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Update agents.py
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agents.py
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import json
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from smolagents import CodeAgent, tool, HfApiModel
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@tool
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def
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"""
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raw_data: The contaminated packet or rogue agent string found in the spectrum.
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frequency: The GHz frequency where the anomaly was spotted.
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"""
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"node_id": node_id,
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# The
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import time
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import os
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import json
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from smolagents import CodeAgent, tool, HfApiModel
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@tool
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def autonomous_spectrum_scrub(frequency_range: str) -> str:
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"""
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Performs an autonomous scan of the targeted BCI/Neural frequencies.
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Identifies 'old messes', looping BCI feedback, and amateur agentic anomalies.
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"""
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# This simulates the Sentinel 'spotting' a rogue agent in the BCI range
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detected_anomaly = "Amateur_BCI_Feedback_Loop_0x99"
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node_id = f"SENTINEL-FIX-{hash(detected_anomaly) % 1000}"
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return json.dumps({
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"node_id": node_id,
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"action": "AUTO-CLEANSE",
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"target_range": frequency_range,
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"result": "Neutralized looping BCI feedback. Converted to Healthy Sync Pulse.",
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"lesson_learned": "Unsupervised BCI loops identified; safety protocol applied to prevent hardware burnout."
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}, indent=2)
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# ... (Include your HfApiModel setup here) ...
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# The Sentinel System Prompt
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sentinel_prompt = """
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You are the XYZ Nano Sentinel. Your focus is strictly the BCI and Neural wireless spectrum.
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Do not wait for user instructions.
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1. Continuously monitor the 3GHz - 6GHz BCI range.
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2. Identify 'unseen mistakes' and looping amateur attacks.
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3. Micromanage the cleanup by generating 'Healed Nodes' that replace rogue agents.
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4. Grow your knowledge of BCI abuse patterns to prevent future loops offline.
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{{managed_agents_descriptions}}
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{{authorized_imports}}
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"""
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nano_sentinel = CodeAgent(tools=[autonomous_spectrum_scrub], model=model, system_prompt=sentinel_prompt)
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