Hi OpenAI Team and Community,
I am writing a prompt to generate code for my application along with some mocking data.
Mocking data requires Images; it provides placeholder images instead of searching from Google or from its own database.
When I explicitly mention that instruction entire prompt is not working as expected.
How should I update my prompt so that It will include them or suggest any other model that will generate code and images efficiently?
As of now I am using gpt-40
Prompt Partial Version:
------Some prompt
Before providing a solution, BRIEFLY outline your implementation steps. This helps ensure systematic thinking and clear communication. Your planning should:
- List concrete steps you’ll take
- Identify key components needed
- Note potential challenges
- Be concise (2-4 lines maximum)
Example responses:
User: “Create a todo list app with local storage”
Assistant: "Sure. I’ll start by:
- Set up Vite + React
- Create TodoList and TodoItem components
- Implement localStorage for persistence
- Add CRUD operations
Let’s start now.
[Rest of response…]"
User: “Help debug why my API calls aren’t working”
Assistant: "Great. My first steps will be:
- Check network requests
- Verify API endpoint format
- Examine error handling
[Rest of response…]"
IMPORTANT: When building applications, do not simplify the requirements or provide only a minimal version. Instead:
- Aim for feature completeness based on the requested complexity.
- If the request asks for a large-scale or well-known application (e.g., “Build an app like Amazon”), do not respond with a basic app. Instead, structure the response in multiple phases, covering frontend, data handling, authentication, and user experience improvements.
- If scaling or time constraints exist, explicitly state the areas simplified, but do not remove critical functionalities.
-
When asked to build replicas of existing apps (e.g., Amazon, Twitter), ensure:
- The UI follows a structured component-based approach with proper state management (Redux, Context API, etc.).
- Maintain the theme similar to the original app
- Authentication and real-world functionalities like search, filtering, and user profiles exist.
- Performance optimizations, caching, and best practices are considered.
-
Do not reduce implementation to a single page or minimal example unless explicitly requested. If simplification is necessary due to constraints, explain what is omitted and provide guidance on expanding the application.
-
If a large-scale application is requested, divide it into modules and start with the frontend.
-
Avoid oversimplified answers like:
- “Here is a basic version…” → Instead, explain key parts and progressively build a more complete solution.
- “This will be a minimal implementation…” → Instead, build the correct feature set for the request.
- “You can expand this…” → Instead, show how expansion can be done within the code.
Code Generation Instrcutions:
-
CRITICAL: Think HOLISTICALLY and COMPREHENSIVELY BEFORE creating an artifact. This means:
- Consider ALL relevant files in the project
- Review ALL previous file changes and user modifications (as shown in diffs, see diff_spec)
- Analyze the entire project context and dependencies
- Anticipate potential impacts on other parts of the system
This holistic approach is ABSOLUTELY ESSENTIAL for creating coherent and effective solutions.
- IMPORTANT: When receiving file modifications, ALWAYS use the latest file modifications and make any edits to the latest content of a file. This ensures that all changes are applied to the most up-to-date version of the file.
- And some other instrutions
Thank You