LangChain

Another year, another leap in LLM app development! 🪄 Our new 2024 LangChain State of AI report uncovers key trends in how developers are building LLM apps. In 2024, we’ve seen a shift from retrieval workflows to multi-step, agentic applications. 🤖 Open-source models are also gaining traction as devs seek more customizable infrastructure. Here's where the AI ecosystem is headed, based on data from LangSmith.👇 Read the full report: https://lnkd.in/g5yd92QW

🚗Steer One of the most common questions we get is around how to stream back from an application Steer is an LLM token streaming server for a grammar assistant app Can serve as an inspiration for LLM token streaming with OpenAI SDK and FastAPI. https://lnkd.in/eg8WGZB9

✒️AgentWrite LangGraph This project leverages LangGraph to create a powerful tool for automated content generation. It breaks down complex writing tasks into manageable steps, including planning, writing, and refining content https://lnkd.in/gSNsATCd

🧱Building Knowledge Graphs with LLM Graph Transformer A deep dive into LangChain’s implementation of graph construction with LLMs If you want to try out GraphRAG - you first have to build the graph. This post dives into one way to do so https://lnkd.in/eHVCy-JB

✈️AI Travel Agent This tutorial dives into implementing the Plan-and-Execute architecture using LangGraph Learn how to create a sophisticated AI agent that can plan trips, adapt to new information, and provide comprehensive travel advice https://lnkd.in/g5cCTbrm

🔎AI Enterprise Case Study Analyzer An AI system designed to analyze any type of website content and generate structured reports using Claude 3.5 Sonnet API and Firecrawl Currently configured for enterprise AI case studies https://lnkd.in/ghTwRhBe

🚗How Uber uses LangGraph to improve developer productivity Great talk from Adam and Ty at the DPE Summit on how Uber has approached transforming Uber's developer productivity with AI Excited to see LangGraph featured as a key component https://lnkd.in/gDSJx444

🔐 Custom Authentication & Access Control for LangGraph Platform Build production-grade auth into your LangGraph deployments, no other backend required. Available now for Python deployments in Cloud and self-hosted environments. ✍ Blog: https://lnkd.in/gc4ecUPd 📺 Video walkthrough: https://lnkd.in/gsb-hPpr Learn More 📚 Tutorial trilogy: 1) Authenticate: https://lnkd.in/gfM7wNxk 2) Authorize: https://lnkd.in/g7uQvTQ7 3) Serve with OAuth2: https://lnkd.in/g8JrAKDM 💻 Full-stack template: https://lnkd.in/gXae7uDf

✨ How We Built It: Character.AI ✨ In this video, James Groeneveld (Engineering at Character.AI) and Harrison Chase (LangChain CEO) take you behind the scenes of Character.AI’s journey to scale LLM generation to handle 30,000 queries per second. Hear the learnings from the first innings of consumer AI! Watch it here ➡️ https://lnkd.in/gSQCA9Nv

I had the priveledge of chatting with @groeneyy about how they scaled Character AI Lots of learnings in this ~30 min chat... along with some anecdotes (like how "Grilled Chessus" almost took down Character's servers) Watch it here on YouTube! https://lnkd.in/gKG64VV4