Update app.py

app.py

@@ -1,7 +1,6 @@
 import streamlit as st
 from huggingface_hub import InferenceClient
 import os
-import sys
 import pickle
 
 st.title("CODEFUSSION ☄")
@@ -52,7 +51,7 @@ def reset_conversation():
     '''
     st.session_state.conversation = []
     st.session_state.messages = []
-    save_conversation_history([])  
+    save_conversation_history([])  # Clear the conversation history file
     return None
 
 def load_conversation_history():
@@ -69,6 +68,14 @@ def save_conversation_history(conversation_history):
     with open(history_file, "wb") as f:
         pickle.dump(conversation_history, f)
 
+# Ensure session state is initialized
+if "conversation" not in st.session_state:
+    st.session_state.conversation = []
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+if "prev_option" not in st.session_state:
+    st.session_state.prev_option = None
+
 models = [key for key in model_links.keys()]
 selected_model = st.sidebar.selectbox("Select Model", models)
 temp_values = st.sidebar.slider('Select a temperature value', 0.0, 1.0, (0.5))
@@ -80,23 +87,16 @@ st.sidebar.image(model_info[selected_model]['logo'])
 
 st.sidebar.markdown("\*Generating the code might go slow if you are using low power resources \*")
 
-if "prev_option" not in st.session_state:
-    st.session_state.prev_option = selected_model
-
 if st.session_state.prev_option != selected_model:
     st.session_state.messages = []
     st.session_state.prev_option = selected_model
 
-if "conversation" not in st.session_state:
-    st.session_state.conversation = []
-
-reset_conversation()
-
 repo_id = model_links[selected_model]
 st.subheader(f'{selected_model}')
 
 # Load the conversation history from the file
-st.session_state.messages = load_conversation_history()
+if not st.session_state.messages:
+    st.session_state.messages = load_conversation_history()
 
 for message in st.session_state.messages:
     with st.chat_message(message["role"]):
@@ -107,7 +107,6 @@ if prompt := st.chat_input(f"Hi I'm {selected_model}, How can I help you today?"
     with st.chat_message("user"):
         st.markdown(prompt)
     
-    
     st.session_state.messages.append({"role": "user", "content": prompt})
     conversation_history = [(message["role"], message["content"]) for message in st.session_state.messages]