Tencent Cloud Coding Plan Launched - Beginner-Friendly Configuration Tutorial

2026-03-10

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Hello everyone, this is programmer Wan Feng actively working on various AI projects.

Tencent Cloud Coding Plan's launch made many developers eager to try but don't know how to quickly get started. Today I'm bringing you a beginner-friendly configuration tutorial, letting you set up your own AI development environment in 30 minutes!

Pre-Requirements

1. Environment Requirements

Tencent Cloud account (free registration)
Git client
Basic command line operation ability

2. Access Coding Plan

Log into Tencent Cloud console
Go to 「Developer Services」→「Coding」
Click 「Coding Plan」 to enter new feature page

Step 1: Create Project

1. New Project

Click 「New Project」 button
Select project template (recommend 「AI Development Template」)
Fill in basic project info (name, description, visibility)

2. Configure Code Repository

Select repository type (Git)
Set branch strategy (recommend main branch protection)
Configure SSH key (optional but recommended)

Step 2: Configure AI Development Environment

1. Enable OpenClaw Integration

Find 「AI Assistant」 option in project settings
Enable 「OpenClaw Integration」
Select preset AI model (recommend Hunyuan large model)

2. Configure Development Environment

# coding-plan.yaml
version: "1.0"
environment:
  python: "3.9"
  dependencies:
    - openclaw>=1.0.0
    - requests>=2.28.0
ai_assistant:
  enabled: true
  model: "hunyuan-large"
  context_awareness: true

Step 3: Set Up CI/CD Pipeline

1. Create Pipeline Configuration

# coding-ci.yaml
stages:
  - name: build
    steps:
      - name: install-dependencies
        script: pip install -r requirements.txt
      - name: run-tests
        script: pytest tests/
  - name: deploy
    steps:
      - name: deploy-to-staging
        script: ./deploy.sh staging

2. Configure Deployment Environment

Create staging and production environments in 「Environment Management」
Set environment variables and keys
Configure auto deployment trigger conditions

Step 4: Enable Intelligent Code Review

1. Configure Code Review Rules

Enable AI code review in 「Code Quality」
Set review level (recommend starting from 「Medium」)
Configure ignore rules (such as specific folders)

2. Integrate Team Collaboration

Invite team members to join project
Set permission levels
Configure notification channels (WeChat Work/email)

Common Problem Troubleshooting

1. AI Assistant Slow Response

Check network connection
Confirm if model quota is sufficient
Try switching to lightweight model

2. Pipeline Failure

View detailed log output
Check dependency version compatibility
Confirm environment variable configuration is correct

3. Permission Errors

Confirm account permission level
Check SSH key configuration
Contact project administrator

Performance Optimization Suggestions

Cache dependencies: Configure dependency caching, reduce build time
Parallel testing: Group test cases for parallel execution
Incremental deployment: Only deploy changed parts, reduce deployment time

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