Create app.py

app.py

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+import gradio as gr
+import requests
+import os
+
+# Environment variables for API details
+API_TOKEN = os.getenv("HUGGINGFACE_API_TOKEN")  # Fetching the API token from environment variable
+
+# Function to query Hugging Face API
+def query_huggingface_api(api_url, prompt):
+    headers = {"Authorization": f"Bearer {API_TOKEN}"}
+    data = {"inputs": prompt}
+    response = requests.post(api_url, headers=headers, json=data)
+    
+    if response.status_code == 200:
+        # Assuming the API returns binary image data
+        return response.content
+    else:
+        return None, f"Error {response.status_code}: {response.text}"
+
+# Gradio function for generating the image
+def generate_image(api_url, prompt):
+    result, error = query_huggingface_api(f"https://api-inference.huggingface.co/models/{api_url}", prompt)
+    
+    if result:
+        return result, None
+    else:
+        return None, error
+
+# Create Gradio Blocks Interface
+with gr.Blocks() as demo:
+    gr.Markdown(
+        """
+        # Text to Image Generator
+        Enter a text prompt, and the custom model will generate an image.
+        """
+    )
+
+    with gr.Row():
+        with gr.Column():
+            text_input = gr.Textbox(
+                label="Enter your prompt", 
+                placeholder="Type something here..."
+            )
+            model_input = gr.Textbox(
+                label="Model URL", 
+                placeholder="Enter the model URL...",
+                value="user/sdwarm"
+            )
+            generate_btn = gr.Button("Generate Image")
+        
+        with gr.Column():
+            image_output = gr.Image(label="Generated Image")
+            error_output = gr.Textbox(label="Error", interactive=False)
+
+    # Define the action for the button
+    generate_btn.click(
+        fn=generate_image, 
+        inputs=[model_input, text_input],  # Pass both model URL and prompt
+        outputs=[image_output, error_output]
+    )
+
+# Launch the Gradio Blocks WebUI
+demo.launch()