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Jerry Liu
LlamaIndex 🦙
7,288 posts
user avatar
Jerry Liu
LlamaIndex 🦙
@jerryjliu0
Parsing the world's hardest PDFs @llama_index. cofounder/CEO Careers: llamaindex.ai/careers Enterprise: llamaindex.ai/contact
llamaindex.ai
Joined September 2011
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  • Pinned
    user avatar
    Jerry Liu
    LlamaIndex 🦙
    @jerryjliu0
    Jun 18
    We built the fastest PDF -> markdown parser in the world 🚀⚡️ AND it’s more accurate than any other open-source, model-free parser (pymupdf4llm, opendataloader, pdf-inspector, markitdown) on 3 standardized benchmarks: olmOCR0-bench, opendataloader-bench, ParseBench Introducing
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    LlamaIndex 🦙
    @llama_index
    Jun 18
    LiteParse v2.1 is here, and its bringing the fastest markdown output possible. In this release, we are fulfilling our top request: markdown output. But in the spirit of "lite"-ness, we are doing this completely LLM-free and fast. Not only is it fast, it also beats all other
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  • user avatar
    Jerry Liu
    LlamaIndex 🦙
    @jerryjliu0
    May 14, 2024
    Google vs OpenAI is the beef we’re all here for Dumping updates from I/O in this 🧵
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    Jerry Liu
    LlamaIndex 🦙
    @jerryjliu0
    Apr 19, 2025
    I am a $200 / month ChatGPT Pro power user (and Claude and now Gemini), and I really really want a "fork" feature I have so much preloaded context I don't want to 1) deal with different tasks on the same convo thread, or 2) repaste that context every time
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    Jerry Liu
    LlamaIndex 🦙
    @jerryjliu0
    Jul 19, 2024
    Introducing LlamaCloud Chat Get a full-blown ChatGPT UI over any production data source in minutes. Connect to data sources like S3, Sharepoint, Notion, Slack, parse and index complex document types (PDFs, powerpoints, spreadsheets), and get back an advanced retrieval endpoint.
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    LlamaIndex 🦙
    @llama_index
    Jul 19, 2024
    ✨ LlamaCloud updates! ✨ The team has been hard at work shipping updates to LlamaCloud, here are some recent highlights: ⭐️ LlamaCloud Chat, an instant conversational interface to your data, to quickly get you up and running. ⭐️ Teams features so you can add collaborators and
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    Jerry Liu
    LlamaIndex 🦙
    @jerryjliu0
    Jul 5, 2025
    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
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    LlamaIndex 🦙
    @llama_index
    Jul 4, 2025
    🔍 Extracting the core knowledge from documents is a common problem for many people, from students to corporate employees - and many people have found @NotebookLM useful . But what if you could have your own, fully open-source NotebookLM, running on your computer at any time you
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    Jerry Liu
    LlamaIndex 🦙
    @jerryjliu0
    Jun 6, 2023
    I’m super excited to make it official: @disiok and I have started a company around @llama_index, and we’ve raised a $8.5M seed round led by @GreylockVC! 🔥🚀 We are building the open-source data framework to unlock LLM capabilities on your private data.
    Medium
    Building the data framework for LLMs
    From medium.com
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    Jerry Liu
    LlamaIndex 🦙
    @jerryjliu0
    Dec 15, 2024
    This weekend learn how to build a legal document agent from scratch 👨‍⚖️📑 I made a tutorial showing you how to build a contract review agentic workflow - given a vendor agreement, parse it into a set of key clauses, match it with relevant clauses from a set of guidelines (GDPR),
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    LlamaIndex 🦙
    @llama_index
    Dec 14, 2024
    We’re introducing a brand-new tutorial 💫 on how to build an agentic workflow that can ensure contract compliance 📝🧑‍⚖️ - given a vendor contract, pull apart the relevant clauses and make sure that each clause is consistent with the relevant guidelines (e.g. GDPR), and then
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    Jerry Liu
    LlamaIndex 🦙
    @jerryjliu0
    Jul 29, 2023
    The `rebel-large` model is awesome for relation extraction 🔗 Paired with CUDA, it’s blazing fast ⚡️. With @llama_index 🦙, we can now build a knowledge graph over any text data super quickly! 🕸️ Full Colab notebook showing how you can use it: 
 colab.research.google.com/drive/1G6pcR0p…
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    Jerry Liu
    LlamaIndex 🦙
    @jerryjliu0
    Nov 21, 2023
    I’m excited to introduce RAGs - create a “ChatGPT over your data” purely with natural language 💬 Setup and use a full RAG pipeline over files/web urls in three simple steps: 1️⃣ RAG Builder: Describe your RAG pipeline in natural language (data, parameters like top-k, system
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    LlamaIndex 🦙
    @llama_index
    Nov 21, 2023
    Introducing RAGs, a @streamlit app that allows you to create and customize your own RAG agent and then use it over your own data, all with natural language 🔥 Directly inspired by @OpenAI GPTs, you can converse with an agent to help you do search/retrieval over any data you
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    Jerry Liu
    LlamaIndex 🦙
    @jerryjliu0
    Jan 6, 2024
    There was a lot of cool RAG research in the past year or two, and luckily for you, all of these efforts are tracked under one place! “Retrieval-Augmented Generation for Large Language Models: A Survey” by Gao et al. does an admirable job categorizing all RAG research into three
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    LlamaIndex 🦙
    @llama_index
    Jan 6, 2024
    One thing we loved about 2023 was the volume of new research around RAG from the entire community ❤️. This survey by Gao et al. is the most comprehensive survey of this research we’ve seen yet - it covers 100+ papers, blog posts, and projects across every step of the RAG
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    Jerry Liu
    LlamaIndex 🦙
    @jerryjliu0
    Dec 20, 2023
    New RAG technique alert 🚨 We’ve come up with an advanced RAG technique in @llama_index that lets you ask structured questions over many documents ✨: 1. Model each document as a metadata dictionary - store more attributes beyond a simple text summary. (e.g. a row in SQL
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    LlamaIndex 🦙
    @llama_index
    Dec 20, 2023
    Structured Hierarchical RAG 💫 Doing RAG well over many docs is hard. A popular existing approach is hierarchical retrieval: select the relevant doc summaries before retrieving the content inside. But selecting docs purely based on summaries is tough - a doc can have a bunch of
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    Jerry Liu
    LlamaIndex 🦙
    @jerryjliu0
    Jul 6, 2023
    If you’re building “chat over your PDFs” with LLMs, you need to deal with the pesky issue of how to parse embedded tables/diagrams. Native text splitting + top-k on your tables == bad results! ⛔️🚫 A nuanced, hierarchical data representation over your PDF can help 👇
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    Jerry Liu
    LlamaIndex 🦙
    @jerryjliu0
    Jan 5, 2024
    Our gift to you this new year is an advanced RAG diagram you can print out and frame 🖼️ @_nerdai_ compiled 15+ advanced RAG techniques, categorized them, and added full @llama_index recipes + notebook links for each of these components. They’re categorized to help you jointly
    user avatar
    LlamaIndex 🦙
    @llama_index
    Jan 5, 2024
    Advanced RAG Cheat Sheet + Recipes 🧑‍🍳 We’re publishing a comprehensive diagram outlining all the different components of advanced RAG, the pain points they solve, and links to LlamaIndex resources. Here’s some core concepts that motivate advanced RAGs: 💡 Success metric for RAG
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    Jerry Liu
    LlamaIndex 🦙
    @jerryjliu0
    Feb 23, 2024
    I’ve talked about how a big step towards better RAG, no matter what downstream model you’re using (GPT-4, Mistral, Gemini 1.5 Pro, etc.) is to just have a really nice PDF parser. It’s so important because a good parser unlocks way more interesting indexing/retrieval strategies
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