Document parsing tool for LLM training and Rag
Project description
DocParser 📄
DocParser is a powerful tool for LLM traning and other application, for examples: RAG, which support to parse multi type file, includes:
Feature 🎉
File types supported for parsing:
- Pdf: Use OCR to parse PDF documents and output text in markdown format. The parsing results can be used for LLM pretrain, RAG, etc.
- Html: Use jina to parse multi html pages and output text in markdown.
Install
From pip:
pip install docparser_feb
From repository:
pip install git+https://github.com/feb-co/DocParser.git
Or install it directly through the installation package:
git clone https://github.com/feb-co/DocParser.git
cd DocParser
pip install -e .
API/Functional
From CLI
You can run the following script to get the pdf parsing results:
export LOG_LEVEL="ERROR"
export DOC_PARSER_MODEL_DIR="xxx"
export DOC_PARSER_OPENAI_URL="xxx"
export DOC_PARSER_OPENAI_KEY="xxx"
export DOC_PARSER_OPENAI_MODEL="gpt-4-0125-preview"
export DOC_PARSER_OPENAI_RETRY="3"
docparser-pdf \
--inputs path/to/file.pdf or path/to/directory \
--output_dir output_directory \
--page_range '0:1' --mode 'figure latex' \
--rendering --use_llm --overwrite_result
The following is a description of the relevant parameters:
usage: docparser-pdf [-h] --inputs INPUTS --output_dir OUTPUT_DIR [--page_range PAGE_RANGE] [--mode {plain,figure placehold,figure latex}] [--rendering] [--use_llm]
options:
-h, --help show this help message and exit
--inputs INPUTS Directory where to store PDFs, or a file path to a single PDF
--output_dir OUTPUT_DIR
Directory where to store the output results (md/json/images).
--page_range PAGE_RANGE
The page range to parse the PDF, the format is 'start_page:end_page', that is, [start, end). Default: full.
--mode {plain,figure placehold,figure latex}
The mode for parsing the PDF, to extract only the plain text or the text plus images.
--rendering Is it necessary to render the recognition results of the input PDF to output the recognition range? Default: False.
--use_llm Do you need to use LLM to format the parsing results? If so, please specify the corresponding parameters through the environment variables: DOC_PARSER_OPENAI_URL, DOC_PARSER_OPENAI_KEY, DOC_PARSER_OPENAI_MODEL. Default: False.
--overwrite_result If the parsed target file already exists, should it be rewritten? Default: False.
From Python
Html
From CLI
You can run the following script to get the html parsing results:
docparser-html https://github.com/mem0ai/mem0
From Python
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
docparser_feb-0.1.1.tar.gz
(422.3 kB
view details)
Built Distribution
File details
Details for the file docparser_feb-0.1.1.tar.gz
.
File metadata
- Download URL: docparser_feb-0.1.1.tar.gz
- Upload date:
- Size: 422.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.12.5
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0a24fa5952cc39cc3daeec19ab97dc18933553f4e76af7c852d027492fb7e462 |
|
MD5 | 457ed172e53fd8b765e881b463246ddd |
|
BLAKE2b-256 | 2a53629379df3f3a2e5a99c3609593b377a53c787dc0878ad56b2f8e48ccaa13 |
File details
Details for the file docparser_feb-0.1.1-py3-none-any.whl
.
File metadata
- Download URL: docparser_feb-0.1.1-py3-none-any.whl
- Upload date:
- Size: 7.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.12.5
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | fe748766b9e3e6d06f6de018a6704338445d9f1b5754a1a4dce09eef361e6ee9 |
|
MD5 | 0a6e2494e29e684612e3465ac67bfa35 |
|
BLAKE2b-256 | 799ff78f8de639a4eff0df9084ce97a38edaf143dd00e7c620110b576af0eed5 |