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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Transforms PDF, Documents and Images into Enriched Structured Data
| Date | Stars |
|---|---|
| 2026-07-24 | 6177 |
| 2026-07-25 | 6177 |
| 2026-07-28 | 6177 |
| 2026-07-30 | 6177 |
| 2026-08-06 | 6177 |
Today
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growth rate 0.00%/day
<p align='center'> <img src="assets/logo.png" width="275"><br /> </p> <h2 align="center"><i>Turn your documents into data!</i></h2> <p align="center"> <a href="https://cloud.drone.io/axa-group/Parsr"><img src="https://cloud.drone.io/api/badges/axa-group/Parsr/status.svg"></a> </p> <p align="center"> <a href="README_fr.md">Français</a> | <a href="README_pt.md">Portuguese</a> | <a href="README_sp.md">Spanish</a> | <a href="README_zh-cn.md">中文</a> </p> <!--p align='center'> <img src="assets/demo_screen.gif"> </p--> > [!WARNING] > **This project is no longer maintained.** Security patches are not being applied. Consider using an alternative such as [LiteParse](https://github.com/run-llama/liteparse) if you need a local, Apache 2.0–licensed parsing solution. - **Parsr**, is a minimal-footprint document (**image, pdf, docx, eml**) cleaning, parsing and extraction toolchain which generates readily available, organized and usable data in **JSON, Markdown (MD), CSV/Pandas DF** or **TXT** formats. - It provides analysts, data scientists and developers with clean structured and label-enriched information set for ready-to-use applications ranging from data entry and document analysts automation, archival, and many others. - Currently, Parsr can perform: document cleaning, _hierarchy regeneration_ (words, lines, paragraphs), detection of _headings, tables, lists, table of contents, page numbers, headers/footers, links_, and others. Check out [all the features](server/src/processing/README.md#1-current-processing-modules). # Table of Contents - [Table of Contents](#table-of-contents) - [Getting Started](#getting-started) - [Installation](#installation) - [Usage](#usage) - [Documentation](#documentation) - [Contribute](#contribute) - [Third Party Licenses](#third-party-licenses) - [License](#license) # Getting Started ## Installation _-- The advanced installation guide is available [here](docs/installation.md) --_ The quickest way to install and run the Parsr API is through the [docker image](https://hub.docker.com/r/axarev/parsr): ```sh docker pull axarev/parsr ``` If you also wish to install the GUI for sending documents and visualising results: ```sh docker pull axarev/parsr-ui-localhost ``` Note: Parsr can also be installed bare-metal (not via Docker containers), the procedure for which is documented in the [installation guide](docs/installation.md). ## Usage _-- The advanced usage guide is available [here](docs/usage.md) --_ To run the [API](docs/api-guide.md), issue: ```sh docker run -p 3001:3001 axarev/parsr ``` which will launch it on [http://localhost:3001](http://localhost:3001). Consult the documentation on the [usage of the API](docs/api-guide.md). 1. To access the **python** client to Parsr API, issue: ```sh pip install parsr-client ``` To sample the **Jupyter Notebook**, using the python client, head over to the [jupyter demo](demo/parsr-jupyter-demo). 2) To use the GUI tool (the API needs to already be running), issue: ```sh docker run -t -p 8080:80 axarev/parsr-ui-localhost:latest ``` Then, access it through [http://localhost:8080](http://localhost:8080). Refer to the [Configuration documentation](docs/configuration.md) to interpret the configurable options in the GUI viewer. The [API based usage](docs/usage.md#3-api) and the [command line usage](docs/usage.md#23-command-line-usage) are documented in the [advanced usage](docs/usage.md) guide. # Documentation All documentation files can be found [here](docs/README.md). # Contribute Please refer to the [contribution guidelines](CONTRIBUTING.md). # Third Party Licenses Third Party Libraries licenses for its [dependencies](docs/dependencies.md): 1. **QPDF**: Apache [http://qpdf.sourceforge.net](http://qpdf.sourceforge.net/) 2. **ImageMagick**: Apache 2.0 [https://imagemagick.org/script/license.php](https://imagemagick.org/script/license.php) 3. **Pdfminer.six**: MIT [https://github.com/pdfminer/pdfminer
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Sacha Bron · LlamaIndex (@run-llama) · Switzerland
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Pierre-Loic Doulcet · LlamaIndex
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Lluis Sanchez · Spain
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Giorgio Patrini · Netherlands
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Martin Høst Normark · @LEGO · Denmark
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Ken Geis · @UCB-RAC · United States
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:b5dc5746ccfefe9d, topic:ocr
matched fp:b5dc5746ccfefe9d, topic:nlp