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Do not retry every failed decision-model call. First classify the failure from the HTTP status, structured error fields, SDK exception, and stream state. Then validate any response before your application acts on it, retry only transient failures within a finite attempt and time budget, and return an explicit, risk-appropriate fallback when the service remains unavailable.
A timeout can leave completion uncertain, a HTTP 200 stream can still contain an error event, and syntactically valid model output can still violate business rules. Reliable integrations treat transport, provider, parsing, schema, semantic, and policy failures as separate states.
Build the failure path around classification, not repetition
A decision-model API is part of a larger decision system. Its answer may authorize an action, select a workflow, assign a risk tier, or decline a request. The integration therefore has two responsibilities: recover from failures that are likely to clear, and prevent an invalid or unknown result from being mistaken for a valid decision.
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At the adapter boundary, convert every provider response and SDK exception into an internal error record. Do not make business code parse provider-specific message strings. OpenAI’s guidance recommends using structured error fields, tolerating unknown codes and missing fields; Anthropic SDKs expose typed failures and request IDs. Provider taxonomies differ, so keep the original fields as well as your normalized category.
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| Failure class | Typical signals | Default response | Do not do this |
|---|---|---|---|
| Rate limit or temporary overload | HTTP 429, a provider rate-limit code, or a typed throttling exception | Honor Retry-After when supplied, back off with jitter, and retry within the operation budget |
Retry immediately in a tight loop |
| Temporary service failure | HTTP 5xx, provider temporary-service code, or a typed server exception | Use bounded exponential backoff and stop at the deadline | Assume every 5xx is safe to repeat when the call has side effects |
| Timeout or connection interruption | Client deadline, socket reset, DNS/TLS failure, or a stream that ends unexpectedly | Determine whether work completed; replay only when safe or deduplicated | Assume the server did nothing |
| Malformed request or validation error | HTTP 400-class response or a typed invalid-parameter exception | Correct the request, schema, encoding, or configuration before trying again | Send the identical request repeatedly |
| Authentication or permission failure | HTTP 401/403 or an authentication/authorization exception | Repair credentials, project configuration, scope, or access policy | Spend the retry budget on unchanged credentials |
| Unavailable model or resource | Provider says the selected model, deployment, region, or resource is unavailable | Apply an explicitly approved alternate route or fail safely | Silently switch to an unapproved model with different behavior |
| Malformed, refused, incomplete, or semantically invalid output | Parse error, missing field, refusal state, incomplete status, invalid enum, or failed domain check | Discard the result and follow the output-failure policy | Use the partial or plausible-looking answer |
Keep a provider’s structured code or type even when it is unknown to your current SDK. Future codes can appear, fields can be absent, and message wording can change. A normalized record should preserve enough information for logging and later classification without exposing secrets to callers.
Normalize provider errors at one adapter boundary
Put provider-specific handling in a small adapter rather than scattering it through controllers, queues, and business rules. The adapter should return either a validated decision object or a typed failure object. A useful internal record contains:
- Provider name, endpoint, model or deployment identifier, and SDK version.
- HTTP status when one exists.
- Structured provider code and error type, retained verbatim even if your mapper labels it
unknown. Retry-Afterduration or date when supplied.- Provider request ID or trace ID when available.
- Timeout, connection, DNS, TLS, protocol, or stream classification.
- Whether a response body arrived, whether a stream began, and whether an error event appeared after output started.
- Whether the request may have been submitted to the service and whether completion is therefore uncertain.
- A safe, user-facing summary separate from internal diagnostic details.
InternalFailure {
category: transient | permanent | uncertain_completion | invalid_output | unavailable,
provider: string,
endpoint: string,
model: string,
http_status: integer | null,
provider_code: string | null,
provider_type: string | null,
retry_after: duration | null,
request_id: string | null,
phase: connect | request | response | stream | parse | validate,
response_started: boolean,
completion_state: unknown | completed | not_completed,
retryable: boolean,
detail_for_logs: string
}Classify from status, structured fields, and the SDK’s typed exception together. No single signal is sufficient: a status may be generic, an SDK may wrap the provider code, and a stream can report a failure after an initially successful HTTP response.
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Transport success is not decision success. Validation should be an explicit pipeline, with each failed layer producing its own metric and control-flow outcome.
1. Check transport and response status
Reject non-success statuses unless the adapter has a documented recovery path. Confirm that the response belongs to the expected request and provider endpoint. For streaming, do not equate HTTP 200 with a valid answer. Anthropic documents server-sent-event errors that can occur after HTTP 200; the consumer must recognize the error event and discard or mark any partial output.
2. Parse the complete payload
Parse only after the body or stream has reached a valid terminal state. A truncated JSON document, a stream closed between tokens, invalid encoding, or an absent terminal event is an incomplete result, not a low-confidence answer. Preserve the raw provider request ID and a bounded diagnostic excerpt, but avoid logging full prompts, credentials, or sensitive decision data.
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3. Enforce the expected shape
Require the expected top-level object, answer count, answer names, required fields, and data types. If the provider supports schema-constrained output, use it to reduce format drift. OpenAI’s Decisions documentation describes typed predicate, choice, and score answers and possible refusal outcomes; its Responses interface includes JSON Schema formatting and explicit failed and incomplete statuses. Those features improve structure but do not enforce every application rule.
4. Apply domain and policy checks
Check allowed enum values, numeric ranges, units, mutually exclusive fields, required evidence, and domain thresholds. A schema can require a number, but your application still has to decide whether that number is within an acceptable range and whether the combination of fields makes sense. Treat a refusal as a refusal, not as an empty answer to be filled with a default. Treat incomplete output as incomplete even when the fields received so far look plausible.
| Validation layer | Example failure | Result state |
|---|---|---|
| Transport | Non-success status or stream error event | provider_failure |
| Syntax | Invalid or truncated JSON | parse_failure |
| Shape | Missing answer object or wrong answer count | schema_failure |
| Provider state | Refusal, failed, or incomplete |
non_decision_state |
| Semantics | Unknown enum, impossible combination, or out-of-range score | domain_validation_failure |
Set two time budgets before adding retries
Use a per-attempt timeout and an overall operation deadline. The per-attempt limit bounds one network call; the overall deadline includes connection time, response time, queue waits, backoff, and every retry. Select values from the caller’s latency budget and workload. There is no universally correct timeout number established by the provider documentation.
Use a monotonic clock for deadline calculations so a wall-clock adjustment cannot extend a request. Pass the remaining time to each attempt and stop before starting another attempt if the remaining budget cannot accommodate it.
deadline = monotonic_now() + operation_budget
attempt = 0
while attempt < max_attempts and monotonic_now() < deadline:
remaining = deadline - monotonic_now()
result = call_provider(timeout=min(per_attempt_limit, remaining))
if result.is_valid_decision:
return result
failure = normalize(result)
if not failure.retryable:
return failure
if failure.completion_state == "unknown" and not replay_is_safe(request):
return failure_as_indeterminate(failure)
delay = provider_retry_after(failure) or exponential_backoff_with_jitter(attempt)
if monotonic_now() + delay >= deadline:
break
sleep(delay)
attempt += 1
return unavailable_or_indeterminate()A retry count alone is not enough. Two attempts can consume milliseconds for one endpoint and minutes for another. Record both the attempt limit and deadline in configuration, and make them visible in telemetry.
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Rate limits, temporary service errors, overload, and some network timeouts may clear without a request change. Retry them only while both the attempt count and overall deadline remain. Exponential backoff with jitter prevents many clients from retrying at the same instant. The exact base, multiplier, cap, and randomization range should come from your latency and load objectives rather than an invented universal value.
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Honor Retry-After when the provider supplies it, subject to your own maximum deadline. OpenAI’s error guidance calls out Retry-After and gradual request-rate reduction. Anthropic’s SDK documentation describes retries for selected transient failures, exponential backoff, and honoring retry-after; it documents two SDK retries by default. Verify the behavior of the exact SDK version you deploy.
Layered retries are a common outage amplifier. If an SDK retries twice, an HTTP client retries three times, and a queue retries five times, one user operation can produce many provider calls. Decide which layer owns retries, or calculate a deliberately small combined budget. Record the effective attempt number so operators can see the real load.
Stop immediately for permanent causes
Do not automatically retry malformed requests, invalid credentials, permission failures, unsupported parameters, or an unavailable model or resource. Correct the input or configuration first. A retry may be appropriate after the correction, but repeating the unchanged request cannot repair a permanent cause. An SDK’s generic “retryable” flag is a hint, not a substitute for your policy.
Use jitter and cancellation correctly
When a caller cancels, propagate cancellation through the sleep and network operation; do not continue hidden retries. Cap backoff at the remaining deadline, and avoid sleeping longer than a provider’s retry-after instruction unless your service policy requires a later retry. For high-volume systems, combine per-operation backoff with a concurrency limit or circuit breaker so an outage does not exhaust worker pools.
Resolve uncertain completion before replaying a request
A timeout or connection reset reports what the client observed, not necessarily what the server did. The request may have completed just before the connection failed. Before replaying, check a provider operation, session, turn, job, or result endpoint when available. OpenAI’s recovery guidance explicitly recommends checking saved or completed work before retrying.
For a pure classification call, duplicate computation may mainly add cost and latency. For a call that triggers an email, payment, account change, moderation action, or workflow transition, a duplicate can create real harm. Use a provider-supported idempotency key where available, or store an application-side operation ID and deduplicate downstream effects. Make the idempotency record durable enough to survive worker restarts.
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- Known completed: retrieve and validate the stored result; do not issue the action again.
- Known not completed: replay only if the request is safe and still within its deadline.
- Unknown: return an indeterminate state or route to review unless your deduplication mechanism makes replay safe.
Document the uncertainty in the API contract. A caller should be able to distinguish “the model chose no” from “the model outcome is unknown.”
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Never convert an output-validation failure into a confident business decision. Return a typed failure that identifies whether parsing, schema, provider state, or domain validation failed. This distinction matters for remediation: a parser defect is different from a provider refusal, and a valid schema with an impossible score is different from a network outage.
When a refusal or incomplete state is retriable, retry only under a documented policy. For example, a transient provider failure around an otherwise valid request may be retried, while a policy refusal may require a different workflow or human review. Do not keep retrying a refusal simply because the requested field is absent.
Persist validation metrics separately from transport metrics. Track the endpoint and model version, validation layer, answer type, and provider request ID. This reveals regressions such as a model deployment that remains available but starts producing more incomplete or semantically invalid decisions.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Choose the fallback before an outage
After the retry and deadline budget is exhausted, return a typed unavailable or indeterminate outcome. The fallback is an application risk decision, not a provider default. Select it according to the consequence of a wrong answer.
| Decision consequence | Suitable fallback pattern | Required safeguards |
|---|---|---|
| A wrong approval could cause material loss or harm | Explicit failure or human review | Show the reason, preserve context, and prevent automatic execution |
| A conservative denial is safer than an accidental approval | Safe default that blocks or defers the action | Make the default visible and provide a retry or appeal path |
| The policy can be expressed deterministically | Versioned deterministic rule | Log that the rule, not the model, made the decision |
| Delay is acceptable but a final answer is needed | Queue for later processing | Use an idempotent operation ID and communicate pending status |
| Neither default nor automation is acceptable | Explicit failure | Return a stable error type; never fabricate a model answer |
Do not silently substitute an unapproved model, region, or prompt. An alternate route changes behavior and may require separate validation, privacy review, cost controls, and approval. If failover is part of the design, encode the allowed alternatives and their order explicitly.
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Streaming requires its own error state machine
Streaming clients must handle more than connect versus disconnect. A robust consumer tracks states such as connecting, receiving, completed, provider-error-event, transport-ended, and cancelled. If an error event arrives after partial tokens, discard or quarantine the partial output. Do not parse a prefix as a decision merely because it contains a complete-looking field.
Require the provider’s terminal success signal before validation. If the stream ends without that signal, classify the result as incomplete. If a retry follows, apply the same uncertain-completion and idempotency rules as for a non-streaming request.
Compare deployed provider and SDK behavior explicitly
Provider documentation is endpoint- and version-specific. Before adopting a retry or validation assumption, compare the exact versions in production on these axes:
| Axis | Questions to answer |
|---|---|
| Timeouts | Does the setting cover connection, first byte, each read, the whole attempt, or the entire operation? |
| Built-in retries | How many retries occur by default, and which statuses or exception types qualify? |
| Retry timing | Is exponential backoff used, is jitter included, and is Retry-After honored? |
| Error data | Are structured codes, typed exceptions, and request IDs available in every failure path? |
| Streaming | Can an error arrive after HTTP 200, and what terminal event proves success? |
| Output states | How are refusal, failed, incomplete, and partial results represented? |
| Constrained output | Does the endpoint support JSON Schema or another structured format, and what does it not enforce? |
| Replay guarantees | Are idempotency keys, operation lookup, or completed-work inspection supported? |
OpenAI and Anthropic documentation provide useful examples of these behaviors, but neither provider’s defaults should be treated as universal. Pin SDK versions where practical, review changes during upgrades, and test the behavior rather than relying on a generic HTTP status table.
Instrument the path without leaking sensitive data
For every operation, record a correlation ID, provider request ID when available, endpoint and model version, start and end timestamps, attempt count, backoff duration, final category, and validation result. Add whether a response or stream began and whether completion was known, unknown, or confirmed. These fields let you distinguish provider latency from local queueing and malformed output from transport failure.
Do not log API keys, authorization headers, full prompts, personal data, or complete decision payloads by default. If debugging requires payload samples, redact them, restrict access, apply retention limits, and record the redaction policy. Keep user-facing messages concise while retaining detailed diagnostics for operators.
Test every branch with controlled failures
Use fakes, a local proxy, or provider-supported test mechanisms to exercise the failure state machine. Tests should assert both the returned outcome and the number and timing of provider calls.
- Connection timeout before request submission.
- Timeout after submission with completion known and unknown.
- Connection reset after a response or stream begins.
- Rate-limit response with and without
Retry-After. - Temporary server error followed by recovery.
- Malformed request, invalid credential, permission failure, and unavailable model.
- Invalid JSON, missing fields, wrong answer count, unknown enum, and out-of-range score.
- Provider refusal and explicit incomplete or failed status.
- Server-sent-event error after HTTP 200 and stream termination without a success event.
- Caller cancellation during network I/O and during backoff.
- Duplicate delivery of the same operation ID to verify idempotency.
Verify that permanent errors make no extra attempts, transient errors stop at the deadline, retry-after values are respected, and uncertain side-effecting operations do not replay without deduplication. Include contract tests for each SDK upgrade so a changed default retry policy cannot silently multiply traffic.
Quick Recap
Reference implementation checklist
- Define the internal success, invalid-output, transient, permanent, unavailable, and indeterminate result types.
- Normalize HTTP responses and SDK exceptions at the adapter boundary while preserving structured provider fields.
- Set a per-attempt timeout and an overall deadline from the caller’s latency budget.
- Validate status, stream terminal state, parseability, schema, provider state, and domain constraints before application use.
- Retry only classified transient failures, with bounded exponential backoff, jitter, and
Retry-Afterhandling. - Account for retries already performed by the SDK or HTTP client.
- Check completed work after uncertain completion and use idempotency or deduplication for side effects.
- Return an explicit unavailable or indeterminate outcome when the budget ends.
- Apply the preapproved safe default, deterministic rule, queue, human review, or explicit failure for that risk class.
- Instrument request IDs, attempts, latency, validation failures, and final outcomes without logging secrets.
- Exercise every branch with controlled tests before production rollout.
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