# 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 15 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") 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() ``` {% 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 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 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(); ``` {% 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="" %} --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.aimlapi.com/api-references/video-models/sber-ai/kandinsky5-text-to-video.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.