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Tools and Configuration Setup

Make sure you have installed Azure CLI and are signed in to your Azure account. If you already have Azure CLI installed, run the az bicep upgrade command to ensure you're on the latest version of Bicep.

librechat.yaml

The librechat.yaml file should be located in the parent directory of the main.bicep script. To properly configure the librechat.yaml as part of the Bicep deployment, create an OpenAI group named "openai", and set the apiKey to "openai-key" and the instanceName to "openai-instance-name".

endpoints:
  azureOpenAI:
    (...)
    groups:
    - group: "openai"
      apiKey: "openai-key"
      instanceName: "openai-instance-name"
      forcePrompt: false
      assistants: true
      models:
        gpt-4-turbo:
          deploymentName: gpt-4-turbo
          version: "2024-02-15-preview"
        gpt-3.5-turbo-16k:
          deploymentName: gpt-35-turbo-16k
          version: "2024-02-15-preview"

models.json

The models.json file should be located in the same directory of the main.bicep script. Configure the modelName, version, and capacity for each model based on the desired models available in Azure OpenAI Service. Ensure the deploymentName for each model matches the deploymentName parameter in your librechat.yaml file.

{
  "models": [
    {
      "deploymentName": "gpt-4-turbo",
      "modelName": "gpt-4",
      "version": "turbo-2024-04-09",
      "capacity": 75
    },
    {
      "deploymentName": "gpt-35-turbo-16k",
      "modelName": "gpt-35-turbo-16k",
      "version": "0613",
      "capacity": 150
    }
  ]
}

Deployment Instructions

To get a list of available location names for deployment, use the az account list-locations command and use the given name property when referencing that location.

To ensure compatibility and availability of OpenAI models in your selected region, consult the Model Summary Table and Region Availability guide. This provides detailed information on which AI models are available in specific OpenAI service regions.

Provisioning a New Resource Group

To provision a new resource group and deploy resources to it, use the following command. Replace your_region with your preferred Azure location, resource_group_name with your desired resource group name, and openai_service_region with the OpenAI service region that supports the models you need.

az deployment sub create --name librechat --location your_region --template-file .\rg.bicep --parameters resourcegroup=resource_group_name location=your_region openAiService_location=openai_service_region

If you accidentally deploy to the wrong region or want to deploy this script across multiple regions, you might get the following error:

{"code": "InvalidDeploymentLocation", "message": "Invalid deployment location 'westeurope'. The deployment 'librechat' already exists in location 'eastus'."}

To fix this, change the --name parameter in the command from librechat to something else, eg. librechat2.

Deploying to an Existing Resource Group

For deploying resources to an existing resource group, execute the command below. Replace resource_group_name with the name of your existing resource group and openai_service_region with the appropriate OpenAI service region.

az deployment group create --resource-group resource_group_name --template-file .\main.bicep --parameters openAiService_location=openai_service_region createMonogexpressAuthConfig=true

The createMonogexpressAuthConfig parameter will automatically setup a Microsoft identity provider for mongo-express. Remove this parameter or set it to false if you don't want this.