API reference · WeChat MP

wechat-mp/v2/account-articles

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/account-articles
01

Input Schema

5 parameters · 1 required · 4 optional

ParameterTypeRequiredDescription
usernamestringRequiredOfficial account `gh_username` (`gh_…`). E.g. `gh_363b924965e9` · Max length: 64
rawbooleanOptionalOptional, default True. True=raw; False=simplified parsing.
offsetunionOptionalOptional pagination cursor (base64), **leave empty for the first page**; for the next page pass `next_offset` from the previous response. E.g. `CAMQChiS5KfRBiAKOJLkp9EGQABIAVgAYABwAQ==`
page_sizeintegerOptionalOptional, default 20, range **10-20**. Articles per page. · Min: 10 · Max: 20
item_show_typeunionOptionalOptional content tab (matches the "Articles / Videos / Audios" tabs on the account homepage). Empty / `0`=articles (default), `5`=videos, `7`=audios, `8`=image-text posts. Omitting it = articles, behavior unchanged.
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/account-articles"
  }),
});

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