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LlamaIndex @llamaindex.bsky.social · 12/05/2026

It also integrates easily with: - @redis.io for caching and rate limiting - @opentelemetry.io -compatible collectors for traces and metrics - observability tools like Jaeger, Prometheus and Grafana

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LlamaIndex @llamaindex.bsky.social · 12/05/2026

Deploy it as: 🐳 a @docker.com container ⚡ or a serverless Express.js API

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LlamaIndex @llamaindex.bsky.social · 12/05/2026

Need document parsing that stays fully local and private? 👀 Meet liteparse-server, a self-hostable, open-source HTTP server for parsing documents and generating screenshots from PDFs, Office files, and images. ✅ 100% self-hosted ✅ Private by default ✅ Open source ✅ Built for production deployments

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LlamaIndex @llamaindex.bsky.social · 11/05/2026

Mount your local workspace, give the agent shell access, and let it do its magic 🪄 👩‍💻 GitHub: github.com/run-llama/s... 📚 Learn more about LiteParse: developers.llamaindex.ai/liteparse?u...–

github.com

GitHub - run-llama/sandboxed-lit: Sandboxed shell agent with access to LiteParse

Sandboxed shell agent with access to LiteParse. Contribute to run-llama/sandboxed-lit development by creating an account on GitHub.

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LlamaIndex @llamaindex.bsky.social · 11/05/2026

- LiteParse, our lightning-fast local parser for PDFs, images, Office files, and more - A secure sandbox powered by MicroSandbox - Full filesystem mounting, so your agent can safely interact with local files inside the sandbox

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LlamaIndex @llamaindex.bsky.social · 11/05/2026

Ever wished your agent could read PDFs, images, and Office documents as easily as plain text? Or combine the safety of a secure sandbox with the full power of Bash access? We built exactly that. Meet 𝘀𝗮𝗻𝗱𝗯𝗼𝘅𝗲𝗱-𝗹𝗶𝘁, a Rust 🦀 CLI agent that combines:

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LlamaIndex @llamaindex.bsky.social · 07/05/2026

The guide itself relies on some fun hacks with vite and mocking. We expect this process to improve with future releases, so stay tuned!

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LlamaIndex @llamaindex.bsky.social · 07/05/2026

A few weeks ago @simonw got Claude to port LiteParse to the browser. Today, we are launching that work as a complete guide in our docs! developers.llamaindex.ai/liteparse/g...

developers.llamaindex.ai

Browser Usage

Run LiteParse in the browser with Vite.

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LlamaIndex @llamaindex.bsky.social · 06/05/2026

Three steps, that’s it: 🔑 Add your API key (securely stored on-device) 📸 Snap a photo of anything with text 📄 Parse it and, in under a minute, get clean, copyable text No hassle, no manual typing.

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LlamaIndex @llamaindex.bsky.social · 06/05/2026

What if you could extract text from any photo on your phone? We built LlamaParse Mobile, an @expo.dev + @reactnative.dev app for iOS & Android, powered by the LlamaParse TypeScript SDK 📱

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LlamaIndex @llamaindex.bsky.social · 06/05/2026

LlamaIndex NYC takeover, 5/13 🗽 Our CEO Jerry Liu is in town. Two events, open to every NYC builder: 🛠️ FinParse Workshop — laptops out, hands-on with @jerryjliu0 → luma.com/updli8i6 🍕 AI Engineers on Tap — happy hour w/ @tabs → luma.com/tklfgwh8

luma.com

NYC AI Engineer On Tap · Luma

Calling all AI Engineers in NYC. What happens when an AI infrastructure powerhouse (LlamaIndex) and a fintech darling (Tabs) walk into a bar? You get the…

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LlamaIndex @llamaindex.bsky.social · 30/04/2026

👩‍💻 Explore the repo to see it in action: github.com/render-exam... 📚 And check out the step-by-step breakdown: render.com/blog/buildi...

render.com

Building Document Pipelines That Actually Scale

Create a distributed processing engine with LlamaIndex and Render Workflows.

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LlamaIndex @llamaindex.bsky.social · 30/04/2026

📝 Leverages the LlamaParse platform to parse, classify, extract, and retrieve information from documents ⚙️ Uses Render Workflows to distribute tasks and accelerate background processing ⚡ Deploys a lightweight server and database on Render, giving you an instant interface into your pipeline

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LlamaIndex @llamaindex.bsky.social · 30/04/2026

Building scalable, distributed document processing pipelines isn’t easy. That’s why we teamed up with @render.com to build a system that:

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LlamaIndex @llamaindex.bsky.social · 29/04/2026

We wrote up all of it, from the OAuth flow, to the token-based upload design, to the tradeoffs we hit along the way📝 📚 Read the full blog: <blog-link> 👩‍💻 GitHub repository: github.com/run-llam/mc...

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LlamaIndex @llamaindex.bsky.social · 29/04/2026

Building a production MCP server surfaced some challenges: getting auth to align with an existing platform identity system using WorkOS, working around MCP's lack of built-in file upload support, and making deployments, rate limiting and observability feel native with @vercel.com and @axiom.co

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LlamaIndex @llamaindex.bsky.social · 29/04/2026

Once connected, you'll be able to: 📁 Parse documents into clean markdown 🔍 Classify files against your own categories ✂️ Split long documents into labelled sections ⬆️ Upload files via URL or a browser-based upload flow

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LlamaIndex @llamaindex.bsky.social · 29/04/2026

Parsing documents with AI agents just got a lot more seamless🚀 We've rebuilt the LlamaParse MCP server to handle your document processing workflows, and you can connect it today to any MCP-compatible client at mcp.llamaindex.ai/mcp 🌐

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LlamaIndex @llamaindex.bsky.social · 27/04/2026

🔍 Cross-document validation with Claude — catches W-2/pay-stub gaps, unexplained Zelle/Venmo deposits, employer name mismatches 📊 Self-contained HTML report with a COMPLETE / REVIEW / FLAG decision

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LlamaIndex @llamaindex.bsky.social · 27/04/2026

Loan processors spend 40–60% of their time reconciling income across tax returns, pay stubs, W-2s, and bank statements. We built an end-to-end pipeline that automates it with LlamaParse + the Claude Agent SDK: 📄 Schema-driven extraction across 4 doc types with confidence scores + citations

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LlamaIndex @llamaindex.bsky.social · 23/04/2026

ParseBench is now live on @Kaggle. The first document OCR benchmark built for AI agents — 2,000 enterprise pages, 167K+ test rules, 5 dimensions that actually break downstream agents. Benchmark your parser against 14 methods including GPT-5 Mini, Gemini 3, Textract, and LlamaParse.

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LlamaIndex @llamaindex.bsky.social · 22/04/2026

LiteParse: our open-source, layout-aware PDF parser for AI agents. The secret? Grid projection. Instead of heavy ML layout models or flat text extraction, it projects text onto a monospace grid so alignment preserves structure. Full deep dive into the grid projection algorithm behind the magic ↓

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LlamaIndex @llamaindex.bsky.social · 10/04/2026

Raw financial PDFs → structured agent-ready data. We'll build it live. Register → landing.llamaindex.ai/liteparse

landing.llamaindex.ai

Build a Financial Research Agent with LiteParse

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LlamaIndex @llamaindex.bsky.social · 10/04/2026

LiteParse hit 4K+ GitHub stars in 3 weeks. ~500 pages in 2 seconds. No GPU. No API keys. 50+ file formats. Now @LoganMarkewich, our Head of Open Source, will show you how to build with it. Live workshop — April 28, 9 AM PST: Build a Financial Due Diligence Agent with LiteParse.

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LlamaIndex @llamaindex.bsky.social · 09/04/2026

📚Learn more about the problem, and how the skills solve it: <blog-link> 🦙 Get started with LlamaParse: cloud.llamaindex.ai/signup?utm_...

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LlamaIndex @llamaindex.bsky.social · 09/04/2026

That’s why we created LlamaParse and LiteParse Agent Skills, designed to give agents access to a deeper layer of document understanding, enabling more reliable knowledge extraction and automation across complex documents📝

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LlamaIndex @llamaindex.bsky.social · 09/04/2026

When it comes to PDFs and other unstructured documents, most agents struggle. The tools they rely on often return only raw text, losing critical context like layout, tables, and images❌

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LlamaIndex @llamaindex.bsky.social · 09/04/2026

Agents like OpenClaw are incredibly powerful, as long as the information they receive is clean and structured🦞

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LlamaIndex @llamaindex.bsky.social · 07/04/2026

📚 Full breakdown: www.lancedb.com/blog/smart-... 🦙 Learn more about LiteParse: developers.llamaindex.ai/liteparse/?...

developers.llamaindex.ai

What is LiteParse?

Fast, local PDF parsing with spatial text parsing, OCR, and bounding boxes.

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LlamaIndex @llamaindex.bsky.social · 07/04/2026

In our evaluations, the agent achieved near-perfect scores across most tasks, showing how strong parsing (LiteParse) plus multimodal storage (LanceDB) can significantly improve agentic search pipelines📈

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LlamaIndex @llamaindex.bsky.social · 07/04/2026

1. LiteParse extracts structured text and captures page screenshots 2. We embed the text with Gemini 2 Embedding 3. Text, vectors, and images are stored in LanceDB 4. A Claude agent retrieves the relevant context and, if text isn’t enough, it falls back to image-based reasoning on the screenshots

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LlamaIndex @llamaindex.bsky.social · 07/04/2026

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:

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LlamaIndex @llamaindex.bsky.social · 07/04/2026

Open call to fintech leaders in NYC 🏦 May 13, in-person workshop with @jerryjliu0 on turning complex financial docs into LLM-ready data using agentic OCR. Build real pipelines. Hear from a Top 5 PE firm's production agent. Make sure to bring your laptops→ luma.com/updli8i6

luma.com

Turn Complex Financial Docs into LLM-ready Data with Jerry Liu and LlamaIndex · Luma

A hands-on workshop for engineers building VLM-powered OCR that works on real-world financial documents. Most document pipelines fail quietly. They work on a…

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LlamaIndex @llamaindex.bsky.social · 02/04/2026

And for those who need a transition period: Extract v1 will remain accessible via the UI under 'Settings → General' for a limited time.

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LlamaIndex @llamaindex.bsky.social · 02/04/2026

✦ 𝗖𝗼𝗻𝗳𝗶𝗴𝘂𝗿𝗮𝗯𝗹𝗲 𝗱𝗼𝗰𝘂𝗺𝗲𝗻𝘁 𝗽𝗮𝗿𝘀𝗶𝗻𝗴: now you can control how your documents get parsed before extraction, giving you more flexibility and better results end to end.

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LlamaIndex @llamaindex.bsky.social · 02/04/2026

✦ 𝗣𝗿𝗲-𝘀𝗮𝘃𝗲𝗱 𝗲𝘅𝘁𝗿𝗮𝗰𝘁 𝗰𝗼𝗻𝗳𝗶𝗴𝘂𝗿𝗮𝘁𝗶𝗼𝗻𝘀: load your saved extraction configs directly, so you can skip the setup and get straight to extracting.

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LlamaIndex @llamaindex.bsky.social · 02/04/2026

✦ 𝗦𝗶𝗺𝗽𝗹𝗶𝗳𝗶𝗲𝗱 𝘁𝗶𝗲𝗿𝘀: we've replaced modes with cleaner, more intuitive tiers. (And stay tuned: agentic plus is coming to Extract too, very soon.)

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LlamaIndex @llamaindex.bsky.social · 02/04/2026

After the release of Parse v2, Extract is also getting an upgrade — 𝗶𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝗶𝗻𝗴 𝗘𝘅𝘁𝗿𝗮𝗰𝘁 𝘃2! 🎉 We've been reworking the experience from the ground up to make document extraction more powerful and easier to use than ever. Here's what's new:

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LlamaIndex @llamaindex.bsky.social · 31/03/2026

90+ leading investors and corporate development leaders. It recognizes the private companies wi th the most potential to shape the future of enterprise technology. Thank you to Wing Venture Capital and Eric Newcomer, and congratulations to all the companies honored this year.

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LlamaIndex @llamaindex.bsky.social · 31/03/2026

LlamaIndex is proud to be named to the 2026 Enterprise Tech 30, #3 in the Early Stage category. The ET30 is an annual list by @Wing_VC and Eric Newcomer, voted on by

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LlamaIndex @llamaindex.bsky.social · 30/03/2026

We’ve moved to a new office and it’s time to celebrate. Swing by this Thursday to meet our team, grab a bite, and make new friends. Note: Space is limited, so please RSVP early. luma.com/mkh44c7w

luma.com

Startup Party Up for First Thursday · Luma

We’ve moved to the 'AI Waterfront' and it’s time to celebrate. Swing by on April 2nd to see our new office on 2nd street, meet our team, and make new…

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LlamaIndex @llamaindex.bsky.social · 30/03/2026

• Retrieval: Query stored files with optional path-based filtering and configurable relevance thresholds • Runtime: @bun.sh for speed and versatility 💻 Check out the repository and try it yourself: github.com/AstraBert/l... 📚 LiteParse docs: developers.llamaindex.ai/liteparse?u...

developers.llamaindex.ai

What is LiteParse?

Fast, local PDF parsing with spatial text parsing, OCR, and bounding boxes.

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LlamaIndex @llamaindex.bsky.social · 30/03/2026

• Parsing: LiteParse, the fast and accurate document parser we recently open sourced • Chunking: @chonkie.bsky.social • Embeddings: A local model via @hf.co transformers.js • Vector storage: A local @qdrant.bsky.social edge shard (custom-built in Rust and compiled as a native add-on)

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LlamaIndex @llamaindex.bsky.social · 30/03/2026

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:

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