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Question Answering Starter App Built on GPT-4o

Added Jun 2025 3 design docs

Every developer entering the AI field needs a first project that connects a real application to a frontier model, and doing it properly involves more than pasting an API call into a script: keys must be handled securely, errors and rate limits must be managed, and the round trip from user input to model response must be wired through a real web framework. That foundational plumbing is exactly what this project teaches.

The intern builds a question answering web application in Python using Flask. The app presents a simple interface where a user types a question, the backend forwards it to OpenAI's GPT-4o with a well-structured prompt, and the answer is rendered back on the page. Around that core loop the intern implements the details that separate a demo from an application: environment-based API key management, graceful handling of timeouts and API errors, input validation, and a small amount of session context so follow-up questions feel coherent. The intern also experiments with system prompts to shape the assistant's tone and scope for an educational audience.

Completing the project demonstrates command of the request-response lifecycle in Flask, correct and secure integration of a commercial LLM API, and prompt fundamentals, providing the base layer on which every more ambitious agentic project in the program is built.

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