One API. Every AI Model.

curl -X POST https://ai.codexpert.io/api/v1/openai \
  -H "API-Key: your_api_key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4o",
    "messages": [
      {"role": "system", "content": "You are a helpful assistant."},
      {"role": "user", "content": "Explain quantum computing in simple terms."}
    ],
    "temperature": 0.7,
    "max_tokens": 500
  }'

{
  "id": "chatcmpl-abc123",
  "object": "chat.completion",
  "choices": [{
    "index": 0,
    "message": {
      "role": "assistant",
      "content": "Quantum computing uses quantum bits (qubits) that can exist in multiple states simultaneously..."
    },
    "finish_reason": "stop"
  }],
  "usage": { "prompt_tokens": 28, "completion_tokens": 145, "total_tokens": 173 }
}

DeepSeek uses the same format. Just change the endpoint to /v1/deepseek and the model to deepseek-chat.

curl -X POST https://ai.codexpert.io/api/v1/claude \
  -H "API-Key: your_api_key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "claude-sonnet-4-6",
    "max_tokens": 1024,
    "messages": [
      {"role": "user", "content": "Write a Python function to reverse a linked list."}
    ]
  }'

{
  "id": "msg_abc123",
  "type": "message",
  "role": "assistant",
  "content": [{
    "type": "text",
    "text": "Here's a Python function to reverse a linked list:\n\n```python\ndef reverse_linked_list(head):\n    prev = None\n    current = head\n    while current:\n        next_node = current.next\n        current.next = prev\n        prev = current\n        current = next_node\n    return prev\n```"
  }],
  "usage": { "input_tokens": 18, "output_tokens": 95 }
}

Claude requires max_tokens in every request. The response uses input_tokens / output_tokens instead of OpenAI's naming.

curl -X POST https://ai.codexpert.io/api/v1/gemini \
  -H "API-Key: your_api_key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-2.5-flash",
    "contents": [{
      "parts": [{"text": "Summarize the history of the internet in 3 paragraphs."}]
    }]
  }'

{
  "candidates": [{
    "content": {
      "parts": [{"text": "The internet originated in the late 1960s..."}],
      "role": "model"
    },
    "finishReason": "STOP"
  }],
  "usageMetadata": {
    "promptTokenCount": 14,
    "candidatesTokenCount": 280,
    "totalTokenCount": 294
  }
}

Gemini uses contents / parts instead of messages. The model is specified in the request body but handled via the URL internally.

const response = await fetch('https://ai.codexpert.io/api/v1/openai', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'API-Key': 'your_api_key'
  },
  body: JSON.stringify({
    model: 'gpt-4o',
    messages: [
      { role: 'system', content: 'You are a helpful assistant.' },
      { role: 'user', content: 'What is machine learning?' }
    ]
  })
});

const data = await response.json();

if (!response.ok) {
  console.error('Error:', data.message);
} else {
  console.log(data.choices[0].message.content);
}

import requests

response = requests.post(
    'https://ai.codexpert.io/api/v1/openai',
    headers={
        'Content-Type': 'application/json',
        'API-Key': 'your_api_key'
    },
    json={
        'model': 'gpt-4o',
        'messages': [
            {'role': 'user', 'content': 'Explain recursion with an analogy.'}
        ]
    }
)

data = response.json()

if response.ok:
    print(data['choices'][0]['message']['content'])
else:
    print(f"Error {response.status_code}: {data.get('message', 'Unknown error')}")

from openai import OpenAI

client = OpenAI(
    api_key="your_api_key",
    base_url="https://ai.codexpert.io/api/v1/openai",
    default_headers={"API-Key": "your_api_key"}
)

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {"role": "system", "content": "You are a helpful coding assistant."},
        {"role": "user", "content": "Write a merge sort in Python."}
    ],
    temperature=0.3
)

print(response.choices[0].message.content)

Works with the official OpenAI Python SDK. Just override base_url and add the API-Key header.

$response = wp_remote_post( 'https://ai.codexpert.io/api/v1/openai', array(
    'headers' => array(
        'Content-Type' => 'application/json',
        'API-Key'      => 'your_api_key',
    ),
    'body'    => wp_json_encode( array(
        'model'    => 'gpt-4o',
        'messages' => array(
            array( 'role' => 'user', 'content' => 'Hello from WordPress!' ),
        ),
    ) ),
    'timeout' => 60,
) );

if ( ! is_wp_error( $response ) ) {
    $body = json_decode( wp_remote_retrieve_body( $response ), true );
    echo $body['choices'][0]['message']['content'];
}