## Basic model info

- Model name: midjourney/midjourney v7-reverse
- Model description: Generate and edit images with Midjourney v7 via reverse-engineered channel.
- Endpoint name: action


## Model schema

The model schema is defined in the OpenAPI schema: [OpenAPI Schema](https://oapi.sunra.ai/main/midjourney/v7-reverse/latest.json)

### Model input schema

The model input schema is:



```json
{
  "properties": {
    "custom_id": {
      "description": "The custom ID of the action to be performed on the image",
      "title": "Custom Id",
      "type": "string",
      "x-sr-order": 102
    },
    "task_id": {
      "description": "Task ID from the last image generation result which needs to be processed",
      "title": "Task Id",
      "type": "string",
      "x-sr-order": 101
    }
  },
  "required": [
    "task_id",
    "custom_id"
  ],
  "title": "ImageActionInput",
  "type": "object"
}
```



### Model output schema

The model output schema is:



```json
{
  "properties": {
    "action_type": {
      "title": "Action Type",
      "type": "string"
    },
    "images": {
      "items": {
        "properties": {
          "actions": {
            "items": {
              "properties": {
                "custom_id": {
                  "title": "Custom Id",
                  "type": "string"
                },
                "label": {
                  "title": "Label",
                  "type": "string"
                },
                "task_id": {
                  "title": "Task Id",
                  "type": "string"
                }
              },
              "required": [
                "task_id",
                "custom_id",
                "label"
              ],
              "title": "ImageS1OutputActionItem",
              "type": "object"
            },
            "title": "Actions",
            "type": "array"
          },
          "content_type": {
            "description": "The mime type of the file.",
            "title": "Content Type",
            "type": "string"
          },
          "file_name": {
            "description": "The name of the file. It will be auto-generated if not provided.",
            "title": "File Name",
            "type": "string"
          },
          "file_size": {
            "description": "The size of the file in bytes.",
            "title": "File Size",
            "type": "integer"
          },
          "url": {
            "description": "The URL where the file can be downloaded from.",
            "title": "Url",
            "type": "string"
          }
        },
        "required": [
          "content_type",
          "file_name",
          "file_size",
          "url",
          "actions"
        ],
        "title": "ImageS1ImageOutputItem",
        "type": "object"
      },
      "title": "Images",
      "type": "array"
    },
    "mode": {
      "title": "Mode",
      "type": "string"
    },
    "units_used": {
      "title": "Units Used",
      "type": "integer"
    }
  },
  "required": [
    "images",
    "action_type",
    "mode",
    "units_used"
  ],
  "title": "ImageS1Output",
  "type": "object"
}
```



## Example inputs and outputs

Use the following example inputs and outputs to understand the model.

### Input example



```json
{
  "custom_id": "",
  "task_id": ""
}
```



### Output example



```json
{
}
```



## Model code examples

### JavaScript



```javascript
import { sunra } from "@sunra/client";

const result = await sunra.subscribe("midjourney/v7-reverse/action", {
  input: {
  	task_id: '',
  	custom_id: ''
  },
  logs: true,
  onQueueUpdate: (update) => {
    console.log(`Status Update: ${update.status}, Request ID: ${update.request_id}`);
  },
});
console.log(result.data);
console.log(result.requestId);
```



### Python



```python
import sunra_client

result = sunra_client.subscribe(
    "midjourney/v7-reverse/action",
    arguments={
        "task_id": "",
        "custom_id": ""
    },
    with_logs=True,
    on_enqueue=print,
    on_queue_update=print,
)
print(result)
```



### Java



```java
import ai.sunra.client.*;
import java.util.Map;
import com.google.gson.JsonObject;

var client = SunraClient.withEnvCredentials();

var response = client.subscribe(
    "midjourney/v7-reverse/action",
    SubscribeOptions.<JsonObject>builder()
        .input(Map.of(
            "task_id", "",
            "custom_id", ""))
        .resultType(JsonObject.class)
        .onQueueUpdate(update -> System.out.printf(
            "\nStatus Update: %s, Request ID: %s%n",
            update.getStatus(),
            update.getRequestId()
        ))
        .logs(true)
        .build()
);

System.out.println("Completed!");
System.out.println(response.getData());
  
```



### Kotlin



```kotlin
import ai.sunra.client.kt.*
import com.google.gson.JsonObject

val client = createSunraClient()

val response = client.subscribe<JsonObject>(
    endpointId = "midjourney/v7-reverse/action",
    input = mapOf(
            "task_id" to "",
            "custom_id" to ""),
    options = ai.sunra.client.kt.SubscribeOptions(logs = true),
    onUpdate = { update ->
        println("\nStatus Update: ${update.status}, Request ID: ${update.requestId}")
    }
)

println("Completed!")
println(response.data)
  
```



### Curl



```bash

curl --request POST \
  --url https://api.sunra.ai/v1/queue/midjourney/v7-reverse/action \
  --header "Authorization: Key $SUNRA_KEY" \
  --header "Content-Type: application/json" \
  --data '{"task_id":"","custom_id":""}'
    
```



## Model readme

>