> ## Documentation Index
> Fetch the complete documentation index at: https://docs.orq.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# List Azure Foundry deployments under a resource

> 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.



## OpenAPI

````yaml post /v2/models/azure-foundry/deployments
openapi: 3.1.0
info:
  title: orq.ai API
  version: '2.0'
  description: orq.ai API documentation
servers:
  - url: https://api.orq.ai
security:
  - ApiKey: []
tags:
  - description: List models available through the AI Router.
    name: Models
  - name: Guardrail Rules
  - name: Policies
  - name: Routing Rules
  - name: API keys
    description: >-
      API keys authenticate programmatic access to the workspace. The unified
      key model exposes opaque tokens, per-domain access grants, and budget /
      rate-limit constraints (see ADR 0001 and ADR 0002).
  - name: Budgets
    description: >-
      Budgets govern spend, token usage, and request rate across six scopes:
      workspace, project, identity, api-key, provider, and model. A budget is
      hierarchical and defense-in-depth — every applicable budget is a hard
      gate, and the most restrictive one wins per dimension (see ADR 0007).
  - name: Documentation
    description: >-
      Search the orq.ai documentation. Proxies the workspace's query to the
      hosted docs search index.
  - name: Files
    description: File upload and retrieval operations.
  - name: Identities
    description: >-
      Identities represent end users from your system for usage and engagement
      tracking.
  - name: Projects
    description: Projects organize resources within a workspace
  - name: Skills
    description: >-
      Skills are modular instructions you can use to codify processes and
      conventions
  - name: Responses
  - description: >-
      Run agents on a cadence — cron, interval, or one-off. Minimum firing
      interval is 1 hour.
    name: Agent Schedules
  - name: Embeddings
  - name: Reporting
    description: >-
      GenAI reporting API over canonical analytics rollups. Accepts a metric
      name, time range, grain, group-by, and filters; returns a typed time
      series and optional totals.
externalDocs:
  url: https://docs.orq.ai
  description: orq.ai Documentation
paths:
  /v2/models/azure-foundry/deployments:
    post:
      tags:
        - Models
      summary: List Azure Foundry deployments under a resource
      description: >-
        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.
      operationId: ModelAzureFoundryDeployments
      requestBody:
        content:
          application/json:
            schema:
              additionalProperties: false
              properties:
                api_key:
                  type: string
                api_version:
                  type: string
                base_url:
                  type: string
                provider:
                  type: string
              required:
                - provider
                - base_url
                - api_key
              type: object
        required: true
      responses:
        '200':
          content:
            application/json:
              schema:
                additionalProperties: false
                properties:
                  deployments:
                    items:
                      $ref: '#/components/schemas/AzureFoundryDeployment'
                    type:
                      - array
                      - 'null'
                  region:
                    type: string
                required:
                  - region
                  - deployments
                type: object
          description: Azure Foundry deployments listed
        '400':
          description: Invalid request or base_url
      x-code-samples:
        - label: Node.js
          lang: typescript
          source: |-
            await orq.models.azureFoundryDeployments({
              provider: "azure",
              base_url: "https://my-resource.openai.azure.com/openai/v1",
              api_key: "...",
            });
components:
  schemas:
    AzureFoundryDeployment:
      additionalProperties: false
      properties:
        id:
          type: string
        master_data:
          $ref: '#/components/schemas/AzureFoundryDeploymentMasterData'
        model:
          type: string
      required:
        - id
        - model
      type: object
    AzureFoundryDeploymentMasterData:
      additionalProperties: false
      properties:
        has_functions:
          type: boolean
        id:
          type: string
        input_cost:
          type: number
          format: double
        metadata:
          type: object
          additionalProperties: {}
        model_developer:
          type:
            - string
            - 'null'
        model_family:
          type:
            - string
            - 'null'
        model_id:
          type: string
        model_type:
          type: string
        output_cost:
          type: number
          format: double
        parameters:
          items: {}
          type:
            - array
            - 'null'
      required:
        - input_cost
        - output_cost
        - has_functions
        - model_type
        - id
        - model_id
        - parameters
        - model_developer
        - model_family
      type: object
  securitySchemes:
    ApiKey:
      type: http
      scheme: bearer
      bearerFormat: JWT

````