Fix empty migration (#2978 )

docs: Add documentation for LANGSMITH_RUNS_ENDPOINTS env var (#2976 )
Update SDK registration (#2974 )
2026-09-28 20:45:05 +02:00 · 2025-01-09 23:14:02 +00:00 · 2025-01-09 13:24:41 -08:00 · 2025-01-09 09:20:54 -08:00 · 2025-01-09 08:56:05 -08:00 · 2025-01-09 08:46:17 -08:00
53 changed files with 1873 additions and 193 deletions
@@ -8,7 +8,7 @@
 ⚡ Building language agents as graphs ⚡
 > [!NOTE]
-> Looking for the JS version? Click [here](https://github.com/langchain-ai/langgraphjs) ([JS docs](https://langchain-ai.github.io/langgraphjs/)).
+> Looking for the JS version? See the [JS repo](https://github.com/langchain-ai/langgraphjs) and the [JS docs](https://langchain-ai.github.io/langgraphjs/).
 ## Overview
@@ -0,0 +1,93 @@
 import functools
 from urllib3 import __version__ as urllib3version  # type: ignore[import-untyped]
 from urllib3 import connection  # type: ignore[import-untyped]
 def _ensure_str(s, encoding="utf-8", errors="strict") -> str:
    if isinstance(s, str):
        return s
    if isinstance(s, bytes):
        return s.decode(encoding, errors)
    return str(s)
 # Copied from https://github.com/urllib3/urllib3/blob/1c994dfc8c5d5ecaee8ed3eb585d4785f5febf6e/src/urllib3/connection.py#L231
 def request(self, method, url, body=None, headers=None):
    """Make the request.
    This function is based on the urllib3 request method, with modifications
    to handle potential issues when using vcrpy in concurrent workloads.
    Args:
        self: The HTTPConnection instance.
        method (str): The HTTP method (e.g., 'GET', 'POST').
        url (str): The URL for the request.
        body (Optional[Any]): The body of the request.
        headers (Optional[dict]): Headers to send with the request.
    Returns:
        The result of calling the parent request method.
    """
    # Update the inner socket's timeout value to send the request.
    # This only triggers if the connection is re-used.
    if getattr(self, "sock", None) is not None:
        self.sock.settimeout(self.timeout)
    if headers is None:
        headers = {}
    else:
        # Avoid modifying the headers passed into .request()
        headers = headers.copy()
    if "user-agent" not in (_ensure_str(k.lower()) for k in headers):
        headers["User-Agent"] = connection._get_default_user_agent()
    # The above is all the same ^^^
    # The following is different:
    return self._parent_request(method, url, body=body, headers=headers)
 _PATCHED = False
 def patch_urllib3():
    """Patch the request method of urllib3 to avoid type errors when using vcrpy.
    In concurrent workloads (such as the tracing background queue), the
    connection pool can get in a state where an HTTPConnection is created
    before vcrpy patches the HTTPConnection class. In urllib3 >= 2.0 this isn't
    a problem since they use the proper super().request(...) syntax, but in older
    versions, super(HTTPConnection, self).request is used, resulting in a TypeError
    since self is no longer a subclass of "HTTPConnection" (which at this point
    is vcr.stubs.VCRConnection).
    This method patches the class to fix the super() syntax to avoid mixed inheritance.
    In the case of the LangSmith tracing logic, it doesn't really matter since we always
    exclude cache checks for calls to LangSmith.
    The patch is only applied for urllib3 versions older than 2.0.
    """
    global _PATCHED
    if _PATCHED:
        return
    from packaging import version
    if version.parse(urllib3version) >= version.parse("2.0"):
        _PATCHED = True
        return
    # Lookup the parent class and its request method
    parent_class = connection.HTTPConnection.__bases__[0]
    parent_request = parent_class.request
    def new_request(self, *args, **kwargs):
        """Handle parent request.
        This method binds the parent's request method to self and then
        calls our modified request function.
        """
        self._parent_request = functools.partial(parent_request, self)
        return request(self, *args, **kwargs)
    connection.HTTPConnection.request = new_request
    _PATCHED = True
@@ -6,6 +6,9 @@ import re
 from typing import List, Literal, Optional
 from typing_extensions import TypedDict
 from functools import lru_cache
 import nbformat
 from nbconvert.preprocessors import Preprocessor
@@ -47,6 +50,8 @@ MANUAL_API_REFERENCES_LANGGRAPH = [
    (["langgraph.graph"], "langgraph.constants", "END", "constants"),
    (["langgraph.constants"], "langgraph.types", "Send", "types"),
    (["langgraph.constants"], "langgraph.types", "Interrupt", "types"),
    (["langgraph.constants"], "langgraph.types", "interrupt", "types"),
    (["langgraph.constants"], "langgraph.types", "Command", "types"),
    ([], "langgraph.types", "RetryPolicy", "types"),
    ([], "langgraph.checkpoint.base", "Checkpoint", "checkpoints"),
    ([], "langgraph.checkpoint.base", "CheckpointMetadata", "checkpoints"),
@@ -83,8 +88,11 @@ _IMPORT_LANGCHAIN_RE = _make_regular_expression("langchain")
 _IMPORT_LANGGRAPH_RE = _make_regular_expression("langgraph")
-def _get_full_module_name(module_path, class_name) -> Optional[str]:
+
-    """Get full module name using inspect"""
+
@lru_cache(maxsize=10_000)
 def _get_full_module_name(module_path: str, class_name: str) -> Optional[str]:
    """Get full module name using inspect, with LRU cache to memoize results."""
    try:
        module = importlib.import_module(module_path)
        class_ = getattr(module, class_name)
@@ -95,13 +103,12 @@ def _get_full_module_name(module_path, class_name) -> Optional[str]:
            return module_path
        return module.__name__
    except AttributeError as e:
-        logger.warning(f"Could not find module for {class_name}, {e}")
+        logger.warning(f"API Reference: Could not find module for {class_name}, {e}")
        return None
    except ImportError as e:
-        logger.warning(f"Failed to load for class {class_name}, {e}")
+        logger.warning(f"API Reference: Failed to load for class {class_name}, {e}")
        return None
 def _get_doc_title(data: str, file_name: str) -> str:
    try:
        return re.findall(r"^#\s*(.*)", data, re.MULTILINE)[0]
@@ -115,10 +122,10 @@ def _get_doc_title(data: str, file_name: str) -> str:
 class ImportInformation(TypedDict):
-    imported: str  # imported class name
+    imported: str  # The name of the class that was imported.
-    source: str  # module path
+    source: str  # The full module path from which the class was imported.
-    docs: str  # URL to the documentation
+    docs: str  # The URL pointing to the class's documentation.
-    title: str  # Title of the document
+    title: str  # The title of the document where the import is used.
 def _get_imports(
@@ -211,36 +218,73 @@ def _get_imports(
    return imports
-class ImportPreprocessor(Preprocessor):
+def get_imports(code: str, doc_title: str) -> List[ImportInformation]:
-    """A preprocessor to replace imports in each Python code cell with links to their
+    """Retrieve all import references from the given code for specified ecosystems.
    documentation and append the import info in a comment."""
-    def preprocess(self, nb, resources):
+    Args:
-        self.all_imports = []
+        code: The source code from which to extract import references.
-        file_name = os.path.basename(resources.get("metadata", {}).get("name", ""))
+        doc_title: The documentation title associated with the code.
        _DOC_TITLE = _get_doc_title(nb.cells[0].source, file_name)
-        cells = []
+    Returns:
-        for cell in nb.cells:
+        A list of import information for each import found.
            if cell.cell_type == "code":
                cells.append(cell)
                imports = _get_imports(
                    cell.source, _DOC_TITLE, "langchain"
                ) + _get_imports(cell.source, _DOC_TITLE, "langgraph")
                if not imports:
                    continue
                cells.append(
                    nbformat.v4.new_markdown_cell(
                        source=f"""
 <div>
 <b>API Reference:</b>
 {' | '.join(f'<a href="{imp["docs"]}">{imp["imported"]}</a>' for imp in imports)}
 </div>
    """
    ecosystems = ["langchain", "langgraph"]
    all_imports = []
    for package_ecosystem in ecosystems:
        all_imports.extend(_get_imports(code, doc_title, package_ecosystem))
    return all_imports
 def update_markdown_with_imports(markdown: str) -> str:
    """Update markdown to include API reference links for imports in Python code blocks.
    This function scans the markdown content for Python code blocks, extracts any imports, and appends links to their API documentation.
    Args:
        markdown: The markdown content to process.
    Returns:
        Updated markdown with API reference links appended to Python code blocks.
    Example:
        Given a markdown with a Python code block:
        ```python
        from langchain.nlp import TextGenerator
        ```
        This function will append an API reference link to the `TextGenerator` class from the `langchain.nlp` module if it's recognized.
    """
    code_block_pattern = re.compile(
        r'(?P<indent>[ \t]*)```(?P<language>python|py)\n(?P<code>.*?)\n(?P=indent)```', re.DOTALL
    )
    def replace_code_block(match: re.Match) -> str:
        """Replace the matched code block with additional API reference links if imports are found.
        Args:
            match (re.Match): The regex match object containing the code block.
        Returns:
            str: The modified code block with API reference links appended if applicable.
        """
        indent = match.group('indent')
        code_block = match.group('code')
        language = match.group('language')  # Preserve the language from the regex match
        # Retrieve import information from the code block
        imports = get_imports(code_block, "__unused__")
        original_code_block = match.group(0)
        # If no imports are found, return the original code block
        if not imports:
            return original_code_block
        # Generate API reference links for each import
        api_links = ' | '.join(
            f'<a href="{imp["docs"]}">{imp["imported"]}</a>' for imp in imports
        )
-            else:
+        # Return the code block with appended API reference links
-                cells.append(cell)
+        return f'{original_code_block}\n\n{indent}API Reference: {api_links}'
-        nb.cells = cells
+
-        return nb, resources
+    # Apply the replace_code_block function to all matches in the markdown
    updated_markdown = code_block_pattern.sub(replace_code_block, markdown)
    return updated_markdown
@@ -6,8 +6,6 @@ import nbformat
 from nbconvert.exporters import MarkdownExporter
 from nbconvert.preprocessors import Preprocessor
 from generate_api_reference_links import ImportPreprocessor
 class EscapePreprocessor(Preprocessor):
    def preprocess_cell(self, cell, resources, cell_index):
@@ -107,7 +105,6 @@ exporter = MarkdownExporter(
    preprocessors=[
        EscapePreprocessor,
        ExtractAttachmentsPreprocessor,
        ImportPreprocessor,
    ],
    template_name="mdoutput",
    extra_template_basedirs=[
@@ -1,10 +1,13 @@
 import logging
 import os
 import re
 from typing import Any, Dict
 from mkdocs.structure.pages import Page
 from mkdocs.structure.files import Files, File
 from mkdocs.structure.pages import Page
 from notebook_convert import convert_notebook
 from generate_api_reference_links import update_markdown_with_imports
 logger = logging.getLogger(__name__)
 logging.basicConfig()
@@ -35,12 +38,83 @@ def on_files(files: Files, **kwargs: Dict[str, Any]):
    return new_files
 def _highlight_code_blocks(markdown: str) -> str:
    """Find code blocks with highlight comments and add hl_lines attribute.
    Args:
        markdown: The markdown content to process.
    Returns:
        updated Markdown code with code blocks containing highlight comments
        updated to use the hl_lines attribute.
    """
    # Pattern to find code blocks with highlight comments and without
    # existing hl_lines for Python and JavaScript
    # Pattern to find code blocks with highlight comments, handling optional indentation
    code_block_pattern = re.compile(
        r"(?P<indent>[ \t]*)```(?P<language>py|python|js|javascript)(?!\s+hl_lines=)\n"
        r"(?P<code>((?:.*\n)*?))"  # Capture the code inside the block using named group
        r"(?P=indent)```"  # Match closing backticks with the same indentation
    )
    def replace_highlight_comments(match: re.Match) -> str:
        indent = match.group("indent")
        language = match.group("language")
        code_block = match.group("code")
        lines = code_block.split("\n")
        highlighted_lines = []
        # Skip initial empty lines
        while lines and not lines[0].strip():
            lines.pop(0)
        lines_to_keep = []
        comment_syntax = (
            "# highlight-next-line"
            if language in ["py", "python"]
            else "// highlight-next-line"
        )
        for line in lines:
            if comment_syntax in line:
                count = len(lines_to_keep) + 1
                highlighted_lines.append(str(count))
            else:
                lines_to_keep.append(line)
        # Reconstruct the new code block
        new_code_block = "\n".join(lines_to_keep)
        if highlighted_lines:
            return (
                f'{indent}```{language} hl_lines="{" ".join(highlighted_lines)}"\n'
                # The indent and terminating \n is already included in the code block
                f'{new_code_block}'
                f'{indent}```'
            )
        else:
            return (
                f"{indent}```{language}\n"
                # The indent and terminating \n is already included in the code block
                f"{new_code_block}"
                f"{indent}```"
            )
    # Replace all code blocks in the markdown
    markdown = code_block_pattern.sub(replace_highlight_comments, markdown)
    return markdown
 def on_page_markdown(markdown: str, page: Page, **kwargs: Dict[str, Any]):
    if DISABLED:
        return markdown
    if page.file.src_path.endswith(".ipynb"):
        logger.info("Processing Jupyter notebook: %s", page.file.src_path)
-        body = convert_notebook(page.file.abs_src_path)
+        markdown = convert_notebook(page.file.abs_src_path)
        return body
    # Append API reference links to code blocks
    markdown = update_markdown_with_imports(markdown)
    # Apply highlight comments to code blocks
    markdown = _highlight_code_blocks(markdown)
    return markdown
@@ -43,7 +43,9 @@ NOTEBOOKS_NO_EXECUTION = [
    "docs/docs/tutorials/lats/lats.ipynb",  # issues only when running with VCR
    "docs/docs/tutorials/rag/langgraph_crag.ipynb",  # flakiness from tavily
    "docs/docs/tutorials/rag/langgraph_adaptive_rag.ipynb",  # Cannot create a consistent method resolution error from VCR
-    "docs/docs/how-tos/map-reduce.ipynb"  # flakiness from structured output, only when running with VCR
+    "docs/docs/how-tos/map-reduce.ipynb",  # flakiness from structured output, only when running with VCR
    "docs/docs/tutorials/tot/tot.ipynb",
    "docs/docs/how-tos/visualization.ipynb"
 ]
@@ -86,6 +88,7 @@ def add_vcr_to_notebook(
 ) -> nbformat.NotebookNode:
    """Inject `with vcr.cassette` into each code cell of the notebook."""
    uses_langsmith = False
    # Inject VCR context manager into each code cell
    for idx, cell in enumerate(notebook.cells):
        if cell.cell_type != "code":
@@ -120,6 +123,9 @@ def add_vcr_to_notebook(
            f"    {line}" for line in lines
        )
        if any("hub.pull" in line or "from langsmith import" in line for line in lines):
            uses_langsmith = True
    # Add import statement
    vcr_import_lines = [
        "import nest_asyncio",
@@ -152,6 +158,15 @@ def add_vcr_to_notebook(
        "custom_vcr.register_serializer('advanced_compressed', AdvancedCompressedSerializer())",
        "custom_vcr.serializer = 'advanced_compressed'",
    ]
    if uses_langsmith:
        vcr_import_lines.extend(
            # patch urllib3 to handle vcr errors, see more here:
            # https://github.com/langchain-ai/langsmith-sdk/blob/main/python/langsmith/_internal/_patch.py
            "import sys",
            f"sys.path.insert(0, '{os.path.join(DOCS_PATH, '_scripts')}')",
            "import _patch as patch_urllib3",
            "patch_urllib3.patch_urllib3()",
        )
    import_cell = nbformat.v4.new_code_cell(source="\n".join(vcr_import_lines))
    import_cell.pop("id", None)
    notebook.cells.insert(0, import_cell)
@@ -11,7 +11,7 @@ LangGraph Cloud is available within <a href="https://www.langchain.com/langsmith
 Starting from the <a href="https://smith.langchain.com/" target="_blank">LangSmith UI</a>...
-1. In the left-hand navigation panel, select `LangGraph Cloud`. The `LangGraph Cloud` view contains a list of existing LangGraph Cloud deployments.
+1. In the left-hand navigation panel, select `LangGraph Platform`. The `LangGraph Platform` view contains a list of existing LangGraph Cloud deployments.
 1. In the top-right corner, select `+ New Deployment` to create a new deployment.
 1. In the `Create New Deployment` panel, fill out the required fields.
    1. `Deployment details`
@@ -38,7 +38,7 @@ When [creating a new deployment](#create-new-deployment), a new revision is crea
 Starting from the <a href="https://smith.langchain.com/" target="_blank">LangSmith UI</a>...
-1. In the left-hand navigation panel, select `LangGraph Cloud`. The `LangGraph Cloud` view contains a list of existing LangGraph Cloud deployments.
+1. In the left-hand navigation panel, select `LangGraph Platform`. The `LangGraph Platform` view contains a list of existing LangGraph Cloud deployments.
 1. Select an existing deployment to create a new revision for.
 1. In the `Deployment` view, in the top-right corner, select `+ New Revision`.
 1. In the `New Revision` modal, fill out the required fields.
@@ -52,15 +52,15 @@ Starting from the <a href="https://smith.langchain.com/" target="_blank">LangSmi
        1. Update the value of existing secrets or environment variables.
 1. Select `Submit`. After a few seconds, the `New Revision` modal will close and the new revision will be queued for deployment.
-## View Build and Deployment Logs
+## View Build and Server Logs
-Build and deployment logs are available for each revision.
+Build and server logs are available for each revision.
-Starting from the `LangGraph Cloud` view...
+Starting from the `LangGraph Platform` view...
 1. Select the desired revision from the `Revisions` table. A panel slides open from the right-hand side and the `Build` tab is selected by default, which displays build logs for the revision.
-1. In the panel, select the `Deploy` tab to view deployment logs for the revision.
+1. In the panel, select the `Server` tab to view server logs for the revision. Server logs are only available after a revision has been deployed.
-1. Within the `Deploy` tab, adjust the date/time range picker as needed. By default, the date/time range picker is set to the `Last 15 minutes`.
+1. Within the `Server` tab, adjust the date/time range picker as needed. By default, the date/time range picker is set to the `Last 7 days`.
 ## Interrupt Revision
@@ -69,7 +69,7 @@ Interrupting a revision will stop deployment of the revision.
 !!! warning "Undefined Behavior"
    Interrupted revisions have undefined behavior. This is only useful if you need to deploy a new revision and you already have a revision "stuck" in progress. In the future, this feature may be removed.
-Starting from the `LangGraph Cloud` view...
+Starting from the `LangGraph Platform` view...
 1. Select the menu icon (three dots) on the right-hand side of the row for the desired revision from the `Revisions` table.
 1. Select `Interrupt` from the menu.
@@ -79,13 +79,13 @@ Starting from the `LangGraph Cloud` view...
 Starting from the <a href="https://smith.langchain.com/" target="_blank">LangSmith UI</a>...
-1. In the left-hand navigation panel, select `LangGraph Cloud`. The `LangGraph Cloud` view contains a list of existing LangGraph Cloud deployments.
+1. In the left-hand navigation panel, select `LangGraph Platform`. The `LangGraph Platform` view contains a list of existing LangGraph Cloud deployments.
 1. Select the menu icon (three dots) on the right-hand side of the row for the desired deployment and select `Delete`.
 1. A `Confirmation` modal will appear. Select `Delete`.
 ## Deployment Settings
-Starting from the `LangGraph Cloud` view...
+Starting from the `LangGraph Platform` view...
 1. In the top-right corner, select the gear icon (`Deployment Settings`).
 1. Update the `Git Branch` to the desired branch.
@@ -0,0 +1,19 @@
 <!doctype html>
 <html>
  <head>
    <title>LangGraph Cloud API Reference</title>
    <meta charset="utf-8" />
    <meta
      name="viewport"
      content="width=device-width, initial-scale=1" />
  </head>
  <body>
    <script id="api-reference" data-url="./openapi_control_plane.json"></script>
    <script>
      var configuration = {}
      document.getElementById('api-reference').dataset.configuration =
        JSON.stringify(configuration)
    </script>
    <script src="https://cdn.jsdelivr.net/npm/@scalar/api-reference"></script>
  </body>
 </html>
@@ -0,0 +1,695 @@
 {
  "openapi": "3.1.0",
  "info": {
    "title": "LangGraph Control Plane API (Beta)",
    "version": "0.0.1",
    "description": "The LangGraph Control Plane API is used to programmatically create and manage LangGraph Server deployments. For example, the APIs can be orchestrated to create custom CI/CD workflows.\n\n### Beta\nThis API is currently in beta and may change or break without notice. This API documentation may not be up-to-date with actual API functionality.\n### Host\nhttps://api.host.langchain.com/\n\n### Authentication\nTo authenticate with the LangGraph Control Plane API, set the `X-Api-Key` header to a valid LangSmith API key for each request.\n\n### Versioning\nEach endpoint path is prefixed with a version (e.g. `v1`).\n\n### Quick Start\n\n1. Call `GET /{version}/projects` to retrieve the `Project` `id`. The `Project` `id` is needed in subsequent API calls.\n2. Call `POST /{version}/projects/{project_id}/revisions` to create a new `Revision` for the `Project`.\n3. Call `GET /{version}/projects/{project_id}/revisions` to get the latest `Revision` (first element in returned list). Get the `Revision` `id`.\n4. Poll for `Revision` `status` until `status` is `DEPLOYED` by calling `GET /{version}/projects/{project_id}/revisions/{revision_id}`."
  },
  "servers": [
    {
      "url": "https://api.host.langchain.com"
    }
  ],
  "tags": [
    {
      "name": "Projects (v1)",
      "description": "A project corresponds to a LangGraph Server deployment and the associated LangSmith tracing project.\n\nCreating a project via API is not currently supported/documented."
    },
    {
      "name": "Revisions (v1)",
      "description": "A revision is a version of a LangGraph Server deployment. Different revisions may contain different code and/or environment variables. A project can have many revisions."
    }
  ],
  "paths": {
    "/v1/projects": {
      "get": {
        "tags": ["Projects (v1)"],
        "summary": "List Projects",
        "description": "List all projects.",
        "operationId": "list_projects_projects_get",
        "parameters": [
          {
            "required": false,
            "schema": {
              "type": "integer",
              "title": "Limit",
              "description": "Maximum number of results to return. Minimum: 1. Maximum: 100.",
              "default": 20
            },
            "name": "limit",
            "in": "query"
          },
          {
            "required": false,
            "schema": {
              "type": "integer",
              "title": "Offset",
              "description": "Pagination offset value. Pass this value in subsequent requests to retrieve the next page of results. Minimum: 0.",
              "default": 0
            },
            "name": "offset",
            "in": "query"
          },
          {
            "required": false,
            "schema": {
              "type": "string",
              "title": "Name Contains",
              "description": "Filter string to filter projects by `name`."
            },
            "name": "name_contains",
            "in": "query"
          }
        ],
        "responses": {
          "200": {
            "description": "Success",
            "content": {
              "application/json": {
                "schema": {
                  "type": "array",
                  "items": {
                    "$ref": "#/components/schemas/Project"
                  }
                }
              }
            }
          }
        }
      }
    },
    "/v1/projects/{project_id}": {
      "get": {
        "tags": ["Projects (v1)"],
        "summary": "Get Project",
        "description": "Get project by ID.",
        "operationId": "get_project_projects__project_id__get",
        "parameters": [
          {
            "required": true,
            "schema": {
              "type": "string",
              "format": "uuid",
              "title": "Project ID"
            },
            "name": "project_id",
            "in": "path"
          }
        ],
        "responses": {
          "200": {
            "description": "Success",
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/Project"
                }
              }
            }
          }
        }
      },
      "delete": {
        "tags": ["Projects (v1)"],
        "summary": "Delete Project",
        "description": "Delete project by ID.",
        "operationId": "delete_project_projects__project_id__delete",
        "parameters": [
          {
            "required": true,
            "schema": {
              "type": "string",
              "format": "uuid",
              "title": "Project ID"
            },
            "name": "project_id",
            "in": "path"
          }
        ],
        "responses": {
          "200": {
            "description": "Success",
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/Project"
                }
              }
            }
          }
        }
      }
    },
    "/v1/projects/{project_id}/revisions": {
      "get": {
        "tags": ["Revisions (v1)"],
        "summary": "List Revisions",
        "description": "List revisions of a project.",
        "operationId": "list_revisions_projects__project_id__revisions_get",
        "parameters": [
          {
            "required": true,
            "schema": {
              "type": "string",
              "format": "uuid",
              "title": "Project ID"
            },
            "name": "project_id",
            "in": "path"
          },
          {
            "required": false,
            "schema": {
              "type": "integer",
              "title": "Limit",
              "description": "Maximum number of results to return. Minimum: 1. Maximum: 100.",
              "default": 20
            },
            "name": "limit",
            "in": "query"
          },
          {
            "required": false,
            "schema": {
              "type": "integer",
              "title": "Offset",
              "description": "Pagination offset value. Pass this value in subsequent requests to retrieve the next page of results. Minimum: 0.",
              "default": 0
            },
            "name": "offset",
            "in": "query"
          }
        ],
        "responses": {
          "200": {
            "description": "Success",
            "content": {
              "application/json": {
                "schema": {
                  "type": "array",
                  "items": {
                    "$ref": "#/components/schemas/Revision"
                  }
                }
              }
            }
          }
        }
      },
      "post": {
        "tags": ["Revisions (v1)"],
        "summary": "Create Revision",
        "description": "Create a new revision for a project.",
        "operationId": "create_revision_projects__project_id__revisions_post",
        "parameters": [
          {
            "required": true,
            "schema": {
              "type": "string",
              "format": "uuid",
              "title": "Project ID"
            },
            "name": "project_id",
            "in": "path"
          }
        ],
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/CreateRevisionRequest"
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "description": "Success",
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/Project"
                }
              }
            }
          }
        }
      }
    },
    "/v1/projects/{project_id}/revisions/{revision_id}": {
      "get": {
        "tags": ["Revisions (v1)"],
        "summary": "Get Revision",
        "description": "Get revision by ID.",
        "operationId": "get_revision_projects__project_id__revisions__revision_id__get",
        "parameters": [
          {
            "required": true,
            "schema": {
              "type": "string",
              "format": "uuid",
              "title": "Project ID"
            },
            "name": "project_id",
            "in": "path"
          },
          {
            "required": true,
            "schema": {
              "type": "string",
              "format": "uuid",
              "title": "Revision ID"
            },
            "name": "revision_id",
            "in": "path"
          }
        ],
        "responses": {
          "200": {
            "description": "Success",
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/Revision"
                }
              }
            }
          }
        }
      }
    },
    "/v1/projects/{project_id}/revisions/{revision_id}/interrupt": {
      "post": {
        "tags": ["Revisions (v1)"],
        "summary": "Interrupt Revision",
        "description": "Interrupt revision by ID.\n\nIf the deployment of a revision appears \"stuck\", the revision may need to be interrupted. A new revision cannot be created if the latest revision is in a non-terminal `status`. In this scenario, the revision may need to be interrupted.",
        "operationId": "interrupt_revision_projects__project_id__revisions__revision_id__interrupt_post",
        "parameters": [
          {
            "required": true,
            "schema": {
              "type": "string",
              "format": "uuid",
              "title": "Project ID"
            },
            "name": "project_id",
            "in": "path"
          },
          {
            "required": true,
            "schema": {
              "type": "string",
              "format": "uuid",
              "title": "Revision ID"
            },
            "name": "revision_id",
            "in": "path"
          }
        ]
      }
    }
  },
  "components": {
    "securitySchemes": {
      "apiKeyAuth": {
        "type": "apiKey",
        "in": "header",
        "name": "X-Api-Key"
      }
    },
    "schemas": {
      "EnvVar": {
        "type": "object",
        "description": "An environment variable or secret.",
        "properties": {
          "name": {
            "type": "string",
            "description": "Environment variable or secret name.",
            "required": true
          },
          "value": {
            "type": "string",
            "description": "Environment variable or secret value.",
            "required": true
          },
          "type": {
            "type": "string",
            "enum": [
              "default",
              "secret"
            ],
            "description": "Field to designate type of the environment variable (default) or secret.",
            "required": true
          }
        }
      },
      "ContainerSpec": {
        "type": "object",
        "description": "Container specification for a revision's deployment.\n\nIf any field is omitted or set to `null`, the internal default value is used depending on the deployment type (`dev` or `prod`).",
        "properties": {
          "min_scale": {
            "type": ["integer", "null"],
            "description": "Minimum number of replicas in deployment.",
            "default": "null"
          },
          "max_scale": {
            "type": ["integer", "null"],
            "description": "Maximum number of replicas in deployment.",
            "default": "null"
          },
          "cpu": {
            "type": ["integer", "null"],
            "description": "Number of vCPU cores per replica.",
            "default": "null"
          },
          "memory_mb": {
            "type": ["integer", "null"],
            "description": "Amount of memory in MB per replica.",
            "default": "null"
          }
        }
      },
      "CreateRevisionRequest": {
        "type": "object",
        "description": "Object for creating a new revision.",
        "properties": {
          "image_path": {
            "type": ["string", "null"],
            "description": "URI of the Docker image to deploy.\n\nIf this field is omitted or set to `null`, the previous revision's `image_path` value is used. Set this field for BYOC deployments. Omit this field if creating a new revision from a GitHub repository.",
            "default": "null"
          },
          "repo_path": {
            "type": ["string", "null"],
            "description": "Path to `langgraph.json` configuration file. For example, `langgraph.json` or `src/langgraph.json`.\n\nIf this field is omitted or set to `null`, the previous revision's `repo_path` value is used. Set this field for deployments from a GitHub repository. Omit this field if creating a new revision from a Docker image.",
            "default": "null"
          },
          "env_vars": {
            "type": "array",
            "description": "List of environment variables or secrets.\n\nIf this field is omitted or set to `null`, the previous revision's `env_vars` value is used.",
            "items": {
              "$ref": "#/components/schemas/EnvVar"
            },
            "default": "null"
          },
          "shareable": {
            "type": ["boolean", "null"],
            "description": "Boolean flag to configure if a deployment is shareable through LangGraph Studio.\n\nIf this field is omitted or set to `null`, the previous revision's `shareable` value is used. This field does not apply to BYOC deployments.",
            "default": "null"
          },
          "container_spec": {
            "description": "If this field is omitted or set to `null`, the previous revision's `container_spec` value is used.",
            "$ref": "#/components/schemas/ContainerSpec",
            "default": "null"
          }
        }
      },
      "Project": {
        "type": "object",
        "description": "A project corresponds to a LangGraph Server deployment and the associated LangSmith tracing project.",
        "properties": {
          "id": {
            "type": "string",
            "format": "uuid",
            "description": "ID of the project.",
            "required": true
          },
          "tool_name": {
            "type": ["string", "null"],
            "description": "Do not use."
          },
          "display_name": {
            "type": ["string", "null"],
            "description": "Do not use."
          },
          "description": {
            "type": ["string", "null"],
            "description": "Do not use."
          },
          "example_input": {
            "type": ["object", "null"],
            "description": "Do not use."
          },
          "tenant_id": {
            "type": "string",
            "format": "uuid",
            "description": "ID of the tenant/workspace of the project.",
            "required": true
          },
          "created_at": {
            "type": "string",
            "format": "date-time",
            "description": "Timestamp of when the project was created.",
            "required": true
          },
          "updated_at": {
            "type": "string",
            "format": "date-time",
            "description": "Timestamp of when the project was updated.",
            "required": true
          },
          "name": {
            "type": "string",
            "description": "Name of the project.\n\nThis is also the name of the LangSmith tracing project for the LangGraph deployment.",
            "required": true
          },
          "lc_hosted": {
            "type": "boolean",
            "description": "Boolean flag to indicate if the deployment is hosted in LangChain's cloud or an external cloud (e.g. BYOC).",
            "required": true
          },
          "repo_url": {
            "type": ["string", "null"],
            "description": "URL of the GitHub repository.\n\nThis field is not used for deployments from a Docker image."
          },
          "repo_branch": {
            "type": ["string", "null"],
            "description": "Branch of the GitHub repository.\n\nThis field is not used for deployments from a Docker image."
          },
          "tracer_session_id": {
            "type": ["string", "null"],
            "format": "uuid",
            "description": "Do not use."
          },
          "api_key_id": {
            "type": ["string", "null"],
            "format": "uuid",
            "description": "Do not use."
          },
          "build_on_push": {
            "type": "boolean",
            "description": "Boolean flag to indicate if a new revision is automatically created on push to GitHub branch (`repo_branch`).\n\nThis field does not apply for BYOC deployments."
          },
          "input_json_schemas": {
            "type": ["object", "null"],
            "description": "Do not use."
          },
          "output_json_schemas": {
            "type": ["object", "null"],
            "description": "Do not use."
          },
          "host_integration_id": {
            "type": ["string", "null"],
            "format": "uuid",
            "description": "Do not use."
          },
          "metadata": {
            "$ref": "#/components/schemas/ProjectMetadata"
          },
          "resource": {
            "$ref": "#/components/schemas/ResourceService"
          }
        }
      },
      "ProjectMetadata": {
        "type": "object",
        "description": "Metadata associated with a `Project`.",
        "properties": {
          "deployment_type": {
            "type": "string",
            "description": "Development (`dev`) or Production (`prod`) type deployment.",
            "enum": [
              "dev",
              "prod"
            ]
          },
          "image_source": {
            "type": "string",
            "description": "Do not use.",
            "enum": [
              "github",
              "internal_docker",
              "external_docker"
            ]
          },
          "shareable": {
            "type": "boolean",
            "description": "Boolean flag to configure if a deployment is shareable through LangGraph Studio.\n\nThis field does not apply to BYOC deployments."
          },
          "region": {
            "type": "string",
            "description": "Region of deployment.\n\nRegion value is cloud provider specific."
          },
          "aws_account_id": {
            "type": "string",
            "description": "AWS account ID of BYOC deployment.\n\nThis field does not apply to non-BYOC deployments."
          },
          "aws_external_id": {
            "type": "string",
            "description": "Do not use."
          }
        }
      },
      "ResourceId": {
        "type": "object",
        "description": "Internal identifier for a `ResourceRevision` or `ResourceService`.",
        "properties": {
          "type": {
            "type": "string",
            "enum": [
              "revisions",
              "services"
            ]
          },
          "name": {
            "type": "string"
          }
        }
      },
      "ResourceRevision": {
        "type": "object",
        "description": "Internal revision resource for a `ResourceService`.",
        "properties": {
          "id": {
            "$ref": "#/components/schemas/ResourceId"
          },
          "env_vars": {
            "type": "array",
            "items": {
              "$ref": "#/components/schemas/EnvVar"
            }
          },
          "hosted_langserve_revision_id": {
            "type": "string",
            "format": "uuid",
            "description": "References `id` of a `Revision`."
          }
        }
      },
      "ResourceService": {
        "type": "object",
        "description": "Internal service resource for a `Project`.",
        "properties": {
          "id": {
            "$ref": "#/components/schemas/ResourceId"
          },
          "url": {
            "type": ["string", "null"],
            "description": "URL of LangGraph Server deployment."
          },
          "latest_revision": {
            "description": "References latest `ResourceRevision`.\n\nThe latest `ResourceRevision` may not be active if it's currently being deployed.",
            "$ref": "#/components/schemas/ResourceRevision"
          },
          "latest_active_revision": {
            "description": "References latest active `ResourceRevision`.\n\nThe latest active `ResourceRevision` is not always the latest `ResourceRevision`.",
            "$ref": "#/components/schemas/ResourceRevision"
          }
        }
      },
      "Revision": {
        "type": "object",
        "description": "A revision is a version of a LangGraph Server deployment.\n\nDifferent revisions may contain different code and/or environment variables. A project can have many revisions.",
        "properties": {
          "id": {
            "type": "string",
            "format": "uuid",
            "description": "ID of the revision.",
            "required": true
          },
          "project_id": {
            "type": "string",
            "format": "uuid",
            "description": "References `id` of `Project`.",
            "required": true
          },
          "created_at": {
            "type": "string",
            "format": "date-time",
            "description": "Timestamp of when the revision was created.",
            "required": true
          },
          "updated_at": {
            "type": "string",
            "format": "date-time",
            "description": "Timestamp of when the revision was updated.",
            "required": true
          },
          "repo_path": {
            "type": ["string", "null"],
            "description": "Path to `langgraph.json` configuration file. For example, `langgraph.json` or `src/langgraph.json`.\n\nThis field only applies to deployments from a GitHub repository.",
            "default": "null"
          },
          "repo_commit": {
            "type": ["string", "null"],
            "description": "Git branch name of deployment.\n\nThis field only applies to deployments from a GitHub repository.",
            "default": "null"
          },
          "status": {
            "type": "string",
            "enum": [
              "CREATING",
              "AWAITING_BUILD",
              "BUILDING",
              "AWAITING_DEPLOY",
              "DEPLOYING",
              "CREATE_FAILED",
              "BUILD_FAILED",
              "DEPLOY_FAILED",
              "DEPLOYED",
              "INTERRUPTED",
              "UNKNOWN"
            ],
            "description": "Deployment status of the revision.\n\nNon-terminal statuses: `CREATING`, `AWAITING_BUILD`, `BUILDING`, `AWAITING_DEPLOY`, `DEPLOYING`. All other statuses are terminal."
          },
          "status_message": {
            "type": "string",
            "description": "Message associated with the `status`."
          },
          "gcp_build_name": {
            "type": ["string", "null"],
            "description": "Do not use."
          },
          "metadata": {
            "$ref": "#/components/schemas/RevisionMetadata"
          },
          "image_path": {
            "type": ["string", "null"],
            "description": "URI of the Docker image to deploy.\n\nThis field does not apply to deployments from a GitHub repository.",
            "default": "null"
          },
          "container_spec": {
            "$ref": "#/components/schemas/ContainerSpec"
          },
          "resource": {
            "$ref": "#/components/schemas/ResourceRevision"
          }
        }
      },
      "RevisionMetadata": {
        "type": "object",
        "description": "Metadata associated with a `Revision`.",
        "properties": {
          "created_by": {
            "type": "object",
            "description": "Do not use."
          },
          "repo_commit_sha": {
            "type": "string",
            "description": "Git commit SHA of the deployment.\n\nThis field only applies to deployments from a GitHub repository."
          }
        }
      }
    }
  }
 }
@@ -61,6 +61,7 @@ The LangGraph CLI requires a JSON configuration file with the following keys:
 All deployments come with a DB-backed BaseStore. Adding an "index" configuration to your `langgraph.json` will enable [semantic search](../deployment/semantic_search.md) within the BaseStore of your deployment.
 The `fields` configuration determines which parts of your documents to embed:
 - If omitted or set to `["$"]`, the entire document will be embedded
 - To embed specific fields, use JSON path notation: `["metadata.title", "content.text"]`
 - Documents missing specified fields will still be stored but won't have embeddings for those fields
@@ -1,6 +1,6 @@
 # Environment Variables
-The LangGraph Cloud API supports specific environment variables for configuring a deployment.
+The LangGraph Cloud Server supports specific environment variables for configuring a deployment.
 ## `LANGCHAIN_TRACING_SAMPLING_RATE`
@@ -10,10 +10,42 @@ See <a href="https://docs.smith.langchain.com/how_to_guides/tracing/sample_trace
 ## `LANGGRAPH_AUTH_TYPE`
-Type of authentication for the LangGraph Cloud API deployment. Valid values: `langsmith`, `noop`.
+Type of authentication for the LangGraph Cloud Server deployment. Valid values: `langsmith`, `noop`.
 For deployments to LangGraph Cloud, this environment variable is set automatically. For local development or deployments where authentication is handled externally (e.g. self-hosted), set this environment variable to `noop`.
 ## `LANGSMITH_RUNS_ENDPOINTS`
 For [Bring Your Own Cloud (BYOC)](../../concepts/bring_your_own_cloud.md) deployments with [self-hosted LangSmith](https://docs.smith.langchain.com/self_hosting) only.
 Set this environment variable to have a BYOC deployment send traces to a self-hosted LangSmith instance. The value of `LANGSMITH_RUNS_ENDPOINTS` is a JSON string: `{"<SELF_HOSTED_LANGSMITH_HOSTNAME>":"<LANGSMITH_API_KEY>"}`.
 `SELF_HOSTED_LANGSMITH_HOSTNAME` is the hostname of the self-hosted LangSmith instance. It must be accessible to the BYOC deployment. `LANGSMITH_API_KEY` is a LangSmith API generated from the self-hosted LangSmith instance.
 ## `N_JOBS_PER_WORKER`
 Number of jobs per worker for the LangGraph Cloud task queue. Defaults to `10`.
 ## `POSTGRES_URI_CUSTOM`
 For [Bring Your Own Cloud (BYOC)](../../concepts/bring_your_own_cloud.md) deployments only.
 Specify `POSTGRES_URI_CUSTOM` to use an externally managed Postgres instance. The value of `POSTGRES_URI_CUSTOM` must be a valid [Postgres connection URI](https://www.postgresql.org/docs/current/libpq-connect.html#LIBPQ-CONNSTRING-URIS).
 Postgres:
 - Version 15.8 or higher.
 - An initial database must be present and the connection URI must reference the database.
 Control Plane Functionality:
 - If `POSTGRES_URI_CUSTOM` is specified, the LangGraph Control Plane will not provision a database for the server.
 - If `POSTGRES_URI_CUSTOM` is removed, the LangGraph Control Plane will not provision a database for the server and will not delete the externally managed Postgres instance.
 - If `POSTGRES_URI_CUSTOM` is removed, deployment of the revision will not succeed. Once `POSTGRES_URI_CUSTOM` is specified, it must always be set for the lifecycle of the deployment.
 - If the deployment is deleted, the LangGraph Control Plane will not delete the externally managed Postgres instance.
 - The value of `POSTGRES_URI_CUSTOM` can be updated. For example, a password in the URI can be updated.
 Database Connectivity:
 - The externally managed Postgres instance must be accessible by the LangGraph Server service in the ECS cluster. The BYOC user is responsible for ensuring connectivity.
 - For example, if an AWS RDS Postgres instance is provisioned, it can be provisioned in the same VPC (`langgraph-cloud-vpc`) as the ECS cluster with the `langgraph-cloud-service-sg` security group to ensure connectivity.
@@ -39,6 +39,7 @@ LangChain has no direct access to the resources created in your cloud account, a
            - Read CloudWatch metrics/logs to monitor your instances/push deployment logs
        - https://docs.aws.amazon.com/aws-managed-policy/latest/reference/AmazonRDSFullAccess.html
            - Provision `RDS` instances for your LangGraph Cloud instances
            - Alternatively, an externally managed Postgres instance can be used instead of the default `RDS` instance. LangChain does not monitor or manage the externally managed Postgres instance. See details for [`POSTGRES_URI_CUSTOM` environment variable](../cloud/reference/env_var.md#postgres_uri_custom).
    2. Either
        - Tags an existing vpc / subnets as `langgraph-cloud-enabled`
        - Creates a new vpc and subnets and tags them as `langgraph-cloud-enabled`
@@ -50,5 +51,5 @@ LangChain has no direct access to the resources created in your cloud account, a
 Notes for customers using [self-hosted LangSmith](https://docs.smith.langchain.com/self_hosting):
- Creation of new LangGraph Cloud projects and revisions currently needs to be done on smith.langchain.com.
+- Creation of new LangGraph Cloud projects and revisions currently needs to be done on `smith.langchain.com`.
- You can however set up the project to trace to your self-hosted LangSmith instance if desired
+- However, you can set up the project to trace to your self-hosted LangSmith instance if desired. See details for [`LANGSMITH_RUNS_ENDPOINTS` environment variable](../cloud/reference/env_var.md#langsmith_runs_endpoints).
@@ -444,7 +444,7 @@
    "\n",
    "    # Check the signed-in user actually has this ticket\n",
    "    cursor.execute(\n",
-    "        \"SELECT flight_id FROM tickets WHERE ticket_no = ? AND passenger_id = ?\",\n",
+    "        \"SELECT ticket_no FROM tickets WHERE ticket_no = ? AND passenger_id = ?\",\n",
    "        (ticket_no, passenger_id),\n",
    "    )\n",
    "    current_ticket = cursor.fetchone()\n",
@@ -4444,7 +4444,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.11.9"
+   "version": "3.12.3"
  }
 },
 "nbformat": 4,
@@ -1659,7 +1659,7 @@
   "id": "584de971-6b10-4931-986e-cc35f7adbb3d",
   "metadata": {},
   "source": [
-    "Now the graph is complete, since we've provided the final response message! Since state updates simulate a graph step, they even generate corresponding traces. Inspec the [LangSmith trace](https://smith.langchain.com/public/6d72aeb5-3bca-4090-8684-a11d5a36b10c/r) of the `update_state` call above to see what's going on.\n",
+    "Now the graph is complete, since we've provided the final response message! Since state updates simulate a graph step, they even generate corresponding traces. Inspect the [LangSmith trace](https://smith.langchain.com/public/6d72aeb5-3bca-4090-8684-a11d5a36b10c/r) of the `update_state` call above to see what's going on.\n",
    "\n",
    "**Notice** that our new messages are _appended_ to the messages already in the state. Remember how we defined the `State` type?\n",
    "\n",
@@ -135,7 +135,7 @@
    "from typing_extensions import TypedDict\n",
    "\n",
    "from langchain_anthropic import ChatAnthropic\n",
-    "from langgraph.graph import MessagesState\n",
+    "from langgraph.graph import MessagesState, END\n",
    "from langgraph.types import Command\n",
    "\n",
    "\n",
@@ -26,7 +26,7 @@
   "outputs": [],
   "source": [
    "%%capture --no-stderr\n",
-    "%pip install -U --quiet langchain-community tiktoken langchain-openai langchainhub chromadb langchain langgraph langchain-text-splitters"
+    "%pip install -U --quiet langchain-community tiktoken langchain-openai langchainhub chromadb langchain langgraph langchain-text-splitters beautifulsoup4"
   ]
  },
  {
@@ -2,6 +2,7 @@ site_name: ""
 site_description: Build language agents as graphs
 site_url: https://langchain-ai.github.io/langgraph/
 repo_url: https://github.com/langchain-ai/langgraph
 edit_uri: edit/main/docs/docs/
 theme:
  name: material
  custom_dir: overrides
@@ -16,6 +17,7 @@ theme:
    - content.code.copy
    - content.code.select
    - content.tabs.link
    - content.action.edit
    - content.tooltips
    - header.autohide
    - navigation.expand
@@ -58,8 +58,6 @@ MIGRATIONS = [
 );""",
    "ALTER TABLE checkpoint_blobs ALTER COLUMN blob DROP not null;",
    """
    """,
    """
    CREATE INDEX CONCURRENTLY IF NOT EXISTS checkpoints_thread_id_idx ON checkpoints(thread_id);
    """,
    """
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langgraph-checkpoint-postgres"
-version = "2.0.9"
+version = "2.0.10"
 description = "Library with a Postgres implementation of LangGraph checkpoint saver."
 authors = []
 license = "MIT"
@@ -1,5 +1,6 @@
 # type: ignore
 import re
 from contextlib import contextmanager
 from typing import Any, Optional
 from uuid import uuid4
@@ -782,3 +783,10 @@ def test_scores(
        assert len(results) == 1
        assert results[0].score == pytest.approx(similarities[0], abs=1e-3)
 def test_nonnull_migrations() -> None:
    _leading_comment_remover = re.compile(r"^/\*.*?\*/")
    for migration in PostgresStore.MIGRATIONS:
        statement = _leading_comment_remover.sub("", migration).split()[0]
        assert statement.strip()
@@ -1,5 +1,6 @@
 # type: ignore
 import re
 from contextlib import contextmanager
 from typing import Any
 from uuid import uuid4
@@ -238,3 +239,10 @@ def test_null_chars(saver_name: str, test_data) -> None:
            list(saver.list(None, filter={"my_key": "abc"}))[0].metadata["my_key"]
            == "abc"
        )
 def test_nonnull_migrations() -> None:
    _leading_comment_remover = re.compile(r"^/\*.*?\*/")
    for migration in PostgresSaver.MIGRATIONS:
        statement = _leading_comment_remover.sub("", migration).split()[0]
        assert statement.strip()
@@ -8,7 +8,7 @@
 ⚡ Building language agents as graphs ⚡
 > [!NOTE]
-> Looking for the JS version? Click [here](https://github.com/langchain-ai/langgraphjs) ([JS docs](https://langchain-ai.github.io/langgraphjs/)).
+> Looking for the JS version? See the [JS repo](https://github.com/langchain-ai/langgraphjs) and the [JS docs](https://langchain-ai.github.io/langgraphjs/).
 ## Overview
@@ -1,5 +1,7 @@
 import operator
-from typing import Annotated, TypedDict
+from typing import Annotated
 from typing_extensions import TypedDict
 from langgraph.constants import END, START, Send
 from langgraph.graph.state import StateGraph
@@ -1,9 +1,9 @@
 import asyncio
 import concurrent
 import concurrent.futures
 import functools
 import inspect
 import types
 from functools import partial, update_wrapper
 from typing import (
    Any,
    Awaitable,
@@ -33,17 +33,17 @@ T = TypeVar("T")
 def call(
-    func: Callable[[P1], T],
+    func: Callable[P, T],
-    input: P1,
+    *args: Any,
    *,
    retry: Optional[RetryPolicy] = None,
    **kwargs: Any,
 ) -> concurrent.futures.Future[T]:
    from langgraph.constants import CONFIG_KEY_CALL
    from langgraph.utils.config import get_configurable
    conf = get_configurable()
    impl = conf[CONFIG_KEY_CALL]
-    fut = impl(func, input, retry=retry)
+    fut = impl(func, (args, kwargs), retry=retry)
    return fut
@@ -59,16 +59,51 @@ def task(  # type: ignore[overload-cannot-match]
 ) -> Callable[[Callable[P, T]], Callable[P, concurrent.futures.Future[T]]]: ...
@overload
 def task(
-    *, retry: Optional[RetryPolicy] = None
+    __func_or_none__: Callable[P, T],
 ) -> Callable[P, concurrent.futures.Future[T]]: ...
@overload
 def task(
    __func_or_none__: Callable[P, Awaitable[T]],
 ) -> Callable[P, asyncio.Future[T]]: ...
 def task(
    __func_or_none__: Optional[Union[Callable[P, T], Callable[P, Awaitable[T]]]] = None,
    *,
    retry: Optional[RetryPolicy] = None,
 ) -> Union[
    Callable[[Callable[P, Awaitable[T]]], Callable[P, asyncio.Future[T]]],
    Callable[[Callable[P, T]], Callable[P, concurrent.futures.Future[T]]],
    Callable[P, asyncio.Future[T]],
    Callable[P, concurrent.futures.Future[T]],
 ]:
-    def _task(func: Callable[P, T]) -> Callable[P, concurrent.futures.Future[T]]:
+    def decorator(
-        return update_wrapper(partial(call, func, retry=retry), func)
+        func: Union[Callable[P, Awaitable[T]], Callable[P, T]],
    ) -> Callable[P, concurrent.futures.Future[T]]:
        if asyncio.iscoroutinefunction(func):
-    return _task
+            @functools.wraps(func)
            async def _tick(__allargs__: tuple) -> T:
                return await func(*__allargs__[0], **__allargs__[1])
        else:
            @functools.wraps(func)
            def _tick(__allargs__: tuple) -> T:
                return func(*__allargs__[0], **__allargs__[1])
        return functools.update_wrapper(
            functools.partial(call, _tick, retry=retry), func
        )
    if __func_or_none__ is not None:
        return decorator(__func_or_none__)
    return decorator
 def entrypoint(
@@ -8,7 +8,6 @@ from typing import (
    Literal,
    Optional,
    Sequence,
    TypedDict,
    Union,
    cast,
 )
@@ -22,6 +21,7 @@ from langchain_core.messages import (
    convert_to_messages,
    message_chunk_to_message,
 )
 from typing_extensions import TypedDict
 from langgraph.graph.state import StateGraph
@@ -398,9 +398,11 @@ class StateGraph(Graph):
        return self
    def add_edge(self, start_key: Union[str, list[str]], end_key: str) -> Self:
-        """Adds a directed edge from the start node to the end node.
+        """Adds a directed edge from the start node (or list of start nodes) to the end node.
-        If the graph transitions to the start_key node, it will always transition to the end_key node next.
+        When a single start node is provided, the graph will wait for that node to complete
        before executing the end node. When multiple start nodes are provided,
        the graph will wait for ALL of the start nodes to complete before executing the end node.
        Args:
            start_key (Union[str, list[str]]): The key(s) of the start node(s) of the edge.
@@ -381,7 +381,7 @@ def create_react_agent(
        Add complex prompt with custom graph state:
        ```pycon
-        >>> from typing import TypedDict
+        >>> from typing_extensions import TypedDict
        >>>
        >>> from langgraph.managed import IsLastStep
        >>> prompt = ChatPromptTemplate.from_messages(
@@ -554,6 +554,10 @@ def create_react_agent(
    )
    model_runnable = preprocessor | model
    # If any of the tools are configured to return_directly after running,
    # our graph needs to check if these were called
    should_return_direct = {t.name for t in tool_classes if t.return_direct}
    # Define the function that calls the model
    def call_model(state: AgentState, config: RunnableConfig) -> AgentState:
        _validate_chat_history(state["messages"])
@@ -673,10 +677,6 @@ def create_react_agent(
        should_continue,
    )
    # If any of the tools are configured to return_directly after running,
    # our graph needs to check if these were called
    should_return_direct = {t.name for t in tool_classes if t.return_direct}
    def route_tool_responses(state: AgentState) -> Literal["agent", "__end__"]:
        for m in reversed(state["messages"]):
            if not isinstance(m, ToolMessage):
@@ -601,7 +601,8 @@ def tools_condition(
        >>> from langgraph.prebuilt import ToolNode, tools_condition
        >>> from langgraph.graph.message import add_messages
        ...
-        >>> from typing import TypedDict, Annotated
+        >>> from typing import Annotated
        >>> from typing_extensions import TypedDict
        ...
        >>> @tool
        >>> def divide(a: float, b: float) -> int:
@@ -74,7 +74,8 @@ class ValidationNode(RunnableCallable):
    Examples:
        Example usage for re-prompting the model to generate a valid response:
-        >>> from typing import Literal, Annotated, TypedDict
+        >>> from typing import Literal, Annotated
        >>> from typing_extensions import TypedDict
        ...
        >>> from langchain_anthropic import ChatAnthropic
        >>> from pydantic import BaseModel, validator
@@ -10,13 +10,13 @@ from typing import (
    Mapping,
    Optional,
    Sequence,
    TypedDict,
    Union,
 )
 from uuid import UUID
 from langchain_core.runnables.config import RunnableConfig
 from langchain_core.utils.input import get_bolded_text, get_colored_text
 from typing_extensions import TypedDict
 from langgraph.channels.base import BaseChannel
 from langgraph.checkpoint.base import Checkpoint, CheckpointMetadata, PendingWrite
@@ -1,3 +1,4 @@
 from collections import Counter
 from typing import Any, Iterator, Literal, Mapping, Optional, Sequence, TypeVar, Union
 from uuid import UUID
@@ -181,10 +182,25 @@ def map_output_updates(
                (task.name, value) for chan, value in writes if chan == output_channels
            )
        elif any(chan in output_channels for chan, _ in writes):
            counts = Counter(chan for chan, _ in writes)
            if any(counts[chan] > 1 for chan in output_channels):
                updated.extend(
                    (
                        task.name,
                        {chan: value},
                    )
                    for chan, value in writes
                    if chan in output_channels
                )
            else:
                updated.append(
                    (
                        task.name,
-                    {chan: value for chan, value in writes if chan in output_channels},
+                        {
                            chan: value
                            for chan, value in writes
                            if chan in output_channels
                        },
                    )
                )
    grouped: dict[str, list[Any]] = {t.name: [] for t, _ in output_tasks}
@@ -1032,6 +1032,13 @@ class AsyncPregelLoop(PregelLoop, AsyncContextManager):
        traceback: Optional[TracebackType],
    ) -> Optional[bool]:
        # unwind stack
-        return await asyncio.shield(
+        exit_task = asyncio.create_task(
            self.stack.__aexit__(exc_type, exc_value, traceback)
        )
        try:
            return await exit_task
        except asyncio.CancelledError as e:
            # Bubble up the exit task upon cancellation to permit the API
            # consumer to await it before e.g., re-using the DB connection.
            e.args = (*e.args, exit_task)
            raise
@@ -13,14 +13,13 @@ from typing import (
    Optional,
    Sequence,
    Type,
    TypedDict,
    TypeVar,
    Union,
    cast,
 )
 from langchain_core.runnables import Runnable, RunnableConfig
-from typing_extensions import Self
+from typing_extensions import Self, TypedDict
 from langgraph.checkpoint.base import (
    BaseCheckpointSaver,
@@ -373,7 +372,8 @@ def interrupt(value: Any) -> Any:
    Example:
        ```python
        import uuid
-        from typing import TypedDict, Optional
+        from typing import Optional
        from typing_extensions import TypedDict
        from langgraph.checkpoint.memory import MemorySaver
        from langgraph.constants import START
@@ -965,13 +965,13 @@ testing = ["Django", "attrs", "colorama", "docopt", "pytest (<7.0.0)"]
 [[package]]
 name = "jinja2"
-version = "3.1.4"
+version = "3.1.5"
 description = "A very fast and expressive template engine."
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "jinja2-3.1.4-py3-none-any.whl", hash = "sha256:bc5dd2abb727a5319567b7a813e6a2e7318c39f4f487cfe6c89c6f9c7d25197d"},
+    {file = "jinja2-3.1.5-py3-none-any.whl", hash = "sha256:aba0f4dc9ed8013c424088f68a5c226f7d6097ed89b246d7749c2ec4175c6adb"},
-    {file = "jinja2-3.1.4.tar.gz", hash = "sha256:4a3aee7acbbe7303aede8e9648d13b8bf88a429282aa6122a993f0ac800cb369"},
+    {file = "jinja2-3.1.5.tar.gz", hash = "sha256:8fefff8dc3034e27bb80d67c671eb8a9bc424c0ef4c0826edbff304cceff43bb"},
 ]
 [package.dependencies]
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langgraph"
-version = "0.2.60"
+version = "0.2.61"
 description = "Building stateful, multi-actor applications with LLMs"
 authors = []
 license = "MIT"
@@ -38,7 +38,7 @@ py-spy = "^0.3.14"
 types-requests = "^2.32.0.20240914"
 [tool.ruff]
-lint.select = [ "E", "F", "I" ]
+lint.select = [ "E", "F", "I", "TID251" ]
 lint.ignore = [ "E501" ]
 line-length = 88
 indent-width = 4
@@ -52,6 +52,9 @@ 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."
 [tool.mypy]
 # https://mypy.readthedocs.io/en/stable/config_file.html
 disallow_untyped_defs = "True"
@@ -1,7 +1,6 @@
 from typing import TypedDict
 import pytest
 from pytest_mock import MockerFixture
 from typing_extensions import TypedDict
 from langgraph.graph import END, START, StateGraph
 from tests.conftest import (
@@ -4,13 +4,14 @@ import re
 import time
 from contextlib import contextmanager
 from dataclasses import replace
-from typing import Annotated, Any, Iterator, Literal, Optional, TypedDict, Union, cast
+from typing import Annotated, Any, Iterator, Literal, Optional, Union, cast
 import httpx
 import pytest
 from langchain_core.runnables import RunnableConfig, RunnableMap, RunnablePick
 from pytest_mock import MockerFixture
 from syrupy import SnapshotAssertion
 from typing_extensions import TypedDict
 from langgraph.channels.context import Context
 from langgraph.channels.last_value import LastValue
@@ -9,7 +9,6 @@ from typing import (
    AsyncIterator,
    Literal,
    Optional,
    TypedDict,
    Union,
    cast,
 )
@@ -21,6 +20,7 @@ from langchain_core.runnables import RunnableConfig, RunnablePick
 from pydantic import BaseModel
 from pytest_mock import MockerFixture
 from syrupy import SnapshotAssertion
 from typing_extensions import TypedDict
 from langgraph.channels.context import Context
 from langgraph.channels.last_value import LastValue
@@ -1,4 +1,5 @@
 import dataclasses
 import inspect
 import json
 from functools import partial
 from typing import (
@@ -2040,3 +2041,9 @@ def test__get_state_args() -> None:
        return 0.0
    assert _get_state_args(foo) == {"a": None, "b": "bar"}
 def test_inspect_react() -> None:
    model = FakeToolCallingModel(tool_calls=[])
    agent = create_react_agent(model, [])
    inspect.getclosurevars(agent.nodes["agent"].bound.func)
@@ -21,7 +21,6 @@ from typing import (
    Optional,
    Sequence,
    Tuple,
    TypedDict,
    Union,
    get_type_hints,
 )
@@ -36,6 +35,7 @@ from langchain_core.runnables import (
 from langsmith import traceable
 from pytest_mock import MockerFixture
 from syrupy import SnapshotAssertion
 from typing_extensions import TypedDict
 from langgraph.channels.base import BaseChannel
 from langgraph.channels.binop import BinaryOperatorAggregate
@@ -1515,27 +1515,32 @@ def test_imp_stream_order(
    checkpointer = request.getfixturevalue(f"checkpointer_{checkpointer_name}")
    @task()
-    def foo(state: dict) -> dict:
+    def foo(state: dict) -> tuple:
-        return {"a": state["a"] + "foo", "b": "bar"}
+        return state["a"] + "foo", "bar"
-    @task()
+    @task
-    def bar(state: dict) -> dict:
+    def bar(a: str, b: str, c: Optional[str] = None) -> dict:
-        return {"a": state["a"] + state["b"], "c": "bark"}
+        return {"a": a + b, "c": (c or "") + "bark"}
-    @task()
+    @task
    def baz(state: dict) -> dict:
        return {"a": state["a"] + "baz", "c": "something else"}
    @entrypoint(checkpointer=checkpointer)
    def graph(state: dict) -> dict:
        fut_foo = foo(state)
-        fut_bar = bar(fut_foo.result())
+        fut_bar = bar(*fut_foo.result())
        fut_baz = baz(fut_bar.result())
        return fut_baz.result()
    thread1 = {"configurable": {"thread_id": "1"}}
    assert [c for c in graph.stream({"a": "0"}, thread1)] == [
-        {"foo": {"a": "0foo", "b": "bar"}},
+        {
            "foo": (
                "0foo",
                "bar",
            )
        },
        {"bar": {"a": "0foobar", "c": "bark"}},
        {"baz": {"a": "0foobarbaz", "c": "something else"}},
        {"graph": {"a": "0foobarbaz", "c": "something else"}},
@@ -4168,10 +4173,12 @@ def test_store_injected(
        def __call__(self, inputs: State, config: RunnableConfig, store: BaseStore):
            assert isinstance(store, BaseStore)
            store.put(
                (
                    namespace
                    if self.i is not None
                    and config["configurable"]["thread_id"] in (thread_1, thread_2)
-                else (f"foo_{self.i}", "bar"),
+                    else (f"foo_{self.i}", "bar")
                ),
                doc_id,
                {
                    **doc,
@@ -5242,3 +5249,54 @@ def test_checkpoint_recovery(request: pytest.FixtureRequest, checkpointer_name:
    # Verify the error was recorded in checkpoint
    failed_checkpoint = next(c for c in history if c.tasks and c.tasks[0].error)
    assert "RuntimeError('Simulated failure')" in failed_checkpoint.tasks[0].error
 def test_multiple_updates_root() -> None:
    def node_a(state):
        return [Command(update="a1"), Command(update="a2")]
    def node_b(state):
        return "b"
    graph = (
        StateGraph(Annotated[str, operator.add])
        .add_sequence([node_a, node_b])
        .add_edge(START, "node_a")
        .compile()
    )
    assert graph.invoke("") == "a1a2b"
    # only streams the last update from node_a
    assert [c for c in graph.stream("", stream_mode="updates")] == [
        {"node_a": ["a1", "a2"]},
        {"node_b": "b"},
    ]
 def test_multiple_updates() -> None:
    class State(TypedDict):
        foo: Annotated[str, operator.add]
    def node_a(state):
        return [Command(update={"foo": "a1"}), Command(update={"foo": "a2"})]
    def node_b(state):
        return {"foo": "b"}
    graph = (
        StateGraph(State)
        .add_sequence([node_a, node_b])
        .add_edge(START, "node_a")
        .compile()
    )
    assert graph.invoke({"foo": ""}) == {
        "foo": "a1a2b",
    }
    # only streams the last update from node_a
    assert [c for c in graph.stream({"foo": ""}, stream_mode="updates")] == [
        {"node_a": [{"foo": "a1"}, {"foo": "a2"}]},
        {"node_b": {"foo": "b"}},
    ]
@@ -19,7 +19,6 @@ from typing import (
    Literal,
    Optional,
    Tuple,
    TypedDict,
    Union,
 )
 from uuid import UUID
@@ -34,6 +33,7 @@ from langchain_core.runnables import (
 from langchain_core.utils.aiter import aclosing
 from pytest_mock import MockerFixture
 from syrupy import SnapshotAssertion
 from typing_extensions import TypedDict
 from langgraph.channels.base import BaseChannel
 from langgraph.channels.binop import BinaryOperatorAggregate
@@ -180,6 +180,262 @@ async def test_checkpoint_errors() -> None:
            pass
 async def test_py_async_with_cancel_behavior() -> None:
    """This test confirms that in all versions of Python we support, __aexit__
    is not cancelled when the coroutine containing the async with block is cancelled."""
    logs: list[str] = []
    class MyContextManager:
        async def __aenter__(self):
            logs.append("Entering")
            return self
        async def __aexit__(self, exc_type, exc_val, exc_tb):
            logs.append("Starting exit")
            try:
                # Simulate some cleanup work
                await asyncio.sleep(2)
                logs.append("Cleanup completed")
            except asyncio.CancelledError:
                logs.append("Cleanup was cancelled!")
                raise
            logs.append("Exit finished")
    async def main():
        try:
            async with MyContextManager():
                logs.append("In context")
                await asyncio.sleep(1)
                logs.append("This won't print if cancelled")
        except asyncio.CancelledError:
            logs.append("Context was cancelled")
            raise
    # create task
    t = asyncio.create_task(main())
    # cancel after 0.2 seconds
    await asyncio.sleep(0.2)
    t.cancel()
    # check logs before cancellation is handled
    assert logs == [
        "Entering",
        "In context",
    ], "Cancelled before cleanup started"
    # wait for task to finish
    try:
        await t
    except asyncio.CancelledError:
        # check logs after cancellation is handled
        assert logs == [
            "Entering",
            "In context",
            "Starting exit",
            "Cleanup completed",
            "Exit finished",
            "Context was cancelled",
        ], "Cleanup started and finished after cancellation"
    else:
        assert False, "Task should be cancelled"
 async def test_checkpoint_put_after_cancellation() -> None:
    logs: list[str] = []
    class LongPutCheckpointer(MemorySaver):
        async def aput(
            self,
            config: RunnableConfig,
            checkpoint: Checkpoint,
            metadata: CheckpointMetadata,
            new_versions: ChannelVersions,
        ) -> RunnableConfig:
            logs.append("checkpoint.aput.start")
            try:
                await asyncio.sleep(1)
                return await super().aput(config, checkpoint, metadata, new_versions)
            finally:
                logs.append("checkpoint.aput.end")
    inner_task_cancelled = False
    async def awhile(input: Any) -> None:
        logs.append("awhile.start")
        try:
            await asyncio.sleep(1)
        except asyncio.CancelledError:
            nonlocal inner_task_cancelled
            inner_task_cancelled = True
            raise
        finally:
            logs.append("awhile.end")
    builder = Graph()
    builder.add_node("agent", awhile)
    builder.set_entry_point("agent")
    builder.set_finish_point("agent")
    graph = builder.compile(checkpointer=LongPutCheckpointer())
    thread1 = {"configurable": {"thread_id": "1"}}
    # start the task
    t = asyncio.create_task(graph.ainvoke(1, thread1))
    # cancel after 0.2 seconds
    await asyncio.sleep(0.2)
    t.cancel()
    # check logs before cancellation is handled
    assert sorted(logs) == [
        "awhile.start",
        "checkpoint.aput.start",
    ], "Cancelled before checkpoint put started"
    # wait for task to finish
    try:
        await t
    except asyncio.CancelledError:
        # check logs after cancellation is handled
        assert sorted(logs) == [
            "awhile.end",
            "awhile.start",
            "checkpoint.aput.end",
            "checkpoint.aput.start",
        ], "Checkpoint put is not cancelled"
    else:
        assert False, "Task should be cancelled"
 async def test_checkpoint_put_after_cancellation_stream_anext() -> None:
    logs: list[str] = []
    class LongPutCheckpointer(MemorySaver):
        async def aput(
            self,
            config: RunnableConfig,
            checkpoint: Checkpoint,
            metadata: CheckpointMetadata,
            new_versions: ChannelVersions,
        ) -> RunnableConfig:
            logs.append("checkpoint.aput.start")
            try:
                await asyncio.sleep(1)
                return await super().aput(config, checkpoint, metadata, new_versions)
            finally:
                logs.append("checkpoint.aput.end")
    inner_task_cancelled = False
    async def awhile(input: Any) -> None:
        logs.append("awhile.start")
        try:
            await asyncio.sleep(1)
        except asyncio.CancelledError:
            nonlocal inner_task_cancelled
            inner_task_cancelled = True
            raise
        finally:
            logs.append("awhile.end")
    builder = Graph()
    builder.add_node("agent", awhile)
    builder.set_entry_point("agent")
    builder.set_finish_point("agent")
    graph = builder.compile(checkpointer=LongPutCheckpointer())
    thread1 = {"configurable": {"thread_id": "1"}}
    # start the task
    s = graph.astream(1, thread1)
    t = asyncio.create_task(s.__anext__())
    # cancel after 0.2 seconds
    await asyncio.sleep(0.2)
    t.cancel()
    # check logs before cancellation is handled
    assert sorted(logs) == [
        "awhile.start",
        "checkpoint.aput.start",
    ], "Cancelled before checkpoint put started"
    # wait for task to finish
    try:
        await t
    except asyncio.CancelledError:
        # check logs after cancellation is handled
        assert sorted(logs) == [
            "awhile.end",
            "awhile.start",
            "checkpoint.aput.end",
            "checkpoint.aput.start",
        ], "Checkpoint put is not cancelled"
    else:
        assert False, "Task should be cancelled"
 async def test_checkpoint_put_after_cancellation_stream_events_anext() -> None:
    logs: list[str] = []
    class LongPutCheckpointer(MemorySaver):
        async def aput(
            self,
            config: RunnableConfig,
            checkpoint: Checkpoint,
            metadata: CheckpointMetadata,
            new_versions: ChannelVersions,
        ) -> RunnableConfig:
            logs.append("checkpoint.aput.start")
            try:
                await asyncio.sleep(1)
                return await super().aput(config, checkpoint, metadata, new_versions)
            finally:
                logs.append("checkpoint.aput.end")
    inner_task_cancelled = False
    async def awhile(input: Any) -> None:
        logs.append("awhile.start")
        try:
            await asyncio.sleep(1)
        except asyncio.CancelledError:
            nonlocal inner_task_cancelled
            inner_task_cancelled = True
            raise
        finally:
            logs.append("awhile.end")
    builder = Graph()
    builder.add_node("agent", awhile)
    builder.set_entry_point("agent")
    builder.set_finish_point("agent")
    graph = builder.compile(checkpointer=LongPutCheckpointer())
    thread1 = {"configurable": {"thread_id": "1"}}
    # start the task
    s = graph.astream_events(1, thread1, version="v2", include_names=["LangGraph"])
    # skip first event (happens right away)
    await s.__anext__()
    # start the task for 2nd event
    t = asyncio.create_task(s.__anext__())
    # cancel after 0.2 seconds
    await asyncio.sleep(0.2)
    t.cancel()
    # check logs before cancellation is handled
    assert logs == [
        "checkpoint.aput.start",
        "awhile.start",
    ], "Cancelled before checkpoint put started"
    # wait for task to finish
    try:
        await t
    except asyncio.CancelledError:
        # check logs after cancellation is handled
        assert logs == [
            "checkpoint.aput.start",
            "awhile.start",
            "awhile.end",
            "checkpoint.aput.end",
        ], "Checkpoint put is not cancelled"
    else:
        assert False, "Task should be cancelled"
 async def test_node_cancellation_on_external_cancel() -> None:
    inner_task_cancelled = False
@@ -2315,9 +2571,9 @@ async def test_imp_sync_from_async(checkpointer_name: str) -> None:
        def foo(state: dict) -> dict:
            return {"a": state["a"] + "foo", "b": "bar"}
-        @task()
+        @task
-        def bar(state: dict) -> dict:
+        def bar(a: str, b: str, c: Optional[str] = None) -> dict:
-            return {"a": state["a"] + state["b"], "c": "bark"}
+            return {"a": a + b, "c": (c or "") + "bark"}
        @task()
        def baz(state: dict) -> dict:
@@ -2325,8 +2581,8 @@ async def test_imp_sync_from_async(checkpointer_name: str) -> None:
        @entrypoint(checkpointer=checkpointer)
        def graph(state: dict) -> dict:
-            fut_foo = foo(state)
+            foo_result = foo(state).result()
-            fut_bar = bar(fut_foo.result())
+            fut_bar = bar(foo_result["a"], foo_result["b"])
            fut_baz = baz(fut_bar.result())
            return fut_baz.result()
@@ -2351,9 +2607,9 @@ async def test_imp_stream_order(checkpointer_name: str) -> None:
        async def foo(state: dict) -> dict:
            return {"a": state["a"] + "foo", "b": "bar"}
-        @task()
+        @task
-        async def bar(state: dict) -> dict:
+        async def bar(a: str, b: str, c: Optional[str] = None) -> dict:
-            return {"a": state["a"] + state["b"], "c": "bark"}
+            return {"a": a + b, "c": (c or "") + "bark"}
        @task()
        async def baz(state: dict) -> dict:
@@ -2361,8 +2617,9 @@ async def test_imp_stream_order(checkpointer_name: str) -> None:
        @entrypoint(checkpointer=checkpointer)
        async def graph(state: dict) -> dict:
-            fut_foo = foo(state)
+            foo_res = await foo(state)
-            fut_bar = bar(await fut_foo)
+
            fut_bar = bar(foo_res["a"], foo_res["b"])
            fut_baz = baz(await fut_bar)
            return await fut_baz
@@ -6362,3 +6619,54 @@ async def test_checkpoint_recovery_async(checkpointer_name: str):
        # Verify the error was recorded in checkpoint
        failed_checkpoint = next(c for c in history if c.tasks and c.tasks[0].error)
        assert "RuntimeError('Simulated failure')" in failed_checkpoint.tasks[0].error
 async def test_multiple_updates_root() -> None:
    def node_a(state):
        return [Command(update="a1"), Command(update="a2")]
    def node_b(state):
        return "b"
    graph = (
        StateGraph(Annotated[str, operator.add])
        .add_sequence([node_a, node_b])
        .add_edge(START, "node_a")
        .compile()
    )
    assert await graph.ainvoke("") == "a1a2b"
    # only streams the last update from node_a
    assert [c async for c in graph.astream("", stream_mode="updates")] == [
        {"node_a": ["a1", "a2"]},
        {"node_b": "b"},
    ]
 async def test_multiple_updates() -> None:
    class State(TypedDict):
        foo: Annotated[str, operator.add]
    def node_a(state):
        return [Command(update={"foo": "a1"}), Command(update={"foo": "a2"})]
    def node_b(state):
        return {"foo": "b"}
    graph = (
        StateGraph(State)
        .add_sequence([node_a, node_b])
        .add_edge(START, "node_a")
        .compile()
    )
    assert await graph.ainvoke({"foo": ""}) == {
        "foo": "a1a2b",
    }
    # only streams the last update from node_a
    assert [c async for c in graph.astream({"foo": ""}, stream_mode="updates")] == [
        {"node_a": [{"foo": "a1"}, {"foo": "a2"}]},
        {"node_b": {"foo": "b"}},
    ]
@@ -1,13 +1,14 @@
 import json
 import sys
 import time
-from typing import Any, Callable, Tuple, TypedDict, TypeVar
+from typing import Any, Callable, Tuple, TypeVar
 from unittest.mock import MagicMock
 import langsmith as ls
 import pytest
 from langchain_core.runnables import RunnableConfig
 from langchain_core.tracers import LangChainTracer
 from typing_extensions import TypedDict
 from langgraph.graph import StateGraph
@@ -9,7 +9,6 @@ from typing import (
    List,
    Literal,
    Optional,
    TypedDict,
    TypeVar,
    Union,
 )
@@ -17,7 +16,7 @@ from unittest.mock import patch
 import langsmith
 import pytest
-from typing_extensions import Annotated, NotRequired, Required
+from typing_extensions import Annotated, NotRequired, Required, TypedDict
 from langgraph.graph import END, StateGraph
 from langgraph.graph.graph import CompiledGraph
@@ -1,6 +1,6 @@
 {
  "name": "@langchain/langgraph-sdk",
-  "version": "0.0.32",
+  "version": "0.0.34",
  "description": "Client library for interacting with the LangGraph API",
  "type": "module",
  "packageManager": "yarn@1.22.19",
@@ -817,6 +817,8 @@ export class RunsClient extends BaseClient {
      command: payload?.command,
      config: payload?.config,
      metadata: payload?.metadata,
      stream_mode: payload?.streamMode,
      stream_subgraphs: payload?.streamSubgraphs,
      assistant_id: assistantId,
      interrupt_before: payload?.interruptBefore,
      interrupt_after: payload?.interruptAfter,
@@ -1,5 +1,15 @@
 import { Checkpoint, Config, Metadata } from "./schema.js";
 /**
 * Stream modes
 * - "values": Stream only the state values.
 * - "messages": Stream complete messages.
 * - "messages-tuple": Stream (message chunk, metadata) tuples.
 * - "updates": Stream updates to the state.
 * - "events": Stream events occurring during execution.
 * - "debug": Stream detailed debug information.
 * - "custom": Stream custom events.
 */
 export type StreamMode =
  | "values"
  | "messages"
@@ -32,7 +42,7 @@ export interface Command {
  /**
   * An object to update the thread state with.
   */
-  update?: Record<string, unknown>;
+  update?: Record<string, unknown> | [string, unknown][];
  /**
   * The value to return from an `interrupt` function call.
@@ -140,13 +150,7 @@ interface RunsInvokePayload {
 export interface RunsStreamPayload extends RunsInvokePayload {
  /**
-   * One of `"values"`, `"messages"`, `"updates"` or `"events"`.
+   * One of `"values"`, `"messages"`, `"messages-tuple"`, `"updates"`, `"events"`, `"debug"`, `"custom"`.
   * - `"values"`: Stream the thread state any time it changes.
   * - `"messages"`: Stream chat messages from thread state and calls to chat models,
   *                 token-by-token where possible.
   * - `"updates"`: Stream the state updates returned by each node.
   * - `"events"`: Stream all events produced by the run. You can also access these
   *               afterwards using the `client.runs.listEvents()` method.
   */
  streamMode?: StreamMode | Array<StreamMode>;
@@ -162,7 +166,17 @@ export interface RunsStreamPayload extends RunsInvokePayload {
  feedbackKeys?: string[];
 }
-export interface RunsCreatePayload extends RunsInvokePayload {}
+export interface RunsCreatePayload extends RunsInvokePayload {
  /**
   * One of `"values"`, `"messages"`, `"messages-tuple"`, `"updates"`, `"events"`, `"debug"`, `"custom"`.
   */
  streamMode?: StreamMode | Array<StreamMode>;
  /**
   * Stream output from subgraphs. By default, streams only the top graph.
   */
  streamSubgraphs?: boolean;
 }
 export interface CronsCreatePayload extends RunsCreatePayload {
  /**
@@ -461,6 +461,73 @@ class _CronsOn(
    Search = types.CronsSearch
 class _StoreOn:
    def __init__(self, auth: Auth) -> None:
        self._auth = auth
    @typing.overload
    def __call__(
        self,
        *,
        actions: typing.Optional[
            typing.Union[
                typing.Literal["put", "get", "search", "list_namespaces", "delete"],
                Sequence[
                    typing.Literal["put", "get", "search", "list_namespaces", "delete"]
                ],
            ]
        ] = None,
    ) -> Callable[[AHO], AHO]: ...
    @typing.overload
    def __call__(self, fn: AHO) -> AHO: ...
    def __call__(
        self,
        fn: typing.Optional[AHO] = None,
        *,
        actions: typing.Optional[
            typing.Union[
                typing.Literal["put", "get", "search", "list_namespaces", "delete"],
                Sequence[
                    typing.Literal["put", "get", "search", "list_namespaces", "delete"]
                ],
            ]
        ] = None,
    ) -> typing.Union[AHO, Callable[[AHO], AHO]]:
        """Register a handler for specific resources and actions.
        Can be used as a decorator or with explicit resource/action parameters:
        @auth.on.store
        async def handler(): ... # Handle all store ops
        @auth.on.store(actions=("put", "get", "search", "delete"))
        async def handler(): ... # Handle specific store ops
        @auth.on.store.put
        async def handler(): ... # Handle store.put ops
        """
        if fn is not None:
            # Used as a plain decorator
            _register_handler(self._auth, "store", None, fn)
            return fn
        # Used with parameters, return a decorator
        def decorator(
            handler: AHO,
        ) -> AHO:
            if isinstance(actions, str):
                action_list = [actions]
            else:
                action_list = list(actions) if actions is not None else ["*"]
            for action in action_list:
                _register_handler(self._auth, "store", action, handler)
            return handler
        return decorator
 AHO = typing.TypeVar("AHO", bound=_ActionHandler[dict[str, typing.Any]])
@@ -524,6 +591,7 @@ class _On:
        "threads",
        "runs",
        "crons",
        "store",
        "value",
    )
@@ -532,6 +600,7 @@ class _On:
        self.assistants = _AssistantsOn(auth, "assistants")
        self.threads = _ThreadsOn(auth, "threads")
        self.crons = _CronsOn(auth, "crons")
        self.store = _StoreOn(auth)
        self.value = dict[str, typing.Any]
    @typing.overload
@@ -5,7 +5,7 @@ request handling in LangGraph. It includes user protocols, authentication contex
 and typed dictionaries for various API operations.
 Note:
-    All typing.TypedDict classes use total=False to make all fields optional by default.
+    All typing.TypedDict classes use total=False to make all fields typing.Optional by default.
 """
 import functools
@@ -157,7 +157,7 @@ class MinimalUserDict(typing.TypedDict, total=False):
    identity: typing_extensions.Required[str]
    """The required unique identifier for the user."""
    display_name: str
-    """The optional display name for the user."""
+    """The typing.Optional display name for the user."""
    is_authenticated: bool
    """Whether the user is authenticated. Defaults to True."""
    permissions: Sequence[str]
@@ -358,11 +358,34 @@ class AuthContext(BaseAuthContext):
    allowing for fine-grained access control decisions.
    """
-    resource: typing.Literal["runs", "threads", "crons", "assistants"]
+    resource: typing.Literal["runs", "threads", "crons", "assistants", "store"]
    """The resource being accessed."""
-    action: typing.Literal["create", "read", "update", "delete", "search", "create_run"]
+    action: typing.Literal[
-    """The action being performed on the resource."""
+        "create",
        "read",
        "update",
        "delete",
        "search",
        "create_run",
        "put",
        "get",
        "list_namespaces",
    ]
    """The action being performed on the resource.
    Most resources support the following actions:
    - create: Create a new resource
    - read: Read information about a resource
    - update: Update an existing resource
    - delete: Delete a resource
    - search: Search for resources
    The store supports the following actions:
    - put: Add or update a document in the store
    - get: Get a document from the store
    - list_namespaces: List the namespaces in the store
    """
 class ThreadsCreate(typing.TypedDict, total=False):
@@ -759,6 +782,84 @@ class CronsSearch(typing.TypedDict, total=False):
    """Offset for pagination."""
 class StoreGet(typing.TypedDict):
    """Operation to retrieve a specific item by its namespace and key."""
    namespace: tuple[str, ...]
    """Hierarchical path that uniquely identifies the item's location."""
    key: str
    """Unique identifier for the item within its specific namespace."""
 class StoreSearch(typing.TypedDict):
    """Operation to search for items within a specified namespace hierarchy."""
    namespace: tuple[str, ...]
    """Prefix filter for defining the search scope."""
    filter: typing.Optional[dict[str, typing.Any]]
    """Key-value pairs for filtering results based on exact matches or comparison operators."""
    limit: int
    """Maximum number of items to return in the search results."""
    offset: int
    """Number of matching items to skip for pagination."""
    query: typing.Optional[str]
    """Naturalj language search query for semantic search capabilities."""
 class StoreListNamespaces(typing.TypedDict):
    """Operation to list and filter namespaces in the store."""
    namespace: typing.Optional[tuple[str, ...]]
    """Prefix filter namespaces."""
    suffix: typing.Optional[tuple[str, ...]]
    """Optional conditions for filtering namespaces."""
    max_depth: typing.Optional[int]
    """Maximum depth of namespace hierarchy to return.
    Note:
        Namespaces deeper than this level will be truncated.
    """
    limit: int
    """Maximum number of namespaces to return."""
    offset: int
    """Number of namespaces to skip for pagination."""
 class StorePut(typing.TypedDict):
    """Operation to store, update, or delete an item in the store."""
    namespace: tuple[str, ...]
    """Hierarchical path that identifies the location of the item."""
    key: str
    """Unique identifier for the item within its namespace."""
    value: typing.Optional[dict[str, typing.Any]]
    """The data to store, or None to mark the item for deletion."""
    index: typing.Optional[typing.Union[typing.Literal[False], list[str]]]
    """Optional index configuration for full-text search."""
 class StoreDelete(typing.TypedDict):
    """Operation to delete an item from the store."""
    namespace: tuple[str, ...]
    """Hierarchical path that uniquely identifies the item's location."""
    key: str
    """Unique identifier for the item within its specific namespace."""
 class on:
    """Namespace for type definitions of different API operations.
@@ -894,6 +995,38 @@ class on:
            value = CronsSearch
    class store:
        """Types for store-related operations."""
        value = typing.Union[
            StoreGet, StoreSearch, StoreListNamespaces, StorePut, StoreDelete
        ]
        class put:
            """Type for store put parameters."""
            value = StorePut
        class get:
            """Type for store get parameters."""
            value = StoreGet
        class search:
            """Type for store search parameters."""
            value = StoreSearch
        class delete:
            """Type for store delete parameters."""
            value = StoreDelete
        class list_namespaces:
            """Type for store list namespaces parameters."""
            value = StoreListNamespaces
 __all__ = [
    "on",
@@ -909,4 +1042,9 @@ __all__ = [
    "AssistantsUpdate",
    "AssistantsDelete",
    "AssistantsSearch",
    "StoreGet",
    "StoreSearch",
    "StoreListNamespaces",
    "StorePut",
    "StoreDelete",
 ]
@@ -1779,7 +1779,7 @@ class RunsClient:
        Args:
            thread_id: The thread ID to cancel.
-            run_id: The run ID to cancek.
+            run_id: The run ID to cancel.
            wait: Whether to wait until run has completed.
            action: Action to take when cancelling the run. Possible values
                are `interrupt` or `rollback`. Default is `interrupt`.
@@ -3917,7 +3917,7 @@ class SyncRunsClient:
        Args:
            thread_id: The thread ID to cancel.
-            run_id: The run ID to cancek.
+            run_id: The run ID to cancel.
            wait: Whether to wait until run has completed.
            action: Action to take when cancelling the run. Possible values
                are `interrupt` or `rollback`. Default is `interrupt`.
@@ -1,7 +1,17 @@
 """Data models for interacting with the LangGraph API."""
 from datetime import datetime
-from typing import Any, Dict, Literal, NamedTuple, Optional, Sequence, TypedDict, Union
+from typing import (
    Any,
    Dict,
    Literal,
    NamedTuple,
    Optional,
    Sequence,
    Tuple,
    TypedDict,
    Union,
 )
 Json = Optional[dict[str, Any]]
 """Represents a JSON-like structure, which can be None or a dictionary with string keys and any values."""
@@ -374,5 +384,5 @@ class Send(TypedDict):
 class Command(TypedDict, total=False):
    goto: Union[Send, str, Sequence[Union[Send, str]]]
-    update: dict[str, Any]
+    update: Union[dict[str, Any], Sequence[Tuple[str, Any]]]
    resume: Any
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langgraph-sdk"
-version = "0.1.48"
+version = "0.1.51"
 description = "SDK for interacting with LangGraph API"
 authors = []
 license = "MIT"
@@ -2251,13 +2251,13 @@ testing = ["Django", "attrs", "colorama", "docopt", "pytest (<7.0.0)"]
 [[package]]
 name = "jinja2"
-version = "3.1.4"
+version = "3.1.5"
 description = "A very fast and expressive template engine."
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "jinja2-3.1.4-py3-none-any.whl", hash = "sha256:bc5dd2abb727a5319567b7a813e6a2e7318c39f4f487cfe6c89c6f9c7d25197d"},
+    {file = "jinja2-3.1.5-py3-none-any.whl", hash = "sha256:aba0f4dc9ed8013c424088f68a5c226f7d6097ed89b246d7749c2ec4175c6adb"},
-    {file = "jinja2-3.1.4.tar.gz", hash = "sha256:4a3aee7acbbe7303aede8e9648d13b8bf88a429282aa6122a993f0ac800cb369"},
+    {file = "jinja2-3.1.5.tar.gz", hash = "sha256:8fefff8dc3034e27bb80d67c671eb8a9bc424c0ef4c0826edbff304cceff43bb"},
 ]
 [package.dependencies]
@@ -2862,21 +2862,21 @@ adal = ["adal (>=1.0.2)"]
 [[package]]
 name = "langchain"
-version = "0.3.9"
+version = "0.3.14"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "langchain-0.3.9-py3-none-any.whl", hash = "sha256:ade5a1fee2f94f2e976a6c387f97d62cc7f0b9f26cfe0132a41d2bda761e1045"},
+    {file = "langchain-0.3.14-py3-none-any.whl", hash = "sha256:5df9031702f7fe6c956e84256b4639a46d5d03a75be1ca4c1bc9479b358061a2"},
-    {file = "langchain-0.3.9.tar.gz", hash = "sha256:4950c4ad627d0aa95ce6bda7de453e22059b7e7836b562a8f781fb0b05d7294c"},
+    {file = "langchain-0.3.14.tar.gz", hash = "sha256:4a5ae817b5832fa0e1fcadc5353fbf74bebd2f8e550294d4dc039f651ddcd3d1"},
 ]
 [package.dependencies]
 aiohttp = ">=3.8.3,<4.0.0"
 async-timeout = {version = ">=4.0.0,<5.0.0", markers = "python_version < \"3.11\""}
-langchain-core = ">=0.3.21,<0.4.0"
+langchain-core = ">=0.3.29,<0.4.0"
-langchain-text-splitters = ">=0.3.0,<0.4.0"
+langchain-text-splitters = ">=0.3.3,<0.4.0"
-langsmith = ">=0.1.17,<0.2.0"
+langsmith = ">=0.1.17,<0.3"
 numpy = [
    {version = ">=1.22.4,<2", markers = "python_version < \"3.12\""},
    {version = ">=1.26.2,<3", markers = "python_version >= \"3.12\""},
@@ -2906,45 +2906,46 @@ pydantic = ">=2.7.4,<3.0.0"
 [[package]]
 name = "langchain-community"
-version = "0.3.1"
+version = "0.3.14"
 description = "Community contributed LangChain integrations."
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "langchain_community-0.3.1-py3-none-any.whl", hash = "sha256:627eb26c16417764762ac47dd0d3005109f750f40242a88bb8f2958b798bcf90"},
+    {file = "langchain_community-0.3.14-py3-none-any.whl", hash = "sha256:cc02a0abad0551edef3e565dff643386a5b2ee45b933b6d883d4a935b9649f3c"},
-    {file = "langchain_community-0.3.1.tar.gz", hash = "sha256:c964a70628f266a61647e58f2f0434db633d4287a729f100a81dd8b0654aec93"},
+    {file = "langchain_community-0.3.14.tar.gz", hash = "sha256:d8ba0fe2dbb5795bff707684b712baa5ee379227194610af415ccdfdefda0479"},
 ]
 [package.dependencies]
 aiohttp = ">=3.8.3,<4.0.0"
 dataclasses-json = ">=0.5.7,<0.7"
-langchain = ">=0.3.1,<0.4.0"
+httpx-sse = ">=0.4.0,<0.5.0"
-langchain-core = ">=0.3.6,<0.4.0"
+langchain = ">=0.3.14,<0.4.0"
-langsmith = ">=0.1.125,<0.2.0"
+langchain-core = ">=0.3.29,<0.4.0"
 langsmith = ">=0.1.125,<0.3"
 numpy = [
-    {version = ">=1,<2", markers = "python_version < \"3.12\""},
+    {version = ">=1.22.4,<2", markers = "python_version < \"3.12\""},
-    {version = ">=1.26.0,<2.0.0", markers = "python_version >= \"3.12\""},
+    {version = ">=1.26.2,<3", markers = "python_version >= \"3.12\""},
 ]
 pydantic-settings = ">=2.4.0,<3.0.0"
 PyYAML = ">=5.3"
 requests = ">=2,<3"
 SQLAlchemy = ">=1.4,<3"
-tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
+tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10"
 [[package]]
 name = "langchain-core"
-version = "0.3.23"
+version = "0.3.29"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "langchain_core-0.3.23-py3-none-any.whl", hash = "sha256:550c0b996990830fa6515a71a1192a8a0343367999afc36d4ede14222941e420"},
+    {file = "langchain_core-0.3.29-py3-none-any.whl", hash = "sha256:817db1474871611a81105594a3e4d11704949661008e455a10e38ca9ff601a1a"},
-    {file = "langchain_core-0.3.23.tar.gz", hash = "sha256:f9e175e3b82063cc3b160c2ca2b155832e1c6f915312e1204828f97d4aabf6e1"},
+    {file = "langchain_core-0.3.29.tar.gz", hash = "sha256:773d6aeeb612e7ce3d996c0be403433d8c6a91e77bbb7a7461c13e15cfbe5b06"},
 ]
 [package.dependencies]
 jsonpatch = ">=1.33,<2.0"
-langsmith = ">=0.1.125,<0.2.0"
+langsmith = ">=0.1.125,<0.3"
 packaging = ">=23.2,<25"
 pydantic = [
    {version = ">=2.5.2,<3.0.0", markers = "python_full_version < \"3.12.4\""},
@@ -3021,21 +3022,21 @@ tiktoken = ">=0.7,<1"
 [[package]]
 name = "langchain-text-splitters"
-version = "0.3.0"
+version = "0.3.5"
 description = "LangChain text splitting utilities"
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "langchain_text_splitters-0.3.0-py3-none-any.whl", hash = "sha256:e84243e45eaff16e5b776cd9c81b6d07c55c010ebcb1965deb3d1792b7358e83"},
+    {file = "langchain_text_splitters-0.3.5-py3-none-any.whl", hash = "sha256:8c9b059827438c5fa8f327b4df857e307828a5ec815163c9b5c9569a3e82c8ee"},
-    {file = "langchain_text_splitters-0.3.0.tar.gz", hash = "sha256:f9fe0b4d244db1d6de211e7343d4abc4aa90295aa22e1f0c89e51f33c55cd7ce"},
+    {file = "langchain_text_splitters-0.3.5.tar.gz", hash = "sha256:11cb7ca3694e5bdd342bc16d3875b7f7381651d4a53cbb91d34f22412ae16443"},
 ]
 [package.dependencies]
-langchain-core = ">=0.3.0,<0.4.0"
+langchain-core = ">=0.3.29,<0.4.0"
 [[package]]
 name = "langgraph"
-version = "0.2.59"
+version = "0.2.61"
 description = "Building stateful, multi-actor applications with LLMs"
 optional = false
 python-versions = ">=3.9.0,<4.0"
@@ -3053,7 +3054,7 @@ url = "libs/langgraph"
 [[package]]
 name = "langgraph-checkpoint"
-version = "2.0.8"
+version = "2.0.9"
 description = "Library with base interfaces for LangGraph checkpoint savers."
 optional = false
 python-versions = "^3.9.0,<4.0"
@@ -3087,7 +3088,7 @@ pymongo = ">=4.9.0,<4.10.0"
 [[package]]
 name = "langgraph-checkpoint-postgres"
-version = "2.0.8"
+version = "2.0.9"
 description = "Library with a Postgres implementation of LangGraph checkpoint saver."
 optional = false
 python-versions = "^3.9.0,<4.0"
@@ -3123,7 +3124,7 @@ url = "libs/checkpoint-sqlite"
 [[package]]
 name = "langgraph-sdk"
-version = "0.1.43"
+version = "0.1.49"
 description = "SDK for interacting with LangGraph API"
 optional = false
 python-versions = "^3.9.0,<4.0"
@@ -3140,23 +3141,28 @@ url = "libs/sdk-py"
 [[package]]
 name = "langsmith"
-version = "0.1.129"
+version = "0.2.10"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
-python-versions = "<4.0,>=3.8.1"
+python-versions = "<4.0,>=3.9"
 files = [
-    {file = "langsmith-0.1.129-py3-none-any.whl", hash = "sha256:31393fbbb17d6be5b99b9b22d530450094fab23c6c37281a6a6efb2143d05347"},
+    {file = "langsmith-0.2.10-py3-none-any.whl", hash = "sha256:b02f2f174189ff72e54c88b1aa63343defd6f0f676c396a690c63a4b6495dcc2"},
-    {file = "langsmith-0.1.129.tar.gz", hash = "sha256:6c3ba66471bef41b9f87da247cc0b493268b3f54656f73648a256a205261b6a0"},
+    {file = "langsmith-0.2.10.tar.gz", hash = "sha256:153c7b3ccbd823528ff5bec84801e7e50a164e388919fc583252df5b27dd7830"},
 ]
 [package.dependencies]
 httpx = ">=0.23.0,<1"
-orjson = ">=3.9.14,<4.0.0"
+orjson = {version = ">=3.9.14,<4.0.0", markers = "platform_python_implementation != \"PyPy\""}
 pydantic = [
    {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""},
    {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
 ]
 requests = ">=2,<3"
 requests-toolbelt = ">=1.0.0,<2.0.0"
 [package.extras]
 compression = ["zstandard (>=0.23.0,<0.24.0)"]
 langsmith-pyo3 = ["langsmith-pyo3 (>=0.1.0rc2,<0.2.0)"]
 [[package]]
 name = "loguru"
@@ -5965,6 +5971,20 @@ requests = ">=2.0.0"
 [package.extras]
 rsa = ["oauthlib[signedtoken] (>=3.0.0)"]
 [[package]]
 name = "requests-toolbelt"
 version = "1.0.0"
 description = "A utility belt for advanced users of python-requests"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
    {file = "requests-toolbelt-1.0.0.tar.gz", hash = "sha256:7681a0a3d047012b5bdc0ee37d7f8f07ebe76ab08caeccfc3921ce23c88d5bc6"},
    {file = "requests_toolbelt-1.0.0-py2.py3-none-any.whl", hash = "sha256:cccfdd665f0a24fcf4726e690f65639d272bb0637b9b92dfd91a5568ccf6bd06"},
 ]
 [package.dependencies]
 requests = ">=2.0.1,<3.0.0"
 [[package]]
 name = "rfc3339-validator"
 version = "0.1.4"
@@ -7485,4 +7505,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "367f5fb480a8fa5d8ab1c0964a1e9450dbb28e6998097e7536966e7a5fe30c90"
+content-hash = "981f40de9c31530b17537a089651f9e51901b945fbc01b43ac33a466c8a7d9eb"
@@ -42,7 +42,7 @@ langchain-fireworks = "^0.2.0"
 langchain-community = "^0.3.0"
 langchain-experimental = "^0.3.2"
 langgraph-checkpoint-mongodb = "^0.1.0"
-langsmith = "^0.1.129"
+langsmith = "^0.2.0"
 chromadb = "^0.5.5"
 gpt4all = "^2.8.2"
 scikit-learn = "^1.5.2"