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chui / app.py

Update app.py

b4eed25 about 3 years ago

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import streamlit as st
import random
import time
from transformers import GPT2LMHeadModel, GPT2Tokenizer

st.title("Simple chat with Hugging Face")

# Initialize chat history
if "messages" not in st.session_state:
    st.session_state.messages = []

# Load pre-trained model and tokenizer
model = GPT2LMHeadModel.from_pretrained("gpt2")
tokenizer = GPT2Tokenizer.from_pretrained("gpt2")

# 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("What is up?"):
    # 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})
    
    # Encode the new user input and add end of sentence token
    inputs = tokenizer.encode(prompt + tokenizer.eos_token, return_tensors="pt")
    
    # Generate a response
    outputs = model.generate(inputs, max_length=50, num_return_sequences=1, pad_token_id=tokenizer.eos_token_id)
    
    # Decode the response
    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
    
    # Display the response in the chat
    with st.chat_message("bot"):
        st.markdown(response)
    # Add bot message to chat history
    st.session_state.messages.append({"role": "bot", "content": response})

	import streamlit as st
	import random
	import time
	from transformers import GPT2LMHeadModel, GPT2Tokenizer

	st.title("Simple chat with Hugging Face")

	# Initialize chat history
	if "messages" not in st.session_state:
	st.session_state.messages = []

	# Load pre-trained model and tokenizer
	model = GPT2LMHeadModel.from_pretrained("gpt2")
	tokenizer = GPT2Tokenizer.from_pretrained("gpt2")

	# 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("What is up?"):
	# 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})

	# Encode the new user input and add end of sentence token
	inputs = tokenizer.encode(prompt + tokenizer.eos_token, return_tensors="pt")

	# Generate a response
	outputs = model.generate(inputs, max_length=50, num_return_sequences=1, pad_token_id=tokenizer.eos_token_id)

	# Decode the response
	response = tokenizer.decode(outputs[0], skip_special_tokens=True)

	# Display the response in the chat
	with st.chat_message("bot"):
	st.markdown(response)
	# Add bot message to chat history
	st.session_state.messages.append({"role": "bot", "content": response})