Dev Tools
mediapipe
Google's cross-platform framework for on-device ML perception: vision, text and audio pipelines
★ 37.2k starsApache-2.0
View guide →Google's Python library for extracting structured data from unstructured text with LLMs, with grounding
langextract is an open-source dev tools project by google (google/langextract on GitHub). It has 38,930 GitHub stars and 2,720 forks, is released under the Apache-2.0 license, and was last updated on GitHub on 6 October 2026.
Decide what you want from langextract and check the README and requirements to confirm it fits your setup and Python environment.
Clone the repository from GitHub (github.com/google/langextract) or use the documented install channel if you do not need the source.
Follow the README quickstart to install dependencies and set any required configuration or credentials.
Work through the README's first example end to end, then adapt it to your own project or data.
Extracts structured information from unstructured text using LLMs.
Every extraction is grounded to its exact source span in the document.
Visualize extraction results interactively to verify quality.
Scales to longer documents beyond a single context window.
Supports Vertex AI batch processing for large jobs.
Works with Gemini models and other providers as documented.
Start by getting the source and entering the project directory.
git clone https://github.com/google/langextract.git
cd langextractInstall the langextract package.
pip install langextract # see README Installation sectionDefine your extraction task with examples, run it on text, then visualize the grounded results.
# see README Quick Start for the example codeIt is maintained by google and contributors on GitHub, where the repository github.com/google/langextract is the canonical home for code, issues and releases.
Yes — it is open source under the Apache-2.0 license. Read the license in the repository for what is permitted, including any conditions on redistribution or commercial use.
Yes for cloud models — for example a Gemini API key; setup for cloud models is documented in the README.
Compared with hand-written regex or plain prompting: LangExtract adds few-shot task definition, exact source grounding and visualization on top of raw LLM prompting.
Clone github.com/google/langextract, follow the README quickstart to install it, and run the documented first example before adapting it to your own work.
Google's cross-platform framework for on-device ML perception: vision, text and audio pipelines
Trafilatura — a Python and CLI tool to crawl the web and extract clean text and metadata for corpora and RAG.
A Node.js crawler that turns websites into LLM-ready data and extracts structured SERP results.
A Python metasearch library aggregating many web search services — plus CLI, API and MCP server
Hugging Face's library for loading and processing datasets for AI models in one line
GenBI for AI agents - governed text-to-SQL and dashboards through an open context layer
The most-starred other Dev Tools projects in the LibreAI catalogue — the realistic shortlist if langextract is not the right fit.
The open source coding agent
The model-definition framework behind modern AI — thousands of pretrained transformers for text, vision, and audio.
Anthropic's agentic coding tool that lives in your terminal and works across your whole codebase
Cross-platform desktop all-in-one manager for Claude Code, Codex, OpenCode and other coding agents
OpenAI's lightweight coding agent that runs locally in your terminal
Free and open — grab the source, star the repo, and start creating.