Update app.py

app.py

@@ -14,10 +14,14 @@ logging.basicConfig(level=logging.DEBUG)
 with open('loras.json', 'r') as f:
     loras = json.load(f)
 
-# Define the function to run when the button is clicked
 def update_selection(selected_state: gr.SelectData):
     logging.debug(f"Inside update_selection, selected_state: {selected_state}")
-    # ... your existing code
+    selected_lora_index = selected_state['index']
+    updated_text = loras[selected_lora_index]['title']
+    instance_prompt = "Your custom instance prompt here"
+    new_placeholder = "Your new placeholder here"
+    use_with_diffusers = "Your use_with_diffusers here"
+    use_with_uis = "Your use_with_uis here"
     logging.debug(f"Updated selected_state: {selected_state}")
     return (
         updated_text,
@@ -33,21 +37,12 @@ def run_lora(prompt, selected_state, progress=gr.Progress(track_tqdm=True)):
     if not selected_state:
         logging.error("selected_state is None or empty.")
         raise gr.Error("You must select a LoRA")
-
     selected_lora_index = selected_state['index']
     selected_lora = loras[selected_lora_index]
     api_url = f"https://api-inference.huggingface.co/models/{selected_lora['repo']}"
     trigger_word = selected_lora["trigger_word"]
     token = os.getenv("API_TOKEN")
     payload = {"inputs": f"{prompt} {trigger_word}"}
-    
-    # API call
-    headers = {"Authorization": f"Bearer {token}"}
-    response = requests.post(api_url, headers=headers, json=payload)
-    if response.status_code == 200:
-        return Image.open(io.BytesIO(response.content))
-    else:
-        return "API Error"
 
 # Gradio UI
 with gr.Blocks(css="custom.css") as app: