| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| import unittest |
|
|
| import pytest |
|
|
| from smolagents.agent_types import _AGENT_TYPE_MAPPING |
| from smolagents.default_tools import ( |
| DuckDuckGoSearchTool, |
| PythonInterpreterTool, |
| SpeechToTextTool, |
| VisitWebpageTool, |
| WikipediaSearchTool, |
| ) |
|
|
| from .test_tools import ToolTesterMixin |
| from .utils.markers import require_run_all |
|
|
|
|
| class DefaultToolTests(unittest.TestCase): |
| def test_visit_webpage(self): |
| arguments = {"url": "https://en.wikipedia.org/wiki/United_States_Secretary_of_Homeland_Security"} |
| result = VisitWebpageTool()(arguments) |
| assert isinstance(result, str) |
| assert "* [About Wikipedia](/wiki/Wikipedia:About)" in result |
|
|
| @require_run_all |
| def test_ddgs_with_kwargs(self): |
| result = DuckDuckGoSearchTool(timeout=20)("DeepSeek parent company") |
| assert isinstance(result, str) |
|
|
|
|
| class TestPythonInterpreterTool(ToolTesterMixin): |
| def setup_method(self): |
| self.tool = PythonInterpreterTool(authorized_imports=["numpy"]) |
| self.tool.setup() |
|
|
| def test_exact_match_arg(self): |
| result = self.tool("(2 / 2) * 4") |
| assert result == "Stdout:\n\nOutput: 4.0" |
|
|
| def test_exact_match_kwarg(self): |
| result = self.tool(code="(2 / 2) * 4") |
| assert result == "Stdout:\n\nOutput: 4.0" |
|
|
| def test_agent_type_output(self): |
| inputs = ["2 * 2"] |
| output = self.tool(*inputs, sanitize_inputs_outputs=True) |
| output_type = _AGENT_TYPE_MAPPING[self.tool.output_type] |
| assert isinstance(output, output_type) |
|
|
| def test_agent_types_inputs(self): |
| inputs = ["2 * 2"] |
| _inputs = [] |
|
|
| for _input, expected_input in zip(inputs, self.tool.inputs.values()): |
| input_type = expected_input["type"] |
| if isinstance(input_type, list): |
| _inputs.append([_AGENT_TYPE_MAPPING[_input_type](_input) for _input_type in input_type]) |
| else: |
| _inputs.append(_AGENT_TYPE_MAPPING[input_type](_input)) |
|
|
| |
| output = self.tool(*inputs, sanitize_inputs_outputs=True) |
| output_type = _AGENT_TYPE_MAPPING[self.tool.output_type] |
| assert isinstance(output, output_type) |
|
|
| def test_imports_work(self): |
| result = self.tool("import numpy as np") |
| assert "import from numpy is not allowed" not in result.lower() |
|
|
| def test_unauthorized_imports_fail(self): |
| with pytest.raises(Exception) as e: |
| self.tool("import sympy as sp") |
| assert "sympy" in str(e).lower() |
|
|
|
|
| class TestSpeechToTextTool: |
| def test_new_instance(self): |
| from transformers.models.whisper import WhisperForConditionalGeneration, WhisperProcessor |
|
|
| tool = SpeechToTextTool() |
| assert tool is not None |
| assert tool.pre_processor_class == WhisperProcessor |
| assert tool.model_class == WhisperForConditionalGeneration |
|
|
| def test_initialization(self): |
| from transformers.models.whisper import WhisperForConditionalGeneration, WhisperProcessor |
|
|
| tool = SpeechToTextTool(model="dummy_model_id") |
| assert tool is not None |
| assert tool.pre_processor_class == WhisperProcessor |
| assert tool.model_class == WhisperForConditionalGeneration |
|
|
|
|
| @pytest.mark.parametrize( |
| "language, content_type, extract_format, query", |
| [ |
| ("en", "summary", "HTML", "Python_(programming_language)"), |
| ("en", "text", "WIKI", "Python_(programming_language)"), |
| ("es", "summary", "HTML", "Python_(lenguaje_de_programación)"), |
| ("es", "text", "WIKI", "Python_(lenguaje_de_programación)"), |
| ], |
| ) |
| def test_wikipedia_search(language, content_type, extract_format, query): |
| tool = WikipediaSearchTool( |
| user_agent="TestAgent (test@example.com)", |
| language=language, |
| content_type=content_type, |
| extract_format=extract_format, |
| ) |
|
|
| result = tool.forward(query) |
|
|
| assert isinstance(result, str), "Output should be a string" |
| assert "✅ **Wikipedia Page:**" in result, "Response should contain Wikipedia page title" |
| assert "🔗 **Read more:**" in result, "Response should contain Wikipedia page URL" |
|
|
| if content_type == "summary": |
| assert len(result.split()) < 1000, "Summary mode should return a shorter text" |
| if content_type == "text": |
| assert len(result.split()) > 1000, "Full text mode should return a longer text" |
|
|