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🔍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!

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LangChain

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25,866 просмотров • 1 год назад •via X (Twitter)

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🚀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 iterate faster. LangGraph Studio integrates with LangSmith so you can collaborate with teammates to debug failure modes LangGraph Studio is available for free to all LangSmith users on any plan tier during its early development. Read more about it here: Watch a YouTube walkthrough: Try out LangGraph Studio for free here: Sign up for a LangSmith account:
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🚀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 iterate faster. LangGraph Studio integrates with LangSmith so you can collaborate with teammates to debug failure modes LangGraph Studio is available for free to all LangSmith users on any plan tier during its early development. Read more about it here: Watch a YouTube walkthrough: Try out LangGraph Studio for free here: Sign up for a LangSmith account:

LangChain

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Polly is our AI assistant built directly into LangSmith to help you debug, analyze, and improve your agents — now generally available. Now, Polly lives on every page of LangSmith, remembers your full session as you navigate, and can take action to update prompts, compare experiments, write evaluators, and more. Read the blog: See the docs: Try Polly in LangSmith:
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Polly is our AI assistant built directly into LangSmith to help you debug, analyze, and improve your agents — now generally available. Now, Polly lives on every page of LangSmith, remembers your full session as you navigate, and can take action to update prompts, compare experiments, write evaluators, and more. Read the blog: See the docs: Try Polly in LangSmith:

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🚀 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:
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🚀 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:

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49,572 просмотров • 5 месяцев назад

🚀Launching: LangSmith Engine LangSmith Engine is an agent that sits on top of your traces It runs in the background and automatically identifies issues It then proactively suggests action items (code changes, evaluators to add) Try it today:
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🚀Launching: LangSmith Engine LangSmith Engine is an agent that sits on top of your traces It runs in the background and automatically identifies issues It then proactively suggests action items (code changes, evaluators to add) Try it today:

Harrison Chase

164,615 просмотров • 3 месяцев назад

We built a tracing plugin for every Codex session into LangSmith. Now every turn (tool calls, token usage, subagent threads) lands in LangSmith as a real trace you can dig into. Two config blocks and one flag, and it's live.
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We built a tracing plugin for every Codex session into LangSmith. Now every turn (tool calls, token usage, subagent threads) lands in LangSmith as a real trace you can dig into. Two config blocks and one flag, and it's live.

LangChain

13,491 просмотров • 1 месяц назад

🚀 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:
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🚀 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 просмотров • 2 лет назад

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
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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 просмотров • 1 год назад

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:
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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

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🔗 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 ➡️
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🔗 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

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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:
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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

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Introducing On-Call Copilot - a new agent template in LangSmith Fleet → Triages every alert and investigates root cause across your code and traces → Manages tickets and routes every incident to the right channels → Continuously learns from your runbooks, escalation rules, and noise patterns
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Introducing On-Call Copilot - a new agent template in LangSmith Fleet → Triages every alert and investigates root cause across your code and traces → Manages tickets and routes every incident to the right channels → Continuously learns from your runbooks, escalation rules, and noise patterns

LangChain

14,235 просмотров • 1 месяц назад

📊We’ve rebuilt Dashboards in LangSmith to make them more useful for investigation and reporting. Put KPIs next to trends, compare metrics with different units, break traces down by model or user, add notes, and arrange the dashboard freely.
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📊We’ve rebuilt Dashboards in LangSmith to make them more useful for investigation and reporting. Put KPIs next to trends, compare metrics with different units, break traces down by model or user, add notes, and arrange the dashboard freely.

LangChain

15,364 просмотров • 3 дней назад

🚀 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:
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🚀 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

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🔥 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:
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🔥 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

45,405 просмотров • 1 год назад

We’re making LangSmith Sandboxes available to try for free. Start today:
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We’re making LangSmith Sandboxes available to try for free. Start today:

LangChain

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Today we’re announcing FLUX.1 Kontext in LTX Studio. We’ve partnered with BlackForestLabsAI - Unofficial to bring their new state-of-the-art image model directly into your workflow. Here’s what it can do 👇
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Today we’re announcing FLUX.1 Kontext in LTX Studio. We’ve partnered with BlackForestLabsAI - Unofficial to bring their new state-of-the-art image model directly into your workflow. Here’s what it can do 👇

LTX.io

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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:
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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

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introducing annotation mode in AI Studio refining your app should be as easy as pointing at what you want to change: simply highlight any component, button or text in your app and Gemini will handle the heavy lifting
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introducing annotation mode in AI Studio refining your app should be as easy as pointing at what you want to change: simply highlight any component, button or text in your app and Gemini will handle the heavy lifting

Google AI Studio

122,249 просмотров • 9 месяцев назад

Introducing Gemini CLI extensions, a new framework that allows you to customize Gemini CLI and connect it to the tools you use most—all from the command line. No more context-switching. Start using your favorite tools directly in your workflow today →
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Introducing Gemini CLI extensions, a new framework that allows you to customize Gemini CLI and connect it to the tools you use most—all from the command line. No more context-switching. Start using your favorite tools directly in your workflow today →

Google Cloud Tech

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