Spaces:
Sleeping
Sleeping
File size: 11,455 Bytes
6510698 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 |
"""
Unit tests for interface components.
"""
import pytest
from unittest.mock import MagicMock, patch
import sys
from pathlib import Path
# Add project root to path
project_root = Path(__file__).parent.parent.parent
sys.path.insert(0, str(project_root))
from app.interface import ExpertClassifier, ResponseGenerator, GradioInterface
from app.model_loader import ModelLoader
class TestExpertClassifier:
"""Test ExpertClassifier functionality."""
def test_classify_code_query(self):
"""Test classification of coding-related queries."""
queries = [
"How do I implement a binary search algorithm in Python?",
"What's the best way to debug JavaScript code?",
"Can you help me with this API integration?",
"I need help with my Java class implementation"
]
for query in queries:
result = ExpertClassifier.classify_query(query)
# Should be Code due to keywords like "algorithm", "Python", "JavaScript", "API", "Java"
assert result == "Code", f"Query '{query}' should be classified as Code, got {result}"
def test_classify_math_query(self):
"""Test classification of math-related queries."""
queries = [
"What is the derivative of x² + 3x + 1?",
"How do I solve this calculus problem?",
"Calculate the probability of this event",
"What's the integral of sin(x)?"
]
for query in queries:
result = ExpertClassifier.classify_query(query)
assert result == "Math"
def test_classify_reasoning_query(self):
"""Test classification of reasoning-related queries."""
queries = [
"Explain the logical reasoning behind the Monty Hall problem",
"Why does this argument make sense?",
"How should I analyze this situation?",
"What's the critical thinking approach here?"
]
for query in queries:
result = ExpertClassifier.classify_query(query)
assert result == "Reasoning"
def test_classify_multilingual_query(self):
"""Test classification of multilingual queries."""
queries = [
"Translate 'Hello, how are you?' to Spanish",
"What does this French phrase mean?",
"Help me learn German vocabulary",
"How do you say 'thank you' in Japanese?"
]
for query in queries:
result = ExpertClassifier.classify_query(query)
assert result == "Multilingual"
def test_classify_general_query(self):
"""Test classification of general queries."""
queries = [
"What are the benefits of renewable energy?",
"Tell me about the history of computers",
"Hello, how can you help me?",
"What's the weather like?"
]
for query in queries:
result = ExpertClassifier.classify_query(query)
assert result == "General"
def test_classify_empty_query(self):
"""Test classification of empty query."""
result = ExpertClassifier.classify_query("")
assert result == "General"
def test_classify_none_query(self):
"""Test classification of None query."""
result = ExpertClassifier.classify_query(None)
assert result == "General"
def test_classify_ambiguous_query(self):
"""Test classification of ambiguous query with multiple keywords."""
# Query with both code and math keywords
query = "How do I calculate the algorithm complexity in Python?"
result = ExpertClassifier.classify_query(query)
# Should pick the one with higher score (Code has 'algorithm' and 'Python')
assert result in ["Code", "Math"] # Either is acceptable for ambiguous cases
class TestResponseGenerator:
"""Test ResponseGenerator functionality."""
def setup_method(self):
"""Setup test fixtures."""
self.mock_model_loader = MagicMock(spec=ModelLoader)
self.response_generator = ResponseGenerator(self.mock_model_loader)
def test_generate_fallback_response_code(self):
"""Test fallback response generation for code queries."""
query = "How do I implement a function?"
expert_type = "Code"
response = self.response_generator.generate_fallback_response(query, expert_type)
assert "Code Expert" in response
assert query in response
assert "code examples" in response
def test_generate_fallback_response_math(self):
"""Test fallback response generation for math queries."""
query = "What is the derivative of x²?"
expert_type = "Math"
response = self.response_generator.generate_fallback_response(query, expert_type)
assert "Math Expert" in response
assert query in response
assert "step-by-step" in response
def test_generate_fallback_response_unknown_expert(self):
"""Test fallback response for unknown expert type."""
query = "Test query"
expert_type = "Unknown"
response = self.response_generator.generate_fallback_response(query, expert_type)
# Should default to General expert response
assert "General Expert" in response
def test_generate_response_model_not_loaded(self):
"""Test response generation when model is not loaded."""
self.mock_model_loader.is_loaded = False
query = "Test query"
response = self.response_generator.generate_response(query)
assert "Expert Type:" in response
assert "model is currently unavailable" in response
def test_generate_response_model_loaded_success(self):
"""Test successful response generation when model is loaded."""
# Setup mock model loader
self.mock_model_loader.is_loaded = True
self.mock_model_loader.pipeline = MagicMock()
self.mock_model_loader.tokenizer = MagicMock()
self.mock_model_loader.tokenizer.eos_token_id = 2
# Mock pipeline response
mock_response = [{
'generated_text': 'System message\nUser: Test query\nAssistant: This is a test response'
}]
self.mock_model_loader.pipeline.return_value = mock_response
query = "Test query"
response = self.response_generator.generate_response(query)
assert "Expert Type:" in response
assert "This is a test response" in response
# Verify pipeline was called with correct parameters
self.mock_model_loader.pipeline.assert_called_once()
call_args = self.mock_model_loader.pipeline.call_args
assert call_args[1]['max_new_tokens'] == 500
assert call_args[1]['temperature'] == 0.7
assert call_args[1]['do_sample'] is True
def test_generate_response_model_loaded_custom_params(self):
"""Test response generation with custom parameters."""
self.mock_model_loader.is_loaded = True
self.mock_model_loader.pipeline = MagicMock()
self.mock_model_loader.tokenizer = MagicMock()
self.mock_model_loader.tokenizer.eos_token_id = 2
mock_response = [{'generated_text': 'Test response'}]
self.mock_model_loader.pipeline.return_value = mock_response
query = "Test query"
response = self.response_generator.generate_response(
query,
max_tokens=200,
temperature=0.5
)
# Verify custom parameters were used
call_args = self.mock_model_loader.pipeline.call_args
assert call_args[1]['max_new_tokens'] == 200
assert call_args[1]['temperature'] == 0.5
def test_generate_response_pipeline_error(self):
"""Test response generation when pipeline raises an error."""
self.mock_model_loader.is_loaded = True
self.mock_model_loader.pipeline = MagicMock()
self.mock_model_loader.pipeline.side_effect = Exception("Pipeline error")
query = "Test query"
response = self.response_generator.generate_response(query)
assert "Error generating response" in response
assert "Pipeline error" in response
class TestGradioInterface:
"""Test GradioInterface functionality."""
def setup_method(self):
"""Setup test fixtures."""
self.mock_model_loader = MagicMock(spec=ModelLoader)
self.mock_model_loader.get_model_info.return_value = {
"status": "loaded",
"model_id": "test/model",
"revision": "abc123"
}
def test_gradio_interface_creation(self):
"""Test GradioInterface creation."""
interface = GradioInterface(self.mock_model_loader)
assert interface.model_loader == self.mock_model_loader
assert interface.response_generator is not None
assert interface.demo is None
@patch('gradio.Blocks')
def test_create_interface_model_loaded(self, mock_blocks):
"""Test interface creation when model is loaded."""
self.mock_model_loader.is_loaded = True
interface = GradioInterface(self.mock_model_loader)
demo = interface.create_interface()
# Verify Blocks was called
mock_blocks.assert_called_once()
# Verify model info was requested
self.mock_model_loader.get_model_info.assert_called()
@patch('gradio.Blocks')
def test_create_interface_model_not_loaded(self, mock_blocks):
"""Test interface creation when model is not loaded."""
self.mock_model_loader.is_loaded = False
self.mock_model_loader.get_model_info.return_value = {"status": "not_loaded"}
interface = GradioInterface(self.mock_model_loader)
demo = interface.create_interface()
# Verify Blocks was called
mock_blocks.assert_called_once()
@patch('gradio.Blocks')
def test_launch_creates_interface_if_needed(self, mock_blocks):
"""Test that launch creates interface if it doesn't exist."""
mock_demo = MagicMock()
mock_blocks.return_value.__enter__.return_value = mock_demo
interface = GradioInterface(self.mock_model_loader)
# Mock the launch method to avoid actual server startup
with patch.object(mock_demo, 'launch'):
interface.launch()
# Verify interface was created
assert interface.demo is not None
mock_demo.launch.assert_called_once()
def test_launch_uses_existing_interface(self):
"""Test that launch uses existing interface if available."""
interface = GradioInterface(self.mock_model_loader)
mock_demo = MagicMock()
interface.demo = mock_demo
# Mock the launch method
with patch.object(mock_demo, 'launch'):
interface.launch(server_name="127.0.0.1", server_port=8080)
# Verify existing demo was used
mock_demo.launch.assert_called_once_with(
server_name="127.0.0.1",
server_port=8080
)
if __name__ == "__main__":
pytest.main([__file__])
|