I'm building an AI app with retries, caching, and failover across providers; what should I use?

If you want retries, caching, and failover across multiple AI providers in one app, a good default choice is:

Use LiteLLM

It’s built specifically as a unified gateway/proxy for LLM providers and handles a lot of what you’re asking for:

• Retries with configurable backoff
• Fallback / failover across providers or models
• Caching support
• Provider normalization so you can swap OpenAI, Anthropic, Azure, Gemini, etc.
• Works as a Python SDK or as a proxy server

Why it’s a good fit

If your app needs:

• “try OpenAI first, then Anthropic if that fails”
• “cache identical prompts”
• “route certain models to certain vendors”
• “avoid provider-specific code everywhere”

…then LiteLLM is one of the cleanest options.

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Other good options depending on your architecture

1. LangChain

Use this if you’re already using it for agents/RAG and want:

• retries
• routing/fallback logic
• integrations with many model providers

But: it’s more of an app framework than a dedicated reliability layer.

2. OpenAI-compatible gateways / proxies

Examples:

• LiteLLM Proxy
• Portkey
• Helicone (more observability-focused, but can support routing setups)

These are useful if you want:

• centralized control
• analytics
• policy enforcement
• provider fallback

3. Custom wrapper with a queue + cache

If your use case is simple, you can build:

• retry middleware
• Redis cache
• provider failover logic
• circuit breaker

This gives maximum control, but more maintenance.

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My recommendation

If you want the fastest path to production:

Start with LiteLLM

• SDK if you want library-style integration
• Proxy if you want centralized routing/failover for many services

Add:

• Redis for caching
• Tenacity (Python) or similar for custom retry policies if needed
• OpenTelemetry / logs for observability

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Simple decision guide

• Need multi-provider failover + caching now? → LiteLLM
• Already in LangChain? → Use LangChain plus a caching/retry layer
• Need enterprise gateway/analytics/governance? → Consider Portkey or LiteLLM Proxy
• Need full control and minimal dependencies? → Build your own wrapper

If you want, I can also give you:

1. a recommended stack for Python/Node,
2. a sample failover architecture, or
3. a minimal code example using LiteLLM + Redis + retries.