【自然语言处理】python之人工智能应用篇——文本生成技术

import random
from collections import defaultdict
class MarkovTextGenerator:
    def __init__(self, source_file='source_text.txt', chain_order=2):
        self.chain_order = chain_order
        self.model = defaultdict(list)
        with open(source_file, 'r', encoding='utf-8') as file:
            text = file.read().split()
        self._train(text)
    def _train(self, words):
        for i in range(len(words) - self.chain_order):
            state = tuple(words[i:i + self.chain_order])
            next_word = words[i + self.chain_order]
            self.model[state].append(next_word)
    def generate_text(self, length=100):
        if not self.model:
            return "模型未训练，请先加载数据。"
        
        state = random.choice(list(self.model.keys()))
        output = list(state)
        
        for _ in range(length):
            if state in self.model:
                next_word = random.choice(self.model[state])
                output.append(next_word)
                state = tuple(output[-self.chain_order:])
            else:  # 如果当前状态没有后续词，则重新选择一个起始状态
                state = random.choice(list(self.model.keys()))
                output = list(state)
        
        return ' '.join(output)
if __name__ == "__main__":
    generator = MarkovTextGenerator()
    generated_text = generator.generate_text(100)
    print(generated_text)

import random
class SimpleChatBot:
    def __init__(self):
        self.greetings = ["你好！", "嗨，有什么可以帮助你的吗？", "你好呀！"]
        self.goodbyes = ["再见！祝你有美好的一天！", "下次见！", "拜拜~"]
        self.questions_answers = {
            "你叫什么名字？": "我是小智，你的私人助手。",
            "今天天气怎么样？": "我是个简单的机器人，无法查看实时天气，请查询天气应用。",
            "你喜欢什么？": "我喜欢帮助人们解答问题。",
            "讲个笑话吧": "为什么袜子总是只丢一只？因为丢两只根本就不会发现！",
        }
    def respond_to(self, user_input):
        # 检查问候语
        for greeting in self.greetings:
            if user_input.lower() == greeting.lower():
                return random.choice(self.greetings)
        # 检查问题与答案
        for question, answer in self.questions_answers.items():
            if question.lower() in user_input.lower():
                return answer
        # 如果没有匹配到，则给出默认回复
        return "抱歉，我不太明白你在说什么。你可以问我其他问题，比如我的名字或者讲个笑话。"
    def run(self):
        print("你好！我是你的聊天机器人。你可以开始提问了。（输入'再见'结束对话）")
        while True:
            user_input = input("> ")
            if user_input.lower() == "再见":
                print(random.choice(self.goodbyes))
                break
            else:
                response = self.respond_to(user_input)
                print(response)
if __name__ == "__main__":
    chat_bot = SimpleChatBot()
    chat_bot.run()

import random
from datetime import datetime, timedelta
# 新闻类别列表
news_categories = ["科技", "体育", "娱乐", "国际", "财经"]
# 地点列表
locations = ["北京", "纽约", "巴黎", "东京", "伦敦"]
# 人物角色列表
characters = ["专家", "明星", "企业家", "运动员", "政要"]
# 随机生成新闻标题和内容的函数
def generate_news_item():
    # 随机选择新闻类别、地点和人物
    category = random.choice(news_categories)
    location = random.choice(locations)
    character = random.choice(characters)
    
    # 生成随机日期，模拟新闻发布日期（最近一周内）
    publish_date = datetime.now() - timedelta(days=random.randint(0, 6))
    formatted_date = publish_date.strftime("%Y年%m月%d日")
    
    # 构建新闻标题和内容
    title = f"{character}在{location}{random.choice(['发现', '宣布', '参与', '赢得'])}了{category}界的大事件！"
    content = f"近日，据消息人士透露，{character}于{formatted_date}在{location}的一次{category}盛会上{title.split('了')[-1]}。这一事件迅速引起了业界的广泛关注。更多细节敬请期待后续报道。"
    
    return {
        "title": title,
        "date": formatted_date,
        "content": content,
        "category": category
    }
# 生成一条新闻并打印
news_item = generate_news_item()
print("新闻标题:", news_item["title"])
print("发布日期:", news_item["date"])
print("新闻内容:\n", news_item["content"])
print("类别:", news_item["category"])