Niken
105 lines
3.9 KiB
Python
105 lines
3.9 KiB
Python
import base64
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import aiohttp
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import logging
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from aiogram import Dispatcher, Bot
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from aiogram.types import Message
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from utils.antispam import saving, save_message
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from aiogram.filters import Command
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from models.state import BotState
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logger = logging.getLogger(__name__)
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def register_handlers(dp: Dispatcher, state: BotState, bot: Bot):
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chat_history = {}
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MAX_HISTORY = 20 # храним последние 20 сообщений (user+assistant)
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@dp.message(Command("gpt"))
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@saving
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async def ask_gpt(message: Message):
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chat_id = message.chat.id
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if chat_id not in chat_history:
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chat_history[chat_id] = []
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content_blocks = []
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user_prompt = None
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# Текст после команды или caption
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if message.text:
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parts = message.text.split(maxsplit=1)
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if len(parts) > 1:
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user_prompt = parts[1]
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if message.caption:
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user_prompt = message.caption
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if user_prompt:
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content_blocks.append({"type": "text", "text": user_prompt})
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# Фото → base64 → image_url
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if message.photo:
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photo = message.photo[-1]
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file = await bot.get_file(photo.file_id)
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file_bytes = await bot.download_file(file.file_path)
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image_b64 = base64.b64encode(file_bytes.read()).decode("utf-8")
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content_blocks.append(
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{
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"type": "image_url",
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"image_url": {"url": f"data:image/jpeg;base64,{image_b64}"},
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}
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)
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if not content_blocks:
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await message.reply("❗ Укажи текст или прикрепи фото")
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return
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url = "http://192.168.31.197:1234/v1/chat/completions"
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# Добавляем новое сообщение в историю
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chat_history[chat_id].append({"role": "user", "content": content_blocks})
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# Ограничиваем историю (оставляем последние MAX_HISTORY сообщений)
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if len(chat_history[chat_id]) > MAX_HISTORY:
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chat_history[chat_id] = chat_history[chat_id][-MAX_HISTORY:]
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payload = {
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"model": "qwen/qwen3-vl-4b",
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"messages": chat_history[ chat_id],
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"temperature": 0.7,
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"max_tokens": 4096,
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"stream": False,
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}
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try:
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async with aiohttp.ClientSession() as session:
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async with session.post(url, json=payload) as resp:
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if resp.status != 200:
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error_text = await resp.text()
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await message.reply(
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f"❌ Ошибка LM Studio: {resp.status} {error_text}"
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)
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return
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data = await resp.json()
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reply_text = data["choices"][0]["message"]["content"]
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# Сохраняем ответ ассистента в историю
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chat_history[chat_id].append(
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{
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"role": "assistant",
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"content": [{"type": "text", "text": reply_text}],
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}
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)
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# Ограничиваем снова (чтобы не разрасталось)
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if len(chat_history[chat_id]) > MAX_HISTORY:
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chat_history[chat_id] = chat_history[chat_id][-MAX_HISTORY:]
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msg = await message.reply(f"🤖 Ответ:\n{reply_text}")
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save_message(msg.chat.id, msg.message_id)
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except Exception as e:
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logger.error(f"Ошибка при запросе к LM Studio: {e}")
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await message.reply(f"❌ Ошибка при запросе к LM Studio: {e}")
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@dp.message(Command("clear"))
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async def clear(message: Message):
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chat_history.pop(message.chat.id, None) |