OpenViSTAI · Agents · Blockchain · Crypto
Submit a project
Menu
RAG & Knowledge Systems

Ragxplorer

RAGxplorer is an open-source Python tool for visualizing retrieval-augmented generation workflows, including loading a PDF and viewing a query's handling.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Ragxplorer — OpenViST project profile in RAG & Knowledge Systems.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use RAGxplorer when you want to inspect a document-based RAG query visually, or follow a notebook-oriented quick start to explore the workflow.

Who it is for

  • Developers exploring or building document-based RAG workflows
  • People teaching or learning RAG query behavior through a notebook or demo

Documented uses

  • Load a PDF into a RAGxplorer client.
  • Visualize a natural-language query against the loaded document.
Before you choose

Requirements & limits

  • The README's quick start uses the thenlper/gte-large embedding model.
  • The project provides a Jupyter quickstart notebook and identifies a Streamlit demo.
  • The repository specifies an MIT license.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Install RAGxplorer and visualize a PDF query

Use the documented Python quick start to load a PDF and request a query visualization.

Before you start

  • Python environment with pip
  • A local PDF file
  • The documented embedding model identifier: thenlper/gte-large

Steps

  1. Install the package with the command below.

    Documented command
    pip install ragxplorer

  2. Import RAGxplorer and create a client with RAGxplorer(embedding_model="thenlper/gte-large").

  3. Load a PDF using client.load_pdf("presentation.pdf", verbose=True).

  4. Call client.visualize_query("What are the top revenue drivers for Microsoft?").

Expected outcome

The documented workflow loads the PDF and produces a visualization for the supplied query.

Guide limitations

  • The README does not specify additional environment setup, PDF constraints, or visualization controls.
Documentation 1 ↗
COMPARE OPTIONS

Compare options for Retrieval-augmented applications

These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.

ProjectDocumented purposePlatformAccess and requirements
RagxplorerLoad a PDF into a RAGxplorer client.CLI, Cloud, Web
LangsearchCrawl website or local data for a knowledge base.CLI, Self-hosted, Server
Hybrid Search RagCombine document retrieval and language-model generation in a configurable workflow.
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
15 October 2026
Original website title
gabrielchua/RAGxplorer · Official homepage title · retained in its source language
How we review sourcesSuggest a correction