~ | improve Vercel & g4f.Completion.create

added `.Completion.create` class.

```py
response = g4f.Completion.create(
    model='text-davinci-003', prompt="Hello")

print(response)
```

g4f/Provider/Vercel.py

@@ -48,9 +48,11 @@ class Vercel(BaseProvider):
             'playgroundId': str(uuid.uuid4()),
             'chatIndex'   : 0} | model_info[model]['default_params']
 
-
         server_error = True
-        while server_error:
+        retries      = 0
+        max_retries  = kwargs.get('max_retries', 20)
+        
+        while server_error and not retries > max_retries:
             response = requests.post('https://sdk.vercel.ai/api/generate', 
                                     headers=headers, json=json_data, stream=True)
 
@@ -58,6 +60,8 @@ class Vercel(BaseProvider):
                 if token != b'Internal Server Error':
                     server_error = False
                     yield (token.decode())
+                    
+            retries += 1
 
 def AntiBotToken() -> str:
     headers = {

g4f/__init__.py

@@ -68,3 +68,30 @@ class ChatCompletion:
             raise Exception(f"Provider: {provider.__name__} doesn't support create_async")
 
         return await provider.create_async(model.name, messages, **kwargs)
+
+class Completion:
+    @staticmethod
+    def create(
+        model    : Union[models.Model, str],
+        prompt   : str,
+        provider : Union[type[BaseProvider], None] = None,
+        stream   : bool                            = False, **kwargs) -> Union[CreateResult, str]:
+        
+        allowed_models = [
+            'code-davinci-002',
+            'text-ada-001',
+            'text-babbage-001',
+            'text-curie-001',
+            'text-davinci-002',
+            'text-davinci-003'
+        ]
+        
+        if model not in allowed_models:
+            raise Exception(f'ValueError: Can\'t use {model} with Completion.create()')
+        
+        model, provider = get_model_and_provider(model, provider, stream)
+
+        result = provider.create_completion(model.name, 
+                                            [{"role": "user", "content": prompt}], stream, **kwargs)
+
+        return result if stream else ''.join(result)