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https://github.com/richardleighdavies/prompt-engineering-in-practice
Practical code examples and implementations from the book "Prompt Engineering in Practice". Demonstrates text generation, prompt chaining, and prompt routing using Python and LangChain. Features real-world examples of interacting with OpenAI's GPT models, structured output handling, and multi-step prompt workflows.
https://github.com/richardleighdavies/prompt-engineering-in-practice
ai artificial-intelligence chatbot data-science deep-learning gpt langchain llm machine-learning natural-language-processing nlp openai prompt-engineering pydantic python text-generation
Last synced: 8 days ago
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Practical code examples and implementations from the book "Prompt Engineering in Practice". Demonstrates text generation, prompt chaining, and prompt routing using Python and LangChain. Features real-world examples of interacting with OpenAI's GPT models, structured output handling, and multi-step prompt workflows.
- Host: GitHub
- URL: https://github.com/richardleighdavies/prompt-engineering-in-practice
- Owner: richardleighdavies
- License: mit
- Created: 2024-10-27T20:05:17.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2024-12-01T18:08:52.000Z (about 2 months ago)
- Last Synced: 2024-12-01T18:36:13.730Z (about 2 months ago)
- Topics: ai, artificial-intelligence, chatbot, data-science, deep-learning, gpt, langchain, llm, machine-learning, natural-language-processing, nlp, openai, prompt-engineering, pydantic, python, text-generation
- Language: Python
- Homepage: https://www.manning.com/books/prompt-engineering-in-practice
- Size: 29.3 KB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Prompt Engineering in Practice - Code Examples
This repository contains the practical code examples from the book "Prompt Engineering in Practice" by Richard Davies, published by Manning Publications.
## About the Book
"Prompt Engineering in Practice" teaches you how to write, refine, organize, and optimize AI prompts that generate relevant and useful text and images. The book covers essential techniques for working with models like ChatGPT, Stable Diffusion, and Gemini, focusing on:
- Designing prompts that generate accurate and readable responses from LLMs
- Mitigating hallucinations in LLM output
- Domain-aware content generation using RAG (Retrieval Augmented Generation)
- Understanding how AI model design affects your prompts
- Evaluating, optimizing, and organizing your prompts
## Project Structure
```
.
├── chapter_07_text_generation/
├── chapter_08_prompt_chaining/
├── chapter_09_prompt_routing/
├── LICENSE
├── pyproject.toml
└── README.md
```
## Features
- Text generation with customizable system prompts
- Structured output handling using Pydantic schemas
- Prompt chaining for complex conversational flows
- Dynamic prompt routing based on user input
- Integration with OpenAI's GPT models
## Requirements
- Python 3.x
- OpenAI API key
- Required packages listed in `requirements.txt`
## Installation
1. Clone the repository:
```sh
git clone https://github.com/richardleighdavies/prompt-engineering-in-practice.git
cd prompt-engineering-in-practice
```
2. Navigate to the desired example directory and set up your `.env` file:
```sh
cd chapter_07_text_generation/practical_example_01
echo "OPENAI_API_KEY=your_api_key_here" > .env
```
3. Create a virtual environment and install dependencies:
```sh
python3 -m venv .venv
source .venv/bin/activate
pip install --upgrade pip
pip install -r requirements.txt
```
## Usage
Execute the example:
```sh
python3 main.py
```
### Notes
- **Self-Contained Examples:** Each section is an independent project. Repeat the steps above for each example you wish to run.
## License
This project is licensed under the MIT License - see the `LICENSE` file for details.
## Author
Richard Davies - Chief Technology Officer (CTO) at Vera, specializing in Applied Artificial Intelligence.
## Contributing
This is a companion repository for the book "Prompt Engineering in Practice". While we appreciate your interest, we are not accepting contributions at this time.