Update app.py

app.py

@@ -2,50 +2,44 @@ import requests
 import io
 from PIL import Image
 import gradio as gr
-import os  # To access environment variables
+import os
 
-# Access the Hugging Face API token securely
-API_TOKEN = os.getenv("HF_API_TOKEN")
+# Assuming you've set up API_TOKEN and other constants as before
 
-if not API_TOKEN:
-    raise ValueError("Hugging Face API token not found. Please check your Space's secrets configuration.")
-
-API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0"
-headers = {"Authorization": f"Bearer {API_TOKEN}"}
-
-def query(payload):
-    response = requests.post(API_URL, headers=headers, json=payload)
-    return response.content
-
-def generate_image(prompt, negative_prompt, guidance_scale, width, height, num_inference_steps):
+def generate_image(prompt, negative_prompt=None, guidance_scale=7.5, width=1024, height=768, num_inference_steps=30):
     payload = {
         "inputs": prompt,
         "parameters": {
-            "negative_prompt": negative_prompt,
-            "guidance_scale": guidance_scale,
             "width": width,
             "height": height,
+            "guidance_scale": guidance_scale,
             "num_inference_steps": num_inference_steps,
         },
     }
-    image_bytes = query(payload)
+    # Include negative prompt in the payload if provided
+    if negative_prompt:
+        payload["parameters"]["negative_prompt"] = negative_prompt
+
+    response = requests.post(API_URL, headers=headers, json=payload)
+    image_bytes = response.content
     image = Image.open(io.BytesIO(image_bytes))
     return image
 
-# Create Gradio interface
+# Define Gradio interface components
 iface = gr.Interface(
     fn=generate_image,
     inputs=[
-        gr.Slider(label="Guidance Scale", minimum=1, maximum=20, step=0.1, value=7.5),
-gr.Slider(label="Width", minimum=768, maximum=1024, step=1, value=1024),
-gr.Slider(label="Height", minimum=768, maximum=1024, step=1, value=768),
-gr.Slider(label="Number of Inference Steps", minimum=20, maximum=50, step=1, value=30)
-
+        gr.Textbox(label="Prompt", placeholder="Enter your prompt here..."),
+        gr.Textbox(label="Negative Prompt", placeholder="Enter a negative prompt here (optional)...", optional=True),
+        gr.Slider(label="Guidance Scale", minimum=1, maximum=20, step=0.1, default=7.5),
+        gr.Slider(label="Width", minimum=768, maximum=1024, step=1, default=1024),
+        gr.Slider(label="Height", minimum=768, maximum=1024, step=1, default=768),
+        gr.Slider(label="Number of Inference Steps", minimum=20, maximum=50, step=1, default=30)
     ],
     outputs=gr.Image(type="pil"),
     title="Stable Diffusion XL Image Generator",
-    description="Generate images with Stable Diffusion XL. Provide a prompt, specify any negative prompts, and adjust the image generation parameters.",
+    description="Generate images with Stable Diffusion XL. Provide a prompt, optionally specify a negative prompt, and adjust other parameters as desired."
 )
 
-# Launch the Gradio app, setting share=True for Hugging Face Spaces
-iface.launch(share=True)
+# Launch the Gradio app
+iface.launch()