Replace lazy_static! with OnceLock in ai crate (#8647)

This PR replaces a `lazy_static!` usage in the `ai` crate with
`OnceLock` from the standard library.

This allows us to drop the `lazy_static` dependency from this crate.

Release Notes:

- N/A

Cargo.lock

@@ -84,7 +84,6 @@ dependencies = [
  "gpui",
  "isahc",
  "language",
- "lazy_static",
  "log",
  "matrixmultiply",
  "ordered-float 2.10.0",

crates/ai/Cargo.toml

@@ -20,7 +20,6 @@ futures.workspace = true
 gpui.workspace = true
 isahc.workspace = true
 language.workspace = true
-lazy_static.workspace = true
 log.workspace = true
 matrixmultiply = "0.3.7"
 ordered-float.workspace = true

crates/ai/src/providers/open_ai/embedding.rs

@@ -8,7 +8,6 @@ use gpui::BackgroundExecutor;
 use isahc::http::StatusCode;
 use isahc::prelude::Configurable;
 use isahc::{AsyncBody, Response};
-use lazy_static::lazy_static;
 use parking_lot::{Mutex, RwLock};
 use parse_duration::parse;
 use postage::watch;
@@ -16,7 +15,7 @@ use serde::{Deserialize, Serialize};
 use serde_json;
 use std::env;
 use std::ops::Add;
-use std::sync::Arc;
+use std::sync::{Arc, OnceLock};
 use std::time::{Duration, Instant};
 use tiktoken_rs::{cl100k_base, CoreBPE};
 use util::http::{HttpClient, Request};
@@ -29,8 +28,9 @@ use crate::providers::open_ai::OpenAiLanguageModel;
 
 use crate::providers::open_ai::OPEN_AI_API_URL;
 
-lazy_static! {
+pub(crate) fn open_ai_bpe_tokenizer() -> &'static CoreBPE {
-    pub(crate) static ref OPEN_AI_BPE_TOKENIZER: CoreBPE = cl100k_base().unwrap();
+    static OPEN_AI_BPE_TOKENIZER: OnceLock<CoreBPE> = OnceLock::new();
+    OPEN_AI_BPE_TOKENIZER.get_or_init(|| cl100k_base().unwrap())
 }
 
 #[derive(Clone)]

crates/ai/src/providers/open_ai/model.rs

@@ -3,7 +3,7 @@ use tiktoken_rs::CoreBPE;
 
 use crate::models::{LanguageModel, TruncationDirection};
 
-use super::OPEN_AI_BPE_TOKENIZER;
+use super::open_ai_bpe_tokenizer;
 
 #[derive(Clone)]
 pub struct OpenAiLanguageModel {
@@ -13,8 +13,8 @@ pub struct OpenAiLanguageModel {
 
 impl OpenAiLanguageModel {
     pub fn load(model_name: &str) -> Self {
-        let bpe =
+        let bpe = tiktoken_rs::get_bpe_from_model(model_name)
-            tiktoken_rs::get_bpe_from_model(model_name).unwrap_or(OPEN_AI_BPE_TOKENIZER.to_owned());
+            .unwrap_or(open_ai_bpe_tokenizer().to_owned());
         OpenAiLanguageModel {
             name: model_name.to_string(),
             bpe: Some(bpe),