Mtkhang90/SmartConEstimator

1import streamlit as st2import pandas as pd3import numpy as np4import torch5import openai6import os7import io8import re9from sentence_transformers import SentenceTransformer10from sklearn.metrics.pairwise import cosine_similarity11import matplotlib.pyplot as plt12 13# --- Groq API setup ---14openai.api_key = os.getenv("GROQ_API_KEY")15openai.api_base = "https://api.groq.com/openai/v1"16GROQ_MODEL = "llama3-8b-8192"17 18# --- Load Excel ---19@st.cache_data20def load_excel(file):21    xl = pd.read_excel(file, sheet_name=None)22    all_data = pd.concat(xl.values(), ignore_index=True)23    return all_data24 25# --- Chunk using regex instead of nltk ---26def chunk_data(df, max_tokens=100):27    text = "\n".join(df.astype(str).apply(lambda row: " | ".join(row), axis=1))28    # Split on period, newline, or semicolon29    sentences = re.split(r'(?<=[.;])\s+|\n+', text)30    chunks, current_chunk, current_len = [], [], 031 32    for sent in sentences:33        tokens = sent.split()34        if current_len + len(tokens) > max_tokens:35            chunks.append(" ".join(current_chunk))36            current_chunk, current_len = [], 037        current_chunk.append(sent)38        current_len += len(tokens)39 40    if current_chunk:41        chunks.append(" ".join(current_chunk))42 43    return chunks44 45# --- Embed chunks ---46@st.cache_resource47def embed_chunks(chunks):48    model = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")49    embeddings = model.encode(chunks)50    return embeddings, model51 52# --- Query chunks ---53def query_embedding(user_query, chunks, embeddings, model):54    query_vec = model.encode([user_query])55    similarities = cosine_similarity(query_vec, embeddings)[0]56    top_indices = similarities.argsort()[::-1][:5]57    top_chunks = "\n\n".join([chunks[i] for i in top_indices])58    return top_chunks59 60# --- Generate Estimate from Groq ---61def generate_estimate(context, user_input):62    prompt = f"""You are a construction estimator in Pakistan. Use the following schedule of rates:63 64{context}65 66Estimate a full itemized construction BOQ for:67{user_input}68 69Include all relevant items for a complete house: excavation, foundation, RCC, masonry, plastering, flooring, doors, windows, paint, distemper, fans, lights, wiring, DBs, plumbing, sanitary fittings, water supply, cupboards, wardrobes, gate, etc.70 71Provide output in a markdown table with columns: Item No, Description, Qty, Unit, Rate, Amount in Rs.72"""73    response = openai.ChatCompletion.create(74        model=GROQ_MODEL,75        messages=[{"role": "user", "content": prompt}]76    )77    return response['choices'][0]['message']['content']78 79# --- Quantity Calculator ---80def calculate_quantities(rooms, area, baths, car_porch, living):81    return {82        "Total Area (sqft)": area,83        "No. of Rooms": rooms,84        "No. of Bathrooms": baths,85        "Living Rooms": living,86        "Car Porch Area (est.)": car_porch * 20087    }88 89# --- Floor Plan Sketch ---90def draw_floor_plan(rooms, baths, living, car_porch, area):91    total_spaces = rooms + baths + living + car_porch92    cols = int(np.ceil(np.sqrt(total_spaces)))93    rows = int(np.ceil(total_spaces / cols))94 95    fig, ax = plt.subplots(figsize=(10, 8))96    scale = np.sqrt(area) / 1097    width, height = scale, scale * 0.7598 99    labels = (["Room"] * rooms + ["Bath"] * baths +100              ["Living"] * living + ["Car Porch"] * car_porch)101 102    for i, label in enumerate(labels):103        row = i // cols104        col = i % cols105        x = col * width106        y = (rows - 1 - row) * height107        ax.add_patch(plt.Rectangle((x, y), width, height, edgecolor='black', facecolor='lightblue'))108        ax.text(x + width / 2, y + height / 2, label, ha='center', va='center', fontsize=8)109 110    ax.set_xlim(0, cols * width)111    ax.set_ylim(0, rows * height)112    ax.set_aspect('equal')113    ax.set_title(f"Tentative Floor Plan (Scale: 1 unit = {int(scale)} sqft)")114    ax.axis('off')115 116    buf = io.BytesIO()117    plt.savefig(buf, format='png')118    buf.seek(0)119    return buf120 121# --- Main App ---122def main():123    st.set_page_config(page_title="Construction Estimator", layout="centered")124    st.title("🧱 Construction Estimator (RAG + LLaMA 3 + Sketch)")125 126    excel_file = st.file_uploader("Upload Schedule of Rates (.xlsx or .xlsm)", type=["xlsx", "xlsm"])127    if excel_file:128        df = load_excel(excel_file)129        st.success("Excel file loaded successfully.")130        chunks = chunk_data(df)131        embeddings, model = embed_chunks(chunks)132 133        st.subheader("🏗️ Enter Project Details")134        rooms = st.number_input("Number of Rooms", min_value=1, value=3)135        area = st.number_input("Total Covered Area (sqft)", min_value=100, value=1200)136        baths = st.number_input("Number of Washrooms", min_value=1, value=2)137        living = st.number_input("Number of Living Rooms", min_value=0, value=1)138        car_porch = st.number_input("Number of Car Porches", min_value=0, value=1)139 140        if st.button("Generate Estimate"):141            quantities = calculate_quantities(rooms, area, baths, car_porch, living)142            user_query = f"Estimate cost for {rooms} rooms, {baths} bathrooms, {living} living rooms, total area {area} sqft, and {car_porch} car porch(es)."143            context = query_embedding(user_query, chunks, embeddings, model)144            response = generate_estimate(context, user_query)145 146            st.subheader("📊 Input Quantities")147            st.json(quantities)148 149            st.subheader("💸 Estimated Construction Cost (BOQ Style)")150            st.markdown(response)151 152            buf = draw_floor_plan(rooms, baths, living, car_porch, area)153            st.subheader("🏠 Tentative Floor Plan Sketch")154            st.image(buf, caption="Auto-generated Line Plan", use_column_width=True)155            st.download_button("📥 Download Sketch", buf, file_name="floor_plan.png", mime="image/png")156 157if __name__ == "__main__":158    main()159