llm-integration

To make LLM API calls production-ready, implement circuit breakers, exponential backoff, and provider failover. These resilience patterns handle API instability and rate limits gracefully, keeping your application responsive during high traffic.

The best way to reduce LLM latency and token costs is by implementing streaming responses and ephemeral prompt caching. These performance optimization strategies minimize token usage and lower latency for high-scale applications.

Multi-provider failover for language model APIs works by routing requests to backup providers when the primary API fails. Combined with circuit breaking, it ensures system stability and prevents cascading failures during provider outages.

Yes, you can use prompt caching and streaming together in a customer-facing chatbot. Streaming responses keeps the application responsive during high traffic, while effective caching minimizes token costs.

For token accounting and budget control in LLM features, implement strategies that track usage and combine them with circuit breaking and prompt caching. This ensures system stability and enforces budget limits during high-scale operations.