open-parse
unstract
| open-parse | unstract | |
|---|---|---|
| 3 | 5 | |
| 1,782 | 109 | |
| - | 2.8% | |
| 9.2 | 9.7 | |
| 8 days ago | 4 days ago | |
| Python | Python | |
| MIT License | GNU Affero General Public License v3.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
open-parse
- Show HN: Beyond text splitting – improved file parsing for LLM's
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Running OCR against PDFs and images directly in the browser
I recently built a similar tool except it’s configured to use some deep learning libraries for the table extraction. I’m excited to integrate unitable which has state of the art performance later this week.
I built this because most of the basic layout detection libraries have terrible performance on anything non trivial. Deep learning is really the long term solution here.
https://github.com/Filimoa/open-parse
- Show HN: Open-source, high performance document chunking for LLM's
unstract
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Ask HN: Is RAG the Future of LLMs?
Fast changing libraries are a huge pain. That's why a no-code approach like Unstract (https://github.com/zipstack/unstract) makes sense.
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Show HN: LLMWhisperer – Prep complex documents ready for use in LLMs
Hey HN!
Over the last few months, we’ve seen many tools here trying to tackle the problem of making complex, unstructured documents ready for LLMs.
The complexity primarily includes parsing highly complex documents in terms of format, layout, design, complex tables, checkboxes, etc, with high accuracy and reliability.
LLMWhisperer is our take on the problem. LLMwhisperer solves most of the document complexity with reliable accuracy.
With our user-friendly playground (https://pg.llmwhisperer.unstract.com/), you can effortlessly test your document use case. No sign-up is required. We eagerly await your valuable feedback.
LLMWhisperer is also a part of Unstract, an open-source document processing automation platform.
Links: https://llmwhisperer.unstract.com/
Playground: https://pg.llmwhisperer.unstract.com/
Unstract: https://github.com/Zipstack/unstract
Feature screenshot: https://imgur.com/a/QtrqNbB
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RAGFlow is an open-source RAG engine based on deep document understanding
If anyone is interested in exploring this space, try another similar tool LLMWhisperer (https://llmwhisperer.unstract.com/). It is a part of Unstract, an open-source document processing tool (https://github.com/Zipstack/unstract)
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Show HN: Unstract – AGPL, LLM-powered Fivetran/Twilio for unstructured docs
Unstract supports a variety of providers for LLMs, Vector Databases, Embeddings, Cloud File Storage systems and databases/data warehouses. A full list is available on our Github page (https://github.com/Zipstack/unstract).
No-code Prompt Studio:
- Running OCR against PDFs and images directly in the browser