do not use dataclass

app.py

@@ -132,34 +132,37 @@ class App:
                         files_subtitles = gr.Files(label="Downloadable output file", scale=3, interactive=False)
 
                     params = [input_file, dd_file_format, cb_timestamp]
-                    whisper_params = WhisperParameters(model_size=dd_model,
-                                                       lang=dd_lang,
-                                                       is_translate=cb_translate,
-                                                       beam_size=nb_beam_size,
-                                                       log_prob_threshold=nb_log_prob_threshold,
-                                                       no_speech_threshold=nb_no_speech_threshold,
-                                                       compute_type=dd_compute_type,
-                                                       best_of=nb_best_of,
-                                                       patience=nb_patience,
-                                                       condition_on_previous_text=cb_condition_on_previous_text,
-                                                       initial_prompt=tb_initial_prompt,
-                                                       temperature=sd_temperature,
-                                                       compression_ratio_threshold=nb_compression_ratio_threshold,
-                                                       vad_filter=cb_vad_filter,
-                                                       threshold=sd_threshold,
-                                                       min_speech_duration_ms=nb_min_speech_duration_ms,
-                                                       max_speech_duration_s=nb_max_speech_duration_s,
-                                                       min_silence_duration_ms=nb_min_silence_duration_ms,
-                                                       window_size_sample=nb_window_size_sample,
-                                                       speech_pad_ms=nb_speech_pad_ms,
-                                                       chunk_length_s=nb_chunk_length_s,
-                                                       batch_size=nb_batch_size,
-                                                       is_diarize=cb_diarize,
-                                                       hf_token=tb_hf_token,
-                                                       diarization_device=dd_diarization_device)
+
+                    whisper_params = [
+                        dd_model,
+                        dd_lang,
+                        cb_translate,
+                        nb_beam_size,
+                        nb_log_prob_threshold,
+                        nb_no_speech_threshold,
+                        dd_compute_type,
+                        nb_best_of,
+                        nb_patience,
+                        cb_condition_on_previous_text,
+                        tb_initial_prompt,
+                        sd_temperature,
+                        nb_compression_ratio_threshold,
+                        cb_vad_filter,
+                        sd_threshold,
+                        nb_min_speech_duration_ms,
+                        nb_max_speech_duration_s,
+                        nb_min_silence_duration_ms,
+                        nb_window_size_sample,
+                        nb_speech_pad_ms,
+                        nb_chunk_length_s,
+                        nb_batch_size,
+                        cb_diarize,
+                        tb_hf_token,
+                        dd_diarization_device
+                    ]
 
                     btn_run.click(fn=self.whisper_inf.transcribe_file,
-                                  inputs=params + whisper_params.as_list(),
+                                  inputs=params + whisper_params,
                                   outputs=[tb_indicator, files_subtitles])
                     dd_model.change(fn=self.on_change_models, inputs=[dd_model], outputs=[cb_translate])