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

# Key Concepts

> Key concepts of Podonos SDK

## Intro

The Podonos SDK has three major components: [Client](#client), [Evaluator](#evaluator), and [File](#file).

## Three Key Components

### Client

Client manages multiple evaluations and can create multiple [Evaluator](#evaluator)s. Each evaluator corresponds to one types of evaluation (e.g., naturalness, preferences). So if you want to evaluate your inputs along multiple dimensions, you will create multiple evaluators from one client like:

<CodeGroup>
  ```python simple theme={null}
  etor_natural = client.create_evaluator(
      name='My first naturalness evaluation',
      desc='My new speech generation model',
      type='NMOS', lan='en-us', num_eval=7
  )
  ```

  ```python full theme={null}
  etor = client.create_evaluator(
      name='Naturalness evaluation',
      desc='My model can speak French fluently?',
      type='NMOS',
      lan='fr-fr',
      num_eval=7,
      use_annotation=False,
      use_loudness_normalization=True,
      max_upload_workers=20
  )

  ```

  ```python multiple theme={null}
  etor_natural = client.create_evaluator(
      name='My first naturalness evaluation',
      desc='My new speech generation model',
      type='NMOS', lan='en-us', num_eval=7
  )

  etor_pref = client.create_evaluator(
      name='Preferences my model vs Google',
      desc='Measure human preferences between my model and Google TTS',
      type='PREF', lan='en-us', num_eval=10
  )

  ```
</CodeGroup>

There are key parameters:

* `name`: Name of the evaluation.
* `desc`: Detailed description of the evaluation.
* `type`: One of the evaluation types. For details, see **type** in [create\_evaluator()](reference#create-evaluator).
* `lan`: Language to be evaluated. Real human who fluently speaks the language and lives in the country will evaluate.
* `num_eval`: The number of people who evaluates one file. The higher this number is, the more reliable the evaluation will be.
* `use_annotation`: This is for uncovering the evaluation details.
* `use_loudness_normalization`: When set to true, audio files will be volume-normalized before evaluation.
* `max_upload_workers`: The maximum number of upload workers.

You can also get the whole list of evaluations you created so far by calling [get\_evaluation\_list()](reference#get-evaluation-list).

```python Python theme={null}
eval_list = client.get_evaluation_list()
print(eval_list)
```

In addition, you can get the detailed statistics of one evaluation:

```python Python theme={null}
eval_detail_list = client.get_stats_json_by_id(evaluation_id='<EVALUATION_ID>')
print(eval_detail_list)
```

For more details, see [get\_stats\_json\_by\_id()](reference#get-stats-dict-by-id).

### Evaluator

Evaluator object manages the details of one evaluation type. With this object, you can add files to evaluate.

<CodeGroup>
  ```python add_file() theme={null}
  etor.add_file(file=myfile)
  ```

  ```python add_files() theme={null}
  etor.add_files(file0=myfile0, file1=myfile1)
  ```
</CodeGroup>

### File

File represents one file and its details.

```python theme={null}
File(path='/path/to/1.mp3', model_tag='my_new_model',
     tags=['male', 'american', 'narrative'])
```

Here are the key parameters:

* `path`: Path to the file to evaluate.
* `model_tag`: Name of your model (or any unique name). In the evluation report, you will see the statistics grouped by this model name.
* `tags`: List of multiple tags strings. In the evaluation report, you can see the statistics grouped by one or more tags.

For more details, see [File](reference#file).

### Tags

In the [File](keyconcepts#file) above, you see the two parameters: `model_tag` and `tags`. The `model_tag` may be
the name of your AI model our any other unique name. `tags` are any unique strings that describes the attributes of
the file. They may include training parameters, genders, voice types, ages, regions, or any.