# Execution Logs Implementation - Complete

**Date**: January 18, 2026
**Priority**: P1
**Status**: ✅ Complete

## Summary

Implemented comprehensive execution logs in the benchmark viewer, allowing users to see detailed step-by-step logs during task execution with color-coded log levels, search/filter functionality, and a collapsible panel.

## Changes Made

### 1. Data Collection (`openadapt_evals/benchmarks/data_collection.py`)

**Added:**
- `LogEntry` dataclass for structured log entries
- `TaskLogHandler` custom logging handler that captures logs during task execution
- Log capture integration in `ExecutionTraceCollector`:
  - Automatic attachment to root logger
  - Per-task log collection with relative timestamps
  - Support for INFO, WARNING, ERROR, and SUCCESS log levels
  - Logs saved in `execution.json` under `"logs"` key

**Key Features:**
- Relative timestamps (seconds since task start)
- Automatic log level mapping from Python logging levels
- SUCCESS detection via `[SUCCESS]` marker in log messages
- Non-intrusive log capture (doesn't interfere with normal logging)

**Example log structure in `execution.json`:**
```json
{
  "task_id": "chrome_1",
  "success": true,
  "steps": [...],
  "logs": [
    {"timestamp": 0.0002, "level": "INFO", "message": "Started collecting data for task: chrome_1"},
    {"timestamp": 0.0525, "level": "INFO", "message": "Environment reset complete"},
    {"timestamp": 0.0530, "level": "INFO", "message": "Step 0: Getting action from agent"},
    {"timestamp": 0.0654, "level": "SUCCESS", "message": "[SUCCESS] Task completed successfully (score: 1.00)"}
  ]
}
```

### 2. Enhanced Logging in Runner (`openadapt_evals/benchmarks/runner.py`)

**Added detailed logging at key points:**
- Task start/reset
- Each step (action selection, execution)
- Agent reasoning (when available)
- Task completion (success/failure)
- Error conditions

**Example log output:**
```
INFO: Resetting environment for task chrome_1
INFO: Environment reset complete, starting task execution
INFO: Step 0: Getting action from agent
INFO: Step 0: Agent chose action: click
INFO: Step 0: Executing action in environment
INFO: Step 1: Getting action from agent
INFO: Step 1: Agent signaled task completion
INFO: Evaluating task result
INFO: [SUCCESS] Task chrome_1 completed successfully (score: 1.00)
```

### 3. Viewer UI (`openadapt_evals/benchmarks/viewer.py`)

**Added:**

#### CSS Styles
- `.log-panel` - Main container for log display
- `.log-panel-header` - Collapsible header with expand/collapse icon
- `.log-controls` - Search box and filter buttons
- `.log-container` - Scrollable log entries container
- `.log-entry` - Individual log entry with grid layout (timestamp | level | message)
- Color-coded log levels:
  - INFO: default text color
  - WARNING: orange (`--warning`)
  - ERROR: red (`--error`)
  - SUCCESS: green (`--success`)

#### HTML Structure
```html
<div class="log-panel">
  <div class="log-panel-header" onclick="toggleLogPanel()">
    <h4>
      <span class="expand-icon">▼</span>
      Execution Logs
      <span id="log-count">(11 entries)</span>
    </h4>
  </div>
  <div class="log-controls">
    <input type="text" class="log-search" placeholder="Search logs...">
    <button class="log-filter-btn active" data-level="all">All</button>
    <button class="log-filter-btn" data-level="INFO">Info</button>
    <button class="log-filter-btn" data-level="WARNING">Warning</button>
    <button class="log-filter-btn" data-level="ERROR">Error</button>
    <button class="log-filter-btn" data-level="SUCCESS">Success</button>
  </div>
  <div class="log-container">
    <!-- Log entries rendered here -->
  </div>
</div>
```

#### JavaScript Functions
- `renderLogs()` - Render all log entries from execution data
- `toggleLogPanel()` - Expand/collapse log panel
- `setLogLevel(level)` - Filter logs by level (all/INFO/WARNING/ERROR/SUCCESS)
- `filterLogs()` - Combined search and level filtering
- `escapeHtml(text)` - Sanitize log messages for display

**Features:**
- Real-time search (case-insensitive)
- Filter by log level
- Auto-scroll to latest log
- Expandable/collapsible panel
- Monospace font for readability
- Color-coded by severity

## Testing

Created comprehensive test script: `test_execution_logs.py`

**Tests:**
1. ✅ Log capture during successful task execution
2. ✅ Log capture during failed task execution
3. ✅ Log structure validation (timestamp, level, message)
4. ✅ Viewer generation with log panel
5. ✅ Viewer contains all required functions
6. ✅ Logs embedded in viewer HTML

**Test Results:**
```
Testing Execution Logs Feature
============================================================
✓ Success test passed: 11 logs captured, 1 SUCCESS
✓ Failure test passed: 29 logs captured
✓ Log structure test passed: 11 entries validated
✓ Viewer generation passed
============================================================
All tests passed!
```

## Usage

### Running Evaluation with Logs

```bash
# Mock evaluation (automatic log capture)
uv run python -m openadapt_evals.benchmarks.cli mock --tasks 5 --output /tmp/results

# Live evaluation (automatic log capture)
uv run python -m openadapt_evals.benchmarks.cli live --agent api-claude --server http://vm:5000

# Generate viewer
uv run python -m openadapt_evals.benchmarks.cli view --run-name my_eval --benchmark-dir /tmp/results
```

### Programmatic Usage

```python
from openadapt_evals import WAAMockAdapter, SmartMockAgent, evaluate_agent_on_benchmark
from openadapt_evals.benchmarks.runner import EvaluationConfig
from openadapt_evals.benchmarks.viewer import generate_benchmark_viewer
from pathlib import Path

# Run evaluation
config = EvaluationConfig(
    max_steps=15,
    save_execution_traces=True,  # Enables log capture
    output_dir='benchmark_results',
)

results = evaluate_agent_on_benchmark(
    agent=SmartMockAgent(),
    adapter=WAAMockAdapter(),
    config=config
)

# Generate viewer with logs
viewer_path = generate_benchmark_viewer(
    benchmark_dir=Path('benchmark_results/waa_eval_20260118'),
)
```

### Viewing Logs in Browser

1. Open the generated `benchmark.html` or `viewer.html`
2. Select a task from the list
3. Scroll down to the "Execution Logs" panel
4. Use the search box to filter by text
5. Click log level buttons to filter by severity
6. Click the panel header to collapse/expand

## Benefits

1. **Debugging**: See exactly what happened during task execution
2. **Performance**: Identify slow steps via timestamps
3. **Error tracking**: Quickly find errors and warnings
4. **Transparency**: Full visibility into agent decision-making
5. **Reproducibility**: Logs are saved with execution traces

## Future Enhancements (Optional)

- [ ] Log export to text file
- [ ] Log highlighting (syntax highlighting for structured messages)
- [ ] Log level statistics (count of each level)
- [ ] Scroll to log from step (link step to its logs)
- [ ] Multi-task log comparison
- [ ] Log playback (show logs as steps progress)

## Files Modified

1. `openadapt_evals/benchmarks/data_collection.py` - Log capture infrastructure
2. `openadapt_evals/benchmarks/runner.py` - Enhanced logging statements
3. `openadapt_evals/benchmarks/viewer.py` - Log panel UI and functionality

## Files Added

1. `test_execution_logs.py` - Comprehensive test suite
2. `EXECUTION_LOGS_IMPLEMENTATION.md` - This documentation

## Backward Compatibility

✅ Fully backward compatible:
- Old execution.json files without logs still work (logs default to empty array)
- Viewer gracefully handles missing logs with "No logs available" message
- Log capture can be disabled via `capture_logs=False` in ExecutionTraceCollector
