from orxhestra import LlmAgent
from langchain_core.tools import tool
from langchain_openai import ChatOpenAI

@tool
async def search(query: str) -> str:
    """Search the web."""
    return f"Results for: {query}"

agent = LlmAgent(
    name="assistant",
    model=ChatOpenAI(model="gpt-5.4"),
    tools=[search],
    instructions="You are a helpful assistant.",
    max_iterations=10,
)

# Async streaming
async for event in agent.astream("Hello"):
    if event.is_final_response():
        print(event.text)

# Sync convenience
result = agent.invoke("Hello")
print(result.text)

async def dynamic_instructions(ctx):
    return f"You are helping user in session {ctx.session_id}."

agent = LlmAgent(
    name="dynamic",
    model=model,
    instructions=dynamic_instructions,
)

from orxhestra import ReActAgent

agent = ReActAgent(
    name="reasoner",
    model=ChatOpenAI(model="gpt-5.4"),
    tools=[search],
    instructions="Think step by step.",  # appended to ReAct prompt
    max_iterations=10,
)

from orxhestra import Runner, InMemorySessionService

runner = Runner(
    agent=agent,
    app_name="my-app",
    session_service=InMemorySessionService(),
)

session = await runner.session_service.create_session(app_name="my-app")

async for event in runner.run(
    user_message="Hello!",
    session_id=session.id,
):
    if event.is_final_response():
        print(event.text)