{"id":534,"date":"2018-10-13T13:16:14","date_gmt":"2018-10-13T13:16:14","guid":{"rendered":"http:\/\/ai.intelligentonlinetools.com\/ml\/?p=534"},"modified":"2018-10-19T01:46:31","modified_gmt":"2018-10-19T01:46:31","slug":"how-to-create-a-chatbot-with-chatbot-open-source","status":"publish","type":"post","link":"https:\/\/ai.intelligentonlinetools.com\/ml\/how-to-create-a-chatbot-with-chatbot-open-source\/","title":{"rendered":"How to Create a Chatbot with ChatBot Open Source and Deploy It on the Web"},"content":{"rendered":"<div class=\"xbhpq69f22a3ab4242\" ><script async src=\"\/\/pagead2.googlesyndication.com\/pagead\/js\/adsbygoogle.js\"><\/script>\n<!-- Text analytics techniques 728_90 horizontal top -->\n<ins class=\"adsbygoogle\"\n     style=\"display:inline-block;width:728px;height:90px\"\n     data-ad-client=\"ca-pub-3416618249440971\"\n     data-ad-slot=\"2926649501\"><\/ins>\n<script>\n(adsbygoogle = window.adsbygoogle || []).push({});\n<\/script><\/div><style type=\"text\/css\">\r\n.xbhpq69f22a3ab4242 {\r\nmargin: 5px; padding: 0px;\r\n}\r\n@media screen and (min-width: 1201px) {\r\n.xbhpq69f22a3ab4242 {\r\ndisplay: block;\r\n}\r\n}\r\n@media screen and (min-width: 993px) and (max-width: 1200px) {\r\n.xbhpq69f22a3ab4242 {\r\ndisplay: block;\r\n}\r\n}\r\n@media screen and (min-width: 769px) and (max-width: 992px) {\r\n.xbhpq69f22a3ab4242 {\r\ndisplay: block;\r\n}\r\n}\r\n@media screen and (min-width: 768px) and (max-width: 768px) {\r\n.xbhpq69f22a3ab4242 {\r\ndisplay: block;\r\n}\r\n}\r\n@media screen and (max-width: 767px) {\r\n.xbhpq69f22a3ab4242 {\r\ndisplay: block;\r\n}\r\n}\r\n<\/style>\r\n<p><b>Chatbots<\/b> have become very popular due to progress in AI, ML and NLP. They are now used on many websites. With increased popularity of chatbots there are many different frameworks to create chatbot. We will explore one of such framework in this post.  We will review how to create a chatbot and deploy online based on open source  for <b>ChatterBot<\/b>. Our platform will be <b>Django<\/b> on pythonanywhere.  <\/p>\n<p>This chatbot tutorial introduces the basic concepts and terms needed to understand and deploy chatbot ChatterBot and provides a simple usage example. <\/p>\n<h2>What is ChatterBot?<\/h2>\n<p>ChatterBot is a Python library that makes it easy to generate automated responses to a user\u2019s input. To produce different types of responses ChatterBot uses a selection of machine learning algorithms such as search and \/or classification algorithms. This makes it easy for developers to create chat bots and automate conversations with users. [1]<\/p>\n<p>To install this chatbot open source you need just run:<br \/>\npip install chatterbot<\/p>\n<h2>ChatterBot Features<\/h2>\n<p>The functionality of chatterBot is provided through adapters &#8211; a pluggable class that allows a ChatBot instance to execute some kind of functionality.<\/p>\n<p>ChatBot has the following groups of adapters<br \/>\ninput adapters<br \/>\noutput adapters<br \/>\nstorage adapters<br \/>\nlogic adapters<\/p>\n<p>Inside of each group there several adapters that support different functionalities. For example within logic adapters we can use Best Match Adapter, Time Logic Adapter and few other. <\/p>\n<p><a href=\"http:\/\/ai.intelligentonlinetools.com\/ml\/python-chatbot-code-example\/\" target=\"_blank\">Here<\/a> is the example how do you run chatbot. Below is the output of running the code:<\/p>\n<pre class=\"brush: python; title: ; notranslate\" title=\"\">\r\nResult of program run:\r\nUSER: How are you doing?\r\nBOT:I am fine\r\nUSER: Hello\r\nBOT:Hi there!\r\nUSER: Good morning!\r\nBOT:How are today!\r\nUSER: Do you like machine learning?\r\nBOT:Yes, I like machine learning\r\nUSER: How do I make a neural network?\r\nBOTI am sorry, but I do not understand.\r\nUSER: Let us talk about current activities\r\nBOT:What are working now?\r\nUSER: I am just browsing Internet for news\r\nBOT:What a waste of time! Dont you have any other things to do?\r\nUSER: I am working on python script to make new chatbot\r\nBOT:This is great. Keep working on this\r\nUSER: Bye\r\nBOT:Bye\r\n<\/pre>\n<p>During the testing I confirmed that it correctly responds to new (but similar) inputs even if we did not train exactly.<\/p>\n<p>Once you trained the bot,  the result of training is staying there even after turning off\/on PC. So if you run program multiple times, you need run training just first time.  You still can run training later, for example if you want retrain or update python chatbot code.<\/p>\n<h2>Deployment<\/h2>\n<p>This section describes how to deploy ChatterBot on pythonanywhere web hosting site with Django programming web framework.  <\/p>\n<p>PythonAnywhere is an online integrated development environment (IDE) and web hosting service based on the Python programming language.[3] It has free account that allows to deploy our Chatbot.  Django is needed to connect web front interface with our python code for ChatterBot in the backend.  Other web frameworks like Flask can be used on pythonanywhere (instead of Django). <\/p>\n<p>Below is the diagram that is showing setup that will be described below.<br \/>\n<figure id=\"attachment_549\" aria-describedby=\"caption-attachment-549\" style=\"width: 640px\" class=\"wp-caption aligncenter\"><img decoding=\"async\" loading=\"lazy\" src=\"http:\/\/ai.intelligentonlinetools.com\/ml\/wp-content\/uploads\/2018\/10\/chatbot44-e1539536212864.png\" alt=\"Chatbot online diagram\" width=\"650\" height=\"352\" class=\"size-full wp-image-549\" \/><figcaption id=\"caption-attachment-549\" class=\"wp-caption-text\">Chatbot online diagram<\/figcaption><\/figure><\/p>\n<p>Here is how ChatterBot can be deployed on pythonanywhere with Django:<\/p>\n<li>Go to pythonanywhere and select plan  signup<\/li>\n<li>Select Create new web framework<\/li>\n<li>Select Django<\/li>\n<li>Select python version (3.6 was used in this example)<\/li>\n<li>Select project name directory<\/li>\n<p>It will create the following:<br \/>\n\/home\/user\/project_name<br \/>\n        manage.py<br \/>\n        my_template.html<br \/>\n        views.py<br \/>\n&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;-project_name<br \/>\n               init_.py<br \/>\n               settings.py<br \/>\n               urls.py<br \/>\n               wsgi.py<\/p>\n<li>create folder cbot  under user folder<\/li>\n<p>    \/home\/user\/cbot<\/p>\n<li>inside of this folder create<\/li>\n<p>        __init__.py    (this is just empty file)<br \/>\n      chatbotpy.py<\/p>\n<p>Inside <b>chatbotpy<\/b> wrap everything into function <strong>runbot<\/strong> like below. In this function we are initiating chatbot object, taking user input, if needed we train chatbot and then asking for chatbot response. The response provided by chatbot is the output of this function.  The input of this function is the user input that we are getting through web.<\/p>\n<pre class=\"brush: python; title: ; notranslate\" title=\"\">\r\ndef runbot(inp, train_bot=False):\r\n from chatterbot import ChatBot\r\n\r\n chatbot = ChatBot(&quot;mychatbot&quot;,\r\n        logic_adapters=[\r\n        {\r\n            &quot;import_path&quot;: &quot;chatterbot.logic.BestMatch&quot;,\r\n            &quot;statement_comparison_function&quot;: &quot;chatterbot.comparisons.levenshtein_distance&quot;,\r\n            &quot;response_selection_method&quot;: &quot;chatterbot.response_selection.get_first_response&quot;\r\n        },\r\n        {\r\n            'import_path': 'chatterbot.logic.LowConfidenceAdapter',\r\n            'threshold': 0.65,\r\n            'default_response': 'I am sorry, but I do not understand.'\r\n        }\r\n ],\r\n trainer='chatterbot.trainers.ListTrainer')\r\n\r\n\r\n if (train_bot == True):\r\n    print &quot;Training&quot;\r\n &quot;&quot;&quot;\r\n  Insert here training code from the python code for ChatterBot example \r\n &quot;&quot;&quot;\r\n\r\n response = chatbot.get_response(inp)\r\n return (response)\r\n<\/pre>\n<p>Now update <b>views.py<\/b> like below code box. Here we are taking user input from web, feeding this input to runbot function and sending output of runbot function (which is chatbot reponse) to web template.<\/p>\n<pre class=\"brush: python; title: ; notranslate\" title=\"\">\r\n\r\nfrom django.shortcuts import render\r\nfrom cbot.chatbotpy import runbot\r\n\r\ndef press_my_buttons(request):\r\n    resp=&quot;&quot;\r\n    conv=&quot;&quot;\r\n    if request.POST:\r\n        conv=request.POST.get('conv', '')\r\n        user_input=request.POST.get('user_input', '')\r\n\r\n        resp=runbot(user_input)\r\n\r\n        conv=conv + &quot;&quot; + str(user_input) + &quot;\\n&quot; + &quot;BOT:&quot;+ str(resp) + &quot;\\n&quot;\r\n    else:\r\n        resp=runbot(&quot;&quot;)\r\n        conv =  &quot;BOT:&quot;+ str(resp) + &quot;\\n&quot;;\r\n   \r\n    return render(request, 'my_template.html', {'conv': conv})\r\n<\/pre>\n<p>Now update <b>my_template.html<\/b> like below. Here we just show new response together with previous conversation information.<\/p>\n<pre class=\"brush: python; title: ; notranslate\" title=\"\">\r\n&lt;html&gt;\r\n&lt;form method=&quot;post&quot;&gt;\r\n    {% csrf_token %}\r\n\r\n    &lt;textarea rows=20 cols=60&gt;{{conv}}&lt;\/textarea&gt;\r\n\r\n    &lt;br&gt;&lt;br&gt;\r\n    &lt;input type=&quot;textbox&quot; name=&quot;user_input&quot; value=&quot;&quot;\/&gt;\r\n\r\n    &lt;button type=&quot;submit&quot;&gt;Submit&lt;\/button&gt;\r\n\r\n    &lt;input type=&quot;hidden&quot; name =conv  value=&quot;{{conv}}&quot; \/&gt;\r\n    {{resp}}\r\n&lt;\/form&gt;\r\n&lt;\/html&gt;\r\n<\/pre>\n<p>Now update some <b>configuration<\/b>.<br \/>\nUpdate or confirm  <b>manage.py<\/b> to include the line with settings.  <\/p>\n<pre class=\"brush: python; title: ; notranslate\" title=\"\">\r\nif __name__ == '__main__':\r\n    os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'cbotdjango.settings')\r\n<\/pre>\n<p>Update or confirm <b>urls.py<\/b> to have path like below<\/p>\n<pre class=\"brush: python; title: ; notranslate\" title=\"\">\r\nimport sys\r\npath = &quot;\/home\/user\/cbotdjango&quot;\r\nif path not in sys.path:\r\n    sys.path.append(path)\r\n<\/pre>\n<p>Now you are ready do testing chatbot online and should see the screen similar in the setup diagram on right side.<\/p>\n<h2>Conclusion<\/h2>\n<p>We saw how to train  ChatterBot  and some functionality of it.  We investigated how to install ChatterBot on pythonanywhere with Django web framework.  Hope this will make easy to deploy chatbot in case you are going this route.  If you have any tips or anything else to add, please leave a comment below. <\/p>\n<p><strong>References<\/strong><br \/>\n1. <a href=\"https:\/\/chatterbot.readthedocs.io\/en\/stable\/\" target=\"_blank\">ChatterBot<\/a><br \/>\n2. <a href=\"http:\/\/ai.intelligentonlinetools.com\/ml\/python-chatbot-code-example\/\" target=\"_blank\">Python chatbot code example<\/a><br \/>\n3. <a href=\"https:\/\/en.wikipedia.org\/wiki\/PythonAnywhere\" target=\"_blank\">Python Anywhere<\/a><\/p>\n<div class=\"kdtvt69f22a3ab4298\" ><center>\n<script async src=\"\/\/pagead2.googlesyndication.com\/pagead\/js\/adsbygoogle.js\"><\/script>\n<!-- Text analytics techniques link ads horizontal Medium after content -->\n<ins class=\"adsbygoogle\"\n     style=\"display:inline-block;width:468px;height:15px\"\n     data-ad-client=\"ca-pub-3416618249440971\"\n     data-ad-slot=\"5765984772\"><\/ins>\n<script>\n(adsbygoogle = window.adsbygoogle || []).push({});\n<\/script>\n\n<script async src=\"\/\/pagead2.googlesyndication.com\/pagead\/js\/adsbygoogle.js\"><\/script>\n<ins class=\"adsbygoogle\"\n     style=\"display:block\"\n     data-ad-format=\"autorelaxed\"\n     data-ad-client=\"ca-pub-3416618249440971\"\n     data-ad-slot=\"3903486841\"><\/ins>\n<script>\n     (adsbygoogle = window.adsbygoogle || []).push({});\n<\/script>\n<\/center><\/div><style type=\"text\/css\">\r\n.kdtvt69f22a3ab4298 {\r\nmargin: 5px; padding: 0px;\r\n}\r\n@media screen and (min-width: 1201px) {\r\n.kdtvt69f22a3ab4298 {\r\ndisplay: block;\r\n}\r\n}\r\n@media screen and (min-width: 993px) and (max-width: 1200px) {\r\n.kdtvt69f22a3ab4298 {\r\ndisplay: block;\r\n}\r\n}\r\n@media screen and (min-width: 769px) and (max-width: 992px) {\r\n.kdtvt69f22a3ab4298 {\r\ndisplay: block;\r\n}\r\n}\r\n@media screen and (min-width: 768px) and (max-width: 768px) {\r\n.kdtvt69f22a3ab4298 {\r\ndisplay: block;\r\n}\r\n}\r\n@media screen and (max-width: 767px) {\r\n.kdtvt69f22a3ab4298 {\r\ndisplay: block;\r\n}\r\n}\r\n<\/style>\r\n","protected":false},"excerpt":{"rendered":"<p>Chatbots have become very popular due to progress in AI, ML and NLP. They are now used on many websites. With increased popularity of chatbots there are many different frameworks to create chatbot. We will explore one of such framework in this post. We will review how to create a chatbot and deploy online based &#8230; <a title=\"How to Create a Chatbot with ChatBot Open Source and Deploy It on the Web\" class=\"read-more\" href=\"https:\/\/ai.intelligentonlinetools.com\/ml\/how-to-create-a-chatbot-with-chatbot-open-source\/\" aria-label=\"More on How to Create a Chatbot with ChatBot Open Source and Deploy It on the Web\">Read more<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0},"categories":[47],"tags":[48,50,49],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.4 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>How to Create a Chatbot with ChatBot Open Source and Deploy It on the Web - Text Analytics Techniques<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"http:\/\/ai.intelligentonlinetools.com\/ml\/how-to-create-a-chatbot-with-chatbot-open-source\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"How to Create a Chatbot with ChatBot Open Source and Deploy It on the Web - Text Analytics Techniques\" \/>\n<meta property=\"og:description\" content=\"Chatbots have become very popular due to progress in AI, ML and NLP. 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