Type Alias: GatewayRoute
GatewayRoute =
z.infer<typeofGatewayRouteSchema>
GatewayRoute fields
Section titled “GatewayRoute fields”Deterministic route selected for one gateway request.
clientProtocol: Protocol the caller used.upstreamProtocol: Protocol selected for the upstream call.target: Discovered model this request will invoke.target.id: Canonical model id advertised by the gateway.target.aliases: Additional names that resolve to this model.target.displayName: Human-readable label shown to clients.target.family(optional): Detected model family used for grouping.target.modelServiceName(optional): Canonical model-service name for metadata lookup.target.endpoint(optional): Normalized serving endpoint backing this target, when discovered.target.endpoint.name: Serving endpoint invoke id.target.endpoint.displayName(optional): Human-readable label when the workspace provides one.target.endpoint.family(optional): Detected model family used for grouping and sort order.target.endpoint.task(optional): Databricks serving task reported for the endpoint.target.endpoint.state(optional): Serving endpoint lifecycle state.target.endpoint.description(optional): Workspace-provided endpoint description.target.endpoint.supportsTools(optional): True when the endpoint accepts tool calls.target.endpoint.profile(optional): Relative quality, speed, and cost scores.target.endpoint.profile.quality(optional): Relative quality score for ranking.target.endpoint.profile.speed(optional): Relative speed score for ranking.target.endpoint.profile.cost(optional): Relative cost score for ranking.target.endpoint.class(optional): Intent-oriented class assigned to this endpoint.target.endpoint.serviceNames(optional): Provider-specific service name aliases keyed by protocol.target.endpoint.modelServiceName(optional): Canonical model-service name used for metadata lookup.target.endpoint.reasoningEfforts(optional): Reasoning effort values this endpoint accepts.target.endpoint.status(optional): Retirement status for this endpoint.target.endpoint.status.deprecated(optional): True when the model should no longer be selected by default.target.endpoint.dimension(optional): Embedding vector size when the endpoint is an embedding model.target.capabilities: Protocol and feature capabilities for this target.target.capabilities.responses: True when the model can serve the Databricks Responses API.target.capabilities.openResponses: True when the model can serve OpenAI Responses.target.capabilities.chat: True when the model can serve Chat Completions.target.capabilities.anthropic: True when the model can serve Anthropic Messages.target.capabilities.embeddings: True when the model can serve embeddings.target.capabilities.aiGatewayCodex: True when the model is reachable through AI Gateway Codex.target.capabilities.tools: True when the model accepts tools.target.capabilities.reasoning: True when the model accepts reasoning effort.target.capabilities.streaming: True when the model can stream tokens.target.capabilities.parallelTools: True when the model can run multiple tools in one turn.target.capabilities.customTools: True when the model accepts custom tool definitions.target.capabilities.structuredOutput: True when the model can return structured output.target.capabilities.webSearch: True when the model can use web search.target.reasoningEfforts: Reasoning effort values this target accepts.upstreamModel: Model identifier sent to the upstream provider.translateRequest: True when the request body must be translated.translateResponse: True when the response body must be translated.