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OpenAI compat embeddings API
This commit is contained in:
Hardik Shah
parent
2603f10f95
commit
f2c2a05f58
20 changed files with 706 additions and 0 deletions
176
docs/_static/llama-stack-spec.html
vendored
176
docs/_static/llama-stack-spec.html
vendored
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@ -3607,6 +3607,49 @@
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}
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}
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},
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"/v1/openai/v1/embeddings": {
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"post": {
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"responses": {
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"200": {
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"description": "An OpenAIEmbeddingsResponse containing the embeddings.",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/OpenAIEmbeddingsResponse"
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}
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}
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}
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},
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"400": {
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"$ref": "#/components/responses/BadRequest400"
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},
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"429": {
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"$ref": "#/components/responses/TooManyRequests429"
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},
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"500": {
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"$ref": "#/components/responses/InternalServerError500"
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},
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"default": {
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"$ref": "#/components/responses/DefaultError"
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}
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},
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"tags": [
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"Inference"
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],
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"description": "Generate OpenAI-compatible embeddings for the given input using the specified model.",
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"parameters": [],
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"requestBody": {
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/OpenaiEmbeddingsRequest"
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}
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}
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},
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"required": true
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}
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}
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},
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"/v1/openai/v1/models": {
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"get": {
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"responses": {
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@ -11767,6 +11810,139 @@
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"title": "OpenAICompletionChoice",
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"description": "A choice from an OpenAI-compatible completion response."
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},
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"OpenaiEmbeddingsRequest": {
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"type": "object",
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"properties": {
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"model": {
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"type": "string",
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"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."
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},
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"input": {
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"oneOf": [
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{
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"type": "string"
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},
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{
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"type": "array",
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"items": {
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"type": "string"
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}
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}
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],
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"description": "Input text to embed, encoded as a string or array of strings. To embed multiple inputs in a single request, pass an array of strings."
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},
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"encoding_format": {
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"type": "string",
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"description": "(Optional) The format to return the embeddings in. Can be either \"float\" or \"base64\". Defaults to \"float\"."
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},
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"dimensions": {
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"type": "integer",
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"description": "(Optional) The number of dimensions the resulting output embeddings should have. Only supported in text-embedding-3 and later models."
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},
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"user": {
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"type": "string",
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"description": "(Optional) A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse."
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}
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},
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"additionalProperties": false,
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"required": [
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"model",
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"input"
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],
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"title": "OpenaiEmbeddingsRequest"
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},
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"OpenAIEmbeddingData": {
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"type": "object",
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"properties": {
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"object": {
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"type": "string",
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"const": "embedding",
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"default": "embedding",
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"description": "The object type, which will be \"embedding\""
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},
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"embedding": {
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"oneOf": [
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{
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"type": "array",
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"items": {
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"type": "number"
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}
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},
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{
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"type": "string"
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}
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],
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"description": "The embedding vector as a list of floats (when encoding_format=\"float\") or as a base64-encoded string (when encoding_format=\"base64\")"
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},
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"index": {
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"type": "integer",
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"description": "The index of the embedding in the input list"
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}
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},
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"additionalProperties": false,
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"required": [
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"object",
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"embedding",
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"index"
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],
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"title": "OpenAIEmbeddingData",
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"description": "A single embedding data object from an OpenAI-compatible embeddings response."
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},
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"OpenAIEmbeddingUsage": {
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"type": "object",
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"properties": {
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"prompt_tokens": {
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"type": "integer",
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"description": "The number of tokens in the input"
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},
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"total_tokens": {
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"type": "integer",
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"description": "The total number of tokens used"
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}
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},
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"additionalProperties": false,
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"required": [
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"prompt_tokens",
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"total_tokens"
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],
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"title": "OpenAIEmbeddingUsage",
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"description": "Usage information for an OpenAI-compatible embeddings response."
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},
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"OpenAIEmbeddingsResponse": {
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"type": "object",
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"properties": {
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"object": {
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"type": "string",
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"const": "list",
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"default": "list",
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"description": "The object type, which will be \"list\""
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},
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"data": {
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"type": "array",
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"items": {
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"$ref": "#/components/schemas/OpenAIEmbeddingData"
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},
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"description": "List of embedding data objects"
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},
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"model": {
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"type": "string",
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"description": "The model that was used to generate the embeddings"
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},
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"usage": {
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"$ref": "#/components/schemas/OpenAIEmbeddingUsage",
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"description": "Usage information"
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}
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},
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"additionalProperties": false,
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"required": [
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"object",
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"data",
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"model",
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"usage"
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],
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"title": "OpenAIEmbeddingsResponse",
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"description": "Response from an OpenAI-compatible embeddings request."
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},
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"OpenAIModel": {
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"type": "object",
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"properties": {
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144
docs/_static/llama-stack-spec.yaml
vendored
144
docs/_static/llama-stack-spec.yaml
vendored
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@ -2520,6 +2520,38 @@ paths:
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schema:
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$ref: '#/components/schemas/OpenaiCompletionRequest'
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required: true
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/v1/openai/v1/embeddings:
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post:
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responses:
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'200':
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description: >-
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An OpenAIEmbeddingsResponse containing the embeddings.
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content:
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application/json:
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schema:
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$ref: '#/components/schemas/OpenAIEmbeddingsResponse'
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'400':
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$ref: '#/components/responses/BadRequest400'
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'429':
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$ref: >-
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#/components/responses/TooManyRequests429
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'500':
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$ref: >-
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#/components/responses/InternalServerError500
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default:
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$ref: '#/components/responses/DefaultError'
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tags:
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- Inference
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description: >-
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Generate OpenAI-compatible embeddings for the given input using the specified
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model.
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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/OpenaiEmbeddingsRequest'
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required: true
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/v1/openai/v1/models:
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get:
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responses:
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@ -8177,6 +8209,118 @@ components:
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title: OpenAICompletionChoice
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description: >-
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A choice from an OpenAI-compatible completion response.
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OpenaiEmbeddingsRequest:
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type: object
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properties:
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model:
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type: string
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description: >-
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The identifier of the model to use. The model must be an embedding model
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registered with Llama Stack and available via the /models endpoint.
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input:
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oneOf:
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- type: string
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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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Input text to embed, encoded as a string or array of strings. To embed
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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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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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dimensions:
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type: integer
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description: >-
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(Optional) The number of dimensions the resulting output embeddings should
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have. Only supported in text-embedding-3 and later models.
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user:
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type: string
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description: >-
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(Optional) A unique identifier representing your end-user, which can help
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OpenAI to monitor and detect abuse.
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additionalProperties: false
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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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OpenAIEmbeddingData:
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type: object
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properties:
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object:
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type: string
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const: embedding
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default: embedding
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description: >-
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The object type, which will be "embedding"
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embedding:
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oneOf:
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- type: array
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items:
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type: number
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- type: string
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description: >-
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The embedding vector as a list of floats (when encoding_format="float")
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or as a base64-encoded string (when encoding_format="base64")
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index:
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type: integer
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description: >-
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The index of the embedding in the input list
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additionalProperties: false
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required:
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- object
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- embedding
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- index
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title: OpenAIEmbeddingData
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description: >-
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A single embedding data object from an OpenAI-compatible embeddings response.
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OpenAIEmbeddingUsage:
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type: object
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properties:
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prompt_tokens:
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type: integer
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description: The number of tokens in the input
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total_tokens:
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type: integer
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description: The total number of tokens used
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additionalProperties: false
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required:
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- prompt_tokens
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- total_tokens
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title: OpenAIEmbeddingUsage
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description: >-
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Usage information for an OpenAI-compatible embeddings response.
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OpenAIEmbeddingsResponse:
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type: object
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properties:
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object:
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type: string
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const: list
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default: list
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description: The object type, which will be "list"
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data:
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type: array
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items:
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$ref: '#/components/schemas/OpenAIEmbeddingData'
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description: List of embedding data objects
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model:
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type: string
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description: >-
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The model that was used to generate the embeddings
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usage:
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$ref: '#/components/schemas/OpenAIEmbeddingUsage'
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description: Usage information
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additionalProperties: false
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required:
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- object
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- data
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- model
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- usage
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title: OpenAIEmbeddingsResponse
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description: >-
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Response from an OpenAI-compatible embeddings request.
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OpenAIModel:
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type: object
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properties:
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