Update app.py

app.py

@@ -1,35 +1,56 @@
+from pathlib import Path
 import gradio as gr
 
-from diffusers import DiffusionPipeline
-
-
+ANIMALS = [animal.strip() for animal in Path("animals.txt").read_text().splitlines()]
 KEYWORDS = [
     "cute",
     "small",
     "cartoon",
 ]
-
-PIPELINE = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0")
-PIPELINE.load_lora_weights("artificialguybr/LogoRedmond-LogoLoraForSDXL-V2")
+MODEL = gr.Interface.load(
+    "models/artificialguybr/LogoRedmond-LogoLoraForSDXL-V2",
+    live=False,
+    preprocess=True,
+    postprocess=False,
+)
 
 
 def predict(user_prompt: str):
     prompt = ", ".join(KEYWORDS)
     if user_prompt:
-        prompt += ", " + user_prompt
+        prompt += ", " + user_prompt.lower()
+
+    return MODEL(prompt)
 
-    return PIPELINE(prompt).images[0]
 
+select_animal_tab = gr.Interface(
+    predict,
+    inputs=[
+        gr.Dropdown(
+            choices=ANIMALS, value="Cat", filterable=True, label="Select an animal"
+        )
+    ],
+    outputs=[gr.Image(label="Your super cute animal logo 🥺", show_label=True)],
+    allow_flagging="never",
+)
 
-gradio_app = gr.Interface(
+free_input_tab = gr.Interface(
     predict,
     inputs=[
-        gr.Textbox(),
+        gr.Textbox(
+            placeholder="Enter your corporate keywords",
+            label="Generate your Teklia logo",
+        )
     ],
-    outputs=[gr.Image()],
-    title="Cute Logo Creator",
+    outputs=[gr.Image(label="Your super cute corporate logo 🥺", show_label=True)],
+    allow_flagging="never",
 )
 
+qte_app = gr.TabbedInterface(
+    [select_animal_tab, free_input_tab],
+    tab_names=["Cuteness overload", "TekQ-te"],
+    title="Q-te logo creator",
+)
 
 if __name__ == "__main__":
-    gradio_app.launch()
+    qte_app.launch()