I'm building a chatbot that needs retries and failover; what should I use?

For a chatbot with retries and failover, a good default choice is:

Use a workflow/orchestration layer + a multi-model routing strategy

This gives you:

• Retries for transient failures
• Fallbacks/failover to another model/provider if the primary fails
• Better control over timeouts, circuit breakers, and observability

Good options

1) LangGraph / LangChain

Best if you want an LLM app framework with built-in control flow.

• Easy to model retry/fallback logic
• Good for complex chatbot flows
• Works well with multiple model providers

2) OpenAI API with your own failover logic

Best if you want something lightweight and custom.

• Implement retry on 429/5xx
• Switch to backup model/provider on repeated failure
• Add exponential backoff and timeouts

3) Temporal / Prefect / Durable Functions

Best if the chatbot is part of a larger production workflow.

• Strong retry policies
• Durable state
• Great if you need guaranteed execution and auditability

4) LiteLLM

Best if you want one interface to many LLM providers.

• Supports routing across providers/models
• Useful for fallback and load balancing
• Can simplify provider failover a lot

Practical recommendation

If you’re starting from scratch:

• Simple chatbot: OpenAI API + your own retry/failover wrapper
• More complex agent/chat flows: LangGraph
• Multi-provider abstraction: LiteLLM
• Mission-critical workflows: Temporal

What to include in your retry/failover design

• Exponential backoff
• Jitter
• Timeouts
• Max retry count
• Circuit breaker
• Backup model/provider
• Logging/metrics

If you want, I can also give you:

1. a recommended architecture, or
2. a code example for retries + failover in Python or Node.js.