Update app.py

app.py

@@ -64,19 +64,25 @@ external_log_dir = "./logs"
 LOGDIR = external_log_dir
 VOTEDIR = "./votes"
 
+import gradio, uvicorn, websockets, pathlib
+print("Gradio:", gradio.__version__)
+print("uvicorn:", uvicorn.__version__)
+print("websockets:", websockets.__version__)
 
-def install_gradio_4_35_0():
-    current_version = gr.__version__
-    if current_version != "4.35.0":
-        print(f"Current Gradio version: {current_version}")
-        print("Installing Gradio 4.35.0...")
-        subprocess.check_call([sys.executable, "-m", "pip", "install", "gradio==4.35.0", "--force-reinstall"])
-        print("Gradio 4.35.0 installed successfully.")
-    else:
-        print("Gradio 4.35.0 is already installed.")
+
+
+# def install_gradio_4_35_0():
+#     current_version = gr.__version__
+#     if current_version != "4.35.0":
+#         print(f"Current Gradio version: {current_version}")
+#         print("Installing Gradio 4.35.0...")
+#         subprocess.check_call([sys.executable, "-m", "pip", "install", "gradio==4.35.0", "--force-reinstall"])
+#         print("Gradio 4.35.0 installed successfully.")
+#     else:
+#         print("Gradio 4.35.0 is already installed.")
 
 # Call the function to install Gradio 4.35.0 if needed
-install_gradio_4_35_0()
+# install_gradio_4_35_0()
 
 import gradio as gr
 import gradio_client
@@ -487,7 +493,8 @@ with gr.Blocks(
                     label="Max output tokens",
                 )
         with gr.Row():
-            chatbot = gr.Chatbot([], elem_id="Pangea", bubble_full_width=False, height=750)
+            # chatbot = gr.Chatbot([], elem_id="Pangea", bubble_full_width=False, height=750)
+            chatbot = gr.Chatbot([], elem_id="Pangea", type="tuple", height=750)
 
         with gr.Row():
             upvote_btn = gr.Button(value="👍  Upvote", interactive=True)
@@ -734,4 +741,13 @@ if __name__ == "__main__":
     device = (torch.device("cuda") if torch.cuda.is_available() else torch.device("mps") if getattr(torch.backends, "mps", None) and torch.backends.mps.is_available() else torch.device("cpu"))
     model = model.to(device)
     chat_image_num = 0
-    demo.launch()
+    # demo.launch()
+    demo.queue()
+
+    # Spaces sets $PORT; Gradio also respects GRADIO_SERVER_PORT if you prefer.
+    port = int(os.environ.get("PORT", os.environ.get("GRADIO_SERVER_PORT", 7860)))
+    
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=port,
+    )