arcade-mcp/toolkits/gmail/arcade_gmail/tools/utils.py
Nate Barbettini 408f2e6300
gmail: search_emails_by_header tool (#28)
Adds a new gmail tool to search email, plus some cleanup.
2024-08-30 15:29:02 -07:00

98 lines
2.6 KiB
Python

from base64 import urlsafe_b64decode
import re
from typing import Any, Dict, Optional
from bs4 import BeautifulSoup
def parse_email(email_data: Dict[str, Any]) -> Optional[Dict[str, str]]:
"""
Parse email data and extract relevant information.
Args:
email_data (Dict[str, Any]): Raw email data from Gmail API.
Returns:
Optional[Dict[str, str]]: Parsed email details or None if parsing fails.
"""
try:
payload = email_data["payload"]
headers = {d["name"].lower(): d["value"] for d in payload["headers"]}
body_data = _get_email_body(payload)
return {
"from": headers.get("from", ""),
"date": headers.get("date", ""),
"subject": headers.get("subject", "No subject"),
"body": _clean_email_body(body_data) if body_data else "",
}
except Exception as e:
print(f"Error parsing email {email_data.get('id', 'unknown')}: {e}")
return None
def _get_email_body(payload: Dict[str, Any]) -> Optional[str]:
"""
Extract email body from payload.
Args:
payload (Dict[str, Any]): Email payload data.
Returns:
Optional[str]: Decoded email body or None if not found.
"""
if "body" in payload and payload["body"].get("data"):
return urlsafe_b64decode(payload["body"]["data"]).decode()
for part in payload.get("parts", []):
if part.get("mimeType") == "text/plain" and "data" in part["body"]:
return urlsafe_b64decode(part["body"]["data"]).decode()
return None
def _clean_email_body(body: str) -> str:
"""
Remove HTML tags and clean up email body text while preserving most content.
Args:
body (str): The raw email body text.
Returns:
str: Cleaned email body text.
"""
try:
# Remove HTML tags using BeautifulSoup
soup = BeautifulSoup(body, "html.parser")
text = soup.get_text(separator=" ")
# Clean up the text
text = _clean_text(text)
return text.strip()
except Exception as e:
print(f"Error cleaning email body: {e}")
return body
def _clean_text(text: str) -> str:
"""
Clean up the text while preserving most content.
Args:
text (str): The input text.
Returns:
str: Cleaned text.
"""
# Replace multiple newlines with a single newline
text = re.sub(r"\n+", "\n", text)
# Replace multiple spaces with a single space
text = re.sub(r"\s+", " ", text)
# Remove leading/trailing whitespace from each line
text = "\n".join(line.strip() for line in text.split("\n"))
return text