Update app.py

app.py

@@ -1,68 +1,68 @@
 import streamlit as st
 import pandas as pd
 import numpy as np
-import os
-from sentence_transformers import SentenceTransformer
-from sklearn.metrics.pairwise import cosine_similarity
 import matplotlib.pyplot as plt
 import io
-from openai import OpenAI
 
-# Set page config FIRST
 st.set_page_config(page_title="Construction Estimator", layout="centered")
 
-# Setup OpenAI/Groq client
-client = OpenAI(
-    api_key=os.getenv("GROQ_API_KEY"),
-    base_url="https://api.groq.com/openai/v1"
-)
-GROQ_MODEL = "llama3-8b-8192"
-
-# Embed chunks - keep for similarity search if needed in future
-@st.cache_resource
-def embed_chunks(chunks):
-    model = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")
-    embeddings = model.encode(chunks)
-    return embeddings, model
-
-# Generate estimate with Groq
-def generate_estimate(context, user_input):
-    prompt = f"""You are a construction estimator working in Pakistan. Using the following schedule of rates and quantities:
-
-{context}
-
-Generate a detailed BOQ estimate including item numbers, full descriptions, unit rates, quantities, and total amount in Rs for:
-{user_input}
-
-Present the result in a markdown table with columns: Item No, Description, Qty, Unit, Rate, Amount."""
-    
-    response = client.chat.completions.create(
-        model=GROQ_MODEL,
-        messages=[{"role": "user", "content": prompt}]
-    )
-    return response.choices[0].message.content
-
-# Sketch generator
-def draw_floor_plan(rooms, baths, living, car_porch, area):
+def calculate_scaled_quantities(base_qty_df, covered_area):
+    """
+    base_qty_df: DataFrame with columns: Material, Unit, Quantity_per_1000sqft
+    covered_area: float, in sqft
+
+    Returns a DataFrame with scaled quantities according to covered area
+    """
+    scale_factor = covered_area / 1000
+    base_qty_df['Scaled Quantity'] = base_qty_df['Quantity_per_1000sqft'] * scale_factor
+    return base_qty_df
+
+def calculate_costs(qty_df, rates_df):
+    """
+    qty_df: DataFrame with scaled quantities (Material, Unit, Scaled Quantity)
+    rates_df: DataFrame with columns: Material, Unit, Rate_per_Unit
+
+    Returns a DataFrame with cost calculations
+    """
+    df = pd.merge(qty_df, rates_df, on=['Material', 'Unit'], how='left')
+    df['Amount'] = df['Scaled Quantity'] * df['Rate_per_Unit']
+    df.fillna({'Rate_per_Unit':0, 'Amount':0}, inplace=True)
+    return df
+
+def generate_boq_table(df):
+    df = df.reset_index(drop=True)
+    df.index += 1
+    df_out = df.rename(columns={
+        'Material': 'Description',
+        'Scaled Quantity': 'Qty',
+        'Unit': 'Unit',
+        'Rate_per_Unit': 'Rate (PKR)',
+        'Amount': 'Amount (PKR)'
+    })[['Description', 'Qty', 'Unit', 'Rate (PKR)', 'Amount (PKR)']]
+    return df_out
+
+def draw_floor_plan(rooms, baths, living, car_porch, covered_area):
     total_spaces = rooms + baths + living + car_porch
+    if total_spaces == 0:
+        total_spaces = 1
     cols = int(np.ceil(np.sqrt(total_spaces)))
     rows = int(np.ceil(total_spaces / cols))
 
     fig, ax = plt.subplots(figsize=(10, 8))
-    scale = np.sqrt(area) / 10
+    scale = np.sqrt(covered_area) / 10
     width, height = scale, scale * 0.75
-    labels = (["Room"] * rooms + ["Bath"] * baths + ["Living"] * living + ["Car Porch"] * car_porch)
 
+    labels = (["Room"] * rooms + ["Bath"] * baths + ["Living"] * living + ["Car Porch"] * car_porch)
     for i, label in enumerate(labels):
         row = i // cols
         col = i % cols
         x = col * width
         y = (rows - 1 - row) * height
         ax.add_patch(plt.Rectangle((x, y), width, height, edgecolor='black', facecolor='lightblue'))
-        ax.text(x + width / 2, y + height / 2, label, ha='center', va='center', fontsize=8)
+        ax.text(x + width/2, y + height/2, label, ha='center', va='center', fontsize=10)
 
-    ax.set_xlim(0, cols * width)
-    ax.set_ylim(0, rows * height)
+    ax.set_xlim(0, cols*width)
+    ax.set_ylim(0, rows*height)
     ax.set_aspect('equal')
     ax.set_title(f"Tentative Floor Plan (Scale: 1 unit = {int(scale)} sqft)")
     ax.axis('off')
@@ -72,59 +72,54 @@ def draw_floor_plan(rooms, baths, living, car_porch, area):
     buf.seek(0)
     return buf
 
-# -------------------- MAIN APP --------------------
 def main():
-    st.title("🧱 Construction Estimator (RAG + LLaMA 3 + Sketch)")
-
-    st.subheader("Upload Material Data")
-
-    material_qty_file = st.file_uploader("Upload Material Quantities Excel", type=["xlsx", "xlsm"])
-    material_cost_file = st.file_uploader("Upload Material Costs Excel", type=["xlsx", "xlsm"])
-
-    if material_qty_file and material_cost_file:
-        qty_df = pd.read_excel(material_qty_file)
-        cost_df = pd.read_excel(material_cost_file)
-
-        st.write("### Material Quantities")
-        st.dataframe(qty_df)
-
-        st.write("### Material Costs")
-        st.dataframe(cost_df)
-
-        # Attempt to get covered area from quantities file if exists
-        area = None
-        if "Covered Area (sqft)" in qty_df.columns:
-            try:
-                area = float(qty_df["Covered Area (sqft)"].iloc[0])
-            except Exception:
-                area = None
-
-        context_qty = qty_df.to_string(index=False)
-        context_cost = cost_df.to_string(index=False)
-        context = f"Material Quantities:\n{context_qty}\n\nMaterial Costs:\n{context_cost}"
-
-        st.subheader("🏗️ Enter Other Project Details")
-        rooms = st.number_input("Number of Rooms", min_value=1, value=3)
-        baths = st.number_input("Number of Washrooms", min_value=1, value=2)
-        living = st.number_input("Number of Living Rooms", min_value=0, value=1)
-        car_porch = st.number_input("Number of Car Porches", min_value=0, value=1)
-
-        if st.button("Generate Estimate"):
-            user_query = f"Estimate cost for {rooms} rooms, {baths} bathrooms, {living} living rooms, and {car_porch} car porch(es)."
-            response = generate_estimate(context, user_query)
-
-            st.subheader("💸 Estimated Construction Cost (BOQ Style)")
-            st.markdown("**This BOQ is a simplified estimate. Use it for planning, not execution.**")
-            st.markdown(response)
-
-            # Use area if available, else default 1200 sqft for sketch scaling
-            sketch_area = area if area else 1200
-            buf = draw_floor_plan(rooms, baths, living, car_porch, sketch_area)
-            st.subheader("🏠 Tentative Floor Plan Sketch")
-            st.image(buf, caption="Auto-generated Line Plan", use_column_width=True)
-            st.download_button("📥 Download Sketch", buf, file_name="floor_plan.png", mime="image/png")
-    else:
-        st.info("Please upload both Material Quantities and Material Costs Excel files.")
+    st.title("🧱 Construction Material Estimator")
+
+    st.markdown("Upload **Base Quantities per 1000 sqft** and **Material Rates** Excel files. Then enter project details to calculate detailed BOQ and cost.")
+
+    qty_file = st.file_uploader("Upload Base Quantities Excel (Material, Unit, Quantity_per_1000sqft)", type=["xlsx", "xls"])
+    rate_file = st.file_uploader("Upload Material Rates Excel (Material, Unit, Rate_per_Unit)", type=["xlsx", "xls"])
+
+    if qty_file and rate_file:
+        try:
+            qty_df = pd.read_excel(qty_file)
+            rate_df = pd.read_excel(rate_file)
+
+            # Validate expected columns
+            required_qty_cols = {'Material', 'Unit', 'Quantity_per_1000sqft'}
+            required_rate_cols = {'Material', 'Unit', 'Rate_per_Unit'}
+
+            if not required_qty_cols.issubset(set(qty_df.columns)):
+                st.error(f"Base Quantities Excel missing columns: {required_qty_cols - set(qty_df.columns)}")
+                return
+            if not required_rate_cols.issubset(set(rate_df.columns)):
+                st.error(f"Material Rates Excel missing columns: {required_rate_cols - set(rate_df.columns)}")
+                return
+
+            covered_area = st.number_input("Covered Area (sqft)", min_value=100, value=1200)
+            rooms = st.number_input("Number of Rooms", min_value=0, value=3)
+            baths = st.number_input("Number of Bathrooms", min_value=0, value=2)
+            living = st.number_input("Number of Living Rooms", min_value=0, value=1)
+            car_porch = st.number_input("Number of Car Porches", min_value=0, value=1)
+
+            if st.button("Calculate BOQ & Cost"):
+                scaled_qty_df = calculate_scaled_quantities(qty_df, covered_area)
+                cost_df = calculate_costs(scaled_qty_df, rate_df)
+                boq_table = generate_boq_table(cost_df)
+
+                st.subheader("Scaled Material Quantities & Cost Estimate")
+                st.dataframe(boq_table.style.format({"Qty": "{:.2f}", "Rate (PKR)": "₨ {:,.2f}", "Amount (PKR)": "₨ {:,.2f}"}))
+
+                total_cost = boq_table['Amount (PKR)'].sum()
+                st.markdown(f"### Total Estimated Cost: ₨ {total_cost:,.2f}")
+
+                buf = draw_floor_plan(rooms, baths, living, car_porch, covered_area)
+                st.subheader("Tentative Floor Plan Sketch")
+                st.image(buf, use_column_width=True)
+                st.download_button("Download Floor Plan Sketch", buf, file_name="floor_plan.png", mime="image/png")
+
+        except Exception as e:
+            st.error(f"Error processing files: {e}")
 
 if __name__ == "__main__":
     main()