#AI应用开发
8 related articles
Building Production-Grade Agents from Scratch: A Full Breakdown of LLM Application Development
A full breakdown of LLM application development — covering model selection, prompt engineering, RAG, agent orchestration, and private deployment to help you ship production-grade AI agents.
Building a Real-Time Voice Cooking Assistant with Firebase AI Logic
Learn how to build a real-time voice cooking assistant on Android using Firebase AI Logic, Gemini Live API, and Function Calling — from permissions to Firestore data persistence and App Check security.
Deep DivesLangChain Core Architecture Explained: A Practical Guide to Its Five Key Modules
Deep dive into LangChain's five core modules: Model I/O, Data Connection & Retrieval, Chains, Agents, and Memory. Learn RAG workflows, Agent decision-making, and practical AI app development.
TutorialsGoogle AI Studio Tutorial: A Complete Guide to Building AI Apps with Zero Code
Complete guide to Google AI Studio: interface layout, Gemini model selection, parameter tuning, and building zero-code AI apps with Build. Covers image, video, and music generation with practical examples.
TutorialsGetting Started with Coze: A Complete Guide to Building AI Agents from Scratch
A detailed guide to ByteDance's Coze AI development platform, covering core advantages, domestic vs. international versions, agents vs. apps, and step-by-step instructions for building AI agents from scratch.
Deep DivesThe Five-Dimensional Agent Evaluation Framework: A Complete Guide to the Must-Ask AI Product Manager Interview Question
A complete guide to the five-dimensional AI Agent evaluation framework covering task set design, process and result evaluation, and controlled experiments for AI product managers.
Tech FrontiersInside the SJSU Hackathon Winning Projects: A Practical Guide to Building High-Impact AI Agents
Deep analysis of SJSU hackathon-winning AI Agent projects covering architecture design, core elements, and UX optimization—a practical guide from prototype to product.
TutorialsPractical Guide to Developing an AI Agent-Based Crop Pest and Disease Early Warning System
A detailed guide to developing an AI Agent-based crop pest and disease early warning system, covering image recognition, data visualization, and meteorological monitoring modules.