Update app.py

app.py

@@ -1,5 +1,6 @@
 import os
 from datasets import load_dataset
+import random
 import pickle
 from nltk.tokenize import sent_tokenize
 import nltk
@@ -83,6 +84,23 @@ def remove_redundant_information(text):
 # Define a maximum token limit to avoid infinite loops
 MAX_TOKEN_LIMIT = 400
 
+import random
+
+def generate_dynamic_question(text_chunks):
+    # Randomly pick a sentence from the text chunks and frame a question
+    random_sentence = random.choice(text_chunks)
+    return f"What is the significance of: '{random_sentence}'?"
+
+def display_example_questions(dynamic_question):
+    if not st.session_state['chat_history']:
+        st.markdown("""
+            <div class="question-box" id="question1">Was genau ist ein Belegarzt?</div>
+            <div class="question-box" id="question2">Wofür wird die Alpha-ID verwendet?</div>
+            <br>
+            <div class="question-box" id="question3">Was sind die Vorteile des ambulanten operierens?</div>
+            <div class="question-box" id="question4">AI Generated Question: {0}</div>
+        """.format(dynamic_question), unsafe_allow_html=True)
+
 def main():
     st.title("BinDocs Chat App")
 
@@ -102,17 +120,11 @@ def main():
         </style>
     """, unsafe_allow_html=True)
 
-    
-
     if "chat_history" not in st.session_state:
         st.session_state['chat_history'] = []
 
     display_chat_history(st.session_state['chat_history'])
 
-    st.write("<!-- Start Spacer -->", unsafe_allow_html=True)
-    st.write("<div style='flex: 1;'></div>", unsafe_allow_html=True)
-    st.write("<!-- End Spacer -->", unsafe_allow_html=True)
-
     new_messages_placeholder = st.empty()
 
     pdf = st.file_uploader("Upload your PDF", type="pdf")
@@ -134,37 +146,51 @@ def main():
             
             with get_openai_callback() as cb:
                 response = chain.run(input_documents=docs, question=query)
-            
+
             # Post-processing to remove incomplete sentences and redundant information
             filtered_response = remove_incomplete_sentences(response)
             filtered_response = remove_redundant_information(filtered_response)
             
-            # Check if the response ends with a sentence-ending punctuation
-            while not filtered_response.strip().endswith(('.', '!', '?')) and max_tokens < MAX_TOKEN_LIMIT:
-                max_tokens += 100  # Increase the max_tokens limit
-                chain = load_chatbot(max_tokens=max_tokens)
-                additional_response = chain.run(input_documents=docs, question=query)
-                filtered_response += additional_response  # Append the additional response to the filtered_response
+            # Dynamic question generation and display example questions
+            dynamic_question = generate_dynamic_question(chunks)
+            display_example_questions(dynamic_question)
 
             st.session_state['chat_history'].append(("Bot", filtered_response, "new"))
 
-            # Display new messages at the bottom
             new_messages = st.session_state['chat_history'][-2:]
             for chat in new_messages:
                 background_color = "#FFA07A" if chat[2] == "new" else "#acf" if chat[0] == "User" else "#caf"
                 new_messages_placeholder.markdown(f"<div style='background-color: {background_color}; padding: 10px; border-radius: 10px; margin: 10px;'>{chat[0]}: {chat[1]}</div>", unsafe_allow_html=True)
 
-            # Scroll to the latest response using JavaScript
             st.write("<script>document.getElementById('response').scrollIntoView();</script>", unsafe_allow_html=True)
 
             loading_message.empty()
 
-            # Clear the input field by setting the query variable to an empty string
             query = ""
 
-        # Mark all messages as old after displaying
         st.session_state['chat_history'] = [(sender, msg, "old") for sender, msg, _ in st.session_state['chat_history']]
+    
+    # JavaScript for handling question box clicks
+    st.markdown("""
+        <script>
+            document.getElementById('question1').onclick = function() {
+                document.querySelector('input').value = 'Was genau ist ein Belegarzt?';
+                document.querySelector('input').dispatchEvent(new Event('change'));
+            };
+            document.getElementById('question2').onclick = function() {
+                document.querySelector('input').value = 'Wofür wird die Alpha-ID verwendet?';
+                document.querySelector('input').dispatchEvent(new Event('change'));
+            };
+            document.getElementById('question3').onclick = function() {
+                document.querySelector('input').value = 'Was sind die Vorteile des ambulanten operierens?';
+                document.querySelector('input').dispatchEvent(new Event('change'));
+            };
+            document.getElementById('question4').onclick = function() {
+                document.querySelector('input').value = 'AI Generated Question: {0}';
+                document.querySelector('input').dispatchEvent(new Event('change'));
+            };
+        </script>
+    """.format(dynamic_question), unsafe_allow_html=True)
 
 if __name__ == "__main__":
     main()
-