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

"""
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.

Phase 5: this handler is the thin event loop + fail-closed auth + routing. The
work has moved to flat sibling modules (bare-name imports resolve via the same
flat-landing bundling as ses_auth/template_parser):
  extraction.py  -- extract_with_bedrock + the <email>-tag neutralizer
  telemetry.py   -- emit_parse_metric (stdout EMF)
  persistence.py -- save_work_order / save_event / comment_id determinism
  prompts.py     -- EXTRACTION_PROMPT (re-exported below for tests)
"""

import logging
import re

import boto3
from email_parsing import parse_raw_email
from extraction import extract_with_bedrock
from persistence import save_event, save_work_order
from prompts import EXTRACTION_PROMPT  # noqa: F401  (re-export for tests)
from ses_auth import authenticate_inbound_email
from telemetry import emit_parse_metric
from template_parser import try_deterministic_parse, validate_ai_fallback

logger = logging.getLogger()
logger.setLevel(logging.INFO)

# Lazy cached S3 client. Keeps the public attribute name ``s3`` so the test
# monkeypatch target changes module only, not attribute name.
s3 = None


def _get_s3():
    global s3
    if s3 is None:
        s3 = boto3.client("s3")
    return s3


def handler(event, context):
    """Lambda entry point. Triggered by S3 ObjectCreated events."""
    # Deploy-guard healthcheck (Phase 0): a top-level direct-invoke
    # {"healthcheck": true} probe returns immediately, BEFORE any S3 fetch,
    # SES sender-auth gate, or Records iteration. Real mail arrives as S3
    # ObjectCreated events whose top-level keys ("Records") AWS controls, so
    # email content can never set this key -- this creates no accept path for
    # mail. It emits NO EMF and no log line matching the sender_auth_rejected
    # metric-filter, so repeated post-deploy smoke invokes never page.
    if isinstance(event, dict) and event.get("healthcheck") is True:
        return {"healthcheck": "ok"}

    for record in event.get("Records", []):
        bucket = record["s3"]["bucket"]["name"]
        key = record["s3"]["object"]["key"]
        s3_key = f"s3://{bucket}/{key}"

        logger.info(f"Processing email: {s3_key}")

        # Fetch raw email from S3
        response = _get_s3().get_object(Bucket=bucket, Key=key)
        raw_email = response["Body"].read()

        # Fail-closed sender authentication (INFRA-107): only mail with an
        # SES-stamped dkim=pass verdict for an allowlisted domain may create
        # or update work orders. Rejected mail is logged and skipped without
        # erroring the invocation (no retries / DLQ spam).
        if not authenticate_inbound_email(raw_email, s3_key):
            continue

        # Parse the raw email
        email_data = parse_raw_email(raw_email)
        logger.info(f"Subject: {email_data['subject']}")

        # Deterministic template parse first; fall back to the AI extractor only
        # on a miss or an invalid (fail-closed) result.
        parsed, method, template_id, reason = try_deterministic_parse(email_data)
        if parsed is None:
            parsed = extract_with_bedrock(email_data)
            method = "ai_fallback"
            # Fail-closed validation gate on AI output: a prompt-injected
            # email body could steer the model into returning arbitrary
            # field values, so enforce the same structural contract on both
            # parse paths BEFORE any DynamoDB write.
            ok, val_reason = validate_ai_fallback(parsed)
            if not ok:
                logger.warning(
                    f"AI-fallback validation failed ({val_reason}), skipping: {key}"
                )
                emit_parse_metric(
                    "ai_fallback_rejected",
                    template_id,
                    val_reason,
                    parsed.get("work_order_id") if isinstance(parsed, dict) else None,
                )
                continue
        logger.info(
            f"Parsed ({method}/{template_id}/{reason}): "
            f"type={parsed.get('email_type')}, wo={parsed.get('work_order_id')}"
        )

        emit_parse_metric(method, template_id, reason, parsed.get("work_order_id"))

        # work_order_id becomes a DynamoDB partition key and the leading, '#'-
        # delimited segment of the comment_id range key, so it must be digits
        # only. The template path already guarantees this via validate(); the
        # AI-fallback path returns raw model output, which a prompt-injected
        # email body could steer into a non-numeric or '#'-bearing value that
        # forges key segments or lands on an arbitrary WO. Enforce the same
        # contract on both paths and skip (fail closed) on a violation.
        # [0-9] not \d: \d is Unicode-aware and would admit fullwidth digits
        # (e.g. "１２３４５") as a distinct-but-lookalike partition key.
        work_order_id = parsed.get("work_order_id")
        if not work_order_id or not re.fullmatch(r"[0-9]+", str(work_order_id)):
            logger.warning(f"Missing or non-numeric work order ID, skipping: {key}")
            continue

        # Always upsert the work order with any new info
        save_work_order(parsed, s3_key)

        # Save every email as an event for history tracking. The raw object key
        # (not the s3:// URI) drives the retry-idempotent comment_id suffix;
        # the parse method decides whether comment_time may enter the key (A1).
        save_event(parsed, s3_key, key, method, email_data.get("date"))

    return {"statusCode": 200, "body": "OK"}