Create app.py

app.py

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+import gradio as gr
+import requests
+import random
+from io import BytesIO
+from PIL import Image
+import os
+import time
+
+# Ambil base URL dari HF Secret (sembunyikan dari code)
+BASE_URL = os.environ.get('POLLINATIONS_URL')  # Fallback jika secret tidak ada (untuk testing lokal)
+
+def generate_image(prompt, model):
+    if not prompt:
+        raise gr.Error("Please enter a prompt.")
+
+    # Randomize seed
+    seed = random.randint(1, 999999)
+
+    # Construct full URL (direct to Pollinations)
+    url = f"{BASE_URL}{prompt}?width=2048&height=2048&seed={seed}&nologo=true&model={model}"
+
+    max_retries = 2  # Retry jika error (misal limit)
+    for attempt in range(max_retries):
+        try:
+            response = requests.get(url, stream=True)
+            response.raise_for_status()  # Raise error jika bukan 200
+
+            # Convert to PIL Image
+            img = Image.open(BytesIO(response.content))
+            return img
+
+        except requests.exceptions.HTTPError as e:
+            if response.status_code == 500 and 'Access to kontext model' in response.text:
+                if attempt < max_retries - 1:
+                    time.sleep(1)  # Delay sebelum retry
+                    continue
+                raise gr.Error("Access denied for kontext model (limit reached). Try turbo/flux or authenticate at pollinations.ai.")
+            else:
+                raise gr.Error(f"Error: {response.status_code} - {response.text}")
+        except Exception as e:
+            raise gr.Error(f"Unexpected error: {str(e)}")
+
+# Gradio Interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Fake flux pro Image Generator")
+    gr.Markdown("The Hugging Face Space https://huggingface.co/spaces/NihalGazi/FLUX-Pro-Unlimited by NihalGazi seems to be a fake version of FLUX Pro. It appears to be using the Pollinations API, because when I tried to replicate it using the same API, the image results were very similar.")
+
+    prompt_input = gr.Textbox(label="Prompt", placeholder="e.g., emma watson")
+    model_input = gr.Dropdown(choices=["kontext", "turbo", "flux"], label="Model", value="turbo")  # Default turbo (lebih reliable)
+
+    generate_btn = gr.Button("Generate")
+    output_image = gr.Image(label="Generated Image")
+
+    generate_btn.click(generate_image, inputs=[prompt_input, model_input], outputs=output_image)
+
+demo.launch()