This guide shows how to set up a minimal deployment to use the TensorZero Gateway with OpenAI-compatible endpoints like Ollama.

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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: 
- config/
  - tensorzero.toml
- docker-compose.yml
You can also find the complete code for this example on GitHub.
For production deployments, see our Deployment Guide.

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Configuration

Create a minimal configuration file that defines a model and a simple chat function:
config/tensorzero.toml
[models.llama3_1_8b_instruct]
routing = ["ollama"]

[models.llama3_1_8b_instruct.providers.ollama]
type = "openai"
api_base = "http://host.docker.internal:11434/v1"  # for Ollama running locally on the host
model_name = "llama3.1"
api_key_location = "none"  # by default, Ollama requires no API key

[functions.my_function_name]
type = "chat"

[functions.my_function_name.variants.my_variant_name]
type = "chat_completion"
model = "llama3_1_8b_instruct"

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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): 
    api_key_location = "none"
  • If your endpoint requires an API key, you have two options:
    1. Configure it in advance through an environment variable: 
      api_key_location = "env::ENVIRONMENT_VARIABLE_NAME"
      You’ll need to set the environment variable before starting the gateway.
    2. Provide it at inference time: 
      api_key_location = "dynamic::ARGUMENT_NAME"
      The API key can then be passed in the inference request.
See the Credential Management guide, 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".

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Deployment (Docker Compose)

Create a minimal Docker Compose configuration:
docker-compose.yml
# This is a simplified example for learning purposes. Do not use this in production.
# For production-ready deployments, see: https://www.tensorzero.com/docs/gateway/deployment

services:
  gateway:
    image: tensorzero/gateway
    volumes:
      - ./config:/app/config:ro
    command: --config-file /app/config/tensorzero.toml
    # environment:
    # - OLLAMA_API_KEY=${OLLAMA_API_KEY:?Environment variable OLLAMA_API_KEY must be set.} // not necessary for this example
    ports:
      - "3000:3000"
    extra_hosts:
      - "host.docker.internal:host-gateway"
You can start the gateway with docker compose up.

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Inference

Make an inference request to the gateway: 
curl -X POST http://localhost:3000/inference \
  -H "Content-Type: application/json" \
  -d '{
    "function_name": "my_function_name",
    "input": {
      "messages": [
        {
          "role": "user",
          "content": "What is the capital of Japan?"
        }
      ]
    }
  }'