procurement-ingest/lambdas/wo/email_processor/handler.py

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Merge workorder-ingest into unified procurement repo (#22) * Merge workorder-ingest pipeline into unified repo Move PO lambdas under lambdas/po/, add WO pipeline under lambdas/wo/. Two independent CloudFormation stacks in one CDK app. Fix WO stack compliance: ARM64 architecture, 60-day log retention, aarch64 bundling, RETAIN on Anthropic secret. Remove stale CodePipeline buildspec. * Fix test_local.py import path and remove dead shared/models.py test_local.py referenced the old lambdas/email_processor path. Updated to lambdas/wo/email_processor. Removed shared/ directory entirely as nothing imports from it. * Escape HTML in both web UI dashboards to prevent XSS Both Function URLs are public (auth_type=NONE) and render email-derived content via f-strings. Attacker-crafted emails could inject scripts. Added html.escape() on all interpolated values in both PO and WO dashboards. * Add pagination to WO web UI scan get_work_orders() only fetched the first 1MB page from DynamoDB. Loop on LastEvaluatedKey to match the PO web UI pattern. * Fix esc(None) TypeError and javascript: scheme in PO web UI Coerce supplier name through `or ""` before escaping to handle nested None from DynamoDB. Add scheme allowlist on view_order_url to block javascript:/data: hrefs from LLM-extracted URLs. * Fix WO render_badge None guard, updated_at slice, and backfill path Add null guard to WO render_badge matching the PO version. Use `or ""` before slicing updated_at to handle explicit None values. Fix backfill_sites.py sys.path to use new lambdas/po/site_extractor. * Harden WO web UI and fix JS-context XSS in both dashboards - Use json.dumps for onclick URLs to prevent JS string breakout - Add .lower() to WO render_badge color lookup matching PO pattern - Add pagination to get_comments query - Cap get_work_orders to 500 results matching PO pattern * Apply ruff formatting to web UI handlers
2026-05-12 15:21:06 -04:00
"""
Email processor Lambda.
Triggered by S3 events when SES delivers an email.
Parses the raw email, sends it to Claude for structured extraction,
then writes the result to DynamoDB.
"""
import email
import json
import logging
import os
import re
from datetime import datetime
from email import policy
import anthropic
import boto3
logger = logging.getLogger()
logger.setLevel(logging.INFO)
s3 = boto3.client("s3")
dynamodb = boto3.resource("dynamodb")
WORK_ORDERS_TABLE = os.environ.get("WORK_ORDERS_TABLE", "WorkOrders")
COMMENTS_TABLE = os.environ.get("COMMENTS_TABLE", "WorkOrderComments")
ANTHROPIC_API_KEY_SECRET_ARN = os.environ.get("ANTHROPIC_API_KEY_SECRET_ARN")
EXTRACTION_PROMPT = """\
You are an email parser for a facilities maintenance work order system.
The emails come from Amazon's APM system (via Hexagon EAM / HxGN SmartCloud).
Analyze the following email and extract structured data. Return ONLY valid JSON with these fields:
{
"email_type": "new_work_order" | "update" | "comment" | "cancellation",
"work_order_id": "string or null",
"description": "work order description or null",
"status": "new" | "assigned" | "in_progress" | "on_hold" | "completed" | "cancelled" | "unknown",
"site_code": "building/site code like WIL1, ZDL8, etc. or null",
"building": "full building identifier or null",
"address": "physical address or null",
"severity": "severity level or null",
"priority": "priority level or null",
"date_reported": "ISO 8601 date or null",
"scheduled_start": "ISO 8601 date or null",
"due_date": "ISO 8601 date or null",
"assigned_to": "person/team assigned or null",
"commenter": "person who left a comment or null",
"comment_text": "the comment text or null",
"comment_time": "ISO 8601 datetime of the comment or null"
}
Rules:
- "email_type" detection:
- "new_work_order": email announces a new WO assignment
- "comment": email contains a new comment on an existing WO
- "cancellation": email announces a WO has been cancelled
- "update": any other update to an existing WO (status change, reassignment, etc.)
- Extract the site_code from the building field (e.g., "WIL1" from "building WIL1")
- Dates should be converted to ISO 8601 format
- If a field is not present in the email, set it to null
- Do NOT invent or infer data that is not explicitly in the email
"""
def get_anthropic_client() -> anthropic.Anthropic:
"""Create Anthropic client, fetching API key from Secrets Manager if configured."""
if ANTHROPIC_API_KEY_SECRET_ARN:
secrets = boto3.client("secretsmanager")
secret = secrets.get_secret_value(SecretId=ANTHROPIC_API_KEY_SECRET_ARN)
api_key = secret["SecretString"]
return anthropic.Anthropic(api_key=api_key)
# Fall back to ANTHROPIC_API_KEY env var (for local testing)
return anthropic.Anthropic()
def parse_raw_email(raw_bytes: bytes) -> dict:
"""Parse a raw email into subject, sender, body text."""
msg = email.message_from_bytes(raw_bytes, policy=policy.default)
subject = msg.get("Subject", "")
sender = msg.get("From", "")
to = msg.get("To", "")
cc = msg.get("Cc", "")
date = msg.get("Date", "")
body = ""
if msg.is_multipart():
for part in msg.walk():
content_type = part.get_content_type()
if content_type == "text/plain":
body = part.get_content()
break
elif content_type == "text/html" and not body:
body = part.get_content()
else:
body = msg.get_content()
return {
"subject": subject,
"sender": sender,
"to": to,
"cc": cc,
"date": date,
"body": body,
}
def extract_with_claude(email_data: dict) -> dict:
"""Send parsed email to Claude for structured extraction."""
client = get_anthropic_client()
email_text = (
f"Subject: {email_data['subject']}\n"
f"From: {email_data['sender']}\n"
f"To: {email_data['to']}\n"
f"CC: {email_data['cc']}\n"
f"Date: {email_data['date']}\n"
f"\n---\n\n"
f"{email_data['body']}"
)
response = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[
{
"role": "user",
"content": f"{EXTRACTION_PROMPT}\n\nEMAIL:\n{email_text}",
}
],
)
response_text = response.content[0].text
# Extract JSON from response (handle markdown code blocks)
json_match = re.search(r"```(?:json)?\s*(.*?)```", response_text, re.DOTALL)
if json_match:
response_text = json_match.group(1)
return json.loads(response_text.strip())
def save_work_order(parsed: dict, s3_key: str):
"""Create or update a work order in DynamoDB."""
table = dynamodb.Table(WORK_ORDERS_TABLE)
work_order_id = parsed["work_order_id"]
now = datetime.utcnow().isoformat()
# Build update expression dynamically from non-null fields
field_map = {
"description": "description",
"status": "wo_status", # 'status' is a DynamoDB reserved word
"site_code": "site_code",
"building": "building",
"address": "address",
"severity": "severity",
"priority": "priority",
"date_reported": "date_reported",
"scheduled_start": "scheduled_start",
"due_date": "due_date",
"assigned_to": "assigned_to",
}
update_parts = ["#updated_at = :updated_at", "#source_key = :source_key"]
attr_names = {
"#updated_at": "updated_at",
"#source_key": "source_email_s3_key",
}
attr_values = {
":updated_at": now,
":source_key": s3_key,
}
for src_field, dynamo_field in field_map.items():
value = parsed.get(src_field)
if value is not None:
placeholder = f":{dynamo_field}"
name_placeholder = f"#{dynamo_field}"
update_parts.append(f"{name_placeholder} = {placeholder}")
attr_names[name_placeholder] = dynamo_field
attr_values[placeholder] = value
# For new items, set created_at
update_parts.append("#created_at = if_not_exists(#created_at, :created_at)")
attr_names["#created_at"] = "created_at"
attr_values[":created_at"] = now
# Customer is always AMAZON for now
update_parts.append("#customer = :customer")
attr_names["#customer"] = "customer"
attr_values[":customer"] = "AMAZON"
# Track the record type (new_work_order, update, comment)
email_type = parsed.get("email_type")
if email_type:
update_parts.append("#record_type = :record_type")
attr_names["#record_type"] = "record_type"
attr_values[":record_type"] = email_type
table.update_item(
Key={"work_order_id": work_order_id},
UpdateExpression="SET " + ", ".join(update_parts),
ExpressionAttributeNames=attr_names,
ExpressionAttributeValues=attr_values,
)
logger.info(f"Saved work order {work_order_id}")
def save_event(parsed: dict, s3_key: str):
"""Save an event to the events table. Every email creates an event entry."""
table = dynamodb.Table(COMMENTS_TABLE)
work_order_id = parsed["work_order_id"]
email_type = parsed.get("email_type", "unknown")
event_time = parsed.get("comment_time") or datetime.utcnow().isoformat()
event_id = f"{work_order_id}#{event_time}"
item = {
"work_order_id": work_order_id,
"comment_id": event_id, # keeping key name for table compatibility
"record_type": email_type,
"commenter": parsed.get("commenter") or "",
"text": parsed.get("comment_text") or "",
"created_at": event_time,
"source_email_s3_key": s3_key,
"ingested_at": datetime.utcnow().isoformat(),
}
table.put_item(Item=item)
logger.info(f"Saved event {event_id} (type={email_type})")
def handler(event, context):
"""Lambda entry point. Triggered by S3 ObjectCreated events."""
for record in event.get("Records", []):
bucket = record["s3"]["bucket"]["name"]
key = record["s3"]["object"]["key"]
logger.info(f"Processing email: s3://{bucket}/{key}")
# Fetch raw email from S3
response = s3.get_object(Bucket=bucket, Key=key)
raw_email = response["Body"].read()
# Parse the raw email
email_data = parse_raw_email(raw_email)
logger.info(f"Subject: {email_data['subject']}")
# Extract structured data with Claude
parsed = extract_with_claude(email_data)
logger.info(
f"Parsed: type={parsed.get('email_type')}, wo={parsed.get('work_order_id')}"
)
if not parsed.get("work_order_id"):
logger.warning(f"No work order ID found in email, skipping: {key}")
continue
s3_key = f"s3://{bucket}/{key}"
# Always upsert the work order with any new info
save_work_order(parsed, s3_key)
# Save every email as an event for history tracking
save_event(parsed, s3_key)
return {"statusCode": 200, "body": "OK"}