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import streamlit as st
from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
# Configure the Hugging Face API key (no need to pass it in the pipeline call)
HF_API_KEY = st.secrets['huggingface_api_key']
# Ensure you're logged in using the Hugging Face CLI if using private models
# huggingface-cli login
# Initialize the Hugging Face model and tokenizer
model_name = 'gpt2-medium' # or another GPT-2 version you want to use
model = AutoModelForCausalLM.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)
# Initialize the text generation pipeline
generator = pipeline('text-generation', model=model, tokenizer=tokenizer)
# Function to get response from the Hugging Face model
def get_chatbot_response(user_input):
try:
# Generate the response using the Hugging Face model
response = generator(user_input, max_length=100, num_return_sequences=1)
return response[0]['generated_text']
except Exception as e:
return f"Error: {str(e)}"
# Streamlit interface
st.set_page_config(page_title="Smart ChatBot", layout="centered")
# Custom CSS for chat bubbles with full width and emojis
st.markdown("""
<style>
.chat-container {
display: flex;
flex-direction: column;
width: 100%;
}
.chat-bubble {
width: 100%;
padding: 15px;
margin: 10px 0;
border-radius: 10px;
font-size: 18px;
color: white;
display: inline-block;
line-height: 1.5;
}
.user-bubble {
background: #6a82fb; /* Soft blue */
align-self: flex-end;
border-radius: 10px 10px 10px 10px;
}
.bot-bubble {
background: #fc5c7d; /* Soft pink */
align-self: flex-start;
border-radius: 10px 10px 10px 10px;
}
.chat-header {
font-size: 35px;
font-weight: bold;
margin-bottom: 20px;
color: #3d3d3d;
}
.emoji {
font-size: 22px;
margin-right: 10px;
}
</style>
""", unsafe_allow_html=True)
# Chat header and intro
st.markdown('<div class="chat-header">AI Chatbot - Your Companion 💻</div>', unsafe_allow_html=True)
st.write("Powered by Hugging Face AI for smart, engaging conversations. 🤖")
# Initialize session state for conversation history if not already initialized
if "history" not in st.session_state:
st.session_state["history"] = []
# Create the chat form
with st.form(key="chat_form", clear_on_submit=True):
user_input = st.text_input("Your message here... ✍️", max_chars=2000, label_visibility="collapsed")
submit_button = st.form_submit_button("Send 🚀")
if submit_button:
if user_input:
# Get response from the chatbot
response = get_chatbot_response(user_input)
# Store user input and bot response in session state history
st.session_state.history.append((user_input, response))
else:
st.warning("Please Enter A Prompt 😅")
# Display chat history
if st.session_state["history"]:
st.markdown('<div class="chat-container">', unsafe_allow_html=True)
for user_input, response in st.session_state["history"]:
st.markdown(f'<div class="chat-bubble user-bubble"><span class="emoji">👤</span>You: {user_input}</div>', unsafe_allow_html=True)
st.markdown(f'<div class="chat-bubble bot-bubble"><span class="emoji">🤖</span>Bot: {response}</div>', unsafe_allow_html=True)
st.markdown('</div>', unsafe_allow_html=True)
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