Lab 00 · Hello, agent

langchain==1.4.2
langchain-core==1.6.4
langchain-openai==1.6.2
python-dotenv==1.2.3

# Azure OpenAI settings. Your instructor gives you these three values.
AZURE_OPENAI_ENDPOINT=https://<your-resource>.openai.azure.com/openai/v1
AZURE_OPENAI_API_KEY=<paste-your-key-here>
AZURE_OPENAI_DEPLOYMENT=<your-chat-deployment-name>

# Only used when your endpoint does NOT end in /openai/v1.
OPENAI_API_VERSION=2025-04-01-preview

"""Azure OpenAI model setup shared by every lab.

Import it in lab code as:  from model_setup import get_model, get_embeddings
"""

import asyncio
import os
import sys

from dotenv import load_dotenv
from langchain_core.embeddings import Embeddings
from langchain_core.language_models import BaseChatModel

# Read AZURE_OPENAI_* values from the .env file next to your lab code.
load_dotenv()

# Windows consoles default to cp1252 and crash on the curly quotes models love to print.
for _stream in (sys.stdout, sys.stderr):
    if hasattr(_stream, "reconfigure"):
        _stream.reconfigure(encoding="utf-8", errors="replace")

def _setting(name: str) -> str:
    """Return a required setting from .env, or stop with a readable message."""
    value = os.getenv(name, "").strip()
    if not value:
        sys.exit(f"Missing {name} in your .env file. Open .env and fill it in.")
    return value


def _uses_v1_api(endpoint: str) -> bool:
    """True for the OpenAI-compatible Azure endpoint that ends in /openai/v1."""
    return endpoint.rstrip("/").endswith("/openai/v1")

def get_model(deployment: str | None = None, **kwargs) -> BaseChatModel:
    """Return a chat model for your Azure OpenAI deployment."""
    endpoint = _setting("AZURE_OPENAI_ENDPOINT")
    api_key = _setting("AZURE_OPENAI_API_KEY")
    name = deployment or _setting("AZURE_OPENAI_DEPLOYMENT")

    if _uses_v1_api(endpoint):
        from langchain_openai import ChatOpenAI

        return ChatOpenAI(model=name, base_url=endpoint, api_key=api_key, **kwargs)

    from langchain_openai import AzureChatOpenAI

    return AzureChatOpenAI(
        azure_deployment=name,
        azure_endpoint=endpoint,
        api_key=api_key,
        api_version=os.getenv("OPENAI_API_VERSION", "2025-04-01-preview"),
        **kwargs,
    )

def get_embeddings(deployment: str | None = None) -> Embeddings:
    """Return an embeddings model for your Azure OpenAI embeddings deployment."""
    endpoint = _setting("AZURE_OPENAI_ENDPOINT")
    api_key = _setting("AZURE_OPENAI_API_KEY")
    name = deployment or _setting("AZURE_OPENAI_EMBEDDING_DEPLOYMENT")

    if _uses_v1_api(endpoint):
        from langchain_openai import OpenAIEmbeddings

        return OpenAIEmbeddings(model=name, base_url=endpoint, api_key=api_key)

    from langchain_openai import AzureOpenAIEmbeddings

    return AzureOpenAIEmbeddings(
        azure_deployment=name,
        azure_endpoint=endpoint,
        api_key=api_key,
        api_version=os.getenv("OPENAI_API_VERSION", "2025-04-01-preview"),
    )

def use_stable_event_loop() -> None:
    """On Windows, use the Selector event loop so async MCP code exits cleanly."""
    if sys.platform == "win32":
        asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy())

"""Lab 00: a Northwind support agent with two tools.

Run:  python hello_agent.py
"""

from langchain.agents import create_agent
from langchain.tools import tool

from model_setup import get_model

ORDERS = {
    "A-100": {"status": "shipped via DHL, arriving 2026-09-15", "total": 249.00},
    "A-101": {"status": "processing, expected 2026-09-18", "total": 1299.50},
}

@tool
def get_order_status(order_id: str) -> str:
    """Look up the shipping status of an order, such as A-100."""
    order = ORDERS.get(order_id.upper())
    if not order:
        return f"No order found with id {order_id}."
    return f"Order {order_id.upper()} is {order['status']}."

@tool
def get_invoice_total(order_id: str) -> str:
    """Return the amount charged for an order. Use for questions about price or total."""
    order = ORDERS.get(order_id.upper())
    if not order:
        return f"No order found with id {order_id}."
    return f"Order {order_id.upper()} total: {order['total']:.2f} USD."

SYSTEM_PROMPT = (
    "You are the Northwind support assistant. Answer briefly and only about orders. "
    "Never guess a status or an amount: always call the matching tool."
)

def build_agent(model=None):
    """Build the agent. Pass a model to override the Azure OpenAI default."""
    return create_agent(
        model=model or get_model(),
        tools=[get_order_status, get_invoice_total],
        system_prompt=SYSTEM_PROMPT,
    )

if __name__ == "__main__":
    agent = build_agent()

    questions = [
        "Where is A-100 and how much was it?",
        "What is the status of order Z-999?",
    ]
    for question in questions:
        result = agent.invoke({"messages": [{"role": "user", "content": question}]})
        tools_used = [
            call["name"] for message in result["messages"] for call in getattr(message, "tool_calls", [])
        ]
        print(f"You:   {question}")
        print(f"Tools: {', '.join(tools_used) or 'none'}")
        print(f"Agent: {result['messages'][-1].text}\n")

You:   Where is A-100 and how much was it?
Tools: get_order_status, get_invoice_total
Agent: Order A-100 is shipped via DHL and arriving 2026-09-15. Total charged: 249.00 USD.

You:   What is the status of order Z-999?
Tools: get_order_status
Agent: I couldn’t find an order with ID Z-999. Please confirm the order number and I’ll check the status.