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use crate::Embed;
use crate::embeddings::{EmbeddingModel, EmbeddingsBuilder};
/// A provider client with embedding capabilities.
/// Clone is required for conversions between client types.
pub trait EmbeddingsClient {
/// The type of EmbeddingModel used by the Client
type EmbeddingModel: EmbeddingModel;
/// Create an embedding model with the given model.
///
/// # Example
/// ```no_run
/// use rig_core::prelude::*;
/// use rig_core::providers::openai::{Client, self};
///
/// # fn run() -> Result<(), Box<dyn std::error::Error>> {
/// // Initialize the OpenAI client
/// let openai = Client::new("your-open-ai-api-key")?;
///
/// let embedding_model = openai.embedding_model(openai::TEXT_EMBEDDING_3_LARGE);
/// # Ok(())
/// # }
/// ```
fn embedding_model(&self, model: impl Into<String>) -> Self::EmbeddingModel;
/// Create an embedding model with the given model identifier string and the number of dimensions in the embedding generated by the model.
/// Use this when the provider supports a model whose dimensionality is not
/// known by Rig.
///
/// # Example with OpenAI
/// ```no_run
/// use rig_core::prelude::*;
/// use rig_core::providers::openai::{Client, self};
///
/// # fn run() -> Result<(), Box<dyn std::error::Error>> {
/// // Initialize the OpenAI client
/// let openai = Client::new("your-open-ai-api-key")?;
///
/// let embedding_model = openai.embedding_model_with_ndims("model-unknown-to-rig", 3072);
/// # Ok(())
/// # }
/// ```
fn embedding_model_with_ndims(
&self,
model: impl Into<String>,
ndims: usize,
) -> Self::EmbeddingModel;
/// Create an embedding builder with the given embedding model.
///
/// # Example with OpenAI
/// ```no_run
/// use rig_core::prelude::*;
/// use rig_core::providers::openai::{Client, self};
///
/// # async fn run() -> Result<(), Box<dyn std::error::Error>> {
/// // Initialize the OpenAI client
/// let openai = Client::new("your-open-ai-api-key")?;
///
/// let embeddings = openai.embeddings(openai::TEXT_EMBEDDING_3_LARGE)
/// .documents(vec!["Hello, world!", "Goodbye, world!"])?
/// .build()
/// .await?;
/// # Ok(())
/// # }
/// ```
fn embeddings<D: Embed>(
&self,
model: impl Into<String>,
) -> EmbeddingsBuilder<Self::EmbeddingModel, D> {
EmbeddingsBuilder::new(self.embedding_model(model))
}
/// Create an embedding builder with the given name and the number of dimensions in the embedding generated by the model.
///
/// # Example with OpenAI
/// ```no_run
/// use rig_core::prelude::*;
/// use rig_core::providers::openai::{Client, self};
///
/// # async fn run() -> Result<(), Box<dyn std::error::Error>> {
/// // Initialize the OpenAI client
/// let openai = Client::new("your-open-ai-api-key")?;
///
/// let embeddings = openai.embeddings_with_ndims(openai::TEXT_EMBEDDING_3_LARGE, 3072)
/// .documents(vec!["Hello, world!", "Goodbye, world!"])?
/// .build()
/// .await?;
/// # Ok(())
/// # }
/// ```
fn embeddings_with_ndims<D: Embed>(
&self,
model: &str,
ndims: usize,
) -> EmbeddingsBuilder<Self::EmbeddingModel, D> {
EmbeddingsBuilder::new(self.embedding_model_with_ndims(model, ndims))
}
}