feat(frontend): 优化 TensorBoard 端口占用问题

- 新增端口检测逻辑，动态分配可用端口
- 修改 TensorBoard 启动过程，使用动态分配的端口
- 添加 socket 模块，用于端口检测

frontend/train_page.py

@@ -8,7 +8,7 @@ from transformers import TrainerCallback
 
 sys.path.append(str(Path(__file__).resolve().parent.parent))
 from global_var import get_model, get_tokenizer, get_datasets, get_workdir
-from tools import train_model
+from tools import train_model, find_available_port
 
 def train_page():
     with gr.Blocks() as demo:
@@ -56,11 +56,13 @@ def train_page():
             next_dir_number = max([int(d) for d in existing_dirs], default=0) + 1
             new_training_dir = os.path.join(training_dir, str(next_dir_number))
 
-            # 启动 TensorBoard 子进程
+            tensorboard_port = find_available_port(6006)  # 从默认端口 6006 开始检测
+            print(f"TensorBoard 将使用端口: {tensorboard_port}")
+
             tensorboard_logdir = os.path.join(new_training_dir, "logs")
             os.makedirs(tensorboard_logdir, exist_ok=True)  # 确保日志目录存在
             tensorboard_process = subprocess.Popen(
-                ["tensorboard", "--logdir", tensorboard_logdir, "--port", "6006"],
+                ["tensorboard", "--logdir", tensorboard_logdir, "--port", str(tensorboard_port)],
                 stdout=subprocess.PIPE,
                 stderr=subprocess.PIPE
             )

tools/__init__.py

@@ -1,4 +1,5 @@
 from .parse_markdown import parse_markdown
 from .scan_doc_dir import *
 from .json_example import generate_example_json
-from .model import *
+from .model import *
+from .socket import *

tools/socket.py

@@ -0,0 +1,10 @@
+import socket
+
+# 启动 TensorBoard 子进程前添加端口检测逻辑
+def find_available_port(start_port):
+    port = start_port
+    while True:
+        with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
+            if s.connect_ex(('localhost', port)) != 0:  # 端口未被占用
+                return port
+            port += 1  # 如果端口被占用，尝试下一个端口