At the core of the Theory L.I.F.E is the idea that learning is a deeply personal and
nonlinear process. It encourages individuals to immerse themselves in real-life
challenges, engage in reflective observation, draw meaningful insights, and apply these
learnings to future endeavors. The framework consists of four interconnected stages:
1. **Concrete Experience**: Engaging directly in new, hands-on experiences that
challenge existing perspectives.
2. **Reflective Observation**: Taking the time to reflect on these experiences,
considering what they reveal about oneself and the environment.
3. **Abstract Conceptualization**: Formulating lessons learned and new ideas based
on reflections, allowing for deeper understanding and growth.
4. **Active Experimentation**: Implementing newfound insights in practical settings,
thus fostering continuous development.
**Calculating Self-Development**
 “© [Sergio Miguel Paya Borrull] [2025]. All rights reserved.”
The Theory L.I.F.E can be expressed mathematically to illustrate the relationship
between learning, individual agency, and experiential engagement in the journey of self�development. This can be represented by the following equation:
**Self-Development = (Learning + Individual) / Experience**

…ce Theory Algorithm Code 2025 Copyright Sergio Paya Borrull. All rights Reserved 3.py

…ry Algorithm Code 2025 Copyright Sergio Paya Borrull. All rights Reserved 3.py

[skip ci]

…ython-promptflow

on:
  push:
    branches: [ main ]
  pull_request:
    branches: [ main ]

jobs:
  build-and-test:
    runs-on: ubuntu-latest
    steps:
    - uses: actions/checkout@v4

    - name: Set up Python
      uses: actions/setup-python@v4
      with:
        python-version: '3.10'

    - name: Install dependencies
      run: |
        pip install -r requirements.txt
        pip install torch onnxruntime azure-ai-ml

    - name: Run tests
      run: |
        pytest tests/ --cov=src/ --cov-report=xml

    - name: Upload coverage
      uses: codecov/codecov-action@v3

  deploy-to-azure:
    needs: build-and-test
    runs-on: ubuntu-latest
    steps:
    - name: Azure Login
      uses: azure/login@v1
      with:
        client-id: ${{ secrets.AZURE_CLIENT_ID }}
        tenant-id: ${{ secrets.AZURE_TENANT_ID }}
        subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}

    - name: Deploy to AKS
      run: |
        az aks get-credentials --resource-group life-rg --name life-cluster
        kubectl apply -f deployment/