统一消息系统

# 定义统一消息类

class UnifiedMessage:

def __init__(self, sender_id, receiver_id, content, timestamp, source_platform):

self.sender_id = sender_id

self.receiver_id = receiver_id

self.content = content

self.timestamp = timestamp

self.source_platform = source_platform

def to_dict(self):

return {

"sender_id": self.sender_id,

"receiver_id": self.receiver_id,

"content": self.content,

"timestamp": self.timestamp,

"source_platform": self.source_platform

}

# 模拟从不同平台获取消息

def get_message_from_wechat():

return UnifiedMessage("user123", "admin", "你好，请问今天有空吗？", "2025-04-05T10:00:00Z", "wechat")

def get_message_from_email():

return UnifiedMessage("user456", "admin", "请查看附件中的报告", "2025-04-05T11:00:00Z", "email")

# AI助手处理消息

def ai_assistant(message):

from transformers import pipeline

classifier = pipeline("text-classification", model="distilbert-base-uncased-finetuned-sst-2-english")

result = classifier(message.content)

label = result[0]["label"]

score = result[0]["score"]

if label == "POSITIVE":

return f"这条消息是积极的，分数为 {score:.2f}，建议回复问候。"

elif label == "NEGATIVE":

return f"这条消息是消极的，分数为 {score:.2f}，建议关注用户情绪。"

else:

return f"这条消息是中性的，分数为 {score:.2f}，无需特别处理。"

# 主程序

if __name__ == "__main__":

msg1 = get_message_from_wechat()

print(f"收到来自 {msg1.source_platform} 的消息：{msg1.content}")

response = ai_assistant(msg1)

print("AI助手回复：", response)

msg2 = get_message_from_email()

print(f"收到来自 {msg2.source_platform} 的消息：{msg2.content}")

response = ai_assistant(msg2)

print("AI助手回复：", response)

# 自动回复函数

def auto_reply(message):

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")

model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")

input_ids = tokenizer.encode(message.content + tokenizer.eos_token, return_tensors="pt")

response_ids = model.generate(input_ids, max_length=100, pad_token_id=tokenizer.eos_token_id)

response = tokenizer.decode(response_ids[:, input_ids.shape[-1]:][0], skip_special_tokens=True)

return f"AI助手回复：{response}"