WIP - first working version with UI, hooray!

- added logging in UI
- added switcher for models, batch size etc.
- added device configuration dataclass
- minor improvements in audio transcription

ui/ui.py

@@ -0,0 +1,123 @@
+import tkinter as tk
+from tkinter.scrolledtext import ScrolledText
+from ui.ui_log_handler import UILogHandler, setup_ui_logger
+from transcription.torch_checker import check_torch
+from transcription.device_configuration import DeviceConfiguration
+from transcription.audio_transcription import AudioTranscription
+
+def main():
+    root = tk.Tk()
+    root.title("Audio Transcriptor")
+    root.geometry("800x600")
+
+    for col in range(4):
+        root.grid_columnconfigure(col, weight=1)
+    root.grid_rowconfigure(6, weight=1)
+
+    ### Buttons selector
+    check_torch_baton = tk.Button(root, text="Check Torch")
+    check_torch_baton.grid(row=0, column=0, padx=5, pady=5, sticky="ew")
+
+    # TODO: implement saving function
+    save_configuration_baton = tk.Button(root, text="Save configuration")
+    save_configuration_baton.grid(row=0, column=1, padx=5, pady=5, sticky="ew")
+
+    # TODO: implement deleting function
+    delete_configuration_baton = tk.Button(root, text="Delete configuration")
+    delete_configuration_baton.grid(row=0, column=2, padx=5, pady=5, sticky="ew")
+
+    start_transcription_baton = tk.Button(root, text="Transcript")
+    start_transcription_baton.grid(row=0, column=3, padx=5, pady=5, sticky="ew")
+
+    ### Model options selector
+    model_options = [
+        "openai/whisper-large-v2",
+        "openai/whisper-large",
+        "openai/whisper-medium",
+        "openai/whisper-small",
+        "openai/whisper-tiny"
+    ]
+    selected_model = tk.StringVar(value=model_options[0])
+    label_model = tk.Label(root, text="Model name:")
+    label_model.grid(row=1, column=0, sticky="w", pady=5, padx=5)
+    dropdown_model_selection = tk.OptionMenu(root, selected_model, *model_options)
+    dropdown_model_selection.grid(row=1, column=1, sticky="ew", pady=5, padx=5)
+
+    ### Batch size selector
+    batch_sizes = ["32", "16", "8", "4", "2"]
+    selected_batch_size = tk.StringVar(value=batch_sizes[0])
+    label_batch_size = tk.Label(root, text="Batch size:")
+    label_batch_size.grid(row=1, column=2, sticky="w", pady=5, padx=5)
+    dropdown_batch_size_selection = tk.OptionMenu(root, selected_batch_size, *batch_sizes)
+    dropdown_batch_size_selection.grid(row=1, column=3, sticky="ew", pady=5, padx=5)
+
+    ### Data type selector
+    data_types = ["torch.float16", "torch.float32", "torch.bfloat16"]
+    selected_data_type = tk.StringVar(value=data_types[0])
+    label_data_type = tk.Label(root, text="Data type:")
+    label_data_type.grid(row=2, column=0, sticky="w", pady=5, padx=5)
+    dropdown_data_type_selection = tk.OptionMenu(root, selected_data_type, *data_types)
+    dropdown_data_type_selection.grid(row=2, column=1, sticky="ew", pady=5, padx=5)
+
+    ### Chunk length selector
+    chunk_lengths = ["30", "25", "20", "15", "10", "5"]
+    selected_chunk_length = tk.StringVar(value=chunk_lengths[0])
+    label_chunk_length = tk.Label(root, text="Chunk length:")
+    label_chunk_length.grid(row=2, column=2, sticky="w", pady=5, padx=5)
+    dropdown_chunk_length_selection = tk.OptionMenu(root, selected_chunk_length, *chunk_lengths)
+    dropdown_chunk_length_selection.grid(row=2, column=3, sticky="ew", pady=5, padx=5)
+    
+    # TODO: add device selector (cuda/mps/cpu)
+
+    ### Filepath (input)
+    # TODO: add checker if path is valid/invalid (i think in utils or something)
+    label_file_path = tk.Label(root, text="Input filepath:")
+    label_file_path.grid(row=3, column=0, sticky="w", pady=5, padx=5)
+    file_path = tk.Text(root, height=1)
+    file_path.grid(row=3, column=1, columnspan=3, sticky="ew", pady=5, padx=5)
+
+    ### Filepath (output)
+    # TODO: add question mark here with tip while mouse is on it
+    label_output_file_path = tk.Label(root, text="Output filepath:")
+    label_output_file_path.grid(row=4, column=0, sticky="w", pady=5, padx=5)
+    output_file_path = tk.Text(root, height=1)
+    output_file_path.grid(row=4, column=1, columnspan=3, sticky="ew", pady=5, padx=5)
+
+    def show_selections():
+        ui_logger.info(f"Selected model: {selected_model.get()}")
+        ui_logger.info(f"Selected batch size: {selected_batch_size.get()} chunks")
+        ui_logger.info(f"Selected data type: {selected_data_type.get()}")
+    
+    show_selections_baton = tk.Button(root, text="Show Selections", command=show_selections)
+    show_selections_baton.grid(row=5, column=0, columnspan=4, pady=5, sticky="ew")
+
+    log_box = ScrolledText(root, wrap="word")
+    log_box.grid(row=6, column=0, columnspan=4, sticky="nsew", padx=10, pady=5)
+    ui_logger = setup_ui_logger(log_box)
+    
+    def transcribe():
+        current_device_config = DeviceConfiguration(
+            device="cuda",
+            model_name=selected_model.get(),
+            batch_size=int(selected_batch_size.get()),
+            chunk_length_s=30,
+            data_type=selected_data_type.get()
+        )
+        Audio = AudioTranscription(
+            filepath=file_path.get("1.0", "end-1c"),
+            device_configuration=current_device_config,
+            logger=ui_logger
+        )
+        transcription = Audio.transcribe_audio()
+        with open(f"{file_path.get('1.0', 'end-1c')}.txt", "w") as output_file:
+            output_file.write(transcription)
+    
+    check_torch_baton.config(command=lambda: check_torch(ui_logger))
+    start_transcription_baton.config(command=transcribe)
+    
+    root.mainloop()
+
+
+
+if __name__ == "__main__":
+    main()