import os
from pathlib import Path
from models.generator import Generator
from models.emoji_db import check_emoji, update_description
from controllers.localfile_handles import get_emoji_count, yield_emoji_path
from controllers.compress_image import compress_image
from models.logger import setup_logger

logger = setup_logger()

root_folder = "D:\\Python\\mcunc\\EmojiTextGenerator\\"
emoji_folder = "D:\\Python\\mcunc\\EmojiTextGenerator\\emojis\\"
emoji = yield_emoji_path(emoji_folder)

api_key = "sk-213f83213fce4e2ba41b8e67721f19cb"
gen = Generator(api_key)

emoji_file = next(emoji)
emoji_uuid = ''
p = Path(emoji_file)
if p.suffix == ".jpg" or p.suffix == ".jpeg":
    emoji_uuid = p.stem
# print(emoji_uuid)
image = compress_image(emoji_file)
image_path = Path(root_folder) / image
print(image_path)

if check_emoji(emoji_uuid):
    description = gen.process_single_image(str(image_path))
    update_description(emoji_uuid, description)
    logger.info(f"图片 {emoji_file} 的描述词生成完毕， 其 description 为: {description}")
else:
    logger.error(f"图片 {emoji_uuid} 不在数据库中！")

# # 本地图像的绝对路径
# local_path = r"D:\Python\mcunc\EmojiTextGenerator\emojis\00e4f193-74af-40f7-8722-59d5a5931f92.jpg"
# image_path = f"file://{local_path}"
# messages = [
#                 {'role':'user',
#                 'content': [{'image': image_path},
#                             {'text': '使用简洁语言描述该表情包 ，例如 在吗 ，生气，？'}]}]
# response = MultiModalConversation.call(
#     api_key="sk-213f83213fce4e2ba41b8e67721f19cb",
#     model='qwen3-vl-plus',
#     messages=messages)
#
# print(response.output.choices[0].message.content[0]["text"])