I have been building tons of applications. My latest one is Gitroom. It helps you to: Schedule your posts on multiple social media platforms and cross-post them to publishing platforms such as DEV, Medium, and Hashnode.
Track your GitHub repository metrics.
Monitor GitHub trendings (it's open-sourced 🙏🏻)That's nice and all, but here is the real kicker. Add AI to your application. I see tons of AI libraries every day, and most of them are really cool, but I ask myself, will they help me in real life? Yes, babyagi might be the next big thing. But honestly, I don't see anything I can do with it. So what can you do with AI, and what do people usually do? I think in today's ChatGPT world and local LLMs, the use case is pretty simple: Auto-complete content - perfect for Gitroom to let you generate additional information or use something like GitHub copilot.


Automation - You pass content to the LLM, which returns a JSON with operations you can perform.


Function calling - Mostly with ChatGPT, you pass different functions to the LLM, and they decide which one to run.


Miscellaneous - Classification, translation, etc. I think "function calling" is not leveraged enough because adding it in a way that makes sense is complex. Help your users with everything. I admit I love to build stuff, but I sometimes skip developing a good UX, which causes people to leave the system because they don't know what to do. I think inherently, if you build systems for developers, you can get away with it - because they are more sophisticated. But that is mostly not the case. You should have: Onboardings
Tutorials
YouTube videos (inside your system, yes, yes) This is where AI can save you without writing too much code. Add a chatbot that can do everything for you. So, one of the things more and more companies offer is a chatbot that can interact with your data and perform actions for the user. For example, I can tell the chatbot I want to schedule a new post for Gitroom at 7:00 p.m. US time. And it will do it for me. The problem with most of the solutions I found is that they are: Not open-source
It is not an infrastructure product but a complete product that is mainly for product managers. CopilotKit can help you. So, I found this incredible open-source library licensed under MIT - which is fantastic. It's just a chatbot sitting on your right sidebar. You feed it with: Your current context information.
Your data resources, such as your database, dropbox, Google Drive, etc.
Different functions in the system can be called. Once you have finished doing that, it's just like magic. Does somebody want to schedule a post? It will trigger the schedulePost function. Of course, it uses the ChatGPT "function calling" in the background, but it simplifies everything. I think it fits any app. You can use it with big LLMs like ChatGPT / Gemini, but also with smaller ones like LLAMA2 and Mistral. Check out CopilotKit I started a new YouTube channel mostly about Tech, open-source, and marketing :) If that's something that interests you, feel free to subscribe to it here: https://www.youtube.com/@nevo-david Also published here. I have been building tons of applications. My latest one is Gitroom . It helps you to: Gitroom Schedule your posts on multiple social media platforms and cross-post them to publishing platforms such as DEV, Medium, and Hashnode. Track your GitHub repository metrics. Monitor GitHub trendings Schedule your posts on multiple social media platforms and cross-post them to publishing platforms such as DEV, Medium, and Hashnode. Track your GitHub repository metrics. Monitor GitHub trendings ( it's open-sourced 🙏🏻)That's nice and all, but here is the real kicker. it's open-sourced Add AI to your application. I see tons of AI libraries every day, and most of them are really cool, but I ask myself, will they help me in real life? Yes, babyagi might be the next big thing. But honestly, I don't see anything I can do with it. babyagi So what can you do with AI, and what do people usually do? I think in today's ChatGPT world and local LLMs, the use case is pretty simple: Auto-complete content - perfect for Gitroom to let you generate additional information or use something like GitHub copilot. Automation - You pass content to the LLM, which returns a JSON with operations you can perform. Function calling - Mostly with ChatGPT, you pass different functions to the LLM, and they decide which one to run. Miscellaneous - Classification, translation, etc. Auto-complete content - perfect for Gitroom to let you generate additional information or use something like GitHub copilot. Auto-complete content - perfect for Gitroom to let you generate additional information or use something like GitHub copilot. Auto-complete content Automation - You pass content to the LLM, which returns a JSON with operations you can perform. Automation - You pass content to the LLM, which returns a JSON with operations you can perform. Automation Function calling - Mostly with ChatGPT, you pass different functions to the LLM, and they decide which one to run. Function calling - Mostly with ChatGPT, you pass different functions to the LLM, and they decide which one to run. Function calling Miscellaneous - Classification, translation, etc. Miscellaneous - Classification, translation, etc. Miscellaneous I think "function calling" is not leveraged enough because adding it in a way that makes sense is complex. Help your users with everything. I admit I love to build stuff, but I sometimes skip developing a good UX, which causes people to leave the system because they don't know what to do. I think inherently, if you build systems for developers, you can get away with it - because they are more sophisticated. But that is mostly not the case. You should have: Onboardings Tutorials YouTube videos (inside your system, yes, yes) Onboardings Tutorials YouTube videos (inside your system, yes, yes) This is where AI can save you without writing too much code. Add a chatbot that can do everything for you. So, one of the things more and more companies offer is a chatbot that can interact with your data and perform actions for the user. For example, I can tell the chatbot I want to schedule a new post for Gitroom at 7:00 p.m. US time. And it will do it for me. The problem with most of the solutions I found is that they are: Not open-source It is not an infrastructure product but a complete product that is mainly for product managers. Not open-source It is not an infrastructure product but a complete product that is mainly for product managers. CopilotKit can help you. So, I found this incredible open-source library licensed under MIT - which is fantastic. open-source library It's just a chatbot sitting on your right sidebar. You feed it with: Your current context information. Your data resources, such as your database, dropbox, Google Drive, etc. Different functions in the system can be called. Your current context information. Your data resources, such as your database, dropbox, Google Drive, etc. Different functions in the system can be called. Once you have finished doing that, it's just like magic. Does somebody want to schedule a post? It will trigger the schedulePost function. Of course, it uses the ChatGPT "function calling" in the background, but it simplifies everything. schedulePost I think it fits any app. You can use it with big LLMs like ChatGPT / Gemini, but also with smaller ones like LLAMA2 and Mistral. Check out CopilotKit Check out CopilotKit I started a new YouTube channel mostly about Tech, open-source, and marketing :) If that's something that interests you, feel free to subscribe to it here: https://www.youtube.com/@nevo-david https://www.youtube.com/@nevo-david Also published here. Also published here . here

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The React AI Library Upgrade You May Have Been Looking For

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The React AI Library Upgrade You May Have Been Looking For

Too Long; Didn't Read

Nevo David

STORY’S CREDIBILITY

Guide

About Author

TOPICS

THIS ARTICLE WAS FEATURED IN...

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