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# chatapi.ai-now.space API Documentation

This API provides access to a variety of large language models (LLMs) for chat completions, token counting, and moderation.

## Table of Contents

* [Authentication](#authentication)
* [Endpoints](#endpoints)
    * [/models - List Available Models](#models)
    * [/chat/completions - Generate Chat Completions](#chatcompletions)
        * [Request Body](#chatcompletions-request-body)
        * [Non-Streaming Response](#chatcompletions-non-streaming-response)
        * [Streaming Response](#chatcompletions-streaming-response)
    * [/tokens - Count Tokens](#tokens)
    * [/credits - Check Remaining Credits](#credits)
    * [/moderate - Moderate Text](#moderate)
* [Supported Models](#supported-models)
* [Usage Examples](#usage-examples)
    * [Python](#usage-examples-python)
        * [Non-Streaming Example](#usage-examples-python-non-streaming-example)
        * [Streaming Example](#usage-examples-python-streaming-example)
    * [C#](#usage-examples-c)
        * [Non-Streaming Example](#usage-examples-c-non-streaming-example)
        * [Streaming Example](#usage-examples-c-streaming-example)
    * [Node.js](#usage-examples-nodejs)
        * [Non-Streaming Example](#usage-examples-nodejs-non-streaming-example)
        * [Streaming Example](#usage-examples-nodejs-streaming-example)

## Authentication

You need an API key to use this API. To obtain an API key, please contact `[email protected]`.

Once you have an API key, include it in the `Authorization` header of your requests as a Bearer token:

Authorization: Bearer YOUR_API_KEY

## Endpoints

### /models

**Method:** GET

**Description:** Returns a list of available models with their associated input and output costs.

**Response:**

```json
{
  "data": [
    {
      "id": "Claude 3.5 Sonnet",
      "inputCost": 0.002,
      "outputCost": 0.003
    },
    {
      "id": "GPT-4 Turbo",
      "inputCost": 0.03,
      "outputCost": 0.06
    },
    // ... other models
  ]
}

/chat/completions

Method: POST

Description: Generates chat completions using the specified model.

Request Body

{
  "model": "MODEL_NAME", // See the list of supported models below
  "messages": [
    {
      "role": "system",
      "content": "You are a helpful assistant."
    },
    {
      "role": "user",
      "content": "What is the capital of France?"
    }
  ],
  "stream": true/false, // Optional, defaults to false
  // ... other parameters (see model-specific documentation)
}

Non-Streaming Response

{
  "id": "chatcmpl-...",
  "object": "chat.completion",
  "created": 1677652288,
  "model": "MODEL_NAME",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "The capital of France is Paris."
      },
      "finish_reason": "stop"
    }
  ],
  "input_tokens": ...,
  "output_tokens": ...,
  "input_tokens_cost": ...,
  "output_tokens_cost": ...,
  "total_tokens_cost": ...,
  "total_time_taken": ...,
  "tokens_per_second": ...
}

Streaming Response

data: {"id": "chatcmpl-...", "object": "chat.completion.chunk", "created": 1677652288, "model": "MODEL_NAME", "choices": [{"index": 0, "delta": {"content": "The"}, "finish_reason": null}]}

data: {"id": "chatcmpl-...", "object": "chat.completion.chunk", "created": 1677652288, "model": "MODEL_NAME", "choices": [{"index": 0, "delta": {"content": " capital"}, "finish_reason": null}]}

data: {"id": "chatcmpl-...", "object": "chat.completion.chunk", "created": 1677652288, "model": "MODEL_NAME", "choices": [{"index": 0, "delta": {"content": " of"}, "finish_reason": null}]}

// ... more chunks

data: {"id": "chatcmpl-...", "object": "chat.completion.chunk", "created": 1677652288, "model": "MODEL_NAME", "choices": [{"index": 0, "delta": {"content": " is Paris."}, "finish_reason": "stop"}]}

data: {"input_tokens": ..., "output_tokens": ..., "input_tokens_cost": ..., "output_tokens_cost": ..., "total_tokens_cost": ..., "total_time_taken": ..., "tokens_per_second": ..., "time_to_first_data": ...}

/tokens

Method: POST

Description: Counts the number of tokens in a given text.

Request Body:

{
  "text": "Your text here"
}

Response:

{
  "tokens": 123
}

/credits

Method: GET

Description: Returns the remaining credits for your API key.

Response:

{
  "credits": 1000
}

/moderate

Method: POST

Description: Moderates the given input text using OpenAI's moderation API.

Request Body:

{
  "input": "Your text here"
}

Response:

{
  "results": [
    {
      "categories": {
        "hate": false,
        "hate/threatening": false,
        // ... other categories
      },
      "category_scores": {
        "hate": 0.0000000000000000,
        "hate/threatening": 0.0000000000000000,
        // ... other category scores
      },
      "flagged": false
    }
  ]
}

Supported Models

You can easily copy the model names below and use them in your requests.

Claude 3.5 Sonnet
GPT-4 Turbo
Gemini 1.5 Pro Exp
Deepseek Chat
Llama 3.1 405b
Mixtral 8x7b
GPT-4o
Command-R Plus
Mixtral-8x22B-Instruct-v0.1
GLM-4
Llama-3-70b-chat-hf
WizardLM-13B-V1.2
Command-R Plus Online
Meta-Llama-3.1-405B-Instruct-Turbo

Usage Examples

Python

Non-Streaming Example

import requests

headers = {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json'
}

data = {
    'model': 'GPT-4 Turbo',
    'messages': [
        {'role': 'system', 'content': 'You are a helpful assistant.'},
        {'role': 'user', 'content': 'What is the capital of France?'}
    ]
}

response = requests.post('https://chatapi.ai-now.space/chat/completions', headers=headers, json=data)

print(response.json())

Streaming Example

import requests

headers = {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json'
}

data = {
    'model': 'Claude 3.5 Sonnet',
    'messages': [
        {'role': 'system', 'content': 'You are a helpful assistant.'},
        {'role': 'user', 'content': 'Write a short poem about the sea.'}
    ],
    'stream': True
}

response = requests.post('https://chatapi.ai-now.space/chat/completions', headers=headers, json=data, stream=True)

for line in response.iter_lines():
    if line:
        decoded_line = line.decode('utf-8')
        if decoded_line.startswith('data: '):
            print(decoded_line[6:])

C#

Non-Streaming Example

using System;
using System.Net.Http;
using System.Net.Http.Headers;
using System.Text;
using System.Threading.Tasks;
using Newtonsoft.Json;

public class ChatCompletionExample
{
    public static async Task Main(string[] args)
    {
        using (var client = new HttpClient())
        {
            client.DefaultRequestHeaders.Authorization = new AuthenticationHeaderValue("Bearer", "YOUR_API_KEY");
            client.DefaultRequestHeaders.Accept.Add(new MediaTypeWithQualityHeaderValue("application/json"));

            var requestBody = new
            {
                model = "GPT-4 Turbo",
                messages = new[]
                {
                    new { role = "system", content = "You are a helpful assistant." },
                    new { role = "user", content = "What is the capital of France?" }
                }
            };

            var json = JsonConvert.SerializeObject(requestBody);
            var content = new StringContent(json, Encoding.UTF8, "application/json");

            var response = await client.PostAsync("https://chatapi.ai-now.space/chat/completions", content);
            var responseString = await response.Content.ReadAsStringAsync();

            Console.WriteLine(responseString);
        }
    }
}

Streaming Example

using System;
using System.Net.Http;
using System.Net.Http.Headers;
using System.Text;
using System.Threading.Tasks;
using Newtonsoft.Json;

public class ChatCompletionStreamingExample
{
    public static async Task Main(string[] args)
    {
        using (var client = new HttpClient())
        {
            client.DefaultRequestHeaders.Authorization = new AuthenticationHeaderValue("Bearer", "YOUR_API_KEY");
            client.DefaultRequestHeaders.Accept.Add(new MediaTypeWithQualityHeaderValue("application/json"));

            var requestBody = new
            {
                model = "Claude 3.5 Sonnet",
                messages = new[]
                {
                    new { role = "system", content = "You are a helpful assistant." },
                    new { role = "user", content = "Write a short poem about the sea." }
                },
                stream = true
            };

            var json = JsonConvert.SerializeObject(requestBody);
            var content = new StringContent(json, Encoding.UTF8, "application/json");

            var response = await client.PostAsync("https://chatapi.ai-now.space/chat/completions", content);

            using (var stream = await response.Content.ReadAsStreamAsync())
            using (var reader = new System.IO.StreamReader(stream))
            {
                string line;
                while ((line = await reader.ReadLineAsync()) != null)
                {
                    if (line.StartsWith("data: "))
                    {
                        Console.WriteLine(line.Substring(6));
                    }
                }
            }
        }
    }
}

Node.js

Non-Streaming Example

const axios = require('axios');

const headers = {
  'Authorization': 'Bearer YOUR_API_KEY',
  'Content-Type': 'application/json'
};

const data = {
  model: 'GPT-4 Turbo',
  messages: [
    { role: 'system', content: 'You are a helpful assistant.' },
    { role: 'user', content: 'What is the capital of France?' }
  ]
};

axios.post('https://chatapi.ai-now.space/chat/completions', data, { headers })
  .then(response => {
    console.log(response.data);
  })
  .catch(error => {
    console.error(error);
  });

Streaming Example

const axios = require('axios');

const headers = {
  'Authorization': 'Bearer YOUR_API_KEY',
  'Content-Type': 'application/json'
};

const data = {
  model: 'Claude 3.5 Sonnet',
  messages: [
    { role: 'system', content: 'You are a helpful assistant.' },
    { role: 'user', content: 'Write a short poem about the sea.' }
  ],
  stream: true
};

axios.post('https://chatapi.ai-now.space/chat/completions', data, { headers, responseType: 'stream' })
  .then(response => {
    response.data.on('data', (chunk) => {
      const lines = chunk.toString().split('\n');
      lines.forEach(line => {
        if (line.startsWith('data: ')) {
          console.log(line.substring(6));
        }
      });
    });
  })
  .catch(error => {
    console.error(error);
  });

Remember to replace YOUR_API_KEY with your actual API key.