Update app.py

app.py

@@ -1,14 +1,17 @@
 import os
 import gradio as gr
+import logging
+
+LOG_FORMAT = '%(asctime)s - %(levelname)s  [%(name)s] %(funcName)s -> %(message)s'
+logging.basicConfig(level = logging.DEBUG, format = LOG_FORMAT)
+logger = logging.getLogger(__name__)
+logger.debug('Logging started')
 
 API_KEY=os.environ.get('HUGGING_FACE_HUB_TOKEN', None)
 article = """---
 This space was created using [SD Space Creator](https://huggingface.co/spaces/anzorq/sd-space-creator)."""
-import gradio as gr
-
-article = """---This space was created using [SD Space Creator](https://huggingface.co/spaces/anzorq/sd-space-creator)."""
 
-MODLS=[
+models = [
 "models/ItsJayQz/Marvel_WhatIf_Diffusion",
 "models/DGSpitzer/Cyberpunk-Anime-Diffusion",
 "models/DGSpitzer/Guan-Yu-Diffusion",
@@ -19,24 +22,29 @@ MODLS=[
 "models/stabilityai/stable-diffusion-2-1"
 ]
 
-TXT="AlStable Demo"
-
-def prediction(input_choice):
-    return  gr.Image(input_choice)
-
-def prediction(model_choice, input):
-  modl = MODLS[model_choice]
-  return modl
-
-sandbox = gr.Interface(
-    fn=prediction,
-    inputs=gr.inputs.Dropdown(MODLS),
-    outputs=gr.Image(),
-    title=TXT,
-    description=TXT,
+custom_model = "models/dreamlike-art/dreamlike-diffusion-1.0"
+
+def selectModel(message):
+    message = message.lower()
+    for i in range(len(models)):
+        if message.find(models[i].prefix)!=-1:
+            c_model=models[i].path
+            logging.warning('model selected = '+c_model)
+            return c_model
+    c_model=models[i].path
+    logging.warning('model selected = '+c_model)
+    return c_model
+
+sandbox = gr.Interface.load(
+    fn= selectModel,
+    name= custom_model, 
+    title="""AlStable sandbox""",
+    inputs = gr.Textbox(label="Prompt", show_label=False, max_lines=2, placeholder="Enter your prompt", elem_id="input-prompt"), 
+    description="""Demo for <a href="https://huggingface.co/stabilityai/stable-diffusion-2-1">AlStable</a> Stable Diffusion model.""",
     article=article,
-    api_key=API_KEY    
+    api_key=API_KEY
 )
 
-sandbox.queue(concurrency_count=20).launch()
+logging.warning('model chosen = '+custom_model)
 
+sandbox.queue(concurrency_count=20).launch()