the app

app.py

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+from openai import OpenAI
+import streamlit as st
+import os
+import sys
+from dotenv import load_dotenv, dotenv_values
+load_dotenv()
+
+
+# initialize the client
+client = OpenAI(
+  base_url="https://api-inference.huggingface.co/v1",
+  api_key=os.environ.get('HUGGINGFACEHUB_API_TOKEN')  #"hf_xxx" # Replace with your token
+) 
+
+
+st.title("💬 Chatbot")
+st.caption("🚀 A streamlit chatbot powered by Google Gemma")
+
+# Initialize chat history
+if 'messages' not in st.session_state:
+    st.session_state['messages'] = [] #[{"role": "assistant", "content": "How can I help you?"}]
+
+# Display chat messages from history on app rerun
+for messasge in st.session_state.messages:
+    st.chat_message(messasge["role"]).write(messasge["content"])
+
+# React to user input
+if prompt := st.chat_input():
+    
+     # Display user message in chat message container
+    st.chat_message("user").write(prompt)
+    # Add user message to chat history
+    st.session_state.messages.append({"role": "user", "content": prompt})
+
+    ##Get response to the message using client
+    response = client.chat.completions.create(model="google/gemma-2b-it", messages=st.session_state.messages)
+
+    msg = response.choices[0].message.content
+    
+     # Display assistant response in chat message container
+    st.chat_message("assistant").write(msg)
+
+    # Add assistant response to chat history
+    st.session_state.messages.append({"role": "assistant", "content": msg})