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"""
Tests for api_key ${VAR} environment variable substitution in configuration.
"""
import os
import tempfile
import unittest
from openevolve.config import Config, LLMModelConfig, _resolve_env_var
class TestEnvVarSubstitution(unittest.TestCase):
"""Tests for ${VAR} environment variable substitution in api_key fields"""
def setUp(self):
"""Set up test environment variables"""
self.test_env_var = "TEST_OPENEVOLVE_API_KEY"
self.test_api_key = "test-secret-key-12345"
os.environ[self.test_env_var] = self.test_api_key
def tearDown(self):
"""Clean up test environment variables"""
if self.test_env_var in os.environ:
del os.environ[self.test_env_var]
def test_resolve_env_var_with_match(self):
"""Test that _resolve_env_var resolves ${VAR} syntax"""
result = _resolve_env_var(f"${{{self.test_env_var}}}")
self.assertEqual(result, self.test_api_key)
def test_resolve_env_var_no_match(self):
"""Test that strings without ${VAR} are returned unchanged"""
result = _resolve_env_var("regular-api-key")
self.assertEqual(result, "regular-api-key")
def test_resolve_env_var_none(self):
"""Test that None is returned unchanged"""
result = _resolve_env_var(None)
self.assertIsNone(result)
def test_resolve_env_var_missing_var(self):
"""Test that missing environment variable raises ValueError"""
with self.assertRaises(ValueError) as context:
_resolve_env_var("${NONEXISTENT_ENV_VAR_12345}")
self.assertIn("NONEXISTENT_ENV_VAR_12345", str(context.exception))
self.assertIn("is not set", str(context.exception))
def test_api_key_env_var_in_model_config(self):
"""Test that api_key ${VAR} works in LLMModelConfig"""
model_config = LLMModelConfig(name="test-model", api_key=f"${{{self.test_env_var}}}")
self.assertEqual(model_config.api_key, self.test_api_key)
def test_api_key_direct_value(self):
"""Test that direct api_key value still works"""
direct_key = "direct-api-key-value"
model_config = LLMModelConfig(name="test-model", api_key=direct_key)
self.assertEqual(model_config.api_key, direct_key)
def test_api_key_none(self):
"""Test that api_key can be None"""
model_config = LLMModelConfig(name="test-model", api_key=None)
self.assertIsNone(model_config.api_key)
def test_api_key_env_var_in_llm_config(self):
"""Test that api_key ${VAR} works at LLM config level"""
yaml_config = {
"log_level": "INFO",
"llm": {
"api_base": "https://api.openai.com/v1",
"api_key": f"${{{self.test_env_var}}}",
"models": [{"name": "test-model", "weight": 1.0}],
},
}
config = Config.from_dict(yaml_config)
self.assertEqual(config.llm.api_key, self.test_api_key)
# Models should inherit the resolved api_key
self.assertEqual(config.llm.models[0].api_key, self.test_api_key)
def test_api_key_env_var_per_model(self):
"""Test that api_key ${VAR} can be specified per model"""
# Set up a second env var for testing
second_env_var = "TEST_OPENEVOLVE_API_KEY_2"
second_api_key = "second-secret-key-67890"
os.environ[second_env_var] = second_api_key
try:
yaml_config = {
"log_level": "INFO",
"llm": {
"api_base": "https://api.openai.com/v1",
"models": [
{
"name": "model-1",
"weight": 1.0,
"api_key": f"${{{self.test_env_var}}}",
},
{
"name": "model-2",
"weight": 0.5,
"api_key": f"${{{second_env_var}}}",
},
],
},
}
config = Config.from_dict(yaml_config)
self.assertEqual(config.llm.models[0].api_key, self.test_api_key)
self.assertEqual(config.llm.models[1].api_key, second_api_key)
finally:
if second_env_var in os.environ:
del os.environ[second_env_var]
def test_api_key_env_var_in_evaluator_models(self):
"""Test that api_key ${VAR} works in evaluator_models"""
yaml_config = {
"log_level": "INFO",
"llm": {
"api_base": "https://api.openai.com/v1",
"models": [{"name": "evolution-model", "weight": 1.0, "api_key": "direct-key"}],
"evaluator_models": [
{
"name": "evaluator-model",
"weight": 1.0,
"api_key": f"${{{self.test_env_var}}}",
}
],
},
}
config = Config.from_dict(yaml_config)
self.assertEqual(config.llm.evaluator_models[0].api_key, self.test_api_key)
def test_yaml_file_loading_with_env_var(self):
"""Test loading api_key ${VAR} from actual YAML file"""
yaml_content = f"""
log_level: INFO
llm:
api_base: https://api.openai.com/v1
api_key: ${{{self.test_env_var}}}
models:
- name: test-model
weight: 1.0
"""
with tempfile.NamedTemporaryFile(mode="w", suffix=".yaml", delete=False) as f:
f.write(yaml_content)
f.flush()
try:
config = Config.from_yaml(f.name)
self.assertEqual(config.llm.api_key, self.test_api_key)
finally:
os.unlink(f.name)
def test_mixed_api_key_sources(self):
"""Test mixing direct api_key and ${VAR} in same config"""
yaml_config = {
"log_level": "INFO",
"llm": {
"api_base": "https://api.openai.com/v1",
"api_key": "llm-level-direct-key",
"models": [
{
"name": "model-with-env",
"weight": 1.0,
"api_key": f"${{{self.test_env_var}}}",
},
{
"name": "model-with-direct",
"weight": 0.5,
"api_key": "model-direct-key",
},
],
},
}
config = Config.from_dict(yaml_config)
self.assertEqual(config.llm.api_key, "llm-level-direct-key")
self.assertEqual(config.llm.models[0].api_key, self.test_api_key)
self.assertEqual(config.llm.models[1].api_key, "model-direct-key")
if __name__ == "__main__":
unittest.main()
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