Studio cli command

Add compilation benchmark alone

README.md

@@ -1,7 +1,7 @@
 <picture class="github-only">
-  <source media="(prefers-color-scheme: light)" srcset="docs/docs/static/wordmark_dark.svg">
-  <source media="(prefers-color-scheme: dark)" srcset="docs/docs/static/wordmark_light.svg">
-  <img alt="LangGraph Logo" src="docs/docs/static/wordmark_dark.svg" width="80%">
+  <source media="(prefers-color-scheme: light)" srcset="https://langchain-ai.github.io/langgraph/static/wordmark_dark.svg">
+  <source media="(prefers-color-scheme: dark)" srcset="https://langchain-ai.github.io/langgraph/static/wordmark_light.svg">
+  <img alt="LangGraph Logo" src="https://langchain-ai.github.io/langgraph/static/wordmark_dark.svg" width="80%">
 </picture>
 
 <div>

docs/docs/concepts/langgraph_platform.md

@@ -1,3 +1,8 @@
+---
+search:
+  boost: 2
+---
+
 # LangGraph Platform
 
 ## Overview

docs/docs/concepts/v0-human-in-the-loop.md

@@ -1,3 +1,8 @@
+---
+search:
+  exclude: true
+---
+
 # Human-in-the-loop
 
 !!! note "Use the `interrupt` function instead."

docs/docs/index.md

@@ -20,7 +20,7 @@ title: Home
 </p>
 
 <style>
-h1 {
+.md-content h1 {
   display: none;
 }
 </style>

docs/docs/llms-txt-overview.md

@@ -0,0 +1,36 @@
+# LLMs-txt for LangGraph
+
+## 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).
+
+| 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) |
+
+## Differences Between `llms.txt` and `llms-full.txt`
+
+- **`llms.txt`** is an index file containing links with brief descriptions of the content. An LLM or agent must follow these links to access detailed information.
+
+- **`llms-full.txt`** includes all the detailed content directly in a single file, eliminating the need for additional navigation.
+
+A key consideration when using `llms-full.txt` is its size. For extensive documentation, this file may become too large to fit into an LLM's context window.
+
+## 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.
+
+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.
+
+## Using `llms-full.txt`
+
+The LangGraph `llms-full.txt` file typically contains several hundred thousand tokens, exceeding the context window limitations of most LLMs. To effectively use this file:
+
+1. **With IDEs (e.g., Cursor, Windsurf)**:
+    - Add the `llms-full.txt` as custom documentation. The IDE will automatically chunk and index the content, implementing Retrieval-Augmented Generation (RAG).
+
+2. **Without IDE support**:
+    - Use a chat model with a large context window.
+    - Implement a RAG strategy to manage and query the documentation efficiently.
+

docs/docs/tutorials/deployment.md

@@ -1,3 +1,8 @@
+---
+search:
+  boost: 2
+---
+
 # Deployment
 
 Get started deploying your LangGraph applications locally or on the cloud with

docs/mkdocs.yml

@@ -54,7 +54,7 @@ theme:
     code: "Roboto Mono"
 plugins:
   - search:
-      separator: '[\s\u200b\-_,:!=\[\]()"`/]+|\.(?!\d)|&[lg]t;|(?!\b)(?=[A-Z][a-z])'
+      separator: '[\s\u200b\-,:!=\[\]()"`/]+|\.(?!\d)|&[lg]t;'
   - autorefs
   - mkdocstrings:
       handlers:
@@ -361,6 +361,7 @@ nav:
       # NOTE: prebuilt.md is auto-generated by `make build-prebuilt`
       - Prebuilt Agents: prebuilt.md
       - Companies using LangGraph: adopters.md
+      - LLMS-txt: llms-txt-overview.md
       - FAQ: concepts/faq.md
       - Troubleshooting:
           - Troubleshooting: troubleshooting/errors/index.md

libs/checkpoint-postgres/poetry.lock

@@ -397,7 +397,7 @@ typing-extensions = ">=4.7"
 
 [[package]]
 name = "langgraph-checkpoint"
-version = "2.0.18"
+version = "2.0.21"
 description = "Library with base interfaces for LangGraph checkpoint savers."
 optional = false
 python-versions = "^3.9.0,<4.0"
@@ -1404,4 +1404,4 @@ cffi = ["cffi (>=1.11)"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.9.0,<4.0"
-content-hash = "369bfffecb9489835b43b8255932e043176a11d2f639aad2d055ffd89263ca1e"
+content-hash = "4b0efdd115566f294fcd876334f9c3787aafc81f2689473759d88189a71d4635"

libs/cli/langgraph_cli/cli.py

@@ -574,6 +574,12 @@ def dockerfile(save_path: str, config: pathlib.Path, add_docker_compose: bool) -
     help="Wait for a debugger client to connect to the debug port before starting the server",
     default=False,
 )
+@click.option(
+    "--studio-url",
+    type=str,
+    default=None,
+    help="URL of the LangGraph Studio instance to connect to. Defaults to https://smith.langchain.com",
+)
 @cli.command(
     "dev",
     help="🏃‍♀️‍➡️ Run LangGraph API server in development mode with hot reloading and debugging support",
@@ -588,6 +594,7 @@ def dev(
     no_browser: bool,
     debug_port: Optional[int],
     wait_for_client: bool,
+    studio_url: Optional[str],
 ):
     """CLI entrypoint for running the LangGraph API server."""
     try:
@@ -651,6 +658,7 @@ def dev(
         wait_for_client=wait_for_client,
         auth=config_json.get("auth"),
         http=config_json.get("http"),
+        studio_url=studio_url,
     )
 
 

libs/cli/poetry.lock

@@ -535,42 +535,42 @@ langgraph-sdk = ">=0.1.42,<0.2.0"
 
 [[package]]
 name = "langgraph-api"
-version = "0.0.27"
+version = "0.0.32"
 description = ""
 optional = true
 python-versions = "<4.0,>=3.11.0"
 files = [
-    {file = "langgraph_api-0.0.27-py3-none-any.whl", hash = "sha256:9b21742238b15b8db9c2d3fd760a670332c8897d0bcbbd9d82e43b6ac15a7937"},
-    {file = "langgraph_api-0.0.27.tar.gz", hash = "sha256:c21eb2b7fe3b93998379f7b13ad7d23b3ef06ab821b008c6b12b954acfb587ec"},
+    {file = "langgraph_api-0.0.32-py3-none-any.whl", hash = "sha256:7990cedc65f784813aba867c5bde3fdfae3fa4588baef1aa346cbeac7c3aebf1"},
+    {file = "langgraph_api-0.0.32.tar.gz", hash = "sha256:6f5b698ad8d136b73c2c53bcfa30670e9244a318b08b5e9cf00a707ea57c058c"},
 ]
 
 [package.dependencies]
 cryptography = ">=43.0.3,<44.0.0"
 httpx = ">=0.25.0"
-jsonschema-rs = ">=0.20.0,<0.21.0"
+jsonschema-rs = ">=0.20.0,<0.30"
 langchain-core = ">=0.2.38,<0.4.0"
 langgraph = ">=0.2.56,<0.4.0"
-langgraph-checkpoint = ">=2.0.15,<3.0"
-langgraph-sdk = ">=0.1.53,<0.2.0"
+langgraph-checkpoint = ">=2.0.21,<3.0"
+langgraph-sdk = ">=0.1.58,<0.2.0"
 langsmith = ">=0.1.63,<0.4.0"
 orjson = ">=3.9.7"
 pyjwt = ">=2.9.0,<3.0.0"
 sse-starlette = ">=2.1.0,<2.2.0"
 starlette = ">=0.38.6"
-structlog = ">=23.1.0,<24.0.0"
+structlog = ">=24.1.0,<26"
 tenacity = ">=8.0.0"
 uvicorn = ">=0.26.0"
 watchfiles = ">=0.13"
 
 [[package]]
 name = "langgraph-checkpoint"
-version = "2.0.16"
+version = "2.0.21"
 description = "Library with base interfaces for LangGraph checkpoint savers."
 optional = true
 python-versions = "<4.0.0,>=3.9.0"
 files = [
-    {file = "langgraph_checkpoint-2.0.16-py3-none-any.whl", hash = "sha256:dfab51076a6eddb5f9e146cfe1b977e3dd6419168b2afa23ff3f4e47973bf06f"},
-    {file = "langgraph_checkpoint-2.0.16.tar.gz", hash = "sha256:49ba8cfa12b2aae845ccc3b1fbd1d7a8d3a6c4a2e387ab3a92fca40dd3d4baa5"},
+    {file = "langgraph_checkpoint-2.0.21-py3-none-any.whl", hash = "sha256:ca89c2090cd9729f83f9782226935dc5ff9fe7756c24936f484ccb0ce367f87b"},
+    {file = "langgraph_checkpoint-2.0.21.tar.gz", hash = "sha256:52beeb6dc1bd8c487b8315466cab271093b65eb97f54a0942dfe105cd20b237f"},
 ]
 
 [package.dependencies]
@@ -594,13 +594,13 @@ langgraph-checkpoint = ">=2.0.10,<3.0.0"
 
 [[package]]
 name = "langgraph-sdk"
-version = "0.1.53"
+version = "0.1.58"
 description = "SDK for interacting with LangGraph API"
 optional = true
 python-versions = "<4.0.0,>=3.9.0"
 files = [
-    {file = "langgraph_sdk-0.1.53-py3-none-any.whl", hash = "sha256:4fab62caad73661ffe4c3ababedcd0d7bfaaba986bee4416b9c28948458a3af5"},
-    {file = "langgraph_sdk-0.1.53.tar.gz", hash = "sha256:12906ed965905fa27e0c28d9fa07dc6fd89e6895ff321ff049fdf3965d057cc4"},
+    {file = "langgraph_sdk-0.1.58-py3-none-any.whl", hash = "sha256:65f88cf5582da0c316714dc475126fa03c5f74d72bc0b9221dd42649de8e23d4"},
+    {file = "langgraph_sdk-0.1.58.tar.gz", hash = "sha256:ef8b0e4c08af8c7efd3919497879c87a3627806b51e4ba5e8b06e0717e3d44cd"},
 ]
 
 [package.dependencies]
@@ -1357,18 +1357,18 @@ full = ["httpx (>=0.27.0,<0.29.0)", "itsdangerous", "jinja2", "python-multipart
 
 [[package]]
 name = "structlog"
-version = "23.3.0"
+version = "25.2.0"
 description = "Structured Logging for Python"
 optional = true
 python-versions = ">=3.8"
 files = [
-    {file = "structlog-23.3.0-py3-none-any.whl", hash = "sha256:d6922a88ceabef5b13b9eda9c4043624924f60edbb00397f4d193bd754cde60a"},
-    {file = "structlog-23.3.0.tar.gz", hash = "sha256:24b42b914ac6bc4a4e6f716e82ac70d7fb1e8c3b1035a765591953bfc37101a5"},
+    {file = "structlog-25.2.0-py3-none-any.whl", hash = "sha256:0fecea2e345d5d491b72f3db2e5fcd6393abfc8cd06a4851f21fcd4d1a99f437"},
+    {file = "structlog-25.2.0.tar.gz", hash = "sha256:d9f9776944207d1035b8b26072b9b140c63702fd7aa57c2f85d28ab701bd8e92"},
 ]
 
 [package.extras]
-dev = ["structlog[tests,typing]"]
-docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-mermaid", "sphinxext-opengraph", "twisted"]
+dev = ["freezegun (>=0.2.8)", "mypy (>=1.4)", "pretend", "pytest (>=6.0)", "pytest-asyncio (>=0.17)", "rich", "simplejson", "twisted"]
+docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-mermaid", "sphinxext-opengraph", "twisted"]
 tests = ["freezegun (>=0.2.8)", "pretend", "pytest (>=6.0)", "pytest-asyncio (>=0.17)", "simplejson"]
 typing = ["mypy (>=1.4)", "rich", "twisted"]
 
@@ -1717,4 +1717,4 @@ inmem = ["langgraph-api", "python-dotenv"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.9.0,<4.0"
-content-hash = "d0e2bdcb600ad031867413025fcc58bb162609209359d63ca99a77060cf8cbb4"
+content-hash = "f5aa4d66f9c0b98b8321a70a82387dc6e5f3a3a7ecedd87ac00d6415199038f9"

libs/cli/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langgraph-cli"
-version = "0.1.77"
+version = "0.1.78"
 description = "CLI for interacting with LangGraph API"
 authors = []
 license = "MIT"
@@ -14,7 +14,7 @@ langgraph = "langgraph_cli.cli:cli"
 [tool.poetry.dependencies]
 python = "^3.9.0,<4.0"
 click = "^8.1.7"
-langgraph-api = { version = ">=0.0.27,<0.1.0", optional = true, python = ">=3.11,<4.0" }
+langgraph-api = { version = ">=0.0.32,<0.1.0", optional = true, python = ">=3.11,<4.0" }
 python-dotenv = { version = ">=0.8.0", optional = true }
 
 [tool.poetry.group.dev.dependencies]

libs/langgraph/README.md

@@ -1,7 +1,7 @@
 <picture class="github-only">
-  <source media="(prefers-color-scheme: light)" srcset="docs/docs/static/wordmark_dark.svg">
-  <source media="(prefers-color-scheme: dark)" srcset="docs/docs/static/wordmark_light.svg">
-  <img alt="LangGraph Logo" src="docs/docs/static/wordmark_dark.svg" width="80%">
+  <source media="(prefers-color-scheme: light)" srcset="https://langchain-ai.github.io/langgraph/static/wordmark_dark.svg">
+  <source media="(prefers-color-scheme: dark)" srcset="https://langchain-ai.github.io/langgraph/static/wordmark_light.svg">
+  <img alt="LangGraph Logo" src="https://langchain-ai.github.io/langgraph/static/wordmark_dark.svg" width="80%">
 </picture>
 
 <div>

libs/langgraph/bench/__main__.py

@@ -11,6 +11,7 @@ from bench.react_agent import react_agent
 from bench.sequential import create_sequential
 from bench.wide_state import wide_state
 from langgraph.checkpoint.memory import MemorySaver
+from langgraph.graph import StateGraph
 from langgraph.pregel import Pregel
 
 
@@ -44,6 +45,11 @@ def run(graph: Pregel, input: dict):
     )
 
 
+def compile_graph(graph: StateGraph) -> None:
+    """Compile the graph."""
+    graph.compile()
+
+
 benchmarks = (
     (
         "fanout_to_subgraph_10x",
@@ -330,7 +336,43 @@ benchmarks = (
 
 r = Runner()
 
+# Full graph run time
 for name, agraph, graph, input in benchmarks:
     r.bench_async_func(name, arun, agraph, input, loop_factory=new_event_loop)
     if graph is not None:
         r.bench_func(name + "_sync", run, graph, input)
+
+# Graph compilation times
+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:
+    r.bench_func(name + "_compilation", compile_graph, graph)

libs/langgraph/langgraph/graph/branch.py

@@ -138,6 +138,7 @@ class Branch(NamedTuple):
                 reader=reader,
                 name=None,
                 trace=False,
+                func_accepts_config=True,
             )
         )
 

libs/langgraph/langgraph/graph/state.py

@@ -859,8 +859,10 @@ class CompiledStateGraph(CompiledGraph):
                 # subscribe to channel
                 self.nodes[end].triggers.append(channel_name)
                 # publish to channel
-                self.nodes[START] |= ChannelWrite(
-                    [ChannelWriteEntry(channel_name, START)], tags=[TAG_HIDDEN]
+                self.nodes[START].writers.append(
+                    ChannelWrite(
+                        [ChannelWriteEntry(channel_name, START)], tags=[TAG_HIDDEN]
+                    )
                 )
             elif end != END:
                 # subscribe to start channel
@@ -873,8 +875,10 @@ class CompiledStateGraph(CompiledGraph):
             self.nodes[end].triggers.append(channel_name)
             # publish to channel
             for start in starts:
-                self.nodes[start] |= ChannelWrite(
-                    [ChannelWriteEntry(channel_name, start)], tags=[TAG_HIDDEN]
+                self.nodes[start].writers.append(
+                    ChannelWrite(
+                        [ChannelWriteEntry(channel_name, start)], tags=[TAG_HIDDEN]
+                    )
                 )
 
     def attach_branch(
@@ -910,28 +914,31 @@ class CompiledStateGraph(CompiledGraph):
             if start in self.builder.nodes
             else self.builder.schema
         )
-        # attach branch publisher
-        self.nodes[start] |= branch.run(
-            branch_writer,
-            _get_state_reader(self.builder, schema) if with_reader else None,
-        )
 
-        # attach branch subscribers
-        ends = (
-            branch.ends.values()
-            if branch.ends
-            else [node for node in self.builder.nodes if node != branch.then]
+        # attach branch publisher
+        self.nodes[start].writers.append(
+            branch.run(
+                branch_writer,
+                _get_state_reader(self.builder, schema) if with_reader else None,
+            )
         )
 
         # attach then subscriber
         if branch.then and branch.then != END:
+            ends = (
+                branch.ends.values()
+                if branch.ends
+                else [node for node in self.builder.nodes if node != branch.then]
+            )
             channel_name = f"branch:{start}:{name}::then"
             self.channels[channel_name] = DynamicBarrierValue(str)
             self.nodes[branch.then].triggers.append(channel_name)
             for end in ends:
                 if end != END:
-                    self.nodes[end] |= ChannelWrite(
-                        [ChannelWriteEntry(channel_name, end)], tags=[TAG_HIDDEN]
+                    self.nodes[end].writers.append(
+                        ChannelWrite(
+                            [ChannelWriteEntry(channel_name, end)], tags=[TAG_HIDDEN]
+                        )
                     )
 
 
@@ -1013,7 +1020,12 @@ async def _acontrol_branch(value: Any) -> Sequence[Union[str, Send]]:
 
 
 CONTROL_BRANCH_PATH = RunnableCallable(
-    _control_branch, _acontrol_branch, tags=[TAG_HIDDEN], trace=False, recurse=False
+    _control_branch,
+    _acontrol_branch,
+    tags=[TAG_HIDDEN],
+    trace=False,
+    recurse=False,
+    func_accepts_config=False,
 )
 CONTROL_BRANCH = Branch(CONTROL_BRANCH_PATH, None)
 

libs/langgraph/langgraph/pregel/__init__.py

@@ -504,6 +504,8 @@ class Pregel(PregelProtocol):
 
     name: str = "LangGraph"
 
+    trigger_to_nodes: Optional[Mapping[str, Sequence[str]]] = None
+
     def __init__(
         self,
         *,
@@ -525,6 +527,7 @@ class Pregel(PregelProtocol):
         config_type: Optional[Type[Any]] = None,
         input_model: Optional[Type[BaseModel]] = None,
         config: Optional[RunnableConfig] = None,
+        trigger_to_nodes: Optional[Mapping[str, Sequence[str]]] = None,
         name: str = "LangGraph",
     ) -> None:
         self.nodes = nodes
@@ -544,25 +547,28 @@ class Pregel(PregelProtocol):
         self.config_type = config_type
         self.input_model = input_model
         self.config = config
+        self.trigger_to_nodes = trigger_to_nodes
         self.name = name
         if auto_validate:
             self.validate()
 
     def get_graph(
-        self, config: RunnableConfig | None = None, *, xray: int | bool = False
+        self, config: Optional[RunnableConfig] = None, *, xray: Union[int, bool] = False
     ) -> Graph:
         raise NotImplementedError
 
     async def aget_graph(
-        self, config: RunnableConfig | None = None, *, xray: int | bool = False
+        self, config: Optional[RunnableConfig] = None, *, xray: Union[int, bool] = False
     ) -> Graph:
         raise NotImplementedError
 
-    def copy(self, update: dict[str, Any] | None = None) -> Self:
+    def copy(self, update: Optional[dict[str, Any]] = None) -> Self:
         attrs = {**self.__dict__, **(update or {})}
         return self.__class__(**attrs)
 
-    def with_config(self, config: RunnableConfig | None = None, **kwargs: Any) -> Self:
+    def with_config(
+        self, config: Optional[RunnableConfig] = None, **kwargs: Any
+    ) -> Self:
         return self.copy(
             {"config": merge_configs(self.config, config, cast(RunnableConfig, kwargs))}
         )
@@ -577,6 +583,7 @@ class Pregel(PregelProtocol):
             self.interrupt_after_nodes,
             self.interrupt_before_nodes,
         )
+        self.trigger_to_nodes = _trigger_to_nodes(self.nodes)
         return self
 
     @property
@@ -2276,12 +2283,7 @@ class Pregel(PregelProtocol):
                 interrupt_after=interrupt_after_,
                 manager=run_manager,
                 debug=debug,
-                # `self.nodes` can be modified after creation of `Pregel`. For example,
-                # that's how StateGraph compilation currently works.
-                # For now, we recompute the trigger_to_nodes mapping every time the
-                # loop is created. We could potentially memoize this if it becomes a
-                # performance issue.
-                trigger_to_nodes=_trigger_to_nodes(self.nodes),
+                trigger_to_nodes=self.trigger_to_nodes,
             ) as loop:
                 # create runner
                 runner = PregelRunner(
@@ -2751,10 +2753,10 @@ class Pregel(PregelProtocol):
             return chunks
 
 
-def _trigger_to_nodes(nodes: dict[str, PregelNode]) -> Mapping[str, list[str]]:
+def _trigger_to_nodes(nodes: dict[str, PregelNode]) -> Mapping[str, Sequence[str]]:
     """Index from a trigger to nodes that depend on it."""
     trigger_to_nodes: defaultdict[str, list[str]] = defaultdict(list)
     for name, node in nodes.items():
         for trigger in node.triggers:
-            trigger_to_nodes.setdefault(trigger, []).append(name)
-    return cast(Mapping[str, list[str]], trigger_to_nodes)
+            trigger_to_nodes[trigger].append(name)
+    return dict(trigger_to_nodes)

libs/langgraph/langgraph/pregel/algo.py

@@ -323,8 +323,8 @@ def apply_writes(
     # Channels that weren't updated in this step are notified of a new step
     if bump_step:
         for chan in channels:
-            if chan not in updated_channels:
-                if channels[chan].update([]) and get_next_version is not None:
+            if channels[chan].is_available() and chan not in updated_channels:
+                if channels[chan].update(EMPTY_SEQ) and get_next_version is not None:
                     checkpoint["channel_versions"][chan] = get_next_version(
                         max_version,
                         channels[chan],
@@ -347,7 +347,7 @@ def prepare_next_tasks(
     store: Literal[None] = None,
     checkpointer: Literal[None] = None,
     manager: Literal[None] = None,
-    trigger_to_nodes: Optional[Mapping[str, list[str]]] = None,
+    trigger_to_nodes: Optional[Mapping[str, Sequence[str]]] = None,
     updated_channels: Optional[set[str]] = None,
 ) -> dict[str, PregelTask]: ...
 
@@ -366,7 +366,7 @@ def prepare_next_tasks(
     store: Optional[BaseStore],
     checkpointer: Optional[BaseCheckpointSaver],
     manager: Union[None, ParentRunManager, AsyncParentRunManager],
-    trigger_to_nodes: Optional[Mapping[str, list[str]]] = None,
+    trigger_to_nodes: Optional[Mapping[str, Sequence[str]]] = None,
     updated_channels: Optional[set[str]] = None,
 ) -> dict[str, PregelExecutableTask]: ...
 
@@ -384,7 +384,7 @@ def prepare_next_tasks(
     store: Optional[BaseStore] = None,
     checkpointer: Optional[BaseCheckpointSaver] = None,
     manager: Union[None, ParentRunManager, AsyncParentRunManager] = None,
-    trigger_to_nodes: Optional[Mapping[str, list[str]]] = None,
+    trigger_to_nodes: Optional[Mapping[str, Sequence[str]]] = None,
     updated_channels: Optional[set[str]] = None,
 ) -> Union[dict[str, PregelTask], dict[str, PregelExecutableTask]]:
     """Prepare the set of tasks that will make up the next Pregel step.
@@ -452,6 +452,8 @@ def prepare_next_tasks(
                 triggered_nodes.update(node_ids)
         # Sort the nodes to ensure deterministic order
         candidate_nodes: Iterable[str] = sorted(triggered_nodes)
+    elif not checkpoint["channel_versions"]:
+        candidate_nodes = ()
     else:
         candidate_nodes = processes.keys()
 

libs/langgraph/langgraph/pregel/loop.py

@@ -210,7 +210,7 @@ class PregelLoop(LoopProtocol):
         manager: Union[None, AsyncParentRunManager, ParentRunManager] = None,
         input_model: Optional[Type[BaseModel]] = None,
         debug: bool = False,
-        trigger_to_nodes: Optional[Mapping[str, list[str]]] = None,
+        trigger_to_nodes: Optional[Mapping[str, Sequence[str]]] = None,
     ) -> None:
         super().__init__(
             step=0,
@@ -412,7 +412,7 @@ class PregelLoop(LoopProtocol):
         updated_channels: set[str] | None = None
 
         if self.input not in (INPUT_DONE, INPUT_RESUMING, INPUT_SHOULD_VALIDATE):
-            self._first(input_keys=input_keys)
+            updated_channels = self._first(input_keys=input_keys)
         elif self.to_interrupt:
             # if we need to interrupt, do so
             self.status = "interrupt_before"
@@ -582,7 +582,7 @@ class PregelLoop(LoopProtocol):
                 else:
                     task.writes.append((k, v))
 
-    def _first(self, *, input_keys: Union[str, Sequence[str]]) -> None:
+    def _first(self, *, input_keys: Union[str, Sequence[str]]) -> Optional[set[str]]:
         # resuming from previous checkpoint requires
         # - finding a previous checkpoint
         # - receiving None input (outer graph) or RESUMING flag (subgraph)
@@ -599,6 +599,8 @@ class PregelLoop(LoopProtocol):
                 ),
             )
         )
+        # this can be set only when there are input_writes
+        updated_channels: Optional[set[str]] = None
 
         # map command to writes
         if isinstance(self.input, Command):
@@ -668,7 +670,7 @@ class PregelLoop(LoopProtocol):
                 manager=None,
             )
             # apply input writes
-            mv_writes, _ = apply_writes(
+            mv_writes, updated_channels = apply_writes(
                 self.checkpoint,
                 self.channels,
                 [
@@ -698,6 +700,7 @@ class PregelLoop(LoopProtocol):
             self.config = patch_configurable(
                 self.config, {CONFIG_KEY_RESUMING: is_resuming}
             )
+        return updated_channels
 
     def _put_checkpoint(self, metadata: CheckpointMetadata) -> None:
         for k, v in self.config["metadata"].items():
@@ -890,7 +893,7 @@ class SyncPregelLoop(PregelLoop, ContextManager):
         stream_keys: Union[str, Sequence[str]] = EMPTY_SEQ,
         input_model: Optional[Type[BaseModel]] = None,
         debug: bool = False,
-        trigger_to_nodes: Optional[Mapping[str, list[str]]] = None,
+        trigger_to_nodes: Optional[Mapping[str, Sequence[str]]] = None,
     ) -> None:
         super().__init__(
             input,
@@ -1033,7 +1036,7 @@ class AsyncPregelLoop(PregelLoop, AsyncContextManager):
         stream_keys: Union[str, Sequence[str]] = EMPTY_SEQ,
         input_model: Optional[Type[BaseModel]] = None,
         debug: bool = False,
-        trigger_to_nodes: Optional[Mapping[str, list[str]]] = None,
+        trigger_to_nodes: Optional[Mapping[str, Sequence[str]]] = None,
     ) -> None:
         super().__init__(
             input,

libs/langgraph/langgraph/pregel/read.py

@@ -62,7 +62,13 @@ class ChannelRead(RunnableCallable):
         mapper: Optional[Callable[[Any], Any]] = None,
         tags: Optional[list[str]] = None,
     ) -> None:
-        super().__init__(func=self._read, afunc=self._aread, tags=tags, name=None)
+        super().__init__(
+            func=self._read,
+            afunc=self._aread,
+            tags=tags,
+            name=None,
+            func_accepts_config=True,
+        )
         self.fresh = fresh
         self.mapper = mapper
         self.channel = channel
@@ -161,6 +167,7 @@ class PregelNode(Runnable):
         metadata: Optional[Mapping[str, Any]] = None,
         bound: Optional[Runnable[Any, Any]] = None,
         retry_policy: Optional[RetryPolicy] = None,
+        subgraphs: Optional[Sequence[PregelProtocol]] = None,
     ) -> None:
         self.channels = channels
         self.triggers = list(triggers)
@@ -170,7 +177,9 @@ class PregelNode(Runnable):
         self.retry_policy = retry_policy
         self.tags = tags
         self.metadata = metadata
-        if self.bound is not DEFAULT_BOUND:
+        if subgraphs is not None:
+            self.subgraphs = subgraphs
+        elif self.bound is not DEFAULT_BOUND:
             try:
                 subgraph = find_subgraph_pregel(self.bound)
             except Exception:
@@ -184,7 +193,6 @@ class PregelNode(Runnable):
 
     def copy(self, update: dict[str, Any]) -> PregelNode:
         attrs = {**self.__dict__, **update}
-        attrs.pop("subgraphs")
         return PregelNode(**attrs)
 
     @cached_property

libs/langgraph/langgraph/pregel/write.py

@@ -57,7 +57,13 @@ class ChannelWrite(RunnableCallable):
         tags: Optional[Sequence[str]] = None,
         require_at_least_one_of: Optional[Sequence[str]] = None,  # ignored
     ):
-        super().__init__(func=self._write, afunc=self._awrite, name=None, tags=tags)
+        super().__init__(
+            func=self._write,
+            afunc=self._awrite,
+            name=None,
+            tags=tags,
+            func_accepts_config=True,
+        )
         self.writes = cast(
             list[Union[ChannelWriteEntry, ChannelWriteTupleEntry, Send]], writes
         )

libs/langgraph/langgraph/utils/runnable.py

@@ -251,6 +251,7 @@ class RunnableCallable(Runnable):
         trace: bool = True,
         recurse: bool = True,
         explode_args: bool = False,
+        func_accepts_config: Optional[bool] = None,
         **kwargs: Any,
     ) -> None:
         self.name = name
@@ -276,27 +277,32 @@ class RunnableCallable(Runnable):
         # check signature
         if func is None and afunc is None:
             raise ValueError("At least one of func or afunc must be provided.")
-        params = inspect.signature(cast(Callable, func or afunc)).parameters
 
-        self.func_accepts_config = "config" in params
-        # Mapping from kwarg name to (config key, default value) to be used.
-        # The default value is used if the config key is not found in the config.
-        self.func_accepts: dict[str, Tuple[str, Any]] = {}
+        if func_accepts_config is not None:
+            self.func_accepts_config = func_accepts_config
+            self.func_accepts: dict[str, Tuple[str, Any]] = {}
+        else:
+            params = inspect.signature(cast(Callable, func or afunc)).parameters
 
-        for kw, typ, config_key, default in KWARGS_CONFIG_KEYS:
-            p = params.get(kw)
+            self.func_accepts_config = "config" in params
+            # Mapping from kwarg name to (config key, default value) to be used.
+            # The default value is used if the config key is not found in the config.
+            self.func_accepts = {}
 
-            if p is None or p.kind not in VALID_KINDS:
-                # If parameter is not found or is not a valid kind, skip
-                continue
+            for kw, typ, config_key, default in KWARGS_CONFIG_KEYS:
+                p = params.get(kw)
 
-            if typ != (ANY_TYPE,) and p.annotation not in typ:
-                # A specific type is required, but the function annotation does
-                # not match the expected type.
-                continue
+                if p is None or p.kind not in VALID_KINDS:
+                    # If parameter is not found or is not a valid kind, skip
+                    continue
 
-            # If the kwarg is accepted by the function, store the default value
-            self.func_accepts[kw] = (config_key, default)
+                if typ != (ANY_TYPE,) and p.annotation not in typ:
+                    # A specific type is required, but the function annotation does
+                    # not match the expected type.
+                    continue
+
+                # If the kwarg is accepted by the function, store the default value
+                self.func_accepts[kw] = (config_key, default)
 
     def __repr__(self) -> str:
         repr_args = {

libs/langgraph/poetry.lock

@@ -1324,14 +1324,14 @@ files = [
 
 [[package]]
 name = "langchain-core"
-version = "0.3.44"
+version = "0.3.46"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.9"
 groups = ["main", "dev"]
 files = [
-    {file = "langchain_core-0.3.44-py3-none-any.whl", hash = "sha256:d989ce8bd62f1d07765acd575e6ec1254aec0cf7775aaea39fe4af8102377459"},
-    {file = "langchain_core-0.3.44.tar.gz", hash = "sha256:7c0a01e78360f007cbca448178fe7e032404068e6431dbe8ce905f84febbdfa5"},
+    {file = "langchain_core-0.3.46-py3-none-any.whl", hash = "sha256:28b5689fc347975ea520b5364ab4aee5567e661553bbee5e97cabf4596c28ce0"},
+    {file = "langchain_core-0.3.46.tar.gz", hash = "sha256:5fca010eeb0a427be5aa8a8525e2112995dde790c584cef165be7c5e0ee1c2b5"},
 ]
 
 [package.dependencies]

libs/langgraph/tests/test_pregel_async.py

@@ -1,4 +1,5 @@
 import asyncio
+import enum
 import functools
 import gc
 import logging
@@ -4546,8 +4547,13 @@ async def test_nested_pydantic_models(version: str) -> None:
         name: str
         friends: list[str] = Field(default_factory=list)  # IDs of friends
 
+    class MyEnum(enum.Enum):
+        A = 1
+        B = 2
+
     class MyTypedDict(TypedDict):
         x: int
+        my_enum: MyEnum
 
     class State(BaseModel):
         # Basic nested model tests
@@ -4556,6 +4562,7 @@ async def test_nested_pydantic_models(version: str) -> None:
         optional_nested: Optional[NestedModel] = None
         dict_nested: dict[str, NestedModel]
         my_set: set[int]
+        my_enum: MyEnum
         list_nested: Annotated[
             Union[dict, list[dict[str, NestedModel]]], lambda x, y: (x or []) + [y]
         ]
@@ -4583,7 +4590,8 @@ async def test_nested_pydantic_models(version: str) -> None:
         "nested": {"value": 42, "name": "test"},
         "optional_nested": {"value": 10, "name": "optional"},
         "my_set": [1, 2, 7],
-        "my_typed_dict": {"x": 1},
+        "my_enum": MyEnum.B,
+        "my_typed_dict": {"x": 1, "my_enum": MyEnum.A},
         "dict_nested": {"a": {"value": 5, "name": "a"}},
         "list_nested": [{"a": {"value": 6, "name": "b"}}],
         "list_nested_reversed": ["foo", "bar"],