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fix(proxy): log alias model mismatch at debug, not warning #21749

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fix(proxy): log alias model mismatch at debug, not warning #21749

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4b3cb5e
fix(proxy): log alias model mismatch at debug, not warning
Elliot0122 Feb 21, 2026
902ddf7
fix(proxy): apply upstream_model alias check to dict response branch
Elliot0122 Feb 21, 2026
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50 changes: 36 additions & 14 deletions litellm/proxy/common_request_processing.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -249,6 +249,7 @@ def _override_openai_response_model(
response_obj: Any,
requested_model: str,
log_context: str,
upstream_model: Optional[str] = None,
) -> None:
"""
Force the OpenAI-compatible `model` field in the response to match what the client requested.
Expand Down Expand Up @@ -289,12 +290,21 @@ def _override_openai_response_model(
if isinstance(response_obj, dict):
downstream_model = response_obj.get("model")
if downstream_model != requested_model:
verbose_proxy_logger.debug(
"%s: response model mismatch - requested=%r downstream=%r. Overriding response['model'] to requested model.",
log_context,
requested_model,
downstream_model,
)
if upstream_model and downstream_model == upstream_model:
verbose_proxy_logger.debug(
"%s: response model is known alias - requested=%r upstream=%r downstream=%r. Overriding response['model'].",
log_context,
requested_model,
upstream_model,
downstream_model,
)
else:
verbose_proxy_logger.warning(
"%s: response model mismatch - requested=%r downstream=%r. Overriding response['model'] to requested model.",
log_context,
requested_model,
downstream_model,
)
response_obj["model"] = requested_model
return

Expand All @@ -308,12 +318,21 @@ def _override_openai_response_model(

downstream_model = getattr(response_obj, "model", None)
if downstream_model != requested_model:
verbose_proxy_logger.debug(
"%s: response model mismatch - requested=%r downstream=%r. Overriding response.model to requested model.",
log_context,
requested_model,
downstream_model,
)
if upstream_model and downstream_model == upstream_model:
verbose_proxy_logger.debug(
"%s: response model is known alias - requested=%r upstream=%r downstream=%r. Overriding response.model.",
log_context,
requested_model,
upstream_model,
downstream_model,
)
else:
verbose_proxy_logger.warning(
"%s: response model mismatch - requested=%r downstream=%r. Overriding response.model to requested model.",
log_context,
requested_model,
downstream_model,
)
Comment on lines +329 to +335
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@greptile-apps greptile-apps bot Feb 21, 2026

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Re-introduces WARNING that was intentionally removed

PR #20994 (commit a2e9e73b6) deliberately changed all model-mismatch logs from WARNING to DEBUG because high-traffic customers using model aliases were generating millions of warnings per day, flooding logs and causing disk space issues.

This PR re-introduces WARNING for the non-alias mismatch case (when upstream_model is None or doesn't match downstream_model). However, many legitimate scenarios produce this mismatch without an upstream_model being available — e.g., the streaming path in proxy_server.py:5059 doesn't pass upstream_model at all.

Consider whether the WARNING reintroduction here is intentional, given the history of #20994. If it is, the streaming path in proxy_server.py should also be updated for consistency.


try:
setattr(response_obj, "model", requested_model)
Expand Down Expand Up @@ -978,10 +997,12 @@ async def base_process_llm_request(
# Always return the client-requested model name (not provider-prefixed internal identifiers)
# for OpenAI-compatible responses.
if requested_model_from_client:
_upstream_model = getattr(logging_obj, "model", None)
_override_openai_response_model(
response_obj=response,
requested_model=requested_model_from_client,
log_context=f"litellm_call_id={logging_obj.litellm_call_id}",
upstream_model=_upstream_model,
)

hidden_params = (
Expand Down Expand Up @@ -1198,11 +1219,12 @@ async def _handle_llm_api_exception(
elif isinstance(e, httpx.HTTPStatusError):
# Handle httpx.HTTPStatusError - extract actual error from response
# This matches the original behavior before the refactor in commit 511d435f6f
error_body = await e.response.aread()
http_status_error: httpx.HTTPStatusError = e
error_body = await http_status_error.response.aread()
error_text = error_body.decode("utf-8")

raise HTTPException(
status_code=e.response.status_code,
status_code=http_status_error.response.status_code,
detail={"error": error_text},
)
error_msg = f"{str(e)}"
Expand Down
202 changes: 198 additions & 4 deletions tests/test_litellm/proxy/test_common_request_processing.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1229,7 +1229,7 @@ def test_override_model_no_requested_model(self):
without modifying the response.
"""
fallback_model = "gpt-3.5-turbo"

# Create a mock object response
response_obj = MagicMock()
response_obj.model = fallback_model
Expand All @@ -1238,14 +1238,14 @@ def test_override_model_no_requested_model(self):
"x-litellm-attempted-fallbacks": 1
}
}

# Call the function with None requested_model
_override_openai_response_model(
response_obj=response_obj,
requested_model=None,
log_context="test_context",
)

# Verify the model was not changed
assert response_obj.model == fallback_model

Expand All @@ -1255,8 +1255,202 @@ def test_override_model_no_requested_model(self):
requested_model="",
log_context="test_context",
)

# Verify the model was not changed
assert response_obj.model == fallback_model

def test_override_model_known_alias_logs_debug_not_warning(self):
"""
When downstream_model matches upstream_model (a known alias/internal name),
the function should log at DEBUG level — not WARNING — and still override
response.model to the client-requested model.
"""
from unittest.mock import patch

requested_model = "my-alias"
upstream_model = "hosted_vllm/meta-llama/Llama-3-8b"

response_obj = MagicMock()
response_obj.model = upstream_model # downstream == upstream (known alias)
response_obj._hidden_params = {}

with patch(
"litellm.proxy.common_request_processing.verbose_proxy_logger"
) as mock_logger:
_override_openai_response_model(
response_obj=response_obj,
requested_model=requested_model,
log_context="test_context",
upstream_model=upstream_model,
)

# Model must still be overridden to the client-requested value
assert response_obj.model == requested_model

# debug() should have been called (alias path)
mock_logger.debug.assert_called()
# warning() must NOT have been called — this is a known alias, not a real mismatch
mock_logger.warning.assert_not_called()

def test_override_model_unknown_mismatch_logs_warning(self):
"""
When downstream_model differs from both requested_model and upstream_model,
the function should log at WARNING level to surface unexpected mismatches.
"""
from unittest.mock import patch

requested_model = "my-alias"
upstream_model = "hosted_vllm/meta-llama/Llama-3-8b"
downstream_model = "some-other-model" # Unexpected — matches neither

response_obj = MagicMock()
response_obj.model = downstream_model
response_obj._hidden_params = {}

with patch(
"litellm.proxy.common_request_processing.verbose_proxy_logger"
) as mock_logger:
_override_openai_response_model(
response_obj=response_obj,
requested_model=requested_model,
log_context="test_context",
upstream_model=upstream_model,
)

assert response_obj.model == requested_model

mock_logger.warning.assert_called()
mock_logger.debug.assert_not_called()

def test_override_model_no_upstream_model_logs_warning(self):
"""
When upstream_model is not provided (None) and downstream_model differs
from requested_model, the function should log at WARNING level.
"""
from unittest.mock import patch

requested_model = "gpt-4"
downstream_model = "gpt-3.5-turbo"

response_obj = MagicMock()
response_obj.model = downstream_model
response_obj._hidden_params = {}

with patch(
"litellm.proxy.common_request_processing.verbose_proxy_logger"
) as mock_logger:
_override_openai_response_model(
response_obj=response_obj,
requested_model=requested_model,
log_context="test_context",
# upstream_model omitted (defaults to None)
)

assert response_obj.model == requested_model

mock_logger.warning.assert_called()
mock_logger.debug.assert_not_called()

def test_override_model_no_mismatch_no_logging(self):
"""
When downstream_model already equals requested_model, no mismatch logging
should occur at all (neither debug nor warning).
"""
from unittest.mock import patch

requested_model = "gpt-4"

response_obj = MagicMock()
response_obj.model = requested_model # Already correct
response_obj._hidden_params = {}

with patch(
"litellm.proxy.common_request_processing.verbose_proxy_logger"
) as mock_logger:
_override_openai_response_model(
response_obj=response_obj,
requested_model=requested_model,
log_context="test_context",
upstream_model="hosted_vllm/gpt-4",
)

assert response_obj.model == requested_model
mock_logger.warning.assert_not_called()
mock_logger.debug.assert_not_called()

def test_override_model_dict_known_alias_logs_debug_not_warning(self):
"""
Dict branch: when downstream_model matches upstream_model (a known alias),
the function should log at DEBUG — not WARNING — and override response["model"].
"""
from unittest.mock import patch

requested_model = "my-alias"
upstream_model = "hosted_vllm/meta-llama/Llama-3-8b"
response_obj = {"model": upstream_model, "choices": []}

with patch(
"litellm.proxy.common_request_processing.verbose_proxy_logger"
) as mock_logger:
_override_openai_response_model(
response_obj=response_obj,
requested_model=requested_model,
log_context="test_context",
upstream_model=upstream_model,
)

assert response_obj["model"] == requested_model
mock_logger.debug.assert_called()
mock_logger.warning.assert_not_called()

def test_override_model_dict_unknown_mismatch_logs_warning(self):
"""
Dict branch: when downstream_model differs from both requested_model and
upstream_model, the function should log at WARNING level.
"""
from unittest.mock import patch

requested_model = "my-alias"
upstream_model = "hosted_vllm/meta-llama/Llama-3-8b"
downstream_model = "some-other-model"
response_obj = {"model": downstream_model, "choices": []}

with patch(
"litellm.proxy.common_request_processing.verbose_proxy_logger"
) as mock_logger:
_override_openai_response_model(
response_obj=response_obj,
requested_model=requested_model,
log_context="test_context",
upstream_model=upstream_model,
)

assert response_obj["model"] == requested_model
mock_logger.warning.assert_called()
mock_logger.debug.assert_not_called()

def test_override_model_dict_no_upstream_model_logs_warning(self):
"""
Dict branch: when upstream_model is not provided (None) and downstream_model
differs from requested_model, the function should log at WARNING level.
"""
from unittest.mock import patch

requested_model = "gpt-4"
downstream_model = "gpt-3.5-turbo"
response_obj = {"model": downstream_model, "choices": []}

with patch(
"litellm.proxy.common_request_processing.verbose_proxy_logger"
) as mock_logger:
_override_openai_response_model(
response_obj=response_obj,
requested_model=requested_model,
log_context="test_context",
)

assert response_obj["model"] == requested_model
mock_logger.warning.assert_called()
mock_logger.debug.assert_not_called()


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