JGalego/RAGmap

A simple Streamlit application to visualize document chunks and queries in embedding space πŸ—ΊοΈπŸ”

42
/ 100
Emerging

This tool helps you visually understand how your documents and search queries relate to each other in a RAG (Retrieval Augmented Generation) system. You input various document types like PDFs or Word files, along with your natural language questions. It outputs interactive 2D or 3D maps, showing you which parts of your documents are most relevant to your queries, helping you refine your search strategy or improve your RAG application. Anyone building or troubleshooting a RAG system, such as AI engineers or data scientists, would find this useful.

No commits in the last 6 months. Available on PyPI.

Use this if you need to visually debug and explore the relationship between your RAG system's documents and user queries to ensure accurate information retrieval.

Not ideal if you are looking for a tool to build or deploy a RAG system from scratch, as this focuses specifically on visualization and analysis.

AI-engineering RAG-system-analysis information-retrieval data-visualization natural-language-processing
Stale 6m
Maintenance 2 / 25
Adoption 8 / 25
Maturity 18 / 25
Community 14 / 25

How are scores calculated?

Stars

13

Forks

3

Language

Python

License

MIT

Last pushed

Apr 15, 2025

Monthly downloads

27

Commits (30d)

0

Dependencies

13

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curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/JGalego/RAGmap"

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