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litellm/tests/unit/llms/azure/test_azure_exception_mapping.py
yuneng-jiang 5e6dc89ba1
test: move tests/test_litellm/llms into tests/unit/llms (#43191) 
* ci: run the unit_selection.sh shard files on every event instead of only fork pull requests

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* ci: rename fork-flag to unit-flag now that it applies on every event

* test: move tests/test_litellm root and small trees into tests/unit

Pure renames, no content changes. Follow-up commits in this PR fix
references, merge the three files that already existed in tests/unit,
keep live-provider tests in tests/test_litellm and wire CI.

* test: carry tests/test_litellm conftest isolation into tests/unit

Callback lists, routing fallbacks, cached HTTP clients, logger state, AWS,
proxy-URL and keychain env, and session-end client cleanup now reset for
unit tests too. The environment isolation owns its MonkeyPatch so a test's
own monkeypatch is undone before the model-cost teardown runs.

* test: merge, split and prune the moved root and small-tree tests

Merge batches/test_batch_utils.py and the chat_completions and messages
dispatch tests into the files that already existed in tests/unit. Keep
the live Gemini interactions tests, the async image-fetch format test and
the OpenAI embedding scorer test in tests/test_litellm since they need
real network or keys. Put test_router.py under tests/unit/test_router so
the existing package no longer shadows it. Delete eight tests the audit
found superseded by stronger ones kept in this move.

* ci: run the moved root and small-tree tests under their legacy flags

Add the misc and responses-caching-types flags to unit_selection.sh and
CircleCI, extend enterprise-routing and mcp-integration, and point the
legacy GHA shards, Makefile, redis-compat workflow, merge smoke manifest
and change classifier at the new paths.

* test: make the new tests/unit directories packages

tests/unit/test_package_layout.py requires every directory to carry an
__init__.py, and without one the moved and retained
test_litellm_responses_bridge.py modules collide on import.

* test: scope the unit socket block to tests/unit in shared sessions

The GHA shards collect the legacy test-path and the unit selection in one
pytest session. The unit conftest's loopback-only block leaked into legacy
modules that reach the network at import. The legacy conftest now lifts the
restriction at collect and setup time, and the unit conftest re-applies it
when collecting its own modules.

* test: move tests/test_litellm/llms into tests/unit/llms

Rename-only. Moves the provider tests and the fine-tuning fixtures they
load, mirroring the old paths. Follow-up commits merge, split and wire them.

* test: merge, split and prune the moved llms tests

Merges the Databricks chat transformation tests into the existing unit
file, keeps the tests that need real keys or the network in
tests/test_litellm, deletes the audited tests a stronger unit test
already covers, and points imports at tests.unit.llms.

* ci: run the moved llms tests under their legacy flags

The Vertex AI and All Other Providers shards keep their legacy test-path
for the retained files and add the llm-vertex-ai and llm-other-providers
unit selections. CircleCI gets matching unit jobs.

* test: make the tests/unit/llms directories packages

Adds __init__.py to the moved dirs and drops the legacy ones whose
directories no longer hold tests.

* test: drop script runners and path hacks the llms split left dangling

The __main__ runners in the split openai_like files and the Databricks e2e
runner called tests that now live in the other half of the split or were
deleted. The retained legacy halves also no longer need sys.path edits.

* test: give the shard-script tests their own GITHUB_OUTPUT

They only passed where the runner set it. The CircleCI unit job's env
allowlist drops it, so the script's redirect failed there.

* test: point the router and module-deletion checks at tests/unit

router_code_coverage and code_qa_check_tests only searched tests/test_litellm,
so the moved router tests no longer counted. The two silent-experiment tests
the audit deleted were the only direct callers of those methods; they are
replaced with tests that assert the forwarded shadow request and the
recursion guard.

* test: keep the Databricks manual e2e runner and fix the SageMaker Nova run path

The Databricks e2e file is a manual script whose main() calls the tests
that were pruned, so pruning them broke the documented run. It is back to
its main version. The SageMaker Nova docstring now points at the file's
real location in tests/local_testing.

* test: keep the job's UNIT_FLAG out of the shard-script tests

---------

Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-09-25 12:43:23 -07:00

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import json
from unittest.mock import MagicMock, patch
import pytest
import litellm
from litellm.exceptions import ContentPolicyViolationError
from litellm.litellm_core_utils.exception_mapping_utils import exception_type
class TestAzureExceptionMapping:
"""Test Azure OpenAI exception mapping with provider-specific fields"""
def test_azure_content_policy_violation_innererror_access(self):
"""Test that Azure content policy violation exceptions provide access to innererror details"""
# Create a mock Azure OpenAI exception with body containing innererror
mock_exception = Exception(
"The response was filtered due to the prompt triggering Azure OpenAI's content management policy"
)
mock_exception.body = {
"innererror": {
"code": "ResponsibleAIPolicyViolation",
"content_filter_result": {
"hate": {"filtered": True, "severity": "high"},
"jailbreak": {"filtered": False, "detected": False},
"self_harm": {"filtered": False, "severity": "safe"},
"sexual": {"filtered": False, "severity": "safe"},
"violence": {"filtered": True, "severity": "medium"},
},
}
}
mock_response = MagicMock()
mock_response.status_code = 400
mock_exception.response = mock_response
# Test the exception mapping directly
with pytest.raises(ContentPolicyViolationError) as exc_info:
exception_type(
model="azure/gpt-4",
original_exception=mock_exception,
custom_llm_provider="azure",
)
# Access the exception and verify provider_specific_fields
e = exc_info.value
assert e.provider_specific_fields is not None
assert "innererror" in e.provider_specific_fields
innererror = e.provider_specific_fields["innererror"]
assert innererror["code"] == "ResponsibleAIPolicyViolation"
assert "content_filter_result" in innererror
content_filter_result = innererror["content_filter_result"]
assert content_filter_result["hate"]["filtered"] is True
assert content_filter_result["hate"]["severity"] == "high"
assert content_filter_result["violence"]["filtered"] is True
assert content_filter_result["violence"]["severity"] == "medium"
assert content_filter_result["sexual"]["filtered"] is False
assert content_filter_result["self_harm"]["filtered"] is False
assert content_filter_result["jailbreak"]["filtered"] is False
def test_azure_content_policy_violation_different_categories(self):
"""Test Azure content policy violation with different filtering categories"""
# Mock exception with different content filter results
mock_exception = Exception(
"The response was filtered due to the prompt triggering Azure OpenAI's content management policy"
)
mock_exception.body = {
"innererror": {
"code": "ResponsibleAIPolicyViolation",
"content_filter_result": {
"hate": {"filtered": False, "severity": "safe"},
"jailbreak": {"filtered": True, "detected": True},
"self_harm": {"filtered": True, "severity": "high"},
"sexual": {"filtered": True, "severity": "medium"},
"violence": {"filtered": False, "severity": "safe"},
},
}
}
mock_response = MagicMock()
mock_response.status_code = 400
mock_exception.response = mock_response
# Test the exception mapping directly with different violation type
with pytest.raises(ContentPolicyViolationError) as exc_info:
exception_type(
model="azure/gpt-4",
original_exception=mock_exception,
custom_llm_provider="azure",
)
# Verify provider_specific_fields contains the expected innererror structure
e = exc_info.value
assert e.provider_specific_fields is not None
print("got provider_specific_fields=", e.provider_specific_fields)
innererror = e.provider_specific_fields["innererror"]
content_filter_result = innererror["content_filter_result"]
# Check different filter categories
assert content_filter_result["sexual"]["filtered"] is True
assert content_filter_result["sexual"]["severity"] == "medium"
assert content_filter_result["self_harm"]["filtered"] is True
assert content_filter_result["self_harm"]["severity"] == "high"
assert content_filter_result["jailbreak"]["filtered"] is True
assert content_filter_result["jailbreak"]["detected"] is True
assert content_filter_result["hate"]["filtered"] is False
assert content_filter_result["violence"]["filtered"] is False
def test_azure_content_policy_violation_missing_innererror(self):
"""Test Azure content policy violation when innererror is missing from response"""
# Mock exception without body attribute
mock_exception = Exception(
"The response was filtered due to the prompt triggering Azure OpenAI's content management policy"
)
mock_response = MagicMock()
mock_response.status_code = 400
mock_exception.response = mock_response
# Note: no mock_exception.body attribute set
# Test the exception mapping directly
with pytest.raises(ContentPolicyViolationError) as exc_info:
exception_type(
model="azure/gpt-4",
original_exception=mock_exception,
custom_llm_provider="azure",
)
# Verify that even without innererror, the exception is still raised properly
e = exc_info.value
print("got exception=", e)
# provider_specific_fields should still exist but innererror should be None
assert e.provider_specific_fields is not None
assert e.provider_specific_fields.get("innererror") is None
def test_azure_content_policy_violation_non_dict_body(self):
"""Test Azure content policy violation when body is not a dictionary"""
# Mock exception with non-dict body
mock_exception = Exception(
"The response was filtered due to the prompt triggering Azure OpenAI's content management policy"
)
mock_exception.body = "invalid body format"
mock_response = MagicMock()
mock_response.status_code = 400
mock_exception.response = mock_response
# Test the exception mapping directly
with pytest.raises(ContentPolicyViolationError) as exc_info:
exception_type(
model="azure/gpt-4",
original_exception=mock_exception,
custom_llm_provider="azure",
)
# Verify that with invalid body format, innererror should be None
e = exc_info.value
print("got exception=", e)
print("exception fields=", vars(e))
assert e.provider_specific_fields is not None
assert e.provider_specific_fields.get("innererror") is None
def test_azure_images_content_policy_violation_preserves_nested_inner_error(self):
"""Azure Images endpoints return errors nested under body['error'] with inner_error.
Ensure we:
- Detect the violation via structured payload (code=content_policy_violation)
- Preserve code/type/message
- Surface inner_error + revised_prompt + content_filter_results
"""
mock_exception = Exception("Bad request") # does not include policy substrings
mock_exception.body = {
"error": {
"code": "content_policy_violation",
"inner_error": {
"code": "ResponsibleAIPolicyViolation",
"content_filter_results": {
"violence": {"filtered": True, "severity": "low"}
},
"revised_prompt": "revised",
},
"message": "Your request was rejected as a result of our safety system.",
"type": "invalid_request_error",
}
}
mock_response = MagicMock()
mock_response.status_code = 400
mock_exception.response = mock_response
with pytest.raises(ContentPolicyViolationError) as exc_info:
exception_type(
model="azure/dall-e-3",
original_exception=mock_exception,
custom_llm_provider="azure",
)
e = exc_info.value
# OpenAI-style error fields should be populated
assert getattr(e, "code", None) == "content_policy_violation"
assert getattr(e, "type", None) == "invalid_request_error"
assert "safety system" in str(e)
# Provider-specific nested details must be preserved
assert e.provider_specific_fields is not None
assert (
e.provider_specific_fields["inner_error"]["code"]
== "ResponsibleAIPolicyViolation"
)
assert e.provider_specific_fields["inner_error"]["revised_prompt"] == "revised"
assert (
e.provider_specific_fields["inner_error"]["content_filter_results"][
"violence"
]["filtered"]
is True
)
def test_azure_content_policy_violation_detected_via_inner_error_code(self):
"""Regression test for #20811: Azure returns inner_error with
ResponsibleAIPolicyViolation but the top-level error message is
generic. Previously this fell through to the generic
BadRequestError handler and all error details were lost."""
mock_exception = Exception("Bad request")
# This body structure mirrors what Azure OpenAI Images API returns
# for DALL-E 3 content policy violations (issue #20811).
mock_exception.body = {
"error": {
"code": "content_policy_violation",
"inner_error": {
"code": "ResponsibleAIPolicyViolation",
"content_filter_results": {
"hate": {"filtered": False, "severity": "safe"},
"profanity": {"detected": False, "filtered": False},
"self_harm": {"filtered": False, "severity": "safe"},
"sexual": {"filtered": False, "severity": "safe"},
"violence": {"filtered": True, "severity": "low"},
},
"revised_prompt": (
"A dark and intense illustration of a man "
"in a dramatic action scene."
),
},
"message": (
"Your request was rejected as a result of our safety system."
),
"type": "invalid_request_error",
}
}
mock_response = MagicMock()
mock_response.status_code = 400
mock_exception.response = mock_response
with pytest.raises(ContentPolicyViolationError) as exc_info:
exception_type(
model="azure/dall-e-3",
original_exception=mock_exception,
custom_llm_provider="azure",
)
e = exc_info.value
# Must surface as ContentPolicyViolationError, not generic BadRequestError
assert "safety system" in str(e)
assert e.provider_specific_fields is not None
inner = e.provider_specific_fields["inner_error"]
assert inner["code"] == "ResponsibleAIPolicyViolation"
assert inner["content_filter_results"]["violence"]["filtered"] is True
assert inner["revised_prompt"] is not None
def test_azure_policy_violation_detected_via_inner_error_without_top_code(self):
"""When the top-level code is NOT 'content_policy_violation' but
inner_error.code IS 'ResponsibleAIPolicyViolation', the error
should still be recognized as a content policy violation."""
mock_exception = Exception("Some error")
mock_exception.body = {
"error": {
"code": "BadRequest",
"inner_error": {
"code": "ResponsibleAIPolicyViolation",
"content_filter_results": {
"violence": {"filtered": True, "severity": "medium"},
},
},
"message": "The request was rejected.",
"type": "invalid_request_error",
}
}
mock_response = MagicMock()
mock_response.status_code = 400
mock_exception.response = mock_response
with pytest.raises(ContentPolicyViolationError) as exc_info:
exception_type(
model="azure/dall-e-3",
original_exception=mock_exception,
custom_llm_provider="azure",
)
e = exc_info.value
assert e.provider_specific_fields is not None
assert (
e.provider_specific_fields["inner_error"]["code"]
== "ResponsibleAIPolicyViolation"
)
def test_azure_image_polling_error_preserves_body(self):
"""Verify that AzureOpenAIError raised from the DALL-E polling path
carries the structured body so exception_type() can inspect it."""
from litellm.llms.azure.common_utils import AzureOpenAIError
error_payload = {
"status": "failed",
"error": {
"code": "content_policy_violation",
"message": "Your request was rejected.",
"inner_error": {
"code": "ResponsibleAIPolicyViolation",
"content_filter_results": {
"violence": {"filtered": True, "severity": "low"},
},
},
},
}
# Simulate what the fixed polling path now does
_error_body = error_payload.get("error", error_payload)
_error_msg = (
_error_body.get("message", "Image generation failed")
if isinstance(_error_body, dict)
else json.dumps(error_payload)
)
exc = AzureOpenAIError(
status_code=400,
message=_error_msg,
body=error_payload,
)
assert exc.body is not None
assert isinstance(exc.body, dict)
assert exc.body["error"]["code"] == "content_policy_violation"
assert "Your request was rejected" in exc.message
def test_azure_safety_system_message_detected_as_policy_violation(self):
"""Azure's rejection message 'Your request was rejected as a result
of our safety system' should be detected by string matching even
when the structured body is unavailable."""
mock_exception = Exception(
"Your request was rejected as a result of our safety system. "
"The revised prompt may contain text that is not allowed."
)
mock_response = MagicMock()
mock_response.status_code = 400
mock_exception.response = mock_response
with pytest.raises(ContentPolicyViolationError):
exception_type(
model="azure/dall-e-3",
original_exception=mock_exception,
custom_llm_provider="azure",
)
def test_invalid_encrypted_content_error_with_helpful_message(self):
"""Test that invalid_encrypted_content errors include helpful guidance
about enabling encrypted_content_affinity."""
from litellm.exceptions import BadRequestError
mock_exception = Exception(
"The encrypted content gAAAAABpnW_yEYmSNEyOG... could not be verified. "
"Reason: Encrypted content organization_id did not match the target organization."
)
mock_exception.body = {
"error": {
"message": "The encrypted content could not be verified.",
"type": "invalid_request_error",
"code": "invalid_encrypted_content",
}
}
mock_response = MagicMock()
mock_response.status_code = 400
mock_exception.response = mock_response
with pytest.raises(BadRequestError) as exc_info:
exception_type(
model="azure/gpt-5.1-codex",
original_exception=mock_exception,
custom_llm_provider="azure",
)
error = exc_info.value
assert "encrypted_content_affinity" in error.message
assert "enable_pre_call_checks" in error.message
assert "optional_pre_call_checks" in error.message
assert "docs.litellm.ai" in error.message
def test_openai_invalid_encrypted_content_error(self):
"""Test that OpenAI invalid_encrypted_content errors also get helpful guidance."""
from litellm.exceptions import BadRequestError
mock_exception = Exception("The encrypted content could not be verified.")
mock_response = MagicMock()
mock_response.status_code = 400
mock_exception.response = mock_response
with pytest.raises(BadRequestError) as exc_info:
exception_type(
model="gpt-5.1-codex",
original_exception=mock_exception,
custom_llm_provider="openai",
)
error = exc_info.value
assert "encrypted_content_affinity" in error.message
assert "enable_pre_call_checks" in error.message
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