app.py

import openai
import streamlit as st
import sqlite3
from PIL import Image
import time

openai.api_key = "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"

# Database Connection

conn = sqlite3.connect('bank.db')
c = conn.cursor()


def chatbot():
    st.title("Welcome to OneInsurance")

    policy_doc_link = "https://www.hdfcergo.com/docs/default-source/downloads/policy-wordings/health/arogya-sanjeevani---a5-size---pw---hehi.pdf"

    question_1 = "Do you want health insurance?"
    options_1 = ["Yes", "No"]

    st.write(question_1)
    selected_option_1 = st.selectbox("Please enter your option:", options_1)
    if selected_option_1 == "No":
        st.write("Thank you")
        image = Image.open('thankyou.png')
        st.image(image, caption='Please visit again!')
        return

    question_2 = "Select the Institution from where you want the Insurance"
    options_2 = ["Bank of Baroda", "State Bank of India(SBI)", "HDFC Bank", "LIC"]

    st.subheader(question_2)
    selected_option_2 = st.selectbox("Please enter your option:", options_2)



    c.execute('SELECT Policy_Name FROM BANK WHERE Bank_Name= "{}"'.format(selected_option_2))
    options_3 = c.fetchall()

        # st.write(options_3)
    my_options = []
    for row in options_3:
        my_options.append(row[0])

    st.subheader("Select the Policy Name")
    selected_option_3 = st.selectbox("Please enter your option:", my_options)
        
    c.execute('SELECT Policy_doc FROM BANK WHERE Policy_Name = "{}"'.format(selected_option_3))
    policy_doc_link = c.fetchone()

        # st.write(policy_doc_link)
    st.subheader("List of Questions")        
    question_list= """ 

            1. What is covered under the policy?
            2. What are the policy exclusions?
            3. What are the conditions to avail the benefits of the insurance policy?
            4. What is the policy deductible and how does it work?
            5. What is the policy's out-of-pocket maximum?
            6. What is the policy's co-pay amount?
            7. Is there a network of providers or can I see any doctor I choose?
            8. Are pre-existing conditions covered under the policy?
            9. What is the process for filing a claim?
            10. What is the policy's premium and how often is it due?
            11. How does the policy handle cost-sharing for prescription drugs?
            12. Are there any limits on the number of visits or treatments for a particular condition?
            13. Does the policy offer coverage for mental health services and rehabilitation? 
            """

    st.write(question_list)
    def switch_question(argument):
        switch = {
                    1: "What is covered under the policy?",
                    2: "What are the policy exclusions?",
                    3: "What are the conditions to avail the benefits of the insurance policy?",
                    4: "What is the policy deductible and how does it work?",
                    5: "What is the policy's out-of-pocket maximum?",
                    6: "What is the policy's co-pay amount?",
                    7: "Is there a network of providers or can I see any doctor I choose?",
                    8: "Are pre-existing conditions covered under the policy?",
                    9: "What is the process for filing a claim?",
                    10: "What is the policy's premium and how often is it due?",
                    11: "How does the policy handle cost-sharing for prescription drugs?",
                    12: "Are there any limits on the number of visits or treatments for a particular condition?",
                    13: "Does the policy offer coverage for mental health services and rehabilitation?"
            }
        return switch.get(argument, "Invalid Input")

    question_number = st.number_input("Please select a question number", min_value=1, max_value=13)
    selected_question = switch_question(question_number)
    response = "Sorry, I cannot answer that."

    if selected_question != "Invalid Input":
        response = openai.Completion.create(
                    model="text-davinci-003",
                    prompt="Read the following PDF Document\n\n{}\n\nAnswer the question based on the document provided\n{}".format(policy_doc_link, selected_question),
                    temperature=0,
                    max_tokens=250,
                    top_p=1,
                    frequency_penalty=0.5,
                    presence_penalty=0,
                    stop=["?"]
        )


        message = response.choices[0].text
        st.write(f"Answer: {message}")
    else:
        st.write(response)

    def fetch_data():
    # connect to the database
        conn1 = sqlite3.connect("life_insurer_data.db")

    # create a cursor
        cursor = conn1.cursor()

    # fetch the data from the database
        fetch_query = """
        SELECT * FROM life_insurer_data;
        """
        cursor.execute(fetch_query)
        data = cursor.fetchall()

    # close the connection to the database
        conn.close()

        return data

# display the data in a table
    st.title("Life Insurer Data")
    st.write("Data Scrapped from https://freefincal.com/irda-life-insurance-claim-settlement-ratio-2023/")
    st.write("Data fetched from SQLite database")

    life_insurers = [row[0] for row in fetch_data()]
    selected_life_insurer = st.selectbox("Select a life insurer", life_insurers)

    with st.spinner("Fetching data..."):
        time.sleep(2)
        for row in fetch_data():
            if row[0] == selected_life_insurer:
                st.write(f"Claim Settlement Ratio for {row[0]}: {row[1]}")

if __name__ == '__main__':
    chatbot()