docs(langgraph): rewrite stream_v2 references to stream_events v3

Update all docstrings and comments in production code that referred to
stream_v2/astream_v2 to use stream_events(version="v3") /
astream_events(version="v3") instead.

libs/langgraph/langgraph/graph/state.py

@@ -1128,7 +1128,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
             name: The name to use for the compiled graph.
             transformers: Optional sequence of `StreamTransformer` classes or
                 configured factories. Classes and factories are instantiated
-                per run whenever `stream_v2` / `astream_v2` is called and are
+                per run whenever `stream_events(version="v3")` / `astream_events(version="v3")` is called and are
                 propagated to subgraph scopes. Custom factories should follow
                 the standard `StreamTransformer` constructor shape by
                 accepting `scope` as their first argument. Appended after the

libs/langgraph/langgraph/pregel/_messages.py

@@ -349,7 +349,7 @@ class StreamMessagesHandlerV2(StreamMessagesHandler, _V2StreamingCallbackHandler
         tags: list[str] | None = None,
         **kwargs: Any,
     ) -> Any:
-        """Forward a protocol event from `stream_v2` as a messages stream part.
+        """Forward a protocol event from `stream_events(version="v3")` as a messages stream part.
 
         Fires once per `MessagesData` event (`message-start`, per-block
         `content-block-*`, `message-finish`). The transformer layer

libs/langgraph/langgraph/pregel/main.py

@@ -378,7 +378,7 @@ def _collect_stream_modes(mux: Any) -> list[StreamMode]:
     """Return the union of `required_stream_modes` across registered transformers.
 
     Transformers declare the stream modes they need to function, and
-    `stream_v2` asks the graph for exactly that union — no hardcoded
+    `stream_events(version="v3")` asks the graph for exactly that union — no hardcoded
     default set. If zero transformers declare a given mode, the graph
     does not stream events for it.
     """
@@ -408,14 +408,14 @@ def _normalize_stream_transformer_factories(
     for spec in specs or ():
         if isinstance(spec, StreamTransformer):
             raise TypeError(
-                "stream_v2 transformers must be scope-aware callables, "
+                "stream_events(version='v3') transformers must be scope-aware callables, "
                 f"got pre-built instance {type(spec).__name__}. Pass the "
                 "transformer class or a factory like "
                 "`lambda scope: MyTransformer(scope, ...)`."
             )
         if not callable(spec):
             raise TypeError(
-                "stream_v2 transformers must be scope-aware callables, "
+                "stream_events(version='v3') transformers must be scope-aware callables, "
                 f"got {type(spec).__name__}."
             )
 
@@ -4145,7 +4145,7 @@ def _resolve_parent_ns(
 ) -> tuple[str, ...]:
     """Return the checkpoint namespace the caller is running under.
 
-    `stream_v2` uses this to scope its native projections
+    `stream_events(version="v3")` uses this to scope its native projections
     (`ValuesTransformer`, `MessagesTransformer`) to events emitted at
     the run's own level. A root call resolves to `()`; a call made
     from inside a node carries the outer graph's task namespace so the

libs/langgraph/langgraph/stream/__init__.py

@@ -1,7 +1,7 @@
 """Streaming infrastructure for LangGraph.
 
-Compile a graph with `transformers=[...]` and call `graph.stream_v2()` /
-`graph.astream_v2()` to drive a transformer pipeline that projects the
+Compile a graph with `transformers=[...]` and call `graph.stream_events(version="v3")` /
+`graph.astream_events(version="v3")` to drive a transformer pipeline that projects the
 graph's raw events into ergonomic per-channel streams.
 """
 

libs/langgraph/langgraph/stream/_types.py

@@ -88,7 +88,7 @@ class StreamTransformer(ABC):
         required_stream_modes: Stream modes the graph must emit for
             this transformer to have anything to process. Computed as
             the union across all registered transformers to determine
-            which modes a `stream_v2` run requests from the graph.
+            which modes a `stream_events(version="v3")` run requests from the graph.
             Empty tuple means the transformer consumes only synthetic
             events (or is purely passive).
     """

libs/langgraph/langgraph/stream/transformers.py

@@ -38,8 +38,8 @@ class ValuesTransformer(StreamTransformer):
     Only values events at the run's own level are captured; snapshots
     from deeper subgraphs are left in the main event log but excluded
     from the projection. "Own level" is defined by `scope`, which
-    `stream_v2` / `astream_v2` populate from the caller's
-    checkpoint namespace so that a nested `stream_v2` call still
+    `stream_events(version="v3")` / `astream_events(version="v3")` populate from the caller's
+    checkpoint namespace so that a nested `stream_events(version="v3")` call still
     sees its own root snapshots.
     """
 
@@ -165,7 +165,7 @@ class MessagesTransformer(StreamTransformer):
     metadata)` from `StreamMessagesHandler`):
 
     1. Protocol event (dict with `"event"` key) — emitted by
-       `stream_v2()` / `astream_v2()` via the `on_stream_event`
+       `stream_events(version="v3")` / `astream_events(version="v3")` via the `on_stream_event`
        callback. Routed to an existing `ChatModelStream` by
        `metadata["run_id"]`. A `message-start` event creates a new
        stream; `message-finish` closes it.
@@ -177,15 +177,15 @@ class MessagesTransformer(StreamTransformer):
     V1 `AIMessageChunk` tuples (from `on_llm_new_token`) are not
     streamed into this projection: chat models that want to populate
     `run.messages` with content-block streaming must use
-    `stream_v2()` / `astream_v2()`. Models called via the legacy
+    `stream_events(version="v3")` / `astream_events(version="v3")`. Models called via the legacy
     `stream()` method still surface their final `AIMessage` via
     `on_chain_end` when a node returns it as state.
 
     Only events at the run's own level are projected; tokens from
     deeper subgraphs are left in the main event log but excluded from
     `.messages`. "Own level" is defined by `scope`, which
-    `stream_v2` / `astream_v2` populate from the caller's checkpoint
-    namespace so that a `stream_v2` call inside a node still sees its
+    `stream_events(version="v3")` / `astream_events(version="v3")` populate from the caller's checkpoint
+    namespace so that a `stream_events(version="v3")` call inside a node still sees its
     own root chat model streams on `.messages`. Consumers that need
     subgraph tokens should iterate the raw event stream or register a
     custom transformer.
@@ -281,7 +281,7 @@ class MessagesTransformer(StreamTransformer):
         ):
             self._route_whole_message(payload, node=node)
         # Legacy AIMessageChunk tuples (from on_llm_new_token) are ignored;
-        # v1 streaming callers must switch to stream_v2() to populate this
+        # v1 streaming callers must switch to stream_events(version="v3") to populate this
         # projection.
 
         return True