forked from phoenix-oss/llama-stack-mirror
09269e2a44
# What does this PR do? This is a follow-up to #425. That PR allows for specifying models in the registry, but each entry needs to look like: ```yaml - identifier: ... provider_id: ... provider_resource_identifier: ... ``` This is headache-inducing. The current PR makes this situation better by adopting the shape of our APIs. Namely, we need the user to only specify `model-id`. The rest should be optional and figured out by the Stack. You can always override it. Here's what example `ollama` "full stack" registry looks like (we still need to kill or simplify shield_type crap): ```yaml models: - model_id: Llama3.2-3B-Instruct - model_id: Llama-Guard-3-1B shields: - shield_id: llama_guard shield_type: llama_guard ``` ## Test Plan See test plan for #425. Re-ran it.
92 lines
3 KiB
Python
92 lines
3 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 tempfile
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import pytest
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import pytest_asyncio
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from llama_stack.apis.models import ModelInput
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from llama_stack.distribution.datatypes import Api, Provider
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from llama_stack.providers.inline.agents.meta_reference import (
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MetaReferenceAgentsImplConfig,
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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 llama_stack.providers.utils.kvstore.config import SqliteKVStoreConfig
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from ..conftest import ProviderFixture, remote_stack_fixture
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from ..safety.fixtures import get_shield_to_register
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def pick_inference_model(inference_model):
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# This is not entirely satisfactory. The fixture `inference_model` can correspond to
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# multiple models when you need to run a safety model in addition to normal agent
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# inference model. We filter off the safety model by looking for "Llama-Guard"
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if isinstance(inference_model, list):
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inference_model = next(m for m in inference_model if "Llama-Guard" not in m)
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assert inference_model is not None
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return inference_model
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@pytest.fixture(scope="session")
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def agents_remote() -> ProviderFixture:
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return remote_stack_fixture()
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@pytest.fixture(scope="session")
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def agents_meta_reference() -> ProviderFixture:
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sqlite_file = tempfile.NamedTemporaryFile(delete=False, suffix=".db")
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return ProviderFixture(
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providers=[
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Provider(
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provider_id="meta-reference",
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provider_type="meta-reference",
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config=MetaReferenceAgentsImplConfig(
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# TODO: make this an in-memory store
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persistence_store=SqliteKVStoreConfig(
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db_path=sqlite_file.name,
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),
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).model_dump(),
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)
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],
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)
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AGENTS_FIXTURES = ["meta_reference", "remote"]
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@pytest_asyncio.fixture(scope="session")
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async def agents_stack(request, inference_model, safety_model):
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fixture_dict = request.param
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providers = {}
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provider_data = {}
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for key in ["inference", "safety", "memory", "agents"]:
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fixture = request.getfixturevalue(f"{key}_{fixture_dict[key]}")
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providers[key] = fixture.providers
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if fixture.provider_data:
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provider_data.update(fixture.provider_data)
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shield_input = get_shield_to_register(
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providers["safety"][0].provider_type, safety_model
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)
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inference_models = (
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inference_model if isinstance(inference_model, list) else [inference_model]
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)
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impls = await resolve_impls_for_test_v2(
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[Api.agents, Api.inference, Api.safety, Api.memory],
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providers,
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provider_data,
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models=[
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ModelInput(
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model_id=model,
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)
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for model in inference_models
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],
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shields=[shield_input],
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)
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return impls[Api.agents], impls[Api.memory]
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