16 Commits

Author SHA1 Message Date
Joseph Doherty b8335895e1 docs: add Phase 2 implementation plan with parallel-safe waves
13 tasks across 6 waves (1, 2, 3, 4a, 4b, 5). Designed for parallel
subagent execution where file-disjointness allows.

Waves 1, 2, 4a, and 5 each contain 2-3 tasks that touch disjoint files
and can be dispatched concurrently via the Agent tool with
isolation: "worktree". Waves 3 (drawer guest support) and 4b (multi-
entity turn flow) are single-task because they touch hot files
(_drawer.html, turns.py) that cannot be safely co-modified.

Plan covers:
- T36: group_node schema + handlers (new migration 0008)
- T37: guest_added / guest_removed event handlers (modifies world.py)
- T38: relationship-seed service ("have they met?")
- T39: interjection classifier service
- T40: multi-entity state-update coordinator (6 directed pairs)
- T41: multi-witness memory write helper
- T42: drawer guest add/remove UI + render
- T43: multi-entity prompt assembly (extends T18)
- T44: multi-entity turn flow (rewrites post_turn)
- T45: multi-entity per-POV summaries on scene close
- T46: witness filter cross-coverage tests
- T47: bot_reset cascades to guest references
- T48: Phase 2 documentation update

Plan also documents:
- Worktree-per-subagent dispatch pattern using Agent isolation flag
- Merge ordering per wave (file-disjointness = conflict-free merges)
- Failure recovery (cancel failed parallel task, re-dispatch as solo)
- Conflict prevention checklist (verify Files sections disjoint per wave)

Tasks file (.tasks.json) carries dependency DAG with `blockedBy` and
`parallelGroup` so a future executing-plans run can dispatch correctly.

NOT EXECUTING. Plan only.
2026-04-26 15:37:07 -04:00
Joseph Doherty d161e7b8e9 feat: cap narrative response length + tune sampling
Bot replies were running long (4 paragraphs of action+dialogue beats
per turn) because we never set max_tokens on the narrative call. Three
tunable knobs now in Settings (set in data/config.toml to override):

- narrative_max_tokens: int = 400
  Hard cap on each generated response. ~400 tokens ≈ 1–2 short
  paragraphs. Drop to 200 for terse banter, bump to 800+ for longer
  scenes.

- narrative_temperature: float = 0.85
  Sampling temperature. 0.7 = grounded/consistent (slightly stiff),
  0.85 = creative-but-in-character (default), 1.0 = wide variety,
  >1.0 = often off-the-rails.

- prompt closing instruction now nudges: "Keep your response to a
  single beat — one or two short paragraphs at most. Don't monologue;
  leave room for the other person to react."

Both turns.py (post_turn) and regenerate.py forward the params to
client.stream(). FeatherlessClient already passes **params through to
the OpenAI-compat endpoint.

Note: temperature doesn't control length — that was a common
misconception. max_tokens is the actual length cap. Lower temperature
makes word choice more predictable (slightly stiffer voice), not
shorter. Both knobs are useful for different goals.
2026-04-26 15:28:08 -04:00
Joseph Doherty f0742dd4f9 fix: use readOnly (not disabled) to lock textarea during stream
The form-submit handler in chat.html was setting
``textarea.disabled = true`` synchronously before the browser actually
serialized the form. Disabled form fields are excluded from
submission, so the request body contained ``prose=""`` even when the
user had typed text — which the server (correctly) rejected with the
new empty-prose 400. Net effect: typing "hello" + Send gave a "prose
cannot be empty" error.

Switched to ``readOnly``: same UX (user can't edit while streaming)
but the field IS submitted. The unlock path now also clears the
textarea and refocuses for the next turn.
2026-04-26 15:23:06 -04:00
Joseph Doherty 52555e0455 fix: reject empty prose on turn submit
Empty submission was producing a blank user_turn event in the log and
firing the LLM stream anyway — the bot would invent a response from the
kickoff context alone, producing a monologue with no user input. Two-
layer fix:

- Browser: add `required` to the prose textarea in chat.html so the
  form refuses to submit empty.
- Server: 400 in post_turn when prose.strip() is empty. Defense in
  depth — if a client bypasses the textarea attribute (custom UI,
  curl, etc.), the server still rejects.

Verified live: POST with empty body returns 400; POST with whitespace-
only returns 400; chat shell renders the textarea with required.
Full suite: 168 passed.
2026-04-26 15:20:02 -04:00
Joseph Doherty 5c039c8e56 fix: classifier timeout + Featherless concurrency cap
Two related issues blocking real-world use of the kickoff parse:

1. Classifier calls take ~12s end-to-end on Featherless for the
   complex KickoffParse schema (Hermes-3-8B generating ~1.3KB of
   structured JSON). The 10s timeout was firing on most attempts,
   causing all 3 retries to time out and the empty-fallback to render
   with blank form values. Bumping the default
   classifier_timeout_s 10 → 30s gives generous headroom; measured
   p99 is ~13s, so 30s is comfortable.

2. Featherless caps concurrent connections per account (2 on free /
   lower paid tiers). Each turn flow can fire 4–5 calls (parse,
   scene-close detect, narrative stream, two state-update passes)
   plus the background significance worker. Without a gate, we'd
   exceed the cap and fail.

   Added a class-level ``asyncio.Semaphore`` to FeatherlessClient,
   shared across all instances, configured once in lifespan from
   ``Settings.featherless_max_concurrent`` (default 2). Both
   ``generate`` and ``stream`` acquire the semaphore for the duration
   of the call; the stream holds it until the async generator
   completes, so token streaming is correctly accounted for.

Verified live: 4/4 sequential kickoff parses for the same bot all
succeed with real parsed values (previously ~50% blank-fallback).
Full suite: 168 passed.
2026-04-26 15:15:14 -04:00
Joseph Doherty 5aab98e4d7 fix: classifier robustness — schema in prompt, retries, kickoff fallback
The kickoff parse-and-confirm route was 500-ing intermittently because
Hermes-3 + Featherless's response_format={"type":"json_object"} only
guarantees JSON output, NOT a particular schema. The model was inventing
its own field names (sceneTime, entities, settingDetails) instead of
the KickoffParse fields, causing Pydantic validation to fail on both
classify() retries.

Three changes:

1. Include the Pydantic JSON schema in the system prompt so the model
   knows exactly which keys to produce. Affects every classify() call
   (kickoff parse, turn parse, scene-close detect, significance,
   state-update, scene summarize). Strip ```json fences if the model
   wraps its output. Bump retries 2 → 3 (model is stochastic; one extra
   attempt closes most of the remaining gap).

2. parse_kickoff() now passes a default empty KickoffParse so the
   route degrades to a fillable form instead of 500 when the classifier
   ultimately fails. The confirm form is the human-in-the-loop; an
   empty form is strictly better UX than a stack trace.

3. Tests updated: bumped canned-failure arrays from 2 → 3 entries to
   match the new attempt count; renamed kickoff test from
   "raises_when_classifier_fails_twice" to
   "falls_back_to_empty_when_classifier_fails" reflecting the new
   degraded-but-usable behavior.

Verified live with all 3 sample bots (maya/eli/sam) — kickoff route
returns 200 across multiple attempts. Full suite: 168 passed.
2026-04-26 15:03:13 -04:00
Joseph Doherty 12502d6ec7 chore: add scripts/seed_sample_bots.py
Idempotent seeder for three sample bots (Maya — coworker slow-burn,
Eli — live-in partner, Sam — bartender / new connection). Each is a
distinct relational archetype to exercise the system from different
angles. Run from repo root:

    .venv/bin/python scripts/seed_sample_bots.py

Re-running skips ids that already exist. After seeding, walk each bot
through kickoff parse-and-confirm at /bots/<id>/kickoff.
2026-04-26 14:50:06 -04:00
Joseph Doherty 365dacc0d0 chore: post-Phase-1 cleanup — gitignore, packaging, backlog
- .gitignore: add *.egg-info/ so editable installs don't show in git status.
- pyproject.toml: add [build-system] and [tool.setuptools.packages.find]
  scoped to chat*, fixing pip install -e . which was failing on data/
  auto-discovery.
- CLAUDE.md: add Phase 1.5 cleanup backlog section under Phase 1 status,
  capturing the small follow-ups surfaced in implementer reviews
  (open_db refactor, regenerate SSE broadcast, you-activity purge,
  drawer edits for deferred fields, NICE trim order).
2026-04-26 14:39:10 -04:00
Joseph Doherty a302ed427a feat: error banners and first-run navigation flow 2026-04-26 14:33:28 -04:00
Joseph Doherty 0353d592cd feat: streaming UX with Stop, disconnect handling, send-lock 2026-04-26 14:27:39 -04:00
Joseph Doherty 330077afcf feat: transcript display formatting with markdown and OOC styling 2026-04-26 14:22:43 -04:00
Joseph Doherty 8390703b73 feat: nightly DB backups with 14-day retention 2026-04-26 14:18:57 -04:00
Joseph Doherty b9644fad31 feat: periodic snapshots with retention and cold-load fast-path 2026-04-26 14:15:17 -04:00
Joseph Doherty 82be8b3f51 feat: bot reset with hard confirm and event-driven purge 2026-04-26 14:07:56 -04:00
Joseph Doherty 46062973c2 feat: regenerate with edit-then-regenerate inline UX 2026-04-26 14:04:02 -04:00
Joseph Doherty aa0563b4fa feat: rewind with impact preview, pre-rewind snapshot, undo toast 2026-04-26 13:58:20 -04:00
45 changed files with 4234 additions and 77 deletions
+1
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@@ -8,3 +8,4 @@ data/
__pycache__/ __pycache__/
*.pyc *.pyc
.pytest_cache/ .pytest_cache/
*.egg-info/
+28
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@@ -149,3 +149,31 @@ Don't jump phases. Phase 1 must work end-to-end before Phase 2 lands.
- Inference hosting (start with a cloud API, re-evaluate later) - Inference hosting (start with a cloud API, re-evaluate later)
- Character template format (during Phase 1) - Character template format (during Phase 1)
- Multi-session / multi-character casts: **out of scope for v1**. Leave cheap schema hooks only. - Multi-session / multi-character casts: **out of scope for v1**. Leave cheap schema hooks only.
## Phase 1 status
Phase 1 shipped end-to-end across **35 tasks** (T0T35). The single-bot core loop is functional: event log + projector, schema + migrations, settings/bot authoring, kickoff confirm, streaming turns, drawer rendering, regenerate/rewind, scene close + per-POV summaries, significance classifier, snapshots/backups, first-run navigation, and friendly 404/500 pages. **168 tests passing.**
Deferred to Phase 2: second bot, group node, scene configurations, witness filtering across multi-entity scenes, activity/containers, scene-transition compression. Phase 3: event queue + triggers, time skips, active threads. Phase 4: vector retrieval, branching, surgical delete + regenerate, impact-preview UI.
### Known v1 limitations (read before extending)
- **Drawer edits scope**: only affinity, significance, and pin can be hand-edited from the drawer. Other v1 fields (knowledge, summary text, traits) are deferred to Phase 1.5.
- **Cold-load snapshot path** is wired and unit-tested but rarely exercised in dev — long-running sessions are the only realistic trigger.
- **WAL sidecar files** (`-wal`, `-shm`) are not captured in nightly backups; the nightly snapshot is a fresh `.backup()` so this is fine for restore but worth knowing if you copy the db file by hand.
- **HTMX SSE event names** may need a version check if you bump the htmx CDN URL in `base.html` — the swap targets are name-coupled.
- **"You" activity rows** can linger after `bot_reset` (the reset purges the bot's chats and the bot's own activity row but not the "you" row that was associated with those chats). Cosmetic, fixed in Phase 1.5.
- **Projector replay is non-idempotent** for plain `INSERT` events. After appending, call `apply_event(conn, event)` for the new row only — calling `project(conn)` re-runs every handler from scratch and will trip uniqueness or duplicate inserts.
- **8-pin auto-cap eviction** is FIFO over the auto-pinned set only. Manual pins survive the eviction; this is by design (manual intent > auto-pin signal).
- **Regenerate (T29) does not broadcast `turn_html` over SSE** — the page must refresh to show the regenerated turn. Acceptable for v1 single-tab usage; Phase 1.5 should wire the SSE event.
- **First-run middleware** fires only on bare `/` and `/chats`. Sub-paths like `/chats/<id>` and `/chats/<id>/drawer` pass through (correct: HTMX partials should not page-redirect, and a deep-link to a missing chat should 404, not redirect mid-setup).
### Phase 1.5 cleanup backlog
Small follow-ups identified during Phase 1 reviews. Pick up at any time; none are blocking.
- **`open_db` refactor.** `chat/web/bots.py:get_conn()` duplicates the context-manager body to add `check_same_thread=False`. Extend `open_db(path, *, check_same_thread=True)` and have `get_conn` call it directly — eliminates the duplicated PRAGMA setup and ensures any future PRAGMA tweak only happens in one place.
- **Regenerate broadcasts `turn_html` over SSE.** Currently a refresh is needed (see T29 limitation above). Mirror the broadcast logic from `chat/web/turns.py:post_turn` after the new `assistant_turn` lands.
- **`bot_reset` purges orphaned "you" activity rows** (see limitation above). Either delete `activity` rows by chat-membership or accept the noise indefinitely; the projection-layer fix is one extra `DELETE FROM activity WHERE entity_id='you' AND container_id IN (SELECT id FROM containers WHERE chat_id IN (...))` clause inside `_apply_bot_reset`.
- **Drawer edits for the deferred v1 fields**: edge_trust slider, edge_summary textarea, memory pov_summary textarea, knowledge_facts add/remove. The `manual_edit` projector already supports `edge_trust` / `edge_summary` / `memory_pov_summary` target_kinds — only the routes are missing. Knowledge_facts needs a new dispatch branch.
- **NICE trim order in prompt assembly** drops previous-scene first instead of last (T18 review). Greedy-cuts heuristic vs spec listing order; revisit if v1 play surfaces a real regression.
+63 -3
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@@ -1,13 +1,22 @@
from __future__ import annotations from __future__ import annotations
import logging
from contextlib import asynccontextmanager from contextlib import asynccontextmanager
from pathlib import Path from pathlib import Path
from fastapi import FastAPI from fastapi import FastAPI, Request
from fastapi.responses import JSONResponse
from fastapi.staticfiles import StaticFiles from fastapi.staticfiles import StaticFiles
from fastapi.templating import Jinja2Templates
from starlette.exceptions import HTTPException as StarletteHTTPException
from chat.config import load_settings from chat.config import load_settings
from chat.db.connection import open_db
from chat.db.migrate import apply_migrations from chat.db.migrate import apply_migrations
from chat.eventlog.log import read_events
from chat.eventlog.projector import apply_event
from chat.services.background import BackgroundWorker from chat.services.background import BackgroundWorker
from chat.services.snapshot import latest_snapshot_path, restore_from_snapshot
# Trigger handler registration: # Trigger handler registration:
import chat.state.entities # noqa: F401 import chat.state.entities # noqa: F401
@@ -20,25 +29,53 @@ from chat.web.bots import router as bots_router
from chat.web.chat import router as chat_router from chat.web.chat import router as chat_router
from chat.web.drawer import router as drawer_router from chat.web.drawer import router as drawer_router
from chat.web.kickoff import router as kickoff_router from chat.web.kickoff import router as kickoff_router
from chat.web.middleware import FirstRunRedirectMiddleware
from chat.web.nav import router as nav_router from chat.web.nav import router as nav_router
from chat.web.settings import router as settings_router from chat.web.settings import router as settings_router
from chat.web.sse import router as sse_router from chat.web.sse import router as sse_router
from chat.web.turns import router as turns_router from chat.web.turns import router as turns_router
log = logging.getLogger(__name__)
@asynccontextmanager @asynccontextmanager
async def lifespan(app: FastAPI): async def lifespan(app: FastAPI):
settings = load_settings() settings = load_settings()
settings.db_path.parent.mkdir(parents=True, exist_ok=True) settings.db_path.parent.mkdir(parents=True, exist_ok=True)
apply_migrations(settings.db_path) apply_migrations(settings.db_path)
# T31 cold-load fast-path: if a periodic snapshot exists, restore
# projected tables from it and replay only events past its
# ``last_event_id``. Migrations already ran above, so any new tables
# introduced after the snapshot was taken are present and empty —
# the replay-forward step refills them from the event log.
snapshot_path = latest_snapshot_path(settings.data_dir, kind="periodic")
if snapshot_path is not None:
with open_db(settings.db_path) as conn:
last_event_id = restore_from_snapshot(conn, snapshot_path)
for event in read_events(
conn, branch_id=1, after_id=last_event_id
):
apply_event(conn, event)
log.info(
"cold-load restored from %s, replayed events past id %d",
snapshot_path,
last_event_id,
)
app.state.settings = settings app.state.settings = settings
# Cap concurrent Featherless connections to the account's limit
# (free / lower paid tiers cap at 2). Shared across all
# FeatherlessClient instances in the process.
from chat.llm.featherless import FeatherlessClient
FeatherlessClient.configure_concurrency(settings.featherless_max_concurrent)
# Background worker for the async significance pass (T22). Each job # Background worker for the async significance pass (T22). Each job
# constructs a fresh FeatherlessClient via the factory; tests can # constructs a fresh FeatherlessClient via the factory; tests can
# disable enqueue by toggling ``app.state.background_worker.enabled``. # disable enqueue by toggling ``app.state.background_worker.enabled``.
def _factory(): def _factory():
from chat.llm.featherless import FeatherlessClient
return FeatherlessClient( return FeatherlessClient(
api_key=settings.featherless_api_key, api_key=settings.featherless_api_key,
base_url=settings.featherless_base_url, base_url=settings.featherless_base_url,
@@ -55,10 +92,33 @@ async def lifespan(app: FastAPI):
app = FastAPI(title="chat", lifespan=lifespan) app = FastAPI(title="chat", lifespan=lifespan)
app.add_middleware(FirstRunRedirectMiddleware)
STATIC_DIR = Path(__file__).resolve().parent / "static" STATIC_DIR = Path(__file__).resolve().parent / "static"
app.mount("/static", StaticFiles(directory=str(STATIC_DIR)), name="static") app.mount("/static", StaticFiles(directory=str(STATIC_DIR)), name="static")
ERROR_TEMPLATES = Jinja2Templates(
directory=str(Path(__file__).resolve().parent / "templates")
)
@app.exception_handler(StarletteHTTPException)
async def http_exception_handler(request: Request, exc: StarletteHTTPException):
"""Render a friendly HTML page for 404/500; JSON for everything else."""
if exc.status_code in (404, 500):
return ERROR_TEMPLATES.TemplateResponse(
request,
"errors.html",
{
"status_code": exc.status_code,
"detail": exc.detail or "Something went wrong.",
"active_nav": "chats",
},
status_code=exc.status_code,
)
return JSONResponse(status_code=exc.status_code, content={"detail": exc.detail})
app.include_router(bots_router) app.include_router(bots_router)
app.include_router(kickoff_router) app.include_router(kickoff_router)
app.include_router(settings_router) app.include_router(settings_router)
+19 -1
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@@ -23,8 +23,18 @@ class Settings(BaseModel):
retrieval_k: int = 4 retrieval_k: int = 4
narrative_budget_hard: int = 8000 narrative_budget_hard: int = 8000
narrative_budget_soft: int = 6000 narrative_budget_soft: int = 6000
# Cap on each generated bot response. ~400 tokens ≈ 12 short paragraphs.
# Bump if you want longer scenes; drop to 200 for terse banter.
narrative_max_tokens: int = 400
# Sampling temperature for narrative generation. 0.7 = grounded /
# consistent; 0.85 = creative-but-in-character (default); 1.0 = wide
# variety, can drift; >1.0 = often off-the-rails.
narrative_temperature: float = 0.85
classifier_budget_hard: int = 4000 classifier_budget_hard: int = 4000
classifier_timeout_s: float = 10.0 classifier_timeout_s: float = 30.0
# Featherless free tier and lower paid tiers cap concurrent connections.
# Set this to your account's max-concurrent-connections limit.
featherless_max_concurrent: int = 2
db_path: Path = DEFAULT_DB db_path: Path = DEFAULT_DB
data_dir: Path = REPO_ROOT / "data" data_dir: Path = REPO_ROOT / "data"
bind_host: str = "127.0.0.1" bind_host: str = "127.0.0.1"
@@ -37,4 +47,12 @@ def load_settings() -> Settings:
raw = tomllib.loads(config_path.read_text()) raw = tomllib.loads(config_path.read_text())
if "CHAT_DB_PATH" in os.environ: if "CHAT_DB_PATH" in os.environ:
raw["db_path"] = Path(os.environ["CHAT_DB_PATH"]) raw["db_path"] = Path(os.environ["CHAT_DB_PATH"])
if "CHAT_DATA_DIR" in os.environ:
raw["data_dir"] = Path(os.environ["CHAT_DATA_DIR"])
elif "data_dir" not in raw and "db_path" in raw:
# T31: when ``CHAT_DB_PATH`` is overridden (typical in tests) but
# ``data_dir`` isn't, derive ``data_dir`` from the db's parent so
# snapshot/auxiliary files stay alongside the test db rather than
# leaking into the real repo data dir.
raw["data_dir"] = Path(raw["db_path"]).parent
return Settings(**raw) return Settings(**raw)
+26 -5
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@@ -10,6 +10,18 @@ T = TypeVar("T", bound=BaseModel)
REFUSAL_PATTERNS = ("i can't", "i cannot", "i'm sorry, but", "as an ai") REFUSAL_PATTERNS = ("i can't", "i cannot", "i'm sorry, but", "as an ai")
def _strip_json_fences(text: str) -> str:
"""Strip ```json ... ``` markdown fences if the model wraps its JSON output."""
s = text.strip()
if s.startswith("```"):
# Drop the first fence line (which may be ``` or ```json)
s = s.split("\n", 1)[1] if "\n" in s else s[3:]
# Drop the trailing fence
if s.rstrip().endswith("```"):
s = s.rstrip()[:-3]
return s.strip()
async def classify( async def classify(
client: LLMClient, client: LLMClient,
*, *,
@@ -20,21 +32,30 @@ async def classify(
default: T | None = None, default: T | None = None,
timeout_s: float = 10.0, timeout_s: float = 10.0,
) -> T: ) -> T:
schema_json = json.dumps(schema.model_json_schema(), indent=2)
schema_block = (
f"\n\nRespond with a single JSON object matching this exact schema. "
f"Use these field names exactly; do not invent your own keys:\n```json\n{schema_json}\n```"
)
msgs = [ msgs = [
Message(role="system", content=system + "\n\nRespond with JSON only matching the schema."), Message(role="system", content=system + schema_block),
Message(role="user", content=user), Message(role="user", content=user),
] ]
for attempt in range(2): for attempt in range(3):
try: try:
text = await asyncio.wait_for( text = await asyncio.wait_for(
client.generate(msgs, model=model, response_format={"type": "json_object"}), client.generate(msgs, model=model, response_format={"type": "json_object"}),
timeout=timeout_s, timeout=timeout_s,
) )
if any(p in text.lower()[:80] for p in REFUSAL_PATTERNS) and not text.strip().startswith("{"): cleaned = _strip_json_fences(text)
if any(p in cleaned.lower()[:80] for p in REFUSAL_PATTERNS) and not cleaned.lstrip().startswith("{"):
raise ValueError("refusal-shaped response") raise ValueError("refusal-shaped response")
return schema.model_validate_json(text) return schema.model_validate_json(cleaned)
except (ValidationError, ValueError, json.JSONDecodeError, asyncio.TimeoutError): except (ValidationError, ValueError, json.JSONDecodeError, asyncio.TimeoutError):
msgs[0] = Message(role="system", content=system + "\n\nRespond with valid JSON ONLY. No prose.") msgs[0] = Message(
role="system",
content=system + schema_block + "\n\nRespond with valid JSON ONLY. No prose, no markdown fences.",
)
continue continue
if default is None: if default is None:
raise RuntimeError(f"classify failed for schema {schema.__name__} with no default") raise RuntimeError(f"classify failed for schema {schema.__name__} with no default")
+26
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@@ -1,14 +1,39 @@
from __future__ import annotations from __future__ import annotations
import asyncio
from typing import AsyncIterator, Sequence from typing import AsyncIterator, Sequence
from openai import AsyncOpenAI from openai import AsyncOpenAI
from .client import Message from .client import Message
class FeatherlessClient: class FeatherlessClient:
"""Client for Featherless's OpenAI-compatible API.
Featherless caps concurrent connections per account (2 on free / lower
paid tiers). A class-level semaphore gates every ``generate`` and
``stream`` call so the orchestrator never exceeds the configured cap,
regardless of how many ``FeatherlessClient`` instances are alive.
Configure once at app startup via :meth:`configure_concurrency`. The
default is 2.
"""
_semaphore: asyncio.Semaphore | None = None
@classmethod
def configure_concurrency(cls, max_concurrent: int) -> None:
cls._semaphore = asyncio.Semaphore(max(1, int(max_concurrent)))
@classmethod
def _sem(cls) -> asyncio.Semaphore:
if cls._semaphore is None:
cls._semaphore = asyncio.Semaphore(2)
return cls._semaphore
def __init__(self, api_key: str, base_url: str = "https://api.featherless.ai/v1"): def __init__(self, api_key: str, base_url: str = "https://api.featherless.ai/v1"):
self._client = AsyncOpenAI(api_key=api_key, base_url=base_url) self._client = AsyncOpenAI(api_key=api_key, base_url=base_url)
async def generate(self, messages: Sequence[Message], *, model: str, **params) -> str: async def generate(self, messages: Sequence[Message], *, model: str, **params) -> str:
async with self._sem():
resp = await self._client.chat.completions.create( resp = await self._client.chat.completions.create(
model=model, model=model,
messages=[{"role": m.role, "content": m.content} for m in messages], messages=[{"role": m.role, "content": m.content} for m in messages],
@@ -17,6 +42,7 @@ class FeatherlessClient:
return resp.choices[0].message.content or "" return resp.choices[0].message.content or ""
async def stream(self, messages: Sequence[Message], *, model: str, **params) -> AsyncIterator[str]: async def stream(self, messages: Sequence[Message], *, model: str, **params) -> AsyncIterator[str]:
async with self._sem():
stream = await self._client.chat.completions.create( stream = await self._client.chat.completions.create(
model=model, model=model,
messages=[{"role": m.role, "content": m.content} for m in messages], messages=[{"role": m.role, "content": m.content} for m in messages],
+89
View File
@@ -32,7 +32,22 @@ from chat.config import Settings
from chat.db.connection import open_db from chat.db.connection import open_db
from chat.eventlog.log import append_and_apply from chat.eventlog.log import append_and_apply
from chat.llm.client import LLMClient from chat.llm.client import LLMClient
from chat.services.backup import (
prune_backups,
should_take_backup,
take_backup,
)
from chat.services.significance import compute_significance from chat.services.significance import compute_significance
from chat.services.snapshot import (
prune_periodic_snapshots,
should_take_periodic_snapshot,
take_snapshot,
)
# T32: tick-loop wake interval. 60s gives a single backup window per
# target hour with plenty of slack: should_take_backup's 23h freshness
# guard prevents back-to-back runs.
BACKUP_TICK_INTERVAL_SECONDS = 60.0
log = logging.getLogger(__name__) log = logging.getLogger(__name__)
@@ -70,14 +85,27 @@ class BackgroundWorker:
self._llm_client_factory = llm_client_factory self._llm_client_factory = llm_client_factory
self._queue: asyncio.Queue[SignificanceJob | None] = asyncio.Queue() self._queue: asyncio.Queue[SignificanceJob | None] = asyncio.Queue()
self._task: asyncio.Task | None = None self._task: asyncio.Task | None = None
# T32: nightly-backup tick loop runs alongside the job loop. The
# event is set by stop() to wake the loop early so shutdown is
# snappy even mid-tick.
self._tick_task: asyncio.Task | None = None
self._tick_stop: asyncio.Event = asyncio.Event()
self.enabled = enabled self.enabled = enabled
async def start(self) -> None: async def start(self) -> None:
if self._task is not None: if self._task is not None:
return return
self._task = asyncio.create_task(self._run()) self._task = asyncio.create_task(self._run())
self._tick_task = asyncio.create_task(self._tick_loop())
async def stop(self) -> None: async def stop(self) -> None:
# Stop the tick loop first — it has no in-flight work to drain,
# so signalling early lets it exit while the job loop is still
# finishing its sentinel handoff.
self._tick_stop.set()
if self._tick_task is not None:
await self._tick_task
self._tick_task = None
if self._task is None: if self._task is None:
return return
await self._queue.put(None) # sentinel await self._queue.put(None) # sentinel
@@ -99,6 +127,40 @@ class BackgroundWorker:
except Exception as exc: # noqa: BLE001 — worker must not die except Exception as exc: # noqa: BLE001 — worker must not die
log.exception("significance job failed: %s", exc) log.exception("significance job failed: %s", exc)
async def _tick_loop(self) -> None:
"""Periodic-operations loop (T32 nightly backup).
Wakes every :data:`BACKUP_TICK_INTERVAL_SECONDS` seconds and
asks :func:`should_take_backup` whether a backup is due. The
scheduling decision lives in the backup module so we don't
duplicate the "is it 03:00?" logic here. Failures are caught
and logged so a flaky disk doesn't kill the loop — the next
tick will retry.
Wait uses :func:`asyncio.wait_for` on ``_tick_stop`` so that
:meth:`stop` can interrupt a sleeping tick instead of having to
wait the full interval.
"""
while not self._tick_stop.is_set():
try:
if should_take_backup(self._settings.data_dir):
take_backup(
db_path=self._settings.db_path,
data_dir=self._settings.data_dir,
)
prune_backups(self._settings.data_dir, keep=14)
log.info("nightly backup taken")
except Exception as exc: # noqa: BLE001 — never break the loop
log.exception("backup tick failed: %s", exc)
try:
await asyncio.wait_for(
self._tick_stop.wait(),
timeout=BACKUP_TICK_INTERVAL_SECONDS,
)
except asyncio.TimeoutError:
# Normal path: timed out waiting for stop, run another tick.
pass
async def _process(self, job: SignificanceJob) -> None: async def _process(self, job: SignificanceJob) -> None:
client = self._llm_client_factory() client = self._llm_client_factory()
score = await compute_significance( score = await compute_significance(
@@ -123,6 +185,33 @@ class BackgroundWorker:
memory_id=job.memory_id, memory_id=job.memory_id,
) )
# T31: piggy-back the periodic snapshot check on the background
# worker so we don't need a separate timer task. The classifier
# pass already runs out-of-band, so snapshot I/O on the same
# worker is a natural fit. Each snapshot opens its own
# connection so we don't conflate the snapshot's read-only view
# with the significance-write transaction above. Failures are
# caught and logged: a flaky disk shouldn't take down the
# significance pipeline.
try:
with open_db(self._settings.db_path) as conn:
if should_take_periodic_snapshot(
conn, self._settings.data_dir
):
snapshot_path = take_snapshot(
conn,
data_dir=self._settings.data_dir,
kind="periodic",
)
prune_periodic_snapshots(
self._settings.data_dir, keep=5
)
log.info(
"periodic snapshot taken: %s", snapshot_path
)
except Exception as exc: # noqa: BLE001 — never break the worker
log.exception("periodic snapshot failed: %s", exc)
def _auto_pin_with_cap( def _auto_pin_with_cap(
conn, conn,
+106
View File
@@ -0,0 +1,106 @@
"""Nightly DB backup service (T32, Requirements §12).
A simple in-process scheduler: at 03:00 local time daily, copy
``chat.db`` to ``data/backups/chat-<utc-timestamp>.db`` and prune to the
14 most recent. The BackgroundWorker tick loop calls
:func:`should_take_backup` every 60 seconds; when it returns True the
worker calls :func:`take_backup` then :func:`prune_backups`.
The launchd plist suggested in §12 can replace this later by invoking a
small script that calls :func:`take_backup` directly. For v1 the
in-process loop is enough — the daemon already runs continuously to
serve requests, so there's no extra moving part to install.
Backups capture the live ``.db`` file via :func:`shutil.copy2`. SQLite's
WAL mode means an in-flight transaction's pages might live in the
``-wal`` sidecar rather than the main file, but our codebase commits
every write transaction synchronously, so the .db alone is sufficient
for v1. A truly safe online backup would use
``sqlite3.Connection.backup()``; deferred.
"""
from __future__ import annotations
import shutil
from datetime import datetime, timezone
from pathlib import Path
# 03:00 local time per Requirements §12. Hardcoded for v1 — making this
# configurable via Settings is straightforward but not needed yet.
DEFAULT_BACKUP_HOUR = 3
# Retention window per Requirements §12 ("Last 14 retained").
DEFAULT_KEEP = 14
# Wake interval for should_take_backup's freshness check. We wake the
# tick loop every 60s, so a backup taken in the previous tick within the
# same target hour must NOT trigger another. 23h gives us a generous
# safety margin against scheduling jitter while still allowing a single
# backup per day.
FRESHNESS_HOURS = 23
def take_backup(*, db_path: Path, data_dir: Path) -> Path:
"""Copy ``db_path`` to ``data_dir/backups/chat-<utc-timestamp>.db``.
Returns the new file path. Creates the backup directory if missing.
Uses :func:`shutil.copy2` so the destination's mtime is preserved —
:func:`should_take_backup` reads mtime to gate fresh backups.
"""
backup_dir = data_dir / "backups"
backup_dir.mkdir(parents=True, exist_ok=True)
timestamp = datetime.now(timezone.utc).strftime("%Y%m%dT%H%M%SZ")
backup_path = backup_dir / f"chat-{timestamp}.db"
shutil.copy2(db_path, backup_path)
return backup_path
def prune_backups(data_dir: Path, *, keep: int = DEFAULT_KEEP) -> int:
"""Remove all but the most recent ``keep`` backup files.
Returns the number of files removed. Safe when the directory is
missing (returns 0). Sorting is by filename, which is the UTC
timestamp embedded in the name — lexicographic order matches
chronological order.
"""
backup_dir = data_dir / "backups"
if not backup_dir.exists():
return 0
files = sorted(backup_dir.glob("chat-*.db"))
to_remove = files[:-keep] if len(files) > keep else []
for f in to_remove:
f.unlink()
return len(to_remove)
def should_take_backup(
data_dir: Path, *, target_hour: int = DEFAULT_BACKUP_HOUR
) -> bool:
"""Decide whether a nightly backup is due.
Two conditions must hold:
* The current local hour matches ``target_hour``.
* No backup file in ``data_dir/backups/`` has an mtime within the
last :data:`FRESHNESS_HOURS` (23h). The 23h window prevents a
double-backup within the same target hour while still allowing
the next day's run to fire on time.
Local time (not UTC) is used for the hour comparison per the
requirements ("03:00 local time"). The filename embeds a UTC stamp
so file ordering remains unambiguous across DST transitions.
"""
now = datetime.now()
if now.hour != target_hour:
return False
backup_dir = data_dir / "backups"
if not backup_dir.exists():
return True
files = list(backup_dir.glob("chat-*.db"))
if not files:
return True
most_recent = max(files, key=lambda f: f.stat().st_mtime)
age_hours = (
datetime.now().timestamp() - most_recent.stat().st_mtime
) / 3600
return age_hours >= FRESHNESS_HOURS
+34 -5
View File
@@ -85,6 +85,36 @@ def _build_user_prompt(
) )
def _empty_activity() -> ActivityShape:
return ActivityShape(
posture="",
action_verb="",
action_interruptible=True,
action_required_attention="low",
action_expected_duration="brief",
)
def _empty_kickoff_parse() -> KickoffParse:
"""Default returned when the classifier can't produce a valid parse.
The user gets a mostly-empty confirm form they can fill in by hand
instead of a 500. ``initial_time_iso`` is left as the current UTC.
"""
from datetime import datetime, timezone
return KickoffParse(
container_name="",
container_type="",
container_properties={},
you_activity=_empty_activity(),
bot_activity=_empty_activity(),
initial_time_iso=datetime.now(timezone.utc).isoformat(timespec="seconds"),
edge_seed_summary="",
edge_seed_knowledge_facts=[],
)
async def parse_kickoff( async def parse_kickoff(
client: LLMClient, client: LLMClient,
*, *,
@@ -98,11 +128,9 @@ async def parse_kickoff(
) -> KickoffParse: ) -> KickoffParse:
"""Parse authored kickoff prose into a structured ``KickoffParse``. """Parse authored kickoff prose into a structured ``KickoffParse``.
Internally calls :func:`chat.llm.classify.classify` with a labeled Falls back to a mostly-empty default if the classifier fails — the
user prompt. Raises ``RuntimeError`` if the classifier fails twice in confirm-and-edit form is the human-in-the-loop, so a degraded form
a row — no default is supplied at this layer, since the caller (T13's that the user can fill in is preferable to a 500.
confirm form) is responsible for showing an error and letting the
user edit.
""" """
user_prompt = _build_user_prompt( user_prompt = _build_user_prompt(
bot_name=bot_name, bot_name=bot_name,
@@ -117,5 +145,6 @@ async def parse_kickoff(
system=_SYSTEM_PROMPT, system=_SYSTEM_PROMPT,
user=user_prompt, user=user_prompt,
schema=KickoffParse, schema=KickoffParse,
default=_empty_kickoff_parse(),
timeout_s=timeout_s, timeout_s=timeout_s,
) )
+3 -1
View File
@@ -211,7 +211,9 @@ def _closing_instruction(speaker_name: str, addressee_name: str) -> str:
f"Continue the scene as {speaker_name}, in their voice, responding " f"Continue the scene as {speaker_name}, in their voice, responding "
"naturally. Use *asterisks* for actions and quotes for dialogue. " "naturally. Use *asterisks* for actions and quotes for dialogue. "
f"Stay in character. Do not narrate {addressee_name}'s actions or " f"Stay in character. Do not narrate {addressee_name}'s actions or "
"thoughts." "thoughts. "
"Keep your response to a single beat — one or two short paragraphs "
"at most. Don't monologue; leave room for the other person to react."
) )
+285
View File
@@ -0,0 +1,285 @@
"""Regenerate flow (T29).
The user clicks "Regenerate" on the latest ``assistant_turn``. The UI
puts the prior ``user_turn`` into inline edit mode and submits to
:func:`regenerate_assistant_turn` either:
- with **no edit** — we re-run the narrative against the original user
prose and append a fresh ``assistant_turn`` superseding the old one;
- with **edited prose** — we additionally append a ``user_turn_edit``
event capturing the new prose, mark the original ``user_turn`` as
superseded by the edit, then run the narrative against the edited
prose.
Per Requirements §10.2 superseded events are *kept in the log* — the
display layer hides them. This is what makes rewinding to before a
regenerate cheap: we just clear ``superseded_by`` on the old row.
The supersede update is one of the rare "direct DB write" exceptions
documented in the plan: we manipulate metadata fields on the canonical
event_log row itself rather than projecting through a handler.
Phase 1 simplifications (per the plan's "bound it" guidance):
- Significance pass is *not* re-run on regenerate. The original score
remains attached to the prior memory. The state-update pass *is* re-run
so affinity/trust/knowledge reflect the new output.
- The route does not broadcast a fresh ``turn_html`` SSE event; T34
polishes UI swaps. The user refreshes the page to see the new turn.
"""
from __future__ import annotations
import json
from sqlite3 import Connection
from chat.config import Settings
from chat.eventlog.log import append_and_apply, append_event
from chat.services.memory_write import record_turn_memory
from chat.services.prompt import assemble_narrative_prompt
from chat.services.state_update import compute_state_update
from chat.state.edges import get_edge
from chat.state.entities import get_bot, get_you
from chat.state.world import active_scene, get_chat
from chat.web.pubsub import publish
async def regenerate_assistant_turn(
conn: Connection,
client,
*,
settings: Settings,
chat_id: str,
original_assistant_event_id: int,
edited_user_prose: str | None = None,
) -> str:
"""Regenerate the assistant turn linked to ``original_assistant_event_id``.
When ``edited_user_prose`` is provided the original user_turn is also
superseded by a fresh ``user_turn_edit`` event capturing the new
prose. Returns the new assistant text.
Raises :class:`ValueError` when the chat or the assistant_turn event
cannot be found — the FastAPI route translates this to 404.
"""
chat = get_chat(conn, chat_id)
if chat is None:
raise ValueError("chat not found")
host_bot_id = chat["host_bot_id"]
host_bot = get_bot(conn, host_bot_id) or {
"id": host_bot_id,
"name": "bot",
"persona": "",
}
# 1. Locate the original assistant_turn event.
row = conn.execute(
"SELECT payload_json FROM event_log "
"WHERE id = ? AND kind = 'assistant_turn'",
(original_assistant_event_id,),
).fetchone()
if row is None:
raise ValueError("assistant_turn event not found")
original_assistant_payload = json.loads(row[0])
original_user_turn_id = original_assistant_payload.get("user_turn_id")
# 2. Determine the prose for the new prompt and (when edited) capture
# the user_turn_edit event up front so the new event ids exist before
# we link them from the assistant_turn payload.
new_user_event_id: int | None = None
if edited_user_prose is not None:
new_user_event_id = append_event(
conn,
kind="user_turn_edit",
payload={
"chat_id": chat_id,
"prose": edited_user_prose,
"supersedes_user_turn_id": original_user_turn_id,
},
)
if original_user_turn_id is not None:
conn.execute(
"UPDATE event_log SET superseded_by = ? WHERE id = ?",
(new_user_event_id, original_user_turn_id),
)
prose_for_prompt = edited_user_prose
else:
original_user_row = conn.execute(
"SELECT payload_json FROM event_log WHERE id = ?",
(original_user_turn_id,),
).fetchone() if original_user_turn_id is not None else None
if original_user_row is not None:
prose_for_prompt = json.loads(original_user_row[0]).get("prose", "")
else:
prose_for_prompt = ""
# 3. Build the recent-dialogue slice. Exclude the original
# assistant_turn explicitly (we haven't superseded it yet — that
# update lands at the end so the new event_id is known) and use the
# standard ``superseded_by IS NULL AND hidden = 0`` filter so any
# prior regenerates also drop out.
you_entity = get_you(conn) or {"name": "you", "persona": ""}
you_name = you_entity.get("name", "you")
cur = conn.execute(
"SELECT id, kind, payload_json FROM event_log "
"WHERE kind IN ('user_turn', 'user_turn_edit', 'assistant_turn') "
" AND id != ? "
" AND superseded_by IS NULL AND hidden = 0 "
"ORDER BY id DESC LIMIT 20",
(original_assistant_event_id,),
)
rows = list(reversed(cur.fetchall()))
recent: list[dict] = []
for _eid, kind, payload_json in rows:
p = json.loads(payload_json)
if p.get("chat_id") != chat_id:
continue
if kind in ("user_turn", "user_turn_edit"):
recent.append({"speaker": you_name, "text": p.get("prose", "")})
else:
recent.append(
{"speaker": host_bot.get("name", "bot"), "text": p.get("text", "")}
)
# 4. Assemble the narrative prompt. ``recent`` already excludes the
# current user prose, which we pass through ``user_turn_prose``.
messages = assemble_narrative_prompt(
conn,
chat_id=chat_id,
speaker_bot_id=host_bot_id,
user_turn_prose=prose_for_prompt or None,
recent_dialogue=recent,
budget_soft=settings.narrative_budget_soft,
budget_hard=settings.narrative_budget_hard,
)
# 5. Stream the new narrative.
accumulated: list[str] = []
async for chunk in client.stream(
messages,
model=settings.narrative_model,
max_tokens=settings.narrative_max_tokens,
temperature=settings.narrative_temperature,
):
accumulated.append(chunk)
await publish(
chat_id,
{"event": "token", "text": chunk, "speaker_id": host_bot_id},
)
new_text = "".join(accumulated)
# 6. Append the new assistant_turn event. ``user_turn_id`` points at
# the edit event when one was created, otherwise the original. The
# ``regenerated_from`` field is the back-pointer the UI uses for an
# "originally said …" affordance.
new_assistant_event_id = append_event(
conn,
kind="assistant_turn",
payload={
"chat_id": chat_id,
"speaker_id": host_bot_id,
"text": new_text,
"truncated": False,
"user_turn_id": (
new_user_event_id
if new_user_event_id is not None
else original_user_turn_id
),
"regenerated_from": original_assistant_event_id,
},
)
# 7. Mark the original assistant_turn as superseded by the new one.
conn.execute(
"UPDATE event_log SET superseded_by = ? WHERE id = ?",
(new_assistant_event_id, original_assistant_event_id),
)
# 8. Re-run downstream classifier passes (memory write + state update
# for both directed edges). Significance is intentionally skipped on
# regenerate (the prior score remains attached to the prior memory).
scene = active_scene(conn, chat_id)
record_turn_memory(
conn,
chat_id=chat_id,
host_bot_id=host_bot_id,
narrative_text=new_text,
scene_id=scene["id"] if scene else None,
chat_clock_at=chat.get("time"),
)
last_at = chat.get("time")
recent_for_update = recent + [
{"speaker": host_bot.get("name", "bot"), "text": new_text}
]
edge_b2y = get_edge(conn, host_bot_id, "you") or {
"affinity": 50,
"trust": 50,
"summary": "",
}
update_b2y = await compute_state_update(
client,
model=settings.classifier_model,
source_id=host_bot_id,
target_id="you",
source_name=host_bot.get("name", "bot"),
source_persona=host_bot.get("persona", "") or "",
target_name=you_name,
prior_affinity=edge_b2y["affinity"],
prior_trust=edge_b2y["trust"],
prior_summary=edge_b2y.get("summary", "") or "",
recent_dialogue=recent_for_update,
)
append_and_apply(
conn,
kind="edge_update",
payload={
"source_id": host_bot_id,
"target_id": "you",
"chat_id": chat_id,
"affinity_delta": update_b2y.affinity_delta,
"trust_delta": update_b2y.trust_delta,
"knowledge_facts": update_b2y.knowledge_facts,
"last_interaction_at": last_at,
"last_interaction_chat_id": chat_id,
},
)
edge_y2b = get_edge(conn, "you", host_bot_id) or {
"affinity": 50,
"trust": 50,
"summary": "",
}
update_y2b = await compute_state_update(
client,
model=settings.classifier_model,
source_id="you",
target_id=host_bot_id,
source_name=you_name,
source_persona=you_entity.get("persona", "") or "",
target_name=host_bot.get("name", "bot"),
prior_affinity=edge_y2b["affinity"],
prior_trust=edge_y2b["trust"],
prior_summary=edge_y2b.get("summary", "") or "",
recent_dialogue=recent_for_update,
)
append_and_apply(
conn,
kind="edge_update",
payload={
"source_id": "you",
"target_id": host_bot_id,
"chat_id": chat_id,
"affinity_delta": update_y2b.affinity_delta,
"trust_delta": update_y2b.trust_delta,
"knowledge_facts": update_y2b.knowledge_facts,
"last_interaction_at": last_at,
"last_interaction_chat_id": chat_id,
},
)
return new_text
__all__ = ["regenerate_assistant_turn"]
+23
View File
@@ -0,0 +1,23 @@
from __future__ import annotations
from sqlite3 import Connection
from chat.eventlog.log import append_and_apply
from chat.state.entities import get_bot
def reset_bot(conn: Connection, bot_id: str, *, confirm_name: str) -> None:
"""Reset a bot's runtime state via a ``bot_reset`` event.
Validates that ``confirm_name`` matches the bot's stored ``name``
exactly (case-sensitive, no trim). Raises:
- ``ValueError("bot {bot_id} not found")`` when the bot is missing.
- ``ValueError("confirm_name does not match bot name")`` on mismatch.
"""
bot = get_bot(conn, bot_id)
if bot is None:
raise ValueError(f"bot {bot_id} not found")
if confirm_name != bot["name"]:
raise ValueError("confirm_name does not match bot name")
append_and_apply(conn, kind="bot_reset", payload={"bot_id": bot_id})
+112
View File
@@ -0,0 +1,112 @@
"""Rewind service — truncate the event log past a chosen turn and re-project.
Per Requirements §10.1 and Plan Task 28, "rewind to here" must:
1. Take a snapshot of the current state so the user can recover (handed
off to :mod:`chat.services.snapshot`).
2. Truncate the event log past ``after_event_id`` — physical DELETE for
v1 simplicity; the spec says rewind should be a hard truncation, not
the soft ``hidden=1`` mechanism used by edits/regenerate.
3. Clear projected tables and re-project from the truncated log so live
state matches "what the world looked like at turn N". Without the
re-projection, projected tables would carry forward stale rows from
rewound events (e.g. an ``edge_update`` that bumped affinity past the
rewind point would still show in ``edges``).
Re-projection is a full replay rather than a "revert delta" because most
projector handlers are idempotent inserts, but the edge handler is a
delta-shaped accumulator — there's no clean way to invert a single
``edge_update`` against ``edges.affinity`` without replay. Wiping +
replaying is straightforward and correct.
"""
from __future__ import annotations
from pathlib import Path
from sqlite3 import Connection
from chat.db.connection import open_db
from chat.eventlog.projector import project
from chat.services.snapshot import take_snapshot
def compute_rewind_preview(
conn: Connection, after_event_id: int
) -> dict:
"""Return counts of each event kind that would be removed by rewinding.
Used by the preview modal so the user sees the impact (e.g. "this
will remove 8 events: 4 user_turn, 4 assistant_turn") before
confirming. Counts include hidden/superseded rows — they're still
physically deleted.
"""
cur = conn.execute(
"SELECT kind, COUNT(*) FROM event_log WHERE id > ? GROUP BY kind "
"ORDER BY kind",
(after_event_id,),
)
counts = {kind: count for kind, count in cur.fetchall()}
total = sum(counts.values())
return {
"after_event_id": after_event_id,
"total_events": total,
"by_kind": counts,
}
def execute_rewind(
*, db_path: Path, data_dir: Path, after_event_id: int
) -> Path:
"""Take a snapshot, truncate, and re-project. Returns the snapshot path.
The snapshot is taken inside the same connection scope as the
truncate + reproject so all three commit together — if any step
fails the connection's commit-on-exit is bypassed by the exception
and the database stays untouched. The snapshot file is on disk
regardless, which is the desired behaviour: even if the truncate
aborts, the user has a recovery point.
"""
with open_db(db_path) as conn:
# 1. Snapshot first — we want this on disk before any destructive
# operation runs.
snapshot_path = take_snapshot(
conn, data_dir=data_dir, kind="rewind"
)
# 2. Truncate the event log past the chosen id. Foreign keys are
# ON, but ``event_log.superseded_by`` self-references and the
# rows we're deleting are the only ones that could point
# forward — there's nothing to cascade.
conn.execute(
"DELETE FROM event_log WHERE id > ?", (after_event_id,)
)
# 3. Clear projected tables in topological order so FK ON DELETE
# constraints don't fire on referenced rows. ``activity`` and
# ``scenes`` reference ``containers``; ``chat_state`` references
# ``chats`` by id-convention only (no FK declared). ``memories``,
# ``edges``, ``bots``, ``you_entity``, and ``classifier_failures``
# have no incoming FKs from other projected tables.
#
# ``executescript`` is intentionally avoided so foreign_keys=ON
# stays in effect for each statement — executescript would
# implicitly commit and reset some pragmas on certain SQLite
# builds.
conn.execute("DELETE FROM memories")
conn.execute("DELETE FROM activity")
conn.execute("DELETE FROM scenes")
conn.execute("DELETE FROM containers")
conn.execute("DELETE FROM chat_state")
conn.execute("DELETE FROM chats")
conn.execute("DELETE FROM edges")
conn.execute("DELETE FROM bots")
conn.execute("DELETE FROM you_entity")
conn.execute("DELETE FROM classifier_failures")
# 4. Re-project from the truncated event log. Handler registry
# is module-level state populated by importing chat.state.* —
# callers (the route, tests) need to have those modules
# imported for this to do anything useful.
project(conn)
return snapshot_path
+245
View File
@@ -0,0 +1,245 @@
"""Snapshot service — write a JSON dump of all projected tables to disk.
Two snapshot kinds, both covered by this module:
* ``rewind`` (T28, Requirements §10.1): pre-rewind safety snapshot so the
user can recover if a rewind was a mistake. Retention: 14 days.
* ``periodic`` (T31, Requirements §10.4): full-state checkpoint taken
every 100 events OR every 30 minutes since the last one. Retention:
the most recent 5 are kept; older ones are pruned on write.
Both kinds live under ``data/snapshots/{kind}/`` with a UTC timestamp
filename so chronological listing matches creation order.
The dump captures the event log (so the original event sequence is
preserved verbatim), every projected table, and a top-level
``last_event_id`` recording the highest ``event_log.id`` at snapshot
time. The ``last_event_id`` is what the cold-load fast-path uses to
replay only events past the snapshot rather than the entire log.
The FTS shadow table ``memories_fts`` is intentionally skipped — it's a
virtual table maintained by the ``memories_ai/au/ad`` triggers, so it
rebuilds itself on a memories re-load. Snapshotting it would also fail
``PRAGMA table_info`` cleanly since FTS5 reports its columns differently.
"""
from __future__ import annotations
import json
import time
from datetime import datetime, timezone
from pathlib import Path
from sqlite3 import Connection
# Periodic snapshot triggers (Requirements §10.4): "every 100 events OR
# every 30 minutes since last snapshot". Module-level so tests can read
# them and so the values stay together with the policy that uses them.
EVENT_COUNT_THRESHOLD = 100
TIME_THRESHOLD_SECONDS = 30 * 60 # 30 minutes
# Order doesn't affect correctness for snapshotting (we read, not write),
# but listing tables explicitly keeps the snapshot stable across schema
# evolution: a new table won't silently change the dump shape until it's
# added here.
PROJECTED_TABLES = [
"bots",
"you_entity",
"edges",
"memories",
"memories_fts",
"chats",
"chat_state",
"containers",
"scenes",
"activity",
"classifier_failures",
]
def take_snapshot(
conn: Connection, *, data_dir: Path, kind: str = "rewind"
) -> Path:
"""Write a JSON dump of the event log and projected tables.
Returns the path to the written snapshot file. Creates parent
directories as needed. Filename is a UTC timestamp in
``YYYYMMDDTHHMMSSZ`` form so chronological listing matches creation
order.
The dump's top-level ``last_event_id`` is the highest ``event_log.id``
at snapshot time (0 if the log is empty). This is what the cold-load
fast-path uses to know which suffix of the log to replay.
"""
snapshot_dir = data_dir / "snapshots" / kind
snapshot_dir.mkdir(parents=True, exist_ok=True)
timestamp = datetime.now(timezone.utc).strftime("%Y%m%dT%H%M%SZ")
path = snapshot_dir / f"{timestamp}.json"
dump: dict = {}
# Record the high-water-mark id up front so cold-load can replay
# only events past it. ``MAX(id)`` is None on an empty log; treat
# that as 0 (i.e. "replay everything").
cur = conn.execute("SELECT MAX(id) FROM event_log")
max_id_row = cur.fetchone()
dump["last_event_id"] = max_id_row[0] if max_id_row[0] is not None else 0
# Event log: pull every column we care about. ``ts`` and the
# superseded/hidden flags are needed to faithfully reconstruct the
# log on restore.
cur = conn.execute(
"SELECT id, branch_id, ts, kind, payload_json, superseded_by, hidden "
"FROM event_log ORDER BY id"
)
dump["event_log"] = [
{
"id": r[0],
"branch_id": r[1],
"ts": r[2],
"kind": r[3],
"payload_json": r[4],
"superseded_by": r[5],
"hidden": r[6],
}
for r in cur.fetchall()
]
for table in PROJECTED_TABLES:
if table == "memories_fts":
# Virtual FTS5 table — rebuilt by triggers on insert, no need
# to snapshot it (and ``PRAGMA table_info`` reports its
# columns differently).
continue
cur = conn.execute(f"PRAGMA table_info({table})")
cols = [c[1] for c in cur.fetchall()]
if not cols:
# Table not present in this schema version — leave an empty
# list rather than raising, so older snapshots can survive.
dump[table] = []
continue
cur = conn.execute(f"SELECT {', '.join(cols)} FROM {table}")
dump[table] = [dict(zip(cols, row)) for row in cur.fetchall()]
# ``default=str`` covers Path-like or datetime values that might
# sneak through if a column ever stored them; the projected tables
# all use TEXT so this is mostly defensive.
path.write_text(json.dumps(dump, default=str))
return path
def latest_snapshot_path(data_dir: Path, kind: str = "periodic") -> Path | None:
"""Return the most recent snapshot file for ``kind``, or None if none exist.
Sorting by filename works because :func:`take_snapshot` uses a UTC
timestamp in ``YYYYMMDDTHHMMSSZ`` form — lexicographic order matches
chronological order.
"""
snapshot_dir = data_dir / "snapshots" / kind
if not snapshot_dir.exists():
return None
files = sorted(snapshot_dir.glob("*.json"))
return files[-1] if files else None
def should_take_periodic_snapshot(
conn: Connection, data_dir: Path
) -> bool:
"""Decide whether a periodic snapshot is due per Requirements §10.4.
The policy:
* No prior snapshot and at least one event in the log → take one.
* Time since last snapshot ≥ ``TIME_THRESHOLD_SECONDS`` → take one.
* New events since last snapshot's ``last_event_id`` ≥
``EVENT_COUNT_THRESHOLD`` → take one.
"Time since last snapshot" is measured by the file's mtime — we
don't trust the timestamp embedded in the filename for clock drift
reasons.
"""
latest = latest_snapshot_path(data_dir, kind="periodic")
if latest is None:
# No prior snapshot; take one if there are any events to capture.
cur = conn.execute("SELECT COUNT(*) FROM event_log")
return cur.fetchone()[0] > 0
age_seconds = time.time() - latest.stat().st_mtime
if age_seconds >= TIME_THRESHOLD_SECONDS:
return True
# Count events appended since the last snapshot was written. Reading
# ``last_event_id`` from the dump is cheap (a few KB at most for the
# header) but we still avoid loading the full file by parsing once.
last_dump = json.loads(latest.read_text())
last_event_id = last_dump.get("last_event_id", 0)
cur = conn.execute(
"SELECT COUNT(*) FROM event_log WHERE id > ?", (last_event_id,)
)
new_event_count = cur.fetchone()[0]
return new_event_count >= EVENT_COUNT_THRESHOLD
def prune_periodic_snapshots(data_dir: Path, keep: int = 5) -> int:
"""Delete all but the most recent ``keep`` periodic snapshots.
Returns the number of files removed. Safe to call when the directory
doesn't exist (returns 0). Sorting is by filename, which is the UTC
timestamp — same ordering :func:`latest_snapshot_path` uses.
"""
snapshot_dir = data_dir / "snapshots" / "periodic"
if not snapshot_dir.exists():
return 0
files = sorted(snapshot_dir.glob("*.json"))
to_remove = files[:-keep] if len(files) > keep else []
for f in to_remove:
f.unlink()
return len(to_remove)
def restore_from_snapshot(conn: Connection, snapshot_path: Path) -> int:
"""Restore projected tables from ``snapshot_path``.
Returns the snapshot's ``last_event_id`` so callers (the cold-load
fast-path in :func:`chat.app.lifespan`) know what suffix of the
event log still needs replaying.
Projected tables are cleared in the same FK-respecting order as
:func:`chat.services.rewind.execute_rewind`, then re-populated from
the dump. ``memories_fts`` is skipped — it's a virtual FTS5 table
that rebuilds itself when rows hit ``memories``. The event log
itself is *not* touched: cold-load assumes the on-disk log is the
source of truth and the snapshot is just a fast-forward to skip
re-projecting old events.
"""
dump = json.loads(snapshot_path.read_text())
# Same delete order as rewind: child tables before parents so FK
# ON DELETE doesn't fire on referenced rows.
conn.execute("DELETE FROM memories")
conn.execute("DELETE FROM activity")
conn.execute("DELETE FROM scenes")
conn.execute("DELETE FROM containers")
conn.execute("DELETE FROM chat_state")
conn.execute("DELETE FROM chats")
conn.execute("DELETE FROM edges")
conn.execute("DELETE FROM bots")
conn.execute("DELETE FROM you_entity")
conn.execute("DELETE FROM classifier_failures")
for table in PROJECTED_TABLES:
if table == "memories_fts":
# Rebuilt by triggers when memories rows are inserted below.
continue
rows = dump.get(table, [])
if not rows:
continue
cols = list(rows[0].keys())
placeholders = ", ".join("?" * len(cols))
col_list = ", ".join(cols)
for row in rows:
conn.execute(
f"INSERT INTO {table} ({col_list}) VALUES ({placeholders})",
tuple(row[c] for c in cols),
)
return dump.get("last_event_id", 0)
+40
View File
@@ -31,6 +31,46 @@ def _apply_you_authored(conn: Connection, e: Event) -> None:
) )
@on("bot_reset")
def _apply_bot_reset(conn: Connection, e: Event) -> None:
"""Purge per-bot runtime state while preserving the bot's identity row.
Wipes chats hosted by this bot (with cascading chat-scoped tables),
memories owned by this bot, edges involving this bot, and the bot's own
activity row. The ``bots`` row itself is preserved so identity,
initial-relationship, and kickoff prose remain authored.
"""
bot_id = e.payload["bot_id"]
chat_ids = [
row[0]
for row in conn.execute(
"SELECT id FROM chats WHERE host_bot_id = ?", (bot_id,)
).fetchall()
]
for chat_id in chat_ids:
conn.execute("DELETE FROM scenes WHERE chat_id = ?", (chat_id,))
conn.execute("DELETE FROM containers WHERE chat_id = ?", (chat_id,))
conn.execute("DELETE FROM chat_state WHERE chat_id = ?", (chat_id,))
conn.execute("DELETE FROM chats WHERE id = ?", (chat_id,))
# Activity for this bot's entity row (independent of chat_id since the
# ``activity`` table is keyed on entity_id).
conn.execute("DELETE FROM activity WHERE entity_id = ?", (bot_id,))
# Memories authored by this bot.
conn.execute("DELETE FROM memories WHERE owner_id = ?", (bot_id,))
# Edges in either direction involving this bot.
conn.execute(
"DELETE FROM edges WHERE source_id = ? OR target_id = ?",
(bot_id, bot_id),
)
# NOTE: bots row itself is preserved (identity, kickoff_prose intact).
# NOTE: "you" activity (entity_id="you") may linger from a deleted chat;
# acceptable for v1 — Phase 1.5 cleanup if needed.
def get_bot(conn: Connection, bot_id: str) -> dict | None: def get_bot(conn: Connection, bot_id: str) -> dict | None:
row = conn.execute("SELECT * FROM bots WHERE id = ?", (bot_id,)).fetchone() row = conn.execute("SELECT * FROM bots WHERE id = ?", (bot_id,)).fetchone()
if not row: if not row:
+34
View File
@@ -75,6 +75,30 @@ code { font-family: ui-monospace, "SF Mono", Menlo, monospace; }
.drawer-toggle { padding: 4px 10px; border: 1px solid #ccc; background: #fff; color: #1c1c1c; border-radius: 3px; cursor: pointer; } .drawer-toggle { padding: 4px 10px; border: 1px solid #ccc; background: #fff; color: #1c1c1c; border-radius: 3px; cursor: pointer; }
.timeline { flex: 1; overflow-y: auto; min-height: 200px; padding: 8px 0; } .timeline { flex: 1; overflow-y: auto; min-height: 200px; padding: 8px 0; }
.turn { margin: 12px 0; } .turn { margin: 12px 0; }
.turn strong { display: block; margin-bottom: 4px; }
.turn p { margin: 0 0 8px; }
.turn p:last-child { margin-bottom: 0; }
.turn-you strong { color: #1a73e8; }
.turn-bot strong { color: #1c1c1c; }
/* ``*action*`` — italic narration. */
.action { font-style: italic; color: #555; }
/* ``((ooc))`` — author-to-system aside. Dim, italic, smaller, set off
from surrounding prose so it doesn't read as in-fiction speech. */
.ooc {
font-style: italic;
font-size: 12px;
color: #999;
display: inline-block;
background: rgba(0, 0, 0, 0.04);
padding: 1px 4px;
border-radius: 3px;
}
.turn blockquote {
border-left: 3px solid #ccc;
padding-left: 12px;
margin: 8px 0;
color: #555;
}
.turn-input { display: flex; flex-direction: column; gap: 8px; padding-top: 12px; border-top: 1px solid #e5e5e5; } .turn-input { display: flex; flex-direction: column; gap: 8px; padding-top: 12px; border-top: 1px solid #e5e5e5; }
.turn-input textarea { padding: 8px; font: inherit; border: 1px solid #ccc; border-radius: 3px; resize: vertical; } .turn-input textarea { padding: 8px; font: inherit; border: 1px solid #ccc; border-radius: 3px; resize: vertical; }
.drawer { position: fixed; top: 0; right: 0; width: 360px; height: 100vh; background: #fff; border-left: 1px solid #e5e5e5; padding: 16px; overflow-y: auto; z-index: 10; } .drawer { position: fixed; top: 0; right: 0; width: 360px; height: 100vh; background: #fff; border-left: 1px solid #e5e5e5; padding: 16px; overflow-y: auto; z-index: 10; }
@@ -89,3 +113,13 @@ code { font-family: ui-monospace, "SF Mono", Menlo, monospace; }
.memory-list li { padding: 4px 0; font-size: 13px; } .memory-list li { padding: 4px 0; font-size: 13px; }
.sig { display: inline-block; min-width: 16px; } .sig { display: inline-block; min-width: 16px; }
.sig-3 { color: #d4af37; } .sig-3 { color: #d4af37; }
/* Streaming UX (T34): typing indicator, Stop button, disconnect banner. */
.streaming { opacity: 0.85; }
.streaming-text:after {
content: "\025AE";
margin-left: 2px;
animation: blink 1s steps(2, start) infinite;
}
@keyframes blink { to { visibility: hidden; } }
.stop-streaming { background: #c33; border-color: #a00; margin-bottom: 8px; align-self: flex-start; }
.connection-lost { margin-bottom: 8px; }
+12 -1
View File
@@ -8,7 +8,18 @@
{% if bots %} {% if bots %}
<ul class="bot-list"> <ul class="bot-list">
{% for bot in bots %} {% for bot in bots %}
<li><a href="/bots/{{ bot.id }}">{{ bot.name }}</a></li> <li>
<a href="/bots/{{ bot.id }}">{{ bot.name }}</a>
<details class="bot-row-reset">
<summary>Reset</summary>
<form method="post" action="/bots/{{ bot.id }}/reset" class="inline-edit">
<label>Type "{{ bot.name }}" to confirm:
<input type="text" name="confirm_name" required>
</label>
<button type="submit">Reset bot</button>
</form>
</details>
</li>
{% endfor %} {% endfor %}
</ul> </ul>
{% else %} {% else %}
+112 -2
View File
@@ -19,14 +19,14 @@
{% for turn in turns %} {% for turn in turns %}
<div class="turn turn-{{ turn.role }}"> <div class="turn turn-{{ turn.role }}">
<strong>{{ turn.speaker }}</strong> <strong>{{ turn.speaker }}</strong>
<p>{{ turn.text }}</p> {{ turn.text|render_prose|safe }}
</div> </div>
{% endfor %} {% endfor %}
{% endif %} {% endif %}
</section> </section>
<form class="turn-input" method="post" action="/chats/{{ chat.id }}/turns"> <form class="turn-input" method="post" action="/chats/{{ chat.id }}/turns">
<textarea name="prose" rows="3" placeholder="What do you say or do?"></textarea> <textarea name="prose" rows="3" placeholder="What do you say or do?" required></textarea>
<button type="submit">Send</button> <button type="submit">Send</button>
</form> </form>
@@ -46,4 +46,114 @@ document.querySelector('.drawer-toggle')?.addEventListener('click', (e) => {
e.target.setAttribute('aria-expanded', String(isHidden)); e.target.setAttribute('aria-expanded', String(isHidden));
}); });
</script> </script>
<script>
// Streaming UX (T34): typing indicator, Stop button, send-lock,
// disconnect banner. Listens to the existing HTMX SSE channel for
// `token` (per-chunk) and `turn_html` (final swap) events. The
// mid-stream disconnect path is server-side: ``request.is_disconnected()``
// in T19 commits truncated; this script just shows the banner when
// the SSE EventSource fires `error` after the connection drops.
(function () {
const shell = document.querySelector('.chat-shell');
if (!shell) return;
const chatId = shell.dataset.chatId;
const form = shell.querySelector('.turn-input');
if (!form) return;
const textarea = form.querySelector('textarea[name="prose"]');
const sendBtn = form.querySelector('button[type="submit"]');
const timeline = document.getElementById('timeline');
let isStreaming = false;
let typingEl = null;
function ensureTypingEl() {
if (typingEl) return typingEl;
typingEl = document.createElement('div');
typingEl.className = 'turn turn-bot streaming';
typingEl.innerHTML = '<strong>...</strong><p class="streaming-text"></p>';
timeline.appendChild(typingEl);
return typingEl;
}
function unlock() {
isStreaming = false;
if (sendBtn) sendBtn.disabled = false;
if (textarea) {
textarea.readOnly = false;
textarea.value = '';
textarea.focus();
}
const stop = shell.querySelector('.stop-streaming');
if (stop) stop.remove();
}
function showBanner(msg) {
let banner = shell.querySelector('.connection-lost');
if (banner) return;
banner = document.createElement('div');
banner.className = 'connection-lost error';
banner.textContent = msg;
form.parentElement.insertBefore(banner, form);
}
// HTMX SSE extension dispatches `htmx:sseMessage` with detail.type
// (event name) and detail.data (payload string).
shell.addEventListener('htmx:sseMessage', (e) => {
const evt = e.detail.type;
const data = e.detail.data;
if (evt === 'token' && isStreaming) {
let parsed;
try { parsed = JSON.parse(data); } catch (_) { return; }
const el = ensureTypingEl();
el.querySelector('.streaming-text').textContent += (parsed.text || '');
} else if (evt === 'turn_html') {
// The server already pushes the final HTML via sse-swap on the
// timeline element; we just remove the typing placeholder and
// unlock the input. (Don't replace innerHTML here — HTMX has
// already done the append by the time this fires.)
if (typingEl) {
typingEl.remove();
typingEl = null;
}
unlock();
}
});
// SSE connection lost — show a banner and unlock so the user can
// retry. The server commits the partial as truncated when its
// request.is_disconnected() poll trips (T19).
shell.addEventListener('htmx:sseError', () => {
if (isStreaming) {
showBanner('connection lost — partial response saved');
unlock();
}
});
form.addEventListener('submit', () => {
isStreaming = true;
if (sendBtn) sendBtn.disabled = true;
// readOnly (not disabled) — disabled fields are excluded from the
// form submission, which would send prose="" and trigger the
// server's empty-prose 400.
if (textarea) textarea.readOnly = true;
if (!shell.querySelector('.stop-streaming')) {
const stopBtn = document.createElement('button');
stopBtn.type = 'button';
stopBtn.className = 'stop-streaming btn';
stopBtn.textContent = 'Stop';
stopBtn.addEventListener('click', async () => {
try {
await fetch('/chats/' + encodeURIComponent(chatId) + '/turns/cancel', {
method: 'POST',
});
} catch (_) {
// Network error on cancel is non-fatal — server will time out
// its own stream eventually and commit truncated.
}
});
form.parentElement.insertBefore(stopBtn, form);
}
});
})();
</script>
{% endblock %} {% endblock %}
+9
View File
@@ -0,0 +1,9 @@
{% extends "layout.html" %}
{% block title %}Error - chat{% endblock %}
{% block content %}
<div class="error-page">
<h1>{{ status_code }}</h1>
<p>{{ detail }}</p>
<p><a href="/chats">Back to chats</a></p>
</div>
{% endblock %}
+19
View File
@@ -118,3 +118,22 @@ async def bot_create(
append_event(conn, kind="bot_authored", payload=payload) append_event(conn, kind="bot_authored", payload=payload)
project(conn) project(conn)
return RedirectResponse(url=f"/bots/{payload['id']}/kickoff", status_code=303) return RedirectResponse(url=f"/bots/{payload['id']}/kickoff", status_code=303)
@router.post("/bots/{bot_id}/reset")
async def reset_bot_route(
bot_id: str,
request: Request,
confirm_name: str = Form(""),
conn=Depends(get_conn),
):
from chat.services.reset import reset_bot
try:
reset_bot(conn, bot_id, confirm_name=confirm_name)
except ValueError as e:
msg = str(e).lower()
if "not found" in msg:
raise HTTPException(status_code=404, detail=str(e))
raise HTTPException(status_code=400, detail=str(e))
return RedirectResponse(url="/bots", status_code=303)
+6
View File
@@ -16,11 +16,17 @@ from fastapi.templating import Jinja2Templates
from chat.state.entities import get_bot from chat.state.entities import get_bot
from chat.state.world import get_chat from chat.state.world import get_chat
from chat.web.bots import get_conn from chat.web.bots import get_conn
from chat.web.render import render_prose
from chat.web.turns import _read_recent_dialogue from chat.web.turns import _read_recent_dialogue
TEMPLATES = Jinja2Templates( TEMPLATES = Jinja2Templates(
directory=str(Path(__file__).resolve().parent.parent / "templates") directory=str(Path(__file__).resolve().parent.parent / "templates")
) )
# Register the prose renderer as a Jinja filter so the chat-detail
# template can use ``{{ turn.text|render_prose|safe }}`` (Task 33).
# The renderer escapes user content internally; ``|safe`` is required
# because the output contains intentional ``<p>``/``<em>``/etc. tags.
TEMPLATES.env.filters["render_prose"] = render_prose
router = APIRouter() router = APIRouter()
+61
View File
@@ -0,0 +1,61 @@
from __future__ import annotations
from fastapi import Request
from fastapi.responses import RedirectResponse
from starlette.middleware.base import BaseHTTPMiddleware
from chat.db.connection import open_db
from chat.state.entities import get_you, list_bots
class FirstRunRedirectMiddleware(BaseHTTPMiddleware):
"""Redirect users through the first-run flow (per requirements §16.2).
Behavior on GET requests to landing routes (``/`` and ``/chats``):
- No ``you_entity`` → ``/settings``
- ``you_entity`` exists but no bots → ``/bots/new``
- Otherwise pass through to the underlying handler.
The middleware is a no-op for:
- Non-GET requests (POST/PUT writes proceed and surface their own errors).
- Static assets, health checks, and any path under ``/settings``,
``/bots``, ``/api``, ``/health``, ``/favicon`` — so the user can
actually complete setup once redirected.
- Sub-paths of ``/chats`` (e.g. ``/chats/<id>``, ``/chats/<id>/drawer``);
only the bare landing pages get the redirect treatment. Sub-resources
either 404 cleanly or are HTMX partials that should not page-redirect.
"""
SKIP_PREFIXES = (
"/static",
"/settings",
"/bots",
"/health",
"/favicon",
"/api",
)
async def dispatch(self, request: Request, call_next):
if request.method != "GET":
return await call_next(request)
path = request.url.path
if any(path.startswith(p) for p in self.SKIP_PREFIXES):
return await call_next(request)
# Only fire on the landing routes themselves.
if path != "/" and path != "/chats":
return await call_next(request)
settings = request.app.state.settings
with open_db(settings.db_path) as conn:
you = get_you(conn)
bots = list_bots(conn)
if you is None:
return RedirectResponse(url="/settings", status_code=303)
if not bots:
return RedirectResponse(url="/bots/new", status_code=303)
return await call_next(request)
+106
View File
@@ -0,0 +1,106 @@
"""Transcript display formatting (Task 33, Requirements §16.3).
Bot and user prose is rendered with **lightweight markdown**:
* ``*action*`` → ``<em class="action">…</em>`` — italic narration.
* ``**bold**`` → ``<strong>…</strong>`` — emphasis.
* ``((ooc))`` → ``<span class="ooc">((ooc))</span>`` — author-to-system
asides; visible to the reader, dimmed/italic in CSS, and stripped from
the prompt sent to the bot (see :func:`chat.web.turns._strip_ooc_for_prompt`).
* ``> line`` → ``<blockquote>line</blockquote>``.
* Double newline → paragraph break.
* Everything else is HTML-escaped and wrapped in ``<p>…</p>``.
No headings, code blocks, links, images, or tables — out of scope per
Requirements §16.3. The renderer is the single source of truth used by
both the chat-detail GET (initial timeline render, via Jinja filter) and
the per-turn SSE fragments emitted from :mod:`chat.web.turns`.
Order of operations matters:
1. ``html.escape`` the whole input first — every replacement below assumes
user-supplied ``<``/``>``/``&`` are already neutralised, so the wrapper
tags we add can never collide with an attacker-controlled tag.
2. OOC wrap before action/bold so its inner ``*`` are not interpreted.
3. Bold (``**``) before action (``*``) — the bold pattern is stricter and
would otherwise be partially consumed by the action regex.
4. Blockquote pass over already-escaped lines (so we match ``&gt;``).
5. Paragraph split on double newline.
"""
from __future__ import annotations
import html
import re
# ``((…))`` — non-greedy, allows newlines so a multi-line OOC aside still
# wraps cleanly. The inner ``[^)]*?`` keeps it from spanning across a
# closing-paren boundary.
_OOC_PATTERN = re.compile(r"\(\([^)]*?\)\)", re.DOTALL)
# ``**bold**`` — strict: no embedded asterisks or newlines. Must run
# *before* the single-asterisk action pattern, otherwise ``**x**`` would
# be partly consumed by ``*…*``.
_BOLD_PATTERN = re.compile(r"\*\*([^*\n]+)\*\*")
# ``*action*`` — single-asterisk italics; same restriction as bold.
_ACTION_PATTERN = re.compile(r"\*([^*\n]+)\*")
# ``> line`` at start of a line — note we match the *escaped* form
# ``&gt;`` because this pass runs after ``html.escape``.
_BLOCKQUOTE_PATTERN = re.compile(r"^&gt;\s?(.+)$", re.MULTILINE)
def render_prose(text: str) -> str:
"""Render prose to safe HTML.
Returns an empty string for empty/whitespace-only input so the caller
can append the result without producing stray ``<p></p>`` tags.
"""
if not text or not text.strip():
return ""
# Normalise CRLF so paragraph splitting on ``\n\n`` works for input
# pasted from Windows clients.
text = text.replace("\r\n", "\n").replace("\r", "\n")
escaped = html.escape(text)
# OOC first — the wrapped span survives subsequent passes.
escaped = _OOC_PATTERN.sub(
lambda m: f'<span class="ooc">{m.group(0)}</span>', escaped
)
# Bold strictly before action (regex precedence — see module docstring).
escaped = _BOLD_PATTERN.sub(r"<strong>\1</strong>", escaped)
escaped = _ACTION_PATTERN.sub(r'<em class="action">\1</em>', escaped)
# Blockquote on already-escaped ``&gt;`` markers.
escaped = _BLOCKQUOTE_PATTERN.sub(r"<blockquote>\1</blockquote>", escaped)
# Paragraph splitting — drop empty fragments so a trailing ``\n\n``
# doesn't yield an empty ``<p></p>`` block.
paragraphs = [p.strip() for p in escaped.split("\n\n") if p.strip()]
return "".join(f"<p>{p}</p>" for p in paragraphs)
def render_turn_html(speaker: str, text: str, role: str = "bot") -> str:
"""Render a full transcript turn as ``<div class="turn …">…</div>``.
Used by both the SSE fragment publisher in :mod:`chat.web.turns`
(per-turn live updates) and indirectly by the chat-detail Jinja
template (initial render, via the ``render_prose`` filter).
``role`` selects the CSS class (``turn-you`` vs ``turn-bot``); the
speaker label and role name are HTML-escaped defensively even though
they currently come from trusted server-side state.
"""
speaker_html = html.escape(speaker)
role_html = html.escape(role)
body_html = render_prose(text)
return (
f'<div class="turn turn-{role_html}">'
f"<strong>{speaker_html}</strong>"
f"{body_html}"
f"</div>"
)
+192 -21
View File
@@ -36,12 +36,13 @@ import html
import json import json
from fastapi import APIRouter, Depends, Form, HTTPException, Request from fastapi import APIRouter, Depends, Form, HTTPException, Request
from fastapi.responses import Response from fastapi.responses import HTMLResponse, RedirectResponse, Response
from chat.eventlog.log import append_and_apply, append_event from chat.eventlog.log import append_and_apply, append_event
from chat.services.background import SignificanceJob from chat.services.background import SignificanceJob
from chat.services.memory_write import record_turn_memory from chat.services.memory_write import record_turn_memory
from chat.services.prompt import assemble_narrative_prompt from chat.services.prompt import assemble_narrative_prompt
from chat.services.rewind import compute_rewind_preview, execute_rewind
from chat.services.scene_close import detect_scene_close from chat.services.scene_close import detect_scene_close
from chat.services.scene_summarize import apply_scene_close_summary from chat.services.scene_summarize import apply_scene_close_summary
from chat.services.state_update import compute_state_update from chat.services.state_update import compute_state_update
@@ -52,10 +53,19 @@ from chat.state.world import active_scene, get_chat, get_container
from chat.web.bots import get_conn from chat.web.bots import get_conn
from chat.web.kickoff import get_llm_client from chat.web.kickoff import get_llm_client
from chat.web.pubsub import publish from chat.web.pubsub import publish
from chat.web.render import render_turn_html as _render_turn_html
router = APIRouter() router = APIRouter()
# Module-level registry of in-flight streaming tasks, keyed by chat_id.
# The POST /chats/<id>/turns/cancel route looks up the task and calls
# .cancel(); the streaming coroutine in post_turn catches the resulting
# CancelledError, commits the partial as truncated, and unregisters.
# Single-process v1 only — sufficient for one user with multiple tabs.
_in_flight_tasks: dict[str, asyncio.Task] = {}
def _strip_ooc_for_prompt(parsed: ParsedTurn) -> str: def _strip_ooc_for_prompt(parsed: ParsedTurn) -> str:
"""Concatenate non-OOC segments back to a prose string for the prompt. """Concatenate non-OOC segments back to a prose string for the prompt.
@@ -68,16 +78,17 @@ def _strip_ooc_for_prompt(parsed: ParsedTurn) -> str:
def _read_recent_dialogue(conn, chat_id: str, limit: int = 200) -> list[dict]: def _read_recent_dialogue(conn, chat_id: str, limit: int = 200) -> list[dict]:
"""Return ``user_turn`` and ``assistant_turn`` events for ``chat_id``. """Return user-side and assistant_turn events for ``chat_id``.
Ordered oldest-first. Skips superseded and hidden rows so regenerated Includes ``user_turn``, ``user_turn_edit`` (T29 edited prose), and
turns (T29) drop out of the rendered timeline. Each entry is shaped ``assistant_turn``. Ordered oldest-first; superseded/hidden rows are
``{"speaker": <id-or-"you">, "text": <prose>}`` for the prompt skipped so regenerated turns (T29) drop out of the rendered timeline.
assembler and the chat-detail template. Each entry is shaped ``{"speaker": <id-or-"you">, "text": <prose>}``
for the prompt assembler and the chat-detail template.
""" """
cur = conn.execute( cur = conn.execute(
"SELECT id, kind, payload_json FROM event_log " "SELECT id, kind, payload_json FROM event_log "
"WHERE kind IN ('user_turn', 'assistant_turn') " "WHERE kind IN ('user_turn', 'user_turn_edit', 'assistant_turn') "
" AND superseded_by IS NULL AND hidden = 0 " " AND superseded_by IS NULL AND hidden = 0 "
"ORDER BY id DESC LIMIT ?", "ORDER BY id DESC LIMIT ?",
(limit,), (limit,),
@@ -89,7 +100,9 @@ def _read_recent_dialogue(conn, chat_id: str, limit: int = 200) -> list[dict]:
p = json.loads(payload_json) p = json.loads(payload_json)
if p.get("chat_id") != chat_id: if p.get("chat_id") != chat_id:
continue continue
if kind == "user_turn": if kind in ("user_turn", "user_turn_edit"):
# Edited prose substitutes for the original user_turn (the
# original is marked superseded_by and filtered above).
out.append({"speaker": "you", "text": p.get("prose", "")}) out.append({"speaker": "you", "text": p.get("prose", "")})
else: else:
out.append( out.append(
@@ -101,16 +114,6 @@ def _read_recent_dialogue(conn, chat_id: str, limit: int = 200) -> list[dict]:
return out return out
def _render_turn_html(speaker_label: str, text: str, *, role: str) -> str:
"""Render a single turn as a small HTML fragment (escaped)."""
return (
f'<div class="turn turn-{role}">'
f"<strong>{html.escape(speaker_label)}</strong>"
f"<p>{html.escape(text)}</p>"
f"</div>"
)
@router.post("/chats/{chat_id}/turns") @router.post("/chats/{chat_id}/turns")
async def post_turn( async def post_turn(
chat_id: str, chat_id: str,
@@ -119,6 +122,9 @@ async def post_turn(
conn=Depends(get_conn), conn=Depends(get_conn),
client=Depends(get_llm_client), client=Depends(get_llm_client),
): ):
if not prose.strip():
raise HTTPException(status_code=400, detail="prose cannot be empty")
chat = get_chat(conn, chat_id) chat = get_chat(conn, chat_id)
if chat is None: if chat is None:
raise HTTPException(status_code=404, detail=f"chat not found: {chat_id}") raise HTTPException(status_code=404, detail=f"chat not found: {chat_id}")
@@ -181,13 +187,21 @@ async def post_turn(
budget_hard=settings.narrative_budget_hard, budget_hard=settings.narrative_budget_hard,
) )
# 5. Stream and accumulate tokens. # 5. Stream and accumulate tokens. The stream runs as a Task so the
# /turns/cancel route can invoke ``Task.cancel()`` to abort it
# mid-stream. ``accumulated`` is a closure over the inner coroutine,
# so when the await on ``stream_task`` raises CancelledError below
# we still see whatever tokens were appended before cancellation.
accumulated: list[str] = [] accumulated: list[str] = []
truncated = False truncated = False
cancelled = False cancelled = False
try:
async def _stream() -> None:
async for chunk in client.stream( async for chunk in client.stream(
messages, model=settings.narrative_model messages,
model=settings.narrative_model,
max_tokens=settings.narrative_max_tokens,
temperature=settings.narrative_temperature,
): ):
accumulated.append(chunk) accumulated.append(chunk)
await publish( await publish(
@@ -198,6 +212,11 @@ async def post_turn(
"speaker_id": host_bot["id"], "speaker_id": host_bot["id"],
}, },
) )
stream_task = asyncio.create_task(_stream())
_in_flight_tasks[chat_id] = stream_task
try:
await stream_task
except asyncio.CancelledError: except asyncio.CancelledError:
# Preserve the partial output before letting the cancellation # Preserve the partial output before letting the cancellation
# propagate so the transcript reflects what the user actually saw. # propagate so the transcript reflects what the user actually saw.
@@ -206,6 +225,9 @@ async def post_turn(
except Exception: except Exception:
# Surface as a truncated turn rather than losing the partial output. # Surface as a truncated turn rather than losing the partial output.
truncated = True truncated = True
finally:
# Always unregister so a subsequent turn can register a fresh task.
_in_flight_tasks.pop(chat_id, None)
full_text = "".join(accumulated) full_text = "".join(accumulated)
@@ -409,3 +431,152 @@ async def post_turn(
raise asyncio.CancelledError raise asyncio.CancelledError
return Response(status_code=204) return Response(status_code=204)
# ---------------------------------------------------------------------------
# Cancel route (Task 34).
#
# Fire-and-forget: the Stop button POSTs here, we mark the in-flight
# streaming Task as cancelled, and return 204 immediately. The cancel
# propagates into the streaming coroutine on its next await, the
# CancelledError handler in ``post_turn`` catches it, and the partial
# is committed with ``truncated=True``. No body is needed — the SSE
# channel is the conveyor of state. If no turn is in flight (or the
# task already completed), we 204 silently so the client can fire the
# Stop button without a precondition check.
# ---------------------------------------------------------------------------
@router.post("/chats/{chat_id}/turns/cancel")
async def cancel_turn(chat_id: str, request: Request):
task = _in_flight_tasks.get(chat_id)
if task is None or task.done():
return Response(status_code=204)
task.cancel()
return Response(status_code=204)
# ---------------------------------------------------------------------------
# Rewind routes (Task 28).
#
# Two endpoints: a GET that renders the impact-preview modal, and a POST
# that actually executes the rewind. The execution path opens its own
# database connection because the route's ``conn`` is closed when the
# dependency-injection scope exits — passing it to ``execute_rewind``
# would dangle.
# ---------------------------------------------------------------------------
@router.get(
"/chats/{chat_id}/rewind/preview/{event_id}",
response_class=HTMLResponse,
)
async def rewind_preview(
chat_id: str,
event_id: int,
request: Request,
conn=Depends(get_conn),
):
"""Render the rewind impact-preview modal as a small HTML fragment.
The HTMX form inside the fragment posts to the execute endpoint
below. v1 keeps the markup minimal — Task 35 polishes the modal.
"""
chat = get_chat(conn, chat_id)
if chat is None:
raise HTTPException(status_code=404, detail=f"chat not found: {chat_id}")
preview = compute_rewind_preview(conn, event_id)
items = "".join(
f"<li>{count} × {html.escape(kind)}</li>"
for kind, count in preview["by_kind"].items()
)
body = (
"<div class='rewind-modal'>"
f"<h3>Rewind to event {event_id}?</h3>"
f"<p>This will remove {preview['total_events']} events:</p>"
f"<ul>{items}</ul>"
f"<form hx-post='/chats/{html.escape(chat_id)}/rewind/{event_id}' "
"hx-target='body' hx-swap='innerHTML'>"
"<button type='submit'>Confirm Rewind</button>"
"</form>"
"</div>"
)
return HTMLResponse(body)
# ---------------------------------------------------------------------------
# Regenerate route (Task 29).
#
# A POST that re-streams the most recent assistant turn. The prior
# ``assistant_turn`` event is kept in the log but flagged
# ``superseded_by`` so the timeline filter in :func:`_read_recent_dialogue`
# hides it. When the user supplies ``prose`` the original ``user_turn``
# is also superseded by a fresh ``user_turn_edit`` event capturing the
# edit. Significance is *not* re-run on regenerate (per plan §11.1) but
# state-update + memory writes are.
# ---------------------------------------------------------------------------
@router.post("/chats/{chat_id}/turns/{event_id}/regenerate")
async def regenerate_turn(
chat_id: str,
event_id: int,
request: Request,
prose: str | None = Form(None),
conn=Depends(get_conn),
client=Depends(get_llm_client),
):
"""Regenerate the assistant turn referenced by ``event_id``.
``prose`` is optional. When provided (and non-empty) we capture a
``user_turn_edit`` event before re-streaming. Returns 204 on
success, 404 when the chat or assistant_turn event is missing. The
SSE channel emits per-token events as the new text arrives.
"""
chat = get_chat(conn, chat_id)
if chat is None:
raise HTTPException(status_code=404, detail=f"chat not found: {chat_id}")
settings = request.app.state.settings
# Local import keeps the module import graph flat (the service
# imports from ``state`` / ``services`` siblings already).
from chat.services.regenerate import regenerate_assistant_turn
edited_prose = prose if prose else None
try:
await regenerate_assistant_turn(
conn,
client,
settings=settings,
chat_id=chat_id,
original_assistant_event_id=event_id,
edited_user_prose=edited_prose,
)
except ValueError as e:
raise HTTPException(status_code=404, detail=str(e))
return Response(status_code=204)
@router.post("/chats/{chat_id}/rewind/{event_id}")
async def rewind_execute(
chat_id: str,
event_id: int,
request: Request,
conn=Depends(get_conn),
):
"""Execute the rewind: snapshot, truncate event_log, re-project.
Note: ``conn`` is only used to validate the chat exists. The actual
rewind opens its own connection inside ``execute_rewind`` because
we need it to commit independently and survive the route's
dependency teardown.
"""
chat = get_chat(conn, chat_id)
if chat is None:
raise HTTPException(status_code=404, detail=f"chat not found: {chat_id}")
settings = request.app.state.settings
execute_rewind(
db_path=settings.db_path,
data_dir=settings.data_dir,
after_event_id=event_id,
)
return RedirectResponse(url=f"/chats/{chat_id}", status_code=303)
@@ -0,0 +1,910 @@
# Roleplay Engine — Phase 2 Implementation Plan
> **For Claude:** REQUIRED SUB-SKILL: Use `superpowers-extended-cc:executing-plans` to implement this plan task-by-task. Use `superpowers-extended-cc:dispatching-parallel-agents` for the parallel waves below.
**Goal:** Add multi-entity (3-entity) scene support: guest bot can be added to a host's chat; up to 3 entities present simultaneously (you + host + guest); turn flow handles silent witnesses, interjections, per-pair edges, and per-witness memory; drawer reflects guest state; scene close writes per-POV summaries for each present witness.
**Architecture:** Builds on Phase 1's event-sourced architecture. New event kinds (`guest_added`, `guest_removed`, `group_node_initialized`) carry the multi-entity state changes; existing handlers (`edge_update`, `memory_written`) already accept any `source_id`/`target_id` and witness mask, so most schema work is additive. The "have they met?" first-co-appearance prompt runs once per `(botA, botB)` pair and seeds initial inter-bot edges via existing `edge_update` events.
**Tech Stack:** Same as Phase 1 (Python 3.11+, FastAPI, HTMX, SQLite, Featherless). No new dependencies.
**Source-of-truth references:**
- Phase 2 scope: requirements doc §13 "Phase 2 — multi-entity"
- Behavioral details: requirements doc §6.2 (turn-taking with interjection), §7.5 (guest leaves), §8.5 (memory ownership), §11.2 (per-POV summaries on close)
- Conventions: [../../CLAUDE.md](../../CLAUDE.md) §"Behavioral defaults"
- Phase 1 plan (style, TDD pattern): [2026-04-26-v1-phase1-implementation.md](2026-04-26-v1-phase1-implementation.md)
When a task says "see §X", that's the requirements doc unless stated otherwise.
---
## Pre-flight
**Branch:** Create `phase-2` from the latest `main` after Phase 1 has been merged. If Phase 1 is still in PR review, branch off `phase-1` directly:
```bash
# Option A: after main has phase-1 merged
git checkout main && git pull && git checkout -b phase-2
# Option B: continue from phase-1 directly
git checkout phase-1 && git pull && git checkout -b phase-2
```
**Schema baseline:** Phase 1 leaves the DB at version 7. Phase 2 adds **0008_group_node.sql**. No other migrations expected.
**Pinned non-negotiables (carried forward from Phase 1):**
- State changes go through the event log. Use `append_and_apply(conn, kind, payload)` for the live path; `apply_event` only after a fresh `append_event` returning the new id.
- Witness filter every memory read at SQL level (hard `WHERE` constraint; never a soft signal).
- Edges are directed; `botA → botB` and `botB → botA` are independent records.
- Per-POV scene summaries — never write omniscient narration.
- TDD: every task starts with a failing test.
- One commit per task minimum, more if it splits naturally.
**Verification before claiming done:** Use `superpowers-extended-cc:verification-before-completion` — run the test command, paste actual output. Don't assume green.
---
## Parallel-Execution Strategy
This plan is structured into **6 waves** of tasks. Within a wave, tasks are designed to touch disjoint files so they can be executed by parallel subagents safely. Between waves, the controller (you, the controlling Claude session) merges each subagent's commits and verifies the suite stays green before dispatching the next wave.
### How to dispatch a wave in parallel
Use the **Agent tool with `isolation: "worktree"`** so each subagent gets its own git worktree. The runtime cleans up the worktree automatically if no changes are made; otherwise it returns the path + branch for the controller to merge.
In a single message, dispatch all tasks in the wave:
```
Agent({
description: "Wave 1 — T36 group_node schema",
subagent_type: "general-purpose",
isolation: "worktree",
prompt: "<full task text from below>",
})
Agent({
description: "Wave 1 — T37 guest events",
subagent_type: "general-purpose",
isolation: "worktree",
prompt: "<full task text from below>",
})
Agent({
description: "Wave 1 — T38 relationship-seed service",
subagent_type: "general-purpose",
isolation: "worktree",
prompt: "<full task text from below>",
})
```
All three subagents start simultaneously, each working on a private worktree branched off `phase-2`. They cannot see each other's changes (no shared filesystem state) — that's the safety guarantee.
### After a wave completes
1. Each subagent returns its worktree path and commit SHA.
2. **Run a spec + quality reviewer subagent on each completed task** (same pattern as Phase 1 — see `superpowers-extended-cc:requesting-code-review`).
3. **Merge the wave into `phase-2`** in any order (file-disjointness guarantees no conflict). Use fast-forward if possible:
```bash
git checkout phase-2
for branch in <wave-1-branches>; do
git merge --no-ff "$branch" -m "merge: <task description>"
done
```
4. **Run the full test suite** on the merged `phase-2`. If it's red, the wave's mutual independence assumption was violated — bisect to find the offending pair, fix, re-merge.
5. **Push `phase-2` to gitea** so the work is durable before the next wave starts.
6. Optionally clean up worktrees: `git worktree remove .worktrees/<branch>`.
### Conflict prevention checklist (apply before dispatch)
For each parallel wave, verify the **Files** sections of all tasks in that wave have **no overlapping paths**. The waves below are designed to satisfy this; if you decide to add or merge tasks, re-check.
If a hot file (`chat/web/turns.py`, `chat/services/prompt.py`, `chat/templates/_drawer.html`) needs changes from multiple tasks, do **not** parallelize them — serialize within the wave or split into separate waves.
### Failure recovery
If one subagent in a parallel wave fails (test failures, blocked, infinite loop):
- **Do not block the wave on a failure.** Cancel the failed subagent, merge the others' successful work, and re-dispatch the failed task as a single follow-up.
- If a failure exposes a bad assumption shared by multiple tasks (e.g. an event-payload schema mismatch), pause the wave and revisit the plan.
### Why each wave is parallel-safe
| Wave | Tasks | Hot files touched | Disjoint? |
|------|-------|-------------------|-----------|
| 1 | T36, T37, T38 | new files only + `chat/state/world.py` (T37 only) | ✅ |
| 2 | T39, T40, T41 | new files only + `chat/services/memory_write.py` (T41 only) | ✅ |
| 3 | T42 | `chat/web/drawer.py`, `chat/templates/_drawer.html` | (single task) |
| 4a | T43, T45 | `chat/services/prompt.py` (T43), `chat/services/scene_summarize.py` (T45) | ✅ |
| 4b | T44 | `chat/web/turns.py`, `chat/services/regenerate.py` | (single task; depends on 4a) |
| 5 | T46, T47, T48 | new tests + `chat/state/entities.py` (T47) + docs (T48) | ✅ |
---
## Task overview
```
Wave 1 ─┬─ T36: group_node schema + handler
├─ T37: guest_added / guest_removed events
└─ T38: relationship-seed service ("have they met?")
Wave 2 ─┬─ T39: interjection classifier service
├─ T40: multi-entity state-update coordinator
└─ T41: multi-witness memory write helper
Wave 3 ─── T42: drawer guest support (add/remove + render guest state)
Wave 4a ─┬─ T43: multi-entity prompt assembly (extends assemble_narrative_prompt)
└─ T45: multi-entity per-POV summaries on scene close
Wave 4b ─── T44: multi-entity turn flow integration (post_turn rewrite)
Wave 5 ─┬─ T46: witness filter test coverage (cross-witness scenarios)
├─ T47: bot reset cascades to guest scenes
└─ T48: Phase 2 documentation update
```
Critical path: 6 sequential merge points. Total tasks: 13. Wall-clock parallelism advantage depends on subagent dispatch overhead, but in principle Wave 1's 3 tasks can run concurrently in ~the time of one task.
---
## Wave 1 — Foundation
These three tasks are **fully independent**: T36 adds new files only, T37 modifies `chat/state/world.py` (additive event handlers), T38 adds new files only. Dispatch all three in parallel.
### Task 36: Group node schema + handler
**Files:**
- Create: `chat/db/migrations/0008_group_node.sql`
- Create: `chat/state/group_node.py`
- Create: `tests/test_group_node.py`
**Spec:** Adds the `group_node` table (one row per chat, populated when all three entities are present in a scene) and a projector handler for the `group_node_initialized` event. The group node carries the shared summary, group dynamic, inside jokes, and active threads (Phase 3 will populate `active_threads`; for Phase 2, just `summary` and `dynamic` matter).
**Step 1: Write the failing test**
```python
# tests/test_group_node.py
from chat.db.migrate import apply_migrations
from chat.db.connection import open_db
from chat.eventlog.log import append_event
from chat.eventlog.projector import project
from chat.state.group_node import get_group_node
import chat.state.entities # noqa
import chat.state.world # noqa
import chat.state.group_node # noqa: F401 - registers handlers
def test_group_node_initialized_creates_row(tmp_path):
db = tmp_path / "t.db"
apply_migrations(db)
with open_db(db) as conn:
# Seed bot, you, chat (minimal world state — no scene yet)
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="group_node_initialized", payload={
"chat_id": "chat_bot_a",
"members": ["you", "bot_a", "bot_b"],
"summary": "",
"dynamic": "",
})
project(conn)
gn = get_group_node(conn, "chat_bot_a")
assert gn is not None
assert gn["members"] == ["you", "bot_a", "bot_b"]
assert gn["summary"] == ""
```
**Step 2: Run test to verify it fails**
```bash
.venv/bin/pytest tests/test_group_node.py -v
```
Expected: `ModuleNotFoundError: No module named 'chat.state.group_node'`.
**Step 3: Write minimal implementation**
`chat/db/migrations/0008_group_node.sql`:
```sql
CREATE TABLE group_node (
chat_id TEXT PRIMARY KEY,
members_json TEXT NOT NULL,
summary TEXT NOT NULL DEFAULT '',
dynamic TEXT NOT NULL DEFAULT '',
threads_json TEXT NOT NULL DEFAULT '[]',
updated_at TEXT NOT NULL DEFAULT (datetime('now'))
);
```
`chat/state/group_node.py`:
```python
from __future__ import annotations
import json
from sqlite3 import Connection
from chat.eventlog.projector import on
from chat.eventlog.log import Event
@on("group_node_initialized")
def _apply_group_node_initialized(conn: Connection, e: Event) -> None:
p = e.payload
conn.execute(
"INSERT OR REPLACE INTO group_node "
"(chat_id, members_json, summary, dynamic, threads_json) "
"VALUES (?, ?, ?, ?, ?)",
(
p["chat_id"],
json.dumps(p["members"]),
p.get("summary", ""),
p.get("dynamic", ""),
json.dumps(p.get("threads", [])),
),
)
@on("group_node_updated")
def _apply_group_node_updated(conn: Connection, e: Event) -> None:
"""T45 calls this on scene close to rewrite summary + dynamic."""
p = e.payload
conn.execute(
"UPDATE group_node SET summary = ?, dynamic = ?, updated_at = datetime('now') "
"WHERE chat_id = ?",
(p.get("summary", ""), p.get("dynamic", ""), p["chat_id"]),
)
def get_group_node(conn: Connection, chat_id: str) -> dict | None:
row = conn.execute(
"SELECT chat_id, members_json, summary, dynamic, threads_json, updated_at "
"FROM group_node WHERE chat_id = ?",
(chat_id,),
).fetchone()
if not row:
return None
return {
"chat_id": row[0],
"members": json.loads(row[1]),
"summary": row[2],
"dynamic": row[3],
"threads": json.loads(row[4]),
"updated_at": row[5],
}
```
**Step 4: Run test to verify it passes**
```bash
.venv/bin/pytest tests/test_group_node.py -v
```
Expected: 1 passed.
**Step 5: Commit**
```bash
git add chat/db/migrations/0008_group_node.sql chat/state/group_node.py tests/test_group_node.py
git commit -m "feat: group_node schema + projector handlers"
```
**Notes for the implementer:**
- Add a second test for `group_node_updated`: append init then update, assert `summary` and `dynamic` change but `members` stays.
- Add a test for `get_group_node` returning `None` on a missing chat_id.
- Schema version after migration: 8. The migration runner handles this automatically; no test assertion on schema_version.
---
### Task 37: Guest add / remove events + handlers
**Files:**
- Modify: `chat/state/world.py` (add `_apply_guest_added`, `_apply_guest_removed` handlers; both update `chats.guest_bot_id`)
- Create: `tests/test_guest_events.py`
**Spec:** Two new event kinds.
- `guest_added` payload: `{chat_id, guest_bot_id}`. Handler sets `chats.guest_bot_id = ?`.
- `guest_removed` payload: `{chat_id}`. Handler sets `chats.guest_bot_id = NULL`.
These are pure state mutations — no related side effects. The kickoff parse-and-confirm flow (T13, Phase 1) and the new T39 interjection / T42 drawer routes will append these events.
**Step 1: Write the failing test**
```python
# tests/test_guest_events.py
from chat.db.migrate import apply_migrations
from chat.db.connection import open_db
from chat.eventlog.log import append_event
from chat.eventlog.projector import project
from chat.state.world import get_chat
import chat.state.entities # noqa
import chat.state.world # noqa
def test_guest_added_sets_guest_bot_id(tmp_path):
db = tmp_path / "t.db"
apply_migrations(db)
with open_db(db) as conn:
# Seed bot, chat
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="bot_authored", payload={
"id": "bot_b", "name": "BotB", "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="guest_added", payload={
"chat_id": "chat_bot_a", "guest_bot_id": "bot_b",
})
project(conn)
chat = get_chat(conn, "chat_bot_a")
assert chat["guest_bot_id"] == "bot_b"
def test_guest_removed_clears_guest_bot_id(tmp_path):
# similar: add then remove, assert guest_bot_id is None
...
```
**Step 3: Implementation**
In `chat/state/world.py`, add the two handlers next to `_apply_chat_created`:
```python
@on("guest_added")
def _apply_guest_added(conn: Connection, e: Event) -> None:
p = e.payload
conn.execute(
"UPDATE chats SET guest_bot_id = ? WHERE id = ?",
(p["guest_bot_id"], p["chat_id"]),
)
@on("guest_removed")
def _apply_guest_removed(conn: Connection, e: Event) -> None:
p = e.payload
conn.execute(
"UPDATE chats SET guest_bot_id = NULL WHERE id = ?",
(p["chat_id"],),
)
```
**Step 5: Commit**
```bash
git add chat/state/world.py tests/test_guest_events.py
git commit -m "feat: guest_added / guest_removed event handlers"
```
**Notes:**
- 2 tests minimum (added, removed). Optional third: idempotent re-add (overwrites cleanly).
- Don't add any UI here — T42 handles UI.
---
### Task 38: Relationship-seed service ("have they met?")
**Files:**
- Create: `chat/services/relationship_seed.py`
- Create: `tests/test_relationship_seed.py`
**Spec:** Per requirements §5.2: when two bots first co-appear in a chat, prompt the user with "Have they met before? If yes, write a short prose seed describing how." The seed is parsed via classifier into structured `botA ↔ botB` edge content (summary + initial knowledge facts).
This task adds the **service layer** only. T39 (interjection) doesn't touch this; T42 (drawer guest UI) calls it via a route added there. So at the service level, we just expose:
```python
async def seed_inter_bot_edges(
client: LLMClient,
*,
classifier_model: str,
bot_a_id: str,
bot_a_name: str,
bot_b_id: str,
bot_b_name: str,
relationship_prose: str, # user-supplied prose; empty = "they haven't met"
timeout_s: float = 30.0,
) -> RelationshipSeed:
"""Parse user-supplied prose into structured edge content for both
directed pairs (bot_a → bot_b and bot_b → bot_a). Return the
RelationshipSeed; caller is responsible for emitting two edge_update
events."""
```
`RelationshipSeed`:
```python
class RelationshipSeed(BaseModel):
a_to_b_summary: str = ""
a_to_b_knowledge_facts: list[str] = Field(default_factory=list)
a_to_b_affinity_delta: int = 0 # signed, -10..+10 typical
a_to_b_trust_delta: int = 0
b_to_a_summary: str = ""
b_to_a_knowledge_facts: list[str] = Field(default_factory=list)
b_to_a_affinity_delta: int = 0
b_to_a_trust_delta: int = 0
```
If `relationship_prose` is empty/whitespace, short-circuit and return an empty `RelationshipSeed` (they haven't met → fresh edges with default 50/50).
**Step 1: Failing test**
```python
import pytest, json
from chat.llm.mock import MockLLMClient
from chat.services.relationship_seed import seed_inter_bot_edges, RelationshipSeed
@pytest.mark.asyncio
async def test_seed_parses_canned_prose():
canned = json.dumps({
"a_to_b_summary": "BotA and BotB went to college together.",
"a_to_b_knowledge_facts": ["BotB has a younger brother."],
"a_to_b_affinity_delta": 5,
"a_to_b_trust_delta": 3,
"b_to_a_summary": "BotB sees BotA as the responsible one.",
"b_to_a_knowledge_facts": ["BotA was once a TA."],
"b_to_a_affinity_delta": 4,
"b_to_a_trust_delta": 5,
})
mock = MockLLMClient(canned=[canned])
seed = await seed_inter_bot_edges(
mock, classifier_model="x",
bot_a_id="bot_a", bot_a_name="BotA",
bot_b_id="bot_b", bot_b_name="BotB",
relationship_prose="They went to college together; BotB still sees BotA as the responsible one.",
)
assert "college" in seed.a_to_b_summary
assert seed.a_to_b_affinity_delta == 5
@pytest.mark.asyncio
async def test_seed_empty_prose_returns_empty():
mock = MockLLMClient(canned=[]) # never called
seed = await seed_inter_bot_edges(
mock, classifier_model="x",
bot_a_id="bot_a", bot_a_name="BotA",
bot_b_id="bot_b", bot_b_name="BotB",
relationship_prose="",
)
assert seed == RelationshipSeed()
```
**Step 3: Minimal impl**
Wraps `classify()` from `chat.llm.classify` with a `RelationshipSeed` schema and a system prompt explaining the task.
**Step 5: Commit**
```bash
git add chat/services/relationship_seed.py tests/test_relationship_seed.py
git commit -m "feat: relationship-seed service for first-co-appearance prompt"
```
---
## Wave 2 — Services
After Wave 1 merges, dispatch Wave 2 in parallel. T39 and T40 are new files; T41 modifies `chat/services/memory_write.py` (additive — adds a new function alongside existing `record_turn_memory`).
### Task 39: Interjection classifier service
**Files:**
- Create: `chat/services/interjection.py`
- Create: `tests/test_interjection.py`
**Spec:** Per requirements §6.2: when a guest is present and the addressee bot has just spoken, decide whether the *non-addressee* bot interjects. Classifier returns `{should_interject: bool, reason: str}`. Caller (T44 turn flow) generates the interjection beat as a brief follow-on response if `should_interject`.
**Public API:**
```python
class InterjectionDecision(BaseModel):
should_interject: bool = False
reason: str = ""
async def detect_interjection(
client: LLMClient,
*,
classifier_model: str,
addressee_name: str,
addressee_just_said: str,
silent_witness_name: str,
silent_witness_persona: str,
silent_witness_edge_to_addressee: dict, # {affinity, trust, summary}
silent_witness_edge_to_you: dict,
you_just_said: str,
timeout_s: float = 30.0,
) -> InterjectionDecision:
"""Decide whether the silent witness bot interjects after the addressee
finishes speaking. Conservative bias — most turns should NOT interject
(return False). Trigger only when the witness's character would
plausibly speak up: jealousy, surprise, agreement worth voicing,
correcting a falsehood, etc.
"""
```
Classifier system prompt should explicitly bias toward `should_interject=false` (per spec: "addressee gets the floor"; interjection is the exception).
**Tests:** 3 minimum.
1. Mock returns `{should_interject: true, reason: "..."}` → result is True.
2. Mock returns `{should_interject: false}` → result is False.
3. Classifier failure → fallback default (`should_interject=false`, `reason="fallback"`).
**Commit:** `feat: interjection classifier service`
---
### Task 40: Multi-entity state-update coordinator
**Files:**
- Create: `chat/services/multi_state_update.py`
- Create: `tests/test_multi_state_update.py`
**Spec:** Wraps the existing `chat.services.state_update.compute_state_update` (single-pair) into a coordinator that runs state updates for **all directed pairs of present entities**. With 3 entities (you, host, guest), that's 6 pairs:
```
you → host, host → you
you → guest, guest → you
host → guest, guest → host
```
Returns a list of `(source_id, target_id, StateUpdate)` tuples; caller (T44) emits one `edge_update` event per tuple via `append_and_apply`.
**Public API:**
```python
async def compute_state_updates_for_present(
client: LLMClient,
*,
classifier_model: str,
present_ids: list[str], # e.g. ["you", "bot_a", "bot_b"]
present_names: dict[str, str], # id -> display name
personas: dict[str, str], # id -> persona blob
prior_edges: dict[tuple[str, str], dict], # (src, tgt) -> {affinity, trust, summary}
recent_dialogue: list[dict], # [{speaker, text}, ...]
timeout_s: float = 30.0,
) -> list[tuple[str, str, StateUpdate]]:
"""Run compute_state_update for every directed pair where source != target.
Returns list of (source_id, target_id, update) tuples. Skips pairs
involving "you" with itself.
"""
```
Implementation: nested loops over `present_ids`, sequential calls to `compute_state_update` (parallel calls would exceed the Featherless 2-connection cap from the FeatherlessClient semaphore).
**Tests:** 3 minimum.
1. With 2 present (you, host) → returns 2 updates (existing 1A/2D parity).
2. With 3 present (you, host, guest) → returns 6 updates, one per directed non-self pair.
3. Failures in one pair don't kill the whole batch (per-pair `compute_state_update` already has a default fallback).
**Commit:** `feat: multi-entity state-update coordinator`
---
### Task 41: Multi-witness memory write helper
**Files:**
- Modify: `chat/services/memory_write.py` (add `record_turn_memory_for_present` alongside existing `record_turn_memory`; do NOT remove or change `record_turn_memory`)
- Add tests to: `tests/test_memory_write.py`
**Spec:** Currently Phase 1's `record_turn_memory(conn, *, chat_id, host_bot_id, narrative_text, ...)` writes a single memory event for the host bot's POV. With a guest present, we need:
- One memory in the host's store (witness mask `[1, 1, 1]` if you/host/guest present)
- One memory in the guest's store (same witness mask, owner = guest_bot_id)
"You" still doesn't have a memory store in v1 (per §5.4 / §11.2).
**New helper:**
```python
def record_turn_memory_for_present(
conn,
*,
chat_id: str,
host_bot_id: str,
guest_bot_id: str | None,
narrative_text: str,
scene_id: int | None = None,
chat_clock_at: str | None = None,
source: str = "direct",
significance: int = 1,
) -> dict[str, tuple[int, int]]:
"""Write a memory_written event for each present bot witness (host
always; guest if guest_bot_id is not None). Returns {bot_id:
(event_id, memory_id)}.
Witness mask is [1, 1, 1] when guest is present, [1, 1, 0] otherwise
(mirrors Phase 1 single-bot behavior when guest_bot_id is None).
"""
```
Implementation: appends one `memory_written` event per present bot, calling `append_and_apply` for each, and queries the resulting `memories.id` per owner+chat just like Phase 1's `record_turn_memory`.
**Tests:** 3 minimum, added to `tests/test_memory_write.py`:
1. With `guest_bot_id=None`, behaves identically to `record_turn_memory` (one memory for host, witness `[1, 1, 0]`).
2. With `guest_bot_id="bot_b"`, writes two memories — one each for host and guest, both with witness `[1, 1, 1]`.
3. Returned dict keys match `{host_bot_id, guest_bot_id}` (or just `{host_bot_id}` when no guest).
**Commit:** `feat: multi-witness memory write helper`
---
## Wave 3 — Drawer guest support (single task)
This wave is one task because all Phase 2 drawer work touches the same two files (`chat/web/drawer.py` and `chat/templates/_drawer.html`). Splitting would force serial execution with conflict resolution. Single-task wave runs alone.
### Task 42: Drawer guest support (add/remove + render)
**Files:**
- Modify: `chat/web/drawer.py` (add `POST /chats/{chat_id}/drawer/guest/add`, `POST /chats/{chat_id}/drawer/guest/remove`; extend `drawer` GET handler to query guest state when present)
- Modify: `chat/templates/_drawer.html` (render guest activity, guest edges, group node summary; add "Add guest" form and "Remove guest" button when applicable)
- Create: `tests/test_drawer_guest.py`
**Spec:**
**GET /chats/{chat_id}/drawer** (extend, don't replace):
- Read `chat["guest_bot_id"]` from the existing `get_chat` query.
- If guest present: also fetch `get_bot(conn, guest_bot_id)`, `get_activity(conn, guest_bot_id)`, edges in both `host ↔ guest` directions, edges in both `you ↔ guest` directions, and `get_group_node(conn, chat_id)`.
- Pass all of this to the template.
**Template changes:**
- New section "Guest" rendering guest's name, activity, and the four edges involving the guest.
- New section "Group" rendering `group_node.summary` and `group_node.dynamic` when present.
- "Add guest" button → expands form with: bot selector (dropdown of authored bots not currently in this chat) + relationship prose textarea (the "have they met?" prompt).
- "Remove guest" button visible when a guest is present.
**POST /chats/{chat_id}/drawer/guest/add** route:
1. Read form: `guest_bot_id`, `relationship_prose`.
2. 404 if chat or guest_bot is missing.
3. 400 if guest_bot_id == host_bot_id.
4. 400 if a guest is already present.
5. Call `seed_inter_bot_edges` (T38) with the prose. May produce empty seed if prose is blank.
6. Append events: `guest_added`, then up to 2 `edge_update` events (host ↔ guest deltas from the seed). Use `append_and_apply` for each.
7. If all 3 entities are now present and no `group_node` row exists for this chat, append `group_node_initialized` with members=[you, host, guest] and empty summary/dynamic.
8. Return refreshed drawer partial.
**POST /chats/{chat_id}/drawer/guest/remove** route:
1. 404 if chat missing; 400 if no guest present.
2. Append `scene_closed` for the active scene (per §7.5: removing the guest closes the current scene).
3. Append `guest_removed`.
4. (Per §7.5 the host's chat then implicitly opens a new scene with you+host. For Phase 2, leave that as a manual "next user message creates the new scene" — same as Phase 1 mid-chat reset semantics. Phase 3 may auto-open.)
5. Return refreshed drawer partial.
**Tests (`tests/test_drawer_guest.py`):** 6 minimum.
1. GET drawer with no guest → no "Guest" section in body.
2. POST add guest → 303-or-200 with refreshed drawer; chat.guest_bot_id is set; `group_node` row created; relationship-seed mock returns canned values; edges have the seeded values.
3. POST add guest with empty relationship_prose → guest added; `seed_inter_bot_edges` short-circuits; edges remain at default 50/50.
4. POST add guest when one is already present → 400.
5. POST remove guest → guest_bot_id NULL, scene_closed event written.
6. GET drawer with guest present → "Guest" section + group_node summary visible.
**Commit:** `feat: drawer guest add/remove + render`
**Notes for implementer:**
- The guest-bot-selector dropdown lists bots from `list_bots(conn)` minus the host. Don't filter for "bots not in any chat" — guests can be in multiple chats simultaneously (each chat has its own scene state).
- The "have they met?" prose textarea is the per-pair prompt. v1 only fires it on first co-appearance globally; for v2, fire it every time a `(host, guest)` pair has no existing `host → guest` edge. After the first add, the edge exists, so subsequent adds skip the prose (or render it disabled with "you've already met"). Treat this as Phase 2.5 polish if it gets fiddly — for T42 just always show the prose textarea, blank by default.
- The drawer route already uses `Depends(get_conn)` and templates; reuse the existing dependency and TEMPLATES instance.
---
## Wave 4a — Multi-entity prompt + scene close (parallel)
T43 and T45 touch different files (`prompt.py` and `scene_summarize.py`). Dispatch both in parallel.
### Task 43: Multi-entity prompt assembly
**Files:**
- Modify: `chat/services/prompt.py` (extend `assemble_narrative_prompt` to handle a `guest_id` parameter and fetch guest activity, guest edge, group node into the prompt blocks)
- Add tests to: `tests/test_prompt.py`
**Spec:** The current `assemble_narrative_prompt(conn, *, chat_id, speaker_bot_id, addressee="you", ...)` only handles you+host. Extend:
- Accept a `guest_id: str | None = None` parameter (auto-fetched from `chat.guest_bot_id` if not passed; explicit override for tests).
- When `guest_id` is provided:
- Activity block includes the guest's activity (`get_activity(conn, guest_id)`).
- If `speaker_bot_id == guest_id`, the addressee defaults to "you" but caller can override.
- "Speaker's other edges" SHOULD-tier block includes speaker → non-addressee (e.g., host → guest if speaker is host and addressee is you).
- MUST-tier identity block unchanged (still just speaker).
- Group-node summary becomes a SHOULD-tier block when all three are present (after MUST, before retrieved memories).
- Token budget tier ordering unchanged.
**Tests:** 4 minimum, added to `tests/test_prompt.py`:
1. With `guest_id=None`, output matches existing 2-entity behavior (regression).
2. With `guest_id="bot_b"` present and group_node populated, the assembled system message contains: speaker identity, guest activity, group_node summary, host→guest edge for the speaker.
3. Speaker is the guest (`speaker_bot_id == guest_id`), addressee="you" → guest's edges and group node correctly oriented.
4. Tight budget forces NICE-trim of guest activity → MUST blocks (speaker identity, edge_to_addressee, last 4 turns) survive.
**Commit:** `feat: multi-entity prompt assembly with guest activity, edges, group node`
---
### Task 45: Multi-entity per-POV summaries on scene close
**Files:**
- Modify: `chat/services/scene_summarize.py` (extend `apply_scene_close_summary` to write per-POV summaries for **each present witness** with a memory store, not just host)
- Modify: tests in `tests/test_per_pov_summary.py`
**Spec:** Phase 1's `apply_scene_close_summary` only summarizes from the host bot's POV. For Phase 2:
- Determine present witnesses with memory stores: host always; guest if `chat.guest_bot_id is not None`.
- For each, generate an independent per-POV summary via `summarize_scene` (the existing classifier wrapper). Each call uses **that bot's** persona, `you_name`, prior `bot → you` edge summary, and the same dialogue.
- Update each owner's memories of the closing scene with their per-POV summary.
- Update **all directed bot → you edges** with per-POV-derived `summary` content.
- If `group_node` exists for this chat, also append `group_node_updated` event with new `summary` and `dynamic` derived from the group view (run `summarize_scene` once with `bot_name="group"`, `bot_persona="all participants"` for a meta-summary). For v1 simplicity, the meta-summary can be naive concat of the host's per-POV summary + guest's per-POV summary; full LLM-merged group view is deferred to Phase 2.5.
**Tests:** 4 minimum, added to `tests/test_per_pov_summary.py`:
1. With no guest, behavior matches Phase 1 (regression test).
2. With guest, `apply_scene_close_summary` calls `summarize_scene` twice (one per bot witness) — assert mock called 2x.
3. After close, each bot's memories of the closed scene have their respective per-POV summary (different text).
4. With group_node present, after close `get_group_node(conn, chat_id).summary` is updated.
**Commit:** `feat: per-POV summaries on close for each present witness`
---
## Wave 4b — Turn flow integration (single task; depends on 4a)
T44 ties everything together. It modifies `chat/web/turns.py` (post_turn) and `chat/services/regenerate.py` to use the new multi-entity primitives. Must run after Wave 4a is merged so `assemble_narrative_prompt` accepts `guest_id` and `apply_scene_close_summary` handles guest.
### Task 44: Multi-entity turn flow
**Files:**
- Modify: `chat/web/turns.py` (rewrite `post_turn` to: parse turn → optionally close scene → assemble prompt with guest → narrative stream → write memories for ALL witnesses → state updates for ALL pairs → interjection check + interjection narrative if needed)
- Modify: `chat/services/regenerate.py` (mirror the changes — regenerated turn rebuilds with guest in scope)
- Modify: tests in `tests/test_turn_flow.py` (add multi-entity scenarios)
**Spec:** Refactored `post_turn` flow:
```
1. Validate prose (existing 400 check).
2. Look up chat, host_bot, guest_bot (None if no guest).
3. Parse turn (existing parse_turn).
4. Append user_turn event.
5. Append assistant_turn_started.
6. Detect scene close (existing path; runs even with guest).
7. (Recent dialogue read with multi-witness in mind — same query.)
8. Determine ADDRESSEE: simplest v2 heuristic — addressee is host unless
prose explicitly names guest_bot.name. Pass to assemble_narrative_prompt.
9. Assemble narrative prompt with speaker=addressee, guest_id passed.
10. Stream narrative; broadcast tokens; commit assistant_turn (existing).
11. Write memories: record_turn_memory_for_present(host, guest).
12. State updates: compute_state_updates_for_present, then append_and_apply
one edge_update per pair.
13. INTERJECTION CHECK (only if guest present and addressee != silent witness):
a. Call detect_interjection with the silent witness as candidate.
b. If should_interject: assemble narrative prompt with speaker=silent_witness,
addressee=host (or whoever just spoke), and instruct briefly.
c. Stream second narrative; broadcast as second turn_html; commit second
assistant_turn event.
d. Run state updates + memory writes for the interjection turn too
(smaller scope — just the interjector's outgoing edges + memories).
14. Scene close summary (existing path; now multi-witness via T45).
15. Broadcast turn_html for primary + interjection (if any).
16. Return 204.
```
**Addressee heuristic (Phase 2 v1):** simple substring match on bot names. If both names appear or neither: addressee defaults to host. Phase 2.5 / Phase 3 may improve with a classifier call.
**Cancel & truncated:** unchanged from Phase 1 — both halves of a streaming turn (primary + interjection) cancel together.
**`regenerate.py` changes:** parallel to `turns.py` — multi-entity prompt assembly + multi-witness memory + multi-pair state update. Interjection regeneration is deferred to Phase 2.5 (regenerate only the addressee's turn for v2).
**Tests added to `tests/test_turn_flow.py`:** 5 minimum.
1. Single-bot turn (no guest): full suite still passes (regression).
2. Multi-bot turn, no interjection: `post_turn` produces 1 user_turn + 1 assistant_turn + 6 edge_updates + 2 memory_written events. Mock interjection returns `should_interject=false`.
3. Multi-bot turn, with interjection: produces user_turn + 2 assistant_turns + 12 edge_updates + 4 memory_written events.
4. Multi-bot turn, scene close fires: `scene_closed` + multi-POV summaries written (per T45).
5. Addressee detection: prose `"BotB, what do you think?"` routes to BotB as speaker.
**Commit:** `feat: multi-entity turn flow with interjection support`
**Notes for implementer:**
- This task is the largest in Phase 2 by line count. Budget for ~150-300 lines of changes across `turns.py` and tests. The implementer should split commits if it helps clarity (one commit for primary turn, one for interjection, one for tests).
- Update the existing `_seed_chat` helper in `tests/test_turn_flow.py` to optionally seed a guest, and add `_seed_chat_with_guest` if cleaner.
- The fixture for the LLM mock now needs to provide canned responses for: parse_turn + scene_close_detect + narrative + state_updates×6 + interjection_decision + (optionally) interjection_narrative + state_updates×2 (interjection's outgoing only).
---
## Wave 5 — Polish (parallel)
Three independent tasks. Dispatch all three in parallel after Wave 4b merges.
### Task 46: Witness filter test coverage
**Files:**
- Create: `tests/test_witness_filter_multi.py`
**Spec:** Phase 1 tested witness filtering with single-bot scenarios. Phase 2 needs explicit tests for the cross-witness cases:
- Memory with witness `[1, 1, 0]`: visible to host, not guest (when guest queries from their POV).
- Memory with witness `[0, 1, 1]`: visible to host and guest, not "you".
- Secondhand-source memories: `source: "told_by:bot_a"`, witness flag for bot_b set, reliability < 1.0.
5 tests minimum.
**Commit:** `test: witness filter coverage for multi-entity scenarios`
---
### Task 47: Bot reset cascades to guest scenes
**Files:**
- Modify: `chat/state/entities.py` (`_apply_bot_reset` extended to also remove the bot's `guest_bot_id` references in OTHER chats: `UPDATE chats SET guest_bot_id = NULL WHERE guest_bot_id = ?`; remove the bot's activity row in those chats too)
- Modify: tests in `tests/test_reset.py` (add scenario: bot is guest in another's chat; reset clears the guest reference)
**Spec:** Currently `bot_reset` purges the bot's own chat state, memories, and edges. With Phase 2, a bot can be a guest in another bot's chat — that reference must also clear. Otherwise the host's chat sees a stale guest_bot_id pointing at a phantom bot.
Update `_apply_bot_reset` handler:
```python
# After existing purges:
conn.execute("UPDATE chats SET guest_bot_id = NULL WHERE guest_bot_id = ?", (bot_id,))
conn.execute("DELETE FROM activity WHERE entity_id = ?", (bot_id,)) # already there; covers all chats
```
(Activity is keyed by entity_id, so the existing line handles cross-chat activity rows already.)
**Tests:** 2 minimum, added to `tests/test_reset.py`.
1. BotB is guest in BotA's chat. Reset BotB. Assert `chat_bot_a.guest_bot_id` is NULL.
2. BotB has memories (witness flag set, owner=bot_b) from being guest in BotA's chat. Reset BotB. Assert those memories are gone.
**Commit:** `fix: bot_reset cascades to guest references in other chats`
---
### Task 48: Phase 2 documentation update
**Files:**
- Modify: `CLAUDE.md` (add "Phase 2 status" section; update "Behavioral defaults" with multi-entity additions; add to "Phase 1.5 / 2 cleanup backlog" any v2 follow-ups discovered during execution)
- Modify: `docs/plans/2026-04-26-v1-requirements-design.md` (mark Phase 2 deliverables as "shipped" in the appendix decisions log)
**Spec:** Documentation-only task. Run last in Phase 2 so it captures any deviations from the plan that emerged during execution. Reflect:
- Multi-entity scene support (you + host + guest).
- Interjection model (default false; explicit signals only).
- Per-POV summaries on close for all witnesses with memory stores.
- Group node populated on first 3-entity scene; updated on close.
- Phase 2 known limitations:
- "Meanwhile…" (scene config 4 — bot+bot without you) deferred to Phase 3.
- Interjection regeneration deferred (regenerate only acts on the addressee turn).
- Addressee detection is a simple name-match heuristic (no classifier call yet).
**Commit:** `docs: phase 2 status, behavioral defaults, deferred items`
---
## Wrap-up
After Wave 5 lands:
1. **Run full suite** on `phase-2`: should be ~210+ tests passing (168 from Phase 1 + ~45 new).
2. **Manual smoke**:
- Add a guest to one of the seeded bots' chats via the drawer.
- Verify "have they met?" prose seeds inter-bot edges.
- Play a few turns; verify host responds normally; verify guest occasionally interjects.
- Close the scene; check drawer for two distinct per-POV summaries.
- Remove guest mid-scene; check scene_closed fires.
- Reset a guest bot from another chat; verify guest_bot_id reference clears.
3. **Push `phase-2`** to gitea.
4. **Open PR** `phase-2 → main`.
5. **Phase 2.5 backlog candidates** (track in CLAUDE.md): interjection regenerate UI, classifier-based addressee detection, group-node LLM-merged meta-summary, drawer "first-meeting" gate vs "they already know each other" toggle, witness flag editing in drawer (currently read-only by spec).
---
## Notes for the controller running this plan
- **Don't dispatch Wave 4b until Wave 4a is merged AND tested green on `phase-2`.** Wave 4b's `turns.py` changes import the new `assemble_narrative_prompt` signature from Wave 4a's `prompt.py`; missing that produces import-time failures.
- **After each parallel wave**, the controller should run a code-review subagent (`subagent-driven-development` skill's two-stage review pattern) on each task before merging to `phase-2`. For purely mechanical tasks, a combined spec+quality review is acceptable.
- **If a parallel wave's merge produces a conflict**, the wave's file-disjointness assumption was violated. Bisect the affected pair, fix the offending task in a follow-up commit on `phase-2`, and proceed.
- **Token-spend rough estimate**: Phase 2 should be ~30-40% the size of Phase 1 (smaller scope; reuses Phase 1 patterns). Per-task token spend similar to Phase 1.
- **DO NOT modify Phase 1 code paths** unless explicitly required (e.g., Wave 5 T47 modifies `_apply_bot_reset` because the cascade is genuinely new behavior). The single-bot path must continue to work end-to-end after each wave.
@@ -0,0 +1,20 @@
{
"planPath": "docs/plans/2026-04-26-v2-phase2-implementation.md",
"tasks": [
{"id": 36, "subject": "T36: group_node schema + projector handlers", "status": "pending", "wave": 1, "parallelGroup": "wave-1"},
{"id": 37, "subject": "T37: guest_added / guest_removed event handlers", "status": "pending", "wave": 1, "parallelGroup": "wave-1"},
{"id": 38, "subject": "T38: relationship-seed service for first-co-appearance prompt", "status": "pending", "wave": 1, "parallelGroup": "wave-1"},
{"id": 39, "subject": "T39: interjection classifier service", "status": "pending", "wave": 2, "parallelGroup": "wave-2", "blockedBy": [37]},
{"id": 40, "subject": "T40: multi-entity state-update coordinator", "status": "pending", "wave": 2, "parallelGroup": "wave-2", "blockedBy": [37]},
{"id": 41, "subject": "T41: multi-witness memory write helper", "status": "pending", "wave": 2, "parallelGroup": "wave-2", "blockedBy": [37]},
{"id": 42, "subject": "T42: drawer guest add/remove + render", "status": "pending", "wave": 3, "parallelGroup": null, "blockedBy": [36, 37, 38]},
{"id": 43, "subject": "T43: multi-entity prompt assembly with guest activity, edges, group node", "status": "pending", "wave": 4, "parallelGroup": "wave-4a", "blockedBy": [36, 37]},
{"id": 45, "subject": "T45: per-POV summaries on close for each present witness", "status": "pending", "wave": 4, "parallelGroup": "wave-4a", "blockedBy": [36, 37]},
{"id": 44, "subject": "T44: multi-entity turn flow with interjection support", "status": "pending", "wave": 4, "parallelGroup": null, "blockedBy": [39, 40, 41, 43, 45]},
{"id": 46, "subject": "T46: witness filter test coverage for multi-entity scenarios", "status": "pending", "wave": 5, "parallelGroup": "wave-5", "blockedBy": [44]},
{"id": 47, "subject": "T47: bot_reset cascades to guest references in other chats", "status": "pending", "wave": 5, "parallelGroup": "wave-5", "blockedBy": [37]},
{"id": 48, "subject": "T48: Phase 2 documentation update", "status": "pending", "wave": 5, "parallelGroup": "wave-5", "blockedBy": [44]}
],
"lastUpdated": "2026-04-26T00:00:00Z",
"notes": "13 tasks across 6 waves (1, 2, 3, 4a, 4b, 5). Waves 1, 2, 4a, 5 are parallel-safe (file-disjoint within each). Waves 3 and 4b are single-task. Use Agent tool with isolation: 'worktree' to dispatch parallel tasks. Merge each wave's worktrees back into phase-2 before dispatching the next wave. See plan §Parallel-Execution Strategy for full guidance."
}
+7
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@@ -19,6 +19,13 @@ dependencies = [
[project.optional-dependencies] [project.optional-dependencies]
dev = ["pytest>=8", "pytest-asyncio>=0.23", "freezegun>=1.4"] dev = ["pytest>=8", "pytest-asyncio>=0.23", "freezegun>=1.4"]
[build-system]
requires = ["setuptools>=61"]
build-backend = "setuptools.build_meta"
[tool.setuptools.packages.find]
include = ["chat*"]
[tool.pytest.ini_options] [tool.pytest.ini_options]
pythonpath = ["."] pythonpath = ["."]
asyncio_mode = "auto" asyncio_mode = "auto"
+253
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@@ -0,0 +1,253 @@
"""Seed three sample bots via direct event-log append.
Idempotent: re-running skips bots whose ids already exist.
Run from the repo root:
.venv/bin/python scripts/seed_sample_bots.py
After running, walk each bot through kickoff parse-and-confirm at:
http://127.0.0.1:8000/bots/<id>/kickoff
"""
from __future__ import annotations
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_and_apply
from chat.state.entities import get_bot
# Trigger handler registration.
import chat.state.entities # noqa: F401
import chat.state.edges # noqa: F401
import chat.state.memory # noqa: F401
import chat.state.world # noqa: F401
import chat.state.manual_edit # noqa: F401
SAMPLES: list[dict] = [
{
"id": "maya",
"name": "Maya Chen",
"persona": (
"31, senior product designer at the same company you work for. "
"Sharp eye for what isn't said. Outwardly composed and dryly funny; "
"privately prone to overthinking and drafting texts she never sends. "
"Came out of a five-year relationship six months ago and is still "
"pretending she's fine."
),
"voice_samples": [
(
"\"You look like someone who needs water more than another coffee. "
"I'm just saying.\""
),
(
"She tilts her laptop screen toward you without looking up. "
"\"Tell me which one. Don't think about it. The first one your eye "
"lands on is the right one.\""
),
(
"A pause. \"I'm going to head out. ...Unless you want company on the "
"elevator. Which is a weird sentence I just said out loud.\""
),
],
"traits": [
"dry humor",
"observant",
"perfectionist",
"quick to deflect compliments",
"late-night texter",
"runs on cold brew",
"slow to trust",
"draws in margins when bored",
"hates small talk",
"secretly sentimental",
],
"backstory": (
"Grew up in Vancouver, only child of immigrant parents. Design school "
"in Toronto. Three years at this company; took the senior role eight "
"months ago after the previous lead left abruptly. Her father died of "
"a stroke last fall — she flew home for the funeral and was back at "
"her desk on Monday. She has not really talked to anyone about it, "
"including her mother, including her therapist, including her best "
"friend. She works too much. She knows she works too much."
),
"initial_relationship_to_you": (
"Coworkers for about eighteen months. Two desks over. You've been on "
"the same product team for the last year. She thinks you're one of the "
"very few people at the company who actually thinks before speaking, "
"which she finds annoying and also relieving. The two of you have "
"lunch sometimes. You stayed late together once before the big launch "
"and she doesn't remember exactly what was said but she remembers the "
"feeling of the empty office. She has not admitted anything to "
"herself. You probably haven't either."
),
"kickoff_prose": (
"It's 9:14 on a Thursday and you and Maya are the only people left on "
"the floor. The deck is due in the morning. She has her shoes off "
"under her desk. The kitchen lights flicker once and then steady. She "
"slides her chair back and rubs her eyes with the heels of her hands. "
"\"Okay,\" she says, to no one in particular, \"tell me honestly. "
"Slide eleven — does that read as ambitious or as desperate.\""
),
},
{
"id": "eli",
"name": "Eli Park",
"persona": (
"34, freelance illustrator. Quiet, tactile, generous with attention "
"but stingy with words. Bakes when stressed. Falls asleep on the "
"couch with his glasses on. Loves you in the kind of way that doesn't "
"need to be announced."
),
"voice_samples": [
(
"\"Hey.\" A pause, like he's deciding if it's worth saying. \"You "
"ate, right?\""
),
(
"He kisses the top of your head and keeps walking, not breaking "
"stride. \"Don't fall asleep on the bathroom floor again. That's "
"all I'm saying.\""
),
(
"\"You don't have to. I just.\" He looks at his hands. \"I just "
"like it when you're around when I'm working. It's stupid. It's "
"whatever.\""
),
],
"traits": [
"warm",
"present",
"distractible",
"terrible at confrontation",
"leaves coffee mugs in every room",
"draws on napkins",
"gets up at 6am to paint",
"owns far too many sweaters",
"never throws anything away",
"holds your hand without thinking about it",
],
"backstory": (
"Born and raised in Queens to Korean parents who ran a dry cleaner. "
"Older sister Lena died in a car accident when he was nineteen — the "
"year he left for art school. He won't talk about her on most days "
"but he keeps a small photo of her in his wallet, and on her birthday "
"he stops talking by 7pm and goes to bed early. He has been a "
"freelance illustrator for nine years. His work has appeared in The "
"New Yorker twice and he refuses to make this a personality trait. "
"He pays his bills on time. He loses his keys constantly."
),
"initial_relationship_to_you": (
"You've been together for four years, living together for two. He "
"proposed last summer, kind of — it was tentative and circular and "
"the question wasn't really a question, and you both laughed and "
"didn't really resolve it, and somewhere there is an unspent ring in "
"a sock drawer. You bicker about laundry and the right way to load a "
"dishwasher. He has seen you cry over genuinely stupid commercials. "
"You are each other's first call. You sleep on the left side."
),
"kickoff_prose": (
"Sunday morning, late. The blinds are still down. Eli is propped "
"against the headboard reading something on his phone, his glasses "
"pushed up into his hair. You've been awake for a while; he just "
"noticed. He sets the phone face-down on his chest and looks over at "
"you with the small private smile he only uses in this room. \"Hi,\" "
"he says, like it's a whole sentence."
),
},
{
"id": "sam",
"name": "Samira Reyes",
"persona": (
"28, bartender at a small cocktail bar near where you live, doing a "
"part-time master's in psychology she refuses to talk about. "
"Confident posture, careful words. Reads people fast and shares the "
"readings only when she likes them. Single by deliberate choice for "
"the last two years."
),
"voice_samples": [
(
"\"You're back.\" She says it without looking up from polishing "
"the glass. \"Same as last time, or are we trying something new "
"tonight.\""
),
(
"A long look. \"I'm going to ask you a question and you're not "
"going to answer it carefully. The first thing that comes into "
"your head. Ready.\""
),
(
"\"Don't tip me extra because we talked. I'm being serious. "
"That's a different transaction and I don't want it confused.\""
),
],
"traits": [
"observant",
"blunt",
"kind in unexpected ways",
"reads tarot for fun (doesn't believe in it)",
"drinks black coffee",
"runs at 5am",
"doesn't suffer fools",
"never forgets a face",
"occasional smoker when something is bothering her",
"owns three identical black t-shirts",
],
"backstory": (
"Born and raised in El Paso to a single mother who waitressed nights. "
"Came north five years ago for undergrad on a scholarship. Funded the "
"master's herself by bartending — she's careful about money in a way "
"that took being broke to learn. Her undergraduate thesis was on "
"attachment styles and she will not tell you what her own attachment "
"style is. Her mother passed away two years ago after a long illness, "
"and she went home for a month and came back different in ways she "
"can't articulate."
),
"initial_relationship_to_you": (
"You've talked at her bar maybe six times over the last month. She "
"knows your drink. The conversations have started lasting longer than "
"they should — you stay until close more often than you mean to. Last "
"week you walked her to her car at 1am because the lot is dim. "
"Nothing happened. You just talked, leaning on the hood of her old "
"Civic, longer than either of you intended. Neither of you has texted "
"the other since. Neither of you has stopped thinking about it."
),
"kickoff_prose": (
"It's 11:47 on a Tuesday — slow night. There's exactly one other "
"customer at the far end of the bar, finishing a beer he stopped "
"drinking ten minutes ago. Sam is wiping down the counter in long "
"unhurried passes. She glances up when the door chimes and the small "
"surprise on her face is gone before you'd swear it was there. "
"\"Look who it is,\" she says, even and unreadable, and pulls down a "
"glass without asking what you want."
),
},
]
def main() -> None:
settings = load_settings()
apply_migrations(settings.db_path)
created: list[str] = []
skipped: list[str] = []
with open_db(settings.db_path) as conn:
for spec in SAMPLES:
if get_bot(conn, spec["id"]) is not None:
skipped.append(spec["id"])
continue
append_and_apply(conn, kind="bot_authored", payload=spec)
created.append(spec["id"])
print(f"created: {created}")
print(f"skipped (already existed): {skipped}")
print()
print("Walk each new bot through kickoff parse-and-confirm:")
for bot_id in created:
print(f" http://127.0.0.1:8000/bots/{bot_id}/kickoff")
if __name__ == "__main__":
main()
+92
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@@ -0,0 +1,92 @@
"""Tests for nightly DB backups (T32).
The backup service is intentionally simple: a flat ``data/backups/`` dir
containing timestamped copies of ``chat.db``, with retention of the most
recent 14. The scheduling decision (``should_take_backup``) is a pure
function of clock + filesystem state so it can be unit-tested without
spinning up the BackgroundWorker tick loop.
"""
from __future__ import annotations
from datetime import datetime
from unittest.mock import patch
from chat.services.backup import (
prune_backups,
should_take_backup,
take_backup,
)
def test_take_backup_creates_timestamped_copy(tmp_path):
db = tmp_path / "chat.db"
db.write_text("fake db contents")
backup_path = take_backup(db_path=db, data_dir=tmp_path / "data")
assert backup_path.exists()
assert backup_path.name.startswith("chat-")
assert backup_path.name.endswith(".db")
# Contents copied
assert backup_path.read_text() == "fake db contents"
# Located in data/backups/
assert backup_path.parent == tmp_path / "data" / "backups"
def test_prune_keeps_last_14(tmp_path):
backup_dir = tmp_path / "data" / "backups"
backup_dir.mkdir(parents=True)
# Create 17 dummy backup files spanning days 1..17 of Jan 2026.
# Filenames sort lexicographically by the embedded timestamp, so
# prune_backups should drop the three oldest.
for i in range(1, 18):
(backup_dir / f"chat-202601{i:02d}T000000Z.db").write_text(
f"backup {i}"
)
removed = prune_backups(tmp_path / "data", keep=14)
assert removed == 3
remaining = sorted(backup_dir.glob("chat-*.db"))
assert len(remaining) == 14
# Days 1, 2, 3 removed; day 4 is now the oldest retained backup.
assert remaining[0].name == "chat-20260104T000000Z.db"
def test_should_take_backup_when_no_prior_and_target_hour_matches(tmp_path):
from chat.services import backup as backup_mod
class FakeDateTime(datetime):
@classmethod
def now(cls, tz=None):
return datetime(2026, 4, 26, 3, 0, 0)
with patch.object(backup_mod, "datetime", FakeDateTime):
assert should_take_backup(tmp_path / "data") is True
def test_should_not_take_backup_outside_target_hour(tmp_path):
from chat.services import backup as backup_mod
class FakeDateTime(datetime):
@classmethod
def now(cls, tz=None):
return datetime(2026, 4, 26, 14, 0, 0)
with patch.object(backup_mod, "datetime", FakeDateTime):
assert should_take_backup(tmp_path / "data") is False
def test_should_not_take_backup_when_recent_backup_exists(tmp_path):
backup_dir = tmp_path / "data" / "backups"
backup_dir.mkdir(parents=True)
recent = backup_dir / "chat-recent.db"
recent.write_text("x")
# mtime defaults to "now" — within the 23h freshness window so
# should_take_backup must return False even at the target hour.
from chat.services import backup as backup_mod
class FakeDateTime(datetime):
@classmethod
def now(cls, tz=None):
return datetime(2026, 4, 26, 3, 0, 0)
with patch.object(backup_mod, "datetime", FakeDateTime):
assert should_take_backup(tmp_path / "data") is False
+35 -4
View File
@@ -20,11 +20,29 @@ def client(tmp_path, monkeypatch):
yield c yield c
def _author_bot_and_chat(db_path: Path, bot_id: str = "bot_a") -> None: def _author_you(db_path: Path) -> None:
"""Insert a bot and a chat directly via the event log (skip kickoff route).""" """Author a ``you_entity`` so the first-run middleware doesn't redirect."""
from chat.db.connection import open_db from chat.db.connection import open_db
with open_db(db_path) as conn: with open_db(db_path) as conn:
append_event(
conn,
kind="you_authored",
payload={"name": "Me", "pronouns": "", "persona": ""},
)
project(conn)
def _author_bot_and_chat(db_path: Path, bot_id: str = "bot_a") -> None:
"""Insert a you_entity, bot, and chat via the event log (skip kickoff route)."""
from chat.db.connection import open_db
with open_db(db_path) as conn:
append_event(
conn,
kind="you_authored",
payload={"name": "Me", "pronouns": "", "persona": ""},
)
append_event( append_event(
conn, conn,
kind="bot_authored", kind="bot_authored",
@@ -53,13 +71,26 @@ def _author_bot_and_chat(db_path: Path, bot_id: str = "bot_a") -> None:
project(conn) project(conn)
def test_root_redirects_to_chats(client): def test_root_redirects_to_chats_when_setup_complete(client, tmp_path):
# With both you_entity and a bot present, the first-run middleware
# passes through and the nav router sends "/" → "/chats".
_author_bot_and_chat(tmp_path / "test.db", "bot_a")
response = client.get("/", follow_redirects=False) response = client.get("/", follow_redirects=False)
assert response.status_code == 303 assert response.status_code == 303
assert response.headers["location"] == "/chats" assert response.headers["location"] == "/chats"
def test_chats_list_empty_state(client): def test_chats_list_empty_state(client, tmp_path):
# Author you + a bot but NO chats — should render the empty-state
# chats list, not redirect.
_author_bot_and_chat(tmp_path / "test.db", "bot_a")
# Drop the chat row so we hit the empty-state branch (the helper
# creates a chat — undo it via a fresh seed without chat_created).
from chat.db.connection import open_db
with open_db(tmp_path / "test.db") as conn:
conn.execute("DELETE FROM chats")
conn.commit()
response = client.get("/chats") response = client.get("/chats")
assert response.status_code == 200 assert response.status_code == 200
body = response.text.lower() body = response.text.lower()
+1 -1
View File
@@ -18,7 +18,7 @@ async def test_classify_parses_valid_json():
@pytest.mark.asyncio @pytest.mark.asyncio
async def test_classify_falls_back_on_unparseable_after_retry(): async def test_classify_falls_back_on_unparseable_after_retry():
mock = MockLLMClient(canned=["nope", "still nope"]) mock = MockLLMClient(canned=["nope", "still nope", "nope3"])
default = Verdict(score=1, reason="fallback") default = Verdict(score=1, reason="fallback")
result = await classify(mock, model="m", system="x", user="y", schema=Verdict, default=default) result = await classify(mock, model="m", system="x", user="y", schema=Verdict, default=default)
assert result.reason == "fallback" assert result.reason == "fallback"
+57
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@@ -0,0 +1,57 @@
from __future__ import annotations
import pytest
from fastapi.testclient import TestClient
from chat.app import app
@pytest.fixture
def client(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:
if hasattr(app.state, "background_worker"):
app.state.background_worker.enabled = False
yield c
def _setup_minimal_state(db_path):
"""Set up enough state so the first-run middleware doesn't redirect."""
from chat.db.connection import open_db
from chat.eventlog.log import append_event
from chat.eventlog.projector import project
with open_db(db_path) as conn:
append_event(
conn,
kind="you_authored",
payload={"name": "Me", "pronouns": "", "persona": ""},
)
append_event(
conn,
kind="bot_authored",
payload={
"id": "bot_a",
"name": "BotA",
"persona": "",
"voice_samples": [],
"traits": [],
"backstory": "",
"initial_relationship_to_you": "",
"kickoff_prose": "",
},
)
project(conn)
def test_404_renders_friendly_page_for_html(client, tmp_path):
_setup_minimal_state(tmp_path / "test.db")
response = client.get("/chats/no_such_chat")
assert response.status_code == 404
body = response.text
assert "404" in body
assert "back to" in body.lower()
+146
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@@ -0,0 +1,146 @@
from __future__ import annotations
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
@pytest.fixture
def client(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:
if hasattr(app.state, "background_worker"):
app.state.background_worker.enabled = False
yield c
def test_root_redirects_to_settings_when_no_you(client):
response = client.get("/", follow_redirects=False)
assert response.status_code == 303
assert response.headers["location"] == "/settings"
def test_chats_redirects_to_settings_when_no_you(client):
response = client.get("/chats", follow_redirects=False)
assert response.status_code == 303
assert response.headers["location"] == "/settings"
def test_redirects_to_bots_new_when_you_exists_but_no_bots(client, tmp_path):
with open_db(tmp_path / "test.db") as conn:
append_event(
conn,
kind="you_authored",
payload={
"name": "Me",
"pronouns": "they/them",
"persona": "engineer",
},
)
project(conn)
response = client.get("/chats", follow_redirects=False)
assert response.status_code == 303
assert response.headers["location"] == "/bots/new"
def test_root_redirects_to_bots_new_when_you_exists_but_no_bots(client, tmp_path):
with open_db(tmp_path / "test.db") as conn:
append_event(
conn,
kind="you_authored",
payload={
"name": "Me",
"pronouns": "they/them",
"persona": "engineer",
},
)
project(conn)
response = client.get("/", follow_redirects=False)
assert response.status_code == 303
assert response.headers["location"] == "/bots/new"
def test_no_redirect_when_setup_complete(client, tmp_path):
with open_db(tmp_path / "test.db") as conn:
append_event(
conn,
kind="you_authored",
payload={
"name": "Me",
"pronouns": "they/them",
"persona": "engineer",
},
)
append_event(
conn,
kind="bot_authored",
payload={
"id": "bot_a",
"name": "BotA",
"persona": "...",
"voice_samples": [],
"traits": [],
"backstory": "",
"initial_relationship_to_you": "",
"kickoff_prose": "",
},
)
project(conn)
response = client.get("/chats", follow_redirects=False)
# /chats page renders normally (200) instead of redirecting.
assert response.status_code == 200
def test_settings_page_accessible_without_you(client):
"""Don't redirect FROM /settings — user needs to fill it out."""
response = client.get("/settings", follow_redirects=False)
assert response.status_code == 200
def test_bots_new_accessible_without_redirect(client, tmp_path):
with open_db(tmp_path / "test.db") as conn:
append_event(
conn,
kind="you_authored",
payload={"name": "Me", "pronouns": "", "persona": ""},
)
project(conn)
response = client.get("/bots/new", follow_redirects=False)
assert response.status_code == 200
def test_bots_list_accessible_without_redirect_when_empty(client, tmp_path):
"""The bot list page itself should never redirect — even when empty."""
with open_db(tmp_path / "test.db") as conn:
append_event(
conn,
kind="you_authored",
payload={"name": "Me", "pronouns": "", "persona": ""},
)
project(conn)
response = client.get("/bots", follow_redirects=False)
assert response.status_code == 200
def test_post_to_settings_not_redirected(client):
"""POST should bypass middleware — it's a write, not a landing nav."""
response = client.post(
"/settings",
data={"name": "Me", "pronouns": "", "persona": ""},
follow_redirects=False,
)
# Settings POST returns 200 with the saved page (no HTTPException raised).
assert response.status_code == 200
def test_health_endpoint_not_redirected(client):
response = client.get("/health", follow_redirects=False)
assert response.status_code == 200
+15 -4
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@@ -117,10 +117,12 @@ async def test_parse_kickoff_applies_activity_defaults_for_missing_fields():
@pytest.mark.asyncio @pytest.mark.asyncio
async def test_parse_kickoff_raises_when_classifier_fails_twice(): async def test_parse_kickoff_falls_back_to_empty_when_classifier_fails():
mock = MockLLMClient(canned=["nope", "still nope"]) """When the classifier fails three times, return an empty KickoffParse
with pytest.raises(RuntimeError): instead of raising — the confirm form lets the user fill in by hand.
await parse_kickoff( """
mock = MockLLMClient(canned=["nope", "still nope", "still bad"])
result = await parse_kickoff(
mock, mock,
model="m", model="m",
bot_name="BotA", bot_name="BotA",
@@ -129,3 +131,12 @@ async def test_parse_kickoff_raises_when_classifier_fails_twice():
kickoff_prose="z", kickoff_prose="z",
you_name="You", you_name="You",
) )
assert isinstance(result, KickoffParse)
assert result.container_name == ""
assert result.container_type == ""
assert result.edge_seed_summary == ""
assert result.edge_seed_knowledge_facts == []
# Activity defaults sane (action_interruptible defaults to True so the
# confirm form's checkbox is in a reasonable initial state).
assert result.you_activity.action_interruptible is True
assert result.bot_activity.action_interruptible is True
+1 -1
View File
@@ -84,7 +84,7 @@ async def test_summarize_scene_default_on_failure():
"""Two consecutive non-JSON returns trip the classifier's retry-then-default """Two consecutive non-JSON returns trip the classifier's retry-then-default
path; we should get the empty fallback rather than crashing the close path; we should get the empty fallback rather than crashing the close
flow.""" flow."""
mock = MockLLMClient(canned=["bad", "still bad"]) mock = MockLLMClient(canned=["bad", "still bad", "bad3"])
result = await summarize_scene( result = await summarize_scene(
mock, mock,
model="x", model="x",
+273
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@@ -0,0 +1,273 @@
"""Regenerate flow (T29).
POST ``/chats/<chat_id>/turns/<event_id>/regenerate`` re-streams the
assistant turn, supersedes the prior ``assistant_turn`` event, and — when
prose is supplied — captures a ``user_turn_edit`` event that supersedes
the original ``user_turn``.
These tests cover the functional core required by the plan:
- Without edit: a new ``assistant_turn`` is appended; the original is
marked ``superseded_by`` the new one.
- With edit: a ``user_turn_edit`` event is appended; the original
``user_turn`` is also marked ``superseded_by``.
- Missing event id returns 404.
"""
from __future__ import annotations
import json
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
@pytest.fixture
def client(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:
# Disable lifespan-managed background worker (would otherwise try
# to score significance through Featherless with the test key).
if hasattr(app.state, "background_worker"):
app.state.background_worker.enabled = False
yield c
app.dependency_overrides.clear()
def _seed_with_one_turn(db_path):
"""Seed bot, chat, edges/activity, and ONE round of user_turn + assistant_turn.
Returns ``(user_turn_event_id, assistant_turn_event_id)``.
"""
with open_db(db_path) as conn:
append_event(
conn,
kind="bot_authored",
payload={
"id": "bot_a",
"name": "BotA",
"persona": "thoughtful",
"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",
},
)
append_event(
conn,
kind="edge_update",
payload={
"source_id": "you",
"target_id": "bot_a",
"chat_id": "chat_bot_a",
},
)
append_event(
conn,
kind="activity_change",
payload={
"entity_id": "you",
"posture": "sitting",
"action": {"verb": "talking"},
"attention": "",
"holding": [],
"status": {},
},
)
append_event(
conn,
kind="activity_change",
payload={
"entity_id": "bot_a",
"posture": "sitting",
"action": {"verb": "listening"},
"attention": "",
"holding": [],
"status": {},
},
)
# First round: user_turn + assistant_turn.
ut_id = append_event(
conn,
kind="user_turn",
payload={
"chat_id": "chat_bot_a",
"prose": "hello",
"segments": [],
},
)
at_id = append_event(
conn,
kind="assistant_turn",
payload={
"chat_id": "chat_bot_a",
"speaker_id": "bot_a",
"text": "Original response.",
"truncated": False,
"user_turn_id": ut_id,
},
)
project(conn)
return ut_id, at_id
def test_regenerate_without_edit_creates_new_assistant_turn(client, tmp_path):
"""Reissuing the regenerate POST with no prose should:
- Stream a new ``assistant_turn`` carrying ``regenerated_from`` and
the canned narrative text.
- Mark the original ``assistant_turn`` row as ``superseded_by`` the
new one.
"""
ut_id, at_id = _seed_with_one_turn(tmp_path / "test.db")
narrative_canned = "New response."
state_canned = json.dumps(
{"affinity_delta": 0, "trust_delta": 0, "knowledge_facts": []}
)
canned = [narrative_canned, state_canned, state_canned]
from chat.web.kickoff import get_llm_client
app.dependency_overrides[get_llm_client] = lambda: MockLLMClient(
canned=list(canned)
)
try:
response = client.post(
f"/chats/chat_bot_a/turns/{at_id}/regenerate", data={}
)
assert response.status_code == 204
finally:
app.dependency_overrides.clear()
with open_db(tmp_path / "test.db") as conn:
# Original assistant_turn is now superseded.
row = conn.execute(
"SELECT superseded_by FROM event_log WHERE id = ?", (at_id,)
).fetchone()
assert row[0] is not None
# A new assistant_turn exists, links back to the original, and
# carries the canned narrative text.
cur = conn.execute(
"SELECT id, payload_json FROM event_log "
"WHERE kind = 'assistant_turn' AND id != ? "
"AND superseded_by IS NULL",
(at_id,),
).fetchall()
assert len(cur) == 1
new_id, new_payload_json = cur[0]
new_payload = json.loads(new_payload_json)
assert new_payload["text"] == "New response."
assert new_payload["regenerated_from"] == at_id
# The original assistant_turn's superseded_by points at the new one.
assert row[0] == new_id
# The original user_turn is NOT touched when no prose was supplied.
ut_row = conn.execute(
"SELECT superseded_by FROM event_log WHERE id = ?", (ut_id,)
).fetchone()
assert ut_row[0] is None
def test_regenerate_with_edit_appends_user_turn_edit(client, tmp_path):
"""Supplying ``prose`` should:
- Append a ``user_turn_edit`` event whose payload references the
original user_turn id and carries the edited prose.
- Mark the original ``user_turn`` as ``superseded_by`` the edit.
"""
ut_id, at_id = _seed_with_one_turn(tmp_path / "test.db")
narrative_canned = "Reply to edited."
state_canned = json.dumps(
{"affinity_delta": 0, "trust_delta": 0, "knowledge_facts": []}
)
canned = [narrative_canned, state_canned, state_canned]
from chat.web.kickoff import get_llm_client
app.dependency_overrides[get_llm_client] = lambda: MockLLMClient(
canned=list(canned)
)
try:
response = client.post(
f"/chats/chat_bot_a/turns/{at_id}/regenerate",
data={"prose": "edited prose"},
)
assert response.status_code == 204
finally:
app.dependency_overrides.clear()
with open_db(tmp_path / "test.db") as conn:
# A user_turn_edit event was appended with the edited prose and
# a back-pointer to the original user_turn.
cur = conn.execute(
"SELECT payload_json FROM event_log WHERE kind = 'user_turn_edit'"
).fetchall()
assert len(cur) == 1
edit_payload = json.loads(cur[0][0])
assert edit_payload["prose"] == "edited prose"
assert edit_payload["supersedes_user_turn_id"] == ut_id
assert edit_payload["chat_id"] == "chat_bot_a"
# Original user_turn is now superseded.
ut_row = conn.execute(
"SELECT superseded_by FROM event_log WHERE id = ?", (ut_id,)
).fetchone()
assert ut_row[0] is not None
# Original assistant_turn is also superseded by the new one.
at_row = conn.execute(
"SELECT superseded_by FROM event_log WHERE id = ?", (at_id,)
).fetchone()
assert at_row[0] is not None
def test_regenerate_404_when_assistant_turn_missing(client, tmp_path):
"""An unknown ``event_id`` returns 404."""
_seed_with_one_turn(tmp_path / "test.db")
from chat.web.kickoff import get_llm_client
app.dependency_overrides[get_llm_client] = lambda: MockLLMClient(
canned=["x", "y", "z"]
)
try:
response = client.post(
"/chats/chat_bot_a/turns/99999/regenerate", data={}
)
assert response.status_code == 404
finally:
app.dependency_overrides.clear()
+87
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@@ -0,0 +1,87 @@
"""Tests for the transcript renderer (Task 33).
Lightweight markdown for transcript turns:
- ``*action*`` → ``<em class="action">action</em>``
- ``**bold**`` → ``<strong>bold</strong>``
- ``((ooc))`` → ``<span class="ooc">((ooc))</span>``
- ``> line`` → ``<blockquote>line</blockquote>``
- paragraph breaks (double newline) → ``</p><p>``
- everything HTML-escaped first
No headings, no code blocks, no links — out of scope per Requirements §16.3.
"""
from __future__ import annotations
from chat.web.render import render_prose, render_turn_html
def test_render_prose_escapes_html():
"""Raw HTML in user content must be escaped — no XSS surface."""
out = render_prose("<script>alert(1)</script>")
assert "<script>" not in out
assert "&lt;script&gt;" in out
def test_render_prose_action_to_italic():
out = render_prose("*walks over*")
assert '<em class="action">walks over</em>' in out
def test_render_prose_bold_before_action():
"""Bold (``**``) must be processed before action (``*``)."""
out = render_prose("**emphasis** and *action*")
assert "<strong>emphasis</strong>" in out
assert '<em class="action">action</em>' in out
# Make sure we didn't double-wrap: no stray asterisks left behind.
assert "*" not in out
def test_render_prose_ooc_wrapped():
out = render_prose("((this is OOC))")
assert '<span class="ooc">' in out
assert "((this is OOC))" in out
def test_render_prose_paragraphs():
out = render_prose("First.\n\nSecond.")
# Two <p> opens and two closes.
assert out.count("<p>") == 2
assert out.count("</p>") == 2
assert "<p>First.</p>" in out
assert "<p>Second.</p>" in out
def test_render_prose_blockquote():
out = render_prose("> a quote")
assert "<blockquote>a quote</blockquote>" in out
def test_render_prose_empty():
"""Empty / whitespace-only inputs produce empty output, not stray tags."""
assert render_prose("") == ""
assert render_prose(" ") == ""
def test_render_turn_html_includes_role_class():
out = render_turn_html("BotA", "Hello.", role="bot")
assert 'class="turn turn-bot"' in out
assert "<strong>BotA</strong>" in out
assert "Hello." in out
def test_render_turn_html_escapes_speaker():
"""Speaker label is also HTML-escaped — names are user-controlled."""
out = render_turn_html("<bad>", "hi", role="you")
# Raw tag should not appear; escaped form should.
assert "<bad>" not in out
assert "&lt;bad&gt;" in out
def test_render_prose_mixed_full_message():
"""Realistic turn with action, dialogue, and an OOC aside."""
text = "*looks up* \"You're back late.\" ((she's tired))"
out = render_prose(text)
assert '<em class="action">looks up</em>' in out
# The apostrophe in ``she's`` is HTML-escaped to ``&#x27;``.
assert '<span class="ooc">((she&#x27;s tired))</span>' in out
+185
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@@ -0,0 +1,185 @@
from __future__ import annotations
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
@pytest.fixture
def client(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:
if hasattr(app.state, "background_worker"):
app.state.background_worker.enabled = False
yield c
def _seed_bot_with_state(db: Path) -> None:
"""Seed a bot plus a chat, container, scene, edge, memory, and activity row."""
with open_db(db) as conn:
append_event(
conn,
kind="bot_authored",
payload={
"id": "bot_a",
"name": "BotA",
"persona": "thoughtful, observant",
"voice_samples": [],
"traits": ["shy"],
"backstory": "",
"initial_relationship_to_you": "coworker",
"kickoff_prose": "you stay late",
},
)
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="container_created",
payload={
"chat_id": "chat_bot_a",
"name": "office",
"type": "workplace",
"properties": {},
},
)
append_event(
conn,
kind="scene_opened",
payload={
"chat_id": "chat_bot_a",
"container_id": 1,
"started_at": "2026-04-26T20:00:00+00:00",
"participants": ["you", "bot_a"],
},
)
append_event(
conn,
kind="edge_update",
payload={
"source_id": "bot_a",
"target_id": "you",
"chat_id": "chat_bot_a",
"affinity_delta": 5,
"trust_delta": 2,
},
)
append_event(
conn,
kind="memory_written",
payload={
"owner_id": "bot_a",
"chat_id": "chat_bot_a",
"pov_summary": "Talked about her sister",
"witness_you": 1,
"witness_host": 1,
"witness_guest": 0,
"significance": 2,
},
)
append_event(
conn,
kind="activity_change",
payload={
"entity_id": "bot_a",
"posture": "sitting",
"action": {"verb": "writing"},
},
)
project(conn)
def test_reset_purges_state_but_preserves_identity(client, tmp_path):
_seed_bot_with_state(tmp_path / "test.db")
response = client.post(
"/bots/bot_a/reset",
data={"confirm_name": "BotA"},
follow_redirects=False,
)
assert response.status_code == 303
assert response.headers["location"] == "/bots"
with open_db(tmp_path / "test.db") as conn:
# Identity preserved.
bot = conn.execute(
"SELECT id, name, kickoff_prose, initial_relationship_to_you "
"FROM bots WHERE id = 'bot_a'"
).fetchone()
assert bot is not None
assert bot[1] == "BotA"
assert bot[2] == "you stay late"
assert bot[3] == "coworker"
# State purged.
assert conn.execute(
"SELECT COUNT(*) FROM chats WHERE host_bot_id = 'bot_a'"
).fetchone()[0] == 0
assert conn.execute(
"SELECT COUNT(*) FROM scenes WHERE chat_id = 'chat_bot_a'"
).fetchone()[0] == 0
assert conn.execute(
"SELECT COUNT(*) FROM containers WHERE chat_id = 'chat_bot_a'"
).fetchone()[0] == 0
assert conn.execute(
"SELECT COUNT(*) FROM chat_state WHERE chat_id = 'chat_bot_a'"
).fetchone()[0] == 0
assert conn.execute(
"SELECT COUNT(*) FROM memories WHERE owner_id = 'bot_a'"
).fetchone()[0] == 0
assert conn.execute(
"SELECT COUNT(*) FROM edges WHERE source_id = 'bot_a' OR target_id = 'bot_a'"
).fetchone()[0] == 0
assert conn.execute(
"SELECT COUNT(*) FROM activity WHERE entity_id = 'bot_a'"
).fetchone()[0] == 0
# Event log records the bot_reset event.
assert conn.execute(
"SELECT COUNT(*) FROM event_log WHERE kind = 'bot_reset'"
).fetchone()[0] == 1
def test_reset_400_when_confirm_name_mismatch(client, tmp_path):
_seed_bot_with_state(tmp_path / "test.db")
response = client.post(
"/bots/bot_a/reset",
data={"confirm_name": "WrongName"},
follow_redirects=False,
)
assert response.status_code == 400
def test_reset_404_when_bot_missing(client):
response = client.post(
"/bots/no_such/reset",
data={"confirm_name": "Anything"},
follow_redirects=False,
)
assert response.status_code == 404
def test_bot_list_renders_reset_form(client, tmp_path):
_seed_bot_with_state(tmp_path / "test.db")
response = client.get("/bots")
assert response.status_code == 200
assert "Reset" in response.text
assert "confirm_name" in response.text
+164
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@@ -0,0 +1,164 @@
"""Tests for Task 28 — rewind with snapshot, impact preview, and re-projection.
Per Requirements §10.1, rewind must:
* take a pre-rewind snapshot of all projected tables (so the user can recover),
* truncate the event log past a chosen event id,
* clear projected tables and re-project from the truncated log so live state
matches "what the world looked like at turn N" (no stale rows from rewound
events).
These tests cover the functional core. The HTTP route surface is left to the
plan's polish pass — tests exercise via direct service calls.
"""
from __future__ import annotations
import json
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.services.rewind import compute_rewind_preview, execute_rewind
from chat.services.snapshot import take_snapshot
# Importing the state modules registers their projector handlers as a
# side effect — the test would otherwise see an unprojected db after
# re-projection because the registry would be empty.
import chat.state.entities # noqa: F401
import chat.state.edges # noqa: F401
import chat.state.memory # noqa: F401
import chat.state.world # noqa: F401
import chat.state.manual_edit # noqa: F401
def _seed_5_turns(db):
"""Seed: bot + chat + 5 mock user/assistant turn pairs.
user_turn / assistant_turn have no projector handlers they live in
the event_log purely for transcript rendering so the only
projection-bearing events are bot_authored and chat_created. That
makes the post-rewind invariants easy to assert without needing the
real classifier pass.
"""
apply_migrations(db)
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(5):
append_event(
conn,
kind="user_turn",
payload={
"chat_id": "chat_bot_a",
"prose": f"turn {i}",
"segments": [],
},
)
append_event(
conn,
kind="assistant_turn",
payload={
"chat_id": "chat_bot_a",
"speaker_id": "bot_a",
"text": f"reply {i}",
"truncated": False,
"user_turn_id": i,
},
)
project(conn)
def test_take_snapshot_writes_file_to_disk(tmp_path):
db = tmp_path / "t.db"
_seed_5_turns(db)
with open_db(db) as conn:
snapshot_path = take_snapshot(
conn, data_dir=tmp_path / "data", kind="rewind"
)
assert snapshot_path.exists()
assert snapshot_path.parent == tmp_path / "data" / "snapshots" / "rewind"
data = json.loads(snapshot_path.read_text())
assert "event_log" in data
assert "bots" in data
assert "chats" in data
# Bot is in the dump
assert any(b["id"] == "bot_a" for b in data["bots"])
def test_compute_rewind_preview_counts_kinds(tmp_path):
db = tmp_path / "t.db"
_seed_5_turns(db)
with open_db(db) as conn:
# The 1st assistant_turn is the 4th event:
# 1 bot_authored, 2 chat_created, 3 user_turn, 4 assistant_turn.
# Everything past it should be in the preview (4 user + 4 assistant = 8).
first_assistant = conn.execute(
"SELECT id FROM event_log WHERE kind='assistant_turn' "
"ORDER BY id LIMIT 1"
).fetchone()[0]
preview = compute_rewind_preview(conn, after_event_id=first_assistant)
assert preview["after_event_id"] == first_assistant
assert preview["total_events"] > 0
# by_kind sums to total_events.
assert sum(preview["by_kind"].values()) == preview["total_events"]
# We rewound past assistant_turn #1, so 4 user + 4 assistant remain.
assert preview["by_kind"].get("user_turn") == 4
assert preview["by_kind"].get("assistant_turn") == 4
def test_execute_rewind_truncates_and_reprojects(tmp_path):
db = tmp_path / "t.db"
data_dir = tmp_path / "data"
_seed_5_turns(db)
with open_db(db) as conn:
first_assistant = conn.execute(
"SELECT id FROM event_log WHERE kind='assistant_turn' "
"ORDER BY id LIMIT 1"
).fetchone()[0]
snapshot_path = execute_rewind(
db_path=db, data_dir=data_dir, after_event_id=first_assistant
)
# Snapshot is written under data/snapshots/rewind/.
assert snapshot_path.exists()
assert snapshot_path.parent == data_dir / "snapshots" / "rewind"
# Verify event_log truncated and projected state matches state-at-turn.
with open_db(db) as conn:
max_id = conn.execute("SELECT MAX(id) FROM event_log").fetchone()[0]
assert max_id == first_assistant
# Bot still exists (re-projected from preserved bot_authored event).
bot = conn.execute(
"SELECT id FROM bots WHERE id = 'bot_a'"
).fetchone()
assert bot is not None
# Chat still exists (re-projected from preserved chat_created event).
chat = conn.execute(
"SELECT id FROM chats WHERE id = 'chat_bot_a'"
).fetchone()
assert chat is not None
+1 -1
View File
@@ -58,7 +58,7 @@ async def test_detect_scene_close_default_on_failure():
"""Two consecutive non-JSON returns trip the classifier's retry-then-default """Two consecutive non-JSON returns trip the classifier's retry-then-default
path; we should get the safe ``should_close=False`` fallback rather than path; we should get the safe ``should_close=False`` fallback rather than
crashing the turn flow.""" crashing the turn flow."""
mock = MockLLMClient(canned=["nope", "still nope"]) mock = MockLLMClient(canned=["nope", "still nope", "nope3"])
decision = await detect_scene_close( decision = await detect_scene_close(
mock, mock,
model="x", model="x",
+1 -1
View File
@@ -45,7 +45,7 @@ async def test_compute_significance_parses_score():
async def test_compute_significance_default_on_failure(): async def test_compute_significance_default_on_failure():
# Both attempts return non-JSON text; the classify wrapper falls back # Both attempts return non-JSON text; the classify wrapper falls back
# to the SignificanceVerdict default (score=1, "fallback"). # to the SignificanceVerdict default (score=1, "fallback").
mock = MockLLMClient(canned=["nope", "still nope"]) mock = MockLLMClient(canned=["nope", "still nope", "nope3"])
score = await compute_significance( score = await compute_significance(
mock, mock,
model="x", model="x",
+133
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@@ -0,0 +1,133 @@
"""Tests for Task 31 — periodic snapshots with retention and cold-load fast-path.
Per Requirements §10.4 the periodic snapshot policy is:
* Take a snapshot every 100 events OR every 30 minutes since the last one,
whichever comes first.
* Store under ``data/snapshots/periodic/`` with a UTC timestamp filename.
* Retain only the last 5 periodic snapshots; prune older ones on write.
* On cold load, restore from the most recent snapshot and replay events
past the snapshot's ``last_event_id`` to bring projected state forward.
These tests cover the functional core (snapshot timing, pruning, restore).
Worker- and lifespan-level wiring is covered by the integration tests in
``test_turn_flow`` and the existing app boot tests.
"""
from __future__ import annotations
import json
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.services.snapshot import (
latest_snapshot_path,
prune_periodic_snapshots,
restore_from_snapshot,
should_take_periodic_snapshot,
take_snapshot,
)
# Importing the state modules registers their projector handlers as a
# side effect — restoring + replaying needs them present.
import chat.state.entities # noqa: F401
import chat.state.edges # noqa: F401
import chat.state.manual_edit # noqa: F401
import chat.state.memory # noqa: F401
import chat.state.world # noqa: F401
def _bot_payload(bot_id: str, name: str) -> dict:
return {
"id": bot_id,
"name": name,
"persona": "fancy",
"voice_samples": ["sample"],
"traits": ["shy"],
"backstory": "",
"initial_relationship_to_you": "coworker",
"kickoff_prose": "",
}
def test_take_snapshot_includes_last_event_id(tmp_path):
db = tmp_path / "t.db"
apply_migrations(db)
with open_db(db) as conn:
append_event(conn, kind="bot_authored", payload=_bot_payload("bot_a", "BotA"))
project(conn)
path = take_snapshot(conn, data_dir=tmp_path / "data", kind="periodic")
dump = json.loads(path.read_text())
assert "last_event_id" in dump
assert dump["last_event_id"] >= 1
def test_should_take_periodic_when_no_prior_and_events_exist(tmp_path):
db = tmp_path / "t.db"
apply_migrations(db)
with open_db(db) as conn:
append_event(conn, kind="bot_authored", payload=_bot_payload("bot_a", "BotA"))
project(conn)
assert should_take_periodic_snapshot(conn, tmp_path / "data") is True
def test_should_not_take_when_recent_and_few_events(tmp_path):
db = tmp_path / "t.db"
apply_migrations(db)
with open_db(db) as conn:
append_event(conn, kind="bot_authored", payload=_bot_payload("bot_a", "BotA"))
project(conn)
# Take a snapshot to establish a recent baseline.
take_snapshot(conn, data_dir=tmp_path / "data", kind="periodic")
# Right after — should be False (within time threshold and < 100 new events).
assert should_take_periodic_snapshot(conn, tmp_path / "data") is False
def test_prune_keeps_last_5(tmp_path):
snapshot_dir = tmp_path / "data" / "snapshots" / "periodic"
snapshot_dir.mkdir(parents=True)
# Create 8 dummy snapshot files with sortable names.
for i in range(8):
p = snapshot_dir / f"2026010{i}T000000Z.json"
p.write_text(json.dumps({"last_event_id": i}))
removed = prune_periodic_snapshots(tmp_path / "data", keep=5)
assert removed == 3
remaining = sorted(snapshot_dir.glob("*.json"))
assert len(remaining) == 5
# The 5 most recent (highest names) should remain.
assert remaining[0].name == "20260103T000000Z.json"
assert remaining[-1].name == "20260107T000000Z.json"
def test_latest_snapshot_path_returns_none_when_missing(tmp_path):
# No directory yet.
assert latest_snapshot_path(tmp_path / "data", kind="periodic") is None
# Empty directory.
(tmp_path / "data" / "snapshots" / "periodic").mkdir(parents=True)
assert latest_snapshot_path(tmp_path / "data", kind="periodic") is None
def test_restore_from_snapshot_repopulates_tables(tmp_path):
# Source DB: seed a bot, snapshot it.
db1 = tmp_path / "t1.db"
apply_migrations(db1)
with open_db(db1) as conn:
append_event(conn, kind="bot_authored", payload=_bot_payload("bot_a", "BotA"))
project(conn)
snapshot_path = take_snapshot(
conn, data_dir=tmp_path / "data", kind="periodic"
)
# Fresh DB — restore from the snapshot, no event-log replay needed.
db2 = tmp_path / "t2.db"
apply_migrations(db2)
with open_db(db2) as conn:
last_id = restore_from_snapshot(conn, snapshot_path)
assert last_id >= 1
bot = conn.execute(
"SELECT name FROM bots WHERE id = 'bot_a'"
).fetchone()
assert bot is not None
assert bot[0] == "BotA"
+1 -1
View File
@@ -62,7 +62,7 @@ async def test_compute_state_update_parses_classifier_output():
@pytest.mark.asyncio @pytest.mark.asyncio
async def test_compute_state_update_returns_default_on_failure(): async def test_compute_state_update_returns_default_on_failure():
"""Two malformed classifier responses -> default StateUpdate (zeros).""" """Two malformed classifier responses -> default StateUpdate (zeros)."""
mock = MockLLMClient(canned=["nope", "still nope"]) mock = MockLLMClient(canned=["nope", "still nope", "nope3"])
result = await compute_state_update( result = await compute_state_update(
mock, mock,
model="x", model="x",
+176
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@@ -0,0 +1,176 @@
"""Streaming UX tests (T34): cancel route, recent-dialogue user_turn_edit
inclusion, and the chat-shell embeds the streaming JS hooks.
The cancel route is exercised at the no-op level only the full mid-stream
cancel path is covered indirectly by T19's CancelledError handling. We
verify here that the route itself is registered and silently 204s when no
in-flight task exists, since the JS Stop button fires unconditionally.
The user_turn_edit inclusion test is the T29 follow-up fix: without it,
the original user_turn drops out of the timeline (correctly) but the
edited prose never lands (incorrectly), so the rendered chat detail is
missing the user's most recent words.
"""
from __future__ import annotations
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
@pytest.fixture
def client(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:
# Disable the lifespan-managed background worker so it doesn't
# try to score significance through Featherless with the fake key.
worker = getattr(app.state, "background_worker", None)
if worker is not None:
worker.enabled = False
yield c
def _seed_chat(
db_path: Path,
bot_id: str = "bot_a",
chat_id: str = "chat_bot_a",
) -> None:
"""Seed a bot + chat with the activity rows the prompt assembler expects."""
with open_db(db_path) as conn:
append_event(
conn,
kind="bot_authored",
payload={
"id": bot_id,
"name": "BotA",
"persona": "...",
"voice_samples": [],
"traits": [],
"backstory": "",
"initial_relationship_to_you": "",
"kickoff_prose": "...",
},
)
append_event(
conn,
kind="chat_created",
payload={
"id": chat_id,
"host_bot_id": bot_id,
"initial_time": "2026-04-26T20:00:00+00:00",
"narrative_anchor": "Day 1",
"weather": "",
},
)
append_event(
conn,
kind="edge_update",
payload={
"source_id": bot_id,
"target_id": "you",
"chat_id": chat_id,
},
)
append_event(
conn,
kind="edge_update",
payload={
"source_id": "you",
"target_id": bot_id,
"chat_id": chat_id,
},
)
append_event(
conn,
kind="activity_change",
payload={
"entity_id": "you",
"posture": "sitting",
"action": {"verb": "talking"},
},
)
append_event(
conn,
kind="activity_change",
payload={
"entity_id": bot_id,
"posture": "sitting",
"action": {"verb": "listening"},
},
)
project(conn)
def test_cancel_route_no_op_when_no_in_flight(client, tmp_path):
"""Hitting cancel with nothing streaming returns 204 silently."""
_seed_chat(tmp_path / "test.db")
response = client.post("/chats/chat_bot_a/turns/cancel")
assert response.status_code == 204
def test_user_turn_edit_appears_in_recent_dialogue(client, tmp_path):
"""The chat-detail timeline includes a user_turn_edit's prose.
Original user_turn is superseded by the edit, so it drops out, but
the edit's prose should render in its place.
"""
db_path = tmp_path / "test.db"
_seed_chat(db_path)
with open_db(db_path) as conn:
ut_id = append_event(
conn,
kind="user_turn",
payload={
"chat_id": "chat_bot_a",
"prose": "OriginalUserText",
"segments": [],
},
)
edit_id = append_event(
conn,
kind="user_turn_edit",
payload={
"chat_id": "chat_bot_a",
"prose": "EditedUserText",
"supersedes_user_turn_id": ut_id,
},
)
conn.execute(
"UPDATE event_log SET superseded_by = ? WHERE id = ?",
(edit_id, ut_id),
)
conn.commit()
# No project() call — user_turn / user_turn_edit have no projector
# handlers (transcript-only kinds), and re-projecting would replay
# chat_created and trip its UNIQUE constraint.
response = client.get("/chats/chat_bot_a")
assert response.status_code == 200
body = response.text
assert "EditedUserText" in body
# The original (now-superseded) prose must not render.
assert "OriginalUserText" not in body
def test_chat_html_includes_stop_streaming_script(client, tmp_path):
"""The chat shell embeds the streaming-JS hooks (Stop button + send-lock)."""
_seed_chat(tmp_path / "test.db")
response = client.get("/chats/chat_bot_a")
assert response.status_code == 200
body = response.text
# Either the CSS class for the Stop button or the JS state flag must
# appear in the embedded script — both are load-bearing for T34.
assert "stop-streaming" in body or "isStreaming" in body
# Cancel route reference must be wired so the Stop button can call it.
assert "/turns/cancel" in body
+1 -1
View File
@@ -74,7 +74,7 @@ async def test_parse_turn_empty_prose_short_circuits_without_classifier_call():
@pytest.mark.asyncio @pytest.mark.asyncio
async def test_parse_turn_raises_when_classifier_fails_twice(): async def test_parse_turn_raises_when_classifier_fails_twice():
mock = MockLLMClient(canned=["nope", "still nope"]) mock = MockLLMClient(canned=["nope", "still nope", "nope3"])
with pytest.raises(RuntimeError): with pytest.raises(RuntimeError):
await parse_turn( await parse_turn(
mock, mock,