Update app.py

app.py

@@ -127,78 +127,109 @@ def rag_pipeline(files, question, summarize_before_sending=False):
     except Exception as e:
         return f"Error: {str(e)}"
 
-# Enhanced UI with modern and clean style
+# # Enhanced UI with modern and clean style
+# with gr.Blocks() as app:
+#     with gr.Row():
+#         # Left Column for instructions
+#         with gr.Column(scale=1, min_width=250):
+#             gr.Markdown("""
+#             <div style="background: linear-gradient(145deg, #6e7dff, #1c2b58); padding: 30px; border-radius: 12px; box-shadow: 0 5px 15px rgba(0, 0, 0, 0.1); font-family: 'Roboto', sans-serif;">
+#                 <h2 style="color: #fff; font-size: 32px; font-weight: bold;">DocAI: Document Assistant</h2>
+#                 <p style="color: #ddd; font-size: 18px;">Welcome to DocAI! Upload your documents and get intelligent answers based on their content.</p>
+#                 <p style="color: #ddd; font-size: 16px; line-height: 1.6;"><strong>Steps to use:</strong></p>
+#                 <ul style="color: #ddd; font-size: 16px; line-height: 1.6;">
+#                     <li>Upload your PDF or DOCX files.</li>
+#                     <li>Ask questions related to the document.</li>
+#                     <li>Enable "Summarize Before Sending" for a brief summary of the document.</li>
+#                     <li>Click "Submit" to get your answers.</li>
+#                 </ul>
+#                 <p style="color: #ddd; font-size: 16px; line-height: 1.6;">Upload multiple files and get answers based on their contents.</p>
+#             </div>
+#             """)
+
+#         # Right Column for the main application content
+#         with gr.Column(scale=2, min_width=600):
+#             gr.Markdown("""
+#             <div style="background: linear-gradient(135deg, #6e7dff, #1c2b58); padding: 20px; border-radius: 15px; box-shadow: 0 5px 15px rgba(0, 0, 0, 0.2); font-family: 'Roboto', sans-serif;">
+#                 <h2 style="color: #fff; font-size: 36px; font-weight: bold; text-align: center; letter-spacing: 2px; text-transform: uppercase;">
+#                     Ask Your Document
+#                 </h2>
+#                 <p style="color: #ddd; font-size: 18px; text-align: center; line-height: 1.6;">
+#                     Get intelligent answers based on the content of your uploaded documents. Just ask a question!
+#                 </p>
+#             </div>
+#             """)
+
+#             # File input
+#             file_input = gr.File(
+#                 label="Upload Documents (PDF/DOCX)", 
+#                 file_types=[".pdf", ".docx"], 
+#                 file_count="multiple", 
+#                 interactive=True
+#             )
+
+#             # Question input
+#             question_input = gr.Textbox(
+#                 label="Ask a question", 
+#                 placeholder="Type your question here...", 
+#                 interactive=True, 
+#                 lines=2, 
+#                 max_lines=4
+#             )
+
+#             # Summarize before sending checkbox
+#             summarize_before_input = gr.Checkbox(
+#                 label="Summarize Before Sending", 
+#                 value=False
+#             )
+
+#             # Output text box with enhanced styling
+#             output = gr.Textbox(
+#                 label="Answer from LLM", 
+#                 interactive=False, 
+#                 lines=4, 
+#                 max_lines=6
+#             )
+            
+#             # Submit button with icon and modern styling
+#             submit_button = gr.Button("Submit", icon="send")
+
+#             # Loading spinner
+#             with gr.Row():
+#                 with gr.Column(scale=1, min_width=250):
+#                     gr.Markdown("<div style='font-size: 14px; color: #555;'>Your answer will appear here...</div>")
+            
+#             # Apply the logic for the button to trigger the RAG pipeline
+#             submit_button.click(rag_pipeline, inputs=[file_input, question_input, summarize_before_input], outputs=output)
+
+# Launch the app
+# app.launch()
 with gr.Blocks() as app:
     with gr.Row():
-        # Left Column for instructions
         with gr.Column(scale=1, min_width=250):
             gr.Markdown("""
-            <div style="background: linear-gradient(145deg, #6e7dff, #1c2b58); padding: 30px; border-radius: 12px; box-shadow: 0 5px 15px rgba(0, 0, 0, 0.1); font-family: 'Roboto', sans-serif;">
-                <h2 style="color: #fff; font-size: 32px; font-weight: bold;">DocAI: Document Assistant</h2>
-                <p style="color: #ddd; font-size: 18px;">Welcome to DocAI! Upload your documents and get intelligent answers based on their content.</p>
-                <p style="color: #ddd; font-size: 16px; line-height: 1.6;"><strong>Steps to use:</strong></p>
-                <ul style="color: #ddd; font-size: 16px; line-height: 1.6;">
-                    <li>Upload your PDF or DOCX files.</li>
-                    <li>Ask questions related to the document.</li>
-                    <li>Enable "Summarize Before Sending" for a brief summary of the document.</li>
-                    <li>Click "Submit" to get your answers.</li>
-                </ul>
-                <p style="color: #ddd; font-size: 16px; line-height: 1.6;">Upload multiple files and get answers based on their contents.</p>
-            </div>
+                <h2>Welcome to DocAI</h2>
+                <p>Upload your documents and get intelligent answers.</p>
             """)
 
-        # Right Column for the main application content
         with gr.Column(scale=2, min_width=600):
             gr.Markdown("""
-            <div style="background: linear-gradient(135deg, #6e7dff, #1c2b58); padding: 20px; border-radius: 15px; box-shadow: 0 5px 15px rgba(0, 0, 0, 0.2); font-family: 'Roboto', sans-serif;">
-                <h2 style="color: #fff; font-size: 36px; font-weight: bold; text-align: center; letter-spacing: 2px; text-transform: uppercase;">
-                    Ask Your Document
-                </h2>
-                <p style="color: #ddd; font-size: 18px; text-align: center; line-height: 1.6;">
-                    Get intelligent answers based on the content of your uploaded documents. Just ask a question!
-                </p>
-            </div>
+                <h2>Ask Your Document</h2>
+                <p>Get intelligent answers based on the content of your uploaded documents. Just ask a question!</p>
             """)
 
             # File input
-            file_input = gr.File(
-                label="Upload Documents (PDF/DOCX)", 
-                file_types=[".pdf", ".docx"], 
-                file_count="multiple", 
-                interactive=True
-            )
+            file_input = gr.File(label="Upload Documents (PDF/DOCX)", file_types=[".pdf", ".docx"], file_count="multiple")
 
             # Question input
-            question_input = gr.Textbox(
-                label="Ask a question", 
-                placeholder="Type your question here...", 
-                interactive=True, 
-                lines=2, 
-                max_lines=4
-            )
-
-            # Summarize before sending checkbox
-            summarize_before_input = gr.Checkbox(
-                label="Summarize Before Sending", 
-                value=False
-            )
-
-            # Output text box with enhanced styling
-            output = gr.Textbox(
-                label="Answer from LLM", 
-                interactive=False, 
-                lines=4, 
-                max_lines=6
-            )
-            
-            # Submit button with icon and modern styling
+            question_input = gr.Textbox(label="Ask a question", placeholder="Type your question here...")
+
+            # Output text box
+            output = gr.Textbox(label="Answer from LLM")
+
+            # Submit button
             submit_button = gr.Button("Submit", icon="send")
 
-            # Loading spinner
-            with gr.Row():
-                with gr.Column(scale=1, min_width=250):
-                    gr.Markdown("<div style='font-size: 14px; color: #555;'>Your answer will appear here...</div>")
-            
             # Apply the logic for the button to trigger the RAG pipeline
             submit_button.click(rag_pipeline, inputs=[file_input, question_input, summarize_before_input], outputs=output)