langextract
A Python library for extracting structured information from unstructured text using LLMs.
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Decision brief
langextract is a Python library that leverages LLM capabilities to extract and structure data from unstructured text, providing features such as precise source grounding and interactive visualizations for improved data洞察
Good fit when
- - When you require extraction of structured information with precise source references in your Python projects
- - If you are working on NLP tasks that demand interactive visualization to better understand the extracted information
Avoid when
- - For tasks where real-time performance is critical, as langextract relies heavily on LLMs which may introduce latency
- - When the project stack does not include Python or there's an existing strong preference for another programming language
Observed Jul 11, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Very active (4d since push)
- As of 4d
- Provenance
- Not a fork · Organization account
- As of 4d
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Backing
Company context for Google. Display-only - separate from trust and ranking.
- Company
- Google·GitHub org profile·1mo
- Employees
- 47,756·Wikidata (P1128 employees)·1mo
- Commercial model
- Pure OSS·GitHub org profile (public repos)·1mo
Install
pip install langextractHow it fits your stack(16)
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
google/langextract is a Python-based tool that uses large language models to extract and structure data from unstructured text sources, offering precise source grounding and interactive visualization features.
Capability facts
- Deploy
- Self-host
Source: dockerfile:Dockerfile · Aug 16, 2026
- Docker
- Dockerfile present
Source: dockerfile:Dockerfile · Aug 16, 2026
- Languages
- python
Source: github.language+pyproject.toml · Aug 16, 2026
Categories
Graph entities
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 16, 2026)
docker run --rm -e LANGEXTRACT_API_KEY="your-api-key" langextract python your_script.pySource link
Tags
README
Quick Start
Note: Using cloud-hosted models like Gemini requires an API key. See the API Key Setup section for instructions on how to get and configure your key.
Extract structured information with just a few lines of code.
For basic installation:
pip install -e .
Docker
docker build -t langextract .
docker run --rm -e LANGEXTRACT_API_KEY="your-api-key" langextract python your_script.py
Install with test dependencies
pip install -e ".[test]"
For agents
This page has a .md twin and JSON over the API.