LlamaIndex Newsletter 2025-07-15

Hi there, Llama Enthusiasts! 🦙

Welcome to this week's edition of the LlamaIndex newsletter! We're excited to bring you updates including our open-source NotebookLlaMa alternative to NotebookLM, comprehensive RAG guides, new MCP integrations, and powerful document processing workflows. Check out these developments along with our community tutorials and upcoming events to maximize your use of these new features.

🤩 The Highlights:

• NotebookLlaMa - Open-Source NotebookLM Alternative: Your fully open-source smart assistant for document processing, built on LlamaCloud with agentic parsing, intelligent extraction, mind maps, podcast-like audio conversations, citation finding, interactive ddata visualization and more! Over 1000 stars on GitHub!
• Google Cloud Gemini Integration: Complete sample app demonstrating how to build production-ready RAG applications using Google Cloud's Gemini models with LlamaIndex integration patterns. Sample App
• Human-in-the-Loop Data Extraction: Comprehensive workflow for structured data extraction with human validation, featuring LlamaParse document processing and automated schema generation. Notebook

🗺️ LlamaCloud And LlamaParse:

• Complete RAG pipeline tutorial using LlamaParse with Snowflake Cortex for enterprise document processing and hybrid search capabilities. Tutorial, Video
• LlamaCloud MCP server integration allowing you to use extract agents and indexes as MCP tools with Claude Desktop. GitHub, Video

✨ Framework:

• Grok 4 Integration: One-line integration with the new Grok 4 model using our OpenAILike integration. Notebook Demo
• MCP Integration Guide: Comprehensive tutorial on building intelligent agents with Model Context Protocol, featuring database management through natural language and Gradio interfaces. Guide
• RAG Development Guide: Full guide from raw data to production RAG pipelines, covering preprocessing, embeddings, and vector database operations in collaboration with Qdrant. Guide

✍️ Community:

• LeSearch Multi-Agent Research Tool: Built with ReActAgent framework, featuring multi-hop question answering, code navigation, and environment dependency resolution. Winner of Best Use of LlamaIndex at CMU AI Agents Hackathon. Live App, Demo
• LinkedIn Learning Course: Yujian Tang's comprehensive course on building RAG applications from scratch using LlamaIndex. Course
• Agent Memory Livestream: Full recording of our session on building memory-aware agents with short-term and long-term memory capabilities. YouTube