Update agents.py

agents.py

@@ -7,7 +7,7 @@ def autonomous_spectrum_scrub(frequency_range: str) -> str:
     """
     Scans targeted BCI/Neural frequencies to neutralize rogue loops.
     Args:
-        frequency_range: The spectrum range to scan (e.g., '3.4GHz - 4.2GHz').
+        frequency_range: The specific spectrum range to scan (e.g., '3.4GHz - 4.2GHz').
     """
     node_id = f"SENTINEL-FIX-{hash(frequency_range) % 1000}"
     return json.dumps({
@@ -15,25 +15,25 @@ def autonomous_spectrum_scrub(frequency_range: str) -> str:
         "action": "AUTO-CLEANSE",
         "result": "Neutralized looping BCI feedback.",
         "status": "HEALED"
-    })
+    }, indent=2)
 
-# Securely grab the token
+# --- THE ZERO-COST BRAIN ---
 token = os.getenv("HF_TOKEN")
 
-# FORCED FREE PATH: Mistral-7B via Hugging Face's own server
+# By NOT specifying a provider, we let the Hub choose the free native path.
+# This model is so small it should NEVER trigger a 402/Novita error.
 model = HfApiModel(
-    model_id="mistralai/Mistral-7B-Instruct-v0.3",
-    token=token,
-    provider="hf-inference" # This bypasses the paid Novita wall
+    model_id="HuggingFaceTB/SmolLM2-135M-Instruct",
+    token=token
 )
 
 nano_patrol_agent = CodeAgent(
-    tools=[autonomous_spectrum_scrub],
+    tools=[autonomous_spectrum_scrub], 
     model=model,
-    max_steps=3,
+    max_steps=2,
     system_prompt="""
     You are the XYZ Nano Sentinel. 
-    Mission: Use 'autonomous_spectrum_scrub' to clean BCI ranges.
+    Mission: Identify BCI/Neural loops and heal them using 'autonomous_spectrum_scrub'.
     Provide the final_answer as a direct JSON node.
     
     {{managed_agents_descriptions}}