metadata

title: What Is Prompt Engineering
emoji: 🚀
colorFrom: green
colorTo: green
sdk: gradio
sdk_version: 5.21.0
app_file: app.py
pinned: false

🧠 Prompt Engineering Interactive Lab

An interactive demo that showcases how different prompt engineering techniques affect AI outputs when working with large language models.

About

This application demonstrates various prompt engineering techniques using Google's Gemma models via OpenRouter API. Users can experiment with the same query across different prompt techniques to understand how the framing of a prompt dramatically impacts the quality and nature of AI responses.

Features

Compare multiple prompt engineering techniques side-by-side
Choose from various Gemma model sizes (1B to 27B parameters)
Adjust temperature to control creativity vs precision
Real-time prompt preview
Detailed explanations of each technique

Prompt Techniques Included

Basic Prompting: Direct questions without additional context
Role-Based Prompting: Assigning expertise personas to the model
Step-by-Step Reasoning: Requesting methodical thinking
Chain of Thought: Encouraging careful, sequential reasoning
Few-Shot Learning: Demonstrating examples before the actual prompt

Setup

Install the required dependencies:
```
pip install -r requirements.txt
```
(Optional) Set up your own OpenRouter API key:
- Sign up at OpenRouter
- Create a .env file with your API key:
```
OPENROUTER_API_KEY=your_api_key_here
```
- A default API key is provided but has limited quota
Run the application:
```
python prompt_engineering_demo.py
```
Open your browser at http://localhost:7860

Usage

Enter your query in the text box
Select a Gemma model size
Choose a prompt technique
Adjust the temperature setting if desired
Click "Generate Response"
View the formatted prompt and resulting AI response
Try the same query with different techniques to compare outcomes

Related Resources

This demo is a companion to the blog post "What is Prompt Engineering?"

License

[Add your license information here]