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OpenAI API Prompt Engineering Cheat Sheet

Common Variables Used in OpenAI API

Endpoint URL

API Key

Model

Prompt

Temperature

Max Tokens

Top PSets the probability threshold for sampling (a float between 0 and 1). This threshold helps in determining the diversity of the generated text by intricately controlling the nucleus sampling process. By setting this threshold, the model can be instructed to produce more predictable or more diverse outputs, depending on the specific requirements of the task at hand. Adjusting the Top P value has a significant impact on the quality and variety of the text generation outcomes.

Frequency Penalty

Presence Penalty

Deep Learning Applications

Exploring how deep learning revolutionizes various sectors.

Healthcare

Deep learning improves patient care and diagnosis accuracy.

Medical Imaging

Analyzing X-rays, MRIs for early disease detection.

Drug Discovery

Accelerating the creation of new pharmaceuticals.

Genomics

Understanding DNA for personalized medicine.

Predictive Analytics

Forecasting patient outcomes to support treatment decisions.

Autonomous Vehicles

Deep learning powers self-driving car technology.

Sensor Fusion

Combining data from cameras, radar, and LiDAR.

Path Planning

Determining the best path for the vehicle to take.

Object Detection

Identifying pedestrians, vehicles, and other obstacles.

Behavior Prediction

Anticipating the actions of other road users.

Finance

Risk management and algorithmic trading use deep learning.

Credit Scoring

Evaluating loan eligibility more accurately.

Fraud Detection

Identifying suspicious transactions quickly.

Algorithmic Trading

Executing trades using predictive models.

Portfolio Management

Optimizing investment strategies with AI.

Entertainment

Changing how content is created and consumed.

Content Recommendation

Personalizing what users watch or listen to.

Game Development

Creating more realistic and interactive AI characters.

Visual Effects

Automating complex visual effect tasks.

Music Composition

Composing music with deep learning models.

Understanding Max Tokens in Language Models

Definition

Importance

Impact on Output Text

Chat with AI

Create a simple HTML code to dispay the time on a webpage

<!DOCTYPE html>
<html>
<head>
<title>Display Time</title>
<script>
function startTime() {
    var today = new Date();
    var h = today.getHours();
    var m = today.getMinutes();
    var s = today.getSeconds();
    m = checkTime(m);
    s = checkTime(s);
    document.getElementById('txt').innerHTML =
    h + ":" + m + ":" + s;
    var t = setTimeout(startTime, 500);
}
function checkTime(i) {
    if (i < 10) {i = "0" + i};  // add zero in front of numbers < 10
    return i;
}
</script>
</head>

<body onload="startTime()">

<div id="txt"></div>

</body>
</html>

By using JavaScript within this HTML document, the time is generated and updated every half a second for accuracy.

Chat with AI

Explain it

The HTML document provided defines a digital clock feature using JavaScript. Let's break down each part:

This code creates a simple digital clock on a webpage that updates in real-time.

Chat with AI

How can i do this

To create a content-rich text card with the given information, follow these steps:

  1. Define the Title: Determine a clear and concise title that represents the content of the card, such as "API Key Authentication".

  2. Establish Hierarchy: Use formatting to denote the importance of different sections. For instance, make the title bold and larger, and sub-sections slightly smaller.

  3. Content Breakdown: Separate the content into logical blocks. For example, the definition of API Key, its purpose, and a caution about security could be individual blocks.

  4. Emphasize Key Points: Bold or highlight key terms and phrases like "unique token", "authentication", and "must be kept secure".

  5. Add an Icon or Graphic: If possible, include a relevant icon (like a key) to visually represent the concept of an API key.

  6. Provide Clear Instructions: Since it mentions the need for security, adding a brief tip on how to secure an API key can be both educational and practical.

Here is an example of how your text card content could be arranged:

API Key Authentication A unique token required for authentication. Must be kept secure to prevent unauthorized access.

Tip for Security: Store your API keys in environment variables or a secure key management service.

By following these guidelines, you create a clear, informative, and visually appealing text card for users or developers who need to understand the significance and security of an API Key.

Top P Sampling

Top P Sampling controls the diversity of generated text using a probability threshold.

Concept Explanation

Understanding the mechanism behind Top P Sampling.

Probability Threshold

Determines the cut-off for picking the next word based on its probability.

Nucleus Sampling

A method where only the top P% probabilities are considered.

Diversity Control

Adjusting Top P affects the randomness and uniqueness of the text.

Task Requirement Adaptation

Top P can be tuned for tasks needing more predictable or diverse text.

Impact on Text Generation

The consequences of modifying the Top P value.

Predictability

A lower Top P leads to more predictable outputs.

Diversity

A higher Top P encourages a wider variety of generated text.

Quality of Output

Finding a balance in Top P can influence the perceived quality of text.

Variety

Changes the range of different words and ideas introduced in the text.

Implementation

Technical aspects of applying Top P in models.

Model Instruction

How to set the Top P value in machine learning models.

Threshold Setting

Choosing the appropriate Top P value between 0 and 1.

Algorithm Integration

Incorporating Top P into the text generation algorithm.

Sampling Process

The step-by-step process of selecting words based on the Top P threshold.

Chat with AI

Make longer

A prompt is the input text that the model uses to generate its response. It can include instructions or context for the desired output. Essentially, it serves as a cue or stimulus that guides the artificial intelligence in understanding the task at hand and producing the relevant information or content in response to the user's request.

What is a prompt?

A prompt is the input text that triggers the model's response. It's the instruction set or question you ask the model.

Importance of Prompts

Prompts guide the model to understand the desired output format and context, ensuring relevance in the response.

Prompt Design

Crafting an effective prompt involves clarity, context, and sometimes examples to steer the model's generation.

Response Interpretation

The model's output needs interpretation, as it's dependent on how well the prompt was structured and phrased.

Keep it Clear and Concise

Use clear and direct language to avoid ambiguity and improve the likelihood of a relevant response.

Provide Examples

When possible, include examples in the prompt to guide the AI in generating similar content.

Iterate and Refine

Use the responses to refine your prompts, making them more effective with each iteration.

Use Constraints

Specify constraints in your prompts to narrow down the model's focus and control the output.

Token Limits

Be aware of the token limits for prompts and responses to ensure your inputs are within the permissible range.

Temperature Setting

Adjust the temperature parameter to control randomness in responses; lower for deterministic outputs.

Max Tokens

Set the max_tokens parameter to define the length of the generated content.

Stop Sequences

Use stop sequences to indicate to the model where to end the response.

Chain of Thought Prompting

Provide a reasoning structure in the prompt to guide the model through a thought process.

Few-Shot Learning

Include a few examples of input-output pairs to help the model understand the expected task.

Zero-Shot Learning

Design prompts that require the model to generate content without prior examples, based on the given context.

Fine-Tuning

For specialized responses, consider fine-tuning the model with specific data relevant to your domain.

Chatbots

Use prompts to simulate conversation, answer questions, or provide user support.

Content Generation

Craft prompts for articles, stories, code, or any creative content generation.

Data Analysis

Guide the model to perform data analysis, summarize information, or make predictions.

Translation and Language Tasks

Prompt the model for translating text or performing other language-related tasks.

Monitor Outputs

Regularly review the outputs for errors or misinterpretations to refine the prompts.

A/B Testing

Test different versions of prompts to see which yields better results for your specific use case.

Role Playing

Frame the prompt as if the AI is a specific character or expert, which can influence the nature of the output.

Feedback Loops

Incorporate the model's outputs back into new prompts as a feedback mechanism for advanced prompt engineering.

Chat with AI

Doesn't openai API key have a system prompt message as well as w user message

Yes, OpenAI's API typically features two types of prompts when interacting with their system:

  1. System Prompt: This is a predefined message or a group of instructions that the system uses to initialize conversations or to set a particular context for the AI's performance. It ensures the system operates within a designed framework.

  2. User Prompt: This is the input provided by the user that they want the AI to respond to. It can be a question, a statement, a set of instructions, or just a topic the user wants the AI to elaborate on or generate content related to.

The distinction between these prompts allows for a structured interaction where the AI understands the context given by the system and individual queries or commands by the user.

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