Resources and tutorials for programmers' advanced learning journey. Advanced tracks in Java, Python, and C#. Blog: https://blog.csdn.net/badao_liumang_qizhi
This article walks through constructing a lightweight YAML‑based DSL workflow engine on Spring AI 1.1.2 and Ollama, showing how to define state graphs, register tools, parse and execute nodes—including conditional edges, while loops, and parallel branches—without external orchestration tools.
This tutorial demonstrates how to integrate Spring AI with Ollama, define @Tool‑annotated weather and translation utilities, register them for automatic chaining, and let a large language model answer queries like “fetch Beijing weather and reply in English” using a concise end‑to‑end example.
This article explains the limitations of large language models, introduces Retrieval‑Augmented Generation (RAG) and its four‑step workflow, details Spring AI's RAG components and vector‑store options, and provides complete, runnable Java code—including Maven, configuration, and service classes—to build a local knowledge‑base Q&A system.
This article explains how to replace Spring AI's default in‑memory ChatMemory with a JDBC‑backed implementation that stores conversation history in a MySQL table, covering component changes, schema design, auto‑configuration, and best‑practice configuration details.
This guide explains how Spring AI abstracts LLM conversation memory using a three‑layer architecture, demonstrates configuring MessageWindowChatMemory with a sliding‑window strategy, shows two ways to register the memory advisor, and provides complete Maven, YAML, and Java code examples with test screenshots.
This article walks through using Spring AI with Ollama to enforce JSON‑schema‑based structured output for agents, showing why structured responses matter, how Spring AI generates schemas from Java beans, and providing complete runnable code for both basic and advanced tool‑calling scenarios.
This guide walks through integrating Ollama’s local LLM with Spring AI, explaining Prompt and PromptTemplate concepts, configuring application.yml, implementing a PromptService, adding controller endpoints, using external template files, and testing the setup with curl commands.
This article walks through setting up Spring AI with Ollama, explains the tool‑calling workflow, shows two ways to define tools, provides full Maven and YAML configurations, presents runnable Java code for services, chat client, and controller, and addresses common compatibility and dependency issues.
This guide walks through replacing DashScope with a local Ollama model in a Spring AI project, showing how to configure multiple MCP servers, adjust Maven and YAML settings, run zero‑code changes, and troubleshoot common issues.
This article introduces MongoDB fundamentals, walks through Windows installation, shows how to integrate Spring Boot with MongoDB via Maven, configures connection settings, demonstrates both MongoRepository and MongoTemplate usage with full code examples, and compares MongoDB to Redis for typical use cases.
