openapi: 3.1.0
info:
  title: NVIDIA NIM API for nvidia/nvclip-vit-h-14
  description: The NVIDIA NIM REST API. Please see https://docs.api.nvidia.com/nim for more details.
  version: 1.0.0
  termsOfService: https://nvidia.com/legal/terms-of-use
  contact:
    name: NVIDIA Support
    url: https://help.nvidia.com/
  license:
    name: NVIDIA AI Foundation Models Community License
    url: https://docs.nvidia.com/ai-foundation-models-community-license.pdf
tags:
  - name: "${nvclip_long_name} API"
    description: Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms.
paths:
  /v1/health/ready:
    get:
      summary: Service ready check
      description: This endpoint will return a 200 status when the service is ready
        to receive inference requests
      operationId: health_v1_health_ready_get
      responses:
        '200':
          description: Successful Response
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/NIMHealthSuccessResponse'
        '503':
          description: Service is not ready to receive requests.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Errors'
  /v1/health/live:
    get:
      summary: Service liveness check
      description: This endpoint will return a 200 status as soon as the service is
        able to accept traffic, but it does not mean the service is ready to accept
        inference requests.
      operationId: health_ready_v1_health_live_get
      responses:
        '200':
          description: Successful Response
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/NIMHealthSuccessResponse'
  /v1/metrics: 
    get: 
      summary: Metrics
      description: Handler for metrics endpoint.
      operationId: metrics_v1_metrics_get
      responses:
        200: 
          description: Successful Response
          content: 
            application/json: 
              schema: 
                type: string
                title: Response Metrics V1 Metrics Get
  /v1/license:
    get:
      summary: Provide NIM LICENSE
      description: This endpoint will return the NIM Container license information
      operationId: show_license_v1_license_get
      responses:
        '200':
          description: Successful Response
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/NIMLicenseInfoResponse'
  /v1/metadata:
    get:
      summary: Provide NIM Metadata
      description: This endpoint will return the NIM Container Version, associated
        models, assets and license information
      operationId: show_metadata_v1_metadata_get
      responses:
        '200':
          description: Successful Response
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/NIMMetadataResponse'
  /v1/manifest:
    get:
      summary: Provide NIM Manifest file
      description: This endpoint will return the NIM manifest file content
      operationId: manifest_v1_manifest_get
      responses:
        '200':
          description: Successful Response
          content:
            application/json:
              manifest_file:
                type: string
                title: ManifestFile
                description: Manifest file contents
  "/v1/embeddings":
    post:
      tags:
        - Embeddings
      summary: Creates an embedding vector representing the input text or image.
      description: "Invokes inference using the embedding parameters. If uploading
        large images, this POST should be used in conjunction with the NVCF API which
        allows for the upload of large assets. \nYou can find details on how to use
        NVCF Asset APIs here: https://docs.api.nvidia.com/cloud-functions/reference/createasset."
      operationId: createEmbedding
      parameters:
      - in: header
        name: NVCF-INPUT-ASSET-REFERENCES
        schema:
          type: string
          maxLength: 370
          format: uuid
        required: false
        description: 'String of asset IDs separated by commas. Data is uploaded to
          AWS S3 using NVCF Asset APIs and associated with these asset IDs.If the
          size of an image is more than 180KB, it needs to be uploaded to a presigned
          S3 URL bucket. The presigned URL allows for secure and temporary access
          to the S3 bucket for uploading the image. Once the asset is requested, an
          asset ID is generated for it. Please include this asset ID in this header
          and to use the uploaded image in a prompt, you need to refer to it using
          the following format: `<img src="data:image/png;asset_id,{asset_id}" />`.'
      requestBody:
        content:
          application/json:
            schema:
              "$ref": "#/components/schemas/EmbeddingsRequest"
        required: true
      x-nvai-meta:
        name: "Create Text Embedding"
        description: |
          Generates an embedding vector from the provided text
          using a specified model. The embedding can be returned
          in either float array or base64-encoded format.
        path: "create"
        templates:
          - title: "Synchronous requests"
            requestEjs:
              curl: |
                curl -X POST https://integrate.api.nvidia.com/v1/embeddings \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $NVIDIA_API_KEY" \
                  -d '{
                    "input": ["Image of a dog",
                              "data:image/jpeg;base64,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"],
                    "model": "nvidia/nvclip-vit-h-14",
                    "encoding_format": "float"
                  }'
              python: |
                from openai import OpenAI

                client = OpenAI(
                  api_key="$NVIDIA_API_KEY",
                  base_url="https://integrate.api.nvidia.com/v1"
                )

                response = client.embeddings.create(
                    input=[ "Image of a dog",
                            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"],
                    model="nvidia/nvclip-vit-h-14",
                    encoding_format="float"
                )

                print(response.data[0].embedding)
              node: |
                import OpenAI from 'openai';

                const openai = new OpenAI({
                  apiKey: '$NVIDIA_API_KEY',
                  baseURL: 'https://integrate.api.nvidia.com/v1/',
                })

                async function main() {
                  const response = await openai.embeddings.create({
                    input: ["The quick brown fox jumped over the lazy dog",
                    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"
                  ],
                    model: "nvidia/nvclip-vit-h-14",
                    encoding_format: "float"
                  })

                  const embedding = response.data[0].embedding;
                  process.stdout.write(`${embedding}\n`);
                }

                main();

            response: >
              {
                "object":"list",
                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                "object":"embedding"}],
                "usage":{"num_images":1,"prompt_tokens":77,"total_tokens":77},
                "model":"nvidia/nvclip-vit-h-14"
              }
      responses:
        '200':
          description: Invocation is fulfilled.
          content:
            application/json:
              schema:
                "$ref": "#/components/schemas/EmbeddingsResponse"
        '402':
            description: Payment Required.
            content:
              application/json:
                schema:
                  properties:
                    detail:
                      type: string
                      maxLength: 256
                      format: ^[a-zA-Z-]{1,64}$
                      description: Contains specific information related to the error and why it occurred.
                      example: You have reached your limit of credits.
                  type: object
                  title: PaymentRequiredError
        '422':
          description: Validation failed, provided entity could not be processed.
          content:
            application/json:
              schema:
                "$ref": "#/components/schemas/Errors"
              example:
                type: urn:nvcf-worker-service:problem-details:unprocessable-entity
                title: Unprocessable Entity
                status: 422
                detail: string
                instance: "/v2/nvcf/pexec/functions/bc205f8e-1740-40df-8d32-c4321763498a"
                requestId: 3fa85f64-5717-4562-b3fc-2c963f66afa6
        '500':
          description: The invocation ended with an error.
          content:
            application/json:
              schema:
                "$ref": "#/components/schemas/Errors"
              example:
                type: urn:nvcf-worker-service:problem-details:internal-server-error
                title: Internal Server Error
                status: 500
                detail: string
                instance: "/v2/nvcf/pexec/functions/bc205f8e-1740-40df-8d32-c4321763498a"
                requestId: 3fa85f64-5717-4562-b3fc-2c963f66afa6
security:
- Token: []
components:
  securitySchemes:
    Token:
      type: http
      scheme: bearer
  schemas:
    NIMAssetInfoResponse:
      properties:
        assetName:
          type: string
          title: Assetname
          description: The name of the asset used by NIMs.
        url:
          type: string
          title: Url
          description: The url of the asset being used.
        checksum:
          type: string
          title: Checksum
          description: The unique identifier for asset.
      type: object
      required:
      - assetName
      - url
      - checksum
      title: NIMAssetInfoResponse
    NIMHealthSuccessResponse:
      properties:
        object:
          type: string
          title: Object
          default: health.response
        message:
          type: string
          title: Message
      type: object
      required:
      - message
      title: NIMHealthSuccessResponse
    NIMLicenseInfoResponse:
      properties:
        name:
          type: string
          title: Name
          description: The name of the NIMs license.
        path:
          type: string
          title: Path
          description: The path of the NIMs license file inside the container.
        sha:
          type: string
          title: Sha
          description: The unique identifier of the license.
        size:
          type: integer
          title: Size
          description: The size of the license file in bytes.
        url:
          type: string
          title: Url
          description: The url of the NIMs license.
        type:
          type: string
          title: Type
          description: The content type of the license.
        content:
          type: string
          title: Content
          description: The content inside the NIMs license file.
      type: object
      required:
      - name
      - path
      - sha
      - size
      - url
      - type
      - content
      title: NIMLicenseInfoResponse
    NIMMetadataResponse:
      properties:
        version:
          type: string
          title: version
          description: The version of the NIM service.
        modelInfo:
          items:
            $ref: '#/components/schemas/NIMModelInfoResponse'
          type: array
          title: Modelinfo
          description: The list of information of models being served inside NIMs
            container
          default: []
        assetInfo:
          items:
            $ref: '#/components/schemas/NIMAssetInfoResponse'
          type: array
          title: Assetinfo
          description: The list of different assets used by the NIMs
          default: []
        licenseInfo:
          allOf:
          - $ref: '#/components/schemas/NIMLicenseInfoResponse'
          description: The information of the license of released NIMs
      type: object
      required:
      - version
      - licenseInfo
      title: NIMMetadataResponse
    NIMModelInfoResponse:
      properties:
        shortName:
          type: string
          title: Shortname
          description: The name of the model served by NIMs
        modelUrl:
          type: string
          title: Modelurl
          description: The URL from which the model is downloaded.
      type: object
      required:
      - shortName
      - modelUrl
      title: NIMModelInfoResponse
    EmbeddingsRequest:
      additionalProperties: false
      properties:
        input:
          oneOf:
          - type: string
            title: string
            example: "This is a test."
            pattern: ^.*$
          - type: array
            items:
              type: string
              pattern: ^.*$
            maxItems: 64
          title: Input
          description: 'The list of images or texts that you want to generate embeddings
            for. Images should be in form of `data:image/{format};base64,{base64encodedimage}`.
            If the size of an image is more than 200KB, it needs to be uploaded to
            a presigned S3 bucket using NVCF Asset APIs. Once uploaded you can refer
            to it using the following format: `<img src="data:image/png;asset_id,{asset_id}"
            />`. Accepted formats are `jpg`, `png` and `jpeg`.'
          examples:
          - - The quick brown fox jumped over the lazy dog
            - data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAIAAACQd1PeAAAAEElEQVR4nGK6HcwNCAAA//8DTgE8HuxwEQAAAABJRU5ErkJggg==
          - - The quick brown fox jumped over the lazy dog
            - data:image/png;asset_id,87b132b0-08f9-43ea-8fab-f107350a5d00
        encoding_format:
          type: string
          enum:
          - float
          - base64
          title: Encoding Format
          description: "The format to return the embeddings in. Can be either `float` or `base64`."
          default: float
        model:
          type: string
          enum: [nvidia/nvclip-vit-h-14]
          title: Model
          description: ID of the embedding model.
          examples: nvidia/nvclip-vit-h-14
      type: object
      required:
        - input
        - model
      title: EmbeddingsRequest
    EmbeddingsResponse:
      type: object
      properties:
        object:
          description: 'The object type, which is always `list`.'
          enum:
            - list
          title: Object
          type: string
        data:
          items:
            "$ref": "#/components/schemas/Embedding"
          type: array
          title: Data
          description: The list of embeddings generated by the model.
          maxItems: 128
          examples:
          - - embedding:
              - 0.1
              - 0.1
              - 0.1
              index: 0
              object: embedding
            - embedding:
              - 0.1
              - 0.1
              - 0.1
              index: 1
              object: embedding
        model:
          type: string
          description: Model used to generate embeddings.
          example: nvidia/nvclip-vit-h-14
          title: Model
          const: nvidia/nvclip-vit-h-14
        usage:
          allOf:
          - "$ref": "#/components/schemas/Usage"
          description: Usage statistics for the embeddings request.
          examples:
          - num_images: 1
            prompt_tokens: 80
            total_tokens: 80
      required:
        - object
        - data
        - usage
        - model
      title: EmbeddingsResponse
    Embedding:
      type: object
      description: Represents an embedding vector returned by embedding endpoint.
      properties:
        object:
          description: 'The object type, which is always `embedding`.'
          enum:
           - embedding
          title: Object
          type: string
        index:
          type: integer
          format: int32
          title: Index
          description: The index of the embedding in the list of embeddings.
          minimum: 0
          maximum: 127
        embedding:
          oneOf:
            - type: array
              description: |
                The embedding vector as a list of floats, The length of the vector depends on the model.
              items:
                - type: number
              maxItems: 1024
            - type: string
              description: |
                The embedding vector as base64 string. The length of the vector depends on the model.
              format: ^(?:[A-Za-z0-9+/]{4})*(?:[A-Za-z0-9+/]{4}|[A-Za-z0-9+/]{3}=|[A-Za-z0-9+/]{2}==)$
        title: Embedding
      required:
        - index
        - object
        - embedding
      title: Embeddings
    Usage:
      properties:
        num_images:
          type: integer
          format: int32
          title: Num Images
          minimum: 0
          maximum: 64
          description: Number of images passed.
        prompt_tokens:
          type: integer
          format: int32
          title: Prompt Tokens
          description: Number of tokens in the prompt.
          minimum: 77
          maximum: 4928
        total_tokens:
          type: integer
          format: int32
          title: Total Tokens
          description: Total number of tokens used in the request.
          minimum: 77
          maximum: 4928
      type: object
      required:
        - num_images
        - prompt_tokens
        - total_tokens
      title: Usage
    Errors:
      properties:
        type:
          type: string
          format: "^.{1, 128}$"
          maxLength: 128
          description: Error type
        title:
          type: string
          format: "^.{1, 128}$"
          maxLength: 128
          description: Error title
        status:
          type: integer
          format: int32
          minimum: 100
          maximum: 999
          description: Error status code
        detail:
          type: string
          format: "^.{1, 1024}$"
          maxLength: 1024
          description: Detailed information about the error
        instance:
          type: string
          format: "^.{1, 256}$"
          maxLength: 256
          description: Function instance used to invoke the request
        requestId:
          type: string
          format: uuid
          maxLength: 36
          description: UUID of the request
      type: object
      required:
        - type
        - title
        - status
        - detail
        - instance
        - requestId
      title: InvokeError
