ai_assistant_agent.py•4.49 kB
#!/usr/bin/env python3
"""
AI Assistant Agent - Future
Advanced AI assistant agent prepared for future activation
"""
# import asyncio
from datetime import datetime
from typing import Dict,Any
# import logging
# Add project root to path
import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).parent.parent.parent))
from agents.base_agent import BaseMCPAgent, AgentCapability, MCPMessage
# Agent metadata for auto-discovery
AGENT_METADATA = {
"id": "ai_assistant_agent",
"name": "AI Assistant Agent",
"version": "1.0.0",
"author": "MCP System",
"description": "Advanced AI assistant with natural language processing and reasoning capabilities",
"category": "ai",
"status": "future",
"dependencies": ["openai", "anthropic", "transformers"],
"auto_load": False,
"priority": 1,
"health_check_interval": 60,
"max_failures": 3,
"recovery_timeout": 120,
"future_requirements": [
"AI API credentials (OpenAI, Anthropic, etc.)",
"Natural language processing models",
"Reasoning and conversation capabilities",
"Integration with external AI services"
]
}
class AIAssistantAgent(BaseMCPAgent):
"""AI Assistant Agent for advanced natural language processing - future implementation."""
def __init__(self):
capabilities = [
AgentCapability(
name="natural_language_processing",
description="Advanced natural language understanding and generation",
input_types=["text", "dict"],
output_types=["dict", "text"],
methods=["process", "chat", "reason", "analyze", "info"],
version="1.0.0"
)
]
super().__init__("ai_assistant_agent", "AI Assistant Agent", capabilities)
self.failure_count = 0
self.last_health_check = datetime.now()
self.is_future = True # Marked as future
self.logger.info("AI Assistant Agent initialized (FUTURE)")
async def health_check(self) -> Dict[str, Any]:
"""Health check for future agent."""
return {
"agent_id": self.agent_id,
"status": "future",
"reason": "Agent prepared for future activation",
"last_check": datetime.now().isoformat(),
"failure_count": self.failure_count,
"version": AGENT_METADATA["version"],
"can_activate": False,
"future_requirements": AGENT_METADATA["future_requirements"]
}
async def handle_process(self, message: MCPMessage) -> Dict[str, Any]:
"""Handle process requests for future agent."""
return {
"status": "future",
"message": "AI Assistant Agent is prepared for future activation. Advanced AI capabilities not yet available.",
"agent": self.agent_id,
"version": AGENT_METADATA["version"],
"future_capabilities": [
"Natural language understanding",
"Conversational AI",
"Reasoning and analysis",
"Multi-modal processing"
]
}
async def handle_info(self, message: MCPMessage) -> Dict[str, Any]:
"""Handle info request for future agent."""
return {
"status": "future",
"info": self.get_info(),
"metadata": AGENT_METADATA,
"health": await self.health_check(),
"planned_features": [
"Integration with OpenAI GPT models",
"Anthropic Claude integration",
"Local transformer models",
"Advanced reasoning capabilities",
"Multi-turn conversations",
"Context-aware responses"
],
"agent": self.agent_id
}
# Agent registration functions
def get_agent_metadata():
"""Get agent metadata for auto-discovery."""
return AGENT_METADATA
def create_agent():
"""Create and return the agent instance."""
return AIAssistantAgent()
def get_agent_info():
"""Get agent information for compatibility."""
return {
"name": "AI Assistant Agent",
"description": "Advanced AI assistant (future implementation)",
"version": "1.0.0",
"author": "MCP System",
"capabilities": ["natural_language_processing", "conversational_ai", "reasoning"],
"category": "ai",
"status": "future"
}