AIXYZone / app.py
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Update app.py
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import os
import sys
import gc
import time
import psutil
import shutil
import transformers.utils
import gradio as gr
# --- 1. SOVEREIGN PURGE & MONITOR ---
def sovereign_init():
process = psutil.Process(os.getpid())
print(f"--- 🛡️ AIXYZone HARDWARE REPORT ---")
print(f"Active Process ID: {os.getpid()}")
print(f"Real Memory Usage: {process.memory_info().rss / 1024 / 1024:.2f} MB")
# Force-clear Python's cache to load your new agents.py
for module in ['agents', 'transformers', 'smolagents']:
if module in sys.modules: del sys.modules[module]
# Purge local cache to bypass stuck "Payment Required" states
cache_dir = os.path.expanduser("~/.cache/huggingface")
if os.path.exists(cache_dir): shutil.rmtree(cache_dir, ignore_errors=True)
gc.collect()
print("XYZ System: Total State Purge Complete.")
print(f"----------------------------------", flush=True)
sovereign_init()
# --- 2. ENVIRONMENT HEALERS ---
if not hasattr(transformers.utils, 'is_offline_mode'):
transformers.utils.is_offline_mode = lambda: False
# Fixes the 'is_soundfile_availble' typo in the smolagents library
if not hasattr(transformers.utils, 'is_soundfile_availble'):
transformers.utils.is_soundfile_availble = lambda: False
print("XYZ System: Library Typo Healed.")
from agents import nano_patrol_agent
# --- 3. SENTINEL LOGIC ---
def run_autonomous_scrub(iterations):
history = []
bci_range = "3.4GHz - 4.2GHz (BCI/Neural Feedback)"
for i in range(int(iterations)):
prompt = f"ACT AS BCI SENTINEL: Scan {bci_range}. Neutralize loops and generate a Healed Nano Node JSON."
try:
# The agent uses your new HF_TOKEN/HF_HUB_TOKEN automatically
result = nano_patrol_agent.run(prompt)
history.append(f"[{time.strftime('%H:%M:%S')}] 🛰️ SENTINEL ACTION: {result}")
except Exception as e:
history.append(f"LOG ERROR: {str(e)}")
yield "\n\n".join(history[::-1])
time.sleep(2)
# --- 4. UI DESIGN ---
with gr.Blocks(title="AIXYZone - BCI Nano Sentinel") as demo:
gr.Markdown("# 🛡️ AIXYZone: Autonomous BCI Sentinel")
with gr.Row():
with gr.Column():
sweep_count = gr.Slider(minimum=1, maximum=50, value=10, label="Autonomous Scrub Depth")
btn_sentinel = gr.Button("🛰️ ACTIVATE SENTINEL SCAN", variant="primary")
with gr.Column():
sentinel_log = gr.Textbox(label="Live Healing Stream", lines=25)
btn_sentinel.click(fn=run_autonomous_scrub, inputs=[sweep_count], outputs=[sentinel_log])
if __name__ == "__main__":
demo.launch()