refactor: 添加数据集元数据加载和保存功能，重构相关逻辑

src-tauri/src/commands.rs

@@ -1,4 +1,5 @@
 use crate::config::{AppConfig, AppConfigState, ProxyKind};
+use crate::dataset_meta::{load_dataset_meta, save_dataset_meta, DatasetMeta};
 use tauri::State;
 use tauri::{AppHandle, WebviewWindow};
 
@@ -55,6 +56,16 @@ pub fn list_proxy_kind_options() -> Vec<SelectOption> {
     ]
 }
 
+#[tauri::command]
+pub fn load_dataset_meta_by_dir(dataset_dir: String) -> Result<DatasetMeta, String> {
+    load_dataset_meta(&dataset_dir).map_err(|e| format!("读取数据集元数据失败: {e}"))
+}
+
+#[tauri::command]
+pub fn save_dataset_meta_by_dir(dataset_dir: String, meta: DatasetMeta) -> Result<(), String> {
+    save_dataset_meta(&dataset_dir, &meta).map_err(|e| format!("保存数据集元数据失败: {e}"))
+}
+
 fn proxy_kind_value(kind: &ProxyKind) -> &'static str {
     match kind {
         ProxyKind::Http => "Http",

src-tauri/src/dataset_meta.rs

@@ -0,0 +1,63 @@
+use serde::{Deserialize, Serialize};
+use std::{fs, path::PathBuf};
+
+const DATASET_META_FILE: &str = "meta.toml";
+
+#[derive(Clone, Deserialize, Serialize)]
+#[serde(rename_all = "camelCase")]
+pub struct DatasetMeta {
+    pub name: String,
+    pub target_model: String,
+    pub lora_type: String,
+    pub unified_image_size: bool,
+    pub unified_image_ratio: bool,
+    pub image_size: [u32; 2],
+    pub trigger_words: Vec<String>,
+}
+
+impl DatasetMeta {
+    pub fn validate(&self) -> anyhow::Result<()> {
+        if self.name.trim().is_empty() {
+            anyhow::bail!("数据集名称不能为空")
+        }
+
+        if self.target_model.trim().is_empty() {
+            anyhow::bail!("目标模型不能为空")
+        }
+
+        if self.image_size[0] == 0 || self.image_size[1] == 0 {
+            anyhow::bail!("imageSize 必须为正整数")
+        }
+
+        Ok(())
+    }
+}
+
+fn dataset_meta_path(dataset_dir: &str) -> PathBuf {
+    PathBuf::from(dataset_dir).join(DATASET_META_FILE)
+}
+
+pub fn save_dataset_meta(dataset_dir: &str, meta: &DatasetMeta) -> anyhow::Result<()> {
+    meta.validate()?;
+
+    let meta_path = dataset_meta_path(dataset_dir);
+    if let Some(parent_dir) = meta_path.parent() {
+        fs::create_dir_all(parent_dir)?;
+    }
+
+    let content = toml::to_string_pretty(meta)?;
+    fs::write(meta_path, content)?;
+    Ok(())
+}
+
+pub fn load_dataset_meta(dataset_dir: &str) -> anyhow::Result<DatasetMeta> {
+    let meta_path = dataset_meta_path(dataset_dir);
+    if !meta_path.exists() {
+        anyhow::bail!("缺少 meta.toml")
+    }
+
+    let content = fs::read_to_string(meta_path)?;
+    let meta: DatasetMeta = toml::from_str(&content)?;
+    meta.validate()?;
+    Ok(meta)
+}

src-tauri/src/lib.rs

@@ -1,5 +1,6 @@
 mod commands;
 mod config;
+mod dataset_meta;
 
 use tauri::Manager;
 
@@ -19,7 +20,9 @@ pub fn run() {
             commands::set_window_title,
             commands::load_app_config,
             commands::save_app_config,
-            commands::list_proxy_kind_options
+            commands::list_proxy_kind_options,
+            commands::load_dataset_meta_by_dir,
+            commands::save_dataset_meta_by_dir
         ])
         .run(tauri::generate_context!())
         .expect("error while running tauri application");

src/lib/stores/dataset.ts

@@ -1,6 +1,5 @@
 import type { DatasetMeta, ImageMeta } from "$lib/types/meta";
-import { join } from "@tauri-apps/api/path";
-import { writeTextFile } from "@tauri-apps/plugin-fs";
+import { saveDatasetMetaByDir } from "$lib/utils/dataset-meta";
 import { get, writable } from "svelte/store";
 
 export const openedDatasetDir = writable<string | null>(null);
@@ -25,8 +24,7 @@ export async function updateActiveDatasetMeta(updater: DatasetMetaUpdater): Prom
 	const nextMeta =
 		typeof updater === "function" ? updater(currentMeta) : { ...currentMeta, ...updater };
 
-	const metaPath = await join(datasetDir, "meta.json");
-	await writeTextFile(metaPath, JSON.stringify(nextMeta, null, 2));
+	await saveDatasetMetaByDir(datasetDir, nextMeta);
 	activeDatasetMeta.set(nextMeta);
 
 	return nextMeta;

src/lib/utils/dataset-meta.ts

@@ -0,0 +1,10 @@
+import type { DatasetMeta } from '$lib/types/meta';
+import { invoke } from '@tauri-apps/api/core';
+
+export async function loadDatasetMetaByDir(datasetDir: string) {
+  return invoke<DatasetMeta>('load_dataset_meta_by_dir', { datasetDir });
+}
+
+export async function saveDatasetMetaByDir(datasetDir: string, meta: DatasetMeta) {
+  await invoke('save_dataset_meta_by_dir', { datasetDir, meta });
+}

src/routes/boot/+page.svelte

@@ -4,15 +4,56 @@ import NewFolder from '$lib/components/icons/NewFolder.svelte';
 import OpenFolder from '$lib/components/icons/OpenFolder.svelte';
 import { openedDatasetDir } from '$lib/stores/dataset';
 import { currentActivate } from '$lib/stores/navigate';
-import { isDatasetMeta } from '$lib/types/meta';
-import { join } from '@tauri-apps/api/path';
+import { loadDatasetMetaByDir } from '$lib/utils/dataset-meta';
 import { message, open } from '@tauri-apps/plugin-dialog';
-import { readDir, readTextFile } from '@tauri-apps/plugin-fs';
 
 afterNavigate(() => {
   currentActivate.set('start');
 });
 
+function normalizeErrorMessage(error: unknown): string {
+  if (typeof error === 'string') {
+    return error;
+  }
+
+  if (error instanceof Error) {
+    return error.message;
+  }
+
+  return String(error);
+}
+
+function resolveDatasetLoadPrompt(error: unknown): { title: string; text: string } {
+  const message = normalizeErrorMessage(error);
+  const detail = message.replace('读取数据集元数据失败:', '').trim();
+
+  if (detail.includes('缺少 meta.toml')) {
+    return {
+      title: 'Missing meta.toml',
+      text: 'The selected folder does not contain meta.toml. Please choose a valid dataset folder.',
+    };
+  }
+
+  if (detail.includes('TOML parse error')) {
+    return {
+      title: 'Invalid meta.toml',
+      text: 'meta.toml has invalid TOML syntax. Please fix the file and try again.',
+    };
+  }
+
+  if (detail.includes('不能为空') || detail.includes('imageSize 必须为正整数')) {
+    return {
+      title: 'Invalid Dataset Metadata',
+      text: `meta.toml content is invalid: ${detail}`,
+    };
+  }
+
+  return {
+    title: 'Invalid Dataset Folder',
+    text: `Failed to read dataset metadata: ${detail || 'Unknown error'}`,
+  };
+}
+
 async function loadDataset() {
   try {
     const selectResult = await open({
@@ -34,25 +75,13 @@ async function loadDataset() {
       return;
     }
 
-    const entries = await readDir(selectedPath);
-    const hasMetaFile = entries.some((entry) => entry.name === 'meta.json');
-
-    if (!hasMetaFile) {
-      await message('The selected folder is not a valid dataset folder.', {
+    try {
+      await loadDatasetMetaByDir(selectedPath);
+    } catch (error) {
+      const prompt = resolveDatasetLoadPrompt(error);
+      await message(prompt.text, {
         kind: 'warning',
-        title: 'Invalid Dataset Folder',
-      });
-      return;
-    }
-
-    const metaPath = await join(selectedPath, 'meta.json');
-    const metaText = await readTextFile(metaPath);
-    const parsedMeta: unknown = JSON.parse(metaText);
-
-    if (!isDatasetMeta(parsedMeta)) {
-      await message('Dataset meta information is invalid.', {
-        kind: 'warning',
-        title: 'Invalid meta.json',
+        title: prompt.title,
       });
       return;
     }

src/routes/dataset/+page.ts

@@ -1,6 +1,7 @@
 import { goto } from '$app/navigation';
 import { activeDatasetImageMetas, activeDatasetMeta, openedDatasetDir } from '$lib/stores/dataset';
-import { isDatasetMeta, type ImageMeta } from '$lib/types/meta';
+import type { ImageMeta } from '$lib/types/meta';
+import { loadDatasetMetaByDir } from '$lib/utils/dataset-meta';
 import { join } from '@tauri-apps/api/path';
 import { readDir, readTextFile } from '@tauri-apps/plugin-fs';
 import { isNil } from 'es-toolkit';
@@ -16,18 +17,8 @@ export const load = (async () => {
   }
 
   try {
-    const metaPath = await join(activeDataset, 'meta.json');
-    const metaText = await readTextFile(metaPath);
-    const parsedMeta: unknown = JSON.parse(metaText);
-
-    if (!isDatasetMeta(parsedMeta)) {
-      activeDatasetMeta.set(null);
-      activeDatasetImageMetas.set([]);
-      await goto('/boot');
-      return {};
-    }
-
-    activeDatasetMeta.set(parsedMeta);
+    const meta = await loadDatasetMetaByDir(activeDataset);
+    activeDatasetMeta.set(meta);
 
     const entries = await readDir(activeDataset);
     const hasImagesMeta = entries.some((entry) => entry.name === 'images.json');