File size: 1,653 Bytes
fd7b88e e4b011f fd7b88e 1ced004 fd7b88e 1ced004 fd7b88e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 |
import requests
import streamlit as st
import time
st.title("Rasa Chatbot Interface")
# 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 user_input := st.chat_input("What is up?"):
# Add user message to chat history
st.session_state.messages.append({"role": "user", "content": user_input})
# Display user message in chat message container
with st.chat_message("user"):
st.markdown(user_input)
# Send user input to Rasa webhook
payload = {"sender": "user", "message": user_input}
response = requests.post('https://omdenalc-omdena-ng-lagos-chatbot-model.hf.space/webhooks/rest/webhook', json=payload)
bot_reply = response.json()
# Extract assistant response
assistant_response = bot_reply[0]["text"]
# Display assistant response in chat message container
with st.chat_message("assistant"):
message_placeholder = st.empty()
full_response = ""
# Simulate stream of response with milliseconds delay
for chunk in assistant_response.split():
full_response += chunk + " "
time.sleep(0.05)
# Add a blinking cursor to simulate typing
message_placeholder.markdown(full_response + "▌")
message_placeholder.markdown(full_response)
# Add assistant response to chat history
st.session_state.messages.append({"role": "assistant", "content": full_response}) |