diff --git a/swarmauri/standard/llms/concrete/ShuttleAIToolModel.py b/swarmauri/standard/llms/concrete/ShuttleAIToolModel.py
index c4e4a24ef..ebf87ec20 100644
--- a/swarmauri/standard/llms/concrete/ShuttleAIToolModel.py
+++ b/swarmauri/standard/llms/concrete/ShuttleAIToolModel.py
@@ -1,14 +1,17 @@
 import json
 import logging
 from typing import List, Literal, Dict, Any
-import requests 
+import requests
 from swarmauri.core.typing import SubclassUnion
 
 from swarmauri.standard.messages.base.MessageBase import MessageBase
 from swarmauri.standard.messages.concrete.AgentMessage import AgentMessage
 from swarmauri.standard.messages.concrete.FunctionMessage import FunctionMessage
 from swarmauri.standard.llms.base.LLMBase import LLMBase
-from swarmauri.standard.schema_converters.concrete.ShuttleAISchemaConverter import ShuttleAISchemaConverter
+from swarmauri.standard.schema_converters.concrete.ShuttleAISchemaConverter import (
+    ShuttleAISchemaConverter,
+)
+
 
 class ShuttleAIToolModel(LLMBase):
     api_key: str
@@ -24,87 +27,100 @@ class ShuttleAIToolModel(LLMBase):
         "wizardlm-2-8x22b",
         "mistral-7b-instruct-v0.2",
         "gemini-1.5-pro-latest",
-        "gemini-1.0-pro-latest"
+        "gemini-1.0-pro-latest",
     ]
     name: str = "shuttle-2-turbo"
-    type: Literal['ShuttleAIToolModel'] = 'ShuttleAIToolModel'
-    
+    type: Literal["ShuttleAIToolModel"] = "ShuttleAIToolModel"
+
     def _schema_convert_tools(self, tools) -> List[Dict[str, Any]]:
         return [ShuttleAISchemaConverter().convert(tools[tool]) for tool in tools]
 
-    def _format_messages(self, messages: List[SubclassUnion[MessageBase]]) -> List[Dict[str, str]]:
-        message_properties = ['content', 'role', 'name', 'tool_call_id', 'tool_calls']
-        formatted_messages = [message.model_dump(include=message_properties, exclude_none=True) for message in messages]
+    def _format_messages(
+        self, messages: List[SubclassUnion[MessageBase]]
+    ) -> List[Dict[str, str]]:
+        message_properties = ["content", "role", "name", "tool_call_id", "tool_calls"]
+        formatted_messages = [
+            message.model_dump(include=message_properties, exclude_none=True)
+            for message in messages
+        ]
         return formatted_messages
-    
-    def predict(self, 
-        conversation, 
-        toolkit=None, 
-        tool_choice=None, 
-        temperature=0.7, 
-        max_tokens=1024, 
-        top_p=1.0, 
-        internet=True, 
-        raw=False, 
-        image=None, 
-        citations=True, 
-        tone='precise'):
 
+    def predict(
+        self,
+        conversation,
+        toolkit=None,
+        tool_choice=None,
+        temperature=0.7,
+        max_tokens=1024,
+        top_p=1.0,
+        internet=True,
+        raw=False,
+        image=None,
+        citations=True,
+        tone="precise",
+    ):
         formatted_messages = self._format_messages(conversation.history)
 
         if toolkit and not tool_choice:
             tool_choice = "auto"
 
         url = "https://api.shuttleai.app/v1/chat/completions"
-        headers = { 
-            "Authorization": f"Bearer {self.api_key}", 
-            "Content-Type": "application/json", 
+        headers = {
+            "Authorization": f"Bearer {self.api_key}",
+            "Content-Type": "application/json",
         }
 
-        formatted_messages = self._format_messages(conversation.history) 
- 
-        payload = { 
-            "model": self.name, 
-            "messages": formatted_messages, 
-            "max_tokens": max_tokens, 
-            "temperature": temperature, 
-            "top_p": top_p, 
-            "internet": internet, 
-            "raw": raw, 
-            "image": image, 
-            "tool_choice": tool_choice, 
+        formatted_messages = self._format_messages(conversation.history)
+
+        payload = {
+            "model": self.name,
+            "messages": formatted_messages,
+            "max_tokens": max_tokens,
+            "temperature": temperature,
+            "top_p": top_p,
+            "internet": internet,
+            # "raw": raw,
+            # "image": image,
+            "tool_choice": tool_choice,
             "tools": self._schema_convert_tools(toolkit.tools),
-        } 
+        }
 
-        if self.name in ['gpt-4-bing', 'gpt-4-turbo-bing']: 
-            payload['tone'] = tone 
-            payload['citations'] = citations  
+        if self.name in ["gpt-4-bing", "gpt-4-turbo-bing"]:
+            payload["tone"] = tone
+            payload["citations"] = citations
 
-        agent_response = requests.request("POST", url, json=payload, headers=headers) 
-        logging.info(agent_response.json()) 
+        agent_response = requests.request("POST", url, json=payload, headers=headers)
+        logging.info(agent_response.json())
 
-        try: 
-            messages = [formatted_messages[-1], agent_response.json()['choices'][0]['message']['content']]
-        except Exception as error: 
-            logging.warn(error) 
-        tool_calls = agent_response.json()['choices'][0]['message'].get('tool_calls', None) 
+        try:
+            messages = [
+                formatted_messages[-1],
+                agent_response.json()["choices"][0]["message"]["content"],
+            ]
+        except Exception as error:
+            logging.warn(error)
+        tool_calls = agent_response.json()["choices"][0]["message"].get(
+            "tool_calls", None
+        )
         if tool_calls:
             for tool_call in tool_calls:
-                func_name = tool_call['function']['name'] 
+                func_name = tool_call["function"]["name"]
                 func_call = toolkit.get_tool_by_name(func_name)
-                func_args = json.loads(tool_call['function']['arguments']) 
+                func_args = json.loads(tool_call["function"]["arguments"])
                 func_result = func_call(**func_args)
                 messages.append(
                     {
-                        "tool_call_id": tool_call.id,
+                        "tool_call_id": tool_call["id"],
                         "role": "tool",
                         "name": func_name,
                         "content": func_result,
                     }
                 )
-        logging.info(f'messages: {messages}')
+        logging.info(f"messages: {messages}")
         logging.info(f"agent_response: {agent_response.json()}")
-        agent_message = AgentMessage(content=agent_response.json()['choices'][0]['message']['content'])
+        agent_message = AgentMessage(
+            content=agent_response.json()["choices"][0]["message"]["content"]
+        )
         conversation.add_message(agent_message)
         logging.info(f"conversation: {conversation}")
-        return conversation
\ No newline at end of file
+        return conversation