Adaptive Engine enables you to connect proprietary models, so you can use them through the Adaptive API in tandem with other platform features - such as
interaction and feedback logging. The only requirement is that you supply a valid external API key.
This feature currently supports OpenAI (both via OpenAI’s API and Azure OpenAI Service) and Google models.
external_model = adaptive.models.add_external(
provider="open_ai",
external_model_id="GPT4O",
name="GPT-4o",
api_key="OPENAI_API_KEY"
)
GPT4OGPT4O_MINIGPT4GPT4_TURBOGPT3_5_TURBO
external_model = adaptive.models.add_external(
provider="azure",
external_model_id="DEPLOYMENT_NAME",
name="Azure GPT-4o",
api_key="AZURE_API_KEY",
endpoint="AZURE_OPENAI_SUBSCRIPTION_ENDPOINT"
)
- the
external_model_id should be the the deployment name/id of your model
- the
endpoint should be your Azure OpenAI subscription endpoint, which should
look something like https://aoairesource.openai.azure.com.
See here for more information.external_model = adaptive.models.add_external(
provider="google",
external_model_id="gemini-1.5-pro",
name="Gemini 1.5 Pro",
api_key="GOOGLE_API_KEY"
)
Once the proprietary model is connected to Adaptive Engine, you can attach it to a use-case
and make inference requests the same way you would for any other Adaptive Engine model. 
