Upload app.py

app.py

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+import sqlite3
+import pandas as pd
+import openai
+import os
+import streamlit as st
+import datetime
+
+# Set OpenAI API Key (Ensure it's set properly)
+openai.api_key = os.getenv("sk-NOBe-504FBda5dOQPesE8xKYgzmvBhG_Z_21UZGXtvT3BlbkFJF2vDvLgwzMMrIYgqAC6ezqMnupr9ZAelUCMH4XBP8A") or "sk-NOBe-504FBda5dOQPesE8xKYgzmvBhG_Z_21UZGXtvT3BlbkFJF2vDvLgwzMMrIYgqAC6ezqMnupr9ZAelUCMH4XBP8A"
+
+# Create sample house data
+house_data = [
+    ("Alice", "1234567890", 15000, True, "Delhi", "2BHK", "Furnished"),
+    ("Bob", "9876543210", 45000, False, "Mumbai", "3BHK", "Semi Furnished"),
+    ("Charlie", "5556667777", 30000, True, "Pune", "4BHK", "Non Furnished"),
+    ("David", "4445556666", 25000, True, "Jaipur", "1BHK", "Furnished"),
+    ("Eve", "3332221111", 40000, False, "Ahmedabad", "3BHK", "Semi Furnished")
+]
+
+# Create DataFrame and save to CSV
+df = pd.DataFrame(house_data, columns=["owner_name", "contact", "price", "for_sale", "location", "house_type", "house_details"])
+df.to_csv("houses.csv", index=False)
+
+# Connect to SQLite Database
+conn = sqlite3.connect("houses.db")
+cursor = conn.cursor()
+
+# Create Table if it doesn't exist
+cursor.execute('''
+    CREATE TABLE IF NOT EXISTS houses (
+        id INTEGER PRIMARY KEY AUTOINCREMENT,
+        owner_name TEXT,
+        contact TEXT,
+        price INTEGER,
+        for_sale BOOLEAN,
+        location TEXT,
+        house_type TEXT,
+        house_details TEXT
+    )
+''')
+
+# Load data from CSV and insert into database (replace table content if exists)
+df = pd.read_csv("houses.csv")
+df.to_sql("houses", conn, if_exists="replace", index=False)
+conn.commit()
+
+# Function to retrieve data from SQLite Database
+def retrieve_data():
+    cursor.execute("SELECT * FROM houses")
+    rows = cursor.fetchall()
+    # Assuming the table now includes the 'id' column, we include it in the DataFrame.
+    return pd.DataFrame(rows, columns=["owner_name", "contact", "price", "for_sale", "location", "house_type", "house_details"])
+
+# Chatbot function that uses the database records in its prompt
+def chatbot(query):
+    df = retrieve_data()
+    relevant_data = df.to_string(index=False)
+    prompt = f"Given the following real estate records:\n{relevant_data}\n\nAnswer the user's query based on the provided data.\n\nUser Query: {query}\nResponse:"
+    
+    response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo", 
+        messages=[
+            {"role": "system", "content": "You are an AI assistant that uses the provided database records to answer user queries."},
+            {"role": "user", "content": prompt}
+        ]
+    )
+    return response["choices"][0]["message"]["content"]
+
+# Streamlit UI
+st.title("Real Estate Chatbot")
+
+st.write("### Available Houses")
+st.dataframe(retrieve_data())
+
+query = st.text_input("Ask about available houses:")
+if st.button("Ask Chatbot"):
+    if query:
+        response_text = chatbot(query)
+        # Get the current date and time
+        now = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+        st.write("### User Query:")
+        st.write(query)
+        st.write(f"### Chatbot Response (Generated on {now}):")
+        st.write(response_text)
+    else:
+        st.warning("Please enter a query.")
+
+conn.close()