mirror of
https://github.com/Sea-Haven-Industries/procurement-ingest.git
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* 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
271 lines
9 KiB
Python
271 lines
9 KiB
Python
"""
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Email processor Lambda.
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Triggered by S3 events when SES delivers an email.
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Parses the raw email, sends it to Claude for structured extraction,
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then writes the result to DynamoDB.
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"""
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import email
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import json
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import logging
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import os
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import re
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from datetime import datetime
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from email import policy
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import anthropic
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import boto3
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logger = logging.getLogger()
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logger.setLevel(logging.INFO)
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s3 = boto3.client("s3")
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dynamodb = boto3.resource("dynamodb")
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WORK_ORDERS_TABLE = os.environ.get("WORK_ORDERS_TABLE", "WorkOrders")
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COMMENTS_TABLE = os.environ.get("COMMENTS_TABLE", "WorkOrderComments")
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ANTHROPIC_API_KEY_SECRET_ARN = os.environ.get("ANTHROPIC_API_KEY_SECRET_ARN")
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EXTRACTION_PROMPT = """\
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You are an email parser for a facilities maintenance work order system.
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The emails come from Amazon's APM system (via Hexagon EAM / HxGN SmartCloud).
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Analyze the following email and extract structured data. Return ONLY valid JSON with these fields:
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{
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"email_type": "new_work_order" | "update" | "comment" | "cancellation",
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"work_order_id": "string or null",
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"description": "work order description or null",
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"status": "new" | "assigned" | "in_progress" | "on_hold" | "completed" | "cancelled" | "unknown",
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"site_code": "building/site code like WIL1, ZDL8, etc. or null",
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"building": "full building identifier or null",
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"address": "physical address or null",
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"severity": "severity level or null",
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"priority": "priority level or null",
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"date_reported": "ISO 8601 date or null",
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"scheduled_start": "ISO 8601 date or null",
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"due_date": "ISO 8601 date or null",
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"assigned_to": "person/team assigned or null",
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"commenter": "person who left a comment or null",
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"comment_text": "the comment text or null",
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"comment_time": "ISO 8601 datetime of the comment or null"
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}
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Rules:
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- "email_type" detection:
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- "new_work_order": email announces a new WO assignment
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- "comment": email contains a new comment on an existing WO
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- "cancellation": email announces a WO has been cancelled
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- "update": any other update to an existing WO (status change, reassignment, etc.)
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- Extract the site_code from the building field (e.g., "WIL1" from "building WIL1")
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- Dates should be converted to ISO 8601 format
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- If a field is not present in the email, set it to null
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- Do NOT invent or infer data that is not explicitly in the email
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"""
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def get_anthropic_client() -> anthropic.Anthropic:
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"""Create Anthropic client, fetching API key from Secrets Manager if configured."""
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if ANTHROPIC_API_KEY_SECRET_ARN:
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secrets = boto3.client("secretsmanager")
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secret = secrets.get_secret_value(SecretId=ANTHROPIC_API_KEY_SECRET_ARN)
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api_key = secret["SecretString"]
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return anthropic.Anthropic(api_key=api_key)
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# Fall back to ANTHROPIC_API_KEY env var (for local testing)
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return anthropic.Anthropic()
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def parse_raw_email(raw_bytes: bytes) -> dict:
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"""Parse a raw email into subject, sender, body text."""
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msg = email.message_from_bytes(raw_bytes, policy=policy.default)
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subject = msg.get("Subject", "")
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sender = msg.get("From", "")
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to = msg.get("To", "")
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cc = msg.get("Cc", "")
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date = msg.get("Date", "")
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body = ""
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if msg.is_multipart():
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for part in msg.walk():
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content_type = part.get_content_type()
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if content_type == "text/plain":
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body = part.get_content()
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break
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elif content_type == "text/html" and not body:
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body = part.get_content()
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else:
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body = msg.get_content()
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return {
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"subject": subject,
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"sender": sender,
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"to": to,
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"cc": cc,
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"date": date,
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"body": body,
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}
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def extract_with_claude(email_data: dict) -> dict:
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"""Send parsed email to Claude for structured extraction."""
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client = get_anthropic_client()
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email_text = (
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f"Subject: {email_data['subject']}\n"
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f"From: {email_data['sender']}\n"
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f"To: {email_data['to']}\n"
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f"CC: {email_data['cc']}\n"
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f"Date: {email_data['date']}\n"
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f"\n---\n\n"
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f"{email_data['body']}"
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)
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response = client.messages.create(
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model="claude-haiku-4-5-20251001",
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max_tokens=1024,
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messages=[
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{
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"role": "user",
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"content": f"{EXTRACTION_PROMPT}\n\nEMAIL:\n{email_text}",
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}
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],
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)
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response_text = response.content[0].text
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# Extract JSON from response (handle markdown code blocks)
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json_match = re.search(r"```(?:json)?\s*(.*?)```", response_text, re.DOTALL)
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if json_match:
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response_text = json_match.group(1)
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return json.loads(response_text.strip())
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def save_work_order(parsed: dict, s3_key: str):
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"""Create or update a work order in DynamoDB."""
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table = dynamodb.Table(WORK_ORDERS_TABLE)
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work_order_id = parsed["work_order_id"]
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now = datetime.utcnow().isoformat()
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# Build update expression dynamically from non-null fields
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field_map = {
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"description": "description",
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"status": "wo_status", # 'status' is a DynamoDB reserved word
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"site_code": "site_code",
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"building": "building",
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"address": "address",
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"severity": "severity",
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"priority": "priority",
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"date_reported": "date_reported",
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"scheduled_start": "scheduled_start",
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"due_date": "due_date",
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"assigned_to": "assigned_to",
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}
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update_parts = ["#updated_at = :updated_at", "#source_key = :source_key"]
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attr_names = {
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"#updated_at": "updated_at",
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"#source_key": "source_email_s3_key",
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}
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attr_values = {
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":updated_at": now,
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":source_key": s3_key,
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}
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for src_field, dynamo_field in field_map.items():
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value = parsed.get(src_field)
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if value is not None:
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placeholder = f":{dynamo_field}"
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name_placeholder = f"#{dynamo_field}"
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update_parts.append(f"{name_placeholder} = {placeholder}")
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attr_names[name_placeholder] = dynamo_field
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attr_values[placeholder] = value
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# For new items, set created_at
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update_parts.append("#created_at = if_not_exists(#created_at, :created_at)")
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attr_names["#created_at"] = "created_at"
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attr_values[":created_at"] = now
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# Customer is always AMAZON for now
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update_parts.append("#customer = :customer")
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attr_names["#customer"] = "customer"
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attr_values[":customer"] = "AMAZON"
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# Track the record type (new_work_order, update, comment)
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email_type = parsed.get("email_type")
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if email_type:
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update_parts.append("#record_type = :record_type")
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attr_names["#record_type"] = "record_type"
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attr_values[":record_type"] = email_type
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table.update_item(
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Key={"work_order_id": work_order_id},
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UpdateExpression="SET " + ", ".join(update_parts),
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ExpressionAttributeNames=attr_names,
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ExpressionAttributeValues=attr_values,
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)
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logger.info(f"Saved work order {work_order_id}")
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def save_event(parsed: dict, s3_key: str):
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"""Save an event to the events table. Every email creates an event entry."""
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table = dynamodb.Table(COMMENTS_TABLE)
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work_order_id = parsed["work_order_id"]
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email_type = parsed.get("email_type", "unknown")
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event_time = parsed.get("comment_time") or datetime.utcnow().isoformat()
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event_id = f"{work_order_id}#{event_time}"
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item = {
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"work_order_id": work_order_id,
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"comment_id": event_id, # keeping key name for table compatibility
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"record_type": email_type,
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"commenter": parsed.get("commenter") or "",
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"text": parsed.get("comment_text") or "",
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"created_at": event_time,
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"source_email_s3_key": s3_key,
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"ingested_at": datetime.utcnow().isoformat(),
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}
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table.put_item(Item=item)
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logger.info(f"Saved event {event_id} (type={email_type})")
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def handler(event, context):
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"""Lambda entry point. Triggered by S3 ObjectCreated events."""
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for record in event.get("Records", []):
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bucket = record["s3"]["bucket"]["name"]
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key = record["s3"]["object"]["key"]
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logger.info(f"Processing email: s3://{bucket}/{key}")
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# Fetch raw email from S3
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response = s3.get_object(Bucket=bucket, Key=key)
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raw_email = response["Body"].read()
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# Parse the raw email
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email_data = parse_raw_email(raw_email)
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logger.info(f"Subject: {email_data['subject']}")
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# Extract structured data with Claude
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parsed = extract_with_claude(email_data)
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logger.info(
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f"Parsed: type={parsed.get('email_type')}, wo={parsed.get('work_order_id')}"
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)
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if not parsed.get("work_order_id"):
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logger.warning(f"No work order ID found in email, skipping: {key}")
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continue
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s3_key = f"s3://{bucket}/{key}"
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# Always upsert the work order with any new info
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save_work_order(parsed, s3_key)
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# Save every email as an event for history tracking
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save_event(parsed, s3_key)
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return {"statusCode": 200, "body": "OK"}
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