diff --git a/tools/common_tools/common_tools.py b/tools/common_tools/common_tools.py
index 1f462ee18..d70b54999 100755
--- a/tools/common_tools/common_tools.py
+++ b/tools/common_tools/common_tools.py
@@ -6,7 +6,8 @@ import uvicorn
 def argsparser():
     parser = argparse.ArgumentParser(description=__doc__)
     parser.add_argument(
-        'tools', choices=['compress', 'convert', 'simple_serving', 'paddle2coreml'])
+        'tools',
+        choices=['compress', 'convert', 'simple_serving', 'paddle2coreml'])
     ## argumentments for auto compression
     parser.add_argument(
         '--config_path',
@@ -89,44 +90,34 @@ def argsparser():
         "--p2c_paddle_model_dir",
         type=str,
         default=None,
-        required=True,
         help="define paddle model path")
     parser.add_argument(
         "--p2c_coreml_model_dir",
         type=str,
         default=None,
-        required=True,
         help="define generated coreml model path")
     parser.add_argument(
         "--p2c_coreml_model_name",
         type=str,
         default="coreml_model",
-        required=False,
         help="define generated coreml model name")
     parser.add_argument(
-        "--p2c_input_names",
-        type=str,
-        default=None,
-        required=True,
-        help="define input names")
+        "--p2c_input_names", type=str, default=None, help="define input names")
     parser.add_argument(
         "--p2c_input_dtypes",
         type=str,
         default="float32",
-        required=True,
         help="define input dtypes")
     parser.add_argument(
         "--p2c_input_shapes",
         type=str,
         default=None,
-        required=True,
-        help="define input shapes") 
+        help="define input shapes")
     parser.add_argument(
         "--p2c_output_names",
         type=str,
         default=None,
-        required=True,
-        help="define output names")  
+        help="define output names")
     ## arguments for other tools
     return parser
 
@@ -214,9 +205,19 @@ def main():
                     app_dir='.',
                     log_config=custom_logging_config)
     if args.tools == "paddle2coreml":
+        if any([
+                args.p2c_paddle_model_dir is None,
+                args.p2c_coreml_model_dir is None,
+                args.p2c_input_names is None, args.p2c_input_shapes is None,
+                args.p2c_output_names is None
+        ]):
+            raise Exception(
+                "paddle2coreml need to define --p2c_paddle_model_dir, --p2c_coreml_model_dir, --p2c_input_names, --p2c_input_shapes, --p2c_output_names"
+            )
         import coremltools as ct
         import os
         import numpy as np
+
         def type_to_np_dtype(dtype):
             if dtype == 'float32':
                 return np.float32
@@ -240,24 +241,29 @@ def main():
                 return np.int16
             else:
                 raise Exception("Unsupported dtype: {}".format(dtype))
+
         input_names = args.p2c_input_names.split(' ')
-        input_shapes = [[int(i) for i in shape.split(',')] for shape in args.p2c_input_shapes.split(' ')]
+        input_shapes = [[int(i) for i in shape.split(',')]
+                        for shape in args.p2c_input_shapes.split(' ')]
         input_dtypes = map(type_to_np_dtype, args.p2c_input_dtypes.split(' '))
         output_names = args.p2c_output_names.split(' ')
-        sample_input = [ct.TensorType(
-                                name=k,
-                                shape=s,
-                                dtype=d,
-                            ) for k, s, d in zip(input_names, input_shapes, input_dtypes)]
+        sample_input = [
+            ct.TensorType(
+                name=k,
+                shape=s,
+                dtype=d, )
+            for k, s, d in zip(input_names, input_shapes, input_dtypes)
+        ]
 
         coreml_model = ct.convert(
             args.p2c_paddle_model_dir,
             convert_to="mlprogram",
             minimum_deployment_target=ct.target.macOS13,
             inputs=sample_input,
-            outputs=[ct.TensorType(name=name) for name in output_names],
-        )
-        coreml_model.save(os.path.join(args.p2c_coreml_model_dir, args.p2c_coreml_model_name))        
+            outputs=[ct.TensorType(name=name) for name in output_names], )
+        coreml_model.save(
+            os.path.join(args.p2c_coreml_model_dir,
+                         args.p2c_coreml_model_name))
 
 
 if __name__ == '__main__':
diff --git a/tools/setup.py b/tools/setup.py
index ccc922ae3..31b807395 100644
--- a/tools/setup.py
+++ b/tools/setup.py
@@ -7,7 +7,7 @@ install_requires = ['uvicorn==0.16.0']
 
 setuptools.setup(
     name="fastdeploy-tools",  # name of package
-    version="0.0.4",  #version of package
+    version="0.0.5",  #version of package
     description="A toolkit for FastDeploy.",
     long_description=long_description,
     long_description_content_type="text/plain",