name: Vector Database Export

on:
  workflow_dispatch:
    inputs:
      skill_name:
        description: 'Skill name to export (e.g., react, django, godot)'
        required: true
        type: string
      targets:
        description: 'Vector databases to export (comma-separated: weaviate,chroma,faiss,qdrant or "all")'
        required: true
        default: 'all'
        type: string
      config_path:
        description: 'Path to config file (optional, auto-detected from skill_name if not provided)'
        required: false
        type: string
  schedule:
    # Run weekly on Sunday at 2 AM UTC for popular frameworks
    - cron: '0 2 * * 0'

jobs:
  export:
    name: Export to Vector Databases
    runs-on: ubuntu-latest
    strategy:
      fail-fast: false
      matrix:
        # For scheduled runs, export popular frameworks
        skill: ${{ github.event_name == 'schedule' && fromJson('["react", "django", "godot", "fastapi"]') || fromJson(format('["{0}"]', github.event.inputs.skill_name)) }}

    env:
      SKILL_NAME: ${{ matrix.skill }}
      TARGETS_INPUT: ${{ github.event.inputs.targets }}
      CONFIG_PATH_INPUT: ${{ github.event.inputs.config_path }}

    steps:
    - uses: actions/checkout@v3
      with:
        submodules: recursive

    - name: Set up Python 3.12
      uses: actions/setup-python@v4
      with:
        python-version: '3.12'

    - name: Install dependencies
      run: |
        python -m pip install --upgrade pip
        pip install -e .

    - name: Determine config path
      id: config
      run: |
        if [ -n "$CONFIG_PATH_INPUT" ]; then
          echo "path=$CONFIG_PATH_INPUT" >> $GITHUB_OUTPUT
        else
          echo "path=configs/$SKILL_NAME.json" >> $GITHUB_OUTPUT
        fi

    - name: Check if config exists
      id: check_config
      run: |
        CONFIG_FILE="${{ steps.config.outputs.path }}"
        if [ -f "$CONFIG_FILE" ]; then
          echo "exists=true" >> $GITHUB_OUTPUT
        else
          echo "exists=false" >> $GITHUB_OUTPUT
          echo "⚠️  Config not found: $CONFIG_FILE"
        fi

    - name: Scrape documentation
      if: steps.check_config.outputs.exists == 'true'
      run: |
        echo "📥 Scraping documentation for $SKILL_NAME..."
        skill-seekers scrape --config "${{ steps.config.outputs.path }}" --max-pages 100
      continue-on-error: true

    - name: Determine export targets
      id: targets
      run: |
        TARGETS="${TARGETS_INPUT:-all}"
        if [ "$TARGETS" = "all" ]; then
          echo "list=weaviate chroma faiss qdrant" >> $GITHUB_OUTPUT
        else
          echo "list=$(echo "$TARGETS" | tr ',' ' ')" >> $GITHUB_OUTPUT
        fi

    - name: Export to vector databases
      if: steps.check_config.outputs.exists == 'true'
      env:
        EXPORT_TARGETS: ${{ steps.targets.outputs.list }}
      run: |
        SKILL_DIR="output/$SKILL_NAME"

        if [ ! -d "$SKILL_DIR" ]; then
          echo "❌ Skill directory not found: $SKILL_DIR"
          exit 1
        fi

        echo "📦 Exporting $SKILL_NAME to vector databases..."

        for target in $EXPORT_TARGETS; do
          echo ""
          echo "🔹 Exporting to $target..."

          # Use adaptor directly via CLI
          python -c "
import sys
from pathlib import Path
sys.path.insert(0, 'src')

from skill_seekers.cli.adaptors import get_adaptor

adaptor = get_adaptor('$target')
package_path = adaptor.package(Path('$SKILL_DIR'), Path('output'))
print(f'✅ Exported to {package_path}')
          "

          if [ $? -eq 0 ]; then
            echo "✅ $target export complete"
          else
            echo "❌ $target export failed"
          fi
        done

    - name: Generate quality report
      if: steps.check_config.outputs.exists == 'true'
      run: |
        SKILL_DIR="output/$SKILL_NAME"

        if [ -d "$SKILL_DIR" ]; then
          echo "📊 Generating quality metrics..."

          python -c "
import sys
from pathlib import Path
sys.path.insert(0, 'src')

from skill_seekers.cli.quality_metrics import QualityAnalyzer

analyzer = QualityAnalyzer(Path('$SKILL_DIR'))
report = analyzer.generate_report()
formatted = analyzer.format_report(report)
print(formatted)

# Save to file
with open('quality_report_${SKILL_NAME}.txt', 'w') as f:
    f.write(formatted)
          "
        fi
      continue-on-error: true

    - name: Upload vector database exports
      if: steps.check_config.outputs.exists == 'true'
      uses: actions/upload-artifact@v3
      with:
        name: ${{ env.SKILL_NAME }}-vector-exports
        path: |
          output/${{ env.SKILL_NAME }}-*.json
        retention-days: 30

    - name: Upload quality report
      if: steps.check_config.outputs.exists == 'true'
      uses: actions/upload-artifact@v3
      with:
        name: ${{ env.SKILL_NAME }}-quality-report
        path: quality_report_${{ env.SKILL_NAME }}.txt
        retention-days: 30
      continue-on-error: true

    - name: Create export summary
      if: steps.check_config.outputs.exists == 'true'
      env:
        EXPORT_TARGETS: ${{ steps.targets.outputs.list }}
      run: |
        echo "## 📦 Vector Database Export Summary: $SKILL_NAME" >> $GITHUB_STEP_SUMMARY
        echo "" >> $GITHUB_STEP_SUMMARY

        for target in $EXPORT_TARGETS; do
          FILE="output/${SKILL_NAME}-${target}.json"
          if [ -f "$FILE" ]; then
            SIZE=$(du -h "$FILE" | cut -f1)
            echo "✅ **$target**: $SIZE" >> $GITHUB_STEP_SUMMARY
          else
            echo "❌ **$target**: Export failed" >> $GITHUB_STEP_SUMMARY
          fi
        done

        echo "" >> $GITHUB_STEP_SUMMARY

        if [ -f "quality_report_${SKILL_NAME}.txt" ]; then
          echo "### 📊 Quality Metrics" >> $GITHUB_STEP_SUMMARY
          echo "\`\`\`" >> $GITHUB_STEP_SUMMARY
          head -30 "quality_report_${SKILL_NAME}.txt" >> $GITHUB_STEP_SUMMARY
          echo "\`\`\`" >> $GITHUB_STEP_SUMMARY
        fi