ragas Agent Skills & AI Rules

# Async Evaluation

## aevaluate()

::: ragas.evaluation.aevaluate

## Async Usage

Ragas provides both synchronous and asynchronous evaluation APIs to accommodate different use cases:

### Using aevaluate() (Recommended for Production)

For production async applications, use `aevaluate()` to avoid event loop conflicts:

```python
import asyncio
from ragas import aevaluate

async def evaluate_app():
    result = await aevaluate(dataset, metrics)
    return result

# In your async application
result = await evaluate_app()
```

### Using evaluate() with Async Control

For backward compatibility and Jupyter notebook usage, `evaluate()` provides optional control over `nest_asyncio`:

```python
# Default behavior (Jupyter-compatible)
result = evaluate(dataset, metrics)  # allow_nest_asyncio=True

# Production-safe (avoids event loop patching)
result = evaluate(dataset, metrics, allow_nest_asyncio=False)
```

### Migration from nest_asyncio Issues

If you're experiencing issues with `nest_asyncio` in production:

**Before (problematic):**
```python
# This may cause event loop conflicts
result = evaluate(dataset, metrics)
```

**After (fixed):**
```python
# Option 1: Use async API
result = await aevaluate(dataset, metrics)

# Option 2: Disable nest_asyncio
result = evaluate(dataset, metrics, allow_nest_asyncio=False)
```