# https://huggingface.co/docs/smolagents/tutorials/inspect_runs

import os
from langfuse import Langfuse

import smolagents.local_python_executor as lpe
from concurrent.futures import ThreadPoolExecutor

# Fix for compatibility with smolagents >= 1.22.0 and openinference-instrumentation-smolagents
if not hasattr(lpe, "ThreadPoolExecutor"):
    lpe.ThreadPoolExecutor = ThreadPoolExecutor

from smolagents import (
    CodeAgent,
    ToolCallingAgent,
    WebSearchTool,
    VisitWebpageTool,
    InferenceClientModel,
)

# Initialize Langfuse
langfuse = Langfuse()

# Verify connection
if langfuse.auth_check():
    print("✓ Langfuse connection successful!")
else:
    print("✗ Langfuse connection failed. Check your API key and host.")

model = InferenceClientModel("deepseek-ai/DeepSeek-V4-Flash")

search_agent = CodeAgent(
    tools=[WebSearchTool(), VisitWebpageTool()],
    model=model,
    name="search_agent",
    description="This is an agent that can do web search.",
)

manager_agent = CodeAgent(
    tools=[],
    model=model,
    managed_agents=[search_agent],
)

if __name__ == "__main__":
    result = manager_agent.run(
        "How can Langfuse be used to monitor and improve the reasoning and decision-making of smolagents when they execute multi-step tasks, like dynamically adjusting a recipe based on user feedback or available ingredients?"
    )
    
    print("\nAgent Result:")
    print(result)
    print("\n✓ Done!")