LangChain

LangChain and LangGraph 1.0s We’ve heard your feedback loud and clear. Today, we’re launching 1.0 versions (in both Python and Typescript) of LangChain and LangGraph, the two most popular agent frameworks, based on what the community has been asking for. • LangGraph: Low-level agent orchestration with built-in durable execution, memory, streaming, and human in the loop • LangChain: Revamped to be more flexible — with a new `create_agent` template to build agents quickly, middleware for customizing behavior, and standard content blocks that work across any model provider We’ve also unified all our docs (Python and TypeScript languages, as well as `langchain`, `langgraph`, and LangSmith) at docs.langchain.com. We know this has been a long time coming! Read the full breakdown in this blog ➡️ https://lnkd.in/g6GP_unz

Thanks to these investors that also participated in the round! We're proud to partner with you. ServiceNow Ventures, Workday Ventures, Cisco Investments, Datadog Ventures, Databricks Ventures, and Frontline Ventures. https://lnkd.in/ezTFxHJJ

We’ve raised a $125M Series B at a $1.25B valuation to build the platform for agent engineering. Thank you to our investors (IVP, Sequoia Capital, Benchmark , Amplify Partners, Sapphire Ventures, CapitalG, and more) for your belief in us, and to our customers like Replit, Clay, Vanta, Cloudflare, Rippling, Cisco, Workday, and many more, for your trust and feedback along the way. Over the past few years, we’ve come to believe building agents requires a new discipline. We call it agent engineering, or the iterative process of refining non-deterministic LLM systems into reliable experiences. It combines aspects of product, engineering, and data science thinking, creating a way of working that produces more capable, more reliable agents. The space never stops, and neither do we. Since the launch of `langchain`, developers have told us they want more control, visibility, and flexibility when building agents. In rapid response, we built: • LangChain: Completely revamped in 1.0 with a core agent template and middleware for flexibility • LangGraph: A lower-level orchestration framework and runtime • LangSmith: Our platform for taking agents to production with observability, evaluation, and deployment This week, we’re launching new capabilities to help you iterate even faster: a new Insights Agent for aggregating usage patterns on production data, major 1.0 releases of LangGraph and LangChain, and our first no code text-to-agent builder, now in private preview. Read the full story and see what’s new: https://lnkd.in/gKVYYMUm

We're hosting an intimate evening in San Francisco to celebrate LangChain's 3rd birthday and share our biggest product releases of the year. If you're an AI builder and want to connect with the community (plus get an early look at what we've been working on), join us. 👉 RSVP: https://luma.com/7baj9rx5

🎨 AI-Powered Canvas Template Brandon from CopilotKit released a production template for AI canvas apps. Built with LangGraph for agent coordination, it delivers real-time UI-AI synchronization through a Python-Next.js stack. Watch the walkthrough: https://lnkd.in/gkDVTwQH

🤖 🧠 Deep Agents Evolution A breakthrough in AI architecture enabling agents to scale from 15 to 500+ steps through advanced planning and memory systems, revolutionizing how AI handles complex tasks. Learn more about this evolution 🔍 https://lnkd.in/gcM82m2n

📚🤖 Article Explainer An AI document analysis tool that breaks down complex technical articles using LangGraph's Swarm Architecture. The system uses multiple agents to provide interactive explanations and insights through natural language queries. Check it out on GitHub 🔍 https://lnkd.in/g6NjHi_z

📚🔍 Event Deep Research An AI system that transforms historical research into structured timelines, automatically extracting and organizing biographical data from multiple sources into chronological JSON format. Check out the project 🎯 https://lnkd.in/gUY7PbJb

🧠 LangGraph × cognee Integration cognee brings persistent memory to LangGraph agents, letting AI applications maintain context across sessions while seamlessly working with existing LangGraph features. Check out how to add memory to your agents 🔗 https://lnkd.in/gAUc2S_s

Launch Week is right around the corner — and we're kicking it off in person! We'll be hosting meetups in San Francisco, Boston, and NYC to celebrate LangChain's 3rd birthday and share what's coming next during Launch Week. Come hang with the team, connect with our amazing community of builders shipping agents in production, and get the inside scoop on what's happening during Launch Week. Expect great food, drinks, and good conversation. It’s going to be an exciting evening! 📍 Pick your city and RSVP: 🌉 SF: https://luma.com/7baj9rx5 🦪 Boston: https://luma.com/135zbg4u 🗽 NYC: https://luma.com/f5jrv7t6 See you there 👋