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Bwook (Byoungwook) Kim 2025-08-12 09:36:03 -07:00 committed by GitHub
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2 changed files with 157 additions and 2 deletions

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@ -113,10 +113,41 @@ class ChromaIndex(EmbeddingIndex):
k: int, k: int,
score_threshold: float, score_threshold: float,
) -> QueryChunksResponse: ) -> QueryChunksResponse:
raise NotImplementedError("Keyword search is not supported in Chroma") results = await maybe_await(
self.collection.query(
query_texts=[query_string],
where_document={"$contains": query_string},
n_results=k,
include=["documents", "distances"],
)
)
distances = results["distances"][0] if results["distances"] else []
documents = results["documents"][0] if results["documents"] else []
chunks = []
scores = []
for dist, doc in zip(distances, documents, strict=False):
try:
doc_data = json.loads(doc)
chunk = Chunk(**doc_data)
except Exception:
log.exception(f"Failed to parse document: {doc}")
continue
score = 1.0 / (1.0 + float(dist)) if dist is not None else 1.0
if score < score_threshold:
continue
chunks.append(chunk)
scores.append(score)
return QueryChunksResponse(chunks=chunks, scores=scores)
async def delete_chunk(self, chunk_id: str) -> None: async def delete_chunk(self, chunk_id: str) -> None:
raise NotImplementedError("delete_chunk is not supported in Chroma") await maybe_await(self.collection.delete([chunk_id]))
async def query_hybrid( async def query_hybrid(
self, self,

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@ -0,0 +1,124 @@
# 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 json
from unittest.mock import MagicMock, patch
import numpy as np
import pytest
from llama_stack.apis.vector_io import QueryChunksResponse
# Mock the entire chromadb module
chromadb_mock = MagicMock()
chromadb_mock.AsyncHttpClient = MagicMock
chromadb_mock.PersistentClient = MagicMock
# Apply the mock before importing ChromaIndex
with patch.dict("sys.modules", {"chromadb": chromadb_mock}):
from llama_stack.providers.remote.vector_io.chroma.chroma import ChromaIndex
# This test is a unit test for the ChromaVectorIOAdapter class. This should only contain
# tests which are specific to this class. More general (API-level) tests should be placed in
# tests/integration/vector_io/
#
# How to run this test:
#
# pytest tests/unit/providers/vector_io/test_chroma.py \
# -v -s --tb=short --disable-warnings --asyncio-mode=auto
CHROMA_PROVIDER = "chromadb"
@pytest.fixture
async def mock_chroma_collection() -> MagicMock:
"""Create a mock Chroma collection with common method behaviors."""
collection = MagicMock()
collection.name = "test_collection"
# Mock add operation
collection.add.return_value = None
# Mock query operation for vector search
collection.query.return_value = {
"distances": [[0.1, 0.2]],
"documents": [
[
json.dumps({"content": "mock chunk 1", "metadata": {"document_id": "doc1"}}),
json.dumps({"content": "mock chunk 2", "metadata": {"document_id": "doc2"}}),
]
],
}
# Mock delete operation
collection.delete.return_value = None
return collection
@pytest.fixture
async def mock_chroma_client(mock_chroma_collection):
"""Create a mock Chroma client with common method behaviors."""
client = MagicMock()
# Mock collection operations
client.get_or_create_collection.return_value = mock_chroma_collection
client.get_collection.return_value = mock_chroma_collection
client.delete_collection.return_value = None
return client
@pytest.fixture
async def chroma_index(mock_chroma_client, mock_chroma_collection):
"""Create a ChromaIndex with mocked client and collection."""
index = ChromaIndex(client=mock_chroma_client, collection=mock_chroma_collection)
yield index
# No real cleanup needed since we're using mocks
async def test_add_chunks(chroma_index, sample_chunks, sample_embeddings, mock_chroma_collection):
await chroma_index.add_chunks(sample_chunks, sample_embeddings)
# Verify data was inserted
mock_chroma_collection.add.assert_called_once()
# Verify the add call had the right number of chunks
add_call = mock_chroma_collection.add.call_args
assert len(add_call[1]["documents"]) == len(sample_chunks)
async def test_query_chunks_vector(
chroma_index, sample_chunks, sample_embeddings, embedding_dimension, mock_chroma_collection
):
# Setup: Add chunks first
await chroma_index.add_chunks(sample_chunks, sample_embeddings)
# Test vector search
query_embedding = np.random.rand(embedding_dimension).astype(np.float32)
response = await chroma_index.query_vector(query_embedding, k=2, score_threshold=0.0)
assert isinstance(response, QueryChunksResponse)
assert len(response.chunks) == 2
mock_chroma_collection.query.assert_called_once()
async def test_query_chunks_keyword_search(chroma_index, sample_chunks, sample_embeddings, mock_chroma_collection):
await chroma_index.add_chunks(sample_chunks, sample_embeddings)
# Test keyword search
query_string = "Sentence 5"
response = await chroma_index.query_keyword(query_string=query_string, k=2, score_threshold=0.0)
assert isinstance(response, QueryChunksResponse)
assert len(response.chunks) == 2
async def test_delete_collection(chroma_index, mock_chroma_client):
# Test collection deletion
await chroma_index.delete()
mock_chroma_client.delete_collection.assert_called_once_with(chroma_index.collection.name)