| import os | |
| import sys | |
| # Append parent directory to path to allow importing from the baseline core | |
| sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '../../'))) | |
| try: | |
| # Importing the foundation architecture you built previously | |
| from src.model import TriHeadAttention, FluidicMemoryManifold | |
| except ImportError: | |
| print("[-] Warning: Baseline Vitalis Core modules not found in path.") | |
| print("[-] Ensure DevCore is correctly positioned relative to the core architecture.") | |
| class CoreBridge: | |
| def __init__(self, mode="inference"): | |
| self.mode = mode | |
| print("[+] CoreBridge Initialized: Preparing Tri-Head synchronization.") | |
| # In a full deployment, this is where we load the hardened W_core weights | |
| self.manifold_active = True | |
| def analyze_and_correct(self, flawed_code, traceback_error): | |
| """ | |
| Passes the failed code and terminal traceback through the Sensu/Ratio/Cor heads. | |
| """ | |
| if not self.manifold_active: | |
| return flawed_code | |
| print(f"[*] Sensu Head: Ingesting traceback sequence...") | |
| print(f"[*] Ratio Head: Aligning semantic logic trees...") | |
| print(f"[*] Cor Head: Stabilizing fluidic weights for output generation...") | |
| # Here we will eventually format the prompt for the actual model. | |
| # Format: <CODE>{flawed_code}</CODE> <ERROR>{traceback_error}</ERROR> <TASK>Fix</TASK> | |
| # For our immediate architectural test of the bridge, we define the dynamic prompt structure: | |
| dynamic_prompt = f"Analyze structural failure:\n{traceback_error}\nCorrect the following logic:\n{flawed_code}" | |
| # We will connect the actual torch inference loop in the next iteration. | |
| return dynamic_prompt | |
| if __name__ == "__main__": | |
| bridge = CoreBridge() | |
| test_analysis = bridge.analyze_and_correct("print(10/0)", "ZeroDivisionError") | |
| print("\n[+] Dynamic Prompt Ready for Engine Execution:") | |
| print(test_analysis) | |