From the uDemy course on LLM engineering.
https://www.udemy.com/course/llm-engineering-master-ai-and-large-language-models
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
|
1 month ago | |
---|---|---|
.. | ||
README.md | 1 month ago | |
deploy-production.yml | 1 month ago | |
deploy-staging.yml | 1 month ago | |
docker-build.yml | 1 month ago | |
python-test.yml | 1 month ago |
README.md
CodeXchange AI CI/CD Workflows
This directory contains GitHub Actions workflows for continuous integration and deployment of the CodeXchange AI application.
Workflow Overview
- python-test.yml: Runs Python tests, linting, and code coverage
- docker-build.yml: Builds and validates Docker images with security scanning
- deploy-staging.yml: Deploys to staging environment when changes are pushed to develop branch
- deploy-production.yml: Deploys to production environment when a new release is published
Required GitHub Secrets
To use these workflows, you need to set up the following secrets in your GitHub repository:
- Go to your GitHub repository
- Navigate to Settings → Secrets and Variables → Actions
- Add the following secrets:
Secret Name | Description |
---|---|
DOCKERHUB_USERNAME |
Your Docker Hub username |
DOCKERHUB_TOKEN |
A personal access token from Docker Hub (not your password) |
Getting a Docker Hub Access Token
- Log in to Docker Hub
- Go to Account Settings → Security
- Create a new access token with appropriate permissions
- Copy the token immediately (it's only shown once)
- Add it as a GitHub secret
Customizing Deployment
The deployment workflows currently include placeholder comments where you would add your specific deployment commands. Update these sections based on your hosting environment:
- For VPS hosting: Add SSH-based deployment steps
- For cloud providers: Add their specific deployment APIs
- For Kubernetes: Add kubectl commands or Helm chart updates
Testing GitHub Actions Locally
You can test GitHub Actions locally using act:
# Install act
brew install act
# Run a specific workflow
act -j test -W .github/workflows/python-test.yml