chore(api): remove deprecated embeddings impls

docs/_static/llama-stack-spec.yaml

@@ -616,39 +616,6 @@ paths:
           required: true
           schema:
             type: string
-  /v1/inference/embeddings:
-    post:
-      responses:
-        '200':
-          description: >-
-            An array of embeddings, one for each content. Each embedding is a list
-            of floats. The dimensionality of the embedding is model-specific; you
-            can check model metadata using /models/{model_id}.
-          content:
-            application/json:
-              schema:
-                $ref: '#/components/schemas/EmbeddingsResponse'
-        '400':
-          $ref: '#/components/responses/BadRequest400'
-        '429':
-          $ref: >-
-            #/components/responses/TooManyRequests429
-        '500':
-          $ref: >-
-            #/components/responses/InternalServerError500
-        default:
-          $ref: '#/components/responses/DefaultError'
-      tags:
-        - Inference
-      description: >-
-        Generate embeddings for content pieces using the specified model.
-      parameters: []
-      requestBody:
-        content:
-          application/json:
-            schema:
-              $ref: '#/components/schemas/EmbeddingsRequest'
-        required: true
   /v1/eval/benchmarks/{benchmark_id}/evaluations:
     post:
       responses:
@@ -7173,72 +7140,6 @@ components:
       title: OpenAIDeleteResponseObject
       description: >-
         Response object confirming deletion of an OpenAI response.
-    EmbeddingsRequest:
-      type: object
-      properties:
-        model_id:
-          type: string
-          description: >-
-            The identifier of the model to use. The model must be an embedding model
-            registered with Llama Stack and available via the /models endpoint.
-        contents:
-          oneOf:
-            - type: array
-              items:
-                type: string
-            - type: array
-              items:
-                $ref: '#/components/schemas/InterleavedContentItem'
-          description: >-
-            List of contents to generate embeddings for. Each content can be a string
-            or an InterleavedContentItem (and hence can be multimodal). The behavior
-            depends on the model and provider. Some models may only support text.
-        text_truncation:
-          type: string
-          enum:
-            - none
-            - start
-            - end
-          description: >-
-            (Optional) Config for how to truncate text for embedding when text is
-            longer than the model's max sequence length.
-        output_dimension:
-          type: integer
-          description: >-
-            (Optional) Output dimensionality for the embeddings. Only supported by
-            Matryoshka models.
-        task_type:
-          type: string
-          enum:
-            - query
-            - document
-          description: >-
-            (Optional) How is the embedding being used? This is only supported by
-            asymmetric embedding models.
-      additionalProperties: false
-      required:
-        - model_id
-        - contents
-      title: EmbeddingsRequest
-    EmbeddingsResponse:
-      type: object
-      properties:
-        embeddings:
-          type: array
-          items:
-            type: array
-            items:
-              type: number
-          description: >-
-            List of embedding vectors, one per input content. Each embedding is a
-            list of floats. The dimensionality of the embedding is model-specific;
-            you can check model metadata using /models/{model_id}
-      additionalProperties: false
-      required:
-        - embeddings
-      title: EmbeddingsResponse
-      description: >-
-        Response containing generated embeddings.
     AgentCandidate:
       type: object
       properties: