add docstring

modules/whisper_data_class.py

@@ -11,12 +11,51 @@ class WhisperGradioComponents:
     log_prob_threshold: gr.Number
     no_speech_threshold: gr.Number
     compute_type: gr.Dropdown
+    """
+    A data class to pass Gradio components to the function before Gradio pre-processing.
+    See this documentation for more info: https://www.gradio.app/docs/components
 
-    def to_list(self):
+    Parameters
+    ----------
+    model_size: gr.Dropdown
+        Whisper model size.
+    lang: gr.Dropdown
+        Source language of the file to transcribe.
+    is_translate: gr.Checkbox
+        Boolean value that determines whether to translate to English.
+        It's Whisper's feature to translate speech from another language directly into English end-to-end.
+    beam_size: gr.Number
+        Int value that is used for decoding option.
+    log_prob_threshold: gr.Number
+        If the average log probability over sampled tokens is below this value, treat as failed.
+    no_speech_threshold: gr.Number
+        If the no_speech probability is higher than this value AND 
+        the average log probability over sampled tokens is below `log_prob_threshold`,
+        consider the segment as silent.
+    compute_type: gr.Dropdown
+        compute type for transcription.
+        see more info : https://opennmt.net/CTranslate2/quantization.html
+    """
+
+    def to_list(self) -> list:
+        """
+        Use this to pass parameters before Gradio pre-processing to the function.
+
+        Returns
+        ----------
+        A list of Gradio components
+        """
         return [getattr(self, f.name) for f in fields(self)]
 
     @staticmethod
     def to_values(*params):
+        """
+        Use this to use parameters after Gradio pre-processing in the function.
+
+        Returns
+        ----------
+        A WhisperValues data class
+        """
         return WhisperValues(*params)
 
 
@@ -29,3 +68,7 @@ class WhisperValues:
     log_prob_threshold: float
     no_speech_threshold: float
     compute_type: str
+    """
+    A data class to use Whisper parameters in the function after gradio pre-processing.
+    See this documentation for more info : https://www.gradio.app/docs/components
+    """