OpenAI API Prompt Engineering Cheat Sheet
Common Variables Used in OpenAI API
Endpoint URL
The base URL for the OpenAI API calls.
Specific API functions' URLs, like text completion, which uses a different endpoint.
API Key
A unique token required for authentication.
Must be kept secure to prevent unauthorized access.
Model
Specifies the language model to use (e.g.,
text-davinci-003).Each model has different capabilities and costs.
Prompt
The input text that the model uses to generate its response.
Can include instructions or context for the desired output.
Temperature
Controls the randomness of the output (a float between 0 and 1).
Lower values make the model more deterministic, higher values make it more creative.
Max Tokens
The maximum number of tokens to generate in the model's response.
Affects the length of the output text.
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
Discourages the model from repeating itself (a float between -2.0 and 2.0).
Helps in reducing redundancy in the generated text.
Presence Penalty
Affects the likelihood of introducing new concepts (a float between -2.0 and 2.0).
Encourages the model to explore new ideas in the completion.
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
Max Tokens refer to the upper limit on the number of tokens that a language model can generate in a single response.
Importance
This limit affects the length and detail of the model's output, ensuring responses are concise and relevant.
Impact on Output Text
The setting for Max Tokens directly influences how much content the model will produce, impacting both the verbosity and complexity of the 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:
<!DOCTYPE html>: This declaration defines the document to be HTML5.<html>: The root element of an HTML page.<head>: Contains meta-information about the HTML document, such as its title and scripts.Display Time>: Sets the text shown on the tab or window title as "Display Time".<script>: Contains the JavaScript code which makes the clock work.function startTime(): This is the main function that updates the clock. It is called when the body of the document is loaded and recursively every 500 milliseconds.var today = new Date();: Creates a new Date object representing the current time.var h = today.getHours();: Gets the current hour from the Date object.var m = today.getMinutes();: Gets the current minute from the Date object.var s = today.getSeconds();: Gets the current second from the Date object.m = checkTime(m); s = checkTime(s);: Calls the checkTime function to add a leading zero to the minute and second values if they are less than 10.document.getElementById('txt').innerHTML = h + ":" + m + ":" + s;: Updates the inner HTML of the div element with the id "txt" to display the current time.var t = setTimeout(startTime, 500);: Uses the setTimeout function to call the startTime function again after 500 milliseconds.
function checkTime(i): The helper function to format the time.if (i < 10) {i = "0" + i};: Adds a leading zero to the number if it is less than 10.return i;: Returns the formatted string.
<body onload="startTime()">: Contains the content of the HTML document and triggers thestartTimefunction when the body is loaded.<div id="txt"></div>: An emptydivwhere the time is displayed. Its content is updated by the JavaScript.
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:
Define the Title: Determine a clear and concise title that represents the content of the card, such as "API Key Authentication".
Establish Hierarchy: Use formatting to denote the importance of different sections. For instance, make the title bold and larger, and sub-sections slightly smaller.
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.
Emphasize Key Points: Bold or highlight key terms and phrases like "unique token", "authentication", and "must be kept secure".
Add an Icon or Graphic: If possible, include a relevant icon (like a key) to visually represent the concept of an API key.
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.
Definition: An API Key is a secure string that identifies a user or application making a call to an API service.
Purpose: It ensures that API requests are made by known and authorized users or services.
Security Caution: API keys are sensitive and should be protected. Do not expose them in publicly accessible areas such as GitHub, client-side code, etc.
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:
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.
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.