app2.py

import os
import streamlit as st
import transformers
import torch
import time

# Ensure the Hugging Face API Token is set in the environment
hf_token = os.getenv("HUGGING_FACE_API_TOKEN")
if not hf_token:
    st.error("Hugging Face API token not found. Please set the HUGGING_FACE_API_TOKEN environment variable.")
    st.stop()

# Initialize the model and tokenizer using Hugging Face pipeline
model_id = "meta-llama/Meta-Llama-3.1-8B-Instruct"
pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
    use_auth_token=hf_token
)

def generate_response(prompt):
    messages = [
        {"role": "user", "content": prompt}
    ]
    # Generate a response using the pipeline
    response = pipeline(messages, max_new_tokens=256)
    return response[0]["generated_text"]

def response_generator(content):
    words = content.split()
    for word in words:
        yield word + " "
        time.sleep(0.1)

def show_messages():
    for msg in st.session_state.messages:
        role = msg["role"]
        with st.chat_message(role):
            st.write(msg["content"])

def save_chat():
    if not os.path.exists('./Intermediate-Chats'):
        os.makedirs('./Intermediate-Chats')
    if st.session_state['messages']:
        formatted_messages = '\n'.join(f"{msg['role']}: {msg['content']}" for msg in st.session_state['messages'])
        filename = f'./Intermediate-Chats/chat_{int(time.time())}.txt'
        with open(filename, 'w') as f:
            for message in st.session_state['messages']:
                encoded_content = message['content'].replace('\n', '\\n')
                f.write(f"{message['role']}: {encoded_content}\n")
        st.session_state['messages'].clear()
    else:
        st.warning("No chat messages to save.")

def load_saved_chats():
    chat_dir = './Intermediate-Chats'
    if os.path.exists(chat_dir):
        files = os.listdir(chat_dir)
        files.sort(key=lambda x: os.path.getmtime(os.path.join(chat_dir, x)), reverse=True)
        for file_name in files:
            display_name = file_name[:-4] if file_name.endswith('.txt') else file_name
            if st.sidebar.button(display_name):
                st.session_state['show_chats'] = False
                st.session_state['is_loaded'] = True
                load_chat(os.path.join(chat_dir, file_name))

def load_chat(file_path):
    st.session_state['messages'].clear()
    with open(file_path, 'r') as file:
        for line in file.readlines():
            role, content = line.strip().split(': ', 1)
            decoded_content = content.replace('\\n', '\n')
            st.session_state['messages'].append({'role': role, 'content': decoded_content})

def main():
    st.title("LLaMA Chat Interface")

    if 'messages' not in st.session_state:
        st.session_state['messages'] = []
    if 'show_chats' not in st.session_state:
        st.session_state['show_chats'] = False

    show_messages()

    user_input = st.chat_input("Enter your prompt:")
    if user_input:
        st.session_state.messages.append({"role": "user", "content": user_input})
        response = generate_response(user_input)
        st.session_state.messages.append({"role": "assistant", "content": response})

        with st.chat_message("assistant"):
            for word in response_generator(response):
                st.write(word, end="")

    chat_log = '\n'.join(f"{msg['role']}: {msg['content']}" for msg in st.session_state['messages'])
    st.sidebar.download_button(
        label="Download Chat Log",
        data=chat_log,
        file_name="chat_log.txt",
        mime="text/plain"
    )

    if st.sidebar.button("Save Chat"):
        save_chat()

    if st.sidebar.button("New Chat"):
        st.session_state['messages'].clear()

    if st.sidebar.checkbox("Show/hide chat history", value=st.session_state['show_chats']):
        st.sidebar.title("Previous Chats")
        load_saved_chats()

if __name__ == "__main__":
    main()