mirror of
https://github.com/crewAIInc/crewAI.git
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36d9ca099e
Fixes #4028 - WebsiteSearchTool always requires OpenAI API key even when Ollama or other providers are specified. The issue was that the documentation showed the old config format with 'llm' and 'embedder' keys, but the actual RagToolConfig type expects 'embedding_model' and 'vectordb' keys. When the old format was passed, the embedder config was not recognized, causing the tool to fall back to the default OpenAI embedding function which requires OPENAI_API_KEY. Changes: - Add _normalize_legacy_config method to RagTool that maps legacy 'embedder' key to 'embedding_model' - Emit deprecation warnings for legacy config keys - Ignore 'llm' key with warning (not used in RAG tools) - Add tests for backward compatibility - Update documentation to show new config format with examples Co-Authored-By: João <joao@crewai.com>
477 lines
16 KiB
Python
477 lines
16 KiB
Python
from pathlib import Path
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from tempfile import TemporaryDirectory
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from typing import cast
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from unittest.mock import MagicMock, Mock, patch
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import warnings
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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, 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, 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(
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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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)
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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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{
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"content": "Machine learning is a subset of artificial intelligence.",
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"metadata": {},
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"score": 0.85,
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}
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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, 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(
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return_value=[
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{
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"content": "Python is a programming language known for its simplicity.",
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"metadata": {"file_path": "test.txt"},
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"score": 0.95,
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}
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]
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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(
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"Python is a programming language known for its simplicity."
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)
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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.build_embedder")
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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, mock_build_embedder: 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_build_embedder.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(
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return_value=[{"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": {"provider": "chromadb", "config": {}},
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"embedding_model": {
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"provider": "openai",
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"config": {"model": "text-embedding-3-small"},
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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_build_embedder.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, 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
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@patch("crewai_tools.adapters.crewai_rag_adapter.create_client")
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def test_rag_tool_with_azure_config_without_env_vars(
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mock_create_client: Mock,
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) -> None:
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"""Test that RagTool accepts Azure config without requiring env vars.
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This test verifies the fix for the issue where RAG tools were ignoring
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the embedding configuration passed via the config parameter and instead
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requiring environment variables like EMBEDDINGS_OPENAI_API_KEY.
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"""
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mock_embedding_func = MagicMock()
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mock_embedding_func.return_value = [[0.1] * 1536]
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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_create_client.return_value = mock_client
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# Patch the embedding function builder to avoid actual API calls
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with patch(
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"crewai_tools.tools.rag.rag_tool.build_embedder",
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return_value=mock_embedding_func,
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):
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class MyTool(RagTool):
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pass
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# Configuration with explicit Azure credentials - should work without env vars
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config = {
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"embedding_model": {
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"provider": "azure",
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"config": {
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"model": "text-embedding-3-small",
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"api_key": "test-api-key",
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"api_base": "https://test.openai.azure.com/",
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"api_version": "2024-02-01",
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"api_type": "azure",
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"deployment_id": "test-deployment",
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},
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}
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}
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# This should not raise a validation error about missing env vars
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tool = MyTool(config=config)
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assert tool.adapter is not None
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assert isinstance(tool.adapter, CrewAIRagAdapter)
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@patch("crewai_tools.adapters.crewai_rag_adapter.create_client")
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def test_rag_tool_with_openai_config_without_env_vars(
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mock_create_client: Mock,
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) -> None:
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"""Test that RagTool accepts OpenAI config without requiring env vars."""
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mock_embedding_func = MagicMock()
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mock_embedding_func.return_value = [[0.1] * 1536]
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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_create_client.return_value = mock_client
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with patch(
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"crewai_tools.tools.rag.rag_tool.build_embedder",
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return_value=mock_embedding_func,
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):
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class MyTool(RagTool):
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pass
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config = {
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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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"api_key": "sk-test123",
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},
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}
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}
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tool = MyTool(config=config)
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assert tool.adapter is not None
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assert isinstance(tool.adapter, CrewAIRagAdapter)
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@patch("crewai_tools.adapters.crewai_rag_adapter.create_client")
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def test_rag_tool_config_with_qdrant_and_azure_embeddings(
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mock_create_client: Mock,
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) -> None:
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"""Test RagTool with Qdrant vector DB and Azure embeddings config."""
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mock_embedding_func = MagicMock()
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mock_embedding_func.return_value = [[0.1] * 1536]
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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_create_client.return_value = mock_client
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with patch(
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"crewai_tools.tools.rag.rag_tool.build_embedder",
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return_value=mock_embedding_func,
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):
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class MyTool(RagTool):
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pass
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config = {
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"vectordb": {"provider": "qdrant", "config": {}},
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"embedding_model": {
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"provider": "azure",
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"config": {
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"model": "text-embedding-3-large",
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"api_key": "test-key",
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"api_base": "https://test.openai.azure.com/",
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"api_version": "2024-02-01",
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"deployment_id": "test-deployment",
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},
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},
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}
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tool = MyTool(config=config)
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assert tool.adapter is not None
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assert isinstance(tool.adapter, CrewAIRagAdapter)
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@patch("crewai_tools.adapters.crewai_rag_adapter.create_client")
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def test_rag_tool_with_legacy_embedder_config(
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mock_create_client: Mock,
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) -> None:
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"""Test that RagTool accepts legacy 'embedder' config key with deprecation warning.
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This test verifies the fix for issue #4028 where WebsiteSearchTool and other
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RAG tools always required OpenAI API key even when using Ollama or other providers.
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The legacy config format used 'embedder' key instead of 'embedding_model'.
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"""
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mock_embedding_func = MagicMock()
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mock_embedding_func.return_value = [[0.1] * 1536]
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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_create_client.return_value = mock_client
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with patch(
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"crewai_tools.tools.rag.rag_tool.build_embedder",
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return_value=mock_embedding_func,
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):
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class MyTool(RagTool):
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pass
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# Legacy config format using 'embedder' key (as shown in old docs)
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legacy_config = {
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"embedder": {
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"provider": "ollama",
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"config": {
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"model_name": "nomic-embed-text",
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"url": "http://localhost:11434/api/embeddings",
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},
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},
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}
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# Should emit deprecation warning but still work
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with warnings.catch_warnings(record=True) as w:
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warnings.simplefilter("always")
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tool = MyTool(config=legacy_config)
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# Check that deprecation warning was issued
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deprecation_warnings = [
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warning
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for warning in w
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if issubclass(warning.category, DeprecationWarning)
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]
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assert len(deprecation_warnings) >= 1
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assert "embedder" in str(deprecation_warnings[0].message)
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assert "embedding_model" in str(deprecation_warnings[0].message)
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assert tool.adapter is not None
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assert isinstance(tool.adapter, CrewAIRagAdapter)
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@patch("crewai_tools.adapters.crewai_rag_adapter.create_client")
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def test_rag_tool_with_legacy_llm_config_ignored(
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mock_create_client: Mock,
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) -> None:
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"""Test that RagTool ignores legacy 'llm' config key with deprecation warning.
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The 'llm' key was shown in old documentation but is not used by RAG tools.
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The LLM for generation is controlled by the agent's LLM configuration.
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"""
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mock_embedding_func = MagicMock()
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mock_embedding_func.return_value = [[0.1] * 1536]
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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_create_client.return_value = mock_client
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with patch(
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"crewai_tools.tools.rag.rag_tool.build_embedder",
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return_value=mock_embedding_func,
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):
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class MyTool(RagTool):
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pass
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# Legacy config format with both 'llm' and 'embedder' keys
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legacy_config = {
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"llm": {
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"provider": "ollama",
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"config": {
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"model": "llama2",
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},
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},
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"embedder": {
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"provider": "ollama",
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"config": {
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"model_name": "nomic-embed-text",
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"url": "http://localhost:11434/api/embeddings",
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},
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},
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}
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# Should emit deprecation warnings for both keys
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with warnings.catch_warnings(record=True) as w:
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warnings.simplefilter("always")
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tool = MyTool(config=legacy_config)
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# Check that deprecation warnings were issued for both keys
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deprecation_warnings = [
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warning
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for warning in w
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if issubclass(warning.category, DeprecationWarning)
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]
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assert len(deprecation_warnings) >= 2
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warning_messages = [str(warning.message) for warning in deprecation_warnings]
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assert any("llm" in msg for msg in warning_messages)
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assert any("embedder" in msg for msg in warning_messages)
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assert tool.adapter is not None
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assert isinstance(tool.adapter, CrewAIRagAdapter)
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@patch("crewai_tools.adapters.crewai_rag_adapter.create_client")
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def test_rag_tool_legacy_config_does_not_override_new_config(
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mock_create_client: Mock,
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) -> None:
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"""Test that legacy 'embedder' key does not override 'embedding_model' if both present."""
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mock_embedding_func = MagicMock()
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mock_embedding_func.return_value = [[0.1] * 1536]
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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_create_client.return_value = mock_client
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with patch(
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"crewai_tools.tools.rag.rag_tool.build_embedder",
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return_value=mock_embedding_func,
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) as mock_build:
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class MyTool(RagTool):
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pass
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# Config with both old and new keys - new key should take precedence
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config = {
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"embedder": {
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"provider": "ollama",
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"config": {"model_name": "old-model"},
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},
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"embedding_model": {
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"provider": "openai",
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"config": {"model": "text-embedding-3-small", "api_key": "test-key"},
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},
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}
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# No deprecation warning for 'embedder' since 'embedding_model' is present
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with warnings.catch_warnings(record=True) as w:
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warnings.simplefilter("always")
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tool = MyTool(config=config)
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# Should NOT warn about 'embedder' since 'embedding_model' takes precedence
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embedder_warnings = [
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warning
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for warning in w
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if issubclass(warning.category, DeprecationWarning)
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and "embedder" in str(warning.message)
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]
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assert len(embedder_warnings) == 0
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assert tool.adapter is not None
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# Verify that the new 'embedding_model' config was used, not the legacy 'embedder'
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call_args = mock_build.call_args
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assert call_args is not None
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spec = call_args[0][0]
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assert spec["provider"] == "openai"
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