Create app.py

app.py

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+import streamlit as st
+import pandas as pd
+from sentence_transformers import SentenceTransformer
+import os
+import matplotlib.pyplot as plt
+import io
+from PIL import Image
+import base64
+import requests  # To fetch online data
+
+# --- Configuration ---
+GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
+LLAMA3_MODEL = "llama3-8b-8192"
+EMBEDDING_MODEL = "all-mpnet-base-v2"
+embedding_model = SentenceTransformer(EMBEDDING_MODEL)
+
+# --- Function to Fetch Islamabad Construction Material Prices ---
+@st.cache_data(ttl=3600)  # Cache for 1 hour
+def get_islamabad_material_prices():
+    """
+    Fetches current construction material prices for Islamabad.
+    This is a placeholder; in a real application, you would:
+    1. Scrape data from reliable online sources.
+    2. Use a paid API for real-time pricing.
+    3. Maintain an internal database updated with local prices.
+
+    For this example, we'll return a static dictionary.
+    """
+    # **IMPORTANT:** Replace this with actual data fetching logic.
+    prices = {
+        "Cement (per bag)": 1200,
+        "Steel (per ton)": 220000,
+        "Bricks (per 1000)": 15000,
+        "Sand (per cubic foot)": 50,
+        "Crush (per cubic foot)": 70,
+        "Labor (per day - skilled)": 2500,
+        "Labor (per day - unskilled)": 1200,
+        "Paint (per liter)": 800,
+        "Plumbing Fixtures (average cost per set)": 15000,
+        "Electrical Wiring (per point)": 3000,
+    }
+    return pd.DataFrame(list(prices.items()), columns=['Material', 'Price (PKR)'])
+
+# --- Function to Generate Realistic Floor Plan using AI (Placeholder) ---
+def generate_realistic_floor_plan(num_rooms, num_bathrooms, num_living_rooms, total_area, num_car_porches):
+    """
+    This is a placeholder for an AI-powered floor plan generator.
+    In a real application, you would integrate with an AI model
+    specialized in architectural design or use libraries that can
+    generate more complex layouts.
+
+    For this example, we'll return a textual description.
+    """
+    prompt = f"Generate a realistic floor plan for a house with {num_rooms} rooms, {num_bathrooms} bathrooms, {num_living_rooms} living rooms, approximately {total_area} sq ft, and {num_car_porches} car porches."
+    response = f"**Floor Plan Description:** A well-laid-out house with {num_rooms} rooms strategically placed for privacy and access. The {num_living_rooms} living rooms offer spacious areas for family and guests. {num_bathrooms} bathrooms are conveniently located. The design incorporates {num_car_porches} car porches. The total area of {total_area} sq ft allows for comfortable living spaces and efficient flow."
+    return response
+
+# --- Streamlit App ---
+st.title("Realistic Construction Cost Estimator & AI Floor Plan (Islamabad)")
+
+# --- Input Parameters ---
+st.subheader("Project Details")
+num_rooms = st.number_input("Number of Rooms", min_value=1, value=3)
+total_area = st.number_input("Total Covered Area (sq ft)", min_value=100, value=1500)
+num_bathrooms = st.number_input("Number of Bathrooms", min_value=1, value=2)
+num_living_rooms = st.number_input("Number of Living Rooms", min_value=0, value=1)
+num_car_porches = st.number_input("Number of Car Porches", min_value=0, value=1)
+
+# --- Fetch Material Prices ---
+material_prices_df = get_islamabad_material_prices()
+st.subheader("Current Construction Material Prices in Islamabad")
+st.dataframe(material_prices_df)
+
+if st.button("Generate Estimate and Floor Plan"):
+    if not GROQ_API_KEY:
+        st.error("Please set the GROQ_API_KEY environment variable.")
+    else:
+        st.subheader("Estimated Construction Cost (Conceptual)")
+        st.info("This is a simplified estimate based on the provided material prices and does not include all construction aspects.")
+
+        # Basic cost calculation (very simplified)
+        estimated_cost = (
+            material_prices_df[material_prices_df['Material'] == 'Cement (per bag)']['Price (PKR)'].iloc[0] * (total_area / 100) +  # Rough cement estimate
+            material_prices_df[material_prices_df['Material'] == 'Steel (per ton)']['Price (PKR)'].iloc[0] * (total_area / 500) +  # Rough steel estimate
+            material_prices_df[material_prices_df['Material'] == 'Bricks (per 1000)']['Price (PKR)'].iloc[0] * (total_area / 10) +  # Rough brick estimate
+            material_prices_df[material_prices_df['Material'] == 'Labor (per day - skilled)']['Price (PKR)'].iloc[0] * (num_rooms * 10) # Very rough labor
+        )
+        st.write(f"**Estimated Total Cost (Conceptual):** {estimated_cost:,.2f} PKR")
+        st.warning("This is a highly simplified cost. A detailed BOQ requires a comprehensive understanding of the design and material quantities.")
+
+        # --- Generate Realistic Floor Plan (Placeholder) ---
+        st.subheader("Realistic Floor Plan (AI Generated - Conceptual)")
+        floor_plan_description = generate_realistic_floor_plan(num_rooms, num_bathrooms, num_living_rooms, total_area, num_car_porches)
+        st.write(floor_plan_description)
+
+        st.info("AI-powered realistic floor plan generation is a complex task. This output is a textual description as a placeholder. Integrating with advanced AI models or architectural design tools would be required for a visual and detailed floor plan.")