autogen/test/agentchat/contrib/test_img_utils.py

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import base64
import os
import pdb
import unittest
from unittest.mock import patch
import pytest
import requests
try:
from PIL import Image
from autogen.agentchat.contrib.img_utils import extract_img_paths, get_image_data, gpt4v_formatter, llava_formater
except ImportError:
skip = True
else:
skip = False
base64_encoded_image = (
"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAUAAAAFCAYAAACNbyblAAAAHElEQVQI12P4"
"//8/w38GIAXDIBKE0DHxgljNBAAO9TXL0Y4OHwAAAABJRU5ErkJggg=="
)
raw_encoded_image = (
"iVBORw0KGgoAAAANSUhEUgAAAAUAAAAFCAYAAACNbyblAAAAHElEQVQI12P4"
"//8/w38GIAXDIBKE0DHxgljNBAAO9TXL0Y4OHwAAAABJRU5ErkJggg=="
)
@pytest.mark.skipif(skip, reason="dependency is not installed")
class TestGetImageData(unittest.TestCase):
def test_http_image(self):
with patch("requests.get") as mock_get:
mock_response = requests.Response()
mock_response.status_code = 200
mock_response._content = b"fake image content"
mock_get.return_value = mock_response
result = get_image_data("http://example.com/image.png")
self.assertEqual(result, base64.b64encode(b"fake image content").decode("utf-8"))
def test_base64_encoded_image(self):
result = get_image_data(base64_encoded_image)
self.assertEqual(result, base64_encoded_image.split(",", 1)[1])
def test_local_image(self):
# Create a temporary file to simulate a local image file.
temp_file = "_temp.png"
image = Image.new("RGB", (60, 30), color=(73, 109, 137))
image.save(temp_file)
result = get_image_data(temp_file)
with open(temp_file, "rb") as temp_image_file:
temp_image_file.seek(0)
expected_content = base64.b64encode(temp_image_file.read()).decode("utf-8")
self.assertEqual(result, expected_content)
os.remove(temp_file)
@pytest.mark.skipif(skip, reason="dependency is not installed")
class TestLlavaFormater(unittest.TestCase):
def test_no_images(self):
"""
Test the llava_formater function with a prompt containing no images.
"""
prompt = "This is a test."
expected_output = (prompt, [])
result = llava_formater(prompt)
self.assertEqual(result, expected_output)
@patch("autogen.agentchat.contrib.img_utils.get_image_data")
def test_with_images(self, mock_get_image_data):
"""
Test the llava_formater function with a prompt containing images.
"""
# Mock the get_image_data function to return a fixed string.
mock_get_image_data.return_value = raw_encoded_image
prompt = "This is a test with an image <img http://example.com/image.png>."
expected_output = ("This is a test with an image <image>.", [raw_encoded_image])
result = llava_formater(prompt)
self.assertEqual(result, expected_output)
@patch("autogen.agentchat.contrib.img_utils.get_image_data")
def test_with_ordered_images(self, mock_get_image_data):
"""
Test the llava_formater function with ordered image tokens.
"""
# Mock the get_image_data function to return a fixed string.
mock_get_image_data.return_value = raw_encoded_image
prompt = "This is a test with an image <img http://example.com/image.png>."
expected_output = ("This is a test with an image <image 0>.", [raw_encoded_image])
result = llava_formater(prompt, order_image_tokens=True)
self.assertEqual(result, expected_output)
@pytest.mark.skipif(skip, reason="dependency is not installed")
class TestGpt4vFormatter(unittest.TestCase):
def test_no_images(self):
"""
Test the gpt4v_formatter function with a prompt containing no images.
"""
prompt = "This is a test."
expected_output = [{"type": "text", "text": prompt}]
result = gpt4v_formatter(prompt)
self.assertEqual(result, expected_output)
@patch("autogen.agentchat.contrib.img_utils.get_image_data")
def test_with_images(self, mock_get_image_data):
"""
Test the gpt4v_formatter function with a prompt containing images.
"""
# Mock the get_image_data function to return a fixed string.
mock_get_image_data.return_value = raw_encoded_image
prompt = "This is a test with an image <img http://example.com/image.png>."
expected_output = [
{"type": "text", "text": "This is a test with an image "},
{"type": "image_url", "image_url": {"url": base64_encoded_image}},
{"type": "text", "text": "."},
]
result = gpt4v_formatter(prompt)
self.assertEqual(result, expected_output)
@patch("autogen.agentchat.contrib.img_utils.get_image_data")
def test_multiple_images(self, mock_get_image_data):
"""
Test the gpt4v_formatter function with a prompt containing multiple images.
"""
# Mock the get_image_data function to return a fixed string.
mock_get_image_data.return_value = raw_encoded_image
prompt = (
"This is a test with images <img http://example.com/image1.png> and <img http://example.com/image2.png>."
)
expected_output = [
{"type": "text", "text": "This is a test with images "},
{"type": "image_url", "image_url": {"url": base64_encoded_image}},
{"type": "text", "text": " and "},
{"type": "image_url", "image_url": {"url": base64_encoded_image}},
{"type": "text", "text": "."},
]
result = gpt4v_formatter(prompt)
self.assertEqual(result, expected_output)
@pytest.mark.skipif(skip, reason="dependency is not installed")
class TestExtractImgPaths(unittest.TestCase):
def test_no_images(self):
"""
Test the extract_img_paths function with a paragraph containing no images.
"""
paragraph = "This is a test paragraph with no images."
expected_output = []
result = extract_img_paths(paragraph)
self.assertEqual(result, expected_output)
def test_with_images(self):
"""
Test the extract_img_paths function with a paragraph containing images.
"""
paragraph = (
"This is a test paragraph with images http://example.com/image1.jpg and http://example.com/image2.png."
)
expected_output = ["http://example.com/image1.jpg", "http://example.com/image2.png"]
result = extract_img_paths(paragraph)
self.assertEqual(result, expected_output)
def test_mixed_case(self):
"""
Test the extract_img_paths function with mixed case image extensions.
"""
paragraph = "Mixed case extensions http://example.com/image.JPG and http://example.com/image.Png."
expected_output = ["http://example.com/image.JPG", "http://example.com/image.Png"]
result = extract_img_paths(paragraph)
self.assertEqual(result, expected_output)
def test_local_paths(self):
"""
Test the extract_img_paths function with local file paths.
"""
paragraph = "Local paths image1.jpeg and image2.GIF."
expected_output = ["image1.jpeg", "image2.GIF"]
result = extract_img_paths(paragraph)
self.assertEqual(result, expected_output)
if __name__ == "__main__":
unittest.main()