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How to Build Safe LLM Invoice Extraction in Node.js with Idempotency and Observability

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Developers building Node.js pipelines for LLM-based supplier invoice extraction must distinguish between three separate identities: the business operation, the queue delivery, and the execution attempt. Collapsing these into one can cause duplicate records or hide retry costs, since a worker may complete a model call and write a database row before losing its broker acknowledgement, triggering a repeat run. The recommended approach enforces idempotency at the database write boundary using a tenant-scoped operation ID that persists across the webhook, worker queue, and JSON extraction pipeline. Structured logs should capture identifiers and state transitions rather than raw invoice content, as invoices often contain sensitive personal and financial data that increases exposure risk if logged in full. Tenant-level metrics, correlated logs, and distributed traces together diagnose duplication, but only a unique database constraint can reliably prevent it.

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