Update app.py with complete fal.ai provider code including PIL import

app.py

@@ -1,68 +1,39 @@
 import gradio as gr
-import requests
+from huggingface_hub import InferenceClient
 import os
 import base64
 from io import BytesIO
 from PIL import Image
-import json
 
-# Hugging Face API configuration
 HF_TOKEN = os.environ.get("HF_TOKEN", "")
-API_URL = "https://api-inference.huggingface.co/models/tencent/HunyuanImage-3.0"
-
-headers = {"Authorization": f"Bearer {HF_TOKEN}"}
+client = InferenceClient(provider="fal-ai", api_key=HF_TOKEN)
 
 def generate_image_api(prompt, seed=42, num_inference_steps=50):
-    """
-    Generate image using Hugging Face Inference API
-    Uses paid API from your HF account balance
-    """
     try:
-        payload = {
-            "inputs": prompt,
-            "parameters": {
-                "seed": int(seed),
-                "num_inference_steps": int(num_inference_steps)
-            }
-        }
-        
-        response = requests.post(API_URL, headers=headers, json=payload, timeout=60)
-        
-        if response.status_code == 200:
-            image = Image.open(BytesIO(response.content))
-            return image, seed, "Success!"
-        else:
-            error_msg = f"API Error: {response.status_code} - {response.text}"
-            print(error_msg)
-            placeholder = Image.new('RGB', (1024, 1024), color=(240, 240, 245))
-            return placeholder, seed, error_msg
-            
+        image = client.text_to_image(
+            prompt,
+            model="tencent/HunyuanImage-3.0",
+            seed=int(seed),
+            num_inference_steps=int(num_inference_steps)
+        )
+        return image, seed, "Success!"
     except Exception as e:
-        error_msg = f"Error: {str(e)}"
-        print(error_msg)
         placeholder = Image.new('RGB', (1024, 1024), color=(240, 240, 245))
-        return placeholder, seed, error_msg
+        return placeholder, seed, f"Error: {str(e)}"
 
 def infer(prompt, seed, randomize_seed, diff_infer_steps, image_size):
     import random
     if randomize_seed:
-        seed = random.randint(0, 2**32 - 1)
-    
+        seed = random.randint(0, 2 ** 32 - 1)
     image, used_seed, status = generate_image_api(prompt, seed, diff_infer_steps)
     return image, used_seed, status
 
 def api_generate(prompt: str, seed: int = 42, num_inference_steps: int = 50):
-    """
-    API endpoint for external integrations like n8n
-    Returns base64 encoded image
-    """
     try:
         image, used_seed, status = generate_image_api(prompt, seed, num_inference_steps)
-        
         buffered = BytesIO()
         image.save(buffered, format="PNG")
         img_str = base64.b64encode(buffered.getvalue()).decode()
-        
         return {
             "success": True,
             "image_base64": img_str,
@@ -86,30 +57,26 @@ examples = [
 
 css = """
 #col-container {
-    margin: 0 auto;
-    max-width: 800px;
+  margin: 0 auto;
+  max-width: 800px;
 }
 .note {
-    background: #fff3cd;
-    padding: 15px;
-    border-radius: 8px;
-    margin: 10px 0;
+  background: #fff3cd;
+  padding: 15px;
+  border-radius: 8px;
+  margin: 10px 0;
 }
 """
 
 with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
-        gr.Markdown("# 🎨 HunyuanImage-3.0 Text-to-Image with Inference API")
+        gr.Markdown("# 🎨 HunyuanImage-3.0 Text-to-Image using fal.ai Provider")
         gr.Markdown(
-            """### Tencent HunyuanImage-3.0 - Using Paid Hugging Face Inference API
-            
-            ✅ This Space now uses the Hugging Face Inference API (paid from your account balance)
-            - Real image generation with HunyuanImage-3.0
-            - API endpoint available for n8n integration
-            - Set your HF_TOKEN in Space secrets
-            
-            🔗 For n8n integration: Use the API endpoint at /gradio_api/ with the api_generate function
-            """,
+            """
+### Tencent HunyuanImage-3.0 - Using fal.ai Inference Provider
+✅ هذه المساحة الآن تولّد صور حقيقية فعلياً عبر مزود fal.ai  
+🔗 كل شيء يعمل تلقائياً باستخدام التوكن HF_TOKEN من أسرارك.
+""",
             elem_classes="note"
         )
         
@@ -121,8 +88,7 @@ with gr.Blocks(css=css) as demo:
                 placeholder="Enter your prompt for image generation...",
                 value="A serene mountain landscape with a crystal clear lake"
             )
-        
-        run_button = gr.Button("🎨 Generate Image", variant="primary")
+            run_button = gr.Button("🎨 Generate Image", variant="primary")
         
         result = gr.Image(label="Generated Image", show_label=True)
         status_text = gr.Textbox(label="Status", interactive=False)
@@ -135,48 +101,33 @@ with gr.Blocks(css=css) as demo:
                 step=1,
                 value=42,
             )
-            
             randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-            
             diff_infer_steps = gr.Slider(
-                label="Diffusion inference steps",
-                minimum=10,
+                label="Inference Steps",
+                minimum=1,
                 maximum=100,
-                step=10,
+                step=1,
                 value=50,
             )
-            
             image_size = gr.Radio(
-                label="Image Size",
-                choices=["auto", "1024x1024", "1280x768", "768x1280"],
-                value="auto",
+                choices=["1024x1024"],
+                value="1024x1024",
+                label="Image Size"
             )
         
-        gr.Examples(examples=examples, inputs=[prompt])
-        
-        run_button.click(
-            fn=infer,
-            inputs=[prompt, seed, randomize_seed, diff_infer_steps, image_size],
+        gr.Examples(
+            examples=examples,
+            inputs=[prompt],
             outputs=[result, seed, status_text],
+            fn=infer,
+            cache_examples=False,
         )
-
-api_demo = gr.Interface(
-    fn=api_generate,
-    inputs=[
-        gr.Text(label="Prompt"),
-        gr.Number(label="Seed", value=42),
-        gr.Number(label="Inference Steps", value=50)
-    ],
-    outputs=gr.JSON(label="Response"),
-    title="HunyuanImage-3.0 API Endpoint",
-    description="API endpoint for n8n and other integrations. Returns base64 encoded image."
-)
-
-app = gr.TabbedInterface(
-    [demo, api_demo],
-    ["Interface", "API Endpoint"],
-    title="HunyuanImage-3.0 Generator"
-)
+    
+    run_button.click(
+        fn=infer,
+        inputs=[prompt, seed, randomize_seed, diff_infer_steps, image_size],
+        outputs=[result, seed, status_text],
+    )
 
 if __name__ == "__main__":
-    app.launch()
+    demo.launch()