phira-ai

phira-ai / OpenPlot

Public

The agentic plotting "IDE" built for everyone

43
0
100% credibility
Found Mar 24, 2026 at 43 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

OpenPlot is an interactive desktop app that lets users generate, refine, and version-control data plots using AI agents connected to local files.

How It Works

1
📖 Discover OpenPlot

You hear about a friendly app that turns your data files into beautiful charts using smart helpers, without needing to code.

2
⬇️ Get the app

Download the ready-to-use program for your computer and open it up.

3
📁 Pick your data

Choose files from your computer, preview them, and tell the helper what kind of chart you want.

4
✨ Watch magic happen

The smart helper creates your first chart draft automatically while you relax.

5
Tweak or pinpoint?
💬
Chat refinements

Describe changes in simple words and get updated drafts.

✏️
Draw fixes

Circle problem spots and say what's wrong for targeted updates.

6
🔄 Review versions

Switch between saved chart versions like flipping pages to compare easily.

✅ Download perfection

Grab your final chart image and the ready-to-run instructions to share or reuse anytime.

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Star Growth

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AI-Generated Review

What is OpenPlot?

OpenPlot is a Python desktop app that acts as an agentic plotting IDE, connecting your data files to AI coding agents like Codex, Claude Code, or OpenCode for generating and refining visualizations. Instead of verbose prompting loops, you preview plots, drag-select problem areas for lazy feedback like "move legend," and watch agents fix them live via structured prompts. Built with a React frontend and FastAPI backend, it runs locally on macOS, Windows, or Linux, exporting runnable scripts alongside images.

Why is it gaining traction?

It bridges agentic github copilot-style coding with precise plot iteration: annotation mode scopes changes to exact regions, git-like branching tracks versions, and auto mode runs self-refining loops without babysitting. Multi-runner support and built-in Python runtime with matplotlib/seaborn mean no setup hassles, turning github agentic workflows into a coffee-break task versus hours of tweaks.

Who should use this?

Data analysts crafting reports from CSV/Excel, ML engineers prototyping model outputs, or scientists needing publication-ready figures fast. Ideal for teams using agentic github actions or github agentic chat for viz, skipping manual seaborn hacks.

Verdict

Try it if agentic plotting fits your flow—pre-built binaries and CLI like `openplot serve file.py` make onboarding quick—but with 43 stars and 1.0% credibility, it's early alpha. Solid docs and packaging offset the immaturity; watch for runner integrations.

(187 words)

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