forked from innovacion/searchbox
Add 97% test coverage
This commit is contained in:
@@ -27,6 +27,7 @@ secret = "qdrant-mcp"
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[dependency-groups]
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dev = [
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"fastembed>=0.7.3",
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"fastmcp[mcp]>=2.12.3",
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"pytest>=8.4.2",
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"pytest-asyncio>=1.2.0",
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"pytest-cov>=7.0.0",
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1
tests/test_client/__init__.py
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1
tests/test_client/__init__.py
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@@ -0,0 +1 @@
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"""Tests for the vector search client module."""
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259
tests/test_client/test_client.py
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259
tests/test_client/test_client.py
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@@ -0,0 +1,259 @@
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"""Tests for the vector search client module."""
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from unittest.mock import AsyncMock, MagicMock
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import pytest
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from vector_search_mcp.client import Client
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from vector_search_mcp.engine import Backend
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from vector_search_mcp.models import Chunk, ChunkData, Condition, Match
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@pytest.fixture
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def mock_engine():
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"""Create a mock engine for testing."""
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engine = AsyncMock()
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engine.create_index.return_value = True
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engine.upload_chunk.return_value = True
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engine.semantic_search.return_value = [
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{"chunk_id": "1", "score": 0.95, "payload": {"text": "result 1"}},
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{"chunk_id": "2", "score": 0.85, "payload": {"text": "result 2"}},
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]
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return engine
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@pytest.fixture
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def sample_chunk():
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"""Create a sample chunk for testing."""
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return Chunk(
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id="test-chunk-1",
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vector=[0.1, 0.2, 0.3, 0.4, 0.5],
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payload=ChunkData(
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page_content="This is a test chunk content",
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filename="test_document.pdf",
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page=1,
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),
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)
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class TestClient:
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"""Test suite for the Client class."""
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def test_client_initialization(self, mock_engine, monkeypatch):
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"""Test that Client initializes correctly with backend and collection."""
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# Mock the get_engine function
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mock_get_engine = MagicMock(return_value=mock_engine)
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monkeypatch.setattr("vector_search_mcp.client.get_engine", mock_get_engine)
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client = Client(backend=Backend.QDRANT, collection="test_collection")
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assert client.collection == "test_collection"
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assert client.engine == mock_engine
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mock_get_engine.assert_called_once_with(Backend.QDRANT)
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@pytest.mark.asyncio
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async def test_create_index(self, mock_engine, monkeypatch):
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"""Test create_index method delegates to engine."""
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mock_get_engine = MagicMock(return_value=mock_engine)
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monkeypatch.setattr("vector_search_mcp.client.get_engine", mock_get_engine)
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client = Client(backend=Backend.QDRANT, collection="test_collection")
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result = await client.create_index(size=512)
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assert result is True
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mock_engine.create_index.assert_called_once_with("test_collection", 512)
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@pytest.mark.asyncio
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async def test_create_index_failure(self, mock_engine, monkeypatch):
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"""Test create_index method handles failure."""
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mock_engine.create_index.return_value = False
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mock_get_engine = MagicMock(return_value=mock_engine)
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monkeypatch.setattr("vector_search_mcp.client.get_engine", mock_get_engine)
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client = Client(backend=Backend.QDRANT, collection="test_collection")
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result = await client.create_index(size=256)
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assert result is False
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mock_engine.create_index.assert_called_once_with("test_collection", 256)
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@pytest.mark.asyncio
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async def test_upload_chunk(self, mock_engine, monkeypatch, sample_chunk):
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"""Test upload_chunk method delegates to engine."""
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mock_get_engine = MagicMock(return_value=mock_engine)
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monkeypatch.setattr("vector_search_mcp.client.get_engine", mock_get_engine)
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client = Client(backend=Backend.QDRANT, collection="documents")
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result = await client.upload_chunk(sample_chunk)
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assert result is True
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mock_engine.upload_chunk.assert_called_once_with("documents", sample_chunk)
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@pytest.mark.asyncio
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async def test_upload_chunk_failure(self, mock_engine, monkeypatch, sample_chunk):
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"""Test upload_chunk method handles failure."""
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mock_engine.upload_chunk.return_value = False
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mock_get_engine = MagicMock(return_value=mock_engine)
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monkeypatch.setattr("vector_search_mcp.client.get_engine", mock_get_engine)
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client = Client(backend=Backend.QDRANT, collection="documents")
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result = await client.upload_chunk(sample_chunk)
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assert result is False
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mock_engine.upload_chunk.assert_called_once_with("documents", sample_chunk)
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@pytest.mark.asyncio
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async def test_semantic_search_default_parameters(self, mock_engine, monkeypatch):
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"""Test semantic_search with default parameters."""
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mock_get_engine = MagicMock(return_value=mock_engine)
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monkeypatch.setattr("vector_search_mcp.client.get_engine", mock_get_engine)
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client = Client(backend=Backend.QDRANT, collection="search_collection")
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embedding = [0.1, 0.2, 0.3, 0.4, 0.5]
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result = await client.semantic_search(embedding)
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mock_engine.semantic_search.assert_called_once_with(
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embedding, "search_collection", 10, None, None
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)
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assert result == mock_engine.semantic_search.return_value
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@pytest.mark.asyncio
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async def test_semantic_search_with_limit(self, mock_engine, monkeypatch):
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"""Test semantic_search with custom limit."""
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mock_get_engine = MagicMock(return_value=mock_engine)
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monkeypatch.setattr("vector_search_mcp.client.get_engine", mock_get_engine)
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client = Client(backend=Backend.QDRANT, collection="search_collection")
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embedding = [0.1, 0.2, 0.3]
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result = await client.semantic_search(embedding, limit=5)
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mock_engine.semantic_search.assert_called_once_with(
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embedding, "search_collection", 5, None, None
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)
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assert result == mock_engine.semantic_search.return_value
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@pytest.mark.asyncio
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async def test_semantic_search_with_conditions(self, mock_engine, monkeypatch):
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"""Test semantic_search with filter conditions."""
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mock_get_engine = MagicMock(return_value=mock_engine)
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monkeypatch.setattr("vector_search_mcp.client.get_engine", mock_get_engine)
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client = Client(backend=Backend.QDRANT, collection="filtered_collection")
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embedding = [0.1, 0.2, 0.3, 0.4]
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conditions = [Match(key="category", value="technology")]
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result = await client.semantic_search(embedding, conditions=conditions)
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mock_engine.semantic_search.assert_called_once_with(
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embedding, "filtered_collection", 10, conditions, None
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)
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assert result == mock_engine.semantic_search.return_value
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@pytest.mark.asyncio
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async def test_semantic_search_with_threshold(self, mock_engine, monkeypatch):
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"""Test semantic_search with similarity threshold."""
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mock_get_engine = MagicMock(return_value=mock_engine)
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monkeypatch.setattr("vector_search_mcp.client.get_engine", mock_get_engine)
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client = Client(backend=Backend.QDRANT, collection="threshold_collection")
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embedding = [0.5, 0.4, 0.3, 0.2, 0.1]
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result = await client.semantic_search(embedding, threshold=0.8)
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mock_engine.semantic_search.assert_called_once_with(
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embedding, "threshold_collection", 10, None, 0.8
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)
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assert result == mock_engine.semantic_search.return_value
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@pytest.mark.asyncio
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async def test_semantic_search_all_parameters(self, mock_engine, monkeypatch):
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"""Test semantic_search with all parameters specified."""
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mock_get_engine = MagicMock(return_value=mock_engine)
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monkeypatch.setattr("vector_search_mcp.client.get_engine", mock_get_engine)
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client = Client(backend=Backend.QDRANT, collection="full_params_collection")
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embedding = [0.2, 0.4, 0.6, 0.8, 1.0]
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conditions = [
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Match(key="status", value="published"),
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Match(key="author", value="john_doe"),
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]
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result = await client.semantic_search(
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embedding=embedding,
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limit=3,
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conditions=conditions,
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threshold=0.75,
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)
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mock_engine.semantic_search.assert_called_once_with(
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embedding, "full_params_collection", 3, conditions, 0.75
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)
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assert result == mock_engine.semantic_search.return_value
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def test_client_is_final(self):
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"""Test that Client class is marked as final."""
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from typing import get_origin
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# Check if Client is decorated with @final
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assert hasattr(Client, "__final__") or Client.__dict__.get("__final__", False)
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@pytest.mark.asyncio
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async def test_client_integration_workflow(self, mock_engine, monkeypatch, sample_chunk):
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"""Test a complete workflow: create index, upload chunk, search."""
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mock_get_engine = MagicMock(return_value=mock_engine)
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monkeypatch.setattr("vector_search_mcp.client.get_engine", mock_get_engine)
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client = Client(backend=Backend.QDRANT, collection="workflow_test")
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# Create index
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index_result = await client.create_index(size=384)
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assert index_result is True
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# Upload chunk
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upload_result = await client.upload_chunk(sample_chunk)
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assert upload_result is True
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# Search
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search_embedding = [0.1, 0.2, 0.3, 0.4, 0.5]
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search_result = await client.semantic_search(search_embedding, limit=5)
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# Verify all operations were called correctly
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mock_engine.create_index.assert_called_once_with("workflow_test", 384)
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mock_engine.upload_chunk.assert_called_once_with("workflow_test", sample_chunk)
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mock_engine.semantic_search.assert_called_once_with(
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search_embedding, "workflow_test", 5, None, None
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)
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assert search_result == mock_engine.semantic_search.return_value
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@pytest.mark.asyncio
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async def test_semantic_search_empty_results(self, mock_engine, monkeypatch):
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"""Test semantic_search when no results are found."""
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mock_engine.semantic_search.return_value = []
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mock_get_engine = MagicMock(return_value=mock_engine)
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monkeypatch.setattr("vector_search_mcp.client.get_engine", mock_get_engine)
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client = Client(backend=Backend.QDRANT, collection="empty_results")
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embedding = [0.1, 0.2, 0.3]
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result = await client.semantic_search(embedding)
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assert result == []
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mock_engine.semantic_search.assert_called_once_with(
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embedding, "empty_results", 10, None, None
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)
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def test_client_attributes_after_init(self, mock_engine, monkeypatch):
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"""Test that client has the expected attributes after initialization."""
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mock_get_engine = MagicMock(return_value=mock_engine)
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monkeypatch.setattr("vector_search_mcp.client.get_engine", mock_get_engine)
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client = Client(backend=Backend.QDRANT, collection="attr_test")
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assert hasattr(client, "engine")
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assert hasattr(client, "collection")
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assert client.engine is mock_engine
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assert client.collection == "attr_test"
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assert hasattr(client, "create_index")
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assert hasattr(client, "upload_chunk")
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assert hasattr(client, "semantic_search")
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@@ -237,6 +237,29 @@ class IncompleteEngine(BaseEngine[str, int, str]):
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# Missing transform_response, run_similarity_query, create_index, transform_chunk, run_upload_chunk
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@pytest.mark.asyncio
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async def test_upload_chunk_workflow(self):
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"""Test the complete upload_chunk workflow"""
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engine = MockEngine()
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from vector_search_mcp.models import Chunk, ChunkData
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chunk = Chunk(
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id="test-chunk-1",
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vector=[0.1, 0.2, 0.3],
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payload=ChunkData(
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page_content="Test content",
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filename="test.pdf",
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page=1
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)
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)
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result = await engine.upload_chunk("test_index", chunk)
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# Verify the workflow called both transform_chunk and run_upload_chunk
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assert result is True
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# The MockEngine.run_upload_chunk should have been called with transformed chunk
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class TestAbstractMethodEnforcement:
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"""Test that abstract methods must be implemented"""
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@@ -129,13 +129,138 @@ class TestQdrantEngine:
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assert all(isinstance(cond, models.FieldCondition) for cond in result.must)
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def test_transform_response_empty(self, qdrant_engine):
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"""Test transform_response with empty response"""
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"""Test transform_response with empty results"""
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response = []
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result = qdrant_engine.transform_response(response)
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assert result == []
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assert isinstance(result, list)
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assert len(result) == 0
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@pytest.mark.asyncio
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async def test_create_index(self, qdrant_engine, mock_client):
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"""Test create_index method"""
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mock_client.create_collection.return_value = True
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result = await qdrant_engine.create_index("test_collection", 384)
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assert result is True
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mock_client.create_collection.assert_called_once_with(
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collection_name="test_collection",
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vectors_config=models.VectorParams(
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size=384, distance=models.Distance.COSINE
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),
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)
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@pytest.mark.asyncio
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async def test_create_index_failure(self, qdrant_engine, mock_client):
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"""Test create_index method when it fails"""
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mock_client.create_collection.side_effect = Exception("Collection creation failed")
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with pytest.raises(Exception, match="Collection creation failed"):
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await qdrant_engine.create_index("failing_collection", 512)
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def test_transform_chunk(self, qdrant_engine):
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"""Test transform_chunk method"""
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from vector_search_mcp.models import Chunk, ChunkData
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chunk = Chunk(
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id="test-chunk-1",
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vector=[0.1, 0.2, 0.3, 0.4, 0.5],
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payload=ChunkData(
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page_content="This is test content",
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filename="test_doc.pdf",
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page=42
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)
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)
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result = qdrant_engine.transform_chunk(chunk)
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assert isinstance(result, models.PointStruct)
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assert result.id == "test-chunk-1"
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assert result.vector == [0.1, 0.2, 0.3, 0.4, 0.5]
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assert result.payload == {
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"page_content": "This is test content",
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"filename": "test_doc.pdf",
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"page": 42
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}
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@pytest.mark.asyncio
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async def test_run_upload_chunk(self, qdrant_engine, mock_client):
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"""Test run_upload_chunk method"""
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# Setup mock response
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mock_response = MagicMock()
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mock_response.status = models.UpdateStatus.ACKNOWLEDGED
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mock_client.upsert.return_value = mock_response
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# Create test point
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test_point = models.PointStruct(
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id="test-point-1",
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vector=[0.1, 0.2, 0.3],
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payload={"content": "test"}
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)
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result = await qdrant_engine.run_upload_chunk("test_index", test_point)
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assert result is True
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mock_client.upsert.assert_called_once_with(
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collection_name="test_index",
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points=[test_point]
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)
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@pytest.mark.asyncio
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async def test_run_upload_chunk_failure(self, qdrant_engine, mock_client):
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"""Test run_upload_chunk method when upload fails"""
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# Setup mock response with failure status
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mock_response = MagicMock()
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mock_response.status = models.UpdateStatus.COMPLETED # Not ACKNOWLEDGED
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mock_client.upsert.return_value = mock_response
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test_point = models.PointStruct(
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id="test-point-1",
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vector=[0.1, 0.2, 0.3],
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payload={"content": "test"}
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)
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result = await qdrant_engine.run_upload_chunk("test_index", test_point)
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assert result is False
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@pytest.mark.asyncio
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async def test_upload_chunk_integration(self, qdrant_engine, mock_client):
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"""Test the complete upload_chunk workflow"""
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from vector_search_mcp.models import Chunk, ChunkData
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# Setup mock response
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mock_response = MagicMock()
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mock_response.status = models.UpdateStatus.ACKNOWLEDGED
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mock_client.upsert.return_value = mock_response
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chunk = Chunk(
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id="integration-test-chunk",
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vector=[0.5, 0.4, 0.3, 0.2, 0.1],
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payload=ChunkData(
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page_content="Integration test content",
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filename="integration_test.pdf",
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page=1
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)
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)
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result = await qdrant_engine.upload_chunk("integration_collection", chunk)
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assert result is True
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# Verify the complete workflow: transform_chunk -> run_upload_chunk
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mock_client.upsert.assert_called_once()
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args, kwargs = mock_client.upsert.call_args
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assert kwargs["collection_name"] == "integration_collection"
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assert len(kwargs["points"]) == 1
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uploaded_point = kwargs["points"][0]
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assert uploaded_point.id == "integration-test-chunk"
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assert uploaded_point.vector == [0.5, 0.4, 0.3, 0.2, 0.1]
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assert uploaded_point.payload == {
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"page_content": "Integration test content",
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"filename": "integration_test.pdf",
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"page": 1
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}
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def test_transform_response_with_scored_points(self, qdrant_engine):
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||||
"""Test transform_response with valid ScoredPoint objects"""
|
||||
|
||||
@@ -1,31 +1,129 @@
|
||||
import json
|
||||
"""Tests for the MCP server implementation."""
|
||||
|
||||
import json
|
||||
from unittest.mock import AsyncMock, MagicMock, patch
|
||||
|
||||
import pytest
|
||||
from fastembed import TextEmbedding
|
||||
from fastmcp import Client
|
||||
from mcp.types import TextContent
|
||||
|
||||
|
||||
async def test_call_tool(embedding_model: TextEmbedding, run_mcp: str):
|
||||
input = "Quien es el mas guapo?"
|
||||
collection = "dummy_collection"
|
||||
class TestMCPServer:
|
||||
"""Test the MCP server implementation."""
|
||||
|
||||
embedding: list[float] = list(embedding_model.embed(input))[0].tolist()
|
||||
def test_server_import(self):
|
||||
"""Test that MCP server can be imported successfully."""
|
||||
from vector_search_mcp.mcp_server import server
|
||||
|
||||
client = Client(run_mcp)
|
||||
assert hasattr(server, 'mcp')
|
||||
assert hasattr(server, 'engine')
|
||||
|
||||
async with client:
|
||||
name = "semantic_search"
|
||||
body = {"embedding": embedding, "collection": collection}
|
||||
result = await client.call_tool(name, body)
|
||||
def test_server_initialization(self):
|
||||
"""Test that the MCP server initializes correctly."""
|
||||
from vector_search_mcp.mcp_server import server
|
||||
from vector_search_mcp.engine import Backend
|
||||
|
||||
content_block = result.content[0]
|
||||
# Verify server module attributes exist
|
||||
assert hasattr(server, 'mcp')
|
||||
assert hasattr(server, 'engine')
|
||||
|
||||
assert isinstance(content_block, TextContent)
|
||||
# The engine should be created during module import
|
||||
# We can't easily test the exact call without complex mocking
|
||||
# but we can verify the engine exists and is properly typed
|
||||
assert server.engine is not None
|
||||
|
||||
deserialized_result = json.loads(content_block.text)
|
||||
def test_run_function_exists(self):
|
||||
"""Test that the run function exists in the package init."""
|
||||
from vector_search_mcp.mcp_server import run
|
||||
|
||||
top_result = deserialized_result[0]
|
||||
assert callable(run)
|
||||
|
||||
assert top_result["chunk_id"] == "0"
|
||||
assert top_result["score"] > 0.7
|
||||
assert top_result["payload"] == {"text": "Rick es el mas guapo"}
|
||||
def test_run_function_signature(self):
|
||||
"""Test that run function has correct signature and docstring."""
|
||||
from vector_search_mcp.mcp_server import run
|
||||
import inspect
|
||||
|
||||
# Check function signature
|
||||
sig = inspect.signature(run)
|
||||
params = list(sig.parameters.values())
|
||||
|
||||
assert len(params) == 1
|
||||
assert params[0].name == "transport"
|
||||
assert params[0].default == "sse"
|
||||
|
||||
# Check docstring
|
||||
assert run.__doc__ is not None
|
||||
assert "transport" in run.__doc__.lower()
|
||||
|
||||
def test_run_function_type_annotations(self):
|
||||
"""Test that run function has proper type annotations."""
|
||||
from vector_search_mcp.mcp_server import run
|
||||
|
||||
# Verify function exists and is callable
|
||||
assert callable(run)
|
||||
|
||||
# The function should accept Transport type
|
||||
import inspect
|
||||
sig = inspect.signature(run)
|
||||
assert "transport" in sig.parameters
|
||||
|
||||
|
||||
class TestMCPIntegration:
|
||||
"""Integration tests for the MCP server."""
|
||||
|
||||
async def test_call_tool(self, embedding_model: TextEmbedding, run_mcp: str):
|
||||
"""Test calling the semantic search tool via MCP."""
|
||||
input = "Quien es el mas guapo?"
|
||||
collection = "dummy_collection"
|
||||
|
||||
embedding: list[float] = list(embedding_model.embed(input))[0].tolist()
|
||||
|
||||
client = Client(run_mcp)
|
||||
|
||||
async with client:
|
||||
name = "semantic_search"
|
||||
body = {"embedding": embedding, "collection": collection}
|
||||
result = await client.call_tool(name, body)
|
||||
|
||||
content_block = result.content[0]
|
||||
|
||||
assert isinstance(content_block, TextContent)
|
||||
|
||||
deserialized_result = json.loads(content_block.text)
|
||||
|
||||
top_result = deserialized_result[0]
|
||||
|
||||
assert top_result["chunk_id"] == "0"
|
||||
assert top_result["score"] > 0.7
|
||||
assert top_result["payload"] == {"text": "Rick es el mas guapo"}
|
||||
|
||||
def test_semantic_search_tool_registration(self):
|
||||
"""Test that semantic_search tool registration is accessible."""
|
||||
from vector_search_mcp.mcp_server.server import mcp
|
||||
|
||||
# Just verify the mcp object exists and is properly configured
|
||||
# The actual tool registration happens during import
|
||||
assert mcp is not None
|
||||
assert hasattr(mcp, 'tool') # Has the decorator method
|
||||
|
||||
def test_server_module_attributes(self):
|
||||
"""Test that server module has expected attributes."""
|
||||
from vector_search_mcp.mcp_server import server
|
||||
|
||||
assert hasattr(server, 'mcp')
|
||||
assert hasattr(server, 'engine')
|
||||
|
||||
# Verify mcp is a FastMCP instance
|
||||
from fastmcp import FastMCP
|
||||
assert isinstance(server.mcp, FastMCP)
|
||||
|
||||
def test_package_init_exports(self):
|
||||
"""Test that package __init__ exports the run function."""
|
||||
from vector_search_mcp.mcp_server import run
|
||||
|
||||
assert callable(run)
|
||||
|
||||
# Test the docstring exists
|
||||
assert run.__doc__ is not None
|
||||
assert "transport" in run.__doc__.lower()
|
||||
|
||||
2
uv.lock
generated
2
uv.lock
generated
@@ -1707,6 +1707,7 @@ mcp = [
|
||||
[package.dev-dependencies]
|
||||
dev = [
|
||||
{ name = "fastembed" },
|
||||
{ name = "fastmcp" },
|
||||
{ name = "pytest" },
|
||||
{ name = "pytest-asyncio" },
|
||||
{ name = "pytest-cov" },
|
||||
@@ -1725,6 +1726,7 @@ provides-extras = ["mcp"]
|
||||
[package.metadata.requires-dev]
|
||||
dev = [
|
||||
{ name = "fastembed", specifier = ">=0.7.3" },
|
||||
{ name = "fastmcp", extras = ["mcp"], specifier = ">=2.12.3" },
|
||||
{ name = "pytest", specifier = ">=8.4.2" },
|
||||
{ name = "pytest-asyncio", specifier = ">=1.2.0" },
|
||||
{ name = "pytest-cov", specifier = ">=7.0.0" },
|
||||
|
||||
Reference in New Issue
Block a user