Fix novelty feature bugs and update test configuration

- Fix novelty check in database.py to pass program.id instead of program object
- Fix missing self parameter in embedding.py _get_client_model method
- Fix serialization error by clearing novelty_llm before config deepcopy
- Update function_minimization config for testing with different models

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <[email protected]>

Author: bluebread

examples/function_minimization/config.yaml

@@ -1,17 +1,20 @@
 # Configuration for function minimization example
-max_iterations: 50
+max_iterations: 10
 checkpoint_interval: 5
 
 # LLM configuration
 llm:
-  primary_model: "gemini-2.5-flash-lite"
+  # primary_model: "gemini-2.5-flash-lite"
+  primary_model: "gpt-5-mini"
   # primary_model: "llama3.1-8b"
   primary_model_weight: 0.8
-  secondary_model: "gemini-2.5-flash"
+  # secondary_model: "gemini-2.5-flash"
   # secondary_model: "llama-4-scout-17b-16e-instruct"
+  secondary_model: "gpt-5-nano"
   secondary_model_weight: 0.2
-  api_base: "https://generativelanguage.googleapis.com/v1beta/openai/"
+  # api_base: "https://generativelanguage.googleapis.com/v1beta/openai/"
   # api_base: "https://api.cerebras.ai/v1"
+  api_base: "https://api.openai.com/v1"
   temperature: 0.7
   max_tokens: 16000
   timeout: 120

openevolve/database.py

@@ -251,7 +251,7 @@ def add(
         island_idx = island_idx % len(self.islands)  # Ensure valid island
 
         # Novelty check before adding
-        if not self._is_novel(program, island_idx):
+        if not self._is_novel(program.id, island_idx):
             logger.debug(f"Program {program.id} failed in novelty check and won't be added in the island {island_idx}")
             return program.id  # Do not add non-novel program
 

openevolve/embedding.py

@@ -38,7 +38,7 @@ def __init__(
         """
         self.client, self.model = self._get_client_model(model_name)
 
-    def _get_client_model(model_name: str) -> tuple[openai.OpenAI, str]:
+    def _get_client_model(self, model_name: str) -> tuple[openai.OpenAI, str]:
         if model_name in OPENAI_EMBEDDING_MODELS:
             client = openai.OpenAI()
             model_to_use = model_name

openevolve/process_parallel.py

@@ -295,6 +295,10 @@ def __init__(self, config: Config, evaluation_file: str, database: ProgramDataba
     def _serialize_config(self, config: Config) -> dict:
         """Serialize config object to a dictionary that can be pickled"""
         # Manual serialization to handle nested objects properly
+
+        # The asdict() call itself triggers the deepcopy which tries to serialize novelty_llm. Remove it first.
+        config.database.novelty_llm = None
+        
         return {
             "llm": {
                 "models": [asdict(m) for m in config.llm.models],