object Embeddings
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- class Live extends Embeddings
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- def createEmbedding(input: Input, model: Model, encodingFormat: Optional[EncodingFormat] = Optional.Absent, dimensions: Optional[Dimensions] = Optional.Absent, user: Optional[String] = Optional.Absent): ZIO[Embeddings, OpenAIFailure, CreateEmbeddingResponse]
Creates an embedding vector representing the input text.
Creates an embedding vector representing the input text.
- input
Input text to embed, encoded as a string or array of tokens. To embed multiple inputs in a single request, pass an array of strings or array of token arrays. The input must not exceed the max input tokens for the model (8192 tokens for
text-embedding-ada-002), cannot be an empty string, and any array must be 2048 dimensions or less. [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for counting tokens.- model
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.
- encodingFormat
The format to return the embeddings in. Can be either
floator [base64](https://pypi.org/project/pybase64/).- dimensions
The number of dimensions the resulting output embeddings should have. Only supported in
text-embedding-3and later models.- user
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).
- def createEmbedding(body: CreateEmbeddingRequest): ZIO[Embeddings, OpenAIFailure, CreateEmbeddingResponse]
Creates an embedding vector representing the input text.
- def default: ZLayer[Any, Throwable, Embeddings]
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- def live: ZLayer[Client, Nothing, Embeddings]
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