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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

79,015 subscribers

137,793 Aufrufe • vor 1 Jahr •via X (Twitter)

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11 Kommentare

Profilbild von Josue

Josuevor 1 Jahr

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

Profilbild von Mobile Scanner

Mobile Scannervor 1 Jahr

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

Profilbild von Ed Choudhry

Ed Choudhryvor 1 Jahr

@Scobleizer Here’s the new YC batch lol

Profilbild von eimen

eimenvor 1 Jahr

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

Profilbild von Peter Wilczynski

Peter Wilczynskivor 1 Jahr

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

Profilbild von Nikhil Chaudhari

Nikhil Chaudharivor 1 Jahr

This is amazing Jerry!

Profilbild von psy

psyvor 1 Jahr

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 ☺️

Profilbild von Shubham Saboo

Shubham Saboovor 1 Jahr

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.

Profilbild von Peter Steinberger

Peter Steinbergervor 1 Jahr

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.

Profilbild von elvis

elvisvor 1 Jahr

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.

Profilbild von Trae

Traevor 1 Jahr

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

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257,050 Aufrufe • vor 5 Monaten

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55,620 Aufrufe • vor 8 Monaten

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141,258 Aufrufe • vor 2 Jahren

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Jerry Liu

21,073 Aufrufe • vor 7 Monaten

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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

46,748 Aufrufe • vor 10 Monaten

“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:

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21,369 Aufrufe • vor 1 Jahr

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Santiago

126,434 Aufrufe • vor 11 Monaten

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 Aufrufe • vor 9 Monaten

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I just built this CRACKED Cursor MCP extension that makes your IDE fully aware of all the logs in your browser. Was struggling with a few issues recently and kept having to copy/paste logs but with this tool you can: ✅ Check all console logs + errors ✅ Analyze network requests, responses and errors ✅ Make changes to a selected element in your browser ✅ Take screenshots of your browser ... without EVER having to leave your IDE 🦾 Open source, FREE and compatible with Cursor, Cline, Continue and Zed. Link to the docs with setup instructions down below 👇

Ted Werbel

179,882 Aufrufe • vor 1 Jahr

Build a loan underwriting agent workflow in ~5 mins 💵🤖 (No code, just English) I built an agentic workflow that can process incoming PDFs of financial statements: checking statements, bank statements, brokerage accounts, and extract/normalize the financials in each source of data. I did this by specifying the schemas and classification logic in plain English; our agent compiles this into a deterministic workflow with calls to agentic parsing to extract out all the information that you need. Our agent builder is now in LlamaCloud, you can sign up and try it yourself! Blog: Sign up:

Build a loan underwriting agent workflow in ~5 mins 💵🤖 (No code, just English) I built an agentic workflow that can process incoming PDFs of financial statements: checking statements, bank statements, brokerage accounts, and extract/normalize the financials in each source of data. I did this by specifying the schemas and classification logic in plain English; our agent compiles this into a deterministic workflow with calls to agentic parsing to extract out all the information that you need. Our agent builder is now in LlamaCloud, you can sign up and try it yourself! Blog: Sign up:

Jerry Liu

30,015 Aufrufe • vor 7 Monaten

I just built an open NotebookLM clone! Here's what it can do for you: - Process multi-modal data - Scrape websites and YouTube videos - Create a unified knowledge base - Lets you do RAG over it - Remember every conversation - Generate a podcast 🎙️ The idea here is not to reinvent the wheel but to understand how one of the most powerful tools for learning and research actually works, by building it step-by-step! So by the end of this video, you'll learn how to: ↳ Process multimodal data (text, audio, video, URLs, and YouTube videos) into a format ready for LLMs ↳ Store everything in a vector database for fast retrieval ↳ Add a memory layer that remembers conversations and preferences for a personalized experience ↳ Chat with your knowledge base or generate podcasts using a fully open-source, locally running text-to-speech model The podcast generation feature is my favorite part! There's something powerful about turning written content into conversational audio that you can listen to while doing something else. The entire code is 100% open-source. I've shared a link in the replies! ____ Don't forget to drop a like if you enjoy my videos. It shows me I should be making more content like this. Cheers! :)

I just built an open NotebookLM clone! Here's what it can do for you: - Process multi-modal data - Scrape websites and YouTube videos - Create a unified knowledge base - Lets you do RAG over it - Remember every conversation - Generate a podcast 🎙️ The idea here is not to reinvent the wheel but to understand how one of the most powerful tools for learning and research actually works, by building it step-by-step! So by the end of this video, you'll learn how to: ↳ Process multimodal data (text, audio, video, URLs, and YouTube videos) into a format ready for LLMs ↳ Store everything in a vector database for fast retrieval ↳ Add a memory layer that remembers conversations and preferences for a personalized experience ↳ Chat with your knowledge base or generate podcasts using a fully open-source, locally running text-to-speech model The podcast generation feature is my favorite part! There's something powerful about turning written content into conversational audio that you can listen to while doing something else. The entire code is 100% open-source. I've shared a link in the replies! ____ Don't forget to drop a like if you enjoy my videos. It shows me I should be making more content like this. Cheers! :)

Akshay 🚀

83,187 Aufrufe • vor 10 Monaten

I built a Claude Code skill that allows it to generate a deep research report over any collection of complex docs (PDFs, Word, Pptx)….and generate word-level citations and bounding boxes directly back to the source! 📝 Check out “/research-docs”. 1. It parses out text and bounding boxes from every doc with liteparse, in seconds. 2. It then generates a full HTML report of the outputs that let you see word-level citations in each page. Raw Claude obviously has deep research capabilities, but it lacks an audit trail back to the source. This skill gives you a researched report that can be audited by others. Check it out: LiteParse:

I built a Claude Code skill that allows it to generate a deep research report over any collection of complex docs (PDFs, Word, Pptx)….and generate word-level citations and bounding boxes directly back to the source! 📝 Check out “/research-docs”. 1. It parses out text and bounding boxes from every doc with liteparse, in seconds. 2. It then generates a full HTML report of the outputs that let you see word-level citations in each page. Raw Claude obviously has deep research capabilities, but it lacks an audit trail back to the source. This skill gives you a researched report that can be audited by others. Check it out: LiteParse:

Jerry Liu

77,259 Aufrufe • vor 4 Monaten

Building with AI gets easier every day. Here is an open-source library that makes integrating AI into an application extremely easy: Star the repository! This library alone can make React the best front-end framework out there! There are a bunch of cool things I like about CopilotKit. Here are 3 of them: 1. It allows you to take any -powered agent and bring it into your application. (This is a brand-new feature!) 2. You can build an AI-powered chatbot in your application. The chatbot will have access to your context and can act on the application. 3. You can build a RAG workflow to process and answer questions from a real-time knowledge base. I recorded a video to show you how simple it is to make some of this happen. A few lines of code, and you are in business. Here is a link to the sample application: CopilotKit is open-source. You can self-host it. You can use it with any LLM. Thanks to the team for showing me their tool and collaborating with me on this post!

Santiago

108,835 Aufrufe • vor 2 Jahren

Google's NotebookLM is truly the best AI second brain. You can easily learn, memorize, generate new ideas, and more. Give it the knowledge files you want and: - Ask any question - Create new summaries or other content - Generate an ultra-realistic podcast to learn - Add notes on the fly to expand the info available There's virtually no limit to the number of things you can feed it: the context window is huge (1M tokens?). Unlike other tools, you can use only the information you already trust. This makes the answers much more relevant, and with far fewer hallucinations. As a reminder, it's completely free to use. So it's definitely worth a try if you haven't already.

Google's NotebookLM is truly the best AI second brain. You can easily learn, memorize, generate new ideas, and more. Give it the knowledge files you want and: - Ask any question - Create new summaries or other content - Generate an ultra-realistic podcast to learn - Add notes on the fly to expand the info available There's virtually no limit to the number of things you can feed it: the context window is huge (1M tokens?). Unlike other tools, you can use only the information you already trust. This makes the answers much more relevant, and with far fewer hallucinations. As a reminder, it's completely free to use. So it's definitely worth a try if you haven't already.

Paul Couvert

113,529 Aufrufe • vor 1 Jahr

Here is an open-source tool to generate a complete dataset. 1. Describe the data you want 2. An orchestrator agent searches the web 3. Sub-agents run in parallel to fetch the data 4. You get a structured dataset you can download For example, you can run Bigset with the query "all leica lenses being sold on amazon", or "leica stores in kyoto with their opening hours and ratings". Bigset uses TinyFish's free Search and Fetch APIs in the background. You can configure it to refresh the data on a schedule. You can self-host it with your own keys. Here is the GitHub repository: You can get free TinyFish API keys here: Thanks to the TinyFish team for partnering with me on this post.

Here is an open-source tool to generate a complete dataset. 1. Describe the data you want 2. An orchestrator agent searches the web 3. Sub-agents run in parallel to fetch the data 4. You get a structured dataset you can download For example, you can run Bigset with the query "all leica lenses being sold on amazon", or "leica stores in kyoto with their opening hours and ratings". Bigset uses TinyFish's free Search and Fetch APIs in the background. You can configure it to refresh the data on a schedule. You can self-host it with your own keys. Here is the GitHub repository: You can get free TinyFish API keys here: Thanks to the TinyFish team for partnering with me on this post.

Santiago

20,877 Aufrufe • vor 3 Monaten