Test your understanding of caching basics for generated responses, including cache keys, time-to-live (TTL), cache invalidation, and the differences between client-side and server-side caching. This easy-level quiz is designed to reinforce core caching concepts with practical questions and real-world scenarios.
Which three key elements are commonly combined to form a unique cache key for storing generated responses?
Explanation: Prompt, parameters, and model version are typically used together to generate a unique cache key, ensuring responses are correctly matched to specific requests. Server name, client ID, and timestamp are unrelated to the content of generated responses for most caching scenarios. Prompt with user location and data format could be relevant in specific use cases but is not a general standard. Prompt, file size, and network speed are not directly related to uniquely identifying cached responses.
What does the TTL (Time To Live) setting in a cache control?
Explanation: TTL specifies how long a cached response should be considered fresh before being removed or replaced. It does not set the storage quota—that is a function of cache capacity. TTL doesn't affect how many users can access the cache, nor does it determine the size of responses.
If two requests share the same prompt but have different parameters, why should their cache keys differ?
Explanation: Even with the same prompt, different parameters (like length or temperature) can lead to unique generated outputs, so cache keys must differ. Saving memory space does not directly relate to changing cache keys. Network routing errors are unrelated to caching logic, and increasing computation time is not a direct result of differing cache keys.
Which cache type stores generated responses on the user's device for faster repeated access?
Explanation: Client-side caching means storing responses locally on the user's device, reducing load times for repeated requests. Server-side caching keeps responses on the server, not on the user device. Database caching refers to optimizing database queries, and proxy caching involves an intermediate system, but not directly the end user's device.
What is cache invalidation in the context of caching generated responses?
Explanation: Cache invalidation is the process of removing entries that are no longer valid, ensuring users receive up-to-date results. Creating new entries isn't invalidation; that's caching. Increasing TTL extends validity rather than removing outdated data. Encrypting cached data is a security measure, not invalidation.
If a cache entry has a TTL of 5 minutes but is accessed after 10 minutes, what usually happens?
Explanation: When the TTL is exceeded, the cache treats the entry as expired and will typically generate a new response. Returning an expired entry defeats the purpose of TTL. TTL doesn't automatically extend unless specifically configured. Deleting all cache entries due to one expiry is unnecessary and incorrect.
If the same parameters and model version are used but the prompt text slightly changes, what should happen with the cache key?
Explanation: Even small changes to the prompt mean the generated response will likely differ, so a completely new cache key is needed. Reusing the key would cause mismatches. Increasing TTL does not address prompt changes. Bypassing the cache is unnecessary—valid caching can still occur with a new key.
What is a likely effect of reducing the TTL for cached generated responses from 10 minutes to 1 minute?
Explanation: A shorter TTL means cached entries expire faster, leading to fewer cache hits and more new computations. Accuracy can improve, but memory use often declines with shorter TTLs. Network speed isn't directly affected by TTL. Changing TTL doesn't mean cache keys themselves change.
If consistent responses are needed across multiple users, which caching strategy is preferable?
Explanation: Server-side caching allows all users to benefit from the same cached responses, ensuring consistency. Client-side caches are limited to individual users. Browser local storage is a kind of client-side caching, so it's also user-specific. Direct database caching optimizes database queries, not generated response sharing.
Why is it important to include the model version in the cache key when storing generated responses?
Explanation: Updates to the underlying model can change response behavior, so the cache key needs to reflect the version used. Storage cost does not hinge on including the model version. User interface colors are unrelated. Model upgrades do not by themselves empty the whole cache; isolation is achieved through cache key versioning.
A user complains of getting outdated information repeatedly even after an update. What cache problem is likely occurring?
Explanation: If users receive outdated data, it usually means invalidation policies have failed and old entries weren't removed. Storage space issues might cause missed cache hits, but not persistent outdated data. Prompt generality is not directly linked to stale caches. Device type does not control cache freshness.
When a cache reaches its storage limit, what often happens to make room for new responses?
Explanation: Many cache systems use a least recently used (LRU) strategy to delete the oldest unused entries for space. Duplicating entries wastes space. Setting TTL to zero expires all items, not just the oldest. Caching only new responses without removing old ones doesn't free memory.
When a parameter like 'max_length' changes from 50 to 100 for the same prompt, what should a correct caching system do?
Explanation: Changing relevant parameters such as 'max_length' alters the output, so each unique parameter set deserves its own cache entry. Overwriting would lose previous results. Ignoring the parameter risks delivering incorrect outputs. Unlimited TTL is unrelated to parameter changes.
If two different requests accidentally share the same cache key, which issue is most likely to happen?
Explanation: Cache key collisions cause different requests to return the same, potentially incorrect, cached result. Increased memory isn't direct; in fact, it may reduce unique entries. Server processing time isn't necessarily affected by key reuse. Encryption isn't linked to cache key issues.
Which of the following actions bypasses cached responses and always generates a fresh response?
Explanation: Disabling caching forces a new response regardless of cache content. A long TTL keeps responses cached longer, not bypasses. Increasing cache size lets you store more entries. Reusing the same key uses whatever is in the cache, not a fresh computation.
When the data used to generate responses changes significantly, what should a cache system ideally do?
Explanation: To maintain accurate and up-to-date answers, affected cache entries should be invalidated when data changes. Just reducing TTL on unrelated items doesn't address accuracy. Changing from client- to server-side caching is more about architecture, not timely accuracy. Serving outdated entries risks delivering incorrect responses.