don't download sdxl anymore

stop downloading clip tokenizer from hf
vae wasn't cached in memory
2026-11-01 15:25:55 -05:00 · 2025-03-13 00:31:51 -04:00 · 2025-03-13 00:24:06 -04:00 · 2025-03-12 23:58:52 -04:00 · 2025-03-12 23:54:42 -04:00 · 2025-03-12 23:38:49 -04:00
63 changed files with 4031 additions and 1999 deletions
@@ -2,6 +2,7 @@
  <dictionary name="bt">
    <words>
      <w>arpabet</w>
+      <w>artcraft</w>
      <w>backfill</w>
      <w>backfilling</w>
      <w>backfills</w>
@@ -664,7 +664,11 @@ dependencies = [
 "candle-nn",
 "candle-transformers",
 "cudarc",
+ "directories 6.0.0",
+ "dirs 6.0.0",
 "filesys",
+ "futures 0.3.29",
+ "half",
 "hf-hub 0.3.2",
 "image",
 "libloading 0.8.6",
@@ -672,13 +676,19 @@ dependencies = [
 "memory_caching",
 "once_cell",
 "rand 0.8.5",
+ "reqwest 0.12.12",
 "serde",
 "serde_json",
 "serde_yaml",
+ "serial_test",
 "tauri",
 "tauri-build",
 "tauri-plugin-log",
+ "tempdir",
+ "tempfile",
 "tokenizers 0.15.2",
+ "tokio",
+ "tokio-util",
 ]

 [[package]]
@@ -1079,7 +1089,7 @@ dependencies = [
 "rustversion",
 "serde",
 "sync_wrapper 0.1.2",
- "tower",
+ "tower 0.4.13",
 "tower-layer",
 "tower-service",
 ]
@@ -1815,6 +1825,7 @@ dependencies = [
 "candle-flash-attn",
 "candle-nn",
 "fancy-regex",
+ "half",
 "intel-mkl-src",
 "num-traits",
 "rand 0.8.5",
@@ -2832,19 +2843,6 @@ dependencies = [
 "syn 2.0.87",
 ]

-[[package]]
-name = "dashmap"
-version = "5.5.3"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "978747c1d849a7d2ee5e8adc0159961c48fb7e5db2f06af6723b80123bb53856"
-dependencies = [
- "cfg-if 1.0.0",
- "hashbrown 0.14.5",
- "lock_api 0.4.12",
- "once_cell",
- "parking_lot_core 0.9.10",
-]
-
 [[package]]
 name = "dasp_sample"
 version = "0.11.0"
@@ -3187,6 +3185,15 @@ dependencies = [
 "dirs-sys 0.4.1",
 ]

+[[package]]
+name = "directories"
+version = "6.0.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "16f5094c54661b38d03bd7e50df373292118db60b585c08a411c6d840017fe7d"
+dependencies = [
+ "dirs-sys 0.5.0",
+]
+
 [[package]]
 name = "dirs"
 version = "5.0.1"
@@ -3316,7 +3323,7 @@ dependencies = [
 "google_drive_common",
 "hashing",
 "hostname 0.4.0",
- "hyper 1.3.1",
+ "hyper 1.6.0",
 "jobs_common",
 "log",
 "mimetypes",
@@ -3762,12 +3769,12 @@ dependencies = [

 [[package]]
 name = "errno"
-version = "0.3.9"
+version = "0.3.10"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "534c5cf6194dfab3db3242765c03bbe257cf92f22b38f6bc0c58d59108a820ba"
+checksum = "33d852cb9b869c2a9b3df2f71a3074817f01e1844f839a144f5fcef059a4eb5d"
 dependencies = [
 "libc",
- "windows-sys 0.52.0",
+ "windows-sys 0.59.0",
 ]

 [[package]]
@@ -3886,9 +3893,9 @@ dependencies = [

 [[package]]
 name = "fastrand"
-version = "2.1.0"
+version = "2.3.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "9fc0510504f03c51ada170672ac806f1f105a88aa97a5281117e1ddc3368e51a"
+checksum = "37909eebbb50d72f9059c3b6d82c0463f2ff062c9e95845c43a6c9c0355411be"

 [[package]]
 name = "fdeflate"
@@ -4616,6 +4623,18 @@ dependencies = [
 "wasm-bindgen",
 ]

+[[package]]
+name = "getrandom"
+version = "0.3.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "43a49c392881ce6d5c3b8cb70f98717b7c07aabbdff06687b9030dbfbe2725f8"
+dependencies = [
+ "cfg-if 1.0.0",
+ "libc",
+ "wasi 0.13.3+wasi-0.2.2",
+ "windows-targets 0.52.6",
+]
+
 [[package]]
 name = "getset"
 version = "0.1.4"
@@ -4762,7 +4781,7 @@ dependencies = [
 "errors",
 "jwt-simple",
 "my-workspace-hack",
- "reqwest 0.12.7",
+ "reqwest 0.12.12",
 "serde",
 "serde_derive",
 "serde_json",
@@ -4988,7 +5007,7 @@ dependencies = [
 "native-tls",
 "num_cpus",
 "rand 0.8.5",
- "reqwest 0.12.7",
+ "reqwest 0.12.12",
 "serde",
 "serde_json",
 "thiserror 2.0.11",
@@ -5192,9 +5211,9 @@ dependencies = [

 [[package]]
 name = "httparse"
-version = "1.8.0"
+version = "1.10.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d897f394bad6a705d5f4104762e116a75639e470d80901eed05a860a95cb1904"
+checksum = "6dbf3de79e51f3d586ab4cb9d5c3e2c14aa28ed23d180cf89b4df0454a69cc87"

 [[package]]
 name = "httpdate"
@@ -5234,9 +5253,9 @@ dependencies = [

 [[package]]
 name = "hyper"
-version = "1.3.1"
+version = "1.6.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "fe575dd17d0862a9a33781c8c4696a55c320909004a67a00fb286ba8b1bc496d"
+checksum = "cc2b571658e38e0c01b1fdca3bbbe93c00d3d71693ff2770043f8c29bc7d6f80"
 dependencies = [
 "bytes 1.10.0",
 "futures-channel",
@@ -5260,7 +5279,7 @@ checksum = "08afdbb5c31130e3034af566421053ab03787c640246a446327f550d11bcb333"
 dependencies = [
 "futures-util",
 "http 1.1.0",
- "hyper 1.3.1",
+ "hyper 1.6.0",
 "hyper-util",
 "rustls 0.23.13",
 "rustls-pki-types",
@@ -5303,7 +5322,7 @@ checksum = "70206fc6890eaca9fde8a0bf71caa2ddfc9fe045ac9e5c70df101a7dbde866e0"
 dependencies = [
 "bytes 1.10.0",
 "http-body-util",
- "hyper 1.3.1",
+ "hyper 1.6.0",
 "hyper-util",
 "native-tls",
 "tokio",
@@ -5313,20 +5332,19 @@ dependencies = [

 [[package]]
 name = "hyper-util"
-version = "0.1.5"
+version = "0.1.10"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "7b875924a60b96e5d7b9ae7b066540b1dd1cbd90d1828f54c92e02a283351c56"
+checksum = "df2dcfbe0677734ab2f3ffa7fa7bfd4706bfdc1ef393f2ee30184aed67e631b4"
 dependencies = [
 "bytes 1.10.0",
 "futures-channel",
 "futures-util",
 "http 1.1.0",
 "http-body 1.0.0",
- "hyper 1.3.1",
+ "hyper 1.6.0",
 "pin-project-lite",
 "socket2",
 "tokio",
- "tower",
 "tower-service",
 "tracing",
 ]
@@ -5563,7 +5581,7 @@ dependencies = [
 "rand 0.8.5",
 "redis_common",
 "redis_schema",
- "reqwest 0.12.7",
+ "reqwest 0.12.12",
 "serde",
 "serde_derive",
 "serde_json",
@@ -5971,7 +5989,7 @@ dependencies = [
 "chumsky",
 "email-encoding",
 "email_address",
- "fastrand 2.1.0",
+ "fastrand 2.3.0",
 "futures-util",
 "hostname 0.3.1",
 "httpdate",
@@ -6189,6 +6207,12 @@ version = "0.4.14"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "78b3ae25bc7c8c38cec158d1f2757ee79e9b3740fbc7ccf0e59e4b08d793fa89"

+[[package]]
+name = "linux-raw-sys"
+version = "0.9.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "6db9c683daf087dc577b7506e9695b3d556a9f3849903fa28186283afd6809e9"
+
 [[package]]
 name = "local-channel"
 version = "0.1.5"
@@ -6852,7 +6876,7 @@ dependencies = [
 "heck 0.4.1",
 "hmac 0.12.1",
 "hyper 0.14.28",
- "hyper 1.3.1",
+ "hyper 1.6.0",
 "hyper-util",
 "indexmap 2.2.6",
 "itertools 0.12.1",
@@ -6878,7 +6902,7 @@ dependencies = [
 "regex",
 "regex-automata",
 "regex-syntax",
- "reqwest 0.12.7",
+ "reqwest 0.12.12",
 "rsa",
 "rustls-pki-types",
 "semver 1.0.23",
@@ -6904,7 +6928,7 @@ dependencies = [
 "tokio",
 "tokio-stream",
 "tokio-util",
- "tower",
+ "tower 0.4.13",
 "tracing",
 "unicode-bidi",
 "unicode-normalization",
@@ -7557,7 +7581,7 @@ dependencies = [
 "base16ct",
 "base64 0.22.1",
 "chrono",
- "directories",
+ "directories 5.0.1",
 "flate2",
 "lazy_static",
 "log",
@@ -9269,9 +9293,9 @@ dependencies = [

 [[package]]
 name = "reqwest"
-version = "0.12.7"
+version = "0.12.12"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f8f4955649ef5c38cc7f9e8aa41761d48fb9677197daea9984dc54f56aad5e63"
+checksum = "43e734407157c3c2034e0258f5e4473ddb361b1e85f95a66690d67264d7cd1da"
 dependencies = [
 "base64 0.22.1",
 "bytes 1.10.0",
@@ -9283,7 +9307,7 @@ dependencies = [
 "http 1.1.0",
 "http-body 1.0.0",
 "http-body-util",
- "hyper 1.3.1",
+ "hyper 1.6.0",
 "hyper-rustls",
 "hyper-tls 0.6.0",
 "hyper-util",
@@ -9308,6 +9332,7 @@ dependencies = [
 "tokio-native-tls",
 "tokio-rustls",
 "tokio-util",
+ "tower 0.5.2",
 "tower-service",
 "url",
 "wasm-bindgen",
@@ -9502,7 +9527,7 @@ dependencies = [
 "minidom",
 "percent-encoding",
 "quick-xml 0.36.2",
- "reqwest 0.12.7",
+ "reqwest 0.12.12",
 "serde",
 "serde_derive",
 "serde_json",
@@ -9590,10 +9615,23 @@ dependencies = [
 "bitflags 2.5.0",
 "errno",
 "libc",
- "linux-raw-sys",
+ "linux-raw-sys 0.4.14",
 "windows-sys 0.52.0",
 ]

+[[package]]
+name = "rustix"
+version = "1.0.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "f7178faa4b75a30e269c71e61c353ce2748cf3d76f0c44c393f4e60abf49b825"
+dependencies = [
+ "bitflags 2.5.0",
+ "errno",
+ "libc",
+ "linux-raw-sys 0.9.2",
+ "windows-sys 0.59.0",
+]
+
 [[package]]
 name = "rustls"
 version = "0.21.12"
@@ -9725,6 +9763,15 @@ dependencies = [
 "winapi-util",
 ]

+[[package]]
+name = "scc"
+version = "2.3.3"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "ea091f6cac2595aa38993f04f4ee692ed43757035c36e67c180b6828356385b1"
+dependencies = [
+ "sdd",
+]
+
 [[package]]
 name = "schannel"
 version = "0.1.23"
@@ -9814,6 +9861,12 @@ dependencies = [
 "untrusted",
 ]

+[[package]]
+name = "sdd"
+version = "3.0.8"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "584e070911c7017da6cb2eb0788d09f43d789029b5877d3e5ecc8acf86ceee21"
+
 [[package]]
 name = "seahash"
 version = "4.1.0"
@@ -10134,23 +10187,23 @@ dependencies = [

 [[package]]
 name = "serial_test"
-version = "3.0.0"
+version = "3.2.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "953ad9342b3aaca7cb43c45c097dd008d4907070394bd0751a0aa8817e5a018d"
+checksum = "1b258109f244e1d6891bf1053a55d63a5cd4f8f4c30cf9a1280989f80e7a1fa9"
 dependencies = [
- "dashmap",
 "futures 0.3.29",
- "lazy_static",
 "log",
+ "once_cell",
 "parking_lot 0.12.2",
+ "scc",
 "serial_test_derive",
 ]

 [[package]]
 name = "serial_test_derive"
-version = "3.0.0"
+version = "3.2.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b93fb4adc70021ac1b47f7d45e8cc4169baaa7ea58483bc5b721d19a26202212"
+checksum = "5d69265a08751de7844521fd15003ae0a888e035773ba05695c5c759a6f89eef"
 dependencies = [
 "proc-macro2",
 "quote",
@@ -10833,7 +10886,7 @@ dependencies = [
 "redis_common",
 "redis_schema",
 "regex",
- "reqwest 0.12.7",
+ "reqwest 0.12.12",
 "reusable_types",
 "rust-s3",
 "serde",
@@ -11597,7 +11650,7 @@ dependencies = [
 "percent-encoding",
 "plist",
 "raw-window-handle",
- "reqwest 0.12.7",
+ "reqwest 0.12.12",
 "serde",
 "serde_json",
 "serde_repr",
@@ -11825,14 +11878,16 @@ dependencies = [

 [[package]]
 name = "tempfile"
-version = "3.10.1"
+version = "3.18.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "85b77fafb263dd9d05cbeac119526425676db3784113aa9295c88498cbf8bff1"
+checksum = "2c317e0a526ee6120d8dabad239c8dadca62b24b6f168914bbbc8e2fb1f0e567"
 dependencies = [
 "cfg-if 1.0.0",
- "fastrand 2.1.0",
- "rustix",
- "windows-sys 0.52.0",
+ "fastrand 2.3.0",
+ "getrandom 0.3.1",
+ "once_cell",
+ "rustix 1.0.2",
+ "windows-sys 0.59.0",
 ]

 [[package]]
@@ -11945,7 +12000,7 @@ dependencies = [
 "easyenv",
 "log",
 "my-workspace-hack",
- "reqwest 0.12.7",
+ "reqwest 0.12.12",
 "serde_json",
 ]

@@ -12399,7 +12454,7 @@ dependencies = [
 "prost",
 "tokio",
 "tokio-stream",
- "tower",
+ "tower 0.4.13",
 "tower-layer",
 "tower-service",
 "tracing",
@@ -12435,16 +12490,31 @@ dependencies = [
 ]

 [[package]]
-name = "tower-layer"
-version = "0.3.2"
+name = "tower"
+version = "0.5.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c20c8dbed6283a09604c3e69b4b7eeb54e298b8a600d4d5ecb5ad39de609f1d0"
+checksum = "d039ad9159c98b70ecfd540b2573b97f7f52c3e8d9f8ad57a24b916a536975f9"
+dependencies = [
+ "futures-core",
+ "futures-util",
+ "pin-project-lite",
+ "sync_wrapper 1.0.1",
+ "tokio",
+ "tower-layer",
+ "tower-service",
+]
+
+[[package]]
+name = "tower-layer"
+version = "0.3.3"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "121c2a6cda46980bb0fcd1647ffaf6cd3fc79a013de288782836f6df9c48780e"

 [[package]]
 name = "tower-service"
-version = "0.3.2"
+version = "0.3.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b6bc1c9ce2b5135ac7f93c72918fc37feb872bdc6a5533a8b85eb4b86bfdae52"
+checksum = "8df9b6e13f2d32c91b9bd719c00d1958837bc7dec474d94952798cc8e69eeec3"

 [[package]]
 name = "tracing"
@@ -12581,7 +12651,7 @@ dependencies = [
 "google_drive_common",
 "hashing",
 "hostname 0.4.0",
- "hyper 1.3.1",
+ "hyper 1.6.0",
 "jobs_common",
 "log",
 "my-workspace-hack",
@@ -12619,7 +12689,7 @@ dependencies = [
 "my-workspace-hack",
 "mysql_queries",
 "r2d2_redis",
- "reqwest 0.12.7",
+ "reqwest 0.12.12",
 "serde",
 "serde_derive",
 "serde_json",
@@ -12979,7 +13049,7 @@ dependencies = [
 "actix-web",
 "mime_guess",
 "regex",
- "reqwest 0.12.7",
+ "reqwest 0.12.12",
 "rust-embed",
 "serde",
 "serde_json",
@@ -13108,7 +13178,7 @@ dependencies = [
 "google_drive_common",
 "hashing",
 "hostname 0.4.0",
- "hyper 1.3.1",
+ "hyper 1.6.0",
 "jobs_common",
 "log",
 "my-workspace-hack",
@@ -13138,7 +13208,7 @@ dependencies = [
 "filesys",
 "google_drive_common",
 "hostname 0.4.0",
- "hyper 1.3.1",
+ "hyper 1.6.0",
 "jobs_common",
 "log",
 "my-workspace-hack",
@@ -13190,6 +13260,15 @@ version = "0.11.0+wasi-snapshot-preview1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "9c8d87e72b64a3b4db28d11ce29237c246188f4f51057d65a7eab63b7987e423"

+[[package]]
+name = "wasi"
+version = "0.13.3+wasi-0.2.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "26816d2e1a4a36a2940b96c5296ce403917633dff8f3440e9b236ed6f6bacad2"
+dependencies = [
+ "wit-bindgen-rt",
+]
+
 [[package]]
 name = "wasite"
 version = "0.1.0"
@@ -13315,7 +13394,7 @@ dependencies = [
 "log",
 "my-workspace-hack",
 "once_cell",
- "reqwest 0.12.7",
+ "reqwest 0.12.12",
 "rss",
 "scraper",
 "serde",
@@ -13959,6 +14038,15 @@ dependencies = [
 "windows-sys 0.48.0",
 ]

+[[package]]
+name = "wit-bindgen-rt"
+version = "0.33.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "3268f3d866458b787f390cf61f4bbb563b922d091359f9608842999eaee3943c"
+dependencies = [
+ "bitflags 2.5.0",
+]
+
 [[package]]
 name = "wry"
 version = "0.48.1"
@@ -14049,8 +14137,8 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "e105d177a3871454f754b33bb0ee637ecaaac997446375fd3e5d43a2ed00c909"
 dependencies = [
 "libc",
- "linux-raw-sys",
- "rustix",
+ "linux-raw-sys 0.4.14",
+ "rustix 0.38.34",
 ]

 [[package]]
@@ -1,7 +1,8 @@
-image_width: 512
-image_height: 512
+image_width: 1024
+image_height: 1024
 #scheduler_steps: 15
 # NB(bt): It looks like we can get down to 2 sampling steps, perhaps ?
-scheduler_steps: 2
+scheduler_steps: 8
 scheduler_samples: 1
-cfg_scale: 1.1
+cfg_scale: 15.0
+seed: 42
@@ -0,0 +1,4 @@
+# Don't restart the dev server on Rust changes
+crates/
+Cargo.toml
+Cargo.lock
@@ -27,30 +27,49 @@ memory_caching = { path = "../../lib/caching/memory_caching" }
 cudarc = "0.13.7"

 # External
+#openssl = { version = "0.10", features = ["vendored"] }
 anyhow = "1.0"
-bytes = "1.10"
 base64 = "0.22.1"
+bytes = "1.10"
 candle-core = { path = "../../vendor/candle/candle-core", features = ["cuda"] }
 candle-nn = { path = "../../vendor/candle/candle-nn", features = ["cuda"] }
 candle-transformers = { path = "../../vendor/candle/candle-transformers", features = ["cuda"] }
+dirs = "6.0.0"
+directories = "6.0.0"
+futures = "0.3"
 hf-hub = "0.3.2"
 image = "0.25.5"
-serde_yaml = "0.9"
 log = "0.4"
 once_cell = "1.20.3"
-rand = "0.8"
+rand = "0.8.5"
+# NB(bt,2025-03-10): default-features = false on Windows while I debug openssl / rustls
+reqwest = { version = "0.12.12", features = ["stream"], default-features = false }
 serde = { version = "1.0", features = ["derive"] }
 serde_json = "1.0"
+serde_yaml = "0.9"
 tauri = { version = "2.2.4", features = [] }
 tauri-plugin-log = "2"
+tempdir = "0.3.7"
+tempfile = "3.18.0"
 tokenizers = "0.15.2"
+tokio = { version = "1.42", features = ["rt", "rt-multi-thread", "fs"] }
+tokio-util = { version = "0.7", features = ["codec"] }
+half = { version = "2.3.1", features = ["num-traits", "use-intrinsics", "rand_distr"] }

 [features]
 default = ["cuda"]
-cuda = ["candle-core/cuda", "candle-nn/cuda", "candle-transformers/cuda"]
+cuda = [
+    "candle-core/cuda",
+    "candle-nn/cuda",
+    "candle-transformers/cuda",
+# NB(bt,2025-03-10): Building without Flash attention on Windows for now to bypass linker issues
+    "candle-transformers/flash-attn",
+    "candle-core/cudnn"
+]

 [dev-dependencies]
 libloading = "0.8.6"
+serial_test = "3.2.0"

 [profile.dev]
 incremental = true # Compile your binary in smaller steps.
@@ -0,0 +1,16 @@
+use crate::ml::downloads::download_all_models::download_all_models;
+use crate::state::app_dir::AppDataRoot;
+use tauri::State;
+
+#[tauri::command]
+pub async fn download_models(
+  app_data_root: State<'_, AppDataRoot>,
+) -> Result<String, String> {
+  
+  download_all_models(&app_data_root).await
+    .map_err(|err| {
+      "error downloading models".to_string()
+    })?;
+  
+  Ok(("downloaded".to_string()))
+}
@@ -1,6 +1,7 @@
+use crate::ml::downloads::download_all_models::download_all_models;
 use crate::ml::model_cache::ModelCache;
 use crate::ml::prompt_cache::PromptCache;
-use crate::ml::stable_diffusion::stable_diffusion_pipeline::{stable_diffusion_pipeline, Args};
+use crate::ml::stable_diffusion::lcm_pipeline::{lcm_pipeline, Args};
 use crate::state::app_config::AppConfig;
 use base64::{engine::general_purpose::STANDARD as BASE64_STANDARD, Engine};
 use bytes::BytesMut;
@@ -10,12 +11,15 @@ use log::{error, info};
 use std::io::Cursor;
 use std::path::PathBuf;
 use tauri::{AppHandle, State};
+use crate::state::app_dir::AppDataRoot;

 const PROMPT_FILENAME : &str = "prompt.txt";
-const PROMPT: &str = "A beautiful landscape with mountains and a lake";
+const PROMPT: &str = "green goblin, blood dripping from lips, detailed, photorealistic, 8k";

 const NEGATIVE_PROMPT: &str = "bad quality, bad faces, poor quality, blurry faces, watermark";

+const RANDOM_SEED: u32 = 42;
+
 // TODO: Mark async https://github.com/tauri-apps/tauri/discussions/7737


@@ -29,6 +33,7 @@ pub async fn infer_image(
  model_config: State<'_, AppConfig>,
  model_cache: State<'_, ModelCache>,
  prompt_cache: State<'_, PromptCache>,
+  app_data_root: State<'_, AppDataRoot>,
  app: AppHandle,
 ) -> Result<String, String> {

@@ -40,7 +45,23 @@ pub async fn infer_image(
  let image = hydrate_base64_image(image)
    .map_err(|err| format!("Couldn't hydrate image from base64: {}", err))?;

-  let result = do_infer_image(&prompt, image, strength, &model_config, &model_cache, prompt_cache, app);
+  // TODO(bt): Move this to another endpoint
+  download_all_models(&app_data_root).await
+    .map_err(|err| {
+      error!("couldn't download models: {:?}", err);
+      "Couldn't download models".to_string()
+    })?;
+
+  let result = do_infer_image(
+    &prompt, 
+    image, 
+    strength, 
+    &model_config, 
+    &model_cache, 
+    prompt_cache, 
+    app, 
+    &app_data_root
+  ).await;
  
  if let Err(err) = result.as_deref() {
    error!("There was an error: {:?}", err);
@@ -49,31 +70,32 @@ pub async fn infer_image(
  result
 }

-fn do_infer_image(
+async fn do_infer_image(
  prompt: &str,
  image: DynamicImage,
  strength: Option<u8>,
  config: &AppConfig,
  model_cache: &ModelCache,
-  prompt_cache: State<PromptCache>,
+  prompt_cache: State<'_, PromptCache>,
  app: AppHandle,
+  app_data_root: &AppDataRoot,
 ) -> Result<String, String> {
-  println!("infer_image called; generating image with SDXL Turbo...");
-  
+
  let args = Args {
    image: &image,
    prompt: prompt.to_string(),
    uncond_prompt: NEGATIVE_PROMPT.to_string(),
-    //guidance_scale: Some(0.0),
    model_cache,
    configs: config,
    prompt_cache: &prompt_cache,
    i2i_strength: strength,
    cfg_scale: config.cfg_scale,
    app: &app,
+    app_data_root,
+    use_flash_attn: true,
  };

-  match stable_diffusion_pipeline(args) {
+  match lcm_pipeline(args) {
    Ok(image) => {
      let mut bytes = Vec::with_capacity(1024*1024);
      
@@ -1,3 +1,4 @@
+pub mod download_models;
 pub mod flip_image;
 pub mod image_endpoint;
 pub mod test_counter;
@@ -3,9 +3,11 @@ use serde::Serialize;

 #[derive(Clone, Copy, Serialize)]
 #[serde(rename_all = "snake_case")]
-pub enum ModelType {
+pub enum NotificationModelType {
  Unet,
  Vae,
+  Json,
+  ClipEncoder,
 }

 #[derive(Clone, Serialize)]
@@ -13,10 +15,16 @@ pub enum ModelType {
 pub enum NotificationEvent<'a> {
  ModelDownloadStarted {
    model_name: &'a str, 
-    model_type: ModelType,
+    model_type: NotificationModelType,
+  },
+  ModelDownloadProgress {
+    model_name: &'a str,
+    model_type: NotificationModelType,
+    currently_downloaded_bytes: usize,
+    total_file_bytes: usize,
  },
  ModelDownloadComplete {
    model_name: &'a str,
-    model_type: ModelType,
+    model_type: NotificationModelType,
  }
 }
@@ -2,12 +2,16 @@ pub mod endpoints;
 pub mod events;
 pub mod ml;
 pub mod state;
+pub mod threads;
+pub mod transfer;

+use crate::endpoints::download_models::download_models;
+use crate::endpoints::image_endpoint::infer_image;
+use crate::endpoints::test_counter::test_counter;
 use crate::ml::model_cache::ModelCache;
 use crate::ml::prompt_cache::PromptCache;
 use crate::state::app_config::AppConfig;
-use endpoints::image_endpoint::infer_image;
-use endpoints::test_counter::test_counter;
+use crate::threads::downloader_thread::downloader_thread;
 use tauri_plugin_log::Target;
 use tauri_plugin_log::TargetKind;

@@ -26,6 +30,9 @@ pub fn run() {
  println!("Creating model cache...");
  
  let model_cache = ModelCache::new();
+  
+  let app_data_root = config.app_data_root.clone();
+  let app_data_root2 = config.app_data_root.clone();

  println!("Initializing backend runtime...");

@@ -42,14 +49,20 @@ pub fn run() {
      //      .build(),
      //  )?;
      //}
+      let app = app.handle().clone();
+
+      tauri::async_runtime::spawn(downloader_thread(app_data_root2, app));
+
      Ok(())
    })
    .manage(config)
    .manage(prompt_cache)
    .manage(model_cache)
+    .manage(app_data_root)
    .invoke_handler(tauri::generate_handler![
      test_counter, 
      infer_image,
+      download_models,
    ])
    .run(tauri::generate_context!())
    .expect("error while running tauri application");
@@ -0,0 +1,15 @@
+use crate::ml::downloads::download_model_registry_file::download_model_registry_file;
+use crate::ml::model_type::ModelType;
+use crate::state::app_dir::AppDataRoot;
+
+pub async fn download_all_models(app_data_root: &AppDataRoot) -> anyhow::Result<()> {
+  let weights_dir = app_data_root.weights_dir();
+  
+  //download_model_registry_file(ModelType::ClipJson, weights_dir).await?;
+  //download_model_registry_file(ModelType::SdxlTurboUnet, weights_dir).await?;
+  //download_model_registry_file(ModelType::SdxlTurboVae, weights_dir).await?;
+  //download_model_registry_file(ModelType::SdxlTurboClipEncoder, weights_dir).await?;
+  //download_model_registry_file(ModelType::SdxlTurboClipEncoder2, weights_dir).await?;
+  
+  Ok(())
+}
@@ -0,0 +1,30 @@
+use crate::ml::model_type::ModelType;
+use crate::state::app_dir::AppWeightsDir;
+use log::info;
+use std::fs::File;
+use std::path::{Path, PathBuf};
+
+pub async fn download_model_registry_file(
+  model_type: ModelType,
+  weights_dir: &AppWeightsDir,
+) -> anyhow::Result<PathBuf> {
+  
+  let path = weights_dir.model_path(&model_type);
+
+  if path.exists() {
+    return Ok(path);
+  }
+
+  info!("downloading model: {:?} to {:?}", model_type, path);
+
+  let body = reqwest::get(model_type.get_download_url())
+    .await?
+    .bytes()
+    .await?;
+  
+  let _file = File::create(&path)?;
+  
+  std::fs::write(&path, body.as_ref())?;
+  
+  Ok(path)
+}
@@ -0,0 +1,2 @@
+pub mod download_model_registry_file;
+pub mod download_all_models;
@@ -3,4 +3,6 @@ pub mod model_cache;
 pub mod model_file;
 pub mod models;
 pub mod prompt_cache;
-pub mod stable_diffusion;
+pub mod stable_diffusion;
+pub mod model_type;
+pub mod downloads;
@@ -4,80 +4,177 @@ extern crate accelerate_src;
 extern crate intel_mkl_src;

 use candle_transformers::models::stable_diffusion;
+use anyhow::{Error as E, Result};
+use hf_hub::api::sync::Api;
+#[derive(Debug, Clone, Copy, PartialEq, Eq)]
+pub enum StableDiffusionVersion {
+    V1_5,
+    V1_5Inpaint,
+    V2_1,
+    V2Inpaint,
+    Xl,
+    XlInpaint,
+    Turbo,
+}

 #[derive(Debug, Clone, Copy, PartialEq, Eq)]
 pub enum ModelFile {
-  Tokenizer,
-  Tokenizer2,
-  Clip,
-  Clip2,
-  Unet,
-  Vae,
-}
-
-#[derive(Debug, Clone, Copy, PartialEq, Eq)]
-pub enum StableDiffusionVersion {
-  V1_5,
-  V1_5Inpaint,
-  V2_1,
-  V2Inpaint,
-  Xl,
-  XlInpaint,
-  Turbo,
+    Tokenizer,
+    Tokenizer2,
+    Clip,
+    Clip2,
+    Unet,
+    UnetLcm,
+    Vae,
 }

 impl StableDiffusionVersion {
-  pub fn repo(&self) -> &'static str {
-    match self {
-      Self::XlInpaint => "diffusers/stable-diffusion-xl-1.0-inpainting-0.1",
-      Self::Xl => "stabilityai/stable-diffusion-xl-base-1.0",
-      Self::V2Inpaint => "stabilityai/stable-diffusion-2-inpainting",
-      Self::V2_1 => "stabilityai/stable-diffusion-2-1",
-      Self::V1_5 => "runwayml/stable-diffusion-v1-5",
-      Self::V1_5Inpaint => "stable-diffusion-v1-5/stable-diffusion-inpainting",
-      Self::Turbo => "stabilityai/sdxl-turbo",
+    pub fn repo(&self) -> &'static str {
+        match self {
+            Self::XlInpaint => "diffusers/stable-diffusion-xl-1.0-inpainting-0.1",
+            Self::Xl => "stabilityai/stable-diffusion-xl-base-1.0",
+            Self::V2Inpaint => "stabilityai/stable-diffusion-2-inpainting",
+            Self::V2_1 => "stabilityai/stable-diffusion-2-1",
+            Self::V1_5 => "Lykon/dreamshaper-7",
+            Self::V1_5Inpaint => "stable-diffusion-v1-5/stable-diffusion-inpainting",
+            Self::Turbo => "Lykon/dreamshaper-7",
+        }
+    }
+
+    fn unet_file(&self, use_f16: bool) -> &'static str {
+        match self {
+            Self::V1_5
+            | Self::V1_5Inpaint
+            | Self::V2_1
+            | Self::V2Inpaint
+            | Self::Xl
+            | Self::XlInpaint
+            | Self::Turbo => {
+                if use_f16 {
+                    "unet/diffusion_pytorch_model.fp16.safetensors"
+                } else {
+                    "unet/diffusion_pytorch_model.safetensors"
+                }
+            }
+        }
+    }
+
+    fn vae_file(&self, use_f16: bool) -> &'static str {
+        match self {
+            Self::V1_5
+            | Self::V1_5Inpaint
+            | Self::V2_1
+            | Self::V2Inpaint
+            | Self::Xl
+            | Self::XlInpaint
+            | Self::Turbo => {
+                if use_f16 {
+                    "vae/diffusion_pytorch_model.fp16.safetensors"
+                } else {
+                    "vae/diffusion_pytorch_model.safetensors"
+                }
+            }
+        }
+    }
+
+    fn clip_file(&self, use_f16: bool) -> &'static str {
+        match self {
+            Self::V1_5
+            | Self::V1_5Inpaint
+            | Self::V2_1
+            | Self::V2Inpaint
+            | Self::Xl
+            | Self::XlInpaint
+            | Self::Turbo => {
+                if use_f16 {
+                    "text_encoder/model.fp16.safetensors"
+                } else {
+                    "text_encoder/model.safetensors"
+                }
+            }
+        }
+    }
+
+    fn clip2_file(&self, use_f16: bool) -> &'static str {
+        match self {
+            Self::V1_5
+            | Self::V1_5Inpaint
+            | Self::V2_1
+            | Self::V2Inpaint
+            | Self::Xl
+            | Self::XlInpaint
+            | Self::Turbo => {
+                if use_f16 {
+                    "text_encoder_2/model.fp16.safetensors"
+                } else {
+                    "text_encoder_2/model.safetensors"
+                }
+            }
+        }
    }
-  }
 }

 impl ModelFile {
-  pub fn get(
-    &self,
-    filename: Option<String>,
-    version: StableDiffusionVersion,
-    use_f16: bool,
-  ) -> anyhow::Result<std::path::PathBuf> {
-    use hf_hub::api::sync::Api;
-    match filename {
-      Some(filename) => Ok(std::path::PathBuf::from(filename)),
-      None => {
-        let (repo, path) = match self {
-          Self::Tokenizer => {
-            let tokenizer_repo = match version {
-              StableDiffusionVersion::V1_5
-              | StableDiffusionVersion::V2_1
-              | StableDiffusionVersion::V1_5Inpaint
-              | StableDiffusionVersion::V2Inpaint => "openai/clip-vit-base-patch32",
-              StableDiffusionVersion::Xl
-              | StableDiffusionVersion::XlInpaint
-              | StableDiffusionVersion::Turbo => {
-                "openai/clip-vit-large-patch14"
-              }
-            };
-            (tokenizer_repo, "tokenizer.json")
-          }
-          Self::Tokenizer2 => {
-            ("laion/CLIP-ViT-bigG-14-laion2B-39B-b160k", "tokenizer.json")
-          }
-          Self::Clip => (version.repo(), "text_encoder/model.safetensors"),
-          Self::Clip2 => (version.repo(), "text_encoder_2/model.safetensors"),
-          Self::Unet => (version.repo(), "unet/diffusion_pytorch_model.safetensors"),
-          Self::Vae => (version.repo(), "vae/diffusion_pytorch_model.safetensors"),
-        };
-        let filename = Api::new()?.model(repo.to_string()).get(path)?;
-        Ok(filename)
-      }
+    pub fn get(
+        &self,
+        filename: Option<String>,
+        version: StableDiffusionVersion,
+        use_f16: bool,
+    ) -> Result<std::path::PathBuf> {
+        match filename {
+            Some(filename) => Ok(std::path::PathBuf::from(filename)),
+            None => {
+                let (repo, path) = match self {
+                    Self::Tokenizer => {
+                        let tokenizer_repo = match version {
+                            StableDiffusionVersion::V1_5
+                            | StableDiffusionVersion::V2_1
+                            | StableDiffusionVersion::V1_5Inpaint
+                            | StableDiffusionVersion::V2Inpaint => "openai/clip-vit-base-patch32",
+                            StableDiffusionVersion::Xl
+                            | StableDiffusionVersion::XlInpaint
+                            | StableDiffusionVersion::Turbo => {
+                                // This seems similar to the patch32 version except some very small
+                                // difference in the split regex.
+                                "openai/clip-vit-large-patch14"
+                            }
+                        };
+                        (tokenizer_repo, "tokenizer.json")
+                    }
+                    Self::Tokenizer2 => {
+                        ("laion/CLIP-ViT-bigG-14-laion2B-39B-b160k", "tokenizer.json")
+                    }
+                    Self::Clip => (version.repo(), version.clip_file(use_f16)),
+                    Self::Clip2 => (version.repo(), version.clip2_file(use_f16)),
+                    Self::UnetLcm => (
+                        "SimianLuo/LCM_Dreamshaper_v7",
+                        if use_f16 {
+                            "unet/diffusion_pytorch_model.fp16.safetensors"
+                        } else {
+                            "unet/diffusion_pytorch_model.safetensors"
+                        },
+                    ),
+                    Self::Unet => (version.repo(), version.unet_file(use_f16)),
+                    Self::Vae => {
+                        // Override for SDXL when using f16 weights.
+                        // See https://github.com/huggingface/candle/issues/1060
+                        if matches!(
+                            version,
+                            StableDiffusionVersion::Xl | StableDiffusionVersion::Turbo,
+                        ) && use_f16
+                        {
+                            (
+                                "madebyollin/sdxl-vae-fp16-fix",
+                                "diffusion_pytorch_model.safetensors",
+                            )
+                        } else {
+                            (version.repo(), version.vae_file(use_f16))
+                        }
+                    }
+                };
+                let filename = Api::new()?.model(repo.to_string()).get(path)?;
+                Ok(filename)
+            }
+        }
    }
-  }
 }
-
@@ -0,0 +1,86 @@
+use crate::events::notification_event::NotificationModelType;
+use crate::state::app_dir::AppWeightsDir;
+use std::path::PathBuf;
+
+#[derive(Copy, Clone, Debug)]
+pub enum ModelType {
+  ClipJson,
+  SdxlTurboUnet,
+  SdxlTurboVae,
+  SdxlTurboClipEncoder,
+  SdxlTurboClipEncoder2,
+  SimianLuoLcmDreamshaperV7Unet,
+  LykonDreamshaper7Vae,
+  LykonDreamshaper7TextEncoderFp16,
+}
+
+impl ModelType {
+  pub fn get_name(&self) -> &'static str {
+    match self {
+      Self::ClipJson => "CLIP (JSON)",
+      Self::SdxlTurboUnet => "SDXL Turbo UNET",
+      Self::SdxlTurboVae => "SDXL Turbo VAE",
+      Self::SdxlTurboClipEncoder => "Clip Encoder #1",
+      Self::SdxlTurboClipEncoder2 => "Clip Encoder #2",
+      Self::SimianLuoLcmDreamshaperV7Unet => "SimianLuo LCM Dreamshaper v7 UNET",
+      Self::LykonDreamshaper7Vae => "Lykon Dreamshaper 7 VAE",
+      Self::LykonDreamshaper7TextEncoderFp16 => "Lykon Dreamshaper Text Encoder (fp16)",
+    }
+  }
+
+  pub fn get_notification_type(&self) -> NotificationModelType {
+    match self {
+      Self::ClipJson => NotificationModelType::Json,
+      Self::SdxlTurboUnet => NotificationModelType::Unet,
+      Self::SdxlTurboVae => NotificationModelType::Vae,
+      Self::SdxlTurboClipEncoder => NotificationModelType::ClipEncoder,
+      Self::SdxlTurboClipEncoder2 => NotificationModelType::ClipEncoder,
+      Self::SimianLuoLcmDreamshaperV7Unet => NotificationModelType::Unet,
+      Self::LykonDreamshaper7Vae => NotificationModelType::Vae,
+      Self::LykonDreamshaper7TextEncoderFp16 => NotificationModelType::ClipEncoder,
+    }
+  }
+
+  pub fn get_hf_id(&self) -> Option<&'static str> {
+    match self {
+      Self::ClipJson => Some("laion/CLIP-ViT-bigG-14-laion2B-39B-b160k"),
+      Self::SdxlTurboUnet 
+      | Self::SdxlTurboVae
+      | Self::SdxlTurboClipEncoder
+      | Self::SdxlTurboClipEncoder2 => Some("stabilityai/sdxl-turbo"),
+      Self::SimianLuoLcmDreamshaperV7Unet => Some("SimianLuo/LCM_Dreamshaper_v7"),
+      Self::LykonDreamshaper7Vae
+      | Self::LykonDreamshaper7TextEncoderFp16 => Some("Lykon/dreamshaper-7"),
+    }
+  }
+
+  pub fn get_download_url(&self) -> &'static str {
+    match self {
+      Self::ClipJson => "https://pub-bc5e2bc0cdee4bb5ae8fca9d641ca0d6.r2.dev/tokenizer.json",
+      Self::SdxlTurboUnet => "https://pub-bc5e2bc0cdee4bb5ae8fca9d641ca0d6.r2.dev/diffusion_pytorch_model.unet.safetensors",
+      Self::SdxlTurboVae => "https://pub-bc5e2bc0cdee4bb5ae8fca9d641ca0d6.r2.dev/diffusion_pytorch_model.vae.safetensors",
+      Self::SdxlTurboClipEncoder => "https://pub-bc5e2bc0cdee4bb5ae8fca9d641ca0d6.r2.dev/clip_text_encoder.safetensors",
+      Self::SdxlTurboClipEncoder2 => "https://pub-bc5e2bc0cdee4bb5ae8fca9d641ca0d6.r2.dev/clip_text_encoder_2.safetensors",
+      Self::SimianLuoLcmDreamshaperV7Unet => "https://pub-bc5e2bc0cdee4bb5ae8fca9d641ca0d6.r2.dev/simianluo_lcm_dreamshaper_v7_unet.safetensors",
+      Self::LykonDreamshaper7Vae => "https://pub-bc5e2bc0cdee4bb5ae8fca9d641ca0d6.r2.dev/lykon_dreamshaper_7_vae.safetensors",
+      Self::LykonDreamshaper7TextEncoderFp16 => "https://pub-bc5e2bc0cdee4bb5ae8fca9d641ca0d6.r2.dev/lykon_dreamshaper_7_text_encoder.fp16.safetensors",
+    }
+  }
+
+  pub fn get_filename(&self) -> &'static str {
+    match self {
+      Self::ClipJson => "clip_vit_bigg_14_lion2b_39b_b160k.tokenizer.json",
+      Self::SdxlTurboUnet => "diffusion_pytorch_model.unet.safetensors",
+      Self::SdxlTurboVae => "diffusion_pytorch_model.vae.safetensors",
+      Self::SdxlTurboClipEncoder => "clip_text_encoder.safetensors",
+      Self::SdxlTurboClipEncoder2 => "clip_text_encoder_2.safetensors",
+      Self::SimianLuoLcmDreamshaperV7Unet => "simianluo_lcm_dreamshaper_v7_unet.safetensors",
+      Self::LykonDreamshaper7Vae => "lykon_dreamshaper_7_vae.safetensors",
+      Self::LykonDreamshaper7TextEncoderFp16 => "lykon_dreamshaper_7_text_encoder.fp16.safetensors",
+    }
+  }
+  
+  pub fn get_path(&self, weights_dir: &AppWeightsDir) -> PathBuf {
+    weights_dir.model_path(self)
+  }
+}
@@ -8,28 +8,23 @@ pub struct UNetModel {
 }

 impl UNetModel {
-  pub fn new<P: AsRef<Path>>(
-    sd_config: &StableDiffusionConfig,
-    unet_weights_file: P,
-    device: &Device,
-    dtype: DType,
-  ) -> anyhow::Result<Self> {
+  pub fn new<P: AsRef<Path>>(sd_config: &StableDiffusionConfig, unet_weights_file: P, device: &Device, dtype: DType) -> anyhow::Result<Self> {
    println!("building unet model... (1)");
-    
-    let model = sd_config.build_unet(
-      unet_weights_file, 
-      &device, 
-      4, 
-      false, 
-      dtype
-    )?;
-    
-    Ok(Self {
-      model,
-    })
+
+    let model = sd_config.build_unet(unet_weights_file, &device, 4, true, dtype)?;
+
+    Ok(Self { model })
  }
-  
+
+  pub fn new_with_inner(model: UNet2DConditionModel) -> Self {
+    Self { model }
+  }
+
  pub fn inference(&self, latent_model_input: &Tensor, timestep: f64, text_embeddings: &Tensor) -> anyhow::Result<Tensor> {
    Ok(self.model.forward(&latent_model_input, timestep, &text_embeddings)?)
  }
+
+  pub fn forward_with_guidance(&self, latent_model_input: &Tensor, timestep: f64, text_embeddings: &Tensor, guidance_scale_embedding: &Tensor) -> anyhow::Result<Tensor> {
+    Ok(self.model.forward_with_guidance(&latent_model_input, timestep, &text_embeddings, Some(guidance_scale_embedding))?)
+  }
 }
@@ -3,6 +3,7 @@ extern crate accelerate_src;
 #[cfg(feature = "mkl")]
 extern crate intel_mkl_src;

+use std::path::PathBuf;
 use candle_transformers::models::stable_diffusion;

 use crate::ml::model_file::{ModelFile, StableDiffusionVersion};
@@ -10,27 +11,15 @@ use anyhow::Error as E;
 use candle_core::{DType, Device, Module, Tensor, D};
 use log::info;
 use tokenizers::Tokenizer;
+use crate::ml::model_type::ModelType;
+use crate::state::app_dir::AppWeightsDir;

 #[allow(clippy::too_many_arguments)]
-pub fn infer_clip_text_embeddings(
-  prompt: &str,
-  uncond_prompt: &str,
-  tokenizer: Option<String>,
-  clip_weights: Option<String>,
-  clip2_weights: Option<String>,
-  sd_version: StableDiffusionVersion,
-  sd_config: &stable_diffusion::StableDiffusionConfig,
-  use_f16: bool,
-  device: &Device,
-  dtype: DType,
-  use_guide_scale: bool,
-) -> anyhow::Result<Tensor> {
-  info!("Preparing text embeddings...");
+pub fn infer_clip_text_embeddings(prompt: &str, uncond_prompt: &str, tokenizer: Option<String>, clip_weights: Option<String>, clip2_weights: Option<String>, sd_version: StableDiffusionVersion, sd_config: &stable_diffusion::StableDiffusionConfig, use_f16: bool, device: &Device, dtype: DType, use_guide_scale: bool, weights_dir: &AppWeightsDir) -> anyhow::Result<Tensor> {
+  info!("Preparing text embeddings... for {:?}", sd_version);

  let which = match sd_version {
-    StableDiffusionVersion::Xl
-    | StableDiffusionVersion::XlInpaint
-    | StableDiffusionVersion::Turbo => vec![true, false],
+    StableDiffusionVersion::Xl | StableDiffusionVersion::XlInpaint | StableDiffusionVersion::Turbo => vec![true, false],
    _ => vec![true],
  };

@@ -41,7 +30,7 @@ pub fn infer_clip_text_embeddings(
        &prompt,
        &uncond_prompt,
        None, // tokenizer
-        None, // clip_weights
+        clip_weights.clone(),
        None, // clip2_weights
        sd_version,
        &sd_config,
@@ -50,55 +39,45 @@ pub fn infer_clip_text_embeddings(
        dtype,
        use_guide_scale,
        *first,
+        weights_dir,
      )
    })
    .collect::<anyhow::Result<Vec<_>>>()?;

  let text_embeddings = Tensor::cat(&text_embeddings, D::Minus1)?;
-  
+
  Ok(text_embeddings)
 }

 #[allow(clippy::too_many_arguments)]
-fn do_infer_clip_text_embeddings(
-    prompt: &str,
-    uncond_prompt: &str,
-    tokenizer: Option<String>,
-    clip_weights: Option<String>,
-    clip2_weights: Option<String>,
-    sd_version: StableDiffusionVersion,
-    sd_config: &stable_diffusion::StableDiffusionConfig,
-    use_f16: bool,
-    device: &Device,
-    dtype: DType,
-    use_guide_scale: bool,
-    first: bool,
-  ) -> anyhow::Result<Tensor> {
-  
-  let tokenizer_file = if first {
-    ModelFile::Tokenizer
-  } else {
-    ModelFile::Tokenizer2
-  };
-  let tokenizer = tokenizer_file.get(tokenizer, sd_version, use_f16)?;
+fn do_infer_clip_text_embeddings(prompt: &str, uncond_prompt: &str, tokenizer: Option<String>, clip_weights: Option<String>, clip2_weights: Option<String>, sd_version: StableDiffusionVersion, sd_config: &stable_diffusion::StableDiffusionConfig, use_f16: bool, device: &Device, dtype: DType, use_guide_scale: bool, first: bool, weights_dir: &AppWeightsDir) -> anyhow::Result<Tensor> {
+  info!("do_infer_clip_text_embeddings called with args {:?}", (prompt, uncond_prompt, tokenizer.clone().unwrap_or_else(|| "None".to_string()), clip_weights.clone().unwrap_or_else(|| "None".to_string()), clip2_weights.clone().unwrap_or_else(|| "None".to_string()), sd_version, sd_config, use_f16, device, dtype, use_guide_scale, first));
+
+  //let tokenizer_file = if first {
+  //  info!("ModelFile::Tokenizer");
+  //  ModelFile::Tokenizer
+  //} else {
+  //  info!("ModelFile::Tokenizer2");
+  //  ModelFile::Tokenizer2
+  //};
+
+  //let tokenizer = tokenizer_file.get(tokenizer, sd_version, use_f16)?;
+
+  let tokenizer = weights_dir.model_path(&ModelType::ClipJson);
+
+  info!("Loading Clip Tokenizer path: {:?}", tokenizer);
+
  let tokenizer = Tokenizer::from_file(tokenizer).map_err(E::msg)?;
+
  let pad_id = match &sd_config.clip.pad_with {
    Some(padding) => *tokenizer.get_vocab(true).get(padding.as_str()).unwrap(),
    None => *tokenizer.get_vocab(true).get("<|endoftext|>").unwrap(),
  };

  println!("Running with prompt \"{prompt}\".");
-  let mut tokens = tokenizer
-    .encode(prompt, true)
-    .map_err(E::msg)?
-    .get_ids()
-    .to_vec();
+  let mut tokens = tokenizer.encode(prompt, true).map_err(E::msg)?.get_ids().to_vec();
  if tokens.len() > sd_config.clip.max_position_embeddings {
-    anyhow::bail!(
-            "the prompt is too long, {} > max-tokens ({})",
-            tokens.len(),
-            sd_config.clip.max_position_embeddings
-        )
+    anyhow::bail!("the prompt is too long, {} > max-tokens ({})", tokens.len(), sd_config.clip.max_position_embeddings)
  }
  while tokens.len() < sd_config.clip.max_position_embeddings {
    tokens.push(pad_id)
@@ -106,37 +85,23 @@ fn do_infer_clip_text_embeddings(
  let tokens = Tensor::new(tokens.as_slice(), device)?.unsqueeze(0)?;

  println!("Building the Clip transformer.");
-  let clip_weights_file = if first {
-    ModelFile::Clip
-  } else {
-    ModelFile::Clip2
-  };
+  let clip_weights_file = if first { ModelFile::Clip } else { ModelFile::Clip2 };
  let clip_weights = if first {
-    clip_weights_file.get(clip_weights, sd_version, use_f16)?
+    //clip_weights_file.get(clip_weights, sd_version, use_f16)?
+    weights_dir.model_path(&ModelType::SdxlTurboClipEncoder)
  } else {
-    clip_weights_file.get(clip2_weights, sd_version, use_f16)?
-  };
-  let clip_config = if first {
-    &sd_config.clip
-  } else {
-    sd_config.clip2.as_ref().unwrap()
+    //clip_weights_file.get(clip2_weights, sd_version, use_f16)?
+    weights_dir.model_path(&ModelType::SdxlTurboClipEncoder2)
  };
+  let clip_config = if first { &sd_config.clip } else { sd_config.clip2.as_ref().unwrap() };
  let text_model = stable_diffusion::build_clip_transformer(clip_config, clip_weights, device, DType::F32)?;

  let text_embeddings = text_model.forward(&tokens)?;

  let text_embeddings = if use_guide_scale {
-    let mut uncond_tokens = tokenizer
-      .encode(uncond_prompt, true)
-      .map_err(E::msg)?
-      .get_ids()
-      .to_vec();
+    let mut uncond_tokens = tokenizer.encode(uncond_prompt, true).map_err(E::msg)?.get_ids().to_vec();
    if uncond_tokens.len() > sd_config.clip.max_position_embeddings {
-      anyhow::bail!(
-                "the negative prompt is too long, {} > max-tokens ({})",
-                uncond_tokens.len(),
-                sd_config.clip.max_position_embeddings
-            )
+      anyhow::bail!("the negative prompt is too long, {} > max-tokens ({})", uncond_tokens.len(), sd_config.clip.max_position_embeddings)
    }
    while uncond_tokens.len() < sd_config.clip.max_position_embeddings {
      uncond_tokens.push(pad_id)
@@ -0,0 +1,291 @@
+use std::path::PathBuf;
+use std::sync::{Arc, RwLock, RwLockReadGuard, RwLockWriteGuard};
+
+use crate::events::notification_event::{NotificationEvent, NotificationModelType};
+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;
+use crate::ml::model_file::{ModelFile, StableDiffusionVersion};
+use crate::ml::model_type::ModelType;
+use crate::ml::models::unet_model::UNetModel;
+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;
+use crate::state::app_config::AppConfig;
+use crate::state::app_dir::AppDataRoot;
+use anyhow::{anyhow, Error as E, Result};
+use candle_core::{DType, IndexOp, Tensor, D};
+use candle_nn::VarBuilder;
+use candle_transformers::models::stable_diffusion::lcm::LCMScheduler;
+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 image::DynamicImage;
+use log::info;
+use rand::Rng;
+use tauri::{AppHandle, Emitter};
+
+pub struct Args<'a> {
+  pub image: &'a DynamicImage,
+  pub prompt: String,
+  pub uncond_prompt: String,
+  pub cfg_scale: Option<f64>,
+  pub i2i_strength: Option<u8>,
+  pub configs: &'a AppConfig,
+  pub model_cache: &'a ModelCache,
+  pub prompt_cache: &'a PromptCache,
+  pub app_data_root: &'a AppDataRoot,
+  pub app: &'a AppHandle,
+  pub use_flash_attn: bool,
+}
+
+pub fn lcm_pipeline(args: Args<'_>) -> Result<RgbImage> {
+  let Args { prompt, uncond_prompt, cfg_scale, i2i_strength, configs, model_cache, prompt_cache, app, image, app_data_root, use_flash_attn } = args;
+
+  let weights_dir = app_data_root.weights_dir();
+
+  let img2img_strength = args.i2i_strength.unwrap_or(75) as f64 / 100.0;
+  let use_f16 = true;
+
+  //println!("Starting image generation with the following configuration:");
+  //println!("  Model: {:?}", configs.sd_version);
+  //println!("  Prompt: {}", prompt);
+  //println!("  Steps: {}", configs.scheduler_steps);
+  //println!("  Device: {:?}", configs.device);
+
+  //println!("Model dimensions: {}x{}", configs.sd_config.width, configs.sd_config.height);
+
+  // Use LCM Scheduler instead of Euler Ancestral for better speed and quality
+  let mut scheduler = LCMScheduler::new(configs.scheduler_steps, img2img_strength, candle_transformers::models::stable_diffusion::lcm::LCMSchedulerConfig::default())?;
+
+  let seed = configs.seed.unwrap_or_else(|| rand::thread_rng().gen());
+  configs.device.set_seed(seed)?;
+
+  //info!("Using seed: {}", seed);
+
+  let guidance_scale = match cfg_scale {
+    Some(guidance_scale) => guidance_scale,
+    None => match configs.sd_version {
+      StableDiffusionVersion::V1_5 | StableDiffusionVersion::V2_1 | StableDiffusionVersion::Xl => 7.5,
+      StableDiffusionVersion::Turbo => 0.,
+      _ => 0., // NB: Not sure what the other model families should use, so sticking with "0"
+    },
+  };
+
+  // let use_guide_scale = guidance_scale > 1.0;
+  let use_guide_scale = false;
+
+  //info!("Using guide scale: {}", use_guide_scale);
+
+  //info!("Checking if prompt is cached");
+  let maybe_cached = prompt_cache.get_copy(&prompt)?;
+
+  let mut text_embeddings = if let Some(tensor) = maybe_cached {
+    tensor
+  } else {
+    info!("Loading clip weights...");
+    //println!("Loading clip weights for {:?} with model {:?}", configs.sd_version, configs.sd_version.repo());
+    //let api = configs.hf_api.clone();
+
+    //let clip_path = api.model(configs.sd_version.repo().to_string()).get(if use_f16 { "text_encoder/model.fp16.safetensors" } else { "text_encoder/model.safetensors" })?;
+
+    //println!(">>>> CLIP REPO = {:?}", configs.sd_version.repo());
+    //println!(">>>> CLIP PATH = {:?}", clip_path);
+    //println!(">>>> USE_FP16 = {:?}", use_f16);
+    //let clip_weights = Some(clip_path.to_string_lossy().to_string());
+
+    let clip_weights = weights_dir.model_path(&ModelType::LykonDreamshaper7TextEncoderFp16);
+    let clip_weights = Some(clip_weights.to_string_lossy().to_string());
+
+    info!("Prompt is NOT cached! Calculating embedding...");
+    let tensor = infer_clip_text_embeddings(
+      &prompt,
+      &uncond_prompt,
+      None, // tokenizer
+      clip_weights,
+      None, // clip2_weights
+      configs.sd_version,
+      &configs.sd_config,
+      use_f16, // use_f16
+      &configs.device,
+      configs.dtype,
+      use_guide_scale,
+      weights_dir,
+    )?;
+    prompt_cache.store_copy(&prompt, &tensor)?;
+    tensor
+  };
+
+  println!("Text embeddings shape: {:?}", text_embeddings.shape());
+
+  println!("Loading input image into tensor...");
+
+  let input_image = dynamic_image_to_tensor(image, &configs.device, configs.dtype)?;
+
+  println!("Reference image shape: {:?}", input_image.shape());
+
+  let vae_scale = get_vae_scale(configs.sd_version);
+
+  let maybe_vae = model_cache.get_vae()?;
+
+  let vae = match maybe_vae {
+    Some(vae) => vae,
+    None => {
+      //let repo = configs.sd_version.repo();
+      //println!(">>>>> VAE REPO = {:?}", repo);
+      //println!("Building VAE model from : {:?} ... (3)", repo);
+      //let vae_file = configs.hf_api.model(repo.to_string()).get("vae/diffusion_pytorch_model.safetensors")?;
+
+      let vae_file = weights_dir.model_path(&ModelType::LykonDreamshaper7Vae);
+
+      println!("Building VAE model from file {:?}...", &vae_file);
+
+      let vae = configs.sd_config.build_vae(vae_file, &configs.device, configs.dtype)?;
+
+      let vae = Arc::new(vae);
+
+      model_cache.set_vae(vae.clone())?;
+
+      vae
+    }
+  };
+
+  let maybe_unet = model_cache.get_unet()?;
+
+  let unet = match maybe_unet {
+    Some(unet) => unet,
+    None => {
+      info!("No unet found in cache; loading...");
+
+      let unet_weights = weights_dir.model_path(&ModelType::SimianLuoLcmDreamshaperV7Unet);
+
+      let in_channels = match configs.sd_version {
+        StableDiffusionVersion::XlInpaint | StableDiffusionVersion::V2Inpaint | StableDiffusionVersion::V1_5Inpaint => 9,
+        _ => 4,
+      };
+
+      // For LCM models, ensure that:
+      // 1. We're using the correct prediction type (epsilon)
+      // 2. The cross-attention dimension is correct (768 for Dreamshaper)
+      // 3. The in_channels matches the expected input (4 for standard, 9 for inpainting)
+      let unet_config = UNet2DConditionModelConfig {
+        // LCM specific config values
+        cross_attention_dim: 768,      // Dreamshaper v7 uses 768
+        time_cond_proj_dim: Some(256), // LCM models use 256-dimensional guidance embeddings
+        // Rest of configuration...
+        center_input_sample: false,
+        flip_sin_to_cos: true,
+        freq_shift: 0.0,
+        blocks: vec![
+          BlockConfig { out_channels: 320, use_cross_attn: Some(1), attention_head_dim: 8 },
+          BlockConfig { out_channels: 640, use_cross_attn: Some(1), attention_head_dim: 8 },
+          BlockConfig { out_channels: 1280, use_cross_attn: Some(1), attention_head_dim: 8 },
+          BlockConfig { out_channels: 1280, use_cross_attn: None, attention_head_dim: 8 }
+        ],
+        layers_per_block: 2,
+        downsample_padding: 1,
+        mid_block_scale_factor: 1.0,
+        norm_num_groups: 32,
+        norm_eps: 1e-5,
+        sliced_attention_size: None,
+        use_linear_projection: false,
+        time_embed_dim: Some(1280),
+        // time_embed_dim: Some(256),
+      };
+
+      // Load the model directly from the safetensors file
+      let vs_unet = unsafe { VarBuilder::from_mmaped_safetensors(&[unet_weights], configs.dtype, &configs.device)? };
+
+      let unet = UNet2DConditionModel::new(vs_unet, in_channels, 4, use_flash_attn, unet_config)?;
+
+      let unet = UNetModel::new_with_inner(unet);
+
+      let unet = Arc::new(unet);
+
+      model_cache.set_unet(unet.clone())?;
+
+      unet
+    },
+  };
+
+  let init_latent_dist: DiagonalGaussianDistribution = vae.encode(&input_image)?;
+
+  // Parse and calculate the img2img strength
+  let img2img_strength = match i2i_strength {
+    None => 0.75f64,
+    Some(strength) => (strength as f64) / 100.0f64,
+  };
+
+  // Create LCM guidance scale embeddings
+  let embedding_dim = 1280;
+  let guidance_scale_embedding = scheduler.get_guidance_scale_embedding(guidance_scale, embedding_dim, &configs.device, configs.dtype)?;
+
+  // Generate latents from input image using the LCM approach
+  println!("Generating latents from input image...");
+  let init_latents = (init_latent_dist.sample()? * vae_scale)?;
+  println!("Initial latents shape: {:?}", init_latents.shape());
+
+  // Calculate timesteps for LCM with proper img2img handling
+  let timesteps = LCMScheduler::get_timesteps_for_steps(configs.scheduler_steps, img2img_strength);
+  let t_start = timesteps[0]; // First denoising step
+
+  // Add noise at the appropriate timestep for img2img
+  println!("Adding noise to latents for t_start={}", t_start);
+  let noise = init_latents.randn_like(0f64, 1f64)?;
+  let latents = scheduler.add_noise(&init_latents, noise, t_start)?;
+
+  println!("Latents initialized successfully");
+  println!("Initial noise shape: {:?}", latents.shape());
+
+  println!("Starting diffusion process...");
+
+  let mut latents = latents;
+  let timesteps: Vec<_> = scheduler.timesteps().iter().copied().collect();
+
+  for (timestep_index, &timestep) in timesteps.iter().enumerate() {
+    println!("Processing step {}/{} @ timestamp = {}", timestep_index + 1, timesteps.len(), timestep);
+
+    let latent_model_input = if use_guide_scale { Tensor::cat(&[&latents, &latents], 0)? } else { latents.clone() };
+
+    let latent_model_input = scheduler.scale_model_input(latent_model_input, timestep);
+
+    // Use the guidance scale embedding in the UNet inference with the proper method name
+    let mut noise_pred = match unet.forward_with_guidance(&latent_model_input, timestep as f64, &text_embeddings, &guidance_scale_embedding) {
+      Ok(pred) => pred,
+      Err(e) => {
+        println!("UNet inference failed with error: {}", e);
+        return Err(anyhow::anyhow!("UNet inference failed: {}", e));
+      },
+    };
+
+    if use_guide_scale {
+      let chunks = noise_pred.chunk(2, 0)?;
+      let (noise_pred_uncond, noise_pred_text) = (&chunks[0], &chunks[1]);
+      noise_pred = (noise_pred_uncond + (guidance_scale * (noise_pred_text - noise_pred_uncond)?)?)?;
+    }
+
+    // Apply the LCM scheduler step
+    latents = scheduler.step(&noise_pred, timestep, &latents, timestep_index, configs.scheduler_steps)?;
+  }
+
+  println!("Diffusion process completed, decoding image...");
+  let image = vae.decode(&(latents / vae_scale)?)?;
+
+  println!("VAE decode completed");
+
+  println!("Scaling image back");
+  let image = ((image / 2.)? + 0.5)?;
+
+  println!("Normalized image values");
+  let image = (image.clamp(0f32, 1.)? * 255.)?;
+
+  println!("Convert to int8");
+  let image = image.to_dtype(DType::U8)?;
+
+  println!("Converted to 8-bit format");
+
+  let image = tensor_to_image_buffer(&image.i(0)?)?;
+
+  Ok(image)
+}
@@ -1,3 +1,4 @@
 pub mod get_vae_scale;
 pub mod infer_clip_text_embeddings;
-pub mod stable_diffusion_pipeline;
+pub mod stable_diffusion_pipeline;
+pub mod lcm_pipeline;
@@ -1,9 +1,12 @@
 use std::sync::{Arc, RwLock, RwLockReadGuard, RwLockWriteGuard};

+use crate::events::notification_event::{NotificationModelType, NotificationEvent};
 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;
 use crate::ml::model_file::StableDiffusionVersion;
+use crate::ml::model_type::ModelType;
+use crate::ml::models::unet_model::UNetModel;
 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;
@@ -15,8 +18,7 @@ use image::DynamicImage;
 use log::info;
 use rand::Rng;
 use tauri::{AppHandle, Emitter};
-use crate::events::notification_event::{ModelType, NotificationEvent};
-use crate::ml::models::unet_model::UNetModel;
+use crate::state::app_dir::AppDataRoot;

 pub struct Args<'a> {
    pub image: &'a DynamicImage,
@@ -27,6 +29,7 @@ pub struct Args<'a> {
    pub configs: &'a AppConfig,
    pub model_cache: &'a ModelCache,
    pub prompt_cache: &'a PromptCache,
+    pub app_data_root: &'a AppDataRoot,
    pub app: &'a AppHandle,
 }

@@ -40,9 +43,12 @@ pub fn stable_diffusion_pipeline(args: Args<'_>) -> Result<RgbImage> {
        model_cache, 
        prompt_cache, 
        app, 
-        image,  
+        image,
+        app_data_root,
    } = args;
    
+    let weights_dir = app_data_root.weights_dir();
+    
    println!("Starting image generation with the following configuration:");
    println!("  Model: {:?}", configs.sd_version);
    println!("  Prompt: {}", prompt);
@@ -97,6 +103,7 @@ pub fn stable_diffusion_pipeline(args: Args<'_>) -> Result<RgbImage> {
            &configs.device,
            configs.dtype,
            use_guide_scale,
+            weights_dir,
        )?;
        prompt_cache.store_copy(&prompt, &tensor)?;
        tensor
@@ -122,25 +129,18 @@ pub fn stable_diffusion_pipeline(args: Args<'_>) -> Result<RgbImage> {
        None => {
            info!("No vae found in cache; loading...");
            
-            let repo = configs.sd_version.repo();
-
-            println!("Building VAE model from : {:?} ... (3)", repo);
-
-            let vae_file = configs.hf_api.model(repo.to_string())
-              .get("vae/diffusion_pytorch_model.safetensors")?;
-
-            println!("Building VAE model from file {:?}...", &vae_file);
-
            let mut notify_download_complete = false;
            //if !vae_file.exists() {
            if true {
                notify_download_complete = true;
                app.emit("notification", NotificationEvent::ModelDownloadStarted {
-                    model_name: repo,
-                    model_type: ModelType::Vae,
+                    model_name: "sdxl-turbo-vae",
+                    model_type: NotificationModelType::Vae,
                })?;
            }
            
+            let vae_file = weights_dir.model_path(&ModelType::SdxlTurboVae);
+            
            let vae = configs
              .sd_config
              .build_vae(vae_file, &configs.device, configs.dtype)?;
@@ -151,8 +151,8 @@ pub fn stable_diffusion_pipeline(args: Args<'_>) -> Result<RgbImage> {
            
            if notify_download_complete {
                app.emit("notification", NotificationEvent::ModelDownloadComplete {
-                    model_name: repo,
-                    model_type: ModelType::Vae,
+                    model_name: "sdxl-turbo-vae",
+                    model_type: NotificationModelType::Vae,
                })?;
            }
            
@@ -167,23 +167,17 @@ pub fn stable_diffusion_pipeline(args: Args<'_>) -> Result<RgbImage> {
        None => {
            info!("No unet found in cache; loading...");

-            let repo = configs.sd_version.repo();
-
-            info!("Downloading UNET model files from: {} ...", repo);
-
-            let unet_file = configs.hf_api.model(repo.to_string())
-              .get("unet/diffusion_pytorch_model.safetensors")
-              .map_err(|err| anyhow!("error fetching model: {:?}", err))?;
-
            let mut notify_download_complete = false;
            //if !unet_file.exists() {
            if true {
                notify_download_complete = true;
                app.emit("notification", NotificationEvent::ModelDownloadStarted {
-                    model_name: repo,
-                    model_type: ModelType::Unet,
+                    model_name: "sdxl-turbo-unet",
+                    model_type: NotificationModelType::Unet,
                })?;
            }
+            
+            let unet_file = weights_dir.model_path(&ModelType::SdxlTurboUnet);

            let unet = UNetModel::new(&configs.sd_config, unet_file, &configs.device, configs.dtype)
              .map_err(|err| anyhow!("error initializing unet model: {:?}", err))?;
@@ -194,8 +188,8 @@ pub fn stable_diffusion_pipeline(args: Args<'_>) -> Result<RgbImage> {

            if notify_download_complete {
                app.emit("notification", NotificationEvent::ModelDownloadComplete {
-                    model_name: repo,
-                    model_type: ModelType::Unet,
+                    model_name: "sdxl-turbo-unet",
+                    model_type: NotificationModelType::Unet,
                })?;
            }

@@ -1,18 +1,19 @@
 use crate::ml::model_file::StableDiffusionVersion;
+use crate::state::app_dir::AppDataRoot;
+use crate::state::os_platform::OsPlatform;
 use crate::state::yaml_config::YamlConfig;
 use candle_core::{DType, Device};
 use candle_transformers::models::stable_diffusion::StableDiffusionConfig;
 use filesys::recursively_find_file_by_name::recursively_find_file_by_name;
 use hf_hub::api::sync::Api;
 use log::info;
+use std::path::PathBuf;

-const CONFIG_FILENAME : &str = "app_config.yaml";
-
-const DEFAULT_SD_IMAGE_WIDTH: usize = 512;
-const DEFAULT_SD_IMAGE_HEIGHT: usize = 512;
+const DEFAULT_SD_IMAGE_WIDTH: usize = 1024;
+const DEFAULT_SD_IMAGE_HEIGHT: usize = 1024;

 const DEFAULT_SD_NUMERIC_DATATYPE: DType = DType::F32;
-const SD_VERSION: StableDiffusionVersion = StableDiffusionVersion::Turbo;
+const SD_VERSION: StableDiffusionVersion = StableDiffusionVersion::V1_5;

 /// A central place to configure app-wide details.
 pub struct AppConfig {
@@ -37,13 +38,15 @@ pub struct AppConfig {
  
  /// Probably shouldn't be here.
  pub hf_api: Api,
+  
+  /// Root location for application data.
+  pub app_data_root: AppDataRoot,
 }

 impl AppConfig {
  
  pub fn init() -> anyhow::Result<Self> {
-    println!("Configuration filename: {}", CONFIG_FILENAME);
-    let yaml_configs = load_yaml_configs();
+    let yaml_configs = YamlConfig::load_from_config_file_recursive();
    
    println!("Configs: {:?}", yaml_configs);
    
@@ -52,18 +55,42 @@ impl AppConfig {
          info!("CUDA not available ({}), falling back to CPU", e);
          Device::Cpu
        });
+
    
    let sd_config = match SD_VERSION {
      StableDiffusionVersion::Turbo => {
        StableDiffusionConfig::sdxl_turbo(None, Some(DEFAULT_SD_IMAGE_HEIGHT), Some(DEFAULT_SD_IMAGE_WIDTH))
      }
-      _ => {
+      StableDiffusionVersion::V1_5 | StableDiffusionVersion::V1_5Inpaint => {
+        StableDiffusionConfig::v1_5(None, Some(DEFAULT_SD_IMAGE_HEIGHT), Some(DEFAULT_SD_IMAGE_WIDTH))
+      }
+      StableDiffusionVersion::V2_1 | StableDiffusionVersion::V2Inpaint => {
        StableDiffusionConfig::v2_1(None, Some(DEFAULT_SD_IMAGE_HEIGHT), Some(DEFAULT_SD_IMAGE_WIDTH))
      }
+      StableDiffusionVersion::Xl | StableDiffusionVersion::XlInpaint => {
+        StableDiffusionConfig::sdxl(None, Some(DEFAULT_SD_IMAGE_HEIGHT), Some(DEFAULT_SD_IMAGE_WIDTH))
+      }
    };
    
    let hf_api = Api::new()?;
    
+    let os_platform = OsPlatform::get();
+
+    let default_data_root = match os_platform {
+      OsPlatform::Linux => yaml_configs.linux_default_data_path.as_deref(),
+      OsPlatform::MacOs => yaml_configs.mac_default_data_path.as_deref(),
+      OsPlatform::Windows => yaml_configs.windows_default_data_path.as_deref(),
+    };
+    
+    println!("Possible user-defined data root: {:?}", default_data_root);
+
+    let app_data_root = match default_data_root {
+      None => AppDataRoot::create_default()?,
+      Some(path) => AppDataRoot::create_existing(path)?,
+    };
+
+    println!("App data root: {:?}", app_data_root.path());
+
    Ok(Self {
      device,
      dtype: DEFAULT_SD_NUMERIC_DATATYPE,
@@ -71,26 +98,12 @@ impl AppConfig {
      sd_config,
      image_height: yaml_configs.image_height.unwrap_or(DEFAULT_SD_IMAGE_HEIGHT),
      image_width: yaml_configs.image_width.unwrap_or(DEFAULT_SD_IMAGE_WIDTH),
-      scheduler_steps: yaml_configs.scheduler_steps.unwrap_or(1),
+      scheduler_steps: yaml_configs.scheduler_steps.unwrap_or(4),
      scheduler_samples: yaml_configs.scheduler_samples.unwrap_or(15),
      seed: yaml_configs.seed,
      cfg_scale: yaml_configs.cfg_scale,
      hf_api,
+      app_data_root,
    })
  }
 }
-
-fn load_yaml_configs() -> YamlConfig {
-  let maybe_path = recursively_find_file_by_name(CONFIG_FILENAME, "../../../", 5)
-    .ok()
-    .flatten();
-  if let Some(path) = maybe_path {
-    let path = path.canonicalize().unwrap_or(path);
-    println!("Attempting to load configs from: {:?}", &path);
-    if let Ok(config) = YamlConfig::read_from_file(path) {
-      return config;
-    }
-  }
-  println!("Loading default configs.");
-  YamlConfig::default()
-}
@@ -0,0 +1,186 @@
+use crate::ml::model_type::ModelType;
+use crate::state::expanduser::expanduser;
+use crate::state::os_platform::OsPlatform;
+use anyhow::anyhow;
+use directories::UserDirs;
+use std::path::{Path, PathBuf};
+use tempdir::TempDir;
+use tempfile::{Builder, NamedTempFile};
+const DEFAULT_DATA_DIR : &str = "artcraft";
+const ASSETS_SUBDIRECTORY : &str = "assets";
+const WEIGHTS_SUBDIRECTORY : &str = "weights";
+
+const TEMPORARY_SUBDIRECTORY : &str = "temp";
+
+/// The path to the application data directory, which includes "asset" and "weights" data.
+#[derive(Clone)]
+pub struct AppDataRoot {
+  path: PathBuf,
+  assets_dir: AppAssetsDir,
+  weights_dir: AppWeightsDir,
+  temp_dir: TemporaryDir,
+}
+
+#[derive(Clone)]
+pub struct AppAssetsDir {
+  path: PathBuf,
+}
+
+#[derive(Clone)]
+pub struct AppWeightsDir {
+  path: PathBuf,
+}
+
+#[derive(Clone)]
+pub struct TemporaryDir {
+  path: PathBuf,
+}
+
+impl AppDataRoot {
+  pub fn create_default() -> anyhow::Result<Self> {
+    let directory = get_default_data_dir()?;
+    Self::create_existing(directory)
+  }
+
+  pub fn create_existing<P: AsRef<Path>>(dir: P) -> anyhow::Result<Self> {
+    let mut dir = dir.as_ref().to_path_buf();
+    
+    match OsPlatform::get() {
+      OsPlatform::Linux | OsPlatform::MacOs => {
+        if let Some(d) = dir.as_os_str().to_str() {
+          dir = expanduser(d)?;
+        }
+      },
+      OsPlatform::Windows => {}
+    }
+    
+    if !dir.is_dir() {
+      println!("Creating directory {:?}", dir);
+      std::fs::create_dir_all(&dir)?;
+    }
+
+    match dir.canonicalize() {
+      Ok(d) => dir = d,
+      Err(err) => {
+        println!("Error canonicalizing {:?}: {}", dir, err);
+      }
+    }
+    
+    let assets_dir = AppAssetsDir::create_existing(dir.join(ASSETS_SUBDIRECTORY))?;
+    let weights_dir = AppWeightsDir::create_existing(dir.join(WEIGHTS_SUBDIRECTORY))?;
+    let temp_dir = TemporaryDir::create_existing(dir.join(TEMPORARY_SUBDIRECTORY))?;
+
+    Ok(Self {
+      path: dir,
+      assets_dir,
+      weights_dir,
+      temp_dir,
+    })
+  }
+  
+  pub fn assets_dir(&self) -> &AppAssetsDir {
+    &self.assets_dir
+  }
+  
+  pub fn weights_dir(&self) -> &AppWeightsDir {
+    &self.weights_dir
+  }
+
+  pub fn temp_dir(&self) -> &TemporaryDir {
+    &self.temp_dir
+  }
+
+  pub fn path(&self) -> &Path {
+    &self.path
+  }
+}
+
+impl AppAssetsDir {
+  pub fn create_existing<P: AsRef<Path>>(dir: P) -> anyhow::Result<Self> {
+    let mut dir = dir.as_ref().to_path_buf();
+    match dir.canonicalize() {
+      Ok(d) => dir = d,
+      Err(err) => {
+        println!("Error canonicalizing {:?}: {}", dir, err);
+      }
+    }
+    if !dir.exists() {
+      println!("Creating directory {:?}", dir);
+      std::fs::create_dir(&dir)?;
+    }
+    Ok(Self {
+      path: dir,
+    })
+  }
+
+  pub fn path(&self) -> &Path {
+    &self.path
+  }
+}
+
+impl AppWeightsDir {
+  pub fn create_existing<P: AsRef<Path>>(dir: P) -> anyhow::Result<Self> {
+    let mut dir = dir.as_ref().to_path_buf();
+    match dir.canonicalize() {
+      Ok(d) => dir = d,
+      Err(err) => {
+        println!("Error canonicalizing {:?}: {}", dir, err);
+      }
+    }
+    if !dir.exists() {
+      println!("Creating directory {:?}", dir);
+      std::fs::create_dir(&dir)?;
+    }
+    Ok(Self {
+      path: dir,
+    })
+  }
+
+  pub fn path(&self) -> &Path {
+    &self.path
+  }
+  
+  pub fn model_path(&self, model_registry: &ModelType) -> PathBuf {
+    self.path.join(model_registry.get_filename())
+  }
+}
+
+impl TemporaryDir {
+  pub fn create_existing<P: AsRef<Path>>(dir: P) -> anyhow::Result<Self> {
+    let mut dir = dir.as_ref().to_path_buf();
+    match dir.canonicalize() {
+      Ok(d) => dir = d,
+      Err(err) => {
+        println!("Error canonicalizing {:?}: {}", dir, err);
+      }
+    }
+    if !dir.exists() {
+      println!("Creating directory {:?}", dir);
+      std::fs::create_dir(&dir)?;
+    }
+    Ok(Self {
+      path: dir,
+    })
+  }
+
+  pub fn with_prefix(&self, prefix: &str) -> anyhow::Result<TempDir> {
+    let tempdir = TempDir::new_in(&self.path, prefix)?;
+    Ok(tempdir)
+  }
+
+  pub fn new_named_temp_file(&self) -> anyhow::Result<NamedTempFile> {
+    let tempfile = Builder::new()
+      .prefix("temp_")
+      .suffix(".bin")
+      .tempfile_in(&self.path)?;
+    Ok(tempfile)
+  }
+}
+
+// eg. /home/bob/artcraft, /Users/bob/artcraft, or C:\Users\Alice\artcraft
+fn get_default_data_dir() -> anyhow::Result<PathBuf> {
+  Ok(UserDirs::new()
+      .ok_or_else(|| anyhow!("could not determine user home directory"))?
+      .home_dir()
+      .join(DEFAULT_DATA_DIR))
+}
@@ -0,0 +1,73 @@
+use once_cell::sync::Lazy;
+use std::io;
+use std::path::{PathBuf, MAIN_SEPARATOR};
+
+static PREFIX: Lazy<String> = Lazy::new(|| format!("~{}", MAIN_SEPARATOR));
+
+/// The "expanduser" crate doesn't compile on Windows, so we replace its functionality slightly
+pub fn expanduser<P: AsRef<str>>(path: P) -> io::Result<PathBuf> {
+
+   Ok(match path.as_ref() {
+       // matches an exact "~"
+       s if s == "~" => {
+           home_dir()?
+       },
+       // matches paths that start with `~/`
+       s if s.starts_with(&*PREFIX) => {
+           let home = home_dir()?;
+           home.join(&s[2..])
+       },
+       // // matches paths that start with `~` but not `~/`, might be a `~username/` path
+       // s if s.starts_with("~") => {
+       //     let mut parts = s[1..].splitn(2, MAIN_SEPARATOR);
+       //     let user = parts.next()
+       //         .ok_or_else(|| io::Error::new(io::ErrorKind::Other, "malformed path"))?;
+       //     let user = Passwd::from_name(&user)
+       //         .map_err(|_| io::Error::new(io::ErrorKind::Other, "error searching for user"))?
+       //         .ok_or_else(|| io::Error::new(io::ErrorKind::Other, format!("user '{}', does not exist", &user)))?;
+       //     if let Some(ref path) = parts.next() {
+       //         PathBuf::from(user.dir).join(&path)
+       //     } else {
+       //         PathBuf::from(user.dir)
+       //     }
+       // },
+       // nothing to expand, just make a PathBuf
+       s => PathBuf::from(s)
+   })
+}
+
+pub fn home_dir() -> io::Result<PathBuf> {
+    dirs::home_dir()
+        .ok_or_else(|| io::Error::new(io::ErrorKind::Other, "no home directory is set"))
+}
+
+#[cfg(test)]
+mod tests {
+    use crate::state::expanduser::expanduser;
+    use std::env;
+    use std::path::PathBuf;
+
+    #[test]
+    #[serial_test::serial]
+    fn test_success() {
+        let old_home = env::var("HOME").expect("no home dir set");
+        let new_home = "/home/foo";
+        env::set_var("HOME", new_home);
+        let path = expanduser("~/path/to/directory");
+        env::set_var("HOME", old_home);
+        assert_eq!(path.expect("io error"), PathBuf::from("/home/foo/path/to/directory"));
+    }
+
+    #[test]
+    #[serial_test::serial]
+    fn test_only_tilde() {
+        let old_home = env::var("HOME").expect("no home dir set");
+        let new_home = "/home/foo";
+        env::set_var("HOME", new_home);
+        let pathstr = "~";
+        let path = expanduser(pathstr);
+        env::set_var("HOME", old_home);
+        assert_eq!(path.expect("io error"), PathBuf::from("/home/foo"));
+    }
+
+}
@@ -1,2 +1,5 @@
+pub mod app_config;
+pub mod app_dir;
+pub mod os_platform;
 pub mod yaml_config;
-pub mod app_config;
+pub mod expanduser;
@@ -0,0 +1,20 @@
+
+#[derive(Copy,Clone,Eq,PartialEq,Debug)]
+pub enum OsPlatform {
+  Linux,
+  MacOs,
+  Windows,
+}
+
+impl OsPlatform {
+  pub fn get() -> OsPlatform {
+    // Totally scientific.
+    // https://doc.rust-lang.org/std/env/consts/constant.OS.html
+    match std::env::consts::OS {
+      "linux" => OsPlatform::Linux,
+      "windows" => OsPlatform::Windows,
+      "macos" | "apple" => OsPlatform::MacOs,
+      _ => OsPlatform::Linux,
+    }
+  }
+}
@@ -1,7 +1,10 @@
+use filesys::recursively_find_file_by_name::recursively_find_file_by_name;
 use std::fs::File;
 use std::io::BufReader;
 use std::path::Path;

+const CONFIG_FILENAME : &str = "app_config.yaml";
+
 /// Configuration read or derived from a YAML config file at startup
 /// This is not meant to contain any runtime config values.
 /// This may not be exhaustive.
@@ -13,6 +16,15 @@ pub struct YamlConfig {
  pub scheduler_samples: Option<usize>,
  pub seed: Option<u64>,
  pub cfg_scale: Option<f64>,
+
+  /// Override the default location to store data on Linux
+  pub linux_default_data_path: Option<String>,
+
+  /// Override the default location to store data on Windows
+  pub windows_default_data_path: Option<String>,
+  
+  /// Override the default location to store data on Mac
+  pub mac_default_data_path: Option<String>,
 }

 impl YamlConfig {
@@ -22,4 +34,19 @@ impl YamlConfig {
    let config = serde_yaml::from_reader(reader)?;
    Ok(config)
  }
+
+  pub fn load_from_config_file_recursive() -> YamlConfig {
+    let maybe_path = recursively_find_file_by_name(CONFIG_FILENAME, "../../../", 5)
+      .ok()
+      .flatten();
+    if let Some(path) = maybe_path {
+      let path = path.canonicalize().unwrap_or(path);
+      println!("Attempting to load configs from: {:?}", &path);
+      if let Ok(config) = YamlConfig::read_from_file(path) {
+        return config;
+      }
+    }
+    println!("Couldn't load config file. Using default configs.");
+    YamlConfig::default()
+  }
 }
@@ -0,0 +1,172 @@
+use crate::events::notification_event::{NotificationEvent, NotificationModelType};
+use crate::ml::model_type::ModelType;
+use crate::state::app_dir::AppDataRoot;
+use crate::transfer::download::{download_async, ProgressUpdate};
+use futures::stream::FuturesUnordered;
+use futures::StreamExt;
+use log::{debug, error, info};
+use std::collections::VecDeque;
+use std::path::PathBuf;
+use std::sync::mpsc::Receiver;
+use std::sync::{Arc, Mutex};
+use tauri::{AppHandle, Emitter};
+use tempfile::NamedTempFile;
+use tokio::task::JoinHandle;
+
+const NOTIFICATION_CHANNEL_NAME : &str = "notification";
+const MAX_FILES : usize = 8;
+const CHUNK_SIZE : usize = 1024 * 1024;
+const PARALLEL_FAILURES : usize = 8;
+const MAX_RETRIES : usize = 30;
+
+struct ModelDownloadStatusChannel {
+  pub model_name: String,
+  pub model_type: NotificationModelType,
+  pub final_file_path: PathBuf,
+  pub receiver: Receiver<ProgressUpdate>,
+}
+
+pub async fn downloader_thread(app_data_root: AppDataRoot, app: AppHandle) -> ! {
+
+  let mut status_check_queue : Arc<Mutex<Vec<ModelDownloadStatusChannel>>> = Arc::new(Mutex::new(Vec::new()));
+
+  {
+    let status_check_queue2 = status_check_queue.clone();
+    let app2 = app.clone();
+
+    tokio::spawn(download_notify_thread(status_check_queue2, app2));
+  }
+
+  let mut download_queue = VecDeque::new();
+
+  // TODO: Automatic enqueue of known important models + enqueue new models on-demand
+  download_queue.push_back(ModelType::ClipJson);
+  //download_queue.push_back(ModelType::SdxlTurboUnet);
+  //download_queue.push_back(ModelType::SdxlTurboVae);
+  download_queue.push_back(ModelType::SdxlTurboClipEncoder); // TODO(bt): Why is this still needed?
+  //download_queue.push_back(ModelType::SdxlTurboClipEncoder2);
+  download_queue.push_back(ModelType::SimianLuoLcmDreamshaperV7Unet);
+  download_queue.push_back(ModelType::LykonDreamshaper7Vae);
+  download_queue.push_back(ModelType::LykonDreamshaper7TextEncoderFp16);
+
+  let mut handles = FuturesUnordered::new();
+
+  while let Some(model) = download_queue.pop_front() {
+    let url = model.get_download_url().to_string();
+
+    let filename = app_data_root.weights_dir().model_path(&model);
+
+    if filename.exists() {
+      info!("File already exists: {:?}", &filename);
+      continue;
+    }
+
+    let headers = None;
+    
+    let (tx, rx) = std::sync::mpsc::channel();
+
+    info!("Download: {:?}", filename);
+
+    let temp_file = match app_data_root.temp_dir().new_named_temp_file() {
+      Ok(file) => file,
+      Err(err) => {
+        error!("Couldn't create a temporary file: {:?}", err);
+        continue;
+      }
+    };
+
+    let result = app.emit(NOTIFICATION_CHANNEL_NAME, NotificationEvent::ModelDownloadStarted {
+      model_name: model.get_name(),
+      model_type: model.get_notification_type(),
+    });
+
+    if let Err(err) = result {
+      error!("Could not emit event: {}", err);
+    }
+
+    let task = tokio::spawn(download_async(
+      url,
+      temp_file,
+      filename.clone(),
+      MAX_FILES,
+      CHUNK_SIZE,
+      PARALLEL_FAILURES,
+      MAX_RETRIES,
+      headers,
+      Some(tx),
+    ));
+
+    match status_check_queue.lock() {
+      Err(err) => error!("Could not unlock: {:?}", err),
+      Ok(mut lock) => {
+        lock.push(ModelDownloadStatusChannel {
+          receiver: rx,
+          final_file_path: filename.clone(),
+          model_name: model.get_name().to_string(),
+          model_type: model.get_notification_type(),
+        })
+      }
+    }
+
+    handles.push(task);
+  }
+
+  while let Some(result) = handles.next().await {
+    match result {
+      Err(err) => error!("Error downloading: {:?}", err),
+      Ok(_) => {},
+    }
+  }
+
+  loop {
+    // TODO(bt,2025-03-10): Queue management for new files entering the queue.
+    tokio::time::sleep(std::time::Duration::from_millis(60_000)).await;
+  }
+}
+
+pub async fn download_notify_thread(queue: Arc<Mutex<Vec<ModelDownloadStatusChannel>>>, app: AppHandle) -> ! {
+  loop {
+    match queue.lock() {
+      Err(err) => error!("Could not unlock: {:?}", err),
+      Ok(mut lock) => {
+        debug!(">>>>> Notifier has {} items", lock.len());
+
+        let mut reenqueue = Vec::with_capacity(lock.len());
+
+        for item in (*lock).drain(..) {
+          if let Ok(update) = item.receiver.try_recv() {
+            let result = app.emit(NOTIFICATION_CHANNEL_NAME, NotificationEvent::ModelDownloadProgress {
+              model_name: &item.model_name,
+              model_type: item.model_type,
+              currently_downloaded_bytes: update.complete,
+              total_file_bytes: update.total_length,
+            });
+
+            if let Err(err) = result {
+              error!("Could not emit event: {}", err);
+            }
+          }
+
+          if item.final_file_path.exists() {
+            debug!("No longer sending notifications for {:?}", &item.final_file_path);
+
+            let result = app.emit(NOTIFICATION_CHANNEL_NAME, NotificationEvent::ModelDownloadComplete {
+              model_name: &item.model_name,
+              model_type: item.model_type,
+            });
+
+            if let Err(err) = result {
+              error!("Could not emit event: {}", err);
+            }
+          } else {
+            reenqueue.push(item);
+          }
+        }
+
+        lock.extend(reenqueue);
+      }
+    }
+
+    tokio::time::sleep(std::time::Duration::from_millis(500)).await;
+  }
+}
@@ -0,0 +1 @@
+pub mod downloader_thread;
@@ -0,0 +1,241 @@
+//! Implemented from https://github.com/huggingface/hf_transfer/blob/main/src/lib.rs
+
+use crate::transfer::error::Error;
+use crate::transfer::util::{exponential_backoff, BASE_WAIT_TIME, MAX_WAIT_TIME};
+use futures::stream::FuturesUnordered;
+use futures::StreamExt;
+use reqwest::header::{
+  HeaderMap, HeaderName, HeaderValue, AUTHORIZATION, CONTENT_RANGE,
+  RANGE,
+};
+use reqwest::Url;
+use std::collections::HashMap;
+use std::fmt::Display;
+use std::fs::remove_file;
+use std::io::SeekFrom;
+use std::path::Path;
+use std::sync::Arc;
+use std::sync::atomic::{AtomicUsize, Ordering};
+use std::sync::mpsc::Sender;
+use std::time::Duration;
+use log::info;
+use tempfile::NamedTempFile;
+use tokio::fs::OpenOptions;
+use tokio::io::AsyncWriteExt;
+use tokio::io::AsyncSeekExt;
+use tokio::sync::Semaphore;
+use tokio::time::sleep;
+
+pub struct ProgressUpdate {
+  pub complete: usize,
+  pub total_length: usize,
+}
+
+/// max_files: Number of open file handles, which determines the maximum number of parallel downloads
+/// parallel_failures:  Number of maximum failures of different chunks in parallel (cannot exceed max_files)
+/// max_retries: Number of maximum attempts per chunk. (Retries are exponentially backed off + jitter)
+///
+/// The number of threads can be tuned by the environment variable `TOKIO_WORKER_THREADS` as documented in
+/// https://docs.rs/tokio/latest/tokio/runtime/struct.Builder.html#method.worker_threads
+#[allow(clippy::too_many_arguments)]
+pub async fn download_async<P: AsRef<Path>>(
+  url: String,
+  filename: NamedTempFile,
+  final_filename: P,
+  max_files: usize,
+  chunk_size: usize,
+  parallel_failures: usize,
+  max_retries: usize,
+  input_headers: Option<HashMap<String, String>>,
+  maybe_progress_sender: Option<Sender<ProgressUpdate>>,
+) -> Result<(), Error> {
+  info!(">>> Downloading: {}", filename.as_ref().display());
+
+  let client = reqwest::Client::builder()
+    // https://github.com/hyperium/hyper/issues/2136#issuecomment-589488526
+    .http2_keep_alive_timeout(Duration::from_secs(15))
+    .build()?;
+
+  let mut headers = HeaderMap::new();
+  let mut auth_token = None;
+  if let Some(input_headers) = input_headers {
+    headers.reserve(input_headers.len());
+    for (k, v) in input_headers {
+      let name: HeaderName = k
+        .try_into()
+        .map_err(|err| Error::new_err(format!("Invalid header: {err}")))?;
+      let value: HeaderValue = AsRef::<str>::as_ref(&v)
+        .try_into()
+        .map_err(|err| Error::new_err(format!("Invalid header value: {err}")))?;
+      if name == AUTHORIZATION {
+        auth_token = Some(value);
+      } else {
+        headers.insert(name, value);
+      }
+    }
+  };
+
+  let response = if let Some(token) = auth_token.as_ref() {
+    client.get(&url).header(AUTHORIZATION, token)
+  } else {
+    client.get(&url)
+  }
+    .headers(headers.clone())
+    .header(RANGE, "bytes=0-0")
+    .send()
+    .await
+    .map_err(|err| Error::new_err(format!("Error while downloading: {err}")))?
+    .error_for_status()
+    .map_err(|err| Error::new_err(err.to_string()))?;
+
+  // Only call the final redirect URL to avoid overloading the Hub with requests and also
+  // altering the download count
+  let redirected_url = response.url();
+  if Url::parse(&url)
+    .map_err(|err| Error::new_err(format!("failed to parse url: {err}")))?
+    .host()
+    == redirected_url.host()
+  {
+    if let Some(token) = auth_token {
+      headers.insert(AUTHORIZATION, token);
+    }
+  }
+
+  let content_range = response
+    .headers()
+    .get(CONTENT_RANGE)
+    .ok_or(Error::new_err("No content length".to_string()))?
+    .to_str()
+    .map_err(|err| Error::new_err(format!("Error while downloading: {err}")))?;
+
+  let size: Vec<&str> = content_range.split('/').collect();
+  // Content-Range: bytes 0-0/702517648
+  // https://developer.mozilla.org/en-US/docs/Web/HTTP/Headers/Content-Range
+  let length: usize = size
+    .last()
+    .ok_or(Error::new_err(
+      "Error while downloading: No size was detected".to_string(),
+    ))?
+    .parse()
+    .map_err(|err| Error::new_err(format!("Error while downloading: {err}")))?;
+
+
+  info!("File {:?} is {:?} length", filename.as_ref(), length);
+
+  let mut handles = FuturesUnordered::new();
+  let semaphore = Arc::new(Semaphore::new(max_files));
+  let parallel_failures_semaphore = Arc::new(Semaphore::new(parallel_failures));
+  let max_chunk_complete = Arc::new(AtomicUsize::new(0));
+
+  for start in (0..length).step_by(chunk_size) {
+    let url = redirected_url.to_string();
+    let filename = filename.as_ref().to_owned();
+    let client = client.clone();
+    let headers = headers.clone();
+
+    let stop = std::cmp::min(start + chunk_size - 1, length);
+    let semaphore = semaphore.clone();
+    let parallel_failures_semaphore = parallel_failures_semaphore.clone();
+    let maybe_progress = maybe_progress_sender.clone();
+    let max_chunk_complete = max_chunk_complete.clone();
+    handles.push(tokio::spawn(async move {
+      let permit = semaphore
+        .acquire_owned()
+        .await
+        .map_err(|err| Error::new_err(format!("Error while downloading: {err}")))?;
+      let mut chunk = download_chunk(&client, &url, &filename, start, stop, headers.clone()).await;
+      let mut i = 0;
+      if parallel_failures > 0 {
+        while let Err(dlerr) = chunk {
+          if i >= max_retries {
+            return Err(Error::new_err(format!(
+              "Failed after too many retries ({max_retries}): {dlerr}"
+            )));
+          }
+          let parallel_failure_permit = parallel_failures_semaphore.clone().try_acquire_owned().map_err(|err| {
+            Error::new_err(format!(
+              "Failed too many failures in parallel ({parallel_failures}): {dlerr} ({err})"
+            ))
+          })?;
+
+          let wait_time = exponential_backoff(BASE_WAIT_TIME, i, MAX_WAIT_TIME);
+          sleep(Duration::from_millis(wait_time as u64)).await;
+
+          chunk = download_chunk(&client, &url, &filename, start, stop, headers.clone()).await;
+          i += 1;
+          drop(parallel_failure_permit);
+          
+          if let Some(sender) = maybe_progress.as_ref() {
+            // NB: Calling fetch_max twice. First call will return the lower value.
+            let _old = max_chunk_complete.fetch_max(stop, Ordering::SeqCst);
+            let max_chunk = max_chunk_complete.fetch_max(stop, Ordering::SeqCst);
+            let progress_update = ProgressUpdate { 
+              complete: max_chunk,
+              total_length: length,
+            };
+            if let Err(_err) = sender.send(progress_update) {
+              // Fail silently, not essential to issue progress updates
+            }
+          }
+        }
+      }
+      drop(permit);
+      chunk.map_err(|e| Error::new_err(format!("Downloading error {e}"))).and(Ok(stop - start))
+    }));
+  }
+
+  // Output the chained result
+  while let Some(result) = handles.next().await {
+    match result {
+      Ok(Ok(size)) => {
+        //if let Some(ref callback) = callback {
+        //  callback.call((size,), None)?;
+        //}
+      }
+      Ok(Err(py_err)) => {
+        return Err(py_err);
+      }
+      Err(err) => {
+        return Err(Error::new_err(format!(
+          "Error while downloading: {err}"
+        )));
+      }
+    }
+  }
+
+  let file = filename.persist(final_filename)
+    .map_err(|e| Error::new_err(format!("Could not rename to final filename: {:?}", e)))?;
+
+  file.sync_all()?;
+
+  Ok(())
+}
+
+async fn download_chunk<P: AsRef<Path>>(
+  client: &reqwest::Client,
+  url: &str,
+  filename: P,
+  start: usize,
+  stop: usize,
+  headers: HeaderMap,
+) -> Result<(), Error> {
+  // Process each socket concurrently.
+  let range = format!("bytes={start}-{stop}");
+  let mut file = OpenOptions::new()
+    .write(true)
+    .truncate(false)
+    .create(true)
+    .open(filename)
+    .await?;
+  file.seek(SeekFrom::Start(start as u64)).await?;
+  let response = client
+    .get(url)
+    .headers(headers)
+    .header(RANGE, range)
+    .send()
+    .await?
+    .error_for_status()?;
+  let content = response.bytes().await?;
+  file.write_all(&content).await?;
+  Ok(())
+}
@@ -0,0 +1,49 @@
+//! Implemented from https://github.com/huggingface/hf_transfer/blob/main/src/lib.rs
+
+use std::fmt::Display;
+use reqwest::header::ToStrError;
+
+#[derive(Debug)]
+pub enum Error {
+  Io(std::io::Error),
+  Request(reqwest::Error),
+  ToStrError(ToStrError),
+  Misc(String),
+}
+
+impl From<std::io::Error> for Error {
+  fn from(value: std::io::Error) -> Self {
+    Self::Io(value)
+  }
+}
+
+impl From<reqwest::Error> for Error {
+  fn from(value: reqwest::Error) -> Self {
+    Self::Request(value)
+  }
+}
+
+impl From<ToStrError> for Error {
+  fn from(value: ToStrError) -> Self {
+    Self::ToStrError(value)
+  }
+}
+
+impl Display for Error {
+  fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+    match self {
+      Self::Io(io) => write!(f, "Io: {io}"),
+      Self::Request(req) => write!(f, "Request: {req}"),
+      Self::ToStrError(req) => write!(f, "Response non ascii: {req}"),
+      Self::Misc(err) => write!(f, "Misc error: {err}"),
+    }
+  }
+}
+
+impl std::error::Error for Error {}
+
+impl Error {
+  pub fn new_err(reason: String) -> Self {
+    Self::Misc(reason)
+  }
+}
@@ -0,0 +1,4 @@
+pub mod download;
+pub mod upload;
+pub mod util;
+pub mod error;
@@ -0,0 +1,189 @@
+//! Implemented from https://github.com/huggingface/hf_transfer/blob/main/src/lib.rs
+
+use crate::transfer::error::Error;
+use crate::transfer::util::{exponential_backoff, BASE_WAIT_TIME, MAX_WAIT_TIME};
+use futures::stream::FuturesUnordered;
+use futures::StreamExt;
+use reqwest::header::CONTENT_LENGTH;
+use std::collections::HashMap;
+use std::fmt::Display;
+use std::io::SeekFrom;
+use std::sync::Arc;
+use std::time::Duration;
+use tokio::fs::OpenOptions;
+use tokio::io::{AsyncReadExt, AsyncSeekExt};
+use tokio::sync::Semaphore;
+use tokio::time::sleep;
+use tokio_util::codec::{BytesCodec, FramedRead};
+
+/// parts_urls: Dictionary consisting of part numbers as keys and the associated url as values
+/// completion_url: The url that should be called when the upload is finished
+/// max_files: Number of open file handles, which determines the maximum number of parallel uploads
+/// parallel_failures:  Number of maximum failures of different chunks in parallel (cannot exceed max_files)
+/// max_retries: Number of maximum attempts per chunk. (Retries are exponentially backed off + jitter)
+///
+/// The number of threads can be tuned by the environment variable `TOKIO_WORKER_THREADS` as documented in
+/// https://docs.rs/tokio/latest/tokio/runtime/struct.Builder.html#method.worker_threads
+///
+/// See https://docs.aws.amazon.com/AmazonS3/latest/userguide/mpuoverview.html for more information
+/// on the multipart upload
+#[allow(clippy::too_many_arguments)]
+fn multipart_upload(
+  file_path: String,
+  parts_urls: Vec<String>,
+  chunk_size: u64,
+  max_files: usize,
+  parallel_failures: usize,
+  max_retries: usize,
+) -> Result<Vec<HashMap<String, String>>, Error> {
+  if parallel_failures > max_files {
+    return Err(Error::new_err(
+      "Error parallel_failures cannot be > max_files".to_string(),
+    ));
+  }
+  if (parallel_failures == 0) != (max_retries == 0) {
+    return Err(Error::new_err(
+      "For retry mechanism you need to set both `parallel_failures` and `max_retries`"
+        .to_string(),
+    ));
+  }
+
+  tokio::runtime::Builder::new_multi_thread()
+    .enable_all()
+    .build()?
+    .block_on(async {
+      upload_async(
+        file_path,
+        parts_urls,
+        chunk_size,
+        max_files,
+        parallel_failures,
+        max_retries,
+      )
+        .await
+    })
+}
+
+
+
+#[allow(clippy::too_many_arguments)]
+async fn upload_async(
+  file_path: String,
+  parts_urls: Vec<String>,
+  chunk_size: u64,
+  max_files: usize,
+  parallel_failures: usize,
+  max_retries: usize,
+) -> Result<Vec<HashMap<String, String>>, Error> {
+  let client = reqwest::Client::new();
+
+  let mut handles = FuturesUnordered::new();
+  let semaphore = Arc::new(Semaphore::new(max_files));
+  let parallel_failures_semaphore = Arc::new(Semaphore::new(parallel_failures));
+
+  for (part_number, part_url) in parts_urls.iter().enumerate() {
+    let url = part_url.to_string();
+    let path = file_path.to_owned();
+    let client = client.clone();
+
+    let start = (part_number as u64) * chunk_size;
+    let semaphore = semaphore.clone();
+    let parallel_failures_semaphore = parallel_failures_semaphore.clone();
+    handles.push(tokio::spawn(async move {
+      let permit = semaphore
+        .clone()
+        .acquire_owned()
+        .await
+        .map_err(|err| Error::new_err(format!("Error acquiring semaphore: {err}")))?;
+      let mut chunk = upload_chunk(&client, &url, &path, start, chunk_size).await;
+      let mut i = 0;
+      if parallel_failures > 0 {
+        while let Err(ul_err) = chunk {
+          if i >= max_retries {
+            return Err(Error::new_err(format!(
+              "Failed after too many retries ({max_retries}): {ul_err}"
+            )));
+          }
+
+          let parallel_failure_permit = parallel_failures_semaphore.clone().try_acquire_owned().map_err(|err| {
+            Error::new_err(format!(
+              "Failed too many failures in parallel ({parallel_failures}): {ul_err} ({err})"
+            ))
+          })?;
+
+          let wait_time = exponential_backoff(BASE_WAIT_TIME, i, MAX_WAIT_TIME);
+          sleep(Duration::from_millis(wait_time as u64)).await;
+
+          chunk = upload_chunk(&client, &url, &path, start, chunk_size).await;
+          i += 1;
+          drop(parallel_failure_permit);
+        }
+      }
+      drop(permit);
+      chunk.map_err(|e|{
+        //match e {
+        //  Error::Io(io) => Error::new_err(format!("Io error {io}")),
+        //  Error::Request(req) => Error::new_err(format!("Error while sending chunk {req}")),
+        //  Error::ToStrError(req) => Error::new_err(format!("Response header contains non ASCII chars: {req}")),
+        //}
+        e
+      }).map(|chunk| (part_number, chunk, chunk_size))
+    }));
+  }
+
+  let mut results: Vec<HashMap<String, String>> = vec![HashMap::default(); parts_urls.len()];
+
+  while let Some(result) = handles.next().await {
+    match result {
+      Ok(Ok((part_number, headers, size))) => {
+        //if let Some(ref callback) = callback {
+        //  callback.call((size,), None)?;
+        //}
+        results[part_number] = headers;
+      }
+      Ok(Err(py_err)) => {
+        return Err(py_err);
+      }
+      Err(err) => {
+        return Err(Error::new_err(format!(
+          "Error occurred while uploading: {err}"
+        )));
+      }
+    }
+  }
+
+  Ok(results)
+}
+
+async fn upload_chunk(
+  client: &reqwest::Client,
+  url: &str,
+  path: &str,
+  start: u64,
+  chunk_size: u64,
+) -> Result<HashMap<String, String>, Error> {
+  let mut options = OpenOptions::new();
+  let mut file = options.read(true).open(path).await?;
+  let file_size = file.metadata().await?.len();
+  let bytes_transferred = std::cmp::min(file_size - start, chunk_size);
+
+  file.seek(SeekFrom::Start(start)).await?;
+  let chunk = file.take(chunk_size);
+
+  let response = client
+    .put(url)
+    .header(CONTENT_LENGTH, bytes_transferred)
+    .body(reqwest::Body::wrap_stream(FramedRead::new(
+      chunk,
+      BytesCodec::new(),
+    )))
+    .send()
+    .await?;
+  let response = response.error_for_status()?;
+  let mut headers = HashMap::new();
+  for (name, value) in response.headers().into_iter() {
+    headers.insert(name.to_string(), value.to_str()?.to_owned());
+  }
+  Ok(headers)
+}
+
@@ -0,0 +1,15 @@
+//! Implemented from https://github.com/huggingface/hf_transfer/blob/main/src/lib.rs
+
+use rand::{thread_rng, Rng};
+use std::fmt::Display;
+
+pub const BASE_WAIT_TIME: usize = 300;
+pub const MAX_WAIT_TIME: usize = 10_000;
+
+fn jitter() -> usize {
+  thread_rng().gen_range(0..=500)
+}
+
+pub fn exponential_backoff(base_wait_time: usize, n: usize, max: usize) -> usize {
+  (base_wait_time + n.pow(2) + jitter()).min(max)
+}
@@ -1,6 +1,6 @@
 {
  "$schema": "https://schema.tauri.app/config/2.0.0-rc",
-  "productName": "Realtime Desktop App",
+  "productName": "ArtCraft",
  "version": "0.1.0",
  "identifier": "com.unique.value.thing.why",
  "build": {
@@ -12,9 +12,9 @@
  "app": {
    "windows": [
      {
-        "title": "Realtime Desktop App Title Goes Here",
-        "width": 1200,
-        "height": 800,
+        "title": "ArtCraft",
+        "width": 2400,
+        "height": 1300,
        "resizable": true,
        "fullscreen": false
      }
@@ -118,24 +118,40 @@ pub static DEVELOPMENT_PREMIUM_PLANS: Lazy<HashSet<Plan>> = Lazy::new(|| {

 /// All paid-for production premium plans in the system.
 pub static PRODUCTION_PREMIUM_PLANS: Lazy<HashSet<Plan>> = Lazy::new(|| {
-    let mut plans = HashSet::new();
+  let mut plans = HashSet::new();

-    // ========== All-locale plans ==========
+  // ========== All-locale plans ==========

-    plans.insert(PlanBuilder::new("fakeyou_plus")
-        .plan_category(PlanCategory::Paid)
-        .stripe_product_id("prod_MoLv23HrxPiY7D")
-        .stripe_price_id("price_1M4jDCEU5se17MekOaJ92HYX")
-        .cost_per_month_dollars(7)
-        .tts_base_priority_level(20)
-        .tts_max_character_length(2048)
-        .tts_max_duration_seconds(30)
-        .web_vc_base_priority_level(20)
-        .web_vc_requires_frontend_keepalive(false)
-        .lipsync_requires_frontend_keepalive(false)
-        .build());
+  // Old "plus" price
+  plans.insert(PlanBuilder::new("fakeyou_plus")
+      .plan_category(PlanCategory::Paid)
+      .stripe_product_id("prod_MoLv23HrxPiY7D")
+      .stripe_price_id("price_1M4jDCEU5se17MekOaJ92HYX")
+      .cost_per_month_dollars(7)
+      .tts_base_priority_level(20)
+      .tts_max_character_length(2048)
+      .tts_max_duration_seconds(30)
+      .web_vc_base_priority_level(20)
+      .web_vc_requires_frontend_keepalive(false)
+      .lipsync_requires_frontend_keepalive(false)
+      .build());

-    plans.insert(PlanBuilder::new("fakeyou_pro")
+  // New "plus" price
+  plans.insert(PlanBuilder::new("fakeyou_plus_plan")
+      .plan_category(PlanCategory::Paid)
+      .stripe_product_id("prod_RvC5qUgLTSLGSD")
+      .stripe_price_id("price_1R1Lh8EU5se17MekaUNtWc59")
+      .cost_per_month_dollars(12)
+      .tts_base_priority_level(20)
+      .tts_max_character_length(2048)
+      .tts_max_duration_seconds(30)
+      .web_vc_base_priority_level(20)
+      .web_vc_requires_frontend_keepalive(false)
+      .lipsync_requires_frontend_keepalive(false)
+      .build());
+
+  // Old "pro" price
+  plans.insert(PlanBuilder::new("fakeyou_pro")
        .plan_category(PlanCategory::Paid)
        .stripe_product_id("prod_MoLw8nA6eFxHzc")
        .stripe_price_id("price_1M4jEQEU5se17MeksNfA0EKm")
@@ -149,7 +165,23 @@ pub static PRODUCTION_PREMIUM_PLANS: Lazy<HashSet<Plan>> = Lazy::new(|| {
        .can_remove_visual_watermarks(true)
        .build());

-    plans.insert(PlanBuilder::new("fakeyou_elite")
+  // New "pro" price
+  plans.insert(PlanBuilder::new("fakeyou_pro_plan")
+      .plan_category(PlanCategory::Paid)
+      .stripe_product_id("prod_RvC6nB9rw6yAsI")
+      .stripe_price_id("price_1R1LhzEU5se17Mek3JLwN3Gg")
+      .cost_per_month_dollars(25)
+      .tts_base_priority_level(30)
+      .tts_max_character_length(3072)
+      .tts_max_duration_seconds(60 * 2)
+      .web_vc_base_priority_level(30)
+      .web_vc_requires_frontend_keepalive(false)
+      .lipsync_requires_frontend_keepalive(false)
+      .can_remove_visual_watermarks(true)
+      .build());
+
+  // Old "elite" price
+  plans.insert(PlanBuilder::new("fakeyou_elite")
        .plan_category(PlanCategory::Paid)
        .stripe_product_id("prod_MoLxQmLA4R24fv")
        .stripe_price_id("price_1M4jFREU5se17Mekc8pQaSKB")
@@ -163,6 +195,21 @@ pub static PRODUCTION_PREMIUM_PLANS: Lazy<HashSet<Plan>> = Lazy::new(|| {
        .can_remove_visual_watermarks(true)
        .build());

+  // New "elite" price
+  plans.insert(PlanBuilder::new("fakeyou_elite_plan")
+      .plan_category(PlanCategory::Paid)
+      .stripe_product_id("prod_RvC6i84YiAYStd")
+      .stripe_price_id("price_1R1LiQEU5se17MekiJdBcsHQ")
+      .cost_per_month_dollars(40)
+      .tts_base_priority_level(40)
+      .tts_max_character_length(4096)
+      .tts_max_duration_seconds(60 * 5)
+      .web_vc_base_priority_level(40)
+      .web_vc_requires_frontend_keepalive(false)
+      .lipsync_requires_frontend_keepalive(false)
+      .can_remove_visual_watermarks(true)
+      .build());
+
    // ========== Spanish plans ==========

    plans.insert(PlanBuilder::new("fakeyou_basic")
@@ -293,7 +340,7 @@ mod test {
    // making ourselves check twice when we make additions, removals, or other changes.
    #[test]
    fn test_number_of_plans_is_expected() {
-        assert_eq!(11, ALL_PLANS_BY_SLUG.len());
+        assert_eq!(14, ALL_PLANS_BY_SLUG.len());
    }

    #[test]
@@ -303,7 +350,7 @@ mod test {
            .filter(|plan| !plan.is_synthetic_plan()) // NB: Synthetic plans are production!
            .collect::<Vec<&Plan>>();

-        let expected = 4;
+        let expected = 7;

        assert_eq!(expected, production_plans.len());
        assert_eq!(expected, PRODUCTION_PREMIUM_PLANS.len());
@@ -346,6 +393,9 @@ mod test {
            "prod_MoLw8nA6eFxHzc".to_string(), // NB: Production
            "prod_MoLxQmLA4R24fv".to_string(), // NB: Production
            "prod_MoLyt8qMDmscjr".to_string(), // NB: Production
+            "prod_RvC5qUgLTSLGSD".to_string(), // NB: Production - new "plus" product
+            "prod_RvC6nB9rw6yAsI".to_string(), // NB: Production - new "pro" product
+            "prod_RvC6i84YiAYStd".to_string(), // NB: Production - new "elite" product
        ];

        assert_that(&product_ids).contains_all_of(&expected_product_ids.iter());
@@ -366,6 +416,9 @@ mod test {
            "price_1M4jEQEU5se17MeksNfA0EKm".to_string(), // NB: Production
            "price_1M4jFREU5se17Mekc8pQaSKB".to_string(), // NB: Production
            "price_1M4jGPEU5se17Mek2FiztNE5".to_string(), // NB: Production
+            "price_1R1Lh8EU5se17MekaUNtWc59".to_string(), // NB: Production - new "plus" price
+            "price_1R1LhzEU5se17Mek3JLwN3Gg".to_string(), // NB: Production - new "pro" price
+            "price_1R1LiQEU5se17MekiJdBcsHQ".to_string(), // NB: Production - new "elite" price
        ];

        assert_that(&price_ids).contains_all_of(&expected_price_ids.iter());
@@ -86,6 +86,8 @@ fn main() -> Result<()> {
        .arg("--expt-relaxed-constexpr")
        .arg("--expt-extended-lambda")
        .arg("--use_fast_math")
+        .arg("--compiler-options")
+        .arg("-fPIC")
        .arg("--verbose");

    if let Ok(target) = std::env::var("TARGET") {
@@ -100,7 +102,12 @@ fn main() -> Result<()> {
    println!("cargo:rustc-link-search={}", build_dir.display());
    println!("cargo:rustc-link-lib=flashattention");
    println!("cargo:rustc-link-lib=dylib=cudart");
-    println!("cargo:rustc-link-lib=dylib=stdc++");
+
+
+    // TODO(bt,2025-03-12): Fix builds on windows
+    //println!("cargo:rustc-link-lib=dylib=stdc++");
+
+

    Ok(())
 }
@@ -32,3 +32,4 @@ metal = ["candle/metal", "dep:candle-metal-kernels", "dep:metal"]
 [[bench]]
 name = "bench_main"
 harness = false
+
@@ -17,6 +17,7 @@ serde = { version = "1.0.171", features = ["derive"] }
 serde_json = "1.0.99"
 serde_plain = "1.0.2"
 tracing = "0.1.37"
+half = { version = "2.3.1", features = ["num-traits", "use-intrinsics", "rand_distr"] }

 [features]
 default = []
@@ -84,6 +84,8 @@ impl StableDiffusionConfig {
        };
        // https://huggingface.co/runwayml/stable-diffusion-v1-5/blob/main/unet/config.json
        let unet = unet_2d::UNet2DConditionModelConfig {
+            time_embed_dim: None,
+            time_cond_proj_dim: None,
            blocks: vec![
                bc(320, Some(1), 8),
                bc(640, Some(1), 8),
@@ -153,6 +155,8 @@ impl StableDiffusionConfig {
        };
        // https://huggingface.co/stabilityai/stable-diffusion-2-1/blob/main/unet/config.json
        let unet = unet_2d::UNet2DConditionModelConfig {
+            time_cond_proj_dim: None,
+            time_embed_dim: None,
            blocks: vec![
                bc(320, Some(1), 5),
                bc(640, Some(1), 10),
@@ -237,6 +241,8 @@ impl StableDiffusionConfig {
        };
        // https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/unet/config.json
        let unet = unet_2d::UNet2DConditionModelConfig {
+            time_cond_proj_dim: None,
+            time_embed_dim: None,
            blocks: vec![
                bc(320, None, 5),
                bc(640, Some(2), 10),
@@ -306,6 +312,8 @@ impl StableDiffusionConfig {
        };
        // https://huggingface.co/stabilityai/sdxl-turbo/blob/main/unet/config.json
        let unet = unet_2d::UNet2DConditionModelConfig {
+            time_cond_proj_dim: None,
+            time_embed_dim: None,
            blocks: vec![
                bc(320, None, 5),
                bc(640, Some(2), 10),
@@ -405,6 +413,8 @@ impl StableDiffusionConfig {
        };
        // https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/unet/config.json
        let unet = unet_2d::UNet2DConditionModelConfig {
+            time_cond_proj_dim: None,
+            time_embed_dim: None,
            blocks: vec![
                bc(320, None, 5),
                bc(640, Some(2), 10),
@@ -10,6 +10,10 @@ use candle_nn as nn;
 use candle_nn::Module;
 use std::collections::HashMap;

+// fn save_tensor_as_numpy(tensor: &Tensor, filename: &str) -> Result<()> {
+//     // Use Candle's built-in NPY serialization
+//     tensor.write_npy(filename).map_err(|e| anyhow::anyhow!("{}", e))
+// }
 #[derive(Debug, Clone, Copy)]
 pub struct BlockConfig {
  pub out_channels: usize,
@@ -33,11 +37,13 @@ pub struct UNet2DConditionModelConfig {
  pub cross_attention_dim: usize,
  pub sliced_attention_size: Option<usize>,
  pub use_linear_projection: bool,
+  pub time_cond_proj_dim: Option<usize>,
+  pub time_embed_dim: Option<usize>,
 }

 impl Default for UNet2DConditionModelConfig {
  fn default() -> Self {
-    Self { center_input_sample: false, flip_sin_to_cos: true, freq_shift: 0., blocks: vec![BlockConfig { out_channels: 320, use_cross_attn: Some(1), attention_head_dim: 8 }, BlockConfig { out_channels: 640, use_cross_attn: Some(1), attention_head_dim: 8 }, BlockConfig { out_channels: 1280, use_cross_attn: Some(1), attention_head_dim: 8 }, BlockConfig { out_channels: 1280, use_cross_attn: None, attention_head_dim: 8 }], layers_per_block: 2, downsample_padding: 1, mid_block_scale_factor: 1., norm_num_groups: 32, norm_eps: 1e-5, cross_attention_dim: 1280, sliced_attention_size: None, use_linear_projection: false }
+    Self { center_input_sample: false, flip_sin_to_cos: true, freq_shift: 0., blocks: vec![BlockConfig { out_channels: 320, use_cross_attn: Some(1), attention_head_dim: 8 }, BlockConfig { out_channels: 640, use_cross_attn: Some(1), attention_head_dim: 8 }, BlockConfig { out_channels: 1280, use_cross_attn: Some(1), attention_head_dim: 8 }, BlockConfig { out_channels: 1280, use_cross_attn: None, attention_head_dim: 8 }], layers_per_block: 2, downsample_padding: 1, mid_block_scale_factor: 1., norm_num_groups: 32, norm_eps: 1e-5, cross_attention_dim: 1280, sliced_attention_size: None, use_linear_projection: false, time_cond_proj_dim: Some(256), time_embed_dim: None }
  }
 }

@@ -73,8 +79,16 @@ impl UNet2DConditionModel {
    let b_channels = config.blocks[0].out_channels;
    let bl_channels = config.blocks.last().unwrap().out_channels;
    let bl_attention_head_dim = config.blocks.last().unwrap().attention_head_dim;
-    let time_embed_dim = b_channels * 4;
+    let time_embed_dim = config.time_embed_dim.unwrap_or(b_channels * 4);
    let conv_cfg = nn::Conv2dConfig { padding: 1, ..Default::default() };
+
+    // Log important configuration details
+    println!("Creating UNet2DConditionModel with {} blocks", n_blocks);
+    if let Some(proj_dim) = config.time_cond_proj_dim {
+      println!("UNet configured with time_cond_proj_dim: {}", proj_dim);
+      println!("This means the model expects guidance embeddings of dimension {}", proj_dim);
+    }
+
    let conv_in = conv2d(in_channels, b_channels, 3, conv_cfg, vs.pp("conv_in"))?;

    let time_proj = Timesteps::new(b_channels, config.flip_sin_to_cos, config.freq_shift);
@@ -241,18 +255,138 @@ impl UNet2DConditionModel {

    // Add guidance embedding if provided
    if let Some(guidance_emb) = guidance_embedding {
-      // Print shapes for debugging
-      println!("Guidance embedding shape: {:?}", guidance_emb.shape());
-      println!("Time embedding shape: {:?}", time_emb.shape());
+      // Get dimensions of both embeddings
+      let (batch_size, time_emb_dim) = time_emb.dims2()?;
+      let (guidance_batch, guidance_emb_dim) = guidance_emb.dims2()?;

-      // Get the batch size and embedding dimension
-      let (batch_size, emb_dim) = time_emb.dims2()?;
+      println!("==== Guidance Embedding Integration ====");
+      println!("Time embedding dims: [{}, {}]", batch_size, time_emb_dim);
+      println!("Guidance embedding dims: [{}, {}]", guidance_batch, guidance_emb_dim);

-      // Reshape guidance embedding to match time embedding dimensions
-      let guidance_emb = guidance_emb.reshape(&[1, emb_dim])?.expand(&[batch_size, emb_dim])?;
+      // Use time_cond_proj_dim from config to determine expected guidance embedding dimension
+      let expected_guidance_dim = self.config.time_cond_proj_dim.unwrap_or(time_emb_dim);
+      println!("Expected guidance dimension from config: {}", expected_guidance_dim);
+
+      // Check if dimensions match the expected projection dimension
+      let processed_guidance_emb = if guidance_emb_dim != time_emb_dim {
+        // Convert guidance_emb to f32 for calculations
+        let guidance_emb_f32 = guidance_emb.to_dtype(DType::F32)?;
+        println!("Converting guidance embedding to F32 for processing");
+
+        // If the guidance embedding dimension matches the expected projection dimension,
+        // we need to project it to match the time embedding dimension
+        if guidance_emb_dim == expected_guidance_dim {
+          println!("Projecting guidance embedding from {} to {}", guidance_emb_dim, time_emb_dim);
+
+          // Use linear interpolation
+          let src_positions: Vec<f32> = (0..guidance_emb_dim).map(|i| i as f32 / (guidance_emb_dim - 1) as f32).collect();
+          let dst_positions: Vec<f32> = (0..time_emb_dim).map(|i| i as f32 / (time_emb_dim - 1) as f32).collect();
+
+          // Get guidance embedding data (now f32)
+          let guidance_data = guidance_emb_f32.reshape((guidance_emb_dim,))?.to_vec1::<f32>()?;
+          println!("Reshaping guidance data to vector of length {}", guidance_data.len());
+
+          // Perform linear interpolation
+          let mut interpolated_data = Vec::with_capacity(time_emb_dim);
+          for &t in &dst_positions {
+            // Find the two source positions that surround the target position
+            let mut i = 0;
+            while i < src_positions.len() - 1 && src_positions[i + 1] < t {
+              i += 1;
+            }
+
+            if i == src_positions.len() - 1 {
+              // At or beyond the last position
+              interpolated_data.push(guidance_data[i]);
+            } else if t <= src_positions[0] {
+              // At or before the first position
+              interpolated_data.push(guidance_data[0]);
+            } else {
+              // Linear interpolation between two points
+              let t_norm = (t - src_positions[i]) / (src_positions[i + 1] - src_positions[i]);
+              let value = guidance_data[i] * (1.0 - t_norm) + guidance_data[i + 1] * t_norm;
+              interpolated_data.push(value);
+            }
+          }
+
+          println!("Created interpolated data of length {}", interpolated_data.len());
+
+          // Create tensor and convert to time_emb's dtype
+          let tensor = Tensor::from_vec(interpolated_data, (1, time_emb_dim), device)?;
+          let result = tensor.to_dtype(time_emb.dtype())?;
+          println!("Final projected guidance embedding shape: {:?}", result.shape());
+          result
+        } else {
+          // Unusual case - dimensions don't match expected pattern
+          println!("Warning: Guidance embedding dimension ({}) doesn't match expected projection dimension ({})", guidance_emb_dim, expected_guidance_dim);
+
+          // Fallback to generic interpolation
+          let guidance_data = guidance_emb_f32.reshape((guidance_emb_dim,))?.to_vec1::<f32>()?;
+
+          let src_positions: Vec<f32> = (0..guidance_emb_dim).map(|i| i as f32 / (guidance_emb_dim - 1) as f32).collect();
+          let dst_positions: Vec<f32> = (0..time_emb_dim).map(|i| i as f32 / (time_emb_dim - 1) as f32).collect();
+
+          let mut interpolated_data = Vec::with_capacity(time_emb_dim);
+          for &t in &dst_positions {
+            let mut i = 0;
+            while i < src_positions.len() - 1 && src_positions[i + 1] < t {
+              i += 1;
+            }
+
+            if i == src_positions.len() - 1 {
+              interpolated_data.push(guidance_data[i]);
+            } else if t <= src_positions[0] {
+              interpolated_data.push(guidance_data[0]);
+            } else {
+              let t_norm = (t - src_positions[i]) / (src_positions[i + 1] - src_positions[i]);
+              let value = guidance_data[i] * (1.0 - t_norm) + guidance_data[i + 1] * t_norm;
+              interpolated_data.push(value);
+            }
+          }
+
+          println!("Created interpolated data of length {}", interpolated_data.len());
+          let tensor = Tensor::from_vec(interpolated_data, (1, time_emb_dim), device)?;
+          let result = tensor.to_dtype(time_emb.dtype())?;
+          println!("Final fallback guidance embedding shape: {:?}", result.shape());
+          result
+        }
+      } else {
+        // Dimensions match, no processing needed
+        println!("Guidance dimension already matches time embedding dimension, no interpolation needed");
+        let result = guidance_emb.reshape((1, time_emb_dim))?.to_dtype(time_emb.dtype())?;
+        println!("Reshaped guidance embedding shape: {:?}", result.shape());
+        result
+      };
+
+      // Expand to match batch size if needed
+      let expanded_guidance = processed_guidance_emb.broadcast_as(time_emb.shape())?;
+      println!("Expanded guidance embedding shape: {:?}", expanded_guidance.shape());
+
+      // Save the processed and expanded guidance embeddings to disk if requested
+      if let Ok(save_dir) = std::env::var("CANDLE_SAVE_TENSORS_DIR") {
+        // Save pre-expansion (original projection)
+        let proc_path = format!("{}/unet_processed_guidance_embedding.npy", save_dir);
+        println!("Saving processed guidance embedding to {}", proc_path);
+        if let Err(e) = processed_guidance_emb.write_npy(&proc_path) {
+          println!("Error saving processed guidance embedding: {}", e);
+        } else {
+          println!("Successfully saved processed guidance embedding to {}", proc_path);
+        }
+
+        // Save post-expansion (final tensor used for addition to time_emb)
+        let exp_path = format!("{}/unet_expanded_guidance_embedding.npy", save_dir);
+        println!("Saving expanded guidance embedding to {}", exp_path);
+        if let Err(e) = expanded_guidance.write_npy(&exp_path) {
+          println!("Error saving expanded guidance embedding: {}", e);
+        } else {
+          println!("Successfully saved expanded guidance embedding to {}", exp_path);
+        }
+      }

      // Add to time embeddings
-      time_emb = (time_emb + guidance_emb)?;
+      time_emb = (time_emb + expanded_guidance)?;
+      println!("Final time embedding with guidance shape: {:?}", time_emb.shape());
+      println!("==== End Guidance Integration ====");
    }

    // 2. pre-process
@@ -546,7 +546,7 @@ export class Engine {
          canvasPosition: this.realTimeDrawEngine.captureCanvas.position(),
          canvasSize: this.realTimeDrawEngine.captureCanvas.size(),
          shapeType: shapeNode.shapeType,
-          size: shapeNode.size,
+          size: shapeNode.kNode.size(),
          color: nodeColor.color,
          mediaLayerRef: this.mediaLayer,
          selectionManagerRef: this.selectionManager,
@@ -581,7 +581,7 @@ export class Engine {
      canvasPosition: this.realTimeDrawEngine.captureCanvas.position(),
      canvasSize: this.realTimeDrawEngine.captureCanvas.size(),
      shapeType: type,
-      size: size,
+      size: { width: size, height: size },
      color: color,
      mediaLayerRef: this.mediaLayer,
      selectionManagerRef: this.selectionManager,
@@ -7,9 +7,11 @@ import { RealTimeDrawEngine } from "../RenderingPrimitives/RealTimeDrawEngine";
 import { MouseEventHandler } from "react";
 import { KonvaEventObject } from "konva/lib/Node";

+export type SupportedNode = Konva.Image | Konva.Group | Konva.Shape;
+
 export abstract class BaseNode {
  protected selectionManagerRef: SelectionManager;
-  public kNode: Konva.Image | Konva.Group;
+  public kNode: SupportedNode;
  protected mediaLayerRef: Konva.Layer;

  // Internal State members
@@ -31,7 +33,7 @@ export abstract class BaseNode {
  }: {
    selectionManagerRef: SelectionManager;
    mediaLayerRef: Konva.Layer;
-    kNode: Konva.Image | Konva.Group | Konva.Shape;
+    kNode: SupportedNode;
  }) {
    // console.log("Node constructed");
    // this.uuid = uuidv4();
@@ -62,7 +64,7 @@ export abstract class BaseNode {
  }
  public highlight() {
    // console.log("Highlight", this.kNode._id);
-    if (this.kNode instanceof Konva.Image) {
+    if (this.kNode instanceof Konva.Image || this.kNode instanceof Konva.Shape) {
      this.kNode.stroke(primaryOrange);
      this.kNode.strokeWidth(highlightStrokeWidth);
      return;
@@ -85,7 +87,7 @@ export abstract class BaseNode {

  public unhighlight() {
    // console.log("unHighlight", this.kNode._id);
-    if (this.kNode instanceof Konva.Image) {
+    if (this.kNode instanceof Konva.Image || this.kNode instanceof Konva.Shape) {
      this.kNode.strokeWidth(0);
      return;
    }
@@ -1,7 +1,7 @@
 import Konva from "konva";
 import { v4 as uuidv4 } from "uuid";
 import { SelectionManager } from "../NodesManagers";
-import { BaseNode } from "./BaseNode";
+import { BaseNode, SupportedNode } from "./BaseNode";
 import { Size } from "../types";
 import { LoadingVideosProvider } from "../EngineUtitlities/LoadingVideosProvider";
 import { NodeProgressEventDetail } from "../types/events";
@@ -20,7 +20,7 @@ export enum UploadStatus {
 }

 export abstract class NetworkedNode extends BaseNode {
-  public kNode: Konva.Image;
+  public kNode: SupportedNode;

  // members to deal with loading progress
  public didFinishLoading: boolean = false;
@@ -49,7 +49,7 @@ export abstract class NetworkedNode extends BaseNode {
    localFile,
    loadingVideosProviderRef,
  }: {
-    kNode: Konva.Image;
+    kNode: SupportedNode;
    selectionManagerRef: SelectionManager;
    mediaLayerRef: Konva.Layer;
    loadingVideosProviderRef?: LoadingVideosProvider;
@@ -15,7 +15,7 @@ interface ShapeNodeConstructor {
  canvasPosition: Position;
  canvasSize: Size;
  shapeType: ShapeType;
-  size: number;
+  size: Size;
  color?: string; // Hex color string
  transform?: TransformationData;
  mediaLayerRef: Konva.Layer;
@@ -29,7 +29,7 @@ export class ShapeNode extends NetworkedNode {
  }

  public shapeType: ShapeType;
-  public size: number;
+  public size: Size;
  public color: string;

  constructor({
@@ -46,6 +46,7 @@ export class ShapeNode extends NetworkedNode {
    // Create the actual shape inside the group
    const transform = NodeUtilities.getInitialTransform({
      existingTransform,
+      mediaFileSize: size,
      canvasPosition,
      canvasSize,
    });
@@ -54,110 +55,48 @@ export class ShapeNode extends NetworkedNode {

    switch (shapeType) {
      case ShapeType.CIRCLE:
-        const circleShape = new Konva.Circle({
-          radius: 50,
+        shape = new Konva.Ellipse({
+          x: size.width,
+          y: size.height,
+          radiusX: size.width,
+          radiusY: size.height,
          ...transform,
          fill: color,
          strokeScaleEnabled: false,
          draggable: true,
        });
-
-        // Convert circle to image
-        const dataURL = circleShape.toDataURL();
-        const imageObj = new Image();
-        imageObj.src = dataURL;
-
-        shape = new Konva.Image({
-          image: imageObj,
-          x: circleShape.x(),
-          y: circleShape.y(),
-          width: circleShape.width(),
-          height: circleShape.height(),
-          ...transform,
-          fill: "transparent",
-          strokeScaleEnabled: false,
-          draggable: true,
-        });
-
-        imageObj.onload = () => {
-          this.mediaLayerRef.draw();
-          loaded();
-        };
-
-        // Clean up the temporary circle
-        circleShape.destroy();
        break;

      case ShapeType.SQUARE:
-        const squareShape = new Konva.Rect({
-          width: 100,
-          height: 100,
+        shape = new Konva.Rect({
+          width: size.width,
+          height: size.height,
          ...transform,
          fill: color,
          strokeScaleEnabled: false,
          draggable: true,
        });
-
-        // Convert square to image
-        const squareDataURL = squareShape.toDataURL();
-        const squareImageObj = new Image();
-        squareImageObj.src = squareDataURL;
-
-        shape = new Konva.Image({
-          image: squareImageObj,
-          x: squareShape.x(),
-          y: squareShape.y(),
-          width: squareShape.width(),
-          height: squareShape.height(),
-          ...transform,
-          fill: "transparent",
-          strokeScaleEnabled: false,
-          draggable: true,
-        });
-
-        squareImageObj.onload = () => {
-          this.mediaLayerRef.draw();
-          loaded();
-        };
-
-        // Clean up the temporary square
-        squareShape.destroy();
        break;

      case ShapeType.TRIANGLE:
-        const triangleShape = new Konva.RegularPolygon({
-          sides: 3,
-          radius: 50,
+        shape = new Konva.Shape({
+          x: 0,
+          y: 0,
+          width: size.width,
+          height: size.height,
          ...transform,
          fill: color,
          strokeScaleEnabled: false,
          draggable: true,
+          sceneFunc: (context, shape) => {
+            context.beginPath();
+            context.moveTo(shape.width() / 2, 0);
+            context.lineTo(shape.width(), shape.height());
+            context.lineTo(0, shape.height());
+            context.closePath();
+            context.fillStrokeShape(shape);
+          }
        });
-
-        // Convert triangle to image
-        const triangleDataURL = triangleShape.toDataURL();
-        const triangleImageObj = new Image();
-        triangleImageObj.src = triangleDataURL;
-
-        shape = new Konva.Image({
-          image: triangleImageObj,
-          x: triangleShape.x(),
-          y: triangleShape.y(),
-          width: triangleShape.width(),
-          height: triangleShape.height(),
-          ...transform,
-          fill: "transparent",
-          strokeScaleEnabled: false,
-          draggable: true,
-        });
-
-        triangleImageObj.onload = () => {
-          this.mediaLayerRef.draw();
-          loaded();
-        };
-
-        // Clean up the temporary triangle
-        triangleShape.destroy();
        break;

      default:
@@ -252,8 +252,6 @@ export class SelectionManager {
        },
      ),
    );
-    this.updateContextComponents();
-    this.showContextComponents();
  }

  public updateNodeTransformer() {
@@ -4,7 +4,7 @@ import { Shape } from "konva/lib/Shape";
 import { Group } from "konva/lib/Group";

 import { invoke } from "@tauri-apps/api/core";
-import { listen } from '@tauri-apps/api/event';
+import { listen } from "@tauri-apps/api/event";

 import { FileUtilities } from "../FileUtilities/FileUtilities";
 import { ImageNode, VideoNode, TextNode, ShapeNode, ShapeType } from "../Nodes";
@@ -12,7 +12,7 @@ import { MediaNode } from "../types";

 import { RenderTask } from "./RenderTask";
 import { OffScreenSceneCanvas } from "./OffScreenSceneCanvas";
-import { Image } from "@tauri-apps/api/image";
+

 import { PaintNode } from "../Nodes/PaintNode";

@@ -31,7 +31,6 @@ interface ServerSettings {
  lora_path?: string;
 }

-
 interface GenerateImageParams {
  image: string;
  prompt: string;
@@ -62,9 +61,13 @@ export class RealTimeDrawEngine {
  private positionPreviewY: number;

  private port: MessagePort | undefined;
-
  public captureCanvas: Konva.Rect;
+  public backgroundRasterRect: Konva.Image;
+  
+
  public previewCanvas: Konva.Image;
+  
+

  public videoLoadingCanvas: VideoNode | undefined;

@@ -88,13 +91,15 @@ export class RealTimeDrawEngine {
      y: number;
    },
  ) => void;
+  private offscreenRenderDiv: HTMLDivElement;

  private onPreviewCopyCallback?: (previewCopy: Konva.Image) => void; // New Callback

  private client: WebSocketClient | null = null;
  private isConnected: boolean = false;

-  private backgroundNode: ShapeNode | null = null;
+
+
  public backgroundColor: string = "#d2d2d2";
  constructor({
    width,
@@ -184,25 +189,33 @@ export class RealTimeDrawEngine {
      fill: "white",
    });

+    this.offscreenRenderDiv = document.createElement("div");
+
+    this.backgroundRasterRect = new Konva.Image({
+      name: "backgroundRasterRect",
+      x: this.positionX,
+      y: this.positionY,
+      width: this.width,
+      height: this.height,
+      fill: this.backgroundColor,
+      image: undefined,
+      stroke: "black",
+      strokeWidth: 1,
+      draggable: false,
+    });
+ 
    this.mediaLayerRef.add(this.captureCanvas);
+    this.mediaLayerRef.add(this.backgroundRasterRect);
    this.mediaLayerRef.add(this.previewCanvas);
    // send back
    this.captureCanvas.setZIndex(0);
+    this.backgroundRasterRect.setZIndex(0);
    this.previewCanvas.setZIndex(1);
    // Add mouse events for preview canvas copying
    this.previewCopyListener();
-
-    //this.startServer();
-    // isLoadingVisible.value = true;
-    // const fakeTimer = setInterval(() => {
-    //   loadingProgress.value += 1;
-    //   if (loadingProgress.value >= 100) {
-    //     clearInterval(fakeTimer);
-    //     isLoadingVisible.value = false;
-    //   }
-    // }, 1000);
-
+    
    this.listenToServerEvents();
+   
  }

  public async listenToServerEvents() {
@@ -210,16 +223,18 @@ export class RealTimeDrawEngine {
      console.log(event);
      // Handle model download events
      const payload = event.payload as any;
-      
+
      // Model download started
      if (payload.model_download_started) {
        const modelInfo = payload.model_download_started;
-        console.log(`Model download started: ${modelInfo.model_name} (${modelInfo.model_type})`);
-        
+        console.log(
+          `Model download started: ${modelInfo.model_name} (${modelInfo.model_type})`,
+        );
+
        // Set up loading indicator
        isLoadingVisible.value = true;
        loadingProgress.value = 0;
-        
+
        // Create fake progress updates
        const downloadTimer = setInterval(() => {
          loadingProgress.value += 2;
@@ -230,23 +245,23 @@ export class RealTimeDrawEngine {
          }
        }, 500);
      }
-      
+
      // Model download completed
      if (payload.model_download_complete) {
        const modelInfo = payload.model_download_complete;
-        console.log(`Model download completed: ${modelInfo.model_name} (${modelInfo.model_type})`);
-        
+        console.log(
+          `Model download completed: ${modelInfo.model_name} (${modelInfo.model_type})`,
+        );
+
        // Complete the loading progress
        loadingProgress.value = 100;
-        
+
        // Hide loading indicator after a short delay
        setTimeout(() => {
          isLoadingVisible.value = false;
        }, 1000);
      }
-  
    });
-    
  }

  private isEnabled: boolean = false;
@@ -320,9 +335,16 @@ export class RealTimeDrawEngine {
    const ctx = cursorCanvas.getContext("2d");
    if (!ctx) return;

-    // Draw the circle
+    // Draw the outer circle with a light stroke
    ctx.beginPath();
    ctx.arc(size, size, size / 2, 0, Math.PI * 2);
+    ctx.strokeStyle = "white";
+    ctx.lineWidth = 3;
+    ctx.stroke();
+
+    // Draw the inner circle with a dark stroke
+    ctx.beginPath();
+    ctx.arc(size, size, size / 2 - 1, 0, Math.PI * 2);
    ctx.strokeStyle = "black";
    ctx.lineWidth = 1;
    ctx.stroke();
@@ -785,6 +807,27 @@ export class RealTimeDrawEngine {
    }
  }

+  private cloneStageForRender(stage: Konva.Stage, layerOfInterest: Konva.Layer): Konva.Stage {
+    const stageClone = new Konva.Stage({
+      width: stage.width(),
+      height: stage.height(),
+      container: this.offscreenRenderDiv,
+    });
+
+    const renderLayer = new Konva.Layer();
+
+    // Clone all the nodes then reset them to render right
+    layerOfInterest.getChildren().forEach((node) => {
+      const dupNode = node.clone();
+      dupNode.strokeWidth(0);
+      renderLayer.add(dupNode);
+    });
+
+    stageClone.add(renderLayer);
+
+    return stageClone;
+  }
+
  private async renderFrame(config: {
    layerOfInterest: Konva.Layer; // layer where the element that you want to clip lives.
    // XY and height of a captureCanvas ( region of interest )
@@ -805,54 +848,25 @@ export class RealTimeDrawEngine {
      const y = config.y !== undefined ? config.y : Math.floor(box.y);
      const pixelRatio = config.pixelRatio || 1;

-      const container = config.layerOfInterest as Container<Group | Shape>;
-
-      const offScreenSceneCanvas = new OffScreenSceneCanvas({
-        width:
-          config.width || Math.ceil(box.width) || (stage ? stage.width() : 0),
-        height:
-          config.height ||
-          Math.ceil(box.height) ||
-          (stage ? stage.height() : 0),
+      // Clone the required layer from the stage
+      // Set the right details (like removing highlight stroke)
+      // Then render the cloned stage to a bitmap
+      const stageClone = this.cloneStageForRender(stage, config.layerOfInterest);
+      const stageBlob = await stageClone.toBlob({
+        x: x,
+        y: y,
+        width: config.width || Math.ceil(box.width),
+        height: config.height || Math.ceil(box.height),
        pixelRatio: pixelRatio,
-      });
-
-      const context = offScreenSceneCanvas.getContext();
-
-      const buffer = new OffScreenSceneCanvas({
-        width:
-          offScreenSceneCanvas.width / offScreenSceneCanvas.pixelRatio +
-          Math.abs(x),
-        height:
-          offScreenSceneCanvas.height / offScreenSceneCanvas.pixelRatio +
-          Math.abs(y),
-        pixelRatio: offScreenSceneCanvas.pixelRatio,
-      });
-
-      context.save();
-
-      if (x || y) {
-        context.translate(-1 * x, -1 * y);
-      }
-      container.drawScene(offScreenSceneCanvas, undefined, buffer);
-      // Not a type mistake ... DO NOT FIX
-      // @ts-ignore
-      const offscreenCanvas = offScreenSceneCanvas._canvas as OffscreenCanvas;
-      let result = undefined;
+      }) as Blob;

      // if config.test is true, the result is downloaded to the local files
      // config.test = true;
      if (config.test) {
-        const blob = await offscreenCanvas.convertToBlob({
-          quality: config.quality ?? 1.0,
-          type: "image/jpeg",
-        });
-        await FileUtilities.blobToFileJpeg(blob, "1");
-        result = blob;
-      } else {
-        result = offscreenCanvas.transferToImageBitmap();
+        await FileUtilities.blobToFileJpeg(stageBlob, "1");
      }
-      context.restore();
+
+      const result = await createImageBitmap(stageBlob);
      return result;
    } catch (error) {
      throw error;
@@ -965,8 +979,8 @@ export class RealTimeDrawEngine {

    // Test code
    if (false) {
-      //this.outputBitmap = bitmap;
-      //this.previewCanvas.image(bitmap);
+      this.outputBitmap = bitmap;
+      this.previewCanvas.image(bitmap);
      const base64Bitmap = await this.imageBitmapToBase64(bitmap);
      console.log(this.currentStrength);
      await this.client?.generateImage({
@@ -979,6 +993,7 @@ export class RealTimeDrawEngine {
        width: 1024,
        lora_strength: 1.0,
      });
+      this.isProcessing = false
      return;
    }

@@ -1034,6 +1049,19 @@ export class RealTimeDrawEngine {
  // Add method to create or update background
  public updateBackground(color: string) {
    this.captureCanvas.fill(color);
-    this.mediaLayerRef.batchDraw();
+
+    const captureCanvasImage = this.captureCanvas.toDataURL();
+    const imageSource = new Image();
+    imageSource.src = captureCanvasImage;
+
+    imageSource.onload = () => {      
+      this.backgroundRasterRect.fill(color);
+      this.backgroundRasterRect.image(imageSource)
+
+      this.mediaLayerRef.batchDraw();
+      this.render();
+    };
+
+
  }
 }
@@ -3,6 +3,7 @@ import { LoadingBar, LoadingBarStatus } from "~/components/ui";
 import {
  isLoadingVisible,
  loadingProgress,
+  loadingText,
 } from "~/signals/uiEvents/loadingIndicator";

 export const SignaledLoadingIndicator = () => {
@@ -10,6 +11,7 @@ export const SignaledLoadingIndicator = () => {
  useSignalEffect(() => {
    isLoadingVisible.value;
    loadingProgress.value;
+    loadingText.value;
  });

  if (!isLoadingVisible.value) {
@@ -47,7 +49,7 @@ export const SignaledLoadingIndicator = () => {
            className="text-white/90"
          ></path>
        </svg>
-        Downloading models - {loadingProgress.value}%
+        {loadingText.value} - {loadingProgress.value}%
      </div>
    </div>
  );
@@ -6,6 +6,21 @@
  :root {
    @apply select-none bg-ui-background font-sans text-white;
  }
+
+  /* Remove all focus styles */
+  button {
+    @apply outline-none ring-0;
+    -webkit-tap-highlight-color: transparent !important;
+    outline: none !important;
+    box-shadow: none !important;
+  }
+
+  button:focus {
+    @apply outline-none ring-0;
+    outline: none !important;
+    box-shadow: none !important;
+  }
+
  .pegboard {
    background-image: radial-gradient(#ffffff25 1px, transparent 0);
    background-color: #1b1b1f;
@@ -187,3 +202,30 @@
    background-position: -200% 0;
  }
 }
+
+.react-colorful__saturation {
+  margin: 16px 0;
+  border-radius: 10px !important;
+  border-bottom: none !important;
+}
+
+.react-colorful__saturation-pointer {
+  width: 24px !important;
+  height: 24px !important;
+}
+
+.react-colorful__hue,
+.react-colorful__alpha {
+  height: 20px !important;
+  border-radius: 50px !important;
+}
+
+.react-colorful__hue {
+  margin-bottom: 12px;
+}
+
+.react-colorful__hue-pointer,
+.react-colorful__alpha-pointer {
+  width: 20px !important;
+  height: 20px !important;
+}
@@ -58,6 +58,12 @@ export const ToolbarButton = ({
      className={mergedButtonClasses}
      disabled={disabled}
      autoFocus={false}
+      tabIndex={-1}
+      style={{
+        outline: "none",
+        boxShadow: "none",
+        WebkitTapHighlightColor: "transparent",
+      }}
      {...restButtonProps}
      onClick={(e) => {
        e.preventDefault();
@@ -1,17 +1,43 @@
 import { twMerge } from "tailwind-merge";
+import { TabSelector, TabItem } from "~/components/ui/TabSelector";
+import { useComputed } from "@preact/signals-react";
+import { appMode, dispatchUiEvents } from "~/signals";

 // import { paperWrapperStyles } from "~/components/styles";
 // import { faPlus, faQuestion } from "@fortawesome/pro-solid-svg-icons";
 // import { ToolbarButton } from "~/components/features/ToolbarButton";

 export const ToolbarTopLeft = () => {
+  // Use the appMode signal directly with useComputed for reactivity - active tab sets the app mode
+  const activeTab = useComputed(() => appMode.value);
+
+  const tabs: TabItem[] = [
+    { id: "image", label: "Image" },
+    { id: "edit", label: "Edit" },
+    // { id: "video", label: "Video" },
+  ];
+
+  const handleTabChange = (tabId: string) => {
+    // Update the global signal
+    dispatchUiEvents.changeAppMode(tabId as "image" | "edit");
+  };
+
+  console.log(appMode.value);
+
  return (
-    <div className={twMerge("z-20 flex h-fit w-fit items-center gap-1")}>
+    <div className={twMerge("z-20 flex h-fit w-fit items-center gap-8 px-4")}>
      <img
        src="/brand/mira-logo.png"
        alt="logo"
        className="h-[30px] select-none pb-1"
      />
+
+      <TabSelector
+        tabs={tabs}
+        activeTab={activeTab.value}
+        onTabChange={handleTabChange}
+      />
+
      {/* <ToolbarButton icon={faPlus}>
        <span className="font-semibold">New Board</span>
      </ToolbarButton>
@@ -28,17 +28,17 @@ export const Button = ({
  function getVariantClassNames(variant: string) {
    switch (variant) {
      case "tertiary": {
-        return "bg-tertiary hover:bg-tertiary-400 text-white focus-visible:outline-tertiary-600";
+        return "bg-tertiary hover:bg-tertiary-400 text-white";
      }
      case "secondary": {
-        return "bg-ui-controls hover:bg-ui-controls/80 text-white focus-visible:outline-secondary";
+        return "bg-ui-controls hover:bg-ui-controls/80 text-white";
      }
      case "action": {
-        return " bg-action hover:bg-action-500 text-white focus-visible:outline-action";
+        return "bg-action hover:bg-action-500 text-white";
      }
      case "primary":
      default: {
-        return "bg-primary hover:bg-primary-600 text-white focus-visible:outline-primary-600";
+        return "bg-primary hover:bg-primary-600 text-white";
      }
    }
  }
@@ -51,7 +51,6 @@ export const Button = ({
    "text-[15px] font-semibold rounded-lg px-3 py-2 shadow-sm",
    "flex gap-2 items-center justify-center",
    "transition-all duration-150",
-    "focus-visible:outline focus-visible:outline-2 focus-visible:outline-offset-2",
    getVariantClassNames(propsVariant),
    propsClassName,
    disabledClass,
@@ -1,12 +1,13 @@
-import { MouseEvent, MouseEventHandler, useState } from "react";
-import { HexColorPicker } from "react-colorful";
-import { EyeDropper } from "react-eyedrop";
 import { Button } from "./Button";
 import { faEyedropper } from "@fortawesome/pro-solid-svg-icons";
 import { twMerge } from "tailwind-merge";

-type ColorPickerHTMLAttributes = Omit<React.HTMLAttributes<HTMLDivElement>, "color" | "onChange" | "onChangeCapture">;
-interface ColorPickerBaseProps<T extends string> extends ColorPickerHTMLAttributes {
+type ColorPickerHTMLAttributes = Omit<
+  React.HTMLAttributes<HTMLDivElement>,
+  "color" | "onChange" | "onChangeCapture"
+>;
+interface ColorPickerBaseProps<T extends string>
+  extends ColorPickerHTMLAttributes {
  color: T;
  onChange: (newColor: T) => void;
 }
@@ -17,7 +18,7 @@ export const HexEyedropPicker = ({
  dropperClassName,
  pickerClassName,
  onPickerChange,
-  Picker
+  Picker,
 }: {
  color: string;
  onDropperChange?: (newColor: string) => void;
@@ -26,9 +27,8 @@ export const HexEyedropPicker = ({
  onPickerChange: (newColor: string) => void;
  Picker: (props: Partial<ColorPickerBaseProps<string>>) => JSX.Element;
 }) => {
-
  const handleDropperClick = () => {
-    if (!('EyeDropper' in window)) {
+    if (!("EyeDropper" in window)) {
      // NOTE: This shouldn't happen cuz we're using Chromium
      console.error("EyeDropper not found in window");
      return;
@@ -46,42 +46,40 @@ export const HexEyedropPicker = ({
        // User cancelled the picker
        return null;
      }
-    }
+    };

    startEyeDrop().then((newColor) => {
      if (newColor) {
        onDropperChange?.(newColor);
      }
    });
-  }
+  };

-  const [isDragging, setIsDragging] = useState(false);
-  const handleOnMouseDown = () => {
-    setIsDragging(true);
-  }
-  const handleOnMouseUp = () => {
-    setIsDragging(false);
-  }
+  // const [isDragging, setIsDragging] = useState(false);
+  // const handleOnMouseDown = () => {
+  //   setIsDragging(true);
+  // };
+  // const handleOnMouseUp = () => {
+  //   setIsDragging(false);
+  // };

  return (
    <div className={"relative"}>
-      <Picker
-        className={pickerClassName}
-        color={color}
-        onChange={onPickerChange}
-        onMouseDown={handleOnMouseDown}
-        onMouseUp={handleOnMouseUp}
-      />
      <Button
        className={twMerge([
-          "rounded-full m-1 size-8 text-ui-controls bg-transparent hover:bg-black/70 hover:text-white z-20 shadow-none hover:shadow-xl duration-200",
+          "z-20 size-8 rounded-xl bg-ui-background/30 text-white shadow-none duration-200 hover:bg-white/10 hover:text-white hover:shadow-xl",
          dropperClassName,
-          "absolute left-0 top-0",
-          isDragging ? "opacity-0 -z-10" : ""
        ])}
        icon={faEyedropper}
        onClick={handleDropperClick}
      />
+      <Picker
+        className={pickerClassName}
+        color={color}
+        onChange={onPickerChange}
+        // onMouseDown={handleOnMouseDown}
+        // onMouseUp={handleOnMouseUp}
+      />
    </div>
-  )
-}
+  );
+};
@@ -0,0 +1,82 @@
+import React, { useRef, useEffect, useState } from "react";
+import { Tab, TabGroup, TabList } from "@headlessui/react";
+import { twMerge } from "tailwind-merge";
+
+export interface TabItem {
+  id: string;
+  label: string;
+}
+
+interface TabSelectorProps {
+  tabs: TabItem[];
+  activeTab: string;
+  onTabChange: (tabId: string) => void;
+  className?: string;
+}
+
+export const TabSelector: React.FC<TabSelectorProps> = ({
+  tabs,
+  activeTab,
+  onTabChange,
+  className,
+}) => {
+  // Find the index of the active tab
+  const selectedIndex = tabs.findIndex((tab) => tab.id === activeTab);
+  const tabsRef = useRef<(HTMLElement | null)[]>([]);
+  const [indicatorStyle, setIndicatorStyle] = useState({
+    left: 0,
+    width: 0,
+  });
+
+  // Handle tab change
+  const handleTabChange = (index: number) => {
+    onTabChange(tabs[index].id);
+  };
+
+  // Update the indicator position when the selected tab changes
+  useEffect(() => {
+    if (selectedIndex >= 0 && tabsRef.current[selectedIndex]) {
+      const currentTab = tabsRef.current[selectedIndex];
+      if (currentTab) {
+        setIndicatorStyle({
+          left: currentTab.offsetLeft,
+          width: currentTab.offsetWidth,
+        });
+      }
+    }
+  }, [selectedIndex, tabs]);
+
+  return (
+    <TabGroup
+      selectedIndex={selectedIndex}
+      onChange={handleTabChange}
+      className={twMerge("w-full", className)}
+    >
+      <TabList className="glass relative inline-flex min-w-fit overflow-x-auto rounded-lg p-1 shadow-lg">
+        {/* Animated indicator */}
+        <div
+          className="absolute top-1 z-10 h-[calc(100%-8px)] rounded-md border-2 border-primary bg-primary/30 transition-all duration-300 ease-in-out"
+          style={{
+            left: indicatorStyle.left,
+            width: indicatorStyle.width,
+          }}
+        />
+
+        {tabs.map((tab, index) => (
+          <Tab
+            key={tab.id}
+            ref={(el) => (tabsRef.current[index] = el)}
+            className={({ selected }) =>
+              twMerge(
+                "relative z-20 mx-0.5 min-w-max rounded-md border-2 border-transparent px-4 py-1 text-center font-semibold transition-all duration-300 ease-in-out",
+                selected ? "text-white" : "text-gray-300 hover:text-white",
+              )
+            }
+          >
+            {tab.label}
+          </Tab>
+        ))}
+      </TabList>
+    </TabGroup>
+  );
+};
@@ -91,7 +91,7 @@ export const ColorPicker = ({
    if (streamChanges) {
      onChange(color);
    }
-  }
+  };

  return (
    <Popover className="relative">
@@ -124,7 +124,7 @@ export const ColorPicker = ({
                anchor={anchor}
                className={twMerge(
                  paperWrapperStyles,
-                  "flex flex-col items-center gap-2 overflow-hidden",
+                  "flex flex-col items-center gap-2 overflow-hidden p-4",
                )}
                style={
                  {
@@ -134,13 +134,14 @@ export const ColorPicker = ({
                static
              >
                <HexEyedropPicker
-                  pickerClassName="overflow-hidden"
                  color={currColor}
                  onPickerChange={handleColorChange}
                  onDropperChange={handleColorChange}
                  Picker={HexAlphaColorPicker}
                />
                <Input
+                  className="mt-2"
+                  inputClassName="bg-ui-background/30"
                  style={{ width: "198px" }}
                  icon={faHashtag}
                  value={textInput}
@@ -11,17 +11,9 @@ import { twMerge } from "tailwind-merge";

 import { useSignals } from "@preact/signals-react/runtime";
 import { paperWrapperStyles } from "~/components/styles";
-import {
-  BRUSH_MAX_SIZE,
-  BRUSH_MIN_SIZE,
-  paintBrushSize,
-  setPaintBrushSize,
-} from "~/signals/uiEvents/toolbarMain/paintMode";
 import { Button } from "../Button";
-import { Input } from "../Input";
-import { Slider } from "../Slider";
-import { EyeDropper } from "react-eyedrop";
 import { HexEyedropPicker } from "../HexEyedropPicker";
+import { Input } from "../Input";

 export const BackgroundMenu = ({
  color: prevColor,
@@ -5,13 +5,18 @@ import {
 } from "@fortawesome/pro-solid-svg-icons";
 import { FontAwesomeIcon } from "@fortawesome/react-fontawesome";
 import { Popover, PopoverButton, PopoverPanel } from "@headlessui/react";
-import { ChangeEvent, useEffect, useState } from "react";
+import { ChangeEvent, useEffect, useState, useRef } from "react";
 import { HexAlphaColorPicker } from "react-colorful";
 import { twMerge } from "tailwind-merge";

 import { useSignals } from "@preact/signals-react/runtime";
 import { paperWrapperStyles } from "~/components/styles";
-import { BRUSH_MAX_SIZE, BRUSH_MIN_SIZE, paintBrushSize, setPaintBrushSize } from "~/signals/uiEvents/toolbarMain/paintMode";
+import {
+  BRUSH_MAX_SIZE,
+  BRUSH_MIN_SIZE,
+  paintBrushSize,
+  setPaintBrushSize,
+} from "~/signals/uiEvents/toolbarMain/paintMode";
 import { Button } from "../Button";
 import { Input } from "../Input";
 import { Slider } from "../Slider";
@@ -52,16 +57,58 @@ export const PaintModeMenu = ({
    currColor: prevColor,
    textInput: prevColor.substring(1),
  });
+  const [isMouseDown, setIsMouseDown] = useState(false);
+  const [isMouseOutside, setIsMouseOutside] = useState(false);
+  const closeRef = useRef<(() => void) | null>(null);
+  const closeTimeoutRef = useRef<NodeJS.Timeout | null>(null);

  useEffect(() => {
    setIsOpen(defaultOpen);
  }, [defaultOpen]);

+  // Global mouse up handler
+  useEffect(() => {
+    const handleGlobalMouseUp = () => {
+      if (isMouseDown) {
+        setIsMouseDown(false);
+
+        // If mouse is outside when released, close the panel after a short delay
+        if (isMouseOutside && closeOnMouseLeave && closeRef.current) {
+          closeTimeoutRef.current = setTimeout(() => {
+            onChange(currColor);
+            setIsOpen(false);
+            closeRef.current?.();
+          }, 500);
+        }
+      }
+    };
+
+    window.addEventListener("mouseup", handleGlobalMouseUp);
+
+    return () => {
+      window.removeEventListener("mouseup", handleGlobalMouseUp);
+    };
+  }, [isMouseDown, isMouseOutside, closeOnMouseLeave, currColor, onChange]);
+
  const handleMouseLeave = (close: () => void) => {
-    if (closeOnMouseLeave) {
-      onChange(currColor);
-      setIsOpen(false);
-      close();
+    closeRef.current = close;
+    setIsMouseOutside(true);
+
+    // Only close if mouse is not down and closeOnMouseLeave is true
+    if (closeOnMouseLeave && !isMouseDown) {
+      closeTimeoutRef.current = setTimeout(() => {
+        onChange(currColor);
+        setIsOpen(false);
+        close();
+      }, 200);
+    }
+  };
+
+  const handleMouseEnter = () => {
+    setIsMouseOutside(false);
+    if (closeTimeoutRef.current) {
+      clearTimeout(closeTimeoutRef.current);
+      closeTimeoutRef.current = null;
    }
  };

@@ -92,7 +139,7 @@ export const PaintModeMenu = ({
    if (streamChanges) {
      onChange(color);
    }
-  }
+  };

  // Rerender the component when these signals change:
  useSignals();
@@ -123,12 +170,16 @@ export const PaintModeMenu = ({
            )}
          </PopoverButton>
          {(open || isOpen) && (
-            <div onMouseLeave={() => handleMouseLeave(close)}>
+            <div
+              onMouseLeave={() => handleMouseLeave(close)}
+              onMouseEnter={handleMouseEnter}
+              onMouseDown={() => setIsMouseDown(true)}
+            >
              <PopoverPanel
                anchor={anchor}
                className={twMerge(
                  paperWrapperStyles,
-                  "flex flex-col items-center gap-2 overflow-hidden",
+                  "flex flex-col items-center gap-2 overflow-hidden p-4",
                )}
                style={
                  {
@@ -138,20 +189,23 @@ export const PaintModeMenu = ({
                static
              >
                <HexEyedropPicker
-                  pickerClassName="overflow-hidden"
                  color={currColor}
                  onPickerChange={handleColorChange}
                  onDropperChange={handleColorChange}
                  Picker={HexAlphaColorPicker}
                />
                <Input
+                  className="mt-2"
+                  inputClassName="bg-ui-background/30"
                  style={{ width: "198px" }}
                  icon={faHashtag}
                  value={textInput}
                  onChange={handleTextInput}
                />
-                <div className="flex flex-col w-full mt-2 gap-2">
-                  <p className="text-white font-medium text-sm w-full justify-start">Brush Size:</p>
+                <div className="mt-2 flex w-full flex-col gap-2">
+                  <p className="w-full justify-start text-sm font-medium text-white">
+                    Brush Size:
+                  </p>
                  <Slider
                    min={BRUSH_MIN_SIZE}
                    max={BRUSH_MAX_SIZE}
@@ -8,6 +8,7 @@ export * from "./PanelRight";
 export * from "./Slider";
 export * from "./Spinner";
 export * from "./Switches";
+export * from "./TabSelector";
 export * from "./TextArea";
 export * from "./TextEditor";
 export * from "./Tooltip";
@@ -0,0 +1,38 @@
+import { signal, effect } from "@preact/signals-core";
+
+// this is to control the app mode - BFlat
+
+// Define the app mode types
+export type AppModeType = "image" | "edit";
+
+// Create a signal for the current app mode
+export const appMode = signal<AppModeType>("image");
+
+// Create a function to change the app mode
+export const changeAppMode = (mode: AppModeType) => {
+  appMode.value = mode;
+};
+
+// Store callbacks for mode changes
+const callbacks: ((mode: AppModeType) => void)[] = [];
+
+// Set up an effect to notify callbacks when the mode changes
+effect(() => {
+  const currentMode = appMode.value;
+  callbacks.forEach((callback) => callback(currentMode));
+});
+
+// Export an event handler for components to use
+export const appModeEvents = {
+  onChange: (callback: (mode: AppModeType) => void) => {
+    callbacks.push(callback);
+
+    // Return a function to unsubscribe
+    return () => {
+      const index = callbacks.indexOf(callback);
+      if (index !== -1) {
+        callbacks.splice(index, 1);
+      }
+    };
+  },
+};
@@ -36,6 +36,7 @@ import {
  dispatchers as modelSelectionDispatchers,
  events as modelSelectionEvents,
 } from "./modelSelection";
+import { appMode, changeAppMode, appModeEvents } from "./appMode";

 export const uiEvents = {
  ...addMediaEvents,
@@ -49,6 +50,7 @@ export const uiEvents = {
  promptEvents: promptEvents,
  loadingIndicator: loadingIndicatorEvents,
  modelSelection: modelSelectionEvents,
+  appMode: appModeEvents,
 };
 export const dispatchUiEvents = {
  ...addMediaDispatchers,
@@ -62,4 +64,7 @@ export const dispatchUiEvents = {
  promptSettings: promptDispatchers,
  loadingIndicator: loadingIndicatorDispatchers,
  modelSelection: modelSelectionDispatchers,
+  changeAppMode,
 };
+
+export { appMode };
@@ -28,13 +28,28 @@ const onLoadingProgressChanged = (callback: (progress: number) => void) => {
  });
 };

+// Loading text signal
+export const DEFAULT_LOADING_TEXT = "Downloading";
+export const loadingText = signal<string>(DEFAULT_LOADING_TEXT);
+const setLoadingText = (text: string) => {
+  loadingText.value = text;
+};
+
+const onLoadingTextChanged = (callback: (text: string) => void) => {
+  effect(() => {
+    callback(loadingText.value);
+  });
+};
+
 // EXPORTS
 export const dispatchers = {
  setIsLoadingVisible,
  setLoadingProgress,
+  setLoadingText,
 };

 export const events = {
  onIsLoadingVisibleChanged,
  onLoadingProgressChanged,
+  onLoadingTextChanged,
 };
Author	SHA1	Message	Date
Brandon Thomas	b2a7a40f5f	don't download sdxl anymore	2025-03-13 00:31:51 -04:00
Brandon Thomas	9085c288bd	stop downloading clip tokenizer from hf	2025-03-13 00:24:06 -04:00
Brandon Thomas	dd71d022ae	vae wasn't cached in memory	2025-03-12 23:58:52 -04:00
Brandon Thomas	692c409e1b	load text encoder from our bucket	2025-03-12 23:54:42 -04:00
Brandon Thomas	3ed775cf76	vae and unet from cloudflare instead of hf	2025-03-12 23:38:49 -04:00
Brandon Thomas	08ea29d44c	cleanup lcm	2025-03-12 22:16:18 -04:00
Brandon Thomas	43df6c9181	app default size	2025-03-12 21:58:27 -04:00
Tanish Manku	a8e029497f	Fix context menu showing up after transforming (#453 )	2025-03-12 15:18:00 -07:00
Brandon Thomas	4936662ddd	correct default path on windows	2025-03-12 18:08:23 -04:00
BFlat	883e32220c	tabs and app mode signals (#450 ) Usage example - Conditional Rendering Based on App Mode: ```typescript import { appMode } from "~/signals"; function ConditionalComponent() { return ( <div className="app-container"> {/* Show/hide components based on current mode */} {appMode.value === 'image' && ( <div className="image-tools"> <h3>Image Mode Tools</h3> </div> )} {appMode.value === 'edit' && ( <div className="edit-tools"> <h3>Edit Mode Tools</h3> </div> )} ); } ```	2025-03-12 13:26:10 -04:00
Brandon Thomas	727eead5a7	fix windows search for missing stdc++.lib during build	2025-03-12 01:27:27 -04:00
Kasisnu	b4cc5b84cf	f16	2025-03-11 22:30:02 +05:30
Brandon Thomas	d7e77775ca	Add new premium plan identifiers	2025-03-11 02:15:46 -04:00
Brandon Thomas	b75472c434	fix windows builds by disabling flash attn/cutlass, openssl, etc.	2025-03-11 00:49:30 -04:00
Brandon Thomas	a4f876daa9	Multithreaded downloader + notifications (#447 )	2025-03-10 21:51:07 -04:00
Tanish Manku	4b309a5dd8	Render shapes as vectors and revamp rendering logic (#442 )	2025-03-07 14:41:11 -08:00
Tanish Manku	08384955e4	Remove 'React-Eyedrop' and unused imports (#443 ) As simple as it sounds	2025-03-06 23:05:23 -08:00
Brandon Thomas	31037b83a3	downloader thread	2025-03-06 22:48:48 -05:00
Brandon Thomas	53d93cb1ac	change name of app	2025-03-06 21:45:01 -05:00
Brandon Thomas	a0de8fc603	load all models from model registry	2025-03-06 21:39:19 -05:00
Brandon Thomas	ef3527dd85	weights directory, assets directory	2025-03-06 21:06:58 -05:00
Brandon Thomas	1a887d7414	don't download anything from huggingface	2025-03-06 19:27:22 -05:00
Brandon Thomas	48abc0d731	no longer download clip encoders from huggingface	2025-03-06 15:22:10 -05:00
CrossPr0duct	0233105393	Merge branch 'main' of github.com:storytold/storyteller-rust	2025-03-06 15:12:28 -05:00
CrossPr0duct	8f94f81db4	Background Hack Implemented without engine refactors.	2025-03-06 15:12:04 -05:00
Kasisnu	3f25aefc3f	starting point (#440 )	2025-03-06 10:41:08 -05:00
BFlat	c2929cfdb6	color picker ux and make paint cursor visible on both dark/light bg (#441 ) ux updates to color picker and paint cursor	2025-03-06 20:52:25 +07:00
Brandon Thomas	a859bd427b	download clip models (not using them yet)	2025-03-06 08:42:44 -05:00
Brandon Thomas	706becfd7e	download unet	2025-03-05 19:32:41 -05:00
Brandon Thomas	ada1f46e62	model downloading (wip)	2025-03-05 18:24:05 -05:00
bflatastic	3556dcbfd3	removed annoying focus on buttons 2	2025-03-05 23:40:33 +07:00
bflatastic	4ab6ca1caa	disabled annoying focus ring	2025-03-05 23:21:11 +07:00
BFlat	74f5b14d18	added loading indicator text (#439 ) added signal for loading indicator text change	2025-03-05 10:23:48 +07:00