litellm/tests/unit/proxy/auth/test_model_checks.py

import datetime
import ipaddress
import json
import ssl
import threading
from collections.abc import Generator, Iterator, Mapping
from contextlib import contextmanager
from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
from pathlib import Path
from typing import Final
from unittest.mock import patch

import httpx
import pytest
import respx
from cryptography import x509
from cryptography.hazmat.primitives import hashes, serialization
from cryptography.hazmat.primitives.asymmetric import rsa
from cryptography.x509.oid import NameOID

from litellm import Router
from litellm.utils import AZURE_MODEL_PLACEHOLDER


def test_get_team_models_for_all_models_and_team_only_models():
    from litellm.proxy.auth.model_checks import get_team_models

    team_models = ["all-proxy-models", "team-only-model", "team-only-model-2"]
    proxy_model_list = ["model1", "model2", "model3"]
    model_access_groups = {}
    include_model_access_groups = False

    result: Final = get_team_models(team_models, proxy_model_list, model_access_groups, include_model_access_groups)
    combined_models = team_models + proxy_model_list
    assert set(result) == set(combined_models)


def test_get_team_models_all_proxy_models_includes_access_groups():
    """
    When a team has 'all-proxy-models' and include_model_access_groups=True,
    the result should include model access group names (e.g. 'claude-model-group')
    in addition to individual model names.
    """
    from litellm.proxy.auth.model_checks import get_team_models

    team_models = ["all-proxy-models"]
    proxy_model_list = ["model1", "model2"]
    model_access_groups = {
        "group-a": ["model1"],
        "group-b": ["model2"],
    }

    result = get_team_models(
        team_models,
        proxy_model_list,
        model_access_groups,
        include_model_access_groups=True,
    )
    assert "group-a" in result
    assert "group-b" in result
    assert "model1" in result
    assert "model2" in result
    assert len(result) == len(set(result)), "result should have no duplicates"


def test_get_team_models_all_proxy_models_without_include_flag():
    """
    When include_model_access_groups=False, access group names should NOT
    appear in the result even with 'all-proxy-models'.
    """
    from litellm.proxy.auth.model_checks import get_team_models

    team_models = ["all-proxy-models"]
    proxy_model_list = ["model1", "model2"]
    model_access_groups = {
        "group-a": ["model1"],
        "group-b": ["model2"],
    }

    result = get_team_models(
        team_models,
        proxy_model_list,
        model_access_groups,
        include_model_access_groups=False,
    )
    assert "group-a" not in result
    assert "group-b" not in result
    assert "model1" in result
    assert "model2" in result


def test_get_key_models_all_proxy_models_includes_access_groups():
    """
    When a key has 'all-proxy-models' and include_model_access_groups=True,
    the result should include model access group names.
    """
    from litellm.proxy._types import UserAPIKeyAuth
    from litellm.proxy.auth.model_checks import get_key_models

    user_api_key_dict = UserAPIKeyAuth(
        models=["all-proxy-models"],
        api_key="test-key",
    )
    proxy_model_list = ["model1", "model2"]
    model_access_groups = {
        "group-a": ["model1"],
    }

    result = get_key_models(
        user_api_key_dict=user_api_key_dict,
        proxy_model_list=proxy_model_list,
        model_access_groups=model_access_groups,
        include_model_access_groups=True,
    )
    assert "group-a" in result
    assert "model1" in result
    assert "model2" in result
    assert len(result) == len(set(result)), "result should have no duplicates"


def test_get_key_models_passes_include_model_access_groups():
    """
    When a key explicitly has an access group name in its models list and
    include_model_access_groups=True, the group name should be retained
    (not stripped by _get_models_from_access_groups).
    """
    from litellm.proxy._types import UserAPIKeyAuth
    from litellm.proxy.auth.model_checks import get_key_models

    user_api_key_dict = UserAPIKeyAuth(
        models=["group-a"],
        api_key="test-key",
    )
    proxy_model_list = ["model1", "model2"]
    model_access_groups = {
        "group-a": ["model1", "model2"],
    }

    result = get_key_models(
        user_api_key_dict=user_api_key_dict,
        proxy_model_list=proxy_model_list,
        model_access_groups=model_access_groups,
        include_model_access_groups=True,
    )
    assert "group-a" in result
    assert "model1" in result
    assert "model2" in result


def test_get_key_models_keeps_literal_model_colliding_with_group_name():
    """A name that is BOTH a deployed model and an access group grants both at
    runtime (_check_model_access_helper unions them), so the listing must keep
    the literal model alongside the group members instead of dropping it."""
    from litellm.proxy._types import UserAPIKeyAuth
    from litellm.proxy.auth.model_checks import get_key_models

    user_api_key_dict = UserAPIKeyAuth(models=["beta-models"], api_key="test-key")

    result = get_key_models(
        user_api_key_dict=user_api_key_dict,
        proxy_model_list=["beta-models", "member-a", "unrelated"],
        model_access_groups={"beta-models": ["member-a"]},
        include_model_access_groups=False,
    )
    assert sorted(result) == ["beta-models", "member-a"]


def test_get_team_models_keeps_literal_model_colliding_with_group_name():
    """Team flavor of the collision case: literal deployment survives group expansion."""
    from litellm.proxy.auth.model_checks import get_team_models

    result = get_team_models(
        team_models=["beta-models"],
        proxy_model_list=["beta-models", "member-a", "unrelated"],
        model_access_groups={"beta-models": ["member-a"]},
        include_model_access_groups=False,
    )
    assert sorted(result) == ["beta-models", "member-a"]


def test_get_team_models_drops_group_name_that_is_not_a_deployed_model():
    """No collision: a pure access-group name is still replaced by its members."""
    from litellm.proxy.auth.model_checks import get_team_models

    result = get_team_models(
        team_models=["beta-models"],
        proxy_model_list=["member-a", "unrelated"],
        model_access_groups={"beta-models": ["member-a"]},
        include_model_access_groups=False,
    )
    assert result == ["member-a"]


def test_get_key_models_does_not_mutate_input():
    """
    get_key_models must not mutate user_api_key_dict.models in-place.
    _get_models_from_access_groups uses .pop()/.extend() which would corrupt
    cached UserAPIKeyAuth objects if all_models were an alias instead of a copy.
    """
    from litellm.proxy._types import UserAPIKeyAuth
    from litellm.proxy.auth.model_checks import get_key_models

    original_models = ["group-a", "extra-model"]
    user_api_key_dict = UserAPIKeyAuth(
        models=list(original_models),  # give it a list
        api_key="test-key",
    )
    model_access_groups = {
        "group-a": ["model1", "model2"],
    }

    _ = get_key_models(
        user_api_key_dict=user_api_key_dict,
        proxy_model_list=["model1", "model2"],
        model_access_groups=model_access_groups,
        include_model_access_groups=False,
    )
    # The original models list on the auth object must be unchanged
    assert user_api_key_dict.models == original_models


@pytest.mark.parametrize(
    "key_models,team_models,proxy_model_list,model_list,expected",
    [
        (
            [
                "anthropic/claude-3-haiku-20240307",
                "anthropic/claude-3-5-haiku-20241022",
            ],
            [],
            [],
            [{"model_name": "anthropic/*", "litellm_params": {"model": "anthropic/*"}}],
            [
                "anthropic/claude-3-haiku-20240307",
                "anthropic/claude-3-5-haiku-20241022",
            ],
        ),
        (
            [],
            [
                "anthropic/claude-3-haiku-20240307",
                "anthropic/claude-3-5-haiku-20241022",
            ],
            [],
            [{"model_name": "anthropic/*", "litellm_params": {"model": "anthropic/*"}}],
            [
                "anthropic/claude-3-haiku-20240307",
                "anthropic/claude-3-5-haiku-20241022",
            ],
        ),
        (
            [],
            [],
            [
                "anthropic/claude-3-haiku-20240307",
                "anthropic/claude-3-5-haiku-20241022",
            ],
            [{"model_name": "anthropic/*", "litellm_params": {"model": "anthropic/*"}}],
            [
                "anthropic/claude-3-haiku-20240307",
                "anthropic/claude-3-5-haiku-20241022",
            ],
        ),
    ],
)
def test_get_complete_model_list_order(key_models, team_models, proxy_model_list, model_list, expected):
    """
    Test that get_complete_model_list preserves order
    """
    from litellm.proxy.auth.model_checks import get_complete_model_list
    from litellm import Router

    assert (
        get_complete_model_list(
            proxy_model_list=proxy_model_list,
            key_models=key_models,
            team_models=team_models,
            user_model=None,
            infer_model_from_keys=False,
            llm_router=Router(model_list=model_list),
        )
        == expected
    )


def test_get_complete_model_list_byok_wildcard_expansion():
    """
    Test that wildcard models (e.g., openai/*) are expanded when the router has
    no deployment for them - BYOK case where team has openai/* but proxy has
    no openai config.
    """
    from litellm.proxy.auth.model_checks import get_complete_model_list
    from litellm import Router

    # Router with empty model_list - no openai/* deployment (BYOK scenario)
    result = get_complete_model_list(
        key_models=[],
        team_models=["openai/*"],
        proxy_model_list=[],
        user_model=None,
        infer_model_from_keys=False,
        llm_router=Router(model_list=[]),
    )
    # Should expand openai/* to actual OpenAI models
    assert len(result) > 0
    assert all(m.startswith("openai/") for m in result)
    assert "openai/*" not in result


def test_get_complete_model_list_expands_team_scoped_wildcard_with_stored_credential(
    monkeypatch,
):
    """
    Team-scoped BYOK wildcard deployments are stored under an internal model_name,
    with the public wildcard name in model_info.team_public_model_name.
    """
    import litellm
    from litellm import Router
    from litellm.proxy.auth import model_checks
    from litellm.proxy.auth.model_checks import get_complete_model_list
    from litellm.types.utils import CredentialItem

    monkeypatch.setattr(
        litellm,
        "credential_list",
        [
            CredentialItem(
                credential_name="openai-credential",
                credential_info={"provider": "openai"},
                credential_values={
                    "api_key": "stored-openai-key",
                    "api_base": "https://example.openai.test/v1",
                },
            )
        ],
    )

    captured_params = {}

    def fake_get_provider_models(provider, litellm_params=None):
        captured_params["provider"] = provider
        captured_params["api_key"] = litellm_params.api_key
        captured_params["api_base"] = litellm_params.api_base
        captured_params["credential_name"] = litellm_params.litellm_credential_name
        return ["gpt-4o"]

    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 = get_complete_model_list(
        key_models=[],
        team_models=["openai/*"],
        proxy_model_list=[],
        user_model=None,
        infer_model_from_keys=False,
        llm_router=router,
        team_id="team-1",
    )

    assert "openai/gpt-4o" in result
    assert captured_params == {
        "provider": "openai",
        "api_key": "stored-openai-key",
        "api_base": "https://example.openai.test/v1",
        "credential_name": None,
    }


def test_wildcard_credential_hydration_preserves_deployment_params(
    monkeypatch,
):
    import litellm
    from litellm.proxy.auth import model_checks
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
    from litellm.types.router import LiteLLM_Params
    from litellm.types.utils import CredentialItem

    monkeypatch.setattr(
        litellm,
        "credential_list",
        [
            CredentialItem(
                credential_name="openai-credential",
                credential_info={"provider": "openai"},
                credential_values={
                    "api_key": "stored-openai-key",
                    "api_version": "credential-version",
                    "model": "openai/wrong-model",
                    "unexpected_field": "unexpected-value",
                },
            )
        ],
    )

    captured_params = {}

    def fake_get_provider_models(provider, litellm_params=None):
        captured_params["provider"] = provider
        captured_params["model"] = litellm_params.model
        captured_params["api_key"] = litellm_params.api_key
        captured_params["api_version"] = litellm_params.api_version
        captured_params["credential_name"] = litellm_params.litellm_credential_name
        captured_params["has_unexpected_field"] = hasattr(litellm_params, "unexpected_field")
        return ["gpt-4o"]

    monkeypatch.setattr(model_checks, "get_provider_models", fake_get_provider_models)

    result = get_known_models_from_wildcard(
        wildcard_model="openai/*",
        litellm_params=LiteLLM_Params(
            model="openai/*",
            custom_llm_provider="openai",
            api_version="deployment-version",
            litellm_credential_name="openai-credential",
        ),
    )

    assert result == ["openai/gpt-4o"]
    assert captured_params == {
        "provider": "openai",
        "model": "openai/*",
        "api_key": "stored-openai-key",
        "api_version": "deployment-version",
        "credential_name": None,
        "has_unexpected_field": False,
    }


@respx.mock
def test_hosted_vllm_wildcard_lists_the_server_models_without_an_api_key(monkeypatch: pytest.MonkeyPatch) -> None:
    import litellm
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
    from litellm.types.router import LiteLLM_Params

    monkeypatch.setattr(litellm, "check_provider_endpoint", True)
    models_route: Final = respx.get("http://vllm-without-key.test:8000/v1/models").mock(
        return_value=httpx.Response(
            200,
            json={
                "data": [
                    {"id": "meta-llama/Llama-3.1-8B-Instruct"},
                    {"id": "qwen2.5"},
                    {"id": "openai/gpt-oss-20b"},
                ]
            },
        )
    )

    listed: Final = get_known_models_from_wildcard(
        "hosted_vllm/*",
        LiteLLM_Params(model="hosted_vllm/*", api_base="http://vllm-without-key.test:8000/v1"),
    )

    assert listed == [
        "hosted_vllm/meta-llama/Llama-3.1-8B-Instruct",
        "hosted_vllm/qwen2.5",
        "hosted_vllm/openai/gpt-oss-20b",
    ]
    assert "authorization" not in models_route.calls.last.request.headers


@respx.mock
def test_hosted_vllm_wildcard_sends_the_configured_api_key_as_a_bearer_token(monkeypatch: pytest.MonkeyPatch) -> None:
    import litellm
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
    from litellm.types.router import LiteLLM_Params

    monkeypatch.setattr(litellm, "check_provider_endpoint", True)
    models_route: Final = respx.get(
        "http://vllm-with-key.test:8000/v1/models", headers={"Authorization": "Bearer vllm-test-key"}
    ).mock(return_value=httpx.Response(200, json={"data": [{"id": "qwen2.5"}]}))

    listed: Final = get_known_models_from_wildcard(
        "hosted_vllm/*",
        LiteLLM_Params(model="hosted_vllm/*", api_base="http://vllm-with-key.test:8000/v1", api_key="vllm-test-key"),
    )

    assert listed == ["hosted_vllm/qwen2.5"]
    assert models_route.call_count == 1


@respx.mock
def test_hosted_vllm_wildcard_without_api_base_lists_the_server_chat_would_call(monkeypatch: pytest.MonkeyPatch) -> None:
    import litellm
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
    from litellm.types.router import LiteLLM_Params

    monkeypatch.setattr(litellm, "check_provider_endpoint", True)
    monkeypatch.setenv("HOSTED_VLLM_API_BASE", "http://hosted-vllm-env.test:8000/v1")
    monkeypatch.setenv("HOSTED_VLLM_API_KEY", "hosted-vllm-env-key")
    monkeypatch.setenv("VLLM_API_BASE", "http://vllm-passthrough-env.test:8000")
    passthrough_server_route: Final = respx.get("http://vllm-passthrough-env.test:8000/v1/models").mock(
        return_value=httpx.Response(200, json={"data": [{"id": "model-on-the-passthrough-server"}]})
    )
    respx.get(
        "http://hosted-vllm-env.test:8000/v1/models", headers={"Authorization": "Bearer hosted-vllm-env-key"}
    ).mock(return_value=httpx.Response(200, json={"data": [{"id": "qwen2.5"}]}))

    listed: Final = get_known_models_from_wildcard(
        "hosted_vllm/*", LiteLLM_Params(model="hosted_vllm/*", custom_llm_provider="hosted_vllm")
    )

    assert listed == ["hosted_vllm/qwen2.5"]
    assert not passthrough_server_route.called


@respx.mock
def test_hosted_vllm_wildcard_listing_does_not_wait_the_completion_timeout_on_a_hung_server(
    monkeypatch: pytest.MonkeyPatch,
) -> None:
    import litellm
    from litellm.constants import NON_LLM_CONNECTION_TIMEOUT
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
    from litellm.types.router import LiteLLM_Params

    monkeypatch.setattr(litellm, "check_provider_endpoint", True)
    models_route: Final = respx.get("http://vllm-timeout.test:8000/v1/models").mock(
        return_value=httpx.Response(200, json={"data": [{"id": "qwen2.5"}]})
    )

    get_known_models_from_wildcard(
        "hosted_vllm/*", LiteLLM_Params(model="hosted_vllm/*", api_base="http://vllm-timeout.test:8000/v1")
    )

    read_timeout: Final = models_route.calls.last.request.extensions["timeout"]["read"]
    assert read_timeout is not None
    assert read_timeout <= NON_LLM_CONNECTION_TIMEOUT


@respx.mock
def test_hosted_vllm_wildcard_listing_sends_the_deployment_extra_headers(monkeypatch: pytest.MonkeyPatch) -> None:
    import litellm
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
    from litellm.types.router import LiteLLM_Params

    monkeypatch.setattr(litellm, "check_provider_endpoint", True)
    respx.get(
        "http://vllm-behind-gateway.test:8000/v1/models",
        headers={"X-Tenant": "team-a", "Authorization": "Bearer vllm-test-key"},
    ).mock(return_value=httpx.Response(200, json={"data": [{"id": "qwen2.5"}]}))

    listed: Final = get_known_models_from_wildcard(
        "hosted_vllm/*",
        LiteLLM_Params(
            model="hosted_vllm/*",
            api_base="http://vllm-behind-gateway.test:8000/v1",
            api_key="vllm-test-key",
            extra_headers={"X-Tenant": "team-a"},
        ),
    )

    assert listed == ["hosted_vllm/qwen2.5"]



@respx.mock
def test_vllm_wildcard_never_lists_the_ids_of_a_configured_vllm_server(monkeypatch: pytest.MonkeyPatch) -> None:
    import litellm
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
    from litellm.types.router import LiteLLM_Params

    monkeypatch.setattr(litellm, "check_provider_endpoint", True)
    monkeypatch.setenv("VLLM_API_BASE", "http://vllm-library-env.test:8000")
    monkeypatch.setenv("VLLM_API_KEY", "vllm-library-env-key")
    server_route: Final = respx.get(url__regex=r"http://vllm-library(-env)?\.test:8000/.*").mock(
        return_value=httpx.Response(200, json={"data": [{"id": "model-only-a-server-serves"}]})
    )

    listed: Final = get_known_models_from_wildcard(
        "vllm/*",
        LiteLLM_Params(model="vllm/*", api_base="http://vllm-library.test:8000", api_key="vllm-library-key"),
    )

    assert "vllm/model-only-a-server-serves" not in listed
    assert not server_route.called

_SELF_SIGNED_CERT_NOT_VALID_BEFORE: Final = datetime.datetime(2000, 1, 1, tzinfo=datetime.UTC)
_SELF_SIGNED_CERT_NOT_VALID_AFTER: Final = datetime.datetime(9999, 12, 31, tzinfo=datetime.UTC)


def _self_signed_cert(directory: Path) -> tuple[Path, Path]:
    key: Final = rsa.generate_private_key(public_exponent=65537, key_size=2048)
    name: Final = x509.Name([x509.NameAttribute(NameOID.COMMON_NAME, "127.0.0.1")])
    cert: Final = (
        x509.CertificateBuilder()
        .subject_name(name)
        .issuer_name(name)
        .public_key(key.public_key())
        .serial_number(x509.random_serial_number())
        .not_valid_before(_SELF_SIGNED_CERT_NOT_VALID_BEFORE)
        .not_valid_after(_SELF_SIGNED_CERT_NOT_VALID_AFTER)
        .add_extension(
            x509.SubjectAlternativeName([x509.IPAddress(ipaddress.IPv4Address("127.0.0.1"))]), critical=False
        )
        .sign(key, hashes.SHA256())
    )
    cert_path: Final = directory / "cert.pem"
    key_path: Final = directory / "key.pem"
    cert_path.write_bytes(cert.public_bytes(serialization.Encoding.PEM))
    key_path.write_bytes(
        key.private_bytes(serialization.Encoding.PEM, serialization.PrivateFormat.PKCS8, serialization.NoEncryption())
    )
    return cert_path, key_path


@pytest.fixture
def self_signed_vllm_api_base(tmp_path: Path) -> Iterator[str]:
    cert_path, key_path = _self_signed_cert(tmp_path)

    class Handler(BaseHTTPRequestHandler):
        timeout = 5

        def do_GET(self) -> None:
            body: Final = json.dumps({"data": [{"id": "qwen2.5"}]}).encode()
            self.send_response(200)
            self.send_header("Content-Type", "application/json")
            self.send_header("Content-Length", str(len(body)))
            self.end_headers()
            self.wfile.write(body)

        def log_message(self, format: str, *args: object) -> None:
            pass

    server: Final = ThreadingHTTPServer(("127.0.0.1", 0), Handler)
    context: Final = ssl.SSLContext(ssl.PROTOCOL_TLS_SERVER)
    context.load_cert_chain(cert_path, key_path)
    server.socket = context.wrap_socket(server.socket, server_side=True, do_handshake_on_connect=False)
    threading.Thread(target=server.serve_forever, daemon=True).start()
    try:
        yield f"https://127.0.0.1:{server.server_address[1]}/v1"
    finally:
        server.shutdown()
        server.server_close()


def test_hosted_vllm_wildcard_lists_a_self_signed_server_only_when_the_deployment_turns_off_ssl_verify(
    monkeypatch: pytest.MonkeyPatch, self_signed_vllm_api_base: str
) -> None:
    import litellm
    from litellm.caching.llm_caching_handler import LLMClientCache
    from litellm.llms.custom_httpx import http_handler
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
    from litellm.types.router import LiteLLM_Params

    monkeypatch.setattr(litellm, "check_provider_endpoint", True)
    monkeypatch.setattr(litellm, "ssl_verify", True)
    monkeypatch.setattr(litellm, "in_memory_llm_clients_cache", LLMClientCache())
    monkeypatch.setattr(http_handler, "_ssl_context_cache", {})
    monkeypatch.delenv("SSL_VERIFY", raising=False)
    monkeypatch.delenv("SSL_CERT_FILE", raising=False)

    verified: Final = get_known_models_from_wildcard(
        "hosted_vllm/*", LiteLLM_Params(model="hosted_vllm/*", api_base=self_signed_vllm_api_base)
    )
    unverified: Final = get_known_models_from_wildcard(
        "hosted_vllm/*",
        LiteLLM_Params(model="hosted_vllm/*", api_base=self_signed_vllm_api_base, ssl_verify=False),
    )

    assert verified == []
    assert unverified == ["hosted_vllm/qwen2.5"]


@respx.mock
def test_custom_prefix_over_a_litellm_proxy_wildcard_lists_upstream_models_under_the_prefix_alone(
    monkeypatch: pytest.MonkeyPatch,
) -> None:
    import litellm
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
    from litellm.types.router import LiteLLM_Params

    monkeypatch.setattr(litellm, "check_provider_endpoint", True)
    respx.get("http://upstream-proxy.test:4000/v1/models").mock(
        return_value=httpx.Response(200, json={"data": [{"id": "gpt-4o"}, {"id": "claude-sonnet"}]})
    )

    listed: Final = get_known_models_from_wildcard(
        "team-proxy/*",
        LiteLLM_Params(model="litellm_proxy/*", api_base="http://upstream-proxy.test:4000", api_key="sk-upstream"),
    )

    assert listed == ["team-proxy/gpt-4o", "team-proxy/claude-sonnet"]


def test_wildcard_custom_prefix_does_not_stack_provider_prefix(monkeypatch):
    """Regression test for #30358.

    A wildcard with a custom prefix (e.g. ``ollama_server1/*`` to distinguish multiple Ollama
    instances) must not stack the provider's own prefix onto the expanded model ids. The expanded
    ids should be ``ollama_server1/gemma3:1b`` rather than ``ollama_server1/ollama/gemma3:1b``.
    """
    from litellm.proxy.auth import model_checks
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
    from litellm.types.router import LiteLLM_Params

    monkeypatch.setattr(
        model_checks,
        "get_provider_models",
        lambda provider, litellm_params=None: ["ollama/gemma3:1b", "ollama/llama3:8b"],
    )

    result = get_known_models_from_wildcard(
        wildcard_model="ollama_server1/*",
        litellm_params=LiteLLM_Params(model="ollama_chat/*", custom_llm_provider="ollama_chat"),
    )

    assert result == ["ollama_server1/gemma3:1b", "ollama_server1/llama3:8b"]


def test_wildcard_custom_prefix_keeps_org_segment_for_non_provider_first_segment(
    monkeypatch,
):
    """Only a known provider prefix should be stripped before re-prefixing.

    If ``get_provider_models`` returns ids whose first segment is an org rather than a litellm
    provider (e.g. ``meta-llama/Llama-3-8B``), stripping the first slash segment would drop the
    org and produce an uncallable id. The org segment must be preserved.
    """
    from litellm.proxy.auth import model_checks
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
    from litellm.types.router import LiteLLM_Params

    monkeypatch.setattr(
        model_checks,
        "get_provider_models",
        lambda provider, litellm_params=None: ["meta-llama/Llama-3-8B"],
    )

    result = get_known_models_from_wildcard(
        wildcard_model="my_hf/*",
        litellm_params=LiteLLM_Params(model="huggingface/*", custom_llm_provider="huggingface"),
    )

    assert result == ["my_hf/meta-llama/Llama-3-8B"]


def test_wildcard_credential_hydration_preserves_missing_credential_name(
    monkeypatch,
):
    import litellm
    from litellm.proxy.auth import model_checks
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
    from litellm.types.router import LiteLLM_Params

    monkeypatch.setattr(litellm, "credential_list", [])

    captured_params = {}

    def fake_get_provider_models(provider, litellm_params=None):
        captured_params["provider"] = provider
        captured_params["api_key"] = litellm_params.api_key
        captured_params["credential_name"] = litellm_params.litellm_credential_name
        return ["gpt-4o"]

    monkeypatch.setattr(model_checks, "get_provider_models", fake_get_provider_models)

    result = get_known_models_from_wildcard(
        wildcard_model="openai/*",
        litellm_params=LiteLLM_Params(
            model="openai/*",
            custom_llm_provider="openai",
            api_key=None,
            litellm_credential_name="missing-credential",
        ),
    )

    assert result == ["openai/gpt-4o"]
    assert captured_params == {
        "provider": "openai",
        "api_key": None,
        "credential_name": "missing-credential",
    }


def test_hydrate_credential_name_none_leaves_params_untouched(monkeypatch):
    import litellm
    from litellm.proxy.auth.model_checks import _hydrate_litellm_credential_name
    from litellm.types.router import LiteLLM_Params
    from litellm.types.utils import CredentialItem

    monkeypatch.setattr(
        litellm,
        "credential_list",
        [
            CredentialItem(
                credential_name="shared-credential",
                credential_info={},
                credential_values={"api_key": "sk-shared"},
            )
        ],
    )
    params = LiteLLM_Params(model="openai/gpt-4o", litellm_credential_name=None)

    result = _hydrate_litellm_credential_name(params)

    assert result is not None
    assert result.api_key is None
    assert result.litellm_credential_name is None


def test_hydrate_replaced_credential_uses_new_credential_values(monkeypatch):
    import litellm
    from litellm.proxy.auth.model_checks import _hydrate_litellm_credential_name
    from litellm.types.router import LiteLLM_Params
    from litellm.types.utils import CredentialItem

    monkeypatch.setattr(
        litellm,
        "credential_list",
        [
            CredentialItem(
                credential_name="shared-credential",
                credential_info={},
                credential_values={"api_key": "sk-shared"},
            ),
            CredentialItem(
                credential_name="other-credential",
                credential_info={},
                credential_values={"api_key": "sk-other"},
            ),
        ],
    )
    params = LiteLLM_Params(model="openai/gpt-4o", litellm_credential_name="other-credential")

    result = _hydrate_litellm_credential_name(params)

    assert result is not None
    assert result.api_key == "sk-other"
    assert result.litellm_credential_name is None


def test_hydrate_inline_api_key_wins_over_stored_credential(monkeypatch):
    import litellm
    from litellm.proxy.auth.model_checks import _hydrate_litellm_credential_name
    from litellm.types.router import LiteLLM_Params
    from litellm.types.utils import CredentialItem

    monkeypatch.setattr(
        litellm,
        "credential_list",
        [
            CredentialItem(
                credential_name="shared-credential",
                credential_info={},
                credential_values={"api_key": "sk-shared"},
            )
        ],
    )
    params = LiteLLM_Params(
        model="openai/gpt-4o",
        api_key="sk-inline",
        litellm_credential_name="shared-credential",
    )

    result = _hydrate_litellm_credential_name(params)

    assert result is not None
    assert result.api_key == "sk-inline"


@pytest.mark.asyncio
async def test_get_available_models_for_user_expands_query_team_wildcard(
    monkeypatch,
):
    import litellm
    from litellm import Router
    from litellm.proxy.auth import model_checks
    from litellm.proxy._types import UserAPIKeyAuth
    from litellm.proxy.utils import get_available_models_for_user
    from litellm.types.utils import CredentialItem

    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 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]



@pytest.mark.parametrize(
    ("allowed_model_names", "expected_names", "expected_listings"),
    [
        pytest.param(None, ["qwen-qwen2.5"], 1, id="unscoped"),
        pytest.param(["qwen-qwen2.5"], ["qwen-qwen2.5"], 1, id="granted-a-listed-name"),
        pytest.param(["hosted_vllm/qwen2.5"], [], 0, id="granted-only-the-provider-id"),
    ],
)
@respx.mock
def test_expand_wildcard_alias_without_a_slash_lists_and_filters_by_its_own_pattern(
    monkeypatch: pytest.MonkeyPatch,
    request: pytest.FixtureRequest,
    allowed_model_names: list[str] | None,
    expected_names: list[str],
    expected_listings: int,
) -> None:
    import litellm
    from litellm.proxy.auth.model_checks import expand_wildcard_deployments_for_model_info

    monkeypatch.setattr(litellm, "check_provider_endpoint", True)
    api_base: Final = f"http://vllm-alias-{request.node.callspec.id}.test:8000/v1"
    listing: Final = respx.get(f"{api_base}/models").mock(
        return_value=httpx.Response(200, json={"data": [{"id": "qwen2.5"}]})
    )
    deployment: Final = {"model_name": "qwen-*", "litellm_params": {"model": "hosted_vllm/*", "api_base": api_base}}

    rows: Final = expand_wildcard_deployments_for_model_info([deployment], allowed_model_names=allowed_model_names)

    assert ([row["model_name"] for row in rows], listing.call_count) == (expected_names, expected_listings)


@pytest.mark.parametrize(
    ("allowed_model_names", "keeps_the_alias"),
    [
        pytest.param(["gpt-4o-mini"], True, id="granted-a-name-the-alias-matches"),
        pytest.param(["claude-sonnet"], False, id="granted-only-other-names"),
    ],
)
def test_expand_wildcard_alias_over_one_model_is_kept_only_for_keys_with_a_name_it_matches(
    allowed_model_names: list[str], keeps_the_alias: bool
) -> None:
    from litellm.proxy.auth.model_checks import expand_wildcard_deployments_for_model_info

    deployment: Final = {"model_name": "gpt-4o*", "litellm_params": {"model": "openai/gpt-4o"}}

    rows: Final = expand_wildcard_deployments_for_model_info([deployment], allowed_model_names=allowed_model_names)

    assert rows == ([deployment] if keeps_the_alias else [])

def test_get_complete_model_list_excludes_wildcard_routes_by_default():
    """Regression (LIT-4108): a wildcard with a matching router deployment leaked into /v1/models."""
    from litellm import Router
    from litellm.proxy.auth.model_checks import get_complete_model_list

    router = Router(
        model_list=[
            {
                "model_name": "bedrock/*",
                "litellm_params": {"model": "bedrock/*"},
            },
            {
                "model_name": "gpt-4",
                "litellm_params": {"model": "openai/gpt-4"},
            },
        ]
    )

    result = get_complete_model_list(
        key_models=[],
        team_models=[],
        proxy_model_list=["bedrock/*", "gpt-4"],
        user_model=None,
        infer_model_from_keys=False,
        return_wildcard_routes=False,
        llm_router=router,
    )

    assert "bedrock/*" not in result
    assert "gpt-4" in result
    assert any(m.startswith("bedrock/") for m in result)


def test_get_complete_model_list_excludes_wildcard_routes_without_router():
    from litellm.proxy.auth.model_checks import get_complete_model_list

    result = get_complete_model_list(
        key_models=[],
        team_models=[],
        proxy_model_list=["bedrock/*", "gpt-4"],
        user_model=None,
        infer_model_from_keys=False,
        return_wildcard_routes=False,
        llm_router=None,
    )

    assert "bedrock/*" not in result
    assert "gpt-4" in result
    assert any(m.startswith("bedrock/") for m in result)


def test_get_complete_model_list_includes_wildcard_routes_when_requested():
    from litellm import Router
    from litellm.proxy.auth.model_checks import get_complete_model_list

    router = Router(
        model_list=[
            {
                "model_name": "bedrock/*",
                "litellm_params": {"model": "bedrock/*"},
            },
        ]
    )

    result = get_complete_model_list(
        key_models=[],
        team_models=[],
        proxy_model_list=["bedrock/*"],
        user_model=None,
        infer_model_from_keys=False,
        return_wildcard_routes=True,
        llm_router=router,
    )

    assert result.count("bedrock/*") == 1
    assert any(m.startswith("bedrock/") and m != "bedrock/*" for m in result)


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"]


def test_wildcard_lists_a_model_once_when_registered_both_bare_and_provider_prefixed():
    import litellm
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard

    bare: Final = "gpt-dedupe-regression"
    entry: Final = {"litellm_provider": "openai", "mode": "chat"}
    try:
        litellm.register_model({bare: entry, f"openai/{bare}": entry}, persist_across_reloads=False)

        listed: Final = get_known_models_from_wildcard("openai/*")

        assert listed.count(f"openai/{bare}") == 1
    finally:
        litellm.model_cost.pop(bare, None)
        litellm.model_cost.pop(f"openai/{bare}", None)
        litellm.open_ai_chat_completion_models.discard(bare)
        litellm.open_ai_chat_completion_models.discard(f"openai/{bare}")
        litellm.add_known_models(model_cost_map={})


def _is_vertex_ai_label(label: object) -> bool:
    return label == "vertex_ai" or (isinstance(label, str) and label.startswith("vertex_ai-"))


def test_vertex_wildcard_lists_every_vertex_cost_map_row_under_its_callable_id():
    import litellm
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard

    vertex_rows: Final = {
        f"vertex_ai/{name.removeprefix('vertex_ai/')}"
        for name, info in litellm.model_cost.items()
        if _is_vertex_ai_label(info.get("litellm_provider"))
    }
    assert vertex_rows

    listed: Final = set(get_known_models_from_wildcard("vertex_ai/*"))

    assert sorted(vertex_rows - listed) == []


VERTEX_COST_MAP_LABELS: Final = (
    "vertex_ai",
    "vertex_ai-language-models",
    "vertex_ai-vision-models",
    "vertex_ai-chat-models",
    "vertex_ai-code-chat-models",
    "vertex_ai-text-models",
    "vertex_ai-code-text-models",
    "vertex_ai-embedding-models",
    "vertex_ai-anthropic_models",
    "vertex_ai-llama_models",
    "vertex_ai-deepseek_models",
    "vertex_ai-mistral_models",
    "vertex_ai-ai21_models",
    "vertex_ai-image-models",
    "vertex_ai-video-models",
    "vertex_ai-openai_models",
    "vertex_ai-minimax_models",
    "vertex_ai-moonshot_models",
    "vertex_ai-zai_models",
    "vertex_ai-qwen_models",
)


@contextmanager
def _registered_rows(label_per_key: Mapping[str, str]) -> Generator[None, None, None]:
    import litellm

    try:
        litellm.register_model(
            {key: {"litellm_provider": label, "mode": "chat"} for key, label in label_per_key.items()},
            persist_across_reloads=False,
        )
        yield
    finally:
        provider_model_sets: Final = tuple(value for value in vars(litellm).values() if isinstance(value, set))
        for key in label_per_key:
            for provider_models in provider_model_sets:
                provider_models.discard(key)
                provider_models.discard(key.removeprefix("vertex_ai/"))
        litellm.add_known_models(model_cost_map={})


@pytest.mark.parametrize("label", VERTEX_COST_MAP_LABELS)
def test_vertex_wildcard_lists_a_row_registered_under_any_vertex_label(label: str):
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard

    key: Final = f"vertex_ai/fake-{label}-row"
    with _registered_rows({key: label}):
        listed: Final = get_known_models_from_wildcard("vertex_ai/*")

    assert key in listed


@pytest.mark.parametrize(
    ("wildcard_model", "listed_prefix"),
    [("vertex_ai/*", "vertex_ai"), ("my_vertex/*", "my_vertex")],
)
def test_wildcard_keeps_a_publisher_segment_that_names_another_provider(wildcard_model: str, listed_prefix: str):
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
    from litellm.types.router import LiteLLM_Params

    with _registered_rows(
        {
            "vertex_ai/openai/fake-publisher-maas": "vertex_ai-openai_models",
            "vertex_ai/meta/fake-publisher-maas": "vertex_ai-llama_models",
        }
    ):
        listed: Final = get_known_models_from_wildcard(
            wildcard_model=wildcard_model,
            litellm_params=LiteLLM_Params(model="vertex_ai/*"),
        )

    assert f"{listed_prefix}/openai/fake-publisher-maas" in listed
    assert f"{listed_prefix}/meta/fake-publisher-maas" in listed
    assert f"{listed_prefix}/fake-publisher-maas" not in listed


@pytest.mark.parametrize("provider", ["replicate", "wandb"])
def test_wildcard_lists_each_model_once_under_its_full_owner_id(provider: str):
    import litellm
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard

    full_ids: Final = {
        f"{provider}/{model.removeprefix(f'{provider}/')}" for model in litellm.models_by_provider[provider]
    }
    assert any(model.count("/") > 1 for model in full_ids)

    assert sorted(get_known_models_from_wildcard(f"{provider}/*")) == sorted(full_ids)


def test_get_complete_model_list_drops_no_default_models_sentinel():
    from litellm.proxy.auth.model_checks import get_complete_model_list

    result = get_complete_model_list(
        key_models=["no-default-models", "model-a"],
        team_models=[],
        proxy_model_list=["model-a", "model-b"],
        user_model=None,
        infer_model_from_keys=False,
    )
    assert result == ["model-a"]


def test_get_complete_model_list_sentinel_only_grants_nothing():
    from litellm.proxy.auth.model_checks import get_complete_model_list

    result = get_complete_model_list(
        key_models=["no-default-models"],
        team_models=["no-default-models"],
        proxy_model_list=["model-a", "model-b"],
        user_model=None,
        infer_model_from_keys=False,
    )
    assert result == []


def test_get_provider_models_admits_providers_without_a_static_catalog():
    """Providers without a static model list are no longer rejected up front.

    With endpoint discovery off, get_valid_models falls back to the (empty)
    static list, so the result is [] rather than None. Before the fix this
    returned None and the wildcard was never expanded.
    """
    import litellm
    from litellm.proxy.auth.model_checks import get_provider_models
    from litellm.types.router import LiteLLM_Params

    assert "litellm_proxy" not in litellm.models_by_provider
    assert "hosted_vllm" not in litellm.models_by_provider

    result = get_provider_models(
        "litellm_proxy",
        litellm_params=LiteLLM_Params(
            model="litellm_proxy/*",
            api_base="http://upstream:4000",
            api_key="sk-upstream",
        ),
    )

    assert result == []


def test_get_complete_model_list_discovers_litellm_proxy_wildcard_models(monkeypatch):
    """A litellm_proxy/* deployment lists the upstream proxy's models when endpoint discovery is on."""
    import litellm
    from litellm import Router
    from litellm.llms.openai.chat.gpt_transformation import OpenAIGPTConfig
    from litellm.proxy.auth.model_checks import get_complete_model_list

    monkeypatch.setattr(litellm, "check_provider_endpoint", True)
    captured = {}

    def fake_get_models(self, api_key=None, api_base=None):
        captured["api_key"] = api_key
        captured["api_base"] = api_base
        return ["gpt-4o", "claude-sonnet"]

    monkeypatch.setattr(OpenAIGPTConfig, "get_models", fake_get_models)

    router = Router(
        model_list=[
            {
                "model_name": "litellm_proxy/*",
                "litellm_params": {
                    "model": "litellm_proxy/*",
                    "api_base": "http://upstream:4000",
                    "api_key": "sk-upstream",
                },
            }
        ]
    )
    result = get_complete_model_list(
        key_models=[],
        team_models=[],
        proxy_model_list=["litellm_proxy/*"],
        user_model=None,
        infer_model_from_keys=False,
        llm_router=router,
    )

    assert captured == {"api_key": "sk-upstream", "api_base": "http://upstream:4000"}
    assert "litellm_proxy/gpt-4o" in result
    assert "litellm_proxy/claude-sonnet" in result


def test_get_provider_models_returns_none_for_an_unknown_provider():
    from litellm.proxy.auth.model_checks import get_provider_models

    assert get_provider_models("not-a-real-provider") is None


def test_transcribe_is_a_known_provider_for_wildcard_expansion():
    import litellm
    from litellm.proxy.auth.model_checks import (
        get_known_models_from_wildcard,
        get_provider_models,
    )

    assert "transcribe" in litellm.models_by_provider
    assert "transcribe/StartTranscriptionJob" in litellm.models_by_provider["transcribe"]
    assert get_provider_models("transcribe") == ["transcribe/StartTranscriptionJob"]
    assert get_known_models_from_wildcard("transcribe/*") == ["transcribe/StartTranscriptionJob"]


@respx.mock
def test_partial_bedrock_wildcard_filters_the_discovered_ids(monkeypatch: pytest.MonkeyPatch) -> None:
    import litellm
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
    from litellm.types.router import LiteLLM_Params

    monkeypatch.setattr(litellm, "check_provider_endpoint", True)
    monkeypatch.delenv("AWS_BEARER_TOKEN_BEDROCK", raising=False)
    region: Final = "ap-south-1"
    respx.get(
        f"https://bedrock.{region}.amazonaws.com/foundation-models", params={"byInferenceType": "ON_DEMAND"}
    ).mock(
        return_value=httpx.Response(
            200,
            json={
                "modelSummaries": [
                    {"modelId": "anthropic.claude-haiku-4-5-20251001-v1:0"},
                    {"modelId": "amazon.nova-micro-v1:0"},
                ]
            },
        )
    )
    respx.get(
        f"https://bedrock.{region}.amazonaws.com/inference-profiles", params={"typeEquals": "SYSTEM_DEFINED"}
    ).mock(
        return_value=httpx.Response(
            200,
            json={
                "inferenceProfileSummaries": [
                    {"inferenceProfileId": "us.anthropic.claude-haiku-4-5-20251001-v1:0", "status": "ACTIVE"}
                ]
            },
        )
    )
    deployment: Final = LiteLLM_Params(
        model="bedrock/anthropic.*",
        aws_access_key_id="AKIAPARTIALWILDCARD",
        aws_secret_access_key="partial-wildcard-secret",
        aws_region_name=region,
    )

    assert get_known_models_from_wildcard("bedrock/anthropic.*", deployment) == [
        "bedrock/anthropic.claude-haiku-4-5-20251001-v1:0"
    ]


@respx.mock
def test_partial_bedrock_wildcard_lists_nothing_when_no_discovered_id_carries_its_prefix(
    monkeypatch: pytest.MonkeyPatch,
) -> None:
    import litellm
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
    from litellm.types.router import LiteLLM_Params

    monkeypatch.setattr(litellm, "check_provider_endpoint", True)
    monkeypatch.delenv("AWS_BEARER_TOKEN_BEDROCK", raising=False)
    region: Final = "ap-southeast-2"
    respx.get(
        f"https://bedrock.{region}.amazonaws.com/foundation-models", params={"byInferenceType": "ON_DEMAND"}
    ).mock(return_value=httpx.Response(200, json={"modelSummaries": [{"modelId": "amazon.nova-micro-v1:0"}]}))
    respx.get(
        f"https://bedrock.{region}.amazonaws.com/inference-profiles", params={"typeEquals": "SYSTEM_DEFINED"}
    ).mock(
        return_value=httpx.Response(
            200,
            json={
                "inferenceProfileSummaries": [
                    {"inferenceProfileId": "us.anthropic.claude-haiku-4-5-20251001-v1:0", "status": "ACTIVE"}
                ]
            },
        )
    )
    deployment: Final = LiteLLM_Params(
        model="bedrock/anthropic.*",
        aws_access_key_id="AKIAPROFILEONLYACCOUNT",
        aws_secret_access_key="profile-only-secret",
        aws_region_name=region,
    )

    assert get_known_models_from_wildcard("bedrock/anthropic.*", deployment) == []


@pytest.mark.parametrize(
    ("wildcard", "deployment_model", "listed_ids"),
    [
        (
            "openrouter/*",
            "openrouter/*",
            ["openrouter/openai/gpt-5.4-mini", "openrouter/anthropic/claude-haiku-5-5"],
        ),
        ("or-team/*", "openrouter/*", ["or-team/openai/gpt-5.4-mini", "or-team/anthropic/claude-haiku-5-5"]),
        ("openrouter/openai/*", "openrouter/openai/*", ["openrouter/openai/gpt-5.4-mini"]),
        ("*", "openrouter/*", ["openai/gpt-5.4-mini", "anthropic/claude-haiku-5-5"]),
    ],
)
@respx.mock
def test_openrouter_wildcard_lists_the_live_catalog_with_each_vendor_namespace(
    monkeypatch: pytest.MonkeyPatch, wildcard: str, deployment_model: str, listed_ids: list[str]
) -> None:
    import litellm
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
    from litellm.types.router import LiteLLM_Params

    monkeypatch.setattr(litellm, "check_provider_endpoint", True)
    monkeypatch.delenv("OPENROUTER_API_BASE", raising=False)
    respx.get("https://openrouter.ai/api/v1/models/user").mock(
        return_value=httpx.Response(
            200, json={"data": [{"id": "openai/gpt-5.4-mini"}, {"id": "anthropic/claude-haiku-5-5"}]}
        )
    )

    assert (
        get_known_models_from_wildcard(wildcard, LiteLLM_Params(model=deployment_model, api_key=f"sk-or-{wildcard}"))
        == listed_ids
    )


@respx.mock
def test_key_granted_openrouter_wildcard_without_an_openrouter_deployment_lists_no_environment_catalog(
    monkeypatch: pytest.MonkeyPatch,
) -> None:
    import litellm
    from litellm import Router
    from litellm.proxy.auth.model_checks import get_complete_model_list

    monkeypatch.setattr(litellm, "check_provider_endpoint", True)
    monkeypatch.setenv("OPENROUTER_API_KEY", "sk-or-environment-only")
    catalog: Final = respx.get("https://openrouter.ai/api/v1/models/user").mock(
        return_value=httpx.Response(200, json={"data": [{"id": "anthropic/claude-haiku-5-5"}]})
    )
    router: Final = Router(
        model_list=[{"model_name": "or-team/*", "litellm_params": {"model": "openrouter/*", "api_key": "sk-or-team"}}]
    )

    listed: Final = get_complete_model_list(
        key_models=["openrouter/*"],
        team_models=[],
        proxy_model_list=router.model_names,
        user_model=None,
        infer_model_from_keys=False,
        llm_router=router,
    )

    assert (listed, catalog.call_count) == ([], 0)


@respx.mock
def test_key_granted_hosted_vllm_wildcard_without_a_hosted_vllm_deployment_lists_no_environment_server(
    monkeypatch: pytest.MonkeyPatch,
) -> None:
    import litellm
    from litellm import Router
    from litellm.proxy.auth.model_checks import get_complete_model_list

    monkeypatch.setattr(litellm, "check_provider_endpoint", True)
    monkeypatch.setenv("HOSTED_VLLM_API_BASE", "http://hosted-vllm-environment-only.test:8000/v1")
    environment_server: Final = respx.get("http://hosted-vllm-environment-only.test:8000/v1/models").mock(
        return_value=httpx.Response(200, json={"data": [{"id": "qwen2.5"}]})
    )
    router: Final = Router(
        model_list=[
            {
                "model_name": "vllm-team/*",
                "litellm_params": {"model": "hosted_vllm/*", "api_base": "http://vllm-team.test:8000/v1"},
            }
        ]
    )

    listed: Final = get_complete_model_list(
        key_models=["hosted_vllm/*"],
        team_models=[],
        proxy_model_list=router.model_names,
        user_model=None,
        infer_model_from_keys=False,
        llm_router=router,
    )

    assert (listed, environment_server.call_count) == ([], 0)


@contextmanager
def _openai_catalog_behind_a_catch_all(
    monkeypatch: pytest.MonkeyPatch, concrete_name: str, concrete_model_info: Mapping[str, str]
) -> Generator[Router, None, None]:
    import litellm

    monkeypatch.setattr(litellm, "check_provider_endpoint", True)
    monkeypatch.delenv("OPENAI_API_BASE", raising=False)
    monkeypatch.delenv("OPENAI_BASE_URL", raising=False)
    with respx.mock(assert_all_called=False) as respx_mock:
        respx_mock.get("https://api.openai.com/v1/models").mock(
            return_value=httpx.Response(200, json={"data": [{"id": "gpt-4o"}, {"id": "gpt-4o-mini"}]})
        )
        yield Router(
            model_list=[
                {"model_name": "*", "litellm_params": {"model": "openai/*", "api_key": "sk-openai-catch-all"}},
                {
                    "model_name": concrete_name,
                    "litellm_params": {"model": "openrouter/openai/gpt-4o", "api_key": "sk-or-gpt-4o"},
                    "model_info": dict(concrete_model_info),
                },
            ]
        )


@pytest.mark.parametrize(
    ("concrete_name", "concrete_model_info", "team_id"),
    [
        ("gpt-4o", {}, None),
        ("model_name_team-x_gpt-4o", {"team_id": "team-x", "team_public_model_name": "gpt-4o"}, "team-x"),
    ],
)
def test_catch_all_wildcard_lists_a_name_a_concrete_deployment_serves_once(
    monkeypatch: pytest.MonkeyPatch, concrete_name: str, concrete_model_info: Mapping[str, str], team_id: str | None
) -> None:
    from litellm.proxy.auth.model_checks import get_complete_model_list

    with _openai_catalog_behind_a_catch_all(monkeypatch, concrete_name, concrete_model_info) as router:
        listed: Final = get_complete_model_list(
            key_models=[],
            team_models=[],
            proxy_model_list=router.get_model_names(team_id=team_id),
            user_model=None,
            infer_model_from_keys=False,
            llm_router=router,
            team_id=team_id,
        )

    assert sorted(listed) == ["gpt-4o", "gpt-4o-mini"]


def test_catch_all_wildcard_model_info_keeps_only_the_concrete_row_for_a_deployed_name(
    monkeypatch: pytest.MonkeyPatch,
) -> None:
    from litellm.proxy.auth.model_checks import expand_wildcard_deployments_for_model_info

    with _openai_catalog_behind_a_catch_all(monkeypatch, "gpt-4o", {}) as router:
        rows: Final = expand_wildcard_deployments_for_model_info(
            [dict(deployment) for deployment in router.get_model_list() or ()], llm_router=router
        )

    assert sorted((row["model_name"], row["litellm_params"]["model"]) for row in rows) == [
        ("gpt-4o", "openrouter/openai/gpt-4o"),
        ("gpt-4o-mini", "openai/gpt-4o-mini"),
    ]


@contextmanager
def _openrouter_catalog_beside_a_named_deployment(
    monkeypatch: pytest.MonkeyPatch,
    wildcard_name: str,
    named: str,
    catalog: tuple[str, ...] = ("openai/gpt-5.4-mini", "anthropic/claude-haiku-5-5"),
    wildcard_key: str | None = None,
) -> Generator[Router, None, None]:
    import litellm

    monkeypatch.setattr(litellm, "check_provider_endpoint", True)
    monkeypatch.delenv("OPENROUTER_API_BASE", raising=False)
    with respx.mock(assert_all_called=False) as respx_mock:
        respx_mock.get("https://openrouter.ai/api/v1/models/user").mock(
            return_value=httpx.Response(200, json={"data": [{"id": catalog_id} for catalog_id in catalog]})
        )
        yield Router(
            model_list=[
                {
                    "model_name": wildcard_name,
                    "litellm_params": {
                        "model": "openrouter/*",
                        "api_key": wildcard_key or f"sk-or-wildcard-{wildcard_name}",
                    },
                },
                {
                    "model_name": named,
                    "litellm_params": {"model": "openrouter/openai/gpt-5.4-mini", "api_key": "sk-or-named"},
                },
            ]
        )


@pytest.mark.parametrize(
    ("wildcard_name", "named"),
    [("openrouter/*", "openrouter/openai/gpt-5.4-mini"), ("or-team/*", "or-team/openai/gpt-5.4-mini")],
)
def test_provider_wildcard_lists_a_name_a_named_deployment_serves_once(
    monkeypatch: pytest.MonkeyPatch, wildcard_name: str, named: str
) -> None:
    from litellm.proxy.auth.model_checks import expand_wildcard_deployments_for_model_info, get_complete_model_list

    with _openrouter_catalog_beside_a_named_deployment(monkeypatch, wildcard_name, named) as router:
        listed: Final = get_complete_model_list(
            key_models=[],
            team_models=[],
            proxy_model_list=list(router.model_names),
            user_model=None,
            infer_model_from_keys=False,
            llm_router=router,
        )
        rows: Final = expand_wildcard_deployments_for_model_info(
            [dict(deployment) for deployment in router.get_model_list() or ()], llm_router=router
        )

    vendor_prefix: Final = wildcard_name.removesuffix("*")
    assert sorted(listed) == [f"{vendor_prefix}anthropic/claude-haiku-5-5", named]
    assert sorted((row["model_name"], row["litellm_params"]["api_key"]) for row in rows) == [
        (f"{vendor_prefix}anthropic/claude-haiku-5-5", f"sk-or-wildcard-{wildcard_name}"),
        (named, "sk-or-named"),
    ]


@pytest.mark.parametrize(
    ("wildcard_name", "named"),
    [("openrouter/*", "openrouter/openai/gpt-5.4-mini"), ("or-team/*", "or-team/openai/gpt-5.4-mini")],
)
def test_provider_wildcard_whose_whole_catalog_is_deployed_by_name_shows_only_the_named_row(
    monkeypatch: pytest.MonkeyPatch, wildcard_name: str, named: str
) -> None:
    from litellm.proxy.auth.model_checks import expand_wildcard_deployments_for_model_info

    with _openrouter_catalog_beside_a_named_deployment(
        monkeypatch,
        wildcard_name,
        named,
        catalog=("openai/gpt-5.4-mini",),
        wildcard_key=f"sk-or-one-model-{wildcard_name}",
    ) as router:
        rows: Final = expand_wildcard_deployments_for_model_info(
            [dict(deployment) for deployment in router.get_model_list() or ()], llm_router=router
        )

    assert [(row["model_name"], row["litellm_params"]["api_key"]) for row in rows] == [(named, "sk-or-named")]


@respx.mock
def test_custom_prefix_that_starts_a_discovered_id_still_prefixes_every_listed_model(
    monkeypatch: pytest.MonkeyPatch,
) -> None:
    import litellm
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
    from litellm.types.router import LiteLLM_Params

    monkeypatch.setattr(litellm, "check_provider_endpoint", True)
    monkeypatch.delenv("AWS_BEARER_TOKEN_BEDROCK", raising=False)
    region: Final = "ca-central-1"
    respx.get(
        f"https://bedrock.{region}.amazonaws.com/foundation-models", params={"byInferenceType": "ON_DEMAND"}
    ).mock(
        return_value=httpx.Response(
            200,
            json={
                "modelSummaries": [
                    {"modelId": "anthropic.claude-haiku-4-5-20251001-v1:0"},
                    {"modelId": "amazon.nova-micro-v1:0"},
                ]
            },
        )
    )
    respx.get(
        f"https://bedrock.{region}.amazonaws.com/inference-profiles", params={"typeEquals": "SYSTEM_DEFINED"}
    ).mock(
        return_value=httpx.Response(
            200,
            json={
                "inferenceProfileSummaries": [
                    {"inferenceProfileId": "us.anthropic.claude-haiku-4-5-20251001-v1:0", "status": "ACTIVE"}
                ]
            },
        )
    )
    deployment: Final = LiteLLM_Params(
        model="bedrock/*",
        aws_access_key_id="AKIACUSTOMPREFIXACCOUNT",
        aws_secret_access_key="custom-prefix-secret",
        aws_region_name=region,
    )

    assert get_known_models_from_wildcard("anthropic/*", deployment) == [
        "anthropic/amazon.nova-micro-v1:0",
        "anthropic/anthropic.claude-haiku-4-5-20251001-v1:0",
        "anthropic/us.anthropic.claude-haiku-4-5-20251001-v1:0",
    ]


@contextmanager
def _registered_chat_models(provider_by_model: Mapping[str, str]) -> Generator[None, None, None]:
    import litellm

    litellm.register_model(
        {model: {"litellm_provider": provider, "mode": "chat"} for model, provider in provider_by_model.items()},
        persist_across_reloads=False,
    )
    try:
        yield
    finally:
        provider_model_sets: Final = tuple(known for known in vars(litellm).values() if isinstance(known, set))
        for model in provider_by_model:
            litellm.model_cost.pop(model, None)
            for provider_models in provider_model_sets:
                provider_models.discard(model)
        litellm.add_known_models(model_cost_map={})


@pytest.mark.parametrize(
    ("wildcard", "deployment_model", "catalog", "expected"),
    [
        pytest.param(
            "cloudflare/@cf/partial-wildcard-org/*",
            "cloudflare/@cf/partial-wildcard-org/*",
            ("cloudflare/@cf/partial-wildcard-org/model-a", "cloudflare/@hf/partial-wildcard-org/model-b"),
            ["cloudflare/@cf/partial-wildcard-org/model-a"],
            id="prefixed-catalog-with-deployment",
        ),
        pytest.param(
            "cloudflare/@cf/partial-wildcard-org/*",
            None,
            ("cloudflare/@cf/partial-wildcard-org/model-a", "cloudflare/@hf/partial-wildcard-org/model-b"),
            ["cloudflare/@cf/partial-wildcard-org/model-a"],
            id="prefixed-catalog-without-deployment",
        ),
        pytest.param(
            "gemini/gemini-partial-wildcard-9*",
            "gemini/gemini-partial-wildcard-9*",
            (
                "gemini-partial-wildcard-9-flash",
                "gemini/gemini-partial-wildcard-9-pro",
                "gemini/gemini-other-partial-wildcard-9",
            ),
            ["gemini/gemini-partial-wildcard-9-flash", "gemini/gemini-partial-wildcard-9-pro"],
            id="mixed-bare-and-prefixed-catalog",
        ),
    ],
)
def test_partial_wildcard_lists_catalog_ids_stored_with_the_provider_prefix(
    wildcard: str, deployment_model: str | None, catalog: tuple[str, ...], expected: list[str]
) -> None:
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
    from litellm.types.router import LiteLLM_Params

    provider: Final = wildcard.split("/", 1)[0]
    deployment: Final = None if deployment_model is None else LiteLLM_Params(model=deployment_model)
    with _registered_chat_models(dict.fromkeys(catalog, provider)):
        listed: Final = get_known_models_from_wildcard(wildcard, deployment)

    assert sorted(listed) == expected


@pytest.mark.parametrize(
    ("provider", "routing_segment"), [("bedrock", "converse"), ("bedrock", "us-east-1"), ("openai", "responses")]
)
def test_routing_segment_lists_the_same_catalog_ids_as_the_bare_provider_wildcard(
    provider: str, routing_segment: str
) -> None:
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
    from litellm.types.router import LiteLLM_Params

    bare_listing: Final = get_known_models_from_wildcard(f"{provider}/*", LiteLLM_Params(model=f"{provider}/*"))
    routed_listing: Final = get_known_models_from_wildcard(
        f"{provider}/*", LiteLLM_Params(model=f"{provider}/{routing_segment}/*")
    )

    assert bare_listing
    assert sorted(routed_listing) == sorted(bare_listing)


def test_provider_wildcard_lists_cost_map_models_but_not_pricing_tiers() -> None:
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard

    model_id: Final = "together_ai/partial-wildcard-org/model-t"
    pricing_tier: Final = "together-ai-partial-wildcard-tier"
    with _registered_chat_models({model_id: "together_ai", pricing_tier: "together_ai"}):
        listed: Final = get_known_models_from_wildcard("together_ai/*")

    assert model_id in listed
    assert [listed_id for listed_id in listed if pricing_tier in listed_id] == []


def test_provider_wildcard_stops_listing_a_cost_map_model_once_it_is_retired() -> None:
    import litellm
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard

    model_id: Final = "together_ai/partial-wildcard-org/model-retired"
    with _registered_chat_models({model_id: "together_ai"}):
        listed_while_served: Final = get_known_models_from_wildcard("together_ai/*")
        litellm.add_known_models({model_id: {"litellm_provider": "together_ai", "deprecation_date": "2000-01-01"}})
        listed_once_retired: Final = get_known_models_from_wildcard("together_ai/*")

    assert model_id in listed_while_served
    assert model_id not in listed_once_retired


_ROUTE_CF_ID: Final = "cloudflare/@cf/partial-route-org/model-a-instruct"
_ROUTE_CF_SUFFIXED_ID: Final = "cloudflare/@cf/partial-route-org/model-b-instruct-v2"
_ROUTE_HF_ID: Final = "cloudflare/@hf/partial-route-org/model-c"
_ROUTE_GEMINI_ID: Final = "gemini-partial-route-9-flash"
_ROUTE_OPENAI_ID: Final = "gpt-partial-route-9-mini"
_ROUTE_BEDROCK_ID: Final = "anthropic.partial-route-9-v1:0"
_ROUTE_TOGETHER_ID: Final = "together_ai/partial-route-org/model-t"
_ROUTE_CF_IDS: Final = {_ROUTE_CF_ID, _ROUTE_CF_SUFFIXED_ID}


@pytest.mark.parametrize(
    ("model_name", "deployment_model", "key_model", "reachable"),
    [
        pytest.param("cloudflare/@cf/*", "cloudflare/@cf/*", None, _ROUTE_CF_IDS, id="filter"),
        pytest.param(
            "cloudflare/@cf/*-instruct", "cloudflare/@cf/*-instruct", None, {_ROUTE_CF_ID}, id="filter-with-suffix"
        ),
        pytest.param(
            "cloudflare/@cf/*",
            "cloudflare/*",
            None,
            {*_ROUTE_CF_IDS, _ROUTE_HF_ID},
            id="alias-whose-prefix-matches-catalog-ids",
        ),
        pytest.param("cloudflare/team-*", "cloudflare/*", None, {*_ROUTE_CF_IDS, _ROUTE_HF_ID}, id="alias"),
        pytest.param("cloudflare/cf-*", "cloudflare/@cf/*", None, _ROUTE_CF_IDS, id="alias-over-partial-deployment"),
        pytest.param("my-cf/*", "cloudflare/@cf/*", None, _ROUTE_CF_IDS, id="bare-alias-over-partial-deployment"),
        pytest.param(
            "cloudflare/team-*", "cloudflare/@cf/*/*", None, set(), id="alias-with-fewer-wildcards-than-its-deployment"
        ),
        pytest.param("partial-route-v/*/*", "cloudflare/@cf/*/*", None, _ROUTE_CF_IDS, id="multi-wildcard-alias"),
        pytest.param(
            "partial-route-v/*-*", "cloudflare/@cf/*/*", None, set(), id="multi-wildcard-alias-routing-splits-elsewhere"
        ),
        pytest.param(
            "partial-route-team/*", "openai/gpt-partial-route-9*", None, set(), id="alias-over-mid-word-deployment"
        ),
        pytest.param(
            "team/gpt-partial-route-9*",
            "openai/gpt-partial-route-9*",
            None,
            {f"openai/{_ROUTE_OPENAI_ID}"},
            id="alias-repeating-the-deployment-partial-word",
        ),
        pytest.param(
            "team/gpt-partial-route-9-prod*",
            "openai/gpt-partial-route-9*",
            None,
            {f"openai/{_ROUTE_OPENAI_ID}"},
            id="alias-extending-the-deployment-partial-word",
        ),
        pytest.param(
            "partial-route-g/*",
            "gemini/gemini-partial-route-*",
            None,
            {_ROUTE_GEMINI_ID},
            id="alias-over-deployment-cut-at-a-word-boundary",
        ),
        pytest.param(
            "cloudflare/*", "cloudflare/*", "cloudflare/@cf/*", _ROUTE_CF_IDS, id="key-filter-over-provider-wildcard"
        ),
        pytest.param("gemini/gemini-*", "gemini/*", None, {_ROUTE_GEMINI_ID}, id="alias-over-bare-id"),
        pytest.param(
            "gemini/*", "gemini/*", "gemini/gemini-partial-route-9*", {_ROUTE_GEMINI_ID}, id="key-filter-over-bare-id"
        ),
        pytest.param(
            "openai/*", "openai/responses/*", None, {f"openai/responses/{_ROUTE_OPENAI_ID}"}, id="responses-route"
        ),
        pytest.param(
            "openai/*",
            "openai/responses/*",
            "openai/gpt-partial-route-9*",
            {f"openai/responses/{_ROUTE_OPENAI_ID}"},
            id="key-filter-over-responses-route",
        ),
        pytest.param(
            "bedrock/*", "bedrock/converse/*", None, {f"bedrock/converse/{_ROUTE_BEDROCK_ID}"}, id="converse-route"
        ),
        pytest.param(
            "openai/partial-route-org/*",
            "openai/partial-route-org/*",
            None,
            set(),
            id="same-name-namespace-the-catalog-lacks",
        ),
        pytest.param(
            "together/*", "together_ai/partial-route-missing-org/*", None, set(), id="alias-over-org-the-catalog-lacks"
        ),
        pytest.param(
            "openai/*",
            "openai/chat_completions/*",
            None,
            {f"openai/chat_completions/{_ROUTE_OPENAI_ID}"},
            id="chat-completions-bridge-route",
        ),
        pytest.param(
            "bedrock/*", "bedrock/llama/*", None, {f"bedrock/llama/{_ROUTE_BEDROCK_ID}"}, id="invoke-format-route"
        ),
        pytest.param(
            "together/*",
            "together_ai/partial-route-org/*",
            None,
            {_ROUTE_TOGETHER_ID},
            id="alias-over-org-a-cost-map-catalog-carries",
        ),
        pytest.param(
            "bedrock/*", "bedrock/us-east-1/*", None, {f"bedrock/us-east-1/{_ROUTE_BEDROCK_ID}"}, id="region-route"
        ),
        pytest.param(
            "*", "openai/*", "openai/gpt-partial-route-9*", set(), id="provider-prefixed-key-filter-over-catch-all"
        ),
        pytest.param(
            "gpt-partial-route-*",
            "openai/gpt-partial-route-*",
            None,
            {f"openai/{_ROUTE_OPENAI_ID}"},
            id="slashless-name-repeating-the-deployment-partial-word",
        ),
        pytest.param("team-*", "cloudflare/@cf/*", None, _ROUTE_CF_IDS, id="slashless-alias-over-partial-deployment"),
        pytest.param(
            "team-*", "openai/*", None, {f"openai/{_ROUTE_OPENAI_ID}"}, id="slashless-alias-over-provider-catch-all"
        ),
        pytest.param(
            "team-*", "cloudflare/@cf/*/*", None, set(), id="slashless-alias-with-fewer-wildcards-than-its-deployment"
        ),
        pytest.param(
            "*partial-route-9*",
            "openai/gpt-partial-route-9*",
            None,
            {f"openai/{_ROUTE_OPENAI_ID}"},
            id="slashless-name-with-more-wildcards-than-its-deployment",
        ),
        pytest.param(
            "gemini/*partial-route-9*",
            "gemini/gemini-*",
            None,
            {_ROUTE_GEMINI_ID},
            id="slashed-name-with-more-wildcards-than-its-deployment",
        ),
        pytest.param("*", "cloudflare/@cf/*", None, _ROUTE_CF_IDS, id="catch-all-over-partial-deployment"),
        pytest.param("*", "gemini/gemini-partial-route-9*", None, set(), id="catch-all-over-mid-word-deployment"),
        pytest.param("*", "openai/responses/gpt-partial-route-9*", None, set(), id="catch-all-over-mid-word-route"),
        pytest.param(
            "*", "gemini/gemini-partial-route-9-flash*", None, set(), id="catch-all-whose-only-match-is-its-fixed-text"
        ),
    ],
)
def test_every_listed_partial_wildcard_id_routes_to_the_catalog_model_it_names(
    model_name: str, deployment_model: str, key_model: str | None, reachable: set[str]
) -> None:
    from pydantic import TypeAdapter

    from litellm import Router
    from litellm.proxy.auth.model_checks import expand_wildcard_deployments_for_model_info, get_complete_model_list
    from litellm.types.router import LiteLLM_Params

    routed_params: Final = TypeAdapter(tuple[LiteLLM_Params, ...])
    router: Final = Router(model_list=[{"model_name": model_name, "litellm_params": {"model": deployment_model}}])

    def routed_model(listed_id: str) -> str:
        routed: Final = routed_params.validate_python(
            tuple(deployment["litellm_params"] for deployment in router.wildcard_route_deployments(listed_id, None))
        )
        return routed[0].model if routed else listed_id

    def routed_catalog_ids(listed: list[str]) -> list[str]:
        routed_models: Final = [routed_model(listed_id) for listed_id in listed]
        return sorted(
            routed.removeprefix("gemini/") if routed.startswith("gemini/gemini-") else routed
            for routed in routed_models
            if "partial-route" in routed
        )

    with _registered_chat_models(
        {
            _ROUTE_CF_ID: "cloudflare",
            _ROUTE_CF_SUFFIXED_ID: "cloudflare",
            _ROUTE_HF_ID: "cloudflare",
            _ROUTE_GEMINI_ID: "gemini",
            _ROUTE_OPENAI_ID: "openai",
            _ROUTE_BEDROCK_ID: "bedrock",
            _ROUTE_TOGETHER_ID: "together_ai",
        }
    ):
        v1_models: Final = get_complete_model_list(
            key_models=[key_model or model_name],
            team_models=[],
            proxy_model_list=[model_name],
            user_model=None,
            infer_model_from_keys=False,
            llm_router=router,
        )
        model_info_names: Final = [
            str(row["model_name"])
            for row in expand_wildcard_deployments_for_model_info(
                [dict(deployment) for deployment in router.get_model_list() or []], router
            )
            if row["model_name"] != model_name
        ]
        listed_v1_models: Final = routed_catalog_ids(v1_models)
        listed_model_info_names: Final = routed_catalog_ids(model_info_names)

    unrouted_ids: Final = [
        listed_id
        for listed_id in [*v1_models, *model_info_names]
        if not router.wildcard_route_deployments(listed_id, None)
    ]
    assert unrouted_ids == []
    assert all(v1_models) and all(model_info_names)
    if model_name == "*":
        assert [listed_id for listed_id in v1_models if not routed_model(listed_id).endswith(f"/{listed_id}")] == []
    assert listed_v1_models == sorted(reachable)
    if key_model is None:
        assert listed_model_info_names == sorted(reachable)


@pytest.mark.parametrize(
    ("model_name", "expected_v1_models"),
    [
        pytest.param("azure/*", [f"azure/{AZURE_MODEL_PLACEHOLDER}"], id="provider-wildcard-lists-as-before"),
        pytest.param("*", [AZURE_MODEL_PLACEHOLDER], id="catch-all-lists-as-before"),
        pytest.param("my-*", [], id="slashless-alias-skips-the-placeholder"),
    ],
)
def test_only_slashless_azure_wildcards_skip_the_catalog_placeholder(
    model_name: str, expected_v1_models: list[str]
) -> None:
    from litellm import Router
    from litellm.proxy.auth.model_checks import expand_wildcard_deployments_for_model_info, get_complete_model_list

    router: Final = Router(model_list=[{"model_name": model_name, "litellm_params": {"model": "azure/*"}}])

    v1_models: Final = get_complete_model_list(
        key_models=[],
        team_models=[],
        proxy_model_list=[model_name],
        user_model=None,
        infer_model_from_keys=False,
        llm_router=router,
    )
    model_info_names: Final = [
        str(row["model_name"])
        for row in expand_wildcard_deployments_for_model_info(
            [dict(deployment) for deployment in router.get_model_list() or []], router
        )
    ]

    assert v1_models == expected_v1_models
    assert model_info_names == (expected_v1_models or [model_name])


@pytest.mark.parametrize(
    ("model_name", "deployment_model"),
    [
        pytest.param("gpt-*", "gpt-*", id="same-wildcards-as-its-deployment"),
        pytest.param("*gpt-5*", "gpt-5*", id="more-wildcards-than-its-deployment"),
    ],
)
def test_slashless_wildcard_over_a_bare_deployment_lists_its_custom_llm_provider_catalog(
    model_name: str, deployment_model: str
) -> None:
    from fnmatch import fnmatchcase

    from litellm import Router
    from litellm.proxy.auth.model_checks import expand_wildcard_deployments_for_model_info, get_complete_model_list
    from litellm.utils import get_valid_models

    router: Final = Router(
        model_list=[
            {
                "model_name": model_name,
                "litellm_params": {"model": deployment_model, "custom_llm_provider": "openai", "api_key": "sk-test"},
            }
        ]
    )

    v1_models: Final = get_complete_model_list(
        key_models=[],
        team_models=[],
        proxy_model_list=[model_name],
        user_model=None,
        infer_model_from_keys=False,
        llm_router=router,
    )
    model_info_rows: Final = expand_wildcard_deployments_for_model_info(
        [dict(deployment) for deployment in router.get_model_list() or []], router
    )
    openai_ids: Final = frozenset(model.removeprefix("openai/") for model in get_valid_models(custom_llm_provider="openai"))
    routed_models: Final = {
        listed_id: [deployment["litellm_params"]["model"] for deployment in router.wildcard_route_deployments(listed_id, None)]
        for listed_id in v1_models
    }

    assert v1_models
    assert [
        listed_id for listed_id in v1_models if listed_id not in openai_ids or not fnmatchcase(listed_id, model_name)
    ] == []
    assert {listed_id: models for listed_id, models in routed_models.items() if models != [listed_id]} == {}
    assert sorted(str(row["model_name"]) for row in model_info_rows) == sorted(v1_models)
    assert [row for row in model_info_rows if row["litellm_params"]["model"] != row["model_name"]] == []


@pytest.mark.parametrize(
    ("model_name", "deployment_model"),
    [
        pytest.param("*", "*", id="catch-all-over-a-bare-catch-all"),
        pytest.param("foo/gpt-*", "gpt-*", id="slashed-name-over-a-bare-deployment"),
        pytest.param("gpt-*", "openai/gpt-*", id="slashless-name-over-a-provider-prefixed-deployment"),
    ],
)
def test_custom_llm_provider_changes_no_listing_outside_slashless_names_over_bare_deployments(
    model_name: str, deployment_model: str
) -> None:
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
    from litellm.types.router import LiteLLM_Params

    with_provider: Final = get_known_models_from_wildcard(
        model_name, LiteLLM_Params(model=deployment_model, custom_llm_provider="openai")
    )
    without_provider: Final = get_known_models_from_wildcard(model_name, LiteLLM_Params(model=deployment_model))

    assert with_provider == without_provider


def test_inference_provider_route_lists_every_id_the_plain_provider_wildcard_lists() -> None:
    from litellm.proxy.auth.model_checks import get_known_models_from_wildcard
    from litellm.types.router import LiteLLM_Params

    plain: Final = get_known_models_from_wildcard("huggingface/*", LiteLLM_Params(model="huggingface/*"))
    routed: Final = get_known_models_from_wildcard(
        "huggingface/*", LiteLLM_Params(model="huggingface/featherless-ai/*")
    )

    assert plain
    assert [model for model in plain if "/" not in model.removeprefix("huggingface/")] == []
    assert sorted(routed) == sorted(plain)


def test_catch_all_lists_no_id_a_more_specific_sibling_wildcard_routes_elsewhere() -> None:
    from litellm import Router
    from litellm.proxy.auth.model_checks import expand_wildcard_deployments_for_model_info, get_complete_model_list

    unshadowed_id: Final = "cloudflare/@cf/unshadowed-route-org/model-d"
    router: Final = Router(
        model_list=[
            {"model_name": "*", "litellm_params": {"model": "cloudflare/@cf/*"}},
            {"model_name": "partial-route-org/*", "litellm_params": {"model": "openai/*"}},
        ]
    )

    def routed_models(listed: list[str]) -> dict[str, object]:
        return {
            listed_id: router.wildcard_route_deployments(listed_id, None)[0]["litellm_params"]["model"]
            for listed_id in listed
            if "route-org/model-" in listed_id
        }

    with _registered_chat_models(
        {_ROUTE_CF_ID: "cloudflare", _ROUTE_CF_SUFFIXED_ID: "cloudflare", unshadowed_id: "cloudflare"}
    ):
        v1_models: Final = get_complete_model_list(
            key_models=[],
            team_models=[],
            proxy_model_list=["*", "partial-route-org/*"],
            user_model=None,
            infer_model_from_keys=False,
            llm_router=router,
        )
        model_info_names: Final = [
            str(row["model_name"])
            for row in expand_wildcard_deployments_for_model_info(
                [dict(deployment) for deployment in router.get_model_list() or []], router
            )
        ]

    assert routed_models(v1_models) == {"unshadowed-route-org/model-d": unshadowed_id}
    assert routed_models(model_info_names) == {"unshadowed-route-org/model-d": unshadowed_id}


def test_wildcard_lists_an_id_a_more_specific_sibling_serves_with_the_same_model() -> None:
    from litellm import Router
    from litellm.proxy.auth.model_checks import expand_wildcard_deployments_for_model_info, get_complete_model_list

    router: Final = Router(
        model_list=[
            {"model_name": "openai/gpt-partial-route-9*", "litellm_params": {"model": "openai/gpt-partial-route-9*"}},
            {
                "model_name": "openai/gpt-partial-route-9-mini*",
                "litellm_params": {"model": "openai/gpt-partial-route-9-mini*"},
            },
        ]
    )
    with _registered_chat_models({_ROUTE_OPENAI_ID: "openai"}):
        v1_models: Final = get_complete_model_list(
            key_models=["openai/gpt-partial-route-9*"],
            team_models=[],
            proxy_model_list=["openai/gpt-partial-route-9*", "openai/gpt-partial-route-9-mini*"],
            user_model=None,
            infer_model_from_keys=False,
            llm_router=router,
        )
        model_info_names: Final = [
            str(row["model_name"])
            for row in expand_wildcard_deployments_for_model_info(
                [dict(deployment) for deployment in router.get_model_list() or []], router
            )
        ]

    assert v1_models == [f"openai/{_ROUTE_OPENAI_ID}"]
    assert "openai/gpt-partial-route-9*" not in model_info_names


def test_prefixed_alias_over_a_bare_catch_all_lists_ids_that_route_through_it(monkeypatch: pytest.MonkeyPatch) -> None:
    from litellm import Router
    from litellm.proxy.auth.model_checks import get_complete_model_list

    monkeypatch.setenv("OPENAI_API_KEY", "sk-partial-route-test")
    router: Final = Router(model_list=[{"model_name": "team-partial-route/*", "litellm_params": {"model": "*"}}])
    with _registered_chat_models({_ROUTE_OPENAI_ID: "openai"}):
        v1_models: Final = get_complete_model_list(
            key_models=[],
            team_models=[],
            proxy_model_list=["team-partial-route/*"],
            user_model=None,
            infer_model_from_keys=False,
            llm_router=router,
        )

    unrouted_ids: Final = [
        listed_id for listed_id in v1_models if not router.wildcard_route_deployments(listed_id, None)
    ]
    assert f"team-partial-route/{_ROUTE_OPENAI_ID}" in v1_models
    assert unrouted_ids == []