# .github/workflows/reindex_on_merge.yml

name: Re-index Repository on Merge (Self-Hosted)

on:
  pull_request:
    types: [closed]
    branches:
      - main
  workflow_dispatch:

jobs:
  reindex:
    # This condition ensures the job only runs if the pull request was actually merged.
    if: github.event.pull_request.merged == true || github.event_name == 'workflow_dispatch'

    runs-on: Windows

    # Set the default shell to PowerShell, which is native to your Windows runner.
    defaults:
      run:
        shell: powershell

    steps:
      # Step 1: Check out the repository's code
      - name: Checkout repository
        uses: actions/checkout@v4

      # Step 2: Set up a specific Python version
      - name: Set up Python 3.11
        id: setup-python
        uses: actions/setup-python@v4
        with:
          python-version: '3.11'

      # Step 3: Create and activate a virtual environment (using PowerShell syntax)
      - name: Create and activate virtual environment
        run: |
          if (-not (Test-Path -Path ".venv")) {
            python -m venv .venv
          }
          .\.venv\Scripts\Activate.ps1

      # Step 4: Install or update dependencies
      - name: Install dependencies
        run: |
          pip install --upgrade pip
          pip install -r requirements.txt
      
      # Step 5: *** NEW - GPU Diagnostics ***
      # This step will help us see if the runner can access the GPU and CUDA.
      - name: Check GPU and CUDA status
        run: |
          echo "--- Checking for nvidia-smi ---"
          # The '|| $true' part ensures the workflow doesn't fail if the command isn't found
          nvidia-smi || $true
          
          echo "--- Checking PyTorch CUDA availability ---"
          # This command will explicitly tell us if PyTorch can see the GPU.
          python -c "import torch; print(f'PyTorch version: {torch.__version__}'); print(f'CUDA available: {torch.cuda.is_available()}'); print(f'CUDA version: {torch.version.cuda}'); print(f'Device count: {torch.cuda.device_count()}')"

      # Step 6: Run the indexing script within the virtual environment
      - name: Run indexing script
        run: |
          python create_index.py
        env:
          GITHUB_REPOSITORY: ${{ github.repository }}
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
        
      # Step 7: Upload the database as an artifact
      - name: Upload database artifact
        uses: actions/upload-artifact@v4
        with:
          name: chroma_db_artifact
          path: ./chroma_db