mcp/server/swiggy_scraper.py

"""
Reusable helper to fetch Swiggy order e-mails and return a list[dict].

Usage:
    from swiggy_scraper import fetch_swiggy_orders
    orders = fetch_swiggy_orders("17-May-2025", "20-May-2025")
"""

import os, imaplib, json
from email import message_from_bytes
from bs4 import BeautifulSoup
from openai import OpenAI
from dotenv import load_dotenv
from datetime import datetime, timedelta
from email.utils import parsedate_to_datetime
from zoneinfo import ZoneInfo

from db_schema import init_db, get_orders_by_date_from_db, save_orders_to_db


load_dotenv()

APP_PASSWORD = os.getenv("APP_PASSWORD")
EMAIL_ID     = os.getenv("EMAIL_ID")
OPENAI_KEY   = os.getenv("OPENAI_API_KEY")

client = OpenAI(api_key=OPENAI_KEY)

def _imap_connect():
    m = imaplib.IMAP4_SSL("imap.gmail.com")
    m.login(EMAIL_ID, APP_PASSWORD)
    m.select('"[Gmail]/All Mail"')
    return m

def _email_to_clean_text(msg):
    html = next(
        (part.get_payload(decode=True).decode(errors="ignore")
         for part in msg.walk()
         if part.get_content_type() == "text/html"),
        None,
    )
    if not html:
        return ""
    soup = BeautifulSoup(html, "html.parser")
    for t in soup(["script", "style", "head", "meta", "link"]):
        t.decompose()
    return "\n".join(
        line.strip() for line in soup.get_text("\n").splitlines() if line.strip()
    )

def _get_all_dates(start_date: str, end_date: str):
    start = datetime.strptime(start_date, "%d-%b-%Y")
    end = datetime.strptime(end_date, "%d-%b-%Y")
    delta = (end - start).days + 1
    return [(start + timedelta(days=i)).strftime("%Y-%m-%d") for i in range(delta)]




def _extract_with_llm(email_number, subject, body, email_date, email_time):
    current_email = {
        "subject": subject,
        "body": body
    }

    prompt = f"""
You are given a Swiggy order confirmation email with a subject and body.

Extract and return only the following:
- "restaurant_name": name of the restaurant
- "delivery_address": the delivery address
- "items": a list of ordered items, each with "name", "quantity", and "price" (number)
- "total_price": the total bill paid including taxes, charges, etc.

Example output format:
{{
  "restaurant_name": "Dominos Pizza",
  "delivery_address": "123 Main St, City",
  "total_price": 567,
  "items": [
    {{ "name": "Veg Pizza", "quantity": 2, "price": 199 }},
    {{ "name": "Coke", "quantity": 1, "price": 45 }}
  ]
}}

Return only valid JSON. No extra text or comments.

{json.dumps(current_email, indent=2)}
"""


    try:
        rsp = client.chat.completions.create(
            model="gpt-4o-mini",
            temperature=0,
            messages=[
                {"role": "system", "content": "You are a precise JSON extractor."},
                {"role": "user", "content": prompt},
            ],
        )

        # Attempt to parse the returned content
        parsed_data = json.loads(rsp.choices[0].message.content)

        # Wrap into final structure
        final_output = {
            "email_number": email_number,
            "order_date": email_date,
            "order_time": email_time,
            "restaurant_name": parsed_data.get("restaurant_name", ""),
            "delivery_address": parsed_data.get("delivery_address", ""),
            "items": parsed_data.get("items", []),
            "total_price": parsed_data.get("total_price", 0)
        }

        
        return final_output

    except json.JSONDecodeError as json_err:
        return {
            "email_number": email_number,
            "error": f"JSON decoding failed: {str(json_err)}",
            "raw_response": rsp.choices[0].message.content if 'rsp' in locals() else None
        }

    except Exception as e:
        return {
            "email_number": email_number,
            "error": f"Unexpected error: {str(e)}"
        }



def fetch_swiggy_orders(start_date: str, end_date: str) -> list[dict]:
    mail = _imap_connect()
    all_dates = _get_all_dates(start_date, end_date)
    orders = []

    for date_str in all_dates:
        # 1) Try loading from DB
        day_orders = get_orders_by_date_from_db(date_str)
        if day_orders:
            print(f"{date_str} loaded from DB")
            orders.extend(day_orders)
            continue

        # 2) Otherwise scrape emails for that date
        print(f"Fetching Swiggy emails for {date_str}")
        dt_obj = datetime.strptime(date_str, "%Y-%m-%d")
        next_day = (dt_obj + timedelta(days=1)).strftime("%d-%b-%Y")
        this_day = dt_obj.strftime("%d-%b-%Y")

        crit = f'(FROM "noreply@swiggy.in") SINCE "{this_day}" BEFORE "{next_day}"'
        _, data = mail.search(None, crit)
        ids = data[0].split()

        scraped_orders = []
        for idx, eid in enumerate(ids, 1):
            _, msg_data = mail.fetch(eid, "(RFC822)")
            msg = message_from_bytes(msg_data[0][1])
            subject = msg.get("Subject", "")
            body_text = _email_to_clean_text(msg)

            try:
                dt_obj = parsedate_to_datetime(msg["Date"]).astimezone(ZoneInfo("Asia/Kolkata"))
                email_date = dt_obj.strftime("%d-%b-%Y")
                email_time = dt_obj.strftime("%H:%M:%S")

                order = _extract_with_llm(idx, subject, body_text, email_date, email_time)
                scraped_orders.append(order)
            except Exception as exc:
                scraped_orders.append({"email_number": idx, "error": str(exc)})

        # 3) Save newly scraped data to DB
        save_orders_to_db(date_str, scraped_orders)
        orders.extend(scraped_orders)

    mail.logout()
    return orders