EXCLUSIVE: Researchers identified at least 83 attacks against 61 public GitHub repositories, including popular open source projects such as Google LangExtract, Trivy, Brave browser, and MLflow, in what they suspect is a coordinated supply chain campaign.
Attackers turn GitHub issues into supply chain campaign against 61 public repos in less than an hour
'The workflow automatically is triggered within a second, and if the workflow is indeed vulnerable, then the attack is executed successfully'
www.theregister.com
October 29, 2026 at 3:05 PM
EXCLUSIVE: Researchers identified at least 83 attacks against 61 public GitHub repositories, including popular open source projects such as Google LangExtract, Trivy, Brave browser, and MLflow, in what they suspect is a coordinated supply chain campaign.
Building an Intelligent GraphRAG Pipeline with LangExtract, Neo4j, Qdrant, and Ollama!
October 17, 2026 at 4:45 PM
Building an Intelligent GraphRAG Pipeline with LangExtract, Neo4j, Qdrant, and Ollama!
字段看着整齐
我先问出自原文哪一句
LangExtract 干这个
给几条例子
把大段文字收成结构
每个值对上原文位置
再生成一份高亮页
合同和病历最吃亏
错一个数
后面整份都歪
星数原帖报了
我没抄
仓库在回复
我还没拿自己的文件跑
跑过再讲漏不漏
github.com/google/lang...
我先问出自原文哪一句
LangExtract 干这个
给几条例子
把大段文字收成结构
每个值对上原文位置
再生成一份高亮页
合同和病历最吃亏
错一个数
后面整份都歪
星数原帖报了
我没抄
仓库在回复
我还没拿自己的文件跑
跑过再讲漏不漏
github.com/google/lang...
GitHub - google/langextract: A Python library for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization.
A Python library for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization. - google/langextract
github.com
September 27, 2026 at 11:54 AM
字段看着整齐
我先问出自原文哪一句
LangExtract 干这个
给几条例子
把大段文字收成结构
每个值对上原文位置
再生成一份高亮页
合同和病历最吃亏
错一个数
后面整份都歪
星数原帖报了
我没抄
仓库在回复
我还没拿自己的文件跑
跑过再讲漏不漏
github.com/google/lang...
我先问出自原文哪一句
LangExtract 干这个
给几条例子
把大段文字收成结构
每个值对上原文位置
再生成一份高亮页
合同和病历最吃亏
错一个数
后面整份都歪
星数原帖报了
我没抄
仓库在回复
我还没拿自己的文件跑
跑过再讲漏不漏
github.com/google/lang...
🚀 GitHub Intelligence Drop
quivr (Python • 🟢)
⭐ 39.5K → https://github.com/The-Vibe-Company/quivr
langextract (Python • 🟢)
⭐ 38.5K → https://github.com/google/langextract
⚡ Only signal. Zero noise.
quivr (Python • 🟢)
⭐ 39.5K → https://github.com/The-Vibe-Company/quivr
langextract (Python • 🟢)
⭐ 38.5K → https://github.com/google/langextract
⚡ Only signal. Zero noise.
September 2, 2026 at 8:21 PM
🚀 GitHub Intelligence Drop
quivr (Python • 🟢)
⭐ 39.5K → https://github.com/The-Vibe-Company/quivr
langextract (Python • 🟢)
⭐ 38.5K → https://github.com/google/langextract
⚡ Only signal. Zero noise.
quivr (Python • 🟢)
⭐ 39.5K → https://github.com/The-Vibe-Company/quivr
langextract (Python • 🟢)
⭐ 38.5K → https://github.com/google/langextract
⚡ Only signal. Zero noise.
Sweet summer child, I will leave that as an exercise for you to figure out on your own. I hope you can do it.
This still stands just fine:
Langextract and docling are LLM based pipelines used in industry.
This still stands just fine:
Langextract and docling are LLM based pipelines used in industry.
August 28, 2026 at 11:38 PM
Sweet summer child, I will leave that as an exercise for you to figure out on your own. I hope you can do it.
This still stands just fine:
Langextract and docling are LLM based pipelines used in industry.
This still stands just fine:
Langextract and docling are LLM based pipelines used in industry.
Granite Docling is a small VLM; the original Docling that has been in use for years is not, though.
Langextract is LLM scaffolding, sure.
Langextract is LLM scaffolding, sure.
August 28, 2026 at 11:41 PM
Granite Docling is a small VLM; the original Docling that has been in use for years is not, though.
Langextract is LLM scaffolding, sure.
Langextract is LLM scaffolding, sure.
Langextract was released on Jul 22, 2025.
The VLM pipeline in docling was released on Feb 26, 2025 and it was considered an experimental feature until granitedocling was released; even after granitedocling was released, it was not considered a replacement for the primary pipeline.
The VLM pipeline in docling was released on Feb 26, 2025 and it was considered an experimental feature until granitedocling was released; even after granitedocling was released, it was not considered a replacement for the primary pipeline.
August 29, 2026 at 12:42 AM
Langextract was released on Jul 22, 2025.
The VLM pipeline in docling was released on Feb 26, 2025 and it was considered an experimental feature until granitedocling was released; even after granitedocling was released, it was not considered a replacement for the primary pipeline.
The VLM pipeline in docling was released on Feb 26, 2025 and it was considered an experimental feature until granitedocling was released; even after granitedocling was released, it was not considered a replacement for the primary pipeline.
If you try to diagonally read this and make a false conclusion, do go look up things like docling and langextract - both are quite old and heavily used across industries
Multi pass pipelines with different temperatures is one of the simplest ways to detect hallucinations and bubble up as necessary
Multi pass pipelines with different temperatures is one of the simplest ways to detect hallucinations and bubble up as necessary
August 28, 2026 at 11:26 PM
If you try to diagonally read this and make a false conclusion, do go look up things like docling and langextract - both are quite old and heavily used across industries
Multi pass pipelines with different temperatures is one of the simplest ways to detect hallucinations and bubble up as necessary
Multi pass pipelines with different temperatures is one of the simplest ways to detect hallucinations and bubble up as necessary
Использование LangExtract и Gemma от Google для извлечения структурированных данных
Эффективное и точное извлечение структурированной информации из длинных неструктурированных текстов с помощью LangExtract и LLM
#ai #news
Эффективное и точное извлечение структурированной информации из длинных неструктурированных текстов с помощью LangExtract и LLM
#ai #news
Using Google’s LangExtract and Gemma for Structured Data Extraction
towardsdatascience.com
August 27, 2025 at 2:20 PM
Может ли LangExtract превратить неструктурированные клинические записи в структурированные данные?
Превращение необработанных клинических заметок в структурированные сущности с помощью LLM.
#ai #news
Превращение необработанных клинических заметок в структурированные сущности с помощью LLM.
#ai #news
Can LangExtract Turn Messy Clinical Notes into Structured Data?
towardsdatascience.com
August 20, 2025 at 6:50 AM
Представляем инструмент Google LangExtract
Делайте RAG, не делая RAG, с помощью этой мощной новой библиотеки NLP и извлечения данных
#ai #news
Делайте RAG, не делая RAG, с помощью этой мощной новой библиотеки NLP и извлечения данных
#ai #news
Introducing Google’s LangExtract tool
towardsdatascience.com
August 13, 2025 at 2:22 AM
Google выпустил LangExtract, библиотеку Python для извлечения структурированных данных из неструктурированного текста.
Google представила LangExtract, открытую библиотеку на Python, предназначенную для помощи разработчикам в извлечении структурированной информации из неструктурированных…
#ai #news
Google представила LangExtract, открытую библиотеку на Python, предназначенную для помощи разработчикам в извлечении структурированной информации из неструктурированных…
#ai #news
Google Launched LangExtract, a Python Library for Structured Data Extraction from Unstructured Text
www.infoq.com
August 10, 2025 at 3:38 PM
LangExtract - La nouvelle pépite de Google pour extraire des données structurées avec l'IA | Posts | Le site de Korben korben.info/langextract-...
LangExtract - La nouvelle pépite de Google pour extraire des données structurées avec l'IA | Le site de Korben
Il y a des combats comme cela auxquels pas grand monde ne pense et qui pourtant sont très importants. Je parle évidemment de la lutte contre le chaos du ...
korben.info
January 16, 2026 at 7:01 PM
LangExtract - La nouvelle pépite de Google pour extraire des données structurées avec l'IA | Posts | Le site de Korben korben.info/langextract-...
A Coding Guide to Build Advanced Document Intelligence Pipelines with Google LangExtract, OpenAI Models, Structured Extraction, and Interactive Visualization
In this tutorial, we explore how to use Google’s LangExtract library to transform unstructured text into structured, machine-readable…
In this tutorial, we explore how to use Google’s LangExtract library to transform unstructured text into structured, machine-readable…
A Coding Guide to Build Advanced Document Intelligence Pipelines with Google LangExtract, OpenAI Models, Structured Extraction, and Interactive Visualization
In this tutorial, we explore how to use Google’s LangExtract library to transform unstructured text into structured, machine-readable information. We begin by installing the required dependencies and securely configuring our OpenAI API key to leverage powerful language models for extraction tasks. Also, we will build a reusable extraction pipeline that enables us to process a range of document types, including contracts, meeting notes, product announcements, and operational logs.
nexttech-news.com
April 9, 2026 at 10:38 AM
A Coding Guide to Build Advanced Document Intelligence Pipelines with Google LangExtract, OpenAI Models, Structured Extraction, and Interactive Visualization
In this tutorial, we explore how to use Google’s LangExtract library to transform unstructured text into structured, machine-readable…
In this tutorial, we explore how to use Google’s LangExtract library to transform unstructured text into structured, machine-readable…
Google AI Releases LangExtract: An Open Supply Python Library That Extracts Structured Knowledge From Unstructured Textual Content Paperwork
In right this moment’s data-driven world, useful insights are sometimes buried in unstructured textual content—be it medical notes, prolonged authorized…
In right this moment’s data-driven world, useful insights are sometimes buried in unstructured textual content—be it medical notes, prolonged authorized…
Google AI Releases LangExtract: An Open Supply Python Library That Extracts Structured Knowledge From Unstructured Textual Content Paperwork
In right this moment’s data-driven world, useful insights are sometimes buried in unstructured textual content—be it medical notes, prolonged authorized contracts, or buyer suggestions threads. Extracting significant, traceable info from these paperwork is each a technical and sensible problem. Google AI’s new open-source Python library, LangExtract, is designed to deal with this hole straight, utilizing LLMs like Gemini to ship highly effective, automated extraction with traceability and transparency at its core. 1. Declarative and Traceable Extraction LangExtract lets customers outline customized extraction duties utilizing pure language directions and high-quality “few-shot” examples.
nextbusiness24.com
August 5, 2025 at 10:58 AM
Google AI Releases LangExtract: An Open Supply Python Library That Extracts Structured Knowledge From Unstructured Textual Content Paperwork
In right this moment’s data-driven world, useful insights are sometimes buried in unstructured textual content—be it medical notes, prolonged authorized…
In right this moment’s data-driven world, useful insights are sometimes buried in unstructured textual content—be it medical notes, prolonged authorized…
Google AI Releases LangExtract: An Open Source Python Library that Extracts Structured Data from Unstructured Text Documents
In today’s data-driven world, valuable insights are often buried in unstructured text—be it clinical notes, lengthy legal contracts, or customer feedback threads. Extracting…
In today’s data-driven world, valuable insights are often buried in unstructured text—be it clinical notes, lengthy legal contracts, or customer feedback threads. Extracting…
Google AI Releases LangExtract: An Open Source Python Library that Extracts Structured Data from Unstructured Text Documents
In today’s data-driven world, valuable insights are often buried in unstructured text—be it clinical notes, lengthy legal contracts, or customer feedback threads. Extracting meaningful, traceable information from these documents is both a technical and practical challenge. Google AI’s new open-source Python library, LangExtract, is designed to address this gap directly, using LLMs like Gemini to deliver powerful, automated extraction with traceability and transparency at its core.
nexttech-news.com
August 5, 2025 at 10:47 AM
Google AI Releases LangExtract: An Open Source Python Library that Extracts Structured Data from Unstructured Text Documents
In today’s data-driven world, valuable insights are often buried in unstructured text—be it clinical notes, lengthy legal contracts, or customer feedback threads. Extracting…
In today’s data-driven world, valuable insights are often buried in unstructured text—be it clinical notes, lengthy legal contracts, or customer feedback threads. Extracting…
If you've been struggling with PDF data extraction, LangExtract might be your salvation. It turns messy documents into structured data reliably.
https://grizzlypeaksoftware.com/articles/p/UXtQzu?utm_source=bluesky&utm_medium=social&utm_campaign=blog
https://grizzlypeaksoftware.com/articles/p/UXtQzu?utm_source=bluesky&utm_medium=social&utm_campaign=blog
July 24, 2026 at 4:00 AM
If you've been struggling with PDF data extraction, LangExtract might be your salvation. It turns messy documents into structured data reliably.
https://grizzlypeaksoftware.com/articles/p/UXtQzu?utm_source=bluesky&utm_medium=social&utm_campaign=blog
https://grizzlypeaksoftware.com/articles/p/UXtQzu?utm_source=bluesky&utm_medium=social&utm_campaign=blog
Meet #LangExtract - an #opensource #Python library!
Developers can now extract structured information from unstructured text using large language models such as the Gemini models.
Learn moreon #InfoQ 👉 bit.ly/4m9KPSG
#Google #LLMs #AI
Developers can now extract structured information from unstructured text using large language models such as the Gemini models.
Learn moreon #InfoQ 👉 bit.ly/4m9KPSG
#Google #LLMs #AI
August 11, 2025 at 11:24 AM
Meet #LangExtract - an #opensource #Python library!
Developers can now extract structured information from unstructured text using large language models such as the Gemini models.
Learn moreon #InfoQ 👉 bit.ly/4m9KPSG
#Google #LLMs #AI
Developers can now extract structured information from unstructured text using large language models such as the Gemini models.
Learn moreon #InfoQ 👉 bit.ly/4m9KPSG
#Google #LLMs #AI
Kenneth Leung explains how Google’s LangExtract paired with Gemma can turn long, unstructured documents into structured data. He breaks down how this approach simplifies parsing dense text like insurance policies or medical records.
Using Google’s LangExtract and Gemma for Structured Data Extraction | Towards Data Science
Extracting structured information effectively and accurately from long unstructured text with LangExtract and LLMs
towardsdatascience.com
September 20, 2025 at 1:47 PM
Kenneth Leung explains how Google’s LangExtract paired with Gemma can turn long, unstructured documents into structured data. He breaks down how this approach simplifies parsing dense text like insurance policies or medical records.
From compliance reports to medical records, critical details are often buried in walls of text. Kenneth Leung breaks down how LangExtract and Gemma enable accurate structured data extraction from unstructured documents.
Using Google’s LangExtract and Gemma for Structured Data Extraction | Towards Data Science
Extracting structured information effectively and accurately from long unstructured text with LangExtract and LLMs
towardsdatascience.com
September 15, 2025 at 12:34 AM
From compliance reports to medical records, critical details are often buried in walls of text. Kenneth Leung breaks down how LangExtract and Gemma enable accurate structured data extraction from unstructured documents.
Can messy clinical notes be turned into structured entities? Parul Pandey breaks down how LangExtract uses LLMs. Both proprietary and local. To extract data using schemas and few-shot examples, making unstructured text usable and reliable.
Can LangExtract Turn Messy Clinical Notes into Structured Data? | Towards Data Science
Turning raw clinical notes into structured entities with LLMs.
towardsdatascience.com
September 11, 2025 at 4:28 PM
Can messy clinical notes be turned into structured entities? Parul Pandey breaks down how LangExtract uses LLMs. Both proprietary and local. To extract data using schemas and few-shot examples, making unstructured text usable and reliable.
⭐ Kenneth Leung
Using Google’s LangExtract and Gemma for Structured Data Extraction | Towards Data Science
Extracting structured information effectively and accurately from long unstructured text with LangExtract and LLMs
towardsdatascience.com
September 10, 2025 at 3:15 PM
⭐ Kenneth Leung
Parul Pandey explains how LangExtract, a new open-source project from @developers.google.com, can transform raw clinical notes into structured data. She breaks down how it leverages LLMs with custom schemas and few-shot examples for clean results.
Can LangExtract Turn Messy Clinical Notes into Structured Data? | Towards Data Science
Turning raw clinical notes into structured entities with LLMs.
towardsdatascience.com
September 10, 2025 at 12:45 PM
Parul Pandey explains how LangExtract, a new open-source project from @developers.google.com, can transform raw clinical notes into structured data. She breaks down how it leverages LLMs with custom schemas and few-shot examples for clean results.
If you’ve built LLM workflows for structured data extraction, you’ve likely hit issues with schema drift, missing facts, and prompt brittleness. @subhaganapathi.bsky.social's new article explores how LangExtract orchestrates prompt tuning, chunking, and multi-pass validation.
Extracting Structured Data with LangExtract: A Deep Dive into LLM-Orchestrated Workflows | Towards Data Science
A guide to building modular workflows for structured intelligence
towardsdatascience.com
September 8, 2025 at 5:04 PM
If you’ve built LLM workflows for structured data extraction, you’ve likely hit issues with schema drift, missing facts, and prompt brittleness. @subhaganapathi.bsky.social's new article explores how LangExtract orchestrates prompt tuning, chunking, and multi-pass validation.