API reference · WeChat Channels
wechat-channels/video-metrics
Integrate this model through SandBase's unified API, with production-ready schemas and examples.
Production endpoint
Send your first request
OpenAI-compatible endpoint with unified authentication and usage tracking.
POST
https://api.sandbase.ai/v1/api/wechat-channels/video-metricsModel ID
wechat-channels/video-metrics01
Input Schema
3 parameters · 1 required · 2 optional
| Parameter | Type | Required | Description |
|---|---|---|---|
objectId | string | Required | WeChat Channels video object id used to fetch interaction metrics. |
last_buffer | string | Optional | Pagination buffer returned by the previous WeChat Channels metrics response. Leave it empty for the first page. For this POST endpoint, send it in an application/x-www-form-urlencoded form body. |
objectNonceId | string | Optional | Optional WeChat Channels object nonce id. |
02
Output Schema
| Field | Type | Description |
|---|---|---|
id | string | Unique identifier for the generation task |
status | string | Task status: pending, running, completed, failed, timeout |
model | string | Model used for the generation |
outputs | array | Array of output items |
outputs[].url | string | URL of the generated artifact |
outputs[].content_type | string | MIME type (e.g. image/png, video/mp4) |
error | object | null | Error details if failed, null on success |
error.type | string | Machine-readable error type code |
error.message | string | Human-readable error description |
03
Code Examples
Ready-to-run snippets
const apiKey = process.env.SANDBASE_API_KEY;
const response = await fetch("https://api.sandbase.ai/v1/api/wechat-channels/video-metrics", {
method: "POST",
headers: {
Authorization: `Bearer ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"objectId": "15042116979764234697",
"objectNonceId": "13454967799950666727_0_0_4_32_0_45d03c48-d38a-11f1-8fe5-9b7987977b23"
}),
});
if (!response.ok) throw new Error(await response.text());
console.log(await response.json());