RAGxplorer is an open-source visualization tool designed to help developers analyze and understand Retrieval-Augmented Generation (RAG) pipelines. Retrieval-augmented generation combines language models with external document retrieval systems in order to produce more accurate and grounded responses. However, RAG systems can be complex because they involve multiple components such as embedding models, vector databases, and retrieval algorithms. RAGxplorer provides visual tools that allow developers to inspect how documents are embedded, retrieved, and used to answer queries. The software can load documents, generate embeddings, and project them into reduced vector spaces so that users can visually explore relationships between queries and retrieved documents. It also includes interactive interfaces that show how retrieval affects the final output of the language model.

Features

  • Visualization of embeddings and document relationships in vector space
  • Interactive exploration of retrieval results for specific queries
  • Support for loading and analyzing document collections such as PDFs
  • Compatibility with various embedding models and inference endpoints
  • Streamlit-based interactive dashboards for RAG experimentation
  • Tools for debugging and optimizing retrieval pipelines

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License

MIT License

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Additional Project Details

Programming Language

Python

Related Categories

Python Large Language Models (LLM)

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3 days ago