update

libs/agno/agno/models/ollama/tools.py

@@ -120,70 +120,6 @@ def parse_provider_response(self, response: ChatResponse) -> ModelResponse:
                 )
         return model_response
 
-    # def create_assistant_message(self, response: Mapping[str, Any], metrics: Metrics) -> Message:
-    #     """
-    #     Create an assistant message from the response.
-
-    #     Args:
-    #         response: The response from Ollama.
-    #         metrics: The metrics for this response.
-
-    #     Returns:
-    #         Message: The assistant message.
-    #     """
-    #     message_data = MessageData()
-
-    #     message_data.response_message = response.get("message")
-    #     if message_data.response_message:
-    #         message_data.response_content = message_data.response_message.get("content")
-    #         message_data.response_role = message_data.response_message.get("role")
-
-    #     assistant_message = Message(
-    #         role=message_data.response_role or "assistant",
-    #         content=message_data.response_content,
-    #     )
-    # -*- Check if the response contains a tool call
-    # try:
-    #     if message_data.response_content is not None:
-    #         if "<tool_call>" in message_data.response_content and "</tool_call>" in message_data.response_content:
-    #             # Break the response into tool calls
-    #             tool_call_responses = message_data.response_content.split("</tool_call>")
-    #             for tool_call_response in tool_call_responses:
-    #                 # Add back the closing tag if this is not the last tool call
-    #                 if tool_call_response != tool_call_responses[-1]:
-    #                     tool_call_response += "</tool_call>"
-
-    #                 if "<tool_call>" in tool_call_response and "</tool_call>" in tool_call_response:
-    #                     # Extract tool call string from response
-    #                     tool_call_content = extract_tool_call_from_string(tool_call_response)
-    #                     # Convert the extracted string to a dictionary
-    #                     try:
-    #                         tool_call_dict = json.loads(tool_call_content)
-    #                     except json.JSONDecodeError:
-    #                         raise ValueError(f"Could not parse tool call from: {tool_call_content}")
-
-    #                     tool_call_name = tool_call_dict.get("name")
-    #                     tool_call_args = tool_call_dict.get("arguments")
-    #                     function_def = {"name": tool_call_name}
-    #                     if tool_call_args is not None:
-    #                         function_def["arguments"] = json.dumps(tool_call_args)
-    #                     message_data.tool_calls.append(
-    #                         {
-    #                             "type": "function",
-    #                             "function": function_def,
-    #                         }
-    #                     )
-    # except Exception as e:
-    #     logger.warning(e)
-    #     pass
-
-    #     if message_data.tool_calls is not None:
-    #         assistant_message.tool_calls = message_data.tool_calls
-
-    #     # -*- Update metrics
-    #     self.update_usage_metrics(assistant_message=assistant_message, metrics=metrics, response=response)
-    #     return assistant_message
-
     def _create_function_call_result(
         self, fc: FunctionCall, success: bool, output: Optional[Union[List[Any], str]], timer: Timer
     ) -> Message: