Michael 4791e94a73
feat(gateway): add /health/ready readiness probe backed by the database (#5166)
* feat(gateway): add /health/ready readiness probe backed by the database

## Why

GET /health only proves the process is up: it returns 200 even when the persistence engine cannot reach the database. Orchestrators already treat it as a readiness gate (docker-compose.yaml marks the gateway service healthy and nginx depends_on service_healthy), so a DB outage or a still-migrating Postgres leaves the stack 'healthy' while every request fails.

## What changed

- New GET /health/ready endpoint: bounded SELECT 1 against the existing persistence engine (deerflow.persistence.engine.get_engine) with a 2s timeout.

- Response is 200 {'status': 'ready', 'database': 'ok'} when reachable, 503 {'status': 'degraded', 'database': 'unreachable'} when the probe fails, and 200 ready with database=not_configured for backend=memory (nothing to probe).

- GET /health is unchanged (pure liveness), and /health/ready is public through the existing /health auth whitelist.

- docker-compose.yaml gateway healthcheck now polls /health/ready so service_healthy reflects database reachability.

- Documented both endpoints in backend/app/gateway/AGENTS.md.

## Surface area

- [x] Backend API - new GET /health/ready endpoint under backend/app/gateway

- [x] Sandbox / Docker - gateway healthcheck in docker/docker-compose.yaml now gates on readiness

- [ ] Frontend UI / Agents / Skills / Dependencies

- [x] Default behavior change - existing /health unchanged; the prod compose healthcheck is stricter (503 while the database is unreachable)

## Validation

- New unit tests in backend/tests/test_gateway_health.py cover ok / unreachable / not_configured probe results and the 200/503 payload mapping (6 passed).

- app.gateway.app imports cleanly and registers both /health and /health/ready.

- ruff check + ruff format clean.

## AI assistance

**Tool(s) used:** Codex (coding agent)

**How you used it:** design, implementation, and unit tests produced with AI assistance; reviewed before commit.

- [ ] I've read and understand every line of this change and take responsibility for it — it's not unreviewed AI output.

* fix(helm): point the gateway readiness probe at /health/ready

## Why

Review on #5166 (willem-bd, P1): the chart still probed /health for readiness,
so Kubernetes marked the pod ready and routed traffic while the database was
unreachable - exactly the failure mode /health/ready was added to catch.

## What changed

- deploy/helm/deer-flow/templates/gateway-deployment.yaml: readinessProbe
  httpGet.path now hits /health/ready (DB-backed, 503 while the database is
  unreachable). The liveness probe stays on /health.

## Verification

- One-line path change inside the existing readinessProbe block; git diff
  confirms only the readiness path changed (liveness untouched).

## AI assistance

**Tool(s) used:** Codex (coding agent)

**How you used it:** implemented the reviewer-requested probe path change; reviewed before commit.

- [ ] I've read and understand every line of this change and take responsibility for it — it's not unreviewed AI output.

* fix(gateway): readiness probe also checks the effective checkpointer/Store backend

## Why

Follow-up review on #5166 (willem-bd, P1): get_engine() only represents the
ORM backend selected by `database:`. The legacy `checkpointer:` section takes
precedence for the LangGraph checkpointer and Store, so a split configuration
(a local SQLite/memory `database:` with `checkpointer.type: postgres`) could
report 200 while the PostgreSQL backend agent runs depend on was down.

## What changed

- GET /health/ready now probes both persistence halves: the ORM engine behind
  `database:` (unchanged) and the effective LangGraph checkpointer/Store
  backend resolved with the runtime's own rule (legacy `checkpointer:` config,
  otherwise derived from `database:`), for memory/sqlite/postgres backends.

- The payload gains a `checkpointer` field with the same
  ok / not_configured / unreachable vocabulary as `database`; 503 degraded is
  returned when either probe is unreachable.

- Probes are bounded by the existing 2s timeout: sqlite via aiosqlite SELECT 1
  on the resolved path, postgres via a bounded psycopg AsyncConnection SELECT 1
  on the DSN with the configured search_path. A missing driver for a configured
  backend degrades readiness (the runtime could not run either).

- Documented the two-probe semantics in the endpoint docstring and
  backend/app/gateway/AGENTS.md.

## Verification

- New tests: healthy ORM engine + unreachable legacy checkpointer backend ->
  503 degraded with database: ok / checkpointer: unreachable; checkpointer
  probe mapping for memory/sqlite(postgres missing-driver) backends; existing
  payload tests now pin the checkpointer field.

- cd backend && python -m pytest tests/test_gateway_health.py: 11 passed.

- app.gateway.app imports cleanly; ruff check + ruff format clean.

## AI assistance

**Tool(s) used:** Codex (coding agent)

**How you used it:** design, implementation, and unit tests produced with AI assistance; reviewed before commit.

- [ ] I've read and understand every line of this change and take responsibility for it — it's not unreviewed AI output.

* fix(gateway): bound /health/ready to one deadline and probe the startup checkpointer snapshot

## Why

Second round of review on #5166 (zhfeng P1/P2, willem-bd P1/P1/P2). Three
correctness issues remained in the readiness endpoint:

- The database and checkpointer probes ran sequentially, each allowed 2s, so a
  healthy response could take almost 4s - past Kubernetes' 1s default
  readinessProbe timeout and inside Docker's 3s client timeout. A slow but
  healthy backend could make every replica unready.

- The checkpointer probe re-resolved process-wide, hot-reloaded configuration
  per request, while app.state.checkpointer/store are built once from the
  startup_config snapshot in langgraph_runtime(). After a live config edit the
  endpoint could probe a backend the running gateway does not use, and a
  resolution failure was swallowed into None -> not_configured -> 200.

- The SQLite probe opened the path with aiosqlite.connect(), which creates the
  file when missing: a deleted checkpoint database was silently resurrected as
  an empty file and reported ok instead of surfacing the outage.

## What changed

- backend/app/gateway/health.py: the two probes now run concurrently beneath a
  single endpoint-wide deadline (_READINESS_DEADLINE_SECONDS=3.0) so a healthy
  response completes within one probe window (~2s), never the sum of both.
  A probe that overruns the deadline degrades the endpoint instead of hanging.

- langgraph_runtime() now records the checkpointer/Store config resolved from
  the same startup_config snapshot its checkpointer/store singletons are built
  from (app.state.checkpointer_config); /health/ready probes that snapshot and
  never re-resolves hot-reloaded config. resolve_checkpointer_config() returns
  None on resolution failure and the endpoint fails closed (503, checkpointer:
  unreachable) instead of reporting not_configured.

- The SQLite probe opens disk-backed paths with the non-creating mode=rw URI
  flag, so a missing database file stays missing and yields unreachable;
  in-memory forms (:memory:, file:...mode=memory) have nothing external to
  probe and report not_configured like the memory backend.

- Orchestrator timeouts now sit above the endpoint bound: Helm readinessProbe
  gains timeoutSeconds: 5 (Kubernetes default is 1s) and the docker-compose
  gateway healthcheck client timeout moves from 3s to 5s.

## Verification

- New regression tests: concurrent probes keep total elapsed time within one
  probe window; a probe ignoring its budget trips the endpoint deadline to 503;
  missing SQLite file stays absent and yields unreachable; in-memory SQLite
  forms map to not_configured; missing startup snapshot / config resolution
  failure fail closed to 503; resolve_checkpointer_config() raising is covered.

- cd backend && python -m pytest tests/test_gateway_health.py: 21 passed;
  tests/test_gateway_docs_toggle.py and lifespan/shutdown gateway suites pass.

- ruff check + ruff format clean on all changed files.

## AI assistance

**Tool(s) used:** Codex (coding agent)

**How you used it:** implemented the reviewer-requested concurrency/deadline, startup-snapshot probing, fail-closed resolution, and non-creating SQLite probe; reviewed before commit.

- [ ] I've read and understand every line of this change and take responsibility for it — it's not unreviewed AI output.

* fix(gateway): serialize connection-opening readiness probes behind a strict gate

## Why

Review on #5166 (willem-bd, P1): every request to /health/ready opened a new
PostgreSQL connection in _probe_postgres_backend, outside both the ORM pool and
the runtime checkpointer pool. The route is public through the /health auth
prefix and nginx proxies /health/*, so concurrent unauthenticated requests
could create an unbounded number of connections (each held for up to two
seconds), exhaust PostgreSQL max_connections, and take down both normal
traffic and the readiness probe itself.

## What changed

- backend/app/gateway/health.py: connection-opening checkpointer probes
  (sqlite connect, postgres AsyncConnection.connect) now run inside a strict
  per-process gate - an asyncio.Lock cached per running event loop - so at
  most one probe connection can be in flight per worker process. Requests
  that queue behind the gate are still shed by the existing endpoint-wide
  deadline, so a flood cannot pile up new connections or open files.

- Memory and unknown-backend decisions stay outside the gate; payload and
  probe semantics are unchanged. The serialization is documented in the
  module docstring and backend/app/gateway/AGENTS.md.

## Verification

- New regression test: 8 concurrent readiness_payload() requests against an
  instrumented sqlite probe assert the maximum number of in-flight probe
  connections is 1 while every request still returns 200.

- cd backend && python -m pytest tests/test_gateway_health.py: 22 passed;
  tests/test_gateway_docs_toggle.py and tests/test_gateway_lifespan_shutdown.py
  also pass on the merged main head.

- ruff check + ruff format clean on all changed files.

## AI assistance

**Tool(s) used:** Codex (coding agent)

**How you used it:** implemented the reviewer-requested strict concurrency bound for the public readiness probe; reviewed before commit.

- [ ] I've read and understand every line of this change and take responsibility for it — it's not unreviewed AI output.
2026-09-04 23:26:53 +08:00

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"""Centralized accessors for singleton objects stored on ``app.state``.
**Getters** (used by routers): raise 503 when a required dependency is
missing, except ``get_store`` which returns ``None``.
``AppConfig`` is intentionally *not* cached on ``app.state``. Routers and the
run path resolve it through :func:`deerflow.config.app_config.get_app_config`,
which performs mtime-based hot reload, so edits to ``config.yaml`` take
effect on the next request without a process restart. The engines created in
:func:`langgraph_runtime` (stream bridge, persistence, checkpointer, store,
run-event store) accept a ``startup_config`` snapshot — they are
restart-required by design and stay bound to that snapshot to keep the live
process consistent with itself.
Initialization is handled directly in ``app.py`` via :class:`AsyncExitStack`.
"""
from __future__ import annotations
import asyncio
import logging
import os
from collections.abc import AsyncGenerator, Callable
from contextlib import AsyncExitStack, asynccontextmanager
from typing import TYPE_CHECKING, Any, TypeVar, cast
from fastapi import FastAPI, HTTPException, Request
from langgraph.types import Checkpointer
from deerflow.community.browser_automation.session import browser_multi_worker_error
from deerflow.config.app_config import AppConfig, get_app_config
from deerflow.persistence.feedback import FeedbackRepository
from deerflow.runtime import ORPHAN_RECOVERY_STOP_REASON, STARTUP_ORPHAN_RECOVERY_ERROR, RunContext, RunManager, StreamBridge
from deerflow.runtime.events.store.base import RunEventStore
from deerflow.runtime.runs.store.base import RunStore
logger = logging.getLogger(__name__)
# Upper bound (seconds) for draining in-flight runs during shutdown, before the
# AsyncExitStack tears down the checkpointer (and its connection pool). Kept
# local to avoid an app -> deps -> app import cycle. This is a *separate* budget
# from ``app.gateway.app._SHUTDOWN_HOOK_TIMEOUT_SECONDS`` (currently also 5.0s,
# which bounds channel-service stop): the two govern independent teardown steps
# and may diverge, but both count toward the lifespan shutdown window — revisit
# them together if their sum must stay within the server's graceful-shutdown
# timeout.
_RUN_DRAIN_TIMEOUT_SECONDS = 5.0
def _browser_tools_enabled_in_config(config: AppConfig) -> bool:
"""Return whether process-local agentic browser sessions are configured."""
get_tool_config = getattr(config, "get_tool_config", None)
if callable(get_tool_config):
return get_tool_config("browser_navigate") is not None
return any(getattr(tool, "name", None) == "browser_navigate" for tool in (getattr(config, "tools", None) or []))
def _enforce_postgres_for_multi_worker(config: AppConfig) -> None:
"""Refuse unsafe multi-process configurations before persistence starts.
Multi-instance scheduler recovery also needs the durable run ownership
contract even when each Pod runs a single Gateway worker.
1. The background scheduler must be disabled for ordinary multi-worker
mode. ``scheduler.multi_instance`` opts into the lease-aware path.
2. Process-local browser sessions must be disabled. Browser tools keep
Chromium and Playwright objects in one worker's memory, while ordinary
uvicorn dispatch provides no thread-id affinity.
3. The DB backend must be Postgres — SQLite write-locks cannot support
concurrent multi-process access.
4. ``run_events.backend`` must be ``db``. Memory and JSONL stores are
process-local, so workers cannot enforce a shared singleton receipt.
5. ``run_ownership.heartbeat_enabled`` must be True — without heartbeat,
every run has a NULL lease, so reconciliation treats all inflight
runs as orphans and Worker B would kill Worker A's live runs on
every rolling update or scale-up.
This gate runs once at startup before any persistence engine is
initialised so the error message is clear and the process exits
immediately.
"""
try:
workers = int(os.environ.get("GATEWAY_WORKERS", "1"))
except (TypeError, ValueError):
workers = 1
scheduler = getattr(config, "scheduler", None)
multi_instance_requested = bool(getattr(scheduler, "multi_instance", False))
multi_instance_scheduler = bool(getattr(scheduler, "enabled", False) and multi_instance_requested)
backend = getattr(config.database, "backend", None)
run_events_backend = getattr(getattr(config, "run_events", None), "backend", None)
run_ownership = getattr(config, "run_ownership", None)
if multi_instance_requested and backend != "postgres":
raise SystemExit(f"scheduler.multi_instance=true requires database.backend='postgres'. database.backend is '{backend}'. Set scheduler.multi_instance=false or configure Postgres.")
if multi_instance_requested and run_events_backend != "db":
raise SystemExit(f"scheduler.multi_instance=true requires run_events.backend='db'. run_events.backend is '{run_events_backend}'. Set scheduler.multi_instance=false or configure run_events.backend: db.")
if multi_instance_requested and (run_ownership is None or not run_ownership.heartbeat_enabled):
raise SystemExit("scheduler.multi_instance=true requires run_ownership.heartbeat_enabled=true so peer runs retain a valid lease. Set scheduler.multi_instance=false or enable run ownership heartbeats.")
if workers <= 1:
return
if config.scheduler.enabled and not multi_instance_scheduler:
raise SystemExit(f"GATEWAY_WORKERS={workers} cannot run with scheduler.enabled=true because each worker starts its own scheduler. Set GATEWAY_WORKERS=1, scheduler.multi_instance=true, or scheduler.enabled=false.")
if _browser_tools_enabled_in_config(config):
raise SystemExit(browser_multi_worker_error(workers))
if backend != "postgres":
raise SystemExit(f"GATEWAY_WORKERS={workers} requires database.backend='postgres', but database.backend is '{backend}'. SQLite cannot support concurrent multi-process access. Set GATEWAY_WORKERS=1 or switch to Postgres.")
if run_events_backend != "db":
raise SystemExit(
f"GATEWAY_WORKERS={workers} requires run_events.backend='db', but run_events.backend is '{run_events_backend}'. "
"Memory and JSONL event stores are process-local, so delivery receipt singleton guarantees cannot hold across workers. "
"Set GATEWAY_WORKERS=1 or configure run_events.backend: db."
)
if run_ownership is None or not run_ownership.heartbeat_enabled:
raise SystemExit(
f"GATEWAY_WORKERS={workers} requires run_ownership.heartbeat_enabled=true. "
"Without heartbeat, every run has a NULL lease, so reconciliation "
"treats all inflight runs as orphans — Worker B would kill Worker A's "
"live runs on every rolling update or scale-up. "
"Set run_ownership.heartbeat_enabled=true in config.yaml."
)
def _validate_agent_storage(config: AppConfig) -> None:
"""Fail fast on an agent-storage backend the database cannot support.
``agent_storage.backend: db`` needs a durable, shared SQL database — a
``memory`` database is per-process, so custom-agent and managed-subagent
definitions would silently diverge across nodes (and there is no SQL URL
to open). Mirrors deermem's create_storage fail-fast and the multi-worker
gate above.
Also warns when a multi-worker Postgres deployment leaves agent storage on
``file``: custom agents created on one node's local disk are invisible to
the others, exactly the divergence the db backend exists to fix.
"""
agent_storage = getattr(config, "agent_storage", None)
backend = getattr(agent_storage, "backend", "file")
db_backend = getattr(getattr(config, "database", None), "backend", None)
if backend == "db" and db_backend not in ("sqlite", "postgres"):
raise SystemExit(
f"agent_storage.backend='db' requires database.backend to be 'sqlite' or 'postgres', "
f"but database.backend is '{db_backend}'. A 'memory' database is per-process and cannot "
"share agent definitions across nodes. Set database.backend, or use agent_storage.backend='file'."
)
try:
workers = int(os.environ.get("GATEWAY_WORKERS", "1"))
except (TypeError, ValueError):
workers = 1
if workers > 1 and db_backend == "postgres" and backend == "file":
logger.warning(
"GATEWAY_WORKERS=%s with database.backend='postgres' but agent_storage.backend='file': "
"custom agents and managed subagents are stored per-node on local disk and are not visible "
"across workers/nodes. Set agent_storage.backend='db' to share them.",
workers,
)
async def _drain_inflight_runs(run_manager: RunManager) -> None:
"""Drain in-flight runs before the checkpointer is torn down (issue #3373).
Shields the (internally-bounded) drain so that even if the lifespan
coroutine is itself cancelled mid-shutdown — a second SIGINT or the server's
graceful-shutdown timeout, i.e. the same signal storm behind #3373 — the
checkpointer pool is not closed while run tasks are still writing
checkpoints. On such a cancellation we let the already-running drain finish
(it is bounded by ``RunManager.shutdown``'s own timeout) and then propagate
the cancellation.
"""
drain = asyncio.create_task(run_manager.shutdown(timeout=_RUN_DRAIN_TIMEOUT_SECONDS))
try:
await asyncio.shield(drain)
except asyncio.CancelledError:
# Re-shield so this second wait does not abandon the in-flight drain;
# it is bounded, so this cannot hang. Then re-raise to honour shutdown.
try:
await asyncio.shield(drain)
except Exception:
logger.exception("In-flight run drain failed after shutdown cancellation")
raise
except Exception:
logger.exception("Failed to drain in-flight runs during shutdown")
async def _publish_recovered_run_stream_end(
bridge: StreamBridge,
recovered_runs: list[RunRecord],
*,
cleanup_delay: float = 60.0,
on_cleanup_scheduled: Callable[[str, asyncio.Task[None]], None] | None = None,
) -> list[tuple[str, asyncio.Task[None]]]:
"""Terminate retained streams for runs recovered as orphaned."""
cleanup_tasks: list[tuple[str, asyncio.Task[None]]] = []
for record in recovered_runs:
stream_exists = getattr(bridge, "stream_exists", None)
if stream_exists is not None:
try:
if not await stream_exists(record.run_id):
logger.debug("Skipping recovered stream end for %s: stream already expired", record.run_id)
continue
except Exception:
logger.debug("Failed to check recovered stream existence for %s", record.run_id, exc_info=True)
try:
await bridge.publish_end(record.run_id)
except Exception:
logger.warning(
"Failed to publish recovered run stream end for %s",
record.run_id,
exc_info=True,
)
continue
task = asyncio.create_task(bridge.cleanup(record.run_id, delay=cleanup_delay))
task.add_done_callback(lambda task, run_id=record.run_id: _log_recovered_stream_cleanup_result(task, run_id))
cleanup_tasks.append((record.run_id, task))
if on_cleanup_scheduled is not None:
on_cleanup_scheduled(record.run_id, task)
return cleanup_tasks
def _log_recovered_stream_cleanup_result(task: asyncio.Task[None], run_id: str) -> None:
if task.cancelled():
return
try:
task.result()
except Exception:
logger.warning("Failed to clean up recovered run stream for %s", run_id, exc_info=True)
async def _flush_recovered_stream_cleanups(
bridge: StreamBridge,
cleanup_tasks: dict[asyncio.Task[None], str],
*,
timeout: float = 1.0,
) -> None:
"""Cancel delayed cleanups and delete their streams before bridge shutdown."""
pending = [(task, run_id) for task, run_id in cleanup_tasks.items() if not task.done()]
if not pending:
return
for task, _run_id in pending:
task.cancel()
await asyncio.gather(*(task for task, _run_id in pending), return_exceptions=True)
run_ids = list(dict.fromkeys(run_id for _task, run_id in pending))
try:
results = await asyncio.wait_for(
asyncio.gather(
*(bridge.cleanup(run_id, delay=0) for run_id in run_ids),
return_exceptions=True,
),
timeout=max(0.0, timeout),
)
except TimeoutError:
logger.warning(
"Immediate recovered stream cleanup exceeded %.1fs for run_ids=%s; bridge TTL remains the final safety net",
timeout,
run_ids,
)
else:
for run_id, result in zip(run_ids, results):
if isinstance(result, BaseException):
logger.warning(
"Failed to immediately clean up recovered run stream for %s: %r",
run_id,
result,
)
if TYPE_CHECKING:
from app.gateway.auth.local_provider import LocalAuthProvider
from app.gateway.auth.repositories.sqlite import SQLiteUserRepository
from deerflow.persistence.thread_meta.base import ThreadMetaStore
from deerflow.runtime import RunRecord
T = TypeVar("T")
async def _mark_latest_startup_recovered_threads_error(
run_manager: RunManager,
thread_store: ThreadMetaStore,
recovered_runs: list[RunRecord],
) -> None:
"""Project startup recovery before request-serving concurrency begins.
This helper must remain on the pre-``yield`` startup path. ``ThreadMetaStore``
has no ``latest_run_id`` column, so it cannot express an atomic conditional
update keyed by the recovered run. Periodic recovery deliberately skips this
projection; moving this helper after request serving starts would reintroduce
a read/update race with newer runs.
"""
recovered_by_thread: dict[str, set[str]] = {}
for record in recovered_runs:
recovered_by_thread.setdefault(record.thread_id, set()).add(record.run_id)
for thread_id, recovered_run_ids in recovered_by_thread.items():
try:
latest_runs = await run_manager.list_by_thread(thread_id, user_id=None, limit=1)
except Exception:
logger.warning("Failed to find latest run for thread %s during run reconciliation", thread_id, exc_info=True)
continue
if not latest_runs or latest_runs[0].run_id not in recovered_run_ids:
continue
try:
await thread_store.update_status(thread_id, "error", user_id=None)
except Exception:
logger.warning("Failed to mark thread %s as error during run reconciliation", thread_id, exc_info=True)
async def _terminalize_recovered_runs(
bridge: StreamBridge,
recovered_runs: list[RunRecord],
*,
cleanup_delay: float,
on_cleanup_scheduled: Callable[[str, asyncio.Task[None]], None] | None = None,
) -> list[tuple[str, asyncio.Task[None]]]:
"""Publish terminal markers and schedule retained-stream cleanup."""
return await _publish_recovered_run_stream_end(
bridge,
recovered_runs,
cleanup_delay=cleanup_delay,
on_cleanup_scheduled=on_cleanup_scheduled,
)
def get_config() -> AppConfig:
"""Return the freshest ``AppConfig`` for the current request.
Routes through :func:`deerflow.config.app_config.get_app_config`, which
honours runtime ``ContextVar`` overrides and reloads ``config.yaml`` from
disk when its mtime changes. ``AppConfig`` is not cached on ``app.state``
at all — the only startup-time snapshot lives as a local
``startup_config`` variable inside ``lifespan()`` and is passed
explicitly into :func:`langgraph_runtime` for the engines that are
restart-required by design. Routing every request through
:func:`get_app_config` closes the bytedance/deer-flow issue #3107 BUG-001
split-brain where the worker / lead-agent thread saw a stale startup
snapshot.
Hot-reload boundary: fields backed by startup-time singletons
(engines, sandbox provider, IM channels, logging handler) require a
process restart to change at runtime. The authoritative list lives in
:mod:`deerflow.config.reload_boundary` and is mirrored by the
standardised ``"startup-only:"`` prefix on the matching
``Field(description=...)`` in :class:`AppConfig` — IDE hover on those
fields will surface the boundary inline. See
``backend/CLAUDE.md`` "Config Hot-Reload Boundary" for the operator
summary.
Any failure to materialise the config (missing file, permission denied,
YAML parse error, validation error) is reported as 503 — semantically
"the gateway cannot serve requests without a usable configuration" — and
logged with the original exception so operators have something to debug.
"""
try:
return get_app_config()
except Exception as exc: # noqa: BLE001 - request boundary: log and degrade gracefully
logger.exception("Failed to load AppConfig at request time")
raise HTTPException(status_code=503, detail="Configuration not available") from exc
@asynccontextmanager
async def langgraph_runtime(app: FastAPI, startup_config: AppConfig) -> AsyncGenerator[None, None]:
"""Bootstrap and tear down all LangGraph runtime singletons.
``startup_config`` is the ``AppConfig`` snapshot taken once during
``lifespan()`` for one-shot infrastructure bootstrap. The engines and
stores constructed here (stream bridge, persistence engine, checkpointer,
store, run-event store) are restart-required by design — they hold live
connections, file handles, or singleton providers — so they bind to this
snapshot and survive across `config.yaml` edits. Request-time consumers
must still go through :func:`get_config` for any field that should be
hot-reloadable. See ``backend/CLAUDE.md`` "Config Hot-Reload Boundary".
The matching ``run_events_config`` is frozen onto ``app.state`` so
:func:`get_run_context` pairs a freshly-loaded ``AppConfig`` with the
*startup-time* run-events configuration the underlying ``event_store``
was built from — otherwise the runtime could end up combining a live
new ``run_events_config`` with an event store still bound to the
previous backend.
Usage in ``app.py``::
async with langgraph_runtime(app, startup_config):
yield
"""
from deerflow.persistence.engine import close_engine, get_session_factory, init_engine_from_config
from deerflow.runtime import make_store, make_stream_bridge
from deerflow.runtime.checkpoint_mode import freeze_checkpoint_channel_mode, freeze_checkpoint_snapshot_frequency
from deerflow.runtime.checkpointer.async_provider import make_checkpointer
from deerflow.runtime.events.store import make_run_event_store
# ------------------------------------------------------------------
# Multi-worker safety gate: reject SQLite when GATEWAY_WORKERS > 1.
# SQLite write-locks cannot support concurrent multi-process access.
# ------------------------------------------------------------------
_enforce_postgres_for_multi_worker(startup_config)
# Reject agent_storage.backend='db' on a non-durable database, and warn on
# node-divergent file storage under multi-worker Postgres.
_validate_agent_storage(startup_config)
async with AsyncExitStack() as stack:
# Lifecycle and system-model hooks can originate on isolated subagent
# loops. Bind them to the Gateway's serving loop before any runtime
# dependency starts, then reset the binding last through the exit
# stack. Registering the callback synchronously here also covers every
# startup-failure and cancellation path below.
try:
from deerflow.extensions.notify import (
reset_extension_notify_loop,
set_extension_notify_loop,
)
set_extension_notify_loop(asyncio.get_running_loop())
except Exception:
logger.exception("Failed to register the extension notify loop; sync observations will be dropped")
else:
def reset_notify_loop_safely() -> None:
try:
reset_extension_notify_loop()
except Exception:
logger.debug(
"Failed to reset the extension notify loop (non-fatal)",
exc_info=True,
)
stack.callback(reset_notify_loop_safely)
config = startup_config
app.state.checkpoint_channel_mode = freeze_checkpoint_channel_mode(config.database.checkpoint_channel_mode)
app.state.checkpoint_snapshot_frequency = freeze_checkpoint_snapshot_frequency(config.database.checkpoint_delta.snapshot_frequency)
app.state.stream_bridge = await stack.enter_async_context(make_stream_bridge(config))
# Initialize persistence engine BEFORE checkpointer so that
# auto-create-database logic runs first (postgres backend).
# Own cleanup before initialization so partial startup and host
# cancellation cannot strand an engine created along the way.
stack.push_async_callback(close_engine)
await init_engine_from_config(config.database)
app.state.checkpointer = await stack.enter_async_context(make_checkpointer(config))
app.state.store = await stack.enter_async_context(make_store(config))
# Record the checkpointer/Store backend selected from this startup
# snapshot so GET /health/ready probes what the running process
# actually uses. These singletons are restart-required by design and
# are never rebuilt on config.yaml hot reload, so the probe must not
# re-resolve process-wide configuration per request.
from app.gateway.health import READINESS_CHECKPOINTER_CONFIG_ATTR, resolve_checkpointer_config
setattr(app.state, READINESS_CHECKPOINTER_CONFIG_ATTR, resolve_checkpointer_config(config))
# Initialize repositories — one get_session_factory() call for all.
sf = get_session_factory()
if sf is not None:
from deerflow.persistence.feedback import FeedbackRepository
from deerflow.persistence.personal_access_tokens import PersonalAccessTokenRepository
from deerflow.persistence.run import RunRepository
app.state.run_store = RunRepository(sf)
app.state.feedback_repo = FeedbackRepository(sf)
from app.gateway.auth.pat import PAT_LAST_USED_WRITE_INTERVAL_SECONDS
app.state.pat_repo = PersonalAccessTokenRepository(sf, last_used_write_interval_seconds=PAT_LAST_USED_WRITE_INTERVAL_SECONDS)
else:
from deerflow.runtime.runs.store.memory import MemoryRunStore
app.state.run_store = MemoryRunStore()
app.state.feedback_repo = None
# Memory backend has no durable PAT store, so Bearer credentials
# cannot be validated there and are rejected by the middleware.
app.state.pat_repo = None
# Services are app-scoped. Capture this app's immutable extension set
# once and close over the same object for teardown; the process-wide
# singleton may be replaced by another app/test before shutdown.
from deerflow.extensions import EMPTY_EXTENSIONS, record_runtime_diagnostics
from deerflow.extensions.gateway import start_services, stop_services
extensions = getattr(app.state, "extensions", EMPTY_EXTENSIONS)
attempted_services: list[tuple[str, Any]] = []
async def stop_extension_services() -> None:
record_runtime_diagnostics(
await stop_services(
extensions,
service_entries=attempted_services,
)
)
# Register cleanup before starting: start() can partially acquire
# resources and then fail or be cancelled.
stack.push_async_callback(stop_extension_services)
record_runtime_diagnostics(
await start_services(
extensions,
config,
sf,
attempted_services=attempted_services,
)
)
from deerflow.persistence.thread_meta import make_thread_store
app.state.thread_store = make_thread_store(sf, app.state.store)
if sf is not None:
from deerflow.persistence.mcp_tasks import McpTaskRepository
from deerflow.persistence.scheduled_task_runs import (
ScheduledTaskRunRepository,
)
from deerflow.persistence.scheduled_tasks import ScheduledTaskRepository
from deerflow.persistence.subagent_batches import SubagentBatchRepository
app.state.scheduled_task_repo = ScheduledTaskRepository(
sf,
run_repository=app.state.run_store,
)
app.state.scheduled_task_run_repo = ScheduledTaskRunRepository(
sf,
run_repository=app.state.run_store,
)
app.state.mcp_task_repo = McpTaskRepository(sf)
app.state.subagent_batch_repo = SubagentBatchRepository(sf)
else:
app.state.mcp_task_repo = None
app.state.subagent_batch_repo = None
app.state.scheduled_task_repo = None
app.state.scheduled_task_run_repo = None
# Run event store. The store and the matching ``run_events_config`` are
# both frozen at startup so ``get_run_context`` does not combine a
# freshly-reloaded ``AppConfig.run_events`` with a store still bound to
# the previous backend.
run_events_config = getattr(config, "run_events", None)
app.state.run_events_config = run_events_config
app.state.run_event_store = make_run_event_store(run_events_config)
# RunManager with store backing for persistence
run_ownership_config = getattr(config, "run_ownership", None)
sb_config = getattr(config, "stream_bridge", None)
cleanup_delay = getattr(sb_config, "recovered_stream_cleanup_delay_seconds", 60.0) if sb_config else 60.0
recovered_stream_cleanup_tasks: dict[asyncio.Task[None], str] = {}
def track_recovered_stream_cleanup(
run_id: str,
task: asyncio.Task[None],
) -> None:
recovered_stream_cleanup_tasks[task] = run_id
task.add_done_callback(lambda completed: recovered_stream_cleanup_tasks.pop(completed, None))
async def terminalize_recovered_runs(recovered_runs: list[RunRecord]) -> None:
await _terminalize_recovered_runs(
app.state.stream_bridge,
recovered_runs,
cleanup_delay=cleanup_delay,
on_cleanup_scheduled=track_recovered_stream_cleanup,
)
app.state.run_manager = RunManager(
store=app.state.run_store,
run_ownership_config=run_ownership_config,
event_store=app.state.run_event_store,
on_orphans_recovered=terminalize_recovered_runs,
)
# Startup recovery: mark inflight runs whose lease has expired as error.
# In single-worker mode (SQLite / backend=memory), no run has a lease, so
# all inflight rows are reclaimed (unchanged behaviour). In multi-worker
# mode (Postgres), only runs with an expired lease are reclaimed; runs
# owned by another live worker are skipped.
from deerflow.utils.time import now_iso
recovered_runs = await app.state.run_manager.reconcile_orphaned_inflight_runs(
error=STARTUP_ORPHAN_RECOVERY_ERROR,
before=now_iso(),
stop_reason=ORPHAN_RECOVERY_STOP_REASON,
)
await _terminalize_recovered_runs(
app.state.stream_bridge,
recovered_runs,
cleanup_delay=cleanup_delay,
on_cleanup_scheduled=track_recovered_stream_cleanup,
)
await _mark_latest_startup_recovered_threads_error(
app.state.run_manager,
app.state.thread_store,
recovered_runs,
)
# Start the lease heartbeat if enabled (multi-worker deployments).
await app.state.run_manager.start_heartbeat()
try:
yield
finally:
# Drain in-flight run tasks BEFORE the AsyncExitStack tears down the
# checkpointer (and its connection pool). A run still mid-graph would
# otherwise leak into asyncio.run() shutdown, where langgraph's
# _checkpointer_put_after_previous aput races the closed pool and
# raises PoolClosed (issue #3373).
run_manager = getattr(app.state, "run_manager", None)
if run_manager is not None:
shutdown_deadline = asyncio.get_running_loop().time() + _RUN_DRAIN_TIMEOUT_SECONDS
try:
await _drain_inflight_runs(run_manager)
finally:
await _flush_recovered_stream_cleanups(
app.state.stream_bridge,
recovered_stream_cleanup_tasks,
timeout=min(
1.0,
max(
0.0,
shutdown_deadline - asyncio.get_running_loop().time(),
),
),
)
# ---------------------------------------------------------------------------
# Getters called by routers per-request
# ---------------------------------------------------------------------------
def _require(attr: str, label: str) -> Callable[[Request], T]:
"""Create a FastAPI dependency that returns ``app.state.<attr>`` or 503."""
def dep(request: Request) -> T:
val = getattr(request.app.state, attr, None)
if val is None:
raise HTTPException(status_code=503, detail=f"{label} not available")
return cast(T, val)
dep.__name__ = dep.__qualname__ = f"get_{attr}"
return dep
get_stream_bridge: Callable[[Request], StreamBridge] = _require("stream_bridge", "Stream bridge")
get_run_manager: Callable[[Request], RunManager] = _require("run_manager", "Run manager")
get_checkpointer: Callable[[Request], Checkpointer] = _require("checkpointer", "Checkpointer")
get_run_event_store: Callable[[Request], RunEventStore] = _require("run_event_store", "Run event store")
get_feedback_repo: Callable[[Request], FeedbackRepository] = _require("feedback_repo", "Feedback")
get_run_store: Callable[[Request], RunStore] = _require("run_store", "Run store")
def get_store(request: Request):
"""Return the global store (may be ``None`` if not configured)."""
return getattr(request.app.state, "store", None)
def get_thread_store(request: Request) -> ThreadMetaStore:
"""Return the thread metadata store (SQL or memory-backed)."""
val = getattr(request.app.state, "thread_store", None)
if val is None:
raise HTTPException(status_code=503, detail="Thread metadata store not available")
return val
def get_scheduled_task_repo(request: Request):
val = getattr(request.app.state, "scheduled_task_repo", None)
if val is None:
raise HTTPException(status_code=503, detail="Scheduled task repo not available")
return val
def get_scheduled_task_run_repo(request: Request):
val = getattr(request.app.state, "scheduled_task_run_repo", None)
if val is None:
raise HTTPException(status_code=503, detail="Scheduled task run repo not available")
return val
def get_scheduled_task_service(request: Request):
val = getattr(request.app.state, "scheduled_task_service", None)
if val is None:
raise HTTPException(status_code=503, detail="Scheduled task service not available")
return val
def get_mcp_task_repo(request: Request):
val = getattr(request.app.state, "mcp_task_repo", None)
if val is None:
raise HTTPException(status_code=503, detail="MCP task repo not available")
return val
def get_mcp_task_service(request: Request):
val = getattr(request.app.state, "mcp_task_service", None)
if val is None:
raise HTTPException(status_code=503, detail="MCP task service not available")
return val
def get_subagent_batch_repo(request: Request):
val = getattr(request.app.state, "subagent_batch_repo", None)
if val is None:
raise HTTPException(status_code=503, detail="Subagent batch repository not available")
return val
def get_subagent_batch_service(request: Request):
val = getattr(request.app.state, "subagent_batch_service", None)
if val is None:
raise HTTPException(status_code=503, detail="Subagent batch service not available")
return val
def get_run_context(request: Request) -> RunContext:
"""Build a :class:`RunContext` from ``app.state`` singletons.
Returns a *base* context with infrastructure dependencies. The
``app_config`` field is resolved live so per-run fields (e.g.
``models[*].max_tokens``) follow ``config.yaml`` edits; the
``event_store`` / ``run_events_config`` pair stays frozen to the snapshot
captured in :func:`langgraph_runtime` so callers never see a store bound
to one backend paired with a config pointing at another.
"""
return RunContext(
checkpointer=get_checkpointer(request),
store=get_store(request),
event_store=get_run_event_store(request),
run_events_config=getattr(request.app.state, "run_events_config", None),
checkpoint_channel_mode=getattr(request.app.state, "checkpoint_channel_mode", "full"),
checkpoint_snapshot_frequency=getattr(request.app.state, "checkpoint_snapshot_frequency", None),
thread_store=get_thread_store(request),
mcp_task_repo=getattr(request.app.state, "mcp_task_repo", None),
app_config=get_config(),
extensions=getattr(request.app.state, "extensions", None),
on_run_completed=getattr(request.app.state, "scheduled_task_service", None).handle_run_completion if getattr(request.app.state, "scheduled_task_service", None) is not None else None,
)
# ---------------------------------------------------------------------------
# Auth helpers (used by authz.py and auth middleware)
# ---------------------------------------------------------------------------
# Cached singletons to avoid repeated instantiation per request
_cached_local_provider: LocalAuthProvider | None = None
_cached_repo: SQLiteUserRepository | None = None
def get_local_provider() -> LocalAuthProvider:
"""Get or create the cached LocalAuthProvider singleton.
Must be called after ``init_engine_from_config()`` — the shared
session factory is required to construct the user repository.
"""
global _cached_local_provider, _cached_repo
if _cached_repo is None:
from app.gateway.auth.repositories.sqlite import SQLiteUserRepository
from deerflow.persistence.engine import get_session_factory
sf = get_session_factory()
if sf is None:
raise RuntimeError("get_local_provider() called before init_engine_from_config(); cannot access users table")
_cached_repo = SQLiteUserRepository(sf)
if _cached_local_provider is None:
from app.gateway.auth.local_provider import LocalAuthProvider
_cached_local_provider = LocalAuthProvider(repository=_cached_repo)
return _cached_local_provider
def get_pat_repo(request: Request):
"""Return the personal-access-token repository from app state.
Raises 503 when the process runs on the memory backend (no durable PAT
storage), so PAT management routes fail explicitly instead of silently
accepting tokens nobody can validate.
"""
pat_repo = getattr(request.app.state, "pat_repo", None)
if pat_repo is None:
raise HTTPException(status_code=503, detail="Personal access tokens require a configured database")
return pat_repo
async def get_current_user_from_request(request: Request):
"""Get the current authenticated user from the request cookie.
Raises HTTPException 401 if not authenticated.
"""
state = getattr(request, "state", None)
state_user = getattr(state, "user", None)
from app.gateway.auth_disabled import AUTH_SOURCE_AUTH_DISABLED, AUTH_SOURCE_INTERNAL, AUTH_SOURCE_PAT, AUTH_SOURCE_SESSION
if state_user is not None and getattr(state, "auth_source", None) in {
AUTH_SOURCE_SESSION,
AUTH_SOURCE_AUTH_DISABLED,
AUTH_SOURCE_INTERNAL,
AUTH_SOURCE_PAT,
}:
return state_user
from app.gateway.auth import decode_token
from app.gateway.auth.errors import AuthErrorCode, AuthErrorResponse, TokenError, token_error_to_code
access_token = request.cookies.get("access_token")
if not access_token:
raise HTTPException(
status_code=401,
detail=AuthErrorResponse(code=AuthErrorCode.NOT_AUTHENTICATED, message="Not authenticated").model_dump(),
)
payload = decode_token(access_token)
if isinstance(payload, TokenError):
raise HTTPException(
status_code=401,
detail=AuthErrorResponse(code=token_error_to_code(payload), message=f"Token error: {payload.value}").model_dump(),
)
provider = get_local_provider()
user = await provider.get_user(payload.sub)
if user is None:
raise HTTPException(
status_code=401,
detail=AuthErrorResponse(code=AuthErrorCode.USER_NOT_FOUND, message="User not found").model_dump(),
)
# Token version mismatch → password was changed, token is stale
if user.token_version != payload.ver:
raise HTTPException(
status_code=401,
detail=AuthErrorResponse(code=AuthErrorCode.TOKEN_INVALID, message="Token revoked (password changed)").model_dump(),
)
return user
async def is_admin_user(request: Request) -> bool:
"""Return whether the authenticated caller is an admin user.
``AuthMiddleware`` normally stamps ``request.state.user`` before the request
reaches a router. Falling back to the strict dependency keeps the route safe
in tests or alternative ASGI compositions that mount a router without the
global middleware.
Centralising this here means a future change to the admin definition (e.g.
allowing an internal system role, adding audit logging, or switching to a
permission-based check) lands in one place instead of drifting across the
per-router copies that previously existed in ``mcp``, ``channel_connections``
and ``channels``.
"""
# PAT credentials never carry admin capability: no scope in the PAT
# universe grants it, so an admin's automation token must not unlock
# admin-only routes (skill installs, integration credentials, MCP config).
from app.gateway.auth_disabled import AUTH_SOURCE_PAT
if getattr(request.state, "auth_source", None) == AUTH_SOURCE_PAT:
return False
user = getattr(request.state, "user", None)
if user is None:
user = await get_current_user_from_request(request)
return getattr(user, "system_role", None) == "admin"
async def require_admin_user(request: Request, *, detail: str) -> None:
"""Require the authenticated caller to be an admin user.
``detail`` is the route-specific 403 message. The shared predicate keeps
read-side redaction and write authorization on the same admin definition.
"""
if not await is_admin_user(request):
raise HTTPException(status_code=403, detail=detail)
async def get_optional_user_from_request(request: Request):
"""Get optional authenticated user from request.
Returns None if not authenticated.
"""
try:
return await get_current_user_from_request(request)
except HTTPException:
return None
async def get_current_user(request: Request) -> str | None:
"""Extract user_id from request cookie, or None if not authenticated.
Thin adapter that returns the string id for callers that only need
identification (e.g., ``feedback.py``). Full-user callers should use
``get_current_user_from_request`` or ``get_optional_user_from_request``.
"""
user = await get_optional_user_from_request(request)
return str(user.id) if user else None