update summary rev

app.py

@@ -29,6 +29,9 @@ def summary(self):
     avg_doc_length = sum(len(doc) for doc in self.documents) / num_documents
     return f"Number of documents: {num_documents}, Average document length: {avg_doc_length}"
 
+# Gradio state
+summary_state = gr.State(initial_value="pending")
+
 # PDF summary and query using stuffing
 def pdf_changes(pdf_doc):
     try:
@@ -54,6 +57,8 @@ def pdf_changes(pdf_doc):
         # Generate summary using StuffDocumentsChain
         global full_summary
         full_summary = stuff_chain.run(documents)
+        # Update the state variable
+        return {summary_state: full_summary}
 
         # Other existing logic for Chroma, embeddings, and retrieval
         embeddings = OpenAIEmbeddings()
@@ -116,23 +121,23 @@ def infer(question, history):
         return f"Error querying chatbot: {str(e)}"
 
 def auto_clear_data():
-    global qa, db, last_interaction_time
-    if time.time() - last_interaction_time > 1000:
+      global qa, db, last_interaction_time
+      if time.time() - last_interaction_time > 1000:
         qa = None
         db = None
         print("Data cleared successfully.")  # Logging
-
+        
 def periodic_clear():
-    while True:
-        auto_clear_data()
-        time.sleep(1000)
-
+      while True:
+      auto_clear_data()
+      time.sleep(1000)
+        
 threading.Thread(target=periodic_clear).start()
-
+        
 css = """
 #col-container {max-width: 700px; margin-left: auto; margin-right: auto;}
 """
-
+        
 title = """
 <div style="text-align: center;max-width: 700px;">
     <h1>CauseWriter Chat with PDF • OpenAI</h1>
@@ -141,52 +146,39 @@ title = """
     This version is set to erase chat history automatically after page timeout and uses OpenAI.</p>
 </div>
 """
-# Global variable for tracking last interaction time
-last_interaction_time = 0
-full_summary = ""  # Added global full_summary
-
-def update_summary_box():
-    global full_summary
-    return {"summary_box": full_summary}
-
+        
 with gr.Blocks(css=css) as demo:
-    with gr.Column(elem_id="col-container"):
-        gr.HTML(title)
+        with gr.Column(elem_id="col-container"):
+            gr.HTML(title)
+                
+            with gr.Column():
+                  pdf_doc = gr.File(label="Load a pdf", file_types=['.pdf'], type="file")
+                  with gr.Row():
+                      langchain_status = gr.Textbox(label="Status", placeholder="", interactive=False)
+                      load_pdf = gr.Button("Convert PDF to Magic AI language")
+                      clear_btn = gr.Button("Clear Data")
+                    
+                    # New Textbox to display summary
+                  summary_box = gr.Textbox(
+                      label="Document Summary",
+                      placeholder="Summary will appear here.",
+                      interactive=False,
+                      rows=5,
+                      elem_id="summary_box"  # Set the elem_id to match the state key
+                    )
+                
+            chatbot = gr.Chatbot([], elem_id="chatbot").style(height=450)
+            question = gr.Textbox(label="Question", placeholder="Type your question and hit Enter")
+            submit_btn = gr.Button("Send Message")
         
-        with gr.Column():
-            pdf_doc = gr.File(label="Load a pdf", file_types=['.pdf'], type="file")
-            with gr.Row():
-                langchain_status = gr.Textbox(label="Status", placeholder="", interactive=False)
-                load_pdf = gr.Button("Convert PDF to Magic AI language")
-                clear_btn = gr.Button("Clear Data")
-            
-            # New Textbox to display summary
-            summary_box = gr.Textbox(
-              label="Document Summary",
-              placeholder="Summary will appear here.",
-              interactive=False,
-              rows=5,
-              elem_id="summary_box"  # Set the elem_id to match the state key
+            # Step 2 and 3: Put the State object as an input and output
+            load_pdf.click(pdf_changes, inputs=[pdf_doc, summary_state], outputs=[langchain_status, summary_state])
+            clear_btn.click(clear_data, outputs=[langchain_status])
+            question.submit(add_text, [chatbot, question], [chatbot, question]).then(
+                  bot, chatbot, chatbot
+            )
+            submit_btn.click(add_text, [chatbot, question], [chatbot, question]).then(
+                  bot, chatbot, chatbot
             )
-
         
-        chatbot = gr.Chatbot([], elem_id="chatbot").style(height=450)
-        question = gr.Textbox(label="Question", placeholder="Type your question and hit Enter")
-        submit_btn = gr.Button("Send Message")
-
-        load_pdf.click(loading_pdf, None, langchain_status, queue=False)
-        load_pdf.click(pdf_changes, inputs=[pdf_doc], outputs=[langchain_status], queue=False).then(
-          update_summary_box
-      )
-
-
-    # Then update the summary_box
-    clear_btn.click(clear_data, outputs=[langchain_status], queue=False)
-    question.submit(add_text, [chatbot, question], [chatbot, question]).then(
-        bot, chatbot, chatbot
-    )
-    submit_btn.click(add_text, [chatbot, question], [chatbot, question]).then(
-        bot, chatbot, chatbot
-    )
-
 demo.launch()