j

Author: codelion

openevolve/api.py

@@ -11,7 +11,7 @@
 from pathlib import Path
 
 from openevolve.controller import OpenEvolve
-from openevolve.config import Config, load_config
+from openevolve.config import Config, load_config, LLMModelConfig
 from openevolve.database import Program
 
 
@@ -28,6 +28,7 @@ def __repr__(self):
         return f"EvolutionResult(best_score={self.best_score:.4f})"
 
 
+
 def run_evolution(
     initial_program: Union[str, Path, List[str]],
     evaluator: Union[str, Path, Callable],
@@ -114,6 +115,17 @@ async def _run_evolution_async(
         else:
             config_obj = load_config(str(config))
 
+        # Validate that LLM models are configured
+        if not config_obj.llm.models:
+            raise ValueError(
+                "No LLM models configured. Please provide a config with LLM models, or set up "
+                "your configuration with models. For example:\n\n"
+                "from openevolve.config import Config, LLMModelConfig\n"
+                "config = Config()\n"
+                "config.llm.models = [LLMModelConfig(name='gpt-4', api_key='your-key')]\n"
+                "result = run_evolution(program, evaluator, config=config)"
+            )
+        
         # Set up output directory
         if output_dir is None and cleanup:
             temp_dir = tempfile.mkdtemp(prefix="openevolve_")

tests/integration/test_library_api.py

@@ -9,6 +9,35 @@
 from pathlib import Path
 
 from openevolve import run_evolution, evolve_function, evolve_code, evolve_algorithm
+from openevolve.config import Config, LLMModelConfig
+
+
+def _get_library_test_config(port: int = 8000) -> Config:
+    """Get config for library API tests with optillm server"""
+    config = Config()
+    config.max_iterations = 100
+    config.checkpoint_interval = 25
+    config.database.in_memory = True
+    config.evaluator.cascade_evaluation = False
+    config.evaluator.parallel_evaluations = 1
+    config.evaluator.timeout = 60
+    
+    # Configure to use optillm server
+    base_url = f"http://localhost:{port}/v1"
+    config.llm.api_base = base_url
+    config.llm.timeout = 120
+    config.llm.retries = 0
+    config.llm.models = [
+        LLMModelConfig(
+            name="google/gemma-3-270m-it",
+            api_key="optillm",
+            api_base=base_url,
+            weight=1.0,
+            timeout=120,
+            retries=0
+        )
+    ]
+    return config
 
 
 class TestLibraryAPIIntegration:
@@ -45,7 +74,8 @@ def simple_multiply(x, y):
             test_cases,
             iterations=2,  # Very small number for CI speed
             output_dir=str(temp_workspace / "evolve_function_output"),
-            cleanup=False  # Keep files for inspection
+            cleanup=False,  # Keep files for inspection
+            config=_get_library_test_config(optillm_server['port'])
         )
 
         # Verify the result structure
@@ -136,7 +166,8 @@ def fibonacci_evaluator(program_path):
             fibonacci_evaluator,
             iterations=1,  # Minimal for CI speed
             output_dir=str(temp_workspace / "evolve_code_output"),
-            cleanup=False  # Keep output directory
+            cleanup=False,  # Keep output directory
+            config=_get_library_test_config(optillm_server['port'])
         )
 
         # Verify result structure
@@ -233,7 +264,8 @@ def evaluate(program_path):
             evaluator=str(evaluator_file),
             iterations=1,  # Minimal for CI speed
             output_dir=str(temp_workspace / "run_evolution_output"),
-            cleanup=False  # Keep output directory
+            cleanup=False,  # Keep output directory
+            config=_get_library_test_config(optillm_server['port'])
         )
 
         # Verify result
@@ -258,7 +290,9 @@ def evaluate(program_path):
             initial_program=initial_program.read_text(),
             evaluator=lambda path: {"score": 0.8, "test": "passed"},  # Simple callable evaluator
             iterations=1,
-            output_dir=str(temp_workspace / "run_evolution_string_output")
+            output_dir=str(temp_workspace / "run_evolution_string_output"),
+            cleanup=False,  # Keep output directory
+            config=_get_library_test_config(optillm_server['port'])
         )
 
         assert result2 is not None