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# For reading credentials from the .env file
import os
from dotenv import load_dotenv
import streamlit as st
import webchat
# URL of the hosted LLMs is hardcoded because at this time all LLMs share the same endpoint
url = "https://us-south.ml.cloud.ibm.com"
# These global variables will be updated in get_credentials() function
watsonx_project_id = ""
# Replace with your IBM Cloud key
api_key = ""
def get_credentials():
load_dotenv()
# Update the global variables that will be used for authentication in another function
globals()["api_key"] = os.getenv("api_key", None)
globals()["watsonx_project_id"] = os.getenv("project_id", None)
def main():
# Get the API key and project id and update global variables
get_credentials()
# Use the full page instead of a narrow central column
st.set_page_config(layout="wide")
# Streamlit app title
st.title("🌠Demo of RAG with a Web page")
user_url = st.text_input('Provide a URL')
collection_name = st.text_input('Provide a unique name for this website (lower case). Use the same name for the same URL to avoid loading data multiple times.')
# UI component to enter the question
question = st.text_area('Question',height=100)
button_clicked = st.button("Answer the question")
st.subheader("Response")
# Invoke the LLM when the button is clicked
if button_clicked:
response = webchat.answer_questions_from_web(api_key,watsonx_project_id,user_url,question,collection_name)
st.write(response)
if __name__ == "__main__":
main()
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