Cline (VS Code)

AI programming assistant for VS Code integration guide

Cline (formerly Claude Dev) is a powerful AI programming assistant plugin for VS Code that supports multiple AI models. Through APIYI, you can flexibly switch between various mainstream AI models to assist with programming.

Quick Installation

1. Install Plugin

Search for “Cline” in VS Code extension store and install

2. Configure APIYI

1. Click the Cline icon on the left
2. Click settings button (gear icon)
3. Select OpenAI Compatible
4. Configure parameters:
   • Base URL: https://api.apiyi.com/v1
   • API Key: Your APIYI key
   • Model Name: Enter model name

Recommended Models

🎯 Programming Development First Choice

• claude-sonnet-4-20250514 ⭐ (Claude 4 latest, extremely strong programming)
• o4-mini (OpenAI reasoning model, first choice for programming tasks)
• gemini-2.5-pro ⭐ (2M context, strong multimodal)
• deepseek-coder (Code-specialized model, 128K context)

💡 Complex Reasoning Tasks

• o3 ⭐ (Latest reasoning model, significantly reduced pricing)
• claude-sonnet-4-20250514-thinking (Claude 4 chain-of-thought mode)
• deepseek-r1 ⭐ (Latest reasoning model, 64K context)
• grok-3-mini (Lightweight model with reasoning)

🚀 Fast Response

• gpt-3.5-turbo (Classic model, high cost-performance)
• gemini-2.5-flash ⭐ (Fast, low cost, 1M context)
• claude-3-haiku (Lightweight fast version, 200K context)
• gpt-4o-mini (Lightweight fast version, 128K context)

💰 Super Cost-Effective

• deepseek-chat (128K context, strong overall capability)
• qwen-turbo (Alibaba Qwen fast version)
• gpt-4.1-nano (Ultra-low cost version, 128K context)

Core Features

Smart Code Completion

# Input comment, AI auto-generates code
# Calculate the nth Fibonacci number
def fibonacci(n):
    # Cline will auto-complete implementation

Code Explanation

Select code snippet and use:

• Cline: Explain Code: Explain code
• Cline: Explain Error: Explain errors

Code Refactoring

• Performance Optimization: Provide optimization suggestions
• Improve Readability: Refactor complex code
• Fix Issues: Auto-fix common problems

Generate Tests

// Original function
function add(a, b) {
    return a + b;
}

// Test generated by Cline
describe('add function', () => {
    test('should add two numbers correctly', () => {
        expect(add(2, 3)).toBe(5);
        expect(add(-1, 1)).toBe(0);
    });
});

Common Commands

Command	Shortcut	Function
Cline: Ask	Ctrl+Shift+L	Ask AI
Cline: Explain	Ctrl+Shift+E	Explain code
Cline: Refactor	Ctrl+Shift+R	Refactor code
Cline: Generate	Ctrl+Shift+G	Generate code

Advanced Features

Multi-File Operations

Cline can understand and operate on multiple related files:

"Move functions from utils.js to helpers.js and update all references"

Architecture Design

Generate project architecture:

Please design architecture for e-commerce admin system including:
- User management
- Product management
- Order processing
- Data analysis
Using React + Node.js + PostgreSQL

Code Review

Review PR:
- Check code standards
- Find potential bugs
- Performance optimization suggestions
- Security vulnerability scan

Usage Tips

1. Context Management

Provide better context:

// @context: React component for user authentication
// @requirements: Support OAuth2 login flow
// @constraints: Compatible with NextJS 13+

// AI generates more accurate code based on context

2. Custom Prompts

Configure in settings:

{
    "cline.customPrompts": {
        "codeReview": "Review code focusing on performance, security, standards",
        "optimize": "Optimize code performance and readability",
        "document": "Generate detailed Chinese documentation"
    }
}

3. Project-Level Configuration

Create .cline/config.json:

{
    "model": "claude-3-5-sonnet-20241022",
    "temperature": 0.7,
    "language": "zh-CN",
    "codeStyle": {
        "naming": "camelCase",
        "indent": 4,
        "quotes": "single"
    }
}

Troubleshooting

Connection Failed

Check configuration:

• Base URL: https://api.apiyi.com/v1
• API key is valid
• Network connection is normal

Response Timeout

Solutions:

1. Use faster models
2. Reduce request complexity
3. Break down large tasks

Poor Generation Quality

Improvement methods:

1. Provide more context
2. Use more powerful models
3. Specify requirements clearly

gpt-5.6 / gpt-5.5 / gpt-5.4 fails with 400

The error Function tools with reasoning_effort are not supported for ... in /v1/chat/completions (400) is an official OpenAI restriction introduced with the GPT-5.4 series: on /v1/chat/completions, tool calling cannot be combined with reasoning_effort other than none (the default medium counts). Cline’s OpenAI Compatible path is hard-wired to the chat/completions endpoint and does not support /v1/responses yet, so there is no client-side workaround.

What to do:

1. Switch to an unaffected model: gpt-5.1 / gpt-5.2, Claude, Gemini, DeepSeek, etc.
2. Use a client that supports the Responses endpoint — see the full client support table in the OpenAI Responses API Native Guide

Best Practices

1. Model Selection Strategy

Task Type	Recommended Model	Cost Level	Reason
Simple Completion	gpt-3.5-turbo / gemini-2.5-flash	Very Low	Fast, low cost
Code Generation	claude-sonnet-4-20250514 / o4-mini	Medium	Strongest programming
Complex Reasoning	o3 / deepseek-r1	Medium-Low	Strong reasoning, o3 price reduced
Architecture Design	deepseek-r1 + claude-4-sonnet	Low	Plan first, implement later, save cost
Code Review	gemini-2.5-pro / claude-4-sonnet	Medium	Long context, strong understanding
Batch Refactoring	deepseek-chat / qwen-turbo	Very Low	Fast and economical
Documentation	gpt-4.1 / qwen-max	Medium-Low	Natural expression
Long Text Processing	gemini-2.5-pro (2M)	Medium	Ultra-long context

2. Prompt Optimization

❌ Bad prompt: Fix this function

✅ Good prompt: Fix floating point precision issue in calculateTotal function,
ensure amount calculation accurate to 2 decimal places

3. Progressive Development

1. Generate basic framework first
2. Gradually add features
3. Finally optimize performance
4. Add error handling

4. Security Awareness

• Don’t include sensitive information in code
• Review AI-generated code
• Verify third-party dependencies
• Watch for security vulnerabilities

Integration Workflow

Git Integration

# Auto-generate commit message
git add .
# Cline: Generate commit message based on changes

Test-Driven Development

1. Write test cases first
2. Cline generates implementation code
3. Run tests to verify
4. Iterate and optimize

CI/CD Integration

Generate configuration files:

# Cline can generate GitHub Actions config
name: CI
on: [push, pull_request]
jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - name: Run tests
        run: npm test

Token Optimization & Cost Control

1. Monitor Token Usage

• Real-time Monitoring: Check estimated cost in Cline sidebar
• Session Limits: Keep sessions short, avoid context accumulation
• Regular Reset: Complete long tasks in multiple sessions

2. Smart Model Switching

Planning Phase → DeepSeek-R1 or o3 (strong reasoning, low cost)
Implementation Phase → Claude-4-Sonnet or o4-mini (strongest programming)
Simple Tasks → GPT-3.5-Turbo or Gemini-2.5-Flash (fast)
Long Text → Gemini-2.5-Pro (2M context)

3. Using .clinerules Configuration

Create .clinerules file in project root:

# Limit Cline operation scope
- Don't allow modifying node_modules
- Don't allow deleting important files
- Limit number of files modified at once
- Require confirmation for destructive operations

4. Alternative Solutions to Reduce Cost

GitHub Copilot Pro Integration

• Monthly fee only $10, unlimited use
• Use through VSCode LM API
• Suitable for high-frequency scenarios

Local Models (Ollama)

# Install Ollama and run local models
ollama run deepseek-coder:6.7b
ollama run qwen2.5-coder:7b
ollama run codellama:13b

Use Domestic Models to Reduce Cost

• qwen-turbo (Alibaba Qwen)
• glm-4 (Zhipu Tsinghua)
• ernie-4.0 (Baidu Wenxin)

5. Cache Optimization

• Use services like Requesty Router
• Can save over 50% API cost
• Auto-cache repeated requests

Advanced Best Practices

1. Plan/Act Mode Usage

• Plan Mode: For design and review, read-only
• Act Mode: Direct implementation, suitable for simple tasks
• Model Memory: Cline remembers model preference for each mode

2. Context Management Skills

// Explicit context comments
// @context: React 18 + TypeScript 5
// @requirements: Support SSR, compatible with Next.js 14
// @constraints: Don't use external state management library
// @performance: First screen load < 3s

3. Task Management System

• Bookmark Important Conversations: Use star feature
• Export Valuable Content: Save as Markdown
• Task Sorting: Sort by cost, Token usage
• Batch Cleanup: Regularly clean low-value sessions

4. Avoid Token Explosion

❌ Wrong Approach:
- Handle multiple unrelated tasks in same session
- Let Cline read entire large codebase
- Constantly changing requirements causing context confusion

✅ Correct Approach:
- Start new session for each feature
- Only include relevant files
- Start after clarifying requirements
- Commit code immediately after completion

5. Cost-Benefit Analysis

Scenario	Traditional Dev Time	Cline Cost	Time Saved	ROI
CRUD Module	4 hours	$5-10	3.5 hours	Very High
Complex Refactoring	2 days	$20-50	1.5 days	High
Architecture Design	1 week	$50-100	5 days	High

6. Workflow Optimization

# 1. Planning Phase (use reasoning models)
"Use o3 or DeepSeek-R1 to analyze requirements and develop architecture"

# 2. Implementation Phase (use programming-specialized models)
"Switch to Claude-4-Sonnet or o4-mini to implement core features"

# 3. Testing Optimization (use fast models)
"Use Gemini-2.5-Flash or GPT-3.5-Turbo for unit testing and optimization"

# 4. Documentation Phase (use comprehensive models)
"Use GPT-4.1 or Qwen-Max to generate project documentation"

# 5. Code Review (use long-context models)
"Use Gemini-2.5-Pro for comprehensive code review"

Performance Optimization

1. Model Switching

Choose model based on task:

• Development phase: Lightweight models
• Complex tasks: Advanced models
• Production: Balance performance and cost

2. Caching Strategy

• Enable response caching
• Cache common code snippets
• Regularly clean cache

3. Request Optimization

• Batch related requests
• Use streaming responses
• Set reasonable timeouts

Need more help? Please check the Detailed Integration Documentation.