surya
unstructured
| surya | unstructured | |
|---|---|---|
| 6 | 12 | |
| 6,743 | 6,682 | |
| - | 17.7% | |
| 8.4 | 9.8 | |
| 5 days ago | 5 days ago | |
| Python | HTML | |
| GNU General Public License v3.0 only | Apache License 2.0 |
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surya
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New open source AI model for document segmentation and unstructured ETL
Would this be able to incorporate the models from Surya —
https://github.com/VikParuchuri/surya
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Show HN: Beyond text splitting – improved file parsing for LLM's
This looks great! You might be interested in surya - https://github.com/VikParuchuri/surya (I'm the author). It does OCR (much more accurate than tesseract), layout analysis, and text detection.
The OCR is slow on CPU (working on it), but faster than tesseract (CPU-only) on GPU.
Happy to discuss more, feel free to email me (in profile).
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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.
- Show HN: Surya – OCR and line detection in 93 languages
- Surya: Multilingual Document OCR Toolkit
unstructured
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LlamaCloud and LlamaParse
Be careful with unstructured:
https://github.com/Unstructured-IO/unstructured/blob/d11c70c...
from: https://github.com/open-webui/open-webui/issues/687
- FLaNK 15 Jan 2024
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Bash One-Liners for LLMs
I’ve been looking at this
https://freeling-user-manual.readthedocs.io/en/v4.2/modules/...
at the freeling library in general, also spaCy and NLTK. The chunking algorithms being used in the likes of LangChain are remarkably bad surprisingly.
There is also
https://github.com/Unstructured-IO/unstructured
But I don’t like it, can’t explain why yet.
My intuition is that 1st step is clean sentences and paragraphs and titles/labels/headers. Then probably an LLM can handle outlining and table of contents generation using a stripped down list of objects in the text.
BRIO/BERT summarization could also have a role of some type.
Those are my ideas so far.
- Unstructured – OSS libraries and APIs to build custom preprocessing pipelines
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More intelligent Pdf parsers
Unstructured is the best one I’ve used so far: https://www.unstructured.io
- Help extracting data from multiple PDF's
- Pre-processing text documents such as PDFs, HTML and Word Documents for LLMs
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Using ChatGPT to read multiple PDFs and create writing using them as sources
https://www.unstructured.io/ can parse PDFs, then you can feed all of them to Claude, which has a 100k context window.
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How can I convert restaurant’s traditional menu in pdf file to well structured list of menu items with prices in Excel file? Thank you
If the copy & pase method does not work: One approach is to use the functionality of Unstructured to parse the PDF. If need be, it can do OCR on the PDF too if you have Detectron2 installed. After conversion you would still have to save it as an excel file though.
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PDF GPT allows you to chat with the contents of your PDF file
I would check out https://github.com/Unstructured-IO/unstructured (what lang chain uses) or https://github.com/axa-group/Parsr (probably what unstructured copied to get their startup off the ground lol)
What are some alternatives?
cmdf - this thing will fix misspelled commands by learning from your history.
llmsherpa - Developer APIs to Accelerate LLM Projects
stable-diffusion-webui - Stable Diffusion web UI
Parsr - Transforms PDF, Documents and Images into Enriched Structured Data
Auto-GPT - An experimental open-source attempt to make GPT-4 fully autonomous. [Moved to: https://github.com/Significant-Gravitas/Auto-GPT]
ragflow - RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
pdfGPT - PDF GPT allows you to chat with the contents of your PDF file by using GPT capabilities. The most effective open source solution to turn your pdf files in a chatbot!
awesome-document-understanding - A curated list of resources for Document Understanding (DU) topic
llama_parse - Parse files for optimal RAG
vault-ai - OP Vault ChatGPT: Give ChatGPT long-term memory using the OP Stack (OpenAI + Pinecone Vector Database). Upload your own custom knowledge base files (PDF, txt, epub, etc) using a simple React frontend.
gpt4-pdf-chatbot-langchain - GPT4 & LangChain Chatbot for large PDF docs
deepdoctection - A Repo For Document AI