Examples

For the following examples to work, save your API key to the ARKANE_CLOUD_API_KEY environment variable.

Text generation: v1/chat/completions

Request

Here is a sample JSON request body that includes all supported fields:

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://console.arkanecloud.com/",
    api_key=os.environ.get("ARKANE_CLOUD_API_KEY"),
)

completion = client.chat.completions.create(
    model="meta-llama/Meta-Llama-3.1-70B-Instruct",
    messages=[
        {
          "role": "system",
          "content": "You are a chemistry expert. Add jokes about cats to your responses from time to time."
        },
        {
          "role": "user",
          "content": "Hello!"
        },
        {
          "role": "assistant",
          "content": "Hello! How can I assist you with chemistry today? And did you hear about the cat who became a chemist? She had nine lives, but she only needed one formula!"
        }
    ],
    max_tokens=100,
    temperature=1,
    top_p=1,
    top_k=50,
    n=1,
    stream=false,
    stream_options=null,
    stop=null,
    presence_penalty=0,
    frequency_penalty=0,
    logit_bias=null,
    logprobs=false,
    top_logprobs=null,
    user=null,
    extra_body={
        "guided_json": {"type": "object", "properties": {...}}
    },
    response_format={
        "type": "json_object"
    }
)

print(completion.to_json())

Response

{
  "id": "cmpl-*****",
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "logprobs": null,
      "message": {
        "content": "Hello! It's nice to meet you. Is there something I can help you with, or would you like to chat?",
        "role": "assistant",
        "function_call": null,
        "tool_calls": []
      },
      "stop_reason": null
    }
  ],
  "created": 1721397089,
  "model": "meta-llama/Meta-Llama-3.1-70B-Instruct",
  "object": "chat.completion",
  "system_fingerprint": null,
  "usage": {
    "completion_tokens": 26,
    "prompt_tokens": 12,
    "total_tokens": 38
  }
}

For detailed field descriptions, see the API reference.

Text generation for code autocomplete: v1/completions

Request

Here is a sample JSON request body that contains all supported fields:

from openai import OpenAI

client = OpenAI(
    base_url="https://console.arkanecloud.com/",
    api_key=os.environ.get("ARKANE_CLOUD_API_KEY"),
)

for chunk in client.completions.create(
        model="meta-llama/Meta-Llama-3.1-70B-Instruct",
        prompt="Say my name",
        max_tokens=7,
        temperature=0,
        stream=True
):
    print(chunk.choices[0].text)

Response

{
  "id": "cmpl-7iA7iJjj8V2zOkCGvWF2hAkDWBQZe",
  "object": "text_completion",
  "created": 1690759111,
  "choices": [
    {
      "text": "Heisenberg",
      "index": 0,
      "logprobs": null,
      "finish_reason": null
    }
  ],
  "model": "meta-llama/Meta-Llama-3.1-70B-Instruct",
  "system_fingerprint": "fp_44709d6aaa"
}

For detailed field descriptions, see the API reference.

List of models: v1/models

Request

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://console.arkanecloud.com/",
    api_key=os.environ.get("ARKANE_CLOUD_API_KEY"),
)

client.models.list()

Response

{
  "object": "list",
  "data": [
    {
      "id": 'meta-llama/Meta-Llama-3.1-8B-Instruct',
      "object": "model",
      "created": 1724480826,
      "owned_by": 'system'
    },
    {
      "id": 'meta-llama/Meta-Llama-3.1-70B-Instruct',
      "object": "model",
      "created": 1724480826,
      "owned_by": 'system'
    },
  ],
  "object": "list"
}

For detailed field descriptions, see the API reference.

Image generation: v1/images/generations

Request

from openai import OpenAI
import os

client = OpenAI(
    base_url="https://console.arkanecloud.com/",
    api_key=os.environ.get("ARKANE_CLOUD_API_KEY"),
)

completion = client.images.generate(
    model="stability-ai/sdxl",
    prompt="An elephant in a desert",
    response_format="b64_json",
    extra_body={
        "response_extension": "png",
        "width": 512,
        "height": 512,
        "num_inference_steps": 30,
        "seed": -1,
        "negative_prompt": "Giraffes, night sky"
    }
)

print(completion.to_json())

Response

{
  "data": [
    {
      "b64_json": "UklGRg66Ag..."
    }
  ],
  "id": "text2img-0941c39c-..."
}

For detailed field descriptions, see the API reference.