ai-model-wechat▌
tencentcloudbase/skills · updated Apr 8, 2026
AI text generation and streaming for WeChat Mini Programs via wx.cloud.extend.AI.
- ›Supports two methods: generateText() for non-streaming responses and streamText() for real-time streaming with callback support ( onText , onEvent , onFinish )
- ›Built-in models include Hunyuan (recommended: hunyuan-2.0-instruct-20251111 ) and DeepSeek (recommended: deepseek-v3.2 )
- ›API differs from JS/Node SDK: generateText() returns raw model response; streamText() requires parameters wrapped in a data o
When to use this skill
Use this skill for calling AI models in WeChat Mini Program using wx.cloud.extend.AI.
Use it when you need to:
- Integrate AI text generation in a Mini Program
- Stream AI responses with callback support
- Call Hunyuan models from WeChat environment
Do NOT use for:
- Browser/Web apps → use
ai-model-webskill - Node.js backend or cloud functions → use
ai-model-nodejsskill - Image generation → use
ai-model-nodejsskill (not available in Mini Program) - HTTP API integration → use
http-apiskill
Available Providers and Models
CloudBase provides these built-in providers and models:
| Provider | Models | Recommended |
|---|---|---|
hunyuan-exp |
hunyuan-turbos-latest, hunyuan-t1-latest, hunyuan-2.0-thinking-20251109, hunyuan-2.0-instruct-20251111 |
✅ hunyuan-2.0-instruct-20251111 |
deepseek |
deepseek-r1-0528, deepseek-v3-0324, deepseek-v3.2 |
✅ deepseek-v3.2 |
Prerequisites
- WeChat base library 3.7.1+
- No extra SDK installation needed
Initialization
// app.js
App({
onLaunch: function() {
wx.cloud.init({ env: "<YOUR_ENV_ID>" });
}
})
generateText() - Non-streaming
⚠️ Different from JS/Node SDK: Return value is raw model response.
const model = wx.cloud.extend.AI.createModel("hunyuan-exp");
const res = await model.generateText({
model: "hunyuan-2.0-instruct-20251111", // Recommended model
messages: [{ role: "user", content: "你好" }],
});
// ⚠️ Return value is RAW model response, NOT wrapped like JS/Node SDK
console.log(res.choices[0].message.content); // Access via choices array
console.log(res.usage); // Token usage
streamText() - Streaming
⚠️ Different from JS/Node SDK: Must wrap parameters in data object, supports callbacks.
const model = wx.cloud.extend.AI.createModel("hunyuan-exp");
// ⚠️ Parameters MUST be wrapped in `data` object
const res = await model.streamText({
data: { // ⚠️ Required wrapper
model: "hunyuan-2.0-instruct-20251111", // Recommended model
messages: [{ role: "user", content: "hi" }]
},
onText: (text) => { // Optional: incremental text callback
console.log("New text:", text);
},
onEvent: ({ data }) => { // Optional: raw event callback
console.log("Event:", data);
},
onFinish: (fullText) => { // Optional: completion callback
console.log("Done:", fullText);
}
});
// Async iteration also available
for await (let str of res.textStream) {
console.log(str);
}
// Check for completion with eventStream
for await (let event of res.eventStream) {
console.log(event);
if (event.data === "[DONE]") { // ⚠️ Check for [DONE] to stop
break;
}
}
Error Handling Pattern
const model = wx.cloud.extend.AI.createModel("deepseek");
try {
const res = await model.generateText({
model: "deepseek-v3.2",
messages: [{ role: "user", content: "生成一段欢迎文案" }],
});
console.log(res.choices[0].message.content);
} catch (error) {
console.error("Mini Program AI request failed", error);
}
API Comparison: JS/Node SDK vs WeChat Mini Program
| Feature | JS/Node SDK | WeChat Mini Program |
|---|---|---|
| Namespace | app.ai() |
wx.cloud.extend.AI |
| generateText params | Direct object | Direct object |
| generateText return | { text, usage, messages } |
Raw: { choices, usage } |
| streamText params | Direct object | ⚠️ Wrapped in data: {...} |
| streamText return | { textStream, dataStream } |
{ textStream, eventStream } |
| Callbacks | Not supported | onText, onEvent, onFinish |
| Image generation | Node SDK only | Not available |
Type Definitions
streamText() Input
interface WxStreamTextInput {
data: { // ⚠️ Required wrapper object
model: string;
messages: Array<{
role: "user" | "system" | "assistant";
content: string;
}>;
};
onText?: (text: string) => void; // Incremental text callback
onEvent?: (prop: { data: string }) => void; // Raw event callback
onFinish?: (text: string) => void; // Completion callback
}
streamText() Return
interface WxStreamTextResult {
textStream: AsyncIterable<string>; // Incremental text stream
eventStream: AsyncIterable<{ // Raw event stream
event?Discussion
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Ratings
4.4★★★★★67 reviews- ★★★★★Daniel Thomas· Dec 28, 2024
We added ai-model-wechat from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Isabella Jain· Dec 24, 2024
I recommend ai-model-wechat for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Neel Perez· Dec 24, 2024
ai-model-wechat reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Ava Brown· Dec 12, 2024
Useful defaults in ai-model-wechat — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Tariq Khan· Dec 4, 2024
ai-model-wechat is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Amina Rahman· Nov 23, 2024
Solid pick for teams standardizing on skills: ai-model-wechat is focused, and the summary matches what you get after install.
- ★★★★★Kabir Garcia· Nov 19, 2024
ai-model-wechat reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Ava Taylor· Nov 19, 2024
I recommend ai-model-wechat for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Neel Malhotra· Nov 15, 2024
We added ai-model-wechat from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Daniel Sanchez· Nov 3, 2024
Useful defaults in ai-model-wechat — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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