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feat(api)!: support extra_body to embeddings and vector_stores APIs (#3794)
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Applies the same pattern from https://github.com/llamastack/llama-stack/pull/3777 to embeddings and vector_stores.create() endpoints. This should _not_ be a breaking change since (a) our tests were already using the `extra_body` parameter when passing in to the backend (b) but the backend probably wasn't extracting the parameters correctly. This PR will fix that. Updated APIs: `openai_embeddings(), openai_create_vector_store(), openai_create_vector_store_file_batch()`
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26 changed files with 451 additions and 426 deletions
68
docs/static/stainless-llama-stack-spec.yaml
vendored
68
docs/static/stainless-llama-stack-spec.yaml
vendored
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@ -620,7 +620,7 @@ paths:
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content:
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application/json:
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schema:
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$ref: '#/components/schemas/OpenaiEmbeddingsRequest'
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$ref: '#/components/schemas/OpenAIEmbeddingsRequestWithExtraBody'
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required: true
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deprecated: false
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/v1/files:
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@ -2416,13 +2416,16 @@ paths:
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tags:
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- VectorIO
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summary: Creates a vector store.
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description: Creates a vector store.
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description: >-
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Creates a vector store.
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Generate an OpenAI-compatible vector store with the given parameters.
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parameters: []
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requestBody:
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content:
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application/json:
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schema:
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$ref: '#/components/schemas/OpenaiCreateVectorStoreRequest'
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$ref: '#/components/schemas/OpenAICreateVectorStoreRequestWithExtraBody'
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required: true
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deprecated: false
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/v1/vector_stores/{vector_store_id}:
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@ -2548,7 +2551,11 @@ paths:
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tags:
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- VectorIO
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summary: Create a vector store file batch.
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description: Create a vector store file batch.
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description: >-
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Create a vector store file batch.
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Generate an OpenAI-compatible vector store file batch for the given vector
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store.
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parameters:
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- name: vector_store_id
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in: path
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@ -2561,7 +2568,7 @@ paths:
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content:
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application/json:
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schema:
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$ref: '#/components/schemas/OpenaiCreateVectorStoreFileBatchRequest'
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$ref: '#/components/schemas/OpenAICreateVectorStoreFileBatchRequestWithExtraBody'
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required: true
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deprecated: false
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/v1/vector_stores/{vector_store_id}/file_batches/{batch_id}:
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@ -6242,7 +6249,7 @@ components:
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- deleted
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title: ConversationItemDeletedResource
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description: Response for deleted conversation item.
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OpenaiEmbeddingsRequest:
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OpenAIEmbeddingsRequestWithExtraBody:
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type: object
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properties:
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model:
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@ -6261,6 +6268,7 @@ components:
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multiple inputs in a single request, pass an array of strings.
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encoding_format:
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type: string
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default: float
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description: >-
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(Optional) The format to return the embeddings in. Can be either "float"
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or "base64". Defaults to "float".
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@ -6278,7 +6286,9 @@ components:
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required:
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- model
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- input
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title: OpenaiEmbeddingsRequest
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title: OpenAIEmbeddingsRequestWithExtraBody
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description: >-
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Request parameters for OpenAI-compatible embeddings endpoint.
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OpenAIEmbeddingData:
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type: object
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properties:
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@ -11057,19 +11067,18 @@ components:
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- metadata
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title: VectorStoreObject
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description: OpenAI Vector Store object.
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OpenaiCreateVectorStoreRequest:
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"OpenAICreateVectorStoreRequestWithExtraBody":
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type: object
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properties:
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name:
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type: string
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description: A name for the vector store.
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description: (Optional) A name for the vector store
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file_ids:
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type: array
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items:
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type: string
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description: >-
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A list of File IDs that the vector store should use. Useful for tools
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like `file_search` that can access files.
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List of file IDs to include in the vector store
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expires_after:
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type: object
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additionalProperties:
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@ -11081,7 +11090,7 @@ components:
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- type: array
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- type: object
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description: >-
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The expiration policy for a vector store.
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(Optional) Expiration policy for the vector store
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chunking_strategy:
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type: object
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additionalProperties:
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@ -11093,8 +11102,7 @@ components:
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- type: array
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- type: object
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description: >-
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The chunking strategy used to chunk the file(s). If not set, will use
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the `auto` strategy.
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(Optional) Strategy for splitting files into chunks
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metadata:
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type: object
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additionalProperties:
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@ -11106,21 +11114,12 @@ components:
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- type: array
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- type: object
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description: >-
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Set of 16 key-value pairs that can be attached to an object.
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embedding_model:
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type: string
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description: >-
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The embedding model to use for this vector store.
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embedding_dimension:
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type: integer
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description: >-
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The dimension of the embedding vectors (default: 384).
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provider_id:
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type: string
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description: >-
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The ID of the provider to use for this vector store.
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Set of key-value pairs that can be attached to the vector store
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additionalProperties: false
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title: OpenaiCreateVectorStoreRequest
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title: >-
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OpenAICreateVectorStoreRequestWithExtraBody
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description: >-
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Request to create a vector store with extra_body support.
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OpenaiUpdateVectorStoreRequest:
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type: object
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properties:
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@ -11241,7 +11240,7 @@ components:
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title: VectorStoreChunkingStrategyStaticConfig
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description: >-
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Configuration for static chunking strategy.
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OpenaiCreateVectorStoreFileBatchRequest:
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"OpenAICreateVectorStoreFileBatchRequestWithExtraBody":
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type: object
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properties:
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file_ids:
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@ -11249,7 +11248,7 @@ components:
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items:
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type: string
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description: >-
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A list of File IDs that the vector store should use.
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A list of File IDs that the vector store should use
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attributes:
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type: object
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additionalProperties:
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@ -11261,16 +11260,19 @@ components:
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- type: array
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- type: object
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description: >-
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(Optional) Key-value attributes to store with the files.
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(Optional) Key-value attributes to store with the files
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chunking_strategy:
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$ref: '#/components/schemas/VectorStoreChunkingStrategy'
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description: >-
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(Optional) The chunking strategy used to chunk the file(s). Defaults to
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auto.
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auto
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additionalProperties: false
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required:
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- file_ids
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title: OpenaiCreateVectorStoreFileBatchRequest
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title: >-
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OpenAICreateVectorStoreFileBatchRequestWithExtraBody
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description: >-
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Request to create a vector store file batch with extra_body support.
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VectorStoreFileBatchObject:
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type: object
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properties:
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