Integrate ChatGPT & Stable Diffusion into Your WeChat App in 1 Minute

This tutorial shows how to quickly integrate ChatGPT and Stable Diffusion AIGC models into a WeChat public account or mini‑program using the AIGCaaS platform, covering registration, API Explorer usage, code customization, asynchronous handling, and deployment with Python Flask.

Programmer DD
Programmer DD
Programmer DD
Integrate ChatGPT & Stable Diffusion into Your WeChat App in 1 Minute

1‑Minute ChatGPT Integration

Register and log in to the AIGCaaS website, then open the API Explorer, select the "Chatbot" category, choose the ChatGPT application, and pick the Chat Completion interface. Fill in the required JSON parameters (e.g., [{"role":"user","content":"Hello"}]) and click the online call button to send the request.

After a short wait, the response appears. To enable streaming, add stream in the streaming input field.

Copy the provided example code, replace the placeholder secret ID and key on lines 12‑13 with your own credentials, and run the script locally. Adjust dependencies as needed for your language.

1‑Minute Stable Diffusion Integration

Stable Diffusion generates images from text prompts. In the API Explorer, select the "Image Generation" category and choose a scene such as "Open Journey". Enter a descriptive prompt (e.g., "1girl, white hair, golden eyes, detailed sky") and send the request.

The generated images are displayed; different models produce varied styles, including anime‑style results.

Copy the example code, replace the secret information on lines 13‑14, and run it locally to download the generated image via the returned URL.

WeChat Public Account Integration (Python Flask)

Use Flask as the backend framework. The server receives XML messages from WeChat, extracts the user text, and forwards it to the ChatGPT API. Responses are wrapped in XML and sent back to the user.

# coding:utf-8
import os, time, json, redis, random, base64, hashlib, logging, requests, xmltodict, urllib.parse, urllib.request
from flask import Flask, request, abort
# ... (rest of the code as shown in the source, kept inside <code> tags) ...

The implementation includes asynchronous handling with a thread pool to avoid WeChat's 5‑second timeout. If the AI response takes longer, the user receives a friendly prompt to reply "continue" later to fetch the result.

Summary

The guide demonstrates how to obtain various AIGC services—ChatGPT, Stable Diffusion, etc.—in under a minute and integrate them with a WeChat public account using Python Flask. The same approach can be adapted for mini‑programs or other platforms, leveraging AIGCaaS's ready‑to‑use APIs.

ChatGPT integration screenshot
ChatGPT integration screenshot
ChatGPT request screenshot
ChatGPT request screenshot
Stable Diffusion example image
Stable Diffusion example image
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PythonChatGPTStable DiffusionFlaskAIGCWeChat
Programmer DD
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Programmer DD

A tinkering programmer and author of "Spring Cloud Microservices in Action"

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