Update app.py

app.py

@@ -1,19 +1,15 @@
 import gradio as gr
 from transformers import AutoProcessor, PaliGemmaForConditionalGeneration
-import requests
-from PIL import Image
-import torch, os, re, json
-import spaces
+import torch
 
+# Baixando imagens de exemplo
 torch.hub.download_url_to_file('https://raw.githubusercontent.com/vis-nlp/ChartQA/main/ChartQA%20Dataset/test/png/74801584018932.png', 'chart_example_1.png')
 torch.hub.download_url_to_file('https://raw.githubusercontent.com/vis-nlp/ChartQA/main/ChartQA%20Dataset/val/png/multi_col_1229.png', 'chart_example_2.png')
 
-
-
+# Carregando modelo e processador
 model = PaliGemmaForConditionalGeneration.from_pretrained("ahmed-masry/chartgemma")
 processor = AutoProcessor.from_pretrained("ahmed-masry/chartgemma")
 
-
 @spaces.GPU
 def predict(image, input_text):
     device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
@@ -26,20 +22,25 @@ def predict(image, input_text):
     
     prompt_length = inputs['input_ids'].shape[1]
     
-    # Generate
+    # Geração
     generate_ids = model.generate(**inputs, max_new_tokens=512)
     output_text = processor.batch_decode(generate_ids[:, prompt_length:], skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
 
     return output_text
 
-   
-image = gr.components.Image(type="pil", label="Chart Image")
-input_prompt = gr.components.Textbox(label="Input Prompt")
-model_output = gr.components.Textbox(label="Model Output")
-examples = [["chart_example_1.png", "Describe the trend of the mortality rates for children before age 5"],
-            ["chart_example_2.png", "What is the share of respondants who prefer Facebook Messenger in the 30-59 age group?"]]
+# Definindo os componentes da interface
+image = gr.components.Image(type="pil", label="Imagem do Gráfico")
+input_prompt = gr.components.Textbox(label="Texto de Entrada")
+model_output = gr.components.Textbox(label="Saída do Modelo")
+
+# Exemplos
+examples = [["chart_example_1.png", "Descreva a tendência das taxas de mortalidade para crianças menores de 5 anos"],
+            ["chart_example_2.png", "Qual é a proporção de respondentes que preferem o Facebook Messenger no grupo etário de 30 a 59 anos?"]]
+
+# Título da interface
+title = "Demo Interativa do Modelo ChartGemma"
 
-title = "Interactive Gradio Demo for ChartGemma model"
+# Criando e lançando a interface
 interface = gr.Interface(fn=predict, 
                          inputs=[image, input_prompt], 
                          outputs=model_output, 
@@ -47,4 +48,4 @@ interface = gr.Interface(fn=predict,
                          title=title,
                          theme='gradio/soft')
 
-interface.launch()
+interface.launch()