AI Assistant

The AI Assistant is the heart of Trae IDE, providing intelligent coding support through multiple interaction modes. It's designed to understand your code context and provide relevant, helpful assistance throughout your development workflow.

Overview

Trae's AI Assistant offers three main interaction modes:

• Side Chat: Persistent AI conversation panel
• Inline Chat: Context-aware assistance within your code
• Auto-completion: Real-time code suggestions

Side Chat

The Side Chat feature provides a dedicated panel for ongoing conversations with the AI assistant.

Key Features

• Persistent Conversations: Chat history is maintained across sessions
• Code Context Awareness: AI understands your current project and files
• Multi-turn Conversations: Build upon previous questions and answers
• Code Generation: Request complete functions, classes, or modules

How to Use Side Chat

1. Open Side Chat: Click the chat icon in the sidebar or use Ctrl+Shift+C (Windows/Linux) or Cmd+Shift+C (macOS)
2. Ask Questions: Type your question or request in natural language
3. Review Responses: AI provides detailed explanations with code examples
4. Apply Code: Copy and paste suggested code into your project

Example Interactions

💬 You: "How do I handle errors in async/await functions?"

🤖 AI: Here are several ways to handle errors in async/await functions:

1. Try-catch blocks:
```javascript
async function fetchData() {
  try {
    const response = await fetch('/api/data');
    const data = await response.json();
    return data;
  } catch (error) {
    console.error('Error fetching data:', error);
    throw error;
  }
}

2. Error handling with specific error types:

async function processData() {
  try {
    const result = await someAsyncOperation();
    return result;
  } catch (error) {
    if (error instanceof NetworkError) {
      // Handle network errors
    } else if (error instanceof ValidationError) {
      // Handle validation errors
    } else {
      // Handle other errors
    }
  }
}

## Inline Chat

Inline Chat allows you to get AI assistance directly within your code editor, providing context-specific help.

### Key Features

- **Context-Aware**: AI sees the exact code you're working on
- **Quick Access**: Activated with a simple keyboard shortcut
- **Focused Assistance**: Get help for specific lines or code blocks
- **Code Modifications**: AI can suggest changes to existing code

### How to Use Inline Chat

1. **Position Cursor**: Place your cursor where you need help
2. **Activate Inline Chat**: Press `Ctrl+I` (Windows/Linux) or `Cmd+I` (macOS)
3. **Describe Your Need**: Type what you want to accomplish
4. **Review Suggestions**: AI provides contextual code suggestions
5. **Accept or Modify**: Apply the suggestion or ask for modifications

### Use Cases

- **Code Explanation**: "Explain what this function does"
- **Bug Fixing**: "This function isn't working correctly, can you help?"
- **Code Optimization**: "How can I make this code more efficient?"
- **Documentation**: "Add comments to explain this complex logic"
- **Refactoring**: "Convert this to use modern ES6 syntax"

## AI Capabilities

### Code Understanding

The AI assistant can:

- **Analyze Code Structure**: Understand classes, functions, and modules
- **Identify Patterns**: Recognize design patterns and coding conventions
- **Detect Issues**: Spot potential bugs, performance issues, or security vulnerabilities
- **Suggest Improvements**: Recommend better approaches or optimizations

### Language Support

Trae's AI assistant supports multiple programming languages:

- **Web Technologies**: JavaScript, TypeScript, HTML, CSS, React, Vue, Angular
- **Backend Languages**: Python, Java, C#, Go, Rust, PHP
- **Mobile Development**: Swift, Kotlin, Dart (Flutter)
- **Data Science**: Python (NumPy, Pandas), R, SQL
- **DevOps**: Docker, Kubernetes, YAML, Shell scripting

### Code Generation

The AI can generate various types of code:

- **Functions and Methods**: Complete implementations based on descriptions
- **Classes and Interfaces**: Object-oriented structures
- **API Integrations**: REST API calls, GraphQL queries
- **Database Queries**: SQL, NoSQL database operations
- **Test Cases**: Unit tests, integration tests
- **Configuration Files**: Docker, CI/CD, package configurations

## Best Practices

### Effective Communication

1. **Be Specific**: Provide clear, detailed descriptions of what you need
2. **Include Context**: Mention the programming language, framework, or specific requirements
3. **Ask Follow-up Questions**: Build upon previous responses for better results
4. **Provide Examples**: Show the AI what you're trying to achieve

### Example of Good Prompts

❌ **Poor**: "Make this better"

✅ **Good**: "Optimize this Python function for better performance when processing large datasets"

❌ **Poor**: "Fix this"

✅ **Good**: "This React component is not re-rendering when props change. Can you help identify the issue?"

### Code Review and Validation

- **Review AI Suggestions**: Always review generated code before implementation
- **Test Thoroughly**: Test AI-generated code in your specific environment
- **Understand the Logic**: Make sure you understand how the suggested code works
- **Adapt as Needed**: Modify suggestions to fit your project's conventions

## Advanced Features

### Project-Level Understanding

The AI assistant can:

- **Analyze Project Structure**: Understand your entire codebase organization
- **Maintain Consistency**: Suggest code that follows your project's patterns
- **Cross-File References**: Understand relationships between different files
- **Architecture Awareness**: Respect your project's architectural decisions

### Learning from Your Code

The AI adapts to your coding style by:

- **Recognizing Patterns**: Learning your preferred coding conventions
- **Suggesting Consistent Solutions**: Maintaining consistency across your project
- **Respecting Preferences**: Adapting to your choice of libraries and frameworks

## Troubleshooting

### Common Issues

**AI responses are too generic**
- Provide more specific context about your project
- Include relevant code snippets in your questions
- Specify the programming language and framework

**Code suggestions don't work**
- Check for syntax errors in the suggested code
- Ensure all required imports are included
- Verify compatibility with your project's dependencies

**AI doesn't understand my question**
- Rephrase your question with more technical details
- Break complex questions into smaller, specific parts
- Provide examples of what you're trying to achieve

## Tips for Maximum Productivity

1. **Use Both Chat Modes**: Combine Side Chat for planning and Inline Chat for implementation
2. **Iterate on Solutions**: Ask for improvements or alternatives to initial suggestions
3. **Learn from Explanations**: Pay attention to the reasoning behind AI suggestions
4. **Build a Conversation**: Reference previous parts of your conversation for context
5. **Experiment Safely**: Try AI suggestions in a development environment first

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The AI Assistant in Trae IDE is designed to be your intelligent coding partner, helping you write better code faster while learning and adapting to your development style.