API reference · WeChat MP

wechat-mp/v2/comment-replies

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

APISynchronousOpen model
Production endpoint

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OpenAI-compatible endpoint with unified authentication and usage tracking.

POSThttps://api.sandbase.ai/v1/run
Model IDwechat-mp/v2/comment-replies
01

Input Schema

5 parameters · 1 required · 4 optional

ParameterTypeRequiredDescription
urlstringRequiredWeChat MP article URL (`https://mp.weixin.qq.com/s/…`). E.g. `http://mp.weixin.qq.com/s?__biz=Mzk3NTA0MzM5NA==&mid=2247483745&idx=1&sn=3f34e768cf457a501038991ed30be1f4#rd` · Max length: 2048
rawbooleanOptionalOptional, default True. True=full raw reply objects; False=simplified replies.
offsetintegerOptionalOptional, default 0 (>=0). Reply pagination offset; 0 for the first page, pass `next_offset` from the previous response when `has_more=true`. Ignored when `all_pages=true`. · Min: 0
all_pagesbooleanOptionalOptional, default False. When True, ignores `offset` and fetches **all** replies at once (the response omits the `offset` / `next_offset` / `has_more` pagination fields).
content_idunionOptionalOptional (numeric). `content_id` of the target first-level comment, from `$.data.comments[N].content_id` of the `fetch_article_comments` response; **defaults to the first comment that has replies when omitted**. E.g. `12109128638545265979`
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-mp/v2/comment-replies"
  }),
});

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