import os
from openai import OpenAI
from openai import RateLimitError
import time


base_url = os.environ.get('LLM_API_BASE', "")
token = os.environ.get('LLM_API_KEY', "")

if not base_url and not token:
    raise ValueError("LLM_API_BASE or LLM_API_KEY must be set")
elif base_url and not token:
    client = OpenAI(base_url=base_url)
elif not base_url and token:
    client = OpenAI(api_key=token)
else:
    client = OpenAI(api_key=token, base_url=base_url)


def openai_llm(messages: list, model: str, logger=None, **kwargs) -> str:
    if logger:
        logger.debug(f'messages:\n {messages}')
        logger.debug(f'model: {model}')
        logger.debug(f'kwargs:\n {kwargs}')

    try:
        response = client.chat.completions.create(messages=messages, model=model, **kwargs)
    except RateLimitError as e:
        logger.warning(f'{e}\nRetrying in 60 second...')
        time.sleep(60)
        response = client.chat.completions.create(messages=messages, model=model, **kwargs)
        if response and response.choices:
            return response.choices[0].message.content
        else:
            logger.error(f'after many try, llm error: {response}')
            return ""
    except Exception as e:
        if logger:
            logger.error(f'openai_llm error: {e}')
        return ''

    if logger:
        logger.debug(f'result:\n {response.choices[0]}')
        logger.debug(f'usage:\n {response.usage}')

    return response.choices[0].message.content