""" Simple Chatbot @author: Nigel Gebodh @email: nigel.gebodh@gmail.com """ import numpy as np import streamlit as st from openai import OpenAI import os from dotenv import load_dotenv load_dotenv() # Initialize the client client = OpenAI( base_url="https://api-inference.huggingface.co/v1", api_key=os.environ.get('HUGGINGFACEHUB_API_TOKEN') # Replace with your token ) # Define Llama 3 model model_link = "meta-llama/Meta-Llama-3-8B-Instruct" model_info = { 'description': """The Llama (3) model is a **Large Language Model (LLM)** that's able to have question and answer interactions.\n It was created by the [**Meta's AI**](https://llama.meta.com/) team and has over **8 billion parameters.** \n""", 'logo': 'Llama_logo.png' } # Random dog images for error message random_dog = ["0f476473-2d8b-415e-b944-483768418a95.jpg", "1bd75c81-f1d7-4e55-9310-a27595fa8762.jpg", "526590d2-8817-4ff0-8c62-fdcba5306d02.jpg", "1326984c-39b0-492c-a773-f120d747a7e2.jpg"] def reset_conversation(): '''Resets Conversation''' st.session_state.conversation = [] st.session_state.messages = [] return None # Create a temperature slider temp_values = st.sidebar.slider('Select a temperature value', 0.0, 1.0, (0.5)) # Add reset button to clear conversation st.sidebar.button('Reset Chat', on_click=reset_conversation) # Reset button # Create model description st.sidebar.write(f"You're now chatting with **Llama 3**") st.sidebar.markdown(model_info['description']) st.sidebar.image(model_info['logo']) st.sidebar.markdown("*Generated content may be inaccurate or false.*") st.sidebar.markdown("\nRun into issues? \nTry again later as GPU access might be limited.") # 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"]) # Accept user input if prompt := st.chat_input(f"Hi, I'm Llama 3, ask me a question"): # Display user message in chat message container with st.chat_message("user"): st.markdown(prompt) # Add user message to chat history st.session_state.messages.append({"role": "user", "content": prompt}) # Display assistant response in chat message container with st.chat_message("assistant"): try: stream = client.chat.completions.create( model=model_link, messages=[ {"role": m["role"], "content": m["content"]} for m in st.session_state.messages ], temperature=temp_values, stream=True, max_tokens=3000, ) response = st.write_stream(stream) except Exception as e: response = "😵‍💫 Looks like something went wrong! Try again later.\nHere's a random pic of a 🐶:" st.write(response) random_dog_pick = 'https://random.dog/' + random_dog[np.random.randint(len(random_dog))] st.image(random_dog_pick) st.write("This was the error message:") st.write(e) st.session_state.messages.append({"role": "assistant", "content": response})