mirror of
https://github.com/BerriAI/litellm.git
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56 lines
1.7 KiB
Python
56 lines
1.7 KiB
Python
from __future__ import annotations
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from collections.abc import Callable, Iterator
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from dataclasses import dataclass
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from typing import Final
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import pytest
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from cli_harness.rate_limiter import get_default_limiter
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from codex.harness import CodexHarness, codex_harness
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from codex.setups import Deployment, ModelSetup
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from e2e_config import PROXY_BASE_URL, unique_marker
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from lifecycle import ResourceManager
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from models import LiteLLMParamsBody
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from proxy_client import ProxyClient
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@dataclass(frozen=True, slots=True)
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class _Client:
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proxy: ProxyClient
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@pytest.fixture(scope="session")
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def client(proxy: ProxyClient) -> _Client:
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return _Client(proxy)
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@pytest.fixture
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def register_model(proxy: ProxyClient, resources: ResourceManager) -> Callable[[LiteLLMParamsBody], str]:
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def register(litellm_params: LiteLLMParamsBody) -> str:
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model: Final = f"e2e-codex-{unique_marker()}"
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model_id: Final = proxy.create_model(model, litellm_params, provider_live=True)
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resources.defer(lambda: proxy.delete_model(model_id))
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return model
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return register
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@pytest.fixture
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def setup(deployment: Deployment, register_model: Callable[[LiteLLMParamsBody], str]) -> ModelSetup:
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return ModelSetup(model=register_model(deployment.litellm_params), rate_bucket=deployment.rate_bucket)
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@pytest.fixture
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def key_models(setup: ModelSetup) -> tuple[str, ...]:
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return (setup.model,)
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@pytest.fixture
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def codex(setup: ModelSetup, key_models: tuple[str, ...], resources: ResourceManager) -> Iterator[CodexHarness]:
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with codex_harness(
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gateway=PROXY_BASE_URL,
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api_key=resources.key(models=list(key_models), user_id=None),
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rate_bucket=setup.rate_bucket,
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limiter=get_default_limiter(),
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) as harness:
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yield harness
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