6577bb74be
Phase 2 and 3 of the platform rework. - Neutral request/response contract: external_id, metadata, X-AI-Key, run_id in the response; client-specific fields removed. - AI profile is a revision table: saving creates an inactive revision, activation is separate, try-run does not store a run. One chat-completions gateway serves AIHub and OpenAI-compatible profiles. - Add between and in rule operators. - Contracts moved to contracts/lead-scoring/ with a score-response fixture. - Admin Web updated for revisions, runs and the neutral fixture. - Consolidate tests; remove rewrite_architect.md and the stale handoff doc; rewrite spec, CONTEXT and ARCHITECTURE for the current design. Not verified: live AIHub/OpenAI behavior, Omni/EMS integration.
105 lines
3.9 KiB
Python
105 lines
3.9 KiB
Python
import pytest
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from ai_platform.lead_scoring.domain.scoring import (
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Rule,
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ScoringConfiguration,
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derive_metrics,
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score_rules,
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)
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CAPTURED = "2025-09-25T10:00:00Z"
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def _msg(sender, sent_at):
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return {"sender_type": sender, "sent_at": sent_at}
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def _conv(*messages):
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return {"messages": list(messages)}
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def _metrics(*conversations):
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return derive_metrics({"captured_at": CAPTURED, "conversations": list(conversations)})
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def test_counts_and_turns_use_timestamps_not_array_order():
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conversations = [
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_conv(
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_msg("agent", "2025-09-25T11:00:00Z"),
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_msg("contact", "2025-09-25T09:00:00Z"),
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_msg("agent", "2025-09-25T10:00:00Z"),
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),
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_conv(_msg("contact", "2025-09-25T11:00:00Z"), _msg("agent", "2025-09-25T10:00:00Z")),
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]
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metrics = _metrics(*conversations)
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for conversation in conversations:
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conversation["messages"].reverse()
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assert metrics["conversation_turn_count"] == 4
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assert metrics["contact_started_conversation_count"] == 1
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assert metrics["contact_message_count"] == 2
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assert _metrics(*conversations) == metrics
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@pytest.mark.parametrize(
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("sent_at", "hours", "days"),
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[
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("2025-09-25T08:46:00Z", 1.23, 0.05),
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("2025-09-25T08:00:00+02:00", 4.0, 0.17),
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("2025-09-25T11:00:00Z", 0.0, 0.0),
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],
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)
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def test_contact_recency_is_rounded_clamped_and_timezone_aware(sent_at, hours, days):
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metrics = _metrics(_conv(_msg("contact", "not-a-timestamp"), _msg("contact", sent_at)))
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assert metrics["contact_message_recency_hours"] == hours
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assert metrics["contact_message_recency_days"] == days
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def test_no_contact_messages_means_no_recency_and_no_return():
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metrics = _metrics(_conv(), _conv(_msg("agent", "2025-09-25T09:00:00Z")))
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assert metrics["conversation_count"] == 2
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assert metrics["contact_message_count"] == 0
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assert metrics["contact_message_recency_hours"] is None
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assert metrics["customer_initiated_return"] is False
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def test_customer_initiated_return_uses_chronology_and_breaks_ties_by_position():
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agent = _conv(_msg("agent", "2025-09-25T08:00:00Z"))
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contact = _conv(_msg("contact", "2025-09-25T09:00:00Z"))
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later = _conv(_msg("contact", "2025-09-25T10:00:00Z"))
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tie_agent = _conv(_msg("agent", "2025-09-25T07:00:00Z"))
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tie_contact = _conv(_msg("contact", "2025-09-25T07:00:00Z"))
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assert _metrics(later, _conv(), agent, contact)["customer_initiated_return"] is True
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assert _metrics(contact, later, agent)["contact_started_conversation_count"] == 2
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assert _metrics(tie_agent, tie_contact)["customer_initiated_return"] is True
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assert _metrics(tie_contact, tie_agent)["customer_initiated_return"] is False
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def test_caller_rules_see_the_derived_metrics_and_booleans_never_match_numbers():
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snapshot = {
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"captured_at": CAPTURED,
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"lead_profile": {"name": "Example", "email": "a@example.invalid", "custom_fields": {}},
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"conversations": [
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_conv(_msg("contact", "2025-09-24T10:00:00Z"), _msg("agent", "2025-09-25T09:00:00Z")),
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_conv(_msg("bot", "2025-09-25T09:30:00Z")),
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],
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}
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rules = (
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Rule("profile", "metrics.profile_field_count", "eq", 2, 1),
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Rule("conversations", "metrics.conversation_count", "eq", 2, 1),
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Rule("messages", "metrics.message_count", "eq", 3, 1),
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Rule("contacts", "metrics.contact_message_count", "eq", 1, 1),
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Rule("turns", "metrics.conversation_turn_count", "eq", 3, 1),
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Rule("started", "metrics.contact_started_conversation_count", "eq", 1, 1),
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Rule("recency", "metrics.contact_message_recency_days", "eq", 1.0, 1),
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Rule("bool-as-number", "metrics.customer_initiated_return", "eq", 1, 1),
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)
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score, breakdown = score_rules(snapshot, ScoringConfiguration(rules, 1.0, 0.0))
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assert score == 7
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assert [item["matched"] for item in breakdown] == [True] * 7 + [False]
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