Update app.py

app.py

@@ -4,16 +4,20 @@ import json
 import base64
 from datetime import datetime
 
-# Standard imports
 import gradio as gr
 from fastapi import FastAPI, Request
 from fastapi.staticfiles import StaticFiles
 import uvicorn
 
-# Hugging Face Spaces imports
 import spaces
 from spaces.zero.client import _get_token
 
+# Set up environment variables (you can also set these in your Spaces config)
+os.environ["GRADIO_SSR_MODE"] = "True"
+os.environ["GRADIO_SERVER_PORT"] = "7860"
+os.environ["GRADIO_SERVER_NAME"] = "0.0.0.0"
+os.environ["GRADIO_NODE_SERVER_NAME"] = "0.0.0.0"
+
 # Create FastAPI app
 app = FastAPI()
 
@@ -27,40 +31,30 @@ 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)  # Specify GPU duration in seconds
+@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"""
-    # Get and decode the authentication token
     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}")  # For debugging
-
-    # Process the text using GPU function
-    processed_text = process_text(text)
-    
-    # Save to file
-#    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
- #   file_path = static_dir / f"output_{timestamp}.txt"
-  #  with open(file_path, "w") as f:
-   #     f.write(processed_text)
+    print(f"Token payload: {payload}")
     
-  #  return gr.File(value=file_path)
+    processed_text = process_text(text)
+    return processed_text  # Simplified for demonstration
 
 # 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.File(label="Download Processed File")
+    output = gr.Textbox(label="Output")
     
     submit_btn.click(
         fn=process_and_save,
@@ -68,24 +62,9 @@ with gr.Blocks() as demo:
         outputs=output
     )
 
-
-# Set up environment variables (you can also set these in your Spaces config)
-os.environ["GRADIO_SSR_MODE"] = "True"
-os.environ["GRADIO_SERVER_PORT"] = "7860"
-os.environ["GRADIO_SERVER_NAME"] = "0.0.0.0"
-os.environ["GRADIO_NODE_SERVER_NAME"] = "0.0.0.0"
-
-
-
-
-# Mount Gradio app to FastAPI with SSR mode for Spaces
-#app = gr.mount_gradio_app(app, demo, path="/", ssr_mode=True)
+# Mount Gradio app to FastAPI with SSR mode and node_port set to 7861
 app = gr.mount_gradio_app(app, demo, path="/", ssr_mode=True, node_port=7861)
 
-# Run server
+# Run the server on port 7860 (only one public port on Spaces)
 if __name__ == "__main__":
-    # Set SSR mode for Spaces
-    os.environ["GRADIO_SSR_MODE"] = "True"
-    #uvicorn.run(app)
-
     uvicorn.run(app, host="0.0.0.0", port=7860)