AI Engine providers and models

Configure the default AI provider, model, credentials, and provider-specific options for the DecisionRules AI Engine container. ---

In Docker and on-premise deployments, the default AI provider and model can be configured directly through environment variables on the DecisionRules AI Engine container.

This configuration provides a fallback AI configuration. If a request already contains an organization-level provider configuration, the request configuration takes precedence.

Only one fallback provider and model combination can be configured for each AI Engine container.

Requirements

The AI Engine is a separately versioned container. The DecisionRules Client and Server version does not determine the AI Engine version.

Configure the AIA_* variables on the AI Engine container, not on the Client or Server container.

Environment variables

Environment variables

Supported providers and families

Supported AIA_PROVIDER values:

• openai

• anthropic

• google

• google-vertex

• azure

• amazon-bedrock

• litellm

Supported AIA_FAMILY values:

• openai

• anthropic

• google

• amazon

• qwen

Use the following provider and family combinations:

AIA_PROVIDER	Supported AIA_FAMILY	Credential format	Required additional settings
openai	openai	OpenAI API key	None
anthropic	anthropic	Anthropic API key	None
google	google	Google AI API key	None
google-vertex	google, anthropic	Google service account JSON	project when not present in the credentials
azure	openai, anthropic	JSON containing api_key	endpoint or azure_endpoint
amazon-bedrock	amazon, anthropic, google, openai, qwen	Amazon Bedrock API key	None
litellm	openai	API key for the target endpoint	api_base

The selected model must be available through the selected provider. Model capabilities can differ even within the same family.

Additional configuration options

AIA_ADDITIONAL_DATA_JSON must contain a valid JSON object.

Option	Provider	Type	Default	Description
project	google-vertex	string	Service account project_id	Google Cloud project containing the model.
location	google-vertex	string	global	Google Cloud location used by Vertex AI.
endpoint	azure	string	—	Azure or Microsoft Foundry model endpoint.
azure_endpoint	azure	string	—	Alias for endpoint.
region	amazon-bedrock	string	global	AWS region used for Bedrock.
api_base	litellm	string	—	Base URL of the OpenAI-compatible endpoint.
merge_system_prompt	litellm	boolean	false	Combines system messages for models that accept only one system message.
structured_output_mode	litellm	string	tool	Structured output mechanism. Supported values are tool, native, and prompted.
fileAttachmentsEnabled	All providers	boolean	false	Advertises file attachment availability to the DecisionRules Client. The selected model must still support the required input types.

Structured output modes

The structured_output_mode setting supports:

• tool: Uses tool calling to obtain structured output. This is the default.

• native: Uses the provider's native structured-output or JSON Schema capability.

• prompted: Requests structured output through the prompt. Use this as a compatibility fallback when tool-based or native structured output is unavailable.

The merge_system_prompt and structured_output_mode options configure the OpenAI model profile internally.

These options apply only to the current litellm OpenAI-compatible adapter.

Provider examples

OpenAI

ai-engine:
  image: decisionrules/ai-engine
  environment:
    AIA_PROVIDER: "openai"
    AIA_FAMILY: "openai"
    AIA_MODEL: "<OPENAI_MODEL_ID>"
    AIA_SECRET: "<OPENAI_API_KEY>"

Anthropic

ai-engine:
  image: decisionrules/ai-engine
  environment:
    AIA_PROVIDER: "anthropic"
    AIA_FAMILY: "anthropic"
    AIA_MODEL: "<ANTHROPIC_MODEL_ID>"
    AIA_SECRET: "<ANTHROPIC_API_KEY>"

Google AI

Use this variant for models accessed using a Google AI API key.

ai-engine:
  image: decisionrules/ai-engine
  environment:
    AIA_PROVIDER: "google"
    AIA_FAMILY: "google"
    AIA_MODEL: "<GOOGLE_MODEL_ID>"
    AIA_SECRET: "<GOOGLE_API_KEY>"

Google Vertex AI

AIA_SECRET must contain the complete Google service account credentials as a JSON object serialized into an environment variable.

ai-engine:
  image: decisionrules/ai-engine
  environment:
    AIA_PROVIDER: "google-vertex"
    AIA_FAMILY: "google"
    AIA_MODEL: "<VERTEX_MODEL_ID>"
    AIA_SECRET: '<GOOGLE_SERVICE_ACCOUNT_JSON>'
    AIA_ADDITIONAL_DATA_JSON: >-
      {"project":"<GOOGLE_PROJECT_ID>","location":"global"}

To use an Anthropic model hosted on Vertex AI, set:

AIA_FAMILY: "anthropic"

When project is omitted, the AI Engine uses project_id from the service account JSON. When location is omitted, it defaults to global.

Azure and Microsoft Foundry

For Azure, AIA_SECRET must be a JSON object containing api_key or apiKey.

ai-engine:
  image: decisionrules/ai-engine
  environment:
    AIA_PROVIDER: "azure"
    AIA_FAMILY: "openai"
    AIA_MODEL: "<AZURE_DEPLOYMENT_OR_MODEL_ID>"
    AIA_SECRET: >-
      {"api_key":"<AZURE_API_KEY>"}
    AIA_ADDITIONAL_DATA_JSON: >-
      {"endpoint":"<AZURE_OR_FOUNDRY_ENDPOINT>"}

To use an Anthropic model exposed through Microsoft Foundry, set:

AIA_FAMILY: "anthropic"

The endpoint can be supplied using either endpoint or azure_endpoint.

Amazon Bedrock

ai-engine:
  image: decisionrules/ai-engine
  environment:
    AIA_PROVIDER: "amazon-bedrock"
    AIA_FAMILY: "anthropic"
    AIA_MODEL: "<BEDROCK_MODEL_ID>"
    AIA_SECRET: "<BEDROCK_API_KEY>"
    AIA_ADDITIONAL_DATA_JSON: >-
      {"region":"eu-central-1"}

For model families other than openai and qwen, the AI Engine adds the geographic prefix derived from the configured region to the model ID.

For openai and qwen, the configured model ID is used unchanged.

OpenAI-compatible endpoints

In AI Engine, OpenAI-compatible endpoints use:

AIA_PROVIDER: "litellm"
AIA_FAMILY: "openai"

The name litellm selects an adapter included in the DecisionRules AI Engine. It does not require you to install, deploy, or configure a separate LiteLLM service.

ai-engine:
  image: decisionrules/ai-engine
  environment:
    AIA_PROVIDER: "litellm"
    AIA_FAMILY: "openai"
    AIA_MODEL: "<PROVIDER_MODEL_ID>"
    AIA_SECRET: "<PROVIDER_API_KEY>"
    AIA_ADDITIONAL_DATA_JSON: >-
      {"api_base":"<OPENAI_COMPATIBLE_BASE_URL>","merge_system_prompt":true,"structured_output_mode":"tool"}

Example endpoints:

Service	api_base
Scaleway Generative APIs	https://api.scaleway.ai/v1
OpenRouter	https://openrouter.ai/api/v1
LiteLLM Proxy	http://litellm:4000/v1
Other compatible service	Provider-specific OpenAI-compatible base URL

Before using a custom model in production, verify that it supports the capabilities required by the enabled AI Assistant features, particularly:

• function and tool calling,

• structured outputs,

• sufficient context and output-token limits,

• streaming, when required.

OpenAI API compatibility alone does not guarantee that every model supports the complete DecisionRules AI Assistant workflow.