Files
ten31-database/backend/matrix_intake/test_parse.py
T
Keysat 7ad0ee7624 Add Matrix intake bot (M1+M2): typed message → approved fundraising-grid write
New backend/matrix_intake/ runs as its own process (matrix-nio isolated from the
stdlib CRM): local-Qwen parse via Spark Control → in-thread human approval
(yes/edit/no) → write through the CRM's own log-communication endpoint, tagged
source=matrix_intake. Adds read-only GET /api/intake/match (returns grid row id,
no-duplicate contract); threads provenance through handle_log_fundraising_communication.
Reviewer-passed: pop-before-commit closes a double-approve race; edit-grammar fix.
Text-only v1; business-card photo (M3) deferred (no Spark vision model).
26/26 tests green; live Matrix smoke pending deploy.
2026-06-17 07:51:27 -05:00

94 lines
3.2 KiB
Python

"""Tests for the intake parse/normalize layer — Spark/Qwen stubbed (no network)."""
import os
import sys
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
import parse # noqa: E402
def _stub(reply):
"""Return a parse_fn that ignores input and yields `reply` (simulating Qwen's JSON)."""
return lambda text, system=None, max_tokens=400: reply
def test_new_investor_basic():
p = parse.parse_message(
"New investor Acme Capital, contact Jane Doe jane@acme.com, met at the Austin conf",
parse_fn=_stub({"intent": "new_investor", "investor_name": "Acme Capital",
"contact_name": "Jane Doe", "contact_email": "jane@acme.com",
"contact_title": None, "note": "met at the Austin conf"}),
)
assert p["intent"] == "new_investor"
assert p["investor_name"] == "Acme Capital"
assert p["contact_email"] == "jane@acme.com"
def test_email_salvaged_from_source_when_model_misses():
p = parse.parse_message(
"add bob@example.org from Beta LP",
parse_fn=_stub({"intent": "new_investor", "investor_name": "Beta LP",
"contact_name": "Bob", "contact_email": None}),
)
assert p["contact_email"] == "bob@example.org"
def test_fabricated_email_dropped_when_not_in_source():
p = parse.parse_message(
"new prospect Gamma Partners, talked to their GP",
parse_fn=_stub({"intent": "new_investor", "investor_name": "Gamma Partners",
"contact_name": "their GP", "contact_email": "made-up@nowhere.test"}),
)
# the model invented an address that isn't in the source → must be dropped
assert p["contact_email"] is None
def test_meeting_note_intent_preserved():
p = parse.parse_message(
"Note for Acme Capital: wants the Q3 deck",
parse_fn=_stub({"intent": "meeting_note", "investor_name": "Acme Capital",
"note": "wants the Q3 deck"}),
)
assert p["intent"] == "meeting_note"
assert p["note"] == "wants the Q3 deck"
def test_unclear_when_no_entity():
p = parse.parse_message(
"hey what's up",
parse_fn=_stub({"intent": "new_investor", "investor_name": None, "contact_name": None}),
)
assert p["intent"] == "unclear"
def test_null_strings_normalized():
p = parse.parse_message(
"Delta Fund",
parse_fn=_stub({"intent": "new_investor", "investor_name": "Delta Fund",
"contact_name": "null", "contact_email": "N/A", "note": ""}),
)
assert p["contact_name"] is None
assert p["contact_email"] is None
assert p["note"] is None
def test_bad_intent_falls_back_to_unclear():
p = parse.parse_message(
"Epsilon Capital",
parse_fn=_stub({"intent": "garbage", "investor_name": "Epsilon Capital"}),
)
assert p["intent"] == "unclear"
def test_none_model_reply_is_unclear():
p = parse.parse_message("???", parse_fn=_stub(None))
assert p["intent"] == "unclear"
if __name__ == "__main__":
fns = [v for k, v in sorted(globals().items()) if k.startswith("test_") and callable(v)]
for fn in fns:
fn()
print(f"ok {fn.__name__}")
print(f"\n{len(fns)} passed")