Hi there, Llama Friends! 🦙
Welcome to this week's edition of the LlamaIndex newsletter! We have some exciting updates and resources to share, including a new course on building agents, a step-by-step tutorial on corrective RAG, and the launch of LlamaExtract in public beta. Dive in to discover how you can enhance your projects with these innovative tools and insights!
🤩 The Highlights:
- LlamaExtract Public Beta: LlamaExtract is now in public beta! It allows you to define a schema and automatically extract structured data from your documents. Read the full demo post here and sign up today.
- Step-by-Step Tutorial on Corrective RAG: Check out this fantastic tutorial by @akshay_pachaar on building an agentic reasoning system for search and retrieval (specifically, corrective RAG) from scratch using LlamaIndex workflows.
- Free Courses on Building Agents: In case you missed it, we launched some high-profile free courses on building agentic systems with LlamaIndex, one with DeepLearning.AI and another with HuggingFace! Don't miss them.
🗺️ LlamaCloud & LlamaParse:
- AI Voice Assistant Pipeline: Build an AI voice assistant pipeline with ROCm, LlamaIndex, and RAG on @AMD GPUs. This tutorial covers transcription, context-aware responses, and text-to-speech. Get started here.
- Large-Scale Structured Extraction with LlamaExtract: Learn how to extract 50-100 fields from complex documents using LlamaExtract. This guide covers defining schemas, using optional fields, and verifying accuracy. Explore the notebook here and sign up for LlamaExtract.
✨ Framework:
- Gen AI Toolbox for Databases: We've teamed up with @googlecloud to simplify building AI agents using the Gen AI Toolbox for Databases. Learn more about this integration and check out the quickstart.
- Unified Google AI Integration: Now there's a unified integration that supports both Google Gemini and Google Vertex AI, handling everything from streaming to structured prediction. Explore the new integration here.
