Create temp.py

temp.py

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+import streamlit as st
+from transformers import pipeline
+
+
+# Load the conversational model from Hugging Face
+# chatbot = pipeline('text-generation', model='shaneperry0101/Health-Llama-3.2-1B')
+chatbot = pipeline('text-generation', model='microsoft/DialoGPT-medium')
+
+# Initialize session state for storing the conversation
+if 'conversation' not in st.session_state:
+    st.session_state.conversation = []
+
+# Streamlit app layout
+st.title("Chatbot Application")
+user_input = st.text_input("You:", key="input")
+
+if st.button("Send"):
+    if user_input:
+        # Append user input to the conversation
+        st.session_state.conversation.append({"role": "user", "content": user_input})
+
+        # Generate response
+        response = chatbot(user_input)
+        bot_response = response[0]['generated_text']
+
+        # Append bot response to the conversation
+        st.session_state.conversation.append({"role": "bot", "content": bot_response})
+
+# Display the conversation
+for message in st.session_state.conversation:
+    if message["role"] == "user":
+        st.text_area("You:", value=message["content"], key=f"user_{message['content']}", height=50)
+    else:
+        st.text_area("Bot:", value=message["content"], key=f"bot_{message['content']}", height=50)