Top 8 OpenSource Tools for AI Startups - DEV Community

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Med Marrouchi
Posted on 28 de out. • Edited on 31 de out.
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Top 8 OpenSource Tools for AI Startups
#webdev #opensource #startup #ai
Are you building the next AI unicorn? 🦄
Whether you're in the early stages of an AI startup or scaling up, having the right set
of open-source tools can make a world of difference. I've put together a list of some
top-notch open-source tools that have been invaluable to me, and I think they'll be
incredibly helpful for your AI journey too:
Hexabot
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If you're building AI-powered chatbots, you need something flexible, powerful, and
open. Hexabot is an open-source chatbot solution designed to be highly extensible.
It supports multi-channel chat, powerful NLP capabilities, and a great plugin system.
Perfect for rapid prototyping or launching your chatbot product.
Star on GitHub ⭐ - Hexabot
StableStudio
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https://github.com/hexastack/hexabot
https://github.com/hexastack/hexabot
StableStudio is Stability AI's official open-source version of DreamStudio, providing
a user-friendly interface for generative AI. This web-based application enables users
to create and edit generated images, and we're eager to see how the community
contributes to its evolution!
Star on GitHub ⭐ - StableStudio
ChatGPT4all
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https://github.com/Stability-AI/StableStudio
Generative AI is hot, and ChatGPT4all is an exciting open-source option. It allows
you to run your own language model without needing proprietary APIs, enabling a
private and customizable experience.
Star on GitHub ⭐ - ChatGPT4all
Ollama
Ollama is an emerging tool that helps you bring open LLMs into production with
ease. It simplifies serving and running models in a production environment, whether
on the cloud or locally. It's the bridge between prototyping LLMs and making them
work for your customers.
Star on GitHub ⭐ - Ollama
MLflow
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https://github.com/nomic-ai/gpt4all
https://github.com/nomic-ai/gpt4all
https://ollama.com/
https://github.com/ollama/ollama
Managing experiments, versioning, and deployments can quickly get chaotic.
MLflow is an open-source platform that helps with tracking experiments, managing
models, and deploying them. It s̓ a must-have tool if you're serious about ML
engineering.
Star on GitHub ⭐ - MLflow
TensorFlow
This one hardly needs an introduction. TensorFlow by Google is a staple for many AI
projects. It s̓ an end-to-end open-source platform for machine learning, capable of
handling everything from initial prototyping to full deployment in production.
Star on GitHub ⭐ - Tensorflow
PyTorch
For those who prefer a more flexible, Pythonic interface, PyTorch is often the way to
go. Its dynamic computation graphs and ease of use have made it a favorite for
researchers and AI startups alike. Plus, the thriving PyTorch community means
plenty of support and open-source examples.
Star on GitHub ⭐ - PyTorch
Keras
If you need simplicity, Keras is a great high-level API built on top of TensorFlow. It
lets you quickly prototype neural networks without worrying about low-level
implementations. Keras is perfect for getting those first models up and running—an
essential part of the startup hustle.
Star on GitHub ⭐ - Keras
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https://mlflow.org/
https://github.com/mlflow/mlflow
https://www.tensorflow.org/
https://github.com/tensorflow/tensorflow
https://pytorch.org/
https://github.com/pytorch/pytorch
https://keras.io/
https://github.com/keras-team/keras
These tools have proven themselves time and time again, not only in the projects I've
worked on but also within the broader AI community. Whether you are building
advanced NLP systems, tackling MLOps, or developing a full-fledged chatbot
platform, these open-source tools can accelerate your development, save you time,
and help you avoid reinventing the wheel.
Have you used any of these tools? Which ones have made the biggest impact in your
startup journey? I'd love to hear about your experience!
Code of Conduct Report abuse
Top comments (2)
M.Bilal Sardar • 1 de nov.
I recommend refraining from including TensorFlow, PyTorch, and Keras in
lists of relevant technologies going forward. Adding them purely to inflate
the content feels redundant. its an easy way out.
amuhareb • 3 de nov.
also, no mention of langchain is wild
•
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Med Marrouchi
Currently working on http://github.com/hexastack/hexabot I'm a Web Engineer, I love all about
coding and music
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