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Prompt Engineering

Prompt Engineering is a public GitHub repository of 22 hands-on Jupyter Notebook tutorials that demonstrate prompt-engineering techniques for large language models, including few-shot learning, in-context learning, chain-of-thought, self-consistency and tree-of-thought prompting.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Prompt Engineering — OpenViST project profile in AI Developer Tools & SDKs.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when you want tutorial-style notebook examples to study a particular prompt-engineering technique, rather than a hosted model service or API.

Who it is for

  • Learners studying practical prompt-engineering approaches.
  • Developers exploring prompt patterns for large-language-model tasks.

Documented uses

  • Learn prompt-engineering concepts through notebook tutorials.
  • Explore and compare prompt patterns such as few-shot and in-context learning.
  • Consult examples of advanced prompting approaches, including chain-of-thought and tree-of-thought.
Before you choose

Requirements & limits

The GitHub repository is public. A software license is not identified in the available evidence.

  • The repository describes 22 tutorials, spanning basic prompt templates through advanced prompting methods.
  • Getting started involves cloning the repository and choosing a technique notebook.
  • The instructions do not specify the notebook runtime or any model credentials needed to execute examples.

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 the repository to explore a technique

Get the tutorial files locally and locate the technique notebook you want to study.

Before you start

  • Git and a local command-line environment.

Steps

  1. Clone the repository with the command below.

    Documented command
    git clone https://github.com/NirDiamant/Prompt_Engineering.git

  2. Change into the techniques directory with cd all_prompt_engineering_techniques.

  3. Choose a technique and follow the implementation guide in its notebook.

Expected outcome

The repository is available locally and you have located the notebook guide for a selected technique.

Guide limitations

  • The getting-started instructions do not specify notebook execution setup, model credentials or how to run model-backed examples.
  • The repository is public, but the evidence does not identify a software license.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
16 October 2026
Original website title
NirDiamant/Prompt_Engineering · Official homepage title · retained in its source language
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