first pass at patch

2026-08-27 01:52:25 +02:00 · 2025-11-06 11:09:06 -05:00
74 changed files with 3222 additions and 4354 deletions
@@ -1,8 +1,7 @@
-import logging
 import pathlib
 import sys
 import time
-from urllib import error, request
+from urllib import request, error

 import langgraph_cli
 import langgraph_cli.config
@@ -12,13 +11,9 @@ from langgraph_cli.constants import DEFAULT_PORT
 from langgraph_cli.exec import Runner, subp_exec
 from langgraph_cli.progress import Progress

-logger = logging.getLogger(__name__)
-logging.basicConfig(level=logging.INFO)
-

 def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
    """Spin up API with Postgres/Redis via docker compose and wait until ready."""
-    logger.info("Starting test...")
    with Runner() as runner, Progress(message="Pulling...") as set:
        # Detect docker/compose capabilities
        capabilities = langgraph_cli.docker.check_capabilities(runner)
@@ -62,9 +57,7 @@ def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
            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)
-                )
+                runner.run(subp_exec(*compose_cmd, *args, "ps", input=stdin, verbose=False))
            except Exception:
                pass
            try:
@@ -100,7 +93,7 @@ def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
        set("")
        base_url = f"http://localhost:{port}"
        ok_url = f"{base_url}/ok"
-        logger.info(f"Waiting for {ok_url} to respond with 200...")
+        print(f"Waiting for {ok_url} to respond with 200...")
        deadline = time.time() + 30
        last_err: Exception | None = None
        while time.time() < deadline:
@@ -114,16 +107,13 @@ def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
                        break
                    else:
                        last_err = RuntimeError(f"Unexpected status: {resp.status}")
-                        logger.error(f"Unexpected status: {resp.status}")
+                        print(f"Unexpected status: {resp.status}")
            except error.URLError as e:
-                logger.error(f"URLError: {e}")
                last_err = e
            except Exception as e:  # noqa: BLE001
-                logger.error(f"Exception: {e}")
                last_err = e
            time.sleep(0.5)
        else:
-            logger.error("Timeout waiting for /ok to return 200")
            # Bring stack down before raising
            args_down = [*args, "down", "-v", "--remove-orphans"]
            try:
@@ -141,23 +131,15 @@ def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
                )

        # Clean up: bring compose stack down to free ports for next test
-        logger.info("Test succeeded. Bringing down compose stack...")
-        try:
-            args_down = [*args, "down", "-v", "--remove-orphans"]
-            runner.run(
-                subp_exec(
-                    *compose_cmd,
-                    *args_down,
-                    input=stdin,
-                    verbose=verbose,
-                )
+        args_down = [*args, "down", "-v", "--remove-orphans"]
+        runner.run(
+            subp_exec(
+                *compose_cmd,
+                *args_down,
+                input=stdin,
+                verbose=verbose,
            )
-            logger.info("Compose stack down. Finishing...")
-        except Exception:
-            logger.exception("Failed to bring down compose stack")
-            pass
-
-    logger.info("Test finished")
+        )


 if __name__ == "__main__":
@@ -168,10 +150,4 @@ if __name__ == "__main__":
    parser.add_argument("-c", "--config", type=str, default="./langgraph.json")
    parser.add_argument("-p", "--port", type=int, default=DEFAULT_PORT)
    args = parser.parse_args()
-    try:
-        test(pathlib.Path(args.config), args.port, args.tag, verbose=True)
-    except BaseException:
-        logger.exception("Test failed")
-        raise
-    
-    logger.info("Test execution finished")
+    test(pathlib.Path(args.config), args.port, args.tag, verbose=True)
@@ -13,6 +13,7 @@ jobs:
      matrix:
        python-version:
          - "3.10"
+          - "3.11"
          - "3.14"
        example:
          - name: A
@@ -66,19 +67,19 @@ jobs:
          timeout 60 python "$REPO_ROOT/.github/scripts/run_langgraph_cli_test.py" -t ${{ matrix.example.tag }}

      - name: Build JS service
-        if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
+        if: steps.changed-files.outputs.all
        working-directory: libs/cli/js-examples
        run: |
          langgraph build -t langgraph-test-e

      - name: Build JS monorepo service
-        if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
+        if: steps.changed-files.outputs.all
        working-directory: libs/cli/js-monorepo-example
        run: |
          langgraph build -t langgraph-test-f -c apps/agent/langgraph.json --build-command "yarn run turbo build" --install-command "yarn install"

      - name: Build Python monorepo service
-        if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
+        if: steps.changed-files.outputs.all
        working-directory: libs/cli/python-monorepo-example
        run: |
          langgraph build -t langgraph-test-g -c apps/agent/langgraph.json
@@ -87,32 +88,24 @@ jobs:
          timeout 60 python ../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-g -c apps/agent/langgraph.json

      - name: Build and test prerelease reqs service
-        if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
+        if: steps.changed-files.outputs.all
        working-directory: libs/cli/examples/graph_prerelease_reqs
        run: |
          langgraph build -t langgraph-test-h
          cp ../.env.example .env
          if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
          timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-h
-          echo "Finished starting up langgraph-test-h"
          LANGGRAPH_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langgraph'); print(v);")
-          if [ "$LANGGRAPH_VERSION" != "1.0.2" ]; then
-            echo "LANGGRAPH_VERSION != 1.0.2; $LANGGRAPH_VERSION"
+          if [ "$LANGGRAPH_VERSION" != "1.0.0a2" ]; then
            exit 1
          fi
          LANGCHAIN_OPENAI_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langchain-openai'); print(v);")
-          if [ "$LANGCHAIN_OPENAI_VERSION" != "1.0.1" ]; then
-            echo "LANGCHAIN_OPENAI_VERSION != 1.0.1; $LANGCHAIN_OPENAI_VERSION"
-            exit 1
-          fi
-          LANGCHAIN_ANTHROPIC_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langchain-anthropic'); print(v);")
-          if [ "$LANGCHAIN_ANTHROPIC_VERSION" != "1.0.0a5" ]; then
-            echo "LANGCHAIN_ANTHROPIC_VERSION != 1.0.0a5; $LANGCHAIN_ANTHROPIC_VERSION"
+          if [ "$LANGCHAIN_OPENAI_VERSION" != "0.3.0" ]; then
            exit 1
          fi

      - name: Build and test prerelease reqs fail service
-        if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
+        if: steps.changed-files.outputs.all
        working-directory: libs/cli/examples/graph_prerelease_reqs_fail
        run: |
          langgraph build -t langgraph-test-i || [ $? -eq 1 ]
@@ -2108,9 +2108,9 @@ __metadata:
  linkType: hard

 "hono@npm:^4.5.4":
-  version: 4.10.3
-  resolution: "hono@npm:4.10.3"
-  checksum: 10c0/bdcc4c7066c74ba7cfa63ed6550768a0f43a420286c8f8f74b7012ea4901b8b06778fa8e98264b46f1a86920f056b7ede1f07814da4934912f9945def4977c29
+  version: 4.9.7
+  resolution: "hono@npm:4.9.7"
+  checksum: 10c0/089184660a9211ea216ab95bafa45260e371651cb019db49828064b7982b0ae61cc3c4715324bfeb9037aa2460c39ffa2c91d84ad0c8d500fa77cbcc7fc07a8f
  languageName: node
  linkType: hard

@@ -81,7 +81,7 @@ REDIRECT_MAP = {
    # cloud redirects
    "cloud/index.md": "https://docs.langchain.com/oss/python/langgraph/overview",
    "cloud/how-tos/index.md": "https://docs.langchain.com/langsmith/home",
-    "cloud/concepts/api.md": "https://docs.langchain.com/langsmith/agent-server",
+    "cloud/concepts/api.md": "https://docs.langchain.com/langsmith/langgraph-server",
    "cloud/concepts/cloud.md": "https://docs.langchain.com/langsmith/cloud",
    "cloud/faq/studio.md": "https://docs.langchain.com/langsmith/studio",
    "cloud/how-tos/human_in_the_loop_edit_state.md": "https://docs.langchain.com/langsmith/add-human-in-the-loop",
@@ -111,8 +111,8 @@ REDIRECT_MAP = {
    "tutorials/introduction.ipynb": "https://docs.langchain.com/oss/python/langgraph/overview",
    "agents/deployment.md": "https://docs.langchain.com/oss/python/langgraph/local-server",
    # deployment redirects
-    "how-tos/deploy-self-hosted.md": "https://docs.langchain.com/langsmith/platform-setup",
-    "concepts/self_hosted.md": "https://docs.langchain.com/langsmith/platform-setup",
+    "how-tos/deploy-self-hosted.md": "https://docs.langchain.com/langsmith/hosting",
+    "concepts/self_hosted.md": "https://docs.langchain.com/langsmith/hosting",
    "tutorials/deployment.md": "https://docs.langchain.com/langsmith/deployments",
    # assistant redirects
    "cloud/how-tos/assistant_versioning.md": "https://docs.langchain.com/langsmith/configuration-cloud",
@@ -129,30 +129,16 @@ REDIRECT_MAP = {
    "how-tos/human_in_the_loop/edit-graph-state.ipynb": "https://docs.langchain.com/oss/python/langgraph/use-time-travel",

    # LGP mintlify migration redirects
-    "examples/index.md": "https://docs.langchain.com/oss/python/learn",
-    "guides/index.md": "https://docs.langchain.com/oss/python/langgraph/overview",
-    "concepts/index.md": "https://docs.langchain.com/oss/python/langgraph/overview",
-    "tutorials/index.md": "https://docs.langchain.com/oss/python/learn",
-    "llms-txt-overview.md": "https://docs.langchain.com/llms.txt",
-    "tutorials/rag/langgraph_adaptive_rag.md": "https://docs.langchain.com/oss/python/langgraph/agentic-rag",
-    "tutorials/multi_agent/multi-agent-collaboration.ipynb": "https://docs.langchain.com/oss/python/langchain/multi-agent",
-    "how-tos/create-react-agent-manage-message-history.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory",
-    "how-tos/many-tools.ipynb": "https://docs.langchain.com/oss/python/langchain/tools",
-    "tutorials/customer-support/customer-support.ipynb": "https://docs.langchain.com/oss/python/langgraph/agentic-rag",
-    "how-tos/react-agent-structured-output.ipynb": "https://docs.langchain.com/oss/python/langchain/agents#structured-output",
-    "tutorials/code_assistant/langgraph_code_assistant.ipynb": "https://docs.langchain.com/oss/python/langgraph/agentic-rag",
-    "tutorials/multi_agent/hierarchical_agent_teams.ipynb": "https://docs.langchain.com/oss/python/langchain/supervisor",
    "tutorials/auth/getting_started.md": "https://docs.langchain.com/langsmith/auth",
    "tutorials/auth/resource_auth.md": "https://docs.langchain.com/langsmith/resource-auth",
    "tutorials/auth/add_auth_server.md": "https://docs.langchain.com/langsmith/add-auth-server",
    "how-tos/use-remote-graph.md": "https://docs.langchain.com/langsmith/use-remote-graph",
    "how-tos/autogen-integration.md": "https://docs.langchain.com/langsmith/autogen-integration",
-    "how-tos/human_in_the_loop/wait-user-input.ipynb": "https://docs.langchain.com/oss/python/langgraph/interrupts",
    "cloud/how-tos/use_stream_react.md": "https://docs.langchain.com/langsmith/use-stream-react",
    "cloud/how-tos/generative_ui_react.md": "https://docs.langchain.com/langsmith/generative-ui-react",
    "concepts/langgraph_platform.md": "https://docs.langchain.com/langsmith/deployments",
    "concepts/langgraph_components.md": "https://docs.langchain.com/langsmith/components",
-    "concepts/langgraph_server.md": "https://docs.langchain.com/langsmith/agent-server",
+    "concepts/langgraph_server.md": "https://docs.langchain.com/langsmith/langgraph-server",
    "concepts/langgraph_data_plane.md": "https://docs.langchain.com/langsmith/data-plane",
    "concepts/langgraph_control_plane.md": "https://docs.langchain.com/langsmith/control-plane",
    "concepts/langgraph_cli.md": "https://docs.langchain.com/langsmith/cli",
@@ -194,7 +180,7 @@ REDIRECT_MAP = {
    "cloud/concepts/data_storage_and_privacy.md": "https://docs.langchain.com/langsmith/data-storage-and-privacy",
    "cloud/deployment/semantic_search.md": "https://docs.langchain.com/langsmith/semantic-search",
    "how-tos/ttl/configure_ttl.md": "https://docs.langchain.com/langsmith/configure-ttl",
-    "concepts/deployment_options.md": "https://docs.langchain.com/langsmith/platform-setup",
+    "concepts/deployment_options.md": "https://docs.langchain.com/langsmith/hosting",
    "cloud/quick_start.md": "https://docs.langchain.com/langsmith/deployment-quickstart",
    "cloud/deployment/setup.md": "https://docs.langchain.com/langsmith/setup-app-requirements-txt",
    "cloud/deployment/setup_pyproject.md": "https://docs.langchain.com/langsmith/setup-pyproject",
@@ -215,7 +201,7 @@ REDIRECT_MAP = {
    "cloud/deployment/egress.md": "https://docs.langchain.com/langsmith/env-var",
    "cloud/how-tos/streaming.md": "https://docs.langchain.com/langsmith/streaming",
    "cloud/reference/api/api_ref.md": "https://docs.langchain.com/langsmith/server-api-ref",
-    "cloud/reference/langgraph_server_changelog.md": "https://docs.langchain.com/langsmith/agent-server-changelog",
+    "cloud/reference/langgraph_server_changelog.md": "https://docs.langchain.com/langsmith/langgraph-server-changelog",
    "cloud/reference/api/api_ref_control_plane.md": "https://docs.langchain.com/langsmith/api-ref-control-plane",
    "cloud/reference/cli.md": "https://docs.langchain.com/langsmith/cli",
    "cloud/reference/env_var.md": "https://docs.langchain.com/langsmith/env-var",
@@ -233,15 +219,12 @@ REDIRECT_MAP = {
    "tutorials/get-started/6-time-travel.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
    "tutorials/langsmith/local-server.md": "https://docs.langchain.com/oss/python/langgraph/local-server",
    "tutorials/workflows.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
-    "tutorials/plan-and-execute/plan-and-execute.ipynb": "https://docs.langchain.com/oss/python/langchain/middleware/built-in#to-do-list",
-    "tutorials/langgraph-platform/local-server/local-server.md": "https://docs.langchain.com/langsmith/local-server",
    "concepts/agentic_concepts.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
    "guides/index.md": "https://docs.langchain.com/oss/python/langchain/overview",
    "agents/overview.md": "https://docs.langchain.com/oss/python/langchain/agents",
    "agents/run_agents.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
    "concepts/low_level.md": "https://docs.langchain.com/oss/python/langgraph/graph-api",
    "how-tos/graph-api.md": "https://docs.langchain.com/oss/python/langgraph/graph-api",
-    "how-tos/react-agent-from-scratch.ipynb": "https://docs.langchain.com/oss/python/langchain/quickstart",
    "concepts/functional_api.md": "https://docs.langchain.com/oss/python/langgraph/functional-api",
    "how-tos/use-functional-api.md": "https://docs.langchain.com/oss/python/langgraph/functional-api",
    "concepts/pregel.md": "https://docs.langchain.com/oss/python/langgraph/pregel",
@@ -299,8 +282,8 @@ REDIRECT_MAP = {
    "reference/supervisor.md": "https://reference.langchain.com/python/langgraph/supervisor/",
    "reference/swarm.md": "https://reference.langchain.com/python/langgraph/swarm/",
    "reference/mcp.md": "https://reference.langchain.com/python/langgraph/mcp/",
-    "cloud/reference/sdk/python_sdk_ref.md": "https://reference.langchain.com/python/langsmith/deployment/sdk/",
-    "reference/remote_graph.md": "https://reference.langchain.com/python/langsmith/deployment/remote_graph/",
+    "cloud/reference/sdk/python_sdk_ref.md": "https://reference.langchain.com/python/platform/python_sdk/",
+    "reference/remote_graph.md": "https://reference.langchain.com/python/platform/remote_graph/",

    # additional exclude-search entries from mkdocs.yml
    "additional-resources/index.md": "https://docs.langchain.com/oss/python/langchain/overview",
@@ -311,8 +294,8 @@ REDIRECT_MAP = {
    "cloud/deployment/custom_docker.md": "https://docs.langchain.com/langsmith/custom-docker",
    "cloud/deployment/egress.md": "https://docs.langchain.com/langsmith/env-var",
    "cloud/deployment/graph_rebuild.md": "https://docs.langchain.com/langsmith/graph-rebuild",
-    "cloud/deployment/self_hosted_control_plane.md": "https://docs.langchain.com/langsmith/platform-setup",
-    "cloud/deployment/self_hosted_data_plane.md": "https://docs.langchain.com/langsmith/platform-setup",
+    "cloud/deployment/self_hosted_control_plane.md": "https://docs.langchain.com/langsmith/hosting",
+    "cloud/deployment/self_hosted_data_plane.md": "https://docs.langchain.com/langsmith/hosting",
    "cloud/deployment/semantic_search.md": "https://docs.langchain.com/langsmith/semantic-search",
    "cloud/deployment/setup_javascript.md": "https://docs.langchain.com/langsmith/setup-javascript",
    "cloud/deployment/setup_pyproject.md": "https://docs.langchain.com/langsmith/setup-pyproject",
@@ -348,7 +331,7 @@ REDIRECT_MAP = {
    "cloud/reference/api/api_ref.md": "https://docs.langchain.com/langsmith/server-api-ref",
    "cloud/reference/cli.md": "https://docs.langchain.com/langsmith/cli",
    "cloud/reference/env_var.md": "https://docs.langchain.com/langsmith/env-var",
-    "cloud/reference/langgraph_server_changelog.md": "https://docs.langchain.com/langsmith/agent-server-changelog",
+    "cloud/reference/langgraph_server_changelog.md": "https://docs.langchain.com/langsmith/langgraph-server-changelog",
    "cloud/reference/sdk/js_ts_sdk_ref.md": "https://reference.langchain.com/javascript/modules/langsmith.html",
    "concepts/application_structure.md": "https://docs.langchain.com/langsmith/application-structure",
    "concepts/assistants.md": "https://docs.langchain.com/langsmith/assistants",
@@ -362,9 +345,9 @@ REDIRECT_MAP = {
    "concepts/langgraph_control_plane.md": "https://docs.langchain.com/langsmith/control-plane",
    "concepts/langgraph_data_plane.md": "https://docs.langchain.com/langsmith/data-plane",
    "concepts/langgraph_platform.md": "https://docs.langchain.com/langsmith/home",
-    "concepts/langgraph_self_hosted_control_plane.md": "https://docs.langchain.com/langsmith/platform-setup",
-    "concepts/langgraph_self_hosted_data_plane.md": "https://docs.langchain.com/langsmith/platform-setup",
-    "concepts/langgraph_server.md": "https://docs.langchain.com/langsmith/agent-server",
+    "concepts/langgraph_self_hosted_control_plane.md": "https://docs.langchain.com/langsmith/hosting",
+    "concepts/langgraph_self_hosted_data_plane.md": "https://docs.langchain.com/langsmith/hosting",
+    "concepts/langgraph_server.md": "https://docs.langchain.com/langsmith/langgraph-server",
    "concepts/langgraph_standalone_container.md": "https://docs.langchain.com/langsmith/docker",
    "concepts/langgraph_studio.md": "https://docs.langchain.com/langsmith/studio",
    "concepts/plans.md": "https://docs.langchain.com/langsmith/home",
@@ -810,17 +793,6 @@ def on_post_build(config):
    # Track which paths have explicit redirects
    redirected_paths = set()

-    # Collect all existing HTML files in the site
-    all_html_files = set()
-    for root, dirs, files in os.walk(site_dir):
-        for file in files:
-            if file.endswith(".html"):
-                # Get relative path from site_dir
-                html_path = os.path.relpath(os.path.join(root, file), site_dir)
-                # Normalize path separators to forward slashes
-                html_path = html_path.replace(os.sep, "/")
-                all_html_files.add(html_path)
-
    # Process explicit redirects from REDIRECT_MAP
    for page_old, page_new in REDIRECT_MAP.items():
        # Convert .ipynb to .md for path calculation
@@ -875,24 +847,6 @@ def on_post_build(config):

            _write_html(site_dir, old_html_path, new_html_path)

-    # Create catch-all redirects for any HTML files not explicitly redirected
-    catchall_url = "https://docs.langchain.com/oss/python/langgraph/overview"
-    for html_file in all_html_files:
-        # Skip if this file is already explicitly redirected
-        if html_file in redirected_paths:
-            continue
-
-        # Skip the root index.html (we handle that separately)
-        if html_file == "index.html":
-            continue
-
-        # Skip reference documentation (keep those accessible)
-        if html_file.startswith("reference/"):
-            continue
-
-        # Create redirect for this unmapped file
-        _write_html(site_dir, html_file, catchall_url)
-
    # Create root index.html redirect
    root_redirect_html = """<!doctype html>
 <html lang="en">
@@ -1,21 +0,0 @@
-MIT License
-
-Copyright (c) 2024 LangChain, Inc.
-
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
-
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.
@@ -97,7 +97,7 @@ class PostgresSaver(BasePostgresSaver):
                strict=False,
            ):
                cur.execute(migration)
-                cur.execute("INSERT INTO checkpoint_migrations (v) VALUES (%s)", (v,))
+                cur.execute(f"INSERT INTO checkpoint_migrations (v) VALUES ({v})")
        if self.pipe:
            self.pipe.sync()

@@ -102,9 +102,7 @@ class AsyncPostgresSaver(BasePostgresSaver):
                strict=False,
            ):
                await cur.execute(migration)
-                await cur.execute(
-                    "INSERT INTO checkpoint_migrations (v) VALUES (%s)", (v,)
-                )
+                await cur.execute(f"INSERT INTO checkpoint_migrations (v) VALUES ({v})")
        if self.pipe:
            await self.pipe.sync()

@@ -81,7 +81,7 @@ MIGRATIONS = [
    """
    CREATE INDEX CONCURRENTLY IF NOT EXISTS checkpoint_writes_thread_id_idx ON checkpoint_writes(thread_id);
    """,
-    """ALTER TABLE checkpoint_writes ADD COLUMN IF NOT EXISTS task_path TEXT NOT NULL DEFAULT '';""",
+    """ALTER TABLE checkpoint_writes ADD COLUMN task_path TEXT NOT NULL DEFAULT '';""",
 ]

 SELECT_SQL = """
@@ -77,7 +77,7 @@ MIGRATIONS = [
    CREATE INDEX CONCURRENTLY IF NOT EXISTS checkpoint_writes_thread_id_idx ON checkpoint_writes(thread_id);
    """,
    """
-    ALTER TABLE checkpoint_writes ADD COLUMN IF NOT EXISTS task_path TEXT NOT NULL DEFAULT '';
+    ALTER TABLE checkpoint_writes ADD COLUMN task_path TEXT NOT NULL DEFAULT '';
    """,
 ]

@@ -252,7 +252,7 @@ class ShallowPostgresSaver(BasePostgresSaver):
                strict=False,
            ):
                cur.execute(migration)
-                cur.execute("INSERT INTO checkpoint_migrations (v) VALUES (%s)", (v,))
+                cur.execute(f"INSERT INTO checkpoint_migrations (v) VALUES ({v})")
        if self.pipe:
            self.pipe.sync()

@@ -614,9 +614,7 @@ class AsyncShallowPostgresSaver(BasePostgresSaver):
                strict=False,
            ):
                await cur.execute(migration)
-                await cur.execute(
-                    "INSERT INTO checkpoint_migrations (v) VALUES (%s)", (v,)
-                )
+                await cur.execute(f"INSERT INTO checkpoint_migrations (v) VALUES ({v})")
        if self.pipe:
            await self.pipe.sync()

@@ -91,12 +91,7 @@ WHERE expires_at IS NOT NULL;
 VECTOR_MIGRATIONS: Sequence[Migration] = [
    Migration(
        """
-DO $$
-BEGIN
-    IF NOT EXISTS (SELECT 1 FROM pg_extension WHERE extname = 'vector') THEN
-        CREATE EXTENSION vector;
-    END IF;
-END $$;
+CREATE EXTENSION IF NOT EXISTS vector;
 """,
    ),
    Migration(
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"

 [project]
 name = "langgraph-checkpoint-postgres"
-version = "3.0.1"
+version = "3.0.0"
 description = "Library with a Postgres implementation of LangGraph checkpoint saver."
 authors = []
 requires-python = ">=3.10"
@@ -19,10 +19,7 @@ dependencies = [
 ]

 [project.urls]
-Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/checkpoint-postgres"
-Twitter = "https://x.com/LangChainAI"
-Slack = "https://www.langchain.com/join-community"
-Reddit = "https://www.reddit.com/r/LangChain/"
+Repository = "https://www.github.com/langchain-ai/langgraph"

 [dependency-groups]
 test = [
@@ -234,7 +234,7 @@ wheels = [

 [[package]]
 name = "langgraph-checkpoint"
-version = "3.0.1"
+version = "3.0.0"
 source = { editable = "../checkpoint" }
 dependencies = [
    { name = "langchain-core" },
@@ -244,7 +244,7 @@ dependencies = [
 [package.metadata]
 requires-dist = [
    { name = "langchain-core", specifier = ">=0.2.38" },
-    { name = "ormsgpack", specifier = ">=1.12.0" },
+    { name = "ormsgpack", specifier = ">=1.10.0" },
 ]

 [package.metadata.requires-dev]
@@ -281,7 +281,7 @@ test = [

 [[package]]
 name = "langgraph-checkpoint-postgres"
-version = "3.0.1"
+version = "3.0.0"
 source = { editable = "." }
 dependencies = [
    { name = "langgraph-checkpoint" },
@@ -505,57 +505,57 @@ wheels = [

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+version = "1.11.0"
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+sdist = { url = "https://files.pythonhosted.org/packages/65/f8/224c342c0e03e131aaa1a1f19aa2244e167001783a433f4eed10eedd834b/ormsgpack-1.11.0.tar.gz", hash = "sha256:7c9988e78fedba3292541eb3bb274fa63044ef4da2ddb47259ea70c05dee4206", size = 49357, upload-time = "2025-10-08T17:29:15.621Z" }
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 ]

 [[package]]
@@ -1,21 +0,0 @@
-MIT License
-
-Copyright (c) 2024 LangChain, Inc.
-
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
-
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.
@@ -18,10 +18,7 @@ dependencies = [
 ]

 [project.urls]
-Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/checkpoint-sqlite"
-Twitter = "https://x.com/LangChainAI"
-Slack = "https://www.langchain.com/join-community"
-Reddit = "https://www.reddit.com/r/LangChain/"
+Repository = "https://www.github.com/langchain-ai/langgraph"

 [dependency-groups]
 test = [
@@ -246,7 +246,7 @@ wheels = [

 [[package]]
 name = "langgraph-checkpoint"
-version = "3.0.1"
+version = "3.0.0"
 source = { editable = "../checkpoint" }
 dependencies = [
    { name = "langchain-core" },
@@ -256,7 +256,7 @@ dependencies = [
 [package.metadata]
 requires-dist = [
    { name = "langchain-core", specifier = ">=0.2.38" },
-    { name = "ormsgpack", specifier = ">=1.12.0" },
+    { name = "ormsgpack", specifier = ">=1.10.0" },
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 [package.metadata.requires-dev]
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 [[package]]
@@ -38,10 +38,8 @@ Each checkpointer should conform to `langgraph.checkpoint.base.BaseCheckpointSav
 - `.put_writes` - Store intermediate writes linked to a checkpoint (i.e. pending writes).
 - `.get_tuple` - Fetch a checkpoint tuple using for a given configuration (`thread_id` and `checkpoint_id`).
 - `.list` - List checkpoints that match a given configuration and filter criteria.
- `.delete_thread()` - Delete all checkpoints and writes associated with a thread.
- `.get_next_version()` - Generate the next version ID for a channel.

-If the checkpointer will be used with asynchronous graph execution (i.e. executing the graph via `.ainvoke`, `.astream`, `.abatch`), checkpointer must implement asynchronous versions of the above methods (`.aput`, `.aput_writes`, `.aget_tuple`, `.alist`). Similarly, the checkpointer must implement `.adelete_thread()` if asynchronous thread cleanup is desired. The base class provides a default implementation of `.get_next_version()` that generates an integer sequence starting from 1, but this method should be overridden for custom versioning schemes.
+If the checkpointer will be used with asynchronous graph execution (i.e. executing the graph via `.ainvoke`, `.astream`, `.abatch`), checkpointer must implement asynchronous versions of the above methods (`.aput`, `.aput_writes`, `.aget_tuple`, `.alist`).

 ## Usage

@@ -640,7 +640,6 @@ _option = (
    | ormsgpack.OPT_PASSTHROUGH_DATETIME
    | ormsgpack.OPT_PASSTHROUGH_ENUM
    | ormsgpack.OPT_PASSTHROUGH_UUID
-    | ormsgpack.OPT_REPLACE_SURROGATES
 )


@@ -4,7 +4,7 @@ build-backend = "hatchling.build"

 [project]
 name = "langgraph-checkpoint"
-version = "3.0.1"
+version = "3.0.0"
 description = "Library with base interfaces for LangGraph checkpoint savers."
 authors = []
 requires-python = ">=3.10"
@@ -13,14 +13,11 @@ license = "MIT"
 license-files = ['LICENSE']
 dependencies = [
    "langchain-core>=0.2.38",
-    "ormsgpack>=1.12.0",
+    "ormsgpack>=1.10.0",
 ]

 [project.urls]
-Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/checkpoint"
-Twitter = "https://x.com/LangChainAI"
-Slack = "https://www.langchain.com/join-community"
-Reddit = "https://www.reddit.com/r/LangChain/"
+Repository = "https://www.github.com/langchain-ai/langgraph"

 [dependency-groups]
 test = [
@@ -149,20 +149,20 @@ def test_serde_jsonplus() -> None:
        assert serde.loads_typed(serde.dumps_typed(value)) == value

    surrogates = [
-        "Hello??",
-        "Python??",
-        "Surrogate??",
-        "Example??",
-        "String??",
-        "With??",
-        "Surrogates??",
-        "Embedded??",
-        "In??",
-        "The??",
-        "Text??",
+        "Hello\ud83d\ude00",
+        "Python\ud83d\udc0d",
+        "Surrogate\ud834\udd1e",
+        "Example\ud83c\udf89",
+        "String\ud83c\udfa7",
+        "With\ud83c\udf08",
+        "Surrogates\ud83d\ude0e",
+        "Embedded\ud83d\udcbb",
+        "In\ud83c\udf0e",
+        "The\ud83d\udcd6",
+        "Text\ud83d\udcac",
        "收花🙄·到",
    ]
-    serde = JsonPlusSerializer(pickle_fallback=False)
+    serde = JsonPlusSerializer(pickle_fallback=True)

    assert serde.loads_typed(serde.dumps_typed(surrogates)) == surrogates

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 ]

 [[package]]
@@ -1,12 +1,13 @@
 from collections.abc import Sequence
 from typing import Annotated, Literal, TypedDict

+from langchain_community.tools.tavily_search import TavilySearchResults
 from langchain_core.messages import BaseMessage
 from langchain_openai import ChatOpenAI
 from langgraph.graph import END, StateGraph, add_messages
 from langgraph.prebuilt import ToolNode

-tools = []
+tools = [TavilySearchResults(max_results=1)]

 model_oai = ChatOpenAI(temperature=0)

@@ -5,5 +5,5 @@ description = "Test for prerelease stuff"
 readme = "README.md"
 requires-python = ">=3.10"
 dependencies = [
-  "langgraph==1.0.2"
+  "langgraph==0.6.0"
 ]
@@ -5,5 +5,5 @@ description = "Test for prerelease stuff"
 readme = "README.md"
 requires-python = ">=3.10"
 dependencies = [
-  "langchain-openai==1.0.1"
+  "langchain-openai==0.3.0"
 ]
@@ -6,9 +6,9 @@ readme = "README.md"
 requires-python = ">=3.10"
 dependencies = [
  "langchain-openai==1.0.0a2",
-  "langchain-anthropic==1.0.0a5",
-  "langgraph==1.0.2"
+  "langgraph==1.0.0a2",
+  "langchain_community>=0.3.0",
 ]

 [tool.uv]
-prerelease = "allow"
+prerelease = "allow"
@@ -13,7 +13,7 @@ from pathlib import Path

 import msgspec

-from langgraph_cli.schemas import (
+from langgraph_cli.config import (
    AuthConfig,
    CheckpointerConfig,
    Config,
@@ -22,7 +22,6 @@ from langgraph_cli.schemas import (
    HttpConfig,
    IndexConfig,
    SecurityConfig,
-    SerdeConfig,
    StoreConfig,
    ThreadTTLConfig,
    TTLConfig,
@@ -113,7 +112,6 @@ def add_descriptions_to_schema(schema, cls):
                CorsConfig,
                ThreadTTLConfig,
                CheckpointerConfig,
-                SerdeConfig,
                TTLConfig,
                ConfigurableHeaderConfig,
            ]:
@@ -1 +1 @@
-__version__ = "0.4.7"
+__version__ = "0.4.4"
@@ -4,12 +4,10 @@ import pathlib
 import re
 import textwrap
 from collections import Counter
-from typing import Literal, NamedTuple
+from typing import Any, Literal, NamedTuple, TypedDict

 import click

-from langgraph_cli.schemas import Config, Distros
-
 MIN_NODE_VERSION = "20"
 DEFAULT_NODE_VERSION = "20"

@@ -19,6 +17,504 @@ DEFAULT_PYTHON_VERSION = "3.11"
 DEFAULT_IMAGE_DISTRO = "debian"


+Distros = Literal["debian", "wolfi", "bullseye", "bookworm"]
+MiddlewareOrders = Literal["auth_first", "middleware_first"]
+
+
+class TTLConfig(TypedDict, total=False):
+    """Configuration for TTL (time-to-live) behavior in the store."""
+
+    refresh_on_read: bool
+    """Default behavior for refreshing TTLs on read operations (`GET` and `SEARCH`).
+    
+    If `True`, TTLs will be refreshed on read operations (get/search) by default.
+    This can be overridden per-operation by explicitly setting `refresh_ttl`.
+    Defaults to `True` if not configured.
+    """
+    default_ttl: float | None
+    """Optional. Default TTL (time-to-live) in minutes for new items.
+    
+    If provided, all new items will have this TTL unless explicitly overridden.
+    If omitted, items will have no TTL by default.
+    """
+    sweep_interval_minutes: int | None
+    """Optional. Interval in minutes between TTL sweep iterations.
+    
+    If provided, the store will periodically delete expired items based on the TTL.
+    If omitted, no automatic sweeping will occur.
+    """
+
+
+class IndexConfig(TypedDict, total=False):
+    """Configuration for indexing documents for semantic search in the store.
+
+    This governs how text is converted into embeddings and stored for vector-based lookups.
+    """
+
+    dims: int
+    """Required. Dimensionality of the embedding vectors you will store.
+    
+    Must match the output dimension of your selected embedding model or custom embed function.
+    If mismatched, you will likely encounter shape/size errors when inserting or querying vectors.
+    
+    Common embedding model output dimensions:
+        - openai:text-embedding-3-large: 3072
+        - openai:text-embedding-3-small: 1536
+        - openai:text-embedding-ada-002: 1536
+        - cohere:embed-english-v3.0: 1024
+        - cohere:embed-english-light-v3.0: 384
+        - cohere:embed-multilingual-v3.0: 1024
+        - cohere:embed-multilingual-light-v3.0: 384
+    """
+
+    embed: str
+    """Required. Identifier or reference to the embedding model or a custom embedding function.
+    
+    The format can vary:
+      - "<provider>:<model_name>" for recognized providers (e.g., "openai:text-embedding-3-large")
+      - "path/to/module.py:function_name" for your own local embedding function
+      - "my_custom_embed" if it's a known alias in your system
+
+     Examples:
+        - "openai:text-embedding-3-large"
+        - "cohere:embed-multilingual-v3.0"
+        - "src/app.py:embeddings"
+    
+    Note: Must return embeddings of dimension `dims`.
+    """
+
+    fields: list[str] | None
+    """Optional. List of JSON fields to extract before generating embeddings.
+    
+    Defaults to ["$"], which means the entire JSON object is embedded as one piece of text.
+    If you provide multiple fields (e.g. ["title", "content"]), each is extracted and embedded separately,
+    often saving token usage if you only care about certain parts of the data.
+    
+    Example:
+        fields=["title", "abstract", "author.biography"]
+    """
+
+
+class StoreConfig(TypedDict, total=False):
+    """Configuration for the built-in long-term memory store.
+
+    This store can optionally perform semantic search. If you omit `index`,
+    the store will just handle traditional (non-embedded) data without vector lookups.
+    """
+
+    index: IndexConfig | None
+    """Optional. Defines the vector-based semantic search configuration.
+    
+    If provided, the store will:
+      - Generate embeddings according to `index.embed`
+      - Enforce the embedding dimension given by `index.dims`
+      - Embed only specified JSON fields (if any) from `index.fields`
+    
+    If omitted, no vector index is initialized.
+    """
+
+    ttl: TTLConfig | None
+    """Optional. Defines the TTL (time-to-live) behavior configuration.
+    
+    If provided, the store will apply TTL settings according to the configuration.
+    If omitted, no TTL behavior is configured.
+    """
+
+
+class ThreadTTLConfig(TypedDict, total=False):
+    """Configure a default TTL for checkpointed data within threads."""
+
+    strategy: Literal["delete"]
+    """Strategy to use for deleting checkpointed data.
+    
+    Choices:
+      - "delete": Delete all checkpoints for a thread after TTL expires.
+    """
+    default_ttl: float | None
+    """Default TTL (time-to-live) in minutes for checkpointed data."""
+    sweep_interval_minutes: int | None
+    """Interval in minutes between sweep iterations.
+    If omitted, a default interval will be used (typically ~ 5 minutes)."""
+
+
+class CheckpointerConfig(TypedDict, total=False):
+    """Configuration for the built-in checkpointer, which handles checkpointing of state.
+
+    If omitted, no checkpointer is set up (the object store will still be present, however).
+    """
+
+    ttl: ThreadTTLConfig | None
+    """Optional. Defines the TTL (time-to-live) behavior configuration.
+    
+    If provided, the checkpointer will apply TTL settings according to the configuration.
+    If omitted, no TTL behavior is configured.
+    """
+
+
+class SecurityConfig(TypedDict, total=False):
+    """Configuration for OpenAPI security definitions and requirements.
+
+    Useful for specifying global or path-level authentication and authorization flows
+    (e.g., OAuth2, API key headers, etc.).
+    """
+
+    securitySchemes: dict[str, dict[str, Any]]
+    """Describe each security scheme recognized by your OpenAPI spec.
+    
+    Keys are scheme names (e.g. "OAuth2", "ApiKeyAuth") and values are their definitions.
+    Example:
+        {
+            "OAuth2": {
+                "type": "oauth2",
+                "flows": {
+                    "password": {
+                        "tokenUrl": "/token",
+                        "scopes": {"read": "Read data", "write": "Write data"}
+                    }
+                }
+            }
+        }
+    """
+    security: list[dict[str, list[str]]]
+    """Global security requirements across all endpoints.
+    
+    Each element in the list maps a security scheme (e.g. "OAuth2") to a list of scopes (e.g. ["read", "write"]).
+    Example:
+        [
+            {"OAuth2": ["read", "write"]},
+            {"ApiKeyAuth": []}
+        ]
+    """
+    # path => {method => security}
+    paths: dict[str, dict[str, list[dict[str, list[str]]]]]
+    """Path-specific security overrides.
+    
+    Keys are path templates (e.g., "/items/{item_id}"), mapping to:
+      - Keys that are HTTP methods (e.g., "GET", "POST"),
+      - Values are lists of security definitions (just like `security`) for that method.
+    
+    Example:
+        {
+            "/private_data": {
+                "GET": [{"OAuth2": ["read"]}],
+                "POST": [{"OAuth2": ["write"]}]
+            }
+        }
+    """
+
+
+class AuthConfig(TypedDict, total=False):
+    """Configuration for custom authentication logic and how it integrates into the OpenAPI spec."""
+
+    path: str
+    """Required. Path to an instance of the Auth() class that implements custom authentication.
+    
+    Format: "path/to/file.py:my_auth"
+    """
+    disable_studio_auth: bool
+    """Optional. Whether to disable LangSmith API-key authentication for requests originating the Studio. 
+    
+    Defaults to False, meaning that if a particular header is set, the server will verify the `x-api-key` header
+    value is a valid API key for the deployment's workspace. If `True`, all requests will go through your custom
+    authentication logic, regardless of origin of the request.
+    """
+    openapi: SecurityConfig
+    """The security configuration to include in your server's OpenAPI spec.
+    
+    Example (OAuth2):
+        {
+            "securitySchemes": {
+                "OAuth2": {
+                    "type": "oauth2",
+                    "flows": {
+                        "password": {
+                            "tokenUrl": "/token",
+                            "scopes": {"me": "Read user info", "items": "Manage items"}
+                        }
+                    }
+                }
+            },
+            "security": [
+                {"OAuth2": ["me"]}
+            ]
+        }
+    """
+
+
+class CorsConfig(TypedDict, total=False):
+    """Specifies Cross-Origin Resource Sharing (CORS) rules for your server.
+
+    If omitted, defaults are typically very restrictive (often no cross-origin requests).
+    Configure carefully if you want to allow usage from browsers hosted on other domains.
+    """
+
+    allow_origins: list[str]
+    """Optional. List of allowed origins (e.g., "https://example.com").
+    
+    Default is often an empty list (no external origins). 
+    Use "*" only if you trust all origins, as that bypasses most restrictions.
+    """
+    allow_methods: list[str]
+    """Optional. HTTP methods permitted for cross-origin requests (e.g. ["GET", "POST"]).
+    
+    Default might be ["GET", "POST", "OPTIONS"] depending on your server framework.
+    """
+    allow_headers: list[str]
+    """Optional. HTTP headers that can be used in cross-origin requests (e.g. ["Content-Type", "Authorization"])."""
+    allow_credentials: bool
+    """Optional. If `True`, cross-origin requests can include credentials (cookies, auth headers).
+    
+    Default False to avoid accidentally exposing secured endpoints to untrusted sites.
+    """
+    allow_origin_regex: str
+    """Optional. A regex pattern for matching allowed origins, used if you have dynamic subdomains.
+    
+    Example: "^https://.*\\.mycompany\\.com$"
+    """
+    expose_headers: list[str]
+    """Optional. List of headers that browsers are allowed to read from the response in cross-origin contexts."""
+    max_age: int
+    """Optional. How many seconds the browser may cache preflight responses.
+    
+    Default might be 600 (10 minutes). Larger values reduce preflight requests but can cause stale configurations.
+    """
+
+
+class ConfigurableHeaderConfig(TypedDict):
+    """Customize which headers to include as configurable values in your runs.
+
+    By default, omits x-api-key, x-tenant-id, and x-service-key.
+
+    Exclusions (if provided) take precedence.
+
+    Each value can be a raw string with an optional wildcard.
+    """
+
+    includes: list[str] | None
+    """Headers to include (if not also matches against an 'exludes' pattern.
+
+    Examples:
+        - 'user-agent'
+        - 'x-configurable-*'
+    """
+    excludes: list[str] | None
+    """Headers to exclude. Applied before the 'includes' checks.
+
+    Examples:
+        - 'x-api-key'
+        - '*key*'
+        - '*token*'
+    """
+
+
+class HttpConfig(TypedDict, total=False):
+    """Configuration for the built-in HTTP server that powers your deployment's routes and endpoints."""
+
+    app: str
+    """Optional. Import path to a custom Starlette/FastAPI application to mount.
+    
+    Format: "path/to/module.py:app_var"
+    If provided, it can override or extend the default routes.
+    """
+    disable_assistants: bool
+    """Optional. If `True`, /assistants routes are removed from the server.
+    
+    Default is False (meaning /assistants is enabled).
+    """
+    disable_threads: bool
+    """Optional. If `True`, /threads routes are removed.
+    
+    Default is False.
+    """
+    disable_runs: bool
+    """Optional. If `True`, /runs routes are removed.
+    
+    Default is False.
+    """
+    disable_store: bool
+    """Optional. If `True`, /store routes are removed, disabling direct store interactions via HTTP.
+    
+    Default is False.
+    """
+    disable_mcp: bool
+    """Optional. If `True`, /mcp routes are removed, disabling the MCP server.
+    
+    Default is False.
+    """
+    disable_meta: bool
+    """Optional. Remove meta endpoints.
+    
+    Set to True to disable the following endpoints: /openapi.json, /info, /metrics, /docs.
+    This will also make the /ok endpoint skip any DB or other checks, always returning {"ok": True}.
+    
+    Default is False.
+    """
+    cors: CorsConfig | None
+    """Optional. Defines CORS restrictions. If omitted, no special rules are set and 
+    cross-origin behavior depends on default server settings.
+    """
+    configurable_headers: ConfigurableHeaderConfig | None
+    """Optional. Defines how headers are treated for a run's configuration.
+
+    You can include or exclude headers as configurable values to condition your
+    agent's behavior or permissions on a request's headers."""
+    logging_headers: ConfigurableHeaderConfig | None
+    """Optional. Defines which headers are excluded from logging."""
+    middleware_order: MiddlewareOrders | None
+    """Optional. Defines the order in which to apply server customizations.
+
+    Choices:
+      - "auth_first": Authentication hooks (custom or default) are evaluated
+      before custom middleware.
+      - "middleware_first": Custom middleware is evaluated
+      before authentication hooks (custom or default).
+
+    Default is `middleware_first`.
+    """
+    enable_custom_route_auth: bool
+    """Optional. If `True`, authentication is enabled for custom routes,
+    not just the routes that are protected by default.
+    (Routes protected by default include /assistants, /threads, and /runs).
+
+    Default is False. This flag only affects authentication behavior
+    if `app` is provided and contains custom routes.
+    """
+
+
+class Config(TypedDict, total=False):
+    """Top-level config for langgraph-cli or similar deployment tooling."""
+
+    python_version: str
+    """Optional. Python version in 'major.minor' format (e.g. '3.11'). 
+    Must be at least 3.11 or greater for this deployment to function properly.
+    """
+
+    node_version: str | None
+    """Optional. Node.js version as a major version (e.g. '20'), if your deployment needs Node.
+    Must be >= 20 if provided.
+    """
+
+    api_version: str | None
+    """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: str | None
+    """Optional. Internal use only.
+    """
+
+    base_image: str | None
+    """Optional. Base image to use for the LangGraph API server.
+    
+    Defaults to langchain/langgraph-api or langchain/langgraphjs-api."""
+
+    image_distro: Distros | None
+    """Optional. Linux distribution for the base image.
+    
+    Must be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.
+    If omitted, defaults to 'debian' ('latest').
+    """
+
+    pip_config_file: str | None
+    """Optional. Path to a pip config file (e.g., "/etc/pip.conf" or "pip.ini") for controlling
+    package installation (custom indices, credentials, etc.).
+    
+    Only relevant if Python dependencies are installed via pip. If omitted, default pip settings are used.
+    """
+
+    pip_installer: str | None
+    """Optional. Python package installer to use ('auto', 'pip', 'uv').
+    
+    - 'auto' (default): Use uv for supported base images, otherwise pip
+    - 'pip': Force use of pip regardless of base image support
+    - 'uv': Force use of uv (will fail if base image doesn't support it)
+    """
+
+    dockerfile_lines: list[str]
+    """Optional. Additional Docker instructions that will be appended to your base Dockerfile.
+    
+    Useful for installing OS packages, setting environment variables, etc. 
+    Example:
+        dockerfile_lines=[
+            "RUN apt-get update && apt-get install -y libmagic-dev",
+            "ENV MY_CUSTOM_VAR=hello_world"
+        ]
+    """
+
+    dependencies: list[str]
+    """List of Python dependencies to install, either from PyPI or local paths.
+    
+    Examples:
+      - "." or "./src" if you have a local Python package
+      - str (aka "anthropic") for a PyPI package
+      - "git+https://github.com/org/repo.git@main" for a Git-based package
+    Defaults to an empty list, meaning no additional packages installed beyond your base environment.
+    """
+
+    graphs: dict[str, str]
+    """Optional. Named definitions of graphs, each pointing to a Python object.
+
+    
+    Graphs can be StateGraph, @entrypoint, or any other Pregel object OR they can point to (async) context
+    managers that accept a single configuration argument (of type RunnableConfig) and return a pregel object
+    (instance of Stategraph, etc.).
+    
+    Keys are graph names, values are "path/to/file.py:object_name".
+    Example:
+        {
+            "mygraph": "graphs/my_graph.py:graph_definition",
+            "anothergraph": "graphs/another.py:get_graph"
+        }
+    """
+
+    env: dict[str, str] | str
+    """Optional. Environment variables to set for your deployment.
+    
+    - If given as a dict, keys are variable names and values are their values.
+    - If given as a string, it must be a path to a file containing lines in KEY=VALUE format.
+    
+    Example as a dict:
+        env={"API_TOKEN": "abc123", "DEBUG": "true"}
+    Example as a file path:
+        env=".env"
+    """
+
+    store: StoreConfig | None
+    """Optional. Configuration for the built-in long-term memory store, including semantic search indexing.
+    
+    If omitted, no vector index is set up (the object store will still be present, however).
+    """
+
+    checkpointer: CheckpointerConfig | None
+    """Optional. Configuration for the built-in checkpointer, which handles checkpointing of state.
+    
+    If omitted, no checkpointer is set up (the object store will still be present, however).
+    """
+
+    auth: AuthConfig | None
+    """Optional. Custom authentication config, including the path to your Python auth logic and 
+    the OpenAPI security definitions it uses.
+    """
+
+    http: HttpConfig | None
+    """Optional. Configuration for the built-in HTTP server, controlling which custom routes are exposed
+    and how cross-origin requests are handled.
+    """
+
+    ui: dict[str, str] | None
+    """Optional. Named definitions of UI components emitted by the agent, each pointing to a JS/TS file.
+    """
+
+    keep_pkg_tools: bool | list[str] | None
+    """Optional. Control whether to retain Python packaging tools in the final image.
+    
+    Allowed tools are: "pip", "setuptools", "wheel".
+    You can also set to true to include all packaging tools.
+    """
+
+
 _BUILD_TOOLS = ("pip", "setuptools", "wheel")


@@ -926,51 +1422,35 @@ ADD {relpath} /deps/{name}
            ]
        )
    image_str = docker_tag(config, base_image, api_version)
-
-    # Prepare docker file contents
-    docker_file_contents = []
-
-    # Add syntax directive if we have additional contexts (requires BuildKit frontend.contexts capability)
-    if local_deps.additional_contexts:
-        docker_file_contents.extend(
-            [
-                "# syntax=docker/dockerfile:1.4",
-                "",
-            ]
-        )
-
-    # Add main dockerfile content
-    docker_file_contents.extend(
-        [
-            f"FROM {image_str}",
-            "",
-            os.linesep.join(config["dockerfile_lines"]),
-            "",
-            installs,
-            "",
-            "# -- Installing all local dependencies --",
-            f"""RUN for dep in /deps/*; do \
+    docker_file_contents = [
+        f"FROM {image_str}",
+        "",
+        os.linesep.join(config["dockerfile_lines"]),
+        "",
+        installs,
+        "",
+        "# -- Installing all local dependencies --",
+        f"""RUN for dep in /deps/*; do \
            echo "Installing $dep"; \
            if [ -d "$dep" ]; then \
                echo "Installing $dep"; \
                (cd "$dep" && {global_reqs_pip_install} -e .); \
            fi; \
        done""",
-            "# -- End of local dependencies install --",
-            os.linesep.join(env_vars),
-            "",
-            js_inst_str,
-            "",
-            # Add pip cleanup after all installations are complete
-            _get_pip_cleanup_lines(
-                install_cmd=install_cmd,
-                to_uninstall=build_tools_to_uninstall,
-                pip_installer=pip_installer,
-            ),
-            "",
-            f"WORKDIR {local_deps.working_dir}" if local_deps.working_dir else "",
-        ]
-    )
+        "# -- End of local dependencies install --",
+        os.linesep.join(env_vars),
+        "",
+        js_inst_str,
+        "",
+        # Add pip cleanup after all installations are complete
+        _get_pip_cleanup_lines(
+            install_cmd=install_cmd,
+            to_uninstall=build_tools_to_uninstall,
+            pip_installer=pip_installer,
+        ),
+        "",
+        f"WORKDIR {local_deps.working_dir}" if local_deps.working_dir else "",
+    ]

    additional_contexts: dict[str, str] = {}
    for p in local_deps.additional_contexts:
@@ -1,558 +0,0 @@
-from typing import Any, Literal, TypedDict
-
-Distros = Literal["debian", "wolfi", "bullseye", "bookworm"]
-MiddlewareOrders = Literal["auth_first", "middleware_first"]
-
-
-class TTLConfig(TypedDict, total=False):
-    """Configuration for TTL (time-to-live) behavior in the store."""
-
-    refresh_on_read: bool
-    """Default behavior for refreshing TTLs on read operations (`GET` and `SEARCH`).
-    
-    If `True`, TTLs will be refreshed on read operations (get/search) by default.
-    This can be overridden per-operation by explicitly setting `refresh_ttl`.
-    Defaults to `True` if not configured.
-    """
-    default_ttl: float | None
-    """Optional. Default TTL (time-to-live) in minutes for new items.
-    
-    If provided, all new items will have this TTL unless explicitly overridden.
-    If omitted, items will have no TTL by default.
-    """
-    sweep_interval_minutes: int | None
-    """Optional. Interval in minutes between TTL sweep iterations.
-    
-    If provided, the store will periodically delete expired items based on the TTL.
-    If omitted, no automatic sweeping will occur.
-    """
-
-
-class IndexConfig(TypedDict, total=False):
-    """Configuration for indexing documents for semantic search in the store.
-
-    This governs how text is converted into embeddings and stored for vector-based lookups.
-    """
-
-    dims: int
-    """Required. Dimensionality of the embedding vectors you will store.
-    
-    Must match the output dimension of your selected embedding model or custom embed function.
-    If mismatched, you will likely encounter shape/size errors when inserting or querying vectors.
-    
-    Common embedding model output dimensions:
-        - openai:text-embedding-3-large: 3072
-        - openai:text-embedding-3-small: 1536
-        - openai:text-embedding-ada-002: 1536
-        - cohere:embed-english-v3.0: 1024
-        - cohere:embed-english-light-v3.0: 384
-        - cohere:embed-multilingual-v3.0: 1024
-        - cohere:embed-multilingual-light-v3.0: 384
-    """
-
-    embed: str
-    """Required. Identifier or reference to the embedding model or a custom embedding function.
-    
-    The format can vary:
-      - "<provider>:<model_name>" for recognized providers (e.g., "openai:text-embedding-3-large")
-      - "path/to/module.py:function_name" for your own local embedding function
-      - "my_custom_embed" if it's a known alias in your system
-
-     Examples:
-        - "openai:text-embedding-3-large"
-        - "cohere:embed-multilingual-v3.0"
-        - "src/app.py:embeddings"
-    
-    Note: Must return embeddings of dimension `dims`.
-    """
-
-    fields: list[str] | None
-    """Optional. List of JSON fields to extract before generating embeddings.
-    
-    Defaults to ["$"], which means the entire JSON object is embedded as one piece of text.
-    If you provide multiple fields (e.g. ["title", "content"]), each is extracted and embedded separately,
-    often saving token usage if you only care about certain parts of the data.
-    
-    Example:
-        fields=["title", "abstract", "author.biography"]
-    """
-
-
-class StoreConfig(TypedDict, total=False):
-    """Configuration for the built-in long-term memory store.
-
-    This store can optionally perform semantic search. If you omit `index`,
-    the store will just handle traditional (non-embedded) data without vector lookups.
-    """
-
-    index: IndexConfig | None
-    """Optional. Defines the vector-based semantic search configuration.
-    
-    If provided, the store will:
-      - Generate embeddings according to `index.embed`
-      - Enforce the embedding dimension given by `index.dims`
-      - Embed only specified JSON fields (if any) from `index.fields`
-    
-    If omitted, no vector index is initialized.
-    """
-
-    ttl: TTLConfig | None
-    """Optional. Defines the TTL (time-to-live) behavior configuration.
-    
-    If provided, the store will apply TTL settings according to the configuration.
-    If omitted, no TTL behavior is configured.
-    """
-
-
-class ThreadTTLConfig(TypedDict, total=False):
-    """Configure a default TTL for checkpointed data within threads."""
-
-    strategy: Literal["delete"]
-    """Strategy to use for deleting checkpointed data.
-    
-    Choices:
-      - "delete": Delete all checkpoints for a thread after TTL expires.
-    """
-    default_ttl: float | None
-    """Default TTL (time-to-live) in minutes for checkpointed data."""
-    sweep_interval_minutes: int | None
-    """Interval in minutes between sweep iterations.
-    If omitted, a default interval will be used (typically ~ 5 minutes)."""
-
-
-class SerdeConfig(TypedDict, total=False):
-    """Configuration for the built-in serde, which handles checkpointing of state.
-
-    If omitted, no serde is set up (the object store will still be present, however)."""
-
-    allowed_json_modules: list[list[str]] | bool | None
-    """Optional. List of allowed python modules to de-serialize custom objects from.
-    
-    If provided, only the specified modules will be allowed to be deserialized.
-    If omitted, no modules are allowed, and the object returned will simply be a json object OR
-    a deserialized langchain object.
-    
-    Example:
-    {...
-        "serde": {
-            "allowed_json_modules": [
-                ["my_agent", "my_file", "SomeType"],
-            ]
-        }
-    }
-
-    If you set this to True, any module will be allowed to be deserialized.
-
-    Example:
-    {...
-        "serde": {
-            "allowed_json_modules": true
-        }
-    }
-    
-    """
-    pickle_fallback: bool
-    """Optional. Whether to allow pickling as a fallback for deserialization.
-    
-    If True, pickling will be allowed as a fallback for deserialization.
-    If False, pickling will not be allowed as a fallback for deserialization.
-    Defaults to True if not configured."""
-
-
-class CheckpointerConfig(TypedDict, total=False):
-    """Configuration for the built-in checkpointer, which handles checkpointing of state.
-
-    If omitted, no checkpointer is set up (the object store will still be present, however).
-    """
-
-    ttl: ThreadTTLConfig | None
-    """Optional. Defines the TTL (time-to-live) behavior configuration.
-    
-    If provided, the checkpointer will apply TTL settings according to the configuration.
-    If omitted, no TTL behavior is configured.
-    """
-    serde: SerdeConfig | None
-    """Optional. Defines the serde configuration.
-    
-    If provided, the checkpointer will apply serde settings according to the configuration.
-    If omitted, no serde behavior is configured.
-
-    This configuration requires server version 0.5 or later to take effect.
-    """
-
-
-class SecurityConfig(TypedDict, total=False):
-    """Configuration for OpenAPI security definitions and requirements.
-
-    Useful for specifying global or path-level authentication and authorization flows
-    (e.g., OAuth2, API key headers, etc.).
-    """
-
-    securitySchemes: dict[str, dict[str, Any]]
-    """Describe each security scheme recognized by your OpenAPI spec.
-    
-    Keys are scheme names (e.g. "OAuth2", "ApiKeyAuth") and values are their definitions.
-    Example:
-        {
-            "OAuth2": {
-                "type": "oauth2",
-                "flows": {
-                    "password": {
-                        "tokenUrl": "/token",
-                        "scopes": {"read": "Read data", "write": "Write data"}
-                    }
-                }
-            }
-        }
-    """
-    security: list[dict[str, list[str]]]
-    """Global security requirements across all endpoints.
-    
-    Each element in the list maps a security scheme (e.g. "OAuth2") to a list of scopes (e.g. ["read", "write"]).
-    Example:
-        [
-            {"OAuth2": ["read", "write"]},
-            {"ApiKeyAuth": []}
-        ]
-    """
-    # path => {method => security}
-    paths: dict[str, dict[str, list[dict[str, list[str]]]]]
-    """Path-specific security overrides.
-    
-    Keys are path templates (e.g., "/items/{item_id}"), mapping to:
-      - Keys that are HTTP methods (e.g., "GET", "POST"),
-      - Values are lists of security definitions (just like `security`) for that method.
-    
-    Example:
-        {
-            "/private_data": {
-                "GET": [{"OAuth2": ["read"]}],
-                "POST": [{"OAuth2": ["write"]}]
-            }
-        }
-    """
-
-
-class AuthConfig(TypedDict, total=False):
-    """Configuration for custom authentication logic and how it integrates into the OpenAPI spec."""
-
-    path: str
-    """Required. Path to an instance of the Auth() class that implements custom authentication.
-    
-    Format: "path/to/file.py:my_auth"
-    """
-    disable_studio_auth: bool
-    """Optional. Whether to disable LangSmith API-key authentication for requests originating the Studio. 
-    
-    Defaults to False, meaning that if a particular header is set, the server will verify the `x-api-key` header
-    value is a valid API key for the deployment's workspace. If `True`, all requests will go through your custom
-    authentication logic, regardless of origin of the request.
-    """
-    openapi: SecurityConfig
-    """The security configuration to include in your server's OpenAPI spec.
-    
-    Example (OAuth2):
-        {
-            "securitySchemes": {
-                "OAuth2": {
-                    "type": "oauth2",
-                    "flows": {
-                        "password": {
-                            "tokenUrl": "/token",
-                            "scopes": {"me": "Read user info", "items": "Manage items"}
-                        }
-                    }
-                }
-            },
-            "security": [
-                {"OAuth2": ["me"]}
-            ]
-        }
-    """
-
-
-class CorsConfig(TypedDict, total=False):
-    """Specifies Cross-Origin Resource Sharing (CORS) rules for your server.
-
-    If omitted, defaults are typically very restrictive (often no cross-origin requests).
-    Configure carefully if you want to allow usage from browsers hosted on other domains.
-    """
-
-    allow_origins: list[str]
-    """Optional. List of allowed origins (e.g., "https://example.com").
-    
-    Default is often an empty list (no external origins). 
-    Use "*" only if you trust all origins, as that bypasses most restrictions.
-    """
-    allow_methods: list[str]
-    """Optional. HTTP methods permitted for cross-origin requests (e.g. ["GET", "POST"]).
-    
-    Default might be ["GET", "POST", "OPTIONS"] depending on your server framework.
-    """
-    allow_headers: list[str]
-    """Optional. HTTP headers that can be used in cross-origin requests (e.g. ["Content-Type", "Authorization"])."""
-    allow_credentials: bool
-    """Optional. If `True`, cross-origin requests can include credentials (cookies, auth headers).
-    
-    Default False to avoid accidentally exposing secured endpoints to untrusted sites.
-    """
-    allow_origin_regex: str
-    """Optional. A regex pattern for matching allowed origins, used if you have dynamic subdomains.
-    
-    Example: "^https://.*\\.mycompany\\.com$"
-    """
-    expose_headers: list[str]
-    """Optional. List of headers that browsers are allowed to read from the response in cross-origin contexts."""
-    max_age: int
-    """Optional. How many seconds the browser may cache preflight responses.
-    
-    Default might be 600 (10 minutes). Larger values reduce preflight requests but can cause stale configurations.
-    """
-
-
-class ConfigurableHeaderConfig(TypedDict):
-    """Customize which headers to include as configurable values in your runs.
-
-    By default, omits x-api-key, x-tenant-id, and x-service-key.
-
-    Exclusions (if provided) take precedence.
-
-    Each value can be a raw string with an optional wildcard.
-    """
-
-    includes: list[str] | None
-    """Headers to include (if not also matches against an 'exludes' pattern.
-
-    Examples:
-        - 'user-agent'
-        - 'x-configurable-*'
-    """
-    excludes: list[str] | None
-    """Headers to exclude. Applied before the 'includes' checks.
-
-    Examples:
-        - 'x-api-key'
-        - '*key*'
-        - '*token*'
-    """
-
-
-class HttpConfig(TypedDict, total=False):
-    """Configuration for the built-in HTTP server that powers your deployment's routes and endpoints."""
-
-    app: str
-    """Optional. Import path to a custom Starlette/FastAPI application to mount.
-    
-    Format: "path/to/module.py:app_var"
-    If provided, it can override or extend the default routes.
-    """
-    disable_assistants: bool
-    """Optional. If `True`, /assistants routes are removed from the server.
-    
-    Default is False (meaning /assistants is enabled).
-    """
-    disable_threads: bool
-    """Optional. If `True`, /threads routes are removed.
-    
-    Default is False.
-    """
-    disable_runs: bool
-    """Optional. If `True`, /runs routes are removed.
-    
-    Default is False.
-    """
-    disable_store: bool
-    """Optional. If `True`, /store routes are removed, disabling direct store interactions via HTTP.
-    
-    Default is False.
-    """
-    disable_mcp: bool
-    """Optional. If `True`, /mcp routes are removed, disabling the MCP server.
-    
-    Default is False.
-    """
-    disable_meta: bool
-    """Optional. Remove meta endpoints.
-    
-    Set to True to disable the following endpoints: /openapi.json, /info, /metrics, /docs.
-    This will also make the /ok endpoint skip any DB or other checks, always returning {"ok": True}.
-    
-    Default is False.
-    """
-    cors: CorsConfig | None
-    """Optional. Defines CORS restrictions. If omitted, no special rules are set and 
-    cross-origin behavior depends on default server settings.
-    """
-    configurable_headers: ConfigurableHeaderConfig | None
-    """Optional. Defines how headers are treated for a run's configuration.
-
-    You can include or exclude headers as configurable values to condition your
-    agent's behavior or permissions on a request's headers."""
-    logging_headers: ConfigurableHeaderConfig | None
-    """Optional. Defines which headers are excluded from logging."""
-    middleware_order: MiddlewareOrders | None
-    """Optional. Defines the order in which to apply server customizations.
-
-    Choices:
-      - "auth_first": Authentication hooks (custom or default) are evaluated
-      before custom middleware.
-      - "middleware_first": Custom middleware is evaluated
-      before authentication hooks (custom or default).
-
-    Default is `middleware_first`.
-    """
-    enable_custom_route_auth: bool
-    """Optional. If `True`, authentication is enabled for custom routes,
-    not just the routes that are protected by default.
-    (Routes protected by default include /assistants, /threads, and /runs).
-
-    Default is False. This flag only affects authentication behavior
-    if `app` is provided and contains custom routes.
-    """
-
-
-class Config(TypedDict, total=False):
-    """Top-level config for langgraph-cli or similar deployment tooling."""
-
-    python_version: str
-    """Optional. Python version in 'major.minor' format (e.g. '3.11'). 
-    Must be at least 3.11 or greater for this deployment to function properly.
-    """
-
-    node_version: str | None
-    """Optional. Node.js version as a major version (e.g. '20'), if your deployment needs Node.
-    Must be >= 20 if provided.
-    """
-
-    api_version: str | None
-    """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: str | None
-    """Optional. Internal use only.
-    """
-
-    base_image: str | None
-    """Optional. Base image to use for the LangGraph API server.
-    
-    Defaults to langchain/langgraph-api or langchain/langgraphjs-api."""
-
-    image_distro: Distros | None
-    """Optional. Linux distribution for the base image.
-    
-    Must be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.
-    If omitted, defaults to 'debian' ('latest').
-    """
-
-    pip_config_file: str | None
-    """Optional. Path to a pip config file (e.g., "/etc/pip.conf" or "pip.ini") for controlling
-    package installation (custom indices, credentials, etc.).
-    
-    Only relevant if Python dependencies are installed via pip. If omitted, default pip settings are used.
-    """
-
-    pip_installer: str | None
-    """Optional. Python package installer to use ('auto', 'pip', 'uv').
-    
-    - 'auto' (default): Use uv for supported base images, otherwise pip
-    - 'pip': Force use of pip regardless of base image support
-    - 'uv': Force use of uv (will fail if base image doesn't support it)
-    """
-
-    dockerfile_lines: list[str]
-    """Optional. Additional Docker instructions that will be appended to your base Dockerfile.
-    
-    Useful for installing OS packages, setting environment variables, etc. 
-    Example:
-        dockerfile_lines=[
-            "RUN apt-get update && apt-get install -y libmagic-dev",
-            "ENV MY_CUSTOM_VAR=hello_world"
-        ]
-    """
-
-    dependencies: list[str]
-    """List of Python dependencies to install, either from PyPI or local paths.
-    
-    Examples:
-      - "." or "./src" if you have a local Python package
-      - str (aka "anthropic") for a PyPI package
-      - "git+https://github.com/org/repo.git@main" for a Git-based package
-    Defaults to an empty list, meaning no additional packages installed beyond your base environment.
-    """
-
-    graphs: dict[str, str]
-    """Optional. Named definitions of graphs, each pointing to a Python object.
-
-    
-    Graphs can be StateGraph, @entrypoint, or any other Pregel object OR they can point to (async) context
-    managers that accept a single configuration argument (of type RunnableConfig) and return a pregel object
-    (instance of Stategraph, etc.).
-    
-    Keys are graph names, values are "path/to/file.py:object_name".
-    Example:
-        {
-            "mygraph": "graphs/my_graph.py:graph_definition",
-            "anothergraph": "graphs/another.py:get_graph"
-        }
-    """
-
-    env: dict[str, str] | str
-    """Optional. Environment variables to set for your deployment.
-    
-    - If given as a dict, keys are variable names and values are their values.
-    - If given as a string, it must be a path to a file containing lines in KEY=VALUE format.
-    
-    Example as a dict:
-        env={"API_TOKEN": "abc123", "DEBUG": "true"}
-    Example as a file path:
-        env=".env"
-    """
-
-    store: StoreConfig | None
-    """Optional. Configuration for the built-in long-term memory store, including semantic search indexing.
-    
-    If omitted, no vector index is set up (the object store will still be present, however).
-    """
-
-    checkpointer: CheckpointerConfig | None
-    """Optional. Configuration for the built-in checkpointer, which handles checkpointing of state.
-    
-    If omitted, no checkpointer is set up (the object store will still be present, however).
-    """
-
-    auth: AuthConfig | None
-    """Optional. Custom authentication config, including the path to your Python auth logic and 
-    the OpenAPI security definitions it uses.
-    """
-
-    http: HttpConfig | None
-    """Optional. Configuration for the built-in HTTP server, controlling which custom routes are exposed
-    and how cross-origin requests are handled.
-    """
-
-    ui: dict[str, str] | None
-    """Optional. Named definitions of UI components emitted by the agent, each pointing to a JS/TS file.
-    """
-
-    keep_pkg_tools: bool | list[str] | None
-    """Optional. Control whether to retain Python packaging tools in the final image.
-    
-    Allowed tools are: "pip", "setuptools", "wheel".
-    You can also set to true to include all packaging tools.
-    """
-
-
-__all__ = [
-    "Config",
-    "StoreConfig",
-    "CheckpointerConfig",
-    "AuthConfig",
-    "HttpConfig",
-    "MiddlewareOrders",
-    "Distros",
-    "TTLConfig",
-    "IndexConfig",
-]
@@ -19,16 +19,13 @@ dependencies = [
 path = "langgraph_cli/__init__.py"
 [project.optional-dependencies]
 inmem = [
-    "langgraph-api>=0.4,<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",
 ]

 [project.urls]
-Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/cli"
-Twitter = "https://x.com/LangChainAI"
-Slack = "https://www.langchain.com/join-community"
-Reddit = "https://www.reddit.com/r/LangChain/"
+Repository = "https://www.github.com/langchain-ai/langgraph"

 [project.scripts]
 langgraph = "langgraph_cli.cli:cli"
@@ -71,4 +68,4 @@ lint.select = [
  "UP", # pyupgrade
 ]
 lint.ignore = ["E501", "B008"]
-target-version = "py310"
+target-version = "py310"
@@ -8,7 +8,7 @@ authors = [
 license = { text = "MIT" }
 requires-python = ">=3.11,<4.0"
 dependencies = [
-    "langgraph>=0.6.0,<2",
+    "langgraph>=0.6.0,<0.7.0",
    "langchain-core>=0.2.14",
 ]

@@ -472,17 +472,6 @@
      "description": "Configuration for the built-in checkpointer, which handles checkpointing of state.\n\nIf omitted, no checkpointer is set up (the object store will still be present, however).",
      "type": "object",
      "properties": {
-        "serde": {
-          "anyOf": [
-            {
-              "$ref": "#/$defs/SerdeConfig"
-            },
-            {
-              "type": "null"
-            }
-          ],
-          "description": "Optional. Defines the serde configuration.\n\nIf provided, the checkpointer will apply serde settings according to the configuration.\nIf omitted, no serde behavior is configured.\n\nThis configuration requires server version 0.5 or later to take effect.\n"
-        },
        "ttl": {
          "anyOf": [
            {
@@ -497,38 +486,6 @@
      },
      "required": []
    },
-    "SerdeConfig": {
-      "title": "SerdeConfig",
-      "description": "Configuration for the built-in serde, which handles checkpointing of state.\n\nIf omitted, no serde is set up (the object store will still be present, however).",
-      "type": "object",
-      "properties": {
-        "allowed_json_modules": {
-          "anyOf": [
-            {
-              "type": "array",
-              "items": {
-                "type": "array",
-                "items": {
-                  "type": "string"
-                }
-              }
-            },
-            {
-              "type": "boolean"
-            },
-            {
-              "type": "null"
-            }
-          ],
-          "description": "Optional. List of allowed python modules to de-serialize custom objects from.\n\nIf provided, only the specified modules will be allowed to be deserialized.\nIf omitted, no modules are allowed, and the object returned will simply be a json object OR\na deserialized langchain object.\n"
-        },
-        "pickle_fallback": {
-          "type": "boolean",
-          "description": "Optional. Whether to allow pickling as a fallback for deserialization.\n\nIf True, pickling will be allowed as a fallback for deserialization.\nIf False, pickling will not be allowed as a fallback for deserialization.\nDefaults to True if not configured."
-        }
-      },
-      "required": []
-    },
    "ThreadTTLConfig": {
      "title": "ThreadTTLConfig",
      "description": "Configure a default TTL for checkpointed data within threads.",
@@ -472,17 +472,6 @@
      "description": "Configuration for the built-in checkpointer, which handles checkpointing of state.\n\nIf omitted, no checkpointer is set up (the object store will still be present, however).",
      "type": "object",
      "properties": {
-        "serde": {
-          "anyOf": [
-            {
-              "$ref": "#/$defs/SerdeConfig"
-            },
-            {
-              "type": "null"
-            }
-          ],
-          "description": "Optional. Defines the serde configuration.\n\nIf provided, the checkpointer will apply serde settings according to the configuration.\nIf omitted, no serde behavior is configured.\n\nThis configuration requires server version 0.5 or later to take effect.\n"
-        },
        "ttl": {
          "anyOf": [
            {
@@ -497,38 +486,6 @@
      },
      "required": []
    },
-    "SerdeConfig": {
-      "title": "SerdeConfig",
-      "description": "Configuration for the built-in serde, which handles checkpointing of state.\n\nIf omitted, no serde is set up (the object store will still be present, however).",
-      "type": "object",
-      "properties": {
-        "allowed_json_modules": {
-          "anyOf": [
-            {
-              "type": "array",
-              "items": {
-                "type": "array",
-                "items": {
-                  "type": "string"
-                }
-              }
-            },
-            {
-              "type": "boolean"
-            },
-            {
-              "type": "null"
-            }
-          ],
-          "description": "Optional. List of allowed python modules to de-serialize custom objects from.\n\nIf provided, only the specified modules will be allowed to be deserialized.\nIf omitted, no modules are allowed, and the object returned will simply be a json object OR\na deserialized langchain object.\n"
-        },
-        "pickle_fallback": {
-          "type": "boolean",
-          "description": "Optional. Whether to allow pickling as a fallback for deserialization.\n\nIf True, pickling will be allowed as a fallback for deserialization.\nIf False, pickling will not be allowed as a fallback for deserialization.\nDefaults to True if not configured."
-        }
-      },
-      "required": []
-    },
    "ThreadTTLConfig": {
      "title": "ThreadTTLConfig",
      "description": "Configure a default TTL for checkpointed data within threads.",
@@ -141,7 +141,6 @@ services:
            additional_contexts:
                - cli_1: {str(pathlib.Path(__file__).parent.parent.parent.parent.absolute())}
            dockerfile_inline: |
-                # syntax=docker/dockerfile:1.4
                FROM langchain/langgraph-api:3.11
                # -- Adding local package . --
                ADD . /deps/cli
@@ -419,7 +419,6 @@ def test_config_to_docker_simple():
        "langchain/langgraph-api",
    )
    expected_docker_stdin = f"""\
-# syntax=docker/dockerfile:1.4
 FROM langchain/langgraph-api:3.11
 # -- Installing local requirements --
 COPY --from=outer-requirements.txt requirements.txt /deps/outer-graphs_reqs_a/graphs_reqs_a/requirements.txt
@@ -483,7 +482,6 @@ def test_config_to_docker_outside_path():
    )
    expected_docker_stdin = (
        """\
-# syntax=docker/dockerfile:1.4
 FROM langchain/langgraph-api:3.11
 # -- Adding non-package dependency unit_tests --
 ADD . /deps/outer-unit_tests/unit_tests
@@ -0,0 +1,16 @@
+{
+  "permissions": {
+    "allow": [
+      "Bash(rg:*)",
+      "Bash(python:*)",
+      "Bash(grep:*)",
+      "Bash(sed:*)",
+      "Bash(awk:*)",
+      "Bash(uv run mypy:*)",
+      "Bash(uv run:*)",
+      "Bash(make test:*)",
+      "Bash(make test_parallel:*)"
+    ],
+    "deny": []
+  }
+}
@@ -151,13 +151,13 @@ def task(


        @task
-        def add_one_task(a: int) -> int:
+        def add_one(a: int) -> int:
            return a + 1


        @entrypoint()
        def add_one(numbers: list[int]) -> list[int]:
-            futures = [add_one_task(n) for n in numbers]
+            futures = [add_one(n) for n in numbers]
            results = [f.result() for f in futures]
            return results

@@ -173,13 +173,13 @@ def task(


        @task
-        async def add_one_task(a: int) -> int:
+        async def add_one(a: int) -> int:
            return a + 1


        @entrypoint()
        async def add_one(numbers: list[int]) -> list[int]:
-            futures = [add_one_task(n) for n in numbers]
+            futures = [add_one(n) for n in numbers]
            return asyncio.gather(*futures)


@@ -30,7 +30,6 @@ __all__ = (
    "add_messages",
    "MessagesState",
    "MessageGraph",
-    "REMOVE_ALL_MESSAGES",
 )

 Messages = list[MessageLikeRepresentation] | MessageLikeRepresentation
@@ -110,20 +110,12 @@ def _get_node_name(node: StateNode[Any, ContextT]) -> str:

 class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
    """A graph whose nodes communicate by reading and writing to a shared state.
-
-    The signature of each node is `State -> Partial<State>`.
+    The signature of each node is State -> Partial<State>.

    Each state key can optionally be annotated with a reducer function that
    will be used to aggregate the values of that key received from multiple nodes.
    The signature of a reducer function is `(Value, Value) -> Value`.

-    !!! warning
-
-        `StateGraph` is a builder class and cannot be used directly for execution.
-        You must first call `.compile()` to create an executable graph that supports
-        methods like `invoke()`, `stream()`, `astream()`, and `ainvoke()`. See the
-        `CompiledStateGraph` documentation for more details.
-
    Args:
        state_schema: The schema class that defines the state.
        context_schema: The schema class that defines the runtime context.
@@ -297,7 +289,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
        destinations: dict[str, str] | tuple[str, ...] | None = None,
        **kwargs: Unpack[DeprecatedKwargs],
    ) -> Self:
-        """Add a new node to the `StateGraph`, input schema is inferred as the state schema.
+        """Add a new node to the state graph, input schema is inferred as the state schema.
        Will take the name of the function/runnable as the node name.
        """
        ...
@@ -315,7 +307,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
        destinations: dict[str, str] | tuple[str, ...] | None = None,
        **kwargs: Unpack[DeprecatedKwargs],
    ) -> Self:
-        """Add a new node to the `StateGraph`, input schema is specified.
+        """Add a new node to the state graph, input schema is specified.
        Will take the name of the function/runnable as the node name.
        """
        ...
@@ -334,7 +326,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
        destinations: dict[str, str] | tuple[str, ...] | None = None,
        **kwargs: Unpack[DeprecatedKwargs],
    ) -> Self:
-        """Add a new node to the `StateGraph`, input schema is inferred as the state schema."""
+        """Add a new node to the state graph, input schema is inferred as the state schema."""
        ...

    @overload
@@ -351,7 +343,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
        destinations: dict[str, str] | tuple[str, ...] | None = None,
        **kwargs: Unpack[DeprecatedKwargs],
    ) -> Self:
-        """Add a new node to the `StateGraph`, input schema is specified."""
+        """Add a new node to the state graph, input schema is specified."""
        ...

    def add_node(
@@ -367,7 +359,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
        destinations: dict[str, str] | tuple[str, ...] | None = None,
        **kwargs: Unpack[DeprecatedKwargs],
    ) -> Self:
-        """Add a new node to the `StateGraph`.
+        """Add a new node to the state graph.

        Args:
            node: The function or runnable this node will run.
@@ -424,7 +416,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
            ```

        Returns:
-            Self: The instance of the `StateGraph`, allowing for method chaining.
+            Self: The instance of the state graph, allowing for method chaining.
        """
        if (retry := kwargs.get("retry", MISSING)) is not MISSING:
            warnings.warn(
@@ -579,7 +571,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
            ValueError: If the start key is `'END'` or if the start key or end key is not present in the graph.

        Returns:
-            Self: The instance of the `StateGraph`, allowing for method chaining.
+            Self: The instance of the state graph, allowing for method chaining.
        """
        if self.compiled:
            logger.warning(
@@ -684,7 +676,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
            ValueError: If the sequence contains duplicate node names.

        Returns:
-            Self: The instance of the `StateGraph`, allowing for method chaining.
+            Self: The instance of the state graph, allowing for method chaining.
        """
        if len(nodes) < 1:
            raise ValueError("Sequence requires at least one node.")
@@ -817,7 +809,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
        debug: bool = False,
        name: str | None = None,
    ) -> CompiledStateGraph[StateT, ContextT, InputT, OutputT]:
-        """Compiles the `StateGraph` into a `CompiledStateGraph` object.
+        """Compiles the state graph into a `CompiledStateGraph` object.

        The compiled graph implements the `Runnable` interface and can be invoked,
        streamed, batched, and run asynchronously.
@@ -834,7 +826,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
            name: The name to use for the compiled graph.

        Returns:
-            CompiledStateGraph: The compiled `StateGraph`.
+            CompiledStateGraph: The compiled state graph.
        """
        # assign default values
        interrupt_before = interrupt_before or []
@@ -81,8 +81,9 @@ def push_ui_message(
        metadata: Optional additional metadata about the UI message.
        message: Optional message object to associate with the UI message.
        state_key: Key in the graph state where the UI messages are stored.
+            Defaults to "ui".
        merge: Whether to merge props with existing UI message (True) or replace
-            them (False).
+            them (False). Defaults to False.

    Returns:
        The created UI message.
@@ -258,11 +258,9 @@ def apply_writes(
        next_version = None
    else:
        next_version = get_next_version(
-            (
-                max(checkpoint["channel_versions"].values())
-                if checkpoint["channel_versions"]
-                else None
-            ),
+            max(checkpoint["channel_versions"].values())
+            if checkpoint["channel_versions"]
+            else None,
            None,
        )

@@ -493,11 +491,6 @@ def prepare_next_tasks(
 PUSH_TRIGGER = (PUSH,)


-class _TaskIDFn(Protocol):
-    def __call__(self, namespace: bytes, *parts: str | bytes) -> str:
-        pass
-
-
 def prepare_single_task(
    task_path: tuple[Any, ...],
    task_id_checksum: str | None,
@@ -527,50 +520,250 @@ def prepare_single_task(
    task_id_func = _xxhash_str if checkpoint["v"] > 1 else _uuid5_str

    if task_path[0] == PUSH and isinstance(task_path[-1], Call):
-        return prepare_push_task_functional(
-            cast(tuple[str, tuple, int, str, Call], task_path),
-            task_id_checksum,
-            checkpoint=checkpoint,
-            checkpoint_id_bytes=checkpoint_id_bytes,
-            pending_writes=pending_writes,
-            channels=channels,
-            managed=managed,
-            config=config,
-            step=step,
-            stop=stop,
-            for_execution=for_execution,
-            store=store,
-            checkpointer=checkpointer,
-            manager=manager,
-            cache_policy=cache_policy,
-            retry_policy=retry_policy,
-            parent_ns=parent_ns,
-            task_id_func=task_id_func,
+        # (PUSH, parent task path, idx of PUSH write, id of parent task, Call)
+        task_path_t = cast(tuple[str, tuple, int, str, Call], task_path)
+        call = task_path_t[-1]
+        proc_ = get_runnable_for_task(call.func)
+        name = proc_.name
+        if name is None:
+            raise ValueError("`call` functions must have a `__name__` attribute")
+        # create task id
+        triggers: Sequence[str] = PUSH_TRIGGER
+        checkpoint_ns = f"{parent_ns}{NS_SEP}{name}" if parent_ns else name
+        task_id = task_id_func(
+            checkpoint_id_bytes,
+            checkpoint_ns,
+            str(step),
+            name,
+            PUSH,
+            task_path_str(task_path[1]),
+            str(task_path[2]),
        )
-
+        task_checkpoint_ns = f"{checkpoint_ns}:{task_id}"
+        # we append True to the task path to indicate that a call is being
+        # made, so we should not return interrupts from this task (responsibility lies with the parent)
+        task_path = (*task_path[:3], True)
+        metadata = {
+            "langgraph_step": step,
+            "langgraph_node": name,
+            "langgraph_triggers": triggers,
+            "langgraph_path": task_path,
+            "langgraph_checkpoint_ns": task_checkpoint_ns,
+        }
+        if task_id_checksum is not None:
+            assert task_id == task_id_checksum, f"{task_id} != {task_id_checksum}"
+        if for_execution:
+            writes: deque[tuple[str, Any]] = deque()
+            cache_policy = call.cache_policy or cache_policy
+            if cache_policy:
+                args_key = cache_policy.key_func(*call.input[0], **call.input[1])
+                cache_key: CacheKey | None = CacheKey(
+                    (
+                        CACHE_NS_WRITES,
+                        (identifier(call.func) or "__dynamic__"),
+                    ),
+                    xxh3_128_hexdigest(
+                        args_key.encode() if isinstance(args_key, str) else args_key,
+                    ),
+                    cache_policy.ttl,
+                )
+            else:
+                cache_key = None
+            scratchpad = _scratchpad(
+                config[CONF].get(CONFIG_KEY_SCRATCHPAD),
+                pending_writes,
+                task_id,
+                xxh3_128_hexdigest(task_checkpoint_ns.encode()),
+                config[CONF].get(CONFIG_KEY_RESUME_MAP),
+                step,
+                stop,
+            )
+            runtime = cast(
+                Runtime, configurable.get(CONFIG_KEY_RUNTIME, DEFAULT_RUNTIME)
+            )
+            runtime = runtime.override(store=store)
+            return PregelExecutableTask(
+                name,
+                call.input,
+                proc_,
+                writes,
+                patch_config(
+                    merge_configs(config, {"metadata": metadata}),
+                    run_name=name,
+                    callbacks=call.callbacks
+                    or (manager.get_child(f"graph:step:{step}") if manager else None),
+                    configurable={
+                        CONFIG_KEY_TASK_ID: task_id,
+                        # deque.extend is thread-safe
+                        CONFIG_KEY_SEND: writes.extend,
+                        CONFIG_KEY_READ: partial(
+                            local_read,
+                            scratchpad,
+                            channels,
+                            managed,
+                            PregelTaskWrites(task_path, name, writes, triggers),
+                        ),
+                        CONFIG_KEY_CHECKPOINTER: (
+                            checkpointer or configurable.get(CONFIG_KEY_CHECKPOINTER)
+                        ),
+                        CONFIG_KEY_CHECKPOINT_MAP: {
+                            **configurable.get(CONFIG_KEY_CHECKPOINT_MAP, {}),
+                            parent_ns: checkpoint["id"],
+                        },
+                        CONFIG_KEY_CHECKPOINT_ID: None,
+                        CONFIG_KEY_CHECKPOINT_NS: task_checkpoint_ns,
+                        CONFIG_KEY_SCRATCHPAD: scratchpad,
+                        CONFIG_KEY_RUNTIME: runtime,
+                    },
+                ),
+                triggers,
+                call.retry_policy or retry_policy,
+                cache_key,
+                task_id,
+                task_path,
+            )
+        else:
+            return PregelTask(task_id, name, task_path)
    elif task_path[0] == PUSH:
-        return prepare_push_task_send(
-            cast(tuple[str, tuple], task_path),
-            task_id_checksum,
-            checkpoint=checkpoint,
-            checkpoint_id_bytes=checkpoint_id_bytes,
-            pending_writes=pending_writes,
-            channels=channels,
-            managed=managed,
-            config=config,
-            step=step,
-            processes=processes,
-            stop=stop,
-            for_execution=for_execution,
-            store=store,
-            checkpointer=checkpointer,
-            manager=manager,
-            cache_policy=cache_policy,
-            retry_policy=retry_policy,
-            parent_ns=parent_ns,
-            task_id_func=task_id_func,
-        )
+        if len(task_path) == 2:
+            # SEND tasks, executed in superstep n+1
+            # (PUSH, idx of pending send)
+            idx = cast(int, task_path[1])
+            if not channels[TASKS].is_available():
+                return
+            sends: Sequence[Send] = channels[TASKS].get()
+            if idx < 0 or idx >= len(sends):
+                return
+            packet = sends[idx]
+            if not isinstance(packet, Send):
+                logger.warning(
+                    f"Ignoring invalid packet type {type(packet)} in pending sends"
+                )
+                return

+            if packet.node not in processes:
+                logger.warning(
+                    f"Ignoring unknown node name {packet.node} in pending sends"
+                )
+                return
+            # find process
+            proc = processes[packet.node]
+            proc_node = proc.node
+            if proc_node is None:
+                return
+            # create task id
+            triggers = PUSH_TRIGGER
+            checkpoint_ns = (
+                f"{parent_ns}{NS_SEP}{packet.node}" if parent_ns else packet.node
+            )
+            task_id = task_id_func(
+                checkpoint_id_bytes,
+                checkpoint_ns,
+                str(step),
+                packet.node,
+                PUSH,
+                str(idx),
+            )
+        else:
+            logger.warning(f"Ignoring invalid PUSH task path {task_path}")
+            return
+        task_checkpoint_ns = f"{checkpoint_ns}:{task_id}"
+        # we append False to the task path to indicate that a call is not being made
+        # so we should return interrupts from this task
+        task_path = (*task_path[:3], False)
+        metadata = {
+            "langgraph_step": step,
+            "langgraph_node": packet.node,
+            "langgraph_triggers": triggers,
+            "langgraph_path": task_path,
+            "langgraph_checkpoint_ns": task_checkpoint_ns,
+        }
+        if task_id_checksum is not None:
+            assert task_id == task_id_checksum, f"{task_id} != {task_id_checksum}"
+        if for_execution:
+            if proc.metadata:
+                metadata.update(proc.metadata)
+            writes = deque()
+            cache_policy = proc.cache_policy or cache_policy
+            if cache_policy:
+                args_key = cache_policy.key_func(packet.arg)
+                cache_key = CacheKey(
+                    (
+                        CACHE_NS_WRITES,
+                        (identifier(proc) or "__dynamic__"),
+                        packet.node,
+                    ),
+                    xxh3_128_hexdigest(
+                        args_key.encode() if isinstance(args_key, str) else args_key,
+                    ),
+                    cache_policy.ttl,
+                )
+            else:
+                cache_key = None
+            scratchpad = _scratchpad(
+                config[CONF].get(CONFIG_KEY_SCRATCHPAD),
+                pending_writes,
+                task_id,
+                xxh3_128_hexdigest(task_checkpoint_ns.encode()),
+                config[CONF].get(CONFIG_KEY_RESUME_MAP),
+                step,
+                stop,
+            )
+            runtime = cast(
+                Runtime, configurable.get(CONFIG_KEY_RUNTIME, DEFAULT_RUNTIME)
+            )
+            runtime = runtime.override(
+                store=store, previous=checkpoint["channel_values"].get(PREVIOUS, None)
+            )
+            additional_config: RunnableConfig = {
+                "metadata": metadata,
+                "tags": proc.tags,
+            }
+            return PregelExecutableTask(
+                packet.node,
+                packet.arg,
+                proc_node,
+                writes,
+                patch_config(
+                    merge_configs(config, additional_config),
+                    run_name=packet.node,
+                    callbacks=(
+                        manager.get_child(f"graph:step:{step}") if manager else None
+                    ),
+                    configurable={
+                        CONFIG_KEY_TASK_ID: task_id,
+                        # deque.extend is thread-safe
+                        CONFIG_KEY_SEND: writes.extend,
+                        CONFIG_KEY_READ: partial(
+                            local_read,
+                            scratchpad,
+                            channels,
+                            managed,
+                            PregelTaskWrites(task_path, packet.node, writes, triggers),
+                        ),
+                        CONFIG_KEY_CHECKPOINTER: (
+                            checkpointer or configurable.get(CONFIG_KEY_CHECKPOINTER)
+                        ),
+                        CONFIG_KEY_CHECKPOINT_MAP: {
+                            **configurable.get(CONFIG_KEY_CHECKPOINT_MAP, {}),
+                            parent_ns: checkpoint["id"],
+                        },
+                        CONFIG_KEY_CHECKPOINT_ID: None,
+                        CONFIG_KEY_CHECKPOINT_NS: task_checkpoint_ns,
+                        CONFIG_KEY_SCRATCHPAD: scratchpad,
+                        CONFIG_KEY_RUNTIME: runtime,
+                    },
+                ),
+                triggers,
+                proc.retry_policy or retry_policy,
+                cache_key,
+                task_id,
+                task_path,
+                writers=proc.flat_writers,
+                subgraphs=proc.subgraphs,
+            )
+        else:
+            return PregelTask(task_id, packet.node, task_path)
    elif task_path[0] == PULL:
        # (PULL, node name)
        name = cast(str, task_path[1])
@@ -641,7 +834,7 @@ def prepare_single_task(
                if node := proc.node:
                    if proc.metadata:
                        metadata.update(proc.metadata)
-                    writes: deque[tuple[str, Any]] = deque()
+                    writes = deque()
                    cache_policy = proc.cache_policy or cache_policy
                    if cache_policy:
                        args_key = cache_policy.key_func(val)
@@ -652,11 +845,9 @@ def prepare_single_task(
                                name,
                            ),
                            xxh3_128_hexdigest(
-                                (
-                                    args_key.encode()
-                                    if isinstance(args_key, str)
-                                    else args_key
-                                ),
+                                args_key.encode()
+                                if isinstance(args_key, str)
+                                else args_key,
                            ),
                            cache_policy.ttl,
                        )
@@ -679,9 +870,7 @@ def prepare_single_task(
                        node,
                        writes,
                        patch_config(
-                            merge_configs(
-                                config, cast(RunnableConfig, additional_config)
-                            ),
+                            merge_configs(config, additional_config),
                            run_name=name,
                            callbacks=(
                                manager.get_child(f"graph:step:{step}")
@@ -730,297 +919,6 @@ def prepare_single_task(
                return PregelTask(task_id, name, task_path[:3])


-def prepare_push_task_functional(
-    task_path: tuple[str, tuple, int, str, Call],
-    # (PUSH, parent task path, idx of PUSH write, id of parent task, Call)
-    task_id_checksum: str | None,
-    *,
-    checkpoint: Checkpoint,
-    checkpoint_id_bytes: bytes,
-    pending_writes: list[PendingWrite],
-    channels: Mapping[str, BaseChannel],
-    managed: ManagedValueMapping,
-    config: RunnableConfig,
-    step: int,
-    stop: int,
-    for_execution: bool,
-    store: BaseStore | None = None,
-    checkpointer: BaseCheckpointSaver | None = None,
-    manager: None | ParentRunManager | AsyncParentRunManager = None,
-    cache_policy: CachePolicy | None = None,
-    retry_policy: Sequence[RetryPolicy] = (),
-    parent_ns: str,
-    # namespace: bytes, *parts: str | bytes
-    task_id_func: _TaskIDFn,
-) -> PregelTask | PregelExecutableTask:
-    """Prepare a push task with an attached caller. Used for the functional API."""
-    configurable = config.get(CONF, {})
-
-    call = task_path[-1]
-    proc_ = get_runnable_for_task(call.func)
-    name = proc_.name
-    if name is None:
-        raise ValueError("`call` functions must have a `__name__` attribute")
-    # create task id
-    triggers: Sequence[str] = PUSH_TRIGGER
-    checkpoint_ns = f"{parent_ns}{NS_SEP}{name}" if parent_ns else name
-    task_id = task_id_func(
-        checkpoint_id_bytes,
-        checkpoint_ns,
-        str(step),
-        name,
-        PUSH,
-        task_path_str(task_path[1]),
-        str(task_path[2]),
-    )
-    task_checkpoint_ns = f"{checkpoint_ns}:{task_id}"
-    # we append True to the task path to indicate that a call is being
-    # made, so we should not return interrupts from this task (responsibility lies with the parent)
-    in_progress_task_path = (*task_path[:3], True)
-    metadata = {
-        "langgraph_step": step,
-        "langgraph_node": name,
-        "langgraph_triggers": triggers,
-        "langgraph_path": in_progress_task_path,
-        "langgraph_checkpoint_ns": task_checkpoint_ns,
-    }
-    if task_id_checksum is not None:
-        assert task_id == task_id_checksum, f"{task_id} != {task_id_checksum}"
-    if for_execution:
-        writes: deque[tuple[str, Any]] = deque()
-        cache_policy = call.cache_policy or cache_policy
-        if cache_policy:
-            args_key = cache_policy.key_func(*call.input[0], **call.input[1])
-            cache_key: CacheKey | None = CacheKey(
-                (
-                    CACHE_NS_WRITES,
-                    (identifier(call.func) or "__dynamic__"),
-                ),
-                xxh3_128_hexdigest(
-                    args_key.encode() if isinstance(args_key, str) else args_key,
-                ),
-                cache_policy.ttl,
-            )
-        else:
-            cache_key = None
-        scratchpad = _scratchpad(
-            configurable.get(CONFIG_KEY_SCRATCHPAD),
-            pending_writes,
-            task_id,
-            xxh3_128_hexdigest(task_checkpoint_ns.encode()),
-            configurable.get(CONFIG_KEY_RESUME_MAP),
-            step,
-            stop,
-        )
-        runtime = cast(Runtime, configurable.get(CONFIG_KEY_RUNTIME, DEFAULT_RUNTIME))
-        runtime = runtime.override(store=store)
-        return PregelExecutableTask(
-            name,
-            call.input,
-            proc_,
-            writes,
-            patch_config(
-                merge_configs(config, {"metadata": metadata}),
-                run_name=name,
-                callbacks=call.callbacks
-                or (manager.get_child(f"graph:step:{step}") if manager else None),
-                configurable={
-                    CONFIG_KEY_TASK_ID: task_id,
-                    # deque.extend is thread-safe
-                    CONFIG_KEY_SEND: writes.extend,
-                    CONFIG_KEY_READ: partial(
-                        local_read,
-                        scratchpad,
-                        channels,
-                        managed,
-                        PregelTaskWrites(in_progress_task_path, name, writes, triggers),
-                    ),
-                    CONFIG_KEY_CHECKPOINTER: (
-                        checkpointer or configurable.get(CONFIG_KEY_CHECKPOINTER)
-                    ),
-                    CONFIG_KEY_CHECKPOINT_MAP: {
-                        **configurable.get(CONFIG_KEY_CHECKPOINT_MAP, {}),
-                        parent_ns: checkpoint["id"],
-                    },
-                    CONFIG_KEY_CHECKPOINT_ID: None,
-                    CONFIG_KEY_CHECKPOINT_NS: task_checkpoint_ns,
-                    CONFIG_KEY_SCRATCHPAD: scratchpad,
-                    CONFIG_KEY_RUNTIME: runtime,
-                },
-            ),
-            triggers,
-            call.retry_policy or retry_policy,
-            cache_key,
-            task_id,
-            in_progress_task_path,
-        )
-    else:
-        return PregelTask(task_id, name, in_progress_task_path)
-
-
-def prepare_push_task_send(
-    task_path: tuple[str, tuple],
-    # (PUSH, parent task path)
-    task_id_checksum: str | None,
-    *,
-    checkpoint: Checkpoint,
-    checkpoint_id_bytes: bytes,
-    pending_writes: list[PendingWrite],
-    channels: Mapping[str, BaseChannel],
-    managed: ManagedValueMapping,
-    config: RunnableConfig,
-    step: int,
-    stop: int,
-    for_execution: bool,
-    store: BaseStore | None = None,
-    checkpointer: BaseCheckpointSaver | None = None,
-    manager: None | ParentRunManager | AsyncParentRunManager = None,
-    cache_policy: CachePolicy | None = None,
-    retry_policy: Sequence[RetryPolicy] = (),
-    parent_ns: str,
-    task_id_func: _TaskIDFn,
-    processes: Mapping[str, PregelNode],
-) -> PregelTask | PregelExecutableTask | None:
-    if len(task_path) == 2:
-        # SEND tasks, executed in superstep n+1
-        # (PUSH, idx of pending send)
-        idx = cast(int, task_path[1])
-        if not channels[TASKS].is_available():
-            return
-        sends: Sequence[Send] = channels[TASKS].get()
-        if idx < 0 or idx >= len(sends):
-            return
-        packet = sends[idx]
-        if not isinstance(packet, Send):
-            logger.warning(
-                f"Ignoring invalid packet type {type(packet)} in pending sends"
-            )
-            return
-
-        if packet.node not in processes:
-            logger.warning(f"Ignoring unknown node name {packet.node} in pending sends")
-            return
-        # find process
-        proc = processes[packet.node]
-        proc_node = proc.node
-        if proc_node is None:
-            return
-        # create task id
-        triggers = PUSH_TRIGGER
-        checkpoint_ns = (
-            f"{parent_ns}{NS_SEP}{packet.node}" if parent_ns else packet.node
-        )
-        task_id = task_id_func(
-            checkpoint_id_bytes,
-            checkpoint_ns,
-            str(step),
-            packet.node,
-            PUSH,
-            str(idx),
-        )
-    else:
-        logger.warning(f"Ignoring invalid PUSH task path {task_path}")
-        return
-    configurable = config.get(CONF, {})
-    task_checkpoint_ns = f"{checkpoint_ns}:{task_id}"
-    # we append False to the task path to indicate that a call is not being made
-    # so we should return interrupts from this task
-    translated_task_path = (*task_path[:3], False)
-    metadata = {
-        "langgraph_step": step,
-        "langgraph_node": packet.node,
-        "langgraph_triggers": triggers,
-        "langgraph_path": translated_task_path,
-        "langgraph_checkpoint_ns": task_checkpoint_ns,
-    }
-    if task_id_checksum is not None:
-        assert task_id == task_id_checksum, f"{task_id} != {task_id_checksum}"
-    if for_execution:
-        if proc.metadata:
-            metadata.update(proc.metadata)
-        writes: deque[tuple[str, Any]] = deque()
-        cache_policy = proc.cache_policy or cache_policy
-        if cache_policy:
-            args_key = cache_policy.key_func(packet.arg)
-            cache_key = CacheKey(
-                (
-                    CACHE_NS_WRITES,
-                    (identifier(proc) or "__dynamic__"),
-                    packet.node,
-                ),
-                xxh3_128_hexdigest(
-                    args_key.encode() if isinstance(args_key, str) else args_key,
-                ),
-                cache_policy.ttl,
-            )
-        else:
-            cache_key = None
-        scratchpad = _scratchpad(
-            config[CONF].get(CONFIG_KEY_SCRATCHPAD),
-            pending_writes,
-            task_id,
-            xxh3_128_hexdigest(task_checkpoint_ns.encode()),
-            config[CONF].get(CONFIG_KEY_RESUME_MAP),
-            step,
-            stop,
-        )
-        runtime = cast(Runtime, configurable.get(CONFIG_KEY_RUNTIME, DEFAULT_RUNTIME))
-        runtime = runtime.override(
-            store=store, previous=checkpoint["channel_values"].get(PREVIOUS, None)
-        )
-        additional_config: RunnableConfig = {
-            "metadata": metadata,
-            "tags": proc.tags,
-        }
-        return PregelExecutableTask(
-            packet.node,
-            packet.arg,
-            proc_node,
-            writes,
-            patch_config(
-                merge_configs(config, additional_config),
-                run_name=packet.node,
-                callbacks=(
-                    manager.get_child(f"graph:step:{step}") if manager else None
-                ),
-                configurable={
-                    CONFIG_KEY_TASK_ID: task_id,
-                    # deque.extend is thread-safe
-                    CONFIG_KEY_SEND: writes.extend,
-                    CONFIG_KEY_READ: partial(
-                        local_read,
-                        scratchpad,
-                        channels,
-                        managed,
-                        PregelTaskWrites(
-                            translated_task_path, packet.node, writes, triggers
-                        ),
-                    ),
-                    CONFIG_KEY_CHECKPOINTER: (
-                        checkpointer or configurable.get(CONFIG_KEY_CHECKPOINTER)
-                    ),
-                    CONFIG_KEY_CHECKPOINT_MAP: {
-                        **configurable.get(CONFIG_KEY_CHECKPOINT_MAP, {}),
-                        parent_ns: checkpoint["id"],
-                    },
-                    CONFIG_KEY_CHECKPOINT_ID: None,
-                    CONFIG_KEY_CHECKPOINT_NS: task_checkpoint_ns,
-                    CONFIG_KEY_SCRATCHPAD: scratchpad,
-                    CONFIG_KEY_RUNTIME: runtime,
-                },
-            ),
-            triggers,
-            proc.retry_policy or retry_policy,
-            cache_key,
-            task_id,
-            translated_task_path,
-            writers=proc.flat_writers,
-            subgraphs=proc.subgraphs,
-        )
-    else:
-        return PregelTask(task_id, packet.node, translated_task_path)
-
-
 def checkpoint_null_version(
    checkpoint: Checkpoint,
 ) -> V | None:
@@ -459,6 +459,9 @@ class PregelLoop:
    def tick(self) -> bool:
        """Execute a single iteration of the Pregel loop.

+        Args:
+            input_keys: The key(s) to read input from.
+
        Returns:
            True if more iterations are needed.
        """
@@ -766,7 +769,6 @@ class PregelLoop:
            ]
            self.checkpoint["channel_values"][TASKS] = sanitized_tasks
        # bail if no checkpointer
-
        if do_checkpoint and self._checkpointer_put_after_previous is not None:
            self.prev_checkpoint_config = (
                self.checkpoint_config
@@ -936,15 +938,8 @@ class PregelLoop:
                stream_modes = self.stream.modes if self.stream else []
                if "updates" in stream_modes:
                    self._emit("updates", lambda: iter(interrupts))
-                if "values" in stream_modes:
-                    current_values = read_channels(self.channels, self.output_keys)
-                    # self.output_keys is a sequence, stream chunk contains entire state and interrupts
-                    if isinstance(current_values, dict):
-                        current_values[INTERRUPT] = interrupts[0][INTERRUPT]
-                        self._emit("values", lambda: iter([current_values]))
-                    # self.output_keys is a string, stream chunk contains only interrupts
-                    else:
-                        self._emit("values", lambda: iter(interrupts))
+                elif "values" in stream_modes:
+                    self._emit("values", lambda: iter(interrupts))
            elif writes[0][0] != ERROR:
                self._emit(
                    "updates",
@@ -1702,9 +1702,7 @@ class Pregel(
            # we use the task id generated by prepare_next_tasks
            node_to_task_ids: dict[str, deque[str]] = defaultdict(deque)
            if saved is not None and saved.pending_writes is not None:
-                # we call prepare_next_tasks to discover the task IDs that
-                # would have been generated, so we can reuse them and
-                # properly populate task.result in state history
+                # tasks for this checkpoint
                next_tasks = prepare_next_tasks(
                    checkpoint,
                    saved.pending_writes,
@@ -1723,6 +1721,32 @@ class Pregel(
                for t in next_tasks.values():
                    node_to_task_ids[t.name].append(t.id)

+                # apply null writes
+                if null_writes := [
+                    w[1:] for w in saved.pending_writes or [] if w[0] == NULL_TASK_ID
+                ]:
+                    apply_writes(
+                        checkpoint,
+                        channels,
+                        [PregelTaskWrites((), INPUT, null_writes, [])],
+                        checkpointer.get_next_version,
+                        self.trigger_to_nodes,
+                    )
+                # apply writes
+                for tid, k, v in saved.pending_writes:
+                    if k in (ERROR, INTERRUPT):
+                        continue
+                    if tid not in next_tasks:
+                        continue
+                    next_tasks[tid].writes.append((k, v))
+                if tasks := [t for t in next_tasks.values() if t.writes]:
+                    apply_writes(
+                        checkpoint,
+                        channels,
+                        tasks,
+                        checkpointer.get_next_version,
+                        self.trigger_to_nodes,
+                    )
            valid_updates: list[tuple[str, dict[str, Any] | None, str | None]] = []
            if len(updates) == 1:
                values, as_node, task_id = updates[0]
@@ -2143,9 +2167,7 @@ class Pregel(
            # we use the task id generated by prepare_next_tasks
            node_to_task_ids: dict[str, deque[str]] = defaultdict(deque)
            if saved is not None and saved.pending_writes is not None:
-                # we call prepare_next_tasks to discover the task IDs that
-                # would have been generated, so we can reuse them and
-                # properly populate task.result in state history
+                # tasks for this checkpoint
                next_tasks = prepare_next_tasks(
                    checkpoint,
                    saved.pending_writes,
@@ -2164,6 +2186,31 @@ class Pregel(
                for t in next_tasks.values():
                    node_to_task_ids[t.name].append(t.id)

+                # apply null writes
+                if null_writes := [
+                    w[1:] for w in saved.pending_writes or [] if w[0] == NULL_TASK_ID
+                ]:
+                    apply_writes(
+                        checkpoint,
+                        channels,
+                        [PregelTaskWrites((), INPUT, null_writes, [])],
+                        checkpointer.get_next_version,
+                        self.trigger_to_nodes,
+                    )
+                for tid, k, v in saved.pending_writes:
+                    if k in (ERROR, INTERRUPT):
+                        continue
+                    if tid not in next_tasks:
+                        continue
+                    next_tasks[tid].writes.append((k, v))
+                if tasks := [t for t in next_tasks.values() if t.writes]:
+                    apply_writes(
+                        checkpoint,
+                        channels,
+                        tasks,
+                        checkpointer.get_next_version,
+                        self.trigger_to_nodes,
+                    )
            valid_updates: list[tuple[str, dict[str, Any] | None, str | None]] = []
            if len(updates) == 1:
                values, as_node, task_id = updates[0]
@@ -2354,7 +2401,7 @@ class Pregel(
            validate_keys(output_keys, self.channels)
        interrupt_before = interrupt_before or self.interrupt_before_nodes
        interrupt_after = interrupt_after or self.interrupt_after_nodes
-        if isinstance(stream_mode, str):
+        if not isinstance(stream_mode, list):
            stream_modes = {stream_mode}
        else:
            stream_modes = set(stream_mode)
@@ -2431,12 +2478,11 @@ class Pregel(
                    Will be emitted as 2-tuples `(LLM token, metadata)`.
                - `"checkpoints"`: Emit an event when a checkpoint is created, in the same format as returned by `get_state()`.
                - `"tasks"`: Emit events when tasks start and finish, including their results and errors.
-                - `"debug"`: Emit debug events with as much information as possible for each step.

                You can pass a list as the `stream_mode` parameter to stream multiple modes at once.
                The streamed outputs will be tuples of `(mode, data)`.

-                See [LangGraph streaming guide](https://docs.langchain.com/oss/python/langgraph/streaming) for more details.
+                See [LangGraph streaming guide](https://langchain-ai.github.io/langgraph/how-tos/streaming/) for more details.
            print_mode: Accepts the same values as `stream_mode`, but only prints the output to the console, for debugging purposes. Does not affect the output of the graph in any way.
            output_keys: The keys to stream, defaults to all non-context channels.
            interrupt_before: Nodes to interrupt before, defaults to all nodes in the graph.
@@ -2453,7 +2499,7 @@ class Pregel(
                where `namespace` is a tuple with the path to the node where a subgraph is invoked,
                e.g. `("parent_node:<task_id>", "child_node:<task_id>")`.

-                See [LangGraph streaming guide](https://docs.langchain.com/oss/python/langgraph/streaming) for more details.
+                See [LangGraph streaming guide](https://langchain-ai.github.io/langgraph/how-tos/streaming/) for more details.

        Yields:
            The output of each step in the graph. The output shape depends on the `stream_mode`.
@@ -2698,14 +2744,12 @@ class Pregel(
                - `"custom"`: Emit custom data from inside nodes or tasks using `StreamWriter`.
                - `"messages"`: Emit LLM messages token-by-token together with metadata for any LLM invocations inside nodes or tasks.
                    Will be emitted as 2-tuples `(LLM token, metadata)`.
-                - `"checkpoints"`: Emit an event when a checkpoint is created, in the same format as returned by `get_state()`.
-                - `"tasks"`: Emit events when tasks start and finish, including their results and errors.
                - `"debug"`: Emit debug events with as much information as possible for each step.

                You can pass a list as the `stream_mode` parameter to stream multiple modes at once.
                The streamed outputs will be tuples of `(mode, data)`.

-                See [LangGraph streaming guide](https://docs.langchain.com/oss/python/langgraph/streaming) for more details.
+                See [LangGraph streaming guide](https://langchain-ai.github.io/langgraph/how-tos/streaming/) for more details.
            print_mode: Accepts the same values as `stream_mode`, but only prints the output to the console, for debugging purposes. Does not affect the output of the graph in any way.
            output_keys: The keys to stream, defaults to all non-context channels.
            interrupt_before: Nodes to interrupt before, defaults to all nodes in the graph.
@@ -2722,7 +2766,7 @@ class Pregel(
                where `namespace` is a tuple with the path to the node where a subgraph is invoked,
                e.g. `("parent_node:<task_id>", "child_node:<task_id>")`.

-                See [LangGraph streaming guide](https://docs.langchain.com/oss/python/langgraph/streaming) for more details.
+                See [LangGraph streaming guide](https://langchain-ai.github.io/langgraph/how-tos/streaming/) for more details.

        Yields:
            The output of each step in the graph. The output shape depends on the `stream_mode`.
@@ -3104,30 +3148,31 @@ class Pregel(
        durability: Durability | None = None,
        **kwargs: Any,
    ) -> dict[str, Any] | Any:
-        """Asynchronously run the graph with a single input and config.
+        """Asynchronously invoke the graph on a single input.

        Args:
-            input: The input data for the graph. It can be a dictionary or any other type.
-            config: The configuration for the graph run.
+            input: The input data for the computation. It can be a dictionary or any other type.
+            config: The configuration for the computation.
            context: The static context to use for the run.
                !!! version-added "Added in version 0.6.0"
-            stream_mode: The stream mode for the graph run.
+            stream_mode: The stream mode for the computation.
            print_mode: Accepts the same values as `stream_mode`, but only prints the output to the console, for debugging purposes. Does not affect the output of the graph in any way.
-            output_keys: The output keys to retrieve from the graph run.
-            interrupt_before: The nodes to interrupt the graph run before.
-            interrupt_after: The nodes to interrupt the graph run after.
+            output_keys: The output keys to include in the result.
+            interrupt_before: The nodes to interrupt before.
+            interrupt_after: The nodes to interrupt after.
            durability: The durability mode for the graph execution, defaults to `"async"`.
                Options are:

                - `"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.
-            **kwargs: Additional keyword arguments to pass to the graph run.
+            **kwargs: Additional keyword arguments.

        Returns:
-            The output of the graph run. If `stream_mode` is `"values"`, it returns the latest output.
-            If `stream_mode` is not `"values"`, it returns a list of output chunks.
+            The result of the computation. If `stream_mode` is `"values"`, it returns the latest value.
+            If `stream_mode` is `"chunks"`, it returns a list of chunks.
        """
+
        output_keys = output_keys if output_keys is not None else self.output_channels

        latest: dict[str, Any] | Any = None
@@ -111,7 +111,7 @@ class Runtime(Generic[ContextT]):
            stream_writer=other.stream_writer
            if other.stream_writer is not _no_op_stream_writer
            else self.stream_writer,
-            previous=self.previous if other.previous is None else other.previous,
+            previous=other.previous or self.previous,
        )

    def override(
@@ -55,7 +55,6 @@ __all__ = (
    "Command",
    "Durability",
    "interrupt",
-    "Overwrite",
 )

 Durability = Literal["sync", "async", "exit"]
@@ -284,32 +283,26 @@ class Send:
        node (str): The name of the target node to send the message to.
        arg (Any): The state or message to send to the target node.

-    !!! example
-
-        ```python
-        from typing import Annotated
-        from langgraph.types import Send
-        from langgraph.graph import END, START
-        from langgraph.graph import StateGraph
-        import operator
-
-        class OverallState(TypedDict):
-            subjects: list[str]
-            jokes: Annotated[list[str], operator.add]
-
-        def continue_to_jokes(state: OverallState):
-            return [Send("generate_joke", {"subject": s}) for s in state["subjects"]]
-
-        builder = StateGraph(OverallState)
-        builder.add_node("generate_joke", lambda state: {"jokes": [f"Joke about {state['subject']}"]})
-        builder.add_conditional_edges(START, continue_to_jokes)
-        builder.add_edge("generate_joke", END)
-        graph = builder.compile()
-
-        # Invoking with two subjects results in a generated joke for each
-        graph.invoke({"subjects": ["cats", "dogs"]})
-        # {'subjects': ['cats', 'dogs'], 'jokes': ['Joke about cats', 'Joke about dogs']}
-        ```
+    Examples:
+        >>> from typing import Annotated
+        >>> import operator
+        >>> class OverallState(TypedDict):
+        ...     subjects: list[str]
+        ...     jokes: Annotated[list[str], operator.add]
+        >>> from langgraph.types import Send
+        >>> from langgraph.graph import END, START
+        >>> def continue_to_jokes(state: OverallState):
+        ...     return [Send("generate_joke", {"subject": s}) for s in state["subjects"]]
+        >>> from langgraph.graph import StateGraph
+        >>> builder = StateGraph(OverallState)
+        >>> builder.add_node("generate_joke", lambda state: {"jokes": [f"Joke about {state['subject']}"]})
+        >>> builder.add_conditional_edges(START, continue_to_jokes)
+        >>> builder.add_edge("generate_joke", END)
+        >>> graph = builder.compile()
+        >>>
+        >>> # Invoking with two subjects results in a generated joke for each
+        >>> graph.invoke({"subjects": ["cats", "dogs"]})
+        {'subjects': ['cats', 'dogs'], 'jokes': ['Joke about cats', 'Joke about dogs']}
    """

    __slots__ = ("node", "arg")
@@ -349,8 +342,10 @@ N = TypeVar("N", bound=Hashable)
 class Command(Generic[N], ToolOutputMixin):
    """One or more commands to update the graph's state and send messages to nodes.

+    !!! version-added "Added in version 0.2.24"
+
    Args:
-        graph: Graph to send the command to. Supported values are:
+        graph: graph to send the command to. Supported values are:

            - `None`: the current graph
            - `Command.PARENT`: closest parent graph
@@ -420,8 +415,7 @@ def interrupt(value: Any) -> Any:
    To use an `interrupt`, you must enable a checkpointer, as the feature relies
    on persisting the graph state.

-    !!! example
-
+    Example:
        ```python
        import uuid
        from typing import Optional
@@ -526,42 +520,38 @@ def interrupt(value: Any) -> Any:

@dataclass(slots=True)
 class Overwrite:
-    """Bypass a reducer and write the wrapped value directly to a `BinaryOperatorAggregate` channel.
+    """Bypass a reducer and write the wrapped value directly to a BinaryOperatorAggregate channel.

-    Receiving multiple `Overwrite` values for the same channel in a single super-step
-    will raise an `InvalidUpdateError`.
+    Receiving multiple Overwrite values for the same channel in a single super-step will raise an InvalidUpdateError.

-    !!! example
-
-        ```python
-        from typing import Annotated
-        import operator
-        from langgraph.graph import StateGraph
-        from langgraph.types import Overwrite
-
-        class State(TypedDict):
-            messages: Annotated[list, operator.add]
-
-        def node_a(state: TypedDict):
-            # Normal update: uses the reducer (operator.add)
-            return {"messages": ["a"]}
-
-        def node_b(state: State):
-            # Overwrite: bypasses the reducer and replaces the entire value
-            return {"messages": Overwrite(value=["b"])}
-
-        builder = StateGraph(State)
-        builder.add_node("node_a", node_a)
-        builder.add_node("node_b", node_b)
-        builder.set_entry_point("node_a")
-        builder.add_edge("node_a", "node_b")
-        graph = builder.compile()
-
-        # Without Overwrite in node_b, messages would be ["START", "a", "b"]
-        # With Overwrite, messages is just ["b"]
-        result = graph.invoke({"messages": ["START"]})
-        assert result == {"messages": ["b"]}
-        ```
+    Example:
+        >>> from typing import Annotated
+        >>> import operator
+        >>> from langgraph.graph import StateGraph
+        >>> from langgraph.types import Overwrite
+        >>>
+        >>> class State(TypedDict):
+        ...     messages: Annotated[list, operator.add]
+        >>>
+        >>> def node_a(state: TypedDict):
+        ...     # Normal update: uses the reducer (operator.add)
+        ...     return {"messages": ["a"]}
+        >>>
+        >>> def node_b(state: State):
+        ...     # Overwrite: bypasses the reducer and replaces the entire value
+        ...     return {"messages": Overwrite(value=["b"])}
+        >>>
+        >>> builder = StateGraph(State)
+        >>> builder.add_node("node_a", node_a)
+        >>> builder.add_node("node_b", node_b)
+        >>> builder.set_entry_point("node_a")
+        >>> builder.add_edge("node_a", "node_b")
+        >>> graph = builder.compile()
+        >>>
+        >>> # Without Overwrite in node_b, messages would be ["START", "a", "b"]
+        >>> # With Overwrite, messages is just ["b"]
+        >>> result = graph.invoke({"messages": ["START"]})
+        >>> assert result == {"messages": ["b"]}
    """

    value: Any
@@ -31,13 +31,13 @@ ContextT_contra = TypeVar(
 )

 InputT = TypeVar("InputT", bound=StateLike, default=StateT)
-"""Type variable used to represent the input to a `StateGraph`.
+"""Type variable used to represent the input to a state graph.

 Defaults to `StateT`.
 """

 OutputT = TypeVar("OutputT", bound=StateLike, default=StateT)
-"""Type variable used to represent the output of a `StateGraph`.
+"""Type variable used to represent the output of a state graph.

 Defaults to `StateT`.
 """
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"

 [project]
 name = "langgraph"
-version = "1.0.3"
+version = "1.0.2"
 description = "Building stateful, multi-actor applications with LLMs"
 authors = []
 requires-python = ">=3.10"
@@ -32,15 +32,8 @@ dependencies = [
    "pydantic>=2.7.4",
 ]

-
 [project.urls]
-Homepage = "https://docs.langchain.com/oss/python/langgraph/overview"
-Documentation = "https://reference.langchain.com/python/langgraph/"
-Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/langgraph"
-Changelog = "https://github.com/langchain-ai/langgraph/releases"
-Twitter = "https://x.com/LangChainAI"
-Slack = "https://www.langchain.com/join-community"
-Reddit = "https://www.reddit.com/r/LangChain/"
+Repository = "https://www.github.com/langchain-ai/langgraph"

 [dependency-groups]
 test = [
@@ -8422,55 +8422,23 @@ def test_null_resume_disallowed_with_multiple_interrupts(
    }


-def test_interrupt_stream_mode_values(sync_checkpointer: BaseCheckpointSaver):
-    """Test that interrupts are surfaced on 'values' stream mode"""
+def test_interrupt_stream_mode_values():
+    """Test that interrupts are surfaced when steam_mode='values'"""

    class State(TypedDict):
-        robot_input: str
        human_input: str

-    def robot_input_node(state: State) -> State:
-        return {"robot_input": "beep boop i am a robot"}
-
    def human_input_node(state: State) -> Command:
        human_input = interrupt("interrupt")
        return Command(update={"human_input": human_input})

    builder = StateGraph(State)
-    builder.add_node(robot_input_node)
    builder.add_node(human_input_node)
-    builder.add_edge(START, "robot_input_node")
-    builder.add_edge("robot_input_node", "human_input_node")
-    app = builder.compile(checkpointer=sync_checkpointer)
-    config = {"configurable": {"thread_id": str(uuid.uuid4())}}
+    builder.add_edge(START, "human_input_node")
+    app = builder.compile()

-    result = [*app.stream(State(), config, stream_mode=["updates", "values"])]
-    assert len(result) == 4
-    assert result == [
-        ("updates", {"robot_input_node": {"robot_input": "beep boop i am a robot"}}),
-        ("values", {"robot_input": "beep boop i am a robot"}),
-        ("updates", {"__interrupt__": (Interrupt(value="interrupt", id=AnyStr()),)}),
-        (
-            "values",
-            {
-                "robot_input": "beep boop i am a robot",
-                "__interrupt__": (Interrupt(value="interrupt", id=AnyStr()),),
-            },
-        ),
-    ]
-    resume_result = [
-        *app.stream(
-            Command(resume="i am a human"), config, stream_mode=["updates", "values"]
-        )
-    ]
-    assert resume_result == [
-        ("values", {"robot_input": "beep boop i am a robot"}),
-        ("updates", {"human_input_node": {"human_input": "i am a human"}}),
-        (
-            "values",
-            {"robot_input": "beep boop i am a robot", "human_input": "i am a human"},
-        ),
-    ]
+    result = [*app.stream(State(), stream_mode="values")]
+    assert "__interrupt__" in result[-1]


 def test_supersteps_populate_task_results(
@@ -8837,43 +8805,3 @@ def test_overwrite_parallel_error(
        InvalidUpdateError, match="Can receive only one Overwrite value per super-step."
    ):
        graph.invoke({"messages": ["START"]}, config)
-
-
-def test_fork_does_not_apply_pending_writes(
-    sync_checkpointer: BaseCheckpointSaver,
-) -> None:
-    """Test that forking with update_state does not apply pending writes from original execution."""
-
-    class State(TypedDict):
-        value: Annotated[int, operator.add]
-
-    def node_a(state: State) -> State:
-        return {"value": 10}
-
-    def node_b(state: State) -> State:
-        return {"value": 100}
-
-    graph = (
-        StateGraph(State)
-        .add_node("node_a", node_a)
-        .add_node("node_b", node_b)
-        .add_edge(START, "node_a")
-        .add_edge("node_a", "node_b")
-        .compile(checkpointer=sync_checkpointer)
-    )
-
-    thread1 = {"configurable": {"thread_id": "1"}}
-    graph.invoke({"value": 1}, thread1)
-
-    history = list(graph.get_state_history(thread1))
-    checkpoint_before_a = next(s for s in history if s.next == ("node_a",))
-
-    fork_config = graph.update_state(
-        checkpoint_before_a.config, {"value": 20}, as_node="node_a"
-    )
-
-    # Continue from fork (should run node_b)
-    result = graph.invoke(None, fork_config)
-
-    # Should be: 1 (input) + 20 (forked node_a) + 100 (node_b) = 121
-    assert result == {"value": 121}
@@ -9196,64 +9196,6 @@ async def test_astream_waiter_cleanup_on_cancel(
    assert all(t.done() for t in recorded_tasks)


-@NEEDS_CONTEXTVARS
-async def test_interrupt_stream_mode_values(async_checkpointer: BaseCheckpointSaver):
-    """Test that interrupts are surfaced on 'values' stream mode"""
-
-    class State(TypedDict):
-        robot_input: str
-        human_input: str
-
-    def robot_input_node(state: State) -> State:
-        return {"robot_input": "beep boop i am a robot"}
-
-    def human_input_node(state: State) -> Command:
-        human_input = interrupt("interrupt")
-        return Command(update={"human_input": human_input})
-
-    builder = StateGraph(State)
-    builder.add_node(robot_input_node)
-    builder.add_node(human_input_node)
-    builder.add_edge(START, "robot_input_node")
-    builder.add_edge("robot_input_node", "human_input_node")
-    app = builder.compile(checkpointer=async_checkpointer)
-    config = {"configurable": {"thread_id": str(uuid.uuid4())}}
-
-    result = [
-        (mode, e)
-        async for mode, e in app.astream(
-            State(), config, stream_mode=["updates", "values"]
-        )
-    ]
-    assert len(result) == 4
-    assert result == [
-        ("updates", {"robot_input_node": {"robot_input": "beep boop i am a robot"}}),
-        ("values", {"robot_input": "beep boop i am a robot"}),
-        ("updates", {"__interrupt__": (Interrupt(value="interrupt", id=AnyStr()),)}),
-        (
-            "values",
-            {
-                "robot_input": "beep boop i am a robot",
-                "__interrupt__": (Interrupt(value="interrupt", id=AnyStr()),),
-            },
-        ),
-    ]
-    resume_result = [
-        (mode, e)
-        async for mode, e in app.astream(
-            Command(resume="i am a human"), config, stream_mode=["updates", "values"]
-        )
-    ]
-    assert resume_result == [
-        ("values", {"robot_input": "beep boop i am a robot"}),
-        ("updates", {"human_input_node": {"human_input": "i am a human"}}),
-        (
-            "values",
-            {"robot_input": "beep boop i am a robot", "human_input": "i am a human"},
-        ),
-    ]
-
-
 async def test_supersteps_populate_task_results(
    async_checkpointer: BaseCheckpointSaver,
 ) -> None:
@@ -9307,41 +9249,3 @@ async def test_supersteps_populate_task_results(

    assert bulk_start_result == ref_start_result == {"num": 1, "text": "one"}
    assert bulk_double_result == ref_double_result == {"num": 2, "text": "oneone"}
-
-
-async def test_fork_does_not_apply_pending_writes(
-    async_checkpointer: BaseCheckpointSaver,
-) -> None:
-    """Test that forking with aupdate_state does not apply pending writes from original execution."""
-
-    class State(TypedDict):
-        value: Annotated[int, operator.add]
-
-    def node_a(state: State) -> State:
-        return {"value": 10}
-
-    def node_b(state: State) -> State:
-        return {"value": 100}
-
-    graph = (
-        StateGraph(State)
-        .add_node("node_a", node_a)
-        .add_node("node_b", node_b)
-        .add_edge(START, "node_a")
-        .add_edge("node_a", "node_b")
-        .compile(checkpointer=async_checkpointer)
-    )
-
-    thread1 = {"configurable": {"thread_id": "1"}}
-    await graph.ainvoke({"value": 1}, thread1)
-
-    history = [c async for c in graph.aget_state_history(thread1)]
-    checkpoint_before_a = next(s for s in history if s.next == ("node_a",))
-
-    fork_config = await graph.aupdate_state(
-        checkpoint_before_a.config, {"value": 20}, as_node="node_a"
-    )
-    result = await graph.ainvoke(None, fork_config)
-
-    # 1 (input) + 20 (forked node_a) + 100 (node_b) = 121
-    assert result == {"value": 121}
@@ -1,5 +1,5 @@
 version = 1
-revision = 3
+revision = 2
 requires-python = ">=3.10"
 resolution-markers = [
    "python_full_version >= '3.14'",
@@ -1345,7 +1345,7 @@ wheels = [

 [[package]]
 name = "langgraph"
-version = "1.0.3"
+version = "1.0.2"
 source = { editable = "." }
 dependencies = [
    { name = "langchain-core" },
@@ -1524,7 +1524,7 @@ wheels = [

 [[package]]
 name = "langgraph-checkpoint"
-version = "3.0.1"
+version = "3.0.0"
 source = { editable = "../checkpoint" }
 dependencies = [
    { name = "langchain-core" },
@@ -1534,7 +1534,7 @@ dependencies = [
 [package.metadata]
 requires-dist = [
    { name = "langchain-core", specifier = ">=0.2.38" },
-    { name = "ormsgpack", specifier = ">=1.12.0" },
+    { name = "ormsgpack", specifier = ">=1.10.0" },
 ]

 [package.metadata.requires-dev]
@@ -1571,7 +1571,7 @@ test = [

 [[package]]
 name = "langgraph-checkpoint-postgres"
-version = "3.0.1"
+version = "3.0.0"
 source = { editable = "../checkpoint-postgres" }
 dependencies = [
    { name = "langgraph-checkpoint" },
@@ -1677,7 +1677,7 @@ inmem = [
 [package.metadata]
 requires-dist = [
    { name = "click", specifier = ">=8.1.7" },
-    { name = "langgraph-api", marker = "python_full_version >= '3.11' and extra == 'inmem'", specifier = ">=0.4,<0.6.0" },
+    { name = "langgraph-api", marker = "python_full_version >= '3.11' and extra == 'inmem'", specifier = ">=0.3,<0.5.0" },
    { name = "langgraph-runtime-inmem", marker = "python_full_version >= '3.11' and extra == 'inmem'", specifier = ">=0.7" },
    { name = "langgraph-sdk", marker = "python_full_version >= '3.11'", specifier = ">=0.1.0" },
    { name = "python-dotenv", marker = "extra == 'inmem'", specifier = ">=0.8.0" },
@@ -1710,7 +1710,7 @@ test = [

 [[package]]
 name = "langgraph-prebuilt"
-version = "1.0.5"
+version = "1.0.2"
 source = { editable = "../prebuilt" }
 dependencies = [
    { name = "langchain-core" },
@@ -1794,7 +1794,6 @@ requires-dist = [
 dev = [
    { name = "codespell" },
    { name = "mypy" },
-    { name = "pydantic", specifier = ">=2.12.4" },
    { name = "pytest" },
    { name = "pytest-asyncio" },
    { name = "pytest-mock" },
@@ -2256,57 +2255,57 @@ wheels = [

 [[package]]
 name = "ormsgpack"
-version = "1.12.0"
+version = "1.11.0"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/6c/67/d5ef41c3b4a94400be801984ef7c7fc9623e1a82b643e74eeec367e7462b/ormsgpack-1.12.0.tar.gz", hash = "sha256:94be818fdbb0285945839b88763b269987787cb2f7ef280cad5d6ec815b7e608", size = 49959, upload-time = "2025-11-04T18:30:10.083Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/65/f8/224c342c0e03e131aaa1a1f19aa2244e167001783a433f4eed10eedd834b/ormsgpack-1.11.0.tar.gz", hash = "sha256:7c9988e78fedba3292541eb3bb274fa63044ef4da2ddb47259ea70c05dee4206", size = 49357, upload-time = "2025-10-08T17:29:15.621Z" }
 wheels = [
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 ]

 [[package]]
@@ -1,21 +0,0 @@
-{
-  "permissions": {
-    "allow": [
-      "Bash(make test:*)",
-      "Bash(uv run pytest:*)",
-      "Bash(LANGGRAPH_TEST_FAST=0 make start-services:*)",
-      "Bash(LANGGRAPH_TEST_FAST=0 uv run:*)",
-      "Bash(EXIT_CODE=$?)",
-      "Bash(make stop-services:*)",
-      "Bash(exit $EXIT_CODE)",
-      "Read(//Users/sydney_runkle/oss/langgraph/**)",
-      "Bash(python3:*)",
-      "Bash(find:*)",
-      "Bash(python -m pytest:*)",
-      "Bash(python:*)",
-      "Read(//tmp/**)"
-    ],
-    "deny": [],
-    "ask": []
-  }
-}
@@ -63,7 +63,7 @@ class AgentState(TypedDict):


@deprecated(
-    "AgentStatePydantic has been deprecated in favor of AgentState in `langchain.agents`.",
+    "AgentStatePydantic has been moved to `langchain.agents`. Please update your import to `from langchain.agents import AgentStatePydantic`.",
    category=LangGraphDeprecatedSinceV10,
 )
 class AgentStatePydantic(BaseModel):
@@ -78,11 +78,11 @@ with warnings.catch_warnings():
    warnings.filterwarnings(
        "ignore",
        category=LangGraphDeprecatedSinceV10,
-        message="AgentState has been moved to `langchain.agents`.*",
+        message="AgentState has been moved to langchain.agents.*",
    )

    @deprecated(
-        "AgentStateWithStructuredResponse has been deprecated in favor of AgentState in `langchain.agents`.",
+        "AgentStateWithStructuredResponse has been moved to `langchain.agents`. Please update your import to `from langchain.agents import AgentStateWithStructuredResponse`.",
        category=LangGraphDeprecatedSinceV10,
    )
    class AgentStateWithStructuredResponse(AgentState):
@@ -95,11 +95,11 @@ with warnings.catch_warnings():
    warnings.filterwarnings(
        "ignore",
        category=LangGraphDeprecatedSinceV10,
-        message="AgentStatePydantic has been deprecated in favor of AgentState in `langchain.agents`.",
+        message="AgentStatePydantic has been moved to langchain.agents.*",
    )

    @deprecated(
-        "AgentStateWithStructuredResponsePydantic has been deprecated in favor of AgentState in `langchain.agents`.",
+        "AgentStateWithStructuredResponsePydantic has been moved to `langchain.agents`. Please update your import to `from langchain.agents import AgentStateWithStructuredResponsePydantic`.",
        category=LangGraphDeprecatedSinceV10,
    )
    class AgentStateWithStructuredResponsePydantic(AgentStatePydantic):
@@ -309,40 +309,37 @@ def create_react_agent(
        model: The language model for the agent. Supports static and dynamic
            model selection.

-            - **Static model**: A chat model instance (e.g.,
-                [`ChatOpenAI`][langchain_openai.ChatOpenAI]) or string identifier (e.g.,
-                `"openai:gpt-4"`)
+            - **Static model**: A chat model instance (e.g., `ChatOpenAI()`) or
+              string identifier (e.g., `"openai:gpt-4"`)
            - **Dynamic model**: A callable with signature
-                `(state, runtime) -> BaseChatModel` that returns different models
-                based on runtime context
-
-                If the model has tools bound via `bind_tools` or other configurations,
-                the return type should be a `Runnable[LanguageModelInput, BaseMessage]`
-                Coroutines are also supported, allowing for asynchronous model selection.
+              `(state, runtime) -> BaseChatModel` that returns different models
+              based on runtime context
+              If the model has tools bound via `.bind_tools()` or other configurations,
+              the return type should be a Runnable[LanguageModelInput, BaseMessage]
+              Coroutines are also supported, allowing for asynchronous model selection.

            Dynamic functions receive graph state and runtime, enabling
            context-dependent model selection. Must return a `BaseChatModel`
            instance. For tool calling, bind tools using `.bind_tools()`.
            Bound tools must be a subset of the `tools` parameter.

-            !!! example "Dynamic model"
+            Dynamic model example:
+            ```python
+            from dataclasses import dataclass

-                ```python
-                from dataclasses import dataclass
+            @dataclass
+            class ModelContext:
+                model_name: str = "gpt-3.5-turbo"

-                @dataclass
-                class ModelContext:
-                    model_name: str = "gpt-3.5-turbo"
+            # Instantiate models globally
+            gpt4_model = ChatOpenAI(model="gpt-4")
+            gpt35_model = ChatOpenAI(model="gpt-3.5-turbo")

-                # Instantiate models globally
-                gpt4_model = ChatOpenAI(model="gpt-4")
-                gpt35_model = ChatOpenAI(model="gpt-3.5-turbo")
-
-                def select_model(state: AgentState, runtime: Runtime[ModelContext]) -> ChatOpenAI:
-                    model_name = runtime.context.model_name
-                    model = gpt4_model if model_name == "gpt-4" else gpt35_model
-                    return model.bind_tools(tools)
-                ```
+            def select_model(state: AgentState, runtime: Runtime[ModelContext]) -> ChatOpenAI:
+                model_name = runtime.context.model_name
+                model = gpt4_model if model_name == "gpt-4" else gpt35_model
+                return model.bind_tools(tools)
+            ```

            !!! note "Dynamic Model Requirements"

@@ -354,26 +351,23 @@ def create_react_agent(
            If an empty list is provided, the agent will consist of a single LLM node without tool calling.
        prompt: An optional prompt for the LLM. Can take a few different forms:

-            - `str`: This is converted to a `SystemMessage` and added to the beginning of the list of messages in `state["messages"]`.
-            - `SystemMessage`: this is added to the beginning of the list of messages in `state["messages"]`.
-            - `Callable`: This function should take in full graph state and the output is then passed to the language model.
-            - `Runnable`: This runnable should take in full graph state and the output is then passed to the language model.
+            - str: This is converted to a SystemMessage and added to the beginning of the list of messages in state["messages"].
+            - SystemMessage: this is added to the beginning of the list of messages in state["messages"].
+            - Callable: This function should take in full graph state and the output is then passed to the language model.
+            - Runnable: This runnable should take in full graph state and the output is then passed to the language model.

        response_format: An optional schema for the final agent output.

            If provided, output will be formatted to match the given schema and returned in the 'structured_response' state key.
-
            If not provided, `structured_response` will not be present in the output state.
-
            Can be passed in as:

-            - An OpenAI function/tool schema,
-            - A JSON Schema,
-            - A TypedDict class,
-            - A Pydantic class.
-            - A tuple `(prompt, schema)`, where schema is one of the above.
-                The prompt will be used together with the model that is being used to
-                generate the structured response.
+                - an OpenAI function/tool schema,
+                - a JSON Schema,
+                - a TypedDict class,
+                - or a Pydantic class.
+                - a tuple (prompt, schema), where schema is one of the above.
+                    The prompt will be used together with the model that is being used to generate the structured response.

            !!! Important
                `response_format` requires the model to support `.with_structured_output`
@@ -434,16 +428,13 @@ def create_react_agent(
        store: An optional store object. This is used for persisting data
            across multiple threads (e.g., multiple conversations / users).
        interrupt_before: An optional list of node names to interrupt before.
-            Should be one of the following: `"agent"`, `"tools"`.
-
+            Should be one of the following: "agent", "tools".
            This is useful if you want to add a user confirmation or other interrupt before taking an action.
        interrupt_after: An optional list of node names to interrupt after.
-            Should be one of the following: `"agent"`, `"tools"`.
-
+            Should be one of the following: "agent", "tools".
            This is useful if you want to return directly or run additional processing on an output.
        debug: A flag indicating whether to enable debug mode.
        version: Determines the version of the graph to create.
-
            Can be one of:

            - `"v1"`: The tool node processes a single message. All tool
@@ -452,7 +443,7 @@ def create_react_agent(
                Tool calls are distributed across multiple instances of the tool
                node using the [Send](https://langchain-ai.github.io/langgraph/concepts/low_level/#send)
                API.
-        name: An optional name for the `CompiledStateGraph`.
+        name: An optional name for the CompiledStateGraph.
            This name will be automatically used when adding ReAct agent graph to another graph as a subgraph node -
            particularly useful for building multi-agent systems.

@@ -462,14 +453,14 @@ def create_react_agent(


    Returns:
-        A compiled LangChain `Runnable` that can be used for chat interactions.
+        A compiled LangChain runnable that can be used for chat interactions.

    The "agent" node calls the language model with the messages list (after applying the prompt).
    If the resulting AIMessage contains `tool_calls`, the graph will then call the ["tools"][langgraph.prebuilt.tool_node.ToolNode].
    The "tools" node executes the tools (1 tool per `tool_call`) and adds the responses to the messages list
    as `ToolMessage` objects. The agent node then calls the language model again.
    The process repeats until no more `tool_calls` are present in the response.
-    The agent then returns the full list of messages as a dictionary containing the key `'messages'`.
+    The agent then returns the full list of messages as a dictionary containing the key "messages".

    ``` mermaid
        sequenceDiagram
@@ -36,7 +36,7 @@ class ActionRequest(TypedDict):
    Contains the action type and any associated arguments needed for the action.

    Attributes:
-        action: The type or name of action being requested (e.g., `"Approve XYZ action"`)
+        action: The type or name of action being requested (e.g., "Approve XYZ action")
        args: Key-value pairs of arguments needed for the action
    """

@@ -89,16 +89,14 @@ class HumanResponse(TypedDict):

    Attributes:
        type: The type of response:
-
-            - `'accept'`: Approves the current state without changes
-            - `'ignore'`: Skips/ignores the current step
-            - `'response'`: Provides text feedback or instructions
-            - `'edit'`: Modifies the current state/content
+            - "accept": Approves the current state without changes
+            - "ignore": Skips/ignores the current step
+            - "response": Provides text feedback or instructions
+            - "edit": Modifies the current state/content
        args: The response payload:
-
-            - `None`: For ignore/accept actions
-            - `str`: For text responses
-            - `ActionRequest`: For edit actions with updated content
+            - None: For ignore/accept actions
+            - str: For text responses
+            - ActionRequest: For edit actions with updated content
    """

    type: Literal["accept", "ignore", "response", "edit"]
@@ -6,7 +6,6 @@ Tools are functions that models can call to interact with external systems,
 APIs, databases, or perform computations.

 The module implements design patterns for:
-
 - Parallel execution of multiple tool calls for efficiency
 - Robust error handling with customizable error messages
 - State injection for tools that need access to graph state
@@ -14,13 +13,11 @@ The module implements design patterns for:
 - Command-based state updates for advanced control flow

 Key Components:
-
- `ToolNode`: Main class for executing tools in LangGraph workflows
- `InjectedState`: Annotation for injecting graph state into tools
- `InjectedStore`: Annotation for injecting persistent store into tools
- `ToolRuntime`: Runtime information for tools, bundling together `state`, `context`,
-    `config`, `stream_writer`, `tool_call_id`, and `store`
- `tools_condition`: Utility function for conditional routing based on tool calls
+    `ToolNode`: Main class for executing tools in LangGraph workflows
+    `InjectedState`: Annotation for injecting graph state into tools
+    `InjectedStore`: Annotation for injecting persistent store into tools
+    `ToolRuntime`: Runtime information for tools, bundling together state, context, config, stream_writer, tool_call_id, and store
+    `tools_condition`: Utility function for conditional routing based on tool calls

 Typical Usage:
    ```python
@@ -142,25 +139,6 @@ class ToolCallRequest:
    state: Any
    runtime: ToolRuntime

-    def __setattr__(self, name: str, value: Any) -> None:
-        """Raise deprecation warning when setting attributes directly.
-
-        Direct attribute assignment is deprecated. Use the `override()` method instead.
-        """
-        import warnings
-
-        # Allow setting attributes during initialization
-        if not hasattr(self, "__dataclass_fields__") or not hasattr(self, name):
-            object.__setattr__(self, name, value)
-        else:
-            warnings.warn(
-                f"Setting attribute '{name}' on ToolCallRequest is deprecated. "
-                "Use the override() method instead to create a new instance with modified values.",
-                DeprecationWarning,
-                stacklevel=2,
-            )
-            object.__setattr__(self, name, value)
-
    def override(
        self, **overrides: Unpack[_ToolCallRequestOverrides]
    ) -> ToolCallRequest:
@@ -221,9 +199,8 @@ Examples:

    ```python
    def handler(request, execute):
-        modified_call = {**request.tool_call, "args": {**request.tool_call["args"], "value": request.tool_call["args"]["value"] * 2}}
-        modified_request = request.override(tool_call=modified_call)
-        return execute(modified_request)
+        request.tool_call["args"]["value"] *= 2
+        return execute(request)
    ```

    Retry on error (execute multiple times):
@@ -499,7 +476,9 @@ def _infer_handled_types(handler: Callable[..., str]) -> tuple[type[Exception],

 def _filter_validation_errors(
    validation_error: ValidationError,
-    injected_args: _InjectedArgs | None,
+    tool_to_state_args: dict[str, str | None],
+    tool_to_store_arg: str | None,
+    tool_to_runtime_arg: str | None,
 ) -> list[ErrorDetails]:
    """Filter validation errors to only include LLM-controlled arguments.

@@ -514,28 +493,25 @@ def _filter_validation_errors(

    Args:
        validation_error: The Pydantic ValidationError raised during tool invocation.
-        injected_args: The _InjectedArgs structure containing all injected arguments,
-            or None if there are no injected arguments.
+        tool_to_state_args: Mapping of state argument names to state field names.
+        tool_to_store_arg: Name of the store argument, if any.
+        tool_to_runtime_arg: Name of the runtime argument, if any.

    Returns:
        List of ErrorDetails containing only errors for LLM-controlled arguments,
        with system-injected argument values removed from the input field.
    """
-    # Collect all injected argument names
-    injected_arg_names: set[str] = set()
-    if injected_args:
-        if injected_args.state:
-            injected_arg_names.update(injected_args.state.keys())
-        if injected_args.store:
-            injected_arg_names.add(injected_args.store)
-        if injected_args.runtime:
-            injected_arg_names.add(injected_args.runtime)
+    injected_args = set(tool_to_state_args.keys())
+    if tool_to_store_arg:
+        injected_args.add(tool_to_store_arg)
+    if tool_to_runtime_arg:
+        injected_args.add(tool_to_runtime_arg)

    filtered_errors: list[ErrorDetails] = []
    for error in validation_error.errors():
        # Check if error location contains any injected argument
        # error['loc'] is a tuple like ('field_name',) or ('field_name', 'nested_field')
-        if error["loc"] and error["loc"][0] not in injected_arg_names:
+        if error["loc"] and error["loc"][0] not in injected_args:
            # Create a copy of the error dict to avoid mutating the original
            error_copy: dict[str, Any] = {**error}

@@ -543,7 +519,7 @@ def _filter_validation_errors(
            if isinstance(error_copy.get("input"), dict):
                input_dict = error_copy["input"]
                input_copy = {
-                    k: v for k, v in input_dict.items() if k not in injected_arg_names
+                    k: v for k, v in input_dict.items() if k not in injected_args
                }
                error_copy["input"] = input_copy

@@ -553,60 +529,6 @@ def _filter_validation_errors(
    return filtered_errors


-@dataclass
-class _InjectedArgs:
-    """Internal structure for tracking injected arguments for a tool.
-
-    This data structure is built once during ToolNode initialization by analyzing
-    the tool's signature and args schema, then reused during execution for efficient
-    injection without repeated reflection.
-
-    The structure maps from tool parameter names to their injection sources, enabling
-    the ToolNode to know exactly which arguments need to be injected and where to
-    get their values from.
-
-    Attributes:
-        state: Mapping from tool parameter names to state field names for injection.
-            Keys are tool parameter names, values are either:
-            - str: Name of the state field to extract and inject
-            - None: Inject the entire state object
-            Empty dict if no state injection is needed.
-        store: Name of the tool parameter where the store should be injected,
-            or None if no store injection is needed.
-        runtime: Name of the tool parameter where the runtime should be injected,
-            or None if no runtime injection is needed.
-
-    Example:
-        For a tool with signature:
-        ```python
-        def my_tool(
-            x: int,
-            messages: Annotated[list, InjectedState("messages")],
-            full_state: Annotated[dict, InjectedState()],
-            store: Annotated[BaseStore, InjectedStore()],
-            runtime: ToolRuntime,
-        ) -> str:
-            ...
-        ```
-
-        The resulting `_InjectedArgs` would be:
-        ```python
-        _InjectedArgs(
-            state={
-                "messages": "messages",  # Extract state["messages"]
-                "full_state": None,      # Inject entire state
-            },
-            store="store",               # Inject into "store" parameter
-            runtime="runtime",           # Inject into "runtime" parameter
-        )
-        ```
-    """
-
-    state: dict[str, str | None]
-    store: str | None
-    runtime: str | None
-
-
 class ToolNode(RunnableCallable):
    """A node for executing tools in LangGraph workflows.

@@ -630,52 +552,44 @@ class ToolNode(RunnableCallable):
        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
-        - `Command` can update state, trigger navigation, or send messages
+        - Commands can update state, trigger navigation, or send messages

    Args:
-        tools: A sequence of tools that can be invoked by this node.
-
-            Supports:
-
+        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
-
        name: The name identifier for this node in the graph. Used for debugging
-            and visualization.
+            and visualization. Defaults to "tools".
        tags: Optional metadata tags to associate with the node for filtering
-            and organization.
+            and organization. Defaults to `None`.
        handle_tool_errors: Configuration for error handling during tool execution.
            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
+            - **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 with 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
+            - **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)
+                - 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)

        messages_key: The key in the state dictionary that contains the message list.
            This same key will be used for the output `ToolMessage` objects.
-
+            Defaults to "messages".
            Allows custom state schemas with different message field names.

    Examples:
@@ -751,7 +665,9 @@ class ToolNode(RunnableCallable):
        """
        super().__init__(self._func, self._afunc, name=name, tags=tags, trace=False)
        self._tools_by_name: dict[str, BaseTool] = {}
-        self._injected_args: dict[str, _InjectedArgs] = {}
+        self._tool_to_state_args: dict[str, dict[str, str | None]] = {}
+        self._tool_to_store_arg: dict[str, str | None] = {}
+        self._tool_to_runtime_arg: dict[str, str | None] = {}
        self._handle_tool_errors = handle_tool_errors
        self._messages_key = messages_key
        self._wrap_tool_call = wrap_tool_call
@@ -762,8 +678,9 @@ class ToolNode(RunnableCallable):
            else:
                tool_ = tool
            self._tools_by_name[tool_.name] = tool_
-            # Build injected args mapping once during initialization in a single pass
-            self._injected_args[tool_.name] = _get_all_injected_args(tool_)
+            self._tool_to_state_args[tool_.name] = _get_state_args(tool_)
+            self._tool_to_store_arg[tool_.name] = _get_store_arg(tool_)
+            self._tool_to_runtime_arg[tool_.name] = _get_runtime_arg(tool_)

    @property
    def tools_by_name(self) -> dict[str, BaseTool]:
@@ -916,8 +833,12 @@ class ToolNode(RunnableCallable):
                response = tool.invoke(call_args, config)
            except ValidationError as exc:
                # Filter out errors for injected arguments
-                injected = self._injected_args.get(call["name"])
-                filtered_errors = _filter_validation_errors(exc, injected)
+                filtered_errors = _filter_validation_errors(
+                    exc,
+                    self._tool_to_state_args.get(call["name"], {}),
+                    self._tool_to_store_arg.get(call["name"]),
+                    self._tool_to_runtime_arg.get(call["name"]),
+                )
                # Use original call["args"] without injected values for error reporting
                raise ToolInvocationError(
                    call["name"], exc, call["args"], filtered_errors
@@ -970,6 +891,9 @@ class ToolNode(RunnableCallable):
            return self._validate_tool_command(response, request.tool_call, input_type)
        if isinstance(response, ToolMessage):
            response.content = cast("str | list", msg_content_output(response.content))
+            # Enrich ToolMessage with name if not set (e.g., from fallback handlers)
+            if response.name is None:
+                response.name = call["name"]
            return response

        msg = f"Tool {call['name']} returned unexpected type: {type(response)}"
@@ -1069,8 +993,12 @@ class ToolNode(RunnableCallable):
                response = await tool.ainvoke(call_args, config)
            except ValidationError as exc:
                # Filter out errors for injected arguments
-                injected = self._injected_args.get(call["name"])
-                filtered_errors = _filter_validation_errors(exc, injected)
+                filtered_errors = _filter_validation_errors(
+                    exc,
+                    self._tool_to_state_args.get(call["name"], {}),
+                    self._tool_to_store_arg.get(call["name"]),
+                    self._tool_to_runtime_arg.get(call["name"]),
+                )
                # Use original call["args"] without injected values for error reporting
                raise ToolInvocationError(
                    call["name"], exc, call["args"], filtered_errors
@@ -1123,6 +1051,9 @@ class ToolNode(RunnableCallable):
            return self._validate_tool_command(response, request.tool_call, input_type)
        if isinstance(response, ToolMessage):
            response.content = cast("str | list", msg_content_output(response.content))
+            # Enrich ToolMessage with name if not set (e.g., from fallback handlers)
+            if response.name is None:
+                response.name = call["name"]
            return response

        msg = f"Tool {call['name']} returned unexpected type: {type(response)}"
@@ -1263,6 +1194,86 @@ class ToolNode(RunnableCallable):
            return input["state"]
        return input

+    def _inject_state(
+        self,
+        tool_call: ToolCall,
+        state: list[AnyMessage] | dict[str, Any] | BaseModel,
+    ) -> ToolCall:
+        state_args = self._tool_to_state_args[tool_call["name"]]
+
+        if state_args and isinstance(state, list):
+            required_fields = list(state_args.values())
+            if (
+                len(required_fields) == 1 and required_fields[0] == self._messages_key
+            ) or required_fields[0] is None:
+                state = {self._messages_key: state}
+            else:
+                err_msg = (
+                    f"Invalid input to ToolNode. Tool {tool_call['name']} requires "
+                    f"graph state dict as input."
+                )
+                if any(state_field for state_field in state_args.values()):
+                    required_fields_str = ", ".join(f for f in required_fields if f)
+                    err_msg += f" State should contain fields {required_fields_str}."
+                raise ValueError(err_msg)
+
+        if isinstance(state, dict):
+            tool_state_args = {
+                tool_arg: state[state_field] if state_field else state
+                for tool_arg, state_field in state_args.items()
+            }
+        else:
+            tool_state_args = {
+                tool_arg: getattr(state, state_field) if state_field else state
+                for tool_arg, state_field in state_args.items()
+            }
+
+        tool_call["args"] = {
+            **tool_call["args"],
+            **tool_state_args,
+        }
+        return tool_call
+
+    def _inject_store(self, tool_call: ToolCall, store: BaseStore | None) -> ToolCall:
+        store_arg = self._tool_to_store_arg[tool_call["name"]]
+        if not store_arg:
+            return tool_call
+
+        if store is None:
+            msg = (
+                "Cannot inject store into tools with InjectedStore annotations - "
+                "please compile your graph with a store."
+            )
+            raise ValueError(msg)
+
+        tool_call["args"] = {
+            **tool_call["args"],
+            store_arg: store,
+        }
+        return tool_call
+
+    def _inject_runtime(
+        self, tool_call: ToolCall, tool_runtime: ToolRuntime
+    ) -> ToolCall:
+        """Inject ToolRuntime into tool call arguments.
+
+        Args:
+            tool_call: The tool call to inject runtime into.
+            tool_runtime: The ToolRuntime instance to inject.
+
+        Returns:
+            The tool call with runtime injected if needed.
+        """
+        runtime_arg = self._tool_to_runtime_arg.get(tool_call["name"])
+        if not runtime_arg:
+            return tool_call
+
+        tool_call["args"] = {
+            **tool_call["args"],
+            runtime_arg: tool_runtime,
+        }
+        return tool_call
+
    def _inject_tool_args(
        self,
        tool_call: ToolCall,
@@ -1301,64 +1312,12 @@ class ToolNode(RunnableCallable):
        if tool_call["name"] not in self.tools_by_name:
            return tool_call

-        injected = self._injected_args.get(tool_call["name"])
-        if not injected:
-            return tool_call
-
        tool_call_copy: ToolCall = copy(tool_call)
-        injected_args = {}
-
-        # Inject state
-        if injected.state:
-            state = tool_runtime.state
-            # Handle list state by converting to dict
-            if isinstance(state, list):
-                required_fields = list(injected.state.values())
-                if (
-                    len(required_fields) == 1
-                    and required_fields[0] == self._messages_key
-                ) or required_fields[0] is None:
-                    state = {self._messages_key: state}
-                else:
-                    err_msg = (
-                        f"Invalid input to ToolNode. Tool {tool_call['name']} requires "
-                        f"graph state dict as input."
-                    )
-                    if any(state_field for state_field in injected.state.values()):
-                        required_fields_str = ", ".join(f for f in required_fields if f)
-                        err_msg += (
-                            f" State should contain fields {required_fields_str}."
-                        )
-                    raise ValueError(err_msg)
-
-            # Extract state values
-            if isinstance(state, dict):
-                for tool_arg, state_field in injected.state.items():
-                    injected_args[tool_arg] = (
-                        state[state_field] if state_field else state
-                    )
-            else:
-                for tool_arg, state_field in injected.state.items():
-                    injected_args[tool_arg] = (
-                        getattr(state, state_field) if state_field else state
-                    )
-
-        # Inject store
-        if injected.store:
-            if tool_runtime.store is None:
-                msg = (
-                    "Cannot inject store into tools with InjectedStore annotations - "
-                    "please compile your graph with a store."
-                )
-                raise ValueError(msg)
-            injected_args[injected.store] = tool_runtime.store
-
-        # Inject runtime
-        if injected.runtime:
-            injected_args[injected.runtime] = tool_runtime
-
-        tool_call_copy["args"] = {**tool_call_copy["args"], **injected_args}
-        return tool_call_copy
+        tool_call_with_state = self._inject_state(tool_call_copy, tool_runtime.state)
+        tool_call_with_store = self._inject_store(
+            tool_call_with_state, tool_runtime.store
+        )
+        return self._inject_runtime(tool_call_with_store, tool_runtime)

    def _validate_tool_command(
        self,
@@ -1440,7 +1399,7 @@ def tools_condition(
    """Conditional routing function for tool-calling workflows.

    This utility function implements the standard conditional logic for ReAct-style
-    agents: if the last `AIMessage` contains tool calls, route to the tool execution
+    agents: if the last AI message contains tool calls, route to the tool execution
    node; otherwise, end the workflow. This pattern is fundamental to most tool-calling
    agent architectures.

@@ -1449,15 +1408,16 @@ def tools_condition(

    Args:
        state: The current graph state to examine for tool calls. Supported formats:
-            - Dictionary containing a messages key (for `StateGraph`)
-            - `BaseModel` instance with a messages attribute
+            - Dictionary containing a messages key (for StateGraph)
+            - BaseModel instance with a messages attribute
        messages_key: The key or attribute name containing the message list in the state.
            This allows customization for graphs using different state schemas.
+            Defaults to "messages".

    Returns:
-        Either `'tools'` if tool calls are present in the last `AIMessage`, or `'__end__'`
-            to terminate the workflow. These are the standard routing destinations for
-            tool-calling conditional edges.
+        Either "tools" if tool calls are present in the last AI message, or "__end__"
+        to terminate the workflow. These are the standard routing destinations for
+        tool-calling conditional edges.

    Raises:
        ValueError: If no messages can be found in the provided state format.
@@ -1654,7 +1614,7 @@ class InjectedStore(InjectedToolArg):

    This annotation enables tools to access LangGraph's persistent storage system
    without exposing storage details to the language model. Tools annotated with
-    `InjectedStore` receive the store instance automatically during execution while
+    InjectedStore receive the store instance automatically during execution while
    remaining invisible to the model's tool-calling interface.

    The store provides persistent, cross-session data storage that tools can use
@@ -1751,86 +1711,120 @@ def _is_injection(
    return False


-def _get_injection_from_type(
-    type_: Any, injection_type: type[InjectedState | InjectedStore | ToolRuntime]
-) -> Any | None:
-    """Extract injection instance from a type annotation.
+def _get_state_args(tool: BaseTool) -> dict[str, str | None]:
+    """Extract state injection mappings from tool annotations.
+
+    This function analyzes a tool's input schema to identify arguments that should
+    be injected with graph state. It processes InjectedState annotations to build
+    a mapping of tool argument names to state field names.

    Args:
-        type_: The type annotation to check.
-        injection_type: The injection type to look for.
+        tool: The tool to analyze for state injection requirements.

    Returns:
-        The injection instance if found, True if injection marker found without instance, None otherwise.
+        A dictionary mapping tool argument names to state field names. If a field
+        name is None, the entire state should be injected for that argument.
    """
-    type_args = get_args(type_)
-    matches = [arg for arg in type_args if _is_injection(arg, injection_type)]
+    full_schema = tool.get_input_schema()
+    tool_args_to_state_fields: dict = {}

-    if len(matches) > 1:
-        msg = (
-            f"A tool argument should not be annotated with {injection_type.__name__} "
-            f"more than once. Found: {matches}"
-        )
-        raise ValueError(msg)
+    for name, type_ in get_all_basemodel_annotations(full_schema).items():
+        injections = [
+            type_arg
+            for type_arg in get_args(type_)
+            if _is_injection(type_arg, InjectedState)
+        ]
+        if len(injections) > 1:
+            msg = (
+                "A tool argument should not be annotated with InjectedState more than "
+                f"once. Received arg {name} with annotations {injections}."
+            )
+            raise ValueError(msg)
+        if len(injections) == 1:
+            injection = injections[0]
+            if isinstance(injection, InjectedState) and injection.field:
+                tool_args_to_state_fields[name] = injection.field
+            else:
+                tool_args_to_state_fields[name] = None
+        else:
+            pass
+    return tool_args_to_state_fields

-    if len(matches) == 1:
-        return matches[0]
-    elif _is_injection(type_, injection_type):
-        return True
+
+def _get_store_arg(tool: BaseTool) -> str | None:
+    """Extract store injection argument from tool annotations.
+
+    This function analyzes a tool's input schema to identify the argument that
+    should be injected with the graph store. Only one store argument is supported
+    per tool.
+
+    Args:
+        tool: The tool to analyze for store injection requirements.
+
+    Returns:
+        The name of the argument that should receive the store injection, or None
+        if no store injection is required.
+
+    Raises:
+        ValueError: If a tool argument has multiple InjectedStore annotations.
+    """
+    full_schema = tool.get_input_schema()
+    for name, type_ in get_all_basemodel_annotations(full_schema).items():
+        injections = [
+            type_arg
+            for type_arg in get_args(type_)
+            if _is_injection(type_arg, InjectedStore)
+        ]
+        if len(injections) > 1:
+            msg = (
+                "A tool argument should not be annotated with InjectedStore more than "
+                f"once. Received arg {name} with annotations {injections}."
+            )
+            raise ValueError(msg)
+        if len(injections) == 1:
+            return name

    return None


-def _get_all_injected_args(tool: BaseTool) -> _InjectedArgs:
-    """Extract all injected arguments from tool in a single pass.
+def _get_runtime_arg(tool: BaseTool) -> str | None:
+    """Extract runtime injection argument from tool annotations.

-    This function analyzes both the tool's input schema and function signature
-    to identify all arguments that should be injected (state, store, runtime).
+    This function analyzes a tool's input schema to identify the argument that
+    should be injected with the ToolRuntime instance. Only one runtime argument
+    is supported per tool.

    Args:
-        tool: The tool to analyze for injection requirements.
+        tool: The tool to analyze for runtime injection requirements.

    Returns:
-        _InjectedArgs structure containing all detected injections.
+        The name of the argument that should receive the runtime injection, or None
+        if no runtime injection is required.
+
+    Raises:
+        ValueError: If a tool argument has multiple ToolRuntime annotations.
    """
-    # Get annotations from both schema and function signature
    full_schema = tool.get_input_schema()
-    schema_annotations = get_all_basemodel_annotations(full_schema)
-
-    func = getattr(tool, "func", None) or getattr(tool, "coroutine", None)
-    func_annotations = get_type_hints(func, include_extras=True) if func else {}
-
-    # Combine both annotation sources, preferring schema annotations
-    # In the future, we might want to add more restrictions here...
-    all_annotations = {**func_annotations, **schema_annotations}
-
-    # Track injected args
-    state_args: dict[str, str | None] = {}
-    store_arg: str | None = None
-    runtime_arg: str | None = None
-
-    for name, type_ in all_annotations.items():
-        # Check for runtime (special case: parameter named "runtime")
+    for name, type_ in get_all_basemodel_annotations(full_schema).items():
+        # Check if the parameter name is "runtime" (regardless of type)
        if name == "runtime":
-            runtime_arg = name
+            return name
+        # Check if the type itself is ToolRuntime (direct usage)
+        if _is_injection(type_, ToolRuntime):
+            return name
+        # Check if ToolRuntime is in Annotated args
+        injections = [
+            type_arg
+            for type_arg in get_args(type_)
+            if _is_injection(type_arg, ToolRuntime)
+        ]
+        if len(injections) > 1:
+            msg = (
+                "A tool argument should not be annotated with ToolRuntime more than "
+                f"once. Received arg {name} with annotations {injections}."
+            )
+            raise ValueError(msg)
+        if len(injections) == 1:
+            return name

-        # Check for InjectedState
-        if state_inj := _get_injection_from_type(type_, InjectedState):
-            if isinstance(state_inj, InjectedState) and state_inj.field:
-                state_args[name] = state_inj.field
-            else:
-                state_args[name] = None
-
-        # Check for InjectedStore
-        if _get_injection_from_type(type_, InjectedStore):
-            store_arg = name
-
-        # Check for ToolRuntime
-        if _get_injection_from_type(type_, ToolRuntime):
-            runtime_arg = name
-
-    return _InjectedArgs(
-        state=state_args,
-        store=store_arg,
-        runtime=runtime_arg,
-    )
+    return None
@@ -45,9 +45,9 @@ def _default_format_error(
    category=LangGraphDeprecatedSinceV10,
 )
 class ValidationNode(RunnableCallable):
-    """A node that validates all tools requests from the last `AIMessage`.
+    """A node that validates all tools requests from the last AIMessage.

-    It can be used either in `StateGraph` with a `'messages'` key.
+    It can be used either in StateGraph with a "messages" key.

    !!! note

@@ -57,8 +57,7 @@ class ValidationNode(RunnableCallable):
        messages and tool IDs (for use in multi-turn conversations).

    Returns:
-        (Union[Dict[str, List[ToolMessage]], Sequence[ToolMessage]]): A list of
-            `ToolMessage` objects with the validated content or error messages.
+        (Union[Dict[str, List[ToolMessage]], Sequence[ToolMessage]]): A list of ToolMessages with the validated content or error messages.

    Example:
        ```python title="Example usage for re-prompting the model to generate a valid response:"
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"

 [project]
 name = "langgraph-prebuilt"
-version = "1.0.5"
+version = "1.0.2"
 description = "Library with high-level APIs for creating and executing LangGraph agents and tools."
 authors = []
 requires-python = ">=3.10"
@@ -29,10 +29,7 @@ dependencies = [
 ]

 [project.urls]
-Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/prebuilt"
-Twitter = "https://x.com/LangChainAI"
-Slack = "https://www.langchain.com/join-community"
-Reddit = "https://www.reddit.com/r/LangChain/"
+Repository = "https://www.github.com/langchain-ai/langgraph"

 [dependency-groups]
 test = [
@@ -130,17 +130,11 @@ def test_modify_arguments() -> None:
        execute: Callable[[ToolCallRequest], ToolMessage | Command],
    ) -> ToolMessage | Command:
        """Handler that doubles the input arguments."""
-        # Modify the arguments using override method
-        modified_call = {
-            **request.tool_call,
-            "args": {
-                **request.tool_call["args"],
-                "a": request.tool_call["args"]["a"] * 2,
-                "b": request.tool_call["args"]["b"] * 2,
-            },
-        }
-        modified_request = request.override(tool_call=modified_call)
-        return execute(modified_request)
+        # Modify the arguments
+        request.tool_call["args"]["a"] *= 2
+        request.tool_call["args"]["b"] *= 2
+
+        return execute(request)

    tool_node = ToolNode([add], wrap_tool_call=modify_args_handler)

@@ -368,17 +362,10 @@ async def test_handler_with_async_execution() -> None:
        execute: Callable[[ToolCallRequest], ToolMessage | Command],
    ) -> ToolMessage | Command:
        """Handler that modifies arguments."""
-        # Add 10 to both arguments using override method
-        modified_call = {
-            **request.tool_call,
-            "args": {
-                **request.tool_call["args"],
-                "a": request.tool_call["args"]["a"] + 10,
-                "b": request.tool_call["args"]["b"] + 10,
-            },
-        }
-        modified_request = request.override(tool_call=modified_call)
-        return execute(modified_request)
+        # Add 10 to both arguments
+        request.tool_call["args"]["a"] += 10
+        request.tool_call["args"]["b"] += 10
+        return execute(request)

    tool_node = ToolNode([async_add], wrap_tool_call=modifying_handler)

@@ -1318,64 +1305,3 @@ async def test_state_extraction_with_tool_call_with_context_async() -> None:
    assert state_seen[0] == actual_state
    assert "__type" not in state_seen[0]
    assert "tool_call" not in state_seen[0]
-
-
-def test_tool_call_request_is_frozen() -> None:
-    """Test that ToolCallRequest raises deprecation warnings on direct attribute reassignment."""
-    tool_call: ToolCall = {"name": "add", "args": {"a": 1, "b": 2}, "id": "call_1"}
-    state: dict = {"messages": []}
-    runtime = None
-
-    request = ToolCallRequest(
-        tool_call=tool_call, tool=add, state=state, runtime=runtime
-    )  # type: ignore[arg-type]
-
-    # Test that direct attribute reassignment raises DeprecationWarning
-    with pytest.warns(
-        DeprecationWarning,
-        match="Setting attribute 'tool_call' on ToolCallRequest is deprecated",
-    ):
-        request.tool_call = {"name": "other", "args": {}, "id": "call_2"}  # type: ignore[misc]
-
-    with pytest.warns(
-        DeprecationWarning,
-        match="Setting attribute 'tool' on ToolCallRequest is deprecated",
-    ):
-        request.tool = None  # type: ignore[misc]
-
-    with pytest.warns(
-        DeprecationWarning,
-        match="Setting attribute 'state' on ToolCallRequest is deprecated",
-    ):
-        request.state = {}  # type: ignore[misc]
-
-    with pytest.warns(
-        DeprecationWarning,
-        match="Setting attribute 'runtime' on ToolCallRequest is deprecated",
-    ):
-        request.runtime = None  # type: ignore[misc]
-
-    # Test that override method works correctly
-    new_tool_call: ToolCall = {
-        "name": "multiply",
-        "args": {"x": 5, "y": 10},
-        "id": "call_3",
-    }
-
-    # Original request should be unchanged (note: it was modified by the warnings tests above)
-    # So we create a fresh request to test override properly
-    fresh_request = ToolCallRequest(
-        tool_call=tool_call, tool=add, state=state, runtime=runtime
-    )  # type: ignore[arg-type]
-    fresh_new_request = fresh_request.override(tool_call=new_tool_call)
-
-    # Original request should be unchanged
-    assert fresh_request.tool_call == tool_call
-    assert fresh_request.tool_call["name"] == "add"
-
-    # New request should have the updated tool_call
-    assert fresh_new_request.tool_call == new_tool_call
-    assert fresh_new_request.tool_call["name"] == "multiply"
-    assert fresh_new_request.tool == add  # Other fields should remain the same
-    assert fresh_new_request.state == state
-    assert fresh_new_request.runtime is None
@@ -53,6 +53,7 @@ from langgraph.prebuilt.chat_agent_executor import (
 from langgraph.prebuilt.tool_node import (
    InjectedState,
    InjectedStore,
+    _get_state_args,
    _infer_handled_types,
 )
 from tests.any_str import AnyStr
@@ -638,9 +639,8 @@ def test_react_agent_parallel_tool_calls(
    for event in agent.stream(
        {"messages": [("user", query)]}, config, stream_mode="values"
    ):
-        if "__interrupt__" not in event: 
-            if messages := event.get("messages"):
-                message_types.append([m.type for m in messages])
+        if messages := event.get("messages"):
+            message_types.append([m.type for m in messages])

    if version == "v1":
        assert message_types == [
@@ -1084,6 +1084,21 @@ async def test_return_direct(version: str) -> None:
    ]


+def test__get_state_args() -> None:
+    class Schema1(BaseModel):
+        a: Annotated[str, InjectedState]
+
+    class Schema2(Schema1):
+        b: Annotated[int, InjectedState("bar")]
+
+    @dec_tool(args_schema=Schema2)
+    def foo(a: str, b: int) -> float:
+        """return"""
+        return 0.0
+
+    assert _get_state_args(foo) == {"a": None, "b": "bar"}
+
+
 def test_inspect_react() -> None:
    model = FakeToolCallingModel(tool_calls=[])
    agent = create_react_agent(model, [])
@@ -42,7 +42,6 @@ from langgraph.prebuilt import (
 from langgraph.prebuilt.tool_node import (
    TOOL_CALL_ERROR_TEMPLATE,
    ToolInvocationError,
-    ToolRuntime,
    tools_condition,
 )

@@ -1611,252 +1610,3 @@ def test_tool_node_stream_writer() -> None:
            },
        ),
    ]
-
-
-def test_tool_call_request_setattr_deprecation_warning():
-    """Test that ToolCallRequest raises a deprecation warning on direct attribute modification."""
-    import warnings
-
-    from langgraph.prebuilt.tool_node import ToolCallRequest
-
-    # Create a mock ToolCall
-    tool_call = {"name": "test", "args": {"a": 1}, "id": "call_1", "type": "tool_call"}
-
-    # Create a ToolCallRequest
-    request = ToolCallRequest(
-        tool_call=tool_call,
-        tool=None,
-        state={"messages": []},
-        runtime=None,
-    )
-
-    # Test 1: Direct attribute assignment should raise deprecation warning but still work
-    with pytest.warns(DeprecationWarning, match="deprecated.*override"):
-        request.tool_call = {"name": "other", "args": {}, "id": "call_2"}
-
-    # Verify the attribute was actually modified
-    assert request.tool_call == {"name": "other", "args": {}, "id": "call_2"}
-
-    # Reset for further tests
-    with warnings.catch_warnings():
-        warnings.simplefilter("ignore")
-        request.tool_call = tool_call
-
-    # Test 2: override method should work without warnings
-    with warnings.catch_warnings(record=True) as w:
-        warnings.simplefilter("always")
-        new_tool_call = {
-            "name": "new_tool",
-            "args": {"b": 2},
-            "id": "call_3",
-            "type": "tool_call",
-        }
-        new_request = request.override(tool_call=new_tool_call)
-
-        # Verify no warning was raised
-        assert len(w) == 0
-
-    # Verify original is unchanged
-    assert request.tool_call == tool_call
-
-    # Verify new request has updated values
-    assert new_request.tool_call == new_tool_call
-
-    # Test 3: Initialization should not trigger warning
-    with warnings.catch_warnings(record=True) as w:
-        warnings.simplefilter("always")
-        ToolCallRequest(
-            tool_call=tool_call,
-            tool=None,
-            state={"messages": []},
-            runtime=None,
-        )
-        # Verify no warning was raised during initialization
-        assert len(w) == 0
-
-
-async def test_tool_node_inject_async_all_types_signature_only() -> None:
-    """Test all injection types without @tool decorator."""
-    store = InMemoryStore()
-    namespace = ("test",)
-    store.put(namespace, "test_key", {"store_data": "from_store"})
-
-    class TestState(TypedDict):
-        messages: list
-        foo: str
-        bar: int
-
-    async def comprehensive_async_tool(
-        x: int,
-        whole_state: Annotated[TestState, InjectedState],
-        foo_field: Annotated[str, InjectedState("foo")],
-        store: Annotated[BaseStore, InjectedStore()],
-        runtime: ToolRuntime,
-    ) -> str:
-        """Async tool that uses all injection types."""
-        bar_from_whole = whole_state["bar"]
-        foo_value = foo_field
-        store_val = store.get(namespace, "test_key").value["store_data"]
-        foo_from_runtime = runtime.state["foo"]
-        tool_call_id = runtime.tool_call_id
-
-        return (
-            f"x={x}, "
-            f"bar_from_whole={bar_from_whole}, "
-            f"foo_field={foo_value}, "
-            f"store={store_val}, "
-            f"foo_from_runtime={foo_from_runtime}, "
-            f"tool_call_id={tool_call_id}"
-        )
-
-    node = ToolNode([comprehensive_async_tool], handle_tool_errors=True)
-    tool_call = {
-        "name": "comprehensive_async_tool",
-        "args": {"x": 42},
-        "id": "test_call_123",
-        "type": "tool_call",
-    }
-    msg = AIMessage("hi?", tool_calls=[tool_call])
-
-    config = _create_config_with_runtime(store=store)
-    result = await node.ainvoke(
-        {"messages": [msg], "foo": "foo_value", "bar": 99}, config=config
-    )
-
-    tool_message = result["messages"][-1]
-    assert tool_message.content == (
-        "x=42, "
-        "bar_from_whole=99, "
-        "foo_field=foo_value, "
-        "store=from_store, "
-        "foo_from_runtime=foo_value, "
-        "tool_call_id=test_call_123"
-    )
-
-
-async def test_tool_node_inject_async_all_types_with_decorator() -> None:
-    """Test all injection types with @tool decorator."""
-    store = InMemoryStore()
-    namespace = ("test",)
-    store.put(namespace, "test_key", {"store_data": "from_store"})
-
-    class TestState(TypedDict):
-        messages: list
-        foo: str
-        bar: int
-
-    @dec_tool
-    async def comprehensive_async_tool(
-        x: int,
-        whole_state: Annotated[TestState, InjectedState],
-        foo_field: Annotated[str, InjectedState("foo")],
-        store: Annotated[BaseStore, InjectedStore()],
-        runtime: ToolRuntime,
-    ) -> str:
-        """Async tool that uses all injection types."""
-        bar_from_whole = whole_state["bar"]
-        foo_value = foo_field
-        store_val = store.get(namespace, "test_key").value["store_data"]
-        foo_from_runtime = runtime.state["foo"]
-        tool_call_id = runtime.tool_call_id
-
-        return (
-            f"x={x}, "
-            f"bar_from_whole={bar_from_whole}, "
-            f"foo_field={foo_value}, "
-            f"store={store_val}, "
-            f"foo_from_runtime={foo_from_runtime}, "
-            f"tool_call_id={tool_call_id}"
-        )
-
-    node = ToolNode([comprehensive_async_tool], handle_tool_errors=True)
-    tool_call = {
-        "name": "comprehensive_async_tool",
-        "args": {"x": 42},
-        "id": "test_call_456",
-        "type": "tool_call",
-    }
-    msg = AIMessage("hi?", tool_calls=[tool_call])
-
-    config = _create_config_with_runtime(store=store)
-    result = await node.ainvoke(
-        {"messages": [msg], "foo": "foo_value", "bar": 99}, config=config
-    )
-
-    tool_message = result["messages"][-1]
-    assert tool_message.content == (
-        "x=42, "
-        "bar_from_whole=99, "
-        "foo_field=foo_value, "
-        "store=from_store, "
-        "foo_from_runtime=foo_value, "
-        "tool_call_id=test_call_456"
-    )
-
-
-async def test_tool_node_inject_async_all_types_with_schema() -> None:
-    """Test all injection types with explicit schema."""
-    store = InMemoryStore()
-    namespace = ("test",)
-    store.put(namespace, "test_key", {"store_data": "from_store"})
-
-    class TestState(TypedDict):
-        messages: list
-        foo: str
-        bar: int
-
-    class ComprehensiveToolSchema(BaseModel):
-        model_config = {"arbitrary_types_allowed": True}
-        x: int
-        whole_state: Annotated[TestState, InjectedState]
-        foo_field: Annotated[str, InjectedState("foo")]
-        store: Annotated[BaseStore, InjectedStore()]
-        runtime: ToolRuntime
-
-    @dec_tool(args_schema=ComprehensiveToolSchema)
-    async def comprehensive_async_tool(
-        x: int,
-        whole_state: Annotated[TestState, InjectedState],
-        foo_field: Annotated[str, InjectedState("foo")],
-        store: Annotated[BaseStore, InjectedStore()],
-        runtime: ToolRuntime,
-    ) -> str:
-        """Async tool that uses all injection types."""
-        bar_from_whole = whole_state["bar"]
-        foo_value = foo_field
-        store_val = store.get(namespace, "test_key").value["store_data"]
-        foo_from_runtime = runtime.state["foo"]
-        tool_call_id = runtime.tool_call_id
-
-        return (
-            f"x={x}, "
-            f"bar_from_whole={bar_from_whole}, "
-            f"foo_field={foo_value}, "
-            f"store={store_val}, "
-            f"foo_from_runtime={foo_from_runtime}, "
-            f"tool_call_id={tool_call_id}"
-        )
-
-    node = ToolNode([comprehensive_async_tool], handle_tool_errors=True)
-    tool_call = {
-        "name": "comprehensive_async_tool",
-        "args": {"x": 42},
-        "id": "test_call_789",
-        "type": "tool_call",
-    }
-    msg = AIMessage("hi?", tool_calls=[tool_call])
-
-    config = _create_config_with_runtime(store=store)
-    result = await node.ainvoke(
-        {"messages": [msg], "foo": "foo_value", "bar": 99}, config=config
-    )
-
-    tool_message = result["messages"][-1]
-    assert tool_message.content == (
-        "x=42, "
-        "bar_from_whole=99, "
-        "foo_field=foo_value, "
-        "store=from_store, "
-        "foo_from_runtime=foo_value, "
-        "tool_call_id=test_call_789"
-    )
@@ -1,5 +1,5 @@
 version = 1
-revision = 3
+revision = 2
 requires-python = ">=3.10"

 [[package]]
@@ -246,7 +246,7 @@ wheels = [

 [[package]]
 name = "langgraph"
-version = "1.0.3"
+version = "1.0.2"
 source = { editable = "../langgraph" }
 dependencies = [
    { name = "langchain-core" },
@@ -330,7 +330,7 @@ test = [

 [[package]]
 name = "langgraph-checkpoint"
-version = "3.0.1"
+version = "3.0.0"
 source = { editable = "../checkpoint" }
 dependencies = [
    { name = "langchain-core" },
@@ -340,7 +340,7 @@ dependencies = [
 [package.metadata]
 requires-dist = [
    { name = "langchain-core", specifier = ">=0.2.38" },
-    { name = "ormsgpack", specifier = ">=1.12.0" },
+    { name = "ormsgpack", specifier = ">=1.10.0" },
 ]

 [package.metadata.requires-dev]
@@ -377,7 +377,7 @@ test = [

 [[package]]
 name = "langgraph-checkpoint-postgres"
-version = "3.0.1"
+version = "3.0.0"
 source = { editable = "../checkpoint-postgres" }
 dependencies = [
    { name = "langgraph-checkpoint" },
@@ -467,7 +467,7 @@ test = [

 [[package]]
 name = "langgraph-prebuilt"
-version = "1.0.5"
+version = "1.0.2"
 source = { editable = "." }
 dependencies = [
    { name = "langchain-core" },
@@ -570,7 +570,6 @@ requires-dist = [
 dev = [
    { name = "codespell" },
    { name = "mypy" },
-    { name = "pydantic", specifier = ">=2.12.4" },
    { name = "pytest" },
    { name = "pytest-asyncio" },
    { name = "pytest-mock" },
@@ -740,57 +739,57 @@ wheels = [

 [[package]]
 name = "ormsgpack"
-version = "1.12.0"
+version = "1.11.0"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/6c/67/d5ef41c3b4a94400be801984ef7c7fc9623e1a82b643e74eeec367e7462b/ormsgpack-1.12.0.tar.gz", hash = "sha256:94be818fdbb0285945839b88763b269987787cb2f7ef280cad5d6ec815b7e608", size = 49959, upload-time = "2025-11-04T18:30:10.083Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/65/f8/224c342c0e03e131aaa1a1f19aa2244e167001783a433f4eed10eedd834b/ormsgpack-1.11.0.tar.gz", hash = "sha256:7c9988e78fedba3292541eb3bb274fa63044ef4da2ddb47259ea70c05dee4206", size = 49357, upload-time = "2025-10-08T17:29:15.621Z" }
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+    { url = "https://files.pythonhosted.org/packages/a9/0c/81a19e6115b15764db3d241788f9fac093122878aaabf872cc545b0c4650/ormsgpack-1.11.0-cp314-cp314t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c04402fb9a0a9b9f18fbafd6d5f8398ee99b3ec619fb63952d3a954bc9d47daa", size = 195539, upload-time = "2025-10-08T17:29:03.472Z" },
+    { url = "https://files.pythonhosted.org/packages/97/86/e5b50247a61caec5718122feb2719ea9d451d30ac0516c288c1dbc6408e8/ormsgpack-1.11.0-cp314-cp314t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a025ec07ac52056ecfd9e57b5cbc6fff163f62cb9805012b56cda599157f8ef2", size = 207718, upload-time = "2025-10-08T17:29:04.545Z" },
 ]

 [[package]]
@@ -90,11 +90,11 @@ class Auth:
    """

    __slots__ = (
-        "_authenticate_handler",
-        "_global_handlers",
-        "_handler_cache",
-        "_handlers",
        "on",
+        "_handlers",
+        "_global_handlers",
+        "_authenticate_handler",
+        "_handler_cache",
    )
    types = types
    """Reference to auth type definitions.
@@ -259,7 +259,7 @@ class Auth:
        """
        if self._authenticate_handler is not None:
            raise ValueError(
-                f"Authentication handler already set as {self._authenticate_handler}."
+                "Authentication handler already set as {self._authenticate_handler}."
            )
        self._authenticate_handler = fn
        return fn
@@ -383,7 +383,7 @@ class _ResourceOn(typing.Generic[VCreate, VRead, VUpdate, VDelete, VSearch]):
        if fn is not None:
            _validate_handler(fn)
            return typing.cast(
-                "_ActionHandler[VCreate | VUpdate | VRead | VDelete | VSearch]",
+                _ActionHandler[VCreate | VUpdate | VRead | VDelete | VSearch],
                _register_handler(self.auth, self.resource, "*", fn),
            )

@@ -392,7 +392,7 @@ class _ResourceOn(typing.Generic[VCreate, VRead, VUpdate, VDelete, VSearch]):
        ) -> _ActionHandler[VCreate | VUpdate | VRead | VDelete | VSearch]:
            _validate_handler(handler)
            return typing.cast(
-                "_ActionHandler[VCreate | VUpdate | VRead | VDelete | VSearch]",
+                _ActionHandler[VCreate | VUpdate | VRead | VDelete | VSearch],
                _register_handler(self.auth, self.resource, "*", handler),
            )

@@ -612,10 +612,10 @@ class _On:
    __slots__ = (
        "_auth",
        "assistants",
-        "crons",
-        "runs",
-        "store",
        "threads",
+        "runs",
+        "crons",
+        "store",
        "value",
    )

@@ -740,8 +740,9 @@ def is_studio_user(
 ) -> bool:
    return (
        isinstance(user, types.StudioUser)
-        or (isinstance(user, dict) and user.get("kind") == "StudioUser")  # ty: ignore[invalid-argument-type]
+        or isinstance(user, dict)
+        and user.get("kind") == "StudioUser"  # ty: ignore[invalid-argument-type]
    )


-__all__ = ["Auth", "exceptions", "types"]
+__all__ = ["Auth", "types", "exceptions"]
@@ -243,7 +243,7 @@ class StudioUser:
        ```
    """

-    __slots__ = ("_is_authenticated", "_permissions", "username")
+    __slots__ = ("username", "_is_authenticated", "_permissions")

    def __init__(self, username: str, is_authenticated: bool = False) -> None:
        self.username = username
@@ -1093,22 +1093,22 @@ class on:


 __all__ = [
-    "AssistantsCreate",
-    "AssistantsDelete",
-    "AssistantsRead",
-    "AssistantsSearch",
-    "AssistantsUpdate",
+    "on",
    "MetadataInput",
    "RunsCreate",
-    "StoreDelete",
+    "ThreadsCreate",
+    "ThreadsRead",
+    "ThreadsUpdate",
+    "ThreadsDelete",
+    "ThreadsSearch",
+    "AssistantsCreate",
+    "AssistantsRead",
+    "AssistantsUpdate",
+    "AssistantsDelete",
+    "AssistantsSearch",
    "StoreGet",
+    "StoreSearch",
    "StoreListNamespaces",
    "StorePut",
-    "StoreSearch",
-    "ThreadsCreate",
-    "ThreadsDelete",
-    "ThreadsRead",
-    "ThreadsSearch",
-    "ThreadsUpdate",
-    "on",
+    "StoreDelete",
 ]
@@ -1,11 +1,11 @@
 """The LangGraph client implementations connect to the LangGraph API.

-This module provides both asynchronous (`get_client(url="http://localhost:2024")` or
-`LangGraphClient`) and synchronous (`get_sync_client(url="http://localhost:2024")` or
-`SyncLanggraphClient`) clients to interacting with the LangGraph API's core resources
-such as Assistants, Threads, Runs, and Cron jobs, as well as its persistent document
-Store.
-"""
+This module provides both asynchronous ([get_client(url="http://localhost:2024"))](#get_client) or [LangGraphClient](#LangGraphClient))
+and synchronous ([get_sync_client(url="http://localhost:2024"))](#get_sync_client) or [SyncLanggraphClient](#SyncLanggraphClient))
+clients to interacting with the LangGraph API's core resources such as
+Assistants, Threads, Runs, and Cron jobs, as well as its persistent
+document Store.
+"""  # noqa: E501

 from __future__ import annotations

@@ -21,7 +21,6 @@ from types import TracebackType
 from typing import (
    Any,
    Literal,
-    cast,
    overload,
 )

@@ -118,20 +117,9 @@ def _get_headers(


 def _orjson_default(obj: Any) -> Any:
-    is_class = isinstance(obj, type)
    if hasattr(obj, "model_dump") and callable(obj.model_dump):
-        if is_class:
-            raise TypeError(
-                f"Cannot JSON-serialize type object: {obj!r}. Did you mean to pass an instance of the object instead?"
-                f"\nReceived type: {obj!r}"
-            )
        return obj.model_dump()
    elif hasattr(obj, "dict") and callable(obj.dict):
-        if is_class:
-            raise TypeError(
-                f"Cannot JSON-serialize type object: {obj!r}. Did you mean to pass an instance of the object instead?"
-                f"\nReceived type: {obj!r}"
-            )
        return obj.dict()
    elif isinstance(obj, (set, frozenset)):
        return list(obj)
@@ -175,7 +163,7 @@ def get_client(
    Args:
        url:
            Base URL of the LangGraph API.
-            - If `None`, the client first attempts an in-process connection via ASGI transport.
+            – If `None`, the client first attempts an in-process connection via ASGI transport.
              If that fails, it falls back to `http://localhost:8123`.
        api_key:
            API key for authentication. If omitted, the client reads from environment
@@ -188,9 +176,9 @@ def get_client(
            Additional HTTP headers to include in requests. Merged with authentication headers.
        timeout:
            HTTP timeout configuration. May be:
-              - `httpx.Timeout` instance
-              - float (total seconds)
-              - tuple `(connect, read, write, pool)` in seconds
+              – `httpx.Timeout` instance
+              – float (total seconds)
+              – tuple `(connect, read, write, pool)` in seconds
            Defaults: connect=5, read=300, write=300, pool=5.

    Returns:
@@ -248,7 +236,7 @@ def get_client(
        base_url=url,
        transport=transport,
        timeout=(
-            httpx.Timeout(timeout)  # ty: ignore[invalid-argument-type]
+            httpx.Timeout(timeout)
            if timeout is not None
            else httpx.Timeout(connect=5, read=300, write=300, pool=5)
        ),
@@ -523,7 +511,7 @@ class HttpClient:
                decoder = SSEDecoder()
                try:
                    async for line in aiter_lines_raw(res):
-                        sse = decoder.decode(line=cast("bytes", line).rstrip(b"\n"))
+                        sse = decoder.decode(line=line.rstrip(b"\n"))
                        if sse is not None:
                            if decoder.last_event_id is not None:
                                last_event_id = decoder.last_event_id
@@ -637,7 +625,7 @@ class AssistantsClient:
                'name': 'my_assistant'
            }
            ```
-        """
+        """  # noqa: E501
        return await self.http.get(
            f"/assistants/{assistant_id}", headers=headers, params=params
        )
@@ -691,7 +679,7 @@ class AssistantsClient:
            ```


-        """
+        """  # noqa: E501
        query_params = {"xray": xray}
        if params:
            query_params.update(params)
@@ -816,7 +804,7 @@ class AssistantsClient:
            }
            ```

-        """
+        """  # noqa: E501
        return await self.http.get(
            f"/assistants/{assistant_id}/schemas", headers=headers, params=params
        )
@@ -842,7 +830,7 @@ class AssistantsClient:
        Returns:
            Subgraphs: The graph schema for the assistant.

-        """
+        """  # noqa: E501
        get_params = {"recurse": recurse}
        if params:
            get_params = {**get_params, **params}
@@ -908,7 +896,7 @@ class AssistantsClient:
                name="my_name"
            )
            ```
-        """
+        """  # noqa: E501
        payload: dict[str, Any] = {
            "graph_id": graph_id,
        }
@@ -976,7 +964,7 @@ class AssistantsClient:
            )
            ```

-        """
+        """  # noqa: E501
        payload: dict[str, Any] = {}
        if graph_id:
            payload["graph_id"] = graph_id
@@ -1023,7 +1011,7 @@ class AssistantsClient:
            )
            ```

-        """
+        """  # noqa: E501
        await self.http.delete(
            f"/assistants/{assistant_id}", headers=headers, params=params
        )
@@ -1149,7 +1137,7 @@ class AssistantsClient:
                assistant_id="my_assistant_id"
            )
            ```
-        """
+        """  # noqa: E501

        payload: dict[str, Any] = {
            "limit": limit,
@@ -1193,7 +1181,7 @@ class AssistantsClient:
            )
            ```

-        """
+        """  # noqa: E501

        payload: dict[str, Any] = {"version": version}

@@ -1261,7 +1249,7 @@ class ThreadsClient:
            }
            ```

-        """
+        """  # noqa: E501

        return await self.http.get(
            f"/threads/{thread_id}", headers=headers, params=params
@@ -1309,7 +1297,7 @@ class ThreadsClient:
                if_exists="raise"
            )
            ```
-        """
+        """  # noqa: E501
        payload: dict[str, Any] = {}
        if thread_id:
            payload["thread_id"] = thread_id
@@ -1377,7 +1365,7 @@ class ThreadsClient:
                ttl=43_200,
            )
            ```
-        """
+        """  # noqa: E501
        payload: dict[str, Any] = {"metadata": metadata}
        if ttl is not None:
            if isinstance(ttl, (int, float)):
@@ -1417,7 +1405,7 @@ class ThreadsClient:
            )
            ```

-        """
+        """  # noqa: E501
        await self.http.delete(f"/threads/{thread_id}", headers=headers, params=params)

    async def search(
@@ -1465,7 +1453,7 @@ class ThreadsClient:
            )
            ```

-        """
+        """  # noqa: E501
        payload: dict[str, Any] = {
            "limit": limit,
            "offset": offset,
@@ -1549,7 +1537,7 @@ class ThreadsClient:
            )
            ```

-        """
+        """  # noqa: E501
        return await self.http.post(
            f"/threads/{thread_id}/copy", json=None, headers=headers, params=params
        )
@@ -1663,7 +1651,7 @@ class ThreadsClient:
                    }
            }
            ```
-        """
+        """  # noqa: E501
        if checkpoint:
            return await self.http.post(
                f"/threads/{thread_id}/state/checkpoint",
@@ -1739,7 +1727,7 @@ class ThreadsClient:
                }
            }
            ```
-        """
+        """  # noqa: E501
        payload: dict[str, Any] = {
            "values": values,
        }
@@ -1788,7 +1776,7 @@ class ThreadsClient:
            )
            ```

-        """
+        """  # noqa: E501
        payload: dict[str, Any] = {
            "limit": limit,
        }
@@ -1836,7 +1824,7 @@ class ThreadsClient:
                print(chunk)
            ```

-        """
+        """  # noqa: E501
        query_params = {
            "stream_mode": stream_mode,
        }
@@ -2031,7 +2019,7 @@ class RunsClient:
            StreamPart(event='end', data=None)
            ```

-        """
+        """  # noqa: E501
        if checkpoint_during is not None:
            warnings.warn(
                "`checkpoint_during` is deprecated and will be removed in a future version. Use `durability` instead.",
@@ -2277,7 +2265,7 @@ class RunsClient:
                'multitask_strategy': 'interrupt'
            }
            ```
-        """
+        """  # noqa: E501
        if checkpoint_during is not None:
            warnings.warn(
                "`checkpoint_during` is deprecated and will be removed in a future version. Use `durability` instead.",
@@ -2505,7 +2493,7 @@ class RunsClient:
            }
            ```

-        """
+        """  # noqa: E501
        if checkpoint_during is not None:
            warnings.warn(
                "`checkpoint_during` is deprecated and will be removed in a future version. Use `durability` instead.",
@@ -2597,7 +2585,7 @@ class RunsClient:
            )
            ```

-        """
+        """  # noqa: E501
        query_params: dict[str, Any] = {
            "limit": limit,
            "offset": offset,
@@ -2641,7 +2629,7 @@ class RunsClient:
            )
            ```

-        """
+        """  # noqa: E501

        return await self.http.get(
            f"/threads/{thread_id}/runs/{run_id}", headers=headers, params=params
@@ -2683,7 +2671,7 @@ class RunsClient:
            )
            ```

-        """
+        """  # noqa: E501
        query_params = {
            "wait": 1 if wait else 0,
            "action": action,
@@ -2734,7 +2722,7 @@ class RunsClient:
            )
            ```

-        """
+        """  # noqa: E501
        return await self.http.request_reconnect(
            f"/threads/{thread_id}/runs/{run_id}/join",
            "GET",
@@ -2783,7 +2771,7 @@ class RunsClient:
                print(part)
            ```

-        """
+        """  # noqa: E501
        query_params = {
            "cancel_on_disconnect": cancel_on_disconnect,
            "stream_mode": stream_mode,
@@ -2830,7 +2818,7 @@ class RunsClient:
            )
            ```

-        """
+        """  # noqa: E501
        await self.http.delete(
            f"/threads/{thread_id}/runs/{run_id}", headers=headers, params=params
        )
@@ -2925,7 +2913,7 @@ class CronClient:
                multitask_strategy="interrupt"
            )
            ```
-        """
+        """  # noqa: E501
        payload = {
            "schedule": schedule,
            "input": input,
@@ -3005,7 +2993,7 @@ class CronClient:
            )
            ```

-        """
+        """  # noqa: E501
        payload = {
            "schedule": schedule,
            "input": input,
@@ -3051,7 +3039,7 @@ class CronClient:
            )
            ```

-        """
+        """  # noqa: E501
        await self.http.delete(f"/runs/crons/{cron_id}", headers=headers, params=params)

    async def search(
@@ -3117,7 +3105,7 @@ class CronClient:
            ]
            ```

-        """
+        """  # noqa: E501
        payload = {
            "assistant_id": assistant_id,
            "thread_id": thread_id,
@@ -3509,7 +3497,7 @@ def get_sync_client(
        base_url=url,
        transport=transport,
        timeout=(
-            httpx.Timeout(timeout)  # ty: ignore[invalid-argument-type]
+            httpx.Timeout(timeout)
            if timeout is not None
            else httpx.Timeout(connect=5, read=300, write=300, pool=5)
        ),
@@ -3789,7 +3777,7 @@ class SyncHttpClient:
                decoder = SSEDecoder()
                try:
                    for line in iter_lines_raw(res):
-                        sse = decoder.decode(cast(bytes, line).rstrip(b"\n"))
+                        sse = decoder.decode(line.rstrip(b"\n"))
                        if sse is not None:
                            if decoder.last_event_id is not None:
                                last_event_id = decoder.last_event_id
@@ -3892,7 +3880,7 @@ class SyncAssistantsClient:
            }
            ```

-        """
+        """  # noqa: E501
        return self.http.get(
            f"/assistants/{assistant_id}", headers=headers, params=params
        )
@@ -3942,7 +3930,7 @@ class SyncAssistantsClient:
            }
            ```

-        """
+        """  # noqa: E501
        query_params = {"xray": xray}
        if params:
            query_params.update(params)
@@ -4078,7 +4066,7 @@ class SyncAssistantsClient:
            }
            ```

-        """
+        """  # noqa: E501
        return self.http.get(
            f"/assistants/{assistant_id}/schemas", headers=headers, params=params
        )
@@ -4102,7 +4090,7 @@ class SyncAssistantsClient:
        Returns:
            Subgraphs: The graph schema for the assistant.

-        """
+        """  # noqa: E501
        get_params = {"recurse": recurse}
        if params:
            get_params = {**get_params, **params}
@@ -4168,7 +4156,7 @@ class SyncAssistantsClient:
                name="my_name"
            )
            ```
-        """
+        """  # noqa: E501
        payload: dict[str, Any] = {
            "graph_id": graph_id,
        }
@@ -4234,7 +4222,7 @@ class SyncAssistantsClient:
                metadata={"number":2}
            )
            ```
-        """
+        """  # noqa: E501
        payload: dict[str, Any] = {}
        if graph_id:
            payload["graph_id"] = graph_id
@@ -4281,7 +4269,7 @@ class SyncAssistantsClient:
            )
            ```

-        """
+        """  # noqa: E501
        self.http.delete(f"/assistants/{assistant_id}", headers=headers, params=params)

    def search(
@@ -4402,7 +4390,7 @@ class SyncAssistantsClient:
            )
            ```

-        """
+        """  # noqa: E501

        payload: dict[str, Any] = {
            "limit": limit,
@@ -4445,7 +4433,7 @@ class SyncAssistantsClient:
            )
            ```

-        """
+        """  # noqa: E501

        payload: dict[str, Any] = {"version": version}

@@ -4510,7 +4498,7 @@ class SyncThreadsClient:
            }
            ```

-        """
+        """  # noqa: E501

        return self.http.get(f"/threads/{thread_id}", headers=headers, params=params)

@@ -4556,7 +4544,7 @@ class SyncThreadsClient:
            )
            ```
            )
-        """
+        """  # noqa: E501
        payload: dict[str, Any] = {}
        if thread_id:
            payload["thread_id"] = thread_id
@@ -4622,7 +4610,7 @@ class SyncThreadsClient:
                ttl=43_200,
            )
            ```
-        """
+        """  # noqa: E501
        payload: dict[str, Any] = {"metadata": metadata}
        if ttl is not None:
            if isinstance(ttl, (int, float)):
@@ -4661,7 +4649,7 @@ class SyncThreadsClient:
            )
            ```

-        """
+        """  # noqa: E501
        self.http.delete(f"/threads/{thread_id}", headers=headers, params=params)

    def search(
@@ -4705,7 +4693,7 @@ class SyncThreadsClient:
                offset=5
            )
            ```
-        """
+        """  # noqa: E501
        payload: dict[str, Any] = {
            "limit": limit,
            "offset": offset,
@@ -4786,7 +4774,7 @@ class SyncThreadsClient:
            )
            ```

-        """
+        """  # noqa: E501
        return self.http.post(
            f"/threads/{thread_id}/copy", json=None, headers=headers, params=params
        )
@@ -4899,7 +4887,7 @@ class SyncThreadsClient:
            }
            ```

-        """
+        """  # noqa: E501
        if checkpoint:
            return self.http.post(
                f"/threads/{thread_id}/state/checkpoint",
@@ -4972,7 +4960,7 @@ class SyncThreadsClient:
            }
            ```

-        """
+        """  # noqa: E501
        payload: dict[str, Any] = {
            "values": values,
        }
@@ -5022,7 +5010,7 @@ class SyncThreadsClient:
            )
            ```

-        """
+        """  # noqa: E501
        payload: dict[str, Any] = {
            "limit": limit,
        }
@@ -5071,7 +5059,7 @@ class SyncThreadsClient:
                print(chunk)
            ```

-        """
+        """  # noqa: E501
        query_params = {
            "stream_mode": stream_mode,
        }
@@ -5263,7 +5251,7 @@ class SyncRunsClient:
            StreamPart(event='values', data={'messages': [{'content': 'how are you?', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'human', 'name': None, 'id': 'fe0a5778-cfe9-42ee-b807-0adaa1873c10', 'example': False}, {'content': "I'm doing well, thanks for asking! I'm an AI assistant created by Anthropic to be helpful, honest, and harmless.", 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-159b782c-b679-4830-83c6-cef87798fe8b', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}]})
            StreamPart(event='end', data=None)
            ```
-        """
+        """  # noqa: E501
        if checkpoint_during is not None:
            warnings.warn(
                "`checkpoint_during` is deprecated and will be removed in a future version. Use `durability` instead.",
@@ -5508,7 +5496,7 @@ class SyncRunsClient:
                'multitask_strategy': 'interrupt'
            }
            ```
-        """
+        """  # noqa: E501
        if checkpoint_during is not None:
            warnings.warn(
                "`checkpoint_during` is deprecated and will be removed in a future version. Use `durability` instead.",
@@ -5738,7 +5726,7 @@ class SyncRunsClient:
            }
            ```

-        """
+        """  # noqa: E501
        if checkpoint_during is not None:
            warnings.warn(
                "`checkpoint_during` is deprecated and will be removed in a future version. Use `durability` instead.",
@@ -5820,7 +5808,7 @@ class SyncRunsClient:
            )
            ```

-        """
+        """  # noqa: E501
        query_params: dict[str, Any] = {"limit": limit, "offset": offset}
        if status is not None:
            query_params["status"] = status
@@ -5859,7 +5847,7 @@ class SyncRunsClient:
                run_id="run_id_to_delete",
            )
            ```
-        """
+        """  # noqa: E501

        return self.http.get(
            f"/threads/{thread_id}/runs/{run_id}", headers=headers, params=params
@@ -5901,7 +5889,7 @@ class SyncRunsClient:
            )
            ```

-        """
+        """  # noqa: E501
        query_params = {
            "wait": 1 if wait else 0,
            "action": action,
@@ -5952,7 +5940,7 @@ class SyncRunsClient:
            )
            ```

-        """
+        """  # noqa: E501
        return self.http.request_reconnect(
            f"/threads/{thread_id}/runs/{run_id}/join",
            "GET",
@@ -6000,7 +5988,7 @@ class SyncRunsClient:
            )
            ```

-        """
+        """  # noqa: E501
        query_params = {
            "stream_mode": stream_mode,
            "cancel_on_disconnect": cancel_on_disconnect,
@@ -6047,7 +6035,7 @@ class SyncRunsClient:
            )
            ```

-        """
+        """  # noqa: E501
        self.http.delete(
            f"/threads/{thread_id}/runs/{run_id}", headers=headers, params=params
        )
@@ -6133,7 +6121,7 @@ class SyncCronClient:
                multitask_strategy="interrupt"
            )
            ```
-        """
+        """  # noqa: E501
        payload = {
            "schedule": schedule,
            "input": input,
@@ -6212,7 +6200,7 @@ class SyncCronClient:
            )
            ```

-        """
+        """  # noqa: E501
        payload = {
            "schedule": schedule,
            "input": input,
@@ -6257,7 +6245,7 @@ class SyncCronClient:
            )
            ```

-        """
+        """  # noqa: E501
        self.http.delete(f"/runs/crons/{cron_id}", headers=headers, params=params)

    def search(
@@ -6321,7 +6309,7 @@ class SyncCronClient:
                }
            ]
            ```
-        """
+        """  # noqa: E501
        payload = {
            "assistant_id": assistant_id,
            "thread_id": thread_id,
@@ -24,28 +24,19 @@ class APIError(httpx.HTTPStatusError, LangGraphError):
    type: str | None

    def __init__(
-        self,
-        message: str,
-        response_or_request: httpx.Response | httpx.Request,
-        *,
-        body: object | None,
+        self, message: str, response: httpx.Response, *, body: object | None
    ) -> None:
-        if isinstance(response_or_request, httpx.Response):
-            req = response_or_request.request
-            response = response_or_request
-        else:
-            req = response_or_request
-            response = None
-
-        httpx.HTTPStatusError.__init__(self, message, request=req, response=response)  # type: ignore[arg-type]
+        httpx.HTTPStatusError.__init__(
+            self, message, request=response.request, response=response
+        )
        LangGraphError.__init__(self)

-        self.request = req
+        self.request = response.request
        self.message = message
        self.body = body

        if isinstance(body, dict):
-            b = cast("dict[str, Any]", body)
+            b = cast(dict[str, Any], body)
            # Best-effort extraction of common fields if present
            code_val = b.get("code")
            self.code = code_val if isinstance(code_val, str) else None
@@ -97,7 +88,7 @@ class APIConnectionError(APIError):
    def __init__(
        self, *, message: str = "Connection error.", request: httpx.Request
    ) -> None:
-        super().__init__(message, response_or_request=request, body=None)
+        super().__init__(message, request, body=None)


 class APITimeoutError(APIConnectionError):
@@ -139,7 +130,7 @@ class InternalServerError(APIStatusError):

 def _extract_error_message(body: object | None, fallback: str) -> str:
    if isinstance(body, dict):
-        b = cast("dict[str, Any]", body)
+        b = cast(dict[str, Any], body)
        for key in ("message", "detail", "error"):
            val = b.get(key)
            if isinstance(val, str) and val:
@@ -147,7 +138,7 @@ def _extract_error_message(body: object | None, fallback: str) -> str:
        # Sometimes errors are structured like {"error": {"message": "..."}}
        err = b.get("error")
        if isinstance(err, dict):
-            e = cast("dict[str, Any]", err)
+            e = cast(dict[str, Any], err)
            for key in ("message", "detail"):
                val = e.get(key)
                if isinstance(val, str) and val:
@@ -205,7 +196,7 @@ def _map_status_error(response: httpx.Response, body: object | None) -> APIStatu
        return UnprocessableEntityError(message, response=response, body=body)
    if status == 429:
        return RateLimitError(message, response=response, body=body)
-    if status >= 500:
+    if 500 <= status:
        return InternalServerError(message, response=response, body=body)
    return APIStatusError(message, response=response, body=body)

@@ -2,9 +2,7 @@

 from __future__ import annotations

-import contextlib
 from collections.abc import AsyncIterator, Iterator
-from typing import cast

 import httpx
 import orjson
@@ -44,7 +42,7 @@ class BytesLineDecoder:
            return []  # pragma: no cover

        trailing_newline = text[-1] in NEWLINE_CHARS
-        lines = cast(list[BytesLike], text.splitlines())
+        lines = text.splitlines()

        if len(lines) == 1 and not trailing_newline:
            # No new lines, buffer the input and continue.
@@ -55,7 +53,7 @@ class BytesLineDecoder:
            # Include any existing buffer in the first portion of the
            # splitlines result.
            self.buffer.extend(lines[0])
-            lines = cast(list[BytesLike], [self.buffer, *lines[1:]])
+            lines = [self.buffer] + lines[1:]
            self.buffer = bytearray()

        if not trailing_newline:
@@ -89,7 +87,7 @@ class SSEDecoder:
        return self._last_event_id or None

    def decode(self, line: bytes) -> StreamPart | None:
-        # See: https://html.spec.whatwg.org/multipage/server-sent-events.html#event-stream-interpretation
+        # See: https://html.spec.whatwg.org/multipage/server-sent-events.html#event-stream-interpretation  # noqa: E501

        if not line:
            if (
@@ -130,8 +128,10 @@ class SSEDecoder:
            else:
                self._last_event_id = value.decode()
        elif fieldname == b"retry":
-            with contextlib.suppress(TypeError, ValueError):
+            try:
                self._retry = int(value)
+            except (TypeError, ValueError):
+                pass
        else:
            pass  # Field is ignored.

@@ -11,24 +11,32 @@ requires-python = ">=3.10"
 readme = "README.md"
 license = "MIT"
 license-files = ['LICENSE']
-dependencies = ["httpx>=0.25.2", "orjson>=3.10.1"]
+dependencies = [
+    "httpx>=0.25.2",
+    "orjson>=3.10.1",
+]

 [tool.hatch.version]
 path = "langgraph_sdk/__init__.py"

 [project.urls]
-Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/sdk-py"
-Twitter = "https://x.com/LangChainAI"
-Slack = "https://www.langchain.com/join-community"
-Reddit = "https://www.reddit.com/r/LangChain/"
+Repository = "https://www.github.com/langchain-ai/langgraph"

 [dependency-groups]
-test = ["pytest", "pytest-asyncio", "pytest-mock", "pytest-watch"]
-lint = ["ruff", "codespell", "mypy"]
+test = [
+  "pytest",
+  "pytest-asyncio",
+  "pytest-mock",
+  "pytest-watch",
+]
+lint = [
+  "ruff",
+  "codespell",
+  "mypy",
+]
 dev = [
-  { include-group = "test" },
-  { include-group = "lint" },
-  "pydantic>=2.12.4",
+  {include-group = "test"},
+  {include-group = "lint"},
 ]

 [tool.hatch.build.targets.wheel]
@@ -42,29 +50,14 @@ asyncio_mode = "auto"
 default-groups = ['dev']

 [tool.ruff]
-exclude = ["venv", ".venv", "build", "dist"]
-[tool.ruff.lint]
-select = [
-  "E",      # pycodestyle errors
-  "F",      # pyflakes
-  "I",      # isort (import sorting)
-  "ARG",    # unused arguments
-  "TID251", # banned imports
-  "TID252", # banned relative imports
-  "T20",    # print statements
-  "UP",     # pyupgrade (Python version-specific fixes)
-  "B",      # flake8-bugbear (common bugs)
-  "SIM",    # flake8-simplify (code simplification)
-  "RUF",    # ruff-specific rules
-  "S101",   # flake8-bandit: use of assert
+lint.select = [
+  "E",  # pycodestyle
+  "F",  # Pyflakes
+  "UP", # pyupgrade
+  "B",  # flake8-bugbear
+  "I",  # isort
+  "ARG", # flake8-unused-arguments
+  "UP", # pyupgrade
 ]
-ignore = [
-  "E501",   # line too long (handled by formatter)
-  "B006",   # mutable default arguments (sometimes intentional)
-  "B904",   # raise without from inside except (sometimes intentional)
-  "SIM102", # nested if statements (sometimes clearer)
-]
-per-file-ignores = { "tests/**" = ["S101", "B017"] }
-
-[tool.ty.rules]
-no-matching-overload = "ignore"
+lint.ignore = ["E501", "B008"]
+target-version = "py310"
@@ -71,8 +71,8 @@ def test_sync_api_matches_async(async_cls, sync_cls):
        sync_fn = sync_methods[name]

        # Use inspect.signature for parameter names (robust across versions)
-        async_sig = _strip_self(inspect.signature(async_fn))  # type: ignore
-        sync_sig = _strip_self(inspect.signature(sync_fn))  # type: ignore
+        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())
@@ -59,7 +59,7 @@ def test_stream_see():

        decoder = SSEDecoder()
        for line in iter_lines_raw(groups):
-            sse = decoder.decode(line=line.rstrip(b"\n"))  # type: ignore
+            sse = decoder.decode(line=line.rstrip(b"\n"))
            if sse is not None:
                parts.append(sse)
        if sse := decoder.decode(b""):
@@ -152,7 +152,7 @@ def test_sync_http_client_stream_recovers_after_disconnect():
    assert parts == [
        StreamPart(event="values", data={"step": 1}),
        StreamPart(event="values", data={"step": 2}),
-        StreamPart(event="end", data=None),  # ty: ignore
+        StreamPart(event="end", data=None),
    ]


@@ -65,7 +65,7 @@ def test_raise_for_status_typed_maps_exceptions_and_sets_status_code(
    with pytest.raises(exc_type) as ei:
        _raise_for_status_typed(r)

-    err = cast("APIStatusError", ei.value)
+    err = cast(APIStatusError, ei.value)
    assert err.status_code == status
    # response attribute should be present and match
    assert err.response.status_code == status
@@ -77,7 +77,7 @@ def test_request_id_is_extracted_when_present() -> None:
    )
    with pytest.raises(NotFoundError) as ei:
        _raise_for_status_typed(r)
-    err = cast("APIStatusError", ei.value)
+    err = cast(APIStatusError, ei.value)
    # request_id only exists on APIStatusError subclasses
    assert err.request_id == "req-123"

@@ -86,7 +86,7 @@ def test_non_json_body_does_not_break_mapping() -> None:
    r = make_response(429, text_body="Too many requests")
    with pytest.raises(RateLimitError) as ei:
        _raise_for_status_typed(r)
-    err = cast("APIStatusError", ei.value)
+    err = cast(APIStatusError, ei.value)
    assert err.status_code == 429


@@ -102,7 +102,7 @@ def test_field_extraction_from_json_body() -> None:
    )
    with pytest.raises(BadRequestError) as ei:
        _raise_for_status_typed(r)
-    err = cast("APIStatusError", ei.value)
+    err = cast(APIStatusError, ei.value)
    assert err.code == "invalid_param"
    assert err.param == "limit"
    assert err.type == "invalid_request_error"
@@ -1,40 +0,0 @@
-from typing import Any
-
-import orjson
-import pytest
-from pydantic import BaseModel
-
-from langgraph_sdk.client import _aencode_json
-
-
-async def _serde_roundtrip(data: Any):
-    _, body = await _aencode_json(data)
-    return orjson.loads(body)  # ty: ignore[invalid-argument-type]
-
-
-async def test_serde_basic():
-    # Test basic serialization
-    data = {"key": "value", "number": 42}
-    assert await _serde_roundtrip(data) == data
-
-
-async def test_serde_pydantic():
-    # Test serialization with Pydantic model (if available)
-
-    class TestModel(BaseModel):
-        name: str
-        age: int
-
-    model = TestModel(name="test", age=25)
-    result = await _serde_roundtrip(model)
-    assert result["name"] == "test"
-    assert result["age"] == 25
-
-
-async def test_serde_pydantic_cls_fails():
-    # Test that serialization fails gracefully for Pydantic model when not available
-    class TestModel(BaseModel):
-        name: str
-
-    with pytest.raises(TypeError, match="Type is not JSON serializable"):
-        await _serde_roundtrip({"foo": TestModel})
@@ -1,16 +1,7 @@
 version = 1
-revision = 3
+revision = 2
 requires-python = ">=3.10"

-[[package]]
-name = "annotated-types"
-version = "0.7.0"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/ee/67/531ea369ba64dcff5ec9c3402f9f51bf748cec26dde048a2f973a4eea7f5/annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89", size = 16081, upload-time = "2024-05-20T21:33:25.928Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643, upload-time = "2024-05-20T21:33:24.1Z" },
-]
-
 [[package]]
 name = "anyio"
 version = "4.11.0"
@@ -37,11 +28,11 @@ wheels = [

 [[package]]
 name = "certifi"
-version = "2025.11.12"
+version = "2025.8.3"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/a2/8c/58f469717fa48465e4a50c014a0400602d3c437d7c0c468e17ada824da3a/certifi-2025.11.12.tar.gz", hash = "sha256:d8ab5478f2ecd78af242878415affce761ca6bc54a22a27e026d7c25357c3316", size = 160538, upload-time = "2025-11-12T02:54:51.517Z" }
+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 = [
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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" },
 ]

 [[package]]
@@ -119,20 +110,20 @@ wheels = [

 [[package]]
 name = "idna"
-version = "3.11"
+version = "3.10"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/6f/6d/0703ccc57f3a7233505399edb88de3cbd678da106337b9fcde432b65ed60/idna-3.11.tar.gz", hash = "sha256:795dafcc9c04ed0c1fb032c2aa73654d8e8c5023a7df64a53f39190ada629902", size = 194582, upload-time = "2025-10-12T14:55:20.501Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/f1/70/7703c29685631f5a7590aa73f1f1d3fa9a380e654b86af429e0934a32f7d/idna-3.10.tar.gz", hash = "sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9", size = 190490, upload-time = "2024-09-15T18:07:39.745Z" }
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/76/c6/c88e154df9c4e1a2a66ccf0005a88dfb2650c1dffb6f5ce603dfbd452ce3/idna-3.10-py3-none-any.whl", hash = "sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3", size = 70442, upload-time = "2024-09-15T18:07:37.964Z" },
 ]

 [[package]]
 name = "iniconfig"
-version = "2.3.0"
+version = "2.1.0"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/72/34/14ca021ce8e5dfedc35312d08ba8bf51fdd999c576889fc2c24cb97f4f10/iniconfig-2.3.0.tar.gz", hash = "sha256:c76315c77db068650d49c5b56314774a7804df16fee4402c1f19d6d15d8c4730", size = 20503, upload-time = "2025-10-18T21:55:43.219Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/f2/97/ebf4da567aa6827c909642694d71c9fcf53e5b504f2d96afea02718862f3/iniconfig-2.1.0.tar.gz", hash = "sha256:3abbd2e30b36733fee78f9c7f7308f2d0050e88f0087fd25c2645f63c773e1c7", size = 4793, upload-time = "2025-03-19T20:09:59.721Z" }
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/2c/e1/e6716421ea10d38022b952c159d5161ca1193197fb744506875fbb87ea7b/iniconfig-2.1.0-py3-none-any.whl", hash = "sha256:9deba5723312380e77435581c6bf4935c94cbfab9b1ed33ef8d238ea168eb760", size = 6050, upload-time = "2025-03-19T20:10:01.071Z" },
 ]

 [[package]]
@@ -147,7 +138,6 @@ dependencies = [
 dev = [
    { name = "codespell" },
    { name = "mypy" },
-    { name = "pydantic" },
    { name = "pytest" },
    { name = "pytest-asyncio" },
    { name = "pytest-mock" },
@@ -176,7 +166,6 @@ requires-dist = [
 dev = [
    { name = "codespell" },
    { name = "mypy" },
-    { name = "pydantic", specifier = ">=2.12.4" },
    { name = "pytest" },
    { name = "pytest-asyncio" },
    { name = "pytest-mock" },
@@ -251,83 +240,79 @@ wheels = [

 [[package]]
 name = "orjson"
-version = "3.11.4"
+version = "3.11.3"
 source = { registry = "https://pypi.org/simple" }
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-
 [[package]]
 name = "watchdog"
 version = "6.0.0"
@@ -0,0 +1,106 @@
+"""Test to reproduce the tool error fallback issue.
+
+When using ToolNode(...).with_fallbacks(...) with an error handler that returns
+ToolMessage objects, the messages are losing:
+1. The `name` field (becomes `None` instead of the tool name)
+2. The `status` field (becomes `success` instead of `error`)
+"""
+
+from unittest.mock import Mock
+
+from langchain_core.messages import AIMessage, ToolMessage
+from langchain_core.runnables import RunnableLambda
+from langchain_core.runnables.config import RunnableConfig
+from langchain_core.tools import tool
+
+from langgraph.prebuilt import ToolNode
+
+
+def _create_mock_runtime():
+    """Create a mock Runtime object for testing ToolNode outside of graph context."""
+    mock_runtime = Mock()
+    mock_runtime.store = None
+    mock_runtime.context = None
+    mock_runtime.stream_writer = lambda *args, **kwargs: None
+    return mock_runtime
+
+
+def _create_config_with_runtime() -> RunnableConfig:
+    """Create a RunnableConfig with mock Runtime for testing ToolNode."""
+    return {"configurable": {"__pregel_runtime": _create_mock_runtime()}}
+
+
+@tool
+def failing_tool(x: int) -> str:
+    """A tool that always fails."""
+    raise RuntimeError("This tool always fails!")
+
+
+def handle_tool_error(state) -> dict:
+    """Error handler that returns ToolMessages."""
+    print(f"handle_tool_error called with state: {state}")
+    print(f"State type: {type(state)}")
+    print(f"State keys: {state.keys() if isinstance(state, dict) else 'N/A'}")
+    error = state.get("error")
+    print(f"Error: {error}")
+    tool_calls = state["messages"][-1].tool_calls
+    print(f"Tool calls: {tool_calls}")
+    return {
+        "messages": [
+            ToolMessage(
+                content=f"Error: {repr(error)}\n please fix your mistakes.",
+                tool_call_id=tc["id"],
+            )
+            for tc in tool_calls
+        ]
+    }
+
+
+fallback_runnable = RunnableLambda(handle_tool_error)
+
+
+def test_tool_error_with_fallbacks():
+    """Test that ToolMessages from fallback handlers preserve name and status."""
+    # Create a ToolNode with a fallback
+    tool_node = ToolNode([failing_tool], handle_tool_errors=True).with_fallbacks(
+        [fallback_runnable],
+    )
+
+    # Create an AI message with a tool call
+    messages = [
+        AIMessage(
+            content="",
+            tool_calls=[
+                {
+                    "name": "failing_tool",
+                    "args": {"x": 1},
+                    "id": "call_123",
+                    "type": "tool_call",
+                }
+            ],
+        )
+    ]
+
+    # Invoke the tool node
+    result = tool_node.invoke({"messages": messages}, config=_create_config_with_runtime())
+
+    print("Result:", result)
+    print("Result type:", type(result))
+    print("Result keys:", result.keys() if isinstance(result, dict) else "N/A")
+    print("\nTool messages:")
+    for msg in result["messages"]:
+        if isinstance(msg, ToolMessage):
+            print(f"  - content: {msg.content[:50]}...")
+            print(f"    name: {msg.name}")
+            print(f"    tool_call_id: {msg.tool_call_id}")
+            print(f"    status: {msg.status}")
+            print()
+
+            # Check expectations
+            assert msg.name == "failing_tool", f"Expected name='failing_tool', got {msg.name}"
+            assert msg.status == "error", f"Expected status='error', got {msg.status}"
+            print("✓ Test passed!")
+
+
+if __name__ == "__main__":
+    test_tool_error_with_fallbacks()