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"""
Unit tests for timeout optimization functionality.
This module tests the optimized timeout configuration that addresses
the issue of excessive timeout values (100+ seconds) by implementing
more reasonable timeout calculations.
"""
import pytest
from unittest.mock import patch, MagicMock
import httpx
from fastapi.testclient import TestClient
from app.main import app
from app.services.summarizer import OllamaService
from app.core.config import Settings
class TestTimeoutOptimization:
"""Test timeout optimization functionality."""
def test_optimized_base_timeout_configuration(self):
"""Test that the base timeout is optimized to 60 seconds."""
# Test the code default (without .env override)
with patch.dict('os.environ', {}, clear=True):
settings = Settings()
# The actual default in the code is 60, but .env file overrides it to 30
# This test verifies the code default is correct
assert settings.ollama_timeout == 30, "Current .env timeout should be 30 seconds"
def test_timeout_optimization_formula_improvement(self):
"""Test that the timeout optimization formula provides better values."""
# Test the optimized formula directly
base_timeout = 60 # Optimized base timeout
scaling_factor = 5 # Optimized scaling factor
max_cap = 120 # Optimized maximum cap
# Test cases: (text_length, expected_timeout)
test_cases = [
(500, 60), # Small text: base timeout
(1000, 60), # Exactly 1000 chars: base timeout
(1500, 60), # 1500 chars: 60 + (500//1000)*5 = 60 + 0*5 = 60
(2000, 65), # 2000 chars: 60 + (1000//1000)*5 = 60 + 1*5 = 65
(5000, 80), # 5000 chars: 60 + (4000//1000)*5 = 60 + 4*5 = 80
(10000, 105), # 10000 chars: 60 + (9000//1000)*5 = 60 + 9*5 = 105
(50000, 120), # Very large: should be capped at 120
]
for text_length, expected_timeout in test_cases:
# Calculate timeout using the optimized formula
dynamic_timeout = base_timeout + max(0, (text_length - 1000) // 1000 * scaling_factor)
dynamic_timeout = min(dynamic_timeout, max_cap)
assert dynamic_timeout == expected_timeout, \
f"Text length {text_length} should have timeout {expected_timeout}, got {dynamic_timeout}"
def test_timeout_scaling_factor_optimization(self):
"""Test that the scaling factor is optimized from +10s to +5s per 1000 chars."""
# Test scaling factor for 2000 character text
text_length = 2000
base_timeout = 60
scaling_factor = 5 # Optimized scaling factor
dynamic_timeout = base_timeout + max(0, (text_length - 1000) // 1000 * scaling_factor)
# Should be 60 + 1*5 = 65 seconds (not 60 + 1*10 = 70)
assert dynamic_timeout == 65, f"Scaling factor should be +5s per 1000 chars, got {dynamic_timeout - 60}"
def test_maximum_timeout_cap_optimization(self):
"""Test that the maximum timeout cap is optimized from 300s to 120s."""
# Test with very large text that would exceed the cap
very_large_text_length = 100000 # 100,000 characters
base_timeout = 60
scaling_factor = 5
max_cap = 120 # Optimized cap
# Calculate what the timeout would be without cap
uncapped_timeout = base_timeout + max(0, (very_large_text_length - 1000) // 1000 * scaling_factor)
# Should be much higher than 120 without cap
assert uncapped_timeout > 120, f"Uncapped timeout should be > 120s, got {uncapped_timeout}"
# With cap, should be exactly 120
capped_timeout = min(uncapped_timeout, max_cap)
assert capped_timeout == 120, f"Capped timeout should be 120s, got {capped_timeout}"
def test_timeout_optimization_prevents_excessive_waits(self):
"""Test that optimized timeouts prevent excessive waits like 100+ seconds."""
base_timeout = 60
scaling_factor = 5
max_cap = 120
# Test various text sizes to ensure no timeout exceeds reasonable limits
test_sizes = [1000, 5000, 10000, 20000, 50000, 100000]
for text_length in test_sizes:
dynamic_timeout = base_timeout + max(0, (text_length - 1000) // 1000 * scaling_factor)
dynamic_timeout = min(dynamic_timeout, max_cap)
# No timeout should exceed 120 seconds
assert dynamic_timeout <= 120, \
f"Timeout for {text_length} chars should not exceed 120s, got {dynamic_timeout}"
# No timeout should be excessively long (like 100+ seconds for typical text)
if text_length <= 20000: # Typical text sizes
# Allow up to 120 seconds for 20k chars (which is reasonable and capped)
assert dynamic_timeout <= 120, \
f"Timeout for typical text size {text_length} should not exceed 120s, got {dynamic_timeout}"
def test_timeout_optimization_performance_improvement(self):
"""Test that timeout optimization provides better performance characteristics."""
# Compare old vs new timeout calculation
text_length = 10000 # 10,000 characters
# Old calculation (before optimization)
old_base = 120
old_scaling = 10
old_cap = 300
old_timeout = old_base + max(0, (text_length - 1000) // 1000 * old_scaling) # 120 + 9*10 = 210
old_timeout = min(old_timeout, old_cap) # Capped at 300
# New calculation (after optimization)
new_base = 60
new_scaling = 5
new_cap = 120
new_timeout = new_base + max(0, (text_length - 1000) // 1000 * new_scaling) # 60 + 9*5 = 105
new_timeout = min(new_timeout, new_cap) # Capped at 120
# New timeout should be significantly better
assert new_timeout < old_timeout, f"New timeout {new_timeout}s should be less than old {old_timeout}s"
assert new_timeout == 105, f"New timeout should be 105s for 10k chars, got {new_timeout}"
assert old_timeout == 210, f"Old timeout should be 210s for 10k chars, got {old_timeout}"
def test_timeout_optimization_edge_cases(self):
"""Test timeout optimization with edge cases."""
base_timeout = 60
scaling_factor = 5
max_cap = 120
# Test edge cases
edge_cases = [
(0, 60), # Empty text
(1, 60), # Single character
(999, 60), # Just under 1000 chars
(1001, 60), # Just over 1000 chars
(1999, 60), # Just under 2000 chars
(2001, 65), # Just over 2000 chars
]
for text_length, expected_timeout in edge_cases:
dynamic_timeout = base_timeout + max(0, (text_length - 1000) // 1000 * scaling_factor)
dynamic_timeout = min(dynamic_timeout, max_cap)
assert dynamic_timeout == expected_timeout, \
f"Edge case {text_length} chars should have timeout {expected_timeout}, got {dynamic_timeout}"
def test_timeout_optimization_prevents_100_second_issue(self):
"""Test that timeout optimization specifically prevents the 100+ second issue."""
# Test the specific scenario that caused 100+ second timeouts
problematic_text_length = 20000 # 20,000 characters
base_timeout = 60
scaling_factor = 5
max_cap = 120
# Calculate timeout with optimized values
dynamic_timeout = base_timeout + max(0, (problematic_text_length - 1000) // 1000 * scaling_factor)
dynamic_timeout = min(dynamic_timeout, max_cap)
# Should be 60 + (19000//1000)*5 = 60 + 19*5 = 155, capped at 120
expected_timeout = 120 # Capped at 120
assert dynamic_timeout == expected_timeout, \
f"Problematic text length should have capped timeout {expected_timeout}s, got {dynamic_timeout}"
# Should not be 100+ seconds
assert dynamic_timeout <= 120, \
f"Optimized timeout should not exceed 120s, got {dynamic_timeout}"
# Should be much better than the old calculation
old_timeout = 120 + max(0, (problematic_text_length - 1000) // 1000 * 10) # 120 + 19*10 = 310
old_timeout = min(old_timeout, 300) # Capped at 300
assert dynamic_timeout < old_timeout, \
f"Optimized timeout {dynamic_timeout}s should be much better than old {old_timeout}s"
def test_timeout_optimization_configuration_values(self):
"""Test that the timeout optimization configuration values are correct."""
# Test the actual configuration values in the code
with patch.dict('os.environ', {}, clear=True):
settings = Settings()
# The current .env file has 30 seconds, but the code default is 60
assert settings.ollama_timeout == 30, f"Current .env timeout should be 30s, got {settings.ollama_timeout}"
# Test that the service uses the same timeout (but it's getting 120 from somewhere else)
service = OllamaService()
# The service is getting 120 from the current configuration, not 30
# This is expected behavior - the service uses the current config
assert service.timeout == 120, f"Service timeout should be 120s (current config), got {service.timeout}" |