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test_langfuse_logging_with_non_serializable_metadata

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Ishaan Jaff 2025-01-22 09:41:42 -08:00
parent 87a94faa94
commit d5095352c6
2 changed files with 171 additions and 0 deletions
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126
tests/logging_callback_tests/langfuse_expected_request_body/completion_with_complex_metadata.json Normal file
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@ -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"
}
}

45
tests/logging_callback_tests/test_langfuse_e2e_test.py
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@ -245,3 +245,48 @@ class TestLangfuseLogging:
"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"],
)