MURAL API Samples

Sample code snippets demonstrating using the MURAL API

 

Sample	Demonstrates how to ...
sample-01_create-a-mural	Create a new mural from mural widgets saved in .json format Sample mural .json Sample Python notebook
sample-02_overlap-inside-rectangle	Tell if a sticky note is overlapping or inside of a rectangle shape Sample mural .json Sample Python notebook
sample-03_overlap-inside-circle	Tell if a sticky note is overlapping or inside of a circle shape Sample mural .json Sample Python notebook
sample-04_sentiment	Analyze the sentiment of sticky notes in a mural Uses the IBM Watson NLP Python library Sample mural .json Sample Python notebook
sample-05_color-code-by-sentiment	Change the color of sticky notes in a mural Uses the IBM Watson NLP Python library Sample mural .json Sample Python notebook
sample-06_group	Move sticky notes into organized groupings inside shapes Sample mural .json Sample Python notebook
sample-07_add-sticky-notes	Add sticky notes into a rectangle in organic-seeming, random positions Sample Python notebook
sample-08_paginate-through-widgets	Paginate through getwidgets results Sample mural .json Sample Python notebook
sample-09_absolute-position	Get the absolute [ x, y ] position of grouped widgets Sample mural .json Sample Python notebook
sample-10_translate	Post a copy of each English sticky note translated into French Uses IBM Watson Language Translator Blog post Sample mural .json Sample Python notebook
sample-11_search	Search murals using IBM Watson Discovery Blog post Sample murals (.json) Sample Python notebooks: Create sample murals Read live data from murals Index data in Discovery Search murals Sample Flask app
sample-12_GPT-3	Seed a mural with content generated by a GPT model using the OpenAI API Blog post Sample Python code Demo video
sample-13_devils-advocate	Seed a mural with arguments against proposed plans using a foundation model in IBM watsonx.ai Blog post Sample Python notebook
sample-14_classify-by-class-name	Classify sticky notes by class name only, using a foundation model in IBM watsonx.ai Sample Python notebook
sample-15_classify-by-description	Classify sticky notes by class description, using a foundation model in IBM watsonx.ai Sample Python notebook
sample-16_classify-by-exemplars	Classify sticky notes by class exemplars, using a foundation model in IBM watsonx.ai Sample Python notebook
sample-17_llm-cluster	Cluster sticky notes by using a foundation model in IBM watsonx.ai to identify top three themes in the sticky notes and then classify the sticky notes by those themes. Sample Python notebook
sample-18_llm-summary	Use a foundation model in IBM watsonx.ai to analyze sticky notes in a mural: identify themes, classify sticky notes, and summarize classes. Then generate a report. Sample Python notebook Sample report