Chat Prompt GPT, Midjourney

Search and store tool for GPT Chat Prompt, Midjourney

Welcome to Chat-Prompt.com, a searchable database and platform for exchanging templates for use with the Chat GPT and other AI models.
A text-based request can instruct the ChatGPT model, a big language model developed by OpenAI, to produce text that resembles human writing. Although it can assist you in producing responses, ChatGPT will be unable to do so if the input is inaccurate or does not properly express your goals. Because of this, Chat-Prompt.com was developed to make it easier for you to store and find intriguing prompts to produce the outcomes you need.
You can find a variety of templates in different sectors and topics in Chat-repository Prompt's to meet your demands. To save time while still doing the task precisely and fast, we want to encourage everyone to develop new templates for the community.
You only need to click the copy button on the templates you want to use as input for the Chat GPT to get started utilizing them. These templates might serve as models for new ones that you design.
We hope that Chat-Prompt.com will be a resource for you to find helpful templates to utilize with ChatGPT.

Optimizing SQL query performance by replacing subqueries with JOINs

Rewrite the following SQL query to use JOINs instead of subqueries for improved performance: [SQL query].

sql query optimization joins

Effective Indexing Techniques for Optimizing SQL Queries

Suggest indexing strategies for the following SQL query: [SQL query].

indexing sql optimization

Analyzing SQL Query for Potential Bottlenecks: A Guide to Optimize Database Performance

Analyze the given SQL query for any potential bottlenecks: [SQL query].

sql query database performance bottlenecks

Optimizing SQL Query for Better Performance: Tips and Techniques

Optimize the following SQL query for better performance: [SQL query].

sql performance optimization

How to Create a Quick-Start Guide for [Language] Library with Code Snippet for Easy Setup

Produce a quick-start guide for using the following [language] library: [code snippet].

programming library setup

Opinion Generator Function for Language Code Snippets: Expected Input and Output

Document the expected input and output for the given [language] function: [code snippet].

opinion code snippet language

Tips for Generating Usage Examples for [Language] API: [Code Snippet]

Generate usage examples for the following [language] API: [code snippet].

api programming language

How to Create a Concise API Reference for a Programming Language Class

Create a concise API reference for the given [language] class: [code snippet].

api programming language reference

Keyword Extraction: Extracting Meaningful Words from Text Sample

Perform keyword extraction on the following text: [text sample].

keyword extraction text analysis data mining

How to Identify the Main Topic(s) of Text with Opinion Generation

Identify the main topic(s) of the following text: [text sample].

text analysis opinion generation topic identification

How to Extract Named Entities from Text Sample: Step by Step Guide

Extract named entities from the following text: [text sample].

text analysis named entity recognition data extraction

Assessing [Language] Code Performance and Providing Optimization Suggestions

Assess the performance of the following [language] code and provide optimization suggestions: [code snippet].

code optimization language performance

Evaluating Code Modularity and Maintainability: A [Language] Code Snippet Analysis

Evaluate the modularity and maintainability of the given [language] code: [code snippet].

code modularity maintenance

Improving Error Handling in Language Code: Suggestions and Enhancements

Check the following [language] code for proper error handling and suggest enhancements: [code snippet].

error handling language code enhancements

Analyzing Coding Style for [Language]: [Code Snippet], Tips and Techniques

Analyze the given [language] code for adherence to [coding style guidelines]: [code snippet].

coding style language techniques

Reviewing and Suggesting Improvements for Language Code Snippet: Best Practices

Review the following [language] code for best practices and suggest improvements: [code snippet].

code snippet best practices programming

Reviewing Language Code for Security Vulnerabilities

Review the following [language] code for any security vulnerabilities: [code snippet].

security code vulnerabilities

How to Check for Race Conditions and Concurrency Issues in [Language] Code: A Guide

Check for any race conditions or concurrency issues in the given [language] code: [code snippet].

race conditions concurrency issues programming

How to Find and Fix Memory Leaks in [Language] Code

Find any memory leaks in the following [language] code and suggest fixes: [code snippet].

memory leaks debugging code fixes

How to Prevent Errors in Code: Analyzing and Improving [Language] Snippets

Analyze the given [language] code and suggest improvements to prevent [error type]: [code snippet].

error prevention code analysis programming

Identifying Potential Bugs in [Language] Code Snippet: Tips and Techniques

Identify any potential bugs in the following [language] code snippet: [code snippet].

potential bugs code snippet programming

Tips for Writing an Effective Code Loop in [Language] with [Data Structure] and [Operation]

Complete the following [language] loop that iterates over [data structure] and performs [operation]: [code snippet].

programming data structure code loop

Implementing Error Handling in [Language] for a Given Code Snippet: A Guide

Fill in the missing [language] code to implement error handling for the following function: [code snippet].

error handling programming coding

How to make an API Call using [language] and [API endpoint], Step-by-Step Guide

Complete the [language] code to make an API call to [API endpoint] with [parameters] and process the response: [code snippet].

api [language] code snippet

How to Write a Function that Calculates Desired Output in [Language]

Finish the [language] function that calculates [desired output] given the following input parameters: [function signature].

programming function calculation

How to Initialize a Data Structure with Values in [Language]: A Code Snippet

In [language], complete the following code snippet that initializes a [data structure] with [values]: [code snippet].

code snippet data structure programming

How to Write a Script Using a Library/Framework with Given Requirements

Write a [language] script to perform [task] using [library/framework] with the following requirements: [requirements list].

script library programming

Implementing [Design Pattern] in [Language] for [Use Case]: A Code Snippet

Based on the [design pattern], create a code snippet in [language] that demonstrates its implementation for a [use case].

design pattern code snippet implementation

How to Generate a Language Class for Your Domain Application Easily: Tips and Methods with Properties

Generate a [language] class for a [domain] application that includes methods for [methods list] and properties [properties list].

language class domain application methods list

Creating a Language Function for Data Structure Operations: a Technical Guide

Create a [language] function to perform [operation] on [data structure] with the following inputs: [input variables] and expected output: [output description].

language function data structure programming

What is “prompt engineering”?

A “prompt” is the input that guides a generative AI model to generate useful outputs. Generative AI tools like ChatGPT, GPTs, DALL·E 2, Stable Diffusion, Midjourney, etc. all require prompting as their input.

In a natural language processing (NLP) context, “prompt engineering” is the process of discovering inputs that yield desirable or useful results. As is the story with any processes, better inputs yield better outputs; or commonly said another way “garbage in, garbage out.”

![Source: https://www.youtube.com/watch?v=1NQWJjgi-_k

Designing effective and efficient prompts will increase the likelihood of receiving a response that is both favorable and contextual. With a good prompt, you can spend less time editing content and more time generating it.

Going from beginner → advanced prompt engineer

As companies like PromptBase arise around the idea that the prompt is the “secret sauce” to using generative AI, prompt engineering could easily become the “career of the future.” But, any generative AI user can become an “advanced” prompt engineer. Here’s how

Spend time with the tools

The more time you spend asking ChatGPT questions and receiving responses, the better your idea will be of various prompting approaches and their individual strengths and weaknesses
Use Open AI’s GPT playground to perform interactive trial and error with variations in your prompt, model, temperature and top_p values (uniqueness of answer, i.e. creativity), and more available within the UI itself.

Become a prompt researcher instead of engineer

If you’re already a subject matter expert in something, consider figuring out how to apply your personal skills to generating the best prompts in your field
For example, if you’re an expert in SEO, what questions do you ask yourself when creating SEO strategies? How can you translate this knowledge into better prompts to generate the same level of output with AI?

Become a prompt researcher instead of engineer

The term prompt engineer glosses over the idea that prompt formulation takes hypothesizing, research, result measurement, and repetition. Instead, approach prompting like a research project.
Try as many different variations and formulations of your prompt as possible. One problem can have hundreds of solutions and one solution can have hundreds of approaches. The same can be said of prompting.