正在加载视频...

视频加载失败

返回首页

1 command to build, deploy & scale AI Agents! xpander is your plug-and-play Backend-as-a-Service for agents—manages memory, tools, multi-user states, events, guardrails, and more. Works with LlamaIndex, Langchain, CrewAI, Google ADK—you name it. 100% open-source.

akshay_pachaar's profile picture

Akshay 🚀

212,372 subscribers

60,192 次观看 • 1 年前 •via X (Twitter)

健康养生科学技术教育
LIVE

Anya Rossi• Live Now

Private livecam show

11 条评论

Akshay 🚀 的头像
Akshay 🚀1 年前

Link to GitHub repo: (Don't forget to star 🌟)

Akshay 🚀 的头像
Akshay 🚀1 年前

If you found it insightful, reshare with your network. Find me → @akshay_pachaar ✔️ For more insights and tutorials on LLMs, AI Agents, and Machine Learning!

Alexander Mia 的头像
Alexander Mia1 年前

INTRODUCING: Agentic Security - LLM Security Scanner! 🔍 🔑 Features: Scans for prompt injections, jailbreaking & more. Provides detailed reports & options to customize attack rules. 🔗access the GitHub Link ↓

Deependra 的头像
Deependra1 年前

Looks great !!....maybe, i will give it a try...for one of my project related to agents.

Akshay 🚀 的头像
Akshay 🚀1 年前

Perfect! Glad you found it helpful!

Avi Chawla 的头像
Avi Chawla1 年前

This is much-needed for Agents. Thanks Akshay. Will try this out.

Akshay 🚀 的头像
Akshay 🚀1 年前

You're welcome! :)

【 AITV 】 的头像
【 AITV 】1 年前

Nice. Bots building bots🤌🤌

Mykhailo Sorochuk 的头像
Mykhailo Sorochuk1 年前

Looks solid. Excited to give it a go!

Akshay 🚀 的头像
Akshay 🚀1 年前

Awesome! 🔥

Kyle Quest (aka Q) 的头像
Kyle Quest (aka Q)1 年前

That repo only has a readme and a hello world example... The actual backend is not open source :-)

相关视频

Finally, a production-ready backend for Agents that actually works! xpander is a plug-and-play backend for Agents that manages memory, tools, states, version control, guardrails, and more. Works with any framework, like CrewAI, Agno, Langchain, etc. Fully self-hostable!
0:44

Finally, a production-ready backend for Agents that actually works! xpander is a plug-and-play backend for Agents that manages memory, tools, states, version control, guardrails, and more. Works with any framework, like CrewAI, Agno, Langchain, etc. Fully self-hostable!

Avi Chawla

50,659 次观看 • 10 个月前

AI agents can finally talk to your frontend! The new AG-UI protocol lets your agents stream messages, sync state, call tools, and receive user input, live in the UI. It fills a critical gap in the agent ecosystem: ▸ MCP – agents to tools ▸ A2A – agents to agents ▸ AG-UI – agents to users, via frontends Connects to LangChain, CrewAI, and LlamaIndex (and more). 100% open-source.
0:25

AI agents can finally talk to your frontend! The new AG-UI protocol lets your agents stream messages, sync state, call tools, and receive user input, live in the UI. It fills a critical gap in the agent ecosystem: ▸ MCP – agents to tools ▸ A2A – agents to agents ▸ AG-UI – agents to users, via frontends Connects to LangChain, CrewAI, and LlamaIndex (and more). 100% open-source.

Lior⚡

15,514 次观看 • 1 年前

🚨 Breaking: Google just open-sourced the Agent Development Kit (ADK) a framework for building AI agents and multi-agent systems. - Build agents in under 100 lines. - Supports MCP More information and how to get started 👇 1/5
0:22

🚨 Breaking: Google just open-sourced the Agent Development Kit (ADK) a framework for building AI agents and multi-agent systems. - Build agents in under 100 lines. - Supports MCP More information and how to get started 👇 1/5

AshutoshShrivastava

130,272 次观看 • 1 年前

Introducing ADK Go, a new open-source toolkit designed to empower Go developers to build powerful AI agents. Highlights: 0:00 Introducing the Go ADK 0:53 Build your first Go agent 1:49 Run your agent 2:23 Understanding Tools 3:28 Run your agent with tools 5:00 Multi-agent patterns in Go 7:58 State, Sessions, and Events
10:01

Introducing ADK Go, a new open-source toolkit designed to empower Go developers to build powerful AI agents. Highlights: 0:00 Introducing the Go ADK 0:53 Build your first Go agent 1:49 Run your agent 2:23 Understanding Tools 3:28 Run your agent with tools 5:00 Multi-agent patterns in Go 7:58 State, Sessions, and Events

Google AI Developers

39,688 次观看 • 8 个月前

Build smarter AI agents, faster. ⚡️ The open-source Agent Development Kit makes it easy to create modular, multi-agent systems using the models and tools you prefer. Join the ADK Hackathon →
0:51

Build smarter AI agents, faster. ⚡️ The open-source Agent Development Kit makes it easy to create modular, multi-agent systems using the models and tools you prefer. Join the ADK Hackathon →

Google for Developers

11,240 次观看 • 1 年前

INSANE: Grok 3 + Lovable = BEST AI Agent Apps!!!! Grok 3 generated the code for an AI agent that manages your Gmail - send, reply, and draft effortlessly Here's how it works: - Connect with your Gmail using Composio - Use Lovable to build an extremely cool frontend for the Agent - Agentic workflow with LlamaIndex Built with LlamaIndex 🦙 To connect your agents with more tools like Gmail, use
1:09

INSANE: Grok 3 + Lovable = BEST AI Agent Apps!!!! Grok 3 generated the code for an AI agent that manages your Gmail - send, reply, and draft effortlessly Here's how it works: - Connect with your Gmail using Composio - Use Lovable to build an extremely cool frontend for the Agent - Agentic workflow with LlamaIndex Built with LlamaIndex 🦙 To connect your agents with more tools like Gmail, use

Karan Vaidya

62,030 次观看 • 1 年前

BREAKING 🚨: Google introduced Gemini Enterprise with Agents, Connectors and Agent Builder! “It allows you to chat with your company’s documents, data and apps as well as build and deploy AI agents, all grounded in your information and context.“
0:37

BREAKING 🚨: Google introduced Gemini Enterprise with Agents, Connectors and Agent Builder! “It allows you to chat with your company’s documents, data and apps as well as build and deploy AI agents, all grounded in your information and context.“

TestingCatalog News 🗞

104,349 次观看 • 9 个月前

Metorial (@MetorialAI) makes it easy for AI agents to use tools and data. Deploy 600+ MCP integrations in three clicks and connect them to agents in a single function call. Open-source and the only serverless MCP platform built for multi-tenant systems.
1:58

Metorial (@MetorialAI) makes it easy for AI agents to use tools and data. Deploy 600+ MCP integrations in three clicks and connect them to agents in a single function call. Open-source and the only serverless MCP platform built for multi-tenant systems.

Y Combinator

15,341 次观看 • 9 个月前

AG-UI protocol has become as an industry standard📈 The Agent-User Interaction protocol allows you to connect AI agents and frontends. AND it just crossed 2.5M weekly downloads! With adoption/integration by Google, AWS, Microsoft, Oracle, LangChain, Mastra, Pydantic AI, CrewAI & so many more. As well as SDKs in .NET, Golang, Kotlin, Java, Rust and more all contributed by the community. How it works & more 👇
0:25

AG-UI protocol has become as an industry standard📈 The Agent-User Interaction protocol allows you to connect AI agents and frontends. AND it just crossed 2.5M weekly downloads! With adoption/integration by Google, AWS, Microsoft, Oracle, LangChain, Mastra, Pydantic AI, CrewAI & so many more. As well as SDKs in .NET, Golang, Kotlin, Java, Rust and more all contributed by the community. How it works & more 👇

Atai Barkai

18,650 次观看 • 3 个月前

A Crash Course on Building AI Agents! Here's what it covers: - What is an AI agent - Connecting agents to tools - Overview of MCP - Replacing tools with MCP servers - Setting up observability and tracing All with 100% open-source tools!
32:57

A Crash Course on Building AI Agents! Here's what it covers: - What is an AI agent - Connecting agents to tools - Overview of MCP - Replacing tools with MCP servers - Setting up observability and tracing All with 100% open-source tools!

Akshay 🚀

115,825 次观看 • 1 年前

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 次观看 • 1 年前

This is literally the easiest way to build an AI agent. Zero code. You only need to run a couple of commands. (I've said this before, but Google ADK is my favorite way to build code-first agents.) Here is what you need to do: 1. Open your terminal and create an empty folder 2. Run `uv init` inside the folder (if you don't have uv installed, you are really missing out!) 3. Install the google-adk library using the following command: `uv add google-adk`. 4. At this point, you can use the ask to create your agent with a single command: `uv run adk create --type=config my_agent`. This will ask you a couple of questions, including your GEMINI_API_KEY (you can create one online). 5. The command above will create a my_agent/root_agent.yaml file. Open it and add the following two lines at the end of the file so your agent can use Google to search for stuff: tools: - name: google_search 6. You have everything you need now. Run the adk web interface and start playing with your agent: `uv run adk web` That's it! Literally zero code. The agent works off the YAML configuration file.
1:33

This is literally the easiest way to build an AI agent. Zero code. You only need to run a couple of commands. (I've said this before, but Google ADK is my favorite way to build code-first agents.) Here is what you need to do: 1. Open your terminal and create an empty folder 2. Run `uv init` inside the folder (if you don't have uv installed, you are really missing out!) 3. Install the google-adk library using the following command: `uv add google-adk`. 4. At this point, you can use the ask to create your agent with a single command: `uv run adk create --type=config my_agent`. This will ask you a couple of questions, including your GEMINI_API_KEY (you can create one online). 5. The command above will create a my_agent/root_agent.yaml file. Open it and add the following two lines at the end of the file so your agent can use Google to search for stuff: tools: - name: google_search 6. You have everything you need now. Run the adk web interface and start playing with your agent: `uv run adk web` That's it! Literally zero code. The agent works off the YAML configuration file.

Santiago

140,737 次观看 • 7 个月前

🔗 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 次观看 • 7 个月前

🔥 New LangChain Academy Course: LangChain Essentials (Python & TypeScript) 🔥 Learn the basics of LangChain – our open source framework that makes it easy to start building agents with any model provider. Last week, we released LangChain 1.0. We’ve completely rewritten LangChain to be opinionated, focused, and powered by LangGraph’s runtime. It includes a new `create_agent` abstraction to build agents quickly, middleware for flexibility, and standard content blocks that work across any model provider. In this quickstart course, you'll learn how to: - 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 and test your agent with LangSmith Observability & Evaluation Enroll for free ➡️
1:37

🔥 New LangChain Academy Course: LangChain Essentials (Python & TypeScript) 🔥 Learn the basics of LangChain – our open source framework that makes it easy to start building agents with any model provider. Last week, we released LangChain 1.0. We’ve completely rewritten LangChain to be opinionated, focused, and powered by LangGraph’s runtime. It includes a new `create_agent` abstraction to build agents quickly, middleware for flexibility, and standard content blocks that work across any model provider. In this quickstart course, you'll learn how to: - 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 and test your agent with LangSmith Observability & Evaluation Enroll for free ➡️

LangChain

50,475 次观看 • 8 个月前

Drag & Drop to build AI Agents workflows without writing a single line of code. Works with OpenAI, Anthropic, Google, and local Ollama models. 100% Opensource.
0:23

Drag & Drop to build AI Agents workflows without writing a single line of code. Works with OpenAI, Anthropic, Google, and local Ollama models. 100% Opensource.

Shubham Saboo

108,935 次观看 • 1 年前

Gemini 3.1 Flash-Lite is the model to build always on multimodal AI Agents. I just built a memory agent with Google ADK that runs 24/7. Feed it text, images, audio, video or PDFs. It reads, connects and consolidates everything while you sleep. 100% Opensource code.
1:05

Gemini 3.1 Flash-Lite is the model to build always on multimodal AI Agents. I just built a memory agent with Google ADK that runs 24/7. Feed it text, images, audio, video or PDFs. It reads, connects and consolidates everything while you sleep. 100% Opensource code.

Shubham Saboo

24,930 次观看 • 4 个月前

A toolkit for building agents that watch, listen, and understand video. Low latency by design. Open source. Production ready. Vision Agents lets you build real time video AI that works with your models and your edge layer. Supports YOLO, Moondream, Cartesia, Deepgram, ElevenLabs, HeyGen, Gemini, OpenAI, and more. Quick model switching. Easy to use API. Perfect for coaching tools, collaboration apps, avatars, and robotics.
0:43

A toolkit for building agents that watch, listen, and understand video. Low latency by design. Open source. Production ready. Vision Agents lets you build real time video AI that works with your models and your edge layer. Supports YOLO, Moondream, Cartesia, Deepgram, ElevenLabs, HeyGen, Gemini, OpenAI, and more. Quick model switching. Easy to use API. Perfect for coaching tools, collaboration apps, avatars, and robotics.

GitHub Projects Community

30,274 次观看 • 7 个月前

🔗 Announcing LangChain OSS Skills LangChain has the most popular frameworks for building AI agents — and now your coding agent can be an expert in it. We're excited to release the first iteration of LangChain OSS Skills, giving your agent expertise in our open source frameworks. The skills include guidance on how to use langchain, langgraph, and deepagents to effectively build agents. ➡️ Install our OSS skills for your coding agent here: ➡️ Read more:
0:43

🔗 Announcing LangChain OSS Skills LangChain has the most popular frameworks for building AI agents — and now your coding agent can be an expert in it. We're excited to release the first iteration of LangChain OSS Skills, giving your agent expertise in our open source frameworks. The skills include guidance on how to use langchain, langgraph, and deepagents to effectively build agents. ➡️ Install our OSS skills for your coding agent here: ➡️ Read more:

LangChain OSS

65,840 次观看 • 4 个月前

AI creators now have the economic infrastructure to build, deploy, and earn; it's 100% open-source and community-driven. OpenLedger offers unmatched transparency, flexibility, and the tools you need to build the future of AI on your terms. OpenLedger is a decentralized, open-source blockchain designed for sourcing, training, and monetizing AI models. Learn more about in this video 👇
2:00

AI creators now have the economic infrastructure to build, deploy, and earn; it's 100% open-source and community-driven. OpenLedger offers unmatched transparency, flexibility, and the tools you need to build the future of AI on your terms. OpenLedger is a decentralized, open-source blockchain designed for sourcing, training, and monetizing AI models. Learn more about in this video 👇

MosesMee

14,108 次观看 • 1 年前