{"slug": "openai-responses-api-user-migration-split-safety-from-prompt-caching", "title": "OpenAI Responses API `user` Migration: Split Safety from Prompt Caching", "summary": "OpenAI's Responses API migration splits the deprecated `user` field into `safety_identifier` and `prompt_cache_key`, separating end-user safety attribution from prompt-cache routing. A developer demonstrates a .NET implementation that uses HMAC-SHA-256 with a secret pepper for the safety identifier and a structured cache key, ensuring privacy and cache efficiency.", "body_md": "The OpenAI Responses API `user`\n\nmigration is easy to misread as a one-field rename. It is actually a split. The deprecated field mixed end-user safety attribution with prompt-cache routing, while the current request contract provides `safety_identifier`\n\nand `prompt_cache_key`\n\nfor those separate jobs.\n\nI would rather make that distinction explicit in one request builder than scatter it across call sites. The result is easier to review, keeps raw identity out of the payload, and can be verified without sending a model request.\n\n`user`\n\nmigration is a split\nThe [Responses API create reference](https://developers.openai.com/api/reference/cli/resources/responses/methods/create) marks `user`\n\nas deprecated and says it is being replaced by both fields. It describes `safety_identifier`\n\nas a stable end-user identifier used to help detect policy abuse, with a maximum length of 64 characters. It describes `prompt_cache_key`\n\nas a key that helps route requests with similar reusable prefixes.\n\nThose are different lifecycles.\n\nA safety identifier should remain stable for one account across prompts. In this scheme, I change the cache key when the reusable prompt contract changes, and I can share it across users whose requests have the same prefix. Blindly copying the old value into both fields misses the chance to separate the policies; it may still be valid when the old value is privacy-preserving and per-user cache grouping is intentional.\n\nI model the split with two inputs:\n\nThat makes a review question concrete: does this value identify a user, or does it identify reusable prompt structure?\n\nOpenAI's [safety guidance](https://developers.openai.com/api/docs/guides/safety-best-practices) recommends hashing a username or email instead of sending identifying information. In production I prefer an opaque internal account ID when one exists. I also use HMAC-SHA-256 with a secret pepper, rather than an unkeyed hash, so a copied digest is less useful for guessing common identifiers.\n\nHMAC is an application choice here, not an API requirement. The pepper belongs in a secret manager and should be at least 32 random bytes. The committed sample uses an obvious fixed fixture solely to keep its output reproducible.\n\nThe derived value remains a stable, linkable pseudonym—not anonymous—and its privacy depends on protecting the pepper.\n\n``` js\nvar subjectBytes = Encoding.UTF8.GetBytes(subject);\nvar safetyIdentifier = Convert.ToHexString(\n    HMACSHA256.HashData(privacyPepper, subjectBytes))\n    .ToLowerInvariant();\n\nvar promptCacheKey =\n    $\"{cacheGroup.Length}_{cacheGroup}_{cacheVersion.Length}_{cacheVersion}\";\n\nif (promptCacheKey.Length > 64)\n    throw new ArgumentException(\"Prompt cache key is too long.\");\n\nvar request = new\n{\n    model = \"your-model\",\n    input,\n    safety_identifier = safetyIdentifier,\n    prompt_cache_key = promptCacheKey\n};\n```\n\nThe lowercase hexadecimal digest is exactly 64 characters, which fits the documented safety-identifier maximum. The sample also caps the cache key at 64 characters and restricts its components to a conservative ASCII subset. Length prefixes keep pairs such as `a-b`\n\nplus `c`\n\ndistinct from `a`\n\nplus `b-c`\n\n.\n\nThe cache key says nothing about the person. In the sample, `12_support-flow_2_v3`\n\nidentifies one reusable prompt contract; changing the prompt contract to `v4`\n\nchanges the key.\n\nThat separation also makes rotation decisions visible. Rotating the HMAC pepper changes safety identifiers, so a production rollout may need a deliberate overlap plan. In this sample's policy, a deliberate prompt-contract revision advances the cache version even when the identity policy stays unchanged.\n\nThe runnable [sample on main](https://github.com/ssukhpinder/dev-to-code-samples/tree/main/098-openai-user-field-migration) uses only the .NET 10 shared framework. It builds JSON locally and performs fourteen checks, including these invariants:\n\n```\nuser is absent\nsafety_identifier is stable for the same subject\ndifferent subjects produce different identifiers\nraw identity is absent from JSON\nprompt_cache_key is shared across matching prompt contracts\na prompt-version change produces a different cache key\n```\n\nIt also rejects a short pepper before a transport boundary and serializes the same request twice to prove the bytes are identical. The executable makes no OpenAI request and requires no runtime network connection; restore and vulnerability-audit commands may contact configured NuGet sources.\n\nThis is useful because a successful HTTP response would not prove the migration is correct. Both replacement fields are optional. A request can be accepted while omitting the per-user safety signal, the application-supplied cache-routing key, or both. A local contract test catches the omission where the request is assembled.\n\nThe [prompt-caching guide](https://developers.openai.com/api/docs/guides/prompt-caching) adds one important boundary: `prompt_cache_key`\n\ninfluences routing, but it does not pin traffic to a machine or guarantee a cache hit. Prefix content still has to match, and cache eligibility depends on the model and prompt shape. I treat the key as a routing hint, not a response cache or correctness mechanism.\n\nThis sample does not prove that OpenAI accepts a chosen model, that a cache read occurs, or that any safety action will result. Those belong to integration tests and production telemetry. It also does not prescribe one universal cache-key scheme; high-volume applications should tune grouping against real prefix reuse and overflow behavior.\n\nFor anonymous previews, OpenAI's guidance allows a session ID as the safety identifier. For trusted internal batch jobs with no individual end user, forcing a fictional per-user identity would be misleading. I would document that boundary instead of inventing one.\n\nThe practical migration rule is small: remove `user`\n\n, derive `safety_identifier`\n\nfrom a stable privacy-preserving identity policy, derive `prompt_cache_key`\n\nfrom a reusable prompt policy, and test both independently.\n\nWhat deprecated request field are you turning into an explicit contract test next?\n\nHappy coding!", "url": "https://wpnews.pro/news/openai-responses-api-user-migration-split-safety-from-prompt-caching", "canonical_source": "https://dev.to/ssukhpinder/openai-responses-api-user-migration-split-safety-from-prompt-caching-32io", "published_at": "2026-08-30 16:15:42+00:00", "updated_at": "2026-08-30 16:23:30.898211+00:00", "lang": "en", "topics": ["developer-tools", "ai-infrastructure"], "entities": ["OpenAI", "Responses API"], "alternates": {"html": "https://wpnews.pro/news/openai-responses-api-user-migration-split-safety-from-prompt-caching", "markdown": "https://wpnews.pro/news/openai-responses-api-user-migration-split-safety-from-prompt-caching.md", "text": "https://wpnews.pro/news/openai-responses-api-user-migration-split-safety-from-prompt-caching.txt", "jsonld": "https://wpnews.pro/news/openai-responses-api-user-migration-split-safety-from-prompt-caching.jsonld"}}