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Introducing NotebookLlama - an open-source version of NotebookLM! 📓🦙 NotebookLlama is a full implementation of NotebookLM that includes all the capabilities that makes it so great for researchers+business users: ✅ Create a knowledge repository of documents. Has likely higher accuracy than NotebookLM since it’s using LlamaCloud under the hood... for high-quality parsing/extraction over complex docs. ✅ Generate summaries and knowledge graph mind-maps 🤯 ✅ Generate podcasts thanks to ElevenLabs 🗣️ ✅ Agentic chat with docs and view metrics with OpenTelemetry This all lives within an open-source repo so you can clone/modify at will to swap in your own components! Huge shoutout to Clelia Bertelli (🦙/acc) for leading this. Repo: LlamaCloud helps power the parsing/ingestion. You can always use your own stuff too, but in the meantime you can check out LlamaCloud here:show more

Jerry Liu

75,447 subscribers

137,734 просмотров • 11 месяцев назад •via X (Twitter)

Здоровье и велнес Наука и технологии Образование

Anya Rossi• Live Now

Private livecam show

Комментарии: 11

Фото профиля Josue

Josue11 месяцев назад

Why do open-source versions always have to look so bad?

Фото профиля Mobile Scanner

Mobile Scanner11 месяцев назад

Scan any documents, convert images into text, PDF files, etc. 👍

Фото профиля Ed Choudhry

Ed Choudhry11 месяцев назад

@Scobleizer Here’s the new YC batch lol

Фото профиля eimen

eimen11 месяцев назад

man, if you'd improve the UIs of your demos, adoption would be crazy

Фото профиля Peter Wilczynski

Peter Wilczynski11 месяцев назад

@Scobleizer Does it generate real podcasts (eg can I open them in my podcast app)?

Фото профиля Nikhil Chaudhari

Nikhil Chaudhari11 месяцев назад

This is amazing Jerry!

Фото профиля psy

psy11 месяцев назад

Hi Jerry I’m making a react agent as code assistant, the aim is for the agent to understand the repo and it’s md documentations. I have summary, vector and some other tools - in your opinion what’s the best way to optimise this so the agent picks the most relevant tools? Thanks ☺️

Фото профиля Shubham Saboo

Shubham Saboo11 месяцев назад

Turn any LLM into a real-time voice AI agent. Unmute wraps a LLM into speech-to-text and text-to-speech models, while preserving the reasoning and tool calling capabilities. 100% Opensource.

Фото профиля Peter Steinberger

Peter Steinberger11 месяцев назад

Telling the agent to keep track of the work in a markdown is so effective, especially once you automated the loop that it can work for hours.

Фото профиля elvis

elvis11 месяцев назад

Context Engineering Guide I'm writing a detailed guide on context engineering for AI devs. v1 is out now! (bookmark it) I use a concrete deep research multi-agent example to show what context engineering involves.

Фото профиля Trae

Trae11 месяцев назад

We’ve open-sourced Trae-Agent. You can all `git clone` `cd trae-agent` now

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🦙 Since you loved NotebookLlaMa, our open-source, LlamaCloud-backed NotebookLM alternative, we decided to give you more features! In the latest release you can: 📊 Extract and download images and tables from your files, and interactively visualize all tabular data ✅ Chat with your document and verify immediately everything that AI is saying about it, using the new claim verification and citation finding functionality 👇 Watch the video below for a full demo of the new functionalities 👩‍💻🧑‍💻 There is also a bonus: thanks to the community effort and contribution, you can now customize the embedding model you want to use to build the LlamaCloud index, through a textualize.io CLI! ⭐ Star NotebookLlaMa on GitHub: 🦙☁️ Sign-up for LlamaCloud and test our awesome products: 📚 Learn more about LlamaCloud:

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LlamaIndex 🦙

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We built LobsterX 🦞, an OpenClaw🦞 specialized for document work on your computer. It uses high-accuracy document parsing, extraction, classification through LlamaCloud, meaning it can comb through complicated PDFs (with scans, tables, diagrams) and extract out 100% accurate context! It can run as a Telegram bot and is built on top of agentfs (Turso) as a file system. Big shoutout to Clelia Bertelli (🦙/acc). This is a fun project inspired by OpenClaw🦞’s success, and besides being a fun tool to use, it can be a great reference for building your own generalized coding agents! Readme: LlamaCloud:

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Jerry Liu

27,071 просмотров • 4 месяцев назад

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Jerry Liu

20,413 просмотров • 10 месяцев назад

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Jerry Liu

255,997 просмотров • 3 месяцев назад

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Jerry Liu

57,827 просмотров • 11 месяцев назад

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LlamaIndex 🦙

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We're excited to launch HyperBookLM. The open-source NotebookLM with web-agents. Simply drop URLs, PDFs & Txt files and, - Ask questions across all your sources - Create structured mind maps - Export to slides in one click - Generate audio summaries you can listen to Open-source & Powered by Hyperbrowser.

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Hyperbrowser

68,005 просмотров • 6 месяцев назад

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We’re excited to officially launch LlamaParse, the first genAI-native document parsing solution. Not only is it better at parsing out images/tables/charts 📊📈 than virtually every other parser, it is now steerable through natural language instructions - output the document in whatever format you desire! It is also the only parsing solution that seamlessly allows you to build accurate RAG over complex documents, free of hallucinations 🔥 We launched it in private preview a few weeks ago and hit 2k users, 1M total PDF pages parsed. And now it’s better than ever. LlamaParse contains the following killer features: ✅ SOTA table/chart extraction ✅ Seamless integration with LlamaIndex 🦙 advanced RAG/agents ✅✨ Natural language Parsing Instructions ✅✨JSON mode and image extraction ✅✨Support for ~10 document types (.pdf, .pptx, .docx, .xml) and more Our pricing is simple: 1k free per day, and additional pages at 0.3c a page, or $3 for 1k pages. If you want advanced document RAG and/or private deployments, come get in touch with us to chat about LlamaCloud. Check out our full blog post here: LlamaParse client repo: Signup at 🦙☁️: Come talk to us:

LlamaIndex 🦙

143,123 просмотров • 2 лет назад

HyperbookLM - an open-source NotebookLM alternative with a web agent. You can add URLs and it browses, reads, and remembers everything. Then ask questions across all your sources, generate audio summaries, create mind maps, or export to slides. Powered by Hyperbrowser and GPT-5.2. Coming soon as open-source.

HyperbookLM - an open-source NotebookLM alternative with a web agent. You can add URLs and it browses, reads, and remembers everything. Then ask questions across all your sources, generate audio summaries, create mind maps, or export to slides. Powered by Hyperbrowser and GPT-5.2. Coming soon as open-source.

AshutoshShrivastava

45,539 просмотров • 6 месяцев назад

GitHub + Cursor is just INSANE GitHub has 28 million open-source projects that anyone can fork and build a new product So I built a new product: Repo to Docs The Agent will scan entire GitHub repo, analyze all files and create a knowledge base (docs) for AI coding tools: ↓

GitHub + Cursor is just INSANE GitHub has 28 million open-source projects that anyone can fork and build a new product So I built a new product: Repo to Docs The Agent will scan entire GitHub repo, analyze all files and create a knowledge base (docs) for AI coding tools: ↓

CJ Zafir

123,037 просмотров • 1 год назад

Building “RAG 2.0” is just making Claude Code running over your filesystem 🤖🗂️ To make this work well, you need to solve three things 1️⃣ Virtualize your filesystem to prevent the agent from messing stuff up. AgentFS by Turso is a nice example of how you can give the agent access to a copy of all your files without messing up your raw data. 2️⃣ Parse unstructured documents like PDFs, pptx, Word into an LLM-ready format. Agentic OCR solutions like LlamaParse can help here 3️⃣ Creating an agentic loop with human-in-the-loop. If you want to control the agent implementation instead of using Claude Code out of the box, you can use LlamaIndex 🦙 workflows to help orchestrate these long-running agent tasks. Shoutout Clelia Bertelli (🦙/acc), check it out! Blog: Repo:

Building “RAG 2.0” is just making Claude Code running over your filesystem 🤖🗂️ To make this work well, you need to solve three things 1️⃣ Virtualize your filesystem to prevent the agent from messing stuff up. AgentFS by Turso is a nice example of how you can give the agent access to a copy of all your files without messing up your raw data. 2️⃣ Parse unstructured documents like PDFs, pptx, Word into an LLM-ready format. Agentic OCR solutions like LlamaParse can help here 3️⃣ Creating an agentic loop with human-in-the-loop. If you want to control the agent implementation instead of using Claude Code out of the box, you can use LlamaIndex 🦙 workflows to help orchestrate these long-running agent tasks. Shoutout Clelia Bertelli (🦙/acc), check it out! Blog: Repo:

Jerry Liu

55,620 просмотров • 6 месяцев назад

Introducing LlamaCloud 🦙🌤️ Today we’re thrilled to introduce LlamaCloud, a managed service designed to bring production-grade data for your LLM and RAG app. Spend less time data wrangling and more time on application logic. Launching with the following components: 1️⃣ LlamaParse 📑: a proprietary parser designed to be really really good at complex documents with embedded tables. Build advanced RAG over semi-structured PDFs, and ask questions that simply aren’t possible with the naive stack. Available publicly day 1 🔥 2️⃣ Managed Ingestion/Retrieval API ⚙️: An API letting you easily ingest/retrieve data from data sources. Opening up in private beta to select enterprises. We’re excited to be joined by launch users, partners, and collaborators: Mendable POC MongoDB Qdrant NVIDIA + some awesome hackathon projects at the LlamaIndex 🦙 hackathon Check out our FULL blog post on LlamaCloud and LlamaParse: LlamaParse Client Repo: Signup for a LlamaCloud account to use LlamaParse: Interested in the broader LlamaCloud offering? Come talk to us: Also we have a slick new website 🌐:

Introducing LlamaCloud 🦙🌤️ Today we’re thrilled to introduce LlamaCloud, a managed service designed to bring production-grade data for your LLM and RAG app. Spend less time data wrangling and more time on application logic. Launching with the following components: 1️⃣ LlamaParse 📑: a proprietary parser designed to be really really good at complex documents with embedded tables. Build advanced RAG over semi-structured PDFs, and ask questions that simply aren’t possible with the naive stack. Available publicly day 1 🔥 2️⃣ Managed Ingestion/Retrieval API ⚙️: An API letting you easily ingest/retrieve data from data sources. Opening up in private beta to select enterprises. We’re excited to be joined by launch users, partners, and collaborators: Mendable POC MongoDB Qdrant NVIDIA + some awesome hackathon projects at the LlamaIndex 🦙 hackathon Check out our FULL blog post on LlamaCloud and LlamaParse: LlamaParse Client Repo: Signup for a LlamaCloud account to use LlamaParse: Interested in the broader LlamaCloud offering? Come talk to us: Also we have a slick new website 🌐:

LlamaIndex 🦙

141,236 просмотров • 2 лет назад

I vibe-coded an AI agent for making presentations 🤖🖼️ - accessible to everyone and open-source! You can upload both your context files, as well as a style template (a file that captures the style of the presentation you want to create). Then you launch a prompt and watch the agent one-shot your presentation. After the presentation is generated, you can edit the text inline, chat with the agent to add/modify/delete slides, and export to Powerpoint or PDF. Built with Claude Code, powered by Claude Agent SDK + LlamaParse. Hosted on Vercel/Render. To use it, you do need to specify your LlamaCloud API key and Anthropic API key (see below). App: Repo: Sign up to LlamaCloud:

I vibe-coded an AI agent for making presentations 🤖🖼️ - accessible to everyone and open-source! You can upload both your context files, as well as a style template (a file that captures the style of the presentation you want to create). Then you launch a prompt and watch the agent one-shot your presentation. After the presentation is generated, you can edit the text inline, chat with the agent to add/modify/delete slides, and export to Powerpoint or PDF. Built with Claude Code, powered by Claude Agent SDK + LlamaParse. Hosted on Vercel/Render. To use it, you do need to specify your LlamaCloud API key and Anthropic API key (see below). App: Repo: Sign up to LlamaCloud:

Jerry Liu

21,073 просмотров • 4 месяцев назад

I used Claude Code Skills + souped up PDF parsing to create an M&A deal comp agent 🤖 Given a directory of public M&A filings (DEF 14A), it parses and analyzes each pdf, and generates an Excel sheet with deal terms and comparables. 1️⃣ The native parsing is pypdf which sucks, so I swapped it out with LlamaIndex semtools. This uses LlamaCloud for parsing - letting it handle deeply complex financial tables, charts, and anything else you throw at it. 2️⃣ Claude has native skills to write Excel spreadsheets! Full prompt is in the video below 👇 LlamaCloud + Semtools access also takes < 5 mins to setup, come check it out! Some notes: - disclaimer: Some of the values in the Excel spreadsheet are 100x bigger because they’re formatted as percentages not raw values - We’re working on native Claude skill integrations too! Semtools: LlamaCloud:

I used Claude Code Skills + souped up PDF parsing to create an M&A deal comp agent 🤖 Given a directory of public M&A filings (DEF 14A), it parses and analyzes each pdf, and generates an Excel sheet with deal terms and comparables. 1️⃣ The native parsing is pypdf which sucks, so I swapped it out with LlamaIndex semtools. This uses LlamaCloud for parsing - letting it handle deeply complex financial tables, charts, and anything else you throw at it. 2️⃣ Claude has native skills to write Excel spreadsheets! Full prompt is in the video below 👇 LlamaCloud + Semtools access also takes < 5 mins to setup, come check it out! Some notes: - disclaimer: Some of the values in the Excel spreadsheet are 100x bigger because they’re formatted as percentages not raw values - We’re working on native Claude skill integrations too! Semtools: LlamaCloud:

Jerry Liu

46,702 просмотров • 8 месяцев назад

Knowledge graphs for representing information are unbeatable. After this, you will never build a RAG system without knowledge graphs. It will take you five lines of code to build a knowledge graph with your data. I recorded a video to show you how you can do this. I used Cognee, an open-source library that outperforms any basic vector search approach in terms of retrieval relevance. They are collaborating with me on this post. Cognee is: • Easy to use • Reduces hallucinations • Open-source Here is a link to the repository: They also offer a comprehensive platform and UI with Python notebooks you can utilize to manage your data. Here is the link:

Knowledge graphs for representing information are unbeatable. After this, you will never build a RAG system without knowledge graphs. It will take you five lines of code to build a knowledge graph with your data. I recorded a video to show you how you can do this. I used Cognee, an open-source library that outperforms any basic vector search approach in terms of retrieval relevance. They are collaborating with me on this post. Cognee is: • Easy to use • Reduces hallucinations • Open-source Here is a link to the repository: They also offer a comprehensive platform and UI with Python notebooks you can utilize to manage your data. Here is the link:

Santiago

125,928 просмотров • 8 месяцев назад

“Chat with your PDF” still fails on ChatGPT/Claude when the doc is too complex 📉🧾 . If it’s a complicated financial report with scanned tables, you’re going to get back hallucinated values in your analysis! Check out the video 🎬 - in the first part, Claude gives back hallucinated values on the scanned tables in the equity research report. Having a proper document MCP server capable of high-accuracy parsing/indexing can help 💡. In the second part of the video I plug in LlamaCloud as an MCP tool to help with doc parsing and retrieval - it is fully able to render the scanned table in 2D format. You can set one up for yourself in 5 mins in the UI, no coding required. LlamaCloud: MCP Server:

“Chat with your PDF” still fails on ChatGPT/Claude when the doc is too complex 📉🧾 . If it’s a complicated financial report with scanned tables, you’re going to get back hallucinated values in your analysis! Check out the video 🎬 - in the first part, Claude gives back hallucinated values on the scanned tables in the equity research report. Having a proper document MCP server capable of high-accuracy parsing/indexing can help 💡. In the second part of the video I plug in LlamaCloud as an MCP tool to help with doc parsing and retrieval - it is fully able to render the scanned table in 2D format. You can set one up for yourself in 5 mins in the UI, no coding required. LlamaCloud: MCP Server:

Jerry Liu

21,369 просмотров • 11 месяцев назад

We’ve fully revamped our LlamaCloud integration with n8n.io as part of the LlamaParse v2 + new LlamaCloud SDK launch. What’s new: ✅ Fully stable nodes for LlamaParse, LlamaExtract, and LlamaCloud Index 🆕 Two new services: LlamaClassify and LlamaSheets 📘 A complete step-by-step setup guide Automating your document workflows has never been easier: parse → classify → extract → retrieve, just by plugging in a few nodes! ⭐ Find the repo on GitHub: 📚 Get started with our guide: 🦙 Sign up to LlamaCloud:

We’ve fully revamped our LlamaCloud integration with n8n.io as part of the LlamaParse v2 + new LlamaCloud SDK launch. What’s new: ✅ Fully stable nodes for LlamaParse, LlamaExtract, and LlamaCloud Index 🆕 Two new services: LlamaClassify and LlamaSheets 📘 A complete step-by-step setup guide Automating your document workflows has never been easier: parse → classify → extract → retrieve, just by plugging in a few nodes! ⭐ Find the repo on GitHub: 📚 Get started with our guide: 🦙 Sign up to LlamaCloud:

LlamaIndex 🦙

13,010 просмотров • 4 месяцев назад

ELON: WE’RE BUILDING A MODERN LIBRARY OF ALEXANDRIA ACROSS EARTH, THE MOON, AND MARS “The idea behind Galactica is to create an open source repository of all knowledge, a distillation of all knowledge, meaning anyone can access it, anyone can use it, and if other people want to train on it, they can do so. We want to create copies of this and distribute them throughout Earth, and even put them on the Moon, Mars, and out into deep space. In a way, it’s a modern day Library of Alexandria. It was a great tragedy that the Library of Alexandria burned down, and so to preserve this knowledge, we want to literally etch it in stone and distribute it widely." Source: Source: Baron Capital

ELON: WE’RE BUILDING A MODERN LIBRARY OF ALEXANDRIA ACROSS EARTH, THE MOON, AND MARS “The idea behind Galactica is to create an open source repository of all knowledge, a distillation of all knowledge, meaning anyone can access it, anyone can use it, and if other people want to train on it, they can do so. We want to create copies of this and distribute them throughout Earth, and even put them on the Moon, Mars, and out into deep space. In a way, it’s a modern day Library of Alexandria. It was a great tragedy that the Library of Alexandria burned down, and so to preserve this knowledge, we want to literally etch it in stone and distribute it widely." Source: Source: Baron Capital

Mario Nawfal

90,633 просмотров • 7 месяцев назад