Reject the invalid 'llm.model' config key with an actionable error

README.md

@@ -356,7 +356,7 @@ export OPENAI_API_KEY="sk-..."
 # config.yaml
 llm:
   api_base: "https://generativelanguage.googleapis.com/v1beta/openai/"
-  model: "gemini-2.5-pro"
+  primary_model: "gemini-2.5-pro"
 ```
 
 ```bash
@@ -372,7 +372,7 @@ export OPENAI_API_KEY="your-gemini-api-key"
 # config.yaml
 llm:
   api_base: "http://localhost:11434/v1"  # Ollama
-  model: "codellama:7b"
+  primary_model: "codellama:7b"
 ```
 
 </details>
@@ -396,7 +396,7 @@ export OPENAI_API_KEY="your-actual-key"
 ```yaml
 llm:
   api_base: "http://localhost:8000/v1"
-  model: "moa&readurls-o3"  # Test-time compute + web access
+  primary_model: "moa&readurls-o3"  # Test-time compute + web access
 ```
 
 </details>

openevolve/config.py

@@ -489,6 +489,16 @@ def from_dict(cls, config_dict: Dict[str, Any]) -> "Config":
                 del config_dict["llm"]["temperature"]
             if "top_p" in config_dict["llm"] and config_dict["llm"]["top_p"] is None:
                 del config_dict["llm"]["top_p"]
+            # 'model' is not a config field (models are 'llm.models' or
+            # 'llm.primary_model'), and dacite silently drops unknown keys. Left
+            # unchecked, such configs pass validation with an empty model ensemble
+            # and every LLM call later fails with "IndexError: list index out of
+            # range" (issue #427). Fail here with the correct spelling instead.
+            if isinstance(config_dict["llm"], dict) and "model" in config_dict["llm"]:
+                raise ValueError(
+                    "Invalid config key 'llm.model'. Use 'llm.primary_model' or the "
+                    "'llm.models' array instead (see README configuration section)."
+                )
 
         config: Config = dacite.from_dict(
             data_class=cls,

tests/test_llm_model_key_rejected.py

@@ -0,0 +1,63 @@
+"""
+Tests for rejection of the legacy/mistaken 'llm.model' config key (issue #427).
+
+The LLM config has no 'model' field - models are configured via 'llm.models'
+or 'llm.primary_model'. dacite silently drops unknown keys, so a config using
+'model:' (as several README provider examples taught) produced an empty model
+ensemble that later crashed every LLM call with "IndexError: list index out
+of range". Config.from_dict must reject the key with an actionable error.
+"""
+
+import unittest
+
+from openevolve.config import Config
+
+
+class TestLLMModelKeyRejected(unittest.TestCase):
+    """The 'llm.model' key must fail loudly instead of building an empty ensemble"""
+
+    def test_model_key_raises_helpful_error(self):
+        """A bare llm.model key raises ValueError pointing at the right keys"""
+        with self.assertRaises(ValueError) as ctx:
+            Config.from_dict({"llm": {"model": "glm-ocr"}})
+        self.assertIn("primary_model", str(ctx.exception))
+        self.assertIn("llm.models", str(ctx.exception))
+
+    def test_model_key_with_other_keys_still_raises(self):
+        """llm.model raises even when mixed into an otherwise valid config"""
+        config_dict = {
+            "max_iterations": 100,
+            "llm": {
+                "api_base": "http://localhost:3000/api/",
+                "api_key": "test",
+                "model": "glm-ocr",
+                "temperature": 0.7,
+            },
+        }
+        with self.assertRaises(ValueError) as ctx:
+            Config.from_dict(config_dict)
+        self.assertIn("llm.model", str(ctx.exception))
+
+    def test_primary_model_config_still_valid(self):
+        """The documented primary_model spelling keeps working"""
+        config = Config.from_dict(
+            {"llm": {"primary_model": "glm-ocr", "api_base": "http://localhost:3000/api/"}}
+        )
+        self.assertEqual(len(config.llm.models), 1)
+        self.assertEqual(config.llm.models[0].name, "glm-ocr")
+
+    def test_models_array_config_still_valid(self):
+        """The models array spelling keeps working"""
+        config = Config.from_dict({"llm": {"models": [{"name": "gpt-4o-mini", "weight": 1.0}]}})
+        self.assertEqual(len(config.llm.models), 1)
+        self.assertEqual(config.llm.models[0].name, "gpt-4o-mini")
+
+    def test_code_constructed_config_unaffected(self):
+        """Internally constructed Config() (which never goes through from_dict)
+        keeps its empty default ensemble - that path is not a user error"""
+        config = Config()
+        self.assertEqual(config.llm.models, [])
+
+
+if __name__ == "__main__":
+    unittest.main()