UpstageAI/solar-prompt-cookbook

UpstageAI/solar-prompt-cookbook

Description: Solar Prompt Cookbook

Language: Jupyter Notebook

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Open issues: 2

Created: 2024-11-04T07:11:37Z

Pushed: 2026-02-11T14:47:56Z

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README:

Solar Prompt Cookbook

Getting Started Quickly with Codespace


Prompting serves as a cohesive natural language interface for human-AI interactions and has become widely adopted with the rise of large language models (LLMs). LLMs are particularly sensitive to prompt design. This cookbook aims to provide a comprehensive, step-by-step guide for crafting highly effective prompts within Solar, emphasizing practical techniques and strategies. Central to this course is the concept of a prompt engineering cookbook-a collection of structured recipes outlining best practices for prompt creation. These recipes present proven methods to optimize interactions with solar models, addressing common challenges and providing frameworks for diverse use cases.

By the end of this book, you will be able to:

1. Build a strong foundation in basic prompt structure. 2. Develop a thorough understanding of Solar’s capabilities and limitations. 3. Discover solutions for overcoming common challenges to maximize prompt engineering with Solar. 4. Create optimized prompts from scratch for a wide range of applications, from common use cases to industrial fields.

Some of you may wonder when to use prompt engineering versus fine-tuning. Here’s a quick guide on each:

Use *prompt engineering* when:

• You need flexibility, fast iteration, and cost efficiency.
• Tasks are general or the model is instruction-tuned.
• Requirements may change often.

Use *fine-tuning* when:

• Tasks are speciliazed or domain-specific.
• Consistency, accuracy, and scalability are critical.
• Base model lacks necessary knowledge.

Start with prompt engineering; move to fine-tuning if results are inconsistent or too complex to handle with prompts alone.

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Course Structure and Content

This cookbook is designed to guide non-expert users in optimizing their interactions with Upstage’s `Solar Pro` model.

Each chapter is structured with:

• a lesson
• prompt example
• practice section

In the example section, a comparison between the results of good and bad prompts is provided.

Once you're ready to begin, head over to [Getting Started-Tutorial How-To.](./00_Chapter%200.%20Getting%20Started-Tutorial%20How-To.ipynb)

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Table of Contents

0. Setting Up Your Environment

• [Chapter 0: Getting Started-Tutorial How-To](./00_Chapter%200.%20Getting%20Started-Tutorial%20How-To.ipynb)

1. Introduction to Prompts

• [Chapter 1: Basic Prompt Structure](./01_Chapter%201.%20Basic%20Prompt%20Structure.ipynb)
• [Chapter 2: Direct and Clear Prompts](./02_Chapter%202.%20Direct%20and%20Clear%20Prompts.ipynb)
• [Chapter 3: Five Focal Prompt Elements and Types](./03_Chapter%203.%20Five%20Focal%20Prompt%20Elements%20and%20Types%20.ipynb)

2. Basic Prompt Engineering Techniques

• [Chapter 4: Examples and Few-Shot Prompting](./04_Chapter%204.%20Examples%20and%20Few-Shot%20Prompting.ipynb)
• [Chapter 5: Role and Style Prompting](./05_Chapter%205.%20Role%20and%20Style%20Prompting.ipynb)
• [Chapter 6: Structured vs. Unstructured Prompting](./06_Chapter%206.%20Unstructured%20vs.%20Structured%20Prompting.ipynb)
• [Chapter 7: Reasoning and Chain-of-Thought Prompting](./07_Chapter%207.%20Reasoning%20and%20Chain-of-Thought%20Prompting.ipynb)

3. Advanced Prompt Engineering Techniques

• [Chapter 8: Resolving Hallucinations](./08_Chapter%208.%20Resolving%20Hallucinations.ipynb)
• [Chapter 9: Complex Prompt Chaining](./09_Chapter%209.%20Complex%20Prompt%20Chaining.ipynb)

[Appendix. Use Cases: Industry Use Cases](./10_Appendix.%20Use%20Cases:%20Industry%20Use%20Cases.ipynb)

[Appendix. Use Cases: Prompt Optimization](./11_Appendix.%20Use%20Cases:%20Prompt%20Optimization.ipynb)