llama_parse
unstructured
| llama_parse | unstructured | |
|---|---|---|
| 4 | 12 | |
| 1,108 | 6,808 | |
| 45.0% | 19.2% | |
| 9.1 | 9.8 | |
| 7 days ago | 3 days ago | |
| Python | HTML | |
| MIT License | Apache License 2.0 |
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llama_parse
- FLaNK AI for 11 March 2024
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LlamaCloud and LlamaParse
I'm part of the team that build LlamaParse. It's net improvement compare to other PDF->Structured Text extractors (I build several in the past, includig https://github.com/axa-group/Parsr).
For character extraction, LlamaParse use a mixture of OCR / character extraction from the PDF (it's the only parser I'm aware of that address some of the buggy PDF font issues, check the 'text' mode to see raw document before reconstruction), use a mixture of heuristic and Machine learning models to reconstruct the document.
Once plug with a Recursive retrieval strategy, allow you to get Sota result on question answering over complexe text (see notebook: https://github.com/run-llama/llama_parse/blob/main/examples/...).
AMA
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?
llmsherpa - Developer APIs to Accelerate LLM Projects
llama-hub - A library of data loaders for LLMs made by the community -- to be used with LlamaIndex and/or LangChain
Parsr - Transforms PDF, Documents and Images into Enriched Structured Data
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
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
private-gpt - Interact with your documents using the power of GPT, 100% privately, no data leaks
jan - Jan is an open source alternative to ChatGPT that runs 100% offline on your computer. Multiple engine support (llama.cpp, TensorRT-LLM)