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ai-agent-book 精选快照(<2MB 代码与文档,来自 github.com/bojieli/ai-agent-book)
2026-08-20 13:12:50 +00:00

230 lines
7.5 KiB
Python

"""
Test script for multimodal agent functionality
"""
import asyncio
import unittest
from unittest.mock import Mock, patch, AsyncMock
from pathlib import Path
from agent import MultimodalAgent, MultimodalContent, MultimodalTools, Message
from config import ExtractionMode, Provider
class TestMultimodalContent(unittest.TestCase):
"""Test MultimodalContent class"""
def test_content_creation(self):
"""Test creating multimodal content"""
content = MultimodalContent(
type="image",
path="test.jpg",
mime_type="image/jpeg"
)
self.assertEqual(content.type, "image")
self.assertEqual(content.path, "test.jpg")
self.assertEqual(content.mime_type, "image/jpeg")
def test_get_base64(self):
"""Test base64 encoding"""
content = MultimodalContent(
type="text",
data=b"Hello World"
)
base64_str = content.get_base64()
self.assertEqual(base64_str, "SGVsbG8gV29ybGQ=")
class TestMessage(unittest.TestCase):
"""Test Message class"""
def test_message_creation(self):
"""Test creating messages"""
msg = Message(
role="user",
content="Hello"
)
self.assertEqual(msg.role, "user")
self.assertEqual(msg.content, "Hello")
def test_message_to_dict(self):
"""Test converting message to dictionary"""
msg = Message(
role="assistant",
content="Hi there",
tool_calls=[{"id": "1", "function": {"name": "test"}}]
)
msg_dict = msg.to_dict()
self.assertEqual(msg_dict["role"], "assistant")
self.assertEqual(msg_dict["content"], "Hi there")
self.assertIn("tool_calls", msg_dict)
class TestMultimodalAgent(unittest.IsolatedAsyncioTestCase):
"""Test MultimodalAgent class"""
async def test_agent_initialization(self):
"""Test agent initialization"""
agent = MultimodalAgent(
model="gemini-3.5-flash",
mode=ExtractionMode.NATIVE,
enable_tools=False
)
self.assertEqual(agent.current_model, "gemini-3.5-flash")
self.assertEqual(agent.extraction_mode, ExtractionMode.NATIVE)
self.assertFalse(agent.enable_multimodal_tools)
self.assertIsNone(agent.tools)
async def test_agent_with_tools(self):
"""Test agent initialization with tools"""
agent = MultimodalAgent(
model="gemini-3.5-flash",
mode=ExtractionMode.EXTRACT_TO_TEXT,
enable_tools=True
)
self.assertTrue(agent.enable_multimodal_tools)
self.assertIsNotNone(agent.tools)
self.assertEqual(len(agent.tool_definitions), 3)
async def test_conversation_history(self):
"""Test conversation history management"""
agent = MultimodalAgent()
# Add messages
agent.add_message(Message(role="user", content="Hello"))
agent.add_message(Message(role="assistant", content="Hi"))
history = agent.get_conversation_history()
self.assertEqual(len(history), 2)
self.assertEqual(history[0]["role"], "user")
self.assertEqual(history[1]["role"], "assistant")
# Reset conversation
agent.reset_conversation()
history = agent.get_conversation_history()
self.assertEqual(len(history), 0)
@patch('agent.genai.Client')
async def test_extract_pdf_to_text(self, mock_client_class):
"""Test PDF extraction to text"""
agent = MultimodalAgent(mode=ExtractionMode.EXTRACT_TO_TEXT)
# Mock Gemini response
mock_response = Mock()
mock_response.candidates = []
mock_response.text = "Extracted PDF text"
mock_client = Mock()
mock_client.models.generate_content.return_value = mock_response
mock_client_class.return_value = mock_client
content = MultimodalContent(
type="pdf",
data=b"PDF content"
)
result = await agent._extract_pdf_to_text(content)
self.assertEqual(result, "Extracted PDF text")
@patch('agent.AsyncOpenAI')
async def test_extract_image_to_text(self, mock_openai_class):
"""Test image extraction to text"""
agent = MultimodalAgent(mode=ExtractionMode.EXTRACT_TO_TEXT)
# Mock OpenAI response
mock_client = AsyncMock()
mock_response = AsyncMock()
mock_choice = Mock()
mock_message = Mock()
mock_message.content = "Image description"
mock_choice.message = mock_message
mock_response.choices = [mock_choice]
mock_client.chat.completions.create.return_value = mock_response
mock_openai_class.return_value = mock_client
content = MultimodalContent(
type="image",
data=b"Image data",
mime_type="image/jpeg"
)
result = await agent._extract_image_to_text(content)
self.assertEqual(result, "Image description")
@patch('agent.genai.Client')
async def test_process_native_gemini(self, mock_client_class):
"""Test native Gemini processing"""
agent = MultimodalAgent(
model="gemini-3.5-flash",
mode=ExtractionMode.NATIVE
)
# Mock Gemini response
mock_response = Mock()
mock_response.candidates = []
mock_response.text = "Gemini analysis result"
mock_client = Mock()
mock_client.models.generate_content.return_value = mock_response
mock_client_class.return_value = mock_client
content = MultimodalContent(
type="pdf",
data=b"PDF content"
)
result = await agent._process_native_gemini(content, "Analyze this")
self.assertEqual(result, "Gemini analysis result")
class TestMultimodalTools(unittest.IsolatedAsyncioTestCase):
"""Test MultimodalTools class"""
async def test_tools_initialization(self):
"""Test tools initialization"""
agent = MultimodalAgent(enable_tools=True)
tools = MultimodalTools(agent)
self.assertEqual(tools.agent, agent)
@patch('agent.AsyncOpenAI')
async def test_analyze_image_tool(self, mock_openai_class):
"""Test image analysis tool"""
agent = MultimodalAgent(enable_tools=True)
# Mock OpenAI response
mock_client = AsyncMock()
mock_response = AsyncMock()
mock_choice = Mock()
mock_message = Mock()
mock_message.content = "Image analysis"
mock_choice.message = mock_message
mock_response.choices = [mock_choice]
mock_client.chat.completions.create.return_value = mock_response
mock_openai_class.return_value = mock_client
# Create temporary test image
import tempfile
with tempfile.NamedTemporaryFile(suffix='.jpg', delete=False) as tmp:
tmp.write(b"test image data")
tmp_path = tmp.name
try:
result = await agent.tools.analyze_image(tmp_path, "What's in this image?")
self.assertEqual(result, "Image analysis")
finally:
Path(tmp_path).unlink()
def run_tests():
"""Run all tests"""
unittest.main(argv=[''], exit=False, verbosity=2)
if __name__ == "__main__":
run_tests()