Загрузка видео...

Не удалось загрузить видео

На главную

Today we’re excited to introduce GenSX, an open source TypeScript framework for building backend workflows and agents with reusable, React-like components. If you know how to write a React component, then you’ll feel right at home building agents in GenSX.

_Evan_Boyle's profile picture

Evan Boyle

7,604 subscribers

14,446 просмотров • 1 год назад •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

Introducing Agents UI, an open-source shadcn component library for building polished React frontends for your voice agents. Audio visualizers. Media controls. Session management tools. Chat transcripts. All wired to LiveKit Agents. Install via the shadcn CLI and own the code.
0:43

Introducing Agents UI, an open-source shadcn component library for building polished React frontends for your voice agents. Audio visualizers. Media controls. Session management tools. Chat transcripts. All wired to LiveKit Agents. Install via the shadcn CLI and own the code.

LiveKit

182,672 просмотров • 4 месяцев назад

- Beautiful React/NextJS components - Backend hosting for Javascript, PHP, Python, Go... - Browser API for AI agents - JSON visualizer - Open source workflow automation
0:40

- Beautiful React/NextJS components - Backend hosting for Javascript, PHP, Python, Go... - Browser API for AI agents - JSON visualizer - Open source workflow automation

Csaba Kissi

14,742 просмотров • 1 год назад

⚛️ How to type generic components in React with TypeScript ↓
0:23

⚛️ How to type generic components in React with TypeScript ↓

George Moller

94,044 просмотров • 2 лет назад

Follow this video to learn how to build a simple AI agent without writing any code. I'm using Langflow. In my opinion, it's the best tool I've found for building agents. It's open-source, comes with a huge list of reusable components, and provides an awesome experience for builders.
16:29

Follow this video to learn how to build a simple AI agent without writing any code. I'm using Langflow. In my opinion, it's the best tool I've found for building agents. It's open-source, comes with a huge list of reusable components, and provides an awesome experience for builders.

Santiago

73,897 просмотров • 1 год назад

3 months ago we started building an IDE for the AI agents era Today we’re introducing Superset: an open source app for running any agents in parallel. And today we launched Chat 😉, enabling us to build way more superpowers into how users interact with agents (@ context, link Linear tickets, / commands, etc)
2:37

3 months ago we started building an IDE for the AI agents era Today we’re introducing Superset: an open source app for running any agents in parallel. And today we launched Chat 😉, enabling us to build way more superpowers into how users interact with agents (@ context, link Linear tickets, / commands, etc)

Avi Peltz

56,584 просмотров • 4 месяцев назад

We’re excited to launch the Codex app, a command center for building with agents. It gives you a focused space to manage multiple agents at once, run work in parallel, and collaborate with agents over long-running tasks.
4:21

We’re excited to launch the Codex app, a command center for building with agents. It gives you a focused space to manage multiple agents at once, run work in parallel, and collaborate with agents over long-running tasks.

OpenAI Developers

1,303,913 просмотров • 4 месяцев назад

Multimodal Real-Time Agents will be the future! 💯 Here is an early demo from what i am currently building! It uses Live API with Google DeepMind Gemini 2.0 Flash and React. Code will be open-source soon with a blog post on how to build your own Real-Time Agents! 🚀
1:23

Multimodal Real-Time Agents will be the future! 💯 Here is an early demo from what i am currently building! It uses Live API with Google DeepMind Gemini 2.0 Flash and React. Code will be open-source soon with a blog post on how to build your own Real-Time Agents! 🚀

Philipp Schmid

27,385 просмотров • 1 год назад

we released our react package build an ai chat w/ interactive components in a few lines of code. add it to your app with: npx tambo full-send we support: - streaming for both messages and components - message history and message threads - state manage for generated components - suggested actions based on available components - component library that uses the react package the react package is open-source. server package will be open-sourced later this year.
1:01

we released our react package build an ai chat w/ interactive components in a few lines of code. add it to your app with: npx tambo full-send we support: - streaming for both messages and components - message history and message threads - state manage for generated components - suggested actions based on available components - component library that uses the react package the react package is open-source. server package will be open-sourced later this year.

Michael Magán

65,473 просмотров • 1 год назад

"How to share state between React client components with a parent server component?" 👇
0:32

"How to share state between React client components with a parent server component?" 👇

Alex Sidorenko

51,480 просмотров • 1 год назад

Today, we’re excited to announce and launch Reflex Cloud on Product Hunt! Reflex is an open-source framework for building and deploying data and AI web apps in pure Python. Frontend and Backend in Pure Python: No JavaScript required! With Reflex Cloud, you can now deploy, manage, and scale your Python apps with just a single command! If you're a Python developer, an upvote or a share would mean a lot to us :)💪❤️
3:04

Today, we’re excited to announce and launch Reflex Cloud on Product Hunt! Reflex is an open-source framework for building and deploying data and AI web apps in pure Python. Frontend and Backend in Pure Python: No JavaScript required! With Reflex Cloud, you can now deploy, manage, and scale your Python apps with just a single command! If you're a Python developer, an upvote or a share would mean a lot to us :)💪❤️

Reflex

55,024 просмотров • 1 год назад

We’re excited today to announce Mastra’s Agent Studio: an interactive interface for building and testing your Mastra agents. Now, engineers and product folks can collaborate in the same environment together:
2:07

We’re excited today to announce Mastra’s Agent Studio: an interactive interface for building and testing your Mastra agents. Now, engineers and product folks can collaborate in the same environment together:

Sam Bhagwat

22,150 просмотров • 8 месяцев назад

For a few weeks we've been building agents that are capable of understanding any app and then autonomously convert it to a React Native app. Powered by agent-device and react-native-best-practices skills from Callstack Engineers and some custom instructions DM if you're interested
1:10

For a few weeks we've been building agents that are capable of understanding any app and then autonomously convert it to a React Native app. Powered by agent-device and react-native-best-practices skills from Callstack Engineers and some custom instructions DM if you're interested

Michał Pierzchała

10,386 просмотров • 1 месяц назад

What we’re building for you and your agents: • Deploy with Projects: programmatically provision services from the CLI—now available to everyone. • Sell with Machine Payments Protocol: a protocol that lets agents know how to pay for services. • Buy with Link agent wallet: enable agents to spend on your behalf. Everything we announced at Stripe Sessions:
1:18

What we’re building for you and your agents: • Deploy with Projects: programmatically provision services from the CLI—now available to everyone. • Sell with Machine Payments Protocol: a protocol that lets agents know how to pay for services. • Buy with Link agent wallet: enable agents to spend on your behalf. Everything we announced at Stripe Sessions:

Stripe

30,269 просмотров • 2 месяцев назад

🔗 New LangChain Academy Course: Introduction to LangChain (Python) 🔗 Learn how to build with LangChain – our open source framework that makes it easy to start building agents with any model provider. In this course, you’ll create agents that can reason, use tools, and take action, and learn how to debug their behavior with LangSmith. Along the way, you’ll: - Build an agent with the `create_agent` abstraction - Use LangChain’s core building blocks: Models, Messages, Memory, and Tools - Customize your agent with middleware - Debug your agent with LangSmith Observability & Studio By the end of the course, you’ll have assembled a full team of personal assistants. Enroll for free ➡️
2:25

🔗 New LangChain Academy Course: Introduction to LangChain (Python) 🔗 Learn how to build with LangChain – our open source framework that makes it easy to start building agents with any model provider. In this course, you’ll create agents that can reason, use tools, and take action, and learn how to debug their behavior with LangSmith. Along the way, you’ll: - Build an agent with the `create_agent` abstraction - Use LangChain’s core building blocks: Models, Messages, Memory, and Tools - Customize your agent with middleware - Debug your agent with LangSmith Observability & Studio By the end of the course, you’ll have assembled a full team of personal assistants. Enroll for free ➡️

LangChain

41,016 просмотров • 6 месяцев назад

Introducing web-agent, an open framework for building web agents 🔥 Build AI agents that search, scrape, and interact with the web - powered by the same architecture behind our /agent endpoint. 100% open source. Bring any model. Anthropic, OpenAI, or your own.
0:25

Introducing web-agent, an open framework for building web agents 🔥 Build AI agents that search, scrape, and interact with the web - powered by the same architecture behind our /agent endpoint. 100% open source. Bring any model. Anthropic, OpenAI, or your own.

Firecrawl

123,163 просмотров • 2 месяцев назад

you can steal react components from any website without source code most people screenshot UIs and ask AI to recreate them. but with react fiber, you can extract the exact component 1:1 - same styling, props, design system, component structure
0:54

you can steal react components from any website without source code most people screenshot UIs and ask AI to recreate them. but with react fiber, you can extract the exact component 1:1 - same styling, props, design system, component structure

david fant

323,765 просмотров • 5 месяцев назад

Pydantic quietly dropped the most underrated framework for building Agents with MCP and tool calling. Learn how to run it in just 3 mintues.
3:30

Pydantic quietly dropped the most underrated framework for building Agents with MCP and tool calling. Learn how to run it in just 3 mintues.

matt palmer

84,917 просмотров • 1 год назад

We're excited to announce that Coinbase Developer Platform🛡️ AgentKit supports the new OpenAI Agents SDK. OpenAI’s new Agents SDK is an open source framework for building and scaling agents that includes built-in tools for web search, file search, and computer use, and tools to track and optimize agent performance—making it easier than ever to build production-ready AI agents. Coinbase AgentKit complements this by adding secure crypto wallets directly to your agents, enabling them to transact globally, instantly, and with near-zero fees—unlocking true financial autonomy.
1:46

We're excited to announce that Coinbase Developer Platform🛡️ AgentKit supports the new OpenAI Agents SDK. OpenAI’s new Agents SDK is an open source framework for building and scaling agents that includes built-in tools for web search, file search, and computer use, and tools to track and optimize agent performance—making it easier than ever to build production-ready AI agents. Coinbase AgentKit complements this by adding secure crypto wallets directly to your agents, enabling them to transact globally, instantly, and with near-zero fees—unlocking true financial autonomy.

Coinbase Developer Platform🛡️

20,287 просмотров • 1 год назад

New Course: ACP: Agent Communication Protocol Learn to build agents that communicate and collaborate across different frameworks using ACP in this short course built with IBM Research's BeeAI, and taught by Sandi Besen, AI Research Engineer & Ecosystem Lead at IBM, and Nicholas Renotte, Head of AI Developer Advocacy at IBM. Building a multi-agent system with agents built or used by different teams and organizations can become challenging. You may need to write custom integrations each time a team updates their agent design or changes their choice of agentic orchestration framework. The Agent Communication Protocol (ACP) is an open protocol that addresses this challenge by standardizing how agents communicate, using a unified RESTful interface that works across frameworks. In this protocol, you host an agent inside an ACP server, which handles requests from an ACP client and passes them to the appropriate agent. Using a standardized client-server interface allows multiple teams to reuse agents across projects. It also makes it easier to switch between frameworks, replace an agent with a new version, or update a multi-agent system without refactoring the entire system. In this course, you’ll learn to connect agents through ACP. You’ll understand the lifecycle of an ACP Agent and how it compares to other protocols, such as MCP (Model Context Protocol) and A2A (Agent-to-Agent). You’ll build ACP-compliant agents and implement both sequential and hierarchical workflows of multiple agents collaborating using ACP. Through hands-on exercises, you’ll build: - A RAG agent with CrewAI and wrap it inside an ACP server. - An ACP Client to make calls to the ACP server you created. - A sequential workflow that chains an ACP server, created with Smolagents, to the RAG agent. - A hierarchical workflow using a router agent that transforms user queries into tasks, delegated to agents available through ACP servers. - An agent that uses MCP to access tools and ACP to communicate with other agents. You’ll finish up by importing your ACP agents into the BeeAI platform, an open-source registry for discovering and sharing agents. ACP enables collaboration between agents across teams and organizations. By the end of this course, you’ll be able to build ACP agents and workflows that communicate and collaborate regardless of framework. Please sign up here:
2:49

New Course: ACP: Agent Communication Protocol Learn to build agents that communicate and collaborate across different frameworks using ACP in this short course built with IBM Research's BeeAI, and taught by Sandi Besen, AI Research Engineer & Ecosystem Lead at IBM, and Nicholas Renotte, Head of AI Developer Advocacy at IBM. Building a multi-agent system with agents built or used by different teams and organizations can become challenging. You may need to write custom integrations each time a team updates their agent design or changes their choice of agentic orchestration framework. The Agent Communication Protocol (ACP) is an open protocol that addresses this challenge by standardizing how agents communicate, using a unified RESTful interface that works across frameworks. In this protocol, you host an agent inside an ACP server, which handles requests from an ACP client and passes them to the appropriate agent. Using a standardized client-server interface allows multiple teams to reuse agents across projects. It also makes it easier to switch between frameworks, replace an agent with a new version, or update a multi-agent system without refactoring the entire system. In this course, you’ll learn to connect agents through ACP. You’ll understand the lifecycle of an ACP Agent and how it compares to other protocols, such as MCP (Model Context Protocol) and A2A (Agent-to-Agent). You’ll build ACP-compliant agents and implement both sequential and hierarchical workflows of multiple agents collaborating using ACP. Through hands-on exercises, you’ll build: - A RAG agent with CrewAI and wrap it inside an ACP server. - An ACP Client to make calls to the ACP server you created. - A sequential workflow that chains an ACP server, created with Smolagents, to the RAG agent. - A hierarchical workflow using a router agent that transforms user queries into tasks, delegated to agents available through ACP servers. - An agent that uses MCP to access tools and ACP to communicate with other agents. You’ll finish up by importing your ACP agents into the BeeAI platform, an open-source registry for discovering and sharing agents. ACP enables collaboration between agents across teams and organizations. By the end of this course, you’ll be able to build ACP agents and workflows that communicate and collaborate regardless of framework. Please sign up here:

Andrew Ng

105,261 просмотров • 1 год назад

Introducing Agent React DevTools. AI agents can now inspect React apps beyond the UI: → Component tree and state → Renders and performance → Structured output for debugging Works with React and React Native. Learn more ⬇️
0:25

Introducing Agent React DevTools. AI agents can now inspect React apps beyond the UI: → Component tree and state → Renders and performance → Structured output for debugging Works with React and React Native. Learn more ⬇️

Callstack Engineers

18,203 просмотров • 2 месяцев назад