[Method] Bot to respond to HARO emails for backlinks using OpenAI

# %%
import imaplib
import json
import email
import openai
import time
import email.charset
import datetime
import pytz
import pandas as pd
# %%
# Read the email username and password from the config.json file
with open("config.json", "r") as config_file:
config_data = json.load(config_file)
email_username = config_data["email_username"]
email_password = config_data["email_password"]
openai.api_key = config_data["API_KEY"]
# %%
mail = imaplib.IMAP4_SSL("imap.gmail.com")
# Login to the email account
mail.login(email_username, email_password)
# Select the inbox
# %%
# Define the date range for last week
now = datetime.datetime.now(pytz.timezone("UTC"))
last_week = now - datetime.timedelta(days=7)
mail.select("inbox")
# Search for emails from the specified sender in the date range
status, emails = mail.search(None, f'FROM "[email protected]" SINCE "30-Jan-2023"')

# %%
keywords = ['Pregnancy','Pediatrician']
results = []
# Scrape all instances of the desired content
email_ids = emails[0].split()
for email_id in email_ids:
status, email_data = mail.fetch(email_id, "(RFC822)")
email_body = email_data[0][1].decode("utf-8")
msg = email.message_from_string(email_body)
email_body = email_body.replace("\r", "").replace("\n", "")
start = 0
while True:

start = email_body.find("Summary:", start)
if start == -1:
break
start += len("Summary:")
end = email_body.find("Name:", start)
summary = email_body[start:end].strip()
start = email_body.find("Email:", end) + len("Email:")
end = email_body.find("Media Outlet:", start)
address = email_body[start:end].strip()
start = email_body.find("Query:", end) + len("Query:")
end = email_body.find("Requirements:", start)
query = email_body[start:end].strip()
start = email_body.find("Requirements:", end) + len("Requirements:")
end = email_body.find("-----------------------------------", start)
requirements = email_body[start:end].strip()

# Check if any of the keywords are included in summary, email, query, and requirements
for keyword in keywords:
if keyword in summary or keyword in address or keyword in query or keyword in requirements:
# Add the summary, email, query and requirements to the questions dictionary
results.append((msg['Date'], summary, address, query, requirements))
break
df = pd.DataFrame(results, columns=["Date", "Summary", "Address", "Query", "Requirements"])
prompt = "I want you to write a professional email response to this question or questions: '{}'. In each response, you must include: '{}' You will act as the professional the email seeks. Introduce yourself by name at the start of the email. Any required links will be included in your email signature. After introducing yourself, immediately answer the questions asked. Do not beat around the bush. You are to list the question and immediately give your expert opinion."
return_emails = []
for index, row in df.iterrows():
query = row['Query']
requirements = row['Requirements']
response = openai.Completion.create(engine="text-davinci-003", prompt=prompt.format(query, requirements), temperature=0.7,max_tokens=1000,top_p=0.5)
response_text = response['choices'][0]['text']
return_emails.append(response_text)





# %%
for i, address in enumerate(df['Address']):
msg = email.message.Message()
msg["To"] = address
msg["Subject"] = "HARO Question"
msg.set_payload(return_emails)
return_emails = msg.as_string()
drafts = mail.append("[Gmail]/Drafts", "", imaplib.Time2Internaldate(time.time()), return_emails.encode())

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