2 API Gateway Designs for OpenAI, Claude, Gemini Batch Moderation (US/EU)

Описание и применение

В финтех‑команде реализован единый API‑шлюз для модерации сообщений, поддерживающий несколько LLM‑провайдеров. Шлюз унифицирует контракт, обеспечивает строгую схему JSON, записывает выбранную модель и поддерживает пакетную обработку для не‑срочных запросов, сохраняя при этом контроль над маршрутизацией и соблюдением регуляций.

Задача

Fintech teams need to classify moderation reports before human review while balancing cost, latency, and regulatory control across multiple LLM providers.

Результат

The hosted gateway (Infrai) enabled rapid deployment, unified billing, and batch moderation for non‑urgent reports, reducing integration overhead. For teams needing strict routing control, a self‑hosted LiteLLM gateway remains viable.

Рабочий процесс

• 1. Define a normalized moderation schema (report_id, category, risk, rationale, urgent_human_review).
• 2. Freeze operating rules: exclude account data, validate output against schema, attach correlation ID and model name, route failures to human review.
• 3. Choose gateway shape: hosted (Infrai) for quick deployment and cost control, or self‑hosted (LiteLLM) for strict routing and policy control.
• 4. Benchmark candidate models on a fixed evaluation set, measuring classification accuracy, token counts, cost, and batch suitability.
• 5. Deploy the gateway, configure the chosen model via environment variables, and instrument cache hits and per‑call cost.
• 6. For urgent reports, keep synchronous calls; for backlog, enqueue for nightly batch processing.
• 7. Continuously monitor validation failures, cost metrics, and adjust routing rules based on observed traffic.

Доказательства

Use an OpenAI-compatible API gateway across Claude and Gemini when moderation classification is replaceable and cost-sensitive; self-host when routing policy or data-plane control matters more than setup time.

Источник

The hosted design wins my first-call test. The application submits a normalized moderation report, requests a strict JSON result, and records the chosen model with the response.

Источник