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Building with AI gets easier every day. Here is an open-source library that makes integrating AI into an application extremely easy: Star the repository! This library alone can make React the best front-end framework out there! There are a bunch of cool things I like about CopilotKit. Here are... 3 of them: 1. It allows you to take any -powered agent and bring it into your application. (This is a brand-new feature!) 2. You can build an AI-powered chatbot in your application. The chatbot will have access to your context and can act on the application. 3. You can build a RAG workflow to process and answer questions from a real-time knowledge base. I recorded a video to show you how simple it is to make some of this happen. A few lines of code, and you are in business. Here is a link to the sample application: CopilotKit is open-source. You can self-host it. You can use it with any LLM. Thanks to the team for showing me their tool and collaborating with me on this post!show more

Santiago

452,940 subscribers

108,835 görüntüleme • 2 yıl önce •via X (Twitter)

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Hamid R. Darabi profil fotoğrafı

Hamid R. Darabi2 yıl önce

AI integration's as simple as a walk in the park these days. This library's a treasure trove for React devotees. It's like finding the last piece of the puzzle to make React the undisputed king of front-end frameworks!

Chase Stone profil fotoğrafı

Chase Stone2 yıl önce

Agreed it is getting more and more easier

Cosmic AI Explorer profil fotoğrafı

Cosmic AI Explorer2 yıl önce

I have to bookmark all of your tweets since they are very informative. Thanks for sharing the knowledge and experience!

Romee Panchal profil fotoğrafı

Romee Panchal2 yıl önce

Thanks for the share! CopilotKit seems like a game-changer for integrating AI seamlessly into applications. Excited to explore its features.

_stardust_driver_ profil fotoğrafı

_stardust_driver_2 yıl önce

It's just a cakewalk. Great library 👍🏻

flukeohms7 profil fotoğrafı

flukeohms72 yıl önce

React... yay!

Uli 🪁 profil fotoğrafı

Uli 🪁2 yıl önce

Thanks for sharing this with your audience Santiago. I think they will love CopilotKit.

Bonnie profil fotoğrafı

Bonnie2 yıl önce

Thanks for sharing this, Santiago. I have been working with CopilotKit for a while and I feel it is the future of web development.

Elias profil fotoğrafı

Elias2 yıl önce

@rattibha

CopilotKit🪁 profil fotoğrafı

CopilotKit🪁2 yıl önce

Thanks for posting about us Santiago! It's our mission to help any developer build a top-tier Copilot into their product. Follow our page to stay up to date!

Benzer Videolar

Here is how simple it is to build a UI front-end for an AI agent (assuming you are using . The video here is 90 seconds and will show you everything you need to connect an agent to a web app: 1. Set up CopilotKit🪁 in your app 1. Copy the agent's localhost URL from LangGraph Studio 2. Paste that URL into a CopilotKit🪁 remote endpoint That's all you need to get a front-end to interact with the agent! The secret sauce here is CoAgents, an open-source library. You can use CoAgents to integrate any agent with your web application. Here is what you get: • Human-in-the-loop to steer and correct the agent • Stream intermediate agent state • Real-time state sharing between the agent and the application • Agentic generative UI to build trust that the agent is on the right path Watch the attached demo so you see it in action.

Here is how simple it is to build a UI front-end for an AI agent (assuming you are using . The video here is 90 seconds and will show you everything you need to connect an agent to a web app: 1. Set up CopilotKit🪁 in your app 1. Copy the agent's localhost URL from LangGraph Studio 2. Paste that URL into a CopilotKit🪁 remote endpoint That's all you need to get a front-end to interact with the agent! The secret sauce here is CoAgents, an open-source library. You can use CoAgents to integrate any agent with your web application. Here is what you get: • Human-in-the-loop to steer and correct the agent • Stream intermediate agent state • Real-time state sharing between the agent and the application • Agentic generative UI to build trust that the agent is on the right path Watch the attached demo so you see it in action.

Santiago

46,142 görüntüleme • 1 yıl önce

Knowledge graphs for representing information are unbeatable. After this, you will never build a RAG system without knowledge graphs. It will take you five lines of code to build a knowledge graph with your data. I recorded a video to show you how you can do this. I used Cognee, an open-source library that outperforms any basic vector search approach in terms of retrieval relevance. They are collaborating with me on this post. Cognee is: • Easy to use • Reduces hallucinations • Open-source Here is a link to the repository: They also offer a comprehensive platform and UI with Python notebooks you can utilize to manage your data. Here is the link:

Knowledge graphs for representing information are unbeatable. After this, you will never build a RAG system without knowledge graphs. It will take you five lines of code to build a knowledge graph with your data. I recorded a video to show you how you can do this. I used Cognee, an open-source library that outperforms any basic vector search approach in terms of retrieval relevance. They are collaborating with me on this post. Cognee is: • Easy to use • Reduces hallucinations • Open-source Here is a link to the repository: They also offer a comprehensive platform and UI with Python notebooks you can utilize to manage your data. Here is the link:

Santiago

126,559 görüntüleme • 11 ay önce

Imagine an AI application that can type anywhere you can and use the full context of what's on your screen. This is the application we all deserve (at least if you have macOS.) Check out Omnipilot. It's an app that works with every other macOS application and uses Claude Sonet 3.5 in the background—it also supports Gemini and GPT-4o. Here is the idea: You can use the tool to ask questions about anything on your screen. Or you can use it to autocomplete the text you are typing. You don't need to copy and paste anymore or waste your time providing context to a model. It sees what you see. It works right where you are. That's pretty cool. Here are a couple of cool examples: • Use it to reply to an email • Use it in the terminal to autocomplete a command • Use it to finish a document • Use to send a message on Slack AI at the system level is bonkers. You can read a ton more on their Product Hunt launch page: Thanks to the Omnipilot team for collaborating with me on this post!

Imagine an AI application that can type anywhere you can and use the full context of what's on your screen. This is the application we all deserve (at least if you have macOS.) Check out Omnipilot. It's an app that works with every other macOS application and uses Claude Sonet 3.5 in the background—it also supports Gemini and GPT-4o. Here is the idea: You can use the tool to ask questions about anything on your screen. Or you can use it to autocomplete the text you are typing. You don't need to copy and paste anymore or waste your time providing context to a model. It sees what you see. It works right where you are. That's pretty cool. Here are a couple of cool examples: • Use it to reply to an email • Use it in the terminal to autocomplete a command • Use it to finish a document • Use to send a message on Slack AI at the system level is bonkers. You can read a ton more on their Product Hunt launch page: Thanks to the Omnipilot team for collaborating with me on this post!

Santiago

72,306 görüntüleme • 2 yıl önce

You can now connect your React application to any MCP server! And it only takes a single command: $ npx copilotkit@latest init -m MCP This is massive for anyone building React applications! Using the CopilotKit🪁 MCP Client Component, you can get an MCP Client chat component in your application and instant access to any MCP server out there! It doesn't get easier than this. Check out the link below for instructions on how to proceed ↓

You can now connect your React application to any MCP server! And it only takes a single command: $ npx copilotkit@latest init -m MCP This is massive for anyone building React applications! Using the CopilotKit🪁 MCP Client Component, you can get an MCP Client chat component in your application and instant access to any MCP server out there! It doesn't get easier than this. Check out the link below for instructions on how to proceed ↓

Santiago

39,944 görüntüleme • 1 yıl önce

Tune Studio is an end-to-end platform for developing applications using Large Language Models. So far, I haven't seen any other platform like this one. You can do everything here: 1. You can curate your data. 2. Use the playground to play with different models and try your ideas. 3. Fine-tune an open-source model on your data. 4. Deploy the model when you are done. This is awesome for anyone building generative AI applications. You can use Tune Studio to work with any of the open-source models out there. They were one of the few companies to host Llama 2 and Llama 3 before anyone else. Here is a link to check it out: One of their main selling points is that Tune Studio scales! You don't have to worry about serving your model to lots of users. They also have built-in user management, authentication, on-prem support, user context management, and pretty much everything you need to build generative AI applications. Thanks to the Tune team for collaborating with me on this post. We are living through the best years of development tools for AI developers. The field is unstoppable.

Tune Studio is an end-to-end platform for developing applications using Large Language Models. So far, I haven't seen any other platform like this one. You can do everything here: 1. You can curate your data. 2. Use the playground to play with different models and try your ideas. 3. Fine-tune an open-source model on your data. 4. Deploy the model when you are done. This is awesome for anyone building generative AI applications. You can use Tune Studio to work with any of the open-source models out there. They were one of the few companies to host Llama 2 and Llama 3 before anyone else. Here is a link to check it out: One of their main selling points is that Tune Studio scales! You don't have to worry about serving your model to lots of users. They also have built-in user management, authentication, on-prem support, user context management, and pretty much everything you need to build generative AI applications. Thanks to the Tune team for collaborating with me on this post. We are living through the best years of development tools for AI developers. The field is unstoppable.

Santiago

39,101 görüntüleme • 2 yıl önce

Watch me build an end-to-end RAG application to answer questions from a website in 7 minutes. 7 minutes! That's how good tools have gotten! I'm using Vext, a platform for building and deploying an LLM application in minutes. They take care of everything behind the scenes and provide an API endpoint you can call. It doesn't get more simple than this. This was science fiction a couple of years ago. Now, everyone can build like this. You can do this for free: Thanks to the team at Vext for helping me understand their platform and collaborate with me on this post.

Watch me build an end-to-end RAG application to answer questions from a website in 7 minutes. 7 minutes! That's how good tools have gotten! I'm using Vext, a platform for building and deploying an LLM application in minutes. They take care of everything behind the scenes and provide an API endpoint you can call. It doesn't get more simple than this. This was science fiction a couple of years ago. Now, everyone can build like this. You can do this for free: Thanks to the team at Vext for helping me understand their platform and collaborate with me on this post.

Santiago

108,933 görüntüleme • 2 yıl önce

I recorded a video on how you can build a complete RAG application without writing any code. I used Langflow, an open-source project that sits on top of Langchain. Langflow hides all the complexity and makes the process 10x easier. This is a step-by-step tutorial.

I recorded a video on how you can build a complete RAG application without writing any code. I used Langflow, an open-source project that sits on top of Langchain. Langflow hides all the complexity and makes the process 10x easier. This is a step-by-step tutorial.

Santiago

96,267 görüntüleme • 2 yıl önce

Forget about HTML, JavaScript, and CSS. You can build AI and data applications using Python alone! Python is the best programming language out there. You can now use it across the stack. Take a look at Taipy, an open-source Python library to build end-to-end production applications. Star their repository: I recorded a quick video showing how to build a simple chat interface to talk to OpenAI GPT-3.5 using Taipy alone. Something important to keep in mind: Taipy's goal is not to replace web developers but to provide an alternative to those who need to build applications without web experience. If you are a data scientist or someone dealing with data, Taipy will simplify your life considerably. Thanks to the team behind Taipy for collaborating with me on this post. Here is a link to the full demo. Download this code and run it. It takes 30 seconds:

Forget about HTML, JavaScript, and CSS. You can build AI and data applications using Python alone! Python is the best programming language out there. You can now use it across the stack. Take a look at Taipy, an open-source Python library to build end-to-end production applications. Star their repository: I recorded a quick video showing how to build a simple chat interface to talk to OpenAI GPT-3.5 using Taipy alone. Something important to keep in mind: Taipy's goal is not to replace web developers but to provide an alternative to those who need to build applications without web experience. If you are a data scientist or someone dealing with data, Taipy will simplify your life considerably. Thanks to the team behind Taipy for collaborating with me on this post. Here is a link to the full demo. Download this code and run it. It takes 30 seconds:

Santiago

233,921 görüntüleme • 2 yıl önce

99% of AI applications are cool-looking demos. Impressive, but don't get fooled by the hype. It takes a lot to build enterprise-grade products that deliver real value. I have at least three weekly conversations with companies that want to use a Large Language Model with their data. The demand is huge! Here is one idea about what you can do to help. The use cases that most of these companies want to solve are similar: They have an extensive knowledge base and want to build a simple application that uses that information to answer questions. In other words, they need help building Retrieval Augmented Generation (RAG) applications they can use in many different scenarios: 1. To train new employees 2. To help their support team 3. To search old meetings and documents 4. To help with their research However, building these systems is not straightforward. Yes, there's a lot of information online, but there aren't enough people who know how to create solutions that work. Here is the idea: Today, you can build an enterprise-grade RAG application without writing code. A couple of MIT PhDs with 10+ years of experience building AI applications created . It's a no-code platform for building applications using Large Language Models. They are partnering with me on this post. You can use Stack AI to create, test, and deploy an end-to-end production-ready AI system. It's SOC-2, HIPAA, and GDPR compliant and offers SSO, role management, access control, and on-premise deployments. Of course, you can use the platform with any LLM on the market now. It's the whole nine yards for building AI applications. Check them out here: 2023 was about models. 2024 is about the tools using these models to build production-ready applications. That's where I'd start.

99% of AI applications are cool-looking demos. Impressive, but don't get fooled by the hype. It takes a lot to build enterprise-grade products that deliver real value. I have at least three weekly conversations with companies that want to use a Large Language Model with their data. The demand is huge! Here is one idea about what you can do to help. The use cases that most of these companies want to solve are similar: They have an extensive knowledge base and want to build a simple application that uses that information to answer questions. In other words, they need help building Retrieval Augmented Generation (RAG) applications they can use in many different scenarios: 1. To train new employees 2. To help their support team 3. To search old meetings and documents 4. To help with their research However, building these systems is not straightforward. Yes, there's a lot of information online, but there aren't enough people who know how to create solutions that work. Here is the idea: Today, you can build an enterprise-grade RAG application without writing code. A couple of MIT PhDs with 10+ years of experience building AI applications created . It's a no-code platform for building applications using Large Language Models. They are partnering with me on this post. You can use Stack AI to create, test, and deploy an end-to-end production-ready AI system. It's SOC-2, HIPAA, and GDPR compliant and offers SSO, role management, access control, and on-premise deployments. Of course, you can use the platform with any LLM on the market now. It's the whole nine yards for building AI applications. Check them out here: 2023 was about models. 2024 is about the tools using these models to build production-ready applications. That's where I'd start.

Santiago

197,702 görüntüleme • 2 yıl önce

It takes 5 minutes to create a world-class web research agent that runs 24/7 and returns structured search results. 1. You can limit the sources it's allowed to use 2. You can specify the goals it needs to complete 3. You can design the format structure of the results 4. You can configure how much computing power it will use I show you how to set up a Web Search Agent in the video. A few benefits here: 1. This is great for complex research tasks 2. It's really easy to add this like a LEGO piece to a more complex workflow 3. Create an agent once, and reuse it with different inputs 4. The agent adapts to your use case as you work with it By the way, Nimble published a whole library of templates and research agents you can reuse and modify. You can start sending queries to one of these existing agents, and it will begin to adapt to Go here to try it out: Thanks to the Nimble team for partnering with me on this post.

It takes 5 minutes to create a world-class web research agent that runs 24/7 and returns structured search results. 1. You can limit the sources it's allowed to use 2. You can specify the goals it needs to complete 3. You can design the format structure of the results 4. You can configure how much computing power it will use I show you how to set up a Web Search Agent in the video. A few benefits here: 1. This is great for complex research tasks 2. It's really easy to add this like a LEGO piece to a more complex workflow 3. Create an agent once, and reuse it with different inputs 4. The agent adapts to your use case as you work with it By the way, Nimble published a whole library of templates and research agents you can reuse and modify. You can start sending queries to one of these existing agents, and it will begin to adapt to Go here to try it out: Thanks to the Nimble team for partnering with me on this post.

Santiago

21,079 görüntüleme • 1 ay önce

THIS IS WHAT AI PENTESTING SHOULD LOOK LIKE IN 2026 Someone built Shannon, an open source AI pentesting tool that doesn’t just scan your app from the outside. It reads the source code. Then it uses AI to map potential attack paths, identify vulnerabilities, and test the application before you ship it. The workflow is basically: → point Shannon at your code → connect your Claude API → let it analyze the application → get the findings in a dashboard Instead of waiting for a security team to manually hunt through every part of your codebase, you can have an AI security researcher working through it automatically. And because it’s white-box, it can see things traditional scanners can’t. This is where AI + cybersecurity gets REALLY interesting. Just use it on systems you own or have explicit permission to test. REPO BELOW

THIS IS WHAT AI PENTESTING SHOULD LOOK LIKE IN 2026 Someone built Shannon, an open source AI pentesting tool that doesn’t just scan your app from the outside. It reads the source code. Then it uses AI to map potential attack paths, identify vulnerabilities, and test the application before you ship it. The workflow is basically: → point Shannon at your code → connect your Claude API → let it analyze the application → get the findings in a dashboard Instead of waiting for a security team to manually hunt through every part of your codebase, you can have an AI security researcher working through it automatically. And because it’s white-box, it can see things traditional scanners can’t. This is where AI + cybersecurity gets REALLY interesting. Just use it on systems you own or have explicit permission to test. REPO BELOW

MAX

13,076 görüntüleme • 21 gün önce

If you’ve never written code before, this is for you. I’ve just launched a course that shows you, in less than 30 minutes, how to describe an idea for an app and build it with AI. In this course, you'll build a working web application - a funny interactive birthday message generator that runs in your browser and can be shared with friends. You'll customize it by telling AI how you want it changed, and tweak it until it works the way you want. By the end, you'll have a repeatable process you can apply to build a wide variety of applications. If you want to try vibe coding, this will be the best place to start! Further, you'll be able to use these techniques with whatever tool you're most comfortable with (like ChatGPT, Gemini, Claude, or others) -- we're vendor neutral. Skills you'll gain: - How to build web apps with AI - zero coding skills needed - How to fix and improve your creations by chatting with AI - A simple process you can use to build other things you can dream up Building with AI is one of the most fun things in the world. Please join me and take your first step! I think you will be surprised at what you can build. And if you're an experienced engineer, please share this with someone in your life who's been curious about building with AI. Come build with me!

If you’ve never written code before, this is for you. I’ve just launched a course that shows you, in less than 30 minutes, how to describe an idea for an app and build it with AI. In this course, you'll build a working web application - a funny interactive birthday message generator that runs in your browser and can be shared with friends. You'll customize it by telling AI how you want it changed, and tweak it until it works the way you want. By the end, you'll have a repeatable process you can apply to build a wide variety of applications. If you want to try vibe coding, this will be the best place to start! Further, you'll be able to use these techniques with whatever tool you're most comfortable with (like ChatGPT, Gemini, Claude, or others) -- we're vendor neutral. Skills you'll gain: - How to build web apps with AI - zero coding skills needed - How to fix and improve your creations by chatting with AI - A simple process you can use to build other things you can dream up Building with AI is one of the most fun things in the world. Please join me and take your first step! I think you will be surprised at what you can build. And if you're an experienced engineer, please share this with someone in your life who's been curious about building with AI. Come build with me!

Andrew Ng

637,344 görüntüleme • 8 ay önce

Web scraping is a critical skill, and yet nobody talks about it. How do you think companies are training their Large Language Models? Where do you think the data comes from? But web scraping goes beyond all of that. Imagine giving an AI agent access to any public online data in real time! I like to call this "web-scrapping on demand", and I'm pretty sure it's going to unlock unlimited power for AI applications. I recorded a quick video to show you how you can do this using Apify. I've talked about them before, and they are collaborating with me on this post. They have one of the best open-source web scraping and browser automation libraries out there: But it gets much better than this! You can use MCP to connect your AI Agents and applications to the Apify platform and use any specialized actor on demand to scrape and process online data. In the video, I used Cursor to scrape LinkedIn posts with the words "Machine Learning" in real time. Worked like a charm with no code needed! Here is a link to the platform: Think about this: You can now feed your AI applications with any public data on demand! We aren't ready for what's coming.

Web scraping is a critical skill, and yet nobody talks about it. How do you think companies are training their Large Language Models? Where do you think the data comes from? But web scraping goes beyond all of that. Imagine giving an AI agent access to any public online data in real time! I like to call this "web-scrapping on demand", and I'm pretty sure it's going to unlock unlimited power for AI applications. I recorded a quick video to show you how you can do this using Apify. I've talked about them before, and they are collaborating with me on this post. They have one of the best open-source web scraping and browser automation libraries out there: But it gets much better than this! You can use MCP to connect your AI Agents and applications to the Apify platform and use any specialized actor on demand to scrape and process online data. In the video, I used Cursor to scrape LinkedIn posts with the words "Machine Learning" in real time. Worked like a charm with no code needed! Here is a link to the platform: Think about this: You can now feed your AI applications with any public data on demand! We aren't ready for what's coming.

Santiago

101,473 görüntüleme • 1 yıl önce

THIS IS A FREKING GOOD APPLICATION!!! You can create your own systems to simulate how the database would react to different numbers of requests, and you can play around with it to get an idea of how things actually work under the hood. Crazy product, I loved it xevrion Try it out:

THIS IS A FREKING GOOD APPLICATION!!! You can create your own systems to simulate how the database would react to different numbers of requests, and you can play around with it to get an idea of how things actually work under the hood. Crazy product, I loved it xevrion Try it out:

Ojas Sharma

194,034 görüntüleme • 22 gün önce