✨ The Definitive Guide to Testing LLM Applications by LangChain ✨ Reviewing LLM app responses can be a time-consuming and daunting process, from defining criteria for style and accuracy, to spotting new regressions. After partnering with hundreds of companies to enhance their GenAI apps, we've put together a comprehensive guide of best practices for testing throughout the development lifecycle. In this guide, you'll learn how to: • Design a self-correcting RAG or code generation application • Build a dataset for your test suite • Test agents and RAG performance ... and much more! 👉 Get the guide here: https://lnkd.in/eX6yA6H4
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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🕙Using LangChain and Tecton to Personalize LLM Applications with Up-to-Date Context Everyone wants personalized LLM responses! In to achieve this, the LLM needs to be passed up-to-date information Tecton + LangChain can help you do this https://lnkd.in/gKCBQ8-M
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We've teamed up with Cerebras Systems to bring you lightning-fast LLM workflows ⚡️ With our latest integration, you can build and deploy faster than ever. Cerebras supports 1,800t/s for Llama3.1-8b and 450t/s for Llama3.1-70b. Try out the Cerebras Module on LangChain: https://lnkd.in/gXjqmpNJ Check out the demo app: https://lnkd.in/gcVQfAsG
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Advanced RAG Techniques: Elevating Your Retrieval-Augmented Generation Systems 🚀 There are a lot of different RAG techniques out there. Nir Diamant has put together a ✨fantastic✨ repo implementing a lot of these. Plus - a community Discord! https://lnkd.in/gia_ktaF
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💸 Welcome to the Financial Agent UI! Combining Vercel's AI SDK and LangChain agents to deliver real-time stock data and financial insights via Polygon's API. Super cool to see generative AI in finance! Check it out 👇 https://lnkd.in/gwPm_UF2
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📰✒️CiteME Can Language Models accurately cite scientific claims? CiteME is a benchmark designed to test the abilities of language models in finding papers that are cited in scientific texts. Find more details and the preprint and code here: https://lnkd.in/gZmCMbn4
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🧠 Deep Dive Alert: GraphRAG Analysis, Part 1 Exploring how Neo4j’s indexing can elevate vector database performance in RAG tasks. From context relevancy to answer faithfulness, see how Neo4j stacks up against FAISS https://lnkd.in/gt6H79up
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⭐️Community Content 🚀 RAG Basics to Intermediate Dive deep into RAG techniques—from the basics to more advanced topics like query transformation, construction, and routing. Perfect for enhancing your retriever game! https://lnkd.in/gEDGFQ7R
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🔍 Exploring GraphRAG with Neo4j and LangChain 📝 Check out Tomaz Bratanic's deep dive into "From Local to Global" GraphRAG implementation Covers how to extract entities & relationships from text and summarize graph structures into natural language. https://lnkd.in/gPE3BNR3
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📊 Insights from 10k+ "Ask HN: Who Is Hiring" Comments By structuring over 10k HN comments with GPT-4o and LangChain, Tamer C uncovers job market trends! How areremote work, visa sponsorship, and tech stacks like PostgreSQL and React evolving? https://lnkd.in/eii65Esj
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