chore(langgraph): bump version (#6245)

- Bump langgraph version from 0.6.8 to 0.6.9

.github/ISSUE_TEMPLATE/config.yml

@@ -1,6 +1,9 @@
 blank_issues_enabled: false
 version: 2.1
 contact_links:
+  - name: Documentation
+    url: https://github.com/langchain-ai/docs/issues/new?template=langgraph.yml
+    about: Report an issue related to the LangGraph documentation
   - name: LangChain Forum
     url:  https://forum.langchain.com/
-    about: General community discussions, support, and feature requests
+    about: General community discussions and support

.github/ISSUE_TEMPLATE/documentation.yml

@@ -1,19 +0,0 @@
-name: Documentation
-description: Report an issue related to the LangGraph documentation.
-title: "DOC: <Please write a comprehensive title after the 'DOC: ' prefix>"
-labels: [documentation]
-
-body:
-- type: textarea
-  attributes: 
-    label: "Issue with current documentation:"
-    description: >
-      Please make sure to leave a reference to the document/code you're
-      referring to.
-
-- type: textarea
-  attributes:
-    label: "Idea or request for content:"
-    description: >
-      Please describe as clearly as possible what topics you think are missing
-      from the current documentation.

.github/workflows/_integration_test.yml

@@ -58,8 +58,8 @@ jobs:
           # Build the image for this example
           langgraph build -t ${{ matrix.example.tag }}
           # Prepare environment file from local or parent example directory
-          if [ -f .env.example ]; then cp .env.example .env; elif [ -f ../.env.example ]; then cp ../.env.example .env; fi
-          if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
+          if [ -f .env.example ]; then cp .env.example .env; elif [ -f ../.env.example ]; then cp ../.env.example .env && cp ../.env.example ../.env; fi
+          if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; if [ -f ../.env ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> ../.env; fi; fi
           # Run the integration test using the built tag
           # Compute repo root to reference the shared script robustly
           REPO_ROOT=$(git rev-parse --show-toplevel)
@@ -94,3 +94,17 @@ jobs:
           cp ../.env.example .env
           if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
           timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-h
+          LANGGRAPH_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langgraph'); print(v);")
+          if [ "$LANGGRAPH_VERSION" != "1.0.0a2" ]; then
+            exit 1
+          fi
+          LANGCHAIN_OPENAI_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langchain-openai'); print(v);")
+          if [ "$LANGCHAIN_OPENAI_VERSION" != "0.3.0" ]; then
+            exit 1
+          fi
+
+      - name: Build and test prerelease reqs fail service
+        if: steps.changed-files.outputs.all
+        working-directory: libs/cli/examples/graph_prerelease_reqs_fail
+        run: |
+          langgraph build -t langgraph-test-i || [ $? -eq 1 ]

.github/workflows/bench.yml

@@ -57,7 +57,7 @@ jobs:
             echo EOF
           } >> "$GITHUB_OUTPUT"
       - name: Annotation
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             const file = JSON.parse(`${{ steps.files.outputs.added_modified_renamed }}`)[0]

.github/workflows/uv_lock_ugprade.yml

@@ -33,8 +33,8 @@ jobs:
         uses: peter-evans/create-pull-request@v7
         with:
           token: ${{ secrets.GITHUB_TOKEN }}
-          commit-message: "chore[deps]: upgrade dependencies with `uv lock --upgrade`"
-          title: "chore[deps]: upgrade dependencies with `uv lock --upgrade`"
+          commit-message: "chore(deps): upgrade dependencies with `uv lock --upgrade`"
+          title: "chore(deps): upgrade dependencies with `uv lock --upgrade`"
           body: |
             This PR updates the dependencies in all Python packages using `uv lock --upgrade`.
             

CONTRIBUTING.md

@@ -277,9 +277,9 @@ def my_function(arg1: int, arg2: str) -> float:
     Examples:
         This is a section for examples of how to use the function.
 
-        .. code-block:: python
-
-            my_function(1, "hello")
+        ```python
+        my_function(1, "hello")
+        \```
 
     Args:
         arg1: This is a description of arg1. We do not need to specify the type since

docs/README.md

@@ -1,24 +1,126 @@
-# Setup
+# LangGraph Documentation
 
-To setup requirements for building docs you can run:
+For more information on contributing to our documentation, see the [Contributing Guide](../CONTRIBUTING.md).
 
-```bash
-uv sync --group test
+## Structure
+
+The primary documentation is located in the `docs/` directory. This directory contains both the source files for the main documentation as well as the API reference doc build process.
+
+### Main Documentation
+
+Main documentation files are located in `docs/docs/` and are written in Markdown format. The site uses [**MkDocs**](https://www.mkdocs.org/) with the [Material theme](https://squidfunk.github.io/mkdocs-material/) and includes:
+
+- **Concepts**: Core LangGraph concepts and explanations
+- **Tutorials**: Step-by-step learning guides
+- **How-tos**: Task-focused guides for specific use cases
+- **Examples**: Real-world applications and use cases
+- **Jupyter Notebooks**: Interactive tutorials that are automatically converted to markdown
+
+### API Reference
+
+API reference documentation is defined in `docs/docs/reference/`. Each `.md` file outlines the "template" that each page is built from. Reference content is automatically generated from docstrings in the codebase using the **mkdocstrings** plugin. Once generated, the content is plugged into the corresponding markdown file where it is referenced by using manual directives to specify which classes and/or functions are documented:
+
+```markdown
+::: langgraph.graph.state.StateGraph
+    options:
+      show_if_no_docstring: true
+      show_root_heading: true
+      show_root_full_path: false
+      members:
+        - add_node
+        - add_edge
+        - add_conditional_edges
+        - add_sequence
+        - compile
 ```
 
-## Serving documentation locally
+## Build Process
 
-To run the documentation server locally you can run:
+Docs are built following these steps:
+
+1. **Content Processing:**
+   - `_scripts/notebook_hooks.py` - Main processing pipeline that:
+     - Converts how-tos/tutorial Jupyter notebooks to markdown using `notebook_convert.py`
+     - Adds automatic API reference links to code blocks using `generate_api_reference_links.py`
+     - Handles conditional rendering for Python/JS versions
+     - Processes highlight comments and custom syntax
+
+2. **API Reference Generation:**
+   - **mkdocstrings** plugin extracts docstrings from Python source code
+   - Manual `::: module.Class` directives in reference pages (`/docs/docs/*`) specify what to document
+   - Cross-references are automatically generated between docs and API
+
+3. **Site Generation:**
+   - **MkDocs** processes all markdown files and generates static HTML
+   - Custom hooks handle redirects and inject additional functionality
+
+4. **Deployment:**
+   - Site is deployed with Vercel
+   - `make build-docs` generates production build (also usable for local testing)
+   - Automatic redirects handle URL changes between versions
+
+### Local Development
+
+For local development, use the Makefile targets:
 
 ```bash
+# Serve docs locally with hot reloading
 make serve-docs
+
+# Clean build for production testing
+make build-docs
+
+# Serve with clean build
+make serve-clean-docs
 ```
 
-This will start the documentation server on [http://127.0.0.1:8000/langgraph/](http://127.0.0.1:8000/langgraph/).
+The `serve-docs` command:
+
+- Watches source files for changes
+- Includes dirty builds for faster iteration
+- Serves on [http://127.0.0.1:8000/langgraph/](http://127.0.0.1:8000/langgraph/)
+
+## Standards
+
+**Docstring Format:**
+The API reference uses **Google-style docstrings** with Markdown markup. The `mkdocstrings` plugin processes these to generate documentation.
+
+**Required format:**
+
+```python
+def example_function(param1: str, param2: int = 5) -> bool:
+    """Brief description of the function.
+
+    Longer description can go here. Use Markdown syntax for
+    rich formatting like **bold** and *italic*.
+
+    Args:
+        param1: Description of the first parameter.
+        param2: Description of the second parameter with default value.
+
+    Returns:
+        Description of the return value.
+
+    Raises:
+        ValueError: When param1 is empty.
+        TypeError: When param2 is not an integer.
+
+    !!! warning
+        This function is experimental and may change.
+
+    !!! version-added "Added in version 0.2.0"
+    """
+```
+
+**Special Markers:**
+
+- **MkDocs admonitions**: `!!! warning`, `!!! note`, `!!! version-added`
+- **Code blocks**: Standard markdown ``` syntax
+- **Cross-references**: Automatic linking via `generate_api_reference_links.py`
 
 ## Execute notebooks
 
-If you would like to automatically execute all of the notebooks, to mimic the "Run notebooks" GHA, you can run:
+If you would like to automatically execute all of the notebooks, to mimic the "Run notebooks" GitHub action, you can run:
 
 ```bash
 python _scripts/prepare_notebooks_for_ci.py
@@ -33,8 +135,9 @@ python _scripts/prepare_notebooks_for_ci.py --comment-install-cells
 ```
 
 `prepare_notebooks_for_ci.py` script will add VCR cassette context manager for each cell in the notebook, so that:
-* when the notebook is run for the first time, cells with network requests will be recorded to a VCR cassette file
-* when the notebook is run subsequently, the cells with network requests will be replayed from the cassettes
+
+- when the notebook is run for the first time, cells with network requests will be recorded to a VCR cassette file
+- when the notebook is run subsequently, the cells with network requests will be replayed from the cassettes
 
 ## Adding new notebooks
 

docs/_scripts/generate_api_reference_links.py

@@ -1,3 +1,5 @@
+"""Generate API reference links for imports in Python code blocks within markdown files."""
+
 import ast
 import importlib
 import logging
@@ -70,8 +72,18 @@ MANUAL_API_REFERENCES_LANGGRAPH = [
     ([], "langgraph.checkpoint.postgres.aio", "AsyncPostgresSaver", "checkpoints"),
     ([], "langgraph.checkpoint.postgres", "PostgresSaver", "checkpoints"),
     # other prebuilts
-    (["langgraph_supervisor"], "langgraph_supervisor.supervisor", "create_supervisor", "supervisor"),
-    (["langgraph_supervisor"], "langgraph_supervisor.handoff", "create_handoff_tool", "supervisor"),
+    (
+        ["langgraph_supervisor"],
+        "langgraph_supervisor.supervisor",
+        "create_supervisor",
+        "supervisor",
+    ),
+    (
+        ["langgraph_supervisor"],
+        "langgraph_supervisor.handoff",
+        "create_handoff_tool",
+        "supervisor",
+    ),
     ([], "langgraph_supervisor.handoff", "create_forward_message_tool", "supervisor"),
     (["langgraph_swarm"], "langgraph_swarm.swarm", "create_swarm", "swarm"),
     (["langgraph_swarm"], "langgraph_swarm.swarm", "add_active_agent_router", "swarm"),

docs/_scripts/js_translation/codeblocks/yarn.lock

@@ -2108,9 +2108,9 @@ __metadata:
   linkType: hard
 
 "hono@npm:^4.5.4":
-  version: 4.9.6
-  resolution: "hono@npm:4.9.6"
-  checksum: 10c0/182a144eb3b9e05bd9e43d15af15c93f60d3d747fef6c6904b9993e9db8129ea7fadf6190331d6f76b1bf6dd2b2c3b13efea105236f541ef411397e30475422d
+  version: 4.9.7
+  resolution: "hono@npm:4.9.7"
+  checksum: 10c0/089184660a9211ea216ab95bafa45260e371651cb019db49828064b7982b0ae61cc3c4715324bfeb9037aa2460c39ffa2c91d84ad0c8d500fa77cbcc7fc07a8f
   languageName: node
   linkType: hard
 

docs/_scripts/notebook_convert.py

@@ -1,3 +1,5 @@
+"""Convert Jupyter notebooks to markdown with custom processing."""
+
 import ast
 import os
 import re

docs/_scripts/notebook_hooks.py

@@ -144,13 +144,13 @@ REDIRECT_MAP = {
     "concepts/langgraph_cli.md": "https://docs.langchain.com/langgraph-platform/langgraph-cli",
     "concepts/langgraph_studio.md": "https://docs.langchain.com/langgraph-platform/langgraph-studio",
     "cloud/how-tos/studio/quick_start.md": "https://docs.langchain.com/langgraph-platform/quick-start-studio",
-    "cloud/how-tos/invoke_studio.md": "https://docs.langchain.com/langgraph-platform/invoke-studio",
-    "cloud/how-tos/studio/manage_assistants.md": "https://docs.langchain.com/langgraph-platform/manage-assistants-studio",
-    "cloud/how-tos/threads_studio.md": "https://docs.langchain.com/langgraph-platform/threads-studio",
-    "cloud/how-tos/iterate_graph_studio.md": "https://docs.langchain.com/langgraph-platform/iterate-graph-studio",
-    "cloud/how-tos/studio/run_evals.md": "https://docs.langchain.com/langgraph-platform/run-evals-studio",
-    "cloud/how-tos/clone_traces_studio.md": "https://docs.langchain.com/langgraph-platform/clone-traces-studio",
-    "cloud/how-tos/datasets_studio.md": "https://docs.langchain.com/langgraph-platform/datasets-studio",
+    "cloud/how-tos/invoke_studio.md": "https://docs.langchain.com/langgraph-platform/use-studio#run-application",
+    "cloud/how-tos/studio/manage_assistants.md": "https://docs.langchain.com/langgraph-platform/use-studio#manage-assistants",
+    "cloud/how-tos/threads_studio.md": "https://docs.langchain.com/langgraph-platform/use-studio#manage-threads",
+    "cloud/how-tos/iterate_graph_studio.md": "https://docs.langchain.com/langgraph-platform/observability-studio#iterate-on-prompts",
+    "cloud/how-tos/studio/run_evals.md": "https://docs.langchain.com/langgraph-platform/observability-studio#run-experiments-over-a-dataset",
+    "cloud/how-tos/clone_traces_studio.md": "https://docs.langchain.com/langgraph-platform/observability-studio#debug-langsmith-traces",
+    "cloud/how-tos/datasets_studio.md": "https://docs.langchain.com/langgraph-platform/observability-studio#add-node-to-dataset",
     "concepts/sdk.md": "https://docs.langchain.com/langgraph-platform/sdk",
     "concepts/plans.md": "https://docs.langchain.com/langgraph-platform/plans",
     "concepts/application_structure.md": "https://docs.langchain.com/langgraph-platform/application-structure",

docs/docs/agents/context.md

@@ -33,7 +33,7 @@ LangGraph provides three ways to manage context, which combines the mutability a
 
 **Static runtime context** represents immutable data like user metadata, tools, and database connections that are passed to an application at the start of a run via the `context` argument to `invoke`/`stream`. This data does not change during execution.
 
-!!! version-added "New in LangGraph v0.6: `context` replaces `config['configurable']`"
+!!! version-added "Added in version 0.6.0: `context` replaces `config['configurable']`"
 
     Runtime context is now passed to the `context` argument of `invoke`/`stream`,
     which replaces the previous pattern of passing application configuration to `config['configurable']`.

docs/docs/agents/models.md

@@ -211,7 +211,7 @@ output = agent.invoke(
 print(output["messages"][-1].text())
 ```
 
-!!! version-added "New in LangGraph v0.6"
+!!! version-added "Added in version 0.6.0"
 
 :::
 
@@ -351,11 +351,13 @@ If your desired LLM isn't officially supported by LangChain, consider these opti
 :::python
 
 1. **Implement a custom LangChain chat model**: Create a model conforming to the [LangChain chat model interface](https://python.langchain.com/docs/how_to/custom_chat_model/). This enables full compatibility with LangGraph's agents and workflows but requires understanding of the LangChain framework.
+
    :::
 
 :::js
 
 1. **Implement a custom LangChain chat model**: Create a model conforming to the [LangChain chat model interface](https://js.langchain.com/docs/how_to/custom_chat/). This enables full compatibility with LangGraph's agents and workflows but requires understanding of the LangChain framework.
+
    :::
 
 2. **Direct invocation with custom streaming**: Use your model directly by [adding custom streaming logic](../how-tos/streaming.md#use-with-any-llm) with `StreamWriter`.
@@ -371,6 +373,7 @@ If your desired LLM isn't officially supported by LangChain, consider these opti
 - [Force model to call a specific tool](https://python.langchain.com/docs/how_to/tool_choice/)
 - [All chat model how-to guides](https://python.langchain.com/docs/how_to/#chat-models)
 - [Chat model integrations](https://python.langchain.com/docs/integrations/chat/)
+
   :::
 
 :::js
@@ -381,4 +384,5 @@ If your desired LLM isn't officially supported by LangChain, consider these opti
 - [Force model to call a specific tool](https://js.langchain.com/docs/how_to/tool_choice/)
 - [All chat model how-to guides](https://js.langchain.com/docs/how_to/#chat-models)
 - [Chat model integrations](https://js.langchain.com/docs/integrations/chat/)
+
   :::

docs/docs/how-tos/tool-calling.md

@@ -244,7 +244,7 @@ output = agent.invoke(
 print(output["messages"][-1].text())
 ```
 
-!!! version-added "New in langgraph>=0.6"
+!!! version-added "Added in version 0.6.0"
 
 :::
 

docs/overrides/main.html

@@ -291,7 +291,7 @@ j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src=
     }
 
     .md-banner {
-      background-color: #CFC9FA;
+      background-color: #FFAE42;
       color: #000000;
     }
 
@@ -360,5 +360,5 @@ j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src=
 {% endblock %}
 
 {% block announce %}
-Our new LangChain Academy Course Deep Research with LangGraph is now live! <a href="https://academy.langchain.com/courses/deep-research-with-langgraph/?utm_medium=internal&utm_source=docs&utm_campaign=q3-2025_deep-research-course_co" target="_blank">Enroll for free</a>.
+These docs will be deprecated and removed with the release of LangGraph v1.0 in October 2025. <a href="https://docs.langchain.com/oss/python/langgraph/overview" target="_blank">Visit the v1.0 alpha docs</a>
 {% endblock %}

docs/pyproject.toml

@@ -7,14 +7,14 @@ name = "langgraph-docs"
 version = "0.0.1"
 description = "LangGraph docs"
 authors = []
-requires-python = "~=3.11"
+requires-python = ">=3.11.0,<4.0.0"
 readme = "README.md"
 license = "MIT"
 dependencies = [
     "aiohappyeyeballs==2.4.3",
-    "hub>=3.0.1,<4",
-    "xxhash>=3.5.0,<4",
-    "black>=25.1.0,<26",
+    "hub>=3.0.1,<4.0.0",
+    "xxhash>=3.5.0,<4.0.0",
+    "black>=25.1.0,<26.0.0",
 ]
 
 [dependency-groups]

docs/uv.lock

@@ -1,5 +1,5 @@
 version = 1
-revision = 2
+revision = 3
 requires-python = ">=3.11, <4"
 resolution-markers = [
     "python_full_version >= '3.13' and platform_python_implementation != 'PyPy'",
@@ -2337,7 +2337,7 @@ wheels = [
 
 [[package]]
 name = "langgraph"
-version = "0.6.2"
+version = "0.6.7"
 source = { editable = "../libs/langgraph" }
 dependencies = [
     { name = "langchain-core" },
@@ -2380,6 +2380,7 @@ dev = [
     { name = "pytest-repeat" },
     { name = "pytest-watcher" },
     { name = "pytest-xdist", extras = ["psutil"] },
+    { name = "redis" },
     { name = "ruff" },
     { name = "syrupy" },
     { name = "types-requests" },
@@ -2413,6 +2414,7 @@ dev = [
     { name = "pytest-asyncio" },
     { name = "pytest-mock" },
     { name = "pytest-watcher" },
+    { name = "redis" },
     { name = "ruff" },
 ]
 
@@ -2643,7 +2645,7 @@ test = [
 
 [[package]]
 name = "langgraph-prebuilt"
-version = "0.6.2"
+version = "0.6.4"
 source = { editable = "../libs/prebuilt" }
 dependencies = [
     { name = "langchain-core" },
@@ -2674,7 +2676,6 @@ dev = [
 
 [[package]]
 name = "langgraph-sdk"
-version = "0.2.0"
 source = { editable = "../libs/sdk-py" }
 dependencies = [
     { name = "httpx" },

examples/persistence_postgres.ipynb

@@ -5,7 +5,7 @@
    "id": "18526f23",
    "metadata": {},
    "source": [
-    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/persistence_postgres.ipynb"
+    "This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/memory/add-memory.md"
    ]
   }
  ],

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

@@ -7,11 +7,6 @@ from contextlib import contextmanager
 from typing import Any
 
 from langchain_core.runnables import RunnableConfig
-from psycopg import Capabilities, Connection, Cursor, Pipeline
-from psycopg.rows import DictRow, dict_row
-from psycopg.types.json import Jsonb
-from psycopg_pool import ConnectionPool
-
 from langgraph.checkpoint.base import (
     WRITES_IDX_MAP,
     ChannelVersions,
@@ -19,12 +14,17 @@ from langgraph.checkpoint.base import (
     CheckpointMetadata,
     CheckpointTuple,
     get_checkpoint_id,
-    get_checkpoint_metadata,
+    get_serializable_checkpoint_metadata,
 )
+from langgraph.checkpoint.serde.base import SerializerProtocol
+from psycopg import Capabilities, Connection, Cursor, Pipeline
+from psycopg.rows import DictRow, dict_row
+from psycopg.types.json import Jsonb
+from psycopg_pool import ConnectionPool
+
 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
 
@@ -325,7 +325,7 @@ class PostgresSaver(BasePostgresSaver):
                     checkpoint["id"],
                     checkpoint_id,
                     Jsonb(copy),
-                    Jsonb(get_checkpoint_metadata(config, metadata)),
+                    Jsonb(get_serializable_checkpoint_metadata(config, metadata)),
                 ),
             )
         return next_config
@@ -450,7 +450,7 @@ class PostgresSaver(BasePostgresSaver):
             {
                 **value["checkpoint"],
                 "channel_values": {
-                    **value["checkpoint"].get("channel_values"),
+                    **(value["checkpoint"].get("channel_values") or {}),
                     **self._load_blobs(value["channel_values"]),
                 },
             },

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

@@ -7,11 +7,6 @@ from contextlib import asynccontextmanager
 from typing import Any
 
 from langchain_core.runnables import RunnableConfig
-from psycopg import AsyncConnection, AsyncCursor, AsyncPipeline, Capabilities
-from psycopg.rows import DictRow, dict_row
-from psycopg.types.json import Jsonb
-from psycopg_pool import AsyncConnectionPool
-
 from langgraph.checkpoint.base import (
     WRITES_IDX_MAP,
     ChannelVersions,
@@ -19,12 +14,17 @@ from langgraph.checkpoint.base import (
     CheckpointMetadata,
     CheckpointTuple,
     get_checkpoint_id,
-    get_checkpoint_metadata,
+    get_serializable_checkpoint_metadata,
 )
+from langgraph.checkpoint.serde.base import SerializerProtocol
+from psycopg import AsyncConnection, AsyncCursor, AsyncPipeline, Capabilities
+from psycopg.rows import DictRow, dict_row
+from psycopg.types.json import Jsonb
+from psycopg_pool import AsyncConnectionPool
+
 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
 
@@ -283,7 +283,7 @@ class AsyncPostgresSaver(BasePostgresSaver):
                     checkpoint["id"],
                     checkpoint_id,
                     Jsonb(copy),
-                    Jsonb(get_checkpoint_metadata(config, metadata)),
+                    Jsonb(get_serializable_checkpoint_metadata(config, metadata)),
                 ),
             )
         return next_config
@@ -409,7 +409,7 @@ class AsyncPostgresSaver(BasePostgresSaver):
             {
                 **value["checkpoint"],
                 "channel_values": {
-                    **value["checkpoint"].get("channel_values"),
+                    **(value["checkpoint"].get("channel_values") or {}),
                     **self._load_blobs(value["channel_values"]),
                 },
             },

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

@@ -1,12 +1,12 @@
 from __future__ import annotations
 
 import random
+import warnings
 from collections.abc import Sequence
+from importlib.metadata import version as get_version
 from typing import Any, Optional, cast
 
 from langchain_core.runnables import RunnableConfig
-from psycopg.types.json import Jsonb
-
 from langgraph.checkpoint.base import (
     WRITES_IDX_MAP,
     BaseCheckpointSaver,
@@ -14,9 +14,22 @@ from langgraph.checkpoint.base import (
     get_checkpoint_id,
 )
 from langgraph.checkpoint.serde.types import TASKS
+from psycopg.types.json import Jsonb
 
 MetadataInput = Optional[dict[str, Any]]
 
+try:
+    major, minor = get_version("langgraph").split(".")[:2]
+    if int(major) == 0 and int(minor) < 5:
+        warnings.warn(
+            "You're using incompatible versions of langgraph and checkpoint-postgres. Please upgrade langgraph to avoid unexpected behavior.",
+            DeprecationWarning,
+            stacklevel=2,
+        )
+except Exception:
+    # skip version check if running from source
+    pass
+
 """
 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.

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

@@ -6,6 +6,16 @@ from contextlib import asynccontextmanager, contextmanager
 from typing import Any, Optional
 
 from langchain_core.runnables import RunnableConfig
+from langgraph.checkpoint.base import (
+    WRITES_IDX_MAP,
+    ChannelVersions,
+    Checkpoint,
+    CheckpointMetadata,
+    CheckpointTuple,
+    get_serializable_checkpoint_metadata,
+)
+from langgraph.checkpoint.serde.base import SerializerProtocol
+from langgraph.checkpoint.serde.types import TASKS
 from psycopg import (
     AsyncConnection,
     AsyncCursor,
@@ -19,18 +29,8 @@ 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.
@@ -441,7 +441,7 @@ class ShallowPostgresSaver(BasePostgresSaver):
                     thread_id,
                     checkpoint_ns,
                     Jsonb(copy),
-                    Jsonb(get_checkpoint_metadata(config, metadata)),
+                    Jsonb(get_serializable_checkpoint_metadata(config, metadata)),
                 ),
             )
         return next_config
@@ -774,7 +774,7 @@ class AsyncShallowPostgresSaver(BasePostgresSaver):
                     thread_id,
                     checkpoint_ns,
                     Jsonb(copy),
-                    Jsonb(get_checkpoint_metadata(config, metadata)),
+                    Jsonb(get_serializable_checkpoint_metadata(config, metadata)),
                 ),
             )
         return next_config

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

@@ -1,4 +1,4 @@
 from langgraph.store.postgres.aio import AsyncPostgresStore
-from langgraph.store.postgres.base import PostgresStore
+from langgraph.store.postgres.base import PoolConfig, PostgresStore
 
-__all__ = ["AsyncPostgresStore", "PostgresStore"]
+__all__ = ["AsyncPostgresStore", "PoolConfig", "PostgresStore"]

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

@@ -8,11 +8,6 @@ from types import TracebackType
 from typing import Any, Callable, cast
 
 import orjson
-from psycopg import AsyncConnection, AsyncCursor, AsyncPipeline, Capabilities
-from psycopg.rows import DictRow, dict_row
-from psycopg_pool import AsyncConnectionPool
-
-from langgraph.checkpoint.postgres import _ainternal
 from langgraph.store.base import (
     GetOp,
     ListNamespacesOp,
@@ -22,6 +17,11 @@ from langgraph.store.base import (
     SearchOp,
 )
 from langgraph.store.base.batch import AsyncBatchedBaseStore
+from psycopg import AsyncConnection, AsyncCursor, AsyncPipeline, Capabilities
+from psycopg.rows import DictRow, dict_row
+from psycopg_pool import AsyncConnectionPool
+
+from langgraph.checkpoint.postgres import _ainternal
 from langgraph.store.postgres.base import (
     PLACEHOLDER,
     BasePostgresStore,

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

@@ -22,14 +22,6 @@ from typing import (
 )
 
 import orjson
-from psycopg import Capabilities, Connection, Cursor, Pipeline
-from psycopg.rows import DictRow, dict_row
-from psycopg.types.json import Jsonb
-from psycopg_pool import ConnectionPool
-from typing_extensions import TypedDict
-
-from langgraph.checkpoint.postgres import _ainternal as _ainternal
-from langgraph.checkpoint.postgres import _internal as _pg_internal
 from langgraph.store.base import (
     BaseStore,
     GetOp,
@@ -46,6 +38,14 @@ from langgraph.store.base import (
     get_text_at_path,
     tokenize_path,
 )
+from psycopg import Capabilities, Connection, Cursor, Pipeline
+from psycopg.rows import DictRow, dict_row
+from psycopg.types.json import Jsonb
+from psycopg_pool import ConnectionPool
+from typing_extensions import TypedDict
+
+from langgraph.checkpoint.postgres import _ainternal as _ainternal
+from langgraph.checkpoint.postgres import _internal as _pg_internal
 
 if TYPE_CHECKING:
     from langchain_core.embeddings import Embeddings

libs/checkpoint-postgres/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-checkpoint-postgres"
-version = "2.0.23"
+version = "2.0.25"
 description = "Library with a Postgres implementation of LangGraph checkpoint saver."
 authors = []
 requires-python = ">=3.9"
@@ -12,7 +12,7 @@ readme = "README.md"
 license = "MIT"
 license-files = ['LICENSE']
 dependencies = [
-  "langgraph-checkpoint>=2.0.21,<3.0.0",
+  "langgraph-checkpoint>=2.1.2,<3.0.0",
   "orjson>=3.10.1",
   "psycopg>=3.2.0",
   "psycopg-pool>=3.2.0",

libs/checkpoint-postgres/tests/test_async.py

@@ -6,10 +6,6 @@ from uuid import uuid4
 
 import pytest
 from langchain_core.runnables import RunnableConfig
-from psycopg import AsyncConnection
-from psycopg.rows import dict_row
-from psycopg_pool import AsyncConnectionPool
-
 from langgraph.checkpoint.base import (
     EXCLUDED_METADATA_KEYS,
     Checkpoint,
@@ -17,11 +13,15 @@ from langgraph.checkpoint.base import (
     create_checkpoint,
     empty_checkpoint,
 )
+from langgraph.checkpoint.serde.types import TASKS
+from psycopg import AsyncConnection
+from psycopg.rows import dict_row
+from psycopg_pool import AsyncConnectionPool
+
 from langgraph.checkpoint.postgres.aio import (
     AsyncPostgresSaver,
     AsyncShallowPostgresSaver,
 )
-from langgraph.checkpoint.serde.types import TASKS
 from tests.conftest import DEFAULT_POSTGRES_URI
 
 
@@ -187,13 +187,11 @@ def test_data():
     metadata_1: CheckpointMetadata = {
         "source": "input",
         "step": 2,
-        "writes": {},
         "score": 1,
     }
     metadata_2: CheckpointMetadata = {
         "source": "loop",
         "step": 1,
-        "writes": {"foo": "bar"},
         "score": None,
     }
     metadata_3: CheckpointMetadata = {}
@@ -220,7 +218,6 @@ async def test_combined_metadata(saver_name: str, test_data) -> None:
         metadata: CheckpointMetadata = {
             "source": "loop",
             "step": 1,
-            "writes": {"foo": "bar"},
             "score": None,
         }
         await saver.aput(config, chkpnt, metadata, {})
@@ -246,7 +243,6 @@ async def test_asearch(saver_name: str, test_data) -> None:
         query_1 = {"source": "input"}  # search by 1 key
         query_2 = {
             "step": 1,
-            "writes": {"foo": "bar"},
         }  # search by multiple keys
         query_3: dict[str, Any] = {}  # search by no keys, return all checkpoints
         query_4 = {"source": "update", "step": 1}  # no match
@@ -344,3 +340,34 @@ async def test_pending_sends_migration(saver_name: str) -> None:
             TASKS: ["send-1", "send-2", "send-3"]
         }
         assert TASKS in search_results[0].checkpoint["channel_versions"]
+
+
+@pytest.mark.parametrize("saver_name", ["base", "pool", "pipe"])
+async def test_get_checkpoint_no_channel_values(
+    monkeypatch, saver_name: str, test_data
+) -> None:
+    """Backwards compatibility test that verifies a checkpoint with no channel_values key can be retrieved without throwing an error."""
+    async with _saver(saver_name) as saver:
+        config = {
+            "configurable": {
+                "thread_id": "thread-2",
+                "checkpoint_ns": "",
+                "__super_private_key": "super_private_value",
+            },
+            "metadata": {"run_id": "my_run_id"},
+        }
+        chkpnt: Checkpoint = create_checkpoint(empty_checkpoint(), {}, 1)
+        await saver.aput(config, chkpnt, {}, {})
+
+        load_checkpoint_tuple = saver._load_checkpoint_tuple
+
+        def patched_load_checkpoint_tuple(value):
+            value["checkpoint"].pop("channel_values", None)
+            return load_checkpoint_tuple(value)
+
+        monkeypatch.setattr(
+            saver, "_load_checkpoint_tuple", patched_load_checkpoint_tuple
+        )
+
+        checkpoint = await saver.aget_tuple(config)
+        assert checkpoint.checkpoint["channel_values"] == {}

libs/checkpoint-postgres/tests/test_async_store.py

@@ -12,8 +12,6 @@ from typing import Any
 
 import pytest
 from langchain_core.embeddings import Embeddings
-from psycopg import AsyncConnection
-
 from langgraph.store.base import (
     GetOp,
     Item,
@@ -21,6 +19,8 @@ from langgraph.store.base import (
     PutOp,
     SearchOp,
 )
+from psycopg import AsyncConnection
+
 from langgraph.store.postgres import AsyncPostgresStore
 from tests.conftest import (
     DEFAULT_URI,

libs/checkpoint-postgres/tests/test_store.py

@@ -9,8 +9,6 @@ from uuid import uuid4
 
 import pytest
 from langchain_core.embeddings import Embeddings
-from psycopg import Connection
-
 from langgraph.store.base import (
     GetOp,
     Item,
@@ -19,6 +17,8 @@ from langgraph.store.base import (
     PutOp,
     SearchOp,
 )
+from psycopg import Connection
+
 from langgraph.store.postgres import PostgresStore
 from tests.conftest import (
     DEFAULT_URI,
@@ -879,12 +879,7 @@ def test_non_ascii(
     distance_type: str,
 ) -> None:
     """Test support for non-ascii characters"""
-    with _create_vector_store(
-        vector_type,
-        distance_type,
-        fake_embeddings
-    ) as store:
-    
+    with _create_vector_store(vector_type, distance_type, fake_embeddings) as store:
         store.put(("user_123", "memories"), "1", {"text": "这是中文"})  # Chinese
         store.put(
             ("user_123", "memories"), "2", {"text": "これは日本語です"}

libs/checkpoint-postgres/tests/test_sync.py

@@ -7,10 +7,6 @@ from uuid import uuid4
 
 import pytest
 from langchain_core.runnables import RunnableConfig
-from psycopg import Connection
-from psycopg.rows import dict_row
-from psycopg_pool import ConnectionPool
-
 from langgraph.checkpoint.base import (
     EXCLUDED_METADATA_KEYS,
     Checkpoint,
@@ -18,8 +14,12 @@ from langgraph.checkpoint.base import (
     create_checkpoint,
     empty_checkpoint,
 )
-from langgraph.checkpoint.postgres import PostgresSaver, ShallowPostgresSaver
 from langgraph.checkpoint.serde.types import TASKS
+from psycopg import Connection
+from psycopg.rows import dict_row
+from psycopg_pool import ConnectionPool
+
+from langgraph.checkpoint.postgres import PostgresSaver, ShallowPostgresSaver
 from tests.conftest import DEFAULT_POSTGRES_URI
 
 
@@ -169,13 +169,11 @@ def test_data():
     metadata_1: CheckpointMetadata = {
         "source": "input",
         "step": 2,
-        "writes": {},
         "score": 1,
     }
     metadata_2: CheckpointMetadata = {
         "source": "loop",
         "step": 1,
-        "writes": {"foo": "bar"},
         "score": None,
     }
     metadata_3: CheckpointMetadata = {}
@@ -202,7 +200,6 @@ def test_combined_metadata(saver_name: str, test_data) -> None:
         metadata: CheckpointMetadata = {
             "source": "loop",
             "step": 1,
-            "writes": {"foo": "bar"},
             "score": None,
         }
         saver.put(config, chkpnt, metadata, {})
@@ -228,7 +225,6 @@ def test_search(saver_name: str, test_data) -> None:
         query_1 = {"source": "input"}  # search by 1 key
         query_2 = {
             "step": 1,
-            "writes": {"foo": "bar"},
         }  # search by multiple keys
         query_3: dict[str, Any] = {}  # search by no keys, return all checkpoints
         query_4 = {"source": "update", "step": 1}  # no match
@@ -332,3 +328,33 @@ def test_pending_sends_migration(saver_name: str) -> None:
             TASKS: ["send-1", "send-2", "send-3"]
         }
         assert TASKS in search_results[0].checkpoint["channel_versions"]
+
+
+@pytest.mark.parametrize("saver_name", ["base", "pool", "pipe"])
+def test_get_checkpoint_no_channel_values(
+    monkeypatch, saver_name: str, test_data
+) -> None:
+    """Backwards compatibility test that verifies a checkpoint with no channel_values key can be retrieved without throwing an error."""
+    with _saver(saver_name) as saver:
+        config = {
+            "configurable": {
+                "thread_id": "thread-2",
+                "checkpoint_ns": "",
+                "__super_private_key": "super_private_value",
+            },
+        }
+        chkpnt: Checkpoint = create_checkpoint(empty_checkpoint(), {}, 1)
+        saver.put(config, chkpnt, {}, {})
+
+        load_checkpoint_tuple = saver._load_checkpoint_tuple
+
+        def patched_load_checkpoint_tuple(value):
+            value["checkpoint"].pop("channel_values", None)
+            return load_checkpoint_tuple(value)
+
+        monkeypatch.setattr(
+            saver, "_load_checkpoint_tuple", patched_load_checkpoint_tuple
+        )
+
+        checkpoint = saver.get_tuple(config)
+        assert checkpoint.checkpoint["channel_values"] == {}

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

@@ -8,7 +8,6 @@ from contextlib import closing, contextmanager
 from typing import Any, cast
 
 from langchain_core.runnables import RunnableConfig
-
 from langgraph.checkpoint.base import (
     WRITES_IDX_MAP,
     BaseCheckpointSaver,
@@ -21,6 +20,7 @@ from langgraph.checkpoint.base import (
     get_checkpoint_metadata,
 )
 from langgraph.checkpoint.serde.jsonplus import JsonPlusSerializer
+
 from langgraph.checkpoint.sqlite.utils import search_where
 
 _AIO_ERROR_MSG = (

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

@@ -8,7 +8,6 @@ from typing import Any, Callable, TypeVar, cast
 
 import aiosqlite
 from langchain_core.runnables import RunnableConfig
-
 from langgraph.checkpoint.base import (
     WRITES_IDX_MAP,
     BaseCheckpointSaver,
@@ -21,6 +20,7 @@ from langgraph.checkpoint.base import (
     get_checkpoint_metadata,
 )
 from langgraph.checkpoint.serde.jsonplus import JsonPlusSerializer
+
 from langgraph.checkpoint.sqlite.utils import search_where
 
 T = TypeVar("T", bound=Callable)

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

@@ -5,7 +5,6 @@ from collections.abc import Sequence
 from typing import Any
 
 from langchain_core.runnables import RunnableConfig
-
 from langgraph.checkpoint.base import get_checkpoint_id
 
 

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

@@ -11,7 +11,6 @@ from typing import Any, Callable, cast
 import aiosqlite
 import orjson
 import sqlite_vec  # type: ignore[import-untyped]
-
 from langgraph.store.base import (
     GetOp,
     ListNamespacesOp,
@@ -22,6 +21,7 @@ from langgraph.store.base import (
     TTLConfig,
 )
 from langgraph.store.base.batch import AsyncBatchedBaseStore
+
 from langgraph.store.sqlite.base import (
     _PLACEHOLDER,
     BaseSqliteStore,
@@ -507,7 +507,9 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore):
             results: List to store results in.
             cur: Database cursor.
         """
-        queries, embedding_requests = self._prepare_batch_search_queries(search_ops)
+        prepared_queries, embedding_requests = self._prepare_batch_search_queries(
+            search_ops
+        )
 
         # Setup dot_product function if it doesn't exist
         if embedding_requests and self.embeddings:
@@ -515,23 +517,60 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore):
                 [query for _, query in embedding_requests]
             )
 
-            for (idx, _), embedding in zip(embedding_requests, vectors):
-                _params_list: list = queries[idx][1]
-                for i, param in enumerate(_params_list):
-                    if param is _PLACEHOLDER:
-                        _params_list[i] = sqlite_vec.serialize_float32(embedding)
+            for (embed_req_idx, _), embedding in zip(embedding_requests, vectors):
+                # Find the corresponding query in prepared_queries
+                # The embed_req_idx is the original index in search_ops, which should map to prepared_queries
+                if embed_req_idx < len(prepared_queries):
+                    _params_list: list = prepared_queries[embed_req_idx][1]
+                    for i, param in enumerate(_params_list):
+                        if param is _PLACEHOLDER:
+                            _params_list[i] = sqlite_vec.serialize_float32(embedding)
+                else:
+                    logger.warning(
+                        f"Embedding request index {embed_req_idx} out of bounds for prepared_queries."
+                    )
 
-        for (idx, _), (query, params) in zip(search_ops, queries):
+        for (original_op_idx, _), (query, params, needs_refresh) in zip(
+            search_ops, prepared_queries
+        ):
             await cur.execute(query, params)
             rows = await cur.fetchall()
 
-            if "score" in query:
+            if needs_refresh and rows and self.ttl_config:
+                keys_to_refresh = []
+                for row_data in rows:
+                    # Assuming row_data[0] is prefix (text), row_data[1] is key (text)
+                    # These are raw text values directly from the DB.
+                    keys_to_refresh.append((row_data[0], row_data[1]))
+
+                if keys_to_refresh:
+                    updates_by_prefix = defaultdict(list)
+                    for prefix_text, key_text in keys_to_refresh:
+                        updates_by_prefix[prefix_text].append(key_text)
+
+                    for prefix_text, key_list in updates_by_prefix.items():
+                        placeholders = ",".join(["?"] * len(key_list))
+                        update_query = f"""
+                            UPDATE store
+                            SET expires_at = DATETIME(CURRENT_TIMESTAMP, '+' || ttl_minutes || ' minutes')
+                            WHERE prefix = ? AND key IN ({placeholders}) AND ttl_minutes IS NOT NULL
+                        """
+                        update_params = (prefix_text, *key_list)
+                        try:
+                            await cur.execute(update_query, update_params)
+                        except Exception as e:
+                            logger.error(
+                                f"Error during TTL refresh update for search: {e}"
+                            )
+
+            # Process rows into items
+            if "score" in query:  # Vector search query
                 items = [
                     _row_to_search_item(
-                        _decode_ns_text(row[0]),
+                        _decode_ns_text(row[0]),  # prefix
                         {
-                            "key": row[1],
-                            "value": row[2],
+                            "key": row[1],  # key
+                            "value": row[2],  # value
                             "created_at": row[3],
                             "updated_at": row[4],
                             "expires_at": row[5] if len(row) > 5 else None,
@@ -545,10 +584,10 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore):
             else:  # Regular search query
                 items = [
                     _row_to_search_item(
-                        _decode_ns_text(row[0]),
+                        _decode_ns_text(row[0]),  # prefix
                         {
-                            "key": row[1],
-                            "value": row[2],
+                            "key": row[1],  # key
+                            "value": row[2],  # value
                             "created_at": row[3],
                             "updated_at": row[4],
                             "expires_at": row[5] if len(row) > 5 else None,
@@ -559,7 +598,7 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore):
                     for row in rows
                 ]
 
-            results[idx] = items
+            results[original_op_idx] = items
 
     async def _batch_list_namespaces_ops(
         self,

libs/checkpoint-sqlite/langgraph/store/sqlite/base.py

@@ -13,7 +13,6 @@ from typing import Any, Callable, Literal, NamedTuple, cast
 
 import orjson
 import sqlite_vec  # type: ignore[import-untyped]
-
 from langgraph.store.base import (
     BaseStore,
     GetOp,
@@ -372,13 +371,15 @@ class BaseSqliteStore:
     def _prepare_batch_search_queries(
         self, search_ops: Sequence[tuple[int, SearchOp]]
     ) -> tuple[
-        list[tuple[str, list[None | str | list[float]]]],  # queries, params
+        list[
+            tuple[str, list[None | str | list[float]], bool]
+        ],  # queries, params, needs_refresh
         list[tuple[int, str]],  # idx, query_text pairs to embed
     ]:
         """
-        Build per-SearchOp SQL queries (with optional TTL refresh) plus embedding requests.
+        Build per-SearchOp SQL queries (with optional TTL refresh flag) plus embedding requests.
         Returns:
-        - queries: list of (SQL, param_list)
+        - queries: list of (SQL, param_list, needs_ttl_refresh_flag)
         - embedding_requests: list of (original_index_in_search_ops, text_query)
         """
         queries = []
@@ -519,30 +520,18 @@ class BaseSqliteStore:
                 logger.debug(f"Search query: {base_query}")
                 logger.debug(f"Search params: {params}")
 
-            # Handle TTL refresh if requested
-            if (
+            # Determine if TTL refresh is needed
+            needs_ttl_refresh = bool(
                 op.refresh_ttl
                 and self.ttl_config
                 and self.ttl_config.get("refresh_on_read", False)
-            ):
-                final_sql = f"""
-                    WITH search_results AS (
-                        {base_query}
-                    ),
-                    updated AS (
-                        UPDATE store
-                        SET expires_at = DATETIME(CURRENT_TIMESTAMP, '+' || ttl_minutes || ' minutes')
-                        WHERE (prefix, key) IN (SELECT prefix, key FROM search_results)
-                        AND ttl_minutes IS NOT NULL
-                    )
-                    SELECT * FROM search_results
-                """
-                final_params = params[:]  # copy params
-            else:
-                final_sql = base_query
-                final_params = params
+            )
 
-            queries.append((final_sql, final_params))
+            # The base_query is now the final_sql, and we pass the refresh flag
+            final_sql = base_query
+            final_params = params
+
+            queries.append((final_sql, final_params, needs_ttl_refresh))
 
         return queries, embedding_requests
 
@@ -1331,7 +1320,9 @@ class SqliteStore(BaseSqliteStore, BaseStore):
         results: list[Result],
         cur: sqlite3.Cursor,
     ) -> None:
-        queries, embedding_requests = self._prepare_batch_search_queries(search_ops)
+        prepared_queries, embedding_requests = self._prepare_batch_search_queries(
+            search_ops
+        )
 
         # Setup similarity functions if they don't exist
         if embedding_requests and self.embeddings:
@@ -1341,16 +1332,48 @@ class SqliteStore(BaseSqliteStore, BaseStore):
             )
 
             # Replace placeholders with actual embeddings
-            for (idx, _), embedding in zip(embedding_requests, embeddings):
-                _params_list: list = queries[idx][1]
-                for i, param in enumerate(_params_list):
-                    if param is _PLACEHOLDER:
-                        _params_list[i] = sqlite_vec.serialize_float32(embedding)
+            for (embed_req_idx, _), embedding in zip(embedding_requests, embeddings):
+                if embed_req_idx < len(prepared_queries):
+                    _params_list: list = prepared_queries[embed_req_idx][1]
+                    for i, param in enumerate(_params_list):
+                        if param is _PLACEHOLDER:
+                            _params_list[i] = sqlite_vec.serialize_float32(embedding)
+                else:
+                    logger.warning(
+                        f"Embedding request index {embed_req_idx} out of bounds for prepared_queries."
+                    )
 
-        for (idx, _), (query, params) in zip(search_ops, queries):
+        for (original_op_idx, _), (query, params, needs_refresh) in zip(
+            search_ops, prepared_queries
+        ):
             cur.execute(query, params)
             rows = cur.fetchall()
 
+            if needs_refresh and rows and self.ttl_config:
+                keys_to_refresh = []
+                for row_data in rows:
+                    keys_to_refresh.append((row_data[0], row_data[1]))
+
+                if keys_to_refresh:
+                    updates_by_prefix = defaultdict(list)
+                    for prefix_text, key_text in keys_to_refresh:
+                        updates_by_prefix[prefix_text].append(key_text)
+
+                    for prefix_text, key_list in updates_by_prefix.items():
+                        placeholders = ",".join(["?"] * len(key_list))
+                        update_query = f"""
+                            UPDATE store
+                            SET expires_at = DATETIME(CURRENT_TIMESTAMP, '+' || ttl_minutes || ' minutes')
+                            WHERE prefix = ? AND key IN ({placeholders}) AND ttl_minutes IS NOT NULL
+                        """
+                        update_params = (prefix_text, *key_list)
+                        try:
+                            cur.execute(update_query, update_params)
+                        except Exception as e:
+                            logger.error(
+                                f"Error during TTL refresh update for search: {e}"
+                            )
+
             if "score" in query:  # Vector search query
                 items = [
                     _row_to_search_item(
@@ -1385,7 +1408,7 @@ class SqliteStore(BaseSqliteStore, BaseStore):
                     for row in rows
                 ]
 
-            results[idx] = items
+            results[original_op_idx] = items
 
     def _batch_list_namespaces_ops(
         self,

libs/checkpoint-sqlite/tests/test_aiosqlite.py

@@ -2,13 +2,13 @@ from typing import Any
 
 import pytest
 from langchain_core.runnables import RunnableConfig
-
 from langgraph.checkpoint.base import (
     Checkpoint,
     CheckpointMetadata,
     create_checkpoint,
     empty_checkpoint,
 )
+
 from langgraph.checkpoint.sqlite.aio import AsyncSqliteSaver
 
 

libs/checkpoint-sqlite/tests/test_async_store.py

@@ -8,7 +8,6 @@ from contextlib import asynccontextmanager
 from typing import Optional, Union, cast
 
 import pytest
-
 from langgraph.store.base import (
     GetOp,
     Item,
@@ -16,6 +15,7 @@ from langgraph.store.base import (
     PutOp,
     SearchOp,
 )
+
 from langgraph.store.sqlite import AsyncSqliteStore
 from langgraph.store.sqlite.base import SqliteIndexConfig
 from tests.test_store import CharacterEmbeddings

libs/checkpoint-sqlite/tests/test_sqlite.py

@@ -2,13 +2,13 @@ from typing import Any, cast
 
 import pytest
 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
 
@@ -116,7 +116,17 @@ class TestSqliteSaver:
                 search_results_5[1].config["configurable"]["checkpoint_ns"],
             } == {"", "inner"}
 
-            # TODO: test before and limit params
+            # search with before param
+            search_results_6 = list(saver.list(None, before=search_results_5[1].config))
+            assert len(search_results_6) == 1
+            assert search_results_6[0].config["configurable"]["thread_id"] == "thread-1"
+
+            # search with limit param
+            search_results_7 = list(
+                saver.list({"configurable": {"thread_id": "thread-2"}}, limit=1)
+            )
+            assert len(search_results_7) == 1
+            assert search_results_7[0].config["configurable"]["thread_id"] == "thread-2"
 
     def test_search_where(self) -> None:
         # call method / assertions

libs/checkpoint-sqlite/tests/test_store.py

@@ -9,7 +9,6 @@ from typing import Any, Literal, Optional, Union, cast
 
 import pytest
 from langchain_core.embeddings import Embeddings
-
 from langgraph.store.base import (
     GetOp,
     Item,
@@ -18,6 +17,7 @@ from langgraph.store.base import (
     PutOp,
     SearchOp,
 )
+
 from langgraph.store.sqlite import SqliteStore
 from langgraph.store.sqlite.base import SqliteIndexConfig
 

libs/checkpoint-sqlite/tests/test_ttl.py

@@ -7,6 +7,7 @@ import time
 from collections.abc import Generator
 
 import pytest
+from langgraph.store.base import TTLConfig
 
 from langgraph.store.sqlite import SqliteStore
 from langgraph.store.sqlite.aio import AsyncSqliteStore
@@ -93,9 +94,13 @@ def test_ttl_sweeper(temp_db_file: str) -> None:
     ttl_seconds = 2
     ttl_minutes = ttl_seconds / 60
 
+    ttl_config: TTLConfig = {
+        "default_ttl": ttl_minutes,
+        "sweep_interval_minutes": ttl_minutes / 2,
+    }
     with SqliteStore.from_conn_string(
         temp_db_file,
-        ttl={"default_ttl": ttl_minutes, "sweep_interval_minutes": ttl_minutes / 2},
+        ttl=ttl_config,
     ) as store:
         store.setup()
 
@@ -298,9 +303,14 @@ async def test_async_ttl_sweeper(temp_db_file: str) -> None:
     ttl_seconds = 2
     ttl_minutes = ttl_seconds / 60
 
+    ttl_config: TTLConfig = {
+        "default_ttl": ttl_minutes,
+        "sweep_interval_minutes": ttl_minutes / 2,
+    }
+
     async with AsyncSqliteStore.from_conn_string(
         temp_db_file,
-        ttl={"default_ttl": ttl_minutes, "sweep_interval_minutes": ttl_minutes / 2},
+        ttl=ttl_config,
     ) as store:
         await store.setup()
 
@@ -353,3 +363,67 @@ async def test_async_search_with_ttl(temp_db_file: str) -> None:
         # Search after expiration
         results = await store.asearch(("test",), filter={"value": "apple"})
         assert len(results) == 0
+
+
+@pytest.mark.asyncio
+@pytest.mark.flaky(retries=3)
+async def test_async_asearch_refresh_ttl(temp_db_file: str) -> None:
+    """Test TTL refresh on asearch with async API."""
+    ttl_seconds = 4.0  # Increased TTL for less sensitivity to timing
+    ttl_minutes = ttl_seconds / 60.0
+
+    async with AsyncSqliteStore.from_conn_string(
+        temp_db_file, ttl={"default_ttl": ttl_minutes, "refresh_on_read": True}
+    ) as store:
+        await store.setup()
+
+        namespace = ("docs", "user1")
+        # t=0: items put, expire at t=4.0s
+        await store.aput(namespace, "item1", {"text": "content1", "id": 1})
+        await store.aput(namespace, "item2", {"text": "content2", "id": 2})
+
+        # t=3.0s: (after sleep ttl_seconds * 0.75 = 3s)
+        await asyncio.sleep(ttl_seconds * 0.75)
+
+        # Perform asearch with refresh_ttl=True for item1.
+        # item1's TTL should be refreshed. New expiry: t=3.0s + 4.0s = t=7.0s.
+        # item2's TTL is not affected. Expires at t=4.0s.
+        searched_items = await store.asearch(
+            namespace, filter={"id": 1}, refresh_ttl=True
+        )
+        assert len(searched_items) == 1
+        assert searched_items[0].key == "item1"
+
+        # t=5.0s: (after sleep ttl_seconds * 0.5 = 2s more. Total elapsed: 3s + 2s = 5s)
+        await asyncio.sleep(ttl_seconds * 0.5)
+        # At this point:
+        # - item1 (refreshed by asearch) should expire at t=7.0s. Should be ALIVE.
+        # - item2 (original TTL) should have expired at t=4.0s. Should be GONE after sweep.
+
+        await store.sweep_ttl()
+
+        # Check item1 (should exist due to asearch refresh)
+        item1_check1 = await store.aget(namespace, "item1", refresh_ttl=False)
+        assert item1_check1 is not None, (
+            "Item1 should exist after asearch refresh and first sweep"
+        )
+        assert item1_check1.value["text"] == "content1"
+
+        # Check item2 (should be gone)
+        item2_check1 = await store.aget(namespace, "item2", refresh_ttl=False)
+        assert item2_check1 is None, (
+            "Item2 should be gone after its original TTL expired"
+        )
+
+        # t=7.5s: (after sleep ttl_seconds * 0.625 = 2.5s more. Total elapsed: 5s + 2.5s = 7.5s)
+        await asyncio.sleep(ttl_seconds * 0.625)
+        # At this point:
+        # - item1 (refreshed by asearch, expired at t=7.0s) should be GONE after sweep.
+
+        await store.sweep_ttl()
+
+        # Check item1 again (should be gone now)
+        item1_final_check = await store.aget(namespace, "item1", refresh_ttl=False)
+        assert item1_final_check is None, (
+            "Item1 should be gone after its refreshed TTL expired"
+        )

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

@@ -404,6 +404,16 @@ def get_checkpoint_metadata(
     return metadata
 
 
+def get_serializable_checkpoint_metadata(
+    config: RunnableConfig, metadata: CheckpointMetadata
+) -> CheckpointMetadata:
+    """Get checkpoint metadata in a backwards-compatible manner."""
+    checkpoint_metadata = get_checkpoint_metadata(config, metadata)
+    if "writes" in checkpoint_metadata:
+        checkpoint_metadata.pop("writes")
+    return checkpoint_metadata
+
+
 """
 Mapping from error type to error index.
 Regular writes just map to their index in the list of writes being saved.

libs/checkpoint/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-checkpoint"
-version = "2.1.1"
+version = "2.1.2"
 description = "Library with base interfaces for LangGraph checkpoint savers."
 authors = []
 requires-python = ">=3.9"

libs/checkpoint/tests/test_store.py

@@ -950,8 +950,8 @@ async def test_embed_with_path(fake_embeddings: CharacterEmbeddings) -> None:
     assert results[0].key != results[1].key
     ascore = results[0].score
     bscore = results[1].score
-    assert ascore == bscore
     assert ascore is not None and bscore is not None
+    assert ascore == pytest.approx(bscore, abs=1e-5)
 
     results = await store.asearch(("test",), query="uuu")
     assert len(results) == 2

libs/cli/examples/graph_prerelease_reqs/agent.py

@@ -1,7 +1,6 @@
 from collections.abc import Sequence
 from typing import Annotated, Literal, TypedDict
 
-from langchain.chat_models import init_chat_model
 from langchain_community.tools.tavily_search import TavilySearchResults
 from langchain_core.messages import BaseMessage
 from langchain_openai import ChatOpenAI
@@ -10,10 +9,8 @@ from langgraph.prebuilt import ToolNode
 
 tools = [TavilySearchResults(max_results=1)]
 
-model_anth = init_chat_model("claude-3-7-sonnet-20250219", model_provider="anthropic")
 model_oai = ChatOpenAI(temperature=0)
 
-model_anth = model_anth.bind_tools(tools)
 model_oai = model_oai.bind_tools(tools)
 
 
@@ -35,10 +32,7 @@ def should_continue(state):
 
 # Define the function that calls the model
 def call_model(state, config):
-    if config["configurable"].get("model", "anthropic") == "anthropic":
-        model = model_anth
-    else:
-        model = model_oai
+    model = model_oai
     messages = state["messages"]
     response = model.invoke(messages)
     # We return a list, because this will get added to the existing list

libs/cli/examples/graph_prerelease_reqs/deps/additional_deps/pyproject.toml

@@ -0,0 +1,9 @@
+[project]
+name = "graph-prerelease-reqs-additional-deps"
+version = "0.1.0"
+description = "Test for prerelease stuff"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = [
+  "langgraph==0.6.0"
+]

libs/cli/examples/graph_prerelease_reqs/deps/zuper_deps/pyproject.toml

@@ -0,0 +1,9 @@
+[project]
+name = "graph-prerelease-reqs-zuper-deps"
+version = "0.1.0"
+description = "Test for prerelease stuff"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = [
+  "langchain-openai==0.3.0"
+]

libs/cli/examples/graph_prerelease_reqs/langgraph.json

@@ -1,7 +1,9 @@
 {
     "python_version": "3.12",
     "dependencies": [
-      "."
+      ".",
+      "./deps/additional_deps",
+      "./deps/zuper_deps"
     ],
     "graphs": {
       "agent": "./agent.py:graph"

libs/cli/examples/graph_prerelease_reqs/pyproject.toml

@@ -0,0 +1,14 @@
+[project]
+name = "graph-prerelease-reqs"
+version = "0.1.0"
+description = "Test for prerelease stuff"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = [
+  "langchain-openai==1.0.0a2",
+  "langgraph==1.0.0a2",
+  "langchain_community>=0.3.0",
+]
+
+[tool.uv]
+prerelease = "allow"

libs/cli/examples/graph_prerelease_reqs/requirements.txt

@@ -1,6 +0,0 @@
-requests
-langchain_anthropic
-langchain_openai
-langchain_community
-langchain
-langgraph==1.0.0a2

libs/cli/examples/graph_prerelease_reqs_fail/agent.py

@@ -0,0 +1,89 @@
+from collections.abc import Sequence
+from typing import Annotated, Literal, TypedDict
+
+from langchain_community.tools.tavily_search import TavilySearchResults
+from langchain_core.messages import BaseMessage
+from langchain_openai import ChatOpenAI
+from langgraph.graph import END, StateGraph, add_messages
+from langgraph.prebuilt import ToolNode
+
+tools = [TavilySearchResults(max_results=1)]
+
+model_oai = ChatOpenAI(temperature=0)
+
+model_oai = model_oai.bind_tools(tools)
+
+
+class AgentState(TypedDict):
+    messages: Annotated[Sequence[BaseMessage], add_messages]
+
+
+# Define the function that determines whether to continue or not
+def should_continue(state):
+    messages = state["messages"]
+    last_message = messages[-1]
+    # If there are no tool calls, then we finish
+    if not last_message.tool_calls:
+        return "end"
+    # Otherwise if there is, we continue
+    else:
+        return "continue"
+
+
+# Define the function that calls the model
+def call_model(state, config):
+    model = model_oai
+    messages = state["messages"]
+    response = model.invoke(messages)
+    # We return a list, because this will get added to the existing list
+    return {"messages": [response]}
+
+
+# Define the function to execute tools
+tool_node = ToolNode(tools)
+
+
+class ContextSchema(TypedDict):
+    model: Literal["anthropic", "openai"]
+
+
+# Define a new graph
+workflow = StateGraph(AgentState, context_schema=ContextSchema)
+
+# Define the two nodes we will cycle between
+workflow.add_node("agent", call_model)
+workflow.add_node("action", tool_node)
+
+# Set the entrypoint as `agent`
+# This means that this node is the first one called
+workflow.set_entry_point("agent")
+
+# We now add a conditional edge
+workflow.add_conditional_edges(
+    # First, we define the start node. We use `agent`.
+    # This means these are the edges taken after the `agent` node is called.
+    "agent",
+    # Next, we pass in the function that will determine which node is called next.
+    should_continue,
+    # Finally we pass in a mapping.
+    # The keys are strings, and the values are other nodes.
+    # END is a special node marking that the graph should finish.
+    # What will happen is we will call `should_continue`, and then the output of that
+    # will be matched against the keys in this mapping.
+    # Based on which one it matches, that node will then be called.
+    {
+        # If `tools`, then we call the tool node.
+        "continue": "action",
+        # Otherwise we finish.
+        "end": END,
+    },
+)
+
+# We now add a normal edge from `tools` to `agent`.
+# This means that after `tools` is called, `agent` node is called next.
+workflow.add_edge("action", "agent")
+
+# Finally, we compile it!
+# This compiles it into a LangChain Runnable,
+# meaning you can use it as you would any other runnable
+graph = workflow.compile()

libs/cli/examples/graph_prerelease_reqs_fail/langgraph.json

@@ -0,0 +1,11 @@
+{
+    "python_version": "3.12",
+    "dependencies": [
+      "."
+    ],
+    "graphs": {
+      "agent": "./agent.py:graph"
+    },
+    "env": "../.env"
+  }
+  

libs/cli/examples/graph_prerelease_reqs_fail/pyproject.toml

@@ -0,0 +1,11 @@
+[project]
+name = "graph-prerelease-reqs"
+version = "0.1.0"
+description = "Test for prerelease stuff"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = [
+  "langchain-openai==1.0.0a2",
+  "langgraph==1.0.0a2",
+  "langchain_community>=0.3.0",
+]

libs/cli/examples/graphs/langgraph.json

@@ -1,4 +1,5 @@
 {
+  "$schema": "https://langgra.ph/schema.json",
   "python_version": "3.12",
   "dependencies": [
     "langchain_community",

libs/cli/examples/graphs_reqs_a/langgraph.json

@@ -1,4 +1,5 @@
 {
+  "$schema": "https://langgra.ph/schema.json",
   "dependencies": [
     "."
   ],

libs/cli/examples/graphs_reqs_b/langgraph.json

@@ -1,4 +1,5 @@
 {
+  "$schema": "https://langgra.ph/schema.json",
   "dependencies": [
     "."
   ],

libs/cli/js-examples/langgraph.json

@@ -1,4 +1,5 @@
 {
+  "$schema": "https://langgra.ph/schema.json",
   "node_version": "20",
   "graphs": {
     "agent": "./src/agent/graph.ts:graph"

libs/cli/langgraph_cli/config.py

@@ -18,6 +18,7 @@ DEFAULT_IMAGE_DISTRO = "debian"
 
 
 Distros = Literal["debian", "wolfi", "bullseye", "bookworm"]
+MiddlewareOrders = Literal["auth_first", "middleware_first"]
 
 
 class TTLConfig(TypedDict, total=False):
@@ -359,6 +360,25 @@ class HttpConfig(TypedDict, total=False):
     agent's behavior or permissions on a request's headers."""
     logging_headers: Optional[ConfigurableHeaderConfig]
     """Optional. Defines which headers are excluded from logging."""
+    middleware_order: Optional[MiddlewareOrders]
+    """Optional. Defines the order in which to apply server customizations.
+
+    Choices:
+      - "auth_first": Authentication hooks (custom or default) are evaluated
+      before custom middleware.
+      - "middleware_first": Custom middleware is evaluated
+      before authentication hooks (custom or default).
+
+    Default is `middleware_first`.
+    """
+    enable_custom_route_auth: bool
+    """Optional. If True, authentication is enabled for custom routes,
+    not just the routes that are protected by default.
+    (Routes protected by default include /assistants, /threads, and /runs).
+
+    Default is False. This flag only affects authentication behavior
+    if `app` is provided and contains custom routes.
+    """
 
 
 class Config(TypedDict, total=False):
@@ -1256,16 +1276,22 @@ def python_config_to_docker(
         else:
             pip_installer = "pip"
     if pip_installer == "uv":
-        install_cmd = "uv pip install --system --prerelease=allow"
+        install_cmd = "uv pip install --system"
     elif pip_installer == "pip":
         install_cmd = "pip install"
     else:
         raise ValueError(f"Invalid pip_installer: {pip_installer}")
 
     # configure pip
-    pip_install = f"PYTHONDONTWRITEBYTECODE=1 {install_cmd} --no-cache-dir -c /api/constraints.txt"
+    local_reqs_pip_install = f"PYTHONDONTWRITEBYTECODE=1 {install_cmd} --no-cache-dir -c /api/constraints.txt"
+    global_reqs_pip_install = f"PYTHONDONTWRITEBYTECODE=1 {install_cmd} --no-cache-dir -c /api/constraints.txt"
     if config.get("pip_config_file"):
-        pip_install = f"PIP_CONFIG_FILE=/pipconfig.txt {pip_install}"
+        local_reqs_pip_install = (
+            f"PIP_CONFIG_FILE=/pipconfig.txt {local_reqs_pip_install}"
+        )
+        global_reqs_pip_install = (
+            f"PIP_CONFIG_FILE=/pipconfig.txt {global_reqs_pip_install}"
+        )
     pip_config_file_str = (
         f"ADD {config['pip_config_file']} /pipconfig.txt"
         if config.get("pip_config_file")
@@ -1282,7 +1308,9 @@ def python_config_to_docker(
     # Rewrite HTTP app path, so it points to the correct location in the Docker container
     _update_http_app_path(config_path, config, local_deps)
 
-    pip_pkgs_str = f"RUN {pip_install} {' '.join(pypi_deps)}" if pypi_deps else ""
+    pip_pkgs_str = (
+        f"RUN {local_reqs_pip_install} {' '.join(pypi_deps)}" if pypi_deps else ""
+    )
     if local_deps.pip_reqs:
         pip_reqs_str = os.linesep.join(
             (
@@ -1292,7 +1320,7 @@ def python_config_to_docker(
             )
             for reqpath, destpath in local_deps.pip_reqs
         )
-        pip_reqs_str += f"{os.linesep}RUN {pip_install} {' '.join('-r ' + r for _, r in local_deps.pip_reqs)}"
+        pip_reqs_str += f"{os.linesep}RUN {local_reqs_pip_install} {' '.join('-r ' + r for _, r in local_deps.pip_reqs)}"
         pip_reqs_str = f"""# -- Installing local requirements --
 {pip_reqs_str}
 # -- End of local requirements install --"""
@@ -1402,7 +1430,13 @@ ADD {relpath} /deps/{name}
         installs,
         "",
         "# -- Installing all local dependencies --",
-        f"RUN {pip_install} -e /deps/*",
+        f"""RUN for dep in /deps/*; do \
+            echo "Installing $dep"; \
+            if [ -d "$dep" ]; then \
+                echo "Installing $dep"; \
+                (cd "$dep" && {global_reqs_pip_install} .); \
+            fi; \
+        done""",
         "# -- End of local dependencies install --",
         os.linesep.join(env_vars),
         "",

libs/cli/langgraph_cli/docker.py

@@ -40,7 +40,9 @@ def _parse_version(version: str) -> Version:
         patch = "0"
     else:
         major, minor, patch = parts
-    return Version(int(major.lstrip("v")), int(minor), int(patch.split("-")[0]))
+    return Version(
+        int(major.lstrip("v")), int(minor), int(patch.split("-")[0].split("+")[0])
+    )
 
 
 def check_capabilities(runner) -> DockerCapabilities:

libs/cli/python-monorepo-example/apps/agent/langgraph.json

@@ -1,4 +1,5 @@
 {
+  "$schema": "https://langgra.ph/schema.json",
   "dependencies": [".", "../../libs/shared", "../../libs/common"],
   "graphs": {
     "agent": "./src/agent/graph.py:graph"

libs/cli/schemas/schema.json

@@ -577,6 +577,10 @@
           "type": "boolean",
           "description": "Optional. If True, /threads routes are removed.\n\nDefault is False.\n"
         },
+        "enable_custom_route_auth": {
+          "type": "boolean",
+          "description": "Optional. If True, authentication is enabled for custom routes,\nnot just the routes that are protected by default.\n(Routes protected by default include /assistants, /threads, and /runs).\n\nDefault is False. This flag only affects authentication behavior\nif `app` is provided and contains custom routes.\n"
+        },
         "logging_headers": {
           "anyOf": [
             {
@@ -587,6 +591,20 @@
             }
           ],
           "description": "Optional. Defines which headers are excluded from logging."
+        },
+        "middleware_order": {
+          "anyOf": [
+            {
+              "enum": [
+                "auth_first",
+                "middleware_first"
+              ]
+            },
+            {
+              "type": "null"
+            }
+          ],
+          "description": "Optional. Defines the order in which to apply server customizations.\n"
         }
       },
       "required": []

libs/cli/schemas/schema.v0.json

@@ -577,6 +577,10 @@
           "type": "boolean",
           "description": "Optional. If True, /threads routes are removed.\n\nDefault is False.\n"
         },
+        "enable_custom_route_auth": {
+          "type": "boolean",
+          "description": "Optional. If True, authentication is enabled for custom routes,\nnot just the routes that are protected by default.\n(Routes protected by default include /assistants, /threads, and /runs).\n\nDefault is False. This flag only affects authentication behavior\nif `app` is provided and contains custom routes.\n"
+        },
         "logging_headers": {
           "anyOf": [
             {
@@ -587,6 +591,20 @@
             }
           ],
           "description": "Optional. Defines which headers are excluded from logging."
+        },
+        "middleware_order": {
+          "anyOf": [
+            {
+              "enum": [
+                "auth_first",
+                "middleware_first"
+              ]
+            },
+            {
+              "type": "null"
+            }
+          ],
+          "description": "Optional. Defines the order in which to apply server customizations.\n"
         }
       },
       "required": []

libs/cli/tests/unit_tests/cli/test_cli.py

@@ -15,7 +15,7 @@ from langgraph_cli.docker import DEFAULT_POSTGRES_URI, DockerCapabilities, Versi
 from langgraph_cli.util import clean_empty_lines
 
 FORMATTED_CLEANUP_LINES = _get_pip_cleanup_lines(
-    install_cmd="uv pip install --system --prerelease=allow",
+    install_cmd="uv pip install --system",
     to_uninstall=("pip", "setuptools", "wheel"),
     pip_installer="uv",
 )
@@ -149,7 +149,7 @@ services:
                 COPY --from=cli_1 . /deps/cli_1
                 # -- End of local package ../../.. --
                 # -- Installing all local dependencies --
-                RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+                RUN for dep in /deps/*; do             echo "Installing $dep";             if [ -d "$dep" ]; then                 echo "Installing $dep";                 (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .);             fi;         done
                 # -- End of local dependencies install --
                 ENV LANGSERVE_GRAPHS='{{"agent": "agent.py:graph"}}'
 {textwrap.indent(textwrap.dedent(FORMATTED_CLEANUP_LINES), "                ")}

libs/cli/tests/unit_tests/test_config.py

@@ -20,7 +20,7 @@ from langgraph_cli.config import (
 from langgraph_cli.util import clean_empty_lines
 
 FORMATTED_CLEANUP_LINES = _get_pip_cleanup_lines(
-    install_cmd="uv pip install --system --prerelease=allow",
+    install_cmd="uv pip install --system",
     to_uninstall=("pip", "setuptools", "wheel"),
     pip_installer="uv",
 )
@@ -422,7 +422,7 @@ def test_config_to_docker_simple():
 FROM langchain/langgraph-api:3.11
 # -- Installing local requirements --
 COPY --from=outer-requirements.txt requirements.txt /deps/outer-graphs_reqs_a/graphs_reqs_a/requirements.txt
-RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -r /deps/outer-graphs_reqs_a/graphs_reqs_a/requirements.txt
+RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -r /deps/outer-graphs_reqs_a/graphs_reqs_a/requirements.txt
 # -- End of local requirements install --
 # -- Adding local package ../../examples --
 COPY --from=examples . /deps/examples
@@ -456,7 +456,7 @@ RUN set -ex && \\
     done
 # -- End of non-package dependency graphs_reqs_a --
 # -- Installing all local dependencies --
-RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+RUN for dep in /deps/*; do             echo "Installing $dep";             if [ -d "$dep" ]; then                 echo "Installing $dep";                 (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .);             fi;         done
 # -- End of local dependencies install --
 ENV LANGGRAPH_HTTP='{{"app": "/deps/examples/my_app.py:app"}}'
 ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}}'
@@ -512,7 +512,7 @@ RUN set -ex && \\
     done
 # -- End of non-package dependency tests --
 # -- Installing all local dependencies --
-RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+RUN for dep in /deps/*; do             echo "Installing $dep";             if [ -d "$dep" ]; then                 echo "Installing $dep";                 (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .);             fi;         done
 # -- End of local dependencies install --
 ENV LANGSERVE_GRAPHS='{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}'
 """
@@ -559,7 +559,7 @@ RUN set -ex && \\
     done
 # -- End of non-package dependency unit_tests --
 # -- Installing all local dependencies --
-RUN PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+RUN for dep in /deps/*; do             echo "Installing $dep";             if [ -d "$dep" ]; then                 echo "Installing $dep";                 (cd "$dep" && PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .);             fi;         done
 # -- End of local dependencies install --
 ENV LANGSERVE_GRAPHS='{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}'
 """
@@ -621,7 +621,7 @@ RUN set -ex && \\
     done
 # -- End of non-package dependency graphs --
 # -- Installing all local dependencies --
-RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+RUN for dep in /deps/*; do             echo "Installing $dep";             if [ -d "$dep" ]; then                 echo "Installing $dep";                 (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .);             fi;         done
 # -- End of local dependencies install --
 ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-graphs/src/agent.py:graph"}}'
 {FORMATTED_CLEANUP_LINES}\
@@ -657,7 +657,7 @@ dependencies = ["langchain"]"""
 ADD . /deps/unit_tests
 # -- End of local package . --
 # -- Installing all local dependencies --
-RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+RUN for dep in /deps/*; do             echo "Installing $dep";             if [ -d "$dep" ]; then                 echo "Installing $dep";                 (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .);             fi;         done
 # -- End of local dependencies install --
 ENV LANGSERVE_GRAPHS='{"agent": "/deps/unit_tests/graphs/agent.py:graph"}'
 """
@@ -689,7 +689,7 @@ def test_config_to_docker_end_to_end():
 ARG meow
 ARG foo
 ADD pipconfig.txt /pipconfig.txt
-RUN PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt langchain langchain_openai
+RUN PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt langchain langchain_openai
 # -- Adding non-package dependency graphs --
 ADD ./graphs/ /deps/outer-graphs/src
 RUN set -ex && \\
@@ -705,7 +705,7 @@ RUN set -ex && \\
     done
 # -- End of non-package dependency graphs --
 # -- Installing all local dependencies --
-RUN PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+RUN for dep in /deps/*; do             echo "Installing $dep";             if [ -d "$dep" ]; then                 echo "Installing $dep";                 (cd "$dep" && PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .);             fi;         done
 # -- End of local dependencies install --
 ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-graphs/src/agent.py:graph"}}'
 {FORMATTED_CLEANUP_LINES}"""
@@ -811,7 +811,7 @@ RUN set -ex && \\
     done
 # -- End of non-package dependency unit_tests --
 # -- Installing all local dependencies --
-RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+RUN for dep in /deps/*; do             echo "Installing $dep";             if [ -d "$dep" ]; then                 echo "Installing $dep";                 (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .);             fi;         done
 # -- End of local dependencies install --
 ENV LANGGRAPH_UI='{{"agent": "./graphs/agent.ui.jsx"}}'
 ENV LANGGRAPH_UI_CONFIG='{{"shared": ["nuqs"]}}'
@@ -857,7 +857,7 @@ RUN set -ex && \\
     done
 # -- End of non-package dependency unit_tests --
 # -- Installing all local dependencies --
-RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+RUN for dep in /deps/*; do             echo "Installing $dep";             if [ -d "$dep" ]; then                 echo "Installing $dep";                 (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .);             fi;         done
 # -- End of local dependencies install --
 ENV LANGSERVE_GRAPHS='{{"python": "/deps/outer-unit_tests/unit_tests/multiplatform/python.py:graph", "js": "/deps/outer-unit_tests/unit_tests/multiplatform/js.mts:graph"}}'
 # -- Installing JS dependencies --
@@ -887,7 +887,7 @@ def test_config_to_docker_pip_installer():
     docker_auto, _ = config_to_docker(
         PATH_TO_CONFIG, config_auto, "langchain/langgraph-api:0.2.47"
     )
-    assert "uv pip install --system --prerelease=allow" in docker_auto
+    assert "uv pip install --system " in docker_auto
     assert "rm /usr/bin/uv /usr/bin/uvx" in docker_auto
 
     # Test explicit pip setting
@@ -895,7 +895,7 @@ def test_config_to_docker_pip_installer():
     docker_pip, _ = config_to_docker(
         PATH_TO_CONFIG, config_pip, "langchain/langgraph-api:0.2.47"
     )
-    assert "uv pip install --system --prerelease=allow" not in docker_pip
+    assert "uv pip install --system " not in docker_pip
     assert "pip install" in docker_pip
     assert "rm /usr/bin/uv" not in docker_pip
 
@@ -904,7 +904,7 @@ def test_config_to_docker_pip_installer():
     docker_uv, _ = config_to_docker(
         PATH_TO_CONFIG, config_uv, "langchain/langgraph-api:0.2.47"
     )
-    assert "uv pip install --system --prerelease=allow" in docker_uv
+    assert "uv pip install --system " in docker_uv
     assert "rm /usr/bin/uv /usr/bin/uvx" in docker_uv
 
     # Test auto behavior with older image (should use pip)
@@ -914,7 +914,7 @@ def test_config_to_docker_pip_installer():
     docker_auto_old, _ = config_to_docker(
         PATH_TO_CONFIG, config_auto_old, "langchain/langgraph-api:0.2.46"
     )
-    assert "uv pip install --system --prerelease=allow" not in docker_auto_old
+    assert "uv pip install --system " not in docker_auto_old
     assert "pip install" in docker_auto_old
     assert "rm /usr/bin/uv" not in docker_auto_old
 
@@ -923,7 +923,7 @@ def test_config_to_docker_pip_installer():
     docker_default, _ = config_to_docker(
         PATH_TO_CONFIG, config_default, "langchain/langgraph-api:0.2.47"
     )
-    assert "uv pip install --system --prerelease=allow" in docker_default
+    assert "uv pip install --system " in docker_default
 
 
 def test_config_retain_build_tools():
@@ -998,7 +998,7 @@ def test_config_to_compose_simple_config():
                     done
                 # -- End of non-package dependency unit_tests --
                 # -- Installing all local dependencies --
-                RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+                RUN for dep in /deps/*; do             echo "Installing $dep";             if [ -d "$dep" ]; then                 echo "Installing $dep";                 (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .);             fi;         done
                 # -- End of local dependencies install --
                 ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}}'
 {textwrap.indent(textwrap.dedent(FORMATTED_CLEANUP_LINES), "                ")}
@@ -1039,7 +1039,7 @@ def test_config_to_compose_env_vars():
                     done
                 # -- End of non-package dependency unit_tests --
                 # -- Installing all local dependencies --
-                RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+                RUN for dep in /deps/*; do             echo "Installing $dep";             if [ -d "$dep" ]; then                 echo "Installing $dep";                 (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .);             fi;         done
                 # -- End of local dependencies install --
                 ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}}'
 {textwrap.indent(textwrap.dedent(FORMATTED_CLEANUP_LINES), "                ")}
@@ -1084,7 +1084,7 @@ def test_config_to_compose_env_file():
                     done
                 # -- End of non-package dependency unit_tests --
                 # -- Installing all local dependencies --
-                RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+                RUN for dep in /deps/*; do             echo "Installing $dep";             if [ -d "$dep" ]; then                 echo "Installing $dep";                 (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .);             fi;         done
                 # -- End of local dependencies install --
                 ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}}'
 {textwrap.indent(textwrap.dedent(FORMATTED_CLEANUP_LINES), "                ")}
@@ -1122,7 +1122,7 @@ def test_config_to_compose_watch():
                     done
                 # -- End of non-package dependency unit_tests --
                 # -- Installing all local dependencies --
-                RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+                RUN for dep in /deps/*; do             echo "Installing $dep";             if [ -d "$dep" ]; then                 echo "Installing $dep";                 (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .);             fi;         done
                 # -- End of local dependencies install --
                 ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}}'
 {textwrap.indent(textwrap.dedent(FORMATTED_CLEANUP_LINES), "                ")}
@@ -1169,7 +1169,7 @@ def test_config_to_compose_end_to_end():
                     done
                 # -- End of non-package dependency unit_tests --
                 # -- Installing all local dependencies --
-                RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+                RUN for dep in /deps/*; do             echo "Installing $dep";             if [ -d "$dep" ]; then                 echo "Installing $dep";                 (cd "$dep" && PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt .);             fi;         done
                 # -- End of local dependencies install --
                 ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}}'
 {textwrap.indent(textwrap.dedent(FORMATTED_CLEANUP_LINES), "                ")}

libs/cli/tests/unit_tests/test_docker.py

@@ -1,7 +1,10 @@
+import pytest
+
 from langgraph_cli.docker import (
     DEFAULT_POSTGRES_URI,
     DockerCapabilities,
     Version,
+    _parse_version,
     compose,
 )
 from langgraph_cli.util import clean_empty_lines
@@ -363,3 +366,22 @@ services:
             REDIS_URI: redis://langgraph-redis:6379
             POSTGRES_URI: {DEFAULT_POSTGRES_URI}"""
     assert clean_empty_lines(actual_compose_str) == expected_compose_str
+
+
+@pytest.mark.parametrize(
+    "input_str,expected",
+    [
+        ("1.2.3", Version(1, 2, 3)),
+        ("v1.2.3", Version(1, 2, 3)),
+        ("1.2.3-alpha", Version(1, 2, 3)),
+        ("1.2.3+1", Version(1, 2, 3)),
+        ("1.2.3-alpha+build", Version(1, 2, 3)),
+        ("1.2", Version(1, 2, 0)),
+        ("1", Version(1, 0, 0)),
+        ("v28.1.1+1", Version(28, 1, 1)),
+        ("2.0.0-beta.1+exp.sha.5114f85", Version(2, 0, 0)),
+        ("v3.4.5-rc1+build.123", Version(3, 4, 5)),
+    ],
+)
+def test_parse_version_w_edge_cases(input_str, expected):
+    assert _parse_version(input_str) == expected

libs/cli/tests/unit_tests/test_util.py

@@ -0,0 +1,188 @@
+from unittest.mock import patch
+
+from langgraph_cli.util import clean_empty_lines, warn_non_wolfi_distro
+
+
+def test_clean_empty_lines():
+    """Test clean_empty_lines function."""
+    # Test with empty lines
+    input_str = "line1\n\nline2\n\nline3"
+    result = clean_empty_lines(input_str)
+    assert result == "line1\nline2\nline3"
+
+    # Test with no empty lines
+    input_str = "line1\nline2\nline3"
+    result = clean_empty_lines(input_str)
+    assert result == "line1\nline2\nline3"
+
+    # Test with only empty lines
+    input_str = "\n\n\n"
+    result = clean_empty_lines(input_str)
+    assert result == ""
+
+    # Test empty string
+    input_str = ""
+    result = clean_empty_lines(input_str)
+    assert result == ""
+
+
+def test_warn_non_wolfi_distro_with_debian(capsys):
+    """Test that warning is shown when image_distro is 'debian'."""
+    config = {"image_distro": "debian"}
+
+    warn_non_wolfi_distro(config)
+
+    captured = capsys.readouterr()
+    assert (
+        "⚠️  Security Recommendation: Consider switching to Wolfi Linux for enhanced security."
+        in captured.out
+    )
+    assert (
+        "Wolfi is a security-oriented, minimal Linux distribution designed for containers."
+        in captured.out
+    )
+    assert (
+        'To switch, add \'"image_distro": "wolfi"\' to your langgraph.json config file.'
+        in captured.out
+    )
+
+
+def test_warn_non_wolfi_distro_with_default_debian(capsys):
+    """Test that warning is shown when image_distro is missing (defaults to debian)."""
+    config = {}  # No image_distro key, should default to debian
+
+    warn_non_wolfi_distro(config)
+
+    captured = capsys.readouterr()
+    assert (
+        "⚠️  Security Recommendation: Consider switching to Wolfi Linux for enhanced security."
+        in captured.out
+    )
+    assert (
+        "Wolfi is a security-oriented, minimal Linux distribution designed for containers."
+        in captured.out
+    )
+    assert (
+        'To switch, add \'"image_distro": "wolfi"\' to your langgraph.json config file.'
+        in captured.out
+    )
+
+
+def test_warn_non_wolfi_distro_with_wolfi(capsys):
+    """Test that no warning is shown when image_distro is 'wolfi'."""
+    config = {"image_distro": "wolfi"}
+
+    warn_non_wolfi_distro(config)
+
+    captured = capsys.readouterr()
+    assert captured.out == ""  # No output should be generated
+
+
+def test_warn_non_wolfi_distro_with_other_distro(capsys):
+    """Test that warning is shown when image_distro is something other than 'wolfi'."""
+    config = {"image_distro": "ubuntu"}
+
+    warn_non_wolfi_distro(config)
+
+    captured = capsys.readouterr()
+    assert (
+        "⚠️  Security Recommendation: Consider switching to Wolfi Linux for enhanced security."
+        in captured.out
+    )
+    assert (
+        "Wolfi is a security-oriented, minimal Linux distribution designed for containers."
+        in captured.out
+    )
+    assert (
+        'To switch, add \'"image_distro": "wolfi"\' to your langgraph.json config file.'
+        in captured.out
+    )
+
+
+def test_warn_non_wolfi_distro_output_formatting():
+    """Test that the warning output is properly formatted with colors and empty line."""
+    config = {"image_distro": "debian"}
+
+    with patch("click.secho") as mock_secho:
+        warn_non_wolfi_distro(config)
+
+    # Verify click.secho was called with the correct parameters
+    expected_calls = [
+        (
+            (
+                "⚠️  Security Recommendation: Consider switching to Wolfi Linux for enhanced security.",
+            ),
+            {"fg": "yellow", "bold": True},
+        ),
+        (
+            (
+                "   Wolfi is a security-oriented, minimal Linux distribution designed for containers.",
+            ),
+            {"fg": "yellow"},
+        ),
+        (
+            (
+                '   To switch, add \'"image_distro": "wolfi"\' to your langgraph.json config file.',
+            ),
+            {"fg": "yellow"},
+        ),
+        (
+            ("",),  # Empty line
+            {},
+        ),
+    ]
+
+    assert mock_secho.call_count == 4
+    for i, (expected_args, expected_kwargs) in enumerate(expected_calls):
+        actual_call = mock_secho.call_args_list[i]
+        assert actual_call.args == expected_args
+        assert actual_call.kwargs == expected_kwargs
+
+
+def test_warn_non_wolfi_distro_various_configs(capsys):
+    """Test warn_non_wolfi_distro with various config scenarios."""
+    test_cases = [
+        # (config, should_warn, description)
+        ({"image_distro": "debian"}, True, "explicit debian"),
+        ({"image_distro": "wolfi"}, False, "explicit wolfi"),
+        ({}, True, "missing image_distro (defaults to debian)"),
+        ({"image_distro": "alpine"}, True, "other distro"),
+        ({"image_distro": "ubuntu"}, True, "ubuntu distro"),
+        ({"other_config": "value"}, True, "unrelated config keys"),
+    ]
+
+    for config, should_warn, description in test_cases:
+        # Clear any previous output
+        capsys.readouterr()
+
+        warn_non_wolfi_distro(config)
+
+        captured = capsys.readouterr()
+        if should_warn:
+            assert "⚠️  Security Recommendation" in captured.out, (
+                f"Should warn for {description}"
+            )
+            assert "Wolfi" in captured.out, f"Should mention Wolfi for {description}"
+        else:
+            assert captured.out == "", f"Should not warn for {description}"
+
+
+def test_warn_non_wolfi_distro_return_value():
+    """Test that warn_non_wolfi_distro returns None."""
+    config = {"image_distro": "debian"}
+    result = warn_non_wolfi_distro(config)
+    assert result is None
+
+    config = {"image_distro": "wolfi"}
+    result = warn_non_wolfi_distro(config)
+    assert result is None
+
+
+def test_warn_non_wolfi_distro_does_not_modify_config():
+    """Test that warn_non_wolfi_distro does not modify the input config."""
+    original_config = {"image_distro": "debian", "other_key": "value"}
+    config_copy = original_config.copy()
+
+    warn_non_wolfi_distro(config_copy)
+
+    assert config_copy == original_config  # Config should remain unchanged

libs/langgraph/Makefile

@@ -76,7 +76,7 @@ test:
 test_parallel:
 	make start-services &&\
 	make start-dev-server &&\
-	uv run pytest -n auto --dist worksteal $(TEST); \
+	uv run pytest -n auto --dist worksteal $(TEST) --lf --snapshot-update; \
 	EXIT_CODE=$$?; \
 	make stop-services; \
 	make stop-dev-server; \

libs/langgraph/bench/__main__.py

@@ -2,6 +2,7 @@ import random
 from uuid import uuid4
 
 from langchain_core.messages import HumanMessage
+from langgraph.checkpoint.memory import InMemorySaver
 from pyperf._runner import Runner
 from uvloop import new_event_loop
 
@@ -11,7 +12,6 @@ from bench.react_agent import react_agent
 from bench.sequential import create_sequential
 from bench.wide_dict import wide_dict
 from bench.wide_state import wide_state
-from langgraph.checkpoint.memory import InMemorySaver
 from langgraph.graph import StateGraph
 from langgraph.pregel import Pregel
 

libs/langgraph/bench/fanout_to_subgraph.py

@@ -114,7 +114,6 @@ if __name__ == "__main__":
     import time
 
     import uvloop
-
     from langgraph.checkpoint.memory import InMemorySaver
 
     graph = fanout_to_subgraph().compile(checkpointer=InMemorySaver())

libs/langgraph/bench/pydantic_state.py

@@ -303,7 +303,6 @@ if __name__ == "__main__":
     import asyncio
 
     import uvloop
-
     from langgraph.checkpoint.memory import InMemorySaver
 
     graph = pydantic_state(1000).compile(checkpointer=InMemorySaver())

libs/langgraph/bench/react_agent.py

@@ -8,9 +8,9 @@ from langchain_core.language_models.fake_chat_models import (
 from langchain_core.messages import AIMessage, BaseMessage, HumanMessage
 from langchain_core.outputs import ChatGeneration, ChatResult
 from langchain_core.tools import StructuredTool
-
 from langgraph.checkpoint.base import BaseCheckpointSaver
 from langgraph.prebuilt.chat_agent_executor import create_react_agent
+
 from langgraph.pregel import Pregel
 
 
@@ -67,7 +67,6 @@ if __name__ == "__main__":
     import asyncio
 
     import uvloop
-
     from langgraph.checkpoint.memory import InMemorySaver
 
     graph = react_agent(100, checkpointer=InMemorySaver())

libs/langgraph/bench/wide_dict.py

@@ -129,7 +129,6 @@ if __name__ == "__main__":
     import asyncio
 
     import uvloop
-
     from langgraph.checkpoint.memory import InMemorySaver
 
     graph = wide_dict(1000).compile(checkpointer=InMemorySaver())

libs/langgraph/bench/wide_state.py

@@ -139,7 +139,6 @@ if __name__ == "__main__":
     import asyncio
 
     import uvloop
-
     from langgraph.checkpoint.memory import InMemorySaver
 
     graph = wide_state(1000).compile(checkpointer=InMemorySaver())

libs/langgraph/langgraph/_internal/_config.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 from collections import ChainMap
-from collections.abc import Mapping, Sequence
+from collections.abc import Sequence
 from os import getenv
 from typing import Any, cast
 
@@ -17,6 +17,7 @@ from langchain_core.runnables.config import (
     COPIABLE_KEYS,
     var_child_runnable_config,
 )
+from langgraph.checkpoint.base import CheckpointMetadata
 
 from langgraph._internal._constants import (
     CONF,
@@ -26,7 +27,6 @@ from langgraph._internal._constants import (
     NS_END,
     NS_SEP,
 )
-from langgraph.checkpoint.base import CheckpointMetadata
 
 DEFAULT_RECURSION_LIMIT = int(getenv("LANGGRAPH_DEFAULT_RECURSION_LIMIT", "25"))
 
@@ -312,22 +312,11 @@ def ensure_config(*configs: RunnableConfig | None) -> RunnableConfig:
         for k, v in config.items():
             if _is_not_empty(v) and k not in CONFIG_KEYS:
                 empty[CONF][k] = v
-    _empty_metadata = empty["metadata"]
     for key, value in empty[CONF].items():
-        if _exclude_as_metadata(key, value, _empty_metadata):
-            continue
-        _empty_metadata[key] = value
+        if (
+            not key.startswith("__")
+            and isinstance(value, (str, int, float, bool))
+            and key not in empty["metadata"]
+        ):
+            empty["metadata"][key] = value
     return empty
-
-
-_OMIT = ("key", "token", "secret", "password", "auth")
-
-
-def _exclude_as_metadata(key: str, value: Any, metadata: Mapping[str, Any]) -> bool:
-    key_lower = key.casefold()
-    return (
-        key.startswith("__")
-        or not isinstance(value, (str, int, float, bool))
-        or key in metadata
-        or any(substr in key_lower for substr in _OMIT)
-    )

libs/langgraph/langgraph/_internal/_runnable.py

@@ -41,6 +41,7 @@ from langchain_core.runnables.config import (
 )
 from langchain_core.runnables.utils import Input, Output
 from langchain_core.tracers.langchain import LangChainTracer
+from langgraph.store.base import BaseStore
 from typing_extensions import TypeGuard
 
 from langgraph._internal._config import (
@@ -54,7 +55,6 @@ from langgraph._internal._constants import (
     CONFIG_KEY_RUNTIME,
 )
 from langgraph._internal._typing import MISSING
-from langgraph.store.base import BaseStore
 from langgraph.types import StreamWriter
 
 try:
@@ -345,7 +345,7 @@ class RunnableCallable(Runnable):
             args = (input,)
             kwargs = {**self.kwargs, **kwargs}
 
-        runtime = config[CONF].get(CONFIG_KEY_RUNTIME)
+        runtime = config.get(CONF, {}).get(CONFIG_KEY_RUNTIME)
 
         for kw, (runtime_key, default) in self.func_accepts.items():
             # If the kwarg is already set, use the set value
@@ -417,7 +417,7 @@ class RunnableCallable(Runnable):
             args = (input,)
             kwargs = {**self.kwargs, **kwargs}
 
-        runtime = config[CONF].get(CONFIG_KEY_RUNTIME)
+        runtime = config.get(CONF, {}).get(CONFIG_KEY_RUNTIME)
 
         for kw, (runtime_key, default) in self.func_accepts.items():
             # If the kwarg has already been set, use the set value

libs/langgraph/langgraph/config.py

@@ -4,9 +4,9 @@ from typing import Any
 
 from langchain_core.runnables import RunnableConfig
 from langchain_core.runnables.config import var_child_runnable_config
+from langgraph.store.base import BaseStore
 
 from langgraph._internal._constants import CONF, CONFIG_KEY_RUNTIME
-from langgraph.store.base import BaseStore
 from langgraph.types import StreamWriter
 
 
@@ -66,14 +66,17 @@ def get_store() -> BaseStore:
         store = InMemoryStore()
         store.put(("values",), "foo", {"bar": 2})
 
+
         class State(TypedDict):
             foo: int
 
+
         def my_node(state: State):
             my_store = get_store()
             stored_value = my_store.get(("values",), "foo").value["bar"]
             return {"foo": stored_value + 1}
 
+
         graph = (
             StateGraph(State)
             .add_node(my_node)
@@ -85,7 +88,7 @@ def get_store() -> BaseStore:
         ```
 
         ```pycon
-        {'foo': 3}
+        {"foo": 3}
         ```
 
     Example: Using with functional API
@@ -97,16 +100,19 @@ def get_store() -> BaseStore:
         store = InMemoryStore()
         store.put(("values",), "foo", {"bar": 2})
 
+
         @task
         def my_task(value: int):
             my_store = get_store()
             stored_value = my_store.get(("values",), "foo").value["bar"]
             return stored_value + 1
 
+
         @entrypoint(store=store)
         def workflow(value: int):
             return my_task(value).result()
 
+
         workflow.invoke(1)
         ```
 
@@ -134,14 +140,17 @@ def get_stream_writer() -> StreamWriter:
         from langgraph.graph import StateGraph, START
         from langgraph.config import get_stream_writer
 
+
         class State(TypedDict):
             foo: int
 
+
         def my_node(state: State):
             my_stream_writer = get_stream_writer()
             my_stream_writer({"custom_data": "Hello!"})
             return {"foo": state["foo"] + 1}
 
+
         graph = (
             StateGraph(State)
             .add_node(my_node)
@@ -154,7 +163,7 @@ def get_stream_writer() -> StreamWriter:
         ```
 
         ```pycon
-        {'custom_data': 'Hello!'}
+        {"custom_data": "Hello!"}
         ```
 
     Example: Using with functional API
@@ -162,22 +171,25 @@ def get_stream_writer() -> StreamWriter:
         from langgraph.func import entrypoint, task
         from langgraph.config import get_stream_writer
 
+
         @task
         def my_task(value: int):
             my_stream_writer = get_stream_writer()
             my_stream_writer({"custom_data": "Hello!"})
             return value + 1
 
+
         @entrypoint(store=store)
         def workflow(value: int):
             return my_task(value).result()
 
+
         for chunk in workflow.stream(1, stream_mode="custom"):
             print(chunk)
         ```
 
         ```pycon
-        {'custom_data': 'Hello!'}
+        {"custom_data": "Hello!"}
         ```
     """
     runtime = get_config()[CONF][CONFIG_KEY_RUNTIME]

libs/langgraph/langgraph/errors.py

@@ -5,10 +5,10 @@ from enum import Enum
 from typing import Any
 from warnings import warn
 
-from typing_extensions import deprecated
-
 # EmptyChannelError is re-exported from langgraph.channels.base
 from langgraph.checkpoint.base import EmptyChannelError  # noqa: F401
+from typing_extensions import deprecated
+
 from langgraph.types import Command, Interrupt
 from langgraph.warnings import LangGraphDeprecatedSinceV10
 

libs/langgraph/langgraph/func/__init__.py

@@ -1,7 +1,5 @@
 from __future__ import annotations
 
-import asyncio
-import concurrent.futures
 import functools
 import inspect
 import warnings
@@ -18,14 +16,15 @@ from typing import (
     overload,
 )
 
+from langgraph.cache.base import BaseCache
+from langgraph.checkpoint.base import BaseCheckpointSaver
+from langgraph.store.base import BaseStore
 from typing_extensions import Unpack
 
 from langgraph._internal._constants import CACHE_NS_WRITES, PREVIOUS
 from langgraph._internal._typing import MISSING, DeprecatedKwargs
-from langgraph.cache.base import BaseCache
 from langgraph.channels.ephemeral_value import EphemeralValue
 from langgraph.channels.last_value import LastValue
-from langgraph.checkpoint.base import BaseCheckpointSaver
 from langgraph.constants import END, START
 from langgraph.pregel import Pregel
 from langgraph.pregel._call import (
@@ -38,7 +37,6 @@ from langgraph.pregel._call import (
 )
 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.typing import ContextT
 from langgraph.warnings import LangGraphDeprecatedSinceV05, LangGraphDeprecatedSinceV10
@@ -49,7 +47,7 @@ __all__ = ("task", "entrypoint")
 class _TaskFunction(Generic[P, T]):
     def __init__(
         self,
-        func: Callable[P, T],
+        func: Callable[P, Awaitable[T]] | Callable[P, T],
         *,
         retry_policy: Sequence[RetryPolicy],
         cache_policy: CachePolicy[Callable[P, str | bytes]] | None = None,
@@ -60,7 +58,7 @@ class _TaskFunction(Generic[P, T]):
                 # handle class methods
                 # NOTE: we're modifying the instance method to avoid modifying
                 # the original class method in case it's shared across multiple tasks
-                instance_method = functools.partial(func.__func__, func.__self__)  # type: ignore [attr-defined]
+                instance_method = functools.partial(func.__func__, func.__self__)  # type: ignore [union-attr]
                 instance_method.__name__ = name  # type: ignore [attr-defined]
                 func = instance_method
             else:
@@ -95,6 +93,7 @@ class _TaskFunction(Generic[P, T]):
 
 @overload
 def task(
+    __func_or_none__: None = None,
     *,
     name: str | None = None,
     retry_policy: RetryPolicy | Sequence[RetryPolicy] | None = None,
@@ -107,9 +106,11 @@ def task(
 
 
 @overload
-def task(
-    __func_or_none__: Callable[P, Awaitable[T]] | Callable[P, T],
-) -> _TaskFunction[P, T]: ...
+def task(__func_or_none__: Callable[P, Awaitable[T]]) -> _TaskFunction[P, T]: ...
+
+
+@overload
+def task(__func_or_none__: Callable[P, T]) -> _TaskFunction[P, T]: ...
 
 
 def task(
@@ -149,16 +150,19 @@ def task(
         ```python
         from langgraph.func import entrypoint, task
 
+
         @task
         def add_one(a: int) -> int:
             return a + 1
 
+
         @entrypoint()
         def add_one(numbers: list[int]) -> list[int]:
             futures = [add_one(n) for n in numbers]
             results = [f.result() for f in futures]
             return results
 
+
         # Call the entrypoint
         add_one.invoke([1, 2, 3])  # Returns [2, 3, 4]
         ```
@@ -168,15 +172,18 @@ def task(
         import asyncio
         from langgraph.func import entrypoint, task
 
+
         @task
         async def add_one(a: int) -> int:
             return a + 1
 
+
         @entrypoint()
         async def add_one(numbers: list[int]) -> list[int]:
             futures = [add_one(n) for n in numbers]
             return asyncio.gather(*futures)
 
+
         # Call the entrypoint
         await add_one.ainvoke([1, 2, 3])  # Returns [2, 3, 4]
         ```
@@ -200,7 +207,7 @@ def task(
 
     def decorator(
         func: Callable[P, Awaitable[T]] | Callable[P, T],
-    ) -> Callable[P, concurrent.futures.Future[T]] | Callable[P, asyncio.Future[T]]:
+    ) -> Callable[P, SyncAsyncFuture[T]]:
         return _TaskFunction(
             func, retry_policy=retry_policies, cache_policy=cache_policy, name=name
         )
@@ -341,15 +348,13 @@ class entrypoint(Generic[ContextT]):
 
         from langgraph.func import entrypoint
 
+
         @entrypoint(checkpointer=InMemorySaver())
         def my_workflow(input_data: str, previous: Optional[str] = None) -> str:
             return "world"
 
-        config = {
-            "configurable": {
-                "thread_id": "some_thread"
-            }
-        }
+
+        config = {"configurable": {"thread_id": "some_thread"}}
         my_workflow.invoke("hello", config)
         ```
 
@@ -366,19 +371,21 @@ class entrypoint(Generic[ContextT]):
 
         from langgraph.func import entrypoint
 
+
         @entrypoint(checkpointer=InMemorySaver())
-        def my_workflow(number: int, *, previous: Any = None) -> entrypoint.final[int, int]:
+        def my_workflow(
+            number: int,
+            *,
+            previous: Any = None,
+        ) -> entrypoint.final[int, int]:
             previous = previous or 0
             # This will return the previous value to the caller, saving
             # 2 * number to the checkpoint, which will be used in the next invocation
             # for the `previous` parameter.
             return entrypoint.final(value=previous, save=2 * number)
 
-        config = {
-            "configurable": {
-                "thread_id": "some_thread"
-            }
-        }
+
+        config = {"configurable": {"thread_id": "some_thread"}}
 
         my_workflow.invoke(3, config)  # 0 (previous was None)
         my_workflow.invoke(1, config)  # 6 (previous was 3 * 2 from the previous invocation)
@@ -433,19 +440,21 @@ class entrypoint(Generic[ContextT]):
             from langgraph.checkpoint.memory import InMemorySaver
             from langgraph.func import entrypoint
 
+
             @entrypoint(checkpointer=InMemorySaver())
-            def my_workflow(number: int, *, previous: Any = None) -> entrypoint.final[int, int]:
+            def my_workflow(
+                number: int,
+                *,
+                previous: Any = None,
+            ) -> entrypoint.final[int, int]:
                 previous = previous or 0
                 # This will return the previous value to the caller, saving
                 # 2 * number to the checkpoint, which will be used in the next invocation
                 # for the `previous` parameter.
                 return entrypoint.final(value=previous, save=2 * number)
 
-            config = {
-                "configurable": {
-                    "thread_id": "1"
-                }
-            }
+
+            config = {"configurable": {"thread_id": "1"}}
 
             my_workflow.invoke(3, config)  # 0 (previous was None)
             my_workflow.invoke(1, config)  # 6 (previous was 3 * 2 from the previous invocation)

libs/langgraph/langgraph/graph/_node.py

@@ -6,11 +6,11 @@ from dataclasses import dataclass
 from typing import Any, Generic, Protocol, Union
 
 from langchain_core.runnables import Runnable, RunnableConfig
+from langgraph.store.base import BaseStore
 from typing_extensions import TypeAlias
 
 from langgraph._internal._typing import EMPTY_SEQ
 from langgraph.runtime import Runtime
-from langgraph.store.base import BaseStore
 from langgraph.types import CachePolicy, RetryPolicy, StreamWriter
 from langgraph.typing import ContextT, NodeInputT, NodeInputT_contra
 

libs/langgraph/langgraph/graph/message.py

@@ -92,6 +92,7 @@ def add_messages(
     Example:
         ```python title="Basic usage"
         from langchain_core.messages import AIMessage, HumanMessage
+
         msgs1 = [HumanMessage(content="Hello", id="1")]
         msgs2 = [AIMessage(content="Hi there!", id="2")]
         add_messages(msgs1, msgs2)
@@ -110,9 +111,11 @@ def add_messages(
         from typing_extensions import TypedDict
         from langgraph.graph import StateGraph
 
+
         class State(TypedDict):
             messages: Annotated[list, add_messages]
 
+
         builder = StateGraph(State)
         builder.add_node("chatbot", lambda state: {"messages": [("assistant", "Hello")]})
         builder.set_entry_point("chatbot")
@@ -127,30 +130,35 @@ def add_messages(
         from typing_extensions import TypedDict
         from langgraph.graph import StateGraph, add_messages
 
+
         class State(TypedDict):
-            messages: Annotated[list, add_messages(format='langchain-openai')]
+            messages: Annotated[list, add_messages(format="langchain-openai")]
+
 
         def chatbot_node(state: State) -> list:
-            return {"messages": [
-                {
-                    "role": "user",
-                    "content": [
-                        {
-                            "type": "text",
-                            "text": "Here's an image:",
-                            "cache_control": {"type": "ephemeral"},
-                        },
-                        {
-                            "type": "image",
-                            "source": {
-                                "type": "base64",
-                                "media_type": "image/jpeg",
-                                "data": "1234",
+            return {
+                "messages": [
+                    {
+                        "role": "user",
+                        "content": [
+                            {
+                                "type": "text",
+                                "text": "Here's an image:",
+                                "cache_control": {"type": "ephemeral"},
                             },
-                        },
-                    ]
-                },
-            ]}
+                            {
+                                "type": "image",
+                                "source": {
+                                    "type": "base64",
+                                    "media_type": "image/jpeg",
+                                    "data": "1234",
+                                },
+                            },
+                        ],
+                    },
+                ]
+            }
+
 
         builder = StateGraph(State)
         builder.add_node("chatbot", chatbot_node)

libs/langgraph/langgraph/graph/state.py

@@ -24,6 +24,9 @@ from typing import (
 )
 
 from langchain_core.runnables import Runnable, RunnableConfig
+from langgraph.cache.base import BaseCache
+from langgraph.checkpoint.base import Checkpoint
+from langgraph.store.base import BaseStore
 from pydantic import BaseModel, TypeAdapter
 from typing_extensions import NotRequired, Required, Self, Unpack, is_typeddict
 
@@ -41,7 +44,6 @@ from langgraph._internal._fields import (
 from langgraph._internal._pydantic import create_model
 from langgraph._internal._runnable import coerce_to_runnable
 from langgraph._internal._typing import EMPTY_SEQ, MISSING, DeprecatedKwargs
-from langgraph.cache.base import BaseCache
 from langgraph.channels.base import BaseChannel
 from langgraph.channels.binop import BinaryOperatorAggregate
 from langgraph.channels.ephemeral_value import EphemeralValue
@@ -50,7 +52,6 @@ from langgraph.channels.named_barrier_value import (
     NamedBarrierValue,
     NamedBarrierValueAfterFinish,
 )
-from langgraph.checkpoint.base import Checkpoint
 from langgraph.constants import END, START, TAG_HIDDEN
 from langgraph.errors import (
     ErrorCode,
@@ -71,7 +72,6 @@ from langgraph.pregel._write import (
     ChannelWriteEntry,
     ChannelWriteTupleEntry,
 )
-from langgraph.store.base import BaseStore
 from langgraph.types import (
     All,
     CachePolicy,
@@ -141,25 +141,31 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         from langgraph.graph import StateGraph
         from langgraph.runtime import Runtime
 
+
         def reducer(a: list, b: int | None) -> list:
             if b is not None:
                 return a + [b]
             return a
 
+
         class State(TypedDict):
             x: Annotated[list, reducer]
 
+
         class Context(TypedDict):
             r: float
 
+
         graph = StateGraph(state_schema=State, context_schema=Context)
 
+
         def node(state: State, runtime: Runtime[Context]) -> dict:
             r = runtime.context.get("r", 1.0)
             x = state["x"][-1]
             next_value = x * r * (1 - x)
             return {"x": next_value}
 
+
         graph.add_node("A", node)
         graph.set_entry_point("A")
         graph.set_finish_point("A")
@@ -385,12 +391,15 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
             from langchain_core.runnables import RunnableConfig
             from langgraph.graph import START, StateGraph
 
+
             class State(TypedDict):
                 x: int
 
+
             def my_node(state: State, config: RunnableConfig) -> State:
                 return {"x": state["x"] + 1}
 
+
             builder = StateGraph(State)
             builder.add_node(my_node)  # node name will be 'my_node'
             builder.add_edge(START, "my_node")
@@ -1360,10 +1369,14 @@ def _get_channel(
 def _is_field_channel(typ: type[Any]) -> BaseChannel | None:
     if hasattr(typ, "__metadata__"):
         meta = typ.__metadata__
-        if len(meta) >= 1 and isinstance(meta[-1], BaseChannel):
-            return meta[-1]
-        elif len(meta) >= 1 and isclass(meta[-1]) and issubclass(meta[-1], BaseChannel):
-            return meta[-1](typ.__origin__ if hasattr(typ, "__origin__") else typ)
+        # Search through all annotated medata to find channel annotations
+        for item in meta:
+            if isinstance(item, BaseChannel):
+                return item
+            elif isclass(item) and issubclass(item, BaseChannel):
+                # ex, Annotated[int, EphemeralValue, SomeOtherAnnotation]
+                # would return EphemeralValue(int)
+                return item(typ.__origin__ if hasattr(typ, "__origin__") else typ)
     return None
 
 

libs/langgraph/langgraph/graph/ui.py

@@ -82,18 +82,19 @@ def push_ui_message(
         message: Optional message object to associate with the UI message.
         state_key: Key in the graph state where the UI messages are stored.
             Defaults to "ui".
+        merge: Whether to merge props with existing UI message (True) or replace
+            them (False). Defaults to False.
 
     Returns:
         The created UI message.
 
     Example:
-
-    .. code-block:: python
-
+        ```python
         push_ui_message(
             name="component-name",
             props={"content": "Hello world"},
         )
+        ```
 
     """
     from langgraph._internal._constants import CONFIG_KEY_SEND
@@ -144,10 +145,9 @@ def delete_ui_message(id: str, *, state_key: str = "ui") -> RemoveUIMessage:
         The remove UI message.
 
     Example:
-
-    .. code-block:: python
-
+        ```python
         delete_ui_message("message-123")
+        ```
 
     """
     from langgraph._internal._constants import CONFIG_KEY_SEND
@@ -181,13 +181,12 @@ def ui_message_reducer(
         Combined list of UI messages with removals applied.
 
     Example:
-
-    .. code-block:: python
-
+        ```python
         messages = ui_message_reducer(
             [{"type": "ui", "id": "1", "name": "Chat", "props": {}}],
-            {"type": "remove-ui", "id": "1"}
+            {"type": "remove-ui", "id": "1"},
         )
+        ```
 
     """
     if not isinstance(left, list):

libs/langgraph/langgraph/pregel/_algo.py

@@ -23,6 +23,14 @@ from typing import (
 from langchain_core.callbacks import Callbacks
 from langchain_core.callbacks.manager import AsyncParentRunManager, ParentRunManager
 from langchain_core.runnables.config import RunnableConfig
+from langgraph.checkpoint.base import (
+    BaseCheckpointSaver,
+    ChannelVersions,
+    Checkpoint,
+    PendingWrite,
+    V,
+)
+from langgraph.store.base import BaseStore
 from xxhash import xxh3_128_hexdigest
 
 from langgraph._internal._config import merge_configs, patch_config
@@ -57,13 +65,6 @@ from langgraph._internal._scratchpad import PregelScratchpad
 from langgraph._internal._typing import EMPTY_SEQ, MISSING
 from langgraph.channels.base import BaseChannel
 from langgraph.channels.topic import Topic
-from langgraph.checkpoint.base import (
-    BaseCheckpointSaver,
-    ChannelVersions,
-    Checkpoint,
-    PendingWrite,
-    V,
-)
 from langgraph.constants import TAG_HIDDEN
 from langgraph.managed.base import ManagedValueMapping
 from langgraph.pregel._call import get_runnable_for_task, identifier
@@ -71,7 +72,6 @@ from langgraph.pregel._io import read_channels
 from langgraph.pregel._log import logger
 from langgraph.pregel._read import INPUT_CACHE_KEY_TYPE, PregelNode
 from langgraph.runtime import DEFAULT_RUNTIME, Runtime
-from langgraph.store.base import BaseStore
 from langgraph.types import (
     All,
     CacheKey,
@@ -715,13 +715,17 @@ def prepare_single_task(
             runtime = runtime.override(
                 store=store, previous=checkpoint["channel_values"].get(PREVIOUS, None)
             )
+            additional_config: RunnableConfig = {
+                "metadata": metadata,
+                "tags": proc.tags,
+            }
             return PregelExecutableTask(
                 packet.node,
                 packet.arg,
                 proc_node,
                 writes,
                 patch_config(
-                    merge_configs(config, {"metadata": metadata, "tags": proc.tags}),
+                    merge_configs(config, additional_config),
                     run_name=packet.node,
                     callbacks=(
                         manager.get_child(f"graph:step:{step}") if manager else None
@@ -856,15 +860,17 @@ def prepare_single_task(
                         previous=checkpoint["channel_values"].get(PREVIOUS, None),
                         store=store,
                     )
+                    additional_config = {
+                        "metadata": metadata,
+                        "tags": proc.tags,
+                    }
                     return PregelExecutableTask(
                         name,
                         val,
                         node,
                         writes,
                         patch_config(
-                            merge_configs(
-                                config, {"metadata": metadata, "tags": proc.tags}
-                            ),
+                            merge_configs(config, additional_config),
                             run_name=name,
                             callbacks=(
                                 manager.get_child(f"graph:step:{step}")

libs/langgraph/langgraph/pregel/_call.py

@@ -7,7 +7,7 @@ import functools
 import inspect
 import sys
 import types
-from collections.abc import Generator, Sequence
+from collections.abc import Awaitable, Generator, Sequence
 from typing import Any, Callable, Generic, TypeVar, cast
 
 from langchain_core.runnables import Runnable
@@ -251,7 +251,7 @@ class SyncAsyncFuture(Generic[T], concurrent.futures.Future[T]):
 
 
 def call(
-    func: Callable[P, T],
+    func: Callable[P, Awaitable[T]] | Callable[P, T],
     *args: Any,
     retry_policy: Sequence[RetryPolicy] | None = None,
     cache_policy: CachePolicy | None = None,

libs/langgraph/langgraph/pregel/_checkpoint.py

@@ -3,10 +3,11 @@ from __future__ import annotations
 from collections.abc import Mapping
 from datetime import datetime, timezone
 
-from langgraph._internal._typing import MISSING
-from langgraph.channels.base import BaseChannel
 from langgraph.checkpoint.base import Checkpoint
 from langgraph.checkpoint.base.id import uuid6
+
+from langgraph._internal._typing import MISSING
+from langgraph.channels.base import BaseChannel
 from langgraph.managed.base import ManagedValueMapping, ManagedValueSpec
 
 LATEST_VERSION = 4

libs/langgraph/langgraph/pregel/_draw.py

@@ -2,14 +2,15 @@ from __future__ import annotations
 
 from collections import defaultdict
 from collections.abc import Mapping, Sequence
-from typing import Any, cast
+from typing import Any, NamedTuple, cast
 
 from langchain_core.runnables.config import RunnableConfig
 from langchain_core.runnables.graph import Graph, Node
+from langgraph.checkpoint.base import BaseCheckpointSaver
 
 from langgraph._internal._constants import CONF, CONFIG_KEY_SEND, INPUT
 from langgraph.channels.base import BaseChannel
-from langgraph.checkpoint.base import BaseCheckpointSaver
+from langgraph.channels.last_value import LastValueAfterFinish
 from langgraph.constants import END, START
 from langgraph.managed.base import ManagedValueSpec
 from langgraph.pregel._algo import (
@@ -25,6 +26,19 @@ from langgraph.pregel._write import ChannelWrite
 from langgraph.types import All, Checkpointer
 
 
+class Edge(NamedTuple):
+    source: str
+    target: str
+    conditional: bool
+    data: str | None
+
+
+class TriggerEdge(NamedTuple):
+    source: str
+    conditional: bool
+    data: str | None
+
+
 def draw_graph(
     config: RunnableConfig,
     *,
@@ -49,7 +63,7 @@ def draw_graph(
         The graph for this Pregel instance.
     """
     # (src, dest, is_conditional, label)
-    edges: set[tuple[str, str, bool, str | None]] = set()
+    edges: set[Edge] = set()
 
     step = -1
     checkpoint = empty_checkpoint()
@@ -63,8 +77,9 @@ def draw_graph(
         checkpoint,
     )
     static_seen: set[Any] = set()
-    sources: dict[str, set[tuple[str, bool, str | None]]] = {}
-    step_sources: dict[str, set[tuple[str, bool, str | None]]] = {}
+    sources: dict[str, set[TriggerEdge]] = {}
+    step_sources: dict[str, set[TriggerEdge]] = {}
+    static_declared_writes: dict[str, set[TriggerEdge]] = defaultdict(set)
     # remove node mappers
     nodes = {
         k: v.copy(update={"mapper": None}) if v.mapper is not None else v
@@ -123,32 +138,36 @@ def draw_graph(
                         # END writes are not written, but become edges directly
                         for t in writes:
                             if t[0] == END:
-                                edges.add((task.name, t[0], True, t[2]))
+                                edges.add(Edge(task.name, t[0], True, t[2]))
                         writes = [t for t in writes if t[0] != END]
                         conditionals.update(
                             {(task.name, t[0], t[1] or None): t[2] for t in writes}
                         )
+                        # record static writes for edge creation
+                        for t in writes:
+                            static_declared_writes[task.name].add(
+                                TriggerEdge(t[0], True, t[2])
+                            )
                         task.config[CONF][CONFIG_KEY_SEND]([t[:2] for t in writes])
         # collect sources
-        step_sources = {
-            task.name: {
-                (
+        step_sources = {}
+        for task in tasks.values():
+            task_edges = {
+                TriggerEdge(
                     w[0],
                     (task.name, w[0], w[1] or None) in conditionals,
                     conditionals.get((task.name, w[0], w[1] or None)),
                 )
                 for w in task.writes
             }
-            for task in tasks.values()
-        }
+            task_edges |= static_declared_writes.get(task.name, set())
+            step_sources[task.name] = task_edges
         sources.update(step_sources)
         # invert triggers
-        trigger_to_sources: dict[str, set[tuple[str, bool, str | None]]] = defaultdict(
-            set
-        )
+        trigger_to_sources: dict[str, set[TriggerEdge]] = defaultdict(set)
         for src, triggers in sources.items():
             for trigger, cond, label in triggers:
-                trigger_to_sources[trigger].add((src, cond, label))
+                trigger_to_sources[trigger].add(TriggerEdge(src, cond, label))
         # apply writes
         updated_channels = apply_writes(
             checkpoint, channels, tasks.values(), get_next_version, trigger_to_nodes
@@ -170,26 +189,39 @@ def draw_graph(
             trigger_to_nodes=trigger_to_nodes,
             updated_channels=updated_channels,
         )
+        # collect deferred nodes
+        deferred_nodes: set[str] = set()
+        edges_to_deferred_nodes: set[Edge] = set()
+        for channel, item in channels.items():
+            if isinstance(item, LastValueAfterFinish):
+                deferred_node = channel.split(":", 2)[-1]
+                deferred_nodes.add(deferred_node)
         # collect edges
         for task in tasks.values():
             added = False
             for trigger in task.triggers:
                 for src, cond, label in sorted(trigger_to_sources[trigger]):
-                    edges.add((src, task.name, cond, label))
+                    # record edge to be reviewed later
+                    if task.name in deferred_nodes:
+                        edges_to_deferred_nodes.add(Edge(src, task.name, cond, label))
+                    edges.add(Edge(src, task.name, cond, label))
                     # if the edge is from this step, skip adding the implicit edges
                     if (trigger, cond, label) in step_sources.get(src, set()):
                         added = True
                     else:
-                        sources[src].discard((trigger, cond, label))
+                        sources[src].discard(TriggerEdge(trigger, cond, label))
             # if no edges from this step, add implicit edges from all previous tasks
             if not added:
                 for src in step_sources:
-                    edges.add((src, task.name, True, None))
+                    edges.add(Edge(src, task.name, True, None))
+
     # assemble the graph
     graph = Graph()
     # add nodes
     for name, node in nodes.items():
         metadata = dict(node.metadata or {})
+        if name in deferred_nodes:
+            metadata["defer"] = True
         if name in interrupt_before_nodes and name in interrupt_after_nodes:
             metadata["__interrupt"] = "before,after"
         elif name in interrupt_before_nodes:
@@ -215,10 +247,11 @@ def draw_graph(
     termini = {d for _, d, _, _ in edges if d != END}.difference(
         s for s, _, _, _ in edges
     )
+    end_edge_exists = any(d == END for _, d, _, _ in edges)
     if termini:
         for src in sorted(termini):
             add_edge(graph, src, END)
-    elif len(step_sources) == 1:
+    elif len(step_sources) == 1 and not end_edge_exists:
         for src in sorted(step_sources):
             add_edge(graph, src, END, conditional=True)
     # replace subgraphs

libs/langgraph/langgraph/pregel/_loop.py

@@ -25,6 +25,17 @@ from typing import (
 
 from langchain_core.callbacks import AsyncParentRunManager, ParentRunManager
 from langchain_core.runnables import RunnableConfig
+from langgraph.cache.base import BaseCache
+from langgraph.checkpoint.base import (
+    WRITES_IDX_MAP,
+    BaseCheckpointSaver,
+    ChannelVersions,
+    Checkpoint,
+    CheckpointMetadata,
+    CheckpointTuple,
+    PendingWrite,
+)
+from langgraph.store.base import BaseStore
 from typing_extensions import ParamSpec, Self
 
 from langgraph._internal._config import patch_configurable
@@ -50,17 +61,7 @@ from langgraph._internal._constants import (
 )
 from langgraph._internal._scratchpad import PregelScratchpad
 from langgraph._internal._typing import EMPTY_SEQ, MISSING
-from langgraph.cache.base import BaseCache
 from langgraph.channels.base import BaseChannel
-from langgraph.checkpoint.base import (
-    WRITES_IDX_MAP,
-    BaseCheckpointSaver,
-    ChannelVersions,
-    Checkpoint,
-    CheckpointMetadata,
-    CheckpointTuple,
-    PendingWrite,
-)
 from langgraph.constants import TAG_HIDDEN
 from langgraph.errors import (
     EmptyInputError,
@@ -108,12 +109,12 @@ from langgraph.pregel.debug import (
     map_debug_tasks,
 )
 from langgraph.pregel.protocol import StreamChunk, StreamProtocol
-from langgraph.store.base import BaseStore
 from langgraph.types import (
     All,
     CachePolicy,
     Command,
     Durability,
+    Interrupt,
     PregelExecutableTask,
     RetryPolicy,
     StreamMode,
@@ -248,6 +249,7 @@ class PregelLoop:
         self.retry_policy = retry_policy
         self.cache_policy = cache_policy
         self.durability = durability
+        self.skipped_task_ids: set[str] = set()
         if self.stream is not None and CONFIG_KEY_STREAM in config[CONF]:
             self.stream = DuplexStream(self.stream, config[CONF][CONFIG_KEY_STREAM])
         scratchpad: PregelScratchpad | None = config[CONF].get(CONFIG_KEY_SCRATCHPAD)
@@ -316,14 +318,19 @@ class PregelLoop:
             writes_to_save: WritesT = [
                 w[1:] for w in self.checkpoint_pending_writes if w[0] == task_id
             ] + list(writes)
+            self.checkpoint_pending_writes.extend((task_id, c, v) for c, v in writes)
         else:
-            # remove existing writes for this task
+            writes_to_save = [
+                # aggregate existing interrupts for this task
+                (ch, self._merge_interrupts(task_id, v) if ch == INTERRUPT else v)
+                for ch, v in writes
+            ]
+
+            # replace all writes for this task_id in one shot
             self.checkpoint_pending_writes = [
                 w for w in self.checkpoint_pending_writes if w[0] != task_id
-            ]
-            writes_to_save = writes
-        # save writes
-        self.checkpoint_pending_writes.extend((task_id, c, v) for c, v in writes)
+            ] + [(task_id, c, v) for c, v in writes_to_save]
+
         if self.durability != "exit" and self.checkpointer_put_writes is not None:
             config = patch_configurable(
                 self.checkpoint_config,
@@ -471,6 +478,20 @@ class PregelLoop:
             cache_policy=self.cache_policy,
         )
 
+        resume_map = self.config.get(CONF, {}).get(CONFIG_KEY_RESUME_MAP, {})
+        if resume_map:
+            skipped_interrupt_ids = self._pending_interrupts() - set(resume_map)
+            self.skipped_task_ids = {
+                task_id
+                for task_id, channel, value in self.checkpoint_pending_writes
+                if channel == INTERRUPT
+                # interrupts within a task are uncovered sequentially as resumes are provided,
+                # so we only need to check the last interrupt id
+                and value[-1].id in skipped_interrupt_ids
+            }
+        else:
+            self.skipped_task_ids = set()
+
         # produce debug output
         if self._checkpointer_put_after_previous is not None:
             self._emit(
@@ -516,9 +537,45 @@ class PregelLoop:
             if task.writes:
                 self.output_writes(task.id, task.writes, cached=True)
 
+        if self.skipped_task_ids:
+            # remove tasks with writes that may have been matched from previous loop
+            self.skipped_task_ids = {
+                task_id
+                for task_id in self.skipped_task_ids
+                if not self.tasks[task_id].writes
+            }
+            # output interrupt writes for blocked tasks so they are still visible in the stream
+            for task_id, channel, value in self.checkpoint_pending_writes:
+                if task_id in self.skipped_task_ids and channel == INTERRUPT:
+                    # find resume count for this task
+                    resumes = next(
+                        (
+                            v
+                            for tid, ch, v in self.checkpoint_pending_writes
+                            if tid == task_id and ch == RESUME
+                        ),
+                        None,
+                    )
+                    resume_count = len(resumes) if resumes is not None else 0
+                    # only output unresumed interrupts
+                    if resume_count < len(value):
+                        self.output_writes(task_id, [(INTERRUPT, value[resume_count:])])
+
         return True
 
     def after_tick(self) -> None:
+        if self.skipped_task_ids:
+            # raise early GraphInterrupt for skipped tasks.
+            # since we know len(resumes) != len(interrupts) for these tasks, we
+            # can prevent unnecessary node re-execution by raising preemptively
+            interrupts = []
+            for task_id, channel, value in self.checkpoint_pending_writes:
+                if channel == INTERRUPT and task_id in self.skipped_task_ids:
+                    interrupts.extend(value)
+            if interrupts:
+                raise GraphInterrupt(interrupts)
+
+        self.skipped_task_ids.clear()
         # finish superstep
         writes = [w for t in self.tasks.values() for w in t.writes]
         # all tasks have finished
@@ -568,6 +625,55 @@ class PregelLoop:
             if task := tasks.get(tid):
                 task.writes.append((k, v))
 
+    def _pending_interrupts(self) -> set[str]:
+        """Return the set of interrupt ids that are pending without corresponding resume values."""
+        # mapping of task ids to (interrupt_id, interrupt_count)
+        pending_interrupts: dict[str, tuple[str, int]] = {}
+        # mapping of task ids to resume count
+        pending_resumes: dict[str, int] = {}
+
+        for task_id, channel, value in self.checkpoint_pending_writes:
+            if channel == INTERRUPT:
+                pending_interrupts[task_id] = (
+                    value[0].id,
+                    len(value),
+                )
+            elif channel == RESUME:
+                resume_list = value if isinstance(value, list) else [value]
+                pending_resumes[task_id] = len(resume_list)
+
+        # keep only interrupt ids where resume_count < interrupt_count
+        hanging_interrupts: set[str] = {
+            interrupt_id
+            for task_id, (interrupt_id, interrupt_count) in pending_interrupts.items()
+            if pending_resumes.get(task_id, 0) < interrupt_count
+        }
+
+        return hanging_interrupts
+
+    def _merge_interrupts(
+        self, task_id: str, value: Sequence[Interrupt]
+    ) -> Sequence[Interrupt]:
+        """Normalize interrupt value to list and merge with existing interrupts.
+
+        If the interrupt ID matches existing, append; otherwise replace.
+
+        Returns list of Interrupt objects for this task.
+        """
+        new = value if isinstance(value, list) else list(value)
+        existing = next(
+            (
+                v
+                for tid, ch, v in self.checkpoint_pending_writes
+                if tid == task_id and ch == INTERRUPT
+            ),
+            None,
+        )
+        if existing is None:
+            return new
+        old = existing if isinstance(existing, list) else list(existing)
+        return old + new if old and new and old[0].id == new[0].id else new
+
     def _first(
         self, *, input_keys: str | Sequence[str], updated_channels: set[str] | None
     ) -> set[str] | None:
@@ -590,16 +696,24 @@ class PregelLoop:
 
         # map command to writes
         if isinstance(self.input, Command):
-            if resume_is_map := (
-                (resume := self.input.resume) is not None
-                and isinstance(resume, dict)
-                and all(is_xxh3_128_hexdigest(k) for k in resume)
-            ):
-                self.config[CONF][CONFIG_KEY_RESUME_MAP] = self.input.resume
-            if resume is not None and not self.checkpointer:
-                raise RuntimeError(
-                    "Cannot use Command(resume=...) without checkpointer"
-                )
+            if (resume := self.input.resume) is not None:
+                if not self.checkpointer:
+                    raise RuntimeError(
+                        "Cannot use Command(resume=...) without checkpointer"
+                    )
+
+                if resume_is_map := (
+                    isinstance(resume, dict)
+                    and all(is_xxh3_128_hexdigest(k) for k in resume)
+                ):
+                    self.config[CONF][CONFIG_KEY_RESUME_MAP] = resume
+                else:
+                    if len(self._pending_interrupts()) > 1:
+                        raise RuntimeError(
+                            "When there are multiple pending interrupts, you must specify the interrupt id when resuming. "
+                            "Docs: https://docs.langchain.com/oss/python/langgraph/add-human-in-the-loop#resume-multiple-interrupts-with-one-invocation."
+                        )
+
             writes: defaultdict[str, list[tuple[str, Any]]] = defaultdict(list)
             # group writes by task ID
             for tid, c, v in map_command(cmd=self.input):
@@ -866,7 +980,11 @@ class PregelLoop:
                         )
                     }
                 ]
-                self._emit("updates", lambda: iter(interrupts))
+                stream_modes = self.stream.modes if self.stream else []
+                if "updates" in stream_modes:
+                    self._emit("updates", lambda: iter(interrupts))
+                elif "values" in stream_modes:
+                    self._emit("values", lambda: iter(interrupts))
             elif writes[0][0] != ERROR:
                 self._emit(
                     "updates",
@@ -984,6 +1102,7 @@ class SyncPregelLoop(PregelLoop, AbstractContextManager):
 
     def put_writes(self, task_id: str, writes: WritesT) -> None:
         """Put writes for a task, to be read by the next tick."""
+
         super().put_writes(task_id, writes)
         if not writes or self.cache is None or not hasattr(self, "tasks"):
             return

libs/langgraph/langgraph/pregel/_read.py

@@ -231,9 +231,10 @@ class PregelNode:
         config: RunnableConfig | None = None,
         **kwargs: Any | None,
     ) -> Any:
+        self_config: RunnableConfig = {"metadata": self.metadata, "tags": self.tags}
         return self.bound.invoke(
             input,
-            merge_configs({"metadata": self.metadata, "tags": self.tags}, config),
+            merge_configs(self_config, config),
             **kwargs,
         )
 
@@ -243,9 +244,10 @@ class PregelNode:
         config: RunnableConfig | None = None,
         **kwargs: Any | None,
     ) -> Any:
+        self_config: RunnableConfig = {"metadata": self.metadata, "tags": self.tags}
         return await self.bound.ainvoke(
             input,
-            merge_configs({"metadata": self.metadata, "tags": self.tags}, config),
+            merge_configs(self_config, config),
             **kwargs,
         )
 
@@ -255,9 +257,10 @@ class PregelNode:
         config: RunnableConfig | None = None,
         **kwargs: Any | None,
     ) -> Iterator[Any]:
+        self_config: RunnableConfig = {"metadata": self.metadata, "tags": self.tags}
         yield from self.bound.stream(
             input,
-            merge_configs({"metadata": self.metadata, "tags": self.tags}, config),
+            merge_configs(self_config, config),
             **kwargs,
         )
 
@@ -267,9 +270,10 @@ class PregelNode:
         config: RunnableConfig | None = None,
         **kwargs: Any | None,
     ) -> AsyncIterator[Any]:
+        self_config: RunnableConfig = {"metadata": self.metadata, "tags": self.tags}
         async for item in self.bound.astream(
             input,
-            merge_configs({"metadata": self.metadata, "tags": self.tags}, config),
+            merge_configs(self_config, config),
             **kwargs,
         ):
             yield item

libs/langgraph/langgraph/pregel/_utils.py

@@ -7,10 +7,10 @@ import textwrap
 from typing import Any, Callable
 
 from langchain_core.runnables import Runnable, RunnableLambda, RunnableSequence
+from langgraph.checkpoint.base import ChannelVersions
 from typing_extensions import override
 
 from langgraph._internal._runnable import RunnableCallable, RunnableSeq
-from langgraph.checkpoint.base import ChannelVersions
 from langgraph.pregel.protocol import PregelProtocol
 
 

libs/langgraph/langgraph/pregel/debug.py

@@ -6,6 +6,7 @@ from typing import Any
 from uuid import UUID
 
 from langchain_core.runnables import RunnableConfig
+from langgraph.checkpoint.base import CheckpointMetadata, PendingWrite
 from typing_extensions import TypedDict
 
 from langgraph._internal._config import patch_checkpoint_map
@@ -20,7 +21,6 @@ from langgraph._internal._constants import (
 )
 from langgraph._internal._typing import MISSING
 from langgraph.channels.base import BaseChannel
-from langgraph.checkpoint.base import CheckpointMetadata, PendingWrite
 from langgraph.constants import TAG_HIDDEN
 from langgraph.pregel._io import read_channels
 from langgraph.types import PregelExecutableTask, PregelTask, StateSnapshot
@@ -40,7 +40,7 @@ class TaskResultPayload(TypedDict):
     name: str
     error: str | None
     interrupts: list[dict]
-    result: list[tuple[str, Any]]
+    result: dict[str, Any]
 
 
 class CheckpointTask(TypedDict):
@@ -48,7 +48,7 @@ class CheckpointTask(TypedDict):
     name: str
     error: str | None
     interrupts: list[dict]
-    state: RunnableConfig | None
+    state: StateSnapshot | RunnableConfig | None
 
 
 class CheckpointPayload(TypedDict):
@@ -77,6 +77,38 @@ def map_debug_tasks(tasks: Iterable[PregelExecutableTask]) -> Iterator[TaskPaylo
         }
 
 
+def is_multiple_channel_write(value: Any) -> bool:
+    """Return True if the payload already wraps multiple writes from the same channel."""
+    return (
+        isinstance(value, dict)
+        and "$writes" in value
+        and isinstance(value["$writes"], list)
+    )
+
+
+def map_task_result_writes(writes: Sequence[tuple[str, Any]]) -> dict[str, Any]:
+    """Folds task writes into a result dict and aggregates multiple writes to the same channel.
+
+    If the channel contains a single write, we record the write in the result dict as `{channel: write}`
+    If the channel contains multiple writes, we record the writes in the result dict as `{channel: {'$writes': [write1, write2, ...]}}`"""
+
+    result: dict[str, Any] = {}
+    for channel, value in writes:
+        existing = result.get(channel)
+
+        if existing is not None:
+            channel_writes = (
+                existing["$writes"]
+                if is_multiple_channel_write(existing)
+                else [existing]
+            )
+            channel_writes.append(value)
+            result[channel] = {"$writes": channel_writes}
+        else:
+            result[channel] = value
+    return result
+
+
 def map_debug_task_results(
     task_tup: tuple[PregelExecutableTask, Sequence[tuple[str, Any]]],
     stream_keys: str | Sequence[str],
@@ -90,7 +122,9 @@ def map_debug_task_results(
         "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],
+        "result": map_task_result_writes(
+            [w for w in writes if w[0] in stream_channels_list or w[0] == RETURN]
+        ),
         "interrupts": [
             asdict(v)
             for w in writes
@@ -196,54 +230,56 @@ def tasks_w_writes(
             ),
             MISSING,
         )
+        task_error = next(
+            (exc for tid, n, exc in pending_writes if tid == task.id and n == ERROR),
+            None,
+        )
+        task_interrupts = tuple(
+            v
+            for tid, n, vv in pending_writes
+            if tid == task.id and n == INTERRUPT
+            for v in (vv if isinstance(vv, Sequence) else [vv])
+        )
+
+        task_writes = [
+            (chan, val)
+            for tid, chan, val in pending_writes
+            if tid == task.id and chan not in (ERROR, INTERRUPT, RETURN)
+        ]
+
+        if rtn is not MISSING:
+            task_result = rtn
+        elif isinstance(output_keys, str):
+            # unwrap single channel writes to just the write value
+            filtered_writes = [
+                (chan, val) for chan, val in task_writes if chan == output_keys
+            ]
+            mapped_writes = map_task_result_writes(filtered_writes)
+            task_result = mapped_writes.get(str(output_keys)) if mapped_writes else None
+        else:
+            if isinstance(output_keys, str):
+                output_keys = [output_keys]
+            # map task result writes to the desired output channels
+            # repeateed writes to the same channel are aggregated into: {'$writes': [write1, write2, ...]}
+            filtered_writes = [
+                (chan, val) for chan, val in task_writes if chan in output_keys
+            ]
+            mapped_writes = map_task_result_writes(filtered_writes)
+            task_result = mapped_writes if filtered_writes else {}
+
+        has_writes = rtn is not MISSING or any(
+            w[0] == task.id and w[1] not in (ERROR, INTERRUPT) for w in pending_writes
+        )
+
         out.append(
             PregelTask(
                 task.id,
                 task.name,
                 task.path,
-                next(
-                    (
-                        exc
-                        for tid, n, exc in pending_writes
-                        if tid == task.id and n == ERROR
-                    ),
-                    None,
-                ),
-                tuple(
-                    v
-                    for tid, n, vv in pending_writes
-                    if tid == task.id and n == INTERRUPT
-                    for v in (vv if isinstance(vv, Sequence) else [vv])
-                ),
+                task_error,
+                task_interrupts,
                 states.get(task.id) if states else None,
-                (
-                    rtn
-                    if rtn is not MISSING
-                    else next(
-                        (
-                            val
-                            for tid, chan, val in pending_writes
-                            if tid == task.id and chan == output_keys
-                        ),
-                        None,
-                    )
-                    if isinstance(output_keys, str)
-                    else {
-                        chan: val
-                        for tid, chan, val in pending_writes
-                        if tid == task.id
-                        and (
-                            chan == output_keys
-                            if isinstance(output_keys, str)
-                            else chan in output_keys
-                        )
-                    }
-                )
-                if any(
-                    w[0] == task.id and w[1] not in (ERROR, INTERRUPT)
-                    for w in pending_writes
-                )
-                else None,
+                task_result if has_writes else None,
             )
         )
     return tuple(out)

libs/langgraph/langgraph/pregel/main.py

@@ -3,15 +3,24 @@ from __future__ import annotations
 import asyncio
 import concurrent
 import concurrent.futures
+import contextlib
 import queue
 import warnings
 import weakref
 from collections import defaultdict, deque
-from collections.abc import AsyncIterator, Iterator, Mapping, Sequence
+from collections.abc import AsyncIterator, Awaitable, Iterator, Mapping, Sequence
 from dataclasses import is_dataclass
 from functools import partial
 from inspect import isclass
-from typing import Any, Callable, Generic, Optional, Union, cast, get_type_hints
+from typing import (
+    Any,
+    Callable,
+    Generic,
+    Optional,
+    Union,
+    cast,
+    get_type_hints,
+)
 from uuid import UUID, uuid5
 
 from langchain_core.globals import get_debug
@@ -25,6 +34,13 @@ from langchain_core.runnables.config import (
     get_callback_manager_for_config,
 )
 from langchain_core.runnables.graph import Graph
+from langgraph.cache.base import BaseCache
+from langgraph.checkpoint.base import (
+    BaseCheckpointSaver,
+    Checkpoint,
+    CheckpointTuple,
+)
+from langgraph.store.base import BaseStore
 from pydantic import BaseModel, TypeAdapter
 from typing_extensions import Self, Unpack, deprecated, is_typeddict
 
@@ -73,14 +89,8 @@ from langgraph._internal._runnable import (
     coerce_to_runnable,
 )
 from langgraph._internal._typing import MISSING, DeprecatedKwargs
-from langgraph.cache.base import BaseCache
 from langgraph.channels.base import BaseChannel
 from langgraph.channels.topic import Topic
-from langgraph.checkpoint.base import (
-    BaseCheckpointSaver,
-    Checkpoint,
-    CheckpointTuple,
-)
 from langgraph.config import get_config
 from langgraph.constants import END
 from langgraph.errors import (
@@ -117,7 +127,6 @@ from langgraph.pregel._write import ChannelWrite, ChannelWriteEntry
 from langgraph.pregel.debug import get_bolded_text, get_colored_text, tasks_w_writes
 from langgraph.pregel.protocol import PregelProtocol, StreamChunk, StreamProtocol
 from langgraph.runtime import DEFAULT_RUNTIME, Runtime
-from langgraph.store.base import BaseStore
 from langgraph.types import (
     All,
     CachePolicy,
@@ -377,7 +386,7 @@ class Pregel(
 
     However, for **advanced** use cases, Pregel can be used directly. If you're
     not sure whether you need to use Pregel directly, then the answer is probably no
-    – you should use the Graph API or Functional API instead. These are higher-level
+    - you should use the Graph API or Functional API instead. These are higher-level
     interfaces that will compile down to Pregel under the hood.
 
     Here are some examples to give you a sense of how it works:
@@ -479,7 +488,7 @@ class Pregel(
         ```
 
         ```pycon
-        {'c': ['foofoo', 'foofoofoofoo']}
+        {"c": ["foofoo", "foofoofoofoo"]}
         ```
 
     Example: Using a BinaryOperatorAggregate channel
@@ -507,6 +516,7 @@ class Pregel(
             else:
                 return update
 
+
         app = Pregel(
             nodes={"node1": node1, "node2": node2},
             channels={
@@ -515,7 +525,7 @@ class Pregel(
                 "c": BinaryOperatorAggregate(str, operator=reducer),
             },
             input_channels=["a"],
-            output_channels=["c"]
+            output_channels=["c"],
         )
 
         app.invoke({"a": "foo"})
@@ -535,7 +545,8 @@ class Pregel(
         from langgraph.pregel import Pregel, NodeBuilder, ChannelWriteEntry
 
         example_node = (
-            NodeBuilder().subscribe_only("value")
+            NodeBuilder()
+            .subscribe_only("value")
             .do(lambda x: x + x if len(x) < 10 else None)
             .write_to(ChannelWriteEntry(channel="value", skip_none=True))
         )
@@ -546,7 +557,7 @@ class Pregel(
                 "value": EphemeralValue(str),
             },
             input_channels=["value"],
-            output_channels=["value"]
+            output_channels=["value"],
         )
 
         app.invoke({"value": "a"})
@@ -1684,12 +1695,10 @@ class Pregel(
 
                 return patch_checkpoint_map(next_config, saved.metadata)
 
-            # apply pending writes, if not on specific checkpoint
-            if (
-                CONFIG_KEY_CHECKPOINT_ID not in config[CONF]
-                and saved is not None
-                and saved.pending_writes
-            ):
+            # task ids can be provided in the StateUpdate, but if not,
+            # we use the task id generated by prepare_next_tasks
+            node_to_task_ids: dict[str, deque[str]] = defaultdict(deque)
+            if saved is not None and saved.pending_writes is not None:
                 # tasks for this checkpoint
                 next_tasks = prepare_next_tasks(
                     checkpoint,
@@ -1705,6 +1714,10 @@ class Pregel(
                     checkpointer=checkpointer,
                     manager=None,
                 )
+                # collect task ids to reuse so we can properly attach task results
+                for t in next_tasks.values():
+                    node_to_task_ids[t.name].append(t.id)
+
                 # apply null writes
                 if null_writes := [
                     w[1:] for w in saved.pending_writes or [] if w[0] == NULL_TASK_ID
@@ -1786,8 +1799,14 @@ class Pregel(
                     raise InvalidUpdateError(f"Node {as_node} has no writers")
                 writes: deque[tuple[str, Any]] = deque()
                 task = PregelTaskWrites((), as_node, writes, [INTERRUPT])
-                task_id = provided_task_id or str(
-                    uuid5(UUID(checkpoint["id"]), INTERRUPT)
+                # get the task ids that were prepared for this node
+                # if a task id was provided in the StateUpdate, we use it
+                # otherwise, we use the next available task id
+                prepared_task_ids = node_to_task_ids.get(as_node, deque())
+                task_id = provided_task_id or (
+                    prepared_task_ids.popleft()
+                    if prepared_task_ids
+                    else str(uuid5(UUID(checkpoint["id"]), INTERRUPT))
                 )
                 run_tasks.append(task)
                 run_task_ids.append(task_id)
@@ -2140,12 +2159,11 @@ class Pregel(
                 return patch_checkpoint_map(
                     next_config, saved.metadata if saved else None
                 )
-            # apply pending writes, if not on specific checkpoint
-            if (
-                CONFIG_KEY_CHECKPOINT_ID not in config[CONF]
-                and saved is not None
-                and saved.pending_writes
-            ):
+
+            # task ids can be provided in the StateUpdate, but if not,
+            # we use the task id generated by prepare_next_tasks
+            node_to_task_ids: dict[str, deque[str]] = defaultdict(deque)
+            if saved is not None and saved.pending_writes is not None:
                 # tasks for this checkpoint
                 next_tasks = prepare_next_tasks(
                     checkpoint,
@@ -2161,6 +2179,10 @@ class Pregel(
                     checkpointer=checkpointer,
                     manager=None,
                 )
+                # collect task ids to reuse so we can properly attach task results
+                for t in next_tasks.values():
+                    node_to_task_ids[t.name].append(t.id)
+
                 # apply null writes
                 if null_writes := [
                     w[1:] for w in saved.pending_writes or [] if w[0] == NULL_TASK_ID
@@ -2237,8 +2259,14 @@ class Pregel(
                     raise InvalidUpdateError(f"Node {as_node} has no writers")
                 writes: deque[tuple[str, Any]] = deque()
                 task = PregelTaskWrites((), as_node, writes, [INTERRUPT])
-                task_id = provided_task_id or str(
-                    uuid5(UUID(checkpoint["id"]), INTERRUPT)
+                # get the task ids that were prepared for this node
+                # if a task id was provided in the StateUpdate, we use it
+                # otherwise, we use the next available task id
+                prepared_task_ids = node_to_task_ids.get(as_node, deque())
+                task_id = provided_task_id or (
+                    prepared_task_ids.popleft()
+                    if prepared_task_ids
+                    else str(uuid5(UUID(checkpoint["id"]), INTERRUPT))
                 )
                 run_tasks.append(task)
                 run_task_ids.append(task_id)
@@ -2434,7 +2462,7 @@ class Pregel(
             input: The input to the graph.
             config: The configuration to use for the run.
             context: The static context to use for the run.
-                !!! version-added "Added in version 0.6.0."
+                !!! version-added "Added in version 0.6.0"
             stream_mode: The mode to stream output, defaults to `self.stream_mode`.
                 Options are:
 
@@ -2612,6 +2640,7 @@ class Pregel(
                 if subgraphs:
                     loop.config[CONF][CONFIG_KEY_STREAM] = loop.stream
                 # enable concurrent streaming
+                get_waiter: Callable[[], concurrent.futures.Future[None]] | None = None
                 if (
                     self.stream_eager
                     or subgraphs
@@ -2634,8 +2663,6 @@ class Pregel(
                         else:
                             return waiter
 
-                else:
-                    get_waiter = None  # type: ignore[assignment]
                 # Similarly to Bulk Synchronous Parallel / Pregel model
                 # computation proceeds in steps, while there are channel updates.
                 # Channel updates from step N are only visible in step N+1
@@ -2645,7 +2672,11 @@ class Pregel(
                     for task in loop.match_cached_writes():
                         loop.output_writes(task.id, task.writes, cached=True)
                     for _ in runner.tick(
-                        [t for t in loop.tasks.values() if not t.writes],
+                        [
+                            t
+                            for t in loop.tasks.values()
+                            if not t.writes and t.id not in loop.skipped_task_ids
+                        ],
                         timeout=self.step_timeout,
                         get_waiter=get_waiter,
                         schedule_task=loop.accept_push,
@@ -2701,7 +2732,7 @@ class Pregel(
             input: The input to the graph.
             config: The configuration to use for the run.
             context: The static context to use for the run.
-                !!! version-added "Added in version 0.6.0."
+                !!! version-added "Added in version 0.6.0"
             stream_mode: The mode to stream output, defaults to `self.stream_mode`.
                 Options are:
 
@@ -2916,45 +2947,81 @@ class Pregel(
                         stream_put, stream_modes
                     )
                 # enable concurrent streaming
+                get_waiter: Callable[[], asyncio.Task[None]] | None = None
+                _cleanup_waiter: Callable[[], Awaitable[None]] | None = None
                 if (
                     self.stream_eager
                     or subgraphs
                     or "messages" in stream_modes
                     or "custom" in stream_modes
                 ):
+                    # Keep a single waiter task alive; ensure cleanup on exit.
+                    waiter: asyncio.Task[None] | None = None
 
                     def get_waiter() -> asyncio.Task[None]:
-                        return aioloop.create_task(stream.wait())
+                        nonlocal waiter
+                        if waiter is None or waiter.done():
+                            waiter = aioloop.create_task(stream.wait())
+
+                            def _clear(t: asyncio.Task[None]) -> None:
+                                nonlocal waiter
+                                if waiter is t:
+                                    waiter = None
+
+                            waiter.add_done_callback(_clear)
+                        return waiter
+
+                    async def _cleanup_waiter() -> None:
+                        """Wake pending waiter and/or cancel+await to avoid pending tasks."""
+                        nonlocal waiter
+                        # Try to wake via semaphore like SyncPregelLoop
+                        with contextlib.suppress(Exception):
+                            if hasattr(stream, "_count"):
+                                stream._count.release()
+                        t = waiter
+                        waiter = None
+                        if t is not None and not t.done():
+                            t.cancel()
+                            with contextlib.suppress(asyncio.CancelledError):
+                                await t
 
-                else:
-                    get_waiter = None  # type: ignore[assignment]
                 # Similarly to Bulk Synchronous Parallel / Pregel model
                 # computation proceeds in steps, while there are channel updates
                 # channel updates from step N are only visible in step N+1
                 # channels are guaranteed to be immutable for the duration of the step,
                 # with channel updates applied only at the transition between steps
-                while loop.tick():
-                    for task in await loop.amatch_cached_writes():
-                        loop.output_writes(task.id, task.writes, cached=True)
-                    async for _ in runner.atick(
-                        [t for t in loop.tasks.values() if not t.writes],
-                        timeout=self.step_timeout,
-                        get_waiter=get_waiter,
-                        schedule_task=loop.aaccept_push,
-                    ):
-                        # emit output
-                        for o in _output(
-                            stream_mode,
-                            print_mode,
-                            subgraphs,
-                            stream.get_nowait,
-                            asyncio.QueueEmpty,
+                try:
+                    while loop.tick():
+                        for task in await loop.amatch_cached_writes():
+                            loop.output_writes(task.id, task.writes, cached=True)
+                        async for _ in runner.atick(
+                            [
+                                t
+                                for t in loop.tasks.values()
+                                if not t.writes and t.id not in loop.skipped_task_ids
+                            ],
+                            timeout=self.step_timeout,
+                            get_waiter=get_waiter,
+                            schedule_task=loop.aaccept_push,
                         ):
-                            yield o
-                    loop.after_tick()
-                    # wait for checkpoint
-                    if durability_ == "sync":
-                        await cast(asyncio.Future, loop._put_checkpoint_fut)
+                            # emit output
+                            for o in _output(
+                                stream_mode,
+                                print_mode,
+                                subgraphs,
+                                stream.get_nowait,
+                                asyncio.QueueEmpty,
+                            ):
+                                yield o
+                        loop.after_tick()
+                        # wait for checkpoint
+                        if durability_ == "sync":
+                            await cast(asyncio.Future, loop._put_checkpoint_fut)
+                finally:
+                    # ensure waiter doesn't remain pending on cancel/shutdown
+                    if _cleanup_waiter is not None:
+                        await _cleanup_waiter()
+
             # emit output
             for o in _output(
                 stream_mode,
@@ -3001,7 +3068,7 @@ class Pregel(
             input: The input data for the graph. It can be a dictionary or any other type.
             config: Optional. The configuration for the graph run.
             context: The static context to use for the run.
-                !!! version-added "Added in version 0.6.0."
+                !!! version-added "Added in version 0.6.0"
             stream_mode: Optional[str]. The stream mode for the graph run. Default is "values".
             print_mode: Accepts the same values as `stream_mode`, but only prints the output to the console, for debugging purposes. Does not affect the output of the graph in any way.
             output_keys: Optional. The output keys to retrieve from the graph run.
@@ -3086,7 +3153,7 @@ class Pregel(
             input: The input data for the computation. It can be a dictionary or any other type.
             config: Optional. The configuration for the computation.
             context: The static context to use for the run.
-                !!! version-added "Added in version 0.6.0."
+                !!! version-added "Added in version 0.6.0"
             stream_mode: Optional. The stream mode for the computation. Default is "values".
             print_mode: Accepts the same values as `stream_mode`, but only prints the output to the console, for debugging purposes. Does not affect the output of the graph in any way.
             output_keys: Optional. The output keys to include in the result. Default is None.

libs/langgraph/langgraph/pregel/remote.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import logging
 from collections.abc import AsyncIterator, Iterator, Sequence
 from dataclasses import asdict
 from typing import (
@@ -7,6 +8,7 @@ from typing import (
     Literal,
     cast,
 )
+from uuid import UUID
 
 import langsmith as ls
 from langchain_core.runnables import RunnableConfig
@@ -19,6 +21,7 @@ from langchain_core.runnables.graph import (
 from langchain_core.runnables.graph import (
     Node as DrawableNode,
 )
+from langgraph.checkpoint.base import CheckpointMetadata
 from langgraph_sdk.client import (
     LangGraphClient,
     SyncLangGraphClient,
@@ -49,7 +52,6 @@ from langgraph._internal._constants import (
     INTERRUPT,
     NS_SEP,
 )
-from langgraph.checkpoint.base import CheckpointMetadata
 from langgraph.errors import GraphInterrupt, ParentCommand
 from langgraph.pregel.protocol import PregelProtocol, StreamProtocol
 from langgraph.types import (
@@ -61,6 +63,8 @@ from langgraph.types import (
     StreamMode,
 )
 
+logger = logging.getLogger(__name__)
+
 __all__ = ("RemoteGraph", "RemoteException")
 
 _CONF_DROPLIST = frozenset(
@@ -75,7 +79,7 @@ _CONF_DROPLIST = frozenset(
 
 def _sanitize_config_value(v: Any) -> Any:
     """Recursively sanitize a config value to ensure it contains only primitives."""
-    if isinstance(v, (str, int, float, bool)):
+    if isinstance(v, (str, int, float, bool, UUID)):
         return v
     elif isinstance(v, dict):
         sanitized_dict = {}
@@ -950,6 +954,7 @@ class RemoteGraph(PregelProtocol):
         try:
             return chunk
         except UnboundLocalError:
+            logger.warning("No events received from remote graph")
             return None
 
     async def ainvoke(
@@ -990,6 +995,7 @@ class RemoteGraph(PregelProtocol):
         try:
             return chunk
         except UnboundLocalError:
+            logger.warning("No events received from remote graph")
             return None
 
 

libs/langgraph/langgraph/runtime.py

@@ -3,11 +3,11 @@ from __future__ import annotations
 from dataclasses import dataclass, field, replace
 from typing import Any, Generic, cast
 
+from langgraph.store.base import BaseStore
 from typing_extensions import TypedDict, Unpack
 
 from langgraph._internal._constants import CONF, CONFIG_KEY_RUNTIME
 from langgraph.config import get_config
-from langgraph.store.base import BaseStore
 from langgraph.types import _DC_KWARGS, StreamWriter
 from langgraph.typing import ContextT
 

libs/langgraph/langgraph/types.py

@@ -19,6 +19,7 @@ from typing import (
 from warnings import warn
 
 from langchain_core.runnables import Runnable, RunnableConfig
+from langgraph.checkpoint.base import BaseCheckpointSaver, CheckpointMetadata
 from typing_extensions import Unpack, deprecated
 from xxhash import xxh3_128_hexdigest
 
@@ -26,7 +27,6 @@ from langgraph._internal._cache import default_cache_key
 from langgraph._internal._fields import get_cached_annotated_keys, get_update_as_tuples
 from langgraph._internal._retry import default_retry_on
 from langgraph._internal._typing import MISSING, DeprecatedKwargs
-from langgraph.checkpoint.base import BaseCheckpointSaver, CheckpointMetadata
 from langgraph.warnings import LangGraphDeprecatedSinceV10
 
 if TYPE_CHECKING:
@@ -106,7 +106,7 @@ else:
 class RetryPolicy(NamedTuple):
     """Configuration for retrying nodes.
 
-    !!! version-added "Added in version 0.2.24."
+    !!! version-added "Added in version 0.2.24"
     """
 
     initial_interval: float = 0.5
@@ -148,7 +148,7 @@ _DEFAULT_INTERRUPT_ID = "placeholder-id"
 class Interrupt:
     """Information about an interrupt that occurred in a node.
 
-    !!! version-added "Added in version 0.2.24."
+    !!! version-added "Added in version 0.2.24"
 
     !!! version-changed "Changed in version v0.4.0"
         * `interrupt_id` was introduced as a property
@@ -296,12 +296,10 @@ class Send:
         >>> class OverallState(TypedDict):
         ...     subjects: list[str]
         ...     jokes: Annotated[list[str], operator.add]
-        ...
         >>> from langgraph.types import Send
         >>> from langgraph.graph import END, START
         >>> def continue_to_jokes(state: OverallState):
-        ...     return [Send("generate_joke", {"subject": s}) for s in state['subjects']]
-        ...
+        ...     return [Send("generate_joke", {"subject": s}) for s in state["subjects"]]
         >>> from langgraph.graph import StateGraph
         >>> builder = StateGraph(OverallState)
         >>> builder.add_node("generate_joke", lambda state: {"jokes": [f"Joke about {state['subject']}"]})
@@ -351,7 +349,7 @@ N = TypeVar("N", bound=Hashable)
 class Command(Generic[N], ToolOutputMixin):
     """One or more commands to update the graph's state and send messages to nodes.
 
-    !!! version-added "Added in version 0.2.24."
+    !!! version-added "Added in version 0.2.24"
 
     Args:
         graph: graph to send the command to. Supported values are:

libs/langgraph/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph"
-version = "0.6.8"
+version = "0.6.9"
 description = "Building stateful, multi-actor applications with LLMs"
 authors = []
 requires-python = ">=3.9"
@@ -74,14 +74,6 @@ target-version = "py39"
 [tool.ruff.lint.per-file-ignores]
 "tests/bench/*" = ["UP006", "UP007"]
 
-[tool.ruff.format]
-quote-style = "double"
-indent-style = "space"
-skip-magic-trailing-comma = false
-line-ending = "auto"
-docstring-code-format = false
-docstring-code-line-length = "dynamic"
-
 [tool.ruff.lint.flake8-tidy-imports.banned-api]
 "typing.TypedDict".msg = "Use typing_extensions.TypedDict instead."