How to Configure a Proxy for AI Coding Assistants and Domestic LLMs: A Practical Guide for Developers

Disclaimer: This article uses generic procedures as examples. Always refer to the official documentation for specific tool versions and APIs. Proxy usage must comply with local laws, regulations, and service terms. API calls require attention to cross-border data compliance and account security risks.

1. Why a Proxy Is Needed and What This Article Covers

AI coding assistants built on large language models (LLMs) often expose their capabilities through command-line interfaces (CLIs), enabling code generation, refactoring, and bug localization. However, many of these tools’ service endpoints are hosted overseas, and direct connections from certain regions may be restricted. More critically, mainstream CLI tools such as Claude Code do not natively support domestic LLM APIs, so you cannot simply switch models with a dropdown.

This article provides an end-to-end workflow—local environment + system proxy + domestic model adaptation—that lets you use AI coding assistants reliably without changing your development habits. It covers proxy selection, model bridging, and security/compliance guidance from start to finish.

2. Setting Up the Node.js Runtime

Most AI coding assistant CLIs are built with JavaScript or TypeScript and require a Node.js runtime (version 18 LTS or newer is recommended).

2.1 Installation and Verification

Download the LTS installer from the Node.js official website and follow the default options. Verify the installation in a terminal:

node -v
npm -v

Both commands should return version numbers without errors.

2.2 Version Management by Platform

If you need to maintain multiple Node.js versions, a version manager is recommended:

• macOS/Linux: Use nvm (Node Version Manager)

  curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.7/install.sh | bash
  nvm install lts
  nvm install 20.12.2
  nvm use 20.12.2
  nvm alias default 20.12.2

• Windows: Use nvm-windows. The lts alias is not available; specify a concrete version such as nvm install 20.12.2. You can also use Corepack, which ships with Node.js.

Version managers isolate project dependencies and allow fast rollbacks—especially valuable in enterprise environments.

3. Installing AI Coding Assistant CLI Tools and Alternatives

Take Claude Code as an example. Its npm package is @anthropic-ai/claude-code, but the package is hosted on an overseas registry that may be unreachable via direct connection.

3.1 Switching the npm Registry

npm config set registry https://registry.npmmirror.com
npm install -g @anthropic-ai/claude-code

If the package is not available on the mirror, enable your proxy and retry. Global installation (-g) may require elevated privileges; you can use a user-level install or install through the nvm-managed Node environment instead.

3.2 Alternatives That Support Domestic LLMs

Since tools like Claude Code do not natively support domestic model endpoints, consider these options:

• Aider: An open-source CLI coding assistant that supports domestic model endpoints via OpenAI-compatible interfaces.
• Continue.dev: A VS Code extension that lets you configure domestic LLM API endpoints directly in its settings.
• CodeGeeX: A coding assistant by Zhipu AI that natively supports domestic models and works out of the box.

When choosing a tool, verify whether it supports the OpenAI-compatible protocol or custom API endpoint configuration.

4. Deploying a Proxy Tool (Clash Example)

Ensure proxy usage complies with local laws, regulations, and service terms. Be aware of cross-border data compliance and account security risks.

A proxy tool intercepts and forwards traffic at the system network level—it does not directly modify how a CLI tool calls its model. This section uses the open-source tool Clash (and its fork mihomo) as an example.

4.1 Download and Installation

Clash is available for Windows, macOS, and Linux. Download the appropriate client from the project’s GitHub releases page and follow the setup wizard.

4.2 Core Functions and CLI Proxy Configuration

After launching Clash, the interface shows subscription management, proxy mode selection, a system proxy toggle, and connection status. Clash acts as a local gateway and does not automatically alter CLI code. To route CLI traffic through the proxy, configure it separately:

• Method 1: Set environment variables in your terminal

  # Linux/macOS
  export HTTP_PROXY="http://127.0.0.1:7890"
  export HTTPS_PROXY="http://127.0.0.1:7890"
  # Windows PowerShell
  $env:HTTP_PROXY="http://127.0.0.1:7890"
  $env:HTTPS_PROXY="http://127.0.0.1:7890"

• Method 2: Specify a proxy endpoint in the CLI tool’s own settings (e.g., the Proxy configuration item in Continue.dev).

5. Obtaining API Keys for Domestic LLMs

Taking mainstream platforms such as Tongyi Qianwen (Qwen), Zhipu GLM, and DeepSeek as examples:

1. Visit the official website, register, and sign in.
2. Navigate to the API platform or developer console.
3. Create a new key in “API Key Management” with a descriptive name (e.g., coding-assistant).
4. Copy and save the key immediately—most platforms display it only once.

Billing models vary: Qwen uses tiered token pricing, Zhipu offers a free tier, and DeepSeek charges per call volume. Start with a small top-up to validate, and monitor usage regularly.

Note: API calls may involve cross-border data transfer. Confirm compliance with applicable data protection regulations such as the Data Security Law.

6. Bridging to Domestic LLMs via a Compatibility Layer

Because overseas CLIs like Claude Code cannot switch to domestic models directly, you need either an OpenAI-compatible relay service or a tool that supports domestic endpoints natively.

6.1 Using OpenAI-Compatible Endpoints

Some domestic platforms expose APIs that follow the OpenAI format. With Aider, for example:

1. Configure the model endpoint and key in the Aider settings:

   aider --model openai/deepseek-chat --api-key <YOUR_API_KEY> --api-base https://api.deepseek.com/v1

2. Pass the key via environment variables rather than hard-coding it.

6.2 Using Tools That Accept Domestic Endpoints Directly

Tools like Continue.dev let you enter a domestic model’s API address in the settings UI. The core steps:

1. Locate the “API Provider” or custom endpoint option in the tool’s settings.
2. Enter the domestic platform’s API URL and key.
3. Test the connection, then save.

7. Best Practices

7.1 Environment Isolation

Create a dedicated project directory for each coding assistant project and maintain separate configuration files per project.

7.2 Secret Key Security

Never hard-code API keys or commit them to version control. Use environment variables or a .env file:

# Linux/macOS
export MODEL_API_KEY="<YOUR_API_KEY>"
# Windows PowerShell
$env:MODEL_API_KEY="<YOUR_API_KEY>"

Add .env to .gitignore. Never paste real keys into online tools or public repositories. Placeholders above are for demonstration only—always replace them with real keys and store them securely.

7.3 Network Stability and Troubleshooting

Monitor your proxy provider’s SLA and status page. Common errors:

Error Code	Meaning	Suggested Fix
401	Invalid or expired key	Regenerate the API key and update config
403	Insufficient permissions	Check account balance and API call permissions
429	Rate limit exceeded	Reduce call frequency or top up to raise the quota
502	Proxy node failure	Switch to a backup node or check proxy service status
Timeout	No network connectivity	Enable debug logs to locate the failure point

7.4 Cost Control

LLMs charge per token, and coding assistant sessions can consume hundreds to thousands of tokens per interaction. Set call-frequency limits and review usage regularly to avoid unnecessary expenses.

7.5 Debug Logging

Enable debug mode on your proxy tool to inspect request and response details. This helps you quickly determine whether an issue lies at the network, authentication, or model service layer.

8. Summary and FAQ

This article covered the full path of local environment + system proxy + domestic model adaptation, including Node.js setup, CLI installation, Clash deployment, model bridging, and security/compliance.

Frequently Asked Questions

• Can Claude Code use domestic LLMs directly? No. You need a tool that supports OpenAI-compatible interfaces (like Aider) or a tool with built-in domestic endpoint support (like Continue.dev).
• What if the proxy connection fails? Verify that Clash’s system proxy is enabled and the node is reachable. Try switching nodes or restarting the service, and confirm that the CLI has HTTP_PROXY / HTTPS_PROXY environment variables set.
• Do domestic LLMs differ from overseas models in capability? Yes. Domestic models have made rapid progress in code generation, but they may lag slightly in complex reasoning tasks. Choose based on the nature of your work.
• How do I pick a proxy tool? Clash/mihomo are open-source, free, and rule-flexible. Commercial options like v2rayN offer a more graphical experience. Choose based on your platform and needs.
• What are the approximate token costs? A single coding assistant interaction typically uses hundreds to thousands of tokens. Depending on the domestic platform’s tiered pricing, monthly costs can range from tens to hundreds of currency units—set a budget cap to stay in control.

By adapting these steps to your own tech stack and model preference, you can achieve efficient and stable local AI-powered coding assistance.