Update auth user type (#4062)

- This is a performance improvement when calling async functions that do
not use await, as they are run immediately and never scheduled in the
loop

.github/workflows/deploy_docs.yml

@@ -99,7 +99,7 @@ jobs:
         env:
           LANGCHAIN_API_KEY: test
         run: |
-          if [ "${{ github.event_name }}" == "schedule" ] || [ "${{ github.event_name }}" == "workflow_dispatch" ] || ([ "${{ github.event_name }}" == "push" ] && [ "${{ github.ref }}" == "refs/heads/main" ]); then
+          if [ "${{ github.event_name }}" == "schedule" ]; then
             echo "Running link check on all HTML files matching notebooks in docs directory..."
             poetry run pytest -v \
               --check-links-ignore "https://(api|web|docs)\.smith\.langchain\.com/.*" \

docs/_scripts/third_party_page/packages.yml

@@ -36,3 +36,6 @@ packages:
   - name: "langgraph-reflection"
     repo: "langchain-ai/langgraph-reflection"
     description: "LangGraph agent that runs a reflection step."
+  - name: "langgraph-codeact"
+    repo: "langchain-ai/langgraph-codeact"
+    description: "LangGraph implementation of CodeAct agent that generates and executes code instead of tool calling."

docs/docs/adopters.md

@@ -10,14 +10,17 @@ This list of companies using LangGraph and their success stories is compiled fro
 | [Athena Intelligence](https://www.athenaintel.com/) | Software & Technology (GenAI Native) | Research & summarization | [Case study, 2024](https://blog.langchain.dev/customers-athena-intelligence/) |
 | [Captide](https://www.captide.co/) | Software & Technology (GenAI Native) | Data extraction | [Case study, 2025](https://blog.langchain.dev/how-captide-is-redefining-equity-research-with-agentic-workflows-built-on-langgraph-and-langsmith/) |
 | [Cisco Outshift](https://outshift.cisco.com/) | Software & Technology | DevOps | [Blog post, 2025](https://outshift.cisco.com/blog/build-react-agent-application-for-devops-tasks-using-rest-apis) |
+| [C.H. Robinson](https://www.chrobinson.com/en-us/) | Logistics | Automation | [Case study, 2025](https://blog.langchain.dev/customers-chrobinson/) |
 | [Elastic](https://www.elastic.co/) | Software & Technology | Copilot for domain-specific task | [Blog post, 2025](https://www.elastic.co/blog/elastic-security-generative-ai-features) |
 | [GitLab](https://about.gitlab.com/) | Software & Technology | Code generation | [Duo workflow docs](https://handbook.gitlab.com/handbook/engineering/architecture/design-documents/duo_workflow/) |
+| [Inconvo](https://inconvo.ai/?ref=blog.langchain.dev) | Software & Technology | Code generation | [Case study, 2025](https://blog.langchain.dev/customers-inconvo/) |
 | [Infor](https://infor.com/) | Software & Technology | GenAI embedded product experiences; customer support; copilot | [Case study, 2025](https://blog.langchain.dev/customers-infor/) |
 | [Klarna](https://www.klarna.com/) | Fintech | Copilot for domain-specific task | [Case study, 2025](https://blog.langchain.dev/customers-klarna/) |
 | [Komodo Health](https://www.komodohealth.com/) | Healthcare | Copilot for domain-specific task | [Blog post](https://www.komodohealth.com/perspectives/new-gen-ai-assistant-empowers-the-enterprise/) |
 | [LinkedIn](https://www.linkedin.com/) | Social Media | Code generation; Search & discovery | [Blog post, 2025](https://www.linkedin.com/blog/engineering/ai/practical-text-to-sql-for-data-analytics); [Blog post, 2024](https://www.linkedin.com/blog/engineering/generative-ai/behind-the-platform-the-journey-to-create-the-linkedin-genai-application-tech-stack) |
 | [Minimal](https://gominimal.ai/) | E-commerce | Customer support | [Case study, 2025](https://blog.langchain.dev/how-minimal-built-a-multi-agent-customer-support-system-with-langgraph-langsmith/) |
 | [OpenRecovery](https://www.openrecovery.com/) | Healthcare | Copilot for domain-specific task | [Case study, 2024](https://blog.langchain.dev/customers-openrecovery/) |
+| [Qodo](https://www.qodo.ai/) | Software & Technology (GenAI Native) | Code generation | [Blog post, 2025](https://www.qodo.ai/blog/why-we-chose-langgraph-to-build-our-coding-agent/) |
 | [Rakuten](https://www.rakuten.com/) | E-commerce / Fintech | Copilot for domain-specific task | [Blog post, 2025](https://rakuten.today/blog/from-ai-hype-to-real-world-tools-rakuten-teams-up-with-langchain.html) |
 | [Replit](https://replit.com/) | Software & Technology | Code generation | [Blog post, 2024](https://blog.langchain.dev/customers-replit/); [Breakout agent story, 2024](https://www.langchain.com/breakoutagents/replit); [Fireside chat video, 2024](https://www.youtube.com/watch?v=ViykMqljjxU) |
 | [Rexera](https://www.rexera.com/) | Real Estate (GenAI Native) | Copilot for domain-specific task | [Case study, 2024](https://blog.langchain.dev/customers-rexera/) |
@@ -25,3 +28,4 @@ This list of companies using LangGraph and their success stories is compiled fro
 | [Uber](https://www.uber.com/) | Transportation | Developer productivity; Code generation | [Presentation, 2024](https://dpe.org/sessions/ty-smith-adam-huda/this-year-in-ubers-ai-driven-developer-productivity-revolution/); [Video, 2024](https://www.youtube.com/watch?v=8rkA5vWUE4Y) |
 | [Unify](https://www.unifygtm.com/) | Software & Technology (GenAI Native) | Copilot for domain-specific task | [Blog post, 2024](https://blog.langchain.dev/unify-launches-agents-for-account-qualification-using-langgraph-and-langsmith/) |
 | [Vizient](https://www.vizientinc.com/) | Healthcare | Copilot for domain-specific task | [Case study, 2025](https://blog.langchain.dev/p/3d2cd58c-13a5-4df9-bd84-7d54ed0ed82c/) |
+| [Vodafone](https://www.vodafone.com/) | Telecommunications | Code generation; internal search | [Case study, 2025](https://blog.langchain.dev/customers-vodafone/) |

docs/docs/llms-txt-overview.md

@@ -1,13 +1,20 @@
-# LLMs-txt for LangGraph
+# LLMs-txt Overview
 
 ## Overview
 
-LangGraph provides documentation files in the [`llms.txt`](https://llmstxt.org/) format, specifically `llms.txt` and `llms-full.txt`. These files allow large language models (LLMs) and agents to access programming documentation and APIs, particularly useful within integrated development environments (IDEs).
+Below you can find a list of documentation files in the [`llms.txt`](https://llmstxt.org/) format, specifically `llms.txt` and `llms-full.txt`. These files allow large language models (LLMs) and agents to access programming documentation and APIs, particularly useful within integrated development environments (IDEs).
 
 | Language Version | llms.txt                                                                                                   | llms-full.txt                                                                                                        |
 |------------------|------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------|
 | LangGraph Python | [https://langchain-ai.github.io/langgraph/llms.txt](https://langchain-ai.github.io/langgraph/llms.txt)     | [https://langchain-ai.github.io/langgraph/llms-full.txt](https://langchain-ai.github.io/langgraph/llms-full.txt)     |
 | LangGraph JS     | [https://langchain-ai.github.io/langgraphjs/llms.txt](https://langchain-ai.github.io/langgraphjs/llms.txt) | [https://langchain-ai.github.io/langgraphjs/llms-full.txt](https://langchain-ai.github.io/langgraphjs/llms-full.txt) |
+| LangChain Python | [https://python.langchain.com/llms.txt](https://python.langchain.com/llms.txt)                             | N/A                                                                                                                  |
+| LangChain JS     | [https://js.langchain.com/llms.txt](https://js.langchain.com/llms.txt)                                     | N/A                                                                                                                  |
+
+!!! info "Review the output"
+
+    Even with access to up-to-date documentation, current state-of-the-art models may not always generate correct code. Treat the generated code as a starting point, and always review it before shipping
+    code to production.
 
 ## Differences Between `llms.txt` and `llms-full.txt`
 
@@ -19,9 +26,17 @@ A key consideration when using `llms-full.txt` is its size. For extensive docume
 
 ## Using `llms.txt` via an MCP Server
 
-As of March 9, 2025, IDEs [do not yet have robust native support for `llms.txt`](https://x.com/jeremyphoward/status/1902109312216129905?t=1eHFv2vdNdAckajnug0_Vw&s=19). However, you can utilize `llms.txt` effectively through an MCP server.
+As of March 9, 2025, IDEs [do not yet have robust native support for `llms.txt`](https://x.com/jeremyphoward/status/1902109312216129905?t=1eHFv2vdNdAckajnug0_Vw&s=19). However, you can still use `llms.txt` effectively through an MCP server.
 
-We provide an MCP server specifically designed to serve documentation, called [`mcpdoc`](https://github.com/langchain-ai/mcpdoc). This setup is compatible with IDEs and platforms such as Cursor, Windsurf, Claude, and Claude Code. Instructions for using `mcpdoc` with these tools are available in the repository.
+### 🚀 Use the `mcpdoc` Server
+
+We provide an **MCP server** that was designed to serve documentation for LLMs and IDEs:
+
+👉 **[langchain-ai/mcpdoc GitHub Repository](https://github.com/langchain-ai/mcpdoc)**
+
+This MCP server allows integrating `llms.txt` into tools like **Cursor**, **Windsurf**, **Claude**, and **Claude Code**.
+
+📘 **Setup instructions and usage examples** are available in the repository.
 
 ## Using `llms-full.txt`
 

docs/docs/stylesheets/version_admonitions.css

@@ -0,0 +1,38 @@
+:root {
+  --md-admonition-icon--version-added: url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 2H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h4l3 3 3-3h4c1.1 0 2-.9 2-2V4c0-1.1-.9-2-2-2m0 16h-4.2l-.8.8-2 2-2-2-.8-.8H5V4h14z"/><path d="M11 15h2v2h-2v-2m0-10h2v8h-2V5"/></svg>');
+  --md-admonition-icon--version-changed: url('data:image/svg+xml;charset=utf-8,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 2H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h4l3 3 3-3h4c1.1 0 2-.9 2-2V4c0-1.1-.9-2-2-2m0 16h-4.2l-.8.8-2 2-2-2-.8-.8H5V4h14z"/><path d="M15 11h-2V9h-2v2H9v2h2v2h2v-2h2v-2Z"/></svg>');
+}
+
+.md-typeset .admonition.version-added,
+.md-typeset details.version-added {
+  border-color: rgb(0, 191, 165);
+}
+
+.md-typeset .version-added > .admonition-title,
+.md-typeset .version-added > summary {
+  background-color: rgba(0, 191, 165, 0.1);
+}
+
+.md-typeset .version-added > .admonition-title::before,
+.md-typeset .version-added > summary::before {
+  background-color: rgb(0, 191, 165);
+  -webkit-mask-image: var(--md-admonition-icon--version-added);
+          mask-image: var(--md-admonition-icon--version-added);
+}
+
+.md-typeset .admonition.version-changed,
+.md-typeset details.version-changed {
+  border-color: rgb(100, 221, 23);
+}
+
+.md-typeset .version-changed > .admonition-title,
+.md-typeset .version-changed > summary {
+  background-color: rgba(100, 221, 23, 0.1);
+}
+
+.md-typeset .version-changed > .admonition-title::before,
+.md-typeset .version-changed > summary::before {
+  background-color: rgb(100, 221, 23);
+  -webkit-mask-image: var(--md-admonition-icon--version-changed);
+          mask-image: var(--md-admonition-icon--version-changed);
+} 

docs/mkdocs.yml

@@ -503,3 +503,5 @@ validation:
   not_found: info
 copyright: >
   Copyright &copy; 2025 LangChain, Inc | <a href="#__consent">Consent Preferences</a>
+extra_css:
+  - stylesheets/version_admonitions.css

libs/cli/langgraph_cli/config.py

@@ -1022,6 +1022,28 @@ def node_config_to_docker(
         except OSError:
             return False
 
+    # inspired by `package-manager-detector`
+    def get_pkg_manager_name():
+        try:
+            with open(config_path.parent / "package.json") as f:
+                pkg = json.load(f)
+
+                if (pkg_manager_name := pkg.get("packageManager")) and isinstance(
+                    pkg_manager_name, str
+                ):
+                    return pkg_manager_name.lstrip("^").split("@")[0]
+
+                if (
+                    dev_engine_name := (
+                        (pkg.get("devEngines") or {}).get("packageManager") or {}
+                    ).get("name")
+                ) and isinstance(dev_engine_name, str):
+                    return dev_engine_name
+
+                return None
+        except Exception:
+            return None
+
     npm, yarn, pnpm, bun = [
         test_file("package-lock.json"),
         test_file("yarn.lock"),
@@ -1038,7 +1060,16 @@ def node_config_to_docker(
     elif bun:
         install_cmd = "bun i"
     else:
-        install_cmd = "npm i"
+        pkg_manager_name = get_pkg_manager_name()
+
+        if pkg_manager_name == "yarn":
+            install_cmd = "yarn install"
+        elif pkg_manager_name == "pnpm":
+            install_cmd = "pnpm i"
+        elif pkg_manager_name == "bun":
+            install_cmd = "bun i"
+        else:
+            install_cmd = "npm i"
     store_config = config.get("store")
     env_additional_config = (
         ""

libs/cli/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langgraph-cli"
-version = "0.1.79"
+version = "0.1.80"
 description = "CLI for interacting with LangGraph API"
 authors = []
 license = "MIT"

libs/langgraph/bench/__main__.py

@@ -252,27 +252,15 @@ benchmarks = (
         },
     ),
     (
-        "sequential_20",
-        create_sequential(20).compile(),
-        create_sequential(20).compile(),
+        "sequential_10",
+        create_sequential(10).compile(),
+        create_sequential(10).compile(),
         {"messages": []},  # Empty list of messages
     ),
     (
-        "sequential_50",
-        create_sequential(50).compile(),
-        create_sequential(50).compile(),
-        {"messages": []},  # Empty list of messages
-    ),
-    (
-        "sequential_100",
-        create_sequential(100).compile(),
-        create_sequential(100).compile(),
-        {"messages": []},  # Empty list of messages
-    ),
-    (
-        "sequential_200",
-        create_sequential(200).compile(),
-        create_sequential(200).compile(),
+        "sequential_1000",
+        create_sequential(1000).compile(),
+        create_sequential(1000).compile(),
         {"messages": []},  # Empty list of messages
     ),
     (
@@ -383,8 +371,17 @@ for name, agraph, graph, input in benchmarks:
         r.bench_func(name + "_sync", run, graph, input)
 
 
+# Pick a handful of graphs to measure the first event latency.
+# At the moment, limiting just due to the size of the annotation on github.
+GRAPHS_FOR_1st_EVENT_LATENCY = (
+    "sequential_1000",
+    "pydantic_state_25x300",
+)
+
 # First event latency
 for name, agraph, graph, input in benchmarks:
+    if graph not in GRAPHS_FOR_1st_EVENT_LATENCY:
+        continue
     r.bench_async_func(
         name + "_first_event_latency",
         arun_first_event_latency,
@@ -403,30 +400,14 @@ compilation_benchmarks = (
         "sequential_1000",
         create_sequential(1_000),
     ),
-    (
-        "sequential_10000",
-        create_sequential(10_000),
-    ),
     (
         "pydantic_state_25x300",
         pydantic_state(300),
     ),
-    (
-        "pydantic_state_15x600",
-        pydantic_state(600),
-    ),
-    (
-        "pydantic_state_9x1200",
-        pydantic_state(1200),
-    ),
     (
         "wide_state_15x600",
         wide_state(600),
     ),
-    (
-        "wide_state_9x1200",
-        wide_state(1200),
-    ),
 )
 
 for name, graph in compilation_benchmarks:

libs/langgraph/langgraph/channels/topic.py

@@ -62,7 +62,7 @@ class Topic(
                 empty.values = checkpoint
         return empty
 
-    def update(self, values: Sequence[Union[Value, list[Value]]]) -> None:
+    def update(self, values: Sequence[Union[Value, list[Value]]]) -> bool:
         current = list(self.values)
         if not self.accumulate:
             self.values = list[Value]()

libs/langgraph/langgraph/graph/state.py

@@ -242,7 +242,7 @@ class StateGraph(Graph):
         metadata: Optional[dict[str, Any]] = None,
         input: Optional[Type[Any]] = None,
         retry: Optional[RetryPolicy] = None,
-        destinations: Optional[Union[dict[str, str], tuple[str]]] = None,
+        destinations: Optional[Union[dict[str, str], tuple[str, ...]]] = None,
     ) -> Self:
         """Adds a new node to the state graph.
         Will take the name of the function/runnable as the node name.
@@ -267,7 +267,7 @@ class StateGraph(Graph):
         metadata: Optional[dict[str, Any]] = None,
         input: Optional[Type[Any]] = None,
         retry: Optional[RetryPolicy] = None,
-        destinations: Optional[Union[dict[str, str], tuple[str]]] = None,
+        destinations: Optional[Union[dict[str, str], tuple[str, ...]]] = None,
     ) -> Self:
         """Adds a new node to the state graph.
 
@@ -291,7 +291,7 @@ class StateGraph(Graph):
         metadata: Optional[dict[str, Any]] = None,
         input: Optional[Type[Any]] = None,
         retry: Optional[RetryPolicy] = None,
-        destinations: Optional[Union[dict[str, str], tuple[str]]] = None,
+        destinations: Optional[Union[dict[str, str], tuple[str, ...]]] = None,
     ) -> Self:
         """Adds a new node to the state graph.
 
@@ -303,7 +303,7 @@ class StateGraph(Graph):
             metadata (Optional[dict[str, Any]]): The metadata associated with the node. (default: None)
             input (Optional[Type[Any]]): The input schema for the node. (default: the graph's input schema)
             retry (Optional[RetryPolicy]): The policy for retrying the node. (default: None)
-            destinations (Optional[Union[dict[str, str], tuple[str]]]): Destinations that indicate where a node can route to.
+            destinations (Optional[Union[dict[str, str], tuple[str, ...]]]): Destinations that indicate where a node can route to.
                 This is useful for edgeless graphs with nodes that return `Command` objects.
                 If a dict is provided, the keys will be used as the target node names and the values will be used as the labels for the edges.
                 If a tuple is provided, the values will be used as the target node names.

libs/langgraph/langgraph/pregel/executor.py

@@ -156,10 +156,16 @@ class AsyncBackgroundExecutor(AsyncContextManager):
         if self.semaphore:
             coro = gated(self.semaphore, coro)
         if CONTEXT_NOT_SUPPORTED:
-            task = run_coroutine_threadsafe(coro, self.loop, name=__name__)
+            task = run_coroutine_threadsafe(
+                coro, self.loop, name=__name__, lazy=__next_tick__
+            )
         else:
             task = run_coroutine_threadsafe(
-                coro, self.loop, name=__name__, context=copy_context()
+                coro,
+                self.loop,
+                name=__name__,
+                context=copy_context(),
+                lazy=__next_tick__,
             )
         self.tasks[task] = (__cancel_on_exit__, __reraise_on_exit__)
         task.add_done_callback(self.done)

libs/langgraph/langgraph/pregel/remote.py

@@ -654,7 +654,9 @@ class RemoteGraph(PregelProtocol):
             # raise interrupt or errors
             if chunk.event.startswith("updates"):
                 if isinstance(chunk.data, dict) and INTERRUPT in chunk.data:
-                    raise GraphInterrupt(chunk.data[INTERRUPT])
+                    raise GraphInterrupt(
+                        [Interrupt(**i) for i in chunk.data[INTERRUPT]]
+                    )
             elif chunk.event.startswith("error"):
                 raise RemoteException(chunk.data)
             # filter for what was actually requested
@@ -746,7 +748,9 @@ class RemoteGraph(PregelProtocol):
             # raise interrupt or errors
             if chunk.event.startswith("updates"):
                 if isinstance(chunk.data, dict) and INTERRUPT in chunk.data:
-                    raise GraphInterrupt(chunk.data[INTERRUPT])
+                    raise GraphInterrupt(
+                        [Interrupt(**i) for i in chunk.data[INTERRUPT]]
+                    )
             elif chunk.event.startswith("error"):
                 raise RemoteException(chunk.data)
             # filter for what was actually requested

libs/langgraph/langgraph/pregel/runner.py

@@ -44,6 +44,18 @@ from langgraph.utils.future import chain_future
 F = TypeVar("F", concurrent.futures.Future, asyncio.Future)
 E = TypeVar("E", threading.Event, asyncio.Event)
 
+# List of filenames to exclude from exception traceback
+# Note: Frames will be removed if they are the last frame in traceback, recursively
+EXCLUDED_FRAME_FNAMES = (
+    "langgraph/pregel/retry.py",
+    "langgraph/pregel/runner.py",
+    "langgraph/pregel/executor.py",
+    "langgraph/utils/runnable.py",
+    "langchain_core/runnables/config.py",
+    "concurrent/futures/thread.py",
+    "concurrent/futures/_base.py",
+)
+
 
 class FuturesDict(Generic[F, E], dict[F, Optional[PregelExecutableTask]]):
     event: E
@@ -167,6 +179,13 @@ class PregelRunner:
                     fut.set_exception(exc)
                     futures.done.add(fut)
                 elif reraise:
+                    if tb := exc.__traceback__:
+                        while tb.tb_next is not None and any(
+                            tb.tb_frame.f_code.co_filename.endswith(name)
+                            for name in EXCLUDED_FRAME_FNAMES
+                        ):
+                            tb = tb.tb_next
+                        exc.__traceback__ = tb
                     raise
             if not futures:  # maybe `t` schuduled another task
                 return
@@ -229,10 +248,20 @@ class PregelRunner:
         # give control back to the caller
         yield
         # panic on failure or timeout
-        _panic_or_proceed(
-            futures.done.union(f for f, t in futures.items() if t is not None),
-            panic=reraise,
-        )
+        try:
+            _panic_or_proceed(
+                futures.done.union(f for f, t in futures.items() if t is not None),
+                panic=reraise,
+            )
+        except Exception as exc:
+            if tb := exc.__traceback__:
+                while tb.tb_next is not None and any(
+                    tb.tb_frame.f_code.co_filename.endswith(name)
+                    for name in EXCLUDED_FRAME_FNAMES
+                ):
+                    tb = tb.tb_next
+                exc.__traceback__ = tb
+            raise
 
     async def atick(
         self,
@@ -283,6 +312,13 @@ class PregelRunner:
                     fut.set_exception(exc)
                     futures.done.add(fut)
                 elif reraise:
+                    if tb := exc.__traceback__:
+                        while tb.tb_next is not None and any(
+                            tb.tb_frame.f_code.co_filename.endswith(name)
+                            for name in EXCLUDED_FRAME_FNAMES
+                        ):
+                            tb = tb.tb_next
+                        exc.__traceback__ = tb
                     raise
             if not futures:  # maybe `t` schuduled another task
                 return
@@ -357,11 +393,21 @@ class PregelRunner:
         for fut in futures:
             fut.cancel()
         # panic on failure or timeout
-        _panic_or_proceed(
-            futures.done.union(f for f, t in futures.items() if t is not None),
-            timeout_exc_cls=asyncio.TimeoutError,
-            panic=reraise,
-        )
+        try:
+            _panic_or_proceed(
+                futures.done.union(f for f, t in futures.items() if t is not None),
+                timeout_exc_cls=asyncio.TimeoutError,
+                panic=reraise,
+            )
+        except Exception as exc:
+            if tb := exc.__traceback__:
+                while tb.tb_next is not None and any(
+                    tb.tb_frame.f_code.co_filename.endswith(name)
+                    for name in EXCLUDED_FRAME_FNAMES
+                ):
+                    tb = tb.tb_next
+                exc.__traceback__ = tb
+            raise
 
     def commit(
         self,

libs/langgraph/langgraph/types.py

@@ -101,7 +101,10 @@ def default_retry_on(exc: Exception) -> bool:
 
 
 class RetryPolicy(NamedTuple):
-    """Configuration for retrying nodes."""
+    """Configuration for retrying nodes.
+
+    !!! version-added "Added in version 0.2.24."
+    """
 
     initial_interval: float = 0.5
     """Amount of time that must elapse before the first retry occurs. In seconds."""
@@ -120,13 +123,20 @@ class RetryPolicy(NamedTuple):
 
 
 class CachePolicy(NamedTuple):
-    """Configuration for caching nodes."""
+    """Configuration for caching nodes.
+
+    !!! version-added "Added in version 0.2.24."
+    """
 
     pass
 
 
 @dataclasses.dataclass(**_DC_KWARGS)
 class Interrupt:
+    """
+    !!! version-added "Added in version 0.2.24."
+    """
+
     value: Any
     resumable: bool = False
     ns: Optional[Sequence[str]] = None
@@ -268,6 +278,8 @@ 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."
+
     Args:
         graph: graph to send the command to. Supported values are:
 

libs/langgraph/langgraph/utils/future.py

@@ -10,6 +10,7 @@ T = TypeVar("T")
 AnyFuture = Union[asyncio.Future, concurrent.futures.Future]
 
 CONTEXT_NOT_SUPPORTED = sys.version_info < (3, 11)
+EAGER_NOT_SUPPORTED = sys.version_info < (3, 12)
 
 
 def _get_loop(fut: asyncio.Future) -> asyncio.AbstractEventLoop:
@@ -142,6 +143,7 @@ def _ensure_future(
     loop: asyncio.AbstractEventLoop,
     name: Optional[str] = None,
     context: Optional[contextvars.Context] = None,
+    lazy: bool = True,
 ) -> asyncio.Task[T]:
     called_wrap_awaitable = False
     if not asyncio.iscoroutine(coro_or_future):
@@ -159,8 +161,12 @@ def _ensure_future(
     try:
         if CONTEXT_NOT_SUPPORTED:
             return loop.create_task(coro_or_future, name=name)
-        else:
+        elif EAGER_NOT_SUPPORTED or lazy:
             return loop.create_task(coro_or_future, name=name, context=context)
+        else:
+            return asyncio.eager_task_factory(
+                loop, coro_or_future, name=name, context=context
+            )
     except RuntimeError:
         if not called_wrap_awaitable:
             coro_or_future.close()
@@ -180,6 +186,8 @@ def _wrap_awaitable(awaitable: Awaitable[T]) -> Generator[None, None, T]:
 def run_coroutine_threadsafe(
     coro: Coroutine[None, None, T],
     loop: asyncio.AbstractEventLoop,
+    *,
+    lazy: bool,
     name: Optional[str] = None,
     context: Optional[contextvars.Context] = None,
 ) -> asyncio.Future[T]:
@@ -187,18 +195,23 @@ def run_coroutine_threadsafe(
 
     Return a asyncio.Future to access the result.
     """
-    future: asyncio.Future[T] = asyncio.Future(loop=loop)
 
-    def callback() -> None:
-        try:
-            chain_future(
-                _ensure_future(coro, loop=loop, name=name, context=context), future
-            )
-        except (SystemExit, KeyboardInterrupt):
-            raise
-        except BaseException as exc:
-            future.set_exception(exc)
-            raise
+    if asyncio._get_running_loop() is loop:
+        return _ensure_future(coro, loop=loop, name=name, context=context, lazy=lazy)
+    else:
+        future: asyncio.Future[T] = asyncio.Future(loop=loop)
 
-    loop.call_soon_threadsafe(callback, context=context)
-    return future
+        def callback() -> None:
+            try:
+                chain_future(
+                    _ensure_future(coro, loop=loop, name=name, context=context),
+                    future,
+                )
+            except (SystemExit, KeyboardInterrupt):
+                raise
+            except BaseException as exc:
+                future.set_exception(exc)
+                raise
+
+        loop.call_soon_threadsafe(callback, context=context)
+        return future

libs/langgraph/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langgraph"
-version = "0.3.20"
+version = "0.3.21"
 description = "Building stateful, multi-actor applications with LLMs"
 authors = []
 license = "MIT"

libs/langgraph/tests/test_remote_graph.py

@@ -12,6 +12,7 @@ from langgraph_sdk.schema import StreamPart
 from langgraph.errors import GraphInterrupt
 from langgraph.pregel.remote import RemoteGraph
 from langgraph.pregel.types import StateSnapshot
+from langgraph.types import Interrupt
 
 
 def test_with_config():
@@ -415,7 +416,19 @@ def test_stream():
         StreamPart(event="values", data={"chunk": "data2"}),
         StreamPart(event="values", data={"chunk": "data3"}),
         StreamPart(event="updates", data={"chunk": "data4"}),
-        StreamPart(event="updates", data={"__interrupt__": ()}),
+        StreamPart(
+            event="updates",
+            data={
+                "__interrupt__": [
+                    {
+                        "value": {"question": "Does this look good?"},
+                        "resumable": True,
+                        "ns": ["some_ns"],
+                        "when": "during",
+                    }
+                ]
+            },
+        ),
     ]
 
     # call method / assertions
@@ -426,7 +439,7 @@ def test_stream():
 
     # stream modes doesn't include 'updates'
     stream_parts = []
-    with pytest.raises(GraphInterrupt):
+    with pytest.raises(GraphInterrupt) as exc:
         for stream_part in remote_pregel.stream(
             {"input": "data"},
             config={"configurable": {"thread_id": "thread_1"}},
@@ -434,6 +447,15 @@ def test_stream():
         ):
             stream_parts.append(stream_part)
 
+    assert exc.value.args[0] == [
+        Interrupt(
+            value={"question": "Does this look good?"},
+            resumable=True,
+            ns=["some_ns"],
+            when="during",
+        )
+    ]
+
     assert stream_parts == [
         {"chunk": "data1"},
         {"chunk": "data2"},
@@ -517,7 +539,19 @@ async def test_astream():
         StreamPart(event="values", data={"chunk": "data2"}),
         StreamPart(event="values", data={"chunk": "data3"}),
         StreamPart(event="updates", data={"chunk": "data4"}),
-        StreamPart(event="updates", data={"__interrupt__": ()}),
+        StreamPart(
+            event="updates",
+            data={
+                "__interrupt__": [
+                    {
+                        "value": {"question": "Does this look good?"},
+                        "resumable": True,
+                        "ns": ["some_ns"],
+                        "when": "during",
+                    }
+                ]
+            },
+        ),
     ]
     mock_async_client.runs.stream.return_value = async_iter
 
@@ -529,7 +563,7 @@ async def test_astream():
 
     # stream modes doesn't include 'updates'
     stream_parts = []
-    with pytest.raises(GraphInterrupt):
+    with pytest.raises(GraphInterrupt) as exc:
         async for stream_part in remote_pregel.astream(
             {"input": "data"},
             config={"configurable": {"thread_id": "thread_1"}},
@@ -537,6 +571,15 @@ async def test_astream():
         ):
             stream_parts.append(stream_part)
 
+    assert exc.value.args[0] == [
+        Interrupt(
+            value={"question": "Does this look good?"},
+            resumable=True,
+            ns=["some_ns"],
+            when="during",
+        )
+    ]
+
     assert stream_parts == [
         {"chunk": "data1"},
         {"chunk": "data2"},

libs/prebuilt/langgraph/prebuilt/tool_node.py

@@ -292,7 +292,7 @@ class ToolNode(RunnableCallable):
                             goto=cast(list[Send], parent_command.goto) + output.goto,
                         )
                     else:
-                        parent_command = output
+                        parent_command = Command(graph=Command.PARENT, goto=output.goto)
                 else:
                     combined_outputs.append(output)
             else:

libs/prebuilt/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langgraph-prebuilt"
-version = "0.1.6"
+version = "0.1.7"
 description = "Library with high-level APIs for creating and executing LangGraph agents and tools."
 authors = []
 license = "MIT"

libs/sdk-js/src/schema.ts

@@ -57,25 +57,25 @@ export interface GraphSchema {
    * The schema for the input state.
    * Missing if unable to generate JSON schema from graph.
    */
-  input_schema?: JSONSchema7;
+  input_schema?: JSONSchema7 | null | undefined;
 
   /**
    * The schema for the output state.
    * Missing if unable to generate JSON schema from graph.
    */
-  output_schema?: JSONSchema7;
+  output_schema?: JSONSchema7 | null | undefined;
 
   /**
    * The schema for the graph state.
    * Missing if unable to generate JSON schema from graph.
    */
-  state_schema?: JSONSchema7;
+  state_schema?: JSONSchema7 | null | undefined;
 
   /**
    * The schema for the graph config.
    * Missing if unable to generate JSON schema from graph.
    */
-  config_schema?: JSONSchema7;
+  config_schema?: JSONSchema7 | null | undefined;
 }
 
 export type Subgraphs = Record<string, GraphSchema>;

libs/sdk-py/langgraph_sdk/auth/types.py

@@ -192,6 +192,18 @@ class BaseUser(typing.Protocol):
         """The permissions associated with the user."""
         ...
 
+    def __getitem__(self, key):
+        """Get a key from your minimal user dict."""
+        ...
+
+    def __contains__(self, key):
+        """Check if a property exists."""
+        ...
+
+    def __iter__(self):
+        """Iterate over the keys of the user."""
+        ...
+
 
 class StudioUser:
     """A user object that's populated from authenticated requests from the LangGraph studio.

libs/sdk-py/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langgraph-sdk"
-version = "0.1.59"
+version = "0.1.60"
 description = "SDK for interacting with LangGraph API"
 authors = []
 license = "MIT"