KodyKlupt

KodyKlupt / PromptMOL

Public

Control PyMOL with natural language prompts using an LLM to make better figures, analyze structures, and more...

protein-structure pymol pymol-plugin structural-biology
27
9
100% credibility
Found May 01, 2026 at 27 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

PromptMOL is a plugin for the PyMOL molecular viewer that translates natural language instructions into PyMOL commands using AI, enabling easy visualization, analysis, and export of molecular structures.

How It Works

1
🔍 Discover PromptMOL

You hear about a handy helper that lets you talk to PyMOL in plain English to visualize molecules easily.

2
📦 Add to PyMOL

You simply add this friendly assistant to your PyMOL so it loads every time you open it.

3
Pick Your Helper
🏠
Local Helper

Use the easy local option that works offline without any sign-up.

☁️
Online Helper

Connect to a quick online service by sharing a simple access code.

4
💬 Chat in English

Type everyday words like 'fetch this protein and show it as a colorful cartoon' right in PyMOL.

5
✨ See Magic Happen

Watch your molecule appear perfectly styled, measured, or analyzed just as you asked.

6
🔄 Refine and Undo

Ask follow-up questions naturally or step back if you want to try something different.

7
💾 Save Your Work

Save beautiful images, data tables, or your whole session to share or reuse later.

🎉 Pro Results Easily

You now create stunning molecular views and insights effortlessly, like a visualization expert.

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Star Growth

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AI-Generated Review

What is PromptMOL?

PromptMOL is a Python plugin for PyMOL that lets you control the visualizer with natural language prompts via an LLM. Instead of typing cryptic PyMOL commands, just say "fetch 1HPV, show as cartoon colored by chain" or "analyze residues within 4 angstroms of the ligand" – it generates and runs the code automatically. It solves the pain of learning PyMOL syntax for making better figures and structural analysis, supporting local LM Studio or cloud LLMs like OpenAI and Anthropic.

Why is it gaining traction?

Multi-turn conversations keep context across prompts, so follow-ups like "make the ligand yellow sticks" just work without reloading. Dry-run previews commands safely, undo restores scenes, and session logs save replayable scripts – perfect for reproducible analysis. Local LLM support means no API keys or costs, hooking devs who want quick control over PyMOL without syntax hunting.

Who should use this?

Structural biologists scripting PyMOL for protein figures, molecular modelers analyzing contacts or B-factors, and researchers exporting CSVs or high-DPI renders from sessions. If you're tired of command-line guesswork for distances, alignments, or styling, this speeds up daily viz workflows.

Verdict

Grab it if you live in PyMOL – install is a one-liner, docs are thorough, and it delivers immediate value despite 27 stars and 1.0% credibility signaling early maturity. Test with LM Studio first; scale to paid LLMs for complex analysis.

(178 words)

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