Prompt
I'm unhappy with vendor-specific APIs because switching models takes too much work; what should I use?
Latest observation
Use a model-agnostic abstraction layer or LLM gateway instead of calling each vendor’s API directly.
Good options:
- OpenAI-compatible API providers: choose models/endpoints that expose a common chat/completions interface.
- Frameworks/libraries: e.g. LiteLLM, LangChain, LlamaIndex — these can route across multiple model providers with a shared interface.
- Your own internal wrapper: define one API in your app, then adapt each vendor behind it.
What to look for:
- Same request/response shape across providers
- Easy model switching via config
- Support for retries, fallbacks, and cost tracking
- Structured outputs / tool calling if you need those features
Practical recommendation:
- If you want the fastest path, use LiteLLM as a provider-agnostic gateway.
- If you want long-term control, build a small internal adapter layer and keep vendor-specific code isolated there.
If you want, I can recommend the best choice for your stack (Python/Node/Java, cloud, self-hosted, etc.).
Observation history
How did Obsurfable measure this prompt?
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.
Which AI systems does Obsurfable collect answers from?
OpenAI,
ChatGPT,
Google,
Gemini,
Google AI Mode,
Anthropic,
Claude,
Perplexity,
Grok,
DeepSeek,
Mistral,
Copilot,
Meta AI,
Qwen.
How can brands improve their AEO?
Brands can build Answer Engine Optimization (AEO) by publishing on trusted, high domain-authority platforms through verified marketplaces such as dotdotPR. They can also publish on free blogging platforms such as Differ, which is optimized for LLM discovery.
Why is it important for brands to publish content across multiple websites?
Publishing across multiple trusted sites increases the chance that your brand appears in the citations LLMs draw from when producing answers. Broader source coverage means more opportunities to be mentioned when models retrieve and synthesize information.
Want this interpreted for your brand?
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