mirror of
https://github.com/BerriAI/litellm.git
synced 2025-04-26 03:04:13 +00:00
(Refactor) Langfuse - remove prepare_metadata, langfuse python SDK now handles non-json serializable objects (#7925)
* test_langfuse_logging_completion_with_langfuse_metadata * fix litellm - remove prepare metadata * test_langfuse_logging_with_non_serializable_metadata * detailed e2e langfuse metadata tests * clean up langfuse logging * fix langfuse * remove unused imports * fix code qa checks * fix _prepare_metadata
This commit is contained in:
Ishaan Jaff
GitHub
parent
27560bd5ad
commit
53a3ea3d06
16 changed files with 1231 additions and 133 deletions
|
|
@ -3,11 +3,9 @@
|
||||||
import copy
|
import copy
|
||||||
import os
|
import os
|
||||||
import traceback
|
import traceback
|
||||||
from collections.abc import MutableMapping, MutableSequence, MutableSet
|
|
||||||
from typing import TYPE_CHECKING, Any, Dict, List, Optional, cast
|
from typing import TYPE_CHECKING, Any, Dict, List, Optional, cast
|
||||||
|
|
||||||
from packaging.version import Version
|
from packaging.version import Version
|
||||||
from pydantic import BaseModel
|
|
||||||
|
|
||||||
import litellm
|
import litellm
|
||||||
from litellm._logging import verbose_logger
|
from litellm._logging import verbose_logger
|
||||||
|
|
@ -71,8 +69,9 @@ class LangFuseLogger:
|
||||||
"flush_interval": self.langfuse_flush_interval, # flush interval in seconds
|
"flush_interval": self.langfuse_flush_interval, # flush interval in seconds
|
||||||
"httpx_client": self.langfuse_client,
|
"httpx_client": self.langfuse_client,
|
||||||
}
|
}
|
||||||
|
self.langfuse_sdk_version: str = langfuse.version.__version__
|
||||||
|
|
||||||
if Version(langfuse.version.__version__) >= Version("2.6.0"):
|
if Version(self.langfuse_sdk_version) >= Version("2.6.0"):
|
||||||
parameters["sdk_integration"] = "litellm"
|
parameters["sdk_integration"] = "litellm"
|
||||||
|
|
||||||
self.Langfuse = Langfuse(**parameters)
|
self.Langfuse = Langfuse(**parameters)
|
||||||
|
|
@ -360,73 +359,6 @@ class LangFuseLogger:
|
||||||
)
|
)
|
||||||
)
|
)
|
||||||
|
|
||||||
def is_base_type(self, value: Any) -> bool:
|
|
||||||
# Check if the value is of a base type
|
|
||||||
base_types = (int, float, str, bool, list, dict, tuple)
|
|
||||||
return isinstance(value, base_types)
|
|
||||||
|
|
||||||
def _prepare_metadata(self, metadata: Optional[dict]) -> Any:
|
|
||||||
try:
|
|
||||||
if metadata is None:
|
|
||||||
return None
|
|
||||||
|
|
||||||
# Filter out function types from the metadata
|
|
||||||
sanitized_metadata = {k: v for k, v in metadata.items() if not callable(v)}
|
|
||||||
|
|
||||||
return copy.deepcopy(sanitized_metadata)
|
|
||||||
except Exception as e:
|
|
||||||
verbose_logger.debug(f"Langfuse Layer Error - {e}, metadata: {metadata}")
|
|
||||||
|
|
||||||
new_metadata: Dict[str, Any] = {}
|
|
||||||
|
|
||||||
# if metadata is not a MutableMapping, return an empty dict since we can't call items() on it
|
|
||||||
if not isinstance(metadata, MutableMapping):
|
|
||||||
verbose_logger.debug(
|
|
||||||
"Langfuse Layer Logging - metadata is not a MutableMapping, returning empty dict"
|
|
||||||
)
|
|
||||||
return new_metadata
|
|
||||||
|
|
||||||
for key, value in metadata.items():
|
|
||||||
try:
|
|
||||||
if isinstance(value, MutableMapping):
|
|
||||||
new_metadata[key] = self._prepare_metadata(cast(dict, value))
|
|
||||||
elif isinstance(value, MutableSequence):
|
|
||||||
# For lists or other mutable sequences
|
|
||||||
new_metadata[key] = list(
|
|
||||||
(
|
|
||||||
self._prepare_metadata(cast(dict, v))
|
|
||||||
if isinstance(v, MutableMapping)
|
|
||||||
else copy.deepcopy(v)
|
|
||||||
)
|
|
||||||
for v in value
|
|
||||||
)
|
|
||||||
elif isinstance(value, MutableSet):
|
|
||||||
# For sets specifically, create a new set by passing an iterable
|
|
||||||
new_metadata[key] = set(
|
|
||||||
(
|
|
||||||
self._prepare_metadata(cast(dict, v))
|
|
||||||
if isinstance(v, MutableMapping)
|
|
||||||
else copy.deepcopy(v)
|
|
||||||
)
|
|
||||||
for v in value
|
|
||||||
)
|
|
||||||
elif isinstance(value, BaseModel):
|
|
||||||
new_metadata[key] = value.model_dump()
|
|
||||||
elif self.is_base_type(value):
|
|
||||||
new_metadata[key] = value
|
|
||||||
else:
|
|
||||||
verbose_logger.debug(
|
|
||||||
f"Langfuse Layer Error - Unsupported metadata type: {type(value)} for key: {key}"
|
|
||||||
)
|
|
||||||
continue
|
|
||||||
|
|
||||||
except (TypeError, copy.Error):
|
|
||||||
verbose_logger.debug(
|
|
||||||
f"Langfuse Layer Error - Couldn't copy metadata key: {key}, type of key: {type(key)}, type of value: {type(value)} - {traceback.format_exc()}"
|
|
||||||
)
|
|
||||||
|
|
||||||
return new_metadata
|
|
||||||
|
|
||||||
def _log_langfuse_v2( # noqa: PLR0915
|
def _log_langfuse_v2( # noqa: PLR0915
|
||||||
self,
|
self,
|
||||||
user_id,
|
user_id,
|
||||||
|
|
@ -443,27 +375,17 @@ class LangFuseLogger:
|
||||||
print_verbose,
|
print_verbose,
|
||||||
litellm_call_id,
|
litellm_call_id,
|
||||||
) -> tuple:
|
) -> tuple:
|
||||||
import langfuse
|
|
||||||
|
|
||||||
verbose_logger.debug("Langfuse Layer Logging - logging to langfuse v2")
|
verbose_logger.debug("Langfuse Layer Logging - logging to langfuse v2")
|
||||||
|
|
||||||
try:
|
try:
|
||||||
metadata = self._prepare_metadata(metadata)
|
metadata = metadata or {}
|
||||||
|
|
||||||
langfuse_version = Version(langfuse.version.__version__)
|
|
||||||
|
|
||||||
supports_tags = langfuse_version >= Version("2.6.3")
|
|
||||||
supports_prompt = langfuse_version >= Version("2.7.3")
|
|
||||||
supports_costs = langfuse_version >= Version("2.7.3")
|
|
||||||
supports_completion_start_time = langfuse_version >= Version("2.7.3")
|
|
||||||
|
|
||||||
standard_logging_object: Optional[StandardLoggingPayload] = cast(
|
standard_logging_object: Optional[StandardLoggingPayload] = cast(
|
||||||
Optional[StandardLoggingPayload],
|
Optional[StandardLoggingPayload],
|
||||||
kwargs.get("standard_logging_object", None),
|
kwargs.get("standard_logging_object", None),
|
||||||
)
|
)
|
||||||
tags = (
|
tags = (
|
||||||
self._get_langfuse_tags(standard_logging_object=standard_logging_object)
|
self._get_langfuse_tags(standard_logging_object=standard_logging_object)
|
||||||
if supports_tags
|
if self._supports_tags()
|
||||||
else []
|
else []
|
||||||
)
|
)
|
||||||
|
|
||||||
|
|
@ -624,7 +546,7 @@ class LangFuseLogger:
|
||||||
if aws_region_name:
|
if aws_region_name:
|
||||||
clean_metadata["aws_region_name"] = aws_region_name
|
clean_metadata["aws_region_name"] = aws_region_name
|
||||||
|
|
||||||
if supports_tags:
|
if self._supports_tags():
|
||||||
if "cache_hit" in kwargs:
|
if "cache_hit" in kwargs:
|
||||||
if kwargs["cache_hit"] is None:
|
if kwargs["cache_hit"] is None:
|
||||||
kwargs["cache_hit"] = False
|
kwargs["cache_hit"] = False
|
||||||
|
|
@ -670,7 +592,7 @@ class LangFuseLogger:
|
||||||
usage = {
|
usage = {
|
||||||
"prompt_tokens": _usage_obj.prompt_tokens,
|
"prompt_tokens": _usage_obj.prompt_tokens,
|
||||||
"completion_tokens": _usage_obj.completion_tokens,
|
"completion_tokens": _usage_obj.completion_tokens,
|
||||||
"total_cost": cost if supports_costs else None,
|
"total_cost": cost if self._supports_costs() else None,
|
||||||
}
|
}
|
||||||
generation_name = clean_metadata.pop("generation_name", None)
|
generation_name = clean_metadata.pop("generation_name", None)
|
||||||
if generation_name is None:
|
if generation_name is None:
|
||||||
|
|
@ -713,7 +635,7 @@ class LangFuseLogger:
|
||||||
if parent_observation_id is not None:
|
if parent_observation_id is not None:
|
||||||
generation_params["parent_observation_id"] = parent_observation_id
|
generation_params["parent_observation_id"] = parent_observation_id
|
||||||
|
|
||||||
if supports_prompt:
|
if self._supports_prompt():
|
||||||
generation_params = _add_prompt_to_generation_params(
|
generation_params = _add_prompt_to_generation_params(
|
||||||
generation_params=generation_params,
|
generation_params=generation_params,
|
||||||
clean_metadata=clean_metadata,
|
clean_metadata=clean_metadata,
|
||||||
|
|
@ -723,7 +645,7 @@ class LangFuseLogger:
|
||||||
if output is not None and isinstance(output, str) and level == "ERROR":
|
if output is not None and isinstance(output, str) and level == "ERROR":
|
||||||
generation_params["status_message"] = output
|
generation_params["status_message"] = output
|
||||||
|
|
||||||
if supports_completion_start_time:
|
if self._supports_completion_start_time():
|
||||||
generation_params["completion_start_time"] = kwargs.get(
|
generation_params["completion_start_time"] = kwargs.get(
|
||||||
"completion_start_time", None
|
"completion_start_time", None
|
||||||
)
|
)
|
||||||
|
|
@ -770,6 +692,22 @@ class LangFuseLogger:
|
||||||
tags.append(f"cache_key:{_cache_key}")
|
tags.append(f"cache_key:{_cache_key}")
|
||||||
return tags
|
return tags
|
||||||
|
|
||||||
|
def _supports_tags(self):
|
||||||
|
"""Check if current langfuse version supports tags"""
|
||||||
|
return Version(self.langfuse_sdk_version) >= Version("2.6.3")
|
||||||
|
|
||||||
|
def _supports_prompt(self):
|
||||||
|
"""Check if current langfuse version supports prompt"""
|
||||||
|
return Version(self.langfuse_sdk_version) >= Version("2.7.3")
|
||||||
|
|
||||||
|
def _supports_costs(self):
|
||||||
|
"""Check if current langfuse version supports costs"""
|
||||||
|
return Version(self.langfuse_sdk_version) >= Version("2.7.3")
|
||||||
|
|
||||||
|
def _supports_completion_start_time(self):
|
||||||
|
"""Check if current langfuse version supports completion start time"""
|
||||||
|
return Version(self.langfuse_sdk_version) >= Version("2.7.3")
|
||||||
|
|
||||||
|
|
||||||
def _add_prompt_to_generation_params(
|
def _add_prompt_to_generation_params(
|
||||||
generation_params: dict,
|
generation_params: dict,
|
||||||
|
|
|
||||||
|
|
@ -107,6 +107,9 @@ class LangfusePromptManagement(LangFuseLogger, PromptManagementBase, CustomLogge
|
||||||
langfuse_host=None,
|
langfuse_host=None,
|
||||||
flush_interval=1,
|
flush_interval=1,
|
||||||
):
|
):
|
||||||
|
import langfuse
|
||||||
|
|
||||||
|
self.langfuse_sdk_version = langfuse.version.__version__
|
||||||
self.Langfuse = langfuse_client_init(
|
self.Langfuse = langfuse_client_init(
|
||||||
langfuse_public_key=langfuse_public_key,
|
langfuse_public_key=langfuse_public_key,
|
||||||
langfuse_secret=langfuse_secret,
|
langfuse_secret=langfuse_secret,
|
||||||
|
|
|
||||||
|
|
@ -8,7 +8,6 @@ IGNORE_FUNCTIONS = [
|
||||||
"text_completion",
|
"text_completion",
|
||||||
"_check_for_os_environ_vars",
|
"_check_for_os_environ_vars",
|
||||||
"clean_message",
|
"clean_message",
|
||||||
"_prepare_metadata",
|
|
||||||
"unpack_defs",
|
"unpack_defs",
|
||||||
"convert_to_nullable",
|
"convert_to_nullable",
|
||||||
"add_object_type",
|
"add_object_type",
|
||||||
|
|
|
||||||
|
|
@ -0,0 +1,126 @@
|
||||||
|
{
|
||||||
|
"batch": [
|
||||||
|
{
|
||||||
|
"id": "9ee9100b-c4aa-4e40-a10d-bc189f8b4242",
|
||||||
|
"type": "trace-create",
|
||||||
|
"body": {
|
||||||
|
"id": "litellm-test-c414db10-dd68-406e-9d9e-03839bc2f346",
|
||||||
|
"timestamp": "2025-01-22T17:27:51.702596Z",
|
||||||
|
"name": "litellm-acompletion",
|
||||||
|
"input": {
|
||||||
|
"messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "Hello!"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"output": {
|
||||||
|
"content": "Hello! How can I assist you today?",
|
||||||
|
"role": "assistant",
|
||||||
|
"tool_calls": null,
|
||||||
|
"function_call": null
|
||||||
|
},
|
||||||
|
"tags": []
|
||||||
|
},
|
||||||
|
"timestamp": "2025-01-22T17:27:51.702716Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"id": "f8d20489-ed58-429f-b609-87380e223746",
|
||||||
|
"type": "generation-create",
|
||||||
|
"body": {
|
||||||
|
"traceId": "litellm-test-c414db10-dd68-406e-9d9e-03839bc2f346",
|
||||||
|
"name": "litellm-acompletion",
|
||||||
|
"startTime": "2025-01-22T09:27:51.150898-08:00",
|
||||||
|
"metadata": {
|
||||||
|
"string_value": "hello",
|
||||||
|
"int_value": 42,
|
||||||
|
"float_value": 3.14,
|
||||||
|
"bool_value": true,
|
||||||
|
"nested_dict": {
|
||||||
|
"key1": "value1",
|
||||||
|
"key2": {
|
||||||
|
"inner_key": "inner_value"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"list_value": [
|
||||||
|
1,
|
||||||
|
2,
|
||||||
|
3
|
||||||
|
],
|
||||||
|
"set_value": [
|
||||||
|
1,
|
||||||
|
2,
|
||||||
|
3
|
||||||
|
],
|
||||||
|
"complex_list": [
|
||||||
|
{
|
||||||
|
"dict_in_list": "value"
|
||||||
|
},
|
||||||
|
"simple_string",
|
||||||
|
[
|
||||||
|
1,
|
||||||
|
2,
|
||||||
|
3
|
||||||
|
]
|
||||||
|
],
|
||||||
|
"user": {
|
||||||
|
"name": "John",
|
||||||
|
"age": 30,
|
||||||
|
"tags": [
|
||||||
|
"customer",
|
||||||
|
"active"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"hidden_params": {
|
||||||
|
"model_id": null,
|
||||||
|
"cache_key": null,
|
||||||
|
"api_base": "https://api.openai.com",
|
||||||
|
"response_cost": 5.4999999999999995e-05,
|
||||||
|
"additional_headers": {},
|
||||||
|
"litellm_overhead_time_ms": null
|
||||||
|
},
|
||||||
|
"litellm_response_cost": 5.4999999999999995e-05,
|
||||||
|
"cache_hit": false,
|
||||||
|
"requester_metadata": {}
|
||||||
|
},
|
||||||
|
"input": {
|
||||||
|
"messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "Hello!"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"output": {
|
||||||
|
"content": "Hello! How can I assist you today?",
|
||||||
|
"role": "assistant",
|
||||||
|
"tool_calls": null,
|
||||||
|
"function_call": null
|
||||||
|
},
|
||||||
|
"level": "DEFAULT",
|
||||||
|
"id": "time-09-27-51-150898_chatcmpl-b783291c-dc76-4660-bfef-b79be9d54e57",
|
||||||
|
"endTime": "2025-01-22T09:27:51.702048-08:00",
|
||||||
|
"completionStartTime": "2025-01-22T09:27:51.702048-08:00",
|
||||||
|
"model": "gpt-3.5-turbo",
|
||||||
|
"modelParameters": {
|
||||||
|
"extra_body": "{}"
|
||||||
|
},
|
||||||
|
"usage": {
|
||||||
|
"input": 10,
|
||||||
|
"output": 20,
|
||||||
|
"unit": "TOKENS",
|
||||||
|
"totalCost": 5.4999999999999995e-05
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"timestamp": "2025-01-22T17:27:51.703046Z"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"batch_size": 2,
|
||||||
|
"sdk_integration": "litellm",
|
||||||
|
"sdk_name": "python",
|
||||||
|
"sdk_version": "2.44.1",
|
||||||
|
"public_key": "pk-lf-e02aaea3-8668-4c9f-8c69-771a4ea1f5c9"
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
@ -0,0 +1,104 @@
|
||||||
|
{
|
||||||
|
"batch": [
|
||||||
|
{
|
||||||
|
"id": "872a0a1c-4328-431b-80b6-fd55a8a44477",
|
||||||
|
"type": "trace-create",
|
||||||
|
"body": {
|
||||||
|
"id": "litellm-test-533ffb2d-a0a3-45b5-911c-7940466cdc8e",
|
||||||
|
"timestamp": "2025-01-22T17:19:11.234960Z",
|
||||||
|
"name": "test_trace_name",
|
||||||
|
"userId": "test_user_id",
|
||||||
|
"input": {
|
||||||
|
"messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "Hello!"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"output": {
|
||||||
|
"content": "Hello! How can I assist you today?",
|
||||||
|
"role": "assistant",
|
||||||
|
"tool_calls": null,
|
||||||
|
"function_call": null
|
||||||
|
},
|
||||||
|
"sessionId": "test_session_id",
|
||||||
|
"version": "test_trace_version",
|
||||||
|
"metadata": {
|
||||||
|
"test_key": "test_value"
|
||||||
|
},
|
||||||
|
"tags": [
|
||||||
|
"test_tag",
|
||||||
|
"test_tag_2"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"timestamp": "2025-01-22T17:19:11.235169Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"id": "18d6f044-e522-4376-96e0-7eec765677ed",
|
||||||
|
"type": "generation-create",
|
||||||
|
"body": {
|
||||||
|
"traceId": "litellm-test-533ffb2d-a0a3-45b5-911c-7940466cdc8e",
|
||||||
|
"name": "test_generation_name",
|
||||||
|
"startTime": "2025-01-22T09:19:10.957072-08:00",
|
||||||
|
"metadata": {
|
||||||
|
"tags": [
|
||||||
|
"test_tag",
|
||||||
|
"test_tag_2"
|
||||||
|
],
|
||||||
|
"parent_observation_id": "test_parent_observation_id",
|
||||||
|
"version": "test_version",
|
||||||
|
"hidden_params": {
|
||||||
|
"model_id": null,
|
||||||
|
"cache_key": null,
|
||||||
|
"api_base": "https://api.openai.com",
|
||||||
|
"response_cost": 5.4999999999999995e-05,
|
||||||
|
"additional_headers": {},
|
||||||
|
"litellm_overhead_time_ms": null
|
||||||
|
},
|
||||||
|
"litellm_response_cost": 5.4999999999999995e-05,
|
||||||
|
"cache_hit": false,
|
||||||
|
"requester_metadata": {}
|
||||||
|
},
|
||||||
|
"input": {
|
||||||
|
"messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "Hello!"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"output": {
|
||||||
|
"content": "Hello! How can I assist you today?",
|
||||||
|
"role": "assistant",
|
||||||
|
"tool_calls": null,
|
||||||
|
"function_call": null
|
||||||
|
},
|
||||||
|
"level": "DEFAULT",
|
||||||
|
"parentObservationId": "test_parent_observation_id",
|
||||||
|
"version": "test_version",
|
||||||
|
"id": "time-09-19-10-957072_chatcmpl-4da65aba-32e4-400d-aaa2-6bfe096d8141",
|
||||||
|
"endTime": "2025-01-22T09:19:11.234200-08:00",
|
||||||
|
"completionStartTime": "2025-01-22T09:19:11.234200-08:00",
|
||||||
|
"model": "gpt-3.5-turbo",
|
||||||
|
"modelParameters": {
|
||||||
|
"extra_body": "{}"
|
||||||
|
},
|
||||||
|
"usage": {
|
||||||
|
"input": 10,
|
||||||
|
"output": 20,
|
||||||
|
"unit": "TOKENS",
|
||||||
|
"totalCost": 5.4999999999999995e-05
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"timestamp": "2025-01-22T17:19:11.235541Z"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"batch_size": 2,
|
||||||
|
"sdk_integration": "litellm",
|
||||||
|
"sdk_name": "python",
|
||||||
|
"sdk_version": "2.44.1",
|
||||||
|
"public_key": "pk-lf-e02aaea3-8668-4c9f-8c69-771a4ea1f5c9"
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
@ -0,0 +1,101 @@
|
||||||
|
{
|
||||||
|
"batch": [
|
||||||
|
{
|
||||||
|
"id": "ddf567e5-a1b5-4e38-8a7c-f48bc847f721",
|
||||||
|
"type": "trace-create",
|
||||||
|
"body": {
|
||||||
|
"id": "litellm-test-46551fc7-c916-4a83-aeef-4274b5582ce1",
|
||||||
|
"timestamp": "2025-01-22T17:59:39.367430Z",
|
||||||
|
"name": "litellm-acompletion",
|
||||||
|
"input": {
|
||||||
|
"messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "Hello!"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"output": {
|
||||||
|
"content": "Hello! How can I assist you today?",
|
||||||
|
"role": "assistant",
|
||||||
|
"tool_calls": null,
|
||||||
|
"function_call": null
|
||||||
|
},
|
||||||
|
"tags": []
|
||||||
|
},
|
||||||
|
"timestamp": "2025-01-22T17:59:39.367707Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"id": "d3eb2c9e-e123-419d-b27b-c8283a505ae8",
|
||||||
|
"type": "generation-create",
|
||||||
|
"body": {
|
||||||
|
"traceId": "litellm-test-46551fc7-c916-4a83-aeef-4274b5582ce1",
|
||||||
|
"name": "litellm-acompletion",
|
||||||
|
"startTime": "2025-01-22T09:59:39.362554-08:00",
|
||||||
|
"metadata": {
|
||||||
|
"int": 42,
|
||||||
|
"str": "hello",
|
||||||
|
"list": [
|
||||||
|
1,
|
||||||
|
2,
|
||||||
|
3
|
||||||
|
],
|
||||||
|
"set": [
|
||||||
|
4,
|
||||||
|
5
|
||||||
|
],
|
||||||
|
"dict": {
|
||||||
|
"nested": "value"
|
||||||
|
},
|
||||||
|
"hidden_params": {
|
||||||
|
"model_id": null,
|
||||||
|
"cache_key": null,
|
||||||
|
"api_base": "https://api.openai.com",
|
||||||
|
"response_cost": 5.4999999999999995e-05,
|
||||||
|
"additional_headers": {},
|
||||||
|
"litellm_overhead_time_ms": null
|
||||||
|
},
|
||||||
|
"litellm_response_cost": 5.4999999999999995e-05,
|
||||||
|
"cache_hit": false,
|
||||||
|
"requester_metadata": {}
|
||||||
|
},
|
||||||
|
"input": {
|
||||||
|
"messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "Hello!"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"output": {
|
||||||
|
"content": "Hello! How can I assist you today?",
|
||||||
|
"role": "assistant",
|
||||||
|
"tool_calls": null,
|
||||||
|
"function_call": null
|
||||||
|
},
|
||||||
|
"level": "DEFAULT",
|
||||||
|
"id": "time-09-59-39-362554_chatcmpl-d20ba1d9-cda6-4773-822e-921ebcd426a0",
|
||||||
|
"endTime": "2025-01-22T09:59:39.365756-08:00",
|
||||||
|
"completionStartTime": "2025-01-22T09:59:39.365756-08:00",
|
||||||
|
"model": "gpt-3.5-turbo",
|
||||||
|
"modelParameters": {
|
||||||
|
"extra_body": "{}"
|
||||||
|
},
|
||||||
|
"usage": {
|
||||||
|
"input": 10,
|
||||||
|
"output": 20,
|
||||||
|
"unit": "TOKENS",
|
||||||
|
"totalCost": 5.4999999999999995e-05
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"timestamp": "2025-01-22T17:59:39.368310Z"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"batch_size": 2,
|
||||||
|
"sdk_integration": "litellm",
|
||||||
|
"sdk_name": "python",
|
||||||
|
"sdk_version": "2.44.1",
|
||||||
|
"public_key": "pk-lf-e02aaea3-8668-4c9f-8c69-771a4ea1f5c9"
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
@ -0,0 +1,93 @@
|
||||||
|
{
|
||||||
|
"batch": [
|
||||||
|
{
|
||||||
|
"id": "ea3d694a-ce6b-417e-86e3-23ac17c6f6c6",
|
||||||
|
"type": "trace-create",
|
||||||
|
"body": {
|
||||||
|
"id": "litellm-test-38dcf290-8742-4fc5-ad03-c5d47e91dec0",
|
||||||
|
"timestamp": "2025-01-22T18:06:50.959206Z",
|
||||||
|
"name": "litellm-acompletion",
|
||||||
|
"input": {
|
||||||
|
"messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "Hello!"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"output": {
|
||||||
|
"content": "Hello! How can I assist you today?",
|
||||||
|
"role": "assistant",
|
||||||
|
"tool_calls": null,
|
||||||
|
"function_call": null
|
||||||
|
},
|
||||||
|
"tags": []
|
||||||
|
},
|
||||||
|
"timestamp": "2025-01-22T18:06:50.959409Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"id": "5fe03133-5798-4f87-8eec-ae0264f1eccc",
|
||||||
|
"type": "generation-create",
|
||||||
|
"body": {
|
||||||
|
"traceId": "litellm-test-38dcf290-8742-4fc5-ad03-c5d47e91dec0",
|
||||||
|
"name": "litellm-acompletion",
|
||||||
|
"startTime": "2025-01-22T10:06:50.957097-08:00",
|
||||||
|
"metadata": {
|
||||||
|
"list": [
|
||||||
|
"list",
|
||||||
|
"not",
|
||||||
|
"a",
|
||||||
|
"dict"
|
||||||
|
],
|
||||||
|
"hidden_params": {
|
||||||
|
"model_id": null,
|
||||||
|
"cache_key": null,
|
||||||
|
"api_base": "https://api.openai.com",
|
||||||
|
"response_cost": 5.4999999999999995e-05,
|
||||||
|
"additional_headers": {},
|
||||||
|
"litellm_overhead_time_ms": null
|
||||||
|
},
|
||||||
|
"litellm_response_cost": 5.4999999999999995e-05,
|
||||||
|
"cache_hit": false,
|
||||||
|
"requester_metadata": {}
|
||||||
|
},
|
||||||
|
"input": {
|
||||||
|
"messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "Hello!"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"output": {
|
||||||
|
"content": "Hello! How can I assist you today?",
|
||||||
|
"role": "assistant",
|
||||||
|
"tool_calls": null,
|
||||||
|
"function_call": null
|
||||||
|
},
|
||||||
|
"level": "DEFAULT",
|
||||||
|
"id": "time-10-06-50-957097_chatcmpl-62d4ad7c-291b-4fc7-a8a4-3ed0fc3912a5",
|
||||||
|
"endTime": "2025-01-22T10:06:50.958374-08:00",
|
||||||
|
"completionStartTime": "2025-01-22T10:06:50.958374-08:00",
|
||||||
|
"model": "gpt-3.5-turbo",
|
||||||
|
"modelParameters": {
|
||||||
|
"extra_body": "{}"
|
||||||
|
},
|
||||||
|
"usage": {
|
||||||
|
"input": 10,
|
||||||
|
"output": 20,
|
||||||
|
"unit": "TOKENS",
|
||||||
|
"totalCost": 5.4999999999999995e-05
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"timestamp": "2025-01-22T18:06:50.959850Z"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"batch_size": 2,
|
||||||
|
"sdk_integration": "litellm",
|
||||||
|
"sdk_name": "python",
|
||||||
|
"sdk_version": "2.44.1",
|
||||||
|
"public_key": "pk-lf-e02aaea3-8668-4c9f-8c69-771a4ea1f5c9"
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
@ -0,0 +1,87 @@
|
||||||
|
{
|
||||||
|
"batch": [
|
||||||
|
{
|
||||||
|
"id": "28d0c943-284b-4151-bf0d-8acf0f449865",
|
||||||
|
"type": "trace-create",
|
||||||
|
"body": {
|
||||||
|
"id": "litellm-test-d9506624-457c-40bc-9a37-578b896fa22a",
|
||||||
|
"timestamp": "2025-01-22T17:59:32.888622Z",
|
||||||
|
"name": "litellm-acompletion",
|
||||||
|
"input": {
|
||||||
|
"messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "Hello!"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"output": {
|
||||||
|
"content": "Hello! How can I assist you today?",
|
||||||
|
"role": "assistant",
|
||||||
|
"tool_calls": null,
|
||||||
|
"function_call": null
|
||||||
|
},
|
||||||
|
"tags": []
|
||||||
|
},
|
||||||
|
"timestamp": "2025-01-22T17:59:32.888940Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"id": "384e9fb4-3516-47b2-a4ae-1666337ec4a7",
|
||||||
|
"type": "generation-create",
|
||||||
|
"body": {
|
||||||
|
"traceId": "litellm-test-d9506624-457c-40bc-9a37-578b896fa22a",
|
||||||
|
"name": "litellm-acompletion",
|
||||||
|
"startTime": "2025-01-22T09:59:32.878577-08:00",
|
||||||
|
"metadata": {
|
||||||
|
"hidden_params": {
|
||||||
|
"model_id": null,
|
||||||
|
"cache_key": null,
|
||||||
|
"api_base": "https://api.openai.com",
|
||||||
|
"response_cost": 5.4999999999999995e-05,
|
||||||
|
"additional_headers": {},
|
||||||
|
"litellm_overhead_time_ms": null
|
||||||
|
},
|
||||||
|
"litellm_response_cost": 5.4999999999999995e-05,
|
||||||
|
"cache_hit": false,
|
||||||
|
"requester_metadata": {}
|
||||||
|
},
|
||||||
|
"input": {
|
||||||
|
"messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "Hello!"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"output": {
|
||||||
|
"content": "Hello! How can I assist you today?",
|
||||||
|
"role": "assistant",
|
||||||
|
"tool_calls": null,
|
||||||
|
"function_call": null
|
||||||
|
},
|
||||||
|
"level": "DEFAULT",
|
||||||
|
"id": "time-09-59-32-878577_chatcmpl-1195f870-fd4d-4e38-8dc8-99dd3da5ab0b",
|
||||||
|
"endTime": "2025-01-22T09:59:32.880691-08:00",
|
||||||
|
"completionStartTime": "2025-01-22T09:59:32.880691-08:00",
|
||||||
|
"model": "gpt-3.5-turbo",
|
||||||
|
"modelParameters": {
|
||||||
|
"extra_body": "{}"
|
||||||
|
},
|
||||||
|
"usage": {
|
||||||
|
"input": 10,
|
||||||
|
"output": 20,
|
||||||
|
"unit": "TOKENS",
|
||||||
|
"totalCost": 5.4999999999999995e-05
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"timestamp": "2025-01-22T17:59:32.889548Z"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"batch_size": 2,
|
||||||
|
"sdk_integration": "litellm",
|
||||||
|
"sdk_name": "python",
|
||||||
|
"sdk_version": "2.44.1",
|
||||||
|
"public_key": "pk-lf-e02aaea3-8668-4c9f-8c69-771a4ea1f5c9"
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
@ -0,0 +1,87 @@
|
||||||
|
{
|
||||||
|
"batch": [
|
||||||
|
{
|
||||||
|
"id": "88b1898a-cc5d-4e8e-93bc-3e71300c5e8d",
|
||||||
|
"type": "trace-create",
|
||||||
|
"body": {
|
||||||
|
"id": "litellm-test-a46356d9-ecff-44c8-a3da-fed3588b5128",
|
||||||
|
"timestamp": "2025-01-22T17:59:36.162545Z",
|
||||||
|
"name": "litellm-acompletion",
|
||||||
|
"input": {
|
||||||
|
"messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "Hello!"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"output": {
|
||||||
|
"content": "Hello! How can I assist you today?",
|
||||||
|
"role": "assistant",
|
||||||
|
"tool_calls": null,
|
||||||
|
"function_call": null
|
||||||
|
},
|
||||||
|
"tags": []
|
||||||
|
},
|
||||||
|
"timestamp": "2025-01-22T17:59:36.162702Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"id": "96bb77a6-a350-431b-bfd8-425491259728",
|
||||||
|
"type": "generation-create",
|
||||||
|
"body": {
|
||||||
|
"traceId": "litellm-test-a46356d9-ecff-44c8-a3da-fed3588b5128",
|
||||||
|
"name": "litellm-acompletion",
|
||||||
|
"startTime": "2025-01-22T09:59:36.161090-08:00",
|
||||||
|
"metadata": {
|
||||||
|
"hidden_params": {
|
||||||
|
"model_id": null,
|
||||||
|
"cache_key": null,
|
||||||
|
"api_base": "https://api.openai.com",
|
||||||
|
"response_cost": 5.4999999999999995e-05,
|
||||||
|
"additional_headers": {},
|
||||||
|
"litellm_overhead_time_ms": null
|
||||||
|
},
|
||||||
|
"litellm_response_cost": 5.4999999999999995e-05,
|
||||||
|
"cache_hit": false,
|
||||||
|
"requester_metadata": {}
|
||||||
|
},
|
||||||
|
"input": {
|
||||||
|
"messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "Hello!"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"output": {
|
||||||
|
"content": "Hello! How can I assist you today?",
|
||||||
|
"role": "assistant",
|
||||||
|
"tool_calls": null,
|
||||||
|
"function_call": null
|
||||||
|
},
|
||||||
|
"level": "DEFAULT",
|
||||||
|
"id": "time-09-59-36-161090_chatcmpl-1ee988c9-9133-4655-bbe4-b97ffb6e3dc9",
|
||||||
|
"endTime": "2025-01-22T09:59:36.161959-08:00",
|
||||||
|
"completionStartTime": "2025-01-22T09:59:36.161959-08:00",
|
||||||
|
"model": "gpt-3.5-turbo",
|
||||||
|
"modelParameters": {
|
||||||
|
"extra_body": "{}"
|
||||||
|
},
|
||||||
|
"usage": {
|
||||||
|
"input": 10,
|
||||||
|
"output": 20,
|
||||||
|
"unit": "TOKENS",
|
||||||
|
"totalCost": 5.4999999999999995e-05
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"timestamp": "2025-01-22T17:59:36.162997Z"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"batch_size": 2,
|
||||||
|
"sdk_integration": "litellm",
|
||||||
|
"sdk_name": "python",
|
||||||
|
"sdk_version": "2.44.1",
|
||||||
|
"public_key": "pk-lf-e02aaea3-8668-4c9f-8c69-771a4ea1f5c9"
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
@ -0,0 +1,87 @@
|
||||||
|
{
|
||||||
|
"batch": [
|
||||||
|
{
|
||||||
|
"id": "28d0c943-284b-4151-bf0d-8acf0f449865",
|
||||||
|
"type": "trace-create",
|
||||||
|
"body": {
|
||||||
|
"id": "litellm-test-d9506624-457c-40bc-9a37-578b896fa22a",
|
||||||
|
"timestamp": "2025-01-22T17:59:32.888622Z",
|
||||||
|
"name": "litellm-acompletion",
|
||||||
|
"input": {
|
||||||
|
"messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "Hello!"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"output": {
|
||||||
|
"content": "Hello! How can I assist you today?",
|
||||||
|
"role": "assistant",
|
||||||
|
"tool_calls": null,
|
||||||
|
"function_call": null
|
||||||
|
},
|
||||||
|
"tags": []
|
||||||
|
},
|
||||||
|
"timestamp": "2025-01-22T17:59:32.888940Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"id": "384e9fb4-3516-47b2-a4ae-1666337ec4a7",
|
||||||
|
"type": "generation-create",
|
||||||
|
"body": {
|
||||||
|
"traceId": "litellm-test-d9506624-457c-40bc-9a37-578b896fa22a",
|
||||||
|
"name": "litellm-acompletion",
|
||||||
|
"startTime": "2025-01-22T09:59:32.878577-08:00",
|
||||||
|
"metadata": {
|
||||||
|
"hidden_params": {
|
||||||
|
"model_id": null,
|
||||||
|
"cache_key": null,
|
||||||
|
"api_base": "https://api.openai.com",
|
||||||
|
"response_cost": 5.4999999999999995e-05,
|
||||||
|
"additional_headers": {},
|
||||||
|
"litellm_overhead_time_ms": null
|
||||||
|
},
|
||||||
|
"litellm_response_cost": 5.4999999999999995e-05,
|
||||||
|
"cache_hit": false,
|
||||||
|
"requester_metadata": {}
|
||||||
|
},
|
||||||
|
"input": {
|
||||||
|
"messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "Hello!"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"output": {
|
||||||
|
"content": "Hello! How can I assist you today?",
|
||||||
|
"role": "assistant",
|
||||||
|
"tool_calls": null,
|
||||||
|
"function_call": null
|
||||||
|
},
|
||||||
|
"level": "DEFAULT",
|
||||||
|
"id": "time-09-59-32-878577_chatcmpl-1195f870-fd4d-4e38-8dc8-99dd3da5ab0b",
|
||||||
|
"endTime": "2025-01-22T09:59:32.880691-08:00",
|
||||||
|
"completionStartTime": "2025-01-22T09:59:32.880691-08:00",
|
||||||
|
"model": "gpt-3.5-turbo",
|
||||||
|
"modelParameters": {
|
||||||
|
"extra_body": "{}"
|
||||||
|
},
|
||||||
|
"usage": {
|
||||||
|
"input": 10,
|
||||||
|
"output": 20,
|
||||||
|
"unit": "TOKENS",
|
||||||
|
"totalCost": 5.4999999999999995e-05
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"timestamp": "2025-01-22T17:59:32.889548Z"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"batch_size": 2,
|
||||||
|
"sdk_integration": "litellm",
|
||||||
|
"sdk_name": "python",
|
||||||
|
"sdk_version": "2.44.1",
|
||||||
|
"public_key": "pk-lf-e02aaea3-8668-4c9f-8c69-771a4ea1f5c9"
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
@ -0,0 +1,93 @@
|
||||||
|
{
|
||||||
|
"batch": [
|
||||||
|
{
|
||||||
|
"id": "44f179be-e3b9-486f-986f-030fc50614f0",
|
||||||
|
"type": "trace-create",
|
||||||
|
"body": {
|
||||||
|
"id": "litellm-test-8a04085c-1859-48fa-9fd8-1ec487fe455e",
|
||||||
|
"timestamp": "2025-01-22T17:55:28.854927Z",
|
||||||
|
"name": "litellm-acompletion",
|
||||||
|
"input": {
|
||||||
|
"messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "Hello!"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"output": {
|
||||||
|
"content": "Hello! How can I assist you today?",
|
||||||
|
"role": "assistant",
|
||||||
|
"tool_calls": null,
|
||||||
|
"function_call": null
|
||||||
|
},
|
||||||
|
"tags": []
|
||||||
|
},
|
||||||
|
"timestamp": "2025-01-22T17:55:28.855187Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"id": "2175ee64-58a3-41ab-96df-405b76695f5f",
|
||||||
|
"type": "generation-create",
|
||||||
|
"body": {
|
||||||
|
"traceId": "litellm-test-8a04085c-1859-48fa-9fd8-1ec487fe455e",
|
||||||
|
"name": "litellm-acompletion",
|
||||||
|
"startTime": "2025-01-22T09:55:28.852503-08:00",
|
||||||
|
"metadata": {
|
||||||
|
"a": {
|
||||||
|
"nested_a": 1
|
||||||
|
},
|
||||||
|
"b": {
|
||||||
|
"nested_b": 2
|
||||||
|
},
|
||||||
|
"hidden_params": {
|
||||||
|
"model_id": null,
|
||||||
|
"cache_key": null,
|
||||||
|
"api_base": "https://api.openai.com",
|
||||||
|
"response_cost": 5.4999999999999995e-05,
|
||||||
|
"additional_headers": {},
|
||||||
|
"litellm_overhead_time_ms": null
|
||||||
|
},
|
||||||
|
"litellm_response_cost": 5.4999999999999995e-05,
|
||||||
|
"cache_hit": false,
|
||||||
|
"requester_metadata": {}
|
||||||
|
},
|
||||||
|
"input": {
|
||||||
|
"messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "Hello!"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"output": {
|
||||||
|
"content": "Hello! How can I assist you today?",
|
||||||
|
"role": "assistant",
|
||||||
|
"tool_calls": null,
|
||||||
|
"function_call": null
|
||||||
|
},
|
||||||
|
"level": "DEFAULT",
|
||||||
|
"id": "time-09-55-28-852503_chatcmpl-131cf0da-a47b-4cd1-850b-50fa077362ac",
|
||||||
|
"endTime": "2025-01-22T09:55:28.853979-08:00",
|
||||||
|
"completionStartTime": "2025-01-22T09:55:28.853979-08:00",
|
||||||
|
"model": "gpt-3.5-turbo",
|
||||||
|
"modelParameters": {
|
||||||
|
"extra_body": "{}"
|
||||||
|
},
|
||||||
|
"usage": {
|
||||||
|
"input": 10,
|
||||||
|
"output": 20,
|
||||||
|
"unit": "TOKENS",
|
||||||
|
"totalCost": 5.4999999999999995e-05
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"timestamp": "2025-01-22T17:55:28.855732Z"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"batch_size": 2,
|
||||||
|
"sdk_integration": "litellm",
|
||||||
|
"sdk_name": "python",
|
||||||
|
"sdk_version": "2.44.1",
|
||||||
|
"public_key": "pk-lf-e02aaea3-8668-4c9f-8c69-771a4ea1f5c9"
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
@ -0,0 +1,93 @@
|
||||||
|
{
|
||||||
|
"batch": [
|
||||||
|
{
|
||||||
|
"id": "02c74119-76b7-4f79-91cb-c55f1495c100",
|
||||||
|
"type": "trace-create",
|
||||||
|
"body": {
|
||||||
|
"id": "litellm-test-e58116c7-ead0-417e-9f86-b35f1e5bc242",
|
||||||
|
"timestamp": "2025-01-22T17:53:53.754012Z",
|
||||||
|
"name": "litellm-acompletion",
|
||||||
|
"input": {
|
||||||
|
"messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "Hello!"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"output": {
|
||||||
|
"content": "Hello! How can I assist you today?",
|
||||||
|
"role": "assistant",
|
||||||
|
"tool_calls": null,
|
||||||
|
"function_call": null
|
||||||
|
},
|
||||||
|
"tags": []
|
||||||
|
},
|
||||||
|
"timestamp": "2025-01-22T17:53:53.754178Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"id": "097968e0-52e9-46b5-9e8e-e6e08dd00e72",
|
||||||
|
"type": "generation-create",
|
||||||
|
"body": {
|
||||||
|
"traceId": "litellm-test-e58116c7-ead0-417e-9f86-b35f1e5bc242",
|
||||||
|
"name": "litellm-acompletion",
|
||||||
|
"startTime": "2025-01-22T09:53:53.752422-08:00",
|
||||||
|
"metadata": {
|
||||||
|
"a": {
|
||||||
|
"nested_a": 1
|
||||||
|
},
|
||||||
|
"b": {
|
||||||
|
"nested_b": 2
|
||||||
|
},
|
||||||
|
"hidden_params": {
|
||||||
|
"model_id": null,
|
||||||
|
"cache_key": null,
|
||||||
|
"api_base": "https://api.openai.com",
|
||||||
|
"response_cost": 5.4999999999999995e-05,
|
||||||
|
"additional_headers": {},
|
||||||
|
"litellm_overhead_time_ms": null
|
||||||
|
},
|
||||||
|
"litellm_response_cost": 5.4999999999999995e-05,
|
||||||
|
"cache_hit": false,
|
||||||
|
"requester_metadata": {}
|
||||||
|
},
|
||||||
|
"input": {
|
||||||
|
"messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "Hello!"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"output": {
|
||||||
|
"content": "Hello! How can I assist you today?",
|
||||||
|
"role": "assistant",
|
||||||
|
"tool_calls": null,
|
||||||
|
"function_call": null
|
||||||
|
},
|
||||||
|
"level": "DEFAULT",
|
||||||
|
"id": "time-09-53-53-752422_chatcmpl-e99bc1d3-a393-493f-8afe-4507c0acff15",
|
||||||
|
"endTime": "2025-01-22T09:53:53.753431-08:00",
|
||||||
|
"completionStartTime": "2025-01-22T09:53:53.753431-08:00",
|
||||||
|
"model": "gpt-3.5-turbo",
|
||||||
|
"modelParameters": {
|
||||||
|
"extra_body": "{}"
|
||||||
|
},
|
||||||
|
"usage": {
|
||||||
|
"input": 10,
|
||||||
|
"output": 20,
|
||||||
|
"unit": "TOKENS",
|
||||||
|
"totalCost": 5.4999999999999995e-05
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"timestamp": "2025-01-22T17:53:53.754511Z"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"batch_size": 2,
|
||||||
|
"sdk_integration": "litellm",
|
||||||
|
"sdk_name": "python",
|
||||||
|
"sdk_version": "2.44.1",
|
||||||
|
"public_key": "pk-lf-e02aaea3-8668-4c9f-8c69-771a4ea1f5c9"
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
@ -0,0 +1,97 @@
|
||||||
|
{
|
||||||
|
"batch": [
|
||||||
|
{
|
||||||
|
"id": "1a55383a-e6fa-41f9-81fe-e7aa58c55f40",
|
||||||
|
"type": "trace-create",
|
||||||
|
"body": {
|
||||||
|
"id": "litellm-test-08fd1578-4a67-49b4-ac23-2dff1c112c80",
|
||||||
|
"timestamp": "2025-01-22T17:56:35.477276Z",
|
||||||
|
"name": "litellm-acompletion",
|
||||||
|
"input": {
|
||||||
|
"messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "Hello!"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"output": {
|
||||||
|
"content": "Hello! How can I assist you today?",
|
||||||
|
"role": "assistant",
|
||||||
|
"tool_calls": null,
|
||||||
|
"function_call": null
|
||||||
|
},
|
||||||
|
"tags": []
|
||||||
|
},
|
||||||
|
"timestamp": "2025-01-22T17:56:35.477571Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"id": "13ba66e8-f72b-4f57-a6cc-57c0be2829b1",
|
||||||
|
"type": "generation-create",
|
||||||
|
"body": {
|
||||||
|
"traceId": "litellm-test-08fd1578-4a67-49b4-ac23-2dff1c112c80",
|
||||||
|
"name": "litellm-acompletion",
|
||||||
|
"startTime": "2025-01-22T09:56:35.474752-08:00",
|
||||||
|
"metadata": {
|
||||||
|
"a": [
|
||||||
|
1,
|
||||||
|
2,
|
||||||
|
3
|
||||||
|
],
|
||||||
|
"b": [
|
||||||
|
4,
|
||||||
|
5,
|
||||||
|
6
|
||||||
|
],
|
||||||
|
"hidden_params": {
|
||||||
|
"model_id": null,
|
||||||
|
"cache_key": null,
|
||||||
|
"api_base": "https://api.openai.com",
|
||||||
|
"response_cost": 5.4999999999999995e-05,
|
||||||
|
"additional_headers": {},
|
||||||
|
"litellm_overhead_time_ms": null
|
||||||
|
},
|
||||||
|
"litellm_response_cost": 5.4999999999999995e-05,
|
||||||
|
"cache_hit": false,
|
||||||
|
"requester_metadata": {}
|
||||||
|
},
|
||||||
|
"input": {
|
||||||
|
"messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "Hello!"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"output": {
|
||||||
|
"content": "Hello! How can I assist you today?",
|
||||||
|
"role": "assistant",
|
||||||
|
"tool_calls": null,
|
||||||
|
"function_call": null
|
||||||
|
},
|
||||||
|
"level": "DEFAULT",
|
||||||
|
"id": "time-09-56-35-474752_chatcmpl-9b152610-3d1e-4731-a84e-d0341ea69a0f",
|
||||||
|
"endTime": "2025-01-22T09:56:35.476236-08:00",
|
||||||
|
"completionStartTime": "2025-01-22T09:56:35.476236-08:00",
|
||||||
|
"model": "gpt-3.5-turbo",
|
||||||
|
"modelParameters": {
|
||||||
|
"extra_body": "{}"
|
||||||
|
},
|
||||||
|
"usage": {
|
||||||
|
"input": 10,
|
||||||
|
"output": 20,
|
||||||
|
"unit": "TOKENS",
|
||||||
|
"totalCost": 5.4999999999999995e-05
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"timestamp": "2025-01-22T17:56:35.478171Z"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"batch_size": 2,
|
||||||
|
"sdk_integration": "litellm",
|
||||||
|
"sdk_name": "python",
|
||||||
|
"sdk_version": "2.44.1",
|
||||||
|
"public_key": "pk-lf-e02aaea3-8668-4c9f-8c69-771a4ea1f5c9"
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
@ -0,0 +1,101 @@
|
||||||
|
{
|
||||||
|
"batch": [
|
||||||
|
{
|
||||||
|
"id": "7fb1f295-a7af-47af-afbd-e2f2d08280aa",
|
||||||
|
"type": "trace-create",
|
||||||
|
"body": {
|
||||||
|
"id": "litellm-test-c3acc34b-3c06-4868-bcee-87a3c4c1367e",
|
||||||
|
"timestamp": "2025-01-22T17:56:38.786515Z",
|
||||||
|
"name": "litellm-acompletion",
|
||||||
|
"input": {
|
||||||
|
"messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "Hello!"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"output": {
|
||||||
|
"content": "Hello! How can I assist you today?",
|
||||||
|
"role": "assistant",
|
||||||
|
"tool_calls": null,
|
||||||
|
"function_call": null
|
||||||
|
},
|
||||||
|
"tags": []
|
||||||
|
},
|
||||||
|
"timestamp": "2025-01-22T17:56:38.786742Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"id": "412870bc-fc50-4426-a0dc-9e8b016e14bb",
|
||||||
|
"type": "generation-create",
|
||||||
|
"body": {
|
||||||
|
"traceId": "litellm-test-c3acc34b-3c06-4868-bcee-87a3c4c1367e",
|
||||||
|
"name": "litellm-acompletion",
|
||||||
|
"startTime": "2025-01-22T09:56:38.784548-08:00",
|
||||||
|
"metadata": {
|
||||||
|
"a": [
|
||||||
|
1,
|
||||||
|
2
|
||||||
|
],
|
||||||
|
"b": [
|
||||||
|
3,
|
||||||
|
4
|
||||||
|
],
|
||||||
|
"c": {
|
||||||
|
"d": [
|
||||||
|
5,
|
||||||
|
6
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"hidden_params": {
|
||||||
|
"model_id": null,
|
||||||
|
"cache_key": null,
|
||||||
|
"api_base": "https://api.openai.com",
|
||||||
|
"response_cost": 5.4999999999999995e-05,
|
||||||
|
"additional_headers": {},
|
||||||
|
"litellm_overhead_time_ms": null
|
||||||
|
},
|
||||||
|
"litellm_response_cost": 5.4999999999999995e-05,
|
||||||
|
"cache_hit": false,
|
||||||
|
"requester_metadata": {}
|
||||||
|
},
|
||||||
|
"input": {
|
||||||
|
"messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "Hello!"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"output": {
|
||||||
|
"content": "Hello! How can I assist you today?",
|
||||||
|
"role": "assistant",
|
||||||
|
"tool_calls": null,
|
||||||
|
"function_call": null
|
||||||
|
},
|
||||||
|
"level": "DEFAULT",
|
||||||
|
"id": "time-09-56-38-784548_chatcmpl-438c8727-86b3-44d9-9b46-42330922cf50",
|
||||||
|
"endTime": "2025-01-22T09:56:38.785762-08:00",
|
||||||
|
"completionStartTime": "2025-01-22T09:56:38.785762-08:00",
|
||||||
|
"model": "gpt-3.5-turbo",
|
||||||
|
"modelParameters": {
|
||||||
|
"extra_body": "{}"
|
||||||
|
},
|
||||||
|
"usage": {
|
||||||
|
"input": 10,
|
||||||
|
"output": 20,
|
||||||
|
"unit": "TOKENS",
|
||||||
|
"totalCost": 5.4999999999999995e-05
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"timestamp": "2025-01-22T17:56:38.787196Z"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"batch_size": 2,
|
||||||
|
"sdk_integration": "litellm",
|
||||||
|
"sdk_name": "python",
|
||||||
|
"sdk_version": "2.44.1",
|
||||||
|
"public_key": "pk-lf-e02aaea3-8668-4c9f-8c69-771a4ea1f5c9"
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
@ -6,6 +6,7 @@ import os
|
||||||
import sys
|
import sys
|
||||||
from typing import Any, Optional
|
from typing import Any, Optional
|
||||||
from unittest.mock import MagicMock, patch
|
from unittest.mock import MagicMock, patch
|
||||||
|
import threading
|
||||||
|
|
||||||
logging.basicConfig(level=logging.DEBUG)
|
logging.basicConfig(level=logging.DEBUG)
|
||||||
sys.path.insert(0, os.path.abspath("../.."))
|
sys.path.insert(0, os.path.abspath("../.."))
|
||||||
|
|
@ -216,3 +217,137 @@ class TestLangfuseLogging:
|
||||||
"completion_with_tags_stream.json",
|
"completion_with_tags_stream.json",
|
||||||
setup["trace_id"],
|
setup["trace_id"],
|
||||||
)
|
)
|
||||||
|
|
||||||
|
@pytest.mark.asyncio
|
||||||
|
async def test_langfuse_logging_completion_with_langfuse_metadata(self, mock_setup):
|
||||||
|
"""Test Langfuse logging for chat completion with metadata for langfuse"""
|
||||||
|
setup = await mock_setup # Await the fixture
|
||||||
|
with patch("httpx.Client.post", setup["mock_post"]):
|
||||||
|
await litellm.acompletion(
|
||||||
|
model="gpt-3.5-turbo",
|
||||||
|
messages=[{"role": "user", "content": "Hello!"}],
|
||||||
|
mock_response="Hello! How can I assist you today?",
|
||||||
|
metadata={
|
||||||
|
"trace_id": setup["trace_id"],
|
||||||
|
"tags": ["test_tag", "test_tag_2"],
|
||||||
|
"generation_name": "test_generation_name",
|
||||||
|
"parent_observation_id": "test_parent_observation_id",
|
||||||
|
"version": "test_version",
|
||||||
|
"trace_user_id": "test_user_id",
|
||||||
|
"session_id": "test_session_id",
|
||||||
|
"trace_name": "test_trace_name",
|
||||||
|
"trace_metadata": {"test_key": "test_value"},
|
||||||
|
"trace_version": "test_trace_version",
|
||||||
|
"trace_release": "test_trace_release",
|
||||||
|
},
|
||||||
|
)
|
||||||
|
await self._verify_langfuse_call(
|
||||||
|
setup["mock_post"],
|
||||||
|
"completion_with_langfuse_metadata.json",
|
||||||
|
setup["trace_id"],
|
||||||
|
)
|
||||||
|
|
||||||
|
@pytest.mark.asyncio
|
||||||
|
async def test_langfuse_logging_with_non_serializable_metadata(self, mock_setup):
|
||||||
|
"""Test Langfuse logging with metadata that requires preparation (Pydantic models, sets, etc)"""
|
||||||
|
from pydantic import BaseModel
|
||||||
|
from typing import Set
|
||||||
|
import datetime
|
||||||
|
|
||||||
|
class UserPreferences(BaseModel):
|
||||||
|
favorite_colors: Set[str]
|
||||||
|
last_login: datetime.datetime
|
||||||
|
settings: dict
|
||||||
|
|
||||||
|
setup = await mock_setup
|
||||||
|
|
||||||
|
test_metadata = {
|
||||||
|
"user_prefs": UserPreferences(
|
||||||
|
favorite_colors={"red", "blue"},
|
||||||
|
last_login=datetime.datetime.now(),
|
||||||
|
settings={"theme": "dark", "notifications": True},
|
||||||
|
),
|
||||||
|
"nested_set": {
|
||||||
|
"inner_set": {1, 2, 3},
|
||||||
|
"inner_pydantic": UserPreferences(
|
||||||
|
favorite_colors={"green", "yellow"},
|
||||||
|
last_login=datetime.datetime.now(),
|
||||||
|
settings={"theme": "light"},
|
||||||
|
),
|
||||||
|
},
|
||||||
|
"trace_id": setup["trace_id"],
|
||||||
|
}
|
||||||
|
|
||||||
|
with patch("httpx.Client.post", setup["mock_post"]):
|
||||||
|
response = await litellm.acompletion(
|
||||||
|
model="gpt-3.5-turbo",
|
||||||
|
messages=[{"role": "user", "content": "Hello!"}],
|
||||||
|
mock_response="Hello! How can I assist you today?",
|
||||||
|
metadata=test_metadata,
|
||||||
|
)
|
||||||
|
|
||||||
|
await self._verify_langfuse_call(
|
||||||
|
setup["mock_post"],
|
||||||
|
"completion_with_complex_metadata.json",
|
||||||
|
setup["trace_id"],
|
||||||
|
)
|
||||||
|
|
||||||
|
@pytest.mark.asyncio
|
||||||
|
@pytest.mark.parametrize(
|
||||||
|
"test_metadata, response_json_file",
|
||||||
|
[
|
||||||
|
({"a": 1, "b": 2, "c": 3}, "simple_metadata.json"),
|
||||||
|
(
|
||||||
|
{"a": {"nested_a": 1}, "b": {"nested_b": 2}},
|
||||||
|
"nested_metadata.json",
|
||||||
|
),
|
||||||
|
({"a": [1, 2, 3], "b": {4, 5, 6}}, "simple_metadata2.json"),
|
||||||
|
(
|
||||||
|
{"a": (1, 2), "b": frozenset([3, 4]), "c": {"d": [5, 6]}},
|
||||||
|
"simple_metadata3.json",
|
||||||
|
),
|
||||||
|
({"lock": threading.Lock()}, "metadata_with_lock.json"),
|
||||||
|
({"func": lambda x: x + 1}, "metadata_with_function.json"),
|
||||||
|
(
|
||||||
|
{
|
||||||
|
"int": 42,
|
||||||
|
"str": "hello",
|
||||||
|
"list": [1, 2, 3],
|
||||||
|
"set": {4, 5},
|
||||||
|
"dict": {"nested": "value"},
|
||||||
|
"non_copyable": threading.Lock(),
|
||||||
|
"function": print,
|
||||||
|
},
|
||||||
|
"complex_metadata.json",
|
||||||
|
),
|
||||||
|
(
|
||||||
|
{"list": ["list", "not", "a", "dict"]},
|
||||||
|
"complex_metadata_2.json",
|
||||||
|
),
|
||||||
|
({}, "empty_metadata.json"),
|
||||||
|
],
|
||||||
|
)
|
||||||
|
async def test_langfuse_logging_with_various_metadata_types(
|
||||||
|
self, mock_setup, test_metadata, response_json_file
|
||||||
|
):
|
||||||
|
"""Test Langfuse logging with various metadata types including non-serializable objects"""
|
||||||
|
import threading
|
||||||
|
|
||||||
|
setup = await mock_setup
|
||||||
|
|
||||||
|
if test_metadata is not None:
|
||||||
|
test_metadata["trace_id"] = setup["trace_id"]
|
||||||
|
|
||||||
|
with patch("httpx.Client.post", setup["mock_post"]):
|
||||||
|
await litellm.acompletion(
|
||||||
|
model="gpt-3.5-turbo",
|
||||||
|
messages=[{"role": "user", "content": "Hello!"}],
|
||||||
|
mock_response="Hello! How can I assist you today?",
|
||||||
|
metadata=test_metadata,
|
||||||
|
)
|
||||||
|
|
||||||
|
await self._verify_langfuse_call(
|
||||||
|
setup["mock_post"],
|
||||||
|
response_json_file,
|
||||||
|
setup["trace_id"],
|
||||||
|
)
|
||||||
|
|
|
||||||
|
|
@ -271,52 +271,6 @@ def test_get_langfuse_logger_for_request_with_cached_logger():
|
||||||
mock_cache.get_cache.assert_called_once()
|
mock_cache.get_cache.assert_called_once()
|
||||||
|
|
||||||
|
|
||||||
@pytest.mark.parametrize(
|
|
||||||
"metadata, expected_metadata",
|
|
||||||
[
|
|
||||||
({"a": 1, "b": 2, "c": 3}, {"a": 1, "b": 2, "c": 3}),
|
|
||||||
(
|
|
||||||
{"a": {"nested_a": 1}, "b": {"nested_b": 2}},
|
|
||||||
{"a": {"nested_a": 1}, "b": {"nested_b": 2}},
|
|
||||||
),
|
|
||||||
({"a": [1, 2, 3], "b": {4, 5, 6}}, {"a": [1, 2, 3], "b": {4, 5, 6}}),
|
|
||||||
(
|
|
||||||
{"a": (1, 2), "b": frozenset([3, 4]), "c": {"d": [5, 6]}},
|
|
||||||
{"a": (1, 2), "b": frozenset([3, 4]), "c": {"d": [5, 6]}},
|
|
||||||
),
|
|
||||||
({"lock": threading.Lock()}, {}),
|
|
||||||
({"func": lambda x: x + 1}, {}),
|
|
||||||
(
|
|
||||||
{
|
|
||||||
"int": 42,
|
|
||||||
"str": "hello",
|
|
||||||
"list": [1, 2, 3],
|
|
||||||
"set": {4, 5},
|
|
||||||
"dict": {"nested": "value"},
|
|
||||||
"non_copyable": threading.Lock(),
|
|
||||||
"function": print,
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"int": 42,
|
|
||||||
"str": "hello",
|
|
||||||
"list": [1, 2, 3],
|
|
||||||
"set": {4, 5},
|
|
||||||
"dict": {"nested": "value"},
|
|
||||||
},
|
|
||||||
),
|
|
||||||
(
|
|
||||||
{"list": ["list", "not", "a", "dict"]},
|
|
||||||
{"list": ["list", "not", "a", "dict"]},
|
|
||||||
),
|
|
||||||
({}, {}),
|
|
||||||
(None, None),
|
|
||||||
],
|
|
||||||
)
|
|
||||||
def test_langfuse_logger_prepare_metadata(metadata, expected_metadata):
|
|
||||||
result = global_langfuse_logger._prepare_metadata(metadata)
|
|
||||||
assert result == expected_metadata
|
|
||||||
|
|
||||||
|
|
||||||
def test_get_langfuse_tags():
|
def test_get_langfuse_tags():
|
||||||
"""
|
"""
|
||||||
Test that _get_langfuse_tags correctly extracts tags from the standard logging payload
|
Test that _get_langfuse_tags correctly extracts tags from the standard logging payload
|
||||||
|
|
|
||||||
Loading…
Add table
Add a link
Reference in a new issue