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| from dotenv import load_dotenv | |
| import streamlit as st | |
| import os | |
| import google.generativeai as genai | |
| # Load the environment variables | |
| load_dotenv() | |
| # Configure the API key | |
| genai.configure(api_key=os.getenv("Google_api_key")) | |
| # Initialize the model | |
| model = genai.GenerativeModel('gemini-pro') | |
| # Function to load gemini model and response | |
| def load_gemini_model(question): | |
| response = model.generate_content(question) | |
| return response.text | |
| # Set up the Streamlit application | |
| st.set_page_config(page_title="Question Answering Bot with Gemini model", page_icon="π€", layout="centered", initial_sidebar_state="auto") | |
| # Set the header as Gemini pro application | |
| st.header("Gemini pro application") | |
| # Initialize the chat history | |
| chat_history = [] | |
| # Set the input field | |
| input = st.text_input("input:", key="input") | |
| submit = st.button("ASK a QUESTION") | |
| # When the submit button is clicked | |
| if submit: | |
| response = load_gemini_model(input) | |
| # Append the question and answer to the chat history | |
| chat_history.append({"user": input, "bot": response}) | |
| # Display the chat history | |
| for chat in chat_history: | |
| st.subheader("User:") | |
| st.write(chat["user"]) | |
| st.subheader("Bot:") | |
| st.write(chat["bot"]) |