This commit is contained in:
kgod
2026-05-26 21:02:17 +08:00
commit 8697477a53
10000 changed files with 1541403 additions and 0 deletions
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"""Streaming infrastructure for LangGraph.
Compile a graph with `transformers=[...]` and call `graph.stream_events(version="v3")` /
`graph.astream_events(version="v3")` to drive a transformer pipeline that projects the
graph's raw events into ergonomic per-channel streams.
"""
from langgraph.stream._types import ProtocolEvent, StreamTransformer
from langgraph.stream.run_stream import (
AsyncGraphRunStream,
AsyncSubgraphRunStream,
GraphRunStream,
SubgraphRunStream,
)
from langgraph.stream.stream_channel import StreamChannel
from langgraph.stream.transformers import (
CheckpointsTransformer,
CustomTransformer,
DebugTransformer,
LifecyclePayload,
LifecycleTransformer,
SubgraphStatus,
SubgraphTransformer,
TasksTransformer,
UpdatesTransformer,
)
__all__ = [
"AsyncGraphRunStream",
"AsyncSubgraphRunStream",
"CheckpointsTransformer",
"CustomTransformer",
"DebugTransformer",
"GraphRunStream",
"LifecyclePayload",
"LifecycleTransformer",
"ProtocolEvent",
"StreamChannel",
"StreamTransformer",
"SubgraphRunStream",
"SubgraphStatus",
"SubgraphTransformer",
"TasksTransformer",
"UpdatesTransformer",
]
@@ -0,0 +1,32 @@
from __future__ import annotations
import time
from typing import Any, cast
from langgraph.stream._types import ProtocolEvent, _ProtocolEventParams
from langgraph.types import StreamPart
def convert_to_protocol_event(part: StreamPart) -> ProtocolEvent:
"""Convert a v2 StreamPart to a ProtocolEvent.
Args:
part: A stream part with keys `type`, `ns`, `data`, and
optionally `interrupts` (present on values events).
Returns:
The equivalent ProtocolEvent.
"""
part_dict = cast(dict[str, Any], part)
params: _ProtocolEventParams = {
"namespace": list(part_dict["ns"]),
"timestamp": int(time.time() * 1000),
"data": part_dict["data"],
}
if "interrupts" in part_dict:
params["interrupts"] = part_dict["interrupts"]
return {
"type": "event",
"method": part_dict["type"],
"params": params,
}
@@ -0,0 +1,498 @@
from __future__ import annotations
import asyncio
import time
from collections.abc import Awaitable, Callable
from typing import Any
from langgraph.stream._types import (
ProtocolEvent,
StreamTransformer,
transformer_requires_async,
)
from langgraph.stream.stream_channel import StreamChannel
TransformerFactory = Callable[["tuple[str, ...]"], StreamTransformer]
"""Factory that builds a scoped transformer for a mux.
Called once per `StreamMux` with the mux's scope (typically `()` for
the root). Standard transformer classes accept a single positional
scope argument, so the class itself is a valid factory. User
transformers can close over their config:
`lambda scope: MyTransformer(scope, foo=...)`.
"""
class StreamMux:
"""Central event dispatcher for the streaming infrastructure.
Owns the main event log and routes events through a transformer
pipeline. StreamChannels with a name discovered in transformer
projections are auto-wired so that every `push()` also injects a
`ProtocolEvent` into the main log. StreamChannels without a name
are local-only.
Pass `is_async=True` when the mux will be consumed via async
iteration (`handler.astream()`). All StreamChannel instances
discovered during registration are automatically bound to the
matching mode.
Attributes:
extensions: Merged projection dict across all registered
transformers. Treat as read-only — mutations won't be
reflected back in individual transformers' state.
native_keys: Projection keys contributed by transformers with
`_native = True`.
"""
def __init__(
self,
transformers: list[StreamTransformer] | None = None,
*,
is_async: bool = False,
factories: list[TransformerFactory] | None = None,
scope: tuple[str, ...] = (),
_assign_seq: bool = True,
) -> None:
"""Initialize the mux and register transformers in order.
Callers pass either `transformers` (pre-built instances) or
`factories` (callables producing fresh instances per mux). Each
transformer's `init()` is called, projections are merged into
`extensions`, `_native` keys are recorded in `native_keys`, and
any StreamChannel instances are bound and (if named) wired.
Args:
transformers: Already-built transformer instances. Registered
only on this mux — they are NOT cloned into child
mini-muxes built by `_make_child`. Use `factories` for
transformers that should propagate to nested scopes.
is_async: True for async dispatch (`apush` / `aclose` /
`afail`), False for the sync path.
factories: One-argument callables `(scope) -> StreamTransformer`.
Called once with this mux's `scope` here, and cloned
again per child scope by `_make_child` so each
sub-mux gets fresh instances.
scope: The namespace the mux operates within. The root mux
is `()`.
_assign_seq: Internal flag for child muxes. Root muxes assign
monotonic `seq` numbers when appending to their main event
log; child muxes share forwarded event objects and must not
mutate their envelopes.
Raises:
RuntimeError: If any transformer requires an async run but
the mux is in sync mode.
TypeError: If a transformer's `init()` doesn't return a dict.
ValueError: If transformers' projection keys collide.
"""
self.is_async = is_async
self.scope: tuple[str, ...] = scope
self._assign_seq = _assign_seq
self._events: StreamChannel[ProtocolEvent] = StreamChannel()
self._events._bind(is_async=is_async)
self._events._bind_mux(self)
self._transformers: list[StreamTransformer] = []
self._channels: list[StreamChannel[Any]] = []
self._seq = 0
self._push_seq = 0
self.extensions: dict[str, Any] = {}
self.native_keys: set[str] = set()
self._projection_owners: dict[str, str] = {}
self._transformer_by_key: dict[str, StreamTransformer] = {}
# Stored only when constructed from factories — used by
# `_make_child` to clone the transformer pipeline at a deeper
# scope. Pre-built transformers can't be cloned, so a mux
# built with `transformers=` rejects child construction.
self._factories: list[TransformerFactory] | None = (
list(factories) if factories is not None else None
)
self._pump_fn: Callable[[], bool] | None = None
self._apump_fn: Callable[[], Awaitable[bool]] | None = None
# Factories run first (they propagate to child mini-muxes
# via `_make_child`), then any pre-built `transformers=`
# instances are registered as root-only — they aren't cloned
# for child scopes.
if factories is not None:
for factory in factories:
self._register(factory(scope))
for transformer in transformers or ():
self._register(transformer)
def transformer_by_key(self, key: str) -> StreamTransformer | None:
"""Return the transformer that contributed `key` to the projection."""
return self._transformer_by_key.get(key)
def _next_push_seq(self) -> int:
self._push_seq += 1
return self._push_seq
# ------------------------------------------------------------------
# Pump wiring + mini-mux nesting
# ------------------------------------------------------------------
def bind_pump(self, fn: Callable[[], bool]) -> None:
"""Wire the sync pull callback onto every projection in this mux.
Records the pump on the mux so child mini-muxes built by
`_make_child` can inherit it. Propagates to:
- the main event log (`self._events`)
- every projection StreamChannel in `extensions`
- any registered transformer that exposes `_bind_pump` (e.g.
`MessagesTransformer` so `ChatModelStream` instances drive the
shared pump from their cursors)
"""
self._pump_fn = fn
self._events._request_more = fn
for ch in self._channels:
ch._request_more = fn
for transformer in self._transformers:
bind = getattr(transformer, "_bind_pump", None)
if bind is not None:
bind(fn)
def bind_apump(self, fn: Callable[[], Awaitable[bool]]) -> None:
"""Async counterpart to `bind_pump`."""
self._apump_fn = fn
self._events._arequest_more = fn
for ch in self._channels:
ch._arequest_more = fn
for transformer in self._transformers:
abind = getattr(transformer, "_bind_apump", None)
if abind is not None:
abind(fn)
def _make_child(self, scope: tuple[str, ...]) -> StreamMux:
"""Build a mini-mux with the same factories scoped to `scope`.
Used by `SubgraphTransformer` to attach a fresh transformer
pipeline to each discovered subgraph handle. The child mux
inherits the current pump bindings (so cursors on its
projection logs drive the root pump), carries the same factory
list forward to any grandchild subgraphs, and does not assign
`seq` numbers so forwarded events can be shared without
mutating their envelope.
Raises:
RuntimeError: If the mux was not constructed with
`factories=`. Mini-muxes require factories so each scope
gets its own fresh transformer instances.
"""
if self._factories is None:
raise RuntimeError(
"StreamMux._make_child requires the mux to be constructed "
"with `factories=`; pre-built transformers can't be "
"cloned to a new scope."
)
child = StreamMux(
factories=self._factories,
is_async=self.is_async,
scope=scope,
_assign_seq=False,
)
if self._pump_fn is not None:
child.bind_pump(self._pump_fn)
if self._apump_fn is not None:
child.bind_apump(self._apump_fn)
return child
def _register(self, transformer: StreamTransformer) -> None:
"""Register a single transformer.
Calls `transformer.init()`, stores the transformer for event
processing, binds any StreamChannel instances in the projection,
and merges the projection into `extensions`.
"""
if transformer_requires_async(transformer) and not self.is_async:
raise RuntimeError(
f"{type(transformer).__name__} requires an async run — "
"it overrides aprocess/afinalize/afail or sets "
"requires_async=True. Use astream(), not stream()."
)
projection = transformer.init()
if not isinstance(projection, dict):
raise TypeError(
f"StreamTransformer.init() must return a dict, "
f"got {type(projection).__name__}"
)
conflicts = set(projection) & set(self.extensions)
if conflicts:
attributions = ", ".join(
f"{key!r} (owned by {self._projection_owners[key]})"
for key in sorted(conflicts)
)
raise ValueError(
f"Transformer {type(transformer).__name__} returned "
f"projection keys that conflict with already-registered "
f"keys: {attributions}"
)
is_native = bool(getattr(transformer, "_native", False))
self._transformers.append(transformer)
self._bind_and_wire(projection, native=is_native)
self.extensions.update(projection)
owner_name = type(transformer).__name__
for key in projection:
self._projection_owners[key] = owner_name
self._transformer_by_key[key] = transformer
if is_native:
self.native_keys.update(projection.keys())
transformer._on_register(self)
def push(self, event: ProtocolEvent) -> None:
"""Route an event through all transformers, then append to the main log.
Each transformer's `process()` is called in registration order.
If any transformer returns False, the event is suppressed from
the main log, but transformers that already saw it keep their
side effects.
On the root mux, `seq` is assigned right before an event enters
the main log, not before the transformer pipeline runs. This
ensures that events auto-forwarded from StreamChannels during
`process()` get earlier seq numbers than the original event,
preserving monotonic ordering in the root log. Child muxes do
not assign `seq`, so subgraph forwarding can share event objects
without mutating their envelopes.
Args:
event: The protocol event to dispatch.
"""
keep = True
for transformer in self._transformers:
if not transformer.process(event):
keep = False
if keep:
if self._assign_seq:
self._seq += 1
event["seq"] = self._seq
self._events.push(event)
def close(self) -> None:
"""Finalize all transformers, close all projections and the main log.
StreamChannels discovered in transformer projections are
auto-closed after `finalize()` runs — transformers don't need
to close them manually. If any transformer's `finalize()` raises,
the remaining transformers, projections, and the main log are
still closed; the first error is re-raised after cleanup
completes.
Raises:
BaseException: The first error raised by a transformer's
`finalize()`, re-raised after cleanup finishes.
"""
first_error: BaseException | None = None
for transformer in self._transformers:
try:
transformer.finalize()
except BaseException as e:
if first_error is None:
first_error = e
for ch in self._channels:
if not ch._closed:
ch.close()
self._events.close()
if first_error is not None:
raise first_error
def fail(self, err: BaseException) -> None:
"""Fail all transformers, projections, and the main log.
StreamChannels discovered in transformer projections are
auto-failed — transformers don't need to fail them manually.
If any transformer's `fail()` raises, the remaining
transformers, projections, and the main log are still failed.
Args:
err: The exception that ended the run.
"""
for transformer in self._transformers:
try:
transformer.fail(err)
except BaseException:
pass
for ch in self._channels:
if not ch._closed:
ch.fail(err)
self._events.fail(err)
# ------------------------------------------------------------------
# Async dispatch
# ------------------------------------------------------------------
async def apush(self, event: ProtocolEvent) -> None:
"""Dispatch an event on the async lane.
Awaits each transformer's `aprocess` in registration order
before appending to the main log. A slow `aprocess` serializes
the pipeline by design — that's the guarantee that lets a later
transformer (or a synchronous consumer) see the result of the
async work. For decoupled work, use `schedule()` from inside
`process` / `aprocess` instead.
The main log append is a non-blocking `push` — matching v1's
`put_nowait` shape. The root mux assigns `seq`; child muxes do
not, so forwarded subgraph events can be shared without copying.
Memory is bounded by caller pace via the caller-driven pump; see
`StreamChannel` for the full tradeoff story.
Args:
event: The protocol event to dispatch.
"""
keep = True
for transformer in self._transformers:
if not await transformer.aprocess(event):
keep = False
if keep:
if self._assign_seq:
self._seq += 1
event["seq"] = self._seq
self._events.push(event)
async def aclose(self) -> None:
"""Finalize on the async lane.
Awaits every task started via `StreamTransformer.schedule()`
across all transformers, then calls `afinalize()` on each,
then auto-closes channels and the main event log.
If any scheduled task raised under `on_error="raise"`, or any
transformer's `afinalize` raises, the exception propagates.
The caller (the pump) handles it by routing into `afail`.
Raises:
BaseException: The first scheduled-task or `afinalize`
error, re-raised after cleanup.
"""
pending = self._collect_scheduled_tasks()
if pending:
results = await asyncio.gather(*pending, return_exceptions=True)
first_err = next(
(
r
for r in results
if isinstance(r, BaseException)
and not isinstance(r, asyncio.CancelledError)
),
None,
)
if first_err is not None:
raise first_err
first_error: BaseException | None = None
for transformer in self._transformers:
try:
await transformer.afinalize()
except BaseException as e:
if first_error is None:
first_error = e
for ch in self._channels:
if not ch._closed:
ch.close()
self._events.close()
if first_error is not None:
raise first_error
async def afail(self, err: BaseException) -> None:
"""Fail on the async lane.
Cancels every scheduled task across all transformers, awaits
them to completion, then runs each transformer's `afail` hook
and auto-fails channels and the main event log.
Args:
err: The exception that ended the run.
"""
pending = self._collect_scheduled_tasks()
for task in pending:
task.cancel()
if pending:
await asyncio.gather(*pending, return_exceptions=True)
for transformer in self._transformers:
try:
await transformer.afail(err)
except BaseException:
pass
for ch in self._channels:
if not ch._closed:
ch.fail(err)
if not self._events._closed:
self._events.fail(err)
def _collect_scheduled_tasks(self) -> list[asyncio.Task[Any]]:
"""Return a snapshot of in-flight tasks scheduled via transformers."""
return [
task
for transformer in self._transformers
for task in getattr(transformer, "_stream_scheduled_tasks", ())
if not task.done()
]
# ------------------------------------------------------------------
# Binding and StreamChannel auto-wiring
# ------------------------------------------------------------------
def _bind_and_wire(
self, projection: dict[str, Any], *, native: bool = False
) -> None:
"""Bind and optionally wire StreamChannel instances in a projection.
All StreamChannels are bound and tracked. Channels with a name
are additionally wired for protocol auto-forwarding.
Args:
projection: The projection dict returned by a transformer's
`init()`.
native: True when the owning transformer is `_native`.
Named channels owned by a native transformer use the
channel name directly as the protocol method;
user-defined channels are prefixed with `custom:`.
"""
for value in projection.values():
if isinstance(value, StreamChannel):
value._bind(is_async=self.is_async)
value._bind_mux(self)
self._channels.append(value)
if value.name is not None:
method = value.name if native else f"custom:{value.name}"
def _make_forward(method_name: str) -> Callable[[Any], None]:
def _forward(item: Any) -> None:
self._forward(method_name, item)
return _forward
value._wire(_make_forward(method))
def _forward(self, method: str, item: Any) -> None:
"""Inject a ProtocolEvent for a StreamChannel push.
Forwarded events bypass the transformer pipeline to avoid
infinite recursion (a transformer that pushes to a channel
during `process()` would re-trigger itself). These events are
visible in this mux's main event log but are not passed through
transformers' `process()` methods. Only the root mux assigns
`seq` to forwarded channel events.
Args:
method: The full protocol method (already with or without
the `custom:` prefix; resolved by `_bind_and_wire`).
item: The payload pushed onto the channel.
"""
event: ProtocolEvent = {
"type": "event",
"method": method,
"params": {
"namespace": [],
"timestamp": int(time.time() * 1000),
"data": item,
},
}
if self._assign_seq:
self._seq += 1
event["seq"] = self._seq
self._events.push(event)
@@ -0,0 +1,313 @@
from __future__ import annotations
import asyncio
import logging
from abc import ABC, abstractmethod
from collections.abc import Coroutine
from typing import Any, ClassVar, Literal
from typing_extensions import NotRequired, TypedDict
_logger = logging.getLogger(__name__)
class _ProtocolEventParams(TypedDict):
"""Parameters for a protocol event.
`timestamp` is wall-clock milliseconds since the epoch and can go
backwards across NTP adjustments — use `ProtocolEvent.seq` for
ordering.
"""
namespace: list[str]
timestamp: int
data: Any
interrupts: NotRequired[tuple[Any, ...]]
class ProtocolEvent(TypedDict):
"""A protocol event emitted by the streaming infrastructure.
Wraps a raw stream part (values, messages, custom, etc.) in a uniform
envelope with a monotonic sequence number assigned by the root StreamMux.
Consumers that need a total order across root events should use `seq`, not
`params.timestamp` (which is wall-clock and not monotonic).
"""
type: Literal["event"]
eventId: NotRequired[str]
seq: NotRequired[int]
method: str # StreamMode value: "values", "messages", "custom", etc.
params: _ProtocolEventParams
class StreamTransformer(ABC):
"""Extension point for custom stream projections.
Transformers observe protocol events flowing through the StreamMux and
build typed derived projections (StreamChannels, promises, etc.).
Set `_native = True` on a transformer to have its projection keys
exposed as direct attributes on the run stream (in addition to
appearing in `run.extensions`).
Subclasses must implement `init` and override at least one of
`process` / `aprocess`. The `finalize` / `afinalize` and `fail` /
`afail` hooks are optional — the default implementations are no-ops.
StreamChannel instances in the projection dict are auto-closed /
auto-failed by the mux, so most transformers don't need `finalize`
or `fail` at all.
Transformers that need async work pick the async lane by:
1. Overriding `aprocess` (and optionally `afinalize` / `afail`), or
2. Calling `self.schedule(coro)` from inside a sync `process`, or
3. Setting `requires_async = True` explicitly.
The mux detects these cases at registration and raises if they're
used under sync `stream()` — they only work under `astream()`.
Use `aprocess` when the pump must wait for async work before the
next transformer sees the event (e.g. PII redaction that mutates
`event` in place). Use `schedule()` for decoupled async work whose
result lands on an independent projection (e.g. async moderation
scoring, cost lookup, external tracing).
Attributes:
scope: Namespace the transformer operates within — `()` for the
root mux. Set at construction from the mux's scope (each
factory is called as `factory(scope)`).
requires_async: Explicit opt-in for transformers that need a
running event loop but don't override any async method (for
example, transformers that call `schedule()` from a sync
`process`). The mux also auto-detects the async lane when
`aprocess`, `afinalize`, or `afail` is overridden.
supports_sync: Set True only for transformers that override
async-lane hooks while still fully supporting the sync lane.
Such transformers may be registered under `stream()`.
required_stream_modes: Stream modes the graph must emit for
this transformer to have anything to process. Computed as
the union across all registered transformers to determine
which modes a `stream_events(version="v3")` run requests from the graph.
Empty tuple means the transformer consumes only synthetic
events (or is purely passive).
"""
requires_async: ClassVar[bool] = False
supports_sync: ClassVar[bool] = False
required_stream_modes: ClassVar[tuple[str, ...]] = ()
def __init__(self, scope: tuple[str, ...] = ()) -> None:
"""Initialize the transformer with its mux's scope.
Args:
scope: The namespace tuple the owning mux is scoped to.
`()` for the root. Factories receive this at
construction time (`factory(scope)` in `StreamMux`).
"""
self.scope: tuple[str, ...] = scope
@abstractmethod
def init(self) -> dict[str, Any]:
"""Return the projection dict.
Keys become entries in `run.extensions`. If the transformer has
`_native = True`, keys are also set as direct attributes on the
run stream.
StreamChannel instances in the return value are automatically
wired by the StreamMux for protocol event auto-forwarding.
"""
...
def _on_register(self, mux: Any) -> None:
"""Called by `StreamMux._register` after this transformer is wired in.
Default is a no-op. Override to capture a reference to the
owning mux — needed for transformers that build mini-muxes
via `mux._make_child(...)` (e.g. `SubgraphTransformer`).
"""
def process(self, event: ProtocolEvent) -> bool:
"""Handle an event on the sync lane.
Called for every event before it is appended to the main event
log. Subclasses must override either `process` or `aprocess`.
The default raises so a missing override fails loudly rather
than silently passing every event through.
Args:
event: The protocol event to observe.
Returns:
True to keep the event in the main log, False to suppress it.
"""
raise NotImplementedError(
f"{type(self).__name__} must override process() or aprocess()"
)
async def aprocess(self, event: ProtocolEvent) -> bool:
"""Handle an event on the async lane.
The mux awaits this before dispatching to the next transformer,
so a slow `aprocess` serializes the pipeline. Use it only when
a later transformer — or a consumer reading the event
synchronously — must see the result of the async work (e.g.
PII redaction that mutates `event` in place).
The default delegates to `process`, so purely-sync transformers
run unchanged under `astream()`.
Args:
event: The protocol event to observe.
Returns:
True to keep the event in the main log, False to suppress it.
"""
return self.process(event)
def finalize(self) -> None:
"""Called when the run ends normally (sync lane).
Override to close StreamChannels, resolve promises, or perform
other teardown. StreamChannel instances in the projection dict
are auto-closed by the mux.
"""
async def afinalize(self) -> None:
"""Called when the run ends normally (async lane).
By the time this runs, the mux has already awaited every task
started via `schedule()`, so StreamChannels can be closed here
without a last-task-wins race.
The default delegates to `finalize`.
"""
self.finalize()
def fail(self, err: BaseException) -> None:
"""Called when the run ends with an error (sync lane).
Override to fail StreamChannels, reject promises, or perform
other teardown. StreamChannel instances in the projection dict
are auto-failed by the mux.
Args:
err: The exception that ended the run.
"""
async def afail(self, err: BaseException) -> None:
"""Called when the run ends with an error (async lane).
The mux cancels and awaits every task started via `schedule()`
before calling this, so cleanup doesn't race with in-flight work.
The default delegates to `fail`.
Args:
err: The exception that ended the run.
"""
self.fail(err)
# ------------------------------------------------------------------
# Scheduled async work
# ------------------------------------------------------------------
def schedule(
self,
coro: Coroutine[Any, Any, Any],
*,
on_error: Literal["log", "raise"] = "log",
) -> asyncio.Task[Any]:
"""Schedule a coroutine tied to this transformer's lifecycle.
The mux holds the task reference, awaits all scheduled tasks
during `aclose()` before calling `afinalize()`, and cancels
them on `afail()`. Authors don't need to track tasks or
implement the last-task-closes-the-log dance.
Requires a running event loop — call only under `astream()`.
Set `requires_async = True` on the class so registration under
sync `stream()` fails fast with a clear message.
Args:
coro: The coroutine to run. Its lifecycle is owned by the
mux from this point on.
on_error: `"log"` (default) catches and logs any exception
the coroutine raises, so a single failure doesn't tear
down the run. `"raise"` lets the exception propagate
when the mux joins pendings, converting the close path
into the fail path.
Returns:
The asyncio Task. Authors rarely need to await it directly
— consumers read results from whatever projection the
coroutine pushes into.
Raises:
RuntimeError: If called without a running event loop (i.e.
under sync `stream()` rather than `astream()`).
"""
try:
asyncio.get_running_loop()
except RuntimeError:
raise RuntimeError(
f"{type(self).__name__}.schedule() requires a running "
"event loop; this transformer must run under astream(), "
"not stream(). Set requires_async=True on the class so "
"this fails at registration rather than at first event."
) from None
wrapped = self._wrap_scheduled(coro) if on_error == "log" else coro
task = asyncio.create_task(wrapped)
tasks = self._scheduled_task_set()
tasks.add(task)
task.add_done_callback(tasks.discard)
return task
@staticmethod
async def _wrap_scheduled(coro: Coroutine[Any, Any, Any]) -> Any:
try:
return await coro
except asyncio.CancelledError:
raise
except BaseException:
_logger.exception("Scheduled StreamTransformer task failed")
def _scheduled_task_set(self) -> set[asyncio.Task[Any]]:
"""Return the lazily-allocated task set.
Avoids requiring subclasses to call `super().__init__()`.
"""
tasks: set[asyncio.Task[Any]] | None = getattr(
self, "_stream_scheduled_tasks", None
)
if tasks is None:
tasks = set()
self._stream_scheduled_tasks = tasks
return tasks
def transformer_requires_async(transformer: StreamTransformer) -> bool:
"""Return True if the transformer needs a running event loop.
A transformer requires async if it explicitly opts in
(`requires_async = True`) or overrides any of the async-lane methods
(`aprocess`, `afinalize`, `afail`) without also declaring that it
supports the sync lane.
Args:
transformer: The transformer to inspect.
Returns:
True if the transformer cannot run under sync `stream()`.
"""
if transformer.requires_async:
return True
if transformer.supports_sync:
return False
cls = type(transformer)
for name in ("aprocess", "afinalize", "afail"):
if getattr(cls, name) is not getattr(StreamTransformer, name):
return True
return False
@@ -0,0 +1,608 @@
from __future__ import annotations
import asyncio
from collections.abc import AsyncIterator, Awaitable, Callable, Iterator, Mapping
from types import MappingProxyType, TracebackType
from typing import TYPE_CHECKING, Any
from langchain_core._api import beta
from langgraph.stream._convert import convert_to_protocol_event
from langgraph.stream._mux import StreamMux
from langgraph.stream._types import ProtocolEvent
if TYPE_CHECKING:
from langgraph.stream.transformers import SubgraphStatus
def _drive_until_done(pump: Callable[[], bool]) -> None:
"""Call the sync pump until it returns False."""
while pump():
pass
async def _adrive_until_done(pump: Callable[[], Awaitable[bool]]) -> None:
"""Call the async pump until it returns False."""
while await pump():
pass
@beta(message="The v3 streaming protocol on Pregel is experimental.")
class GraphRunStream:
"""Sync run stream with caller-driven pumping.
The caller's iteration on any projection (`values`, `messages`,
raw events, or `output`) drives the graph forward. No background
thread is used — the caller's `for` loop is the pump.
Projections are single-consumer — iterating `run.values` twice
raises. Use `projection.tee(n)` if you genuinely need fan-out.
All transformer projections live in `extensions`. Native transformer
projections (those with `_native = True`) are also set as direct
attributes on this instance (e.g. `run.values`, `run.messages`).
!!! warning
Returned by `Pregel.stream_events(version="v3")`, which is
experimental and may change.
"""
def __init__(
self,
graph_iter: Iterator[Any] | None,
mux: StreamMux,
*,
wire_pump: bool = True,
) -> None:
"""Initialize the run stream.
Args:
graph_iter: Pull-based iterator over the graph's stream,
or `None` for nested run streams whose pump is driven
by an outer run (e.g. `SubgraphRunStream`).
mux: The StreamMux owning projections and the main log.
wire_pump: When True (default), bind `_pump_next` as the
mux's pump callable. Subclasses that inherit a parent
pump via `StreamMux._make_child` should pass False to
preserve the parent binding.
"""
self._graph_iter = graph_iter
self._mux = mux
self.extensions: Mapping[str, Any] = MappingProxyType(mux.extensions)
self._exhausted = False
self._latest: dict[str, Any] | None = None
self._interrupted = False
self._interrupts: list[Any] = []
self._scope_list: list[str] = list(mux.scope)
for key in mux.native_keys:
setattr(self, key, mux.extensions[key])
if wire_pump:
self._wire_request_more(mux)
def _wire_request_more(self, mux: StreamMux) -> None:
"""Wire the sync pull callback through the mux.
Routing through `mux.bind_pump` (rather than walking
projections directly here) lets child mini-muxes built by
`mux._make_child(...)` inherit the same pump callable, so
cursors on a subgraph handle's projections drive the root
pump just like cursors on `run.values` do.
"""
mux.bind_pump(self._pump_next)
def _observe_event(self, event: ProtocolEvent) -> None:
"""Track values-event state for output/interrupted/interrupts."""
if event["method"] != "values":
return
params = event["params"]
if params["namespace"] != self._scope_list:
return
self._latest = params["data"]
interrupts = params.get("interrupts", ())
if interrupts:
self._interrupted = True
self._interrupts.extend(interrupts)
def _pump_next(self) -> bool:
"""Pull one event from the graph and push it through the mux.
Returns:
True if an event was pulled, False if the graph is exhausted
or has raised. Always False when constructed with
`graph_iter=None` (the run is driven by an outer pump).
"""
if self._exhausted or self._graph_iter is None:
return False
try:
part = next(self._graph_iter)
event = convert_to_protocol_event(part)
self._observe_event(event)
self._mux.push(event)
return True
except StopIteration:
self._mux.close()
self._exhausted = True
return False
except Exception as e:
self._mux.fail(e)
self._exhausted = True
return False
def abort(self) -> None:
"""Stop the run early.
Closes the mux and marks the stream exhausted. The graph
iterator is dropped; any in-flight nodes see the closure on
their next yield point. Idempotent.
"""
if self._exhausted:
return
self._exhausted = True
try:
self._mux.close()
except Exception:
pass
def __enter__(self) -> GraphRunStream:
return self
def __exit__(
self,
exc_type: type[BaseException] | None,
exc: BaseException | None,
tb: TracebackType | None,
) -> None:
self.abort()
@property
def output(self) -> dict[str, Any] | None:
"""Drive the run to completion and return the final state."""
_drive_until_done(self._pump_next)
if (err := self._mux._events._error) is not None:
raise err
return self._latest
@property
def interrupted(self) -> bool:
"""Drive the run to completion, then return whether it was
interrupted.
Raises:
BaseException: If the run ended with an error.
"""
_drive_until_done(self._pump_next)
if (err := self._mux._events._error) is not None:
raise err
return self._interrupted
@property
def interrupts(self) -> list[Any]:
"""Drive the run to completion, then return interrupt payloads.
Raises:
BaseException: If the run ended with an error.
"""
_drive_until_done(self._pump_next)
if (err := self._mux._events._error) is not None:
raise err
return self._interrupts
def __iter__(self) -> Iterator[ProtocolEvent]:
"""Subscribe to the main event log and iterate protocol events."""
return iter(self._mux._events)
def interleave(self, *names: str) -> Iterator[tuple[str, Any]]:
"""Iterate multiple projections in arrival order, yielding ``(name, item)``.
Items are ordered by a monotonic push stamp assigned when each
transformer pushes into its `StreamChannel`. This gives strict
arrival ordering across projections, unlike round-robin.
Args:
*names: Projection keys to interleave. Must match keys in
``extensions``.
Yields:
``(name, item)`` tuples in arrival order across the named
projections.
Each named channel is locked for the duration of iteration and
released when the generator completes, is closed, or raises.
Channels cannot be subscribed concurrently — use `.tee(n)` if
you need fan-out.
Raises:
KeyError: If a name doesn't match a registered projection.
Example:
```python
for name, item in run.interleave("messages", "values"):
if name == "messages":
print("msg:", item)
else:
print("val:", item)
```
"""
from langgraph.stream.stream_channel import StreamChannel
channels: dict[str, StreamChannel[Any]] = {}
try:
for name in names:
ch = self.extensions[name]
if not isinstance(ch, StreamChannel):
raise TypeError(
f"interleave() requires StreamChannel projections, "
f"got {type(ch).__name__} for {name!r}"
)
if ch._is_async is None:
raise TypeError(
f"StreamChannel {name!r} has not been bound yet. "
"Register the transformer with a StreamMux first."
)
if ch._is_async:
raise TypeError(
f"StreamChannel {name!r} is bound to async mode — "
"sync interleave() cannot consume async channels."
)
if ch._subscribed:
raise RuntimeError(
f"StreamChannel {name!r} already has a subscriber; "
"use .tee(n) for fan-out."
)
ch._subscribed = True
channels[name] = ch
done: set[str] = set()
while len(done) < len(channels):
best: tuple[int, str] | None = None
for name, ch in channels.items():
if name in done:
continue
if ch._closed and not ch._items:
if ch._error is not None:
raise ch._error
done.add(name)
continue
if ch._items:
stamp = ch._items[0][0]
if best is None or stamp < best[0]:
best = (stamp, name)
if best is not None:
_stamp, item = channels[best[1]]._items.popleft()
yield (best[1], item)
else:
pump = self._mux._pump_fn
if pump is None or not pump():
before = len(done)
for name, ch in channels.items():
if name not in done and not ch._items:
if ch._closed:
if ch._error is not None:
raise ch._error
done.add(name)
if len(done) == before:
break
finally:
for ch in channels.values():
ch._subscribed = False
@beta(message="The v3 streaming protocol on Pregel is experimental.")
class AsyncGraphRunStream:
"""Async run stream with caller-driven pumping.
Async iteration on any projection drives the graph forward — there
is no background task. Concurrent consumers share a single-flight
pump via an `asyncio.Lock`, so each awaiting cursor contributes one
event per acquisition. Backpressure comes from the logs: when a
subscribed log's buffer reaches `maxlen`, `apush` awaits the
subscriber to drain, which holds back the pump and paces the graph.
Projections are single-consumer — a second `aiter(run.values)`
raises. Use `projection.tee(n)` for fan-out.
Use as an async context manager to guarantee clean shutdown on
early exit:
```python
async with await handler.astream(input) as run:
async for msg in run.messages:
...
```
!!! warning
Awaited from `Pregel.astream_events(version="v3")`, which is
experimental and may change.
"""
def __init__(
self,
graph_aiter: AsyncIterator[Any] | None,
mux: StreamMux,
*,
wire_pump: bool = True,
) -> None:
"""Initialize the async run stream.
Args:
graph_aiter: Async iterator over the graph's stream, or
`None` for nested run streams whose pump is driven by
an outer run (e.g. `AsyncSubgraphRunStream`).
mux: The StreamMux owning projections and the main log.
wire_pump: When True (default), bind `_apump_next` as the
mux's async pump callable. Subclasses that inherit a
parent pump via `StreamMux._make_child` should pass
False to preserve the parent binding.
"""
self._graph_aiter = graph_aiter
self._mux = mux
self.extensions: Mapping[str, Any] = MappingProxyType(mux.extensions)
self._exhausted = False
self._latest: dict[str, Any] | None = None
self._interrupted = False
self._interrupts: list[Any] = []
self._scope_list: list[str] = list(mux.scope)
self._pump_cond = asyncio.Condition()
self._pumping = False
for key in mux.native_keys:
setattr(self, key, mux.extensions[key])
if wire_pump:
self._wire_arequest_more(mux)
def _observe_event(self, event: ProtocolEvent) -> None:
"""Track values-event state for output/interrupted/interrupts."""
if event["method"] != "values":
return
params = event["params"]
if params["namespace"] != self._scope_list:
return
self._latest = params["data"]
interrupts = params.get("interrupts", ())
if interrupts:
self._interrupted = True
self._interrupts.extend(interrupts)
def _wire_arequest_more(self, mux: StreamMux) -> None:
"""Wire the async pull callback through the mux.
Mirrors `_wire_request_more`: routing through
`mux.bind_apump` lets child mini-muxes inherit the pump
callable so cursors on subgraph handles drive the root
pump.
"""
mux.bind_apump(self._apump_next)
async def _apump_next(self) -> bool:
"""Drive one pump step, or wait for the active pumper to drive one.
"Take-a-number" semantics: at most one task at a time calls
`graph_aiter.__anext__()` (asyncio iterators can't be advanced
concurrently). Other callers wait on a Condition that the
active pumper notifies after each step. This lets a "passive"
consumer — one whose projection's buffer is being filled by the
active pumper's push — wake up as soon as its data lands,
instead of queueing on the pump and only observing its data one
graph event late.
`except Exception` is intentional — `CancelledError` and other
`BaseException` subclasses propagate, matching asyncio's
cancellation contract.
Returns:
True if a pump step completed (by this task or another),
False if the graph is exhausted.
"""
async with self._pump_cond:
if self._exhausted or self._graph_aiter is None:
return False
if self._pumping:
# Another task is pumping; wait for its progress signal.
await self._pump_cond.wait()
return not self._exhausted
self._pumping = True
try:
try:
part = await self._graph_aiter.__anext__()
event = convert_to_protocol_event(part)
self._observe_event(event)
await self._mux.apush(event)
return True
except StopAsyncIteration:
self._exhausted = True
await self._mux.aclose()
return False
except Exception as e:
self._exhausted = True
await self._mux.afail(e)
return False
finally:
async with self._pump_cond:
self._pumping = False
self._pump_cond.notify_all()
async def abort(self) -> None:
"""Stop the run early.
Marks the stream exhausted, wakes any pump-waiters, and closes
the mux. Any `apush` blocked on backpressure wakes and returns
without appending. Idempotent.
"""
async with self._pump_cond:
if self._exhausted:
return
self._exhausted = True
self._pump_cond.notify_all()
try:
await self._mux.aclose()
except Exception:
pass
async def __aenter__(self) -> AsyncGraphRunStream:
return self
async def __aexit__(
self,
exc_type: type[BaseException] | None,
exc: BaseException | None,
tb: TracebackType | None,
) -> None:
await self.abort()
async def output(self) -> dict[str, Any] | None:
"""Drive the run to completion and return the final state.
Methods (not properties) on the async lane so `run.output`
without `await` raises at type-check time instead of silently
yielding a coroutine object.
Example:
```python
output = await run.output()
```
Raises:
BaseException: If the run ended with an error.
"""
await _adrive_until_done(self._apump_next)
if (err := self._mux._events._error) is not None:
raise err
return self._latest
async def interrupted(self) -> bool:
"""Drive the run to completion and return whether it was
interrupted.
Raises:
BaseException: If the run ended with an error.
"""
await _adrive_until_done(self._apump_next)
if (err := self._mux._events._error) is not None:
raise err
return self._interrupted
async def interrupts(self) -> list[Any]:
"""Drive the run to completion and return interrupt payloads.
Raises:
BaseException: If the run ended with an error.
"""
await _adrive_until_done(self._apump_next)
if (err := self._mux._events._error) is not None:
raise err
return self._interrupts
def __aiter__(self) -> AsyncIterator[ProtocolEvent]:
"""Subscribe to the main event log and iterate protocol events."""
return self._mux._events.__aiter__()
class _SubgraphRunStreamMixin:
"""Subgraph metadata + parent-pump delegation shared by both lanes.
Inherits from `GraphRunStream` (or `AsyncGraphRunStream`) with
`graph_iter=None` + `wire_pump=False` — the mini-mux is driven
by the parent's pump (inherited via `StreamMux._make_child`), and
the handle never pulls upstream itself. Pump-driving methods
delegate to the parent pump so `handle.output` and friends drive
the root run.
Subclasses set the parent pump function captured at construction
(`_parent_pump_fn` / `_parent_apump_fn`) and override
`_pump_next` / `_apump_next` to delegate to it.
Status is updated in place by `SubgraphTransformer`. Iterate
`run.subgraphs` to receive handles as subgraphs spawn, then
drill into projections inside the loop body **before** the next
pump cycle — same lazy-subscribe constraint as root projections.
"""
path: tuple[str, ...]
graph_name: str | None
trigger_call_id: str | None
status: SubgraphStatus
error: str | None
_seen_terminal: bool
class SubgraphRunStream(GraphRunStream, _SubgraphRunStreamMixin):
"""Sync handle for a discovered subgraph (extends `GraphRunStream`)."""
def __init__(
self,
mux: StreamMux,
*,
path: tuple[str, ...],
graph_name: str | None = None,
trigger_call_id: str | None = None,
) -> None:
# Capture the parent-inherited pump before super().__init__
# touches anything; we delegate to it from `_pump_next`.
self._parent_pump_fn: Callable[[], bool] | None = mux._pump_fn
super().__init__(
graph_iter=None,
mux=mux,
wire_pump=False,
)
self.path = path
self.graph_name = graph_name
self.trigger_call_id = trigger_call_id
self.status = "started"
self.error = None
self._seen_terminal = False
def _pump_next(self) -> bool:
"""Delegate to the parent's pump.
Cursors on this handle's projections call here when their
buffers empty. Driving the parent fans events into our
mini-mux, transparently advancing the whole run.
"""
if (
self._exhausted
or self._seen_terminal
or self._mux._events._closed
or self._parent_pump_fn is None
):
return False
return self._parent_pump_fn()
class AsyncSubgraphRunStream(AsyncGraphRunStream, _SubgraphRunStreamMixin):
"""Async handle for a discovered subgraph (extends `AsyncGraphRunStream`)."""
def __init__(
self,
mux: StreamMux,
*,
path: tuple[str, ...],
graph_name: str | None = None,
trigger_call_id: str | None = None,
) -> None:
self._parent_apump_fn: Callable[[], Awaitable[bool]] | None = mux._apump_fn
super().__init__(
graph_aiter=None,
mux=mux,
wire_pump=False,
)
self.path = path
self.graph_name = graph_name
self.trigger_call_id = trigger_call_id
self.status = "started"
self.error = None
self._seen_terminal = False
async def _apump_next(self) -> bool:
"""Delegate to the parent's async pump."""
if (
self._exhausted
or self._seen_terminal
or self._mux._events._closed
or self._parent_apump_fn is None
):
return False
return await self._parent_apump_fn()
@@ -0,0 +1,341 @@
from __future__ import annotations
import asyncio
from collections import deque
from collections.abc import AsyncIterator, Awaitable, Callable, Iterator
from typing import TYPE_CHECKING, Generic, TypeVar
if TYPE_CHECKING:
from langgraph.stream._mux import StreamMux
T = TypeVar("T")
class StreamChannel(Generic[T]):
"""Single-consumer drainable queue for streaming events, with optional
protocol auto-forwarding.
When constructed with a `name`, the StreamMux auto-wires every
`push()` to also inject a `ProtocolEvent` into the main event stream
using the channel's name as the method. When constructed without a
name, the channel is local-only — items are only visible to
in-process consumers that iterate the channel directly.
Items are popped off the front as the consumer advances — there is
no retention beyond what's currently queued. A channel accepts
exactly one subscriber; a second `__iter__` / `__aiter__` call
raises. Use `tee(n)` / `atee(n)` for fan-out.
Starts unbound — neither `__iter__` nor `__aiter__` is available
until the StreamMux calls `_bind(is_async)`. After binding, only
the matching iteration protocol works; the other raises `TypeError`.
Pump wiring (set by the run stream, not by `_bind`):
- `_request_more`: sync pump callable, returns True if a new
event was produced.
- `_arequest_more`: async pump coroutine factory, same contract.
Memory is bounded by caller pace: both sync and async use caller-
driven pumps, so each cursor advance produces at most one event.
Lazy-subscribe: `push` appends to the local buffer only when a
subscriber has registered. Auto-forward via `_wire_fn` always fires
regardless of subscription state.
Lifecycle (`close` / `fail`) is managed by the mux — transformers
don't need to close their channels manually.
"""
def __init__(self, name: str | None = None, *, maxlen: int | None = None) -> None:
"""Initialize the channel.
Args:
name: Optional protocol channel name. When set, the
StreamMux wires every `push()` to also inject a
`ProtocolEvent` into the main event stream. Surfaced
on the wire as `custom:<name>` for user-defined
transformers, or as `<name>` for channels owned by a
native transformer (`_native = True`). When `None`,
the channel is local-only.
maxlen: Accepted for forward compatibility; currently
unused. The caller-driven pump bounds memory naturally
for single-consumer use.
Raises:
ValueError: If `maxlen` is not a positive integer or `None`.
"""
if maxlen is not None and maxlen <= 0:
raise ValueError("StreamChannel maxlen must be a positive int or None")
self.name = name
self._items: deque[tuple[int, T]] = deque()
self._maxlen: int | None = maxlen
self._closed = False
self._error: BaseException | None = None
self._is_async: bool | None = None
self._subscribed = False
self._request_more: Callable[[], bool] | None = None
self._arequest_more: Callable[[], Awaitable[bool]] | None = None
self._wire_fn: Callable[[T], None] | None = None
self._mux: StreamMux | None = None
# ------------------------------------------------------------------
# Binding
# ------------------------------------------------------------------
def _bind_mux(self, mux: StreamMux) -> None:
self._mux = mux
def _bind(self, *, is_async: bool) -> None:
"""Bind this channel to sync or async mode.
Called by the StreamMux after transformer registration. Must be
called exactly once before any iteration.
Args:
is_async: True to enable async iteration, False for sync.
Raises:
RuntimeError: If the channel has already been bound.
"""
if self._is_async is not None:
raise RuntimeError("StreamChannel is already bound")
self._is_async = is_async
# ------------------------------------------------------------------
# Mux wiring (not called by transformers directly)
# ------------------------------------------------------------------
def _wire(self, fn: Callable[[T], None]) -> None:
"""Install the auto-forward callback (called by StreamMux)."""
self._wire_fn = fn
# ------------------------------------------------------------------
# Producer API
# ------------------------------------------------------------------
def push(self, item: T) -> None:
"""Append an item. Auto-forwards if wired.
The local buffer append is a no-op when no subscriber is
registered, but auto-forwarding always fires so wired events
reach the main event log regardless of subscription state.
Items are stored as `(stamp, item)` tuples where stamp is a
monotonic counter from the owning mux. Stamps are stripped by
the default cursors; raw stamped tuples are visible on `_items`.
Raises:
RuntimeError: If the channel is closed (and subscribed).
"""
if self._subscribed:
if self._closed:
raise RuntimeError("Cannot push to a closed StreamChannel")
stamp = self._mux._next_push_seq() if self._mux is not None else 0
self._items.append((stamp, item))
if self._wire_fn is not None:
self._wire_fn(item)
def close(self) -> None:
"""Mark the channel as complete."""
self._closed = True
def fail(self, err: BaseException) -> None:
"""Mark the channel as errored.
Args:
err: The exception to surface to the subscriber.
"""
self._error = err
self._closed = True
# ------------------------------------------------------------------
# Sync iteration (caller-driven pump)
# ------------------------------------------------------------------
def __iter__(self) -> Iterator[T]:
"""Subscribe and return a sync cursor. Can be called only once.
Raises:
TypeError: If the channel is unbound or bound to async mode.
RuntimeError: If the channel already has a subscriber.
"""
if self._is_async is None:
raise TypeError(
"StreamChannel has not been bound yet. "
"Register the transformer with a StreamMux first."
)
if self._is_async:
raise TypeError(
"This StreamChannel is bound to async mode — use 'async for' instead."
)
if self._subscribed:
raise RuntimeError(
"StreamChannel already has a subscriber; use .tee(n) for fan-out."
)
self._subscribed = True
return self._sync_cursor()
def _sync_cursor(self) -> Iterator[T]:
while True:
if self._items:
_stamp, item = self._items.popleft()
yield item
elif self._closed:
if self._error is not None:
raise self._error
return
elif self._request_more is not None:
if not self._request_more():
if not self._items and not self._closed:
return
else:
return
# ------------------------------------------------------------------
# Async iteration (caller-driven pump)
# ------------------------------------------------------------------
def __aiter__(self) -> AsyncIterator[T]:
"""Subscribe and return an async cursor. Can be called only once.
Raises:
TypeError: If the channel is unbound or bound to sync mode.
RuntimeError: If the channel already has a subscriber.
"""
if self._is_async is None:
raise TypeError(
"StreamChannel has not been bound yet. "
"Register the transformer with a StreamMux first."
)
if not self._is_async:
raise TypeError(
"This StreamChannel is bound to sync mode — use 'for' instead."
)
if self._subscribed:
raise RuntimeError(
"StreamChannel already has a subscriber; use .atee(n) for fan-out."
)
self._subscribed = True
return self._async_cursor()
async def _async_cursor(self) -> AsyncIterator[T]:
while True:
if self._items:
_stamp, item = self._items.popleft()
yield item
elif self._closed:
if self._error is not None:
raise self._error
return
elif self._arequest_more is not None:
if not await self._arequest_more():
if not self._items and not self._closed:
return
else:
return
# ------------------------------------------------------------------
# Fan-out via tee
# ------------------------------------------------------------------
def tee(self, n: int = 2) -> tuple[Iterator[T], ...]:
"""Subscribe and return `n` independent sync iterators.
Each branch has its own buffer; items pulled from the
underlying cursor are copied into every branch. Branches are
naturally bounded by caller pace since the sync pump is
caller-driven.
Args:
n: Number of branches to create. Must be >= 1.
Returns:
A tuple of `n` iterators over the same underlying stream.
Raises:
TypeError: If the channel is unbound or bound to async mode.
RuntimeError: If the channel already has a subscriber.
ValueError: If `n` < 1.
"""
if n < 1:
raise ValueError("tee() requires n >= 1")
source = self.__iter__()
buffers: list[deque[T]] = [deque() for _ in range(n)]
exhausted = [False]
def branch(i: int) -> Iterator[T]:
buf = buffers[i]
while True:
if buf:
yield buf.popleft()
elif exhausted[0]:
return
else:
try:
item = next(source)
except StopIteration:
exhausted[0] = True
return
for b in buffers:
b.append(item)
return tuple(branch(i) for i in range(n))
def atee(self, n: int = 2) -> tuple[AsyncIterator[T], ...]:
"""Subscribe and return `n` independent async iterators.
Caller-driven fan-out: each branch's `__anext__` either pops
from its own buffer or, under a shared `asyncio.Lock`, pulls
one item from the underlying cursor and distributes it to
every branch's buffer.
Args:
n: Number of branches to create. Must be >= 1.
Returns:
A tuple of `n` async iterators over the same underlying
stream.
Raises:
TypeError: If the channel is unbound or bound to sync mode.
RuntimeError: If the channel already has a subscriber.
ValueError: If `n` < 1.
"""
if n < 1:
raise ValueError("atee() requires n >= 1")
source = self.__aiter__()
buffers: list[deque[T]] = [deque() for _ in range(n)]
exhausted = [False]
error: list[BaseException | None] = [None]
lock = asyncio.Lock()
async def branch(i: int) -> AsyncIterator[T]:
buf = buffers[i]
while True:
if buf:
yield buf.popleft()
continue
if exhausted[0]:
if error[0] is not None:
raise error[0]
return
async with lock:
if buf or exhausted[0]:
continue
try:
item = await source.__anext__()
except StopAsyncIteration:
exhausted[0] = True
continue
except Exception as e:
error[0] = e
exhausted[0] = True
continue
for b in buffers:
b.append(item)
return tuple(branch(i) for i in range(n))
@@ -0,0 +1,928 @@
from __future__ import annotations
import logging
from typing import TYPE_CHECKING, Any, Literal, cast
from langchain_core.language_models._compat_bridge import message_to_events
from langchain_core.language_models.chat_model_stream import (
AsyncChatModelStream,
ChatModelStream,
)
from langchain_core.messages import AIMessageChunk, BaseMessage
from langchain_protocol.protocol import MessagesData
from typing_extensions import NotRequired, TypedDict
from langgraph.errors import GraphDrained, GraphInterrupt
from langgraph.stream._types import ProtocolEvent, StreamTransformer
from langgraph.stream.run_stream import AsyncSubgraphRunStream, SubgraphRunStream
from langgraph.stream.stream_channel import StreamChannel
if TYPE_CHECKING:
from collections.abc import Awaitable, Callable
from langgraph.stream._mux import StreamMux
_logger = logging.getLogger(__name__)
class ValuesTransformer(StreamTransformer):
"""Capture values events as a drainable stream of state snapshots.
Provides the `run.values` projection. `run.output`,
`run.interrupted` and `run.interrupts` are tracked directly
by the run stream and do not depend on this transformer.
Native transformer — projection keys are exposed as direct
attributes on the run stream (e.g. `run.values`).
Only values events at the run's own level are captured; snapshots
from deeper subgraphs are left in the main event log but excluded
from the projection. "Own level" is defined by `scope`, which
`stream_events(version="v3")` / `astream_events(version="v3")` populate from the caller's
checkpoint namespace so that a nested `stream_events(version="v3")` call still
sees its own root snapshots.
"""
_native = True
required_stream_modes = ("values",)
def __init__(self, scope: tuple[str, ...] = ()) -> None:
super().__init__(scope)
self._log: StreamChannel[dict[str, Any]] = StreamChannel()
self._latest: dict[str, Any] | None = None
self._interrupted = False
self._interrupts: list[Any] = []
# Cached as a list once for cheap equality with the protocol
# event's `namespace` field, which is `list[str]`.
self._scope_list: list[str] = list(scope)
def init(self) -> dict[str, Any]:
return {"values": self._log}
@property
def error(self) -> BaseException | None:
"""The error that ended the run, or `None` if it succeeded.
Set by the mux when it auto-fails the projection log.
"""
return self._log._error
def process(self, event: ProtocolEvent) -> bool:
if event["method"] != "values":
return True
params = event["params"]
if params["namespace"] != self._scope_list:
return True
self._latest = params["data"]
interrupts = params.get("interrupts", ())
if interrupts:
self._interrupted = True
self._interrupts.extend(interrupts)
self._log.push(params["data"])
return True
class CustomTransformer(StreamTransformer):
"""Capture custom events as a drainable stream of arbitrary payloads.
Nodes emit custom data via `get_stream_writer()`. This transformer
surfaces those events on `run.custom` as a `StreamChannel[Any]`,
preserving payloads in arrival order.
Only events at the run's own scope are captured; custom data from
deeper subgraphs is available on the respective subgraph handle's
`.custom` projection.
Native transformer — `run.custom` is a direct attribute.
"""
_native = True
required_stream_modes = ("custom",)
def __init__(self, scope: tuple[str, ...] = ()) -> None:
super().__init__(scope)
self._log: StreamChannel[Any] = StreamChannel()
self._scope_list: list[str] = list(scope)
def init(self) -> dict[str, Any]:
return {"custom": self._log}
def process(self, event: ProtocolEvent) -> bool:
if event["method"] != "custom":
return True
params = event["params"]
if params["namespace"] != self._scope_list:
return True
self._log.push(params["data"])
return True
class UpdatesTransformer(StreamTransformer):
"""Capture updates events as a drainable stream of node outputs.
Surfaces `stream_mode="updates"` data on `run.updates` as a
`StreamChannel[dict[str, Any]]`. Each item is a dict mapping a node
(or task) name to the update it returned after a step.
Only events at the run's own scope are captured; updates from deeper
subgraphs are available on the respective subgraph handle's
`.updates` projection.
Native transformer — `run.updates` is a direct attribute.
"""
_native = True
required_stream_modes = ("updates",)
def __init__(self, scope: tuple[str, ...] = ()) -> None:
super().__init__(scope)
self._log: StreamChannel[dict[str, Any]] = StreamChannel()
self._scope_list: list[str] = list(scope)
def init(self) -> dict[str, Any]:
return {"updates": self._log}
def process(self, event: ProtocolEvent) -> bool:
if event["method"] != "updates":
return True
params = event["params"]
if params["namespace"] != self._scope_list:
return True
self._log.push(params["data"])
return True
class MessagesTransformer(StreamTransformer):
"""Capture messages events as ChatModelStream objects.
The messages projection yields one `ChatModelStream` (or
`AsyncChatModelStream`) per LLM call. Consumers iterate
`run.messages` to get stream handles, then use each handle's typed
projections (`.text`, `.reasoning`, `.tool_calls`, `.usage`,
`.output`) for per-message content.
Two input shapes are handled (via `params["data"] = (payload,
metadata)` from `StreamMessagesHandler`):
1. Protocol event (dict with `"event"` key) — emitted by
`stream_events(version="v3")` / `astream_events(version="v3")` via the `on_stream_event`
callback. Routed to an existing `ChatModelStream` by
`metadata["run_id"]`. A `message-start` event creates a new
stream; `message-finish` closes it.
2. Whole `AIMessage` — emitted from `on_chain_end` when a node
returns a finalized message. Replayed as a synthetic protocol
event lifecycle via `message_to_events`, then the
already-complete stream is pushed to the log.
V1 `AIMessageChunk` tuples (from `on_llm_new_token`) are not
streamed into this projection: chat models that want to populate
`run.messages` with content-block streaming must use
`stream_events(version="v3")` / `astream_events(version="v3")`. Models called via the legacy
`stream()` method still surface their final `AIMessage` via
`on_chain_end` when a node returns it as state.
Only events at the run's own level are projected; tokens from
deeper subgraphs are left in the main event log but excluded from
`.messages`. "Own level" is defined by `scope`, which
`stream_events(version="v3")` / `astream_events(version="v3")` populate from the caller's checkpoint
namespace so that a `stream_events(version="v3")` call inside a node still sees its
own root chat model streams on `.messages`. Consumers that need
subgraph tokens should iterate the raw event stream or register a
custom transformer.
Native transformer — the `messages` projection is exposed as a
direct attribute on the run stream.
"""
_native = True
required_stream_modes = ("messages",)
def __init__(self, scope: tuple[str, ...] = ()) -> None:
super().__init__(scope)
self._log: StreamChannel[ChatModelStream] = StreamChannel()
# Correlate protocol events back to a ChatModelStream by run_id
# (attached to the event's metadata by StreamMessagesHandler).
self._by_run: dict[str, ChatModelStream] = {}
self._pump_fn: Callable[[], bool] | None = None
self._apump_fn: Callable[[], Awaitable[bool]] | None = None
# Cached as a list once for cheap equality with the protocol
# event's `namespace` field, which is `list[str]`.
self._scope_list: list[str] = list(scope)
def init(self) -> dict[str, Any]:
return {"messages": self._log}
def _bind_pump(self, fn: Callable[[], bool]) -> None:
"""Wire the sync pull callback. Called by GraphRunStream._wire_request_more."""
self._pump_fn = fn
def _bind_apump(self, fn: Callable[[], Awaitable[bool]]) -> None:
"""Wire the async pull callback.
Called by `AsyncGraphRunStream._wire_arequest_more` so each
`AsyncChatModelStream` this transformer creates can drive the
shared graph pump from its projection cursors.
"""
self._apump_fn = fn
def _make_stream(
self,
*,
namespace: list[str],
node: str | None,
message_id: str | None,
) -> ChatModelStream:
"""Create a ChatModelStream (sync) or AsyncChatModelStream (async).
Wires whichever pump is bound. Prefers the async pump so nested
iteration under `AsyncGraphRunStream` drives the graph forward
without a background task. The unwired fallback (no pump bound)
is used by unit tests that dispatch events manually.
"""
if self._apump_fn is not None:
astream = AsyncChatModelStream(
namespace=namespace,
node=node,
message_id=message_id,
)
astream.set_arequest_more(self._apump_fn)
return astream
if self._pump_fn is not None:
stream: ChatModelStream = ChatModelStream(
namespace=namespace,
node=node,
message_id=message_id,
)
stream.set_request_more(self._pump_fn)
return stream
return AsyncChatModelStream(
namespace=namespace,
node=node,
message_id=message_id,
)
def process(self, event: ProtocolEvent) -> bool:
if event["method"] != "messages":
return True
params = event["params"]
if params["namespace"] != self._scope_list:
return True
payload, metadata = params["data"]
node: str | None = metadata.get("langgraph_node")
run_id = str(metadata.get("run_id", "")) if metadata else ""
if isinstance(payload, dict) and "event" in payload:
self._route_protocol_event(
cast("MessagesData", payload), run_id=run_id, node=node
)
elif isinstance(payload, BaseMessage) and not isinstance(
payload, AIMessageChunk
):
self._route_whole_message(payload, node=node)
# Legacy AIMessageChunk tuples (from on_llm_new_token) are ignored;
# v1 streaming callers must switch to stream_events(version="v3") to populate this
# projection.
return True
def _route_protocol_event(
self,
event: MessagesData,
*,
run_id: str,
node: str | None,
) -> None:
event_type = event.get("event")
if event_type == "message-start":
message_id = event.get("message_id")
stream = self._make_stream(
namespace=[],
node=node,
message_id=str(message_id) if message_id is not None else None,
)
self._by_run[run_id] = stream
self._log.push(stream)
stream.dispatch(event)
elif run_id in self._by_run:
stream = self._by_run[run_id]
stream.dispatch(event)
if event_type == "message-finish":
del self._by_run[run_id]
def _route_whole_message(self, message: BaseMessage, *, node: str | None) -> None:
stream = self._make_stream(namespace=[], node=node, message_id=message.id)
for evt in message_to_events(message, message_id=message.id):
stream.dispatch(evt)
self._log.push(stream)
def finalize(self) -> None:
"""Clear any routing state — streams close themselves via `message-finish`."""
self._by_run.clear()
def fail(self, err: BaseException) -> None:
"""Propagate run error to any streams still open when the graph fails."""
for stream in list(self._by_run.values()):
stream.fail(err)
self._by_run.clear()
SubgraphStatus = Literal["started", "completed", "failed", "interrupted", "drained"]
def _parse_ns_segment(segment: str) -> tuple[str, str | None]:
"""Split a namespace segment into `(graph_name, trigger_call_id)`.
Segments are formatted `node_name:task_id` by `prepare_next_tasks`.
Returns `(segment, None)` if no `:` is present.
"""
name, sep, task_id = segment.partition(":")
return name, task_id if sep else None
class LifecyclePayload(TypedDict, total=False):
"""Payload of a lifecycle event surfaced on the `lifecycle` channel.
Auto-forwarded as `lifecycle` protocol events (no `custom:` prefix
because `LifecycleTransformer` is a native transformer) so remote
SDK clients receive the same data in-process consumers see via
`run.lifecycle`.
"""
event: SubgraphStatus
namespace: list[str]
graph_name: NotRequired[str]
trigger_call_id: NotRequired[str]
error: NotRequired[str]
class _TasksLifecycleBase(StreamTransformer):
"""Shared bookkeeping for `tasks`-event-driven lifecycle inference.
Both `LifecycleTransformer` (wire-serializable channel) and
`SubgraphTransformer` (in-process navigation handles) discover
subgraphs by watching the same `tasks` stream — `started` on the
first event at a tracked namespace, terminal status when the
parent's `TaskResultPayload` arrives. Centralizing the dispatch
+ open-set bookkeeping here keeps the inference rules from
drifting between the two surfaces.
Subclasses provide three template-method hooks:
- `_should_track(ns)` — scope filter (e.g. multi-depth vs
direct-children-only).
- `_on_started(ns, graph_name, trigger_call_id)` — first sighting
action (push payload / build handle / etc.). Called once per
discovered namespace.
- `_on_terminal(ns, status, error)` — terminal action (push
terminal payload / mark handle status). Called once per
tracked namespace at result time, or via `finalize` / `fail`
sweeps if no parent result arrived.
Tasks events are suppressed from the main event log (`process`
returns False) — they're folded into whichever projection the
subclass populates; consumers iterating the raw protocol stream
see the higher-level view.
"""
required_stream_modes = ("tasks",)
def __init__(self, scope: tuple[str, ...] = ()) -> None:
super().__init__(scope)
self._seen: set[tuple[str, ...]] = set()
# Maps tracked namespace -> task_id of the parent task whose
# `TaskResultPayload` will close it.
self._open: dict[tuple[str, ...], str] = {}
# --- Template-method hooks (subclass overrides) ---
def _should_track(self, ns: tuple[str, ...]) -> bool:
"""Scope filter — return True iff `ns` is in this transformer's region."""
raise NotImplementedError
def _on_started(
self,
ns: tuple[str, ...],
graph_name: str | None,
trigger_call_id: str | None,
) -> None:
"""Fired once per discovered namespace (first observed task event)."""
raise NotImplementedError
def _on_terminal(
self,
ns: tuple[str, ...],
status: SubgraphStatus,
error: str | None,
) -> None:
"""Fired once per tracked namespace when its parent's result arrives,
or via finalize/fail safety-net sweeps.
"""
raise NotImplementedError
# --- Dispatch + bookkeeping (shared) ---
def process(self, event: ProtocolEvent) -> bool:
if event["method"] != "tasks":
return True
ns = tuple(event["params"]["namespace"])
data = event["params"]["data"]
if "result" in data:
self._handle_task_result(ns, data)
else:
self._handle_task_start(ns)
# Tasks events are folded into the synthesized projections;
# suppress from the main event log so iterators don't double-see
# the same information in two shapes.
return False
def _handle_task_start(self, ns: tuple[str, ...]) -> None:
if not self._should_track(ns) or ns in self._seen:
return
self._seen.add(ns)
graph_name, trigger_call_id = _parse_ns_segment(ns[-1])
self._on_started(ns, graph_name or None, trigger_call_id)
if trigger_call_id is not None:
self._open[ns] = trigger_call_id
def _pop_terminal_transitions(
self, ns: tuple[str, ...], data: dict[str, Any]
) -> list[tuple[tuple[str, ...], SubgraphStatus, str | None]]:
"""Return and remove tracked children closed by this task result."""
result_id = data.get("id")
if not result_id:
return []
transitions: list[tuple[tuple[str, ...], SubgraphStatus, str | None]] = []
for child_ns, parent_task_id in list(self._open.items()):
if child_ns[:-1] != ns or parent_task_id != result_id:
continue
status, error = _terminal_from_result(data)
transitions.append((child_ns, status, error))
del self._open[child_ns]
return transitions
def _handle_task_result(self, ns: tuple[str, ...], data: dict[str, Any]) -> None:
for child_ns, status, error in self._pop_terminal_transitions(ns, data):
self._on_terminal(child_ns, status, error)
def finalize(self) -> None:
"""Emit `completed` for any tracked namespace still open at run end."""
for ns in list(self._open):
self._on_terminal(ns, "completed", None)
self._open.clear()
def fail(self, err: BaseException) -> None:
"""Emit terminal status for any tracked namespace still open."""
status, error_str = _status_from_exception(err)
for ns in list(self._open):
self._on_terminal(ns, status, error_str)
self._open.clear()
def _status_from_exception(err: BaseException) -> tuple[SubgraphStatus, str | None]:
"""Map a run exception to a subgraph terminal status and error string."""
if isinstance(err, GraphDrained):
return "drained", None
if isinstance(err, GraphInterrupt):
return "interrupted", None
return "failed", str(err)
def _terminal_from_result(
payload: dict[str, Any],
) -> tuple[SubgraphStatus, str | None]:
"""Map a `TaskResultPayload` to a `(status, error)` pair.
Order matters: a result with both `error` and `interrupts` prefers
the interrupt classification, since `GraphInterrupt` manifests as
a populated `interrupts` list, not as `error`.
"""
if payload.get("interrupts"):
return "interrupted", None
error = payload.get("error")
if error:
return "failed", str(error)
return "completed", None
class LifecycleTransformer(_TasksLifecycleBase):
"""Surface subgraph lifecycle as `lifecycle` protocol events.
Pushes `LifecyclePayload` to a `StreamChannel` named `lifecycle`.
The channel is auto-forwarded by the mux so payloads land in the
main event log under `method = "lifecycle"` (native transformer —
no `custom:` prefix) — visible to remote SDK clients over the
wire and to in-process consumers via `run.lifecycle`.
Tracks subgraphs at every depth strictly below the transformer's
scope, so a graph → subgraph → subgraph chain produces lifecycle
events for both nested levels in a flat stream.
Native transformer — projection key `lifecycle` is exposed as
`run.lifecycle`.
"""
_native = True
def __init__(self, scope: tuple[str, ...] = ()) -> None:
super().__init__(scope)
self._channel: StreamChannel[LifecyclePayload] = StreamChannel("lifecycle")
def init(self) -> dict[str, Any]:
return {"lifecycle": self._channel}
def _should_track(self, ns: tuple[str, ...]) -> bool:
depth = len(self.scope)
return len(ns) > depth and ns[:depth] == self.scope
def _on_started(
self,
ns: tuple[str, ...],
graph_name: str | None,
trigger_call_id: str | None,
) -> None:
if trigger_call_id is None:
# Without a task id we can't correlate a parent-result
# event back to this namespace — skip the started payload
# and rely on finalize/fail to close.
return
payload: LifecyclePayload = {"event": "started", "namespace": list(ns)}
if graph_name:
payload["graph_name"] = graph_name
payload["trigger_call_id"] = trigger_call_id
self._channel.push(payload)
def _on_terminal(
self,
ns: tuple[str, ...],
status: SubgraphStatus,
error: str | None,
) -> None:
payload: LifecyclePayload = {"event": status, "namespace": list(ns)}
if error is not None:
payload["error"] = error
self._channel.push(payload)
class SubgraphTransformer(_TasksLifecycleBase):
"""Discover subgraph invocations as in-process navigation handles.
Per discovered direct-child subgraph, builds a `SubgraphRunStream`
(or `AsyncSubgraphRunStream`) wrapping a child mini-mux scoped to
the subgraph's namespace. Consumers iterate `run.subgraphs` to
receive handles, then drill into `handle.values` / `handle.messages`
/ `handle.subgraphs` (recursive grandchildren) / `handle.lifecycle`.
Each mini-mux owns its own scope and uses its own
`SubgraphTransformer` to discover its direct children, so
grandchildren live on the child handle — never on the root's
`subgraphs` log. Forwarding events into the matching child mini-mux
is what keeps the child's projections populated.
Native transformer — `subgraphs` is exposed as `run.subgraphs`.
"""
_native = True
supports_sync = True
def __init__(self, scope: tuple[str, ...] = ()) -> None:
super().__init__(scope)
self._log: StreamChannel[SubgraphRunStream | AsyncSubgraphRunStream] = (
StreamChannel()
)
self._handles: dict[
tuple[str, ...], SubgraphRunStream | AsyncSubgraphRunStream
] = {}
self._mux: StreamMux | None = None
def init(self) -> dict[str, Any]:
return {"subgraphs": self._log}
def _on_register(self, mux: Any) -> None:
self._mux = mux
def _should_track(self, ns: tuple[str, ...]) -> bool:
# Direct children only — grandchildren are picked up by the
# child mini-mux's own SubgraphTransformer.
depth = len(self.scope)
return len(ns) == depth + 1 and ns[:depth] == self.scope
def _on_started(
self,
ns: tuple[str, ...],
graph_name: str | None,
trigger_call_id: str | None,
) -> None:
if self._mux is None:
return
try:
child_mux = self._mux._make_child(ns)
except RuntimeError:
return
handle_cls = AsyncSubgraphRunStream if child_mux.is_async else SubgraphRunStream
handle = handle_cls(
mux=child_mux,
path=ns,
graph_name=graph_name,
trigger_call_id=trigger_call_id,
)
self._handles[ns] = handle
self._log.push(handle)
def _on_terminal(
self,
ns: tuple[str, ...],
status: SubgraphStatus,
error: str | None,
) -> None:
handle = self._handles.get(ns)
if handle is None or not self._mark_terminal(handle, status, error):
return
self._close_or_fail_handle(handle, status, error)
async def _aon_terminal(
self,
ns: tuple[str, ...],
status: SubgraphStatus,
error: str | None,
) -> None:
handle = self._handles.get(ns)
if handle is None or not self._mark_terminal(handle, status, error):
return
await self._aclose_or_fail_handle(handle, status, error)
def _mark_terminal(
self,
handle: SubgraphRunStream | AsyncSubgraphRunStream,
status: SubgraphStatus,
error: str | None,
) -> bool:
"""Mark a handle terminal once. Returns True on first transition."""
if handle._seen_terminal:
return False
handle.status = status
if error is not None and handle.error is None:
handle.error = error
handle._seen_terminal = True
return True
def _close_or_fail_handle(
self,
handle: SubgraphRunStream | AsyncSubgraphRunStream,
status: SubgraphStatus,
error: str | None,
) -> None:
if handle._mux is None or handle._mux._events._closed:
return
if status == "failed":
handle._mux.fail(RuntimeError(error or "Subgraph failed"))
else:
handle._mux.close()
async def _aclose_or_fail_handle(
self,
handle: SubgraphRunStream | AsyncSubgraphRunStream,
status: SubgraphStatus,
error: str | None,
) -> None:
if handle._mux is None or handle._mux._events._closed:
return
if status == "failed":
await handle._mux.afail(RuntimeError(error or "Subgraph failed"))
else:
await handle._mux.aclose()
def _handle_for_event(
self, event: ProtocolEvent
) -> SubgraphRunStream | AsyncSubgraphRunStream | None:
ns = tuple(event["params"]["namespace"])
depth = len(self.scope)
if len(ns) < depth + 1:
return None
handle = self._handles.get(ns[: depth + 1])
if handle is None or handle._mux is None or handle._mux._events._closed:
return None
return handle
def process(self, event: ProtocolEvent) -> bool:
# Run tasks bookkeeping first so a `started` handle exists
# by the time we forward the event to the child mini-mux.
keep = super().process(event)
handle = self._handle_for_event(event)
if handle is not None:
handle._observe_event(event)
handle._mux.push(event)
return keep
async def aprocess(self, event: ProtocolEvent) -> bool:
# Async counterpart: repeats the tasks bookkeeping here so
# child mini-muxes receive events through their async lane.
if event["method"] == "tasks":
ns = tuple(event["params"]["namespace"])
data = event["params"]["data"]
if "result" in data:
for child_ns, status, error in self._pop_terminal_transitions(ns, data):
await self._aon_terminal(child_ns, status, error)
else:
self._handle_task_start(ns)
keep = False
else:
keep = True
handle = self._handle_for_event(event)
if handle is not None:
handle._observe_event(event)
await handle._mux.apush(event)
return keep
def _complete_open_handles(self) -> BaseException | None:
first_error: BaseException | None = None
for ns in list(self._open):
try:
self._on_terminal(ns, "completed", None)
except BaseException as e:
if first_error is None:
first_error = e
self._open.clear()
for handle in self._handles.values():
if self._mark_terminal(handle, "completed", None):
try:
self._close_or_fail_handle(handle, "completed", None)
except BaseException as e:
if first_error is None:
first_error = e
return first_error
async def _acomplete_open_handles(self) -> BaseException | None:
first_error: BaseException | None = None
for ns in list(self._open):
try:
await self._aon_terminal(ns, "completed", None)
except BaseException as e:
if first_error is None:
first_error = e
self._open.clear()
for handle in self._handles.values():
if self._mark_terminal(handle, "completed", None):
try:
await self._aclose_or_fail_handle(handle, "completed", None)
except BaseException as e:
if first_error is None:
first_error = e
return first_error
def finalize(self) -> None:
first_error = self._complete_open_handles()
if first_error is not None:
raise first_error
async def afinalize(self) -> None:
first_error = await self._acomplete_open_handles()
if first_error is not None:
raise first_error
def fail(self, err: BaseException) -> None:
status, error_str = _status_from_exception(err)
self._open.clear()
for handle in self._handles.values():
self._mark_terminal(handle, status, error_str)
if handle._mux is not None and not handle._mux._events._closed:
try:
handle._mux.fail(err)
except Exception:
_logger.warning(
"Error failing subgraph mini-mux at %s; "
"subscribers may not see the terminal error.",
handle.path,
exc_info=True,
)
async def afail(self, err: BaseException) -> None:
status, error_str = _status_from_exception(err)
self._open.clear()
for handle in self._handles.values():
self._mark_terminal(handle, status, error_str)
if handle._mux is not None and not handle._mux._events._closed:
try:
await handle._mux.afail(err)
except Exception:
_logger.warning(
"Error failing subgraph mini-mux at %s; "
"subscribers may not see the terminal error.",
handle.path,
exc_info=True,
)
class CheckpointsTransformer(StreamTransformer):
"""Capture checkpoint events as a drainable stream.
Surfaces `stream_mode="checkpoints"` data on `run.checkpoints` as
a `StreamChannel[dict[str, Any]]`. Each item is in the same format
as returned by `get_state()`.
Checkpoint events are only emitted when a checkpointer is configured
on the graph. When no checkpointer is present, the projection exists
but receives no events.
Only events at the run's own scope are captured; checkpoint data from
deeper subgraphs is available on the respective subgraph handle's
`.checkpoints` projection.
Native transformer — `run.checkpoints` is a direct attribute.
"""
_native = True
required_stream_modes = ("checkpoints",)
def __init__(self, scope: tuple[str, ...] = ()) -> None:
super().__init__(scope)
self._log: StreamChannel[dict[str, Any]] = StreamChannel()
self._scope_list: list[str] = list(scope)
def init(self) -> dict[str, Any]:
return {"checkpoints": self._log}
def process(self, event: ProtocolEvent) -> bool:
if event["method"] != "checkpoints":
return True
params = event["params"]
if params["namespace"] != self._scope_list:
return True
self._log.push(params["data"])
return True
class DebugTransformer(StreamTransformer):
"""Capture debug events as a drainable stream.
Surfaces `stream_mode="debug"` data on `run.debug` as a
`StreamChannel[dict[str, Any]]`. Each item is a debug event with
step-level detail (checkpoint snapshots, task payloads, and
task results wrapped with step number and timestamp).
Only events at the run's own scope are captured; debug data from
deeper subgraphs is available on the respective subgraph handle's
`.debug` projection.
Native transformer — `run.debug` is a direct attribute.
"""
_native = True
required_stream_modes = ("debug",)
def __init__(self, scope: tuple[str, ...] = ()) -> None:
super().__init__(scope)
self._log: StreamChannel[dict[str, Any]] = StreamChannel()
self._scope_list: list[str] = list(scope)
def init(self) -> dict[str, Any]:
return {"debug": self._log}
def process(self, event: ProtocolEvent) -> bool:
if event["method"] != "debug":
return True
params = event["params"]
if params["namespace"] != self._scope_list:
return True
self._log.push(params["data"])
return True
class TasksTransformer(StreamTransformer):
"""Capture raw task events as a drainable stream.
Surfaces `stream_mode="tasks"` data on `run.tasks` as a
`StreamChannel[dict[str, Any]]`. Each item is a task payload
(start or result).
`LifecycleTransformer` and `SubgraphTransformer` also consume
`tasks` events for subgraph discovery and lifecycle tracking.
This transformer captures the raw payloads independently for
consumers who need task-level detail.
Only events at the run's own scope are captured; task data from
deeper subgraphs is available on the respective subgraph handle's
`.tasks` projection.
Native transformer — `run.tasks` is a direct attribute.
"""
_native = True
required_stream_modes = ("tasks",)
def __init__(self, scope: tuple[str, ...] = ()) -> None:
super().__init__(scope)
self._log: StreamChannel[dict[str, Any]] = StreamChannel()
self._scope_list: list[str] = list(scope)
def init(self) -> dict[str, Any]:
return {"tasks": self._log}
def process(self, event: ProtocolEvent) -> bool:
if event["method"] != "tasks":
return True
params = event["params"]
if params["namespace"] != self._scope_list:
return True
self._log.push(params["data"])
return True