Update app.py

app.py

@@ -3,6 +3,13 @@ import numpy as np
 import random
 import torch
 from diffusers import DiffusionPipeline
+from huggingface_hub import login
+
+# Replace 'YOUR_HUGGINGFACE_API_TOKEN' with your actual token
+api_token = 'YOUR_HUGGINGFACE_API_TOKEN'
+
+# Log in to Hugging Face Hub
+login(token=api_token)
 
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024
@@ -16,14 +23,12 @@ def infer(
     height,
     guidance_scale,
     num_inference_steps,
-    user_info,
 ):
-    if not user_info or "username" not in user_info:
-        return "Please log in to generate images.", None
-
     # Load the pipeline only when this function is called
-    pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev")
-    pipe.load_lora_weights("EvanZhouDev/open-genmoji")
+    pipe = DiffusionPipeline.from_pretrained(
+        "black-forest-labs/FLUX.1-dev", use_auth_token=api_token
+    )
+    pipe.load_lora_weights("EvanZhouDev/open-genmoji", use_auth_token=api_token)
     device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
     pipe = pipe.to(device)
 
@@ -62,20 +67,6 @@ with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
         gr.Markdown(" # Text-to-Image Gradio Template")
 
-        # Login Button inside the Blocks context
-        login_button = gr.LoginButton()
-        login_button.activate()
-        user_info = gr.State()
-
-        def update_user_info(profile):
-            if profile is None:
-                return "No user information available"
-            return profile
-
-        login_button.click(
-            update_user_info, inputs=None, outputs=user_info
-        )
-
         with gr.Row():
             prompt = gr.Text(
                 label="Prompt",
@@ -147,7 +138,6 @@ with gr.Blocks(css=css) as demo:
                 height,
                 guidance_scale,
                 num_inference_steps,
-                user_info,
             ],
             outputs=[result, seed],
         )