Update app.py

app.py

@@ -22,7 +22,7 @@ from langchain_core.utils.utils import secret_from_env
 from io import BytesIO
 from pathlib import Path
 import os
-from utils.block_relation_builder import block_builder, separate_scripts, transform_logic_to_action_flow#, variable_adder_main
+from utils.block_relation_builder import block_builder, separate_scripts, transform_logic_to_action_flow, analyze_opcode_counts#, variable_adder_main
 from langchain.chat_models import ChatOpenAI
 from langchain_openai import ChatOpenAI
 from pydantic import Field, SecretStr
@@ -1017,6 +1017,12 @@ def node_optimizer(state: GameState):
     refined_logic_data = raw.get("refined_logic", {})
     sprite_name = refined_logic_data.get("name_variable", "<unknown>")
     pseudo      = refined_logic_data.get("pseudocode", "")
+    sprite_name = {}
+    project_json_targets = state.get("project_json", {}).get("targets", [])
+    for target in project_json_targets:
+        sprite_name[target["name"]] = target["name"]
+    action_flow = state.get("action_plan", {}) 
+    
     try:
         refined_logic_data["pseudocode"] = separate_scripts(str(pseudo))
         # Step 4: If you want to update the `state` dictionary with the new refined_logic_data
@@ -1024,6 +1030,28 @@ def node_optimizer(state: GameState):
         print(f"[The pseudo_code generated here]: { state['pseudo_code']}")
         state["action_plan"] = transform_logic_to_action_flow(state["pseudo_code"])
         print(f"[The action plan generated here]: { state['action_plan']}")
+ 
+        action_flow = state.get("action_plan", {})     
+        if action_flow.get("action_overall_flow", {}) == {}:
+            plan_data = action_flow.items()
+        else:
+            plan_data = action_flow.get("action_overall_flow", {}).items()
+            
+        refined_flow: Dict[str, Any] = {}
+        for sprite, sprite_data in plan_data:
+            refined_plans = []
+            for plan in sprite_data.get("plans", []):
+                logic = plan.get("logic", "")
+                plan["opcode_counts"]= analyze_opcode_counts(str(logic))
+                refined_plans.append(plan)
+            refined_flow[sprite] = {
+                "description": sprite_data.get("description", ""),
+                "plans": refined_plans
+            }
+        if refined_flow:
+            state["action_plan"] = refined_flow  
+            logger.info("Node Optimization completed.")
+        
         return state
     except Exception as e:
         logger.error(f"Error in Node Optimizer Node: {e}")