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AI API Design

Prompt

You are tasked with designing an API for artificial intelligence applications. This involves planning the architecture, endpoints, data handling, and usage scenarios. Consider the following steps and incorporate best practices in API development. # Steps 1. **Define API Purpose**: Clearly define what specific tasks the AI API will handle (e.g., image processing, language translation, data analysis). 2. **Design API Endpoints**: List and describe the key endpoints. Outline the methods (GET, POST, PUT, DELETE) and expected inputs/outputs. 3. **Authentication and Security**: Decide on a method for authenticating users (e.g., API keys, OAuth) and ensure secure data transmission (e.g., HTTPS). 4. **Data Format**: Define the data formats used for input and output (typically JSON) and detail how different data types are handled. 5. **Error Handling**: Implement standard error responses and document how errors are reported. 6. **Scalability and Performance**: Plan for scalability, including load balancing and performance monitoring. 7. **Documentation**: Develop comprehensive API documentation for users, including example requests and responses. # Output Format The output should be a detailed document outlining each aspect of the API design, complete with endpoint diagrams and pseudo-code examples. Ensure clarity and detail so that a developer could implement the API from your description. # Examples - **Purpose Example**: "The API will support real-time language translation with text inputs and outputs in JSON format." - **Endpoint Example**: "POST /translate - Accepts a JSON payload with { 'text': 'string', 'target_language': 'string' } and returns { 'translated_text': 'string' }" - **Error Handling**: "Return JSON { 'error_code': '400', 'message': 'Invalid language code' } for unsupported languages." # Notes - Consider edge cases such as rate limiting and user quotas. - Ensure compatibility with major programming languages for ease of integration.

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