PdfItDown has WASM bindings that provide you with fast conversion to PDF in the browser and on the edge. You can get started by deploying a @cloudflare.social worker with less than 20 lines of code, using the snippet below👇 Full example: github.com/AstraBert/P...

Write your first agent in Rust with 𝗺𝗶𝗰𝗿𝗼𝗮𝗴𝗲𝗻𝘁𝘀🦀 Define a provider, create custom tools, load skills from local or global .𝚊𝚐𝚎𝚗𝚝𝚜/𝚜𝚔𝚒𝚕𝚕𝚜, add instructions, and stream agent events in real time🤖 Get started: microag.clelia.dev ⭐ the GitHub repo: github.com/AstraBert/m...

Happy Pride Month!!!🏳️‍🌈🏳️‍⚧️ I hope each and every one of you will be able to feel how loved you are every day, by me, by the community and by all the allies out there💖

My latest setup for agentic engineering in personal projects includes Copilot and Pi powered by Kimi K2.6.

I miss programming by hand. My day-job is now project-leading something that acts like a know-it-all junior developer on cocaine. Worst part is, that if you look past the obvious security issues it's the most productive I've ever been.

daaaamn london

Coding agents might feel like magic, but they aren’t 🪄 That’s exactly why I’ve been eager lately to understand how they work under the hood, using the most natural approach I could think of: observability.

Coding agents shouldn’t be black boxes ❌ If you’re calling models through APIs and can configure provider settings (base URL, API key, etc.), I highly recommend putting a local instrumented API proxy in front of them. I built one for the Anthropic Messages API:

Do you actually own your document parsing infrastructure? 👀 At LlamaIndex, we wanted to make that easier, so we built 𝗹𝗶𝘁𝗲𝗽𝗮𝗿𝘀𝗲-𝘀𝗲𝗿𝘃𝗲𝗿, a lightweight HTTP backend built on top of LiteParse that can parse and generate page screenshots from PDFs, images, and Office documents🦙

I have one big problem with agentic engineering: I want agents to operate autonomously, but I also want granular, reversible control over every change they make. I could solve this by committing every intermediate step to Git, but that would completely pollute my repo history.

For 2026, I decided I'm going to build all of my side projects with Rust when possible🦀 So here's the first one: 𝗳𝗶𝗹𝗲-𝘀𝘁𝗼𝗿𝗮𝗴𝗲, a self-hostable file storage application built on a modern open source stack, with a full Rust backend and a @react.dev + @vite.dev frontend🚀 With file-storage, you get:

Scaling document pipelines is harder than it looks, and not because of tooling, but mostly because of orchestration⚙️ That's why I teamed up with @render.com and focused on building a system where each component does one job well, and scales independently:

The LlamaParse MCP got a new face, and it is now easier than ever to run document processing workflows from your agents🚀

I'll be speaking at the Applied AI Conf organized by Tech Europe!🇪🇺 On the 28th of May, I'll be in Berlin to give my talk about how you can build reliable document agents by leveraging harness engineering with the building blocks provided by @llamaindex.bsy.social 🦙

I'll be speaking at the upcoming Voxel51 event in Stuttgart this Tuesday!🚀 I'll talk about the anatomy of AI agents, with a focus on document agents and building good harnesses for them⚙️ Swing by if you're interested, and check the official page for more details: voxel51.com/events/stut...

I've been building sunbears, a typescript library for CSV data loading written in Rust🦀

ParseBench is here!📊 We’ve just released ParseBench, an open benchmark + dataset for evaluating document parsing at scale.

I'm building 𝘀𝘂𝗻𝗯𝗲𝗮𝗿𝘀, a CSV data loader library for TS written in Rust🦀 In Node, it can read a file with 1.000.000 rows in 0.3s, write the same amount of rows in 0.15s, respectively 4x and 2x faster than the `csv` package⚡

Visually rich documents are especially challenging for agents. Tables, charts, and images often break traditional document pipelines, making complex reasoning difficult📄 So we teamed up with LanceDB to build a structure-aware PDF QA pipeline🚀 Here’s how it works:

How can you improve your agentic search pipeline? I just wrote a blog post in collab with LanceDB to answer exactly that. TLDR:

At @llamaindex.bsky.social, we're committed to building the most capable document agents.

I just published a TypeScript library for loading CSV data, with an API inspired by Pandas and @pola.rs, but fully written in Rust 🦀

Our OSS engineer @cle-does-things.bsky.social recently built 𝗹𝗶𝘁𝗲𝘀𝗲𝗮𝗿𝗰𝗵, a fully local document ingestion and retrieval CLI/TUI application powered by LiteParse ⚡ litesearch demonstrates how developers can assemble a high-performance, local-first pipeline using tools from across the ecosystem:

Hey there 👋 , I built 𝗹𝗶𝘁𝗲𝘀𝗲𝗮𝗿𝗰𝗵, a fully local document ingestion and retrieval CLI and TUI app, powered by LiteParse⚡

🚀 New release: 𝗯𝗲𝘁𝘁𝗲𝗿-𝗿𝗲𝘀𝘂𝗹𝘁-𝗽𝘆 𝘃𝟭.𝟭.𝟬 Inspired by the better-result library in the JS ecosystem, I built better-result-py to bring a Rust-style Result type to Python. With v1.1.0, I introduced the 𝙾𝚔 and 𝙴𝚛𝚛 classes to make control flow clearer and more explicit:

The Google DeepMind team really cooked with Gemini 3.1 in the Live API: it's fast and the output quality is great🔥 That's why at @llamaindex.bsky.social we decided to test it out with our bread and butter: document processing📄

I created 𝘀𝗸𝗶𝗹𝗹𝘇𝘆, a simple CLI written in Rust for your agent skills📝 → 𝘴𝘬𝘪𝘭𝘭𝘻𝘺 𝘪𝘯𝘪𝘵 will allow you to create the frontmatter for a skill, also generating the required folders and skill file → 𝘴𝘬𝘪𝘭𝘭𝘻𝘺 𝘤𝘩𝘦𝘤𝘬 will validate your existing skills against the agentskills.io specification

𝗷𝗮𝗸𝗲, the Make-like task executor for Unix OS I wrote in Rust🦀, has now reached 𝘃𝟬.𝟳.𝟬! Here's what's new:

notion-cli, the app I built in Golang to interact with @notion.com pages from your terminal and with your agents, got to v0.3.0🚀 This version adds a search command, which allows your (or your agent's) flow to be smoother: search → read → modify.

So excited to see live the article Vishal and I wrote on LlamaParse x Google Gemini!