README.md

Unemployeed - Experiments Repository

This is an experimentation repository for Unemployeed - a place to play around with code, test new ideas, and prototype features before integrating them into the main project.

📁 Repository Structure

experiments/
├── ai-experiments/          # AI/ML related experiments
│   └── hf_models/          # Hugging Face model services for career prep
├── alt-stacks/             # Alternative tech stack experiments
├── design-experiments/     # UI/UX and design system experiments
└── README.md              # This file

🧪 Experiment Categories

AI Experiments (ai-experiments/)

Experiments related to artificial intelligence, machine learning, and LLM integrations.

Current Projects:

• hf_models/: Career Prep LLM Services - A Hugging Face Spaces-compatible service layer providing:

  • Career diagnosis
  • Breakthrough analysis
  • Personalized roadmap generation
  • Resume analysis with ATS scoring

  See ai-experiments/hf_models/README.md for detailed documentation.

Alt Stacks (alt-stacks/)

Experiments with alternative technology stacks, frameworks, or architectures.

Design Experiments (design-experiments/)

UI/UX prototypes, design system components, and visual experiments.

🚀 Quick Start

Prerequisites

• Python 3.9+ (for AI experiments)
• Git
• Virtual environment tool (venv, conda, etc.)

Setting Up an Experiment

1. Navigate to the experiment directory:

   cd ai-experiments/hf_models  # or your experiment directory
   

2. Create a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   

3. Install dependencies:

   pip install -r requirements.txt
   

4. Follow the experiment-specific README for detailed setup instructions.

📝 Adding New Experiments

When creating a new experiment:

1. Create a new directory under the appropriate category (or create a new category if needed)
2. Add a README.md explaining:
   • What the experiment does
   • How to set it up
   • How to run it
   • Key findings or notes
3. Include a .gitignore if needed (the root .gitignore covers most cases)
4. Document dependencies in a requirements.txt or equivalent

🎯 Experiment Guidelines

• Keep it experimental: This is a safe space to try new things
• Document learnings: Update READMEs with findings and insights
• Isolate experiments: Each experiment should be self-contained
• Clean up: Remove experiments that are no longer relevant or have been integrated

🔧 Common Commands

Running Tests

# From a Python experiment directory
pytest
pytest --cov=. --cov-report=html  # With coverage

Managing Dependencies

# Generate requirements.txt
pip freeze > requirements.txt

# Install from requirements.txt
pip install -r requirements.txt

📚 Resources

• AI Experiments - HF Models - Career Prep LLM Services documentation

🤝 Contributing

This is a personal experimentation repository. Feel free to:

• Add new experiments
• Document findings
• Refactor and improve existing experiments
• Remove outdated experiments

📄 License

[Add your license here]

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Note: This repository is for experimentation and prototyping. Code here may be incomplete, unstable, or experimental. Use at your own discretion.