@sha3/openai v2.0.0

OpenAI TypeScript Client

A modern, type-safe TypeScript client for interacting with the OpenAI API. This library provides a clean, intuitive interface for working with OpenAI's powerful language models, including GPT-4 and others.

✨ Features

• Type-Safe - Built with TypeScript for enhanced developer experience
• Simple API - Clean, intuitive methods for common operations
• Flexible Configuration - Customize model parameters and token limits
• Promise-based - Async/await support for all operations
• Comprehensive Error Handling - Clear error messages and status codes

🚀 Quick Start

Installation

npm install @your-org/openai
# or
yarn add @your-org/openai

Basic Usage

import { OpenAI } from '@your-org/openai';

// Initialize the client
const openai = new OpenAI({
  apikey: 'your-api-key',
  model: 'gpt-4',
  systemPrompt: 'You are a helpful assistant.',
  maxNumberOfInputTokens: 4096,
  maxNumberOfOutputTokens: 1024
});

// Process a prompt
async function getResponse() {
  try {
    const response = await openai.processPrompt("Tell me about TypeScript", {
      temperature: 0.7,
      user: 'user-123'
    });
    
    console.log(response);
  } catch (error) {
    console.error('Error processing prompt:', error);
  }
}

getResponse();

📖 Documentation

Initialization

const openai = new OpenAI({
  apikey: string;                 // Required: Your OpenAI API key
  systemPrompt?: string;          // Optional: Initial system prompt
  model: string;                  // Required: Model to use (e.g., 'gpt-4')
  maxNumberOfInputTokens?: number; // Optional: Max input tokens (default: 4096)
  maxNumberOfOutputTokens?: number; // Optional: Max output tokens (default: 1024)
});

Methods

loadSystemPrompt(prompt: string): void

Loads a system prompt and encodes it into tokens.

processPrompt(prompt: string, options: ProcessPromptOptions): Promise<ProcessPromptResponse>

Processes a user prompt and returns the model's response.

Types

ProcessPromptOptions

{
  temperature?: number;           // Controls randomness (0.0 to 1.0)
  user?: string;                  // Unique user identifier
  // Additional options...
}

ProcessPromptResponse

{
  id: string;                    // Completion ID
  created: number;                // Creation timestamp
  model: string;                 // Model used
  choices: Array<{
    message: CompletionMessage;
    finish_reason: string;
    index: number;
  }>;
  usage: {
    prompt_tokens: number;
    completion_tokens: number;
    total_tokens: number;
  };
}

🔧 Configuration

Environment Variables

OPENAI_API_KEY=your_api_key_here
OPENAI_DEFAULT_MODEL=gpt-4

Runtime Configuration

All configuration options can be passed to the constructor or set via environment variables.

💡 Examples

Chat Completion

const response = await openai.processPrompt("What's the weather like?", {
  temperature: 0.8,
  max_tokens: 150
});

Streaming Responses

// Example of streaming implementation would go here
// This depends on your specific streaming requirements

📊 Pricing

Pricing is based on the official OpenAI pricing model. For the most up-to-date information, refer to:

• OpenAI Pricing
• Pricing Data Source

🤝 Contributing

We welcome contributions! Please follow these steps:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• OpenAI for their amazing API
• The TypeScript community for their support
• All contributors who help improve this project