Learn to build an AI Scheduler for smart meetings using Zoom, LlamaIndex & Qdrant @ the AWS Loft on September 20th! Join us for a hands-on workshop where you'll: 🚀 Create a RAG recommendation engine for meeting productivity 🔍 Use Zoom's transcription SDK to analyze missed content 🧠 Fine-tune models for more accurate meeting suggestions Our co-founder Simon Suo will be presenting the closing talk! Event details and registration: https://lu.ma/csll5v5j
LlamaIndex
Technology, Information and Internet
San Francisco, California 203,477 followers
The central interface between LLMs and your external data.
About us
The data framework for LLMs Python: Github: https://github.com/jerryjliu/llama_index Docs: https://docs.llamaindex.ai/ Typescript/Javascript: Github: https://github.com/run-llama/LlamaIndexTS Docs: https://ts.llamaindex.ai/ Other: Discord: discord.gg/dGcwcsnxhU LlamaHub: llamahub.ai Twitter: https://twitter.com/llama_index Blog: blog.llamaindex.ai #ai #llms #rag
- Website
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https://www.llamaindex.ai/
External link for LlamaIndex
- Industry
- Technology, Information and Internet
- Company size
- 2-10 employees
- Headquarters
- San Francisco, California
- Type
- Public Company
Locations
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Primary
San Francisco, California, US
Employees at LlamaIndex
Updates
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LlamaIndex reposted this
AI Strategist & Ecosystem Builder | Innovation & Partnerships Leader | Driving Collaboration Between Startups & Enterprises
🚀🚀🚀 Countdown - 4 weeks to the Agentic RAG-a-thon @ 500 Global HQ in Palo Alto. A big shout out to early-adopter enterprises, Box and SAP as platinum sponsors. Let's build together, Oct. 11-13. Reg here: https://lnkd.in/gQ4NJR-z #arize #hanahaus #500global #llamaindex #pinecone Scott Hurrey Dawn Lauter Stephanie Mosqueda Collin Sommerhauser Yi Ding Laurie Voss
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Build your own RAG-based document QA system with Kotaemon, an open-source UI for chatting with your documents 📚🤖 Learn how to: ➡️ Set up a clean, customizable RAG UI for end users and developers ➡️ Organize LLM & embedding models, supporting both local and API providers ➡️ Implement hybrid RAG pipelines with full-text & vector retrieval ➡️ Enable multi-modal QA support for documents with figures & tables Kotaemon offers: ✅ Multi-user login and document collection management ✅ Advanced citations with document preview ✅ Support for complex reasoning methods ✅ Configurable settings UI for fine-tuning retrieval & generation Get started with Kotaemon: https://lnkd.in/gapR3jVy
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A nice quick tutorial on building retrieval-augmented generation with LlamaIndex! https://lnkd.in/gSQ8VnAh
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Check out this Maven course, Search For RAG in the LLM era, featuring a guest lecture by Jerry Liu! You get: 🔥 Live Code Walkthroughs: Engage with code examples and implementations by coding along in real-time 🚀 Expert-led Sessions: Learn from industry veterans with over 2-decades of experience, providing practical knowhow and tricks 📚 Comprehensive Course Content: Gain a deep working knowledge of GenerativeAI technologies and their applications 🏃♀️ Intensive Week-long Case Study Sprint: Dive into practical projects like building your own LM, Customer Support Bot, and more https://lnkd.in/g-Pv4y6y
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Catch a recording of Laurie Voss last week talking about Agentic RAG in 2024! This talk covers a lot of ground: ➡️ What is LlamaIndex and why should you use it? ➡️ What is RAG and how does it work? ➡️ Why RAG is necessary but not sufficient ➡️ Adding agentic strategies to improve RAG ➡️ Building full agents with reasoning, reflection and planning ➡️ LlamaIndex workflows and how to build agents with them Check it out here! https://lnkd.in/gPamCU5d
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LlamaIndex reposted this
RAGapp makes hosting your custom GPTs with any LLM a breeze. v0.0.23 adds HTTPS deployments using your domains and full-state persistence. Thanks to Arturo Castellanos from William & Mary – Raymond A. Mason School of Business for sponsoring this feature! Open-source and built using LlamaIndex. 🖥️ $ docker run -p 8000:8000 ragapp/ragapp 📄 https://lnkd.in/guXjrpJe
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Learn to build advanced LLM agents in this comprehensive course from llmagents-learning.org, including a guest lecture from co-founder Jerry Liu! 🤖🧠 Gain expertise in: 🔹 LLM foundations and essential abilities for task automation 🔹 Agent applications like code generation, robotics, and web automation 🔹 Ethical considerations, safety, and human-agent interaction Course highlights: • Guest lectures from industry leaders at Google DeepMind, OpenAI, and more • Hands-on topics covering reasoning, planning, and multi-agent collaboration • Insights into the future of AI and its impact on daily life Explore the full syllabus and enroll now: https://lnkd.in/gKFjZHSW
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Watch Ravi Theja Desetty implement our multi-step query engine using workflows! The multi-step query pattern breaks a complex question up into sequential sub-questions. This video covers: ➡️ The process of creating a workflow that includes query decomposition, stopping conditions, and response synthesis ➡️ Implementation details such as generating step queries, and updating reasoning based on intermediate responses ➡️ How to use OpenAI's API, index data, and set up the necessary components for the multi-step query engine Check out the video here: https://lnkd.in/gbptsUbP
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Instead of using fixed chunking/transformations for RAG, LLMs can increasingly automate the ETL stack with data-specific decisions. This tutorial by RS Rohan shows you how to build an automated extraction + filtering RAG pipeline within the LlamaIndex ecosystem: ✅ LlamaExtract for structured extraction ✅ Vector indexing with LlamaIndex + Chroma ✅ Advanced querying with auto-retrieval Notebook: https://lnkd.in/g8yxt7-v Video: https://lnkd.in/gGNGVsQD
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