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Probly

Probly is a browser-based spreadsheet application for analyzing tabular data with formulas, Python computation through Pyodide/WebAssembly, interactive visualizations, AI-assisted analysis and image data extraction.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Probly — OpenViST project profile in AI Data & Analytics.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Probly when spreadsheet data needs to be explored with formulas, browser-side Python, charts or AI-assisted questions, or when image-based data needs to be extracted into a spreadsheet workflow.

Who it is for

  • People who want to explore spreadsheet data with formulas, Python and charts in one browser-based workflow.
  • Users who want natural-language questions, AI suggestions or trend analysis alongside spreadsheet work.
  • Teams or individuals who need to extract data from images into a spreadsheet workflow.

Documented uses

  • Import data or start a blank sheet and work with spreadsheet formulas.
  • Run Python analysis in the browser using WebAssembly.
  • Create interactive charts and visualizations from spreadsheet data.
  • Ask natural-language questions and use saved or predefined prompts for analysis.
  • Extract data from images for spreadsheet use.
Before you choose

Requirements & limits

The repository documents Docker and manual installation. Self-hosting requires an OpenAI API key for AI features; the README lists Node.js 18 or higher, npm or yarn, and a modern browser for manual setup.

  • Python execution uses Pyodide/WebAssembly and is described as running locally in the browser.
  • OpenAI API calls are proxied through the server; image extraction uses a Vision API.
  • The documented implementation uses Next.js 14, TypeScript, React, Handsontable, HyperFormula and ECharts.
  • The repository is public and states that Probly is licensed under MIT.

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

Set up Probly with Docker

Build and start the documented self-hosted Probly application with Docker.

Before you start

  • Docker and Docker Compose
  • Git
  • An OpenAI API key

Steps

  1. Clone the repository and change into the probly directory.

  2. Create a .env file containing OPENAI_API_KEY=your_api_key_here, replacing the placeholder with your key.

  3. Run docker compose build.

  4. Run docker compose up -d, then access the application at http://localhost:3000.

Expected outcome

The README directs users to the application at http://localhost:3000 after the Docker startup steps.

Guide limitations

  • AI features require an OpenAI API key.
  • These are repository instructions, not a report of a tested deployment.
Documentation 1 ↗
Source-based practical guide

Install Probly manually for development

Install dependencies and start the documented development server.

Before you start

  • Node.js 18 or higher
  • npm or yarn
  • A modern web browser
  • An OpenAI API key

Steps

  1. Clone the repository and change into the probly directory.

  2. Run npm install.

  3. Set the OPENAI_API_KEY environment variable to your key.

  4. Run npm run dev and launch the application in a browser.

Expected outcome

The documented development server is started for browser access.

Guide limitations

  • AI features require the OpenAI API key.
  • These are repository instructions, not a report of a tested installation.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
13 October 2026
Original website title
PragmaticMachineLearning/probly · Official homepage title · retained in its source language
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