test-extended.yml

name: Extended Tests

on:
  push:
    branches: [ main ]
  pull_request:
    branches: [ main ]
  schedule:
    # Run nightly at 2 AM UTC
    - cron: '0 2 * * *'
  workflow_dispatch:  # Allow manual triggering

jobs:
  test-examples:
    runs-on: ubuntu-latest
    timeout-minutes: 15
    
    steps:
    - name: Checkout code
      uses: actions/checkout@v4

    - name: Set up Python
      uses: actions/setup-python@v5
      with:
        python-version: 3.11

    - name: Install UV
      run: |
        curl -LsSf https://astral.sh/uv/install.sh | sh
        echo "$HOME/.local/bin" >> $GITHUB_PATH


    - name: Install dependencies
      run: |
        cd src/praisonai
        uv pip install --system ."[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
        uv pip install --system duckduckgo_search
        # Install knowledge dependencies from praisonai-agents
        uv pip install --system "praisonaiagents[knowledge]"

    - name: Set environment variables
      run: |
        echo "OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}" >> $GITHUB_ENV
        echo "OPENAI_API_BASE=${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}" >> $GITHUB_ENV
        echo "OPENAI_MODEL_NAME=${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}" >> $GITHUB_ENV
        echo "PYTHONPATH=${{ github.workspace }}/src/praisonai-agents:$PYTHONPATH" >> $GITHUB_ENV
        echo "PRAISONAI_TELEMETRY_DISABLED=true" >> $GITHUB_ENV
        echo "PRAISONAI_DISABLE_TELEMETRY=true" >> $GITHUB_ENV
        echo "DO_NOT_TRACK=true" >> $GITHUB_ENV

    - name: Test Key Example Scripts
      run: |
        echo "🧪 Testing key example scripts from praisonai-agents..."
        
        # Create a timeout function for consistent handling
        timeout_run() {
          timeout 30s "$@" || echo "⏱️  $1 test completed/timed out"
        }
        
        # Test basic agent functionality
        timeout_run python ${{ github.workspace }}/src/praisonai-agents/basic-agents.py
        
        # Test async functionality  
        timeout_run python ${{ github.workspace }}/src/praisonai-agents/async_example.py
        
        # Test knowledge/RAG functionality
        timeout_run python ${{ github.workspace }}/src/praisonai-agents/knowledge-agents.py
        
        # Test MCP functionality
        timeout_run python ${{ github.workspace }}/src/praisonai-agents/mcp-basic.py
        
        # Test UI functionality
        timeout_run python ${{ github.workspace }}/src/praisonai-agents/ui.py
        
        echo "✅ Example script testing completed"
      continue-on-error: true

  performance-test:
    runs-on: ubuntu-latest
    timeout-minutes: 15
    
    steps:
    - name: Checkout code
      uses: actions/checkout@v4

    - name: Set up Python
      uses: actions/setup-python@v5
      with:
        python-version: 3.11

    - name: Install UV
      run: |
        curl -LsSf https://astral.sh/uv/install.sh | sh
        echo "$HOME/.local/bin" >> $GITHUB_PATH


    - name: Install dependencies
      run: |
        cd src/praisonai
        uv pip install --system ."[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
        uv pip install --system pytest pytest-benchmark
        # Install knowledge dependencies from praisonai-agents
        uv pip install --system "praisonaiagents[knowledge]"

    - name: Set environment variables
      run: |
        echo "PRAISONAI_TELEMETRY_DISABLED=true" >> $GITHUB_ENV
        echo "PRAISONAI_DISABLE_TELEMETRY=true" >> $GITHUB_ENV
        echo "DO_NOT_TRACK=true" >> $GITHUB_ENV

    - name: Run Performance Benchmarks
      run: |
        echo "🏃 Running performance benchmarks..."
        python -c "
        import time
        import sys
        import statistics
        sys.path.insert(0, 'src/praisonai')
        
        print('🏃 Testing agent creation performance...')
        times = []
        try:
            from praisonaiagents import Agent
            for i in range(5):
                start_time = time.time()
                agent = Agent(name=f'PerfAgent{i}')
                times.append(time.time() - start_time)
            
            avg_time = statistics.mean(times)
            print(f'✅ Average agent creation time: {avg_time:.3f}s')
            print(f'📊 Min: {min(times):.3f}s, Max: {max(times):.3f}s')
        except Exception as e:
            print(f'❌ Agent creation benchmark failed: {e}')
        
        print('🏃 Testing import performance...')
        start_time = time.time()
        try:
            import praisonaiagents
            import_time = time.time() - start_time
            print(f'✅ Import completed in {import_time:.3f}s')
        except Exception as e:
            print(f'❌ Import benchmark failed: {e}')
        
        print('🏃 Testing memory usage...')
        try:
            import psutil
            import os
            process = psutil.Process(os.getpid())
            memory_mb = process.memory_info().rss / 1024 / 1024
            print(f'📊 Memory usage: {memory_mb:.1f} MB')
        except ImportError:
            print('⚠️  psutil not available for memory testing')
        except Exception as e:
            print(f'❌ Memory benchmark failed: {e}')
        "
      continue-on-error: true

    - name: Generate Performance Report
      run: |
        echo "## 📊 Performance Test Results" > performance_report.md
        echo "" >> performance_report.md
        echo "### Benchmarks Run:" >> performance_report.md
        echo "- ⚡ Agent creation speed" >> performance_report.md
        echo "- 📦 Import performance" >> performance_report.md
        echo "- 💾 Memory usage" >> performance_report.md
        echo "- 🧪 Example script execution" >> performance_report.md
        echo "" >> performance_report.md
        echo "_Performance results are logged in the CI output above._" >> performance_report.md

    - name: Upload Performance Report
      uses: actions/upload-artifact@v4
      with:
        name: performance-report
        path: performance_report.md
        retention-days: 5