import { ClientSDK, RequestOptions } from "../lib/sdks.js";
import * as components from "../models/components/index.js";
import * as operations from "../models/operations/index.js";
export declare class Models extends ClientSDK {
    /**
     * Create custom model
     *
     * @remarks
     * Creates a new custom model for the workspace. Provider credentials in the configuration are encrypted using the workspace encryption key before being persisted.
     */
    create(request: operations.ModelCreateRequestBody, options?: RequestOptions): Promise<operations.ModelCreateResponseBody>;
    /**
     * Create autorouter custom model
     *
     * @remarks
     * Creates an autorouter model that routes between a strong and economical source model based on the requested profile. Both source models must already exist for the workspace and be marked autorouter-eligible in master data.
     */
    createAutorouter(request: operations.ModelCreateAutorouterRequestBody, options?: RequestOptions): Promise<operations.ModelCreateAutorouterResponseBody>;
    /**
     * Update autorouter custom model
     *
     * @remarks
     * Re-configures an autorouter model. Each of key/strong_model/economical_model/profile falls back to the existing value when omitted. Changing the key enforces uniqueness and rewrites PRICING_KV.
     */
    updateAutorouter(request: operations.ModelUpdateAutorouterRequest, options?: RequestOptions): Promise<operations.ModelUpdateAutorouterResponseBody>;
    /**
     * Create AWS Bedrock custom model
     *
     * @remarks
     * Registers an AWS Bedrock inference profile as a custom model for the workspace. Credentials are resolved at request time via either the integration reference or pod-identity — nothing is stored with the model.
     */
    createAwsBedrock(request: operations.ModelCreateAwsBedrockRequestBody, options?: RequestOptions): Promise<operations.ModelCreateAwsBedrockResponseBody>;
    /**
     * Validate AWS Bedrock inference profile
     *
     * @remarks
     * Performs a live Bedrock Converse probe to verify the inference profile ARN and credentials, then best-effort enriches the response from known system models.
     */
    validateAwsBedrock(request: operations.ModelValidateAwsBedrockRequestBody, options?: RequestOptions): Promise<void>;
    /**
     * Update AWS Bedrock custom model
     *
     * @remarks
     * Updates an AWS Bedrock custom model. ARN changes are format-validated (live AWS validation lives in the dedicated validate endpoint). Configuration and metadata are spread-merged. Parameters are replaced only when the request produces a non-empty list.
     */
    updateAwsBedrock(request: operations.ModelUpdateAwsBedrockRequest, options?: RequestOptions): Promise<operations.ModelUpdateAwsBedrockResponseBody>;
    /**
     * List Azure Foundry deployments under a resource
     *
     * @remarks
     * Lists Azure Foundry deployments under the given base_url and joins each entry with the Orq master-data row. Only OpenAI-developed deployments in succeeded state with chat/completion/embedding/vision model types are returned.
     */
    azureFoundryDeployments(request: operations.ModelAzureFoundryDeploymentsRequestBody, options?: RequestOptions): Promise<operations.ModelAzureFoundryDeploymentsResponseBody>;
    /**
     * Import models from LiteLLM
     *
     * @remarks
     * Bulk-imports a list of LiteLLM model definitions into the workspace model garden.
     */
    importLitellm(request: Array<components.LiteLLMModel> | null, options?: RequestOptions): Promise<Array<components.ModelDocument>>;
    /**
     * List models from configured LiteLLM instance
     *
     * @remarks
     * Fetches the list of models from the LiteLLM instance configured for the workspace. Requires a stored LiteLLM integration.
     */
    listLitellm(options?: RequestOptions): Promise<Array<{
        [k: string]: any;
    }>>;
    /**
     * Create OpenAI-compatible custom model
     *
     * @remarks
     * Creates a custom model backed by any OpenAI-compatible endpoint. The handler probes the target API with the supplied credentials before persisting the model.
     */
    createOpenaiLike(request: operations.ModelCreateOpenAILikeRequestBody, options?: RequestOptions): Promise<operations.ModelCreateOpenAILikeResponseBody>;
    /**
     * Update OpenAI-compatible custom model
     *
     * @remarks
     * Updates an OpenAI-compatible custom model. Live-re-probes the target API when base_url or model_id changes, using the stored encrypted api_key. Metadata is merged (existing preserved, new overrides).
     */
    updateOpenaiLike(request: operations.ModelUpdateOpenAILikeRequest, options?: RequestOptions): Promise<operations.ModelUpdateOpenAILikeResponseBody>;
    /**
     * Validate model endpoint
     *
     * @remarks
     * Validates a provider endpoint by performing a minimal live probe. Currently supports Azure OpenAI. Response includes the resolved region, whether the model is known to Orq, and either the full model document or a synthesized default.
     */
    validate(request: operations.ModelValidateRequestBody, options?: RequestOptions): Promise<void>;
    /**
     * Create Vertex AI custom model
     *
     * @remarks
     * Registers a Google Vertex AI model as a custom model for the workspace. The service account credentials are probed against Vertex AI with a minimal GenerateContent call before persisting.
     */
    createVertex(request: operations.ModelCreateVertexRequestBody, options?: RequestOptions): Promise<operations.ModelCreateVertexResponseBody>;
    /**
     * Delete custom model
     *
     * @remarks
     * Deletes a custom model from the workspace. System models cannot be deleted. Returns 200 with an explanatory message if the model is a system model or is still referenced by experiments.
     */
    delete(request: operations.ModelDeleteRequest, options?: RequestOptions): Promise<void>;
    /**
     * Update custom model
     *
     * @remarks
     * Updates a custom model. Only fields present in the request body are modified, except for `metadata` and `parameters`, which are fully replaced when present (preserved from the legacy handler's behavior).
     */
    update(request: operations.ModelUpdateRequest, options?: RequestOptions): Promise<operations.ModelUpdateResponseBody>;
    /**
     * Enable model for workspace
     *
     * @remarks
     * Adds the model to the workspace's enabled set. Idempotent — re-enabling an already-enabled model returns 204 with no state change.
     */
    enable(request: operations.ModelEnableRequestBody, options?: RequestOptions): Promise<void>;
    /**
     * Disable model for workspace
     *
     * @remarks
     * Removes the model from the workspace's enabled set. Idempotent — disabling an already-disabled model returns 204.
     */
    disable(request: operations.ModelDisableRequest, options?: RequestOptions): Promise<void>;
    /**
     * List models
     *
     * @remarks
     * Lists all models available through the AI Router. Returns each model in OpenAI-compatible shape with its provider, ID, and creation timestamp.
     */
    list(options?: RequestOptions): Promise<operations.ListModelsResponseBody>;
}
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