Wan 2.7 (Text-to-Video)

This documentation is valid for the following list of our models:

• alibaba/wan-2-7-t2v

Try in Playground

A state-of-the-art text-to-video generation model designed to produce high-quality, realistic or stylized cinematic videos from prompts, with support for multi-shot composition and synchronized audio generation, offering flexible 720p/1080p output typically ranging from 5 to 15 seconds.

Setup your API Key

If you don’t have an API key for the AI/ML API yet, feel free to use our Quickstart guide.

How to Make a Call

Step-by-Step Instructions

Generating a video using this model involves sequentially calling two endpoints:

• The first one is for creating and sending a video generation task to the server (returns a generation ID).

• The second one is for requesting the generated video from the server using the generation ID received from the first endpoint.

Below, you can find both corresponding API schemas.

API Schemas

Create a video generation task and send it to the server

This endpoint creates and sends a video generation task to the server — and returns its ID.

post

Body

modelstring · enumRequiredPossible values:

promptstringRequired

The text description of the scene, subject, or action to generate in the video.

audio_urlstring · uriOptional

The URL of the audio file. The model will use this audio to generate the video.

aspect_ratiostring · enumOptional

The aspect ratio of the generated video.

Default: 16:9Possible values:

resolutionstring · enumOptional

An enumeration where the short side of the video frame determines the resolution.

Default: 1080pPossible values:

durationinteger · enumOptional

The length of the output video in seconds.

Default: 10Possible values:

negative_promptstringOptional

The description of elements to avoid in the generated video.

shot_typestring · enumOptional

Specifies the shot type of the generated video, that is, whether the video consists of a single continuous shot or multiple switched shots. This parameter takes effect only when "prompt_extend" is set to 'true':

• single: (default) Outputs a single-shot video.
• multi: Outputs a multi-shot video.

Default: singlePossible values:

generate_audiobooleanOptional

Specifies whether to automatically add audio to the generated video. This parameter takes effect only when 'audio_url' is not provided.

Default: true

seedintegerOptional

Varying the seed integer is a way to get different results for the same other request parameters. Using the same value for an identical request will produce similar results. If unspecified, a random number is chosen.

enhance_promptbooleanOptional

Whether to enable prompt expansion.

Default: true

Responses

200Success

application/json

idstringRequired

The ID of the generated video.

Example: 60ac7c34-3224-4b14-8e7d-0aa0db708325

statusstring · enumRequired

The current status of the generation task.

Example: completedPossible values:

post/v2/video/generations

curl -L \
  --request POST \
  --url 'https://api.aimlapi.com/v2/video/generations' \
  --header 'Authorization: Bearer <YOUR_AIMLAPI_KEY>' \
  --header 'Content-Type: application/json' \
  --data '{
      "model": "alibaba/wan-2-7-t2v",
      "prompt": "A menacing evil dragon appears in a distance above the tallest mountain, then rushes toward the camera with its jaws open, revealing massive fangs. We see it’s coming."
    }'

200Success

{
  "id": "60ac7c34-3224-4b14-8e7d-0aa0db708325",
  "status": "completed",
  "video": {
    "url": "https://cdn.aimlapi.com/generations/hedgehog/1759866285599-0cdfb138-c03a-49d4-a601-4f6413e27b15.mp4"
  },
  "error": {
    "name": "text",
    "message": "text"
  },
  "meta": {
    "usage": {
      "credits_used": 120000,
      "usd_spent": 0.06
    }
  }
}

Retrieve the generated video from the server

After sending a request for video generation, this task is added to the queue. This endpoint lets you check the status of a video generation task using its id, obtained from the endpoint described above. If the video generation task status is completed, the response will include the final result — with the generated video URL and additional metadata.

get

Authorizations

AuthorizationstringRequired

Bearer key

Query parameters

generation_idstringRequiredExample: <REPLACE_WITH_YOUR_GENERATION_ID>

Responses

200Success

application/json

idstringRequired

The ID of the generated video.

Example: 60ac7c34-3224-4b14-8e7d-0aa0db708325

statusstring · enumRequired

The current status of the generation task.

Example: completedPossible values:

get/v2/video/generations

curl -L \
  --request GET \
  --url 'https://api.aimlapi.com/v2/video/generations?generation_id=<REPLACE_WITH_YOUR_GENERATION_ID>' \
  --header 'Authorization: Bearer <YOUR_AIMLAPI_KEY>'

200Success

{
  "id": "60ac7c34-3224-4b14-8e7d-0aa0db708325",
  "status": "completed",
  "video": {
    "url": "https://cdn.aimlapi.com/generations/hedgehog/1759866285599-0cdfb138-c03a-49d4-a601-4f6413e27b15.mp4"
  },
  "error": {
    "name": "text",
    "message": "text"
  },
  "meta": {
    "usage": {
      "credits_used": 120000
    }
  }
}

Full Example: Multi-shot

Let’s define a sequence of scenes in the prompt to achieve a more cinematic result. Set the shot_type parameter to multi.

The code below creates a video generation task, then automatically polls the server every 15 seconds until it finally receives the video URL.

Python

import requests
import time

# Insert your AIML API Key instead of <YOUR_AIMLAPI_KEY>:
api_key = "<YOUR_AIMLAPI_KEY>"
base_url = "https://api.aimlapi.com/v2"

# Creating and sending a video generation task to the server
def generate_video():
    url = f"{base_url}/video/generations"
    headers = {
        "Authorization": f"Bearer {api_key}", 
    }

    data = {
        "model": "alibaba/wan-2-7-t2v",
        "prompt": "A cheerful white raccoon runs through a giant sequoia forest. Sunlight streams through the tall trees, soft volumetric light, cinematic camera movement following the raccoon from the side, shallow depth of field, animated film style, 3 seconds. Then close-up of the raccoons face. The raccoon gently raises its head and looks up toward the towering sequoia treetops. Soft light on the fur, expressive eyes, subtle head movement, cinematic close-up, animated film style, 2 seconds. Then first-person view from the raccoon's perspective. Massive sequoia trees sway and rustle in the wind high above. Suddenly, a huge pterodactyl flies across the sky, blurred and partially hidden in mist and haze. Slight handheld camera feel, cinematic motion blur, dramatic atmosphere, animated film style, 4 seconds.",
        "aspect_ratio": "16:9",
        "resolution": "1080p",
        "duration": 10,
        "shot_type": "multi"
    }
 
    response = requests.post(url, json=data, headers=headers)
    if response.status_code >= 400:
        print(f"Error: {response.status_code} - {response.text}")
    else:
        response_data = response.json()
        return response_data
    

# Requesting the result of the task from the server using the generation_id
def get_video(gen_id):
    url = f"{base_url}/video/generations"
    params = {
        "generation_id": gen_id,
    }
    headers = {
        "Authorization": f"Bearer {api_key}", 
        "Content-Type": "application/json"
        }
    response = requests.get(url, params=params, headers=headers)
    return response.json()


def main():
    # Running video generation and getting a task id
    gen_response = generate_video()
    gen_id = gen_response.get("id")
    print("Generation ID:  ", gen_id)

    # Trying to retrieve the video from the server every 15 sec
    if gen_id:
        start_time = time.time()

        timeout = 1000   # 1000 sec = 16 min 40 sec
        while time.time() - start_time < timeout:
            response_data = get_video(gen_id)

            if response_data is None:
                print("Error: No response from API")
                break
        
            status = response_data.get("status")

            if status in ["queued", "generating"]:
                print(f"Status: {status}. Checking again in 15 seconds.")
                time.sleep(15)
            else:
                print("Processing complete:\n", response_data)
                return response_data
   
        print("Timeout reached. Stopping.")
        return None     


if __name__ == "__main__":
    main()

JavaScript

// Insert your AIML API Key instead of <YOUR_AIMLAPI_KEY>
const apiKey = "<YOUR_AIMLAPI_KEY>";
const baseUrl = "https://api.aimlapi.com/v2";
const https = require("https");
const { URL } = require("url");

// Creating and sending a video generation task to the server
function generateVideo(callback) {
    const data = JSON.stringify({
        model: 'alibaba/wan-2-7-t2v',
        prompt: `A cheerful white raccoon runs through a giant sequoia forest. Sunlight streams through the tall trees, soft volumetric light, cinematic camera movement following the raccoon from the side, shallow depth of field, animated film style, 3 seconds. Then close-up of the raccoons face. The raccoon gently raises its head and looks up toward the towering sequoia treetops. Soft light on the fur, expressive eyes, subtle head movement, cinematic close-up, animated film style, 2 seconds. Then first-person view from the raccoon's perspective. Massive sequoia trees sway and rustle in the wind high above. Suddenly, a huge pterodactyl flies across the sky, blurred and partially hidden in mist and haze. Slight handheld camera feel, cinematic motion blur, dramatic atmosphere, animated film style, 4 seconds.`,
        duration: 10,
        aspect_ratio: '16:9'
        resolution: '1080p',
        shot_type: 'multi'
    });

    const url = new URL(`${baseUrl}/video/generations`);
    const options = {
        method: "POST",
        headers: {
            "Authorization": `Bearer ${apiKey}`,
            "Content-Type": "application/json",
            "Content-Length": Buffer.byteLength(data)
        }
    };

    const req = https.request(url, options, (res) => {
        let body = "";
        res.on("data", (chunk) => body += chunk);
        res.on("end", () => {
            if (res.statusCode >= 400) {
                console.error(`Error: ${res.statusCode} - ${body}`);
                callback(null);
            } else {
                const result = JSON.parse(body);
                callback(result);
            }
        });
    });

    req.on("error", (err) => {
        console.error("Request error:", err);
        callback(null);
    });

    req.write(data);
    req.end();
}

// Requesting the result of the task from the server using the generation_id
function getVideo(genId, callback) {
    const url = new URL(`${baseUrl}/video/generations`);
    url.searchParams.append("generation_id", genId);

    const options = {
        method: "GET",
        headers: {
            "Authorization": `Bearer ${apiKey}`,
            "Content-Type": "application/json"
        }
    };

    const req = https.request(url, options, (res) => {
        let body = "";
        res.on("data", (chunk) => body += chunk);
        res.on("end", () => {
            const result = JSON.parse(body);
            callback(result);
        });
    });

    req.on("error", (err) => {
        console.error("Request error:", err);
        callback(null);
    });

    req.end();
}

// Initiates video generation and checks the status every 15 seconds until completion or timeout
function main() {
    generateVideo((genResponse) => {
        if (!genResponse || !genResponse.id) {
            console.error("No generation ID received.");
            return;
        }

        const genId = genResponse.id;
        console.log("Generation ID:", genId);

        const timeout = 1000 * 1000; // 1000 sec = 16 min 40 sec
        const interval = 15 * 1000; // 15 sec
        const startTime = Date.now();

        const checkStatus = () => {
            if (Date.now() - startTime >= timeout) {
                console.log("Timeout reached. Stopping.");
                return;
            }

            getVideo(genId, (responseData) => {
                if (!responseData) {
                    console.error("Error: No response from API");
                    return;
                }

                const status = responseData.status;
        
                if (["queued", "generating"].includes(status)) {
                    console.log(`Status: ${status}. Checking again in 15 seconds.`);
                    setTimeout(checkStatus, interval);
                } else {
                    console.log("Processing complete:\n", responseData);
                }
            });
        };
        checkStatus();
    })
}

main();

Response

{'id': 'QC4qjlUKt8ZedNi7r09LM', 'status': 'queued', 'meta': {'usage': {'credits_used': 3900000, 'usd_spent': 1.95}}}
Generation ID:   QC4qjlUKt8ZedNi7r09LM
Status: queued. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
...
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Status: generating. Checking again in 15 seconds.
Processing complete:
 {'id': 'QC4qjlUKt8ZedNi7r09LM', 'status': 'completed', 'video': {'url': 'https://cdn.aimlapi.com/generations/alligator/1778027467317-6ca89b94-4a86-413b-b1ad-6dccef4daffa.mp4'}}

Processing time: ~ 8 min 23 sec.

Generated video (1920x1080, with sound):

https://drive.google.com/file/d/1IrdYMD0MbYnzwVvfT4ELegPewjf2USXU/viewdrive.google.com