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TL;DR: Put an OpenAI-compatible Chat Completions boundary in front of OpenAI-, Claude-, and Gemini-style models, but do not confuse wire compatibility with output correctness.
The least complex cheap LLM API gateway that works for logistics moderation is the one that makes every accepted report traceable to a tenant, a queue item, and an estimated cost before a human-review deadline is threatened. A single API key is convenient, but it is not the control plane.
Short answer: put an OpenAI-compatible image request behind a small dispatcher, load image-capable model IDs from a catalog at deploy time, and keep the primary and fallback in configuration. Fail over only on transient failures. A rejected prompt is not a reason to ask another provider.
A candidate-scoring pipeline should treat transcription as a discovered dependency, not as a feature implied by an OpenAI-compatible base URL. Check the capability manifest before accepting audio, keep separate eligibility decisions for US and EU deployments, and route to an approved speech…
You know the feeling. Pager goes off at 2 AM. You stumble to your laptop, open the terminal, and stare at a PostgreSQL stack trace you've seen before — but can't remember exactly what fixed it last time. You dig through Slack threads, closed Jira tickets, and a half-finished runbook.
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