#GPU selection guide
146 related articles
·5 min
The Complete Guide to OpenCode: Installation, Configuration, and Advanced Usage
A comprehensive guide to OpenCode, the open-source AI coding tool — covering installation (desktop/WSL), model config, rules files, custom commands, MCP extensions, and Agent SQL capabilities.
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·7 min
Complete Guide to OpenCode: Installation, Configuration, and Custom Commands in Practice
A systematic guide to OpenCode, the open-source terminal AI coding tool: installation methods (including WSL), model configuration, rules files, Agent types, custom commands, and MCP tool extensions.
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·4 min
Dify Beginner's Guide: Interface Overview & Complete Docker Self-Hosted Deployment Guide
Complete guide to Dify's four core modules (Explore, Studio, Knowledge Base, Tools) with step-by-step Docker self-hosted deployment instructions for building production-grade AI apps.
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·4 min
OpenAI Agents SDK in Practice: Harness and Sandbox Separation Architecture Explained
Deep dive into OpenAI Agents SDK updates covering Harness-Compute separation, Codex-style orchestration, sandbox snapshots, skills system, and multi-agent collaboration with practical demos.
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·4 min
LangGraph.js Practical Guide: A Frontend Engineer's Path to AI Agent Development
A practical LangGraph.js guide for frontend engineers covering LangGraph vs LangChain comparison, workflow vs general-purpose agent types, and layered Agent architecture design.
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·3 min
Ideogram 4 Fully Automated Workflow: Run Locally with Just 8GB VRAM, No Complex Prompts Needed
Ideogram 4 automated ComfyUI workflow using Qwen2.5 VL-8B: run locally with 8GB VRAM, auto-generate structured JSON prompts from simple descriptions, with image reverse-engineering support.
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·3 min
Vibe Coding Practical Guide: Tool Selection, Development Workflow, and Lessons Learned
In-depth analysis of Vibe Coding methodology covering Claude Code, Cursor, and Codex tool strategies, full development workflow tips, and four key principles for avoiding pitfalls in complex systems.
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·4 min
From Vibe Coding to Enterprise-Grade AI Programming: A Complete Progression Path with Practical Analysis
Deep analysis of Vibe Coding's limitations, comparison of Claude Code vs Codex, and a three-layer AI engineering methodology for progressing from casual AI coding to enterprise-grade development.
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·3 min
NVIDIA XR AI Platform Explained: Full-Stack AI Agent Development for AR Glasses
Deep dive into how NVIDIA's XR AI platform enables AI Agent development for AR glasses through cloud-edge architecture, covering visual perception, voice interaction, and multimodal reasoning.
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·3 min
748-Episode AI Large Language Model Development Tutorial: Seven Core Modules from Zero to Project Deployment
Analysis of a 748-episode, 198-hour AI LLM development tutorial covering API integration, prompt engineering, RAG, AI Agents, fine-tuning, multimodal development, and deployment.
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·3 min
The Complete Skill Map for AI Application Engineers: A Progressive Roadmap from Fundamentals to Production
A systematic breakdown of the complete skill structure for AI application engineers, covering Python & deep learning fundamentals, small model engineering, LLM fine-tuning, Agent development, and enterprise projects.
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·3 min
Full Walkthrough: Recreating Apple's AI Photo Reconstruction Feature with TRAE Work
A Bilibili creator uses TRAE Work AI Agent to recreate Apple's photo spatial reconstruction feature, covering research, cloud development, and multi-device collaboration.
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·2 min
AI Coding Terminal Tools Compared: cmux vs Ghostty+tmux vs iTerm2
In-depth comparison of cmux, Ghostty+tmux, iTerm2, and Mac Terminal for AI coding. Discover why cmux's zero-config setup, sidebar management, and smart alerts make it the best terminal for heavy AI programming users.
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·4 min
Codewell Hands-On Review: Is This Terminal AI Coding Assistant with Nearly 40K GitHub Stars Actually Worth It?
Hands-on review of Codewell (formerly DeepSeek2E), the open-source terminal AI coding assistant with nearly 40K GitHub stars. Supports 25 LLM providers, local models at zero cost, and MIT license.
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·3 min
PyTorch Image Classification in Practice: Complete Pipeline from Data Preprocessing to Model Training
A PyTorch flower classification project covering the full image classification pipeline: data preprocessing, transforms augmentation, ResNet pretrained models, and Resize strategies with reusable template code.
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·4 min
AI + Java Backend Learning Roadmap: Four Stages from CRUD to Senior AI Engineer
A complete AI + Java backend learning roadmap based on Spring AI Alibaba: from prompt engineering and LLM API integration to RAG knowledge bases and Agent systems across four stages.
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·3 min
AI Large Model Learning Roadmap Breakdown: Three Stages from Application Development to Model Fine-Tuning
Deep breakdown of a popular AI large model learning roadmap covering LangChain, RAG, Agent, and LoRA fine-tuning across three stages, with analysis of its strengths and limitations for career changers.
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·3 min
Claude Code with Local LLMs: Token-Free Deployment Guide & Configuration
Learn how to connect Claude Code to local LLMs for token-free AI coding. Covers three-layer architecture, Ollama/LM Studio/vLLM setup, protocol translation, and hardware selection.
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·3 min
LFM2.5 Local Deployment Hands-On: An 8B Parameter Model That Outperforms GPT-o3s in Tool Calling
Hands-on test of Liquid AI's LFM2.5 local deployment: architecture breakdown, 16GB VRAM troubleshooting, and GraphRAG tool-calling benchmarks vs GPT-o3s.
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·4 min
Complete AI Large Language Model Learning Roadmap: From Beginner to Production-Ready
A systematic guide to learning AI large language models, covering Transformer architecture, prompt engineering, RAG, AI Agents, fine-tuning, and enterprise projects from beginner to production-ready.
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