LlamaIndex Newsletter 2024-05-28

Greetings, LlamaIndex Family! 🦙

Welcome to your latest weekly update from LlamaIndex! We're excited to present a variety of outstanding integration updates, detailed guides, demos, educational tutorials, and informative webinars this week.

🤩 The highlights:

• Secure Code Execution with AzureCodeInterpreterTool: Securely run LLM-generated code with Azure Container Apps, integrated with LlamaIndex for safe code execution.
• Build Automated Email Agents: Create email agents with MultiOn and LlamaIndex that autonomously read, index, and respond to emails.
• LlamaFS for Organized Files: Alex Reibman's team developed LlamaFS to automatically structure messy file directories, enhanced by Llama 3 and Groq Inc.'s API.
• RAGApp's No-Code Chatbots: Deploy RAG chatbots easily with RAGApp's no-code interface, fully open-source and cloud-compatible.

✨ Feature Releases and Enhancements:

1. We have launched Azure Container Apps dynamic sessions to securely run LLM-generated code in a sandbox. Integrated into LlamaIndex, this feature ensures safe execution of complex code tasks by your agents. Set up a session pool on Azure, add the AzureCodeInterpreterTool to your agent, and you’re ready to go. Blogpost, Tweet.
2. We have integrated with the open source Nomic embed, now fully operable locally. This integration allows for completely local embeddings and introduces a dynamic inference mode that optimizes embedding latency. The system automatically selects between local and remote embeddings based on speed, ensuring optimal performance. Docs, Tweet.
3. We have integrated the Vespa vector store, supporting hybrid search with BM25. Docs, Tweet.
4. We have integrated with MyMagic AI to facilitate batch data processing for GenAI applications. This setup allows you to pre-process large datasets with an LLM, enabling advanced analysis and querying capabilities. Docs, Tweet.

🗺️ Guides:

• Guide to building an automated Email Agent with MultiOn and LlamaIndex that can autonomously read and index emails for easy retrieval and draft responses using advanced browsing capabilities.
• Guide to building Full-Stack Job Search Assistant by Rishi Raj Jain using Gokoyeb, MongoDB, and LlamaIndex. This guide takes you through setting up MongoDB Atlas, crafting a Next.js application, developing UI components, and deploying your app on Koyeb, complete with real-time response streaming and continuous job updates.

🖥️ Demos:

• LlamaFS, a project developed by Alex Reibman and his team, automatically organizes messy file directories into neatly structured folders with interpretable names. Enhanced by Llama 3 and supported by Groq Inc.'s API, Ollama's fully local mode and LlamaIndex, this tool significantly improves file management efficiency. Code, Tweet.
• RAGApp, a project developed by Marcus Schiesser, offers a no-code interface for configuring RAG chatbots as simply as GPTs by OpenAI. This fully open-source docker container can be deployed on any cloud platform, allowing users to set up the LLM, define system prompts, upload knowledge bases, and launch chatbots via UI or API. Code, Tweet.

✍️ Tutorials:

• Phil Chirchir’s tutorial on DSPy RAG with LlamaIndex. It demonstrates how to integrate DSPy bootstrapping models with a LlamaIndex RAG pipeline powered by LlamaParse.
• Pavan Kumar’s tutorial on advanced image indexing for RAG demonstrates how to combine image embeddings with structured annotations using multimodal models. It details how to enhance image search with LlamaIndex and Qdrant Engine’s capabilities.
• Jayita Bhattacharyya’s tutorial on Building a RAG Chatbot using Llamaindex, Groq with Llama3 & Chainlit.

📹 Webinar:

• Webinar with OpenDevin team to learn how to build an Open-Source Coding Assistant using OpenDevin.