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RAGVizExpander

Welcome to RAGVizExpander, an extension of the RAGxplorer project, where we aim to incorporate new features tailored to personal interests and enhance the overall user experience.

You can use this program to test the effects of different embedding models and chunking strategies.

Install

  • Install from source
pip install -e .
  • Install from PyPI
pip install ragvizexpander

Components

Below are the components you can use:

Type What Where
LLM OpenAI Built-in
ollama examples
Embedding OpenAI Built-in
SentenceTransformer Built-in
HuggingFace Built-in
Endpoint-based examples
File Loader DOCX Built-in
PPTX Built-in
TXT Built-in
PDF Built-in

Document loader

Type Tool Where
WORD Default Location
doc2txt Location
unstructured Location
llama-index Location
PDF Default Location
unstructured Location
llama-index Location
TXT Default Location
unstructured Location
llama-index Location
PPTX Default Location
unstructured Location
llama-index Location

DEMO

Streamlit demo

Usge: streamlit run app.py

Huggingface Space: RagVizExpander

Features

  • Custom LLM & Embedding model
  • Custom chunking strategy
  • Support for parsing multiple types of files

Acknowledgments 💙

License

This project is licensed under the MIT license - see the LICENSE for details.

Metadata

Release files for ragvizexpander 1.1.0

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