Getting Started with OpenAI-Compatible Endpoints (e.g. Ollama)
This guide shows how to set up a minimal deployment to use the TensorZero Gateway with OpenAI-compatible endpoints like Ollama.
Setup
This guide assumes that you are running Ollama locally with ollama serve
and that you’ve pulled the llama3.1
model in advance (e.g. ollama pull llama3.1
).
Make sure to update the api_base
and model_name
in the configuration below to match your OpenAI-compatible endpoint and model.
For this minimal setup, you’ll need just two files in your project directory:
Directoryconfig/
- tensorzero.toml
- docker-compose.yml
For production deployments, see our Deployment Guide.
Configuration
Create a minimal configuration file that defines a model and a simple chat function:
Credentials
The api_key_location
field in your model provider configuration specifies how to handle API key authentication:
-
If your endpoint does not require an API key (e.g. Ollama by default):
-
If your endpoint requires an API key, you have two options:
-
Configure it in advance through an environment variable:
You’ll need to set the environment variable before starting the gateway.
-
Provide it at inference time:
The API key can then be passed in the inference request.
-
See the Configuration Reference and the API reference for more details.
In this example, Ollama is running locally without authentication, so we use api_key_location = "none"
.
Deployment (Docker Compose)
Create a minimal Docker Compose configuration:
You can start the gateway with docker compose up
.
Inference
Make an inference request to the gateway: