PiAPI/Midjourney-API

Midjourney API

Model Page: Midjourney API

This model card illustartes the steps to use Midjourney API's endpoint. You can also check out other model cards:

• Faceswap API
• Suno API
• Dream Machine API

Model Information

Renowned for its exceptional text-to-image generative AI capabilities, Midjourney is a preferred tool among graphic designers, photographers, and creatives aiming to explore AI-driven artistry. Despite the absence of an official API from Midjourney, PiAPI has introduced the unofficial Midjourney API, empowering developers to incorporate this cutting-edge text-to-image model into their AI applications.

Usage Steps

Below we share the code snippets on how to use Midjourney API's upscale endpoint.

• The programming language is Python
• The origin task ID should be the task ID of the fetched imagine endpoint

Create an upscale task ID

  import http.client
  
  conn = http.client.HTTPSConnection("api.piapi.ai")
  
  payload = "{\n  \"origin_task_id\": \"9c6796dd*********1e7dfef5203b\",\n  \"index\": \"1\",\n  \"webhook_endpoint\": \"\",\n  \"webhook_secret\": \"\"\n}"
  
  headers = {
      'X-API-Key': "{{x-api-key}}",             //Insert your API Key here
      'Content-Type': "application/json",
      'Accept': "application/json"
  }
  
  conn.request("POST", "/mj/v2/upscale", payload, headers)
  
  res = conn.getresponse()
  data = res.read()
  
  print(data.decode("utf-8"))

Retrieve the task ID

  {
      "code": 200,
      "data": {
          "task_id": :3be7e0b0****************d1a725da0b1d"      //Record the taskID provided in your response terminal
      },
      "message": "success"
  }

Insert the upscale task ID into the fetch endpoint

  import http.client
  
  conn = http.client.HTTPSConnection("api.piapi.ai")
  
  payload = "{\n  \"task_id\": \"3be7e0b0****************d1a725da0b1d\"\n}" /Replace the task ID with your task ID
  
  headers = {
      'Content-Type': "application/json",
      'Accept': "application/json"
  }
  
  conn.request("POST", "/mj/v2/fetch", payload, headers)
  
  res = conn.getresponse()
  data = res.read()
  
  print(data.decode("utf-8"))

For fetch endpoint responses - Refer to our documentation for more detailed information.

Contact us

Contact us at contact@piapi.ai for any inquires.