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op.py

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+import streamlit as st
+import yfinance as yf
+import requests
+import json
+import pandas as pd
+
+# Setup Google Generative AI
+GOOGLE_API_KEY = "AIzaSyCffMQoYpKJzdk46zTONhlQm6VI21ihWLQ"
+GENERATIVE_MODEL = "gemini-1.5-flash"
+
+def get_generative_ai_response(prompt):
+    try:
+        url = f"https://generativeai.googleapis.com/v1/models/{GENERATIVE_MODEL}:generateText?key={GOOGLE_API_KEY}"
+        headers = {
+            "Content-Type": "application/json",
+        }
+        payload = {
+            "prompt": prompt
+        }
+        response = requests.post(url, headers=headers, json=payload)
+        response.raise_for_status()
+        result = response.json()
+        return result.get('candidates', [{}])[0].get('output', 'No response text available')
+    except Exception as e:
+        st.error(f"Error fetching response from Generative AI: {e}")
+        return None
+
+# Title
+st.title("Investment Advice App")
+
+# User inputs
+monthly_savings = st.number_input("Enter your monthly savings (in Rs):", min_value=0, value=5000, step=100)
+investment_duration = st.number_input("Enter the investment duration (in months):", min_value=1, value=24, step=1)
+
+# Calculate total savings
+total_savings = monthly_savings * investment_duration
+st.write(f"Total savings after {investment_duration} months: Rs {total_savings}")
+
+# Generate investment advice
+st.header("Investment Advice")
+
+# Risk Tolerance
+risk_tolerance = st.selectbox("Select your risk tolerance level:", ["Low", "Moderate", "High"])
+
+# User input for custom prompt
+user_input_prompt = st.text_area("Enter your custom prompt for investment advice:", value=f"""
+I am currently in class 11th and have 2 years before joining an engineering college. The total fees for 4 years of college is Rs. 10 lakh. I can save Rs. {monthly_savings} every month, accumulating a total amount of Rs. {total_savings} after {investment_duration} months. 
+I want to invest this money on a monthly basis to maximize profit or return with minimal risk, so that I can pay as much of my fees from the investment as possible. 
+Please provide specific companies, stocks, or mutual funds suitable for a {risk_tolerance} risk tolerance.
+""")
+
+if st.button("Get Investment Advice"):
+    response = get_generative_ai_response(user_input_prompt)
+    if response:
+        st.write(response)
+
+# Fetch stock data using yfinance
+def fetch_stock_data(ticker):
+    stock = yf.Ticker(ticker)
+    hist = stock.history(period="1y")
+    return hist
+
+# Example stock tickers (you can replace these with your choices)
+stock_tickers = {
+    "HDFC Bank": "HDFCBANK.NS",
+    "Reliance Industries": "RELIANCE.NS",
+    "TCS": "TCS.NS",
+    "Infosys": "INFY.NS"
+}
+
+# Display stock data
+st.header("Stock Data")
+for company, ticker in stock_tickers.items():
+    st.subheader(company)
+    data = fetch_stock_data(ticker)
+    st.line_chart(data["Close"])
+
+# Monthly Savings Plan Table
+st.header("Monthly Savings Plan")
+
+# Table data
+table_data = {
+    "Expense": ["Hostel Fees", "Mess Fees", "Personal Expenses", "Academic Supplies", "Miscellaneous"],
+    "Original Amount (Rs)": [5000, 3000, 2000, 1000, 1000],
+    "Savings Strategy": [
+        "Shared room or annual payment discount (10%)",
+        "Cooking 5 meals a month (saves Rs 50 per meal)",
+        "Reducing non-essential expenses by 20%",
+        "Buying second-hand or digital books (saves 30%)",
+        "Limiting miscellaneous spending by 20%"
+    ],
+    "New Amount (Rs)": [4500, 2750, 1600, 700, 800],
+    "Monthly Savings (Rs)": [500, 250, 400, 300, 200]
+}
+
+# Create DataFrame
+df = pd.DataFrame(table_data)
+
+# Display table
+st.table(df)
+
+# Footer
+st.write("This app provides general investment advice based on your inputs. Please consult with a financial advisor before making any investment decisions.")
+

requirements.txt

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+streamlit==1.21.0
+yfinance==0.2.12
+pandas==1.5.3
+requests==2.28.2