release v1.5.2

add translation.

.github/workflows/release.yml

@@ -63,10 +63,10 @@ jobs:
           Expand-Archive ./python-3.10.11-embed-amd64.zip -DestinationPath ./py310
           $content=Get-Content "./py310/python310._pth"; $content | ForEach-Object {if ($_.ReadCount -eq 3) {"Lib\\site-packages"} else {$_}} | Set-Content ./py310/python310._pth
           ./py310/python ./backend-python/get-pip.py
-          ./py310/python -m pip install Cython==0.29.36
+          ./py310/python -m pip install Cython==3.0.4
           Copy-Item -Path "${{ steps.cp310.outputs.python-path }}/../include" -Destination "py310/include" -Recurse
           Copy-Item -Path "${{ steps.cp310.outputs.python-path }}/../libs" -Destination "py310/libs" -Recurse
-          ./py310/python -m pip install cyac==1.7
+          ./py310/python -m pip install cyac==1.9
           git clone https://github.com/josStorer/ai00_rwkv_server --depth=1
           cd ai00_rwkv_server
           cargo build --release
@@ -107,11 +107,10 @@ jobs:
           mv ./target/x86_64-unknown-linux-gnu/release/ai00_server ../backend-rust/webgpu_server
           cd ..
           go install github.com/wailsapp/wails/v2/cmd/wails@latest
-          rm -rf ./backend-python/wkv_cuda_utils
+          rm ./backend-python/rwkv_pip/wkv_cuda.pyd
+          rm ./backend-python/rwkv_pip/rwkv5.pyd
+          rm ./backend-python/rwkv_pip/beta/wkv_cuda.pyd
           rm ./backend-python/get-pip.py
-          sed -i '1,2d' ./backend-golang/wsl_not_windows.go
-          rm ./backend-golang/wsl.go
-          mv ./backend-golang/wsl_not_windows.go ./backend-golang/wsl.go
           make
           mv build/bin/RWKV-Runner build/bin/RWKV-Runner_linux_x64
 
@@ -139,11 +138,10 @@ jobs:
           mv ./target/release/ai00_server ../backend-rust/webgpu_server
           cd ..
           go install github.com/wailsapp/wails/v2/cmd/wails@latest
-          rm -rf ./backend-python/wkv_cuda_utils
+          rm ./backend-python/rwkv_pip/wkv_cuda.pyd
+          rm ./backend-python/rwkv_pip/rwkv5.pyd
+          rm ./backend-python/rwkv_pip/beta/wkv_cuda.pyd
           rm ./backend-python/get-pip.py
-          sed -i '' '1,2d' ./backend-golang/wsl_not_windows.go
-          rm ./backend-golang/wsl.go
-          mv ./backend-golang/wsl_not_windows.go ./backend-golang/wsl.go
           make
           cp build/darwin/Readme_Install.txt build/bin/Readme_Install.txt
           cp build/bin/RWKV-Runner.app/Contents/MacOS/RWKV-Runner build/bin/RWKV-Runner_darwin_universal

.gitignore

@@ -18,6 +18,7 @@ __pycache__
 /cmd-helper.bat
 /install-py-dep.bat
 /backend-python/wkv_cuda
+/backend-python/rwkv5
 *.exe
 *.old
 .DS_Store
@@ -26,3 +27,4 @@ __pycache__
 train_log.txt
 finetune/json2binidx_tool/data
 /wsl.state
+/components

CURRENT_CHANGE.md

@@ -1,14 +1,10 @@
 ## Changes
 
-- frontend: update manifest (a lot of new models)
-- frontend: correct Preset UI description
-- frontend: add HardwareMonitor (Windows Only)
-- lora finetune: fix max_epochs (#170)
-- python-backend: allow message content to be empty
-- python-backend: extra ChatCompletionBody params (`raw`, `presystem`)
-- python-backend: add default_stop when stop is null
-- webgpu: fix webgpu_server file permissions of linux and macos
-- chore
+### Improvements
+
+- improve mobile webview
+- add client upgrade progress
+- improve user guide
 
 ## Install
 

Makefile

@@ -18,6 +18,16 @@ build-linux:
 	@echo ---- build for linux
 	wails build -upx -ldflags "-s -w" -platform linux/amd64
 
+build-web:
+	@echo ---- build for web
+	cd frontend && npm run build
+
 dev:
 	wails dev
 
+dev-web:
+	cd frontend && npm run dev
+
+preview:
+	cd frontend && npm run preview
+

README.md

@@ -47,7 +47,9 @@ English | [简体中文](README_ZH.md) | [日本語](README_JA.md)
 
 </div>
 
-#### Default configs has enabled custom CUDA kernel acceleration, which is much faster and consumes much less VRAM. If you encounter possible compatibility issues, go to the Configs page and turn off `Use Custom CUDA kernel to Accelerate`.
+#### Tip: You can deploy [backend-python](./backend-python/) on a server and use this program as a client only. Fill in your server address in the Settings `API URL`.
+
+#### Default configs has enabled custom CUDA kernel acceleration, which is much faster and consumes much less VRAM. If you encounter possible compatibility issues (output garbled), go to the Configs page and turn off `Use Custom CUDA kernel to Accelerate`, or try to upgrade your gpu driver.
 
 #### If Windows Defender claims this is a virus, you can try downloading [v1.3.7_win.zip](https://github.com/josStorer/RWKV-Runner/releases/download/v1.3.7/RWKV-Runner_win.zip) and letting it update automatically to the latest version, or add it to the trusted list (`Windows Security` -> `Virus & threat protection` -> `Manage settings` -> `Exclusions` -> `Add or remove exclusions` -> `Add an exclusion` -> `Folder` -> `RWKV-Runner`).
 

README_JA.md

@@ -47,7 +47,9 @@
 
 </div>
 
-#### デフォルトの設定はカスタム CUDA カーネルアクセラレーションを有効にしています。互換性の問題が発生する可能性がある場合は、コンフィグページに移動し、`Use Custom CUDA kernel to Accelerate` をオフにしてください。
+#### ヒント：サーバーに[backend-python](./backend-python/)をデプロイし、このプログラムをクライアントとして使用することができます。設定された`API URL`にサーバーアドレスを入力してください。
+
+#### デフォルトの設定はカスタム CUDA カーネルアクセラレーションを有効にしています。互換性の問題 (文字化けを出力する) が発生する可能性がある場合は、コンフィグページに移動し、`Use Custom CUDA kernel to Accelerate` をオフにしてください、あるいは、GPUドライバーをアップグレードしてみてください。
 
 #### Windows Defender がこれをウイルスだと主張する場合は、[v1.3.7_win.zip](https://github.com/josStorer/RWKV-Runner/releases/download/v1.3.7/RWKV-Runner_win.zip) をダウンロードして最新版に自動更新させるか、信頼済みリストに追加してみてください (`Windows Security` -> `Virus & threat protection` -> `Manage settings` -> `Exclusions` -> `Add or remove exclusions` -> `Add an exclusion` -> `Folder` -> `RWKV-Runner`)。
 
@@ -91,8 +93,8 @@ body.json:
 
 ## 埋め込み API の例
 
-Note: v1.4.0 has improved the quality of embeddings API. The generated results are not compatible
-with previous versions. If you are using embeddings API to generate knowledge bases or similar, please regenerate.
+注意: v1.4.0 では、埋め込み API の品質が向上しました。生成される結果は、以前のバージョンとは互換性がありません。
+もし、embeddings API を使って知識ベースなどを生成している場合は、再生成してください。
 
 LangChain を使用している場合は、`OpenAIEmbeddings(openai_api_base="http://127.0.0.1:8000", openai_api_key="sk-")`
 を使用してください

README_ZH.md

@@ -46,7 +46,9 @@ API兼容的接口，这意味着一切ChatGPT客户端都是RWKV客户端。
 
 </div>
 
-#### 预设配置已经开启自定义CUDA算子加速，速度更快，且显存消耗更少。如果你遇到可能的兼容性问题，前往配置页面，关闭`使用自定义CUDA算子加速`
+#### 小贴士：你可以在服务器部署[backend-python](./backend-python/)，然后将此程序仅用作客户端，在设置的`API URL`中填入你的服务器地址
+
+#### 预设配置已经开启自定义CUDA算子加速，速度更快，且显存消耗更少。如果你遇到可能的兼容性(输出乱码)问题，前往配置页面，关闭`使用自定义CUDA算子加速`，或更新你的显卡驱动
 
 #### 如果Windows Defender说这是一个病毒，你可以尝试下载[v1.3.7_win.zip](https://github.com/josStorer/RWKV-Runner/releases/download/v1.3.7/RWKV-Runner_win.zip)，然后让其自动更新到最新版，或添加信任 (`Windows Security` -> `Virus & threat protection` -> `Manage settings` -> `Exclusions` -> `Add or remove exclusions` -> `Add an exclusion` -> `Folder` -> `RWKV-Runner`)
 

backend-golang/app.go

@@ -4,12 +4,14 @@ import (
 	"bufio"
 	"context"
 	"errors"
+	"io"
 	"net/http"
 	"os"
 	"os/exec"
 	"path/filepath"
 	"runtime"
 	"syscall"
+	"time"
 
 	"github.com/fsnotify/fsnotify"
 	"github.com/minio/selfupdate"
@@ -118,13 +120,50 @@ func (a *App) monitorHardware() {
 	monitor.Start()
 }
 
+type ProgressReader struct {
+	reader io.Reader
+	total  int64
+	err    error
+}
+
+func (pr *ProgressReader) Read(p []byte) (n int, err error) {
+	n, err = pr.reader.Read(p)
+	pr.err = err
+	pr.total += int64(n)
+	return
+}
+
 func (a *App) UpdateApp(url string) (broken bool, err error) {
 	resp, err := http.Get(url)
 	if err != nil {
 		return false, err
 	}
 	defer resp.Body.Close()
-	err = selfupdate.Apply(resp.Body, selfupdate.Options{})
+	pr := &ProgressReader{reader: resp.Body}
+
+	ticker := time.NewTicker(250 * time.Millisecond)
+	defer ticker.Stop()
+
+	go func() {
+		for {
+			<-ticker.C
+			wruntime.EventsEmit(a.ctx, "updateApp", &DownloadStatus{
+				Name:        filepath.Base(url),
+				Path:        "",
+				Url:         url,
+				Transferred: pr.total,
+				Size:        resp.ContentLength,
+				Speed:       0,
+				Progress:    100 * (float64(pr.total) / float64(resp.ContentLength)),
+				Downloading: pr.err == nil && pr.total < resp.ContentLength,
+				Done:        pr.total == resp.ContentLength,
+			})
+			if pr.err != nil || pr.total == resp.ContentLength {
+				break
+			}
+		}
+	}()
+	err = selfupdate.Apply(pr, selfupdate.Options{})
 	if err != nil {
 		if rerr := selfupdate.RollbackError(err); rerr != nil {
 			return true, rerr

backend-golang/file.go

@@ -53,12 +53,12 @@ type FileInfo struct {
 	ModTime string `json:"modTime"`
 }
 
-func (a *App) ReadFileInfo(fileName string) (FileInfo, error) {
+func (a *App) ReadFileInfo(fileName string) (*FileInfo, error) {
 	info, err := os.Stat(a.exDir + fileName)
 	if err != nil {
-		return FileInfo{}, err
+		return nil, err
 	}
-	return FileInfo{
+	return &FileInfo{
 		Name:    info.Name(),
 		Size:    info.Size(),
 		IsDir:   info.IsDir(),
@@ -145,6 +145,20 @@ func (a *App) OpenSaveFileDialogBytes(filterPattern string, defaultFileName stri
 	return path, nil
 }
 
+// Only return the path of the selected file, because communication between frontend and backend is slow. Use AssetServer Handler to read the file.
+func (a *App) OpenOpenFileDialog(filterPattern string) (string, error) {
+	path, err := wruntime.OpenFileDialog(a.ctx, wruntime.OpenDialogOptions{
+		Filters: []wruntime.FileFilter{{Pattern: filterPattern}},
+	})
+	if err != nil {
+		return "", err
+	}
+	if path == "" {
+		return "", nil
+	}
+	return path, nil
+}
+
 func (a *App) OpenFileFolder(path string, relative bool) error {
 	var absPath string
 	var err error

backend-golang/rwkv.go

@@ -10,7 +10,7 @@ import (
 	"strings"
 )
 
-func (a *App) StartServer(python string, port int, host string, rwkvBeta bool) (string, error) {
+func (a *App) StartServer(python string, port int, host string, webui bool, rwkvBeta bool) (string, error) {
 	var err error
 	if python == "" {
 		python, err = GetPython()
@@ -19,6 +19,9 @@ func (a *App) StartServer(python string, port int, host string, rwkvBeta bool) (
 		return "", err
 	}
 	args := []string{python, "./backend-python/main.py"}
+	if webui {
+		args = append(args, "--webui")
+	}
 	if rwkvBeta {
 		args = append(args, "--rwkv-beta")
 	}
@@ -28,8 +31,7 @@ func (a *App) StartServer(python string, port int, host string, rwkvBeta bool) (
 
 func (a *App) StartWebGPUServer(port int, host string) (string, error) {
 	args := []string{"./backend-rust/webgpu_server"}
-	args = append(args, "-a", "0", "-t", "backend-rust/assets/rwkv_vocab_v20230424.json",
-		"--port", strconv.Itoa(port), "--ip", host)
+	args = append(args, "--port", strconv.Itoa(port), "--ip", host)
 	return Cmd(args...)
 }
 
@@ -149,9 +151,9 @@ func (a *App) InstallPyDep(python string, cnMirror bool) (string, error) {
 
 	if runtime.GOOS == "windows" {
 		ChangeFileLine("./py310/python310._pth", 3, "Lib\\site-packages")
-		installScript := python + " ./backend-python/get-pip.py -i https://pypi.tuna.tsinghua.edu.cn/simple\n" +
-			python + " -m pip install torch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1 --index-url https://download.pytorch.org/whl/cu117\n" +
-			python + " -m pip install -r ./backend-python/requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple\n" +
+		installScript := python + " ./backend-python/get-pip.py -i https://pypi.tuna.tsinghua.edu.cn/simple --no-warn-script-location\n" +
+			python + " -m pip install torch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1 --index-url https://download.pytorch.org/whl/cu117 --no-warn-script-location\n" +
+			python + " -m pip install -r ./backend-python/requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple --no-warn-script-location\n" +
 			"exit"
 		if !cnMirror {
 			installScript = strings.Replace(installScript, " -i https://pypi.tuna.tsinghua.edu.cn/simple", "", -1)

backend-golang/utils.go

@@ -5,12 +5,15 @@ import (
 	"bufio"
 	"embed"
 	"errors"
+	"fmt"
 	"io"
 	"io/fs"
+	"net"
 	"os"
 	"os/exec"
 	"path/filepath"
 	"runtime"
+	"strconv"
 	"strings"
 )
 
@@ -205,3 +208,12 @@ func Unzip(source, destination string) error {
 	}
 	return nil
 }
+
+func (a *App) IsPortAvailable(port int) bool {
+	l, err := net.Listen("tcp", fmt.Sprintf("127.0.0.1:%s", strconv.Itoa(port)))
+	if err != nil {
+		return false
+	}
+	defer l.Close()
+	return true
+}

backend-python/convert_model.py

@@ -231,5 +231,6 @@ try:
         convert_and_save_and_exit=args.out,
     )
 except Exception as e:
+    print(e)
     with open("error.txt", "w") as f:
         f.write(str(e))

backend-python/convert_safetensors.py

@@ -18,20 +18,31 @@ parser.add_argument(
 args = parser.parse_args()
 
 
-def convert_file(
-    pt_filename: str,
-    sf_filename: str,
-):
+def rename_key(rename, name):
+    for k, v in rename.items():
+        if k in name:
+            name = name.replace(k, v)
+    return name
+
+
+def convert_file(pt_filename: str, sf_filename: str, transpose_names=[], rename={}):
     loaded = torch.load(pt_filename, map_location="cpu")
     if "state_dict" in loaded:
         loaded = loaded["state_dict"]
 
     loaded = {k: v.clone().half() for k, v in loaded.items()}
-    for k, v in loaded.items():
-        print(f"{k}\t{v.shape}\t{v.dtype}")
+    # for k, v in loaded.items():
+    #     print(f'{k}\t{v.shape}\t{v.dtype}')
 
     # For tensors to be contiguous
-    loaded = {k: v.contiguous() for k, v in loaded.items()}
+    for k, v in loaded.items():
+        for transpose_name in transpose_names:
+            if transpose_name in k:
+                loaded[k] = v.transpose(0, 1)
+    loaded = {rename_key(rename, k).lower(): v.contiguous() for k, v in loaded.items()}
+
+    for k, v in loaded.items():
+        print(f"{k}\t{v.shape}\t{v.dtype}")
 
     dirname = os.path.dirname(sf_filename)
     os.makedirs(dirname, exist_ok=True)
@@ -46,8 +57,14 @@ def convert_file(
 
 if __name__ == "__main__":
     try:
-        convert_file(args.input, args.output)
+        convert_file(
+            args.input,
+            args.output,
+            ["lora_A"],
+            {"time_faaaa": "time_first", "lora_A": "lora.0", "lora_B": "lora.1"},
+        )
         print(f"Saved to {args.output}")
     except Exception as e:
+        print(e)
         with open("error.txt", "w") as f:
             f.write(str(e))

backend-python/dep_check.py

@@ -1,3 +1,5 @@
+import multipart
+import fitz
 import safetensors
 import midi2audio
 import mido
@@ -9,6 +11,7 @@ import GPUtil
 
 import torch
 import rwkv
+import langchain
 import numpy
 import tokenizers
 import fastapi

backend-python/global_var.py

@@ -4,6 +4,7 @@ Args = "args"
 Model = "model"
 Model_Status = "model_status"
 Model_Config = "model_config"
+Deploy_Mode = "deploy_mode"
 
 
 class ModelStatus(Enum):
@@ -16,6 +17,7 @@ def init():
     global GLOBALS
     GLOBALS = {}
     set(Model_Status, ModelStatus.Offline)
+    set(Deploy_Mode, False)
 
 
 def set(key, value):

backend-python/main.py

@@ -2,70 +2,8 @@ import time
 
 start_time = time.time()
 
-import os
-import sys
 import argparse
-from typing import Sequence
-
-sys.path.append(os.path.dirname(os.path.realpath(__file__)))
-
-import psutil
-from fastapi import Depends, FastAPI
-from fastapi.middleware.cors import CORSMiddleware
-import uvicorn
-
-from utils.rwkv import *
-from utils.torch import *
-from utils.ngrok import *
-from utils.log import log_middleware
-from routes import completion, config, state_cache, midi, misc
-import global_var
-
-app = FastAPI(dependencies=[Depends(log_middleware)])
-
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],
-    allow_credentials=True,
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
-
-app.include_router(completion.router)
-app.include_router(config.router)
-app.include_router(midi.router)
-app.include_router(misc.router)
-app.include_router(state_cache.router)
-
-
-@app.on_event("startup")
-def init():
-    global_var.init()
-    cmd_params = os.environ["RWKV_RUNNER_PARAMS"]
-    global_var.set(
-        global_var.Args, get_args(cmd_params.split(" ") if cmd_params else None)
-    )
-
-    state_cache.init()
-
-    set_torch()
-
-    if os.environ.get("ngrok_token") is not None:
-        ngrok_connect()
-
-
-@app.get("/", tags=["Root"])
-def read_root():
-    return {"Hello": "World!"}
-
-
-@app.post("/exit", tags=["Root"])
-def exit():
-    parent_pid = os.getpid()
-    parent = psutil.Process(parent_pid)
-    for child in parent.children(recursive=True):
-        child.kill()
-    parent.kill()
+from typing import Union, Sequence
 
 
 def get_args(args: Union[Sequence[str], None] = None):
@@ -84,6 +22,11 @@ def get_args(args: Union[Sequence[str], None] = None):
         help="host to run the server on (default: 127.0.0.1)",
     )
     group = parser.add_argument_group(title="mode arguments")
+    group.add_argument(
+        "--webui",
+        action="store_true",
+        help="whether to enable WebUI (default: False)",
+    )
     group.add_argument(
         "--rwkv-beta",
         action="store_true",
@@ -96,6 +39,96 @@ def get_args(args: Union[Sequence[str], None] = None):
 
 if __name__ == "__main__":
     args = get_args()
+
+
+import os
+import sys
+
+sys.path.append(os.path.dirname(os.path.realpath(__file__)))
+
+import psutil
+from contextlib import asynccontextmanager
+from fastapi import Depends, FastAPI, status
+from fastapi.middleware.cors import CORSMiddleware
+import uvicorn
+
+from utils.rwkv import *
+from utils.torch import *
+from utils.ngrok import *
+from utils.log import log_middleware
+from routes import completion, config, state_cache, midi, misc, file_process
+import global_var
+
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    init()
+    yield
+
+
+app = FastAPI(lifespan=lifespan, dependencies=[Depends(log_middleware)])
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+app.include_router(completion.router)
+app.include_router(config.router)
+app.include_router(midi.router)
+app.include_router(file_process.router)
+app.include_router(misc.router)
+app.include_router(state_cache.router)
+
+
+@app.post("/exit", tags=["Root"])
+def exit():
+    if global_var.get(global_var.Deploy_Mode) is True:
+        raise HTTPException(status.HTTP_403_FORBIDDEN)
+
+    parent_pid = os.getpid()
+    parent = psutil.Process(parent_pid)
+    for child in parent.children(recursive=True):
+        child.kill()
+    parent.kill()
+
+
+try:
+    if (
+        "RWKV_RUNNER_PARAMS" in os.environ
+        and "--webui" in os.environ["RWKV_RUNNER_PARAMS"].split(" ")
+    ) or args.webui:
+        from webui_server import webui_server
+
+        app.mount("/", webui_server)
+except NameError:
+    pass
+
+
+@app.get("/", tags=["Root"])
+def read_root():
+    return {"Hello": "World!"}
+
+
+def init():
+    global_var.init()
+    cmd_params = os.environ["RWKV_RUNNER_PARAMS"]
+    global_var.set(
+        global_var.Args, get_args(cmd_params.split(" ") if cmd_params else None)
+    )
+
+    state_cache.init()
+
+    set_torch()
+
+    if os.environ.get("ngrok_token") is not None:
+        ngrok_connect()
+
+
+if __name__ == "__main__":
     os.environ["RWKV_RUNNER_PARAMS"] = " ".join(sys.argv[1:])
     print("--- %s seconds ---" % (time.time() - start_time))
     uvicorn.run("main:app", port=args.port, host=args.host, workers=1)

backend-python/routes/completion.py

@@ -40,19 +40,21 @@ default_stop = [
 
 class ChatCompletionBody(ModelConfigBody):
     messages: Union[List[Message], None]
-    model: str = "rwkv"
+    model: Union[str, None] = "rwkv"
     stream: bool = False
     stop: Union[str, List[str], None] = default_stop
-    user_name: Union[str, None] = Field(None, description="Internal user name")
+    user_name: Union[str, None] = Field(
+        None, description="Internal user name", min_length=1
+    )
     assistant_name: Union[str, None] = Field(
-        None, description="Internal assistant name"
+        None, description="Internal assistant name", min_length=1
     )
     presystem: bool = Field(
         True, description="Whether to insert default system prompt at the beginning"
     )
 
-    class Config:
-        schema_extra = {
+    model_config = {
+        "json_schema_extra": {
             "example": {
                 "messages": [
                     {"role": Role.User.value, "content": "hello", "raw": False}
@@ -70,16 +72,17 @@ class ChatCompletionBody(ModelConfigBody):
                 "frequency_penalty": 0.4,
             }
         }
+    }
 
 
 class CompletionBody(ModelConfigBody):
     prompt: Union[str, List[str], None]
-    model: str = "rwkv"
+    model: Union[str, None] = "rwkv"
     stream: bool = False
     stop: Union[str, List[str], None] = None
 
-    class Config:
-        schema_extra = {
+    model_config = {
+        "json_schema_extra": {
             "example": {
                 "prompt": "The following is an epic science fiction masterpiece that is immortalized, "
                 + "with delicate descriptions and grand depictions of interstellar civilization wars.\nChapter 1.\n",
@@ -93,6 +96,7 @@ class CompletionBody(ModelConfigBody):
                 "frequency_penalty": 0.4,
             }
         }
+    }
 
 
 completion_lock = Lock()
@@ -317,11 +321,13 @@ The following is a coherent verbose detailed conversation between a girl named {
         completion_text += append_message + "\n\n"
     completion_text += f"{bot}{interface}"
 
+    user_code = model.pipeline.decode([model.pipeline.encode(user)[0]])
+    bot_code = model.pipeline.decode([model.pipeline.encode(bot)[0]])
     if type(body.stop) == str:
-        body.stop = [body.stop, f"\n\n{user}", f"\n\n{bot}"]
+        body.stop = [body.stop, f"\n\n{user_code}", f"\n\n{bot_code}"]
     elif type(body.stop) == list:
-        body.stop.append(f"\n\n{user}")
-        body.stop.append(f"\n\n{bot}")
+        body.stop.append(f"\n\n{user_code}")
+        body.stop.append(f"\n\n{bot_code}")
     elif body.stop is None:
         body.stop = default_stop
 
@@ -368,12 +374,12 @@ async def completions(body: CompletionBody, request: Request):
 
 class EmbeddingsBody(BaseModel):
     input: Union[str, List[str], List[List[int]], None]
-    model: str = "rwkv"
+    model: Union[str, None] = "rwkv"
     encoding_format: str = None
     fast_mode: bool = False
 
-    class Config:
-        schema_extra = {
+    model_config = {
+        "json_schema_extra": {
             "example": {
                 "input": "a big apple",
                 "model": "rwkv",
@@ -381,6 +387,7 @@ class EmbeddingsBody(BaseModel):
                 "fast_mode": False,
             }
         }
+    }
 
 
 def embedding_base64(embedding: List[float]) -> str:

backend-python/routes/config.py

@@ -10,39 +10,34 @@ import global_var
 router = APIRouter()
 
 
-def get_tokens_path(model_path: str):
-    model_path = model_path.lower()
-    tokenizer_dir = f"{pathlib.Path(__file__).parent.parent.resolve()}/rwkv_pip/"
-
-    default_tokens_path = tokenizer_dir + "20B_tokenizer.json"
-
-    if "raven" in model_path:
-        return default_tokens_path
-    elif "world" in model_path:
-        return "rwkv_vocab_v20230424"
-    elif "midi" in model_path:
-        return tokenizer_dir + "tokenizer-midi.json"
-    else:
-        return default_tokens_path
-
-
 class SwitchModelBody(BaseModel):
     model: str
     strategy: str
+    tokenizer: Union[str, None] = None
     customCuda: bool = False
+    deploy: bool = Field(
+        False,
+        description="Deploy mode. If success, will disable /switch-model, /exit and other dangerous APIs (state cache APIs, part of midi APIs)",
+    )
 
-    class Config:
-        schema_extra = {
+    model_config = {
+        "json_schema_extra": {
             "example": {
                 "model": "models/RWKV-4-World-3B-v1-20230619-ctx4096.pth",
                 "strategy": "cuda fp16",
+                "tokenizer": None,
                 "customCuda": False,
+                "deploy": False,
             }
         }
+    }
 
 
 @router.post("/switch-model", tags=["Configs"])
 def switch_model(body: SwitchModelBody, response: Response, request: Request):
+    if global_var.get(global_var.Deploy_Mode) is True:
+        raise HTTPException(Status.HTTP_403_FORBIDDEN)
+
     if global_var.get(global_var.Model_Status) is global_var.ModelStatus.Loading:
         response.status_code = Status.HTTP_304_NOT_MODIFIED
         return
@@ -68,17 +63,7 @@ def switch_model(body: SwitchModelBody, response: Response, request: Request):
     try:
         global_var.set(
             global_var.Model,
-            TextRWKV(
-                model=body.model,
-                strategy=body.strategy,
-                tokens_path=get_tokens_path(body.model),
-            )
-            if "midi" not in body.model.lower()
-            else MusicRWKV(
-                model=body.model,
-                strategy=body.strategy,
-                tokens_path=get_tokens_path(body.model),
-            ),
+            RWKV(model=body.model, strategy=body.strategy, tokenizer=body.tokenizer),
         )
     except Exception as e:
         print(e)
@@ -88,6 +73,8 @@ def switch_model(body: SwitchModelBody, response: Response, request: Request):
             Status.HTTP_500_INTERNAL_SERVER_ERROR, f"failed to load: {e}"
         )
 
+    if body.deploy:
+        global_var.set(global_var.Deploy_Mode, True)
     if global_var.get(global_var.Model_Config) is None:
         global_var.set(
             global_var.Model_Config, get_rwkv_config(global_var.get(global_var.Model))

backend-python/routes/file_process.py

@@ -0,0 +1,79 @@
+import os
+from fastapi import (
+    APIRouter,
+    HTTPException,
+    status,
+    Depends,
+    File,
+    UploadFile,
+)
+from pydantic import BaseModel
+from typing import Iterator
+
+router = APIRouter()
+
+
+class FileToTextParams(BaseModel):
+    file_name: str
+    file_encoding: str = "utf-8"
+
+
+@router.post("/file-to-text", tags=["File Process"])
+async def file_to_text(
+    params: FileToTextParams = Depends(), file_data: UploadFile = File(...)
+):
+    from langchain.schema import Document
+    from langchain.document_loaders.blob_loaders import Blob
+
+    # from langchain
+    def parse_text(blob: Blob) -> Iterator[Document]:
+        yield Document(page_content=blob.as_string(), metadata={"source": blob.source})
+
+    # from langchain
+    def parse_pdf(blob: Blob) -> Iterator[Document]:
+        import fitz
+
+        with blob.as_bytes_io() as stream:
+            doc = fitz.Document(stream=stream)
+
+            yield from [
+                Document(
+                    page_content=page.get_text(),
+                    metadata=dict(
+                        {
+                            "source": blob.source,
+                            "file_path": blob.source,
+                            "page": page.number,
+                            "total_pages": len(doc),
+                        },
+                        **{
+                            k: doc.metadata[k]
+                            for k in doc.metadata
+                            if type(doc.metadata[k]) in [str, int]
+                        },
+                    ),
+                )
+                for page in doc
+            ]
+
+    file_parsers = {".txt": parse_text, ".pdf": parse_pdf}
+
+    file_name = file_data.filename or params.file_name
+    file_ext = os.path.splitext(file_name)[-1]
+
+    if file_ext not in file_parsers:
+        raise HTTPException(status.HTTP_400_BAD_REQUEST, "file type not supported")
+
+    try:
+        pages: Iterator[Document] = file_parsers[file_ext](
+            Blob.from_data(
+                await file_data.read(),
+                encoding=params.file_encoding,
+                path=file_name,
+            )
+        )
+        pages = list(pages)
+    except Exception as e:
+        raise HTTPException(status.HTTP_400_BAD_REQUEST, f"{e}")
+
+    return {"pages": pages}

backend-python/routes/midi.py

@@ -1,4 +1,5 @@
 import io
+import global_var
 from fastapi import APIRouter, HTTPException, status
 from starlette.responses import StreamingResponse
 from pydantic import BaseModel
@@ -11,12 +12,13 @@ router = APIRouter()
 class TextToMidiBody(BaseModel):
     text: str
 
-    class Config:
-        schema_extra = {
+    model_config = {
+        "json_schema_extra": {
             "example": {
                 "text": "p:24:a p:2a:a p:31:a p:39:a p:3b:a p:45:a b:26:a g:3e:a g:3e:a g:42:a g:42:a g:45:a g:45:a pi:3e:a pi:42:a pi:45:a t14 p:24:0 p:2a:0 p:31:0 p:39:0 p:3b:0 p:45:0 t2 p:2a:a p:3b:a p:45:a t14 p:2a:0 p:3b:0 p:45:0 b:26:0 g:3e:0 g:3e:0 g:42:0 g:42:0 g:45:0 g:45:0 pi:3e:0 pi:42:0 pi:45:0 t2 p:2e:a p:3b:a p:45:a b:26:a g:3e:a g:3e:a g:42:a g:42:a g:45:a g:45:a pi:3e:a pi:42:a pi:45:a t14 p:2e:0 p:3b:0 p:45:0 g:3e:0 g:3e:0 g:42:0 g:42:0 g:45:0 g:45:0 pi:3e:0 pi:42:0 pi:45:0 t2 p:2e:a p:3b:a p:45:a g:3e:a g:3e:a g:42:a g:42:a g:45:a g:45:a pi:3e:a pi:42:a pi:45:a t14 p:2e:0 p:3b:0 p:45:0 b:26:0 g:3e:0 g:3e:0 g:42:0 g:42:0 g:45:0 g:45:0 pi:3e:0 pi:42:0 pi:45:0 t2 p:26:a p:2a:a p:3b:a p:45:a t14 p:26:0 p:2a:0 p:3b:0 p:45:0 t2 p:2a:a p:3b:a p:45:a b:26:a g:3e:a g:3e:a g:42:a g:42:a g:45:a g:45:a pi:3e:a pi:42:a pi:45:a t14 p:2a:0 p:3b:0 p:45:0 b:26:0 t2 p:24:a p:2a:a p:3b:a p:45:a b:2d:a t14 p:24:0 p:2a:0 p:3b:0 p:45:0 b:2d:0 g:3e:0 g:3e:0 g:42:0 g:42:0 g:45:0 g:45:0 pi:3e:0 pi:42:0 pi:45:0 t2 p:24:a p:2a:a p:3b:a p:45:a b:21:a g:39:a g:39:a g:3d:a g:3d:a g:40:a g:40:a pi:39:a pi:3d:a pi:40:a t14 p:24:0 p:2a:0 p:3b:0 p:45:0 t2 p:2a:a p:3b:a p:45:a t14 p:2a:0 p:3b:0 p:45:0 b:21:0 g:39:0 g:39:0 g:3d:0 g:3d:0 g:40:0 g:40:0 pi:39:0 pi:3d:0 pi:40:0 t2 p:24:a p:2e:a p:3b:a p:45:a b:21:a g:39:a g:39:a g:3d:a g:3d:a g:40:a g:40:a pi:39:a pi:3d:a pi:40:a t14 p:24:0 p:2e:0 p:3b:0 p:45:0 b:21:0 g:39:0 g:39:0 g:3d:0 g:3d:0 g:40:0 g:40:0 pi:39:0 pi:3d:0 pi:40:0 t2 p:24:a p:2a:a p:3b:a p:45:a b:21:a g:39:a g:39:a g:3d:a g:3d:a g:40:a g:40:a pi:39:a pi:3d:a pi:40:a t14 p:24:0 p:2a:0 p:3b:0 p:45:0 t2 p:2a:a p:3b:a p:45:a t14 p:2a:0 p:3b:0 p:45:0 b:21:0 g:39:0 g:39:0 g:3d:0 g:3d:0 g:40:0 g:40:0 pi:39:0 pi:3d:0 pi:40:0 t2 p:26:a p:2a:a p:3b:a p:45:a b:21:a g:39:a g:39:a g:3d:a g:3d:a g:40:a g:40:a pi:39:a pi:3d:a pi:40:a t14 p:26:0 p:2a:0 p:3b:0 p:45:0 t2 p:2a:a p:3b:a p:45:a t14 p:2a:0 p:3b:0 p:45:0 b:21:0 g:39:0 g:39:0 g:3d:0 g:3d:0 g:40:0 g:40:0 pi:39:0 pi:3d:0 pi:40:0 t2 p:26:a p:2e:a p:31:a p:39:a p:3b:a p:45:a b:21:a g:39:a g:39:a g:3d:a g:3d:a g:40:a g:40:a pi:39:a pi:3d:a pi:40:a t14 p:26:0 p:2e:0 p:31:0 p:39:0 p:3b:0 p:45:0 b:21:0 t2 p:26:a p:2e:a p:31:a p:39:a p:3b:a p:45:a b:21:a t14 p:26:0 p:2e:0 p:31:0 p:39:0 p:3b:0 p:45:0 b:21:0 g:39:0 g:39:0 g:3d:0 g:3d:0 g:40:0 g:40:0 pi:39:0 pi:3d:0 pi:40:0 t2 p:24:a p:2a:a p:31:a p:39:a p:3b:a p:45:a b:1f:a g:3b:a g:3b:a g:3e:a g:3e:a g:43:a g:43:a pi:3b:a pi:3e:a pi:43:a t14 p:24:0 p:2a:0 p:31:0 p:39:0 p:3b:0 p:45:0 t2 p:2a:a p:3b:a p:45:a t14 p:2a:0 p:3b:0 p:45:0 b:1f:0 g:3b:0 g:3b:0 g:3e:0 g:3e:0 g:43:0 g:43:0 pi:3b:0 pi:3e:0 pi:43:0 t2 p:2e:a p:3b:a p:45:a b:1f:a g:3b:a g:3b:a g:3e:a g:3e:a g:43:a g:43:a pi:3b:a pi:3e:a pi:43:a t14 p:2e:0 p:3b:0 p:45:0 g:3b:0 g:3b:0 g:3e:0 g:3e:0 g:43:0 g:43:0 pi:3b:0 pi:3e:0 pi:43:0 t2 p:2e:a p:3b:a p:45:a g:3b:a g:3b:a g:3e:a g:3e:a g:43:a g:43:a pi:3b:a pi:3e:a pi:43:a t14 p:2e:0 p:3b:0 p:45:0 b:1f:0 g:3b:0 g:3b:0 g:3e:0 g:3e:0 g:43:0 g:43:0 pi:3b:0 pi:3e:0 pi:43:0 t2 p:26:a p:2a:a p:3b:a p:45:a t14 p:26:0 p:2a:0 p:3b:0 p:45:0 t2 p:2a:a p:3b:a p:45:a b:1f:a g:3b:a g:3b:a g:3e:a g:3e:a g:43:a g:43:a pi:3b:a pi:3e:a pi:43:a t14 p:2a:0 p:3b:0 p:45:0 b:1f:0 t2 p:24:a p:2a:a p:3b:a p:45:a b:1f:a t14 p:24:0 p:2a:0 p:3b:0 p:45:0 b:1f:0 g:3b:0 g:3b:0 g:3e:0 g:3e:0 g:43:0 g:43:0 pi:3b:0 pi:3e:0 pi:43:0 t2 p:24:a p:2e:a p:3b:a p:45:a b:26:a g:39:a g:39:a g:3e:a g:3e:a g:42:a g:42:a pi:39:a pi:3e:a pi:42:a t14 p:24:0 p:2e:0 p:3b:0 p:45:0 t2 p:2a:a p:3b:a p:45:a t14 p:2a:0 p:3b:0",
             }
         }
+    }
 
 
 @router.post("/text-to-midi", tags=["MIDI"])
@@ -35,17 +37,21 @@ class TxtToMidiBody(BaseModel):
     txt_path: str
     midi_path: str
 
-    class Config:
-        schema_extra = {
+    model_config = {
+        "json_schema_extra": {
             "example": {
                 "txt_path": "midi/sample.txt",
                 "midi_path": "midi/sample.mid",
             }
         }
+    }
 
 
 @router.post("/txt-to-midi", tags=["MIDI"])
 def txt_to_midi(body: TxtToMidiBody):
+    if global_var.get(global_var.Deploy_Mode) is True:
+        raise HTTPException(status.HTTP_403_FORBIDDEN)
+
     if not body.midi_path.startswith("midi/"):
         raise HTTPException(status.HTTP_400_BAD_REQUEST, "bad output path")
 
@@ -65,14 +71,15 @@ class MidiToWavBody(BaseModel):
     wav_path: str
     sound_font_path: str = "assets/default_sound_font.sf2"
 
-    class Config:
-        schema_extra = {
+    model_config = {
+        "json_schema_extra": {
             "example": {
                 "midi_path": "midi/sample.mid",
                 "wav_path": "midi/sample.wav",
                 "sound_font_path": "assets/default_sound_font.sf2",
             }
         }
+    }
 
 
 @router.post("/midi-to-wav", tags=["MIDI"])
@@ -81,6 +88,9 @@ def midi_to_wav(body: MidiToWavBody):
     Install fluidsynth first, see more: https://github.com/FluidSynth/fluidsynth/wiki/Download#distributions
     """
 
+    if global_var.get(global_var.Deploy_Mode) is True:
+        raise HTTPException(status.HTTP_403_FORBIDDEN)
+
     if not body.wav_path.startswith("midi/"):
         raise HTTPException(status.HTTP_400_BAD_REQUEST, "bad output path")
 
@@ -95,14 +105,15 @@ class TextToWavBody(BaseModel):
     wav_name: str
     sound_font_path: str = "assets/default_sound_font.sf2"
 
-    class Config:
-        schema_extra = {
+    model_config = {
+        "json_schema_extra": {
             "example": {
                 "text": "p:24:a p:2a:a p:31:a p:39:a p:3b:a p:45:a b:26:a g:3e:a g:3e:a g:42:a g:42:a g:45:a g:45:a pi:3e:a pi:42:a pi:45:a t14 p:24:0 p:2a:0 p:31:0 p:39:0 p:3b:0 p:45:0 t2 p:2a:a p:3b:a p:45:a t14 p:2a:0 p:3b:0 p:45:0 b:26:0 g:3e:0 g:3e:0 g:42:0 g:42:0 g:45:0 g:45:0 pi:3e:0 pi:42:0 pi:45:0 t2 p:2e:a p:3b:a p:45:a b:26:a g:3e:a g:3e:a g:42:a g:42:a g:45:a g:45:a pi:3e:a pi:42:a pi:45:a t14 p:2e:0 p:3b:0 p:45:0 g:3e:0 g:3e:0 g:42:0 g:42:0 g:45:0 g:45:0 pi:3e:0 pi:42:0 pi:45:0 t2 p:2e:a p:3b:a p:45:a g:3e:a g:3e:a g:42:a g:42:a g:45:a g:45:a pi:3e:a pi:42:a pi:45:a t14 p:2e:0 p:3b:0 p:45:0 b:26:0 g:3e:0 g:3e:0 g:42:0 g:42:0 g:45:0 g:45:0 pi:3e:0 pi:42:0 pi:45:0 t2 p:26:a p:2a:a p:3b:a p:45:a t14 p:26:0 p:2a:0 p:3b:0 p:45:0 t2 p:2a:a p:3b:a p:45:a b:26:a g:3e:a g:3e:a g:42:a g:42:a g:45:a g:45:a pi:3e:a pi:42:a pi:45:a t14 p:2a:0 p:3b:0 p:45:0 b:26:0 t2 p:24:a p:2a:a p:3b:a p:45:a b:2d:a t14 p:24:0 p:2a:0 p:3b:0 p:45:0 b:2d:0 g:3e:0 g:3e:0 g:42:0 g:42:0 g:45:0 g:45:0 pi:3e:0 pi:42:0 pi:45:0 t2 p:24:a p:2a:a p:3b:a p:45:a b:21:a g:39:a g:39:a g:3d:a g:3d:a g:40:a g:40:a pi:39:a pi:3d:a pi:40:a t14 p:24:0 p:2a:0 p:3b:0 p:45:0 t2 p:2a:a p:3b:a p:45:a t14 p:2a:0 p:3b:0 p:45:0 b:21:0 g:39:0 g:39:0 g:3d:0 g:3d:0 g:40:0 g:40:0 pi:39:0 pi:3d:0 pi:40:0 t2 p:24:a p:2e:a p:3b:a p:45:a b:21:a g:39:a g:39:a g:3d:a g:3d:a g:40:a g:40:a pi:39:a pi:3d:a pi:40:a t14 p:24:0 p:2e:0 p:3b:0 p:45:0 b:21:0 g:39:0 g:39:0 g:3d:0 g:3d:0 g:40:0 g:40:0 pi:39:0 pi:3d:0 pi:40:0 t2 p:24:a p:2a:a p:3b:a p:45:a b:21:a g:39:a g:39:a g:3d:a g:3d:a g:40:a g:40:a pi:39:a pi:3d:a pi:40:a t14 p:24:0 p:2a:0 p:3b:0 p:45:0 t2 p:2a:a p:3b:a p:45:a t14 p:2a:0 p:3b:0 p:45:0 b:21:0 g:39:0 g:39:0 g:3d:0 g:3d:0 g:40:0 g:40:0 pi:39:0 pi:3d:0 pi:40:0 t2 p:26:a p:2a:a p:3b:a p:45:a b:21:a g:39:a g:39:a g:3d:a g:3d:a g:40:a g:40:a pi:39:a pi:3d:a pi:40:a t14 p:26:0 p:2a:0 p:3b:0 p:45:0 t2 p:2a:a p:3b:a p:45:a t14 p:2a:0 p:3b:0 p:45:0 b:21:0 g:39:0 g:39:0 g:3d:0 g:3d:0 g:40:0 g:40:0 pi:39:0 pi:3d:0 pi:40:0 t2 p:26:a p:2e:a p:31:a p:39:a p:3b:a p:45:a b:21:a g:39:a g:39:a g:3d:a g:3d:a g:40:a g:40:a pi:39:a pi:3d:a pi:40:a t14 p:26:0 p:2e:0 p:31:0 p:39:0 p:3b:0 p:45:0 b:21:0 t2 p:26:a p:2e:a p:31:a p:39:a p:3b:a p:45:a b:21:a t14 p:26:0 p:2e:0 p:31:0 p:39:0 p:3b:0 p:45:0 b:21:0 g:39:0 g:39:0 g:3d:0 g:3d:0 g:40:0 g:40:0 pi:39:0 pi:3d:0 pi:40:0 t2 p:24:a p:2a:a p:31:a p:39:a p:3b:a p:45:a b:1f:a g:3b:a g:3b:a g:3e:a g:3e:a g:43:a g:43:a pi:3b:a pi:3e:a pi:43:a t14 p:24:0 p:2a:0 p:31:0 p:39:0 p:3b:0 p:45:0 t2 p:2a:a p:3b:a p:45:a t14 p:2a:0 p:3b:0 p:45:0 b:1f:0 g:3b:0 g:3b:0 g:3e:0 g:3e:0 g:43:0 g:43:0 pi:3b:0 pi:3e:0 pi:43:0 t2 p:2e:a p:3b:a p:45:a b:1f:a g:3b:a g:3b:a g:3e:a g:3e:a g:43:a g:43:a pi:3b:a pi:3e:a pi:43:a t14 p:2e:0 p:3b:0 p:45:0 g:3b:0 g:3b:0 g:3e:0 g:3e:0 g:43:0 g:43:0 pi:3b:0 pi:3e:0 pi:43:0 t2 p:2e:a p:3b:a p:45:a g:3b:a g:3b:a g:3e:a g:3e:a g:43:a g:43:a pi:3b:a pi:3e:a pi:43:a t14 p:2e:0 p:3b:0 p:45:0 b:1f:0 g:3b:0 g:3b:0 g:3e:0 g:3e:0 g:43:0 g:43:0 pi:3b:0 pi:3e:0 pi:43:0 t2 p:26:a p:2a:a p:3b:a p:45:a t14 p:26:0 p:2a:0 p:3b:0 p:45:0 t2 p:2a:a p:3b:a p:45:a b:1f:a g:3b:a g:3b:a g:3e:a g:3e:a g:43:a g:43:a pi:3b:a pi:3e:a pi:43:a t14 p:2a:0 p:3b:0 p:45:0 b:1f:0 t2 p:24:a p:2a:a p:3b:a p:45:a b:1f:a t14 p:24:0 p:2a:0 p:3b:0 p:45:0 b:1f:0 g:3b:0 g:3b:0 g:3e:0 g:3e:0 g:43:0 g:43:0 pi:3b:0 pi:3e:0 pi:43:0 t2 p:24:a p:2e:a p:3b:a p:45:a b:26:a g:39:a g:39:a g:3e:a g:3e:a g:42:a g:42:a pi:39:a pi:3e:a pi:42:a t14 p:24:0 p:2e:0 p:3b:0 p:45:0 t2 p:2a:a p:3b:a p:45:a t14 p:2a:0 p:3b:0",
                 "wav_name": "sample",
                 "sound_font_path": "assets/default_sound_font.sf2",
             }
         }
+    }
 
 
 @router.post("/text-to-wav", tags=["MIDI"])
@@ -111,6 +122,9 @@ def text_to_wav(body: TextToWavBody):
     Install fluidsynth first, see more: https://github.com/FluidSynth/fluidsynth/wiki/Download#distributions
     """
 
+    if global_var.get(global_var.Deploy_Mode) is True:
+        raise HTTPException(status.HTTP_403_FORBIDDEN)
+
     text = body.text.strip()
     if not text.startswith("<start>"):
         text = "<start> " + text

backend-python/routes/state_cache.py

@@ -4,12 +4,13 @@ from fastapi import APIRouter, HTTPException, Request, Response, status
 from pydantic import BaseModel
 import gc
 import copy
+import global_var
 
 router = APIRouter()
 
 trie = None
 dtrie: Dict = {}
-max_trie_len = 3000
+max_trie_len = 300
 loop_start_id = 1  # to prevent preloaded prompts from being deleted
 loop_del_trie_id = loop_start_id
 
@@ -36,6 +37,9 @@ def init():
 def disable_state_cache():
     global trie, dtrie
 
+    if global_var.get(global_var.Deploy_Mode) is True:
+        raise HTTPException(status.HTTP_403_FORBIDDEN)
+
     trie = None
     dtrie = {}
     gc.collect()
@@ -46,6 +50,10 @@ def disable_state_cache():
 @router.post("/enable-state-cache", tags=["State Cache"])
 def enable_state_cache():
     global trie, dtrie
+
+    if global_var.get(global_var.Deploy_Mode) is True:
+        raise HTTPException(status.HTTP_403_FORBIDDEN)
+
     try:
         import cyac
 
@@ -68,6 +76,10 @@ class AddStateBody(BaseModel):
 @router.post("/add-state", tags=["State Cache"])
 def add_state(body: AddStateBody):
     global trie, dtrie, loop_del_trie_id
+
+    if global_var.get(global_var.Deploy_Mode) is True:
+        raise HTTPException(status.HTTP_403_FORBIDDEN)
+
     if trie is None:
         raise HTTPException(status.HTTP_400_BAD_REQUEST, "trie not loaded")
 
@@ -108,6 +120,10 @@ def add_state(body: AddStateBody):
 @router.post("/reset-state", tags=["State Cache"])
 def reset_state():
     global trie, dtrie
+
+    if global_var.get(global_var.Deploy_Mode) is True:
+        raise HTTPException(status.HTTP_403_FORBIDDEN)
+
     if trie is None:
         raise HTTPException(status.HTTP_400_BAD_REQUEST, "trie not loaded")
 
@@ -144,6 +160,10 @@ def __get_a_dtrie_buff_size(dtrie_v):
 @router.post("/longest-prefix-state", tags=["State Cache"])
 def longest_prefix_state(body: LongestPrefixStateBody, request: Request):
     global trie
+
+    if global_var.get(global_var.Deploy_Mode) is True:
+        raise HTTPException(status.HTTP_403_FORBIDDEN)
+
     if trie is None:
         raise HTTPException(status.HTTP_400_BAD_REQUEST, "trie not loaded")
 
@@ -183,6 +203,10 @@ def longest_prefix_state(body: LongestPrefixStateBody, request: Request):
 @router.post("/save-state", tags=["State Cache"])
 def save_state():
     global trie
+
+    if global_var.get(global_var.Deploy_Mode) is True:
+        raise HTTPException(status.HTTP_403_FORBIDDEN)
+
     if trie is None:
         raise HTTPException(status.HTTP_400_BAD_REQUEST, "trie not loaded")
 

backend-python/rwkv_pip/beta/cuda/att_one.cu

@@ -88,7 +88,7 @@ struct Mix {
 
 using torch::Tensor;
 
-void gemm_fp16_cublas(Tensor a, Tensor b, Tensor c);
+void gemm_fp16_cublas_tensor(Tensor a, Tensor b, Tensor c);
 
 Tensor att_one(Tensor x, Tensor ln_w, Tensor ln_b, Tensor sx, Tensor k_mix,
              Tensor v_mix, Tensor r_mix, Tensor kw,
@@ -105,9 +105,9 @@ Tensor att_one(Tensor x, Tensor ln_w, Tensor ln_b, Tensor sx, Tensor k_mix,
                    data_ptr<half>(vx), data_ptr<half>(rx)},
                x.numel());
 
-  gemm_fp16_cublas(kx, kw, k);
-  gemm_fp16_cublas(vx, vw, v);
-  gemm_fp16_cublas(rx, rw, r);
+  gemm_fp16_cublas_tensor(kx, kw, k);
+  gemm_fp16_cublas_tensor(vx, vw, v);
+  gemm_fp16_cublas_tensor(rx, rw, r);
   at::sigmoid_(r);
 
   element_wise(WkvForwardOne{data_ptr<float>(t_first), data_ptr<float>(k),
@@ -118,7 +118,7 @@ Tensor att_one(Tensor x, Tensor ln_w, Tensor ln_b, Tensor sx, Tensor k_mix,
                              data_ptr<half>(r)},
                x.numel());
 
-  gemm_fp16_cublas(r, ow, x_plus_out);
+  gemm_fp16_cublas_tensor(r, ow, x_plus_out);
   x_plus_out += x;
   return xx;
 }

backend-python/rwkv_pip/beta/cuda/att_one_v5.cu

@@ -0,0 +1,109 @@
+#include "ATen/ATen.h"
+#include <cuda_fp16.h>
+#include <cuda_runtime.h>
+#include <torch/extension.h>
+
+#include "element_wise.h"
+#include "util.h"
+
+// Equivalent Python code:
+// s1 = t_first * a + s
+// s2 = a + t_decay * s
+struct Fused1 {
+  const float *t_first;
+  const float *t_decay;
+  const float *a;
+  const float *s;
+  const int32_t inner_size;
+  /* out */ float *s1;
+  /* out */ float *s2;
+
+  __device__ void operator()(int i) const {
+    const int j = i / inner_size;
+    s1[i] = t_first[j] * a[i] + s[i];
+    s2[i] = a[i] + t_decay[j] * s[i];
+  }
+};
+
+/*
+   Equivalent Python code:
+   kx = xx * k_mix + sx * (1 - k_mix)
+   vx = xx * v_mix + sx * (1 - v_mix)
+   rx = xx * r_mix + sx * (1 - r_mix)
+*/
+
+struct Mix {
+  const half *xx;
+  const half *sx;
+  const half *k_mix;
+  const half *v_mix;
+  const half *r_mix;
+  /* out */ half *kx;
+  /* out */ half *vx;
+  /* out */ half *rx;
+
+  __device__ void operator()(int i) const {
+    half xx_ = xx[i];
+    half sx_ = sx[i];
+    half k_mix_ = k_mix[i];
+    half v_mix_ = v_mix[i];
+    half r_mix_ = r_mix[i];
+    kx[i] = __hadd(__hmul(xx_, k_mix_),
+                   __hmul(sx_, __hsub(__float2half(1), k_mix_)));
+    vx[i] = __hadd(__hmul(xx_, v_mix_),
+                   __hmul(sx_, __hsub(__float2half(1), v_mix_)));
+    rx[i] = __hadd(__hmul(xx_, r_mix_),
+                   __hmul(sx_, __hsub(__float2half(1), r_mix_)));
+  }
+};
+
+using torch::Tensor;
+
+void gemm_fp16_cublas_tensor(Tensor a, Tensor b, Tensor c);
+
+Tensor att_one_v5(Tensor x, Tensor sx, Tensor s, Tensor ln_w, Tensor ln_b,
+                  Tensor lx_w, Tensor lx_b, Tensor k_mix, Tensor v_mix,
+                  Tensor r_mix, Tensor kw,
+                  /* imm */ Tensor kx, Tensor vw, /* imm */ Tensor vx,
+                  Tensor rw,
+                  /* imm */ Tensor rx, Tensor ow, Tensor t_first,
+                  /* imm */ Tensor k, Tensor t_decay, /* imm */ Tensor v,
+                  /* imm */ Tensor r, /* imm */ Tensor s1,
+                  /* out */ Tensor x_plus_out, /* out */ Tensor s2) {
+  Tensor xx = at::layer_norm(x, {x.size(-1)}, ln_w, ln_b);
+  element_wise(Mix{data_ptr<half>(xx), data_ptr<half>(sx),
+                   data_ptr<half>(k_mix), data_ptr<half>(v_mix),
+                   data_ptr<half>(r_mix), data_ptr<half>(kx),
+                   data_ptr<half>(vx), data_ptr<half>(rx)},
+               x.numel());
+
+  int H = t_decay.size(0);
+  int S = x.size(-1) / H;
+  gemm_fp16_cublas_tensor(rx, rw, r);
+  r = at::reshape(r, {H, 1, S});
+  gemm_fp16_cublas_tensor(kx, kw, k);
+  k = at::reshape(k, {H, S, 1});
+  gemm_fp16_cublas_tensor(vx, vw, v);
+  v = at::reshape(v, {H, 1, S});
+
+  {
+    Tensor a = at::matmul(k, v);
+
+    // s1 = t_first * a + s
+    // s2 = a + t_decay * s
+    element_wise(Fused1{data_ptr<float>(t_first), data_ptr<float>(t_decay),
+                        data_ptr<float>(a), data_ptr<float>(s),
+                        static_cast<int32_t>(a.size(1) * a.size(2)),
+                        data_ptr<float>(s1), data_ptr<float>(s2)},
+                 a.numel());
+  }
+
+  Tensor out = at::matmul(r, s1);
+  out = at::flatten(out);
+  out = at::squeeze(at::group_norm(at::unsqueeze(out, 0), H, lx_w, lx_b), 0);
+  out = at::_cast_Half(out);
+
+  gemm_fp16_cublas_tensor(out, ow, x_plus_out);
+  x_plus_out += x;
+  return xx;
+}

backend-python/rwkv_pip/beta/cuda/att_seq.cu

@@ -8,7 +8,6 @@
 
 using torch::Tensor;
 
-void gemm_fp16_cublas(Tensor a, Tensor b, Tensor c);
 void gemm_fp16_cublas(const void *a, const void *b, void *c, int m,
                       int n, int k, bool output_fp32);
 

backend-python/rwkv_pip/beta/cuda/gemm_fp16_cublas.cpp

@@ -70,11 +70,59 @@ void gemm_fp16_cublas(const void *a, const void *b, void *c, int ori_m,
       cuda_c_data_type, cublas_ldc, compute_type, algo));
 }
 
-void gemm_fp16_cublas(torch::Tensor a, torch::Tensor b, torch::Tensor c) {
-  // comptiable with rwkv one mode, 1-D tensor * 2-D tensor
-  const int m = a.dense_dim() == 1 ? 1 : a.size(0);
-  const int n = b.size(1);
-  const int k = b.size(0);
-  gemm_fp16_cublas(a.data_ptr(), b.data_ptr(), c.data_ptr(), m, n, k,
-                   c.dtype() == torch::kFloat32);
+/*
+  NOTE: blas gemm is column-major by default, but we need row-major output.
+  The data of row-major, transposed matrix is exactly the same as the
+  column-major, non-transposed matrix, and C = A * B ---> C^T = B^T * A^T
+ */
+void gemm_fp16_cublas_tensor(torch::Tensor a, torch::Tensor b, torch::Tensor c) {
+  if (a.sizes().size() == 1) {
+    assert(b.sizes().size() == 2);
+    a = at::unsqueeze(a, 0);
+  }
+  const auto cuda_data_type = CUDA_R_16F;
+  const auto cuda_c_data_type =
+      c.dtype() == torch::kFloat32 ? CUDA_R_32F : CUDA_R_16F;
+  const auto compute_type = CUDA_R_32F;
+  const float sp_alpha = 1.f;
+  // swap a and b, and use CUBLAS_OP_N. see the notes above
+  std::swap(a, b);
+  const cublasOperation_t cublas_trans_a = CUBLAS_OP_N;
+  const cublasOperation_t cublas_trans_b = CUBLAS_OP_N;
+  // m = (B^T).size(0) = B.size(1), and = A.size(1) after swap,
+  // negative axis is used because of the existence of batch matmul.
+  const int m = a.size(-1);
+  const int k = a.size(-2);
+  const int n = b.size(-2);
+  const int cublas_lda = m;
+  const int cublas_ldb = k;
+  const int cublas_ldc = m;
+  cublasHandle_t cublas_handle = get_cublas_handle();
+
+#if CUDA_VERSION >= 11000
+  cublasGemmAlgo_t algo = CUBLAS_GEMM_DEFAULT;
+#else
+  cublasGemmAlgo_t algo = CUBLAS_GEMM_DFALT_TENSOR_OP;
+#endif
+  const float sp_beta = 0.f;
+  if (a.sizes().size() == 2 && b.sizes().size() == 2) {
+    CUBLAS_CHECK(cublasGemmEx(
+        cublas_handle, cublas_trans_a, cublas_trans_b, m, n, k, &sp_alpha,
+        a.data_ptr(), cuda_data_type, cublas_lda, b.data_ptr(), cuda_data_type,
+        cublas_ldb, &sp_beta, c.data_ptr(), cuda_c_data_type, cublas_ldc,
+        compute_type, algo));
+  } else {
+    // batch matmul
+    assert(a.sizes().size() == 3 && b.sizes().size() == 3);
+
+    const long long int cublas_stride_a = m * k;
+    const long long int cublas_stride_b = k * n;
+    const long long int cublas_stride_c = m * n;
+    CUBLAS_CHECK(cublasGemmStridedBatchedEx(
+        cublas_handle, cublas_trans_a, cublas_trans_b, m,
+        n, k, &sp_alpha, a.data_ptr(), cuda_data_type, cublas_lda,
+        cublas_stride_a, b.data_ptr(), cuda_data_type, cublas_ldb, cublas_stride_b,
+        &sp_beta, c.data_ptr(), cuda_c_data_type, cublas_ldc, cublas_stride_c,
+        a.size(0), compute_type, algo));
+  }
 }

backend-python/rwkv_pip/beta/cuda/wrapper.cpp

@@ -118,7 +118,9 @@ void mm8_one(int64_t N, int64_t M,
 
 using torch::Tensor;
 
-void gemm_fp16_cublas(Tensor a, Tensor b, Tensor c);
+#ifndef DISABLE_CUBLAS_GEMM
+void gemm_fp16_cublas_tensor(Tensor a, Tensor b, Tensor c);
+#endif
 
 Tensor att_one(Tensor x, Tensor ln_w, Tensor ln_b, Tensor sx, Tensor k_mix,
              Tensor v_mix, Tensor r_mix, Tensor kw,
@@ -134,6 +136,16 @@ Tensor att_seq(Tensor x, Tensor sx, Tensor ln_w, Tensor ln_b, Tensor k_mix,
                Tensor ow, Tensor t_first, Tensor pp, Tensor aa, Tensor bb,
                Tensor t_decay, /* imm */ Tensor buf, /* out */ Tensor x_plus_out);
 
+Tensor att_one_v5(Tensor x, Tensor sx, Tensor s, Tensor ln_w, Tensor ln_b,
+                  Tensor lx_w, Tensor lx_b, Tensor k_mix, Tensor v_mix,
+                  Tensor r_mix, Tensor kw,
+                  /* imm */ Tensor kx, Tensor vw, /* imm */ Tensor vx,
+                  Tensor rw,
+                  /* imm */ Tensor rx, Tensor ow, Tensor t_first,
+                  /* imm */ Tensor k, Tensor t_decay, /* imm */ Tensor v,
+                  /* imm */ Tensor r, /* imm */ Tensor s1,
+                  /* out */ Tensor x_plus_out, /* out */ Tensor s2);
+
 Tensor ffn_seq(Tensor x, Tensor sx, Tensor ln_w, Tensor ln_b, Tensor k_mix,
                Tensor r_mix, Tensor kw, Tensor vw, Tensor rw,
                /* imm */ Tensor buf,
@@ -148,8 +160,9 @@ PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
     m.def("wkv_forward", &wkv_forward, "wkv forward");
     m.def("mm8_seq", &mm8_seq, "mm8 seq");
     m.def("mm8_one", &mm8_one, "mm8 one");
-    m.def("gemm_fp16_cublas", &gemm_fp16_cublas, "gemv fp16 cublas");
+    m.def("gemm_fp16_cublas", &gemm_fp16_cublas_tensor, "gemv fp16 cublas");
     m.def("att_one", &att_one, "att one");
+    m.def("att_one_v5", &att_one_v5, "att one v5");
     m.def("att_seq", &att_seq, "att seq");
     m.def("ffn_seq", &ffn_seq, "ffn seq");
     m.def("ffn_one", &ffn_one, "ffn one");
@@ -159,8 +172,9 @@ TORCH_LIBRARY(rwkv, m) {
     m.def("wkv_forward", wkv_forward);
     m.def("mm8_seq", mm8_seq);
     m.def("mm8_one", mm8_one);
-    m.def("gemm_fp16_cublas", gemm_fp16_cublas);
+    m.def("gemm_fp16_cublas", gemm_fp16_cublas_tensor);
     m.def("att_one", att_one);
+    m.def("att_one_v5", &att_one_v5);
     m.def("att_seq", att_seq);
     m.def("ffn_seq", ffn_seq);
     m.def("ffn_one", ffn_one);

backend-python/rwkv_pip/beta/model.py

@@ -3,7 +3,7 @@
 ########################################################################################################
 
 from typing import Optional
-import types, gc, os, time, re
+import types, gc, os, time, re, platform
 import torch
 from torch.nn import functional as F
 
@@ -91,8 +91,10 @@ if os.environ.get("RWKV_CUDA_ON") == "1":
                 f"{current_path}/cuda/att_one.cu",
                 f"{current_path}/cuda/att_seq.cu",
                 f"{current_path}/cuda/ffn.cu",
+                f"{current_path}/cuda/att_one_v5.cu",
             ],
             verbose=True,
+            extra_ldflags=["cublas.lib" if os.name == "nt" else ""],
             extra_cuda_cflags=[
                 "-t 4",
                 "-std=c++17",
@@ -149,26 +151,40 @@ if os.environ.get("RWKV_CUDA_ON") == "1":
         torch.ops.rwkv.mm8_one(N, M, x, w, mx, rx, my, ry, y)
         return y.to(dtype=x.dtype)
 
+else:
+    os.environ["RWKV_CUDA_ON"] = "0"
+
+if os.environ.get("RWKV_CUDA_ON") == "1":
+
     @MyStatic
     def gemm(a, b, output_dtype: Optional[torch.dtype] = None):
         if output_dtype is None:
             output_dtype = a.dtype
         if a.dtype == b.dtype == torch.float16 and a.device.type == "cuda":
-            assert len(b.shape) == 2
             if len(a.shape) == 1:
+                assert len(b.shape) == 2
                 c = torch.empty((b.shape[-1],), dtype=output_dtype, device=a.device)
                 a = a.unsqueeze(0)
             else:
-                c = torch.empty(
-                    (a.shape[0], b.shape[-1]), dtype=output_dtype, device=a.device
-                )
+                assert len(a.shape) == len(b.shape)
+                assert len(a.shape) == 2 or len(a.shape) == 3
+                # torch.empty((*a.shape[:-1], b.shape[-1])) doesn't work with jit
+                if len(a.shape) == 2:
+                    c = torch.empty(
+                        (a.shape[0], b.shape[-1]), dtype=output_dtype, device=a.device
+                    )
+                else:
+                    c = torch.empty(
+                        (a.shape[0], a.shape[1], b.shape[-1]),
+                        dtype=output_dtype,
+                        device=a.device,
+                    )
             torch.ops.rwkv.gemm_fp16_cublas(a, b, c)
             return c
         else:
             return (a @ b).to(output_dtype)
 
 else:
-    os.environ["RWKV_CUDA_ON"] = "0"
 
     def gemm(a, b, output_dtype: Optional[torch.dtype] = None):
         if output_dtype is None:
@@ -217,7 +233,7 @@ class RWKV(MyModule):
             )  # load model to CPU first
             # it is supported to load a pure meta-tensor state dict (e.g. for quick testing)
             for k, v in self.w.items():
-                if v.is_meta:
+                if isinstance(v, torch.Tensor) and v.is_meta:
                     # torch.zeros_like(v, device='cpu') doesn't produce an all-zero tensor
                     # if v is a meta tensor
                     self.w[k] = torch.zeros(v.shape, dtype=v.dtype, device="cpu")
@@ -247,9 +263,14 @@ class RWKV(MyModule):
             args.n_embd = w["emb.weight"].shape[1]
             args.n_layer = 0
             keys = list(w.keys())
+            self.version = 4
             for x in keys:
                 layer_id = int(x.split(".")[1]) if ("blocks." in x) else 0
                 args.n_layer = max(args.n_layer, layer_id + 1)
+                if "ln_x" in x:
+                    self.version = 5
+                if self.version == 5 and "att.time_decay" in x:
+                    args.n_head = w[x].shape[0]
 
             ####################### Compute strategy
 
@@ -352,6 +373,20 @@ class RWKV(MyModule):
                 del w["blocks.0.ln0.bias"]
 
             print_need_newline = False
+
+            REAL_TIME_FIRST = False
+            for x in list(w.keys()):
+                if ".time_faaaa" in x:
+                    REAL_TIME_FIRST = True
+            if REAL_TIME_FIRST:
+                w = {
+                    k.replace(".time_faaaa", ".time_first")
+                    if ".time_faaaa" in k
+                    else k: v
+                    for k, v in w.items()
+                }
+                self.w = w
+
             keys = list(w.keys())
             for x in keys:
                 w[x].requires_grad = False
@@ -382,8 +417,19 @@ class RWKV(MyModule):
                         w[x] = w[x].t()
 
                     if ".time_decay" in x:  # need fp32 for this
-                        w[x] = -torch.exp(w[x].float())
+                        if self.version == 4:
+                            w[x] = -torch.exp(w[x].float())
+                        elif self.version == 5:
+                            w[x] = torch.exp(-torch.exp(w[x].float())).reshape(-1, 1, 1)
                     elif ".time_first" in x:  # need fp32 for this
+                        if self.version == 4:
+                            w[x] = w[x].float()
+                        elif self.version == 5:
+                            if REAL_TIME_FIRST:
+                                w[x] = w[x].float().reshape(-1, 1, 1)
+                            else:
+                                w[x] = torch.exp(w[x].float()).reshape(-1, 1, 1)
+                    elif ".ln_x" in x:  # need fp32 for group_norm
                         w[x] = w[x].float()
                     else:
                         if (len(w[x].shape) == 2) and ("emb" not in x):
@@ -931,6 +977,147 @@ class RWKV(MyModule):
 
     ########################################################################################################
 
+    @MyFunction
+    def att_one_v5(
+        self,
+        x,
+        sx,
+        s,
+        ln_w,
+        ln_b,
+        lx_w,
+        lx_b,
+        k_mix,
+        v_mix,
+        r_mix,
+        t_decay,
+        t_first,
+        kw,
+        vw,
+        rw,
+        ow,
+        kmx,
+        krx,
+        kmy,
+        kry,
+        vmx,
+        vrx,
+        vmy,
+        vry,
+        rmx,
+        rrx,
+        rmy,
+        rry,
+        omx,
+        orx,
+        omy,
+        ory,
+    ):
+        xx = F.layer_norm(x, (x.shape[-1],), weight=ln_w, bias=ln_b)
+        kx = xx * k_mix + sx * (1 - k_mix)
+        vx = xx * v_mix + sx * (1 - v_mix)
+        rx = xx * r_mix + sx * (1 - r_mix)
+
+        H = t_decay.shape[0]
+        S = x.shape[-1] // H
+
+        r = gemm(rx, rw, output_dtype=torch.float32).view(H, 1, S)
+        k = gemm(kx, kw, output_dtype=torch.float32).view(H, S, 1)
+        v = gemm(vx, vw, output_dtype=torch.float32).view(H, 1, S)
+
+        a = gemm(k, v)
+        out = r @ (t_first * a + s)
+        s = a + t_decay * s
+
+        out = out.flatten()
+        out = F.group_norm(
+            out.unsqueeze(0), num_groups=H, weight=lx_w, bias=lx_b
+        ).squeeze(0)
+        out = out.to(dtype=x.dtype)
+        out = gemm(out, ow)
+
+        return x + out, xx, s
+
+    @MyFunction
+    def att_seq_v5(
+        self,
+        x,
+        sx,
+        s,
+        ln_w,
+        ln_b,
+        lx_w,
+        lx_b,
+        k_mix,
+        v_mix,
+        r_mix,
+        t_decay,
+        t_first,
+        kw,
+        vw,
+        rw,
+        ow,
+        kmx,
+        krx,
+        kmy,
+        kry,
+        vmx,
+        vrx,
+        vmy,
+        vry,
+        rmx,
+        rrx,
+        rmy,
+        rry,
+        omx,
+        orx,
+        omy,
+        ory,
+    ):
+        xx = F.layer_norm(x, (x.shape[-1],), weight=ln_w, bias=ln_b)
+        sx = torch.cat((sx.unsqueeze(0), xx[:-1, :]))
+        kx = xx * k_mix + sx * (1 - k_mix)
+        vx = xx * v_mix + sx * (1 - v_mix)
+        rx = xx * r_mix + sx * (1 - r_mix)
+
+        H = t_decay.shape[0]
+        S = x.shape[-1] // H
+        T = x.shape[0]
+
+        w = t_decay.reshape(-1, 1)
+        u = t_first.reshape(-1, 1)
+        ws = w.pow(T).reshape(H, 1, 1)
+        ind = torch.arange(T - 1, -1, -1, device=w.device).unsqueeze(0).repeat(H, 1)
+        w = w.repeat(1, T).pow(ind)
+        wk = w.reshape(H, 1, T)
+        wb = wk.transpose(-2, -1).flip(1)
+        w = torch.cat([w[:, 1:], u], dim=1)
+        w = F.pad(w, (0, T))
+        w = torch.tile(w, [T])
+        w = w[:, :-T].reshape(-1, T, 2 * T - 1)
+        w = w[:, :, T - 1 :].reshape(H, T, T)
+
+        r = gemm(rx, rw, output_dtype=torch.float32).view(T, H, S).transpose(0, 1)
+        k = (
+            gemm(kx, kw, output_dtype=torch.float32)
+            .view(T, H, S)
+            .transpose(0, 1)
+            .transpose(-2, -1)
+        )
+        v = gemm(vx, vw, output_dtype=torch.float32).view(T, H, S).transpose(0, 1)
+
+        out = ((r @ k) * w) @ v + (r @ s) * wb
+        s = ws * s + (k * wk) @ v
+
+        out = out.transpose(0, 1).contiguous().reshape(T, H * S)
+        out = F.group_norm(out, num_groups=H, weight=lx_w, bias=lx_b)
+        out = out.to(dtype=x.dtype)
+        out = gemm(out, ow)
+
+        return x + out, xx[-1, :], s
+
+    ########################################################################################################
+
     if os.environ["RWKV_CUDA_ON"] == "1":
 
         @MyFunction
@@ -1140,7 +1327,7 @@ class RWKV(MyModule):
             xx = torch.ops.rwkv.ffn_seq(
                 x, sx, ln_w, ln_b, k_mix, r_mix, kw, vw, rw, buf, x_plus_out
             )
-            return x_plus_out, xx[-1:]
+            return x_plus_out, xx[-1, :]
 
         @MyFunction
         def cuda_att_one_fp16(
@@ -1220,6 +1407,86 @@ class RWKV(MyModule):
             )
             return x_plus_out_t, xx, t1_t, t2_t, p_t
 
+        @MyFunction
+        def cuda_att_one_v5_fp16(
+            self,
+            x,
+            sx,
+            s,
+            ln_w,
+            ln_b,
+            lx_w,
+            lx_b,
+            k_mix,
+            v_mix,
+            r_mix,
+            t_decay,
+            t_first,
+            kw,
+            vw,
+            rw,
+            ow,
+            kmx,
+            krx,
+            kmy,
+            kry,
+            vmx,
+            vrx,
+            vmy,
+            vry,
+            rmx,
+            rrx,
+            rmy,
+            rry,
+            omx,
+            orx,
+            omy,
+            ory,
+        ):
+            kx = torch.empty_like(x)
+            vx = torch.empty_like(x)
+            rx = torch.empty_like(x)
+
+            H = t_decay.shape[0]
+            S = x.shape[-1] // H
+
+            r = torch.empty((H * S,), dtype=torch.float32, device=x.device)
+            k = torch.empty((H * S,), dtype=torch.float32, device=x.device)
+            v = torch.empty((H * S,), dtype=torch.float32, device=x.device)
+            s1 = torch.empty((H, S, S), dtype=torch.float32, device=x.device)
+            s2 = torch.empty((H, S, S), dtype=torch.float32, device=x.device)
+            x_plus_out = torch.empty_like(x)
+
+            xx = torch.ops.rwkv.att_one_v5(
+                x,
+                sx,
+                s,
+                ln_w,
+                ln_b,
+                lx_w,
+                lx_b,
+                k_mix,
+                v_mix,
+                r_mix,
+                kw,
+                kx,
+                vw,
+                vx,
+                rw,
+                rx,
+                ow,
+                t_first,
+                k,
+                t_decay,
+                v,
+                r,
+                s1,
+                x_plus_out,
+                s2,
+            )
+
+            return x_plus_out, xx, s2
+
         @MyFunction
         def cuda_ffn_one_fp16(
             self,
@@ -1265,34 +1532,63 @@ class RWKV(MyModule):
             args = self.args
 
             if state == None:
-                state = [None] * args.n_layer * 5
-                for i in range(
-                    args.n_layer
-                ):  # state: 0=att_xx 1=att_aa 2=att_bb 3=att_pp 4=ffn_xx
-                    dd = self.strategy[i]
-                    dev = dd.device
-                    atype = dd.atype
-                    state[i * 5 + 0] = torch.zeros(
-                        args.n_embd, dtype=atype, requires_grad=False, device=dev
-                    ).contiguous()
-                    state[i * 5 + 1] = torch.zeros(
-                        args.n_embd, dtype=torch.float, requires_grad=False, device=dev
-                    ).contiguous()
-                    state[i * 5 + 2] = torch.zeros(
-                        args.n_embd, dtype=torch.float, requires_grad=False, device=dev
-                    ).contiguous()
-                    state[i * 5 + 3] = (
-                        torch.zeros(
+                if self.version == 4:
+                    state = [None] * args.n_layer * 5
+                    for i in range(
+                        args.n_layer
+                    ):  # state: 0=att_xx 1=att_aa 2=att_bb 3=att_pp 4=ffn_xx
+                        dd = self.strategy[i]
+                        dev = dd.device
+                        atype = dd.atype
+                        state[i * 5 + 0] = torch.zeros(
+                            args.n_embd, dtype=atype, requires_grad=False, device=dev
+                        ).contiguous()
+                        state[i * 5 + 1] = torch.zeros(
                             args.n_embd,
                             dtype=torch.float,
                             requires_grad=False,
                             device=dev,
                         ).contiguous()
-                        - 1e30
-                    )
-                    state[i * 5 + 4] = torch.zeros(
-                        args.n_embd, dtype=atype, requires_grad=False, device=dev
-                    ).contiguous()
+                        state[i * 5 + 2] = torch.zeros(
+                            args.n_embd,
+                            dtype=torch.float,
+                            requires_grad=False,
+                            device=dev,
+                        ).contiguous()
+                        state[i * 5 + 3] = (
+                            torch.zeros(
+                                args.n_embd,
+                                dtype=torch.float,
+                                requires_grad=False,
+                                device=dev,
+                            ).contiguous()
+                            - 1e30
+                        )
+                        state[i * 5 + 4] = torch.zeros(
+                            args.n_embd, dtype=atype, requires_grad=False, device=dev
+                        ).contiguous()
+                elif self.version == 5:
+                    state = [None] * args.n_layer * 3
+                    for i in range(args.n_layer):  # state: 0=att_xx 1=att_kv 2=ffn_xx
+                        dd = self.strategy[i]
+                        dev = dd.device
+                        atype = dd.atype
+                        state[i * 3 + 0] = torch.zeros(
+                            args.n_embd, dtype=atype, requires_grad=False, device=dev
+                        ).contiguous()
+                        state[i * 3 + 1] = torch.zeros(
+                            (
+                                args.n_head,
+                                args.n_embd // args.n_head,
+                                args.n_embd // args.n_head,
+                            ),
+                            dtype=torch.float,
+                            requires_grad=False,
+                            device=dev,
+                        ).contiguous()
+                        state[i * 3 + 2] = torch.zeros(
+                            args.n_embd, dtype=atype, requires_grad=False, device=dev
+                        ).contiguous()
 
             seq_mode = len(tokens) > 1
 
@@ -1317,9 +1613,13 @@ class RWKV(MyModule):
                             ATT = self.cuda_att_seq_i8
                         else:
                             ATT = self.cuda_att_seq_naive
+                    if self.version == 5:
+                        ATT = self.att_seq_v5
                 else:
                     ATT = self.att_one if wtype != torch.uint8 else self.att_one_i8
                     FFN = self.ffn_one if wtype != torch.uint8 else self.ffn_one_i8
+                    if self.version == 5:
+                        ATT = self.att_one_v5
                     if (
                         "cuda" in str(dev)
                         and os.environ["RWKV_CUDA_ON"] == "1"
@@ -1327,6 +1627,8 @@ class RWKV(MyModule):
                     ):
                         ATT = self.cuda_att_one_fp16
                         FFN = self.cuda_ffn_one_fp16
+                        if self.version == 5:
+                            ATT = self.cuda_att_one_v5_fp16
 
                 x = x.to(dtype=atype, device=dev)
 
@@ -1355,46 +1657,82 @@ class RWKV(MyModule):
                 orx = w[f"{att}output.weight_rx"] if wtype == torch.uint8 else x
                 omy = w[f"{att}output.weight_my"] if wtype == torch.uint8 else x
                 ory = w[f"{att}output.weight_ry"] if wtype == torch.uint8 else x
-                (
-                    x,
-                    state[i * 5 + 0],
-                    state[i * 5 + 1],
-                    state[i * 5 + 2],
-                    state[i * 5 + 3],
-                ) = ATT(
-                    x,
-                    state[i * 5 + 0],
-                    state[i * 5 + 1],
-                    state[i * 5 + 2],
-                    state[i * 5 + 3],
-                    w[f"{bbb}ln1.weight"],
-                    w[f"{bbb}ln1.bias"],
-                    w[f"{att}time_mix_k"],
-                    w[f"{att}time_mix_v"],
-                    w[f"{att}time_mix_r"],
-                    w[f"{att}time_decay"],
-                    w[f"{att}time_first"],
-                    kw,
-                    vw,
-                    rw,
-                    ow,
-                    kmx,
-                    krx,
-                    kmy,
-                    kry,
-                    vmx,
-                    vrx,
-                    vmy,
-                    vry,
-                    rmx,
-                    rrx,
-                    rmy,
-                    rry,
-                    omx,
-                    orx,
-                    omy,
-                    ory,
-                )
+                if self.version == 4:
+                    (
+                        x,
+                        state[i * 5 + 0],
+                        state[i * 5 + 1],
+                        state[i * 5 + 2],
+                        state[i * 5 + 3],
+                    ) = ATT(
+                        x,
+                        state[i * 5 + 0],
+                        state[i * 5 + 1],
+                        state[i * 5 + 2],
+                        state[i * 5 + 3],
+                        w[f"{bbb}ln1.weight"],
+                        w[f"{bbb}ln1.bias"],
+                        w[f"{att}time_mix_k"],
+                        w[f"{att}time_mix_v"],
+                        w[f"{att}time_mix_r"],
+                        w[f"{att}time_decay"],
+                        w[f"{att}time_first"],
+                        kw,
+                        vw,
+                        rw,
+                        ow,
+                        kmx,
+                        krx,
+                        kmy,
+                        kry,
+                        vmx,
+                        vrx,
+                        vmy,
+                        vry,
+                        rmx,
+                        rrx,
+                        rmy,
+                        rry,
+                        omx,
+                        orx,
+                        omy,
+                        ory,
+                    )
+                elif self.version == 5:
+                    x, state[i * 3 + 0], state[i * 3 + 1] = ATT(
+                        x,
+                        state[i * 3 + 0],
+                        state[i * 3 + 1],
+                        w[f"{bbb}ln1.weight"],
+                        w[f"{bbb}ln1.bias"],
+                        w[f"{att}ln_x.weight"],
+                        w[f"{att}ln_x.bias"],
+                        w[f"{att}time_mix_k"],
+                        w[f"{att}time_mix_v"],
+                        w[f"{att}time_mix_r"],
+                        w[f"{att}time_decay"],
+                        w[f"{att}time_first"],
+                        kw,
+                        vw,
+                        rw,
+                        ow,
+                        kmx,
+                        krx,
+                        kmy,
+                        kry,
+                        vmx,
+                        vrx,
+                        vmy,
+                        vry,
+                        rmx,
+                        rrx,
+                        rmy,
+                        rry,
+                        omx,
+                        orx,
+                        omy,
+                        ory,
+                    )
                 if dd.stream:
                     del kw, vw, rw, ow
 
@@ -1417,9 +1755,13 @@ class RWKV(MyModule):
                 rrx = w[f"{ffn}receptance.weight_rx"] if wtype == torch.uint8 else x
                 rmy = w[f"{ffn}receptance.weight_my"] if wtype == torch.uint8 else x
                 rry = w[f"{ffn}receptance.weight_ry"] if wtype == torch.uint8 else x
-                x, state[i * 5 + 4] = FFN(
+                if self.version == 4:
+                    offset = i * 5 + 4
+                elif self.version == 5:
+                    offset = i * 3 + 2
+                x, state[offset] = FFN(
                     x,
-                    state[i * 5 + 4],
+                    state[offset],
                     w[f"{bbb}ln2.weight"],
                     w[f"{bbb}ln2.bias"],
                     w[f"{ffn}time_mix_k"],

backend-python/rwkv_pip/cuda/gemm_fp16_cublas.cpp

@@ -0,0 +1,75 @@
+#include <cublas_v2.h>
+#include <cuda.h>
+#include <cuda_fp16.h>
+#include <cuda_runtime.h>
+#include <torch/extension.h>
+#include <c10/cuda/CUDAGuard.h>
+#include <ATen/cuda/CUDAContext.h>
+
+#define CUBLAS_CHECK(condition)                                                \
+  for (cublasStatus_t _cublas_check_status = (condition);                      \
+       _cublas_check_status != CUBLAS_STATUS_SUCCESS;)                         \
+    throw std::runtime_error("cuBLAS error " +                                 \
+                             std::to_string(_cublas_check_status) + " at " +   \
+                             std::to_string(__LINE__));
+
+#define CUDA_CHECK(condition)                                                  \
+  for (cudaError_t _cuda_check_status = (condition);                           \
+       _cuda_check_status != cudaSuccess;)                                     \
+    throw std::runtime_error(                                                  \
+        "CUDA error " + std::string(cudaGetErrorString(_cuda_check_status)) +  \
+        " at " + std::to_string(__LINE__));
+
+/*
+  NOTE: blas gemm is column-major by default, but we need row-major output.
+  The data of row-major, transposed matrix is exactly the same as the
+  column-major, non-transposed matrix, and C = A * B ---> C^T = B^T * A^T
+ */
+void gemm_fp16_cublas(torch::Tensor a, torch::Tensor b, torch::Tensor c) {
+  const at::cuda::OptionalCUDAGuard device_guard(device_of(a));
+  const auto cuda_data_type = CUDA_R_16F;
+  const auto cuda_c_data_type =
+      c.dtype() == torch::kFloat32 ? CUDA_R_32F : CUDA_R_16F;
+  const auto compute_type = CUDA_R_32F;
+  const float sp_alpha = 1.f;
+  // swap a and b, and use CUBLAS_OP_N. see the notes above
+  std::swap(a, b);
+  const cublasOperation_t cublas_trans_a = CUBLAS_OP_N;
+  const cublasOperation_t cublas_trans_b = CUBLAS_OP_N;
+  // m = (B^T).size(0) = B.size(1), and = A.size(1) after swap,
+  // negative axis is used because of the existence of batch matmul.
+  const int m = a.size(-1);
+  const int k = a.size(-2);
+  const int n = b.size(-2);
+  const int cublas_lda = m;
+  const int cublas_ldb = k;
+  const int cublas_ldc = m;
+  cublasHandle_t cublas_handle = at::cuda::getCurrentCUDABlasHandle();
+
+#if CUDA_VERSION >= 11000
+  cublasGemmAlgo_t algo = CUBLAS_GEMM_DEFAULT;
+#else
+  cublasGemmAlgo_t algo = CUBLAS_GEMM_DFALT_TENSOR_OP;
+#endif
+  const float sp_beta = 0.f;
+  if (a.sizes().size() == 2 && b.sizes().size() == 2) {
+    CUBLAS_CHECK(cublasGemmEx(
+        cublas_handle, cublas_trans_a, cublas_trans_b, m, n, k, &sp_alpha,
+        a.data_ptr(), cuda_data_type, cublas_lda, b.data_ptr(), cuda_data_type,
+        cublas_ldb, &sp_beta, c.data_ptr(), cuda_c_data_type, cublas_ldc,
+        compute_type, algo));
+  } else {
+    // batch matmul
+    assert(a.sizes().size() == 3 && b.sizes().size() == 3);
+
+    const long long int cublas_stride_a = m * k;
+    const long long int cublas_stride_b = k * n;
+    const long long int cublas_stride_c = m * n;
+    CUBLAS_CHECK(cublasGemmStridedBatchedEx(
+        cublas_handle, cublas_trans_a, cublas_trans_b, m,
+        n, k, &sp_alpha, a.data_ptr(), cuda_data_type, cublas_lda,
+        cublas_stride_a, b.data_ptr(), cuda_data_type, cublas_ldb, cublas_stride_b,
+        &sp_beta, c.data_ptr(), cuda_c_data_type, cublas_ldc, cublas_stride_c,
+        a.size(0), compute_type, algo));
+  }
+}

backend-python/rwkv_pip/cuda/operators.cu

@@ -0,0 +1,246 @@
+#include <stdio.h>
+#include <assert.h>
+#include "ATen/ATen.h"
+#include <cuda_fp16.h>
+#define MIN_VALUE (-1e38)
+typedef at::Half fp16;
+__half *cast(fp16 *ptr) {
+    return reinterpret_cast<__half *>(ptr);
+}
+
+template <typename F>
+__global__ void kernel_wkv_forward(const int B, const int T, const int C,
+                               const float *__restrict__ const _w, const float *__restrict__ const _u, const F *__restrict__ const _k, const F *__restrict__ const _v,
+                               F *__restrict__ const _y, float *__restrict__ const _aa, float *__restrict__ const _bb, float *__restrict__ const _pp) {
+    const int idx = blockIdx.x * blockDim.x + threadIdx.x;
+    const int _b = idx / C;
+    const int _c = idx % C;
+    const int _offset = _b * T * C + _c;
+    const int _state_offset = _b * C + _c;
+
+    float u = _u[_c];
+    float w = _w[_c];
+    const F *__restrict__ const k = _k + _offset;
+    const F *__restrict__ const v = _v + _offset;
+    F *__restrict__ const y = _y + _offset;
+
+    float aa = _aa[_state_offset];
+    float bb = _bb[_state_offset];
+    float pp = _pp[_state_offset];
+    for (int i = 0; i < T; i++) {
+        const int ii = i * C;
+        const float kk = float(k[ii]);
+        const float vv = float(v[ii]);
+        float ww = u + kk;
+        float p = max(pp, ww);
+        float e1 = exp(pp - p);
+        float e2 = exp(ww - p);
+        y[ii] = F((e1 * aa + e2 * vv) / (e1 * bb + e2));
+        ww = w + pp;
+        p = max(ww, kk);
+        e1 = exp(ww - p);
+        e2 = exp(kk - p);
+        aa = e1 * aa + e2 * vv;
+        bb = e1 * bb + e2;
+        pp = p;
+    }
+    _aa[_state_offset] = aa;
+    _bb[_state_offset] = bb;
+    _pp[_state_offset] = pp;
+}
+
+template <typename F>
+void cuda_wkv_forward(int B, int T, int C, float *w, float *u, F *k, F *v, F *y, float *aa, float *bb, float *pp) {
+    dim3 threadsPerBlock( min(C, 32) );
+    assert(B * C % threadsPerBlock.x == 0);
+    dim3 numBlocks(B * C / threadsPerBlock.x);
+    kernel_wkv_forward<<<numBlocks, threadsPerBlock>>>(B, T, C, w, u, k, v, y, aa, bb, pp);
+}
+
+template void cuda_wkv_forward<fp16>(
+    int B, int T, int C,
+    float *w, float *u, fp16 *k, fp16 *v, fp16 *y,
+    float *aa, float *bb, float *pp);
+template void cuda_wkv_forward<float>(
+    int B, int T, int C,
+    float *w, float *u, float *k, float *v, float *y,
+    float *aa, float *bb, float *pp);
+
+__global__ void kernel_mm_seq_fp32i8(
+    const int B, const int N, const int M,
+    const float *__restrict__ const x, const int x_stride,
+    const uint8_t *__restrict__ const w, const int w_stride,
+    const float *__restrict__ const mx,
+    const float *__restrict__ const rx,
+    const float *__restrict__ const my,
+    const float *__restrict__ const ry,
+    float *__restrict__ const y, const int y_stride) {
+
+    const int i = blockIdx.x * blockDim.x + threadIdx.x;
+    const int k = blockIdx.y * blockDim.y + threadIdx.y;
+
+    if (i < B && k < M) {
+        float y_local = 0;
+        for (int j = 0; j < N; ++j) {
+            y_local += x[i * x_stride + j] * (
+                (float(w[j * w_stride + k]) + 0.5f)
+                * rx[k] * ry[j] + mx[k] + my[j]
+            );
+        }
+        y[i * y_stride + k] = y_local;
+    }
+}
+
+template <typename F>
+void cuda_mm8_seq(int B, int N, int M,
+                  F *x, int x_stride,
+                  uint8_t *w, int w_stride,
+                  F *mx, F *rx,
+                  F *my, F *ry,
+                  F *y, int y_stride);
+
+template <>
+void cuda_mm8_seq<float>(int B, int N, int M,
+                         float *x, int x_stride,
+                         uint8_t *w, int w_stride,
+                         float *mx, float *rx,
+                         float *my, float *ry,
+                         float *y, int y_stride) {
+    dim3 blockSize(1, 128);
+    dim3 gridSize((B + blockSize.x - 1) / blockSize.x, (M + blockSize.y - 1) / blockSize.y);
+    kernel_mm_seq_fp32i8<<<gridSize, blockSize>>>(
+        B, N, M, x, x_stride, w, w_stride,
+        mx, rx, my, ry, y, y_stride);
+}
+
+__global__ void kernel_mm_seq_fp16i8(
+    const int B, const int N, const int M,
+    const __half *__restrict__ const x, const int x_stride,
+    const uint8_t *__restrict__ const w, const int w_stride,
+    const __half *__restrict__ const mx,
+    const __half *__restrict__ const rx,
+    const __half *__restrict__ const my,
+    const __half *__restrict__ const ry,
+    __half *__restrict__ const y, const int y_stride) {
+
+    const int i = blockIdx.x * blockDim.x + threadIdx.x;
+    const int k = blockIdx.y * blockDim.y + threadIdx.y;
+
+    if (i < B && k < M) {
+        float y_local = 0;
+        for (int j = 0; j < N; ++j) {
+            y_local += __half2float(x[i * x_stride + j]) * (
+                (float(w[j * w_stride + k]) + 0.5f)
+                * __half2float(rx[k]) * __half2float(ry[j])
+                + __half2float(mx[k]) + __half2float(my[j])
+            );
+        }
+        y[i * y_stride + k] = __float2half(y_local);
+    }
+}
+
+template <>
+void cuda_mm8_seq<fp16>(int B, int N, int M,
+                        fp16 *x, int x_stride,
+                        uint8_t *w, int w_stride,
+                        fp16 *mx, fp16 *rx,
+                        fp16 *my, fp16 *ry,
+                        fp16 *y, int y_stride) {
+    dim3 blockSize(1, 128);
+    dim3 gridSize((B + blockSize.x - 1) / blockSize.x, (M + blockSize.y - 1) / blockSize.y);
+    kernel_mm_seq_fp16i8<<<gridSize, blockSize>>>(
+        B, N, M, cast(x), x_stride, w, w_stride,
+        cast(mx), cast(rx), cast(my), cast(ry), cast(y), y_stride);
+}
+
+#define MM8_ONE_JSPLIT 24
+#define MM8_ONE_TILE 1024
+
+__global__ void kernel_mm_one_fp32i8(
+    const int N, const int M,
+    const float *__restrict__ const x,
+    const uint8_t *__restrict__ const w, const int w_stride,
+    const float *__restrict__ const mx,
+    const float *__restrict__ const rx,
+    const float *__restrict__ const my,
+    const float *__restrict__ const ry,
+    float *__restrict__ const y) {
+
+    const int k = blockIdx.y * blockDim.y + threadIdx.y;
+    const int j0 = min(N, blockIdx.x * ((N + MM8_ONE_JSPLIT - 1) / MM8_ONE_JSPLIT));
+    const int j1 = min(N, (blockIdx.x + 1) * ((N + MM8_ONE_JSPLIT - 1) / MM8_ONE_JSPLIT));
+
+    if (k < M) {
+        float y_local = 0;
+        for (int j = j0; j < j1; ++j) {
+            y_local += x[j] * (
+                (float(w[j * w_stride + k]) + 0.5f)
+                * rx[k] * ry[j] + mx[k] + my[j]
+            );
+        }
+        atomicAdd(&y[k], y_local);
+    }
+}
+
+template <typename F>
+void cuda_mm8_one(int N, int M,
+                  F *x,
+                  uint8_t *w, int w_stride,
+                  F *mx, F *rx,
+                  F *my, F *ry,
+                  float *y);
+
+template <>
+void cuda_mm8_one<float>(int N, int M,
+                        float *x,
+                        uint8_t *w, int w_stride,
+                        float *mx, float *rx,
+                        float *my, float *ry,
+                        float *y) {
+    dim3 blockSize(1, MM8_ONE_TILE);
+    dim3 gridSize(MM8_ONE_JSPLIT, (M + blockSize.y - 1) / blockSize.y);
+    kernel_mm_one_fp32i8<<<gridSize, blockSize>>>(
+        N, M, x, w, w_stride,
+        mx, rx, my, ry, y);
+}
+
+__global__ void kernel_mm_one_fp16i8(
+    const int N, const int M,
+    const __half *__restrict__ const x,
+    const uint8_t *__restrict__ const w, const int w_stride,
+    const __half *__restrict__ const mx,
+    const __half *__restrict__ const rx,
+    const __half *__restrict__ const my,
+    const __half *__restrict__ const ry,
+    float *__restrict__ const y) {
+
+    const int k = blockIdx.y * blockDim.y + threadIdx.y;
+    const int j0 = min(N, blockIdx.x * ((N + MM8_ONE_JSPLIT - 1) / MM8_ONE_JSPLIT));
+    const int j1 = min(N, (blockIdx.x + 1) * ((N + MM8_ONE_JSPLIT - 1) / MM8_ONE_JSPLIT));
+
+    if (k < M) {
+        float y_local = 0;
+        for (int j = j0; j < j1; ++j) {
+            y_local += __half2float(x[j]) * (
+                (float(w[j * w_stride + k]) + 0.5f)
+                * __half2float(rx[k]) * __half2float(ry[j])
+                + __half2float(mx[k]) + __half2float(my[j])
+            );
+        }
+        atomicAdd(&y[k], y_local);
+    }
+}
+
+template <>
+void cuda_mm8_one<fp16>(int N, int M,
+                        fp16 *x,
+                        uint8_t *w, int w_stride,
+                        fp16 *mx, fp16 *rx,
+                        fp16 *my, fp16 *ry,
+                        float *y) {
+    dim3 blockSize(1, MM8_ONE_TILE);
+    dim3 gridSize(MM8_ONE_JSPLIT, (M + blockSize.y - 1) / blockSize.y);
+    kernel_mm_one_fp16i8<<<gridSize, blockSize>>>(
+        N, M, cast(x), w, w_stride,
+        cast(mx), cast(rx), cast(my), cast(ry), y);
+}

backend-python/rwkv_pip/cuda/rwkv5.cu

@@ -0,0 +1,88 @@
+#include <stdio.h>
+#include <assert.h>
+#include "ATen/ATen.h"
+typedef at::BFloat16 bf16;
+typedef at::Half fp16;
+typedef float fp32;
+
+template <typename F>
+__global__ void kernel_forward(const int B, const int T, const int C, const int H, float *__restrict__ _state,
+                               const F *__restrict__ const _r, const F *__restrict__ const _k, const F *__restrict__ const _v, const float *__restrict__ _w, const F *__restrict__ _u,
+                               F *__restrict__ const _y)
+{
+    const int b = blockIdx.x / H;
+    const int h = blockIdx.x % H;
+    const int i = threadIdx.x;
+    _w += h*_N_;
+    _u += h*_N_;
+    _state += h*_N_*_N_ + i*_N_; // wrong if B > 1 !!!
+
+    __shared__ float r[_N_], k[_N_], u[_N_], w[_N_];
+    
+    float state[_N_];
+    #pragma unroll
+    for (int j = 0; j < _N_; j++)
+        state[j] = _state[j];
+    
+    __syncthreads();
+    u[i] = float(_u[i]);
+    w[i] = _w[i];
+    __syncthreads();
+
+    for (int t = b*T*C + h*_N_ + i; t < (b+1)*T*C + h*_N_ + i; t += C)
+    {
+        __syncthreads();
+        r[i] = float(_r[t]);
+        k[i] = float(_k[t]);
+        __syncthreads();
+
+        const float v = float(_v[t]);
+        float y = 0;
+
+        #pragma unroll
+        for (int j = 0; j < _N_; j+=4)
+        {
+            const float4& r_ = (float4&)(r[j]);
+            const float4& k_ = (float4&)(k[j]);
+            const float4& w_ = (float4&)(w[j]);
+            const float4& u_ = (float4&)(u[j]);
+            float4& s = (float4&)(state[j]);
+            float4 x;
+
+            x.x = k_.x * v;
+            x.y = k_.y * v;
+            x.z = k_.z * v;
+            x.w = k_.w * v;
+
+            y += r_.x * (u_.x * x.x + s.x);
+            y += r_.y * (u_.y * x.y + s.y);
+            y += r_.z * (u_.z * x.z + s.z);
+            y += r_.w * (u_.w * x.w + s.w);
+
+            s.x = s.x * w_.x + x.x;
+            s.y = s.y * w_.y + x.y;
+            s.z = s.z * w_.z + x.z;
+            s.w = s.w * w_.w + x.w;
+        }
+        _y[t] = F(y);
+    }
+    #pragma unroll
+    for (int j = 0; j < _N_; j++)
+        _state[j] = state[j];
+}
+
+void cuda_forward_bf16(int B, int T, int C, int H, float *state, bf16 *r, bf16 *k, bf16 *v, float *w, bf16 *u, bf16 *y)
+{
+    assert(H*_N_ == C);
+    kernel_forward<<<dim3(B * H), dim3(_N_)>>>(B, T, C, H, state, r, k, v, w, u, y);
+}
+void cuda_forward_fp16(int B, int T, int C, int H, float *state, fp16 *r, fp16 *k, fp16 *v, float *w, fp16 *u, fp16 *y)
+{
+    assert(H*_N_ == C);
+    kernel_forward<<<dim3(B * H), dim3(_N_)>>>(B, T, C, H, state, r, k, v, w, u, y);
+}
+void cuda_forward_fp32(int B, int T, int C, int H, float *state, fp32 *r, fp32 *k, fp32 *v, float *w, fp32 *u, fp32 *y)
+{
+    assert(H*_N_ == C);
+    kernel_forward<<<dim3(B * H), dim3(_N_)>>>(B, T, C, H, state, r, k, v, w, u, y);
+}

backend-python/rwkv_pip/cuda/rwkv5_op.cpp

@@ -0,0 +1,34 @@
+#include <torch/extension.h>
+#include "ATen/ATen.h"
+#include <c10/cuda/CUDAGuard.h>
+typedef at::BFloat16 bf16;
+typedef at::Half fp16;
+typedef float fp32;
+
+void cuda_forward_bf16(int B, int T, int C, int H, float *state, bf16 *r, bf16 *k, bf16 *v, float *w, bf16 *u, bf16 *y);
+void cuda_forward_fp16(int B, int T, int C, int H, float *state, fp16 *r, fp16 *k, fp16 *v, float *w, fp16 *u, fp16 *y);
+void cuda_forward_fp32(int B, int T, int C, int H, float *state, fp32 *r, fp32 *k, fp32 *v, float *w, fp32 *u, fp32 *y);
+
+void forward_bf16(int64_t B, int64_t T, int64_t C, int64_t H, torch::Tensor &state, torch::Tensor &r, torch::Tensor &k, torch::Tensor &v, torch::Tensor &w, torch::Tensor &u, torch::Tensor &y) {
+    const at::cuda::OptionalCUDAGuard device_guard(device_of(state));
+    cuda_forward_bf16(B, T, C, H, state.data_ptr<float>(), r.data_ptr<bf16>(), k.data_ptr<bf16>(), v.data_ptr<bf16>(), w.data_ptr<float>(), u.data_ptr<bf16>(), y.data_ptr<bf16>());
+}
+void forward_fp16(int64_t B, int64_t T, int64_t C, int64_t H, torch::Tensor &state, torch::Tensor &r, torch::Tensor &k, torch::Tensor &v, torch::Tensor &w, torch::Tensor &u, torch::Tensor &y) {
+    const at::cuda::OptionalCUDAGuard device_guard(device_of(state));
+    cuda_forward_fp16(B, T, C, H, state.data_ptr<float>(), r.data_ptr<fp16>(), k.data_ptr<fp16>(), v.data_ptr<fp16>(), w.data_ptr<float>(), u.data_ptr<fp16>(), y.data_ptr<fp16>());
+}
+void forward_fp32(int64_t B, int64_t T, int64_t C, int64_t H, torch::Tensor &state, torch::Tensor &r, torch::Tensor &k, torch::Tensor &v, torch::Tensor &w, torch::Tensor &u, torch::Tensor &y) {
+    const at::cuda::OptionalCUDAGuard device_guard(device_of(state));
+    cuda_forward_fp32(B, T, C, H, state.data_ptr<float>(), r.data_ptr<fp32>(), k.data_ptr<fp32>(), v.data_ptr<fp32>(), w.data_ptr<float>(), u.data_ptr<fp32>(), y.data_ptr<fp32>());
+}
+
+PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
+    m.def("forward_bf16", &forward_bf16, "rwkv5 forward_bf16");
+    m.def("forward_fp16", &forward_fp16, "rwkv5 forward_fp16");
+    m.def("forward_fp32", &forward_fp32, "rwkv5 forward_fp32");
+}
+TORCH_LIBRARY(rwkv5, m) {
+    m.def("forward_bf16", forward_bf16);
+    m.def("forward_fp16", forward_fp16);
+    m.def("forward_fp32", forward_fp32);
+}

backend-python/rwkv_pip/cuda/wrapper.cpp

@@ -0,0 +1,141 @@
+#include <torch/extension.h>
+#include "ATen/ATen.h"
+#include <iostream>
+#include <c10/cuda/CUDAGuard.h>
+
+typedef at::Half fp16;
+
+template <typename F>
+void cuda_wkv_forward(int B, int T, int C,
+                      float *w, float *u, F *k, F *v, F *y,
+                      float *aa, float *bb, float *pp);
+template <typename F>
+void cuda_mm8_seq(int B, int N, int M,
+                  F *x, int x_stride,
+                  uint8_t *w, int w_stride,
+                  F *mx, F *rx,
+                  F *my, F *ry,
+                  F *y, int y_stride);
+template <typename F>
+void cuda_mm8_one(int N, int M,
+                  F *x,
+                  uint8_t *w, int w_stride,
+                  F *mx, F *rx,
+                  F *my, F *ry,
+                  float *y);
+
+void wkv_forward(int64_t B, int64_t T, int64_t C,
+                 torch::Tensor &w, torch::Tensor &u,
+                 torch::Tensor &k, torch::Tensor &v, torch::Tensor &y,
+                 torch::Tensor &aa, torch::Tensor &bb, torch::Tensor &pp) {
+    const at::cuda::OptionalCUDAGuard device_guard(device_of(w));
+    switch (k.scalar_type()) {
+    case c10::ScalarType::Half:
+        cuda_wkv_forward(B, T, C,
+                         w.data_ptr<float>(), u.data_ptr<float>(),
+                         k.data_ptr<fp16>(), v.data_ptr<fp16>(), y.data_ptr<fp16>(),
+                         aa.data_ptr<float>(), bb.data_ptr<float>(), pp.data_ptr<float>());
+        break;
+    case c10::ScalarType::Float:
+        cuda_wkv_forward(B, T, C,
+                         w.data_ptr<float>(), u.data_ptr<float>(),
+                         k.data_ptr<float>(), v.data_ptr<float>(), y.data_ptr<float>(),
+                         aa.data_ptr<float>(), bb.data_ptr<float>(), pp.data_ptr<float>());
+        break;
+    default:
+        assert(false && "Only FP16 and FP32 are currently supported");
+    }
+}
+
+void mm8_seq(int64_t B, int64_t N, int64_t M,
+             torch::Tensor &x, torch::Tensor &w,
+             torch::Tensor &mx, torch::Tensor &rx,
+             torch::Tensor &my, torch::Tensor &ry,
+             torch::Tensor &y) {
+    assert(x.stride(1) == 1);
+    assert(w.stride(1) == 1);
+    assert(mx.stride(0) == 1 && rx.stride(0) == 1);
+    assert(my.stride(0) == 1 && ry.stride(0) == 1);
+    assert(y.stride(1) == 1);
+    const at::cuda::OptionalCUDAGuard device_guard(device_of(w));
+    switch (x.scalar_type()) {
+    case c10::ScalarType::Half:
+        cuda_mm8_seq(
+            B, N, M,
+            x.data_ptr<fp16>(), x.stride(0),
+            w.data_ptr<uint8_t>(), w.stride(0),
+            mx.data_ptr<fp16>(), rx.data_ptr<fp16>(),
+            my.data_ptr<fp16>(), ry.data_ptr<fp16>(),
+            y.data_ptr<fp16>(), y.stride(0));
+        break;
+    case c10::ScalarType::Float:
+        cuda_mm8_seq(
+            B, N, M,
+            x.data_ptr<float>(), x.stride(0),
+            w.data_ptr<uint8_t>(), w.stride(0),
+            mx.data_ptr<float>(), rx.data_ptr<float>(),
+            my.data_ptr<float>(), ry.data_ptr<float>(),
+            y.data_ptr<float>(), y.stride(0));
+        break;
+    default:
+        assert(false && "Only FP16 and FP32 are currently supported");
+    }
+}
+void mm8_one(int64_t N, int64_t M,
+             torch::Tensor &x, torch::Tensor &w,
+             torch::Tensor &mx, torch::Tensor &rx,
+             torch::Tensor &my, torch::Tensor &ry,
+             torch::Tensor &y) {
+    assert(x.stride(0) == 1);
+    assert(w.stride(1) == 1);
+    assert(mx.stride(0) == 1 && rx.stride(0) == 1);
+    assert(my.stride(0) == 1 && ry.stride(0) == 1);
+    assert(y.stride(0) == 1);
+    const at::cuda::OptionalCUDAGuard device_guard(device_of(w));
+    switch (x.scalar_type()) {
+    case c10::ScalarType::Half:
+        cuda_mm8_one(
+            N, M,
+            x.data_ptr<fp16>(),
+            w.data_ptr<uint8_t>(), w.stride(0),
+            mx.data_ptr<fp16>(), rx.data_ptr<fp16>(),
+            my.data_ptr<fp16>(), ry.data_ptr<fp16>(),
+            y.data_ptr<float>());
+        break;
+    case c10::ScalarType::Float:
+        cuda_mm8_one(
+            N, M,
+            x.data_ptr<float>(),
+            w.data_ptr<uint8_t>(), w.stride(0),
+            mx.data_ptr<float>(), rx.data_ptr<float>(),
+            my.data_ptr<float>(), ry.data_ptr<float>(),
+            y.data_ptr<float>());
+        break;
+    default:
+        assert(false && "Only FP16 and FP32 are currently supported");
+    }
+}
+
+using torch::Tensor;
+
+#ifndef DISABLE_CUBLAS_GEMM
+void gemm_fp16_cublas(Tensor a, Tensor b, Tensor c);
+#endif
+
+PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
+    m.def("wkv_forward", &wkv_forward, "wkv forward");
+    m.def("mm8_seq", &mm8_seq, "mm8 seq");
+    m.def("mm8_one", &mm8_one, "mm8 one");
+#ifndef DISABLE_CUBLAS_GEMM
+    m.def("gemm_fp16_cublas", &gemm_fp16_cublas, "gemv fp16 cublas");
+#endif
+}
+
+TORCH_LIBRARY(rwkv, m) {
+    m.def("wkv_forward", wkv_forward);
+    m.def("mm8_seq", mm8_seq);
+    m.def("mm8_one", mm8_one);
+#ifndef DISABLE_CUBLAS_GEMM
+    m.def("gemm_fp16_cublas", gemm_fp16_cublas);
+#endif
+}

backend-python/rwkv_pip/utils.py

@@ -16,6 +16,7 @@ class PIPELINE_ARGS:
         top_k=0,
         alpha_frequency=0.2,
         alpha_presence=0.2,
+        alpha_decay=0.996,
         token_ban=[],
         token_stop=[],
         chunk_len=256,
@@ -25,6 +26,7 @@ class PIPELINE_ARGS:
         self.top_k = top_k
         self.alpha_frequency = alpha_frequency  # Frequency Penalty (as in GPT-3)
         self.alpha_presence = alpha_presence  # Presence Penalty (as in GPT-3)
+        self.alpha_decay = alpha_decay  # gradually decay the penalty
         self.token_ban = token_ban  # ban the generation of some tokens
         self.token_stop = token_stop  # stop generation whenever you see any token here
         self.chunk_len = (
@@ -33,7 +35,7 @@ class PIPELINE_ARGS:
 
 
 class PIPELINE:
-    def __init__(self, model, WORD_NAME):
+    def __init__(self, model, WORD_NAME: str):
         self.model = model
         if WORD_NAME == "cl100k_base":
             import tiktoken
@@ -47,9 +49,15 @@ class PIPELINE:
                 os.path.dirname(os.path.abspath(__file__)) + "/rwkv_vocab_v20230424.txt"
             )
         else:
-            from tokenizers import Tokenizer
+            if WORD_NAME.endswith(".txt"):
+                sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+                from rwkv_tokenizer import TRIE_TOKENIZER
 
-            self.tokenizer = Tokenizer.from_file(WORD_NAME)
+                self.tokenizer = TRIE_TOKENIZER(WORD_NAME)
+            else:
+                from tokenizers import Tokenizer
+
+                self.tokenizer = Tokenizer.from_file(WORD_NAME)
 
     def refine_context(self, context):
         context = context.strip().split("\n")
@@ -73,12 +81,13 @@ class PIPELINE:
     def sample_logits(self, logits, temperature=1.0, top_p=0.85, top_k=0):
         probs = F.softmax(logits.float(), dim=-1)
         top_k = int(top_k)
-        if probs.device == torch.device("cpu"):
-            probs = probs.numpy()
+        # 'privateuseone' is the type of custom devices like `torch_directml.device()`
+        if probs.device.type in ["cpu", "privateuseone"]:
+            probs = probs.cpu().numpy()
             sorted_ids = np.argsort(probs)
             sorted_probs = probs[sorted_ids][::-1]
             cumulative_probs = np.cumsum(sorted_probs)
-            cutoff = float(sorted_probs[np.argmax(cumulative_probs > top_p)])
+            cutoff = float(sorted_probs[np.argmax(cumulative_probs >= top_p)])
             probs[probs < cutoff] = 0
             if top_k < len(probs) and top_k > 0:
                 probs[sorted_ids[:-top_k]] = 0
@@ -92,7 +101,7 @@ class PIPELINE:
             sorted_probs = probs[sorted_ids]
             sorted_probs = torch.flip(sorted_probs, dims=(0,))
             cumulative_probs = torch.cumsum(sorted_probs, dim=-1).cpu().numpy()
-            cutoff = float(sorted_probs[np.argmax(cumulative_probs > top_p)])
+            cutoff = float(sorted_probs[np.argmax(cumulative_probs >= top_p)])
             probs[probs < cutoff] = 0
             if top_k < len(probs) and top_k > 0:
                 probs[sorted_ids[:-top_k]] = 0
@@ -127,10 +136,13 @@ class PIPELINE:
             if token in args.token_stop:
                 break
             all_tokens += [token]
+            for xxx in occurrence:
+                occurrence[xxx] *= args.alpha_decay
             if token not in occurrence:
                 occurrence[token] = 1
             else:
                 occurrence[token] += 1
+            # print(occurrence) # debug
 
             # output
             tmp = self.decode(all_tokens[out_last:])

backend-python/utils/log.py

@@ -10,7 +10,7 @@ logger = logging.getLogger()
 logger.setLevel(logging.INFO)
 formatter = logging.Formatter("%(asctime)s - %(levelname)s\n%(message)s")
 fh = logging.handlers.RotatingFileHandler(
-    "api.log", mode="a", maxBytes=3 * 1024 * 1024, backupCount=3
+    "api.log", mode="a", maxBytes=3 * 1024 * 1024, backupCount=3, encoding="utf-8"
 )
 fh.setFormatter(formatter)
 logger.addHandler(fh)

backend-python/utils/ngrok.py

@@ -1,11 +1,13 @@
 import os
-import sys
+import global_var
 
 
 def ngrok_connect():
     from pyngrok import ngrok, conf
 
-    conf.set_default(conf.PyngrokConfig(ngrok_path="./ngrok"))
+    conf.set_default(
+        conf.PyngrokConfig(ngrok_path="./ngrok.exe" if os.name == "nt" else "./ngrok")
+    )
     ngrok.set_auth_token(os.environ["ngrok_token"])
-    http_tunnel = ngrok.connect(8000 if len(sys.argv) == 1 else int(sys.argv[1]))
-    print(http_tunnel.public_url)
+    http_tunnel = ngrok.connect(global_var.get(global_var.Args).port)
+    print(f"ngrok url: {http_tunnel.public_url}")

backend-python/utils/rwkv.py

@@ -4,7 +4,7 @@ import os
 import pathlib
 import copy
 import re
-from typing import Dict, Iterable, List, Tuple, Union
+from typing import Dict, Iterable, List, Tuple, Union, Type
 from utils.log import quick_log
 from fastapi import HTTPException
 from pydantic import BaseModel, Field
@@ -21,33 +21,21 @@ os.environ["TORCH_EXTENSIONS_DIR"] = f"{pathlib.Path(__file__).parent.parent.res
 
 
 class RWKVType(Enum):
+    NoneType = auto()
     Raven = auto()
     World = auto()
     Music = auto()
 
 
 class AbstractRWKV(ABC):
-    def __init__(self, model: str, strategy: str, tokens_path: str):
-        rwkv_beta = global_var.get(global_var.Args).rwkv_beta
-
-        # dynamic import to make RWKV_CUDA_ON work
-        if rwkv_beta:
-            from rwkv_pip.beta.model import (
-                RWKV as Model,
-            )
-        else:
-            from rwkv.model import (
-                RWKV as Model,
-            )
-        from rwkv_pip.utils import PIPELINE
-
-        filename, _ = os.path.splitext(os.path.basename(model))
-        self.name = filename
-        self.model = Model(model, strategy)
-        self.pipeline = PIPELINE(self.model, tokens_path)
+    def __init__(self, model, pipeline):
+        self.name = "rwkv"
+        self.model = model
+        self.pipeline = pipeline
         self.model_state = None
         self.model_tokens = []
-        self.rwkv_type: RWKVType = None
+        self.rwkv_type: RWKVType = RWKVType.NoneType
+        self.tokenizer_len = len(model.w["emb.weight"])
 
         self.max_tokens_per_generation = 500
         self.temperature = 1
@@ -348,8 +336,8 @@ class AbstractRWKV(ABC):
 
 
 class TextRWKV(AbstractRWKV):
-    def __init__(self, model: str, strategy: str, tokens_path: str) -> None:
-        super().__init__(model, strategy, tokens_path)
+    def __init__(self, model, pipeline) -> None:
+        super().__init__(model, pipeline)
 
         self.CHUNK_LEN = 256
 
@@ -361,16 +349,16 @@ class TextRWKV(AbstractRWKV):
         self.penalty_alpha_frequency = 1
 
         self.interface = ":"
-        if "world" in self.name.lower():
-            self.rwkv_type = RWKVType.World
-            self.user = "Question"
-            self.bot = "Answer"
-            self.END_OF_LINE = 11
-        else:
+        if self.tokenizer_len < 65536:
             self.rwkv_type = RWKVType.Raven
             self.user = "Bob"
             self.bot = "Alice"
             self.END_OF_LINE = 187
+        else:
+            self.rwkv_type = RWKVType.World
+            self.user = "User"
+            self.bot = "Assistant"
+            self.END_OF_LINE = 11
 
         self.AVOID_REPEAT_TOKENS = []
         AVOID_REPEAT = "，：？！"
@@ -469,8 +457,8 @@ The following is a coherent verbose detailed conversation between a girl named {
 
 
 class MusicRWKV(AbstractRWKV):
-    def __init__(self, model: str, strategy: str, tokens_path: str):
-        super().__init__(model, strategy, tokens_path)
+    def __init__(self, model, pipeline):
+        super().__init__(model, pipeline)
 
         self.max_tokens_per_generation = 500
         self.temperature = 1
@@ -510,6 +498,52 @@ class MusicRWKV(AbstractRWKV):
         return " " + delta
 
 
+def get_tokenizer(tokenizer_len: int):
+    tokenizer_dir = f"{pathlib.Path(__file__).parent.parent.resolve()}/rwkv_pip/"
+    if tokenizer_len < 50277:
+        return tokenizer_dir + "tokenizer-midi.json"
+    elif tokenizer_len < 65536:
+        return tokenizer_dir + "20B_tokenizer.json"
+    else:
+        return "rwkv_vocab_v20230424"
+
+
+def RWKV(model: str, strategy: str, tokenizer: Union[str, None]) -> AbstractRWKV:
+    rwkv_beta = global_var.get(global_var.Args).rwkv_beta
+
+    # dynamic import to make RWKV_CUDA_ON work
+    if rwkv_beta:
+        from rwkv_pip.beta.model import (
+            RWKV as Model,
+        )
+    else:
+        from rwkv_pip.model import (
+            RWKV as Model,
+        )
+    from rwkv_pip.utils import PIPELINE
+
+    filename, _ = os.path.splitext(os.path.basename(model))
+    model = Model(model, strategy)
+    if not tokenizer:
+        tokenizer = get_tokenizer(len(model.w["emb.weight"]))
+    pipeline = PIPELINE(model, tokenizer)
+
+    rwkv_map: dict[str, Type[AbstractRWKV]] = {
+        "20B_tokenizer": TextRWKV,
+        "rwkv_vocab_v20230424": TextRWKV,
+        "tokenizer-midi": MusicRWKV,
+    }
+    tokenizer_name = os.path.splitext(os.path.basename(tokenizer))[0]
+    rwkv: AbstractRWKV
+    if tokenizer_name in rwkv_map:
+        rwkv = rwkv_map[tokenizer_name](model, pipeline)
+    else:
+        rwkv = TextRWKV(model, pipeline)
+    rwkv.name = filename
+
+    return rwkv
+
+
 class ModelConfigBody(BaseModel):
     max_tokens: int = Field(default=None, gt=0, le=102400)
     temperature: float = Field(default=None, ge=0, le=2)
@@ -517,8 +551,8 @@ class ModelConfigBody(BaseModel):
     presence_penalty: float = Field(default=None, ge=-2, le=2)
     frequency_penalty: float = Field(default=None, ge=-2, le=2)
 
-    class Config:
-        schema_extra = {
+    model_config = {
+        "json_schema_extra": {
             "example": {
                 "max_tokens": 1000,
                 "temperature": 1.2,
@@ -527,6 +561,7 @@ class ModelConfigBody(BaseModel):
                 "frequency_penalty": 0.4,
             }
         }
+    }
 
 
 def set_rwkv_config(model: AbstractRWKV, body: ModelConfigBody):

backend-python/webui_server.py

@@ -0,0 +1,14 @@
+from fastapi import FastAPI
+from fastapi.middleware.gzip import GZipMiddleware
+from fastapi.staticfiles import StaticFiles
+import uvicorn
+
+webui_server = FastAPI()
+
+webui_server.add_middleware(GZipMiddleware, minimum_size=1000)
+webui_server.mount(
+    "/", StaticFiles(directory="frontend/dist", html=True), name="static"
+)
+
+if __name__ == "__main__":
+    uvicorn.run("webui_server:webui_server")

backend-python/wkv_cuda_utils/wkv_cuda_model.py

@@ -1,734 +0,0 @@
-########################################################################################################
-# The RWKV Language Model - https://github.com/BlinkDL/RWKV-LM
-########################################################################################################
-
-import types, gc, os, time, re
-import torch
-from torch.nn import functional as F
-torch.backends.cudnn.benchmark = True
-torch.backends.cudnn.allow_tf32 = True
-torch.backends.cuda.matmul.allow_tf32 = True
-current_path = os.path.dirname(os.path.abspath(__file__))
-
-# https://zhuanlan.zhihu.com/p/612879065
-def LoadPreCompileLibrary(file):
-    import importlib
-    import os
-
-    import torch
-
-    # load the custom_op_library and register the custom ops
-    lib_dir = os.path.dirname(__file__)
-    if os.name == "nt":
-        # Register the main torchvision library location on the default DLL path
-        import ctypes
-        import sys
-
-        kernel32 = ctypes.WinDLL("kernel32.dll", use_last_error=True)
-        with_load_library_flags = hasattr(kernel32, "AddDllDirectory")
-        prev_error_mode = kernel32.SetErrorMode(0x0001)
-
-        if with_load_library_flags:
-            kernel32.AddDllDirectory.restype = ctypes.c_void_p
-
-        if sys.version_info >= (3, 8):
-            os.add_dll_directory(lib_dir)
-        elif with_load_library_flags:
-            res = kernel32.AddDllDirectory(lib_dir)
-            if res is None:
-                err = ctypes.WinError(ctypes.get_last_error())
-                err.strerror += f' Error adding "{lib_dir}" to the DLL directories.'
-                raise ValueError(err)
-
-        kernel32.SetErrorMode(prev_error_mode)
-
-    loader_details = (
-        importlib.machinery.ExtensionFileLoader,
-        importlib.machinery.EXTENSION_SUFFIXES,
-    )
-
-    extfinder = importlib.machinery.FileFinder(lib_dir, loader_details)
-    ext_specs = extfinder.find_spec(file)
-    if ext_specs is None:
-        return False
-
-    try:
-        torch.ops.load_library(ext_specs.origin)
-    except OSError as exc:
-        return False
-    return True
-
-########################################################################################################
-
-if os.environ.get('RWKV_JIT_ON') != '0':
-    os.environ["RWKV_JIT_ON"] = '1'
-    MyModule = torch.jit.ScriptModule
-    MyFunction = torch.jit.script_method
-    MyStatic = torch.jit.script
-else:
-    MyModule = torch.nn.Module
-    def __nop(ob):
-        return ob
-    MyFunction = __nop
-    MyStatic = __nop
-
-if os.environ.get('RWKV_CUDA_ON') == '1':
-    if LoadPreCompileLibrary('wkv_cuda') is False:
-        from torch.utils.cpp_extension import load
-        load(
-            name=f"wkv_cuda",
-            sources=[f"{current_path}/cuda/wrapper.cpp", f"{current_path}/cuda/operators.cu"],
-            verbose=True,
-            extra_cuda_cflags=["-t 4", "-std=c++17", "--use_fast_math", "-O3", "--extra-device-vectorization"],
-            is_python_module=False)
-
-    @MyStatic
-    def cuda_wkv(T: int, C: int, w, u, k, v, aa, bb, pp):
-        assert 1 * C % min(C, 32) == 0
-        assert k.dtype == v.dtype == torch.float16 or k.dtype == v.dtype == torch.float32
-        assert w.dtype == u.dtype == aa.dtype == bb.dtype == pp.dtype == torch.float32
-        w = w.contiguous()
-        u = u.contiguous()
-        k = k.contiguous()
-        v = v.contiguous()
-        y = torch.empty((T, C), device=w.device, memory_format=torch.contiguous_format, dtype=k.dtype)
-        torch.ops.rwkv.wkv_forward(1, T, C, w, u, k, v, y, aa, bb, pp)
-        return y, aa, bb, pp
-    @MyStatic
-    def cuda_mm8_seq(B: int, N: int, M: int, x, w, mx, rx, my, ry):
-        assert x.dtype == mx.dtype == rx.dtype == my.dtype == ry.dtype
-        assert x.dtype == torch.float32 or x.dtype == torch.float16
-        assert w.dtype == torch.uint8
-        assert x.shape == [B, N]
-        assert w.shape == [N, M]
-        assert rx.shape == mx.shape == [M]
-        assert ry.shape == my.shape == [N, 1]
-        y = torch.empty((B, M), device=w.device, dtype=x.dtype)
-        torch.ops.rwkv.mm8_seq(B, N, M, x, w, mx, rx, my, ry, y)
-        return y
-    @MyStatic
-    def cuda_mm8_one(N: int, M: int, x, w, mx, rx, my, ry):
-        assert x.dtype == mx.dtype == rx.dtype == my.dtype == ry.dtype
-        assert x.dtype == torch.float32 or x.dtype == torch.float16
-        assert w.dtype == torch.uint8
-        assert x.shape == [N]
-        assert w.shape == [N, M]
-        assert rx.shape == mx.shape == [M]
-        assert ry.shape == my.shape == [N, 1]
-        y = torch.zeros((M,), device=w.device, dtype=torch.float32)
-        torch.ops.rwkv.mm8_one(N, M, x, w, mx, rx, my, ry, y)
-        return y.to(dtype=x.dtype)
-else:
-    os.environ["RWKV_CUDA_ON"] = '0'
-
-########################################################################################################
-
-class RWKV(MyModule):
-    def __init__(self, model, strategy, verbose = True, convert_and_save_and_exit = None):
-        super().__init__()
-        if verbose:
-            prxxx = lambda *args, **kwargs: print(*args, **kwargs)
-        else:
-            prxxx = lambda *args, **kwargs: None
-
-        STRATEGY_REGEX = r"^(?:(?:^|->) *(?:cuda(?::[\d]+)?|cpu|mps) (?:fp(?:16|32)|bf16)(?:i8|i4|i3)?(?: \*[\d]+\+?)? *)+$"
-        if not re.match(STRATEGY_REGEX, strategy):
-            raise ValueError("Invalid strategy. Please read https://pypi.org/project/rwkv/")
-
-        strategy = ('->'.join([x.strip() for x in strategy.split('->')])).replace('->', ' -> ')
-        self.args = types.SimpleNamespace()
-        args = self.args
-        args.MODEL_NAME = model
-        args.strategy_string = strategy
-
-        # Rescale for fp16 mode: set x = x/2 every X layer (to avoid fp16 overflow)
-        self.RESCALE_LAYER = 6 if 'fp16' in strategy else 0
-        prxxx(f'RWKV_JIT_ON {os.environ["RWKV_JIT_ON"]} RWKV_CUDA_ON {os.environ["RWKV_CUDA_ON"]} RESCALE_LAYER {self.RESCALE_LAYER}\n')
-
-        args.MODEL_NAME = args.MODEL_NAME.strip()
-        if not args.MODEL_NAME.endswith('.pth'):
-            args.MODEL_NAME += '.pth'
-        prxxx(f'Loading {args.MODEL_NAME} ...')
-        with torch.no_grad():
-            self.w = torch.load(args.MODEL_NAME, map_location='cpu') # load model to CPU first
-            gc.collect()
-            w = self.w
-
-            ALREADY_CONVERTED = False
-            if '_strategy' in w:
-                ALREADY_CONVERTED = True
-                assert convert_and_save_and_exit == None # you should only convert a raw model
-                prxxx(f"Converted model: strategy {w['_strategy']}, version {w['_version']}\n")
-                assert w['_strategy'] == args.strategy_string # if you are using a new strategy, re-convert the model
-                assert float(w['_version']) >= 0.7 # sometimes you should re-convert using latest convert_model.py
-                assert w['_rescale_layer'] == self.RESCALE_LAYER
-                del w['_strategy']
-                del w['_version']
-                del w['_rescale_layer']
-            
-            args.n_embd = w['emb.weight'].shape[1]
-            args.n_layer = 0
-            keys = list(w.keys())
-            for x in keys:
-                layer_id = int(x.split('.')[1]) if ('blocks.' in x) else 0
-                args.n_layer = max(args.n_layer, layer_id+1)
-
-            ####################### Compute strategy
-
-            s = [x.strip().split(' ') for x in strategy.split('->')]
-            plan = [0] * len(s)
-            stream_i = -1
-            stream_count = 0
-            to_allocate = args.n_layer + 1
-            allocated = 0
-            free_slots = 0
-            for i in range(len(s)):
-                si = s[i]
-                si1 = si[1]
-                if si1.startswith('fp32'): si[1] = [torch.float]
-                elif si1.startswith('fp16'): si[1] = [torch.float16]
-                elif si1.startswith('bf16'): si[1] = [torch.bfloat16]
-                if si1.endswith('i8'): si[1] += [torch.uint8]
-                else: si[1] += [si[1][0]]
-                if len(si) > 2:
-                    ss = si[2]
-                    assert ss.startswith('*')
-                    if ss.endswith('+'):
-                        plan[i] = int(ss[1:-1])
-                        stream_i = i
-                    else:
-                        plan[i] = int(ss[1:])
-                    allocated += plan[i]
-                    if allocated >= to_allocate:
-                        plan[i] += to_allocate - allocated
-                        break
-                else:
-                    free_slots += 1
-            if stream_i < 0:
-                if free_slots > 0 and to_allocate > allocated:
-                    for i in range(len(s)):
-                        if plan[i] == 0:
-                            plan[i] = (to_allocate - allocated) // free_slots
-                            allocated += plan[i]
-                            free_slots -= 1
-                if to_allocate > allocated:
-                    plan[len(s)-1] += to_allocate - allocated
-            else:
-                if to_allocate > allocated:
-                    stream_count = to_allocate - allocated
-                    plan[stream_i] += stream_count
-            prxxx(f'Strategy: (total {args.n_layer}+1={args.n_layer+1} layers)')
-            for i in range(len(s)):
-                ss = s[i]
-                if i != stream_i:
-                    prxxx(f'* {ss[0]} {str(ss[1]).replace("torch.","")}, store {plan[i]} layers')
-                else:
-                    prxxx(f'* {ss[0]} {str(ss[1]).replace("torch.","")}, store {plan[i]-stream_count} layers, stream {stream_count} layers')
-                plan[i] += (0 if i == 0 else plan[i-1])
-            self.strategy = [None] * (args.n_layer + 1)
-            strategy = self.strategy
-            for n in range(args.n_layer + 1):
-                for i in range(len(s)):
-                    if n < plan[i]:
-                        strategy[n] = types.SimpleNamespace()
-                        strategy[n].device = s[i][0]
-                        strategy[n].atype = s[i][1][0]
-                        strategy[n].wtype = s[i][1][1]
-                        strategy[n].stream = False
-                        if i == stream_i and n >= (plan[i] - stream_count):
-                            strategy[n].stream = True
-                        break
-                prxxx(f"{n}-{strategy[n].device}-{str(strategy[n].atype).replace('torch.','')}-{str(strategy[n].wtype).replace('torch.','')}{'-stream' if strategy[n].stream else ''}",end=' ')
-            prxxx()
-
-            ####################### Load weights to self.w
-
-            if not ALREADY_CONVERTED:
-                try: # precompute embedding
-                    w['emb.weight'] = F.layer_norm(w['emb.weight'], (args.n_embd,), weight=w['blocks.0.ln0.weight'], bias=w['blocks.0.ln0.bias'])
-                except:
-                    w['emb.weight'] = F.layer_norm(w['emb.weight'].float(), (args.n_embd,), weight=w['blocks.0.ln0.weight'].float(), bias=w['blocks.0.ln0.bias'].float())
-                del w['blocks.0.ln0.weight']
-                del w['blocks.0.ln0.bias']
-
-            print_need_newline = False
-            keys = list(w.keys())
-            for x in keys:
-                w[x].requires_grad = False
-                layer_id = int(x.split('.')[1]) if ('blocks.' in x) else 0
-                if ('ln_out.' in x) or ('head.' in x):
-                    layer_id = args.n_layer
-                dd = strategy[layer_id]
-                DEVICE = dd.device
-                ATYPE = dd.atype
-                WTYPE = dd.wtype
-
-                if not ALREADY_CONVERTED:
-                    if self.RESCALE_LAYER > 0:
-                        if 'att.output.weight' in x:
-                            w[x] = w[x] / (2 ** int(layer_id // self.RESCALE_LAYER))
-                        if 'ffn.value.weight' in x:
-                            w[x] = w[x] / (2 ** int(layer_id // self.RESCALE_LAYER))
-
-                    if '.time_' in x:
-                        w[x] = w[x].squeeze()
-                    if 'key.weight' in x or 'value.weight' in x or 'receptance.weight' in x or 'output.weight' in x or 'head.weight' in x:
-                        w[x] = w[x].t()
-
-                    if '.time_decay' in x: # need fp32 for this
-                        w[x] = -torch.exp(w[x].float())
-                    elif '.time_first' in x: # need fp32 for this
-                        w[x] = w[x].float()
-                    else:
-                        if (len(w[x].shape) == 2) and ('emb' not in x):
-                            if WTYPE != torch.uint8:
-                                w[x] = w[x].to(dtype=WTYPE)
-                            else:
-                                w[x] = w[x].float()
-
-                                if w[x].shape[0] > w[x].shape[1]:
-                                    w[x+'_my'] = torch.amin(w[x], dim=1).unsqueeze(1)
-                                    w[x] = w[x] - w[x+'_my']
-                                    w[x+'_mx'] = torch.amin(w[x], dim=0)
-                                    w[x] = w[x] - w[x+'_mx']
-                                    w[x+'_rx'] = torch.amax(w[x], dim=0)
-                                    w[x] = w[x] / w[x+'_rx']
-                                    w[x+'_ry'] = torch.amax(w[x], dim=1).unsqueeze(1)
-                                    w[x] = w[x] / w[x+'_ry']
-                                else:
-                                    w[x+'_mx'] = torch.amin(w[x], dim=0)
-                                    w[x] = w[x] - w[x+'_mx']
-                                    w[x+'_my'] = torch.amin(w[x], dim=1).unsqueeze(1)
-                                    w[x] = w[x] - w[x+'_my']
-                                    w[x+'_rx'] = torch.amax(w[x], dim=0)
-                                    w[x] = w[x] / w[x+'_rx']
-                                    w[x+'_ry'] = torch.amax(w[x], dim=1).unsqueeze(1)
-                                    w[x] = w[x] / w[x+'_ry']
-
-                                w[x] = torch.clip(torch.floor(w[x] * 256), min=0, max=255).to(dtype=torch.uint8)
-                                w[x+'_mx'] = w[x+'_mx'].to(dtype=ATYPE).contiguous()
-                                w[x+'_rx'] = (w[x+'_rx'] / 16).to(dtype=ATYPE).contiguous()
-                                w[x+'_my'] = w[x+'_my'].to(dtype=ATYPE).contiguous()
-                                w[x+'_ry'] = (w[x+'_ry'] / 16).to(dtype=ATYPE).contiguous()
-                        else:
-                            w[x] = w[x].to(dtype=ATYPE)
-                
-                if convert_and_save_and_exit == None:
-                    if 'emb.' in x:
-                        w[x] = w[x].contiguous()
-                    elif (dd.stream) and (x.endswith('key.weight') or x.endswith('value.weight') or x.endswith('receptance.weight') or x.endswith('output.weight')):
-                        try:
-                            w[x] = w[x].contiguous().pin_memory() # if you see "CUDA error: out of memory" here, that's out of CPU RAM, not VRAM. Get more RAM :)
-                        except:
-                            print('Note: You are running out of RAM. Get more CPU RAM. Now this will run much slower.')
-                    elif DEVICE != 'cpu':
-                        w[x] = w[x].to(device=DEVICE).contiguous()
-                    
-                    if (dd.stream) or (DEVICE != 'cpu'):
-                        try:
-                            w[x+'_mx'] = w[x+'_mx'].to(device=DEVICE).contiguous()
-                            w[x+'_rx'] = w[x+'_rx'].to(device=DEVICE).contiguous()
-                            w[x+'_my'] = w[x+'_my'].to(device=DEVICE).contiguous()
-                            w[x+'_ry'] = w[x+'_ry'].to(device=DEVICE).contiguous()
-                        except:
-                            pass
-
-                if 'ffn.value.weight' in x:
-                    gc.collect()
-                    if 'cuda' in args.strategy_string:
-                        torch.cuda.empty_cache()
-
-                shape = [i for i in w[x].shape if i != 1]
-                if len(shape) > 1:
-                    shape = f" {str(shape[0]).rjust(5)} {str(shape[1]).rjust(5)}"
-                else:
-                    shape = f" {str(shape[0]).rjust(5)}      "
-                if layer_id == 0 or layer_id >= args.n_layer-1:
-                    if print_need_newline:
-                        prxxx('\n', end = '')
-                        print_need_newline = False
-                    dt = str(w[x].dtype).replace('torch.', '')
-                    dt = dt.replace('float32', 'f32').replace('bfloat16', 'bf16').replace('float16', 'f16').replace('uint8', 'i8')
-                    prxxx(x.ljust(32), dt.rjust(4), str(w[x].device).rjust(8), shape, ' (pinned)' if w[x].is_pinned() else '')
-                else:
-                    print_need_newline = True
-                    prxxx('.', end = '', flush = True)
-            
-            if convert_and_save_and_exit:
-                w['_strategy'] = args.strategy_string
-                w['_rescale_layer'] = self.RESCALE_LAYER
-                w['_version'] = '0.7'
-                if not convert_and_save_and_exit.endswith('.pth'):
-                    convert_and_save_and_exit += '.pth'
-                prxxx(f'Saving to {convert_and_save_and_exit}...')
-                torch.save(w, convert_and_save_and_exit)
-                prxxx(f'Converted and saved. Now this will exit.')
-                exit(0)
-            
-            gc.collect()
-            if 'cuda' in args.strategy_string:
-                torch.cuda.empty_cache()
-
-    @MyFunction
-    def torch_mm8_seq(self, x, w, mx, rx, my, ry):
-        return x @ ((w.to(dtype=x.dtype) + 0.5) * ry * rx + my + mx)
-
-    @MyFunction
-    def torch_mm8_one(self, x, w, mx, rx, my, ry):
-        return x @ ((w.to(dtype=x.dtype) + 0.5) * ry * rx + my + mx)
-
-    if os.environ.get('RWKV_CUDA_ON') == '1':
-        @MyFunction
-        def mm8_seq(self, x, w, mx, rx, my, ry):
-            if w.device.type == 'cuda' and x.dtype == torch.float16:
-                B, N, M = x.shape[0], w.shape[0], w.shape[1]
-                return cuda_mm8_seq(B, N, M, x, w, mx, rx, my, ry)
-            else:
-                return self.torch_mm8_seq(x, w, mx, rx, my, ry)
-        @MyFunction
-        def mm8_one(self, x, w, mx, rx, my, ry):
-            if w.device.type == 'cuda':
-                N, M = w.shape[0], w.shape[1]
-                return cuda_mm8_one(N, M, x, w, mx, rx, my, ry)
-            else:
-                return self.torch_mm8_one(x, w, mx, rx, my, ry)
-    else:
-        @MyFunction
-        def mm8_seq(self, x, w, mx, rx, my, ry):
-            return self.torch_mm8_seq(x, w, mx, rx, my, ry)
-        @MyFunction
-        def mm8_one(self, x, w, mx, rx, my, ry):
-            return self.torch_mm8_one(x, w, mx, rx, my, ry)
-
-    ########################################################################################################
-
-    @MyFunction
-    def ffn_one(self, x, sx, ln_w, ln_b, k_mix, r_mix, kw, vw, rw, kmx, krx, kmy, kry, vmx, vrx, vmy, vry, rmx, rrx, rmy, rry):
-        xx = F.layer_norm(x, (x.shape[-1],), weight=ln_w, bias=ln_b)
-        kx = xx * k_mix + sx * (1 - k_mix)
-        rx = xx * r_mix + sx * (1 - r_mix)
-
-        r = torch.sigmoid(rx @ rw)
-        vx = torch.square(torch.relu(kx @ kw))
-        out = r * (vx @ vw)
-        return x + out, xx
-
-    @MyFunction
-    def ffn_one_i8(self, x, sx, ln_w, ln_b, k_mix, r_mix, kw, vw, rw, kmx, krx, kmy, kry, vmx, vrx, vmy, vry, rmx, rrx, rmy, rry):
-        xx = F.layer_norm(x, (x.shape[-1],), weight=ln_w, bias=ln_b)
-        kx = xx * k_mix + sx * (1 - k_mix)
-        rx = xx * r_mix + sx * (1 - r_mix)
-
-        r = torch.sigmoid(self.mm8_one(rx, rw, rmx, rrx, rmy, rry))
-        vx = torch.square(torch.relu(self.mm8_one(kx, kw, kmx, krx, kmy, kry)))
-        out = r * (self.mm8_one(vx, vw, vmx, vrx, vmy, vry))
-        return x + out, xx
-    
-    ########################################################################################################
-
-    @MyFunction
-    def ffn_seq(self, x, sx, ln_w, ln_b, k_mix, r_mix, kw, vw, rw, kmx, krx, kmy, kry, vmx, vrx, vmy, vry, rmx, rrx, rmy, rry):
-        xx = F.layer_norm(x, (x.shape[-1],), weight=ln_w, bias=ln_b)
-        sx = torch.cat((sx.unsqueeze(0), xx[:-1,:]))
-        kx = xx * k_mix + sx * (1 - k_mix)
-        rx = xx * r_mix + sx * (1 - r_mix)
-
-        r = torch.sigmoid(rx @ rw)
-        vx = torch.square(torch.relu(kx @ kw))
-        out = r * (vx @ vw)
-        return x + out, xx[-1,:]
-
-    @MyFunction
-    def ffn_seq_i8(self, x, sx, ln_w, ln_b, k_mix, r_mix, kw, vw, rw, kmx, krx, kmy, kry, vmx, vrx, vmy, vry, rmx, rrx, rmy, rry):
-        xx = F.layer_norm(x, (x.shape[-1],), weight=ln_w, bias=ln_b)
-        sx = torch.cat((sx.unsqueeze(0), xx[:-1,:]))
-        kx = xx * k_mix + sx * (1 - k_mix)
-        rx = xx * r_mix + sx * (1 - r_mix)
-
-        r = torch.sigmoid(self.mm8_seq(rx, rw, rmx, rrx, rmy, rry))
-        vx = torch.square(torch.relu(self.mm8_seq(kx, kw, kmx, krx, kmy, kry)))
-        out = r * (self.mm8_seq(vx, vw, vmx, vrx, vmy, vry))
-        return x + out, xx[-1,:]
-
-    ########################################################################################################
-
-    @MyFunction
-    def att_one(self, x, sx, aa, bb, pp, ln_w, ln_b, k_mix, v_mix, r_mix, t_decay, t_first, kw, vw, rw, ow, kmx, krx, kmy, kry, vmx, vrx, vmy, vry, rmx, rrx, rmy, rry, omx, orx, omy, ory):
-        xx = F.layer_norm(x, (x.shape[-1],), weight=ln_w, bias=ln_b)
-        kx = xx * k_mix + sx * (1 - k_mix)
-        vx = xx * v_mix + sx * (1 - v_mix)
-        rx = xx * r_mix + sx * (1 - r_mix)
-
-        r = torch.sigmoid(rx @ rw)
-        k = (kx @ kw).float()
-        v = (vx @ vw).float()
-
-        ww = t_first + k
-        p = torch.maximum(pp, ww)
-        e1 = torch.exp(pp - p)
-        e2 = torch.exp(ww - p)
-        wkv = ((e1 * aa + e2 * v) / (e1 * bb + e2)).to(dtype=x.dtype)
-        ww = t_decay + pp
-        p = torch.maximum(ww, k)
-        e1 = torch.exp(ww - p)
-        e2 = torch.exp(k - p)
-
-        out = (r * wkv) @ ow
-        return x + out, xx, e1 * aa + e2 * v, e1 * bb + e2, p
-
-    @MyFunction
-    def att_one_i8(self, x, sx, aa, bb, pp, ln_w, ln_b, k_mix, v_mix, r_mix, t_decay, t_first, kw, vw, rw, ow, kmx, krx, kmy, kry, vmx, vrx, vmy, vry, rmx, rrx, rmy, rry, omx, orx, omy, ory):
-        xx = F.layer_norm(x, (x.shape[-1],), weight=ln_w, bias=ln_b)
-        kx = xx * k_mix + sx * (1 - k_mix)
-        vx = xx * v_mix + sx * (1 - v_mix)
-        rx = xx * r_mix + sx * (1 - r_mix)
-
-        r = torch.sigmoid(self.mm8_one(rx, rw, rmx, rrx, rmy, rry))
-        k = (self.mm8_one(kx, kw, kmx, krx, kmy, kry)).float()
-        v = (self.mm8_one(vx, vw, vmx, vrx, vmy, vry)).float()
-
-        ww = t_first + k
-        p = torch.maximum(pp, ww)
-        e1 = torch.exp(pp - p)
-        e2 = torch.exp(ww - p)
-        wkv = ((e1 * aa + e2 * v) / (e1 * bb + e2)).to(dtype=x.dtype)
-        ww = t_decay + pp
-        p = torch.maximum(ww, k)
-        e1 = torch.exp(ww - p)
-        e2 = torch.exp(k - p)
-
-        out = self.mm8_one(r * wkv, ow, omx, orx, omy, ory)
-        return x + out, xx, e1 * aa + e2 * v, e1 * bb + e2, p
-
-    ########################################################################################################
-
-    @MyFunction
-    def att_seq(self, x, sx, aa, bb, pp, ln_w, ln_b, k_mix, v_mix, r_mix, t_decay, t_first, kw, vw, rw, ow, kmx, krx, kmy, kry, vmx, vrx, vmy, vry, rmx, rrx, rmy, rry, omx, orx, omy, ory):
-        xx = F.layer_norm(x, (x.shape[-1],), weight=ln_w, bias=ln_b)
-        sx = torch.cat((sx.unsqueeze(0), xx[:-1,:]))
-        kx = xx * k_mix + sx * (1 - k_mix)
-        vx = xx * v_mix + sx * (1 - v_mix)
-        rx = xx * r_mix + sx * (1 - r_mix)
-
-        r = torch.sigmoid(rx @ rw)
-        k = (kx @ kw).float()
-        v = (vx @ vw).float()
-
-        T = x.shape[0]
-        for t in range(T):
-            kk = k[t]
-            vv = v[t]
-            ww = t_first + kk
-            p = torch.maximum(pp, ww)
-            e1 = torch.exp(pp - p)
-            e2 = torch.exp(ww - p)
-            sx[t] = ((e1 * aa + e2 * vv) / (e1 * bb + e2)).to(dtype=x.dtype)
-            ww = t_decay + pp
-            p = torch.maximum(ww, kk)
-            e1 = torch.exp(ww - p)
-            e2 = torch.exp(kk - p)
-            aa = e1 * aa + e2 * vv
-            bb = e1 * bb + e2
-            pp = p
-        out = (r * sx) @ ow
-        return x + out, xx[-1,:], aa, bb, pp
-
-    @MyFunction
-    def att_seq_i8(self, x, sx, aa, bb, pp, ln_w, ln_b, k_mix, v_mix, r_mix, t_decay, t_first, kw, vw, rw, ow, kmx, krx, kmy, kry, vmx, vrx, vmy, vry, rmx, rrx, rmy, rry, omx, orx, omy, ory):
-        xx = F.layer_norm(x, (x.shape[-1],), weight=ln_w, bias=ln_b)
-        sx = torch.cat((sx.unsqueeze(0), xx[:-1,:]))
-        kx = xx * k_mix + sx * (1 - k_mix)
-        vx = xx * v_mix + sx * (1 - v_mix)
-        rx = xx * r_mix + sx * (1 - r_mix)
-
-        r = torch.sigmoid(self.mm8_seq(rx, rw, rmx, rrx, rmy, rry))
-        k = self.mm8_seq(kx, kw, kmx, krx, kmy, kry).float()
-        v = self.mm8_seq(vx, vw, vmx, vrx, vmy, vry).float()
-
-        T = x.shape[0]
-        for t in range(T):
-            kk = k[t]
-            vv = v[t]
-            ww = t_first + kk
-            p = torch.maximum(pp, ww)
-            e1 = torch.exp(pp - p)
-            e2 = torch.exp(ww - p)
-            sx[t] = ((e1 * aa + e2 * vv) / (e1 * bb + e2)).to(dtype=x.dtype)
-            ww = t_decay + pp
-            p = torch.maximum(ww, kk)
-            e1 = torch.exp(ww - p)
-            e2 = torch.exp(kk - p)
-            aa = e1 * aa + e2 * vv
-            bb = e1 * bb + e2
-            pp = p
-        out = self.mm8_seq(r * sx, ow, omx, orx, omy, ory)
-        return x + out, xx[-1,:], aa, bb, pp
-
-    ########################################################################################################
-
-    if os.environ["RWKV_CUDA_ON"] == '1':
-        @MyFunction
-        def cuda_att_seq(self, x, sx, aa, bb, pp, ln_w, ln_b, k_mix, v_mix, r_mix, t_decay, t_first, kw, vw, rw, ow, kmx, krx, kmy, kry, vmx, vrx, vmy, vry, rmx, rrx, rmy, rry, omx, orx, omy, ory):
-            T, C = x.size()
-            xx = F.layer_norm(x, (C,), weight=ln_w, bias=ln_b)
-            sx = torch.cat((sx.unsqueeze(0), xx[:-1,:]))
-            kx = xx * k_mix + sx * (1 - k_mix)
-            vx = xx * v_mix + sx * (1 - v_mix)
-            rx = xx * r_mix + sx * (1 - r_mix)
-
-            r = torch.sigmoid(rx @ rw)
-            k = kx @ kw
-            v = vx @ vw
-            y, aa, bb, pp = cuda_wkv(T, C, t_decay, t_first, k, v, aa, bb, pp)
-            
-            out = (r * y) @ ow
-            return x + out, xx[-1,:], aa, bb, pp
-
-        @MyFunction
-        def cuda_att_seq_i8(self, x, sx, aa, bb, pp, ln_w, ln_b, k_mix, v_mix, r_mix, t_decay, t_first, kw, vw, rw, ow, kmx, krx, kmy, kry, vmx, vrx, vmy, vry, rmx, rrx, rmy, rry, omx, orx, omy, ory):
-            T, C = x.size()
-            xx = F.layer_norm(x, (C,), weight=ln_w, bias=ln_b)
-            sx = torch.cat((sx.unsqueeze(0), xx[:-1,:]))
-            kx = xx * k_mix + sx * (1 - k_mix)
-            vx = xx * v_mix + sx * (1 - v_mix)
-            rx = xx * r_mix + sx * (1 - r_mix)
-
-            r = torch.sigmoid(self.mm8_seq(rx, rw, rmx, rrx, rmy, rry))
-            k = self.mm8_seq(kx, kw, kmx, krx, kmy, kry)
-            v = self.mm8_seq(vx, vw, vmx, vrx, vmy, vry)
-            y, aa, bb, pp = cuda_wkv(T, C, t_decay, t_first, k, v, aa, bb, pp)
-
-            out = self.mm8_seq(r * y, ow, omx, orx, omy, ory)
-            return x + out, xx[-1,:], aa, bb, pp
-
-    ########################################################################################################
-
-    def forward(self, tokens, state, full_output=False):
-        with torch.no_grad():
-            w = self.w
-            args = self.args
-
-            if state == None:
-                state = [None] * args.n_layer * 5
-                for i in range(args.n_layer): # state: 0=att_xx 1=att_aa 2=att_bb 3=att_pp 4=ffn_xx
-                    dd = self.strategy[i]
-                    dev = dd.device
-                    atype = dd.atype
-                    state[i*5+0] = torch.zeros(args.n_embd, dtype=atype, requires_grad=False, device=dev).contiguous()
-                    state[i*5+1] = torch.zeros(args.n_embd, dtype=torch.float, requires_grad=False, device=dev).contiguous()
-                    state[i*5+2] = torch.zeros(args.n_embd, dtype=torch.float, requires_grad=False, device=dev).contiguous()
-                    state[i*5+3] = torch.zeros(args.n_embd, dtype=torch.float, requires_grad=False, device=dev).contiguous() - 1e30
-                    state[i*5+4] = torch.zeros(args.n_embd, dtype=atype, requires_grad=False, device=dev).contiguous()
-
-            seq_mode = len(tokens) > 1
-
-            x = w['emb.weight'][tokens if seq_mode else tokens[0]]
-
-            for i in range(args.n_layer):
-                bbb = f'blocks.{i}.'
-                att = f'blocks.{i}.att.'
-                ffn = f'blocks.{i}.ffn.'
-                dd = self.strategy[i]
-                dev = dd.device
-                atype = dd.atype
-                wtype = dd.wtype
-                if seq_mode:
-                    if 'cuda' in str(dev) and os.environ["RWKV_CUDA_ON"] == '1':
-                        ATT = self.cuda_att_seq if wtype != torch.uint8 else self.cuda_att_seq_i8
-                    else:
-                        ATT = self.att_seq if wtype != torch.uint8 else self.att_seq_i8
-                    FFN = self.ffn_seq if wtype != torch.uint8 else self.ffn_seq_i8
-                else:
-                    ATT = self.att_one if wtype != torch.uint8 else self.att_one_i8
-                    FFN = self.ffn_one if wtype != torch.uint8 else self.ffn_one_i8
-
-                x = x.to(dtype=atype, device=dev)
-
-                kw = w[f'{att}key.weight']
-                vw = w[f'{att}value.weight']
-                rw = w[f'{att}receptance.weight']
-                ow = w[f'{att}output.weight']
-                if dd.stream:
-                    kw = kw.to(device=dev, non_blocking=True)
-                    vw = vw.to(device=dev, non_blocking=True)
-                    rw = rw.to(device=dev, non_blocking=True)
-                    ow = ow.to(device=dev, non_blocking=True)
-                kmx = w[f'{att}key.weight_mx'] if wtype == torch.uint8 else x
-                krx = w[f'{att}key.weight_rx'] if wtype == torch.uint8 else x
-                kmy = w[f'{att}key.weight_my'] if wtype == torch.uint8 else x
-                kry = w[f'{att}key.weight_ry'] if wtype == torch.uint8 else x
-                vmx = w[f'{att}value.weight_mx'] if wtype == torch.uint8 else x
-                vrx = w[f'{att}value.weight_rx'] if wtype == torch.uint8 else x
-                vmy = w[f'{att}value.weight_my'] if wtype == torch.uint8 else x
-                vry = w[f'{att}value.weight_ry'] if wtype == torch.uint8 else x
-                rmx = w[f'{att}receptance.weight_mx'] if wtype == torch.uint8 else x
-                rrx = w[f'{att}receptance.weight_rx'] if wtype == torch.uint8 else x
-                rmy = w[f'{att}receptance.weight_my'] if wtype == torch.uint8 else x
-                rry = w[f'{att}receptance.weight_ry'] if wtype == torch.uint8 else x
-                omx = w[f'{att}output.weight_mx'] if wtype == torch.uint8 else x
-                orx = w[f'{att}output.weight_rx'] if wtype == torch.uint8 else x
-                omy = w[f'{att}output.weight_my'] if wtype == torch.uint8 else x
-                ory = w[f'{att}output.weight_ry'] if wtype == torch.uint8 else x
-                x, state[i*5+0], state[i*5+1], state[i*5+2], state[i*5+3] = ATT(
-                    x, state[i*5+0], state[i*5+1], state[i*5+2], state[i*5+3],
-                    w[f'{bbb}ln1.weight'], w[f'{bbb}ln1.bias'],
-                    w[f'{att}time_mix_k'], w[f'{att}time_mix_v'], w[f'{att}time_mix_r'],
-                    w[f'{att}time_decay'], w[f'{att}time_first'],
-                    kw, vw, rw, ow,
-                    kmx, krx, kmy, kry,
-                    vmx, vrx, vmy, vry,
-                    rmx, rrx, rmy, rry,
-                    omx, orx, omy, ory,
-                    )
-                if dd.stream:
-                    del kw, vw, rw, ow
-
-                kw = w[f'{ffn}key.weight']
-                vw = w[f'{ffn}value.weight']
-                rw = w[f'{ffn}receptance.weight']
-                if dd.stream:
-                    kw = kw.to(device=dev, non_blocking=True)
-                    vw = vw.to(device=dev, non_blocking=True)
-                    rw = rw.to(device=dev, non_blocking=True)
-                kmx = w[f'{ffn}key.weight_mx'] if wtype == torch.uint8 else x
-                krx = w[f'{ffn}key.weight_rx'] if wtype == torch.uint8 else x
-                kmy = w[f'{ffn}key.weight_my'] if wtype == torch.uint8 else x
-                kry = w[f'{ffn}key.weight_ry'] if wtype == torch.uint8 else x
-                vmx = w[f'{ffn}value.weight_mx'] if wtype == torch.uint8 else x
-                vrx = w[f'{ffn}value.weight_rx'] if wtype == torch.uint8 else x
-                vmy = w[f'{ffn}value.weight_my'] if wtype == torch.uint8 else x
-                vry = w[f'{ffn}value.weight_ry'] if wtype == torch.uint8 else x
-                rmx = w[f'{ffn}receptance.weight_mx'] if wtype == torch.uint8 else x
-                rrx = w[f'{ffn}receptance.weight_rx'] if wtype == torch.uint8 else x
-                rmy = w[f'{ffn}receptance.weight_my'] if wtype == torch.uint8 else x
-                rry = w[f'{ffn}receptance.weight_ry'] if wtype == torch.uint8 else x                    
-                x, state[i*5+4] = FFN(
-                    x, state[i*5+4],
-                    w[f'{bbb}ln2.weight'], w[f'{bbb}ln2.bias'],
-                    w[f'{ffn}time_mix_k'], w[f'{ffn}time_mix_r'],
-                    kw, vw, rw,
-                    kmx, krx, kmy, kry,
-                    vmx, vrx, vmy, vry,
-                    rmx, rrx, rmy, rry,                    
-                    )
-                if dd.stream:                
-                    del kw, vw, rw
-                
-                if self.RESCALE_LAYER > 0:
-                    if (i+1) % self.RESCALE_LAYER == 0:
-                        x = x / 2
-            
-            dd = self.strategy[args.n_layer]
-            x = x[-1,:] if (seq_mode and (not full_output)) else x
-            x = x.to(dtype=dd.atype, device=dd.device)
-            
-            x = F.layer_norm(x, (args.n_embd,), weight=w['ln_out.weight'], bias=w['ln_out.bias'])
-            if w['head.weight'].dtype != torch.uint8:
-                x = x @ w['head.weight']
-            else:
-                if seq_mode and full_output:
-                    x = self.mm8_seq(x, w['head.weight'], w['head.weight_mx'], w['head.weight_rx'], w['head.weight_my'], w['head.weight_ry'])
-                else:
-                    x = self.mm8_one(x, w['head.weight'], w['head.weight_mx'], w['head.weight_rx'], w['head.weight_my'], w['head.weight_ry'])
-
-            return x.float(), state

deploy-examples/RWKV-Runner-WebUI/setup.bat

@@ -0,0 +1,18 @@
+: install git python3.10 npm by yourself
+: change model and strategy according to your hardware
+
+git clone https://github.com/josStorer/RWKV-Runner --depth=1
+python -m pip install torch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1 --index-url https://download.pytorch.org/whl/cu117
+python -m pip install -r RWKV-Runner/backend-python/requirements.txt
+cd RWKV-Runner/frontend
+call npm ci
+call npm run build
+cd ..
+
+start python ./backend-python/main.py --webui
+start "C:\Program Files (x86)\Microsoft\Edge\Application\msedge.exe" "http://127.0.0.1:8000"
+
+powershell -Command "(Test-Path ./models) -or (mkdir models)"
+powershell -Command "Import-Module BitsTransfer"
+powershell -Command "(Test-Path ./models/RWKV-4-World-1.5B-v1-fixed-20230612-ctx4096.pth) -or (Start-BitsTransfer https://huggingface.co/BlinkDL/rwkv-4-world/resolve/main/RWKV-4-World-1.5B-v1-fixed-20230612-ctx4096.pth ./models/RWKV-4-World-1.5B-v1-fixed-20230612-ctx4096.pth)"
+powershell -Command "Invoke-WebRequest http://127.0.0.1:8000/switch-model -Method POST -ContentType 'application/json' -Body '{\"model\":\"./models/RWKV-4-World-1.5B-v1-fixed-20230612-ctx4096.pth\",\"strategy\":\"cuda fp32 *20+\",\"deploy\":\"true\"}'"

deploy-examples/RWKV-Runner-WebUI/setup.sh

@@ -0,0 +1,21 @@
+# install git python3.10 npm by yourself
+# change model and strategy according to your hardware
+
+sudo apt install python3-dev
+
+git clone https://github.com/josStorer/RWKV-Runner --depth=1
+python3 -m pip install torch torchvision torchaudio
+python3 -m pip install -r RWKV-Runner/backend-python/requirements.txt
+cd RWKV-Runner/frontend
+npm ci
+npm run build
+cd ..
+
+python3 ./backend-python/main.py --webui > log.txt &
+
+if [ ! -d models ]; then
+    mkdir models
+fi
+wget -N https://huggingface.co/BlinkDL/rwkv-4-world/resolve/main/RWKV-4-World-0.1B-v1-20230520-ctx4096.pth -P models/
+
+curl http://127.0.0.1:8000/switch-model -X POST -H "Content-Type: application/json" -d '{"model":"./models/RWKV-4-World-0.1B-v1-20230520-ctx4096.pth","strategy":"cpu fp32","deploy":"true"}'

finetune/data/sample.jsonl

@@ -1,7 +1,5 @@
-{"text": "1:This is the first document."}
-{"text": "2:Hello\nWorld"}
-{"text": "3:1+1=2\n1+2=3\n2+2=4"}
-{"text": "4:You will be training the GPT version because it's paralleziable and faster to train."}
-{"text": "5:Read the inference code in src/model.py and try using the final hidden state(.xx .aa .bb)"}
-{"text": "6:You can fine-tune the model with longer ctxLen and it can quickly adapt to longer ctxLens."}
-{"text": "7:Consider RWKV 14B. The state has 200 vectors, that is, 5 vectors for each block: fp16 (xx), fp32 (aa), fp32 (bb), fp32 (pp), fp16 (xx)."}
+{"text": "The following is an epic science fiction masterpiece that is immortalized, with delicate descriptions and grand depictions of interstellar civilization wars.\nChapter 1.\nAs I sit down to write here amidst the shadows of vine-leaves under the blue sky of southern Italy, it comes to me with a certain quality of astonishment that my participation in these amazing adventures of Mr. Cavor was, after all, the outcome of the purest accident. It might have been any one. I fell into these things at a time when I thought myself removed from the slightest possibility of disturbing experiences. I had gone to Lympne because I had imagined it the most uneventful place in the world. “Here, at any rate,” said I, “I shall find peace and a chance to work!”"}
+{"text": "Translate the following into Chinese.\n\nEnglish: What rooms do you have available?\nChinese: 你们有哪些房间可以提供"}
+{"text": "User: Hello.\n\nAssistant: I'm here, meow~.\n\nUser: Can you tell some jokes?\n\nAssistant: Of course, master. What kind of jokes would you like to hear?"}
+{"text": "Instruction: Write a story using the following information\n\nInput: A man named Alex chops a tree down\n\nResponse: Once upon a time, there was a man named Alex who lived in the heart of the forest. He had always been fascinated by trees and spent most of his days exploring the forest and learning about its many wonders. One day, while wandering through the woods, he stumbled upon an old oak tree that stood tall and proud in the middle of a clearing."}
+{"text": "def get_args(args: Union[Sequence[str], None] = None):\n    parser = argparse.ArgumentParser()\n    group = parser.add_argument_group(title=\"server arguments\")\n    group.add_argument(\n        \"--port\",\n        type=int,\n        default=8000,\n        help=\"port to run the server on (default: 8000)\",\n    )\n    group.add_argument(\n        \"--host\",\n        type=str,\n        default=\"127.0.0.1\",\n        help=\"host to run the server on (default: 127.0.0.1)\",\n    )"}

finetune/json2binidx_tool/tools/preprocess_data.py

@@ -246,5 +246,6 @@ if __name__ == "__main__":
     try:
         main()
     except Exception as e:
+        print(e)
         with open("error.txt", "w") as f:
             f.write(str(e))

finetune/lora/merge_lora.py

@@ -64,5 +64,6 @@ try:
 
         torch.save(output_w, output)
 except Exception as e:
+    print(e)
     with open("error.txt", "w") as f:
         f.write(str(e))

finetune/lora/train.py

@@ -264,7 +264,7 @@ if __name__ == "__main__":
 #
 # Data = {args.data_file} ({args.data_type}), ProjDir = {args.proj_dir}
 #
-# Epoch = {args.epoch_begin} to {args.epoch_begin + args.epoch_count - 1} (will continue afterwards), save every {args.epoch_save} epoch
+# Epoch = {args.epoch_begin} to {args.epoch_begin + args.epoch_count - 1}, save every {args.epoch_save} epoch
 #
 # Each "epoch" = {args.epoch_steps} steps, {samples_per_epoch} samples, {tokens_per_epoch} tokens
 #

finetune/requirements.txt

@@ -1,3 +1,3 @@
 torch==1.13.1
 pytorch_lightning==1.9.5
-deepspeed
+deepspeed==0.11.2

frontend/index.html

@@ -1,9 +1,10 @@
 <!DOCTYPE html>
 <html lang="en">
 <head>
-    <meta charset="UTF-8"/>
-    <meta content="width=device-width, initial-scale=1.0" name="viewport"/>
-    <title>RWKV-Runner</title>
+  <meta charset="UTF-8" />
+  <meta content="width=device-width, initial-scale=1.0" name="viewport" />
+  <title>RWKV-Runner</title>
+  <link href="./src/assets/images/logo.png" rel="icon" type="image/x-icon">
 </head>
 <body>
 <div id="root"></div>

frontend/package-lock.json

@@ -15,7 +15,7 @@
         "@primer/octicons-react": "^19.1.0",
         "chart.js": "^4.3.0",
         "classnames": "^2.3.2",
-        "github-markdown-css": "^5.2.0",
+        "file-saver": "^2.0.5",
         "html-midi-player": "^1.5.0",
         "i18next": "^22.4.15",
         "mobx": "^6.9.0",
@@ -37,6 +37,7 @@
         "uuid": "^9.0.0"
       },
       "devDependencies": {
+        "@types/file-saver": "^2.0.7",
         "@types/react": "^18.2.6",
         "@types/react-beautiful-dnd": "^13.1.4",
         "@types/react-dom": "^18.2.4",
@@ -74,12 +75,13 @@
       }
     },
     "node_modules/@babel/code-frame": {
-      "version": "7.22.5",
-      "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.22.5.tgz",
-      "integrity": "sha512-Xmwn266vad+6DAqEB2A6V/CcZVp62BbwVmcOJc2RPuwih1kw02TjQvWVWlcKGbBPd+8/0V5DEkOcizRGYsspYQ==",
+      "version": "7.22.13",
+      "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.22.13.tgz",
+      "integrity": "sha512-XktuhWlJ5g+3TJXc5upd9Ks1HutSArik6jf2eAjYFyIOf4ej3RN+184cZbzDvbPnuTJIUhPKKJE3cIsYTiAT3w==",
       "dev": true,
       "dependencies": {
-        "@babel/highlight": "^7.22.5"
+        "@babel/highlight": "^7.22.13",
+        "chalk": "^2.4.2"
       },
       "engines": {
         "node": ">=6.9.0"
@@ -125,12 +127,12 @@
       }
     },
     "node_modules/@babel/generator": {
-      "version": "7.22.5",
-      "resolved": "https://registry.npmjs.org/@babel/generator/-/generator-7.22.5.tgz",
-      "integrity": "sha512-+lcUbnTRhd0jOewtFSedLyiPsD5tswKkbgcezOqqWFUVNEwoUTlpPOBmvhG7OXWLR4jMdv0czPGH5XbflnD1EA==",
+      "version": "7.23.0",
+      "resolved": "https://registry.npmjs.org/@babel/generator/-/generator-7.23.0.tgz",
+      "integrity": "sha512-lN85QRR+5IbYrMWM6Y4pE/noaQtg4pNiqeNGX60eqOfo6gtEj6uw/JagelB8vVztSd7R6M5n1+PQkDbHbBRU4g==",
       "dev": true,
       "dependencies": {
-        "@babel/types": "^7.22.5",
+        "@babel/types": "^7.23.0",
         "@jridgewell/gen-mapping": "^0.3.2",
         "@jridgewell/trace-mapping": "^0.3.17",
         "jsesc": "^2.5.1"
@@ -159,22 +161,22 @@
       }
     },
     "node_modules/@babel/helper-environment-visitor": {
-      "version": "7.22.5",
-      "resolved": "https://registry.npmjs.org/@babel/helper-environment-visitor/-/helper-environment-visitor-7.22.5.tgz",
-      "integrity": "sha512-XGmhECfVA/5sAt+H+xpSg0mfrHq6FzNr9Oxh7PSEBBRUb/mL7Kz3NICXb194rCqAEdxkhPT1a88teizAFyvk8Q==",
+      "version": "7.22.20",
+      "resolved": "https://registry.npmjs.org/@babel/helper-environment-visitor/-/helper-environment-visitor-7.22.20.tgz",
+      "integrity": "sha512-zfedSIzFhat/gFhWfHtgWvlec0nqB9YEIVrpuwjruLlXfUSnA8cJB0miHKwqDnQ7d32aKo2xt88/xZptwxbfhA==",
       "dev": true,
       "engines": {
         "node": ">=6.9.0"
       }
     },
     "node_modules/@babel/helper-function-name": {
-      "version": "7.22.5",
-      "resolved": "https://registry.npmjs.org/@babel/helper-function-name/-/helper-function-name-7.22.5.tgz",
-      "integrity": "sha512-wtHSq6jMRE3uF2otvfuD3DIvVhOsSNshQl0Qrd7qC9oQJzHvOL4qQXlQn2916+CXGywIjpGuIkoyZRRxHPiNQQ==",
+      "version": "7.23.0",
+      "resolved": "https://registry.npmjs.org/@babel/helper-function-name/-/helper-function-name-7.23.0.tgz",
+      "integrity": "sha512-OErEqsrxjZTJciZ4Oo+eoZqeW9UIiOcuYKRJA4ZAgV9myA+pOXhhmpfNCKjEH/auVfEYVFJ6y1Tc4r0eIApqiw==",
       "dev": true,
       "dependencies": {
-        "@babel/template": "^7.22.5",
-        "@babel/types": "^7.22.5"
+        "@babel/template": "^7.22.15",
+        "@babel/types": "^7.23.0"
       },
       "engines": {
         "node": ">=6.9.0"
@@ -245,9 +247,9 @@
       }
     },
     "node_modules/@babel/helper-split-export-declaration": {
-      "version": "7.22.5",
-      "resolved": "https://registry.npmjs.org/@babel/helper-split-export-declaration/-/helper-split-export-declaration-7.22.5.tgz",
-      "integrity": "sha512-thqK5QFghPKWLhAV321lxF95yCg2K3Ob5yw+M3VHWfdia0IkPXUtoLH8x/6Fh486QUvzhb8YOWHChTVen2/PoQ==",
+      "version": "7.22.6",
+      "resolved": "https://registry.npmjs.org/@babel/helper-split-export-declaration/-/helper-split-export-declaration-7.22.6.tgz",
+      "integrity": "sha512-AsUnxuLhRYsisFiaJwvp1QF+I3KjD5FOxut14q/GzovUe6orHLesW2C7d754kRm53h5gqrz6sFl6sxc4BVtE/g==",
       "dev": true,
       "dependencies": {
         "@babel/types": "^7.22.5"
@@ -266,9 +268,9 @@
       }
     },
     "node_modules/@babel/helper-validator-identifier": {
-      "version": "7.22.5",
-      "resolved": "https://registry.npmjs.org/@babel/helper-validator-identifier/-/helper-validator-identifier-7.22.5.tgz",
-      "integrity": "sha512-aJXu+6lErq8ltp+JhkJUfk1MTGyuA4v7f3pA+BJ5HLfNC6nAQ0Cpi9uOquUj8Hehg0aUiHzWQbOVJGao6ztBAQ==",
+      "version": "7.22.20",
+      "resolved": "https://registry.npmjs.org/@babel/helper-validator-identifier/-/helper-validator-identifier-7.22.20.tgz",
+      "integrity": "sha512-Y4OZ+ytlatR8AI+8KZfKuL5urKp7qey08ha31L8b3BwewJAoJamTzyvxPR/5D+KkdJCGPq/+8TukHBlY10FX9A==",
       "dev": true,
       "engines": {
         "node": ">=6.9.0"
@@ -298,13 +300,13 @@
       }
     },
     "node_modules/@babel/highlight": {
-      "version": "7.22.5",
-      "resolved": "https://registry.npmjs.org/@babel/highlight/-/highlight-7.22.5.tgz",
-      "integrity": "sha512-BSKlD1hgnedS5XRnGOljZawtag7H1yPfQp0tdNJCHoH6AZ+Pcm9VvkrK59/Yy593Ypg0zMxH2BxD1VPYUQ7UIw==",
+      "version": "7.22.20",
+      "resolved": "https://registry.npmjs.org/@babel/highlight/-/highlight-7.22.20.tgz",
+      "integrity": "sha512-dkdMCN3py0+ksCgYmGG8jKeGA/8Tk+gJwSYYlFGxG5lmhfKNoAy004YpLxpS1W2J8m/EK2Ew+yOs9pVRwO89mg==",
       "dev": true,
       "dependencies": {
-        "@babel/helper-validator-identifier": "^7.22.5",
-        "chalk": "^2.0.0",
+        "@babel/helper-validator-identifier": "^7.22.20",
+        "chalk": "^2.4.2",
         "js-tokens": "^4.0.0"
       },
       "engines": {
@@ -312,9 +314,9 @@
       }
     },
     "node_modules/@babel/parser": {
-      "version": "7.22.5",
-      "resolved": "https://registry.npmjs.org/@babel/parser/-/parser-7.22.5.tgz",
-      "integrity": "sha512-DFZMC9LJUG9PLOclRC32G63UXwzqS2koQC8dkx+PLdmt1xSePYpbT/NbsrJy8Q/muXz7o/h/d4A7Fuyixm559Q==",
+      "version": "7.23.0",
+      "resolved": "https://registry.npmjs.org/@babel/parser/-/parser-7.23.0.tgz",
+      "integrity": "sha512-vvPKKdMemU85V9WE/l5wZEmImpCtLqbnTvqDS2U1fJ96KrxoW7KrXhNsNCblQlg8Ck4b85yxdTyelsMUgFUXiw==",
       "dev": true,
       "bin": {
         "parser": "bin/babel-parser.js"
@@ -365,33 +367,33 @@
       }
     },
     "node_modules/@babel/template": {
-      "version": "7.22.5",
-      "resolved": "https://registry.npmjs.org/@babel/template/-/template-7.22.5.tgz",
-      "integrity": "sha512-X7yV7eiwAxdj9k94NEylvbVHLiVG1nvzCV2EAowhxLTwODV1jl9UzZ48leOC0sH7OnuHrIkllaBgneUykIcZaw==",
+      "version": "7.22.15",
+      "resolved": "https://registry.npmjs.org/@babel/template/-/template-7.22.15.tgz",
+      "integrity": "sha512-QPErUVm4uyJa60rkI73qneDacvdvzxshT3kksGqlGWYdOTIUOwJ7RDUL8sGqslY1uXWSL6xMFKEXDS3ox2uF0w==",
       "dev": true,
       "dependencies": {
-        "@babel/code-frame": "^7.22.5",
-        "@babel/parser": "^7.22.5",
-        "@babel/types": "^7.22.5"
+        "@babel/code-frame": "^7.22.13",
+        "@babel/parser": "^7.22.15",
+        "@babel/types": "^7.22.15"
       },
       "engines": {
         "node": ">=6.9.0"
       }
     },
     "node_modules/@babel/traverse": {
-      "version": "7.22.5",
-      "resolved": "https://registry.npmjs.org/@babel/traverse/-/traverse-7.22.5.tgz",
-      "integrity": "sha512-7DuIjPgERaNo6r+PZwItpjCZEa5vyw4eJGufeLxrPdBXBoLcCJCIasvK6pK/9DVNrLZTLFhUGqaC6X/PA007TQ==",
+      "version": "7.23.2",
+      "resolved": "https://registry.npmjs.org/@babel/traverse/-/traverse-7.23.2.tgz",
+      "integrity": "sha512-azpe59SQ48qG6nu2CzcMLbxUudtN+dOM9kDbUqGq3HXUJRlo7i8fvPoxQUzYgLZ4cMVmuZgm8vvBpNeRhd6XSw==",
       "dev": true,
       "dependencies": {
-        "@babel/code-frame": "^7.22.5",
-        "@babel/generator": "^7.22.5",
-        "@babel/helper-environment-visitor": "^7.22.5",
-        "@babel/helper-function-name": "^7.22.5",
+        "@babel/code-frame": "^7.22.13",
+        "@babel/generator": "^7.23.0",
+        "@babel/helper-environment-visitor": "^7.22.20",
+        "@babel/helper-function-name": "^7.23.0",
         "@babel/helper-hoist-variables": "^7.22.5",
-        "@babel/helper-split-export-declaration": "^7.22.5",
-        "@babel/parser": "^7.22.5",
-        "@babel/types": "^7.22.5",
+        "@babel/helper-split-export-declaration": "^7.22.6",
+        "@babel/parser": "^7.23.0",
+        "@babel/types": "^7.23.0",
         "debug": "^4.1.0",
         "globals": "^11.1.0"
       },
@@ -400,13 +402,13 @@
       }
     },
     "node_modules/@babel/types": {
-      "version": "7.22.5",
-      "resolved": "https://registry.npmjs.org/@babel/types/-/types-7.22.5.tgz",
-      "integrity": "sha512-zo3MIHGOkPOfoRXitsgHLjEXmlDaD/5KU1Uzuc9GNiZPhSqVxVRtxuPaSBZDsYZ9qV88AjtMtWW7ww98loJ9KA==",
+      "version": "7.23.0",
+      "resolved": "https://registry.npmjs.org/@babel/types/-/types-7.23.0.tgz",
+      "integrity": "sha512-0oIyUfKoI3mSqMvsxBdclDwxXKXAUA8v/apZbc+iSyARYou1o8ZGDxbUYyLFoW2arqS2jDGqJuZvv1d/io1axg==",
       "dev": true,
       "dependencies": {
         "@babel/helper-string-parser": "^7.22.5",
-        "@babel/helper-validator-identifier": "^7.22.5",
+        "@babel/helper-validator-identifier": "^7.22.20",
         "to-fast-properties": "^2.0.0"
       },
       "engines": {
@@ -2279,6 +2281,12 @@
         "@types/ms": "*"
       }
     },
+    "node_modules/@types/file-saver": {
+      "version": "2.0.7",
+      "resolved": "https://registry.npmjs.org/@types/file-saver/-/file-saver-2.0.7.tgz",
+      "integrity": "sha512-dNKVfHd/jk0SkR/exKGj2ggkB45MAkzvWCaqLUUgkyjITkGNzH8H+yUwr+BLJUBjZOe9w8X3wgmXhZDRg1ED6A==",
+      "dev": true
+    },
     "node_modules/@types/hast": {
       "version": "2.3.4",
       "resolved": "https://registry.npmmirror.com/@types/hast/-/hast-2.3.4.tgz",
@@ -2288,9 +2296,9 @@
       }
     },
     "node_modules/@types/hoist-non-react-statics": {
-      "version": "3.3.1",
-      "resolved": "https://registry.npmjs.org/@types/hoist-non-react-statics/-/hoist-non-react-statics-3.3.1.tgz",
-      "integrity": "sha512-iMIqiko6ooLrTh1joXodJK5X9xeEALT1kM5G3ZLhD3hszxBdIEd5C75U834D9mLcINgD4OyZf5uQXjkuYydWvA==",
+      "version": "3.3.5",
+      "resolved": "https://registry.npmjs.org/@types/hoist-non-react-statics/-/hoist-non-react-statics-3.3.5.tgz",
+      "integrity": "sha512-SbcrWzkKBw2cdwRTwQAswfpB9g9LJWfjtUeW/jvNwbhC8cpmmNYVePa+ncbUe0rGTQ7G3Ff6mYUN2VMfLVr+Sg==",
       "dependencies": {
         "@types/react": "*",
         "hoist-non-react-statics": "^3.3.0"
@@ -2371,9 +2379,9 @@
       }
     },
     "node_modules/@types/react-redux": {
-      "version": "7.1.25",
-      "resolved": "https://registry.npmjs.org/@types/react-redux/-/react-redux-7.1.25.tgz",
-      "integrity": "sha512-bAGh4e+w5D8dajd6InASVIyCo4pZLJ66oLb80F9OBLO1gKESbZcRCJpTT6uLXX+HAB57zw1WTdwJdAsewuTweg==",
+      "version": "7.1.29",
+      "resolved": "https://registry.npmjs.org/@types/react-redux/-/react-redux-7.1.29.tgz",
+      "integrity": "sha512-orHCOWqBBQ1LP1uD6JVdXL+ZRTEWhGGne+VOPcXef03rC+QYdzktLhxR3ozymPDyZK0CNCUuQs9tyQhfg1ku+w==",
       "dependencies": {
         "@types/hoist-non-react-statics": "^3.3.0",
         "@types/react": "*",
@@ -2649,10 +2657,24 @@
       }
     },
     "node_modules/caniuse-lite": {
-      "version": "1.0.30001482",
-      "resolved": "https://registry.npmmirror.com/caniuse-lite/-/caniuse-lite-1.0.30001482.tgz",
-      "integrity": "sha512-F1ZInsg53cegyjroxLNW9DmrEQ1SuGRTO1QlpA0o2/6OpQ0gFeDRoq1yFmnr8Sakn9qwwt9DmbxHB6w167OSuQ==",
-      "dev": true
+      "version": "1.0.30001561",
+      "resolved": "https://registry.npmjs.org/caniuse-lite/-/caniuse-lite-1.0.30001561.tgz",
+      "integrity": "sha512-NTt0DNoKe958Q0BE0j0c1V9jbUzhBxHIEJy7asmGrpE0yG63KTV7PLHPnK2E1O9RsQrQ081I3NLuXGS6zht3cw==",
+      "dev": true,
+      "funding": [
+        {
+          "type": "opencollective",
+          "url": "https://opencollective.com/browserslist"
+        },
+        {
+          "type": "tidelift",
+          "url": "https://tidelift.com/funding/github/npm/caniuse-lite"
+        },
+        {
+          "type": "github",
+          "url": "https://github.com/sponsors/ai"
+        }
+      ]
     },
     "node_modules/ccount": {
       "version": "2.0.1",
@@ -3232,6 +3254,11 @@
       "resolved": "https://registry.npmjs.org/fft.js/-/fft.js-4.0.4.tgz",
       "integrity": "sha512-f9c00hphOgeQTlDyavwTtu6RiK8AIFjD6+jvXkNkpeQ7rirK3uFWVpalkoS4LAwbdX7mfZ8aoBfFVQX1Re/8aw=="
     },
+    "node_modules/file-saver": {
+      "version": "2.0.5",
+      "resolved": "https://registry.npmjs.org/file-saver/-/file-saver-2.0.5.tgz",
+      "integrity": "sha512-P9bmyZ3h/PRG+Nzga+rbdI4OEpNDzAVyy74uVO9ATgzLK6VtAsYybF/+TOCvrc0MO793d6+42lLyZTw7/ArVzA=="
+    },
     "node_modules/fill-range": {
       "version": "7.0.1",
       "resolved": "https://registry.npmmirror.com/fill-range/-/fill-range-7.0.1.tgz",
@@ -3316,11 +3343,6 @@
         "node": "6.* || 8.* || >= 10.*"
       }
     },
-    "node_modules/github-markdown-css": {
-      "version": "5.2.0",
-      "resolved": "https://registry.npmmirror.com/github-markdown-css/-/github-markdown-css-5.2.0.tgz",
-      "integrity": "sha512-hq5RaCInSUZ48bImOZpkppW2/MT44StRgsbsZ8YA4vJFwLKB/Vo3k7R2t+pUGqO+ThG0QDMi96TewV/B3vyItg=="
-    },
     "node_modules/glob": {
       "version": "7.1.6",
       "resolved": "https://registry.npmmirror.com/glob/-/glob-7.1.6.tgz",
@@ -4591,10 +4613,24 @@
       }
     },
     "node_modules/postcss": {
-      "version": "8.4.23",
-      "resolved": "https://registry.npmmirror.com/postcss/-/postcss-8.4.23.tgz",
-      "integrity": "sha512-bQ3qMcpF6A/YjR55xtoTr0jGOlnPOKAIMdOWiv0EIT6HVPEaJiJB4NLljSbiHoC2RX7DN5Uvjtpbg1NPdwv1oA==",
+      "version": "8.4.31",
+      "resolved": "https://registry.npmjs.org/postcss/-/postcss-8.4.31.tgz",
+      "integrity": "sha512-PS08Iboia9mts/2ygV3eLpY5ghnUcfLV/EXTOW1E2qYxJKGGBUtNjN76FYHnMs36RmARn41bC0AZmn+rR0OVpQ==",
       "dev": true,
+      "funding": [
+        {
+          "type": "opencollective",
+          "url": "https://opencollective.com/postcss/"
+        },
+        {
+          "type": "tidelift",
+          "url": "https://tidelift.com/funding/github/npm/postcss"
+        },
+        {
+          "type": "github",
+          "url": "https://github.com/sponsors/ai"
+        }
+      ],
       "dependencies": {
         "nanoid": "^3.3.6",
         "picocolors": "^1.0.0",
@@ -4696,9 +4732,9 @@
       "integrity": "sha512-kma4U7AFCTwpqq5twzC1YVIDXSqg6qQK6JN0smOw8fgRy1OkMi0CYSzFmsy6dnqSenamAtj0CyXMUJ1Mf6oROg=="
     },
     "node_modules/protobufjs": {
-      "version": "6.11.3",
-      "resolved": "https://registry.npmjs.org/protobufjs/-/protobufjs-6.11.3.tgz",
-      "integrity": "sha512-xL96WDdCZYdU7Slin569tFX712BxsxslWwAfAhCYjQKGTq7dAU91Lomy6nLLhh/dyGhk/YH4TwTSRxTzhuHyZg==",
+      "version": "6.11.4",
+      "resolved": "https://registry.npmjs.org/protobufjs/-/protobufjs-6.11.4.tgz",
+      "integrity": "sha512-5kQWPaJHi1WoCpjTGszzQ32PG2F4+wRY6BmAT4Vfw56Q2FZ4YZzK20xUYQH4YkfehY1e6QSICrJquM6xXZNcrw==",
       "hasInstallScript": true,
       "dependencies": {
         "@protobufjs/aspromise": "^1.1.2",

frontend/package.json

@@ -16,7 +16,7 @@
     "@primer/octicons-react": "^19.1.0",
     "chart.js": "^4.3.0",
     "classnames": "^2.3.2",
-    "github-markdown-css": "^5.2.0",
+    "file-saver": "^2.0.5",
     "html-midi-player": "^1.5.0",
     "i18next": "^22.4.15",
     "mobx": "^6.9.0",
@@ -38,6 +38,7 @@
     "uuid": "^9.0.0"
   },
   "devDependencies": {
+    "@types/file-saver": "^2.0.7",
     "@types/react": "^18.2.6",
     "@types/react-beautiful-dnd": "^13.1.4",
     "@types/react-dom": "^18.2.4",

frontend/src/App.tsx

@@ -26,18 +26,22 @@
 import { FluentProvider, Tab, TabList, webDarkTheme, webLightTheme } from '@fluentui/react-components';
 import { FC, useEffect, useState } from 'react';
 import { Route, Routes, useLocation, useNavigate } from 'react-router';
-import { pages } from './pages';
+import { pages as clientPages } from './pages';
 import { useMediaQuery } from 'usehooks-ts';
 import commonStore from './stores/commonStore';
 import { observer } from 'mobx-react-lite';
 import { useTranslation } from 'react-i18next';
 import { CustomToastContainer } from './components/CustomToastContainer';
+import { LazyImportComponent } from './components/LazyImportComponent';
 
 const App: FC = observer(() => {
   const { t } = useTranslation();
   const navigate = useNavigate();
   const location = useLocation();
   const mq = useMediaQuery('(min-width: 640px)');
+  const pages = commonStore.platform === 'web' ? clientPages.filter(page =>
+    !['/configs', '/models', '/downloads', '/train', '/about'].some(path => page.path === path)
+  ) : clientPages;
 
   const [path, setPath] = useState<string>(pages[0].path);
 
@@ -47,10 +51,10 @@ const App: FC = observer(() => {
   useEffect(() => setPath(location.pathname), [location]);
 
   return (
-    <FluentProvider className="h-screen"
+    <FluentProvider
       theme={commonStore.settings.darkMode ? webDarkTheme : webLightTheme}
       data-theme={commonStore.settings.darkMode ? 'dark' : 'light'}>
-      <div className="flex h-full">
+      <div className="flex h-screen">
         <div className="flex flex-col w-16 sm:w-48 p-2 justify-between">
           <TabList
             size="large"
@@ -82,7 +86,7 @@ const App: FC = observer(() => {
         <div className="h-full w-full p-2 box-border overflow-y-hidden">
           <Routes>
             {pages.map(({ path, element }, index) => (
-              <Route key={`${path}-${index}`} path={path} element={element} />
+              <Route key={`${path}-${index}`} path={path} element={<LazyImportComponent lazyChildren={element} />} />
             ))}
           </Routes>
         </div>

frontend/src/_locales/ja/main.json

@@ -13,7 +13,7 @@
   "Working": "動作中",
   "Stop": "停止",
   "Enable High Precision For Last Layer": "最後の層で高精度を有効にする",
-  "Stored Layers": "メモリ層読み込み",
+  "Stored Layers": "保存されるレイヤー",
   "Precision": "精度",
   "Device": "デバイス",
   "Convert model with these configs. Using a converted model will greatly improve the loading speed, but model parameters of the converted model cannot be modified.": "これらの設定でモデルを変換します。変換されたモデルを使用すると、読み込み速度が大幅に向上しますが、変換したモデルのパラメータを変更することはできません。",
@@ -100,7 +100,7 @@
   "Model Config Exception": "モデル設定例外",
   "Use Gitee Updates Source": "Gitee更新ソースを使用",
   "Use Custom CUDA kernel to Accelerate": "カスタムCUDAカーネルを使用して加速",
-  "Enabling this option can greatly improve inference speed and save some VRAM, but there may be compatibility issues. If it fails to start, please turn off this option.": "このオプションを有効にすると、推論速度が大幅に向上し、一部のVRAMを節約できますが、互換性の問題が生じる可能性があります。起動に失敗した場合は、このオプションをオフにしてください。",
+  "Enabling this option can greatly improve inference speed and save some VRAM, but there may be compatibility issues (output garbled). If it fails to start, please turn off this option, or try to upgrade your gpu driver.": "このオプションを有効にすると、推論速度が大幅に向上し、一部のVRAMを節約できますが、互換性の問題 (文字化けを出力する) が生じる可能性があります。起動に失敗した場合は、このオプションを無効にするか、GPUドライバーをアップグレードしてみてください。",
   "Supported custom cuda file not found": "対応しているカスタムCUDAファイルが見つかりません",
   "Failed to copy custom cuda file": "カスタムCUDAファイルのコピーに失敗しました",
   "Downloading update, please wait. If it is not completed, please manually download the program from GitHub and replace the original program.": "更新をダウンロード中です、お待ちください。完了しない場合は、GitHubから手動でプログラムをダウンロードし、元のプログラムを置き換えてください。",
@@ -226,14 +226,14 @@
   "Please select a LoRA model": "LoRAモデルを選択してください",
   "You are using sample data for training. For formal training, please make sure to create your own jsonl file.": "トレーニングにはサンプルデータを使用しています。正式なトレーニングのためには、自身でjsonlファイルを作成してください。",
   "WSL is not running, please retry. If it keeps happening, it means you may be using an outdated version of WSL, run \"wsl --update\" to update.": "WSLが実行されていません、もう一度試してください。これが続く場合、古いバージョンのWSLを使用している可能性があります。\"wsl --update\"を実行して更新してください。",
-  "Memory is not enough, try to increase the virtual memory or use a smaller base model.": "メモリが不足しています、仮想メモリを増やすか小さなベースモデルを使用してみてください。",
+  "Memory is not enough, try to increase the virtual memory (Swap of WSL) or use a smaller base model.": "メモリが不足しています、仮想メモリ (WSL Swap) を増やすか小さなベースモデルを使用してみてください。",
   "VRAM is not enough": "ビデオRAMが不足しています",
   "Training data is not enough, reduce context length or add more data for training": "トレーニングデータが不足しています、コンテキストの長さを減らすか、トレーニング用のデータをさらに追加してください",
   "You are using WSL 1 for training, please upgrade to WSL 2. e.g. Run \"wsl --set-version Ubuntu-22.04 2\"": "トレーニングにWSL 1を使用しています、WSL 2にアップグレードしてください。例:\"wsl --set-version Ubuntu-22.04 2\"を実行する",
   "Matched CUDA is not installed": "対応するCUDAがインストールされていません",
   "Failed to convert data": "データの変換に失敗しました",
   "Failed to merge model": "モデルのマージに失敗しました",
-  "The data path should be a directory or a file in jsonl format (more formats will be supported in the future).\n\nWhen you provide a directory path, all the txt files within that directory will be automatically converted into training data. This is commonly used for large-scale training in writing, code generation, or knowledge bases.\n\nThe jsonl format file can be referenced at https://github.com/Abel2076/json2binidx_tool/blob/main/sample.jsonl.\nYou can also write it similar to OpenAI's playground format, as shown in https://platform.openai.com/playground/p/default-chat.\nEven for multi-turn conversations, they must be written in a single line using `\\n` to indicate line breaks. If they are different dialogues or topics, they should be written in separate lines.": "データのパスはディレクトリまたはjsonl形式のファイルでなければなりません（将来的にはより多くの形式がサポートされる予定です）。ディレクトリパスを提供した場合、そのディレクトリ内のすべてのtxtファイルが自動的にトレーニングデータに変換されます。これは大規模なライティング、コード生成、または知識ベースのトレーニングで一般的に使用されます。jsonl形式のファイルは、https://github.com/Abel2076/json2binidx_tool/blob/main/sample.jsonl を参照してください。\nhttps://platform.openai.com/playground/p/default-chat のように、OpenAIのプレイグラウンド形式に似た形式で書くこともできます。複数ターンの対話であっても、一行で書く必要があり、行の区切りを示すために`\\n`を使用します。それらが異なる対話やトピックであれば、それらは別々の行に書かれるべきです。",
+  "The data path should be a directory or a file in jsonl format (more formats will be supported in the future).\n\nWhen you provide a directory path, all the txt files within that directory will be automatically converted into training data. This is commonly used for large-scale training in writing, code generation, or knowledge bases.\n\nThe jsonl format file can be referenced at https://github.com/josStorer/RWKV-Runner/blob/master/finetune/data/sample.jsonl.\nYou can also write it similar to OpenAI's playground format, as shown in https://platform.openai.com/playground/p/default-chat.\nEven for multi-turn conversations, they must be written in a single line using `\\n` to indicate line breaks. If they are different dialogues or topics, they should be written in separate lines.": "データのパスはディレクトリまたはjsonl形式のファイルでなければなりません（将来的にはより多くの形式がサポートされる予定です）。ディレクトリパスを提供した場合、そのディレクトリ内のすべてのtxtファイルが自動的にトレーニングデータに変換されます。これは大規模なライティング、コード生成、または知識ベースのトレーニングで一般的に使用されます。jsonl形式のファイルは、https://github.com/josStorer/RWKV-Runner/blob/master/finetune/data/sample.jsonl を参照してください。\nhttps://platform.openai.com/playground/p/default-chat のように、OpenAIのプレイグラウンド形式に似た形式で書くこともできます。複数ターンの対話であっても、一行で書く必要があり、行の区切りを示すために`\\n`を使用します。それらが異なる対話やトピックであれば、それらは別々の行に書かれるべきです。",
   "Size mismatch for blocks. You are attempting to continue training from the LoRA model, but it does not match the base model. Please set LoRA model to None.": "ブロックのサイズが一致しません。LoRAモデルからトレーニングを続けようとしていますが、それはベースモデルと一致しません。LoRAモデルをNoneに設定してください。",
   "Instruction: Write a story using the following information\n\nInput: A man named Alex chops a tree down\n\nResponse:": "Instruction: Write a story using the following information\n\nInput: アレックスという男が木を切り倒す\n\nResponse:",
   "Composition": "作曲",
@@ -248,5 +248,25 @@
   "Preview Only": "プレビューのみ",
   "RAM": "RAM",
   "VRAM": "VRAM",
-  "GPU Usage": "GPU使用率"
+  "GPU Usage": "GPU使用率",
+  "Use Custom Tokenizer": "カスタムトークナイザーを使用する",
+  "Tokenizer Path (e.g. backend-python/rwkv_pip/20B_tokenizer.json)": "トークナイザーパス (例: backend-python/rwkv_pip/20B_tokenizer.json)",
+  "User Name": "ユーザー名",
+  "Assistant Name": "アシスタント名",
+  "Insert default system prompt at the beginning": "最初にデフォルトのシステムプロンプトを挿入",
+  "Format Content": "内容フォーマットの規格化",
+  "Add An Attachment (Accepts pdf, txt)": "添付ファイルを追加 (pdf, txtを受け付けます)",
+  "Uploading Attachment": "添付ファイルアップロード中",
+  "Remove Attachment": "添付ファイルを削除",
+  "The content of file": "ファイル",
+  "is as follows. When replying to me, consider the file content and respond accordingly:": "の内容は以下の通りです。私に返信する際は、ファイルの内容を考慮して適切に返信してください:",
+  "What's the file name": "ファイル名は何ですか",
+  "The file name is: ": "ファイル名は次のとおりです: ",
+  "Port is occupied. Change it in Configs page or close the program that occupies the port.": "ポートが占有されています。設定ページで変更するか、ポートを占有しているプログラムを終了してください。",
+  "Loading...": "読み込み中...",
+  "Hello, what can I do for you?": "こんにちは、何かお手伝いできますか？",
+  "Enable WebUI": "WebUIを有効化",
+  "Server is working on deployment mode, please close the terminal window manually": "サーバーはデプロイモードで動作しています、ターミナルウィンドウを手動で閉じてください",
+  "Server is working on deployment mode, please exit the program manually to stop the server": "サーバーはデプロイモードで動作しています、サーバーを停止するにはプログラムを手動で終了してください",
+  "You can increase the number of stored layers in Configs page to improve performance": "パフォーマンスを向上させるために、保存されるレイヤーの数を設定ページで増やすことができます"
 }

frontend/src/_locales/zh-hans/main.json

@@ -100,7 +100,7 @@
   "Model Config Exception": "模型配置异常",
   "Use Gitee Updates Source": "使用Gitee更新源",
   "Use Custom CUDA kernel to Accelerate": "使用自定义CUDA算子加速",
-  "Enabling this option can greatly improve inference speed and save some VRAM, but there may be compatibility issues. If it fails to start, please turn off this option.": "开启这个选项能大大提升推理速度并节省显存，但可能存在兼容性问题，如果启动失败，请关闭此选项",
+  "Enabling this option can greatly improve inference speed and save some VRAM, but there may be compatibility issues (output garbled). If it fails to start, please turn off this option, or try to upgrade your gpu driver.": "开启这个选项能大大提升推理速度并节省显存，但可能存在兼容性(回复乱码)问题，如果发生相关问题，请关闭此选项。或更新你的显卡驱动",
   "Supported custom cuda file not found": "没有找到支持的自定义cuda文件",
   "Failed to copy custom cuda file": "自定义cuda文件复制失败",
   "Downloading update, please wait. If it is not completed, please manually download the program from GitHub and replace the original program.": "正在下载更新，请等待。如果一直未完成，请从Github手动下载并覆盖原程序",
@@ -226,14 +226,14 @@
   "Please select a LoRA model": "请选择一个LoRA模型",
   "You are using sample data for training. For formal training, please make sure to create your own jsonl file.": "你正在使用示例数据训练，对于正式训练场合，请务必创建你自己的jsonl训练数据",
   "WSL is not running, please retry. If it keeps happening, it means you may be using an outdated version of WSL, run \"wsl --update\" to update.": "WSL没有运行，请重试。如果一直出现此错误，意味着你可能正在使用旧版本的WSL，请在cmd执行\"wsl --update\"以更新",
-  "Memory is not enough, try to increase the virtual memory or use a smaller base model.": "内存不足，尝试增加虚拟内存，或使用一个更小规模的基底模型",
+  "Memory is not enough, try to increase the virtual memory (Swap of WSL) or use a smaller base model.": "内存不足，尝试增加虚拟内存(WSL Swap)，或使用一个更小规模的基底模型",
   "VRAM is not enough": "显存不足",
   "Training data is not enough, reduce context length or add more data for training": "训练数据不足，请减小上下文长度或增加训练数据",
   "You are using WSL 1 for training, please upgrade to WSL 2. e.g. Run \"wsl --set-version Ubuntu-22.04 2\"": "你正在使用WSL 1进行训练，请升级到WSL 2。例如，运行\"wsl --set-version Ubuntu-22.04 2\"",
   "Matched CUDA is not installed": "未安装匹配的CUDA",
   "Failed to convert data": "数据转换失败",
   "Failed to merge model": "合并模型失败",
-  "The data path should be a directory or a file in jsonl format (more formats will be supported in the future).\n\nWhen you provide a directory path, all the txt files within that directory will be automatically converted into training data. This is commonly used for large-scale training in writing, code generation, or knowledge bases.\n\nThe jsonl format file can be referenced at https://github.com/Abel2076/json2binidx_tool/blob/main/sample.jsonl.\nYou can also write it similar to OpenAI's playground format, as shown in https://platform.openai.com/playground/p/default-chat.\nEven for multi-turn conversations, they must be written in a single line using `\\n` to indicate line breaks. If they are different dialogues or topics, they should be written in separate lines.": "数据路径必须是一个文件夹，或者jsonl格式文件 (未来会支持更多格式)\n\n当你填写的路径是一个文件夹时，该文件夹内的所有txt文件会被自动转换为训练数据，通常这用于大批量训练写作，代码生成或知识库\n\njsonl文件的格式参考 https://github.com/Abel2076/json2binidx_tool/blob/main/sample.jsonl\n你也可以仿照openai的playground编写，参考 https://platform.openai.com/playground/p/default-chat\n即使是多轮对话也必须写在一行，用`\\n`表示换行，如果是不同对话或主题，则另起一行",
+  "The data path should be a directory or a file in jsonl format (more formats will be supported in the future).\n\nWhen you provide a directory path, all the txt files within that directory will be automatically converted into training data. This is commonly used for large-scale training in writing, code generation, or knowledge bases.\n\nThe jsonl format file can be referenced at https://github.com/josStorer/RWKV-Runner/blob/master/finetune/data/sample.jsonl.\nYou can also write it similar to OpenAI's playground format, as shown in https://platform.openai.com/playground/p/default-chat.\nEven for multi-turn conversations, they must be written in a single line using `\\n` to indicate line breaks. If they are different dialogues or topics, they should be written in separate lines.": "数据路径必须是一个文件夹，或者jsonl格式文件 (未来会支持更多格式)\n\n当你填写的路径是一个文件夹时，该文件夹内的所有txt文件会被自动转换为训练数据，通常这用于大批量训练写作，代码生成或知识库\n\njsonl文件的格式参考 https://github.com/josStorer/RWKV-Runner/blob/master/finetune/data/sample.jsonl 以及 https://zhuanlan.zhihu.com/p/643433851\n你也可以仿照openai的playground编写，参考 https://platform.openai.com/playground/p/default-chat\n即使是多轮对话也必须写在一行，用`\\n`表示换行，如果是不同对话或主题，则另起一行",
   "Size mismatch for blocks. You are attempting to continue training from the LoRA model, but it does not match the base model. Please set LoRA model to None.": "尺寸不匹配块。你正在尝试从LoRA模型继续训练，但该LoRA模型与基底模型不匹配，请将LoRA模型设为空",
   "Instruction: Write a story using the following information\n\nInput: A man named Alex chops a tree down\n\nResponse:": "Instruction: Write a story using the following information\n\nInput: 艾利克斯砍倒了一棵树\n\nResponse:",
   "Composition": "作曲",
@@ -248,5 +248,25 @@
   "Preview Only": "仅预览",
   "RAM": "内存",
   "VRAM": "显存",
-  "GPU Usage": "GPU占用"
+  "GPU Usage": "GPU占用",
+  "Use Custom Tokenizer": "使用自定义Tokenizer",
+  "Tokenizer Path (e.g. backend-python/rwkv_pip/20B_tokenizer.json)": "Tokenizer路径 (例如: backend-python/rwkv_pip/20B_tokenizer.json)",
+  "User Name": "用户名称",
+  "Assistant Name": "AI名称",
+  "Insert default system prompt at the beginning": "在开头自动插入默认系统提示",
+  "Format Content": "规范格式",
+  "Add An Attachment (Accepts pdf, txt)": "添加一个附件 (支持pdf, txt)",
+  "Uploading Attachment": "正在上传附件",
+  "Remove Attachment": "移除附件",
+  "The content of file": "文件",
+  "is as follows. When replying to me, consider the file content and respond accordingly:": "内容如下。回复时考虑文件内容并做出相应回复:",
+  "What's the file name": "文件名是什么",
+  "The file name is: ": "文件名是：",
+  "Port is occupied. Change it in Configs page or close the program that occupies the port.": "端口被占用。请在配置页面更改端口，或关闭占用端口的程序",
+  "Loading...": "加载中...",
+  "Hello, what can I do for you?": "你好，有什么要我帮忙的吗？",
+  "Enable WebUI": "启用WebUI",
+  "Server is working on deployment mode, please close the terminal window manually": "服务器正在部署模式下运行，请手动关闭终端窗口",
+  "Server is working on deployment mode, please exit the program manually to stop the server": "服务器正在部署模式下运行，请手动退出程序以停止服务器",
+  "You can increase the number of stored layers in Configs page to improve performance": "你可以在配置页面增加载入显存层数以提升性能"
 }

frontend/src/components/DialogButton.tsx

@@ -1,4 +1,4 @@
-import { FC, ReactElement } from 'react';
+import React, { FC, ReactElement } from 'react';
 import {
   Button,
   Dialog,
@@ -11,7 +11,9 @@ import {
 } from '@fluentui/react-components';
 import { ToolTipButton } from './ToolTipButton';
 import { useTranslation } from 'react-i18next';
-import MarkdownRender from './MarkdownRender';
+import { LazyImportComponent } from './LazyImportComponent';
+
+const MarkdownRender = React.lazy(() => import('./MarkdownRender'));
 
 export const DialogButton: FC<{
   text?: string | null
@@ -45,7 +47,9 @@ export const DialogButton: FC<{
         <DialogContent>
           {
             markdown ?
-              <MarkdownRender>{contentText}</MarkdownRender> :
+              <LazyImportComponent lazyChildren={MarkdownRender}>
+                {contentText}
+              </LazyImportComponent> :
               contentText
           }
         </DialogContent>

frontend/src/components/LazyImportComponent.tsx

@@ -0,0 +1,20 @@
+import { FC, LazyExoticComponent, ReactNode, Suspense } from 'react';
+import { useTranslation } from 'react-i18next';
+
+interface LazyImportComponentProps {
+  lazyChildren: LazyExoticComponent<FC<any>>;
+  lazyProps?: any;
+  children?: ReactNode;
+}
+
+export const LazyImportComponent: FC<LazyImportComponentProps> = (props) => {
+  const { t } = useTranslation();
+
+  return (
+    <Suspense fallback={<div>{t('Loading...')}</div>}>
+      <props.lazyChildren {...props.lazyProps}>
+        {props.children}
+      </props.lazyChildren>
+    </Suspense>
+  );
+};

frontend/src/components/MarkdownRender.tsx

@@ -21,7 +21,7 @@ const Hyperlink: FC<any> = ({ href, children }) => {
   );
 };
 
-export const MarkdownRender: FC<ReactMarkdownOptions> = (props) => {
+const MarkdownRender: FC<ReactMarkdownOptions> = (props) => {
   return (
     <div dir="auto" className="markdown-body">
       <ReactMarkdown

frontend/src/components/ReadButton.tsx

@@ -40,6 +40,8 @@ export const ReadButton: FC<{
       voice = voices.find((v) => v.name.toLowerCase().includes('microsoft aria'));
     else if (lang === 'zh')
       voice = voices.find((v) => v.name.toLowerCase().includes('xiaoyi'));
+    else if (lang === 'ja')
+      voice = voices.find((v) => v.name.toLowerCase().includes('nanami'));
     if (!voice) voice = voices.find((v) => v.lang.substring(0, 2) === lang);
     if (!voice) voice = voices.find((v) => v.lang === navigator.language);
 

frontend/src/components/RunButton.tsx

@@ -2,8 +2,8 @@ import React, { FC, MouseEventHandler, ReactElement } from 'react';
 import commonStore, { ModelStatus } from '../stores/commonStore';
 import {
   AddToDownloadList,
-  CopyFile,
   FileExists,
+  IsPortAvailable,
   StartServer,
   StartWebGPUServer
 } from '../../wailsjs/go/backend_golang/App';
@@ -11,12 +11,12 @@ import { Button } from '@fluentui/react-components';
 import { observer } from 'mobx-react-lite';
 import { exit, getStatus, readRoot, switchModel, updateConfig } from '../apis';
 import { toast } from 'react-toastify';
-import { checkDependencies, getStrategy, getSupportedCustomCudaFile, toastWithButton } from '../utils';
+import { checkDependencies, getStrategy, toastWithButton } from '../utils';
 import { useTranslation } from 'react-i18next';
 import { ToolTipButton } from './ToolTipButton';
 import { Play16Regular, Stop16Regular } from '@fluentui/react-icons';
 import { useNavigate } from 'react-router';
-import { WindowShow } from '../../wailsjs/runtime/runtime';
+import { WindowShow } from '../../wailsjs/runtime';
 
 const mainButtonText = {
   [ModelStatus.Offline]: 'Run',
@@ -113,15 +113,23 @@ export const RunButton: FC<{ onClickRun?: MouseEventHandler, iconMode?: boolean
 
       const port = modelConfig.apiParameters.apiPort;
 
-      await exit(1000).catch(() => {
-      });
+      if (!await IsPortAvailable(port)) {
+        await exit(1000).catch(() => {
+        });
+        if (!await IsPortAvailable(port)) {
+          toast(t('Port is occupied. Change it in Configs page or close the program that occupies the port.'), { type: 'error' });
+          commonStore.setStatus({ status: ModelStatus.Offline });
+          return;
+        }
+      }
 
       const startServer = webgpu ?
         (_: string, port: number, host: string) => StartWebGPUServer(port, host)
         : StartServer;
+      const isUsingCudaBeta = modelConfig.modelParameters.device === 'CUDA-Beta';
 
       startServer(commonStore.settings.customPythonPath, port, commonStore.settings.host !== '127.0.0.1' ? '0.0.0.0' : '127.0.0.1',
-        modelConfig.modelParameters.device === 'CUDA-Beta'
+        !!modelConfig.enableWebUI, isUsingCudaBeta
       ).catch((e) => {
         const errMsg = e.message || e;
         if (errMsg.includes('path contains space'))
@@ -162,22 +170,26 @@ export const RunButton: FC<{ onClickRun?: MouseEventHandler, iconMode?: boolean
             if ((modelConfig.modelParameters.device.includes('CUDA') || modelConfig.modelParameters.device === 'Custom')
               && modelConfig.modelParameters.useCustomCuda && !strategy.includes('fp32')) {
               if (commonStore.platform === 'windows') {
-                customCudaFile = getSupportedCustomCudaFile();
-                if (customCudaFile) {
-                  FileExists('./py310/Lib/site-packages/rwkv/model.py').then((exist) => {
-                    // defensive measure. As Python has already been launched, will only take effect the next time it runs.
-                    if (!exist) CopyFile('./backend-python/wkv_cuda_utils/wkv_cuda_model.py', './py310/Lib/site-packages/rwkv/model.py');
-                  });
-                  await CopyFile(customCudaFile, './py310/Lib/site-packages/rwkv/wkv_cuda.pyd').catch(() => {
-                    FileExists('./py310/Lib/site-packages/rwkv/wkv_cuda.pyd').then((exist) => {
-                      if (!exist) {
-                        customCudaFile = '';
-                        toast(t('Failed to copy custom cuda file'), { type: 'error' });
-                      }
-                    });
-                  });
-                } else
-                  toast(t('Supported custom cuda file not found'), { type: 'warning' });
+                // this part is currently unused because there's no longer a need to use different kernels for different GPUs, but it might still be needed in the future
+                //
+                // customCudaFile = getSupportedCustomCudaFile(isUsingCudaBeta);
+                // if (customCudaFile) {
+                //   let kernelTargetPath: string;
+                //   if (isUsingCudaBeta)
+                //     kernelTargetPath = './backend-python/rwkv_pip/beta/wkv_cuda.pyd';
+                //   else
+                //     kernelTargetPath = './backend-python/rwkv_pip/wkv_cuda.pyd';
+                //   await CopyFile(customCudaFile, kernelTargetPath).catch(() => {
+                //     FileExists(kernelTargetPath).then((exist) => {
+                //       if (!exist) {
+                //         customCudaFile = '';
+                //         toast(t('Failed to copy custom cuda file'), { type: 'error' });
+                //       }
+                //     });
+                //   });
+                // } else
+                //   toast(t('Supported custom cuda file not found'), { type: 'warning' });
+                customCudaFile = 'any';
               } else {
                 customCudaFile = 'any';
               }
@@ -186,7 +198,9 @@ export const RunButton: FC<{ onClickRun?: MouseEventHandler, iconMode?: boolean
             switchModel({
               model: modelPath,
               strategy: strategy,
-              customCuda: customCudaFile !== ''
+              tokenizer: modelConfig.modelParameters.useCustomTokenizer ? modelConfig.modelParameters.customTokenizer : undefined,
+              customCuda: customCudaFile !== '',
+              deploy: modelConfig.enableWebUI
             }).then(async (r) => {
               if (r.ok) {
                 commonStore.setStatus({ status: ModelStatus.Working });
@@ -199,6 +213,12 @@ export const RunButton: FC<{ onClickRun?: MouseEventHandler, iconMode?: boolean
                 const buttonFn = () => {
                   navigate({ pathname: '/' + buttonName.toLowerCase() });
                 };
+
+                if ((modelConfig.modelParameters.device === 'CUDA' || modelConfig.modelParameters.device === 'CUDA-Beta') &&
+                  modelConfig.modelParameters.storedLayers < modelConfig.modelParameters.maxStoredLayers &&
+                  commonStore.monitorData && commonStore.monitorData.totalVram !== 0 &&
+                  (commonStore.monitorData.usedVram / commonStore.monitorData.totalVram) < 0.85)
+                  toast(t('You can increase the number of stored layers in Configs page to improve performance'), { type: 'info' });
                 toastWithButton(t('Startup Completed'), t(buttonName), buttonFn, { type: 'success', autoClose: 3000 });
               } else if (r.status === 304) {
                 toast(t('Loading Model'), { type: 'info' });
@@ -233,7 +253,13 @@ export const RunButton: FC<{ onClickRun?: MouseEventHandler, iconMode?: boolean
       }, 1000);
     } else {
       commonStore.setStatus({ status: ModelStatus.Offline });
-      exit();
+      exit().then(r => {
+        if (r.status === 403)
+          if (commonStore.platform !== 'linux')
+            toast(t('Server is working on deployment mode, please close the terminal window manually'), { type: 'info' });
+          else
+            toast(t('Server is working on deployment mode, please exit the program manually to stop the server'), { type: 'info' });
+      });
     }
   };
 

frontend/src/components/WorkHeader.tsx

@@ -25,7 +25,8 @@ export const WorkHeader: FC = observer(() => {
   const { t } = useTranslation();
   const port = commonStore.getCurrentModelConfig().apiParameters.apiPort;
 
-  return (
+  return commonStore.platform === 'web' ?
+    <div /> :
     <div className="flex flex-col gap-1">
       <div className="flex justify-between items-center">
         <div className="flex items-center gap-2">
@@ -42,5 +43,5 @@ export const WorkHeader: FC = observer(() => {
       </Text>
       <Divider style={{ flexGrow: 0 }} />
     </div>
-  );
+    ;
 });

frontend/src/main.tsx

@@ -1,3 +1,4 @@
+import './webWails';
 import React from 'react';
 import { createRoot } from 'react-dom/client';
 import './style.scss';
@@ -6,7 +7,6 @@ import App from './App';
 import { HashRouter } from 'react-router-dom';
 import { startup } from './startup';
 import './_locales/i18n-react';
-import 'html-midi-player';
 import { WindowShow } from '../wailsjs/runtime';
 
 startup().then(() => {

frontend/src/pages/About.tsx

@@ -5,9 +5,7 @@ import MarkdownRender from '../components/MarkdownRender';
 import { observer } from 'mobx-react-lite';
 import commonStore from '../stores/commonStore';
 
-export type AboutContent = { [lang: string]: string }
-
-export const About: FC = observer(() => {
+const About: FC = observer(() => {
   const { t } = useTranslation();
   const lang: string = commonStore.settings.language;
 
@@ -21,3 +19,5 @@ export const About: FC = observer(() => {
     } />
   );
 });
+
+export default About;

frontend/src/pages/Chat.tsx

@@ -10,56 +10,34 @@ import { KebabHorizontalIcon, PencilIcon, SyncIcon, TrashIcon } from '@primer/oc
 import logo from '../assets/images/logo.png';
 import MarkdownRender from '../components/MarkdownRender';
 import { ToolTipButton } from '../components/ToolTipButton';
-import { ArrowCircleUp28Regular, Delete28Regular, RecordStop28Regular, Save28Regular } from '@fluentui/react-icons';
+import {
+  ArrowCircleUp28Regular,
+  ArrowClockwise16Regular,
+  Attach16Regular,
+  Delete28Regular,
+  Dismiss16Regular,
+  RecordStop28Regular,
+  Save28Regular
+} from '@fluentui/react-icons';
 import { CopyButton } from '../components/CopyButton';
 import { ReadButton } from '../components/ReadButton';
 import { toast } from 'react-toastify';
 import { WorkHeader } from '../components/WorkHeader';
 import { DialogButton } from '../components/DialogButton';
-import { OpenFileFolder, OpenSaveFileDialog } from '../../wailsjs/go/backend_golang/App';
-import { toastWithButton } from '../utils';
+import { OpenFileFolder, OpenOpenFileDialog, OpenSaveFileDialog } from '../../wailsjs/go/backend_golang/App';
+import { absPathAsset, bytesToReadable, getServerRoot, toastWithButton } from '../utils';
 import { PresetsButton } from './PresetsManager/PresetsButton';
 import { useMediaQuery } from 'usehooks-ts';
+import { botName, ConversationMessage, MessageType, userName, welcomeUuid } from '../types/chat';
 
-export const userName = 'M E';
-export const botName = 'A I';
+let chatSseControllers: {
+  [id: string]: AbortController
+} = {};
 
-export const welcomeUuid = 'welcome';
-
-export enum MessageType {
-  Normal,
-  Error
-}
-
-export type Side = 'left' | 'right'
-
-export type Color = 'neutral' | 'brand' | 'colorful'
-
-export type MessageItem = {
-  sender: string,
-  type: MessageType,
-  color: Color,
-  avatarImg?: string,
-  time: string,
-  content: string,
-  side: Side,
-  done: boolean
-}
-
-export type Conversation = {
-  [uuid: string]: MessageItem
-}
-
-export type Role = 'assistant' | 'user' | 'system';
-
-export type ConversationMessage = {
-  role: Role;
-  content: string;
-}
-
-let chatSseController: AbortController | null = null;
-
-const MoreUtilsButton: FC<{ uuid: string, setEditing: (editing: boolean) => void }> = observer(({
+const MoreUtilsButton: FC<{
+  uuid: string,
+  setEditing: (editing: boolean) => void
+}> = observer(({
   uuid,
   setEditing
 }) => {
@@ -83,13 +61,15 @@ const MoreUtilsButton: FC<{ uuid: string, setEditing: (editing: boolean) => void
         onClick={() => {
           commonStore.conversationOrder.splice(commonStore.conversationOrder.indexOf(uuid), 1);
           delete commonStore.conversation[uuid];
+          commonStore.setAttachment(uuid, null);
         }} />
     </MenuPopover>
   </Menu>;
 });
 
 const ChatMessageItem: FC<{
-  uuid: string, onSubmit: (message: string | null, answerId: string | null,
+  uuid: string,
+  onSubmit: (message: string | null, answerId: string | null,
     startUuid: string | null, endUuid: string | null, includeEndUuid: boolean) => void
 }> = observer(({ uuid, onSubmit }) => {
   const { t } = useTranslation();
@@ -114,6 +94,13 @@ const ChatMessageItem: FC<{
     }
   };
 
+  let avatarImg: string | undefined;
+  if (commonStore.activePreset && messageItem.sender === botName) {
+    avatarImg = absPathAsset(commonStore.activePreset.avatarImg);
+  } else if (messageItem.avatarImg) {
+    avatarImg = messageItem.avatarImg;
+  }
+
   return <div
     className={classnames(
       'flex gap-2 mb-2 overflow-hidden',
@@ -131,7 +118,7 @@ const ChatMessageItem: FC<{
     <Avatar
       color={messageItem.color}
       name={messageItem.sender}
-      image={(commonStore.activePreset && messageItem.sender === botName) ? { src: commonStore.activePreset.avatarImg } : messageItem.avatarImg ? { src: messageItem.avatarImg } : undefined}
+      image={avatarImg ? { src: avatarImg } : undefined}
     />
     <div
       className={classnames(
@@ -142,13 +129,31 @@ const ChatMessageItem: FC<{
       )}
     >
       {!editing ?
-        <MarkdownRender>{messageItem.content}</MarkdownRender> :
+        <div className="flex flex-col">
+          <MarkdownRender>{messageItem.content}</MarkdownRender>
+          {uuid in commonStore.attachments &&
+            <div className="flex grow">
+              <div className="grow" />
+              <ToolTipButton className="whitespace-nowrap"
+                text={
+                  commonStore.attachments[uuid][0].name.replace(
+                    new RegExp('(^[^\\.]{5})[^\\.]+'), '$1...')
+                }
+                desc={`${commonStore.attachments[uuid][0].name} (${bytesToReadable(commonStore.attachments[uuid][0].size)})`}
+                size="small" shape="circular" appearance="secondary" />
+            </div>
+          }
+        </div> :
         <Textarea ref={textareaRef}
           className="grow"
           style={{ minWidth: 0 }}
           value={messageItem.content}
           onChange={(e) => {
             messageItem.content = e.target.value;
+            commonStore.conversation[uuid].type = MessageType.Normal;
+            commonStore.conversation[uuid].done = true;
+            commonStore.setConversation(commonStore.conversation);
+            commonStore.setConversationOrder([...commonStore.conversationOrder]);
           }}
           onBlur={() => {
             setEditingInner(false);
@@ -166,6 +171,10 @@ const ChatMessageItem: FC<{
           messageItem.sender === botName && uuid !== welcomeUuid &&
           <ToolTipButton desc={t('Retry')} size="small" appearance="subtle"
             icon={<SyncIcon />} onClick={() => {
+            if (uuid in chatSseControllers) {
+              chatSseControllers[uuid].abort();
+              delete chatSseControllers[uuid];
+            }
             onSubmit(null, uuid, null, uuid, false);
           }} />
         }
@@ -187,15 +196,7 @@ const ChatPanel: FC = observer(() => {
   const currentConfig = commonStore.getCurrentModelConfig();
   const apiParams = currentConfig.apiParameters;
   const port = apiParams.apiPort;
-
-  let lastMessageId: string;
-  let generating: boolean = false;
-  if (commonStore.conversationOrder.length > 0) {
-    lastMessageId = commonStore.conversationOrder[commonStore.conversationOrder.length - 1];
-    const lastMessage = commonStore.conversation[lastMessageId];
-    if (lastMessage.sender === botName)
-      generating = !lastMessage.done;
-  }
+  const generating: boolean = Object.keys(chatSseControllers).length > 0;
 
   useEffect(() => {
     if (inputRef.current)
@@ -213,7 +214,7 @@ const ChatPanel: FC = observer(() => {
           color: 'colorful',
           avatarImg: logo,
           time: new Date().toISOString(),
-          content: t('Hello! I\'m RWKV, an open-source and commercially usable large language model.'),
+          content: commonStore.platform === 'web' ? t('Hello, what can I do for you?') : t('Hello! I\'m RWKV, an open-source and commercially usable large language model.'),
           side: 'left',
           done: true
         }
@@ -230,7 +231,7 @@ const ChatPanel: FC = observer(() => {
     e.stopPropagation();
     if (e.type === 'click' || (e.keyCode === 13 && !e.shiftKey)) {
       e.preventDefault();
-      if (commonStore.status.status === ModelStatus.Offline && !commonStore.settings.apiUrl) {
+      if (commonStore.status.status === ModelStatus.Offline && !commonStore.settings.apiUrl && commonStore.platform !== 'web') {
         toast(t('Please click the button in the top right corner to start the model'), { type: 'warning' });
         return;
       }
@@ -260,6 +261,11 @@ const ChatPanel: FC = observer(() => {
       commonStore.setConversation(commonStore.conversation);
       commonStore.conversationOrder.push(newId);
       commonStore.setConversationOrder(commonStore.conversationOrder);
+
+      if (commonStore.currentTempAttachment) {
+        commonStore.setAttachment(newId, [commonStore.currentTempAttachment]);
+        commonStore.setCurrentTempAttachment(null);
+      }
     }
 
     let startIndex = startUuid ? commonStore.conversationOrder.indexOf(startUuid) : 0;
@@ -271,6 +277,17 @@ const ChatPanel: FC = observer(() => {
       if (uuid === welcomeUuid)
         return;
       const messageItem = commonStore.conversation[uuid];
+      if (uuid in commonStore.attachments) {
+        const attachment = commonStore.attachments[uuid][0];
+        messages.push({
+          role: 'user',
+          content: t('The content of file') + ` "${attachment.name}" `
+            + t('is as follows. When replying to me, consider the file content and respond accordingly:')
+            + '\n\n' + attachment.content
+        });
+        messages.push({ role: 'user', content: t('What\'s the file name') });
+        messages.push({ role: 'assistant', content: t('The file name is: ') + attachment.name });
+      }
       if (messageItem.done && messageItem.type === MessageType.Normal && messageItem.sender === userName) {
         messages.push({ role: 'user', content: messageItem.content });
       } else if (messageItem.done && messageItem.type === MessageType.Normal && messageItem.sender === botName) {
@@ -296,11 +313,10 @@ const ChatPanel: FC = observer(() => {
     commonStore.setConversationOrder(commonStore.conversationOrder);
     setTimeout(scrollToBottom);
     let answer = '';
-    chatSseController = new AbortController();
-    fetchEventSource( // https://api.openai.com/v1/chat/completions || http://127.0.0.1:${port}/chat/completions
-      commonStore.settings.apiUrl ?
-        commonStore.settings.apiUrl + '/v1/chat/completions' :
-        `http://127.0.0.1:${port}/chat/completions`,
+    const chatSseController = new AbortController();
+    chatSseControllers[answerId] = chatSseController;
+    fetchEventSource( // https://api.openai.com/v1/chat/completions || http://127.0.0.1:${port}/v1/chat/completions
+      getServerRoot(port) + '/v1/chat/completions',
       {
         method: 'POST',
         headers: {
@@ -312,12 +328,17 @@ const ChatPanel: FC = observer(() => {
           stream: true,
           model: commonStore.settings.apiChatModelName, // 'gpt-3.5-turbo'
           temperature: apiParams.temperature,
-          top_p: apiParams.topP
+          top_p: apiParams.topP,
+          user_name: commonStore.activePreset?.userName || undefined,
+          assistant_name: commonStore.activePreset?.assistantName || undefined,
+          presystem: commonStore.activePreset?.presystem && undefined
         }),
         signal: chatSseController?.signal,
         onmessage(e) {
           scrollToBottom();
           if (e.data.trim() === '[DONE]') {
+            if (answerId! in chatSseControllers)
+              delete chatSseControllers[answerId!];
             commonStore.conversation[answerId!].done = true;
             commonStore.conversation[answerId!].content = commonStore.conversation[answerId!].content.trim();
             commonStore.setConversation(commonStore.conversation);
@@ -347,9 +368,13 @@ const ChatPanel: FC = observer(() => {
           }
         },
         onclose() {
+          if (answerId! in chatSseControllers)
+            delete chatSseControllers[answerId!];
           console.log('Connection closed');
         },
         onerror(err) {
+          if (answerId! in chatSseControllers)
+            delete chatSseControllers[answerId!];
           commonStore.conversation[answerId!].type = MessageType.Error;
           commonStore.conversation[answerId!].done = true;
           err = err.message || err;
@@ -377,33 +402,141 @@ const ChatPanel: FC = observer(() => {
           size={mq ? 'large' : 'small'} shape="circular" appearance="subtle" title={t('Clear')}
           contentText={t('Are you sure you want to clear the conversation? It cannot be undone.')}
           onConfirm={() => {
-            if (generating)
-              chatSseController?.abort();
+            if (generating) {
+              for (const id in chatSseControllers) {
+                chatSseControllers[id].abort();
+              }
+              chatSseControllers = {};
+            }
             commonStore.setConversation({});
             commonStore.setConversationOrder([]);
           }} />
-        <Textarea
-          ref={inputRef}
-          style={{ minWidth: 0 }}
-          className="grow"
-          resize="vertical"
-          placeholder={t('Type your message here')!}
-          value={commonStore.currentInput}
-          onChange={(e) => commonStore.setCurrentInput(e.target.value)}
-          onKeyDown={handleKeyDownOrClick}
-        />
+        <div className="relative flex grow">
+          <Textarea
+            ref={inputRef}
+            style={{ minWidth: 0 }}
+            className="grow"
+            resize="vertical"
+            placeholder={t('Type your message here')!}
+            value={commonStore.currentInput}
+            onChange={(e) => commonStore.setCurrentInput(e.target.value)}
+            onKeyDown={handleKeyDownOrClick}
+          />
+          <div className="absolute right-2 bottom-2">
+            {!commonStore.currentTempAttachment ?
+              <ToolTipButton
+                desc={commonStore.attachmentUploading ?
+                  t('Uploading Attachment') :
+                  t('Add An Attachment (Accepts pdf, txt)')}
+                icon={commonStore.attachmentUploading ?
+                  <ArrowClockwise16Regular className="animate-spin" />
+                  : <Attach16Regular />}
+                size="small" shape="circular" appearance="secondary"
+                onClick={() => {
+                  if (commonStore.status.status === ModelStatus.Offline && !commonStore.settings.apiUrl && commonStore.platform !== 'web') {
+                    toast(t('Please click the button in the top right corner to start the model'), { type: 'warning' });
+                    return;
+                  }
+
+                  if (commonStore.attachmentUploading)
+                    return;
+
+                  OpenOpenFileDialog('*.txt;*.pdf').then(async filePath => {
+                    if (!filePath)
+                      return;
+
+                    commonStore.setAttachmentUploading(true);
+
+                    let blob: Blob;
+                    let attachmentName: string | undefined;
+                    let attachmentContent: string | undefined;
+                    if (commonStore.platform === 'web') {
+                      const webReturn = filePath as any;
+                      blob = webReturn.blob;
+                      attachmentName = blob.name;
+                      attachmentContent = webReturn.content;
+                    } else {
+                      // Both are slow. Communication between frontend and backend is slow. Use AssetServer Handler to read the file.
+                      // const blob = new Blob([atob(info.content as unknown as string)]); // await fetch(`data:application/octet-stream;base64,${info.content}`).then(r => r.blob());
+                      blob = await fetch(absPathAsset(filePath)).then(r => r.blob());
+                      attachmentName = filePath.split(/[\\/]/).pop();
+                    }
+                    if (attachmentContent) {
+                      commonStore.setCurrentTempAttachment(
+                        {
+                          name: attachmentName!,
+                          size: blob.size,
+                          content: attachmentContent
+                        });
+                      commonStore.setAttachmentUploading(false);
+                    } else {
+                      const urlPath = `/file-to-text?file_name=${attachmentName}`;
+                      const bodyForm = new FormData();
+                      bodyForm.append('file_data', blob, attachmentName);
+                      fetch(getServerRoot(port) + urlPath, {
+                        method: 'POST',
+                        body: bodyForm
+                      }).then(async r => {
+                          if (r.status === 200) {
+                            const pages = (await r.json()).pages as any[];
+                            if (pages.length === 1)
+                              attachmentContent = pages[0].page_content;
+                            else
+                              attachmentContent = pages.map((p, i) => `Page ${i + 1}:\n${p.page_content}`).join('\n\n');
+                            commonStore.setCurrentTempAttachment(
+                              {
+                                name: attachmentName!,
+                                size: blob.size,
+                                content: attachmentContent!
+                              });
+                          } else {
+                            toast(r.statusText + '\n' + (await r.text()), {
+                              type: 'error'
+                            });
+                          }
+                          commonStore.setAttachmentUploading(false);
+                        }
+                      ).catch(e => {
+                        commonStore.setAttachmentUploading(false);
+                        toast(t('Error') + ' - ' + (e.message || e), { type: 'error', autoClose: 2500 });
+                      });
+                    }
+                  }).catch(e => {
+                    toast(t('Error') + ' - ' + (e.message || e), { type: 'error', autoClose: 2500 });
+                  });
+                }}
+              /> :
+              <div>
+                <ToolTipButton
+                  text={
+                    commonStore.currentTempAttachment.name.replace(
+                      new RegExp('(^[^\\.]{5})[^\\.]+'), '$1...')
+                  }
+                  desc={`${commonStore.currentTempAttachment.name} (${bytesToReadable(commonStore.currentTempAttachment.size)})`}
+                  size="small" shape="circular" appearance="secondary" />
+                <ToolTipButton desc={t('Remove Attachment')}
+                  icon={<Dismiss16Regular />}
+                  size="small" shape="circular" appearance="subtle"
+                  onClick={() => {
+                    commonStore.setCurrentTempAttachment(null);
+                  }} />
+              </div>
+            }
+          </div>
+        </div>
         <ToolTipButton desc={generating ? t('Stop') : t('Send')}
           icon={generating ? <RecordStop28Regular /> : <ArrowCircleUp28Regular />}
           size={mq ? 'large' : 'small'} shape="circular" appearance="subtle"
           onClick={(e) => {
             if (generating) {
-              chatSseController?.abort();
-              if (lastMessageId) {
-                commonStore.conversation[lastMessageId].type = MessageType.Error;
-                commonStore.conversation[lastMessageId].done = true;
-                commonStore.setConversation(commonStore.conversation);
-                commonStore.setConversationOrder([...commonStore.conversationOrder]);
+              for (const id in chatSseControllers) {
+                chatSseControllers[id].abort();
+                commonStore.conversation[id].type = MessageType.Error;
+                commonStore.conversation[id].done = true;
               }
+              chatSseControllers = {};
+              commonStore.setConversation(commonStore.conversation);
+              commonStore.setConversationOrder([...commonStore.conversationOrder]);
             } else {
               handleKeyDownOrClick(e);
             }
@@ -414,8 +547,8 @@ const ChatPanel: FC = observer(() => {
           onClick={() => {
             let savedContent: string = '';
             const isWorldModel = commonStore.getCurrentModelConfig().modelParameters.modelName.toLowerCase().includes('world');
-            const user = isWorldModel ? 'Question' : 'Bob';
-            const bot = isWorldModel ? 'Answer' : 'Alice';
+            const user = isWorldModel ? 'User' : 'Bob';
+            const bot = isWorldModel ? 'Assistant' : 'Alice';
             commonStore.conversationOrder.forEach((uuid) => {
               if (uuid === welcomeUuid)
                 return;
@@ -439,7 +572,7 @@ const ChatPanel: FC = observer(() => {
   );
 });
 
-export const Chat: FC = observer(() => {
+const Chat: FC = observer(() => {
   return (
     <div className="flex flex-col gap-1 p-2 h-full overflow-hidden">
       <WorkHeader />
@@ -447,3 +580,5 @@ export const Chat: FC = observer(() => {
     </div>
   );
 });
+
+export default Chat;

frontend/src/pages/Completion.tsx

@@ -5,7 +5,6 @@ import { Button, Dropdown, Input, Option, Textarea } from '@fluentui/react-compo
 import { Labeled } from '../components/Labeled';
 import { ValuedSlider } from '../components/ValuedSlider';
 import { useTranslation } from 'react-i18next';
-import { ApiParameters } from './Configs';
 import commonStore, { ModelStatus } from '../stores/commonStore';
 import { fetchEventSource } from '@microsoft/fetch-event-source';
 import { toast } from 'react-toastify';
@@ -14,18 +13,8 @@ import { PresetsButton } from './PresetsManager/PresetsButton';
 import { ToolTipButton } from '../components/ToolTipButton';
 import { ArrowSync20Regular } from '@fluentui/react-icons';
 import { defaultPresets } from './defaultConfigs';
-
-export type CompletionParams = Omit<ApiParameters, 'apiPort'> & {
-  stop: string,
-  injectStart: string,
-  injectEnd: string
-};
-
-export type CompletionPreset = {
-  name: string,
-  prompt: string,
-  params: CompletionParams
-}
+import { CompletionParams, CompletionPreset } from '../types/completion';
+import { getServerRoot } from '../utils';
 
 let completionSseController: AbortController | null = null;
 
@@ -80,7 +69,7 @@ const CompletionPanel: FC = observer(() => {
   const onSubmit = (prompt: string) => {
     commonStore.setCompletionSubmittedPrompt(prompt);
 
-    if (commonStore.status.status === ModelStatus.Offline && !commonStore.settings.apiUrl) {
+    if (commonStore.status.status === ModelStatus.Offline && !commonStore.settings.apiUrl && commonStore.platform !== 'web') {
       toast(t('Please click the button in the top right corner to start the model'), { type: 'warning' });
       commonStore.setCompletionGenerating(false);
       return;
@@ -90,10 +79,8 @@ const CompletionPanel: FC = observer(() => {
 
     let answer = '';
     completionSseController = new AbortController();
-    fetchEventSource( // https://api.openai.com/v1/completions || http://127.0.0.1:${port}/completions
-      commonStore.settings.apiUrl ?
-        commonStore.settings.apiUrl + '/v1/completions' :
-        `http://127.0.0.1:${port}/completions`,
+    fetchEventSource( // https://api.openai.com/v1/completions || http://127.0.0.1:${port}/v1/completions
+      getServerRoot(port) + '/v1/completions',
       {
         method: 'POST',
         headers: {
@@ -269,6 +256,13 @@ const CompletionPanel: FC = observer(() => {
             } />
         </div>
         <div className="grow" />
+        <div className="hidden justify-between gap-2 sm:flex">
+          <Button className="grow" onClick={() => {
+            const newPrompt = prompt.replace(/\n+\ /g, '\n').split('\n').map((line) => line.trim()).join('\n');
+            setPrompt(newPrompt);
+            commonStore.setCompletionSubmittedPrompt(newPrompt);
+          }}>{t('Format Content')}</Button>
+        </div>
         <div className="flex justify-between gap-2">
           <ToolTipButton desc={t('Regenerate')} icon={<ArrowSync20Regular />} onClick={() => {
             completionSseController?.abort();
@@ -296,7 +290,7 @@ const CompletionPanel: FC = observer(() => {
   );
 });
 
-export const Completion: FC = observer(() => {
+const Completion: FC = observer(() => {
   return (
     <div className="flex flex-col gap-1 p-2 h-full overflow-hidden">
       <WorkHeader />
@@ -304,3 +298,5 @@ export const Completion: FC = observer(() => {
     </div>
   );
 });
+
+export default Completion;

frontend/src/pages/Composition.tsx

@@ -1,3 +1,4 @@
+import 'html-midi-player';
 import React, { FC, useEffect, useRef } from 'react';
 import { observer } from 'mobx-react-lite';
 import { WorkHeader } from '../components/WorkHeader';
@@ -16,23 +17,15 @@ import * as mm from '@magenta/music/esm/core.js';
 import { NoteSequence } from '@magenta/music/esm/protobuf.js';
 import { defaultCompositionPrompt } from './defaultConfigs';
 import { FileExists, OpenFileFolder, OpenSaveFileDialogBytes } from '../../wailsjs/go/backend_golang/App';
-import { toastWithButton } from '../utils';
-
-export type CompositionParams = {
-  prompt: string,
-  maxResponseToken: number,
-  temperature: number,
-  topP: number,
-  autoPlay: boolean,
-  useLocalSoundFont: boolean,
-  midi: ArrayBuffer | null,
-  ns: NoteSequence | null
-}
+import { getServerRoot, toastWithButton } from '../utils';
+import { CompositionParams } from '../types/composition';
+import { useMediaQuery } from 'usehooks-ts';
 
 let compositionSseController: AbortController | null = null;
 
 const CompositionPanel: FC = observer(() => {
   const { t } = useTranslation();
+  const mq = useMediaQuery('(min-width: 640px)');
   const inputRef = useRef<HTMLTextAreaElement>(null);
   const port = commonStore.getCurrentModelConfig().apiParameters.apiPort;
   const visualizerRef = useRef<VisualizerElement>(null);
@@ -109,9 +102,7 @@ const CompositionPanel: FC = observer(() => {
   }, []);
 
   const generateNs = (autoPlay: boolean) => {
-    fetch(commonStore.settings.apiUrl ?
-      commonStore.settings.apiUrl + '/text-to-midi' :
-      `http://127.0.0.1:${port}/text-to-midi`, {
+    fetch(getServerRoot(port) + '/text-to-midi', {
       method: 'POST',
       headers: {
         'Content-Type': 'application/json'
@@ -137,7 +128,7 @@ const CompositionPanel: FC = observer(() => {
   const onSubmit = (prompt: string) => {
     commonStore.setCompositionSubmittedPrompt(prompt);
 
-    if (commonStore.status.status === ModelStatus.Offline && !commonStore.settings.apiUrl) {
+    if (commonStore.status.status === ModelStatus.Offline && !commonStore.settings.apiUrl && commonStore.platform !== 'web') {
       toast(t('Please click the button in the top right corner to start the model'), { type: 'warning' });
       commonStore.setCompositionGenerating(false);
       return;
@@ -145,10 +136,8 @@ const CompositionPanel: FC = observer(() => {
 
     let answer = '';
     compositionSseController = new AbortController();
-    fetchEventSource( // https://api.openai.com/v1/completions || http://127.0.0.1:${port}/completions
-      commonStore.settings.apiUrl ?
-        commonStore.settings.apiUrl + '/v1/completions' :
-        `http://127.0.0.1:${port}/completions`,
+    fetchEventSource( // https://api.openai.com/v1/completions || http://127.0.0.1:${port}/v1/completions
+      getServerRoot(port) + '/v1/completions',
       {
         method: 'POST',
         headers: {
@@ -217,62 +206,64 @@ const CompositionPanel: FC = observer(() => {
             setPrompt(e.target.value);
           }}
         />
-        <div className="flex flex-col gap-1 max-h-48 sm:max-w-sm sm:max-h-full overflow-x-hidden overflow-y-auto p-1">
-          <Labeled flex breakline label={t('Max Response Token')}
-            desc={t('By default, the maximum number of tokens that can be answered in a single response, it can be changed by the user by specifying API parameters.')}
-            content={
-              <ValuedSlider value={params.maxResponseToken} min={100} max={4100}
-                step={100}
-                input
-                onChange={(e, data) => {
-                  setParams({
-                    maxResponseToken: data.value
-                  });
-                }} />
-            } />
-          <Labeled flex breakline label={t('Temperature')}
-            desc={t('Sampling temperature, it\'s like giving alcohol to a model, the higher the stronger the randomness and creativity, while the lower, the more focused and deterministic it will be.')}
-            content={
-              <ValuedSlider value={params.temperature} min={0} max={2} step={0.1}
-                input
-                onChange={(e, data) => {
-                  setParams({
-                    temperature: data.value
-                  });
-                }} />
-            } />
-          <Labeled flex breakline label={t('Top_P')}
-            desc={t('Just like feeding sedatives to the model. Consider the results of the top n% probability mass, 0.1 considers the top 10%, with higher quality but more conservative, 1 considers all results, with lower quality but more diverse.')}
-            content={
-              <ValuedSlider value={params.topP} min={0} max={1} step={0.1} input
-                onChange={(e, data) => {
-                  setParams({
-                    topP: data.value
-                  });
-                }} />
-            } />
-          <div className="grow" />
-          <Checkbox className="select-none"
-            size="large" label={t('Use Local Sound Font')} checked={params.useLocalSoundFont}
-            onChange={async (_, data) => {
-              if (data.checked) {
-                if (!await FileExists('assets/sound-font/accordion/instrument.json')) {
-                  toast(t('Failed to load local sound font, please check if the files exist - assets/sound-font'),
-                    { type: 'warning' });
-                  return;
+        <div className="flex flex-col gap-1 max-h-48 sm:max-w-sm sm:max-h-full">
+          <div className="flex flex-col gap-1 grow overflow-x-hidden overflow-y-auto p-1">
+            <Labeled flex breakline label={t('Max Response Token')}
+              desc={t('By default, the maximum number of tokens that can be answered in a single response, it can be changed by the user by specifying API parameters.')}
+              content={
+                <ValuedSlider value={params.maxResponseToken} min={100} max={4100}
+                  step={100}
+                  input
+                  onChange={(e, data) => {
+                    setParams({
+                      maxResponseToken: data.value
+                    });
+                  }} />
+              } />
+            <Labeled flex breakline label={t('Temperature')}
+              desc={t('Sampling temperature, it\'s like giving alcohol to a model, the higher the stronger the randomness and creativity, while the lower, the more focused and deterministic it will be.')}
+              content={
+                <ValuedSlider value={params.temperature} min={0} max={2} step={0.1}
+                  input
+                  onChange={(e, data) => {
+                    setParams({
+                      temperature: data.value
+                    });
+                  }} />
+              } />
+            <Labeled flex breakline label={t('Top_P')}
+              desc={t('Just like feeding sedatives to the model. Consider the results of the top n% probability mass, 0.1 considers the top 10%, with higher quality but more conservative, 1 considers all results, with lower quality but more diverse.')}
+              content={
+                <ValuedSlider value={params.topP} min={0} max={1} step={0.1} input
+                  onChange={(e, data) => {
+                    setParams({
+                      topP: data.value
+                    });
+                  }} />
+              } />
+            <div className="grow" />
+            <Checkbox className="select-none"
+              size="large" label={t('Use Local Sound Font')} checked={params.useLocalSoundFont}
+              onChange={async (_, data) => {
+                if (data.checked) {
+                  if (!await FileExists('assets/sound-font/accordion/instrument.json')) {
+                    toast(t('Failed to load local sound font, please check if the files exist - assets/sound-font'),
+                      { type: 'warning' });
+                    return;
+                  }
                 }
-              }
+                setParams({
+                  useLocalSoundFont: data.checked as boolean
+                });
+                setSoundFont();
+              }} />
+            <Checkbox className="select-none"
+              size="large" label={t('Auto Play At The End')} checked={params.autoPlay} onChange={(_, data) => {
               setParams({
-                useLocalSoundFont: data.checked as boolean
+                autoPlay: data.checked as boolean
               });
-              setSoundFont();
             }} />
-          <Checkbox className="select-none"
-            size="large" label={t('Auto Play At The End')} checked={params.autoPlay} onChange={(_, data) => {
-            setParams({
-              autoPlay: data.checked as boolean
-            });
-          }} />
+          </div>
           <div className="flex justify-between gap-2">
             <ToolTipButton desc={t('Regenerate')} icon={<ArrowSync20Regular />} onClick={() => {
               compositionSseController?.abort();
@@ -311,7 +302,7 @@ const CompositionPanel: FC = observer(() => {
             ref={playerRef}
             style={{ width: '100%' }}
           />
-          <Button icon={<Save28Regular />}
+          <Button icon={<Save28Regular />} size={mq ? 'large' : 'medium'} appearance={mq ? 'secondary' : 'subtle'}
             onClick={() => {
               if (params.midi) {
                 OpenSaveFileDialogBytes('*.mid', 'music.mid', Array.from(new Uint8Array(params.midi))).then((path) => {
@@ -319,7 +310,7 @@ const CompositionPanel: FC = observer(() => {
                     toastWithButton(t('File Saved'), t('Open'), () => {
                       OpenFileFolder(path, false);
                     });
-                }).catch((e: any) => {
+                }).catch((e) => {
                   toast(t('Error') + ' - ' + (e.message || e), { type: 'error', autoClose: 2500 });
                 });
               } else {
@@ -327,7 +318,7 @@ const CompositionPanel: FC = observer(() => {
               }
             }}
           >
-            {t('Save')}
+            {mq ? t('Save') : ''}
           </Button>
         </div>
       </div>
@@ -335,7 +326,7 @@ const CompositionPanel: FC = observer(() => {
   );
 });
 
-export const Composition: FC = observer(() => {
+const Composition: FC = observer(() => {
   return (
     <div className="flex flex-col gap-1 p-2 h-full overflow-hidden">
       <WorkHeader />
@@ -343,3 +334,5 @@ export const Composition: FC = observer(() => {
     </div>
   );
 });
+
+export default Composition;

frontend/src/pages/Configs.tsx

@@ -1,6 +1,19 @@
-import { Dropdown, Input, Label, Option, Select, Switch, Text } from '@fluentui/react-components';
+import {
+  Accordion,
+  AccordionHeader,
+  AccordionItem,
+  AccordionPanel,
+  Checkbox,
+  Dropdown,
+  Input,
+  Label,
+  Option,
+  Select,
+  Switch,
+  Text
+} from '@fluentui/react-components';
 import { AddCircle20Regular, DataUsageSettings20Regular, Delete20Regular, Save20Regular } from '@fluentui/react-icons';
-import React, { FC } from 'react';
+import React, { FC, useEffect, useRef } from 'react';
 import { Section } from '../components/Section';
 import { Labeled } from '../components/Labeled';
 import { ToolTipButton } from '../components/ToolTipButton';
@@ -16,51 +29,28 @@ import { updateConfig } from '../apis';
 import { ConvertModel, ConvertSafetensors, FileExists, GetPyError } from '../../wailsjs/go/backend_golang/App';
 import { checkDependencies, getStrategy } from '../utils';
 import { useTranslation } from 'react-i18next';
-import { WindowShow } from '../../wailsjs/runtime/runtime';
+import { WindowShow } from '../../wailsjs/runtime';
 import strategyImg from '../assets/images/strategy.jpg';
 import strategyZhImg from '../assets/images/strategy_zh.jpg';
 import { ResetConfigsButton } from '../components/ResetConfigsButton';
 import { useMediaQuery } from 'usehooks-ts';
+import { ApiParameters, Device, ModelParameters, Precision } from '../types/configs';
 
-export type ApiParameters = {
-  apiPort: number
-  maxResponseToken: number;
-  temperature: number;
-  topP: number;
-  presencePenalty: number;
-  frequencyPenalty: number;
-}
-
-export type Device = 'CPU' | 'CUDA' | 'CUDA-Beta' | 'WebGPU' | 'MPS' | 'Custom';
-export type Precision = 'fp16' | 'int8' | 'fp32';
-
-export type ModelParameters = {
-  // different models can not have the same name
-  modelName: string;
-  device: Device;
-  precision: Precision;
-  storedLayers: number;
-  maxStoredLayers: number;
-  useCustomCuda?: boolean;
-  customStrategy?: string;
-}
-
-export type ModelConfig = {
-  // different configs can have the same name
-  name: string;
-  apiParameters: ApiParameters
-  modelParameters: ModelParameters
-}
-
-export const Configs: FC = observer(() => {
+const Configs: FC = observer(() => {
   const { t } = useTranslation();
   const [selectedIndex, setSelectedIndex] = React.useState(commonStore.currentModelConfigIndex);
   const [selectedConfig, setSelectedConfig] = React.useState(commonStore.modelConfigs[selectedIndex]);
   const [displayStrategyImg, setDisplayStrategyImg] = React.useState(false);
+  const advancedHeaderRef = useRef<HTMLDivElement>(null);
   const mq = useMediaQuery('(min-width: 640px)');
   const navigate = useNavigate();
   const port = selectedConfig.apiParameters.apiPort;
 
+  useEffect(() => {
+    if (advancedHeaderRef.current)
+      (advancedHeaderRef.current.firstElementChild as HTMLElement).style.padding = '0';
+  }, []);
+
   const updateSelectedIndex = (newIndex: number) => {
     setSelectedIndex(newIndex);
     setSelectedConfig(commonStore.modelConfigs[newIndex]);
@@ -402,7 +392,7 @@ export const Configs: FC = observer(() => {
                 {
                   (selectedConfig.modelParameters.device.includes('CUDA') || selectedConfig.modelParameters.device === 'Custom') &&
                   <Labeled label={t('Use Custom CUDA kernel to Accelerate')}
-                    desc={t('Enabling this option can greatly improve inference speed and save some VRAM, but there may be compatibility issues. If it fails to start, please turn off this option.')}
+                    desc={t('Enabling this option can greatly improve inference speed and save some VRAM, but there may be compatibility issues (output garbled). If it fails to start, please turn off this option, or try to upgrade your gpu driver.')}
                     content={
                       <Switch checked={selectedConfig.modelParameters.useCustomCuda}
                         onChange={(e, data) => {
@@ -412,14 +402,62 @@ export const Configs: FC = observer(() => {
                         }} />
                     } />
                 }
+                {selectedConfig.modelParameters.device !== 'WebGPU' &&
+                  <Accordion className="sm:col-span-2" collapsible
+                    openItems={!commonStore.modelParamsCollapsed && 'advanced'}
+                    onToggle={(e, data) => {
+                      if (data.value === 'advanced')
+                        commonStore.setModelParamsCollapsed(!commonStore.modelParamsCollapsed);
+                    }}>
+                    <AccordionItem value="advanced">
+                      <AccordionHeader ref={advancedHeaderRef} size="small">{t('Advanced')}</AccordionHeader>
+                      <AccordionPanel>
+                        <div className="flex flex-col">
+                          <div className="flex grow">
+                            <Checkbox className="select-none"
+                              size="large" label={t('Use Custom Tokenizer')}
+                              checked={selectedConfig.modelParameters.useCustomTokenizer}
+                              onChange={(_, data) => {
+                                setSelectedConfigModelParams({
+                                  useCustomTokenizer: data.checked as boolean
+                                });
+                              }} />
+                            <Input className="grow"
+                              placeholder={t('Tokenizer Path (e.g. backend-python/rwkv_pip/20B_tokenizer.json)')!}
+                              value={selectedConfig.modelParameters.customTokenizer}
+                              onChange={(e, data) => {
+                                setSelectedConfigModelParams({
+                                  customTokenizer: data.value
+                                });
+                              }} />
+                          </div>
+                        </div>
+                      </AccordionPanel>
+                    </AccordionItem>
+                  </Accordion>
+                }
               </div>
             }
           />
         </div>
         <div className="flex flex-row-reverse sm:fixed bottom-2 right-2">
-          <RunButton onClickRun={onClickSave} />
+          <div className="flex gap-2">
+            {selectedConfig.modelParameters.device !== 'WebGPU'
+              && <Checkbox className="select-none"
+                size="large" label={t('Enable WebUI')}
+                checked={selectedConfig.enableWebUI}
+                onChange={(_, data) => {
+                  setSelectedConfig({
+                    ...selectedConfig,
+                    enableWebUI: data.checked as boolean
+                  });
+                }} />}
+            <RunButton onClickRun={onClickSave} />
+          </div>
         </div>
       </div>
     } />
   );
 });
+
+export default Configs;

frontend/src/pages/Downloads.tsx

@@ -1,28 +1,22 @@
-import React, { FC } from 'react';
+import React, { FC, useEffect } from 'react';
 import { useTranslation } from 'react-i18next';
 import { Page } from '../components/Page';
 import { observer } from 'mobx-react-lite';
 import commonStore from '../stores/commonStore';
 import { Divider, Field, ProgressBar } from '@fluentui/react-components';
-import { bytesToGb, bytesToKb, bytesToMb } from '../utils';
+import { bytesToGb, bytesToKb, bytesToMb, refreshLocalModels } from '../utils';
 import { ToolTipButton } from '../components/ToolTipButton';
 import { Folder20Regular, Pause20Regular, Play20Regular } from '@fluentui/react-icons';
 import { AddToDownloadList, OpenFileFolder, PauseDownload } from '../../wailsjs/go/backend_golang/App';
 
-export type DownloadStatus = {
-  name: string;
-  path: string;
-  url: string;
-  transferred: number;
-  size: number;
-  speed: number;
-  progress: number;
-  downloading: boolean;
-  done: boolean;
-}
-
-export const Downloads: FC = observer(() => {
+const Downloads: FC = observer(() => {
   const { t } = useTranslation();
+  const finishedModelsLen = commonStore.downloadList.filter((status) => status.done && status.name.endsWith('.pth')).length;
+  useEffect(() => {
+    if (finishedModelsLen > 0)
+      refreshLocalModels({ models: commonStore.modelSourceList }, false);
+    console.log('finishedModelsLen:', finishedModelsLen);
+  }, [finishedModelsLen]);
 
   let displayList = commonStore.downloadList.slice();
   const downloadListNames = displayList.map(s => s.name);
@@ -85,3 +79,5 @@ export const Downloads: FC = observer(() => {
     } />
   );
 });
+
+export default Downloads;

frontend/src/pages/Home.tsx

@@ -1,11 +1,13 @@
 import { CompoundButton, Link, Text } from '@fluentui/react-components';
-import React, { FC, ReactElement } from 'react';
+import React, { FC } from 'react';
 import banner from '../assets/images/banner.jpg';
 import {
   Chat20Regular,
   ClipboardEdit20Regular,
   DataUsageSettings20Regular,
-  DocumentSettings20Regular
+  DocumentSettings20Regular,
+  MusicNote220Regular,
+  Settings20Regular
 } from '@fluentui/react-icons';
 import { useNavigate } from 'react-router';
 import { observer } from 'mobx-react-lite';
@@ -14,21 +16,13 @@ import manifest from '../../../manifest.json';
 import { BrowserOpenURL } from '../../wailsjs/runtime';
 import { useTranslation } from 'react-i18next';
 import { ConfigSelector } from '../components/ConfigSelector';
-import MarkdownRender from '../components/MarkdownRender';
 import commonStore from '../stores/commonStore';
-import { Completion } from './Completion';
 import { ResetConfigsButton } from '../components/ResetConfigsButton';
+import { AdvancedGeneralSettings } from './Settings';
+import { NavCard } from '../types/home';
+import { LazyImportComponent } from '../components/LazyImportComponent';
 
-export type IntroductionContent = { [lang: string]: string }
-
-type NavCard = {
-  label: string;
-  desc: string;
-  path: string;
-  icon: ReactElement;
-};
-
-const navCards: NavCard[] = [
+const clientNavCards: NavCard[] = [
   {
     label: 'Chat',
     desc: 'Go to chat page',
@@ -55,7 +49,36 @@ const navCards: NavCard[] = [
   }
 ];
 
-export const Home: FC = observer(() => {
+const webNavCards: NavCard[] = [
+  {
+    label: 'Chat',
+    desc: 'Go to chat page',
+    path: '/chat',
+    icon: <Chat20Regular />
+  },
+  {
+    label: 'Completion',
+    desc: 'Writer, Translator, Role-playing',
+    path: '/completion',
+    icon: <ClipboardEdit20Regular />
+  },
+  {
+    label: 'Composition',
+    desc: '',
+    path: '/composition',
+    icon: <MusicNote220Regular />
+  },
+  {
+    label: 'Settings',
+    desc: '',
+    path: '/settings',
+    icon: <Settings20Regular />
+  }
+];
+
+const MarkdownRender = React.lazy(() => import('../components/MarkdownRender'));
+
+const Home: FC = observer(() => {
   const { t } = useTranslation();
   const navigate = useNavigate();
   const lang: string = commonStore.settings.language;
@@ -64,39 +87,64 @@ export const Home: FC = observer(() => {
     navigate({ pathname: path });
   };
 
-  return (
-    <div className="flex flex-col justify-between h-full">
-      <img className="rounded-xl select-none hidden sm:block"
-        style={{ maxHeight: '40%', margin: '0 auto' }} src={banner} />
-      <div className="flex flex-col gap-2">
-        <Text size={600} weight="medium">{t('Introduction')}</Text>
-        <div className="h-40 overflow-y-auto overflow-x-hidden p-1">
-          <MarkdownRender>
-            {lang in commonStore.introduction ? commonStore.introduction[lang] : commonStore.introduction['en']}
-          </MarkdownRender>
+  return commonStore.platform === 'web' ?
+    (
+      <div className="flex flex-col gap-2 h-full overflow-x-hidden overflow-y-auto">
+        <img className="rounded-xl select-none object-cover grow"
+          style={{ maxHeight: '40%' }} src={banner} />
+        <div className="grow"></div>
+        <div className="grid grid-cols-2 sm:grid-cols-4 gap-5">
+          {webNavCards.map(({ label, path, icon, desc }, index) => (
+            <CompoundButton icon={icon} secondaryContent={t(desc)} key={`${path}-${index}`} value={path}
+              size="large" onClick={() => onClickNavCard(path)}>
+              {t(label)}
+            </CompoundButton>
+          ))}
         </div>
-      </div>
-      <div className="grid grid-cols-2 sm:grid-cols-4 gap-5">
-        {navCards.map(({ label, path, icon, desc }, index) => (
-          <CompoundButton icon={icon} secondaryContent={t(desc)} key={`${path}-${index}`} value={path}
-            size="large" onClick={() => onClickNavCard(path)}>
-            {t(label)}
-          </CompoundButton>
-        ))}
-      </div>
-      <div className="flex flex-col gap-2">
-        <div className="flex flex-row-reverse sm:fixed bottom-2 right-2">
-          <div className="flex gap-3">
-            <ResetConfigsButton />
-            <ConfigSelector />
-            <RunButton />
+        <div className="flex flex-col gap-2">
+          <AdvancedGeneralSettings />
+          <div className="flex gap-4 items-end">
+            {t('Version')}: {manifest.version}
+            <Link onClick={() => BrowserOpenURL('https://github.com/josStorer/RWKV-Runner')}>{t('Help')}</Link>
           </div>
         </div>
-        <div className="flex gap-4 items-end">
-          {t('Version')}: {manifest.version}
-          <Link onClick={() => BrowserOpenURL('https://github.com/josStorer/RWKV-Runner')}>{t('Help')}</Link>
+      </div>
+    )
+    : (
+      <div className="flex flex-col justify-between h-full">
+        <img className="rounded-xl select-none object-cover hidden sm:block"
+          style={{ maxHeight: '40%' }} src={banner} />
+        <div className="flex flex-col gap-2">
+          <Text size={600} weight="medium">{t('Introduction')}</Text>
+          <div className="h-40 overflow-y-auto overflow-x-hidden p-1">
+            <LazyImportComponent lazyChildren={MarkdownRender}>
+              {lang in commonStore.introduction ? commonStore.introduction[lang] : commonStore.introduction['en']}
+            </LazyImportComponent>
+          </div>
+        </div>
+        <div className="grid grid-cols-2 sm:grid-cols-4 gap-5">
+          {clientNavCards.map(({ label, path, icon, desc }, index) => (
+            <CompoundButton icon={icon} secondaryContent={t(desc)} key={`${path}-${index}`} value={path}
+              size="large" onClick={() => onClickNavCard(path)}>
+              {t(label)}
+            </CompoundButton>
+          ))}
+        </div>
+        <div className="flex flex-col gap-2">
+          <div className="flex flex-row-reverse sm:fixed bottom-2 right-2">
+            <div className="flex gap-3">
+              <ResetConfigsButton />
+              <ConfigSelector />
+              <RunButton />
+            </div>
+          </div>
+          <div className="flex gap-4 items-end">
+            {t('Version')}: {manifest.version}
+            <Link onClick={() => BrowserOpenURL('https://github.com/josStorer/RWKV-Runner')}>{t('Help')}</Link>
+          </div>
         </div>
       </div>
-    </div>
-  );
+    );
 });
+
+export default Home;

frontend/src/pages/Models.tsx

@@ -22,21 +22,7 @@ import { Page } from '../components/Page';
 import { bytesToGb, refreshModels, saveConfigs, toastWithButton } from '../utils';
 import { useTranslation } from 'react-i18next';
 import { useNavigate } from 'react-router';
-
-export type ModelSourceItem = {
-  name: string;
-  size: number;
-  lastUpdated: string;
-  desc?: { [lang: string]: string | undefined; };
-  SHA256?: string;
-  url?: string;
-  downloadUrl?: string;
-  isComplete?: boolean;
-  isLocal?: boolean;
-  localSize?: number;
-  lastUpdatedMs?: number;
-  hide?: boolean;
-};
+import { ModelSourceItem } from '../types/models';
 
 const columns: TableColumnDefinition<ModelSourceItem>[] = [
   createTableColumn<ModelSourceItem>({
@@ -165,7 +151,7 @@ const columns: TableColumnDefinition<ModelSourceItem>[] = [
   })
 ];
 
-export const Models: FC = observer(() => {
+const Models: FC = observer(() => {
   const { t } = useTranslation();
 
   return (
@@ -220,3 +206,5 @@ export const Models: FC = observer(() => {
     } />
   );
 });
+
+export default Models;

frontend/src/pages/PresetsManager/MessagesEditor.tsx

@@ -1,14 +1,14 @@
 import React, { FC, useState } from 'react';
 import { DragDropContext, Draggable, Droppable, DropResult } from 'react-beautiful-dnd';
 import commonStore from '../../stores/commonStore';
-import { Preset } from './PresetsButton';
 import { observer } from 'mobx-react-lite';
 import { v4 as uuid } from 'uuid';
 import { Button, Card, Dropdown, Option, Textarea } from '@fluentui/react-components';
 import { useTranslation } from 'react-i18next';
 import { ToolTipButton } from '../../components/ToolTipButton';
 import { Delete20Regular, ReOrderDotsVertical20Regular } from '@fluentui/react-icons';
-import { ConversationMessage, Role } from '../Chat';
+import { Preset } from '../../types/presets';
+import { ConversationMessage, Role } from '../../types/chat';
 
 type Item = {
   id: string;
@@ -31,7 +31,7 @@ const reorder = (list: Item[], startIndex: number, endIndex: number) => {
   return result;
 };
 
-export const MessagesEditor: FC = observer(() => {
+const MessagesEditor: FC = observer(() => {
   const { t } = useTranslation();
 
   const editingPreset = commonStore.editingPreset!;
@@ -152,3 +152,5 @@ export const MessagesEditor: FC = observer(() => {
     </div>
   );
 });
+
+export default MessagesEditor;

frontend/src/pages/PresetsManager/PresetsButton.tsx

@@ -1,6 +1,6 @@
 // TODO refactor
 
-import React, { FC, PropsWithChildren, ReactElement, useState } from 'react';
+import React, { FC, lazy, PropsWithChildren, ReactElement, useState } from 'react';
 import {
   Button,
   Dialog,
@@ -25,40 +25,21 @@ import {
 } from '@fluentui/react-icons';
 import { ToolTipButton } from '../../components/ToolTipButton';
 import { useTranslation } from 'react-i18next';
-import { botName, Conversation, ConversationMessage, MessageType, userName } from '../Chat';
 import { SelectTabEventHandler } from '@fluentui/react-tabs';
 import { Labeled } from '../../components/Labeled';
 import commonStore from '../../stores/commonStore';
 import logo from '../../assets/images/logo.png';
 import { observer } from 'mobx-react-lite';
-import { MessagesEditor } from './MessagesEditor';
 import { ClipboardGetText, ClipboardSetText } from '../../../wailsjs/runtime';
 import { toast } from 'react-toastify';
 import { CustomToastContainer } from '../../components/CustomToastContainer';
 import { v4 as uuid } from 'uuid';
+import { absPathAsset } from '../../utils';
+import { Preset, PresetsNavigationItem } from '../../types/presets';
+import { botName, Conversation, MessageType, userName } from '../../types/chat';
+import { LazyImportComponent } from '../../components/LazyImportComponent';
 
-export type PresetType = 'chat' | 'completion' | 'chatInCompletion'
-
-export type Preset = {
-  name: string,
-  tag: string,
-  // if name and sourceUrl are same, it will be overridden when importing
-  sourceUrl: string,
-  desc: string,
-  avatarImg: string,
-  type: PresetType,
-  // chat
-  welcomeMessage: string,
-  messages: ConversationMessage[],
-  displayPresetMessages: boolean,
-  // completion
-  prompt: string,
-  stop: string,
-  injectStart: string,
-  injectEnd: string,
-}
-
-export const defaultPreset: Preset = {
+const defaultPreset: Preset = {
   name: 'RWKV',
   tag: 'default',
   sourceUrl: '',
@@ -74,6 +55,8 @@ export const defaultPreset: Preset = {
   injectEnd: ''
 };
 
+const MessagesEditor = lazy(() => import('./MessagesEditor'));
+
 const setActivePreset = (preset: Preset) => {
   commonStore.setActivePreset(preset);
   //TODO if (preset.displayPresetMessages) {
@@ -97,7 +80,7 @@ const setActivePreset = (preset: Preset) => {
   //}
 };
 
-export const PresetCardFrame: FC<PropsWithChildren & { onClick?: () => void }> = (props) => {
+const PresetCardFrame: FC<PropsWithChildren & { onClick?: () => void }> = (props) => {
   return <Button
     className="flex flex-col gap-1 w-32 h-56 break-all"
     style={{ minWidth: 0, borderRadius: '0.75rem', justifyContent: 'unset' }}
@@ -107,7 +90,7 @@ export const PresetCardFrame: FC<PropsWithChildren & { onClick?: () => void }> =
   </Button>;
 };
 
-export const PresetCard: FC<{
+const PresetCard: FC<{
   avatarImg: string,
   name: string,
   desc: string,
@@ -121,7 +104,7 @@ export const PresetCard: FC<{
   const { t } = useTranslation();
 
   return <PresetCardFrame onClick={onClick}>
-    <img src={avatarImg} className="rounded-xl select-none ml-auto mr-auto h-28" />
+    <img src={absPathAsset(avatarImg)} className="rounded-xl select-none ml-auto mr-auto h-28" />
     <Text size={400}>{name}</Text>
     <Text size={200} style={{
       overflow: 'hidden', textOverflow: 'ellipsis',
@@ -143,7 +126,7 @@ export const PresetCard: FC<{
   </PresetCardFrame>;
 });
 
-export const ChatPresetEditor: FC<{
+const ChatPresetEditor: FC<{
   triggerButton: ReactElement,
   presetIndex: number
 }> = observer(({ triggerButton, presetIndex }) => {
@@ -164,8 +147,14 @@ export const ChatPresetEditor: FC<{
   const importPreset = () => {
     ClipboardGetText().then((text) => {
       try {
+        if (!text.trim().startsWith('{'))
+          text = new TextDecoder().decode(
+            new Uint8Array(atob(text)
+            .split('')
+            .map((c) => c.charCodeAt(0))));
         const preset = JSON.parse(text);
         setEditingPreset(preset);
+        setEditingMessages(false);
         toast(t('Imported successfully'), {
           type: 'success',
           autoClose: 1000
@@ -239,7 +228,7 @@ export const ChatPresetEditor: FC<{
               <Button appearance="subtle" icon={<Dismiss20Regular />} />
             </DialogTrigger>
           </div>
-          <img src={editingPreset.avatarImg} className="rounded-xl select-none ml-auto mr-auto h-28" />
+          <img src={absPathAsset(editingPreset.avatarImg)} className="rounded-xl select-none ml-auto mr-auto h-28" />
           <Labeled flex breakline label={t('Name')}
             content={
               <div className="flex gap-2">
@@ -255,9 +244,36 @@ export const ChatPresetEditor: FC<{
             } />
           {
             editingMessages ?
-              <MessagesEditor /> :
+              <div className="flex flex-col gap-1">
+                <Labeled flex spaceBetween label={t('Insert default system prompt at the beginning')}
+                  content={
+                    <Switch checked={editingPreset.presystem === undefined ? true : editingPreset.presystem}
+                      onChange={(e, data) => {
+                        setEditingPreset({
+                          presystem: data.checked
+                        });
+                      }} />
+                  } />
+                <Labeled flex breakline label={t('User Name')}
+                  content={
+                    <Input placeholder="User" value={editingPreset.userName} onChange={(e, data) => {
+                      setEditingPreset({
+                        userName: data.value
+                      });
+                    }} />
+                  } />
+                <Labeled flex breakline label={t('Assistant Name')}
+                  content={
+                    <Input placeholder="Assistant" value={editingPreset.assistantName} onChange={(e, data) => {
+                      setEditingPreset({
+                        assistantName: data.value
+                      });
+                    }} />
+                  } />
+                <LazyImportComponent lazyChildren={MessagesEditor} />
+              </div> :
               <div className="flex flex-col gap-1 p-2 overflow-x-hidden overflow-y-auto">
-                <Labeled flex breakline label={`${t('Description')} (${t("Preview Only")})`}
+                <Labeled flex breakline label={`${t('Description')} (${t('Preview Only')})`}
                   content={
                     <Input value={editingPreset.desc} onChange={(e, data) => {
                       setEditingPreset({
@@ -319,7 +335,7 @@ export const ChatPresetEditor: FC<{
   </Dialog>;
 });
 
-export const ChatPresets: FC = observer(() => {
+const ChatPresets: FC = observer(() => {
   const { t } = useTranslation();
 
   return <div className="flex flex-wrap gap-2">
@@ -355,11 +371,6 @@ export const ChatPresets: FC = observer(() => {
   </div>;
 });
 
-type PresetsNavigationItem = {
-  icon: ReactElement;
-  element: ReactElement;
-};
-
 const pages: { [label: string]: PresetsNavigationItem } = {
   Chat: {
     icon: <Chat20Regular />,
@@ -375,7 +386,7 @@ const pages: { [label: string]: PresetsNavigationItem } = {
   }
 };
 
-export const PresetsManager: FC<{ initTab: string }> = ({ initTab }) => {
+const PresetsManager: FC<{ initTab: string }> = ({ initTab }) => {
   const { t } = useTranslation();
   const [tab, setTab] = useState(initTab);
 

frontend/src/pages/Settings.tsx

@@ -16,33 +16,171 @@ import { observer } from 'mobx-react-lite';
 import { useTranslation } from 'react-i18next';
 import { checkUpdate, toastWithButton } from '../utils';
 import { RestartApp } from '../../wailsjs/go/backend_golang/App';
+import { Language, Languages } from '../types/settings';
 
-export const Languages = {
-  dev: 'English', // i18n default
-  zh: '简体中文',
-  ja: '日本語'
-};
+export const GeneralSettings: FC = observer(() => {
+  const { t } = useTranslation();
 
-export type Language = keyof typeof Languages;
+  return <div className="flex flex-col gap-2">
+    <Labeled label={t('Language')} flex spaceBetween content={
+      <Dropdown style={{ minWidth: 0 }} listbox={{ style: { minWidth: 0 } }}
+        value={Languages[commonStore.settings.language]}
+        selectedOptions={[commonStore.settings.language]}
+        onOptionSelect={(_, data) => {
+          if (data.optionValue) {
+            const lang = data.optionValue as Language;
+            commonStore.setSettings({
+              language: lang
+            });
+          }
+        }}>
+        {
+          Object.entries(Languages).map(([langKey, desc]) =>
+            <Option key={langKey} value={langKey}>{desc}</Option>)
+        }
+      </Dropdown>
+    } />
+    {
+      commonStore.platform === 'windows' &&
+      <Labeled label={t('DPI Scaling')} flex spaceBetween content={
+        <Dropdown style={{ minWidth: 0 }} listbox={{ style: { minWidth: 0 } }}
+          value={commonStore.settings.dpiScaling + '%'}
+          selectedOptions={[commonStore.settings.dpiScaling.toString()]}
+          onOptionSelect={(_, data) => {
+            if (data.optionValue) {
+              commonStore.setSettings({
+                dpiScaling: Number(data.optionValue)
+              });
+              toastWithButton(t('Restart the app to apply DPI Scaling.'), t('Restart'), () => {
+                RestartApp();
+              }, {
+                autoClose: 5000
+              });
+            }
+          }}>
+          {
+            Array.from({ length: 7 }, (_, i) => (i + 2) * 25).map((v, i) =>
+              <Option key={i} value={v.toString()}>{v + '%'}</Option>)
+          }
+        </Dropdown>
+      } />
+    }
+    <Labeled label={t('Dark Mode')} flex spaceBetween content={
+      <Switch checked={commonStore.settings.darkMode}
+        onChange={(e, data) => {
+          commonStore.setSettings({
+            darkMode: data.checked
+          });
+        }} />
+    } />
+  </div>;
+});
 
-export type SettingsType = {
-  language: Language
-  darkMode: boolean
-  autoUpdatesCheck: boolean
-  giteeUpdatesSource: boolean
-  cnMirror: boolean
-  host: string
-  dpiScaling: number
-  customModelsPath: string
-  customPythonPath: string
-  apiUrl: string
-  apiKey: string
-  apiChatModelName: string
-  apiCompletionModelName: string
-}
+export const AdvancedGeneralSettings: FC = observer(() => {
+  const { t } = useTranslation();
 
-export const Settings: FC = observer(() => {
-  const { t, i18n } = useTranslation();
+  return <div className="flex flex-col gap-2">
+    <Labeled label={'API URL'}
+      content={
+        <div className="flex gap-2">
+          <Input style={{ minWidth: 0 }} className="grow" value={commonStore.settings.apiUrl}
+            onChange={(e, data) => {
+              commonStore.setSettings({
+                apiUrl: data.value
+              });
+            }} />
+          <Dropdown style={{ minWidth: '33px' }} listbox={{ style: { minWidth: 0 } }}
+            value="..." selectedOptions={[]} expandIcon={null}
+            onOptionSelect={(_, data) => {
+              commonStore.setSettings({
+                apiUrl: data.optionValue
+              });
+              if (data.optionText === 'OpenAI') {
+                if (commonStore.settings.apiChatModelName === 'rwkv')
+                  commonStore.setSettings({
+                    apiChatModelName: 'gpt-3.5-turbo'
+                  });
+                if (commonStore.settings.apiCompletionModelName === 'rwkv')
+                  commonStore.setSettings({
+                    apiCompletionModelName: 'text-davinci-003'
+                  });
+              }
+            }}>
+            <Option value="">{t('Localhost')!}</Option>
+            <Option value="https://api.openai.com">OpenAI</Option>
+          </Dropdown>
+        </div>
+      } />
+    <Labeled label={'API Key'}
+      content={
+        <Input type="password" className="grow" placeholder="sk-" value={commonStore.settings.apiKey}
+          onChange={(e, data) => {
+            commonStore.setSettings({
+              apiKey: data.value
+            });
+          }} />
+      } />
+    <Labeled label={t('API Chat Model Name')}
+      content={
+        <div className="flex gap-2">
+          <Input style={{ minWidth: 0 }} className="grow" placeholder="rwkv"
+            value={commonStore.settings.apiChatModelName}
+            onChange={(e, data) => {
+              commonStore.setSettings({
+                apiChatModelName: data.value
+              });
+            }} />
+          <Dropdown style={{ minWidth: '33px' }} listbox={{ style: { minWidth: 0 } }}
+            value="..." selectedOptions={[]} expandIcon={null}
+            onOptionSelect={(_, data) => {
+              if (data.optionValue) {
+                commonStore.setSettings({
+                  apiChatModelName: data.optionValue
+                });
+              }
+            }}>
+            {
+              ['rwkv', 'gpt-4', 'gpt-4-0613', 'gpt-4-32k', 'gpt-4-32k-0613', 'gpt-3.5-turbo', 'gpt-3.5-turbo-0613', 'gpt-3.5-turbo-16k', 'gpt-3.5-turbo-16k-0613']
+              .map((v, i) =>
+                <Option key={i} value={v}>{v}</Option>
+              )
+            }
+          </Dropdown>
+        </div>
+      } />
+    <Labeled label={t('API Completion Model Name')}
+      content={
+        <div className="flex gap-2">
+          <Input style={{ minWidth: 0 }} className="grow" placeholder="rwkv"
+            value={commonStore.settings.apiCompletionModelName}
+            onChange={(e, data) => {
+              commonStore.setSettings({
+                apiCompletionModelName: data.value
+              });
+            }} />
+          <Dropdown style={{ minWidth: '33px' }} listbox={{ style: { minWidth: 0 } }}
+            value="..." selectedOptions={[]} expandIcon={null}
+            onOptionSelect={(_, data) => {
+              if (data.optionValue) {
+                commonStore.setSettings({
+                  apiCompletionModelName: data.optionValue
+                });
+              }
+            }}>
+            {
+              ['rwkv', 'text-davinci-003', 'text-davinci-002', 'text-curie-001', 'text-babbage-001', 'text-ada-001']
+              .map((v, i) =>
+                <Option key={i} value={v}>{v}</Option>
+              )
+            }
+          </Dropdown>
+        </div>
+      } />
+  </div>;
+});
+
+const Settings: FC = observer(() => {
+  const { t } = useTranslation();
   const advancedHeaderRef = useRef<HTMLDivElement>(null);
 
   useEffect(() => {
@@ -53,227 +191,101 @@ export const Settings: FC = observer(() => {
   return (
     <Page title={t('Settings')} content={
       <div className="flex flex-col gap-2 overflow-y-auto overflow-x-hidden p-1">
-        <Labeled label={t('Language')} flex spaceBetween content={
-          <Dropdown style={{ minWidth: 0 }} listbox={{ style: { minWidth: 0 } }}
-            value={Languages[commonStore.settings.language]}
-            selectedOptions={[commonStore.settings.language]}
-            onOptionSelect={(_, data) => {
-              if (data.optionValue) {
-                const lang = data.optionValue as Language;
-                commonStore.setSettings({
-                  language: lang
-                });
-              }
-            }}>
-            {
-              Object.entries(Languages).map(([langKey, desc]) =>
-                <Option key={langKey} value={langKey}>{desc}</Option>)
-            }
-          </Dropdown>
-        } />
         {
-          commonStore.platform === 'windows' &&
-          <Labeled label={t('DPI Scaling')} flex spaceBetween content={
-            <Dropdown style={{ minWidth: 0 }} listbox={{ style: { minWidth: 0 } }}
-              value={commonStore.settings.dpiScaling + '%'}
-              selectedOptions={[commonStore.settings.dpiScaling.toString()]}
-              onOptionSelect={(_, data) => {
-                if (data.optionValue) {
-                  commonStore.setSettings({
-                    dpiScaling: Number(data.optionValue)
-                  });
-                  toastWithButton(t('Restart the app to apply DPI Scaling.'), t('Restart'), () => {
-                    RestartApp();
-                  }, {
-                    autoClose: 5000
-                  });
-                }
-              }}>
-              {
-                Array.from({ length: 7 }, (_, i) => (i + 2) * 25).map((v, i) =>
-                  <Option key={i} value={v.toString()}>{v + '%'}</Option>)
-              }
-            </Dropdown>
-          } />
-        }
-        <Labeled label={t('Dark Mode')} flex spaceBetween content={
-          <Switch checked={commonStore.settings.darkMode}
-            onChange={(e, data) => {
-              commonStore.setSettings({
-                darkMode: data.checked
-              });
-            }} />
-        } />
-        <Labeled label={t('Automatic Updates Check')} flex spaceBetween content={
-          <Switch checked={commonStore.settings.autoUpdatesCheck}
-            onChange={(e, data) => {
-              commonStore.setSettings({
-                autoUpdatesCheck: data.checked
-              });
-              if (data.checked)
-                checkUpdate(true);
-            }} />
-        } />
-        {
-          commonStore.settings.language === 'zh' &&
-          <Labeled label={t('Use Gitee Updates Source')} flex spaceBetween content={
-            <Switch checked={commonStore.settings.giteeUpdatesSource}
-              onChange={(e, data) => {
-                commonStore.setSettings({
-                  giteeUpdatesSource: data.checked
-                });
-              }} />
-          } />
-        }
-        {
-          commonStore.settings.language === 'zh' && commonStore.platform !== 'linux' &&
-          <Labeled label={t('Use Tsinghua Pip Mirrors')} flex spaceBetween content={
-            <Switch checked={commonStore.settings.cnMirror}
-              onChange={(e, data) => {
-                commonStore.setSettings({
-                  cnMirror: data.checked
-                });
-              }} />
-          } />
-        }
-        <Labeled label={t('Allow external access to the API (service must be restarted)')} flex spaceBetween content={
-          <Switch checked={commonStore.settings.host !== '127.0.0.1'}
-            onChange={(e, data) => {
-              commonStore.setSettings({
-                host: data.checked ? '0.0.0.0' : '127.0.0.1'
-              });
-            }} />
-        } />
-        <Accordion collapsible openItems={!commonStore.advancedCollapsed && 'advanced'} onToggle={(e, data) => {
-          if (data.value === 'advanced')
-            commonStore.setAdvancedCollapsed(!commonStore.advancedCollapsed);
-        }}>
-          <AccordionItem value="advanced">
-            <AccordionHeader ref={advancedHeaderRef} size="large">{t('Advanced')}</AccordionHeader>
-            <AccordionPanel>
-              <div className="flex flex-col gap-2 overflow-hidden">
-                {commonStore.platform !== 'darwin' &&
-                  <Labeled label={t('Custom Models Path')}
-                    content={
-                      <Input className="grow" placeholder="./models" value={commonStore.settings.customModelsPath}
-                        onChange={(e, data) => {
-                          commonStore.setSettings({
-                            customModelsPath: data.value
-                          });
-                        }} />
-                    } />
-                }
-                <Labeled label={t('Custom Python Path')} // if set, will not use precompiled cuda kernel
-                  content={
-                    <Input className="grow" placeholder="./py310/python" value={commonStore.settings.customPythonPath}
-                      onChange={(e, data) => {
-                        commonStore.setDepComplete(false);
-                        commonStore.setSettings({
-                          customPythonPath: data.value
-                        });
-                      }} />
-                  } />
-                <Labeled label={'API URL'}
-                  content={
-                    <div className="flex gap-2">
-                      <Input style={{ minWidth: 0 }} className="grow" value={commonStore.settings.apiUrl}
-                        onChange={(e, data) => {
-                          commonStore.setSettings({
-                            apiUrl: data.value
-                          });
-                        }} />
-                      <Dropdown style={{ minWidth: 0 }} listbox={{ style: { minWidth: 0 } }}
-                        value="..." selectedOptions={[]} expandIcon={null}
-                        onOptionSelect={(_, data) => {
-                          commonStore.setSettings({
-                            apiUrl: data.optionValue
-                          });
-                          if (data.optionText === 'OpenAI') {
-                            if (commonStore.settings.apiChatModelName === 'rwkv')
-                              commonStore.setSettings({
-                                apiChatModelName: 'gpt-3.5-turbo'
-                              });
-                            if (commonStore.settings.apiCompletionModelName === 'rwkv')
-                              commonStore.setSettings({
-                                apiCompletionModelName: 'text-davinci-003'
-                              });
-                          }
-                        }}>
-                        <Option value="">{t('Localhost')!}</Option>
-                        <Option value="https://api.openai.com">OpenAI</Option>
-                      </Dropdown>
-                    </div>
-                  } />
-                <Labeled label={'API Key'}
-                  content={
-                    <Input className="grow" placeholder="sk-" value={commonStore.settings.apiKey}
-                      onChange={(e, data) => {
-                        commonStore.setSettings({
-                          apiKey: data.value
-                        });
-                      }} />
-                  } />
-                <Labeled label={t('API Chat Model Name')}
-                  content={
-                    <div className="flex gap-2">
-                      <Input style={{ minWidth: 0 }} className="grow" placeholder="rwkv"
-                        value={commonStore.settings.apiChatModelName}
-                        onChange={(e, data) => {
-                          commonStore.setSettings({
-                            apiChatModelName: data.value
-                          });
-                        }} />
-                      <Dropdown style={{ minWidth: 0 }} listbox={{ style: { minWidth: 0 } }}
-                        value="..." selectedOptions={[]} expandIcon={null}
-                        onOptionSelect={(_, data) => {
-                          if (data.optionValue) {
-                            commonStore.setSettings({
-                              apiChatModelName: data.optionValue
-                            });
-                          }
-                        }}>
-                        {
-                          ['rwkv', 'gpt-4', 'gpt-4-0613', 'gpt-4-32k', 'gpt-4-32k-0613', 'gpt-3.5-turbo', 'gpt-3.5-turbo-0613', 'gpt-3.5-turbo-16k', 'gpt-3.5-turbo-16k-0613']
-                          .map((v, i) =>
-                            <Option key={i} value={v}>{v}</Option>
-                          )
-                        }
-                      </Dropdown>
-                    </div>
-                  } />
-                <Labeled label={t('API Completion Model Name')}
-                  content={
-                    <div className="flex gap-2">
-                      <Input style={{ minWidth: 0 }} className="grow" placeholder="rwkv"
-                        value={commonStore.settings.apiCompletionModelName}
-                        onChange={(e, data) => {
-                          commonStore.setSettings({
-                            apiCompletionModelName: data.value
-                          });
-                        }} />
-                      <Dropdown style={{ minWidth: 0 }} listbox={{ style: { minWidth: 0 } }}
-                        value="..." selectedOptions={[]} expandIcon={null}
-                        onOptionSelect={(_, data) => {
-                          if (data.optionValue) {
-                            commonStore.setSettings({
-                              apiCompletionModelName: data.optionValue
-                            });
-                          }
-                        }}>
-                        {
-                          ['rwkv', 'text-davinci-003', 'text-davinci-002', 'text-curie-001', 'text-babbage-001', 'text-ada-001']
-                          .map((v, i) =>
-                            <Option key={i} value={v}>{v}</Option>
-                          )
-                        }
-                      </Dropdown>
-                    </div>
-                  } />
+          commonStore.platform === 'web' ?
+            (
+              <div className="flex flex-col gap-2">
+                <GeneralSettings />
+                <AdvancedGeneralSettings />
               </div>
-            </AccordionPanel>
-          </AccordionItem>
-        </Accordion>
+            )
+            :
+            (
+              <div className="flex flex-col gap-2">
+                <GeneralSettings />
+                <Labeled label={t('Automatic Updates Check')} flex spaceBetween content={
+                  <Switch checked={commonStore.settings.autoUpdatesCheck}
+                    onChange={(e, data) => {
+                      commonStore.setSettings({
+                        autoUpdatesCheck: data.checked
+                      });
+                      if (data.checked)
+                        checkUpdate(true);
+                    }} />
+                } />
+                {
+                  commonStore.settings.language === 'zh' &&
+                  <Labeled label={t('Use Gitee Updates Source')} flex spaceBetween content={
+                    <Switch checked={commonStore.settings.giteeUpdatesSource}
+                      onChange={(e, data) => {
+                        commonStore.setSettings({
+                          giteeUpdatesSource: data.checked
+                        });
+                      }} />
+                  } />
+                }
+                {
+                  commonStore.settings.language === 'zh' && commonStore.platform !== 'linux' &&
+                  <Labeled label={t('Use Tsinghua Pip Mirrors')} flex spaceBetween content={
+                    <Switch checked={commonStore.settings.cnMirror}
+                      onChange={(e, data) => {
+                        commonStore.setSettings({
+                          cnMirror: data.checked
+                        });
+                      }} />
+                  } />
+                }
+                <Labeled label={t('Allow external access to the API (service must be restarted)')} flex spaceBetween
+                  content={
+                    <Switch checked={commonStore.settings.host !== '127.0.0.1'}
+                      onChange={(e, data) => {
+                        commonStore.setSettings({
+                          host: data.checked ? '0.0.0.0' : '127.0.0.1'
+                        });
+                      }} />
+                  } />
+                <Accordion collapsible openItems={!commonStore.advancedCollapsed && 'advanced'} onToggle={(e, data) => {
+                  if (data.value === 'advanced')
+                    commonStore.setAdvancedCollapsed(!commonStore.advancedCollapsed);
+                }}>
+                  <AccordionItem value="advanced">
+                    <AccordionHeader ref={advancedHeaderRef} size="large">{t('Advanced')}</AccordionHeader>
+                    <AccordionPanel>
+                      <div className="flex flex-col gap-2 overflow-hidden">
+                        {commonStore.platform !== 'darwin' &&
+                          <Labeled label={t('Custom Models Path')}
+                            content={
+                              <Input className="grow" placeholder="./models"
+                                value={commonStore.settings.customModelsPath}
+                                onChange={(e, data) => {
+                                  commonStore.setSettings({
+                                    customModelsPath: data.value
+                                  });
+                                }} />
+                            } />
+                        }
+                        <Labeled label={t('Custom Python Path')} // if set, will not use precompiled cuda kernel
+                          content={
+                            <Input className="grow" placeholder="./py310/python"
+                              value={commonStore.settings.customPythonPath}
+                              onChange={(e, data) => {
+                                commonStore.setDepComplete(false);
+                                commonStore.setSettings({
+                                  customPythonPath: data.value
+                                });
+                              }} />
+                          } />
+                        <AdvancedGeneralSettings />
+                      </div>
+                    </AccordionPanel>
+                  </AccordionItem>
+                </Accordion>
+              </div>
+            )
+        }
       </div>
     } />
   );
 });
+
+export default Settings;

frontend/src/pages/Train.tsx

@@ -1,4 +1,4 @@
-import React, { FC, ReactElement, useEffect, useRef, useState } from 'react';
+import React, { FC, useEffect, useRef, useState } from 'react';
 import { useTranslation } from 'react-i18next';
 import { Button, Dropdown, Input, Option, Select, Switch, Tab, TabList } from '@fluentui/react-components';
 import {
@@ -24,7 +24,6 @@ import { Labeled } from '../components/Labeled';
 import { ToolTipButton } from '../components/ToolTipButton';
 import { DataUsageSettings20Regular, Folder20Regular } from '@fluentui/react-icons';
 import { useNavigate } from 'react-router';
-import { Precision } from './Configs';
 import {
   CategoryScale,
   Chart as ChartJS,
@@ -40,6 +39,12 @@ import { ChartJSOrUndefined } from 'react-chartjs-2/dist/types';
 import { WindowShow } from '../../wailsjs/runtime';
 import { t } from 'i18next';
 import { DialogButton } from '../components/DialogButton';
+import {
+  DataProcessParameters,
+  LoraFinetuneParameters,
+  LoraFinetunePrecision,
+  TrainNavigationItem
+} from '../types/train';
 
 ChartJS.register(
   CategoryScale,
@@ -86,39 +91,6 @@ const addLossDataToChart = (epoch: number, loss: number) => {
   commonStore.setChartData(commonStore.chartData);
 };
 
-export type DataProcessParameters = {
-  dataPath: string;
-  vocabPath: string;
-}
-
-export type LoraFinetunePrecision = 'bf16' | 'fp16' | 'tf32';
-
-export type LoraFinetuneParameters = {
-  baseModel: string;
-  ctxLen: number;
-  epochSteps: number;
-  epochCount: number;
-  epochBegin: number;
-  epochSave: number;
-  microBsz: number;
-  accumGradBatches: number;
-  preFfn: boolean;
-  headQk: boolean;
-  lrInit: string;
-  lrFinal: string;
-  warmupSteps: number;
-  beta1: number;
-  beta2: number;
-  adamEps: string;
-  devices: number;
-  precision: LoraFinetunePrecision;
-  gradCp: boolean;
-  loraR: number;
-  loraAlpha: number;
-  loraDropout: number;
-  loraLoad: string
-}
-
 const loraFinetuneParametersOptions: Array<[key: keyof LoraFinetuneParameters, type: string, name: string]> = [
   ['devices', 'number', 'Devices'],
   ['precision', 'LoraFinetunePrecision', 'Precision'],
@@ -154,7 +126,7 @@ const showError = (e: any) => {
 };
 
 const errorsMap = Object.entries({
-  'python3 ./finetune/lora/train.py': 'Memory is not enough, try to increase the virtual memory or use a smaller base model.',
+  'python3 ./finetune/lora/train.py': 'Memory is not enough, try to increase the virtual memory (Swap of WSL) or use a smaller base model.',
   'cuda out of memory': 'VRAM is not enough',
   'valueerror: high <= 0': 'Training data is not enough, reduce context length or add more data for training',
   '+= \'+ptx\'': 'You are using WSL 1 for training, please upgrade to WSL 2. e.g. Run "wsl --set-version Ubuntu-22.04 2"',
@@ -414,7 +386,7 @@ const LoraFinetune: FC = observer(() => {
                   contentText={t('The data path should be a directory or a file in jsonl format (more formats will be supported in the future).\n\n' +
                     'When you provide a directory path, all the txt files within that directory will be automatically converted into training data. ' +
                     'This is commonly used for large-scale training in writing, code generation, or knowledge bases.\n\n' +
-                    'The jsonl format file can be referenced at https://github.com/Abel2076/json2binidx_tool/blob/main/sample.jsonl.\n' +
+                    'The jsonl format file can be referenced at https://github.com/josStorer/RWKV-Runner/blob/master/finetune/data/sample.jsonl.\n' +
                     'You can also write it similar to OpenAI\'s playground format, as shown in https://platform.openai.com/playground/p/default-chat.\n' +
                     'Even for multi-turn conversations, they must be written in a single line using `\\n` to indicate line breaks. ' +
                     'If they are different dialogues or topics, they should be written in separate lines.')} />
@@ -568,10 +540,6 @@ const LoraFinetune: FC = observer(() => {
   );
 });
 
-type TrainNavigationItem = {
-  element: ReactElement;
-};
-
 const pages: { [label: string]: TrainNavigationItem } = {
   'LoRA Finetune': {
     element: <LoraFinetune />
@@ -582,7 +550,7 @@ const pages: { [label: string]: TrainNavigationItem } = {
 };
 
 
-export const Train: FC = () => {
+const Train: FC = () => {
   const { t } = useTranslation();
   const [tab, setTab] = useState('LoRA Finetune');
 
@@ -607,3 +575,5 @@ export const Train: FC = () => {
     </div>
   </div>;
 };
+
+export default Train;

frontend/src/pages/defaultConfigs.ts

@@ -1,5 +1,5 @@
-import { ModelConfig } from './Configs';
-import { CompletionPreset } from './Completion';
+import { CompletionPreset } from '../types/completion';
+import { ModelConfig } from '../types/configs';
 
 export const defaultCompositionPrompt = '<pad>';
 

frontend/src/pages/index.tsx

@@ -1,5 +1,4 @@
-import { ReactElement } from 'react';
-import { Configs } from './Configs';
+import { FC, lazy, LazyExoticComponent, ReactElement } from 'react';
 import {
   ArrowDownload20Regular,
   Chat20Regular,
@@ -12,21 +11,12 @@ import {
   Settings20Regular,
   Storage20Regular
 } from '@fluentui/react-icons';
-import { Home } from './Home';
-import { Chat } from './Chat';
-import { Models } from './Models';
-import { Train } from './Train';
-import { Settings } from './Settings';
-import { About } from './About';
-import { Downloads } from './Downloads';
-import { Completion } from './Completion';
-import { Composition } from './Composition';
 
 type NavigationItem = {
   label: string;
   path: string;
   icon: ReactElement;
-  element: ReactElement;
+  element: LazyExoticComponent<FC>;
   top: boolean;
 };
 
@@ -35,70 +25,70 @@ export const pages: NavigationItem[] = [
     label: 'Home',
     path: '/',
     icon: <Home20Regular />,
-    element: <Home />,
+    element: lazy(() => import('./Home')),
     top: true
   },
   {
     label: 'Chat',
     path: '/chat',
     icon: <Chat20Regular />,
-    element: <Chat />,
+    element: lazy(() => import('./Chat')),
     top: true
   },
   {
     label: 'Completion',
     path: '/completion',
     icon: <ClipboardEdit20Regular />,
-    element: <Completion />,
+    element: lazy(() => import('./Completion')),
     top: true
   },
   {
     label: 'Composition',
     path: '/composition',
     icon: <MusicNote220Regular />,
-    element: <Composition />,
+    element: lazy(() => import('./Composition')),
     top: true
   },
   {
     label: 'Configs',
     path: '/configs',
     icon: <DocumentSettings20Regular />,
-    element: <Configs />,
+    element: lazy(() => import('./Configs')),
     top: true
   },
   {
     label: 'Models',
     path: '/models',
     icon: <DataUsageSettings20Regular />,
-    element: <Models />,
+    element: lazy(() => import('./Models')),
     top: true
   },
   {
     label: 'Downloads',
     path: '/downloads',
     icon: <ArrowDownload20Regular />,
-    element: <Downloads />,
+    element: lazy(() => import('./Downloads')),
     top: true
   },
   {
     label: 'Train',
     path: '/train',
     icon: <Storage20Regular />,
-    element: <Train />,
+    element: lazy(() => import('./Train')),
     top: true
   },
   {
     label: 'Settings',
     path: '/settings',
     icon: <Settings20Regular />,
-    element: <Settings />,
+    element: lazy(() => import('./Settings')),
     top: false
   },
   {
     label: 'About',
     path: '/about',
     icon: <Info20Regular />,
-    element: <About />,
+    element: lazy(() => import('./About')),
     top: false
   }
 ];

frontend/src/startup.ts

@@ -1,43 +1,46 @@
-import commonStore, { Platform } from './stores/commonStore';
+import commonStore, { MonitorData, Platform } from './stores/commonStore';
 import { GetPlatform, ListDirFiles, ReadJson } from '../wailsjs/go/backend_golang/App';
 import { Cache, checkUpdate, downloadProgramFiles, LocalConfig, refreshLocalModels, refreshModels } from './utils';
 import { getStatus } from './apis';
 import { EventsOn, WindowSetTitle } from '../wailsjs/runtime';
 import manifest from '../../manifest.json';
 import { defaultModelConfigs, defaultModelConfigsMac } from './pages/defaultConfigs';
-import { Preset } from './pages/PresetsManager/PresetsButton';
-import { wslHandler } from './pages/Train';
 import { t } from 'i18next';
+import { Preset } from './types/presets';
 
 export async function startup() {
-  downloadProgramFiles();
-  EventsOn('downloadList', (data) => {
-    if (data)
-      commonStore.setDownloadList(data);
-  });
-  EventsOn('wsl', wslHandler);
-  EventsOn('wslerr', (e) => {
-    console.log(e);
-  });
-  initLocalModelsNotify();
-  initLoraModels();
-
   initPresets();
 
-  initHardwareMonitor();
-
   await GetPlatform().then(p => commonStore.setPlatform(p as Platform));
+
+  if (commonStore.platform !== 'web') {
+    downloadProgramFiles();
+    EventsOn('downloadList', (data) => {
+      if (data)
+        commonStore.setDownloadList(data);
+    });
+    EventsOn('wsl', (await import('./pages/Train')).wslHandler);
+    EventsOn('wslerr', (e) => {
+      console.log(e);
+    });
+    initLocalModelsNotify();
+    initLoraModels();
+    initHardwareMonitor();
+  }
+
   await initConfig();
 
-  initCache(true).then(initRemoteText); // depends on config customModelsPath
+  if (commonStore.platform !== 'web') {
+    initCache(true).then(initRemoteText); // depends on config customModelsPath
 
-  if (commonStore.settings.autoUpdatesCheck) // depends on config settings
-    checkUpdate();
+    if (commonStore.settings.autoUpdatesCheck) // depends on config settings
+      checkUpdate();
 
-  getStatus(1000).then(status => { // depends on config api port
-    if (status)
-      commonStore.setStatus(status);
-  });
+    getStatus(1000).then(status => { // depends on config api port
+      if (status)
+        commonStore.setStatus(status);
+    });
+  }
 }
 
 async function initRemoteText() {
@@ -88,7 +91,8 @@ async function initCache(initUnfinishedModels: boolean) {
 
 async function initPresets() {
   await ReadJson('presets.json').then((presets: Preset[]) => {
-    commonStore.setPresets(presets, false);
+    if (Array.isArray(presets))
+      commonStore.setPresets(presets, false);
   }).catch(() => {
   });
 }
@@ -121,19 +125,12 @@ async function initLocalModelsNotify() {
   });
 }
 
-type monitorData = {
-  usedMemory: number;
-  totalMemory: number;
-  gpuUsage: number;
-  gpuPower: number;
-  usedVram: number;
-  totalVram: number;
-}
-
 async function initHardwareMonitor() {
   EventsOn('monitor', (data: string) => {
-    const results: monitorData = JSON.parse(data);
-    if (results)
+    const results: MonitorData = JSON.parse(data);
+    if (results) {
+      commonStore.setMonitorData(results);
       WindowSetTitle(`RWKV-Runner (${t('RAM')}: ${results.usedMemory.toFixed(1)}/${results.totalMemory.toFixed(1)} GB, ${t('VRAM')}: ${(results.usedVram / 1024).toFixed(1)}/${(results.totalVram / 1024).toFixed(1)} GB, ${t('GPU Usage')}: ${results.gpuUsage}%)`);
+    }
   });
 }

frontend/src/stores/commonStore.ts

@@ -2,21 +2,20 @@ import { makeAutoObservable } from 'mobx';
 import { getUserLanguage, isSystemLightMode, saveCache, saveConfigs, savePresets } from '../utils';
 import { WindowSetDarkTheme, WindowSetLightTheme } from '../../wailsjs/runtime';
 import manifest from '../../../manifest.json';
-import { ModelConfig } from '../pages/Configs';
-import { Conversation } from '../pages/Chat';
-import { ModelSourceItem } from '../pages/Models';
-import { DownloadStatus } from '../pages/Downloads';
-import { SettingsType } from '../pages/Settings';
-import { IntroductionContent } from '../pages/Home';
-import { AboutContent } from '../pages/About';
 import i18n from 'i18next';
-import { CompletionPreset } from '../pages/Completion';
 import { defaultCompositionPrompt, defaultModelConfigs, defaultModelConfigsMac } from '../pages/defaultConfigs';
-import commonStore from './commonStore';
-import { Preset } from '../pages/PresetsManager/PresetsButton';
-import { DataProcessParameters, LoraFinetuneParameters } from '../pages/Train';
 import { ChartData } from 'chart.js';
-import { CompositionParams } from '../pages/Composition';
+import { Preset } from '../types/presets';
+import { AboutContent } from '../types/about';
+import { Attachment, Conversation } from '../types/chat';
+import { CompletionPreset } from '../types/completion';
+import { CompositionParams } from '../types/composition';
+import { ModelConfig } from '../types/configs';
+import { DownloadStatus } from '../types/downloads';
+import { IntroductionContent } from '../types/home';
+import { ModelSourceItem } from '../types/models';
+import { SettingsType } from '../types/settings';
+import { DataProcessParameters, LoraFinetuneParameters } from '../types/train';
 
 export enum ModelStatus {
   Offline,
@@ -31,9 +30,16 @@ export type Status = {
   device_name: string;
 }
 
-export type Platform = 'windows' | 'darwin' | 'linux';
+export type MonitorData = {
+  usedMemory: number;
+  totalMemory: number;
+  gpuUsage: number;
+  gpuPower: number;
+  usedVram: number;
+  totalVram: number;
+}
 
-const labels = ['January', 'February', 'March', 'April', 'May', 'June', 'July'];
+export type Platform = 'windows' | 'darwin' | 'linux' | 'web';
 
 class CommonStore {
   // global
@@ -42,6 +48,7 @@ class CommonStore {
     pid: 0,
     device_name: 'CPU'
   };
+  monitorData: MonitorData | null = null;
   depComplete: boolean = false;
   platform: Platform = 'windows';
   // presets manager
@@ -54,6 +61,9 @@ class CommonStore {
   conversation: Conversation = {};
   conversationOrder: string[] = [];
   activePreset: Preset | null = null;
+  attachmentUploading: boolean = false;
+  attachments: { [uuid: string]: Attachment[] } = {};
+  currentTempAttachment: Attachment | null = null;
   // completion
   completionPreset: CompletionPreset | null = null;
   completionGenerating: boolean = false;
@@ -74,6 +84,7 @@ class CommonStore {
   // configs
   currentModelConfigIndex: number = 0;
   modelConfigs: ModelConfig[] = [];
+  modelParamsCollapsed: boolean = true;
   // models
   modelSourceManifestList: string = 'https://cdn.jsdelivr.net/gh/josstorer/RWKV-Runner@master/manifest.json;';
   modelSourceList: ModelSourceItem[] = [];
@@ -95,7 +106,7 @@ class CommonStore {
     epochSteps: 200,
     epochCount: 20,
     epochBegin: 0,
-    epochSave: 2,
+    epochSave: 1,
     microBsz: 1,
     accumGradBatches: 8,
     preFfn: false,
@@ -127,7 +138,7 @@ class CommonStore {
     customModelsPath: './models',
     customPythonPath: '',
     apiUrl: '',
-    apiKey: 'sk-',
+    apiKey: '',
     apiChatModelName: 'rwkv',
     apiCompletionModelName: 'rwkv'
   };
@@ -167,7 +178,7 @@ class CommonStore {
   createModelConfig = (config: ModelConfig = defaultModelConfigs[0], saveConfig: boolean = true) => {
     if (config.name === defaultModelConfigs[0].name) {
       // deep copy
-      config = JSON.parse(JSON.stringify(commonStore.platform !== 'darwin' ? defaultModelConfigs[0] : defaultModelConfigsMac[0]));
+      config = JSON.parse(JSON.stringify(this.platform !== 'darwin' ? defaultModelConfigs[0] : defaultModelConfigsMac[0]));
       config.name = new Date().toLocaleString();
     }
     this.modelConfigs.push(config);
@@ -247,6 +258,10 @@ class CommonStore {
     this.completionGenerating = value;
   }
 
+  setMonitorData(value: MonitorData) {
+    this.monitorData = value;
+  }
+
   setPlatform(value: Platform) {
     this.platform = value;
   }
@@ -259,6 +274,10 @@ class CommonStore {
     this.advancedCollapsed = value;
   }
 
+  setModelParamsCollapsed(value: boolean) {
+    this.modelParamsCollapsed = value;
+  }
+
   setLastUnfinishedModelDownloads(value: DownloadStatus[]) {
     this.lastUnfinishedModelDownloads = value;
   }
@@ -320,6 +339,25 @@ class CommonStore {
   setLoraModels(value: string[]) {
     this.loraModels = value;
   }
+
+  setAttachmentUploading(value: boolean) {
+    this.attachmentUploading = value;
+  }
+
+  setAttachments(value: { [uuid: string]: Attachment[] }) {
+    this.attachments = value;
+  }
+
+  setAttachment(uuid: string, value: Attachment[] | null) {
+    if (value === null)
+      delete this.attachments[uuid];
+    else
+      this.attachments[uuid] = value;
+  }
+
+  setCurrentTempAttachment(value: Attachment | null) {
+    this.currentTempAttachment = value;
+  }
 }
 
 export default new CommonStore();

frontend/src/style.scss

@@ -1,12 +1,10 @@
 [data-theme='dark'] {
   @import 'highlight.js/scss/github-dark.scss';
-  @import 'github-markdown-css/github-markdown-dark.css';
   --color-neutral-muted: rgba(110, 118, 129, 0.4);
 }
 
 [data-theme='light'] {
   @import 'highlight.js/scss/github.scss';
-  @import 'github-markdown-css/github-markdown-light.css';
   --color-neutral-muted: rgba(150, 160, 170, 0.3);
 }
 
@@ -16,7 +14,6 @@
 
 body {
   margin: 0;
-  overflow: hidden;
   width: 100%;
   height: 100%;
 }

frontend/src/types/about.ts

@@ -0,0 +1 @@
+export type AboutContent = { [lang: string]: string }

frontend/src/types/chat.ts

@@ -0,0 +1,34 @@
+export const userName = 'M E';
+export const botName = 'A I';
+export const welcomeUuid = 'welcome';
+
+export enum MessageType {
+  Normal,
+  Error
+}
+
+export type Side = 'left' | 'right'
+export type Color = 'neutral' | 'brand' | 'colorful'
+export type MessageItem = {
+  sender: string,
+  type: MessageType,
+  color: Color,
+  avatarImg?: string,
+  time: string,
+  content: string,
+  side: Side,
+  done: boolean
+}
+export type Conversation = {
+  [uuid: string]: MessageItem
+}
+export type Role = 'assistant' | 'user' | 'system';
+export type ConversationMessage = {
+  role: Role;
+  content: string;
+}
+export type Attachment = {
+  name: string;
+  size: number;
+  content: string;
+}

frontend/src/types/completion.ts

@@ -0,0 +1,12 @@
+import { ApiParameters } from './configs';
+
+export type CompletionParams = Omit<ApiParameters, 'apiPort'> & {
+  stop: string,
+  injectStart: string,
+  injectEnd: string
+};
+export type CompletionPreset = {
+  name: string,
+  prompt: string,
+  params: CompletionParams
+}

frontend/src/types/composition.ts

@@ -0,0 +1,12 @@
+import { NoteSequence } from '@magenta/music/esm/protobuf';
+
+export type CompositionParams = {
+  prompt: string,
+  maxResponseToken: number,
+  temperature: number,
+  topP: number,
+  autoPlay: boolean,
+  useLocalSoundFont: boolean,
+  midi: ArrayBuffer | null,
+  ns: NoteSequence | null
+}

frontend/src/types/configs.ts

@@ -0,0 +1,29 @@
+export type ApiParameters = {
+  apiPort: number
+  maxResponseToken: number;
+  temperature: number;
+  topP: number;
+  presencePenalty: number;
+  frequencyPenalty: number;
+}
+export type Device = 'CPU' | 'CUDA' | 'CUDA-Beta' | 'WebGPU' | 'MPS' | 'Custom';
+export type Precision = 'fp16' | 'int8' | 'fp32';
+export type ModelParameters = {
+  // different models can not have the same name
+  modelName: string;
+  device: Device;
+  precision: Precision;
+  storedLayers: number;
+  maxStoredLayers: number;
+  useCustomCuda?: boolean;
+  customStrategy?: string;
+  useCustomTokenizer?: boolean;
+  customTokenizer?: string;
+}
+export type ModelConfig = {
+  // different configs can have the same name
+  name: string;
+  apiParameters: ApiParameters;
+  modelParameters: ModelParameters;
+  enableWebUI?: boolean;
+}

frontend/src/types/downloads.ts

@@ -0,0 +1,11 @@
+export type DownloadStatus = {
+  name: string;
+  path: string;
+  url: string;
+  transferred: number;
+  size: number;
+  speed: number;
+  progress: number;
+  downloading: boolean;
+  done: boolean;
+}

frontend/src/types/home.ts

@@ -0,0 +1,11 @@
+import { ReactElement } from 'react';
+
+export type IntroductionContent = {
+  [lang: string]: string
+}
+export type NavCard = {
+  label: string;
+  desc: string;
+  path: string;
+  icon: ReactElement;
+};

frontend/src/types/models.ts

@@ -0,0 +1,14 @@
+export type ModelSourceItem = {
+  name: string;
+  size: number;
+  lastUpdated: string;
+  desc?: { [lang: string]: string | undefined; };
+  SHA256?: string;
+  url?: string;
+  downloadUrl?: string;
+  isComplete?: boolean;
+  isLocal?: boolean;
+  localSize?: number;
+  lastUpdatedMs?: number;
+  hide?: boolean;
+};

frontend/src/types/presets.ts

@@ -0,0 +1,30 @@
+import { ReactElement } from 'react';
+
+import { ConversationMessage } from './chat';
+
+export type PresetType = 'chat' | 'completion' | 'chatInCompletion'
+export type Preset = {
+  name: string,
+  tag: string,
+  // if name and sourceUrl are same, it will be overridden when importing
+  sourceUrl: string,
+  desc: string,
+  avatarImg: string,
+  type: PresetType,
+  // chat
+  welcomeMessage: string,
+  messages: ConversationMessage[],
+  displayPresetMessages: boolean,
+  // completion
+  prompt: string,
+  stop: string,
+  injectStart: string,
+  injectEnd: string,
+  presystem?: boolean,
+  userName?: string,
+  assistantName?: string
+}
+export type PresetsNavigationItem = {
+  icon: ReactElement;
+  element: ReactElement;
+};

frontend/src/types/settings.ts

@@ -0,0 +1,21 @@
+export const Languages = {
+  dev: 'English', // i18n default
+  zh: '简体中文',
+  ja: '日本語'
+};
+export type Language = keyof typeof Languages;
+export type SettingsType = {
+  language: Language
+  darkMode: boolean
+  autoUpdatesCheck: boolean
+  giteeUpdatesSource: boolean
+  cnMirror: boolean
+  host: string
+  dpiScaling: number
+  customModelsPath: string
+  customPythonPath: string
+  apiUrl: string
+  apiKey: string
+  apiChatModelName: string
+  apiCompletionModelName: string
+}

frontend/src/types/train.ts

@@ -0,0 +1,35 @@
+import { ReactElement } from 'react';
+
+export type DataProcessParameters = {
+  dataPath: string;
+  vocabPath: string;
+}
+export type LoraFinetunePrecision = 'bf16' | 'fp16' | 'tf32';
+export type LoraFinetuneParameters = {
+  baseModel: string;
+  ctxLen: number;
+  epochSteps: number;
+  epochCount: number;
+  epochBegin: number;
+  epochSave: number;
+  microBsz: number;
+  accumGradBatches: number;
+  preFfn: boolean;
+  headQk: boolean;
+  lrInit: string;
+  lrFinal: string;
+  warmupSteps: number;
+  beta1: number;
+  beta2: number;
+  adamEps: string;
+  devices: number;
+  precision: LoraFinetunePrecision;
+  gradCp: boolean;
+  loraR: number;
+  loraAlpha: number;
+  loraDropout: number;
+  loraLoad: string
+}
+export type TrainNavigationItem = {
+  element: ReactElement;
+};

frontend/src/utils/index.tsx

@@ -1,6 +1,5 @@
 import {
   AddToDownloadList,
-  CopyFile,
   DeleteFile,
   DepCheck,
   InstallPyDep,
@@ -16,13 +15,13 @@ import { toast } from 'react-toastify';
 import { t } from 'i18next';
 import { ToastOptions } from 'react-toastify/dist/types';
 import { Button } from '@fluentui/react-components';
-import { Language, Languages, SettingsType } from '../pages/Settings';
-import { ModelSourceItem } from '../pages/Models';
-import { ModelConfig, ModelParameters } from '../pages/Configs';
-import { DownloadStatus } from '../pages/Downloads';
-import { DataProcessParameters, LoraFinetuneParameters } from '../pages/Train';
-import { BrowserOpenURL, WindowShow } from '../../wailsjs/runtime';
+import { BrowserOpenURL, EventsOff, EventsOn, WindowShow } from '../../wailsjs/runtime';
 import { NavigateFunction } from 'react-router';
+import { ModelConfig, ModelParameters } from '../types/configs';
+import { DownloadStatus } from '../types/downloads';
+import { ModelSourceItem } from '../types/models';
+import { Language, Languages, SettingsType } from '../types/settings';
+import { DataProcessParameters, LoraFinetuneParameters } from '../types/train';
 
 export type Cache = {
   version: string
@@ -184,7 +183,7 @@ export const getStrategy = (modelConfig: ModelConfig | undefined = undefined) =>
     case 'CUDA':
     case 'CUDA-Beta':
       if (avoidOverflow)
-        strategy = 'cuda fp32 *1 -> ';
+        strategy = params.useCustomCuda ? 'cuda fp16 *1 -> ' : 'cuda fp32 *1 -> ';
       strategy += 'cuda ';
       strategy += params.precision === 'fp16' ? 'fp16' : params.precision === 'int8' ? 'fp16i8' : 'fp32';
       if (params.storedLayers < params.maxStoredLayers)
@@ -283,6 +282,32 @@ export function bytesToKb(size: number) {
   return (size / 1024).toFixed(2);
 }
 
+export function bytesToReadable(size: number) {
+  if (size < 1024) return size + ' B';
+  else if (size < 1024 * 1024) return bytesToKb(size) + ' KB';
+  else if (size < 1024 * 1024 * 1024) return bytesToMb(size) + ' MB';
+  else return bytesToGb(size) + ' GB';
+}
+
+export function getServerRoot(defaultLocalPort: number) {
+  const customApiUrl = commonStore.settings.apiUrl.trim().replace(/\/$/, '');
+  if (customApiUrl)
+    return customApiUrl;
+  if (commonStore.platform === 'web')
+    return '';
+  return `http://127.0.0.1:${defaultLocalPort}`;
+}
+
+export function absPathAsset(path: string) {
+  if (commonStore.platform === 'web')
+    return path;
+  if ((path.length > 0 && path[0] === '/') ||
+    (path.length > 1 && path[1] === ':')) {
+    return '=>' + path;
+  }
+  return path;
+}
+
 export async function checkUpdate(notifyEvenLatest: boolean = false) {
   fetch(!commonStore.settings.giteeUpdatesSource ?
     'https://api.github.com/repos/josstorer/RWKV-Runner/releases/latest' :
@@ -308,27 +333,47 @@ export async function checkUpdate(notifyEvenLatest: boolean = false) {
                           `https://gitee.com/josc146/RWKV-Runner/releases/download/${versionTag}/${asset.name}`;
                         toastWithButton(t('New Version Available') + ': ' + versionTag, t('Update'), () => {
                           DeleteFile('cache.json');
-                          toast(t('Downloading update, please wait. If it is not completed, please manually download the program from GitHub and replace the original program.'), {
-                            type: 'info',
-                            position: 'bottom-left',
-                            autoClose: false
-                          });
-                          setTimeout(() => {
-                            UpdateApp(updateUrl).then(() => {
-                              toast(t('Update completed, please restart the program.'), {
-                                  type: 'success',
-                                  position: 'bottom-left',
-                                  autoClose: false
-                                }
-                              );
-                            }).catch((e) => {
-                              toast(t('Update Error') + ' - ' + (e.message || e), {
-                                type: 'error',
+                          const progressId = 'update_app';
+                          const progressEvent = 'updateApp';
+                          const updateProgress = (ds: DownloadStatus | null) => {
+                            const content =
+                              t('Downloading update, please wait. If it is not completed, please manually download the program from GitHub and replace the original program.')
+                              + (ds ? ` (${ds.progress.toFixed(2)}%  ${bytesToReadable(ds.transferred)}/${bytesToReadable(ds.size)})` : '');
+                            const options: ToastOptions = {
+                              type: 'info',
+                              position: 'bottom-left',
+                              autoClose: false,
+                              toastId: progressId,
+                              hideProgressBar: false,
+                              progress: ds ? ds.progress / 100 : 0
+                            };
+                            if (toast.isActive(progressId))
+                              toast.update(progressId, {
+                                render: content,
+                                ...options
+                              });
+                            else
+                              toast(content, options);
+                          };
+                          updateProgress(null);
+                          EventsOn(progressEvent, updateProgress);
+                          UpdateApp(updateUrl).then(() => {
+                            toast(t('Update completed, please restart the program.'), {
+                                type: 'success',
                                 position: 'bottom-left',
                                 autoClose: false
-                              });
+                              }
+                            );
+                          }).catch((e) => {
+                            toast(t('Update Error') + ' - ' + (e.message || e), {
+                              type: 'error',
+                              position: 'bottom-left',
+                              autoClose: false
                             });
-                          }, 500);
+                          }).finally(() => {
+                            toast.dismiss(progressId);
+                            EventsOff(progressEvent);
+                          });
                         }, {
                           autoClose: false,
                           position: 'bottom-left'
@@ -402,8 +447,6 @@ export const checkDependencies = async (navigate: NavigateFunction) => {
       return false;
     }
     commonStore.setDepComplete(true);
-    if (commonStore.platform === 'windows')
-      CopyFile('./backend-python/wkv_cuda_utils/wkv_cuda_model.py', './py310/Lib/site-packages/rwkv/model.py');
   }
   return true;
 };
@@ -428,12 +471,16 @@ export function toastWithButton(text: string, buttonText: string, onClickButton:
   return id;
 }
 
-export function getSupportedCustomCudaFile() {
+export function getSupportedCustomCudaFile(isBeta: boolean) {
   if ([' 10', ' 16', ' 20', ' 30', 'MX', 'Tesla P', 'Quadro P', 'NVIDIA P', 'TITAN X', 'TITAN RTX', 'RTX A',
     'Quadro RTX 4000', 'Quadro RTX 5000', 'Tesla T4', 'NVIDIA A10', 'NVIDIA A40'].some(v => commonStore.status.device_name.includes(v)))
-    return './backend-python/wkv_cuda_utils/wkv_cuda10_30.pyd';
+    return isBeta ?
+      './backend-python/wkv_cuda_utils/beta/wkv_cuda10_30.pyd' :
+      './backend-python/wkv_cuda_utils/wkv_cuda10_30.pyd';
   else if ([' 40', 'RTX 5000 Ada', 'RTX 6000 Ada', 'RTX TITAN Ada', 'NVIDIA L40'].some(v => commonStore.status.device_name.includes(v)))
-    return './backend-python/wkv_cuda_utils/wkv_cuda40.pyd';
+    return isBeta ?
+      './backend-python/wkv_cuda_utils/beta/wkv_cuda40.pyd' :
+      './backend-python/wkv_cuda_utils/wkv_cuda40.pyd';
   else
     return '';
 }

frontend/src/webWails.js

@@ -0,0 +1,157 @@
+function defineRuntime(name, func) {
+  window.runtime[name] = func
+}
+
+function defineApp(name, func) {
+  window.go['backend_golang']['App'][name] = func
+}
+
+if (!window.runtime) {
+  window.runtime = {}
+  document.title += ' WebUI'
+
+  // not implemented
+  defineRuntime('EventsOnMultiple', () => {
+  })
+  defineRuntime('WindowSetLightTheme', () => {
+  })
+  defineRuntime('WindowSetDarkTheme', () => {
+  })
+  defineRuntime('WindowShow', () => {
+  })
+  defineRuntime('WindowHide', () => {
+  })
+
+  // implemented
+  defineRuntime('ClipboardGetText', async () => {
+    return await navigator.clipboard.readText()
+  })
+  defineRuntime('ClipboardSetText', async (text) => {
+    await navigator.clipboard.writeText(text)
+    return true
+  })
+  defineRuntime('WindowSetTitle', (title) => {
+    document.title = title
+  })
+  defineRuntime('BrowserOpenURL', (url) => {
+    window.open(url, '_blank', 'noopener, noreferrer')
+  })
+}
+
+if (!window.go) {
+  window.go = {}
+  window.go['backend_golang'] = {}
+  window.go['backend_golang']['App'] = {}
+
+  // not implemented
+  defineApp('AddToDownloadList', async () => {
+  })
+  defineApp('ContinueDownload', async () => {
+  })
+  defineApp('ConvertData', async () => {
+  })
+  defineApp('ConvertModel', async () => {
+  })
+  defineApp('ConvertSafetensors', async () => {
+  })
+  defineApp('CopyFile', async () => {
+  })
+  defineApp('DeleteFile', async () => {
+  })
+  defineApp('DepCheck', async () => {
+  })
+  defineApp('DownloadFile', async () => {
+  })
+  defineApp('GetPyError', async () => {
+  })
+  defineApp('InstallPyDep', async () => {
+  })
+  defineApp('IsPortAvailable', async () => {
+  })
+  defineApp('MergeLora', async () => {
+  })
+  defineApp('OpenFileFolder', async () => {
+  })
+  defineApp('PauseDownload', async () => {
+  })
+  defineApp('ReadFileInfo', async () => {
+  })
+  defineApp('RestartApp', async () => {
+  })
+  defineApp('StartServer', async () => {
+  })
+  defineApp('StartWebGPUServer', async () => {
+  })
+  defineApp('UpdateApp', async () => {
+  })
+  defineApp('WslCommand', async () => {
+  })
+  defineApp('WslEnable', async () => {
+  })
+  defineApp('WslInstallUbuntu', async () => {
+  })
+  defineApp('WslIsEnabled', async () => {
+  })
+  defineApp('WslStart', async () => {
+  })
+  defineApp('WslStop', async () => {
+  })
+
+  // implemented
+  defineApp('FileExists', async () => {
+    return false
+  })
+  defineApp('GetPlatform', async () => {
+    return 'web'
+  })
+  defineApp('ListDirFiles', async () => {
+    return []
+  })
+  defineApp('OpenOpenFileDialog', async (filterPattern) => {
+    return new Promise((resolve, reject) => {
+      const input = document.createElement('input')
+      input.type = 'file'
+      input.accept = filterPattern
+        .replaceAll('*.txt', 'text/plain')
+        .replaceAll('*.', 'application/')
+        .replaceAll(';', ',')
+
+      input.onchange = e => {
+        const file = e.target?.files[0]
+        if (file.type === 'text/plain') {
+          const reader = new FileReader()
+          reader.readAsText(file, 'UTF-8')
+
+          reader.onload = readerEvent => {
+            const content = readerEvent.target?.result
+            resolve({
+              blob: file,
+              content: content
+            })
+          }
+        } else {
+          resolve({
+            blob: file
+          })
+        }
+      }
+      input.click()
+    })
+  })
+  defineApp('OpenSaveFileDialog', async (filterPattern, defaultFileName, savedContent) => {
+    const saver = await import('file-saver')
+    saver.saveAs(new Blob([savedContent], { type: 'text/plain;charset=utf-8' }), defaultFileName)
+    return ''
+  })
+  defineApp('OpenSaveFileDialogBytes', async (filterPattern, defaultFileName, savedContent) => {
+    const saver = await import('file-saver')
+    saver.saveAs(new Blob([new Uint8Array(savedContent)], { type: 'octet/stream' }), defaultFileName)
+    return ''
+  })
+  defineApp('ReadJson', async (fileName) => {
+    return JSON.parse(localStorage.getItem(fileName))
+  })
+  defineApp('SaveJson', async (fileName, data) => {
+    localStorage.setItem(fileName, JSON.stringify(data))
+  })
+}

frontend/vite.config.ts

@@ -1,6 +1,37 @@
-import {defineConfig} from 'vite';
+// @ts-ignore
+import { dependencies } from './package.json';
+import { defineConfig } from 'vite';
 import react from '@vitejs/plugin-react';
-import {visualizer} from 'rollup-plugin-visualizer';
+import { visualizer } from 'rollup-plugin-visualizer';
+
+// dependencies that exist anywhere
+const vendor = [
+  'react', 'react-dom', 'react-router', 'react-router-dom',
+  '@fluentui/react-icons',
+  'mobx', 'mobx-react-lite',
+  'i18next', 'react-i18next',
+  'usehooks-ts', 'react-toastify',
+  'classnames'
+];
+
+const embedded = [
+  // split @fluentui/react-components by components
+  '@fluentui/react-components',
+
+  // dependencies that exist in single component
+  'react-beautiful-dnd',
+  '@magenta/music', 'html-midi-player',
+  'react-markdown', 'rehype-highlight', 'rehype-raw', 'remark-breaks', 'remark-gfm'
+];
+
+function renderChunks(deps: Record<string, string>) {
+  let chunks = {};
+  Object.keys(deps).forEach((key) => {
+    if ([...vendor, ...embedded].includes(key)) return;
+    chunks[key] = [key];
+  });
+  return chunks;
+}
 
 // https://vitejs.dev/config/
 export default defineConfig({
@@ -9,5 +40,16 @@ export default defineConfig({
       template: 'treemap',
       gzipSize: true,
       brotliSize: true
-    })]
+    })],
+  build: {
+    chunkSizeWarningLimit: 3000,
+    rollupOptions: {
+      output: {
+        manualChunks: {
+          vendor,
+          ...renderChunks(dependencies)
+        }
+      }
+    }
+  }
 });

frontend/wailsjs/go/backend_golang/App.d.ts

@@ -28,12 +28,16 @@ export function GetPyError():Promise<string>;
 
 export function InstallPyDep(arg1:string,arg2:boolean):Promise<string>;
 
+export function IsPortAvailable(arg1:number):Promise<boolean>;
+
 export function ListDirFiles(arg1:string):Promise<Array<backend_golang.FileInfo>>;
 
 export function MergeLora(arg1:string,arg2:boolean,arg3:number,arg4:string,arg5:string,arg6:string):Promise<string>;
 
 export function OpenFileFolder(arg1:string,arg2:boolean):Promise<void>;
 
+export function OpenOpenFileDialog(arg1:string):Promise<string>;
+
 export function OpenSaveFileDialog(arg1:string,arg2:string,arg3:string):Promise<string>;
 
 export function OpenSaveFileDialogBytes(arg1:string,arg2:string,arg3:Array<number>):Promise<string>;
@@ -48,7 +52,7 @@ export function RestartApp():Promise<void>;
 
 export function SaveJson(arg1:string,arg2:any):Promise<void>;
 
-export function StartServer(arg1:string,arg2:number,arg3:string,arg4:boolean):Promise<string>;
+export function StartServer(arg1:string,arg2:number,arg3:string,arg4:boolean,arg5:boolean):Promise<string>;
 
 export function StartWebGPUServer(arg1:number,arg2:string):Promise<string>;