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# coding=utf-8
# Copyright 2024 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import unittest
from pathlib import Path
import numpy as np
from PIL import Image
from transformers import is_torch_available
from transformers.testing_utils import get_tests_dir, require_torch
from smolagents.agent_types import _AGENT_TYPE_MAPPING
from smolagents.default_tools import FinalAnswerTool
from .test_tools import ToolTesterMixin
if is_torch_available():
import torch
class FinalAnswerToolTester(unittest.TestCase, ToolTesterMixin):
def setUp(self):
self.inputs = {"answer": "Final answer"}
self.tool = FinalAnswerTool()
def test_exact_match_arg(self):
result = self.tool("Final answer")
self.assertEqual(result, "Final answer")
def test_exact_match_kwarg(self):
result = self.tool(answer=self.inputs["answer"])
self.assertEqual(result, "Final answer")
def create_inputs(self):
inputs_text = {"answer": "Text input"}
inputs_image = {"answer": Image.open(Path(get_tests_dir("fixtures")) / "000000039769.png").resize((512, 512))}
inputs_audio = {"answer": torch.Tensor(np.ones(3000))}
return {"string": inputs_text, "image": inputs_image, "audio": inputs_audio}
@require_torch
def test_agent_type_output(self):
inputs = self.create_inputs()
for input_type, input in inputs.items():
output = self.tool(**input, sanitize_inputs_outputs=True)
agent_type = _AGENT_TYPE_MAPPING[input_type]
self.assertTrue(isinstance(output, agent_type))
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