chat memory for multi‑turn conversations, and testing with Postman and a UI component.
This article walks through Tencent's open‑source TDesign library, covering its cross‑framework component suite, starter‑kit CLI initialization, AI‑friendly MCP server, and step‑by‑step creation of an AI chat page with practical code snippets and screenshots.
This article explains how to implement an online user counting feature by using Redis sorted sets, covering user identification (token or browser fingerprint), adding users with ZADD, querying current online users with ZRANGEBYSCORE, and cleaning up expired entries via ZREMRANGEBYSCORE and ZREM.
This article walks through switching a SpringBoot + MybatisPlus project from MySQL to PostgreSQL, covering driver addition, JDBC URL changes, schema differences, and a detailed list of SQL syntax mismatches and runtime errors with concrete code examples and remediation scripts.
PaddleOCR, the Baidu‑backed open‑source OCR library, now at version 3.7 with the PP‑OCRv6 model, delivers industry‑leading accuracy, 110+ language support, lightweight deployment options and easy Java integration, making it the go‑to solution for document digitization, invoice processing and multilingual text extraction.
The article compares polling, WebSocket, and Server‑Sent Events for server‑to‑client real‑time messaging, explains the advantages and drawbacks of each, and provides a complete Node.js/Express and plain‑HTML demo showing how to implement SSE as a lightweight alternative to WebSocket.
This article details the design and implementation of a locally deployed AI system that automatically extracts, structures, and manages exam questions from scanned papers, supporting multiple subjects, reducing manual effort, and enabling flexible test generation for teachers.
This article walks through the inner workings of Claude Code, explains why it behaves unpredictably out of the box, and provides a step‑by‑step guide—including CLAUDE.md configuration, three operating modes, Hooks, Skills, Agents, and cost‑saving techniques—to transform the tool into a reliable, project‑aware AI coding assistant.
The article explains the AI‑Agent “Loop” concept that has gone viral, contrasting it with traditional programming loops, detailing the ReAct paradigm, single‑agent vs. multi‑agent loops, the four engineering layers of Prompt, Context, Loop and Harness, and discussing Loop engineering’s building blocks, benefits, limitations, and practical use cases.
In two months and a budget of 75,000 CNY, I built a secure on‑premise AI knowledge‑base for a research institute using SpringBoot, Python, DeepSeek‑v4, RAGFlow, and a custom GPU‑rich server, and documented every step from hardware selection to Docker deployment.
