Adds Gemini-powered agent classification system that analyzes agent instructions to determine category, risk level, discipline, and client detection. Includes admin Prompt Audit tab, audit review workflow, and auto-classification on sync. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
40 lines
1.5 KiB
Python
40 lines
1.5 KiB
Python
from motor.motor_asyncio import AsyncIOMotorClient
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from dotenv import load_dotenv
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import os
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load_dotenv()
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MONGODB_URI = os.getenv("MONGODB_URI", "mongodb://localhost:27017")
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MONGODB_DBNAME = os.getenv("MONGODB_DBNAME", "agenthub_db")
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client = AsyncIOMotorClient(MONGODB_URI)
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db = client[MONGODB_DBNAME]
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users_collection = db.get_collection("users")
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agents_collection = db.get_collection("agents")
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agent_usage_collection = db.get_collection("agent_usage")
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notifications_collection = db.get_collection("token_notifications")
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agent_ratings_collection = db.get_collection("agent_ratings")
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audit_history_collection = db.get_collection("audit_history")
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async def ensure_indexes():
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"""Create database indexes for performance"""
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try:
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await agent_ratings_collection.create_index(
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[("agent_id", 1), ("user_id", 1)],
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unique=True
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)
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await agents_collection.create_index([("verification_status", 1)])
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await agents_collection.create_index([("audit_status", 1)])
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await audit_history_collection.create_index([("agent_id", 1), ("audit_date", -1)])
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print("Database indexes ensured successfully")
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except Exception as e:
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print(f"Warning: Failed to create indexes: {e}")
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async def check_database_health():
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"""Check MongoDB connection health"""
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try:
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# Attempt to ping the database
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await client.admin.command('ping')
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return {"status": "connected", "healthy": True}
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except Exception as e:
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return {"status": "disconnected", "healthy": False, "error": str(e)}
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