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