mirror of
https://github.com/BerriAI/litellm.git
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7e8d0d3130
* fix: rebuild models_by_provider in add_known_models so cost map reloads reach wildcard expansion * fix: refresh models_by_provider in place so captured references survive reloads
737 lines
24 KiB
Python
737 lines
24 KiB
Python
from unittest.mock import AsyncMock, patch
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import pytest
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from litellm.proxy._types import LiteLLM_TeamTable, LiteLLM_UserTable, Member
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from litellm.proxy.auth.handle_jwt import JWTAuthManager
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def test_get_team_models_for_all_models_and_team_only_models():
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from litellm.proxy.auth.model_checks import get_team_models
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team_models = ["all-proxy-models", "team-only-model", "team-only-model-2"]
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proxy_model_list = ["model1", "model2", "model3"]
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model_access_groups = {}
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include_model_access_groups = False
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result = get_team_models(
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team_models, proxy_model_list, model_access_groups, include_model_access_groups
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)
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combined_models = team_models + proxy_model_list
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assert set(result) == set(combined_models)
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def test_get_team_models_all_proxy_models_includes_access_groups():
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"""
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When a team has 'all-proxy-models' and include_model_access_groups=True,
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the result should include model access group names (e.g. 'claude-model-group')
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in addition to individual model names.
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"""
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from litellm.proxy.auth.model_checks import get_team_models
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team_models = ["all-proxy-models"]
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proxy_model_list = ["model1", "model2"]
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model_access_groups = {
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"group-a": ["model1"],
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"group-b": ["model2"],
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}
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result = get_team_models(
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team_models,
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proxy_model_list,
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model_access_groups,
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include_model_access_groups=True,
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)
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assert "group-a" in result
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assert "group-b" in result
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assert "model1" in result
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assert "model2" in result
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assert len(result) == len(set(result)), "result should have no duplicates"
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def test_get_team_models_all_proxy_models_without_include_flag():
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"""
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When include_model_access_groups=False, access group names should NOT
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appear in the result even with 'all-proxy-models'.
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"""
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from litellm.proxy.auth.model_checks import get_team_models
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team_models = ["all-proxy-models"]
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proxy_model_list = ["model1", "model2"]
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model_access_groups = {
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"group-a": ["model1"],
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"group-b": ["model2"],
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}
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result = get_team_models(
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team_models,
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proxy_model_list,
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model_access_groups,
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include_model_access_groups=False,
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)
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assert "group-a" not in result
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assert "group-b" not in result
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assert "model1" in result
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assert "model2" in result
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def test_get_key_models_all_proxy_models_includes_access_groups():
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"""
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When a key has 'all-proxy-models' and include_model_access_groups=True,
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the result should include model access group names.
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"""
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from litellm.proxy._types import UserAPIKeyAuth
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from litellm.proxy.auth.model_checks import get_key_models
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user_api_key_dict = UserAPIKeyAuth(
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models=["all-proxy-models"],
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api_key="test-key",
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)
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proxy_model_list = ["model1", "model2"]
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model_access_groups = {
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"group-a": ["model1"],
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}
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result = get_key_models(
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user_api_key_dict=user_api_key_dict,
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proxy_model_list=proxy_model_list,
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model_access_groups=model_access_groups,
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include_model_access_groups=True,
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)
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assert "group-a" in result
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assert "model1" in result
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assert "model2" in result
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assert len(result) == len(set(result)), "result should have no duplicates"
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def test_get_key_models_passes_include_model_access_groups():
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"""
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When a key explicitly has an access group name in its models list and
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include_model_access_groups=True, the group name should be retained
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(not stripped by _get_models_from_access_groups).
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"""
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from litellm.proxy._types import UserAPIKeyAuth
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from litellm.proxy.auth.model_checks import get_key_models
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user_api_key_dict = UserAPIKeyAuth(
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models=["group-a"],
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api_key="test-key",
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)
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proxy_model_list = ["model1", "model2"]
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model_access_groups = {
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"group-a": ["model1", "model2"],
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}
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result = get_key_models(
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user_api_key_dict=user_api_key_dict,
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proxy_model_list=proxy_model_list,
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model_access_groups=model_access_groups,
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include_model_access_groups=True,
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)
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assert "group-a" in result
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assert "model1" in result
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assert "model2" in result
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def test_get_key_models_does_not_mutate_input():
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"""
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get_key_models must not mutate user_api_key_dict.models in-place.
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_get_models_from_access_groups uses .pop()/.extend() which would corrupt
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cached UserAPIKeyAuth objects if all_models were an alias instead of a copy.
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"""
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from litellm.proxy._types import UserAPIKeyAuth
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from litellm.proxy.auth.model_checks import get_key_models
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original_models = ["group-a", "extra-model"]
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user_api_key_dict = UserAPIKeyAuth(
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models=list(original_models), # give it a list
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api_key="test-key",
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)
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model_access_groups = {
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"group-a": ["model1", "model2"],
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}
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_ = get_key_models(
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user_api_key_dict=user_api_key_dict,
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proxy_model_list=["model1", "model2"],
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model_access_groups=model_access_groups,
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include_model_access_groups=False,
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)
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# The original models list on the auth object must be unchanged
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assert user_api_key_dict.models == original_models
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@pytest.mark.parametrize(
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"key_models,team_models,proxy_model_list,model_list,expected",
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[
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(
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[
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"anthropic/claude-3-haiku-20240307",
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"anthropic/claude-3-5-haiku-20241022",
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],
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[],
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[],
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[{"model_name": "anthropic/*", "litellm_params": {"model": "anthropic/*"}}],
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[
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"anthropic/claude-3-haiku-20240307",
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"anthropic/claude-3-5-haiku-20241022",
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],
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),
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(
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[],
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[
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"anthropic/claude-3-haiku-20240307",
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"anthropic/claude-3-5-haiku-20241022",
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],
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[],
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[{"model_name": "anthropic/*", "litellm_params": {"model": "anthropic/*"}}],
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[
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"anthropic/claude-3-haiku-20240307",
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"anthropic/claude-3-5-haiku-20241022",
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],
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),
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(
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[],
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[],
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[
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"anthropic/claude-3-haiku-20240307",
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"anthropic/claude-3-5-haiku-20241022",
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],
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[{"model_name": "anthropic/*", "litellm_params": {"model": "anthropic/*"}}],
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[
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"anthropic/claude-3-haiku-20240307",
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"anthropic/claude-3-5-haiku-20241022",
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],
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),
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],
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)
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def test_get_complete_model_list_order(
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key_models, team_models, proxy_model_list, model_list, expected
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):
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"""
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Test that get_complete_model_list preserves order
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"""
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from litellm.proxy.auth.model_checks import get_complete_model_list
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from litellm import Router
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assert (
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get_complete_model_list(
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proxy_model_list=proxy_model_list,
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key_models=key_models,
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team_models=team_models,
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user_model=None,
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infer_model_from_keys=False,
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llm_router=Router(model_list=model_list),
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)
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== expected
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)
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def test_get_complete_model_list_byok_wildcard_expansion():
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"""
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Test that wildcard models (e.g., openai/*) are expanded when the router has
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no deployment for them - BYOK case where team has openai/* but proxy has
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no openai config.
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"""
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from litellm.proxy.auth.model_checks import get_complete_model_list
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from litellm import Router
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# Router with empty model_list - no openai/* deployment (BYOK scenario)
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result = get_complete_model_list(
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key_models=[],
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team_models=["openai/*"],
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proxy_model_list=[],
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user_model=None,
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infer_model_from_keys=False,
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llm_router=Router(model_list=[]),
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)
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# Should expand openai/* to actual OpenAI models
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assert len(result) > 0
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assert all(m.startswith("openai/") for m in result)
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assert "openai/*" not in result
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def test_get_complete_model_list_expands_team_scoped_wildcard_with_stored_credential(
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monkeypatch,
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):
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"""
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Team-scoped BYOK wildcard deployments are stored under an internal model_name,
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with the public wildcard name in model_info.team_public_model_name.
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"""
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import litellm
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from litellm import Router
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from litellm.proxy.auth import model_checks
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from litellm.proxy.auth.model_checks import get_complete_model_list
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from litellm.types.utils import CredentialItem
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monkeypatch.setattr(
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litellm,
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"credential_list",
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[
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CredentialItem(
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credential_name="openai-credential",
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credential_info={"provider": "openai"},
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credential_values={
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"api_key": "stored-openai-key",
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"api_base": "https://example.openai.test/v1",
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},
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)
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],
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)
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captured_params = {}
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def fake_get_provider_models(provider, litellm_params=None):
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captured_params["provider"] = provider
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captured_params["api_key"] = litellm_params.api_key
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captured_params["api_base"] = litellm_params.api_base
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captured_params["credential_name"] = litellm_params.litellm_credential_name
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return ["gpt-4o"]
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monkeypatch.setattr(model_checks, "get_provider_models", fake_get_provider_models)
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router = Router(
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model_list=[
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{
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"model_name": "model_name_team-1_generated",
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"litellm_params": {
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"model": "openai/*",
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"custom_llm_provider": "openai",
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"litellm_credential_name": "openai-credential",
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},
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"model_info": {
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"team_id": "team-1",
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"team_public_model_name": "openai/*",
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},
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}
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]
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)
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result = get_complete_model_list(
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key_models=[],
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team_models=["openai/*"],
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proxy_model_list=[],
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user_model=None,
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infer_model_from_keys=False,
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llm_router=router,
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team_id="team-1",
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)
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assert "openai/gpt-4o" in result
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assert captured_params == {
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"provider": "openai",
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"api_key": "stored-openai-key",
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"api_base": "https://example.openai.test/v1",
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"credential_name": None,
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}
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def test_wildcard_credential_hydration_preserves_deployment_params(
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monkeypatch,
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):
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import litellm
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from litellm.proxy.auth import model_checks
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from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
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from litellm.types.router import LiteLLM_Params
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from litellm.types.utils import CredentialItem
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monkeypatch.setattr(
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litellm,
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"credential_list",
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[
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CredentialItem(
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credential_name="openai-credential",
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credential_info={"provider": "openai"},
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credential_values={
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"api_key": "stored-openai-key",
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"api_version": "credential-version",
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"model": "openai/wrong-model",
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"unexpected_field": "unexpected-value",
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},
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)
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],
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)
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captured_params = {}
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def fake_get_provider_models(provider, litellm_params=None):
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captured_params["provider"] = provider
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captured_params["model"] = litellm_params.model
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captured_params["api_key"] = litellm_params.api_key
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captured_params["api_version"] = litellm_params.api_version
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captured_params["credential_name"] = litellm_params.litellm_credential_name
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captured_params["has_unexpected_field"] = hasattr(
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litellm_params, "unexpected_field"
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)
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return ["gpt-4o"]
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monkeypatch.setattr(model_checks, "get_provider_models", fake_get_provider_models)
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result = get_known_models_from_wildcard(
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wildcard_model="openai/*",
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litellm_params=LiteLLM_Params(
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model="openai/*",
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custom_llm_provider="openai",
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api_version="deployment-version",
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litellm_credential_name="openai-credential",
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),
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)
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assert result == ["openai/gpt-4o"]
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assert captured_params == {
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"provider": "openai",
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"model": "openai/*",
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"api_key": "stored-openai-key",
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"api_version": "deployment-version",
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"credential_name": None,
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"has_unexpected_field": False,
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}
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def test_wildcard_custom_prefix_does_not_stack_provider_prefix(monkeypatch):
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"""Regression test for #30358.
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A wildcard with a custom prefix (e.g. ``ollama_server1/*`` to distinguish multiple Ollama
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instances) must not stack the provider's own prefix onto the expanded model ids. The expanded
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ids should be ``ollama_server1/gemma3:1b`` rather than ``ollama_server1/ollama/gemma3:1b``.
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"""
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from litellm.proxy.auth import model_checks
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from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
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from litellm.types.router import LiteLLM_Params
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monkeypatch.setattr(
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model_checks,
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"get_provider_models",
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lambda provider, litellm_params=None: ["ollama/gemma3:1b", "ollama/llama3:8b"],
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)
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result = get_known_models_from_wildcard(
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wildcard_model="ollama_server1/*",
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litellm_params=LiteLLM_Params(
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model="ollama_chat/*", custom_llm_provider="ollama_chat"
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),
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)
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assert result == ["ollama_server1/gemma3:1b", "ollama_server1/llama3:8b"]
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def test_wildcard_custom_prefix_keeps_org_segment_for_non_provider_first_segment(
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monkeypatch,
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):
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"""Only a known provider prefix should be stripped before re-prefixing.
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If ``get_provider_models`` returns ids whose first segment is an org rather than a litellm
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provider (e.g. ``meta-llama/Llama-3-8B``), stripping the first slash segment would drop the
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org and produce an uncallable id. The org segment must be preserved.
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"""
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from litellm.proxy.auth import model_checks
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from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
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from litellm.types.router import LiteLLM_Params
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monkeypatch.setattr(
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model_checks,
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"get_provider_models",
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lambda provider, litellm_params=None: ["meta-llama/Llama-3-8B"],
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)
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result = get_known_models_from_wildcard(
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wildcard_model="my_hf/*",
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litellm_params=LiteLLM_Params(
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model="huggingface/*", custom_llm_provider="huggingface"
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),
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)
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assert result == ["my_hf/meta-llama/Llama-3-8B"]
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def test_wildcard_credential_hydration_preserves_missing_credential_name(
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monkeypatch,
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):
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import litellm
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from litellm.proxy.auth import model_checks
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from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
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from litellm.types.router import LiteLLM_Params
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monkeypatch.setattr(litellm, "credential_list", [])
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captured_params = {}
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def fake_get_provider_models(provider, litellm_params=None):
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captured_params["provider"] = provider
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captured_params["api_key"] = litellm_params.api_key
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captured_params["credential_name"] = litellm_params.litellm_credential_name
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return ["gpt-4o"]
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monkeypatch.setattr(model_checks, "get_provider_models", fake_get_provider_models)
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result = get_known_models_from_wildcard(
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wildcard_model="openai/*",
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litellm_params=LiteLLM_Params(
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model="openai/*",
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custom_llm_provider="openai",
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api_key=None,
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litellm_credential_name="missing-credential",
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),
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)
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assert result == ["openai/gpt-4o"]
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assert captured_params == {
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"provider": "openai",
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"api_key": None,
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"credential_name": "missing-credential",
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}
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@pytest.mark.asyncio
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async def test_get_available_models_for_user_expands_query_team_wildcard(
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monkeypatch,
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):
|
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import litellm
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from litellm import Router
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from litellm.proxy.auth import model_checks
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from litellm.proxy._types import UserAPIKeyAuth
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from litellm.proxy.utils import get_available_models_for_user
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from litellm.types.utils import CredentialItem
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|
|
|
monkeypatch.setattr(
|
|
litellm,
|
|
"credential_list",
|
|
[
|
|
CredentialItem(
|
|
credential_name="openai-credential",
|
|
credential_info={"provider": "openai"},
|
|
credential_values={"api_key": "stored-openai-key"},
|
|
)
|
|
],
|
|
)
|
|
|
|
def fake_get_provider_models(provider, litellm_params=None):
|
|
assert litellm_params.api_key == "stored-openai-key"
|
|
assert litellm_params.litellm_credential_name is None
|
|
return ["gpt-4o-mini"]
|
|
|
|
monkeypatch.setattr(model_checks, "get_provider_models", fake_get_provider_models)
|
|
|
|
router = Router(
|
|
model_list=[
|
|
{
|
|
"model_name": "model_name_team-1_generated",
|
|
"litellm_params": {
|
|
"model": "openai/*",
|
|
"custom_llm_provider": "openai",
|
|
"litellm_credential_name": "openai-credential",
|
|
},
|
|
"model_info": {
|
|
"team_id": "team-1",
|
|
"team_public_model_name": "openai/*",
|
|
},
|
|
}
|
|
]
|
|
)
|
|
|
|
result = await get_available_models_for_user(
|
|
user_api_key_dict=UserAPIKeyAuth(
|
|
api_key="sk-test",
|
|
models=[],
|
|
team_id="team-1",
|
|
team_models=["openai/*"],
|
|
),
|
|
llm_router=router,
|
|
general_settings={},
|
|
user_model=None,
|
|
team_id="team-1",
|
|
)
|
|
|
|
assert "openai/gpt-4o-mini" in result
|
|
|
|
|
|
def test_get_key_models_all_team_models_recursive_team():
|
|
"""GH#30619: when key and team both have all-team-models,
|
|
the sentinel should expand to proxy_model_list."""
|
|
from litellm.proxy.auth.model_checks import get_key_models
|
|
from litellm.proxy._types import SpecialModelNames
|
|
|
|
user_api_key_dict = type(
|
|
"obj",
|
|
(object,),
|
|
{
|
|
"models": [SpecialModelNames.all_team_models.value],
|
|
"team_id": "team-1",
|
|
"team_models": [SpecialModelNames.all_team_models.value],
|
|
},
|
|
)()
|
|
proxy_model_list = ["model-a", "model-b"]
|
|
result = get_key_models(user_api_key_dict, proxy_model_list, {})
|
|
assert SpecialModelNames.all_team_models.value not in result
|
|
assert set(result) == {"model-a", "model-b"}
|
|
|
|
|
|
def test_get_key_models_all_team_models_keeps_mixed_team_entries():
|
|
from litellm.proxy.auth.model_checks import get_key_models
|
|
from litellm.proxy._types import SpecialModelNames
|
|
|
|
user_api_key_dict = type(
|
|
"obj",
|
|
(object,),
|
|
{
|
|
"models": [SpecialModelNames.all_team_models.value],
|
|
"team_id": "team-1",
|
|
"team_models": [
|
|
SpecialModelNames.all_team_models.value,
|
|
"restricted-model",
|
|
],
|
|
},
|
|
)()
|
|
result = get_key_models(user_api_key_dict, ["model-a", "model-b"], {})
|
|
assert SpecialModelNames.all_team_models.value not in result
|
|
assert set(result) == {"model-a", "model-b", "restricted-model"}
|
|
|
|
|
|
def test_get_team_models_all_team_models_expands():
|
|
"""GH#30619: all-team-models in team_models should expand."""
|
|
from litellm.proxy.auth.model_checks import get_team_models
|
|
from litellm.proxy._types import SpecialModelNames
|
|
|
|
result = get_team_models(
|
|
[SpecialModelNames.all_team_models.value],
|
|
["model-a", "model-b"],
|
|
{},
|
|
)
|
|
assert SpecialModelNames.all_team_models.value not in result
|
|
assert set(result) == {"model-a", "model-b"}
|
|
|
|
|
|
def test_get_team_models_all_team_models_expands_with_access_groups():
|
|
"""GH#30619: all-team-models with include_model_access_groups
|
|
should include access group keys."""
|
|
from litellm.proxy.auth.model_checks import get_team_models
|
|
from litellm.proxy._types import SpecialModelNames
|
|
|
|
result = get_team_models(
|
|
[SpecialModelNames.all_team_models.value],
|
|
["model-a", "model-b"],
|
|
{"group-1": ["g1-model"], "group-2": ["g2-model"]},
|
|
include_model_access_groups=True,
|
|
)
|
|
assert SpecialModelNames.all_team_models.value not in result
|
|
assert "model-a" in result
|
|
assert "model-b" in result
|
|
assert "group-1" in result
|
|
assert "group-2" in result
|
|
|
|
|
|
def test_get_key_models_teamless_all_team_models_returns_unrestricted():
|
|
"""Teamless key with all-team-models must resolve the same as leaving the
|
|
models field empty ([] = unrestricted). The sentinel must not leak into
|
|
the returned list. Fails if someone adds a team_id guard to the sentinel
|
|
expansion in get_key_models."""
|
|
from litellm.proxy._types import SpecialModelNames
|
|
from litellm.proxy.auth.model_checks import get_key_models
|
|
|
|
user_api_key_dict = type(
|
|
"obj",
|
|
(object,),
|
|
{
|
|
"models": [SpecialModelNames.all_team_models.value],
|
|
"team_id": None,
|
|
"team_models": [],
|
|
},
|
|
)()
|
|
proxy_model_list = ["gpt-4o", "claude-sonnet-4-20250514"]
|
|
result = get_key_models(user_api_key_dict, proxy_model_list, {})
|
|
assert SpecialModelNames.all_team_models.value not in result
|
|
assert result == [], "should return [] (unrestricted), same as an unscoped key"
|
|
|
|
|
|
def test_expand_wildcard_deployments_non_wildcard_passthrough():
|
|
"""Non-wildcard deployments must be returned unchanged."""
|
|
from litellm.proxy.auth.model_checks import (
|
|
expand_wildcard_deployments_for_model_info,
|
|
)
|
|
|
|
deployment = {"model_name": "gpt-4o", "litellm_params": {"model": "gpt-4o"}}
|
|
result = expand_wildcard_deployments_for_model_info([deployment])
|
|
assert result == [deployment]
|
|
|
|
|
|
def test_expand_wildcard_deployments_openai_wildcard():
|
|
"""openai/* should expand into ≥1 known openai model entries."""
|
|
from unittest.mock import patch
|
|
|
|
from litellm.proxy.auth.model_checks import (
|
|
expand_wildcard_deployments_for_model_info,
|
|
)
|
|
|
|
fake_models = ["openai/gpt-4o", "openai/gpt-4o-mini"]
|
|
deployment = {
|
|
"model_name": "openai/*",
|
|
"litellm_params": {"model": "openai/*"},
|
|
}
|
|
with patch(
|
|
"litellm.proxy.auth.model_checks.get_known_models_from_wildcard",
|
|
return_value=fake_models,
|
|
):
|
|
result = expand_wildcard_deployments_for_model_info([deployment])
|
|
|
|
assert len(result) == 2
|
|
assert all(r["model_name"] in fake_models for r in result)
|
|
assert all(r["litellm_params"]["model"] in fake_models for r in result)
|
|
|
|
|
|
def test_expand_wildcard_concrete_model_name_with_wildcard_litellm_params():
|
|
"""Concrete model_name must not be overwritten when only litellm_params.model is wildcard."""
|
|
from litellm.proxy.auth.model_checks import (
|
|
expand_wildcard_deployments_for_model_info,
|
|
)
|
|
|
|
deployment = {
|
|
"model_name": "my-custom-alias",
|
|
"litellm_params": {"model": "openai/*"},
|
|
}
|
|
result = expand_wildcard_deployments_for_model_info([deployment])
|
|
# model_name is not a wildcard, so the deployment passes through unchanged
|
|
assert result == [deployment]
|
|
|
|
|
|
def test_expand_wildcard_invalid_litellm_params_passthrough():
|
|
"""Deployments with invalid litellm_params must pass through unchanged (no 500)."""
|
|
from litellm.proxy.auth.model_checks import (
|
|
expand_wildcard_deployments_for_model_info,
|
|
)
|
|
|
|
deployment = {
|
|
"model_name": "openai/*",
|
|
"litellm_params": {
|
|
"model": "openai/*",
|
|
"max_retries": "not-an-int-field-that-breaks",
|
|
},
|
|
}
|
|
# Even if LiteLLM_Params construction fails the deployment should survive
|
|
result = expand_wildcard_deployments_for_model_info([deployment])
|
|
assert result == [deployment]
|
|
|
|
|
|
def test_add_known_models_refreshes_models_by_provider_for_wildcard_expansion():
|
|
"""models_by_provider was a frozen import-time snapshot of set unions, so cost map
|
|
reloads (which call add_known_models) never reached wildcard expansion until a
|
|
process restart (LIT-4947)."""
|
|
import litellm
|
|
from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
|
|
|
|
fake_model = "vertex_ai/gemini-lit4947-regression"
|
|
captured_reference = litellm.models_by_provider
|
|
assert fake_model not in litellm.models_by_provider["vertex_ai"]
|
|
try:
|
|
litellm.add_known_models(
|
|
model_cost_map={
|
|
fake_model: {"litellm_provider": "vertex_ai-language-models", "mode": "chat"}
|
|
}
|
|
)
|
|
assert fake_model in litellm.models_by_provider["vertex_ai"]
|
|
assert litellm.models_by_provider is captured_reference
|
|
assert fake_model in captured_reference["vertex_ai"]
|
|
assert fake_model in get_known_models_from_wildcard("vertex_ai/*")
|
|
finally:
|
|
litellm.vertex_language_models.discard(fake_model)
|
|
litellm.add_known_models(model_cost_map={})
|
|
assert fake_model not in litellm.models_by_provider["vertex_ai"]
|