I'm as LLM reliant as the next person.. But we forget there are other models too, specialized models that are cheaper and more effective to use depending on the task.. E.g.: Agents need tools for structured data predictions.
We just open-sourced LiteParse 🎉 A lightweight, local document parser in the shape of an easy-to-use CLI. No API calls, no external service, no cloud dependency. Just fast text extraction from common file formats, right from your terminal.
I filmed a walkthrough of LlamaAgent Builder, our new tool for building document agents by just describing what you want @llama_index
We have a new tool to help you build and deploy document agents in LlamaCloud. The LlamaAgents Builder is kiiinda no-code, but not: 🦋 We have a new chat interface: just describe the document processing task you want in natural language
We rebuilt LlamaParse's API from the ground up, and also released new SDKs for LlamaCloud in its entirety. API v2 for LlamaParse simplfies parsing config into structured objects · input_options for file-specific settings. · output_options for controlling what you get back.
I went offline for a couple of days to be with family and it seems like all we talked about on this platform has been coding agents.
The team at LlamaIndex have been cooking! 🧑🍳 🍳 Over the last few weeks, we released: LlamaAgents: This is agent workflows that come with complete, deployable templates (more coming on this this week!)
We shipped LlamaSheets today (beta, free). It approaches spreadsheets as a visual structure: Bold headers, merged cells, color-coded categories.
Yesterday we announced the open preview for LlamaAgents So, me and my colleague Adrian wrote this intro blog to help you get started. Learn about all the document agent templates available to you via llamactl and:
LlamaExtract now has a PER_TABLE_ROW extraction target. Instead of extracting once per doc or per page, you can now apply your schema to each row in a table or each item in a bulleted list—getting back an array of structured JSON objects.
Last week, I spent some time on the DeepSeek OCR paper with @LoganMarkewich and it was genuinely interesting. It's definitely not just OCR - it's using vision as compression. 10x token reduction while maintaining accuracy.
Build Text-to-SQL systems with open source Arctic models and agentic workflows 🚀 Our own @tuana.dev is speaking at Snowflake Build to show you how to create powerful data analysis agents that can handle complex, multi-part questions:
An interesting overlap exists between memory and context. And a new(ish) memory block that was added as an integration to @llama_index is (imo) - a great demonstration of that 👉 the Artifact Memory Block
This past Monday I had the pleasure of joining a panel about open-source and AI, hosted by Merantix at the London AI Hub.
We're opening up early access to LlamaAgents - which allows you to go from local LlamaIndex agent workflows to deployed agents in a matter of minutes.
Wrote about something I've been thinking about lately: how AI coding agents are changing how we build AI agents themselves At LlamaIndex, we've been experimenting with using coding agents like Cursor and Claude Code to speed up build agentic workflows themselves + their UIs
We're making 𝐯𝐢𝐛𝐞-𝐥𝐥𝐚𝐦𝐚 with and for LlamaIndex a lot easier.. Last week we released vibe-llama, a tool developed by @cle-does-things.bsky.social
This is not GraphRAG, it comes before.. Last week, me and Tomaz (from neo4j) published another demo together. The idea: you have a bunch of unstructured documents (think legal, PDFs etc) and you want to construct a knowledge graph out of them.
OpenAI just dropped new open source models 🔥 My colleague Logan spent his morning testing gpt-oss-20b - which runs on consumer hardware, is Apache 2.0 licensed, and the reasoning quality is solid. Also, full chain-of-thought access so you can see exactly how it's thinking.
Ok this is prettyyy cool, another @llamaindex.bsky.social workflows implementation from @cle-does-things.bsky.social 👇
Last week @cle-does-things.bsky.social and I created @llamaindex.bsky.social nodes for @n8n.io Here's what we got: · LlamaExtract: use extraction agents within n8n workflows · LlamaParse: parse complex documents · LlamaCloud: use your existing LlamaCloud indexes as knowledge bases within n8n
A new walkthrough for a research agent using Llamaindex and Google Gemini, fresh out the oven. Given a topic: 🌎 Use Gemini 2.5 pro with its server side google search tool 📝 Create an agent that takes notes as it gets results from its websearch
Watch as Claude acts as a document agent using LlamaCloud MCP tools to: - Query any index with custom parsing. - Use LlamaExtract agents to pull structured data based on LlamaCloud's schema. The demo features extraction agents for invoices and technical resumes. youtu.be/IL3CEONiDF4
Running the Open-Source LlamaCloud MCP Server
In this video, we run the open-source LlamaCloud MCP server which serves a few tools that we can add more to: - Tools to query any index in LlamaCloud - Tool...
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With all of this "context engineering" chatter, I've been thinking about how much of LLM performance hinges not just on model architecture, but on how you feed it context a lot lately. So, co-authored a piece on Context Engineering with Logan: Here it is: 🔗 www.llamaindex.ai/blog/contex...
Context Engineering - What it is, and techniques to consider — LlamaIndex - Build Knowledge Assistants over your Enterprise Data
LlamaIndex is a simple, flexible framework for building knowledge assistants using LLMs connected to your enterprise data.
llamaindex.ai
I like this new terminology around context engineering that's picking up. It's a good way to think about how to build actually effective agentic applications.
Today we're announcing the first stable release of @llama_index workflows. A lightweight framework for building complex, multi-step agentic AI applications in Python and Typescript www.llamaindex.ai/blog/announ...
Announcing Workflows 1.0: A Lightweight Framework for Agentic systems — LlamaIndex - Build Knowledge Assistants over your Enterprise Data
LlamaIndex is a simple, flexible framework for building knowledge assistants using LLMs connected to your enterprise data.
llamaindex.ai
Since MCP there are questions about whether it removes the need for you to build your own RAG workflows with vector search. And my answer to that is:
Last week, we concluded the @gradio-hf.bsky.social MCP hackathon with @hf.co. The project that one the @llamaindex.bsky.social prize was the "Nasa Space Explorer" 🔭🪐 3 servers that provide live data on: ☄️ Asteroids 🤖 the Mars Rover 🌌 Astronomy Here's the space: huggingface.co/spaces/Agen...
Yesterday Zoom announced Zoom RTMS at the developer summit, which gives you real-time access to audio, video, and transcript data from Zoom Meetings.
