This is a lot to hold in your head at once.
Start by clarifying requirements and constraints, then outline the component architecture and state management. Focus on the streaming implementation using fetch with ReadableStream and incremental rendering, while addressing performance and edge cases.
Pro tip: Demonstrate awareness of real-world challenges like handling stream interruptions, optimizing re-renders with memoization, and ensuring accessibility. Mention that you'd use a library like react-markdown for rendering formatted responses, but keep the core logic custom.
Ask about expected message volume, streaming protocol (e.g., SSE, WebSockets), and whether markdown or code highlighting is needed. Confirm browser support and performance targets.
Break down into components: MessageList, MessageItem, ChatInput, and a custom hook (e.g., useChat) for state and streaming logic. Decide on state management (useState/useReducer vs. external store).
Use fetch with ReadableStream to read chunks, decode them, and update the assistant message incrementally. Manage loading state and handle errors/aborts with AbortController.
Memoize message components to prevent unnecessary re-renders. Auto-scroll to the latest message, disable input while loading, and support enter-to-send with shift+enter for new line.
Discuss handling stream interruptions, retries, and message ordering. Consider trade-offs between simplicity and features like markdown rendering or virtualized lists.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
I said disable the input and button while a request is in flight.
Start by clarifying the requirements and constraints, then propose a client-side state management solution that disables or debounces input during streaming, and finally discuss server-side safeguards like idempotency keys. Emphasize trade-offs between responsiveness and preventing duplicate requests, and how you would test and monitor the solution.
Pro tip: Mention that you would use an AbortController to cancel in-flight requests when a new one is triggered, and highlight the importance of idempotency keys to handle retries safely. This shows you understand both frontend and backend concerns.
Ask about the expected user experience, latency requirements, and whether the backend supports cancellation or idempotency. This ensures your solution aligns with product goals and technical capabilities.
Propose disabling the send button or debouncing rapid clicks while a request is in flight. Consider using a loading state and optimistic UI to keep the interface responsive.
Use AbortController to cancel previous requests when a new one is initiated, and generate unique request IDs to deduplicate on the server. This prevents race conditions and wasted resources.
Implement idempotency keys or request deduplication on the backend to handle retries and duplicate submissions. Ensure the server can gracefully handle concurrent requests and return consistent responses.
Describe how you would test edge cases (e.g., rapid clicks, network delays) and monitor for duplicate requests or errors in production. Use metrics and logging to validate the solution.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Classic useEffect cleanup question dressed up in a real scenario.
Start by explaining the need to abort the underlying network request using an AbortController, and then show how to tie that abort to the component's unmount lifecycle. Emphasize that simply ignoring the response is not enough—you must actively cancel to free resources and prevent state updates on unmounted components.
Pro tip: Mention that you also need to handle the case where the stream has already completed or errored before unmount, and that you should avoid setting state after abort by checking a flag or using the abort signal's reason.
Clarify whether you're using fetch with ReadableStream, EventSource, WebSocket, or a library like Axios. Each has different cancellation APIs.
Instantiate an AbortController when the request starts and pass its signal to the fetch or streaming call. Store the controller in a ref or variable accessible in cleanup.
Return a cleanup function from useEffect that calls controller.abort(). This runs on unmount and before re-running the effect.
In the catch block, check if the error is an AbortError and ignore it. Also ensure no state updates occur after abort by using a flag or checking signal.aborted.
For EventSource, call close(); for WebSocket, call close(); for libraries, use their cancellation tokens. Mention that some streaming APIs require manual reader.cancel().
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
I set a status field on the message (something like 'error') and rendered a retry button inline in the message bubble.
Start by outlining a layered error handling strategy: detect and classify the failure (network, server, rate limit), then update the UI to show a clear, non-blocking error state with a retry option. Emphasize graceful degradation, user control, and preserving conversation context so retries feel seamless.
Pro tip: Mention idempotency and exponential backoff with jitter for retries, and note that you'd avoid auto-retrying non-idempotent requests without user consent. This shows you understand both UX and backend reliability concerns.
Identify the failure type (network timeout, 4xx, 5xx, rate limit) and determine whether it's transient or permanent. This informs whether a retry is appropriate and what message to show.
Display a non-intrusive error message near the failed message, preserving the user's input and conversation history. Avoid blocking the entire chat or losing context.
Provide a visible 'Retry' button or action on the failed message. For transient errors, optionally auto-retry with exponential backoff and jitter, but always allow manual retry.
Ensure retries are safe by using idempotency keys or deduplication. For non-idempotent operations, require explicit user action and show a confirmation if needed.
Show loading indicators during retry, and if retries fail repeatedly, offer alternative actions like editing the message, copying it, or contacting support.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.