prebuilt: release 0.1.2 (#3708)

- Now tests a model with inherited fields

.github/workflows/ci.yml

@@ -114,6 +114,42 @@ jobs:
       - name: Run check_sdk_methods script
         run: python .github/scripts/check_sdk_methods.py
 
+  check-schema:
+    needs: changes
+    if: needs.changes.outputs.python == 'true'
+    name: "Check CLI schema hasn't changed #${{ matrix.python-version }}"
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version:
+          - "3.11"
+    steps:
+      - uses: actions/checkout@v4
+      - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
+        with:
+          python-version: "3.11"
+          poetry-version: ${{ env.POETRY_VERSION }}
+          cache-key: schema-check-cli
+      - name: Install CLI dependencies
+        run: |
+          cd libs/cli
+          poetry install
+      - name: Generate schema and check for changes
+        run: |
+          cd libs/cli
+          # Create a temporary copy of the current schema
+          cp schemas/schema.json schemas/schema.current.json
+          # Generate new schema
+          poetry run python generate_schema.py
+          # Compare the new schema with the original
+          if ! diff -q schemas/schema.json schemas/schema.current.json > /dev/null; then
+            echo "Error: Langgraph.json configuration schema has changed. Please run 'poetry run python generate_schema.py' in the libs/cli directory and commit the changes."
+            diff schemas/schema.json schemas/schema.current.json
+            exit 1
+          fi
+          echo "Schema check passed - no changes detected"
+
   integration-test:
     needs: changes
     if: needs.changes.outputs.python == 'true'
@@ -180,6 +216,8 @@ jobs:
         test,
         test-langgraph,
         test-scheduler-kafka,
+        check-sdk-methods,
+        check-schema,
         integration-test,
         test-js,
       ]

docs/_scripts/third_party_page/packages.yml

@@ -23,4 +23,10 @@ packages:
     description: "Build swarm-style multi-agent systems using LangGraph."
   - name: "delve-taxonomy-generator"
     repo: "andrestorres123/delve"
-    description: "A taxonomy generator for unstructured data"
+    description: "A taxonomy generator for unstructured data"
+  - name: "nodeology"
+    repo: "xyin-anl/Nodeology"
+    description: "Enable researcher to build scientific workflows easily with simplified interface."
+  - name: "langgraph-bigtool"
+    repo: "langchain-ai/langgraph-bigtool"
+    description: "Build LangGraph agents with large numbers of tools."

docs/docs/cloud/deployment/semantic_search.md

@@ -17,7 +17,7 @@ This guide explains how to add semantic search to your LangGraph deployment's cr
     ...
     "store": {
         "index": {
-            "embed": "openai:text-embeddings-3-small",
+            "embed": "openai:text-embedding-3-small",
             "dims": 1536,
             "fields": ["$"]
         }
@@ -27,7 +27,7 @@ This guide explains how to add semantic search to your LangGraph deployment's cr
 
 This configuration:
 
-- Uses OpenAI's text-embeddings-3-small model for generating embeddings
+- Uses OpenAI's text-embedding-3-small model for generating embeddings
 - Sets the embedding dimension to 1536 (matching the model's output)
 - Indexes all fields in your stored data (`["$"]` means index everything, or specify specific fields like `["text", "metadata.title"]`)
 

libs/checkpoint/langgraph/checkpoint/serde/jsonplus.py

@@ -487,7 +487,12 @@ def _msgpack_ext_hook(code: int, data: bytes) -> Any:
             except Exception:
                 return cls.construct(**tup[2])
         except Exception:
-            return
+            # for pydantic objects we can't find/reconstruct
+            # let's return the kwargs dict instead
+            try:
+                return tup[2]
+            except NameError:
+                return
     elif code == EXT_PYDANTIC_V2:
         try:
             tup = msgpack.unpackb(
@@ -500,7 +505,12 @@ def _msgpack_ext_hook(code: int, data: bytes) -> Any:
             except Exception:
                 return cls.model_construct(**tup[2])
         except Exception:
-            return
+            # for pydantic objects we can't find/reconstruct
+            # let's return the kwargs dict instead
+            try:
+                return tup[2]
+            except NameError:
+                return
 
 
 def _msgpack_enc(data: Any) -> bytes:

libs/cli/generate_schema.py

@@ -0,0 +1,226 @@
+#!/usr/bin/env python3
+"""
+Script to generate a JSON schema for the langgraph-cli Config class.
+
+This script creates a schema.json file that can be referenced in langgraph.json files
+to provide IDE autocompletion and validation.
+"""
+
+import inspect
+import json
+import textwrap
+from pathlib import Path
+
+import msgspec
+
+from langgraph_cli.config import (
+    AuthConfig,
+    Config,
+    CorsConfig,
+    HttpConfig,
+    IndexConfig,
+    SecurityConfig,
+    StoreConfig,
+)
+
+
+def add_descriptions_to_schema(schema, cls):
+    """Add docstring descriptions to the schema properties."""
+    if schema.get("description"):
+        schema["description"] = inspect.cleandoc(schema["description"])
+    elif class_doc := inspect.getdoc(cls):
+        schema["description"] = inspect.cleandoc(class_doc)
+    # Get attribute docstrings from the class
+    attr_docs = {}
+
+    # Also check class annotations for docstrings
+    source_lines = inspect.getsourcelines(cls)[0]
+    current_attr = None
+    docstring_lines = []
+
+    for line in source_lines:
+        line = line.strip()
+
+        # Check for attribute definition (TypedDict style)
+        if ":" in line and not line.startswith("#") and not line.startswith('"""'):
+            parts = line.split(":", 1)
+            if len(parts) == 2 and parts[0].strip().isidentifier():
+                # If we were collecting a docstring, save it for the previous attribute
+                if current_attr and docstring_lines:
+                    attr_docs[current_attr] = "\n".join(docstring_lines).strip('"')
+                    docstring_lines = []
+
+                current_attr = parts[0].strip()
+
+        # Check for docstring after attribute
+        elif line.startswith('"""') and current_attr:
+            # Start or end of a docstring
+            if len(line) > 3 and line.endswith('"""'):
+                # Single line docstring
+                attr_docs[current_attr] = line.strip('"')
+                current_attr = None
+            elif docstring_lines:
+                # End of multi-line docstring
+                docstring_lines.append(line.rstrip('"'))
+                attr_docs[current_attr] = "\n".join(docstring_lines).strip('"')
+                docstring_lines = []
+                current_attr = None
+            else:
+                # Start of multi-line docstring
+                docstring_lines.append(line.lstrip('"'))
+
+        # Continue multi-line docstring
+        elif docstring_lines and current_attr:
+            docstring_lines.append(line.strip('"'))
+
+    # Add the last docstring if there is one
+    if current_attr and docstring_lines:
+        attr_docs[current_attr] = "\n".join(docstring_lines).strip('"')
+
+    # Add descriptions to properties
+    if "properties" in schema:
+        for prop_name, prop_schema in schema["properties"].items():
+            # First try to get from attribute docstrings
+            if prop_name in attr_docs and "description" not in prop_schema:
+                prop_schema["description"] = textwrap.dedent(attr_docs[prop_name])
+            # Fall back to class docstring parsing
+            elif class_doc:
+                for line in class_doc.split("\n"):
+                    if line.strip().startswith(
+                        f"{prop_name}:"
+                    ) or line.strip().startswith(f'"{prop_name}"'):
+                        description = line.split(":", 1)[1].strip()
+                        if description and "description" not in prop_schema:
+                            prop_schema["description"] = description
+                            break
+
+    # Recursively process nested definitions
+    if "$defs" in schema:
+        for def_name, def_schema in schema["$defs"].items():
+            # Find the class that corresponds to this definition
+            for potential_cls in [
+                Config,
+                StoreConfig,
+                IndexConfig,
+                AuthConfig,
+                SecurityConfig,
+                HttpConfig,
+                CorsConfig,
+            ]:
+                if potential_cls.__name__ == def_name:
+                    add_descriptions_to_schema(def_schema, potential_cls)
+                    break
+
+    return schema
+
+
+def generate_schema():
+    """Generate a JSON schema for the Config class using msgspec."""
+    # Generate the basic schema
+    schema = msgspec.json.schema(Config)
+
+    # Add title and description
+    schema["title"] = "LangGraph CLI Configuration"
+    schema["description"] = "Configuration schema for langgraph-cli"
+
+    # Add docstring descriptions
+    schema = add_descriptions_to_schema(schema, Config)
+
+    # Add constraint that only one of python_version or node_version should be specified
+    config_schema = schema["$defs"]["Config"]
+
+    # Create two subschemas: one with python_version and one with node_version
+    # Define properties specific to Python projects
+    python_specific_props = ["python_version", "pip_config_file"]
+    # Define properties specific to Node.js projects
+    node_specific_props = ["node_version"]
+    # Define properties common to both project types
+    common_props = [
+        k
+        for k in config_schema["properties"]
+        if k not in python_specific_props and k not in node_specific_props
+    ]
+
+    # Create Python schema with python_version and pip_config_file
+    python_schema = {
+        "type": "object",
+        "properties": {
+            # Include Python-specific properties
+            **{k: config_schema["properties"][k].copy() for k in python_specific_props},
+            # Include common properties
+            **{k: config_schema["properties"][k].copy() for k in common_props},
+        },
+        "required": ["dependencies", "graphs"],
+    }
+
+    # Add enum constraint for python_version
+    if "python_version" in python_schema["properties"]:
+        python_schema["properties"]["python_version"]["enum"] = ["3.11", "3.12"]
+
+    # Create Node.js schema with node_version
+    node_schema = {
+        "type": "object",
+        "properties": {
+            # Include Node-specific properties
+            **{k: config_schema["properties"][k].copy() for k in node_specific_props},
+            # Include common properties
+            **{k: config_schema["properties"][k].copy() for k in common_props},
+        },
+        "required": ["node_version", "graphs"],
+    }
+
+    # Add enum constraint for node_version
+    if "node_version" in node_schema["properties"]:
+        node_schema["properties"]["node_version"]["anyOf"] = [
+            {"type": "string", "enum": ["20"]},
+            {"type": "null"},
+        ]
+
+    # Replace the Config schema with a oneOf constraint
+    config_schema["oneOf"] = [python_schema, node_schema]
+
+    # Remove the properties field as it's now defined in the oneOf subschemas
+    if "properties" in config_schema:
+        del config_schema["properties"]
+
+    return schema
+
+
+def main():
+    """Generate the schema and write it to a file."""
+    schema = generate_schema()
+
+    # Add versioning to the schema
+    import importlib.metadata
+
+    try:
+        version = importlib.metadata.version("langgraph_cli").split(".")
+        schema_version = f"v{version[0]}"
+    except importlib.metadata.PackageNotFoundError:
+        schema_version = "v1"
+
+    # Add version to schema
+    schema["version"] = schema_version
+
+    config_dir = Path(__file__).parent / "schemas"
+
+    # Create versioned schema file
+    versioned_path = config_dir / f"schema.{schema_version}.json"
+    with open(versioned_path, "w") as f:
+        json.dump(schema, f, indent=2)
+
+    # Also create a latest version
+    latest_path = config_dir / "schema.json"
+    with open(latest_path, "w") as f:
+        json.dump(schema, f, indent=2)
+
+    print(f"Schema written to {versioned_path} and {latest_path}")
+    print(
+        f"You can now add '$schema: https://raw.githubusercontent.com/langchain-ai/langgraph/refs/heads/main/libs/cli/schemas/schema.json'"
+        f" or '$schema: https://raw.githubusercontent.com/langchain-ai/langgraph/refs/heads/main/libs/cli/schemas/schema.{schema_version}.json'"
+        " to your langgraph.json files"
+    )
+
+
+if __name__ == "__main__":
+    main()

libs/cli/langgraph_cli/config.py

@@ -3,7 +3,7 @@ import os
 import pathlib
 import textwrap
 from collections import Counter
-from typing import NamedTuple, Optional, TypedDict, Union
+from typing import Any, NamedTuple, Optional, TypedDict, Union
 
 import click
 
@@ -12,12 +12,18 @@ MIN_PYTHON_VERSION = "3.11"
 
 
 class IndexConfig(TypedDict, total=False):
-    """Configuration for indexing documents for semantic search in the store."""
+    """Configuration for indexing documents for semantic search in the store.
+
+    This governs how text is converted into embeddings and stored for vector-based lookups.
+    """
 
     dims: int
-    """Number of dimensions in the embedding vectors.
+    """Required. Dimensionality of the embedding vectors you will store.
     
-    Common embedding models have the following dimensions:
+    Must match the output dimension of your selected embedding model or custom embed function.
+    If mismatched, you will likely encounter shape/size errors when inserting or querying vectors.
+    
+    Common embedding model output dimensions:
         - openai:text-embedding-3-large: 3072
         - openai:text-embedding-3-small: 1536
         - openai:text-embedding-ada-002: 1536
@@ -28,42 +34,123 @@ class IndexConfig(TypedDict, total=False):
     """
 
     embed: str
-    """Optional model (string) to generate embeddings from text or path to model or function.
+    """Required. Identifier or reference to the embedding model or a custom embedding function.
     
-    Examples:
+    The format can vary:
+      - "<provider>:<model_name>" for recognized providers (e.g., "openai:text-embedding-3-large")
+      - "path/to/module.py:function_name" for your own local embedding function
+      - "my_custom_embed" if it's a known alias in your system
+
+     Examples:
         - "openai:text-embedding-3-large"
         - "cohere:embed-multilingual-v3.0"
-        - "src/app.py:embeddings
+        - "src/app.py:embeddings"
+    
+    Note: Must return embeddings of dimension `dims`.
     """
 
     fields: Optional[list[str]]
-    """Fields to extract text from for embedding generation.
+    """Optional. List of JSON fields to extract before generating embeddings.
     
-    Defaults to the root ["$"], which embeds the json object as a whole.
+    Defaults to ["$"], which means the entire JSON object is embedded as one piece of text.
+    If you provide multiple fields (e.g. ["title", "content"]), each is extracted and embedded separately,
+    often saving token usage if you only care about certain parts of the data.
+    
+    Example:
+        fields=["title", "abstract", "author.biography"]
     """
 
 
 class StoreConfig(TypedDict, total=False):
-    embed: Optional[IndexConfig]
-    """Configuration for vector embeddings in store."""
+    """Configuration for the built-in long-term memory store.
+
+    This store can optionally perform semantic search. If you omit `index`,
+    the store will just handle traditional (non-embedded) data without vector lookups.
+    """
+
+    index: Optional[IndexConfig]
+    """Optional. Defines the vector-based semantic search configuration.
+    
+    If provided, the store will:
+      - Generate embeddings according to `index.embed`
+      - Enforce the embedding dimension given by `index.dims`
+      - Embed only specified JSON fields (if any) from `index.fields`
+    
+    If omitted, no vector index is initialized.
+    """
 
 
 class SecurityConfig(TypedDict, total=False):
-    securitySchemes: dict
-    security: list
+    """Configuration for OpenAPI security definitions and requirements.
+
+    Useful for specifying global or path-level authentication and authorization flows
+    (e.g., OAuth2, API key headers, etc.).
+    """
+
+    securitySchemes: dict[str, dict[str, Any]]
+    """Required. Dict describing each security scheme recognized by your OpenAPI spec.
+    
+    Keys are scheme names (e.g. "OAuth2", "ApiKeyAuth") and values are their definitions.
+    Example:
+        {
+            "OAuth2": {
+                "type": "oauth2",
+                "flows": {
+                    "password": {
+                        "tokenUrl": "/token",
+                        "scopes": {"read": "Read data", "write": "Write data"}
+                    }
+                }
+            }
+        }
+    """
+    security: list[dict[str, list[str]]]
+    """Optional. Global security requirements across all endpoints.
+    
+    Each element in the list maps a security scheme (e.g. "OAuth2") to a list of scopes (e.g. ["read", "write"]).
+    Example:
+        [
+            {"OAuth2": ["read", "write"]},
+            {"ApiKeyAuth": []}
+        ]
+    """
     # path => {method => security}
-    paths: dict[str, dict[str, list]]
+    paths: dict[str, dict[str, list[dict[str, list[str]]]]]
+    """Optional. Path-specific security overrides.
+    
+    Keys are path templates (e.g., "/items/{item_id}"), mapping to:
+      - Keys that are HTTP methods (e.g., "GET", "POST"),
+      - Values are lists of security definitions (just like `security`) for that method.
+    
+    Example:
+        {
+            "/private_data": {
+                "GET": [{"OAuth2": ["read"]}],
+                "POST": [{"OAuth2": ["write"]}]
+            }
+        }
+    """
 
 
 class AuthConfig(TypedDict, total=False):
-    path: str
-    """Path to the authentication function in a Python file."""
-    disable_studio_auth: bool
-    """Whether to disable auth when connecting from the LangSmith Studio."""
-    openapi: SecurityConfig
-    """The schema to use for updating the openapi spec.
+    """Configuration for custom authentication logic and how it integrates into the OpenAPI spec."""
 
-    Example:
+    path: str
+    """Required. Path to an instance of the Auth() class that implements custom authentication.
+    
+    Format: "path/to/file.py:my_auth"
+    """
+    disable_studio_auth: bool
+    """Optional. Whether to disable LangSmith API-key authentication for requests originating the Studio. 
+    
+    Defaults to False, meaning that if a particular header is set, the server will verify the `x-api-key` header
+    value is a valid API key for the deployment's workspace. If True, all requests will go through your custom
+    authentication logic, regardless of origin of the request.
+    """
+    openapi: SecurityConfig
+    """Required. Detailed security configuration that merges into your deployment's OpenAPI spec.
+    
+    Example (OAuth2):
         {
             "securitySchemes": {
                 "OAuth2": {
@@ -71,88 +158,181 @@ class AuthConfig(TypedDict, total=False):
                     "flows": {
                         "password": {
                             "tokenUrl": "/token",
-                            "scopes": {
-                                "me": "Read information about the current user",
-                                "items": "Access to create and manage items"
-                            }
+                            "scopes": {"me": "Read user info", "items": "Manage items"}
                         }
                     }
                 }
             },
             "security": [
-                {"OAuth2": ["me"]}  # Default security requirement for all endpoints
+                {"OAuth2": ["me"]}
             ]
         }
     """
 
 
 class CorsConfig(TypedDict, total=False):
+    """Specifies Cross-Origin Resource Sharing (CORS) rules for your server.
+
+    If omitted, defaults are typically very restrictive (often no cross-origin requests).
+    Configure carefully if you want to allow usage from browsers hosted on other domains.
+    """
+
     allow_origins: list[str]
+    """Optional. List of allowed origins (e.g., "https://example.com").
+    
+    Default is often an empty list (no external origins). 
+    Use "*" only if you trust all origins, as that bypasses most restrictions.
+    """
     allow_methods: list[str]
+    """Optional. HTTP methods permitted for cross-origin requests (e.g. ["GET", "POST"]).
+    
+    Default might be ["GET", "POST", "OPTIONS"] depending on your server framework.
+    """
     allow_headers: list[str]
+    """Optional. HTTP headers that can be used in cross-origin requests (e.g. ["Content-Type", "Authorization"])."""
     allow_credentials: bool
+    """Optional. If True, cross-origin requests can include credentials (cookies, auth headers).
+    
+    Default False to avoid accidentally exposing secured endpoints to untrusted sites.
+    """
     allow_origin_regex: str
+    """Optional. A regex pattern for matching allowed origins, used if you have dynamic subdomains.
+    
+    Example: "^https://.*\.mycompany\.com$"
+    """
     expose_headers: list[str]
+    """Optional. List of headers that browsers are allowed to read from the response in cross-origin contexts."""
     max_age: int
+    """Optional. How many seconds the browser may cache preflight responses.
+    
+    Default might be 600 (10 minutes). Larger values reduce preflight requests but can cause stale configurations.
+    """
 
 
 class HttpConfig(TypedDict, total=False):
+    """Configuration for the built-in HTTP server that powers your deployment's routes and endpoints."""
+
     app: str
-    """Import path for a custom Starlette/FastAPI app to mount"""
+    """Optional. Import path to a custom Starlette/FastAPI application to mount.
+    
+    Format: "path/to/module.py:app_var"
+    If provided, it can override or extend the default routes.
+    """
     disable_assistants: bool
-    """Disable /assistants routes"""
+    """Optional. If True, /assistants routes are removed from the server.
+    
+    Default is False (meaning /assistants is enabled).
+    """
     disable_threads: bool
-    """Disable /threads routes"""
+    """Optional. If True, /threads routes are removed.
+    
+    Default is False.
+    """
     disable_runs: bool
-    """Disable /runs routes"""
+    """Optional. If True, /runs routes are removed.
+    
+    Default is False.
+    """
     disable_store: bool
-    """Disable /store routes"""
+    """Optional. If True, /store routes are removed, disabling direct store interactions via HTTP.
+    
+    Default is False.
+    """
     disable_meta: bool
-    """Disable /ok, /info, /metrics, and /docs routes"""
+    """Optional. If True, all meta endpoints (/ok, /info, /metrics, /docs) are disabled.
+    
+    Default is False.
+    """
     cors: Optional[CorsConfig]
-    """Cross-Origin Resource Sharing (CORS) configuration"""
+    """Optional. Defines CORS restrictions. If omitted, no special rules are set and 
+    cross-origin behavior depends on default server settings.
+    """
 
 
 class Config(TypedDict, total=False):
-    """Configuration for langgraph-cli."""
+    """Top-level config for langgraph-cli or similar deployment tooling."""
 
     python_version: str
-    """Python version to use."""
+    """Optional. Python version in 'major.minor' format (e.g. '3.11'). 
+    Must be at least 3.11 or greater for this deployment to function properly.
+    """
 
     node_version: Optional[str]
-    """Node.js version to use."""
+    """Optional. Node.js version as a major version (e.g. '20'), if your deployment needs Node.
+    Must be >= 20 if provided.
+    """
 
     pip_config_file: Optional[str]
-    """Path to a pip configuration file."""
+    """Optional. Path to a pip config file (e.g., "/etc/pip.conf" or "pip.ini") for controlling
+    package installation (custom indices, credentials, etc.).
+    
+    Only relevant if Python dependencies are installed via pip. If omitted, default pip settings are used.
+    """
 
     dockerfile_lines: list[str]
-    """Additional lines to add to the Dockerfile."""
+    """Optional. Additional Docker instructions that will be appended to your base Dockerfile.
+    
+    Useful for installing OS packages, setting environment variables, etc. 
+    Example:
+        dockerfile_lines=[
+            "RUN apt-get update && apt-get install -y libmagic-dev",
+            "ENV MY_CUSTOM_VAR=hello_world"
+        ]
+    """
 
     dependencies: list[str]
-    """Additional Python dependencies to install."""
+    """List of Python dependencies to install, either from PyPI or local paths.
+    
+    Examples:
+      - "." or "./src" if you have a local Python package
+      - str (aka "anthropic") for a PyPI package
+      - "git+https://github.com/org/repo.git@main" for a Git-based package
+    Defaults to an empty list, meaning no additional packages installed beyond your base environment.
+    """
 
     graphs: dict[str, str]
-    """Mapping of graph names to their definitions."""
+    """Optional. Named definitions of graphs, each pointing to a Python object.
+
+    
+    Graphs can be StateGraph, @entrypoint, or any other Pregel object OR they can point to (async) context
+    managers that accept a single configuration argument (of type RunnableConfig) and return a pregel object
+    (instance of Stategraph, etc.).
+    
+    Keys are graph names, values are "path/to/file.py:object_name".
+    Example:
+        {
+            "mygraph": "graphs/my_graph.py:graph_definition",
+            "anothergraph": "graphs/another.py:get_graph"
+        }
+    """
 
     env: Union[dict[str, str], str]
-    """Environment variables to set.
-
-    If a dictionary is provided, the keys are environment variable names
-    and the values are the corresponding environment variable values.
-
-    If a string is provided, it is interpreted as a path to a file containing
-    environment variables in the format KEY=VALUE, with one environment variable
-    per line.
+    """Optional. Environment variables to set for your deployment.
+    
+    - If given as a dict, keys are variable names and values are their values.
+    - If given as a string, it must be a path to a file containing lines in KEY=VALUE format.
+    
+    Example as a dict:
+        env={"API_TOKEN": "abc123", "DEBUG": "true"}
+    Example as a file path:
+        env=".env"
     """
 
     store: Optional[StoreConfig]
-    """Configuration for vector embeddings in store."""
+    """Optional. Configuration for the built-in long-term memory store, including semantic search indexing.
+    
+    If omitted, no vector index is set up (the object store will still be present, however).
+    """
 
     auth: Optional[AuthConfig]
-    """Configuration for authentication."""
+    """Optional. Custom authentication config, including the path to your Python auth logic and 
+    the OpenAPI security definitions it uses.
+    """
 
     http: Optional[HttpConfig]
-    """Configuration for HTTP server."""
+    """Optional. Configuration for the built-in HTTP server, controlling which custom routes are exposed
+    and how cross-origin requests are handled.
+    """
 
 
 def _parse_version(version_str: str) -> tuple[int, int]:
@@ -687,9 +867,11 @@ def python_config_to_docker(
     pip_pkgs_str = f"RUN {pip_install} {' '.join(pypi_deps)}" if pypi_deps else ""
     if local_deps.pip_reqs:
         pip_reqs_str = os.linesep.join(
-            f"COPY --from=__outer_{reqpath.name} requirements.txt {destpath}"
-            if reqpath.parent in local_deps.additional_contexts
-            else f"ADD {reqpath.relative_to(config_path.parent)} {destpath}"
+            (
+                f"COPY --from=__outer_{reqpath.name} requirements.txt {destpath}"
+                if reqpath.parent in local_deps.additional_contexts
+                else f"ADD {reqpath.relative_to(config_path.parent)} {destpath}"
+            )
             for reqpath, destpath in local_deps.pip_reqs
         )
         pip_reqs_str += f'{os.linesep}RUN {pip_install} {" ".join("-r " + r for _,r in local_deps.pip_reqs)}'
@@ -724,13 +906,15 @@ RUN set -ex && \\
     )
 
     local_pkgs_str = os.linesep.join(
-        f"""# -- Adding local package {relpath} --
+        (
+            f"""# -- Adding local package {relpath} --
 COPY --from={name} . /deps/{name}
 # -- End of local package {relpath} --"""
-        if fullpath in local_deps.additional_contexts
-        else f"""# -- Adding local package {relpath} --
+            if fullpath in local_deps.additional_contexts
+            else f"""# -- Adding local package {relpath} --
 ADD {relpath} /deps/{name}
 # -- End of local package {relpath} --"""
+        )
         for fullpath, (relpath, name) in local_deps.real_pkgs.items()
     )
 

libs/cli/poetry.lock

@@ -707,6 +707,58 @@ files = [
     {file = "msgpack-1.1.0.tar.gz", hash = "sha256:dd432ccc2c72b914e4cb77afce64aab761c1137cc698be3984eee260bcb2896e"},
 ]
 
+[[package]]
+name = "msgspec"
+version = "0.19.0"
+description = "A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML."
+optional = false
+python-versions = ">=3.9"
+files = [
+    {file = "msgspec-0.19.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d8dd848ee7ca7c8153462557655570156c2be94e79acec3561cf379581343259"},
+    {file = "msgspec-0.19.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:0553bbc77662e5708fe66aa75e7bd3e4b0f209709c48b299afd791d711a93c36"},
+    {file = "msgspec-0.19.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:fe2c4bf29bf4e89790b3117470dea2c20b59932772483082c468b990d45fb947"},
+    {file = "msgspec-0.19.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:00e87ecfa9795ee5214861eab8326b0e75475c2e68a384002aa135ea2a27d909"},
+    {file = "msgspec-0.19.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:3c4ec642689da44618f68c90855a10edbc6ac3ff7c1d94395446c65a776e712a"},
+    {file = "msgspec-0.19.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:2719647625320b60e2d8af06b35f5b12d4f4d281db30a15a1df22adb2295f633"},
+    {file = "msgspec-0.19.0-cp310-cp310-win_amd64.whl", hash = "sha256:695b832d0091edd86eeb535cd39e45f3919f48d997685f7ac31acb15e0a2ed90"},
+    {file = "msgspec-0.19.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:aa77046904db764b0462036bc63ef71f02b75b8f72e9c9dd4c447d6da1ed8f8e"},
+    {file = "msgspec-0.19.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:047cfa8675eb3bad68722cfe95c60e7afabf84d1bd8938979dd2b92e9e4a9551"},
+    {file = "msgspec-0.19.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e78f46ff39a427e10b4a61614a2777ad69559cc8d603a7c05681f5a595ea98f7"},
+    {file = "msgspec-0.19.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6c7adf191e4bd3be0e9231c3b6dc20cf1199ada2af523885efc2ed218eafd011"},
+    {file = "msgspec-0.19.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:f04cad4385e20be7c7176bb8ae3dca54a08e9756cfc97bcdb4f18560c3042063"},
+    {file = "msgspec-0.19.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:45c8fb410670b3b7eb884d44a75589377c341ec1392b778311acdbfa55187716"},
+    {file = "msgspec-0.19.0-cp311-cp311-win_amd64.whl", hash = "sha256:70eaef4934b87193a27d802534dc466778ad8d536e296ae2f9334e182ac27b6c"},
+    {file = "msgspec-0.19.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:f98bd8962ad549c27d63845b50af3f53ec468b6318400c9f1adfe8b092d7b62f"},
+    {file = "msgspec-0.19.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:43bbb237feab761b815ed9df43b266114203f53596f9b6e6f00ebd79d178cdf2"},
+    {file = "msgspec-0.19.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4cfc033c02c3e0aec52b71710d7f84cb3ca5eb407ab2ad23d75631153fdb1f12"},
+    {file = "msgspec-0.19.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d911c442571605e17658ca2b416fd8579c5050ac9adc5e00c2cb3126c97f73bc"},
+    {file = "msgspec-0.19.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:757b501fa57e24896cf40a831442b19a864f56d253679f34f260dcb002524a6c"},
+    {file = "msgspec-0.19.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:5f0f65f29b45e2816d8bded36e6b837a4bf5fb60ec4bc3c625fa2c6da4124537"},
+    {file = "msgspec-0.19.0-cp312-cp312-win_amd64.whl", hash = "sha256:067f0de1c33cfa0b6a8206562efdf6be5985b988b53dd244a8e06f993f27c8c0"},
+    {file = "msgspec-0.19.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:f12d30dd6266557aaaf0aa0f9580a9a8fbeadfa83699c487713e355ec5f0bd86"},
+    {file = "msgspec-0.19.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:82b2c42c1b9ebc89e822e7e13bbe9d17ede0c23c187469fdd9505afd5a481314"},
+    {file = "msgspec-0.19.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:19746b50be214a54239aab822964f2ac81e38b0055cca94808359d779338c10e"},
+    {file = "msgspec-0.19.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:60ef4bdb0ec8e4ad62e5a1f95230c08efb1f64f32e6e8dd2ced685bcc73858b5"},
+    {file = "msgspec-0.19.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:ac7f7c377c122b649f7545810c6cd1b47586e3aa3059126ce3516ac7ccc6a6a9"},
+    {file = "msgspec-0.19.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:a5bc1472223a643f5ffb5bf46ccdede7f9795078194f14edd69e3aab7020d327"},
+    {file = "msgspec-0.19.0-cp313-cp313-win_amd64.whl", hash = "sha256:317050bc0f7739cb30d257ff09152ca309bf5a369854bbf1e57dffc310c1f20f"},
+    {file = "msgspec-0.19.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:15c1e86fff77184c20a2932cd9742bf33fe23125fa3fcf332df9ad2f7d483044"},
+    {file = "msgspec-0.19.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:3b5541b2b3294e5ffabe31a09d604e23a88533ace36ac288fa32a420aa38d229"},
+    {file = "msgspec-0.19.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0f5c043ace7962ef188746e83b99faaa9e3e699ab857ca3f367b309c8e2c6b12"},
+    {file = "msgspec-0.19.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ca06aa08e39bf57e39a258e1996474f84d0dd8130d486c00bec26d797b8c5446"},
+    {file = "msgspec-0.19.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:e695dad6897896e9384cf5e2687d9ae9feaef50e802f93602d35458e20d1fb19"},
+    {file = "msgspec-0.19.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:3be5c02e1fee57b54130316a08fe40cca53af92999a302a6054cd451700ea7db"},
+    {file = "msgspec-0.19.0-cp39-cp39-win_amd64.whl", hash = "sha256:0684573a821be3c749912acf5848cce78af4298345cb2d7a8b8948a0a5a27cfe"},
+    {file = "msgspec-0.19.0.tar.gz", hash = "sha256:604037e7cd475345848116e89c553aa9a233259733ab51986ac924ab1b976f8e"},
+]
+
+[package.extras]
+dev = ["attrs", "coverage", "eval-type-backport", "furo", "ipython", "msgpack", "mypy", "pre-commit", "pyright", "pytest", "pyyaml", "sphinx", "sphinx-copybutton", "sphinx-design", "tomli", "tomli_w"]
+doc = ["furo", "ipython", "sphinx", "sphinx-copybutton", "sphinx-design"]
+test = ["attrs", "eval-type-backport", "msgpack", "pytest", "pyyaml", "tomli", "tomli_w"]
+toml = ["tomli", "tomli_w"]
+yaml = ["pyyaml"]
+
 [[package]]
 name = "mypy"
 version = "1.15.0"
@@ -1665,4 +1717,4 @@ inmem = ["langgraph-api", "python-dotenv"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.9.0,<4.0"
-content-hash = "04a0b0e203ae00f30cca7e454c632be0b41cbb4820d0c05315a346d514b5f98e"
+content-hash = "d0e2bdcb600ad031867413025fcc58bb162609209359d63ca99a77060cf8cbb4"

libs/cli/pyproject.toml

@@ -25,6 +25,7 @@ pytest-asyncio = "^0.21.1"
 pytest-mock = "^3.11.1"
 pytest-watch = "^4.2.0"
 mypy = "^1.10.0"
+msgspec = "^0.19.0"
 
 [tool.poetry.extras]
 inmem = ["langgraph-api", "python-dotenv"]

libs/cli/schemas/schema.json

@@ -0,0 +1,410 @@
+{
+  "$ref": "#/$defs/Config",
+  "$defs": {
+    "Config": {
+      "title": "Config",
+      "description": "Top-level config for langgraph-cli or similar deployment tooling.",
+      "type": "object",
+      "required": [],
+      "oneOf": [
+        {
+          "type": "object",
+          "properties": {
+            "python_version": {
+              "type": "string",
+              "description": "Optional. Python version in 'major.minor' format (e.g. '3.11').\nMust be at least 3.11 or greater for this deployment to function properly.\n",
+              "enum": [
+                "3.11",
+                "3.12"
+              ]
+            },
+            "pip_config_file": {
+              "anyOf": [
+                {
+                  "type": "string"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Path to a pip config file (e.g., \"/etc/pip.conf\" or \"pip.ini\") for controlling\npackage installation (custom indices, credentials, etc.).\n\nOnly relevant if Python dependencies are installed via pip. If omitted, default pip settings are used.\n"
+            },
+            "auth": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/AuthConfig"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Custom authentication config, including the path to your Python auth logic and\nthe OpenAPI security definitions it uses.\n"
+            },
+            "dependencies": {
+              "type": "array",
+              "items": {
+                "type": "string"
+              },
+              "description": "List of Python dependencies to install, either from PyPI or local paths.\n"
+            },
+            "dockerfile_lines": {
+              "type": "array",
+              "items": {
+                "type": "string"
+              },
+              "description": "Optional. Additional Docker instructions that will be appended to your base Dockerfile.\n\nUseful for installing OS packages, setting environment variables, etc."
+            },
+            "env": {
+              "anyOf": [
+                {
+                  "type": "object",
+                  "additionalProperties": {
+                    "type": "string"
+                  }
+                },
+                {
+                  "type": "string"
+                }
+              ],
+              "description": "Optional. Environment variables to set for your deployment.\n\n- If given as a dict, keys are variable names and values are their values.\n- If given as a string, it must be a path to a file containing lines in KEY=VALUE format.\n\nenv=\".env\n"
+            },
+            "graphs": {
+              "type": "object",
+              "additionalProperties": {
+                "type": "string"
+              },
+              "description": "Optional. Named definitions of graphs, each pointing to a Python object.\n\n\nGraphs can be StateGraph, @entrypoint, or any other Pregel object OR they can point to (async) context\nmanagers that accept a single configuration argument (of type RunnableConfig) and return a pregel object\n(instance of Stategraph, etc.).\n"
+            },
+            "http": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/HttpConfig"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Configuration for the built-in HTTP server, controlling which custom routes are exposed\nand how cross-origin requests are handled.\n"
+            },
+            "store": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/StoreConfig"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Configuration for the built-in long-term memory store, including semantic search indexing.\n\nIf omitted, no vector index is set up (the object store will still be present, however).\n"
+            }
+          },
+          "required": [
+            "dependencies",
+            "graphs"
+          ]
+        },
+        {
+          "type": "object",
+          "properties": {
+            "node_version": {
+              "anyOf": [
+                {
+                  "type": "string",
+                  "enum": [
+                    "20"
+                  ]
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Node.js version as a major version (e.g. '20'), if your deployment needs Node.\nMust be >= 20 if provided.\n"
+            },
+            "auth": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/AuthConfig"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Custom authentication config, including the path to your Python auth logic and\nthe OpenAPI security definitions it uses.\n"
+            },
+            "dependencies": {
+              "type": "array",
+              "items": {
+                "type": "string"
+              },
+              "description": "List of Python dependencies to install, either from PyPI or local paths.\n"
+            },
+            "dockerfile_lines": {
+              "type": "array",
+              "items": {
+                "type": "string"
+              },
+              "description": "Optional. Additional Docker instructions that will be appended to your base Dockerfile.\n\nUseful for installing OS packages, setting environment variables, etc."
+            },
+            "env": {
+              "anyOf": [
+                {
+                  "type": "object",
+                  "additionalProperties": {
+                    "type": "string"
+                  }
+                },
+                {
+                  "type": "string"
+                }
+              ],
+              "description": "Optional. Environment variables to set for your deployment.\n\n- If given as a dict, keys are variable names and values are their values.\n- If given as a string, it must be a path to a file containing lines in KEY=VALUE format.\n\nenv=\".env\n"
+            },
+            "graphs": {
+              "type": "object",
+              "additionalProperties": {
+                "type": "string"
+              },
+              "description": "Optional. Named definitions of graphs, each pointing to a Python object.\n\n\nGraphs can be StateGraph, @entrypoint, or any other Pregel object OR they can point to (async) context\nmanagers that accept a single configuration argument (of type RunnableConfig) and return a pregel object\n(instance of Stategraph, etc.).\n"
+            },
+            "http": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/HttpConfig"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Configuration for the built-in HTTP server, controlling which custom routes are exposed\nand how cross-origin requests are handled.\n"
+            },
+            "store": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/StoreConfig"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Configuration for the built-in long-term memory store, including semantic search indexing.\n\nIf omitted, no vector index is set up (the object store will still be present, however).\n"
+            }
+          },
+          "required": [
+            "node_version",
+            "graphs"
+          ]
+        }
+      ]
+    },
+    "AuthConfig": {
+      "title": "AuthConfig",
+      "description": "Configuration for custom authentication logic and how it integrates into the OpenAPI spec.",
+      "type": "object",
+      "properties": {
+        "disable_studio_auth": {
+          "type": "boolean",
+          "description": "Optional. Whether to disable LangSmith API-key authentication for requests originating the Studio.\n\nDefaults to False, meaning that if a particular header is set, the server will verify the `x-api-key` header\nvalue is a valid API key for the deployment's workspace. If True, all requests will go through your custom\nauthentication logic, regardless of origin of the request.\n"
+        },
+        "openapi": {
+          "$ref": "#/$defs/SecurityConfig",
+          "description": "Required. Detailed security configuration that merges into your deployment's OpenAPI spec.\n\n{\n}\n}\n}\n},\n]\n}\n"
+        },
+        "path": {
+          "type": "string",
+          "description": "Required. Path to an instance of the Auth() class that implements custom authentication.\n"
+        }
+      },
+      "required": []
+    },
+    "SecurityConfig": {
+      "title": "SecurityConfig",
+      "description": "Configuration for OpenAPI security definitions and requirements.\n\nUseful for specifying global or path-level authentication and authorization flows\n(e.g., OAuth2, API key headers, etc.).",
+      "type": "object",
+      "properties": {
+        "paths": {
+          "type": "object",
+          "additionalProperties": {
+            "type": "object",
+            "additionalProperties": {
+              "type": "array",
+              "items": {
+                "type": "object",
+                "additionalProperties": {
+                  "type": "array",
+                  "items": {
+                    "type": "string"
+                  }
+                }
+              }
+            }
+          },
+          "description": "Optional. Path-specific security overrides.\n\n- Keys that are HTTP methods (e.g., \"GET\", \"POST\"),\n- Values are lists of security definitions (just like `security`) for that method.\n"
+        },
+        "security": {
+          "type": "array",
+          "items": {
+            "type": "object",
+            "additionalProperties": {
+              "type": "array",
+              "items": {
+                "type": "string"
+              }
+            }
+          },
+          "description": "Optional. Global security requirements across all endpoints.\n\nEach element in the list maps a security scheme (e.g. \"OAuth2\") to a list of scopes (e.g. [\"read\", \"write\"])."
+        },
+        "securitySchemes": {
+          "type": "object",
+          "additionalProperties": {
+            "type": "object"
+          },
+          "description": "Required. Dict describing each security scheme recognized by your OpenAPI spec.\n\nKeys are scheme names (e.g. \"OAuth2\", \"ApiKeyAuth\") and values are their definitions."
+        }
+      },
+      "required": []
+    },
+    "HttpConfig": {
+      "title": "HttpConfig",
+      "description": "Configuration for the built-in HTTP server that powers your deployment's routes and endpoints.",
+      "type": "object",
+      "properties": {
+        "app": {
+          "type": "string",
+          "description": "Optional. Import path to a custom Starlette/FastAPI application to mount.\n"
+        },
+        "cors": {
+          "anyOf": [
+            {
+              "$ref": "#/$defs/CorsConfig"
+            },
+            {
+              "type": "null"
+            }
+          ],
+          "description": "Optional. Defines CORS restrictions. If omitted, no special rules are set and\ncross-origin behavior depends on default server settings.\n"
+        },
+        "disable_assistants": {
+          "type": "boolean",
+          "description": "Optional. If True, /assistants routes are removed from the server.\n\nDefault is False (meaning /assistants is enabled).\n"
+        },
+        "disable_meta": {
+          "type": "boolean",
+          "description": "Optional. If True, all meta endpoints (/ok, /info, /metrics, /docs) are disabled.\n\nDefault is False.\n"
+        },
+        "disable_runs": {
+          "type": "boolean",
+          "description": "Optional. If True, /runs routes are removed.\n\nDefault is False.\n"
+        },
+        "disable_store": {
+          "type": "boolean",
+          "description": "Optional. If True, /store routes are removed, disabling direct store interactions via HTTP.\n\nDefault is False.\n"
+        },
+        "disable_threads": {
+          "type": "boolean",
+          "description": "Optional. If True, /threads routes are removed.\n\nDefault is False.\n"
+        }
+      },
+      "required": []
+    },
+    "CorsConfig": {
+      "title": "CorsConfig",
+      "description": "Specifies Cross-Origin Resource Sharing (CORS) rules for your server.\n\nIf omitted, defaults are typically very restrictive (often no cross-origin requests).\nConfigure carefully if you want to allow usage from browsers hosted on other domains.",
+      "type": "object",
+      "properties": {
+        "allow_credentials": {
+          "type": "boolean",
+          "description": "Optional. If True, cross-origin requests can include credentials (cookies, auth headers).\n\nDefault False to avoid accidentally exposing secured endpoints to untrusted sites.\n"
+        },
+        "allow_headers": {
+          "type": "array",
+          "items": {
+            "type": "string"
+          },
+          "description": "Optional. HTTP headers that can be used in cross-origin requests (e.g. [\"Content-Type\", \"Authorization\"])."
+        },
+        "allow_methods": {
+          "type": "array",
+          "items": {
+            "type": "string"
+          },
+          "description": "Optional. HTTP methods permitted for cross-origin requests (e.g. [\"GET\", \"POST\"]).\n\nDefault might be [\"GET\", \"POST\", \"OPTIONS\"] depending on your server framework.\n"
+        },
+        "allow_origin_regex": {
+          "type": "string",
+          "description": "Optional. A regex pattern for matching allowed origins, used if you have dynamic subdomains.\n"
+        },
+        "allow_origins": {
+          "type": "array",
+          "items": {
+            "type": "string"
+          },
+          "description": "Optional. List of allowed origins (e.g., \"https://example.com\").\n\nDefault is often an empty list (no external origins).\nUse \"*\" only if you trust all origins, as that bypasses most restrictions.\n"
+        },
+        "expose_headers": {
+          "type": "array",
+          "items": {
+            "type": "string"
+          },
+          "description": "Optional. List of headers that browsers are allowed to read from the response in cross-origin contexts."
+        },
+        "max_age": {
+          "type": "integer",
+          "description": "Optional. How many seconds the browser may cache preflight responses.\n\nDefault might be 600 (10 minutes). Larger values reduce preflight requests but can cause stale configurations.\n"
+        }
+      },
+      "required": []
+    },
+    "StoreConfig": {
+      "title": "StoreConfig",
+      "description": "Configuration for the built-in long-term memory store.\n\nThis store can optionally perform semantic search. If you omit `index`,\nthe store will just handle traditional (non-embedded) data without vector lookups.",
+      "type": "object",
+      "properties": {
+        "index": {
+          "anyOf": [
+            {
+              "$ref": "#/$defs/IndexConfig"
+            },
+            {
+              "type": "null"
+            }
+          ],
+          "description": "Optional. Defines the vector-based semantic search configuration.\n\n- Generate embeddings according to `index.embed`\n- Enforce the embedding dimension given by `index.dims`\n- Embed only specified JSON fields (if any) from `index.fields`\n\nIf omitted, no vector index is initialized.\n"
+        }
+      },
+      "required": []
+    },
+    "IndexConfig": {
+      "title": "IndexConfig",
+      "description": "Configuration for indexing documents for semantic search in the store.\n\nThis governs how text is converted into embeddings and stored for vector-based lookups.",
+      "type": "object",
+      "properties": {
+        "dims": {
+          "type": "integer",
+          "description": "Required. Dimensionality of the embedding vectors you will store.\n\nMust match the output dimension of your selected embedding model or custom embed function.\nIf mismatched, you will likely encounter shape/size errors when inserting or querying vectors.\n\n"
+        },
+        "embed": {
+          "type": "string",
+          "description": "Required. Identifier or reference to the embedding model or a custom embedding function.\n\n- \"my_custom_embed\" if it's a known alias in your system\n"
+        },
+        "fields": {
+          "anyOf": [
+            {
+              "type": "array",
+              "items": {
+                "type": "string"
+              }
+            },
+            {
+              "type": "null"
+            }
+          ],
+          "description": "Optional. List of JSON fields to extract before generating embeddings.\n\nDefaults to [\"$\"], which means the entire JSON object is embedded as one piece of text.\nIf you provide multiple fields (e.g. [\"title\", \"content\"]), each is extracted and embedded separately,\noften saving token usage if you only care about certain parts of the data.\n"
+        }
+      },
+      "required": []
+    }
+  },
+  "title": "LangGraph CLI Configuration",
+  "description": "Configuration schema for langgraph-cli",
+  "version": "v0"
+}

libs/cli/schemas/schema.v0.json

@@ -0,0 +1,410 @@
+{
+  "$ref": "#/$defs/Config",
+  "$defs": {
+    "Config": {
+      "title": "Config",
+      "description": "Top-level config for langgraph-cli or similar deployment tooling.",
+      "type": "object",
+      "required": [],
+      "oneOf": [
+        {
+          "type": "object",
+          "properties": {
+            "python_version": {
+              "type": "string",
+              "description": "Optional. Python version in 'major.minor' format (e.g. '3.11').\nMust be at least 3.11 or greater for this deployment to function properly.\n",
+              "enum": [
+                "3.11",
+                "3.12"
+              ]
+            },
+            "pip_config_file": {
+              "anyOf": [
+                {
+                  "type": "string"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Path to a pip config file (e.g., \"/etc/pip.conf\" or \"pip.ini\") for controlling\npackage installation (custom indices, credentials, etc.).\n\nOnly relevant if Python dependencies are installed via pip. If omitted, default pip settings are used.\n"
+            },
+            "auth": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/AuthConfig"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Custom authentication config, including the path to your Python auth logic and\nthe OpenAPI security definitions it uses.\n"
+            },
+            "dependencies": {
+              "type": "array",
+              "items": {
+                "type": "string"
+              },
+              "description": "List of Python dependencies to install, either from PyPI or local paths.\n"
+            },
+            "dockerfile_lines": {
+              "type": "array",
+              "items": {
+                "type": "string"
+              },
+              "description": "Optional. Additional Docker instructions that will be appended to your base Dockerfile.\n\nUseful for installing OS packages, setting environment variables, etc."
+            },
+            "env": {
+              "anyOf": [
+                {
+                  "type": "object",
+                  "additionalProperties": {
+                    "type": "string"
+                  }
+                },
+                {
+                  "type": "string"
+                }
+              ],
+              "description": "Optional. Environment variables to set for your deployment.\n\n- If given as a dict, keys are variable names and values are their values.\n- If given as a string, it must be a path to a file containing lines in KEY=VALUE format.\n\nenv=\".env\n"
+            },
+            "graphs": {
+              "type": "object",
+              "additionalProperties": {
+                "type": "string"
+              },
+              "description": "Optional. Named definitions of graphs, each pointing to a Python object.\n\n\nGraphs can be StateGraph, @entrypoint, or any other Pregel object OR they can point to (async) context\nmanagers that accept a single configuration argument (of type RunnableConfig) and return a pregel object\n(instance of Stategraph, etc.).\n"
+            },
+            "http": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/HttpConfig"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Configuration for the built-in HTTP server, controlling which custom routes are exposed\nand how cross-origin requests are handled.\n"
+            },
+            "store": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/StoreConfig"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Configuration for the built-in long-term memory store, including semantic search indexing.\n\nIf omitted, no vector index is set up (the object store will still be present, however).\n"
+            }
+          },
+          "required": [
+            "dependencies",
+            "graphs"
+          ]
+        },
+        {
+          "type": "object",
+          "properties": {
+            "node_version": {
+              "anyOf": [
+                {
+                  "type": "string",
+                  "enum": [
+                    "20"
+                  ]
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Node.js version as a major version (e.g. '20'), if your deployment needs Node.\nMust be >= 20 if provided.\n"
+            },
+            "auth": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/AuthConfig"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Custom authentication config, including the path to your Python auth logic and\nthe OpenAPI security definitions it uses.\n"
+            },
+            "dependencies": {
+              "type": "array",
+              "items": {
+                "type": "string"
+              },
+              "description": "List of Python dependencies to install, either from PyPI or local paths.\n"
+            },
+            "dockerfile_lines": {
+              "type": "array",
+              "items": {
+                "type": "string"
+              },
+              "description": "Optional. Additional Docker instructions that will be appended to your base Dockerfile.\n\nUseful for installing OS packages, setting environment variables, etc."
+            },
+            "env": {
+              "anyOf": [
+                {
+                  "type": "object",
+                  "additionalProperties": {
+                    "type": "string"
+                  }
+                },
+                {
+                  "type": "string"
+                }
+              ],
+              "description": "Optional. Environment variables to set for your deployment.\n\n- If given as a dict, keys are variable names and values are their values.\n- If given as a string, it must be a path to a file containing lines in KEY=VALUE format.\n\nenv=\".env\n"
+            },
+            "graphs": {
+              "type": "object",
+              "additionalProperties": {
+                "type": "string"
+              },
+              "description": "Optional. Named definitions of graphs, each pointing to a Python object.\n\n\nGraphs can be StateGraph, @entrypoint, or any other Pregel object OR they can point to (async) context\nmanagers that accept a single configuration argument (of type RunnableConfig) and return a pregel object\n(instance of Stategraph, etc.).\n"
+            },
+            "http": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/HttpConfig"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Configuration for the built-in HTTP server, controlling which custom routes are exposed\nand how cross-origin requests are handled.\n"
+            },
+            "store": {
+              "anyOf": [
+                {
+                  "$ref": "#/$defs/StoreConfig"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Configuration for the built-in long-term memory store, including semantic search indexing.\n\nIf omitted, no vector index is set up (the object store will still be present, however).\n"
+            }
+          },
+          "required": [
+            "node_version",
+            "graphs"
+          ]
+        }
+      ]
+    },
+    "AuthConfig": {
+      "title": "AuthConfig",
+      "description": "Configuration for custom authentication logic and how it integrates into the OpenAPI spec.",
+      "type": "object",
+      "properties": {
+        "disable_studio_auth": {
+          "type": "boolean",
+          "description": "Optional. Whether to disable LangSmith API-key authentication for requests originating the Studio.\n\nDefaults to False, meaning that if a particular header is set, the server will verify the `x-api-key` header\nvalue is a valid API key for the deployment's workspace. If True, all requests will go through your custom\nauthentication logic, regardless of origin of the request.\n"
+        },
+        "openapi": {
+          "$ref": "#/$defs/SecurityConfig",
+          "description": "Required. Detailed security configuration that merges into your deployment's OpenAPI spec.\n\n{\n}\n}\n}\n},\n]\n}\n"
+        },
+        "path": {
+          "type": "string",
+          "description": "Required. Path to an instance of the Auth() class that implements custom authentication.\n"
+        }
+      },
+      "required": []
+    },
+    "SecurityConfig": {
+      "title": "SecurityConfig",
+      "description": "Configuration for OpenAPI security definitions and requirements.\n\nUseful for specifying global or path-level authentication and authorization flows\n(e.g., OAuth2, API key headers, etc.).",
+      "type": "object",
+      "properties": {
+        "paths": {
+          "type": "object",
+          "additionalProperties": {
+            "type": "object",
+            "additionalProperties": {
+              "type": "array",
+              "items": {
+                "type": "object",
+                "additionalProperties": {
+                  "type": "array",
+                  "items": {
+                    "type": "string"
+                  }
+                }
+              }
+            }
+          },
+          "description": "Optional. Path-specific security overrides.\n\n- Keys that are HTTP methods (e.g., \"GET\", \"POST\"),\n- Values are lists of security definitions (just like `security`) for that method.\n"
+        },
+        "security": {
+          "type": "array",
+          "items": {
+            "type": "object",
+            "additionalProperties": {
+              "type": "array",
+              "items": {
+                "type": "string"
+              }
+            }
+          },
+          "description": "Optional. Global security requirements across all endpoints.\n\nEach element in the list maps a security scheme (e.g. \"OAuth2\") to a list of scopes (e.g. [\"read\", \"write\"])."
+        },
+        "securitySchemes": {
+          "type": "object",
+          "additionalProperties": {
+            "type": "object"
+          },
+          "description": "Required. Dict describing each security scheme recognized by your OpenAPI spec.\n\nKeys are scheme names (e.g. \"OAuth2\", \"ApiKeyAuth\") and values are their definitions."
+        }
+      },
+      "required": []
+    },
+    "HttpConfig": {
+      "title": "HttpConfig",
+      "description": "Configuration for the built-in HTTP server that powers your deployment's routes and endpoints.",
+      "type": "object",
+      "properties": {
+        "app": {
+          "type": "string",
+          "description": "Optional. Import path to a custom Starlette/FastAPI application to mount.\n"
+        },
+        "cors": {
+          "anyOf": [
+            {
+              "$ref": "#/$defs/CorsConfig"
+            },
+            {
+              "type": "null"
+            }
+          ],
+          "description": "Optional. Defines CORS restrictions. If omitted, no special rules are set and\ncross-origin behavior depends on default server settings.\n"
+        },
+        "disable_assistants": {
+          "type": "boolean",
+          "description": "Optional. If True, /assistants routes are removed from the server.\n\nDefault is False (meaning /assistants is enabled).\n"
+        },
+        "disable_meta": {
+          "type": "boolean",
+          "description": "Optional. If True, all meta endpoints (/ok, /info, /metrics, /docs) are disabled.\n\nDefault is False.\n"
+        },
+        "disable_runs": {
+          "type": "boolean",
+          "description": "Optional. If True, /runs routes are removed.\n\nDefault is False.\n"
+        },
+        "disable_store": {
+          "type": "boolean",
+          "description": "Optional. If True, /store routes are removed, disabling direct store interactions via HTTP.\n\nDefault is False.\n"
+        },
+        "disable_threads": {
+          "type": "boolean",
+          "description": "Optional. If True, /threads routes are removed.\n\nDefault is False.\n"
+        }
+      },
+      "required": []
+    },
+    "CorsConfig": {
+      "title": "CorsConfig",
+      "description": "Specifies Cross-Origin Resource Sharing (CORS) rules for your server.\n\nIf omitted, defaults are typically very restrictive (often no cross-origin requests).\nConfigure carefully if you want to allow usage from browsers hosted on other domains.",
+      "type": "object",
+      "properties": {
+        "allow_credentials": {
+          "type": "boolean",
+          "description": "Optional. If True, cross-origin requests can include credentials (cookies, auth headers).\n\nDefault False to avoid accidentally exposing secured endpoints to untrusted sites.\n"
+        },
+        "allow_headers": {
+          "type": "array",
+          "items": {
+            "type": "string"
+          },
+          "description": "Optional. HTTP headers that can be used in cross-origin requests (e.g. [\"Content-Type\", \"Authorization\"])."
+        },
+        "allow_methods": {
+          "type": "array",
+          "items": {
+            "type": "string"
+          },
+          "description": "Optional. HTTP methods permitted for cross-origin requests (e.g. [\"GET\", \"POST\"]).\n\nDefault might be [\"GET\", \"POST\", \"OPTIONS\"] depending on your server framework.\n"
+        },
+        "allow_origin_regex": {
+          "type": "string",
+          "description": "Optional. A regex pattern for matching allowed origins, used if you have dynamic subdomains.\n"
+        },
+        "allow_origins": {
+          "type": "array",
+          "items": {
+            "type": "string"
+          },
+          "description": "Optional. List of allowed origins (e.g., \"https://example.com\").\n\nDefault is often an empty list (no external origins).\nUse \"*\" only if you trust all origins, as that bypasses most restrictions.\n"
+        },
+        "expose_headers": {
+          "type": "array",
+          "items": {
+            "type": "string"
+          },
+          "description": "Optional. List of headers that browsers are allowed to read from the response in cross-origin contexts."
+        },
+        "max_age": {
+          "type": "integer",
+          "description": "Optional. How many seconds the browser may cache preflight responses.\n\nDefault might be 600 (10 minutes). Larger values reduce preflight requests but can cause stale configurations.\n"
+        }
+      },
+      "required": []
+    },
+    "StoreConfig": {
+      "title": "StoreConfig",
+      "description": "Configuration for the built-in long-term memory store.\n\nThis store can optionally perform semantic search. If you omit `index`,\nthe store will just handle traditional (non-embedded) data without vector lookups.",
+      "type": "object",
+      "properties": {
+        "index": {
+          "anyOf": [
+            {
+              "$ref": "#/$defs/IndexConfig"
+            },
+            {
+              "type": "null"
+            }
+          ],
+          "description": "Optional. Defines the vector-based semantic search configuration.\n\n- Generate embeddings according to `index.embed`\n- Enforce the embedding dimension given by `index.dims`\n- Embed only specified JSON fields (if any) from `index.fields`\n\nIf omitted, no vector index is initialized.\n"
+        }
+      },
+      "required": []
+    },
+    "IndexConfig": {
+      "title": "IndexConfig",
+      "description": "Configuration for indexing documents for semantic search in the store.\n\nThis governs how text is converted into embeddings and stored for vector-based lookups.",
+      "type": "object",
+      "properties": {
+        "dims": {
+          "type": "integer",
+          "description": "Required. Dimensionality of the embedding vectors you will store.\n\nMust match the output dimension of your selected embedding model or custom embed function.\nIf mismatched, you will likely encounter shape/size errors when inserting or querying vectors.\n\n"
+        },
+        "embed": {
+          "type": "string",
+          "description": "Required. Identifier or reference to the embedding model or a custom embedding function.\n\n- \"my_custom_embed\" if it's a known alias in your system\n"
+        },
+        "fields": {
+          "anyOf": [
+            {
+              "type": "array",
+              "items": {
+                "type": "string"
+              }
+            },
+            {
+              "type": "null"
+            }
+          ],
+          "description": "Optional. List of JSON fields to extract before generating embeddings.\n\nDefaults to [\"$\"], which means the entire JSON object is embedded as one piece of text.\nIf you provide multiple fields (e.g. [\"title\", \"content\"]), each is extracted and embedded separately,\noften saving token usage if you only care about certain parts of the data.\n"
+        }
+      },
+      "required": []
+    }
+  },
+  "title": "LangGraph CLI Configuration",
+  "description": "Configuration schema for langgraph-cli",
+  "version": "v0"
+}

libs/langgraph/langgraph/func/__init__.py

@@ -36,23 +36,31 @@ from langgraph.types import _DC_KWARGS, RetryPolicy, StreamMode
 
 @overload
 def task(
-    *, name: Optional[str] = None, retry: Optional[RetryPolicy] = None
-) -> Callable[[Callable[P, T]], Callable[P, SyncAsyncFuture[T]]]: ...
+    *,
+    name: Optional[str] = None,
+    retry: Optional[RetryPolicy] = None,
+) -> Callable[
+    [Union[Callable[P, Awaitable[T]], Callable[P, T]]],
+    Callable[P, SyncAsyncFuture[T]],
+]: ...
 
 
 @overload
 def task(
-    __func_or_none__: Callable[P, T],
+    __func_or_none__: Union[Callable[P, Awaitable[T]], Callable[P, T]],
 ) -> Callable[P, SyncAsyncFuture[T]]: ...
 
 
 def task(
-    __func_or_none__: Optional[Union[Callable[P, T], Callable[P, Awaitable[T]]]] = None,
+    __func_or_none__: Optional[Union[Callable[P, Awaitable[T]], Callable[P, T]]] = None,
     *,
     name: Optional[str] = None,
     retry: Optional[RetryPolicy] = None,
 ) -> Union[
-    Callable[[Callable[P, T]], Callable[P, SyncAsyncFuture[T]]],
+    Callable[
+        [Union[Callable[P, Awaitable[T]], Callable[P, T]]],
+        Callable[P, SyncAsyncFuture[T]],
+    ],
     Callable[P, SyncAsyncFuture[T]],
 ]:
     """Define a LangGraph task using the `task` decorator.
@@ -345,7 +353,7 @@ class entrypoint:
         value: R
         """Value to return. A value will always be returned even if it is None."""
         save: S
-        """The value for the state for the next checkpoint. 
+        """The value for the state for the next checkpoint.
 
         A value will always be saved even if it is None.
         """

libs/langgraph/langgraph/pregel/__init__.py

@@ -18,6 +18,7 @@ from typing import (
     Type,
     Union,
     cast,
+    get_type_hints,
     overload,
 )
 from uuid import UUID, uuid5
@@ -119,7 +120,7 @@ from langgraph.utils.config import (
     recast_checkpoint_ns,
 )
 from langgraph.utils.fields import get_enhanced_type_hints
-from langgraph.utils.pydantic import create_model
+from langgraph.utils.pydantic import create_model, is_supported_by_pydantic
 from langgraph.utils.queue import AsyncQueue, SyncQueue  # type: ignore[attr-defined]
 
 WriteValue = Union[Callable[[Input], Output], Any]
@@ -609,6 +610,36 @@ class Pregel(PregelProtocol):
             ]
         ]
 
+    def config_schema(
+        self, *, include: Optional[Sequence[str]] = None
+    ) -> Type[BaseModel]:
+        # If the config type is not set explicitly, we will try to infer it.
+        # If the config type is provided, but isn't directly supported by pydantic
+        # (e.g., vanilla python class), we will also delegate to the parent class,
+        # which handles cases where Pydantic doesn't support the type.
+        if self.config_type is None or not is_supported_by_pydantic(self.config_type):
+            return super().config_schema(include=include)
+
+        include = include or []
+        fields = {
+            "configurable": (self.config_type, None),
+            **{
+                field_name: (field_type, None)
+                for field_name, field_type in get_type_hints(RunnableConfig).items()
+                if field_name in [i for i in include if i != "configurable"]
+            },
+        }
+        return create_model(self.get_name("Config"), field_definitions=fields)
+
+    def get_config_jsonschema(
+        self, *, include: Optional[Sequence[str]] = None
+    ) -> Dict[str, Any]:
+        schema = self.config_schema(include=include)
+        if hasattr(schema, "model_json_schema"):
+            return schema.model_json_schema()
+        else:
+            return schema.schema()
+
     @property
     def InputType(self) -> Any:
         if isinstance(self.input_channels, str):
@@ -634,7 +665,7 @@ class Pregel(PregelProtocol):
 
     def get_input_jsonschema(
         self, config: Optional[RunnableConfig] = None
-    ) -> Dict[All, Any]:
+    ) -> Dict[str, Any]:
         schema = self.get_input_schema(config)
         if hasattr(schema, "model_json_schema"):
             return schema.model_json_schema()
@@ -666,7 +697,7 @@ class Pregel(PregelProtocol):
 
     def get_output_jsonschema(
         self, config: Optional[RunnableConfig] = None
-    ) -> Dict[All, Any]:
+    ) -> Dict[str, Any]:
         schema = self.get_output_schema(config)
         if hasattr(schema, "model_json_schema"):
             return schema.model_json_schema()

libs/langgraph/langgraph/pregel/loop.py

@@ -2,7 +2,6 @@ import asyncio
 import concurrent.futures
 from collections import defaultdict, deque
 from contextlib import AsyncExitStack, ExitStack
-from dataclasses import replace
 from inspect import signature
 from types import TracebackType
 from typing import (
@@ -55,6 +54,7 @@ from langgraph.constants import (
     ERROR,
     INPUT,
     INTERRUPT,
+    MISSING,
     NS_SEP,
     NULL_TASK_ID,
     PUSH,
@@ -67,7 +67,6 @@ from langgraph.errors import (
     EmptyInputError,
     GraphDelegate,
     GraphInterrupt,
-    ParentCommand,
 )
 from langgraph.managed.base import (
     ManagedValueMapping,
@@ -566,7 +565,13 @@ class PregelLoop(LoopProtocol):
         is_resuming = bool(self.checkpoint["channel_versions"]) and bool(
             configurable.get(
                 CONFIG_KEY_RESUMING,
-                self.input is None or isinstance(self.input, Command),
+                self.input is None
+                or isinstance(self.input, Command)
+                or (
+                    not self.is_nested
+                    and self.config.get("metadata", {}).get("run_id")
+                    == self.checkpoint_metadata.get("run_id", MISSING)
+                ),
             )
         )
 
@@ -742,15 +747,6 @@ class PregelLoop(LoopProtocol):
         exc_value: Optional[BaseException],
         traceback: Optional[TracebackType],
     ) -> Optional[bool]:
-        # add current state to parent command
-        if isinstance(exc_value, ParentCommand):
-            cmd = exc_value.args[0]
-            state = (
-                [(self.output_keys, read_channels(self.channels, self.output_keys))]
-                if isinstance(self.output_keys, str)
-                else list(read_channels(self.channels, self.output_keys).items())
-            )
-            exc_value.args = (replace(cmd, update=[*state, *cmd._update_as_tuples()]),)
         # suppress interrupt
         suppress = isinstance(exc_value, GraphInterrupt) and not self.is_nested
         if suppress:

libs/langgraph/langgraph/utils/pydantic.py

@@ -1,5 +1,9 @@
+import sys
+import typing
+from dataclasses import is_dataclass
 from typing import Any, Dict, Optional, Union
 
+import typing_extensions
 from pydantic import BaseModel
 from pydantic.v1 import BaseModel as BaseModelV1
 
@@ -35,3 +39,31 @@ def create_model(
             v1_kwargs["__root__"] = root
 
         return create_model(model_name, **v1_kwargs, **(field_definitions or {}))
+
+
+def is_supported_by_pydantic(type_: Any) -> bool:
+    """Check if a given "complex" type is supported by pydantic.
+
+    This will return False for primitive types like int, str, etc.
+
+    The check is meant for container types like dataclasses, TypedDicts, etc.
+    """
+    if is_dataclass(type_):
+        return True
+
+    # Pydantic does not support mixing .v1 and root namespaces, so
+    # we only check for BaseModel (not pydantic.v1.BaseModel).
+    if isinstance(type_, type) and issubclass(type_, BaseModel):
+        return True
+
+    if hasattr(type_, "__orig_bases__"):
+        for base in type_.__orig_bases__:
+            if base is typing_extensions.TypedDict:
+                return True
+            elif base is typing.TypedDict:  # noqa: TID251
+                # ignoring TID251 since it's OK to use typing.TypedDict in this case.
+                # Pydantic supports typing.TypedDict from Python 3.12
+                # For older versions, only typing_extensions.TypedDict is supported.
+                if sys.version_info >= (3, 12):
+                    return True
+    return False

libs/langgraph/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langgraph"
-version = "0.3.2"
+version = "0.3.5"
 description = "Building stateful, multi-actor applications with LLMs"
 authors = []
 license = "MIT"

libs/langgraph/tests/__snapshots__/test_pregel.ambr

@@ -1217,6 +1217,426 @@
     'type': 'object',
   })
 # ---
+# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[memory]
+  '''
+  graph TD;
+  	__start__ --> rewrite_query;
+  	analyzer_one --> retriever_one;
+  	qa --> __end__;
+  	retriever_one --> qa;
+  	retriever_two --> qa;
+  	rewrite_query --> analyzer_one;
+  	rewrite_query -.-> retriever_two;
+  
+  '''
+# ---
+# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[memory].1
+  dict({
+    '$defs': dict({
+      'InnerObject': dict({
+        'properties': dict({
+          'yo': dict({
+            'title': 'Yo',
+            'type': 'integer',
+          }),
+        }),
+        'required': list([
+          'yo',
+        ]),
+        'title': 'InnerObject',
+        'type': 'object',
+      }),
+    }),
+    'properties': dict({
+      'inner': dict({
+        '$ref': '#/$defs/InnerObject',
+      }),
+      'query': dict({
+        'title': 'Query',
+        'type': 'string',
+      }),
+    }),
+    'required': list([
+      'query',
+      'inner',
+    ]),
+    'title': 'Input',
+    'type': 'object',
+  })
+# ---
+# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[memory].2
+  dict({
+    'properties': dict({
+      'answer': dict({
+        'title': 'Answer',
+        'type': 'string',
+      }),
+      'docs': dict({
+        'items': dict({
+          'type': 'string',
+        }),
+        'title': 'Docs',
+        'type': 'array',
+      }),
+    }),
+    'required': list([
+      'answer',
+      'docs',
+    ]),
+    'title': 'Output',
+    'type': 'object',
+  })
+# ---
+# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[postgres]
+  '''
+  graph TD;
+  	__start__ --> rewrite_query;
+  	analyzer_one --> retriever_one;
+  	qa --> __end__;
+  	retriever_one --> qa;
+  	retriever_two --> qa;
+  	rewrite_query --> analyzer_one;
+  	rewrite_query -.-> retriever_two;
+  
+  '''
+# ---
+# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[postgres].1
+  dict({
+    '$defs': dict({
+      'InnerObject': dict({
+        'properties': dict({
+          'yo': dict({
+            'title': 'Yo',
+            'type': 'integer',
+          }),
+        }),
+        'required': list([
+          'yo',
+        ]),
+        'title': 'InnerObject',
+        'type': 'object',
+      }),
+    }),
+    'properties': dict({
+      'inner': dict({
+        '$ref': '#/$defs/InnerObject',
+      }),
+      'query': dict({
+        'title': 'Query',
+        'type': 'string',
+      }),
+    }),
+    'required': list([
+      'query',
+      'inner',
+    ]),
+    'title': 'Input',
+    'type': 'object',
+  })
+# ---
+# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[postgres].2
+  dict({
+    'properties': dict({
+      'answer': dict({
+        'title': 'Answer',
+        'type': 'string',
+      }),
+      'docs': dict({
+        'items': dict({
+          'type': 'string',
+        }),
+        'title': 'Docs',
+        'type': 'array',
+      }),
+    }),
+    'required': list([
+      'answer',
+      'docs',
+    ]),
+    'title': 'Output',
+    'type': 'object',
+  })
+# ---
+# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[postgres_pipe]
+  '''
+  graph TD;
+  	__start__ --> rewrite_query;
+  	analyzer_one --> retriever_one;
+  	qa --> __end__;
+  	retriever_one --> qa;
+  	retriever_two --> qa;
+  	rewrite_query --> analyzer_one;
+  	rewrite_query -.-> retriever_two;
+  
+  '''
+# ---
+# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[postgres_pipe].1
+  dict({
+    '$defs': dict({
+      'InnerObject': dict({
+        'properties': dict({
+          'yo': dict({
+            'title': 'Yo',
+            'type': 'integer',
+          }),
+        }),
+        'required': list([
+          'yo',
+        ]),
+        'title': 'InnerObject',
+        'type': 'object',
+      }),
+    }),
+    'properties': dict({
+      'inner': dict({
+        '$ref': '#/$defs/InnerObject',
+      }),
+      'query': dict({
+        'title': 'Query',
+        'type': 'string',
+      }),
+    }),
+    'required': list([
+      'query',
+      'inner',
+    ]),
+    'title': 'Input',
+    'type': 'object',
+  })
+# ---
+# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[postgres_pipe].2
+  dict({
+    'properties': dict({
+      'answer': dict({
+        'title': 'Answer',
+        'type': 'string',
+      }),
+      'docs': dict({
+        'items': dict({
+          'type': 'string',
+        }),
+        'title': 'Docs',
+        'type': 'array',
+      }),
+    }),
+    'required': list([
+      'answer',
+      'docs',
+    ]),
+    'title': 'Output',
+    'type': 'object',
+  })
+# ---
+# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[postgres_pool]
+  '''
+  graph TD;
+  	__start__ --> rewrite_query;
+  	analyzer_one --> retriever_one;
+  	qa --> __end__;
+  	retriever_one --> qa;
+  	retriever_two --> qa;
+  	rewrite_query --> analyzer_one;
+  	rewrite_query -.-> retriever_two;
+  
+  '''
+# ---
+# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[postgres_pool].1
+  dict({
+    '$defs': dict({
+      'InnerObject': dict({
+        'properties': dict({
+          'yo': dict({
+            'title': 'Yo',
+            'type': 'integer',
+          }),
+        }),
+        'required': list([
+          'yo',
+        ]),
+        'title': 'InnerObject',
+        'type': 'object',
+      }),
+    }),
+    'properties': dict({
+      'inner': dict({
+        '$ref': '#/$defs/InnerObject',
+      }),
+      'query': dict({
+        'title': 'Query',
+        'type': 'string',
+      }),
+    }),
+    'required': list([
+      'query',
+      'inner',
+    ]),
+    'title': 'Input',
+    'type': 'object',
+  })
+# ---
+# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[postgres_pool].2
+  dict({
+    'properties': dict({
+      'answer': dict({
+        'title': 'Answer',
+        'type': 'string',
+      }),
+      'docs': dict({
+        'items': dict({
+          'type': 'string',
+        }),
+        'title': 'Docs',
+        'type': 'array',
+      }),
+    }),
+    'required': list([
+      'answer',
+      'docs',
+    ]),
+    'title': 'Output',
+    'type': 'object',
+  })
+# ---
+# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[postgres_shallow]
+  '''
+  graph TD;
+  	__start__ --> rewrite_query;
+  	analyzer_one --> retriever_one;
+  	qa --> __end__;
+  	retriever_one --> qa;
+  	retriever_two --> qa;
+  	rewrite_query --> analyzer_one;
+  	rewrite_query -.-> retriever_two;
+  
+  '''
+# ---
+# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[postgres_shallow].1
+  dict({
+    '$defs': dict({
+      'InnerObject': dict({
+        'properties': dict({
+          'yo': dict({
+            'title': 'Yo',
+            'type': 'integer',
+          }),
+        }),
+        'required': list([
+          'yo',
+        ]),
+        'title': 'InnerObject',
+        'type': 'object',
+      }),
+    }),
+    'properties': dict({
+      'inner': dict({
+        '$ref': '#/$defs/InnerObject',
+      }),
+      'query': dict({
+        'title': 'Query',
+        'type': 'string',
+      }),
+    }),
+    'required': list([
+      'query',
+      'inner',
+    ]),
+    'title': 'Input',
+    'type': 'object',
+  })
+# ---
+# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[postgres_shallow].2
+  dict({
+    'properties': dict({
+      'answer': dict({
+        'title': 'Answer',
+        'type': 'string',
+      }),
+      'docs': dict({
+        'items': dict({
+          'type': 'string',
+        }),
+        'title': 'Docs',
+        'type': 'array',
+      }),
+    }),
+    'required': list([
+      'answer',
+      'docs',
+    ]),
+    'title': 'Output',
+    'type': 'object',
+  })
+# ---
+# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[sqlite]
+  '''
+  graph TD;
+  	__start__ --> rewrite_query;
+  	analyzer_one --> retriever_one;
+  	qa --> __end__;
+  	retriever_one --> qa;
+  	retriever_two --> qa;
+  	rewrite_query --> analyzer_one;
+  	rewrite_query -.-> retriever_two;
+  
+  '''
+# ---
+# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[sqlite].1
+  dict({
+    '$defs': dict({
+      'InnerObject': dict({
+        'properties': dict({
+          'yo': dict({
+            'title': 'Yo',
+            'type': 'integer',
+          }),
+        }),
+        'required': list([
+          'yo',
+        ]),
+        'title': 'InnerObject',
+        'type': 'object',
+      }),
+    }),
+    'properties': dict({
+      'inner': dict({
+        '$ref': '#/$defs/InnerObject',
+      }),
+      'query': dict({
+        'title': 'Query',
+        'type': 'string',
+      }),
+    }),
+    'required': list([
+      'query',
+      'inner',
+    ]),
+    'title': 'Input',
+    'type': 'object',
+  })
+# ---
+# name: test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input[sqlite].2
+  dict({
+    'properties': dict({
+      'answer': dict({
+        'title': 'Answer',
+        'type': 'string',
+      }),
+      'docs': dict({
+        'items': dict({
+          'type': 'string',
+        }),
+        'title': 'Docs',
+        'type': 'array',
+      }),
+    }),
+    'required': list([
+      'answer',
+      'docs',
+    ]),
+    'title': 'Output',
+    'type': 'object',
+  })
+# ---
 # name: test_in_one_fan_out_state_graph_waiting_edge_via_branch[memory]
   '''
   graph TD;
@@ -1528,7 +1948,7 @@
   '''
 # ---
 # name: test_state_graph_w_config_inherited_state_keys
-  '{"$defs": {"Configurable": {"properties": {"tools": {"default": null, "items": {"type": "string"}, "title": "Tools", "type": "array"}}, "title": "Configurable", "type": "object"}}, "properties": {"configurable": {"$ref": "#/$defs/Configurable", "default": null}}, "title": "LangGraphConfig", "type": "object"}'
+  '{"$defs": {"Config": {"properties": {"tools": {"items": {"type": "string"}, "title": "Tools", "type": "array"}}, "title": "Config", "type": "object"}}, "properties": {"configurable": {"$ref": "#/$defs/Config", "default": null}}, "title": "LangGraphConfig", "type": "object"}'
 # ---
 # name: test_state_graph_w_config_inherited_state_keys.1
   '{"$defs": {"AgentAction": {"description": "Represents a request to execute an action by an agent.\\n\\nThe action consists of the name of the tool to execute and the input to pass\\nto the tool. The log is used to pass along extra information about the action.", "properties": {"tool": {"title": "Tool", "type": "string"}, "tool_input": {"anyOf": [{"type": "string"}, {"type": "object"}], "title": "Tool Input"}, "log": {"title": "Log", "type": "string"}, "type": {"const": "AgentAction", "default": "AgentAction", "enum": ["AgentAction"], "title": "Type", "type": "string"}}, "required": ["tool", "tool_input", "log"], "title": "AgentAction", "type": "object"}, "AgentFinish": {"description": "Final return value of an ActionAgent.\\n\\nAgents return an AgentFinish when they have reached a stopping condition.", "properties": {"return_values": {"title": "Return Values", "type": "object"}, "log": {"title": "Log", "type": "string"}, "type": {"const": "AgentFinish", "default": "AgentFinish", "enum": ["AgentFinish"], "title": "Type", "type": "string"}}, "required": ["return_values", "log"], "title": "AgentFinish", "type": "object"}}, "properties": {"input": {"title": "Input", "type": "string"}, "agent_outcome": {"anyOf": [{"$ref": "#/$defs/AgentAction"}, {"$ref": "#/$defs/AgentFinish"}, {"type": "null"}], "default": null, "title": "Agent Outcome"}, "intermediate_steps": {"default": null, "items": {"maxItems": 2, "minItems": 2, "prefixItems": [{"$ref": "#/$defs/AgentAction"}, {"type": "string"}], "type": "array"}, "title": "Intermediate Steps", "type": "array"}}, "required": ["input"], "title": "LangGraphInput", "type": "object"}'

libs/langgraph/tests/test_pregel.py

@@ -10,7 +10,7 @@ import warnings
 from collections import Counter, deque
 from concurrent.futures import ThreadPoolExecutor
 from contextlib import contextmanager
-from dataclasses import dataclass
+from dataclasses import dataclass, field
 from random import randrange
 from typing import (
     Annotated,
@@ -275,6 +275,61 @@ def test_checkpoint_errors() -> None:
         graph.invoke("", {"configurable": {"thread_id": "thread-1"}})
 
 
+def test_config_json_schema() -> None:
+    """Test that config json schema is generated properly."""
+    chain = Channel.subscribe_to("input") | Channel.write_to("output")
+
+    @dataclass
+    class Foo:
+        x: int
+        y: str = field(default="foo")
+
+    app = Pregel(
+        nodes={
+            "one": chain,
+        },
+        channels={
+            "ephemeral": EphemeralValue(Any),
+            "input": LastValue(int),
+            "output": LastValue(int),
+        },
+        input_channels=["input", "ephemeral"],
+        output_channels="output",
+        config_type=Foo,
+    )
+
+    assert app.get_config_jsonschema() == {
+        "$defs": {
+            "Foo": {
+                "properties": {
+                    "x": {
+                        "title": "X",
+                        "type": "integer",
+                    },
+                    "y": {
+                        "default": "foo",
+                        "title": "Y",
+                        "type": "string",
+                    },
+                },
+                "required": [
+                    "x",
+                ],
+                "title": "Foo",
+                "type": "object",
+            },
+        },
+        "properties": {
+            "configurable": {
+                "$ref": "#/$defs/Foo",
+                "default": None,
+            },
+        },
+        "title": "LangGraphConfig",
+        "type": "object",
+    }
+
+
 def test_node_schemas_custom_output() -> None:
     class State(TypedDict):
         hello: str
@@ -1444,7 +1499,7 @@ def test_imp_task(request: pytest.FixtureRequest, checkpointer_name: str) -> Non
     checkpointer = request.getfixturevalue(f"checkpointer_{checkpointer_name}")
     mapper_calls = 0
 
-    class Config:
+    class Configurable:
         model: str
 
     @task()
@@ -1454,7 +1509,7 @@ def test_imp_task(request: pytest.FixtureRequest, checkpointer_name: str) -> Non
         time.sleep(input / 100)
         return str(input) * 2
 
-    @entrypoint(checkpointer=checkpointer, config_schema=Config)
+    @entrypoint(checkpointer=checkpointer, config_schema=Configurable)
     def graph(input: list[int]) -> list[str]:
         futures = [mapper(i) for i in input]
         mapped = [f.result() for f in futures]
@@ -2839,6 +2894,139 @@ def test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic2(
         }
 
 
+@pytest.mark.parametrize("checkpointer_name", ALL_CHECKPOINTERS_SYNC)
+def test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic_input(
+    snapshot: SnapshotAssertion,
+    mocker: MockerFixture,
+    request: pytest.FixtureRequest,
+    checkpointer_name: str,
+) -> None:
+    from pydantic import BaseModel
+
+    checkpointer = request.getfixturevalue(f"checkpointer_{checkpointer_name}")
+
+    def sorted_add(
+        x: list[str], y: Union[list[str], list[tuple[str, str]]]
+    ) -> list[str]:
+        if isinstance(y[0], tuple):
+            for rem, _ in y:
+                x.remove(rem)
+            y = [t[1] for t in y]
+        return sorted(operator.add(x, y))
+
+    class InnerObject(BaseModel):
+        yo: int
+
+    class QueryModel(BaseModel):
+        query: str
+
+    class State(QueryModel):
+        inner: InnerObject
+        answer: Optional[str] = None
+        docs: Annotated[list[str], sorted_add]
+
+    class StateUpdate(BaseModel):
+        query: Optional[str] = None
+        answer: Optional[str] = None
+        docs: Optional[list[str]] = None
+
+    class Input(QueryModel):
+        inner: InnerObject
+
+    class Output(BaseModel):
+        answer: str
+        docs: list[str]
+
+    def rewrite_query(data: State) -> State:
+        return {"query": f"query: {data.query}"}
+
+    def analyzer_one(data: State) -> State:
+        return StateUpdate(query=f"analyzed: {data.query}")
+
+    def retriever_one(data: State) -> State:
+        return {"docs": ["doc1", "doc2"]}
+
+    def retriever_two(data: State) -> State:
+        time.sleep(0.1)
+        return {"docs": ["doc3", "doc4"]}
+
+    def qa(data: State) -> State:
+        return {"answer": ",".join(data.docs)}
+
+    def decider(data: State) -> str:
+        assert isinstance(data, State)
+        return "retriever_two"
+
+    workflow = StateGraph(State, input=Input, output=Output)
+
+    workflow.add_node("rewrite_query", rewrite_query)
+    workflow.add_node("analyzer_one", analyzer_one)
+    workflow.add_node("retriever_one", retriever_one)
+    workflow.add_node("retriever_two", retriever_two)
+    workflow.add_node("qa", qa)
+
+    workflow.set_entry_point("rewrite_query")
+    workflow.add_edge("rewrite_query", "analyzer_one")
+    workflow.add_edge("analyzer_one", "retriever_one")
+    workflow.add_conditional_edges(
+        "rewrite_query", decider, {"retriever_two": "retriever_two"}
+    )
+    workflow.add_edge(["retriever_one", "retriever_two"], "qa")
+    workflow.set_finish_point("qa")
+
+    app = workflow.compile()
+
+    assert app.invoke(
+        Input(query="what is weather in sf", inner=InnerObject(yo=1))
+    ) == {
+        "docs": ["doc1", "doc2", "doc3", "doc4"],
+        "answer": "doc1,doc2,doc3,doc4",
+    }
+
+    assert [
+        *app.stream(Input(query="what is weather in sf", inner=InnerObject(yo=1)))
+    ] == [
+        {"rewrite_query": {"query": "query: what is weather in sf"}},
+        {"analyzer_one": {"query": "analyzed: query: what is weather in sf"}},
+        {"retriever_two": {"docs": ["doc3", "doc4"]}},
+        {"retriever_one": {"docs": ["doc1", "doc2"]}},
+        {"qa": {"answer": "doc1,doc2,doc3,doc4"}},
+    ]
+
+    app_w_interrupt = workflow.compile(
+        checkpointer=checkpointer,
+        interrupt_after=["retriever_one"],
+    )
+    config = {"configurable": {"thread_id": "1"}}
+
+    assert [
+        c
+        for c in app_w_interrupt.stream(
+            Input(query="what is weather in sf", inner=InnerObject(yo=1)), config
+        )
+    ] == [
+        {"rewrite_query": {"query": "query: what is weather in sf"}},
+        {"analyzer_one": {"query": "analyzed: query: what is weather in sf"}},
+        {"retriever_two": {"docs": ["doc3", "doc4"]}},
+        {"retriever_one": {"docs": ["doc1", "doc2"]}},
+        {"__interrupt__": ()},
+    ]
+
+    assert [c for c in app_w_interrupt.stream(None, config)] == [
+        {"qa": {"answer": "doc1,doc2,doc3,doc4"}},
+    ]
+
+    assert app_w_interrupt.update_state(
+        config, {"docs": ["doc5"]}, as_node="rewrite_query"
+    ) == {
+        "configurable": {
+            "thread_id": "1",
+            "checkpoint_id": AnyStr(),
+            "checkpoint_ns": "",
+        }
+    }
+
+
 @pytest.mark.parametrize("checkpointer_name", ALL_CHECKPOINTERS_SYNC)
 def test_in_one_fan_out_state_graph_waiting_edge_plus_regular(
     request: pytest.FixtureRequest, checkpointer_name: str
@@ -2905,14 +3093,24 @@ def test_in_one_fan_out_state_graph_waiting_edge_plus_regular(
         "answer": "doc1,doc2,doc3,doc4",
     }
 
-    assert [*app.stream({"query": "what is weather in sf"})] == [
-        {"rewrite_query": {"query": "query: what is weather in sf"}},
-        {"qa": {"answer": ""}},
-        {"analyzer_one": {"query": "analyzed: query: what is weather in sf"}},
-        {"retriever_two": {"docs": ["doc3", "doc4"]}},
-        {"retriever_one": {"docs": ["doc1", "doc2"]}},
-        {"qa": {"answer": "doc1,doc2,doc3,doc4"}},
-    ]
+    assert [*app.stream({"query": "what is weather in sf"})] in (
+        [
+            {"rewrite_query": {"query": "query: what is weather in sf"}},
+            {"qa": {"answer": ""}},
+            {"analyzer_one": {"query": "analyzed: query: what is weather in sf"}},
+            {"retriever_two": {"docs": ["doc3", "doc4"]}},
+            {"retriever_one": {"docs": ["doc1", "doc2"]}},
+            {"qa": {"answer": "doc1,doc2,doc3,doc4"}},
+        ],
+        [
+            {"rewrite_query": {"query": "query: what is weather in sf"}},
+            {"analyzer_one": {"query": "analyzed: query: what is weather in sf"}},
+            {"qa": {"answer": ""}},
+            {"retriever_two": {"docs": ["doc3", "doc4"]}},
+            {"retriever_one": {"docs": ["doc1", "doc2"]}},
+            {"qa": {"answer": "doc1,doc2,doc3,doc4"}},
+        ],
+    )
 
     app_w_interrupt = workflow.compile(
         checkpointer=checkpointer,
@@ -4883,13 +5081,6 @@ def test_parent_command(request: pytest.FixtureRequest, checkpointer_name: str)
             "source": "loop",
             "writes": {
                 "alice": {
-                    "messages": [
-                        _AnyIdHumanMessage(
-                            content="get user name",
-                            additional_kwargs={},
-                            response_metadata={},
-                        ),
-                    ],
                     "user_name": "Meow",
                 }
             },
@@ -6229,151 +6420,6 @@ def test_multiple_subgraphs_checkpointer(
     ]
 
 
-def test_merging_updates_command_parent():
-    # simple reducer
-    def append_unique(left, right):
-        combined = list(left)
-        for item in right:
-            if item in combined:
-                continue
-            else:
-                combined.append(item)
-        return combined
-
-    class State(TypedDict):
-        foo: str
-        bar: Annotated[list[str], append_unique]
-
-    # Define subgraph
-    def subgraph_node_1(state: State):
-        return Command(
-            goto="subgraph_node_2",
-            update={
-                "foo": "foo",
-                "bar": ["subgraph_node_1"],
-            },
-        )
-
-    def subgraph_node_2(state: State):
-        return Command(
-            goto="node_3",
-            update={"bar": ["subgraph_node_2"]},
-            graph=Command.PARENT,
-        )
-
-    subgraph_builder = StateGraph(State)
-    subgraph_builder.add_node(subgraph_node_1)
-    subgraph_builder.add_node(subgraph_node_2)
-    subgraph_builder.add_edge(START, "subgraph_node_1")
-
-    # Define main graph
-    def node_1(state: State):
-        return Command(
-            goto="node_2",
-            update={"bar": ["node_1"]},
-        )
-
-    def node_3(state: State, store):
-        return Command(
-            update={"bar": ["node_3"]},
-        )
-
-    main_builder = StateGraph(State)
-    main_builder.add_node("node_1", node_1)
-    main_builder.add_node("node_2", subgraph_builder.compile())
-    main_builder.add_node("node_3", node_3)
-    main_builder.add_edge(START, "node_1")
-    main_builder.add_edge("node_2", "node_3")
-    main_graph = main_builder.compile()
-
-    assert main_graph.invoke({"foo": ""}) == {
-        "foo": "foo",
-        "bar": ["node_1", "subgraph_node_1", "subgraph_node_2", "node_3"],
-    }
-
-    assert list(
-        main_graph.stream({"foo": ""}, stream_mode="updates", subgraphs=True)
-    ) == [
-        ((), {"node_1": {"bar": ["node_1"]}}),
-        (
-            (AnyStr("node_2:"),),
-            {"subgraph_node_1": {"foo": "foo", "bar": ["subgraph_node_1"]}},
-        ),
-        (
-            (),
-            {
-                "node_2": [
-                    {"foo": "foo"},
-                    {"bar": ["node_1", "subgraph_node_1"]},
-                    {"bar": ["subgraph_node_2"]},
-                ]
-            },
-        ),
-        ((), {"node_3": {"bar": ["node_3"]}}),
-    ]
-
-
-def test_merging_non_overlapping_updates_command_parent():
-    # simple reducer
-    def append_unique(left, right):
-        combined = list(left)
-        for item in right:
-            if item in combined:
-                continue
-            else:
-                combined.append(item)
-        return combined
-
-    class State(TypedDict):
-        foo: Annotated[list, append_unique]
-
-    # Define subgraph
-    def subgraph_node_1(state: State):
-        return Command(
-            goto="subgraph_node_2",
-            update={
-                "foo": ["bar"],
-                "bar": ["subgraph_node_1"],
-            },
-        )
-
-    def subgraph_node_2(state: State):
-        return Command(
-            goto="node_3",
-            update={"bar": ["subgraph_node_2"]},
-            graph=Command.PARENT,
-        )
-
-    subgraph_builder = StateGraph(State)
-    subgraph_builder.add_node(subgraph_node_1)
-    subgraph_builder.add_node(subgraph_node_2)
-    subgraph_builder.add_edge(START, "subgraph_node_1")
-
-    # Define main graph
-    def node_1(state: State):
-        return Command(
-            goto="node_2",
-            update={"foo": ["foo"]},
-        )
-
-    def node_3(state: State, store):
-        return Command(
-            update={"foo": ["baz"]},
-        )
-
-    main_builder = StateGraph(State)
-    main_builder.add_node("node_1", node_1)
-    main_builder.add_node("node_2", subgraph_builder.compile())
-    main_builder.add_node("node_3", node_3)
-    main_builder.add_edge(START, "node_1")
-    main_builder.add_edge("node_2", "node_3")
-    main_graph = main_builder.compile()
-
-    assert main_graph.invoke({"foo": []}) == {
-        "foo": ["foo", "bar", "baz"],
-    }
-
-
 def test_entrypoint_output_schema_with_return_and_save() -> None:
     """Test output schema inference with entrypoint.final."""
 

libs/langgraph/tests/test_pregel_async.py

@@ -6148,13 +6148,6 @@ async def test_parent_command(checkpointer_name: str) -> None:
                 "source": "loop",
                 "writes": {
                     "alice": {
-                        "messages": [
-                            _AnyIdHumanMessage(
-                                content="get user name",
-                                additional_kwargs={},
-                                response_metadata={},
-                            ),
-                        ],
                         "user_name": "Meow",
                     }
                 },

libs/langgraph/tests/test_pydantic.py

@@ -0,0 +1,43 @@
+import sys
+import typing
+
+import pydantic
+import typing_extensions
+
+from langgraph.utils.pydantic import is_supported_by_pydantic
+
+
+def test_is_supported_by_pydantic() -> None:
+    """Test if types are supported by pydantic."""
+
+    class TypedDictExtensions(typing_extensions.TypedDict):
+        x: int
+
+    assert is_supported_by_pydantic(TypedDictExtensions) is True
+
+    class VanillaClass:
+        x: int
+
+    assert is_supported_by_pydantic(VanillaClass) is False
+
+    class BuiltinTypedDict(typing.TypedDict):  # noqa: TID251
+        x: int
+
+    if sys.version_info >= (3, 12):
+        assert is_supported_by_pydantic(BuiltinTypedDict) is True
+    else:
+        assert is_supported_by_pydantic(BuiltinTypedDict) is False
+
+    class PydanticModel(pydantic.BaseModel):
+        x: int
+
+    assert is_supported_by_pydantic(PydanticModel) is True
+
+    if hasattr(pydantic, "v1"):
+
+        class PydanticModelV1(pydantic.v1.BaseModel):
+            x: int
+
+        assert is_supported_by_pydantic(PydanticModelV1) is False
+
+    assert is_supported_by_pydantic(int) is False

libs/prebuilt/langgraph/prebuilt/chat_agent_executor.py

@@ -22,6 +22,7 @@ from langchain_core.runnables import (
     Runnable,
     RunnableBinding,
     RunnableConfig,
+    RunnableSequence,
 )
 from langchain_core.tools import BaseTool
 from pydantic import BaseModel
@@ -133,6 +134,16 @@ def _convert_modifier_to_prompt(func: F) -> F:
 
 
 def _should_bind_tools(model: LanguageModelLike, tools: Sequence[BaseTool]) -> bool:
+    if isinstance(model, RunnableSequence):
+        model = next(
+            (
+                step
+                for step in model.steps
+                if isinstance(step, (RunnableBinding, BaseChatModel))
+            ),
+            model,
+        )
+
     if not isinstance(model, RunnableBinding):
         return True
 
@@ -168,6 +179,16 @@ def _should_bind_tools(model: LanguageModelLike, tools: Sequence[BaseTool]) -> b
 
 def _get_model(model: LanguageModelLike) -> BaseChatModel:
     """Get the underlying model from a RunnableBinding or return the model itself."""
+    if isinstance(model, RunnableSequence):
+        model = next(
+            (
+                step
+                for step in model.steps
+                if isinstance(step, (RunnableBinding, BaseChatModel))
+            ),
+            model,
+        )
+
     if isinstance(model, RunnableBinding):
         model = model.bound
 

libs/prebuilt/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langgraph-prebuilt"
-version = "0.1.1"
+version = "0.1.2"
 description = "Library with high-level APIs for creating and executing LangGraph agents and tools."
 authors = []
 license = "MIT"

libs/prebuilt/tests/test_react_agent.py

@@ -35,6 +35,8 @@ from langgraph.prebuilt import (
 )
 from langgraph.prebuilt.chat_agent_executor import (
     AgentState,
+    _get_model,
+    _should_bind_tools,
     _validate_chat_history,
 )
 from langgraph.prebuilt.tool_node import (
@@ -1324,3 +1326,66 @@ def test_tool_node_node_interrupt(
             ns=[AnyStr("tools:")],
         ),
     )
+
+
+@pytest.mark.parametrize("tool_style", ["openai", "anthropic"])
+def test_should_bind_tools(tool_style: str) -> None:
+    @dec_tool
+    def some_tool(some_val: int) -> str:
+        """Tool docstring."""
+        return "meow"
+
+    @dec_tool
+    def some_other_tool(some_val: int) -> str:
+        """Tool docstring."""
+        return "meow"
+
+    model = FakeToolCallingModel(tool_style=tool_style)
+    # should bind when a regular model
+    assert _should_bind_tools(model, [])
+    assert _should_bind_tools(model, [some_tool])
+
+    # should bind when a seq
+    seq = model | RunnableLambda(lambda message: message)
+    assert _should_bind_tools(seq, [])
+    assert _should_bind_tools(seq, [some_tool])
+
+    # should not bind when a model with tools
+    assert not _should_bind_tools(model.bind_tools([some_tool]), [some_tool])
+    # should not bind when a seq with tools
+    seq_with_tools = model.bind_tools([some_tool]) | RunnableLambda(
+        lambda message: message
+    )
+    assert not _should_bind_tools(seq_with_tools, [some_tool])
+
+    # should raise on invalid inputs
+    with pytest.raises(ValueError):
+        _should_bind_tools(model.bind_tools([some_tool]), [])
+    with pytest.raises(ValueError):
+        _should_bind_tools(model.bind_tools([some_tool]), [some_other_tool])
+    with pytest.raises(ValueError):
+        _should_bind_tools(model.bind_tools([some_tool]), [some_tool, some_other_tool])
+
+
+def test_get_model() -> None:
+    model = FakeToolCallingModel(tool_calls=[])
+    assert _get_model(model) == model
+
+    @dec_tool
+    def some_tool(some_val: int) -> str:
+        """Tool docstring."""
+        return "meow"
+
+    model_with_tools = model.bind_tools([some_tool])
+    assert _get_model(model_with_tools) == model
+
+    seq = model | RunnableLambda(lambda message: message)
+    assert _get_model(seq) == model
+
+    seq_with_tools = model.bind_tools([some_tool]) | RunnableLambda(
+        lambda message: message
+    )
+    assert _get_model(seq_with_tools) == model
+
+    with pytest.raises(TypeError):
+        _get_model(RunnableLambda(lambda message: message))

libs/sdk-js/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@langchain/langgraph-sdk",
-  "version": "0.0.45",
+  "version": "0.0.46",
   "description": "Client library for interacting with the LangGraph API",
   "type": "module",
   "packageManager": "yarn@1.22.19",

libs/sdk-js/src/react/stream.tsx

@@ -366,11 +366,11 @@ const useControllableThreadId = (options?: {
     onThreadIdRef.current?.(threadId);
   }, []);
 
-  if (typeof options?.threadId === "undefined") {
+  if (!options || !("threadId" in options)) {
     return [localThreadId, onThreadId];
   }
 
-  return [options.threadId, onThreadId];
+  return [options.threadId ?? null, onThreadId];
 };
 
 type BagTemplate = {
@@ -424,6 +424,16 @@ interface UseStreamOptions<
    */
   apiKey?: ClientConfig["apiKey"];
 
+  /**
+   * Custom call options, such as custom fetch implementation.
+   */
+  callerOptions?: ClientConfig["callerOptions"];
+
+  /**
+   * Default headers to send with requests.
+   */
+  defaultHeaders?: ClientConfig["defaultHeaders"];
+
   /**
    * Specify the key within the state that contains messages.
    * Defaults to "messages".
@@ -603,8 +613,19 @@ export function useStream<
   messagesKey ??= "messages";
 
   const client = useMemo(
-    () => new Client({ apiUrl: options.apiUrl, apiKey: options.apiKey }),
-    [options.apiKey, options.apiUrl],
+    () =>
+      new Client({
+        apiUrl: options.apiUrl,
+        apiKey: options.apiKey,
+        callerOptions: options.callerOptions,
+        defaultHeaders: options.defaultHeaders,
+      }),
+    [
+      options.apiKey,
+      options.apiUrl,
+      options.callerOptions,
+      options.defaultHeaders,
+    ],
   );
   const [threadId, onThreadId] = useControllableThreadId(options);
 
@@ -623,9 +644,12 @@ export function useStream<
   >([]);
 
   const trackStreamMode = useCallback(
-    (mode: Exclude<StreamMode, "debug" | "messages">) => {
-      if (!trackStreamModeRef.current.includes(mode))
-        trackStreamModeRef.current.push(mode);
+    (...mode: Exclude<StreamMode, "debug" | "messages">[]) => {
+      for (const m of mode) {
+        if (!trackStreamModeRef.current.includes(m)) {
+          trackStreamModeRef.current.push(m);
+        }
+      }
     },
     [],
   );
@@ -908,7 +932,7 @@ export function useStream<
     },
 
     get messages() {
-      trackStreamMode("messages-tuple");
+      trackStreamMode("messages-tuple", "values");
       return getMessages(values);
     },
 
@@ -916,7 +940,7 @@ export function useStream<
       message: Message,
       index?: number,
     ): MessageMetadata<StateType> | undefined {
-      trackStreamMode("messages-tuple");
+      trackStreamMode("messages-tuple", "values");
       return messageMetadata?.find(
         (m) => m.messageId === (message.id ?? index),
       );

libs/sdk-py/langgraph_sdk/client.py

@@ -2517,7 +2517,7 @@ def encode_json(json: Any) -> tuple[dict[str, str], bytes]:
 
 def decode_json(r: httpx.Response) -> Any:
     body = r.read()
-    return orjson.loads(body if body else None)
+    return orjson.loads(body) if body else None
 
 
 class SyncAssistantsClient: