LangChain 1.1 You can now programmatically access model capabilities and supported features through model.profile. This powers some new features in middleware. One example: SummarizationMiddleware can now dynamically trigger based on the model's available context.
@langchain
-
LangChain Community Jam Session on December 15
By
–
Join our Community Jam Session on Dec 15 (Dec 16 for some APAC zones)! Share your feedback on LangChain 1.0 & 1.1, what’s working, what’s not, and what you love. Your input shapes LangChain’s future! RSVP: https://
luma.com/085nyxmj -
General Purpose Agents: Achieving More with Fewer Tools
By
–
General purpose agents like Claude Code and Manus use remarkably few tools. How? By giving agents access to a computer. With bash and filesystem tools, agents can perform actions without needing specialized bound tools for every task. Skills also offer two key advantages over
-
Agent Skills Now Available in Deep Agents CLI
By
–
Agent skills are now available in the Deep Agents CLI, enabling you to use the large and growing collection of public skills with your agents. In this video we discuss: – What agent skills are and why they’re interesting
– How agents make use of skills
– How you can use skills -
LangChain Seeks Agent Engineering Stack Feedback Survey
By
–
If you're building agents, we want your input on the State of Agent Engineering report. Take 5 mins to share your stack, eval approach, and production blockers. We're analyzing real builder data to publish insights back to the community. Survey: https://
bit.ly/agent-engineer
ing-survey
… -
Deep Agents: Essential Tools and Best Practices Guide
By
–
What are Deep Agents? We break down the key things to know when you’re building an agent to handle more complex tasks: – The 4 essential tools for Deep Agents
– When to use Deep Agents vs LangChain or LangGraph
– Best practices for building Deep Agents Full details in the -
Real Estate Agent Transforms Career to AI Engineer with LangChain
By
–
Check out how Ambassador @gostak_dd leveled up — from real estate agent to AI Engineer — by diving deep into LangChain “How I learned LangChain and became an AI Engineer”
-
Bangalore AI Meetup: Building for the Agentic Era with LangChain
By
–
Join the community in Bangalore to explore how to build for the Agentic Era. We’re sharing an AI meetup organized by @thesysdev , @knacklabs2406 , LangChain Ambassador @ravikiran_16 , and hosted by @Razorpay — featuring technical sessions, real-world insights from production
-
Production-Ready AI Travel Agent with LangChain and Streamlit
By
–
AI Travel Agent Guide A production-ready Streamlit travel assistant built with LangChain agents, featuring weather info, search capabilities, and video integration. The guide covers API setup, deployment options, and performance optimization. Explore the guide
-
LangChain Deep Dive: Build AI Applications with Hands-On Tutorial
By
–
LangChain Deep Dive Eric Burel shows developers how to build AI applications using the LangChain ecosystem in this hands-on tutorial. Key features:
– Chain & agent construction
– LangGraph orchestration
– LangSmith monitoring Watch now: https://
youtu.be/0ImjWIo5fyM
Made by