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LiteParse is the best model-free, open-source document parser for AI agents. It now gets a first-class landing page on our website 💫 Our company mission is building the world's best agentic document processing platform, and liteparse is the central pillar behind our OSS efforts. It's blazing fast (and getting... show more

Jerry Liu

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69,844 просмотров • 2 месяцев назад •via X (Twitter)

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Parse text from any PDF in seconds and give it to Claude Code 📑🤖 LiteParse is our open-source, model-free document parser that lets you digitalize text from any document in seconds. This is especially useful for coding agents, which are great at reading plaintext files but terrible at reading traditional document formats (PDF, Office docs). We have a one-line installable skill that lets you plug LiteParse into Claude Code and 40+ other agents. Repo is here:

Parse text from any PDF in seconds and give it to Claude Code 📑🤖 LiteParse is our open-source, model-free document parser that lets you digitalize text from any document in seconds. This is especially useful for coding agents, which are great at reading plaintext files but terrible at reading traditional document formats (PDF, Office docs). We have a one-line installable skill that lets you plug LiteParse into Claude Code and 40+ other agents. Repo is here:

Jerry Liu

29,746 просмотров • 2 месяцев назад

We built the fastest PDF -> markdown parser in the world 🚀⚡️ AND it’s more accurate than any other open-source, model-free parser (pymupdf4llm, opendataloader, pdf-inspector, markitdown) on 3 standardized benchmarks: olmOCR0-bench, opendataloader-bench, ParseBench Introducing LiteParse v2.1. The v2 base version was already the fastest document->text parser on the planet, and with this new release we’ve introduced markdown. It is fully open-source (Apache 2.0) and free, is usable from CLI/Rust/Node/Python/WASM, and is also installable as a one-click agent skill. Check it out: Come check out LiteParse:

We built the fastest PDF -> markdown parser in the world 🚀⚡️ AND it’s more accurate than any other open-source, model-free parser (pymupdf4llm, opendataloader, pdf-inspector, markitdown) on 3 standardized benchmarks: olmOCR0-bench, opendataloader-bench, ParseBench Introducing LiteParse v2.1. The v2 base version was already the fastest document->text parser on the planet, and with this new release we’ve introduced markdown. It is fully open-source (Apache 2.0) and free, is usable from CLI/Rust/Node/Python/WASM, and is also installable as a one-click agent skill. Check it out: Come check out LiteParse:

Jerry Liu

269,151 просмотров • 3 дней назад

LiteParse Samples 📄🧑‍🏫 LiteParse is our free and fast document parser that can parse text with bounding boxes from any document. I’ve created a new repository that contains some demos on how you can make use of its outputs! ✅ Comparison against PyPDF and PyMuPDF ✅ Visual Citations: search for any keyword and see joined bounding boxes pop up in the source images It should be a default tool to help AI agents OCR any document type (supports PDF, Word, Powerpoint + dozens of other formats), before heavier-weight VLM-based document parsing solutions (like our own LlamaParse). LiteParse Samples repo: LiteParse:

LiteParse Samples 📄🧑‍🏫 LiteParse is our free and fast document parser that can parse text with bounding boxes from any document. I’ve created a new repository that contains some demos on how you can make use of its outputs! ✅ Comparison against PyPDF and PyMuPDF ✅ Visual Citations: search for any keyword and see joined bounding boxes pop up in the source images It should be a default tool to help AI agents OCR any document type (supports PDF, Word, Powerpoint + dozens of other formats), before heavier-weight VLM-based document parsing solutions (like our own LlamaParse). LiteParse Samples repo: LiteParse:

Jerry Liu

13,132 просмотров • 2 месяцев назад

Last week we revamped Liteparse to be the fastest PDF parser out there ⚡️ An underrated part of liteparse is it doesn't just give you text. It gives you bounding boxes that a coding agent can use to paint exact audit trails back to the source document. For instance, check out the deep research skill we compiled in liteparse_samples: Come check out liteparse: We are hard at work making liteparse even better (e.g. Markdown support). Please feel free to open up issues, PRs, and let us know your feature requests 🙏

Last week we revamped Liteparse to be the fastest PDF parser out there ⚡️ An underrated part of liteparse is it doesn't just give you text. It gives you bounding boxes that a coding agent can use to paint exact audit trails back to the source document. For instance, check out the deep research skill we compiled in liteparse_samples: Come check out liteparse: We are hard at work making liteparse even better (e.g. Markdown support). Please feel free to open up issues, PRs, and let us know your feature requests 🙏

Jerry Liu

45,815 просмотров • 19 дней назад

Our OSS engineer Clelia Bertelli (🦙/acc) 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 retrieval pipeline using open tools from across the ecosystem: • Parsing: LiteParse, the fast and accurate document parser we recently open sourced • Chunking: Chonkie • Embeddings: A local Nomic model via Hugging Face transformers.js • Vector storage: A local Qdrant edge shard (custom-built in Rust and compiled as a native add-on) • Retrieval: Query stored files with optional path-based filtering and configurable relevance thresholds • Runtime: Bun for speed and versatility 💻 Check out the repository and try it yourself: 📚 LiteParse docs:

Our OSS engineer Clelia Bertelli (🦙/acc) 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 retrieval pipeline using open tools from across the ecosystem: • Parsing: LiteParse, the fast and accurate document parser we recently open sourced • Chunking: Chonkie • Embeddings: A local Nomic model via Hugging Face transformers.js • Vector storage: A local Qdrant edge shard (custom-built in Rust and compiled as a native add-on) • Retrieval: Query stored files with optional path-based filtering and configurable relevance thresholds • Runtime: Bun for speed and versatility 💻 Check out the repository and try it yourself: 📚 LiteParse docs:

LlamaIndex 🦙

14,853 просмотров • 2 месяцев назад

Our core mission today is using AI to solve document OCR. All of our product offerings, from commercial (LlamaParse) to open-source (LiteParse, ParseBench), are fully aligned towards solving this problem. Introducing our revamped website 👇

Our core mission today is using AI to solve document OCR. All of our product offerings, from commercial (LlamaParse) to open-source (LiteParse, ParseBench), are fully aligned towards solving this problem. Introducing our revamped website 👇

Jerry Liu

26,552 просмотров • 2 месяцев назад

Introducing LiteParse - the best model-free document parsing tool for AI agents 💫 ✅ It’s completely open-source and free. ✅ No GPU required, will process ~500 pages in 2 seconds on commodity hardware ✅ More accurate than PyPDF, PyMuPDF, Markdown. Also way more readable - see below for how we parse tables!! ✅ Supports 50+ file formats, from PDFs to Office docs to images ✅ Is designed to plug and play with Claude Code, OpenClaw, and any other AI agent with a one-line skills install. Supports native screenshotting capabilities. We spent years building up LlamaParse by orchestrating state-of-the-art VLMs over the most complex documents. Along the way we realized that you could get quite far on most docs through fast and cheap text parsing. Take a look at the video below. For really complex tables within PDFs, we output them in a spatial grid that’s both AI and human-interpretable. Any other free/light parser light PyPDF will destroy the representation of this table and output a sequential list. This is not a replacement for a VLM-based OCR tool (it requires 0 GPUs and doesn’t use models), but it is shocking how good it is to parse most documents. Huge shoutout to Logan Markewich and Clelia Bertelli (🦙/acc) for all the work here. Come check it out: Repo:

Introducing LiteParse - the best model-free document parsing tool for AI agents 💫 ✅ It’s completely open-source and free. ✅ No GPU required, will process ~500 pages in 2 seconds on commodity hardware ✅ More accurate than PyPDF, PyMuPDF, Markdown. Also way more readable - see below for how we parse tables!! ✅ Supports 50+ file formats, from PDFs to Office docs to images ✅ Is designed to plug and play with Claude Code, OpenClaw, and any other AI agent with a one-line skills install. Supports native screenshotting capabilities. We spent years building up LlamaParse by orchestrating state-of-the-art VLMs over the most complex documents. Along the way we realized that you could get quite far on most docs through fast and cheap text parsing. Take a look at the video below. For really complex tables within PDFs, we output them in a spatial grid that’s both AI and human-interpretable. Any other free/light parser light PyPDF will destroy the representation of this table and output a sequential list. This is not a replacement for a VLM-based OCR tool (it requires 0 GPUs and doesn’t use models), but it is shocking how good it is to parse most documents. Huge shoutout to Logan Markewich and Clelia Bertelli (🦙/acc) for all the work here. Come check it out: Repo:

Jerry Liu

256,087 просмотров • 3 месяцев назад

Our default document parsing mode is now able to parse a complex research report with multiple embedded charts on a single page. This is the cheapest document OCR model out there that can turn complex visual documents into LLM-ready markdown. This is our agentic mode in LlamaParse. It starts at ~1c per page; if you’re looking to scale consumption we offer volume discounts. Come check it out! Sign up:

Our default document parsing mode is now able to parse a complex research report with multiple embedded charts on a single page. This is the cheapest document OCR model out there that can turn complex visual documents into LLM-ready markdown. This is our agentic mode in LlamaParse. It starts at ~1c per page; if you’re looking to scale consumption we offer volume discounts. Come check it out! Sign up:

Jerry Liu

15,479 просмотров • 4 месяцев назад

“Intelligent Document Processing” 📑🧪 as an industry is gone . With our latest release this week, *anyone* can build and deploy a specialized document agent in seconds ⚡️🤖, and customize the steps via code. Let’s take a tour through our invoice processing and contract matching agent: given an invoice, extract out vendor details and line items, and match it against the corresponding MSA with the vendor. 1️⃣ Put in your name and API key, and deploy the agent in 5 seconds 2️⃣ Upload some sample contracts and invoices, and watch the workflow run. 3️⃣ If you want to customize it, you can clone our source repository, modify the internals, and deploy the agent! It is both more accurate and more customizable than existing IDP solutions. With coding agents today, the ease of use is equivalent too. Click on the “agents” tab in LlamaCloud to check it out! Invoice processing repo: LlamaAgents Docs:

“Intelligent Document Processing” 📑🧪 as an industry is gone . With our latest release this week, anyone can build and deploy a specialized document agent in seconds ⚡️🤖, and customize the steps via code. Let’s take a tour through our invoice processing and contract matching agent: given an invoice, extract out vendor details and line items, and match it against the corresponding MSA with the vendor. 1️⃣ Put in your name and API key, and deploy the agent in 5 seconds 2️⃣ Upload some sample contracts and invoices, and watch the workflow run. 3️⃣ If you want to customize it, you can clone our source repository, modify the internals, and deploy the agent! It is both more accurate and more customizable than existing IDP solutions. With coding agents today, the ease of use is equivalent too. Click on the “agents” tab in LlamaCloud to check it out! Invoice processing repo: LlamaAgents Docs:

Jerry Liu

34,467 просмотров • 6 месяцев назад

Today, we're introducing our document parser built specifically for RAG. The parser combines the best vision, OCR, and vision language models to deliver unmatched accuracy. Try it for free today—the first 500+ pages are on us! 🧵 1/

Today, we're introducing our document parser built specifically for RAG. The parser combines the best vision, OCR, and vision language models to deliver unmatched accuracy. Try it for free today—the first 500+ pages are on us! 🧵 1/

Douwe Kiela

1,308,495 просмотров • 1 год назад

We've spent years building LlamaParse into the most accurate document parser for production AI. Along the way, we learned a lot about what fast, lightweight parsing actually looks like under the hood. Today, we're open-sourcing a light-weight core of that tech as LiteParse 🦙 It's a CLI + TS-native library for layout-aware text parsing from PDFs, Office docs, and images. Local, zero Python dependencies, and built specifically for agents and LLM pipelines. Think of it as our way of giving the community a solid starting point for document parsing: npm i -g @llamaindex/liteparse lit parse anything.pdf - preserves spatial layout (columns, tables, alignment) - built-in local OCR, or bring your own server - screenshots for multimodal LLMs - handles PDFs, office docs, images Blog: Repo:

We've spent years building LlamaParse into the most accurate document parser for production AI. Along the way, we learned a lot about what fast, lightweight parsing actually looks like under the hood. Today, we're open-sourcing a light-weight core of that tech as LiteParse 🦙 It's a CLI + TS-native library for layout-aware text parsing from PDFs, Office docs, and images. Local, zero Python dependencies, and built specifically for agents and LLM pipelines. Think of it as our way of giving the community a solid starting point for document parsing: npm i -g @llamaindex/liteparse lit parse anything.pdf - preserves spatial layout (columns, tables, alignment) - built-in local OCR, or bring your own server - screenshots for multimodal LLMs - handles PDFs, office docs, images Blog: Repo:

LlamaIndex 🦙

580,651 просмотров • 3 месяцев назад

Today we’re launching our first homegrown AI model: an open source turn detection model for building voice agents. Instead of relying solely on voice activity detection (VAD), which only considers when a user is speaking, our model also considers what has and is being said in the context of a conversation and predicts when a user is finished expressing their thoughts before the agent responds. Conversations with AI voice agents using this new model flow much more naturally without constant interruptions from the AI— check it out (more videos, details, and code in the thread):

Today we’re launching our first homegrown AI model: an open source turn detection model for building voice agents. Instead of relying solely on voice activity detection (VAD), which only considers when a user is speaking, our model also considers what has and is being said in the context of a conversation and predicts when a user is finished expressing their thoughts before the agent responds. Conversations with AI voice agents using this new model flow much more naturally without constant interruptions from the AI— check it out (more videos, details, and code in the thread):

LiveKit

126,817 просмотров • 1 год назад

We put 1000s of hours into building open-source camera glasses And now we're giving away everything we learned for free. Checkout this in-depth teardown of the Mentra Live smart glasses. As an OS company, our goal is to spread our OS. That goal encourages us to do crazy things, like build the world's best AI glasses for business and then show you how we made them... all in the name of spreading the OS. It also convinced us to make it 100% open source, so adoption is faster and easier. We're at risk of our competitors easily copypasting our code now... all in the name of spreading our OS. Now we've built the glasses for you, and we've taken the risk, and we've released an open SDK. Now your AI apps and agents can enter the real world on smart glasses. So now, what will you build?

We put 1000s of hours into building open-source camera glasses And now we're giving away everything we learned for free. Checkout this in-depth teardown of the Mentra Live smart glasses. As an OS company, our goal is to spread our OS. That goal encourages us to do crazy things, like build the world's best AI glasses for business and then show you how we made them... all in the name of spreading the OS. It also convinced us to make it 100% open source, so adoption is faster and easier. We're at risk of our competitors easily copypasting our code now... all in the name of spreading our OS. Now we've built the glasses for you, and we've taken the risk, and we've released an open SDK. Now your AI apps and agents can enter the real world on smart glasses. So now, what will you build?

cayden 凯登

20,250 просмотров • 26 дней назад

The MiniMax M2 model is mind-blowing! It's open-source. It outperforms Gemini 2.5, Claude 4.1, and Qwen3 across coding and tool-use benchmarks. Right now, it's one of the world's top 5 models in intelligence! And here is the best part: Claude is one of the best models you can use today, and MiniMax M2 costs only 8% of that! It's smaller, faster, and cheaper. Extremely efficient at using tokens. Minimax M2's biggest strength: High agentic capabilities. The model can plan and execute complex multi-tool workflows. It's reliable and very robust at executing long-horizon tool chains. In summary: • Low latency • Very cheap • Excels at agentic tasks • Open-source The model currently powers the MiniMax Agent and is available for a free global trial. You can access MiniMax M2's API here: To access the agent: And here is the MiniMax website: Thanks to the MiniMax team for showing me the ropes and partnering with me on this post.

The MiniMax M2 model is mind-blowing! It's open-source. It outperforms Gemini 2.5, Claude 4.1, and Qwen3 across coding and tool-use benchmarks. Right now, it's one of the world's top 5 models in intelligence! And here is the best part: Claude is one of the best models you can use today, and MiniMax M2 costs only 8% of that! It's smaller, faster, and cheaper. Extremely efficient at using tokens. Minimax M2's biggest strength: High agentic capabilities. The model can plan and execute complex multi-tool workflows. It's reliable and very robust at executing long-horizon tool chains. In summary: • Low latency • Very cheap • Excels at agentic tasks • Open-source The model currently powers the MiniMax Agent and is available for a free global trial. You can access MiniMax M2's API here: To access the agent: And here is the MiniMax website: Thanks to the MiniMax team for showing me the ropes and partnering with me on this post.

Santiago

91,142 просмотров • 7 месяцев назад

GPT-5 is live across the Vercel AI Cloud, and it's available: • on AI Gateway • as a model in • in our new open-source vibe coding platform

GPT-5 is live across the Vercel AI Cloud, and it's available: • on AI Gateway • as a model in • in our new open-source vibe coding platform

Vercel

14,965 просмотров • 10 месяцев назад

🔗 Announcing LangChain OSS Skills LangChain has the most popular frameworks for building AI agents — and now your coding agent can be an expert in it. We're excited to release the first iteration of LangChain OSS Skills, giving your agent expertise in our open source frameworks. The skills include guidance on how to use langchain, langgraph, and deepagents to effectively build agents. ➡️ Install our OSS skills for your coding agent here: ➡️ Read more:

🔗 Announcing LangChain OSS Skills LangChain has the most popular frameworks for building AI agents — and now your coding agent can be an expert in it. We're excited to release the first iteration of LangChain OSS Skills, giving your agent expertise in our open source frameworks. The skills include guidance on how to use langchain, langgraph, and deepagents to effectively build agents. ➡️ Install our OSS skills for your coding agent here: ➡️ Read more:

LangChain OSS

65,840 просмотров • 3 месяцев назад

The time has come 🔥 We're thrilled to announce the Beta version of our SōzōAI App! Just a simple prompt to trade, research or create your own AI agents - $SOAI is the first all-in-one AI platform. Free and fully open-source, try it now 🔽

The time has come 🔥 We're thrilled to announce the Beta version of our SōzōAI App! Just a simple prompt to trade, research or create your own AI agents - $SOAI is the first all-in-one AI platform. Free and fully open-source, try it now 🔽

SōzōAI

119,090 просмотров • 1 год назад

We are now Cult.Repo. The original creators behind the iconic Open Source documentaries (Vue, React, GraphQL) are back together! Honeypot is now called Cult.Repo and is independently-owned. We are on a mission to document the complete history of every major open source language ever created. With 250K subscribers and over 15M views, we're building on our foundation as creators of the acclaimed Open Source Origin Story documentary format. Coming in 2025: Python Software Foundation, Vite ⚡ documentaries and much more. Our independence is core to our mission. We believe the human stories behind open source deserve authentic, in-depth storytelling. Our new model is powered directly by: - Community support from viewers - Sponsorships from organizations that champion open source This transition represents our commitment to independent, meaningful tech storytelling that honours the collaborative spirit of open source itself.

We are now Cult.Repo. The original creators behind the iconic Open Source documentaries (Vue, React, GraphQL) are back together! Honeypot is now called Cult.Repo and is independently-owned. We are on a mission to document the complete history of every major open source language ever created. With 250K subscribers and over 15M views, we're building on our foundation as creators of the acclaimed Open Source Origin Story documentary format. Coming in 2025: Python Software Foundation, Vite ⚡ documentaries and much more. Our independence is core to our mission. We believe the human stories behind open source deserve authentic, in-depth storytelling. Our new model is powered directly by: - Community support from viewers - Sponsorships from organizations that champion open source This transition represents our commitment to independent, meaningful tech storytelling that honours the collaborative spirit of open source itself.

Cult.Repo

70,722 просмотров • 1 год назад

Today we're introducing the Chat SDK project, a formalization of our successful chat⁠.vercel⁠.ai template. Our goal is to open source the best practices and building blocks for building the next ChatGPT and v0-like UIs. It supports artifacts / canvas, code interpreting, and of course it's based on AI SDK. Excited to keep improving its capabilities together with the community.

Today we're introducing the Chat SDK project, a formalization of our successful chat⁠.vercel⁠.ai template. Our goal is to open source the best practices and building blocks for building the next ChatGPT and v0-like UIs. It supports artifacts / canvas, code interpreting, and of course it's based on AI SDK. Excited to keep improving its capabilities together with the community.

Guillermo Rauch

127,117 просмотров • 1 год назад

ELON: CHINA HAS THE BEST OPEN SOURCE AI MODELS RIGHT NOW “The best open source models are generally from China, which is bizarre. I think the second best one, or maybe it’s better than second best, is Grok 2.5. The open source model is actually very good, and we will continue to open source our models.” Source: The All-In Podcast

ELON: CHINA HAS THE BEST OPEN SOURCE AI MODELS RIGHT NOW “The best open source models are generally from China, which is bizarre. I think the second best one, or maybe it’s better than second best, is Grok 2.5. The open source model is actually very good, and we will continue to open source our models.” Source: The All-In Podcast

Mario Nawfal

1,163,582 просмотров • 7 месяцев назад