forked from phoenix-oss/llama-stack-mirror
125 lines
3.8 KiB
Python
125 lines
3.8 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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import os
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import pytest
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import pytest_asyncio
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from llama_stack.distribution.datatypes import Api, Provider
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from llama_stack.providers.adapters.inference.fireworks import FireworksImplConfig
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from llama_stack.providers.adapters.inference.ollama import OllamaImplConfig
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from llama_stack.providers.adapters.inference.together import TogetherImplConfig
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from llama_stack.providers.impls.meta_reference.inference import (
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MetaReferenceInferenceConfig,
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)
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from llama_stack.providers.tests.resolver import resolve_impls_for_test_v2
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from ..conftest import ProviderFixture, remote_stack_fixture
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from ..env import get_env_or_fail
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@pytest.fixture(scope="session")
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def inference_model(request):
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if hasattr(request, "param"):
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return request.param
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return request.config.getoption("--inference-model", None)
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@pytest.fixture(scope="session")
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def inference_remote() -> ProviderFixture:
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return remote_stack_fixture()
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@pytest.fixture(scope="session")
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def inference_meta_reference(inference_model) -> ProviderFixture:
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inference_model = (
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[inference_model] if isinstance(inference_model, str) else inference_model
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)
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return ProviderFixture(
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providers=[
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Provider(
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provider_id=f"meta-reference-{i}",
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provider_type="meta-reference",
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config=MetaReferenceInferenceConfig(
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model=m,
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max_seq_len=4096,
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create_distributed_process_group=False,
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checkpoint_dir=os.getenv("MODEL_CHECKPOINT_DIR", None),
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).model_dump(),
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)
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for i, m in enumerate(inference_model)
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]
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)
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@pytest.fixture(scope="session")
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def inference_ollama(inference_model) -> ProviderFixture:
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inference_model = (
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[inference_model] if isinstance(inference_model, str) else inference_model
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)
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if "Llama3.1-8B-Instruct" in inference_model:
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pytest.skip("Ollama only supports Llama3.2-3B-Instruct for testing")
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return ProviderFixture(
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providers=[
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Provider(
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provider_id="ollama",
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provider_type="remote::ollama",
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config=OllamaImplConfig(
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host="localhost", port=os.getenv("OLLAMA_PORT", 11434)
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).model_dump(),
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)
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],
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)
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@pytest.fixture(scope="session")
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def inference_fireworks() -> ProviderFixture:
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return ProviderFixture(
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providers=[
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Provider(
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provider_id="fireworks",
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provider_type="remote::fireworks",
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config=FireworksImplConfig(
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api_key=get_env_or_fail("FIREWORKS_API_KEY"),
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).model_dump(),
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)
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],
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)
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@pytest.fixture(scope="session")
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def inference_together() -> ProviderFixture:
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return ProviderFixture(
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providers=[
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Provider(
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provider_id="together",
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provider_type="remote::together",
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config=TogetherImplConfig().model_dump(),
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)
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],
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provider_data=dict(
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together_api_key=get_env_or_fail("TOGETHER_API_KEY"),
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),
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)
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INFERENCE_FIXTURES = ["meta_reference", "ollama", "fireworks", "together", "remote"]
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@pytest_asyncio.fixture(scope="session")
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async def inference_stack(request):
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fixture_name = request.param
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inference_fixture = request.getfixturevalue(f"inference_{fixture_name}")
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impls = await resolve_impls_for_test_v2(
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[Api.inference],
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{"inference": inference_fixture.providers},
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inference_fixture.provider_data,
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)
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return (impls[Api.inference], impls[Api.models])
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