92 lines
3.6 KiB
Python
92 lines
3.6 KiB
Python
import logging
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import math
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from store import redis, get_average_toxic
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from bot.api import telegram_api
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from bot.config import FEEDBACK_CHAT_ID
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from nlp.toxicity_detector import detector
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from handlers.handle_private import handle_private
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from utils.normalize import normalize
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logger = logging.getLogger('handlers.messages_routing')
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logging.basicConfig(level=logging.DEBUG)
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async def messages_routing(msg, state):
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cid = msg["chat"]["id"]
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uid = msg["from"]["id"]
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text = msg.get("text", msg.get("caption"))
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reply_msg = msg.get("reply_to_message")
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if cid == uid:
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# сообщения в личке с ботом
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logger.info("private chat message: ", msg)
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await handle_private(msg, state)
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elif str(cid) == FEEDBACK_CHAT_ID:
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# сообщения из группы обратной связи
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logger.info("feedback chat message: ", msg)
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logger.debug(msg)
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if reply_msg:
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reply_chat_id = reply_msg.get("chat", {}).get("id")
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if reply_chat_id != FEEDBACK_CHAT_ID:
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await telegram_api("sendMessage", chat_id=reply_chat_id, text=text, reply_to_message_id=reply_msg.get("message_id"))
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elif bool(text):
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mid = msg.get("message_id")
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if text == '/toxic@welcomecenter_bot':
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# latest in chat
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latest_toxic_message_id = await redis.get(f"toxic:{cid}")
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# reply_to message_id
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reply_to_msg_id = mid
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if reply_msg:
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reply_to_msg_id = reply_msg.get("message_id")
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if not reply_to_msg_id and latest_toxic_message_id:
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reply_to_msg_id = int(latest_toxic_message_id)
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# count average between all of messages
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toxic_score = await get_average_toxic(msg)
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#
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if reply_to_msg_id:
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one_score = await redis.get(f"toxic:{cid}:{uid}:{reply_to_msg_id}")
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if one_score:
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logger.debug(one_score)
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emoji = '😳' if toxic_score > 90 else '😟' if toxic_score > 80 else '😏' if toxic_score > 60 else '🙂' if toxic_score > 20 else '😇'
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text = f"{int(one_score)}% токсичности\nСредняя токсичность сообщений: {toxic_score}% {emoji}"
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await telegram_api(
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"sendMessage",
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chat_id=cid,
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reply_to_message_id=reply_to_msg_id,
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text=text
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)
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await telegram_api(
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"deleteMessage",
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chat_id=cid,
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message_id=mid
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)
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else:
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toxic_score = detector(normalize(text))
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toxic_perc = math.floor(toxic_score*100)
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await redis.set(f"toxic:{cid}", mid)
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await redis.set(f"toxic:{cid}:{uid}:{mid}", toxic_perc, ex=60*60*24*3)
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logger.info(f'\ntext: {text}\ntoxic: {toxic_perc}%')
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if toxic_score > 0.81:
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if toxic_score > 0.90:
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await redis.set(f"removed:{uid}:{cid}:{mid}", text)
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await telegram_api(
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"deleteMessage",
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chat_id=cid,
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message_id=mid
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)
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else:
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await telegram_api(
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"setMessageReaction",
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chat_id=cid,
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is_big=True,
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message_id=mid,
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reaction=f'[{{"type":"emoji", "emoji":"🙉"}}]'
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)
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else:
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pass
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