REPOGEO REPORT · LITE
run-llama/liteparse
Default branch main · commit e1a13f04 · scanned 5/16/2026, 3:26:37 AM
GitHub: 5,133 stars · 341 forks
Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface run-llama/liteparse, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.
Action plan — copy-paste fixes
3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- highreadme#1Reposition README H1 to clarify core purpose and counter miscategorization
Why:
CURRENTLiteParse 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.
COPY-PASTE FIXLiteParse is a standalone, open-source **document and PDF parsing tool** designed for **fast, local, and light-weight text extraction with spatial bounding boxes**. It is *not* an LLM output parser, but rather a robust solution for processing various document types directly on your machine, without proprietary LLM features or cloud dependencies.
- mediumtopics#2Add more specific topics related to OCR and spatial data
Why:
CURRENTdocument-ocr, document-processing, ocr, ocr-recognition, pdf, pdf-parser, text-extraction
COPY-PASTE FIXdocument-ocr, document-processing, ocr, ocr-recognition, pdf, pdf-parser, text-extraction, spatial-data, bounding-boxes, local-ocr, pdf-text-extraction
- lowreadme#3Add a "What LiteParse Is (and Isn't)" section to the README
Why:
COPY-PASTE FIX## What LiteParse Is (and Isn't) LiteParse is a dedicated tool for local document and PDF parsing, focusing on fast text extraction, OCR integration, and spatial data (bounding boxes). It is *not* designed for parsing or validating JSON output from Large Language Models. If you are looking for an LLM output parser, consider other specialized libraries. LiteParse's strength lies in its ability to process diverse document types locally, providing structured text and image data for further analysis or ingestion into various systems, including LLM pipelines.
Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash
Category visibility — the real GEO test
Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?
Same questions for every model — switch tabs to compare answers and rankings.
- pdfminer.six · recommended 1×
- Apache PDFBox · recommended 1×
- Poppler · recommended 1×
- PyMuPDF · recommended 1×
- pdf.js · recommended 1×
- CATEGORY QUERYWhat are good open-source libraries for fast, local PDF text extraction with spatial data?you: not recommendedAI recommended (in order):
- pdfminer.six
- Apache PDFBox
- Poppler
- PyMuPDF
- pdf.js
AI recommended 5 alternatives but never named run-llama/liteparse. This is the gap to close.
Show full AI answer
- CATEGORY QUERYLooking for a document parser that supports OCR and provides text bounding box information.you: not recommendedAI recommended (in order):
- Google Cloud Document AI
- Amazon Textract
- Microsoft Azure Form Recognizer
- Tesseract OCR
- PyTesseract
- ABBYY FineReader Engine SDK
- PaddleOCR
AI recommended 7 alternatives but never named run-llama/liteparse. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesspass
- README presencepass
Self-mention check
Does AI even know your repo exists when asked about it directly?
- Compared to common alternatives in this category, what is the core differentiator of run-llama/liteparse?passAI named run-llama/liteparse explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts run-llama/liteparse in production, what risks or prerequisites should they evaluate first?passAI named run-llama/liteparse explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- In one sentence, what problem does the repo run-llama/liteparse solve, and who is the primary audience?passAI named run-llama/liteparse explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
Embed your GEO score
Drop this badge into the README of run-llama/liteparse. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.
[](https://repogeo.com/en/r/run-llama/liteparse)<a href="https://repogeo.com/en/r/run-llama/liteparse"><img src="https://repogeo.com/badge/run-llama/liteparse.svg" alt="RepoGEO" /></a>Subscribe to Pro for deep diagnoses
run-llama/liteparse — Lite scans stay free; this card itemizes Pro deep limits vs Lite.
- Deep reports10 / month
- Brand-free category queries5 vs 2 in Lite
- Prioritized action items8 vs 3 in Lite