Create app.py

app.py

@@ -0,0 +1,63 @@
+import requests
+import gradio as gr
+from PIL import Image
+import io
+import os
+
+# API settings
+API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-3-medium-diffusers"
+headers = {"Authorization": f"Bearer {os.getenv('HF_API_KEY')}"}
+
+def query(payload):
+    response = requests.post(API_URL, headers=headers, json=payload)
+    return response.content
+
+def generate_room_plan(space_type, prompt):
+    # Validate the prompt based on selected space type
+    valid_prompt = False
+    if space_type == "office" and "office" in prompt:
+        valid_prompt = True
+    elif space_type == "house" and "house" in prompt:
+        valid_prompt = True
+    elif space_type == "room" and "room" in prompt:
+        valid_prompt = True
+    
+    if not valid_prompt:
+        return "Error: The prompt does not match the selected space type or is invalid."
+
+    image_bytes = query({"inputs": prompt})
+    
+    # Convert the byte content to an image
+    image = Image.open(io.BytesIO(image_bytes))
+    
+    return image
+
+with gr.Blocks() as app:
+    gr.Markdown("# Space Plan Generator")
+
+    with gr.Row():
+        space_type = gr.Dropdown(
+            choices=["office", "house", "room"],
+            label="Select Space Type"
+        )
+        user_prompt = gr.Textbox(label="Enter the dimensions and other details")
+
+    output = gr.Image(label="Generated Space Plan")
+    error_message = gr.Markdown(label="")
+
+    def on_button_click(space_type, prompt):
+        result = generate_room_plan(space_type, prompt)
+        if isinstance(result, str):  # If the result is an error message
+            error_message.update(result)
+            return None
+        else:
+            error_message.update("")
+            return result
+
+    gr.Button("Generate Space Plan").click(
+        on_button_click,
+        inputs=[space_type, user_prompt],
+        outputs=[output]
+    )
+
+app.launch()