Update app.py

Fix gated repo issue with Flux

app.py

@@ -1,24 +1,42 @@
+import os
+import random
 import gradio as gr
 import torch
 from diffusers.utils import load_image
 from diffusers.pipelines.flux.pipeline_flux_controlnet import FluxControlNetPipeline
 from diffusers.models.controlnet_flux import FluxControlNetModel
-import random
 import numpy as np
+from huggingface_hub import login, snapshot_download
 
-import os
-from huggingface_hub import login
-
-login(os.getenv("hfapikey"))
-
-# Initialize models
+# Configuration
 base_model = 'black-forest-labs/FLUX.1-dev'
 controlnet_model = 'promeai/FLUX.1-controlnet-lineart-promeai'
+css = """
+#col-container {
+    margin: 0 auto;
+    max-width: 640px;
+}
+"""
+
+# Setup
+auth_token = os.getenv("HF_AUTH_TOKEN")
+if not auth_token:
+    raise ValueError("Hugging Face auth token not found. Please set HF_AUTH_TOKEN in the environment.")
+
+login(auth_token)
+
+model_dir = snapshot_download(
+    repo_id=base_model,
+    revision="main",
+    use_auth_token=auth_token
+)
+
 device = "cuda" if torch.cuda.is_available() else "cpu"
 torch_dtype = torch.bfloat16 if torch.cuda.is_available() else torch.float32
+print(f"Using device: {device} (torch_dtype={torch_dtype})")
 
 controlnet = FluxControlNetModel.from_pretrained(controlnet_model, torch_dtype=torch_dtype)
-pipe = FluxControlNetPipeline.from_pretrained(base_model, controlnet=controlnet, torch_dtype=torch_dtype)
+pipe = FluxControlNetPipeline.from_pretrained(model_dir, controlnet=controlnet, torch_dtype=torch_dtype)
 pipe = pipe.to(device)
 
 MAX_SEED = np.iinfo(np.int32).max
@@ -50,31 +68,23 @@ def infer(
 
     return result, seed
 
-css = """
-#col-container {
-    margin: 0 auto;
-    max-width: 640px;
-}
-"""
-
 with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
-        gr.Markdown("## Zero-shot Partial Style Transfer for Line Art Images, Powered by FLUX.1")
-
-        with gr.Row():
-            prompt = gr.Textbox(
-                label="Prompt",
-                placeholder="Enter your prompt",
-                max_lines=1,
-            )
-            run_button = gr.Button("Generate", variant="primary")
-
-        with gr.Accordion("Advanced Settings", open=True):
-            control_image = gr.Image(
+        gr.Markdown("Flux.1[dev] LineArt")
+        gr.Markdown("### Zero-shot Partial Style Transfer for Line Art Images, Powered by FLUX.1")
+        control_image = gr.Image(
                 sources=['upload', 'webcam', 'clipboard'],
                 type="filepath",
-                label="Control Image (Line Art)"
-            )
+                label="Control Image (LineArt)"
+        )
+        prompt = gr.Textbox(
+            label="Prompt",
+            placeholder="Enter your prompt",
+            max_lines=1,
+        )
+        run_button = gr.Button("Generate", variant="primary")
+        result = gr.Image(label="Result", show_label=False)
+        with gr.Accordion("Advanced Settings", open=False):
             controlnet_conditioning_scale = gr.Slider(
                 label="ControlNet Conditioning Scale",
                 minimum=0.0,
@@ -105,9 +115,6 @@ with gr.Blocks(css=css) as demo:
             )
             randomize_seed = gr.Checkbox(label="Randomize Seed", value=True)
 
-        
-        result = gr.Image(label="Result", show_label=False)
-
         gr.Examples(
             examples=[
                 "Shiba Inu wearing dinosaur costume riding skateboard",