forked from phoenix/litellm-mirror
fix(langfuse.py): don't overwrite trace details if existing trace id passed in
This commit is contained in:
Krrish Dholakia
parent
fc5a845838
commit
abdae87ba2
2 changed files with 217 additions and 12 deletions
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@ -79,7 +79,7 @@ class LangFuseLogger:
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print_verbose,
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level="DEFAULT",
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status_message=None,
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):
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) -> dict:
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# Method definition
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try:
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@ -111,6 +111,7 @@ class LangFuseLogger:
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pass
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# end of processing langfuse ########################
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print(f"response obj type: {type(response_obj)}")
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if (
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level == "ERROR"
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and status_message is not None
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@ -140,8 +141,11 @@ class LangFuseLogger:
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input = prompt
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output = response_obj["data"]
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print_verbose(f"OUTPUT IN LANGFUSE: {output}; original: {response_obj}")
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trace_id = None
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generation_id = None
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if self._is_langfuse_v2():
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self._log_langfuse_v2(
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print("INSIDE V2 LANGFUSE")
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trace_id, generation_id = self._log_langfuse_v2(
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user_id,
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metadata,
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litellm_params,
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@ -171,10 +175,12 @@ class LangFuseLogger:
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f"Langfuse Layer Logging - final response object: {response_obj}"
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)
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verbose_logger.info(f"Langfuse Layer Logging - logging success")
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return {"trace_id": trace_id, "generation_id": generation_id}
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except:
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traceback.print_exc()
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verbose_logger.debug(f"Langfuse Layer Error - {traceback.format_exc()}")
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pass
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return {"trace_id": None, "generation_id": None}
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async def _async_log_event(
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self, kwargs, response_obj, start_time, end_time, user_id, print_verbose
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@ -246,7 +252,7 @@ class LangFuseLogger:
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response_obj,
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level,
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print_verbose,
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):
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) -> tuple:
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import langfuse
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try:
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@ -272,11 +278,14 @@ class LangFuseLogger:
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## DO NOT SET TRACE_NAME if trace-id set. this can lead to overwriting of past traces.
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trace_name = f"litellm-{kwargs.get('call_type', 'completion')}"
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if existing_trace_id is not None:
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trace_params = {"trace_id": existing_trace_id}
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else: # don't overwrite an existing trace
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trace_params = {
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"name": trace_name,
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"input": input,
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"user_id": metadata.get("trace_user_id", user_id),
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"id": trace_id or existing_trace_id,
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"id": trace_id,
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"session_id": metadata.get("session_id", None),
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}
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@ -414,6 +423,10 @@ class LangFuseLogger:
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print_verbose(f"generation_params: {generation_params}")
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trace.generation(**generation_params)
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generation_client = trace.generation(**generation_params)
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print(f"LANGFUSE TRACE ID - {generation_client.trace_id}")
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return generation_client.trace_id, generation_id
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except Exception as e:
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verbose_logger.debug(f"Langfuse Layer Error - {traceback.format_exc()}")
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return None, None
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@ -348,6 +348,198 @@ def test_langfuse_logging_function_calling():
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# test_langfuse_logging_function_calling()
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def test_langfuse_existing_trace_id():
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"""
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When existing trace id is passed, don't set trace params -> prevents overwriting the trace
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Pass 1 logging object with a trace
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Pass 2nd logging object with the trace id
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Assert no changes to the trace
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"""
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# Test - if the logs were sent to the correct team on langfuse
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import litellm, datetime
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from litellm.integrations.langfuse import LangFuseLogger
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langfuse_Logger = LangFuseLogger(
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langfuse_public_key=os.getenv("LANGFUSE_PROJECT2_PUBLIC"),
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langfuse_secret=os.getenv("LANGFUSE_PROJECT2_SECRET"),
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)
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litellm.success_callback = ["langfuse"]
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# langfuse_args = {'kwargs': { 'start_time': 'end_time': datetime.datetime(2024, 5, 1, 7, 31, 29, 903685), 'user_id': None, 'print_verbose': <function print_verbose at 0x109d1f420>, 'level': 'DEFAULT', 'status_message': None}
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response_obj = litellm.ModelResponse(
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id="chatcmpl-9K5HUAbVRqFrMZKXL0WoC295xhguY",
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choices=[
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litellm.Choices(
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finish_reason="stop",
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index=0,
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message=litellm.Message(
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content="I'm sorry, I am an AI assistant and do not have real-time information. I recommend checking a reliable weather website or app for the most up-to-date weather information in Boston.",
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role="assistant",
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),
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)
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],
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created=1714573888,
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model="gpt-3.5-turbo-0125",
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object="chat.completion",
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system_fingerprint="fp_3b956da36b",
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usage=litellm.Usage(completion_tokens=37, prompt_tokens=14, total_tokens=51),
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)
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### NEW TRACE ###
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message = [{"role": "user", "content": "what's the weather in boston"}]
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langfuse_args = {
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"response_obj": response_obj,
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"kwargs": {
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"model": "gpt-3.5-turbo",
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"litellm_params": {
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"acompletion": False,
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"api_key": None,
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"force_timeout": 600,
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"logger_fn": None,
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"verbose": False,
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"custom_llm_provider": "openai",
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"api_base": "https://api.openai.com/v1/",
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"litellm_call_id": "508113a1-c6f1-48ce-a3e1-01c6cce9330e",
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"model_alias_map": {},
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"completion_call_id": None,
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"metadata": None,
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"model_info": None,
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"proxy_server_request": None,
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"preset_cache_key": None,
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"no-log": False,
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"stream_response": {},
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},
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"messages": message,
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"optional_params": {"temperature": 0.1, "extra_body": {}},
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"start_time": "2024-05-01 07:31:27.986164",
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"stream": False,
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"user": None,
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"call_type": "completion",
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"litellm_call_id": "508113a1-c6f1-48ce-a3e1-01c6cce9330e",
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"completion_start_time": "2024-05-01 07:31:29.903685",
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"temperature": 0.1,
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"extra_body": {},
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"input": [{"role": "user", "content": "what's the weather in boston"}],
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"api_key": "my-api-key",
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"additional_args": {
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"complete_input_dict": {
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"model": "gpt-3.5-turbo",
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"messages": [
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{"role": "user", "content": "what's the weather in boston"}
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],
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"temperature": 0.1,
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"extra_body": {},
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}
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},
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"log_event_type": "successful_api_call",
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"end_time": "2024-05-01 07:31:29.903685",
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"cache_hit": None,
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"response_cost": 6.25e-05,
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},
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"start_time": datetime.datetime(2024, 5, 1, 7, 31, 27, 986164),
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"end_time": datetime.datetime(2024, 5, 1, 7, 31, 29, 903685),
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"user_id": None,
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"print_verbose": litellm.print_verbose,
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"level": "DEFAULT",
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"status_message": None,
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}
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langfuse_response_object = langfuse_Logger.log_event(**langfuse_args)
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import langfuse
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langfuse_client = langfuse.Langfuse(
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public_key=os.getenv("LANGFUSE_PROJECT2_PUBLIC"),
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secret_key=os.getenv("LANGFUSE_PROJECT2_SECRET"),
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)
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trace_id = langfuse_response_object["trace_id"]
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langfuse_client.flush()
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time.sleep(2)
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print(langfuse_client.get_trace(id=trace_id))
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initial_langfuse_trace = langfuse_client.get_trace(id=trace_id)
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### EXISTING TRACE ###
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new_metadata = {"existing_trace_id": trace_id}
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new_messages = [{"role": "user", "content": "What do you know?"}]
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langfuse_args = {
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"response_obj": response_obj,
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"kwargs": {
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"model": "gpt-3.5-turbo",
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"litellm_params": {
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"acompletion": False,
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"api_key": None,
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"force_timeout": 600,
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"logger_fn": None,
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"verbose": False,
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"custom_llm_provider": "openai",
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"api_base": "https://api.openai.com/v1/",
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"litellm_call_id": "508113a1-c6f1-48ce-a3e1-01c6cce9330e",
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"model_alias_map": {},
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"completion_call_id": None,
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"metadata": new_metadata,
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"model_info": None,
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"proxy_server_request": None,
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"preset_cache_key": None,
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"no-log": False,
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"stream_response": {},
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},
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"messages": new_messages,
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"optional_params": {"temperature": 0.1, "extra_body": {}},
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"start_time": "2024-05-01 07:31:27.986164",
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"stream": False,
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"user": None,
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"call_type": "completion",
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"litellm_call_id": "508113a1-c6f1-48ce-a3e1-01c6cce9330e",
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"completion_start_time": "2024-05-01 07:31:29.903685",
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"temperature": 0.1,
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"extra_body": {},
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"input": [{"role": "user", "content": "what's the weather in boston"}],
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"api_key": "my-api-key",
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"additional_args": {
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"complete_input_dict": {
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"model": "gpt-3.5-turbo",
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"messages": [
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{"role": "user", "content": "what's the weather in boston"}
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],
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"temperature": 0.1,
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"extra_body": {},
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}
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},
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"log_event_type": "successful_api_call",
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"end_time": "2024-05-01 07:31:29.903685",
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"cache_hit": None,
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"response_cost": 6.25e-05,
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},
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"start_time": datetime.datetime(2024, 5, 1, 7, 31, 27, 986164),
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"end_time": datetime.datetime(2024, 5, 1, 7, 31, 29, 903685),
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"user_id": None,
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"print_verbose": litellm.print_verbose,
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"level": "DEFAULT",
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"status_message": None,
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}
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langfuse_response_object = langfuse_Logger.log_event(**langfuse_args)
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langfuse_client.flush()
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time.sleep(2)
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print(langfuse_client.get_trace(id=trace_id))
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new_langfuse_trace = langfuse_client.get_trace(id=trace_id)
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assert dict(initial_langfuse_trace) == dict(new_langfuse_trace)
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def test_langfuse_logging_tool_calling():
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litellm.set_verbose = True
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