LlamaIndex-JS Best Practices and Coding Standards
LlamaIndex-JSAIMLbest practicescoding standards
Description
This rule provides comprehensive guidelines for developing AI applications with LlamaIndex-JS, covering code organization, performance, security, and testing best practices. It aims to ensure robust, efficient, and secure LLM-powered applications.
Globs
**/*.{js,ts,jsx,tsx}---
description: This rule provides comprehensive guidelines for developing AI applications with LlamaIndex-JS, covering code organization, performance, security, and testing best practices. It aims to ensure robust, efficient, and secure LLM-powered applications.
globs: **/*.{js,ts,jsx,tsx}
---
# LlamaIndex-JS Best Practices and Coding Standards
This document outlines the best practices and coding standards for developing AI and ML applications using the LlamaIndex-JS library. Following these guidelines will help you build robust, efficient, secure, and maintainable applications.
## 1. Code Organization and Structure
### 1.1. Directory Structure
Adopt a modular directory structure to organize your LlamaIndex-JS project. Here’s a recommended structure:
my-llamaindex-app/
├── src/
│ ├── components/ # Reusable UI components (if applicable)
│ │ ├── MyComponent.tsx
│ │ └── ...
│ ├── services/ # API services and data fetching logic
│ │ ├── llamaIndexService.ts # LlamaIndex specific functionalities
│ │ └── ...
│ ├── utils/ # Utility functions and helpers
│ │ ├── dataProcessing.ts
│ │ └── ...
│ ├── index/ # Index management
│ │ ├── documentLoaders.ts # Custom document loaders
│ │ ├── indexBuilders.ts # Logic for building indices
│ │ └── ...
│ ├── prompts/ # Custom prompt templates
│ │ ├── summarizationPrompt.ts
│ │ └── ...
│ ├── models/ # Data models and interfaces
│ │ ├── document.ts
│ │ └── ...
│ ├── app.ts # Main application entry point
│ └── ...
├── tests/
│ ├── unit/
│ │ └── ...
│ ├── integration/
│ │ └── ...
│ └── ...
├── .env # Environment variables
├── package.json
├── tsconfig.json # TypeScript configuration
├── README.md
└── ...
### 1.2. File Naming Conventions
* Use descriptive and consistent file names.
* For components, use PascalCase (e.g., `MyComponent.tsx`).
* For utility functions and services, use camelCase (e.g., `llamaIndexService.ts`, `dataProcessing.ts`).
* For configuration files, use kebab-case (e.g., `tsconfig.json`).
### 1.3. Module Organization
* **Encapsulation:** Group related functions, classes, and interfaces into modules.
* **Single Responsibility Principle:** Each module should have a clear and specific purpose.
* **Explicit Exports:** Use explicit `export` statements to define the public API of each module.
* **Avoid Circular Dependencies:** Be mindful of circular dependencies between modules, as they can lead to runtime errors and make code harder to understand.
### 1.4. Component Architecture (If Applicable)
* If your LlamaIndex-JS application includes a user interface (e.g., using React), follow a component-based architecture.
* **Presentational Components:** Focus on rendering UI elements and receiving data as props.
* **Container Components:** Handle data fetching, state management, and logic.
* **Component Composition:** Build complex UIs by composing smaller, reusable components.
### 1.5. Code Splitting
* Use dynamic imports (`import()`) to split your code into smaller chunks.
* Lazy-load components or modules that are not immediately needed.
* This can significantly improve initial load time and reduce the overall bundle size.
typescript
// Example of lazy loading a module
async function loadMyModule() {
const myModule = await import('./myModule');
myModule.doSomething();
}
## 2. Common Patterns and Anti-Patterns
### 2.1. Design Patterns
* **Retrieval-Augmented Generation (RAG):** Implement RAG to enhance LLM responses by retrieving relevant data from external sources.
* **Factory Pattern:** Use factory functions to create instances of LlamaIndex objects, abstracting the creation logic.
* **Strategy Pattern:** Employ different indexing or query strategies based on the specific use case.
* **Observer Pattern:** Use this to react to changes in the underlying data or model.
### 2.2. Recommended Approaches for Common Tasks
* **Data Loading:** Use `Document` objects and `BaseReader` classes for loading data from various sources.
* **Indexing:** Choose appropriate index types (e.g., `VectorStoreIndex`, `SummaryIndex`) based on your data and query requirements.
* **Querying:** Use `QueryEngine` to orchestrate complex queries and retrieve relevant information.
* **Evaluation:** Implement evaluation metrics to measure the performance of your RAG pipeline.
### 2.3. Anti-Patterns and Code Smells
* **Tight Coupling:** Avoid tight coupling between LlamaIndex-JS components and other parts of your application.
* **Global State:** Minimize the use of global state, as it can make your application harder to reason about.
* **Ignoring Errors:** Always handle errors gracefully and provide informative error messages.
* **Over-Complicating Queries:** Keep queries simple and focused on retrieving the most relevant information.
* **Not using `async/await`:** Use `async/await` when dealing with asynchronous operations to avoid callback hell.
### 2.4. State Management
* Choose a state management library or pattern that fits your application's needs (e.g., React Context, Redux, Zustand).
* Keep state minimal and derive values as needed.
* Use immutable data structures to simplify state updates.
### 2.5. Error Handling
* Use `try...catch` blocks to handle exceptions.
* Provide informative error messages to the user.
* Log errors for debugging purposes.
* Consider using a centralized error handling mechanism.
## 3. Performance Considerations
### 3.1. Optimization Techniques
* **Efficient Indexing:** Optimize indexing by selecting appropriate chunk sizes and embedding models. Experiment to find optimal values.
* **Caching:** Cache frequently accessed data to reduce latency.
* **Asynchronous Operations:** Use asynchronous operations to avoid blocking the main thread.
* **Vector Store Selection:** Choose vector stores that support efficient similarity search (e.g., FAISS, Annoy, Qdrant).
### 3.2. Memory Management
* Be mindful of memory usage, especially when dealing with large datasets.
* Use garbage collection effectively.
* Avoid creating unnecessary objects.
* Use streams for processing large files.
### 3.3. Rendering Optimization (If Applicable)
* Use virtualization techniques to render large lists efficiently.
* Memoize components to prevent unnecessary re-renders.
* Optimize images and other assets.
### 3.4. Bundle Size Optimization
* Use tree shaking to remove unused code.
* Minify and compress your code.
* Use code splitting to load only the code that is needed for each page.
* Analyze bundle size using tools like Webpack Bundle Analyzer.
### 3.5. Lazy Loading
* Implement lazy loading for non-critical components or modules.
* This can improve initial load time and reduce the overall bundle size.
## 4. Security Best Practices
### 4.1. Common Vulnerabilities
* **Prompt Injection:** Protect against prompt injection attacks by sanitizing user input and validating LLM responses. Consider using libraries such as LLM Guard by Protect AI.
* **Data Leakage:** Prevent data leakage by carefully controlling access to sensitive information.
* **Cross-Site Scripting (XSS):** Sanitize user input to prevent XSS attacks (if applicable, in UI components).
* **API Key Exposure:** Protect API keys and other sensitive credentials by storing them securely and avoiding hardcoding them in your code.
### 4.2. Input Validation
* Validate all user input to prevent malicious data from entering your application.
* Use appropriate validation techniques for each type of input.
* Sanitize input to remove potentially harmful characters.
### 4.3. Authentication and Authorization
* Implement authentication to verify the identity of users.
* Implement authorization to control access to resources.
* Use strong passwords and encryption.
* Follow the principle of least privilege.
### 4.4. Data Protection
* Encrypt sensitive data at rest and in transit.
* Use secure storage mechanisms.
* Implement data loss prevention (DLP) measures.
* Regularly back up your data.
### 4.5. Secure API Communication
* Use HTTPS for all API communication.
* Validate API responses to ensure data integrity.
* Implement rate limiting to prevent abuse.
* Use API keys or other authentication mechanisms.
## 5. Testing Approaches
### 5.1. Unit Testing
* Write unit tests to verify the functionality of individual components and functions.
* Use mocking and stubbing to isolate units of code.
* Aim for high code coverage.
### 5.2. Integration Testing
* Write integration tests to verify the interaction between different components and modules.
* Test the integration with external services and APIs.
### 5.3. End-to-End Testing
* Write end-to-end tests to verify the overall functionality of the application.
* Simulate user interactions and verify the expected behavior.
### 5.4. Test Organization
* Organize your tests into separate directories for unit, integration, and end-to-end tests.
* Use descriptive test names.
* Keep tests concise and focused.
### 5.5. Mocking and Stubbing
* Use mocking and stubbing to isolate units of code during testing.
* Use a mocking library such as Jest or Sinon.
* Avoid over-mocking, as it can make your tests less effective.
## 6. Common Pitfalls and Gotchas
### 6.1. Frequent Mistakes
* Incorrectly configuring the LlamaIndex-JS client.
* Using the wrong index type for your data.
* Not handling errors properly.
* Ignoring performance considerations.
* Not securing your application against vulnerabilities.
### 6.2. Edge Cases
* Handling large documents or datasets.
* Dealing with complex queries.
* Handling different data formats.
* Dealing with rate limits from external APIs.
### 6.3. Version-Specific Issues
* Be aware of breaking changes between LlamaIndex-JS versions.
* Consult the release notes and migration guides when upgrading.
* Test your application thoroughly after upgrading.
### 6.4. Compatibility Concerns
* Ensure compatibility between LlamaIndex-JS and other libraries or frameworks that you are using.
* Test your application in different environments.
### 6.5. Debugging Strategies
* Use a debugger to step through your code and inspect variables.
* Log messages to the console to track the execution flow.
* Use error monitoring tools to track errors in production.
* Use the LlamaIndex-JS documentation and community forums to find solutions to common problems.
## 7. Tooling and Environment
### 7.1. Recommended Development Tools
* Node.js
* npm or yarn
* TypeScript (recommended)
* VS Code or other IDE
* LlamaIndex Studio for visualization
* Postman or Insomnia for testing APIs
### 7.2. Build Configuration
* Use a build tool such as Webpack or Parcel to bundle your code.
* Configure your build tool to optimize your code for production.
* Use environment variables to configure your application.
### 7.3. Linting and Formatting
* Use a linter such as ESLint to enforce coding standards.
* Use a formatter such as Prettier to format your code consistently.
* Configure your IDE to automatically lint and format your code.
### 7.4. Deployment
* Choose a deployment platform that meets your needs (e.g., Vercel, Netlify, AWS).
* Configure your deployment environment to use environment variables.
* Set up monitoring and logging to track the performance of your application.
### 7.5. CI/CD Integration
* Use a CI/CD platform such as GitHub Actions or Jenkins to automate your build, test, and deployment processes.
* Configure your CI/CD pipeline to run your tests automatically.
* Use automated deployment to deploy your application to production.
By following these best practices, you can build robust, efficient, secure, and maintainable AI applications using LlamaIndex-JS.