Observability for Agent Spec with Opik

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import os
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import getpass
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if "OPENAI_API_KEY" not in os.environ:
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    os.environ["OPENAI_API_KEY"] = getpass.getpass("Enter your OpenAI API key: ")

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import asyncio
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from pyagentspec.agent import Agent
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from pyagentspec.llms import OpenAiConfig
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from pyagentspec.property import FloatProperty
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from pyagentspec.tools import ServerTool
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def build_agentspec_agent() -> Agent:
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    tools = [
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        ServerTool(
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            name="sum",
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            description="Sum two numbers",
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            inputs=[FloatProperty(title="a"), FloatProperty(title="b")],
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            outputs=[FloatProperty(title="result")],
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        ),
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        ServerTool(
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            name="subtract",
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            description="Subtract two numbers",
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            inputs=[FloatProperty(title="a"), FloatProperty(title="b")],
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            outputs=[FloatProperty(title="result")],
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        ),
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    ]
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    return Agent(
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        name="calculator_agent",
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        description="An agent that provides assistance with tool use.",
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        llm_config=OpenAiConfig(name="openai-gpt-5-mini", model_id="gpt-5-mini"),
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        system_prompt=(
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            "You are a helpful calculator agent.\n"
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            "Your duty is to compute the result of the given operation using tools, "
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            "and to output the result.\n"
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            "It's important that you reply with the result only.\n"
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        ),
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        tools=tools,
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    )
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async def main():
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    from opik.integrations.agentspec import AgentSpecInstrumentor
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    from pyagentspec.adapters.langgraph import AgentSpecLoader
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    agent = build_agentspec_agent()
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    tool_registry = {
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        "sum": lambda a, b: a + b,
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        "subtract": lambda a, b: a - b,
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    }
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    langgraph_agent = AgentSpecLoader(tool_registry=tool_registry).load_component(agent)
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    with AgentSpecInstrumentor().instrument_context(
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        project_name="agentspec-demo",
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        mask_sensitive_information=False,
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    ):
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        messages = []
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        while True:
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            user_input = input("USER  >>> ")
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            if user_input.lower() in ["exit", "quit"]:
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                break
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            messages.append({"role": "user", "content": user_input})
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            response = langgraph_agent.invoke(
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                input={"messages": messages},
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                config={"configurable": {"thread_id": "1"}},
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            )
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            agent_answer = response["messages"][-1].content.strip()
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            print("AGENT >>>", agent_answer)
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            messages.append({"role": "assistant", "content": agent_answer})
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if __name__ == "__main__":
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    asyncio.run(main())