Update app.py

app.py

@@ -1,6 +1,162 @@
 import gradio as gr
+from huggingface_hub import InferenceClient
+from PIL import Image
+import time
+import os
 
-gr.load(
-   "models/black-forest-labs/FLUX.1-schnell",
-   provider="hf-inference",
-).launch()
+# Get the Hugging Face token from the environment variable, or a secret if available.
+HF_TOKEN = os.environ.get("HF_TOKEN")
+
+# Check if HF_TOKEN is set; if not, raise a configuration error (handled later)
+if not HF_TOKEN:
+    HF_TOKEN_ERROR = "Hugging Face API token (HF_TOKEN) not found.  Please set it as an environment variable or Gradio secret."
+else:
+    HF_TOKEN_ERROR = None  # No error if the token is found
+
+
+client = InferenceClient(token=HF_TOKEN)  # Use token instead of provider and api_key
+
+def generate_image(prompt, progress=gr.Progress()):
+    """Generates an image using the InferenceClient and provides progress updates."""
+
+    if HF_TOKEN_ERROR:
+        raise gr.Error(HF_TOKEN_ERROR)
+
+    progress(0, desc="Sending request to Hugging Face...")
+    try:
+        # Use the client.text_to_image method.  Assume xylaria-iris is valid here.
+        image = client.text_to_image(prompt, model="black-forest-labs/FLUX.1-schnell")
+
+        if not isinstance(image, Image.Image): # Basic type checking.
+             raise Exception(f"Expected a PIL Image, but got: {type(image)}")
+
+        progress(0.8, desc="Processing image...")
+        time.sleep(0.5)  # Simulate some processing
+        progress(1.0, desc="Done!")
+        return image
+    except Exception as e:  # Catch all exceptions from the API call
+        # Check for rate limit errors (different with InferenceClient).  This is a best-effort check.
+        if "rate limit" in str(e).lower(): # Check message, case-insensitively.
+            error_message = f"Rate limit exceeded. Please try again later.  Error: {e}"
+        else:
+            error_message = f"An error occurred: {e}"  # Generic error message
+        raise gr.Error(error_message)
+
+
+
+# Gradio Interface (same CSS as before, for consistency)
+css = """
+.container {
+    max-width: 800px;
+    margin: auto;
+    padding: 20px;
+    border: 1px solid #ddd;
+    border-radius: 10px;
+    box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
+}
+.title {
+    text-align: center;
+    font-size: 2.5em;
+    margin-bottom: 0.5em;
+    color: #333;
+    font-family: 'Arial', sans-serif; /* More readable font */
+}
+.description {
+    text-align: center;
+    font-size: 1.1em;
+    margin-bottom: 1.5em;
+    color: #555;
+}
+.input-section, .output-section {
+    margin-bottom: 1.5em;
+}
+.output-section img {
+    display: block; /* Ensure image takes full width of container */
+    margin: auto;  /* Center the image horizontally */
+    max-width: 100%; /* Prevent image overflow */
+    height: auto;  /* Maintain aspect ratio */
+    border-radius: 8px;  /* Rounded corners for the image */
+    box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);  /* Subtle shadow */
+}
+
+/* Animation for the image appearance - subtle fade-in */
+@keyframes fadeIn {
+    from { opacity: 0; transform: translateY(20px); }
+    to   { opacity: 1; transform: translateY(0); }
+}
+.output-section.animate img {
+    animation: fadeIn 0.8s ease-out;
+}
+
+/* Improve button style */
+.submit-button {
+    display: block;
+    margin: auto;
+    padding: 10px 20px;
+    font-size: 1.1em;
+    color: white;
+    background-color: #4CAF50;
+    border: none;
+    border-radius: 5px;
+    cursor: pointer;
+    transition: background-color 0.3s ease;
+}
+.submit-button:hover {
+    background-color: #367c39;
+}
+
+/* Style the error messages */
+.error-message {
+    color: red;
+    text-align: center;
+    margin-top: 1em;
+    font-weight: bold;
+}
+label{
+    font-weight: bold; /* Make labels bold */
+    display: block;      /* Each label on its own line */
+    margin-bottom: 0.5em; /* Space between label and input */
+}
+"""
+
+
+with gr.Blocks(css=css) as demo:
+    gr.Markdown(
+        """
+        # Xylaria Iris Image Generator
+        Enter a text prompt and generate an image using the Xylaria Iris model!
+        """,
+        elem_classes="title"
+    )
+
+
+    with gr.Row():
+        with gr.Column():
+            with gr.Group(elem_classes="input-section"):
+                prompt_input = gr.Textbox(label="Enter your prompt", placeholder="e.g., A beautiful landscape with a magical tree", lines=3)
+                generate_button = gr.Button("Generate Image", elem_classes="submit-button")
+        with gr.Column():
+            with gr.Group(elem_classes="output-section") as output_group:
+                image_output = gr.Image(label="Generated Image") # Removed width and height
+
+
+    def on_generate_click(prompt):
+        output_group.elem_classes = ["output-section", "animate"]
+        image = generate_image(prompt)
+        output_group.elem_classes = ["output-section"]
+        return image
+
+
+    generate_button.click(on_generate_click, inputs=prompt_input, outputs=image_output)
+    prompt_input.submit(on_generate_click, inputs=prompt_input, outputs=image_output)
+
+    gr.Examples(
+        [["A futuristic cityscape at night"],
+         ["A mystical forest with glowing mushrooms"],
+         ["An astronaut exploring a new planet"],
+         ["A cat wearing a top hat"]],
+        inputs=prompt_input
+    )
+
+if __name__ == "__main__":
+    demo.queue().launch()