8 Best open source AI chatbots to speed up your development process

It is the second year of generative AI, and we have already seen developers and companies of all sizes using AI in some way. 

Google says that over 25% of its code is written by AI. AI is similar to how the Cloud was a few years ago. 

People feared that it would take away jobs, but instead, it helped in multiple processes and created more jobs. 

I see AI as a companion, an assistant that helps us move faster and be more productive. 

In this article, we will talk about some of the best  open source AI chatbots that can be integrated into our existing workflows or used as building blocks for creating custom AI tools for developers.

Here are the top ones for you to try:

Pieces Copilot

Pieces is an AI-enabled tool for software developers, designed by software developers to improve efficiency and collaboration within a team or individual coding. 

Pieces offers an open source copilot project that leverages their TypeScript SDK to imitate the core functionalities of Pieces Copilot where you can run the project locally and interact with available cloud and local large language models.

This copilot example project is powered by Local Large Language models (LLLMs) such as Mistral AI, Phi-2, and Llama 2, as well as cloud-based Large Language Models (LLMs) such as GPT-4, Gemini, and PaLM 2.

There are also SDKs available in Python, Dart, and Kotlin that you can try out.

It can help you save, share, and generate code snippets, whereas a traditional chatbot is only focused on conversational interactions and may span beyond a wider audience. 

Learn the difference between conversational and generative AI before selecting the open source chatbot builder for you. 

Or join a Discord community where you can chat with other developers and collaborate on a project.

Pros: It supports multiple LLMs. It is more than just a chatbot and can help you save snippets, share and transform them. 

They have a very active community of developers where you can get your queries answered and also get a chance to network with other developers.

Cons:  The only con that I see is that it is a slight learning curve for you to fully leverage the copilot’s capabilities. The company is at a promising growing stage, and has already raised series A.

Hugging Chat

Hugging Face is a well-known platform in the field of machine learning, serving as a community for collaborators on models, datasets, and applications.

The hugging face team built an open source AI chatbot that is powered by current free and open source chat AI models such as Mistral AI, Code Llama, Gemma, and Open Assistant that lets users search the web for a more accurate, detailed response.

Hugging Face has a Discord community where you get to talk to other users or developers, learn more about their products and tools, and collaborate on projects.

Pros: As developers, we like customization. Hugging Chat gives you the ability to skip the configuration, and setup, and launch your own Chat UI yourself.

Rasa

Rasa is an open source conversational AI platform that helps you create your own AI tool with the help of its open source chatbot software. 

It provides flexible conversational AI software for building text and voice-based assistants and gives you the flexibility to train models, and customize, and modify your Natural Language Understanding (NLU) component to make it more personalized. It provides the tools and infrastructure to develop, train, and deploy contextual and intelligent virtual assistants that can understand natural language.

Rasa also has a diverse community of conversational AI users and builders and provides quickstarts that can help you develop your first assistant in your browser with Github Codespaces.

Pros:  Rasa’s open source version is a single command installation, which makes it easy to get started and also has great documentation. 

Cons: Rasa does not provide a built-in UI for the chat interface, so creating custom UIs or integrating with existing tools would require extra effort.

Botpress

Botpress is an open source chatbot builder built by the OpenAI team that provides you APIs to build chatbots similar to ChatGPT for your personal or company and can help in improving your or your team’s productivity and efficiency.

With botpress, you can build bots or chatbots that understand natural language, automate tasks easily, and personalize your experience. 

It also has a large and active community of developers and users who contribute to its development and provide support.

Pros: Botpress offers a drag-and-drop interface, which makes it easier to design and develop conversational flows without much coding.

Cons: It lacks quickstart guides for developers who want to build more complex workflows.

Claudia

Claudia.js is an open-source serverless JavaScript framework that helps you build and deploy AI chatbots on AWS.

Claudia uses serverless models to remove the need to manage servers thereby making development easy, cost-efficient ,and scalable.

Claudia also has a large and active community where you can chat with the maintainers or even contribute.

Pros: It is fast and easy to get started. You can deploy your bots directly to AWS Lambda with minimal configuration.

Cons: It requires some prior knowledge of machine learning and AI, making it difficult for beginners to start with.

LM Studio

LM Studio is a desktop app for developing and experimenting with LLMs on your computer. 

This powerful open source application offers users a smooth user interface to experiment with and configure LLM models.

Here’s all that it provides:

• A desktop application for running local LLMs

• A chatbot user interface

• Search & download functionality (via Hugging Face)

• A local server that can listen on OpenAI-like endpoints

• Systems for managing local models and configurations

Pros: It is great for developers wanting local AI development, it also supports multiple AI models, along with easy model downloading and management.

Cons: LM Studio is resource-intensive and has occasional performance inconsistencies across different hardware configurations that can be challenging for developers with limited computing.

FlowiseAI

Flowise is an open source low-code tool for developers to build customized LLM orchestration flows & AI agents. 

Its drag-and-drop UI approach enables quick iterations and can help you go from testing to production faster.

Its APIs can help you build complex assistants easily, and it also has an active open source community where you can contribute and also interact with the maintainers.

Pros: The drag-and-drop UI of Flowise is great for developers to get started quickly, and it has extensive APIs that can help you build more.

Cons: It does not include a single click setup as of now, so it might not be suitable for absolute beginner

Chainlit

Chainlit is an open-source Python package to build production-ready Conversational AI. You can install it using a single command pip install chainlit.

Some of the key features are:

1. It can integrate easily with an existing code base or start from scratch in minutes

2. You can write your assistant logic once, and use it everywhere

3. It can collect, monitor, and analyze data from your users

Pros: Chainlit is compatible with all Python programs and libraries. It also comes with a set of integrations with popular libraries and frameworks such as OpenAI, MistralAI, LangChain etc. 

You can check out more examples of their AI chatbot integrations on GitHub.

Cons: Since it is a Python package, it can only be used by developers who are well-versed in Python.

Why using open source AI chatbots becomes popular?

Open source language models  has been helping developers and even enterprises build or integrate solutions for years now, and some of the main reasons why we keep looking for open source alternatives are:

Cost-effectiveness

Open-source AI chatbots are a cost-effective solution that provides a better user experience. 

With so many developers actively contributing to the software, users can navigate it with ease while getting improvements based on community insights and experiences.

Transparency

As the software or chatbot is open source, it is transparent in the sense that developers have easy access or a free pass to inspect the source code, identify bugs or errors, and improve the overall security.

Customization

Since it is open source, as a developer you have the flexibility to contribute, develop your own solutions as well as easily integrate it with other services.

Community support

Open source is known for its communities, be it for support or help to get started, you will always have a community that listens to you and helps you.

Conclusion

Chatbots are the most common use case of AI. 

Be it for business needs or your own learnings, knowing how to build chatbots and knowing about tools that can help you build one is important. 

This article was first published on March 11th, 2024, and we’ve updated it as of December 13th, 2024, to improve your experience and share the latest information.