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import logging |
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from telegram import Update |
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from telegram.ext import ApplicationBuilder, CommandHandler, MessageHandler, filters |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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import torch |
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logging.basicConfig( |
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format='%(asctime)s - %(name)s - %(levelname)s - %(message)s', |
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level=logging.INFO |
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) |
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model_name = "نام مدل شما" |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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model = AutoModelForCausalLM.from_pretrained(model_name) |
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def generate_response(input_text): |
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inputs = tokenizer(input_text, return_tensors="pt").to("cuda") |
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output = model.generate(**inputs, max_new_tokens=100) |
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response = tokenizer.decode(output[0], skip_special_tokens=True) |
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return response |
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async def start(update: Update, context): |
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await update.message.reply_text('سلام! من یک بات هوش مصنوعی هستم. میتوانید با من چت کنید.') |
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async def echo(update: Update, context): |
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user_message = update.message.text |
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response = generate_response(user_message) |
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await update.message.reply_text(response) |
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def main(): |
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token = "توکن بات شما" |
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application = ApplicationBuilder().token(token).build() |
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start_handler = CommandHandler('start', start) |
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application.add_handler(start_handler) |
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echo_handler = MessageHandler(filters.TEXT & ~filters.COMMAND, echo) |
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application.add_handler(echo_handler) |
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application.run_polling() |
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if __name__ == '__main__': |
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main() |
