Update app.py

app.py

@@ -8,7 +8,6 @@ from tqdm import tqdm
 from huggingface_hub import login, create_repo, HfApi
 import subprocess
 import math
-from dotenv import load_dotenv
 import gradio as gr
 import threading
 import queue
@@ -86,10 +85,10 @@ def check_system_resources(model_name):
     else:
         raise MemoryError(f"❌ 系统内存不足 (需要 {required_memory_gb:.1f}GB, 可用 {available_memory_gb:.1f}GB)")
 
-def setup_environment(model_name):
+def setup_environment(model_name, hf_token):
     """设置环境并返回设备信息"""
-    load_dotenv()
-    hf_token = os.getenv('HF_TOKEN')
+    if not hf_token:
+        hf_token = os.getenv('HF_TOKEN', None) # try to get from env
     if not hf_token:
         raise ValueError("请在环境变量中设置HF_TOKEN")
     login(hf_token)
@@ -98,10 +97,10 @@ def setup_environment(model_name):
     device, available_memory = check_system_resources(model_name)
     return device
 
-def create_hf_repo(repo_name, private=True):
+def create_hf_repo(repo_name, hf_token, private=True):
     """创建HuggingFace仓库"""
     try:
-        repo_url = create_repo(repo_name, private=private)
+        repo_url = create_repo(repo_name, private=private, token=hf_token)
         log(f"创建仓库成功: {repo_url}")
         return repo_url
     except Exception as e:
@@ -204,17 +203,17 @@ def quantize_and_push_model(model_path, repo_id, bits=8):
         log(f"量化或上传过程中出错: {str(e)}")
         raise
 
-def process_model(base_model, lora_model, repo_name, progress=gr.Progress()):
+def process_model(base_model, lora_model, repo_name, hf_token, progress=gr.Progress()):
     """处理模型的主函数，用于Gradio界面"""
     try:
         # 清空之前的日志
         current_logs.clear()
         
         # 设置环境和检查资源
-        device = setup_environment(base_model)
+        device = setup_environment(base_model, hf_token)
         
         # 创建HuggingFace仓库
-        repo_url = create_hf_repo(repo_name)
+        repo_url = create_hf_repo(repo_name, hf_token)
         
         # 设置输出目录
         output_dir = os.path.join(".", "output", repo_name)
@@ -256,7 +255,7 @@ def create_ui():
             with gr.Column():
                 base_model = gr.Textbox(
                     label="基础模型路径",
-                    placeholder="例如: Qwen/Qwen2.5-7B-Instruct",
+                    placeholder="例如: Qwen/Qwen2.5-14B-Instruct",
                     value="Qwen/Qwen2.5-7B-Instruct"
                 )
                 lora_model = gr.Textbox(
@@ -267,6 +266,10 @@ def create_ui():
                     label="HuggingFace仓库名称",
                     placeholder="输入要创建的仓库名称"
                 )
+                hf_token = gr.Textbox(
+                    label="HuggingFace Token",
+                    placeholder="输入你的HuggingFace Token"
+                )
                 convert_btn = gr.Button("开始转换", variant="primary")
             
             with gr.Column():
@@ -281,7 +284,7 @@ def create_ui():
         # 设置事件处理
         convert_btn.click(
             fn=process_model,
-            inputs=[base_model, lora_model, repo_name],
+            inputs=[base_model, lora_model, repo_name, hf_token],
             outputs=output
         )