Add default_headers support to LLM configuration

openevolve/config.py

@@ -55,6 +55,7 @@ class LLMModelConfig:
     api_base: str = None
     api_key: Optional[str] = None
     name: str = None
+    default_headers: Optional[Dict[str, str]] = None
 
     # Custom LLM client
     init_client: Optional[Callable] = None
@@ -84,8 +85,14 @@ class LLMModelConfig:
     _manual_queue_dir: Optional[str] = None
 
     def __post_init__(self):
-        """Post-initialization to resolve ${VAR} env var references in api_key"""
+        """Post-initialization to resolve ${VAR} env var references in api_key and headers"""
         self.api_key = _resolve_env_var(self.api_key)
+        # Resolve environment variables in default_headers values
+        if self.default_headers:
+            resolved_headers = {}
+            for key, value in self.default_headers.items():
+                resolved_headers[key] = _resolve_env_var(value) if isinstance(value, str) else value
+            self.default_headers = resolved_headers
 
 
 @dataclass
@@ -170,6 +177,7 @@ def __post_init__(self):
         shared_config = {
             "api_base": self.api_base,
             "api_key": self.api_key,
+            "default_headers": self.default_headers,
             "temperature": self.temperature,
             "top_p": self.top_p,
             "max_tokens": self.max_tokens,

openevolve/llm/openai.py

@@ -61,6 +61,7 @@ def __init__(
         self.retry_delay = model_cfg.retry_delay
         self.api_base = model_cfg.api_base
         self.api_key = model_cfg.api_key
+        self.default_headers = getattr(model_cfg, "default_headers", None)
         self.random_seed = getattr(model_cfg, "random_seed", None)
         self.reasoning_effort = getattr(model_cfg, "reasoning_effort", None)
 
@@ -82,12 +83,15 @@ def __init__(
             # Set up API client (normal mode)
             # OpenAI client requires max_retries to be int, not None
             max_retries = self.retries if self.retries is not None else 0
-            self.client = openai.OpenAI(
-                api_key=self.api_key,
-                base_url=self.api_base,
-                timeout=self.timeout,
-                max_retries=max_retries,
-            )
+            client_kwargs = {
+                "api_key": self.api_key,
+                "base_url": self.api_base,
+                "timeout": self.timeout,
+                "max_retries": max_retries,
+            }
+            if self.default_headers:
+                client_kwargs["default_headers"] = self.default_headers
+            self.client = openai.OpenAI(**client_kwargs)
 
         # Only log unique models to reduce duplication
         if not hasattr(logger, "_initialized_models"):