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chore: Adding Access Control for OpenAI Vector Stores methods (#2772)
# What does this PR do? Refactors the vector store routing logic by moving OpenAI-compatible vector store operations from the `VectorIORouter` to the `VectorDBsRoutingTable`. Closes https://github.com/meta-llama/llama-stack/issues/2761 ## Test Plan Added unit tests to cover new routing logic and ACL checks. --------- Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
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parent
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commit
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6 changed files with 450 additions and 77 deletions
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@ -11,17 +11,15 @@ from unittest.mock import AsyncMock
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from llama_stack.apis.common.type_system import NumberType
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from llama_stack.apis.datasets.datasets import Dataset, DatasetPurpose, URIDataSource
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from llama_stack.apis.datatypes import Api
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from llama_stack.apis.models import Model, ModelType
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from llama_stack.apis.models import Model
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from llama_stack.apis.shields.shields import Shield
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from llama_stack.apis.tools import ListToolDefsResponse, ToolDef, ToolGroup, ToolParameter
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from llama_stack.apis.vector_dbs.vector_dbs import VectorDB
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from llama_stack.distribution.routing_tables.benchmarks import BenchmarksRoutingTable
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from llama_stack.distribution.routing_tables.datasets import DatasetsRoutingTable
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from llama_stack.distribution.routing_tables.models import ModelsRoutingTable
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from llama_stack.distribution.routing_tables.scoring_functions import ScoringFunctionsRoutingTable
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from llama_stack.distribution.routing_tables.shields import ShieldsRoutingTable
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from llama_stack.distribution.routing_tables.toolgroups import ToolGroupsRoutingTable
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from llama_stack.distribution.routing_tables.vector_dbs import VectorDBsRoutingTable
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class Impl:
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@ -54,17 +52,6 @@ class SafetyImpl(Impl):
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return shield
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class VectorDBImpl(Impl):
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def __init__(self):
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super().__init__(Api.vector_io)
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async def register_vector_db(self, vector_db: VectorDB):
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return vector_db
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async def unregister_vector_db(self, vector_db_id: str):
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return vector_db_id
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class DatasetsImpl(Impl):
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def __init__(self):
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super().__init__(Api.datasetio)
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@ -173,36 +160,6 @@ async def test_shields_routing_table(cached_disk_dist_registry):
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assert "test-shield-2" in shield_ids
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async def test_vectordbs_routing_table(cached_disk_dist_registry):
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table = VectorDBsRoutingTable({"test_provider": VectorDBImpl()}, cached_disk_dist_registry, {})
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await table.initialize()
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m_table = ModelsRoutingTable({"test_provider": InferenceImpl()}, cached_disk_dist_registry, {})
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await m_table.initialize()
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await m_table.register_model(
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model_id="test-model",
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provider_id="test_provider",
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metadata={"embedding_dimension": 128},
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model_type=ModelType.embedding,
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)
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# Register multiple vector databases and verify listing
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await table.register_vector_db(vector_db_id="test-vectordb", embedding_model="test-model")
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await table.register_vector_db(vector_db_id="test-vectordb-2", embedding_model="test-model")
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vector_dbs = await table.list_vector_dbs()
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assert len(vector_dbs.data) == 2
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vector_db_ids = {v.identifier for v in vector_dbs.data}
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assert "test-vectordb" in vector_db_ids
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assert "test-vectordb-2" in vector_db_ids
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await table.unregister_vector_db(vector_db_id="test-vectordb")
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await table.unregister_vector_db(vector_db_id="test-vectordb-2")
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vector_dbs = await table.list_vector_dbs()
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assert len(vector_dbs.data) == 0
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async def test_datasets_routing_table(cached_disk_dist_registry):
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table = DatasetsRoutingTable({"localfs": DatasetsImpl()}, cached_disk_dist_registry, {})
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await table.initialize()
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5
tests/unit/distribution/routing_tables/__init__.py
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5
tests/unit/distribution/routing_tables/__init__.py
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@ -0,0 +1,5 @@
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# 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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274
tests/unit/distribution/routing_tables/test_vector_dbs.py
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274
tests/unit/distribution/routing_tables/test_vector_dbs.py
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@ -0,0 +1,274 @@
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# 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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# Unit tests for the routing tables vector_dbs
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import time
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from unittest.mock import AsyncMock
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import pytest
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from llama_stack.apis.datatypes import Api
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from llama_stack.apis.models import ModelType
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from llama_stack.apis.vector_dbs.vector_dbs import VectorDB
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from llama_stack.apis.vector_io.vector_io import (
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VectorStoreContent,
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VectorStoreDeleteResponse,
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VectorStoreFileContentsResponse,
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VectorStoreFileCounts,
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VectorStoreFileDeleteResponse,
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VectorStoreFileObject,
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VectorStoreObject,
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VectorStoreSearchResponsePage,
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)
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from llama_stack.distribution.access_control.datatypes import AccessRule, Scope
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from llama_stack.distribution.datatypes import User
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from llama_stack.distribution.request_headers import request_provider_data_context
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from llama_stack.distribution.routing_tables.vector_dbs import VectorDBsRoutingTable
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from tests.unit.distribution.routers.test_routing_tables import Impl, InferenceImpl, ModelsRoutingTable
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class VectorDBImpl(Impl):
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def __init__(self):
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super().__init__(Api.vector_io)
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async def register_vector_db(self, vector_db: VectorDB):
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return vector_db
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async def unregister_vector_db(self, vector_db_id: str):
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return vector_db_id
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async def openai_retrieve_vector_store(self, vector_store_id):
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return VectorStoreObject(
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id=vector_store_id,
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name="Test Store",
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created_at=int(time.time()),
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file_counts=VectorStoreFileCounts(completed=0, cancelled=0, failed=0, in_progress=0, total=0),
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)
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async def openai_update_vector_store(self, vector_store_id, **kwargs):
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return VectorStoreObject(
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id=vector_store_id,
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name="Updated Store",
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created_at=int(time.time()),
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file_counts=VectorStoreFileCounts(completed=0, cancelled=0, failed=0, in_progress=0, total=0),
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)
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async def openai_delete_vector_store(self, vector_store_id):
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return VectorStoreDeleteResponse(id=vector_store_id, object="vector_store.deleted", deleted=True)
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async def openai_search_vector_store(self, vector_store_id, query, **kwargs):
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return VectorStoreSearchResponsePage(
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object="vector_store.search_results.page", search_query="query", data=[], has_more=False, next_page=None
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)
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async def openai_attach_file_to_vector_store(self, vector_store_id, file_id, **kwargs):
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return VectorStoreFileObject(
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id=file_id,
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status="completed",
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chunking_strategy={"type": "auto"},
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created_at=int(time.time()),
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vector_store_id=vector_store_id,
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)
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async def openai_list_files_in_vector_store(self, vector_store_id, **kwargs):
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return [
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VectorStoreFileObject(
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id="1",
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status="completed",
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chunking_strategy={"type": "auto"},
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created_at=int(time.time()),
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vector_store_id=vector_store_id,
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)
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]
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async def openai_retrieve_vector_store_file(self, vector_store_id, file_id):
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return VectorStoreFileObject(
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id=file_id,
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status="completed",
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chunking_strategy={"type": "auto"},
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created_at=int(time.time()),
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vector_store_id=vector_store_id,
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)
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async def openai_retrieve_vector_store_file_contents(self, vector_store_id, file_id):
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return VectorStoreFileContentsResponse(
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file_id=file_id,
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filename="Sample File name",
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attributes={"key": "value"},
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content=[VectorStoreContent(type="text", text="Sample content")],
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)
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async def openai_update_vector_store_file(self, vector_store_id, file_id, **kwargs):
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return VectorStoreFileObject(
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id=file_id,
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status="completed",
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chunking_strategy={"type": "auto"},
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created_at=int(time.time()),
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vector_store_id=vector_store_id,
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)
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async def openai_delete_vector_store_file(self, vector_store_id, file_id):
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return VectorStoreFileDeleteResponse(id=file_id, deleted=True)
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async def test_vectordbs_routing_table(cached_disk_dist_registry):
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table = VectorDBsRoutingTable({"test_provider": VectorDBImpl()}, cached_disk_dist_registry, {})
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await table.initialize()
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m_table = ModelsRoutingTable({"test_provider": InferenceImpl()}, cached_disk_dist_registry, {})
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await m_table.initialize()
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await m_table.register_model(
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model_id="test-model",
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provider_id="test_provider",
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metadata={"embedding_dimension": 128},
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model_type=ModelType.embedding,
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)
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# Register multiple vector databases and verify listing
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await table.register_vector_db(vector_db_id="test-vectordb", embedding_model="test-model")
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await table.register_vector_db(vector_db_id="test-vectordb-2", embedding_model="test-model")
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vector_dbs = await table.list_vector_dbs()
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assert len(vector_dbs.data) == 2
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vector_db_ids = {v.identifier for v in vector_dbs.data}
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assert "test-vectordb" in vector_db_ids
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assert "test-vectordb-2" in vector_db_ids
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await table.unregister_vector_db(vector_db_id="test-vectordb")
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await table.unregister_vector_db(vector_db_id="test-vectordb-2")
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vector_dbs = await table.list_vector_dbs()
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assert len(vector_dbs.data) == 0
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async def test_openai_vector_stores_routing_table_roles(cached_disk_dist_registry):
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impl = VectorDBImpl()
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impl.openai_retrieve_vector_store = AsyncMock(return_value="OK")
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table = VectorDBsRoutingTable({"test_provider": impl}, cached_disk_dist_registry, policy=[])
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m_table = ModelsRoutingTable({"test_provider": InferenceImpl()}, cached_disk_dist_registry, policy=[])
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authorized_table = "vs1"
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authorized_team = "team1"
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unauthorized_team = "team2"
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await m_table.initialize()
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await m_table.register_model(
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model_id="test-model",
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provider_id="test_provider",
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metadata={"embedding_dimension": 128},
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model_type=ModelType.embedding,
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)
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authorized_user = User(principal="alice", attributes={"roles": [authorized_team]})
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with request_provider_data_context({}, authorized_user):
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_ = await table.register_vector_db(vector_db_id="vs1", embedding_model="test-model")
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# Authorized reader
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with request_provider_data_context({}, authorized_user):
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res = await table.openai_retrieve_vector_store(authorized_table)
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assert res == "OK"
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# Authorized updater
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impl.openai_update_vector_store_file = AsyncMock(return_value="UPDATED")
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with request_provider_data_context({}, authorized_user):
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res = await table.openai_update_vector_store_file(authorized_table, file_id="file1", attributes={"foo": "bar"})
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assert res == "UPDATED"
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# Unauthorized reader
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unauthorized_user = User(principal="eve", attributes={"roles": [unauthorized_team]})
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with request_provider_data_context({}, unauthorized_user):
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with pytest.raises(ValueError):
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await table.openai_retrieve_vector_store(authorized_table)
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# Unauthorized updater
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with request_provider_data_context({}, unauthorized_user):
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with pytest.raises(ValueError):
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await table.openai_update_vector_store_file(authorized_table, file_id="file1", attributes={"foo": "bar"})
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# Authorized deleter
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impl.openai_delete_vector_store_file = AsyncMock(return_value="DELETED")
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with request_provider_data_context({}, authorized_user):
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res = await table.openai_delete_vector_store_file(authorized_table, file_id="file1")
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assert res == "DELETED"
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# Unauthorized deleter
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with request_provider_data_context({}, unauthorized_user):
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with pytest.raises(ValueError):
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await table.openai_delete_vector_store_file(authorized_table, file_id="file1")
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async def test_openai_vector_stores_routing_table_actions(cached_disk_dist_registry):
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impl = VectorDBImpl()
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policy = [
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AccessRule(permit=Scope(actions=["create", "read", "update", "delete"]), when="user with admin in roles"),
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AccessRule(permit=Scope(actions=["read"]), when="user with reader in roles"),
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]
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table = VectorDBsRoutingTable({"test_provider": impl}, cached_disk_dist_registry, policy=policy)
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m_table = ModelsRoutingTable({"test_provider": InferenceImpl()}, cached_disk_dist_registry, policy=[])
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vector_db_id = "vs1"
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file_id = "file-1"
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admin_user = User(principal="admin", attributes={"roles": ["admin"]})
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read_only_user = User(principal="reader", attributes={"roles": ["reader"]})
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no_access_user = User(principal="outsider", attributes={"roles": ["no_access"]})
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await m_table.initialize()
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await m_table.register_model(
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model_id="test-model",
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provider_id="test_provider",
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metadata={"embedding_dimension": 128},
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model_type=ModelType.embedding,
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)
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with request_provider_data_context({}, admin_user):
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await table.register_vector_db(vector_db_id=vector_db_id, embedding_model="test-model")
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read_methods = [
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(table.openai_retrieve_vector_store, (vector_db_id,), {}),
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(table.openai_search_vector_store, (vector_db_id, "query"), {}),
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(table.openai_list_files_in_vector_store, (vector_db_id,), {}),
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(table.openai_retrieve_vector_store_file, (vector_db_id, file_id), {}),
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(table.openai_retrieve_vector_store_file_contents, (vector_db_id, file_id), {}),
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]
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update_methods = [
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(table.openai_update_vector_store, (vector_db_id,), {"name": "Updated DB"}),
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(table.openai_attach_file_to_vector_store, (vector_db_id, file_id), {}),
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(table.openai_update_vector_store_file, (vector_db_id, file_id), {"attributes": {"key": "value"}}),
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]
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delete_methods = [
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(table.openai_delete_vector_store_file, (vector_db_id, file_id), {}),
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(table.openai_delete_vector_store, (vector_db_id,), {}),
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]
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for user in [admin_user, read_only_user]:
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with request_provider_data_context({}, user):
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for method, args, kwargs in read_methods:
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result = await method(*args, **kwargs)
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assert result is not None, f"Read operation failed with user {user.principal}"
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with request_provider_data_context({}, no_access_user):
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for method, args, kwargs in read_methods:
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with pytest.raises(ValueError):
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await method(*args, **kwargs)
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with request_provider_data_context({}, admin_user):
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for method, args, kwargs in update_methods:
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result = await method(*args, **kwargs)
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assert result is not None, "Update operation failed with admin user"
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with request_provider_data_context({}, admin_user):
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for method, args, kwargs in delete_methods:
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result = await method(*args, **kwargs)
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assert result is not None, "Delete operation failed with admin user"
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for user in [read_only_user, no_access_user]:
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with request_provider_data_context({}, user):
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for method, args, kwargs in delete_methods:
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with pytest.raises(ValueError):
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await method(*args, **kwargs)
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