Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

🚀Announcing LangGraph Studio: The first agent IDE LangGraph Studio offers a new way to develop LLM applications by providing a specialized agent IDE that enables visualization, interaction, and debugging of complex agentic applications With visual graphs and the ability to edit state, you can better understand agent workflows and...

LangChain's profile picture

LangChain

259,081 subscribers

185,861 görüntüleme • 2 yıl önce •via X (Twitter)

EğitimBilim & Teknoloji
LIVE

Anya Rossi• Live Now

Private livecam show

10 Yorum

D profil fotoğrafı
D2 yıl önce

This is huge!! Setting this up asap 🔥

Rami Awar profil fotoğrafı
Rami Awar2 yıl önce

Wait... is this local? Works with local tools?

Assaf Elovic profil fotoğrafı
Assaf Elovic2 yıl önce

This is huge!

Bala Venkatesh profil fotoğrafı
Bala Venkatesh2 yıl önce

Cool😎

OP profil fotoğrafı
OP2 yıl önce

That's amazing a great news!

Bachar profil fotoğrafı
Bachar2 yıl önce

This is amazing 🤩 Brilliant idea!

Damiano Redemagni profil fotoğrafı
Damiano Redemagni2 yıl önce

No way! Wow!

FlowTestAI profil fotoğrafı
FlowTestAI2 yıl önce

Let's go! We at @FlowTestAI also strongly believe that visual graphs are the way to democratize applications of LLMs to large audiences

Paul from DentroAI profil fotoğrafı
Paul from DentroAI2 yıl önce

In case anybody wondered how to send your traces to langsmith EU deployment:

virat profil fotoğrafı
virat2 yıl önce

Wow - this is massive. Congrats team 👏

Benzer Videolar

🚀 Introducing LangGraph Cloud 🚀 LangGraph helps you build reliable agents that actually work. Today, we've launched LangGraph Cloud, our new infrastructure to run fault-tolerant LangGraph agents at scale. With LangGraph Cloud, you can: • Handle large workloads with horizontally-scaling servers, task queues, and built-in persistence • Debug agent failure modes and iterate quickly in a visual playground-like studio • Deploy in one-click and get integrated tracing & monitoring in LangSmith This builds on LangGraph v0.1, our latest stable release supporting diverse control flows - whether it's single- or multi-agent, hierarchal or sequential. You'll be able to create flexible agents with human-in-the-loop collaboration and first-class streaming support. We can't wait to see the agentic workflows you'll ship. LangGraph Cloud is available in closed beta today. 👉 Join the waitlist for LangGraph Cloud: ✍️ Read our blog post announcement: 📽️ Watch the video walkthrough: 🌀 Haven't tried LangGraph yet? Give it a spin here: 🙌 Check out the new LangGraph landing page:
0:23

🚀 Introducing LangGraph Cloud 🚀 LangGraph helps you build reliable agents that actually work. Today, we've launched LangGraph Cloud, our new infrastructure to run fault-tolerant LangGraph agents at scale. With LangGraph Cloud, you can: • Handle large workloads with horizontally-scaling servers, task queues, and built-in persistence • Debug agent failure modes and iterate quickly in a visual playground-like studio • Deploy in one-click and get integrated tracing & monitoring in LangSmith This builds on LangGraph v0.1, our latest stable release supporting diverse control flows - whether it's single- or multi-agent, hierarchal or sequential. You'll be able to create flexible agents with human-in-the-loop collaboration and first-class streaming support. We can't wait to see the agentic workflows you'll ship. LangGraph Cloud is available in closed beta today. 👉 Join the waitlist for LangGraph Cloud: ✍️ Read our blog post announcement: 📽️ Watch the video walkthrough: 🌀 Haven't tried LangGraph yet? Give it a spin here: 🙌 Check out the new LangGraph landing page:

LangChain

134,051 görüntüleme • 2 yıl önce

Our latest LangChain Academy course – Building Ambient Agents with LangGraph – is now available! Most agents today handle one request at a time through chat interfaces. But as models have improved, agents can now run in the background – and take on long-running, complex tasks. LangGraph is built for these “ambient agents,” with support for human-in-the-loop workflows and memory. LangGraph Platform provides the infrastructure to run these agents at scale, and LangSmith helps you observe, evaluate, and improve your agents. Together, they make it easier to build reliable, production-ready agents. In this course, you’ll: 📩 Learn the fundamentals of LangGraph and how to build your own email agent 📊 Evaluate your agent using LangSmith ✅ Add human-in-the-loop for reviews, and memory so your agent adapts over time 🚀 Deploy your agent with LangGraph Platform and connect it to Gmail
3:02

Our latest LangChain Academy course – Building Ambient Agents with LangGraph – is now available! Most agents today handle one request at a time through chat interfaces. But as models have improved, agents can now run in the background – and take on long-running, complex tasks. LangGraph is built for these “ambient agents,” with support for human-in-the-loop workflows and memory. LangGraph Platform provides the infrastructure to run these agents at scale, and LangSmith helps you observe, evaluate, and improve your agents. Together, they make it easier to build reliable, production-ready agents. In this course, you’ll: 📩 Learn the fundamentals of LangGraph and how to build your own email agent 📊 Evaluate your agent using LangSmith ✅ Add human-in-the-loop for reviews, and memory so your agent adapts over time 🚀 Deploy your agent with LangGraph Platform and connect it to Gmail

LangChain

33,192 görüntüleme • 1 yıl önce

🔍New in LangGraph Studio: Trace mode View your LangSmith traces in real time right inside Studio. Annotate runs, and add them to datasets or annotation queues, bringing the power of LangSmith tracing directly into your workflow. Debug faster and dig deeper, without any of the context switching. Try it today!
0:22

🔍New in LangGraph Studio: Trace mode View your LangSmith traces in real time right inside Studio. Annotate runs, and add them to datasets or annotation queues, bringing the power of LangSmith tracing directly into your workflow. Debug faster and dig deeper, without any of the context switching. Try it today!

LangChain

25,866 görüntüleme • 11 ay önce

🔥 Hear how Cisco automated 60% of 1.8 million support cases with LangGraph, LangSmith, and LangGraph Platform 🔥 In his LangChain Interrupt talk, Carlos Pereira, Fellow & Chief Architect at Cisco, shares Cisco’s blueprint for transforming customer experience with AI agents. In this video, you’ll learn about: - How Cisco’s Customer Experience team identifies and prioritizes high-impact AI use cases - Their supervisor architecture that routes complex queries across specialized agents - How LangGraph, LangGraph Platform, and LangSmith power the development and continuous improvement of these agents Watch the video:
1:15

🔥 Hear how Cisco automated 60% of 1.8 million support cases with LangGraph, LangSmith, and LangGraph Platform 🔥 In his LangChain Interrupt talk, Carlos Pereira, Fellow & Chief Architect at Cisco, shares Cisco’s blueprint for transforming customer experience with AI agents. In this video, you’ll learn about: - How Cisco’s Customer Experience team identifies and prioritizes high-impact AI use cases - Their supervisor architecture that routes complex queries across specialized agents - How LangGraph, LangGraph Platform, and LangSmith power the development and continuous improvement of these agents Watch the video:

LangChain

45,375 görüntüleme • 1 yıl önce

New AI Agentic course! Learn to use LangGraph to build single and multi-agent LLM applications in AI Agents in LangGraph. This short course, taught by LangChain founder Harrison Chase Harrison Chase and Tavily founder @weiss_rotem, shows how to integrate agentic search to enhance an agent's knowledge with query-focused answers in predictable formats. Also learn to implement agentic memory to save state for reasoning and debugging, and see how human-in-the-loop input can guide agents at key junctures. You'll build an agent from scratch, then reconstruct it with LangGraph to thoroughly understand the framework. Finally, you'll build a sophisticated essay-writing agent that incorporates all the learnings from the course. Sign up here!
3:29

New AI Agentic course! Learn to use LangGraph to build single and multi-agent LLM applications in AI Agents in LangGraph. This short course, taught by LangChain founder Harrison Chase Harrison Chase and Tavily founder @weiss_rotem, shows how to integrate agentic search to enhance an agent's knowledge with query-focused answers in predictable formats. Also learn to implement agentic memory to save state for reasoning and debugging, and see how human-in-the-loop input can guide agents at key junctures. You'll build an agent from scratch, then reconstruct it with LangGraph to thoroughly understand the framework. Finally, you'll build a sophisticated essay-writing agent that incorporates all the learnings from the course. Sign up here!

Andrew Ng

152,597 görüntüleme • 2 yıl önce

You can turn an existing LangGraph agent into a fully functional voice agent with Pipecat AI. This 17-minute walkthrough shows you exactly how to do it.
16:58

You can turn an existing LangGraph agent into a fully functional voice agent with Pipecat AI. This 17-minute walkthrough shows you exactly how to do it.

LangChain

18,349 görüntüleme • 1 ay önce

🚀Launching CoAgents Public Beta 🪁: Everything you need to build Agent-Native applications, powered by LangGraph & CopilotKit. CoAgents enables in-app agents with: - Agenetic generative UI ✨ - Shared state (between agent application) - Streaming intermediate agent state - Human-in-the-Loop (Human approval & planning) 👨‍🦰 - Frontend Actions 💪 --- We’ve recently seen the emergence of Agent-Native applications that actually work: powered by vertical AI agents + agentic UX + deep in-app integration. (Apps like the Replit AI Agent, OpenAI Canvas, etc, but for any domain) With CoAgents + LangGraph, you can build this next generation of agent apps, for any vertical, with a clean and easy to use infrastructure (in hours). 💻Get started: 🗞️Blog: 🕹️Demo: 🗓️Webinar (Build an Agent-Native Apps with CoAgents & LangGraph): CC: Atai Barkai, , Harrison Chase
1:46

🚀Launching CoAgents Public Beta 🪁: Everything you need to build Agent-Native applications, powered by LangGraph & CopilotKit. CoAgents enables in-app agents with: - Agenetic generative UI ✨ - Shared state (between agent application) - Streaming intermediate agent state - Human-in-the-Loop (Human approval & planning) 👨‍🦰 - Frontend Actions 💪 --- We’ve recently seen the emergence of Agent-Native applications that actually work: powered by vertical AI agents + agentic UX + deep in-app integration. (Apps like the Replit AI Agent, OpenAI Canvas, etc, but for any domain) With CoAgents + LangGraph, you can build this next generation of agent apps, for any vertical, with a clean and easy to use infrastructure (in hours). 💻Get started: 🗞️Blog: 🕹️Demo: 🗓️Webinar (Build an Agent-Native Apps with CoAgents & LangGraph): CC: Atai Barkai, , Harrison Chase

CopilotKit🪁

51,646 görüntüleme • 1 yıl önce

🔗 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 görüntüleme • 7 ay önce

🔥 Our latest LangChain Academy course – Deep Research with LangGraph – is now live! 🔥 Deep research agents are taking off – from major AI labs to companies building their own. Research is inherently open-ended. You can't always predict whether a question needs broad exploration or deep analysis. Agents excel here because they adapt on the fly, using each finding to decide where to dig next. Building these systems ourselves and with customers, we've learned that structure matters. The best research agents scope problems with users first. Then, they coordinate multiple specialists instead of overwhelming one generalist. LangGraph is built for these types of long-running, multi-agent workflows. Its persistence layer tracks progress across agents. LangSmith gives you the observability and evaluation tools you need to track and improve performance. In this course, you'll build and evaluate: - A user scoping agent to define research parameters - A multi-agent research team with supervisor - And add tool integration via MCP Enroll for free ➡️
2:47

🔥 Our latest LangChain Academy course – Deep Research with LangGraph – is now live! 🔥 Deep research agents are taking off – from major AI labs to companies building their own. Research is inherently open-ended. You can't always predict whether a question needs broad exploration or deep analysis. Agents excel here because they adapt on the fly, using each finding to decide where to dig next. Building these systems ourselves and with customers, we've learned that structure matters. The best research agents scope problems with users first. Then, they coordinate multiple specialists instead of overwhelming one generalist. LangGraph is built for these types of long-running, multi-agent workflows. Its persistence layer tracks progress across agents. LangSmith gives you the observability and evaluation tools you need to track and improve performance. In this course, you'll build and evaluate: - A user scoping agent to define research parameters - A multi-agent research team with supervisor - And add tool integration via MCP Enroll for free ➡️

LangChain

61,205 görüntüleme • 11 ay önce

🎨 Introducing Prompt Canvas — a novel UX for prompt engineering Building LLM applications requires new and dedicated tools for prompt engineering. With Prompt Canvas in LangSmith, you can: • Collaborate with an AI agent to draft, refine, and edit your prompts • Define custom quick actions to standardize prompting strategies used across the org ✍️ Learn more: ➡️ Try it out:
4:12

🎨 Introducing Prompt Canvas — a novel UX for prompt engineering Building LLM applications requires new and dedicated tools for prompt engineering. With Prompt Canvas in LangSmith, you can: • Collaborate with an AI agent to draft, refine, and edit your prompts • Define custom quick actions to standardize prompting strategies used across the org ✍️ Learn more: ➡️ Try it out:

LangChain

43,733 görüntüleme • 1 yıl önce

🚀 Announcing LangSmith Skills + CLI 🚀 Agent improvements are increasingly driven by coding agents themselves. We're releasing LangSmith Skills alongside the LangSmith CLI to make coding agents experts at the agent engineering lifecycle. LangSmith Skills enable agents to debug traces, create datasets, and run experiments - and thanks to the CLI, agents are able to do it all natively through the terminal, where they're most comfortable. Try out LangSmith Skills and the CLI with your own coding agents! ➡️ Skills: ➡️ CLI:
1:30

🚀 Announcing LangSmith Skills + CLI 🚀 Agent improvements are increasingly driven by coding agents themselves. We're releasing LangSmith Skills alongside the LangSmith CLI to make coding agents experts at the agent engineering lifecycle. LangSmith Skills enable agents to debug traces, create datasets, and run experiments - and thanks to the CLI, agents are able to do it all natively through the terminal, where they're most comfortable. Try out LangSmith Skills and the CLI with your own coding agents! ➡️ Skills: ➡️ CLI:

LangChain

49,572 görüntüleme • 4 ay önce

Insights Agent & Multi-turn Evals Agents run for a long period of time and have multiple interactions with users, tackling a wide variety of problems. Today we’re launching two new features in LangSmith, our agent engineering platform, so you can better understand your agent behavior: • Insights Agent is a new agent that automatically categorizes agent behavior patterns in LangSmith • Multi-turn Evals lets you evaluate agent trajectory across complete conversations, so you can see if the agent actually accomplished user goals Learn more:
0:40

Insights Agent & Multi-turn Evals Agents run for a long period of time and have multiple interactions with users, tackling a wide variety of problems. Today we’re launching two new features in LangSmith, our agent engineering platform, so you can better understand your agent behavior: • Insights Agent is a new agent that automatically categorizes agent behavior patterns in LangSmith • Multi-turn Evals lets you evaluate agent trajectory across complete conversations, so you can see if the agent actually accomplished user goals Learn more:

LangChain

13,322 görüntüleme • 9 ay önce

Today, we’re shipping new ways to observe, analyze, and debug agents with LangSmith: • Polly: an AI assistant for AI engineering that helps you understand traces, threads, and improve prompts • LangSmith Fetch: a CLI for pulling trace & thread data straight into your terminal or coding agent Agents are running longer and getting more complex, which demands new debugging workflows beyond simple LLM apps. We wrote a blog on the trends behind this shift— and why tools like Polly and LangSmith Fetch are needed. Shipping reliable agents requires full visibility into agent behavior, with tooling that helps you reason over that data in the UI, the terminal, or alongside coding agents. 📔Learn more about Polly: 📔Learn more about LangSmith Fetch: 📔How to observe deep agents: 📽️ Polly video tutorial: 📽️ LangSmith Fetch video tutorial:
7:10

Today, we’re shipping new ways to observe, analyze, and debug agents with LangSmith: • Polly: an AI assistant for AI engineering that helps you understand traces, threads, and improve prompts • LangSmith Fetch: a CLI for pulling trace & thread data straight into your terminal or coding agent Agents are running longer and getting more complex, which demands new debugging workflows beyond simple LLM apps. We wrote a blog on the trends behind this shift— and why tools like Polly and LangSmith Fetch are needed. Shipping reliable agents requires full visibility into agent behavior, with tooling that helps you reason over that data in the UI, the terminal, or alongside coding agents. 📔Learn more about Polly: 📔Learn more about LangSmith Fetch: 📔How to observe deep agents: 📽️ Polly video tutorial: 📽️ LangSmith Fetch video tutorial:

LangChain

31,035 görüntüleme • 7 ay önce

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.
1:32

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

46,109 görüntüleme • 1 yıl önce

🚀 We just shipped a major update to LangSmith Agent Builder: • New agent chat: One always-available agent with access to all your workspace tools • Chat → Agent: Turn any conversation into a specialized agent with one click • File uploads: Attach files directly to Agent Builder • Tool registry: Add, authenticate, and manage your tools in one place Try it now: Learn more:
3:04

🚀 We just shipped a major update to LangSmith Agent Builder: • New agent chat: One always-available agent with access to all your workspace tools • Chat → Agent: Turn any conversation into a specialized agent with one click • File uploads: Attach files directly to Agent Builder • Tool registry: Add, authenticate, and manage your tools in one place Try it now: Learn more:

LangChain

24,885,978 görüntüleme • 5 ay önce

🚀Excited to Introduce Coagents🚀: An innovative framework for building human-in-the-loop agents into applications - powered by LangGraph & CopilotKit. Coagents enable: - End-users to correct agent steps (in-app)🛤️ - Stream intermediate agent state 🪢 - Expose LangGraph agents as specialized skills for an app's copilot 🧠 --- Human-in-the-loop is key to taking agents from cool demos to actually useful tools. Coagents, in combination with LangGraph are a big step towards making in-app, human-in-the-loop agents trivially easy to develop. Check out the first ever demo of Coagents, an AI Children's book generator 👇 Coagents will be entirely open-sourced. Interested in contributing/early access? CC: , shadcn, Harrison Chase, Lance Martin, Ariel Weinberger
2:31

🚀Excited to Introduce Coagents🚀: An innovative framework for building human-in-the-loop agents into applications - powered by LangGraph & CopilotKit. Coagents enable: - End-users to correct agent steps (in-app)🛤️ - Stream intermediate agent state 🪢 - Expose LangGraph agents as specialized skills for an app's copilot 🧠 --- Human-in-the-loop is key to taking agents from cool demos to actually useful tools. Coagents, in combination with LangGraph are a big step towards making in-app, human-in-the-loop agents trivially easy to develop. Check out the first ever demo of Coagents, an AI Children's book generator 👇 Coagents will be entirely open-sourced. Interested in contributing/early access? CC: , shadcn, Harrison Chase, Lance Martin, Ariel Weinberger

CopilotKit🪁

69,301 görüntüleme • 1 yıl önce

LangSmith Agent Builder is generally available 🎉 It’s surprisingly easy to build agents now. Even a VC can do it…👇 Try it free: Read the announcement:
1:44

LangSmith Agent Builder is generally available 🎉 It’s surprisingly easy to build agents now. Even a VC can do it…👇 Try it free: Read the announcement:

LangChain

111,467 görüntüleme • 6 ay önce

I vibe coded Gumloop over the weekend!! Presenting Agent Flow - an open-source alternative to Gumloop! We built a free no-code AI Agent builder with @composiohq and LangChain's Langgraph that lets you automate workflows and complex agentic patterns with drag-and-drop nodes. Try it out: Here's the code: Looking forward to open-sourcing more YC startups over the coming weekends. Comment below which one you would like to use.
1:10

I vibe coded Gumloop over the weekend!! Presenting Agent Flow - an open-source alternative to Gumloop! We built a free no-code AI Agent builder with @composiohq and LangChain's Langgraph that lets you automate workflows and complex agentic patterns with drag-and-drop nodes. Try it out: Here's the code: Looking forward to open-sourcing more YC startups over the coming weekends. Comment below which one you would like to use.

Karan Vaidya

46,666 görüntüleme • 1 yıl önce

Introducing LangSmith Fleet. Agents for every team. → Build agents with natural language → Share and control who can edit, run, or clone each agent → Manage authentication with agent identity → Approve actions with human-in-the-loop → Track and audit actions with tracing in LangSmith Observability Try Fleet:
1:06

Introducing LangSmith Fleet. Agents for every team. → Build agents with natural language → Share and control who can edit, run, or clone each agent → Manage authentication with agent identity → Approve actions with human-in-the-loop → Track and audit actions with tracing in LangSmith Observability Try Fleet:

LangChain

9,398,037 görüntüleme • 4 ay önce