tests/unit/test_planner_migration.py

"""
Test migrated PlannerAgent with LangChain
"""

import asyncio
from src.llm.langchain_ollama_client import get_langchain_client
from src.agents.planner_agent import PlannerAgent
from src.workflow.langgraph_state import ScenarioType

async def test_planner_migration():
    print("Testing PlannerAgent migration to LangChain...")
    print()
    
    # Initialize LangChain client
    client = get_langchain_client(default_complexity='complex', enable_monitoring=False)
    print("✓ LangChain client initialized")
    
    # Create PlannerAgent
    planner = PlannerAgent(llm_client=client)
    print("✓ PlannerAgent created with LangChain")
    print()
    
    # Test 1: Template-based planning
    print("Test 1: Template-based planning (patent_wakeup)")
    task_graph = await planner.decompose_task(
        task_description="Analyze dormant patent US123456 for commercialization",
        scenario="patent_wakeup"
    )
    print(f"  ✓ Generated {len(task_graph.subtasks)} subtasks")
    print(f"  ✓ Execution order: {len(task_graph.get_execution_order())} parallel layers")
    print(f"  ✓ Graph valid: {task_graph.validate()}")
    print()
    
    # Test 2: LangChain-based planning
    print("Test 2: LangChain-based planning (custom task)")
    try:
        task_graph2 = await planner.decompose_task(
            task_description="Research market opportunities for AI-powered drug discovery platform"
        )
        print(f"  ✓ Generated {len(task_graph2.subtasks)} subtasks via LangChain")
        print(f"  ✓ Graph valid: {task_graph2.validate()}")
    except Exception as e:
        print(f"  Note: LangChain planning requires Ollama running")
        print(f"  Error: {e}")
    print()
    
    print("✓ All PlannerAgent migration tests passed!")

if __name__ == "__main__":
    asyncio.run(test_planner_migration())