logs

app.py

@@ -6,8 +6,10 @@ import gradio as gr
 import numpy as np
 import requests
 from dotenv import load_dotenv
+
 from huggingface_hub import InferenceClient
 
+
 load_dotenv()
 
 MAX_SEED = np.iinfo(np.int32).max
@@ -15,13 +17,12 @@ MAX_IMAGE_SIZE = 2048
 TOKEN = None
 FAL_KEY = None
 
+
 def download_locally(url: str, local_path: str = "downloaded_file.png") -> str:
     """Download an image or a video from a URL to a local path.
-
     Args:
         url (str): The URL of the image to download. Must be an http(s) URL.
         local_path (str, optional): The path (including filename) where the file should be saved. Defaults to "downloaded_file.png".
-
     Returns:
         str: The filesystem path of the saved file – suitable for returning to a **gr.File** output, or as an MCP tool response.
     """
@@ -41,7 +42,6 @@ def download_locally(url: str, local_path: str = "downloaded_file.png") -> str:
 def login_hf(oauth_token: gr.OAuthToken | None):
     """
     Login to Hugging Face and check initial key statuses.
-
     Args:
         oauth_token (gr.OAuthToken | None): The OAuth token from Hugging Face.
     """
@@ -52,6 +52,7 @@ def login_hf(oauth_token: gr.OAuthToken | None):
     else:
         print("No OAuth token provided, using environment variable HF_TOKEN.")
         TOKEN = os.environ.get("HF_TOKEN")
+        print("TOKEN: ", TOKEN)
 
 
 def login_fal(fal_key_from_ui: str | None):
@@ -68,6 +69,7 @@ def login_fal(fal_key_from_ui: str | None):
     else:
         FAL_KEY = os.environ.get("FAL_KEY")
         print("FAL_KEY is configured from environment variable.")
+        print("FAL_KEY: ", FAL_KEY)
 
 
 def generate_image(prompt: str, seed: int = 42, width: int = 1024, height: int = 1024, num_inference_steps: int = 25):
@@ -85,7 +87,6 @@ def generate_image(prompt: str, seed: int = 42, width: int = 1024, height: int =
         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(

requirements.txt

@@ -1,4 +1,5 @@
 huggingface-hub
 numpy
 python-dotenv
-fal-client
+fal-client
+gradio