Update app.py

app.py

@@ -47,7 +47,6 @@ def read_docx(file):
 
 @st.cache_resource(show_spinner=False)
 def load_data(uploaded_files):
-    # Create the LLM instance outside the cache
     llm = OpenAI(model="gpt-3.5-turbo", temperature=0.5,
                  system_prompt="You are an expert on the Streamlit Python library and your job is to answer technical questions. Assume that all questions are related to the Streamlit Python library. Keep your answers technical and based on facts – do not hallucinate features.")
     
@@ -66,13 +65,21 @@ def load_data(uploaded_files):
 
 # Function to save the conversation
 def save_conversation():
+    conversations = load_conversations()  # Load existing conversations
+    conversation_count = len(conversations) + 1  # Determine the next conversation number
+    
     with open("conversations.json", "a") as f:
         conversation_data = {
             "messages": st.session_state.messages,
             "file_names": st.session_state.uploaded_file_names
         }
-        if isinstance(conversation_data, dict):
-            json.dump(conversation_data, f)
+        # Prepend conversation number to the saved data
+        conversation_with_number = {
+            "conversation_number": conversation_count,
+            **conversation_data
+        }
+        if isinstance(conversation_with_number, dict):
+            json.dump(conversation_with_number, f)
             f.write("\n")
 
 # Function to load previous conversations
@@ -80,17 +87,13 @@ def load_conversations():
     if os.path.exists("conversations.json"):
         with open("conversations.json", "r") as f:
             conversations = [json.loads(line) for line in f]
-        # Ensure each conversation is a dictionary
-        for conv in conversations:
-            if not isinstance(conv, dict):
-                print("Warning: Loaded conversation is not a dictionary:", conv)
         return conversations
     return []
 
 # Function to delete selected conversations
-def delete_selected_conversations(selected_indices):
+def delete_selected_conversations(selected_conversation_numbers):
     conversations = load_conversations()
-    remaining_conversations = [conv for i, conv in enumerate(conversations) if i not in selected_indices]
+    remaining_conversations = [conv for conv in conversations if conv.get('conversation_number') not in selected_conversation_numbers]
     with open("conversations.json", "w") as f:
         for conv in remaining_conversations:
             json.dump(conv, f)
@@ -158,15 +161,16 @@ if st.session_state.show_conversations:
 
     if conversations:
         selected_indices = []
-        for i, conv in enumerate(conversations):
+        for conv in conversations:
             if isinstance(conv, dict):  # Ensure conv is a dictionary
-                st.sidebar.write(f"Conversation {i + 1}:")
+                conv_number = conv.get('conversation_number', 'Unknown')
+                st.sidebar.write(f"Conversation {conv_number}:")
                 for message in conv.get('messages', []):  # Use get safely
                     st.sidebar.write(f"{message['role']}: {message['content']}")
                 st.sidebar.write(f"Files: {', '.join(conv.get('file_names', []))}")
                 # Checkbox for selecting conversation to delete
-                if st.sidebar.checkbox(f"Select Conversation {i + 1} for Deletion", key=f"delete_checkbox_{i}"):
-                    selected_indices.append(i)
+                if st.sidebar.checkbox(f"Select Conversation {conv_number} for Deletion", key=f"delete_checkbox_{conv_number}"):
+                    selected_indices.append(conv_number)
             else:
                 print("Warning: Encountered a non-dictionary conversation:", conv)