Update app.py

app.py

@@ -1,3 +1,41 @@
 import gradio as gr
+import requests
+import base64
+from io import BytesIO
+import os
 
-gr.load("models/soiz1/shirakami-hubuki-hololive").launch()
+API_URL = "https://api-inference.huggingface.co/models/soiz1/shirakami-hubuki-diffusion"
+HEADERS = {"Authorization": f"Bearer {os.getenv('token')}"}
+
+def generate_image(prompt, negative_prompt, steps, guidance_scale):
+    payload = {
+        "inputs": prompt,
+        "parameters": {
+            "negative_prompt": negative_prompt,
+            "num_inference_steps": steps,
+            "guidance_scale": guidance_scale
+        }
+    }
+    response = requests.post(API_URL, headers=HEADERS, json=payload)
+    if response.status_code == 200:
+        image_data = response.content
+        image = BytesIO(image_data)
+        return image
+    else:
+        return f"Error: {response.status_code}, {response.text}"
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Shirakami Hubuki LoRA Image Generator")
+    with gr.Row():
+        with gr.Column():
+            prompt = gr.Textbox(label="Prompt", placeholder="Describe your image")
+            negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="What to avoid")
+            steps = gr.Slider(1, 50, value=25, step=1, label="Inference Steps")
+            guidance_scale = gr.Slider(1, 20, value=7.5, step=0.1, label="Guidance Scale")
+            submit = gr.Button("Generate")
+        with gr.Column():
+            output_image = gr.Image(label="Generated Image")
+    
+    submit.click(generate_image, inputs=[prompt, negative_prompt, steps, guidance_scale], outputs=output_image)
+
+demo.launch()