Upload 2 files

app.py

@@ -1,23 +1,18 @@
 import gradio as gr
 import requests
-import os  # ✅ 用于读取 secret
+import os
 
-# ✅ 从 Hugging Face Secret 中获取 token
 API_TOKEN = os.getenv("HF_API_TOKEN")
-gr.Textbox(API_TOKEN, label="API Token", interactive=False)
-# ✅ 你私有后端的空间地址（注意大小写）
-BACKEND_URL = "https://dsbb0707-SpatialParseback.hf.space/api/predict/"
+BACKEND_URL = "https://your-backend-url/api/predict/"  # 替换为你的后端地址
 
 def call_backend(input_text):
     try:
-        # ✅ 加入 Authorization 头
         headers = {
             "Authorization": f"Bearer {API_TOKEN}"
         }
-
         response = requests.post(
             BACKEND_URL,
-            headers=headers,  # ✅ 加入 header
+            headers=headers,
             json={"data": [input_text]},
             timeout=10
         )
@@ -28,20 +23,14 @@ def call_backend(input_text):
     except Exception as e:
         return f"⚠️ Connection Error: {str(e)}"
 
-# ✅ Gradio 界面构建
 with gr.Blocks() as demo:
-    gr.Markdown("## 前端交互界面")
+    gr.Markdown("## 地理信息识别系统")
     with gr.Row():
-        input_box = gr.Textbox(label="输入文本", placeholder="请输入...")
-        output_box = gr.Textbox(label="处理结果", interactive=False)
-    submit_btn = gr.Button("提交", variant="primary")
-    
-    submit_btn.click(
-        fn=call_backend,
-        inputs=input_box,
-        outputs=output_box
-    )
+        input_box = gr.Textbox(label="输入描述文本")
+        output_box = gr.Textbox(label="识别结果", interactive=False)
+    submit_btn = gr.Button("提交")
+
+    submit_btn.click(fn=call_backend, inputs=input_box, outputs=output_box)
 
-# ✅ 正确的 Gradio 启动方式
 if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0", server_port=7860)
+    demo.launch(server_name="0.0.0.0", server_port=7860)

requirements.txt

@@ -1,2 +1,2 @@
-streamlit
+gradio
 requests