Build a quote email bot

Building a quote email bot involves automating the process of responding to email inquiries with price quotes or information based on user requests. This can be done using programming languages like Python combined with email APIs and natural language processing (NLP) for understanding user requests.

Here’s a step-by-step guide and a simple example using Python, SMTP (for sending email), IMAP (for reading email), and a basic template for generating quotes.

Basic Concept

1. Read incoming emails from an inbox.

2. Parse the content to understand what quote or info the user is asking for.

3. Generate a quote based on the request.

4. Send an email reply with the generated quote.

Requirements

• Python 3.x

• imaplib and email libraries for reading emails.

• smtplib for sending emails.

• Optional: nltk or spaCy for advanced NLP if you want to parse requests more intelligently.

• An email account configured for IMAP/SMTP access.

Example Code (Simple Version)

python
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import imaplib
import smtplib
import email
from email.mime.text import MIMEText
from email.header import decode_header

# Email credentials
IMAP_SERVER = 'imap.gmail.com'
SMTP_SERVER = 'smtp.gmail.com'
EMAIL_ACCOUNT = 'your_email@gmail.com'
EMAIL_PASSWORD = 'your_password'

# Connect to the IMAP server and check for unseen emails
def fetch_unseen_emails():
    mail = imaplib.IMAP4_SSL(IMAP_SERVER)
    mail.login(EMAIL_ACCOUNT, EMAIL_PASSWORD)
    mail.select('inbox')
    status, messages = mail.search(None, '(UNSEEN)')
    email_ids = messages[0].split()
    unseen_emails = []
    for e_id in email_ids:
        status, msg_data = mail.fetch(e_id, '(RFC822)')
        for response_part in msg_data:
            if isinstance(response_part, tuple):
                msg = email.message_from_bytes(response_part[1])
                unseen_emails.append(msg)
    mail.logout()
    return unseen_emails

# Simple function to extract email body text
def get_email_body(msg):
    if msg.is_multipart():
        for part in msg.walk():
            content_type = part.get_content_type()
            if content_type == 'text/plain':
                return part.get_payload(decode=True).decode()
    else:
        return msg.get_payload(decode=True).decode()
    return ""

# Generate quote based on request content (simple example)
def generate_quote(request_text):
    # This is where you add your own logic
    if "website design" in request_text.lower():
        return "Our website design services start at $1000."
    elif "seo" in request_text.lower():
        return "SEO packages start at $500 per month."
    elif "logo" in request_text.lower():
        return "Logo design starts at $300."
    else:
        return "Please specify the service you are interested in for a quote."

# Send email reply
def send_email(to_email, subject, body):
    msg = MIMEText(body)
    msg['From'] = EMAIL_ACCOUNT
    msg['To'] = to_email
    msg['Subject'] = subject
    
    server = smtplib.SMTP_SSL(SMTP_SERVER, 465)
    server.login(EMAIL_ACCOUNT, EMAIL_PASSWORD)
    server.sendmail(EMAIL_ACCOUNT, to_email, msg.as_string())
    server.quit()

# Main bot logic
def run_quote_email_bot():
    emails = fetch_unseen_emails()
    for msg in emails:
        from_email = email.utils.parseaddr(msg['From'])[1]
        subject = msg['Subject']
        if subject is None:
            subject = "No Subject"
        body = get_email_body(msg)
        
        quote = generate_quote(body)
        reply_subject = f"Re: {subject}"
        send_email(from_email, reply_subject, quote)
        print(f"Sent quote to {from_email}")

if __name__ == "__main__":
    run_quote_email_bot()

Explanation

• The bot connects to your email inbox via IMAP, fetches unseen emails.

• It extracts the text content from the email body.

• It generates a quote based on keywords found in the message.

• It replies to the sender with a corresponding quote.

• You can expand the generate_quote function to be more sophisticated, or connect to a database of services and prices.

Considerations for Deployment

• Use environment variables or a safer method to handle passwords.

• Use OAuth for Gmail or other services instead of plain passwords.

• Schedule the script with cron or a task scheduler to run periodically.

• Implement logging and error handling.

• Add NLP for better understanding of requests.

If you’d like, I can help you make a more advanced or production-ready version!