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import streamlit as st
import os
from together import Together
from utils.helper import *
st.set_page_config(layout="wide")
st.title("Meta Llama3 🦙")
with st.sidebar:
with st.expander("Instruction Manual"):
st.markdown("""
## Meta Llama3 🦙 Chatbot
This Streamlit app allows you to chat with Meta's Llama3 model.
### How to Use:
1. **Input**: Type your prompt into the chat input box labeled "What is up?".
2. **Response**: The app will display a response from Llama3.
3. **Chat History**: Previous conversations will be shown on the app.
### Credits:
- **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!
""")
# Example:
st.success("Example: Explain what is supervised learning.")
st.success("Example: What is large language model?")
st.success("Example: How to conduct an AI experiment?")
st.success("Example: Write a tensorflow flow code with a 3-layer neural network 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"])
# React to user input
if prompt := st.chat_input("😉 Ask any question or feel free to use the examples provided in the left sidebar."):
# 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})
# API Call
response = call_llama(prompt)
# 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})
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