Update app.py

app.py

@@ -5,14 +5,15 @@ import base64
 from datetime import datetime
 
 import gradio as gr
-from fastapi import FastAPI, Request
+from fastapi import FastAPI, Request, Response
 from fastapi.staticfiles import StaticFiles
 import uvicorn
+import httpx
 
 import spaces
 from spaces.zero.client import _get_token
 
-# Set up environment variables (you can also set these in your Spaces config)
+# Set environment variables for SSR
 os.environ["GRADIO_SSR_MODE"] = "True"
 os.environ["GRADIO_SERVER_PORT"] = "7860"
 os.environ["GRADIO_SERVER_NAME"] = "0.0.0.0"
@@ -24,47 +25,46 @@ app = FastAPI()
 # Create and configure static directory
 static_dir = Path("./static")
 static_dir.mkdir(parents=True, exist_ok=True)
-
-# Mount static directory to FastAPI
 app.mount("/static", StaticFiles(directory="static"), name="static")
-
-# Tell Gradio which paths are allowed to be served
 os.environ["GRADIO_ALLOWED_PATHS"] = str(static_dir.resolve())
 
 @spaces.GPU(duration=4*60)
 def process_text(text):
-    """Example GPU function - in reality, this might be model inference"""
     return text.upper()
 
 def process_and_save(request: gr.Request, text):
-    """Main processing function that handles tokens and calls GPU function"""
     token = _get_token(request)
     payload = token.split('.')[1]
     payload = f"{payload}{'=' * ((4 - len(payload) % 4) % 4)}"
     payload = json.loads(base64.urlsafe_b64decode(payload).decode())
     print(f"Token payload: {payload}")
-    
     processed_text = process_text(text)
-    return processed_text  # Simplified for demonstration
+    return processed_text
 
-# Mark main function as not requiring GPU
 process_and_save.zerogpu = True
 
-# Create Gradio interface
 with gr.Blocks() as demo:
     text_input = gr.Textbox(label="Enter some text")
     submit_btn = gr.Button("Process and Download")
     output = gr.Textbox(label="Output")
     
-    submit_btn.click(
-        fn=process_and_save,
-        inputs=[text_input],
-        outputs=output
-    )
+    submit_btn.click(fn=process_and_save, inputs=[text_input], outputs=output)
 
-# Mount Gradio app to FastAPI with SSR mode and node_port set to 7861
+# Mount the Gradio app with SSR mode, using node_port 7861
 app = gr.mount_gradio_app(app, demo, path="/", ssr_mode=True, node_port=7861)
 
-# Run the server on port 7860 (only one public port on Spaces)
+# Manual reverse proxy for SSR assets
+@app.get("/_app/{full_path:path}")
+async def proxy_to_node(full_path: str, request: Request):
+    node_server = "http://127.0.0.1:7861"
+    url = f"{node_server}/_app/{full_path}"
+    async with httpx.AsyncClient() as client:
+        node_response = await client.get(url)
+    return Response(
+        content=node_response.content,
+        status_code=node_response.status_code,
+        media_type=node_response.headers.get("content-type"),
+    )
+
 if __name__ == "__main__":
     uvicorn.run(app, host="0.0.0.0", port=7860)