use crate::{Embedding, EmbeddingProvider, TextToEmbed};use anyhow::Result;use futures::{future::BoxFuture, FutureExt};use http_client::HttpClient;pub use open_ai::OpenAiEmbeddingModel;use std::sync::Arc; pub struct OpenAiEmbeddingProvider {    client: Arc<dyn HttpClient>,    model: OpenAiEmbeddingModel,    api_url: String,    api_key: String,} impl OpenAiEmbeddingProvider {    pub fn new(        client: Arc<dyn HttpClient>,        model: OpenAiEmbeddingModel,        api_url: String,        api_key: String,    ) -> Self {        Self {            client,            model,            api_url,            api_key,        }    }} impl EmbeddingProvider for OpenAiEmbeddingProvider {    fn embed<'a>(&'a self, texts: &'a [TextToEmbed<'a>]) -> BoxFuture<'a, Result<Vec<Embedding>>> {        let embed = open_ai::embed(            self.client.as_ref(),            &self.api_url,            &self.api_key,            self.model,            texts.iter().map(|to_embed| to_embed.text),        );        async move {            let response = embed.await?;            Ok(response                .data                .into_iter()                .map(|data| Embedding::new(data.embedding))                .collect())        }        .boxed()    }     fn batch_size(&self) -> usize {        // From https://platform.openai.com/docs/api-reference/embeddings/create        2048    }}