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Documentation Index

Fetch the complete documentation index at: https://www.truefoundry.com/llms.txt

Use this file to discover all available pages before exploring further.

If you run LLMs on your own infrastructure — on-premises GPUs, private cloud instances, or any model server not deployed through TrueFoundry — you can connect them to the AI Gateway by providing the endpoint URL and authentication details. Once registered, these models appear in the gateway model catalog alongside cloud providers and benefit from all gateway features: routing, guardrails, rate limiting, cost tracking, and observability.

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Prerequisites

Your model server must expose an HTTP endpoint. The gateway works best with OpenAI-compatible APIs, which is the default output format for popular inference frameworks:

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Adding Self-Hosted Models to the Gateway

Follow these steps to add a self-hosted or external model (deployed on TrueFoundry or elsewhere) to the AI Gateway.
1

Navigate to Self Hosted Models in AI Gateway

From the TrueFoundry dashboard, navigate to AI Gateway > Models and select Self Hosted Models.
Navigating to Self Hosted Provider Account in AI Gateway
2

Add Collaborators

Add collaborators to your account, this will give access to the account to other users/teams. Learn more about access control here.
Self Hosted account configuration form with fields for API key and collaborators
3

Configure Model Details

Give a name to your hosted model and add ModelId, add the URL to the hosted model. Choose the correct Model Server for your model and optionally add Auth Data which will be used for Authentication of request to the model.Configuration form showing fields for model ID, URL, and authentication

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Inference

After adding the models, you can perform inference using an OpenAI-compatible API via the Playground or by integrating with your own application.
Code Snippet and Try in Playground Buttons for each model