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

# dataset

## Dataset

Object-centric interface for Galileo datasets.

This class provides an intuitive way to work with Galileo datasets,
encapsulating dataset management operations and providing seamless
integration with dataset content management.

**Examples**

```python theme={null}
# Create a new dataset locally, then persist
dataset = Dataset(
    name="ml-knowledge-evaluation_3",
    content=[
        {"input": "What is machine learning?", "output": "Machine learning ..."},
        {"input": "How does deep learning work?", "output": "Deep learning uses ..."}
    ]
).create()

# Get an existing dataset
dataset = Dataset.get(name="geography-questions")

# List all datasets
datasets = Dataset.list(limit=50)

# Get dataset content
content = dataset.get_content()

# Add rows to dataset
dataset.add_rows([
    {"input": "Australia", "output": "Oceania"},
    {"input": "Egypt", "output": "Africa"},
])

# Get dataset versions
versions = dataset.get_versions()

# Delete dataset
dataset.delete()
```

### add\_rows

```python theme={null}
def add_rows(self, rows: list[dict[str, Any]]) -> Dataset
```

Add rows to this dataset (active mutation).

This method performs an API call and atomically updates the state.

**Arguments**

* `rows` (`list[dict[str, Any]]`): The rows to add to the dataset.

### create

```python theme={null}
def create(self) -> Dataset
```

Persist this dataset to the API.

**Examples**

```python theme={null}
dataset = Dataset(name="test", content=[...]).create()
assert dataset.is_synced()
```

### delete

```python theme={null}
def delete(self) -> None
```

Delete this dataset.

**Examples**

```python theme={null}
dataset = Dataset.get(name="my-dataset")
dataset.delete()
```

### extend

```python theme={null}
def extend(self,
           *,
           prompt: str | None=None,
           instructions: str | None=None,
           examples: list[str] | None=None,
           count: int=10,
           data_types: list[str] | None=None,
           prompt_settings: dict[str, Any] | None=None) -> list[DatasetRow]
```

Extend this dataset with synthetically generated data.

**Arguments**

* `prompt` (`Optional[str]`): A description of the assistant's role.
* `instructions` (`Optional[str]`): Instructions for the assistant.
* `examples` (`Optional[list[str]]`): Examples of user prompts.
* `count` (`int`): The number of synthetic examples to generate.
* `data_types` (`Optional[list[str]]`): The types of data to generate.
* `prompt_settings` (`Optional[dict[str, Any]]`): Settings for the prompt generation.

### generate

```python theme={null}
def generate(cls,
             *,
             prompt: str | None=None,
             instructions: str | None=None,
             examples: list[str] | None=None,
             count: int=10,
             data_types: list[str] | None=None,
             prompt_settings: dict[str, Any] | None=None) -> list[DatasetRow]
```

Generate synthetic dataset rows.

**Arguments**

* `prompt` (`Optional[str]`): A description of the assistant's role.
* `instructions` (`Optional[str]`): Instructions for the assistant.
* `examples` (`Optional[list[str]]`): Examples of user prompts.
* `count` (`int`): The number of synthetic examples to generate.
* `data_types` (`Optional[list[str]]`): The types of data to generate.
* `prompt_settings` (`Optional[dict[str, Any]]`): Settings for the prompt generation.

### get

```python theme={null}
def get(cls, *, id: str | None=None, name: str | None=None) -> Dataset | None
```

Get an existing dataset by ID or name.

**Arguments**

* `id` (`Optional[str]`): The dataset ID.
* `name` (`Optional[str]`): The dataset name.

### get\_content

```python theme={null}
def get_content(self) -> DatasetContent | None
```

Get the content of this dataset.

**Examples**

```python theme={null}
dataset = Dataset.get(name="my-dataset")
content = dataset.get_content()
```

### get\_version\_content

```python theme={null}
def get_version_content(self, *, index: int) -> DatasetVersionContent
```

Get the content of a specific version of this dataset.

**Arguments**

* `index` (`int`): The 1-based version index to retrieve. Must be >= 1.

### get\_versions

```python theme={null}
def get_versions(self) -> ListDatasetVersionResponse
```

Get a list of versions for this dataset.

**Examples**

```python theme={null}
dataset = Dataset.get(name="my-dataset")
versions = dataset.get_versions()
for v in versions.versions:
    print(v.version_index, v.num_rows)
```

### list

```python theme={null}
def list(cls,
         *,
         limit: Unset | int=100,
         project_id: str | None=None,
         project_name: str | None=None) -> list[Dataset]
```

List all available datasets, optionally filtered by project.

**Arguments**

* `limit` (`Union[Unset, int]`): Maximum number of datasets to return.
* `project_id` (`Optional[str]`): Filter datasets used in this project by ID.
* `project_name` (`Optional[str]`): Filter datasets used in this project by name.

### refresh

```python theme={null}
def refresh(self) -> None
```

Refresh this dataset's state from the API.

Updates all attributes with the latest values from the remote API
and sets the state to SYNCED.

**Examples**

```python theme={null}
dataset.refresh()
assert dataset.is_synced()
```

### save

```python theme={null}
def save(self) -> Dataset
```

Save changes to this dataset.

Persists any local changes (name) to the remote API. If the dataset is
LOCAL\_ONLY, delegates to create(). If SYNCED, returns immediately as a
no-op. Raises ValueError for DELETED or FAILED\_SYNC states.

**Examples**

```python theme={null}
dataset = Dataset.get(name="my-dataset")
dataset.name = "renamed-dataset"
dataset.save()
assert dataset.is_synced()
```