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  1. 4 hours ago · Features. Next.js App Router. React Server Components (RSCs), Suspense, and Server Actions. Vercel AI SDK for streaming chat UI. Support for OpenAI (default), Anthropic, Cohere, Hugging Face, or custom AI chat models and/or LangChain. shadcn/ui. Styling with Tailwind CSS. Radix UI for headless component primitives.

  2. 1 hour ago · Building RAG Pipelines using LangchainJoin us for an enlightening session on "Building RAG Pipelines using Langchain." Discover how to leverage Langchain to ...

  3. 13 hours ago · Summary User is asking if it’s possible to pull data directly from a source via API without setting up a destination or connection, mentioning Langchain’s Airbyte document loader. Question Hey guys, is it possible to pull data directly from a source via API without setting up a destination or a connection ? I came across Langchain’s Airbyte document loader which seems to be doing that, i’m not quite sure. This topic has been created from a Slack thread to give it more visibility. It w...

  4. 13 hours ago · LangChain initially focused on easy-to-use chains but has evolved to offer more customizable, low-level orchestration frameworks. These tools enable developers to control the cognitive architecture of their applications more effectively. For straightforward chains and retrieval flows, LangChain's Python and JavaScript versions are recommended.

  5. 13 hours ago · Deluxe 4 is a modern trading platform curated with all categories of traders in mind. With an easy to explore and use interface, we built integrity, innovation, and security into a product that is quickly becoming the favorite among traders in over 60 countries. We are happy to help people unleash their true potential while expanding their portfolios in a wide range of digital currencies. FCA REGULATED

  6. 13 hours ago · 使用 LangChain 开发 LLM 应用 00:前言. 在人工智能快速发展的今天,很多开发者都希望能够学习到有关人工智能的相关知识。. 2018 年,OpenAI 推出了名为 GPT 的系列模型。. 该模型实现了将“人工智障”真正变换为“人工智能”。. 这也就是目前最火的 LLM,即大语言 ...

  7. 13 hours ago · LangChain RAG 上册. 一切都要从这张图开始说起,这是RAG的经典图. 涵盖了Question->Translation->Routing->Construction->DB (VectorStore)->Indexing->Documents->Retrieval->Generation->Answer. 今天我们就来一起学习、拆解这张图,经过这次的学习,你会对RAG有深刻的理解。.

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