Update app.py

app.py

@@ -1,20 +1,36 @@
 import json
-from fastapi import FastAPI, HTTPException
 import gradio as gr
+from fastapi import FastAPI, HTTPException
 from pydantic import BaseModel
 from fastapi.responses import HTMLResponse
 
-app = FastAPI()
+# Store the lists data (in-memory database)
+lists = {}
 
 # Define a model for the incoming request data
 class DataRequest(BaseModel):
     list_name: str
     items: list
 
-# Store the lists data
-lists = {}
+# For Hugging Face Spaces, we need to define the Gradio app first
+with gr.Blocks() as demo:
+    # Create a simple interface to show the data
+    gr.Markdown("# UniShare Data Viewer")
+    output_text = gr.Textbox(label="Stored Data")
+    
+    def show_data():
+        return json.dumps(lists, indent=4)
+    
+    refresh_btn = gr.Button("Refresh Data")
+    refresh_btn.click(fn=show_data, inputs=[], outputs=[output_text])
+    
+    # Initialize with current data
+    demo.load(fn=show_data, inputs=[], outputs=[output_text])
+
+# Create FastAPI app
+app = FastAPI()
 
-# FastAPI endpoint for POST request to store data
+# Endpoint for storing data
 @app.post("/store_data")
 async def store_data(data: DataRequest):
     list_name = data.list_name
@@ -26,7 +42,12 @@ async def store_data(data: DataRequest):
     lists[list_name].append(items)
     return {"message": f"Data stored successfully for {list_name}"}
 
-# FastAPI default root to serve custom HTML
+# Endpoint to get data
+@app.get("/api/data")
+async def get_data():
+    return lists
+
+# Root endpoint serving HTML interface
 @app.get("/", response_class=HTMLResponse)
 def read_root():
     return """
@@ -195,7 +216,7 @@ def read_root():
         }
 
         // Fetch data and populate the lists dynamically
-        fetch('/gradio/data')
+        fetch('/api/data')
           .then(response => response.json())
           .then(data => {
             if (Object.keys(data).length > 0) {
@@ -217,22 +238,5 @@ def read_root():
     </html>
     """
 
-# FastAPI endpoint to get data
-@app.get("/gradio/data")
-async def get_data():
-    return lists
-
-# Define Gradio interface
-def show_data():
-    return json.dumps(lists, indent=4)  # Return the data as formatted JSON
-
-# Create the Gradio interface
-gradio_app = gr.Interface(fn=show_data, inputs=[], outputs="text")
-
-# Mount the Gradio app to FastAPI
-app = gr.mount_gradio_app(app, gradio_app, path="/gradio")
-
-# Add this if you're running this script directly
-if __name__ == "__main__":
-    import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=8000)
+# This is crucial for Hugging Face Spaces
+app = gr.mount_gradio_app(app, demo)