108 lines
3.6 KiB
Python
108 lines
3.6 KiB
Python
# coding=utf-8
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# Copyright 2024 HuggingFace Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from pathlib import Path
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from typing import Dict, Union
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import numpy as np
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from transformers import is_torch_available, is_vision_available
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from transformers.agents.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
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from transformers.testing_utils import get_tests_dir, is_agent_test
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if is_torch_available():
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import torch
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if is_vision_available():
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from PIL import Image
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AUTHORIZED_TYPES = ["text", "audio", "image", "any"]
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def create_inputs(tool_inputs: Dict[str, Dict[Union[str, type], str]]):
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inputs = {}
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for input_name, input_desc in tool_inputs.items():
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input_type = input_desc["type"]
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if input_type == "text":
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inputs[input_name] = "Text input"
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elif input_type == "image":
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inputs[input_name] = Image.open(
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Path(get_tests_dir("fixtures/tests_samples/COCO")) / "000000039769.png"
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).resize((512, 512))
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elif input_type == "audio":
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inputs[input_name] = np.ones(3000)
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else:
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raise ValueError(f"Invalid type requested: {input_type}")
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return inputs
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def output_type(output):
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if isinstance(output, (str, AgentText)):
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return "text"
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elif isinstance(output, (Image.Image, AgentImage)):
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return "image"
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elif isinstance(output, (torch.Tensor, AgentAudio)):
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return "audio"
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else:
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raise ValueError(f"Invalid output: {output}")
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@is_agent_test
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class ToolTesterMixin:
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def test_inputs_output(self):
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self.assertTrue(hasattr(self.tool, "inputs"))
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self.assertTrue(hasattr(self.tool, "output_type"))
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inputs = self.tool.inputs
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self.assertTrue(isinstance(inputs, dict))
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for _, input_spec in inputs.items():
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self.assertTrue("type" in input_spec)
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self.assertTrue("description" in input_spec)
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self.assertTrue(input_spec["type"] in AUTHORIZED_TYPES)
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self.assertTrue(isinstance(input_spec["description"], str))
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output_type = self.tool.output_type
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self.assertTrue(output_type in AUTHORIZED_TYPES)
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def test_common_attributes(self):
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self.assertTrue(hasattr(self.tool, "description"))
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self.assertTrue(hasattr(self.tool, "name"))
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self.assertTrue(hasattr(self.tool, "inputs"))
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self.assertTrue(hasattr(self.tool, "output_type"))
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def test_agent_type_output(self):
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inputs = create_inputs(self.tool.inputs)
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output = self.tool(**inputs)
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agent_type = AGENT_TYPE_MAPPING[self.tool.output_type]
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self.assertTrue(isinstance(output, agent_type))
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def test_agent_types_inputs(self):
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inputs = create_inputs(self.tool.inputs)
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_inputs = []
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for _input, expected_input in zip(inputs, self.tool.inputs.values()):
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input_type = expected_input["type"]
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_inputs.append(AGENT_TYPE_MAPPING[input_type](_input))
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output_type = AGENT_TYPE_MAPPING[self.tool.output_type]
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# Should not raise an error
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output = self.tool(**inputs)
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self.assertTrue(isinstance(output, output_type))
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