app updated

app.py

@@ -95,19 +95,6 @@ with st.sidebar:
             with open("config.yaml", "w") as file:
                 yaml.dump(config, file, default_flow_style=False)
 
-    # Credit: Time
-    def current_year():
-        now = datetime.now()
-        return now.year
-
-    # Credit:
-    current_year = current_year()  # This will print the current year
-    st.markdown(
-        f"""
-            <h6 style='text-align: left;'>Copyright © 2010-{current_year} Present Yiqiao Yin</h6>
-        """,
-        unsafe_allow_html=True,
-    )
 
 # Main
 if st.session_state["authentication_status"]:
@@ -142,3 +129,19 @@ if st.session_state["authentication_status"]:
                 st.error("Username/password is incorrect")
             elif st.session_state["authentication_status"] is None:
                 st.warning("Please enter your username and password")
+
+
+with st.sidebar:
+    # Credit: Time
+    def current_year():
+        now = datetime.now()
+        return now.year
+
+    # Credit:
+    current_year = current_year()  # This will print the current year
+    st.markdown(
+        f"""
+            <h6 style='text-align: left;'>Copyright © 2010-{current_year} Present Yiqiao Yin</h6>
+        """,
+        unsafe_allow_html=True,
+    )

utils/frontend/helper.py

@@ -1,17 +1,18 @@
-import streamlit as st
 import os
+
+import streamlit as st
 from together import Together
 
 from utils.frontend.utils.helper import *
 
-def main_chatbot_page():
 
+def main_chatbot_page():
     st.title("Meta Llama3 🦙")
 
-
     with st.sidebar:
         with st.expander("Instruction Manual"):
-            st.markdown("""
+            st.markdown(
+                """
                 ## Meta Llama3 🦙 Chatbot
 
                 This Streamlit app allows you to chat with Meta's Llama3 model.
@@ -25,36 +26,42 @@ def main_chatbot_page():
                 - **Developer**: [Yiqiao Yin](https://www.y-yin.io/) | [App URL](https://huggingface.co/spaces/eagle0504/meta-llama) | [LinkedIn](https://www.linkedin.com/in/yiqiaoyin/) | [YouTube](https://youtube.com/YiqiaoYin/)
 
                 Enjoy chatting with Meta's Llama3 model!
-            """)
+            """
+            )
 
         # Add a button to clear the session state
         if st.button("Clear Session"):
             st.session_state.messages = []
             st.experimental_rerun()
 
-
     # Initialize chat history
     if "messages" not in st.session_state:
         st.session_state.messages = []
 
-
     # Display chat messages from history on app rerun
     for message in st.session_state.messages:
         with st.chat_message(message["role"]):
             st.markdown(message["content"])
 
+    # Define the prompt as a user message
+    input_prompt_object = [{"role": "user", "content": "You are a helpful assistant."}]
 
     # React to user input
     if prompt := st.chat_input("What is up?"):
+        # Define the prompt as a user message
+        input_prompt_object.append({"role": "user", "content": prompt})
+
         # Display user message in chat message container
         st.chat_message("user").markdown(prompt)
         # Add user message to chat history
         st.session_state.messages.append({"role": "user", "content": prompt})
 
-        response = call_llama(prompt)
+        # Call Llama3 model to generate response
+        response = call_llama(input_prompt_object)
+        input_prompt_object.append({"role": "assistant", "content": response})
 
         # Display assistant response in chat message container
         with st.chat_message("assistant"):
             st.markdown(response)
         # Add assistant response to chat history
-        st.session_state.messages.append({"role": "assistant", "content": response})
+        st.session_state.messages.append({"role": "assistant", "content": response})

utils/frontend/utils/helper.py

@@ -1,34 +1,27 @@
-import streamlit as st
 import os
-from together import Together
 
+import streamlit as st
+from together import Together
 
 client = Together(api_key=os.environ["TOGETHER_API_KEY"])
 
 
-def call_llama(prompt: str) -> str:
+def call_llama(prompt_object: list[dict]) -> str:
     """
-        Send a prompt to the Llama model and return the response.
-        Args:
-            prompt (str): The input prompt to send to the Llama model.
-        Returns:
-            str: The response from the Llama model.
+    Send a prompt to the Llama model and return the response.
+    Args:
+        prompt (str): The input prompt to send to the Llama model.
+    Returns:
+        str: The response from the Llama model.
     """
 
     # Create a completion request with the prompt
     response = client.chat.completions.create(
-
         # Use the Llama-3-8b-chat-hf model
         model="meta-llama/Llama-3-8b-chat-hf",
-
         # Define the prompt as a user message
-        messages=[
-            {
-                "role": "user",
-                "content": prompt  # Use the input prompt
-            }
-        ],
+        messages=prompt_object,
     )
 
     # Return the content of the first response message
-    return response.choices[0].message.content
+    return response.choices[0].message.content