docs: internal doc nits

libs/langgraph/langgraph/graph/graph.py

@@ -1,4 +1,4 @@
 import asyncio
 import logging
 from collections import defaultdict
 from typing import (
@@ -257,7 +257,7 @@
                 selected by `path`.
 
         Returns:
-            None
+            Self: The instance of the graph, allowing for method chaining.
 
         Note: Without typehints on the `path` function's return value (e.g., `-> Literal["foo", "__end__"]:`)
             or a path_map, the graph visualization assumes the edge could transition to any node in the graph.
@@ -308,7 +308,7 @@
             key (str): The key of the node to set as the entry point.
 
         Returns:
-            None
+            Self: The instance of the graph, allowing for method chaining.
         """
         return self.add_edge(START, key)
 
@@ -334,7 +334,7 @@
                 selected by `path`.
 
         Returns:
-            None
+            Self: The instance of the graph, allowing for method chaining.
         """
         return self.add_conditional_edges(START, path, path_map, then)
 
@@ -347,7 +347,7 @@
             key (str): The key of the node to set as the finish point.
 
         Returns:
-            None
+            Self: The instance of the graph, allowing for method chaining.
         """
         return self.add_edge(key, END)
 

libs/langgraph/langgraph/graph/state.py

@@ -107,7 +107,6 @@ class StateGraph(Graph):
         config_schema (Optional[Type[Any]]): The schema class that defines the configuration.
             Use this to expose configurable parameters in your API.
 
-
     Examples:
         >>> from langchain_core.runnables import RunnableConfig
         >>> from typing_extensions import Annotated, TypedDict
@@ -243,7 +242,7 @@ def add_node(
             ValueError: If the key is already being used as a state key.
 
         Returns:
-            StateGraph
+            Self: The instance of the state graph, allowing for method chaining.
         """
         ...
 
@@ -267,7 +266,7 @@ def add_node(
             ValueError: If the key is already being used as a state key.
 
         Returns:
-            StateGraph
+            Self: The instance of the state graph, allowing for method chaining.
         """
         ...
 
@@ -290,10 +289,10 @@ def add_node(
             metadata (Optional[dict[str, Any]]): The metadata associated with the node. (default: None)
             input (Optional[Type[Any]]): The input schema for the node. (default: the graph's input schema)
             retry (Optional[RetryPolicy]): The policy for retrying the node. (default: None)
+
         Raises:
             ValueError: If the key is already being used as a state key.
 
-
         Examples:
             ```pycon
             >>> from langgraph.graph import START, StateGraph
@@ -320,7 +319,7 @@ def add_node(
             ```
 
         Returns:
-            StateGraph
+            Self: The instance of the state graph, allowing for method chaining.
         """
         if not isinstance(node, str):
             action = node
@@ -416,7 +415,7 @@ def add_edge(self, start_key: Union[str, list[str]], end_key: str) -> Self:
             ValueError: If the start key is 'END' or if the start key or end key is not present in the graph.
 
         Returns:
-            StateGraph
+            Self: The instance of the state graph, allowing for method chaining.
         """
         if isinstance(start_key, str):
             return super().add_edge(start_key, end_key)
@@ -455,7 +454,7 @@ def add_sequence(
             ValueError: if the sequence contains duplicate node names.
 
         Returns:
-            StateGraph
+            Self: The instance of the state graph, allowing for method chaining.
         """
         if len(nodes) < 1:
             raise ValueError("Sequence requires at least one node.")

libs/langgraph/langgraph/pregel/__init__.py

@@ -1652,10 +1652,10 @@ def get_waiter() -> concurrent.futures.Future[None]:
                 else:
                     get_waiter = None  # type: ignore[assignment]
                 # Similarly to Bulk Synchronous Parallel / Pregel model
-                # computation proceeds in steps, while there are channel updates
-                # channel updates from step N are only visible in step N+1
+                # computation proceeds in steps, while there are channel updates.
+                # Channel updates from step N are only visible in step N+1
                 # channels are guaranteed to be immutable for the duration of the step,
-                # with channel updates applied only at the transition between steps
+                # with channel updates applied only at the transition between steps.
                 while loop.tick(input_keys=self.input_channels):
                     for _ in runner.tick(
                         loop.tasks.values(),

libs/langgraph/langgraph/pregel/call.py

@@ -1,3 +1,5 @@
+"""Utility to convert a user provided function into a Runnable with a ChannelWrite."""
+
 import sys
 import types
 from typing import Any, Callable, Optional
@@ -6,10 +8,9 @@
 from langgraph.pregel.write import ChannelWrite, ChannelWriteEntry
 from langgraph.utils.runnable import RunnableSeq, coerce_to_runnable
 
-"""
-Utilities borrowed from cloudpickle.
-https://github.com/cloudpipe/cloudpickle/blob/6220b0ce83ffee5e47e06770a1ee38ca9e47c850/cloudpickle/cloudpickle.py#L265
-"""
+##
+# Utilities borrowed from cloudpickle.
+# https://github.com/cloudpipe/cloudpickle/blob/6220b0ce83ffee5e47e06770a1ee38ca9e47c850/cloudpickle/cloudpickle.py#L265
 
 
 def _getattribute(obj: Any, name: str) -> Any:

libs/langgraph/langgraph/pregel/executor.py

@@ -51,6 +51,7 @@ class BackgroundExecutor(ContextManager):
     def __init__(self, config: RunnableConfig) -> None:
         self.stack = ExitStack()
         self.executor = self.stack.enter_context(get_executor_for_config(config))
+        # mapping of Future to (__cancel_on_exit__, __reraise_on_exit__) flags
         self.tasks: dict[concurrent.futures.Future, tuple[bool, bool]] = {}
 
     def submit(  # type: ignore[valid-type]
@@ -68,10 +69,12 @@ def submit(  # type: ignore[valid-type]
         else:
             task = self.executor.submit(fn, *args, **kwargs)
         self.tasks[task] = (__cancel_on_exit__, __reraise_on_exit__)
+        # add a callback to remove the task from the tasks dict when it's done
         task.add_done_callback(self.done)
         return task
 
     def done(self, task: concurrent.futures.Future) -> None:
+        """Remove the task from the tasks dict when it's done."""
         try:
             task.result()
         except GraphBubbleUp:
@@ -103,9 +106,9 @@ def __exit__(
             concurrent.futures.wait(pending)
         # shutdown the executor
         self.stack.__exit__(exc_type, exc_value, traceback)
-        # re-raise the first exception that occurred in a task
+        # if there's already an exception being raised, don't raise another one
         if exc_type is None:
-            # if there's already an exception being raised, don't raise another one
+            # re-raise the first exception that occurred in a task
             for task, (_, reraise) in tasks.items():
                 if not reraise:
                     continue

libs/langgraph/langgraph/pregel/loop.py

@@ -359,7 +359,13 @@ def tick(
         input_keys: Union[str, Sequence[str]],
     ) -> bool:
         """Execute a single iteration of the Pregel loop.
-        Returns True if more iterations are needed."""
+
+        Args:
+            input_keys: The key(s) to read input from.
+
+        Returns:
+            True if more iterations are needed.
+        """
         if self.status != "pending":
             raise RuntimeError("Cannot tick when status is no longer 'pending'")
 

libs/langgraph/langgraph/utils/runnable.py

@@ -298,21 +298,22 @@ def coerce_to_runnable(
 
 
 class RunnableSeq(Runnable):
-    """A simpler version of RunnableSequence."""
+    """Sequence of Runnables, where the output of each is the input of the next.
+
+    RunnableSeq is a simpler version of RunnableSequence that is internal to
+    LangGraph.
+    """
 
     def __init__(
         self,
         *steps: RunnableLike,
         name: Optional[str] = None,
     ) -> None:
-        """Create a new RunnableSequence.
+        """Create a new RunnableSeq.
 
         Args:
             steps: The steps to include in the sequence.
             name: The name of the Runnable. Defaults to None.
-            first: The first Runnable in the sequence. Defaults to None.
-            middle: The middle Runnables in the sequence. Defaults to None.
-            last: The last Runnable in the sequence. Defaults to None.
 
         Raises:
             ValueError: If the sequence has less than 2 steps.