Prompt

What should I use to avoid rewriting code when changing model providers?

Artificial Intelligence / AI Infrastructure1 observationLast seen Oct 10, 2026

Latest observation

Oct 10, 2026OpenAI APIWeb search: off

To avoid rewriting code when switching model providers, use a provider-agnostic abstraction layer or LLM gateway SDK.

Good options:

  • OpenAI-compatible API layer: If your providers support the OpenAI API format, you can swap endpoints/keys with minimal code changes.
  • LiteLLM: A popular library that gives you one interface for many model providers and lets you switch models/providers with config changes.
  • LangChain / LlamaIndex: Helpful if you’re building an app around prompts, tools, retrieval, etc., and want provider flexibility.
  • Your own wrapper interface: Define a small internal interface like generate(prompt, options) and implement adapters per provider.

Best practice:

  1. Put all model calls behind one interface.
  2. Keep provider-specific settings in config, not code.
  3. Normalize responses into your own internal schema.

If you want, I can show a small Python or JavaScript example of how to structure this.

Observation history

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Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.

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