🐛 debug

Signed-off-by: peter szemraj <[email protected]>

app.py

@@ -34,7 +34,7 @@ from grammar_improve import (
     symspeller,
     synthesize_grammar,
 )
-from utils import corr
+from utils import corr, setup_logging
 
 nltk.download("stopwords")  # download stopwords
 
@@ -71,7 +71,7 @@ def chat(
         top_p=top_p,
         top_k=top_k,
         temperature=temperature,
-        constrained_generation="true" in constrained_generation.lower(),
+        constrained_generation=constrained_generation,
     )
     history = [prompt_message, response]
     html = ""
@@ -182,26 +182,47 @@ def get_parser():
     )
 
     parser.add_argument(
-        "--verbose",
+        "--test",
         action="store_true",
         default=False,
-        help="turn on verbose logging",
+        help="load the smallest model for simple testing (ethzanalytics/distilgpt2-tiny-conversational)",
     )
+
     parser.add_argument(
-        "--test",
+        "--verbose",
         action="store_true",
         default=False,
-        help="load the smallest model for simple testing (ethzanalytics/distilgpt2-tiny-conversational)",
+        help="turn on verbose printing",
+    )
+    parser.add_argument(
+        "-q",
+        "--quiet",
+        dest="loglevel",
+        help="set loglevel to WARNING (reduce output)",
+        action="store_const",
+        const=logging.WARNING,
+    )
+    parser.add_argument(
+        "-vv",
+        "--very-verbose",
+        dest="loglevel",
+        help="set loglevel to DEBUG",
+        action="store_const",
+        const=logging.DEBUG,
     )
-
     return parser
 
 
 if __name__ == "__main__":
     args = get_parser().parse_args()
+    loglevel = args.loglevel or logging.INFO
+    setup_logging(loglevel)
+    logging.info("\n\n\nStarting app.py\n\n\n")
+    logging.info(f"args: {args}")
+
     default_model = str(args.model)
-    test = args.test
-    if test:
+
+    if args.test:
         logging.info("loading the smallest model for testing")
         default_model = "ethzanalytics/distilgpt2-tiny-conversational"
 
@@ -217,16 +238,16 @@ if __name__ == "__main__":
         if model_loc.exists() and model_loc.is_dir()
         else pipeline("text-generation", model=default_model, device=device)
     )  # if the model is a name, use it. stays on CPU if no GPU available
-    print(f"using model {my_chatbot.model}")
+    logging.info(f"using model {my_chatbot.model}")
 
     if basic_sc:
-        print("Using the baseline spellchecker")
+        logging.info("Using the baseline spellchecker")
         basic_spell = build_symspell_obj()
     else:
-        print("using neural spell checker")
+        logging.info("using neural spell checker")
         grammarbot = pipeline("text2text-generation", gram_model, device=device)
 
-    logging.info(f"using model stored here: \n {model_loc} \n")
+    logging.debug(f"using model stored here: \n {model_loc} \n")
     iface = gr.Interface(
         chat,
         inputs=[
@@ -242,8 +263,8 @@ if __name__ == "__main__":
             Slider(minimum=0.0, maximum=1.0, step=0.01, default=0.95, label="top_p"),
             Slider(minimum=0, maximum=100, step=5, default=20, label="top_k"),
             Radio(
-                choices=["True", "False"],
-                default="False",
+                choices=[True, False],
+                default=False,
                 label="constrained_generation",
             ),
         ],