feat: log request data to otel (#1149)

letta/agent.py

@@ -60,7 +60,7 @@ from letta.services.tool_manager import ToolManager
 from letta.settings import summarizer_settings
 from letta.streaming_interface import StreamingRefreshCLIInterface
 from letta.system import get_heartbeat, get_token_limit_warning, package_function_response, package_summarize_message, package_user_message
-from letta.tracing import trace_method
+from letta.tracing import log_event, trace_method
 from letta.utils import count_tokens, get_friendly_error_msg, get_tool_call_id, log_telemetry, parse_json, validate_function_response
 
 logger = get_logger(__name__)
@@ -307,7 +307,7 @@ class Agent(BaseAgent):
         # Return updated messages
         return messages
 
-    @trace_method("Get AI Reply")
+    @trace_method
     def _get_ai_reply(
         self,
         message_sequence: List[Message],
@@ -400,7 +400,7 @@ class Agent(BaseAgent):
         log_telemetry(self.logger, "_handle_ai_response finish catch-all exception")
         raise Exception("Retries exhausted and no valid response received.")
 
-    @trace_method("Handle AI Response")
+    @trace_method
     def _handle_ai_response(
         self,
         response_message: ChatCompletionMessage,  # TODO should we eventually move the Message creation outside of this function?
@@ -538,7 +538,24 @@ class Agent(BaseAgent):
                 log_telemetry(
                     self.logger, "_handle_ai_response execute tool start", function_name=function_name, function_args=function_args
                 )
+                log_event(
+                    "tool_call_initiated",
+                    attributes={
+                        "function_name": function_name,
+                        "target_letta_tool": target_letta_tool.model_dump(),
+                        **{f"function_args.{k}": v for k, v in function_args.items()},
+                    },
+                )
+
                 function_response, sandbox_run_result = self.execute_tool_and_persist_state(function_name, function_args, target_letta_tool)
+
+                log_event(
+                    "tool_call_ended",
+                    attributes={
+                        "function_response": function_response,
+                        "sandbox_run_result": sandbox_run_result.model_dump() if sandbox_run_result else None,
+                    },
+                )
                 log_telemetry(
                     self.logger, "_handle_ai_response execute tool finish", function_name=function_name, function_args=function_args
                 )
@@ -640,7 +657,7 @@ class Agent(BaseAgent):
         log_telemetry(self.logger, "_handle_ai_response finish")
         return messages, heartbeat_request, function_failed
 
-    @trace_method("Agent Step")
+    @trace_method
     def step(
         self,
         messages: Union[Message, List[Message]],
@@ -828,6 +845,13 @@ class Agent(BaseAgent):
                     f"{CLI_WARNING_PREFIX}last response total_tokens ({current_total_tokens}) > {summarizer_settings.memory_warning_threshold * int(self.agent_state.llm_config.context_window)}"
                 )
 
+                log_event(
+                    name="memory_pressure_warning",
+                    attributes={
+                        "current_total_tokens": current_total_tokens,
+                        "context_window_limit": self.agent_state.llm_config.context_window,
+                    },
+                )
                 # Only deliver the alert if we haven't already (this period)
                 if not self.agent_alerted_about_memory_pressure:
                     active_memory_warning = True
@@ -1029,9 +1053,18 @@ class Agent(BaseAgent):
         self.agent_alerted_about_memory_pressure = False
         curr_in_context_messages = self.agent_manager.get_in_context_messages(agent_id=self.agent_state.id, actor=self.user)
 
+        current_token_count = sum(get_token_counts_for_messages(curr_in_context_messages))
         logger.info(f"Ran summarizer, messages length {prior_len} -> {len(curr_in_context_messages)}")
-        logger.info(
-            f"Summarizer brought down total token count from {sum(token_counts)} -> {sum(get_token_counts_for_messages(curr_in_context_messages))}"
+        logger.info(f"Summarizer brought down total token count from {sum(token_counts)} -> {current_token_count}")
+        log_event(
+            name="summarization",
+            attributes={
+                "prior_length": prior_len,
+                "current_length": len(curr_in_context_messages),
+                "prior_token_count": sum(token_counts),
+                "current_token_count": current_token_count,
+                "context_window_limit": self.agent_state.llm_config.context_window,
+            },
         )
 
     def add_function(self, function_name: str) -> str:

letta/llm_api/anthropic.py

@@ -40,6 +40,7 @@ from letta.schemas.openai.chat_completion_response import MessageDelta, ToolCall
 from letta.services.provider_manager import ProviderManager
 from letta.settings import model_settings
 from letta.streaming_interface import AgentChunkStreamingInterface, AgentRefreshStreamingInterface
+from letta.tracing import log_event
 
 BASE_URL = "https://api.anthropic.com/v1"
 
@@ -677,10 +678,12 @@ def anthropic_chat_completions_request(
         inner_thoughts_xml_tag=inner_thoughts_xml_tag,
         put_inner_thoughts_in_kwargs=put_inner_thoughts_in_kwargs,
     )
+    log_event(name="llm_request_sent", attributes=data)
     response = anthropic_client.beta.messages.create(
         **data,
         betas=betas,
     )
+    log_event(name="llm_response_received", attributes={"response": response.json()})
     return convert_anthropic_response_to_chatcompletion(response=response, inner_thoughts_xml_tag=inner_thoughts_xml_tag)
 
 
@@ -698,8 +701,9 @@ def anthropic_bedrock_chat_completions_request(
     try:
         # bedrock does not support certain args
         data["tool_choice"] = {"type": "any"}
-
+        log_event(name="llm_request_sent", attributes=data)
         response = client.messages.create(**data)
+        log_event(name="llm_response_received", attributes={"response": response.json()})
         return convert_anthropic_response_to_chatcompletion(response=response, inner_thoughts_xml_tag=inner_thoughts_xml_tag)
     except PermissionDeniedError:
         raise BedrockPermissionError(f"User does not have access to the Bedrock model with the specified ID. {data['model']}")
@@ -839,6 +843,8 @@ def anthropic_chat_completions_process_stream(
         ),
     )
 
+    log_event(name="llm_request_sent", attributes=chat_completion_request.model_dump())
+
     if stream_interface:
         stream_interface.stream_start()
 
@@ -987,4 +993,6 @@ def anthropic_chat_completions_process_stream(
 
     assert len(chat_completion_response.choices) > 0, chat_completion_response
 
+    log_event(name="llm_response_received", attributes=chat_completion_response.model_dump())
+
     return chat_completion_response

letta/llm_api/azure_openai.py

@@ -8,6 +8,7 @@ from letta.schemas.openai.chat_completion_response import ChatCompletionResponse
 from letta.schemas.openai.chat_completions import ChatCompletionRequest
 from letta.schemas.openai.embedding_response import EmbeddingResponse
 from letta.settings import ModelSettings
+from letta.tracing import log_event
 
 
 def get_azure_chat_completions_endpoint(base_url: str, model: str, api_version: str):
@@ -120,10 +121,12 @@ def azure_openai_chat_completions_request(
         data.pop("tool_choice", None)  # extra safe,  should exist always (default="auto")
 
     url = get_azure_chat_completions_endpoint(model_settings.azure_base_url, llm_config.model, model_settings.azure_api_version)
+    log_event(name="llm_request_sent", attributes=data)
     response_json = make_post_request(url, headers, data)
     # NOTE: azure openai does not include "content" in the response when it is None, so we need to add it
     if "content" not in response_json["choices"][0].get("message"):
         response_json["choices"][0]["message"]["content"] = None
+    log_event(name="llm_response_received", attributes=response_json)
     response = ChatCompletionResponse(**response_json)  # convert to 'dot-dict' style which is the openai python client default
     return response
 

letta/llm_api/google_ai.py

@@ -11,6 +11,7 @@ from letta.local_llm.json_parser import clean_json_string_extra_backslash
 from letta.local_llm.utils import count_tokens
 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.tracing import log_event
 from letta.utils import get_tool_call_id
 
 
@@ -422,7 +423,9 @@ def google_ai_chat_completions_request(
     if add_postfunc_model_messages:
         data["contents"] = add_dummy_model_messages(data["contents"])
 
+    log_event(name="llm_request_sent", attributes=data)
     response_json = make_post_request(url, headers, data)
+    log_event(name="llm_response_received", attributes=response_json)
     try:
         return convert_google_ai_response_to_chatcompletion(
             response_json=response_json,

letta/llm_api/google_vertex.py

@@ -8,6 +8,7 @@ from letta.local_llm.json_parser import clean_json_string_extra_backslash
 from letta.local_llm.utils import count_tokens
 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.tracing import log_event
 from letta.utils import get_tool_call_id
 
 
@@ -323,6 +324,9 @@ def google_vertex_chat_completions_request(
     config["tool_config"] = tool_config.model_dump()
 
     # make request to client
+    attributes = config if isinstance(config, dict) else {"config": config}
+    attributes.update({"contents": contents})
+    log_event(name="llm_request_sent", attributes={"contents": contents, "config": config})
     response = client.models.generate_content(
         model=model,
         contents=contents,

letta/llm_api/llm_api_tools.py

@@ -120,7 +120,7 @@ def retry_with_exponential_backoff(
     return wrapper
 
 
-@trace_method("LLM Request")
+@trace_method
 @retry_with_exponential_backoff
 def create(
     # agent_state: AgentState,

letta/llm_api/openai.py

@@ -25,6 +25,7 @@ from letta.schemas.openai.chat_completion_response import (
 )
 from letta.schemas.openai.embedding_response import EmbeddingResponse
 from letta.streaming_interface import AgentChunkStreamingInterface, AgentRefreshStreamingInterface
+from letta.tracing import log_event
 from letta.utils import get_tool_call_id, smart_urljoin
 
 logger = get_logger(__name__)
@@ -243,6 +244,8 @@ def openai_chat_completions_process_stream(
         ),
     )
 
+    log_event(name="llm_request_sent", attributes=chat_completion_request.model_dump())
+
     if stream_interface:
         stream_interface.stream_start()
 
@@ -406,6 +409,7 @@ def openai_chat_completions_process_stream(
     assert len(chat_completion_response.choices) > 0, f"No response from provider {chat_completion_response}"
 
     # printd(chat_completion_response)
+    log_event(name="llm_response_received", attributes=chat_completion_response.model_dump())
     return chat_completion_response
 
 
@@ -437,7 +441,9 @@ def openai_chat_completions_request(
     """
     data = prepare_openai_payload(chat_completion_request)
     client = OpenAI(api_key=api_key, base_url=url, max_retries=0)
+    log_event(name="llm_request_sent", attributes=data)
     chat_completion = client.chat.completions.create(**data)
+    log_event(name="llm_response_received", attributes=chat_completion.model_dump())
     return ChatCompletionResponse(**chat_completion.model_dump())
 
 

letta/local_llm/chat_completion_proxy.py

@@ -22,6 +22,7 @@ from letta.local_llm.webui.api import get_webui_completion
 from letta.local_llm.webui.legacy_api import get_webui_completion as get_webui_completion_legacy
 from letta.prompts.gpt_summarize import SYSTEM as SUMMARIZE_SYSTEM_MESSAGE
 from letta.schemas.openai.chat_completion_response import ChatCompletionResponse, Choice, Message, ToolCall, UsageStatistics
+from letta.tracing import log_event
 from letta.utils import get_tool_call_id
 
 has_shown_warning = False
@@ -149,7 +150,7 @@ def get_chat_completion(
     else:
         model_schema = None
     """
-
+    log_event(name="llm_request_sent", attributes={"prompt": prompt, "grammar": grammar})
     # Run the LLM
     try:
         result_reasoning = None
@@ -178,6 +179,10 @@ def get_chat_completion(
     except requests.exceptions.ConnectionError as e:
         raise LocalLLMConnectionError(f"Unable to connect to endpoint {endpoint}")
 
+    attributes = usage if isinstance(usage, dict) else {"usage": usage}
+    attributes.update({"result": result})
+    log_event(name="llm_request_sent", attributes=attributes)
+
     if result is None or result == "":
         raise LocalLLMError(f"Got back an empty response string from {endpoint}")
     printd(f"Raw LLM output:\n====\n{result}\n====")

letta/server/rest_api/app.py

@@ -237,7 +237,11 @@ def create_application() -> "FastAPI":
         print(f"▶ Using OTLP tracing with endpoint: {endpoint}")
         from letta.tracing import setup_tracing
 
-        setup_tracing(endpoint=endpoint, service_name="memgpt-server")
+        setup_tracing(
+            endpoint=endpoint,
+            app=app,
+            service_name="memgpt-server",
+        )
 
     for route in v1_routes:
         app.include_router(route, prefix=API_PREFIX)

letta/server/rest_api/routers/v1/agents.py

@@ -24,7 +24,6 @@ from letta.schemas.tool import Tool
 from letta.schemas.user import User
 from letta.server.rest_api.utils import get_letta_server
 from letta.server.server import SyncServer
-from letta.tracing import trace_method
 
 # These can be forward refs, but because Fastapi needs them at runtime the must be imported normally
 
@@ -486,7 +485,6 @@ def modify_message(
     response_model=LettaResponse,
     operation_id="send_message",
 )
-@trace_method("POST /v1/agents/{agent_id}/messages")
 async def send_message(
     agent_id: str,
     server: SyncServer = Depends(get_letta_server),
@@ -525,7 +523,6 @@ async def send_message(
         }
     },
 )
-@trace_method("POST /v1/agents/{agent_id}/messages/stream")
 async def send_message_streaming(
     agent_id: str,
     server: SyncServer = Depends(get_letta_server),
@@ -601,7 +598,6 @@ async def process_message_background(
     response_model=Run,
     operation_id="create_agent_message_async",
 )
-@trace_method("POST /v1/agents/{agent_id}/messages/async")
 async def send_message_async(
     agent_id: str,
     background_tasks: BackgroundTasks,

letta/server/server.py

@@ -1172,7 +1172,7 @@ class SyncServer(Server):
         actions = self.get_composio_client(api_key=api_key).actions.get(apps=[composio_app_name])
         return actions
 
-    @trace_method("Send Message")
+    @trace_method
     async def send_message_to_agent(
         self,
         agent_id: str,

letta/services/agent_manager.py

@@ -50,6 +50,7 @@ from letta.services.message_manager import MessageManager
 from letta.services.source_manager import SourceManager
 from letta.services.tool_manager import ToolManager
 from letta.settings import settings
+from letta.tracing import trace_method
 from letta.utils import enforce_types, united_diff
 
 logger = get_logger(__name__)
@@ -72,6 +73,7 @@ class AgentManager:
     # ======================================================================================================================
     # Basic CRUD operations
     # ======================================================================================================================
+    @trace_method
     @enforce_types
     def create_agent(
         self,
@@ -368,6 +370,7 @@ class AgentManager:
             agent = AgentModel.read(db_session=session, name=agent_name, actor=actor)
             return agent.to_pydantic()
 
+    @trace_method
     @enforce_types
     def delete_agent(self, agent_id: str, actor: PydanticUser) -> None:
         """

letta/tracing.py

@@ -1,205 +1,225 @@
-import asyncio
 import inspect
+import re
 import sys
 import time
 from functools import wraps
-from typing import Any, Dict, Optional
+from typing import Any, Dict, List, Optional
 
-from fastapi import Request
+from fastapi import Depends, FastAPI, HTTPException, Request
+from fastapi.exceptions import RequestValidationError
+from fastapi.responses import JSONResponse
 from opentelemetry import trace
-from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
+from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter
 from opentelemetry.instrumentation.requests import RequestsInstrumentor
 from opentelemetry.sdk.resources import Resource
 from opentelemetry.sdk.trace import TracerProvider
 from opentelemetry.sdk.trace.export import BatchSpanProcessor
-from opentelemetry.trace import Span, Status, StatusCode
+from opentelemetry.trace import Status, StatusCode
 
-# Get a tracer instance - will be no-op until setup_tracing is called
 tracer = trace.get_tracer(__name__)
-
-# Track if tracing has been initialized
 _is_tracing_initialized = False
+_excluded_v1_endpoints_regex: List[str] = [
+    "^GET /v1/agents/(?P<agent_id>[^/]+)/messages$",
+    "^GET /v1/agents/(?P<agent_id>[^/]+)/context$",
+    "^GET /v1/agents/(?P<agent_id>[^/]+)/archival-memory$",
+    "^GET /v1/agents/(?P<agent_id>[^/]+)/sources$",
+]
 
 
 def is_pytest_environment():
-    """Check if we're running in pytest"""
     return "pytest" in sys.modules
 
 
-def trace_method(name=None):
-    """Decorator to add tracing to a method"""
+async def trace_request_middleware(request: Request, call_next):
+    if not _is_tracing_initialized:
+        return await call_next(request)
+    initial_span_name = f"{request.method} {request.url.path}"
+    if any(re.match(regex, initial_span_name) for regex in _excluded_v1_endpoints_regex):
+        return await call_next(request)
 
-    def decorator(func):
-        @wraps(func)
-        async def async_wrapper(*args, **kwargs):
-            # Skip tracing if not initialized
-            if not _is_tracing_initialized:
-                return await func(*args, **kwargs)
+    with tracer.start_as_current_span(
+        initial_span_name,
+        kind=trace.SpanKind.SERVER,
+    ) as span:
+        try:
+            response = await call_next(request)
+            span.set_attribute("http.status_code", response.status_code)
+            span.set_status(Status(StatusCode.OK if response.status_code < 400 else StatusCode.ERROR))
+            return response
+        except Exception as e:
+            span.set_status(Status(StatusCode.ERROR))
+            span.record_exception(e)
+            raise
 
-            span_name = name or func.__name__
-            with tracer.start_as_current_span(span_name) as span:
-                span.set_attribute("code.namespace", inspect.getmodule(func).__name__)
-                span.set_attribute("code.function", func.__name__)
 
-                if len(args) > 0 and hasattr(args[0], "__class__"):
-                    span.set_attribute("code.class", args[0].__class__.__name__)
+async def update_trace_attributes(request: Request):
+    """Dependency to update trace attributes after FastAPI has processed the request"""
+    if not _is_tracing_initialized:
+        return
 
-                request = _extract_request_info(args, span)
-                if request and len(request) > 0:
-                    span.set_attribute("agent.id", kwargs.get("agent_id"))
-                    span.set_attribute("actor.id", request.get("http.user_id"))
+    span = trace.get_current_span()
+    if not span:
+        return
 
-                try:
-                    result = await func(*args, **kwargs)
-                    span.set_status(Status(StatusCode.OK))
-                    return result
-                except Exception as e:
-                    span.set_status(Status(StatusCode.ERROR))
-                    span.record_exception(e)
-                    raise
+    # Update span name with route pattern
+    route = request.scope.get("route")
+    if route and hasattr(route, "path"):
+        span.update_name(f"{request.method} {route.path}")
 
-        @wraps(func)
-        def sync_wrapper(*args, **kwargs):
-            # Skip tracing if not initialized
-            if not _is_tracing_initialized:
-                return func(*args, **kwargs)
+    # Add request info
+    span.set_attribute("http.method", request.method)
+    span.set_attribute("http.url", str(request.url))
 
-            span_name = name or func.__name__
-            with tracer.start_as_current_span(span_name) as span:
-                span.set_attribute("code.namespace", inspect.getmodule(func).__name__)
-                span.set_attribute("code.function", func.__name__)
+    # Add path params
+    for key, value in request.path_params.items():
+        span.set_attribute(f"http.{key}", value)
 
-                if len(args) > 0 and hasattr(args[0], "__class__"):
-                    span.set_attribute("code.class", args[0].__class__.__name__)
+    # Add request body if available
+    try:
+        body = await request.json()
+        for key, value in body.items():
+            span.set_attribute(f"http.request.body.{key}", str(value))
+    except Exception:
+        pass
 
-                request = _extract_request_info(args, span)
-                if request and len(request) > 0:
-                    span.set_attribute("agent.id", kwargs.get("agent_id"))
-                    span.set_attribute("actor.id", request.get("http.user_id"))
 
-                try:
-                    result = func(*args, **kwargs)
-                    span.set_status(Status(StatusCode.OK))
-                    return result
-                except Exception as e:
-                    span.set_status(Status(StatusCode.ERROR))
-                    span.record_exception(e)
-                    raise
+async def trace_error_handler(_request: Request, exc: Exception) -> JSONResponse:
+    status_code = getattr(exc, "status_code", 500)
+    error_msg = str(exc)
 
-        return async_wrapper if asyncio.iscoroutinefunction(func) else sync_wrapper
+    # Add error details to current span
+    span = trace.get_current_span()
+    if span:
+        span.add_event(
+            name="exception",
+            attributes={
+                "exception.message": error_msg,
+                "exception.type": type(exc).__name__,
+            },
+        )
 
-    return decorator
+    return JSONResponse(status_code=status_code, content={"detail": error_msg, "trace_id": get_trace_id() or ""})
+
+
+def setup_tracing(
+    endpoint: str,
+    app: Optional[FastAPI] = None,
+    service_name: str = "memgpt-server",
+) -> None:
+    if is_pytest_environment():
+        return
+
+    global _is_tracing_initialized
+
+    provider = TracerProvider(resource=Resource.create({"service.name": service_name}))
+    if endpoint:
+        provider.add_span_processor(BatchSpanProcessor(OTLPSpanExporter(endpoint=endpoint)))
+        _is_tracing_initialized = True
+        trace.set_tracer_provider(provider)
+
+        def requests_callback(span: trace.Span, _: Any, response: Any) -> None:
+            if hasattr(response, "status_code"):
+                span.set_status(Status(StatusCode.OK if response.status_code < 400 else StatusCode.ERROR))
+
+        RequestsInstrumentor().instrument(response_hook=requests_callback)
+
+        if app:
+            # Add middleware first
+            app.middleware("http")(trace_request_middleware)
+
+            # Add dependency to v1 routes
+            from letta.server.rest_api.routers.v1 import ROUTERS as v1_routes
+
+            for router in v1_routes:
+                for route in router.routes:
+                    full_path = ((next(iter(route.methods)) + " ") if route.methods else "") + "/v1" + route.path
+                    if not any(re.match(regex, full_path) for regex in _excluded_v1_endpoints_regex):
+                        route.dependencies.append(Depends(update_trace_attributes))
+
+            # Register exception handlers
+            app.exception_handler(HTTPException)(trace_error_handler)
+            app.exception_handler(RequestValidationError)(trace_error_handler)
+            app.exception_handler(Exception)(trace_error_handler)
+
+
+def trace_method(func):
+    """Decorator that traces function execution with OpenTelemetry"""
+
+    def _get_span_name(func, args):
+        if args and hasattr(args[0], "__class__"):
+            class_name = args[0].__class__.__name__
+        else:
+            class_name = func.__module__
+        return f"{class_name}.{func.__name__}"
+
+    def _add_parameters_to_span(span, func, args, kwargs):
+        try:
+            # Add method parameters as span attributes
+            sig = inspect.signature(func)
+            bound_args = sig.bind(*args, **kwargs)
+            bound_args.apply_defaults()
+
+            # Skip 'self' when adding parameters if it exists
+            param_items = list(bound_args.arguments.items())
+            if args and hasattr(args[0], "__class__"):
+                param_items = param_items[1:]
+
+            for name, value in param_items:
+                # Convert value to string to avoid serialization issues
+                span.set_attribute(f"parameter.{name}", str(value))
+        except:
+            pass
+
+    @wraps(func)
+    async def async_wrapper(*args, **kwargs):
+        if not _is_tracing_initialized:
+            return await func(*args, **kwargs)
+
+        with tracer.start_as_current_span(_get_span_name(func, args)) as span:
+            _add_parameters_to_span(span, func, args, kwargs)
+
+            result = await func(*args, **kwargs)
+            span.set_status(Status(StatusCode.OK))
+            return result
+
+    @wraps(func)
+    def sync_wrapper(*args, **kwargs):
+        if not _is_tracing_initialized:
+            return func(*args, **kwargs)
+
+        with tracer.start_as_current_span(_get_span_name(func, args)) as span:
+            _add_parameters_to_span(span, func, args, kwargs)
+
+            result = func(*args, **kwargs)
+            span.set_status(Status(StatusCode.OK))
+            return result
+
+    return async_wrapper if inspect.iscoroutinefunction(func) else sync_wrapper
 
 
 def log_attributes(attributes: Dict[str, Any]) -> None:
-    """
-    Log multiple attributes to the current active span.
-
-    Args:
-        attributes: Dictionary of attribute key-value pairs
-    """
     current_span = trace.get_current_span()
     if current_span:
         current_span.set_attributes(attributes)
 
 
 def log_event(name: str, attributes: Optional[Dict[str, Any]] = None, timestamp: Optional[int] = None) -> None:
-    """
-    Log an event to the current active span.
-
-    Args:
-        name: Name of the event
-        attributes: Optional dictionary of event attributes
-        timestamp: Optional timestamp in nanoseconds
-    """
     current_span = trace.get_current_span()
     if current_span:
         if timestamp is None:
             timestamp = int(time.perf_counter_ns())
 
+        def _safe_convert(v):
+            if isinstance(v, (str, bool, int, float)):
+                return v
+            return str(v)
+
+        attributes = {k: _safe_convert(v) for k, v in attributes.items()} if attributes else None
         current_span.add_event(name=name, attributes=attributes, timestamp=timestamp)
 
 
-def get_trace_id() -> str:
-    current_span = trace.get_current_span()
-    if current_span:
-        return format(current_span.get_span_context().trace_id, "032x")
-    else:
-        return ""
-
-
-def request_hook(span: Span, _request_context: Optional[Dict] = None, response: Optional[Any] = None):
-    """Hook to update span based on response status code"""
-    if response is not None:
-        if hasattr(response, "status_code"):
-            span.set_attribute("http.status_code", response.status_code)
-            if response.status_code >= 400:
-                span.set_status(Status(StatusCode.ERROR))
-            elif 200 <= response.status_code < 300:
-                span.set_status(Status(StatusCode.OK))
-
-
-def setup_tracing(endpoint: str, service_name: str = "memgpt-server") -> None:
-    """
-    Sets up OpenTelemetry tracing with OTLP exporter for specific endpoints
-
-    Args:
-        endpoint: OTLP endpoint URL
-        service_name: Name of the service for tracing
-    """
-    global _is_tracing_initialized
-
-    # Skip tracing in pytest environment
-    if is_pytest_environment():
-        print("ℹ️ Skipping tracing setup in pytest environment")
-        return
-
-    # Create a Resource to identify our service
-    resource = Resource.create({"service.name": service_name, "service.namespace": "default", "deployment.environment": "production"})
-
-    # Initialize the TracerProvider with the resource
-    provider = TracerProvider(resource=resource)
-
-    # Only set up OTLP export if endpoint is provided
-    if endpoint:
-        otlp_exporter = OTLPSpanExporter(endpoint=endpoint)
-        processor = BatchSpanProcessor(otlp_exporter)
-        provider.add_span_processor(processor)
-        _is_tracing_initialized = True
-    else:
-        print("⚠️ Warning: Tracing endpoint not provided, tracing will be disabled")
-
-    # Set the global TracerProvider
-    trace.set_tracer_provider(provider)
-
-    # Initialize automatic instrumentation for the requests library with response hook
-    if _is_tracing_initialized:
-        RequestsInstrumentor().instrument(response_hook=request_hook)
-
-
-def _extract_request_info(args: tuple, span: Span) -> Dict[str, Any]:
-    """
-    Safely extracts request information from function arguments.
-    Works with both FastAPI route handlers and inner functions.
-    """
-    attributes = {}
-
-    # Look for FastAPI Request object in args
-    request = next((arg for arg in args if isinstance(arg, Request)), None)
-
-    if request:
-        attributes.update(
-            {
-                "http.route": request.url.path,
-                "http.method": request.method,
-                "http.scheme": request.url.scheme,
-                "http.target": str(request.url.path),
-                "http.url": str(request.url),
-                "http.flavor": request.scope.get("http_version", ""),
-                "http.client_ip": request.client.host if request.client else None,
-                "http.user_id": request.headers.get("user_id"),
-            }
-        )
-
-    span.set_attributes(attributes)
-    return attributes
+def get_trace_id() -> Optional[str]:
+    span = trace.get_current_span()
+    if span and span.get_span_context().trace_id:
+        return format(span.get_span_context().trace_id, "032x")
+    return None