AI & Node.js
Create intelligent, efficient, and user-friendly experiences by integrating AI into JavaScript applications
Why Node.js with AI?
Al and Large Language Models (LLMs) are growing as an important tool for Web applications. As a JavaScript/Node.js developer it's important to understand how to fit into this growing space. While Python is often thought of as the language for Al and model development, this does not mean that all application development will shift to Python. Instead the tools/languages that are the best fit for each part of an application will continue to win out and those components will be integrated together to form the overall solution.
Getting Started
Here are some resources to help you get started in adding Al to your Node.js applications.
Granite LLMs with Node.js and Podman Desktop
Guide to downloading the Granite model, running it as a container and integrating the model into your Node.js application.
Creating an LLM powered Chatbot with Node.js
A guide to create an LLM powered chatbot and enable chatting with it using Node.js and React.
Email generation and summarisation with Node.js
A guide to summarize and generate emails using an LLM with Node.js.
Retrieval Augmented Generation (RAG)
An LLMs knowledge is limited to the data it has been trained on. Retrieval Augmented Generation or RAG makes an LLM aware of context-specific knowledge or proprietary data. Below are some posts that will help you to understand this concept.
Using RAG to optimize Al applications
Guide to downloading the Granite model, running it as a container and integrating the model into your Node.js application.
Improving Chatbot results with RAG
A guide to create an LLM powered chatbot and enable chatting with it using Node.js and React.
Tools & Agents
Tools and Agents can help provide LLMs with additional capabilities like integrating with an external APIs and even build an agentic workflow.
Calling a function from LLMs with Node.js and Ollama
A guide to enable LLMS to interact with external API to add additional capabilities.
Building agents with LLMs and Node.js
A guide to building Al Agents using LLMs and Node.js.
Developer Learning Exercises
How to get started with large language models and Node.js
Learn how to access a large language model using Node.js and LangChain.js....
Diving Deeper with large language models and Node.js
In this learning path we dig deeper into using large language models (LLMs)...
Deploying your LangChain.js Node.js applications to OpenShift AI
This learning exercise will deploy an existing Node.js application based on...
Red Hat's products for Al
RHEL AI
RHEL AI is a foundational model platform to seamlessly develop, deploy, and run open source Granite generative Al models to power your enterprise applications. It comes with supported InstructLab, indemnified Granite language & code models, image mode for RHEL and VLLM, DeepSpeed and Pytorch support.
Podman Desktop Al Lab Extension
The Podman Desktop Al Lab Extension enables developers to run Al Models locally so that these models can be integrated into applications. It features a recipes catalog with a rich collection of examples, a catalog to download or import models and playground to quickly try out the models.
Red Hat OpenShift Al
Red Hat OpenShift Al is an artificial intelligence platform that runs on top of Red Hat OpenShift and provides tools across the AI/ML lifecycle to develop, train, serve, and monitor machine learning models on-site, in the public cloud, or at the edge.
