Merge branch 'main' into wfh/return_direct

libs/langgraph/langgraph/constants.py

@@ -1,11 +1,13 @@
 from dataclasses import dataclass
-from typing import Any, Literal
+from types import MappingProxyType
+from typing import Any, Literal, Mapping
 
 INPUT = "__input__"
 CONFIG_KEY_SEND = "__pregel_send"
 CONFIG_KEY_READ = "__pregel_read"
 CONFIG_KEY_CHECKPOINTER = "__pregel_checkpointer"
 CONFIG_KEY_STREAM = "__pregel_stream"
+CONFIG_KEY_STREAM_WRITER = "__pregel_stream_writer"
 CONFIG_KEY_STORE = "__pregel_store"
 CONFIG_KEY_RESUMING = "__pregel_resuming"
 CONFIG_KEY_TASK_ID = "__pregel_task_id"
@@ -34,6 +36,8 @@
     CONFIG_KEY_READ,
     CONFIG_KEY_CHECKPOINTER,
     CONFIG_KEY_CHECKPOINT_MAP,
+    CONFIG_KEY_STREAM,
+    CONFIG_KEY_STREAM_WRITER,
     CONFIG_KEY_STORE,
     CONFIG_KEY_RESUMING,
     CONFIG_KEY_TASK_ID,
@@ -51,6 +55,8 @@
 NS_SEP = "|"
 NS_END = ":"
 
+EMPTY_MAP: Mapping[str, Any] = MappingProxyType({})
+
 
 class Send:
     """A message or packet to send to a specific node in the graph.

libs/langgraph/langgraph/pregel/__init__.py

@@ -60,6 +60,7 @@
     CONFIG_KEY_RESUMING,
     CONFIG_KEY_SEND,
     CONFIG_KEY_STREAM,
+    CONFIG_KEY_STREAM_WRITER,
     CONFIG_KEY_TASK_ID,
     INTERRUPT,
     NS_END,
@@ -1219,6 +1220,11 @@ def output() -> Iterator:
                 run_manager.inheritable_handlers.append(
                     StreamMessagesHandler(stream.put)
                 )
+            # set up custom stream mode
+            if "custom" in stream_modes:
+                config["configurable"][CONFIG_KEY_STREAM_WRITER] = lambda c: stream.put(
+                    ((), "custom", c)
+                )
             with SyncPregelLoop(
                 input,
                 stream=StreamProtocol(stream.put, stream_modes),
@@ -1240,7 +1246,7 @@ def output() -> Iterator:
                 if subgraphs:
                     loop.config["configurable"][CONFIG_KEY_STREAM] = loop.stream
                 # enable concurrent streaming
-                if subgraphs or "messages" in stream_modes:
+                if subgraphs or "messages" in stream_modes or "custom" in stream_modes:
                     # we are careful to have a single waiter live at any one time
                     # because on exit we increment semaphore count by exactly 1
                     waiter: Optional[concurrent.futures.Future] = None
@@ -1435,6 +1441,11 @@ def output() -> Iterator:
                 run_manager.inheritable_handlers.append(
                     StreamMessagesHandler(stream.put_nowait)
                 )
+            # set up custom stream mode
+            if "custom" in stream_modes:
+                config["configurable"][CONFIG_KEY_STREAM_WRITER] = (
+                    lambda c: stream.put_nowait(((), "custom", c))
+                )
             async with AsyncPregelLoop(
                 input,
                 stream=StreamProtocol(stream.put_nowait, stream_modes),
@@ -1456,7 +1467,7 @@ def output() -> Iterator:
                 if subgraphs:
                     loop.config["configurable"][CONFIG_KEY_STREAM] = loop.stream
                 # enable concurrent streaming
-                if subgraphs or "messages" in stream_modes:
+                if subgraphs or "messages" in stream_modes or "custom" in stream_modes:
 
                     def get_waiter() -> asyncio.Task[None]:
                         return aioloop.create_task(stream.wait())

libs/langgraph/langgraph/pregel/algo.py

@@ -35,6 +35,7 @@
     CONFIG_KEY_TASK_ID,
     INTERRUPT,
     NO_WRITES,
+    NS_END,
     NS_SEP,
     PULL,
     PUSH,
@@ -487,7 +488,7 @@ def prepare_single_task(
                 PULL,
                 *triggers,
             )
-            task_checkpoint_ns = f"{checkpoint_ns}:{task_id}"
+            task_checkpoint_ns = f"{checkpoint_ns}{NS_END}{task_id}"
             metadata = {
                 "langgraph_step": step,
                 "langgraph_node": name,

libs/langgraph/langgraph/pregel/types.py

@@ -107,12 +107,18 @@ class StateSnapshot(NamedTuple):
 
 All = Literal["*"]
 
-StreamMode = Literal["values", "updates", "debug", "messages"]
+StreamMode = Literal["values", "updates", "debug", "messages", "custom"]
 """How the stream method should emit outputs.
 
 - 'values': Emit all values of the state for each step.
 - 'updates': Emit only the node name(s) and updates
     that were returned by the node(s) **after** each step.
 - 'debug': Emit debug events for each step.
 - 'messages': Emit LLM messages token-by-token.
+- 'custom': Emit custom output `write: StreamWriter` kwarg of each node.
 """
+
+StreamWriter = Callable[[Any], None]
+"""Callable that accepts a single argument and writes it to the output stream.
+Always injected into nodes if requested,
+but it's a no-op when not using stream_mode="custom"."""

libs/langgraph/langgraph/utils/runnable.py

@@ -30,10 +30,12 @@
     run_in_executor,
     var_child_runnable_config,
 )
-from langchain_core.runnables.utils import Input, accepts_config
+from langchain_core.runnables.utils import Input
 from langchain_core.tracers._streaming import _StreamingCallbackHandler
 from typing_extensions import TypeGuard
 
+from langgraph.constants import CONFIG_KEY_STREAM_WRITER
+from langgraph.pregel.types import StreamWriter
 from langgraph.utils.config import (
     ensure_config,
     get_async_callback_manager_for_config,
@@ -57,6 +59,19 @@ class StrEnum(str, enum.Enum):
 
 ASYNCIO_ACCEPTS_CONTEXT = sys.version_info >= (3, 11)
 
+KWARGS_CONFIG_KEYS: tuple[tuple[str, tuple[Any, ...], str, Any], ...] = (
+    (
+        sys.intern("writer"),
+        (StreamWriter, inspect.Parameter.empty),
+        CONFIG_KEY_STREAM_WRITER,
+        lambda _: None,
+    ),
+)
+"""List of kwargs that can be passed to functions, and their corresponding
+config keys, default values and type annotations."""
+
+VALID_KINDS = (inspect.Parameter.POSITIONAL_OR_KEYWORD, inspect.Parameter.KEYWORD_ONLY)
+
 
 class RunnableCallable(Runnable):
     """A much simpler version of RunnableLambda that requires sync and async functions."""
@@ -86,15 +101,22 @@ def __init__(
                 except AttributeError:
                     pass
         self.func = func
-        if func is not None:
-            self.func_accepts_config = accepts_config(func)
         self.afunc = afunc
-        if afunc is not None:
-            self.afunc_accepts_config = accepts_config(afunc)
         self.tags = tags
         self.kwargs = kwargs
         self.trace = trace
         self.recurse = recurse
+        # check signature
+        if func is None and afunc is None:
+            raise ValueError("At least one of func or afunc must be provided.")
+        params = inspect.signature(cast(Callable, func or afunc)).parameters
+        self.func_accepts_config = "config" in params
+        self.func_accepts: dict[str, bool] = {}
+        for kw, typ, _, _ in KWARGS_CONFIG_KEYS:
+            p = params.get(kw)
+            self.func_accepts[kw] = (
+                p is not None and p.annotation in typ and p.kind in VALID_KINDS
+            )
 
     def __repr__(self) -> str:
         repr_args = {
@@ -113,11 +135,14 @@ def invoke(
                 "\nEither initialize with a synchronous function or invoke"
                 " via the async API (ainvoke, astream, etc.)"
             )
+        if config is None:
+            config = ensure_config()
         kwargs = {**self.kwargs, **kwargs}
         if self.func_accepts_config:
             kwargs["config"] = config
-        if config is None:
-            config = ensure_config()
+        for kw, _, ck, defv in KWARGS_CONFIG_KEYS:
+            if self.func_accepts[kw]:
+                kwargs[kw] = config["configurable"].get(ck, defv)
         context = copy_context()
         if self.trace:
             callback_manager = get_callback_manager_for_config(config, self.tags)
@@ -149,11 +174,14 @@ async def ainvoke(
     ) -> Any:
         if not self.afunc:
             return self.invoke(input, config)
-        kwargs = {**self.kwargs, **kwargs}
-        if self.afunc_accepts_config:
-            kwargs["config"] = config
         if config is None:
             config = ensure_config()
+        kwargs = {**self.kwargs, **kwargs}
+        if self.func_accepts_config:
+            kwargs["config"] = config
+        for kw, _, ck, defv in KWARGS_CONFIG_KEYS:
+            if self.func_accepts[kw]:
+                kwargs[kw] = config["configurable"].get(ck, defv)
         context = copy_context()
         if self.trace:
             callback_manager = get_async_callback_manager_for_config(config, self.tags)

libs/langgraph/tests/test_prebuilt.py

@@ -153,29 +153,35 @@ def test_passing_two_modifiers():
 
 
 def test_system_message_modifier():
-    model = FakeToolCallingModel()
     messages_modifier = SystemMessage(content="Foo")
-    agent_1 = create_react_agent(model, [], messages_modifier=messages_modifier)
-    agent_2 = create_react_agent(model, [], state_modifier=messages_modifier)
+    agent_1 = create_react_agent(
+        FakeToolCallingModel(), [], messages_modifier=messages_modifier
+    )
+    agent_2 = create_react_agent(
+        FakeToolCallingModel(), [], state_modifier=messages_modifier
+    )
     for agent in [agent_1, agent_2]:
         inputs = [HumanMessage("hi?")]
         response = agent.invoke({"messages": inputs})
         expected_response = {
-            "messages": inputs + [AIMessage(content="Foo-hi?", id="0")]
+            "messages": inputs + [AIMessage(content="Foo-hi?", id="0", tool_calls=[])]
         }
         assert response == expected_response
 
 
 def test_system_message_string_modifier():
-    model = FakeToolCallingModel()
     messages_modifier = "Foo"
-    agent_1 = create_react_agent(model, [], messages_modifier=messages_modifier)
-    agent_2 = create_react_agent(model, [], state_modifier=messages_modifier)
+    agent_1 = create_react_agent(
+        FakeToolCallingModel(), [], messages_modifier=messages_modifier
+    )
+    agent_2 = create_react_agent(
+        FakeToolCallingModel(), [], state_modifier=messages_modifier
+    )
     for agent in [agent_1, agent_2]:
         inputs = [HumanMessage("hi?")]
         response = agent.invoke({"messages": inputs})
         expected_response = {
-            "messages": inputs + [AIMessage(content="Foo-hi?", id="0")]
+            "messages": inputs + [AIMessage(content="Foo-hi?", id="0", tool_calls=[])]
         }
         assert response == expected_response
 

libs/langgraph/tests/test_pregel.py

@@ -70,7 +70,7 @@
     StateSnapshot,
 )
 from langgraph.pregel.retry import RetryPolicy
-from langgraph.pregel.types import PregelTask
+from langgraph.pregel.types import PregelTask, StreamWriter
 from langgraph.store.memory import MemoryStore
 from tests.any_str import AnyDict, AnyStr, AnyVersion, UnsortedSequence
 from tests.conftest import ALL_CHECKPOINTERS_SYNC, SHOULD_CHECK_SNAPSHOTS
@@ -10440,11 +10440,13 @@ def get_weather(city: str):
     class SubGraphState(MessagesState):
         city: str
 
-    def model_node(state: SubGraphState):
+    def model_node(state: SubGraphState, writer: StreamWriter):
+        writer(" very")
         result = weather_model.invoke(state["messages"])
         return {"city": cast(AIMessage, result).tool_calls[0]["args"]["city"]}
 
-    def weather_node(state: SubGraphState):
+    def weather_node(state: SubGraphState, writer: StreamWriter):
+        writer(" good")
         result = get_weather.invoke({"city": state["city"]})
         return {"messages": [{"role": "assistant", "content": result}]}
 
@@ -10479,7 +10481,8 @@ class Router(TypedDict):
         ]
     )
 
-    def router_node(state: RouterState):
+    def router_node(state: RouterState, writer: StreamWriter):
+        writer("I'm")
         system_message = "Classify the incoming query as either about weather or not."
         messages = [{"role": "system", "content": system_message}] + state["messages"]
         route = router_model.invoke(messages)
@@ -10510,8 +10513,18 @@ def weather_graph(state: RouterState):
     assert graph.get_graph(xray=1).draw_mermaid() == snapshot
 
     config = {"configurable": {"thread_id": "1"}}
+    thread2 = {"configurable": {"thread_id": "2"}}
     inputs = {"messages": [{"role": "user", "content": "what's the weather in sf"}]}
 
+    # run with custom output
+    assert [c for c in graph.stream(inputs, thread2, stream_mode="custom")] == [
+        "I'm",
+        " very",
+    ]
+    assert [c for c in graph.stream(None, thread2, stream_mode="custom")] == [
+        " good",
+    ]
+
     # run until interrupt
     assert [
         c

libs/langgraph/tests/test_pregel_async.py

@@ -68,7 +68,7 @@
     StateSnapshot,
 )
 from langgraph.pregel.retry import RetryPolicy
-from langgraph.pregel.types import PregelTask
+from langgraph.pregel.types import PregelTask, StreamWriter
 from langgraph.store.memory import MemoryStore
 from tests.any_str import AnyDict, AnyStr, AnyVersion, UnsortedSequence
 from tests.conftest import (
@@ -9051,11 +9051,13 @@ def get_weather(city: str):
     class SubGraphState(MessagesState):
         city: str
 
-    def model_node(state: SubGraphState):
+    def model_node(state: SubGraphState, writer: StreamWriter):
+        writer(" very")
         result = weather_model.invoke(state["messages"])
         return {"city": cast(AIMessage, result).tool_calls[0]["args"]["city"]}
 
-    def weather_node(state: SubGraphState):
+    def weather_node(state: SubGraphState, writer: StreamWriter):
+        writer(" good")
         result = get_weather.invoke({"city": state["city"]})
         return {"messages": [{"role": "assistant", "content": result}]}
 
@@ -9090,7 +9092,8 @@ class Router(TypedDict):
         ]
     )
 
-    def router_node(state: RouterState):
+    def router_node(state: RouterState, writer: StreamWriter):
+        writer("I'm")
         system_message = "Classify the incoming query as either about weather or not."
         messages = [{"role": "system", "content": system_message}] + state["messages"]
         route = router_model.invoke(messages)
@@ -9128,8 +9131,22 @@ def get_first_in_list():
         assert graph.get_graph(xray=1).draw_mermaid() == snapshot
 
         config = {"configurable": {"thread_id": "1"}}
+        thread2 = {"configurable": {"thread_id": "2"}}
         inputs = {"messages": [{"role": "user", "content": "what's the weather in sf"}]}
 
+        # run with custom output
+        assert [
+            c async for c in graph.astream(inputs, thread2, stream_mode="custom")
+        ] == [
+            "I'm",
+            " very",
+        ]
+        assert [
+            c async for c in graph.astream(None, thread2, stream_mode="custom")
+        ] == [
+            " good",
+        ]
+
         # run until interrupt
         assert [
             c