openapi: 3.0.3
info:
  title: Llama Platform Agent Data Embedding Model Configs API
  version: 0.1.0
tags:
- name: Embedding Model Configs
paths:
  /api/v1/embedding-model-configs:
    get:
      tags:
      - Embedding Model Configs
      summary: List Embedding Model Configs
      operationId: list_embedding_model_configs_api_v1_embedding_model_configs_get
      security:
      - HTTPBearer: []
      parameters:
      - name: project_id
        in: query
        required: false
        schema:
          anyOf:
          - type: string
            format: uuid
          - type: 'null'
          title: Project Id
      - name: organization_id
        in: query
        required: false
        schema:
          anyOf:
          - type: string
            format: uuid
          - type: 'null'
          title: Organization Id
      - name: session
        in: cookie
        required: false
        schema:
          anyOf:
          - type: string
          - type: 'null'
          title: Session
      responses:
        '200':
          description: Successful Response
          content:
            application/json:
              schema:
                type: array
                items:
                  $ref: '#/components/schemas/EmbeddingModelConfig'
                title: Response List Embedding Model Configs Api V1 Embedding Model Configs Get
        '422':
          description: Validation Error
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
    post:
      tags:
      - Embedding Model Configs
      summary: Create a new Embedding Model Configuration
      description: Create a new embedding model configuration within a specified project.
      operationId: create_embedding_model_config_api_v1_embedding_model_configs_post
      security:
      - HTTPBearer: []
      parameters:
      - name: project_id
        in: query
        required: false
        schema:
          anyOf:
          - type: string
            format: uuid
          - type: 'null'
          title: Project Id
      - name: organization_id
        in: query
        required: false
        schema:
          anyOf:
          - type: string
            format: uuid
          - type: 'null'
          title: Organization Id
      - name: session
        in: cookie
        required: false
        schema:
          anyOf:
          - type: string
          - type: 'null'
          title: Session
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/EmbeddingModelConfigCreate'
      responses:
        '201':
          description: Successful Response
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/EmbeddingModelConfig'
        '422':
          description: Validation Error
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
  /api/v1/embedding-model-configs/{embedding_model_config_id}:
    put:
      tags:
      - Embedding Model Configs
      summary: Update Embedding Model Config
      description: Update an embedding model config by ID.
      operationId: update_embedding_model_config_api_v1_embedding_model_configs__embedding_model_config_id__put
      security:
      - HTTPBearer: []
      parameters:
      - name: embedding_model_config_id
        in: path
        required: true
        schema:
          type: string
          format: uuid
          title: Embedding Model Config Id
      - name: project_id
        in: query
        required: false
        schema:
          anyOf:
          - type: string
            format: uuid
          - type: 'null'
          title: Project Id
      - name: organization_id
        in: query
        required: false
        schema:
          anyOf:
          - type: string
            format: uuid
          - type: 'null'
          title: Organization Id
      - name: session
        in: cookie
        required: false
        schema:
          anyOf:
          - type: string
          - type: 'null'
          title: Session
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/EmbeddingModelConfigUpdate'
      responses:
        '200':
          description: Successful Response
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/EmbeddingModelConfig'
        '422':
          description: Validation Error
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
    delete:
      tags:
      - Embedding Model Configs
      summary: Delete Embedding Model Config
      description: Delete an embedding model config by ID.
      operationId: delete_embedding_model_config_api_v1_embedding_model_configs__embedding_model_config_id__delete
      security:
      - HTTPBearer: []
      parameters:
      - name: embedding_model_config_id
        in: path
        required: true
        schema:
          type: string
          format: uuid
          title: Embedding Model Config Id
      - name: project_id
        in: query
        required: false
        schema:
          anyOf:
          - type: string
            format: uuid
          - type: 'null'
          title: Project Id
      - name: organization_id
        in: query
        required: false
        schema:
          anyOf:
          - type: string
            format: uuid
          - type: 'null'
          title: Organization Id
      - name: session
        in: cookie
        required: false
        schema:
          anyOf:
          - type: string
          - type: 'null'
          title: Session
      responses:
        '204':
          description: Successful Response
        '422':
          description: Validation Error
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
components:
  schemas:
    OpenAIEmbedding:
      properties:
        model_name:
          type: string
          title: Model Name
          description: The name of the OpenAI embedding model.
          default: text-embedding-ada-002
        embed_batch_size:
          type: integer
          maximum: 2048.0
          exclusiveMinimum: 0.0
          title: Embed Batch Size
          description: The batch size for embedding calls.
          default: 10
        num_workers:
          anyOf:
          - type: integer
          - type: 'null'
          title: Num Workers
          description: The number of workers to use for async embedding calls.
        additional_kwargs:
          additionalProperties: true
          type: object
          title: Additional Kwargs
          description: Additional kwargs for the OpenAI API.
        api_key:
          anyOf:
          - type: string
          - type: 'null'
          title: Api Key
          description: The OpenAI API key.
        api_base:
          anyOf:
          - type: string
          - type: 'null'
          title: Api Base
          description: The base URL for OpenAI API.
          default: https://api.openai.com/v1
        api_version:
          anyOf:
          - type: string
          - type: 'null'
          title: Api Version
          description: The version for OpenAI API.
          default: ''
        max_retries:
          type: integer
          minimum: 0.0
          title: Max Retries
          description: Maximum number of retries.
          default: 10
        timeout:
          type: number
          minimum: 0.0
          title: Timeout
          description: Timeout for each request.
          default: 60.0
        default_headers:
          anyOf:
          - additionalProperties:
              type: string
            type: object
          - type: 'null'
          title: Default Headers
          description: The default headers for API requests.
        reuse_client:
          type: boolean
          title: Reuse Client
          description: Reuse the OpenAI client between requests. When doing anything with large volumes of async API calls, setting this to false can improve stability.
          default: true
        dimensions:
          anyOf:
          - type: integer
          - type: 'null'
          title: Dimensions
          description: The number of dimensions on the output embedding vectors. Works only with v3 embedding models.
        class_name:
          type: string
          title: Class Name
          default: OpenAIEmbedding
      type: object
      title: OpenAIEmbedding
    GeminiEmbedding:
      properties:
        model_name:
          type: string
          title: Model Name
          description: The modelId of the Gemini model to use.
          default: models/embedding-001
        embed_batch_size:
          type: integer
          maximum: 2048.0
          exclusiveMinimum: 0.0
          title: Embed Batch Size
          description: The batch size for embedding calls.
          default: 10
        num_workers:
          anyOf:
          - type: integer
          - type: 'null'
          title: Num Workers
          description: The number of workers to use for async embedding calls.
        title:
          anyOf:
          - type: string
          - type: 'null'
          title: Title
          description: Title is only applicable for retrieval_document tasks, and is used to represent a document title. For other tasks, title is invalid.
          default: ''
        task_type:
          anyOf:
          - type: string
          - type: 'null'
          title: Task Type
          description: The task for embedding model.
          default: retrieval_document
        api_key:
          anyOf:
          - type: string
          - type: 'null'
          title: Api Key
          description: API key to access the model. Defaults to None.
        api_base:
          anyOf:
          - type: string
          - type: 'null'
          title: Api Base
          description: API base to access the model. Defaults to None.
        transport:
          anyOf:
          - type: string
          - type: 'null'
          title: Transport
          description: Transport to access the model. Defaults to None.
        output_dimensionality:
          anyOf:
          - type: integer
          - type: 'null'
          title: Output Dimensionality
          description: Optional reduced dimension for output embeddings. Supported by models/text-embedding-004 and newer (e.g. gemini-embedding-001). Not supported by models/embedding-001.
        class_name:
          type: string
          title: Class Name
          default: GeminiEmbedding
      type: object
      title: GeminiEmbedding
    BedrockEmbedding:
      properties:
        model_name:
          type: string
          title: Model Name
          description: The modelId of the Bedrock model to use.
          default: amazon.titan-embed-text-v1
        embed_batch_size:
          type: integer
          maximum: 2048.0
          exclusiveMinimum: 0.0
          title: Embed Batch Size
          description: The batch size for embedding calls.
          default: 10
        num_workers:
          anyOf:
          - type: integer
          - type: 'null'
          title: Num Workers
          description: The number of workers to use for async embedding calls.
        profile_name:
          anyOf:
          - type: string
          - type: 'null'
          title: Profile Name
          description: The name of aws profile to use. If not given, then the default profile is used.
        aws_access_key_id:
          anyOf:
          - type: string
          - type: 'null'
          title: Aws Access Key Id
          description: AWS Access Key ID to use
        aws_secret_access_key:
          anyOf:
          - type: string
          - type: 'null'
          title: Aws Secret Access Key
          description: AWS Secret Access Key to use
        aws_session_token:
          anyOf:
          - type: string
          - type: 'null'
          title: Aws Session Token
          description: AWS Session Token to use
        region_name:
          anyOf:
          - type: string
          - type: 'null'
          title: Region Name
          description: AWS region name to use. Uses region configured in AWS CLI if not passed
        max_retries:
          type: integer
          exclusiveMinimum: 0.0
          title: Max Retries
          description: The maximum number of API retries.
          default: 10
        timeout:
          type: number
          title: Timeout
          description: The timeout for the Bedrock API request in seconds. It will be used for both connect and read timeouts.
          default: 60.0
        additional_kwargs:
          additionalProperties: true
          type: object
          title: Additional Kwargs
          description: Additional kwargs for the bedrock client.
        class_name:
          type: string
          title: Class Name
          default: BedrockEmbedding
      type: object
      title: BedrockEmbedding
    HTTPValidationError:
      properties:
        detail:
          items:
            $ref: '#/components/schemas/ValidationError'
          type: array
          title: Detail
      type: object
      title: HTTPValidationError
    OpenAIEmbeddingConfig:
      properties:
        type:
          type: string
          const: OPENAI_EMBEDDING
          title: Type
          description: Type of the embedding model.
          default: OPENAI_EMBEDDING
        component:
          $ref: '#/components/schemas/OpenAIEmbedding'
          description: Configuration for the OpenAI embedding model.
      type: object
      title: OpenAIEmbeddingConfig
    HuggingFaceInferenceAPIEmbedding:
      properties:
        model_name:
          anyOf:
          - type: string
          - type: 'null'
          title: Model Name
          description: Hugging Face model name. If None, the task will be used.
        embed_batch_size:
          type: integer
          maximum: 2048.0
          exclusiveMinimum: 0.0
          title: Embed Batch Size
          description: The batch size for embedding calls.
          default: 10
        num_workers:
          anyOf:
          - type: integer
          - type: 'null'
          title: Num Workers
          description: The number of workers to use for async embedding calls.
        pooling:
          anyOf:
          - $ref: '#/components/schemas/Pooling'
          - type: 'null'
          description: Pooling strategy. If None, the model's default pooling is used.
          default: cls
        query_instruction:
          anyOf:
          - type: string
          - type: 'null'
          title: Query Instruction
          description: Instruction to prepend during query embedding.
        text_instruction:
          anyOf:
          - type: string
          - type: 'null'
          title: Text Instruction
          description: Instruction to prepend during text embedding.
        token:
          anyOf:
          - type: string
          - type: boolean
          - type: 'null'
          title: Token
          description: Hugging Face token. Will default to the locally saved token. Pass token=False if you don’t want to send your token to the server.
        timeout:
          anyOf:
          - type: number
          - type: 'null'
          title: Timeout
          description: The maximum number of seconds to wait for a response from the server. Loading a new model in Inference API can take up to several minutes. Defaults to None, meaning it will loop until the server is available.
        headers:
          anyOf:
          - additionalProperties:
              type: string
            type: object
          - type: 'null'
          title: Headers
          description: Additional headers to send to the server. By default only the authorization and user-agent headers are sent. Values in this dictionary will override the default values.
        cookies:
          anyOf:
          - additionalProperties:
              type: string
            type: object
          - type: 'null'
          title: Cookies
          description: Additional cookies to send to the server.
        task:
          anyOf:
          - type: string
          - type: 'null'
          title: Task
          description: Optional task to pick Hugging Face's recommended model, used when model_name is left as default of None.
        class_name:
          type: string
          title: Class Name
          default: HuggingFaceInferenceAPIEmbedding
      type: object
      title: HuggingFaceInferenceAPIEmbedding
    EmbeddingModelConfig:
      properties:
        id:
          type: string
          format: uuid
          title: Id
          description: Unique identifier
        created_at:
          anyOf:
          - type: string
            format: date-time
          - type: 'null'
          title: Created At
          description: Creation datetime
        updated_at:
          anyOf:
          - type: string
            format: date-time
          - type: 'null'
          title: Updated At
          description: Update datetime
        name:
          type: string
          title: Name
          description: The name of the embedding model config.
        embedding_config:
          oneOf:
          - $ref: '#/components/schemas/AzureOpenAIEmbeddingConfig'
          - $ref: '#/components/schemas/CohereEmbeddingConfig'
          - $ref: '#/components/schemas/GeminiEmbeddingConfig'
          - $ref: '#/components/schemas/HuggingFaceInferenceAPIEmbeddingConfig'
          - $ref: '#/components/schemas/OpenAIEmbeddingConfig'
          - $ref: '#/components/schemas/VertexAIEmbeddingConfig'
          - $ref: '#/components/schemas/BedrockEmbeddingConfig'
          title: Embedding Config
          description: The embedding configuration for the embedding model config.
          discriminator:
            propertyName: type
            mapping:
              AZURE_EMBEDDING: '#/components/schemas/AzureOpenAIEmbeddingConfig'
              BEDROCK_EMBEDDING: '#/components/schemas/BedrockEmbeddingConfig'
              COHERE_EMBEDDING: '#/components/schemas/CohereEmbeddingConfig'
              GEMINI_EMBEDDING: '#/components/schemas/GeminiEmbeddingConfig'
              HUGGINGFACE_API_EMBEDDING: '#/components/schemas/HuggingFaceInferenceAPIEmbeddingConfig'
              OPENAI_EMBEDDING: '#/components/schemas/OpenAIEmbeddingConfig'
              VERTEXAI_EMBEDDING: '#/components/schemas/VertexAIEmbeddingConfig'
        project_id:
          type: string
          format: uuid
          title: Project Id
      type: object
      required:
      - id
      - name
      - embedding_config
      - project_id
      title: EmbeddingModelConfig
      description: Schema for an embedding model config.
    EmbeddingModelConfigCreate:
      properties:
        name:
          type: string
          title: Name
          description: The name of the embedding model config.
        embedding_config:
          oneOf:
          - $ref: '#/components/schemas/AzureOpenAIEmbeddingConfig'
          - $ref: '#/components/schemas/CohereEmbeddingConfig'
          - $ref: '#/components/schemas/GeminiEmbeddingConfig'
          - $ref: '#/components/schemas/HuggingFaceInferenceAPIEmbeddingConfig'
          - $ref: '#/components/schemas/OpenAIEmbeddingConfig'
          - $ref: '#/components/schemas/VertexAIEmbeddingConfig'
          - $ref: '#/components/schemas/BedrockEmbeddingConfig'
          title: Embedding Config
          description: The embedding configuration for the embedding model config.
          discriminator:
            propertyName: type
            mapping:
              AZURE_EMBEDDING: '#/components/schemas/AzureOpenAIEmbeddingConfig'
              BEDROCK_EMBEDDING: '#/components/schemas/BedrockEmbeddingConfig'
              COHERE_EMBEDDING: '#/components/schemas/CohereEmbeddingConfig'
              GEMINI_EMBEDDING: '#/components/schemas/GeminiEmbeddingConfig'
              HUGGINGFACE_API_EMBEDDING: '#/components/schemas/HuggingFaceInferenceAPIEmbeddingConfig'
              OPENAI_EMBEDDING: '#/components/schemas/OpenAIEmbeddingConfig'
              VERTEXAI_EMBEDDING: '#/components/schemas/VertexAIEmbeddingConfig'
      type: object
      required:
      - name
      - embedding_config
      title: EmbeddingModelConfigCreate
    CohereEmbeddingConfig:
      properties:
        type:
          type: string
          const: COHERE_EMBEDDING
          title: Type
          description: Type of the embedding model.
          default: COHERE_EMBEDDING
        component:
          $ref: '#/components/schemas/CohereEmbedding'
          description: Configuration for the Cohere embedding model.
      type: object
      title: CohereEmbeddingConfig
    Pooling:
      type: string
      enum:
      - cls
      - mean
      - last
      title: Pooling
      description: Enum of possible pooling choices with pooling behaviors.
    VertexAIEmbeddingConfig:
      properties:
        type:
          type: string
          const: VERTEXAI_EMBEDDING
          title: Type
          description: Type of the embedding model.
          default: VERTEXAI_EMBEDDING
        component:
          $ref: '#/components/schemas/VertexTextEmbedding'
          description: Configuration for the VertexAI embedding model.
      type: object
      title: VertexAIEmbeddingConfig
    EmbeddingModelConfigUpdate:
      properties:
        name:
          anyOf:
          - type: string
          - type: 'null'
          title: Name
          description: The name of the embedding model config.
        embedding_config:
          anyOf:
          - oneOf:
            - $ref: '#/components/schemas/AzureOpenAIEmbeddingConfig'
            - $ref: '#/components/schemas/CohereEmbeddingConfig'
            - $ref: '#/components/schemas/GeminiEmbeddingConfig'
            - $ref: '#/components/schemas/HuggingFaceInferenceAPIEmbeddingConfig'
            - $ref: '#/components/schemas/OpenAIEmbeddingConfig'
            - $ref: '#/components/schemas/VertexAIEmbeddingConfig'
            - $ref: '#/components/schemas/BedrockEmbeddingConfig'
            discriminator:
              propertyName: type
              mapping:
                AZURE_EMBEDDING: '#/components/schemas/AzureOpenAIEmbeddingConfig'
                BEDROCK_EMBEDDING: '#/components/schemas/BedrockEmbeddingConfig'
                COHERE_EMBEDDING: '#/components/schemas/CohereEmbeddingConfig'
                GEMINI_EMBEDDING: '#/components/schemas/GeminiEmbeddingConfig'
                HUGGINGFACE_API_EMBEDDING: '#/components/schemas/HuggingFaceInferenceAPIEmbeddingConfig'
                OPENAI_EMBEDDING: '#/components/schemas/OpenAIEmbeddingConfig'
                VERTEXAI_EMBEDDING: '#/components/schemas/VertexAIEmbeddingConfig'
          - type: 'null'
          title: Embedding Config
          description: The embedding configuration for the embedding model config.
      type: object
      title: EmbeddingModelConfigUpdate
    HuggingFaceInferenceAPIEmbeddingConfig:
      properties:
        type:
          type: string
          const: HUGGINGFACE_API_EMBEDDING
          title: Type
          description: Type of the embedding model.
          default: HUGGINGFACE_API_EMBEDDING
        component:
          $ref: '#/components/schemas/HuggingFaceInferenceAPIEmbedding'
          description: Configuration for the HuggingFace Inference API embedding model.
      type: object
      title: HuggingFaceInferenceAPIEmbeddingConfig
    GeminiEmbeddingConfig:
      properties:
        type:
          type: string
          const: GEMINI_EMBEDDING
          title: Type
          description: Type of the embedding model.
          default: GEMINI_EMBEDDING
        component:
          $ref: '#/components/schemas/GeminiEmbedding'
          description: Configuration for the Gemini embedding model.
      type: object
      title: GeminiEmbeddingConfig
    ValidationError:
      properties:
        loc:
          items:
            anyOf:
            - type: string
            - type: integer
          type: array
          title: Location
        msg:
          type: string
          title: Message
        type:
          type: string
          title: Error Type
        input:
          title: Input
        ctx:
          type: object
          title: Context
      type: object
      required:
      - loc
      - msg
      - type
      title: ValidationError
    VertexTextEmbedding:
      properties:
        model_name:
          type: string
          title: Model Name
          description: The modelId of the VertexAI model to use.
          default: textembedding-gecko@003
        embed_batch_size:
          type: integer
          maximum: 2048.0
          exclusiveMinimum: 0.0
          title: Embed Batch Size
          description: The batch size for embedding calls.
          default: 10
        num_workers:
          anyOf:
          - type: integer
          - type: 'null'
          title: Num Workers
          description: The number of workers to use for async embedding calls.
        location:
          type: string
          title: Location
          description: The default location to use when making API calls.
        project:
          type: string
          title: Project
          description: The default GCP project to use when making Vertex API calls.
        embed_mode:
          $ref: '#/components/schemas/VertexEmbeddingMode'
          description: The embedding mode to use.
          default: retrieval
        additional_kwargs:
          additionalProperties: true
          type: object
          title: Additional Kwargs
          description: Additional kwargs for the Vertex.
        client_email:
          anyOf:
          - type: string
          - type: 'null'
          title: Client Email
          description: The client email for the VertexAI credentials.
        token_uri:
          anyOf:
          - type: string
          - type: 'null'
          title: Token Uri
          description: The token URI for the VertexAI credentials.
        private_key_id:
          anyOf:
          - type: string
          - type: 'null'
          title: Private Key Id
          description: The private key ID for the VertexAI credentials.
        private_key:
          anyOf:
          - type: string
          - type: 'null'
          title: Private Key
          description: The private key for the VertexAI credentials.
        class_name:
          type: string
          title: Class Name
          default: VertexTextEmbedding
      type: object
      required:
      - location
      - project
      - client_email
      - token_uri
      - private_key_id
      - private_key
      title: VertexTextEmbedding
    CohereEmbedding:
      properties:
        model_name:
          type: string
          title: Model Name
          description: The modelId of the Cohere model to use.
          default: embed-english-v3.0
        embed_batch_size:
          type: integer
          maximum: 2048.0
          exclusiveMinimum: 0.0
          title: Embed Batch Size
          description: The batch size for embedding calls.
          default: 10
        num_workers:
          anyOf:
          - type: integer
          - type: 'null'
          title: Num Workers
          description: The number of workers to use for async embedding calls.
        api_key:
          anyOf:
          - type: string
          - type: 'null'
          title: Api Key
          description: The Cohere API key.
        truncate:
          type: string
          title: Truncate
          description: Truncation type - START/ END/ NONE
          default: END
        input_type:
          anyOf:
          - type: string
          - type: 'null'
          title: Input Type
          description: Model Input type. If not provided, search_document and search_query are used when needed.
        embedding_type:
          type: string
          title: Embedding Type
          description: Embedding type. If not provided float embedding_type is used when needed.
          default: float
        class_name:
          type: string
          title: Class Name
          default: CohereEmbedding
      type: object
      required:
      - api_key
      title: CohereEmbedding
    AzureOpenAIEmbeddingConfig:
      properties:
        type:
          type: string
          const: AZURE_EMBEDDING
          title: Type
          description: Type of the embedding model.
          default: AZURE_EMBEDDING
        component:
          $ref: '#/components/schemas/AzureOpenAIEmbedding'
          description: Configuration for the Azure OpenAI embedding model.
      type: object
      title: AzureOpenAIEmbeddingConfig
    VertexEmbeddingMode:
      type: string
      enum:
      - default
      - classification
      - clustering
      - similarity
      - retrieval
      title: VertexEmbeddingMode
      description: 'Copied from llama_index.embeddings.vertex.base.VertexEmbeddingMode

        since importing llama_index.embeddings.vertex.base incurs a lot of memory usage.'
    BedrockEmbeddingConfig:
      properties:
        type:
          type: string
          const: BEDROCK_EMBEDDING
          title: Type
          description: Type of the embedding model.
          default: BEDROCK_EMBEDDING
        component:
          $ref: '#/components/schemas/BedrockEmbedding'
          description: Configuration for the Bedrock embedding model.
      type: object
      title: BedrockEmbeddingConfig
    AzureOpenAIEmbedding:
      properties:
        model_name:
          type: string
          title: Model Name
          description: The name of the OpenAI embedding model.
          default: text-embedding-ada-002
        embed_batch_size:
          type: integer
          maximum: 2048.0
          exclusiveMinimum: 0.0
          title: Embed Batch Size
          description: The batch size for embedding calls.
          default: 10
        num_workers:
          anyOf:
          - type: integer
          - type: 'null'
          title: Num Workers
          description: The number of workers to use for async embedding calls.
        additional_kwargs:
          additionalProperties: true
          type: object
          title: Additional Kwargs
          description: Additional kwargs for the OpenAI API.
        api_key:
          anyOf:
          - type: string
          - type: 'null'
          title: Api Key
          description: The OpenAI API key.
        api_base:
          type: string
          title: Api Base
          description: The base URL for Azure deployment.
          default: ''
        api_version:
          type: string
          title: Api Version
          description: The version for Azure OpenAI API.
          default: ''
        max_retries:
          type: integer
          minimum: 0.0
          title: Max Retries
          description: Maximum number of retries.
          default: 10
        timeout:
          type: number
          minimum: 0.0
          title: Timeout
          description: Timeout for each request.
          default: 60.0
        default_headers:
          anyOf:
          - additionalProperties:
              type: string
            type: object
          - type: 'null'
          title: Default Headers
          description: The default headers for API requests.
        reuse_client:
          type: boolean
          title: Reuse Client
          description: Reuse the OpenAI client between requests. When doing anything with large volumes of async API calls, setting this to false can improve stability.
          default: true
        dimensions:
          anyOf:
          - type: integer
          - type: 'null'
          title: Dimensions
          description: The number of dimensions on the output embedding vectors. Works only with v3 embedding models.
        azure_endpoint:
          anyOf:
          - type: string
          - type: 'null'
          title: Azure Endpoint
          description: The Azure endpoint to use.
        azure_deployment:
          anyOf:
          - type: string
          - type: 'null'
          title: Azure Deployment
          description: The Azure deployment to use.
        class_name:
          type: string
          title: Class Name
          default: AzureOpenAIEmbedding
      type: object
      title: AzureOpenAIEmbedding
  securitySchemes:
    HTTPBearer:
      type: http
      scheme: bearer