Args now sit in a package

app.py

@@ -1,5 +1,4 @@
 import gradio as gr
-
 from download import check_download, download, download_generator
 import argparse
 import anvil.media
@@ -8,26 +7,17 @@ import pathlib
 from pathlib import Path
 from shutil import rmtree
 import dotenv
-from utils.utils import str2bool
-import whisper
+from utils.utils import get_args
 
 dotenv.load_dotenv()
 
 anvil.server.connect(os.environ.get('ANVIL_UPLINK_KEY'))
 queue_placeholder = None
 
-parser = argparse.ArgumentParser(
-        formatter_class=argparse.ArgumentDefaultsHelpFormatter)
-parser.add_argument("--public", type=str2bool, default=False,
-                    help="Wether to share with gradio public or not")
-parser.add_argument("--preload", type=str2bool, default=True,
-                    help="Should the model be preloaded on script launch. Disable for faster debug")
-parser.add_argument("--model", default="medium",
-                    choices=whisper.available_models(), help="name of the Whisper model to use")
-
-args = parser.parse_args().__dict__
-gradio_share: str = args.get("public")
+args = get_args()
+gradio_share: bool = args.get("public")
 model_size: str = args.get("model")
+preload_model: str = args.get("preload")
 
 url_input = gr.Textbox(label="Youtube/Twitter/etc video URL (supports many services)", value='https://twitter.com/starsonxh/status/1552945347194142720', lines=1, elem_id="url_input")
 download_status = gr.Textbox(label="Status:", value='', lines=1, elem_id="download_status")

download.py

@@ -14,21 +14,14 @@ import whisper
 from whisper.tokenizer import LANGUAGES
 import ffmpeg
 from utils.subs import bake_subs
-from utils.utils import str2bool
+from utils.utils import get_args
 
 original_dir = os.getcwd()
 output_dir = Path('output')
 
-parser = argparse.ArgumentParser(
-        formatter_class=argparse.ArgumentDefaultsHelpFormatter)
-parser.add_argument("--preload", type=str2bool, default=True,
-                    help="Should the model be preloaded on script launch. Disable for faster debug")
-parser.add_argument("--model", default="medium",
-                    choices=whisper.available_models(), help="name of the Whisper model to use")
-
-args = parser.parse_args().__dict__
+args = get_args()
 model_size: str = args.get("model")
-preload_model: str = args.get("preload")
+preload_model: bool = args.get("preload")
 
 if preload_model:
   print("Preloading model")

utils/utils.py

@@ -1,7 +1,23 @@
+import whisper
+import argparse
 def str2bool(string):
   str2val = {"True": True, "False": False}
   if string in str2val:
     return str2val[string]
   else:
     raise ValueError(
-      f"Expected one of {set(str2val.keys())}, got {string}")
+      f"Expected one of {set(str2val.keys())}, got {string}")
+
+def get_args():
+  parser = argparse.ArgumentParser(
+    formatter_class=argparse.ArgumentDefaultsHelpFormatter)
+  parser.add_argument("--public", type=str2bool, default=False,
+                      help="Wether to share with gradio public or not")
+  parser.add_argument("--preload", type=str2bool, default=True,
+                      help="Should the model be preloaded on script launch. Disable for faster debug")
+  parser.add_argument("--model", default="medium",
+                      choices=whisper.available_models(), help="name of the Whisper model to use")
+
+  args = parser.parse_args().__dict__
+  return args
+