fix oauth

app.py

@@ -2,8 +2,11 @@ import os
 
 import gradio as gr
 import numpy as np
+from dotenv import load_dotenv
 from huggingface_hub import InferenceClient, login
 
+load_dotenv()
+
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 2048
 TOKEN = None
@@ -11,11 +14,29 @@ TOKEN = None
 def get_token(oauth_token: gr.OAuthToken | None):
     global TOKEN
     if oauth_token and oauth_token.token:
+        print("Received OAuth token, logging in...")
         TOKEN = oauth_token.token
     else:
-        TOKEN = os.getenv("HF_TOKEN")
+        print("No OAuth token provided, using environment variable HF_TOKEN.")
+        TOKEN = os.environ.get("HF_TOKEN")
 
-def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, num_inference_steps=4, progress=gr.Progress(track_tqdm=True)):
+def generate(prompt: str, seed: int =42, width: int =1024, height: int =1024, num_inference_steps: int = 25):
+    """
+    Generate an image from a prompt.
+    Args:
+        prompt (str):
+                The prompt to generate an image from.
+        seed (int, default=42):
+            Seed for the random number generator.
+        height (int,  default=1024):
+            The height in pixels of the output image
+        width (int, default=1024):
+            The width in pixels of the output image
+        num_inference_steps (int, default=25):
+            The number of denoising steps. More denoising steps usually lead to a higher quality image at the
+            expense of slower inference.
+        
+    """
     client = InferenceClient(provider="fal-ai", token=TOKEN)
     image = client.text_to_image(
         prompt=prompt,
@@ -41,11 +62,12 @@ css="""
 """
 
 with gr.Blocks(css=css) as demo:
+    demo.load(get_token, inputs=None, outputs=None)
     with gr.Sidebar():
         gr.Markdown("# Inference Provider")
         gr.Markdown("This Space showcases the black-forest-labs/FLUX.1-dev model, served by the nebius API. Sign in with your Hugging Face account to use this API.")
         button = gr.LoginButton("Sign in")
-        button.click(fn=get_token, inputs=button, outputs=[])
+        button.click(fn=get_token, inputs=[], outputs=[])
         
     with gr.Column(elem_id="col-container"):
         gr.Markdown(f"""# FLUX.1 [schnell] with fal-ai through HF Inference Providers ⚡
@@ -72,11 +94,9 @@ learn more about HF Inference Providers [here](https://huggingface.co/docs/infer
                 minimum=0,
                 maximum=MAX_SEED,
                 step=1,
-                value=0,
+                value=42,
             )
-            
-            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-            
+                        
             with gr.Row():
                 
                 width = gr.Slider(
@@ -103,12 +123,12 @@ learn more about HF Inference Providers [here](https://huggingface.co/docs/infer
                     minimum=1,
                     maximum=50,
                     step=1,
-                    value=4,
+                    value=25,
                 )
         
         gr.Examples(
             examples = examples,
-            fn = infer,
+            fn = generate,
             inputs = [prompt],
             outputs = [result, seed],
             cache_examples="lazy"
@@ -116,8 +136,8 @@ learn more about HF Inference Providers [here](https://huggingface.co/docs/infer
 
     gr.on(
         triggers=[run_button.click, prompt.submit],
-        fn = infer,
-        inputs = [prompt, seed, randomize_seed, width, height, num_inference_steps],
+        fn = generate,
+        inputs = [prompt, seed, width, height, num_inference_steps],
         outputs = [result, seed]
     )
 

requirements.txt

@@ -1,2 +1,3 @@
 huggingface-hub
-numpy
+numpy
+python-dotenv