Free AI Prompt Library - ChatGPT, Claude, Gemini

Prompt Gemini for Generating Python Code

Gemini, Google's artificial intelligence model, stands out as a powerful tool for generating Python code. With its deep understanding of programming languages and best practices, Gemini can produce functional, documented, and optimized code in seconds. Whether you are a beginner developer looking to learn Python basics or a professional wanting to speed up your workflow, a well-structured prompt makes all the difference between an approximate result and production-ready code. The main challenge lies in the precision of your request: the more you specify the context, technical constraints, expected code style, and edge cases to handle, the more Gemini will be able to generate relevant and robust code. In this guide, we offer optimized prompts that fully leverage Gemini's capabilities for Python code generation, covering different complexity levels and common use cases. You will learn how to formulate your requests to obtain clean, tested code compliant with PEP 8 standards.

Sora Prompt for Generating a Database Schema

Sora, the visual generation model developed by OpenAI, offers interesting possibilities for creating visual representations of database schemas. Instead of working with traditional technical tools like dbdiagram.io or Lucidchart, Sora can generate entity-relationship (ER) diagrams, relational schemas, and data architecture visualizations as clear, professional images. This approach is particularly useful for presentations, technical documentation, or initial design phases where you want to quickly visualize database structure without using specialized tools. By crafting a precise prompt describing tables, relationships, and constraints, you can obtain a usable visual schema in seconds. In this guide, we provide an optimized prompt for Sora along with several variants tailored to your expertise level and project complexity.

Prompt Gemini for Creating a Software Architecture

Designing a solid software architecture is one of the most critical steps in any development project. A poor architecture leads to technical debt, scalability issues, and exploding maintenance costs. Gemini, Google's AI model, excels at structuring complex systems thanks to its ability to simultaneously analyze multiple technical constraints. By providing a well-built prompt, you get a detailed architecture covering technology choices, design patterns, data flows, and deployment strategies. Whether you are starting from scratch or looking to modernize an existing monolith, Gemini helps you explore trade-offs between microservices and monolith, identify potential points of failure, and document your architectural decisions. The tool is particularly useful for architects wanting to validate their intuitions, senior developers upskilling on architecture, and teams needing a structured starting point for their ADRs (Architecture Decision Records). Here is how to formulate your prompts to get the most out of it.

GitHub Copilot Prompt for Generating SQL Queries

GitHub Copilot is radically transforming how developers write SQL queries on a daily basis. Integrated directly into your code editor, this AI assistant understands your project context — table schemas, entity relationships, naming conventions — to generate precise and optimized SQL queries. Whether you work with PostgreSQL, MySQL, SQL Server, or SQLite, Copilot adapts to the specific syntax of your database engine. The challenge is not just to generate functional SQL, but to obtain performant, readable, and maintainable queries. A well-structured prompt enables Copilot to produce complex joins, correlated subqueries, window functions, and aggregation queries that follow best practices. By providing your table schema, expected output, and performance constraints, you get production-ready queries rather than drafts that need reworking. This guide offers an optimized main prompt as well as variants suited to your skill level, to fully leverage Copilot in generating reliable and performant SQL queries.

Perplexity Prompt for Generating Python Code

Perplexity AI stands out from other AI assistants with its unique ability to combine real-time web search and code generation. When it comes to producing Python code, this advantage is significant: Perplexity can rely on the latest official documentation, current best practices, and up-to-date libraries to generate reliable and modern code. Unlike a classic LLM whose knowledge is frozen at a cutoff date, Perplexity verifies its sources in real time, drastically reducing the risk of obsolete code or deprecated functions. Whether you are a developer looking to speed up your workflow, a data scientist wanting to prototype quickly, or a beginner learning Python, a well-structured prompt turns Perplexity into a true development assistant. The key lies in the precision of your request: by specifying the technical context, constraints, and expected output format, you get production-ready code rather than a generic snippet. This guide offers optimized prompts to get the most out of Perplexity in your Python projects.

Mistral Prompt for Generating Python Code

Mistral, the artificial intelligence model developed by the French startup Mistral AI, has established itself as an essential benchmark for code generation. Thanks to its optimized architecture and training on massive corpora of open source code, Mistral excels particularly in producing clean, functional, and well-structured Python code. Whether you are a developer looking to speed up your workflow, a data scientist wanting to automate analysis scripts, or a beginner learning the basics of programming, a well-crafted prompt makes all the difference between an unusable snippet and production-ready code. The key lies in the precision of your instructions: specifying the context, technical constraints, expected code style, and edge cases to handle. In this guide, we offer optimized prompts to get the most out of Mistral for Python code generation, with variants tailored to every skill level and use case, from simple utility scripts to complex software architecture.

Stable Diffusion Prompt for Creating a Prototype

Creating prototypes is a crucial step in the product design process, and Stable Diffusion is revolutionizing this phase by enabling you to quickly visualize concepts without resorting to complex modeling tools. Whether you're an industrial designer, app developer, or entrepreneur, AI image generation gives you the ability to produce realistic visual mockups in just seconds. Stable Diffusion excels particularly in prototype creation thanks to its ability to interpret precise technical descriptions and generate photorealistic or stylized renders according to your needs. By mastering the right prompts, you can explore dozens of design variations, test different color palettes, materials, and shapes, and then present compelling concepts to your clients or investors. This guide provides you with optimized prompts to transform your ideas into professional visual prototypes, from the initial concept to the final presentation-ready render.

Mistral Prompt to Generate a Database Schema

Database schema generation is a fundamental step in any software development project. Mistral, the leading French language model, excels at understanding business needs and translating them into relational or NoSQL data structures. Thanks to its mastery of technical context and its ability to produce precise SQL code, Mistral can transform a functional description into a complete schema including tables, relationships, integrity constraints, and indexes. Whether you are designing an e-commerce application, an internal management system, or a SaaS platform, a well-structured prompt yields a normalized, performant schema ready for deployment. Mistral's advantage lies in its deep understanding of French naming conventions and SQL best practices, making it a valuable ally for French-speaking teams. By providing the business context, main entities, and business rules, you get in seconds a schema that would have required hours of manual modeling.

Stable Diffusion Prompt for Creating E2E Tests

Stable Diffusion, renowned for its image generation capabilities, finds an unexpected yet remarkably effective application in creating end-to-end (E2E) tests. By generating realistic visual mockups of user interfaces, reference screenshots, and test graphic assets, Stable Diffusion enables QA teams to design comprehensive visual test scenarios even before the final interface is developed. This approach significantly accelerates the development cycle by allowing early drafting of visual regression tests. The generated images serve as references for pixel-by-pixel comparison tools like Percy or Applitools, and make it possible to simulate interface states that are difficult to reproduce manually: network errors, missing data, loading states, or interfaces in exotic languages. By combining precise prompts with the capabilities of ControlNet and img2img, testers can produce screen variants covering all edge cases, from mobile responsive to dark mode, ensuring exhaustive test coverage without relying on a functional staging environment.

Perplexity Prompt to Create a REST API

Perplexity AI stands out from other AI assistants by its unique ability to combine real-time web search and code generation. For creating a REST API, this advantage is significant: Perplexity can check the latest framework versions, verify current security best practices, and rely on the most recent official documentation. Unlike a classic LLM whose knowledge is fixed, Perplexity guarantees recommendations aligned with the state of the art. Whether you are building an API with Node.js/Express, Python/FastAPI, or any other stack, a well-structured prompt allows you to obtain a complete architecture, consistent endpoints, robust error handling, and test examples. The challenge is to formulate your request with enough business context and technical constraints so that Perplexity generates production-grade code, not just a tutorial. This guide provides optimized prompts to get the most out of Perplexity in designing professional REST APIs, from beginner to advanced versions.

Sora Prompt for Debugging Code

Sora, OpenAI's video generation model, may seem like a surprising choice for debugging code. Yet its ability to produce dynamic visualizations opens up unique perspectives for understanding and resolving complex bugs. By generating visual representations of execution flow, data structures, or interactions between components, Sora allows developers to literally see their code's behavior. This visual approach is particularly effective for bugs related to user interfaces, animations, state transitions, or rendering issues. Instead of sifting through endless logs, you can ask Sora to create a video illustrating expected versus observed behavior, making problem identification easier. The prompts on this page guide you in using Sora for debugging, turning textual bug descriptions into clear visualizations that accelerate resolution. Whether you're working on front-end, visual algorithms, or complex data flows, these techniques help you adopt a visual debugging approach.

DALL-E Prompt for Building a REST API

DALL-E, OpenAI's image generation model, might seem like a surprising choice when talking about building REST APIs. Yet, API design also involves visualization: architecture diagrams, data flow schemas, endpoint mockups, and visual representations of data models. DALL-E lets you quickly generate conceptual illustrations that improve communication between developers, architects, and non-technical stakeholders. Whether you need a microservices architecture diagram, a visual representation of your REST model, or an infographic explaining the HTTP request-response cycle, DALL-E can produce professional visuals in seconds. These illustrations are especially useful for technical documentation, team presentations, technical blog posts, or training materials. By combining precise prompts describing the components of a REST API — endpoints, HTTP methods, status codes, authentication flows — with a suitable visual style, you obtain clear, aesthetic diagrams that make your technical concepts immediately understandable. This guide helps you write optimized prompts to create REST API architecture visuals with DALL-E.