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- Remove embedchain and resolve circular deps with ChromaDB - Adjust lockfile to match crewai requirements - Mock embeddings and vector DB in RAG tool tests
176 lines
5.8 KiB
Python
176 lines
5.8 KiB
Python
"""Tests for RAG tool with mocked embeddings and vector database."""
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from tempfile import TemporaryDirectory
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from typing import Any, cast
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from pathlib import Path
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from unittest.mock import Mock, patch, MagicMock
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import pytest
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from crewai_tools.adapters.crewai_rag_adapter import CrewAIRagAdapter
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from crewai_tools.tools.rag.rag_tool import RagTool
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@patch('crewai_tools.adapters.crewai_rag_adapter.get_rag_client')
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@patch('crewai_tools.adapters.crewai_rag_adapter.create_client')
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def test_rag_tool_initialization(
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mock_create_client: Mock,
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mock_get_rag_client: Mock
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) -> None:
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"""Test that RagTool initializes with CrewAI adapter by default."""
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mock_client = MagicMock()
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mock_client.get_or_create_collection = MagicMock(return_value=None)
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mock_get_rag_client.return_value = mock_client
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mock_create_client.return_value = mock_client
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class MyTool(RagTool):
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pass
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tool = MyTool()
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assert tool.adapter is not None
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assert isinstance(tool.adapter, CrewAIRagAdapter)
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adapter = cast(CrewAIRagAdapter, tool.adapter)
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assert adapter.collection_name == "rag_tool_collection"
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assert adapter._client is not None
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@patch('crewai_tools.adapters.crewai_rag_adapter.get_rag_client')
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@patch('crewai_tools.adapters.crewai_rag_adapter.create_client')
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def test_rag_tool_add_and_query(
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mock_create_client: Mock,
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mock_get_rag_client: Mock
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) -> None:
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"""Test adding content and querying with RagTool."""
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mock_client = MagicMock()
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mock_client.get_or_create_collection = MagicMock(return_value=None)
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mock_client.add_documents = MagicMock(return_value=None)
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mock_client.search = MagicMock(return_value=[
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{"content": "The sky is blue on a clear day.", "metadata": {}, "score": 0.9}
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])
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mock_get_rag_client.return_value = mock_client
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mock_create_client.return_value = mock_client
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class MyTool(RagTool):
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pass
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tool = MyTool()
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tool.add("The sky is blue on a clear day.")
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tool.add("Machine learning is a subset of artificial intelligence.")
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# Verify documents were added
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assert mock_client.add_documents.call_count == 2
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result = tool._run(query="What color is the sky?")
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assert "Relevant Content:" in result
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assert "The sky is blue" in result
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mock_client.search.return_value = [
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{"content": "Machine learning is a subset of artificial intelligence.", "metadata": {}, "score": 0.85}
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]
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result = tool._run(query="Tell me about machine learning")
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assert "Relevant Content:" in result
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assert "Machine learning" in result
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@patch('crewai_tools.adapters.crewai_rag_adapter.get_rag_client')
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@patch('crewai_tools.adapters.crewai_rag_adapter.create_client')
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def test_rag_tool_with_file(
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mock_create_client: Mock,
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mock_get_rag_client: Mock
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) -> None:
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"""Test RagTool with file content."""
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mock_client = MagicMock()
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mock_client.get_or_create_collection = MagicMock(return_value=None)
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mock_client.add_documents = MagicMock(return_value=None)
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mock_client.search = MagicMock(return_value=[
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{"content": "Python is a programming language known for its simplicity.", "metadata": {"file_path": "test.txt"}, "score": 0.95}
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])
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mock_get_rag_client.return_value = mock_client
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mock_create_client.return_value = mock_client
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with TemporaryDirectory() as tmpdir:
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test_file = Path(tmpdir) / "test.txt"
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test_file.write_text("Python is a programming language known for its simplicity.")
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class MyTool(RagTool):
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pass
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tool = MyTool()
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tool.add(str(test_file))
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assert mock_client.add_documents.called
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result = tool._run(query="What is Python?")
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assert "Relevant Content:" in result
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assert "Python is a programming language" in result
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@patch('crewai_tools.tools.rag.rag_tool.RagTool._create_embedding_function')
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@patch('crewai_tools.adapters.crewai_rag_adapter.create_client')
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def test_rag_tool_with_custom_embeddings(
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mock_create_client: Mock,
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mock_create_embedding: Mock
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) -> None:
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"""Test RagTool with custom embeddings configuration to ensure no API calls."""
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mock_embedding_func = MagicMock()
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mock_embedding_func.return_value = [[0.2] * 1536]
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mock_create_embedding.return_value = mock_embedding_func
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mock_client = MagicMock()
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mock_client.get_or_create_collection = MagicMock(return_value=None)
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mock_client.add_documents = MagicMock(return_value=None)
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mock_client.search = MagicMock(return_value=[
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{"content": "Test content", "metadata": {}, "score": 0.8}
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])
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mock_create_client.return_value = mock_client
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class MyTool(RagTool):
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pass
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config = {
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"vectordb": {
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"provider": "chromadb",
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"config": {}
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},
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"embedding_model": {
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"provider": "openai",
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"config": {
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"model": "text-embedding-3-small"
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}
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}
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}
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tool = MyTool(config=config)
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tool.add("Test content")
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result = tool._run(query="Test query")
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assert "Relevant Content:" in result
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assert "Test content" in result
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mock_create_embedding.assert_called()
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@patch('crewai_tools.adapters.crewai_rag_adapter.get_rag_client')
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@patch('crewai_tools.adapters.crewai_rag_adapter.create_client')
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def test_rag_tool_no_results(
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mock_create_client: Mock,
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mock_get_rag_client: Mock
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) -> None:
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"""Test RagTool when no relevant content is found."""
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mock_client = MagicMock()
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mock_client.get_or_create_collection = MagicMock(return_value=None)
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mock_client.search = MagicMock(return_value=[])
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mock_get_rag_client.return_value = mock_client
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mock_create_client.return_value = mock_client
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class MyTool(RagTool):
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pass
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tool = MyTool()
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result = tool._run(query="Non-existent content")
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assert "Relevant Content:" in result
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assert "No relevant content found" in result |