Merge branch 'main' into get-started

docs/docs/cloud/deployment/cloud.md

@@ -62,6 +62,15 @@ Starting from the `LangGraph Platform` view...
 1. In the panel, select the `Server` tab to view server logs for the revision. Server logs are only available after a revision has been deployed.
 1. Within the `Server` tab, adjust the date/time range picker as needed. By default, the date/time range picker is set to the `Last 7 days`.
 
+## View Deployment Metrics
+
+Starting from the <a href="https://smith.langchain.com/" target="_blank">LangSmith UI</a>...
+
+1. In the left-hand navigation panel, select `LangGraph Platform`. The `LangGraph Platform` view contains a list of existing LangGraph Platform deployments.
+1. Select an existing deployment to monitor.
+1. Select the `Monitoring` tab to view the deployment metrics. See a list of [all available metrics](../../concepts/langgraph_control_plane.md#monitoring).
+1. Within the `Monitoring` tab, use the date/time range picker as needed. By default, the date/time range picker is set to the `Last 15 minutes`.
+
 ## Interrupt Revision
 
 Interrupting a revision will stop deployment of the revision.

docs/docs/cloud/how-tos/studio/run_evals.md

@@ -0,0 +1,57 @@
+# Run experiments over a dataset
+
+LangGraph Studio supports evaluations by allowing you to run your assistant over a pre-defined LangSmith dataset. This enables you to understand how your application performs over a variety of inputs, compare the results to reference outputs, and score the results using [evaluators](../../../agents/evals.md).
+
+This guide shows you how to run an experiment end-to-end from Studio.
+
+---
+
+## Prerequisites
+
+Before running an experiment, ensure you have the following:
+
+1.  **A LangSmith dataset**: Your dataset should contain the inputs you want to test and optionally, reference outputs for comparison.
+
+    - The schema for the inputs must match the required input schema for the assistant. For more information on schemas, see [here](../../../concepts/low_level.md#schema).
+    - For more on creating datasets, see [How to Manage Datasets](https://docs.smith.langchain.com/evaluation/how_to_guides/manage_datasets_in_application#set-up-your-dataset).
+
+2.  **(Optional) Evaluators**: You can attach evaluators (e.g., LLM-as-a-Judge, heuristics, or custom functions) to your dataset in LangSmith. These will run automatically after the graph has processed all inputs.
+
+    - To learn more, read about [Evaluation Concepts](https://docs.smith.langchain.com/evaluation/concepts#evaluators).
+
+3.  **A running application**: The experiment can be run against:
+    - An application deployed on [LangGraph Platform](../../quick_start.md).
+    - A locally running application started via the [langgraph-cli](../../../tutorials/langgraph-platform/local-server.md).
+
+---
+
+## Step-by-step guide
+
+### 1. Launch the experiment
+
+Click the **Run experiment** button in the top right corner of the Studio page.
+
+### 2. Select your dataset
+
+In the modal that appears, select the dataset (or a specific dataset split) to use for the experiment and click **Start**.
+
+### 3. Monitor the progress
+
+All of the inputs in the dataset will now be run against the active assistant. Monitor the experiment's progress via the badge in the top right corner.
+
+You can continue to work in Studio while the experiment runs in the background. Click the arrow icon button at any time to navigate to LangSmith and view the detailed experiment results.
+
+---
+
+## Troubleshooting
+
+### "Run experiment" button is disabled
+
+If the "Run experiment" button is disabled, check the following:
+
+- **Deployed application**: If your application is deployed on LangGraph Platform, you may need to create a new revision to enable this feature.
+- **Local development server**: If you are running your application locally, make sure you have upgraded to the latest version of the `langgraph-cli` (`pip install -U langgraph-cli`). Additionally, ensure you have tracing enabled by setting the `LANGSMITH_API_KEY` in your project's `.env` file.
+
+### Evaluator results are missing
+
+When you run an experiment, any attached evaluators are scheduled for execution in a queue. If you don't see results immediately, it likely means they are still pending.

docs/docs/concepts/langgraph_control_plane.md

@@ -19,6 +19,7 @@ From the control plane UI, you can:
 - Update a deployment.
 - Update environment variables for a deployment.
 - View build and server logs of a deployment.
+- View deployment metrics like CPU and memory usage.
 - Delete a deployment.
 
 The Control Plane UI is embedded in [LangSmith](https://docs.smith.langchain.com/langgraph_cloud).
@@ -88,6 +89,15 @@ Infrastructure for deployments and revisions are provisioned and deployed asynch
 
 The control plane and [LangGraph Data Plane](./langgraph_data_plane.md) "listener" application coordinate to achieve asynchronous deployments.
 
+### Monitoring
+
+After a deployment is ready, the control plane monitors the deployment and records various metrics, such as:
+
+- CPU and memory usage of the deployment.
+- Number of container restarts.
+
+These metrics are displayed as charts in the Control Plane UI.
+
 ### LangSmith Integration
 
 A [LangSmith](https://docs.smith.langchain.com/) tracing project is automatically created for each deployment. The tracing project has the same name as the deployment. When creating a deployment, the `LANGCHAIN_TRACING` and `LANGSMITH_API_KEY`/`LANGCHAIN_API_KEY` environment variables do not need to be specified; they are set automatically by the control plane.

docs/docs/concepts/langgraph_studio.md

@@ -24,6 +24,7 @@ Key features of LangGraph Studio:
 - [Manage assistants](../cloud/how-tos/studio/manage_assistants.md)
 - [Manage threads](../cloud/how-tos/threads_studio.md)
 - [Iterate on prompts](../cloud/how-tos/iterate_graph_studio.md)
+- [Run experiments over a dataset](../cloud/how-tos/studio/run_evals.md)
 - Manage [long term memory](memory.md)
 - Debug agent state via [time travel](time-travel.md)
 
@@ -41,4 +42,4 @@ Chat mode is a simpler UI for iterating on and testing chat-specific agents. It
 
 ## Learn more
 
-- See this guide on how to [get started](../cloud/how-tos/studio/quick_start.md) with LangGraph Studio.
+- See this guide on how to [get started](../cloud/how-tos/studio/quick_start.md) with LangGraph Studio.

docs/mkdocs.yml

@@ -195,13 +195,14 @@ nav:
          - Standalone Container: cloud/deployment/standalone_container.md
     - Evaluation:
       - Basic implementation: agents/evals.md
-    - Commercial-only capabilities:
+    - Platform capabilities:
       - LangGraph Studio:
         - Quickstart: cloud/how-tos/studio/quick_start.md
         - cloud/how-tos/invoke_studio.md
         - cloud/how-tos/studio/manage_assistants.md
         - cloud/how-tos/threads_studio.md
         - cloud/how-tos/iterate_graph_studio.md
+        - cloud/how-tos/studio/run_evals.md
         - cloud/how-tos/clone_traces_studio.md
         - cloud/how-tos/datasets_studio.md
       - Authentication & access control:

libs/checkpoint-postgres/langgraph/checkpoint/postgres/__init__.py

@@ -23,6 +23,7 @@ from langgraph.checkpoint.base import (
 )
 from langgraph.checkpoint.postgres import _internal
 from langgraph.checkpoint.postgres.base import BasePostgresSaver
+from langgraph.checkpoint.postgres.shallow import ShallowPostgresSaver
 from langgraph.checkpoint.serde.base import SerializerProtocol
 
 Conn = _internal.Conn  # For backward compatibility
@@ -456,4 +457,4 @@ class PostgresSaver(BasePostgresSaver):
         )
 
 
-__all__ = ["PostgresSaver", "BasePostgresSaver", "Conn"]
+__all__ = ["PostgresSaver", "BasePostgresSaver", "ShallowPostgresSaver", "Conn"]

libs/checkpoint-postgres/langgraph/checkpoint/postgres/aio.py

@@ -23,6 +23,7 @@ from langgraph.checkpoint.base import (
 )
 from langgraph.checkpoint.postgres import _ainternal
 from langgraph.checkpoint.postgres.base import BasePostgresSaver
+from langgraph.checkpoint.postgres.shallow import AsyncShallowPostgresSaver
 from langgraph.checkpoint.serde.base import SerializerProtocol
 
 Conn = _ainternal.Conn  # For backward compatibility
@@ -559,4 +560,4 @@ class AsyncPostgresSaver(BasePostgresSaver):
         ).result()
 
 
-__all__ = ["AsyncPostgresSaver", "Conn"]
+__all__ = ["AsyncPostgresSaver", "AsyncShallowPostgresSaver", "Conn"]

libs/checkpoint-postgres/langgraph/checkpoint/postgres/base.py

@@ -168,7 +168,7 @@ class BasePostgresSaver(BaseCheckpointSaver[str]):
         checkpoint["channel_versions"][TASKS] = (
             max(checkpoint["channel_versions"].values())
             if checkpoint["channel_versions"]
-            else self.get_next_version(None)
+            else self.get_next_version(None, None)
         )
 
     def _load_blobs(
@@ -246,7 +246,7 @@ class BasePostgresSaver(BaseCheckpointSaver[str]):
             for idx, (channel, value) in enumerate(writes)
         ]
 
-    def get_next_version(self, current: str | None) -> str:
+    def get_next_version(self, current: str | None, channel: None) -> str:
         if current is None:
             current_v = 0
         elif isinstance(current, int):

libs/checkpoint-postgres/langgraph/checkpoint/postgres/shallow.py

@@ -0,0 +1,959 @@
+import asyncio
+import threading
+import warnings
+from collections.abc import AsyncIterator, Iterator, Sequence
+from contextlib import asynccontextmanager, contextmanager
+from typing import Any, Optional
+
+from langchain_core.runnables import RunnableConfig
+from psycopg import (
+    AsyncConnection,
+    AsyncCursor,
+    AsyncPipeline,
+    Capabilities,
+    Connection,
+    Cursor,
+    Pipeline,
+)
+from psycopg.rows import DictRow, dict_row
+from psycopg.types.json import Jsonb
+from psycopg_pool import AsyncConnectionPool, ConnectionPool
+
+from langgraph.checkpoint.base import (
+    WRITES_IDX_MAP,
+    ChannelVersions,
+    Checkpoint,
+    CheckpointMetadata,
+    CheckpointTuple,
+    get_checkpoint_metadata,
+)
+from langgraph.checkpoint.postgres import _ainternal, _internal
+from langgraph.checkpoint.postgres.base import BasePostgresSaver
+from langgraph.checkpoint.serde.base import SerializerProtocol
+from langgraph.checkpoint.serde.types import TASKS
+
+"""
+To add a new migration, add a new string to the MIGRATIONS list.
+The position of the migration in the list is the version number.
+"""
+MIGRATIONS = [
+    """CREATE TABLE IF NOT EXISTS checkpoint_migrations (
+    v INTEGER PRIMARY KEY
+);""",
+    """CREATE TABLE IF NOT EXISTS checkpoints (
+    thread_id TEXT NOT NULL,
+    checkpoint_ns TEXT NOT NULL DEFAULT '',
+    type TEXT,
+    checkpoint JSONB NOT NULL,
+    metadata JSONB NOT NULL DEFAULT '{}',
+    PRIMARY KEY (thread_id, checkpoint_ns)
+);""",
+    """CREATE TABLE IF NOT EXISTS checkpoint_blobs (
+    thread_id TEXT NOT NULL,
+    checkpoint_ns TEXT NOT NULL DEFAULT '',
+    channel TEXT NOT NULL,
+    type TEXT NOT NULL,
+    blob BYTEA,
+    PRIMARY KEY (thread_id, checkpoint_ns, channel)
+);""",
+    """CREATE TABLE IF NOT EXISTS checkpoint_writes (
+    thread_id TEXT NOT NULL,
+    checkpoint_ns TEXT NOT NULL DEFAULT '',
+    checkpoint_id TEXT NOT NULL,
+    task_id TEXT NOT NULL,
+    idx INTEGER NOT NULL,
+    channel TEXT NOT NULL,
+    type TEXT,
+    blob BYTEA NOT NULL,
+    PRIMARY KEY (thread_id, checkpoint_ns, checkpoint_id, task_id, idx)
+);""",
+    """
+    CREATE INDEX CONCURRENTLY IF NOT EXISTS checkpoints_thread_id_idx ON checkpoints(thread_id);
+    """,
+    """
+    CREATE INDEX CONCURRENTLY IF NOT EXISTS checkpoint_blobs_thread_id_idx ON checkpoint_blobs(thread_id);
+    """,
+    """
+    CREATE INDEX CONCURRENTLY IF NOT EXISTS checkpoint_writes_thread_id_idx ON checkpoint_writes(thread_id);
+    """,
+    """
+    ALTER TABLE checkpoint_writes ADD COLUMN task_path TEXT NOT NULL DEFAULT '';
+    """,
+]
+
+SELECT_SQL = f"""
+select
+    thread_id,
+    checkpoint,
+    checkpoint_ns,
+    metadata,
+    (
+        select array_agg(array[bl.channel::bytea, bl.type::bytea, bl.blob])
+        from jsonb_each_text(checkpoint -> 'channel_versions')
+        inner join checkpoint_blobs bl
+            on bl.thread_id = checkpoints.thread_id
+            and bl.checkpoint_ns = checkpoints.checkpoint_ns
+            and bl.channel = jsonb_each_text.key
+    ) as channel_values,
+    (
+        select
+        array_agg(array[cw.task_id::text::bytea, cw.channel::bytea, cw.type::bytea, cw.blob] order by cw.task_id, cw.idx)
+        from checkpoint_writes cw
+        where cw.thread_id = checkpoints.thread_id
+            and cw.checkpoint_ns = checkpoints.checkpoint_ns
+            and cw.checkpoint_id = (checkpoint->>'id')
+    ) as pending_writes,
+    (
+        select array_agg(array[cw.type::bytea, cw.blob] order by cw.task_path, cw.task_id, cw.idx)
+        from checkpoint_writes cw
+        where cw.thread_id = checkpoints.thread_id
+            and cw.checkpoint_ns = checkpoints.checkpoint_ns
+            and cw.channel = '{TASKS}'
+    ) as pending_sends
+from checkpoints """
+
+UPSERT_CHECKPOINT_BLOBS_SQL = """
+    INSERT INTO checkpoint_blobs (thread_id, checkpoint_ns, channel, type, blob)
+    VALUES (%s, %s, %s, %s, %s)
+    ON CONFLICT (thread_id, checkpoint_ns, channel) DO UPDATE SET
+        type = EXCLUDED.type,
+        blob = EXCLUDED.blob;
+"""
+
+UPSERT_CHECKPOINTS_SQL = """
+    INSERT INTO checkpoints (thread_id, checkpoint_ns, checkpoint, metadata)
+    VALUES (%s, %s, %s, %s)
+    ON CONFLICT (thread_id, checkpoint_ns)
+    DO UPDATE SET
+        checkpoint = EXCLUDED.checkpoint,
+        metadata = EXCLUDED.metadata;
+"""
+
+UPSERT_CHECKPOINT_WRITES_SQL = """
+    INSERT INTO checkpoint_writes (thread_id, checkpoint_ns, checkpoint_id, task_id, task_path, idx, channel, type, blob)
+    VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s)
+    ON CONFLICT (thread_id, checkpoint_ns, checkpoint_id, task_id, idx) DO UPDATE SET
+        channel = EXCLUDED.channel,
+        type = EXCLUDED.type,
+        blob = EXCLUDED.blob;
+"""
+
+INSERT_CHECKPOINT_WRITES_SQL = """
+    INSERT INTO checkpoint_writes (thread_id, checkpoint_ns, checkpoint_id, task_id, task_path, idx, channel, type, blob)
+    VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s)
+    ON CONFLICT (thread_id, checkpoint_ns, checkpoint_id, task_id, idx) DO NOTHING
+"""
+
+
+def _dump_blobs(
+    serde: SerializerProtocol,
+    thread_id: str,
+    checkpoint_ns: str,
+    values: dict[str, Any],
+    versions: ChannelVersions,
+) -> list[tuple[str, str, str, str, Optional[bytes]]]:
+    if not versions:
+        return []
+
+    return [
+        (
+            thread_id,
+            checkpoint_ns,
+            k,
+            *(serde.dumps_typed(values[k]) if k in values else ("empty", None)),
+        )
+        for k in versions
+    ]
+
+
+class ShallowPostgresSaver(BasePostgresSaver):
+    """A checkpoint saver that uses Postgres to store checkpoints.
+
+    This checkpointer ONLY stores the most recent checkpoint and does NOT retain any history.
+    It is meant to be a light-weight drop-in replacement for the PostgresSaver that
+    supports most of the LangGraph persistence functionality with the exception of time travel.
+    """
+
+    SELECT_SQL = SELECT_SQL
+    MIGRATIONS = MIGRATIONS
+    UPSERT_CHECKPOINT_BLOBS_SQL = UPSERT_CHECKPOINT_BLOBS_SQL
+    UPSERT_CHECKPOINTS_SQL = UPSERT_CHECKPOINTS_SQL
+    UPSERT_CHECKPOINT_WRITES_SQL = UPSERT_CHECKPOINT_WRITES_SQL
+    INSERT_CHECKPOINT_WRITES_SQL = INSERT_CHECKPOINT_WRITES_SQL
+
+    lock: threading.Lock
+
+    def __init__(
+        self,
+        conn: _internal.Conn,
+        pipe: Optional[Pipeline] = None,
+        serde: Optional[SerializerProtocol] = None,
+    ) -> None:
+        warnings.warn(
+            "ShallowPostgresSaver is deprecated as of version 2.0.20 and will be removed in 3.0.0. "
+            "Use PostgresSaver instead, and invoke the graph with `graph.invoke(..., checkpoint_during=False)`.",
+            DeprecationWarning,
+            stacklevel=2,
+        )
+        super().__init__(serde=serde)
+        if isinstance(conn, ConnectionPool) and pipe is not None:
+            raise ValueError(
+                "Pipeline should be used only with a single Connection, not ConnectionPool."
+            )
+
+        self.conn = conn
+        self.pipe = pipe
+        self.lock = threading.Lock()
+        self.supports_pipeline = Capabilities().has_pipeline()
+
+    @classmethod
+    @contextmanager
+    def from_conn_string(
+        cls, conn_string: str, *, pipeline: bool = False
+    ) -> Iterator["ShallowPostgresSaver"]:
+        """Create a new ShallowPostgresSaver instance from a connection string.
+
+        Args:
+            conn_string: The Postgres connection info string.
+            pipeline: whether to use Pipeline
+
+        Returns:
+            ShallowPostgresSaver: A new ShallowPostgresSaver instance.
+        """
+        with Connection.connect(
+            conn_string, autocommit=True, prepare_threshold=0, row_factory=dict_row
+        ) as conn:
+            if pipeline:
+                with conn.pipeline() as pipe:
+                    yield cls(conn, pipe)
+            else:
+                yield cls(conn)
+
+    def setup(self) -> None:
+        """Set up the checkpoint database asynchronously.
+
+        This method creates the necessary tables in the Postgres database if they don't
+        already exist and runs database migrations. It MUST be called directly by the user
+        the first time checkpointer is used.
+        """
+        with self._cursor() as cur:
+            cur.execute(self.MIGRATIONS[0])
+            results = cur.execute(
+                "SELECT v FROM checkpoint_migrations ORDER BY v DESC LIMIT 1"
+            )
+            row = results.fetchone()
+            if row is None:
+                version = -1
+            else:
+                version = row["v"]
+            for v, migration in zip(
+                range(version + 1, len(self.MIGRATIONS)),
+                self.MIGRATIONS[version + 1 :],
+            ):
+                cur.execute(migration)
+                cur.execute(f"INSERT INTO checkpoint_migrations (v) VALUES ({v})")
+        if self.pipe:
+            self.pipe.sync()
+
+    def list(
+        self,
+        config: Optional[RunnableConfig],
+        *,
+        filter: Optional[dict[str, Any]] = None,
+        before: Optional[RunnableConfig] = None,
+        limit: Optional[int] = None,
+    ) -> Iterator[CheckpointTuple]:
+        """List checkpoints from the database.
+
+        This method retrieves a list of checkpoint tuples from the Postgres database based
+        on the provided config. For ShallowPostgresSaver, this method returns a list with
+        ONLY the most recent checkpoint.
+        """
+        where, args = self._search_where(config, filter, before)
+        query = self.SELECT_SQL + where
+        if limit:
+            query += f" LIMIT {limit}"
+        with self._cursor() as cur:
+            cur.execute(self.SELECT_SQL + where, args, binary=True)
+            for value in cur:
+                checkpoint: Checkpoint = {
+                    **value["checkpoint"],
+                    "channel_values": self._load_blobs(value["channel_values"]),
+                    "pending_sends": [
+                        self.serde.loads_typed((t.decode(), v))
+                        for t, v in value["pending_sends"]
+                    ]
+                    if value["pending_sends"]
+                    else [],
+                }
+                yield CheckpointTuple(
+                    config={
+                        "configurable": {
+                            "thread_id": value["thread_id"],
+                            "checkpoint_ns": value["checkpoint_ns"],
+                            "checkpoint_id": checkpoint["id"],
+                        }
+                    },
+                    checkpoint=checkpoint,
+                    metadata=value["metadata"],
+                    pending_writes=self._load_writes(value["pending_writes"]),
+                )
+
+    def get_tuple(self, config: RunnableConfig) -> Optional[CheckpointTuple]:
+        """Get a checkpoint tuple from the database.
+
+        This method retrieves a checkpoint tuple from the Postgres database based on the
+        provided config (matching the thread ID in the config).
+
+        Args:
+            config: The config to use for retrieving the checkpoint.
+
+        Returns:
+            Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
+
+        Examples:
+
+            Basic:
+            >>> config = {"configurable": {"thread_id": "1"}}
+            >>> checkpoint_tuple = memory.get_tuple(config)
+            >>> print(checkpoint_tuple)
+            CheckpointTuple(...)
+
+            With timestamp:
+
+            >>> config = {
+            ...    "configurable": {
+            ...        "thread_id": "1",
+            ...        "checkpoint_ns": "",
+            ...        "checkpoint_id": "1ef4f797-8335-6428-8001-8a1503f9b875",
+            ...    }
+            ... }
+            >>> checkpoint_tuple = memory.get_tuple(config)
+            >>> print(checkpoint_tuple)
+            CheckpointTuple(...)
+        """  # noqa
+        thread_id = config["configurable"]["thread_id"]
+        checkpoint_ns = config["configurable"].get("checkpoint_ns", "")
+        args = (thread_id, checkpoint_ns)
+        where = "WHERE thread_id = %s AND checkpoint_ns = %s"
+
+        with self._cursor() as cur:
+            cur.execute(
+                self.SELECT_SQL + where,
+                args,
+                binary=True,
+            )
+
+            for value in cur:
+                checkpoint: Checkpoint = {
+                    **value["checkpoint"],
+                    "channel_values": self._load_blobs(value["channel_values"]),
+                    "pending_sends": [
+                        self.serde.loads_typed((t.decode(), v))
+                        for t, v in value["pending_sends"]
+                    ]
+                    if value["pending_sends"]
+                    else [],
+                }
+                return CheckpointTuple(
+                    config={
+                        "configurable": {
+                            "thread_id": thread_id,
+                            "checkpoint_ns": checkpoint_ns,
+                            "checkpoint_id": checkpoint["id"],
+                        }
+                    },
+                    checkpoint=checkpoint,
+                    metadata=value["metadata"],
+                    pending_writes=self._load_writes(value["pending_writes"]),
+                )
+
+    def put(
+        self,
+        config: RunnableConfig,
+        checkpoint: Checkpoint,
+        metadata: CheckpointMetadata,
+        new_versions: ChannelVersions,
+    ) -> RunnableConfig:
+        """Save a checkpoint to the database.
+
+        This method saves a checkpoint to the Postgres database. The checkpoint is associated
+        with the provided config. For ShallowPostgresSaver, this method saves ONLY the most recent
+        checkpoint and overwrites a previous checkpoint, if it exists.
+
+        Args:
+            config: The config to associate with the checkpoint.
+            checkpoint: The checkpoint to save.
+            metadata: Additional metadata to save with the checkpoint.
+            new_versions: New channel versions as of this write.
+
+        Returns:
+            RunnableConfig: Updated configuration after storing the checkpoint.
+
+        Examples:
+
+            >>> from langgraph.checkpoint.postgres import ShallowPostgresSaver
+            >>> DB_URI = "postgres://postgres:postgres@localhost:5432/postgres?sslmode=disable"
+            >>> with ShallowPostgresSaver.from_conn_string(DB_URI) as memory:
+            >>>     config = {"configurable": {"thread_id": "1", "checkpoint_ns": ""}}
+            >>>     checkpoint = {"ts": "2024-05-04T06:32:42.235444+00:00", "id": "1ef4f797-8335-6428-8001-8a1503f9b875", "channel_values": {"key": "value"}}
+            >>>     saved_config = memory.put(config, checkpoint, {"source": "input", "step": 1, "writes": {"key": "value"}}, {})
+            >>> print(saved_config)
+            {'configurable': {'thread_id': '1', 'checkpoint_ns': '', 'checkpoint_id': '1ef4f797-8335-6428-8001-8a1503f9b875'}}
+        """
+        configurable = config["configurable"].copy()
+        thread_id = configurable.pop("thread_id")
+        checkpoint_ns = configurable.pop("checkpoint_ns")
+
+        copy = checkpoint.copy()
+        next_config = {
+            "configurable": {
+                "thread_id": thread_id,
+                "checkpoint_ns": checkpoint_ns,
+                "checkpoint_id": checkpoint["id"],
+            }
+        }
+
+        with self._cursor(pipeline=True) as cur:
+            cur.execute(
+                """DELETE FROM checkpoint_writes
+                WHERE thread_id = %s AND checkpoint_ns = %s AND checkpoint_id NOT IN (%s, %s)""",
+                (
+                    thread_id,
+                    checkpoint_ns,
+                    checkpoint["id"],
+                    configurable.get("checkpoint_id", ""),
+                ),
+            )
+            cur.executemany(
+                self.UPSERT_CHECKPOINT_BLOBS_SQL,
+                _dump_blobs(
+                    self.serde,
+                    thread_id,
+                    checkpoint_ns,
+                    copy.pop("channel_values"),  # type: ignore[misc]
+                    new_versions,
+                ),
+            )
+            cur.execute(
+                self.UPSERT_CHECKPOINTS_SQL,
+                (
+                    thread_id,
+                    checkpoint_ns,
+                    Jsonb(copy),
+                    Jsonb(get_checkpoint_metadata(config, metadata)),
+                ),
+            )
+        return next_config
+
+    def put_writes(
+        self,
+        config: RunnableConfig,
+        writes: Sequence[tuple[str, Any]],
+        task_id: str,
+        task_path: str = "",
+    ) -> None:
+        """Store intermediate writes linked to a checkpoint.
+
+        This method saves intermediate writes associated with a checkpoint to the Postgres database.
+
+        Args:
+            config: Configuration of the related checkpoint.
+            writes: List of writes to store.
+            task_id: Identifier for the task creating the writes.
+        """
+        query = (
+            self.UPSERT_CHECKPOINT_WRITES_SQL
+            if all(w[0] in WRITES_IDX_MAP for w in writes)
+            else self.INSERT_CHECKPOINT_WRITES_SQL
+        )
+        with self._cursor(pipeline=True) as cur:
+            cur.executemany(
+                query,
+                self._dump_writes(
+                    config["configurable"]["thread_id"],
+                    config["configurable"]["checkpoint_ns"],
+                    config["configurable"]["checkpoint_id"],
+                    task_id,
+                    task_path,
+                    writes,
+                ),
+            )
+
+    @contextmanager
+    def _cursor(self, *, pipeline: bool = False) -> Iterator[Cursor[DictRow]]:
+        """Create a database cursor as a context manager.
+
+        Args:
+            pipeline: whether to use pipeline for the DB operations inside the context manager.
+                Will be applied regardless of whether the ShallowPostgresSaver instance was initialized with a pipeline.
+                If pipeline mode is not supported, will fall back to using transaction context manager.
+        """
+        with _internal.get_connection(self.conn) as conn:
+            if self.pipe:
+                # a connection in pipeline mode can be used concurrently
+                # in multiple threads/coroutines, but only one cursor can be
+                # used at a time
+                try:
+                    with conn.cursor(binary=True, row_factory=dict_row) as cur:
+                        yield cur
+                finally:
+                    if pipeline:
+                        self.pipe.sync()
+            elif pipeline:
+                # a connection not in pipeline mode can only be used by one
+                # thread/coroutine at a time, so we acquire a lock
+                if self.supports_pipeline:
+                    with (
+                        self.lock,
+                        conn.pipeline(),
+                        conn.cursor(binary=True, row_factory=dict_row) as cur,
+                    ):
+                        yield cur
+                else:
+                    # Use connection's transaction context manager when pipeline mode not supported
+                    with (
+                        self.lock,
+                        conn.transaction(),
+                        conn.cursor(binary=True, row_factory=dict_row) as cur,
+                    ):
+                        yield cur
+            else:
+                with self.lock, conn.cursor(binary=True, row_factory=dict_row) as cur:
+                    yield cur
+
+
+class AsyncShallowPostgresSaver(BasePostgresSaver):
+    """A checkpoint saver that uses Postgres to store checkpoints asynchronously.
+
+    This checkpointer ONLY stores the most recent checkpoint and does NOT retain any history.
+    It is meant to be a light-weight drop-in replacement for the AsyncPostgresSaver that
+    supports most of the LangGraph persistence functionality with the exception of time travel.
+    """
+
+    SELECT_SQL = SELECT_SQL
+    MIGRATIONS = MIGRATIONS
+    UPSERT_CHECKPOINT_BLOBS_SQL = UPSERT_CHECKPOINT_BLOBS_SQL
+    UPSERT_CHECKPOINTS_SQL = UPSERT_CHECKPOINTS_SQL
+    UPSERT_CHECKPOINT_WRITES_SQL = UPSERT_CHECKPOINT_WRITES_SQL
+    INSERT_CHECKPOINT_WRITES_SQL = INSERT_CHECKPOINT_WRITES_SQL
+    lock: asyncio.Lock
+
+    def __init__(
+        self,
+        conn: _ainternal.Conn,
+        pipe: Optional[AsyncPipeline] = None,
+        serde: Optional[SerializerProtocol] = None,
+    ) -> None:
+        warnings.warn(
+            "AsyncShallowPostgresSaver is deprecated as of version 2.0.20 and will be removed in 3.0.0. "
+            "Use AsyncPostgresSaver instead, and invoke the graph with `await graph.ainvoke(..., checkpoint_during=False)`.",
+            DeprecationWarning,
+            stacklevel=2,
+        )
+        super().__init__(serde=serde)
+        if isinstance(conn, AsyncConnectionPool) and pipe is not None:
+            raise ValueError(
+                "Pipeline should be used only with a single AsyncConnection, not AsyncConnectionPool."
+            )
+
+        self.conn = conn
+        self.pipe = pipe
+        self.lock = asyncio.Lock()
+        self.loop = asyncio.get_running_loop()
+        self.supports_pipeline = Capabilities().has_pipeline()
+
+    @classmethod
+    @asynccontextmanager
+    async def from_conn_string(
+        cls,
+        conn_string: str,
+        *,
+        pipeline: bool = False,
+        serde: Optional[SerializerProtocol] = None,
+    ) -> AsyncIterator["AsyncShallowPostgresSaver"]:
+        """Create a new AsyncShallowPostgresSaver instance from a connection string.
+
+        Args:
+            conn_string: The Postgres connection info string.
+            pipeline: whether to use AsyncPipeline
+
+        Returns:
+            AsyncShallowPostgresSaver: A new AsyncShallowPostgresSaver instance.
+        """
+        async with await AsyncConnection.connect(
+            conn_string, autocommit=True, prepare_threshold=0, row_factory=dict_row
+        ) as conn:
+            if pipeline:
+                async with conn.pipeline() as pipe:
+                    yield cls(conn=conn, pipe=pipe, serde=serde)
+            else:
+                yield cls(conn=conn, serde=serde)
+
+    async def setup(self) -> None:
+        """Set up the checkpoint database asynchronously.
+
+        This method creates the necessary tables in the Postgres database if they don't
+        already exist and runs database migrations. It MUST be called directly by the user
+        the first time checkpointer is used.
+        """
+        async with self._cursor() as cur:
+            await cur.execute(self.MIGRATIONS[0])
+            results = await cur.execute(
+                "SELECT v FROM checkpoint_migrations ORDER BY v DESC LIMIT 1"
+            )
+            row = await results.fetchone()
+            if row is None:
+                version = -1
+            else:
+                version = row["v"]
+            for v, migration in zip(
+                range(version + 1, len(self.MIGRATIONS)),
+                self.MIGRATIONS[version + 1 :],
+            ):
+                await cur.execute(migration)
+                await cur.execute(f"INSERT INTO checkpoint_migrations (v) VALUES ({v})")
+        if self.pipe:
+            await self.pipe.sync()
+
+    async def alist(
+        self,
+        config: Optional[RunnableConfig],
+        *,
+        filter: Optional[dict[str, Any]] = None,
+        before: Optional[RunnableConfig] = None,
+        limit: Optional[int] = None,
+    ) -> AsyncIterator[CheckpointTuple]:
+        """List checkpoints from the database asynchronously.
+
+        This method retrieves a list of checkpoint tuples from the Postgres database based
+        on the provided config. For ShallowPostgresSaver, this method returns a list with
+        ONLY the most recent checkpoint.
+        """
+        where, args = self._search_where(config, filter, before)
+        query = self.SELECT_SQL + where
+        if limit:
+            query += f" LIMIT {limit}"
+        async with self._cursor() as cur:
+            await cur.execute(self.SELECT_SQL + where, args, binary=True)
+            async for value in cur:
+                checkpoint: Checkpoint = {
+                    **value["checkpoint"],
+                    "channel_values": self._load_blobs(value["channel_values"]),
+                    "pending_sends": [
+                        self.serde.loads_typed((t.decode(), v))
+                        for t, v in value["pending_sends"]
+                    ]
+                    if value["pending_sends"]
+                    else [],
+                }
+                yield CheckpointTuple(
+                    config={
+                        "configurable": {
+                            "thread_id": value["thread_id"],
+                            "checkpoint_ns": value["checkpoint_ns"],
+                            "checkpoint_id": checkpoint["id"],
+                        }
+                    },
+                    checkpoint=checkpoint,
+                    metadata=value["metadata"],
+                    pending_writes=await asyncio.to_thread(
+                        self._load_writes, value["pending_writes"]
+                    ),
+                )
+
+    async def aget_tuple(self, config: RunnableConfig) -> Optional[CheckpointTuple]:
+        """Get a checkpoint tuple from the database asynchronously.
+
+        This method retrieves a checkpoint tuple from the Postgres database based on the
+        provided config (matching the thread ID in the config).
+
+        Args:
+            config: The config to use for retrieving the checkpoint.
+
+        Returns:
+            Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
+        """
+        thread_id = config["configurable"]["thread_id"]
+        checkpoint_ns = config["configurable"].get("checkpoint_ns", "")
+        args = (thread_id, checkpoint_ns)
+        where = "WHERE thread_id = %s AND checkpoint_ns = %s"
+
+        async with self._cursor() as cur:
+            await cur.execute(
+                self.SELECT_SQL + where,
+                args,
+                binary=True,
+            )
+
+            async for value in cur:
+                checkpoint: Checkpoint = {
+                    **value["checkpoint"],
+                    "channel_values": self._load_blobs(value["channel_values"]),
+                    "pending_sends": [
+                        self.serde.loads_typed((t.decode(), v))
+                        for t, v in value["pending_sends"]
+                    ]
+                    if value["pending_sends"]
+                    else [],
+                }
+                return CheckpointTuple(
+                    config={
+                        "configurable": {
+                            "thread_id": thread_id,
+                            "checkpoint_ns": checkpoint_ns,
+                            "checkpoint_id": checkpoint["id"],
+                        }
+                    },
+                    checkpoint=checkpoint,
+                    metadata=value["metadata"],
+                    pending_writes=await asyncio.to_thread(
+                        self._load_writes, value["pending_writes"]
+                    ),
+                )
+
+    async def aput(
+        self,
+        config: RunnableConfig,
+        checkpoint: Checkpoint,
+        metadata: CheckpointMetadata,
+        new_versions: ChannelVersions,
+    ) -> RunnableConfig:
+        """Save a checkpoint to the database asynchronously.
+
+        This method saves a checkpoint to the Postgres database. The checkpoint is associated
+        with the provided config. For AsyncShallowPostgresSaver, this method saves ONLY the most recent
+        checkpoint and overwrites a previous checkpoint, if it exists.
+
+        Args:
+            config: The config to associate with the checkpoint.
+            checkpoint: The checkpoint to save.
+            metadata: Additional metadata to save with the checkpoint.
+            new_versions: New channel versions as of this write.
+
+        Returns:
+            RunnableConfig: Updated configuration after storing the checkpoint.
+        """
+        configurable = config["configurable"].copy()
+        thread_id = configurable.pop("thread_id")
+        checkpoint_ns = configurable.pop("checkpoint_ns")
+
+        copy = checkpoint.copy()
+        next_config = {
+            "configurable": {
+                "thread_id": thread_id,
+                "checkpoint_ns": checkpoint_ns,
+                "checkpoint_id": checkpoint["id"],
+            }
+        }
+
+        async with self._cursor(pipeline=True) as cur:
+            await cur.execute(
+                """DELETE FROM checkpoint_writes
+                WHERE thread_id = %s AND checkpoint_ns = %s AND checkpoint_id NOT IN (%s, %s)""",
+                (
+                    thread_id,
+                    checkpoint_ns,
+                    checkpoint["id"],
+                    configurable.get("checkpoint_id", ""),
+                ),
+            )
+            await cur.executemany(
+                self.UPSERT_CHECKPOINT_BLOBS_SQL,
+                _dump_blobs(
+                    self.serde,
+                    thread_id,
+                    checkpoint_ns,
+                    copy.pop("channel_values"),  # type: ignore[misc]
+                    new_versions,
+                ),
+            )
+            await cur.execute(
+                self.UPSERT_CHECKPOINTS_SQL,
+                (
+                    thread_id,
+                    checkpoint_ns,
+                    Jsonb(copy),
+                    Jsonb(get_checkpoint_metadata(config, metadata)),
+                ),
+            )
+        return next_config
+
+    async def aput_writes(
+        self,
+        config: RunnableConfig,
+        writes: Sequence[tuple[str, Any]],
+        task_id: str,
+        task_path: str = "",
+    ) -> None:
+        """Store intermediate writes linked to a checkpoint asynchronously.
+
+        This method saves intermediate writes associated with a checkpoint to the database.
+
+        Args:
+            config: Configuration of the related checkpoint.
+            writes: List of writes to store, each as (channel, value) pair.
+            task_id: Identifier for the task creating the writes.
+        """
+        query = (
+            self.UPSERT_CHECKPOINT_WRITES_SQL
+            if all(w[0] in WRITES_IDX_MAP for w in writes)
+            else self.INSERT_CHECKPOINT_WRITES_SQL
+        )
+        params = await asyncio.to_thread(
+            self._dump_writes,
+            config["configurable"]["thread_id"],
+            config["configurable"]["checkpoint_ns"],
+            config["configurable"]["checkpoint_id"],
+            task_id,
+            task_path,
+            writes,
+        )
+        async with self._cursor(pipeline=True) as cur:
+            await cur.executemany(query, params)
+
+    @asynccontextmanager
+    async def _cursor(
+        self, *, pipeline: bool = False
+    ) -> AsyncIterator[AsyncCursor[DictRow]]:
+        """Create a database cursor as a context manager.
+
+        Args:
+            pipeline: whether to use pipeline for the DB operations inside the context manager.
+                Will be applied regardless of whether the AsyncShallowPostgresSaver instance was initialized with a pipeline.
+                If pipeline mode is not supported, will fall back to using transaction context manager.
+        """
+        async with _ainternal.get_connection(self.conn) as conn:
+            if self.pipe:
+                # a connection in pipeline mode can be used concurrently
+                # in multiple threads/coroutines, but only one cursor can be
+                # used at a time
+                try:
+                    async with conn.cursor(binary=True, row_factory=dict_row) as cur:
+                        yield cur
+                finally:
+                    if pipeline:
+                        await self.pipe.sync()
+            elif pipeline:
+                # a connection not in pipeline mode can only be used by one
+                # thread/coroutine at a time, so we acquire a lock
+                if self.supports_pipeline:
+                    async with (
+                        self.lock,
+                        conn.pipeline(),
+                        conn.cursor(binary=True, row_factory=dict_row) as cur,
+                    ):
+                        yield cur
+                else:
+                    # Use connection's transaction context manager when pipeline mode not supported
+                    async with (
+                        self.lock,
+                        conn.transaction(),
+                        conn.cursor(binary=True, row_factory=dict_row) as cur,
+                    ):
+                        yield cur
+            else:
+                async with (
+                    self.lock,
+                    conn.cursor(binary=True, row_factory=dict_row) as cur,
+                ):
+                    yield cur
+
+    def list(
+        self,
+        config: Optional[RunnableConfig],
+        *,
+        filter: Optional[dict[str, Any]] = None,
+        before: Optional[RunnableConfig] = None,
+        limit: Optional[int] = None,
+    ) -> Iterator[CheckpointTuple]:
+        """List checkpoints from the database.
+
+        This method retrieves a list of checkpoint tuples from the Postgres database based
+        on the provided config. For ShallowPostgresSaver, this method returns a list with
+        ONLY the most recent checkpoint.
+        """
+        aiter_ = self.alist(config, filter=filter, before=before, limit=limit)
+        while True:
+            try:
+                yield asyncio.run_coroutine_threadsafe(
+                    anext(aiter_),  # noqa: F821
+                    self.loop,
+                ).result()
+            except StopAsyncIteration:
+                break
+
+    def get_tuple(self, config: RunnableConfig) -> Optional[CheckpointTuple]:
+        """Get a checkpoint tuple from the database.
+
+        This method retrieves a checkpoint tuple from the Postgres database based on the
+        provided config (matching the thread ID in the config).
+
+        Args:
+            config: The config to use for retrieving the checkpoint.
+
+        Returns:
+            Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
+        """
+        try:
+            # check if we are in the main thread, only bg threads can block
+            # we don't check in other methods to avoid the overhead
+            if asyncio.get_running_loop() is self.loop:
+                raise asyncio.InvalidStateError(
+                    "Synchronous calls to AsyncShallowPostgresSaver are only allowed from a "
+                    "different thread. From the main thread, use the async interface."
+                    "For example, use `await checkpointer.aget_tuple(...)` or `await "
+                    "graph.ainvoke(...)`."
+                )
+        except RuntimeError:
+            pass
+        return asyncio.run_coroutine_threadsafe(
+            self.aget_tuple(config), self.loop
+        ).result()
+
+    def put(
+        self,
+        config: RunnableConfig,
+        checkpoint: Checkpoint,
+        metadata: CheckpointMetadata,
+        new_versions: ChannelVersions,
+    ) -> RunnableConfig:
+        """Save a checkpoint to the database.
+
+        This method saves a checkpoint to the Postgres database. The checkpoint is associated
+        with the provided config. For AsyncShallowPostgresSaver, this method saves ONLY the most recent
+        checkpoint and overwrites a previous checkpoint, if it exists.
+
+        Args:
+            config: The config to associate with the checkpoint.
+            checkpoint: The checkpoint to save.
+            metadata: Additional metadata to save with the checkpoint.
+            new_versions: New channel versions as of this write.
+
+        Returns:
+            RunnableConfig: Updated configuration after storing the checkpoint.
+        """
+        return asyncio.run_coroutine_threadsafe(
+            self.aput(config, checkpoint, metadata, new_versions), self.loop
+        ).result()
+
+    def put_writes(
+        self,
+        config: RunnableConfig,
+        writes: Sequence[tuple[str, Any]],
+        task_id: str,
+        task_path: str = "",
+    ) -> None:
+        """Store intermediate writes linked to a checkpoint.
+
+        This method saves intermediate writes associated with a checkpoint to the database.
+
+        Args:
+            config: Configuration of the related checkpoint.
+            writes: List of writes to store, each as (channel, value) pair.
+            task_id: Identifier for the task creating the writes.
+            task_path: Path of the task creating the writes.
+        """
+        return asyncio.run_coroutine_threadsafe(
+            self.aput_writes(config, writes, task_id, task_path), self.loop
+        ).result()

libs/checkpoint-postgres/tests/checkpoint_utils.py

@@ -1,53 +0,0 @@
-from __future__ import annotations
-
-from collections.abc import Mapping
-from datetime import datetime, timezone
-from typing import Any, Protocol
-
-from langgraph.checkpoint.base import Checkpoint, EmptyChannelError
-from langgraph.checkpoint.base.id import uuid6
-
-
-class ChannelProtocol(Protocol):
-    def checkpoint(self) -> Any | None: ...
-
-
-def empty_checkpoint() -> Checkpoint:
-    return Checkpoint(
-        v=1,
-        id=str(uuid6(clock_seq=-2)),
-        ts=datetime.now(timezone.utc).isoformat(),
-        channel_values={},
-        channel_versions={},
-        versions_seen={},
-    )
-
-
-def create_checkpoint(
-    checkpoint: Checkpoint,
-    channels: Mapping[str, ChannelProtocol] | None,
-    step: int,
-    *,
-    id: str | None = None,
-) -> Checkpoint:
-    """Create a checkpoint for the given channels."""
-    ts = datetime.now(timezone.utc).isoformat()
-    if channels is None:
-        values = checkpoint["channel_values"]
-    else:
-        values = {}
-        for k, v in channels.items():
-            if k not in checkpoint["channel_versions"]:
-                continue
-            try:
-                values[k] = v.checkpoint()
-            except EmptyChannelError:
-                pass
-    return Checkpoint(
-        v=1,
-        ts=ts,
-        id=id or str(uuid6(clock_seq=step)),
-        channel_values=values,
-        channel_versions=checkpoint["channel_versions"],
-        versions_seen=checkpoint["versions_seen"],
-    )

libs/checkpoint-postgres/tests/test_async.py

@@ -14,10 +14,14 @@ from langgraph.checkpoint.base import (
     EXCLUDED_METADATA_KEYS,
     Checkpoint,
     CheckpointMetadata,
+    create_checkpoint,
+    empty_checkpoint,
+)
+from langgraph.checkpoint.postgres.aio import (
+    AsyncPostgresSaver,
+    AsyncShallowPostgresSaver,
 )
-from langgraph.checkpoint.postgres.aio import AsyncPostgresSaver
 from langgraph.checkpoint.serde.types import TASKS
-from tests.checkpoint_utils import create_checkpoint, empty_checkpoint
 from tests.conftest import DEFAULT_POSTGRES_URI
 
 
@@ -108,11 +112,41 @@ async def _base_saver():
             await conn.execute(f"DROP DATABASE {database}")
 
 
+@asynccontextmanager
+async def _shallow_saver():
+    """Fixture for shallow connection mode testing."""
+    database = f"test_{uuid4().hex[:16]}"
+    # create unique db
+    async with await AsyncConnection.connect(
+        DEFAULT_POSTGRES_URI, autocommit=True
+    ) as conn:
+        await conn.execute(f"CREATE DATABASE {database}")
+    try:
+        async with await AsyncConnection.connect(
+            DEFAULT_POSTGRES_URI + database,
+            autocommit=True,
+            prepare_threshold=0,
+            row_factory=dict_row,
+        ) as conn:
+            checkpointer = AsyncShallowPostgresSaver(conn)
+            await checkpointer.setup()
+            yield checkpointer
+    finally:
+        # drop unique db
+        async with await AsyncConnection.connect(
+            DEFAULT_POSTGRES_URI, autocommit=True
+        ) as conn:
+            await conn.execute(f"DROP DATABASE {database}")
+
+
 @asynccontextmanager
 async def _saver(name: str):
     if name == "base":
         async with _base_saver() as saver:
             yield saver
+    elif name == "shallow":
+        async with _shallow_saver() as saver:
+            yield saver
     elif name == "pool":
         async with _pool_saver() as saver:
             yield saver
@@ -172,7 +206,7 @@ def test_data():
     }
 
 
-@pytest.mark.parametrize("saver_name", ["base", "pool", "pipe"])
+@pytest.mark.parametrize("saver_name", ["base", "pool", "pipe", "shallow"])
 async def test_combined_metadata(saver_name: str, test_data) -> None:
     async with _saver(saver_name) as saver:
         config = {
@@ -199,7 +233,7 @@ async def test_combined_metadata(saver_name: str, test_data) -> None:
         }
 
 
-@pytest.mark.parametrize("saver_name", ["base", "pool", "pipe"])
+@pytest.mark.parametrize("saver_name", ["base", "pool", "pipe", "shallow"])
 async def test_asearch(saver_name: str, test_data) -> None:
     async with _saver(saver_name) as saver:
         configs = test_data["configs"]
@@ -250,7 +284,7 @@ async def test_asearch(saver_name: str, test_data) -> None:
         } == {"", "inner"}
 
 
-@pytest.mark.parametrize("saver_name", ["base", "pool", "pipe"])
+@pytest.mark.parametrize("saver_name", ["base", "pool", "pipe", "shallow"])
 async def test_null_chars(saver_name: str, test_data) -> None:
     async with _saver(saver_name) as saver:
         config = await saver.aput(

libs/checkpoint-postgres/tests/test_sync.py

@@ -15,10 +15,11 @@ from langgraph.checkpoint.base import (
     EXCLUDED_METADATA_KEYS,
     Checkpoint,
     CheckpointMetadata,
+    create_checkpoint,
+    empty_checkpoint,
 )
-from langgraph.checkpoint.postgres import PostgresSaver
+from langgraph.checkpoint.postgres import PostgresSaver, ShallowPostgresSaver
 from langgraph.checkpoint.serde.types import TASKS
-from tests.checkpoint_utils import create_checkpoint, empty_checkpoint
 from tests.conftest import DEFAULT_POSTGRES_URI
 
 
@@ -97,11 +98,37 @@ def _base_saver():
             conn.execute(f"DROP DATABASE {database}")
 
 
+@contextmanager
+def _shallow_saver():
+    """Fixture for regular connection mode testing with a shallow checkpointer."""
+    database = f"test_{uuid4().hex[:16]}"
+    # create unique db
+    with Connection.connect(DEFAULT_POSTGRES_URI, autocommit=True) as conn:
+        conn.execute(f"CREATE DATABASE {database}")
+    try:
+        with Connection.connect(
+            DEFAULT_POSTGRES_URI + database,
+            autocommit=True,
+            prepare_threshold=0,
+            row_factory=dict_row,
+        ) as conn:
+            checkpointer = ShallowPostgresSaver(conn)
+            checkpointer.setup()
+            yield checkpointer
+    finally:
+        # drop unique db
+        with Connection.connect(DEFAULT_POSTGRES_URI, autocommit=True) as conn:
+            conn.execute(f"DROP DATABASE {database}")
+
+
 @contextmanager
 def _saver(name: str):
     if name == "base":
         with _base_saver() as saver:
             yield saver
+    elif name == "shallow":
+        with _shallow_saver() as saver:
+            yield saver
     elif name == "pool":
         with _pool_saver() as saver:
             yield saver
@@ -161,7 +188,7 @@ def test_data():
     }
 
 
-@pytest.mark.parametrize("saver_name", ["base", "pool", "pipe"])
+@pytest.mark.parametrize("saver_name", ["base", "pool", "pipe", "shallow"])
 def test_combined_metadata(saver_name: str, test_data) -> None:
     with _saver(saver_name) as saver:
         config = {
@@ -188,7 +215,7 @@ def test_combined_metadata(saver_name: str, test_data) -> None:
         }
 
 
-@pytest.mark.parametrize("saver_name", ["base", "pool", "pipe"])
+@pytest.mark.parametrize("saver_name", ["base", "pool", "pipe", "shallow"])
 def test_search(saver_name: str, test_data) -> None:
     with _saver(saver_name) as saver:
         configs = test_data["configs"]
@@ -237,7 +264,7 @@ def test_search(saver_name: str, test_data) -> None:
         } == {"", "inner"}
 
 
-@pytest.mark.parametrize("saver_name", ["base", "pool", "pipe"])
+@pytest.mark.parametrize("saver_name", ["base", "pool", "pipe", "shallow"])
 def test_null_chars(saver_name: str, test_data) -> None:
     with _saver(saver_name) as saver:
         config = saver.put(

libs/checkpoint-sqlite/langgraph/checkpoint/sqlite/__init__.py

@@ -536,7 +536,7 @@ class SqliteSaver(BaseCheckpointSaver[str]):
         """
         raise NotImplementedError(_AIO_ERROR_MSG)
 
-    def get_next_version(self, current: str | None) -> str:
+    def get_next_version(self, current: str | None, channel: None) -> str:
         """Generate the next version ID for a channel.
 
         This method creates a new version identifier for a channel based on its current version.

libs/checkpoint-sqlite/langgraph/checkpoint/sqlite/aio.py

@@ -591,7 +591,7 @@ class AsyncSqliteSaver(BaseCheckpointSaver[str]):
             )
             await self.conn.commit()
 
-    def get_next_version(self, current: str | None) -> str:
+    def get_next_version(self, current: str | None, channel: None) -> str:
         """Generate the next version ID for a channel.
 
         This method creates a new version identifier for a channel based on its current version.

libs/checkpoint-sqlite/tests/checkpoint_utils.py

@@ -1,53 +0,0 @@
-from __future__ import annotations
-
-from collections.abc import Mapping
-from datetime import datetime, timezone
-from typing import Any, Protocol
-
-from langgraph.checkpoint.base import Checkpoint, EmptyChannelError
-from langgraph.checkpoint.base.id import uuid6
-
-
-class ChannelProtocol(Protocol):
-    def checkpoint(self) -> Any | None: ...
-
-
-def empty_checkpoint() -> Checkpoint:
-    return Checkpoint(
-        v=1,
-        id=str(uuid6(clock_seq=-2)),
-        ts=datetime.now(timezone.utc).isoformat(),
-        channel_values={},
-        channel_versions={},
-        versions_seen={},
-    )
-
-
-def create_checkpoint(
-    checkpoint: Checkpoint,
-    channels: Mapping[str, ChannelProtocol] | None,
-    step: int,
-    *,
-    id: str | None = None,
-) -> Checkpoint:
-    """Create a checkpoint for the given channels."""
-    ts = datetime.now(timezone.utc).isoformat()
-    if channels is None:
-        values = checkpoint["channel_values"]
-    else:
-        values = {}
-        for k, v in channels.items():
-            if k not in checkpoint["channel_versions"]:
-                continue
-            try:
-                values[k] = v.checkpoint()
-            except EmptyChannelError:
-                pass
-    return Checkpoint(
-        v=1,
-        ts=ts,
-        id=id or str(uuid6(clock_seq=step)),
-        channel_values=values,
-        channel_versions=checkpoint["channel_versions"],
-        versions_seen=checkpoint["versions_seen"],
-    )

libs/checkpoint-sqlite/tests/test_aiosqlite.py

@@ -6,9 +6,10 @@ from langchain_core.runnables import RunnableConfig
 from langgraph.checkpoint.base import (
     Checkpoint,
     CheckpointMetadata,
+    create_checkpoint,
+    empty_checkpoint,
 )
 from langgraph.checkpoint.sqlite.aio import AsyncSqliteSaver
-from tests.checkpoint_utils import create_checkpoint, empty_checkpoint
 
 
 class TestAsyncSqliteSaver:

libs/checkpoint-sqlite/tests/test_sqlite.py

@@ -6,10 +6,11 @@ from langchain_core.runnables import RunnableConfig
 from langgraph.checkpoint.base import (
     Checkpoint,
     CheckpointMetadata,
+    create_checkpoint,
+    empty_checkpoint,
 )
 from langgraph.checkpoint.sqlite import SqliteSaver
 from langgraph.checkpoint.sqlite.utils import _metadata_predicate, search_where
-from tests.checkpoint_utils import create_checkpoint, empty_checkpoint
 
 
 class TestSqliteSaver:

libs/checkpoint/langgraph/checkpoint/base/__init__.py

@@ -1,10 +1,8 @@
 from __future__ import annotations
 
-from collections.abc import AsyncIterator, Iterator, Sequence
-from inspect import signature
+from collections.abc import AsyncIterator, Iterator, Mapping, Sequence
 from typing import (  # noqa: UP035
     Any,
-    ClassVar,
     Generic,
     Literal,
     NamedTuple,
@@ -15,6 +13,7 @@ from typing import (  # noqa: UP035
 
 from langchain_core.runnables import RunnableConfig
 
+from langgraph.checkpoint.base.id import uuid6
 from langgraph.checkpoint.serde.base import SerializerProtocol, maybe_add_typed_methods
 from langgraph.checkpoint.serde.jsonplus import JsonPlusSerializer
 from langgraph.checkpoint.serde.types import (
@@ -22,6 +21,7 @@ from langgraph.checkpoint.serde.types import (
     INTERRUPT,
     RESUME,
     SCHEDULED,
+    ChannelProtocol,
 )
 
 V = TypeVar("V", int, float, str)
@@ -91,6 +91,7 @@ def copy_checkpoint(checkpoint: Checkpoint) -> Checkpoint:
         channel_values=checkpoint["channel_values"].copy(),
         channel_versions=checkpoint["channel_versions"].copy(),
         versions_seen={k: v.copy() for k, v in checkpoint["versions_seen"].items()},
+        pending_sends=checkpoint.get("pending_sends", []).copy(),
     )
 
 
@@ -118,19 +119,8 @@ class BaseCheckpointSaver(Generic[V]):
         versions to avoid blocking the main thread.
     """
 
-    _get_next_version_legacy: ClassVar[bool] = False
-    """Flag indicating if get_next_version method is legacy (takes two parameters)."""
-
     serde: SerializerProtocol = JsonPlusSerializer()
 
-    def __init_subclass__(cls) -> None:
-        cls._get_next_version_legacy = (
-            len(signature(cls.get_next_version).parameters) > 2  # self + current
-            if hasattr(cls, "get_next_version")
-            else False
-        )
-        return super().__init_subclass__()
-
     def __init__(
         self,
         *,
@@ -138,6 +128,15 @@ class BaseCheckpointSaver(Generic[V]):
     ) -> None:
         self.serde = maybe_add_typed_methods(serde or self.serde)
 
+    @property
+    def config_specs(self) -> list:
+        """Define the configuration options for the checkpoint saver.
+
+        Returns:
+            list: List of configuration field specs.
+        """
+        return []
+
     def get(self, config: RunnableConfig) -> Checkpoint | None:
         """Fetch a checkpoint using the given configuration.
 
@@ -347,7 +346,7 @@ class BaseCheckpointSaver(Generic[V]):
         """
         raise NotImplementedError
 
-    def get_next_version(self, current: V | None) -> V:
+    def get_next_version(self, current: V | None, channel: None) -> V:
         """Generate the next version ID for a channel.
 
         Default is to use integer versions, incrementing by 1. If you override, you can use str/int/float versions,
@@ -355,6 +354,7 @@ class BaseCheckpointSaver(Generic[V]):
 
         Args:
             current: The current version identifier (int, float, or str).
+            channel: Deprecated argument, kept for backwards compatibility.
 
         Returns:
             V: The next version identifier, which must be increasing.
@@ -417,3 +417,54 @@ EXCLUDED_METADATA_KEYS = {
     "checkpoint_ns",
     "checkpoint_map",
 }
+
+# --- below are deprecated utilities used by past versions of LangGraph ---
+
+LATEST_VERSION = 2
+
+
+def empty_checkpoint() -> Checkpoint:
+    from datetime import datetime, timezone
+
+    return Checkpoint(
+        v=LATEST_VERSION,
+        id=str(uuid6(clock_seq=-2)),
+        ts=datetime.now(timezone.utc).isoformat(),
+        channel_values={},
+        channel_versions={},
+        versions_seen={},
+        pending_sends=[],
+    )
+
+
+def create_checkpoint(
+    checkpoint: Checkpoint,
+    channels: Mapping[str, ChannelProtocol] | None,
+    step: int,
+    *,
+    id: str | None = None,
+) -> Checkpoint:
+    """Create a checkpoint for the given channels."""
+    from datetime import datetime, timezone
+
+    ts = datetime.now(timezone.utc).isoformat()
+    if channels is None:
+        values = checkpoint["channel_values"]
+    else:
+        values = {}
+        for k, v in channels.items():
+            if k not in checkpoint["channel_versions"]:
+                continue
+            try:
+                values[k] = v.checkpoint()
+            except EmptyChannelError:
+                pass
+    return Checkpoint(
+        v=LATEST_VERSION,
+        ts=ts,
+        id=id or str(uuid6(clock_seq=step)),
+        channel_values=values,
+        channel_versions=checkpoint["channel_versions"],
+        versions_seen=checkpoint["versions_seen"],
+        pending_sends=checkpoint.get("pending_sends", []),
+    )

libs/checkpoint/langgraph/checkpoint/memory/__init__.py

@@ -512,7 +512,7 @@ class InMemorySaver(
         """
         return self.delete_thread(thread_id)
 
-    def get_next_version(self, current: str | None) -> str:
+    def get_next_version(self, current: str | None, channel: None) -> str:
         if current is None:
             current_v = 0
         elif isinstance(current, int):

libs/checkpoint/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-checkpoint"
-version = "2.0.26"
+version = "2.1.0"
 description = "Library with base interfaces for LangGraph checkpoint savers."
 authors = []
 requires-python = ">=3.9"

libs/checkpoint/tests/checkpoint_utils.py

@@ -1,53 +0,0 @@
-from __future__ import annotations
-
-from collections.abc import Mapping
-from datetime import datetime, timezone
-from typing import Any, Protocol
-
-from langgraph.checkpoint.base import Checkpoint, EmptyChannelError
-from langgraph.checkpoint.base.id import uuid6
-
-
-class ChannelProtocol(Protocol):
-    def checkpoint(self) -> Any | None: ...
-
-
-def empty_checkpoint() -> Checkpoint:
-    return Checkpoint(
-        v=1,
-        id=str(uuid6(clock_seq=-2)),
-        ts=datetime.now(timezone.utc).isoformat(),
-        channel_values={},
-        channel_versions={},
-        versions_seen={},
-    )
-
-
-def create_checkpoint(
-    checkpoint: Checkpoint,
-    channels: Mapping[str, ChannelProtocol] | None,
-    step: int,
-    *,
-    id: str | None = None,
-) -> Checkpoint:
-    """Create a checkpoint for the given channels."""
-    ts = datetime.now(timezone.utc).isoformat()
-    if channels is None:
-        values = checkpoint["channel_values"]
-    else:
-        values = {}
-        for k, v in channels.items():
-            if k not in checkpoint["channel_versions"]:
-                continue
-            try:
-                values[k] = v.checkpoint()
-            except EmptyChannelError:
-                pass
-    return Checkpoint(
-        v=1,
-        ts=ts,
-        id=id or str(uuid6(clock_seq=step)),
-        channel_values=values,
-        channel_versions=checkpoint["channel_versions"],
-        versions_seen=checkpoint["versions_seen"],
-    )

libs/checkpoint/tests/test_memory.py

@@ -6,12 +6,10 @@ from langchain_core.runnables import RunnableConfig
 from langgraph.checkpoint.base import (
     Checkpoint,
     CheckpointMetadata,
-)
-from langgraph.checkpoint.memory import InMemorySaver
-from tests.checkpoint_utils import (
     create_checkpoint,
     empty_checkpoint,
 )
+from langgraph.checkpoint.memory import InMemorySaver
 
 
 class TestMemorySaver:

libs/checkpoint/uv.lock

@@ -324,7 +324,7 @@ wheels = [
 
 [[package]]
 name = "langgraph-checkpoint"
-version = "2.0.26"
+version = "2.1.0"
 source = { editable = "." }
 dependencies = [
     { name = "langchain-core" },

libs/langgraph/langgraph/func/__init__.py

@@ -38,7 +38,7 @@ from langgraph.pregel.read import PregelNode
 from langgraph.pregel.write import ChannelWrite, ChannelWriteEntry
 from langgraph.store.base import BaseStore
 from langgraph.types import _DC_KWARGS, CachePolicy, RetryPolicy, StreamMode
-from langgraph.warnings import LangGraphDeprecatedSinceV10
+from langgraph.warnings import LangGraphDeprecatedSinceV05
 
 
 class TaskFunction(Generic[P, T]):
@@ -179,7 +179,7 @@ def task(
     if (retry := kwargs.get("retry", UNSET)) is not UNSET:
         warnings.warn(
             "`retry` is deprecated and will be removed. Please use `retry_policy` instead.",
-            category=LangGraphDeprecatedSinceV10,
+            category=LangGraphDeprecatedSinceV05,
         )
         if retry_policy is None:
             retry_policy = retry  # type: ignore[assignment]
@@ -383,7 +383,7 @@ class entrypoint:
         if (retry := kwargs.get("retry", UNSET)) is not UNSET:
             warnings.warn(
                 "`retry` is deprecated and will be removed. Please use `retry_policy` instead.",
-                category=LangGraphDeprecatedSinceV10,
+                category=LangGraphDeprecatedSinceV05,
             )
             if retry_policy is None:
                 retry_policy = retry  # type: ignore[assignment]

libs/langgraph/langgraph/graph/state.py

@@ -86,7 +86,7 @@ from langgraph.utils.fields import (
 )
 from langgraph.utils.pydantic import create_model
 from langgraph.utils.runnable import coerce_to_runnable
-from langgraph.warnings import LangGraphDeprecatedSinceV10
+from langgraph.warnings import LangGraphDeprecatedSinceV05
 
 logger = logging.getLogger(__name__)
 
@@ -160,6 +160,7 @@ StateNode: TypeAlias = Union[
     _NodeWithConfigWriter[StateT_contra],
     _NodeWithConfigStore[StateT_contra],
     _NodeWithConfigWriterStore[StateT_contra],
+    Runnable[StateT_contra, Any],
 ]
 
 
@@ -261,7 +262,7 @@ class StateGraph(Generic[StateT, InputT, OutputT]):
         if (input_ := kwargs.get("input", UNSET)) is not UNSET:
             warnings.warn(
                 "`input` is deprecated and will be removed. Please use `input_schema` instead.",
-                category=LangGraphDeprecatedSinceV10,
+                category=LangGraphDeprecatedSinceV05,
                 stacklevel=2,
             )
             if input_schema is None:
@@ -270,7 +271,7 @@ class StateGraph(Generic[StateT, InputT, OutputT]):
         if (output := kwargs.get("output", UNSET)) is not UNSET:
             warnings.warn(
                 "`output` is deprecated and will be removed. Please use `output_schema` instead.",
-                category=LangGraphDeprecatedSinceV10,
+                category=LangGraphDeprecatedSinceV05,
                 stacklevel=2,
             )
             if output_schema is None:
@@ -436,7 +437,7 @@ class StateGraph(Generic[StateT, InputT, OutputT]):
         if (retry := kwargs.get("retry", UNSET)) is not UNSET:
             warnings.warn(
                 "`retry` is deprecated and will be removed. Please use `retry_policy` instead.",
-                category=LangGraphDeprecatedSinceV10,
+                category=LangGraphDeprecatedSinceV05,
             )
             if retry_policy is None:
                 retry_policy = retry  # type: ignore[assignment]
@@ -444,7 +445,7 @@ class StateGraph(Generic[StateT, InputT, OutputT]):
         if (input_ := kwargs.get("input", UNSET)) is not UNSET:
             warnings.warn(
                 "`input` is deprecated and will be removed. Please use `input_schema` instead.",
-                category=LangGraphDeprecatedSinceV10,
+                category=LangGraphDeprecatedSinceV05,
             )
             if input_schema is None:
                 input_schema = cast(Union[type[InputT], None], input_)
@@ -535,7 +536,7 @@ class StateGraph(Generic[StateT, InputT, OutputT]):
         if input_schema is not None:
             self._add_schema(input_schema)
         self.nodes[node] = StateNodeSpec(
-            coerce_to_runnable(action, name=node, trace=False),  # type: ignore
+            coerce_to_runnable(action, name=node, trace=False),
             metadata,
             input=input_schema or self.state_schema,
             retry_policy=retry_policy,
@@ -1101,6 +1102,7 @@ class CompiledStateGraph(
 
     def _migrate_checkpoint(self, checkpoint: Checkpoint) -> None:
         """Migrate a checkpoint to new channel layout."""
+        super()._migrate_checkpoint(checkpoint)
 
         values = checkpoint["channel_values"]
         versions = checkpoint["channel_versions"]

libs/langgraph/langgraph/pregel/__init__.py

@@ -32,7 +32,6 @@ from langgraph.checkpoint.base import (
     BaseCheckpointSaver,
     Checkpoint,
     CheckpointTuple,
-    copy_checkpoint,
 )
 from langgraph.config import get_config
 from langgraph.constants import (
@@ -79,6 +78,7 @@ from langgraph.pregel.algo import (
 from langgraph.pregel.call import identifier
 from langgraph.pregel.checkpoint import (
     channels_from_checkpoint,
+    copy_checkpoint,
     create_checkpoint,
     empty_checkpoint,
 )
@@ -908,7 +908,12 @@ class Pregel(PregelProtocol[StateT, InputT, OutputT], Generic[StateT, InputT, Ou
 
     def _migrate_checkpoint(self, checkpoint: Checkpoint) -> None:
         """Migrate a saved checkpoint to new channel layout."""
-        pass
+        if checkpoint["v"] < 4 and checkpoint.get("pending_sends"):
+            pending_sends: list[Send] = checkpoint.pop("pending_sends")
+            checkpoint["channel_values"][TASKS] = pending_sends
+            checkpoint["channel_versions"][TASKS] = max(
+                checkpoint["channel_versions"].values()
+            )
 
     def _prepare_state_snapshot(
         self,
@@ -2298,7 +2303,8 @@ class Pregel(PregelProtocol[StateT, InputT, OutputT], Generic[StateT, InputT, Ou
                 - `"custom"`: Emit custom data from inside nodes or tasks using `StreamWriter`.
                 - `"messages"`: Emit LLM messages token-by-token together with metadata for any LLM invocations inside nodes or tasks.
                     Will be emitted as 2-tuples `(LLM token, metadata)`.
-                - `"debug"`: Emit debug events with as much information as possible for each step.
+                - `"checkpoints"`: Emit an event when a checkpoint is created, in the same format as returned by get_state().
+                - `"tasks"`: Emit events when tasks start and finish, including their results and errors.
 
                 You can pass a list as the `stream_mode` parameter to stream multiple modes at once.
                 The streamed outputs will be tuples of `(mode, data)`.

libs/langgraph/langgraph/pregel/algo.py

@@ -83,7 +83,7 @@ from langgraph.types import (
 )
 from langgraph.utils.config import merge_configs, patch_config
 
-GetNextVersion = Callable[[Optional[V]], V]
+GetNextVersion = Callable[[Optional[V], None], V]
 SUPPORTS_EXC_NOTES = sys.version_info >= (3, 11)
 
 
@@ -214,7 +214,7 @@ def local_read(
     return values
 
 
-def increment(current: int | None) -> int:
+def increment(current: int | None, channel: None) -> int:
     """Default channel versioning function, increments the current int version."""
     return current + 1 if current is not None else 1
 
@@ -265,7 +265,8 @@ def apply_writes(
         next_version = get_next_version(
             max(checkpoint["channel_versions"].values())
             if checkpoint["channel_versions"]
-            else None
+            else None,
+            None,
         )
 
     # Consume all channels that were read

libs/langgraph/langgraph/pregel/checkpoint.py

@@ -71,3 +71,14 @@ def channels_from_checkpoint(
         },
         managed_specs,
     )
+
+
+def copy_checkpoint(checkpoint: Checkpoint) -> Checkpoint:
+    return Checkpoint(
+        v=checkpoint["v"],
+        ts=checkpoint["ts"],
+        id=checkpoint["id"],
+        channel_values=checkpoint["channel_values"].copy(),
+        channel_versions=checkpoint["channel_versions"].copy(),
+        versions_seen={k: v.copy() for k, v in checkpoint["versions_seen"].items()},
+    )

libs/langgraph/langgraph/pregel/debug.py

@@ -3,13 +3,8 @@ from __future__ import annotations
 from collections import defaultdict
 from collections.abc import Iterable, Iterator, Mapping, Sequence
 from dataclasses import asdict
-from datetime import datetime, timezone
 from pprint import pformat
-from typing import (
-    Any,
-    Literal,
-    Union,
-)
+from typing import Any
 from uuid import UUID
 
 from langchain_core.runnables.config import RunnableConfig
@@ -17,7 +12,7 @@ from langchain_core.utils.input import get_bolded_text, get_colored_text
 from typing_extensions import TypedDict
 
 from langgraph.channels.base import BaseChannel
-from langgraph.checkpoint.base import Checkpoint, CheckpointMetadata, PendingWrite
+from langgraph.checkpoint.base import CheckpointMetadata, PendingWrite
 from langgraph.constants import (
     CONF,
     CONFIG_KEY_CHECKPOINT_NS,
@@ -66,82 +61,43 @@ class CheckpointPayload(TypedDict):
     tasks: list[CheckpointTask]
 
 
-class DebugOutputBase(TypedDict):
-    timestamp: str
-    step: int
-
-
-class DebugOutputTask(DebugOutputBase):
-    type: Literal["task"]
-    payload: TaskPayload
-
-
-class DebugOutputTaskResult(DebugOutputBase):
-    type: Literal["task_result"]
-    payload: TaskResultPayload
-
-
-class DebugOutputCheckpoint(DebugOutputBase):
-    type: Literal["checkpoint"]
-    payload: CheckpointPayload
-
-
-DebugOutput = Union[DebugOutputTask, DebugOutputTaskResult, DebugOutputCheckpoint]
-
-
 TASK_NAMESPACE = UUID("6ba7b831-9dad-11d1-80b4-00c04fd430c8")
 
 
-def map_debug_tasks(
-    step: int, tasks: Iterable[PregelExecutableTask]
-) -> Iterator[DebugOutputTask]:
+def map_debug_tasks(tasks: Iterable[PregelExecutableTask]) -> Iterator[TaskPayload]:
     """Produce "task" events for stream_mode=debug."""
-    ts = datetime.now(timezone.utc).isoformat()
     for task in tasks:
         if task.config is not None and TAG_HIDDEN in task.config.get("tags", []):
             continue
 
         yield {
-            "type": "task",
-            "timestamp": ts,
-            "step": step,
-            "payload": {
-                "id": task.id,
-                "name": task.name,
-                "input": task.input,
-                "triggers": task.triggers,
-            },
+            "id": task.id,
+            "name": task.name,
+            "input": task.input,
+            "triggers": task.triggers,
         }
 
 
 def map_debug_task_results(
-    step: int,
     task_tup: tuple[PregelExecutableTask, Sequence[tuple[str, Any]]],
     stream_keys: str | Sequence[str],
-) -> Iterator[DebugOutputTaskResult]:
+) -> Iterator[TaskResultPayload]:
     """Produce "task_result" events for stream_mode=debug."""
     stream_channels_list = (
         [stream_keys] if isinstance(stream_keys, str) else stream_keys
     )
     task, writes = task_tup
     yield {
-        "type": "task_result",
-        "timestamp": datetime.now(timezone.utc).isoformat(),
-        "step": step,
-        "payload": {
-            "id": task.id,
-            "name": task.name,
-            "error": next((w[1] for w in writes if w[0] == ERROR), None),
-            "result": [
-                w for w in writes if w[0] in stream_channels_list or w[0] == RETURN
-            ],
-            "interrupts": [
-                asdict(v)
-                for w in writes
-                if w[0] == INTERRUPT
-                for v in (w[1] if isinstance(w[1], Sequence) else [w[1]])
-            ],
-        },
+        "id": task.id,
+        "name": task.name,
+        "error": next((w[1] for w in writes if w[0] == ERROR), None),
+        "result": [w for w in writes if w[0] in stream_channels_list or w[0] == RETURN],
+        "interrupts": [
+            asdict(v)
+            for w in writes
+            if w[0] == INTERRUPT
+            for v in (w[1] if isinstance(w[1], Sequence) else [w[1]])
+        ],
     }
 
 
@@ -159,17 +115,15 @@ def rm_pregel_keys(config: RunnableConfig | None) -> RunnableConfig | None:
 
 
 def map_debug_checkpoint(
-    step: int,
     config: RunnableConfig,
     channels: Mapping[str, BaseChannel],
     stream_channels: str | Sequence[str],
     metadata: CheckpointMetadata,
-    checkpoint: Checkpoint,
     tasks: Iterable[PregelExecutableTask],
     pending_writes: list[PendingWrite],
     parent_config: RunnableConfig | None,
     output_keys: str | Sequence[str],
-) -> Iterator[DebugOutputCheckpoint]:
+) -> Iterator[CheckpointPayload]:
     """Produce "checkpoint" events for stream_mode=debug."""
 
     parent_ns = config[CONF].get(CONFIG_KEY_CHECKPOINT_NS, "")
@@ -193,42 +147,35 @@ def map_debug_checkpoint(
         }
 
     yield {
-        "type": "checkpoint",
-        "timestamp": checkpoint["ts"],
-        "step": step,
-        "payload": {
-            "config": rm_pregel_keys(patch_checkpoint_map(config, metadata)),
-            "parent_config": rm_pregel_keys(
-                patch_checkpoint_map(parent_config, metadata)
-            ),
-            "values": read_channels(channels, stream_channels),
-            "metadata": metadata,
-            "next": [t.name for t in tasks],
-            "tasks": [
-                {
-                    "id": t.id,
-                    "name": t.name,
-                    "error": t.error,
-                    "state": t.state,
-                }
-                if t.error
-                else {
-                    "id": t.id,
-                    "name": t.name,
-                    "result": t.result,
-                    "interrupts": tuple(asdict(i) for i in t.interrupts),
-                    "state": t.state,
-                }
-                if t.result
-                else {
-                    "id": t.id,
-                    "name": t.name,
-                    "interrupts": tuple(asdict(i) for i in t.interrupts),
-                    "state": t.state,
-                }
-                for t in tasks_w_writes(tasks, pending_writes, task_states, output_keys)
-            ],
-        },
+        "config": rm_pregel_keys(patch_checkpoint_map(config, metadata)),
+        "parent_config": rm_pregel_keys(patch_checkpoint_map(parent_config, metadata)),
+        "values": read_channels(channels, stream_channels),
+        "metadata": metadata,
+        "next": [t.name for t in tasks],
+        "tasks": [
+            {
+                "id": t.id,
+                "name": t.name,
+                "error": t.error,
+                "state": t.state,
+            }
+            if t.error
+            else {
+                "id": t.id,
+                "name": t.name,
+                "result": t.result,
+                "interrupts": tuple(asdict(i) for i in t.interrupts),
+                "state": t.state,
+            }
+            if t.result
+            else {
+                "id": t.id,
+                "name": t.name,
+                "interrupts": tuple(asdict(i) for i in t.interrupts),
+                "state": t.state,
+            }
+            for t in tasks_w_writes(tasks, pending_writes, task_states, output_keys)
+        ],
     }
 
 

libs/langgraph/langgraph/pregel/loop.py

@@ -11,6 +11,7 @@ from contextlib import (
     AsyncExitStack,
     ExitStack,
 )
+from datetime import datetime, timezone
 from inspect import signature
 from types import TracebackType
 from typing import (
@@ -28,7 +29,6 @@ from typing_extensions import ParamSpec, Self
 
 from langgraph.cache.base import BaseCache
 from langgraph.channels.base import BaseChannel
-from langgraph.channels.last_value import LastValue
 from langgraph.checkpoint.base import (
     EXCLUDED_METADATA_KEYS,
     WRITES_IDX_MAP,
@@ -38,7 +38,6 @@ from langgraph.checkpoint.base import (
     CheckpointMetadata,
     CheckpointTuple,
     PendingWrite,
-    copy_checkpoint,
 )
 from langgraph.constants import (
     CONF,
@@ -85,6 +84,7 @@ from langgraph.pregel.algo import (
 )
 from langgraph.pregel.checkpoint import (
     channels_from_checkpoint,
+    copy_checkpoint,
     create_checkpoint,
     empty_checkpoint,
 )
@@ -119,6 +119,7 @@ from langgraph.types import (
     PregelScratchpad,
     RetryPolicy,
     StreamChunk,
+    StreamMode,
     StreamProtocol,
 )
 from langgraph.utils.config import patch_configurable
@@ -422,7 +423,7 @@ class PregelLoop:
             ),
         ):
             # produce debug output
-            self._emit("debug", map_debug_tasks, self.step, [pushed])
+            self._emit("tasks", map_debug_tasks, [pushed])
             # debug flag
             if self.debug:
                 print_step_tasks(self.step, [pushed])
@@ -472,9 +473,8 @@ class PregelLoop:
         # produce debug output
         if self._checkpointer_put_after_previous is not None:
             self._emit(
-                "debug",
+                "checkpoints",
                 map_debug_checkpoint,
-                self.step - 1,  # printing checkpoint for previous step
                 {
                     **self.checkpoint_config,
                     CONF: {
@@ -485,7 +485,6 @@ class PregelLoop:
                 self.channels,
                 self.stream_keys,
                 self.checkpoint_metadata,
-                self.checkpoint,
                 self.tasks.values(),
                 self.checkpoint_pending_writes,
                 self.prev_checkpoint_config,
@@ -509,7 +508,7 @@ class PregelLoop:
             raise GraphInterrupt()
 
         # produce debug output
-        self._emit("debug", map_debug_tasks, self.step, self.tasks.values())
+        self._emit("tasks", map_debug_tasks, self.tasks.values())
 
         # debug flag
         if self.debug:
@@ -834,17 +833,39 @@ class PregelLoop:
 
     def _emit(
         self,
-        mode: str,
+        mode: StreamMode,
         values: Callable[P, Iterator[Any]],
         *args: P.args,
         **kwargs: P.kwargs,
     ) -> None:
         if self.stream is None:
             return
-        if mode not in self.stream.modes:
+        debug_remap = mode in ("checkpoints", "tasks") and "debug" in self.stream.modes
+        if mode not in self.stream.modes and not debug_remap:
             return
         for v in values(*args, **kwargs):
-            self.stream((self.checkpoint_ns, mode, v))
+            if mode in self.stream.modes:
+                self.stream((self.checkpoint_ns, mode, v))
+            # "debug" mode is "checkpoints" or "tasks" with a wrapper dict
+            if debug_remap:
+                self.stream(
+                    (
+                        self.checkpoint_ns,
+                        "debug",
+                        {
+                            "step": self.step - 1
+                            if mode == "checkpoints"
+                            else self.step,
+                            "timestamp": datetime.now(timezone.utc).isoformat(),
+                            "type": "checkpoint"
+                            if mode == "checkpoints"
+                            else "task_result"
+                            if "result" in v
+                            else "task",
+                            "payload": v,
+                        },
+                    )
+                )
 
     def output_writes(
         self, task_id: str, writes: WritesT, *, cached: bool = False
@@ -885,9 +906,8 @@ class PregelLoop:
                 )
             if not cached:
                 self._emit(
-                    "debug",
+                    "tasks",
                     map_debug_task_results,
-                    self.step,
                     (task, writes),
                     self.stream_keys,
                 )
@@ -942,13 +962,7 @@ class SyncPregelLoop(PregelLoop, AbstractContextManager):
         )
         self.stack = ExitStack()
         if checkpointer:
-            if checkpointer._get_next_version_legacy:
-                empty_channel: LastValue[Any] = LastValue(Any)
-                self.checkpointer_get_next_version = (
-                    lambda c: checkpointer.get_next_version(c, empty_channel)  # type: ignore[call-arg]
-                )
-            else:
-                self.checkpointer_get_next_version = checkpointer.get_next_version
+            self.checkpointer_get_next_version = checkpointer.get_next_version
             self.checkpointer_put_writes = checkpointer.put_writes
             self.checkpointer_put_writes_accepts_task_path = (
                 signature(checkpointer.put_writes).parameters.get("task_path")
@@ -1121,13 +1135,7 @@ class AsyncPregelLoop(PregelLoop, AbstractAsyncContextManager):
         )
         self.stack = AsyncExitStack()
         if checkpointer:
-            if checkpointer._get_next_version_legacy:
-                empty_channel: LastValue[Any] = LastValue(Any)
-                self.checkpointer_get_next_version = (
-                    lambda c: checkpointer.get_next_version(c, empty_channel)  # type: ignore[call-arg]
-                )
-            else:
-                self.checkpointer_get_next_version = checkpointer.get_next_version
+            self.checkpointer_get_next_version = checkpointer.get_next_version
             self.checkpointer_put_writes = checkpointer.aput_writes
             self.checkpointer_put_writes_accepts_task_path = (
                 signature(checkpointer.aput_writes).parameters.get("task_path")

libs/langgraph/langgraph/types.py

@@ -46,7 +46,9 @@ Checkpointer = Union[None, bool, BaseCheckpointSaver]
 - False disables checkpointing, even if the parent graph has a checkpointer.
 - None inherits checkpointer from the parent graph."""
 
-StreamMode = Literal["values", "updates", "debug", "messages", "custom"]
+StreamMode = Literal[
+    "values", "updates", "checkpoints", "tasks", "debug", "messages", "custom"
+]
 """How the stream method should emit outputs.
 
 - `"values"`: Emit all values in the state after each step, including interrupts.
@@ -55,7 +57,9 @@ StreamMode = Literal["values", "updates", "debug", "messages", "custom"]
     If multiple updates are made in the same step (e.g. multiple nodes are run) then those updates are emitted separately.
 - `"custom"`: Emit custom data using from inside nodes or tasks using `StreamWriter`.
 - `"messages"`: Emit LLM messages token-by-token together with metadata for any LLM invocations inside nodes or tasks.
-- `"debug"`: Emit debug events with as much information as possible for each step.
+- `"checkpoints"`: Emit an event when a checkpoint is created, in the same format as returned by get_state().
+- `"tasks"`: Emit events when tasks start and finish, including their results and errors.
+- `"debug"`: Emit "checlkpoints" and "tasks" events, for debugging purposes.
 """
 
 StreamWriter = Callable[[Any], None]

libs/langgraph/langgraph/warnings.py

@@ -41,8 +41,8 @@ class LangGraphDeprecationWarning(DeprecationWarning):
         return message
 
 
-class LangGraphDeprecatedSinceV10(LangGraphDeprecationWarning):
-    """A specific `LangGraphDeprecationWarning` subclass defining functionality deprecated since LangGraph v1.0.0"""
+class LangGraphDeprecatedSinceV05(LangGraphDeprecationWarning):
+    """A specific `LangGraphDeprecationWarning` subclass defining functionality deprecated since LangGraph v0.5.0"""
 
     def __init__(self, message: str, *args: object) -> None:
-        super().__init__(message, *args, since=(1, 0), expected_removal=(2, 0))
+        super().__init__(message, *args, since=(0, 5), expected_removal=(2, 0))

libs/langgraph/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph"
-version = "0.4.7"
+version = "0.5.0rc1"
 description = "Building stateful, multi-actor applications with LLMs"
 authors = []
 requires-python = ">=3.9"
@@ -13,9 +13,9 @@ license = "MIT"
 license-files = ['LICENSE']
 dependencies = [
     "langchain-core>=0.1",
-    "langgraph-checkpoint>=2.0.26",
+    "langgraph-checkpoint>=2.1.0",
     "langgraph-sdk>=0.1.42",
-    "langgraph-prebuilt>=0.2.0",
+    "langgraph-prebuilt>=0.5.0rc0",
     "xxhash>=3.5.0",
     "pydantic>=2.7.4",
 ]

libs/langgraph/tests/conftest.py

@@ -12,6 +12,7 @@ from langgraph.checkpoint.base import BaseCheckpointSaver
 from langgraph.store.base import BaseStore
 from tests.conftest_checkpointer import (
     _checkpointer_memory,
+    _checkpointer_memory_migrate_sends,
     _checkpointer_postgres,
     _checkpointer_postgres_aio,
     _checkpointer_postgres_aio_pipe,
@@ -125,6 +126,7 @@ async def async_store(request: pytest.FixtureRequest) -> AsyncIterator[BaseStore
     if NO_DOCKER
     else [
         "memory",
+        "memory_migrate_sends",
         "sqlite",
         "sqlite_aes",
         "postgres",
@@ -139,6 +141,9 @@ def sync_checkpointer(
     if checkpointer_name == "memory":
         with _checkpointer_memory() as checkpointer:
             yield checkpointer
+    elif checkpointer_name == "memory_migrate_sends":
+        with _checkpointer_memory_migrate_sends() as checkpointer:
+            yield checkpointer
     elif checkpointer_name == "sqlite":
         with _checkpointer_sqlite() as checkpointer:
             yield checkpointer

libs/langgraph/tests/conftest_checkpointer.py

@@ -14,7 +14,10 @@ from langgraph.checkpoint.sqlite.aio import AsyncSqliteSaver
 
 pytest.register_assert_rewrite("tests.memory_assert")
 
-from tests.memory_assert import MemorySaverAssertImmutable  # noqa: E402
+from tests.memory_assert import (  # noqa: E402
+    MemorySaverAssertImmutable,
+    MemorySaverNeedsPendingSendsMigration,
+)
 
 DEFAULT_POSTGRES_URI = "postgres://postgres:postgres@localhost:5442/"
 
@@ -24,6 +27,11 @@ def _checkpointer_memory():
     yield MemorySaverAssertImmutable()
 
 
+@contextmanager
+def _checkpointer_memory_migrate_sends():
+    yield MemorySaverNeedsPendingSendsMigration()
+
+
 @contextmanager
 def _checkpointer_sqlite():
     with SqliteSaver.from_conn_string(":memory:") as checkpointer:
@@ -187,6 +195,7 @@ async def _checkpointer_postgres_aio_pool():
 
 __all__ = [
     "_checkpointer_memory",
+    "_checkpointer_memory_migrate_sends",
     "_checkpointer_sqlite",
     "_checkpointer_sqlite_aes",
     "_checkpointer_postgres",

libs/langgraph/tests/memory_assert.py

@@ -7,6 +7,7 @@ from typing import Any, Optional
 from langchain_core.runnables import RunnableConfig
 
 from langgraph.checkpoint.base import (
+    BaseCheckpointSaver,
     ChannelVersions,
     Checkpoint,
     CheckpointMetadata,
@@ -14,6 +15,7 @@ from langgraph.checkpoint.base import (
     SerializerProtocol,
 )
 from langgraph.checkpoint.memory import InMemorySaver, PersistentDict
+from langgraph.constants import TASKS
 
 
 class NoopSerializer(SerializerProtocol):
@@ -24,6 +26,28 @@ class NoopSerializer(SerializerProtocol):
         return "type", obj
 
 
+class MemorySaverNeedsPendingSendsMigration(BaseCheckpointSaver):
+    def __init__(self) -> None:
+        self.saver = InMemorySaver()
+
+    def __getattribute__(self, name):
+        if name in ("saver", "__class__", "get_tuple"):
+            return object.__getattribute__(self, name)
+        return getattr(self.saver, name)
+
+    def get_tuple(self, config):
+        if tup := self.saver.get_tuple(config):
+            if tup.checkpoint["v"] == 4 and tup.checkpoint["channel_values"].get(TASKS):
+                tup.checkpoint["v"] = 3
+                tup.checkpoint["pending_sends"] = tup.checkpoint["channel_values"].pop(
+                    TASKS
+                )
+                tup.checkpoint["channel_versions"].pop(TASKS)
+                for seen in tup.checkpoint["versions_seen"].values():
+                    seen.pop(TASKS, None)
+        return tup
+
+
 class MemorySaverAssertImmutable(InMemorySaver):
     storage_for_copies: defaultdict[str, dict[str, dict[str, Checkpoint]]]
 

libs/langgraph/tests/test_checkpoint_migration.py

@@ -7,12 +7,9 @@ from typing import Annotated, Literal, Optional, Union
 import pytest
 from typing_extensions import TypedDict
 
-from langgraph.checkpoint.base import (
-    BaseCheckpointSaver,
-    CheckpointTuple,
-    copy_checkpoint,
-)
+from langgraph.checkpoint.base import BaseCheckpointSaver, CheckpointTuple
 from langgraph.graph.state import StateGraph
+from langgraph.pregel.checkpoint import copy_checkpoint
 from langgraph.types import Command, Interrupt, PregelTask, StateSnapshot, interrupt
 from langgraph.utils.config import patch_configurable
 from tests.any_int import AnyInt

libs/langgraph/tests/test_deprecation.py

@@ -4,7 +4,7 @@ from typing_extensions import TypedDict
 from langgraph.func import entrypoint, task
 from langgraph.graph import StateGraph
 from langgraph.types import RetryPolicy
-from langgraph.warnings import LangGraphDeprecatedSinceV10
+from langgraph.warnings import LangGraphDeprecatedSinceV05
 
 
 class PlainState(TypedDict): ...
@@ -14,7 +14,7 @@ def test_add_node_retry_arg() -> None:
     builder = StateGraph(PlainState)
 
     with pytest.warns(
-        LangGraphDeprecatedSinceV10,
+        LangGraphDeprecatedSinceV05,
         match="`retry` is deprecated and will be removed. Please use `retry_policy` instead.",
     ):
         builder.add_node("test_node", lambda state: state, retry=RetryPolicy())  # type: ignore[arg-type]
@@ -22,7 +22,7 @@ def test_add_node_retry_arg() -> None:
 
 def test_task_retry_arg() -> None:
     with pytest.warns(
-        LangGraphDeprecatedSinceV10,
+        LangGraphDeprecatedSinceV05,
         match="`retry` is deprecated and will be removed. Please use `retry_policy` instead.",
     ):
 
@@ -33,7 +33,7 @@ def test_task_retry_arg() -> None:
 
 def test_entrypoint_retry_arg() -> None:
     with pytest.warns(
-        LangGraphDeprecatedSinceV10,
+        LangGraphDeprecatedSinceV05,
         match="`retry` is deprecated and will be removed. Please use `retry_policy` instead.",
     ):
 
@@ -44,7 +44,7 @@ def test_entrypoint_retry_arg() -> None:
 
 def test_state_graph_input_schema() -> None:
     with pytest.warns(
-        LangGraphDeprecatedSinceV10,
+        LangGraphDeprecatedSinceV05,
         match="`input` is deprecated and will be removed. Please use `input_schema` instead.",
     ):
         StateGraph(PlainState, input=PlainState)  # type: ignore[arg-type]
@@ -52,7 +52,7 @@ def test_state_graph_input_schema() -> None:
 
 def test_state_graph_output_schema() -> None:
     with pytest.warns(
-        LangGraphDeprecatedSinceV10,
+        LangGraphDeprecatedSinceV05,
         match="`output` is deprecated and will be removed. Please use `output_schema` instead.",
     ):
         StateGraph(PlainState, output=PlainState)  # type: ignore[arg-type]
@@ -62,7 +62,7 @@ def test_add_node_input_schema() -> None:
     builder = StateGraph(PlainState)
 
     with pytest.warns(
-        LangGraphDeprecatedSinceV10,
+        LangGraphDeprecatedSinceV05,
         match="`input` is deprecated and will be removed. Please use `input_schema` instead.",
     ):
         builder.add_node("test_node", lambda state: state, input=PlainState)  # type: ignore[arg-type]

libs/langgraph/tests/test_pregel.py

@@ -159,7 +159,7 @@ def test_checkpoint_errors() -> None:
             raise ValueError("Faulty put_writes")
 
     class FaultyVersionCheckpointer(InMemorySaver):
-        def get_next_version(self, current: Optional[int]) -> int:
+        def get_next_version(self, current: Optional[int], channel: None) -> int:
             raise ValueError("Faulty get_next_version")
 
     def logic(inp: str) -> str:

libs/langgraph/tests/test_pregel_async.py

@@ -103,7 +103,7 @@ async def test_checkpoint_errors() -> None:
             raise ValueError("Faulty put_writes")
 
     class FaultyVersionCheckpointer(InMemorySaver):
-        def get_next_version(self, current: Optional[int]) -> int:
+        def get_next_version(self, current: Optional[int], channel: None) -> int:
             raise ValueError("Faulty get_next_version")
 
     def logic(inp: str) -> str:

libs/langgraph/uv.lock

@@ -1201,7 +1201,7 @@ wheels = [
 
 [[package]]
 name = "langgraph"
-version = "0.4.7"
+version = "0.5.0rc1"
 source = { editable = "." }
 dependencies = [
     { name = "langchain-core" },
@@ -1310,7 +1310,7 @@ wheels = [
 
 [[package]]
 name = "langgraph-checkpoint"
-version = "2.0.26"
+version = "2.1.0"
 source = { editable = "../checkpoint" }
 dependencies = [
     { name = "langchain-core" },
@@ -1423,7 +1423,7 @@ inmem = [
 
 [[package]]
 name = "langgraph-prebuilt"
-version = "0.2.2"
+version = "0.5.0rc0"
 source = { editable = "../prebuilt" }
 dependencies = [
     { name = "langchain-core" },

libs/prebuilt/langgraph/prebuilt/chat_agent_executor.py

@@ -591,7 +591,7 @@ def create_react_agent(
         workflow = StateGraph(state_schema, config_schema=config_schema)
         workflow.add_node(
             "agent",
-            RunnableCallable(call_model, acall_model),  # type: ignore[call-overload]
+            RunnableCallable(call_model, acall_model),
             input_schema=input_schema,
         )
         if pre_model_hook is not None:
@@ -610,7 +610,7 @@ def create_react_agent(
         if response_format is not None:
             workflow.add_node(
                 "generate_structured_response",
-                RunnableCallable(  # type: ignore[call-overload]
+                RunnableCallable(
                     generate_structured_response,
                     agenerate_structured_response,
                 ),
@@ -660,10 +660,10 @@ def create_react_agent(
     # Define the two nodes we will cycle between
     workflow.add_node(
         "agent",
-        RunnableCallable(call_model, acall_model),  # type: ignore[call-overload]
+        RunnableCallable(call_model, acall_model),
         input_schema=input_schema,
     )
-    workflow.add_node("tools", tool_node)  # type: ignore[call-overload]
+    workflow.add_node("tools", tool_node)
 
     # Optionally add a pre-model hook node that will be called
     # every time before the "agent" (LLM-calling node)
@@ -693,7 +693,7 @@ def create_react_agent(
     if response_format is not None:
         workflow.add_node(
             "generate_structured_response",
-            RunnableCallable(  # type: ignore[call-overload]
+            RunnableCallable(
                 generate_structured_response,
                 agenerate_structured_response,
             ),

libs/prebuilt/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-prebuilt"
-version = "0.2.2"
+version = "0.5.0rc0"
 description = "Library with high-level APIs for creating and executing LangGraph agents and tools."
 authors = []
 requires-python = ">=3.9"
@@ -12,7 +12,7 @@ readme = "README.md"
 license = "MIT"
 license-files = ['LICENSE']
 dependencies = [
-    "langgraph-checkpoint>=2.0.10",
+    "langgraph-checkpoint>=2.1.0",
     "langchain-core>=0.3.22",
 ]
 

libs/prebuilt/tests/memory_assert.py

@@ -13,9 +13,9 @@ from langgraph.checkpoint.base import (
     CheckpointMetadata,
     CheckpointTuple,
     SerializerProtocol,
-    copy_checkpoint,
 )
 from langgraph.checkpoint.memory import InMemorySaver, PersistentDict
+from langgraph.pregel.checkpoint import copy_checkpoint
 
 
 class NoopSerializer(SerializerProtocol):

libs/prebuilt/uv.lock

@@ -320,7 +320,7 @@ wheels = [
 
 [[package]]
 name = "langgraph"
-version = "0.4.7"
+version = "0.5.0rc0"
 source = { editable = "../langgraph" }
 dependencies = [
     { name = "langchain-core" },
@@ -371,7 +371,7 @@ dev = [
 
 [[package]]
 name = "langgraph-checkpoint"
-version = "2.0.26"
+version = "2.1.0"
 source = { editable = "../checkpoint" }
 dependencies = [
     { name = "langchain-core" },
@@ -464,7 +464,7 @@ dev = [
 
 [[package]]
 name = "langgraph-prebuilt"
-version = "0.2.2"
+version = "0.5.0rc0"
 source = { editable = "." }
 dependencies = [
     { name = "langchain-core" },

libs/sdk-py/langgraph_sdk/schema.py

@@ -36,7 +36,15 @@ Represents the status of a thread:
 """
 
 StreamMode = Literal[
-    "values", "messages", "updates", "events", "debug", "custom", "messages-tuple"
+    "values",
+    "messages",
+    "updates",
+    "events",
+    "tasks",
+    "checkpoints",
+    "debug",
+    "custom",
+    "messages-tuple",
 ]
 """
 Defines the mode of streaming:
@@ -44,6 +52,8 @@ Defines the mode of streaming:
 - "messages": Stream complete messages.
 - "updates": Stream updates to the state.
 - "events": Stream events occurring during execution.
+- "checkpoints": Stream checkpoints as they are created.
+- "tasks": Stream task start and finish events.
 - "debug": Stream detailed debug information.
 - "custom": Stream custom events.
 """