#LLM application
80 related articles
Tutorials·3 min
Enterprise RAG Project in Practice: A Complete Guide from Principles to Deployment
Complete guide to enterprise RAG projects covering principles, LangChain implementation, data processing, retrieval optimization, evaluation, and cloud deployment for AI knowledge base applications.
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Tutorials·3 min
Getting Started with AI Agent Development: A Complete Learning Path from Concepts to Practice
A comprehensive guide to AI Agent development for beginners, covering core concepts, market outlook, LangChain framework, RAG knowledge bases, and hands-on projects to systematically master intelligent agent development skills.
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Tutorials·3 min
Alibaba Cloud Bailian Platform Hands-On: Complete Tutorial from API Calls to Multi-Turn Conversations
Complete tutorial on Alibaba Cloud Bailian platform covering API Key setup, Qwen model calls, streaming output, multi-turn conversation principles, and prompt engineering with four roles.
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Tutorials
Firebase AI Logic in Practice: Buildin…
·2 min
Firebase AI Logic in Practice: Building Intelligent Task Decomposition from Scratch with AI Agents
Learn how to add intelligent task decomposition to a cross-platform to-do app using Firebase AI Logic and Gemini, covering structured output, App Check security, and server-side Prompt templates.
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Tutorials·3 min
Complete Guide to Building AI Agent Projects with WindSurf: Practical Tips & Techniques
Complete practical guide to building AI Agent Frameworks with WindSurf, covering technology selection, component generation, code refactoring, debugging, and deployment tips.
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Deep Dives·3 min
Complete Guide to LLM Training: Pre-training, SFT Fine-tuning, and Preference Alignment Explained
Complete guide to the three core LLM training stages: pre-training, supervised fine-tuning (SFT), and preference alignment (DPO/PPO), covering LoRA, distillation, quantization, and pruning.
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Deep Dives·3 min
MCP (Model Context Protocol): Solving the Three Core Pain Points of AI Tool Calling
Deep dive into how MCP (Model Context Protocol) solves three core pain points of Tool Calling: verbose descriptions, unstable invocations, and lack of unified standards.
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Expert Opinions·2 min
Stop Chasing AI Tools: The Right Approach Is Using AI Agents to Solve Real Problems
Learned tons of AI courses but can't apply them? This article reveals the right direction: stop chasing tools, use AI agents to solve real business problems with 10x efficiency gains.
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Tutorials·3 min
Building an AI Agent Mobile App with Zero Code: From Prompt to App Store — A Complete Walkthrough
Learn how to use VibeCodeApp to build a D2C e-commerce AI Agent mobile app with RAG capabilities using natural language prompts — from writing prompts to App Store deployment.
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Tutorials·3 min
Dify Local Deployment Tutorial: Setting Up an AI Development Platform from Scratch with BT Panel + Docker
Step-by-step tutorial on deploying Dify locally using VMware, Ubuntu, BT Panel, and Docker. Covers environment setup, common error fixes, and next steps for building AI apps.
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Tutorials·2 min
Getting Started with Spring AI Alibaba: Best Practices for Java Developers to Integrate LLMs
Deep dive into Spring AI Alibaba's positioning and value, using a JDBC analogy to help Java developers understand how to integrate LLM capabilities into existing microservices architecture.
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Research·4 min
Deep Dive into Claude Code's Open-Source Architecture: The Design Philosophy Behind 510,000 Lines of Code
Deep analysis of Claude Code's open-source architecture: dual-loop design, 7-step tool pipeline, 4-layer token compression, memory systems, and multi-agent collaboration patterns.
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Tutorials·3 min
Hermes Agent Deployment Tutorial: An AI Assistant That Uses Fewer Tokens Than CrawlAI
Complete Hermes Agent deployment tutorial for Windows: environment setup, model configuration, WeChat channel connection, and troubleshooting. Uses fewer tokens than CrawlAI with direct WeChat chat support.
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Tutorials·3 min
Java Developers Transitioning to AI Engineers: New Interview Trends and Learning Roadmap
Deep analysis of interview trends for Java developers transitioning to AI engineers, covering LLM integration, RAG, Spring AI framework practice, with a complete learning roadmap.
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Tutorials·1 min
AI Large Language Model Learning Roadmap: Six Stages from Zero to Engineer
A systematic LLM engineer learning roadmap covering Transformer basics, prompt engineering, RAG, Agent development, API integration, fine-tuning, deployment, and project practice across six stages.
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Tutorials·3 min
Complete Learning Roadmap for Java Developers Transitioning to AI Engineering
A detailed five-phase learning roadmap for Java developers transitioning to AI engineering, covering Spring AI, LangChain4j, RAG core technology, and Agent development.
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Tutorials·3 min
Andrew Ng's Agent AI Course Fully Explained: Why It's Taking the Tech World by Storm
Deep dive into why Andrew Ng's Agent AI course went viral, covering the five-module agent architecture breakdown, course highlights, target audience, and learning tips for developers.
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Deep Dives·3 min
DeepSeek V4 Deep Technical Breakdown: Million-Token Context and Extreme Cost Efficiency
Deep analysis of DeepSeek V4's core architecture: Hybrid Compressed Attention, Manifold-Constrained Hyperconnection, and MUON optimizer—how they cut inference costs by 10x and enable million-token context processing.
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Tutorials·3 min
Getting Started with Spring AI Alibaba: The Go-To Framework for Java Developers Integrating LLMs
A deep dive into Spring AI Alibaba's core positioning and advantages, helping Java developers quickly understand how to integrate LLMs through this framework.
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Tutorials·3 min
Andrew Ng's New Course: A Complete Guide to Building Database Agents
Deep dive into Andrew Ng's Building Your Own Database Agent course with Microsoft, covering LLM-SQL interaction, LangChain Agents, Function Calling, and RAG for tabular data.
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