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Developing a Neighborhood Idle Item Recycling Mini Program Using CloudBase AI CLI

This article will use an example project of a neighborhood idle item recycling mini program to detail how to use CloudBase AI CLI for full-stack development, from environment preparation to final deployment, providing a step-by-step guide on how to use the AI programming tool to quickly build a complete WeChat mini program.

🎯 Project Background​

In the fast-paced modern life, we often have unused items: books that have been read, out-of-season clothes, upgraded digital products... These items are frequently forgotten in corners, taking up space and wasting resources. At the same time, we also need certain items but do not want to spend a fortune to buy new ones.

Based on this pain point, we designed an example project of a neighborhood idle item recycling platform, demonstrating how to revitalize unused items within the community—environmentally friendly, economical, and enhancing neighborhood relationships.

🏗️ Technical Architecture Design​

Overall Architecture​

Core Functional Modules​

🚀 Prepare the Development Environment​

1. Prepare the Basic Environment​

First, we need to prepare the development environment:

Download WeChat Developer Tools

Register Mini Program

2. Install CloudBase AI CLI​

CloudBase AI CLI is a unified AI programming tool management platform developed and launched by Tencent Cloud, supporting multiple AI models, enabling us to perform full-stack development using natural language.

One-click installation (Recommended)

# WSL for Mac/Linux/Windows
curl https://static.cloudbase.net/cli/install/install.sh -fsS | bash

# Windows PowerShell
irm https://static.cloudbase.net/cli/install/install.ps1 | iex

npm installation (Alternative)

npm install -g @cloudbase/cli

After installation completes, verify the installation:

tcb --version

3. Log in to the CloudBase environment​

tcb login

Follow the prompts to complete WeChat scan code login, then select or create a CloudBase environment.

🎨 Project Development Practice​

Step 1: Create Project​

  1. Create Project Directory
mkdir neighborhood-recycling
cd neighborhood-recycling
  1. Start AI Assistant
tcb ai
  1. Select AI Model and Template In AI conversations, we select:
  • AI Model: Claude Code (or Kimi K2)
  • Project Template: Mini Program Cloud Development Template
  1. Describe Project Requirements
Please help me create a WeChat Mini Program sample for neighborhood idle item recycling with the following features:

1. Homepage: Item Browsing, Search, Category Filtering, Sorting
2. Item Details: Image Carousel, Detailed Information, Contact Information, Favorites
3. Item Publishing: Multi-image Upload, Information Filling, Location Selection
4. User Center: Personal Information, My Posts, My Favorites

Tech Stack: WeChat Mini Program + CloudBase (Cloud Functions, Cloud Database, Cloud Storage)
Design Style: Clean and modern, with a green and eco-friendly theme.

Step 2: Project Structure Generation​

AI will automatically generate the project structure based on requirements.

Step 3: Database Design​

AI will help us design the database structure for the sample project:

// items collection structure
{
  _id: "Automatically generated ID",
  title: "Item Title",
  description: "Item description", 
  category: "Item Category", // Digital, Books, Clothing, Home, Sports, Others
  price: 0, // Price (0 indicates free)
  images: ["Image URL array"],
  contactWechat: "WeChat ID",
  contactPhone: "Phone Number", 
  location: {
    latitude: "Latitude",
    longitude: "Longitude", 
    address: "Address"
  },
  status: "available", // available, sold, removed
  openid: "User openid",
  createTime: "Creation timestamp",
  updateTime: "Update timestamp",
  views: "Page views",
  favorites: "Favorites Count"
}

Step 4: Cloud Function Development​

AI will automatically generate the cloud function code for the sample project:

itemManager Cloud Function (Item Management)

// Handles CRUD operations, search, and other functions for items
const cloud = require('wx-server-sdk')
cloud.init()

exports.main = async (event, context) => {
  const db = cloud.database()
  const { action, data } = event
  
  switch(action) {
    case 'create':
      return await createItem(db, data)
    case 'query':
      return await queryItems(db, data)
    case 'update':
      return await updateItem(db, data)
    case 'delete':
      return await deleteItem(db, data)
    default:
      return { error: 'Unknown action' }
  }
}

getOpenId Cloud Function (User Identity Retrieval)

const cloud = require('wx-server-sdk')
cloud.init()

exports.main = async (event, context) => {
  const wxContext = cloud.getWXContext()
  return {
    openid: wxContext.OPENID,
    appid: wxContext.APPID,
    unionid: wxContext.UNIONID,
  }
}

Step 5: Front-end Page Development​

AI will generate the complete front-end code for the sample project, including:

Home (index)

  • Responsive Items Grid Layout
  • Real-time search functionality
  • Category Filtering and Sorting
  • Pull-to-refresh and pull-to-load

Item Detail Page (detail)

  • Image Carousel Display
  • Detailed Item Information
  • Favorite Function
  • Contact Information Display

Publish Page (publish)

  • Multiple Image Upload
  • Complete Form Validation
  • Location Selection
  • Intelligent Classification

User Center (profile)

  • User Information Management
  • Personal Statistics
  • My Publications Management
  • My Favorites

Step 6: Develop in WeChat Developer Tools​

  1. Open Project
# Run in the project directory
tcb ai -- "Use WeChat Developer Tools to open the current project"
  1. Configure Project
  • Import the project in WeChat Developer Tools
  • Configure AppID
  • Enable Cloud Development Capabilities
  1. Real-time Development In the terminal of WeChat Developer Tools, you can continue using the AI assistant:
tcb ai

This way, you can develop while previewing simultaneously, with the AI optimizing your code and resolving issues in real time.

🔧 Core Feature Implementation​

1. Homepage Item Display​

Key Code Implementation:

// pages/index/index.js
Page({
  data: {
    items: [],
    loading: false,
    hasMore: true
  },
  
  onLoad() {
    this.loadItems()
  },
  
  async loadItems() {
    this.setData({ loading: true })
    try {
      const result = await wx.cloud.callFunction({
        name: 'itemManager',
        data: { action: 'query', data: { status: 'available' } }
      })
      this.setData({ 
        items: result.result.data,
        loading: false 
      })
    } catch (error) {
      console.error('Load failed:', error)
    }
  }
})

2. Image Upload Feature​

Implementation Code:

async uploadImages(tempFilePaths) {
  const uploadTasks = tempFilePaths.map(filePath => {
    return wx.cloud.uploadFile({
      cloudPath: `items/${Date.now()}-${Math.random().toString(36).substr(2, 9)}.jpg`,
      filePath: filePath
    })
  })
  
  const uploadResults = await Promise.all(uploadTasks)
  return uploadResults.map(result => result.fileID)
}

3. Search and Filter​

🎨 Design Highlights​

Visual Design​

We adopted a green and eco-friendly theme to reflect the environmental concept of recycling:

/* Theme Color */
:root {
  --primary-color: #4CAF50;    /* Main color: eco-friendly green */
  --secondary-color: #81C784;  /* Secondary color: light green */
  --accent-color: #FF9800;     /* Accent color: orange */
  --text-color: #333333;       /* Text color: dark gray */
  --bg-color: #F5F5F5;         /* Background color: light gray */
}

User Experience Optimization​

  1. Responsive Design: Adapt to different screen sizes
  2. Loading Status: Provide friendly loading feedback
  3. Error Handling: Graceful error prompts
  4. Operation Feedback: Instant operation result feedback

🚀 Deployment and Release​

1. Cloud Function Deployment​

# Run in the project root directory
tcb ai -- -p "Deploy all cloud functions to the CloudBase environment"

2. Database Initialization​

tcb ai -- -p "Create database collections and indexes"

3. Mini Program Preview​

  1. Click "Preview" in WeChat Developer Tools
  2. Use WeChat to scan the QR code for preview on your phone
  3. Test whether all functions are working properly

4. Submit for Review​

  1. Complete Mini Program Information
  2. Upload Mini Program icon and screenshots
  3. Fill in the feature description
  4. Submit for Review

📊 Project Achievements​

Using CloudBase AI CLI, we have successfully built a fully functional neighborhood idle item recycling mini program example:

Technical Achievements​

  • ✅ Complete WeChat Mini Program Application
  • ✅ Cloud Function Backend Service
  • ✅ Cloud database data storage
  • ✅ Cloud Storage File Management
  • ✅ Responsive User Interface

Business Value​

  • 🌱 Environmental Value: Promotes resource recycling
  • 🤝 Social Value: Enhances neighborhood interaction
  • 💰 Economic Value: Helps users save costs
  • 🏠 Community Value: Builds a harmonious community environment

🎯 Development Lessons Learned​

Advantages of CloudBase AI CLI​

  1. Unified Management: Manage multiple AI programming tools with a single command.
  2. Multi-model Support: Supports Claude Code, Kimi K2, and other models.
  3. Cloud Development Integration: Deep integration with the Tencent Cloud development platform
  4. Rapid Development: Significantly reduces coding time and improves development efficiency

Best Practices​

  1. Requirements Clarification: Clarify functional requirements and technical specifications before starting
  2. Progressive Development: First implement core features, then gradually refine them.
  3. Real-time Testing: Test while developing to detect issues promptly.
  4. Documentation: Record the development process and key decisions

🔗 Related Resources​

🎉 Conclusion​

Through CloudBase AI CLI, we successfully transformed a complex full-stack mini-program example project from concept to reality. This not only demonstrates the powerful capabilities of AI programming tools but also proves the value of cloud development platforms in rapid application development.

In the future, with the continuous development of AI technology, we believe more developers will rapidly build valuable products through similar approaches, driving the popularization and application of technology.