mirror of
https://github.com/Sea-Haven-Industries/procurement-ingest.git
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The From header and any raw-MIME Authentication-Results copies are attacker-forgeable, so a forged email to apm@int.seahaven.com or amazon_po@int.seahaven.com could create or mutate a WO/PO (INFRA-107, CRITICAL). Both S3-triggered email processors now authenticate the sender against the Authentication-Results header SES itself prepends at delivery: only the topmost header is consulted, its authserv-id must be amazonses.com, and it must carry dkim=pass for a domain in the per-pipeline ALLOWED_DKIM_DOMAINS env var (comma-separated, set in CDK so ops can adjust without code changes). Allowlists come from live traffic observed 2026-07-15 on both ingest buckets: WO mail arrives via the apm@ Google Groups forward, which re-signs as seahaven.com (the hxgnsmartcloud.com signature does not survive the forward); PO mail passes for amazon.coupahost.com. amazonses.com also passes on PO mail but is deliberately excluded -- every SES customer's outbound mail passes for it. Every failure path (env var unset, header missing or unparseable, verdict fail, unaligned domain) rejects the email: a structured warning with the reason and S3 key is logged and the record skipped without erroring the invocation, so rejected mail causes no Lambda retries or DLQ messages. Handler signatures and event sources are unchanged. Refs: INFRA-107
510 lines
19 KiB
Python
510 lines
19 KiB
Python
"""
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PO email processor Lambda.
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Triggered by S3 events when SES delivers a Coupa PO 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 the purchase-orders DynamoDB table.
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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 decimal import Decimal
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from email import policy
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import anthropic
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import boto3
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from ses_auth import authenticate_inbound_email
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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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PO_TABLE = os.environ.get("PO_TABLE", "purchase-orders")
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ANTHROPIC_API_KEY_SECRET_ARN = os.environ.get("ANTHROPIC_API_KEY_SECRET_ARN")
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# "Cancelled" is a sticky, authoritative status: once a PO reaches it, a later
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# new_po/revision may enrich other fields but must never move it back to a
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# non-cancelled status.
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CANCELLED_STATUS = "Cancelled"
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EXTRACTION_PROMPT = """\
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You are an email parser for a purchase order ingest pipeline.
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The emails are Coupa procurement platform notifications containing purchase order
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data from Amazon.
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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_po" | "revision" | "cancellation",
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"po_number": "string or null",
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"po_status": "string or null",
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"source_system": "coupa",
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"submitted_by": "string or null",
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"on_behalf_of": "string or null",
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"order_date": "string or null",
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"revision_date": "string or null",
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"last_opened": "string or null",
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"acknowledged_at": "string or null",
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"payment_terms": "string or null",
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"requisition_number": "string or null",
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"department": "string or null",
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"view_order_url": "URL string or null",
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"supplier": {
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"name": "string or null"
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},
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"site_code": "string or null",
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"ship_to": {
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"name": "string or null",
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"address": "string or null",
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"street": "string or null",
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"city": "string or null",
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"state": "string or null",
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"zip": "string or null",
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"location_code": "string or null",
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"attn": "string or null"
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},
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"total_amount": 0.0,
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"currency": "USD",
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"fiscal_year": "string or null",
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"trade": "string or null",
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"coupa_category": "string or null",
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"line_items": [
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{
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"description": "string",
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"amount": 0.0,
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"currency": "USD",
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"need_by": "date string or null",
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"category": "string or null",
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"account_code": "string or null",
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"period": "string or null",
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"quantity": "string or null",
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"unit": "string or null",
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"price": "string or null"
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}
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]
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}
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## email_type detection
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- "new_po": email announces a new purchase order being issued
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- "revision": email announces a revised/updated purchase order (look for "revised" in subject or body)
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- "cancellation": email announces a PO has been cancelled
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## PO number
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Extract from the email subject or body. Format is a prefix + hyphen + digits:
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- "2D-18206023", "FK-21088051", "B187-17955555"
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## site_code extraction
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The site code is the Amazon facility code — a 3-5 character alphanumeric code identifying
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the delivery site. Check these locations in order:
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1. Ship-to name in parentheses: "Amazon.com Services LLC (KLAL)" → KLAL
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2. Ship-to name after dash: "Amazon.com Services LLC - SNY5" → SNY5
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3. Ship-to ATTN line with dash or en-dash: "ATTN: Wagon Wheel DS Station –WKY3" → WKY3
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4. Ship-to ATTN line directly: "Attn: HJX1" → HJX1
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5. Ship-to name IS the code: if the name is just "DBU2" or similar, use it
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6. Line item description prefix: "DYO1 - Sea Haven Ind - Plumbing Repairs" → DYO1
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7. Line item description in brackets: "[HMK4] Assemble 3 Wire Security Cages" → HMK4
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**Not site codes — do not extract these as site_code:**
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- RME (Amazon Reliability Maintenance Engineering department)
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- BBM (Coupa description format tag)
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- JLL (Jones Lang LaSalle — facilities management vendor)
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- PARAG, ERIK (vendor/person names)
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- Industry acronyms: HVAC, LED, PVC, ADA, OSHA, EMR, BMS, DDC, MRO, NTE, EST
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If the only candidate matches this skip list, set site_code to null.
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## Ship-to address parsing
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Parse the full address into separate fields. Be aware of these common issues:
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- State abbreviation may be missing entirely (e.g., "Tucson, 85704" with no state)
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- Zip codes may lack leading zeros (e.g., "MA 2149" should be zip "02149", "NJ 7001" should be "07001")
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- City names may be misspelled (e.g., "Charoltte" for Charlotte) — extract as-is, do not correct
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- Format varies: "City, ST - ZIP", "City, ST ZIP", "City, ZIP" (no state)
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If state cannot be determined from the address, set ship_to.state to null.
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## fiscal_year
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The calendar year the work covers. Determine from:
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1. The order_date year (primary source)
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2. Need-by dates on line items
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3. Year in line item descriptions (e.g., "HVB2 - 2025 - Plumbing PM" → "2025")
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Use the 4-digit year string (e.g., "2025").
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## trade classification
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Classify the primary trade from line item descriptions. Use the FIRST match in priority order:
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**Plumbing - PM**: "plumbing pm", "plumbing preventative", "plumbing maintenance",
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or BBM format: "Plumbing - Backflow", "Plumbing - Water Heater - Install/Repair"
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**Plumbing - Reactive**: "plumbing" with: "reactive", "emergency", "repair", "clog",
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"unclog", "leak", "flood", "sewer", "drain", "grease trap", "jetter", "water line",
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"toilet", "faucet", "urinal", "pipe"
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**Electrical**: "electrical", "lighting", "ballast", "outlet", "circuit", "panel",
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"generator", "transformer", "conduit" (but NOT if "dock door" context)
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**HVAC**: "hvac", "heating", "cooling", "air conditioning", "RTU", "AHU", "VAV",
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"refrigerant", "thermostat", "ductwork"
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**Dock Doors**: "dock door", "dock leveler", "dock plate", "dock seal", "dock bumper"
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**Doors**: "door", "overhead door", "roll-up", "automatic door", "access door"
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(only if not matched by Dock Doors above)
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**Signage**: "sign", "banner", "wayfinding", "marquee", "directional"
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**Carpentry**: "carpentry", "cabinet", "millwork", "trim", "shelving", "framing"
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**Fencing/Gates**: "fence", "fencing", "gate", "bollard" (not "dock gate")
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**Conveyance/MHE**: "conveyor", "MHE", "material handling", "sortation"
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**Painting**: "paint", "painting", "primer", "coating", "touch-up"
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**Flooring**: "floor", "tile", "carpet", "epoxy", "polishing"
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**Janitorial**: "janitorial", "cleaning", "custodial", "pressure wash", "power wash"
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**Fire/Life Safety**: "fire", "sprinkler", "extinguisher", "fire alarm", "suppression"
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**Landscaping/Yard**: "landscape", "lawn", "tree", "yard", "mowing", "irrigation"
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**Roofing**: "roof", "roofing", "gutter", "downspout"
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**Security/Locksmith**: "lock", "key", "access control", "camera", "security", "CCTV"
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**Snow Removal**: "snow", "ice", "salt", "de-ice", "plow"
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**PO Uplift**: description is exactly or primarily "PO Uplift"
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**General Building - Emergency**: "EMER" prefix, or "emergency" in a general building context
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**General Building - Handyman**: BBM format "General Building - General Building Technician"
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**General Building - Project**: BBM format "General Building - General Building Project"
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**General Building**: any remaining facility maintenance work
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If a PO has multiple line items with different trades, set "trade" to the primary
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(non-uplift, non-materials) trade. If genuinely mixed, use the trade of the highest-value line item.
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## coupa_category
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The Coupa commodity/category field if present in the email (e.g., "Maintenance - Facilities",
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"Plumbing Equipment & Materials"). This is Coupa's own classification, not the trade field.
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## General rules
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- Extract all line items with descriptions, amounts, and metadata
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- "quantity", "unit" (e.g., "EACH", "HR"), and "price" (unit price) should be extracted when present
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- total_amount should be the numeric total in USD
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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.
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Requires ANTHROPIC_API_KEY_SECRET_ARN to be set. The previous silent
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fallback to a plaintext ANTHROPIC_API_KEY env var is removed: a misconfigured
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deploy must fail loudly rather than quietly run on an unmanaged key.
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"""
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if not ANTHROPIC_API_KEY_SECRET_ARN:
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raise RuntimeError(
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"ANTHROPIC_API_KEY_SECRET_ARN is not set; refusing to fall back to a "
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"plaintext API key. Configure the Secrets Manager ARN."
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)
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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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def parse_raw_email(raw_bytes: bytes) -> dict:
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"""Parse a raw MIME email into subject, sender, and 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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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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"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"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=2048,
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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(), parse_float=Decimal)
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def pad_zip(zip_code: str | None) -> str | None:
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if not zip_code:
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return zip_code
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clean = zip_code.strip().split("-")[0]
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if clean.isdigit() and len(clean) < 5:
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return clean.zfill(5) + zip_code.strip()[len(clean) :]
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return zip_code
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def enrich_parsed(parsed: dict, s3_key: str, email_subject: str):
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"""Add metadata and promote nested fields to top level."""
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now = datetime.utcnow().isoformat()
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parsed["raw_s3_key"] = s3_key
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parsed["processed_at"] = now
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parsed["data_source"] = "email"
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parsed["email_subject"] = email_subject
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ship_to = parsed.get("ship_to") or {}
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if ship_to.get("address"):
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parsed["ship_to_raw"] = ship_to["address"]
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if ship_to.get("state"):
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parsed["state"] = ship_to["state"]
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if ship_to.get("zip"):
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ship_to["zip"] = pad_zip(ship_to["zip"])
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return parsed
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def _write_fields(po_number: str, fields: dict, *, guard_cancelled: bool):
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"""SET the given non-null fields on a PO record via update_item.
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Only the fields supplied are written; absent fields are left untouched, so a
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partial payload can never delete data that an earlier email established. The
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record is created if it does not exist (DynamoDB update_item upsert).
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When ``guard_cancelled`` is True the write carries a ConditionExpression that
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only permits it while the record is not already Cancelled. The condition is
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evaluated atomically by DynamoDB at write time, so a cancellation that lands
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first always wins — there is no read-then-write TOCTOU window. A failed guard
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raises ConditionalCheckFailedException for the caller to handle.
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"""
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table = dynamodb.Table(PO_TABLE)
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set_parts = []
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attr_names = {}
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attr_values = {}
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for key, value in fields.items():
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if value is None or key == "po_number":
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continue
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name_ph = f"#{key}"
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val_ph = f":{key}"
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attr_names[name_ph] = key
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attr_values[val_ph] = value
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set_parts.append(f"{name_ph} = {val_ph}")
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if not set_parts:
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return
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params = {
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"Key": {"po_number": po_number},
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"UpdateExpression": "SET " + ", ".join(set_parts),
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"ExpressionAttributeNames": attr_names,
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"ExpressionAttributeValues": attr_values,
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}
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if guard_cancelled:
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params["ExpressionAttributeValues"][":__cancelled_marker"] = CANCELLED_STATUS
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params["ConditionExpression"] = (
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"attribute_not_exists(po_status) OR po_status <> :__cancelled_marker"
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)
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table.update_item(**params)
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def _merge_update(po_number: str, fields: dict):
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"""Merge (SET-only) the given fields onto a PO record, keeping Cancelled sticky.
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Only the fields supplied are written; absent fields are left untouched. The
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record is created if it does not exist (DynamoDB update_item upsert).
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"Cancelled" is a sticky, authoritative status. When the incoming payload
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carries a non-cancelled ``po_status``, the write is guarded by a
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ConditionExpression so the status is only applied while the record is not
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already Cancelled — enforced atomically at write time, eliminating the
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read-then-write TOCTOU where a concurrently-landing cancellation could be
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silently un-cancelled. If the guard fails (the PO is already Cancelled), the
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same fields are re-written WITHOUT po_status/cancelled_at and
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unconditionally, so the other fields still merge while the Cancelled status
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stays intact.
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A payload with no ``po_status``, or one whose status is already "Cancelled",
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needs no guard — a plain merge is correct. This is what keeps legitimate
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status updates (non-cancelled PO) and status-less revisions from ever being
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dropped: the status is only ever suppressed on a true un-cancel transition.
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"""
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incoming_status = fields.get("po_status")
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if incoming_status is None or incoming_status == CANCELLED_STATUS:
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_write_fields(po_number, fields, guard_cancelled=False)
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return
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try:
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_write_fields(po_number, fields, guard_cancelled=True)
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except dynamodb.meta.client.exceptions.ConditionalCheckFailedException:
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logger.info(
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f"PO {po_number} is Cancelled; suppressing incoming "
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f"po_status={incoming_status!r} and merging remaining fields"
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)
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enrich_fields = {
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k: v for k, v in fields.items() if k not in ("po_status", "cancelled_at")
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}
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_write_fields(po_number, enrich_fields, guard_cancelled=False)
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def save_new_po(parsed: dict):
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"""Create a PO, merging into any pre-existing record.
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Uses a merge update rather than a conditional put so that an out-of-order
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cancellation (which leaves a Cancelled skeleton) is filled in with the full
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PO data instead of the new_po being silently dropped. "Cancelled" is a sticky
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status enforced atomically inside _merge_update: if the PO was already
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cancelled, the new_po backfills its remaining fields (supplier, line_items,
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amounts) but never un-cancels it.
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"""
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po_number = parsed["po_number"]
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fields = {k: v for k, v in parsed.items() if v is not None}
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_merge_update(po_number, fields)
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logger.info(f"Created/merged PO {po_number}")
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def save_revision(parsed: dict):
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"""Merge revised data into an existing PO without deleting omitted fields.
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A revision email often omits unchanged sections (line_items, supplier). The
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previous full-overwrite put_item permanently dropped those. This SETs only the
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fields present in the revision, leaving everything else intact.
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"Cancelled" is a sticky status: a revision may enrich a cancelled PO's fields
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but must never move it to a non-cancelled status. That invariant is enforced
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atomically inside _merge_update and applies ONLY to the un-cancel transition —
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a revision that carries no status change, or one targeting a non-cancelled PO,
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updates po_status normally.
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"""
|
||
po_number = parsed["po_number"]
|
||
fields = {k: v for k, v in parsed.items() if v is not None}
|
||
_merge_update(po_number, fields)
|
||
logger.info(f"Revised PO {po_number}")
|
||
|
||
|
||
def save_cancellation(parsed: dict):
|
||
"""Mark a PO Cancelled, creating a minimal skeleton if it doesn't exist yet.
|
||
|
||
If the cancellation arrives before the new_po, the skeleton it creates is
|
||
later backfilled by save_new_po (which preserves this Cancelled status), so no
|
||
PO data is lost on out-of-order delivery.
|
||
"""
|
||
table = dynamodb.Table(PO_TABLE)
|
||
|
||
table.update_item(
|
||
Key={"po_number": parsed["po_number"]},
|
||
UpdateExpression="SET po_status = :status, cancelled_at = :cancelled_at, raw_s3_key = :s3_key",
|
||
ExpressionAttributeValues={
|
||
":status": "Cancelled",
|
||
":cancelled_at": parsed.get("processed_at", datetime.utcnow().isoformat()),
|
||
":s3_key": parsed.get("raw_s3_key", ""),
|
||
},
|
||
)
|
||
logger.info(f"Cancelled PO {parsed['po_number']}")
|
||
|
||
|
||
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"]
|
||
s3_key = f"s3://{bucket}/{key}"
|
||
|
||
logger.info(f"Processing email: {s3_key}")
|
||
|
||
response = 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 purchase 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
|
||
|
||
email_data = parse_raw_email(raw_email)
|
||
logger.info(f"Subject: {email_data['subject']}")
|
||
|
||
parsed = extract_with_claude(email_data)
|
||
logger.info(
|
||
f"Parsed: type={parsed.get('email_type')}, po={parsed.get('po_number')}"
|
||
)
|
||
|
||
if not parsed.get("po_number"):
|
||
logger.warning(f"No PO number found in email, skipping: {key}")
|
||
continue
|
||
|
||
parsed = enrich_parsed(parsed, s3_key, email_data["subject"])
|
||
|
||
email_type = parsed.get("email_type")
|
||
if email_type == "cancellation":
|
||
save_cancellation(parsed)
|
||
elif email_type == "revision":
|
||
save_revision(parsed)
|
||
else:
|
||
save_new_po(parsed)
|
||
|
||
return {"statusCode": 200, "body": "OK"}
|