Open Source AI Chatbot Tools

Open-source chatbots are informing applications that re-enact a conversation between humans. Open-source implies the primary code for the product is dispersed freely and can easily be altered. Open-source software programs prompt greater levels of straightforwardness, scalability, and control via shared commitments. This lets designers make programming of higher quality while expanding their perception into the product stages themselves. There are many open-source chatbot software programs available nowadays. Which chatbot turns out fine for you may depend on the innovation and coding languages you use, and how distinct businesses have used chatbots can help you with selecting. Now, let’s dig deep into the top open-source chatbot tools everyone needs to understand.

Type Bot

Type Bot is free and open-source software that permits users to build advanced chatbots easily. It provides a visual editor that allows users to create chatbot flows and personalize the appearance of the chat interface. With Type Bot, users can embed chatbots anywhere on their websites or cellular apps and collect valuable consumer information. The platform also supports integrations with Open AI, allowing customers to integrate powerful language models like Chat GPT into their chatbots. Whether you want to create an easy customer-assistant chatbot or a compliant AI-powered conversational agent, Type Bot has the tools and functions to meet your necessities.

Type Bot; Source: Type Bot

Pros:

  • Easy to use and set up. 
  • Automated tasks.
  • Collect effects in real-time.
  • Powerful analytics dashboard.
  • Advanced safety features.
  • Native integrations.

Cons:

  • Limited customization options.
  • Limited customer support. 
  • Pricing plans may be expensive for small companies.

Pricing:

  • Free
  • Starter: $39/month
  • Pro: $89/month

BotMan 

BotMan is a free PHP framework for chatbot development. It is the most widely used open-source PHP chatbot in the world. BotMan was constructed for developers to simplify the project of developing modern bots for multiple messaging systems, consisting of Slack, Telegram, Microsoft Bot Framework, Nexmo, HipChat, Facebook Messenger, and WeChat.

BotMan; Source: Laravel News

BotMan lets you write down your chatbot's logic once and connect it to different messaging offerings, such as Amazon Alexa, Facebook Messenger, Slack, Telegram, or maybe your own website.

BotMan is framework-agnostic, which means you can use it in your current codebase with whatever framework you want. BotMan has an expressive yet powerful syntax that lets you focus on business logic, no longer on framework code. BotMan offers full documentation, is written in PHP, and works on Linux, Windows, and macOS. BotMan is certified under the MIT License.

Pros:

  • Many features 
  • Decent pricing
  • Great customer service
  • Framework agnostic
  • Expressive and effective syntax

Cons:

  • Limited filtering capabilities
  • Room for development in agility and acceleration

Pricing:

  • Contact sales for custom pricing

Microsoft bot framework

This bot framework is also called the Azure bot framework. It enables you to build, connect, and manage interactive chatbots. It consists of active learning and multilanguage aid to help you enhance the conversation with the consumer. It additionally uses the Azure Service platform; which is an included development environment, to make building your bots faster and less complicated.

Microsoft chatbot framework; Source: Koukia

The Microsoft chatbot framework provides pre-built models that you can use on your website, Skype, Slack, Facebook Messenger, Microsoft Teams, and plenty of other channels. It’s geared toward developers because the technique is frequently code-driven. This open-source chatbot gives developers full control over the bot’s development, enjoyment, and access to diverse functions and connectors. 

Pros:

  • Integrates with Microsoft Cognitive Services, Cortana, Kik, and many others
  • SDKs for multiple PC languages to be had
  • Speech-to-text machine learning 

Cons:

  • The NLU engine cannot be set up on-premise

Pricing:

  • Standard channels (Free)
  • Premium channels (10,000 messages/month free, after $0.50 in keeping with 1,000 messages)

Wit.Ai

Wit.ai was acquired by Facebook in 2015, which made deploying bots on Facebook Messenger seamless. It also offers integrations with different channels, together with websites, mobile apps, wearable gadgets, and domestic automation. The SDK is to be had in a couple of coding languages like Ruby, Node.js, and iOS. 

Wit.ai; Source: Y Combinator

This free chatbot framework offers a nicely documented bot API, so even novices can get started with this platform. It offers over 80 distinctive languages and a sturdy NLP engine to create entities and intents. Some argue that it gives higher NLP chatbots than the competition, such as Microsoft and Amazon. You can also use voice-based bots to make it extra user-friendly

Pros:

  • Easy installation on Facebook Messenger
  • Strong NLP engine
  • SDK in a couple of languages, which include Python, Ruby, and Node.Js

Cons:

  • Laborious training

Pricing:

  • Free to use

Rasa

This open-source framework works well for building contextual chatbots, which could add a more human feel to the interactions. You can build stories to teach your bots. These stories will function as expected conversational flows. The system helps with synonyms and hyponyms, so you don’t need to train the bots for every possible variation of the phrase. After deploying the virtual assistants, they interactively research as they communicate with users.

Rasa; Source: The TensorFlow Blog

This chatbot framework consists of two important components. Rasa NLU (natural language understanding) and Rasa Core are used to build conversational chatbots. Combined, these components help users build bots that might be able to manage complex consumer inquiries. You can save information in client databases to grow the knowledge of your clients. 

Pros:

  • Multiple environments for development, staging, and production
  • Analytics for consumer information
  • Highly customizable when it comes to capabilities and design

Cons:

  • It is not appropriate for novices as it requires you to have knowledge of NLP, deepen your knowledge of, and understand Python language to construct contextual chatbots

Pricing:

  • Contact sales for custom pricing

BotPress

This is one of the best open-source chatbot frameworks with a modular architecture, allowing you to build chatbots in modules that can work independently of one another. BotPress allows you to create bots and install them on your own server or on a preferred cloud host. It also includes a visual conversation builder and an emulator for testing conversations. This can help you create more natural and human-like interactions with clients.

BotPress; Source: BotPress

This open-source platform provides actionable chatbot analytics, allowing you to keep a close eye on your results and make better business decisions. It uses NLU modules to help you outline intents, entities, and slots. Advanced permissions can also be used to limit who can edit the bot. Also, it offers spell-checking and language identification for better user conversations. 

Pros:

  • Visual communication builder
  • Advanced permissions
  • Easy-to-understand documentation

Cons:

  • Limited functions, especially rule- and movement-based bots, are available.
  • Github repo not available

Pricing:

  • Free open-source model
  • Enterprise plan: contact income for custom pricing

ChatterBot

ChatterBot is a Python-based bot flow that is computerized through machine learning technology. It is a Python chatbot library that can be imported and used in your Python projects. Its working mechanism is based totally on the procedure; the more input ChatterBot gets, the more efficient and correct the output will be. 

ChatterBot; Source: GitHub

This Python chatbot offers advertising and marketing automation and answering features. It additionally integrates with Facebook and Zapier for added functionality in your system. You can effortlessly customize and edit the code for the chatbot to fit your business needs. On top of that, it has a language independence nature that permits training it in any language. 

Pros:

  • Language independent
  • It works across all devices
  • Efficiency improves with input

Cons:

  • Requires advanced Python programming abilities

Pricing:

  • Free to use

BotKit

This open-source conversational AI was obtained by Microsoft in 2018. Some of its built-in developer tools consist of content control, analytics, and operational mechanisms. You can learn the way your site visitors use the bots and who the users are. It gives considerable documentation and an incredible community where you can seek advice if you have any problems, even when using the framework.

BotKit; Source: GitHub

BotKit is a code-centric platform with a visual conversational builder and plenty of integrations for your needs. Cisco Spark, Google Hangouts, Microsoft Teams, and others are among them. It additionally offers a flexible system for coping with transactional questions and scripted dialogs. You can use the meaningful building blocks for creating conversational user interfaces and provide an excellent user experience for your visitors.

Pros:

  • Easy-to-use interface
  • Visual conversation builder
  • Supports all predominant platforms 

Cons:

  • No built-in NLP—uses Microsoft’s LUIS provider

Pricing:

  • Free to use

Conclusion

Before deciding on the chatbot software you want to invest time and money in, you need to understand how you plan to make use of it and the features that are essential for that. One of the main benefits of open source is that you can try the product before choosing it.

While some agencies have said diverse use cases for their platform, that’s not always the case. We strongly advise journeying through the unique chatbot boards and attempting to find what you need to construct. Still, it’s a high-quality starting point to remove some opponents and grasp their strengths and shortcomings.



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