luzia/luzia_research_agent.py

#!/usr/bin/env python3
"""
Luzia Research Agent Loop - Interactive Research Task Processing

Continuously monitors incoming research tasks and routes them intelligently
based on security, speed, and complexity filters.

Can run in:
- Interactive mode: Process individual tasks
- Loop mode: Monitor queue continuously (default)
"""

import sys
import json
import time
from pathlib import Path
from datetime import datetime

sys.path.insert(0, '/opt/server-agents/orchestrator/lib')

from research_agent import LuziaResearchAgent, TaskFilter, ToolRouter


def run_interactive():
    """Interactive mode: process user input"""
    agent = LuziaResearchAgent()

    print("\n" + "=" * 70)
    print("🔬 LUZIA RESEARCH AGENT - INTERACTIVE MODE")
    print("=" * 70)
    print("\nEnter research tasks to analyze. Type 'exit' to quit.\n")

    while True:
        try:
            task = input("📋 Research task: ").strip()

            if task.lower() in ['exit', 'quit', 'q']:
                print("✅ Exiting research agent")
                break

            if not task:
                print("⚠️  Empty task, try again\n")
                continue

            # Process the task
            result = agent.process_research_task(task)

            print(f"\n{result['analysis']['routing_summary']}")

            if result['clarification']:
                print("❓ Clarification Questions:")
                for q in result['clarification']['questions']:
                    print(f"  {q}")

            print()

        except KeyboardInterrupt:
            print("\n✅ Exiting research agent")
            break
        except Exception as e:
            print(f"❌ Error: {e}\n")


def run_continuous():
    """Continuous loop mode: monitor and process tasks"""
    agent = LuziaResearchAgent()
    queue_file = Path("/opt/server-agents/state/research-queue.json")

    agent.log("🔬 Luzia Research Agent started (continuous mode)")

    while True:
        try:
            # Check if queue file exists
            if not queue_file.exists():
                time.sleep(10)
                continue

            # Read queue
            with open(queue_file) as f:
                queue_data = json.load(f)

            pending = queue_data.get('pending', [])
            if not pending:
                time.sleep(10)
                continue

            # Process first pending task
            task_entry = pending[0]
            task_id = task_entry.get('id', str(uuid.uuid4()))
            task = task_entry.get('task', '')

            agent.log(f"📥 Processing task {task_id}: {task[:50]}...")

            # Analyze and route
            result = agent.process_research_task(task)

            # Move to processed
            queue_data['pending'].pop(0)
            queue_data['processed'] = queue_data.get('processed', [])
            queue_data['processed'].append({
                'id': task_id,
                'task': task,
                'timestamp': datetime.now().isoformat(),
                'analysis': result['analysis'],
                'status': result['status'],
            })

            # Write back
            with open(queue_file, 'w') as f:
                json.dump(queue_data, f, indent=2)

            agent.log(f"✅ Processed: {task[:50]}... → {result['analysis']['recommended_tool']}")

            # Brief sleep between tasks
            time.sleep(2)

        except KeyboardInterrupt:
            agent.log("🛑 Research agent stopped by user")
            break
        except Exception as e:
            agent.log(f"❌ Error in loop: {e}")
            time.sleep(5)


def show_demo():
    """Show demonstration of smart filtering"""
    agent = LuziaResearchAgent()

    demo_tasks = [
        ("quick answer: what is REST?", "Simple question, no urgency"),
        ("urgent critical vulnerability in auth system", "Critical security, needs immediate review"),
        ("research distributed caching approaches and tradeoffs", "Complex decision, needs exploration"),
        ("debug: zen-proxy max_tokens not working", "Error diagnosis, straightforward"),
        ("design: REST vs GraphQL for new API", "Architecture decision, multiple perspectives"),
    ]

    print("\n" + "=" * 80)
    print("🔬 LUZIA RESEARCH AGENT - SMART FILTER DEMONSTRATION")
    print("=" * 80)

    for task, context in demo_tasks:
        print(f"\n📋 Task: {task}")
        print(f"   Context: {context}")
        print("   " + "-" * 70)

        analysis = agent.analyze_task(task)
        print(f"   Security:   {analysis['security']}")
        print(f"   Speed:      {analysis['speed']}")
        print(f"   Complexity: {analysis['complexity']}")
        print(f"   → Tool:     {analysis['recommended_tool']}")
        print(f"   Reason:     {analysis['reasoning']}")


if __name__ == "__main__":
    if len(sys.argv) > 1:
        if sys.argv[1] == "--demo":
            show_demo()
        elif sys.argv[1] == "--interactive":
            run_interactive()
        elif sys.argv[1] == "--continuous":
            run_continuous()
        else:
            print("Usage:")
            print("  luzia_research_agent.py --demo         Show demonstration")
            print("  luzia_research_agent.py --interactive  Interactive mode")
            print("  luzia_research_agent.py --continuous   Continuous queue monitoring")
    else:
        # Default: interactive mode
        run_interactive()