Agent Spec Tracing

pip install openinference-instrumentation-agentspec pyagentspec[langgraph]

from phoenix.otel import register

# configure the Phoenix tracer
tracer_provider = register(
  project_name="my-llm-app", # Default is 'default'
  auto_instrument=True # Auto-instrument your app based on installed OI dependencies
)

from pyagentspec.agent import Agent
from pyagentspec.llms import OpenAiConfig

agent = Agent(
    name="assistant",
    description="A general purpose agent without tools",
    llm_config=OpenAiConfig(name="openai-gpt-5-mini", model_id="gpt-5-mini"),
    system_prompt="You are a helpful assistant. Help the user answering politely.",
)

# Transform the Agent Spec agent into a LangGraph's executable component
from pyagentspec.adapters.langgraph import AgentSpecLoader

langgraph_agent = AgentSpecLoader().load_component(agent)

# Instrument the agent's execution
from openinference.instrumentation.agentspec import AgentSpecInstrumentor
from phoenix.otel import register

tracer_provider = register(batch=True, project_name="hello-world-app")
AgentSpecInstrumentor().instrument(tracer_provider=tracer_provider)

# Run the agent's execution loop
while True:
    user_input = input("USER  >>> ")
    if user_input.lower() in ["exit", "quit"]:
        break
    response = langgraph_agent.invoke(
        input={"messages": [{"role": "user", "content": user_input}]},
        config={"configurable": {"thread_id": "1"}},
    )
    print("AGENT >>>", response['messages'][-1].content.strip())