Box Developers

🚀 Celebrating Innovation at the Agentic Rag-a-thon! 🚀 What happens when you bring together some of the brightest minds in tech, cutting-edge tools, and a whole lot of adrenaline? You get an unforgettable hackathon experience that pushes the boundaries of what's possible! Box was thrilled to sponsor the recent LlamaIndex Agentic Rag-a-thon. This event was a playground for innovation, where teams raced against the clock to bring their groundbreaking ideas to life. We were particularly excited to see how our tools could power and inspire new solutions. One standout project was PureML, a Retrieval-Augmented Generation (RAG) application that leverages Box’s cloud capabilities for seamless document storage and parsing. The team harnessed AI to solve real-world data challenges, like filling in missing values and consolidating datasets — all while using state-of-the-art technology. From brainstorming to late-night coding marathons, the PureML team’s journey is a great example of how Box's platform can empower developers to build the future. Their project even clinched the award for "Best Use of Reflex," highlighting just how versatile our ecosystem can be! 💡 Curious to know more about how PureML went from an idea to an award-winning prototype? Check out the full article to dive into their hackathon journey and see how our Box technology enabled this impressive project. 👉 Read the full article here and get inspired! We can't wait to see what you’ll build next using the power of Box. Let’s keep pushing the boundaries together! #DeveloperCommunity #Hackathon #BoxProud #PureML #AIInnovation #TechForGood

Looking to level up your AI-driven document processing skills? Check out our latest workshop article📝🤖 In this hands-on guide, we show you how to: 🔍 Seamlessly retrieve and search documents stored in Box using the Box API. 📊 Transform those documents into embeddings using a pre-trained Hugging Face model. ⚡️ Store and query document embeddings in ChromaDB for lightning-fast, intelligent searches, all using the LlamaIndex framework. Imagine managing lease agreements for 50 properties stored in Box. You’ll learn how to efficiently index, search, and query those documents to extract meaningful insights in no time. 🔗 Read the full workshop and check our community GitHub and start building smarter applications today! #developers #AI #documentprocessing #BoxAPI #ChromaDB #LlamaIndex #HuggingFace #cloudstorage #vectorsearch #developercommunity #contentextraction

This was a great project, and also the winner of the best use of Box award! Love this event and our partnership with LlamaIndex. Its so energizing to see the amazing problems being solved with Agentic RAG!

Join the Box Platform Developer Day in Toronto on November 20th! 🇨🇦 Learn, code, and connect with other developers from this area. We will be showing off the full gamut of developer options and tools, including getting started, SDKs, Box AI, and Box for Salesforce. Register today!

Say hello to Box DevRel team! Visit the Pavilion at BoxWorks for immersive learning, Box demos, partner conversations, and impactful networking. Discover the Dev Zone to learn more about building on Box; visit Box partner booths to learn more about the content ecosystem. See you! 👋

For those interested in learning more about Box Platform, our world-class developer platform, come find us in the Developer Zone in the expo hall. Who knows?, We might even have some good swag.

🌟 Proud Sponsor Highlight: Innovation in AI Networking! 🌟 At Box, we’re excited to have been a sponsor for the recent Agentic RAG Hackathon, a collaborative event that showcased the incredible potential of LlamaIndex in building AI apps. One standout project, ProNetwork DJ, took home the Innovation Prize for its unique approach to connecting people in more meaningful ways. 🚀 ProNetwork DJ, developed by talented hackers Luis Silva V and Adonai Vera, uses AI to simulate interactions, helping users build deeper connections in less time. Inspired by Black Mirror’s “Hang the DJ” episode, the tool leverages multi-agent systems and Retrieval-Augmented Generation (RAG) to create “clones” that prepare users for key interactions. Imagine a networking experience where you’re matched, prepped, and ready to make impactful connections in minutes! 🤖💼 👉 Interested in learning how this AI-driven app works? Check out this innovative concept, and join us in exploring the future of AI-powered networking.

🚀 Unlock the Power of Unstructured Data with Box and LlamaIndex! 🦙 Are you looking to build a powerful Retrieval-Augmented Generation (RAG) application that can access and provide contextual answers from unstructured data stored in Box? Look no further! 📦 We've just released a detailed step-by-step tutorial on how to create a sophisticated document retrieval system using Box, LlamaIndex, ChromaDB, and HuggingFaceEmbedding. With this guide, you'll learn how to: ✅ Seamlessly access and extract documents from Box using BoxReader. ✅ Process and split text into meaningful chunks for embedding and retrieval. ✅ Create and manage an in-memory vector store with ChromaDB for fast, efficient querying. ✅ Use a language model like Llama-CPP to synthesize natural language responses to user queries. Whether you're a seasoned developer or just starting your journey in AI, this article breaks down each step in building a RAG application—from loading your documents to generating insightful answers. It's an excellent resource for anyone looking to harness the power of vector embeddings and language models for Customer Support Systems, Knowledge Management, or even Educational Tools. 🔗 Read the full article now and start building your intelligent retrieval system today.

Visit the new demo site and embark on a journey of building custom portals with Box UI Elements! Learn more from videos, blog posts and sample code! 🚀 https://lnkd.in/eH7-3ayq

🚀 Build Your First Retrieval-Augmented Generation (RAG) App with LlamaIndex and Box! 🧩 Hey Developers! Ready to dive into AI-driven applications? Check out this fantastic step-by-step guide on creating a RAG application using LlamaIndex, Box, ChromaDB, and HuggingFace Embeddings! 🤖 Key Highlights: 1️⃣ Data Retrieval from Box: Use BoxReaderTextExtraction for direct document content or BoxReader to fetch entire files. 🗂️ 2️⃣ Text Embeddings with HuggingFace: Integrate models like "BAAI/bge-base-en-v1.5" with ease. 🧠 3️⃣ Manage Embeddings with ChromaDB: Efficiently store and query data using ChromaDB as your vector store. 💾 4️⃣ Simple Querying: Quickly find relevant documents with natural language queries. 🕵️♂️ 💡 This guide is perfect for leveraging unstructured data from Box and tapping into the power of AI. 📖 Read the full article on our community blog and get started! Happy Coding! 🚀💻 #DeveloperCommunity #AI #Box #LlamaIndex #ChromaDB #TechInnovation