API reference · WeChat Channels

wechat-channels/v2/collection-videos

Integrate this model through SandBase's unified API, with production-ready schemas and examples.

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OpenAI-compatible endpoint with unified authentication and usage tracking.

POSThttps://api.sandbase.ai/v1/run
Model IDwechat-channels/v2/collection-videos
01

Input Schema

6 parameters · 1 required · 5 optional

ParameterTypeRequiredDescription
topic_idstringRequiredCollection ID (numeric, from topic_id of fetch_user_collections) · Max length: 32
rawbooleanOptionalOptional, default True. True=raw response; False=simplified parsed structure (recommended for media download).
topicunionOptionalCollection name (optional, improves hit rate)
usernameunionOptionalOptional, creator finder username (`v2_…@finder` format), improves hit rate.
topic_typeintegerOptionalOptional, collection type, default 16 (align with the collection's `topic_type` from `fetch_user_collections`). · Min: 0 · Max: 1000
last_bufferunionOptionalOptional pagination cursor (base64), **leave empty for the first page**; when `down_continue` is truthy, pass the previous page's `last_buffer`.
02

Output Schema

FieldTypeDescription
idstringUnique identifier for the generation task
statusstringTask status: pending, running, completed, failed, timeout
modelstringModel used for the generation
outputsarrayArray of output items
outputs[].urlstringURL of the generated artifact
outputs[].content_typestringMIME type (e.g. image/png, video/mp4)
errorobject | nullError details if failed, null on success
error.typestringMachine-readable error type code
error.messagestringHuman-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/run", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "wechat-channels/v2/collection-videos"
  }),
});

if (!response.ok) throw new Error(await response.text());
console.log(await response.json());