ai-prompt-eng: add notes

ai/prompt-engineering-notes/prompt-engineering-notes.md

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+# Prompt Engineering - Notes
+
+## Table of Contents (ToC)
+
+  - [Introduction](#introduction)
+    - [What's Prompt Engineering?](#whats-prompt-engineering)
+    - [Key Concepts and Terminology](#key-concepts-and-terminology)
+    - [Applications](#applications)
+  - [Fundamentals](#fundamentals)
+    - [Prompt Engineering Architecture Pipeline](#prompt-engineering-architecture-pipeline)
+    - [How Prompt Engineering Works?](#how-prompt-engineering-works)
+    - [Prompt Engineering Techniques](#prompt-engineering-techniques)
+    - [Some Hands-on Examples](#some-hands-on-examples)
+  - [Tools \& Frameworks](#tools--frameworks)
+  - [Hello World!](#hello-world)
+  - [Lab: Zero to Hero Projects](#lab-zero-to-hero-projects)
+  - [References](#references)
+  - [References](#references-1)
+
+
+## Introduction
+Prompt engineering is the process of designing and optimizing prompts for AI models to elicit the desired responses.
+
+### What's Prompt Engineering?
+- Crafting input prompts to guide AI outputs.
+- Enhancing model performance with well-designed prompts.
+- A critical skill for interacting with AI systems effectively.
+
+### Key Concepts and Terminology
+- **Prompt**: The input given to an AI model.
+- **Completion**: The output generated by the AI model.
+- **Tokens**: Units of text the model processes.
+- **Context**: The surrounding text influencing the model's output.
+
+### Applications
+- Generating human-like text in chatbots.
+- Summarizing documents and articles.
+- Automating customer service responses.
+- Creating interactive AI-based tools.
+
+## Fundamentals
+
+### Prompt Engineering Architecture Pipeline
+- Defining the task and objectives.
+- Crafting initial prompts.
+- Iterative testing and refinement.
+- Evaluating model outputs for desired performance.
+
+### How Prompt Engineering Works?
+- Identifying the purpose and scope of the task.
+- Designing prompts with specific instructions.
+- Utilizing examples to guide model responses.
+- Refining prompts based on model feedback.
+
+### Prompt Engineering Techniques
+- **Zero-shot**: Providing no examples, relying on the model's general knowledge.
+- **Few-shot**: Giving a few examples to guide the model.
+- **One-shot**: Providing a single example to demonstrate the task.
+- **Multi-shot**: Offering multiple examples to improve response accuracy.
+- **Chain-of-thought**: Structuring prompts to show the reasoning process step-by-step.
+
+### Some Hands-on Examples
+- **Text Summarization**: Crafting prompts for concise summaries.
+- **Conversational Agents**: Designing prompts for engaging dialogues.
+- **Content Generation**: Creating prompts for writing assistance.
+
+## Tools & Frameworks
+- OpenAI GPT
+- Hugging Face Transformers
+- Google's T5
+- Microsoft DialoGPT
+
+## Hello World!
+```python
+import openai
+
+# Set up the OpenAI API key
+openai.api_key = 'your-api-key'
+
+# Define a simple prompt
+prompt = "Explain the concept of prompt engineering in AI."
+
+# Get the completion from the AI model
+response = openai.Completion.create(
+    engine="text-davinci-003",
+    prompt=prompt,
+    max_tokens=100
+)
+
+# Print the response
+print(response.choices[0].text.strip())
+```
+
+## Lab: Zero to Hero Projects
+- **Project 1**: Building a FAQ chatbot using prompt engineering.
+- **Project 2**: Creating a personalized email assistant.
+- **Project 3**: Developing a story generator with adjustable prompts.
+- **Project 4**: Designing an AI-driven content summarizer.
+
+## References
+- [OpenAI documentation](https://beta.openai.com/docs/)
+- [Hugging Face Transformers](https://huggingface.co/transformers/) 
+- [Google's T5](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) 
+- [Microsoft DialoGPT](https://github.com/microsoft/DialoGPT)
+- https://www.promptingguide.ai/techniques
+
+Free Course: 
+
+- [Course on ChatGPT Prompt Engineering for Developers - by DeepLearningAI](https://learn.deeplearning.ai/chatgpt-prompt-eng/lesson/2/guidelines)
+
+Awesome ChatGPT Prompts: 
+
+- [Awesome ChatGPT Prompts](https://prompts.chat/)
+- [Awesome GPT Prompts](https://www.awesomegptprompts.com/)
+
+Visual Prompting
+
+- [INTRODUCING - Visual Prompting - @LandingAI](https://landing.ai/)
+- [What is Visual Prompting? - LandingAI](https://landing.ai/blog/what-is-visual-prompting/)
+- [Visual Prompting Livestream With Andrew Ng](https://www.youtube.com/watch?v=FE88OOUBonQ)
+- [CVPR 2023 Tutorial on Prompting in Vision](https://prompting-in-vision.github.io/)
+

ai/prompt-engineering-notes/readme.md

@@ -7,25 +7,8 @@
 
 Credits to : Max Rascher
 
+## Contributing
 
+Please refer to this [CONTRIBUTING.md](../../CONTRIBUTING.md) file.
 
-## References
-
-Free Course : 
-
-- [Course on ChatGPT Prompt Engineering for Developers - by DeepLearningAI](https://learn.deeplearning.ai/chatgpt-prompt-eng/lesson/2/guidelines)
-
-Awesome ChatGPT Prompts : 
-
-- [Awesome ChatGPT Prompts](https://prompts.chat/)
-- [Awesome GPT Prompts](https://www.awesomegptprompts.com/)
-
-Visual Prompting
-
-- [INTRODUCING - Visual Prompting - @LandingAI](https://landing.ai/)
-- [What is Visual Prompting? - LandingAI](https://landing.ai/blog/what-is-visual-prompting/)
-- [Visual Prompting Livestream With Andrew Ng](https://www.youtube.com/watch?v=FE88OOUBonQ)
-- [CVPR 2023 Tutorial on Prompting in Vision](https://prompting-in-vision.github.io/)
-
-
-
+> **"...And so my hope is someday when the next Aristotle is alive, we can capture the underlying worldview of that Aristotle, in a computer, and someday some students will be able to not only read the words Aristotle wrote but ask Aristotle a question and get an answer."** - Steve Jobs (Generative AI Prediction from 1985 Speech)