💻LLMs for Application Developers Tom Newby of ProcurePro presented a talk "LLMs for Application Developers" at BrisPHP in July 2024 The talk discusses using LangChain.js + LangSmith to solve product problems with LLMs https://lnkd.in/g5WXKskt
About us
We're on a mission to make it easy to build the LLM apps of tomorrow, today. We build products that enable developers to go from an idea to working code in an afternoon and in the hands of users in days or weeks. We’re humbled to support over 50k companies who choose to build with LangChain. And we built LangSmith to support all stages of the AI engineering lifecycle, to get applications into production faster.
- Website
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langchain.com
External link for LangChain
- Industry
- Technology, Information and Internet
- Company size
- 11-50 employees
- Type
- Privately Held
Employees at LangChain
Updates
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⭐️Cool project built on LangChain: Jenova An all-in-one AI assistant that intelligently selects the best models and tools for your tasks. Powered by GPT-4o, Claude 3.5, and Gemini 1.5 Excited to see systems become multi-model! https://www.jenova.ai/
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🧱Building Text-to-Teradata SQL Agents with LangChain and Amazon Bedrock Learn how to develop fully autonomous text-to-Teradata SQL agents while addressing critical considerations around security, operational efficiency, and financial governance. https://lnkd.in/gePkEHRi
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🕸️Implementing GraphReader with Neo4j and LangGraph Lot's of people have been asking for GraphRAG with LangGraph... and @tb_tomaz delivers! A 23(!!) minute read on implementing the graph reader paper with Neo4j and LangGraph 👏 https://lnkd.in/gzEJWdpE
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🥼Agentic customer service This OSS repo implements a customer service bot for various tasks of a medical clinic - get info, cancel, reschedule, check doctor availability, check results, etc Customer service is a huge use case for LangGraph https://lnkd.in/ghftFZhg
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Yesterday, Komodo Health launched their AI assistant. It uses Llama, Mistral & Phi, orchestrated by LangGraph This is a real world example of AI agents being deployed RIGHT NOW in highly regulated industries. Takes work, but its possible 👏👏 https://lnkd.in/eusrZbQw
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LangChain reposted this
🎌 Join us for our first Japan meetup in Tokyo on Saturday, October 26! 🎌 ✨ LangChain and Rakuten invite you to join us for a morning meetup in Japan to discuss the future of AI agents. ✨ Enjoy snacks, drinks, and engaging discussions. Please note that presentations will be given in English and this event is fully in-person. Thank you for your continued partnership Yusuke K.! You're pushing the industry forward 🚀! RSVP here ➡ https://lu.ma/4oz6cvk7
LangChain x Rakuten: AI Agents Meetup in Japan · Luma
lu.ma
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🎌 Join us for our first Japan meetup in Tokyo on Saturday, October 26! 🎌 ✨ LangChain and Rakuten invite you to join us for a morning meetup in Japan to discuss the future of AI agents. ✨ Enjoy snacks, drinks, and engaging discussions. Please note that presentations will be given in English and this event is fully in-person. Thank you for your continued partnership Yusuke K.! You're pushing the industry forward 🚀! RSVP here ➡ https://lu.ma/4oz6cvk7
LangChain x Rakuten: AI Agents Meetup in Japan · Luma
lu.ma
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🕸️ LangGraph Templates 🕸️ It's never been easier to start creating your own agentic applications. LangGraph Templates are a collection of reference architectures that you can clone, configure and then easily modify. 📝 Read more in the blog post: https://lnkd.in/g5kGqnPn 🌐 See the list of curated templates: https://lnkd.in/gVCSehXN
Launching LangGraph Templates
blog.langchain.dev
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LangChain reposted this
🍃🦜 LangGraph.js now integrates with MongoDB! Use them together to build agentic AI applications in JavaScript that have: Efficient data management: MongoDB allows AI agents to access relevant information quickly using vector search. Contextual conversations: LangGraph.js ensures your AI agent maintains conversation history, persisting context between interactions with a MongoDB-backed checkpointing system. Human-in-the-Loop workflows: Easily handle complex interactions with LangGraph.js’s state management and ability to add human input (e.g. editing or interrupting an action) when needed. Jesse Hall has prepared some fantastic guides to get you started: ✍️ Read how to build an AI agent with LangGraph.js and MongoDB: https://lnkd.in/geYXrxU3 📽️ Check out the video tutorial: https://lnkd.in/geCjDHGF