Learn how to build data-backed AI agents with LlamaIndex and Redis in our webinar on December 12! ?? Understand how to architect an agentic system to break complex tasks down ?? Learn best practices for reducing costs and optimizing latency ?? Learn about semantic caching for further improving speeds and costs https://lnkd.in/guqiz9xF
LlamaIndex
科技、信息和网络
San Francisco,California 222,282 位关注者
The fastest way to build production-quality LLM agents over your data
关于我们
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
- 网站
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https://www.llamaindex.ai/
LlamaIndex的外部链接
- 所属行业
- 科技、信息和网络
- 规模
- 2-10 人
- 总部
- San Francisco,California
- 类型
- 上市公司
地点
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主要
US,California,San Francisco
LlamaIndex员工
动态
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LLM-Native Resume Matching Solution with LlamaParse and LlamaCloud Traditional resume screening often depends on manual filtering and matching criteria, making it a slow and tedious process for recruiters. Thanks to Ravi Theja Desetty, we now have an LLM-native solution that simplifies and speeds up the entire process: 1? Parse resumes and extract structured metadata effortlessly. 2? Index resumes for quick and easy retrieval. 3? Enable natural language queries to search for candidates intuitively. 4? Get detailed insights into why a candidate is the right fit for a role. This complete end-to-end flow is powered by LlamaParse, LlamaCloud, and the open-source orchestrator LlamaIndex. Cookbook: https://lnkd.in/gk4-qYGa Video: https://lnkd.in/gWwpjM9q
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We're proud to announce the availability of an end-to-end LlamaIndex + Microsoft Azure solution at #MSIgnite today! Learn more about our integration with Azure Open AI, Azure AI Embeddings, Azure AI Search and more! If you're at Microsoft Ignite this week Laurie Voss will be around all week, so feel free to reach out and meet up! https://lnkd.in/gtPAgwps cc Microsoft Partner
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Learn to build a local agentic RAG application for report generation using open-source LLMs! ?? Our friends at AI Makerspace are hosting a live event next week (November 27) to teach you: ?? How to set up an "on-prem" LLM app stack ?? LlamaIndex Workflows ?? Llama-Deploy ?? and Ollama! Perfect for aspiring AI Engineers, join Dr. Greg Loughnane and Chris "The Wiz" Alexiuk for this hands-on workshop where you'll build, ship, and share a real agentic RAG use case. Register here: https://lu.ma/zxnxgl5v
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Mistral AI released a brand-new state of the art multi-modal image model today and we have day 0 support! pip install llama-index-multi-modal-llms-mistralai to get the latest version and check out this notebook showing how to use it! https://lnkd.in/gv9RSf7e
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Multi-agent workflow to Generate a Structured Financial Report ?? In our new video we show you how to generate simple analyses containing text and tables over a bank of 10K documents. First, we use LlamaCloud to advanced retrieval endpoints allowing you to fetch chunk and document-level context from complex financial reports consisting of text, tables, and sometimes images/diagrams. We then build an agentic workflow on top of LlamaCloud, using OpenAI GPT-4o, consisting of researcher and writer steps in order to generate the final response. Video: https://lnkd.in/gUqRYKbN Signup to LlamaCloud: https://lnkd.in/gi8dxGnt For enterprise usage, come talk to us: https://lnkd.in/g5648-ip
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Generating a Multimedia Research Report with LLM Structured Outputs ???? In our brand-new video ??, we show you how to build a simple report generator that can summarize insights from complex documents (e.g. a slide deck), and synthesize a report with interleaving text and images. Structured outputs is a key building block towards building agentic RAG / report generation workflows, and this video is a great way to get started. Video: https://lnkd.in/gxMpZ9ck Notebook: https://lnkd.in/geP9f3YB Signup for LlamaCloud: https://lnkd.in/gi8dxGnt
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Our Python documentation just got a huge boost thanks to RunLLM! Our new "Ask AI" widget in the bottom-right of every docs page launches a truly magically accurate agentic RAG system that writes accurate, up-to-date code in answer to your questions. Try it out today! https://lnkd.in/gCGQ9GMK
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Learn to build powerful GenAI apps with LlamaIndex and Memgraph in our upcoming Community Call! Join us to explore: ?? Creating knowledge graphs from unstructured data ?? Advanced retrieval methods for efficient information extraction ?? Transforming data into queryable knowledge graphs ?? Performing natural language queries with ease Register now: https://lnkd.in/gWjKfa5e
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Automatically generate cloud configurations with RAGformation! ??? Describe your use case in natural language, get a tailored cloud architecture ??? Visualize your setup with dynamically generated flow diagrams ?? Receive pricing estimates for the generated architecture ?? Refine recommendations based on your preferences and budget RAGformation simplifies cloud complexity, accelerates deployment, and optimizes ROI. Built with LlamaIndex Workflows, Box, and Pinecone, it's open-source and won the Box Award at our recent RAG-a-thon! Learn more about RAGformation in their guest post on our blog: https://lnkd.in/djY_kymn