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Introducing RAGApp 💫 A no-code interface to configure a RAG chatbot, as dead-simple as GPTs by OpenAI. It’s a docker container that’s easily deployable in any cloud infrastructure. Best of all, it’s fully open-source 🔥 1️⃣ Setup the LLM: Configure the model provider (OpenAI, Gemini) 2️⃣ Setup the data:...

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LlamaIndex 🦙

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123,977 görüntüleme • 2 yıl önce •via X (Twitter)

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Kent Langley profil fotoğrafı
Kent Langley2 yıl önce

@OpenAI that may be the easiest and fastest I have ever been able to create anything that useful in this category. very nice work.

Alignment Lab AI profil fotoğrafı
Alignment Lab AI2 yıl önce

@OpenAI srsly give it a shot vectors are for data science, databases are for databasing

David Alexander profil fotoğrafı
David Alexander2 yıl önce

A solution like this is great, but like the other OS solutions that offer a prebuilt chat interface, like Streamlit, LangChain, Flowise, the interface is well, not the most pretty. It’s great for a quick test and prototype, but I couldn’t imagine anyone putting it into production. Open Chat UI, is an example of something you could actually put into production. IMHO

Alex Avery profil fotoğrafı
Alex Avery2 yıl önce

@OpenAI is there a limit to the size of the knowledge base?

Artur Formella profil fotoğrafı
Artur Formella2 yıl önce

@OpenAI Finally! :)

Houdini profil fotoğrafı
Houdini2 yıl önce

@OpenAI For extended functionality. How about if I want to get the LLM to gather and digest data for me from a site that has an API access for example a blockchain site. How do I go about that?

Bryce Amacker profil fotoğrafı
Bryce Amacker2 yıl önce

@OpenAI @memdotai mem it

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Build a UX for your LLM chatbot/agent that not only includes streaming, but also showcases sources as expandable UI elements 📖🔎, similar to Perplexity! Now possible in one-line of code through create-llama. Amazing work by Marcus Schiesser 💫 Check it out:
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Build a UX for your LLM chatbot/agent that not only includes streaming, but also showcases sources as expandable UI elements 📖🔎, similar to Perplexity! Now possible in one-line of code through create-llama. Amazing work by Marcus Schiesser 💫 Check it out:

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Today we’re excited to feature RAGApp v0.1 - which lets any user construct a multi-agent application 🎨🤖 without writing a single line of code 💫 Add any number of agents that you wish, and assign each agent a role, system prompt, and a set of tools. In this example, use a researcher, analyst, and report generation agent to write a news article. This directly generates a full chat interface where you can ask questions and get back answers with full streaming and sources. Huge shoutout to Marcus Schiesser for working on this! RAGApp: create-llama: If you want finer control, you can define your own agentic workflows through code:

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Want to build an OpenAI chatbot? Use Chatbot UI! It’s a simple, fully-functional chatbot starter kit using Next.js, TypeScript, and Tailwind CSS. Clone it and start building instantly. GitHub:
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Want to build an OpenAI chatbot? Use Chatbot UI! It’s a simple, fully-functional chatbot starter kit using Next.js, TypeScript, and Tailwind CSS. Clone it and start building instantly. GitHub:

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Engineering isn’t just about faster typing; it’s about better thinking. Our team is excited to showcase Gemini 3.1 Pro, our best model for systemic reasoning. Watch as the model handles a complex "Legacy Sync" migration, not by just writing functions, but by identifying architectural risks. That’s the difference between a chatbot and an engineering partner.

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Jerry Liu

131,437 görüntüleme • 2 yıl önce

The LM Arena source and the “anonymous-chatbot-0717” tag reads o3 alpha responses 2025 07 17. O3 Alpha is live in stealth. I have a suspicion that it’s the same model that snatched second in the coding comp, It’s one-shotting every task. Doubt it is the incoming ChatGPT agent; if it were, I feel as if OpenAI would be parading full coding benchmark flexes by now. Just look at this thing one shot a Minecraft replica 👇
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The LM Arena source and the “anonymous-chatbot-0717” tag reads o3 alpha responses 2025 07 17. O3 Alpha is live in stealth. I have a suspicion that it’s the same model that snatched second in the coding comp, It’s one-shotting every task. Doubt it is the incoming ChatGPT agent; if it were, I feel as if OpenAI would be parading full coding benchmark flexes by now. Just look at this thing one shot a Minecraft replica 👇

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We are witnessing a fundamental shift in how software is built. Over the decades, UI was static and predictable. But AI is changing the fundamental nature of the interface. We are moving away from fixed UI and toward a new standard: Generative UI. Generative UI lets agents participate in the UI, not just the conversation. It’s a dynamic participant in the user experience. Depending on the complexity of your app, Generative UI generally falls into three categories: 1. Static (AG-UI): UI is chosen from a fixed set of hand-built components 2. Open-Ended (MCP Apps): agent sends arbitrary content like raw HTML or iframes for total flexibility. 3. Declarative (A2UI): agent and frontend communicate via a structured UI spec for dynamic widgets and forms. The AG-UI Protocol by CopilotKit is the real breakthrough. AG-UI acts as the universal transport layer. It provides the integrations and middleware for every Gen-UI spec, making it trivial to bring dynamic components into your existing app. CopilotKit provides the go-to ecosystem for building agentic applications and is the React client of AG-UI. It is designed to be deeply integrated, allowing developers to bring their own frameworks or protocols to the table. Play around with different types of Generative UI here → Check out the video attached to see Generative UI in action. Appreciate the CopilotKit team for collaborating with me on this deep dive.

Pratham

33,920 görüntüleme • 4 ay önce

OpenAI just dropped the Apps SDK, built on MCP. This is the future of how users will interact with your apps. You won’t need to build a chatbot anymore. OpenAI is the chatbot. You just expose your tools through MCP. Exciting progress toward Jarvis!
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OpenAI just dropped the Apps SDK, built on MCP. This is the future of how users will interact with your apps. You won’t need to build a chatbot anymore. OpenAI is the chatbot. You just expose your tools through MCP. Exciting progress toward Jarvis!

Kent C. Dodds 🏹

152,179 görüntüleme • 8 ay önce

Our new short course, Knowledge Graphs for RAG, is now available! Knowledge graphs are a data structure that is great at capturing complex relationships between data of multiple types. By enabling more sophisticated retrieval of text than similarity search alone, knowledge graphs can improve the context you pass to the LLM and the performance of your RAG applications. In this course, taught by Andreas Kollegger of Neo4j, you’ll - Explore how knowledge graphs work by building a graph of public financial documents from scratch - Learn to write queries that retrieve text and data from the graph and use it to enhance the context you pass to an LLM chatbot - Combine a knowledge graph with a question-answer chain to build better RAG-powered chat systems Sign up here!
3:46

Our new short course, Knowledge Graphs for RAG, is now available! Knowledge graphs are a data structure that is great at capturing complex relationships between data of multiple types. By enabling more sophisticated retrieval of text than similarity search alone, knowledge graphs can improve the context you pass to the LLM and the performance of your RAG applications. In this course, taught by Andreas Kollegger of Neo4j, you’ll - Explore how knowledge graphs work by building a graph of public financial documents from scratch - Learn to write queries that retrieve text and data from the graph and use it to enhance the context you pass to an LLM chatbot - Combine a knowledge graph with a question-answer chain to build better RAG-powered chat systems Sign up here!

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