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<h1 class="post-title" itemprop="name headline">使用chatterbot构建自己的中文chat(闲聊)机器人
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<p><strong>TL;DR</strong> 本文使用开源框架chatterbot从零开始构建你自己的聊天机器人（还带有WEB界面奥～）。<a id="more"></a></p>
<p>聊天机器人大体上分为三种：闲聊机器人、问答机器人和任务型机器人。闲聊机器人，顾名思义就是和你闲聊插科打诨的机器人，目前比较典型的代表是微软小冰，小黄鸡等。问答机器人有一个标准答案库，当用户来咨询时机器人负责理解用户的语意，给出符合语意的标准答案，目前比较典型的应用是各类咨询机器人，客服机器人等。最后一类：任务型机器人，通过和客户的沟通帮助用户完成特定任务比如定机票、定闹钟等，目前比较典型的应用是各种私人助理，苹果的siri系统也具备此类功能。</p>
<p>我们这里介绍一个简单易用的闲聊机器人框架chatterbot website: <a href="http://chatterbot.readthedocs.io/" target="_blank" rel="noopener">http://chatterbot.readthedocs.io/</a></p>
<p>先上一个成品图，这将是我们最后完成时的效果：</p>
<p><img src="Chat_Instance-1024x736.png" alt="Chat Instance"></p>
<h2 id="安装"><a href="#安装" class="headerlink" title="安装"></a>安装</h2><figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">pip install chatterbot</span><br></pre></td></tr></table></figure>
<h2 id="快速入门（toy级别的方案）"><a href="#快速入门（toy级别的方案）" class="headerlink" title="快速入门（toy级别的方案）"></a>快速入门（toy级别的方案）</h2><p>下面的代码实现了一个toy聊天机器人</p>
<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br></pre></td><td class="code"><pre><span class="line"># 导入所需的依赖</span><br><span class="line">from chatterbot import ChatBot</span><br><span class="line">from chatterbot.trainers import ListTrainer</span><br><span class="line"></span><br><span class="line">chatbot = ChatBot("SillyRobot") # 这里创建了机器人实例，并设定了机器人的名字：SillyRobot</span><br><span class="line"></span><br><span class="line"># 定义训练数据集</span><br><span class="line">conversation = [</span><br><span class="line"> "Hello",</span><br><span class="line"> "Hi there!",</span><br><span class="line"> "How are you doing?",</span><br><span class="line"> "I'm doing great.",</span><br><span class="line"> "That is good to hear",</span><br><span class="line"> "Thank you.",</span><br><span class="line"> "You're welcome."</span><br><span class="line">]</span><br><span class="line"></span><br><span class="line"># 训练</span><br><span class="line">chatbot.set_trainer(ListTrainer)</span><br><span class="line">chatbot.train(conversation)</span><br><span class="line"></span><br><span class="line"># 响应用户请求</span><br><span class="line">response = chatbot.get_response("Good morning!")</span><br><span class="line">print(response)</span><br></pre></td></tr></table></figure>
<p>上述代码会训练你给定的训练集，并把训练结果保存起来，没有指定的情况下，会使用存储模块<code>chatterbot.storage.SQLStorageAdapter</code>完成模型的存储。在完成训练后就可以将训练代码移除，这样机器人就不会每次都要从头训练了。</p>
<h2 id="比较正式的方案"><a href="#比较正式的方案" class="headerlink" title="比较正式的方案"></a>比较正式的方案</h2><p>上面的方案使用的语料库是硬编码在文档中的，这在正式项目中是不合适的。下面介绍一个比较正式的使用chatter的方案。</p>
<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br></pre></td><td class="code"><pre><span class="line">import os</span><br><span class="line"></span><br><span class="line">from chatterbot import ChatBot</span><br><span class="line">from chatterbot.trainers import ChatterBotCorpusTrainer</span><br><span class="line"></span><br><span class="line">current_dir = os.path.dirname(os.path.realpath(__file__))</span><br><span class="line"></span><br><span class="line">chat_bot = ChatBot("SillyRobot") # 这里创建了机器人实例，并设定了机器人的名字：SillyRobot</span><br><span class="line">chat_bot.set_trainer(ChatterBotCorpusTrainer)</span><br><span class="line"># 使用中文语料库训练它</span><br><span class="line"># chat_bot.train("chatterbot.corpus.chinese") # 语料库</span><br><span class="line"># 开始对话</span><br><span class="line">response = chat_bot.get_response("我好么")</span><br><span class="line">print(response)</span><br></pre></td></tr></table></figure>
<p>官方自带的中文聊天数据集表现比较差，你需要自己实现一个<code>trainer</code>，具体怎么实现见官方文档 <a href="http://chatterbot.readthedocs.io/en/stable/training.html#creating-a-new-training-class" target="_blank" rel="noopener">Creating a new training class</a>.</p>
<h2 id="Web集成"><a href="#Web集成" class="headerlink" title="Web集成"></a>Web集成</h2><p>chatter自带了Django集成，所以很容易架设一个网站，提供HTTP接口、管理后台以及在线聊天页面等功能。具体代码可以拷贝官方的示例代码<a href="https://github.com/gunthercox/ChatterBot/tree/master/examples/django_app" target="_blank" rel="noopener">https://github.com/gunthercox/ChatterBot/tree/master/examples/django_app</a>, 这里需要注意的是，你需要更改chatterbot的配置在<code>settings.py</code>里面的<code>CHATTERBOT</code>变量处，具体怎么修改，请参考<a href="http://chatterbot.readthedocs.io/en/stable/django/settings.html#chatterbot-django-settings" target="_blank" rel="noopener">文档1</a>和<a href="http://chatterbot.readthedocs.io/en/stable/django/training.html#training-settings" target="_blank" rel="noopener">文档2</a>,但你仍然需要以下步骤：</p>
<h3 id="安装Django"><a href="#安装Django" class="headerlink" title="安装Django"></a>安装Django</h3><figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">pip install django</span><br></pre></td></tr></table></figure>
<h3 id="同步数据库"><a href="#同步数据库" class="headerlink" title="同步数据库"></a>同步数据库</h3><figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">python manage.py migrate</span><br></pre></td></tr></table></figure>
<h3 id="创建超级用户"><a href="#创建超级用户" class="headerlink" title="创建超级用户"></a>创建超级用户</h3><figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">python manage.py createsuperuser</span><br></pre></td></tr></table></figure>
<h3 id="训练chatterbot"><a href="#训练chatterbot" class="headerlink" title="训练chatterbot"></a>训练chatterbot</h3><figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">python manage.py train</span><br></pre></td></tr></table></figure>
<h3 id="运行server"><a href="#运行server" class="headerlink" title="运行server"></a>运行server</h3><figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">python manage.py runserver</span><br></pre></td></tr></table></figure>
<p>web服务器默认监听5000端口，访问<a href="http://127.0.0.0.1:5000" target="_blank" rel="noopener">http://127.0.0.0.1:5000</a>就能访问页面了，页面效果如下图：</p>
<p><img src="Django_ChatterBot_Example-1024x561.png" alt="Django ChatterBot Example"></p>
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