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Build your app with LangChain. Build context-aware, reasoning applications with LangChain’s flexible framework that leverages your company’s data and APIs. Future-proof your application by making vendor optionality part of your LLM infrastructure design. Learn more about LangChain.
LangChain is a framework for developing applications powered by large language models (LLMs). LangChain simplifies every stage of the LLM application lifecycle: Development: Build your applications using LangChain's open-source building blocks, components, and third-party integrations.
🤔 What is LangChain? LangChain is a framework for developing applications powered by large language models (LLMs). For these applications, LangChain simplifies the entire application lifecycle: Open-source libraries: Build your applications using LangChain's open-source building blocks, components, and third-party integrations .
architecture to get you from prototype to production. An all-in-one developer platform for every step of the llm-powered application lifecycle, whether you’re building with LangChain or not.
LangChain is an open source orchestration framework for the development of applications using large language models (LLMs). Available in both Python- and Javascript-based libraries, LangChain’s tools and APIs simplify the process of building LLM-driven applications like chatbots and virtual agents .
6 days ago · LangChain provides a standard interface for chains, lots of integrations with other tools, and end-to-end chains for common applications.
LangChain is the platform developers and enterprises choose to build gen AI apps from prototype through production.
LangChain.js provides a few templates and examples showing off generative UI, and other ways of streaming data from the server to the client, specifically in React/Next.js. You can find the template for generative UI in the official LangChain.js Next.js template .
LangChain is a framework for developing applications powered by language models. It enables applications that: Are context-aware: connect a language model to sources of context (prompt instructions, few shot examples, content to ground its response in, etc.)
How Factory used LangSmith to automate their feedback loop and improve iteration speed by 2x. How Factory AI uses LangSmith to debug issues and close the product feedback loop, resulting in a 2x improvement in iteration speed. By LangChain 4 min read.
