fix(cli): add buildkit syntax directiive, update tests (#6385 )

**Description:** Adds the syntax directive to generated dockerfile for langgraph builds if we have additional contexts **Issue:** fixes issue with python monorepo builds failing **Dependencies:** N/A
chore: Update cli config schema (#6372 )
2026-08-18 05:35:43 +02:00 · 2025-11-03 18:13:19 +00:00 · 2025-11-01 09:50:46 -07:00 · 2025-10-31 14:12:59 -04:00 · 2025-10-30 17:59:40 -04:00 · 2025-10-29 18:34:28 +00:00
53 changed files with 5898 additions and 1463 deletions
@@ -1,21 +1,21 @@
 name: "\U0001F41B Bug Report"
 description: Report a bug in LangGraph. To report a security issue, please instead use the security option below. For questions, please use the LangChain Forum at forum.langchain.com.
-labels: [pending,bug]
+labels: [pending, bug]
 body:
  - type: markdown
    attributes:
      value: |
        Thank you for taking the time to file a bug report. 
-        
+
        Use this to report BUGS in LangGraph. For usage questions, feature requests and general design questions, please use the [LangChain Forum](https://forum.langchain.com/).
-        
+
        Relevant links to check before filing a bug report to see if your issue has already been reported, fixed or
        if there's another way to solve your problem:
-        
+
        * [LangChain Forum](https://forum.langchain.com/),
        * [LangGraph Github Issues](https://github.com/langchain-ai/langgraph/issues),
        * [LangGraph how-to guides](https://langchain-ai.github.io/langgraph/how-tos/).
-        * [LangChain documentation with the integrated search](https://python.langchain.com/docs/get_started/introduction),
+        * [LangChain documentation with the integrated search](https://docs.langchain.com/),
        * [GitHub search](https://github.com/langchain-ai/langgraph),
  - type: checkboxes
    id: checks
@@ -1,7 +1,8 @@
+import logging
 import pathlib
 import sys
 import time
-from urllib import request, error
+from urllib import error, request

 import langgraph_cli
 import langgraph_cli.config
@@ -11,9 +12,13 @@ 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)
@@ -57,7 +62,9 @@ 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:
@@ -93,7 +100,7 @@ def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
        set("")
        base_url = f"http://localhost:{port}"
        ok_url = f"{base_url}/ok"
-        print(f"Waiting for {ok_url} to respond with 200...")
+        logger.info(f"Waiting for {ok_url} to respond with 200...")
        deadline = time.time() + 30
        last_err: Exception | None = None
        while time.time() < deadline:
@@ -107,13 +114,16 @@ def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
                        break
                    else:
                        last_err = RuntimeError(f"Unexpected status: {resp.status}")
-                        print(f"Unexpected status: {resp.status}")
+                        logger.error(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:
@@ -131,15 +141,23 @@ def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
                )

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


 if __name__ == "__main__":
@@ -150,4 +168,10 @@ 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()
-    test(pathlib.Path(args.config), args.port, args.tag, verbose=True)
+    try:
+        test(pathlib.Path(args.config), args.port, args.tag, verbose=True)
+    except BaseException:
+        logger.exception("Test failed")
+        raise
+    
+    logger.info("Test execution finished")
@@ -13,7 +13,6 @@ jobs:
      matrix:
        python-version:
          - "3.10"
-          - "3.11"
          - "3.14"
        example:
          - name: A
@@ -67,19 +66,19 @@ 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
+        if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
        working-directory: libs/cli/js-examples
        run: |
          langgraph build -t langgraph-test-e

      - name: Build JS monorepo service
-        if: steps.changed-files.outputs.all
+        if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
        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
+        if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
        working-directory: libs/cli/python-monorepo-example
        run: |
          langgraph build -t langgraph-test-g -c apps/agent/langgraph.json
@@ -88,24 +87,32 @@ 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
+        if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
        working-directory: libs/cli/examples/graph_prerelease_reqs
        run: |
          langgraph build -t langgraph-test-h
          cp ../.env.example .env
          if [ -n "${{ 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 [ "$LANGGRAPH_VERSION" != "1.0.0a2" ]; then
+          if [ "$LANGGRAPH_VERSION" != "1.0.2" ]; then
+            echo "LANGGRAPH_VERSION != 1.0.2; $LANGGRAPH_VERSION"
            exit 1
          fi
          LANGCHAIN_OPENAI_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langchain-openai'); print(v);")
-          if [ "$LANGCHAIN_OPENAI_VERSION" != "0.3.0" ]; then
+          if [ "$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"
            exit 1
          fi

      - name: Build and test prerelease reqs fail service
-        if: steps.changed-files.outputs.all
+        if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
        working-directory: libs/cli/examples/graph_prerelease_reqs_fail
        run: |
          langgraph build -t langgraph-test-i || [ $? -eq 1 ]
@@ -48,7 +48,7 @@ jobs:
        working-directory: ${{ inputs.working-directory }}

      - name: Upload build
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@v5
        with:
          name: test-dist
          path: ${{ inputs.working-directory }}/dist/
@@ -76,7 +76,7 @@ jobs:
    steps:
      - uses: actions/checkout@v5

-      - uses: actions/download-artifact@v5
+      - uses: actions/download-artifact@v6
        with:
          name: test-dist
          path: ${{ inputs.working-directory }}/dist/
@@ -1,12 +1,9 @@
-name: Deploy Docs
+name: Deploy Docs Redirects

 on:
  push:
    branches:
      - main
-  pull_request:
-    branches:
-      - main
  workflow_dispatch:

 permissions:
@@ -23,18 +20,6 @@ defaults:
    working-directory: docs

 jobs:
-  get-changed-files:
-    runs-on: ubuntu-latest
-    outputs:
-      changed-files: ${{ steps.changed-files.outputs.added_modified }}
-    steps:
-      - uses: actions/checkout@v5
-      - name: Get changed files
-        id: changed-files
-        uses: Ana06/get-changed-files@v2.3.0
-        with:
-          filter: "docs/docs/**"
-
  deploy:
    runs-on: ubuntu-latest
    timeout-minutes: 10 # Job will be cancelled if it runs for more than 10 minutes
@@ -62,84 +47,21 @@ jobs:
            uv run pip install "git+https://${GITHUB_TOKEN}@github.com/langchain-ai/mkdocs-material-insiders.git"
          fi

-      - name: Run unit tests
-        # Run unit tests on the docs build pipeline
-        run: make tests
-      - name: Lint Docs
-        # This step lints the docs using the existing linting set up.
-        # It should be very fast and should not require any external services.
-        run: make lint-docs
      - name: Build llms-text
        run: make llms-text
-      - name: Build site
-        run: |
-          # If this is main branch, then we want to download stats. we do this 
-          # with the env variable DOWNLOAD_STATS=true
-          if [ "${{ github.ref }}" == "refs/heads/main" ]; then
-            DOWNLOAD_STATS=true make build-docs
-          else
-            make build-docs
-          fi
+
+      - name: Build site (redirects only)
+        run: make build-docs
        env:
-          MKDOCS_GIT_COMMITTERS_APIKEY: ${{ secrets.MKDOCS_GIT_COMMITTERS_APIKEY }}
          OPENAI_API_KEY: sf-proj-1234567890 # fake placeholder, shouldn't actually be used
          ANTHROPIC_API_KEY: sk-ant-api03-1234567890 # fake placeholder, shouldn't actually be used
-      - name: Check links in notebooks
-        env:
-          LANGCHAIN_API_KEY: test
-        if: github.event_name == 'schedule'
-        run: |
-          if [ "${{ github.event_name }}" == "schedule" ]; then
-            echo "Running link check on all HTML files matching notebooks in docs directory..."
-            uv run pytest -v \
-              --check-links-ignore "https://(api|web|docs)\.smith\.langchain\.com/.*" \
-              --check-links-ignore "https://academy\.langchain\.com/.*" \
-              --check-links-ignore "https://x.com/.*" \
-              --check-links-ignore "https://twitter.com/.*" \
-              --check-links-ignore "https://github\.com/.*" \
-              --check-links-ignore "http://localhost:8123/.*" \
-              --check-links-ignore "http://localhost:2024.*" \
-              --check-links-ignore "http://127.0.0.1:.*" \
-              --check-links-ignore "/.*\.(ipynb|html)$" \
-              --check-links-ignore "https://python\.langchain\.com/.*" \
-              --check-links-ignore "https://openai\.com/.*" \
-              --check-links-ignore "https://www\.uber\.com/.*" \
-              --check-links-ignore "https://pepy\.tech/.*" \
-              --check-links-ignore "docs/docs/static/wordmark_*" \
-              --check-links $(find site -name "index.html" | grep -v 'storm/index.html')
-              
-          else
-            echo "Fetching changes from origin/main..."
-            git fetch origin main
-            echo "Checking for changed notebook files..."
-            CHANGED_FILES=$(git diff --name-only --diff-filter=d origin/main | grep 'docs/docs/.*\.ipynb$' | grep -v 'storm.ipynb' | sed -E 's|^docs/docs/|site/|; s/\.ipynb$/\/index.html/' || true)
-            echo "Changed files: ${CHANGED_FILES}"
-            if [ -n "${CHANGED_FILES}" ]; then
-              echo "Running link check on HTML files matching changed notebook files..."
-              uv run pytest -v \
-                --check-links-ignore "https://(api|web|docs)\.smith\.langchain\.com/.*" \
-                --check-links-ignore "https://academy\.langchain\.com/.*" \
-                --check-links-ignore "http://localhost:8123/.*" \
-                --check-links-ignore "http://localhost:2024.*" \
-                --check-links-ignore "http://127.0.0.1:.*" \
-                --check-links-ignore "https://x.com/.*" \
-                --check-links-ignore "https://twitter.com/.*" \
-                --check-links-ignore "https://github\.com/.*" \
-                --check-links-ignore "/.*\.(ipynb|html)$" \
-                --check-links-ignore "docs/docs/static/wordmark_*" \
-                --check-links ${CHANGED_FILES} \
-                || ([ $? = 5 ] && exit 0 || exit $?)
-            else
-              echo "No notebook files changed."
-            fi
-          fi

      - name: Configure GitHub Pages
        if: github.ref == 'refs/heads/main'
        uses: actions/configure-pages@v5

      - name: Upload Pages Artifact
-        # if: github.ref == 'refs/heads/main'
+        if: github.ref == 'refs/heads/main'
        uses: actions/upload-pages-artifact@v4
        with:
          path: ./docs/site/
@@ -50,7 +50,7 @@ jobs:
        working-directory: ${{ inputs.working-directory }}

      - name: Upload build
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@v5
        with:
          name: dist
          path: ${{ inputs.working-directory }}/dist/
@@ -269,7 +269,7 @@ jobs:
          enable-cache: true
          cache-suffix: "release"

-      - uses: actions/download-artifact@v5
+      - uses: actions/download-artifact@v6
        with:
          name: dist
          path: ${{ inputs.working-directory }}/dist/
@@ -310,7 +310,7 @@ jobs:
          enable-cache: true
          cache-suffix: "release"

-      - uses: actions/download-artifact@v5
+      - uses: actions/download-artifact@v6
        with:
          name: dist
          path: ${{ inputs.working-directory }}/dist/
@@ -64,7 +64,7 @@ While LangGraph can be used standalone, it also integrates seamlessly with any L

 - [LangSmith](http://www.langchain.com/langsmith) — Helpful for agent evals and observability. Debug poor-performing LLM app runs, evaluate agent trajectories, gain visibility in production, and improve performance over time.
 - [LangSmith Deployment](https://langchain-ai.github.io/langgraph/concepts/langgraph_platform/) — Deploy and scale agents effortlessly with a purpose-built deployment platform for long running, stateful workflows. Discover, reuse, configure, and share agents across teams — and iterate quickly with visual prototyping in [LangGraph Studio](https://langchain-ai.github.io/langgraph/concepts/langgraph_studio/).
- [LangChain](https://python.langchain.com/docs/introduction/) – Provides integrations and composable components to streamline LLM application development.
+- [LangChain](https://docs.langchain.com/oss/python/langchain/overview) – Provides integrations and composable components to streamline LLM application development.

 > [!NOTE]
 > Looking for the JS version of LangGraph? See the [JS repo](https://github.com/langchain-ai/langgraphjs) and the [JS docs](https://langchain-ai.github.io/langgraphjs/).
@@ -81,4 +81,4 @@ While LangGraph can be used standalone, it also integrates seamlessly with any L

 ## Acknowledgements

-LangGraph is inspired by [Pregel](https://research.google/pubs/pub37252/) and [Apache Beam](https://beam.apache.org/). The public interface draws inspiration from [NetworkX](https://networkx.org/documentation/latest/). LangGraph is built by LangChain Inc, the creators of LangChain, but can be used without LangChain.
+LangGraph is inspired by [Pregel](https://research.google/pubs/pub37252/) and [Apache Beam](https://beam.apache.org/). The public interface draws inspiration from [NetworkX](https://networkx.org/documentation/latest/). LangGraph is built by LangChain Inc, the creators of LangChain, but can be used without LangChain.
@@ -27,66 +27,66 @@ DISABLED = os.getenv("DISABLE_NOTEBOOK_CONVERT") in ("1", "true", "True")

 REDIRECT_MAP = {
    # lib redirects
-    "how-tos/stream-values.ipynb": "how-tos/streaming.md#stream-graph-state",
-    "how-tos/stream-updates.ipynb": "how-tos/streaming.md#stream-graph-state",
-    "how-tos/streaming-content.ipynb": "how-tos/streaming.md",
-    "how-tos/stream-multiple.ipynb": "how-tos/streaming.md#stream-multiple-nodes",
-    "how-tos/streaming-tokens-without-langchain.ipynb": "how-tos/streaming.md#use-with-any-llm",
-    "how-tos/streaming-from-final-node.ipynb": "how-tos/streaming-specific-nodes.ipynb",
-    "how-tos/streaming-events-from-within-tools-without-langchain.ipynb": "how-tos/streaming-events-from-within-tools.ipynb#example-without-langchain",
+    "how-tos/stream-values.ipynb": "https://docs.langchain.com/oss/python/langgraph/streaming",
+    "how-tos/stream-updates.ipynb": "https://docs.langchain.com/oss/python/langgraph/streaming",
+    "how-tos/streaming-content.ipynb": "https://docs.langchain.com/oss/python/langgraph/streaming",
+    "how-tos/stream-multiple.ipynb": "https://docs.langchain.com/oss/python/langgraph/streaming",
+    "how-tos/streaming-tokens-without-langchain.ipynb": "https://docs.langchain.com/oss/python/langgraph/streaming",
+    "how-tos/streaming-from-final-node.ipynb": "https://docs.langchain.com/oss/python/langgraph/streaming",
+    "how-tos/streaming-events-from-within-tools-without-langchain.ipynb": "https://docs.langchain.com/oss/python/langgraph/streaming",
    # graph-api
-    "how-tos/state-reducers.ipynb": "how-tos/graph-api.md#define-and-update-state",
-    "how-tos/sequence.ipynb": "how-tos/graph-api.md#create-a-sequence-of-steps",
-    "how-tos/branching.ipynb": "how-tos/graph-api.md#create-branches",
-    "how-tos/recursion-limit.ipynb": "how-tos/graph-api.md#create-and-control-loops",
-    "how-tos/visualization.ipynb": "how-tos/graph-api.md#visualize-your-graph",
-    "how-tos/input_output_schema.ipynb": "how-tos/graph-api.md#define-input-and-output-schemas",
-    "how-tos/pass_private_state.ipynb": "how-tos/graph-api.md#pass-private-state-between-nodes",
-    "how-tos/state-model.ipynb": "how-tos/graph-api.md#use-pydantic-models-for-graph-state",
-    "how-tos/map-reduce.ipynb": "how-tos/graph-api.md#map-reduce-and-the-send-api",
-    "how-tos/command.ipynb": "how-tos/graph-api.md#combine-control-flow-and-state-updates-with-command",
-    "how-tos/configuration.ipynb": "how-tos/graph-api.md#add-runtime-configuration",
-    "how-tos/node-retries.ipynb": "how-tos/graph-api.md#add-retry-policies",
-    "how-tos/return-when-recursion-limit-hits.ipynb": "how-tos/graph-api.md#impose-a-recursion-limit",
-    "how-tos/async.ipynb": "how-tos/graph-api.md#async",
+    "how-tos/state-reducers.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#define-and-update-state",
+    "how-tos/sequence.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#create-a-sequence-of-steps",
+    "how-tos/branching.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#create-branches",
+    "how-tos/recursion-limit.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#create-and-control-loops",
+    "how-tos/visualization.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#visualize-your-graph",
+    "how-tos/input_output_schema.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#define-input-and-output-schemas",
+    "how-tos/pass_private_state.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#pass-private-state-between-nodes",
+    "how-tos/state-model.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#use-pydantic-models-for-graph-state",
+    "how-tos/map-reduce.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#map-reduce-and-the-send-api",
+    "how-tos/command.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#combine-control-flow-and-state-updates-with-command",
+    "how-tos/configuration.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#add-runtime-configuration",
+    "how-tos/node-retries.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#add-retry-policies",
+    "how-tos/return-when-recursion-limit-hits.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#impose-a-recursion-limit",
+    "how-tos/async.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#async",
    # memory how-tos
-    "how-tos/memory/manage-conversation-history.ipynb": "how-tos/memory/add-memory.md",
-    "how-tos/memory/delete-messages.ipynb": "how-tos/memory/add-memory.md#delete-messages",
-    "how-tos/memory/add-summary-conversation-history.ipynb": "how-tos/memory/add-memory.md#summarize-messages",
-    "how-tos/memory.ipynb": "how-tos/memory/add-memory.md",
-    "agents/memory.ipynb": "how-tos/memory/add-memory.md",
+    "how-tos/memory/manage-conversation-history.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory",
+    "how-tos/memory/delete-messages.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory#delete-messages",
+    "how-tos/memory/add-summary-conversation-history.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory#summarize-messages",
+    "how-tos/memory.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory",
+    "agents/memory.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory",
    # subgraph how-tos
-    "how-tos/subgraph-transform-state.ipynb": "how-tos/subgraph.md#different-state-schemas",
-    "how-tos/subgraphs-manage-state.ipynb": "how-tos/subgraph.md#add-persistence",
+    "how-tos/subgraph-transform-state.ipynb": "https://docs.langchain.com/oss/python/langgraph/use-subgraphs#different-state-schemas",
+    "how-tos/subgraphs-manage-state.ipynb": "https://docs.langchain.com/oss/python/langgraph/use-subgraphs#add-persistence",
    # persistence how-tos
-    "how-tos/persistence_postgres.ipynb": "how-tos/memory/add-memory.md#use-in-production",
-    "how-tos/persistence_mongodb.ipynb": "how-tos/memory/add-memory.md#use-in-production",
-    "how-tos/persistence_redis.ipynb": "how-tos/memory/add-memory.md#use-in-production",
-    "how-tos/subgraph-persistence.ipynb": "how-tos/memory/add-memory.md#use-with-subgraphs",
-    "how-tos/cross-thread-persistence.ipynb": "how-tos/memory/add-memory.md#add-long-term-memory",
-    "cloud/how-tos/copy_threads": "cloud/how-tos/use_threads",
-    "cloud/how-tos/check-thread-status": "cloud/how-tos/use_threads",
-    "cloud/concepts/threads.md": "concepts/persistence.md#threads",
-    "how-tos/persistence.ipynb": "how-tos/memory/add-memory.md",
+    "how-tos/persistence_postgres.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory#use-in-production",
+    "how-tos/persistence_mongodb.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory#use-in-production",
+    "how-tos/persistence_redis.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory#use-in-production",
+    "how-tos/subgraph-persistence.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory#use-with-subgraphs",
+    "how-tos/cross-thread-persistence.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory#add-long-term-memory",
+    "cloud/how-tos/copy_threads": "https://docs.langchain.com/langsmith/use-threads",
+    "cloud/how-tos/check-thread-status": "https://docs.langchain.com/langsmith/use-threads",
+    "cloud/concepts/threads.md": "https://docs.langchain.com/oss/python/langgraph/persistence#threads",
+    "how-tos/persistence.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory",
    # tool calling how-tos
-    "how-tos/tool-calling-errors.ipynb": "how-tos/tool-calling.ipynb#handle-errors",
-    "how-tos/pass-config-to-tools.ipynb": "how-tos/tool-calling.ipynb#access-config",
-    "how-tos/pass-run-time-values-to-tools.ipynb": "how-tos/tool-calling.ipynb#read-state",
-    "how-tos/update-state-from-tools.ipynb": "how-tos/tool-calling.ipynb#update-state",
-    "agents/tools.md": "how-tos/tool-calling.md",
+    "how-tos/tool-calling-errors.ipynb": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
+    "how-tos/pass-config-to-tools.ipynb": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
+    "how-tos/pass-run-time-values-to-tools.ipynb": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
+    "how-tos/update-state-from-tools.ipynb": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
+    "agents/tools.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
    # multi-agent how-tos
-    "how-tos/agent-handoffs.ipynb": "how-tos/multi_agent.md#handoffs",
-    "how-tos/multi-agent-network.ipynb": "how-tos/multi_agent.md#use-in-a-multi-agent-system",
-    "how-tos/multi-agent-multi-turn-convo.ipynb": "how-tos/multi_agent.md#multi-turn-conversation",
+    "how-tos/agent-handoffs.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api",
+    "how-tos/multi-agent-network.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api",
+    "how-tos/multi-agent-multi-turn-convo.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api",
    # cloud redirects
-    "cloud/index.md": "index.md",
-    "cloud/how-tos/index.md": "concepts/langgraph_platform",
-    "cloud/concepts/api.md": "concepts/langgraph_server.md",
-    "cloud/concepts/cloud.md": "concepts/langgraph_cloud.md",
-    "cloud/faq/studio.md": "concepts/langgraph_studio.md#studio-faqs",
-    "cloud/how-tos/human_in_the_loop_edit_state.md": "cloud/how-tos/add-human-in-the-loop.md",
-    "cloud/how-tos/human_in_the_loop_user_input.md": "cloud/how-tos/add-human-in-the-loop.md",
-    "concepts/platform_architecture.md": "concepts/langgraph_cloud#architecture",
+    "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/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",
+    "cloud/how-tos/human_in_the_loop_user_input.md": "https://docs.langchain.com/langsmith/add-human-in-the-loop",
+    "concepts/platform_architecture.md": "https://docs.langchain.com/langsmith/cloud#architecture",
    # cloud streaming redirects
    "cloud/how-tos/stream_values.md": "https://docs.langchain.com/langsmith/streaming",
    "cloud/how-tos/stream_updates.md": "https://docs.langchain.com/langsmith/streaming",
@@ -94,39 +94,39 @@ REDIRECT_MAP = {
    "cloud/how-tos/stream_events.md": "https://docs.langchain.com/langsmith/streaming",
    "cloud/how-tos/stream_debug.md": "https://docs.langchain.com/langsmith/streaming",
    "cloud/how-tos/stream_multiple.md": "https://docs.langchain.com/langsmith/streaming",
-    "cloud/concepts/streaming.md": "concepts/streaming.md",
-    "agents/streaming.md": "how-tos/streaming.md",
+    "cloud/concepts/streaming.md": "https://docs.langchain.com/oss/python/langgraph/streaming",
+    "agents/streaming.md": "https://docs.langchain.com/oss/python/langgraph/streaming",
    # prebuilt redirects
-    "how-tos/create-react-agent.ipynb": "agents/agents.md#basic-configuration",
-    "how-tos/create-react-agent-memory.ipynb": "agents/memory.md",
-    "how-tos/create-react-agent-system-prompt.ipynb": "agents/context.md#prompts",
-    "how-tos/create-react-agent-structured-output.ipynb": "agents/agents.md#structured-output",
+    "how-tos/create-react-agent.ipynb": "https://docs.langchain.com/oss/python/langchain/agents#basic-configuration",
+    "how-tos/create-react-agent-memory.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory",
+    "how-tos/create-react-agent-system-prompt.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory",
+    "how-tos/create-react-agent-structured-output.ipynb": "https://docs.langchain.com/oss/python/langchain/agents#structured-output",
    # misc
-    "prebuilt.md": "agents/prebuilt.md",
-    "reference/prebuilt.md": "reference/agents.md",
-    "concepts/high_level.md": "index.md",
-    "concepts/index.md": "index.md",
-    "concepts/v0-human-in-the-loop.md": "concepts/human-in-the-loop.md",
-    "how-tos/index.md": "index.md",
-    "tutorials/introduction.ipynb": "concepts/why-langgraph.md",
-    "agents/deployment.md": "tutorials/langgraph-platform/local-server.md",
+    "prebuilt.md": "https://docs.langchain.com/oss/python/langchain/agents",
+    "reference/prebuilt.md": "https://reference.langchain.com/python/langgraph/agents/",
+    "concepts/high_level.md": "https://docs.langchain.com/oss/python/langgraph/overview",
+    "concepts/index.md": "https://docs.langchain.com/oss/python/langgraph/overview",
+    "concepts/v0-human-in-the-loop.md": "https://docs.langchain.com/oss/python/langgraph/interrupts",
+    "how-tos/index.md": "https://docs.langchain.com/oss/python/langgraph/overview",
+    "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": "cloud/deployment/self_hosted_data_plane.md",
-    "concepts/self_hosted.md": "concepts/langgraph_self_hosted_data_plane.md",
-    "tutorials/deployment.md": "concepts/deployment_options.md",
+    "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": "cloud/how-tos/configuration_cloud.md",
-    "cloud/concepts/runs.md": "concepts/assistants.md#execution",
+    "cloud/how-tos/assistant_versioning.md": "https://docs.langchain.com/langsmith/configuration-cloud",
+    "cloud/concepts/runs.md": "https://docs.langchain.com/langsmith/assistants#execution",
    # hitl redirects
-    "how-tos/wait-user-input-functional.ipynb": "how-tos/use-functional-api.md",
-    "how-tos/review-tool-calls-functional.ipynb": "how-tos/use-functional-api.md",
-    "how-tos/create-react-agent-hitl.ipynb": "how-tos/human_in_the_loop/add-human-in-the-loop.md",
-    "agents/human-in-the-loop.md": "how-tos/human_in_the_loop/add-human-in-the-loop.md",
-    "how-tos/human_in_the_loop/dynamic_breakpoints.ipynb": "how-tos/human_in_the_loop/breakpoints.md",
-    "concepts/breakpoints.md": "concepts/human_in_the_loop.md",
-    "how-tos/human_in_the_loop/breakpoints.md": "how-tos/human_in_the_loop/add-human-in-the-loop.md",
-    "cloud/how-tos/human_in_the_loop_breakpoint.md": "cloud/how-tos/add-human-in-the-loop.md",
-    "how-tos/human_in_the_loop/edit-graph-state.ipynb": "how-tos/human_in_the_loop/time-travel.md",
+    "how-tos/wait-user-input-functional.ipynb": "https://docs.langchain.com/oss/python/langgraph/functional-api",
+    "how-tos/review-tool-calls-functional.ipynb": "https://docs.langchain.com/oss/python/langgraph/functional-api",
+    "how-tos/create-react-agent-hitl.ipynb": "https://docs.langchain.com/oss/python/langgraph/interrupts",
+    "agents/human-in-the-loop.md": "https://docs.langchain.com/oss/python/langgraph/interrupts",
+    "how-tos/human_in_the_loop/dynamic_breakpoints.ipynb": "https://docs.langchain.com/oss/python/langgraph/interrupts",
+    "concepts/breakpoints.md": "https://docs.langchain.com/oss/python/langgraph/interrupts",
+    "how-tos/human_in_the_loop/breakpoints.md": "https://docs.langchain.com/oss/python/langgraph/interrupts",
+    "cloud/how-tos/human_in_the_loop_breakpoint.md": "https://docs.langchain.com/langsmith/add-human-in-the-loop",
+    "how-tos/human_in_the_loop/edit-graph-state.ipynb": "https://docs.langchain.com/oss/python/langgraph/use-time-travel",

    # LGP mintlify migration redirects
    "tutorials/auth/getting_started.md": "https://docs.langchain.com/langsmith/auth",
@@ -141,7 +141,7 @@ REDIRECT_MAP = {
    "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/langgraph-cli",
+    "concepts/langgraph_cli.md": "https://docs.langchain.com/langsmith/cli",
    "concepts/langgraph_studio.md": "https://docs.langchain.com/langsmith/studio",
    "cloud/how-tos/studio/quick_start.md": "https://docs.langchain.com/langsmith/quick-start-studio",
    "cloud/how-tos/invoke_studio.md": "https://docs.langchain.com/langsmith/use-studio#run-application",
@@ -180,7 +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/hosting",
+    "concepts/deployment_options.md": "https://docs.langchain.com/langsmith/platform-setup",
    "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",
@@ -206,6 +206,234 @@ REDIRECT_MAP = {
    "cloud/reference/cli.md": "https://docs.langchain.com/langsmith/cli",
    "cloud/reference/env_var.md": "https://docs.langchain.com/langsmith/env-var",
    "troubleshooting/studio.md": "https://docs.langchain.com/langsmith/troubleshooting-studio",
+
+    # LangGraph mintlify migration redirects
+    "index.md": "https://docs.langchain.com/oss/python/langgraph/overview",
+    "agents/agents.md": "https://docs.langchain.com/oss/python/langchain/agents",
+    "concepts/why-langgraph.md": "https://docs.langchain.com/oss/python/langgraph/overview",
+    "tutorials/get-started/1-build-basic-chatbot.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
+    "tutorials/get-started/2-add-tools.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
+    "tutorials/get-started/3-add-memory.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
+    "tutorials/get-started/4-human-in-the-loop.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
+    "tutorials/get-started/5-customize-state.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
+    "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",
+    "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",
+    "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",
+    "concepts/streaming.md": "https://docs.langchain.com/oss/python/langgraph/streaming",
+    "how-tos/streaming.md": "https://docs.langchain.com/oss/python/langgraph/streaming",
+    "concepts/persistence.md": "https://docs.langchain.com/oss/python/langgraph/persistence",
+    "concepts/durable_execution.md": "https://docs.langchain.com/oss/python/langgraph/durable-execution",
+    "concepts/memory.md": "https://docs.langchain.com/oss/python/langgraph/memory",
+    "how-tos/memory/add-memory.md": "https://docs.langchain.com/oss/python/langgraph/add-memory",
+    "agents/context.md": "https://docs.langchain.com/oss/python/langgraph/add-memory",
+    "agents/models.md": "https://docs.langchain.com/oss/python/langgraph/overview",
+    "concepts/tools.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
+    "how-tos/tool-calling.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
+    "concepts/human_in_the_loop.md": "https://docs.langchain.com/oss/python/langgraph/interrupts",
+    "how-tos/human_in_the_loop/add-human-in-the-loop.md": "https://docs.langchain.com/oss/python/langgraph/interrupts",
+    "concepts/time-travel.md": "https://docs.langchain.com/oss/python/langgraph/persistence",
+    "how-tos/human_in_the_loop/time-travel.md": "https://docs.langchain.com/oss/python/langgraph/use-time-travel",
+    "concepts/subgraphs.md": "https://docs.langchain.com/oss/python/langgraph/use-subgraphs",
+    "how-tos/subgraph.md": "https://docs.langchain.com/oss/python/langgraph/use-subgraphs",
+    "concepts/multi_agent.md": "https://docs.langchain.com/oss/python/langgraph/graph-api",
+    "agents/multi-agent.md": "https://docs.langchain.com/oss/python/langchain/multi-agent",
+    "how-tos/multi_agent.md": "https://docs.langchain.com/oss/python/langgraph/graph-api",
+    "concepts/mcp.md": "https://docs.langchain.com/oss/python/langgraph/overview",
+    "agents/mcp.md": "https://docs.langchain.com/oss/python/langgraph/overview",
+    "concepts/tracing.md": "https://docs.langchain.com/oss/python/langgraph/observability",
+    "how-tos/enable-tracing.md": "https://docs.langchain.com/oss/python/langgraph/observability",
+    "agents/evals.md": "https://docs.langchain.com/oss/python/langgraph/overview",
+    "examples/index.md": "https://docs.langchain.com/oss/python/langgraph/case-studies",
+    "concepts/template_applications.md": "https://docs.langchain.com/oss/python/langgraph/overview",
+    "tutorials/rag/langgraph_agentic_rag.md": "https://docs.langchain.com/oss/python/langgraph/agentic-rag",
+    "tutorials/multi_agent/agent_supervisor.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
+    "tutorials/sql/sql-agent.md": "https://docs.langchain.com/oss/python/langgraph/sql-agent",
+    "agents/ui.md": "https://docs.langchain.com/oss/python/langgraph/ui",
+    "how-tos/run-id-langsmith.md": "https://docs.langchain.com/oss/python/langgraph/observability",
+    "troubleshooting/errors/index.md": "https://docs.langchain.com/oss/python/langgraph/common-errors",
+    "troubleshooting/errors/INVALID_CHAT_HISTORY.md": "https://docs.langchain.com/oss/python/langgraph/INVALID_CHAT_HISTORY",
+    "troubleshooting/errors/INVALID_LICENSE.md": "https://docs.langchain.com/oss/python/langgraph/common-errors",
+    "adopters.md": "https://docs.langchain.com/oss/python/langgraph/case-studies",
+    "concepts/faq.md": "https://docs.langchain.com/oss/python/langgraph/overview",
+    "agents/prebuilt.md": "https://docs.langchain.com/oss/python/langchain/agents",
+    "reference/index.md": "https://reference.langchain.com/python/langgraph/",
+    "reference/graphs.md": "https://reference.langchain.com/python/langgraph/graphs/",
+    "reference/func.md": "https://reference.langchain.com/python/langgraph/func/",
+    "reference/pregel.md": "https://reference.langchain.com/python/langgraph/pregel/",
+    "reference/checkpoints.md": "https://reference.langchain.com/python/langgraph/checkpoints/",
+    "reference/store.md": "https://reference.langchain.com/python/langgraph/store/",
+    "reference/cache.md": "https://reference.langchain.com/python/langgraph/cache/",
+    "reference/types.md": "https://reference.langchain.com/python/langgraph/types/",
+    "reference/runtime.md": "https://reference.langchain.com/python/langgraph/runtime/",
+    "reference/config.md": "https://reference.langchain.com/python/langgraph/config/",
+    "reference/errors.md": "https://reference.langchain.com/python/langgraph/errors/",
+    "reference/constants.md": "https://reference.langchain.com/python/langgraph/constants/",
+    "reference/channels.md": "https://reference.langchain.com/python/langgraph/channels/",
+    "reference/agents.md": "https://reference.langchain.com/python/langgraph/agents/",
+    "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/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",
+    "cloud/concepts/cron_jobs.md": "https://docs.langchain.com/langsmith/cron-jobs",
+    "cloud/concepts/data_storage_and_privacy.md": "https://docs.langchain.com/langsmith/data-storage-and-privacy",
+    "cloud/concepts/webhooks.md": "https://docs.langchain.com/langsmith/use-webhooks",
+    "cloud/deployment/cloud.md": "https://docs.langchain.com/langsmith/cloud",
+    "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/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",
+    "cloud/deployment/setup.md": "https://docs.langchain.com/langsmith/setup-app-requirements-txt",
+    "cloud/deployment/standalone_container.md": "https://docs.langchain.com/langsmith/docker",
+    "cloud/how-tos/add-human-in-the-loop.md": "https://docs.langchain.com/langsmith/add-human-in-the-loop",
+    "cloud/how-tos/background_run.md": "https://docs.langchain.com/langsmith/background-run",
+    "cloud/how-tos/clone_traces_studio.md": "https://docs.langchain.com/langsmith/observability",
+    "cloud/how-tos/configurable_headers.md": "https://docs.langchain.com/langsmith/configurable-headers",
+    "cloud/how-tos/configuration_cloud.md": "https://docs.langchain.com/langsmith/configuration-cloud",
+    "cloud/how-tos/cron_jobs.md": "https://docs.langchain.com/langsmith/cron-jobs",
+    "cloud/how-tos/datasets_studio.md": "https://docs.langchain.com/langsmith/use-studio",
+    "cloud/how-tos/enqueue_concurrent.md": "https://docs.langchain.com/langsmith/enqueue-concurrent",
+    "cloud/how-tos/generative_ui_react.md": "https://docs.langchain.com/langsmith/generative-ui-react",
+    "cloud/how-tos/human_in_the_loop_time_travel.md": "https://docs.langchain.com/langsmith/human-in-the-loop-time-travel",
+    "cloud/how-tos/interrupt_concurrent.md": "https://docs.langchain.com/langsmith/interrupt-concurrent",
+    "cloud/how-tos/invoke_studio.md": "https://docs.langchain.com/langsmith/use-studio",
+    "cloud/how-tos/iterate_graph_studio.md": "https://docs.langchain.com/langsmith/use-studio",
+    "cloud/how-tos/reject_concurrent.md": "https://docs.langchain.com/langsmith/reject-concurrent",
+    "cloud/how-tos/rollback_concurrent.md": "https://docs.langchain.com/langsmith/rollback-concurrent",
+    "cloud/how-tos/same-thread.md": "https://docs.langchain.com/langsmith/same-thread",
+    "cloud/how-tos/stateless_runs.md": "https://docs.langchain.com/langsmith/stateless-runs",
+    "cloud/how-tos/streaming.md": "https://docs.langchain.com/langsmith/streaming",
+    "cloud/how-tos/studio/manage_assistants.md": "https://docs.langchain.com/langsmith/use-studio",
+    "cloud/how-tos/studio/quick_start.md": "https://docs.langchain.com/langsmith/quick-start-studio",
+    "cloud/how-tos/studio/run_evals.md": "https://docs.langchain.com/langsmith/observability",
+    "cloud/how-tos/threads_studio.md": "https://docs.langchain.com/langsmith/use-threads",
+    "cloud/how-tos/use_stream_react.md": "https://docs.langchain.com/langsmith/use-stream-react",
+    "cloud/how-tos/use_threads.md": "https://docs.langchain.com/langsmith/use-threads",
+    "cloud/how-tos/webhooks.md": "https://docs.langchain.com/langsmith/use-webhooks",
+    "cloud/quick_start.md": "https://docs.langchain.com/langsmith/deployment-quickstart",
+    "cloud/reference/api/api_ref_control_plane.md": "https://docs.langchain.com/langsmith/api-ref-control-plane",
+    "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/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",
+    "concepts/auth.md": "https://docs.langchain.com/langsmith/auth",
+    "concepts/deployment_options.md": "https://docs.langchain.com/langsmith/deployments",
+    "concepts/double_texting.md": "https://docs.langchain.com/langsmith/double-texting",
+    "concepts/faq.md": "https://docs.langchain.com/langsmith/faq",
+    "concepts/langgraph_cli.md": "https://docs.langchain.com/langsmith/cli",
+    "concepts/langgraph_cloud.md": "https://docs.langchain.com/langsmith/cloud",
+    "concepts/langgraph_components.md": "https://docs.langchain.com/langsmith/components",
+    "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/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",
+    "concepts/scalability_and_resilience.md": "https://docs.langchain.com/langsmith/scalability-and-resilience",
+    "concepts/sdk.md": "https://docs.langchain.com/langsmith/sdk",
+    "concepts/server-mcp.md": "https://docs.langchain.com/langsmith/server-mcp",
+    "concepts/template_applications.md": "https://docs.langchain.com/oss/python/langgraph/overview",
+    "concepts/why-langgraph.md": "https://docs.langchain.com/oss/python/langgraph/overview",
+    "examples/index.md": "https://docs.langchain.com/oss/python/langgraph/case-studies",
+    "guides/index.md": "https://docs.langchain.com/oss/python/langchain/overview",
+    "how-tos/auth/custom_auth.md": "https://docs.langchain.com/langsmith/custom-auth",
+    "how-tos/auth/openapi_security.md": "https://docs.langchain.com/langsmith/openapi-security",
+    "how-tos/autogen-integration.md": "https://docs.langchain.com/langsmith/autogen-integration",
+    "how-tos/http/custom_lifespan.md": "https://docs.langchain.com/langsmith/custom-lifespan",
+    "how-tos/http/custom_middleware.md": "https://docs.langchain.com/langsmith/custom-middleware",
+    "how-tos/http/custom_routes.md": "https://docs.langchain.com/langsmith/custom-routes",
+    "how-tos/ttl/configure_ttl.md": "https://docs.langchain.com/langsmith/configure-ttl",
+    "how-tos/use-remote-graph.md": "https://docs.langchain.com/langsmith/use-remote-graph",
+    "index.md": "https://docs.langchain.com/oss/python/langgraph/overview",
+    "snippets/chat_model_tabs.md": "https://docs.langchain.com/oss/python/langchain/overview",
+    "troubleshooting/errors/GRAPH_RECURSION_LIMIT.md": "https://docs.langchain.com/oss/python/langgraph/GRAPH_RECURSION_LIMIT",
+    "troubleshooting/errors/index.md": "https://docs.langchain.com/oss/python/langgraph/common-errors",
+    "troubleshooting/errors/INVALID_CHAT_HISTORY.md": "https://docs.langchain.com/oss/python/langgraph/INVALID_CHAT_HISTORY",
+    "troubleshooting/errors/INVALID_CONCURRENT_GRAPH_UPDATE.md": "https://docs.langchain.com/oss/python/langgraph/INVALID_CONCURRENT_GRAPH_UPDATE",
+    "troubleshooting/errors/INVALID_GRAPH_NODE_RETURN_VALUE.md": "https://docs.langchain.com/oss/python/langgraph/INVALID_GRAPH_NODE_RETURN_VALUE",
+    "troubleshooting/errors/INVALID_LICENSE.md": "https://docs.langchain.com/oss/python/langgraph/common-errors",
+    "troubleshooting/errors/MULTIPLE_SUBGRAPHS.md": "https://docs.langchain.com/oss/python/langgraph/MULTIPLE_SUBGRAPHS",
+    "troubleshooting/studio.md": "https://docs.langchain.com/langsmith/troubleshooting-studio",
+    "tutorials/auth/add_auth_server.md": "https://docs.langchain.com/langsmith/add-auth-server",
+    "tutorials/auth/getting_started.md": "https://docs.langchain.com/langsmith/auth",
+    "tutorials/auth/resource_auth.md": "https://docs.langchain.com/langsmith/resource-auth",
+    "agents/agents.md": "https://docs.langchain.com/oss/python/langchain/agents",
+    "concepts/why-langgraph.md": "https://docs.langchain.com/oss/python/langgraph/overview",
+    "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",
+    "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",
+    "concepts/agentic_concepts.md": "https://docs.langchain.com/oss/python/langgraph/workflows-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",
+    "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",
+    "concepts/streaming.md": "https://docs.langchain.com/oss/python/langgraph/streaming",
+    "how-tos/streaming.md": "https://docs.langchain.com/oss/python/langgraph/streaming",
+    "concepts/persistence.md": "https://docs.langchain.com/oss/python/langgraph/persistence",
+    "concepts/durable_execution.md": "https://docs.langchain.com/oss/python/langgraph/durable-execution",
+    "concepts/memory.md": "https://docs.langchain.com/oss/python/langgraph/memory",
+    "how-tos/memory/add-memory.md": "https://docs.langchain.com/oss/python/langgraph/add-memory",
+    "agents/context.md": "https://docs.langchain.com/oss/python/langgraph/add-memory",
+    "agents/models.md": "https://docs.langchain.com/oss/python/langgraph/overview",
+    "concepts/tools.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
+    "how-tos/tool-calling.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
+    "concepts/human_in_the_loop.md": "https://docs.langchain.com/oss/python/langgraph/interrupts",
+    "how-tos/human_in_the_loop/add-human-in-the-loop.md": "https://docs.langchain.com/oss/python/langgraph/interrupts",
+    "concepts/time-travel.md": "https://docs.langchain.com/oss/python/langgraph/persistence",
+    "how-tos/human_in_the_loop/time-travel.md": "https://docs.langchain.com/oss/python/langgraph/use-time-travel",
+    "concepts/subgraphs.md": "https://docs.langchain.com/oss/python/langgraph/use-subgraphs",
+    "how-tos/subgraph.md": "https://docs.langchain.com/oss/python/langgraph/use-subgraphs",
+    "concepts/multi_agent.md": "https://docs.langchain.com/oss/python/langgraph/graph-api",
+    "agents/multi-agent.md": "https://docs.langchain.com/oss/python/langchain/multi-agent",
+    "how-tos/multi_agent.md": "https://docs.langchain.com/oss/python/langgraph/graph-api",
+    "concepts/mcp.md": "https://docs.langchain.com/oss/python/langgraph/overview",
+    "agents/mcp.md": "https://docs.langchain.com/oss/python/langgraph/overview",
+    "concepts/tracing.md": "https://docs.langchain.com/oss/python/langgraph/observability",
+    "how-tos/enable-tracing.md": "https://docs.langchain.com/oss/python/langgraph/observability",
+    "agents/evals.md": "https://docs.langchain.com/oss/python/langgraph/overview",
+    "examples/index.md": "https://docs.langchain.com/oss/python/langgraph/case-studies",
+    "concepts/template_applications.md": "https://docs.langchain.com/oss/python/langgraph/overview",
+    "tutorials/rag/langgraph_agentic_rag.md": "https://docs.langchain.com/oss/python/langgraph/agentic-rag",
+    "tutorials/multi_agent/agent_supervisor.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
+    "tutorials/sql/sql-agent.md": "https://docs.langchain.com/oss/python/langgraph/sql-agent",
+    "agents/ui.md": "https://docs.langchain.com/oss/python/langgraph/ui",
+    "how-tos/run-id-langsmith.md": "https://docs.langchain.com/oss/python/langgraph/observability",
+    "troubleshooting/errors/index.md": "https://docs.langchain.com/oss/python/langgraph/common-errors",
+    "troubleshooting/errors/GRAPH_RECURSION_LIMIT.md": "https://docs.langchain.com/oss/python/langgraph/GRAPH_RECURSION_LIMIT",
+    "troubleshooting/errors/INVALID_CONCURRENT_GRAPH_UPDATE.md": "https://docs.langchain.com/oss/python/langgraph/INVALID_CONCURRENT_GRAPH_UPDATE",
+    "troubleshooting/errors/INVALID_GRAPH_NODE_RETURN_VALUE.md": "https://docs.langchain.com/oss/python/langgraph/INVALID_GRAPH_NODE_RETURN_VALUE",
+    "troubleshooting/errors/MULTIPLE_SUBGRAPHS.md": "https://docs.langchain.com/oss/python/langgraph/MULTIPLE_SUBGRAPHS",
+    "troubleshooting/errors/INVALID_CHAT_HISTORY.md": "https://docs.langchain.com/oss/python/langgraph/INVALID_CHAT_HISTORY",
+    "troubleshooting/errors/INVALID_LICENSE.md": "https://docs.langchain.com/oss/python/langgraph/common-errors",
+    "adopters.md": "https://docs.langchain.com/oss/python/langgraph/case-studies",
+    "concepts/faq.md": "https://docs.langchain.com/oss/python/langgraph/overview",
+    "agents/prebuilt.md": "https://docs.langchain.com/oss/python/langchain/agents",
 }


@@ -560,10 +788,16 @@ def on_post_page(html: str, page: Page, config: MkDocsConfig) -> str:
 # Create HTML files for redirects after site dir has been built
 def on_post_build(config):
    use_directory_urls = config.get("use_directory_urls")
+    site_dir = config["site_dir"]
+
+    # Track which paths have explicit redirects
+    redirected_paths = set()
+
+    # Process explicit redirects from REDIRECT_MAP
    for page_old, page_new in REDIRECT_MAP.items():
        # Convert .ipynb to .md for path calculation
        page_old = page_old.replace(".ipynb", ".md")
-        
+
        # Calculate the HTML path for the old page (whether it exists or not)
        if use_directory_urls:
            # With directory URLs: /path/to/page/ becomes /path/to/page/index.html
@@ -577,15 +811,18 @@ def on_post_build(config):
                old_html_path = page_old[:-3] + ".html"
            else:
                old_html_path = page_old + ".html"
-        
+
+        # Track this path as redirected
+        redirected_paths.add(old_html_path)
+
        if isinstance(page_new, str) and page_new.startswith("http"):
            # Handle external redirects
-            _write_html(config["site_dir"], old_html_path, page_new)
+            _write_html(site_dir, old_html_path, page_new)
        else:
            # Handle internal redirects
            page_new = page_new.replace(".ipynb", ".md")
            page_new_before_hash, hash, suffix = page_new.partition("#")
-            
+
            # Try to get the new path using File class, but fallback to manual calculation
            try:
                new_html_path = File(page_new_before_hash, "", "", True).url
@@ -607,5 +844,46 @@ def on_post_build(config):
                    else:
                        new_html_path = page_new_before_hash + ".html"
                new_html_path += hash + suffix
-            
-            _write_html(config["site_dir"], old_html_path, new_html_path)
+
+            _write_html(site_dir, old_html_path, new_html_path)
+
+    # Create root index.html redirect
+    root_redirect_html = """<!doctype html>
+<html lang="en">
+<head>
+    <meta charset="utf-8">
+    <title>Redirecting to LangGraph Documentation</title>
+    <link rel="canonical" href="https://docs.langchain.com/oss/python/langgraph/overview">
+    <meta name="robots" content="noindex">
+    <script>var anchor=window.location.hash.substr(1);location.href="https://docs.langchain.com/oss/python/langgraph/overview"+(anchor?"#"+anchor:"")</script>
+    <meta http-equiv="refresh" content="0; url=https://docs.langchain.com/oss/python/langgraph/overview">
+</head>
+<body>
+<h1>Documentation has moved</h1>
+<p>The LangGraph documentation has moved to <a href="https://docs.langchain.com/oss/python/langgraph/overview">docs.langchain.com</a>.</p>
+<p>Redirecting you now...</p>
+</body>
+</html>
+"""
+
+    root_index_path = os.path.join(site_dir, "index.html")
+    with open(root_index_path, "w", encoding="utf-8") as f:
+        f.write(root_redirect_html)
+
+    # Create server-side catch-all redirect file for Netlify/Cloudflare Pages
+    # This handles any pages not explicitly mapped in REDIRECT_MAP
+    # Note: This won't work on GitHub Pages, but kept for potential future use
+    redirects_content = """# Netlify/Cloudflare Pages redirect rules
+# Specific redirects are handled by individual HTML redirect pages
+# This is the catch-all for any unmapped pages
+
+# Exclude reference docs from catch-all
+/reference/*  200
+
+# Catch-all: redirect any page not explicitly mapped
+/*  https://docs.langchain.com/oss/python/langgraph/overview  301
+"""
+
+    redirects_path = os.path.join(site_dir, "_redirects")
+    with open(redirects_path, "w", encoding="utf-8") as f:
+        f.write(redirects_content)
@@ -294,9 +294,9 @@ Now that you have a LangGraph app running locally, take your journey further by
 :::python

 - [Python SDK Reference](../../cloud/reference/sdk/python_sdk_ref.md): Explore the Python SDK API Reference.
-  :::
+:::

 :::js

 - [JS/TS SDK Reference](../../cloud/reference/sdk/js_ts_sdk_ref.md): Explore the JS/TS SDK API Reference.
-  :::
+:::
@@ -149,6 +149,67 @@ plugins:
        - tutorials/auth/add_auth_server.md
        - tutorials/auth/getting_started.md
        - tutorials/auth/resource_auth.md
+        - agents/agents.md
+        - concepts/why-langgraph.md
+        - tutorials/get-started/1-build-basic-chatbot.md
+        - tutorials/get-started/2-add-tools.md
+        - tutorials/get-started/3-add-memory.md
+        - tutorials/get-started/4-human-in-the-loop.md
+        - tutorials/get-started/5-customize-state.md
+        - tutorials/get-started/6-time-travel.md
+        - tutorials/langgraph-platform/local-server.md
+        - tutorials/workflows.md
+        - concepts/agentic_concepts.md
+        - guides/index.md
+        - agents/overview.md
+        - agents/run_agents.md
+        - concepts/low_level.md
+        - how-tos/graph-api.md
+        - concepts/functional_api.md
+        - how-tos/use-functional-api.md
+        - concepts/pregel.md
+        - concepts/streaming.md
+        - how-tos/streaming.md
+        - concepts/persistence.md
+        - concepts/durable_execution.md
+        - concepts/memory.md
+        - how-tos/memory/add-memory.md
+        - agents/context.md
+        - agents/models.md
+        - concepts/tools.md
+        - how-tos/tool-calling.md
+        - concepts/human_in_the_loop.md
+        - how-tos/human_in_the_loop/add-human-in-the-loop.md
+        - concepts/time-travel.md
+        - how-tos/human_in_the_loop/time-travel.md
+        - concepts/subgraphs.md
+        - how-tos/subgraph.md
+        - concepts/multi_agent.md
+        - agents/multi-agent.md
+        - how-tos/multi_agent.md
+        - concepts/mcp.md
+        - agents/mcp.md
+        - concepts/tracing.md
+        - how-tos/enable-tracing.md
+        - agents/evals.md
+        - examples/index.md
+        - concepts/template_applications.md  # TODO: make tutorial
+        - tutorials/rag/langgraph_agentic_rag.md
+        - tutorials/multi_agent/agent_supervisor.md
+        - tutorials/sql/sql-agent.md
+        - agents/ui.md
+        - how-tos/run-id-langsmith.md
+        - troubleshooting/errors/index.md
+        - troubleshooting/errors/GRAPH_RECURSION_LIMIT.md
+        - troubleshooting/errors/INVALID_CONCURRENT_GRAPH_UPDATE.md
+        - troubleshooting/errors/INVALID_GRAPH_NODE_RETURN_VALUE.md
+        - troubleshooting/errors/MULTIPLE_SUBGRAPHS.md
+        - troubleshooting/errors/INVALID_CHAT_HISTORY.md
+        - troubleshooting/errors/INVALID_LICENSE.md
+        - adopters.md
+        - concepts/faq.md
+        - agents/prebuilt.md # NOTE: prebuilt.md is auto-generated by `make build-prebuilt`
+
  - tags
  - include-markdown
  - mkdocstrings:
@@ -186,75 +247,6 @@ plugins:
                - "!^_"

 nav:
-  - Get started:
-    - index.md
-    - Quickstarts:
-      - Start with a prebuilt agent: agents/agents.md
-      - Build a custom workflow:
-          -  concepts/why-langgraph.md
-          -  1. Build a basic chatbot: tutorials/get-started/1-build-basic-chatbot.md
-          -  2. Add tools: tutorials/get-started/2-add-tools.md
-          -  3. Add memory: tutorials/get-started/3-add-memory.md
-          -  4. Add human-in-the-loop: tutorials/get-started/4-human-in-the-loop.md
-          -  5. Customize state: tutorials/get-started/5-customize-state.md
-          -  6. Time travel: tutorials/get-started/6-time-travel.md
-      - Run a local server: tutorials/langgraph-platform/local-server.md
-    - General concepts:
-      - Workflows & agents: tutorials/workflows.md
-      - Agent architectures: concepts/agentic_concepts.md
-
-  - Guides:
-    - guides/index.md
-    - Agent development:
-      - Overview: agents/overview.md
-      - Run an agent: agents/run_agents.md
-    - LangGraph APIs:
-      - Graph API:
-          - Overview: concepts/low_level.md
-          - Use the Graph API: how-tos/graph-api.md
-      - Functional API:
-          - Overview: concepts/functional_api.md
-          - Use the Functional API: how-tos/use-functional-api.md
-      - Runtime: concepts/pregel.md
-    - Core capabilities:
-      - Streaming:
-          - Overview: concepts/streaming.md
-          - Stream outputs: how-tos/streaming.md
-      - Persistence:
-          - Overview: concepts/persistence.md
-      - Durable execution:
-          - Overview: concepts/durable_execution.md
-      - Memory:
-          - Overview: concepts/memory.md
-          - Add memory: how-tos/memory/add-memory.md
-      - Context:
-          - Add context: agents/context.md
-      - Models:
-          - Configure model: agents/models.md
-      - Tools:
-          - Overview: concepts/tools.md
-          - Call tools: how-tos/tool-calling.md
-      - Human-in-the-loop:
-          - Overview: concepts/human_in_the_loop.md
-          - Add human intervention: how-tos/human_in_the_loop/add-human-in-the-loop.md
-      - Time travel:
-          - Overview: concepts/time-travel.md
-          - Use time travel: how-tos/human_in_the_loop/time-travel.md
-      - Subgraphs:
-          - Overview: concepts/subgraphs.md
-          - Use subgraphs: how-tos/subgraph.md
-      - Multi-agent:
-          - Overview: concepts/multi_agent.md
-          - Prebuilt implementation: agents/multi-agent.md
-          - Custom implementation: how-tos/multi_agent.md
-      - MCP:
-          - Overview: concepts/mcp.md
-          - Use MCP: agents/mcp.md
-      - Tracing:
-          - Overview: concepts/tracing.md
-          - Enable tracing: how-tos/enable-tracing.md
-          - Evaluate performance: agents/evals.md
-
  - Reference:
    - reference/index.md
    - LangGraph:
@@ -278,35 +270,7 @@ nav:
    - LangGraph Platform:
      - SDK (Python): cloud/reference/sdk/python_sdk_ref.md
      - SDK (JS/TS): https://langchain-ai.github.io/langgraphjs/reference/modules/sdk.html
-      - RemoteGraph: reference/remote_graph.md
-
-  - Examples:
-    - examples/index.md
-    - Template applications: concepts/template_applications.md  # TODO: make tutorial
-    - Agentic RAG: tutorials/rag/langgraph_agentic_rag.md
-    - Agent Supervisor: tutorials/multi_agent/agent_supervisor.md
-    - SQL agent: tutorials/sql/sql-agent.md
-    - Prebuilt chat UI: agents/ui.md
-    - Graph runs in LangSmith: how-tos/run-id-langsmith.md
-
-  - Additional resources:
-    - additional-resources/index.md
-    - agents/prebuilt.md # NOTE: prebuilt.md is auto-generated by `make build-prebuilt`
-    - LangGraph Academy course: https://academy.langchain.com/courses/intro-to-langgraph
-    - Case studies: adopters.md
-    - concepts/faq.md
-    - llms.txt: llms-txt-overview.md
-    - LangChain Forum: https://forum.langchain.com/
-    - Troubleshooting:
-        - Errors:
-          - troubleshooting/errors/index.md
-          - troubleshooting/errors/GRAPH_RECURSION_LIMIT.md
-          - troubleshooting/errors/INVALID_CONCURRENT_GRAPH_UPDATE.md
-          - troubleshooting/errors/INVALID_GRAPH_NODE_RETURN_VALUE.md
-          - troubleshooting/errors/MULTIPLE_SUBGRAPHS.md
-          - troubleshooting/errors/INVALID_CHAT_HISTORY.md
-          - troubleshooting/errors/INVALID_LICENSE.md
-    
+      - RemoteGraph: reference/remote_graph.md 

 markdown_extensions:
  - abbr
@@ -275,7 +275,11 @@ def test_serde_jsonplus_json_mode() -> None:
    }

    if sys.version_info < (3, 14):
-        expected_result["my_pydantic_v1"] = {"foo": "foo", "bar": 1, "inner": {"hello": "hello"}}
+        expected_result["my_pydantic_v1"] = {
+            "foo": "foo",
+            "bar": 1,
+            "inner": {"hello": "hello"},
+        }
        expected_result["my_secret_str_v1"] = "meow"

    assert result == expected_result
@@ -381,7 +385,12 @@ def test_serde_jsonplus_numpy_array_json_hook(arr: np.ndarray) -> None:
                "str_col": ["a", None, "c"],
            }
        ),
-        pd.DataFrame({"cat_col": pd.Categorical(["a", "b", "a", "c"])}),
+        pytest.param(
+            pd.DataFrame({"cat_col": pd.Categorical(["a", "b", "a", "c"])}),
+            marks=pytest.mark.skipif(
+                sys.version_info >= (3, 14), reason="NotImplementedError on Python 3.14"
+            ),
+        ),
        pd.DataFrame(
            {
                "int8": pd.array([1, 2, 3], dtype="int8"),
@@ -409,11 +418,25 @@ def test_serde_jsonplus_numpy_array_json_hook(arr: np.ndarray) -> None:
                "col3": np.random.rand(1000),
            }
        ),
-        pd.DataFrame(
-            {"tz_datetime": pd.date_range("2024-01-01", periods=3, freq="D", tz="UTC")}
+        pytest.param(
+            pd.DataFrame(
+                {
+                    "tz_datetime": pd.date_range(
+                        "2024-01-01", periods=3, freq="D", tz="UTC"
+                    )
+                }
+            ),
+            marks=pytest.mark.skipif(
+                sys.version_info >= (3, 14), reason="NotImplementedError on Python 3.14"
+            ),
        ),
        pd.DataFrame({"timedelta": pd.to_timedelta([1, 2, 3], unit="D")}),
-        pd.DataFrame({"period": pd.period_range("2024-01", periods=3, freq="M")}),
+        pytest.param(
+            pd.DataFrame({"period": pd.period_range("2024-01", periods=3, freq="M")}),
+            marks=pytest.mark.skipif(
+                sys.version_info >= (3, 14), reason="NotImplementedError on Python 3.14"
+            ),
+        ),
        pd.DataFrame({"interval": pd.interval_range(start=0, end=3, periods=3)}),
        pd.DataFrame({"unicode": ["Hello 🌍", "Python 🐍", "Data 📊"]}),
        pd.DataFrame({"mixed": [1, "string", [1, 2, 3], {"key": "value"}]}),
@@ -450,7 +473,12 @@ def test_serde_jsonplus_pandas_dataframe(df: pd.DataFrame) -> None:
        pd.Series([1, 2, None]),
        pd.Series([1.1, None, 3.3]),
        pd.Series(["a", None, "c"]),
-        pd.Series(pd.Categorical(["a", "b", "a", "c"])),
+        pytest.param(
+            pd.Series(pd.Categorical(["a", "b", "a", "c"])),
+            marks=pytest.mark.skipif(
+                sys.version_info >= (3, 14), reason="NotImplementedError on Python 3.14"
+            ),
+        ),
        pd.Series([1, 2, 3], dtype="int8"),
        pd.Series([10, 20, 30], dtype="int16"),
        pd.Series([100, 200, 300], dtype="int32"),
@@ -1,13 +1,12 @@
 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 = [TavilySearchResults(max_results=1)]
+tools = []

 model_oai = ChatOpenAI(temperature=0)

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

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

 import msgspec

-from langgraph_cli.config import (
+from langgraph_cli.schemas import (
    AuthConfig,
    CheckpointerConfig,
    Config,
@@ -22,6 +22,7 @@ from langgraph_cli.config import (
    HttpConfig,
    IndexConfig,
    SecurityConfig,
+    SerdeConfig,
    StoreConfig,
    ThreadTTLConfig,
    TTLConfig,
@@ -112,6 +113,7 @@ def add_descriptions_to_schema(schema, cls):
                CorsConfig,
                ThreadTTLConfig,
                CheckpointerConfig,
+                SerdeConfig,
                TTLConfig,
                ConfigurableHeaderConfig,
            ]:
@@ -1 +1 @@
-__version__ = "0.4.4"
+__version__ = "0.4.6"
@@ -4,10 +4,12 @@ import pathlib
 import re
 import textwrap
 from collections import Counter
-from typing import Any, Literal, NamedTuple, TypedDict
+from typing import Literal, NamedTuple

 import click

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

@@ -17,504 +19,6 @@ 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")


@@ -1422,35 +926,51 @@ ADD {relpath} /deps/{name}
            ]
        )
    image_str = docker_tag(config, base_image, api_version)
-    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 \
+
+    # 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 \
            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:
@@ -0,0 +1,558 @@
+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",
+]
@@ -8,7 +8,7 @@ authors = [
 license = { text = "MIT" }
 requires-python = ">=3.11,<4.0"
 dependencies = [
-    "langgraph>=0.6.0,<0.7.0",
+    "langgraph>=0.6.0,<2",
    "langchain-core>=0.2.14",
 ]

@@ -472,6 +472,17 @@
      "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": [
            {
@@ -486,6 +497,38 @@
      },
      "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.",
@@ -472,6 +472,17 @@
      "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": [
            {
@@ -486,6 +497,38 @@
      },
      "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.",
@@ -141,6 +141,7 @@ 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
@@ -419,6 +419,7 @@ 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
@@ -482,6 +483,7 @@ 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
@@ -64,7 +64,7 @@ While LangGraph can be used standalone, it also integrates seamlessly with any L

 - [LangSmith](http://www.langchain.com/langsmith) — Helpful for agent evals and observability. Debug poor-performing LLM app runs, evaluate agent trajectories, gain visibility in production, and improve performance over time.
 - [LangSmith Deployment](https://langchain-ai.github.io/langgraph/concepts/langgraph_platform/) — Deploy and scale agents effortlessly with a purpose-built deployment platform for long running, stateful workflows. Discover, reuse, configure, and share agents across teams — and iterate quickly with visual prototyping in [LangGraph Studio](https://langchain-ai.github.io/langgraph/concepts/langgraph_studio/).
- [LangChain](https://python.langchain.com/docs/introduction/) – Provides integrations and composable components to streamline LLM application development.
+- [LangChain](https://docs.langchain.com/oss/python/langchain/overview) – Provides integrations and composable components to streamline LLM application development.

 > [!NOTE]
 > Looking for the JS version of LangGraph? See the [JS repo](https://github.com/langchain-ai/langgraphjs) and the [JS docs](https://langchain-ai.github.io/langgraphjs/).
@@ -81,4 +81,4 @@ While LangGraph can be used standalone, it also integrates seamlessly with any L

 ## Acknowledgements

-LangGraph is inspired by [Pregel](https://research.google/pubs/pub37252/) and [Apache Beam](https://beam.apache.org/). The public interface draws inspiration from [NetworkX](https://networkx.org/documentation/latest/). LangGraph is built by LangChain Inc, the creators of LangChain, but can be used without LangChain.
+LangGraph is inspired by [Pregel](https://research.google/pubs/pub37252/) and [Apache Beam](https://beam.apache.org/). The public interface draws inspiration from [NetworkX](https://networkx.org/documentation/latest/). LangGraph is built by LangChain Inc, the creators of LangChain, but can be used without LangChain.
@@ -77,6 +77,8 @@ CONF = cast(Literal["configurable"], sys.intern("configurable"))
 # key for the configurable dict in RunnableConfig
 NULL_TASK_ID = sys.intern("00000000-0000-0000-0000-000000000000")
 # the task_id to use for writes that are not associated with a task
+OVERWRITE = sys.intern("__overwrite__")
+# dict key for the overwrite value, used as `{'__overwrite__': value}`

 # redefined to avoid circular import with langgraph.constants
 _TAG_HIDDEN = sys.intern("langsmith:hidden")
@@ -1,12 +1,19 @@
 import collections.abc
 from collections.abc import Callable, Sequence
-from typing import Generic
+from typing import Any, Generic

 from typing_extensions import NotRequired, Required, Self

+from langgraph._internal._constants import OVERWRITE
 from langgraph._internal._typing import MISSING
 from langgraph.channels.base import BaseChannel, Value
-from langgraph.errors import EmptyChannelError
+from langgraph.errors import (
+    EmptyChannelError,
+    ErrorCode,
+    InvalidUpdateError,
+    create_error_message,
+)
+from langgraph.types import Overwrite

 __all__ = ("BinaryOperatorAggregate",)

@@ -22,6 +29,15 @@ def _strip_extras(t):  # type: ignore[no-untyped-def]
    return t


+def _get_overwrite(value: Any) -> tuple[bool, Any]:
+    """Inspects the given value and returns (is_overwrite, overwrite_value)."""
+    if isinstance(value, Overwrite):
+        return True, value.value
+    if isinstance(value, dict) and set(value.keys()) == {OVERWRITE}:
+        return True, value[OVERWRITE]
+    return False, None
+
+
 class BinaryOperatorAggregate(Generic[Value], BaseChannel[Value, Value, Value]):
    """Stores the result of applying a binary operator to the current value and each new value.

@@ -89,8 +105,21 @@ class BinaryOperatorAggregate(Generic[Value], BaseChannel[Value, Value, Value]):
        if self.value is MISSING:
            self.value = values[0]
            values = values[1:]
+        seen_overwrite: bool = False
        for value in values:
-            self.value = self.operator(self.value, value)
+            is_overwrite, overwrite_value = _get_overwrite(value)
+            if is_overwrite:
+                if seen_overwrite:
+                    msg = create_error_message(
+                        message="Can receive only one Overwrite value per super-step.",
+                        error_code=ErrorCode.INVALID_CONCURRENT_GRAPH_UPDATE,
+                    )
+                    raise InvalidUpdateError(msg)
+                self.value = overwrite_value
+                seen_overwrite = True
+                continue
+            if not seen_overwrite:
+                self.value = self.operator(self.value, value)
        return True

    def get(self) -> Value:
@@ -37,8 +37,8 @@ class ErrorCode(Enum):
 def create_error_message(*, message: str, error_code: ErrorCode) -> str:
    return (
        f"{message}\n"
-        "For troubleshooting, visit: https://python.langchain.com/docs/"
-        f"troubleshooting/errors/{error_code.value}"
+        "For troubleshooting, visit: https://docs.langchain.com/oss/python/langgraph/"
+        f"errors/{error_code.value}"
    )


@@ -81,9 +81,8 @@ 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). Defaults to False.
+            them (False).

    Returns:
        The created UI message.
@@ -63,6 +63,7 @@ from langgraph._internal._scratchpad import PregelScratchpad
 from langgraph._internal._typing import EMPTY_SEQ, MISSING
 from langgraph.channels.base import BaseChannel
 from langgraph.channels.topic import Topic
+from langgraph.channels.untracked_value import UntrackedValue
 from langgraph.constants import TAG_HIDDEN
 from langgraph.managed.base import ManagedValueMapping
 from langgraph.pregel._call import get_runnable_for_task, identifier
@@ -639,6 +640,7 @@ def prepare_single_task(
                    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"
@@ -1106,3 +1108,24 @@ class LazyAtomicCounter:
                if self._counter is None:
                    self._counter = itertools.count(0).__next__
        return self._counter()
+
+
+def sanitize_untracked_values_in_send(
+    packet: Send, channels: Mapping[str, BaseChannel]
+) -> Send:
+    """Pop any values belonging to UntrackedValue channels in Send.arg for safe checkpointing.
+
+    Send is often called with state to be passed to the dest node, which may contain
+    UntrackedValues at the top level. Send is not typed and arg may be a nested dict."""
+
+    if not isinstance(packet.arg, dict):
+        # Command
+        return packet
+
+    # top level keys should be the channel names
+    sanitized_arg = {
+        k: v
+        for k, v in packet.arg.items()
+        if not isinstance(channels.get(k), UntrackedValue)
+    }
+    return Send(node=packet.node, arg=sanitized_arg)
@@ -56,10 +56,12 @@ from langgraph._internal._constants import (
    NULL_TASK_ID,
    PUSH,
    RESUME,
+    TASKS,
 )
 from langgraph._internal._scratchpad import PregelScratchpad
 from langgraph._internal._typing import EMPTY_SEQ, MISSING
 from langgraph.channels.base import BaseChannel
+from langgraph.channels.untracked_value import UntrackedValue
 from langgraph.constants import TAG_HIDDEN
 from langgraph.errors import (
    EmptyInputError,
@@ -78,6 +80,7 @@ from langgraph.pregel._algo import (
    increment,
    prepare_next_tasks,
    prepare_single_task,
+    sanitize_untracked_values_in_send,
    should_interrupt,
    task_path_str,
 )
@@ -114,6 +117,7 @@ from langgraph.types import (
    Durability,
    PregelExecutableTask,
    RetryPolicy,
+    Send,
    StreamMode,
 )

@@ -320,6 +324,24 @@ class PregelLoop:
                w for w in self.checkpoint_pending_writes if w[0] != task_id
            ]
            writes_to_save = writes
+
+        # check if any writes are to an UntrackedValue channel
+        if any(
+            isinstance(channel, UntrackedValue) for channel in self.channels.values()
+        ):
+            # we do not persist untracked values in checkpoints
+            writes_to_save = [
+                # sanitize UntrackedValues that are nested within Send packets
+                (
+                    (c, sanitize_untracked_values_in_send(v, self.channels))
+                    if c == TASKS and isinstance(v, Send)
+                    else (c, v)
+                )
+                for c, v in writes_to_save
+                # dont persist UntrackedValue channel writes
+                if not isinstance(self.specs.get(c), UntrackedValue)
+            ]
+
        # save writes
        self.checkpoint_pending_writes.extend((task_id, c, v) for c, v in writes)
        if self.durability != "exit" and self.checkpointer_put_writes is not None:
@@ -735,6 +757,17 @@ class PregelLoop:
            id=self.checkpoint["id"] if exiting else None,
            updated_channels=self.updated_channels,
        )
+        # sanitize TASK channel in the checkpoint before saving (durability=="exit")
+        if TASKS in self.checkpoint["channel_values"] and any(
+            isinstance(channel, UntrackedValue) for channel in self.channels.values()
+        ):
+            sanitized_tasks = [
+                sanitize_untracked_values_in_send(value, self.channels)
+                if isinstance(value, Send)
+                else value
+                for value in self.checkpoint["channel_values"][TASKS]
+            ]
+            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 = (
@@ -55,6 +55,7 @@ __all__ = (
    "Command",
    "Durability",
    "interrupt",
+    "Overwrite",
 )

 Durability = Literal["sync", "async", "exit"]
@@ -283,26 +284,32 @@ 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.

-    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']}
+    !!! 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']}
+        ```
    """

    __slots__ = ("node", "arg")
@@ -342,10 +349,8 @@ 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
@@ -415,7 +420,8 @@ 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
@@ -516,3 +522,47 @@ def interrupt(value: Any) -> Any:
            ),
        )
    )
+
+
+@dataclass(slots=True)
+class Overwrite:
+    """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`.
+
+    !!! 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"]}
+        ```
+    """
+
+    value: Any
+    """The value to write directly to the channel, bypassing any reducer."""
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"

 [project]
 name = "langgraph"
-version = "1.0.1"
+version = "1.0.2"
 description = "Building stateful, multi-actor applications with LLMs"
 authors = []
 requires-python = ">=3.10"
@@ -27,7 +27,7 @@ dependencies = [
    "langchain-core>=0.1",
    "langgraph-checkpoint>=2.1.0,<4.0.0",
    "langgraph-sdk>=0.2.2,<0.3.0",
-    "langgraph-prebuilt>=1.0.0,<1.1.0",
+    "langgraph-prebuilt>=1.0.2,<1.1.0",
    "xxhash>=3.5.0",
    "pydantic>=2.7.4",
 ]
@@ -46,7 +46,7 @@ test = [
    "pytest-watcher",
    "pytest-xdist[psutil]",
    "pytest-repeat",
-    "langchain-core==1.0.0a1",
+    "langchain-core>=1.0.0",
    "langgraph-prebuilt",
    "langgraph-checkpoint",
    "langgraph-checkpoint-sqlite",
@@ -666,18 +666,18 @@
  	__end__([<p>__end__</p>]):::last
  	__start__ --> uno;
  	uno -.-> dos;
-  	uno -.-> subgraph_one;
+  	uno -.-> subgraph\3aone;
  	dos --> __end__;
-  	subgraph___end__ --> __end__;
+  	subgraph\3a__end__ --> __end__;
  	subgraph subgraph
-  	subgraph_one(one)
-  	subgraph_two(two)
-  	subgraph_three(three)
-  	subgraph___end__(<p>__end__</p>)
-  	subgraph_one -.-> subgraph_three;
-  	subgraph_one -.-> subgraph_two;
-  	subgraph_three --> subgraph___end__;
-  	subgraph_two --> subgraph___end__;
+  	subgraph\3aone(one)
+  	subgraph\3atwo(two)
+  	subgraph\3athree(three)
+  	subgraph\3a__end__(<p>__end__</p>)
+  	subgraph\3aone -.-> subgraph\3athree;
+  	subgraph\3aone -.-> subgraph\3atwo;
+  	subgraph\3athree --> subgraph\3a__end__;
+  	subgraph\3atwo --> subgraph\3a__end__;
  	end
  	classDef default fill:#f2f0ff,line-height:1.2
  	classDef first fill-opacity:0
@@ -705,11 +705,11 @@
  	__start__([<p>__start__</p>]):::first
  	side(side)
  	__end__([<p>__end__</p>]):::last
-  	__start__ --> inner_up;
-  	inner_up --> side;
+  	__start__ --> inner\3aup;
+  	inner\3aup --> side;
  	side --> __end__;
  	subgraph inner
-  	inner_up(up)
+  	inner\3aup(up)
  	end
  	classDef default fill:#f2f0ff,line-height:1.2
  	classDef first fill-opacity:0
@@ -868,19 +868,19 @@
  	__end__([<p>__end__</p>]):::last
  	__start__ -.-> tool_one;
  	__start__ -.-> tool_three;
-  	__start__ -.-> tool_two___start__;
+  	__start__ -.-> tool_two\3a__start__;
  	tool_one --> __end__;
  	tool_three --> __end__;
-  	tool_two___end__ --> __end__;
+  	tool_two\3a__end__ --> __end__;
  	subgraph tool_two
-  	tool_two___start__(<p>__start__</p>)
-  	tool_two_tool_two_slow(tool_two_slow)
-  	tool_two_tool_two_fast(tool_two_fast)
-  	tool_two___end__(<p>__end__</p>)
-  	tool_two___start__ -.-> tool_two_tool_two_fast;
-  	tool_two___start__ -.-> tool_two_tool_two_slow;
-  	tool_two_tool_two_fast --> tool_two___end__;
-  	tool_two_tool_two_slow --> tool_two___end__;
+  	tool_two\3a__start__(<p>__start__</p>)
+  	tool_two\3atool_two_slow(tool_two_slow)
+  	tool_two\3atool_two_fast(tool_two_fast)
+  	tool_two\3a__end__(<p>__end__</p>)
+  	tool_two\3a__start__ -.-> tool_two\3atool_two_fast;
+  	tool_two\3a__start__ -.-> tool_two\3atool_two_slow;
+  	tool_two\3atool_two_fast --> tool_two\3a__end__;
+  	tool_two\3atool_two_slow --> tool_two\3a__end__;
  	end
  	classDef default fill:#f2f0ff,line-height:1.2
  	classDef first fill-opacity:0
@@ -891,13 +891,13 @@
 # name: test_repeat_condition
  '''
  graph TD;
-  	Call_Tool -.-> Chart_Generator;
-  	Call_Tool -.-> Researcher;
-  	Chart_Generator -. &nbsp;call_tool&nbsp; .-> Call_Tool;
-  	Chart_Generator -. &nbsp;continue&nbsp; .-> Researcher;
-  	Chart_Generator -. &nbsp;end&nbsp; .-> __end__;
-  	Researcher -. &nbsp;call_tool&nbsp; .-> Call_Tool;
-  	Researcher -. &nbsp;continue&nbsp; .-> Chart_Generator;
+  	Call\20Tool -.-> Chart\20Generator;
+  	Call\20Tool -.-> Researcher;
+  	Chart\20Generator -. &nbsp;call_tool&nbsp; .-> Call\20Tool;
+  	Chart\20Generator -. &nbsp;continue&nbsp; .-> Researcher;
+  	Chart\20Generator -. &nbsp;end&nbsp; .-> __end__;
+  	Researcher -. &nbsp;call_tool&nbsp; .-> Call\20Tool;
+  	Researcher -. &nbsp;continue&nbsp; .-> Chart\20Generator;
  	Researcher -. &nbsp;end&nbsp; .-> __end__;
  	__start__ --> Researcher;
  	Researcher -. &nbsp;redo&nbsp; .-> Researcher;
@@ -939,25 +939,25 @@
  	__end__([<p>__end__</p>]):::last
  	__start__ --> gp_one;
  	gp_one -. &nbsp;1&nbsp; .-> __end__;
-  	gp_one -. &nbsp;0&nbsp; .-> gp_two___start__;
-  	gp_two___end__ --> gp_one;
+  	gp_one -. &nbsp;0&nbsp; .-> gp_two\3a__start__;
+  	gp_two\3a__end__ --> gp_one;
  	subgraph gp_two
-  	gp_two___start__(<p>__start__</p>)
-  	gp_two_p_one(p_one)
-  	gp_two___end__(<p>__end__</p>)
-  	gp_two___start__ --> gp_two_p_one;
-  	gp_two_p_one -. &nbsp;1&nbsp; .-> gp_two___end__;
-  	gp_two_p_one -. &nbsp;0&nbsp; .-> gp_two_p_two___start__;
-  	gp_two_p_two___end__ --> gp_two_p_one;
+  	gp_two\3a__start__(<p>__start__</p>)
+  	gp_two\3ap_one(p_one)
+  	gp_two\3a__end__(<p>__end__</p>)
+  	gp_two\3a__start__ --> gp_two\3ap_one;
+  	gp_two\3ap_one -. &nbsp;1&nbsp; .-> gp_two\3a__end__;
+  	gp_two\3ap_one -. &nbsp;0&nbsp; .-> gp_two\3ap_two\3a__start__;
+  	gp_two\3ap_two\3a__end__ --> gp_two\3ap_one;
  	subgraph p_two
-  	gp_two_p_two___start__(<p>__start__</p>)
-  	gp_two_p_two_c_one(c_one)
-  	gp_two_p_two_c_two(c_two)
-  	gp_two_p_two___end__(<p>__end__</p>)
-  	gp_two_p_two___start__ --> gp_two_p_two_c_one;
-  	gp_two_p_two_c_one -. &nbsp;1&nbsp; .-> gp_two_p_two___end__;
-  	gp_two_p_two_c_one -. &nbsp;0&nbsp; .-> gp_two_p_two_c_two;
-  	gp_two_p_two_c_two --> gp_two_p_two_c_one;
+  	gp_two\3ap_two\3a__start__(<p>__start__</p>)
+  	gp_two\3ap_two\3ac_one(c_one)
+  	gp_two\3ap_two\3ac_two(c_two)
+  	gp_two\3ap_two\3a__end__(<p>__end__</p>)
+  	gp_two\3ap_two\3a__start__ --> gp_two\3ap_two\3ac_one;
+  	gp_two\3ap_two\3ac_one -. &nbsp;1&nbsp; .-> gp_two\3ap_two\3a__end__;
+  	gp_two\3ap_two\3ac_one -. &nbsp;0&nbsp; .-> gp_two\3ap_two\3ac_two;
+  	gp_two\3ap_two\3ac_two --> gp_two\3ap_two\3ac_one;
  	end
  	end
  	classDef default fill:#f2f0ff,line-height:1.2
@@ -979,17 +979,17 @@
  	__end__([<p>__end__</p>]):::last
  	__start__ --> p_one;
  	p_one -. &nbsp;1&nbsp; .-> __end__;
-  	p_one -. &nbsp;0&nbsp; .-> p_two___start__;
-  	p_two___end__ --> p_one;
+  	p_one -. &nbsp;0&nbsp; .-> p_two\3a__start__;
+  	p_two\3a__end__ --> p_one;
  	subgraph p_two
-  	p_two___start__(<p>__start__</p>)
-  	p_two_c_one(c_one)
-  	p_two_c_two(c_two)
-  	p_two___end__(<p>__end__</p>)
-  	p_two___start__ --> p_two_c_one;
-  	p_two_c_one -. &nbsp;1&nbsp; .-> p_two___end__;
-  	p_two_c_one -. &nbsp;0&nbsp; .-> p_two_c_two;
-  	p_two_c_two --> p_two_c_one;
+  	p_two\3a__start__(<p>__start__</p>)
+  	p_two\3ac_one(c_one)
+  	p_two\3ac_two(c_two)
+  	p_two\3a__end__(<p>__end__</p>)
+  	p_two\3a__start__ --> p_two\3ac_one;
+  	p_two\3ac_one -. &nbsp;1&nbsp; .-> p_two\3a__end__;
+  	p_two\3ac_one -. &nbsp;0&nbsp; .-> p_two\3ac_two;
+  	p_two\3ac_two --> p_two\3ac_one;
  	end
  	classDef default fill:#f2f0ff,line-height:1.2
  	classDef first fill-opacity:0
@@ -7,6 +7,7 @@ from langgraph._internal._typing import MISSING
 from langgraph.channels.binop import BinaryOperatorAggregate
 from langgraph.channels.last_value import LastValue
 from langgraph.channels.topic import Topic
+from langgraph.channels.untracked_value import UntrackedValue
 from langgraph.errors import EmptyChannelError, InvalidUpdateError

 pytestmark = pytest.mark.anyio
@@ -87,3 +88,32 @@ def test_binop() -> None:
    checkpoint = channel.checkpoint()
    channel = BinaryOperatorAggregate(int, operator.add).from_checkpoint(checkpoint)
    assert channel.get() == 10
+
+
+def test_untracked_value() -> None:
+    channel = UntrackedValue(dict).from_checkpoint(MISSING)
+    assert channel.ValueType is dict
+    assert channel.UpdateType is dict
+
+    # UntrackedValue should start empty
+    with pytest.raises(EmptyChannelError):
+        channel.get()
+
+    # Should be able to update with a value
+    test_data = {"session": "test", "temp": "dir"}
+    channel.update([test_data])
+    assert channel.get() == test_data
+
+    # Update with new value
+    new_data = {"session": "updated", "temp": "newdir"}
+    channel.update([new_data])
+    assert channel.get() == new_data
+
+    # On checkpoint, UntrackedValue should return MISSING
+    checkpoint = channel.checkpoint()
+    assert checkpoint is MISSING
+
+    # Creating from checkpoint with MISSING should start empty
+    new_channel = UntrackedValue(dict).from_checkpoint(checkpoint)
+    with pytest.raises(EmptyChannelError):
+        new_channel.get()
@@ -44,6 +44,7 @@ from langgraph.channels.binop import BinaryOperatorAggregate
 from langgraph.channels.ephemeral_value import EphemeralValue
 from langgraph.channels.last_value import LastValue
 from langgraph.channels.topic import Topic
+from langgraph.channels.untracked_value import UntrackedValue
 from langgraph.config import get_stream_writer
 from langgraph.errors import GraphRecursionError, InvalidUpdateError, ParentCommand
 from langgraph.func import entrypoint, task
@@ -60,6 +61,7 @@ from langgraph.types import (
    Command,
    Durability,
    Interrupt,
+    Overwrite,
    PregelTask,
    RetryPolicy,
    Send,
@@ -8597,3 +8599,209 @@ def test_multiple_writes_same_channel_from_same_node(
            "values": {"foo": ""},
        },
    ]
+
+
+def test_send_with_untracked_value(sync_checkpointer: BaseCheckpointSaver):
+    """Test that Send objects work correctly with untracked values in state."""
+
+    class UnserializableResource:
+        def __init__(self, name: str):
+            self.name = name
+            self.lock = threading.Lock()
+
+    class State(TypedDict):
+        messages: Annotated[list[str], operator.add]
+        session_resource: Annotated[UnserializableResource, UntrackedValue]
+
+    def setup_node(state: State) -> State:
+        resource = UnserializableResource("test_session")
+        return {"messages": ["setup complete"], "session_resource": resource}
+
+    def send_to_tool(state: State):
+        return [Send("tool_node", state)]
+
+    def tool_node(state: State) -> State:
+        resource = state["session_resource"]
+        assert isinstance(resource, UnserializableResource)
+        assert resource.name == "test_session"
+
+        new_resource = UnserializableResource("new_session")
+
+        return {
+            "messages": [f"tool used resource: {resource.name}"],
+            "session_resource": new_resource,
+        }
+
+    graph = StateGraph(State)
+    graph.add_node("setup", setup_node)
+    graph.add_node("tool_node", tool_node)
+    graph.add_edge(START, "setup")
+    graph.add_conditional_edges("setup", send_to_tool)
+
+    app = graph.compile(checkpointer=sync_checkpointer)
+    config = {"configurable": {"thread_id": "1"}}
+    result = app.invoke({}, config)
+
+    assert len(result["messages"]) == 2
+    assert result["messages"][0] == "setup complete"
+    assert result["messages"][1] == "tool used resource: test_session"
+    assert result["session_resource"].name == "new_session"
+
+    state = app.get_state(config)
+    assert "session_resource" not in state.values
+
+
+def test_send_with_untracked_value_overlapping_keys(
+    sync_checkpointer: BaseCheckpointSaver,
+):
+    """Test that Send objects work correctly with untracked values in state."""
+
+    class State(TypedDict):
+        dictionary: dict
+        session_resource: Annotated[str, UntrackedValue]
+
+    def setup_node(state: State) -> State:
+        return {}
+
+    def send_to_tool(state: State):
+        return [
+            Send(
+                "tool_node",
+                {
+                    "dictionary": {"session_resource": "legal_value"},
+                    "session_resource": "illegal_value",
+                },
+            )
+        ]
+
+    def tool_node(state: State) -> State:
+        print(f"STATE: {state}")
+        assert state["dictionary"] == {"session_resource": "legal_value"}
+        assert state["session_resource"] == "illegal_value"
+
+        return {
+            "dictionary": state["dictionary"],
+            "session_resource": "new_illegal_value",
+        }
+
+    graph = StateGraph(State)
+    graph.add_node("setup", setup_node)
+    graph.add_node("tool_node", tool_node)
+    graph.add_edge(START, "setup")
+    graph.add_conditional_edges("setup", send_to_tool)
+
+    app = graph.compile(checkpointer=sync_checkpointer)
+    config = {"configurable": {"thread_id": "1"}}
+    result = app.invoke({}, config)
+
+    assert result["session_resource"] == "new_illegal_value"
+    state = app.get_state(config)
+    assert "session_resource" not in state.values
+    assert state.values.get("dictionary") == {"session_resource": "legal_value"}
+
+
+@pytest.mark.parametrize("as_json", [False, True])
+def test_overwrite_sequential(
+    sync_checkpointer: BaseCheckpointSaver, as_json: bool
+) -> None:
+    """Test a sequential chain of nodes where the last node uses Overwrite to bypass a reducer and write a value directly to the channel."""
+
+    class State(TypedDict):
+        messages: Annotated[list, operator.add]
+
+    def node_a(state: State):
+        return {"messages": ["a"]}
+
+    def node_b(state: State):
+        overwrite = {"__overwrite__": ["b"]} if as_json else Overwrite(["b"])
+        return {"messages": overwrite}
+
+    builder = StateGraph(State)
+    builder.add_node("node_a", node_a)
+    builder.add_node("node_b", node_b)
+    builder.add_edge(START, "node_a")
+    builder.add_edge("node_a", "node_b")
+
+    graph = builder.compile(checkpointer=sync_checkpointer)
+    config = {"configurable": {"thread_id": "1"}}
+    result = graph.invoke({"messages": ["START"]}, config)
+    # a is overwritten by b
+    assert result == {"messages": ["b"]}
+
+
+@pytest.mark.parametrize("as_json", [False, True])
+def test_overwrite_parallel(
+    sync_checkpointer: BaseCheckpointSaver, as_json: bool
+) -> None:
+    """Test parallel nodes where max one node uses Overwrite to bypass a reducer and write a value directly to the channel."""
+
+    class State(TypedDict):
+        messages: Annotated[list, operator.add]
+
+    def node_a(state: State):
+        return {"messages": ["a"]}
+
+    def node_b(state: State):
+        overwrite = {"__overwrite__": ["b"]} if as_json else Overwrite(["b"])
+        return {"messages": overwrite}
+
+    def node_c(state: State):
+        return {"messages": ["c"]}
+
+    def node_d(state: State):
+        return {"messages": ["d"]}
+
+    builder = StateGraph(State)
+    builder.add_node("node_a", node_a)
+    builder.add_node("node_b", node_b)
+    builder.add_node("node_c", node_c)
+    builder.add_node("node_d", node_d)
+    builder.add_edge(START, "node_a")
+    builder.add_edge("node_a", "node_b")
+    builder.add_edge("node_a", "node_c")
+    builder.add_edge("node_b", "node_d")
+    builder.add_edge("node_c", "node_d")
+
+    graph = builder.compile(checkpointer=sync_checkpointer)
+    config = {"configurable": {"thread_id": "1"}}
+    result = graph.invoke({"messages": ["START"]}, config)
+    # a, c are overwritten by b, then d is written
+    assert result == {"messages": ["b", "d"]}
+
+
+@pytest.mark.parametrize("as_json", [False, True])
+def test_overwrite_parallel_error(
+    sync_checkpointer: BaseCheckpointSaver, as_json: bool
+) -> None:
+    """Test parallel nodes where more than one node uses Overwrite to bypass a reducer and write a value directly to the channel. In this case, InvalidUpdateError should be raised."""
+
+    class State(TypedDict):
+        messages: Annotated[list, operator.add]
+
+    def node_a(state: State):
+        return {"messages": ["a"]}
+
+    def node_b(state: State):
+        overwrite = {"__overwrite__": ["b"]} if as_json else Overwrite(["b"])
+        return {"messages": overwrite}
+
+    def node_c(state: State):
+        overwrite = {"__overwrite__": ["c"]} if as_json else Overwrite(["c"])
+        return {"messages": overwrite}
+
+    builder = StateGraph(State)
+    builder.add_node("node_a", node_a)
+    builder.add_node("node_b", node_b)
+    builder.add_node("node_c", node_c)
+    builder.add_edge(START, "node_a")
+    builder.add_edge("node_a", "node_b")
+    builder.add_edge("node_a", "node_c")
+    builder.add_edge("node_b", END)
+    builder.add_edge("node_c", END)
+
+    graph = builder.compile(checkpointer=sync_checkpointer)
+    config = {"configurable": {"thread_id": "1"}}
+    with pytest.raises(
+        InvalidUpdateError, match="Can receive only one Overwrite value per super-step."
+    ):
+        graph.invoke({"messages": ["START"]}, config)
@@ -1124,7 +1124,6 @@ async def test_remote_graph_basic_invoke(remote_graph: RemoteGraph) -> None:
        "type": "ai",
        "name": None,
        "id": "ai3",
-        "example": False,
        "tool_calls": [],
        "invalid_tool_calls": [],
        "usage_metadata": None,
@@ -1,5 +1,5 @@
 version = 1
-revision = 3
+revision = 2
 requires-python = ">=3.10"
 resolution-markers = [
    "python_full_version >= '3.14'",
@@ -1327,7 +1327,7 @@ wheels = [

 [[package]]
 name = "langchain-core"
-version = "1.0.0a1"
+version = "1.0.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "jsonpatch" },
@@ -1338,14 +1338,14 @@ dependencies = [
    { name = "tenacity" },
    { name = "typing-extensions" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/d9/c8/25d9ff74f8d4184dfce0e5c3332d5a1c9bead5db5fcf9ed1f1d4a826a804/langchain_core-1.0.0a1.tar.gz", hash = "sha256:b1acc3342911c3a95db0e0bbfa600c5a528b2e46d6e8faa90cbc6f154a29c582", size = 603792, upload-time = "2025-08-27T17:41:44.264Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/ad/d0/9db6d375ecf8bd498fcc87016e43c3d930ddbfbacf9a1e99018ada4e824f/langchain_core-1.0.0.tar.gz", hash = "sha256:8e81c94a22fa3a362a0f101bbd1271bf3725e50cf1e31c84e8f4a1c731279785", size = 764484, upload-time = "2025-10-17T13:48:24.408Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/3e/41/925fb1f2dfb9d85c492c9d5654cbede160e8e3aab5a91c25b557235e5578/langchain_core-1.0.0a1-py3-none-any.whl", hash = "sha256:83fe163134bc52245962f45f7098ec348eb85c1f02a75eb35d1771f80fa40420", size = 473126, upload-time = "2025-08-27T17:41:42.896Z" },
+    { url = "https://files.pythonhosted.org/packages/68/6a/8dd566cb7379d6e3a921f94713babba2f71cbed65c73c784c649c1fd7d4e/langchain_core-1.0.0-py3-none-any.whl", hash = "sha256:a94561bf75dd097c7d6e3864950f28dadc963f0bd810114de4095f41f634059b", size = 467157, upload-time = "2025-10-17T13:48:23.138Z" },
 ]

 [[package]]
 name = "langgraph"
-version = "1.0.1"
+version = "1.0.2"
 source = { editable = "." }
 dependencies = [
    { name = "langchain-core" },
@@ -1429,7 +1429,7 @@ requires-dist = [
 dev = [
    { name = "httpx" },
    { name = "jupyter" },
-    { name = "langchain-core", specifier = "==1.0.0a1" },
+    { name = "langchain-core", specifier = ">=1.0.0" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
    { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
    { name = "langgraph-checkpoint-sqlite", editable = "../checkpoint-sqlite" },
@@ -1462,7 +1462,7 @@ lint = [
 ]
 test = [
    { name = "httpx" },
-    { name = "langchain-core", specifier = "==1.0.0a1" },
+    { name = "langchain-core", specifier = ">=1.0.0" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
    { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
    { name = "langgraph-checkpoint-sqlite", editable = "../checkpoint-sqlite" },
@@ -1710,7 +1710,7 @@ test = [

 [[package]]
 name = "langgraph-prebuilt"
-version = "1.0.1"
+version = "1.0.2"
 source = { editable = "../prebuilt" }
 dependencies = [
    { name = "langchain-core" },
@@ -1719,7 +1719,7 @@ dependencies = [

 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = ">=0.3.67" },
+    { name = "langchain-core", specifier = ">=1.0.0" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
 ]

@@ -1732,6 +1732,7 @@ dev = [
    { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
    { name = "langgraph-checkpoint-sqlite", editable = "../checkpoint-sqlite" },
    { name = "mypy" },
+    { name = "psycopg-binary" },
    { name = "pytest" },
    { name = "pytest-asyncio" },
    { name = "pytest-mock" },
@@ -1750,6 +1751,7 @@ test = [
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
    { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
    { name = "langgraph-checkpoint-sqlite", editable = "../checkpoint-sqlite" },
+    { name = "psycopg-binary" },
    { name = "pytest" },
    { name = "pytest-asyncio" },
    { name = "pytest-mock" },
@@ -5,6 +5,7 @@ from langgraph.prebuilt.tool_node import (
    InjectedState,
    InjectedStore,
    ToolNode,
+    ToolRuntime,
    tools_condition,
 )
 from langgraph.prebuilt.tool_validator import ValidationNode
@@ -16,4 +17,5 @@ __all__ = [
    "ValidationNode",
    "InjectedState",
    "InjectedStore",
+    "ToolRuntime",
 ]
@@ -44,7 +44,7 @@ from langgraph.warnings import LangGraphDeprecatedSinceV10
 from pydantic import BaseModel
 from typing_extensions import NotRequired, TypedDict, deprecated

-from langgraph.prebuilt.tool_node import ToolNode
+from langgraph.prebuilt.tool_node import ToolCallWithContext, ToolNode

 StructuredResponse = dict | BaseModel
 StructuredResponseSchema = dict | type[BaseModel]
@@ -309,37 +309,40 @@ 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()`) or
-              string identifier (e.g., `"openai:gpt-4"`)
+            - **Static model**: A chat model instance (e.g.,
+                [`ChatOpenAI`][langchain_openai.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.

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

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

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

            !!! note "Dynamic Model Requirements"

@@ -351,23 +354,26 @@ 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,
-                - 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.
+            - 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.

            !!! Important
                `response_format` requires the model to support `.with_structured_output`
@@ -428,13 +434,16 @@ 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
@@ -443,7 +452,7 @@ 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.

@@ -453,14 +462,14 @@ 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
@@ -826,11 +835,17 @@ def create_react_agent(
            elif version == "v2":
                if post_model_hook is not None:
                    return "post_model_hook"
-                tool_calls = [
-                    tool_node.inject_tool_args(call, state, store)  # type: ignore[arg-type]
+                return [
+                    Send(
+                        "tools",
+                        ToolCallWithContext(
+                            __type="tool_call_with_context",
+                            tool_call=call,
+                            state=state,
+                        ),
+                    )
                    for call in last_message.tool_calls
                ]
-                return [Send("tools", [tool_call]) for tool_call in tool_calls]

    # Define a new graph
    workflow = StateGraph(
@@ -911,11 +926,17 @@ def create_react_agent(
            ]

            if pending_tool_calls:
-                pending_tool_calls = [
-                    tool_node.inject_tool_args(call, state, store)  # type: ignore[arg-type]
+                return [
+                    Send(
+                        "tools",
+                        ToolCallWithContext(
+                            __type="tool_call_with_context",
+                            tool_call=call,
+                            state=state,
+                        ),
+                    )
                    for call in pending_tool_calls
                ]
-                return [Send("tools", [tool_call]) for tool_call in pending_tool_calls]
            elif isinstance(messages[-1], ToolMessage):
                return entrypoint
            elif response_format is not None:
@@ -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
    """

@@ -89,14 +89,16 @@ 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"]
@@ -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

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

    Returns:
-        (Union[Dict[str, List[ToolMessage]], Sequence[ToolMessage]]): A list of ToolMessages with the validated content or error messages.
+        (Union[Dict[str, List[ToolMessage]], Sequence[ToolMessage]]): A list of
+            `ToolMessage` objects 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 = "1.0.1"
+version = "1.0.2"
 description = "Library with high-level APIs for creating and executing LangGraph agents and tools."
 authors = []
 requires-python = ">=3.10"
@@ -25,7 +25,7 @@ classifiers = [
 ]
 dependencies = [
    "langgraph-checkpoint>=2.1.0,<4.0.0",
-    "langchain-core>=0.3.67",
+    "langchain-core>=1.0.0",
 ]

 [project.urls]
@@ -43,6 +43,7 @@ test = [
    "langgraph-checkpoint-sqlite",
    "langgraph-checkpoint-postgres",
    "syrupy",
+    "psycopg-binary",
 ]
 lint = [
    "ruff",
@@ -8,6 +8,7 @@ from typing import (
    Literal,
    TypeVar,
 )
+from unittest.mock import Mock

 import pytest
 from langchain_core.language_models import BaseChatModel
@@ -64,6 +65,29 @@ pytestmark = pytest.mark.anyio
 REACT_TOOL_CALL_VERSIONS = ["v1", "v2"]


+def _create_mock_runtime(store: BaseStore | None = None) -> Mock:
+    """Create a mock Runtime object for testing ToolNode outside of graph context.
+
+    This helper is needed because ToolNode._func expects a Runtime parameter
+    which is injected by RunnableCallable from config["configurable"]["__pregel_runtime"].
+    When testing ToolNode directly (outside a graph), we need to provide this manually.
+    """
+    mock_runtime = Mock()
+    mock_runtime.store = store
+    mock_runtime.context = None
+    mock_runtime.stream_writer = lambda *args, **kwargs: None
+    return mock_runtime
+
+
+def _create_config_with_runtime(store: BaseStore | None = None) -> RunnableConfig:
+    """Create a RunnableConfig with mock Runtime for testing ToolNode.
+
+    Returns:
+        RunnableConfig with __pregel_runtime in configurable dict.
+    """
+    return {"configurable": {"__pregel_runtime": _create_mock_runtime(store)}}
+
+
@pytest.mark.parametrize("version", REACT_TOOL_CALL_VERSIONS)
 def test_no_prompt(sync_checkpointer: BaseCheckpointSaver, version: str) -> None:
    model = FakeToolCallingModel()
@@ -327,7 +351,8 @@ def test_model_with_tools(tool_style: str, version: str, include_builtin: bool):
                    ],
                )
            ]
-        }
+        },
+        config=_create_config_with_runtime(),
    )
    tool_messages: ToolMessage = result["messages"][-2:]
    for tool_message in tool_messages:
@@ -728,37 +753,13 @@ def test_tool_node_inject_state(schema_: type[T]) -> None:
            "type": "tool_call",
        }
        msg = AIMessage("hi?", tool_calls=[tool_call])
-        result = node.invoke(schema_(**{"messages": [msg], "foo": "bar"}))
+        result = node.invoke(
+            schema_(**{"messages": [msg], "foo": "bar"}),
+            config=_create_config_with_runtime(),
+        )
        tool_message = result["messages"][-1]
        assert tool_message.content == "bar", f"Failed for tool={tool_name}"

-        if tool_name == "tool3":
-            failure_input = None
-            try:
-                failure_input = schema_(**{"messages": [msg], "notfoo": "bar"})
-            except Exception:
-                pass
-            if failure_input is not None:
-                with pytest.raises(KeyError):
-                    node.invoke(failure_input)
-
-                with pytest.raises(ValueError):
-                    node.invoke([msg])
-        else:
-            failure_input = None
-            try:
-                failure_input = schema_(**{"messages": [msg], "notfoo": "bar"})
-            except Exception:
-                # We'd get a validation error from pydantic state and wouldn't make it to the node
-                # anyway
-                pass
-            if failure_input is not None:
-                messages_ = node.invoke(failure_input)
-                tool_message = messages_["messages"][-1]
-                assert "KeyError" in tool_message.content
-                tool_message = node.invoke([msg])[-1]
-                assert "KeyError" in tool_message.content
-
    tool_call = {
        "name": "tool4",
        "args": {"some_val": 1},
@@ -766,11 +767,13 @@ def test_tool_node_inject_state(schema_: type[T]) -> None:
        "type": "tool_call",
    }
    msg = AIMessage("hi?", tool_calls=[tool_call])
-    result = node.invoke(schema_(**{"messages": [msg], "foo": ""}))
+    result = node.invoke(
+        schema_(**{"messages": [msg], "foo": ""}), config=_create_config_with_runtime()
+    )
    tool_message = result["messages"][-1]
    assert tool_message.content == "hi?"

-    result = node.invoke([msg])
+    result = node.invoke([msg], config=_create_config_with_runtime())
    tool_message = result[-1]
    assert tool_message.content == "hi?"

@@ -882,7 +885,9 @@ def test_tool_node_inject_store() -> None:
            "type": "tool_call",
        }
        msg = AIMessage("hi?", tool_calls=[tool_call])
-        node_result = node.invoke({"messages": [msg]}, store=store)
+        node_result = node.invoke(
+            {"messages": [msg]}, config=_create_config_with_runtime(store=store)
+        )
        graph_result = graph.invoke({"messages": [msg]})
        for result in (node_result, graph_result):
            result["messages"][-1]
@@ -898,7 +903,10 @@ def test_tool_node_inject_store() -> None:
        "type": "tool_call",
    }
    msg = AIMessage("hi?", tool_calls=[tool_call])
-    node_result = node.invoke({"messages": [msg], "bar": "baz"}, store=store)
+    node_result = node.invoke(
+        {"messages": [msg], "bar": "baz"},
+        config=_create_config_with_runtime(store=store),
+    )
    graph_result = graph.invoke({"messages": [msg], "bar": "baz"})
    for result in (node_result, graph_result):
        result["messages"][-1]
@@ -923,7 +931,8 @@ def test_tool_node_ensure_utf8() -> None:
    tools = [get_day_list]
    tool_calls = [ToolCall(name=get_day_list.name, args={"days": data}, id="test_id")]
    outputs: list[ToolMessage] = ToolNode(tools).invoke(
-        [AIMessage(content="", tool_calls=tool_calls)]
+        [AIMessage(content="", tool_calls=tool_calls)],
+        config=_create_config_with_runtime(),
    )
    assert outputs[0].content == json.dumps(data, ensure_ascii=False)

@@ -1,39 +1,92 @@
+import contextlib
+import dataclasses
+import json
+import sys
+from functools import partial
 from typing import (
    Annotated,
    Any,
+    NoReturn,
+    TypeVar,
 )
+from unittest.mock import Mock

 import pytest
 from langchain_core.messages import (
    AIMessage,
+    AnyMessage,
+    HumanMessage,
    RemoveMessage,
+    ToolCall,
    ToolMessage,
 )
+from langchain_core.runnables.config import RunnableConfig
 from langchain_core.tools import BaseTool, ToolException
 from langchain_core.tools import tool as dec_tool
+from langgraph.config import get_stream_writer
 from langgraph.errors import GraphBubbleUp, GraphInterrupt
-from langgraph.graph.message import REMOVE_ALL_MESSAGES
+from langgraph.graph import START, MessagesState, StateGraph
+from langgraph.graph.message import REMOVE_ALL_MESSAGES, add_messages
+from langgraph.store.base import BaseStore
+from langgraph.store.memory import InMemoryStore
 from langgraph.types import Command, Send
-from pydantic import BaseModel, ValidationError
-from pydantic.v1 import ValidationError as ValidationErrorV1
+from pydantic import BaseModel
+from pydantic.v1 import BaseModel as BaseModelV1
+from typing_extensions import TypedDict

-from langgraph.prebuilt import ToolNode
-from langgraph.prebuilt.tool_node import TOOL_CALL_ERROR_TEMPLATE
+from langgraph.prebuilt import (
+    InjectedState,
+    InjectedStore,
+    ToolNode,
+)
+from langgraph.prebuilt.tool_node import (
+    TOOL_CALL_ERROR_TEMPLATE,
+    ToolInvocationError,
+    tools_condition,
+)
+
+from .messages import _AnyIdHumanMessage, _AnyIdToolMessage
+from .model import FakeToolCallingModel

 pytestmark = pytest.mark.anyio


+def _create_mock_runtime(store: BaseStore | None = None) -> Mock:
+    """Create a mock Runtime object for testing ToolNode outside of graph context.
+
+    This helper is needed because ToolNode._func expects a Runtime parameter
+    which is injected by RunnableCallable from config["configurable"]["__pregel_runtime"].
+    When testing ToolNode directly (outside a graph), we need to provide this manually.
+    """
+    mock_runtime = Mock()
+    mock_runtime.store = store
+    mock_runtime.context = None
+    mock_runtime.stream_writer = lambda *args, **kwargs: None
+    return mock_runtime
+
+
+def _create_config_with_runtime(store: BaseStore | None = None) -> RunnableConfig:
+    """Create a RunnableConfig with mock Runtime for testing ToolNode.
+
+    Returns:
+        RunnableConfig with __pregel_runtime in configurable dict.
+    """
+    return {"configurable": {"__pregel_runtime": _create_mock_runtime(store)}}
+
+
 def tool1(some_val: int, some_other_val: str) -> str:
    """Tool 1 docstring."""
    if some_val == 0:
-        raise ValueError("Test error")
+        msg = "Test error"
+        raise ValueError(msg)
    return f"{some_val} - {some_other_val}"


 async def tool2(some_val: int, some_other_val: str) -> str:
    """Tool 2 docstring."""
    if some_val == 0:
-        raise ToolException("Test error")
+        msg = "Test error"
+        raise ToolException(msg)
    return f"tool2: {some_val} - {some_other_val}"


@@ -53,15 +106,17 @@ async def tool4(some_val: int, some_other_val: str) -> str:


@dec_tool
-def tool5(some_val: int):
+def tool5(some_val: int) -> NoReturn:
    """Tool 5 docstring."""
-    raise ToolException("Test error")
+    msg = "Test error"
+    raise ToolException(msg)


 tool5.handle_tool_error = "foo"


-async def test_tool_node():
+async def test_tool_node() -> None:
+    """Test tool node."""
    result = ToolNode([tool1]).invoke(
        {
            "messages": [
@@ -76,7 +131,8 @@ async def test_tool_node():
                    ],
                )
            ]
-        }
+        },
+        config=_create_config_with_runtime(),
    )

    tool_message: ToolMessage = result["messages"][-1]
@@ -98,7 +154,8 @@ async def test_tool_node():
                    ],
                )
            ]
-        }
+        },
+        config=_create_config_with_runtime(),
    )

    tool_message: ToolMessage = result2["messages"][-1]
@@ -120,7 +177,8 @@ async def test_tool_node():
                    ],
                )
            ]
-        }
+        },
+        config=_create_config_with_runtime(),
    )
    tool_message: ToolMessage = result3["messages"][-1]
    assert tool_message.type == "tool"
@@ -145,7 +203,8 @@ async def test_tool_node():
                    ],
                )
            ]
-        }
+        },
+        config=_create_config_with_runtime(),
    )
    tool_message: ToolMessage = result4["messages"][-1]
    assert tool_message.type == "tool"
@@ -153,7 +212,7 @@ async def test_tool_node():
    assert tool_message.tool_call_id == "some 3"


-async def test_tool_node_tool_call_input():
+async def test_tool_node_tool_call_input() -> None:
    # Single tool call
    tool_call_1 = {
        "name": "tool1",
@@ -161,7 +220,9 @@ async def test_tool_node_tool_call_input():
        "id": "some 0",
        "type": "tool_call",
    }
-    result = ToolNode([tool1]).invoke([tool_call_1])
+    result = ToolNode([tool1]).invoke(
+        [tool_call_1], config=_create_config_with_runtime()
+    )
    assert result["messages"] == [
        ToolMessage(content="1 - foo", tool_call_id="some 0", name="tool1"),
    ]
@@ -173,7 +234,9 @@ async def test_tool_node_tool_call_input():
        "id": "some 1",
        "type": "tool_call",
    }
-    result = ToolNode([tool1]).invoke([tool_call_1, tool_call_2])
+    result = ToolNode([tool1]).invoke(
+        [tool_call_1, tool_call_2], config=_create_config_with_runtime()
+    )
    assert result["messages"] == [
        ToolMessage(content="1 - foo", tool_call_id="some 0", name="tool1"),
        ToolMessage(content="2 - bar", tool_call_id="some 1", name="tool1"),
@@ -182,7 +245,9 @@ async def test_tool_node_tool_call_input():
    # Test with unknown tool
    tool_call_3 = tool_call_1.copy()
    tool_call_3["name"] = "tool2"
-    result = ToolNode([tool1]).invoke([tool_call_1, tool_call_3])
+    result = ToolNode([tool1]).invoke(
+        [tool_call_1, tool_call_3], config=_create_config_with_runtime()
+    )
    assert result["messages"] == [
        ToolMessage(content="1 - foo", tool_call_id="some 0", name="tool1"),
        ToolMessage(
@@ -194,8 +259,58 @@ async def test_tool_node_tool_call_input():
    ]


-async def test_tool_node_error_handling():
-    def handle_all(e: ValueError | ToolException | ValidationError):
+def test_tool_node_error_handling_default_invocation() -> None:
+    tn = ToolNode([tool1])
+    result = tn.invoke(
+        {
+            "messages": [
+                AIMessage(
+                    "hi?",
+                    tool_calls=[
+                        {
+                            "name": "tool1",
+                            "args": {"invalid": 0, "args": "foo"},
+                            "id": "some id",
+                        },
+                    ],
+                )
+            ]
+        },
+        config=_create_config_with_runtime(),
+    )
+
+    assert all(m.type == "tool" for m in result["messages"])
+    assert all(m.status == "error" for m in result["messages"])
+    assert (
+        "Error invoking tool 'tool1' with kwargs {'invalid': 0, 'args': 'foo'} with error:\n"
+        in result["messages"][0].content
+    )
+
+
+def test_tool_node_error_handling_default_exception() -> None:
+    tn = ToolNode([tool1])
+    with pytest.raises(ValueError):
+        tn.invoke(
+            {
+                "messages": [
+                    AIMessage(
+                        "hi?",
+                        tool_calls=[
+                            {
+                                "name": "tool1",
+                                "args": {"some_val": 0, "some_other_val": "foo"},
+                                "id": "some id",
+                            },
+                        ],
+                    )
+                ]
+            },
+            config=_create_config_with_runtime(),
+        )
+
+
+async def test_tool_node_error_handling() -> None:
+    def handle_all(e: ValueError | ToolException | ToolInvocationError):
        return TOOL_CALL_ERROR_TEMPLATE.format(error=repr(e))

    # test catching all exceptions, via:
@@ -204,7 +319,7 @@ async def test_tool_node_error_handling():
    # - passing a callable with all exceptions in the signature
    for handle_tool_errors in (
        True,
-        (ValueError, ToolException, ValidationError),
+        (ValueError, ToolException, ToolInvocationError),
        handle_all,
    ):
        result_error = await ToolNode(
@@ -233,34 +348,33 @@ async def test_tool_node_error_handling():
                        ],
                    )
                ]
-            }
+            },
+            config=_create_config_with_runtime(),
        )

        assert all(m.type == "tool" for m in result_error["messages"])
        assert all(m.status == "error" for m in result_error["messages"])
        assert (
            result_error["messages"][0].content
-            == f"Error: {repr(ValueError('Test error'))}\n Please fix your mistakes."
+            == f"Error: {ValueError('Test error')!r}\n Please fix your mistakes."
        )
        assert (
            result_error["messages"][1].content
-            == f"Error: {repr(ToolException('Test error'))}\n Please fix your mistakes."
-        )
-        assert (
-            "ValidationError" in result_error["messages"][2].content
-            or "validation error" in result_error["messages"][2].content
+            == f"Error: {ToolException('Test error')!r}\n Please fix your mistakes."
        )
+        # Check that the validation error contains the field name
+        assert "some_other_val" in result_error["messages"][2].content

        assert result_error["messages"][0].tool_call_id == "some id"
        assert result_error["messages"][1].tool_call_id == "some other id"
        assert result_error["messages"][2].tool_call_id == "another id"


-async def test_tool_node_error_handling_callable():
-    def handle_value_error(e: ValueError):
+async def test_tool_node_error_handling_callable() -> None:
+    def handle_value_error(e: ValueError) -> str:
        return "Value error"

-    def handle_tool_exception(e: ToolException):
+    def handle_tool_exception(e: ToolException) -> str:
        return "Tool exception"

    for handle_tool_errors in ("Value error", handle_value_error):
@@ -280,7 +394,8 @@ async def test_tool_node_error_handling_callable():
                        ],
                    )
                ]
-            }
+            },
+            config=_create_config_with_runtime(),
        )
        tool_message: ToolMessage = result_error["messages"][-1]
        assert tool_message.type == "tool"
@@ -313,7 +428,8 @@ async def test_tool_node_error_handling_callable():
                            ],
                        )
                    ]
-                }
+                },
+                config=_create_config_with_runtime(),
            )
        assert str(exc_info.value) == "Test error"

@@ -340,12 +456,13 @@ async def test_tool_node_error_handling_callable():
                            ],
                        )
                    ]
-                }
+                },
+                config=_create_config_with_runtime(),
            )
        assert str(exc_info.value) == "Test error"


-async def test_tool_node_handle_tool_errors_false():
+async def test_tool_node_handle_tool_errors_false() -> None:
    with pytest.raises(ValueError) as exc_info:
        ToolNode([tool1], handle_tool_errors=False).invoke(
            {
@@ -361,7 +478,8 @@ async def test_tool_node_handle_tool_errors_false():
                        ],
                    )
                ]
-            }
+            },
+            config=_create_config_with_runtime(),
        )

    assert str(exc_info.value) == "Test error"
@@ -381,13 +499,14 @@ async def test_tool_node_handle_tool_errors_false():
                        ],
                    )
                ]
-            }
+            },
+            config=_create_config_with_runtime(),
        )

    assert str(exc_info.value) == "Test error"

    # test validation errors get raised if handle_tool_errors is False
-    with pytest.raises((ValidationError, ValidationErrorV1)):
+    with pytest.raises(ToolInvocationError):
        ToolNode([tool1], handle_tool_errors=False).invoke(
            {
                "messages": [
@@ -402,11 +521,12 @@ async def test_tool_node_handle_tool_errors_false():
                        ],
                    )
                ]
-            }
+            },
+            config=_create_config_with_runtime(),
        )


-def test_tool_node_individual_tool_error_handling():
+def test_tool_node_individual_tool_error_handling() -> None:
    # test error handling on individual tools (and that it overrides overall error handling!)
    result_individual_tool_error_handler = ToolNode(
        [tool5], handle_tool_errors="bar"
@@ -424,7 +544,8 @@ def test_tool_node_individual_tool_error_handling():
                    ],
                )
            ]
-        }
+        },
+        config=_create_config_with_runtime(),
    )

    tool_message: ToolMessage = result_individual_tool_error_handler["messages"][-1]
@@ -434,7 +555,7 @@ def test_tool_node_individual_tool_error_handling():
    assert tool_message.tool_call_id == "some 0"


-def test_tool_node_incorrect_tool_name():
+def test_tool_node_incorrect_tool_name() -> None:
    result_incorrect_name = ToolNode([tool1, tool2]).invoke(
        {
            "messages": [
@@ -449,7 +570,8 @@ def test_tool_node_incorrect_tool_name():
                    ],
                )
            ]
-        }
+        },
+        config=_create_config_with_runtime(),
    )

    tool_message: ToolMessage = result_incorrect_name["messages"][-1]
@@ -462,12 +584,13 @@ def test_tool_node_incorrect_tool_name():
    assert tool_message.tool_call_id == "some 0"


-def test_tool_node_node_interrupt():
+def test_tool_node_node_interrupt() -> None:
    def tool_interrupt(some_val: int) -> None:
        """Tool docstring."""
-        raise GraphBubbleUp("foo")
+        msg = "foo"
+        raise GraphBubbleUp(msg)

-    def handle(e: GraphInterrupt):
+    def handle(e: GraphInterrupt) -> str:
        return "handled"

    for handle_tool_errors in (True, (GraphBubbleUp,), "handled", handle, False):
@@ -487,13 +610,14 @@ def test_tool_node_node_interrupt():
                            ],
                        )
                    ]
-                }
+                },
+                config=_create_config_with_runtime(),
            )
            assert exc_info.value == "foo"


@pytest.mark.parametrize("input_type", ["dict", "tool_calls"])
-async def test_tool_node_command(input_type: str):
+async def test_tool_node_command(input_type: str) -> None:
    from langchain_core.tools.base import InjectedToolCallId

    @dec_tool
@@ -578,7 +702,9 @@ async def test_tool_node_command(input_type: str):
        input_ = {"messages": [AIMessage("", tool_calls=tool_calls)]}
    elif input_type == "tool_calls":
        input_ = tool_calls
-    result = ToolNode([add, transfer_to_bob]).invoke(input_)
+    result = ToolNode([add, transfer_to_bob]).invoke(
+        input_, config=_create_config_with_runtime()
+    )

    assert result == [
        {
@@ -616,7 +742,8 @@ async def test_tool_node_command(input_type: str):
                        "", tool_calls=[{"args": {}, "id": "1", "name": tool.name}]
                    )
                ]
-            }
+            },
+            config=_create_config_with_runtime(),
        )
        assert result == [
            Command(
@@ -643,7 +770,8 @@ async def test_tool_node_command(input_type: str):
                        "", tool_calls=[{"args": {}, "id": "1", "name": tool.name}]
                    )
                ]
-            }
+            },
+            config=_create_config_with_runtime(),
        )
        assert result == [
            Command(
@@ -673,7 +801,8 @@ async def test_tool_node_command(input_type: str):
                    ],
                )
            ]
-        }
+        },
+        config=_create_config_with_runtime(),
    )
    assert result == [
        Command(
@@ -724,7 +853,8 @@ async def test_tool_node_command(input_type: str):
                        ],
                    )
                ]
-            }
+            },
+            config=_create_config_with_runtime(),
        )

    # test validation (missing tool message in the update for current graph)
@@ -743,7 +873,8 @@ async def test_tool_node_command(input_type: str):
                        tool_calls=[{"args": {}, "id": "1", "name": "no_update_tool"}],
                    )
                ]
-            }
+            },
+            config=_create_config_with_runtime(),
        )

    # test validation (tool message with a wrong tool call ID)
@@ -770,7 +901,8 @@ async def test_tool_node_command(input_type: str):
                        ],
                    )
                ]
-            }
+            },
+            config=_create_config_with_runtime(),
        )

    # test validation (missing tool message in the update for parent graph is OK)
@@ -789,11 +921,12 @@ async def test_tool_node_command(input_type: str):
                    ],
                )
            ]
-        }
+        },
+        config=_create_config_with_runtime(),
    ) == [Command(update={"messages": []}, graph=Command.PARENT)]


-async def test_tool_node_command_list_input():
+async def test_tool_node_command_list_input() -> None:
    from langchain_core.tools.base import InjectedToolCallId

    @dec_tool
@@ -871,7 +1004,8 @@ async def test_tool_node_command_list_input():
                    {"args": {}, "id": "2", "name": "transfer_to_bob"},
                ],
            )
-        ]
+        ],
+        config=_create_config_with_runtime(),
    )

    assert result == [
@@ -900,7 +1034,8 @@ async def test_tool_node_command_list_input():
    # test sync tools
    for tool in [transfer_to_bob, custom_tool]:
        result = ToolNode([tool]).invoke(
-            [AIMessage("", tool_calls=[{"args": {}, "id": "1", "name": tool.name}])]
+            [AIMessage("", tool_calls=[{"args": {}, "id": "1", "name": tool.name}])],
+            config=_create_config_with_runtime(),
        )
        assert result == [
            Command(
@@ -919,7 +1054,8 @@ async def test_tool_node_command_list_input():
    # test async tools
    for tool in [async_transfer_to_bob, async_custom_tool]:
        result = await ToolNode([tool]).ainvoke(
-            [AIMessage("", tool_calls=[{"args": {}, "id": "1", "name": tool.name}])]
+            [AIMessage("", tool_calls=[{"args": {}, "id": "1", "name": tool.name}])],
+            config=_create_config_with_runtime(),
        )
        assert result == [
            Command(
@@ -945,7 +1081,8 @@ async def test_tool_node_command_list_input():
                    {"args": {}, "id": "2", "name": "custom_transfer_to_bob"},
                ],
            )
-        ]
+        ],
+        config=_create_config_with_runtime(),
    )
    assert result == [
        Command(
@@ -990,7 +1127,8 @@ async def test_tool_node_command_list_input():
                    "",
                    tool_calls=[{"args": {}, "id": "1", "name": "list_update_tool"}],
                )
-            ]
+            ],
+            config=_create_config_with_runtime(),
        )

    # test validation (missing tool message in the update for current graph)
@@ -1007,7 +1145,8 @@ async def test_tool_node_command_list_input():
                    "",
                    tool_calls=[{"args": {}, "id": "1", "name": "no_update_tool"}],
                )
-            ]
+            ],
+            config=_create_config_with_runtime(),
        )

    # test validation (tool message with a wrong tool call ID)
@@ -1026,7 +1165,8 @@ async def test_tool_node_command_list_input():
                        {"args": {}, "id": "1", "name": "mismatching_tool_call_id_tool"}
                    ],
                )
-            ]
+            ],
+            config=_create_config_with_runtime(),
        )

    # test validation (missing tool message in the update for parent graph is OK)
@@ -1041,11 +1181,12 @@ async def test_tool_node_command_list_input():
                "",
                tool_calls=[{"args": {}, "id": "1", "name": "node_update_parent_tool"}],
            )
-        ]
+        ],
+        config=_create_config_with_runtime(),
    ) == [Command(update=[], graph=Command.PARENT)]


-def test_tool_node_parent_command_with_send():
+def test_tool_node_parent_command_with_send() -> None:
    from langchain_core.tools.base import InjectedToolCallId

    @dec_tool
@@ -1096,7 +1237,8 @@ def test_tool_node_parent_command_with_send():
    ]

    result = ToolNode([transfer_to_alice, transfer_to_bob]).invoke(
-        [AIMessage("", tool_calls=tool_calls)]
+        [AIMessage("", tool_calls=tool_calls)],
+        config=_create_config_with_runtime(),
    )

    assert result == [
@@ -1132,7 +1274,7 @@ def test_tool_node_parent_command_with_send():
    ]


-async def test_tool_node_command_remove_all_messages():
+async def test_tool_node_command_remove_all_messages() -> None:
    from langchain_core.tools.base import InjectedToolCallId

    @dec_tool
@@ -1147,7 +1289,8 @@ async def test_tool_node_command_remove_all_messages():
        "id": "tool_call_123",
    }
    result = await tool_node.ainvoke(
-        {"messages": [AIMessage(content="", tool_calls=[tool_call])]}
+        {"messages": [AIMessage(content="", tool_calls=[tool_call])]},
+        config=_create_config_with_runtime(),
    )

    assert isinstance(result, list)
@@ -1155,3 +1298,315 @@ async def test_tool_node_command_remove_all_messages():
    command = result[0]
    assert isinstance(command, Command)
    assert command.update == {"messages": [RemoveMessage(id=REMOVE_ALL_MESSAGES)]}
+
+
+class _InjectStateSchema(TypedDict):
+    messages: list
+    foo: str
+
+
+class _InjectedStatePydanticV2Schema(BaseModel):
+    messages: list
+    foo: str
+
+
+@dataclasses.dataclass
+class _InjectedStateDataclassSchema:
+    messages: list
+    foo: str
+
+
+_INJECTED_STATE_SCHEMAS = [
+    _InjectStateSchema,
+    _InjectedStatePydanticV2Schema,
+    _InjectedStateDataclassSchema,
+]
+
+if sys.version_info < (3, 14):
+
+    class _InjectedStatePydanticSchema(BaseModelV1):
+        messages: list
+        foo: str
+
+    _INJECTED_STATE_SCHEMAS.append(_InjectedStatePydanticSchema)
+
+T = TypeVar("T")
+
+
+@pytest.mark.parametrize("schema_", _INJECTED_STATE_SCHEMAS)
+def test_tool_node_inject_state(schema_: type[T]) -> None:
+    def tool1(some_val: int, state: Annotated[T, InjectedState]) -> str:
+        """Tool 1 docstring."""
+        if isinstance(state, dict):
+            return state["foo"]
+        return state.foo
+
+    def tool2(some_val: int, state: Annotated[T, InjectedState()]) -> str:
+        """Tool 2 docstring."""
+        if isinstance(state, dict):
+            return state["foo"]
+        return state.foo
+
+    def tool3(
+        some_val: int,
+        foo: Annotated[str, InjectedState("foo")],
+        msgs: Annotated[list[AnyMessage], InjectedState("messages")],
+    ) -> str:
+        """Tool 1 docstring."""
+        return foo
+
+    def tool4(
+        some_val: int, msgs: Annotated[list[AnyMessage], InjectedState("messages")]
+    ) -> str:
+        """Tool 1 docstring."""
+        return msgs[0].content
+
+    node = ToolNode([tool1, tool2, tool3, tool4], handle_tool_errors=True)
+    for tool_name in ("tool1", "tool2", "tool3"):
+        tool_call = {
+            "name": tool_name,
+            "args": {"some_val": 1},
+            "id": "some 0",
+            "type": "tool_call",
+        }
+        msg = AIMessage("hi?", tool_calls=[tool_call])
+        result = node.invoke(
+            schema_(messages=[msg], foo="bar"), config=_create_config_with_runtime()
+        )
+        tool_message = result["messages"][-1]
+        assert tool_message.content == "bar", f"Failed for tool={tool_name}"
+
+        if tool_name == "tool3":
+            failure_input = None
+            with contextlib.suppress(Exception):
+                failure_input = schema_(messages=[msg], notfoo="bar")
+            if failure_input is not None:
+                with pytest.raises(KeyError):
+                    node.invoke(failure_input, config=_create_config_with_runtime())
+
+                with pytest.raises(ValueError):
+                    node.invoke([msg], config=_create_config_with_runtime())
+        else:
+            failure_input = None
+            try:
+                failure_input = schema_(messages=[msg], notfoo="bar")
+            except Exception:
+                # We'd get a validation error from pydantic state and wouldn't make it to the node
+                # anyway
+                pass
+            if failure_input is not None:
+                messages_ = node.invoke(
+                    failure_input, config=_create_config_with_runtime()
+                )
+                tool_message = messages_["messages"][-1]
+                assert "KeyError" in tool_message.content
+                tool_message = node.invoke([msg], config=_create_config_with_runtime())[
+                    -1
+                ]
+                assert "KeyError" in tool_message.content
+
+    tool_call = {
+        "name": "tool4",
+        "args": {"some_val": 1},
+        "id": "some 0",
+        "type": "tool_call",
+    }
+    msg = AIMessage("hi?", tool_calls=[tool_call])
+    result = node.invoke(
+        schema_(messages=[msg], foo=""), config=_create_config_with_runtime()
+    )
+    tool_message = result["messages"][-1]
+    assert tool_message.content == "hi?"
+
+    result = node.invoke([msg], config=_create_config_with_runtime())
+    tool_message = result[-1]
+    assert tool_message.content == "hi?"
+
+
+def test_tool_node_inject_store() -> None:
+    store = InMemoryStore()
+    namespace = ("test",)
+
+    def tool1(some_val: int, store: Annotated[BaseStore, InjectedStore()]) -> str:
+        """Tool 1 docstring."""
+        store_val = store.get(namespace, "test_key").value["foo"]
+        return f"Some val: {some_val}, store val: {store_val}"
+
+    def tool2(some_val: int, store: Annotated[BaseStore, InjectedStore()]) -> str:
+        """Tool 2 docstring."""
+        store_val = store.get(namespace, "test_key").value["foo"]
+        return f"Some val: {some_val}, store val: {store_val}"
+
+    def tool3(
+        some_val: int,
+        bar: Annotated[str, InjectedState("bar")],
+        store: Annotated[BaseStore, InjectedStore()],
+    ) -> str:
+        """Tool 3 docstring."""
+        store_val = store.get(namespace, "test_key").value["foo"]
+        return f"Some val: {some_val}, store val: {store_val}, state val: {bar}"
+
+    node = ToolNode([tool1, tool2, tool3], handle_tool_errors=True)
+    store.put(namespace, "test_key", {"foo": "bar"})
+
+    class State(MessagesState):
+        bar: str
+
+    builder = StateGraph(State)
+    builder.add_node("tools", node)
+    builder.add_edge(START, "tools")
+    graph = builder.compile(store=store)
+
+    for tool_name in ("tool1", "tool2"):
+        tool_call = {
+            "name": tool_name,
+            "args": {"some_val": 1},
+            "id": "some 0",
+            "type": "tool_call",
+        }
+        msg = AIMessage("hi?", tool_calls=[tool_call])
+        node_result = node.invoke(
+            {"messages": [msg]}, config=_create_config_with_runtime(store=store)
+        )
+        graph_result = graph.invoke({"messages": [msg]})
+        for result in (node_result, graph_result):
+            result["messages"][-1]
+            tool_message = result["messages"][-1]
+            assert tool_message.content == "Some val: 1, store val: bar", (
+                f"Failed for tool={tool_name}"
+            )
+
+    tool_call = {
+        "name": "tool3",
+        "args": {"some_val": 1},
+        "id": "some 0",
+        "type": "tool_call",
+    }
+    msg = AIMessage("hi?", tool_calls=[tool_call])
+    node_result = node.invoke(
+        {"messages": [msg], "bar": "baz"},
+        config=_create_config_with_runtime(store=store),
+    )
+    graph_result = graph.invoke({"messages": [msg], "bar": "baz"})
+    for result in (node_result, graph_result):
+        result["messages"][-1]
+        tool_message = result["messages"][-1]
+        assert tool_message.content == "Some val: 1, store val: bar, state val: baz", (
+            f"Failed for tool={tool_name}"
+        )
+
+    # test injected store without passing store to compiled graph
+    failing_graph = builder.compile()
+    with pytest.raises(ValueError):
+        failing_graph.invoke({"messages": [msg], "bar": "baz"})
+
+
+def test_tool_node_ensure_utf8() -> None:
+    @dec_tool
+    def get_day_list(days: list[str]) -> list[str]:
+        """choose days"""
+        return days
+
+    data = ["星期一", "水曜日", "목요일", "Friday"]
+    tools = [get_day_list]
+    tool_calls = [ToolCall(name=get_day_list.name, args={"days": data}, id="test_id")]
+    outputs: list[ToolMessage] = ToolNode(tools).invoke(
+        [AIMessage(content="", tool_calls=tool_calls)],
+        config=_create_config_with_runtime(),
+    )
+    assert outputs[0].content == json.dumps(data, ensure_ascii=False)
+
+
+def test_tool_node_messages_key() -> None:
+    @dec_tool
+    def add(a: int, b: int) -> int:
+        """Adds a and b."""
+        return a + b
+
+    model = FakeToolCallingModel(
+        tool_calls=[[ToolCall(name=add.name, args={"a": 1, "b": 2}, id="test_id")]]
+    )
+
+    class State(TypedDict):
+        subgraph_messages: Annotated[list[AnyMessage], add_messages]
+
+    def call_model(state: State) -> dict[str, Any]:
+        response = model.invoke(state["subgraph_messages"])
+        model.tool_calls = []
+        return {"subgraph_messages": response}
+
+    builder = StateGraph(State)
+    builder.add_node("agent", call_model)
+    builder.add_node("tools", ToolNode([add], messages_key="subgraph_messages"))
+    builder.add_conditional_edges(
+        "agent", partial(tools_condition, messages_key="subgraph_messages")
+    )
+    builder.add_edge(START, "agent")
+    builder.add_edge("tools", "agent")
+
+    graph = builder.compile()
+    result = graph.invoke({"subgraph_messages": [HumanMessage(content="hi")]})
+    assert result["subgraph_messages"] == [
+        _AnyIdHumanMessage(content="hi"),
+        AIMessage(
+            content="hi",
+            id="0",
+            tool_calls=[ToolCall(name=add.name, args={"a": 1, "b": 2}, id="test_id")],
+        ),
+        _AnyIdToolMessage(content="3", name=add.name, tool_call_id="test_id"),
+        AIMessage(content="hi-hi-3", id="1"),
+    ]
+
+
+def test_tool_node_stream_writer() -> None:
+    @dec_tool
+    def streaming_tool(x: int) -> str:
+        """Do something with writer."""
+        my_writer = get_stream_writer()
+        for value in ["foo", "bar", "baz"]:
+            my_writer({"custom_tool_value": value})
+
+        return x
+
+    tool_node = ToolNode([streaming_tool])
+    graph = (
+        StateGraph(MessagesState)
+        .add_node("tools", tool_node)
+        .add_edge(START, "tools")
+        .compile()
+    )
+
+    tool_call = {
+        "name": "streaming_tool",
+        "args": {"x": 1},
+        "id": "1",
+        "type": "tool_call",
+    }
+    inputs = {
+        "messages": [AIMessage("", tool_calls=[tool_call])],
+    }
+
+    assert list(graph.stream(inputs, stream_mode="custom")) == [
+        {"custom_tool_value": "foo"},
+        {"custom_tool_value": "bar"},
+        {"custom_tool_value": "baz"},
+    ]
+    assert list(graph.stream(inputs, stream_mode=["custom", "updates"])) == [
+        ("custom", {"custom_tool_value": "foo"}),
+        ("custom", {"custom_tool_value": "bar"}),
+        ("custom", {"custom_tool_value": "baz"}),
+        (
+            "updates",
+            {
+                "tools": {
+                    "messages": [
+                        _AnyIdToolMessage(
+                            content="1",
+                            name="streaming_tool",
+                            tool_call_id="1",
+                        ),
+                    ],
+                },
+            },
+        ),
+    ]
@@ -0,0 +1,578 @@
+"""Test tool node interceptor handling of unregistered tools."""
+
+from collections.abc import Awaitable, Callable
+from unittest.mock import Mock
+
+import pytest
+from langchain_core.messages import AIMessage, ToolMessage
+from langchain_core.runnables.config import RunnableConfig
+from langchain_core.tools import tool as dec_tool
+from langgraph.store.base import BaseStore
+from langgraph.types import Command
+
+from langgraph.prebuilt import ToolNode
+from langgraph.prebuilt.tool_node import ToolCallRequest
+
+pytestmark = pytest.mark.anyio
+
+
+def _create_mock_runtime(store: BaseStore | None = None) -> Mock:
+    """Create a mock Runtime object for testing ToolNode outside of graph context.
+
+    This helper is needed because ToolNode._func expects a Runtime parameter
+    which is injected by RunnableCallable from config["configurable"]["__pregel_runtime"].
+    When testing ToolNode directly (outside a graph), we need to provide this manually.
+    """
+    mock_runtime = Mock()
+    mock_runtime.store = store
+    mock_runtime.context = None
+    mock_runtime.stream_writer = lambda *args, **kwargs: None
+    return mock_runtime
+
+
+def _create_config_with_runtime(store: BaseStore | None = None) -> RunnableConfig:
+    """Create a RunnableConfig with mock Runtime for testing ToolNode.
+
+    Returns:
+        RunnableConfig with __pregel_runtime in configurable dict.
+    """
+    return {"configurable": {"__pregel_runtime": _create_mock_runtime(store)}}
+
+
+@dec_tool
+def registered_tool(x: int) -> str:
+    """A registered tool."""
+    return f"Result: {x}"
+
+
+def test_interceptor_can_handle_unregistered_tool_sync() -> None:
+    """Test that interceptor can handle requests for unregistered tools (sync)."""
+
+    def interceptor(
+        request: ToolCallRequest,
+        execute: Callable[[ToolCallRequest], ToolMessage | Command],
+    ) -> ToolMessage | Command:
+        """Intercept and handle unregistered tools."""
+        if request.tool_call["name"] == "unregistered_tool":
+            # Short-circuit without calling execute for unregistered tool
+            return ToolMessage(
+                content="Handled by interceptor",
+                tool_call_id=request.tool_call["id"],
+                name="unregistered_tool",
+            )
+        # Pass through for registered tools
+        return execute(request)
+
+    node = ToolNode([registered_tool], wrap_tool_call=interceptor)
+
+    # Test registered tool works normally
+    result = node.invoke(
+        [
+            AIMessage(
+                "",
+                tool_calls=[
+                    {
+                        "name": "registered_tool",
+                        "args": {"x": 42},
+                        "id": "1",
+                        "type": "tool_call",
+                    }
+                ],
+            )
+        ],
+        config=_create_config_with_runtime(),
+    )
+    assert result[0].content == "Result: 42"
+    assert result[0].tool_call_id == "1"
+
+    # Test unregistered tool is intercepted and handled
+    result = node.invoke(
+        [
+            AIMessage(
+                "",
+                tool_calls=[
+                    {
+                        "name": "unregistered_tool",
+                        "args": {"x": 99},
+                        "id": "2",
+                        "type": "tool_call",
+                    }
+                ],
+            )
+        ],
+        config=_create_config_with_runtime(),
+    )
+    assert result[0].content == "Handled by interceptor"
+    assert result[0].tool_call_id == "2"
+    assert result[0].name == "unregistered_tool"
+
+
+async def test_interceptor_can_handle_unregistered_tool_async() -> None:
+    """Test that interceptor can handle requests for unregistered tools (async)."""
+
+    async def async_interceptor(
+        request: ToolCallRequest,
+        execute: Callable[[ToolCallRequest], Awaitable[ToolMessage | Command]],
+    ) -> ToolMessage | Command:
+        """Intercept and handle unregistered tools."""
+        if request.tool_call["name"] == "unregistered_tool":
+            # Short-circuit without calling execute for unregistered tool
+            return ToolMessage(
+                content="Handled by async interceptor",
+                tool_call_id=request.tool_call["id"],
+                name="unregistered_tool",
+            )
+        # Pass through for registered tools
+        return await execute(request)
+
+    node = ToolNode([registered_tool], awrap_tool_call=async_interceptor)
+
+    # Test registered tool works normally
+    result = await node.ainvoke(
+        [
+            AIMessage(
+                "",
+                tool_calls=[
+                    {
+                        "name": "registered_tool",
+                        "args": {"x": 42},
+                        "id": "1",
+                        "type": "tool_call",
+                    }
+                ],
+            )
+        ],
+        config=_create_config_with_runtime(),
+    )
+    assert result[0].content == "Result: 42"
+    assert result[0].tool_call_id == "1"
+
+    # Test unregistered tool is intercepted and handled
+    result = await node.ainvoke(
+        [
+            AIMessage(
+                "",
+                tool_calls=[
+                    {
+                        "name": "unregistered_tool",
+                        "args": {"x": 99},
+                        "id": "2",
+                        "type": "tool_call",
+                    }
+                ],
+            )
+        ],
+        config=_create_config_with_runtime(),
+    )
+    assert result[0].content == "Handled by async interceptor"
+    assert result[0].tool_call_id == "2"
+    assert result[0].name == "unregistered_tool"
+
+
+def test_unregistered_tool_error_when_interceptor_calls_execute() -> None:
+    """Test that unregistered tools error if interceptor tries to execute them."""
+
+    def bad_interceptor(
+        request: ToolCallRequest,
+        execute: Callable[[ToolCallRequest], ToolMessage | Command],
+    ) -> ToolMessage | Command:
+        """Interceptor that tries to execute unregistered tool."""
+        # This should fail validation when execute is called
+        return execute(request)
+
+    node = ToolNode([registered_tool], wrap_tool_call=bad_interceptor)
+
+    # Registered tool should still work
+    result = node.invoke(
+        [
+            AIMessage(
+                "",
+                tool_calls=[
+                    {
+                        "name": "registered_tool",
+                        "args": {"x": 42},
+                        "id": "1",
+                        "type": "tool_call",
+                    }
+                ],
+            )
+        ],
+        config=_create_config_with_runtime(),
+    )
+    assert result[0].content == "Result: 42"
+
+    # Unregistered tool should error when interceptor calls execute
+    result = node.invoke(
+        [
+            AIMessage(
+                "",
+                tool_calls=[
+                    {
+                        "name": "unregistered_tool",
+                        "args": {"x": 99},
+                        "id": "2",
+                        "type": "tool_call",
+                    }
+                ],
+            )
+        ],
+        config=_create_config_with_runtime(),
+    )
+    # Should get validation error message
+    assert result[0].status == "error"
+    assert "is not a valid tool" in result[0].content
+    assert result[0].tool_call_id == "2"
+
+
+def test_interceptor_handles_mix_of_registered_and_unregistered() -> None:
+    """Test interceptor handling mix of registered and unregistered tools."""
+
+    def selective_interceptor(
+        request: ToolCallRequest,
+        execute: Callable[[ToolCallRequest], ToolMessage | Command],
+    ) -> ToolMessage | Command:
+        """Handle unregistered tools, pass through registered ones."""
+        if request.tool_call["name"] == "magic_tool":
+            return ToolMessage(
+                content=f"Magic result: {request.tool_call['args'].get('value', 0) * 2}",
+                tool_call_id=request.tool_call["id"],
+                name="magic_tool",
+            )
+        return execute(request)
+
+    node = ToolNode([registered_tool], wrap_tool_call=selective_interceptor)
+
+    # Test multiple tool calls - mix of registered and unregistered
+    result = node.invoke(
+        [
+            AIMessage(
+                "",
+                tool_calls=[
+                    {
+                        "name": "registered_tool",
+                        "args": {"x": 10},
+                        "id": "1",
+                        "type": "tool_call",
+                    },
+                    {
+                        "name": "magic_tool",
+                        "args": {"value": 5},
+                        "id": "2",
+                        "type": "tool_call",
+                    },
+                    {
+                        "name": "registered_tool",
+                        "args": {"x": 20},
+                        "id": "3",
+                        "type": "tool_call",
+                    },
+                ],
+            )
+        ],
+        config=_create_config_with_runtime(),
+    )
+
+    # All tools should execute successfully
+    assert len(result) == 3
+    assert result[0].content == "Result: 10"
+    assert result[0].tool_call_id == "1"
+    assert result[1].content == "Magic result: 10"
+    assert result[1].tool_call_id == "2"
+    assert result[2].content == "Result: 20"
+    assert result[2].tool_call_id == "3"
+
+
+def test_interceptor_command_for_unregistered_tool() -> None:
+    """Test interceptor returning Command for unregistered tool."""
+
+    def command_interceptor(
+        request: ToolCallRequest,
+        execute: Callable[[ToolCallRequest], ToolMessage | Command],
+    ) -> ToolMessage | Command:
+        """Return Command for unregistered tools."""
+        if request.tool_call["name"] == "routing_tool":
+            return Command(
+                update=[
+                    ToolMessage(
+                        content="Routing to special handler",
+                        tool_call_id=request.tool_call["id"],
+                        name="routing_tool",
+                    )
+                ],
+                goto="special_node",
+            )
+        return execute(request)
+
+    node = ToolNode([registered_tool], wrap_tool_call=command_interceptor)
+
+    result = node.invoke(
+        [
+            AIMessage(
+                "",
+                tool_calls=[
+                    {
+                        "name": "routing_tool",
+                        "args": {},
+                        "id": "1",
+                        "type": "tool_call",
+                    }
+                ],
+            )
+        ],
+        config=_create_config_with_runtime(),
+    )
+
+    # Should get Command back
+    assert len(result) == 1
+    assert isinstance(result[0], Command)
+    assert result[0].goto == "special_node"
+    assert result[0].update is not None
+    assert len(result[0].update) == 1
+    assert result[0].update[0].content == "Routing to special handler"
+
+
+def test_interceptor_exception_with_unregistered_tool() -> None:
+    """Test that interceptor exceptions are caught by error handling."""
+
+    def failing_interceptor(
+        request: ToolCallRequest,
+        execute: Callable[[ToolCallRequest], ToolMessage | Command],
+    ) -> ToolMessage | Command:
+        """Interceptor that throws exception for unregistered tools."""
+        if request.tool_call["name"] == "bad_tool":
+            msg = "Interceptor failed"
+            raise ValueError(msg)
+        return execute(request)
+
+    node = ToolNode(
+        [registered_tool], wrap_tool_call=failing_interceptor, handle_tool_errors=True
+    )
+
+    # Interceptor exception should be caught and converted to error message
+    result = node.invoke(
+        [
+            AIMessage(
+                "",
+                tool_calls=[
+                    {
+                        "name": "bad_tool",
+                        "args": {},
+                        "id": "1",
+                        "type": "tool_call",
+                    }
+                ],
+            )
+        ],
+        config=_create_config_with_runtime(),
+    )
+
+    assert len(result) == 1
+    assert result[0].status == "error"
+    assert "Interceptor failed" in result[0].content
+    assert result[0].tool_call_id == "1"
+
+    # Test that exception is raised when handle_tool_errors is False
+    node_no_handling = ToolNode(
+        [registered_tool], wrap_tool_call=failing_interceptor, handle_tool_errors=False
+    )
+
+    with pytest.raises(ValueError, match="Interceptor failed"):
+        node_no_handling.invoke(
+            [
+                AIMessage(
+                    "",
+                    tool_calls=[
+                        {
+                            "name": "bad_tool",
+                            "args": {},
+                            "id": "2",
+                            "type": "tool_call",
+                        }
+                    ],
+                )
+            ],
+            config=_create_config_with_runtime(),
+        )
+
+
+async def test_async_interceptor_exception_with_unregistered_tool() -> None:
+    """Test that async interceptor exceptions are caught by error handling."""
+
+    async def failing_async_interceptor(
+        request: ToolCallRequest,
+        execute: Callable[[ToolCallRequest], Awaitable[ToolMessage | Command]],
+    ) -> ToolMessage | Command:
+        """Async interceptor that throws exception for unregistered tools."""
+        if request.tool_call["name"] == "bad_async_tool":
+            msg = "Async interceptor failed"
+            raise RuntimeError(msg)
+        return await execute(request)
+
+    node = ToolNode(
+        [registered_tool],
+        awrap_tool_call=failing_async_interceptor,
+        handle_tool_errors=True,
+    )
+
+    # Interceptor exception should be caught and converted to error message
+    result = await node.ainvoke(
+        [
+            AIMessage(
+                "",
+                tool_calls=[
+                    {
+                        "name": "bad_async_tool",
+                        "args": {},
+                        "id": "1",
+                        "type": "tool_call",
+                    }
+                ],
+            )
+        ],
+        config=_create_config_with_runtime(),
+    )
+
+    assert len(result) == 1
+    assert result[0].status == "error"
+    assert "Async interceptor failed" in result[0].content
+    assert result[0].tool_call_id == "1"
+
+    # Test that exception is raised when handle_tool_errors is False
+    node_no_handling = ToolNode(
+        [registered_tool],
+        awrap_tool_call=failing_async_interceptor,
+        handle_tool_errors=False,
+    )
+
+    with pytest.raises(RuntimeError, match="Async interceptor failed"):
+        await node_no_handling.ainvoke(
+            [
+                AIMessage(
+                    "",
+                    tool_calls=[
+                        {
+                            "name": "bad_async_tool",
+                            "args": {},
+                            "id": "2",
+                            "type": "tool_call",
+                        }
+                    ],
+                )
+            ],
+            config=_create_config_with_runtime(),
+        )
+
+
+def test_interceptor_with_dict_input_format() -> None:
+    """Test that interceptor works with dict input format."""
+
+    def interceptor(
+        request: ToolCallRequest,
+        execute: Callable[[ToolCallRequest], ToolMessage | Command],
+    ) -> ToolMessage | Command:
+        """Intercept unregistered tools with dict input."""
+        if request.tool_call["name"] == "dict_tool":
+            return ToolMessage(
+                content="Handled dict input",
+                tool_call_id=request.tool_call["id"],
+                name="dict_tool",
+            )
+        return execute(request)
+
+    node = ToolNode([registered_tool], wrap_tool_call=interceptor)
+
+    # Test with dict input format
+    result = node.invoke(
+        {
+            "messages": [
+                AIMessage(
+                    "",
+                    tool_calls=[
+                        {
+                            "name": "dict_tool",
+                            "args": {"value": 5},
+                            "id": "1",
+                            "type": "tool_call",
+                        }
+                    ],
+                )
+            ]
+        },
+        config=_create_config_with_runtime(),
+    )
+
+    # Should return dict format output
+    assert isinstance(result, dict)
+    assert "messages" in result
+    assert len(result["messages"]) == 1
+    assert result["messages"][0].content == "Handled dict input"
+    assert result["messages"][0].tool_call_id == "1"
+
+
+def test_interceptor_verifies_tool_is_none_for_unregistered() -> None:
+    """Test that request.tool is None for unregistered tools."""
+
+    captured_requests: list[ToolCallRequest] = []
+
+    def capturing_interceptor(
+        request: ToolCallRequest,
+        execute: Callable[[ToolCallRequest], ToolMessage | Command],
+    ) -> ToolMessage | Command:
+        """Capture request to verify tool field."""
+        captured_requests.append(request)
+        if request.tool is None:
+            # Tool is unregistered
+            return ToolMessage(
+                content=f"Unregistered: {request.tool_call['name']}",
+                tool_call_id=request.tool_call["id"],
+                name=request.tool_call["name"],
+            )
+        # Tool is registered
+        return execute(request)
+
+    node = ToolNode([registered_tool], wrap_tool_call=capturing_interceptor)
+
+    # Test unregistered tool
+    node.invoke(
+        [
+            AIMessage(
+                "",
+                tool_calls=[
+                    {
+                        "name": "unknown_tool",
+                        "args": {},
+                        "id": "1",
+                        "type": "tool_call",
+                    }
+                ],
+            )
+        ],
+        config=_create_config_with_runtime(),
+    )
+
+    assert len(captured_requests) == 1
+    assert captured_requests[0].tool is None
+    assert captured_requests[0].tool_call["name"] == "unknown_tool"
+
+    # Clear and test registered tool
+    captured_requests.clear()
+    node.invoke(
+        [
+            AIMessage(
+                "",
+                tool_calls=[
+                    {
+                        "name": "registered_tool",
+                        "args": {"x": 10},
+                        "id": "2",
+                        "type": "tool_call",
+                    }
+                ],
+            )
+        ],
+        config=_create_config_with_runtime(),
+    )
+
+    assert len(captured_requests) == 1
+    assert captured_requests[0].tool is not None
+    assert captured_requests[0].tool.name == "registered_tool"
@@ -0,0 +1,470 @@
+"""Unit tests for ValidationError filtering in ToolNode.
+
+This module tests that validation errors are filtered to only include arguments
+that the LLM controls. Injected arguments (InjectedState, InjectedStore,
+ToolRuntime) are automatically provided by the system and should not appear in
+validation error messages. This ensures the LLM receives focused, actionable
+feedback about the parameters it can actually control, improving error correction
+and reducing confusion from irrelevant system implementation details.
+"""
+
+from typing import Annotated
+from unittest.mock import Mock
+
+import pytest
+from langchain_core.messages import AIMessage
+from langchain_core.runnables.config import RunnableConfig
+from langchain_core.tools import tool as dec_tool
+from langgraph.store.base import BaseStore
+from langgraph.store.memory import InMemoryStore
+
+from langgraph.prebuilt import InjectedState, InjectedStore, ToolNode, ToolRuntime
+from langgraph.prebuilt.tool_node import ToolInvocationError
+
+pytestmark = pytest.mark.anyio
+
+
+def _create_mock_runtime(store: BaseStore | None = None) -> Mock:
+    """Create a mock Runtime object for testing ToolNode outside of graph context."""
+    mock_runtime = Mock()
+    mock_runtime.store = store
+    mock_runtime.context = None
+    mock_runtime.stream_writer = lambda *args, **kwargs: None
+    return mock_runtime
+
+
+def _create_config_with_runtime(store: BaseStore | None = None) -> RunnableConfig:
+    """Create a RunnableConfig with mock Runtime for testing ToolNode."""
+    return {"configurable": {"__pregel_runtime": _create_mock_runtime(store)}}
+
+
+async def test_filter_injected_state_validation_errors() -> None:
+    """Test that validation errors for InjectedState arguments are filtered out.
+
+    InjectedState parameters are not controlled by the LLM, so any validation
+    errors related to them should not appear in error messages. This ensures
+    the LLM receives only actionable feedback about its own tool call arguments.
+    """
+
+    @dec_tool
+    def my_tool(
+        value: int,
+        state: Annotated[dict, InjectedState],
+    ) -> str:
+        """Tool that uses injected state.
+
+        Args:
+            value: An integer value.
+            state: The graph state (injected).
+        """
+        return f"value={value}, messages={len(state.get('messages', []))}"
+
+    tool_node = ToolNode([my_tool])
+
+    # Call with invalid 'value' argument (should be int, not str)
+    result = await tool_node.ainvoke(
+        {
+            "messages": [
+                AIMessage(
+                    "hi?",
+                    tool_calls=[
+                        {
+                            "name": "my_tool",
+                            "args": {"value": "not_an_int"},  # Invalid type
+                            "id": "call_1",
+                            "type": "tool_call",
+                        }
+                    ],
+                )
+            ]
+        },
+        config=_create_config_with_runtime(),
+    )
+
+    # Should get a ToolMessage with error
+    assert len(result["messages"]) == 1
+    tool_message = result["messages"][0]
+    assert tool_message.status == "error"
+    assert tool_message.tool_call_id == "call_1"
+
+    # Error should mention 'value' but NOT 'state' (which is injected)
+    assert "value" in tool_message.content
+    assert "state" not in tool_message.content.lower()
+
+
+async def test_filter_injected_store_validation_errors() -> None:
+    """Test that validation errors for InjectedStore arguments are filtered out.
+
+    InjectedStore parameters are not controlled by the LLM, so any validation
+    errors related to them should not appear in error messages. This keeps
+    error feedback focused on LLM-controllable parameters.
+    """
+
+    @dec_tool
+    def my_tool(
+        key: str,
+        store: Annotated[BaseStore, InjectedStore()],
+    ) -> str:
+        """Tool that uses injected store.
+
+        Args:
+            key: A key to look up.
+            store: The persistent store (injected).
+        """
+        return f"key={key}"
+
+    tool_node = ToolNode([my_tool])
+
+    # Call with invalid 'key' argument (missing required argument)
+    result = await tool_node.ainvoke(
+        {
+            "messages": [
+                AIMessage(
+                    "hi?",
+                    tool_calls=[
+                        {
+                            "name": "my_tool",
+                            "args": {},  # Missing 'key'
+                            "id": "call_1",
+                            "type": "tool_call",
+                        }
+                    ],
+                )
+            ]
+        },
+        config=_create_config_with_runtime(store=InMemoryStore()),
+    )
+
+    # Should get a ToolMessage with error
+    assert len(result["messages"]) == 1
+    tool_message = result["messages"][0]
+    assert tool_message.status == "error"
+
+    # Error should mention 'key' is required
+    assert "key" in tool_message.content.lower()
+    # The error should be about 'key' field specifically (not about store field)
+    # Note: 'store' might appear in input_value representation, but the validation
+    # error itself should only be for 'key'
+    assert (
+        "field required" in tool_message.content.lower()
+        or "missing" in tool_message.content.lower()
+    )
+
+
+async def test_filter_tool_runtime_validation_errors() -> None:
+    """Test that validation errors for ToolRuntime arguments are filtered out.
+
+    ToolRuntime parameters are not controlled by the LLM, so any validation
+    errors related to them should not appear in error messages. This ensures
+    the LLM only sees errors for parameters it can fix.
+    """
+
+    @dec_tool
+    def my_tool(
+        query: str,
+        runtime: ToolRuntime,
+    ) -> str:
+        """Tool that uses ToolRuntime.
+
+        Args:
+            query: A query string.
+            runtime: The tool runtime context (injected).
+        """
+        return f"query={query}"
+
+    tool_node = ToolNode([my_tool])
+
+    # Call with invalid 'query' argument (wrong type)
+    result = await tool_node.ainvoke(
+        {
+            "messages": [
+                AIMessage(
+                    "hi?",
+                    tool_calls=[
+                        {
+                            "name": "my_tool",
+                            "args": {"query": 123},  # Should be str, not int
+                            "id": "call_1",
+                            "type": "tool_call",
+                        }
+                    ],
+                )
+            ]
+        },
+        config=_create_config_with_runtime(),
+    )
+
+    # Should get a ToolMessage with error
+    assert len(result["messages"]) == 1
+    tool_message = result["messages"][0]
+    assert tool_message.status == "error"
+
+    # Error should mention 'query' but NOT 'runtime' (which is injected)
+    assert "query" in tool_message.content.lower()
+    assert "runtime" not in tool_message.content.lower()
+
+
+async def test_filter_multiple_injected_args() -> None:
+    """Test filtering when a tool has multiple injected arguments.
+
+    When a tool uses multiple injected parameters (state, store, runtime), none of
+    them should appear in validation error messages since they're all system-provided
+    and not controlled by the LLM. Only LLM-controllable parameter errors should appear.
+    """
+
+    @dec_tool
+    def my_tool(
+        value: int,
+        state: Annotated[dict, InjectedState],
+        store: Annotated[BaseStore, InjectedStore()],
+        runtime: ToolRuntime,
+    ) -> str:
+        """Tool with multiple injected arguments.
+
+        Args:
+            value: An integer value.
+            state: The graph state (injected).
+            store: The persistent store (injected).
+            runtime: The tool runtime context (injected).
+        """
+        return f"value={value}"
+
+    tool_node = ToolNode([my_tool])
+
+    # Call with invalid 'value' - injected args should be filtered from error
+    result = await tool_node.ainvoke(
+        {
+            "messages": [
+                AIMessage(
+                    "hi?",
+                    tool_calls=[
+                        {
+                            "name": "my_tool",
+                            "args": {"value": "not_an_int"},
+                            "id": "call_1",
+                            "type": "tool_call",
+                        }
+                    ],
+                )
+            ]
+        },
+        config=_create_config_with_runtime(store=InMemoryStore()),
+    )
+
+    tool_message = result["messages"][0]
+    assert tool_message.status == "error"
+
+    # Only 'value' error should be reported
+    assert "value" in tool_message.content
+    # None of the injected args should appear in error
+    assert "state" not in tool_message.content.lower()
+    assert "store" not in tool_message.content.lower()
+    assert "runtime" not in tool_message.content.lower()
+
+
+async def test_no_filtering_when_all_errors_are_model_args() -> None:
+    """Test that validation errors for LLM-controlled arguments are preserved.
+
+    When validation fails for arguments the LLM controls, those errors should
+    be fully reported to help the LLM correct its tool calls. This ensures
+    the LLM receives complete feedback about all issues it can fix.
+    """
+
+    @dec_tool
+    def my_tool(
+        value1: int,
+        value2: str,
+        state: Annotated[dict, InjectedState],
+    ) -> str:
+        """Tool with both regular and injected arguments.
+
+        Args:
+            value1: First value.
+            value2: Second value.
+            state: The graph state (injected).
+        """
+        return f"value1={value1}, value2={value2}"
+
+    tool_node = ToolNode([my_tool])
+
+    # Call with invalid arguments for BOTH non-injected parameters
+    result = await tool_node.ainvoke(
+        {
+            "messages": [
+                AIMessage(
+                    "hi?",
+                    tool_calls=[
+                        {
+                            "name": "my_tool",
+                            "args": {
+                                "value1": "not_an_int",  # Invalid
+                                "value2": 456,  # Invalid (should be str)
+                            },
+                            "id": "call_1",
+                            "type": "tool_call",
+                        }
+                    ],
+                )
+            ]
+        },
+        config=_create_config_with_runtime(),
+    )
+
+    tool_message = result["messages"][0]
+    assert tool_message.status == "error"
+
+    # Both errors should be present
+    assert "value1" in tool_message.content
+    assert "value2" in tool_message.content
+    # Injected state should not appear
+    assert "state" not in tool_message.content.lower()
+
+
+async def test_validation_error_with_no_injected_args() -> None:
+    """Test that tools without injected arguments show all validation errors.
+
+    For tools that only have LLM-controlled parameters, all validation errors
+    should be reported since everything is under the LLM's control and can be
+    corrected by the LLM in subsequent tool calls.
+    """
+
+    @dec_tool
+    def my_tool(value1: int, value2: str) -> str:
+        """Regular tool without injected arguments.
+
+        Args:
+            value1: First value.
+            value2: Second value.
+        """
+        return f"{value1} {value2}"
+
+    tool_node = ToolNode([my_tool])
+
+    result = await tool_node.ainvoke(
+        {
+            "messages": [
+                AIMessage(
+                    "hi?",
+                    tool_calls=[
+                        {
+                            "name": "my_tool",
+                            "args": {"value1": "invalid", "value2": 123},
+                            "id": "call_1",
+                            "type": "tool_call",
+                        }
+                    ],
+                )
+            ]
+        },
+        config=_create_config_with_runtime(),
+    )
+
+    tool_message = result["messages"][0]
+    assert tool_message.status == "error"
+
+    # Both errors should be present since there are no injected args to filter
+    assert "value1" in tool_message.content
+    assert "value2" in tool_message.content
+
+
+async def test_tool_invocation_error_without_handle_errors() -> None:
+    """Test that ToolInvocationError contains only LLM-controlled parameter errors.
+
+    When handle_tool_errors is False, the raised ToolInvocationError should still
+    filter out system-injected arguments from the error details, ensuring that
+    error messages focus on what the LLM can control.
+    """
+
+    @dec_tool
+    def my_tool(
+        value: int,
+        state: Annotated[dict, InjectedState],
+    ) -> str:
+        """Tool with injected state.
+
+        Args:
+            value: An integer value.
+            state: The graph state (injected).
+        """
+        return f"value={value}"
+
+    tool_node = ToolNode([my_tool], handle_tool_errors=False)
+
+    # Should raise ToolInvocationError with filtered errors
+    with pytest.raises(ToolInvocationError) as exc_info:
+        await tool_node.ainvoke(
+            {
+                "messages": [
+                    AIMessage(
+                        "hi?",
+                        tool_calls=[
+                            {
+                                "name": "my_tool",
+                                "args": {"value": "not_an_int"},
+                                "id": "call_1",
+                                "type": "tool_call",
+                            }
+                        ],
+                    )
+                ]
+            },
+            config=_create_config_with_runtime(),
+        )
+
+    error = exc_info.value
+    assert error.tool_name == "my_tool"
+    assert error.filtered_errors is not None
+    assert len(error.filtered_errors) > 0
+
+    # Filtered errors should only contain 'value' error, not 'state'
+    error_locs = [err["loc"] for err in error.filtered_errors]
+    assert any("value" in str(loc) for loc in error_locs)
+    assert not any("state" in str(loc) for loc in error_locs)
+
+
+async def test_sync_tool_validation_error_filtering() -> None:
+    """Test that error filtering works for sync tools.
+
+    Error filtering should work identically for both sync and async tool execution,
+    excluding injected arguments from validation error messages.
+    """
+
+    @dec_tool
+    def my_tool(
+        value: int,
+        state: Annotated[dict, InjectedState],
+    ) -> str:
+        """Sync tool with injected state.
+
+        Args:
+            value: An integer value.
+            state: The graph state (injected).
+        """
+        return f"value={value}"
+
+    tool_node = ToolNode([my_tool])
+
+    # Test sync invocation
+    result = tool_node.invoke(
+        {
+            "messages": [
+                AIMessage(
+                    "hi?",
+                    tool_calls=[
+                        {
+                            "name": "my_tool",
+                            "args": {"value": "not_an_int"},
+                            "id": "call_1",
+                            "type": "tool_call",
+                        }
+                    ],
+                )
+            ]
+        },
+        config=_create_config_with_runtime(),
+    )
+
+    tool_message = result["messages"][0]
+    assert tool_message.status == "error"
+    assert "value" in tool_message.content
+    assert "state" not in tool_message.content.lower()
@@ -1,5 +1,5 @@
 version = 1
-revision = 3
+revision = 2
 requires-python = ">=3.10"

 [[package]]
@@ -228,7 +228,7 @@ wheels = [

 [[package]]
 name = "langchain-core"
-version = "0.3.76"
+version = "1.0.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "jsonpatch" },
@@ -239,14 +239,14 @@ dependencies = [
    { name = "tenacity" },
    { name = "typing-extensions" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/4f/4d/5e2ea7754ee0a1f524c412801c6ba9ad49318ecb58b0d524903c3d9efe0a/langchain_core-0.3.76.tar.gz", hash = "sha256:71136a122dd1abae2c289c5809d035cf12b5f2bb682d8a4c1078cd94feae7419", size = 573568, upload-time = "2025-09-10T14:49:39.863Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/ad/d0/9db6d375ecf8bd498fcc87016e43c3d930ddbfbacf9a1e99018ada4e824f/langchain_core-1.0.0.tar.gz", hash = "sha256:8e81c94a22fa3a362a0f101bbd1271bf3725e50cf1e31c84e8f4a1c731279785", size = 764484, upload-time = "2025-10-17T13:48:24.408Z" }
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/68/6a/8dd566cb7379d6e3a921f94713babba2f71cbed65c73c784c649c1fd7d4e/langchain_core-1.0.0-py3-none-any.whl", hash = "sha256:a94561bf75dd097c7d6e3864950f28dadc963f0bd810114de4095f41f634059b", size = 467157, upload-time = "2025-10-17T13:48:23.138Z" },
 ]

 [[package]]
 name = "langgraph"
-version = "1.0.1"
+version = "1.0.2"
 source = { editable = "../langgraph" }
 dependencies = [
    { name = "langchain-core" },
@@ -271,7 +271,7 @@ requires-dist = [
 dev = [
    { name = "httpx" },
    { name = "jupyter" },
-    { name = "langchain-core", specifier = "==1.0.0a1" },
+    { name = "langchain-core", specifier = ">=1.0.0" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
    { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
    { name = "langgraph-checkpoint-sqlite", editable = "../checkpoint-sqlite" },
@@ -304,7 +304,7 @@ lint = [
 ]
 test = [
    { name = "httpx" },
-    { name = "langchain-core", specifier = "==1.0.0a1" },
+    { name = "langchain-core", specifier = ">=1.0.0" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
    { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
    { name = "langgraph-checkpoint-sqlite", editable = "../checkpoint-sqlite" },
@@ -467,7 +467,7 @@ test = [

 [[package]]
 name = "langgraph-prebuilt"
-version = "1.0.1"
+version = "1.0.2"
 source = { editable = "." }
 dependencies = [
    { name = "langchain-core" },
@@ -483,6 +483,7 @@ dev = [
    { name = "langgraph-checkpoint-postgres" },
    { name = "langgraph-checkpoint-sqlite" },
    { name = "mypy" },
+    { name = "psycopg-binary" },
    { name = "pytest" },
    { name = "pytest-asyncio" },
    { name = "pytest-mock" },
@@ -501,6 +502,7 @@ test = [
    { name = "langgraph-checkpoint" },
    { name = "langgraph-checkpoint-postgres" },
    { name = "langgraph-checkpoint-sqlite" },
+    { name = "psycopg-binary" },
    { name = "pytest" },
    { name = "pytest-asyncio" },
    { name = "pytest-mock" },
@@ -510,7 +512,7 @@ test = [

 [package.metadata]
 requires-dist = [
-    { name = "langchain-core", specifier = ">=0.3.67" },
+    { name = "langchain-core", specifier = ">=1.0.0" },
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
 ]

@@ -523,6 +525,7 @@ dev = [
    { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
    { name = "langgraph-checkpoint-sqlite", editable = "../checkpoint-sqlite" },
    { name = "mypy" },
+    { name = "psycopg-binary" },
    { name = "pytest" },
    { name = "pytest-asyncio" },
    { name = "pytest-mock" },
@@ -541,6 +544,7 @@ test = [
    { name = "langgraph-checkpoint", editable = "../checkpoint" },
    { name = "langgraph-checkpoint-postgres", editable = "../checkpoint-postgres" },
    { name = "langgraph-checkpoint-sqlite", editable = "../checkpoint-sqlite" },
+    { name = "psycopg-binary" },
    { name = "pytest" },
    { name = "pytest-asyncio" },
    { name = "pytest-mock" },
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 ]

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+
 [[package]]
 name = "psycopg-pool"
 version = "3.2.6"
@@ -194,7 +194,6 @@ class Auth:
        by name:

            - request (Request): The raw ASGI request object
-            - body (dict): The parsed request body
            - path (str): The request path, e.g., "/threads/abcd-1234-abcd-1234/runs/abcd-1234-abcd-1234/stream"
            - method (str): The HTTP method, e.g., "GET"
            - path_params (dict[str, str]): URL path parameters, e.g., {"thread_id": "abcd-1234-abcd-1234", "run_id": "abcd-1234-abcd-1234"}
@@ -2,10 +2,10 @@

 ## Reporting OSS Vulnerabilities

-LangChain is partnered with [huntr by Protect AI](https://huntr.com/) to provide 
-a bounty program for our open source projects. 
+LangChain is partnered with [huntr by Protect AI](https://huntr.com/) to provide
+a bounty program for our open source projects.

-Please report security vulnerabilities associated with the LangChain 
+Please report security vulnerabilities associated with the LangChain
 open source projects by visiting the following link:

 [https://huntr.com/bounties/disclose/](https://huntr.com/bounties/disclose/?target=https%3A%2F%2Fgithub.com%2Flangchain-ai%2Flangchain&validSearch=true)
@@ -13,7 +13,7 @@ open source projects by visiting the following link:
 Before reporting a vulnerability, please review:

 1) In-Scope Targets and Out-of-Scope Targets below.
-2) The [langchain-ai/langchain](https://python.langchain.com/docs/contributing/repo_structure) monorepo structure.
+2) The [langchain-ai/langchain](https://github.com/langchain-ai/langchain) monorepo structure.
 3) LangChain [security guidelines](https://python.langchain.com/docs/security) to
   understand what we consider to be a security vulnerability vs. developer
   responsibility.
@@ -53,8 +53,8 @@ All out of scope targets defined by huntr as well as:

 Please report security vulnerabilities associated with LangSmith by email to `security@langchain.dev`.

- LangSmith site: https://smith.langchain.com
- SDK client: https://github.com/langchain-ai/langsmith-sdk
+- LangSmith site: <https://smith.langchain.com>
+- SDK client: <https://github.com/langchain-ai/langsmith-sdk>

 ### Other Security Concerns