Update app.py

app.py

@@ -5,6 +5,8 @@ import io
 import base64  # Adicionando a biblioteca base64 para decodificação
 from PIL import Image
 import subprocess
+
+# Instalando a dependência flash-attn se necessário
 subprocess.run('pip install flash-attn --no-build-isolation', env={'FLASH_ATTENTION_SKIP_CUDA_BUILD': "TRUE"}, shell=True)
 
 # Carregando o modelo e o processador
@@ -90,20 +92,20 @@ document.querySelector('button').addEventListener('click', function() {
 });
 """
 
-single_task_list =[ 'Product Caption', 'OCR' ]
+single_task_list = ['Product Caption', 'OCR']
 
 with gr.Blocks(css=css) as demo:
     gr.Markdown(DESCRIPTION)
     with gr.Tab(label="Product Image Select"):
         with gr.Row():
             with gr.Column():
-                input_img = gr.Image(label="Input Picture", tool="editor", source="upload", type="pil")  # Suporte a PIL images
+                input_img = gr.Image(label="Input Picture", source="upload", type="pil")  # Suporte a PIL images
                 task_prompt = gr.Dropdown(choices=single_task_list, label="Task Prompt", value="Product Caption")
                 submit_btn = gr.Button(value="Submit")
             with gr.Column():
                 output_text = gr.HTML(label="Output Text", elem_id="output")
         
-        gr.Markdown("""
+        gr.Markdown(""" 
         ## How to use via API
         To use this model via API, you can follow the example code below:
 
@@ -126,12 +128,11 @@ with gr.Blocks(css=css) as demo:
 
         response = requests.post("http://your-space-url-here", json=payload)
         print(response.json())
-        ```
-
+        ``` 
         """)
         
         submit_btn.click(process_image, [input_img, task_prompt], [output_text])
 
     demo.load(lambda: None, inputs=None, outputs=None, js=js)
 
-demo.launch(debug=True)
+demo.launch(debug=True)