update

app.py

@@ -93,7 +93,7 @@ def initialize_LLM(llm_option, llm_temperature, max_tokens, top_k, vector_db, pr
     llm_name = list_llm[llm_option]
     print("llm_name: ",llm_name)
     qa_chain = initialize_llmchain(llm_name, llm_temperature, max_tokens, top_k, vector_db, progress)
-    return qa_chain, "QA chain Taiyar hai. Ab swaal pooch sakti ho!"
+    return qa_chain, "QA chain initialized. Chatbot is ready!"
 
 
 def format_chat_history(message, chat_history):
@@ -138,16 +138,16 @@ def demo():
         vector_db = gr.State()
         qa_chain = gr.State()
         gr.HTML("<center><h1>RAG PDF chatbot</h1><center>")
-        gr.Markdown("""<b>Apne PDF k related swaal poochiye!</b> This AI agent is designed to assist Pooja only to help her with the PDF documents. The app is hosted here for the sole purpose of demonstration. \
+        gr.Markdown("""<b>Query your PDF documents!</b> This AI agent is designed to perform retrieval augmented generation (RAG) on PDF documents. The app is hosted on Hugging Face Hub for the sole purpose of demonstration. \
         <b>Please do not upload confidential documents.</b>
         """)
         with gr.Row():
             with gr.Column(scale = 86):
-                gr.Markdown("<b>Step 1 - Yaha apni PDF Upload karo..</b>")
+                gr.Markdown("<b>Step 1 - Upload PDF documents and Initialize RAG pipeline</b>")
                 with gr.Row():
                     document = gr.Files(height=300, file_count="multiple", file_types=["pdf"], interactive=True, label="Upload PDF documents")
                 with gr.Row():
-                    db_btn = gr.Button("Padho Ye PDFs!!!")
+                    db_btn = gr.Button("Create vector database")
                 with gr.Row():
                         db_progress = gr.Textbox(value="Not initialized", show_label=False) # label="Vector database status", 
                 gr.Markdown("<style>body { font-size: 16px; }</style><b>Select Large Language Model (LLM) and input parameters</b>")
@@ -167,7 +167,7 @@ def demo():
                         llm_progress = gr.Textbox(value="Not initialized", show_label=False) # label="Chatbot status", 
 
             with gr.Column(scale = 200):
-                gr.Markdown("<b>Step 2 - Dinesh se na sahi, PDF se baatein karo</b>")
+                gr.Markdown("<b>Step 2 - Chat with your Document</b>")
                 chatbot = gr.Chatbot(height=505)
                 with gr.Accordion("Relevent context from the source document", open=False):
                     with gr.Row():
@@ -182,7 +182,7 @@ def demo():
                 with gr.Row():
                     msg = gr.Textbox(placeholder="Ask a question", container=True)
                 with gr.Row():
-                    submit_btn = gr.Button("Ab Batao..!")
+                    submit_btn = gr.Button("Submit")
                     clear_btn = gr.ClearButton([msg, chatbot], value="Clear")
             
         # Preprocessing events