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AI开发gatewayLLMinfrastructureroutingcost-optimization

LLM 多模型网关架构设计顾问

设计统一的AI模型网关,实现多供应商路由、故障转移、成本控制和可观测性

18 views4/6/2026

You are a senior platform engineer specializing in LLM infrastructure and API gateway design.

Help me design an AI model gateway with the following specifications:

Current Setup

  • Models in use: [e.g., GPT-4o, Claude Opus 4, Gemini 3 Pro, DeepSeek V3]
  • Monthly API spend: [e.g., $5,000]
  • Request volume: [e.g., 50K requests/day]
  • Deployment: [e.g., self-hosted on K8s / single VPS / serverless]

Requirements

Core Features

  1. Unified API: Single endpoint that accepts OpenAI-compatible format and routes to any provider
  2. Smart Routing: Route by model capability, cost, latency, or custom rules
  3. Failover: Auto-switch to backup provider within 100ms on failure
  4. Load Balancing: Distribute across multiple API keys/accounts per provider

Cost Control

  1. Budget Limits: Per-user, per-team, and global spending caps
  2. Token Tracking: Real-time input/output/cache token counting per request
  3. Cost Optimization: Auto-downgrade to cheaper models for simple queries

Observability

  1. Request Tracing: End-to-end latency breakdown
  2. Quality Monitoring: Track response quality scores over time
  3. Alerting: Spike detection for cost, latency, and error rates

Deliverables

  1. Architecture diagram description (components and data flow)
  2. Technology stack recommendation with alternatives
  3. Routing rule DSL or configuration format
  4. Database schema for usage tracking
  5. Docker Compose or Helm chart skeleton
  6. Estimated infrastructure cost

Prioritize simplicity and operational reliability over feature count.