Ai-Agent/utils.py at main · Kavindu21123/Ai-Agent · GitHub

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import pandas as pd
import os

# --- 1. SYNONYMS DATABASE ---
def get_synonyms():
    return {
        # Engine / Check Engine
        "engine": "check_engine", "engin": "check_engine", "enjin": "check_engine",
        "motor": "check_engine", "check": "check_engine",

        # Oil
        "oil": "oil_pressure", "oyl": "oil_pressure", "oill": "oil_pressure",

        # Battery
        "battery": "battery", "batry": "battery", "batery": "battery", "batary": "battery",

        # Brakes
        "brake": "brake", "brak": "brake", "break": "brake", "brek": "brake",

        # ABS
        "abs": "abs", "antilock": "abs", "anti-lock": "abs",

        # Airbag
        "airbag": "airbag", "air bag": "airbag", "srs": "airbag",

        # Fuel
        "fuel": "low_fuel", "gas": "low_fuel", "petrol": "low_fuel", "diesel": "low_fuel", "empty": "low_fuel",

        # Tires
        "tire": "tire_pressure", "tyre": "tire_pressure", "flat": "tire_pressure", "pressure": "tire_pressure",

        # Temperature / Coolant
        "heat": "coolant_temp", "overheat": "coolant_temp", "hot": "coolant_temp",
        "temp": "coolant_temp", "temperature": "coolant_temp", "coolant": "coolant_temp",

        # Seatbelt
        "seatbelt": "seat_belt", "belt": "seat_belt", "bukle": "seat_belt",

        # Door
        "door": "door_open", "open": "door_open", "close": "door_open",

        # Lights
        "beam": "high_beam", "high": "high_beam", "brights": "high_beam",
        "fog": "fog_light", "mist": "fog_light",

        # Fluids
        "washer": "washer_fluid", "water": "washer_fluid", "wipe": "washer_fluid", "fluid": "washer_fluid",

        # Controls
        "cruise": "cruise_control", "cruse": "cruise_control",
        "traction": "traction_control", "trac": "traction_control", "slip": "traction_control",
        "steering": "power_steering", "steer": "power_steering", "wheel": "power_steering",

        # DPF / Exhaust
        "dpf": "dpf", "diesel filter": "dpf", "particulate": "dpf", "soot": "dpf", "exhaust filter": "dpf",
    }

# --- 2. TEXT PARSER ---
def parse_text_common(user_text, synonyms):
    user_text = user_text.lower()
    found_labels = set()
    for word, label in synonyms.items():
        if word in user_text:
            found_labels.add(label)
    return list(found_labels)

# --- 3. COST ESTIMATOR (UPDATED FOR SRI LANKA & LABOR) ---
class CostEstimator:
    def __init__(self, csv_file='costs.csv'):
        self.csv_file = csv_file
        self.df = None
        self.load_data()

    def load_data(self):
        if os.path.exists(self.csv_file):
            self.df = pd.read_csv(self.csv_file)
        else:
            print(f"⚠️ Warning: {self.csv_file} not found.")

    def get_estimate(self, label):
        if self.df is None or self.df.empty:
            return None

        # Filter for the specific label
        data = self.df[self.df['label'] == label]

        if data.empty:
            return None

        row = data.iloc[0]

        # Calculate average cost
        avg_cost = (row['low_cost'] + row['high_cost']) / 2

        return {
            "part": row['part_name'],
            "average": f"Rs.{int(avg_cost):,}", # Added comma for thousands separator (e.g. Rs.45,000)
            "range": f"Rs.{int(row['low_cost']):,} - Rs.{int(row['high_cost']):,}",
            "labor": row['labor_hours']  # <--- NEW: Reads labor hours from CSV
        }