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import requests | |
import streamlit as st | |
import random | |
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://pvanand-rasa-moodbot.hf.space/webhooks/rest/webhook', json=payload) | |
bot_reply = response.json() | |
# Display assistant response in chat message container | |
with st.chat_message("assistant"): | |
message_placeholder = st.empty() | |
full_response = "" | |
assistant_response = random.choice(bot_reply)["text"] | |
# 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 + "β") | |
message_placeholder.markdown(full_response) | |
# Add assistant response to chat history | |
st.session_state.messages.append({"role": "assistant", "content": full_response}) |