marker
llmsherpa
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| marker | llmsherpa | |
|---|---|---|
| 8 | 6 | |
| 8,044 | 918 | |
| - | 24.2% | |
| 7.8 | 6.9 | |
| 20 days ago | 11 days ago | |
| Python | Jupyter Notebook | |
| GNU General Public License v3.0 only | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
marker
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LlamaCloud and LlamaParse
You may want to try https://github.com/VikParuchuri/surya (I'm the author). I've only benchmarked against tesseract, but it outperforms it by a lot (benchmarks in repo). Happy to discuss.
You could also try https://github.com/VikParuchuri/marker for general PDF parsing (I'm also the author) - it seems like you're more focused on tables.
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Show HN: Texify – OCR math images to LaTeX and Markdown
Hi HN - I made texify to convert equations to markdown/LaTeX for my project marker [1] then realized it could be generally useful.
Texify converts equations and surrounding text to Markdown, with embedded LaTeX (MathJax compatible).
You can either use a GUI to select equations (inline or block) from PDFs and images to convert, or use the CLI to batch convert images. It works on CPU, GPU, or MPS (Mac).
The closest open source comparisons are pix2tex and nougat - marker is more accurate than both of them for this task. However, nougat is more for entire pages, and pix2tex is more for block equations (not inline equations and text).
I trained texify for 2 days on 4x A6000 GPUs - I was pleasantly surprised how far I could get with limited GPU resources by reframing the problem to use small parameter counts/images.
Texify is licensed for commercial use, with the weights under CC-BY-SA 4.0. Fine them here - https://huggingface.co/vikp/texify .
See the texify repo for more details, benchmarks, how to install, etc.
[1] https://github.com/VikParuchuri/marker
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Show HN: Talk to any ArXiv paper just by changing the URL
https://github.com/VikParuchuri/marker
Both are tools to convert pdfs into Latex or Markup with latex formulas. Maybe that helps
- FLaNK Stack Weekly 11 Dec 2023
- Marker: Convert PDF to Markdown quickly with high accuracy
- FLaNK Stack for 04 December 2023
llmsherpa
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LlamaCloud and LlamaParse
To get good RAG performance you will need a good chunking strategy. Simply getting all the text is not good enough and knowing the boundaries of table, list, paragraph, section etc. is helpful.
Great work by llamaindex team. Also feel free to try https://github.com/nlmatics/llmsherpa which takes into account some of the things I mentioned.
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Show HN: Open-source Rule-based PDF parser for RAG
I wrote about split points and the need for including section hierarchy in this post: https://ambikasukla.substack.com/p/efficient-rag-with-docume...
All this is automated in the llmsherpa parser https://github.com/nlmatics/llmsherpa which you can use as an API over this library.
What are some alternatives?
voyager - 🛰️ An approximate nearest-neighbor search library for Python and Java with a focus on ease of use, simplicity, and deployability.
txtai - 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
PyMuPDF - PyMuPDF is a high performance Python library for data extraction, analysis, conversion & manipulation of PDF (and other) documents.
unstructured - Open source libraries and APIs to build custom preprocessing pipelines for labeling, training, or production machine learning pipelines.
node-gtk - GTK+ bindings for NodeJS (via GObject introspection)
llama_parse - Parse files for optimal RAG
FLiPStackWeekly - FLaNK AI Weekly covering Apache NiFi, Apache Flink, Apache Kafka, Apache Spark, Apache Iceberg, Apache Ozone, Apache Pulsar, and more...
Parsr - Transforms PDF, Documents and Images into Enriched Structured Data
langchain4j - Java version of LangChain
paperetl - 📄 ⚙️ ETL processes for medical and scientific papers
nougat - Implementation of Nougat Neural Optical Understanding for Academic Documents
nlm-ingestor - This repo provides the server side code for llmsherpa API to connect. It includes parsers for various file formats.