Update app.py

app.py

@@ -1,8 +1,10 @@
 import argparse
 import os
+
 import gradio as gr
 from loguru import logger
-from similarities import BertSimilarity
+from similarities import BertSimilarity, BM25Similarity
+
 from chatpdf import ChatPDF
 
 pwd_path = os.path.abspath(os.path.dirname(__file__))
@@ -16,6 +18,8 @@ if __name__ == '__main__':
     parser.add_argument("--rerank_model_name", type=str, default="")
     parser.add_argument("--corpus_files", type=str, default="Acuerdo009.pdf")
     parser.add_argument("--device", type=str, default=None)
+    #parser.add_argument("--int4", action='store_true', help="use int4 quantization")
+    #parser.add_argument("--int8", action='store_true', help="use int8 quantization")
     parser.add_argument("--chunk_size", type=int, default=220)
     parser.add_argument("--chunk_overlap", type=int, default=0)
     parser.add_argument("--num_expand_context_chunk", type=int, default=1)
@@ -41,6 +45,8 @@ if __name__ == '__main__':
     )
     logger.info(f"chatpdf model: {model}")
 
+     logger.info(f"chatpdf model: {model}")
+
     def predict_stream(message, history):
         history_format = []
         for human, assistant in history:
@@ -57,21 +63,18 @@ if __name__ == '__main__':
         logger.debug(r)
         return r
 
-    # Crear el chatbot
+
     chatbot_stream = gr.Chatbot(
         height=600,
         avatar_images=(
             os.path.join(pwd_path, "assets/user.png"),
             os.path.join(pwd_path, "assets/Logo1.png"),
-        ),
-        bubble_full_width=False
-    )
-    
+        ), bubble_full_width=False)
+    # Actualizar el título y la descripción
     title = " 🤖ChatPDF Zonia🤖 "
-    css = """.toast-wrap { display: none !important } """
+    # description = "Enlace en Github: [shibing624/ChatPDF](https://github.com/shibing624/ChatPDF)"
+    css = """.toast-wrap { display: none !importante } """
     examples = ['Puede hablarme del PNL?', 'Introducción a la PNL']
-
-    # Crear la interfaz sin utilizar la función que usa yield
     chat_interface_stream = gr.ChatInterface(
         predict_stream,
         textbox=gr.Textbox(lines=4, placeholder="Ask me question", scale=7),  # Añadir submit=True