Update app.py

app.py

@@ -278,36 +278,37 @@ def upload_file(file_obj):
     return list_file_path
 
 
-
-
 def demo():
     with gr.Blocks(theme="base") as demo:
         vector_db = gr.State()
         qa_chain = gr.State()
         collection_name = gr.State()
-        
-        gr.Markdown(
-        """<center><h2>BookMyDarshan: Your Personalized Spiritual Assistant</h2></center>
-        <h3>Explore Sacred Texts and Enhance Your Spiritual Journey</h3>""")
-        
-        gr.Markdown(
-    """<b>About BookMyDarshan.in:</b> We are dedicated to providing pilgrims with exceptional temple darshan experiences. 
-    Our platform offers a comprehensive suite of spiritual and religious services, tailored to meet your devotional needs.<br><br>
-    <b>Note:</b> This spiritual assistant uses state-of-the-art AI to help you explore and understand your uploaded spiritual documents. 
-    Combining technology with tradition, this tool assists in deepening your connection with your faith.<br>"""
-)
-
-        with gr.Tab("Step 1: Upload PDF"):
-            document = gr.Files(label="Upload your PDF documents", file_count="multiple", file_types=["pdf"], interactive=True)
 
-        with gr.Tab("Step 2: Process Document"):
-            db_btn = gr.Radio(["ChromaDB"], label="Select Vector Database", value="ChromaDB", info="Choose your vector database")
-            with gr.Accordion("Advanced Options: Text Splitter", open=False):
-                slider_chunk_size = gr.Slider(minimum=100, maximum=1000, value=600, step=20, label="Chunk Size", info="Adjust chunk size for text splitting")
-                slider_chunk_overlap = gr.Slider(minimum=10, maximum=200, value=40, step=10, label="Chunk Overlap", info="Adjust overlap between chunks")
-            db_progress = gr.Textbox(label="Vector Database Initialization Status", value="None", interactive=False)
-            generate_db_btn = gr.Button("Generate Vector Database")
+        gr.Markdown(
+            """<center><h2>Book My Darshan Chatbot</center></h2>
+            <h3>Plan and book your spiritual journeys effortlessly</h3>""")
 
+        gr.Markdown(
+            """<b>Note:</b> This chatbot helps you book darshan services through BookMyDarshan.in. Simply provide the temple name, date, and time, and the chatbot will assist you with the booking process.""")
+        
+        with gr.Tab("Step 1 - Upload PDF"):
+            with gr.Row():
+                document = gr.Files(height=100, file_count="multiple", file_types=["pdf"], interactive=True, label="Upload your PDF documents (single or multiple)")
+                # upload_btn = gr.UploadButton("Loading document...", height=100, file_count="multiple", file_types=["pdf"], scale=1)
+        
+        with gr.Tab("Step 2 - Process document"):
+            with gr.Row():
+                db_btn = gr.Radio(["ChromaDB"], label="Vector database type", value = "ChromaDB", type="index", info="Choose your vector database")
+            with gr.Accordion("Advanced options - Document text splitter", open=False):
+                with gr.Row():
+                    slider_chunk_size = gr.Slider(minimum = 100, maximum = 1000, value=600, step=20, label="Chunk size", info="Chunk size", interactive=True)
+                with gr.Row():
+                    slider_chunk_overlap = gr.Slider(minimum = 10, maximum = 200, value=40, step=10, label="Chunk overlap", info="Chunk overlap", interactive=True)
+            with gr.Row():
+                db_progress = gr.Textbox(label="Vector database initialization", value="None")
+            with gr.Row():
+                db_btn = gr.Button("Generate vector database")
+            
         with gr.Tab("Step 3 - Initialize QA chain"):
             with gr.Row():
                 llm_btn = gr.Radio(list_llm_simple, \
@@ -324,60 +325,51 @@ def demo():
             with gr.Row():
                 qachain_btn = gr.Button("Initialize Question Answering chain")
 
-   
-
-
-        with gr.Tab("Step 4: Chatbot"):
-            chatbot = gr.Chatbot(label="Chat with your PDF", height=300)
-            with gr.Accordion("Advanced: Document References", open=False):
+        with gr.Tab("Step 4 - Chatbot"):
+            chatbot = gr.Chatbot(height=300)
+            with gr.Accordion("Advanced - Document references", open=False):
                 with gr.Row():
-                    doc_source1 = gr.Textbox(label="Reference 1", lines=2)
-                    source1_page = gr.Number(label="Page", interactive=True)
+                    doc_source1 = gr.Textbox(label="Reference 1", lines=2, container=True, scale=20)
+                    source1_page = gr.Number(label="Page", scale=1)
                 with gr.Row():
-                    doc_source2 = gr.Textbox(label="Reference 2", lines=2)
-                    source2_page = gr.Number(label="Page", interactive=True)
+                    doc_source2 = gr.Textbox(label="Reference 2", lines=2, container=True, scale=20)
+                    source2_page = gr.Number(label="Page", scale=1)
                 with gr.Row():
-                    doc_source3 = gr.Textbox(label="Reference 3", lines=2)
-                    source3_page = gr.Number(label="Page", interactive=True)
-            msg = gr.Textbox(placeholder="Type your question here...", label="Ask a Question", container=True)
+                    doc_source3 = gr.Textbox(label="Reference 3", lines=2, container=True, scale=20)
+                    source3_page = gr.Number(label="Page", scale=1)
             with gr.Row():
-                submit_btn = gr.Button("Submit")
-                clear_btn = gr.Button("Clear Conversation")
-
+                msg = gr.Textbox(placeholder="Type message (e.g. 'What is this document about?')", container=True)
+            with gr.Row():
+                submit_btn = gr.Button("Submit message")
+                clear_btn = gr.ClearButton([msg, chatbot], value="Clear conversation")
+            
         # Preprocessing events
-        generate_db_btn.click(initialize_database, inputs=[document, slider_chunk_size, slider_chunk_overlap], outputs=[vector_db, collection_name, db_progress])
-        qachain_btn.click(
-            initialize_LLM, 
-            inputs=[llm_btn, slider_temperature, slider_maxtokens, slider_topk, vector_db], 
-            outputs=[qa_chain, llm_progress]
-        ).then(
-            lambda: [None, "", 0, "", 0, "", 0],
-            inputs=None,
-            outputs=[chatbot, doc_source1, source1_page, doc_source2, source2_page, doc_source3, source3_page],
-            queue=False
-        )
+        #upload_btn.upload(upload_file, inputs=[upload_btn], outputs=[document])
+        db_btn.click(initialize_database, \
+            inputs=[document, slider_chunk_size, slider_chunk_overlap], \
+            outputs=[vector_db, collection_name, db_progress])
+        qachain_btn.click(initialize_LLM, \
+            inputs=[llm_btn, slider_temperature, slider_maxtokens, slider_topk, vector_db], \
+            outputs=[qa_chain, llm_progress]).then(lambda:[None,"",0,"",0,"",0], \
+            inputs=None, \
+            outputs=[chatbot, doc_source1, source1_page, doc_source2, source2_page, doc_source3, source3_page], \
+            queue=False)
 
         # Chatbot events
-        msg.submit(
-            conversation,
-            inputs=[qa_chain, msg, chatbot],
-            outputs=[qa_chain, msg, chatbot, doc_source1, source1_page, doc_source2, source2_page, doc_source3, source3_page],
-            queue=False
-        )
-        submit_btn.click(
-            conversation,
-            inputs=[qa_chain, msg, chatbot],
-            outputs=[qa_chain, msg, chatbot, doc_source1, source1_page, doc_source2, source2_page, doc_source3, source3_page],
-            queue=False
-        )
-        clear_btn.click(
-            lambda: [None, "", 0, "", 0, "", 0],
-            inputs=None,
-            outputs=[chatbot, doc_source1, source1_page, doc_source2, source2_page, doc_source3, source3_page],
-            queue=False
-        )
+        msg.submit(conversation, \
+            inputs=[qa_chain, msg, chatbot], \
+            outputs=[qa_chain, msg, chatbot, doc_source1, source1_page, doc_source2, source2_page, doc_source3, source3_page], \
+            queue=False)
+        submit_btn.click(conversation, \
+            inputs=[qa_chain, msg, chatbot], \
+            outputs=[qa_chain, msg, chatbot, doc_source1, source1_page, doc_source2, source2_page, doc_source3, source3_page], \
+            queue=False)
+        clear_btn.click(lambda:[None,"",0,"",0,"",0], \
+            inputs=None, \
+            outputs=[chatbot, doc_source1, source1_page, doc_source2, source2_page, doc_source3, source3_page], \
+            queue=False)
     demo.queue().launch(debug=True)
 
 
 if __name__ == "__main__":
-    demo()
+    demo()