diff --git a/mikazuki/app/api.py b/mikazuki/app/api.py
index 731ef81..0049469 100644
--- a/mikazuki/app/api.py
+++ b/mikazuki/app/api.py
@@ -3,8 +3,12 @@ import hashlib
 import json
 import os
 import re
+import random
+
+from glob import glob
 from datetime import datetime
 from pathlib import Path
+from typing import Tuple, Optional
 
 import toml
 from fastapi import APIRouter, BackgroundTasks, Request
@@ -80,6 +84,38 @@ async def load_presets():
             avaliable_presets.append(toml.loads(content))
 
 
+def get_sample_prompts(config: dict) -> Tuple[Optional[str], str]:
+    train_data_dir = config["train_data_dir"]
+    sub_dir = [dir for dir in glob(os.path.join(train_data_dir, '*')) if os.path.isdir(dir)]
+
+    positive_prompts = config.pop('positive_prompts', None)
+    negative_prompts = config.pop('negative_prompts', '')
+    sample_width = config.pop('sample_width', 512)  # 默认宽度 512
+    sample_height = config.pop('sample_height', 512)  # 默认高度 512
+    sample_cfg = config.pop('sample_cfg', 7)  # 默认 CFG 值 7.5
+    sample_seed = config.pop('sample_seed', 2333)  # 默认随机种子 42
+    sample_steps = config.pop('sample_steps', 24)  # 默认步数 50
+    randomly_choice_prompt = config.pop('randomly_choice_prompt', False)
+
+    if randomly_choice_prompt:
+        if len(sub_dir) != 1:
+            raise ValueError('训练数据集下有多个子文件夹，无法启用自动选取 Prompt 功能')
+            # return None, APIResponseFail(message='训练数据集下有多个子文件夹，无法启用自动选取 Prompt 功能')
+        
+        txt_files = glob(os.path.join(sub_dir[0], '*.txt'))
+        if not txt_files:
+            raise ValueError('训练数据集路径没有 txt 文件')
+            # return None, APIResponseFail(message='训练数据集路径没有 txt 文件')
+        try:
+            sample_prompt_file = random.choice(txt_files)
+            with open(sample_prompt_file, 'r', encoding='utf-8') as f:
+                positive_prompts = f.read()
+        except IOError:
+            # positive_prompts = config['positive_prompts']
+            pass
+
+    return positive_prompts, f'{positive_prompts} --n {negative_prompts}  --w {sample_width} --h {sample_height} --l {sample_cfg}  --s {sample_steps}  --d {sample_seed}'
+
 @router.post("/run")
 async def create_toml_file(request: Request):
     timestamp = datetime.now().strftime("%Y%m%d-%H%M%S")
@@ -103,13 +139,19 @@ async def create_toml_file(request: Request):
     if not validated:
         return APIResponseFail(message=message)
 
-    sample_prompts = config.get("sample_prompts", None)
-    if sample_prompts is not None and not os.path.exists(sample_prompts) and train_utils.is_promopt_like(sample_prompts):
-        sample_prompts_file = os.path.join(os.getcwd(), f"config", "autosave", f"{timestamp}-promopt.txt")
-        with open(sample_prompts_file, "w", encoding="utf-8") as f:
-            f.write(sample_prompts)
-        config["sample_prompts"] = sample_prompts_file
-        log.info(f"Wrote promopts to file {sample_prompts_file}")
+    try:
+        positive_prompt, sample_prompts_arg = get_sample_prompts(config=config)
+        
+        if positive_prompt is not None and train_utils.is_promopt_like(sample_prompts_arg):
+            sample_prompts_file = os.path.join(os.getcwd(), f"config", "autosave", f"{timestamp}-promopt.txt")
+            with open(sample_prompts_file, "w", encoding="utf-8") as f:
+                f.write(sample_prompts_arg)
+
+            config["sample_prompts"] = sample_prompts_file
+            log.info(f"Wrote promopts to file {sample_prompts_file}")
+    except ValueError as e:
+        return APIResponseFail(message=str(e))
+
 
     with open(toml_file, "w", encoding="utf-8") as f:
         f.write(toml.dumps(config))
diff --git a/mikazuki/schema/shared.ts b/mikazuki/schema/shared.ts
index c30bb47..8fa93a8 100644
--- a/mikazuki/schema/shared.ts
+++ b/mikazuki/schema/shared.ts
@@ -168,7 +168,14 @@
             Schema.union([
                 Schema.object({
                     enable_preview: Schema.const(true).required(),
-                    sample_prompts: Schema.string().role('textarea').default(SAMPLE_PROMPTS_DEFAULT).description(SAMPLE_PROMPTS_DESCRIPTION),
+                    randomly_choice_prompt: Schema.boolean().default(false).description('随机选择预览图 Prompt'),
+                    positive_prompts: Schema.string().role('textarea').default('masterpiece, best quality, 1girl, solo').description("Prompt"),
+                    negative_prompts: Schema.string().role('textarea').default('lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts,signature, watermark, username, blurry').description("Negative Prompt"),
+                    sample_width: Schema.number().default(512).description('预览图宽'),
+                    sample_height: Schema.number().default(512).description('预览图高'),
+                    sample_cfg: Schema.number().min(1).max(30).default(7).description('CFG Scale'),
+                    sample_seed: Schema.number().default(2333).description('种子'),
+                    sample_steps: Schema.number().min(1).max(300).default(24).description('迭代步数'),
                     sample_sampler: Schema.union(["ddim", "pndm", "lms", "euler", "euler_a", "heun", "dpm_2", "dpm_2_a", "dpmsolver", "dpmsolver++", "dpmsingle", "k_lms", "k_euler", "k_euler_a", "k_dpm_2", "k_dpm_2_a"]).default("euler_a").description("生成预览图所用采样器"),
                     sample_every_n_epochs: Schema.number().default(2).description("每 N 个 epoch 生成一次预览图"),
                 }),