mirror of
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2c733c00f5
* test: modernize models used in CircleCI e2e test suites
Replaces obsolete models (gpt-4o, gpt-4o-mini, gpt-3.5-turbo,
claude-3-5-sonnet-20240620, claude-sonnet-4-20250514) with current
equivalents across the e2e_openai_endpoints and
proxy_e2e_anthropic_messages_tests CircleCI jobs.
- gpt-4o -> gpt-5.5 (responses API e2e tests)
- gpt-4o-mini -> gpt-5-mini (websocket responses, oai_misc_config)
- gpt-4o-mini-2024-07-18 -> gpt-4.1-mini-2025-04-14 (fine-tuning,
still actively fine-tunable)
- gpt-4 / gpt-3.5-turbo target_model_names example -> gpt-5.5 /
gpt-5-mini
- bedrock claude-3-5-sonnet-20240620 batch entry -> haiku-4-5-20251001
(also aligning oai_misc_config model_name with what
test_bedrock_batches_api.py actually requests)
- bedrock claude-sonnet-4-20250514 (deprecated, retires 2026-06-15)
-> claude-sonnet-4-5-20250929
* test: point bedrock-claude-sonnet-4 alias at Sonnet 4.6, not 4.5
Greptile/Cursor flagged that after the previous commit, the
bedrock-claude-sonnet-4 alias collided with bedrock-claude-sonnet-4.5
(both pointed to claude-sonnet-4-5-20250929). Rename to
bedrock-claude-sonnet-4.6 and point it at the Sonnet 4.6 Bedrock ID
(us.anthropic.claude-sonnet-4-6, already in the litellm model
registry) so the alias name matches the underlying model version.
* test: modernize models across remaining CI-mounted configs & tests
Expands the modernization sweep to all CircleCI-mounted proxy configs
and to test directories where the model literal is a fixture/route key
(not the test's subject).
Config changes:
- proxy_server_config.yaml: bump gpt-3.5-turbo / gpt-3.5-turbo-1106 /
gpt-4o / gemini-1.5-flash / dall-e-3 underlying models; rename
gpt-3.5-turbo-end-user-test alias to gpt-5-mini-end-user-test; bump
text-embedding-ada-002 underlying to text-embedding-3-small. User-
facing aliases (gpt-3.5-turbo, gpt-4, text-embedding-ada-002, etc.)
preserved for backward compatibility with tests.
- simple_config.yaml, otel_test_config.yaml, spend_tracking_config.yaml:
bump gpt-3.5-turbo underlying to gpt-5-mini.
- pass_through_config.yaml: claude-3-5-sonnet / claude-3-7-sonnet /
claude-3-haiku entries replaced with claude-sonnet-4-5 / claude-
haiku-4-5 / claude-opus-4-7.
- oai_misc_config.yaml: align alias name with the gpt-5-mini rename.
Test changes (proactive: claude-sonnet-4-20250514 / claude-opus-4-
20250514 retire 2026-06-15):
- tests/llm_translation/test_anthropic_completion.py: bump 3 references
+ paired Vertex AI ID to claude-sonnet-4-5.
- tests/llm_translation/test_optional_params.py: bump 2 references.
- tests/pass_through_unit_tests/test_anthropic_messages_passthrough.py
and test_bedrock_anthropic_messages_test.py: bump router fixtures
using the deprecated model IDs.
- tests/pass_through_unit_tests/base_anthropic_messages_tool_search_test.py:
modernize docstring examples.
- tests/test_end_users.py: update references to renamed alias.
* test: modernize placeholder model literals in router_unit_tests
Mass replace_all on fixture/placeholder model literals across the
router_unit_tests/ suite (model name is a routing key / label, not the
test subject). Sub-agent sweep so far — additional commits will follow
for logging_callback_tests/, enterprise/, top-level tests/test_*.py,
and other CI-mounted dirs.
Mappings applied:
- gpt-3.5-turbo -> gpt-5-mini
- gpt-4 (bare) -> gpt-5.5
- gpt-4o (bare) -> gpt-5
- text-embedding-ada-002 -> text-embedding-3-small
- claude-3-sonnet-20240229 / claude-3-opus-20240229 /
claude-3-haiku-20240307 / claude-3-5-sonnet-20240620 ->
claude-sonnet-4-5-20250929 / claude-opus-4-7 /
claude-haiku-4-5-20251001 as appropriate
Explicitly preserved:
- gpt-4o-mini-* variants (transcribe, tts, etc.) where they're current
- gpt-4-turbo / gpt-4-vision-preview / gpt-4-0613 (subject literals)
- JSONL batch body literals
- Mock LLM response model fields (must match upstream)
- Fake/mock identifiers
* test: modernize placeholder model literals across remaining CI suites
Sub-agent sweep across logging_callback_tests/, guardrails_tests/,
enterprise/, pass_through_unit_tests/, otel_tests/,
llm_responses_api_testing/, batches_tests/, spend_tracking_tests/,
litellm_utils_tests/, unified_google_tests/, and a few top-level
tests/test_*.py files where the model literal is a fixture or
placeholder (router model_list, mock standard logging payload, mock
callback data) rather than the test's subject.
Mappings applied (see scope notes below):
- gpt-3.5-turbo -> gpt-5-mini
- gpt-4 (bare) -> gpt-5.5
- gpt-4o (bare) -> gpt-5.5 (corrected from initial gpt-5 — bare gpt-5
is not a valid OpenAI alias; only gpt-5.5 / gpt-5.4 / gpt-5.2-codex
/ gpt-5-mini exist)
- gpt-4o-mini (bare) -> gpt-5-mini
- text-embedding-ada-002 -> text-embedding-3-small
- claude-3-sonnet-20240229 -> claude-sonnet-4-5-20250929
- claude-3-opus-20240229 -> claude-opus-4-7
- claude-3-haiku-20240307 -> claude-haiku-4-5-20251001
- claude-3-5-sonnet-20240620/20241022 -> claude-sonnet-4-5-20250929
- claude-3-7-sonnet-20250219 -> claude-sonnet-4-6
- gemini-1.5-flash -> gemini-2.5-flash
- gemini-1.5-pro -> gemini-2.5-pro
Explicitly preserved (not modernized):
- llm_translation/ tests where model is the SUBJECT (provider-specific
translation/transformation logic). Only the deprecated 20250514
references were already bumped in a prior commit.
- Cost-calc / tokenizer subject tests in test_utils.py (skip-ranges
documented by the sub-agent).
- Bedrock model IDs in test_health_check.py path-stripping tests.
- JSONL batch request bodies and mock LLM response bodies (must match
upstream literal).
- Langfuse expected-request-body JSON fixtures (cost values are exact-
match-asserted; changing the model would shift response_cost).
- gpt-3.5-turbo-instruct (text-completion endpoint; no modern OpenAI
equivalent).
- Top-level tests calling the proxy through user-facing aliases
(gpt-3.5-turbo, gpt-4, text-embedding-ada-002, dall-e-3) — aliases
in proxy_server_config.yaml stay; only the underlying model was
bumped.
- tests/test_gpt5_azure_temperature_support.py (the test's whole point
is model-name handling).
- Fake / mock / openai/fake identifiers.
Notable side fixes:
- test_spend_accuracy_tests.py: UPSTREAM_MODEL now matches what
spend_tracking_config.yaml's proxy actually routes to (gpt-5-mini),
resolving a latent inconsistency.
- proxy_server_config.yaml: bare `gpt-5` alias renamed to `gpt-5.5`
(bare gpt-5 is not a valid OpenAI alias).
- test_batches_logging_unit_tests.py: explicit_models list entries
kept distinct (gpt-5-mini + gpt-5.5) after bulk rename.
* test: fix CI failures from model modernization sweep
CI surfaced 4 categories of regression from the bulk modernization:
1. Azure deployment names are customer-specific. Reverted:
- tests/litellm_utils_tests/test_health_check.py: azure/text-
embedding-3-small -> azure/text-embedding-ada-002 (the CI Azure
account does not have a text-embedding-3-small deployment).
- tests/logging_callback_tests/test_custom_callback_router.py:
same revert for two router fixtures driving aembedding.
2. gpt-5 family does not accept temperature != 1. Tests that pass a
custom temperature swapped from gpt-5-mini to gpt-4.1-mini (modern
non-reasoning OpenAI mini that still accepts temperature/logprobs):
- tests/logging_callback_tests/test_datadog.py
- tests/logging_callback_tests/test_langsmith_unit_test.py
- tests/logging_callback_tests/test_otel_logging.py
3. proxy_server_config.yaml's gpt-3.5-turbo-large alias was routing to
gpt-5.5 (a reasoning model that rejects logprobs). The proxy test
tests/test_openai_endpoints.py::test_chat_completion_streaming
exercises logprobs/top_logprobs through that alias. Bumped the
underlying model to gpt-4.1 (non-reasoning, still modern).
4. tests/logging_callback_tests/test_gcs_pub_sub.py asserts against a
pinned JSON fixture (gcs_pub_sub_body/spend_logs_payload.json) with
hardcoded model="gpt-4o" and a model-specific spend value. Reverted
the litellm.acompletion calls in the test to model="gpt-4o" so the
fixture's exact-match assertions still hold.
5. tests/pass_through_unit_tests/test_anthropic_messages_passthrough.py:
anthropic.messages.create routing to openai/gpt-5-mini returned an
empty content[0] with max_tokens=100 (reasoning-token consumption).
Swapped to openai/gpt-4.1-mini.
* test: fix Assistants API model + 2 cursor[bot] review nits
1. pass_through_unit_tests/test_custom_logger_passthrough.py: gpt-5.5
isn't accepted by the /v1/assistants endpoint
("unsupported_model"). Switch to gpt-4.1-mini (modern, Assistants-
API-supported, non-reasoning).
2. example_config_yaml/pass_through_config.yaml: the previous sweep
bumped the claude-3-7-sonnet alias to claude-opus-4-7, which is a
tier change (Sonnet -> Opus). Map to claude-sonnet-4-6 to keep the
Sonnet tier intact. (Cursor bugbot review.)
3. example_config_yaml/simple_config.yaml: model_name was left as
gpt-3.5-turbo while the underlying was bumped to gpt-5-mini, which
muddles the "simple" example. Make both sides gpt-5-mini so the
most basic example is a straight 1:1 mapping again. (Cursor bugbot
review.)
* fix: revert gpt-4/gpt-3.5-turbo alias underlying to non-reasoning models
tests/test_openai_endpoints.py::test_completion calls the proxy alias
"gpt-4" with temperature=0, and other tests call gpt-3.5-turbo with
custom temperature / logprobs / the legacy /v1/completions endpoint.
The earlier modernization mapped both aliases to gpt-5.5 / gpt-5-mini,
which are reasoning models that reject temperature != 1 and don't
expose /v1/completions. Map the aliases to gpt-4.1 / gpt-4.1-mini
(modern non-reasoning OpenAI models) instead — keeps user-facing
aliases preserved while picking a current underlying that still
supports the parameters/endpoints the tests exercise.
572 lines
21 KiB
Python
572 lines
21 KiB
Python
import os
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import sys
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sys.path.insert(0, os.path.abspath("../.."))
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import pytest
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from litellm.integrations.posthog import PostHogLogger
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from litellm.types.utils import StandardLoggingPayload
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from typing import cast
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# Set env vars for tests
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os.environ["POSTHOG_API_KEY"] = "test_key"
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os.environ["POSTHOG_API_URL"] = "https://app.posthog.com"
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def create_standard_logging_payload() -> StandardLoggingPayload:
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# Use cast to bypass strict TypedDict requirements for tests
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return cast(
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StandardLoggingPayload,
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{
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"id": "test_id",
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"trace_id": "test_trace_id",
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"call_type": "completion",
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"stream": False,
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"response_cost": 0.1,
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"status": "success",
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"custom_llm_provider": "openai",
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"total_tokens": 30,
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"prompt_tokens": 20,
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"completion_tokens": 10,
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"startTime": 1234567890.0,
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"endTime": 1234567891.0,
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"completionStartTime": 1234567890.5,
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"response_time": 1.0,
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"model": "gpt-5-mini",
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"model_id": "model-123",
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"api_base": "https://api.openai.com",
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"cache_hit": False,
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"saved_cache_cost": 0.0,
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"request_tags": [],
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"end_user": None,
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"messages": [{"role": "user", "content": "Hello, world!"}],
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"response": {"choices": [{"message": {"content": "Hi there!"}}]},
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"error_str": None,
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"model_parameters": {"stream": True},
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},
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)
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@pytest.mark.asyncio
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async def test_create_posthog_event_payload():
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posthog_logger = PostHogLogger()
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standard_payload = create_standard_logging_payload()
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kwargs = {"standard_logging_object": standard_payload}
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event_payload = posthog_logger.create_posthog_event_payload(kwargs)
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assert event_payload["event"] == "$ai_generation"
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assert event_payload["properties"]["$ai_model"] == "gpt-5-mini"
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assert event_payload["properties"]["$ai_input_tokens"] == 20
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assert event_payload["properties"]["$ai_output_tokens"] == 10
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@pytest.mark.asyncio
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async def test_posthog_failure_logging():
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posthog_logger = PostHogLogger()
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standard_payload = create_standard_logging_payload()
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standard_payload["status"] = "failure"
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standard_payload["error_str"] = "Test error"
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kwargs = {"standard_logging_object": standard_payload}
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event_payload = posthog_logger.create_posthog_event_payload(kwargs)
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assert event_payload["properties"]["$ai_is_error"] is True
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assert event_payload["properties"]["$ai_error"] == "Test error"
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@pytest.mark.asyncio
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async def test_posthog_embedding_event():
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posthog_logger = PostHogLogger()
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standard_payload = create_standard_logging_payload()
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standard_payload["call_type"] = "embedding"
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kwargs = {"standard_logging_object": standard_payload}
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event_payload = posthog_logger.create_posthog_event_payload(kwargs)
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assert event_payload["event"] == "$ai_embedding"
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assert "$ai_output_tokens" not in event_payload["properties"]
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@pytest.mark.asyncio
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async def test_trace_id_fallback_from_standard_logging_object():
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"""Test that trace_id is properly extracted from standard_logging_object"""
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posthog_logger = PostHogLogger()
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standard_payload = create_standard_logging_payload()
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standard_payload["trace_id"] = "test-trace-123"
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kwargs = {"standard_logging_object": standard_payload}
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event_payload = posthog_logger.create_posthog_event_payload(kwargs)
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assert event_payload["properties"]["$ai_trace_id"] == "test-trace-123"
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assert (
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event_payload["properties"]["$ai_span_id"] == "test_id"
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) # from standard_payload["id"]
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@pytest.mark.asyncio
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async def test_trace_id_uuid_fallback():
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"""Test that UUID is generated when no trace_id is available"""
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posthog_logger = PostHogLogger()
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standard_payload = create_standard_logging_payload()
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# Remove trace_id to test fallback
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del standard_payload["trace_id"]
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del standard_payload["id"]
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kwargs = {"standard_logging_object": standard_payload}
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event_payload = posthog_logger.create_posthog_event_payload(kwargs)
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# Should have generated UUIDs
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assert len(event_payload["properties"]["$ai_trace_id"]) == 36 # UUID length
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assert len(event_payload["properties"]["$ai_span_id"]) == 36 # UUID length
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assert "-" in event_payload["properties"]["$ai_trace_id"] # UUID format
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@pytest.mark.asyncio
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async def test_distinct_id_fallback_chain():
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"""Test the distinct_id fallback priority chain"""
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posthog_logger = PostHogLogger()
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# Test 1: user_id from metadata (highest priority)
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standard_payload = create_standard_logging_payload()
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kwargs = {
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"standard_logging_object": standard_payload,
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"litellm_params": {"metadata": {"user_id": "metadata-user-123"}},
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}
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distinct_id = posthog_logger._get_distinct_id(standard_payload, kwargs)
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assert distinct_id == "metadata-user-123"
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# Test 2: trace_id from standard_logging_object (second priority)
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kwargs = {"standard_logging_object": standard_payload} # no metadata
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distinct_id = posthog_logger._get_distinct_id(standard_payload, kwargs)
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assert distinct_id == "test_trace_id"
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# Test 3: end_user from standard_logging_object (third priority)
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standard_payload_no_trace = create_standard_logging_payload()
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del standard_payload_no_trace["trace_id"]
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standard_payload_no_trace["end_user"] = "end-user-456"
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distinct_id = posthog_logger._get_distinct_id(standard_payload_no_trace, {})
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assert distinct_id == "end-user-456"
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# Test 4: UUID fallback (lowest priority)
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standard_payload_empty = create_standard_logging_payload()
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del standard_payload_empty["trace_id"]
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del standard_payload_empty["end_user"]
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distinct_id = posthog_logger._get_distinct_id(standard_payload_empty, {})
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assert len(distinct_id) == 36 # UUID length
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assert "-" in distinct_id # UUID format
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@pytest.mark.asyncio
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async def test_missing_standard_logging_object():
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"""Test error handling when standard_logging_object is missing"""
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posthog_logger = PostHogLogger()
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kwargs = {} # Missing standard_logging_object
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with pytest.raises(ValueError, match="standard_logging_object not found in kwargs"):
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posthog_logger.create_posthog_event_payload(kwargs)
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@pytest.mark.asyncio
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async def test_custom_metadata_support():
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"""Test that custom metadata fields are added directly to properties"""
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posthog_logger = PostHogLogger()
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standard_payload = create_standard_logging_payload()
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kwargs = {
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"standard_logging_object": standard_payload,
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"litellm_params": {
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"metadata": {
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"user_id": "user-123", # should be used for distinct_id, not custom property
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"project_name": "test_project", # should appear as project_name
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"environment": "staging", # should appear as environment
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"custom_field": "custom_value", # should appear as custom_field
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}
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},
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}
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event_payload = posthog_logger.create_posthog_event_payload(kwargs)
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# Check that custom fields are added directly
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assert event_payload["properties"]["project_name"] == "test_project"
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assert event_payload["properties"]["environment"] == "staging"
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assert event_payload["properties"]["custom_field"] == "custom_value"
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# Check that user_id is used for distinct_id, not as custom property
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assert event_payload["distinct_id"] == "user-123"
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assert "user_id" not in event_payload["properties"]
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@pytest.mark.asyncio
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async def test_custom_metadata_filters_internal_fields():
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"""Test that LiteLLM internal fields are filtered out from custom metadata"""
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posthog_logger = PostHogLogger()
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standard_payload = create_standard_logging_payload()
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kwargs = {
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"standard_logging_object": standard_payload,
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"litellm_params": {
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"metadata": {
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"custom_field": "should_appear",
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"endpoint": "/chat/completions", # internal field - should be filtered
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"user_api_key_hash": "hash123", # internal field - should be filtered
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"headers": {
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"content-type": "application/json"
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}, # internal field - should be filtered
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"model_info": {"id": "123"}, # internal field - should be filtered
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}
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},
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}
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event_payload = posthog_logger.create_posthog_event_payload(kwargs)
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# Check that custom field appears
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assert event_payload["properties"]["custom_field"] == "should_appear"
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# Check that internal fields are filtered out
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assert "endpoint" not in event_payload["properties"]
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assert "user_api_key_hash" not in event_payload["properties"]
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assert "headers" not in event_payload["properties"]
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assert "model_info" not in event_payload["properties"]
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@pytest.mark.asyncio
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async def test_custom_metadata_with_no_metadata():
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"""Test that logger handles cases with no metadata gracefully"""
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posthog_logger = PostHogLogger()
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standard_payload = create_standard_logging_payload()
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# Test with no litellm_params
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kwargs = {"standard_logging_object": standard_payload}
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event_payload = posthog_logger.create_posthog_event_payload(kwargs)
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# Should not error and should have standard properties
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assert event_payload["event"] == "$ai_generation"
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assert event_payload["properties"]["$ai_model"] == "gpt-5-mini"
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# Test with empty metadata
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kwargs = {
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"standard_logging_object": standard_payload,
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"litellm_params": {"metadata": {}},
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}
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event_payload = posthog_logger.create_posthog_event_payload(kwargs)
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# Should not error and should have standard properties
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assert event_payload["event"] == "$ai_generation"
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assert event_payload["properties"]["$ai_model"] == "gpt-5-mini"
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@pytest.mark.asyncio
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async def test_dynamic_credentials():
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"""Test that per-request credentials override environment variables"""
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from litellm.types.utils import StandardCallbackDynamicParams
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|
|
posthog_logger = PostHogLogger()
|
|
|
|
# Test with no dynamic params - should use env vars
|
|
kwargs = {}
|
|
api_key, api_url = posthog_logger._get_credentials_for_request(kwargs)
|
|
assert api_key == "test_key" # from env var
|
|
assert api_url == "https://app.posthog.com" # from env var
|
|
|
|
# Test with dynamic params - should override env vars
|
|
standard_callback_dynamic_params = StandardCallbackDynamicParams(
|
|
posthog_api_key="dynamic_key", posthog_api_url="https://custom.posthog.com"
|
|
)
|
|
kwargs = {"standard_callback_dynamic_params": standard_callback_dynamic_params}
|
|
api_key, api_url = posthog_logger._get_credentials_for_request(kwargs)
|
|
assert api_key == "dynamic_key"
|
|
assert api_url == "https://custom.posthog.com"
|
|
|
|
# Test partial override - only api_key
|
|
standard_callback_dynamic_params = StandardCallbackDynamicParams(
|
|
posthog_api_key="another_key"
|
|
)
|
|
kwargs = {"standard_callback_dynamic_params": standard_callback_dynamic_params}
|
|
api_key, api_url = posthog_logger._get_credentials_for_request(kwargs)
|
|
assert api_key == "another_key"
|
|
assert api_url == "https://app.posthog.com" # falls back to env var
|
|
|
|
# Test partial override - only api_url
|
|
standard_callback_dynamic_params = StandardCallbackDynamicParams(
|
|
posthog_api_url="https://another.posthog.com"
|
|
)
|
|
kwargs = {"standard_callback_dynamic_params": standard_callback_dynamic_params}
|
|
api_key, api_url = posthog_logger._get_credentials_for_request(kwargs)
|
|
assert api_key == "test_key" # falls back to env var
|
|
assert api_url == "https://another.posthog.com"
|
|
|
|
|
|
def test_async_callback_atexit_handler_exists():
|
|
"""
|
|
Test that atexit handlers are properly registered.
|
|
|
|
This test verifies that both GLOBAL_LOGGING_WORKER and PostHogLogger
|
|
register atexit handlers for flushing pending events.
|
|
|
|
The actual functionality is validated by end-to-end tests (test_async_only.py)
|
|
since unit testing atexit behavior across event loop boundaries is complex.
|
|
"""
|
|
import atexit
|
|
from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER
|
|
|
|
# Verify GLOBAL_LOGGING_WORKER has _flush_on_exit method
|
|
assert hasattr(
|
|
GLOBAL_LOGGING_WORKER, "_flush_on_exit"
|
|
), "GLOBAL_LOGGING_WORKER should have _flush_on_exit method"
|
|
|
|
# Verify PostHogLogger has _flush_on_exit method
|
|
posthog_logger = PostHogLogger()
|
|
assert hasattr(
|
|
posthog_logger, "_flush_on_exit"
|
|
), "PostHogLogger should have _flush_on_exit method"
|
|
|
|
# Verify method can be called without crashing (with empty queue)
|
|
# This tests the early return paths
|
|
GLOBAL_LOGGING_WORKER._flush_on_exit()
|
|
posthog_logger._flush_on_exit()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_posthog_atexit_flushes_internal_queue():
|
|
"""
|
|
Test that PostHog's atexit handler flushes its internal log_queue.
|
|
|
|
This works in conjunction with GLOBAL_LOGGING_WORKER:
|
|
1. GLOBAL_LOGGING_WORKER atexit invokes pending callbacks
|
|
2. Callbacks add events to PostHog's internal log_queue
|
|
3. PostHog's atexit flushes log_queue via HTTP POST
|
|
"""
|
|
from unittest.mock import Mock, patch
|
|
import httpx
|
|
|
|
posthog_logger = PostHogLogger()
|
|
|
|
# Add mock events to internal queue (simulating what callbacks do)
|
|
standard_payload = create_standard_logging_payload()
|
|
kwargs = {"standard_logging_object": standard_payload}
|
|
event_payload = posthog_logger.create_posthog_event_payload(kwargs)
|
|
|
|
posthog_logger.log_queue.append(
|
|
{
|
|
"event": event_payload,
|
|
"api_key": "test_key",
|
|
"api_url": "https://app.posthog.com",
|
|
}
|
|
)
|
|
|
|
assert len(posthog_logger.log_queue) == 1, "Queue should have 1 event"
|
|
|
|
# Mock the sync HTTP client to avoid real API calls
|
|
with patch.object(posthog_logger.sync_client, "post") as mock_post:
|
|
mock_response = Mock()
|
|
mock_response.status_code = 200
|
|
mock_response.raise_for_status = Mock()
|
|
mock_post.return_value = mock_response
|
|
|
|
# Trigger atexit flush
|
|
posthog_logger._flush_on_exit()
|
|
|
|
# Verify HTTP POST was called
|
|
assert mock_post.called, "HTTP POST should be called during flush"
|
|
assert len(posthog_logger.log_queue) == 0, "Queue should be empty after flush"
|
|
|
|
# Verify correct endpoint was called
|
|
call_args = mock_post.call_args
|
|
assert "/batch/" in call_args.kwargs["url"], "Should POST to /batch/ endpoint"
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_safe_dumps_serialization_in_sync_log():
|
|
"""
|
|
Regression test: sync log_success_event should not raise when the payload
|
|
contains objects that are not natively JSON-serializable (e.g. Pydantic
|
|
models like UserAPIKeyAuth).
|
|
|
|
Before the fix httpx's json= kwarg called stdlib json.dumps which would
|
|
raise ``TypeError: Object of type UserAPIKeyAuth is not JSON serializable``.
|
|
After the fix the body is pre-serialized via safe_dumps() and sent with
|
|
content= so non-primitive values are coerced to their str() representation.
|
|
"""
|
|
from unittest.mock import Mock, patch
|
|
from pydantic import BaseModel
|
|
|
|
class FakeNonSerializable(BaseModel):
|
|
"""Stand-in for UserAPIKeyAuth or any Pydantic object in metadata."""
|
|
|
|
token: str = "sk-secret"
|
|
|
|
posthog_logger = PostHogLogger()
|
|
standard_payload = create_standard_logging_payload()
|
|
|
|
kwargs = {
|
|
"standard_logging_object": standard_payload,
|
|
"litellm_params": {
|
|
"metadata": {
|
|
# This custom key would leak a non-serializable object into
|
|
# the PostHog properties dict:
|
|
"custom_auth_obj": FakeNonSerializable(),
|
|
}
|
|
},
|
|
"standard_callback_dynamic_params": None,
|
|
}
|
|
|
|
with patch.object(posthog_logger.sync_client, "post") as mock_post:
|
|
mock_response = Mock()
|
|
mock_response.status_code = 200
|
|
mock_response.raise_for_status = Mock()
|
|
mock_post.return_value = mock_response
|
|
|
|
# Should NOT raise TypeError
|
|
posthog_logger.log_success_event(kwargs, None, 0.0, 0.0)
|
|
|
|
assert mock_post.called, "sync_client.post should have been called"
|
|
call_kwargs = mock_post.call_args.kwargs
|
|
# Must use content= (pre-serialized), NOT json=
|
|
assert "content" in call_kwargs, "Should send pre-serialized body via content="
|
|
assert "json" not in call_kwargs, "Should NOT use json= kwarg"
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_safe_dumps_serialization_in_async_send_batch():
|
|
"""
|
|
Regression test: async_send_batch should not raise when the event payload
|
|
contains non-JSON-serializable objects.
|
|
"""
|
|
from unittest.mock import Mock, AsyncMock, patch
|
|
from pydantic import BaseModel
|
|
|
|
class FakeNonSerializable(BaseModel):
|
|
token: str = "sk-secret"
|
|
|
|
posthog_logger = PostHogLogger()
|
|
standard_payload = create_standard_logging_payload()
|
|
|
|
kwargs = {
|
|
"standard_logging_object": standard_payload,
|
|
"litellm_params": {
|
|
"metadata": {
|
|
"custom_auth_obj": FakeNonSerializable(),
|
|
}
|
|
},
|
|
}
|
|
event_payload = posthog_logger.create_posthog_event_payload(kwargs)
|
|
|
|
posthog_logger.log_queue.append(
|
|
{
|
|
"event": event_payload,
|
|
"api_key": "test_key",
|
|
"api_url": "https://app.posthog.com",
|
|
}
|
|
)
|
|
|
|
with patch.object(posthog_logger.async_client, "post") as mock_post:
|
|
mock_response = Mock()
|
|
mock_response.status_code = 200
|
|
mock_response.raise_for_status = Mock()
|
|
mock_post.return_value = mock_response
|
|
|
|
# Should NOT raise TypeError
|
|
await posthog_logger.async_send_batch()
|
|
|
|
assert mock_post.called, "async_client.post should have been called"
|
|
call_kwargs = mock_post.call_args.kwargs
|
|
assert "content" in call_kwargs, "Should send pre-serialized body via content="
|
|
assert "json" not in call_kwargs, "Should NOT use json= kwarg"
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_safe_dumps_serialization_in_flush_on_exit():
|
|
"""
|
|
Regression test: _flush_on_exit (atexit path) should not raise when the
|
|
event payload contains non-JSON-serializable objects.
|
|
"""
|
|
from unittest.mock import Mock, patch
|
|
from pydantic import BaseModel
|
|
|
|
class FakeNonSerializable(BaseModel):
|
|
token: str = "sk-secret"
|
|
|
|
posthog_logger = PostHogLogger()
|
|
standard_payload = create_standard_logging_payload()
|
|
|
|
kwargs = {
|
|
"standard_logging_object": standard_payload,
|
|
"litellm_params": {
|
|
"metadata": {
|
|
"custom_auth_obj": FakeNonSerializable(),
|
|
}
|
|
},
|
|
}
|
|
event_payload = posthog_logger.create_posthog_event_payload(kwargs)
|
|
|
|
posthog_logger.log_queue.append(
|
|
{
|
|
"event": event_payload,
|
|
"api_key": "test_key",
|
|
"api_url": "https://app.posthog.com",
|
|
}
|
|
)
|
|
|
|
with patch.object(posthog_logger.sync_client, "post") as mock_post:
|
|
mock_response = Mock()
|
|
mock_response.status_code = 200
|
|
mock_response.raise_for_status = Mock()
|
|
mock_post.return_value = mock_response
|
|
|
|
# Should NOT raise TypeError
|
|
posthog_logger._flush_on_exit()
|
|
|
|
assert mock_post.called, "sync_client.post should have been called"
|
|
call_kwargs = mock_post.call_args.kwargs
|
|
assert "content" in call_kwargs, "Should send pre-serialized body via content="
|
|
assert "json" not in call_kwargs, "Should NOT use json= kwarg"
|
|
assert len(posthog_logger.log_queue) == 0, "Queue should be empty after flush"
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_sync_callback_not_affected_by_atexit():
|
|
"""
|
|
Regression test: ensure sync completions still work immediately.
|
|
|
|
Sync callbacks should be invoked immediately during completion(),
|
|
not deferred to atexit. This test verifies atexit handlers don't
|
|
interfere with the sync path.
|
|
"""
|
|
from unittest.mock import Mock, patch
|
|
|
|
# Track when callback is invoked
|
|
callback_invoked_immediately = False
|
|
|
|
def mock_log_success(self, kwargs, response_obj, start_time, end_time):
|
|
nonlocal callback_invoked_immediately
|
|
callback_invoked_immediately = True
|
|
|
|
with patch.object(PostHogLogger, "log_success_event", mock_log_success):
|
|
with patch("httpx.Client.post") as mock_post:
|
|
mock_response = Mock()
|
|
mock_response.status_code = 200
|
|
mock_response.raise_for_status = Mock()
|
|
mock_post.return_value = mock_response
|
|
|
|
posthog_logger = PostHogLogger()
|
|
standard_payload = create_standard_logging_payload()
|
|
kwargs = {"standard_logging_object": standard_payload}
|
|
|
|
# Call sync method directly (simulates what completion() does)
|
|
posthog_logger.log_success_event(kwargs, None, 0.0, 0.0)
|
|
|
|
# Callback should be invoked immediately, not queued for atexit
|
|
assert (
|
|
callback_invoked_immediately
|
|
), "Sync callback should be invoked immediately"
|