DreamTrip-AI

DreamTrip-AI is an intelligent travel agency web application that helps users plan personalized trips using AI-powered recommendations.
This project demonstrates a full-stack setup with secure user authentication, AI integration, and modular development workflows.

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🚀 Overview

DreamTrip-AI allows users to:

• Search and receive AI-based travel recommendations
• Save and manage trip history
• Use personalized features through Clerk authentication
• Interact with the application via a modern, responsive UI

The project is built with scalability and maintainability in mind, using modern frontend and backend technologies.

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🛠️ Tech Stack

• Frontend: React / Next.js
• Backend: Node.js + Express
• Authentication: Clerk
• Database: MongoDB
• AI Integration: Gemini API
• Styling: Tailwind CSS / Material UI
• Containerization & CI/CD: Docker, GitHub Actions, Vercel/Render (future deployment)

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✨ Key Features

• ✅ Personalized travel recommendations powered by AI
• ✅ User authentication and session management with Clerk
• ✅ Persistent trip history in MongoDB
• ✅ Full-stack modular architecture (client & backend separation)
• ✅ CI/CD pipelines with automated linting, testing, and build validation

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📂 Project Structure

client/ # Frontend React/Next.js code backend/ # Node.js + Express backend workflows/ # GitHub Actions workflows docker/ # Docker configuration files package.json # Dependencies and scripts README.md # Project documentation

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GitHub Actions Workflows for DreamTrip-AI

This directory contains the GitHub Actions workflows for the DreamTrip-AI monorepo project during the development phase.

Current Development Phase Workflow Structure

1. CI Workflow (workflows/ci.yml)

• Triggers on every push to any branch
• Runs linting, testing, and building for both frontend and backend
• Backend tests use MongoDB service container

2. PR Checks Workflow (workflows/pr-checks.yml)

• Triggers on pull requests to the main branch
• Ensures code quality before merging to main
• Required checks that must pass before merging

3. MongoDB Service Workflow (workflows/mongodb-service.yml)

• Reusable workflow for setting up MongoDB service
• Can be called by other workflows

4. Local Development Helper (workflows/local-development.yml)

• Manually triggered workflow with component selection (client/backend/both)
• Validates code and generates development reports
• Helpful for sprint reviews and code quality checks -dam bro

5. Deployment Workflow (Currently Disabled)

• The deployment workflow has been commented out as we're still in the development phase
• Will be enabled once we're ready for staging/production deployments

Development Phase Setup

During development, the workflows are focused on ensuring code quality through:

• Linting to maintain code style and catch syntax errors
• Running tests with MongoDB integration for the backend
• Ensuring builds complete successfully

Using the Local Development Helper

The Local Development Helper workflow can be triggered manually from the GitHub Actions tab and offers several benefits during development:

1. Component-specific validation: Select which part of your application to validate (client, backend, or both)
2. Quick feedback: Get linting, testing, and build validation without running the full CI pipeline
3. Development reports: Automatically generates a repository structure report that's uploaded as an artifact
4. Sprint reviews: Use this workflow before sprint reviews to ensure code quality

To run the workflow:

1. Go to the "Actions" tab in your GitHub repository
2. Select "Local Development Helper" from the workflows list
3. Click "Run workflow"
4. Choose the component you want to validate (client/backend/both)
5. Review results and download the development report if needed