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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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124,090 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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Introducing Build That Idea A platform that lets anyone launch their own AI agent in 60 seconds - Define your Agent - Choose a base LLM (OpenAI, Claude, DeepSeek, etc.) - Upload knowledge base - Set pricing and start making money Join the waitlist below

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I’ve created a full-stack financial analysis bot that can query both text + embedded tables across multiple SEC 10Ks 📊🤖 It’s made possible with `create-llama` scaffolding + LlamaIndex 🦙 advanced RAG, and I’m sharing the full template below for you to clone! It’s more sophisticated than a basic RAG setup: 🦾 Unstructured to parse embedded tables into a node graph 🦾 Recursive retriever to retrieve/query embedded tables + text 🦾 An agent to do chain of thought + document comparisons 🦾 Custom callback to stream intermediate function calls to the UI Our goal is to make building full-stack advanced RAG as easy as possible. Created a repo to host this template + future templates here: Want to submit a project? We’d love contributions! 🙌 One caveat: - Right now the index is lazily built/cached during the first query, we’re working to decouple the ingestion process - Check out `create-llama` if you haven’t already:
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I’ve created a full-stack financial analysis bot that can query both text + embedded tables across multiple SEC 10Ks 📊🤖 It’s made possible with `create-llama` scaffolding + LlamaIndex 🦙 advanced RAG, and I’m sharing the full template below for you to clone! It’s more sophisticated than a basic RAG setup: 🦾 Unstructured to parse embedded tables into a node graph 🦾 Recursive retriever to retrieve/query embedded tables + text 🦾 An agent to do chain of thought + document comparisons 🦾 Custom callback to stream intermediate function calls to the UI Our goal is to make building full-stack advanced RAG as easy as possible. Created a repo to host this template + future templates here: Want to submit a project? We’d love contributions! 🙌 One caveat: - Right now the index is lazily built/cached during the first query, we’re working to decouple the ingestion process - Check out `create-llama` if you haven’t already:

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