surya
llama_parse
surya | llama_parse | |
---|---|---|
8 | 4 | |
8,690 | 1,484 | |
- | 44.3% | |
9.0 | 9.1 | |
16 days ago | 4 days ago | |
Python | Python | |
GNU General Public License v3.0 only | MIT License |
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surya
- Ask HN: How to OCR a PDF and preserve whitespace?
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A Picture Is Worth 170 Tokens: How Does GPT-4o Encode Images?
checkout https://github.com/mindee/doctr or https://github.com/VikParuchuri/surya for something practical
multimodal llm would of course blow it all out the water, so some llama3-like model is probably SOTA in terms of what you can run yourself. something like https://huggingface.co/blog/idefics2
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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
llama_parse
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Adding an Amazon Bedrock Knowledge Base to the Forex Rate Assistant
It's fair to think that undesirable artifacts and lack of structural context would impact search accuracy, performance, and ultimately cost. Consequently, it makes sense to perform some data pre-processing before passing the source documents to the RAG workflow. Third-party APIs and tools, such as LlamaParse and LayoutPDFReader, can help with pre-processing PDF data, however keep in mind that source documents may take any forms and there is no one-size-fits-all solution. You may have to resort to developing custom processes for pre-processing and search your unique data.
- FLaNK-AIM Weekly 13 May 2024
- 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
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
unstructured - Open source libraries and APIs to build custom preprocessing pipelines for labeling, training, or production machine learning pipelines.
Auto-GPT - An experimental open-source attempt to make GPT-4 fully autonomous. [Moved to: https://github.com/Significant-Gravitas/Auto-GPT]
llama-hub - A library of data loaders for LLMs made by the community -- to be used with LlamaIndex and/or LangChain
unitable - UniTable: Towards a Unified Table Foundation Model
kamal - Deploy web apps anywhere.
hugeicons-react - 4,000+ Open Source Beautiful React Icons
meetups - Meetup Materials
spring-ai-examples - Spring AI Examples
pg_activity - pg_activity is a top like application for PostgreSQL server activity monitoring.