正在加载视频...

视频加载失败

返回首页

Build Agentic Workflows from Scratch 🤖🔁 It’s tempting for an AI engineer to use an off-the-shelf agent, but building your own agents shouldn’t be scary (and limited to AI research papers)! In our brand-new video tutorial we show you how to build an agent in two intuitive steps: 1️⃣...

llama_index's profile picture

LlamaIndex 🦙

94,628 subscribers

60,531 次观看 • 2 年前 •via X (Twitter)

科学技术
LIVE

Anya Rossi• Live Now

Private livecam show

1 条评论

Raymond Weitekamp 的头像
Raymond Weitekamp2 年前

So cool. Are DAGs available in TS too? @llama_index

相关视频

Building an Agentic Search System Building an agentic system is not too hard. Loops, function calling, tool execution, and the model. That's it! I show in this video how to build a search agent from scratch. ~350 lines of code!
13:01

Building an Agentic Search System Building an agentic system is not too hard. Loops, function calling, tool execution, and the model. That's it! I show in this video how to build a search agent from scratch. ~350 lines of code!

elvis

57,290 次观看 • 1 年前

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 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 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

151,484 次观看 • 2 年前

Today, we're launching a new Laracasts series that will show you the essentials building an AI agent from scratch. We start with a basic chat response and gradually introduce new concepts, such as the agent loop, custom tools, and more. 😀 "So You Want To Build An Agent"
9:08

Today, we're launching a new Laracasts series that will show you the essentials building an AI agent from scratch. We start with a basic chat response and gradually introduce new concepts, such as the agent loop, custom tools, and more. 😀 "So You Want To Build An Agent"

Laracasts

16,303 次观看 • 2 个月前

Here's a clip from my upcoming AI SDK tutorial: We're building what Anthropic calls an 'agent' in TypeScript. Can it react to results of tool calls, deciding when it's completed the task? It's an agent.
3:58

Here's a clip from my upcoming AI SDK tutorial: We're building what Anthropic calls an 'agent' in TypeScript. Can it react to results of tool calls, deciding when it's completed the task? It's an agent.

Matt Pocock

23,015 次观看 • 1 年前

I’m excited to kick off the first of our short courses focused on agents, starting with Building Agentic RAG with LlamaIndex, taught by Jerry Liu, CEO of LlamaIndex 🦙. This covers an important shift in RAG (retrieval augmented generation), in which rather than having the developer write explicit routines to retrieve information to feed into the LLM context, we instead build a RAG agent that that has access to tools for retrieving information. This lets the agent decide what information to fetch, and enables it to answer more complex questions using multi-step reasoning. In detail, you'll learn about: - Routing: Where your agent will use decision-making to route requests to multiple tools. - Tool Use: Where you'll create an interface for agents to select what tool (function call) to use as well as generate the right arguments. - Multi-step reasoning with tool use: Where you'll use an LLM to carry out multiple steps of reasoning, while retaining memory throughout the process. You’ll also learn how to step through what your agent is doing to debug and improve it iteratively. It’s an exciting time to build agents. Sign up and get started here!
2:06

I’m excited to kick off the first of our short courses focused on agents, starting with Building Agentic RAG with LlamaIndex, taught by Jerry Liu, CEO of LlamaIndex 🦙. This covers an important shift in RAG (retrieval augmented generation), in which rather than having the developer write explicit routines to retrieve information to feed into the LLM context, we instead build a RAG agent that that has access to tools for retrieving information. This lets the agent decide what information to fetch, and enables it to answer more complex questions using multi-step reasoning. In detail, you'll learn about: - Routing: Where your agent will use decision-making to route requests to multiple tools. - Tool Use: Where you'll create an interface for agents to select what tool (function call) to use as well as generate the right arguments. - Multi-step reasoning with tool use: Where you'll use an LLM to carry out multiple steps of reasoning, while retaining memory throughout the process. You’ll also learn how to step through what your agent is doing to debug and improve it iteratively. It’s an exciting time to build agents. Sign up and get started here!

Andrew Ng

297,053 次观看 • 2 年前

How to build an AI agent from scratch. This is the question I get the most, so I recorded this video to show you from the very beginning how you can get started. You can do this in Python, TypeScript, JavaScript, or Ruby.
30:13

How to build an AI agent from scratch. This is the question I get the most, so I recorded this video to show you from the very beginning how you can get started. You can do this in Python, TypeScript, JavaScript, or Ruby.

Santiago

71,768 次观看 • 1 年前

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 次观看 • 1 年前

The best agent is now open source. II-Agent is now live on GitHub. From a single prompt to a mobile app. From a research brief to an interactive website. From skills to real workflows. Fork it. Extend it. Show us what you build.
1:19

The best agent is now open source. II-Agent is now live on GitHub. From a single prompt to a mobile app. From a research brief to an interactive website. From skills to real workflows. Fork it. Extend it. Show us what you build.

Intelligent Internet

20,404 次观看 • 2 个月前

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 次观看 • 1 年前

Your agent: Call me, maybe? ❤️ Check out how we used the Copilot SDK to give an agent a voice tool, allowing it to initiate a call and talk back in real time. 👀
0:55

Your agent: Call me, maybe? ❤️ Check out how we used the Copilot SDK to give an agent a voice tool, allowing it to initiate a call and talk back in real time. 👀

GitHub

24,413 次观看 • 3 个月前

Seen a few companies trying to give AI agents a human face . Personally this is how I’d imagine an agent 😅. I want an AI agent to be an agent, not pretending to be human. Animated on Kling . Love how this turned out tbh.
0:22

Seen a few companies trying to give AI agents a human face . Personally this is how I’d imagine an agent 😅. I want an AI agent to be an agent, not pretending to be human. Animated on Kling . Love how this turned out tbh.

Design Chief Priest

12,756 次观看 • 1 年前

I wanted to share a quick demo of what we've been working on with our ai agent cloud. This enables fast deployment of agents that have access to a suite of tools, and was designed with agent interoperability in mind. This demo shows how you can go from nothing to an AI twitter agent in a couple minutes. This is what we are using internally to manage deployments, so we will consistently upgrading its capabilities. The next goals are to enable simple TEE deployments for agents, and focus on building out feature for agent interoperability to simplify agent to agent collaboration.
4:16

I wanted to share a quick demo of what we've been working on with our ai agent cloud. This enables fast deployment of agents that have access to a suite of tools, and was designed with agent interoperability in mind. This demo shows how you can go from nothing to an AI twitter agent in a couple minutes. This is what we are using internally to manage deployments, so we will consistently upgrading its capabilities. The next goals are to enable simple TEE deployments for agents, and focus on building out feature for agent interoperability to simplify agent to agent collaboration.

Johnny

26,738 次观看 • 1 年前

Here’s how to build a Slack clone with Claude 3.7 Sonnet and Cursor Agent in v0.46. Perfect for *anyone* wanting to pick up AI coding tools. Learn how to build an app 100% from scratch with the newest AI coding workflows. Watch for 1hr+ of agentic coding.
1:12:45

Here’s how to build a Slack clone with Claude 3.7 Sonnet and Cursor Agent in v0.46. Perfect for *anyone* wanting to pick up AI coding tools. Learn how to build an app 100% from scratch with the newest AI coding workflows. Watch for 1hr+ of agentic coding.

Mckay Wrigley

212,403 次观看 • 1 年前

Want to build an AI agent that actually does things? This tutorial walks you through: • Qwen3 reasoning • Custom tool calling • Replacing tools with MCPs • Multi-tool Airbnb agent All GPU-accelerated with AMD + vLLM 🔗
0:25

Want to build an AI agent that actually does things? This tutorial walks you through: • Qwen3 reasoning • Custom tool calling • Replacing tools with MCPs • Multi-tool Airbnb agent All GPU-accelerated with AMD + vLLM 🔗

AI at AMD

58,193 次观看 • 1 年前

How did we build & scale Replit Agent? Find out from a Replit AI engineer (and a good friend), James Austin ⠕ We chat about building Replit Agent, what makes a great SWE, and James' journey to becoming an AI engineer
48:33

How did we build & scale Replit Agent? Find out from a Replit AI engineer (and a good friend), James Austin ⠕ We chat about building Replit Agent, what makes a great SWE, and James' journey to becoming an AI engineer

matt palmer

26,222 次观看 • 6 个月前

AGENT ID FOR CLAUDE AGENT issue an agent ID to your claude code agent in 2 min - so it can commit to github as a verified, human-authorized agent not just a random bot this is the first step towards building trust in the agentic internet, powered by Alien
3:40

AGENT ID FOR CLAUDE AGENT issue an agent ID to your claude code agent in 2 min - so it can commit to github as a verified, human-authorized agent not just a random bot this is the first step towards building trust in the agentic internet, powered by Alien

kirill avery

16,225 次观看 • 2 个月前

It is now way easier to build multi-agent workflows in n8n with the new AI Agent Tool node. Instead of juggling sub workflows a parent AI Agent can now use other Agents as tools even several layers deep. Max shows how a cheap GPT 4.1 nano Agent handles heavy data and sends summaries to a parent Agent saving token costs and making debugging simpler. Watch the full walkthrough:
0:38

It is now way easier to build multi-agent workflows in n8n with the new AI Agent Tool node. Instead of juggling sub workflows a parent AI Agent can now use other Agents as tools even several layers deep. Max shows how a cheap GPT 4.1 nano Agent handles heavy data and sends summaries to a parent Agent saving token costs and making debugging simpler. Watch the full walkthrough:

n8n.io

27,766 次观看 • 10 个月前

🤖 HYTOPIA AI Agents Society (Start Building!) 🎮 We've just added the "ai-agents" example to our SDK, which is a starting point of a game with an AI Agent Society! You can use this example as a template to build your own AI agents for a HYTOPIA game:
3:20

🤖 HYTOPIA AI Agents Society (Start Building!) 🎮 We've just added the "ai-agents" example to our SDK, which is a starting point of a game with an AI Agent Society! You can use this example as a template to build your own AI agents for a HYTOPIA game:

HYTOPIA

15,729 次观看 • 1 年前

I just watched an AI agent operate my Mac like a real human. This AI agent responded to candidates' emails and scheduled Zoom meetings, all from a plain English prompt. Skip the Zapier spaghetti. This is agentic AI; you need to know about:
3:58

I just watched an AI agent operate my Mac like a real human. This AI agent responded to candidates' emails and scheduled Zoom meetings, all from a plain English prompt. Skip the Zapier spaghetti. This is agentic AI; you need to know about:

Shruti

36,489 次观看 • 11 个月前