feat: wire embedding worker call sites in turns/meanwhile/skip/regenerate (T97.5)

tests/test_phase4_integration.py

@@ -0,0 +1,180 @@
+"""Phase 4 cross-feature integration tests (T97 follow-up).
+
+Wave 8 / T101 will populate this file with the full Phase 4 retrieval +
+embedding integration suite. For now this houses a single test pinning
+the T97.5 wiring: the production turn route plumbs ``app=request.app``
+all the way through ``record_turn_memory_for_present`` so the embedding
+worker actually receives jobs in production. Without this fix-up the
+plumbing added in T97 was dormant — every per-witness write took the
+no-app branch and silently dropped the embed enqueue.
+
+The test monkeypatches ``app.state.embedding_worker.enqueue`` to record
+jobs (rather than draining the worker mid-test) so the assertion is
+deterministic and free of asyncio-timing flakiness inside FastAPI's
+TestClient. The bug we're guarding against is "did the call site pass
+``app`` at all" — the worker's drain path is exercised in
+:mod:`tests.test_embedding_worker`, so duplicating that here would add
+no coverage.
+"""
+
+from __future__ import annotations
+
+import json
+from pathlib import Path
+
+import pytest
+from fastapi.testclient import TestClient
+
+from chat.app import app
+from chat.db.connection import open_db
+from chat.eventlog.log import append_event
+from chat.eventlog.projector import project
+from chat.llm.mock import MockLLMClient
+
+
+def _zero_state() -> str:
+    return json.dumps(
+        {"affinity_delta": 0, "trust_delta": 0, "knowledge_facts": []}
+    )
+
+
+def _override_llm(canned: list[str]) -> MockLLMClient:
+    from chat.web.kickoff import get_llm_client
+
+    mock = MockLLMClient(canned=list(canned))
+    app.dependency_overrides[get_llm_client] = lambda: mock
+    return mock
+
+
+@pytest.fixture
+def app_state_setup(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))
+    with TestClient(app) as c:
+        # The background worker is disabled so the canned-response queue
+        # is consumed only by the request path. The embedding worker
+        # stays "started" but its loop won't observe the captured
+        # enqueues — we replace ``enqueue`` on the worker instance below.
+        app.state.background_worker.enabled = False
+        yield c
+    app.dependency_overrides.clear()
+
+
+def _seed(db_path: Path) -> None:
+    """Mirror of ``tests/test_turn_flow.py::_seed`` — single bot + chat
+    + edge + activities so the prompt assembler has something to render.
+    """
+    with open_db(db_path) as conn:
+        append_event(
+            conn,
+            kind="bot_authored",
+            payload={
+                "id": "bot_a",
+                "name": "BotA",
+                "persona": "thoughtful, observant",
+                "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="edge_update",
+            payload={
+                "source_id": "bot_a",
+                "target_id": "you",
+                "chat_id": "chat_bot_a",
+                "knowledge_facts": ["coworker"],
+            },
+        )
+        for entity_id, verb in [("you", "talking"), ("bot_a", "listening")]:
+            append_event(
+                conn,
+                kind="activity_change",
+                payload={
+                    "entity_id": entity_id,
+                    "posture": "sitting",
+                    "action": {
+                        "verb": verb,
+                        "interruptible": True,
+                        "required_attention": "low",
+                        "expected_duration": "ongoing",
+                    },
+                    "attention": "",
+                    "holding": [],
+                    "status": {},
+                },
+            )
+        project(conn)
+
+
+def test_post_turn_embeddings_indexed_via_worker_hook(
+    app_state_setup, tmp_path
+):
+    """POST a turn; the route must pass ``app=request.app`` into
+    ``record_turn_memory_for_present`` so the per-witness write enqueues
+    an :class:`EmbeddingJob` on ``app.state.embedding_worker``.
+
+    Without the T97.5 wiring this test fails: the call site previously
+    omitted ``app=`` and the helper's ``app is None`` branch silently
+    skipped every enqueue. We monkeypatch ``enqueue`` on the live
+    embedding worker (rather than draining the queue mid-request) so the
+    assertion does not depend on asyncio scheduling inside the
+    TestClient — the bug is in the wiring, and the wiring is what we
+    pin. The drain path is covered separately in
+    :mod:`tests.test_embedding_worker`.
+    """
+    _seed(tmp_path / "test.db")
+
+    canned_parse = json.dumps(
+        {"segments": [{"kind": "dialogue", "text": "hello"}]}
+    )
+    _override_llm(
+        [canned_parse, "Hi there.", _zero_state(), _zero_state()]
+    )
+
+    captured: list = []
+    worker = app.state.embedding_worker
+    original_enqueue = worker.enqueue
+    worker.enqueue = captured.append  # type: ignore[assignment]
+    try:
+        response = app_state_setup.post(
+            "/chats/chat_bot_a/turns", data={"prose": "hello"}
+        )
+        assert response.status_code == 204
+    finally:
+        worker.enqueue = original_enqueue  # type: ignore[assignment]
+        app.dependency_overrides.clear()
+
+    # Single-bot turn -> one ``memory_written`` -> one EmbeddingJob.
+    # The job's ``memory_id`` should match the freshly-projected memory
+    # row, and its ``text`` should carry the assistant's narrative text.
+    assert len(captured) == 1
+    job = captured[0]
+    assert job.text == "Hi there."
+
+    with open_db(tmp_path / "test.db") as conn:
+        memory_ids = [
+            r[0]
+            for r in conn.execute(
+                "SELECT id FROM memories WHERE owner_id = ?",
+                ("bot_a",),
+            ).fetchall()
+        ]
+    assert job.memory_id in memory_ids