Update app.py

app.py

@@ -1,64 +1,35 @@
-import streamlit as st
+import gradio as gr
 import os
 import shelve
 from g4f.client import Client
 
-
-st.title("Streamlit Chatbot Interface")
-
 USER_AVATAR = "👤"
 BOT_AVATAR = "🤖"
 client = Client()
 
-# Ensure openai_model is initialized in session state
-if "openai_model" not in st.session_state:
-    st.session_state["openai_model"] = "gpt-3.5-turbo"
-
-
-# Load chat history from shelve file
+# Initialize chat history
 def load_chat_history():
     with shelve.open("chat_history") as db:
         return db.get("messages", [])
 
-
-# Save chat history to shelve file
 def save_chat_history(messages):
     with shelve.open("chat_history") as db:
         db["messages"] = messages
 
+chat_history = load_chat_history()
 
-# Initialize or load chat history
-if "messages" not in st.session_state:
-    st.session_state.messages = load_chat_history()
-
-# Sidebar with a button to delete chat history
-with st.sidebar:
-    if st.button("Delete Chat History"):
-        st.session_state.messages = []
-        save_chat_history([])
-
-# Display chat messages
-for message in st.session_state.messages:
-    avatar = USER_AVATAR if message["role"] == "user" else BOT_AVATAR
-    with st.chat_message(message["role"], avatar=avatar):
-        st.markdown(message["content"])
-
-# Main chat interface
-if prompt := st.chat_input("How can I help?"):
-    st.session_state.messages.append({"role": "user", "content": prompt})
-    with st.chat_message("user", avatar=USER_AVATAR):
-        st.markdown(prompt)
-
-    with st.chat_message("assistant", avatar=BOT_AVATAR):
-        message_placeholder = st.empty()
-        full_response = ""
+def chatbot_interface(user_input):
+    global chat_history
+    if user_input:
+        chat_history.append({"role": "user", "content": user_input})
         response = client.chat.completions.create(
             model="gpt-3.5-turbo",
-            messages=st.session_state["messages"],
+            messages=chat_history,
         )
-        full_response = response.choices[0].message.content
-        message_placeholder.markdown(full_response)
-    st.session_state.messages.append({"role": "assistant", "content": full_response})
+        bot_response = response.choices[0].message.content
+        chat_history.append({"role": "assistant", "content": bot_response})
+        save_chat_history(chat_history)
+        return bot_response
 
-# Save chat history after each interaction
-save_chat_history(st.session_state.messages)
+iface = gr.Interface(fn=chatbot_interface, inputs="text", outputs="text", title="Gradio Chatbot Interface")
+iface.launch()