LangChain

🎉🎂 LangChain turns 2!

Two years ago, we launched a Python package called `langchain` to help developers build LLM applications that could reason. Today, we're still chasing that same mission — and as the generative AI ecosystem has evolved, we've evolved too.

LangChain has grown into a fuller ecosystem with LangSmith (for LLM testing & observability) and LangGraph (for building reliable agents). Our technology is now more stable, comprehensive, and production-ready.

✨ By the numbers, we've hit:
• 4,000+ contributors (doubled from last year)
• 130 million+ downloads and 132k apps powered by LangChain
• 700+ integrations (from just 3 providers at launch)

Thank you to our incredible partners, contributors, and LangChain community for being part of this journey. We're just getting started ❤️

➡️ Read our 2nd anniversary reflection: https://lnkd.in/gdBgdHYH

⭐️Want an open source version of OpenAI's Operator?

There's a great open source project called Browser Use that does similar things (and more) while being open source

Allows you to plug in any model you want

Love to see open source leading the way🚀

https://lnkd.in/dFG97Ycd

🚀 Pre-release of LangChain v0.2

The pre-release of LangChain v0.2 is out today, paving the way towards greater stability + security.

Read the full blog here: https://lnkd.in/gPWCkEGi

With the help of our users and developers, we've iterated on our stable library version and have decoupled the `langchain` package from `langchain-community` to make `langchain` more lightweight, focused, and secure.

With v0.2, you can look forward to:
• Versioned docs with improved discoverability, so you can match information and instructions with your minor version
• LangGraph as the recommended way to build agents, which makes it easy to define cycles and built-in memory — and then customize and modify them

Since our last v0.1 release, we've also made improvements to:
• Standard chat model features, including standardized tool calling support and an interface for structuring output
• Async support for many core abstractions
• Streaming support with a new Event Streaming API
• Partner packages for 20+ providers across Python and JavaScript packages

Thank you to our community for helping us build better and more reliably! 🤗

👂Give your feedback: https://lnkd.in/gKeZ--um

🤖GenAI Career Assistant: A Multi-Agent Approach

Features: personalized job search, custom cover letters, company research, resume analysis, interactive UI

Uses a multi-agent architecture (LangGraph) with six different agents

https://lnkd.in/gbjnGaUV

Fully local agents with Llama3.1

With the release of Llama3.1, building agents that run reliably & locally (e.g., on your laptop) is now more feasible.

The video below shows how to build reliable local agents using LangGraph and Llama3.1-8b from scratch. We build a simple corrective RAG agent with Llama3.1-8b, and compare its performance to larger models, like Llama3-70b and GPT-4o.

In our example, we find that Llama3.1-8b performs on par with much larger models, with only a slight increase in latency.

📽️ Video:
https://lnkd.in/gsMc6XJp
📓 Code:
https://lnkd.in/gCSdn6X6

🛠️ AI Agent Service Toolkit

An open-source framework simplifying AI agent deployment. Built with LangGraph, FastAPI, and Streamlit to help developers quickly launch production-ready AI services.

Explore the toolkit 👉 https://lnkd.in/gu8wxm3C