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Getting Started with Mistral

This guide shows how to set up a minimal deployment to use the TensorZero Gateway with the Mistral API.

Setup

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:

config/tensorzero.toml
[models.ministral_8b_2410]
routing = ["mistral"]
[models.ministral_8b_2410.providers.mistral]
type = "mistral"
model_name = "ministral-8b-2410"
[functions.my_function_name]
type = "chat"
[functions.my_function_name.variants.my_variant_name]
type = "chat_completion"
model = "ministral_8b_2410"
# Disable observability to keep this example minimal (not recommended in production)
[gateway]
disable_observability = true

See the list of models available on Mistral.

Credentials

You must set the MISTRAL_API_KEY environment variable before running the gateway.

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
environment:
- MISTRAL_API_KEY=${MISTRAL_API_KEY:?Environment variable MISTRAL_API_KEY must be set.}
ports:
- "3000:3000"

You can start the gateway with docker compose up.

Inference

Make an inference request to the gateway:

Terminal window
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?"
}
]
}
}'