procurement-ingest/lambdas/wo/email_processor/tests/test_bedrock_fallback.py
Adam Moussa 89bf47c1bb
Add offline WO parser test suite
Cover the deterministic parser with golden-file tests over 55 real
scrubbed .eml fixtures (both comment sub-shapes, username Submitted-By,
address present/absent, br+CRLF assign addresses), fail-closed
validation-gate rules, adversarial and prompt-injection cases that must
route to ai_fallback or parse without corrupting other fields, the issue
#23 comment_id idempotency invariants, and the Bedrock-fallback dispatch
plus EMF-metric emission with a mocked invoke_model.

Extend pytest.ini testpaths to discover the co-located suite, and update
tests/conftest.load_handler to put a handler's own directory on sys.path
so the WO handler's new `from template_parser import ...` resolves under
the existing shared handler tests. Point test_local.py at the new
template-first + Bedrock flow.

Refs: #23
2026-07-15 20:11:04 -04:00

172 lines
5 KiB
Python

"""End-to-end dispatch tests: the Bedrock AI extractor is invoked ONLY when the
deterministic parse misses, EMF metrics are emitted on both paths, and the
Bedrock response is decoded through the same contract."""
import json
import os
import pytest
import handler
from _wo_parser_support import FIXTURES
def _raw(subdir, stem):
with open(os.path.join(FIXTURES, subdir, f"{stem}.eml"), "rb") as fh:
return fh.read()
class FakeBody:
def __init__(self, data):
self._data = data
def read(self):
return self._data
class FakeS3:
def __init__(self, raw):
self._raw = raw
def get_object(self, Bucket, Key): # noqa: N803
return {"Body": FakeBody(self._raw)}
class FakeBedrock:
def __init__(self, payload):
self.calls = []
self._payload = payload
def invoke_model(self, modelId, body): # noqa: N803
self.calls.append({"modelId": modelId, "body": body})
text = json.dumps(self._payload)
return {"body": FakeBody(json.dumps({"content": [{"text": text}]}).encode())}
AI_17_KEY = {
"email_type": "comment",
"work_order_id": "77777777777",
"description": None,
"status": None,
"site_code": None,
"building": None,
"address": None,
"severity": None,
"priority": None,
"date_reported": None,
"scheduled_start": None,
"due_date": None,
"assigned_to": None,
"commenter": None,
"comment_text": "ai extracted",
"comment_time": None,
}
def _event():
return {
"Records": [
{
"s3": {
"bucket": {"name": "workorder-ingest-emails-x"},
"object": {"key": "inbound/o1"},
}
}
]
}
@pytest.fixture
def metric_spy(monkeypatch):
calls = []
monkeypatch.setattr(
handler,
"emit_parse_metric",
lambda *a: calls.append(a),
)
return calls
def test_template_path_skips_bedrock(fake_dynamo, metric_spy, monkeypatch):
fake_bedrock = FakeBedrock(AI_17_KEY)
monkeypatch.setattr(
handler, "s3", FakeS3(_raw("update-plaintext", "update-plaintext-01"))
)
monkeypatch.setattr(handler, "bedrock", fake_bedrock)
handler.handler(_event(), None)
assert fake_bedrock.calls == [] # deterministic parse handled it
method, template_id, reason, wo = metric_spy[0]
assert method == "template"
assert template_id == "update_plaintext"
assert reason == "ok"
assert wo == "11144580730"
def test_fallback_path_invokes_bedrock(fake_dynamo, metric_spy, monkeypatch):
fake_bedrock = FakeBedrock(AI_17_KEY)
monkeypatch.setattr(handler, "s3", FakeS3(_raw("ai-fallback", "unknown-subject")))
monkeypatch.setattr(handler, "bedrock", fake_bedrock)
handler.handler(_event(), None)
assert len(fake_bedrock.calls) == 1
# Uses the configured inference profile and the bedrock message contract.
call = fake_bedrock.calls[0]
assert call["modelId"] == handler.BEDROCK_MODEL_ID
body = json.loads(call["body"])
assert body["anthropic_version"] == "bedrock-2023-05-31"
assert body["max_tokens"] == 1024
method, _template_id, _reason, wo = metric_spy[0]
assert method == "ai_fallback"
assert wo == "77777777777"
# The AI result was written through to DynamoDB.
wo_table = fake_dynamo.tables[handler.WORK_ORDERS_TABLE]
assert wo_table.updates, "expected a work-order upsert from the AI path"
def test_extract_with_bedrock_returns_full_contract(monkeypatch):
fake_bedrock = FakeBedrock(AI_17_KEY)
monkeypatch.setattr(handler, "bedrock", fake_bedrock)
email_data = {
"subject": "x",
"sender": "a",
"to": "b",
"cc": "",
"date": "d",
"body": "body",
}
out = handler.extract_with_bedrock(email_data)
assert set(out.keys()) == set(AI_17_KEY.keys())
assert len(fake_bedrock.calls) == 1
def test_extract_with_bedrock_strips_markdown_fence(monkeypatch):
class FenceBedrock:
def invoke_model(self, modelId, body): # noqa: N803
fenced = "```json\n" + json.dumps(AI_17_KEY) + "\n```"
return {
"body": FakeBody(json.dumps({"content": [{"text": fenced}]}).encode())
}
monkeypatch.setattr(handler, "bedrock", FenceBedrock())
out = handler.extract_with_bedrock(
{"subject": "", "sender": "", "to": "", "cc": "", "date": "", "body": ""}
)
assert out["work_order_id"] == "77777777777"
def test_emit_parse_metric_writes_emf(capsys):
handler.emit_parse_metric("template", "update_plaintext", "ok", "123")
line = capsys.readouterr().out.strip()
emf = json.loads(line)
assert emf["ParseMethod"] == "template"
assert emf["TemplateId"] == "update_plaintext"
assert emf["ReasonCode"] == "ok"
assert emf["ParseOutcome"] == 1
dims = emf["_aws"]["CloudWatchMetrics"][0]["Dimensions"][0]
assert dims == ["ParseMethod", "TemplateId"]
assert (
emf["_aws"]["CloudWatchMetrics"][0]["Namespace"] == "Seahaven/WorkorderIngest"
)