Robert Kim’s Post

Creating a beautiful terminal application, GUI, or CLI is good, but capturing a high-fidelity demo of it is even better. You may have used asciinema or screen in the past, but I'm always surprised how few folks know about VHS. VHS is an open-source tool that allows you to write terminal GIFs as code for seamless integration testing and stunning demos. With VHS, you can create pixel-perfect recordings of your CLI tools in action, making it easier than ever to showcase your work. 🎬💻 One of the standout features of VHS is its intuitive and expressive syntax. You define your recordings using a simple yet powerful .tape file format, specifying commands, typing actions, and custom settings like font size, window dimensions, and themes. It's like having a virtual director for your terminal demos! 🎨🎛️ You can also record your actions in the terminal and have your .tape file generated. Removing typos or awkwardness is as simple as editing your .tape file and regenerating your gif. VHS allows you to output in multiple formats, including .mp4 and .gif, even simultaneously. This means you can wire VHS up to your CI/CD process to get excellent recordings or create build artifacts to review as sanity checks that everything is working properly. VHS also offers a wide range of commands to enhance your recordings. You can simulate typing with the Type command, navigate with arrow keys, use special keys like Enter and Tab, and even incorporate dramatic pauses with the Sleep command. VHS provides a built-in SSH server, allowing you to access VHS remotely and leverage the host's commands and applications. You can create demos on your machine and seamlessly share them with others. 🌐🔑 Integration with continuous integration pipelines is a breeze with VHS. You can keep your GIFs up-to-date using the official VHS GitHub Action, ensuring that your demos always reflect the latest changes in your codebase. 🔄✅ VHS is your tool if you want to take your terminal demos to the next level. It's open-source, extensively documented, and supported by a vibrant community. Try it and experience the magic of creating stunning terminal recordings with ease! ✨💻 And be sure to follow me and subscribe to my newsletter for more tips and open-source tool spotlights like this!

Cody is an AI tool that can help you analyze & fix issues in your code. It gets info from the whole codebase, references docs, and can give you key info about functions & variables. Here, Ekemini explains how to use Cody to design & build UI components. https://lnkd.in/gf-qWcxz

Curious to see what Builder.io is up to with their "Figma-to-code launch: Visual Copilot, our new AI-powered, Figma-to-code capability, will let you generate clean, accessible, near-production-ready code that uses your components."

German AI innovator Black Forest Labs has unveiled its new open-source AI model, FLUX.1, which significantly outperforms Midjourney.  https://lnkd.in/eg9eiz-f Key Highlights: Origin: The team behind Black Forest Labs, including pioneers like Robin Rombach, Andreas Blattmann, and Dominik Lorenz, previously spearheaded the Stable Diffusion project at Stability AI before their recent departure. Product Launch: The debut product, FLUX.1, utilizes a hybrid architecture combining transformers and diffusion techniques. It is available in three variants: Flux 1 Pro: API Access. https://docs.bfl.ml/ Flux 1 Dev: Open weight, non-commercial license Flux 1 Schnell: Efficient, 4-step diffusion model, open-source under Apache 2 license Performance: FLUX.1 exhibits superior image quality, particularly in rendering human hands—a noted challenge for earlier models like Stable Diffusion 1.5. Funding and Advisers: The launch coincided with a $31 million Series Seed funding round led by Andreessen Horowitz, and high-profile advisers including former Disney President Michael Ovitz and AI researcher Matthias Bethge. Future Plans: While currently focused on text-to-image generation, Black Forest Labs intends to expand into video generation, positioning itself against major players like OpenAI’s Sora, Runway’s Gen-3 Alpha, and Kuaishou’s Kling. This rapid development and impressive launch illustrate the dynamic pace of innovation in the AI sector, highlighting a significant advancement in the open-source AI ecosystem following the fallout at Stability AI.

📣 Meet Vaadin Copilot - your #AI-powered UI development assistant! Build UIs that delight end users faster, smarter, and more intuitively with Vaadin Copilot, featuring: 🔹 Advanced visual editing tools 🔹 AI assistance 🔹 Seamless IDE integration 🔹 Support for Hilla + React Vaadin Flow support coming soon. Try it now 👉 https://bit.ly/3VgXMOq #Vaadin #Copilot #AI #WebDevelopment #Java #UIDevelopment #Hilla #React

How to run AI Models Locally ⚡️👇 1) Ollama: Its an amazing package to chat with all AI Models locally. Simply install ollama and write "ollama run <model name>" and thats it 2) LM Studio: If you want to use everything with the help of UI, use this, Download and just use it. 3) Hugging Face: Developer? Use this, 6 lines of code and thats it. Any model, up and running If you like content on Tech, do follow Paras Madan as I make 20 content pieces a month to help you out.

This short course, led by Apolinário Passos from Hugging Face, teaches how to create and demo machine learning applications quickly using Gradio. If you're working with generative models, Gradio is a fantastic option for building and sharing your app's UI in just a few minutes. The course takes less than an hour and it's a great tool if you want to share your app with teammates or beta testers.

🌟 Exciting News! 🌟 I'm thrilled to share my latest video: "OpenUI - Build Entire Frontends with a Text Prompt in Seconds!!" Check it out here: https://lnkd.in/gzzX9Eh7 Don't miss out! Like, comment, and share to spread the word! Let's revolutionize human-machine interaction together! Please subscribe to my channel #OpenUI #BuildwebsitesUsingAI #TexttoFrontend #BuildUI with AI Models #LLM #GPT-4 Turbo #Ollama #GPT-3.5 Turbo Models

GPT-4 with Vision can accelerate the transformation of mockups into code. I still can’t believe this is possible and wanted to share my initial impressions about what I learned building a GPT-4V solution on prototypr.ai. ——— But first, what is GPT-4V? GPT-4 with Vision is a multi-modal OpenAI model that can help you understand the content of an image, and then take action on this data in the form of a prompt. These actions can include asking the model questions such as ‘what is in this image’ and then using the answer the model provides to perform a specific task. ——— What GPT-4V use case am I exploring? I’m currently using GPT-4V as an alternate way to start the prototyping process and enhance my workflow. In the video below, I provide the model with a simple sketch of a dashboard and the model outputs a first draft of the UI that I can subsquently build on and polish up. ——— So what did I learn on my GPT-4V travels? Here are 4 key takeaways: --- 1. Descriptions of images are on point and incredibly accurate. This was way better than I imagined. Just seeing how GPT-4V describes a hand drawn dashboard was really eye opening. It was so accurate, that I wasn’t surprised it could then turn my image into code. --- 2. The output of code from a mockup is very good and offers a great starting point for a prototype. I’m still in awe about this, but the fact that you can take a sketch or a screenshot and output a coded prototype is remarkable. From my early experiments with getting the vision model to output specific charts using ChartJS, I found it worked quite well as the charts actually rendered on the screen! --- 3. Workflows and productivity can be enhanced with GPT-4V. Lately, when building user experiences, I’ve been thinking about what is more efficient. Should I draw or describe a user experience with text in order to get that first draft codified. GPT-4V has me re-thinking my prototyping workflow, which is why I’m offering it as an option for customers. I’ve also been thinking about how multi-modal models like GPT-4V can help capture and synthesize information as part of a brainstorming session. At the end of a meeting, one could simply snap and upload a picture (or a series of pictures) to the model and ask it to summarize the session, offering up key take aways and opportunities with the appropriate context. It definitely feels like there is something there. --- 4. Latency is still top of mind when using GPT-4V I imagine this will improve over time, but currently it can take around 30 seconds or so to convert an image to a prototype, which is a bit of a subpar user experience. But, I’m hoping that there will be a fine tuning solution sometime in the future where this speed issue could be addressed. ——— So, that’s my adventure with GPT-4V! If you have any comments or feedback, I’d love to hear it. Thanks for reading! YT Video: https://lnkd.in/gvVz8KZG #gpt4v #multimodal #ai #prototyping

Want to clone your favorite landing page design? Claude's new Artifacts feature lets you turn screenshots into code in < 5 minutes. Here's a step-by-step tutorial: --- And if you like carousels like this: Follow me Ben Tossell for tips and tutorials on how to use AI to work smarter, not harder.