convert memory tests

llama_stack/providers/tests/memory/conftest.py

@@ -0,0 +1,96 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import os
+from typing import Any, Dict, Tuple
+
+import pytest
+import pytest_asyncio
+
+from llama_stack.distribution.datatypes import Api, Provider
+from llama_stack.providers.adapters.memory.pgvector import PGVectorConfig
+from llama_stack.providers.adapters.memory.weaviate import WeaviateConfig
+from llama_stack.providers.impls.meta_reference.memory import FaissImplConfig
+
+from llama_stack.providers.tests.resolver import resolve_impls_for_test_v2
+from ..env import get_env_or_fail
+
+
+@pytest.fixture(scope="session")
+def meta_reference() -> Provider:
+    return Provider(
+        provider_id="meta-reference",
+        provider_type="meta-reference",
+        config=FaissImplConfig().model_dump(),
+    )
+
+
+@pytest.fixture(scope="session")
+def pgvector() -> Provider:
+    return Provider(
+        provider_id="pgvector",
+        provider_type="remote::pgvector",
+        config=PGVectorConfig(
+            host=os.getenv("PGVECTOR_HOST", "localhost"),
+            port=os.getenv("PGVECTOR_PORT", 5432),
+            db=get_env_or_fail("PGVECTOR_DB"),
+            user=get_env_or_fail("PGVECTOR_USER"),
+            password=get_env_or_fail("PGVECTOR_PASSWORD"),
+        ).model_dump(),
+    )
+
+
+@pytest.fixture(scope="session")
+def weaviate() -> Tuple[Provider, Dict[str, Any]]:
+    provider = Provider(
+        provider_id="weaviate",
+        provider_type="remote::weaviate",
+        config=WeaviateConfig().model_dump(),
+    )
+    return provider, dict(
+        weaviate_api_key=get_env_or_fail("WEAVIATE_API_KEY"),
+        weaviate_cluster_url=get_env_or_fail("WEAVIATE_CLUSTER_URL"),
+    )
+
+
+PROVIDER_PARAMS = [
+    pytest.param("meta_reference", marks=pytest.mark.meta_reference),
+    pytest.param("pgvector", marks=pytest.mark.pgvector),
+    pytest.param("weaviate", marks=pytest.mark.weaviate),
+]
+
+
+@pytest_asyncio.fixture(
+    scope="session",
+    params=PROVIDER_PARAMS,
+)
+async def stack_impls(request):
+    provider_fixture = request.param
+    provider = request.getfixturevalue(provider_fixture)
+    if isinstance(provider, tuple):
+        provider, provider_data = provider
+    else:
+        provider_data = None
+
+    impls = await resolve_impls_for_test_v2(
+        [Api.memory],
+        {"memory": [provider.model_dump()]},
+        provider_data,
+    )
+
+    return impls[Api.memory], impls[Api.memory_banks]
+
+
+def pytest_configure(config):
+    config.addinivalue_line("markers", "pgvector: marks tests as pgvector specific")
+    config.addinivalue_line(
+        "markers",
+        "meta_reference: marks tests as metaref specific",
+    )
+    config.addinivalue_line(
+        "markers",
+        "weaviate: marks tests as weaviate specific",
+    )

llama_stack/providers/tests/memory/test_memory.py

@@ -5,39 +5,16 @@
 # the root directory of this source tree.
 
 import pytest
-import pytest_asyncio
 
 from llama_stack.apis.memory import *  # noqa: F403
 from llama_stack.distribution.datatypes import *  # noqa: F403
-from llama_stack.providers.tests.resolver import resolve_impls_for_test
+from .conftest import PROVIDER_PARAMS
 
 # How to run this test:
 #
-# 1. Ensure you have a conda with the right dependencies installed. This is a bit tricky
+# pytest llama_stack/providers/tests/memory/test_memory.py
-#    since it depends on the provider you are testing. On top of that you need
+#   -m "meta_reference"
-#    `pytest` and `pytest-asyncio` installed.
+#   -v -s --tb=short --disable-warnings
-#
-# 2. Copy and modify the provider_config_example.yaml depending on the provider you are testing.
-#
-# 3. Run:
-#
-# ```bash
-# PROVIDER_ID=<your_provider> \
-#   PROVIDER_CONFIG=provider_config.yaml \
-#   pytest -s llama_stack/providers/tests/memory/test_memory.py \
-#   --tb=short --disable-warnings
-# ```
-
-
-@pytest_asyncio.fixture(scope="session")
-async def memory_settings():
-    impls = await resolve_impls_for_test(
-        Api.memory,
-    )
-    return {
-        "memory_impl": impls[Api.memory],
-        "memory_banks_impl": impls[Api.memory_banks],
-    }
 
 
 @pytest.fixture
@@ -77,76 +54,81 @@ async def register_memory_bank(banks_impl: MemoryBanks):
     await banks_impl.register_memory_bank(bank)
 
 
-@pytest.mark.asyncio
+@pytest.mark.parametrize(
-async def test_banks_list(memory_settings):
+    "stack_impls",
-    # NOTE: this needs you to ensure that you are starting from a clean state
+    PROVIDER_PARAMS,
-    # but so far we don't have an unregister API unfortunately, so be careful
+    indirect=True,
-    banks_impl = memory_settings["memory_banks_impl"]
+)
-    response = await banks_impl.list_memory_banks()
+class TestMemory:
-    assert isinstance(response, list)
+    @pytest.mark.asyncio
-    assert len(response) == 0
+    async def test_banks_list(self, stack_impls):
+        # NOTE: this needs you to ensure that you are starting from a clean state
+        # but so far we don't have an unregister API unfortunately, so be careful
+        _, banks_impl = stack_impls
+        response = await banks_impl.list_memory_banks()
+        assert isinstance(response, list)
+        assert len(response) == 0
 
+    @pytest.mark.asyncio
+    async def test_banks_register(self, stack_impls):
+        # NOTE: this needs you to ensure that you are starting from a clean state
+        # but so far we don't have an unregister API unfortunately, so be careful
+        _, banks_impl = stack_impls
+        bank = VectorMemoryBankDef(
+            identifier="test_bank_no_provider",
+            embedding_model="all-MiniLM-L6-v2",
+            chunk_size_in_tokens=512,
+            overlap_size_in_tokens=64,
+        )
 
-@pytest.mark.asyncio
+        await banks_impl.register_memory_bank(bank)
-async def test_banks_register(memory_settings):
+        response = await banks_impl.list_memory_banks()
-    # NOTE: this needs you to ensure that you are starting from a clean state
+        assert isinstance(response, list)
-    # but so far we don't have an unregister API unfortunately, so be careful
+        assert len(response) == 1
-    banks_impl = memory_settings["memory_banks_impl"]
-    bank = VectorMemoryBankDef(
-        identifier="test_bank_no_provider",
-        embedding_model="all-MiniLM-L6-v2",
-        chunk_size_in_tokens=512,
-        overlap_size_in_tokens=64,
-    )
 
-    await banks_impl.register_memory_bank(bank)
+        # register same memory bank with same id again will fail
-    response = await banks_impl.list_memory_banks()
+        await banks_impl.register_memory_bank(bank)
-    assert isinstance(response, list)
+        response = await banks_impl.list_memory_banks()
-    assert len(response) == 1
+        assert isinstance(response, list)
+        assert len(response) == 1
 
-    # register same memory bank with same id again will fail
+    @pytest.mark.asyncio
-    await banks_impl.register_memory_bank(bank)
+    async def test_query_documents(self, stack_impls, sample_documents):
-    response = await banks_impl.list_memory_banks()
+        memory_impl, banks_impl = stack_impls
-    assert isinstance(response, list)
-    assert len(response) == 1
 
+        with pytest.raises(ValueError):
+            await memory_impl.insert_documents("test_bank", sample_documents)
 
-@pytest.mark.asyncio
+        await register_memory_bank(banks_impl)
-async def test_query_documents(memory_settings, sample_documents):
-    memory_impl = memory_settings["memory_impl"]
-    banks_impl = memory_settings["memory_banks_impl"]
-
-    with pytest.raises(ValueError):
         await memory_impl.insert_documents("test_bank", sample_documents)
 
-    await register_memory_bank(banks_impl)
+        query1 = "programming language"
-    await memory_impl.insert_documents("test_bank", sample_documents)
+        response1 = await memory_impl.query_documents("test_bank", query1)
+        assert_valid_response(response1)
+        assert any("Python" in chunk.content for chunk in response1.chunks)
 
-    query1 = "programming language"
+        # Test case 3: Query with semantic similarity
-    response1 = await memory_impl.query_documents("test_bank", query1)
+        query3 = "AI and brain-inspired computing"
-    assert_valid_response(response1)
+        response3 = await memory_impl.query_documents("test_bank", query3)
-    assert any("Python" in chunk.content for chunk in response1.chunks)
+        assert_valid_response(response3)
+        assert any(
+            "neural networks" in chunk.content.lower() for chunk in response3.chunks
+        )
 
-    # Test case 3: Query with semantic similarity
+        # Test case 4: Query with limit on number of results
-    query3 = "AI and brain-inspired computing"
+        query4 = "computer"
-    response3 = await memory_impl.query_documents("test_bank", query3)
+        params4 = {"max_chunks": 2}
-    assert_valid_response(response3)
+        response4 = await memory_impl.query_documents("test_bank", query4, params4)
-    assert any("neural networks" in chunk.content.lower() for chunk in response3.chunks)
+        assert_valid_response(response4)
+        assert len(response4.chunks) <= 2
 
-    # Test case 4: Query with limit on number of results
+        # Test case 5: Query with threshold on similarity score
-    query4 = "computer"
+        query5 = "quantum computing"  # Not directly related to any document
-    params4 = {"max_chunks": 2}
+        params5 = {"score_threshold": 0.2}
-    response4 = await memory_impl.query_documents("test_bank", query4, params4)
+        response5 = await memory_impl.query_documents("test_bank", query5, params5)
-    assert_valid_response(response4)
+        assert_valid_response(response5)
-    assert len(response4.chunks) <= 2
+        print("The scores are:", response5.scores)
-
+        assert all(score >= 0.2 for score in response5.scores)
-    # Test case 5: Query with threshold on similarity score
-    query5 = "quantum computing"  # Not directly related to any document
-    params5 = {"score_threshold": 0.2}
-    response5 = await memory_impl.query_documents("test_bank", query5, params5)
-    assert_valid_response(response5)
-    print("The scores are:", response5.scores)
-    assert all(score >= 0.2 for score in response5.scores)
 
 
 def assert_valid_response(response: QueryDocumentsResponse):