[memory refactor][2/n] Update faiss and make it pass tests (#830)

See https://github.com/meta-llama/llama-stack/issues/827 for the broader
design.

Second part:

- updates routing table / router code 
- updates the faiss implementation


## Test Plan

```
pytest -s -v -k sentence test_vector_io.py --env EMBEDDING_DIMENSION=384
```

llama_stack/providers/tests/vector_io/fixtures.py

@@ -0,0 +1,144 @@
+# 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
+import tempfile
+
+import pytest
+import pytest_asyncio
+
+from llama_stack.apis.models import ModelInput, ModelType
+from llama_stack.distribution.datatypes import Api, Provider
+
+from llama_stack.providers.inline.vector_io.chroma import ChromaInlineImplConfig
+from llama_stack.providers.inline.vector_io.faiss import FaissImplConfig
+from llama_stack.providers.remote.vector_io.chroma import ChromaRemoteImplConfig
+from llama_stack.providers.remote.vector_io.pgvector import PGVectorConfig
+from llama_stack.providers.remote.vector_io.weaviate import WeaviateConfig
+from llama_stack.providers.tests.resolver import construct_stack_for_test
+from llama_stack.providers.utils.kvstore.config import SqliteKVStoreConfig
+
+from ..conftest import ProviderFixture, remote_stack_fixture
+from ..env import get_env_or_fail
+
+
+@pytest.fixture(scope="session")
+def embedding_model(request):
+    if hasattr(request, "param"):
+        return request.param
+    return request.config.getoption("--embedding-model", None)
+
+
+@pytest.fixture(scope="session")
+def vector_io_remote() -> ProviderFixture:
+    return remote_stack_fixture()
+
+
+@pytest.fixture(scope="session")
+def vector_io_faiss() -> ProviderFixture:
+    temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".db")
+    return ProviderFixture(
+        providers=[
+            Provider(
+                provider_id="faiss",
+                provider_type="inline::faiss",
+                config=FaissImplConfig(
+                    kvstore=SqliteKVStoreConfig(db_path=temp_file.name).model_dump(),
+                ).model_dump(),
+            )
+        ],
+    )
+
+
+@pytest.fixture(scope="session")
+def vector_io_pgvector() -> ProviderFixture:
+    return ProviderFixture(
+        providers=[
+            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 vector_io_weaviate() -> ProviderFixture:
+    return ProviderFixture(
+        providers=[
+            Provider(
+                provider_id="weaviate",
+                provider_type="remote::weaviate",
+                config=WeaviateConfig().model_dump(),
+            )
+        ],
+        provider_data=dict(
+            weaviate_api_key=get_env_or_fail("WEAVIATE_API_KEY"),
+            weaviate_cluster_url=get_env_or_fail("WEAVIATE_CLUSTER_URL"),
+        ),
+    )
+
+
+@pytest.fixture(scope="session")
+def vector_io_chroma() -> ProviderFixture:
+    url = os.getenv("CHROMA_URL")
+    if url:
+        config = ChromaRemoteImplConfig(url=url)
+        provider_type = "remote::chromadb"
+    else:
+        if not os.getenv("CHROMA_DB_PATH"):
+            raise ValueError("CHROMA_DB_PATH or CHROMA_URL must be set")
+        config = ChromaInlineImplConfig(db_path=os.getenv("CHROMA_DB_PATH"))
+        provider_type = "inline::chromadb"
+    return ProviderFixture(
+        providers=[
+            Provider(
+                provider_id="chroma",
+                provider_type=provider_type,
+                config=config.model_dump(),
+            )
+        ]
+    )
+
+
+VECTOR_IO_FIXTURES = ["faiss", "pgvector", "weaviate", "chroma"]
+
+
+@pytest_asyncio.fixture(scope="session")
+async def vector_io_stack(embedding_model, request):
+    fixture_dict = request.param
+
+    providers = {}
+    provider_data = {}
+    for key in ["inference", "vector_io"]:
+        fixture = request.getfixturevalue(f"{key}_{fixture_dict[key]}")
+        providers[key] = fixture.providers
+        if fixture.provider_data:
+            provider_data.update(fixture.provider_data)
+
+    test_stack = await construct_stack_for_test(
+        [Api.vector_io, Api.inference],
+        providers,
+        provider_data,
+        models=[
+            ModelInput(
+                model_id=embedding_model,
+                model_type=ModelType.embedding,
+                metadata={
+                    "embedding_dimension": get_env_or_fail("EMBEDDING_DIMENSION"),
+                },
+            )
+        ],
+    )
+
+    return test_stack.impls[Api.vector_io], test_stack.impls[Api.vector_dbs]