Update core/generation_engine.py

core/generation_engine.py

@@ -1,8 +1,7 @@
 # algoforge_prime/core/generation_engine.py
-from core.llm_clients import call_huggingface_api, call_gemini_api, LLMResponse
-from prompts.system_prompts import get_system_prompt # Absolute import from project root
-from prompts.prompt_templates import format_genesis_user_prompt
-
+from core.llm_clients import call_huggingface_api, call_gemini_api, LLMResponse # Changed to absolute
+from prompts.system_prompts import get_system_prompt # Changed to absolute
+from prompts.prompt_templates import format_genesis_user_prompt # Changed to absolute
 
 def generate_initial_solutions(
     problem_description,
@@ -11,32 +10,26 @@ def generate_initial_solutions(
     num_solutions_to_generate,
     llm_client_config # Dict: {"type": ..., "model_id": ..., "temp": ..., "max_tokens": ...}
 ):
-    """
-    Generates a list of initial solution strings using the configured LLM.
-    Returns a list of strings, where each string is either a solution or an error message.
-    """
     solutions_or_errors = []
-    # Select system prompt based on problem type, more specific for Python
     system_p_key = "genesis_general"
     if "python" in problem_type.lower():
         system_p_key = "genesis_python"
-    system_p_genesis = get_system_prompt(system_p_key)
-
+    system_p_genesis = get_system_prompt(system_p_key) # Uses the imported function
 
     for i in range(num_solutions_to_generate):
-        user_p_genesis = format_genesis_user_prompt(
+        user_p_genesis = format_genesis_user_prompt( # Uses the imported function
             problem_description, initial_hints, i + 1, num_solutions_to_generate
         )
         
         llm_response_obj = None # type: LLMResponse
         if llm_client_config["type"] == "hf":
-            llm_response_obj = call_huggingface_api(
+            llm_response_obj = call_huggingface_api( # Uses the imported function
                 user_p_genesis, llm_client_config["model_id"],
                 temperature=llm_client_config["temp"], max_new_tokens=llm_client_config["max_tokens"],
                 system_prompt_text=system_p_genesis
             )
         elif llm_client_config["type"] == "google_gemini":
-            llm_response_obj = call_gemini_api(
+            llm_response_obj = call_gemini_api( # Uses the imported function
                 user_p_genesis, llm_client_config["model_id"],
                 temperature=llm_client_config["temp"], max_new_tokens=llm_client_config["max_tokens"],
                 system_prompt_text=system_p_genesis