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https://github.com/RockChinQ/QChatGPT.git
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97 lines
2.9 KiB
Python
97 lines
2.9 KiB
Python
# 长消息处理相关
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import os
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import time
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import base64
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import config
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from mirai.models.message import MessageComponent, MessageChain, Image
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from mirai.models.message import ForwardMessageNode
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from mirai.models.base import MiraiBaseModel
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from typing import List
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import pkg.utils.context as context
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import pkg.utils.text2img as text2img
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class ForwardMessageDiaplay(MiraiBaseModel):
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title: str = "群聊的聊天记录"
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brief: str = "[聊天记录]"
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source: str = "聊天记录"
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preview: List[str] = []
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summary: str = "查看x条转发消息"
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class Forward(MessageComponent):
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"""合并转发。"""
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type: str = "Forward"
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"""消息组件类型。"""
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display: ForwardMessageDiaplay
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"""显示信息"""
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node_list: List[ForwardMessageNode]
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"""转发消息节点列表。"""
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def __init__(self, *args, **kwargs):
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if len(args) == 1:
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self.node_list = args[0]
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super().__init__(**kwargs)
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super().__init__(*args, **kwargs)
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def __str__(self):
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return '[聊天记录]'
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def text_to_image(text: str) -> MessageComponent:
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"""将文本转换成图片"""
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# 检查temp文件夹是否存在
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if not os.path.exists('temp'):
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os.mkdir('temp')
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img_path = text2img.text_to_image(text_str=text, save_as='temp/{}.png'.format(int(time.time())))
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compressed_path, size = text2img.compress_image(img_path, outfile="temp/{}_compressed.png".format(int(time.time())))
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# 读取图片，转换成base64
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with open(compressed_path, 'rb') as f:
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img = f.read()
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b64 = base64.b64encode(img)
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# 删除图片
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os.remove(img_path)
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# 判断compressed_path是否存在
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if os.path.exists(compressed_path):
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os.remove(compressed_path)
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# 返回图片
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return Image(base64=b64.decode('utf-8'))
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def check_text(text: str) -> list:
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"""检查文本是否为长消息，并转换成该使用的消息链组件"""
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if len(text) > config.blob_message_threshold:
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# logging.info("长消息: {}".format(text))
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if config.blob_message_strategy == 'image':
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# 转换成图片
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return [text_to_image(text)]
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elif config.blob_message_strategy == 'forward':
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# 包装转发消息
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display = ForwardMessageDiaplay(
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title='群聊的聊天记录',
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brief='[聊天记录]',
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source='聊天记录',
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preview=["bot: "+text],
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summary="查看1条转发消息"
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)
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node = ForwardMessageNode(
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sender_id=config.mirai_http_api_config['qq'],
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sender_name='bot',
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message_chain=MessageChain([text])
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)
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forward = Forward(
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display=display,
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node_list=[node]
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)
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return [forward]
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else:
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return [text] |