VSCode + ZooCode + Chinese AI Models: Complete Setup Guide

cover_image: https://aiwave.live/images/cover_04_developer_guide.png

title: VSCode + ZooCode + Chinese AI Models: Complete Setup Guide

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tags: ai, aiwave, vscode, chinese-ai, developer-tools

VSCode + ZooCode + Chinese AI Models: Complete Setup Guide

Published: 2026-07-07 | Category: Developer Tools | Reading Time: 8 min

If you're a developer looking to integrate Chinese AI models into your VSCode workflow, ZooCode is the bridge you need. It's a VSCode extension that turns any OpenAI-compatible API endpoint into a full-featured coding assistant — chat, inline completions, and code generation — right inside your editor.

This guide walks you through connecting ZooCode to AIWave, an OpenAI-compatible API gateway that provides access to 60+ Chinese AI models through a single endpoint. No multiple accounts, no separate SDK installations.

Why ZooCode?

You might wonder why not just use GitHub Copilot or Cursor's built-in AI. Fair question. ZooCode's advantage is model flexibility. Copilot locks you into OpenAI's models. Cursor uses Claude by default. ZooCode lets you pick any model from any vendor — and switch between them per-task.

This matters because:

ZooCode decouples your editor from your model vendor. You get the best tool for each job.

Why Chinese AI Models for Coding?

Before diving into setup, let's address why you'd use Chinese models over the usual suspects:

The trade-off? Some models have slightly weaker English prose quality. For pure code generation, that's rarely an issue.

Prerequisites

Step 1: Get Your AIWave API Key

This Base URL is critical. ZooCode needs it to route requests through AIWave's OpenAI-compatible proxy.

Step 2: Configure ZooCode in VSCode

Open VSCode and launch ZooCode:

Enter the following values:

API Provider: OpenAI Compatible
Base URL: https://aiwave.live/v1?utm_source=dev.to&utm_medium=organic&utm_campaign=SEO_ARTICLES
API Key: [paste your AIWave API key]

Alternatively, if ZooCode supports JSON configuration, edit your settings file directly:

{
  "zoocode.provider": "openai-compatible",
  "zoocode.baseURL": "https://aiwave.live/v1?utm_source=dev.to&utm_medium=organic&utm_campaign=SEO_ARTICLES",
  "zoocode.apiKey": "sk-your-aiwave-key-here",
  "zoocode.defaultModel": "deepseek-v4-flash",
  "zoocode.codeModel": "qwen3-coder-480b-a35b-instruct",
  "zoocode.maxTokens": 8192,
  "zoocode.temperature": 0.3,
  "zoocode.enableInlineCompletions": true,
  "zoocode.enableChat": true
}

Step 3: Model Selection Strategy

Not all models are equal for all tasks. Here's the setup that works best:

Default Model: DeepSeek V4 Flash

Code Model: Qwen3 Coder 480B

Free Fallback: GLM-4.7 Flash

Step 4: ZooCode UI Walkthrough

Once configured, here's how to use ZooCode day-to-day:

Chat Panel

Inline Completions

ZooCode offers ghost-text suggestions as you type. To configure:

The suggestions appear in greyed-out text. Press Tab to accept, Esc to dismiss.

File Context

ZooCode lets you attach files to your chat:

Step 5: Testing Your Setup

Create a test file to verify everything works:

# test_zoocode.py
def fibonacci(n):
    """Return the nth Fibonacci number."""
    if n <= 1:
        return n
    return fibonacci(n - 1) + fibonacci(n - 2)

Open the ZooCode chat and ask:

"Optimize this fibonacci function for performance. The naive recursive approach is O(2^n)."

Expected response should include memoization or dynamic programming:

from functools import lru_cache

@lru_cache(maxsize=None)
def fibonacci(n):
    """Return the nth Fibonacci number. Memoized O(n)."""
    if n <= 1:
        return n
    return fibonacci(n - 1) + fibonacci(n - 2)

Or an iterative version:

def fibonacci(n):
    """Return the nth Fibonacci number. Iterative O(n)."""
    if n <= 1:
        return n
    a, b = 0, 1
    for _ in range(2, n + 1):
        a, b = b, a + b
    return b

If you get a coherent, correct response, your setup is working.

Cost Comparison: How Much Will You Actually Spend?

Let's estimate a typical workday:

| Task | Tokens (avg) | Model | Cost per task |

|------|-------------|-------|---------------|

| Chat question | 2K in / 1K out | DeepSeek V4 Flash | ~$0.0001 |

| Code generation | 5K in / 2K out | Qwen3 Coder | ~$0.0002 |

| Code review | 10K in / 3K out | DeepSeek V4 Flash | ~$0.0003 |

| Documentation | 8K in / 4K out | DeepSeek V4 Flash | ~$0.0003 |

Daily total (50 interactions): ~$0.015 — roughly $0.45/month for a full-time developer. Compare that to GitHub Copilot at $10/month or Claude Pro at $20/month.

Troubleshooting

"API key not recognized": Double-check you're using your AIWave key, not a key from another provider. The Base URL must be exactly https://aiwave.live/v1.?utm_source=dev.to&utm_medium=organic&utm_campaign=SEO_ARTICLES

"Model not found": The model ID must match AIWave's catalog exactly. Use deepseek-v4-flash, not deepseek-v4-flash-2025-06-01 or other variant names.

Slow responses: Chinese models are served from Singapore. If you're in Europe or the Americas, expect 200-500ms added latency. For latency-sensitive work, consider using the free GLM-4.7 Flash ($0.00/1M) for quick tasks.

Next Steps

Chinese AI models have closed the quality gap while maintaining dramatic price advantages. There's never been a better time to integrate them into your daily workflow.

We're a small team behind AIWave. No VC money, no big marketing budget — just a few people who believe Chinese AI models should be accessible to everyone in the world. Your API calls keep this project alive. If you find value in what we're building, stick around. It means more than you know.