291 lines
9.5 KiB
Python
291 lines
9.5 KiB
Python
"""Per-turn memory writes (T21).
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After ``assistant_turn`` lands the turn flow records a ``memory_written``
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event for each present POV owner. Phase 1 single-bot turns only have the
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host bot as a memory-store owner — ``you`` doesn't have a memory store in
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v1 — so we write exactly one row per turn with witness flags
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``[you=1, host=1, guest=0]``. The ``pov_summary`` is the assistant's raw
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narrative text; T27 rewrites at scene close into per-POV summary form.
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"""
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from __future__ import annotations
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import json
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from pathlib import Path
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import pytest
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from fastapi.testclient import TestClient
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from chat.app import app
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from chat.db.connection import open_db
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from chat.db.migrate import apply_migrations
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from chat.eventlog.log import append_event
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from chat.eventlog.projector import project
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from chat.llm.mock import MockLLMClient
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from chat.services.memory_write import record_turn_memory
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import chat.state.entities # noqa: F401 - register handlers
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import chat.state.memory # noqa: F401
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import chat.state.world # noqa: F401
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def _seed_minimal(db_path: Path) -> None:
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"""Author a bot and create a chat — bare minimum for memory writes."""
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with open_db(db_path) as conn:
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append_event(
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conn,
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kind="bot_authored",
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payload={
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"id": "bot_a",
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"name": "BotA",
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"persona": "...",
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"voice_samples": [],
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"traits": [],
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"backstory": "",
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"initial_relationship_to_you": "",
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"kickoff_prose": "",
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},
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)
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append_event(
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conn,
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kind="chat_created",
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payload={
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"id": "chat_bot_a",
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"host_bot_id": "bot_a",
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"initial_time": "2026-04-26T20:00:00+00:00",
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"narrative_anchor": "Day 1",
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"weather": "",
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},
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)
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project(conn)
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def test_record_turn_memory_writes_event_and_projects(tmp_path):
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db = tmp_path / "t.db"
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apply_migrations(db)
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_seed_minimal(db)
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with open_db(db) as conn:
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eid, mid = record_turn_memory(
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conn,
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chat_id="chat_bot_a",
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host_bot_id="bot_a",
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narrative_text="BotA looks up. 'You're back late.'",
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scene_id=None,
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chat_clock_at="2026-04-26T20:00:00+00:00",
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)
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assert eid > 0
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assert mid is not None and mid > 0
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rows = conn.execute(
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"SELECT id, owner_id, chat_id, pov_summary, "
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"witness_you, witness_host, witness_guest, "
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"source, reliability, significance, pinned, auto_pinned, "
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"chat_clock_at "
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"FROM memories WHERE owner_id = ?",
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("bot_a",),
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).fetchall()
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assert len(rows) == 1
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m = rows[0]
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assert m[1] == "bot_a"
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assert m[2] == "chat_bot_a"
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assert "looks up" in m[3]
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assert m[4] == 1 # witness_you
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assert m[5] == 1 # witness_host
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assert m[6] == 0 # witness_guest
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assert m[7] == "direct"
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assert m[8] == 1.0 # reliability default
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assert m[9] == 1 # significance default
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assert m[10] == 0 # pinned default
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assert m[11] == 0 # auto_pinned default
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assert m[12] == "2026-04-26T20:00:00+00:00"
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# And the underlying event_log row is the canonical source.
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cur = conn.execute(
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"SELECT COUNT(*) FROM event_log WHERE kind = 'memory_written'"
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)
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assert cur.fetchone()[0] == 1
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def test_record_turn_memory_omits_optional_fields(tmp_path):
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db = tmp_path / "t.db"
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apply_migrations(db)
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_seed_minimal(db)
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with open_db(db) as conn:
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# Call without scene_id/chat_clock_at — should default to None.
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eid, mid = record_turn_memory(
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conn,
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chat_id="chat_bot_a",
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host_bot_id="bot_a",
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narrative_text="A simple memory.",
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)
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assert eid > 0
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assert mid is not None and mid > 0
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row = conn.execute(
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"SELECT scene_id, chat_clock_at, source, reliability, "
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"significance, pinned, auto_pinned "
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"FROM memories WHERE owner_id = 'bot_a'"
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).fetchone()
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assert row is not None
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scene_id, chat_clock_at, source, reliability, significance, pinned, auto_pinned = row
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assert scene_id is None
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assert chat_clock_at is None
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assert source == "direct"
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assert reliability == 1.0
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assert significance == 1
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assert pinned == 0
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assert auto_pinned == 0
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# ---------------------------------------------------------------------------
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# Integration: POST /chats/<id>/turns produces a memory_written event.
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# ---------------------------------------------------------------------------
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@pytest.fixture
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def client(tmp_path, monkeypatch):
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cfg = tmp_path / "config.toml"
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cfg.write_text('featherless_api_key = "test"\n')
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monkeypatch.setenv("CHAT_CONFIG_PATH", str(cfg))
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db = tmp_path / "test.db"
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monkeypatch.setenv("CHAT_DB_PATH", str(db))
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canned_parse = json.dumps(
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{"segments": [{"kind": "dialogue", "text": "hello"}]}
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)
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canned_response = "BotA nods. 'Hi there.'"
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canned_state_update = json.dumps(
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{"affinity_delta": 0, "trust_delta": 0, "knowledge_facts": []}
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)
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from chat.web.kickoff import get_llm_client
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mock = MockLLMClient(
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canned=[
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canned_parse,
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canned_response,
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canned_state_update,
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canned_state_update,
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]
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)
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app.dependency_overrides[get_llm_client] = lambda: mock
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with TestClient(app) as c:
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# Disable the lifespan-managed background worker — it would try
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# to call Featherless with the test API key. The unit tests in
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# test_significance.py exercise the worker directly with a mock
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# factory; here we only care about the synchronous turn flow.
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app.state.background_worker.enabled = False
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c.mock_llm = mock # type: ignore[attr-defined]
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yield c
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app.dependency_overrides.clear()
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def _seed_full(db_path: Path) -> None:
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"""Seed enough state for a full turn flow (matches test_turn_flow.py)."""
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with open_db(db_path) as conn:
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append_event(
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conn,
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kind="bot_authored",
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payload={
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"id": "bot_a",
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"name": "BotA",
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"persona": "thoughtful, observant",
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"voice_samples": [],
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"traits": [],
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"backstory": "",
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"initial_relationship_to_you": "",
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"kickoff_prose": "...",
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},
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)
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append_event(
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conn,
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kind="chat_created",
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payload={
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"id": "chat_bot_a",
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"host_bot_id": "bot_a",
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"initial_time": "2026-04-26T20:00:00+00:00",
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"narrative_anchor": "Day 1",
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"weather": "",
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},
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)
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append_event(
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conn,
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kind="edge_update",
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payload={
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"source_id": "bot_a",
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"target_id": "you",
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"chat_id": "chat_bot_a",
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"knowledge_facts": ["coworker"],
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},
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)
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append_event(
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conn,
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kind="activity_change",
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payload={
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"entity_id": "you",
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"posture": "sitting",
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"action": {
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"verb": "talking",
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"interruptible": True,
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"required_attention": "low",
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"expected_duration": "ongoing",
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},
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"attention": "",
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"holding": [],
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"status": {},
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},
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)
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append_event(
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conn,
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kind="activity_change",
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payload={
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"entity_id": "bot_a",
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"posture": "sitting",
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"action": {
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"verb": "listening",
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"interruptible": True,
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"required_attention": "low",
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"expected_duration": "ongoing",
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},
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"attention": "",
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"holding": [],
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"status": {},
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},
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)
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project(conn)
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def test_post_turn_writes_memory_for_host_bot(client, tmp_path):
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"""After a POST turn, exactly one memory_written event is appended and
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a corresponding memory row is projected for the host bot's POV."""
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_seed_full(tmp_path / "test.db")
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response = client.post(
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"/chats/chat_bot_a/turns", data={"prose": "hello"}
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)
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assert response.status_code == 204
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with open_db(tmp_path / "test.db") as conn:
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cur = conn.execute(
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"SELECT COUNT(*) FROM event_log WHERE kind = 'memory_written'"
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)
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assert cur.fetchone()[0] == 1
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cur = conn.execute(
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"SELECT owner_id, chat_id, pov_summary, "
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"witness_you, witness_host, witness_guest, source, significance "
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"FROM memories"
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)
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rows = cur.fetchall()
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assert len(rows) == 1
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owner_id, chat_id, pov_summary, w_you, w_host, w_guest, source, sig = rows[0]
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assert owner_id == "bot_a"
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assert chat_id == "chat_bot_a"
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# pov_summary is the assistant's narrative text (Phase 1 simplification).
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assert pov_summary == "BotA nods. 'Hi there.'"
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assert w_you == 1
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assert w_host == 1
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assert w_guest == 0
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assert source == "direct"
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assert sig == 1
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