runs on mac

Cargo.lock

@@ -672,6 +672,7 @@ dependencies = [
  "log",
  "memory_caching",
  "ml_models",
+ "ml_weights_registry",
  "once_cell",
  "primitives",
  "rand 0.8.5",
@@ -6819,6 +6820,7 @@ dependencies = [
  "libloading 0.8.6",
  "log",
  "memory_caching",
+ "ml_weights_registry",
  "ndarray",
  "nvidia-checker",
  "once_cell",
@@ -6839,6 +6841,14 @@ dependencies = [
  "tokio-util",
 ]
 
+[[package]]
+name = "ml_weights_registry"
+version = "0.0.1"
+dependencies = [
+ "anyhow",
+ "const_format",
+]
+
 [[package]]
 name = "mockall"
 version = "0.12.1"

Cargo.toml

@@ -23,6 +23,8 @@ members = [
 
   # Desktop apps
   "crates/desktop/src-tauri",
+  "crates/desktop/ml_models",
+  "crates/desktop/ml_weights_registry",
 
   # Shared libraries
   "crates/lib/actix_cors_configs",

crates/desktop/ml_models/Cargo.toml

@@ -21,6 +21,7 @@ normal = ["my-workspace-hack"]
 # Internal
 filesys = { path = "../../lib/files/filesys" }
 memory_caching = { path = "../../lib/caching/memory_caching" }
+ml_weights_registry = { path = "../ml_weights_registry" }
 primitives = { path = "../../lib/data/primitives" }
 
 # Bypass cudarc issues on Windows https://github.com/coreylowman/cudarc/issues/332

crates/desktop/ml_models/src/ml/mod.rs

@@ -4,5 +4,4 @@ pub mod model_cache;
 pub mod model_config;
 pub mod model_file;
 pub mod prompt_cache;
-pub mod stable_diffusion;
-pub mod weights_registry;
+pub mod stable_diffusion;

crates/desktop/ml_models/src/ml/stable_diffusion/infer_clip_text_embeddings.rs

@@ -7,7 +7,7 @@ use candle_transformers::models::stable_diffusion;
 use std::path::{Path, PathBuf};
 
 use crate::ml::model_file::{ModelFile, StableDiffusionVersion};
-use crate::ml::weights_registry::weights::{CLIP_JSON, SDXL_TURBO_CLIP_TEXT_ENCODER, SDXL_TURBO_CLIP_TEXT_ENCODER_2};
+use ml_weights_registry::weights_registry::weights::{CLIP_JSON, SDXL_TURBO_CLIP_TEXT_ENCODER, SDXL_TURBO_CLIP_TEXT_ENCODER_2};
 use anyhow::Error as E;
 use candle_core::{DType, Device, Module, Tensor, D};
 use log::info;

crates/desktop/ml_models/src/ml/stable_diffusion/lcm_pipeline.rs

@@ -1,6 +1,15 @@
 use std::path::{Path, PathBuf};
 use std::sync::{Arc, RwLock, RwLockReadGuard, RwLockWriteGuard};
 
+use anyhow::{anyhow, Error as E, Result};
+use candle_core::{DType, Device, IndexOp, Tensor, D};
+use candle_nn::VarBuilder;
+use candle_transformers::models::stable_diffusion::StableDiffusionConfig;
+use candle_transformers::models::stable_diffusion::lcm::{LCMScheduler, LCMSchedulerConfig};
+use candle_transformers::models::stable_diffusion::unet_2d::BlockConfig;
+use candle_transformers::models::stable_diffusion::unet_2d::UNet2DConditionModel;
+use candle_transformers::models::stable_diffusion::unet_2d::UNet2DConditionModelConfig;
+use candle_transformers::models::stable_diffusion::vae::{AutoEncoderKL, DiagonalGaussianDistribution};
 use crate::ml::image::dynamic_image_to_tensor::dynamic_image_to_tensor;
 use crate::ml::image::tensor_to_image_buffer::{tensor_to_image_buffer, RgbImage};
 use crate::ml::model_cache::ModelCache;
@@ -10,18 +19,9 @@ use crate::ml::prompt_cache::PromptCache;
 use crate::ml::stable_diffusion::get_vae_scale::get_vae_scale;
 use crate::ml::stable_diffusion::infer_clip_text_embeddings::{infer_clip_text_embeddings, ClipArgs};
 use crate::ml::stable_diffusion::remap_lcm_strength_range::remap_lcm_strength_range;
-use crate::ml::weights_registry::weights::{LYKON_DEAMSHAPER_7_TEXT_ENCODER_FP16, LYKON_DEAMSHAPER_7_VAE, SIMIANLUO_LCM_DREAMSHAPER_V7_UNET};
-use anyhow::{anyhow, Error as E, Result};
-use candle_core::{DType, Device, IndexOp, Tensor, D};
-use candle_nn::VarBuilder;
-use candle_transformers::models::stable_diffusion::lcm::{LCMScheduler, LCMSchedulerConfig};
-use candle_transformers::models::stable_diffusion::unet_2d::BlockConfig;
-use candle_transformers::models::stable_diffusion::unet_2d::UNet2DConditionModel;
-use candle_transformers::models::stable_diffusion::unet_2d::UNet2DConditionModelConfig;
-use candle_transformers::models::stable_diffusion::vae::{AutoEncoderKL, DiagonalGaussianDistribution};
-use candle_transformers::models::stable_diffusion::StableDiffusionConfig;
 use image::DynamicImage;
 use log::info;
+use ml_weights_registry::weights_registry::weights::{LYKON_DEAMSHAPER_7_TEXT_ENCODER_FP16, LYKON_DEAMSHAPER_7_VAE, SIMIANLUO_LCM_DREAMSHAPER_V7_UNET};
 use rand::Rng;
 
 const DEFAULT_STRENGTH : f64 = 75.0;

crates/desktop/ml_weights_registry/Cargo.toml

@@ -0,0 +1,18 @@
+[package]
+name = "ml_weights_registry"
+edition = "2021"
+version = "0.0.1"
+authors = ["storyteller"]
+publish = false
+description = ""
+license = ""
+repository = ""
+
+[lib]
+name = "ml_weights_registry"
+path = "src/lib.rs"
+
+# External
+[dependencies]
+anyhow = "1.0"
+const_format = "0.2.34"

crates/desktop/ml_weights_registry/src/lib.rs

@@ -0,0 +1 @@
+pub mod weights_registry;

crates/desktop/ml_weights_registry/src/weights_registry/weight_descriptor_builder.rs

@@ -5,10 +5,10 @@ pub (super) const R2_BUCKET_URL : &str = "https://pub-bc5e2bc0cdee4bb5ae8fca9d64
 //  and variables (even if they're known to be &'static) and keep allocations static.
 macro_rules! weight {
     ($name: literal, $file_name:literal, $weight_function:expr) => {
-      $crate::ml::weights_registry::weight_descriptor::WeightDescriptor {
+      $crate::weights_registry::weight_descriptor::WeightDescriptor {
         name: $name,
         filename: $file_name,
-        r2_download_url: const_format::concatcp!(crate::ml::weights_registry::weight_descriptor_builder::R2_BUCKET_URL, $file_name),
+        r2_download_url: const_format::concatcp!(crate::weights_registry::weight_descriptor_builder::R2_BUCKET_URL, $file_name),
         function: $weight_function,
       }
     };

crates/desktop/ml_weights_registry/src/weights_registry/weights.rs

@@ -1,5 +1,5 @@
-use crate::ml::weights_registry::weight_descriptor::{WeightDescriptor, WeightFunction};
-use crate::ml::weights_registry::weight_descriptor_builder::weight;
+use crate::weights_registry::weight_descriptor::{WeightDescriptor, WeightFunction};
+use crate::weights_registry::weight_descriptor_builder::weight;
 
 pub const CLIP_JSON : WeightDescriptor = weight!(
   "CLIP",

crates/desktop/src-tauri/Cargo.toml

@@ -23,11 +23,12 @@ tauri-build = { version = "2.0.4", features = [] }
 # Internal
 filesys = { path = "../../lib/files/filesys" }
 memory_caching = { path = "../../lib/caching/memory_caching" }
+ml_weights_registry = { path = "../ml_weights_registry" }
 primitives = { path = "../../lib/data/primitives" }
 
 # Internal ML
 # TODO: Only on Windows and Linux
-ml_models = { path = "../ml_models" }
+ml_models = { path = "../ml_models", optional = true }
 
 # External
 #openssl = { version = "0.10", features = ["vendored"] }
@@ -62,6 +63,12 @@ libloading = "0.8.6"
 serial_test = "3.2.0"
 assertor = "0.0.3"
 
+[target.'cfg(target_os = "macos")'.features]
+default  = []
+
+[target.'cfg(not(target_os = "macos"))'.features]
+default  = ["dep:ml_models"]
+
 [profile.dev]
 incremental = true # Compile your binary in smaller steps.
 

crates/desktop/src-tauri/src/endpoints/realtime_image_endpoint.rs

@@ -1,17 +1,23 @@
+#[cfg(feature = "ml_models")]
+use {
+  ml_models::ml::stable_diffusion::lcm_pipeline::{lcm_pipeline, Args},
+};
+
 use crate::state::app_config::AppConfig;
 use crate::state::app_dir::AppDataRoot;
+use crate::stubs::model_cache::ModelCache;
+use crate::stubs::prompt_cache::PromptCache;
 use crate::utils::image::decode_base64_image::decode_base64_image;
+use crate::utils::image::encode_dynamic_image_base64_png::encode_dynamic_image_base64_png;
 use crate::utils::image::encode_rgb_image_base64_png::encode_rgb_image_base64_png;
 use image::imageops::FilterType;
 use image::{DynamicImage, RgbImage};
 use log::{error, info};
-use ml_models::ml::model_cache::ModelCache;
-use ml_models::ml::prompt_cache::PromptCache;
-use ml_models::ml::stable_diffusion::lcm_pipeline::{lcm_pipeline, Args};
-use ml_models::ml::weights_registry::weights::{CLIP_JSON, LYKON_DEAMSHAPER_7_TEXT_ENCODER_FP16, LYKON_DEAMSHAPER_7_VAE, SDXL_TURBO_CLIP_TEXT_ENCODER, SIMIANLUO_LCM_DREAMSHAPER_V7_UNET};
+use ml_weights_registry::weights_registry::weights::{CLIP_JSON, LYKON_DEAMSHAPER_7_TEXT_ENCODER_FP16, LYKON_DEAMSHAPER_7_VAE, SDXL_TURBO_CLIP_TEXT_ENCODER, SIMIANLUO_LCM_DREAMSHAPER_V7_UNET};
 use std::path::PathBuf;
 use tauri::{AppHandle, State};
 
+
 const PROMPT_FILENAME : &str = "prompt.txt";
 const PROMPT: &str = "shiba inu, cute dog, detailed, walking in a wooded forest, photorealistic, 8k";
 
@@ -43,27 +49,30 @@ pub async fn infer_image(
     .map_err(|err| format!("Couldn't hydrate image from base64: {}", err))?;
   
   // TODO(bt,2025-02-17): Running out of vram with full image buffer size
-  let image = image.resize(512, 512, FilterType::CatmullRom);
+  let mut image = image.resize(512, 512, FilterType::CatmullRom);
 
-  let result = do_infer_image(
-    &prompt, 
-    image, 
-    strength, 
-    &model_config, 
-    &model_cache, 
-    prompt_cache, 
-    &app_data_root
-  ).await;
-  
-  let image = match result {
-    Ok(image) => image,
-    Err(err) => {
-      error!("There was an error generating the image: {:?}", err);
-      return Err(format!("There was an error generating the image: {}", err));
-    }
-  };
+  #[cfg(feature = "ml_models")]
+  {
+    let result = infer_image_impl(
+      &prompt,
+      image,
+      strength,
+      &model_config,
+      &model_cache,
+      prompt_cache,
+      &app_data_root
+    ).await;
 
-  let bytes = encode_rgb_image_base64_png(image)
+    image = match result {
+      Ok(img) => DynamicImage::ImageRgb8(img),
+      Err(err) => {
+        error!("There was an error generating the image: {:?}", err);
+        return Err(format!("There was an error generating the image: {}", err));
+      }
+    };
+  }
+
+  let bytes = encode_dynamic_image_base64_png(image)
     .map_err(|err| format!("failure to encode image: {:?}", err))?;
 
   info!("Inference successful; image converted to base64, serving back to browser...");
@@ -71,7 +80,8 @@ pub async fn infer_image(
   Ok(bytes)
 }
 
-async fn do_infer_image(
+#[cfg(feature = "ml_models")]
+async fn infer_image_impl(
   prompt: &str,
   image: DynamicImage,
   strength: Option<f64>,

crates/desktop/src-tauri/src/endpoints/remove_background_endpoint.rs

@@ -1,37 +1,50 @@
 //! Adapted from https://github.com/dnanhkhoa/rust-background-removal
 
+#[cfg(feature = "ml_models")]
+use {
+  ml_models::ml::background_removal::onnx_session::onnx_session,
+  ml_models::ml::background_removal::remove_image_background::remove_image_background,
+};
+
 use crate::state::app_dir::AppDataRoot;
+use crate::stubs::model_cache::ModelCache;
+use crate::stubs::prompt_cache::PromptCache;
 use crate::utils::image::decode_base64_image::decode_base64_image;
 use crate::utils::image::encode_dynamic_image_base64_png::encode_dynamic_image_base64_png;
 use image::{imageops, DynamicImage};
 use log::{error, info};
-use ml_models::ml::background_removal::onnx_session::onnx_session;
-use ml_models::ml::background_removal::remove_image_background::remove_image_background;
-use ml_models::ml::model_cache::ModelCache;
-use ml_models::ml::weights_registry::weights::{DIS_MEDIUM_ONNX, SIMIANLUO_LCM_DREAMSHAPER_V7_UNET};
+use ml_weights_registry::weights_registry::weights::{DIS_MEDIUM_ONNX, SIMIANLUO_LCM_DREAMSHAPER_V7_UNET};
 use tauri::{AppHandle, State};
 
 /// This handler removes the background from an image.
 #[tauri::command]
 pub async fn remove_background(
   image: &str,
-  model_cache: State<'_, ModelCache>,
   app_data_root: State<'_, AppDataRoot>,
-  app: AppHandle,
 ) -> Result<String, String> {
   info!("remove_background endpoint called.");
 
-  let image = decode_base64_image(image)
-    .map_err(|err| format!("Couldn't hydrate image from base64: {}", err))?;
+  let mut image = decode_base64_image(image)
+      .map_err(|err| format!("Couldn't hydrate image from base64: {}", err))?;
 
-  let model_path = app_data_root.weights_dir().weight_path(&DIS_MEDIUM_ONNX);
-  
-  let image = remove_image_background(model_path, image)
-    .await
-    .map_err(|err| format!("Couldn't remove image from image: {}", err))?;
+  #[cfg(feature = "ml_models")]
+  {
+    image = remove_background_impl(&app_data_root, image).await?;
+  }
 
   let image = encode_dynamic_image_base64_png(image)
     .map_err(|err| format!("failure to encode image: {:?}", err))?;
 
   Ok(image)
 }
+
+#[cfg(feature = "ml_models")]
+async fn remove_background_impl(app_data_root: &AppDataRoot, image: DynamicImage) -> Result<DynamicImage, String> {
+  let model_path = app_data_root.weights_dir().weight_path(&DIS_MEDIUM_ONNX);
+
+  let image = remove_image_background(model_path, image)
+      .await
+      .map_err(|err| format!("Couldn't remove image from image: {}", err))?;
+
+  Ok(image)
+}

crates/desktop/src-tauri/src/endpoints/text_to_image_endpoint.rs

@@ -1,18 +1,24 @@
+#[cfg(feature = "ml_models")]
+use {
+  ml_models::ml::stable_diffusion::lcm_pipeline::{lcm_pipeline, Args},
+};
+
 use crate::state::app_config::AppConfig;
 use crate::state::app_dir::AppDataRoot;
+use crate::stubs::model_cache::ModelCache;
+use crate::stubs::prompt_cache::PromptCache;
 use crate::utils::image::decode_base64_image::decode_base64_image;
+use crate::utils::image::encode_dynamic_image_base64_png::encode_dynamic_image_base64_png;
 use crate::utils::image::encode_rgb_image_base64_png::encode_rgb_image_base64_png;
 use image::imageops::FilterType;
 use image::{DynamicImage, ImageReader, RgbImage};
 use log::{error, info};
-use ml_models::ml::model_cache::ModelCache;
-use ml_models::ml::prompt_cache::PromptCache;
-use ml_models::ml::stable_diffusion::lcm_pipeline::{lcm_pipeline, Args};
+use ml_weights_registry::weights_registry::weights::{CLIP_JSON, LYKON_DEAMSHAPER_7_TEXT_ENCODER_FP16, LYKON_DEAMSHAPER_7_VAE, SDXL_TURBO_CLIP_TEXT_ENCODER, SIMIANLUO_LCM_DREAMSHAPER_V7_UNET};
+
 use once_cell::sync::Lazy;
 use std::io::Cursor;
 use std::path::PathBuf;
 use tauri::{AppHandle, State};
-use ml_models::ml::weights_registry::weights::{CLIP_JSON, LYKON_DEAMSHAPER_7_TEXT_ENCODER_FP16, LYKON_DEAMSHAPER_7_VAE, SDXL_TURBO_CLIP_TEXT_ENCODER, SIMIANLUO_LCM_DREAMSHAPER_V7_UNET};
 
 const RANDOM_SEED: u32 = 42;
 
@@ -39,28 +45,31 @@ pub async fn text_to_image(
 ) -> Result<String, String> {
   info!("text_to_image endpoint called.");
 
-  let image = IMAGE.resize(512, 512, FilterType::CatmullRom);
+  let mut image = IMAGE.resize(512, 512, FilterType::CatmullRom);
 
-  let result = do_infer_image(
-    &prompt, 
-    image, 
-    Some(STRENGTH), 
-    &model_config, 
-    &model_cache, 
-    prompt_cache, 
-    app, 
-    &app_data_root
-  ).await;
-  
-  let image = match result {
-    Ok(image) => image,
-    Err(err) => {
-      error!("There was an error generating the image: {:?}", err);
-      return Err(format!("There was an error generating the image: {}", err));
-    }
-  };
+  #[cfg(feature = "ml_models")]
+  {
+    let result = text_to_image_impl(
+      &prompt,
+      image,
+      Some(STRENGTH),
+      &model_config,
+      &model_cache,
+      prompt_cache,
+      app,
+      &app_data_root
+    ).await;
 
-  let bytes = encode_rgb_image_base64_png(image)
+    image = match result {
+      Ok(img) => DynamicImage::ImageRgb8(img),
+      Err(err) => {
+        error!("There was an error generating the image: {:?}", err);
+        return Err(format!("There was an error generating the image: {}", err));
+      }
+    };
+  }
+
+  let bytes = encode_dynamic_image_base64_png(image)
     .map_err(|err| format!("failure to encode image: {:?}", err))?;
 
   info!("Inference successful; image converted to base64, serving back to browser...");
@@ -68,7 +77,8 @@ pub async fn text_to_image(
   Ok(bytes)
 }
 
-async fn do_infer_image(
+#[cfg(feature = "ml_models")]
+async fn text_to_image_impl(
   prompt: &str,
   image: DynamicImage,
   strength: Option<f64>,

crates/desktop/src-tauri/src/lib.rs

@@ -1,6 +1,7 @@
 pub mod endpoints;
 pub mod events;
 pub mod state;
+pub mod stubs;
 pub mod threads;
 pub mod transfer;
 pub mod utils;
@@ -11,10 +12,11 @@ use crate::endpoints::remove_background_endpoint::remove_background;
 use crate::endpoints::test_counter::test_counter;
 use crate::endpoints::text_to_image_endpoint::text_to_image;
 use crate::state::app_config::AppConfig;
+use crate::stubs::model_cache::ModelCache;
+use crate::stubs::prompt_cache::PromptCache;
 use crate::threads::downloader_thread::downloader_thread;
 use crate::utils::log_environment_details::log_environment_details;
-use ml_models::ml::model_cache::ModelCache;
-use ml_models::ml::prompt_cache::PromptCache;
+
 use tauri_plugin_log::Target;
 use tauri_plugin_log::TargetKind;
 
@@ -27,6 +29,7 @@ pub fn run() {
   let config = AppConfig::init()
     .expect("config should load");
 
+
   let prompt_cache = PromptCache::with_capacity(8)
     .expect("prompt cache should load");
 

crates/desktop/src-tauri/src/state/app_config.rs

@@ -1,7 +1,7 @@
 use crate::state::app_dir::AppDataRoot;
 use crate::state::os_platform::OsPlatform;
 use crate::state::yaml_config::YamlConfig;
-use ml_models::ml::model_config::ModelConfig;
+use crate::stubs::model_config::ModelConfig;
 
 const DEFAULT_SD_IMAGE_WIDTH: usize = 1024;
 const DEFAULT_SD_IMAGE_HEIGHT: usize = 1024;

crates/desktop/src-tauri/src/state/app_dir.rs

@@ -2,7 +2,7 @@ use crate::state::expanduser::expanduser;
 use crate::state::os_platform::OsPlatform;
 use anyhow::anyhow;
 use directories::UserDirs;
-use ml_models::ml::weights_registry::weight_descriptor::WeightDescriptor;
+use ml_weights_registry::weights_registry::weight_descriptor::WeightDescriptor;
 use std::path::{Path, PathBuf};
 use tempdir::TempDir;
 use tempfile::{Builder, NamedTempFile};

crates/desktop/src-tauri/src/stubs/mod.rs

@@ -0,0 +1,3 @@
+pub mod model_cache;
+pub mod model_config;
+pub mod prompt_cache;

crates/desktop/src-tauri/src/stubs/model_cache.rs

@@ -0,0 +1,14 @@
+#[cfg(feature = "ml_models")]
+use ml_models::ml::model_cache::ModelCache;
+
+#[cfg(not(feature = "ml_models"))]
+pub struct ModelCache {
+  // Intentionally left blank
+}
+
+#[cfg(not(feature = "ml_models"))]
+impl ModelCache {
+  pub fn new() -> Self {
+    Self {}
+  }
+}

crates/desktop/src-tauri/src/stubs/model_config.rs

@@ -0,0 +1,14 @@
+#[cfg(feature = "ml_models")]
+use ml_models::ml::model_config::ModelConfig;
+
+#[cfg(not(feature = "ml_models"))]
+pub struct ModelConfig {
+  // Intentionally left blank
+}
+
+#[cfg(not(feature = "ml_models"))]
+impl ModelConfig {
+  pub fn init() -> anyhow::Result<Self> {
+    Ok(Self {})
+  }
+}

crates/desktop/src-tauri/src/stubs/prompt_cache.rs

@@ -0,0 +1,15 @@
+
+#[cfg(feature = "ml_models")]
+pub use ml_models::ml::prompt_cache::PromptCache;
+
+#[cfg(not(feature = "ml_models"))]
+pub struct PromptCache {
+  // Intentionally left blank
+}
+
+#[cfg(not(feature = "ml_models"))]
+impl PromptCache {
+  pub fn with_capacity(capacity: usize) -> anyhow::Result<Self> {
+    Ok(Self {})
+  }
+}

crates/desktop/src-tauri/src/threads/downloader_thread.rs

@@ -1,11 +1,11 @@
 use crate::events::notification_event::{NotificationEvent, NotificationModelType};
 use crate::state::app_dir::AppDataRoot;
 use crate::transfer::download::{download_async, ProgressUpdate};
-use futures::stream::FuturesUnordered;
 use futures::StreamExt;
+use futures::stream::FuturesUnordered;
 use log::{debug, error, info};
-use ml_models::ml::weights_registry::weight_descriptor::WeightFunction;
-use ml_models::ml::weights_registry::weights::{CLIP_JSON, DIS_MEDIUM_ONNX, LYKON_DEAMSHAPER_7_TEXT_ENCODER_FP16, LYKON_DEAMSHAPER_7_VAE, SDXL_TURBO_CLIP_TEXT_ENCODER, SDXL_TURBO_CLIP_TEXT_ENCODER_2, SDXL_TURBO_UNET, SDXL_TURBO_VAE, SIMIANLUO_LCM_DREAMSHAPER_V7_UNET};
+use ml_weights_registry::weights_registry::weight_descriptor::WeightFunction;
+use ml_weights_registry::weights_registry::weights::{CLIP_JSON, DIS_MEDIUM_ONNX, LYKON_DEAMSHAPER_7_TEXT_ENCODER_FP16, LYKON_DEAMSHAPER_7_VAE, SDXL_TURBO_CLIP_TEXT_ENCODER, SDXL_TURBO_CLIP_TEXT_ENCODER_2, SDXL_TURBO_UNET, SDXL_TURBO_VAE, SIMIANLUO_LCM_DREAMSHAPER_V7_UNET};
 use std::collections::VecDeque;
 use std::path::PathBuf;
 use std::sync::mpsc::Receiver;

frontend/realtime/yarn.lock

@@ -222,11 +222,6 @@
   resolved "https://registry.npmjs.org/@emotion/unitless/-/unitless-0.7.5.tgz"
   integrity sha512-OWORNpfjMsSSUBVrRBVGECkhWcULOAJz9ZW8uK9qgxD+87M7jHRcvh/A96XXNhXTLmKcoYSQtBEX7lHMO7YRwg==
 
-"@esbuild/win32-x64@0.21.5":
-  version "0.21.5"
-  resolved "https://registry.npmjs.org/@esbuild/win32-x64/-/win32-x64-0.21.5.tgz"
-  integrity sha512-tQd/1efJuzPC6rCFwEvLtci/xNFcTZknmXs98FYDfGE4wP9ClFV98nyKrzJKVPMhdDnjzLhdUyMX4PsQAPjwIw==
-
 "@eslint-community/eslint-utils@^4.2.0", "@eslint-community/eslint-utils@^4.4.0":
   version "4.4.0"
   resolved "https://registry.npmjs.org/@eslint-community/eslint-utils/-/eslint-utils-4.4.0.tgz"
@@ -741,10 +736,10 @@
   resolved "https://registry.npmjs.org/@remix-run/router/-/router-1.19.1.tgz"
   integrity sha512-S45oynt/WH19bHbIXjtli6QmwNYvaz+vtnubvNpNDvUOoA/OWh6j1OikIP3G+v5GHdxyC6EXoChG3HgYGEUfcg==
 
-"@rollup/rollup-win32-x64-msvc@4.24.0":
+"@rollup/rollup-darwin-arm64@4.24.0":
   version "4.24.0"
-  resolved "https://registry.npmjs.org/@rollup/rollup-win32-x64-msvc/-/rollup-win32-x64-msvc-4.24.0.tgz"
-  integrity sha512-fbMkAF7fufku0N2dE5TBXcNlg0pt0cJue4xBRE2Qc5Vqikxr4VCgKj/ht6SMdFcOacVA9rqF70APJ8RN/4vMJw==
+  resolved "https://registry.npmjs.org/@rollup/rollup-darwin-arm64/-/rollup-darwin-arm64-4.24.0.tgz"
+  integrity sha512-bIv+X9xeSs1XCk6DVvkO+S/z8/2AMt/2lMqdQbMrmVpgFvXlmde9mLcbQpztXm1tajC3raFDqegsH18HQPMYtA==
 
 "@sigstore/bundle@^2.3.2":
   version "2.3.2"
@@ -816,10 +811,10 @@
   resolved "https://registry.npmjs.org/@tauri-apps/api/-/api-2.2.0.tgz"
   integrity sha512-R8epOeZl1eJEl603aUMIGb4RXlhPjpgxbGVEaqY+0G5JG9vzV/clNlzTeqc+NLYXVqXcn8mb4c5b9pJIUDEyAg==
 
-"@tauri-apps/cli-win32-x64-msvc@2.2.7":
+"@tauri-apps/cli-darwin-arm64@2.2.7":
   version "2.2.7"
-  resolved "https://registry.npmjs.org/@tauri-apps/cli-win32-x64-msvc/-/cli-win32-x64-msvc-2.2.7.tgz"
-  integrity sha512-ZB8Kw90j8Ld+9tCWyD2fWCYfIrzbQohJ4DJSidNwbnehlZzP7wAz6Z3xjsvUdKtQ3ibtfoeTqVInzCCEpI+pWg==
+  resolved "https://registry.npmjs.org/@tauri-apps/cli-darwin-arm64/-/cli-darwin-arm64-2.2.7.tgz"
+  integrity sha512-54kcpxZ3X1Rq+pPTzk3iIcjEVY4yv493uRx/80rLoAA95vAC0c//31Whz75UVddDjJfZvXlXZ3uSZ+bnCOnt0A==
 
 "@tauri-apps/cli@^2.2.7":
   version "2.2.7"
@@ -2082,6 +2077,11 @@ fs-minipass@^3.0.0, fs-minipass@^3.0.3:
   dependencies:
     minipass "^7.0.3"
 
+fsevents@~2.3.2, fsevents@~2.3.3:
+  version "2.3.3"
+  resolved "https://registry.npmjs.org/fsevents/-/fsevents-2.3.3.tgz"
+  integrity sha512-5xoDfX+fL7faATnagmWPpbFtwh/R77WmMMqqHGS65C3vvB0YHrgF+B1YmZ3441tMj5n63k0212XNoJwzlhffQw==
+
 function-bind@^1.1.2:
   version "1.1.2"
   resolved "https://registry.npmjs.org/function-bind/-/function-bind-1.1.2.tgz"