.

app.py

@@ -170,9 +170,9 @@ def on_files_cleared():
     return(gr.CheckboxGroup(choices=[]))
 
 # Define the Gradio interface
-title = "Deep Learning - Natural Language Processing"
-subtitle = "Questão e Resposta assistida por LLMs sobre documentos PDF"
-authors = "Hugo Cavalaria | Nuno Seiça | Ricardo Neves | Wilton Nagase"
+title = "Question/Answer over Documents"
+subtitle = "OpenAI GPT 3.5 Turbo LLM assisted Question/Answer over multiple PDF context documents"
+authors = "Hugo Cavalaria "
 custom_layout = "<h1>{}</h1><h2>{}</h2><p>{}</p>".format(title,subtitle,authors)
 
 # Get the list of languages available
@@ -187,15 +187,15 @@ with gr.Blocks() as interface:
 
     with gr.Row():
       with gr.Column(scale=1):
-        upload_pdfs = gr.Files(label="Fazer upload de ficheiros PDF", interactive=True, file_types=['.pdf'], container=True)
-        checkbox_group = gr.CheckboxGroup(label="Selecionar os ficheiros a utilizar.", choices=[], interactive=True)
-        question_text = gr.Textbox(label="Pergunta:")
-        answer_language = gr.Dropdown(label="Selecionar uma linguagem para tradução da resposta.", choices=language_names, value="Portuguese")
+        upload_pdfs = gr.Files(label="Upload multiple PDF files.", interactive=True, file_types=['.pdf'], container=True)
+        checkbox_group = gr.CheckboxGroup(label="Select the files to question.", choices=[], interactive=True)
+        question_text = gr.Textbox(label="Question:")
+        answer_language = gr.Dropdown(label="Answer translation to:", choices=language_names, value="Portuguese")
         secret_key = gr.Textbox(label="OpenAI API Key:")
       with gr.Column(scale=1):
-        output_status = gr.Textbox(label="Resposta:")
+        output_status = gr.Textbox(label="Answer:")
 
-    btn = gr.Button("Perguntar")
+    btn = gr.Button("Ask")
 
     btn.click(fn=run_qa,
               inputs=[upload_pdfs,checkbox_group,question_text,answer_language,secret_key],