diff --git a/swarms/agents/utils/AgentBuilder.py b/swarms/agents/utils/AgentBuilder.py
index 2b11930b..e26ffdf9 100644
--- a/swarms/agents/utils/AgentBuilder.py
+++ b/swarms/agents/utils/AgentBuilder.py
@@ -9,8 +9,8 @@ from langchain.chat_models.base import BaseChatModel
 from langchain.schema import BaseOutputParser
 from langchain.callbacks.base import BaseCallbackManager
 
-from .chat_agent import ConversationalChatAgent
-from .llm import ChatOpenAI
+from .ConversationalChatAgent import ConversationalChatAgent
+from .ChatOpenAI import ChatOpenAI
 from .EvalOutputParser import EvalOutputParser
 
 
diff --git a/swarms/agents/utils/AgentManager.py b/swarms/agents/utils/AgentManager.py
index 4582590a..2e7b201c 100644
--- a/swarms/agents/utils/AgentManager.py
+++ b/swarms/agents/utils/AgentManager.py
@@ -10,7 +10,7 @@ from langchain.memory.chat_memory import BaseChatMemory
 
 from swarms.tools.main import BaseToolSet, ToolsFactory
 from .AgentBuilder import AgentBuilder
-from .callback import EVALCallbackHandler, ExecutionTracingCallbackHandler
+from .Calback import EVALCallbackHandler, ExecutionTracingCallbackHandler
 
 
 CallbackManager.set_handler(handler=EVALCallbackHandler())
diff --git a/swarms/agents/utils/callback.py b/swarms/agents/utils/Calback.py
similarity index 100%
rename from swarms/agents/utils/callback.py
rename to swarms/agents/utils/Calback.py
diff --git a/swarms/agents/utils/llm.py b/swarms/agents/utils/ChatOpenAI.py
similarity index 100%
rename from swarms/agents/utils/llm.py
rename to swarms/agents/utils/ChatOpenAI.py
diff --git a/swarms/agents/utils/chat_agent.py b/swarms/agents/utils/ConversationalChatAgent.py
similarity index 78%
rename from swarms/agents/utils/chat_agent.py
rename to swarms/agents/utils/ConversationalChatAgent.py
index 811cb54d..b95c49ea 100644
--- a/swarms/agents/utils/chat_agent.py
+++ b/swarms/agents/utils/ConversationalChatAgent.py
@@ -1,4 +1,5 @@
 from typing import Any, List, Optional, Sequence, Tuple
+import logging
 
 from langchain.agents.agent import Agent
 from langchain.callbacks.base import BaseCallbackManager
@@ -22,6 +23,7 @@ from langchain.tools.base import BaseTool
 
 from swarms.prompts.prompts import EVAL_TOOL_RESPONSE
 
+logging.basicConfig(level=logging.DEBUG, format='%(asctime)s - %(levelname)s - %(message)s')
 
 class ConversationalChatAgent(Agent):
     """An agent designed to hold a conversation in addition to using tools."""
@@ -51,6 +53,17 @@ class ConversationalChatAgent(Agent):
         output_parser: BaseOutputParser,
         input_variables: Optional[List[str]] = None,
     ) -> BasePromptTemplate:
+        if not isinstance(tools, Sequence):
+            raise TypeError("Tools must be a sequence")
+        if not isinstance(system_message, str):
+            raise TypeError("System message must be a string")
+        if not isinstance(human_message, str):
+            raise TypeError("Human message must be a string")
+        if not isinstance(output_parser, BaseOutputParser):
+            raise TypeError("Output parser must be an instance of BaseOutputParser")
+        if input_variables and not isinstance(input_variables, list):
+            raise TypeError("Input variables must be a list")
+
         tool_strings = "\n".join(
             [f"> {tool.name}: {tool.description}" for tool in tools]
         )
@@ -75,7 +88,8 @@ class ConversationalChatAgent(Agent):
         try:
             response = self.output_parser.parse(llm_output)
             return response["action"], response["action_input"]
-        except Exception:
+        except Exception as e:
+            logging.error(f"Error while extracting tool and input: {str(e)}")
             raise ValueError(f"Could not parse LLM output: {llm_output}")
 
     def _construct_scratchpad(
@@ -118,9 +132,13 @@ class ConversationalChatAgent(Agent):
             callback_manager=callback_manager,
         )
         tool_names = [tool.name for tool in tools]
-        return cls(
-            llm_chain=llm_chain,
-            allowed_tools=tool_names,
-            output_parser=output_parser,
-            **kwargs,
-        )
\ No newline at end of file
+        try:
+            return cls(
+                llm_chain=llm_chain,
+                allowed_tools=tool_names,
+                output_parser=output_parser,
+                **kwargs,
+            )
+        except Exception as e:
+            logging.error(f"Error while creating agent from LLM and tools: {str(e)}")
+            raise e
\ No newline at end of file