#!/usr/bin/env python3
"""
Generated test file for Vision Agent Test
Framework: langgraph
Execution mode: async
Streaming: no"""

import os
import sentry_sdk
import asyncio

from langgraph.prebuilt import create_react_agent
from langchain_anthropic import ChatAnthropic
from langchain_core.messages import HumanMessage, SystemMessage


sentry_sdk.init(
    dsn=os.environ.get("SENTRY_DSN"),
    traces_sample_rate=1.0,
    send_default_pii=True,
    stream_gen_ai_spans=True,
)

# Initialize ChatAnthropic for LangGraph
llm = ChatAnthropic(
    model="claude-haiku-4-5",
    api_key=os.environ.get("ANTHROPIC_API_KEY"),
)

tools = []

# Create react agent
agent = create_react_agent(llm, tools=tools, name="vision_assistant")

async def main():
    # Turn 1: Run agent
    messages = [
        SystemMessage(content="You are a helpful assistant that can analyze images. Be concise."),
        HumanMessage(content=[
            {"type": "text", "text": "What color is this image? Reply with just the color name."},
            {"type": "image_url", "image_url": {"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAoAAAAKCAYAAACNMs+9AAAAFUlEQVR42mP8z8BQz0AEYBxVSF+FABJADveWkH6oAAAAAElFTkSuQmCC"}},
        ]),
    ]

    result = await agent.ainvoke({"messages": messages})

    # Extract the AI's response from the result
    response_text = result["messages"][-1].content

    # Print response
    print(f"Turn 1 Response: {response_text}")

if __name__ == "__main__":
    with sentry_sdk.start_transaction(op="test", name="Vision Agent Test"):
        asyncio.run(main())
    sentry_sdk.flush(timeout=5)