## Basic model info - Model name: reve/reve reve-image - Model description: Reve Image creates, edits and remixes images with strong prompt adherence and typography, via the official Reve API. - Endpoint name: remix ## Model schema The model schema is defined in the OpenAPI schema: [OpenAPI Schema](https://oapi.sunra.ai/main/reve/reve-image/latest.json) ### Model input schema The model input schema is: ```json { "description": "Input schema for Reve Image remix generation with reference images.", "properties": { "prompt": { "description": "The prompt describing the image to generate from the reference images.", "title": "Prompt", "type": "string", "x-sr-order": 200 }, "aspect_ratio": { "default": "3:2", "description": "Aspect ratio of the generated image.", "enum": [ "16:9", "9:16", "1:1", "4:3", "3:4", "3:2", "2:3" ], "title": "Aspect Ratio", "type": "string", "x-sr-order": 401 }, "images": { "description": "Reference image URLs, up to 6. Each must be at least 100x100 pixels.", "items": { "anyOf": [ { "format": "uri", "maxLength": 2083, "minLength": 1, "type": "string" }, { "type": "string" } ] }, "maxItems": 6, "minItems": 1, "title": "Images", "type": "array", "x-sr-order": 301 } }, "required": [ "prompt", "images" ], "title": "RemixInput", "type": "object" } ``` ### Model output schema The model output schema is: ```json { "properties": { "image": { "properties": { "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" ], "title": "SunraFile", "type": "object" } }, "required": [ "image" ], "title": "ImageOutput", "type": "object" } ``` ## Example inputs and outputs Use the following example inputs and outputs to understand the model. ### Input example ```json { "prompt": "", "aspect_ratio": "3:2", "images": [ ] } ``` ### Output example ```json { } ``` ## Model code examples ### JavaScript ```javascript import { sunra } from "@sunra/client"; const result = await sunra.subscribe("reve/reve-image/remix", { input: { prompt: '', images: [], aspect_ratio: '3:2' }, 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( "reve/reve-image/remix", arguments={ "prompt": "", "images": [], "aspect_ratio": "3:2" }, 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( "reve/reve-image/remix", SubscribeOptions.builder() .input(Map.of( "prompt", "", "images", , "aspect_ratio", "3:2")) .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( endpointId = "reve/reve-image/remix", input = mapOf( "prompt" to "", "images" to , "aspect_ratio" to "3:2"), 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/reve/reve-image/remix \ --header "Authorization: Key $SUNRA_KEY" \ --header "Content-Type: application/json" \ --data '{"prompt":"","images":[],"aspect_ratio":"3:2"}' ``` ## Model readme >