--- a
+++ b/main.py
@@ -0,0 +1,55 @@
+
+import argparse
+from whs import load_model
+from overlay import launch_overlay
+
+
+def get_inputs():
+    # Create the parser
+    parser = argparse.ArgumentParser(description='Toggle between Local LLM and ChatGPT.')
+    parser.add_argument('--auto', action='store_true', default=False, help='Automatically get commentary')
+    parser.add_argument('--api_whisper', action='store_true', default=False, help='Run whisper through api instead of locally')
+    parser.add_argument('--api_gpt', action='store_true', default=False, help='Will use use gpt api otherwise, by defualt will use a local LLM through the text-generation-webui API')
+
+    
+    # Parse the arguments
+    args = parser.parse_args()
+
+    # Extract the specific arguments
+    auto = args.auto
+    api_whisper = args.api_whisper
+    api_gpt = args.api_gpt
+
+    return auto, api_whisper, api_gpt
+
+def get_whisper_model(api_whisper):
+    # Load the model
+    # If api_whisper is true, then we will not load the model
+    # This is because we will use the api instead
+    if api_whisper:
+        whs_model = None
+    else:
+        # Load the model
+        whs_model = load_model()
+   
+    return whs_model
+
+def main(whs_model, auto):
+
+    # Launch the GUI in the main thread
+    launch_overlay(whs_model, auto )
+    
+
+if __name__ == "__main__":
+    # Get the inputs
+    auto, api_whisper, api_gpt  =  get_inputs()
+
+    # Get the model
+    whs_model = get_whisper_model(api_whisper)
+
+    # Run the main function
+    main(whs_model, auto)
+
+
+
+