# Kandinsky 5 (Text-to-Video) {% columns %} {% column width="66.66666666666666%" %} {% hint style="info" %} This documentation is valid for the following list of our models: * `sber-ai/kandinsky5-t2v` {% endhint %} {% endcolumn %} {% column width="33.33333333333334%" %} Try in Playground {% endcolumn %} {% endcolumns %} A diffusion model designed for text-to-video generation with a resolution slightly above standard definition (SD). ## 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](https://docs.aimlapi.com/quickstart/setting-up). ## 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 You can generate a video using this API. In the basic setup, you only need a prompt.\ This endpoint creates and sends a video generation task to the server — and returns a generation ID. ## POST /v2/video/generations > ```json {"openapi":"3.0.0","info":{"title":"AIML API","version":"1.0.0"},"servers":[{"url":"https://api.aimlapi.com"}],"paths":{"/v2/video/generations":{"post":{"operationId":"_v2_video_generations","requestBody":{"required":true,"content":{"application/json":{"schema":{"type":"object","properties":{"model":{"type":"string","enum":["sber-ai/kandinsky5-t2v"]},"prompt":{"type":"string","description":"The text description of the scene, subject, or action to generate in the video."},"aspect_ratio":{"type":"string","enum":["3:2","1:1","2:3"],"default":"3:2","description":"The aspect ratio of the generated video."},"duration":{"type":"integer","description":"The length of the output video in seconds.","enum":[5,10],"default":"5"},"num_inference_steps":{"type":"integer","default":30,"description":"Number of inference steps for sampling. Higher values give better quality but take longer."}},"required":["model","prompt"],"title":"sber-ai/kandinsky5-t2v"}}}},"responses":{"200":{"content":{"application/json":{"schema":{"type":"object","properties":{"id":{"type":"string","description":"The ID of the generated video."},"status":{"type":"string","enum":["queued","generating","completed","error"],"description":"The current status of the generation task."},"video":{"type":"object","nullable":true,"properties":{"url":{"type":"string","format":"uri","description":"The URL where the file can be downloaded from."}},"required":["url"]},"error":{"type":"object","nullable":true,"properties":{"name":{"type":"string"},"message":{"type":"string"}},"required":["name","message"],"description":"Description of the error, if any."},"meta":{"type":"object","nullable":true,"properties":{"usage":{"type":"object","nullable":true,"properties":{"credits_used":{"type":"number","description":"The number of tokens consumed during generation."}},"required":["credits_used"]}},"description":"Additional details about the generation."}},"required":["id","status"]}}}}}}}}} ``` ### 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 /v2/video/generations > ```json {"openapi":"3.0.0","info":{"title":"AIML API","version":"1.0.0"},"servers":[{"url":"https://api.aimlapi.com"}],"security":[{"access-token":[]}],"components":{"securitySchemes":{"access-token":{"scheme":"bearer","bearerFormat":"","type":"http","description":"Bearer key","in":"header"}}},"paths":{"/v2/video/generations":{"get":{"operationId":"_v2_video_generations","parameters":[{"name":"generation_id","required":true,"in":"query","schema":{"type":"string"}}],"responses":{"200":{"content":{"application/json":{"schema":{"type":"object","properties":{"id":{"type":"string","description":"The ID of the generated video."},"status":{"type":"string","enum":["queued","generating","completed","error"],"description":"The current status of the generation task."},"video":{"type":"object","nullable":true,"properties":{"url":{"type":"string","format":"uri","description":"The URL where the file can be downloaded from."}},"required":["url"]},"error":{"type":"object","nullable":true,"properties":{"name":{"type":"string"},"message":{"type":"string"}},"required":["name","message"],"description":"Description of the error, if any."},"meta":{"type":"object","nullable":true,"properties":{"usage":{"type":"object","nullable":true,"properties":{"credits_used":{"type":"number","description":"The number of tokens consumed during generation."}},"required":["credits_used"]}},"description":"Additional details about the generation."}},"required":["id","status"]}}}}}}}}} ``` ## Full Example: Generating and Retrieving the Video From the Server The code below creates a video generation task, then automatically polls the server every **10** seconds until it finally receives the video URL. {% tabs %} {% tab title="Python" %} {% code overflow="wrap" %} ```python import requests import time # Insert your AI/ML API key instead of : api_key = "" # Creating and sending a video generation task to the server def generate_video(): url = "https://api.aimlapi.com/v2/generate/video/pixverse/generation" headers = { "Authorization": f"Bearer {api_key}", } data = { "model": "sber-ai/kandinsky5-distill-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.", "resolution": "1080p", "duration": 5 } 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() print(response_data) return response_data # Requesting the result of the task from the server using the generation_id def get_video(gen_id): url = "https://api.aimlapi.com/v2/generate/video/pixverse/generation" 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(): # Generate video gen_response = generate_video() gen_id = gen_response.get("id") print("Generation ID: ", gen_id) # Try to retrieve the video from the server every 10 sec if gen_id: start_time = time.time() timeout = 600 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") print("Status:", status) if status == "waiting" or status == "active" or status == "queued" or status == "generating": print("Still waiting... Checking again in 10 seconds.") time.sleep(10) else: print("Processing complete:\n", response_data) return response_data print("Timeout reached. Stopping.") return None if __name__ == "__main__": main() ``` {% endcode %} {% endtab %} {% tab title="JavaScript" %} {% code overflow="wrap" %} ```javascript // Insert your AIML API Key instead of const apiKey = ""; 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: "sber-ai/kandinsky5-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. `, // duration: 5, }); 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 10 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 const interval = 10 * 1000; // 10 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; console.log("Status:", status); if (["waiting", "active", "queued", "generating"].includes(status)) { console.log("Still waiting... Checking again in 10 seconds."); setTimeout(checkStatus, interval); } else { console.log("Processing complete:\n", responseData); } }); }; checkStatus(); }); } main(); ``` {% endcode %} {% endtab %} {% endtabs %}
Response {% code overflow="wrap" %} ```json5 {'id': '1fe4344e-3d44-4bf8-9f04-0ac4bb312eec:pixverse/v5/text-to-video', 'status': 'queued', 'meta': {'usage': {'tokens_used': 840000}}} Generation ID: 1fe4344e-3d44-4bf8-9f04-0ac4bb312eec:pixverse/v5/text-to-video Status: generating Still waiting... Checking again in 10 seconds. Status: generating Still waiting... Checking again in 10 seconds. Status: generating Still waiting... Checking again in 10 seconds. Status: generating Still waiting... Checking again in 10 seconds. Status: generating Still waiting... Checking again in 10 seconds. Status: generating Still waiting... Checking again in 10 seconds. Status: generating Still waiting... Checking again in 10 seconds. Status: completed Processing complete:\n {'id': '1fe4344e-3d44-4bf8-9f04-0ac4bb312eec:pixverse/v5/text-to-video', 'status': 'completed', 'video': {'url': 'https://cdn.aimlapi.com/eagle/files/penguin/xK3kbIC5S0pR_oEU4Uw1Q_output.mp4', 'content_type': 'video/mp4', 'file_name': 'output.mp4', 'file_size': 6274330}} ``` {% endcode %}
**Processing time**: \~2 min 28 sec. **Generated Video** (768x512, without sound): {% embed url="" %}