Write in a blazingly fast WYSIWYG editor with 30+ custom blocks and native markdown to create built-in diagrams, API docs, Swagger, GraphQL. Check the out of the box integrations with Github, Slack, Lucidchart, Airtable, Google Sheets, Typeform, Jira, or Figma. Inline comments for async collaboration and to enhance team performance or minimize knowledge churn are supported by Archbee's collaborative features.
Based on our record, Jupyter seems to be a lot more popular than Archbee.io. While we know about 216 links to Jupyter, we've tracked only 21 mentions of Archbee.io. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Showcase and share: Easily embed UIs in Jupyter Notebook, Google Colab or share them on Hugging Face using a public link. - Source: dev.to / 2 months ago
LangChain wasn’t designed in isolation — it was built in the data pipeline world, where every data engineer’s tool of choice was Jupyter Notebooks. Jupyter was an innovative tool, making pipeline programming easy to experiment with, iterate on, and debug. It was a perfect fit for machine learning workflows, where you preprocess data, train models, analyze outputs, and fine-tune parameters — all in a structured,... - Source: dev.to / 3 months ago
Leverage versatile resources to prototype and refine your ideas, such as Jupyter Notebooks for rapid iterations, Google Colabs for cloud-based experimentation, OpenAI’s API Playground for testing and fine-tuning prompts, and Anthropic's Prompt Engineering Library for inspiration and guidance on advanced prompting techniques. For frontend experimentation, tools like v0 are invaluable, providing a seamless way to... - Source: dev.to / 4 months ago
Lately I've been working on Langgraph4J which is a Java implementation of the more famous Langgraph.js which is a Javascript library used to create agent and multi-agent workflows by Langchain. Interesting note is that [Langchain.js] uses Javascript Jupyter notebooks powered by a DENO Jupiter Kernel to implement and document How-Tos. So, I faced a dilemma on how to use (or possibly simulate) the same approach in... - Source: dev.to / 9 months ago
One of the most convenient ways to play with datasets is to utilize Jupyter. If you are not familiar with this tool, do not worry. I will show how to use it to solve our problem. For local experiments, I like to use DataSpell by JetBrains, but there are services available online and for free. One of the most well-known services among data scientists is Kaggle. However, their notebooks don't allow you to make... - Source: dev.to / 11 months ago
If you have a tech business, you should look into an internal knowledge base that is aligned with developers. archbee.com is similar to document360, but with features that are relevant to write developer documentation, APIs etc. Source: almost 3 years ago
But if you want something similar with your example, check archbee.com, it has integration with GraphiQL. Source: almost 3 years ago
If you want to get a tool and don't need to start building your own setup I would recommend looking into some documentation platforms like archbee.io. Source: almost 3 years ago
If you want to go with a SaaS, I'd say to check archbee.io - because you can do end user guides and developer documentation... Source: almost 3 years ago
It's hard to enforce developers to update documentation. Ideally, you should have somebody responsible to do it. As for the documentation stack, archbee.io for both internal and external. A good alternative to Notion since it supports markdown, code blocks with more options and API references. Source: almost 3 years ago
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