fleet-memory/hindsight-api/tests/test_config_validation.py
Nicolò Boschi 0430588e32
fix: hindsight-embed profiles are not loaded correctly (#316)
* fix: hindsight-embed profiles are not loaded correctly

* fix: hindsight-embed profiles are not loaded correctly
2026-02-06 17:13:54 +01:00

109 lines
3.8 KiB
Python

"""
Tests for configuration validation.
Verifies that config validation catches invalid parameter combinations.
"""
import os
import pytest
@pytest.fixture(autouse=True)
def setup_test_env():
"""Set up environment for each test, restoring original values after."""
from hindsight_api.config import clear_config_cache
# Save original environment values
env_vars_to_save = [
"HINDSIGHT_API_RETAIN_MAX_COMPLETION_TOKENS",
"HINDSIGHT_API_RETAIN_CHUNK_SIZE",
"HINDSIGHT_API_LLM_PROVIDER",
"HINDSIGHT_API_LLM_MODEL",
]
# Save original values
original_values = {}
for key in env_vars_to_save:
original_values[key] = os.environ.get(key)
clear_config_cache()
yield
# Restore original environment
for key, original_value in original_values.items():
if original_value is None:
os.environ.pop(key, None)
else:
os.environ[key] = original_value
clear_config_cache()
def test_retain_max_completion_tokens_must_be_greater_than_chunk_size():
"""Test that RETAIN_MAX_COMPLETION_TOKENS > RETAIN_CHUNK_SIZE validation works."""
from hindsight_api.config import HindsightConfig
# Set invalid config: max_completion_tokens <= chunk_size
os.environ["HINDSIGHT_API_RETAIN_MAX_COMPLETION_TOKENS"] = "1000"
os.environ["HINDSIGHT_API_RETAIN_CHUNK_SIZE"] = "2000"
os.environ["HINDSIGHT_API_LLM_PROVIDER"] = "mock"
# Should raise ValueError with helpful message
with pytest.raises(ValueError) as exc_info:
HindsightConfig.from_env()
error_message = str(exc_info.value)
# Verify error message contains helpful information
assert "HINDSIGHT_API_RETAIN_MAX_COMPLETION_TOKENS" in error_message
assert "1000" in error_message
assert "HINDSIGHT_API_RETAIN_CHUNK_SIZE" in error_message
assert "2000" in error_message
assert "must be greater than" in error_message
assert "You have two options to fix this:" in error_message
assert "Increase HINDSIGHT_API_RETAIN_MAX_COMPLETION_TOKENS" in error_message
assert "Use a model that supports" in error_message
def test_retain_max_completion_tokens_equal_to_chunk_size_fails():
"""Test that RETAIN_MAX_COMPLETION_TOKENS == RETAIN_CHUNK_SIZE also fails."""
from hindsight_api.config import HindsightConfig
# Set invalid config: max_completion_tokens == chunk_size
os.environ["HINDSIGHT_API_RETAIN_MAX_COMPLETION_TOKENS"] = "3000"
os.environ["HINDSIGHT_API_RETAIN_CHUNK_SIZE"] = "3000"
os.environ["HINDSIGHT_API_LLM_PROVIDER"] = "mock"
# Should raise ValueError
with pytest.raises(ValueError) as exc_info:
HindsightConfig.from_env()
error_message = str(exc_info.value)
assert "must be greater than" in error_message
def test_valid_retain_config_succeeds():
"""Test that valid config with max_completion_tokens > chunk_size works."""
from hindsight_api.config import HindsightConfig
# Set valid config: max_completion_tokens > chunk_size
os.environ["HINDSIGHT_API_RETAIN_MAX_COMPLETION_TOKENS"] = "64000"
os.environ["HINDSIGHT_API_RETAIN_CHUNK_SIZE"] = "3000"
os.environ["HINDSIGHT_API_LLM_PROVIDER"] = "mock"
# Should not raise
config = HindsightConfig.from_env()
assert config.retain_max_completion_tokens == 64000
assert config.retain_chunk_size == 3000
# Note: The BadRequestError wrapping is implemented in fact_extraction.py
# but requires a complex integration test setup. The functionality is
# straightforward: when a BadRequestError containing keywords like
# "max_tokens", "max_completion_tokens", or "maximum context" is caught,
# it's wrapped in a ValueError with helpful guidance.
#
# The config validation tests above ensure users get early feedback
# about invalid configurations before runtime errors occur.