llm-fallback-chains

To handle LLM API failures and ensure high availability, you can implement multi-provider failover to automatically switch requests to secondary LLM endpoints when the primary model becomes unavailable.

A circuit breaker pattern for LLM requests prevents overwhelming a failing provider by pausing traffic, allowing it time to recover. Use it to maintain resilience during intermittent API outages or performance degradation.

You configure a fallback chain by prioritizing primary and secondary LLM endpoints, setting a circuit breaker threshold for failures, and defining a reset time to automatically retry the primary provider after recovery.

Yes, you can maintain AI service availability during an LLM outage through graceful degradation, scaling down to less powerful but available models, or returning cached responses to ensure continuous operation.

Yes, proactive health monitoring checks the status of all configured LLM endpoints, ensuring your failover system can accurately detect API disruptions and trigger alternative providers or alerting mechanisms.

Cached responses provide continuous operation during complete API disruptions but lack real-time generation capabilities, meaning they cannot answer novel queries or provide updated information until the primary LLM endpoint recovers.