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