feat: order env for tensorrt_llm (#10916)

agent/app/service/tensorrt_llm.go

@@ -13,6 +13,7 @@ import (
 	"github.com/1Panel-dev/1Panel/agent/global"
 	"github.com/1Panel-dev/1Panel/agent/utils/compose"
 	"github.com/1Panel-dev/1Panel/agent/utils/docker"
+	"github.com/1Panel-dev/1Panel/agent/utils/env"
 	"github.com/1Panel-dev/1Panel/agent/utils/files"
 	"github.com/subosito/gotenv"
 	"gopkg.in/yaml.v3"
@@ -171,7 +172,7 @@ func handleLLMParams(llm *model.TensorRTLLM, create request.TensorRTLLMCreate) e
 
 	var volumes []interface{}
 	var defaultVolumes = map[string]string{
-		"${MODEL_PATH}": "/models",
+		"${MODEL_PATH}": "${MODEL_PATH}",
 	}
 	for k, v := range defaultVolumes {
 		volumes = append(volumes, fmt.Sprintf("%s:%s", k, v))
@@ -191,23 +192,24 @@ func handleLLMParams(llm *model.TensorRTLLM, create request.TensorRTLLMCreate) e
 }
 
 func handleLLMEnv(llm *model.TensorRTLLM, create request.TensorRTLLMCreate) gotenv.Env {
-	env := make(gotenv.Env)
+	envMap := make(gotenv.Env)
-	env["CONTAINER_NAME"] = create.ContainerName
+	envMap["CONTAINER_NAME"] = create.ContainerName
-	env["MODEL_PATH"] = create.ModelDir
+	envMap["MODEL_PATH"] = create.ModelDir
-	env["VERSION"] = create.Version
+	envMap["VERSION"] = create.Version
-	env["IMAGE"] = create.Image
+	envMap["IMAGE"] = create.Image
-	env["COMMAND"] = create.Command
+	envMap["COMMAND"] = create.Command
 	for i, port := range create.ExposedPorts {
 		containerPortStr := fmt.Sprintf("CONTAINER_PORT_%d", i)
 		hostPortStr := fmt.Sprintf("HOST_PORT_%d", i)
 		hostIPStr := fmt.Sprintf("HOST_IP_%d", i)
-		env[containerPortStr] = strconv.Itoa(port.ContainerPort)
+		envMap[containerPortStr] = strconv.Itoa(port.ContainerPort)
-		env[hostPortStr] = strconv.Itoa(port.HostPort)
+		envMap[hostPortStr] = strconv.Itoa(port.HostPort)
-		env[hostIPStr] = port.HostIP
+		envMap[hostIPStr] = port.HostIP
 	}
-	envStr, _ := gotenv.Marshal(env)
+	orders := []string{"MODEL_PATH", "COMMAND"}
+	envStr, _ := env.MarshalWithOrder(envMap, orders)
 	llm.Env = envStr
-	return env
+	return envMap
 }
 
 func (t TensorRTLLMService) Create(create request.TensorRTLLMCreate) error {
@@ -250,10 +252,10 @@ func (t TensorRTLLMService) Create(create request.TensorRTLLMCreate) error {
 	if err := handleLLMParams(tensorrtLLM, create); err != nil {
 		return err
 	}
-	env := handleLLMEnv(tensorrtLLM, create)
+	envMap := handleLLMEnv(tensorrtLLM, create)
 	llmDir := path.Join(global.Dir.TensorRTLLMDir, create.Name)
 	envPath := path.Join(llmDir, ".env")
-	if err := gotenv.Write(env, envPath); err != nil {
+	if err := env.Write(envMap, envPath); err != nil {
 		return err
 	}
 	dockerComposePath := path.Join(llmDir, "docker-compose.yml")
@@ -287,12 +289,12 @@ func (t TensorRTLLMService) Update(req request.TensorRTLLMUpdate) error {
 		return err
 	}
 
-	env := handleLLMEnv(tensorrtLLM, req.TensorRTLLMCreate)
+	envMap := handleLLMEnv(tensorrtLLM, req.TensorRTLLMCreate)
-	envStr, _ := gotenv.Marshal(env)
+	envStr, _ := gotenv.Marshal(envMap)
 	tensorrtLLM.Env = envStr
 	llmDir := path.Join(global.Dir.TensorRTLLMDir, tensorrtLLM.Name)
 	envPath := path.Join(llmDir, ".env")
-	if err := gotenv.Write(env, envPath); err != nil {
+	if err := env.Write(envMap, envPath); err != nil {
 		return err
 	}
 	dockerComposePath := path.Join(llmDir, "docker-compose.yml")

agent/utils/env/env.go

@@ -10,7 +10,7 @@ import (
 )
 
 func Write(envMap map[string]string, filename string) error {
-	content, err := marshal(envMap)
+	content, err := Marshal(envMap)
 	if err != nil {
 		return err
 	}
@@ -26,7 +26,7 @@ func Write(envMap map[string]string, filename string) error {
 	return file.Sync()
 }
 
-func marshal(envMap map[string]string) (string, error) {
+func Marshal(envMap map[string]string) (string, error) {
 	lines := make([]string, 0, len(envMap))
 	for k, v := range envMap {
 		if d, err := strconv.Atoi(v); err == nil && !isStartWithZero(v) {
@@ -37,10 +37,47 @@ func marshal(envMap map[string]string) (string, error) {
 			lines = append(lines, fmt.Sprintf(`%s="%s"`, k, v))
 		}
 	}
-	sort.Strings(lines)
 	return strings.Join(lines, "\n"), nil
 }
 
+func MarshalWithOrder(envMap map[string]string, orders []string) (string, error) {
+	lines := make([]string, 0, len(envMap))
+	for _, k := range orders {
+		if v, ok := envMap[k]; ok {
+			lines = append(lines, formatEnvLine(k, v))
+		}
+	}
+
+	extraKeys := make([]string, 0)
+	for k := range envMap {
+		found := false
+		for _, okk := range orders {
+			if k == okk {
+				found = true
+				break
+			}
+		}
+		if !found {
+			extraKeys = append(extraKeys, k)
+		}
+	}
+	sort.Strings(extraKeys)
+	for _, k := range extraKeys {
+		lines = append(lines, formatEnvLine(k, envMap[k]))
+	}
+	return strings.Join(lines, "\n"), nil
+}
+
+func formatEnvLine(k, v string) string {
+	if d, err := strconv.Atoi(v); err == nil && !isStartWithZero(v) {
+		return fmt.Sprintf(`%s=%d`, k, d)
+	} else if hasEvenDoubleQuotes(v) {
+		return fmt.Sprintf(`%s='%s'`, k, v)
+	} else {
+		return fmt.Sprintf(`%s="%s"`, k, v)
+	}
+}
+
 func GetEnvValueByKey(envPath, key string) (string, error) {
 	envMap, err := godotenv.Read(envPath)
 	if err != nil {

frontend/src/lang/modules/en.ts

@@ -744,7 +744,7 @@ const message = {
             llm: 'TensorRT LLM',
             modelDir: 'Model Directory',
             commandHelper:
-                'After /models in the startup command, the model name needs to be completed; if external access is required, set the port in the command to be the same as the application port',
+                'If external access is needed, set the port in the command to be the same as the application port',
             imageAlert:
                 'Due to the large image size, it is recommended to manually download the image to the server before installation',
             modelSpeedup: 'Enable model acceleration',

frontend/src/lang/modules/es-es.ts

@@ -744,7 +744,7 @@ const message = {
             llm: 'TensorRT LLM',
             modelDir: 'Directorio del Modelo',
             commandHelper:
-                'Después de /models en el comando de inicio, se debe completar el nombre del modelo; si se requiere acceso externo, configure el puerto en el comando para que sea el mismo que el puerto de la aplicación',
+                'Si se necesita acceso externo, establezca el puerto en el comando para que sea el mismo que el puerto de la aplicación',
             imageAlert:
                 'Debido al gran tamaño de la imagen, se recomienda descargar manualmente la imagen al servidor antes de la instalación',
             modelSpeedup: 'Habilitar aceleración de modelo',

frontend/src/lang/modules/ja.ts

@@ -731,7 +731,7 @@ const message = {
             llm: 'TensorRT LLM',
             modelDir: 'モデルディレクトリ',
             commandHelper:
-                '起動コマンドの /models の後にはモデル名を補完する必要があります；外部アクセスが必要な場合は、コマンド内のポートをアプリケーションポートと同じに設定してください',
+                '外部アクセスが必要な場合は、コマンド内のポートをアプリケーションポートと同じに設定してください',
             imageAlert:
                 'イメージサイズが大きいため、インストール前にサーバーにイメージを手動でダウンロードすることをお勧めします',
             modelSpeedup: 'モデル加速を有効化',

frontend/src/lang/modules/ko.ts

@@ -726,8 +726,7 @@ const message = {
         tensorRT: {
             llm: 'TensorRT LLM',
             modelDir: '모델 디렉토리',
-            commandHelper:
+            commandHelper: '외부 액세스가 필요한 경우 명령에서 포트를 애플리케이션 포트와 동일하게 설정하십시오',
-                '시작 명령의 /models 뒤에는 모델 이름을 완성해야 합니다; 외부 액세스가 필요한 경우 명령의 포트를 애플리케이션 포트와 동일하게 설정하세요',
             imageAlert: '이미지 크기가 크므로 설치 전에 서버에 이미지를 수동으로 다운로드하는 것이 좋습니다',
             modelSpeedup: '모델 가속 활성화',
             modelType: '모델 유형',

frontend/src/lang/modules/ms.ts

@@ -743,8 +743,7 @@ const message = {
         tensorRT: {
             llm: 'TensorRT LLM',
             modelDir: 'Direktori Model',
-            commandHelper:
+            commandHelper: 'Jika akses luar diperlukan, tetapkan port dalam arahan sama dengan port aplikasi',
-                'Selepas /models dalam arahan permulaan, nama model perlu dilengkapkan; jika akses luar diperlukan, tetapkan port dalam arahan sama dengan port aplikasi',
             imageAlert:
                 'Disebabkan saiz imej yang besar, disyorkan untuk memuat turun imej secara manual ke pelayan sebelum pemasangan',
             modelSpeedup: 'Dayakan pecutan model',

frontend/src/lang/modules/pt-br.ts

@@ -740,7 +740,7 @@ const message = {
             llm: 'TensorRT LLM',
             modelDir: 'Diretório do Modelo',
             commandHelper:
-                'Após /models no comando de inicialização, o nome do modelo precisa ser completado; se for necessário acesso externo, defina a porta no comando para ser a mesma que a porta do aplicativo',
+                'Se for necessário acesso externo, defina a porta no comando para ser a mesma que a porta do aplicativo',
             imageAlert:
                 'Devido ao grande tamanho da imagem, recomenda-se baixar manualmente a imagem para o servidor antes da instalação',
             modelSpeedup: 'Ativar aceleração de modelo',

frontend/src/lang/modules/ru.ts

@@ -737,8 +737,7 @@ const message = {
         tensorRT: {
             llm: 'TensorRT LLM',
             modelDir: 'Каталог модели',
-            commandHelper:
+            commandHelper: 'Если требуется внешний доступ, установите порт в команде таким же, как порт приложения',
-                'После /models в команде запуска необходимо указать имя модели; если требуется внешний доступ, установите порт в команде таким же, как порт приложения',
             imageAlert:
                 'Из-за большого размера образа рекомендуется вручную загрузить образ на сервер перед установкой',
             modelSpeedup: 'Включить ускорение модели',

frontend/src/lang/modules/tr.ts

@@ -752,7 +752,7 @@ const message = {
             llm: 'TensorRT LLM',
             modelDir: 'Model Dizini',
             commandHelper:
-                'Başlatma komutundaki /models sonrasında model adı tamamlanmalıdır; harici erişim gerekiyorsa, komuttaki bağlantı noktasını uygulama bağlantı noktasıyla aynı olacak şekilde ayarlayın',
+                'Harici erişim gerekiyorsa, komuttaki bağlantı noktasını uygulama bağlantı noktasıyla aynı olacak şekilde ayarlayın',
             imageAlert:
                 'Görüntü boyutu büyük olduğundan, kurulumdan önce görüntüyü sunucuya manuel olarak indirmeniz önerilir',
             modelSpeedup: 'Model hızlandırmayı etkinleştir',

frontend/src/lang/modules/zh-Hant.ts

@@ -714,7 +714,7 @@ const message = {
         tensorRT: {
             llm: 'TensorRT LLM',
             modelDir: '模型目錄',
-            commandHelper: '啟動指令中的 /models 後需補全模型名稱；若需外部訪問，請將指令中的埠設定為與應用埠相同',
+            commandHelper: '若需外部訪問，請將命令中的端口設置為與應用端口相同',
             imageAlert: '由於鏡像較大，建議先手動將鏡像下載到伺服器後再進行安裝',
             modelSpeedup: '啟用模型加速',
             modelType: '模型類型',