openai: appmixer.openai.core.createEmbedding

Basic Information

Name

appmixer.openai.core.createEmbedding

Version

1.0.0

Visibility

Public

Description

Creates an embedding vector representing the input text.

Properties

Field	Type	Description
No properties defined

Input Ports

in

Field	Type	Description
Input	text	The string that will be turned into an embedding. Example: This is a test.
Model	text	ID of the model to use. You can use the List models API to see all of your available models, or see our Model overview for descriptions of them. Example: text-embedding-ada-002
Encoding Format	select	The format to return the embeddings in. Can be either `float` or `base64`. Example: float
User	text	A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more. Example: user-1234

Output Ports

out

Field	Type	Description
Data		-
Model		-
Object		-
Usage		-
Usage Prompt Tokens		-
Usage Total Tokens		-

Full Metadata

#metadata-viewer { display: none; }{ "version": "1.0.0", "name": "appmixer.openai.core.createEmbedding", "author": "Appmixer <info@appmixer.com>", "description": "<label>Creates an embedding vector representing the input text.</label>", "private": false, "inPorts": [ { "name": "in", "schema": { "type": "object", "required": [ "model", "input" ], "properties": { "input": { "type": "string", "title": "string", "description": "The string that will be turned into an embedding.", "default": "", "example": "This is a test.", "path": "input" }, "model": { "description": "ID of the model to use. You can use the [List models](/docs/api-reference/models/list) API to see all of your available models, or see our [Model overview](/docs/models/overview) for descriptions of them.\n", "example": "text-embedding-ada-002", "x-oaiTypeLabel": "string", "type": "string", "path": "model" }, "encoding_format": { "description": "The format to return the embeddings in. Can be either `float` or [`base64`](https://pypi.org/project/pybase64/).", "example": "float", "default": "float", "type": "string", "enum": [ "float", "base64" ], "path": "encoding_format" }, "user": { "type": "string", "example": "user-1234", "description": "A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](/docs/guides/safety-best-practices/end-user-ids).\n", "path": "user" } } }, "inspector": { "inputs": { "input": { "type": "text", "index": 0, "label": "Input", "tooltip": "The string that will be turned into an embedding. Example: This is a test.", "defaultValue": "" }, "model": { "type": "text", "index": 1, "label": "Model", "tooltip": "ID of the model to use. You can use the <a href=\"https://platform.openai.com/docs/api-reference/models/list\" rel=\"noopener noreferrer\" target=\"_blank\">List models</a> API to see all of your available models, or see our <a href=\"https://platform.openai.com/docs/models/overview\" rel=\"noopener noreferrer\" target=\"_blank\">Model overview</a> for descriptions of them.\n Example: text-embedding-ada-002" }, "encoding_format": { "type": "select", "index": 2, "label": "Encoding Format", "tooltip": "The format to return the embeddings in. Can be either <code>float</code> or <a href=\"https://pypi.org/project/pybase64/\" rel=\"noopener noreferrer\" target=\"_blank\"><code>base64</code></a>. Example: float", "options": [ { "content": "float", "value": "float" }, { "content": "base64", "value": "base64" } ], "defaultValue": "float" }, "user": { "type": "text", "index": 3, "label": "User", "tooltip": "A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. <a href=\"https://platform.openai.com/docs/guides/safety-best-practices/end-user-ids\" rel=\"noopener noreferrer\" target=\"_blank\">Learn more</a>.\n Example: user-1234" } } } } ], "outPorts": [ { "name": "out", "options": [ { "label": "Data", "value": "data", "schema": { "type": "array", "description": "The list of embeddings generated by the model.", "items": { "type": "object", "description": "Represents an embedding vector returned by embedding endpoint.\n", "required": [ "index", "object", "embedding" ], "x-oaiMeta": { "name": "The embedding object", "example": "{\n \"object\": \"embedding\",\n \"embedding\": [\n 0.0023064255,\n -0.009327292,\n .... (1536 floats total for ada-002)\n -0.0028842222,\n ],\n \"index\": 0\n}\n" }, "properties": { "index": { "type": "integer", "description": "The index of the embedding in the list of embeddings." }, "embedding": { "type": "array", "description": "The embedding vector, which is a list of floats. The length of vector depends on the model as listed in the [embedding guide](/docs/guides/embeddings).\n", "items": { "type": "number" } }, "object": { "type": "string", "description": "The object type, which is always \"embedding\".", "enum": [ "embedding" ] } } }, "example": [ { "object": "embedding", "embedding": [ 0.0023, -0.0094, 0.0156 ], "index": 0 } ] } }, { "label": "Model", "value": "model", "schema": { "example": "text-embedding-ada-002" } }, { "label": "Object", "value": "object", "schema": { "example": "list" } }, { "label": "Usage", "value": "usage", "schema": { "example": "{}" } }, { "label": "Usage Prompt Tokens", "value": "usage.prompt_tokens", "schema": { "example": 8 } }, { "label": "Usage Total Tokens", "value": "usage.total_tokens", "schema": { "example": 8 } } ] } ], "properties": {}, "auth": { "service": "appmixer:openai" }, "icon": "data:image/svg+xml;base64,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" }