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license: mit
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---
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license: mit
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---
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# Midjourney API
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**Model Page:** [Midjourney API](https://piapi.ai/midjourney-api)
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This model card illustartes the steps to use Midjourney API's endpoint.
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You can also check out other model cards:
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- [Faceswap API](https://huggingface.co/PiAPI/Faceswap-API)
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- [Suno API](https://huggingface.co/PiAPI/Suno-API)
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- [Dream Machine API](https://huggingface.co/PiAPI/Dream-Machine-API)
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**Model Information**
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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.
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## Usage Steps
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Below we share the code snippets on how to use Midjourney API's upscale endpoint.
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- The programming language is Python
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- The origin task ID should be the task ID of the fetched imagine endpoint
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**Create an upscale task ID**
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<pre><code class="language-python">
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<span class="hljs-keyword">import</span> http.client
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conn = http.client.HTTPSConnection(<span class="hljs-string">"api.piapi.ai"</span>)
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payload = <span class="hljs-string">"{\n \"origin_task_id\": \"9c6796dd*********1e7dfef5203b\",\n \"index\": \"1\",\n \"webhook_endpoint\": \"\",\n \"webhook_secret\": \"\"\n}"</span>
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headers = {
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<span class="hljs-built_in">'X-API-Key': "{{x-api-key}}"</span>, //Insert your API Key here
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<span class="hljs-built_in">'Content-Type': "application/json"</span>,
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<span class="hljs-built_in">'Accept': "application/json"</span>
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}
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conn.request("POST", "/mj/v2/upscale", payload, headers)
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res = conn.getresponse()
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data = res.read()
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<span class="hljs-keyword">print</span>(data.decode("utf-8"))
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</code></pre>
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**Retrieve the task ID**
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<pre><code class="language-python">
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{
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<span class="hljs-built_in">"code"</span>: 200,
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<span class="hljs-built_in">"data"</span>: {
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<span class="hljs-built_in">"task_id"</span>: :3be7e0b0****************d1a725da0b1d" //Record the taskID provided in your response terminal
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},
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<span class="hljs-built_in">"message"</span>: "success"
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}
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</code></pre>
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**Insert the upscale task ID into the fetch endpoint**
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<pre><code class="language-python">
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<span class="hljs-keyword">import</span> http.client
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conn = http.client.HTTPSConnection(<span class="hljs-string">"api.piapi.ai"</span>)
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payload = <span class="hljs-string">"{\n \"task_id\": \"3be7e0b0****************d1a725da0b1d\"\n}"</span> /Replace the task ID with your task ID
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headers = {
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<span class="hljs-built_in">'Content-Type': "application/json"</span>,
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<span class="hljs-built_in">'Accept': "application/json"</span>
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}
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conn.request("POST", "/mj/v2/fetch", payload, headers)
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res = conn.getresponse()
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data = res.read()
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<span class="hljs-keyword">print</span>(data.decode("utf-8"))
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</code></pre>
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**For fetch endpoint responses** - Refer to our [documentation](https://piapi.ai/docs) for more detailed information.
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<br>
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## Contact us
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Contact us at <a href="mailto:[email protected]">[email protected]</a> for any inquires.
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<br>
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