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Top 5 document-understanding Open-Source Projects
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ragflow
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
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document-ai-samples
Sample applications and demos for Document AI, the end-to-end document processing platform on Google Cloud
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
Project mention: Better RAG Results with Reciprocal Rank Fusion and Hybrid Search | news.ycombinator.com | 2024-05-30Within our open source RAG product RAGFlow(https://github.com/infiniflow/ragflow), Elasticsearch is currently used instead of other general vector databases, because it can provide hybrid search right now. Under the default cases, embedding based reranker is not required, just RRF is enough, while even if reranker is used, keywords based retrieval is also a MUST to be hybridized with embedding based retrieval, that's just what RAGFlow's latest 0.7 release has provided.
On the other hand let me introduce another database we developed, Infinity(https://github.com/infiniflow/infinity), which can provide the fastest hybrid search, you can see the performance here(https://github.com/infiniflow/infinity/blob/main/docs/refere...), both vector search and full-text search could perform much faster than other open source alternatives.
From the next version(weeks later), Infinity will also provide more comprehensive hybrid search capabilities, what you have mentioned the 3-way recalls(dense vector, sparse vector, keyword search) could be provided within single request.
Project mention: Show HN: Beyond text splitting – improved file parsing for LLM's | news.ycombinator.com | 2024-04-07https://github.com/deepdoctection/deepdoctection
Have you tried this ?
Thanks for the example and that sounds really solid cost savings and definitely agree with the trend that it is here to stay.
For invoice parsing (various formats), are you just using GPT4V? When GPT4V initially came out, i benchmarked it against an out of the box invoice parser from Google Cloud (https://cloud.google.com/document-ai) on 16 documents and it was much better accuracy wise. For ex: i'd get results parsing 10,100 as 101100 (no comma).
Curious if you saw problems like this in your pipeline or if its gotten much better since?
Week 5: 👓Optical Character Recognition (OCR) & 🔑Keyword Search
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
document-understanding related posts
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Better RAG Results with Reciprocal Rank Fusion and Hybrid Search
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Integrated Rerankers, implemented RAPTOR, RAGFlow 0.7 released
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Ask HN: RAG and unstructured data from several docs
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DeepSeek-V2 integrated, RAGFlow v0.5.0 is released
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When Will the GenAI Bubble Burst?
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RAGFlow is an open-source RAG engine based on deep document understanding
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Based on latest advancements in document transformers, what strategy would you use to parse utility bills?
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A note from our sponsor - Scout Monitoring
www.scoutapm.com | 1 Jun 2024
Index
What are some of the best open-source document-understanding projects? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | ragflow | 8,245 |
| 2 | deepdoctection | 2,268 |
| 3 | awesome-document-understanding | 1,156 |
| 4 | document-ai-samples | 190 |
| 5 | pytesseract-ocr-plugin | 8 |
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