It took 2 hours and 58 minutes to deploy the ideal AI programming assistant, Claude Code, and configure the local self-hosted model

Deploy Claude Code (by Anthropic) and connect it to a self-hosted large language model (e.g., Qwen, Llama series, etc.), completely bypassing Anthropic's official API, enabling secure offline/intranet development assistance. Table of Contents Preface 🔧 1. Install the Claude Code CLI ⚙️ 2. Global Configuration File Setup 💻 3. VS Code Extension Integration ⚠️ 4. Common Issues and Solutions ✅ 5. Summary and Recommendations Preface Introduction to Claude Code Claude Code is Anthropic’s intelligent programming assistant that supports code understanding, generation, debugging, and refactoring. Through its OpenAI-compatible API interface, Claude Code can seamlessly integrate with any locally hosted LLM service that supports this protocol (e.g., llama.cpp, vLLM, Ollama, etc.)—without relying on Anthropic’s official API. 📖 Official documentation: https://code.claude.com/docs Self-Hosted Large Language Models The previous article, “Outperforming 235B-parameter models: Single-GPU private deployment of OpenClaw,” described how to deploy a local LLM service using llama.cpp. This guide uses that setup as the backend…