Add PTC-Bench Interactive Dashboard for Benchmark Visualization

Changes:
- Introduced a new Streamlit-based dashboard in `dashboard.py` for visualizing benchmark results comparing Programmatic Tool Calling (PTC) and Function Calling (FC).
- Enhanced README with instructions on running the dashboard and updated content to reflect the new features.
- Added new assets for visual comparisons, including performance metrics and charts.
- Implemented functionality to load benchmark results from JSON files or run benchmarks directly from the dashboard.

This commit significantly improves user experience by providing an interactive way to analyze and visualize benchmark data, facilitating better insights into the performance of PTC vs FC approaches.

Author: TJKlein

.github/workflows/ptc-benchmark.yml

@@ -0,0 +1,177 @@
+name: PTC-Bench Benchmark
+
+on:
+  push:
+    branches: [ main, master ]
+  pull_request:
+    branches: [ main, master ]
+  schedule:
+    # Run benchmark daily at 2 AM UTC
+    - cron: '0 2 * * *'
+  workflow_dispatch:
+    inputs:
+      backend:
+        description: 'Backend to test'
+        required: true
+        default: 'subprocess'
+        type: choice
+        options:
+          - subprocess
+          - opensandbox
+      approach:
+        description: 'Approach to test'
+        required: true
+        default: 'both'
+        type: choice
+        options:
+          - ptc
+          - function_calling
+          - both
+      profile:
+        description: 'Benchmark profile'
+        required: true
+        default: 'quick'
+        type: choice
+        options:
+          - quick
+          - standard
+          - full
+
+jobs:
+  benchmark:
+    runs-on: ubuntu-latest
+    
+    steps:
+    - name: Checkout repository
+      uses: actions/checkout@v3
+      
+    - name: Set up Python
+      uses: actions/setup-python@v4
+      with:
+        python-version: '3.10'
+        
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install -e .
+        pip install opensandbox opensandbox-server
+        
+    - name: Configure OpenSandbox (if selected)
+      if: github.event.inputs.backend == 'opensandbox' || (github.event_name != 'workflow_dispatch' && github.event.inputs.backend != 'subprocess')
+      run: |
+        opensandbox-server init-config ~/.sandbox.toml --example docker
+        
+    - name: Run PTC-Bench Benchmark
+      id: benchmark
+      env:
+        # Use GitHub Secrets for API keys (optional)
+        OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+        AZURE_OPENAI_API_KEY: ${{ secrets.AZURE_OPENAI_API_KEY }}
+        AZURE_OPENAI_ENDPOINT: ${{ secrets.AZURE_OPENAI_ENDPOINT }}
+      run: |
+        # Determine parameters
+        BACKEND="${{ github.event.inputs.backend || 'subprocess' }}"
+        APPROACH="${{ github.event.inputs.approach || 'both' }}"
+        PROFILE="${{ github.event.inputs.profile || 'quick' }}"
+        
+        # Map profile to categories
+        case $PROFILE in
+          quick)
+            CATEGORIES="compute,ptc"
+            ;;
+          standard)
+            CATEGORIES="compute,ptc,io,import_heavy"
+            ;;
+          full)
+            CATEGORIES=""
+            ;;
+        esac
+        
+        # Determine LLM provider
+        if [ -n "$OPENAI_API_KEY" ] || [ -n "$AZURE_OPENAI_API_KEY" ]; then
+          LLM_PROVIDER="openai"
+          echo "🔑 Using LLM mode with API key"
+        else
+          LLM_PROVIDER="none"
+          echo "ℹ️ Running in baseline mode (no LLM)"
+        fi
+        
+        # Build command
+        CMD="python -m benchmarks run --backend $BACKEND --approach $APPROACH --llm-provider $LLM_PROVIDER --output results.md"
+        
+        if [ -n "$CATEGORIES" ]; then
+          CMD="$CMD --categories $CATEGORIES"
+        fi
+        
+        echo "🚀 Running: $CMD"
+        eval $CMD
+        
+        # Extract summary metrics from results
+        echo "📊 Benchmark Results:"
+        cat results.md | head -100
+        
+    - name: Upload benchmark results
+      uses: actions/upload-artifact@v3
+      with:
+        name: benchmark-results
+        path: |
+          results.md
+          results.json
+        retention-days: 30
+        
+    - name: Comment PR with results
+      if: github.event_name == 'pull_request'
+      uses: actions/github-script@v6
+      with:
+        script: |
+          const fs = require('fs');
+          
+          // Read results file
+          let resultsText = '';
+          try {
+            resultsText = fs.readFileSync('results.md', 'utf8');
+          } catch (e) {
+            resultsText = 'Results file not found';
+          }
+          
+          // Extract key metrics (first 50 lines)
+          const summary = resultsText.split('\n').slice(0, 50).join('\n');
+          
+          // Create comment body
+          const body = `## 📊 PTC-Bench Benchmark Results
+          
+          ${summary}
+          
+          <details>
+          <summary>View full results</summary>
+          
+          \`\`\`
+          ${resultsText.slice(0, 3000)}${resultsText.length > 3000 ? '\n... (truncated)' : ''}
+          \`\`\`
+          
+          </details>
+          
+          ---
+          
+          *Benchmark run on commit ${{ github.sha }}*
+          `;
+          
+          github.rest.issues.createComment({
+            issue_number: context.issue.number,
+            owner: context.repo.owner,
+            repo: context.repo.repo,
+            body: body
+          });
+          
+    - name: Check performance regression
+      if: github.event_name == 'pull_request'
+      run: |
+        echo "⚠️ Performance regression check would run here"
+        echo "Compare results against baseline from main branch"
+        echo "If regression > 10%, fail the check"
+        
+        # TODO: Implement actual regression check
+        # 1. Download baseline results from main branch artifact
+        # 2. Parse JSON results
+        # 3. Compare key metrics (success_rate, avg_time)
+        # 4. Fail if regression exceeds threshold