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import streamlit as st
from langchain_google_genai import ChatGoogleGenerativeAI
from dotenv import load_dotenv
import os
# Load environment variables
load_dotenv()
# Initialize the language model
llm = ChatGoogleGenerativeAI(model="gemini-1.5-pro",
temperature=0.6,
google_api_key=os.getenv("GOOGLE_API_KEY"))
# Set Streamlit page configuration
st.set_page_config(page_title="Q&A Chatbot", page_icon="🤖", layout="centered", initial_sidebar_state="auto")
# Main application interface
st.header("Quest Bot")
# Function to handle user input and model response
def chat(input_question):
try:
# Get response from the model
with st.spinner("getting response..."):
response = llm.invoke(input_question)
return response.content
except ValueError as ve:
st.error(f"ValueError: {str(ve)}")
except Exception as e:
st.error(f"Error: {str(e)}")
return None
# Initialize conversation history
conversation = []
# User input for the question
input_question = st.text_input("Input your question here: ")
# Button to submit the question
if st.button("Ask"):
if input_question:
st.spinner("getting response...")
# Add user input to conversation history
conversation.append(f"You: {input_question}")
# Get response from the model
response = chat(input_question)
if response:
# Add model response to conversation history
conversation.append(f"Quest Bot: {response}")
# Display conversation history
st.subheader("Conversation")
for message in conversation:
st.write(message)
else:
# Show a warning if no question is input
st.warning("Please input a question.")
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