> ## Documentation Index
> Fetch the complete documentation index at: https://www.getmaxim.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# decorators.Generation

> Generation utilities for decorators for automatic logging and instrumentation of functions and methods.

[View module source on GitHub](https://github.com/maximhq/maxim-py/blob/main/maxim/decorators/generation.py)

#### current\_generation

```python theme={null}
def current_generation() -> Optional[Generation]
```

Get the current generation from the context variable.

**Returns**:

| Name                                                                          | Description                                    |
| ----------------------------------------------------------------------------- | ---------------------------------------------- |
| `Optional[[Generation](/sdk/python/references/logger/components/generation)]` | The current generation instance if one exists, |

otherwise None.

#### generation

```python theme={null}
def generation(logger: Optional[Logger] = None,
               id: Optional[Union[Callable, str]] = None,
               name: Optional[str] = None,
               maxim_prompt_id: Optional[str] = None,
               tags: Optional[Dict[str, str]] = None,
               evaluators: Optional[List[str]] = None,
               evaluator_variables: Optional[Dict[str, str]] = None)
```

Decorator for tracking AI model generations with [Maxim](/sdk/python/references/maxim) logging.

This decorator wraps functions to automatically create and manage [Generation](/sdk/python/references/logger/components/generation)
objects for tracking AI model calls, including inputs, outputs, and metadata.
The decorated function must be called within a @trace or @span decorated context.

**Arguments**:

| Name     | Type                                                        | Description                                                                      |
| -------- | ----------------------------------------------------------- | -------------------------------------------------------------------------------- |
| `logger` | *Optional\[[Logger](/sdk/python/references/logger/logger)]* | [Maxim](/sdk/python/references/maxim) logger instance. If None, uses the current |

logger from context.

* `id` *Optional\[Union\[Callable, str]]* - Generation ID. Can be a string or a
  callable that returns a string. If None, generates a UUID.
* `name` *Optional\[str]* - Human-readable name for the generation.
* `maxim_prompt_id` *Optional\[str]* - ID of the Maxim prompt template used.
* `tags` *Optional\[Dict\[str, str]]* - Key-value pairs for tagging the generation.
* `evaluators` *Optional\[List\[str]]* - List of evaluator names to run on this
  generation.
* `evaluator_variables` *Optional\[Dict\[str, str]]* - Variables to pass to
  evaluators.

**Returns**:

| Name       | Description                                            |
| ---------- | ------------------------------------------------------ |
| `Callable` | The decorator function that wraps the target function. |

**Raises**:

* `ValueError` - If no logger is found or if called outside of a trace/span context
  when raise\_exceptions is True.

**Example**:

```python theme={null}
import maxim

logger = maxim.Logger(api_key="your-api-key")

@logger.trace()
def my_ai_workflow():
    result = generate_text("Hello world")
    return result

@generation(
    name="text_generation",
    tags={"model": "gpt-4", "temperature": "0.7"},
    evaluators=["coherence", "relevance"]
)
def generate_text(prompt: str) -> str:
    # Your AI generation logic here
    return "Generated response"
```