google/langextract
A Python library for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
Ranks #505 of 2,503 repositories GStars tracks this week (top 20%).
2 releases in the last 90 days, the latest 5 days ago, with 27 contributors on GitHub.
Peaked at #1 in the weekly ranking the week of Feb 8, its best in the past year.
Use Cases & Benefits
- Extract structured information from unstructured text using LLMs with precise source grounding and interactive visualization.
- Ensures reliable, schema-constrained outputs with exact source mapping and supports flexible LLMs including cloud and local models.
- Use for extracting detailed entities and relationships from literary texts with traceable source highlights.
- Use for structuring clinical notes and medical reports to identify medications, dosages, and related attributes.
- Use for processing large documents or datasets with parallel extraction passes and interactive HTML visualizations for review.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Apache 2.0
Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.
Community files
- README: present
- Contributing guide: present
- Code of conduct: present
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
LangExtract is a Python library that uses LLMs to extract structured information from unstructured text documents based on user-defined instructions. It processes materials such as clinical notes or reports, identifying and organizing key details while ensuring the extracted data corresponds to the source text.
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.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
+1,323 stars over 86 days across 18 snapshot days; best day +121 on Jul 23.
Forks
2.7K+118
Open issues
113+4
Compared with peers in LLM
Fastest-growing repositories GStars tracks in this cohort for the week of Oct 11, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| DietrichGebert/ponytail | 164.4K | +5.0K | 75 | 2 days ago |
| tashfeenahmed/freellmapi | 35.8K | +3.7K | 45 | today |
| thedotmack/claude-mem | 101.1K | +2.9K | 75 | 2 days ago |
| TencentCloud/TencentDB-Agent-Memory | 29.3K | +1.5K | 75 | 2 days ago |
| p-e-w/heretic | 35.4K | +1.4K | 41 | 123 days ago |
| google/langextract | 38.9K | +0 | 75 | 5 days ago |
| Category median | 35.8K | +2.9K | 75 | — |
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