diff --git a/letta/llm_api/anthropic_client.py b/letta/llm_api/anthropic_client.py
index f7509b03..f131e776 100644
--- a/letta/llm_api/anthropic_client.py
+++ b/letta/llm_api/anthropic_client.py
@@ -45,11 +45,13 @@ logger = get_logger(__name__)
 
 class AnthropicClient(LLMClientBase):
 
+    @trace_method
     def request(self, request_data: dict, llm_config: LLMConfig) -> dict:
         client = self._get_anthropic_client(llm_config, async_client=False)
         response = client.beta.messages.create(**request_data, betas=["tools-2024-04-04"])
         return response.model_dump()
 
+    @trace_method
     async def request_async(self, request_data: dict, llm_config: LLMConfig) -> dict:
         client = self._get_anthropic_client(llm_config, async_client=True)
         response = await client.beta.messages.create(**request_data, betas=["tools-2024-04-04"])
@@ -339,6 +341,7 @@ class AnthropicClient(LLMClientBase):
 
     # TODO: Input messages doesn't get used here
     # TODO: Clean up this interface
+    @trace_method
     def convert_response_to_chat_completion(
         self,
         response_data: dict,
diff --git a/letta/llm_api/google_vertex_client.py b/letta/llm_api/google_vertex_client.py
index 2874b62a..e8215813 100644
--- a/letta/llm_api/google_vertex_client.py
+++ b/letta/llm_api/google_vertex_client.py
@@ -17,6 +17,7 @@ from letta.schemas.message import Message as PydanticMessage
 from letta.schemas.openai.chat_completion_request import Tool
 from letta.schemas.openai.chat_completion_response import ChatCompletionResponse, Choice, FunctionCall, Message, ToolCall, UsageStatistics
 from letta.settings import model_settings, settings
+from letta.tracing import trace_method
 from letta.utils import get_tool_call_id
 
 logger = get_logger(__name__)
@@ -32,6 +33,7 @@ class GoogleVertexClient(LLMClientBase):
             http_options={"api_version": "v1"},
         )
 
+    @trace_method
     def request(self, request_data: dict, llm_config: LLMConfig) -> dict:
         """
         Performs underlying request to llm and returns raw response.
@@ -44,6 +46,7 @@ class GoogleVertexClient(LLMClientBase):
         )
         return response.model_dump()
 
+    @trace_method
     async def request_async(self, request_data: dict, llm_config: LLMConfig) -> dict:
         """
         Performs underlying request to llm and returns raw response.
@@ -189,6 +192,7 @@ class GoogleVertexClient(LLMClientBase):
 
         return [{"functionDeclarations": function_list}]
 
+    @trace_method
     def build_request_data(
         self,
         messages: List[PydanticMessage],
@@ -248,6 +252,7 @@ class GoogleVertexClient(LLMClientBase):
 
         return request_data
 
+    @trace_method
     def convert_response_to_chat_completion(
         self,
         response_data: dict,
diff --git a/letta/llm_api/openai_client.py b/letta/llm_api/openai_client.py
index e6ac37a2..d144d03c 100644
--- a/letta/llm_api/openai_client.py
+++ b/letta/llm_api/openai_client.py
@@ -32,6 +32,7 @@ from letta.schemas.openai.chat_completion_request import Tool as OpenAITool
 from letta.schemas.openai.chat_completion_request import ToolFunctionChoice, cast_message_to_subtype
 from letta.schemas.openai.chat_completion_response import ChatCompletionResponse
 from letta.settings import model_settings
+from letta.tracing import trace_method
 
 logger = get_logger(__name__)
 
@@ -124,6 +125,7 @@ class OpenAIClient(LLMClientBase):
 
         return kwargs
 
+    @trace_method
     def build_request_data(
         self,
         messages: List[PydanticMessage],
@@ -213,6 +215,7 @@ class OpenAIClient(LLMClientBase):
 
         return data.model_dump(exclude_unset=True)
 
+    @trace_method
     def request(self, request_data: dict, llm_config: LLMConfig) -> dict:
         """
         Performs underlying synchronous request to OpenAI API and returns raw response dict.
@@ -222,6 +225,7 @@ class OpenAIClient(LLMClientBase):
         response: ChatCompletion = client.chat.completions.create(**request_data)
         return response.model_dump()
 
+    @trace_method
     async def request_async(self, request_data: dict, llm_config: LLMConfig) -> dict:
         """
         Performs underlying asynchronous request to OpenAI API and returns raw response dict.
@@ -230,6 +234,7 @@ class OpenAIClient(LLMClientBase):
         response: ChatCompletion = await client.chat.completions.create(**request_data)
         return response.model_dump()
 
+    @trace_method
     def convert_response_to_chat_completion(
         self,
         response_data: dict,