novel VS ai

novel editor based on TipTap

The difference is I am gonna let users write notion like documents and then share it, unlike pastebin which only lets us share text. For writing documents, I'm gonna use Novel.sh. It is a WYSIWYG editor which provides interface and features similar to Notion. It also lets us use OpenAI API to integrate AI into it.

Probably tiptap.dev, here's a notion-like editor built with it: https://github.com/steven-tey/novel

I love the simplicity of it tbh, the homepage with it's builtin demo is just superb.

https://novel.sh/

Write ++ after the npm install or whatever, the homepage is an editable demo of the editor.

Tiptap is incredible! Built https://novel.sh/ with it and the extensiveness & API is chefs kiss! So proud of you guys and the YC funding is truly well-deserved! Congrats again!

Great guide. One thing that seems to be missing is something I see in a lot of README's: a list of the core tech stack being used in the repo. Good examples here https://github.com/undb-xyz/undb#-tech-stack and here https://github.com/steven-tey/novel#tech-stack. Did you already consider adding this as part of the guide and decide against it, or was it just not something you thought to add?

I'm trying to customize https://github.com/steven-tey/novel 's amazing template. but currently output stream comes in plain text. and even it gives markdown or HTML code the text editor doesn't render them accordingly.

The Vercel AI SDK is built for OpenAI APIs and includes a range of tools for utilizing OpenAI APIs.

The AI is calling a function (https://platform.openai.com/docs/guides/function-calling) that is mapped to developer-controlled logic. The easiest thing to do is render specific UIs for every function call, but you can render however you'd like.

We kept the code snippets in the blog post brief, but you can see the full code for the demo here: https://github.com/vercel/ai/tree/main/examples/next-ai-rsc

In this blog post, we'll build a Next.js chatbot that runs on your computer. We'll use Ollama to serve the OpenHermes 2.5 Mistral LLM (large language model) locally, the Vercel AI SDK to handle stream forwarding and rendering, and ModelFusion to integrate Ollama with the Vercel AI SDK. The chatbot will be able to generate responses to user messages in real-time.

I recently set up the Next-Langchain-starter from Vercel, and it is phenomenal: Easy to setup, easy to modify. So far I've only done a few modifications:

Vercel AI SDK Playground Documentation

I used infrastructure as code (IaC) to provision and deploy Vercel's next-openai example. IaC is useful because it applies the same rigor of application code development to infrastructure provisioning. Instead of manual point and click in a cloud console which can be unrepeatable or error-prone, you just store and change all infrastructure configurations as code in source control .

You can use LLM providers other than hugging face such as Anthropic, Langchain adn OpenAI as well. Follow this doc to change the route handler(/api/chat/route.ts) and refer to the section of your chosen LLM provider.

**References: If you got stuck anywhere feel free to reach out. The Vercel documentation is excellent and the Github repo is also easily clonable if you don't have time to code from the start and just want to get stuck in customising.