Upload 2 files

app.py

@@ -1,8 +1,6 @@
 import logging
 import gradio as gr
 from utils.document_utils import initialize_logging
-from retriever.chat_manager import chat_response
- # Note: DocumentManager is now initialized in retrieve_documents.py
 from globals import app_config 
 
 # Configure logging
@@ -13,47 +11,54 @@ def load_sample_question(question):
     return question
 
 def clear_selection():
-    return [], "", []  # Reset doc_selector to empty list
+    return gr.update(value=[]), "", ""  # Reset doc_selector to empty list
 
 def process_uploaded_file(file, current_selection):
     """Process uploaded file using DocumentManager and update UI."""
-    status, page_list, filename, _ = app_config.doc_manager.process_document(file.name if file else None)
-
-    # Update current selection to include new file if not already present
-    updated_selection = current_selection if current_selection else []
-    if filename and filename not in updated_selection:
-        updated_selection.append(filename)
-
-    return (
-        status,
-        page_list,
-        gr.update(choices=app_config.doc_manager.get_uploaded_documents(), value=updated_selection)
-    )
+    try:
+        if file is None:
+            # When file input is cleared, preserve current selection and choices
+            uploaded_docs = app_config.doc_manager.get_uploaded_documents()
+            return (
+                "",
+                gr.update(choices=uploaded_docs, value=current_selection or []),
+                False,
+                ""
+            )
+        
+        status, filename, doc_id = app_config.doc_manager.process_document(file.name if file else None)
+
+        updated_selection = current_selection if current_selection else []
+        if filename and filename not in updated_selection:
+            updated_selection.append(filename)
+        trigger_summary = bool(filename)
+        logging.info(f"Processed file: {filename}, Trigger summary: {trigger_summary}")
+
+        return (
+            status,
+            gr.update(choices=app_config.doc_manager.get_uploaded_documents(), value=updated_selection),
+            trigger_summary,
+            filename  
+        )
+    except Exception as e:
+        logging.error(f"Error in process_uploaded_file: {e}")
+        return "Error processing file", gr.update(choices=[]), False, ''
 
 def update_doc_selector(selected_docs):
     """Keep selected documents in sync."""
     return selected_docs
 
 # UI Configuration
-models = ["qwen-2.5-32b", "gemma2-9b-it"]
+models = [ "gemma2-9b-it", "llama3-70b-8192"]
+
 example_questions = [
-    "What is communication server?",
+    "What is the architecture of the Communication Server?",
     "Show me an example of a configuration file.",
     "How to create Protected File Directories ?",
-    "What are the attributes Azureblobstorage?",
+    "What functionalities are available in the Communication Server setups?",
     "What is Mediator help?",
     "Why AzureBlobStorage port is used?"
 ]
-all_questions = [
-    "Can you explain Communication Server architecture?",
-    "Why does the other instance of my multi-instance qmgr seem to hang after a failover? Queue manager will not start after failover.",
-    "Explain the concept of blockchain.",
-    "What is the capital of France?",
-    "Do Surface Porosity and Pore Size Influence Mechanical Properties and Cellular Response to PEEK?",
-    "How does a vaccine work?",
-    "Tell me the step-by-step instruction for front-door installation.",
-    "What are the risk factors for heart disease?",
-]
 
 with gr.Blocks(css="""
         .chatbot .user {
@@ -88,6 +93,13 @@ with gr.Blocks(css="""
         # 🤖 IntelliDoc: AI Document Explorer
         **AI Document Explorer** allows you to upload PDF documents and interact with them using AI-powered analysis and summarization. Ask questions, extract key insights, and gain a deeper understanding of your documents effortlessly.
     """)
+    summary_query_state = gr.State()  # State to hold the summary query
+    trigger_summary_state = gr.State()  # State to hold trigger flag
+    filename_state = gr.State()  # State to hold file name
+    chunks_state = gr.State()
+    summary_text_state = gr.State()
+    sample_questions_state = gr.State()
+
     with gr.Row():
         # Left Sidebar
         with gr.Column(scale=2):
@@ -104,18 +116,19 @@ with gr.Blocks(css="""
             upload_status = gr.Textbox(label="Upload Status", interactive=False)
 
             # Process uploaded file and update UI
-            upload_btn.change(
+            upload_event = upload_btn.change(
                 process_uploaded_file,
                 inputs=[upload_btn, doc_selector],
                 outputs=[
                     upload_status,
-                    gr.State(),  # page_list
-                    doc_selector  # Update choices and value together
+                    doc_selector,
+                    trigger_summary_state,  # Store trigger_summary
+                    filename_state
                 ]
             )
             clear_btn.click(
                 clear_selection,
-                outputs=[doc_selector, upload_status, gr.State()]
+                outputs=[doc_selector, upload_status, filename_state]
             )
             # Reinitialize LLM when the model changes
             model_selector.change(
@@ -131,19 +144,20 @@ with gr.Blocks(css="""
             with gr.Row():
                 chat_input = gr.Textbox(label="Ask additional questions about the document...", show_label=False, placeholder="Ask additional questions about the document...", elem_id="chat-input", lines=3)
                 chat_btn = gr.Button("🚀 Send", variant="primary", elem_id="send-button", scale=0)
-            chat_btn.click(chat_response, inputs=[chat_input, doc_selector, chat_history], outputs=chat_history).then(
+            chat_btn.click(app_config.chat_manager.generate_chat_response, inputs=[chat_input, doc_selector, chat_history], outputs=chat_history).then(
                 lambda: "",  # Return an empty string to clear the chat_input
                 outputs=chat_input
             )
 
         # Right Sidebar (Sample Questions & History)
         with gr.Column(scale=2):
-            gr.Markdown("## Frequently asked questions:")
+            gr.Markdown("## Sample questions for this document:")
             with gr.Column():
-                gr.Examples(
-                    examples=example_questions,
-                    inputs=chat_input,
-                    label=""
+                sample_questions = gr.Dropdown(
+                    label="Select a sample question",
+                    choices=[],
+                    interactive=True,
+                    allow_custom_value=True  # Allows users to type custom questions if needed
                 )
                 '''question_dropdown = gr.Dropdown(
                     label="",
@@ -152,9 +166,44 @@ with gr.Blocks(css="""
                     info="Choose a question from the dropdown to populate the query box."
                 )'''
 
+           # After upload, generate "Auto Summary" message only if trigger_summary is True
+            upload_event.then(
+                fn=lambda trigger, filename: "Can you provide summary of the document" if trigger and filename else None,
+                inputs=[trigger_summary_state, filename_state],
+                outputs=[summary_query_state]
+                ).then(
+                    fn=lambda query, history: history + [{"role": "user", "content": ""}, {"role": "assistant", "content": "Generating summary of the document, please wait..."}] if query else history,
+                    inputs=[summary_query_state, chat_history],
+                    outputs=[chat_history]
+                ).then(
+                    fn=lambda trigger, filename: app_config.doc_manager.get_chunks(filename) if trigger and filename else None,
+                    inputs=[trigger_summary_state, filename_state],
+                    outputs=[chunks_state]
+                ).then(
+                    fn=lambda chunks: app_config.chat_manager.generate_summary(chunks) if chunks else None,
+                    inputs=[chunks_state],
+                    outputs=[summary_text_state]
+                ).then(
+                    fn=lambda summary, history: history + [{"role": "assistant", "content": summary}] if summary else history,
+                    inputs=[summary_text_state, chat_history],
+                    outputs=[chat_history]
+                ).then(
+                    fn=lambda chunks: app_config.chat_manager.generate_sample_questions(chunks) if chunks else [],
+                    inputs=[chunks_state],
+                    outputs=[sample_questions_state]
+                ).then(
+                    fn=lambda questions: gr.update(choices=questions if questions else ["No questions available"]),
+                    inputs=[sample_questions_state],
+                    outputs=[sample_questions]
+                )
+            # Populate chat_input when a question is selected
+            sample_questions.change(
+                fn=lambda question: question,
+                inputs=[sample_questions],
+                outputs=[chat_input]
+            )
             #gr.Markdown("## Logs")
             #history = gr.Textbox(label="Previous Queries", interactive=False)
 
-
 if __name__ == "__main__":
     interface.launch()