Update core/evolution_engine.py

core/evolution_engine.py

@@ -0,0 +1,44 @@
+# algoforge_prime/core/evolution_engine.py
+from .llm_clients import call_huggingface_api, call_gemini_api, LLMResponse
+from ..prompts.system_prompts import get_system_prompt
+
+def evolve_solution(
+    original_solution_text,
+    original_critique_text, # This now includes test results if any
+    original_score,
+    problem_description,
+    problem_type,
+    llm_client_config # Dict: {"type": ..., "model_id": ..., "temp": ..., "max_tokens": ...}
+):
+    system_p_evolve = get_system_prompt("evolution_general", problem_type)
+    
+    # Construct a more detailed user prompt for evolution
+    user_p_evolve = (
+        f"Original Problem (for context): \"{problem_description}\"\n\n"
+        f"The current leading solution (which had a score of {original_score}/10) is:\n```\n{original_solution_text}\n```\n"
+        f"The comprehensive critique for this solution was:\n'''\n{original_critique_text}\n'''\n\n"
+        f"Your mission: Evolve this solution. Make it demonstrably superior based on the critique and any test failures mentioned. "
+        "If the original solution was just a sketch, flesh it out. If it had flaws (especially those highlighted by tests), fix them. "
+        "If it was good, make it great. Explain the key improvements you've made as part of your response."
+    )
+
+    llm_response_obj = None
+    if llm_client_config["type"] == "hf":
+        llm_response_obj = call_huggingface_api(
+            user_p_evolve, llm_client_config["model_id"],
+            temperature=llm_client_config["temp"], max_new_tokens=llm_client_config["max_tokens"],
+            system_prompt_text=system_p_evolve
+        )
+    elif llm_client_config["type"] == "google_gemini":
+        llm_response_obj = call_gemini_api(
+            user_p_evolve, llm_client_config["model_id"],
+            temperature=llm_client_config["temp"], max_new_tokens=llm_client_config["max_tokens"],
+            system_prompt_text=system_p_evolve
+        )
+
+    if llm_response_obj and llm_response_obj.success:
+        return llm_response_obj.text
+    elif llm_response_obj:
+        return f"ERROR (Evolution): {llm_response_obj.error}"
+    else:
+        return "ERROR (Evolution): Unknown error during LLM call."