app.py

import streamlit as st
from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
from threading import Thread

# Model Initialization
model_id = "rasyosef/Llama-3.2-180M-Amharic-Instruct"

st.title("Llama 3.2 180M Amharic Chatbot Demo")
st.write("""
This chatbot was created using [Llama-3.2-180M-Amharic-Instruct](https://huggingface.co/rasyosef/Llama-3.2-180M-Amharic-Instruct), 
a finetuned version of the 180 million parameter Llama 3.2 Amharic transformer model.
""")

# Load the tokenizer and model
@st.cache_resource
def load_model():
    tokenizer = AutoTokenizer.from_pretrained(model_id)
    model = AutoModelForCausalLM.from_pretrained(model_id)
    llama_pipeline = pipeline(
        "text-generation",
        model=model,
        tokenizer=tokenizer,
        pad_token_id=tokenizer.pad_token_id,
        eos_token_id=tokenizer.eos_token_id
    )
    return tokenizer, llama_pipeline

tokenizer, llama_pipeline = load_model()

# Generate text
def generate_response(prompt, max_new_tokens):
    response = llama_pipeline(
        prompt,
        max_new_tokens=max_new_tokens,
        repetition_penalty=1.15
    )
    return response[0]['generated_text']

# Sidebar: Configuration
st.sidebar.header("Chatbot Configuration")
max_tokens = st.sidebar.slider("Maximum new tokens", min_value=8, max_value=256, value=64, help="Larger values result in longer responses.")

# Examples
examples = [
    "ሰላም፣ እንዴት ነህ?",
    "የኢትዮጵያ ዋና ከተማ ስም ምንድን ነው?",
    "የኢትዮጵያ የመጨረሻው ንጉስ ማን ነበሩ?",
    "የአማርኛ ግጥም ፃፍልኝ",
    "ተረት ንገረኝ\n\nጅብና አንበሳ",
    "አንድ አስቂኝ ቀልድ ንገረኝ",
    "የፈረንሳይ ዋና ከተማ ስም ምንድን ነው?",
    "አሁን የአሜሪካ ፕሬዚዳንት ማን ነው?",
]

st.subheader("Chat with the Amharic Chatbot")
if "chat_history" not in st.session_state:
    st.session_state.chat_history = []

# Example selector
example = st.selectbox("Choose an example:", ["Type your own message"] + examples)

# User Input
user_input = st.text_input("Your message:", value=example if example != "Type your own message" else "", placeholder="Type your message here...")

if st.button("Send"):
    if user_input:
        # Generate response
        with st.spinner("Generating response..."):
            response = generate_response(user_input, max_tokens)
            st.session_state.chat_history.append((user_input, response))

# Display Chat History
st.write("### Chat History")
for i, (user_msg, bot_response) in enumerate(st.session_state.chat_history):
    st.write(f"**User {i+1}:** {user_msg}")
    st.write(f"**Bot:** {bot_response}")