llmsherpa VS nlm-ingestor

Compare llmsherpa vs nlm-ingestor and see what are their differences.

llmsherpa

Developer APIs to Accelerate LLM Projects (by nlmatics)

nlm-ingestor

This repo provides the server side code for llmsherpa API to connect. It includes parsers for various file formats. (by nlmatics)
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llmsherpa nlm-ingestor
6 3
970 823
16.2% 12.0%
6.6 7.1
7 days ago 24 days ago
Jupyter Notebook Python
MIT License Apache License 2.0
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llmsherpa

Posts with mentions or reviews of llmsherpa. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-02-20.
  • LlamaCloud and LlamaParse
    9 projects | news.ycombinator.com | 20 Feb 2024
    To get good RAG performance you will need a good chunking strategy. Simply getting all the text is not good enough and knowing the boundaries of table, list, paragraph, section etc. is helpful.

    Great work by llamaindex team. Also feel free to try https://github.com/nlmatics/llmsherpa which takes into account some of the things I mentioned.

  • Show HN: Open-source Rule-based PDF parser for RAG
    9 projects | news.ycombinator.com | 23 Jan 2024
    I wrote about split points and the need for including section hierarchy in this post: https://ambikasukla.substack.com/p/efficient-rag-with-docume...

    All this is automated in the llmsherpa parser https://github.com/nlmatics/llmsherpa which you can use as an API over this library.

nlm-ingestor

Posts with mentions or reviews of nlm-ingestor. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-03-06.
  • Pg_vectorize: The simplest way to do vector search and RAG on Postgres
    6 projects | news.ycombinator.com | 6 Mar 2024
    >tree-based approach to organize and summarize text data, capturing both high-level and low-level details.

    https://twitter.com/parthsarthi03/status/1753199233241674040

    processes documents, organizing content and improving readability by handling sections, paragraphs, links, tables, lists, page continuations, and removing redundancies, watermarks, and applying OCR, with additional support for HTML and other formats through Apache Tika:

    https://github.com/nlmatics/nlm-ingestor

  • Show HN: Open-source Rule-based PDF parser for RAG
    9 projects | news.ycombinator.com | 23 Jan 2024
    Here's another notebook from the repo with examples: https://github.com/nlmatics/nlm-ingestor/blob/main/notebooks...

What are some alternatives?

When comparing llmsherpa and nlm-ingestor you can also consider the following projects:

unstructured - Open source libraries and APIs to build custom preprocessing pipelines for labeling, training, or production machine learning pipelines.

txtai - 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows

SemanticSlicer - A recursive text chunker that attempts to preserve context.

llama_parse - Parse files for optimal RAG

Parsr - Transforms PDF, Documents and Images into Enriched Structured Data

marker - Convert PDF to markdown quickly with high accuracy

paperetl - 📄 ⚙️ ETL processes for medical and scientific papers

open-webui - User-friendly WebUI for LLMs (Formerly Ollama WebUI)

llama-hub - A library of data loaders for LLMs made by the community -- to be used with LlamaIndex and/or LangChain

grobid - A machine learning software for extracting information from scholarly documents