feat: To add health check for faiss inline vector_io provider (#2319)

# What does this PR do?
<!-- Provide a short summary of what this PR does and why. Link to
relevant issues if applicable. -->
To add health check for faiss inline vector_io provider.

I tried adding `async def health(self) -> HealthResponse:` like in
inference provider, but it didn't worked for `inline->vector_io->faiss`
provider. And via debug logs, I understood the critical issue, that the
health responses are being stored with the API name as the key, not as a
nested dictionary with provider IDs. This means that all providers of
the same API type (e.g., "vector_io") will share the same health
response, and only the last one processed will be visible in the API
response.
I've created a patch file that fixes this issue by:
- Storing the original get_providers_health method
- Creating a patched version that correctly maps health responses to
providers
- Applying the patch to the `ProviderImpl` class

Not an expert, so please let me know, if there can be any other
workaround using which I can get the health status updated directly from
`faiss.py`.

<!-- If resolving an issue, uncomment and update the line below -->
<!-- Closes #[issue-number] -->

## Test Plan
<!-- Describe the tests you ran to verify your changes with result
summaries. *Provide clear instructions so the plan can be easily
re-executed.* -->
Added unit tests to test the provider patch implementation in the PR.
Adding a screenshot with the FAISS inline vector_io health status as
"OK"


![faiss_health_check](https://github.com/user-attachments/assets/d769e762-890c-41ea-a596-5e90951f79a4)

tests/unit/providers/vector_io/test_faiss.py

@@ -11,9 +11,11 @@ import numpy as np
 import pytest
 import pytest_asyncio
 
+from llama_stack.apis.files import Files
 from llama_stack.apis.inference import EmbeddingsResponse, Inference
 from llama_stack.apis.vector_dbs import VectorDB
 from llama_stack.apis.vector_io import Chunk, QueryChunksResponse
+from llama_stack.providers.datatypes import HealthStatus
 from llama_stack.providers.inline.vector_io.faiss.config import FaissVectorIOConfig
 from llama_stack.providers.inline.vector_io.faiss.faiss import (
     FaissIndex,
@@ -76,6 +78,12 @@ def mock_inference_api(sample_embeddings):
     return mock_api
 
 
+@pytest.fixture
+def mock_files_api():
+    mock_api = MagicMock(spec=Files)
+    return mock_api
+
+
 @pytest.fixture
 def faiss_config():
     config = MagicMock(spec=FaissVectorIOConfig)
@@ -90,11 +98,19 @@ async def faiss_index(embedding_dimension):
 
 
 @pytest_asyncio.fixture
-async def faiss_adapter(faiss_config, mock_inference_api) -> FaissVectorIOAdapter:
-    adapter = FaissVectorIOAdapter(config=faiss_config, inference_api=mock_inference_api)
-    await adapter.initialize()
-    yield adapter
-    await adapter.shutdown()
+async def faiss_adapter(faiss_config, mock_inference_api, mock_files_api) -> FaissVectorIOAdapter:
+    # Create the adapter
+    adapter = FaissVectorIOAdapter(config=faiss_config, inference_api=mock_inference_api, files_api=mock_files_api)
+
+    # Create a mock KVStore
+    mock_kvstore = MagicMock()
+    mock_kvstore.values_in_range = AsyncMock(return_value=[])
+
+    # Patch the initialize method to avoid the kvstore_impl call
+    with patch.object(FaissVectorIOAdapter, "initialize"):
+        # Set the kvstore directly
+        adapter.kvstore = mock_kvstore
+        yield adapter
 
 
 @pytest.mark.asyncio
@@ -118,3 +134,49 @@ async def test_faiss_query_vector_returns_infinity_when_query_and_embedding_are_
 
         assert response.chunks[0] == sample_chunks[0]
         assert response.chunks[1] == sample_chunks[1]
+
+
+@pytest.mark.asyncio
+async def test_health_success():
+    """Test that the health check returns OK status when faiss is working correctly."""
+    # Create a fresh instance of FaissVectorIOAdapter for testing
+    config = MagicMock()
+    inference_api = MagicMock()
+    files_api = MagicMock()
+
+    with patch("llama_stack.providers.inline.vector_io.faiss.faiss.faiss.IndexFlatL2") as mock_index_flat:
+        mock_index_flat.return_value = MagicMock()
+        adapter = FaissVectorIOAdapter(config=config, inference_api=inference_api, files_api=files_api)
+
+        # Calling the health method directly
+        response = await adapter.health()
+
+        # Verifying the response
+        assert isinstance(response, dict)
+        assert response["status"] == HealthStatus.OK
+        assert "message" not in response
+
+        # Verifying that IndexFlatL2 was called with the correct dimension
+        mock_index_flat.assert_called_once_with(128)  # VECTOR_DIMENSION is 128
+
+
+@pytest.mark.asyncio
+async def test_health_failure():
+    """Test that the health check returns ERROR status when faiss encounters an error."""
+    # Create a fresh instance of FaissVectorIOAdapter for testing
+    config = MagicMock()
+    inference_api = MagicMock()
+    files_api = MagicMock()
+
+    with patch("llama_stack.providers.inline.vector_io.faiss.faiss.faiss.IndexFlatL2") as mock_index_flat:
+        mock_index_flat.side_effect = Exception("Test error")
+
+        adapter = FaissVectorIOAdapter(config=config, inference_api=inference_api, files_api=files_api)
+
+        # Calling the health method directly
+        response = await adapter.health()
+
+        # Verifying the response
+        assert isinstance(response, dict)
+        assert response["status"] == HealthStatus.ERROR
+        assert response["message"] == "Health check failed: Test error"