LangChain

from dotenv import load_dotenv
from langchain.agents import create_agent
from langgraph.checkpoint.memory import InMemorySaver


load_dotenv()


def add(a: float, b: float) -> float:
    """Add two numbers."""
    return a + b


def subtract(a: float, b: float) -> float:
    """Subtract two numbers."""
    return a - b


def multiply(a: float, b: float) -> float:
    """Multiply two numbers."""
    return a * b


def divide(a: float, b: float) -> float:
    """Divide two numbers."""
    return a / b


tools = [add, subtract, multiply, divide]


agent = create_agent(
    model="google_genai:gemini-2.5-flash",
    tools=tools,
    system_prompt=(
        "You are a helpful calculator assistant. You must use the tools "
        "according to the BODMAS rule."
    ),
    checkpointer=InMemorySaver(),
)

from quraite.constants.framework import Framework
from quraite.tracing import setup_tracing


tracer_provider = setup_tracing([Framework.LANGCHAIN])

from quraite.adapters import LangchainAdapter


adapter = LangchainAdapter(
    agent_graph=agent,
    tracer_provider=tracer_provider,
)

if __name__ == "__main__":
    from quraite import run_agent

    run_agent(
        adapter,
        port=8080,
        host="0.0.0.0",
        tunnel="cloudflare",
    )