feat(langgraph)!: remove Pregel construction and NodeBuilder from the public API

Building a graph by constructing `Pregel(...)` with `NodeBuilder` nodes
was never meant to be public. Graphs are built with `StateGraph` or
`@entrypoint`.

- Delete `NodeBuilder`; `langgraph.pregel` now exports only `Pregel`.
- `Pregel(...)` raises `TypeError` pointing to `StateGraph` and
  `@entrypoint`. `Pregel` stays public as the type that `compile()` and
  `@entrypoint` return, for type annotations and `isinstance` checks.
- `@entrypoint` builds its graph through a private `_EntrypointPregel`
  subclass, the same way `StateGraph` uses `CompiledStateGraph`.
- Rewrite the `Pregel` docstring to describe the compiled graph type and
  drop the hand-built graph examples.
- Engine tests that build graphs by hand now use a test-only copy of
  `NodeBuilder` and a `RawPregel` subclass in `tests/raw_pregel.py`.

BREAKING CHANGE: `from langgraph.pregel import NodeBuilder` and calling
`Pregel(...)` directly no longer work. Build graphs with `StateGraph` or
`@entrypoint`.

libs/langgraph/langgraph/func/__init__.py

@@ -255,6 +255,11 @@ R = TypeVar("R")
 S = TypeVar("S")
 
 
+class _EntrypointPregel(Pregel):
+    """The graph that `@entrypoint` builds. `Pregel` itself cannot be constructed
+    directly."""
+
+
 # The decorator was wrapped in a class to support the `final` attribute.
 # In this form, the `final` attribute should play nicely with IDE autocompletion,
 # and type checking tools.
@@ -573,7 +578,7 @@ class entrypoint(Generic[ContextT]):
                 else:
                     output_type = save_type = sig.return_annotation
 
-        graph: Pregel[Any, ContextT, Any, Any] = Pregel(
+        graph: Pregel[Any, ContextT, Any, Any] = _EntrypointPregel(
             nodes={
                 func.__name__: PregelNode(
                     bound=bound,

libs/langgraph/langgraph/graph/message.py

@@ -22,7 +22,7 @@ from langchain_core.messages import (
 )
 from typing_extensions import TypedDict, deprecated
 
-from langgraph._internal._constants import CONF, CONFIG_KEY_SEND
+from langgraph._internal._constants import CONF, CONFIG_KEY_SEND, NS_SEP
 from langgraph.graph.state import StateGraph
 from langgraph.pregel._messages import (
     _messages_delta_reducer as _messages_delta_reducer,
@@ -343,7 +343,7 @@ def push_message(
     )
 
     from langgraph.config import get_config
-    from langgraph.pregel._messages import StreamMessagesHandler, graph_namespace
+    from langgraph.pregel._messages import StreamMessagesHandler
 
     config = get_config()
     message = next(x for x in convert_to_messages([message]))
@@ -359,12 +359,15 @@ def push_message(
     ):
         handlers = config["callbacks"]
 
-    metadata = config["metadata"]
-    for handler in handlers:
-        if isinstance(handler, StreamMessagesHandler):
-            ns = graph_namespace(metadata)
-            if handler.subgraphs or not ns or ns == handler.parent_ns:
-                handler._emit((ns, metadata), message, dedupe=False)
+    if stream_handler := next(
+        (x for x in handlers if isinstance(x, StreamMessagesHandler)), None
+    ):
+        metadata = config["metadata"]
+        message_meta = (
+            tuple(cast(str, metadata["langgraph_checkpoint_ns"]).split(NS_SEP)),
+            metadata,
+        )
+        stream_handler._emit(message_meta, message, dedupe=False)
 
     if state_key:
         config[CONF][CONFIG_KEY_SEND]([(state_key, message)])

libs/langgraph/langgraph/pregel/__init__.py

@@ -1,3 +1,3 @@
-from langgraph.pregel.main import NodeBuilder, Pregel
+from langgraph.pregel.main import Pregel
 
-__all__ = ("Pregel", "NodeBuilder")
+__all__ = ("Pregel",)

libs/langgraph/langgraph/pregel/_messages.py

@@ -23,7 +23,7 @@ from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, LLMResul
 from pydantic import BaseModel
 
 from langgraph._internal._config import filter_to_user_tags
-from langgraph._internal._constants import NS_SEP, PUSH
+from langgraph._internal._constants import NS_SEP
 from langgraph.channels.binop import _get_overwrite
 from langgraph.channels.delta import DeltaChannel
 from langgraph.constants import TAG_HIDDEN, TAG_NOSTREAM
@@ -55,23 +55,6 @@ def _state_values(obj: Any) -> Sequence[Any]:
     return ()
 
 
-def graph_namespace(metadata: Mapping[str, Any]) -> tuple[str, ...]:
-    """Namespace of the graph a task runs in, from the task's run metadata.
-
-    Drops the task's own segment, plus one per enclosing `@task` call: a call
-    runs in its caller's graph but nests its segment under the caller's. A
-    call's `langgraph_path` is `(PUSH, <caller's path>, <index>, True)`, while
-    a `Send` task's ends in `False`.
-    """
-    ns = tuple(cast(str, metadata["langgraph_checkpoint_ns"]).split(NS_SEP))
-    path = metadata.get("langgraph_path", ())
-    drop = 1
-    while len(path) == 4 and path[0] == PUSH and path[-1] is True:
-        drop += 1
-        path = path[1]
-    return ns[:-drop]
-
-
 class StreamMessagesHandler(BaseCallbackHandler, _StreamingCallbackHandler):
     """A callback handler that implements stream_mode=messages.
 
@@ -165,7 +148,9 @@ class StreamMessagesHandler(BaseCallbackHandler, _StreamingCallbackHandler):
         **kwargs: Any,
     ) -> Any:
         if metadata and (not tags or (TAG_NOSTREAM not in tags)):
-            ns = graph_namespace(metadata)
+            ns = tuple(cast(str, metadata["langgraph_checkpoint_ns"]).split(NS_SEP))[
+                :-1
+            ]
             if not self.subgraphs and len(ns) > 0 and ns != self.parent_ns:
                 return
             if (filtered_tags := filter_to_user_tags(tags)) is not None:
@@ -228,8 +213,10 @@ class StreamMessagesHandler(BaseCallbackHandler, _StreamingCallbackHandler):
             and kwargs.get("name") == metadata.get("langgraph_node")
             and (not tags or TAG_HIDDEN not in tags)
         ):
-            ns = graph_namespace(metadata)
-            if not self.subgraphs and len(ns) > 0 and ns != self.parent_ns:
+            ns = tuple(cast(str, metadata["langgraph_checkpoint_ns"]).split(NS_SEP))[
+                :-1
+            ]
+            if not self.subgraphs and len(ns) > 0:
                 return
             self.metadata[run_id] = (ns, metadata)
             for value in _state_values(inputs):

libs/langgraph/langgraph/pregel/_tools.py

@@ -7,9 +7,9 @@ from uuid import UUID
 
 from langchain_core.callbacks import BaseCallbackHandler
 
+from langgraph._internal._constants import NS_SEP
 from langgraph.constants import TAG_NOSTREAM
 from langgraph.errors import GraphDrained, GraphInterrupt
-from langgraph.pregel._messages import graph_namespace
 from langgraph.pregel.protocol import StreamChunk
 
 try:
@@ -92,9 +92,12 @@ class StreamToolCallHandler(BaseCallbackHandler, _StreamingCallbackHandler):
     ) -> tuple[str, ...] | None:
         """Resolve the namespace this tool call should emit at, or `None` to skip.
 
-        Mirrors `StreamMessagesHandler.on_chat_model_start`: the namespace
-        is that of the graph the tool runs in (`graph_namespace`). Returns
-        `None` when the call should be silently suppressed:
+        Mirrors `StreamMessagesHandler.on_chat_model_start`'s namespace
+        derivation: parses `langgraph_checkpoint_ns` (which ends with
+        the `node_name:task_id` of the calling node), drops that
+        trailing segment, and returns the containing subgraph's own
+        namespace. Returns `None` when the call should be silently
+        suppressed:
 
         - `metadata` is missing — handler is attached to a context
           without Pregel routing info.
@@ -107,9 +110,11 @@ class StreamToolCallHandler(BaseCallbackHandler, _StreamingCallbackHandler):
             return None
         if tags and TAG_NOSTREAM in tags:
             return None
-        ns = (
-            graph_namespace(metadata) if metadata.get("langgraph_checkpoint_ns") else ()
-        )
+        nskey = metadata.get("langgraph_checkpoint_ns")
+        if not nskey:
+            ns: tuple[str, ...] = ()
+        else:
+            ns = tuple(cast(str, nskey).split(NS_SEP))[:-1]
         if not self.subgraphs and len(ns) > 0 and ns != self.parent_ns:
             return None
         return ns

libs/langgraph/langgraph/pregel/_validate.py

@@ -47,9 +47,7 @@ def validate_graph(
                             f"not in known channels: '{repr(sorted(channels))[:100]}'"
                         )
         else:
-            raise TypeError(
-                f"Invalid node type {type(node)}, expected PregelNode or NodeBuilder"
-            )
+            raise TypeError(f"Invalid node type {type(node)}, expected PregelNode")
 
     for chan in subscribed_channels:
         if chan not in channels:

libs/langgraph/langgraph/pregel/main.py

@@ -17,7 +17,6 @@ from collections.abc import (
     Sequence,
 )
 from dataclasses import is_dataclass, replace
-from datetime import timedelta
 from functools import partial
 from inspect import isclass
 from typing import (
@@ -35,7 +34,6 @@ from langchain_core.globals import get_debug
 from langchain_core.runnables import (
     RunnableSequence,
 )
-from langchain_core.runnables.base import Input, Output
 from langchain_core.runnables.config import (
     RunnableConfig,
     get_async_callback_manager_for_config,
@@ -93,13 +91,6 @@ from langgraph._internal._queue import (  # type: ignore[attr-defined]
     AsyncQueue,
     SyncQueue,
 )
-from langgraph._internal._runnable import (
-    Runnable,
-    RunnableLike,
-    RunnableSeq,
-    coerce_to_runnable,
-)
-from langgraph._internal._timeout import coerce_timeout_policy
 from langgraph._internal._typing import MISSING, DeprecatedKwargs
 from langgraph.callbacks import (
     GraphInterruptEvent,
@@ -155,7 +146,7 @@ from langgraph.pregel._messages import (
     StreamMessagesHandlerV2,
     ensure_message_ids,
 )
-from langgraph.pregel._read import DEFAULT_BOUND, PregelNode
+from langgraph.pregel._read import PregelNode
 from langgraph.pregel._retry import RetryPolicy
 from langgraph.pregel._runner import PregelRunner
 from langgraph.pregel._task_status import read_task_statuses
@@ -165,7 +156,6 @@ from langgraph.pregel._utils import (
     validate_timeout_supported,
 )
 from langgraph.pregel._validate import validate_graph, validate_keys
-from langgraph.pregel._write import ChannelWrite, ChannelWriteEntry
 from langgraph.pregel.debug import get_bolded_text, get_colored_text, tasks_w_writes
 from langgraph.pregel.protocol import PregelProtocol, StreamChunk, StreamProtocol
 from langgraph.runtime import (
@@ -197,7 +187,6 @@ from langgraph.types import (
     StateUpdate,
     StreamMode,
     StreamPart,
-    TimeoutPolicy,
     ensure_valid_checkpointer,
 )
 from langgraph.typing import ContextT, InputT, OutputT, StateT
@@ -208,182 +197,7 @@ try:
 except ImportError:
     _StreamingCallbackHandler = None  # type: ignore
 
-__all__ = ("NodeBuilder", "Pregel")
-
-_WriteValue = Callable[[Input], Output] | Any
-
-
-class NodeBuilder:
-    __slots__ = (
-        "_channels",
-        "_triggers",
-        "_tags",
-        "_metadata",
-        "_writes",
-        "_bound",
-        "_retry_policy",
-        "_cache_policy",
-        "_timeout",
-    )
-
-    _channels: str | list[str]
-    _triggers: list[str]
-    _tags: list[str]
-    _metadata: dict[str, Any]
-    _writes: list[ChannelWriteEntry]
-    _bound: Runnable
-    _retry_policy: list[RetryPolicy]
-    _cache_policy: CachePolicy | None
-    _timeout: TimeoutPolicy | None
-
-    def __init__(
-        self,
-    ) -> None:
-        self._channels = []
-        self._triggers = []
-        self._tags = []
-        self._metadata = {}
-        self._writes = []
-        self._bound = DEFAULT_BOUND
-        self._retry_policy = []
-        self._cache_policy = None
-        self._timeout = None
-
-    def subscribe_only(
-        self,
-        channel: str,
-    ) -> Self:
-        """Subscribe to a single channel."""
-        if not self._channels:
-            self._channels = channel
-        else:
-            raise ValueError(
-                "Cannot subscribe to single channels when other channels are already subscribed to"
-            )
-
-        self._triggers.append(channel)
-
-        return self
-
-    def subscribe_to(
-        self,
-        *channels: str,
-        read: bool = True,
-    ) -> Self:
-        """Add channels to subscribe to.
-
-        Node will be invoked when any of these channels are updated, with a dict of the
-        channel values as input.
-
-        Args:
-            channels: Channel name(s) to subscribe to
-            read: If `True`, the channels will be included in the input to the node.
-                Otherwise, they will trigger the node without being sent in input.
-
-        Returns:
-            Self for chaining
-        """
-        if isinstance(self._channels, str):
-            raise ValueError(
-                "Cannot subscribe to channels when subscribed to a single channel"
-            )
-        if read:
-            if not self._channels:
-                self._channels = list(channels)
-            else:
-                self._channels.extend(channels)
-
-        if isinstance(channels, str):
-            self._triggers.append(channels)
-        else:
-            self._triggers.extend(channels)
-
-        return self
-
-    def read_from(
-        self,
-        *channels: str,
-    ) -> Self:
-        """Adds the specified channels to read from, without subscribing to them."""
-        assert isinstance(self._channels, list), (
-            "Cannot read additional channels when subscribed to single channels"
-        )
-        self._channels.extend(channels)
-        return self
-
-    def do(
-        self,
-        node: RunnableLike,
-    ) -> Self:
-        """Adds the specified node."""
-        if self._bound is not DEFAULT_BOUND:
-            self._bound = RunnableSeq(
-                self._bound, coerce_to_runnable(node, name=None, trace=True)
-            )
-        else:
-            self._bound = coerce_to_runnable(node, name=None, trace=True)
-        return self
-
-    def write_to(
-        self,
-        *channels: str | ChannelWriteEntry,
-        **kwargs: _WriteValue,
-    ) -> Self:
-        """Add channel writes.
-
-        Args:
-            *channels: Channel names to write to.
-            **kwargs: Channel name and value mappings.
-
-        Returns:
-            Self for chaining
-        """
-        self._writes.extend(
-            ChannelWriteEntry(c) if isinstance(c, str) else c for c in channels
-        )
-        self._writes.extend(
-            ChannelWriteEntry(k, mapper=v)
-            if callable(v)
-            else ChannelWriteEntry(k, value=v)
-            for k, v in kwargs.items()
-        )
-
-        return self
-
-    def meta(self, *tags: str, **metadata: Any) -> Self:
-        """Add tags or metadata to the node."""
-        self._tags.extend(tags)
-        self._metadata.update(metadata)
-        return self
-
-    def add_retry_policies(self, *policies: RetryPolicy) -> Self:
-        """Adds retry policies to the node."""
-        self._retry_policy.extend(policies)
-        return self
-
-    def add_cache_policy(self, policy: CachePolicy) -> Self:
-        """Adds cache policies to the node."""
-        self._cache_policy = policy
-        return self
-
-    def set_timeout(self, timeout: float | timedelta | TimeoutPolicy | None) -> Self:
-        """Set the per-attempt timeout policy for this node."""
-        self._timeout = coerce_timeout_policy(timeout)
-        return self
-
-    def build(self) -> PregelNode:
-        """Builds the node."""
-        return PregelNode(
-            channels=self._channels,
-            triggers=self._triggers,
-            tags=self._tags,
-            metadata=self._metadata,
-            writers=[ChannelWrite(self._writes)],
-            bound=self._bound,
-            retry_policy=self._retry_policy,
-            cache_policy=self._cache_policy,
-            timeout=self._timeout,
-        )
+__all__ = ("Pregel",)
 
 
 # Kwargs that ``stream_events(version="v3")`` / ``astream_events(version="v3")``
@@ -461,255 +275,22 @@ class Pregel(
     PregelProtocol[StateT, ContextT, InputT, OutputT],
     Generic[StateT, ContextT, InputT, OutputT],
 ):
-    """Pregel manages the runtime behavior for LangGraph applications.
+    """The compiled graph that runs a LangGraph application.
 
-    ## Overview
+    `StateGraph.compile()` and the `@entrypoint` decorator return an instance of
+    this class. It provides the methods that run and inspect the application,
+    such as `invoke`, `stream`, `get_state` and `update_state`.
 
-    Pregel combines [**actors**](https://en.wikipedia.org/wiki/Actor_model)
-    and **channels** into a single application.
-    **Actors** read data from channels and write data to channels.
-    Pregel organizes the execution of the application into multiple steps,
-    following the **Pregel Algorithm**/**Bulk Synchronous Parallel** model.
+    The runtime is named after Google's
+    [Pregel algorithm](https://research.google/pubs/pub37252/). It runs the
+    application in steps. In each step it plans which nodes to run, runs them in
+    parallel, and then applies their writes to the graph's state, so writes
+    become visible only in the next step. The run ends when no node is
+    scheduled, or when the recursion limit is reached.
 
-    Each step consists of three phases:
-
-    - **Plan**: Determine which **actors** to execute in this step. For example,
-        in the first step, select the **actors** that subscribe to the special
-        **input** channels; in subsequent steps,
-        select the **actors** that subscribe to channels updated in the previous step.
-    - **Execution**: Execute all selected **actors** in parallel,
-        until all complete, or one fails, or a timeout is reached. During this
-        phase, channel updates are invisible to actors until the next step.
-    - **Update**: Update the channels with the values written by the **actors**
-        in this step.
-
-    Repeat until no **actors** are selected for execution, or a maximum number of
-    steps is reached.
-
-    ## Actors
-
-    An **actor** is a `PregelNode`.
-    It subscribes to channels, reads data from them, and writes data to them.
-    It can be thought of as an **actor** in the Pregel algorithm.
-    `PregelNodes` implement LangChain's
-    Runnable interface.
-
-    ## Channels
-
-    Channels are used to communicate between actors (`PregelNodes`).
-    Each channel has a value type, an update type, and an update function – which
-    takes a sequence of updates and
-    modifies the stored value. Channels can be used to send data from one chain to
-    another, or to send data from a chain to itself in a future step. LangGraph
-    provides a number of built-in channels:
-
-    ### Basic channels: LastValue and Topic
-
-    - `LastValue`: The default channel, stores the last value sent to the channel,
-       useful for input and output values, or for sending data from one step to the next
-    - `Topic`: A configurable PubSub Topic, useful for sending multiple values
-       between *actors*, or for accumulating output. Can be configured to deduplicate
-       values, and/or to accumulate values over the course of multiple steps.
-
-    ### Advanced channels: Context and BinaryOperatorAggregate
-
-    - `Context`: exposes the value of a context manager, managing its lifecycle.
-        Useful for accessing external resources that require setup and/or teardown. e.g.
-        `client = Context(httpx.Client)`
-    - `BinaryOperatorAggregate`: stores a persistent value, updated by applying
-        a binary operator to the current value and each update
-        sent to the channel, useful for computing aggregates over multiple steps. e.g.
-        `total = BinaryOperatorAggregate(int, operator.add)`
-
-    ## Examples
-
-    Most users will interact with Pregel via a
-    [StateGraph (Graph API)][langgraph.graph.StateGraph] or via an
-    [entrypoint (Functional API)][langgraph.func.entrypoint].
-
-    However, for **advanced** use cases, Pregel can be used directly. If you're
-    not sure whether you need to use Pregel directly, then the answer is probably no
-    - you should use the Graph API or Functional API instead. These are higher-level
-    interfaces that will compile down to Pregel under the hood.
-
-    Here are some examples to give you a sense of how it works:
-
-    Example: Single node application
-        ```python
-        from langgraph.channels import EphemeralValue
-        from langgraph.pregel import Pregel, NodeBuilder
-
-        node1 = (
-            NodeBuilder().subscribe_only("a")
-            .do(lambda x: x + x)
-            .write_to("b")
-        )
-
-        app = Pregel(
-            nodes={"node1": node1},
-            channels={
-                "a": EphemeralValue(str),
-                "b": EphemeralValue(str),
-            },
-            input_channels=["a"],
-            output_channels=["b"],
-        )
-
-        app.invoke({"a": "foo"})
-        ```
-
-        ```con
-        {'b': 'foofoo'}
-        ```
-
-    Example: Using multiple nodes and multiple output channels
-        ```python
-        from langgraph.channels import LastValue, EphemeralValue
-        from langgraph.pregel import Pregel, NodeBuilder
-
-        node1 = (
-            NodeBuilder().subscribe_only("a")
-            .do(lambda x: x + x)
-            .write_to("b")
-        )
-
-        node2 = (
-            NodeBuilder().subscribe_to("b")
-            .do(lambda x: x["b"] + x["b"])
-            .write_to("c")
-        )
-
-
-        app = Pregel(
-            nodes={"node1": node1, "node2": node2},
-            channels={
-                "a": EphemeralValue(str),
-                "b": LastValue(str),
-                "c": EphemeralValue(str),
-            },
-            input_channels=["a"],
-            output_channels=["b", "c"],
-        )
-
-        app.invoke({"a": "foo"})
-        ```
-
-        ```con
-        {'b': 'foofoo', 'c': 'foofoofoofoo'}
-        ```
-
-    Example: Using a Topic channel
-        ```python
-        from langgraph.channels import LastValue, EphemeralValue, Topic
-        from langgraph.pregel import Pregel, NodeBuilder
-
-        node1 = (
-            NodeBuilder().subscribe_only("a")
-            .do(lambda x: x + x)
-            .write_to("b", "c")
-        )
-
-        node2 = (
-            NodeBuilder().subscribe_only("b")
-            .do(lambda x: x + x)
-            .write_to("c")
-        )
-
-
-        app = Pregel(
-            nodes={"node1": node1, "node2": node2},
-            channels={
-                "a": EphemeralValue(str),
-                "b": EphemeralValue(str),
-                "c": Topic(str, accumulate=True),
-            },
-            input_channels=["a"],
-            output_channels=["c"],
-        )
-
-        app.invoke({"a": "foo"})
-        ```
-
-        ```pycon
-        {"c": ["foofoo", "foofoofoofoo"]}
-        ```
-
-    Example: Using a `BinaryOperatorAggregate` channel
-        ```python
-        from langgraph.channels import EphemeralValue, BinaryOperatorAggregate
-        from langgraph.pregel import Pregel, NodeBuilder
-
-
-        node1 = (
-            NodeBuilder().subscribe_only("a")
-            .do(lambda x: x + x)
-            .write_to("b", "c")
-        )
-
-        node2 = (
-            NodeBuilder().subscribe_only("b")
-            .do(lambda x: x + x)
-            .write_to("c")
-        )
-
-
-        def reducer(current, update):
-            if current:
-                return current + " | " + update
-            else:
-                return update
-
-
-        app = Pregel(
-            nodes={"node1": node1, "node2": node2},
-            channels={
-                "a": EphemeralValue(str),
-                "b": EphemeralValue(str),
-                "c": BinaryOperatorAggregate(str, operator=reducer),
-            },
-            input_channels=["a"],
-            output_channels=["c"],
-        )
-
-        app.invoke({"a": "foo"})
-        ```
-
-        ```con
-        {'c': 'foofoo | foofoofoofoo'}
-        ```
-
-    Example: Introducing a cycle
-        This example demonstrates how to introduce a cycle in the graph, by having
-        a chain write to a channel it subscribes to.
-
-        Execution will continue until a `None` value is written to the channel.
-
-        ```python
-        from langgraph.channels import EphemeralValue
-        from langgraph.pregel import Pregel, NodeBuilder, ChannelWriteEntry
-
-        example_node = (
-            NodeBuilder()
-            .subscribe_only("value")
-            .do(lambda x: x + x if len(x) < 10 else None)
-            .write_to(ChannelWriteEntry(channel="value", skip_none=True))
-        )
-
-        app = Pregel(
-            nodes={"example_node": example_node},
-            channels={
-                "value": EphemeralValue(str),
-            },
-            input_channels=["value"],
-            output_channels=["value"],
-        )
-
-        app.invoke({"value": "a"})
-        ```
-
-        ```con
-        {'value': 'aaaaaaaaaaaaaaaa'}
-        ```
+    `Pregel` is not constructed directly. Build graphs with
+    [`StateGraph`][langgraph.graph.StateGraph] or
+    [`@entrypoint`][langgraph.func.entrypoint].
     """
 
     nodes: dict[str, PregelNode]
@@ -768,7 +349,7 @@ class Pregel(
     def __init__(
         self,
         *,
-        nodes: dict[str, PregelNode | NodeBuilder],
+        nodes: dict[str, PregelNode],
         channels: dict[str, BaseChannel | ManagedValueSpec] | None,
         auto_validate: bool = True,
         stream_mode: StreamMode = "values",
@@ -793,6 +374,13 @@ class Pregel(
         stream_transformers: Sequence[Callable[[tuple[str, ...]], Any]] | None = None,
         **deprecated_kwargs: Unpack[DeprecatedKwargs],
     ) -> None:
+        # LangGraph builds graphs through subclasses: `CompiledStateGraph` and
+        # the graph `@entrypoint` returns.
+        if type(self) is Pregel:
+            raise TypeError(
+                "`Pregel` cannot be constructed directly. "
+                "Build graphs with `StateGraph` or `@entrypoint`."
+            )
         if (
             config_type := deprecated_kwargs.get("config_type", MISSING)
         ) is not MISSING:
@@ -807,9 +395,7 @@ class Pregel(
 
         checkpointer = ensure_valid_checkpointer(checkpointer)
 
-        self.nodes = {
-            k: v.build() if isinstance(v, NodeBuilder) else v for k, v in nodes.items()
-        }
+        self.nodes = dict(nodes)
         self.channels = channels or {}
         if TASKS in self.channels and not isinstance(self.channels[TASKS], Topic):
             raise ValueError(
@@ -2880,18 +2466,6 @@ class Pregel(
                     for h in callback_manager.inheritable_handlers
                     if not isinstance(h, StreamMessagesHandlerV2)
                 ]
-            if CONFIG_KEY_TASK_ID not in config[CONF]:
-                # Not run as a task (a child invoked with its own thread, say),
-                # this graph's namespace starts at the root, so a caller's
-                # handler would take this graph's events for its own graph's.
-                callback_manager.handlers = [
-                    h for h in callback_manager.handlers if not _is_stream_handler(h)
-                ]
-                callback_manager.inheritable_handlers = [
-                    h
-                    for h in callback_manager.inheritable_handlers
-                    if not _is_stream_handler(h)
-                ]
             if "ls_integration" not in callback_manager.metadata:
                 callback_manager.add_metadata({"ls_integration": "langgraph"})
             run_manager = callback_manager.on_chain_start(
@@ -2910,9 +2484,9 @@ class Pregel(
                 )
             # set up subgraph checkpointing
             config = self._own_checkpoint_config(config)
-            stream_handlers: list[StreamMessagesHandler | StreamToolCallHandler] = []
             # set up messages stream mode
             if "messages" in stream_modes:
+                ns_ = cast(str | None, config[CONF].get(CONFIG_KEY_CHECKPOINT_NS))
                 use_stream_messages_v2 = bool(
                     version == "v2" and config[CONF].get(CONFIG_KEY_STREAM_MESSAGES_V2)
                 )
@@ -2921,12 +2495,24 @@ class Pregel(
                     if use_stream_messages_v2
                     else StreamMessagesHandler
                 )
-                stream_handlers.append(messages_handler_cls(stream.put, subgraphs))
+                run_manager.inheritable_handlers.append(
+                    messages_handler_cls(
+                        stream.put,
+                        subgraphs,
+                        parent_ns=tuple(ns_.split(NS_SEP)) if ns_ else None,
+                    )
+                )
 
             # set up tools stream mode
             if "tools" in stream_modes:
-                stream_handlers.append(StreamToolCallHandler(stream.put, subgraphs))
-            run_manager.inheritable_handlers.extend(stream_handlers)
+                ns_tools = cast(str | None, config[CONF].get(CONFIG_KEY_CHECKPOINT_NS))
+                run_manager.inheritable_handlers.append(
+                    StreamToolCallHandler(
+                        stream.put,
+                        subgraphs,
+                        parent_ns=tuple(ns_tools.split(NS_SEP)) if ns_tools else None,
+                    )
+                )
 
             # set up custom stream mode
             if "custom" in stream_modes:
@@ -3009,10 +2595,6 @@ class Pregel(
                 cache_policy=self.cache_policy,
                 has_graph_lifecycle_callbacks=bool(graph_callback_manager.handlers),
             ) as loop:
-                # Known only now: the loop numbers the namespace of every
-                # subgraph a task runs after its first.
-                for handler in stream_handlers:
-                    handler.parent_ns = loop.checkpoint_ns
                 emit_graph_lifecycle_events(loop)
                 # create runner
                 runner = PregelRunner(
@@ -3295,18 +2877,6 @@ class Pregel(
                     for h in callback_manager.inheritable_handlers
                     if not isinstance(h, StreamMessagesHandlerV2)
                 ]
-            if CONFIG_KEY_TASK_ID not in config[CONF]:
-                # Not run as a task (a child invoked with its own thread, say),
-                # this graph's namespace starts at the root, so a caller's
-                # handler would take this graph's events for its own graph's.
-                callback_manager.handlers = [
-                    h for h in callback_manager.handlers if not _is_stream_handler(h)
-                ]
-                callback_manager.inheritable_handlers = [
-                    h
-                    for h in callback_manager.inheritable_handlers
-                    if not _is_stream_handler(h)
-                ]
             if "ls_integration" not in callback_manager.metadata:
                 callback_manager.add_metadata({"ls_integration": "langgraph"})
             run_manager = await callback_manager.on_chain_start(
@@ -3341,9 +2911,10 @@ class Pregel(
                 )
             # set up subgraph checkpointing
             config = self._own_checkpoint_config(config)
-            stream_handlers: list[StreamMessagesHandler | StreamToolCallHandler] = []
             # set up messages stream mode
             if "messages" in stream_modes:
+                # namespace can be None in a root level graph?
+                ns_ = cast(str | None, config[CONF].get(CONFIG_KEY_CHECKPOINT_NS))
                 use_stream_messages_v2 = bool(
                     version == "v2" and config[CONF].get(CONFIG_KEY_STREAM_MESSAGES_V2)
                 )
@@ -3352,12 +2923,24 @@ class Pregel(
                     if use_stream_messages_v2
                     else StreamMessagesHandler
                 )
-                stream_handlers.append(messages_handler_cls(stream_put, subgraphs))
+                run_manager.inheritable_handlers.append(
+                    messages_handler_cls(
+                        stream_put,
+                        subgraphs,
+                        parent_ns=tuple(ns_.split(NS_SEP)) if ns_ else None,
+                    )
+                )
 
             # set up tools stream mode
             if "tools" in stream_modes:
-                stream_handlers.append(StreamToolCallHandler(stream_put, subgraphs))
-            run_manager.inheritable_handlers.extend(stream_handlers)
+                ns_tools = cast(str | None, config[CONF].get(CONFIG_KEY_CHECKPOINT_NS))
+                run_manager.inheritable_handlers.append(
+                    StreamToolCallHandler(
+                        stream_put,
+                        subgraphs,
+                        parent_ns=tuple(ns_tools.split(NS_SEP)) if ns_tools else None,
+                    )
+                )
 
             # set up custom stream mode
             def stream_writer(c: Any) -> None:
@@ -3466,10 +3049,6 @@ class Pregel(
                 cache_policy=self.cache_policy,
                 has_graph_lifecycle_callbacks=bool(graph_callback_manager.handlers),
             ) as loop:
-                # Known only now: the loop numbers the namespace of every
-                # subgraph a task runs after its first.
-                for handler in stream_handlers:
-                    handler.parent_ns = loop.checkpoint_ns
                 await aemit_graph_lifecycle_events(loop)
                 # create runner
                 runner = PregelRunner(
@@ -4467,10 +4046,6 @@ def _coerce_checkpoint_values(payload: Any, mapper: Callable[[Any], Any]) -> Non
         payload["values"] = mapper(payload["values"])
 
 
-def _is_stream_handler(handler: object) -> bool:
-    return isinstance(handler, (StreamMessagesHandler, StreamToolCallHandler))
-
-
 def _resolve_parent_ns(
     graph_config: RunnableConfig | None, call_config: RunnableConfig | None
 ) -> tuple[str, ...]:

libs/langgraph/langgraph/pregel/remote.py

@@ -847,11 +847,6 @@ class RemoteGraph(PregelProtocol):
             # filter for what was actually requested
             if mode not in requested:
                 continue
-            # subgraph events may have been requested only for the parent stream.
-            # messages are exempt: the server dedupes them across namespaces, so
-            # dropping them here would also drop the root-level message
-            if not subgraphs and NS_SEP in chunk.event and mode != "messages":
-                continue
 
             if chunk.event.startswith("messages"):
                 chunk = chunk._replace(data=tuple(chunk.data))
@@ -1002,11 +997,6 @@ class RemoteGraph(PregelProtocol):
             # filter for what was actually requested
             if mode not in requested:
                 continue
-            # subgraph events may have been requested only for the parent stream.
-            # messages are exempt: the server dedupes them across namespaces, so
-            # dropping them here would also drop the root-level message
-            if not subgraphs and NS_SEP in chunk.event and mode != "messages":
-                continue
 
             if chunk.event.startswith("messages"):
                 chunk = chunk._replace(data=tuple(chunk.data))

libs/langgraph/tests/raw_pregel.py

@@ -0,0 +1,222 @@
+"""Build graphs directly on the Pregel engine, for tests of engine behavior.
+
+LangGraph does not expose this: applications build graphs with `StateGraph` or
+`@entrypoint`. Tests use it to set up channels, triggers and writes that those
+APIs do not produce on their own.
+"""
+
+from __future__ import annotations
+
+from collections.abc import Callable
+from datetime import timedelta
+from typing import Any
+
+from langchain_core.runnables.base import Input, Output
+from typing_extensions import Self
+
+from langgraph._internal._runnable import (
+    Runnable,
+    RunnableLike,
+    RunnableSeq,
+    coerce_to_runnable,
+)
+from langgraph._internal._timeout import coerce_timeout_policy
+from langgraph.pregel import Pregel
+from langgraph.pregel._read import DEFAULT_BOUND, PregelNode
+from langgraph.pregel._write import ChannelWrite, ChannelWriteEntry
+from langgraph.types import CachePolicy, RetryPolicy, TimeoutPolicy
+
+__all__ = ("NodeBuilder", "RawPregel")
+
+_WriteValue = Callable[[Input], Output] | Any
+
+
+class NodeBuilder:
+    """Builds a `PregelNode` that reads and writes named channels."""
+
+    __slots__ = (
+        "_channels",
+        "_triggers",
+        "_tags",
+        "_metadata",
+        "_writes",
+        "_bound",
+        "_retry_policy",
+        "_cache_policy",
+        "_timeout",
+    )
+
+    _channels: str | list[str]
+    _triggers: list[str]
+    _tags: list[str]
+    _metadata: dict[str, Any]
+    _writes: list[ChannelWriteEntry]
+    _bound: Runnable
+    _retry_policy: list[RetryPolicy]
+    _cache_policy: CachePolicy | None
+    _timeout: TimeoutPolicy | None
+
+    def __init__(
+        self,
+    ) -> None:
+        self._channels = []
+        self._triggers = []
+        self._tags = []
+        self._metadata = {}
+        self._writes = []
+        self._bound = DEFAULT_BOUND
+        self._retry_policy = []
+        self._cache_policy = None
+        self._timeout = None
+
+    def subscribe_only(
+        self,
+        channel: str,
+    ) -> Self:
+        """Subscribe to a single channel."""
+        if not self._channels:
+            self._channels = channel
+        else:
+            raise ValueError(
+                "Cannot subscribe to single channels when other channels are already subscribed to"
+            )
+
+        self._triggers.append(channel)
+
+        return self
+
+    def subscribe_to(
+        self,
+        *channels: str,
+        read: bool = True,
+    ) -> Self:
+        """Add channels to subscribe to.
+
+        Node will be invoked when any of these channels are updated, with a dict of the
+        channel values as input.
+
+        Args:
+            channels: Channel name(s) to subscribe to
+            read: If `True`, the channels will be included in the input to the node.
+                Otherwise, they will trigger the node without being sent in input.
+
+        Returns:
+            Self for chaining
+        """
+        if isinstance(self._channels, str):
+            raise ValueError(
+                "Cannot subscribe to channels when subscribed to a single channel"
+            )
+        if read:
+            if not self._channels:
+                self._channels = list(channels)
+            else:
+                self._channels.extend(channels)
+
+        if isinstance(channels, str):
+            self._triggers.append(channels)
+        else:
+            self._triggers.extend(channels)
+
+        return self
+
+    def read_from(
+        self,
+        *channels: str,
+    ) -> Self:
+        """Adds the specified channels to read from, without subscribing to them."""
+        assert isinstance(self._channels, list), (
+            "Cannot read additional channels when subscribed to single channels"
+        )
+        self._channels.extend(channels)
+        return self
+
+    def do(
+        self,
+        node: RunnableLike,
+    ) -> Self:
+        """Adds the specified node."""
+        if self._bound is not DEFAULT_BOUND:
+            self._bound = RunnableSeq(
+                self._bound, coerce_to_runnable(node, name=None, trace=True)
+            )
+        else:
+            self._bound = coerce_to_runnable(node, name=None, trace=True)
+        return self
+
+    def write_to(
+        self,
+        *channels: str | ChannelWriteEntry,
+        **kwargs: _WriteValue,
+    ) -> Self:
+        """Add channel writes.
+
+        Args:
+            *channels: Channel names to write to.
+            **kwargs: Channel name and value mappings.
+
+        Returns:
+            Self for chaining
+        """
+        self._writes.extend(
+            ChannelWriteEntry(c) if isinstance(c, str) else c for c in channels
+        )
+        self._writes.extend(
+            ChannelWriteEntry(k, mapper=v)
+            if callable(v)
+            else ChannelWriteEntry(k, value=v)
+            for k, v in kwargs.items()
+        )
+
+        return self
+
+    def meta(self, *tags: str, **metadata: Any) -> Self:
+        """Add tags or metadata to the node."""
+        self._tags.extend(tags)
+        self._metadata.update(metadata)
+        return self
+
+    def add_retry_policies(self, *policies: RetryPolicy) -> Self:
+        """Adds retry policies to the node."""
+        self._retry_policy.extend(policies)
+        return self
+
+    def add_cache_policy(self, policy: CachePolicy) -> Self:
+        """Adds cache policies to the node."""
+        self._cache_policy = policy
+        return self
+
+    def set_timeout(self, timeout: float | timedelta | TimeoutPolicy | None) -> Self:
+        """Set the per-attempt timeout policy for this node."""
+        self._timeout = coerce_timeout_policy(timeout)
+        return self
+
+    def build(self) -> PregelNode:
+        """Builds the node."""
+        return PregelNode(
+            channels=self._channels,
+            triggers=self._triggers,
+            tags=self._tags,
+            metadata=self._metadata,
+            writers=[ChannelWrite(self._writes)],
+            bound=self._bound,
+            retry_policy=self._retry_policy,
+            cache_policy=self._cache_policy,
+            timeout=self._timeout,
+        )
+
+
+class RawPregel(Pregel):
+    """A `Pregel` built from hand-written nodes and channels.
+
+    Accepts `NodeBuilder` values in `nodes`, and builds them.
+    """
+
+    def __init__(self, *, nodes: dict[str, PregelNode | NodeBuilder], **kwargs: Any):
+        super().__init__(
+            nodes={
+                k: v.build() if isinstance(v, NodeBuilder) else v
+                for k, v in nodes.items()
+            },
+            **kwargs,
+        )

libs/langgraph/tests/test_delta_channel_id_stability.py

@@ -19,8 +19,8 @@ from langgraph.channels.delta import DeltaChannel
 from langgraph.channels.last_value import LastValue
 from langgraph.graph import END, START, StateGraph
 from langgraph.graph.message import _messages_delta_reducer
-from langgraph.pregel import NodeBuilder, Pregel
 from langgraph.types import Command, Durability, Overwrite
+from tests.raw_pregel import NodeBuilder, RawPregel
 
 pytestmark = pytest.mark.anyio
 
@@ -279,7 +279,7 @@ def _pregel_graph(seen: list[list[str | None]]) -> Any:
         .do(look)
         .write_to("messages")
     )
-    return Pregel(
+    return RawPregel(
         nodes={"look": node},
         channels={
             "messages": DeltaChannel(_messages_delta_reducer),

libs/langgraph/tests/test_delta_channel_run_input.py

@@ -7,8 +7,9 @@ from langgraph.checkpoint.memory import InMemorySaver
 from langgraph.channels.binop import BinaryOperatorAggregate
 from langgraph.channels.delta import DeltaChannel
 from langgraph.channels.last_value import LastValue
-from langgraph.pregel import NodeBuilder, Pregel
+from langgraph.pregel import Pregel
 from langgraph.types import Durability
+from tests.raw_pregel import NodeBuilder, RawPregel
 
 pytestmark = pytest.mark.anyio
 
@@ -19,7 +20,7 @@ def _sorted_extend(current: list, writes: list) -> list:
 
 def _delta_input_graph() -> Pregel:
     node = NodeBuilder().subscribe_only("go").do(lambda _: [2]).write_to("log", "plain")
-    return Pregel(
+    return RawPregel(
         nodes={"n": node},
         channels={
             "log": DeltaChannel(_sorted_extend),

libs/langgraph/tests/test_delta_channel_seal_subscribers.py

@@ -3,7 +3,8 @@ from langgraph.checkpoint.memory import InMemorySaver
 
 from langgraph.channels.delta import DeltaChannel
 from langgraph.channels.last_value import LastValue
-from langgraph.pregel import NodeBuilder, Pregel
+from langgraph.pregel import Pregel
+from tests.raw_pregel import NodeBuilder, RawPregel
 
 pytestmark = pytest.mark.anyio
 
@@ -17,7 +18,7 @@ def _extend(current: list, writes: list) -> list:
 def _graph(reads: list) -> Pregel:
     writer = NodeBuilder().subscribe_only("a").do(lambda _: [1]).write_to("d")
     reader = NodeBuilder().subscribe_only("d").do(lambda d: reads.append(list(d)))
-    return Pregel(
+    return RawPregel(
         nodes={"writer": writer, "reader": reader},
         channels={"a": LastValue(str), "d": DeltaChannel(_extend)},
         input_channels="a",

libs/langgraph/tests/test_delta_channel_update_overwrite.py

@@ -13,8 +13,9 @@ from langgraph.channels.delta import DeltaChannel
 from langgraph.channels.last_value import LastValue
 from langgraph.graph import START, StateGraph
 from langgraph.graph.message import _messages_delta_reducer
-from langgraph.pregel import NodeBuilder, Pregel
+from langgraph.pregel import Pregel
 from langgraph.types import Overwrite
+from tests.raw_pregel import NodeBuilder, RawPregel
 
 pytestmark = pytest.mark.anyio
 
@@ -36,7 +37,7 @@ def _extend(current: list, writes: list) -> list:
 
 def _delta_input_graph(saver: InMemorySaver) -> Pregel:
     node = NodeBuilder().subscribe_only("go").do(lambda _: [2]).write_to("log")
-    return Pregel(
+    return RawPregel(
         nodes={"n": node},
         channels={"log": DeltaChannel(_extend), "go": LastValue(int)},
         input_channels=["log", "go"],

libs/langgraph/tests/test_delta_channel_update_state.py

@@ -30,8 +30,8 @@ from langgraph.channels.delta import DeltaChannel
 from langgraph.channels.last_value import LastValue
 from langgraph.graph import START, StateGraph
 from langgraph.graph.message import _messages_delta_reducer
-from langgraph.pregel import NodeBuilder, Pregel
 from langgraph.types import Overwrite, StateSnapshot, StateUpdate
+from tests.raw_pregel import NodeBuilder, RawPregel
 
 pytestmark = pytest.mark.anyio
 
@@ -549,7 +549,7 @@ def _sorted_extend(current: list, writes: list) -> list:
 
 def _delta_input_graph(snapshot_frequency: int = 1000) -> Any:
     node = NodeBuilder().subscribe_only("go").do(lambda _: [2]).write_to("log", "plain")
-    return Pregel(
+    return RawPregel(
         nodes={"n": node},
         channels={
             "log": DeltaChannel(_sorted_extend, snapshot_frequency=snapshot_frequency),
@@ -649,7 +649,7 @@ def _messages_input_graph() -> Any:
         .do(lambda _: [HumanMessage("n", id="n")])
         .write_to("messages")
     )
-    return Pregel(
+    return RawPregel(
         nodes={"n": node},
         channels={
             "messages": DeltaChannel(_messages_delta_reducer),

libs/langgraph/tests/test_deprecation.py

@@ -13,13 +13,13 @@ from langgraph.errors import NodeInterrupt
 from langgraph.func import entrypoint, task
 from langgraph.graph import StateGraph
 from langgraph.graph.message import MessageGraph
-from langgraph.pregel import NodeBuilder, Pregel
 from langgraph.types import GraphOutput, Interrupt, RetryPolicy
 from langgraph.warnings import (
     LangGraphDeprecatedSinceV05,
     LangGraphDeprecatedSinceV10,
     LangGraphDeprecatedSinceV11,
 )
+from tests.raw_pregel import NodeBuilder, RawPregel
 
 
 class PlainState(TypedDict): ...
@@ -157,7 +157,7 @@ def test_config_type_deprecation_pregel(mocker: MockerFixture) -> None:
         LangGraphDeprecatedSinceV10,
         match="`config_type` is deprecated and will be removed. Please use `context_schema` instead.",
     ):
-        instance = Pregel(
+        instance = RawPregel(
             nodes={
                 "one": chain,
             },

libs/langgraph/tests/test_large_cases.py

@@ -39,7 +39,6 @@ from langgraph.channels.untracked_value import UntrackedValue
 from langgraph.constants import END, START
 from langgraph.graph import StateGraph
 from langgraph.graph.message import MessagesState, add_messages
-from langgraph.pregel import NodeBuilder, Pregel
 from langgraph.types import (
     Command,
     Durability,
@@ -62,6 +61,7 @@ from tests.messages import (
     _AnyIdHumanMessage,
     _AnyIdToolMessage,
 )
+from tests.raw_pregel import NodeBuilder, RawPregel
 
 
 def test_invoke_two_processes_in_out_interrupt(
@@ -72,7 +72,7 @@ def test_invoke_two_processes_in_out_interrupt(
     one = NodeBuilder().subscribe_only("input").do(add_one).write_to("inbox")
     two = NodeBuilder().subscribe_only("inbox").do(add_one).write_to("output")
 
-    app = Pregel(
+    app = RawPregel(
         nodes={"one": one, "two": two},
         channels={
             "inbox": LastValue(int),

libs/langgraph/tests/test_large_cases_async.py

@@ -39,7 +39,6 @@ from langgraph.constants import END, START
 from langgraph.graph import MessagesState
 from langgraph.graph.message import add_messages
 from langgraph.graph.state import StateGraph
-from langgraph.pregel import NodeBuilder, Pregel
 from langgraph.types import PregelTask, Send, StateSnapshot, StreamWriter
 from tests.any_int import AnyInt
 from tests.any_str import AnyDict, AnyStr, UnsortedSequence
@@ -51,6 +50,7 @@ from tests.messages import (
     _AnyIdHumanMessage,
     _AnyIdToolMessage,
 )
+from tests.raw_pregel import NodeBuilder, RawPregel
 
 pytestmark = pytest.mark.anyio
 
@@ -61,7 +61,7 @@ async def test_invoke_two_processes_in_out_interrupt(
     add_one = mocker.Mock(side_effect=lambda x: x + 1)
     one = NodeBuilder().subscribe_only("input").do(add_one).write_to("inbox")
     two = NodeBuilder().subscribe_only("inbox").do(add_one).write_to("output")
-    app = Pregel(
+    app = RawPregel(
         nodes={"one": one, "two": two},
         channels={
             "inbox": LastValue(int),

libs/langgraph/tests/test_pregel.py

@@ -66,10 +66,7 @@ from langgraph.errors import GraphRecursionError, InvalidUpdateError, ParentComm
 from langgraph.func import entrypoint, task
 from langgraph.graph import END, START, StateGraph
 from langgraph.graph.message import MessagesState, _messages_delta_reducer, add_messages
-from langgraph.pregel import (
-    NodeBuilder,
-    Pregel,
-)
+from langgraph.pregel import Pregel
 from langgraph.pregel._loop import PregelLoop, SyncPregelLoop
 from langgraph.pregel._runner import PregelRunner
 from langgraph.runtime import RunControl
@@ -95,6 +92,7 @@ from tests.messages import (
     _AnyIdHumanMessage,
     _AnyIdToolMessage,
 )
+from tests.raw_pregel import NodeBuilder, RawPregel
 
 pytestmark = pytest.mark.anyio
 
@@ -257,7 +255,7 @@ def test_context_json_schema() -> None:
         x: int
         y: str = field(default="foo")
 
-    app = Pregel(
+    app = RawPregel(
         nodes={
             "one": chain,
         },
@@ -449,7 +447,7 @@ def test_invoke_single_process_in_out(mocker: MockerFixture) -> None:
     add_one = mocker.Mock(side_effect=lambda x: x + 1)
     chain = NodeBuilder().subscribe_only("input").do(add_one).write_to("output")
 
-    app = Pregel(
+    app = RawPregel(
         nodes={
             "one": chain,
         },
@@ -485,7 +483,7 @@ def test_invoke_single_process_in_write_kwargs(mocker: MockerFixture) -> None:
         .write_to("output", fixed=5, output_plus_one=lambda x: x + 1)
     )
 
-    app = Pregel(
+    app = RawPregel(
         nodes={"one": chain},
         channels={
             "input": LastValue(int),
@@ -521,7 +519,7 @@ def test_invoke_single_process_in_out_dict(mocker: MockerFixture) -> None:
     add_one = mocker.Mock(side_effect=lambda x: x + 1)
     chain = NodeBuilder().subscribe_only("input").do(add_one).write_to("output")
 
-    app = Pregel(
+    app = RawPregel(
         nodes={"one": chain},
         channels={"input": LastValue(int), "output": LastValue(int)},
         input_channels="input",
@@ -546,7 +544,7 @@ def test_invoke_single_process_in_dict_out_dict(mocker: MockerFixture) -> None:
     add_one = mocker.Mock(side_effect=lambda x: x + 1)
     chain = NodeBuilder().subscribe_only("input").do(add_one).write_to("output")
 
-    app = Pregel(
+    app = RawPregel(
         nodes={"one": chain},
         channels={"input": LastValue(int), "output": LastValue(int)},
         input_channels=["input"],
@@ -572,7 +570,7 @@ def test_invoke_two_processes_in_out(mocker: MockerFixture) -> None:
     one = NodeBuilder().subscribe_only("input").do(add_one).write_to("inbox")
     two = NodeBuilder().subscribe_only("inbox").do(add_one).write_to("output")
 
-    app = Pregel(
+    app = RawPregel(
         nodes={"one": one, "two": two},
         channels={
             "inbox": LastValue(int),
@@ -677,7 +675,7 @@ def test_batch_two_processes_in_out() -> None:
     one = NodeBuilder().subscribe_only("input").do(add_one_with_delay).write_to("one")
     two = NodeBuilder().subscribe_only("one").do(add_one_with_delay).write_to("output")
 
-    app = Pregel(
+    app = RawPregel(
         nodes={"one": one, "two": two},
         channels={
             "one": LastValue(int),
@@ -709,7 +707,7 @@ def test_invoke_many_processes_in_out(mocker: MockerFixture) -> None:
         )
     nodes["last"] = NodeBuilder().subscribe_only(str(i)).do(add_one).write_to("output")
 
-    app = Pregel(
+    app = RawPregel(
         nodes=nodes,
         channels={str(i): LastValue(int) for i in range(-1, test_size - 2)}
         | {"input": LastValue(int), "output": LastValue(int)},
@@ -737,7 +735,7 @@ def test_batch_many_processes_in_out(mocker: MockerFixture) -> None:
         )
     nodes["last"] = NodeBuilder().subscribe_only(str(i)).do(add_one).write_to("output")
 
-    app = Pregel(
+    app = RawPregel(
         nodes=nodes,
         channels={str(i): LastValue(int) for i in range(-1, test_size - 2)}
         | {"input": LastValue(int), "output": LastValue(int)},
@@ -770,7 +768,7 @@ def test_invoke_two_processes_two_in_two_out_invalid(mocker: MockerFixture) -> N
     one = NodeBuilder().subscribe_only("input").do(add_one).write_to("output")
     two = NodeBuilder().subscribe_only("input").do(add_one).write_to("output")
 
-    app = Pregel(
+    app = RawPregel(
         nodes={"one": one, "two": two},
         channels={"output": LastValue(int), "input": LastValue(int)},
         input_channels="input",
@@ -803,7 +801,7 @@ def test_invoke_two_processes_two_in_two_out_valid(mocker: MockerFixture) -> Non
     one = NodeBuilder().subscribe_only("input").do(add_one).write_to("output")
     two = NodeBuilder().subscribe_only("input").do(add_one).write_to("output")
 
-    app = Pregel(
+    app = RawPregel(
         nodes={"one": one, "two": two},
         channels={
             "input": LastValue(int),
@@ -844,7 +842,7 @@ def test_invoke_checkpoint_two(
         .do(raise_if_above_10)
     )
 
-    app = Pregel(
+    app = RawPregel(
         nodes={"one": one},
         channels={
             "total": BinaryOperatorAggregate(int, operator.add),
@@ -1451,7 +1449,7 @@ def test_invoke_checkpoint_three(
         .do(raise_if_above_10)
     )
 
-    app = Pregel(
+    app = RawPregel(
         nodes={"one": one},
         channels={
             "total": BinaryOperatorAggregate(int, operator.add),
@@ -1576,7 +1574,7 @@ def test_invoke_two_processes_two_in_join_two_out(mocker: MockerFixture) -> None
         NodeBuilder().subscribe_only("inbox").do(add_10_each).write_to("output")
     )
 
-    app = Pregel(
+    app = RawPregel(
         nodes={
             "one": one,
             "chain_three": chain_three,
@@ -1607,7 +1605,7 @@ def test_invoke_join_then_call_other_pregel(
     add_one = mocker.Mock(side_effect=lambda x: x + 1)
     add_10_each = mocker.Mock(side_effect=lambda x: [y + 10 for y in x])
 
-    inner_app = Pregel(
+    inner_app = RawPregel(
         nodes={
             "one": NodeBuilder().subscribe_only("input").do(add_one).write_to("output")
         },
@@ -1628,7 +1626,7 @@ def test_invoke_join_then_call_other_pregel(
     )
     chain_three = NodeBuilder().subscribe_only("outbox_one").do(sum).write_to("output")
 
-    app = Pregel(
+    app = RawPregel(
         nodes={
             "one": one,
             "two": two,
@@ -1669,7 +1667,7 @@ def test_invoke_two_processes_one_in_two_out(mocker: MockerFixture) -> None:
     )
     two = NodeBuilder().subscribe_only("between").do(add_one).write_to("output")
 
-    app = Pregel(
+    app = RawPregel(
         nodes={"one": one, "two": two},
         channels={
             "input": LastValue(int),
@@ -1696,7 +1694,7 @@ def test_invoke_two_processes_no_out(mocker: MockerFixture) -> None:
     one = NodeBuilder().subscribe_only("input").do(add_one).write_to("between")
     two = NodeBuilder().subscribe_only("between").do(add_one)
 
-    app = Pregel(
+    app = RawPregel(
         nodes={"one": one, "two": two},
         channels={
             "input": LastValue(int),
@@ -1719,7 +1717,7 @@ def test_invoke_two_processes_no_in(mocker: MockerFixture) -> None:
     two = NodeBuilder().subscribe_only("between").do(add_one)
 
     with pytest.raises(TypeError):
-        Pregel(nodes={"one": one, "two": two})
+        RawPregel(nodes={"one": one, "two": two})
 
 
 def test_conditional_entrypoint_to_multiple_state_graph(
@@ -4128,7 +4126,7 @@ def test_xray_lance(snapshot: SnapshotAssertion):
 def test_channel_values(sync_checkpointer: BaseCheckpointSaver) -> None:
     config = {"configurable": {"thread_id": "1"}}
     chain = NodeBuilder().subscribe_only("input").write_to("output")
-    app = Pregel(
+    app = RawPregel(
         nodes={
             "one": chain,
         },
@@ -8950,39 +8948,6 @@ def test_subgraph_streaming_sync() -> None:
     assert result["num_chunks"] == 9
 
 
-def test_subgraph_streaming_node_output_messages_sync() -> None:
-    """Messages returned by a node (not streamed by an LLM) are emitted when a
-    graph is explicitly streamed with `stream_mode="messages"` inside a node."""
-
-    def respond(state: MessagesState) -> dict:
-        return {"messages": [AIMessage("hi there", id="ai1")]}
-
-    subgraph = (
-        StateGraph(MessagesState)
-        .add_node("respond", respond)
-        .add_edge(START, "respond")
-        .compile()
-    )
-    msgs = {"messages": [("user", "hello")]}
-
-    top_level = [msg for msg, _ in subgraph.stream(msgs, stream_mode="messages")]
-
-    def parent_node(state: MessagesState, config: RunnableConfig) -> dict:
-        nonlocal in_node
-        in_node = [
-            msg for msg, _ in subgraph.stream(msgs, config, stream_mode="messages")
-        ]
-        return {}
-
-    in_node: list = []
-    StateGraph(MessagesState).add_node("parent", parent_node).add_edge(
-        START, "parent"
-    ).compile().invoke(msgs)
-
-    assert [m.content for m in top_level] == ["hi there"]
-    assert [m.content for m in in_node] == ["hi there"]
-
-
 def test_get_graph_nonterminal_last_step_source(snapshot: SnapshotAssertion) -> None:
     class State(TypedDict):
         messages: list[str]
@@ -9540,7 +9505,7 @@ class _IntVersionSaver(InMemorySaver):
 
 
 def _build_chain_after_a_delta_channel() -> Pregel:
-    return Pregel(
+    return RawPregel(
         nodes={
             "a": NodeBuilder().subscribe_only("inp").do(lambda _: ["a"]).write_to("d"),
             "b": NodeBuilder().subscribe_only("d").do(lambda _: "b").write_to("x"),
@@ -9585,7 +9550,7 @@ async def test_aupdate_state_after_an_exit_snapshot_infers_the_last_writer() ->
 
 
 def test_update_state_after_a_fork_seal_infers_the_subscriber_that_ran() -> None:
-    graph = Pregel(
+    graph = RawPregel(
         nodes={
             "a": NodeBuilder()
             .subscribe_only("inp")
@@ -9620,7 +9585,7 @@ def test_update_state_after_a_fork_seal_infers_the_subscriber_that_ran() -> None
 def test_update_state_after_a_fork_seal_infers_the_node_whose_read_it_advanced() -> (
     None
 ):
-    graph = Pregel(
+    graph = RawPregel(
         nodes={
             "a": NodeBuilder().subscribe_only("inp").do(lambda _: ["a"]).write_to("d"),
             "b": NodeBuilder().subscribe_only("d").do(lambda _: "b").write_to("out"),

libs/langgraph/tests/test_pregel_async.py

@@ -69,7 +69,6 @@ from langgraph.errors import (
 from langgraph.func import entrypoint, task
 from langgraph.graph import END, START, StateGraph
 from langgraph.graph.message import MessagesState, _messages_delta_reducer, add_messages
-from langgraph.pregel import NodeBuilder, Pregel
 from langgraph.pregel._loop import AsyncPregelLoop, PregelLoop
 from langgraph.pregel._runner import PregelRunner
 from langgraph.runtime import RunControl
@@ -95,6 +94,7 @@ from tests.messages import (
     _AnyIdHumanMessage,
     _AnyIdToolMessage,
 )
+from tests.raw_pregel import NodeBuilder, RawPregel
 
 logger = logging.getLogger(__name__)
 
@@ -1446,7 +1446,7 @@ async def test_invoke_single_process_in_out(mocker: MockerFixture) -> None:
     add_one = mocker.Mock(side_effect=lambda x: x + 1)
     chain = NodeBuilder().subscribe_only("input").do(add_one).write_to("output")
 
-    app = Pregel(
+    app = RawPregel(
         nodes={
             "one": chain,
         },
@@ -1479,7 +1479,7 @@ async def test_invoke_single_process_in_write_kwargs(mocker: MockerFixture) -> N
         .write_to("output", fixed=5, output_plus_one=lambda x: x + 1)
     )
 
-    app = Pregel(
+    app = RawPregel(
         nodes={"one": chain},
         channels={
             "input": LastValue(int),
@@ -1515,7 +1515,7 @@ async def test_invoke_single_process_in_out_dict(mocker: MockerFixture) -> None:
     add_one = mocker.Mock(side_effect=lambda x: x + 1)
     chain = NodeBuilder().subscribe_only("input").do(add_one).write_to("output")
 
-    app = Pregel(
+    app = RawPregel(
         nodes={"one": chain},
         channels={"input": LastValue(int), "output": LastValue(int)},
         input_channels="input",
@@ -1540,7 +1540,7 @@ async def test_invoke_single_process_in_dict_out_dict(mocker: MockerFixture) ->
     add_one = mocker.Mock(side_effect=lambda x: x + 1)
     chain = NodeBuilder().subscribe_only("input").do(add_one).write_to("output")
 
-    app = Pregel(
+    app = RawPregel(
         nodes={"one": chain},
         channels={"input": LastValue(int), "output": LastValue(int)},
         input_channels=["input"],
@@ -1567,7 +1567,7 @@ async def test_invoke_two_processes_in_out(mocker: MockerFixture) -> None:
     one = NodeBuilder().subscribe_only("input").do(add_one).write_to("inbox")
     two = NodeBuilder().subscribe_only("inbox").do(add_one).write_to("output")
 
-    app = Pregel(
+    app = RawPregel(
         nodes={"one": one, "two": two},
         channels={
             "inbox": LastValue(int),
@@ -1607,7 +1607,7 @@ async def test_batch_two_processes_in_out() -> None:
     one = NodeBuilder().subscribe_only("input").do(add_one_with_delay).write_to("one")
     two = NodeBuilder().subscribe_only("one").do(add_one_with_delay).write_to("output")
 
-    app = Pregel(
+    app = RawPregel(
         nodes={"one": one, "two": two},
         channels={
             "one": LastValue(int),
@@ -1639,7 +1639,7 @@ async def test_invoke_many_processes_in_out(mocker: MockerFixture) -> None:
         )
     nodes["last"] = NodeBuilder().subscribe_only(str(i)).do(add_one).write_to("output")
 
-    app = Pregel(
+    app = RawPregel(
         nodes=nodes,
         channels={str(i): LastValue(int) for i in range(-1, test_size - 2)}
         | {"input": LastValue(int), "output": LastValue(int)},
@@ -1668,7 +1668,7 @@ async def test_batch_many_processes_in_out(mocker: MockerFixture) -> None:
         )
     nodes["last"] = NodeBuilder().subscribe_only(str(i)).do(add_one).write_to("output")
 
-    app = Pregel(
+    app = RawPregel(
         nodes=nodes,
         channels={str(i): LastValue(int) for i in range(-1, test_size - 2)}
         | {"input": LastValue(int), "output": LastValue(int)},
@@ -1704,7 +1704,7 @@ async def test_invoke_two_processes_two_in_two_out_invalid(
     one = NodeBuilder().subscribe_only("input").do(add_one).write_to("output")
     two = NodeBuilder().subscribe_only("input").do(add_one).write_to("output")
 
-    app = Pregel(
+    app = RawPregel(
         nodes={"one": one, "two": two},
         channels={"output": LastValue(int), "input": LastValue(int)},
         input_channels="input",
@@ -1722,7 +1722,7 @@ async def test_invoke_two_processes_two_in_two_out_valid(mocker: MockerFixture)
     one = NodeBuilder().subscribe_only("input").do(add_one).write_to("output")
     two = NodeBuilder().subscribe_only("input").do(add_one).write_to("output")
 
-    app = Pregel(
+    app = RawPregel(
         nodes={"one": one, "two": two},
         channels={
             "input": LastValue(int),
@@ -1763,7 +1763,7 @@ async def test_invoke_checkpoint(
         .do(raise_if_above_10)
     )
 
-    app = Pregel(
+    app = RawPregel(
         nodes={"one": one},
         channels={
             "total": BinaryOperatorAggregate(int, operator.add),
@@ -3641,7 +3641,7 @@ async def test_invoke_checkpoint_three(
         .do(raise_if_above_10)
     )
 
-    app = Pregel(
+    app = RawPregel(
         nodes={"one": one},
         channels={
             "total": BinaryOperatorAggregate(int, operator.add),
@@ -3765,7 +3765,7 @@ async def test_invoke_two_processes_two_in_join_two_out(mocker: MockerFixture) -
         NodeBuilder().subscribe_only("inbox").do(add_10_each).write_to("output")
     )
 
-    app = Pregel(
+    app = RawPregel(
         nodes={
             "one": one,
             "chain_three": chain_three,
@@ -3799,7 +3799,7 @@ async def test_invoke_two_processes_one_in_two_out(mocker: MockerFixture) -> Non
     )
     two = NodeBuilder().subscribe_only("between").do(add_one).write_to("output")
 
-    app = Pregel(
+    app = RawPregel(
         nodes={"one": one, "two": two},
         channels={
             "input": LastValue(int),
@@ -3823,7 +3823,7 @@ async def test_invoke_two_processes_no_out(mocker: MockerFixture) -> None:
     one = NodeBuilder().subscribe_only("input").do(add_one).write_to("between")
     two = NodeBuilder().subscribe_only("between").do(add_one)
 
-    app = Pregel(
+    app = RawPregel(
         nodes={"one": one, "two": two},
         channels={
             "input": LastValue(int),
@@ -9503,44 +9503,6 @@ async def test_subgraph_streaming_async() -> None:
     assert result["num_chunks"] == 9
 
 
-async def test_subgraph_streaming_node_output_messages_async() -> None:
-    """Messages returned by a node (not streamed by an LLM) are emitted when a
-    graph is explicitly streamed with `stream_mode="messages"` inside a node."""
-
-    async def respond(state: MessagesState) -> dict:
-        return {"messages": [AIMessage("hi there", id="ai1")]}
-
-    subgraph = (
-        StateGraph(MessagesState)
-        .add_node("respond", respond)
-        .add_edge(START, "respond")
-        .compile()
-    )
-    msgs = {"messages": [("user", "hello")]}
-
-    top_level = [msg async for msg, _ in subgraph.astream(msgs, stream_mode="messages")]
-
-    async def parent_node(state: MessagesState, config: RunnableConfig) -> dict:
-        nonlocal in_node
-        in_node = [
-            msg
-            async for msg, _ in subgraph.astream(msgs, config, stream_mode="messages")
-        ]
-        return {}
-
-    in_node: list = []
-    await (
-        StateGraph(MessagesState)
-        .add_node("parent", parent_node)
-        .add_edge(START, "parent")
-        .compile()
-        .ainvoke(msgs)
-    )
-
-    assert [m.content for m in top_level] == ["hi there"]
-    assert [m.content for m in in_node] == ["hi there"]
-
-
 @NEEDS_CONTEXTVARS
 async def test_null_resume_disallowed_with_multiple_interrupts(
     async_checkpointer: BaseCheckpointSaver,

libs/langgraph/tests/test_pregel_construction.py

@@ -0,0 +1,56 @@
+"""`Pregel` is the type of compiled graphs, built only by `StateGraph` and
+`@entrypoint`."""
+
+import pytest
+from langchain_core.runnables import RunnableConfig
+from langgraph.checkpoint.memory import InMemorySaver
+from typing_extensions import TypedDict
+
+import langgraph.pregel
+from langgraph.channels.ephemeral_value import EphemeralValue
+from langgraph.func import entrypoint
+from langgraph.graph import START, StateGraph
+from langgraph.pregel import Pregel
+from langgraph.pregel._read import PregelNode
+
+
+def test_pregel_cannot_be_constructed_directly() -> None:
+    with pytest.raises(TypeError, match="`Pregel` cannot be constructed directly"):
+        Pregel(
+            nodes={"node": PregelNode(channels="a", triggers=["a"])},
+            channels={"a": EphemeralValue(str)},
+            input_channels="a",
+            output_channels="a",
+        )
+
+
+def test_node_builder_is_not_exported() -> None:
+    assert langgraph.pregel.__all__ == ("Pregel",)
+    assert not hasattr(langgraph.pregel, "NodeBuilder")
+
+
+def test_compiled_graphs_are_pregel_instances() -> None:
+    class State(TypedDict):
+        value: int
+
+    def increment(state: State) -> State:
+        return {"value": state["value"] + 1}
+
+    builder = StateGraph(State)
+    builder.add_node("increment", increment)
+    builder.add_edge(START, "increment")
+    graph = builder.compile(checkpointer=InMemorySaver())
+
+    @entrypoint(checkpointer=InMemorySaver())
+    def workflow(value: int) -> int:
+        return value + 1
+
+    assert isinstance(graph, Pregel)
+    assert isinstance(workflow, Pregel)
+
+    # `with_config` copies the graph by calling its constructor again.
+    config: RunnableConfig = {"configurable": {"thread_id": "1"}}
+    assert graph.with_config(recursion_limit=5).invoke({"value": 1}, config) == {
+        "value": 2
+    }
+    assert workflow.with_config(recursion_limit=5).invoke(1, config) == 2

libs/langgraph/tests/test_remote_graph.py

@@ -16,11 +16,9 @@ from langgraph_sdk.schema import StreamPart
 from pydantic import BaseModel
 from typing_extensions import TypedDict
 
-from langgraph._internal._constants import CONFIG_KEY_STREAM
 from langgraph.errors import GraphInterrupt
 from langgraph.graph import END, START, MessagesState, StateGraph, add_messages
 from langgraph.pregel import Pregel
-from langgraph.pregel.protocol import StreamProtocol
 from langgraph.pregel.remote import RemoteGraph
 from langgraph.types import Interrupt, StateSnapshot
 from tests.any_str import AnyStr
@@ -865,87 +863,6 @@ async def test_astream_subgraphs_keeps_caller_namespace():
     assert stream_parts == _CALLER_PREFIXED
 
 
-# Subgraph events requested only on behalf of a streaming parent graph
-_PARENT_STREAMED_PARTS = [
-    StreamPart(event="updates|sub:abc", data={"inner": {"chunk": "inner"}}),
-    StreamPart(event="messages|sub:abc", data=[{"content": "token"}, {}]),
-    StreamPart(event="updates", data={"sub": {"chunk": "root"}}),
-]
-
-
-def _parent_streamed_config(parent_parts: list) -> RunnableConfig:
-    return {
-        "configurable": {
-            "thread_id": "thread_1",
-            "checkpoint_ns": "outer:123",
-            CONFIG_KEY_STREAM: StreamProtocol(
-                parent_parts.append, {"updates", "messages"}
-            ),
-        }
-    }
-
-
-def test_stream_without_subgraphs_skips_parent_requested_subgraph_events():
-    mock_sync_client = MagicMock()
-    mock_sync_client.runs.stream.return_value = _PARENT_STREAMED_PARTS
-    remote_pregel = RemoteGraph("test_graph_id", sync_client=mock_sync_client)
-
-    for stream_mode, expected in [
-        ("updates", [{"sub": {"chunk": "root"}}]),
-        # messages are not filtered: the server dedupes them across namespaces
-        ("messages", [({"content": "token"}, {})]),
-    ]:
-        parent_parts: list = []
-        stream_parts = list(
-            remote_pregel.stream(
-                {"input": "data"},
-                _parent_streamed_config(parent_parts),
-                stream_mode=stream_mode,
-            )
-        )
-
-        assert stream_parts == expected
-        # subgraph events are still requested and forwarded to the parent
-        assert mock_sync_client.runs.stream.call_args.kwargs["stream_subgraphs"]
-        assert [ns for ns, _, _ in parent_parts] == [
-            ("outer:123", "sub:abc"),
-            ("outer:123", "sub:abc"),
-            ("outer:123",),
-        ]
-
-
-async def test_astream_without_subgraphs_skips_parent_requested_subgraph_events():
-    mock_async_client = MagicMock()
-    async_iter = MagicMock()
-    async_iter.__aiter__.return_value = _PARENT_STREAMED_PARTS
-    mock_async_client.runs.stream.return_value = async_iter
-    remote_pregel = RemoteGraph("test_graph_id", client=mock_async_client)
-
-    for stream_mode, expected in [
-        ("updates", [{"sub": {"chunk": "root"}}]),
-        # messages are not filtered: the server dedupes them across namespaces
-        ("messages", [({"content": "token"}, {})]),
-    ]:
-        parent_parts: list = []
-        stream_parts = [
-            part
-            async for part in remote_pregel.astream(
-                {"input": "data"},
-                _parent_streamed_config(parent_parts),
-                stream_mode=stream_mode,
-            )
-        ]
-
-        assert stream_parts == expected
-        # subgraph events are still requested and forwarded to the parent
-        assert mock_async_client.runs.stream.call_args.kwargs["stream_subgraphs"]
-        assert [ns for ns, _, _ in parent_parts] == [
-            ("outer:123", "sub:abc"),
-            ("outer:123", "sub:abc"),
-            ("outer:123",),
-        ]
-
-
 def test_invoke():
     # set up test
     mock_sync_client = MagicMock()

libs/langgraph/tests/test_retry.py

@@ -47,7 +47,6 @@ from langgraph.errors import (
 )
 from langgraph.func import entrypoint, task
 from langgraph.graph import END, START, StateGraph, add_messages
-from langgraph.pregel import NodeBuilder, Pregel
 from langgraph.pregel._read import PregelNode
 from langgraph.pregel._retry import (
     _checkpoint_ns_for_parent_command,
@@ -67,6 +66,7 @@ from langgraph.types import (
     TimeoutPolicy,
     interrupt,
 )
+from tests.raw_pregel import NodeBuilder, RawPregel
 
 NEEDS_CONTEXTVARS = pytest.mark.skipif(
     sys.version_info < (3, 11),
@@ -1260,7 +1260,7 @@ def test_pregel_validate_rejects_sync_writer_timeout():
         return value
 
     with pytest.raises(ValueError, match="only supported for async nodes"):
-        Pregel(
+        RawPregel(
             nodes={
                 "slow": PregelNode(
                     channels="input",
@@ -1284,7 +1284,7 @@ def test_pregel_validate_rejects_wrapped_sync_runnable_lambda_timeout():
         return value + 1
 
     with pytest.raises(ValueError, match="only supported for async nodes"):
-        Pregel(
+        RawPregel(
             nodes={
                 "slow": (
                     NodeBuilder()
@@ -1307,7 +1307,7 @@ def test_pregel_validate_accepts_wrapped_async_runnable_lambda_timeout():
     async def slow(value: int) -> int:
         return value + 1
 
-    Pregel(
+    RawPregel(
         nodes={
             "slow": (
                 NodeBuilder()
@@ -1334,7 +1334,7 @@ def test_pregel_validate_rejects_parallel_sync_branch_timeout():
         return value + 1
 
     with pytest.raises(ValueError, match="only supported for async nodes"):
-        Pregel(
+        RawPregel(
             nodes={
                 "parallel": (
                     NodeBuilder()
@@ -1363,7 +1363,7 @@ def test_pregel_validate_rejects_sync_node_timeout():
         return value + 1
 
     with pytest.raises(ValueError, match="only supported for async nodes"):
-        Pregel(
+        RawPregel(
             nodes={
                 "slow": (
                     NodeBuilder()
@@ -1388,7 +1388,7 @@ async def test_pregel_validate_accepts_async_runnable_lambda_timeout():
         await asyncio.sleep(0.2)
         return value + 1
 
-    graph = Pregel(
+    graph = RawPregel(
         nodes={
             "slow": (
                 NodeBuilder()
@@ -1418,7 +1418,7 @@ async def test_pregel_validate_accepts_runnable_callable_with_sync_and_async_tim
         await asyncio.sleep(0.2)
         return value + 1
 
-    graph = Pregel(
+    graph = RawPregel(
         nodes={
             "slow": (
                 NodeBuilder()
@@ -1632,7 +1632,7 @@ async def test_node_builder_timeout_e2e():
         await asyncio.sleep(0.2)
         return value + 1
 
-    graph = Pregel(
+    graph = RawPregel(
         nodes={
             "slow": (
                 NodeBuilder()

libs/langgraph/tests/test_stream_namespaces.py

@@ -1,308 +0,0 @@
-import sys
-from typing import Any
-
-import pytest
-from langchain_core.language_models.fake_chat_models import GenericFakeChatModel
-from langchain_core.messages import AIMessage
-from langchain_core.tools import tool
-
-from langgraph.func import entrypoint, task
-from langgraph.graph import START, MessagesState, StateGraph
-from langgraph.graph.message import push_message
-from langgraph.graph.state import CompiledStateGraph
-
-pytestmark = pytest.mark.anyio
-
-NEEDS_CONTEXTVARS = pytest.mark.skipif(
-    sys.version_info < (3, 11),
-    reason="Python 3.11+ is required for async contextvars support",
-)
-
-
-@tool
-def echo(text: str) -> str:
-    """Echo the text."""
-    return text
-
-
-def _one_node_graph(node: Any) -> CompiledStateGraph:
-    return (
-        StateGraph(MessagesState)
-        .add_node(node)
-        .add_edge(START, node.__name__)
-        .compile()
-    )
-
-
-def _chat_and_echo(state: MessagesState) -> dict:
-    echo.invoke({"text": "done"})
-    return {"messages": [GenericFakeChatModel(messages=iter(["one two"])).invoke("hi")]}
-
-
-async def _achat_and_echo(state: MessagesState) -> dict:
-    await echo.ainvoke({"text": "done"})
-    model = GenericFakeChatModel(messages=iter(["one two"]))
-    return {"messages": [await model.ainvoke("hi")]}
-
-
-def _segment_names(ns: tuple[str, ...]) -> tuple[str, ...]:
-    return tuple(segment.split(":")[0] for segment in ns)
-
-
-def _summary(part: dict) -> tuple[tuple[str, ...], str]:
-    if part["type"] == "messages":
-        return _segment_names(part["ns"]), part["data"][0].content
-    return _segment_names(part["ns"]), part["data"]["event"]
-
-
-_CHAT_AND_ECHO_EVENTS = [
-    ((), "tool-started"),
-    ((), "tool-finished"),
-    ((), "one"),
-    ((), " "),
-    ((), "two"),
-]
-
-_CHILD_CONFIGS = pytest.mark.parametrize(
-    "child_config",
-    [
-        None,
-        {"configurable": {"thread_id": "child"}},
-        {"configurable": {"thread_id": "parent"}},
-    ],
-    ids=["no_config", "own_thread", "caller_thread"],
-)
-
-
-_TASK_CALLERS = pytest.mark.parametrize(
-    "nested", [False, True], ids=["from_entrypoint", "from_task_in_task"]
-)
-
-
-@_TASK_CALLERS
-@pytest.mark.parametrize("subgraphs", [False, True])
-def test_task_events_stream_under_the_graph_namespace(
-    nested: bool, subgraphs: bool
-) -> None:
-    @task
-    def chat_and_echo() -> None:
-        _chat_and_echo({"messages": []})
-
-    @task
-    def outer() -> None:
-        chat_and_echo().result()
-
-    @entrypoint()
-    def workflow(inputs: dict) -> None:
-        (outer() if nested else chat_and_echo()).result()
-
-    parts = workflow.stream(
-        {}, stream_mode=["messages", "tools"], subgraphs=subgraphs, version="v2"
-    )
-
-    assert [_summary(part) for part in parts] == _CHAT_AND_ECHO_EVENTS
-
-
-@NEEDS_CONTEXTVARS
-@_TASK_CALLERS
-@pytest.mark.parametrize("subgraphs", [False, True])
-async def test_task_events_stream_under_the_graph_namespace_async(
-    nested: bool, subgraphs: bool
-) -> None:
-    @task
-    async def chat_and_echo() -> None:
-        await _achat_and_echo({"messages": []})
-
-    @task
-    async def outer() -> None:
-        await chat_and_echo()
-
-    @entrypoint()
-    async def workflow(inputs: dict) -> None:
-        await (outer() if nested else chat_and_echo())
-
-    parts = workflow.astream(
-        {}, stream_mode=["messages", "tools"], subgraphs=subgraphs, version="v2"
-    )
-
-    assert [_summary(part) async for part in parts] == _CHAT_AND_ECHO_EVENTS
-
-
-def test_task_events_stream_under_the_namespace_of_their_subgraph() -> None:
-    @task
-    def chat_and_echo() -> None:
-        _chat_and_echo({"messages": []})
-
-    def node(state: MessagesState) -> dict:
-        chat_and_echo().result()
-        return {}
-
-    sub = _one_node_graph(node)
-    parent = StateGraph(MessagesState).add_node("sub", sub).add_edge(START, "sub")
-
-    parts = parent.compile().stream(
-        {"messages": []},
-        stream_mode=["messages", "tools"],
-        subgraphs=True,
-        version="v2",
-    )
-
-    assert [_summary(part) for part in parts] == [
-        (("sub",), event) for _, event in _CHAT_AND_ECHO_EVENTS
-    ]
-
-
-@_CHILD_CONFIGS
-def test_child_graph_streams_only_to_the_node_streaming_it(
-    child_config: dict | None,
-) -> None:
-    child = _one_node_graph(_chat_and_echo)
-    received = []
-
-    def node(state: MessagesState) -> dict:
-        received.extend(
-            child.stream(
-                {"messages": []}, child_config, stream_mode=["messages", "tools"]
-            )
-        )
-        return {}
-
-    parts = _one_node_graph(node).stream(
-        {"messages": []},
-        {"configurable": {"thread_id": "parent"}},
-        stream_mode=["messages", "tools"],
-    )
-
-    assert list(parts) == []
-    assert len(received) == len(_CHAT_AND_ECHO_EVENTS)
-
-
-@NEEDS_CONTEXTVARS
-@_CHILD_CONFIGS
-async def test_child_graph_streams_only_to_the_node_streaming_it_async(
-    child_config: dict | None,
-) -> None:
-    child = _one_node_graph(_achat_and_echo)
-    received = []
-
-    async def node(state: MessagesState) -> dict:
-        stream = child.astream(
-            {"messages": []}, child_config, stream_mode=["messages", "tools"]
-        )
-        received.extend([part async for part in stream])
-        return {}
-
-    parts = _one_node_graph(node).astream(
-        {"messages": []},
-        {"configurable": {"thread_id": "parent"}},
-        stream_mode=["messages", "tools"],
-    )
-
-    assert [part async for part in parts] == []
-    assert len(received) == len(_CHAT_AND_ECHO_EVENTS)
-
-
-@pytest.mark.parametrize(
-    "child_config",
-    [
-        {"configurable": {"thread_id": "child"}},
-        {"configurable": {"thread_id": "parent"}},
-    ],
-    ids=["own_thread", "caller_thread"],
-)
-def test_child_graph_on_its_own_thread_skips_a_caller_streaming_subgraphs(
-    child_config: dict,
-) -> None:
-    child = _one_node_graph(_chat_and_echo)
-
-    def node(state: MessagesState) -> dict:
-        child.invoke({"messages": []}, child_config)
-        return {}
-
-    parts = _one_node_graph(node).stream(
-        {"messages": []},
-        {"configurable": {"thread_id": "parent"}},
-        stream_mode=["messages", "tools"],
-        subgraphs=True,
-    )
-
-    assert list(parts) == []
-
-
-def test_node_gets_the_events_of_every_subgraph_it_streams() -> None:
-    sub = _one_node_graph(_chat_and_echo)
-    counts = []
-
-    def node(state: MessagesState) -> dict:
-        for _ in range(2):
-            stream = sub.stream({"messages": []}, stream_mode=["messages", "tools"])
-            counts.append(len(list(stream)))
-        return {}
-
-    _one_node_graph(node).invoke({"messages": []})
-
-    assert counts == [len(_CHAT_AND_ECHO_EVENTS)] * 2
-
-
-@NEEDS_CONTEXTVARS
-async def test_node_gets_the_events_of_every_subgraph_it_streams_async() -> None:
-    sub = _one_node_graph(_achat_and_echo)
-    counts = []
-
-    async def node(state: MessagesState) -> dict:
-        for _ in range(2):
-            stream = sub.astream({"messages": []}, stream_mode=["messages", "tools"])
-            counts.append(len([part async for part in stream]))
-        return {}
-
-    await _one_node_graph(node).ainvoke({"messages": []})
-
-    assert counts == [len(_CHAT_AND_ECHO_EVENTS)] * 2
-
-
-def _push(state: MessagesState) -> dict:
-    push_message(AIMessage(id="pushed", content="hi"), state_key=None)
-    return {}
-
-
-def _namespaces(graph: CompiledStateGraph, subgraphs: bool) -> list[tuple[str, ...]]:
-    parts = graph.stream(
-        {"messages": []}, stream_mode="messages", subgraphs=subgraphs, version="v2"
-    )
-    return [_segment_names(part["ns"]) for part in parts]
-
-
-def _streams_pushing_graph(received: list) -> Any:
-    pushing = _one_node_graph(_push)
-
-    def node(state: MessagesState) -> dict:
-        for message, _ in pushing.stream({"messages": []}, stream_mode="messages"):
-            received.append(message.id)
-        return {}
-
-    return node
-
-
-def test_pushed_message_streams_under_the_namespace_of_its_graph() -> None:
-    pushing = _one_node_graph(_push)
-    parent = StateGraph(MessagesState).add_node("sub", pushing).add_edge(START, "sub")
-
-    assert _namespaces(pushing, subgraphs=True) == [()]
-    assert _namespaces(parent.compile(), subgraphs=False) == []
-    assert _namespaces(parent.compile(), subgraphs=True) == [("sub",)]
-
-
-def test_pushed_message_streams_to_the_node_that_streams_its_graph() -> None:
-    received: list[str] = []
-    graph = _one_node_graph(_streams_pushing_graph(received))
-
-    assert _namespaces(graph, subgraphs=False) == []
-    assert received == ["pushed"]
-
-
-def test_pushed_message_streams_to_every_stream_that_takes_it() -> None:
-    received: list[str] = []
-    graph = _one_node_graph(_streams_pushing_graph(received))
-
-    assert _namespaces(graph, subgraphs=True) == [("node",)]
-    assert received == ["pushed"]

libs/sdk-py/langgraph_sdk/auth/__init__.py

@@ -811,7 +811,7 @@ class _On:
     def __call__(
         self,
         *,
-        resources: str | Sequence[str] | None = None,
+        resources: str | Sequence[str],
         actions: str | Sequence[str] | None = None,
     ) -> Callable[[AHO], AHO]: ...
 

libs/sdk-py/tests/test_auth.py

@@ -1,49 +1,8 @@
-import ast
-import inspect
-
 import pytest
 
 from langgraph_sdk import Auth
 
 
-@pytest.mark.parametrize(
-    "kwargs",
-    [{}, {"actions": "read"}, {"resources": None}],
-)
-def test_global_handler_factory_accepts_optional_resources(kwargs) -> None:
-    auth = Auth()
-    tree = ast.parse(inspect.getsource(type(auth.on)))
-    cls = tree.body[0]
-    assert isinstance(cls, ast.ClassDef)
-    factory_overload = next(
-        node
-        for node in cls.body
-        if isinstance(node, ast.FunctionDef)
-        and node.name == "__call__"
-        and node.decorator_list
-        and any(arg.arg == "resources" for arg in node.args.kwonlyargs)
-    )
-    resources = next(
-        arg for arg in factory_overload.args.kwonlyargs if arg.arg == "resources"
-    )
-    assert resources.annotation is not None
-    assert ast.unparse(resources.annotation) == "str | Sequence[str] | None"
-    default = factory_overload.args.kw_defaults[0]
-    assert isinstance(default, ast.Constant) and default.value is None
-
-    @auth.on(**kwargs)
-    async def handler(ctx, value):
-        del ctx, value
-        return None
-
-    if kwargs.get("actions"):
-        assert auth._handlers == {("*", "read"): [handler]}
-        assert auth._global_handlers == []
-    else:
-        assert auth._global_handlers == [handler]
-        assert auth._handlers == {}
-
-
 def test_handler_multiple_resources_and_actions() -> None:
     auth = Auth()