LangChain

We asked, you answered — our State of AI Agents Report is here! 🤖✨   We surveyed over 1300 industry professionals— from developers to business leaders — on how they are using AI agents in their everyday work, and the results are in. A majority of orgs have agents in production (or plan to soon). Yet, performance quality remains the biggest hurdle to achieving reliable results from AI agents. AI agents from Cursor, Perplexity, and Replit have also become fan favorites and are redefining productivity — from code generation to advanced query search. Read the full report ➡️ https://lnkd.in/gbybb9aH

Introducing diff view in LangSmith's Prompt Hub 🔍 Easily compare changes between any two commits, review updates, or revert to earlier versions. Go to the Commits tab, toggle 'diff,' and track your prompt evolution — so you can iterate quickly and with control. Learn more in the docs: https://lnkd.in/grfjsuN7

🚨 Don’t miss this today! Join experts from Confluent and Elastic as they dive into: ✅ Vector embedding & search for RAG ✅ Real-time inference pipeline workflows ✅ Preventing LLM hallucinations With Apache Flink, Elasticsearch, OpenAI, & LangChain 🚀 📅 Sign up for the virtual talk: https://lnkd.in/gKs88BQE

With the LangChain + Neo4j integration, you can now build GenAI apps on structured and unstructured data with their graph database. The LangChain-Neo4j partner package enables: • Unified retrieval with graph databases (vectors, docs, tables as nodes & edges) • Text-to-query generation via Cypher query language • Seamless chat memory storage to maintain context Learn more: https://lnkd.in/gT-GUd9D

Realm-X Assistant is an AI-powered copilot by AppFolio that is transforming real estate by helping property managers save >10 hours a week on day-to-day workflows. See how the AppFolio team: 🔶 Reduced latency by parallelizing workflows with LangGraph 🔶 Boosted accuracy of text-to-data responses 2x 🔶 Monitored and pinpointed production issues with LangSmith ➡️ Read the full story: https://lnkd.in/giRNyC3J

⭐️Community Content Building LangGraph: The Future of AI Agent Development Learn how to implement a self-improving AI using LangGraph. Automate the generate-reflect cycle and create a system that continuously improves its outputs! https://lnkd.in/g9WDP6uP

🦆Docling: Get your documents ready for gen AI Docling parses documents and exports them to the desired format with ease and speed. Easy integration with LangChain! See the integration notebook: https://lnkd.in/gZrYvYuN

🕸️Building a GraphRAG Agent With Neo4j and Milvus This agent combines the power of graph databases and vector search to provide accurate and relevant answers to user queries. In this example, we will use LangGraph, Llama 3.1 8B with Ollama and GPT-4o. https://lnkd.in/eNz3C_Zu

🧠 Brainstormers One of my main use cases for LLMs is brainstorming. This tool enhances your brainstorming experience by offering curated, optimized chains inspired by real-world effective brainstorming techniques. https://lnkd.in/gq2b9rx8

✒️Exploring Open Canvas: The Open Source Alternative to ChatGPT Canvas The "canvas" UX is great for writing text with the assistance of LLMs We've created an open source version of canvas, check out the video below that walks through it https://lnkd.in/gAYYbPh7