Pats182/Tech_Stack_Advisor

Tech Stack Advisor

A Gradio-based web application that helps recommend technology stacks based on your project requirements. This project demonstrates containerization with Docker and automated deployment to Hugging Face Spaces using GitHub Actions CI/CD.

🚀 Live Demo

Check out the live application: Tech Stack Advisor on Hugging Face Spaces

📋 Project Overview

This project was developed as part of the AI/ML with Docker course at School of DevOps. The application was created by Gourav Shah, and this repository demonstrates the process of:

• —Containerizing a Python/Gradio application with Docker
• —Setting up automated CI/CD pipeline with GitHub Actions
• —Deploying to Hugging Face Spaces

🛠️ Tech Stack

• —Python 3.11 - Programming language
• —Gradio - Web UI framework for machine learning applications
• —Docker - Containerization platform
• —GitHub Actions - CI/CD automation
• —Hugging Face Spaces - Deployment platform

📦 Project Structure

Tech-Stack-Advisor/
├── app.py                    # Main Gradio application
├── requirements.txt          # Python dependencies
├── Dockerfile               # Docker configuration
├── .github/
│   └── workflows/
│       └── Sync to Hugging Face hub     # GitHub Actions workflow
└── README.md                            # Project documentation

🐳 Docker Setup

Dockerfile

The application is containerized using Docker with the following configuration:

FROM python:3.11-slim

WORKDIR /app

COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

COPY . .

EXPOSE 7860

CMD ["python", "app.py"]

Building Locally

To build and run the Docker container locally:

# Build the Docker image
docker build -t tech-stack-advisor .

# Run the container
docker run -p 7860:7860 tech-stack-advisor

Access the application at http://localhost:7860

🔄 CI/CD Pipeline

This project uses GitHub Actions for automated deployment to Hugging Face Spaces. Every push to the main branch triggers the deployment workflow.

Workflow Configuration

The workflow automatically:

1. 1.Checks out the repository
2. 2.Pushes changes to Hugging Face Spaces
3. 3.Triggers a rebuild of the Docker container on Hugging Face

Setup Instructions

To replicate this CI/CD setup:

1. 1.Create a Hugging Face Space
2. 2.Go to Hugging Face Spaces
3. 3.Create a new Space with Docker SDK
4. 4.Note your Space name (e.g., username/space-name)

1. 1.Generate Hugging Face Token
2. 2.Go to Hugging Face Settings > Tokens
3. 3.Create a new token with "Write" permissions
4. 4.Copy the token

1. 1.Add Token to GitHub Secrets
2. 2.Go to your GitHub repository → Settings → Secrets and variables → Actions
3. 3.Create a new secret named HFTSA_TOKEN
4. 4.Paste your Hugging Face token as the value

1. 1.Update Workflow File
2. 2.Modify .github/workflows/Sync to Hugging Face hub/main.yml with your Space URL
3. 3.Commit and push to trigger the deployment

GitHub Actions Workflow

name: Sync to Hugging Face hub

on:
  push:
    branches: [main]
  workflow_dispatch:

jobs:
  sync-to-hub:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
        with:
          fetch-depth: 0
          lfs: true
      
      - name: Push to Hugging Face
        env:
          HFTSA_TOKEN: ${{ secrets.HFTSA_TOKEN }}
        run: |
          git config --global user.email "github-actions[bot]@users.noreply.github.com"
          git config --global user.name "github-actions[bot]"
          git push https://Pats182:$HFTSA_TOKEN@huggingface.co/spaces/Pats182/Tech_Stack_Advisor main --force

🚦 Getting Started

Prerequisites

• —Python 3.11+
• —Docker (for local development)
• —Git
• —GitHub account
• —Hugging Face account

Local Development

1. 1.Clone the repository

   git clone https://github.com/robinpats182/Tech-Stack-Advisor.git
   cd Tech-Stack-Advisor

1. 1.Install dependencies

   pip install -r requirements.txt

1. 1.Run the application

   python app.py

1. 1.Access the app
2. 2.Open your browser to http://localhost:7860

📝 Deployment Steps

1. 1.Make changes to your code locally
2. 2.Commit your changes:

   git add .
   git commit -m "Your commit message"

1. 1.Push to GitHub:

   git push origin main

1. 1.GitHub Actions automatically deploys to Hugging Face Spaces
2. 2.Wait for the build to complete on Hugging Face

🐛 Troubleshooting

Common Issues

Docker build fails on Hugging Face:

• —Ensure Dockerfile has a capital 'D'
• —Verify requirements.txt has compatible versions
• —Check Hugging Face build logs for specific errors

Authentication errors in GitHub Actions:

• —Verify HFTSA_TOKEN secret is set correctly
• —Ensure token has "Write" permissions
• —Check that the token hasn't expired

Application doesn't start:

• —Verify app.py has demo.launch(server_name="0.0.0.0", server_port=7860)
• —Check README.md has sdk: docker and app_port: 7860
• —Review container logs on Hugging Face

📚 Learning Resources

• —Docker Documentation
• —Gradio Documentation
• —Hugging Face Spaces Documentation
• —GitHub Actions Documentation

🙏 Credits

• —Application Creator: Gourav Shah
• —Course: AI/ML with Docker at School of DevOps
• —Dockerization & Deployment: Implementation of CI/CD pipeline and deployment workflow

📄 License

This project is part of an educational course at School of DevOps.

🤝 Contributing

This is an educational project. Feel free to fork and experiment with your own modifications!