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Why admission must happen before inference
A webhook sender normally has a limited acknowledgement window. If your handler waits for an AI completion, that clock now includes network delay, model queueing, token generation, cold starts, and any restart of the host running your application. A timeout can make the sender retry an event that your process may already have labeled. The result is a reliability problem before it is an AI-quality problem.
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The safer question is narrower: Have I durably accepted this provider event? Once the answer is yes, labeling becomes asynchronous work. A database row records the event’s identity and current state; a worker can resume, retry, or report failure without asking the provider to resend the event.
This is an architectural proposal, not a published benchmark. No model name, token quota, machine size, free-access duration, latency result, or production success rate is established. The value is the separation between admission and inference.
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The outbox pattern in one request-to-label flow
| Stage | What happens | Why it matters |
|---|---|---|
| 1. Verify | Check the provider’s shared-secret signature before parsing trusted fields. | Unauthenticated requests never enter the queue. |
| 2. Admit | Insert one row keyed by provider_event_id, including the account, payload hash, and admitted status. |
The database becomes the durable record of acceptance. |
| 3. Acknowledge | Return 202 with the event ID. |
The provider does not wait for model latency. |
| 4. Claim | A worker conditionally changes admitted to running. |
Only one worker owns a row at a time. |
| 5. Label | One client function calls the model and stores a non-empty result, an empty result, or a recorded failure. | Inference is observable and independently retryable. |
| 6. Read | A separate account-scoped endpoint returns status and label. | The UI does not block on webhook delivery. |
Build the webhook admission endpoint
1. Verify the signature first
Use the provider’s documented signing algorithm and shared secret. Reject an invalid signature before deserializing business fields or writing anything. Keep the raw request bytes long enough to verify exactly what the provider signed; re-serializing parsed JSON can change whitespace or key order.
Also enforce the provider’s timestamp or replay window when one is supplied. Signature verification answers “did the secret sign these bytes?”; the unique event ID answers “have I already admitted this event?” You need both.
2. Extract only the admission fields
After verification, retain the provider event ID, account ID, and a cryptographic hash of the raw payload. The hash gives you an audit value without requiring every downstream operation to keep the original body in the outbox row. If later processing needs the complete payload, store it under your applicable retention and privacy rules, or place it in a separate durable store referenced by the row.
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3. Enforce uniqueness in the database
The provider event ID must be a primary key or have a unique constraint. Application-level checks such as “select, then insert” race under concurrent deliveries. Let the database arbitrate the race.
CREATE TABLE webhook_outbox (
provider_event_id TEXT PRIMARY KEY,
account_id TEXT NOT NULL,
payload_hash TEXT NOT NULL,
status TEXT NOT NULL CHECK (status IN ('admitted','running','labeled','empty','failed')),
label_text TEXT,
claimed_at TIMESTAMP,
failure_reason TEXT,
created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
);
The essential columns are provider_event_id, account_id, payload_hash, status, label_text, and claimed_at. A failure field and timestamps make operations easier to inspect, but they do not replace the uniqueness constraint.
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4. Insert and acknowledge in one transaction
Wrap the insert in a short database transaction. On a new ID, insert admitted and commit. On a unique-key conflict, treat the delivery as an already-admitted replay. In either case, return 202 and the event ID; never invoke the model on the conflict path.
verify_signature(raw_body, signature, shared_secret)
event = parse_event(raw_body)
event_id = event['id']
account_id = event['account_id']
payload_hash = sha256(raw_body)
try:
db.execute(
'INSERT INTO webhook_outbox '
'(provider_event_id, account_id, payload_hash, status) '
"VALUES (?, ?, ?, 'admitted')",
(event_id, account_id, payload_hash)
)
db.commit()
except UniqueViolation:
db.rollback() # replay: the existing row remains authoritative
return json_response({'event_id': event_id}, status=202)
The pseudocode is a design outline, not a claim that this exact implementation has run successfully in production. Adapt transaction handling and exception names to your database driver. Do not acknowledge before the insert commits: a process that returns 202 and then loses the row has falsely admitted the event.
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Claim rows conditionally
The worker should claim work with a conditional update that includes the current status. This prevents two workers from both seeing admitted and both calling the model.
UPDATE webhook_outbox
SET status = 'running', claimed_at = CURRENT_TIMESTAMP, updated_at = CURRENT_TIMESTAMP
WHERE provider_event_id = ? AND status = 'admitted';
Check the affected-row count. A count of one means this worker owns the event; zero means another worker claimed it or the row is already terminal. Fetch the payload needed for inference only after a successful claim.
Keep model access behind one client function
Use one function as the boundary to the free model. It should accept the event data, apply the prompt or labeling rules, enforce a timeout, and return either text or a typed error. Centralizing this call lets you change providers, add logging, or introduce a paid fallback without rewriting admission logic.
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Persist one of three outcomes:
labeled: the completion contains non-empty label text; store it inlabel_text.empty: the call completes but returns blank or whitespace-only text; leavelabel_textempty and record the terminal status explicitly.failed: a timeout or other recorded error prevents a usable completion; retain a safe failure reason for operations.
Do not mark a row labeled merely because the HTTP request to the model succeeded. The completion must contain usable text according to your application’s validation rules.
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A restart after the claim can leave a row in running. Add a lease policy: consider a running row reclaimable when its claimed_at is older than your maximum model timeout plus a safety margin. A recovery pass can move stale claims back to admitted or directly to a retry state, while preserving an attempt count and last failure reason. Without a lease, one crashed worker can strand work indefinitely.
Retry only failures that are plausibly transient, such as a timeout or temporary upstream error. An invalid payload or deterministic validation failure should become a terminal failure requiring inspection rather than an endless loop. Back off between attempts so a provider outage does not create a request storm.
Let the UI poll a read endpoint
The browser should not wait for the webhook response to obtain a label. After your application knows the event ID, it can request an account-scoped status endpoint such as GET /accounts/{account_id}/events/{provider_event_id}. Return the status and label only when the authenticated caller owns the matching account.
A typical response shape is:
{
"event_id": "evt_123",
"status": "running",
"label": null
}
Return label when the status is labeled; otherwise return null or omit it according to your API convention. For empty and failed, expose a user-safe explanation and keep diagnostic details restricted to operators. Account filtering is mandatory: knowing an event ID must not allow a caller to read another account’s label.
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Inline inference versus an outbox worker
| Decision axis | Inline model call | Admission plus worker |
|---|---|---|
| Acknowledgement latency | Includes model network and generation time; a timeout can trigger provider retries. | Limited to signature verification and the database commit before 202. |
| Duplicate safety | Requires careful idempotency around a call that may already have completed when the request timed out. | Unique event ID blocks replay admission; the worker claims one row conditionally. |
| Restart recovery | A process restart can lose in-flight context or leave the sender uncertain whether work ran. | Committed rows survive a restart; stale claims can be leased and retried. |
| Intermediate visibility | Usually hidden until the request finishes or fails. | admitted, running, labeled, empty, and failed are queryable states. |
| Retry control | Often coupled to provider retry behavior. | Worker policy can back off, cap attempts, and distinguish transient from permanent errors. |
The outbox is the better default when the sender’s timeout clock must not be coupled to model latency. Inline inference can still be reasonable for a tightly bounded internal call where the caller genuinely needs the answer before proceeding and duplicate handling is already transactional.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Test the dangerous cases, not just the happy path
A green process is not evidence that admission is correct. Test the database state and client-call count under the cases most likely to expose a race.
- Fresh admission: send a valid signed event with a new ID. Assert one row, the correct account and payload hash, status
admitted, and an HTTP202. - Duplicate delivery: submit the identical event twice. Assert two successful acknowledgements, one stored row, and no second model call. The second request must follow the unique-conflict path.
- Empty completion: have the model client return an empty string. Assert status
empty, no fabricated label, and a recorded completion outcome. - Crash after claim: force the worker to stop after changing
admittedtorunning. Restart it, verify that the lease or recovery pass makes the row eligible again, and assert that only one worker owns it at any instant. - Invalid signature: alter the body or signature and assert a rejection with no outbox row.
- Account isolation: request a valid event ID under a different account and assert that the read endpoint does not disclose status or label.
Run these checks against the same migration and startup configuration used by deployment. The proposed examples are suggested checks, not reported execution results.
Operational setup and observability
Package the webhook server and worker in the same deployed image so they share code, migrations, and configuration, while running as separate processes or service commands. Apply the outbox migration before accepting traffic. Start the HTTP server and worker independently, and make worker concurrency explicit.
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- number of rows in each status;
- age of the oldest
admittedrow; - age and count of
runningrows; - model timeout and failure totals;
- duplicate-delivery count;
- worker claim conflicts and recovery events.
A healthy process does not prove that events are being admitted or drained. Alert on an increasing backlog, stale claims, and repeated failures.
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When this pattern is the wrong tool
Choose a synchronous design when a person must receive a model answer before the next interaction can occur and the end-to-end deadline is under your control. Even then, retain an idempotency key if the surrounding request can be retried.
The single-row outbox is also a poor fit when several models must fan out and merge inside one atomic transaction. That workflow needs an explicit job graph, coordination state, and a definition of what partial completion means.
Finally, do not store a payload hash beside an account ID on a shared host if your compliance rules prohibit that association. Use an approved isolated store, tokenize the account reference, or redesign retention. Reliability does not override data-governance requirements.
What the evidence does—and does not—show
This approach is presented as an opinion and implementation proposal rather than a captured production trace or benchmark. It does not establish that a free model is faster, cheaper, or more accurate than a paid model, nor that any particular free server remains available for a specified period. Treat model quotas, access terms, hardware limits, and vendor availability as changeable; verify current terms before deployment.
The durable claim is narrower and more useful: inserting a unique event row before inference gives retries, restarts, workers, and user interfaces a shared state machine. That state machine is what prevents duplicate AI labels and makes recovery testable.
Quick Recap
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