dohertj2/chat
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

feat: async significance pass with auto-pin on score 3

Browse Source
This commit is contained in:
Joseph Doherty
2026-04-26 13:27:25 -04:00
parent a45dabb6ae
commit eb4cdf9cbb
9 changed files with 588 additions and 7 deletions
Download Patch File Download Diff File Expand all files Collapse all files
tests/test_memory_write.py
+9 -2
View File
@@ -64,7 +64,7 @@ def test_record_turn_memory_writes_event_and_projects(tmp_path):
apply_migrations(db)
_seed_minimal(db)
with open_db(db) as conn:
eid = record_turn_memory(
eid, mid = record_turn_memory(
conn,
chat_id="chat_bot_a",
host_bot_id="bot_a",
@@ -73,6 +73,7 @@ def test_record_turn_memory_writes_event_and_projects(tmp_path):
chat_clock_at="2026-04-26T20:00:00+00:00",
)
assert eid > 0
assert mid is not None and mid > 0
rows = conn.execute(
"SELECT id, owner_id, chat_id, pov_summary, "
@@ -110,13 +111,14 @@ def test_record_turn_memory_omits_optional_fields(tmp_path):
_seed_minimal(db)
with open_db(db) as conn:
# Call without scene_id/chat_clock_at — should default to None.
eid = record_turn_memory(
eid, mid = record_turn_memory(
conn,
chat_id="chat_bot_a",
host_bot_id="bot_a",
narrative_text="A simple memory.",
)
assert eid > 0
assert mid is not None and mid > 0
row = conn.execute(
"SELECT scene_id, chat_clock_at, source, reliability, "
@@ -168,6 +170,11 @@ def client(tmp_path, monkeypatch):
app.dependency_overrides[get_llm_client] = lambda: mock
with TestClient(app) as c:
# Disable the lifespan-managed background worker — it would try
# to call Featherless with the test API key. The unit tests in
# test_significance.py exercise the worker directly with a mock
# factory; here we only care about the synchronous turn flow.
app.state.background_worker.enabled = False
c.mock_llm = mock # type: ignore[attr-defined]
yield c
tests/test_significance.py
+237
View File
@@ -0,0 +1,237 @@
"""Async significance pass with auto-pin on score 3 (T22).
After ``assistant_turn`` lands the turn flow enqueues a SignificanceJob on
a background asyncio worker. The worker calls a classifier (per §11.1,
score 0-3) and writes a ``memory_significance_set`` event. On score 3 the
memory is auto-pinned and a soft cap of 8 pins per owner is enforced —
when the cap is exceeded the oldest auto-pin (excluding the just-pinned
row) is unpinned via another ``memory_pin_changed`` event.
"""
from __future__ import annotations
import asyncio
import json
import pytest
from chat.config import load_settings
from chat.db.connection import open_db
from chat.db.migrate import apply_migrations
from chat.eventlog.log import append_event
from chat.eventlog.projector import project
from chat.llm.mock import MockLLMClient
from chat.services.background import BackgroundWorker, SignificanceJob
from chat.services.significance import compute_significance
# Trigger handler registration for projection.
import chat.state.entities # noqa: F401
import chat.state.memory # noqa: F401
import chat.state.world # noqa: F401
async def test_compute_significance_parses_score():
canned = json.dumps({"score": 2, "reason": "notable"})
mock = MockLLMClient(canned=[canned])
score = await compute_significance(
mock,
model="x",
narrative_text="...",
prior_dialogue=[],
)
assert score == 2
async def test_compute_significance_default_on_failure():
# Both attempts return non-JSON text; the classify wrapper falls back
# to the SignificanceVerdict default (score=1, "fallback").
mock = MockLLMClient(canned=["nope", "still nope"])
score = await compute_significance(
mock,
model="x",
narrative_text="...",
prior_dialogue=[],
)
assert score == 1
async def test_background_worker_processes_job_and_updates_significance(
tmp_path, monkeypatch
):
cfg = tmp_path / "config.toml"
cfg.write_text('featherless_api_key = "test"\n')
monkeypatch.setenv("CHAT_CONFIG_PATH", str(cfg))
db = tmp_path / "test.db"
monkeypatch.setenv("CHAT_DB_PATH", str(db))
apply_migrations(db)
settings = load_settings()
# Seed bot, chat, memory.
with open_db(db) as conn:
append_event(
conn,
kind="bot_authored",
payload={
"id": "bot_a",
"name": "BotA",
"persona": "...",
"voice_samples": [],
"traits": [],
"backstory": "",
"initial_relationship_to_you": "",
"kickoff_prose": "",
},
)
append_event(
conn,
kind="chat_created",
payload={
"id": "chat_bot_a",
"host_bot_id": "bot_a",
"initial_time": "2026-04-26T20:00:00+00:00",
"narrative_anchor": "Day 1",
"weather": "",
},
)
append_event(
conn,
kind="memory_written",
payload={
"owner_id": "bot_a",
"chat_id": "chat_bot_a",
"pov_summary": "Some scene",
"witness_you": 1,
"witness_host": 1,
"witness_guest": 0,
"source": "direct",
"reliability": 1.0,
"significance": 1,
"pinned": 0,
"auto_pinned": 0,
},
)
project(conn)
memory_id = conn.execute(
"SELECT id FROM memories WHERE owner_id = 'bot_a'"
).fetchone()[0]
# Worker with mock LLM that returns score=3 (pivotal).
canned = [json.dumps({"score": 3, "reason": "pivotal"})]
factory = lambda: MockLLMClient(canned=list(canned))
worker = BackgroundWorker(settings, llm_client_factory=factory)
await worker.start()
worker.enqueue(
SignificanceJob(
memory_id=memory_id,
narrative_text="...",
prior_dialogue=[],
host_bot_id="bot_a",
)
)
# Drain via stop sentinel — guarantees the prior job completed.
await worker.stop()
# Verify significance updated AND memory auto-pinned.
with open_db(db) as conn:
row = conn.execute(
"SELECT significance, pinned, auto_pinned FROM memories "
"WHERE id = ?",
(memory_id,),
).fetchone()
assert row[0] == 3
assert row[1] == 1 # pinned
assert row[2] == 1 # auto_pinned
async def test_auto_pin_evicts_oldest_when_over_cap(tmp_path, monkeypatch):
"""Pin 9 memories with score 3; verify only 8 are pinned at the end."""
cfg = tmp_path / "config.toml"
cfg.write_text('featherless_api_key = "test"\n')
monkeypatch.setenv("CHAT_CONFIG_PATH", str(cfg))
db = tmp_path / "test.db"
monkeypatch.setenv("CHAT_DB_PATH", str(db))
apply_migrations(db)
settings = load_settings()
with open_db(db) as conn:
append_event(
conn,
kind="bot_authored",
payload={
"id": "bot_a",
"name": "BotA",
"persona": "...",
"voice_samples": [],
"traits": [],
"backstory": "",
"initial_relationship_to_you": "",
"kickoff_prose": "",
},
)
append_event(
conn,
kind="chat_created",
payload={
"id": "chat_bot_a",
"host_bot_id": "bot_a",
"initial_time": "2026-04-26T20:00:00+00:00",
"narrative_anchor": "Day 1",
"weather": "",
},
)
for i in range(9):
append_event(
conn,
kind="memory_written",
payload={
"owner_id": "bot_a",
"chat_id": "chat_bot_a",
"pov_summary": f"memory {i}",
"witness_you": 1,
"witness_host": 1,
"witness_guest": 0,
"source": "direct",
"reliability": 1.0,
"significance": 1,
"pinned": 0,
"auto_pinned": 0,
},
)
project(conn)
memory_ids = [
r[0]
for r in conn.execute(
"SELECT id FROM memories WHERE owner_id = 'bot_a' ORDER BY id"
).fetchall()
]
# Each job runs through its own MockLLMClient with one canned response.
factory = lambda: MockLLMClient(
canned=[json.dumps({"score": 3, "reason": "pivotal"})]
)
worker = BackgroundWorker(settings, llm_client_factory=factory)
await worker.start()
for mid in memory_ids:
worker.enqueue(
SignificanceJob(
memory_id=mid,
narrative_text="...",
prior_dialogue=[],
host_bot_id="bot_a",
)
)
await worker.stop()
with open_db(db) as conn:
pinned_count = conn.execute(
"SELECT COUNT(*) FROM memories "
"WHERE owner_id = 'bot_a' AND pinned = 1"
).fetchone()[0]
assert pinned_count == 8
# The oldest should have been evicted.
first_id = memory_ids[0]
first_pinned = conn.execute(
"SELECT pinned FROM memories WHERE id = ?", (first_id,)
).fetchone()[0]
assert first_pinned == 0
tests/test_turn_flow.py
+5
View File
@@ -58,6 +58,11 @@ def client(tmp_path, monkeypatch):
app.dependency_overrides[get_llm_client] = lambda: mock
with TestClient(app) as c:
# Disable the lifespan-managed background worker — it would
# otherwise try to score significance through Featherless with
# a fake test API key. Worker behavior is exercised directly in
# tests/test_significance.py with a mock LLM factory.
app.state.background_worker.enabled = False
c.mock_llm = mock # type: ignore[attr-defined]
yield c