raggen 0.1.2

RAG dataset generator

RAGGen - RAG Dataset Generator

A universal tool for converting files into high-quality RAG datasets.

Features

• Supports a variety of commonly used formats for storing textual data.
• Robust PDF parsing with OCR utilizing marker library.
• Preserves headers, supports fixing header levels using LLM (OpenAI API).
• Respects tables, does not split them into chunks.
• Supports embedding metadata directly into chunk text.
• Supports adding custom metadata for each input.
• Multiple input formats, standard output format.
• Checksum-based result caching.

Supported formats

• PDF (via marker).
• Word (via mammoth).
• HTML (via html2text).
• Markdown

Installation

pip install raggen

Usage

from raggen import RAGGen

# Initialize RAGGen
gen = RAGGen(cache_dir="cache")

# Define inputs
inputs = ["sample1.pdf", "sample2.html", "sample3.md"]

# Input with custom metadata
inputs.append({"path": "sample4.docx", "metadata": {"title": "Doc title"}})

# Generate RAG dataset as list
data = gen(inputs)

# Generate RAG dataset as pandas DataFrame
data = gen.generate_dataset(inputs)

TODO

• Save images
• Add proper documentation
• Add more usage examples
• Add txt support
• Add Power Point support
• Add Excel support
• Add support for reading files from buffer

Contribution

Feel free to fork this repo and make pull requests.

If you like my work, please, support me:

BTC: 32F3zAnQQGwZzsG7R35rPUS269Xz11cZ8B

Lisense

Free to use under Apache-2.0. See LICENSE for more information.