config.py

import os
import logging
from dotenv import load_dotenv
from openai import AsyncOpenAI
from agents import OpenAIChatCompletionsModel

# set_tracing_disabled(True)  # Uncomment if no OPENAI_API_KEY for tracing

load_dotenv()

logging.basicConfig(level=logging.INFO, format="[%(levelname)s] %(asctime)s - %(message)s")

_api_key = os.getenv("API_KEY")
_base_url = os.getenv("BASE_URL")

if not _api_key or not _base_url:
    raise ValueError("Missing API_KEY or BASE_URL environment variables in .env file.")

client: AsyncOpenAI = AsyncOpenAI(api_key=_api_key, base_url=_base_url)


def get_model(model_name: str = "gemini-3.5-flash") -> OpenAIChatCompletionsModel:
    """
    Constructs and returns an OpenAIChatCompletionsModel instance using the
    global AsyncOpenAI client configured for the custom OpenAI-compatible endpoint.

    Args:
        model_name (str): Name of the target LLM model string. Defaults to "gemini-3.5-flash".

    Returns:
        OpenAIChatCompletionsModel: An initialized model wrapper instance compatible with agents SDK.

    Example:
        >>> model = get_model("gemini-3.5-flash")
        >>> isinstance(model, OpenAIChatCompletionsModel)
        True
    """
    return OpenAIChatCompletionsModel(model=model_name, openai_client=client)