proper implemenation of llm_output_parser

- implements the decision making , when 'choice' type output is received .

swarms/structs/agent.py

@@ -1858,20 +1858,21 @@ class Agent:
 
         return response
 
-    def llm_output_parser(self, response: Any) -> str:
+    def llm_output_parser(self, response):
-        """
+        """Parse the output from the LLM"""
-        Parses the response from the LLM (Low-Level Monitor) and returns it as a string.
+        try:
-
+            if isinstance(response, dict):
-        Args:
+                if 'choices' in response:
-            response (Any): The response from the LLM.
+                    return response['choices'][0]['message']['content']
-
+                else:
-        Returns:
+                    return json.dumps(response)  # Convert dict to string
-            str: The parsed response as a string.
+            elif isinstance(response, str):
-        """
+                return response
-        if response is not str:
+            else:
-            response = str(response)
+                return str(response)  # Convert any other type to string
-
+        except Exception as e:
-        return response
+            logger.error(f"Error parsing LLM output: {e}")
+            return str(response)  # Return string representation as fallback
 
     def log_step_metadata(
         self, loop: int, task: str, response: str