add test

SDK support for:
https://github.com/langchain-ai/langgraph-api/pull/1217/

.github/scripts/check_sdk_methods.py

@@ -1,10 +1,15 @@
 import ast
 import os
 from itertools import filterfalse
-from typing import List, Tuple
+from typing import Dict, List, Tuple
 
 ROOT_PATH = os.path.abspath(os.path.join(__file__, "..", "..", ".."))
 CLIENT_PATH = os.path.join(ROOT_PATH, "libs", "sdk-py", "langgraph_sdk", "client.py")
+ASYNC_TO_SYNC_METHOD_MAP: Dict[str, str] = {
+    "aclose": "close",
+    "__aenter__": "__enter__",
+    "__aexit__": "__exit__",
+}
 
 
 def get_class_methods(node: ast.ClassDef) -> List[str]:
@@ -22,7 +27,7 @@ def find_classes(tree: ast.AST) -> List[Tuple[str, List[str]]]:
 
 def compare_sync_async_methods(sync_methods: List[str], async_methods: List[str]) -> List[str]:
     sync_set = set(sync_methods)
-    async_set = set(async_methods)
+    async_set = {ASYNC_TO_SYNC_METHOD_MAP.get(async_method, async_method) for async_method in async_methods}
     missing_in_sync = list(async_set - sync_set)
     missing_in_async = list(sync_set - async_set)
     return missing_in_sync + missing_in_async

.github/scripts/run_langgraph_cli_test.py

@@ -1,107 +1,145 @@
-import asyncio
-import json
-import os
 import pathlib
 import sys
-import langgraph_cli
-import langgraph_cli.docker
-import langgraph_cli.config
+import time
+from urllib import request, error
 
+import langgraph_cli
+import langgraph_cli.config
+import langgraph_cli.docker
+from langgraph_cli.cli import prepare_args_and_stdin
+from langgraph_cli.constants import DEFAULT_PORT
 from langgraph_cli.exec import Runner, subp_exec
 from langgraph_cli.progress import Progress
-from langgraph_cli.constants import DEFAULT_PORT
 
 
-def test(
-    config: pathlib.Path,
-    port: int,
-    tag: str,
-    verbose: bool,
-):
+def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
+    """Spin up API with Postgres/Redis via docker compose and wait until ready."""
     with Runner() as runner, Progress(message="Pulling...") as set:
-        # check docker available
+        # Detect docker/compose capabilities
         capabilities = langgraph_cli.docker.check_capabilities(runner)
-        # open config
+
+        # Validate config and prepare compose stdin/args using built image
         config_json = langgraph_cli.config.validate_config_file(config)
+        args, stdin = prepare_args_and_stdin(
+            capabilities=capabilities,
+            config_path=config,
+            config=config_json,
+            docker_compose=None,
+            port=port,
+            watch=False,
+            debugger_port=None,
+            debugger_base_url=f"http://127.0.0.1:{port}",
+            postgres_uri=None,
+            api_version=None,
+            image=tag,
+            base_image=None,
+        )
 
-        set("Running...")
-        args = [
-            "run",
-            "--rm",
-            "-p",
-            f"{port}:8000",
-        ]
-        if isinstance(config_json["env"], str):
-            args.extend(
-                [
-                    "--env-file",
-                    str(config.parent / config_json["env"]),
-                ]
-            )
-        else:
-            for k, v in config_json["env"].items():
-                args.extend(
-                    [
-                        "-e",
-                        f"{k}={v}",
-                    ]
-                )
-        if capabilities.healthcheck_start_interval:
-            args.extend(
-                [
-                    "--health-interval",
-                    "5s",
-                    "--health-retries",
-                    "1",
-                    "--health-start-period",
-                    "10s",
-                    "--health-start-interval",
-                    "1s",
-                ]
-            )
-        else:
-            args.extend(
-                [
-                    "--health-interval",
-                    "5s",
-                    "--health-retries",
-                    "2",
-                ]
-            )
+        # Compose up with wait (implies detach), similar to `langgraph up --wait`
+        args_up = [*args, "up", "--remove-orphans", "--wait"]
 
-        _task = None
-
-        def on_stdout(line: str):
-            nonlocal _task
-            if "GET /ok" in line or "Uvicorn running on" in line:
-                set("")
-                sys.stdout.write(
-                    f"""Ready!
-- API: http://localhost:{port}
-"""
-                )
-                sys.stdout.flush()
-                _task.cancel()
-                return True
-            return False
-
-        async def subp_exec_task(*args, **kwargs):
-            nonlocal _task
-            _task = asyncio.create_task(subp_exec(*args, **kwargs))
-            await _task
+        compose_cmd = ["docker", "compose"]
+        if capabilities.compose_type == "standalone":
+            compose_cmd = ["docker-compose"]
 
+        set("Starting...")
         try:
             runner.run(
-                subp_exec_task(
-                    "docker",
-                    *args,
-                    tag,
+                subp_exec(
+                    *compose_cmd,
+                    *args_up,
+                    input=stdin,
                     verbose=verbose,
-                    on_stdout=on_stdout,
                 )
             )
-        except asyncio.CancelledError:
-            pass
+        except Exception as e:  # noqa: BLE001
+            # On failure, show diagnostics then ensure clean teardown
+            sys.stderr.write(f"docker compose up failed: {e}\n")
+            try:
+                sys.stderr.write("\n== docker compose ps ==\n")
+                runner.run(subp_exec(*compose_cmd, *args, "ps", input=stdin, verbose=False))
+            except Exception:
+                pass
+            try:
+                sys.stderr.write("\n== docker compose logs (api) ==\n")
+                runner.run(
+                    subp_exec(
+                        *compose_cmd,
+                        *args,
+                        "logs",
+                        "langgraph-api",
+                        input=stdin,
+                        verbose=False,
+                    )
+                )
+            except Exception:
+                pass
+            finally:
+                try:
+                    runner.run(
+                        subp_exec(
+                            *compose_cmd,
+                            *args,
+                            "down",
+                            "-v",
+                            "--remove-orphans",
+                            input=stdin,
+                            verbose=False,
+                        )
+                    )
+                finally:
+                    raise
+
+        set("")
+        base_url = f"http://localhost:{port}"
+        ok_url = f"{base_url}/ok"
+        print(f"Waiting for {ok_url} to respond with 200...")
+        deadline = time.time() + 30
+        last_err: Exception | None = None
+        while time.time() < deadline:
+            try:
+                with request.urlopen(ok_url, timeout=2) as resp:
+                    if resp.status == 200:
+                        sys.stdout.write(
+                            f"""Ready!\n- API: {base_url}\n- /ok: 200 OK\n"""
+                        )
+                        sys.stdout.flush()
+                        break
+                    else:
+                        last_err = RuntimeError(f"Unexpected status: {resp.status}")
+                        print(f"Unexpected status: {resp.status}")
+            except error.URLError as e:
+                last_err = e
+            except Exception as e:  # noqa: BLE001
+                last_err = e
+            time.sleep(0.5)
+        else:
+            # Bring stack down before raising
+            args_down = [*args, "down", "-v", "--remove-orphans"]
+            try:
+                runner.run(
+                    subp_exec(
+                        *compose_cmd,
+                        *args_down,
+                        input=stdin,
+                        verbose=verbose,
+                    )
+                )
+            finally:
+                raise SystemExit(
+                    f"/ok did not return 202 within timeout. Last error: {last_err}"
+                )
+
+        # Clean up: bring compose stack down to free ports for next test
+        args_down = [*args, "down", "-v", "--remove-orphans"]
+        runner.run(
+            subp_exec(
+                *compose_cmd,
+                *args_down,
+                input=stdin,
+                verbose=verbose,
+            )
+        )
 
 
 if __name__ == "__main__":
@@ -110,6 +148,6 @@ if __name__ == "__main__":
     parser = argparse.ArgumentParser()
     parser.add_argument("-t", "--tag", type=str)
     parser.add_argument("-c", "--config", type=str, default="./langgraph.json")
-    parser.add_argument("-p", "--port", default=DEFAULT_PORT)
+    parser.add_argument("-p", "--port", type=int, default=DEFAULT_PORT)
     args = parser.parse_args()
     test(pathlib.Path(args.config), args.port, args.tag, verbose=True)

.github/workflows/_integration_test.yml

@@ -43,28 +43,43 @@ jobs:
       - name: Build and test service A
         if: steps.changed-files.outputs.all
         working-directory: libs/cli/examples
+        env:
+          LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
         run: |
           # The build-arg isn't used; just testing that we accept other args
-          langgraph build -t langgraph-test-a  --base-image "langchain/langgraph-trial"
-          cp .env.example .envg
+          langgraph build -t langgraph-test-a
+          cp .env.example .env
+          if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
           timeout 60 python ../../../.github/scripts/run_langgraph_cli_test.py -c langgraph.json -t langgraph-test-a
       - name: Build and test service B
         if: steps.changed-files.outputs.all
         working-directory: libs/cli/examples/graphs
+        env:
+          LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
         run: |
-          langgraph build -t langgraph-test-b  --base-image "langchain/langgraph-trial"
+          langgraph build -t langgraph-test-b
+          cp ../.env.example .env
+          if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
           timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-b
       - name: Build and test service C
         if: steps.changed-files.outputs.all
         working-directory: libs/cli/examples/graphs_reqs_a
+        env:
+          LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
         run: |
-          langgraph build -t langgraph-test-c  --base-image "langchain/langgraph-trial"
+          langgraph build -t langgraph-test-c
+          cp ../.env.example .env
+          if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
           timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-c
       - name: Build and test service D
         if: steps.changed-files.outputs.all
         working-directory: libs/cli/examples/graphs_reqs_b
+        env:
+          LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
         run: |
-          langgraph build -t langgraph-test-d  --base-image "langchain/langgraph-trial"
+          langgraph build -t langgraph-test-d
+          cp ../.env.example .env
+          if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
           timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-d
 
       - name: Build JS service

.github/workflows/ci.yml

@@ -78,6 +78,7 @@ jobs:
             "libs/checkpoint-sqlite",
             "libs/checkpoint-postgres",
             "libs/prebuilt",
+            "libs/sdk-py",
           ]
     if: needs.changes.outputs.python == 'true' || needs.changes.outputs.deps == 'true'
     uses: ./.github/workflows/_test.yml

.github/workflows/release.yml

@@ -62,7 +62,13 @@ jobs:
         working-directory: ${{ inputs.working-directory }}
         run: |
           PKG_NAME=$(grep -m 1 "^name = " pyproject.toml | cut -d '"' -f 2)
-          VERSION=$(grep -m 1 "^version = " pyproject.toml | cut -d '"' -f 2)
+          if grep -q 'dynamic.*=.*\[.*"version".*\]' pyproject.toml; then
+            # handle dynamic versioning
+            DIR_NAME=$(echo "$PKG_NAME" | tr '-' '_')
+            VERSION=$(grep -m 1 '^__version__' "${DIR_NAME}/__init__.py" | cut -d '"' -f 2)
+          else
+            VERSION=$(grep -m 1 "^version = " pyproject.toml | cut -d '"' -f 2)
+          fi
           SHORT_PKG_NAME="$(echo "$PKG_NAME" | sed -e 's/langgraph//g' -e 's/-//g')"
           if [ -z $SHORT_PKG_NAME ]; then
             TAG="$VERSION"

docs/_scripts/notebook_hooks.py

@@ -190,11 +190,11 @@ REDIRECT_MAP = {
     "concepts/langgraph_cloud.md": "https://docs.langchain.com/langgraph-platform/cloud",
     "concepts/langgraph_self_hosted_data_plane.md": "https://docs.langchain.com/langgraph-platform/hybrid",
     "concepts/langgraph_self_hosted_control_plane.md": "https://docs.langchain.com/langgraph-platform/self-hosted",
-    "concepts/langgraph_standalone_container.md": "https://docs.langchain.com/langgraph-platform/self-hosted#data-plane-only",
+    "concepts/langgraph_standalone_container.md": "https://docs.langchain.com/langgraph-platform/self-hosted#standalone-server",
     "cloud/deployment/cloud.md": "https://docs.langchain.com/langgraph-platform/cloud",
     "cloud/deployment/self_hosted_data_plane.md": "https://docs.langchain.com/langgraph-platform/deploy-hybrid",
     "cloud/deployment/self_hosted_control_plane.md": "https://docs.langchain.com/langgraph-platform/deploy-self-hosted-full-platform",
-    "cloud/deployment/standalone_container.md": "https://docs.langchain.com/langgraph-platform/deploy-data-plane-only",
+    "cloud/deployment/standalone_container.md": "https://docs.langchain.com/langgraph-platform/deploy-standalone-server",
     "concepts/server-mcp.md": "https://docs.langchain.com/langgraph-platform/server-mcp",
     "cloud/how-tos/human_in_the_loop_time_travel.md": "https://docs.langchain.com/langgraph-platform/human-in-the-loop-time-travel",
     "cloud/how-tos/add-human-in-the-loop.md": "https://docs.langchain.com/langgraph-platform/add-human-in-the-loop",

docs/docs/cloud/deployment/cloud.md

@@ -99,8 +99,8 @@ Starting from the `LangGraph Platform` view...
 1. In the top-right corner, select the gear icon (`Deployment Settings`).
 1. Update the `Git Branch` to the desired branch.
 1. Check/uncheck checkbox to `Automatically update deployment on push to branch`.
-    1. Branch creation/deletion and tag creation/deletion events will not trigger an update. Only pushes to an existing branch will trigger an update.
-    1. Pushes in quick succession to a branch will not trigger subsequent updates. In the future, this functionality may be changed/improved.
+1. Branch creation/deletion and tag creation/deletion events will not trigger an update. Only pushes to an existing branch will trigger an update.
+1. Pushes in quick succession to a branch will queue subsequent updates. Once a build completes, the most recent commit will begin building and the other queued builds will be skipped.
 
 ## Add or Remove GitHub Repositories
 

docs/docs/cloud/reference/api/openapi.json

@@ -28,6 +28,14 @@
     {
       "name": "Store",
       "description": "Store is an API for managing persistent key-value store (long-term memory) that is available from any thread."
+    },
+    {
+      "name": "MCP",
+      "description": "Model Context Protocol related endpoints for exposing an agent as an MCP server."
+    },
+    {
+      "name": "System",
+      "description": "System endpoints for health checks, metrics, and server information."
     }
   ],
   "paths": {
@@ -149,6 +157,59 @@
         }
       }
     },
+    "/assistants/count": {
+      "post": {
+        "tags": [
+          "Assistants"
+        ],
+        "summary": "Count Assistants",
+        "description": "Get the count of assistants matching the specified criteria.",
+        "operationId": "count_assistants_assistants_count_post",
+        "requestBody": {
+          "content": {
+            "application/json": {
+              "schema": {
+                "$ref": "#/components/schemas/AssistantCountRequest"
+              }
+            }
+          },
+          "required": true
+        },
+        "responses": {
+          "200": {
+            "description": "Success",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "type": "integer",
+                  "title": "Count"
+                }
+              }
+            }
+          },
+          "404": {
+            "description": "Not Found",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/ErrorResponse"
+                }
+              }
+            }
+          },
+          "422": {
+            "description": "Validation Error",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/ErrorResponse"
+                }
+              }
+            }
+          }
+        }
+      }
+    },
     "/assistants/{assistant_id}": {
       "get": {
         "tags": [
@@ -805,6 +866,59 @@
         }
       }
     },
+    "/threads/count": {
+      "post": {
+        "tags": [
+          "Threads"
+        ],
+        "summary": "Count Threads",
+        "description": "Get the count of threads matching the specified criteria.",
+        "operationId": "count_threads_threads_count_post",
+        "requestBody": {
+          "content": {
+            "application/json": {
+              "schema": {
+                "$ref": "#/components/schemas/ThreadCountRequest"
+              }
+            }
+          },
+          "required": true
+        },
+        "responses": {
+          "200": {
+            "description": "Success",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "type": "integer",
+                  "title": "Count"
+                }
+              }
+            }
+          },
+          "404": {
+            "description": "Not Found",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/ErrorResponse"
+                }
+              }
+            }
+          },
+          "422": {
+            "description": "Validation Error",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/ErrorResponse"
+                }
+              }
+            }
+          }
+        }
+      }
+    },
     "/threads/{thread_id}/state": {
       "get": {
         "tags": [
@@ -1406,6 +1520,73 @@
         }
       }
     },
+    "/threads/{thread_id}/stream": {
+      "get": {
+        "tags": [
+          "Threads"
+        ],
+        "summary": "Join Thread Stream",
+        "description": "This endpoint streams output in real-time from a thread. The stream will include the output of each run executed sequentially on the thread and will remain open indefinitely. It is the responsibility of the calling client to close the connection.",
+        "operationId": "join_thread_stream_threads__thread_id__stream_get",
+        "parameters": [
+          {
+            "description": "The ID of the thread.",
+            "required": true,
+            "schema": {
+              "type": "string",
+              "format": "uuid",
+              "title": "Thread Id",
+              "description": "The ID of the thread."
+            },
+            "name": "thread_id",
+            "in": "path"
+          },
+          {
+            "required": false,
+            "schema": {
+              "type": "string",
+              "title": "Last Event ID",
+              "description": "The ID of the last event received. Used to resume streaming from a specific point. Pass '-' to resume from the beginning."
+            },
+            "name": "Last-Event-ID",
+            "in": "header"
+          }
+        ],
+        "responses": {
+          "200": {
+            "description": "Success",
+            "content": {
+              "text/event-stream": {
+                "schema": {
+                  "type": "string",
+                  "description": "The server will send a stream of events in SSE format.\n\n**Example event**:\n\nid: 1\n\nevent: message\n\ndata: {}"
+                }
+              }
+            }
+          },
+          "404": {
+            "description": "Not Found",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/ErrorResponse"
+                }
+              }
+            }
+          },
+          "422": {
+            "description": "Validation Error",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/ErrorResponse"
+                }
+              }
+            }
+          }
+        }
+      }
+    },
     "/threads/{thread_id}/runs": {
       "get": {
         "tags": [
@@ -1461,6 +1642,30 @@
             },
             "name": "status",
             "in": "query"
+          },
+          {
+            "required": false,
+            "schema": {
+              "type": "array",
+              "items": {
+                "type": "string",
+                "enum": [
+                  "run_id",
+                  "thread_id",
+                  "assistant_id",
+                  "created_at",
+                  "updated_at",
+                  "status",
+                  "metadata",
+                  "kwargs",
+                  "multitask_strategy"
+                ]
+              },
+              "title": "Select",
+              "description": "Specify which fields to return. If not provided, all fields are returned."
+            },
+            "name": "select",
+            "in": "query"
           }
         ],
         "responses": {
@@ -2312,6 +2517,59 @@
         }
       }
     },
+    "/runs/crons/count": {
+      "post": {
+        "tags": [
+          "Crons (Plus tier)"
+        ],
+        "summary": "Count Crons",
+        "description": "Get the count of crons matching the specified criteria.",
+        "operationId": "count_crons_runs_crons_count_post",
+        "requestBody": {
+          "content": {
+            "application/json": {
+              "schema": {
+                "$ref": "#/components/schemas/CronCountRequest"
+              }
+            }
+          },
+          "required": true
+        },
+        "responses": {
+          "200": {
+            "description": "Success",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "type": "integer",
+                  "title": "Count"
+                }
+              }
+            }
+          },
+          "404": {
+            "description": "Not Found",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/ErrorResponse"
+                }
+              }
+            }
+          },
+          "422": {
+            "description": "Validation Error",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/ErrorResponse"
+                }
+              }
+            }
+          }
+        }
+      }
+    },
     "/runs/stream": {
       "post": {
         "tags": [
@@ -2996,6 +3254,153 @@
           "MCP"
         ]
       }
+    },
+    "/info": {
+      "get": {
+        "tags": [
+          "System"
+        ],
+        "summary": "Server Information",
+        "description": "Get server version information, feature flags, and metadata.",
+        "operationId": "server_info_info_get",
+        "responses": {
+          "200": {
+            "description": "Success",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "type": "object",
+                  "properties": {
+                    "version": {
+                      "type": "string",
+                      "title": "Version",
+                      "description": "LangGraph API version"
+                    },
+                    "langgraph_py_version": {
+                      "type": "string",
+                      "title": "LangGraph Python Version",
+                      "description": "LangGraph Python library version"
+                    },
+                    "flags": {
+                      "type": "object",
+                      "title": "Feature Flags",
+                      "description": "Enabled features and capabilities"
+                    },
+                    "metadata": {
+                      "type": "object",
+                      "title": "Metadata",
+                      "description": "Server deployment metadata"
+                    }
+                  },
+                  "required": ["version", "langgraph_py_version", "flags", "metadata"],
+                  "title": "ServerInfo"
+                }
+              }
+            }
+          }
+        }
+      }
+    },
+    "/metrics": {
+      "get": {
+        "tags": [
+          "System"
+        ],
+        "summary": "System Metrics",
+        "description": "Get system metrics in Prometheus or JSON format for monitoring and observability.",
+        "operationId": "system_metrics_metrics_get",
+        "parameters": [
+          {
+            "name": "format",
+            "in": "query",
+            "required": false,
+            "schema": {
+              "type": "string",
+              "enum": ["prometheus", "json"],
+              "default": "prometheus",
+              "title": "Output Format",
+              "description": "Response format: prometheus (default) or json"
+            }
+          }
+        ],
+        "responses": {
+          "200": {
+            "description": "Success",
+            "content": {
+              "text/plain": {
+                "schema": {
+                  "type": "string",
+                  "title": "Prometheus Metrics",
+                  "description": "Metrics in Prometheus exposition format"
+                }
+              },
+              "application/json": {
+                "schema": {
+                  "type": "object",
+                  "title": "JSON Metrics",
+                  "description": "Metrics in JSON format including queue stats, worker stats, and HTTP metrics"
+                }
+              }
+            }
+          }
+        }
+      }
+    },
+    "/ok": {
+      "get": {
+        "tags": [
+          "System"
+        ],
+        "summary": "Health Check",
+        "description": "Check the health status of the server. Optionally check database connectivity.",
+        "operationId": "health_check_ok_get",
+        "parameters": [
+          {
+            "name": "check_db",
+            "in": "query",
+            "required": false,
+            "schema": {
+              "type": "integer",
+              "enum": [0, 1],
+              "default": 0,
+              "title": "Check Database",
+              "description": "Whether to check database connectivity (0=false, 1=true)"
+            }
+          }
+        ],
+        "responses": {
+          "200": {
+            "description": "Success",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "type": "object",
+                  "properties": {
+                    "ok": {
+                      "type": "boolean",
+                      "const": true,
+                      "title": "OK",
+                      "description": "Indicates the server is healthy"
+                    }
+                  },
+                  "required": ["ok"],
+                  "title": "HealthResponse"
+                }
+              }
+            }
+          },
+          "500": {
+            "description": "Internal Server Error",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/ErrorResponse"
+                }
+              }
+            }
+          }
+        }
+      }
     }
   },
   "components": {
@@ -3035,6 +3440,11 @@
             "title": "Config",
             "description": "The assistant config."
           },
+          "context": {
+            "type": "object",
+            "title": "Context",
+            "description": "Static context added to the assistant."
+          },
           "created_at": {
             "type": "string",
             "format": "date-time",
@@ -3100,6 +3510,11 @@
             "title": "Config",
             "description": "Configuration to use for the graph. Useful when graph is configurable and you want to create different assistants based on different configurations."
           },
+          "context": {
+            "type": "object",
+            "title": "Context",
+            "description": "Static context added to the assistant."
+          },
           "metadata": {
             "type": "object",
             "title": "Metadata",
@@ -3148,6 +3563,11 @@
             "title": "Config",
             "description": "Configuration to use for the graph. Useful when graph is configurable and you want to update the assistant's configuration."
           },
+          "context": {
+            "type": "object",
+            "title": "Context",
+            "description": "Static context added to the assistant."
+          },
           "metadata": {
             "type": "object",
             "title": "Metadata",
@@ -3209,6 +3629,12 @@
             "title": "Cron Id",
             "description": "The ID of the cron."
           },
+          "assistant_id": {
+            "type": ["string", "null"],
+            "format": "uuid",
+            "title": "Assistant Id",
+            "description": "The ID of the assistant."
+          },
           "thread_id": {
             "type": "string",
             "format": "uuid",
@@ -3238,10 +3664,26 @@
             "title": "Updated At",
             "description": "The last time the cron was updated."
           },
+          "user_id": {
+            "type": ["string", "null"],
+            "title": "User Id",
+            "description": "The ID of the user."
+          },
           "payload": {
             "type": "object",
             "title": "Payload",
             "description": "The run payload to use for creating new run."
+          },
+          "next_run_date": {
+            "type": ["string", "null"],
+            "format": "date-time",
+            "title": "Next Run Date",
+            "description": "The next run date of the cron."
+          },
+          "metadata": {
+            "type": "object",
+            "title": "Metadata",
+            "description": "The cron metadata."
           }
         },
         "type": "object",
@@ -3326,6 +3768,11 @@
             "title": "Config",
             "description": "The configuration for the assistant."
           },
+          "context": {
+            "type": "object",
+            "title": "Context",
+            "description": "Static context added to the assistant."
+          },
           "webhook": {
             "type": "string",
             "maxLength": 65536,
@@ -3380,7 +3827,7 @@
             ],
             "title": "Multitask Strategy",
             "description": "Multitask strategy to use. Must be one of 'reject', 'interrupt', 'rollback', or 'enqueue'.",
-            "default": "reject"
+            "default": "enqueue"
           }
         },
         "type": "object",
@@ -3397,7 +3844,7 @@
             "type": "string",
             "format": "uuid",
             "title": "Assistant Id",
-            "description": "The assistant ID or graph name to search for."
+            "description": "The assistant ID or graph name to filter by using exact match."
           },
           "thread_id": {
             "type": "string",
@@ -3433,6 +3880,28 @@
             "description": "The order to sort by.",
             "default": "desc",
             "enum": ["asc", "desc"]
+          },
+          "select": {
+            "type": "array",
+            "items": {
+              "type": "string",
+              "enum": [
+                "cron_id",
+                "assistant_id",
+                "thread_id",
+                "end_time",
+                "schedule",
+                "created_at",
+                "updated_at",
+                "user_id",
+                "payload",
+                "next_run_date",
+                "metadata",
+                "now"
+              ]
+            },
+            "title": "Select",
+            "description": "Specify which fields to return. If not provided, all fields are returned."
           }
         },
         "type": "object",
@@ -3440,6 +3909,25 @@
         "title": "CronSearch",
         "description": "Payload for listing crons"
       },
+      "CronCountRequest": {
+        "properties": {
+          "assistant_id": {
+            "type": "string",
+            "format": "uuid",
+            "title": "Assistant Id",
+            "description": "The assistant ID or graph name to search for."
+          },
+          "thread_id": {
+            "type": "string",
+            "format": "uuid",
+            "title": "Thread Id",
+            "description": "The thread ID to search for."
+          }
+        },
+        "type": "object",
+        "title": "CronCountRequest",
+        "description": "Payload for counting crons"
+      },
       "GraphSchema": {
         "properties": {
           "graph_id": {
@@ -3466,13 +3954,17 @@
             "type": "object",
             "title": "Config Schema",
             "description": "The schema for the graph config. Missing if unable to generate JSON schema from graph."
+          },
+          "context_schema": {
+            "type": "object",
+            "title": "Context Schema",
+            "description": "The schema for the graph context. Missing if unable to generate JSON schema from graph."
           }
         },
         "type": "object",
         "required": [
           "graph_id",
-          "state_schema",
-          "config_schema"
+          "state_schema"
         ],
         "title": "GraphSchema",
         "description": "Defines the structure and properties of a graph."
@@ -3498,14 +3990,18 @@
             "type": "object",
             "title": "Config Schema",
             "description": "The schema for the graph config. Missing if unable to generate JSON schema from graph."
+          },
+          "context_schema": {
+            "type": "object",
+            "title": "Context Schema",
+            "description": "The schema for the graph context. Missing if unable to generate JSON schema from graph."
           }
         },
         "type": "object",
         "required": [
           "input_schema",
           "output_schema",
-          "state_schema",
-          "config_schema"
+          "state_schema"
         ],
         "title": "GraphSchemaNoId",
         "description": "Defines the structure and properties of a graph without an ID."
@@ -3516,7 +4012,7 @@
           "$ref": "#/components/schemas/GraphSchemaNoId"
         },
         "title": "Subgraphs",
-        "description": "Map of graph name to graph schema metadata (`input_schema`, `output_schema`, `state_schema`, `config_schema`)."
+        "description": "Map of graph name to graph schema metadata (`input_schema`, `output_schema`, `state_schema`, `config_schema`, `context_schema`)."
       },
       "Run": {
         "properties": {
@@ -3766,6 +4262,11 @@
             "title": "Config",
             "description": "The configuration for the assistant."
           },
+          "context": {
+            "type": "object",
+            "title": "Context",
+            "description": "Static context added to the assistant."
+          },
           "webhook": {
             "type": "string",
             "maxLength": 65536,
@@ -3819,6 +4320,8 @@
                     "values",
                     "messages",
                     "messages-tuple",
+                    "tasks",
+                    "checkpoints",
                     "updates",
                     "events",
                     "debug",
@@ -3833,6 +4336,8 @@
                   "values",
                   "messages",
                   "messages-tuple",
+                  "tasks",
+                  "checkpoints",
                   "updates",
                   "events",
                   "debug",
@@ -3886,7 +4391,7 @@
             ],
             "title": "Multitask Strategy",
             "description": "Multitask strategy to use. Must be one of 'reject', 'interrupt', 'rollback', or 'enqueue'.",
-            "default": "reject"
+            "default": "enqueue"
           },
           "if_not_exists": {
             "type": "string",
@@ -4005,6 +4510,11 @@
             "title": "Config",
             "description": "The configuration for the assistant."
           },
+          "context": {
+            "type": "object",
+            "title": "Context",
+            "description": "Static context added to the assistant."
+          },
           "webhook": {
             "type": "string",
             "maxLength": 65536,
@@ -4058,6 +4568,8 @@
                     "values",
                     "messages",
                     "messages-tuple",
+                    "tasks",
+                    "checkpoints",
                     "updates",
                     "events",
                     "debug",
@@ -4072,6 +4584,8 @@
                   "values",
                   "messages",
                   "messages-tuple",
+                  "tasks",
+                  "checkpoints",
                   "updates",
                   "events",
                   "debug",
@@ -4191,12 +4705,49 @@
             ],
             "title": "Sort Order",
             "description": "The order to sort by."
+          },
+          "select": {
+            "type": "array",
+            "items": {
+              "type": "string",
+              "enum": [
+                "assistant_id",
+                "graph_id", 
+                "name",
+                "description",
+                "config",
+                "context",
+                "created_at",
+                "updated_at",
+                "metadata",
+                "version"
+              ]
+            },
+            "title": "Select",
+            "description": "Specify which fields to return. If not provided, all fields are returned."
           }
         },
         "type": "object",
         "title": "AssistantSearchRequest",
         "description": "Payload for listing assistants."
       },
+      "AssistantCountRequest": {
+        "properties": {
+          "metadata": {
+            "type": "object",
+            "title": "Metadata",
+            "description": "Metadata to filter by. Exact match filter for each KV pair."
+          },
+          "graph_id": {
+            "type": "string",
+            "title": "Graph Id",
+            "description": "The ID of the graph to filter by. The graph ID is normally set in your langgraph.json configuration."
+          }
+        },
+        "type": "object",
+        "title": "AssistantCountRequest",
+        "description": "Payload for counting assistants."
+      },
       "AssistantVersionsSearchRequest": {
         "properties": {
           "metadata": {
@@ -4281,12 +4832,59 @@
             ],
             "title": "Sort Order",
             "description": "Sort order."
+          },
+          "select": {
+            "type": "array",
+            "items": {
+              "type": "string",
+              "enum": [
+                "thread_id",
+                "created_at",
+                "updated_at",
+                "metadata",
+                "config",
+                "context",
+                "status",
+                "values",
+                "interrupts"
+              ]
+            },
+            "title": "Select",
+            "description": "Specify which fields to return. If not provided, all fields are returned."
           }
         },
         "type": "object",
         "title": "ThreadSearchRequest",
         "description": "Payload for listing threads."
       },
+      "ThreadCountRequest": {
+        "properties": {
+          "metadata": {
+            "type": "object",
+            "title": "Metadata",
+            "description": "Thread metadata to filter on."
+          },
+          "values": {
+            "type": "object",
+            "title": "Values",
+            "description": "State values to filter on."
+          },
+          "status": {
+            "type": "string",
+            "enum": [
+              "idle",
+              "busy",
+              "interrupted",
+              "error"
+            ],
+            "title": "Status",
+            "description": "Thread status to filter on."
+          }
+        },
+        "type": "object",
+        "title": "ThreadCountRequest",
+        "description": "Payload for counting threads."
+      },
       "Thread": {
         "properties": {
           "thread_id": {
@@ -4312,6 +4910,11 @@
             "title": "Metadata",
             "description": "The thread metadata."
           },
+          "config": {
+            "type": "object",
+            "title": "Config",
+            "description": "The thread config."
+          },
           "status": {
             "type": "string",
             "enum": [
@@ -4327,6 +4930,11 @@
             "type": "object",
             "title": "Values",
             "description": "The current state of the thread."
+          },
+          "interrupts": {
+            "type": "object",
+            "title": "Interrupts",
+            "description": "The current interrupts of the thread."
           }
         },
         "type": "object",
@@ -4476,7 +5084,9 @@
                 },
                 "interrupts": {
                   "type": "array",
-                  "items": {}
+                  "items": {
+                    "$ref": "#/components/schemas/Interrupt"
+                  }
                 },
                 "checkpoint": {
                   "$ref": "#/components/schemas/CheckpointConfig",
@@ -4509,6 +5119,12 @@
           "parent_checkpoint": {
             "type": "object",
             "title": "Parent Checkpoint"
+          },
+          "interrupts": {
+            "type": "array",
+            "items": {
+              "$ref": "#/components/schemas/Interrupt"
+            }
           }
         },
         "type": "object",
@@ -4527,7 +5143,7 @@
             "type": "integer",
             "title": "Limit",
             "description": "The maximum number of states to return.",
-            "default": 10,
+            "default": 1,
             "maximum": 1000,
             "minimum": 1
           },
@@ -4954,6 +5570,24 @@
             }
           }
         }
+      },
+      "Interrupt": {
+        "type": "object",
+        "properties": {
+          "id": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "value": {
+            "type": "object"
+          }
+        },
+        "title": "Interrupt",
+        "required": [
+          "value"
+        ]
       }
     }
   }

docs/docs/concepts/low_level.md

@@ -1040,7 +1040,7 @@ def node_a(state: State, runtime: Runtime[ContextSchema]):
     ...
 ```
 
-See [this guide](../how-tos/graph-api.ipynb#add-runtime-configuration) for a full breakdown on configuration.
+See [this guide](../how-tos/graph-api.md#add-runtime-configuration) for a full breakdown on configuration.
 :::
 
 :::js

docs/docs/concepts/persistence.md

@@ -315,7 +315,8 @@ In our example, the output of `get_state_history` will look like this:
         tasks=(),
     ),
     StateSnapshot(
-        values={'foo': 'a', 'bar': ['a']}, next=('node_b',),
+        values={'foo': 'a', 'bar': ['a']},
+        next=('node_b',),
         config={'configurable': {'thread_id': '1', 'checkpoint_ns': '', 'checkpoint_id': '1ef663ba-28f9-6ec4-8001-31981c2c39f8'}},
         metadata={'source': 'loop', 'writes': {'node_a': {'foo': 'a', 'bar': ['a']}}, 'step': 1},
         created_at='2024-08-29T19:19:38.819946+00:00',

docs/docs/concepts/plans.md

@@ -12,7 +12,7 @@ There are three different plans for using it.
 
 - **Developer**: All [LangSmith](https://smith.langchain.com/) users have access to this plan. You can sign up for this plan simply by creating a LangSmith account. This gives you access to the [local deployment](./deployment_options.md#free-deployment) option.
 - **Plus**: All [LangSmith](https://smith.langchain.com/) users with a [Plus account](https://docs.smith.langchain.com/administration/pricing) have access to this plan. You can sign up for this plan simply by upgrading your LangSmith account to the Plus plan type. This gives you access to the [Cloud](./deployment_options.md#cloud-saas) deployment option.
-- **Enterprise**: This is separate from LangSmith plans. You can sign up for this plan by contacting sales@langchain.dev. This gives you access to all [deployment options](./deployment_options.md).
+- **Enterprise**: This is separate from LangSmith plans. You can sign up for this plan by [contacting our sales team](https://www.langchain.com/contact-sales). This gives you access to all [deployment options](./deployment_options.md).
 
 
 ## Plan Details

docs/overrides/main.html

@@ -360,5 +360,5 @@ j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src=
 {% endblock %}
 
 {% block announce %}
-<strong>LangGraph Platform docs have moved!</strong> Find the LangGraph Platform docs at the new <a href="https://docs.langchain.com/langgraph-platform" target="_blank">LangChain Docs</a> site.
+Our new LangChain Academy Course Deep Research with LangGraph is now live! <a href="https://academy.langchain.com/courses/deep-research-with-langgraph/?utm_medium=internal&utm_source=docs&utm_campaign=q3-2025_deep-research-course_co" target="_blank">Enroll for free</a>.
 {% endblock %}

libs/checkpoint/tests/test_redis_cache.py

@@ -161,9 +161,7 @@ class TestRedisCache:
     async def test_async_operations(self):
         """Test async set and get operations with sync Redis client."""
         # Create sync Redis client and cache (like main integration tests)
-        client = redis.Redis(
-            host="localhost", port=6379, db=1, decode_responses=False
-        )
+        client = redis.Redis(host="localhost", port=6379, db=1, decode_responses=False)
         try:
             client.ping()
         except Exception:
@@ -189,9 +187,7 @@ class TestRedisCache:
     async def test_async_clear(self):
         """Test async clear operations with sync Redis client."""
         # Create sync Redis client and cache (like main integration tests)
-        client = redis.Redis(
-            host="localhost", port=6379, db=1, decode_responses=False
-        )
+        client = redis.Redis(host="localhost", port=6379, db=1, decode_responses=False)
         try:
             client.ping()
         except Exception:

libs/cli/Makefile

@@ -4,8 +4,9 @@
 # TESTING AND COVERAGE
 ######################
 
+TEST?= "tests/unit_tests"
 test:
-	uv run pytest tests/unit_tests
+	uv run pytest $(TEST)
 test-integration:
 	uv run pytest tests/integration_tests
 

libs/cli/examples/.env.example

@@ -1,10 +1,3 @@
 OPENAI_API_KEY=placeholder
 ANTHROPIC_API_KEY=placeholder
 TAVILY_API_KEY=placeholder
-LANGCHAIN_TRACING_V2=false
-LANGCHAIN_ENDPOINT=placeholder
-LANGCHAIN_API_KEY=placeholder
-LANGCHAIN_PROJECT=placeholder
-LANGGRAPH_AUTH_TYPE=noop
-LANGSMITH_AUTH_ENDPOINT=placeholder
-LANGSMITH_TENANT_ID=placeholder

libs/cli/generate_schema.py

@@ -163,14 +163,7 @@ def generate_schema():
 
     # Add enum constraint for python_version
     if "python_version" in python_schema["properties"]:
-        python_schema["properties"]["python_version"]["enum"] = ["3.11", "3.12"]
-
-    # Add enum constraint for image_distro
-    if "image_distro" in python_schema["properties"]:
-        python_schema["properties"]["image_distro"]["anyOf"] = [
-            {"type": "string", "enum": ["debian", "wolfi"]},
-            {"type": "null"},
-        ]
+        python_schema["properties"]["python_version"]["enum"] = ["3.11", "3.12", "3.13"]
 
     # Create Node.js schema with node_version
     node_schema = {

libs/cli/langgraph_cli/__init__.py

@@ -0,0 +1 @@
+__version__ = "0.4.0"

libs/cli/langgraph_cli/config.py

@@ -17,6 +17,9 @@ DEFAULT_PYTHON_VERSION = "3.11"
 DEFAULT_IMAGE_DISTRO = "debian"
 
 
+Distros = Literal["debian", "wolfi", "bullseye", "bookworm"]
+
+
 class TTLConfig(TypedDict, total=False):
     """Configuration for TTL (time-to-live) behavior in the store."""
 
@@ -354,6 +357,8 @@ class HttpConfig(TypedDict, total=False):
 
     You can include or exclude headers as configurable values to condition your
     agent's behavior or permissions on a request's headers."""
+    logging_headers: Optional[ConfigurableHeaderConfig]
+    """Optional. Defines which headers are excluded from logging."""
 
 
 class Config(TypedDict, total=False):
@@ -369,6 +374,13 @@ class Config(TypedDict, total=False):
     Must be >= 20 if provided.
     """
 
+    api_version: Optional[str]
+    """Optional. Which semantic version of the LangGraph API server to use.
+    
+    Defaults to latest. Check the
+    [changelog](https://docs.langchain.com/langgraph-platform/langgraph-server-changelog)
+    for more information."""
+
     _INTERNAL_docker_tag: Optional[str]
     """Optional. Internal use only.
     """
@@ -378,10 +390,11 @@ class Config(TypedDict, total=False):
     
     Defaults to langchain/langgraph-api or langchain/langgraphjs-api."""
 
-    image_distro: Optional[str]
+    image_distro: Optional[Distros]
     """Optional. Linux distribution for the base image.
     
-    Must be either 'debian' or 'wolfi'. If omitted, defaults to 'debian'.
+    Must be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.
+    If omitted, defaults to 'debian' ('latest').
     """
 
     pip_config_file: Optional[str]
@@ -587,13 +600,28 @@ def validate_config(config: Config) -> Config:
     )
 
     image_distro = config.get("image_distro", DEFAULT_IMAGE_DISTRO)
+    internal_docker_tag = config.get("_INTERNAL_docker_tag")
+    api_version = config.get("api_version")
+    if internal_docker_tag:
+        if api_version:
+            raise click.UsageError(
+                "Cannot specify both _INTERNAL_docker_tag and api_version."
+            )
+    if api_version:
+        try:
+            parts = tuple(map(int, api_version.split("-")[0].split(".")))
+            if len(parts) > 3:
+                raise ValueError(
+                    "Version must be major or major.minor or major.minor.patch."
+                )
+        except TypeError:
+            raise click.UsageError(f"Invalid version format: {api_version}") from None
 
     config = {
         "node_version": node_version,
         "python_version": python_version,
         "pip_config_file": config.get("pip_config_file"),
         "pip_installer": config.get("pip_installer", "auto"),
-        "_INTERNAL_docker_tag": config.get("_INTERNAL_docker_tag"),
         "base_image": config.get("base_image"),
         "image_distro": image_distro,
         "dependencies": config.get("dependencies", []),
@@ -608,6 +636,10 @@ def validate_config(config: Config) -> Config:
         "ui_config": config.get("ui_config"),
         "keep_pkg_tools": config.get("keep_pkg_tools"),
     }
+    if internal_docker_tag:
+        config["_INTERNAL_docker_tag"] = internal_docker_tag
+    if api_version:
+        config["api_version"] = api_version
 
     if config.get("node_version"):
         node_version = config["node_version"]
@@ -644,17 +676,17 @@ def validate_config(config: Config) -> Config:
                 "Add at least one dependency to 'dependencies' list."
             )
 
-    if not config["graphs"]:
+    if not config.get("graphs"):
         raise click.UsageError(
             "No graphs found in config. Add at least one graph to 'graphs' dictionary."
         )
 
     # Validate image_distro config
     if image_distro := config.get("image_distro"):
-        if image_distro not in ["debian", "wolfi"]:
+        if image_distro not in Distros.__args__:
             raise click.UsageError(
                 f"Invalid image_distro: '{image_distro}'. "
-                "Must be either 'debian' or 'wolfi'."
+                "Must be one of 'debian', 'bullseye', or 'bookworm'."
             )
 
     if pip_installer := config.get("pip_installer"):
@@ -1465,6 +1497,7 @@ def docker_tag(
     base_image: Optional[str] = None,
     api_version: Optional[str] = None,
 ) -> str:
+    api_version = api_version or config.get("api_version")
     base_image = base_image or default_base_image(config)
 
     image_distro = config.get("image_distro")
@@ -1473,9 +1506,6 @@ def docker_tag(
     if config.get("_INTERNAL_docker_tag"):
         return f"{base_image}:{config['_INTERNAL_docker_tag']}"
 
-    if "/langgraph-server" in base_image:
-        return f"{base_image}-py{config['python_version']}"
-
     # Build the standard tag format
     language, version = None, None
     if config.get("node_version") and not config.get("python_version"):
@@ -1488,6 +1518,8 @@ def docker_tag(
     # Prepend API version if provided
     if api_version:
         full_tag = f"{api_version}-{language}{version_distro_tag}"
+    elif "/langgraph-server" in base_image and version_distro_tag not in base_image:
+        return f"{base_image}-{language}{version_distro_tag}"
     else:
         full_tag = version_distro_tag
 

libs/cli/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-cli"
-version = "0.3.6"
+dynamic = ["version"]
 description = "CLI for interacting with LangGraph API"
 authors = []
 requires-python = ">=3.9"
@@ -15,11 +15,12 @@ dependencies = [
     "click>=8.1.7",
     "langgraph-sdk>=0.1.0 ; python_version >= '3.11'",
 ]
-
+[tool.hatch.version]
+path = "langgraph_cli/__init__.py"
 [project.optional-dependencies]
 inmem = [
-    "langgraph-api>=0.2.67,<0.3.0 ; python_version >= '3.11'",
-    "langgraph-runtime-inmem>=0.6.0 ; python_version >= '3.11'",
+    "langgraph-api>=0.3,<0.5.0 ; python_version >= '3.11'",
+    "langgraph-runtime-inmem>=0.7 ; python_version >= '3.11'",
     "python-dotenv>=0.8.0",
 ]
 

libs/cli/schemas/schema.json

@@ -15,7 +15,8 @@
               "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"
+                "3.12",
+                "3.13"
               ]
             },
             "pip_config_file": {
@@ -40,6 +41,17 @@
               ],
               "description": "Optional. Internal use only.\n"
             },
+            "api_version": {
+              "anyOf": [
+                {
+                  "type": "string"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Which semantic version of the LangGraph API server to use.\n\nDefaults to latest. Check the\nfor more information.\n"
+            },
             "auth": {
               "anyOf": [
                 {
@@ -122,8 +134,9 @@
             "image_distro": {
               "anyOf": [
                 {
-                  "type": "string",
                   "enum": [
+                    "bookworm",
+                    "bullseye",
                     "debian",
                     "wolfi"
                   ]
@@ -132,7 +145,7 @@
                   "type": "null"
                 }
               ],
-              "description": "Optional. Linux distribution for the base image.\n\nMust be either 'debian' or 'wolfi'. If omitted, defaults to 'debian'.\n"
+              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
             },
             "keep_pkg_tools": {
               "anyOf": [
@@ -221,6 +234,17 @@
               ],
               "description": "Optional. Internal use only.\n"
             },
+            "api_version": {
+              "anyOf": [
+                {
+                  "type": "string"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Which semantic version of the LangGraph API server to use.\n\nDefaults to latest. Check the\nfor more information.\n"
+            },
             "auth": {
               "anyOf": [
                 {
@@ -313,7 +337,7 @@
                   "type": "null"
                 }
               ],
-              "description": "Optional. Linux distribution for the base image.\n\nMust be either 'debian' or 'wolfi'. If omitted, defaults to 'debian'.\n"
+              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
             },
             "keep_pkg_tools": {
               "anyOf": [
@@ -552,6 +576,17 @@
         "disable_threads": {
           "type": "boolean",
           "description": "Optional. If True, /threads routes are removed.\n\nDefault is False.\n"
+        },
+        "logging_headers": {
+          "anyOf": [
+            {
+              "$ref": "#/$defs/ConfigurableHeaderConfig"
+            },
+            {
+              "type": "null"
+            }
+          ],
+          "description": "Optional. Defines which headers are excluded from logging."
         }
       },
       "required": []

libs/cli/schemas/schema.v0.json

@@ -15,7 +15,8 @@
               "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"
+                "3.12",
+                "3.13"
               ]
             },
             "pip_config_file": {
@@ -40,6 +41,17 @@
               ],
               "description": "Optional. Internal use only.\n"
             },
+            "api_version": {
+              "anyOf": [
+                {
+                  "type": "string"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Which semantic version of the LangGraph API server to use.\n\nDefaults to latest. Check the\nfor more information.\n"
+            },
             "auth": {
               "anyOf": [
                 {
@@ -122,8 +134,9 @@
             "image_distro": {
               "anyOf": [
                 {
-                  "type": "string",
                   "enum": [
+                    "bookworm",
+                    "bullseye",
                     "debian",
                     "wolfi"
                   ]
@@ -132,7 +145,7 @@
                   "type": "null"
                 }
               ],
-              "description": "Optional. Linux distribution for the base image.\n\nMust be either 'debian' or 'wolfi'. If omitted, defaults to 'debian'.\n"
+              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
             },
             "keep_pkg_tools": {
               "anyOf": [
@@ -221,6 +234,17 @@
               ],
               "description": "Optional. Internal use only.\n"
             },
+            "api_version": {
+              "anyOf": [
+                {
+                  "type": "string"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "description": "Optional. Which semantic version of the LangGraph API server to use.\n\nDefaults to latest. Check the\nfor more information.\n"
+            },
             "auth": {
               "anyOf": [
                 {
@@ -313,7 +337,7 @@
                   "type": "null"
                 }
               ],
-              "description": "Optional. Linux distribution for the base image.\n\nMust be either 'debian' or 'wolfi'. If omitted, defaults to 'debian'.\n"
+              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
             },
             "keep_pkg_tools": {
               "anyOf": [
@@ -552,6 +576,17 @@
         "disable_threads": {
           "type": "boolean",
           "description": "Optional. If True, /threads routes are removed.\n\nDefault is False.\n"
+        },
+        "logging_headers": {
+          "anyOf": [
+            {
+              "$ref": "#/$defs/ConfigurableHeaderConfig"
+            },
+            {
+              "type": "null"
+            }
+          ],
+          "description": "Optional. Defines which headers are excluded from logging."
         }
       },
       "required": []

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

@@ -381,7 +381,9 @@ def test_dockerfile_command_with_base_image() -> None:
         assert save_path.exists()
         with open(save_path) as f:
             dockerfile = f.read()
-            assert re.match("FROM langchain/langgraph-server:0.2-py3.*", dockerfile)
+            assert re.match("FROM langchain/langgraph-server:0.2-py3.*", dockerfile), (
+                "\n".join(dockerfile.splitlines()[:3])
+            )
 
 
 def test_dockerfile_command_with_docker_compose() -> None:

libs/cli/tests/unit_tests/test_config.py

@@ -38,7 +38,6 @@ def test_validate_config():
     }
     actual_config = validate_config(expected_config)
     expected_config = {
-        "_INTERNAL_docker_tag": None,
         "base_image": None,
         "python_version": "3.11",
         "node_version": None,
@@ -61,7 +60,6 @@ def test_validate_config():
     # full config
     env = ".env"
     expected_config = {
-        "_INTERNAL_docker_tag": None,
         "base_image": None,
         "python_version": "3.12",
         "node_version": None,
@@ -190,7 +188,6 @@ def test_validate_config_image_distro():
             }
         )
     assert "Invalid image_distro: 'ubuntu'" in str(exc_info.value)
-    assert "Must be either 'debian' or 'wolfi'" in str(exc_info.value)
 
     with pytest.raises(click.UsageError) as exc_info:
         validate_config(
@@ -1339,19 +1336,22 @@ def test_docker_tag_different_node_versions_with_distro():
         assert tag == expected_tag, f"Failed for Node.js {node_version}"
 
 
-def test_docker_tag_with_api_version():
+@pytest.mark.parametrize("in_config", [False, True])
+def test_docker_tag_with_api_version(in_config: bool):
     """Test docker_tag function with api_version parameter."""
 
     # Test 1: Python config with api_version and default distro
+    version = "0.2.74"
     config = validate_config(
         {
             "python_version": "3.11",
             "dependencies": ["."],
             "graphs": {"agent": "./agent.py:graph"},
+            "api_version": version if in_config else None,
         }
     )
-    tag = docker_tag(config, api_version="0.2.74")
-    assert tag == "langchain/langgraph-api:0.2.74-py3.11"
+    tag = docker_tag(config, api_version=version if not in_config else None)
+    assert tag == f"langchain/langgraph-api:{version}-py3.11"
 
     # Test 2: Python config with api_version and wolfi distro
     config = validate_config(
@@ -1360,20 +1360,22 @@ def test_docker_tag_with_api_version():
             "dependencies": ["."],
             "graphs": {"agent": "./agent.py:graph"},
             "image_distro": "wolfi",
+            "api_version": version if in_config else None,
         }
     )
-    tag = docker_tag(config, api_version="0.2.74")
-    assert tag == "langchain/langgraph-api:0.2.74-py3.12-wolfi"
+    tag = docker_tag(config, api_version=version if not in_config else None)
+    assert tag == f"langchain/langgraph-api:{version}-py3.12-wolfi"
 
     # Test 3: Node.js config with api_version and default distro
     config = validate_config(
         {
             "node_version": "20",
             "graphs": {"agent": "./agent.js:graph"},
+            "api_version": version if in_config else None,
         }
     )
-    tag = docker_tag(config, api_version="0.2.74")
-    assert tag == "langchain/langgraphjs-api:0.2.74-node20"
+    tag = docker_tag(config, api_version=version if not in_config else None)
+    assert tag == f"langchain/langgraphjs-api:{version}-node20"
 
     # Test 4: Node.js config with api_version and wolfi distro
     config = validate_config(
@@ -1381,10 +1383,11 @@ def test_docker_tag_with_api_version():
             "node_version": "20",
             "graphs": {"agent": "./agent.js:graph"},
             "image_distro": "wolfi",
+            "api_version": version if in_config else None,
         }
     )
-    tag = docker_tag(config, api_version="0.2.74")
-    assert tag == "langchain/langgraphjs-api:0.2.74-node20-wolfi"
+    tag = docker_tag(config, api_version=version if not in_config else None)
+    assert tag == f"langchain/langgraphjs-api:{version}-node20-wolfi"
 
     # Test 5: Custom base image with api_version
     config = validate_config(
@@ -1393,10 +1396,15 @@ def test_docker_tag_with_api_version():
             "dependencies": ["."],
             "graphs": {"agent": "./agent.py:graph"},
             "base_image": "my-registry/custom-image",
+            "api_version": version if in_config else None,
         }
     )
-    tag = docker_tag(config, base_image="my-registry/custom-image", api_version="1.0.0")
-    assert tag == "my-registry/custom-image:1.0.0-py3.11"
+    tag = docker_tag(
+        config,
+        base_image="my-registry/custom-image",
+        api_version=version if not in_config else None,
+    )
+    assert tag == f"my-registry/custom-image:{version}-py3.11"
 
     # Test 6: api_version with different Python versions
     for python_version in ["3.11", "3.12", "3.13"]:
@@ -1405,10 +1413,11 @@ def test_docker_tag_with_api_version():
                 "python_version": python_version,
                 "dependencies": ["."],
                 "graphs": {"agent": "./agent.py:graph"},
+                "api_version": version if in_config else None,
             }
         )
-        tag = docker_tag(config, api_version="0.2.74")
-        assert tag == f"langchain/langgraph-api:0.2.74-py{python_version}"
+        tag = docker_tag(config, api_version=version if not in_config else None)
+        assert tag == f"langchain/langgraph-api:{version}-py{python_version}"
 
     # Test 7: Without api_version should work as before
     config = validate_config(
@@ -1428,10 +1437,11 @@ def test_docker_tag_with_api_version():
             "node_version": "20",
             "dependencies": ["."],
             "graphs": {"python": "./agent.py:graph", "js": "./agent.js:graph"},
+            "api_version": version if in_config else None,
         }
     )
-    tag = docker_tag(config, api_version="0.2.74")
-    assert tag == "langchain/langgraph-api:0.2.74-py3.11"
+    tag = docker_tag(config, api_version=version if not in_config else None)
+    assert tag == f"langchain/langgraph-api:{version}-py3.11"
 
     # Test 9: api_version with _INTERNAL_docker_tag should ignore api_version
     config = validate_config(
@@ -1451,12 +1461,15 @@ def test_docker_tag_with_api_version():
             "python_version": "3.11",
             "dependencies": ["."],
             "graphs": {"agent": "./agent.py:graph"},
+            "api_version": version if in_config else None,
         }
     )
     tag = docker_tag(
-        config, base_image="langchain/langgraph-server:0.2", api_version="0.2.74"
+        config,
+        base_image="langchain/langgraph-server",
+        api_version=version if not in_config else None,
     )
-    assert tag == "langchain/langgraph-server:0.2-py3.11"
+    assert tag == f"langchain/langgraph-server:{version}-py3.11"
 
 
 def test_config_to_docker_with_api_version():

libs/cli/uv.lock

@@ -18,16 +18,16 @@ wheels = [
 
 [[package]]
 name = "anyio"
-version = "4.9.0"
+version = "4.10.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "idna", marker = "python_full_version >= '3.11'" },
     { name = "sniffio", marker = "python_full_version >= '3.11'" },
     { name = "typing-extensions", marker = "python_full_version >= '3.11' and python_full_version < '3.13'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/95/7d/4c1bd541d4dffa1b52bd83fb8527089e097a106fc90b467a7313b105f840/anyio-4.9.0.tar.gz", hash = "sha256:673c0c244e15788651a4ff38710fea9675823028a6f08a5eda409e0c9840a028", size = 190949, upload-time = "2025-03-17T00:02:54.77Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/f1/b4/636b3b65173d3ce9a38ef5f0522789614e590dab6a8d505340a4efe4c567/anyio-4.10.0.tar.gz", hash = "sha256:3f3fae35c96039744587aa5b8371e7e8e603c0702999535961dd336026973ba6", size = 213252, upload-time = "2025-08-04T08:54:26.451Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/a1/ee/48ca1a7c89ffec8b6a0c5d02b89c305671d5ffd8d3c94acf8b8c408575bb/anyio-4.9.0-py3-none-any.whl", hash = "sha256:9f76d541cad6e36af7beb62e978876f3b41e3e04f2c1fbf0884604c0a9c4d93c", size = 100916, upload-time = "2025-03-17T00:02:52.713Z" },
+    { url = "https://files.pythonhosted.org/packages/6f/12/e5e0282d673bb9746bacfb6e2dba8719989d3660cdb2ea79aee9a9651afb/anyio-4.10.0-py3-none-any.whl", hash = "sha256:60e474ac86736bbfd6f210f7a61218939c318f43f9972497381f1c5e930ed3d1", size = 107213, upload-time = "2025-08-04T08:54:24.882Z" },
 ]
 
 [[package]]
@@ -53,11 +53,11 @@ wheels = [
 
 [[package]]
 name = "certifi"
-version = "2025.7.14"
+version = "2025.8.3"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/b3/76/52c535bcebe74590f296d6c77c86dabf761c41980e1347a2422e4aa2ae41/certifi-2025.7.14.tar.gz", hash = "sha256:8ea99dbdfaaf2ba2f9bac77b9249ef62ec5218e7c2b2e903378ed5fccf765995", size = 163981, upload-time = "2025-07-14T03:29:28.449Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/dc/67/960ebe6bf230a96cda2e0abcf73af550ec4f090005363542f0765df162e0/certifi-2025.8.3.tar.gz", hash = "sha256:e564105f78ded564e3ae7c923924435e1daa7463faeab5bb932bc53ffae63407", size = 162386, upload-time = "2025-08-03T03:07:47.08Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/4f/52/34c6cf5bb9285074dc3531c437b3919e825d976fde097a7a73f79e726d03/certifi-2025.7.14-py3-none-any.whl", hash = "sha256:6b31f564a415d79ee77df69d757bb49a5bb53bd9f756cbbe24394ffd6fc1f4b2", size = 162722, upload-time = "2025-07-14T03:29:26.863Z" },
+    { url = "https://files.pythonhosted.org/packages/e5/48/1549795ba7742c948d2ad169c1c8cdbae65bc450d6cd753d124b17c8cd32/certifi-2025.8.3-py3-none-any.whl", hash = "sha256:f6c12493cfb1b06ba2ff328595af9350c65d6644968e5d3a2ffd78699af217a5", size = 161216, upload-time = "2025-08-03T03:07:45.777Z" },
 ]
 
 [[package]]
@@ -131,76 +131,77 @@ wheels = [
 
 [[package]]
 name = "charset-normalizer"
-version = "3.4.2"
+version = "3.4.3"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/e4/33/89c2ced2b67d1c2a61c19c6751aa8902d46ce3dacb23600a283619f5a12d/charset_normalizer-3.4.2.tar.gz", hash = "sha256:5baececa9ecba31eff645232d59845c07aa030f0c81ee70184a90d35099a0e63", size = 126367, upload-time = "2025-05-02T08:34:42.01Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/83/2d/5fd176ceb9b2fc619e63405525573493ca23441330fcdaee6bef9460e924/charset_normalizer-3.4.3.tar.gz", hash = "sha256:6fce4b8500244f6fcb71465d4a4930d132ba9ab8e71a7859e6a5d59851068d14", size = 122371, upload-time = "2025-08-09T07:57:28.46Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/95/28/9901804da60055b406e1a1c5ba7aac1276fb77f1dde635aabfc7fd84b8ab/charset_normalizer-3.4.2-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:7c48ed483eb946e6c04ccbe02c6b4d1d48e51944b6db70f697e089c193404941", size = 201818, upload-time = "2025-05-02T08:31:46.725Z" },
-    { url = "https://files.pythonhosted.org/packages/d9/9b/892a8c8af9110935e5adcbb06d9c6fe741b6bb02608c6513983048ba1a18/charset_normalizer-3.4.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b2d318c11350e10662026ad0eb71bb51c7812fc8590825304ae0bdd4ac283acd", size = 144649, upload-time = "2025-05-02T08:31:48.889Z" },
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libs/langgraph/bench/react_agent.py

@@ -10,7 +10,7 @@ from langchain_core.outputs import ChatGeneration, ChatResult
 from langchain_core.tools import StructuredTool
 
 from langgraph.checkpoint.base import BaseCheckpointSaver
-from langgraph.prebuilt.chat_agent_executor import create_agent
+from langgraph.prebuilt.chat_agent_executor import create_react_agent
 from langgraph.pregel import Pregel
 
 
@@ -60,7 +60,7 @@ def react_agent(n_tools: int, checkpointer: Optional[BaseCheckpointSaver]) -> Pr
         ]
     )
 
-    return create_agent(model, [tool], checkpointer=checkpointer)
+    return create_react_agent(model, [tool], checkpointer=checkpointer)
 
 
 if __name__ == "__main__":

libs/langgraph/langgraph/pregel/remote.py

@@ -25,9 +25,17 @@ from langgraph_sdk.client import (
     get_client,
     get_sync_client,
 )
-from langgraph_sdk.schema import Checkpoint, ThreadState
-from langgraph_sdk.schema import Command as CommandSDK
-from langgraph_sdk.schema import StreamMode as StreamModeSDK
+from langgraph_sdk.schema import (
+    Checkpoint,
+    QueryParamTypes,
+    ThreadState,
+)
+from langgraph_sdk.schema import (
+    Command as CommandSDK,
+)
+from langgraph_sdk.schema import (
+    StreamMode as StreamModeSDK,
+)
 from typing_extensions import Self
 
 from langgraph._internal._config import merge_configs
@@ -208,6 +216,8 @@ class RemoteGraph(PregelProtocol):
         config: RunnableConfig | None = None,
         *,
         xray: int | bool = False,
+        headers: dict[str, str] | None = None,
+        params: QueryParamTypes | None = None,
     ) -> DrawableGraph:
         """Get graph by graph name.
 
@@ -226,6 +236,8 @@ class RemoteGraph(PregelProtocol):
         graph = sync_client.assistants.get_graph(
             assistant_id=self.assistant_id,
             xray=xray,
+            headers=headers,
+            params=params,
         )
         return DrawableGraph(
             nodes=self._get_drawable_nodes(graph),
@@ -237,6 +249,8 @@ class RemoteGraph(PregelProtocol):
         config: RunnableConfig | None = None,
         *,
         xray: int | bool = False,
+        headers: dict[str, str] | None = None,
+        params: QueryParamTypes | None = None,
     ) -> DrawableGraph:
         """Get graph by graph name.
 
@@ -255,6 +269,8 @@ class RemoteGraph(PregelProtocol):
         graph = await client.assistants.get_graph(
             assistant_id=self.assistant_id,
             xray=xray,
+            headers=headers,
+            params=params,
         )
         return DrawableGraph(
             nodes=self._get_drawable_nodes(graph),
@@ -376,7 +392,12 @@ class RemoteGraph(PregelProtocol):
         return sanitized
 
     def get_state(
-        self, config: RunnableConfig, *, subgraphs: bool = False
+        self,
+        config: RunnableConfig,
+        *,
+        subgraphs: bool = False,
+        headers: dict[str, str] | None = None,
+        params: QueryParamTypes | None = None,
     ) -> StateSnapshot:
         """Get the state of a thread.
 
@@ -388,6 +409,8 @@ class RemoteGraph(PregelProtocol):
             config: A `RunnableConfig` that includes `thread_id` in the
                 `configurable` field.
             subgraphs: Include subgraphs in the state.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
 
         Returns:
             The latest state of the thread.
@@ -399,11 +422,18 @@ class RemoteGraph(PregelProtocol):
             thread_id=merged_config["configurable"]["thread_id"],
             checkpoint=self._get_checkpoint(merged_config),
             subgraphs=subgraphs,
+            headers=headers,
+            params=params,
         )
         return self._create_state_snapshot(state)
 
     async def aget_state(
-        self, config: RunnableConfig, *, subgraphs: bool = False
+        self,
+        config: RunnableConfig,
+        *,
+        subgraphs: bool = False,
+        headers: dict[str, str] | None = None,
+        params: QueryParamTypes | None = None,
     ) -> StateSnapshot:
         """Get the state of a thread.
 
@@ -415,6 +445,8 @@ class RemoteGraph(PregelProtocol):
             config: A `RunnableConfig` that includes `thread_id` in the
                 `configurable` field.
             subgraphs: Include subgraphs in the state.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
 
         Returns:
             The latest state of the thread.
@@ -426,6 +458,8 @@ class RemoteGraph(PregelProtocol):
             thread_id=merged_config["configurable"]["thread_id"],
             checkpoint=self._get_checkpoint(merged_config),
             subgraphs=subgraphs,
+            headers=headers,
+            params=params,
         )
         return self._create_state_snapshot(state)
 
@@ -436,6 +470,8 @@ class RemoteGraph(PregelProtocol):
         filter: dict[str, Any] | None = None,
         before: RunnableConfig | None = None,
         limit: int | None = None,
+        headers: dict[str, str] | None = None,
+        params: QueryParamTypes | None = None,
     ) -> Iterator[StateSnapshot]:
         """Get the state history of a thread.
 
@@ -460,6 +496,8 @@ class RemoteGraph(PregelProtocol):
             before=self._get_checkpoint(before),
             metadata=filter,
             checkpoint=self._get_checkpoint(merged_config),
+            headers=headers,
+            params=params,
         )
         for state in states:
             yield self._create_state_snapshot(state)
@@ -471,6 +509,8 @@ class RemoteGraph(PregelProtocol):
         filter: dict[str, Any] | None = None,
         before: RunnableConfig | None = None,
         limit: int | None = None,
+        headers: dict[str, str] | None = None,
+        params: QueryParamTypes | None = None,
     ) -> AsyncIterator[StateSnapshot]:
         """Get the state history of a thread.
 
@@ -482,6 +522,8 @@ class RemoteGraph(PregelProtocol):
             filter: Metadata to filter on.
             before: A `RunnableConfig` that includes checkpoint metadata.
             limit: Max number of states to return.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
 
         Returns:
             States of the thread.
@@ -495,6 +537,8 @@ class RemoteGraph(PregelProtocol):
             before=self._get_checkpoint(before),
             metadata=filter,
             checkpoint=self._get_checkpoint(merged_config),
+            headers=headers,
+            params=params,
         )
         for state in states:
             yield self._create_state_snapshot(state)
@@ -518,6 +562,9 @@ class RemoteGraph(PregelProtocol):
         config: RunnableConfig,
         values: dict[str, Any] | Any | None,
         as_node: str | None = None,
+        *,
+        headers: dict[str, str] | None = None,
+        params: QueryParamTypes | None = None,
     ) -> RunnableConfig:
         """Update the state of a thread.
 
@@ -540,6 +587,8 @@ class RemoteGraph(PregelProtocol):
             values=values,
             as_node=as_node,
             checkpoint=self._get_checkpoint(merged_config),
+            headers=headers,
+            params=params,
         )
         return self._get_config(response["checkpoint"])
 
@@ -548,6 +597,9 @@ class RemoteGraph(PregelProtocol):
         config: RunnableConfig,
         values: dict[str, Any] | Any | None,
         as_node: str | None = None,
+        *,
+        headers: dict[str, str] | None = None,
+        params: QueryParamTypes | None = None,
     ) -> RunnableConfig:
         """Update the state of a thread.
 
@@ -570,6 +622,8 @@ class RemoteGraph(PregelProtocol):
             values=values,
             as_node=as_node,
             checkpoint=self._get_checkpoint(merged_config),
+            headers=headers,
+            params=params,
         )
         return self._get_config(response["checkpoint"])
 
@@ -634,6 +688,7 @@ class RemoteGraph(PregelProtocol):
         interrupt_after: All | Sequence[str] | None = None,
         subgraphs: bool = False,
         headers: dict[str, str] | None = None,
+        params: QueryParamTypes | None = None,
         **kwargs: Any,
     ) -> Iterator[dict[str, Any] | Any]:
         """Create a run and stream the results.
@@ -678,9 +733,10 @@ class RemoteGraph(PregelProtocol):
             interrupt_after=interrupt_after,
             stream_subgraphs=subgraphs or stream is not None,
             if_not_exists="create",
-            headers=_merge_tracing_headers(headers)
-            if self.distributed_tracing
-            else headers,
+            headers=(
+                _merge_tracing_headers(headers) if self.distributed_tracing else headers
+            ),
+            params=params,
             **kwargs,
         ):
             # split mode and ns
@@ -741,6 +797,7 @@ class RemoteGraph(PregelProtocol):
         interrupt_after: All | Sequence[str] | None = None,
         subgraphs: bool = False,
         headers: dict[str, str] | None = None,
+        params: QueryParamTypes | None = None,
         **kwargs: Any,
     ) -> AsyncIterator[dict[str, Any] | Any]:
         """Create a run and stream the results.
@@ -785,9 +842,10 @@ class RemoteGraph(PregelProtocol):
             interrupt_after=interrupt_after,
             stream_subgraphs=subgraphs or stream is not None,
             if_not_exists="create",
-            headers=_merge_tracing_headers(headers)
-            if self.distributed_tracing
-            else headers,
+            headers=(
+                _merge_tracing_headers(headers) if self.distributed_tracing else headers
+            ),
+            params=params,
             **kwargs,
         ):
             # split mode and ns
@@ -862,6 +920,7 @@ class RemoteGraph(PregelProtocol):
         interrupt_before: All | Sequence[str] | None = None,
         interrupt_after: All | Sequence[str] | None = None,
         headers: dict[str, str] | None = None,
+        params: QueryParamTypes | None = None,
         **kwargs: Any,
     ) -> dict[str, Any] | Any:
         """Create a run, wait until it finishes and return the final state.
@@ -884,6 +943,7 @@ class RemoteGraph(PregelProtocol):
             interrupt_after=interrupt_after,
             headers=headers,
             stream_mode="values",
+            params=params,
             **kwargs,
         ):
             pass
@@ -900,6 +960,7 @@ class RemoteGraph(PregelProtocol):
         interrupt_before: All | Sequence[str] | None = None,
         interrupt_after: All | Sequence[str] | None = None,
         headers: dict[str, str] | None = None,
+        params: QueryParamTypes | None = None,
         **kwargs: Any,
     ) -> dict[str, Any] | Any:
         """Create a run, wait until it finishes and return the final state.
@@ -922,6 +983,7 @@ class RemoteGraph(PregelProtocol):
             interrupt_after=interrupt_after,
             headers=headers,
             stream_mode="values",
+            params=params,
             **kwargs,
         ):
             pass
@@ -934,11 +996,11 @@ class RemoteGraph(PregelProtocol):
 def _merge_tracing_headers(headers: dict[str, str] | None) -> dict[str, str] | None:
     if rt := ls.get_current_run_tree():
         tracing_headers = rt.to_headers()
-        baggage = tracing_headers.pop("baggage")
         if headers:
             if "baggage" in headers:
-                baggage = headers["baggage"] + "," + baggage
-            tracing_headers["baggage"] = baggage
+                tracing_headers["baggage"] = (
+                    f"{headers['baggage']},{tracing_headers['baggage']}"
+                )
             headers.update(tracing_headers)
         else:
             headers = tracing_headers

libs/langgraph/langgraph/types.py

@@ -507,6 +507,7 @@ def interrupt(value: Any) -> Any:
     # find previous resume values
     if scratchpad.resume:
         if idx < len(scratchpad.resume):
+            conf[CONFIG_KEY_SEND]([(RESUME, scratchpad.resume)])
             return scratchpad.resume[idx]
     # find current resume value
     v = scratchpad.get_null_resume(True)

libs/langgraph/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph"
-version = "0.6.4"
+version = "0.6.6"
 description = "Building stateful, multi-actor applications with LLMs"
 authors = []
 requires-python = ">=3.9"
@@ -14,7 +14,7 @@ license-files = ['LICENSE']
 dependencies = [
     "langchain-core>=0.1",
     "langgraph-checkpoint>=2.1.0,<3.0.0",
-    "langgraph-sdk>=0.2.0,<0.3.0",
+    "langgraph-sdk>=0.2.2,<0.3.0",
     "langgraph-prebuilt>=0.6.0,<0.7.0",
     "xxhash>=3.5.0",
     "pydantic>=2.7.4",

libs/langgraph/tests/conftest.py

@@ -69,7 +69,7 @@ def cache(request: pytest.FixtureRequest) -> Iterator[BaseCache]:
     elif request.param == "redis":
         # Get worker ID for parallel test isolation
         worker_id = getattr(request.config, "workerinput", {}).get("workerid", "master")
-        
+
         redis_client = redis.Redis(
             host="localhost", port=6379, db=0, decode_responses=False
         )

libs/langgraph/tests/test_pregel.py

@@ -4805,7 +4805,10 @@ def test_interrupt_subgraph(sync_checkpointer: BaseCheckpointSaver):
     assert graph.invoke(Command(resume="bar"), thread1)
 
 
-def test_interrupt_multiple(sync_checkpointer: BaseCheckpointSaver):
+@pytest.mark.parametrize("resume_style", ["null", "map"])
+def test_interrupt_multiple(
+    sync_checkpointer: BaseCheckpointSaver, resume_style: Literal["null", "map"]
+):
     class State(TypedDict):
         my_key: Annotated[str, operator.add]
 
@@ -4821,7 +4824,8 @@ def test_interrupt_multiple(sync_checkpointer: BaseCheckpointSaver):
     graph = builder.compile(checkpointer=sync_checkpointer)
     thread1 = {"configurable": {"thread_id": "1"}}
 
-    assert [e for e in graph.stream({"my_key": "DE", "market": "DE"}, thread1)] == [
+    result = [e for e in graph.stream({"my_key": "DE", "market": "DE"}, thread1)]
+    assert result == [
         {
             "__interrupt__": (
                 Interrupt(
@@ -4832,12 +4836,19 @@ def test_interrupt_multiple(sync_checkpointer: BaseCheckpointSaver):
         }
     ]
 
-    assert [
+    result = [
         event
         for event in graph.stream(
-            Command(resume="answer 1", update={"my_key": " foofoo "}), thread1
+            Command(
+                resume="answer 1"
+                if resume_style == "null"
+                else {result[0]["__interrupt__"][0].id: "answer 1"},
+                update={"my_key": " foofoo "},
+            ),
+            thread1,
         )
-    ] == [
+    ]
+    assert result == [
         {
             "__interrupt__": (
                 Interrupt(
@@ -4851,7 +4862,13 @@ def test_interrupt_multiple(sync_checkpointer: BaseCheckpointSaver):
     assert [
         event
         for event in graph.stream(
-            Command(resume="answer 2"), thread1, stream_mode="values"
+            Command(
+                resume="answer 2"
+                if resume_style == "null"
+                else {result[0]["__interrupt__"][0].id: "answer 2"}
+            ),
+            thread1,
+            stream_mode="values",
         )
     ] == [
         {"my_key": "DE foofoo "},

libs/langgraph/tests/test_remote_graph.py

@@ -1,6 +1,6 @@
 import re
 import sys
-from typing import Annotated, Union
+from typing import Annotated, Optional, Union
 from unittest.mock import AsyncMock, MagicMock
 
 import langsmith as ls
@@ -1183,7 +1183,10 @@ async def test_remote_graph_stream_messages_tuple(
 @pytest.mark.anyio
 @pytest.mark.parametrize("distributed_tracing", [False, True])
 @pytest.mark.parametrize("stream", [False, True])
-async def test_include_headers(distributed_tracing: bool, stream: bool):
+@pytest.mark.parametrize("headers", [None, {"foo": "bar"}])
+async def test_include_headers(
+    distributed_tracing: bool, stream: bool, headers: Optional[dict[str, str]]
+):
     mock_async_client = MagicMock()
     async_iter = MagicMock()
     return_value = [
@@ -1213,7 +1216,7 @@ async def test_include_headers(distributed_tracing: bool, stream: bool):
                 async for _ in remote_pregel.astream(
                     {"input": {"messages": [{"type": "human", "content": "hello"}]}},
                     config,
-                    headers={"foo": "bar"},
+                    headers=headers,
                 ):
                     pass
 
@@ -1221,12 +1224,14 @@ async def test_include_headers(distributed_tracing: bool, stream: bool):
                 await remote_pregel.ainvoke(
                     {"input": {"messages": [{"type": "human", "content": "hello"}]}},
                     config,
-                    headers={"foo": "bar"},
+                    headers=headers,
                 )
-    expected = {"foo": "bar"}
+    expected = headers.copy() if headers else None
     if distributed_tracing:
+        if expected is None:
+            expected = {}
         expected["langsmith-trace"] = AnyStr()
-        expected["baggage"] = AnyStr()
+        expected["baggage"] = AnyStr("langsmith-metadata=")
 
     assert astream_mock.call_args.kwargs["headers"] == expected
     stream_mock.assert_not_called()
@@ -1237,7 +1242,7 @@ async def test_include_headers(distributed_tracing: bool, stream: bool):
                 for _ in remote_pregel.stream(
                     {"input": {"messages": [{"type": "human", "content": "hello"}]}},
                     config,
-                    headers={"foo": "bar"},
+                    headers=headers,
                 ):
                     pass
 
@@ -1245,6 +1250,6 @@ async def test_include_headers(distributed_tracing: bool, stream: bool):
                 remote_pregel.invoke(
                     {"input": {"messages": [{"type": "human", "content": "hello"}]}},
                     config,
-                    headers={"foo": "bar"},
+                    headers=headers,
                 )
     assert stream_mock.call_args.kwargs["headers"] == expected

libs/prebuilt/langgraph/prebuilt/_internal/_typing.py

@@ -1,10 +0,0 @@
-from __future__ import annotations
-
-from typing import Awaitable, Callable, TypeVar, Union
-
-from typing_extensions import ParamSpec
-
-P = ParamSpec("P")
-R = TypeVar("R")
-
-SyncOrAsync = Callable[P, Union[R, Awaitable[R]]]

libs/prebuilt/langgraph/prebuilt/responses.py

@@ -1,397 +0,0 @@
-"""Types for setting agent response formats."""
-
-from __future__ import annotations
-
-import sys
-import uuid
-from dataclasses import dataclass, is_dataclass
-from typing import (
-    Any,
-    Callable,
-    Generic,
-    Iterable,
-    Literal,
-    TypeVar,
-    Union,
-    get_args,
-    get_origin,
-)
-
-from langchain_core.messages import AIMessage
-from langchain_core.tools import BaseTool, StructuredTool
-from pydantic import BaseModel, TypeAdapter
-from typing_extensions import Self, is_typeddict
-
-# Supported schema types: Pydantic models, dataclasses, TypedDict, JSON schema dicts
-SchemaT = TypeVar("SchemaT")
-
-
-if sys.version_info >= (3, 10):
-    from types import UnionType
-else:
-    UnionType = Union
-
-SchemaKind = Literal["pydantic", "dataclass", "typeddict", "json_schema"]
-
-
-class StructuredOutputError(Exception):
-    """Base class for structured output errors."""
-
-
-class MultipleStructuredOutputsError(StructuredOutputError):
-    """Raised when model returns multiple structured output tool calls when only one is expected."""
-
-    def __init__(self, tool_names: list[str]):
-        self.tool_names = tool_names
-        super().__init__(
-            f"Model incorrectly returned multiple structured responses ({', '.join(tool_names)}) when only one is expected."
-        )
-
-
-class StructuredOutputParsingError(StructuredOutputError):
-    """Raised when structured output tool call arguments fail to parse according to the schema."""
-
-    def __init__(self, tool_name: str, parse_error: Exception):
-        self.tool_name = tool_name
-        self.parse_error = parse_error
-        super().__init__(
-            f"Failed to parse structured output for tool '{tool_name}': {parse_error}."
-        )
-
-
-def _parse_with_schema(
-    schema: Union[type[SchemaT], dict], schema_kind: SchemaKind, data: dict[str, Any]
-) -> Any:
-    """Parse data using for any supported schema type.
-
-    Args:
-        schema: The schema type (Pydantic model, dataclass, or TypedDict)
-        data: The data to parse
-
-    Returns:
-        The parsed instance according to the schema type
-
-    Raises:
-        ValueError: If parsing fails
-    """
-    if schema_kind == "json_schema":
-        return data
-    else:
-        try:
-            adapter: TypeAdapter[SchemaT] = TypeAdapter(schema)
-            return adapter.validate_python(data)
-        except Exception as e:
-            schema_name = getattr(schema, "__name__", str(schema))
-            raise ValueError(f"Failed to parse data to {schema_name}: {e}") from e
-
-
-@dataclass(init=False)
-class _SchemaSpec(Generic[SchemaT]):
-    """Describes a structured output schema."""
-
-    schema: type[SchemaT]
-    """The schema for the response, can be a Pydantic model, dataclass, TypedDict, or JSON schema dict."""
-
-    name: str
-    """Name of the schema, used for tool calling.
-    
-    If not provided, the name will be the model name or "response_format" if it's a JSON schema.
-    """
-
-    description: str
-    """Custom description of the schema. 
-    
-    If not provided, provided will use the model's docstring.
-    """
-
-    schema_kind: SchemaKind
-    """The kind of schema."""
-
-    json_schema: dict[str, Any]
-    """JSON schema associated with the schema."""
-
-    strict: bool = False
-    """Whether to enforce strict validation of the schema."""
-
-    def __init__(
-        self,
-        schema: type[SchemaT],
-        *,
-        name: str | None = None,
-        description: str | None = None,
-        strict: bool = False,
-    ) -> None:
-        """Initialize SchemaSpec with schema and optional parameters."""
-        self.schema = schema
-
-        if name:
-            self.name = name
-        elif isinstance(schema, dict):
-            self.name = str(
-                schema.get("title", f"response_format_{str(uuid.uuid4())[:4]}")
-            )
-        else:
-            self.name = str(
-                getattr(schema, "__name__", f"response_format_{str(uuid.uuid4())[:4]}")
-            )
-
-        self.description = description or (
-            schema.get("description", "")
-            if isinstance(schema, dict)
-            else getattr(schema, "__doc__", None) or ""
-        )
-
-        self.strict = strict
-
-        if isinstance(schema, dict):
-            self.schema_kind = "json_schema"
-            self.json_schema = schema
-        elif isinstance(schema, type) and issubclass(schema, BaseModel):
-            self.schema_kind = "pydantic"
-            self.json_schema = schema.model_json_schema()
-        elif is_dataclass(schema):
-            self.schema_kind = "dataclass"
-            self.json_schema = TypeAdapter(schema).json_schema()
-        elif is_typeddict(schema):
-            self.schema_kind = "typeddict"
-            self.json_schema = TypeAdapter(schema).json_schema()
-        else:
-            raise ValueError(
-                f"Unsupported schema type: {type(schema)}. "
-                f"Supported types: Pydantic models, dataclasses, TypedDicts, and JSON schema dicts."
-            )
-
-
-@dataclass(init=False)
-class ToolOutput(Generic[SchemaT]):
-    """Use a tool calling strategy for model responses."""
-
-    schema: type[SchemaT]
-    """Schema for the tool calls."""
-
-    schema_specs: list[_SchemaSpec[SchemaT]]
-    """Schema specs for the tool calls."""
-
-    tool_message_content: str | None
-    """The content of the tool message to be returned when the model calls an artificial structured output tool."""
-
-    handle_errors: Union[
-        bool,
-        str,
-        type[Exception],
-        tuple[type[Exception], ...],
-        Callable[[Exception], str],
-    ]
-    """Error handling strategy for structured output via ToolOutput. Default is True.
-    
-    - True: Catch all errors with default error template
-    - str: Catch all errors with this custom message
-    - type[Exception]: Only catch this exception type with default message
-    - tuple[type[Exception], ...]: Only catch these exception types with default message
-    - Callable[[Exception], str]: Custom function that returns error message
-    - False: No retry, let exceptions propagate
-    """
-
-    def __init__(
-        self,
-        schema: type[SchemaT],
-        tool_message_content: str | None = None,
-        handle_errors: Union[
-            bool,
-            str,
-            type[Exception],
-            tuple[type[Exception], ...],
-            Callable[[Exception], str],
-        ] = True,
-    ) -> None:
-        """Initialize ToolOutput with schemas, tool message content, and error handling strategy."""
-        self.schema = schema
-        self.tool_message_content = tool_message_content
-        self.handle_errors = handle_errors
-
-        def _iter_variants(schema: Any) -> Iterable[Any]:
-            """Yield leaf variants from Union and JSON Schema oneOf."""
-
-            if get_origin(schema) in (UnionType, Union):
-                for arg in get_args(schema):
-                    yield from _iter_variants(arg)
-                return
-
-            if isinstance(schema, dict) and "oneOf" in schema:
-                for sub in schema.get("oneOf", []):
-                    yield from _iter_variants(sub)
-                return
-
-            yield schema
-
-        self.schema_specs = [_SchemaSpec(s) for s in _iter_variants(schema)]
-
-
-@dataclass(init=False)
-class NativeOutput(Generic[SchemaT]):
-    """Use the model provider's native structured output method."""
-
-    schema: type[SchemaT]
-    """Schema for native mode."""
-
-    schema_spec: _SchemaSpec[SchemaT]
-    """Schema spec for native mode."""
-
-    def __init__(
-        self,
-        schema: type[SchemaT],
-    ) -> None:
-        self.schema = schema
-        self.schema_spec = _SchemaSpec(schema)
-
-    def to_model_kwargs(self) -> dict[str, Any]:
-        # OpenAI:
-        # - see https://platform.openai.com/docs/guides/structured-outputs
-        response_format = {
-            "type": "json_schema",
-            "json_schema": {
-                "name": self.schema_spec.name,
-                "schema": self.schema_spec.json_schema,
-            },
-        }
-        return {"response_format": response_format}
-
-
-@dataclass
-class OutputToolBinding(Generic[SchemaT]):
-    """Information for tracking structured output tool metadata.
-
-    This contains all necessary information to handle structured responses
-    generated via tool calls, including the original schema, its type classification,
-    and the corresponding tool implementation used by the tools strategy.
-    """
-
-    schema: type[SchemaT]
-    """The original schema provided for structured output (Pydantic model, dataclass, TypedDict, or JSON schema dict)."""
-
-    schema_kind: SchemaKind
-    """Classification of the schema type for proper response construction."""
-
-    tool: BaseTool
-    """LangChain tool instance created from the schema for model binding."""
-
-    @classmethod
-    def from_schema_spec(cls, schema_spec: _SchemaSpec[SchemaT]) -> Self:
-        """Create an OutputToolBinding instance from a SchemaSpec.
-
-        Args:
-            schema_spec: The SchemaSpec to convert
-
-        Returns:
-            An OutputToolBinding instance with the appropriate tool created
-        """
-        return cls(
-            schema=schema_spec.schema,
-            schema_kind=schema_spec.schema_kind,
-            tool=StructuredTool(
-                args_schema=schema_spec.json_schema,
-                name=schema_spec.name,
-                description=schema_spec.description,
-            ),
-        )
-
-    def parse(self, tool_args: dict[str, Any]) -> SchemaT:
-        """Parse tool arguments according to the schema.
-
-        Args:
-            tool_args: The arguments from the tool call
-
-        Returns:
-            The parsed response according to the schema type
-
-        Raises:
-            ValueError: If parsing fails
-        """
-        return _parse_with_schema(self.schema, self.schema_kind, tool_args)
-
-
-@dataclass
-class NativeOutputBinding(Generic[SchemaT]):
-    """Information for tracking native structured output metadata.
-
-    This contains all necessary information to handle structured responses
-    generated via native provider output, including the original schema,
-    its type classification, and parsing logic for provider-enforced JSON.
-    """
-
-    schema: type[SchemaT]
-    """The original schema provided for structured output (Pydantic model, dataclass, TypedDict, or JSON schema dict)."""
-
-    schema_kind: SchemaKind
-    """Classification of the schema type for proper response construction."""
-
-    @classmethod
-    def from_schema_spec(cls, schema_spec: _SchemaSpec[SchemaT]) -> Self:
-        """Create a NativeOutputBinding instance from a SchemaSpec.
-
-        Args:
-            schema_spec: The SchemaSpec to convert
-
-        Returns:
-            A NativeOutputBinding instance for parsing native structured output
-        """
-        return cls(
-            schema=schema_spec.schema,
-            schema_kind=schema_spec.schema_kind,
-        )
-
-    def parse(self, response: AIMessage) -> SchemaT:
-        """Parse AIMessage content according to the schema.
-
-        Args:
-            response: The AI message containing the structured output
-
-        Returns:
-            The parsed response according to the schema
-
-        Raises:
-            ValueError: If text extraction, JSON parsing or schema validation fails
-        """
-        # Extract text content from AIMessage and parse as JSON
-        raw_text = self._extract_text_content_from_message(response)
-
-        import json
-
-        try:
-            data = json.loads(raw_text)
-        except Exception as e:
-            schema_name = getattr(self.schema, "__name__", "response_format")
-            raise ValueError(
-                f"Native structured output expected valid JSON for {schema_name}, but parsing failed: {e}."
-            ) from e
-
-        # Parse according to schema
-        return _parse_with_schema(self.schema, self.schema_kind, data)
-
-    def _extract_text_content_from_message(self, message: AIMessage) -> str:
-        """Extract text content from an AIMessage.
-
-        Args:
-            message: The AI message to extract text from
-
-        Returns:
-            The extracted text content
-        """
-        content = message.content
-        if isinstance(content, str):
-            return content
-        if isinstance(content, list):
-            parts: list[str] = []
-            for c in content:
-                if isinstance(c, dict):
-                    if c.get("type") == "text" and "text" in c:
-                        parts.append(str(c["text"]))
-                    elif "content" in c and isinstance(c["content"], str):
-                        parts.append(c["content"])
-                else:
-                    parts.append(str(c))
-            return "".join(parts)
-        return str(content)
-
-
-ResponseFormat = Union[ToolOutput[SchemaT], NativeOutput[SchemaT]]

libs/prebuilt/langgraph/prebuilt/tool_node.py

@@ -31,8 +31,6 @@ Typical Usage:
     ```
 """
 
-from __future__ import annotations
-
 import asyncio
 import inspect
 import json
@@ -70,7 +68,7 @@ from langchain_core.tools.base import (
     TOOL_MESSAGE_BLOCK_TYPES,
     get_all_basemodel_annotations,
 )
-from pydantic import BaseModel, ValidationError
+from pydantic import BaseModel
 from typing_extensions import Annotated, get_args, get_origin
 
 from langgraph._internal._runnable import RunnableCallable
@@ -83,8 +81,6 @@ INVALID_TOOL_NAME_ERROR_TEMPLATE = (
     "Error: {requested_tool} is not a valid tool, try one of [{available_tools}]."
 )
 TOOL_CALL_ERROR_TEMPLATE = "Error: {error}\n Please fix your mistakes."
-TOOL_EXECUTION_ERROR_TEMPLATE = "Error executing tool '{tool_name}' with kwargs {tool_kwargs} with error:\n {error}\n Please fix the error and try again."
-TOOL_INVOCATION_ERROR_TEMPLATE = "Error invoking tool '{tool_name}' with kwargs {tool_kwargs} with error:\n {error}\n Please fix the error and try again."
 
 
 def msg_content_output(output: Any) -> Union[str, list[dict]]:
@@ -126,30 +122,6 @@ def msg_content_output(output: Any) -> Union[str, list[dict]]:
             return str(output)
 
 
-class ToolInvocationError(Exception):
-    """Exception raised when a tool invocation fails due to invalid arguments."""
-
-    def __init__(self, tool_name: str, error: Exception, tool_kwargs: dict[str, Any]):
-        self.message = TOOL_INVOCATION_ERROR_TEMPLATE.format(
-            tool_name=tool_name, tool_kwargs=tool_kwargs, error=error
-        )
-        self.tool_name = tool_name
-        self.tool_kwargs = tool_kwargs
-        self.error = error
-        super().__init__(self.message)
-
-
-def _default_handle_tool_errors(e: Exception) -> str:
-    """Default error handler for tool errors.
-
-    If the tool is a tool invocation error, return its message.
-    Otherwise, raise the error.
-    """
-    if isinstance(e, ToolInvocationError):
-        return e.message
-    raise e
-
-
 def _handle_tool_error(
     e: Exception,
     *,
@@ -157,7 +129,6 @@ def _handle_tool_error(
         bool,
         str,
         Callable[..., str],
-        type[Exception],
         tuple[type[Exception], ...],
     ],
 ) -> str:
@@ -185,14 +156,12 @@ def _handle_tool_error(
         The tuple case is handled by the caller through exception type checking,
         not by this function directly.
     """
-    if isinstance(flag, (bool, tuple)) or (
-        isinstance(flag, type) and issubclass(flag, Exception)
-    ):
+    if isinstance(flag, (bool, tuple)):
         content = TOOL_CALL_ERROR_TEMPLATE.format(error=repr(e))
     elif isinstance(flag, str):
         content = flag
     elif callable(flag):
-        content = flag(e)  # type: ignore [assignment, call-arg]
+        content = flag(e)
     else:
         raise ValueError(
             f"Got unexpected type of `handle_tool_error`. Expected bool, str "
@@ -268,69 +237,39 @@ def _infer_handled_types(handler: Callable[..., str]) -> tuple[type[Exception],
 
 
 class ToolNode(RunnableCallable):
-    """A node for executing tools in LangGraph workflows.
+    """A node that runs the tools called in the last AIMessage.
 
-    Handles tool execution patterns including function calls, state injection,
-    persistent storage, and control flow. Manages parallel execution,
-    error handling.
+    It can be used either in StateGraph with a "messages" state key (or a custom key passed via ToolNode's 'messages_key').
+    If multiple tool calls are requested, they will be run in parallel. The output will be
+    a list of ToolMessages, one for each tool call.
 
-    Input Formats:
-        1. Graph state with `messages` key that has a list of messages:
-           - Common representation for agentic workflows
-           - Supports custom messages key via ``messages_key`` parameter
-
-        2. **Message List**: ``[AIMessage(..., tool_calls=[...])]``
-           - List of messages with tool calls in the last AIMessage
-
-        3. **Direct Tool Calls**: ``[{"name": "tool", "args": {...}, "id": "1", "type": "tool_call"}]``
-           - Bypasses message parsing for direct tool execution
-           - For programmatic tool invocation and testing
-
-    Output Formats:
-        Output format depends on input type and tool behavior:
-
-        **For Regular tools**:
-        - Dict input → ``{"messages": [ToolMessage(...)]}``
-        - List input → ``[ToolMessage(...)]``
-
-        **For Command tools**:
-        - Returns ``[Command(...)]`` or mixed list with regular tool outputs
-        - Commands can update state, trigger navigation, or send messages
+    Tool calls can also be passed directly as a list of `ToolCall` dicts.
 
     Args:
-        tools: A sequence of tools that can be invoked by this node. Supports:
-            - **BaseTool instances**: Tools with schemas and metadata
-            - **Plain functions**: Automatically converted to tools with inferred schemas
+        tools: A sequence of tools that can be invoked by this node. Tools can be
+            BaseTool instances or plain functions that will be converted to tools.
         name: The name identifier for this node in the graph. Used for debugging
             and visualization. Defaults to "tools".
         tags: Optional metadata tags to associate with the node for filtering
             and organization. Defaults to None.
         handle_tool_errors: Configuration for error handling during tool execution.
-            Supports multiple strategies:
+            Defaults to True. Supports multiple strategies:
 
-            - **True**: Catch all errors and return a ToolMessage with the default
+            - True: Catch all errors and return a ToolMessage with the default
               error template containing the exception details.
-            - **str**: Catch all errors and return a ToolMessage with this custom
+            - str: Catch all errors and return a ToolMessage with this custom
               error message string.
-            - **type[Exception]**: Only catch exceptions with the specified type and return the default error message for it.
-            - **tuple[type[Exception], ...]**: Only catch exceptions with the specified
+            - tuple[type[Exception], ...]: Only catch exceptions of the specified
               types and return default error messages for them.
-            - **Callable[..., str]**: Catch exceptions matching the callable's signature
+            - Callable[..., str]: Catch exceptions matching the callable's signature
               and return the string result of calling it with the exception.
-            - **False**: Disable error handling entirely, allowing exceptions to
-              propagate.
-
-            Defaults to a callable that:
-                - catches tool invocation errors (due to invalid arguments provided by the model) and returns a descriptive error message
-                - ignores tool execution errors (they will be re-raised)
+            - False: Disable error handling entirely, allowing exceptions to propagate.
 
         messages_key: The key in the state dictionary that contains the message list.
-            This same key will be used for the output ToolMessages.
-            Defaults to "messages".
-            Allows custom state schemas with different message field names.
+            This same key will be used for the output ToolMessages. Defaults to "messages".
 
-    Examples:
-        Basic usage:
+    Example:
+        Basic usage with simple tools:
 
         ```python
         from langgraph.prebuilt import ToolNode
@@ -344,31 +283,38 @@ class ToolNode(RunnableCallable):
         tool_node = ToolNode([calculator])
         ```
 
-        State injection:
+        Custom error handling:
 
         ```python
-        from typing_extensions import Annotated
-        from langgraph.prebuilt import InjectedState
+        def handle_math_errors(e: ZeroDivisionError) -> str:
+            return "Cannot divide by zero!"
 
-        @tool
-        def context_tool(query: str, state: Annotated[dict, InjectedState]) -> str:
-            \"\"\"Some tool that uses state.\"\"\"
-            return f"Query: {query}, Messages: {len(state['messages'])}"
-
-        tool_node = ToolNode([context_tool])
+        tool_node = ToolNode([calculator], handle_tool_errors=handle_math_errors)
         ```
 
-        Error handling:
+        Direct tool call execution:
 
         ```python
-        def handle_errors(e: ValueError) -> str:
-            return "Invalid input provided"
-
-        tool_node = ToolNode([my_tool], handle_tool_errors=handle_errors)
+        tool_calls = [{"name": "calculator", "args": {"a": 5, "b": 3}, "id": "1", "type": "tool_call"}]
+        result = tool_node.invoke(tool_calls)
         ```
+
+    Note:
+        The ToolNode expects input in one of three formats:
+        1. A dictionary with a messages key containing a list of messages
+        2. A list of messages directly
+        3. A list of tool call dictionaries
+
+        When using message formats, the last message must be an AIMessage with
+        tool_calls populated. The node automatically extracts and processes these
+        tool calls concurrently.
+
+        For advanced use cases involving state injection or store access, tools
+        can be annotated with InjectedState or InjectedStore to receive graph
+        context automatically.
     """
 
-    name: str = "tools"
+    name: str = "ToolNode"
 
     def __init__(
         self,
@@ -377,8 +323,8 @@ class ToolNode(RunnableCallable):
         name: str = "tools",
         tags: Optional[list[str]] = None,
         handle_tool_errors: Union[
-            bool, str, Callable[..., str], type[Exception], tuple[type[Exception], ...]
-        ] = _default_handle_tool_errors,
+            bool, str, Callable[..., str], tuple[type[Exception], ...]
+        ] = True,
         messages_key: str = "messages",
     ) -> None:
         """Initialize the ToolNode with the provided tools and configuration.
@@ -391,24 +337,17 @@ class ToolNode(RunnableCallable):
             messages_key: State key containing messages.
         """
         super().__init__(self._func, self._afunc, name=name, tags=tags, trace=False)
-        self._tools_by_name: dict[str, BaseTool] = {}
-        self._tool_to_state_args: dict[str, dict[str, Optional[str]]] = {}
-        self._tool_to_store_arg: dict[str, Optional[str]] = {}
-        self._handle_tool_errors = handle_tool_errors
-        self._messages_key = messages_key
-        for tool in tools:
-            if not isinstance(tool, BaseTool):
-                tool_ = create_tool(cast(Type[BaseTool], tool))
-            else:
-                tool_ = tool
-            self._tools_by_name[tool_.name] = tool_
-            self._tool_to_state_args[tool_.name] = _get_state_args(tool_)
-            self._tool_to_store_arg[tool_.name] = _get_store_arg(tool_)
-
-    @property
-    def tools_by_name(self) -> dict[str, BaseTool]:
-        """Mapping from tool name to BaseTool instance."""
-        return self._tools_by_name
+        self.tools_by_name: dict[str, BaseTool] = {}
+        self.tool_to_state_args: dict[str, dict[str, Optional[str]]] = {}
+        self.tool_to_store_arg: dict[str, Optional[str]] = {}
+        self.handle_tool_errors = handle_tool_errors
+        self.messages_key = messages_key
+        for tool_ in tools:
+            if not isinstance(tool_, BaseTool):
+                tool_ = create_tool(tool_)
+            self.tools_by_name[tool_.name] = tool_
+            self.tool_to_state_args[tool_.name] = _get_state_args(tool_)
+            self.tool_to_store_arg[tool_.name] = _get_store_arg(tool_)
 
     def _func(
         self,
@@ -451,14 +390,14 @@ class ToolNode(RunnableCallable):
 
     def _combine_tool_outputs(
         self,
-        outputs: list[Union[ToolMessage, Command]],
+        outputs: list[ToolMessage],
         input_type: Literal["list", "dict", "tool_calls"],
     ) -> list[Union[Command, list[ToolMessage], dict[str, list[ToolMessage]]]]:
         # preserve existing behavior for non-command tool outputs for backwards
         # compatibility
         if not any(isinstance(output, Command) for output in outputs):
             # TypedDict, pydantic, dataclass, etc. should all be able to load from dict
-            return outputs if input_type == "list" else {self._messages_key: outputs}
+            return outputs if input_type == "list" else {self.messages_key: outputs}
 
         # LangGraph will automatically handle list of Command and non-command node
         # updates
@@ -486,7 +425,7 @@ class ToolNode(RunnableCallable):
                     combined_outputs.append(output)
             else:
                 combined_outputs.append(
-                    [output] if input_type == "list" else {self._messages_key: [output]}
+                    [output] if input_type == "list" else {self.messages_key: [output]}
                 )
 
         if parent_command:
@@ -498,19 +437,18 @@ class ToolNode(RunnableCallable):
         call: ToolCall,
         input_type: Literal["list", "dict", "tool_calls"],
         config: RunnableConfig,
-    ) -> Union[ToolMessage, Command]:
+    ) -> ToolMessage:
         """Run a single tool call synchronously."""
         if invalid_tool_message := self._validate_tool_call(call):
             return invalid_tool_message
-
         try:
             call_args = {**call, **{"type": "tool_call"}}
             tool = self.tools_by_name[call["name"]]
 
             try:
                 response = tool.invoke(call_args, config)
-            except ValidationError as exc:
-                raise ToolInvocationError(call["name"], exc, call["args"])
+            except NotImplementedError:
+                response = asyncio.run(tool.ainvoke(call_args, config))
 
         # GraphInterrupt is a special exception that will always be raised.
         # It can be triggered in the following scenarios,
@@ -522,27 +460,20 @@ class ToolNode(RunnableCallable):
         except GraphBubbleUp as e:
             raise e
         except Exception as e:
-            handled_types: tuple[type[Exception], ...]
-            if isinstance(self._handle_tool_errors, type) and issubclass(
-                self._handle_tool_errors, Exception
-            ):
-                handled_types = (self._handle_tool_errors,)
-            elif isinstance(self._handle_tool_errors, tuple):
-                handled_types = self._handle_tool_errors
-            elif callable(self._handle_tool_errors) and not isinstance(
-                self._handle_tool_errors, type
-            ):
-                handled_types = _infer_handled_types(self._handle_tool_errors)
+            if isinstance(self.handle_tool_errors, tuple):
+                handled_types: tuple = self.handle_tool_errors
+            elif callable(self.handle_tool_errors):
+                handled_types = _infer_handled_types(self.handle_tool_errors)
             else:
                 # default behavior is catching all exceptions
                 handled_types = (Exception,)
 
             # Unhandled
-            if not self._handle_tool_errors or not isinstance(e, handled_types):
+            if not self.handle_tool_errors or not isinstance(e, handled_types):
                 raise e
             # Handled
             else:
-                content = _handle_tool_error(e, flag=self._handle_tool_errors)
+                content = _handle_tool_error(e, flag=self.handle_tool_errors)
             return ToolMessage(
                 content=content,
                 name=call["name"],
@@ -567,19 +498,14 @@ class ToolNode(RunnableCallable):
         call: ToolCall,
         input_type: Literal["list", "dict", "tool_calls"],
         config: RunnableConfig,
-    ) -> Union[ToolMessage, Command]:
+    ) -> ToolMessage:
         """Run a single tool call asynchronously."""
         if invalid_tool_message := self._validate_tool_call(call):
             return invalid_tool_message
 
         try:
             call_args = {**call, **{"type": "tool_call"}}
-            tool = self.tools_by_name[call["name"]]
-
-            try:
-                response = await tool.ainvoke(call_args, config)
-            except ValidationError as exc:
-                raise ToolInvocationError(call["name"], exc, call["args"])
+            response = await self.tools_by_name[call["name"]].ainvoke(call_args, config)
 
         # GraphInterrupt is a special exception that will always be raised.
         # It can be triggered in the following scenarios,
@@ -591,27 +517,20 @@ class ToolNode(RunnableCallable):
         except GraphBubbleUp as e:
             raise e
         except Exception as e:
-            handled_types: tuple[type[Exception], ...]
-            if isinstance(self._handle_tool_errors, type) and issubclass(
-                self._handle_tool_errors, Exception
-            ):
-                handled_types = (self._handle_tool_errors,)
-            elif isinstance(self._handle_tool_errors, tuple):
-                handled_types = self._handle_tool_errors
-            elif callable(self._handle_tool_errors) and not isinstance(
-                self._handle_tool_errors, type
-            ):
-                handled_types = _infer_handled_types(self._handle_tool_errors)
+            if isinstance(self.handle_tool_errors, tuple):
+                handled_types: tuple = self.handle_tool_errors
+            elif callable(self.handle_tool_errors):
+                handled_types = _infer_handled_types(self.handle_tool_errors)
             else:
                 # default behavior is catching all exceptions
                 handled_types = (Exception,)
 
             # Unhandled
-            if not self._handle_tool_errors or not isinstance(e, handled_types):
+            if not self.handle_tool_errors or not isinstance(e, handled_types):
                 raise e
             # Handled
             else:
-                content = _handle_tool_error(e, flag=self._handle_tool_errors)
+                content = _handle_tool_error(e, flag=self.handle_tool_errors)
 
             return ToolMessage(
                 content=content,
@@ -650,11 +569,9 @@ class ToolNode(RunnableCallable):
             else:
                 input_type = "list"
                 messages = input
-        elif isinstance(input, dict) and (
-            messages := input.get(self._messages_key, [])
-        ):
+        elif isinstance(input, dict) and (messages := input.get(self.messages_key, [])):
             input_type = "dict"
-        elif messages := getattr(input, self._messages_key, []):
+        elif messages := getattr(input, self.messages_key, []):
             # Assume dataclass-like state that can coerce from dict
             input_type = "dict"
         else:
@@ -674,12 +591,10 @@ class ToolNode(RunnableCallable):
         return tool_calls, input_type
 
     def _validate_tool_call(self, call: ToolCall) -> Optional[ToolMessage]:
-        requested_tool = call["name"]
-        if requested_tool not in self.tools_by_name:
-            all_tool_names = list(self.tools_by_name.keys())
+        if (requested_tool := call["name"]) not in self.tools_by_name:
             content = INVALID_TOOL_NAME_ERROR_TEMPLATE.format(
                 requested_tool=requested_tool,
-                available_tools=", ".join(all_tool_names),
+                available_tools=", ".join(self.tools_by_name.keys()),
             )
             return ToolMessage(
                 content, name=requested_tool, tool_call_id=call["id"], status="error"
@@ -696,15 +611,15 @@ class ToolNode(RunnableCallable):
             BaseModel,
         ],
     ) -> ToolCall:
-        state_args = self._tool_to_state_args[tool_call["name"]]
+        state_args = self.tool_to_state_args[tool_call["name"]]
         if state_args and isinstance(input, list):
             required_fields = list(state_args.values())
             if (
                 len(required_fields) == 1
-                and required_fields[0] == self._messages_key
+                and required_fields[0] == self.messages_key
                 or required_fields[0] is None
             ):
-                input = {self._messages_key: input}
+                input = {self.messages_key: input}
             else:
                 err_msg = (
                     f"Invalid input to ToolNode. Tool {tool_call['name']} requires "
@@ -735,7 +650,7 @@ class ToolNode(RunnableCallable):
     def _inject_store(
         self, tool_call: ToolCall, store: Optional[BaseStore]
     ) -> ToolCall:
-        store_arg = self._tool_to_store_arg[tool_call["name"]]
+        store_arg = self.tool_to_store_arg[tool_call["name"]]
         if not store_arg:
             return tool_call
 
@@ -812,15 +727,15 @@ class ToolNode(RunnableCallable):
             # input type is dict when ToolNode is invoked with a dict input (e.g. {"messages": [AIMessage(..., tool_calls=[...])]})
             if input_type not in ("dict", "tool_calls"):
                 raise ValueError(
-                    f"Tools can provide a dict in Command.update only when using dict with '{self._messages_key}' key as ToolNode input, "
+                    f"Tools can provide a dict in Command.update only when using dict with '{self.messages_key}' key as ToolNode input, "
                     f"got: {command.update} for tool '{call['name']}'"
                 )
 
             updated_command = deepcopy(command)
             state_update = cast(dict[str, Any], updated_command.update) or {}
-            messages_update = state_update.get(self._messages_key, [])
+            messages_update = state_update.get(self.messages_key, [])
         elif isinstance(command.update, list):
-            # Input type is list when ToolNode is invoked with a list input (e.g. [AIMessage(..., tool_calls=[...])])
+            # input type is list when ToolNode is invoked with a list input (e.g. [AIMessage(..., tool_calls=[...])])
             if input_type != "list":
                 raise ValueError(
                     f"Tools can provide a list of messages in Command.update only when using list of messages as ToolNode input, "

libs/prebuilt/tests/__snapshots__/test_react_agent_graph.ambr

@@ -1,5 +1,5 @@
 # serializer version: 1
-# name: test_react_agent_graph_structure[None-None-tools0]
+# name: test_react_agent_graph_structure[None-None-None-tools0]
   '''
   graph TD;
   	__start__ --> agent;
@@ -7,7 +7,7 @@
   
   '''
 # ---
-# name: test_react_agent_graph_structure[None-None-tools1]
+# name: test_react_agent_graph_structure[None-None-None-tools1]
   '''
   graph TD;
   	__start__ --> agent;
@@ -17,7 +17,7 @@
   
   '''
 # ---
-# name: test_react_agent_graph_structure[None-pre_model_hook-tools0]
+# name: test_react_agent_graph_structure[None-None-pre_model_hook-tools0]
   '''
   graph TD;
   	__start__ --> pre_model_hook;
@@ -26,7 +26,7 @@
   
   '''
 # ---
-# name: test_react_agent_graph_structure[None-pre_model_hook-tools1]
+# name: test_react_agent_graph_structure[None-None-pre_model_hook-tools1]
   '''
   graph TD;
   	__start__ --> pre_model_hook;
@@ -37,7 +37,7 @@
   
   '''
 # ---
-# name: test_react_agent_graph_structure[post_model_hook-None-tools0]
+# name: test_react_agent_graph_structure[None-post_model_hook-None-tools0]
   '''
   graph TD;
   	__start__ --> agent;
@@ -46,7 +46,7 @@
   
   '''
 # ---
-# name: test_react_agent_graph_structure[post_model_hook-None-tools1]
+# name: test_react_agent_graph_structure[None-post_model_hook-None-tools1]
   '''
   graph TD;
   	__start__ --> agent;
@@ -58,7 +58,7 @@
   
   '''
 # ---
-# name: test_react_agent_graph_structure[post_model_hook-pre_model_hook-tools0]
+# name: test_react_agent_graph_structure[None-post_model_hook-pre_model_hook-tools0]
   '''
   graph TD;
   	__start__ --> pre_model_hook;
@@ -68,7 +68,7 @@
   
   '''
 # ---
-# name: test_react_agent_graph_structure[post_model_hook-pre_model_hook-tools1]
+# name: test_react_agent_graph_structure[None-post_model_hook-pre_model_hook-tools1]
   '''
   graph TD;
   	__start__ --> pre_model_hook;
@@ -81,3 +81,93 @@
   
   '''
 # ---
+# name: test_react_agent_graph_structure[ResponseFormat-None-None-tools0]
+  '''
+  graph TD;
+  	__start__ --> agent;
+  	agent --> generate_structured_response;
+  	generate_structured_response --> __end__;
+  
+  '''
+# ---
+# name: test_react_agent_graph_structure[ResponseFormat-None-None-tools1]
+  '''
+  graph TD;
+  	__start__ --> agent;
+  	agent -.-> generate_structured_response;
+  	agent -.-> tools;
+  	tools --> agent;
+  	generate_structured_response --> __end__;
+  
+  '''
+# ---
+# name: test_react_agent_graph_structure[ResponseFormat-None-pre_model_hook-tools0]
+  '''
+  graph TD;
+  	__start__ --> pre_model_hook;
+  	agent --> generate_structured_response;
+  	pre_model_hook --> agent;
+  	generate_structured_response --> __end__;
+  
+  '''
+# ---
+# name: test_react_agent_graph_structure[ResponseFormat-None-pre_model_hook-tools1]
+  '''
+  graph TD;
+  	__start__ --> pre_model_hook;
+  	agent -.-> generate_structured_response;
+  	agent -.-> tools;
+  	pre_model_hook --> agent;
+  	tools --> pre_model_hook;
+  	generate_structured_response --> __end__;
+  
+  '''
+# ---
+# name: test_react_agent_graph_structure[ResponseFormat-post_model_hook-None-tools0]
+  '''
+  graph TD;
+  	__start__ --> agent;
+  	agent --> post_model_hook;
+  	post_model_hook --> generate_structured_response;
+  	generate_structured_response --> __end__;
+  
+  '''
+# ---
+# name: test_react_agent_graph_structure[ResponseFormat-post_model_hook-None-tools1]
+  '''
+  graph TD;
+  	__start__ --> agent;
+  	agent --> post_model_hook;
+  	post_model_hook -.-> agent;
+  	post_model_hook -.-> generate_structured_response;
+  	post_model_hook -.-> tools;
+  	tools --> agent;
+  	generate_structured_response --> __end__;
+  
+  '''
+# ---
+# name: test_react_agent_graph_structure[ResponseFormat-post_model_hook-pre_model_hook-tools0]
+  '''
+  graph TD;
+  	__start__ --> pre_model_hook;
+  	agent --> post_model_hook;
+  	post_model_hook --> generate_structured_response;
+  	pre_model_hook --> agent;
+  	generate_structured_response --> __end__;
+  
+  '''
+# ---
+# name: test_react_agent_graph_structure[ResponseFormat-post_model_hook-pre_model_hook-tools1]
+  '''
+  graph TD;
+  	__start__ --> pre_model_hook;
+  	agent --> post_model_hook;
+  	post_model_hook -.-> generate_structured_response;
+  	post_model_hook -.-> pre_model_hook;
+  	post_model_hook -.-> tools;
+  	pre_model_hook --> agent;
+  	tools --> pre_model_hook;
+  	generate_structured_response --> __end__;
+  
+  '''
+# ---

libs/prebuilt/tests/model.py

@@ -1,10 +1,7 @@
-import json
-from dataclasses import asdict, is_dataclass
 from typing import (
     Any,
     Callable,
     Dict,
-    Generic,
     List,
     Literal,
     Optional,
@@ -21,16 +18,16 @@ from langchain_core.messages import (
     ToolCall,
 )
 from langchain_core.outputs import ChatGeneration, ChatResult
-from langchain_core.runnables import Runnable
+from langchain_core.runnables import Runnable, RunnableLambda
 from langchain_core.tools import BaseTool
 from pydantic import BaseModel
 
-from langgraph.prebuilt.chat_agent_executor import StructuredResponseT
+from langgraph.prebuilt.chat_agent_executor import StructuredResponse
 
 
-class FakeToolCallingModel(BaseChatModel, Generic[StructuredResponseT]):
-    tool_calls: Optional[Union[list[list[ToolCall]], list[list[dict]]]] = None
-    structured_response: Optional[StructuredResponseT] = None
+class FakeToolCallingModel(BaseChatModel):
+    tool_calls: Optional[list[list[ToolCall]]] = None
+    structured_response: Optional[StructuredResponse] = None
     index: int = 0
     tool_style: Literal["openai", "anthropic"] = "openai"
 
@@ -42,36 +39,15 @@ class FakeToolCallingModel(BaseChatModel, Generic[StructuredResponseT]):
         **kwargs: Any,
     ) -> ChatResult:
         """Top Level call"""
-        rf = kwargs.get("response_format")
-        is_native = isinstance(rf, dict) and rf.get("type") == "json_schema"
-
-        if self.tool_calls:
-            if is_native:
-                tool_calls = (
-                    self.tool_calls[self.index]
-                    if self.index < len(self.tool_calls)
-                    else []
-                )
-            else:
-                tool_calls = self.tool_calls[self.index % len(self.tool_calls)]
-        else:
-            tool_calls = []
-
-        if is_native and not tool_calls:
-            if isinstance(self.structured_response, BaseModel):
-                content_obj = self.structured_response.model_dump()
-            elif is_dataclass(self.structured_response):
-                content_obj = asdict(self.structured_response)
-            elif isinstance(self.structured_response, dict):
-                content_obj = self.structured_response
-            message = AIMessage(content=json.dumps(content_obj), id=str(self.index))
-        else:
-            messages_string = "-".join([m.content for m in messages])
-            message = AIMessage(
-                content=messages_string,
-                id=str(self.index),
-                tool_calls=tool_calls.copy(),
-            )
+        messages_string = "-".join([m.content for m in messages])
+        tool_calls = (
+            self.tool_calls[self.index % len(self.tool_calls)]
+            if self.tool_calls
+            else []
+        )
+        message = AIMessage(
+            content=messages_string, id=str(self.index), tool_calls=tool_calls.copy()
+        )
         self.index += 1
         return ChatResult(generations=[ChatGeneration(message=message)])
 
@@ -79,6 +55,14 @@ class FakeToolCallingModel(BaseChatModel, Generic[StructuredResponseT]):
     def _llm_type(self) -> str:
         return "fake-tool-call-model"
 
+    def with_structured_output(
+        self, schema: Type[BaseModel]
+    ) -> Runnable[LanguageModelInput, StructuredResponse]:
+        if self.structured_response is None:
+            raise ValueError("Structured response is not set")
+
+        return RunnableLambda(lambda x: self.structured_response)
+
     def bind_tools(
         self,
         tools: Sequence[Union[Dict[str, Any], Type[BaseModel], Callable, BaseTool]],

libs/prebuilt/tests/specifications/responses.json

@@ -1,87 +0,0 @@
-[
-    {
-      "name": "updated structured response",
-      "responseFormat": [
-        {
-          "title": "role_schema_structured_output",
-          "type": "object",
-          "properties": {
-            "name": { "type": "string" },
-            "role": { "type": "string" }
-          },
-          "required": ["name", "role"]
-        },
-        {
-          "title": "department_schema_structured_output",
-          "type": "object",
-          "properties": {
-            "name": { "type": "string" },
-            "department": { "type": "string" }
-          },
-          "required": ["name", "department"]
-        }
-      ],
-      "assertionsByInvocation": [
-        {
-          "prompt": "What is the role of Sabine?",
-          "toolsWithExpectedCalls": {
-            "getEmployeeRole": 1,
-            "getEmployeeDepartment": 0
-          },
-          "expectedLastMessage": "Returning structured response: {'name': 'Sabine', 'role': 'Developer'}",
-          "expectedStructuredResponse": { "name": "Sabine", "role": "Developer" },
-          "llmRequestCount": 2
-        },
-        {
-          "prompt": "In which department does Henrik work?",
-          "toolsWithExpectedCalls": {
-            "getEmployeeRole": 1,
-            "getEmployeeDepartment": 1
-          },
-          "expectedLastMessage": "Returning structured response: {'name': 'Henrik', 'department': 'IT'}",
-          "expectedStructuredResponse": { "name": "Henrik", "department": "IT" },
-          "llmRequestCount": 4
-        }
-      ]
-    },
-    {
-      "name": "asking for information that does not fit into the response format",
-      "responseFormat": [
-        {
-          "schema": {
-            "type": "object",
-            "properties": {
-              "name": { "type": "string" },
-              "role": { "type": "string" }
-            },
-            "required": ["name", "role"]
-          }
-        },
-        {
-          "schema": {
-            "type": "object",
-            "properties": {
-              "name": { "type": "string" },
-              "department": { "type": "string" }
-            },
-            "required": ["name", "department"]
-          }
-        }
-      ],
-      "assertionsByInvocation": [
-        {
-          "prompt": "How much does Saskia earn?",
-          "toolsWithExpectedCalls": {
-            "getEmployeeRole": 1,
-            "getEmployeeDepartment": 0
-          },
-          "expectedLastMessage": "Returning structured response: {'name': 'Saskia', 'role': 'Software Engineer'}",
-          "expectedStructuredResponse": {
-            "name": "Saskia",
-            "role": "Software Engineer"
-          },
-          "llmRequestCount": 2
-        }
-      ]
-    }
-  ]

libs/prebuilt/tests/specifications/return_direct.json

@@ -1,48 +0,0 @@
-[
-  {
-    "name": "Scenario: NO return_direct, NO response_format",
-    "returnDirect": false,
-    "responseFormat": null,
-    "expectedToolCalls": 10,
-    "expectedLastMessage": "Attempts: 10",
-    "expectedStructuredResponse": null
-  },
-  {
-    "name": "Scenario: NO return_direct, YES response_format",
-    "returnDirect": false,
-    "responseFormat": {
-      "type": "object",
-      "properties": {
-        "attempts": { "type": "number" },
-        "succeeded": { "type": "boolean" }
-      },
-      "required": ["attempts", "succeeded"]
-    },
-    "expectedToolCalls": 10,
-    "expectedLastMessage": "Returning structured response: {'attempts': 10, 'succeeded': True}",
-    "expectedStructuredResponse": { "attempts": 10, "succeeded": true }
-  },
-  {
-    "name": "Scenario: YES return_direct, NO response_format",
-    "returnDirect": true,
-    "responseFormat": null,
-    "expectedToolCalls": 1,
-    "expectedLastMessage": "{\"status\": \"pending\", \"attempts\": 1}",
-    "expectedStructuredResponse": null
-  },
-  {
-    "name": "Scenario: YES return_direct, YES response_format",
-    "returnDirect": true,
-    "responseFormat": {
-      "type": "object",
-      "properties": {
-        "attempts": { "type": "number" },
-        "succeeded": { "type": "boolean" }
-      },
-      "required": ["attempts", "succeeded"]
-    },
-    "expectedToolCalls": 1,
-    "expectedLastMessage": "{\"status\": \"pending\", \"attempts\": 1}",
-    "expectedStructuredResponse": null
-  }
-]

libs/prebuilt/tests/test_deprecation.py

@@ -14,7 +14,7 @@ class Config(TypedDict):
 @pytest.mark.filterwarnings("ignore:`get_config_jsonschema` is deprecated")
 def test_config_schema_deprecation() -> None:
     with pytest.warns(
-        DeprecationWarning,
+        LangGraphDeprecatedSinceV10,
         match="`config_schema` is deprecated and will be removed. Please use `context_schema` instead.",
     ):
         agent = create_react_agent(FakeToolCallingModel(), [], config_schema=Config)

libs/prebuilt/tests/test_react_agent.py

@@ -1,9 +1,14 @@
 import dataclasses
 import inspect
+import json
+from functools import partial
 from typing import (
     Annotated,
+    List,
     Literal,
     Optional,
+    Type,
+    TypeVar,
     Union,
 )
 
@@ -11,6 +16,7 @@ import pytest
 from langchain_core.language_models import BaseChatModel
 from langchain_core.messages import (
     AIMessage,
+    AnyMessage,
     HumanMessage,
     MessageLikeRepresentation,
     RemoveMessage,
@@ -19,22 +25,27 @@ from langchain_core.messages import (
     ToolMessage,
 )
 from langchain_core.runnables import RunnableConfig, RunnableLambda
-from langchain_core.tools import BaseTool, InjectedToolCallId, ToolException
+from langchain_core.tools import InjectedToolCallId, ToolException
 from langchain_core.tools import tool as dec_tool
 from pydantic import BaseModel, Field
+from pydantic.v1 import BaseModel as BaseModelV1
 from typing_extensions import TypedDict
 
 from langgraph.checkpoint.base import BaseCheckpointSaver
-from langgraph.graph import START, MessagesState, StateGraph
+from langgraph.config import get_stream_writer
+from langgraph.graph import START, MessagesState, StateGraph, add_messages
 from langgraph.graph.message import REMOVE_ALL_MESSAGES
 from langgraph.prebuilt import (
     ToolNode,
     create_react_agent,
+    tools_condition,
 )
 from langgraph.prebuilt.chat_agent_executor import (
     AgentState,
     AgentStatePydantic,
-    StateT,
+    StateSchemaType,
+    _get_model,
+    _should_bind_tools,
     _validate_chat_history,
 )
 from langgraph.prebuilt.tool_node import (
@@ -173,7 +184,7 @@ def test_runnable_prompt():
 
 
 @pytest.mark.parametrize("version", REACT_TOOL_CALL_VERSIONS)
-def test_prompt_with_store(version: Literal["v1", "v2"]):
+def test_prompt_with_store(version: str):
     def add(a: int, b: int):
         """Adds a and b"""
         return a + b
@@ -264,7 +275,7 @@ async def test_prompt_with_store_async():
 @pytest.mark.parametrize("tool_style", ["openai", "anthropic"])
 @pytest.mark.parametrize("version", REACT_TOOL_CALL_VERSIONS)
 @pytest.mark.parametrize("include_builtin", [True, False])
-def test_model_with_tools(tool_style: str, version: str, include_builtin: bool) -> None:
+def test_model_with_tools(tool_style: str, version: str, include_builtin: bool):
     model = FakeToolCallingModel(tool_style=tool_style)
 
     @dec_tool
@@ -277,7 +288,7 @@ def test_model_with_tools(tool_style: str, version: str, include_builtin: bool)
         """Tool 2 docstring."""
         return f"Tool 2: {some_val}"
 
-    tools: list[BaseTool | dict] = [tool1, tool2]
+    tools = [tool1, tool2]
     if include_builtin:
         tools.append(
             {
@@ -295,12 +306,45 @@ def test_model_with_tools(tool_style: str, version: str, include_builtin: bool)
             }
         )
     # check valid agent constructor
+    agent = create_react_agent(
+        model.bind_tools(tools),
+        tools,
+        version=version,
+    )
+    result = agent.nodes["tools"].invoke(
+        {
+            "messages": [
+                AIMessage(
+                    "hi?",
+                    tool_calls=[
+                        {
+                            "name": "tool1",
+                            "args": {"some_val": 2},
+                            "id": "some 1",
+                        },
+                        {
+                            "name": "tool2",
+                            "args": {"some_val": 2},
+                            "id": "some 2",
+                        },
+                    ],
+                )
+            ]
+        }
+    )
+    tool_messages: ToolMessage = result["messages"][-2:]
+    for tool_message in tool_messages:
+        assert tool_message.type == "tool"
+        assert tool_message.content in {"Tool 1: 2", "Tool 2: 2"}
+        assert tool_message.tool_call_id in {"some 1", "some 2"}
+
+    # test mismatching tool lengths
     with pytest.raises(ValueError):
-        create_react_agent(
-            model.bind_tools(tools),
-            tools,
-            version=version,
-        )
+        create_react_agent(model.bind_tools([tool1]), [tool1, tool2])
+
+    # test missing bound tools
+    with pytest.raises(ValueError):
+        create_react_agent(model.bind_tools([tool1]), [tool2])
 
 
 def test__validate_messages():
@@ -434,46 +478,27 @@ def test_react_agent_with_structured_response(version: str) -> None:
     class WeatherResponse(BaseModel):
         temperature: float = Field(description="The temperature in fahrenheit")
 
-    tool_calls = [
-        [{"args": {}, "id": "1", "name": "get_weather"}],
-        [{"name": "WeatherResponse", "id": "2", "args": {"temperature": 75}}],
-    ]
+    tool_calls = [[{"args": {}, "id": "1", "name": "get_weather"}], []]
 
     def get_weather():
         """Get the weather"""
         return "The weather is sunny and 75°F."
 
     expected_structured_response = WeatherResponse(temperature=75)
-    model = FakeToolCallingModel[WeatherResponse](
+    model = FakeToolCallingModel(
         tool_calls=tool_calls, structured_response=expected_structured_response
     )
-    agent = create_react_agent(
-        model,
-        [get_weather],
-        response_format=WeatherResponse,
-        version=version,
-    )
-    response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
-    assert response["structured_response"] == expected_structured_response
-    assert len(response["messages"]) == 5
-
-    # Check message types in message history
-    msg_types = [m.type for m in response["messages"]]
-    assert msg_types == [
-        "human",  # "What's the weather?"
-        "ai",  # "What's the weather?"
-        "tool",  # "The weather is sunny and 75°F."
-        "ai",  # structured response
-        "tool",  # artificial tool message
-    ]
-
-    assert [m.content for m in response["messages"]] == [
-        "What's the weather?",
-        "What's the weather?",
-        "The weather is sunny and 75°F.",
-        "What's the weather?-What's the weather?-The weather is sunny and 75°F.",
-        "Returning structured response: {'temperature': 75.0}",
-    ]
+    for response_format in (WeatherResponse, ("Meow", WeatherResponse)):
+        agent = create_react_agent(
+            model,
+            [get_weather],
+            response_format=response_format,
+            version=version,
+        )
+        response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
+        assert response["structured_response"] == expected_structured_response
+        assert len(response["messages"]) == 4
+        assert response["messages"][-2].content == "The weather is sunny and 75°F."
 
 
 class CustomState(AgentState):
@@ -489,7 +514,7 @@ class CustomStatePydantic(AgentStatePydantic):
 def test_react_agent_update_state(
     sync_checkpointer: BaseCheckpointSaver,
     version: Literal["v1", "v2"],
-    state_schema: StateT,
+    state_schema: StateSchemaType,
 ) -> None:
     @dec_tool
     def get_user_name(tool_call_id: Annotated[str, InjectedToolCallId]):
@@ -629,6 +654,124 @@ def test_react_agent_parallel_tool_calls(
         assert get_weather_execution_count == 1
 
 
+class _InjectStateSchema(TypedDict):
+    messages: list
+    foo: str
+
+
+class _InjectedStatePydanticSchema(BaseModelV1):
+    messages: list
+    foo: str
+
+
+class _InjectedStatePydanticV2Schema(BaseModel):
+    messages: list
+    foo: str
+
+
+@dataclasses.dataclass
+class _InjectedStateDataclassSchema:
+    messages: list
+    foo: str
+
+
+T = TypeVar("T")
+
+
+@pytest.mark.parametrize(
+    "schema_",
+    [
+        _InjectStateSchema,
+        _InjectedStatePydanticSchema,
+        _InjectedStatePydanticV2Schema,
+        _InjectedStateDataclassSchema,
+    ],
+)
+def test_tool_node_inject_state(schema_: Type[T]) -> None:
+    def tool1(some_val: int, state: Annotated[T, InjectedState]) -> str:
+        """Tool 1 docstring."""
+        if isinstance(state, dict):
+            return state["foo"]
+        else:
+            return getattr(state, "foo")
+
+    def tool2(some_val: int, state: Annotated[T, InjectedState()]) -> str:
+        """Tool 2 docstring."""
+        if isinstance(state, dict):
+            return state["foo"]
+        else:
+            return getattr(state, "foo")
+
+    def tool3(
+        some_val: int,
+        foo: Annotated[str, InjectedState("foo")],
+        msgs: Annotated[List[AnyMessage], InjectedState("messages")],
+    ) -> str:
+        """Tool 1 docstring."""
+        return foo
+
+    def tool4(
+        some_val: int, msgs: Annotated[List[AnyMessage], InjectedState("messages")]
+    ) -> str:
+        """Tool 1 docstring."""
+        return msgs[0].content
+
+    node = ToolNode([tool1, tool2, tool3, tool4])
+    for tool_name in ("tool1", "tool2", "tool3"):
+        tool_call = {
+            "name": tool_name,
+            "args": {"some_val": 1},
+            "id": "some 0",
+            "type": "tool_call",
+        }
+        msg = AIMessage("hi?", tool_calls=[tool_call])
+        result = node.invoke(schema_(**{"messages": [msg], "foo": "bar"}))
+        tool_message = result["messages"][-1]
+        assert tool_message.content == "bar", f"Failed for tool={tool_name}"
+
+        if tool_name == "tool3":
+            failure_input = None
+            try:
+                failure_input = schema_(**{"messages": [msg], "notfoo": "bar"})
+            except Exception:
+                pass
+            if failure_input is not None:
+                with pytest.raises(KeyError):
+                    node.invoke(failure_input)
+
+                with pytest.raises(ValueError):
+                    node.invoke([msg])
+        else:
+            failure_input = None
+            try:
+                failure_input = schema_(**{"messages": [msg], "notfoo": "bar"})
+            except Exception:
+                # We'd get a validation error from pydantic state and wouldn't make it to the node
+                # anyway
+                pass
+            if failure_input is not None:
+                messages_ = node.invoke(failure_input)
+                tool_message = messages_["messages"][-1]
+                assert "KeyError" in tool_message.content
+                tool_message = node.invoke([msg])[-1]
+                assert "KeyError" in tool_message.content
+
+    tool_call = {
+        "name": "tool4",
+        "args": {"some_val": 1},
+        "id": "some 0",
+        "type": "tool_call",
+    }
+    msg = AIMessage("hi?", tool_calls=[tool_call])
+    result = node.invoke(schema_(**{"messages": [msg], "foo": ""}))
+    tool_message = result["messages"][-1]
+    assert tool_message.content == "hi?"
+
+    result = node.invoke([msg])
+    tool_message = result[-1]
+    assert tool_message.content == "hi?"
+
+
 class AgentStateExtraKey(AgentState):
     foo: int
 
@@ -642,7 +785,7 @@ class AgentStateExtraKeyPydantic(AgentStatePydantic):
     "state_schema", [AgentStateExtraKey, AgentStateExtraKeyPydantic]
 )
 def test_create_react_agent_inject_vars(
-    version: Literal["v1", "v2"], state_schema: StateT
+    version: Literal["v1", "v2"], state_schema: StateSchemaType
 ) -> None:
     """Test that the agent can inject state and store into tool functions."""
     store = InMemoryStore()
@@ -694,6 +837,135 @@ def test_create_react_agent_inject_vars(
     assert result["foo"] == 2
 
 
+def test_tool_node_inject_store() -> None:
+    store = InMemoryStore()
+    namespace = ("test",)
+
+    def tool1(some_val: int, store: Annotated[BaseStore, InjectedStore()]) -> str:
+        """Tool 1 docstring."""
+        store_val = store.get(namespace, "test_key").value["foo"]
+        return f"Some val: {some_val}, store val: {store_val}"
+
+    def tool2(some_val: int, store: Annotated[BaseStore, InjectedStore()]) -> str:
+        """Tool 2 docstring."""
+        store_val = store.get(namespace, "test_key").value["foo"]
+        return f"Some val: {some_val}, store val: {store_val}"
+
+    def tool3(
+        some_val: int,
+        bar: Annotated[str, InjectedState("bar")],
+        store: Annotated[BaseStore, InjectedStore()],
+    ) -> str:
+        """Tool 3 docstring."""
+        store_val = store.get(namespace, "test_key").value["foo"]
+        return f"Some val: {some_val}, store val: {store_val}, state val: {bar}"
+
+    node = ToolNode([tool1, tool2, tool3], handle_tool_errors=True)
+    store.put(namespace, "test_key", {"foo": "bar"})
+
+    class State(MessagesState):
+        bar: str
+
+    builder = StateGraph(State)
+    builder.add_node("tools", node)
+    builder.add_edge(START, "tools")
+    graph = builder.compile(store=store)
+
+    for tool_name in ("tool1", "tool2"):
+        tool_call = {
+            "name": tool_name,
+            "args": {"some_val": 1},
+            "id": "some 0",
+            "type": "tool_call",
+        }
+        msg = AIMessage("hi?", tool_calls=[tool_call])
+        node_result = node.invoke({"messages": [msg]}, store=store)
+        graph_result = graph.invoke({"messages": [msg]})
+        for result in (node_result, graph_result):
+            result["messages"][-1]
+            tool_message = result["messages"][-1]
+            assert tool_message.content == "Some val: 1, store val: bar", (
+                f"Failed for tool={tool_name}"
+            )
+
+    tool_call = {
+        "name": "tool3",
+        "args": {"some_val": 1},
+        "id": "some 0",
+        "type": "tool_call",
+    }
+    msg = AIMessage("hi?", tool_calls=[tool_call])
+    node_result = node.invoke({"messages": [msg], "bar": "baz"}, store=store)
+    graph_result = graph.invoke({"messages": [msg], "bar": "baz"})
+    for result in (node_result, graph_result):
+        result["messages"][-1]
+        tool_message = result["messages"][-1]
+        assert tool_message.content == "Some val: 1, store val: bar, state val: baz", (
+            f"Failed for tool={tool_name}"
+        )
+
+    # test injected store without passing store to compiled graph
+    failing_graph = builder.compile()
+    with pytest.raises(ValueError):
+        failing_graph.invoke({"messages": [msg], "bar": "baz"})
+
+
+def test_tool_node_ensure_utf8() -> None:
+    @dec_tool
+    def get_day_list(days: list[str]) -> list[str]:
+        """choose days"""
+        return days
+
+    data = ["星期一", "水曜日", "목요일", "Friday"]
+    tools = [get_day_list]
+    tool_calls = [ToolCall(name=get_day_list.name, args={"days": data}, id="test_id")]
+    outputs: list[ToolMessage] = ToolNode(tools).invoke(
+        [AIMessage(content="", tool_calls=tool_calls)]
+    )
+    assert outputs[0].content == json.dumps(data, ensure_ascii=False)
+
+
+def test_tool_node_messages_key() -> None:
+    @dec_tool
+    def add(a: int, b: int):
+        """Adds a and b."""
+        return a + b
+
+    model = FakeToolCallingModel(
+        tool_calls=[[ToolCall(name=add.name, args={"a": 1, "b": 2}, id="test_id")]]
+    )
+
+    class State(TypedDict):
+        subgraph_messages: Annotated[list[AnyMessage], add_messages]
+
+    def call_model(state: State):
+        response = model.invoke(state["subgraph_messages"])
+        model.tool_calls = []
+        return {"subgraph_messages": response}
+
+    builder = StateGraph(State)
+    builder.add_node("agent", call_model)
+    builder.add_node("tools", ToolNode([add], messages_key="subgraph_messages"))
+    builder.add_conditional_edges(
+        "agent", partial(tools_condition, messages_key="subgraph_messages")
+    )
+    builder.add_edge(START, "agent")
+    builder.add_edge("tools", "agent")
+
+    graph = builder.compile()
+    result = graph.invoke({"subgraph_messages": [HumanMessage(content="hi")]})
+    assert result["subgraph_messages"] == [
+        _AnyIdHumanMessage(content="hi"),
+        AIMessage(
+            content="hi",
+            id="0",
+            tool_calls=[ToolCall(name=add.name, args={"a": 1, "b": 2}, id="test_id")],
+        ),
+        _AnyIdToolMessage(content="3", name=add.name, tool_call_id="test_id"),
+        AIMessage(content="hi-hi-3", id="1"),
+    ]
+
+
 @pytest.mark.parametrize("version", REACT_TOOL_CALL_VERSIONS)
 async def test_return_direct(version: str) -> None:
     @dec_tool(return_direct=True)
@@ -910,6 +1182,60 @@ def test_react_with_subgraph_tools(
     ]
 
 
+def test_tool_node_stream_writer() -> None:
+    @dec_tool
+    def streaming_tool(x: int) -> str:
+        """Do something with writer."""
+        my_writer = get_stream_writer()
+        for value in ["foo", "bar", "baz"]:
+            my_writer({"custom_tool_value": value})
+
+        return x
+
+    tool_node = ToolNode([streaming_tool])
+    graph = (
+        StateGraph(MessagesState)
+        .add_node("tools", tool_node)
+        .add_edge(START, "tools")
+        .compile()
+    )
+
+    tool_call = {
+        "name": "streaming_tool",
+        "args": {"x": 1},
+        "id": "1",
+        "type": "tool_call",
+    }
+    inputs = {
+        "messages": [AIMessage("", tool_calls=[tool_call])],
+    }
+
+    assert list(graph.stream(inputs, stream_mode="custom")) == [
+        {"custom_tool_value": "foo"},
+        {"custom_tool_value": "bar"},
+        {"custom_tool_value": "baz"},
+    ]
+    assert list(graph.stream(inputs, stream_mode=["custom", "updates"])) == [
+        ("custom", {"custom_tool_value": "foo"}),
+        ("custom", {"custom_tool_value": "bar"}),
+        ("custom", {"custom_tool_value": "baz"}),
+        (
+            "updates",
+            {
+                "tools": {
+                    "messages": [
+                        _AnyIdToolMessage(
+                            content="1",
+                            name="streaming_tool",
+                            tool_call_id="1",
+                        ),
+                    ],
+                },
+            },
+        ),
+    ]
+
+
 @pytest.mark.parametrize("version", REACT_TOOL_CALL_VERSIONS)
 def test_react_agent_subgraph_streaming_sync(version: Literal["v1", "v2"]) -> None:
     """Test React agent streaming when used as a subgraph node sync version"""
@@ -1165,6 +1491,69 @@ def test_tool_node_node_interrupt(
     )
 
 
+@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))
+
+
 @pytest.mark.parametrize("version", REACT_TOOL_CALL_VERSIONS)
 def test_dynamic_model_basic(version: str) -> None:
     """Test basic dynamic model functionality."""
@@ -1341,17 +1730,9 @@ def test_dynamic_model_with_structured_response(version: str) -> None:
         confidence: float
 
     def dynamic_model(state, runtime: Runtime):
+        expected_response = TestResponse(message="dynamic response", confidence=0.9)
         return FakeToolCallingModel(
-            tool_calls=[
-                [
-                    ToolCall(
-                        name="TestResponse",
-                        args={"message": "dynamic response", "confidence": 0.9},
-                        id="1",
-                        type="tool_call",
-                    )
-                ]
-            ],
+            tool_calls=[], structured_response=expected_response
         )
 
     agent = create_react_agent(
@@ -1616,16 +1997,16 @@ def test_post_model_hook_with_structured_output() -> None:
     class WeatherResponse(BaseModel):
         temperature: float = Field(description="The temperature in fahrenheit")
 
-    tool_calls: list[list[ToolCall]] = [
-        [{"args": {}, "id": "1", "name": "get_weather"}],
-        [{"args": {"temperature": 75}, "id": "2", "name": "WeatherResponse"}],
-    ]
+    tool_calls = [[{"args": {}, "id": "1", "name": "get_weather"}]]
 
     def get_weather():
         """Get the weather"""
         return "The weather is sunny and 75°F."
 
     expected_structured_response = WeatherResponse(temperature=75)
+    model = FakeToolCallingModel(
+        tool_calls=tool_calls, structured_response=expected_structured_response
+    )
 
     class State(AgentState):
         flag: bool
@@ -1634,7 +2015,6 @@ def test_post_model_hook_with_structured_output() -> None:
     def post_model_hook(state: State) -> Union[dict[str, bool], Command]:
         return {"flag": True}
 
-    model = FakeToolCallingModel(tool_calls=tool_calls)
     agent = create_react_agent(
         model,
         [get_weather],
@@ -1644,6 +2024,7 @@ def test_post_model_hook_with_structured_output() -> None:
     )
 
     assert "post_model_hook" in agent.nodes
+    assert "generate_structured_response" in agent.nodes
 
     response = agent.invoke(
         {"messages": [HumanMessage("What's the weather?")], "flag": False}
@@ -1651,19 +2032,10 @@ def test_post_model_hook_with_structured_output() -> None:
     assert response["flag"] is True
     assert response["structured_response"] == expected_structured_response
 
-    # Reset the state of the model
-    model = FakeToolCallingModel(tool_calls=tool_calls)
-    agent = create_react_agent(
-        model,
-        [get_weather],
-        response_format=WeatherResponse,
-        post_model_hook=post_model_hook,
-        state_schema=State,
-    )
-
     events = list(
         agent.stream({"messages": [HumanMessage("What's the weather?")], "flag": False})
     )
+    assert "generate_structured_response" in events[-1]
     assert events == [
         {
             "agent": {
@@ -1672,7 +2044,7 @@ def test_post_model_hook_with_structured_output() -> None:
                         content="What's the weather?",
                         additional_kwargs={},
                         response_metadata={},
-                        id="0",
+                        id="2",
                         tool_calls=[
                             {
                                 "name": "get_weather",
@@ -1693,7 +2065,7 @@ def test_post_model_hook_with_structured_output() -> None:
                         content="The weather is sunny and 75°F.",
                         name="get_weather",
                         tool_call_id="1",
-                    )
+                    ),
                 ]
             }
         },
@@ -1704,26 +2076,25 @@ def test_post_model_hook_with_structured_output() -> None:
                         content="What's the weather?-What's the weather?-The weather is sunny and 75°F.",
                         additional_kwargs={},
                         response_metadata={},
-                        id="1",
+                        id="3",
                         tool_calls=[
                             {
-                                "name": "WeatherResponse",
-                                "args": {"temperature": 75},
-                                "id": "2",
+                                "name": "get_weather",
+                                "args": {},
+                                "id": "1",
                                 "type": "tool_call",
                             }
                         ],
-                    ),
-                    _AnyIdToolMessage(
-                        content="Returning structured response: {'temperature': 75.0}",
-                        name="WeatherResponse",
-                        tool_call_id="2",
-                    ),
-                ],
-                "structured_response": WeatherResponse(temperature=75.0),
+                    )
+                ]
             }
         },
         {"post_model_hook": {"flag": True}},
+        {
+            "generate_structured_response": {
+                "structured_response": WeatherResponse(temperature=75.0)
+            }
+        },
     ]
 
 
@@ -1731,7 +2102,7 @@ def test_post_model_hook_with_structured_output() -> None:
     "state_schema", [AgentStateExtraKey, AgentStateExtraKeyPydantic]
 )
 def test_create_react_agent_inject_vars_with_post_model_hook(
-    state_schema: StateT,
+    state_schema: StateSchemaType,
 ) -> None:
     store = InMemoryStore()
     namespace = ("test",)
@@ -1786,40 +2157,3 @@ def test_create_react_agent_inject_vars_with_post_model_hook(
         AIMessage("hi-hi-6", id="1"),
     ]
     assert result["foo"] == 2
-
-
-@pytest.mark.parametrize("version", REACT_TOOL_CALL_VERSIONS)
-def test_response_format_using_tool_choice(version: Literal["v1", "v2"]) -> None:
-    """Test response format using tool choice."""
-
-    class WeatherResponse(BaseModel):
-        temperature: float = Field(description="The temperature in fahrenheit")
-
-    tool_calls: list[list[ToolCall]] = [
-        [{"args": {}, "id": "1", "name": "get_weather"}],
-        [{"args": {"temperature": "75"}, "id": "2", "name": "WeatherResponse"}],
-    ]
-
-    def get_weather() -> str:
-        """Get the weather"""
-        return "The weather is sunny and 75°F."
-
-    expected_structured_response = WeatherResponse(temperature=75)
-    model = FakeToolCallingModel(tool_calls=tool_calls)
-    agent = create_react_agent(
-        model,
-        [get_weather],
-        response_format=WeatherResponse,
-        version=version,
-    )
-    response = agent.invoke(
-        {
-            "messages": [
-                {
-                    "role": "user",
-                    "content": "What's the weather?",
-                }
-            ]
-        }
-    )
-    assert response.get("structured_response") == expected_structured_response

libs/prebuilt/tests/test_react_agent_graph.py

@@ -34,25 +34,19 @@ class ResponseFormat(BaseModel):
 @pytest.mark.parametrize("tools", [[], [tool]])
 @pytest.mark.parametrize("pre_model_hook", [None, pre_model_hook])
 @pytest.mark.parametrize("post_model_hook", [None, post_model_hook])
+@pytest.mark.parametrize("response_format", [None, ResponseFormat])
 def test_react_agent_graph_structure(
     snapshot: SnapshotAssertion,
     tools: list[Callable],
     pre_model_hook: Union[Callable, None],
     post_model_hook: Union[Callable, None],
+    response_format: Union[type[BaseModel], None],
 ) -> None:
     agent = create_react_agent(
         model,
         tools=tools,
         pre_model_hook=pre_model_hook,
         post_model_hook=post_model_hook,
+        response_format=response_format,
     )
-    try:
-        assert agent.get_graph().draw_mermaid(with_styles=False) == snapshot
-    except Exception as e:
-        raise ValueError(
-            "The graph structure has changed. Please update the snapshot."
-            "Configuration used:\n"
-            f"tools: {tools}, "
-            f"pre_model_hook: {pre_model_hook}, "
-            f"post_model_hook: {post_model_hook}, "
-        ) from e
+    assert agent.get_graph().draw_mermaid(with_styles=False) == snapshot

libs/prebuilt/tests/test_response_format.py

@@ -1,793 +0,0 @@
-"""Test suite for create_react_agent with structured output response_format permutations."""
-
-from dataclasses import dataclass
-from typing import Union
-
-import pytest
-from langchain_core.messages import HumanMessage
-from pydantic import BaseModel, Field
-from typing_extensions import TypedDict
-
-from langgraph.prebuilt import create_react_agent
-from langgraph.prebuilt.responses import (
-    MultipleStructuredOutputsError,
-    NativeOutput,
-    StructuredOutputParsingError,
-    ToolOutput,
-)
-from tests.model import FakeToolCallingModel
-
-try:
-    from langchain_openai import ChatOpenAI
-except ImportError:
-    skip_openai_integration_tests = True
-else:
-    skip_openai_integration_tests = False
-
-
-# Test data models
-class WeatherBaseModel(BaseModel):
-    """Weather response."""
-
-    temperature: float = Field(description="The temperature in fahrenheit")
-    condition: str = Field(description="Weather condition")
-
-
-@dataclass
-class WeatherDataclass:
-    """Weather response."""
-
-    temperature: float
-    condition: str
-
-
-class WeatherTypedDict(TypedDict):
-    """Weather response."""
-
-    temperature: float
-    condition: str
-
-
-weather_json_schema = {
-    "type": "object",
-    "properties": {
-        "temperature": {"type": "number", "description": "Temperature in fahrenheit"},
-        "condition": {"type": "string", "description": "Weather condition"},
-    },
-    "title": "weather_schema",
-    "required": ["temperature", "condition"],
-}
-
-
-class LocationResponse(BaseModel):
-    city: str = Field(description="The city name")
-    country: str = Field(description="The country name")
-
-
-class LocationTypedDict(TypedDict):
-    city: str
-    country: str
-
-
-location_json_schema = {
-    "type": "object",
-    "properties": {
-        "city": {"type": "string", "description": "The city name"},
-        "country": {"type": "string", "description": "The country name"},
-    },
-    "title": "location_schema",
-    "required": ["city", "country"],
-}
-
-
-def get_weather() -> str:
-    """Get the weather."""
-
-    return "The weather is sunny and 75°F."
-
-
-def get_location() -> str:
-    """Get the current location."""
-
-    return "You are in New York, USA."
-
-
-# Standardized test data
-WEATHER_DATA = {"temperature": 75.0, "condition": "sunny"}
-LOCATION_DATA = {"city": "New York", "country": "USA"}
-
-# Standardized expected responses
-EXPECTED_WEATHER_PYDANTIC = WeatherBaseModel(**WEATHER_DATA)
-EXPECTED_WEATHER_DATACLASS = WeatherDataclass(**WEATHER_DATA)
-EXPECTED_WEATHER_DICT: WeatherTypedDict = {"temperature": 75.0, "condition": "sunny"}
-EXPECTED_LOCATION = LocationResponse(**LOCATION_DATA)
-EXPECTED_LOCATION_DICT: LocationTypedDict = {"city": "New York", "country": "USA"}
-
-
-class TestResponseFormatAsModel:
-    def test_pydantic_model(self) -> None:
-        """Test response_format as Pydantic model."""
-        tool_calls = [
-            [{"args": {}, "id": "1", "name": "get_weather"}],
-            [
-                {
-                    "name": "WeatherBaseModel",
-                    "id": "2",
-                    "args": WEATHER_DATA,
-                }
-            ],
-        ]
-
-        model = FakeToolCallingModel(tool_calls=tool_calls)
-
-        agent = create_react_agent(
-            model, [get_weather], response_format=WeatherBaseModel
-        )
-        response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
-
-        assert response["structured_response"] == EXPECTED_WEATHER_PYDANTIC
-        assert len(response["messages"]) == 5
-
-    def test_dataclass(self) -> None:
-        """Test response_format as dataclass."""
-        tool_calls = [
-            [{"args": {}, "id": "1", "name": "get_weather"}],
-            [
-                {
-                    "name": "WeatherDataclass",
-                    "id": "2",
-                    "args": WEATHER_DATA,
-                }
-            ],
-        ]
-
-        model = FakeToolCallingModel(tool_calls=tool_calls)
-
-        agent = create_react_agent(
-            model, [get_weather], response_format=WeatherDataclass
-        )
-        response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
-
-        assert response["structured_response"] == EXPECTED_WEATHER_DATACLASS
-        assert len(response["messages"]) == 5
-
-    def test_typed_dict(self) -> None:
-        """Test response_format as TypedDict."""
-        tool_calls = [
-            [{"args": {}, "id": "1", "name": "get_weather"}],
-            [
-                {
-                    "name": "WeatherTypedDict",
-                    "id": "2",
-                    "args": WEATHER_DATA,
-                }
-            ],
-        ]
-
-        model = FakeToolCallingModel(tool_calls=tool_calls)
-
-        agent = create_react_agent(
-            model, [get_weather], response_format=WeatherTypedDict
-        )
-        response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
-
-        assert response["structured_response"] == EXPECTED_WEATHER_DICT
-        assert len(response["messages"]) == 5
-
-    def test_json_schema(self) -> None:
-        """Test response_format as JSON schema."""
-        tool_calls = [
-            [{"args": {}, "id": "1", "name": "get_weather"}],
-            [
-                {
-                    "name": "weather_schema",
-                    "id": "2",
-                    "args": WEATHER_DATA,
-                }
-            ],
-        ]
-
-        model = FakeToolCallingModel(tool_calls=tool_calls)
-
-        agent = create_react_agent(
-            model, [get_weather], response_format=weather_json_schema
-        )
-        response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
-
-        assert response["structured_response"] == EXPECTED_WEATHER_DICT
-        assert len(response["messages"]) == 5
-
-
-class TestResponseFormatAsToolOutput:
-    def test_pydantic_model(self) -> None:
-        """Test response_format as ToolOutput with Pydantic model."""
-        tool_calls = [
-            [{"args": {}, "id": "1", "name": "get_weather"}],
-            [
-                {
-                    "name": "WeatherBaseModel",
-                    "id": "2",
-                    "args": WEATHER_DATA,
-                }
-            ],
-        ]
-
-        model = FakeToolCallingModel(tool_calls=tool_calls)
-
-        agent = create_react_agent(
-            model, [get_weather], response_format=ToolOutput(WeatherBaseModel)
-        )
-        response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
-
-        assert response["structured_response"] == EXPECTED_WEATHER_PYDANTIC
-        assert len(response["messages"]) == 5
-
-    def test_dataclass(self) -> None:
-        """Test response_format as ToolOutput with dataclass."""
-        tool_calls = [
-            [{"args": {}, "id": "1", "name": "get_weather"}],
-            [
-                {
-                    "name": "WeatherDataclass",
-                    "id": "2",
-                    "args": WEATHER_DATA,
-                }
-            ],
-        ]
-
-        model = FakeToolCallingModel(tool_calls=tool_calls)
-
-        agent = create_react_agent(
-            model, [get_weather], response_format=ToolOutput(WeatherDataclass)
-        )
-        response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
-
-        assert response["structured_response"] == EXPECTED_WEATHER_DATACLASS
-        assert len(response["messages"]) == 5
-
-    def test_typed_dict(self) -> None:
-        """Test response_format as ToolOutput with TypedDict."""
-        tool_calls = [
-            [{"args": {}, "id": "1", "name": "get_weather"}],
-            [
-                {
-                    "name": "WeatherTypedDict",
-                    "id": "2",
-                    "args": WEATHER_DATA,
-                }
-            ],
-        ]
-
-        model = FakeToolCallingModel(tool_calls=tool_calls)
-
-        agent = create_react_agent(
-            model, [get_weather], response_format=ToolOutput(WeatherTypedDict)
-        )
-        response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
-
-        assert response["structured_response"] == EXPECTED_WEATHER_DICT
-        assert len(response["messages"]) == 5
-
-    def test_json_schema(self) -> None:
-        """Test response_format as ToolOutput with JSON schema."""
-        tool_calls = [
-            [{"args": {}, "id": "1", "name": "get_weather"}],
-            [
-                {
-                    "name": "weather_schema",
-                    "id": "2",
-                    "args": WEATHER_DATA,
-                }
-            ],
-        ]
-
-        model = FakeToolCallingModel(tool_calls=tool_calls)
-
-        agent = create_react_agent(
-            model, [get_weather], response_format=ToolOutput(weather_json_schema)
-        )
-        response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
-
-        assert response["structured_response"] == EXPECTED_WEATHER_DICT
-        assert len(response["messages"]) == 5
-
-    def test_union_of_json_schemas(self) -> None:
-        """Test response_format as ToolOutput with union of JSON schemas."""
-        tool_calls = [
-            [{"args": {}, "id": "1", "name": "get_weather"}],
-            [
-                {
-                    "name": "weather_schema",
-                    "id": "2",
-                    "args": WEATHER_DATA,
-                }
-            ],
-        ]
-
-        model = FakeToolCallingModel(tool_calls=tool_calls)
-
-        agent = create_react_agent(
-            model,
-            [get_weather, get_location],
-            response_format=ToolOutput(
-                {"oneOf": [weather_json_schema, location_json_schema]}
-            ),
-        )
-        response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
-
-        assert response["structured_response"] == EXPECTED_WEATHER_DICT
-        assert len(response["messages"]) == 5
-
-        # Test with LocationResponse
-        tool_calls_location = [
-            [{"args": {}, "id": "1", "name": "get_location"}],
-            [
-                {
-                    "name": "location_schema",
-                    "id": "2",
-                    "args": LOCATION_DATA,
-                }
-            ],
-        ]
-
-        model_location = FakeToolCallingModel(tool_calls=tool_calls_location)
-
-        agent_location = create_react_agent(
-            model_location,
-            [get_weather, get_location],
-            response_format=ToolOutput(
-                {"oneOf": [weather_json_schema, location_json_schema]}
-            ),
-        )
-        response_location = agent_location.invoke(
-            {"messages": [HumanMessage("Where am I?")]}
-        )
-
-        assert response_location["structured_response"] == EXPECTED_LOCATION_DICT
-        assert len(response_location["messages"]) == 5
-
-    def test_union_of_types(self) -> None:
-        """Test response_format as ToolOutput with Union of various types."""
-        # Test with WeatherBaseModel
-        tool_calls = [
-            [{"args": {}, "id": "1", "name": "get_weather"}],
-            [
-                {
-                    "name": "WeatherBaseModel",
-                    "id": "2",
-                    "args": WEATHER_DATA,
-                }
-            ],
-        ]
-
-        model = FakeToolCallingModel[Union[WeatherBaseModel, LocationResponse]](
-            tool_calls=tool_calls
-        )
-
-        agent = create_react_agent(
-            model,
-            [get_weather, get_location],
-            response_format=ToolOutput(Union[WeatherBaseModel, LocationResponse]),
-        )
-        response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
-
-        assert response["structured_response"] == EXPECTED_WEATHER_PYDANTIC
-        assert len(response["messages"]) == 5
-
-        # Test with LocationResponse
-        tool_calls_location = [
-            [{"args": {}, "id": "1", "name": "get_location"}],
-            [
-                {
-                    "name": "LocationResponse",
-                    "id": "2",
-                    "args": LOCATION_DATA,
-                }
-            ],
-        ]
-
-        model_location = FakeToolCallingModel(tool_calls=tool_calls_location)
-
-        agent_location = create_react_agent(
-            model_location,
-            [get_weather, get_location],
-            response_format=ToolOutput(Union[WeatherBaseModel, LocationResponse]),
-        )
-        response_location = agent_location.invoke(
-            {"messages": [HumanMessage("Where am I?")]}
-        )
-
-        assert response_location["structured_response"] == EXPECTED_LOCATION
-        assert len(response_location["messages"]) == 5
-
-    def test_multiple_structured_outputs_error_without_retry(self) -> None:
-        """Test that MultipleStructuredOutputsError is raised when model returns multiple structured tool calls without retry."""
-        tool_calls = [
-            [
-                {
-                    "name": "WeatherBaseModel",
-                    "id": "1",
-                    "args": WEATHER_DATA,
-                },
-                {
-                    "name": "LocationResponse",
-                    "id": "2",
-                    "args": LOCATION_DATA,
-                },
-            ],
-        ]
-
-        model = FakeToolCallingModel(tool_calls=tool_calls)
-
-        agent = create_react_agent(
-            model,
-            [],
-            response_format=ToolOutput(
-                Union[WeatherBaseModel, LocationResponse],
-                handle_errors=False,
-            ),
-        )
-
-        with pytest.raises(
-            MultipleStructuredOutputsError,
-            match=".*WeatherBaseModel.*LocationResponse.*",
-        ):
-            agent.invoke({"messages": [HumanMessage("Give me weather and location")]})
-
-    def test_multiple_structured_outputs_with_retry(self) -> None:
-        """Test that retry handles multiple structured output tool calls."""
-        tool_calls = [
-            [
-                {
-                    "name": "WeatherBaseModel",
-                    "id": "1",
-                    "args": WEATHER_DATA,
-                },
-                {
-                    "name": "LocationResponse",
-                    "id": "2",
-                    "args": LOCATION_DATA,
-                },
-            ],
-            [
-                {
-                    "name": "WeatherBaseModel",
-                    "id": "3",
-                    "args": WEATHER_DATA,
-                },
-            ],
-        ]
-
-        model = FakeToolCallingModel(tool_calls=tool_calls)
-
-        agent = create_react_agent(
-            model,
-            [],
-            response_format=ToolOutput(
-                Union[WeatherBaseModel, LocationResponse],
-                handle_errors=True,
-            ),
-        )
-
-        response = agent.invoke({"messages": [HumanMessage("Give me weather")]})
-
-        # HumanMessage, AIMessage, ToolMessage, ToolMessage, AI, ToolMessage
-        assert len(response["messages"]) == 6
-        assert response["structured_response"] == EXPECTED_WEATHER_PYDANTIC
-
-    def test_structured_output_parsing_error_without_retry(self) -> None:
-        """Test that StructuredOutputParsingError is raised when tool args fail to parse without retry."""
-        tool_calls = [
-            [
-                {
-                    "name": "WeatherBaseModel",
-                    "id": "1",
-                    "args": {"invalid": "data"},
-                },
-            ],
-        ]
-
-        model = FakeToolCallingModel(tool_calls=tool_calls)
-
-        agent = create_react_agent(
-            model,
-            [],
-            response_format=ToolOutput(
-                WeatherBaseModel,
-                handle_errors=False,
-            ),
-        )
-
-        with pytest.raises(
-            StructuredOutputParsingError,
-            match=".*WeatherBaseModel.*",
-        ):
-            agent.invoke({"messages": [HumanMessage("What's the weather?")]})
-
-    def test_structured_output_parsing_error_with_retry(self) -> None:
-        """Test that retry handles parsing errors for structured output."""
-        tool_calls = [
-            [
-                {
-                    "name": "WeatherBaseModel",
-                    "id": "1",
-                    "args": {"invalid": "data"},
-                },
-            ],
-            [
-                {
-                    "name": "WeatherBaseModel",
-                    "id": "2",
-                    "args": WEATHER_DATA,
-                },
-            ],
-        ]
-
-        model = FakeToolCallingModel(tool_calls=tool_calls)
-
-        agent = create_react_agent(
-            model,
-            [],
-            response_format=ToolOutput(
-                WeatherBaseModel,
-                handle_errors=(StructuredOutputParsingError,),
-            ),
-        )
-
-        response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
-
-        # HumanMessage, AIMessage, ToolMessage, AIMessage, ToolMessage
-        assert len(response["messages"]) == 5
-        assert response["structured_response"] == EXPECTED_WEATHER_PYDANTIC
-
-    def test_retry_with_custom_function(self) -> None:
-        """Test retry with custom message generation."""
-        tool_calls = [
-            [
-                {
-                    "name": "WeatherBaseModel",
-                    "id": "1",
-                    "args": WEATHER_DATA,
-                },
-                {
-                    "name": "LocationResponse",
-                    "id": "2",
-                    "args": LOCATION_DATA,
-                },
-            ],
-            [
-                {
-                    "name": "WeatherBaseModel",
-                    "id": "3",
-                    "args": WEATHER_DATA,
-                },
-            ],
-        ]
-
-        model = FakeToolCallingModel(tool_calls=tool_calls)
-
-        def custom_message(exception: Exception) -> str:
-            if isinstance(exception, MultipleStructuredOutputsError):
-                return "Custom error: Multiple outputs not allowed"
-            return "Custom error"
-
-        agent = create_react_agent(
-            model,
-            [],
-            response_format=ToolOutput(
-                Union[WeatherBaseModel, LocationResponse],
-                handle_errors=custom_message,
-            ),
-        )
-
-        response = agent.invoke({"messages": [HumanMessage("Give me weather")]})
-
-        # HumanMessage, AIMessage, ToolMessage, ToolMessage, AI, ToolMessage
-        assert len(response["messages"]) == 6
-        assert (
-            response["messages"][2].content
-            == "Custom error: Multiple outputs not allowed"
-        )
-        assert (
-            response["messages"][3].content
-            == "Custom error: Multiple outputs not allowed"
-        )
-        assert response["structured_response"] == EXPECTED_WEATHER_PYDANTIC
-
-    def test_retry_with_custom_string_message(self) -> None:
-        """Test retry with custom static string message."""
-        tool_calls = [
-            [
-                {
-                    "name": "WeatherBaseModel",
-                    "id": "1",
-                    "args": {"invalid": "data"},
-                },
-            ],
-            [
-                {
-                    "name": "WeatherBaseModel",
-                    "id": "2",
-                    "args": WEATHER_DATA,
-                },
-            ],
-        ]
-
-        model = FakeToolCallingModel(tool_calls=tool_calls)
-
-        agent = create_react_agent(
-            model,
-            [],
-            response_format=ToolOutput(
-                WeatherBaseModel,
-                handle_errors="Please provide valid weather data with temperature and condition.",
-            ),
-        )
-
-        response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
-
-        assert len(response["messages"]) == 5
-        assert (
-            response["messages"][2].content
-            == "Please provide valid weather data with temperature and condition."
-        )
-        assert response["structured_response"] == EXPECTED_WEATHER_PYDANTIC
-
-
-class TestResponseFormatAsNativeOutput:
-    def test_pydantic_model(self) -> None:
-        """Test response_format as NativeOutput with Pydantic model."""
-        tool_calls = [
-            [{"args": {}, "id": "1", "name": "get_weather"}],
-        ]
-
-        model = FakeToolCallingModel[WeatherBaseModel](
-            tool_calls=tool_calls, structured_response=EXPECTED_WEATHER_PYDANTIC
-        )
-
-        agent = create_react_agent(
-            model, [get_weather], response_format=NativeOutput(WeatherBaseModel)
-        )
-        response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
-
-        assert response["structured_response"] == EXPECTED_WEATHER_PYDANTIC
-        assert len(response["messages"]) == 4
-
-    def test_dataclass(self) -> None:
-        """Test response_format as NativeOutput with dataclass."""
-        tool_calls = [
-            [{"args": {}, "id": "1", "name": "get_weather"}],
-        ]
-
-        model = FakeToolCallingModel[WeatherDataclass](
-            tool_calls=tool_calls, structured_response=EXPECTED_WEATHER_DATACLASS
-        )
-
-        agent = create_react_agent(
-            model, [get_weather], response_format=NativeOutput(WeatherDataclass)
-        )
-        response = agent.invoke(
-            {"messages": [HumanMessage("What's the weather?")]},
-        )
-
-        assert response["structured_response"] == EXPECTED_WEATHER_DATACLASS
-        assert len(response["messages"]) == 4
-
-    def test_typed_dict(self) -> None:
-        """Test response_format as NativeOutput with TypedDict."""
-        tool_calls = [
-            [{"args": {}, "id": "1", "name": "get_weather"}],
-        ]
-
-        model = FakeToolCallingModel[WeatherTypedDict](
-            tool_calls=tool_calls, structured_response=EXPECTED_WEATHER_DICT
-        )
-
-        agent = create_react_agent(
-            model, [get_weather], response_format=NativeOutput(WeatherTypedDict)
-        )
-        response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
-
-        assert response["structured_response"] == EXPECTED_WEATHER_DICT
-        assert len(response["messages"]) == 4
-
-    def test_json_schema(self) -> None:
-        """Test response_format as NativeOutput with JSON schema."""
-        tool_calls = [
-            [{"args": {}, "id": "1", "name": "get_weather"}],
-        ]
-
-        model = FakeToolCallingModel[dict](
-            tool_calls=tool_calls, structured_response=EXPECTED_WEATHER_DICT
-        )
-
-        agent = create_react_agent(
-            model, [get_weather], response_format=NativeOutput(weather_json_schema)
-        )
-        response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
-
-        assert response["structured_response"] == EXPECTED_WEATHER_DICT
-        assert len(response["messages"]) == 4
-
-
-def test_union_of_types() -> None:
-    """Test response_format as NativeOutput with Union (if supported)."""
-    tool_calls = [
-        [{"args": {}, "id": "1", "name": "get_weather"}],
-        [
-            {
-                "name": "WeatherBaseModel",
-                "id": "2",
-                "args": WEATHER_DATA,
-            }
-        ],
-    ]
-
-    model = FakeToolCallingModel[Union[WeatherBaseModel, LocationResponse]](
-        tool_calls=tool_calls, structured_response=EXPECTED_WEATHER_PYDANTIC
-    )
-
-    agent = create_react_agent(
-        model,
-        [get_weather, get_location],
-        response_format=ToolOutput(Union[WeatherBaseModel, LocationResponse]),
-    )
-    response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
-
-    assert response["structured_response"] == EXPECTED_WEATHER_PYDANTIC
-    assert len(response["messages"]) == 5
-
-
-@pytest.mark.skipif(
-    skip_openai_integration_tests, reason="OpenAI integration tests are disabled."
-)
-def test_inference_to_native_output() -> None:
-    """Test that native output is inferred when a model supports it."""
-    model = ChatOpenAI(model="gpt-5")
-    agent = create_react_agent(
-        model,
-        prompt="You are a helpful weather assistant. Please call the get_weather tool, then use the WeatherReport tool to generate the final response.",
-        tools=[get_weather],
-        response_format=WeatherBaseModel,
-    )
-    response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
-
-    assert isinstance(response["structured_response"], WeatherBaseModel)
-    assert response["structured_response"].temperature == 75.0
-    assert response["structured_response"].condition.lower() == "sunny"
-    assert len(response["messages"]) == 4
-
-    assert [m.type for m in response["messages"]] == [
-        "human",  # "What's the weather?"
-        "ai",  # "What's the weather?"
-        "tool",  # "The weather is sunny and 75°F."
-        "ai",  # structured response
-    ]
-
-
-@pytest.mark.skipif(
-    skip_openai_integration_tests, reason="OpenAI integration tests are disabled."
-)
-def test_inference_to_tool_output() -> None:
-    """Test that tool output is inferred when a model supports it."""
-    model = ChatOpenAI(model="gpt-4")
-    agent = create_react_agent(
-        model,
-        prompt="You are a helpful weather assistant. Please call the get_weather tool, then use the WeatherReport tool to generate the final response.",
-        tools=[get_weather],
-        response_format=ToolOutput(WeatherBaseModel),
-    )
-    response = agent.invoke({"messages": [HumanMessage("What's the weather?")]})
-
-    assert isinstance(response["structured_response"], WeatherBaseModel)
-    assert response["structured_response"].temperature == 75.0
-    assert response["structured_response"].condition.lower() == "sunny"
-    assert len(response["messages"]) == 5
-
-    assert [m.type for m in response["messages"]] == [
-        "human",  # "What's the weather?"
-        "ai",  # "What's the weather?"
-        "tool",  # "The weather is sunny and 75°F."
-        "ai",  # structured response
-        "tool",  # artificial tool message
-    ]

libs/prebuilt/tests/test_responses.py

@@ -1,154 +0,0 @@
-"""Unit tests for langgraph.prebuilt.responses module."""
-
-from typing import Union
-
-import pytest
-from pydantic import BaseModel
-
-from langgraph.prebuilt.responses import (
-    OutputToolBinding,
-    ToolOutput,
-    _SchemaSpec,
-)
-
-
-class _TestModel(BaseModel):
-    """A test model for structured output."""
-
-    name: str
-    age: int
-    email: str = "default@example.com"
-
-
-class CustomModel(BaseModel):
-    """Custom model with a custom docstring."""
-
-    value: float
-    description: str
-
-
-class EmptyDocModel(BaseModel):
-    # No custom docstring, should have no description in tool
-    data: str
-
-
-class TestUsingToolStrategy:
-    """Test UsingToolStrategy dataclass."""
-
-    def test_basic_creation(self):
-        """Test basic UsingToolStrategy creation."""
-        strategy = ToolOutput(schema=_TestModel)
-        assert strategy.schema == _TestModel
-        assert strategy.tool_message_content is None
-        assert len(strategy.schema_specs) == 1
-
-    def test_multiple_schemas(self):
-        """Test UsingToolStrategy with multiple schemas."""
-        strategy = ToolOutput(schema=Union[_TestModel, CustomModel])
-        assert len(strategy.schema_specs) == 2
-        assert strategy.schema_specs[0].schema == _TestModel
-        assert strategy.schema_specs[1].schema == CustomModel
-
-    def test_schema_with_tool_message_content(self):
-        """Test UsingToolStrategy with tool message content."""
-        strategy = ToolOutput(schema=_TestModel, tool_message_content="custom message")
-        assert strategy.schema == _TestModel
-        assert strategy.tool_message_content == "custom message"
-        assert len(strategy.schema_specs) == 1
-
-
-class TestOutputToolBinding:
-    """Test OutputToolBinding dataclass and its methods."""
-
-    def test_from_schema_spec_basic(self):
-        """Test basic OutputToolBinding creation from SchemaSpec."""
-        schema_spec = _SchemaSpec(schema=_TestModel)
-        tool_binding = OutputToolBinding.from_schema_spec(schema_spec)
-
-        assert tool_binding.schema == _TestModel
-        assert tool_binding.schema_kind == "pydantic"
-        assert tool_binding.tool is not None
-        assert tool_binding.tool.name == "_TestModel"
-
-    def test_from_schema_spec_with_custom_name(self):
-        """Test OutputToolBinding creation with custom name."""
-        schema_spec = _SchemaSpec(schema=_TestModel, name="custom_tool_name")
-        tool_binding = OutputToolBinding.from_schema_spec(schema_spec)
-        assert tool_binding.tool.name == "custom_tool_name"
-
-    def test_from_schema_spec_with_custom_description(self):
-        """Test OutputToolBinding creation with custom description."""
-        schema_spec = _SchemaSpec(
-            schema=_TestModel, description="Custom tool description"
-        )
-        tool_binding = OutputToolBinding.from_schema_spec(schema_spec)
-
-        assert tool_binding.tool.description == "Custom tool description"
-
-    def test_from_schema_spec_with_model_docstring(self):
-        """Test OutputToolBinding creation using model docstring as description."""
-        schema_spec = _SchemaSpec(schema=CustomModel)
-        tool_binding = OutputToolBinding.from_schema_spec(schema_spec)
-
-        assert tool_binding.tool.description == "Custom model with a custom docstring."
-
-    @pytest.mark.skip(
-        reason="Need to fix bug in langchain-core for inheritance of doc-strings."
-    )
-    def test_from_schema_spec_empty_docstring(self):
-        """Test OutputToolBinding creation with model that has default docstring."""
-
-        # Create a model with the same docstring as BaseModel
-        class DefaultDocModel(BaseModel):
-            # This should have the same docstring as BaseModel
-            pass
-
-        schema_spec = _SchemaSpec(schema=DefaultDocModel)
-        tool_binding = OutputToolBinding.from_schema_spec(schema_spec)
-
-        # Should use empty description when model has default BaseModel docstring
-        assert tool_binding.tool.description == ""
-
-    def test_parse_payload_pydantic_success(self):
-        """Test successful parsing for Pydantic model."""
-        schema_spec = _SchemaSpec(schema=_TestModel)
-        tool_binding = OutputToolBinding.from_schema_spec(schema_spec)
-
-        tool_args = {"name": "John", "age": 30}
-        result = tool_binding.parse(tool_args)
-
-        assert isinstance(result, _TestModel)
-        assert result.name == "John"
-        assert result.age == 30
-        assert result.email == "default@example.com"  # default value
-
-    def test_parse_payload_pydantic_validation_error(self):
-        """Test parsing failure for invalid Pydantic data."""
-        schema_spec = _SchemaSpec(schema=_TestModel)
-        tool_binding = OutputToolBinding.from_schema_spec(schema_spec)
-
-        # Missing required field 'name'
-        tool_args = {"age": 30}
-
-        with pytest.raises(ValueError, match="Failed to parse data to _TestModel"):
-            tool_binding.parse(tool_args)
-
-
-class TestEdgeCases:
-    """Test edge cases and error conditions."""
-
-    def test_empty_schemas_list(self) -> None:
-        """Test UsingToolStrategy with empty schemas list."""
-        strategy = ToolOutput(EmptyDocModel)
-        assert len(strategy.schema_specs) == 1
-
-    @pytest.mark.skip(
-        reason="Need to fix bug in langchain-core for inheritance of doc-strings."
-    )
-    def test_base_model_doc_constant(self) -> None:
-        """Test that BASE_MODEL_DOC constant is set correctly."""
-        binding = OutputToolBinding.from_schema_spec(_SchemaSpec(EmptyDocModel))
-        assert binding.tool.name == "EmptyDocModel"
-        assert (
-            binding.tool.description[:5] == ""
-        )  # Should be empty for default docstring

libs/prebuilt/tests/test_responses_spec.py

@@ -1,160 +0,0 @@
-from __future__ import annotations
-
-from typing import Any, Dict, List, Optional, Union
-from unittest.mock import MagicMock
-
-import httpx
-import pytest
-from langchain_core.messages import HumanMessage
-from langchain_core.tools import tool
-from pydantic import BaseModel, create_model
-
-from langgraph.prebuilt import create_react_agent
-from langgraph.prebuilt.responses import ToolOutput
-from tests.utils import BaseSchema, load_spec
-
-try:
-    from langchain_openai import ChatOpenAI
-except ImportError:
-    skip_openai_integration_tests = True
-else:
-    skip_openai_integration_tests = False
-
-AGENT_PROMPT = "You are an HR assistant."
-
-
-class ToolCalls(BaseSchema):
-    get_employee_role: int
-    get_employee_department: int
-
-
-class AssertionByInvocation(BaseSchema):
-    prompt: str
-    tools_with_expected_calls: ToolCalls
-    expected_last_message: str
-    expected_structured_response: Optional[Dict[str, Any]]
-    llm_request_count: int
-
-
-class TestCase(BaseSchema):
-    name: str
-    response_format: Union[Dict[str, Any], List[Dict[str, Any]]]
-    assertions_by_invocation: List[AssertionByInvocation]
-
-
-class Employee(BaseModel):
-    name: str
-    role: str
-    department: str
-
-
-EMPLOYEES: list[Employee] = [
-    Employee(name="Sabine", role="Developer", department="IT"),
-    Employee(name="Henrik", role="Product Manager", department="IT"),
-    Employee(name="Jessica", role="HR", department="People"),
-]
-
-TEST_CASES = load_spec("responses", as_model=TestCase)
-
-
-def _make_tool(fn, *, name: str, description: str):
-    mock = MagicMock(side_effect=lambda *, name: fn(name=name))
-    InputModel = create_model(f"{name}_input", name=(str, ...))
-
-    @tool(name, description=description, args_schema=InputModel)
-    def _wrapped(name: str):
-        return mock(name=name)
-
-    return {"tool": _wrapped, "mock": mock}
-
-
-@pytest.mark.skipif(
-    skip_openai_integration_tests, reason="OpenAI integration tests are disabled."
-)
-@pytest.mark.parametrize("case", TEST_CASES, ids=[c.name for c in TEST_CASES])
-def test_responses_integration_matrix(case: TestCase) -> None:
-    if case.name == "asking for information that does not fit into the response format":
-        pytest.xfail(
-            "currently failing due to undefined behavior when model cannot conform to any of the structured response formats."
-        )
-
-    def get_employee_role(*, name: str) -> Optional[str]:
-        for e in EMPLOYEES:
-            if e.name == name:
-                return e.role
-        return None
-
-    def get_employee_department(*, name: str) -> Optional[str]:
-        for e in EMPLOYEES:
-            if e.name == name:
-                return e.department
-        return None
-
-    role_tool = _make_tool(
-        get_employee_role,
-        name="get_employee_role",
-        description="Get the employee role by name",
-    )
-    dept_tool = _make_tool(
-        get_employee_department,
-        name="get_employee_department",
-        description="Get the employee department by name",
-    )
-
-    response_format_spec = case.response_format
-    if isinstance(response_format_spec, dict):
-        response_format_spec = [response_format_spec]
-    # Unwrap nested schema objects
-    response_format_spec = [item.get("schema", item) for item in response_format_spec]
-    if len(response_format_spec) == 1:
-        tool_output = ToolOutput(response_format_spec[0])
-    else:
-        tool_output = ToolOutput({"oneOf": response_format_spec})
-
-    llm_request_count = 0
-
-    for assertion in case.assertions_by_invocation:
-
-        def on_request(request: httpx.Request) -> None:
-            nonlocal llm_request_count
-            llm_request_count += 1
-
-        http_client = httpx.Client(
-            event_hooks={"request": [on_request]},
-        )
-
-        model = ChatOpenAI(
-            model="gpt-4o",
-            temperature=0,
-            http_client=http_client,
-        )
-
-        agent = create_react_agent(
-            model,
-            tools=[role_tool["tool"], dept_tool["tool"]],
-            prompt=AGENT_PROMPT,
-            response_format=tool_output,
-        )
-
-        result = agent.invoke({"messages": [HumanMessage(assertion.prompt)]})
-
-        # Count tool calls
-        assert (
-            role_tool["mock"].call_count
-            == assertion.tools_with_expected_calls.get_employee_role
-        )
-        assert (
-            dept_tool["mock"].call_count
-            == assertion.tools_with_expected_calls.get_employee_department
-        )
-
-        # Count LLM calls
-        assert llm_request_count == assertion.llm_request_count
-
-        # Check last message content
-        last_message = result["messages"][-1]
-        assert last_message.content == assertion.expected_last_message
-
-        # Check structured response
-        structured_response_json = result["structured_response"]
-        assert structured_response_json == assertion.expected_structured_response

libs/prebuilt/tests/test_return_direct_spec.py

@@ -1,117 +0,0 @@
-from __future__ import annotations
-
-from typing import Any, Dict, Optional
-from unittest.mock import MagicMock
-
-import pytest
-from langchain_core.messages import HumanMessage
-from langchain_core.tools import tool
-
-from langgraph.prebuilt import create_react_agent
-from langgraph.prebuilt.responses import ToolOutput
-from tests.utils import BaseSchema, load_spec
-
-try:
-    from langchain_openai import ChatOpenAI
-except ImportError:
-    skip_openai_integration_tests = True
-else:
-    skip_openai_integration_tests = False
-
-AGENT_PROMPT = """
-You are a strict polling bot.
-
-- Only use the "poll_job" tool until it returns { status: "succeeded" }.
-- If status is "pending", call the tool again. Do not produce a final answer.
-- When it is "succeeded", return exactly: "Attempts: <number>" with no extra text.
-"""
-
-
-class TestCase(BaseSchema):
-    name: str
-    return_direct: bool
-    response_format: Optional[Dict[str, Any]]
-    expected_tool_calls: int
-    expected_last_message: str
-    expected_structured_response: Optional[Dict[str, Any]]
-
-
-TEST_CASES = load_spec("return_direct", as_model=TestCase)
-
-
-def _make_tool(return_direct: bool):
-    attempts = 0
-
-    def _side_effect():
-        nonlocal attempts
-        attempts += 1
-        return {
-            "status": "succeeded" if attempts >= 10 else "pending",
-            "attempts": attempts,
-        }
-
-    mock = MagicMock(side_effect=_side_effect)
-
-    @tool(
-        "pollJob",
-        description=(
-            "Check the status of a long-running job. "
-            "Returns { status: 'pending' | 'succeeded', attempts: number }."
-        ),
-        return_direct=return_direct,
-    )
-    def _wrapped():
-        return mock()
-
-    return {"tool": _wrapped, "mock": mock}
-
-
-@pytest.mark.skipif(
-    skip_openai_integration_tests, reason="OpenAI integration tests are disabled."
-)
-@pytest.mark.parametrize("case", TEST_CASES, ids=[c.name for c in TEST_CASES])
-def test_return_direct_integration_matrix(case: TestCase) -> None:
-    poll_tool = _make_tool(case.return_direct)
-
-    model = ChatOpenAI(
-        model="gpt-4o",
-        temperature=0,
-    )
-
-    if case.response_format:
-        agent = create_react_agent(
-            model,
-            tools=[poll_tool["tool"]],
-            prompt=AGENT_PROMPT,
-            response_format=ToolOutput(case.response_format),
-        )
-    else:
-        agent = create_react_agent(
-            model,
-            tools=[poll_tool["tool"]],
-            prompt=AGENT_PROMPT,
-        )
-
-    result = agent.invoke(
-        {
-            "messages": [
-                HumanMessage(
-                    "Poll the job until it's done and tell me how many attempts it took."
-                )
-            ]
-        }
-    )
-
-    # Count tool calls
-    assert poll_tool["mock"].call_count == case.expected_tool_calls
-
-    # Check last message content
-    last_message = result["messages"][-1]
-    assert last_message.content == case.expected_last_message
-
-    # Check structured response
-    if case.expected_structured_response is not None:
-        structured_response_json = result["structured_response"]
-        assert structured_response_json == case.expected_structured_response
-    else:
-        assert "structured_response" not in result

libs/prebuilt/tests/test_tool_node.py

@@ -1,49 +1,25 @@
-import dataclasses
-import json
-from functools import partial
 from typing import (
     Annotated,
     Any,
-    List,
-    Type,
-    TypeVar,
     Union,
 )
 
 import pytest
 from langchain_core.messages import (
     AIMessage,
-    AnyMessage,
-    HumanMessage,
     RemoveMessage,
-    ToolCall,
     ToolMessage,
 )
 from langchain_core.tools import BaseTool, ToolException
 from langchain_core.tools import tool as dec_tool
-from pydantic import BaseModel
-from pydantic.v1 import BaseModel as BaseModelV1
-from typing_extensions import TypedDict
+from pydantic import BaseModel, ValidationError
+from pydantic.v1 import ValidationError as ValidationErrorV1
 
-from langgraph.config import get_stream_writer
 from langgraph.errors import GraphBubbleUp, GraphInterrupt
-from langgraph.graph import START, MessagesState, StateGraph
-from langgraph.graph.message import REMOVE_ALL_MESSAGES, add_messages
-from langgraph.prebuilt import (
-    ToolNode,
-)
-from langgraph.prebuilt.tool_node import (
-    TOOL_CALL_ERROR_TEMPLATE,
-    InjectedState,
-    InjectedStore,
-    ToolInvocationError,
-    tools_condition,
-)
-from langgraph.store.base import BaseStore
-from langgraph.store.memory import InMemoryStore
+from langgraph.graph.message import REMOVE_ALL_MESSAGES
+from langgraph.prebuilt import ToolNode
+from langgraph.prebuilt.tool_node import TOOL_CALL_ERROR_TEMPLATE
 from langgraph.types import Command, Send
-from tests.messages import _AnyIdHumanMessage, _AnyIdToolMessage
-from tests.model import FakeToolCallingModel
 
 pytestmark = pytest.mark.anyio
 
@@ -86,8 +62,7 @@ def tool5(some_val: int):
 tool5.handle_tool_error = "foo"
 
 
-async def test_tool_node() -> None:
-    """Test tool node."""
+async def test_tool_node():
     result = ToolNode([tool1]).invoke(
         {
             "messages": [
@@ -179,7 +154,7 @@ async def test_tool_node() -> None:
     assert tool_message.tool_call_id == "some 3"
 
 
-async def test_tool_node_tool_call_input() -> None:
+async def test_tool_node_tool_call_input():
     # Single tool call
     tool_call_1 = {
         "name": "tool1",
@@ -220,67 +195,17 @@ async def test_tool_node_tool_call_input() -> None:
     ]
 
 
-def test_tool_node_error_handling_default_invocation() -> None:
-    tn = ToolNode([tool1])
-    result = tn.invoke(
-        {
-            "messages": [
-                AIMessage(
-                    "hi?",
-                    tool_calls=[
-                        {
-                            "name": "tool1",
-                            "args": {"invalid": 0, "args": "foo"},
-                            "id": "some id",
-                        },
-                    ],
-                )
-            ]
-        }
-    )
-
-    assert all(m.type == "tool" for m in result["messages"])
-    assert all(m.status == "error" for m in result["messages"])
-    assert (
-        "Error invoking tool 'tool1' with kwargs {'invalid': 0, 'args': 'foo'} with error:\n"
-        in result["messages"][0].content
-    )
-
-
-def test_tool_node_error_handling_default_exception() -> None:
-    tn = ToolNode([tool1])
-    with pytest.raises(ValueError):
-        tn.invoke(
-            {
-                "messages": [
-                    AIMessage(
-                        "hi?",
-                        tool_calls=[
-                            {
-                                "name": "tool1",
-                                "args": {"some_val": 0, "some_other_val": "foo"},
-                                "id": "some id",
-                            },
-                        ],
-                    )
-                ]
-            }
-        )
-
-
-async def test_tool_node_error_handling() -> None:
-    def handle_all(e: Union[ValueError, ToolException, ToolInvocationError]):
+async def test_tool_node_error_handling():
+    def handle_all(e: Union[ValueError, ToolException, ValidationError]):
         return TOOL_CALL_ERROR_TEMPLATE.format(error=repr(e))
 
     # test catching all exceptions, via:
     # - handle_tool_errors = True
-    # - passing a single exception
     # - passing a tuple of all exceptions
     # - passing a callable with all exceptions in the signature
     for handle_tool_errors in (
         True,
-        Exception,
-        (ValueError, ToolException, ToolInvocationError),
+        (ValueError, ToolException, ValidationError),
         handle_all,
     ):
         result_error = await ToolNode(
@@ -332,7 +257,7 @@ async def test_tool_node_error_handling() -> None:
         assert result_error["messages"][2].tool_call_id == "another id"
 
 
-async def test_tool_node_error_handling_callable() -> None:
+async def test_tool_node_error_handling_callable():
     def handle_value_error(e: ValueError):
         return "Value error"
 
@@ -463,7 +388,7 @@ async def test_tool_node_handle_tool_errors_false():
     assert str(exc_info.value) == "Test error"
 
     # test validation errors get raised if handle_tool_errors is False
-    with pytest.raises((ToolInvocationError)):
+    with pytest.raises((ValidationError, ValidationErrorV1)):
         ToolNode([tool1], handle_tool_errors=False).invoke(
             {
                 "messages": [
@@ -1233,302 +1158,34 @@ async def test_tool_node_command_remove_all_messages():
     assert command.update == {"messages": [RemoveMessage(id=REMOVE_ALL_MESSAGES)]}
 
 
-class _InjectStateSchema(TypedDict):
-    messages: list
-    foo: str
+async def test_async_tool_called_syncly() -> None:
+    """Confirm that async tools can be called synchronously."""
 
-
-class _InjectedStatePydanticSchema(BaseModelV1):
-    messages: list
-    foo: str
-
-
-class _InjectedStatePydanticV2Schema(BaseModel):
-    messages: list
-    foo: str
-
-
-@dataclasses.dataclass
-class _InjectedStateDataclassSchema:
-    messages: list
-    foo: str
-
-
-T = TypeVar("T")
-
-
-@pytest.mark.parametrize(
-    "schema_",
-    [
-        _InjectStateSchema,
-        _InjectedStatePydanticSchema,
-        _InjectedStatePydanticV2Schema,
-        _InjectedStateDataclassSchema,
-    ],
-)
-def test_tool_node_inject_state(schema_: Type[T]) -> None:
-    def tool1(some_val: int, state: Annotated[T, InjectedState]) -> str:
-        """Tool 1 docstring."""
-        if isinstance(state, dict):
-            return state["foo"]
-        else:
-            return getattr(state, "foo")
-
-    def tool2(some_val: int, state: Annotated[T, InjectedState()]) -> str:
-        """Tool 2 docstring."""
-        if isinstance(state, dict):
-            return state["foo"]
-        else:
-            return getattr(state, "foo")
-
-    def tool3(
-        some_val: int,
-        foo: Annotated[str, InjectedState("foo")],
-        msgs: Annotated[List[AnyMessage], InjectedState("messages")],
-    ) -> str:
-        """Tool 1 docstring."""
-        return foo
-
-    def tool4(
-        some_val: int, msgs: Annotated[List[AnyMessage], InjectedState("messages")]
-    ) -> str:
-        """Tool 1 docstring."""
-        return msgs[0].content
-
-    node = ToolNode([tool1, tool2, tool3, tool4], handle_tool_errors=True)
-    for tool_name in ("tool1", "tool2", "tool3"):
-        tool_call = {
-            "name": tool_name,
-            "args": {"some_val": 1},
-            "id": "some 0",
-            "type": "tool_call",
-        }
-        msg = AIMessage("hi?", tool_calls=[tool_call])
-        result = node.invoke(schema_(**{"messages": [msg], "foo": "bar"}))
-        tool_message = result["messages"][-1]
-        assert tool_message.content == "bar", f"Failed for tool={tool_name}"
-
-        if tool_name == "tool3":
-            failure_input = None
-            try:
-                failure_input = schema_(**{"messages": [msg], "notfoo": "bar"})
-            except Exception:
-                pass
-            if failure_input is not None:
-                with pytest.raises(KeyError):
-                    node.invoke(failure_input)
-
-                with pytest.raises(ValueError):
-                    node.invoke([msg])
-        else:
-            failure_input = None
-            try:
-                failure_input = schema_(**{"messages": [msg], "notfoo": "bar"})
-            except Exception:
-                # We'd get a validation error from pydantic state and wouldn't make it to the node
-                # anyway
-                pass
-            if failure_input is not None:
-                messages_ = node.invoke(failure_input)
-                tool_message = messages_["messages"][-1]
-                assert "KeyError" in tool_message.content
-                tool_message = node.invoke([msg])[-1]
-                assert "KeyError" in tool_message.content
-
-    tool_call = {
-        "name": "tool4",
-        "args": {"some_val": 1},
-        "id": "some 0",
-        "type": "tool_call",
-    }
-    msg = AIMessage("hi?", tool_calls=[tool_call])
-    result = node.invoke(schema_(**{"messages": [msg], "foo": ""}))
-    tool_message = result["messages"][-1]
-    assert tool_message.content == "hi?"
-
-    result = node.invoke([msg])
-    tool_message = result[-1]
-    assert tool_message.content == "hi?"
-
-
-def test_tool_node_inject_store() -> None:
-    store = InMemoryStore()
-    namespace = ("test",)
-
-    def tool1(some_val: int, store: Annotated[BaseStore, InjectedStore()]) -> str:
-        """Tool 1 docstring."""
-        store_val = store.get(namespace, "test_key").value["foo"]
-        return f"Some val: {some_val}, store val: {store_val}"
-
-    def tool2(some_val: int, store: Annotated[BaseStore, InjectedStore()]) -> str:
-        """Tool 2 docstring."""
-        store_val = store.get(namespace, "test_key").value["foo"]
-        return f"Some val: {some_val}, store val: {store_val}"
-
-    def tool3(
-        some_val: int,
-        bar: Annotated[str, InjectedState("bar")],
-        store: Annotated[BaseStore, InjectedStore()],
-    ) -> str:
-        """Tool 3 docstring."""
-        store_val = store.get(namespace, "test_key").value["foo"]
-        return f"Some val: {some_val}, store val: {store_val}, state val: {bar}"
-
-    node = ToolNode([tool1, tool2, tool3], handle_tool_errors=True)
-    store.put(namespace, "test_key", {"foo": "bar"})
-
-    class State(MessagesState):
-        bar: str
-
-    builder = StateGraph(State)
-    builder.add_node("tools", node)
-    builder.add_edge(START, "tools")
-    graph = builder.compile(store=store)
-
-    for tool_name in ("tool1", "tool2"):
-        tool_call = {
-            "name": tool_name,
-            "args": {"some_val": 1},
-            "id": "some 0",
-            "type": "tool_call",
-        }
-        msg = AIMessage("hi?", tool_calls=[tool_call])
-        node_result = node.invoke({"messages": [msg]}, store=store)
-        graph_result = graph.invoke({"messages": [msg]})
-        for result in (node_result, graph_result):
-            result["messages"][-1]
-            tool_message = result["messages"][-1]
-            assert tool_message.content == "Some val: 1, store val: bar", (
-                f"Failed for tool={tool_name}"
-            )
-
-    tool_call = {
-        "name": "tool3",
-        "args": {"some_val": 1},
-        "id": "some 0",
-        "type": "tool_call",
-    }
-    msg = AIMessage("hi?", tool_calls=[tool_call])
-    node_result = node.invoke({"messages": [msg], "bar": "baz"}, store=store)
-    graph_result = graph.invoke({"messages": [msg], "bar": "baz"})
-    for result in (node_result, graph_result):
-        result["messages"][-1]
-        tool_message = result["messages"][-1]
-        assert tool_message.content == "Some val: 1, store val: bar, state val: baz", (
-            f"Failed for tool={tool_name}"
-        )
-
-    # test injected store without passing store to compiled graph
-    failing_graph = builder.compile()
-    with pytest.raises(ValueError):
-        failing_graph.invoke({"messages": [msg], "bar": "baz"})
-
-
-def test_tool_node_ensure_utf8() -> None:
     @dec_tool
-    def get_day_list(days: list[str]) -> list[str]:
-        """choose days"""
-        return days
+    async def async_tool():
+        """An async tool."""
+        return "async tool"
 
-    data = ["星期一", "水曜日", "목요일", "Friday"]
-    tools = [get_day_list]
-    tool_calls = [ToolCall(name=get_day_list.name, args={"days": data}, id="test_id")]
-    outputs: list[ToolMessage] = ToolNode(tools).invoke(
-        [AIMessage(content="", tool_calls=tool_calls)]
-    )
-    assert outputs[0].content == json.dumps(data, ensure_ascii=False)
-
-
-def test_tool_node_messages_key() -> None:
-    @dec_tool
-    def add(a: int, b: int):
-        """Adds a and b."""
-        return a + b
-
-    model = FakeToolCallingModel(
-        tool_calls=[[ToolCall(name=add.name, args={"a": 1, "b": 2}, id="test_id")]]
-    )
-
-    class State(TypedDict):
-        subgraph_messages: Annotated[list[AnyMessage], add_messages]
-
-    def call_model(state: State):
-        response = model.invoke(state["subgraph_messages"])
-        model.tool_calls = []
-        return {"subgraph_messages": response}
-
-    builder = StateGraph(State)
-    builder.add_node("agent", call_model)
-    builder.add_node("tools", ToolNode([add], messages_key="subgraph_messages"))
-    builder.add_conditional_edges(
-        "agent", partial(tools_condition, messages_key="subgraph_messages")
-    )
-    builder.add_edge(START, "agent")
-    builder.add_edge("tools", "agent")
-
-    graph = builder.compile()
-    result = graph.invoke({"subgraph_messages": [HumanMessage(content="hi")]})
-    assert result["subgraph_messages"] == [
-        _AnyIdHumanMessage(content="hi"),
-        AIMessage(
-            content="hi",
-            id="0",
-            tool_calls=[ToolCall(name=add.name, args={"a": 1, "b": 2}, id="test_id")],
-        ),
-        _AnyIdToolMessage(content="3", name=add.name, tool_call_id="test_id"),
-        AIMessage(content="hi-hi-3", id="1"),
-    ]
-
-
-def test_tool_node_stream_writer() -> None:
-    @dec_tool
-    def streaming_tool(x: int) -> str:
-        """Do something with writer."""
-        my_writer = get_stream_writer()
-        for value in ["foo", "bar", "baz"]:
-            my_writer({"custom_tool_value": value})
-
-        return x
-
-    tool_node = ToolNode([streaming_tool])
-    graph = (
-        StateGraph(MessagesState)
-        .add_node("tools", tool_node)
-        .add_edge(START, "tools")
-        .compile()
-    )
-
-    tool_call = {
-        "name": "streaming_tool",
-        "args": {"x": 1},
-        "id": "1",
-        "type": "tool_call",
-    }
-    inputs = {
-        "messages": [AIMessage("", tool_calls=[tool_call])],
-    }
-
-    assert list(graph.stream(inputs, stream_mode="custom")) == [
-        {"custom_tool_value": "foo"},
-        {"custom_tool_value": "bar"},
-        {"custom_tool_value": "baz"},
-    ]
-    assert list(graph.stream(inputs, stream_mode=["custom", "updates"])) == [
-        ("custom", {"custom_tool_value": "foo"}),
-        ("custom", {"custom_tool_value": "bar"}),
-        ("custom", {"custom_tool_value": "baz"}),
-        (
-            "updates",
-            {
-                "tools": {
-                    "messages": [
-                        _AnyIdToolMessage(
-                            content="1",
-                            name="streaming_tool",
-                            tool_call_id="1",
-                        ),
+    tool_node = ToolNode([async_tool])
+    result = tool_node.invoke(
+        {
+            "messages": [
+                AIMessage(
+                    content="",
+                    tool_calls=[
+                        {
+                            "name": "async_tool",
+                            "args": {},
+                            "id": "1",
+                            "type": "tool_call",
+                        }
                     ],
-                },
-            },
-        ),
-    ]
+                )
+            ]
+        }
+    )
+    assert result == {
+        "messages": [
+            ToolMessage(content="async tool", name="async_tool", tool_call_id="1")
+        ]
+    }

libs/prebuilt/tests/utils.py

@@ -1,22 +0,0 @@
-import json
-from pathlib import Path
-from typing import Type
-
-from pydantic import BaseModel, ConfigDict
-from pydantic.alias_generators import to_camel
-
-
-class BaseSchema(BaseModel):
-    model_config = ConfigDict(
-        alias_generator=to_camel,
-        populate_by_name=True,
-        from_attributes=True,
-    )
-
-
-def load_spec(spec_name: str, as_model: Type[BaseModel]) -> list[BaseModel]:
-    with (Path(__file__).parent / "specifications" / f"{spec_name}.json").open(
-        "r", encoding="utf-8"
-    ) as f:
-        data = json.load(f)
-        return [as_model(**item) for item in data]

libs/prebuilt/uv.lock

@@ -316,7 +316,7 @@ wheels = [
 
 [[package]]
 name = "langgraph"
-version = "0.6.4"
+version = "0.6.6"
 source = { editable = "../langgraph" }
 dependencies = [
     { name = "langchain-core" },
@@ -509,7 +509,6 @@ dev = [
 
 [[package]]
 name = "langgraph-sdk"
-version = "0.2.0"
 source = { editable = "../sdk-py" }
 dependencies = [
     { name = "httpx" },

libs/sdk-py/Makefile

@@ -1,7 +1,7 @@
-.PHONY: lint format
+.PHONY: lint format test
 
 test:
-	echo "No tests to run"
+	uv run pytest tests
 
 ######################
 # LINTING AND FORMATTING
@@ -17,7 +17,7 @@ lint lint_diff:
 	uv run ruff check .
 	[ "$(PYTHON_FILES)" = "" ] || uv run ruff format $(PYTHON_FILES) --diff
 	[ "$(PYTHON_FILES)" = "" ] || uv run ruff check --select I $(PYTHON_FILES)
-	[ "$(PYTHON_FILES)" = "" ] || mkdir -p $(MYPY_CACHE) || uv run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE)
+	uvx ty check .
 
 format format_diff:
 	uv run ruff check --select I --fix $(PYTHON_FILES)

libs/sdk-py/langgraph_sdk/__init__.py

@@ -1,11 +1,6 @@
 from langgraph_sdk.auth import Auth
 from langgraph_sdk.client import get_client, get_sync_client
 
-try:
-    from importlib import metadata
-
-    __version__ = metadata.version(__package__)
-except metadata.PackageNotFoundError:
-    __version__ = "unknown"
+__version__ = "0.2.4"
 
 __all__ = ["Auth", "get_client", "get_sync_client"]

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

@@ -385,6 +385,8 @@ class _ResourceOn(typing.Generic[VCreate, VRead, VUpdate, VDelete, VSearch]):
                 _register_handler(self.auth, self.resource, "*", handler),
             )
 
+        # Accept keyword-only parameters for future filtering behavior; referenced to satisfy linters.
+        _ = resources, actions
         return decorator
 
 
@@ -701,7 +703,7 @@ def _validate_handler(fn: Callable[..., typing.Any]) -> None:
     """
     if not inspect.iscoroutinefunction(fn):
         raise ValueError(
-            f"Auth handler '{fn.__name__}' must be an async function. "
+            f"Auth handler '{getattr(fn, '__name__', fn)}' must be an async function. "
             "Add 'async' before 'def' to make it asynchronous and ensure"
             " any IO operations are non-blocking."
         )
@@ -709,18 +711,20 @@ def _validate_handler(fn: Callable[..., typing.Any]) -> None:
     sig = inspect.signature(fn)
     if "ctx" not in sig.parameters:
         raise ValueError(
-            f"Auth handler '{fn.__name__}' must have a 'ctx: AuthContext' parameter. "
+            f"Auth handler '{getattr(fn, '__name__', fn)}' must have a 'ctx: AuthContext' parameter. "
             "Update the function signature to include this required parameter."
         )
     if "value" not in sig.parameters:
         raise ValueError(
-            f"Auth handler '{fn.__name__}' must have a 'value' parameter. "
+            f"Auth handler '{getattr(fn, '__name__', fn)}' must have a 'value' parameter. "
             " The value contains the mutable data being sent to the endpoint."
             "Update the function signature to include this required parameter."
         )
 
 
-def is_studio_user(user: types.MinimalUser | types.User | types.UserDict) -> bool:
+def is_studio_user(
+    user: types.MinimalUser | types.BaseUser | types.MinimalUserDict,
+) -> bool:
     return (
         isinstance(user, types.StudioUser)
         or isinstance(user, dict)

libs/sdk-py/langgraph_sdk/schema.py

@@ -2,7 +2,7 @@
 
 from __future__ import annotations
 
-from collections.abc import Sequence
+from collections.abc import Mapping, Sequence
 from datetime import datetime
 from typing import (
     Any,
@@ -10,6 +10,7 @@ from typing import (
     NamedTuple,
     Optional,
     TypedDict,
+    Union,
 )
 
 from typing_extensions import TypeAlias
@@ -37,6 +38,14 @@ Represents the status of a thread:
 - "error": An exception occurred during task processing.
 """
 
+ThreadStreamMode = Literal["run_modes", "lifecycle", "state_update"]
+"""
+Defines the mode of streaming:
+- "run_modes": Stream the same events as the runs on thread, as well as run_done events.
+- "lifecycle": Stream only run start/end events.
+- "state_update": Stream state updates on the thread.
+"""
+
 StreamMode = Literal[
     "values",
     "messages",
@@ -90,6 +99,12 @@ Defines action after completion:
 - "keep": Retain resources after completion.
 """
 
+Durability = Literal["sync", "async", "exit"]
+"""Durability mode for the graph execution.
+- `"sync"`: Changes are persisted synchronously before the next step starts.
+- `"async"`: Changes are persisted asynchronously while the next step executes.
+- `"exit"`: Changes are persisted only when the graph exits."""
+
 All = Literal["*"]
 """Represents a wildcard or 'all' selector."""
 
@@ -348,6 +363,72 @@ class Cron(TypedDict):
     """The metadata of the cron."""
 
 
+# Select field aliases for client-side typing of `select` parameters.
+# These mirror the server's allowed field sets.
+
+AssistantSelectField = Literal[
+    "assistant_id",
+    "graph_id",
+    "name",
+    "description",
+    "config",
+    "context",
+    "created_at",
+    "updated_at",
+    "metadata",
+    "version",
+]
+
+ThreadSelectField = Literal[
+    "thread_id",
+    "created_at",
+    "updated_at",
+    "metadata",
+    "config",
+    "context",
+    "status",
+    "values",
+    "interrupts",
+]
+
+RunSelectField = Literal[
+    "run_id",
+    "thread_id",
+    "assistant_id",
+    "created_at",
+    "updated_at",
+    "status",
+    "metadata",
+    "kwargs",
+    "multitask_strategy",
+]
+
+CronSelectField = Literal[
+    "cron_id",
+    "assistant_id",
+    "thread_id",
+    "end_time",
+    "schedule",
+    "created_at",
+    "updated_at",
+    "user_id",
+    "payload",
+    "next_run_date",
+    "metadata",
+    "now",
+]
+
+PrimitiveData = Optional[Union[str, int, float, bool]]
+
+QueryParamTypes = Union[
+    Mapping[str, Union[PrimitiveData, Sequence[PrimitiveData]]],
+    list[tuple[str, PrimitiveData]],
+    tuple[tuple[str, PrimitiveData], ...],
+    str,
+    bytes,
+]
+
+
 class RunCreate(TypedDict):
     """Defines the parameters for initiating a background run."""
 

libs/sdk-py/langgraph_sdk/sse.py

@@ -95,7 +95,7 @@ class SSEDecoder:
 
             sse = StreamPart(
                 event=self._event,
-                data=orjson.loads(self._data) if self._data else None,
+                data=orjson.loads(self._data) if self._data else None,  # type: ignore[invalid-argument-type]
             )
 
             # NOTE: as per the SSE spec, do not reset last_event_id.

libs/sdk-py/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-sdk"
-version = "0.2.0"
+dynamic = ["version"]
 description = "SDK for interacting with LangGraph API"
 authors = []
 requires-python = ">=3.9"
@@ -16,6 +16,9 @@ dependencies = [
     "orjson>=3.10.1",
 ]
 
+[tool.hatch.version]
+path = "langgraph_sdk/__init__.py"
+
 [project.urls]
 Repository = "https://www.github.com/langchain-ai/langgraph"
 
@@ -47,5 +50,6 @@ lint.select = [
   "UP", # pyupgrade
   "B",  # flake8-bugbear
   "I",  # isort
+  "ARG", # flake8-unused-arguments
 ]
 lint.ignore = ["E501", "B008"]

libs/sdk-py/tests/test_api_parity.py

@@ -0,0 +1,120 @@
+from __future__ import annotations
+
+import inspect
+import re
+
+import pytest
+
+from langgraph_sdk.client import (
+    AssistantsClient,
+    CronClient,
+    RunsClient,
+    StoreClient,
+    SyncAssistantsClient,
+    SyncCronClient,
+    SyncRunsClient,
+    SyncStoreClient,
+    SyncThreadsClient,
+    ThreadsClient,
+)
+
+
+def _public_methods(cls) -> dict[str, object]:
+    methods: dict[str, object] = {}
+    # Use the raw class dict to avoid runtime wrappers from plugins/decorators
+    for name, member in cls.__dict__.items():
+        if name.startswith("_"):
+            continue
+        if inspect.isfunction(member):
+            methods[name] = member
+    return methods
+
+
+def _strip_self(sig: inspect.Signature) -> inspect.Signature:
+    params = list(sig.parameters.values())
+    if params and params[0].name == "self":
+        params = params[1:]
+    return sig.replace(parameters=params)
+
+
+def _normalize_return_annotation(ann: object) -> str:
+    s = str(ann)
+    s = re.sub(r"\s+", "", s)
+    s = s.replace("typing.", "").replace("collections.abc.", "")
+    s = re.sub(r"AsyncGenerator\[([^,\]]+)(?:,[^\]]*)?\]", r"Iterator[\1]", s)
+    s = re.sub(r"Generator\[([^,\]]+)(?:,[^\]]*)?\]", r"Iterator[\1]", s)
+    s = re.sub(r"AsyncIterator\[(.+)\]", r"Iterator[\1]", s)
+    s = re.sub(r"AsyncIterable\[(.+)\]", r"Iterable[\1]", s)
+    return s
+
+
+@pytest.mark.parametrize(
+    "async_cls,sync_cls",
+    [
+        (AssistantsClient, SyncAssistantsClient),
+        (ThreadsClient, SyncThreadsClient),
+        (RunsClient, SyncRunsClient),
+        (CronClient, SyncCronClient),
+        (StoreClient, SyncStoreClient),
+    ],
+)
+def test_sync_api_matches_async(async_cls, sync_cls):
+    async_methods = _public_methods(async_cls)
+    sync_methods = _public_methods(sync_cls)
+
+    # Method name parity
+    assert set(sync_methods.keys()) == set(async_methods.keys()), (
+        f"Method sets differ: async-only={set(async_methods) - set(sync_methods)}, sync-only={set(sync_methods) - set(async_methods)}"
+    )
+
+    for name, async_fn in async_methods.items():
+        sync_fn = sync_methods[name]
+
+        # Use inspect.signature for parameter names (robust across versions)
+        async_sig = _strip_self(inspect.signature(async_fn))
+        sync_sig = _strip_self(inspect.signature(sync_fn))
+
+        a_names = list(async_sig.parameters.keys())
+        s_names = list(sync_sig.parameters.keys())
+
+        assert set(a_names) == set(s_names), (
+            f"Parameter names differ for {async_cls.__name__}.{name}: "
+            f"async={a_names}, sync={s_names}"
+        )
+
+        # Compare default presence and parameter kinds (with some tolerance)
+        a_params = async_sig.parameters
+        s_params = sync_sig.parameters
+
+        def kinds_compatible(
+            akind: inspect._ParameterKind, skind: inspect._ParameterKind
+        ) -> bool:
+            if akind == skind:
+                return True
+            return {
+                inspect.Parameter.KEYWORD_ONLY,
+                inspect.Parameter.POSITIONAL_OR_KEYWORD,
+            } == {akind, skind}
+
+        for pname in set(a_names) & set(s_names):
+            apar = a_params[pname]
+            spar = s_params[pname]
+            assert kinds_compatible(apar.kind, spar.kind), (
+                f"Parameter kind mismatch for {async_cls.__name__}.{name}.{pname}: "
+                f"async={apar.kind}, sync={spar.kind}"
+            )
+            assert (apar.default is inspect._empty) == (
+                spar.default is inspect._empty
+            ), (
+                f"Default presence mismatch for {async_cls.__name__}.{name}.{pname}: "
+                f"async_has_default={apar.default is not inspect._empty}, "
+                f"sync_has_default={spar.default is not inspect._empty}"
+            )
+
+        # Return annotations must match or be iterator-equivalent
+        a_ret = _normalize_return_annotation(async_sig.return_annotation)
+        s_ret = _normalize_return_annotation(sync_sig.return_annotation)
+        assert a_ret == s_ret, (
+            f"Return annotation mismatch for {async_cls.__name__}.{name}: "
+            f"async={a_ret}, sync={s_ret}"
+        )

libs/sdk-py/tests/test_select_fields_sync.py

@@ -0,0 +1,76 @@
+import functools
+import json
+import os
+from pathlib import Path
+from typing import get_args
+
+from langgraph_sdk.schema import (
+    AssistantSelectField,
+    CronSelectField,
+    RunSelectField,
+    ThreadSelectField,
+)
+
+current_dir = os.path.dirname(os.path.abspath(__file__))
+
+
+@functools.cache
+def _load_spec() -> dict:
+    with (
+        Path(current_dir).parents[2]
+        / "docs"
+        / "docs"
+        / "cloud"
+        / "reference"
+        / "api"
+        / "openapi.json"
+    ).open() as f:
+        return json.load(f)
+
+
+def _enum_from_request_select(spec: dict, path: str, method: str) -> set[str]:
+    schema = spec["paths"][path][method]["requestBody"]["content"]["application/json"][
+        "schema"
+    ]
+    if "properties" in schema:
+        props = schema["properties"]
+    elif "$ref" in schema:
+        component = spec
+        index = schema["$ref"].split("/")[1:]
+        for part in index:
+            component = component[part]
+        props = component["properties"]
+    else:
+        raise ValueError(f"Unknown schema: {schema}")
+    sel = props["select"]
+    return set(sel["items"]["enum"])
+
+
+def _enum_from_query_select(spec: dict, path: str, method: str) -> set[str]:
+    params = spec["paths"][path][method]["parameters"]
+    sel = next(p for p in params if p["name"] == "select")
+    return set(sel["schema"]["items"]["enum"])
+
+
+def test_assistants_select_enum_matches_sdk():
+    spec = _load_spec()
+    expected = set(get_args(AssistantSelectField))
+    assert _enum_from_request_select(spec, "/assistants/search", "post") == expected
+
+
+def test_threads_select_enum_matches_sdk():
+    spec = _load_spec()
+    expected = set(get_args(ThreadSelectField))
+    assert _enum_from_request_select(spec, "/threads/search", "post") == expected
+
+
+def test_runs_select_enum_matches_sdk():
+    spec = _load_spec()
+    expected = set(get_args(RunSelectField))
+    assert _enum_from_query_select(spec, "/threads/{thread_id}/runs", "get") == expected
+
+
+def test_crons_select_enum_matches_sdk():
+    spec = _load_spec()
+    expected = set(get_args(CronSelectField))
+    assert _enum_from_request_select(spec, "/runs/crons/search", "post") == expected

libs/sdk-py/uv.lock

@@ -4,7 +4,7 @@ requires-python = ">=3.9"
 
 [[package]]
 name = "anyio"
-version = "4.9.0"
+version = "4.10.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "exceptiongroup", marker = "python_full_version < '3.11'" },
@@ -12,18 +12,27 @@ dependencies = [
     { name = "sniffio" },
     { name = "typing-extensions", marker = "python_full_version < '3.13'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/95/7d/4c1bd541d4dffa1b52bd83fb8527089e097a106fc90b467a7313b105f840/anyio-4.9.0.tar.gz", hash = "sha256:673c0c244e15788651a4ff38710fea9675823028a6f08a5eda409e0c9840a028", size = 190949, upload-time = "2025-03-17T00:02:54.77Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/f1/b4/636b3b65173d3ce9a38ef5f0522789614e590dab6a8d505340a4efe4c567/anyio-4.10.0.tar.gz", hash = "sha256:3f3fae35c96039744587aa5b8371e7e8e603c0702999535961dd336026973ba6", size = 213252, upload-time = "2025-08-04T08:54:26.451Z" }
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/6f/12/e5e0282d673bb9746bacfb6e2dba8719989d3660cdb2ea79aee9a9651afb/anyio-4.10.0-py3-none-any.whl", hash = "sha256:60e474ac86736bbfd6f210f7a61218939c318f43f9972497381f1c5e930ed3d1", size = 107213, upload-time = "2025-08-04T08:54:24.882Z" },
+]
+
+[[package]]
+name = "backports-asyncio-runner"
+version = "1.2.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/8e/ff/70dca7d7cb1cbc0edb2c6cc0c38b65cba36cccc491eca64cabd5fe7f8670/backports_asyncio_runner-1.2.0.tar.gz", hash = "sha256:a5aa7b2b7d8f8bfcaa2b57313f70792df84e32a2a746f585213373f900b42162", size = 69893, upload-time = "2025-07-02T02:27:15.685Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/a0/59/76ab57e3fe74484f48a53f8e337171b4a2349e506eabe136d7e01d059086/backports_asyncio_runner-1.2.0-py3-none-any.whl", hash = "sha256:0da0a936a8aeb554eccb426dc55af3ba63bcdc69fa1a600b5bb305413a4477b5", size = 12313, upload-time = "2025-07-02T02:27:14.263Z" },
 ]
 
 [[package]]
 name = "certifi"
-version = "2025.7.14"
+version = "2025.8.3"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/b3/76/52c535bcebe74590f296d6c77c86dabf761c41980e1347a2422e4aa2ae41/certifi-2025.7.14.tar.gz", hash = "sha256:8ea99dbdfaaf2ba2f9bac77b9249ef62ec5218e7c2b2e903378ed5fccf765995", size = 163981, upload-time = "2025-07-14T03:29:28.449Z" }
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+    { url = "https://files.pythonhosted.org/packages/e5/48/1549795ba7742c948d2ad169c1c8cdbae65bc450d6cd753d124b17c8cd32/certifi-2025.8.3-py3-none-any.whl", hash = "sha256:f6c12493cfb1b06ba2ff328595af9350c65d6644968e5d3a2ffd78699af217a5", size = 161216, upload-time = "2025-08-03T03:07:45.777Z" },
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 [[package]]
@@ -119,7 +128,6 @@ wheels = [
 
 [[package]]
 name = "langgraph-sdk"
-version = "0.2.0"
 source = { editable = "." }
 dependencies = [
     { name = "httpx" },
@@ -156,7 +164,7 @@ dev = [
 
 [[package]]
 name = "mypy"
-version = "1.17.0"
+version = "1.17.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "mypy-extensions" },
@@ -164,39 +172,45 @@ dependencies = [
     { name = "tomli", marker = "python_full_version < '3.11'" },
     { name = "typing-extensions" },
 ]
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