后端代码机器人架构 机器人代码开源

import com.github.mpjava.core.Message;

import com.github.mpjava.core.MessageHandler;

public class MyWeChatBot {

public static void main(String[] args) {

WeChatBot bot = new WeChatBot("Your_App_ID", "Your_App_Secret");

bot.setMessageHandler(new MessageHandler {

Override

public void onMessageReceived(Message message) {

String content = message.getContent;

if(content != null && content.startsWith("你好")) {

bot.sendMessage(message.getFromUser, "你好,感谢你的信息!");

});

bot.start;

这段代码展示了微信机器人的基本结构，包括消息接收处理和自动回复功能。

对于Python开发者，以下是使用HuggingChat框架加载对话模型的示例：

from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "microsoft/DialoGPT-medium

tokenizer = AutoTokenizer.from_pretrained(model_name)

model = AutoModelForCausalLM.from_pretrained(model_name)

import torch

chat_history_ids = None

new_user_input = "你好,今天的天气怎么样?

new_user_input_ids = tokenizer.encode(new_user_input + tokenizer.eos_token, return_tensors='pt')

bot_input_ids = torch.cat([chat_history_ids, new_user_input_ids], dim=-1) if chat_history_ids is not None else new_user_input_ids

chat_history_ids = model.generate(bot_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id)