run-llama/liteparse
A fast, helpful, and open-source document parser
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
Ranks #1 among Computer Vision repositories tracked this week, and #1 over the last 30 days; #306 of 2,845 repositories GStars tracks this week (top 11%).
5 releases in the last 90 days, the latest 4 days ago, with 42 contributors on GitHub.
Peaked at #23 in the weekly ranking the week of Sep 27, its best in the past year.
Use Cases & Benefits
- Provides a fast, lightweight, and open-source document parser with spatial text extraction and OCR support running entirely locally.
- Delivers high-quality text parsing with precise bounding boxes and flexible OCR options without cloud dependencies or proprietary features.
- Use for extracting structured text and layout data from PDFs and scanned documents in offline or air-gapped environments.
- Use for batch processing diverse document formats including Office files and images by automatic conversion to PDF for parsing.
- Use for generating high-resolution page screenshots to support visual data extraction in LLM agent workflows.
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
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
LiteParse is a standalone OSS PDF parsing tool focused exclusively on fast and light parsing. It provides high-quality spatial text parsing with bounding boxes, without proprietary LLM features or cloud dependencies. Everything runs locally on your machine.
Hitting the limits of local parsing? For complex documents (dense tables, multi-column layouts, charts, handwritten text, or scanned PDFs), you'll get significantly better results with LlamaParse, our cloud-based document parser built for production document pipelines. LlamaParse handles the hard stuff so your models see clean, structured data and markdown.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
+1,209 stars over 90 days across 14 snapshot days; best day +38 on Aug 12.
Forks
884+96
Open issues
41+16
Compared with peers in Computer Vision
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 |
|---|---|---|---|---|
| koharu-rs/koharu | 6.4K | +483 | 63 | 30 days ago |
| PaddlePaddle/PaddleOCR | 91.6K | +0 | 75 | 135 days ago |
| microsoft/AI-For-Beginners | 69.8K | +0 | 45 | — |
| opendataloader-project/opendataloader-pdf | 29.7K | +0 | 75 | 2 days ago |
| memvid/memvid | 16.6K | +0 | 75 | 150 days ago |
| run-llama/liteparse | 12.9K | +0 | 75 | 4 days ago |
| Category median | 29.7K | +0 | 75 | — |
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