Delete app.py

app.py

@@ -1,39 +0,0 @@
-import streamlit as st
-from transformers import pipeline
-
-# Choose an appropriate Hugging Face model for your chat application (replace with your desired model)
-model_name = "facebook/bart-base"
-
-# Initialize the conversational AI pipeline
-chat_pipeline = pipeline("conversational", model=model_name)
-
-# Initialize session state to store chat history
-if "chat_history" not in st.session_state:
-    st.session_state["chat_history"] = []
-
-def display_chat_history():
-    """Displays the chat history in the Streamlit app."""
-    for message in st.session_state["chat_history"]:
-        st.write(f"{message['user']}: {message['text']}")
-
-def process_user_input(user_input):
-    """Processes user input using the conversational AI model and updates chat history."""
-    if user_input:
-        bot_response = chat_pipeline(user_input, max_length=1000)[0]["generated_text"]
-        st.session_state["chat_history"].append({"user": "You", "text": user_input})
-        st.session_state["chat_history"].append({"user": "Bot", "text": bot_response})
-
-st.title("Streamlit Chat App with Hugging Face Model")
-
-# Display chat history
-display_chat_history()
-
-# User input using st.chat_input
-user_input = st.chat_input("Type your message here...", key="user_input")
-
-# Process user input on Enter key press
-if st.session_state.get("user_input", "") != user_input:
-    process_user_input(user_input)
-    st.session_state["user_input"] = ""  # Clear input field
-
-st.write("**Note:** This is a simple demonstration. For more advanced features, consider using a dedicated chatbot framework.")