> For the complete documentation index, see [llms.txt](https://docs.aimlapi.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.aimlapi.com/api-references/video-models/heygen/avatar-v.md).
# HeyGen Avatar V
{% columns %}
{% column width="66.66666666666666%" %}
{% hint style="info" %}
This documentation is valid for the following list of our models:
* `heygen/avatar-v`
{% endhint %}
{% endcolumn %}
{% column width="33.33333333333334%" %} Try in Playground
{% endcolumn %}
{% endcolumns %}
## Model Overview
HeyGen Avatar V is the highest-fidelity HeyGen engine: a talking-avatar video from a script or an audio track, using a HeyGen photo avatar or digital twin. Does not support tools/function calling.
## Setup your API Key
If you don't have an API key yet, use our [Quickstart guide](https://docs.aimlapi.com/quickstart/setting-up).
## How to Make a Call
Step-by-Step Instructions
Generating a video involves sequentially calling two endpoints:
* Create and submit a video generation task. The response contains a generation ID.
* Poll the retrieval endpoint with that generation ID until the status is `completed`.
## API Schemas
### Create a video generation task and send it to the server
### Retrieve the generated video from the server
Poll this endpoint with the `generation_id` returned by the submit request. When the status is `completed`, the response includes the generated video URL.
## 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"]}}}}}}}}}
```
## Code Example
The examples submit a generation task and poll every **15 seconds** until the final result is available.
{% tabs %}
{% tab title="Python" %}
{% code overflow="wrap" %}
```python
import requests
import time
api_key = ""
url = "https://api.aimlapi.com/v2/video/generations"
headers = {
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json",
}
generation = requests.post(url, headers=headers, json={'model': 'heygen/avatar-v', 'avatar_id': ''})
generation.raise_for_status()
generation_id = generation.json()["id"]
while True:
result = requests.get(
url,
headers=headers,
params={"generation_id": generation_id},
)
result.raise_for_status()
data = result.json()
if data.get("status") not in ("queued", "generating"):
print(data)
break
time.sleep(15)
```
{% endcode %}
{% endtab %}
{% tab title="JavaScript" %}
{% code overflow="wrap" %}
```javascript
const apiKey = "";
const url = "https://api.aimlapi.com/v2/video/generations";
const headers = {
"Authorization": `Bearer ${apiKey}`,
"Content-Type": "application/json",
};
const generation = await fetch(url, {
method: "POST",
headers,
body: JSON.stringify({
"model": "heygen/avatar-v",
"avatar_id": ""
}),
});
const { id: generationId } = await generation.json();
while (true) {
const response = await fetch(
`${url}?generation_id=${encodeURIComponent(generationId)}`,
{ headers },
);
const data = await response.json();
if (!["queued", "generating"].includes(data.status)) {
console.log(data);
break;
}
await new Promise((resolve) => setTimeout(resolve, 15000));
}
```
{% endcode %}
{% endtab %}
{% endtabs %}
Response
{% code overflow="wrap" %}
```json
{
"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": "",
"message": ""
},
"meta": {
"usage": {
"credits_used": 120000,
"usd_spent": 0.06
}
},
"model": "heygen/avatar-v"
}
```
{% endcode %}
---
# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.
## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.
Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:
```
GET https://docs.aimlapi.com/api-references/video-models/heygen/avatar-v.md?ask=&goal=
```
`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.
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.