mirror of
https://github.com/crewAIInc/crewAI.git
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a928cde6ee
* fix: ensure config is not flattened, add tests * chore: refactor inits to model_validator * chore: refactor rag tool config parsing * chore: add initial docs * chore: add additional validation aliases for provider env vars * chore: add solid docs * chore: move imports to top * fix: revert circular import * fix: lazy import qdrant-client * fix: allow collection name config * chore: narrow model names for google * chore: update additional docs * chore: add backward compat on model name aliases * chore: add tests for config changes
116 lines
4.0 KiB
Python
116 lines
4.0 KiB
Python
from unittest.mock import MagicMock, Mock, patch
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from crewai_tools.adapters.crewai_rag_adapter import CrewAIRagAdapter
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from crewai_tools.tools.pdf_search_tool.pdf_search_tool import PDFSearchTool
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@patch("crewai_tools.adapters.crewai_rag_adapter.create_client")
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def test_pdf_search_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 PDFSearchTool accepts Azure config without requiring env vars.
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This verifies the fix for the reported issue where PDFSearchTool would
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throw a validation error:
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pydantic_core._pydantic_core.ValidationError: 1 validation error for PDFSearchTool
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EMBEDDINGS_OPENAI_API_KEY
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Field required [type=missing, input_value={}, input_type=dict]
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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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# 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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# This is the exact config format from the bug report
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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-litellm-api-key",
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"api_base": "https://test.litellm.proxy/",
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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 = PDFSearchTool(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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assert tool.name == "Search a PDF's content"
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@patch("crewai_tools.adapters.crewai_rag_adapter.create_client")
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def test_pdf_search_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 PDFSearchTool 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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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 = PDFSearchTool(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_pdf_search_tool_with_vectordb_and_embedding_config(
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mock_create_client: Mock,
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) -> None:
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"""Test PDFSearchTool with both vector DB and embedding 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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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": {
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"model": "text-embedding-3-large",
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"api_key": "sk-test-key",
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},
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},
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}
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tool = PDFSearchTool(config=config)
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assert tool.adapter is not None
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assert isinstance(tool.adapter, CrewAIRagAdapter) |