Blackboxify

A powerful Node.js client for BlackboxAI with an OpenAI-compatible interface, streaming support, multiple auth accounts, and token pricing.

Features

• 🔄 OpenAI-Compatible Interface: Drop-in replacement for OpenAI's chat completion API
• 🌊 Streaming Support: Real-time streaming responses with token counting
• 🔑 Multiple Auth Accounts: Automatic retry with multiple accounts on rate limits
• 💰 Token Pricing: Accurate token counting and cost estimation
• 🚀 High Performance: Optimized for speed and reliability
• 🛡️ Error Handling: Comprehensive error handling and rate limit detection

Installation

npm install blackboxify

Quick Start

import { BlackboxAI } from 'blackboxify';

const client = new BlackboxAI({
  models: {
    "blackboxai-default": {
      id: "blackboxai-default",
      input: 0,
      output: 0
    }
  },
  auth: [
    {
      email: "[email protected]",
      customer_id: "your_customer_id"
    }
  ]
});

// Basic chat completion
const response = await client.chat.completions.create({
  model: "blackboxai-default",
  messages: [
    { role: "user", content: "Hello, how are you?" }
  ],
  max_tokens: 50,
  temperature: 0.7
});

console.log(response.choices[0].message.content);

Streaming Example

const stream = await client.chat.completions.create({
  model: "blackboxai-default",
  messages: [
    { role: "user", content: "Tell me a story." }
  ],
  stream: true
});

for await (const chunk of stream) {
  process.stdout.write(chunk.choices[0].delta.content);
}

Configuration

Client Options

const client = new BlackboxAI({
  models: {
    // Configure available models with pricing
    "model-name": {
      id: "model-identifier",
      input: 2.5,  // Cost per 1M input tokens
      output: 10   // Cost per 1M output tokens
    }
  },
  auth: [
    // Multiple auth accounts for automatic retry
    {
      email: "[email protected]",
      customer_id: "cus_account1"
    },
    {
      email: "[email protected]",
      customer_id: "cus_account2"
    }
  ]
});

Request Options

const response = await client.chat.completions.create({
  model: "model-name",          // Model identifier
  messages: [],                 // Array of message objects
  max_tokens: 4096,            // Maximum tokens in response
  temperature: 0.7,            // Response randomness (0-1)
  stream: false,               // Enable streaming mode
  user: "user-identifier"      // Optional user identifier
});

Response Format

Regular Response

{
  id: "chatcmpl-123",
  object: "chat.completion",
  created: 1677858242,
  model: "model-name",
  choices: [{
    index: 0,
    message: {
      role: "assistant",
      content: "Response content here"
    },
    finish_reason: "stop"
  }],
  usage: {
    prompt_tokens: 10,
    completion_tokens: 20,
    total_tokens: 30,
    cost: 0.0004
  }
}

Streaming Response

{
  id: "chatcmpl-123",
  object: "chat.completion.chunk",
  created: 1677858242,
  model: "model-name",
  choices: [{
    index: 0,
    delta: {
      content: "Chunk content here"
    },
    finish_reason: null
  }],
  usage: {
    prompt_tokens: 10,
    completion_tokens: 5,
    total_tokens: 15,
    cost: 0.0002
  }
}

Error Handling

try {
  const response = await client.chat.completions.create({
    model: "model-name",
    messages: [{ role: "user", content: "Hello" }]
  });
} catch (error) {
  if (error.statusCode === 429) {
    console.log("Rate limit reached, retrying with next account...");
  } else {
    console.error("Request failed:", error.message);
  }
}

Token Calculation

The client automatically calculates tokens for both input and output:

• Input tokens: Calculated from the messages array
• Output tokens: Calculated from the response content
• Cost: Based on model-specific pricing per 1M tokens

Best Practices

1. Multiple Auth Accounts: Configure multiple accounts for better reliability
2. Error Handling: Always implement proper error handling
3. Streaming: Use streaming for real-time responses and better UX
4. Token Monitoring: Monitor token usage and costs
5. Rate Limits: Handle rate limits gracefully

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

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