feat(prebuilt): add support for handle_tool_errors with single exception type (#6021)

This PR extends the `ToolNode` `handle_tool_errors` property to also
accept a single exception type: `type[Exception]`.

Example:
```python
tool_node_with_error_handling = ToolNode(
    [tool1, tool2, tool3], handle_tool_errors=ValueError
).invoke(...)
"""A tool node that will only retry a failed tool call if a ValueError is raised"""
```

.github/scripts/check_sdk_methods.py

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

.github/scripts/run_langgraph_cli_test.py

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

.github/workflows/_integration_test.yml

@@ -43,43 +43,28 @@ jobs:
       - name: Build and test service A
         if: steps.changed-files.outputs.all
         working-directory: libs/cli/examples
-        env:
-          LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
         run: |
           # The build-arg isn't used; just testing that we accept other args
-          langgraph build -t langgraph-test-a
-          cp .env.example .env
-          if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
+          langgraph build -t langgraph-test-a  --base-image "langchain/langgraph-trial"
+          cp .env.example .envg
           timeout 60 python ../../../.github/scripts/run_langgraph_cli_test.py -c langgraph.json -t langgraph-test-a
       - name: Build and test service B
         if: steps.changed-files.outputs.all
         working-directory: libs/cli/examples/graphs
-        env:
-          LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
         run: |
-          langgraph build -t langgraph-test-b
-          cp ../.env.example .env
-          if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
+          langgraph build -t langgraph-test-b  --base-image "langchain/langgraph-trial"
           timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-b
       - name: Build and test service C
         if: steps.changed-files.outputs.all
         working-directory: libs/cli/examples/graphs_reqs_a
-        env:
-          LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
         run: |
-          langgraph build -t langgraph-test-c
-          cp ../.env.example .env
-          if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
+          langgraph build -t langgraph-test-c  --base-image "langchain/langgraph-trial"
           timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-c
       - name: Build and test service D
         if: steps.changed-files.outputs.all
         working-directory: libs/cli/examples/graphs_reqs_b
-        env:
-          LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
         run: |
-          langgraph build -t langgraph-test-d
-          cp ../.env.example .env
-          if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
+          langgraph build -t langgraph-test-d  --base-image "langchain/langgraph-trial"
           timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-d
 
       - name: Build JS service
@@ -87,27 +72,3 @@ jobs:
         working-directory: libs/cli/js-examples
         run: |
           langgraph build -t langgraph-test-e
-
-      - name: Build JS monorepo service
-        if: steps.changed-files.outputs.all
-        working-directory: libs/cli/js-monorepo-example
-        run: |
-          langgraph build -t langgraph-test-f -c apps/agent/langgraph.json --build-command "yarn run turbo build" --install-command "yarn install"
-
-      - name: Build Python monorepo service
-        if: steps.changed-files.outputs.all
-        working-directory: libs/cli/python-monorepo-example
-        run: |
-          langgraph build -t langgraph-test-g -c apps/agent/langgraph.json
-          cp apps/agent/.env.example apps/agent/.env
-          if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> apps/agent/.env; fi
-          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
-        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

.github/workflows/ci.yml

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

.github/workflows/release.yml

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

docs/_scripts/notebook_hooks.py

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

docs/docs/cloud/deployment/cloud.md

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

docs/docs/cloud/reference/cli.md

@@ -483,19 +483,19 @@ The LangGraph CLI requires a JSON configuration file that follows this [schema](
 
     RUN PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 pip install --no-cache-dir -c /api/constraints.txt langchain_community langchain_anthropic langchain_openai wikipedia scikit-learn
 
-    ADD ./graphs /deps/outer-graphs/src
+    ADD ./graphs /deps/__outer_graphs/src
     RUN set -ex && \
         for line in '[project]' \
                     'name = "graphs"' \
                     'version = "0.1"' \
                     '[tool.setuptools.package-data]' \
                     '"*" = ["**/*"]'; do \
-            echo "$line" >> /deps/outer-graphs/pyproject.toml; \
+            echo "$line" >> /deps/__outer_graphs/pyproject.toml; \
         done
 
     RUN PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 pip install --no-cache-dir -c /api/constraints.txt -e /deps/*
 
-    ENV LANGSERVE_GRAPHS='{"agent": "/deps/outer-graphs/src/agent.py:graph", "storm": "/deps/outer-graphs/src/storm.py:graph"}'
+    ENV LANGSERVE_GRAPHS='{"agent": "/deps/__outer_graphs/src/agent.py:graph", "storm": "/deps/__outer_graphs/src/storm.py:graph"}'
     ```
 
     ???+ note "Updating your langgraph.json file"

docs/docs/concepts/low_level.md

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

docs/docs/concepts/persistence.md

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

docs/docs/concepts/plans.md

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

docs/overrides/main.html

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

libs/checkpoint/tests/test_redis_cache.py

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

libs/cli/Makefile

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

libs/cli/examples/.env.example

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

libs/cli/examples/graph_prerelease_reqs/agent.py

@@ -1,95 +0,0 @@
-from collections.abc import Sequence
-from typing import Annotated, Literal, TypedDict
-
-from langchain.chat_models import init_chat_model
-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)]
-
-model_anth = init_chat_model("claude-3-7-sonnet-20250219", model_provider="anthropic")
-model_oai = ChatOpenAI(temperature=0)
-
-model_anth = model_anth.bind_tools(tools)
-model_oai = model_oai.bind_tools(tools)
-
-
-class AgentState(TypedDict):
-    messages: Annotated[Sequence[BaseMessage], add_messages]
-
-
-# Define the function that determines whether to continue or not
-def should_continue(state):
-    messages = state["messages"]
-    last_message = messages[-1]
-    # If there are no tool calls, then we finish
-    if not last_message.tool_calls:
-        return "end"
-    # Otherwise if there is, we continue
-    else:
-        return "continue"
-
-
-# Define the function that calls the model
-def call_model(state, config):
-    if config["configurable"].get("model", "anthropic") == "anthropic":
-        model = model_anth
-    else:
-        model = model_oai
-    messages = state["messages"]
-    response = model.invoke(messages)
-    # We return a list, because this will get added to the existing list
-    return {"messages": [response]}
-
-
-# Define the function to execute tools
-tool_node = ToolNode(tools)
-
-
-class ContextSchema(TypedDict):
-    model: Literal["anthropic", "openai"]
-
-
-# Define a new graph
-workflow = StateGraph(AgentState, context_schema=ContextSchema)
-
-# Define the two nodes we will cycle between
-workflow.add_node("agent", call_model)
-workflow.add_node("action", tool_node)
-
-# Set the entrypoint as `agent`
-# This means that this node is the first one called
-workflow.set_entry_point("agent")
-
-# We now add a conditional edge
-workflow.add_conditional_edges(
-    # First, we define the start node. We use `agent`.
-    # This means these are the edges taken after the `agent` node is called.
-    "agent",
-    # Next, we pass in the function that will determine which node is called next.
-    should_continue,
-    # Finally we pass in a mapping.
-    # The keys are strings, and the values are other nodes.
-    # END is a special node marking that the graph should finish.
-    # What will happen is we will call `should_continue`, and then the output of that
-    # will be matched against the keys in this mapping.
-    # Based on which one it matches, that node will then be called.
-    {
-        # If `tools`, then we call the tool node.
-        "continue": "action",
-        # Otherwise we finish.
-        "end": END,
-    },
-)
-
-# We now add a normal edge from `tools` to `agent`.
-# This means that after `tools` is called, `agent` node is called next.
-workflow.add_edge("action", "agent")
-
-# Finally, we compile it!
-# This compiles it into a LangChain Runnable,
-# meaning you can use it as you would any other runnable
-graph = workflow.compile()

libs/cli/examples/graph_prerelease_reqs/langgraph.json

@@ -1,11 +0,0 @@
-{
-    "python_version": "3.12",
-    "dependencies": [
-      "."
-    ],
-    "graphs": {
-      "agent": "./agent.py:graph"
-    },
-    "env": "../.env"
-  }
-  

libs/cli/examples/graph_prerelease_reqs/requirements.txt

@@ -1,6 +0,0 @@
-requests
-langchain_anthropic
-langchain_openai
-langchain_community
-langchain
-langgraph==1.0.0a2

libs/cli/generate_schema.py

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

libs/cli/js-monorepo-example/.eslintrc.cjs

@@ -1,62 +0,0 @@
-module.exports = {
-  extends: [
-    "eslint:recommended",
-    "prettier",
-    "plugin:@typescript-eslint/recommended",
-  ],
-  parserOptions: {
-    ecmaVersion: 12,
-    parser: "@typescript-eslint/parser",
-    project: "./tsconfig.json",
-    sourceType: "module",
-  },
-  plugins: ["import", "@typescript-eslint", "no-instanceof"],
-  ignorePatterns: [
-    ".eslintrc.cjs",
-    "scripts",
-    "src/utils/lodash/*",
-    "node_modules",
-    "dist",
-    "dist-cjs",
-    "*.js",
-    "*.cjs",
-    "*.d.ts",
-  ],
-  rules: {
-    "no-process-env": 2,
-    "no-instanceof/no-instanceof": 2,
-    "@typescript-eslint/explicit-module-boundary-types": 0,
-    "@typescript-eslint/no-empty-function": 0,
-    "@typescript-eslint/no-shadow": 0,
-    "@typescript-eslint/no-empty-interface": 0,
-    "@typescript-eslint/no-use-before-define": ["error", "nofunc"],
-    "@typescript-eslint/no-unused-vars": ["warn", { args: "none" }],
-    "@typescript-eslint/no-floating-promises": "error",
-    "@typescript-eslint/no-misused-promises": "error",
-    camelcase: 0,
-    "class-methods-use-this": 0,
-    "import/extensions": [2, "ignorePackages"],
-    "import/no-extraneous-dependencies": [
-      "error",
-      { devDependencies: ["**/*.test.ts"] },
-    ],
-    "import/no-unresolved": 0,
-    "import/prefer-default-export": 0,
-    "keyword-spacing": "error",
-    "max-classes-per-file": 0,
-    "max-len": 0,
-    "no-await-in-loop": 0,
-    "no-bitwise": 0,
-    "no-console": 0,
-    "no-restricted-syntax": 0,
-    "no-shadow": 0,
-    "no-continue": 0,
-    "no-underscore-dangle": 0,
-    "no-use-before-define": 0,
-    "no-useless-constructor": 0,
-    "no-return-await": 0,
-    "consistent-return": 0,
-    "no-else-return": 0,
-    "new-cap": ["error", { properties: false, capIsNew: false }],
-  },
-};

libs/cli/js-monorepo-example/apps/agent/langgraph.json

@@ -1,7 +0,0 @@
-{
-  "node_version": "20",
-  "graphs": {
-    "agent": "./src/graph.ts:graph"
-  },
-  "env": "../../.env"
-}

libs/cli/js-monorepo-example/apps/agent/package.json

@@ -1,18 +0,0 @@
-{
-  "name": "@js-monorepo-example/agent",
-  "version": "0.0.1",
-  "type": "module",
-  "main": "src/graph.ts",
-  "scripts": {
-    "build": "tsc",
-    "clean": "rm -rf dist"
-  },
-  "dependencies": {
-    "@js-monorepo-example/shared": "*",
-    "@langchain/core": "^0.3.2",
-    "@langchain/langgraph": "^0.2.5"
-  },
-  "devDependencies": {
-    "typescript": "^5.3.3"
-  }
-}

libs/cli/js-monorepo-example/apps/agent/src/graph.ts

@@ -1,47 +0,0 @@
-/**
- * Simple LangGraph.js example for monorepo testing
- */
-import { StateGraph } from "@langchain/langgraph";
-import { RunnableConfig } from "@langchain/core/runnables";
-import { StateAnnotation } from "./state.js";
-import { getGreeting } from "@js-monorepo-example/shared";
-
-/**
- * Simple node that uses the shared library
- */
-const callModel = async (
-  state: typeof StateAnnotation.State,
-  _config: RunnableConfig,
-): Promise<typeof StateAnnotation.Update> => {
-  // Use functions from the shared library
-  const greeting = getGreeting();
-
-  return {
-    messages: [
-      {
-        role: "assistant",
-        content: `${greeting}`,
-      },
-    ],
-  };
-};
-
-/**
- * Simple routing function
- */
-export const route = (
-  state: typeof StateAnnotation.State,
-): "__end__" | "callModel" => {
-  if (state.messages.length > 0) {
-    return "__end__";
-  }
-  return "callModel";
-};
-
-// Create the graph
-const builder = new StateGraph(StateAnnotation)
-  .addNode("callModel", callModel)
-  .addEdge("__start__", "callModel")
-  .addConditionalEdges("callModel", route);
-
-export const graph = builder.compile();

libs/cli/js-monorepo-example/apps/agent/src/state.ts

@@ -1,15 +0,0 @@
-import { BaseMessage, BaseMessageLike } from "@langchain/core/messages";
-import { Annotation, messagesStateReducer } from "@langchain/langgraph";
-
-/**
- * Simple state annotation for the agent
- */
-export const StateAnnotation = Annotation.Root({
-  /**
-   * Messages track the primary execution state of the agent.
-   */
-  messages: Annotation<BaseMessage[], BaseMessageLike[]>({
-    reducer: messagesStateReducer,
-    default: () => [],
-  }),
-});

libs/cli/js-monorepo-example/apps/agent/tsconfig.json

@@ -1,9 +0,0 @@
-{
-  "extends": "../../tsconfig.json",
-  "compilerOptions": {
-    "outDir": "./dist",
-    "rootDir": "./src"
-  },
-  "include": ["src/**/*"],
-  "exclude": ["node_modules", "dist"]
-}

libs/cli/js-monorepo-example/libs/shared/package.json

@@ -1,14 +0,0 @@
-{
-  "name": "@js-monorepo-example/shared",
-  "version": "0.0.1",
-  "type": "module",
-  "main": "dist/index.js",
-  "types": "dist/index.d.ts",
-  "scripts": {
-    "build": "tsc",
-    "clean": "rm -rf dist"
-  },
-  "devDependencies": {
-    "typescript": "^5.3.3"
-  }
-}

libs/cli/js-monorepo-example/libs/shared/src/index.ts

@@ -1,6 +0,0 @@
-/**
- * Simple utility functions for monorepo testing
- */
-export function getGreeting(): string {
-  return "Hello from shared library!";
-}

libs/cli/js-monorepo-example/libs/shared/tsconfig.json

@@ -1,9 +0,0 @@
-{
-  "extends": "../../tsconfig.json",
-  "compilerOptions": {
-    "outDir": "./dist",
-    "rootDir": "./src"
-  },
-  "include": ["src/**/*"],
-  "exclude": ["node_modules", "dist"]
-}

libs/cli/js-monorepo-example/package.json

@@ -1,34 +0,0 @@
-{
-  "name": "js-monorepo-example",
-  "version": "0.0.1",
-  "packageManager": "yarn@1.22.22",
-  "description": "A simple monorepo example for LangGraph integration testing.",
-  "private": true,
-  "workspaces": [
-    "libs/*",
-    "apps/*"
-  ],
-  "type": "module",
-  "scripts": {
-    "build": "turbo build",
-    "clean": "turbo clean",
-    "test": "turbo test",
-    "format": "prettier --write .",
-    "lint": "eslint 'apps/**/*.ts' 'libs/**/*.ts'"
-  },
-  "devDependencies": {
-    "turbo": "^2.5.0",
-    "typescript": "^5.3.3",
-    "@tsconfig/recommended": "^1.0.7",
-    "@eslint/eslintrc": "^3.1.0",
-    "@eslint/js": "^9.9.1",
-    "eslint": "^8.41.0",
-    "eslint-config-prettier": "^8.8.0",
-    "eslint-plugin-import": "^2.27.5",
-    "eslint-plugin-no-instanceof": "^1.0.1",
-    "eslint-plugin-prettier": "^4.2.1",
-    "@typescript-eslint/eslint-plugin": "^5.59.8",
-    "@typescript-eslint/parser": "^5.59.8",
-    "prettier": "^3.3.3"
-  }
-}

libs/cli/js-monorepo-example/tsconfig.json

@@ -1,16 +0,0 @@
-{
-  "extends": "@tsconfig/recommended",
-  "compilerOptions": {
-    "target": "ES2022",
-    "module": "ESNext",
-    "moduleResolution": "node",
-    "allowSyntheticDefaultImports": true,
-    "esModuleInterop": true,
-    "skipLibCheck": true,
-    "strict": true,
-    "declaration": true,
-    "outDir": "./dist"
-  },
-  "include": ["apps/**/*", "libs/**/*"],
-  "exclude": ["node_modules", "dist"]
-}

libs/cli/js-monorepo-example/turbo.json

@@ -1,15 +0,0 @@
-{
-  "$schema": "https://turbo.build/schema.json",
-  "tasks": {
-    "build": {
-      "dependsOn": ["^build"],
-      "outputs": ["dist/**"]
-    },
-    "clean": {
-      "dependsOn": ["^clean"]
-    },
-    "test": {
-      "dependsOn": ["^test"]
-    }
-  }
-}

libs/cli/langgraph_cli/__init__.py

@@ -1 +0,0 @@
-__version__ = "0.4.2"

libs/cli/langgraph_cli/cli.py

@@ -303,8 +303,6 @@ def _build(
     pull: bool,
     tag: str,
     passthrough: Sequence[str] = (),
-    install_command: Optional[str] = None,
-    build_command: Optional[str] = None,
 ):
     # pull latest images
     if pull:
@@ -324,38 +322,22 @@ def _build(
         "-t",
         tag,
     ]
-    # determine build context: use current directory for JS projects, config parent for Python
-    is_js_project = config_json.get("node_version") and not config_json.get(
-        "python_version"
-    )
-    # build/install commands only apply to JS projects for now
-    # without install/build command, JS projects will follow the old behavior
-    if is_js_project and (build_command or install_command):
-        build_context = str(pathlib.Path.cwd())
-    else:
-        build_context = str(config.parent)
-
     # apply config
     stdin, additional_contexts = langgraph_cli.config.config_to_docker(
-        config,
-        config_json,
-        base_image,
-        api_version,
-        install_command,
-        build_command,
-        build_context,
+        config, config_json, base_image, api_version
     )
     # add additional_contexts
     if additional_contexts:
         for k, v in additional_contexts.items():
             args.extend(["--build-context", f"{k}={v}"])
+    # run docker build
     runner.run(
         subp_exec(
             "docker",
             "build",
             *args,
             *passthrough,
-            build_context,
+            str(config.parent),
             input=stdin,
             verbose=True,
         )
@@ -384,14 +366,6 @@ def _build(
     "\n    --base-image langchain/langgraph-server:0.2  # Pin to a minor version (Python)",
 )
 @OPT_API_VERSION
-@click.option(
-    "--install-command",
-    help="Custom install command to run from the build context root. If not provided, auto-detects based on package manager files.",
-)
-@click.option(
-    "--build-command",
-    help="Custom build command to run from the langgraph.json directory. If not provided, uses default build process.",
-)
 @click.argument("docker_build_args", nargs=-1, type=click.UNPROCESSED)
 @cli.command(
     help="📦 Build LangGraph API server Docker image.",
@@ -407,8 +381,6 @@ def build(
     api_version: Optional[str],
     pull: bool,
     tag: str,
-    install_command: Optional[str],
-    build_command: Optional[str],
 ):
     with Runner() as runner, Progress(message="Pulling...") as set:
         if shutil.which("docker") is None:
@@ -425,8 +397,6 @@ def build(
             pull,
             tag,
             docker_build_args,
-            install_command,
-            build_command,
         )
 
 

libs/cli/langgraph_cli/config.py

@@ -17,9 +17,6 @@ DEFAULT_PYTHON_VERSION = "3.11"
 DEFAULT_IMAGE_DISTRO = "debian"
 
 
-Distros = Literal["debian", "wolfi", "bullseye", "bookworm"]
-
-
 class TTLConfig(TypedDict, total=False):
     """Configuration for TTL (time-to-live) behavior in the store."""
 
@@ -357,8 +354,6 @@ class HttpConfig(TypedDict, total=False):
 
     You can include or exclude headers as configurable values to condition your
     agent's behavior or permissions on a request's headers."""
-    logging_headers: Optional[ConfigurableHeaderConfig]
-    """Optional. Defines which headers are excluded from logging."""
 
 
 class Config(TypedDict, total=False):
@@ -374,13 +369,6 @@ class Config(TypedDict, total=False):
     Must be >= 20 if provided.
     """
 
-    api_version: Optional[str]
-    """Optional. Which semantic version of the LangGraph API server to use.
-    
-    Defaults to latest. Check the
-    [changelog](https://docs.langchain.com/langgraph-platform/langgraph-server-changelog)
-    for more information."""
-
     _INTERNAL_docker_tag: Optional[str]
     """Optional. Internal use only.
     """
@@ -390,11 +378,10 @@ class Config(TypedDict, total=False):
     
     Defaults to langchain/langgraph-api or langchain/langgraphjs-api."""
 
-    image_distro: Optional[Distros]
+    image_distro: Optional[str]
     """Optional. Linux distribution for the base image.
     
-    Must be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.
-    If omitted, defaults to 'debian' ('latest').
+    Must be either 'debian' or 'wolfi'. If omitted, defaults to 'debian'.
     """
 
     pip_config_file: Optional[str]
@@ -600,28 +587,13 @@ def validate_config(config: Config) -> Config:
     )
 
     image_distro = config.get("image_distro", DEFAULT_IMAGE_DISTRO)
-    internal_docker_tag = config.get("_INTERNAL_docker_tag")
-    api_version = config.get("api_version")
-    if internal_docker_tag:
-        if api_version:
-            raise click.UsageError(
-                "Cannot specify both _INTERNAL_docker_tag and api_version."
-            )
-    if api_version:
-        try:
-            parts = tuple(map(int, api_version.split("-")[0].split(".")))
-            if len(parts) > 3:
-                raise ValueError(
-                    "Version must be major or major.minor or major.minor.patch."
-                )
-        except TypeError:
-            raise click.UsageError(f"Invalid version format: {api_version}") from None
 
     config = {
         "node_version": node_version,
         "python_version": python_version,
         "pip_config_file": config.get("pip_config_file"),
         "pip_installer": config.get("pip_installer", "auto"),
+        "_INTERNAL_docker_tag": config.get("_INTERNAL_docker_tag"),
         "base_image": config.get("base_image"),
         "image_distro": image_distro,
         "dependencies": config.get("dependencies", []),
@@ -636,10 +608,6 @@ def validate_config(config: Config) -> Config:
         "ui_config": config.get("ui_config"),
         "keep_pkg_tools": config.get("keep_pkg_tools"),
     }
-    if internal_docker_tag:
-        config["_INTERNAL_docker_tag"] = internal_docker_tag
-    if api_version:
-        config["api_version"] = api_version
 
     if config.get("node_version"):
         node_version = config["node_version"]
@@ -676,17 +644,17 @@ def validate_config(config: Config) -> Config:
                 "Add at least one dependency to 'dependencies' list."
             )
 
-    if not config.get("graphs"):
+    if not config["graphs"]:
         raise click.UsageError(
             "No graphs found in config. Add at least one graph to 'graphs' dictionary."
         )
 
     # Validate image_distro config
     if image_distro := config.get("image_distro"):
-        if image_distro not in Distros.__args__:
+        if image_distro not in ["debian", "wolfi"]:
             raise click.UsageError(
                 f"Invalid image_distro: '{image_distro}'. "
-                "Must be one of 'debian', 'bullseye', or 'bookworm'."
+                "Must be either 'debian' or 'wolfi'."
             )
 
     if pip_installer := config.get("pip_installer"):
@@ -913,10 +881,10 @@ def _assemble_local_deps(config_path: pathlib.Path, config: Config) -> LocalDeps
                         "Rename the directory to use it as flat-layout package."
                     )
                 check_reserved(resolved.name, local_dep)
-                container_path = f"/deps/outer-{resolved.name}/{resolved.name}"
+                container_path = f"/deps/__outer_{resolved.name}/{resolved.name}"
             else:
                 # src layout
-                container_path = f"/deps/outer-{resolved.name}/src"
+                container_path = f"/deps/__outer_{resolved.name}/src"
                 for file in files:
                     rfile = resolved / file
                     if (
@@ -1256,7 +1224,7 @@ def python_config_to_docker(
         else:
             pip_installer = "pip"
     if pip_installer == "uv":
-        install_cmd = "uv pip install --system --prerelease=allow"
+        install_cmd = "uv pip install --system"
     elif pip_installer == "pip":
         install_cmd = "pip install"
     else:
@@ -1286,7 +1254,7 @@ def python_config_to_docker(
     if local_deps.pip_reqs:
         pip_reqs_str = os.linesep.join(
             (
-                f"COPY --from=outer-{reqpath.name} requirements.txt {destpath}"
+                f"COPY --from=__outer_{reqpath.name} requirements.txt {destpath}"
                 if reqpath.parent in local_deps.additional_contexts
                 else f"ADD {reqpath.relative_to(config_path.parent)} {destpath}"
             )
@@ -1305,7 +1273,7 @@ def python_config_to_docker(
     faux_pkgs_str = f"{os.linesep}{os.linesep}".join(
         (
             f"""# -- Adding non-package dependency {fullpath.name} --
-COPY --from=outer-{fullpath.name} . {destpath}"""
+COPY --from=__outer_{fullpath.name} . {destpath}"""
             if fullpath in local_deps.additional_contexts
             else f"""# -- Adding non-package dependency {fullpath.name} --
 ADD {relpath} {destpath}"""
@@ -1320,7 +1288,7 @@ RUN set -ex && \\
                 '[build-system]' \\
                 'requires = ["setuptools>=61"]' \\
                 'build-backend = "setuptools.build_meta"'; do \\
-        echo "$line" >> /deps/outer-{fullpath.name}/pyproject.toml; \\
+        echo "$line" >> /deps/__outer_{fullpath.name}/pyproject.toml; \\
     done
 # -- End of non-package dependency {fullpath.name} --"""
         for fullpath, (relpath, destpath) in local_deps.faux_pkgs.items()
@@ -1423,7 +1391,7 @@ ADD {relpath} /deps/{name}
         if p in local_deps.real_pkgs:
             name = local_deps.real_pkgs[p][1]
         elif p in local_deps.faux_pkgs:
-            name = f"outer-{p.name}"
+            name = f"__outer_{p.name}"
         else:
             raise RuntimeError(f"Unknown additional context: {p}")
         additional_contexts[name] = str(p)
@@ -1436,28 +1404,9 @@ def node_config_to_docker(
     config: Config,
     base_image: str,
     api_version: Optional[str] = None,
-    install_command: Optional[str] = None,
-    build_command: Optional[str] = None,
-    build_context: Optional[str] = None,
 ) -> tuple[str, dict[str, str]]:
-    # Calculate paths for monorepo support
-    if build_context:
-        relative_workdir = _calculate_relative_workdir(config_path, build_context)
-        container_name = pathlib.Path(build_context).name
-        if relative_workdir:
-            faux_path = f"/deps/{container_name}/{relative_workdir}"
-        else:
-            faux_path = f"/deps/{container_name}"
-    else:
-        # Backward compatibility: use the original behavior
-        faux_path = f"/deps/{config_path.parent.name}"
-
-    # Use custom install command or auto-detect
-    if install_command:
-        install_cmd = install_command
-    else:
-        install_cmd = _get_node_pm_install_cmd(config_path, config)
-
+    faux_path = f"/deps/{config_path.parent.name}"
+    install_cmd = _get_node_pm_install_cmd(config_path, config)
     image_str = docker_tag(config, base_image, api_version)
 
     env_vars: list[str] = []
@@ -1484,35 +1433,20 @@ def node_config_to_docker(
 
     env_vars.append(f"ENV LANGSERVE_GRAPHS='{json.dumps(config['graphs'])}'")
 
-    # For monorepo support, we need to handle install and build commands differently
-    if build_context:
-        # Monorepo case: install from root, build from config directory
-        container_root = f"/deps/{pathlib.Path(build_context).name}"
-        install_step = f"RUN cd {container_root} && {install_cmd}"
-
-        if build_command:
-            build_step = f"RUN cd {faux_path} && {build_command}"
-        else:
-            build_step = 'RUN (test ! -f /api/langgraph_api/js/build.mts && echo "Prebuild script not found, skipping") || tsx /api/langgraph_api/js/build.mts'
-    else:
-        # Original behavior: everything happens in the same directory
-        install_step = f"RUN cd {faux_path} && {install_cmd}"
-        build_step = 'RUN (test ! -f /api/langgraph_api/js/build.mts && echo "Prebuild script not found, skipping") || tsx /api/langgraph_api/js/build.mts'
-
     docker_file_contents = [
         f"FROM {image_str}",
         "",
         os.linesep.join(config["dockerfile_lines"]),
         "",
-        f"ADD . {faux_path if not build_context else container_root}",
+        f"ADD . {faux_path}",
         "",
-        install_step,
+        f"RUN cd {faux_path} && {install_cmd}",
         "",
         os.linesep.join(env_vars),
         "",
         f"WORKDIR {faux_path}",
         "",
-        build_step,
+        'RUN (test ! -f /api/langgraph_api/js/build.mts && echo "Prebuild script not found, skipping") || tsx /api/langgraph_api/js/build.mts',
     ]
 
     return os.linesep.join(docker_file_contents), {}
@@ -1531,7 +1465,6 @@ def docker_tag(
     base_image: Optional[str] = None,
     api_version: Optional[str] = None,
 ) -> str:
-    api_version = api_version or config.get("api_version")
     base_image = base_image or default_base_image(config)
 
     image_distro = config.get("image_distro")
@@ -1540,6 +1473,9 @@ def docker_tag(
     if config.get("_INTERNAL_docker_tag"):
         return f"{base_image}:{config['_INTERNAL_docker_tag']}"
 
+    if "/langgraph-server" in base_image:
+        return f"{base_image}-py{config['python_version']}"
+
     # Build the standard tag format
     language, version = None, None
     if config.get("node_version") and not config.get("python_version"):
@@ -1552,50 +1488,22 @@ def docker_tag(
     # Prepend API version if provided
     if api_version:
         full_tag = f"{api_version}-{language}{version_distro_tag}"
-    elif "/langgraph-server" in base_image and version_distro_tag not in base_image:
-        return f"{base_image}-{language}{version_distro_tag}"
     else:
         full_tag = version_distro_tag
 
     return f"{base_image}:{full_tag}"
 
 
-def _calculate_relative_workdir(config_path: pathlib.Path, build_context: str) -> str:
-    """Calculate the relative path from build context to langgraph.json directory."""
-    config_dir = config_path.parent.resolve()
-    build_context_path = pathlib.Path(build_context).resolve()
-
-    try:
-        relative_path = config_dir.relative_to(build_context_path)
-        return str(relative_path) if str(relative_path) != "." else ""
-    except ValueError as _:
-        raise ValueError(
-            f"Configuration file {config_path} is not under the build context {build_context}. "
-            f"Please run the command from a directory that contains your langgraph.json file, "
-        ) from None
-
-
 def config_to_docker(
     config_path: pathlib.Path,
     config: Config,
     base_image: Optional[str] = None,
     api_version: Optional[str] = None,
-    install_command: Optional[str] = None,
-    build_command: Optional[str] = None,
-    build_context: Optional[str] = None,
 ) -> tuple[str, dict[str, str]]:
     base_image = base_image or default_base_image(config)
 
     if config.get("node_version") and not config.get("python_version"):
-        return node_config_to_docker(
-            config_path,
-            config,
-            base_image,
-            api_version,
-            install_command,
-            build_command,
-            build_context,
-        )
+        return node_config_to_docker(config_path, config, base_image, api_version)
 
     return python_config_to_docker(config_path, config, base_image, api_version)
 

libs/cli/pyproject.toml

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

libs/cli/python-monorepo-example/apps/agent/langgraph.json

@@ -1,7 +0,0 @@
-{
-  "dependencies": [".", "../../libs/shared", "../../libs/common"],
-  "graphs": {
-    "agent": "./src/agent/graph.py:graph"
-  },
-  "env": ".env"
-}

libs/cli/python-monorepo-example/apps/agent/pyproject.toml

@@ -1,19 +0,0 @@
-[project]
-name = "agent"
-version = "0.0.1"
-description = "Agent for the Python monorepo"
-authors = [
-    { name = "Developer", email = "dev@example.com" },
-]
-license = { text = "MIT" }
-requires-python = ">=3.11,<4.0"
-
-[build-system]
-requires = ["setuptools>=73.0.0", "wheel"]
-build-backend = "setuptools.build_meta"
-
-[tool.setuptools]
-packages = ["agent"]
-
-[tool.setuptools.package-dir]
-"agent" = "src/agent"

libs/cli/python-monorepo-example/apps/agent/src/agent/__init__.py

@@ -1 +0,0 @@
-"""Agent package."""

libs/cli/python-monorepo-example/apps/agent/src/agent/graph.py

@@ -1,40 +0,0 @@
-"""Simple LangGraph agent for monorepo testing."""
-
-from common import get_common_prefix
-from langchain_core.messages import AIMessage
-from langgraph.graph import END, START, StateGraph
-from shared import get_dummy_message
-
-from agent.state import State
-
-
-def call_model(state: State) -> dict:
-    """Simple node that uses the shared libraries."""
-    # Use functions from both shared packages
-    dummy_message = get_dummy_message()
-    prefix = get_common_prefix()
-
-    message = AIMessage(content=f"{prefix} Agent says: {dummy_message}")
-
-    return {"messages": [message]}
-
-
-def should_continue(state: State):
-    """Conditional edge - end after first message."""
-    messages = state["messages"]
-    if len(messages) > 0:
-        return END
-    return "call_model"
-
-
-# Build the graph
-workflow = StateGraph(State)
-
-# Add the node
-workflow.add_node("call_model", call_model)
-
-# Add edges
-workflow.add_edge(START, "call_model")
-workflow.add_conditional_edges("call_model", should_continue)
-
-graph = workflow.compile()

libs/cli/python-monorepo-example/apps/agent/src/agent/state.py

@@ -1,13 +0,0 @@
-"""State definition for the agent."""
-
-from collections.abc import Sequence
-from typing import Annotated, TypedDict
-
-from langchain_core.messages import BaseMessage
-from langgraph.graph.message import add_messages
-
-
-class State(TypedDict):
-    """The state of the agent."""
-
-    messages: Annotated[Sequence[BaseMessage], add_messages]

libs/cli/python-monorepo-example/libs/common/__init__.py

@@ -1,5 +0,0 @@
-"""Common helper functions package."""
-
-from .helpers import get_common_prefix
-
-__all__ = ["get_common_prefix"]

libs/cli/python-monorepo-example/libs/common/helpers.py

@@ -1,6 +0,0 @@
-"""Common helper functions."""
-
-
-def get_common_prefix() -> str:
-    """Get a common prefix for messages."""
-    return "[COMMON]"

libs/cli/python-monorepo-example/libs/shared/pyproject.toml

@@ -1,20 +0,0 @@
-[project]
-name = "shared"
-version = "0.0.1"
-description = "Shared utilities for the Python monorepo"
-authors = [
-    { name = "Developer", email = "dev@example.com" },
-]
-license = { text = "MIT" }
-requires-python = ">=3.11,<4.0"
-dependencies = []
-
-[build-system]
-requires = ["setuptools>=73.0.0", "wheel"]
-build-backend = "setuptools.build_meta"
-
-[tool.setuptools]
-packages = ["shared"]
-
-[tool.setuptools.package-dir]
-"shared" = "src/shared"

libs/cli/python-monorepo-example/libs/shared/src/shared/__init__.py

@@ -1,5 +0,0 @@
-"""Shared utilities package."""
-
-from .utils import get_dummy_message
-
-__all__ = ["get_dummy_message"]

libs/cli/python-monorepo-example/libs/shared/src/shared/utils.py

@@ -1,6 +0,0 @@
-"""Shared utility functions."""
-
-
-def get_dummy_message() -> str:
-    """Get a dummy message for testing."""
-    return "Hello from shared library!"

libs/cli/python-monorepo-example/pyproject.toml

@@ -1,46 +0,0 @@
-[project]
-name = "python-monorepo-example"
-version = "0.0.1"
-description = "A Python monorepo example with LangGraph agents and shared packages"
-authors = [
-    { name = "Developer", email = "dev@example.com" },
-]
-license = { text = "MIT" }
-requires-python = ">=3.11,<4.0"
-dependencies = [
-    "langgraph>=0.6.0,<0.7.0",
-    "langchain-core>=0.2.14",
-]
-
-[tool.uv.workspace]
-members = ["apps/*", "libs/shared"]
-
-[tool.uv.sources]
-shared = { workspace = true }
-
-[project.optional-dependencies]
-dev = ["mypy>=1.11.1", "ruff>=0.6.1"]
-
-[build-system]
-requires = ["setuptools>=73.0.0", "wheel"]
-build-backend = "setuptools.build_meta"
-
-[tool.ruff]
-lint.select = [
-    "E",    # pycodestyle
-    "F",    # pyflakes
-    "I",    # isort
-    "D",    # pydocstyle
-    "UP",
-]
-lint.ignore = [
-    "D100",  # Missing docstring in public module
-    "D101",  # Missing docstring in public class
-    "D102",  # Missing docstring in public method
-    "D103",  # Missing docstring in public function
-    "D104",  # Missing docstring in public package
-    "D105",  # Missing docstring in magic method
-]
-
-[tool.ruff.lint.pydocstyle]
-convention = "google"

libs/cli/schemas/schema.json

@@ -15,8 +15,7 @@
               "description": "Optional. Python version in 'major.minor' format (e.g. '3.11').\nMust be at least 3.11 or greater for this deployment to function properly.\n",
               "enum": [
                 "3.11",
-                "3.12",
-                "3.13"
+                "3.12"
               ]
             },
             "pip_config_file": {
@@ -41,17 +40,6 @@
               ],
               "description": "Optional. Internal use only.\n"
             },
-            "api_version": {
-              "anyOf": [
-                {
-                  "type": "string"
-                },
-                {
-                  "type": "null"
-                }
-              ],
-              "description": "Optional. Which semantic version of the LangGraph API server to use.\n\nDefaults to latest. Check the\nfor more information.\n"
-            },
             "auth": {
               "anyOf": [
                 {
@@ -134,9 +122,8 @@
             "image_distro": {
               "anyOf": [
                 {
+                  "type": "string",
                   "enum": [
-                    "bookworm",
-                    "bullseye",
                     "debian",
                     "wolfi"
                   ]
@@ -145,7 +132,7 @@
                   "type": "null"
                 }
               ],
-              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
+              "description": "Optional. Linux distribution for the base image.\n\nMust be either 'debian' or 'wolfi'. If omitted, defaults to 'debian'.\n"
             },
             "keep_pkg_tools": {
               "anyOf": [
@@ -234,17 +221,6 @@
               ],
               "description": "Optional. Internal use only.\n"
             },
-            "api_version": {
-              "anyOf": [
-                {
-                  "type": "string"
-                },
-                {
-                  "type": "null"
-                }
-              ],
-              "description": "Optional. Which semantic version of the LangGraph API server to use.\n\nDefaults to latest. Check the\nfor more information.\n"
-            },
             "auth": {
               "anyOf": [
                 {
@@ -337,7 +313,7 @@
                   "type": "null"
                 }
               ],
-              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
+              "description": "Optional. Linux distribution for the base image.\n\nMust be either 'debian' or 'wolfi'. If omitted, defaults to 'debian'.\n"
             },
             "keep_pkg_tools": {
               "anyOf": [
@@ -576,17 +552,6 @@
         "disable_threads": {
           "type": "boolean",
           "description": "Optional. If True, /threads routes are removed.\n\nDefault is False.\n"
-        },
-        "logging_headers": {
-          "anyOf": [
-            {
-              "$ref": "#/$defs/ConfigurableHeaderConfig"
-            },
-            {
-              "type": "null"
-            }
-          ],
-          "description": "Optional. Defines which headers are excluded from logging."
         }
       },
       "required": []

libs/cli/schemas/schema.v0.json

@@ -15,8 +15,7 @@
               "description": "Optional. Python version in 'major.minor' format (e.g. '3.11').\nMust be at least 3.11 or greater for this deployment to function properly.\n",
               "enum": [
                 "3.11",
-                "3.12",
-                "3.13"
+                "3.12"
               ]
             },
             "pip_config_file": {
@@ -41,17 +40,6 @@
               ],
               "description": "Optional. Internal use only.\n"
             },
-            "api_version": {
-              "anyOf": [
-                {
-                  "type": "string"
-                },
-                {
-                  "type": "null"
-                }
-              ],
-              "description": "Optional. Which semantic version of the LangGraph API server to use.\n\nDefaults to latest. Check the\nfor more information.\n"
-            },
             "auth": {
               "anyOf": [
                 {
@@ -134,9 +122,8 @@
             "image_distro": {
               "anyOf": [
                 {
+                  "type": "string",
                   "enum": [
-                    "bookworm",
-                    "bullseye",
                     "debian",
                     "wolfi"
                   ]
@@ -145,7 +132,7 @@
                   "type": "null"
                 }
               ],
-              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
+              "description": "Optional. Linux distribution for the base image.\n\nMust be either 'debian' or 'wolfi'. If omitted, defaults to 'debian'.\n"
             },
             "keep_pkg_tools": {
               "anyOf": [
@@ -234,17 +221,6 @@
               ],
               "description": "Optional. Internal use only.\n"
             },
-            "api_version": {
-              "anyOf": [
-                {
-                  "type": "string"
-                },
-                {
-                  "type": "null"
-                }
-              ],
-              "description": "Optional. Which semantic version of the LangGraph API server to use.\n\nDefaults to latest. Check the\nfor more information.\n"
-            },
             "auth": {
               "anyOf": [
                 {
@@ -337,7 +313,7 @@
                   "type": "null"
                 }
               ],
-              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
+              "description": "Optional. Linux distribution for the base image.\n\nMust be either 'debian' or 'wolfi'. If omitted, defaults to 'debian'.\n"
             },
             "keep_pkg_tools": {
               "anyOf": [
@@ -576,17 +552,6 @@
         "disable_threads": {
           "type": "boolean",
           "description": "Optional. If True, /threads routes are removed.\n\nDefault is False.\n"
-        },
-        "logging_headers": {
-          "anyOf": [
-            {
-              "$ref": "#/$defs/ConfigurableHeaderConfig"
-            },
-            {
-              "type": "null"
-            }
-          ],
-          "description": "Optional. Defines which headers are excluded from logging."
         }
       },
       "required": []

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

@@ -15,7 +15,7 @@ from langgraph_cli.docker import DEFAULT_POSTGRES_URI, DockerCapabilities, Versi
 from langgraph_cli.util import clean_empty_lines
 
 FORMATTED_CLEANUP_LINES = _get_pip_cleanup_lines(
-    install_cmd="uv pip install --system --prerelease=allow",
+    install_cmd="uv pip install --system",
     to_uninstall=("pip", "setuptools", "wheel"),
     pip_installer="uv",
 )
@@ -149,7 +149,7 @@ services:
                 COPY --from=cli_1 . /deps/cli_1
                 # -- End of local package ../../.. --
                 # -- Installing all local dependencies --
-                RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+                RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e /deps/*
                 # -- End of local dependencies install --
                 ENV LANGSERVE_GRAPHS='{{"agent": "agent.py:graph"}}'
 {textwrap.indent(textwrap.dedent(FORMATTED_CLEANUP_LINES), "                ")}
@@ -381,9 +381,7 @@ def test_dockerfile_command_with_base_image() -> None:
         assert save_path.exists()
         with open(save_path) as f:
             dockerfile = f.read()
-            assert re.match("FROM langchain/langgraph-server:0.2-py3.*", dockerfile), (
-                "\n".join(dockerfile.splitlines()[:3])
-            )
+            assert re.match("FROM langchain/langgraph-server:0.2-py3.*", dockerfile)
 
 
 def test_dockerfile_command_with_docker_compose() -> None:
@@ -570,7 +568,7 @@ def test_build_generate_proper_build_context():
                 catch_exceptions=True,
             )
 
-        build_context_pattern = re.compile(r"--build-context\s+([\w-]+)=([^\s]+)")
+        build_context_pattern = re.compile(r"--build-context\s+(\w+)=([^\s]+)")
 
         build_contexts = re.findall(build_context_pattern, result.output)
         assert len(build_contexts) == 2, (

libs/cli/tests/unit_tests/test_config.py

@@ -20,7 +20,7 @@ from langgraph_cli.config import (
 from langgraph_cli.util import clean_empty_lines
 
 FORMATTED_CLEANUP_LINES = _get_pip_cleanup_lines(
-    install_cmd="uv pip install --system --prerelease=allow",
+    install_cmd="uv pip install --system",
     to_uninstall=("pip", "setuptools", "wheel"),
     pip_installer="uv",
 )
@@ -38,6 +38,7 @@ def test_validate_config():
     }
     actual_config = validate_config(expected_config)
     expected_config = {
+        "_INTERNAL_docker_tag": None,
         "base_image": None,
         "python_version": "3.11",
         "node_version": None,
@@ -60,6 +61,7 @@ def test_validate_config():
     # full config
     env = ".env"
     expected_config = {
+        "_INTERNAL_docker_tag": None,
         "base_image": None,
         "python_version": "3.12",
         "node_version": None,
@@ -188,6 +190,7 @@ def test_validate_config_image_distro():
             }
         )
     assert "Invalid image_distro: 'ubuntu'" in str(exc_info.value)
+    assert "Must be either 'debian' or 'wolfi'" in str(exc_info.value)
 
     with pytest.raises(click.UsageError) as exc_info:
         validate_config(
@@ -421,14 +424,14 @@ def test_config_to_docker_simple():
     expected_docker_stdin = f"""\
 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
-RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -r /deps/outer-graphs_reqs_a/graphs_reqs_a/requirements.txt
+COPY --from=__outer_requirements.txt requirements.txt /deps/__outer_graphs_reqs_a/graphs_reqs_a/requirements.txt
+RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -r /deps/__outer_graphs_reqs_a/graphs_reqs_a/requirements.txt
 # -- End of local requirements install --
 # -- Adding local package ../../examples --
 COPY --from=examples . /deps/examples
 # -- End of local package ../../examples --
 # -- Adding non-package dependency unit_tests --
-ADD . /deps/outer-unit_tests/unit_tests
+ADD . /deps/__outer_unit_tests/unit_tests
 RUN set -ex && \\
     for line in '[project]' \\
                 'name = "unit_tests"' \\
@@ -438,11 +441,11 @@ RUN set -ex && \\
                 '[build-system]' \\
                 'requires = ["setuptools>=61"]' \\
                 'build-backend = "setuptools.build_meta"'; do \\
-        echo "$line" >> /deps/outer-unit_tests/pyproject.toml; \\
+        echo "$line" >> /deps/__outer_unit_tests/pyproject.toml; \\
     done
 # -- End of non-package dependency unit_tests --
 # -- Adding non-package dependency graphs_reqs_a --
-COPY --from=outer-graphs_reqs_a . /deps/outer-graphs_reqs_a/graphs_reqs_a
+COPY --from=__outer_graphs_reqs_a . /deps/__outer_graphs_reqs_a/graphs_reqs_a
 RUN set -ex && \\
     for line in '[project]' \\
                 'name = "graphs_reqs_a"' \\
@@ -452,21 +455,21 @@ RUN set -ex && \\
                 '[build-system]' \\
                 'requires = ["setuptools>=61"]' \\
                 'build-backend = "setuptools.build_meta"'; do \\
-        echo "$line" >> /deps/outer-graphs_reqs_a/pyproject.toml; \\
+        echo "$line" >> /deps/__outer_graphs_reqs_a/pyproject.toml; \\
     done
 # -- End of non-package dependency graphs_reqs_a --
 # -- Installing all local dependencies --
-RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e /deps/*
 # -- End of local dependencies install --
 ENV LANGGRAPH_HTTP='{{"app": "/deps/examples/my_app.py:app"}}'
-ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}}'
+ENV LANGSERVE_GRAPHS='{{"agent": "/deps/__outer_unit_tests/unit_tests/agent.py:graph"}}'
 {FORMATTED_CLEANUP_LINES}
-WORKDIR /deps/outer-unit_tests/unit_tests\
+WORKDIR /deps/__outer_unit_tests/unit_tests\
 """
     assert clean_empty_lines(actual_docker_stdin) == expected_docker_stdin
 
     assert additional_contexts == {
-        "outer-graphs_reqs_a": str(
+        "__outer_graphs_reqs_a": str(
             (pathlib.Path(__file__).parent / "../../examples/graphs_reqs_a").resolve()
         ),
         "examples": str((pathlib.Path(__file__).parent / "../../examples").resolve()),
@@ -484,7 +487,7 @@ def test_config_to_docker_outside_path():
         """\
 FROM langchain/langgraph-api:3.11
 # -- Adding non-package dependency unit_tests --
-ADD . /deps/outer-unit_tests/unit_tests
+ADD . /deps/__outer_unit_tests/unit_tests
 RUN set -ex && \\
     for line in '[project]' \\
                 'name = "unit_tests"' \\
@@ -494,11 +497,11 @@ RUN set -ex && \\
                 '[build-system]' \\
                 'requires = ["setuptools>=61"]' \\
                 'build-backend = "setuptools.build_meta"'; do \\
-        echo "$line" >> /deps/outer-unit_tests/pyproject.toml; \\
+        echo "$line" >> /deps/__outer_unit_tests/pyproject.toml; \\
     done
 # -- End of non-package dependency unit_tests --
 # -- Adding non-package dependency tests --
-COPY --from=outer-tests . /deps/outer-tests/tests
+COPY --from=__outer_tests . /deps/__outer_tests/tests
 RUN set -ex && \\
     for line in '[project]' \\
                 'name = "tests"' \\
@@ -508,22 +511,22 @@ RUN set -ex && \\
                 '[build-system]' \\
                 'requires = ["setuptools>=61"]' \\
                 'build-backend = "setuptools.build_meta"'; do \\
-        echo "$line" >> /deps/outer-tests/pyproject.toml; \\
+        echo "$line" >> /deps/__outer_tests/pyproject.toml; \\
     done
 # -- End of non-package dependency tests --
 # -- Installing all local dependencies --
-RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e /deps/*
 # -- End of local dependencies install --
-ENV LANGSERVE_GRAPHS='{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}'
+ENV LANGSERVE_GRAPHS='{"agent": "/deps/__outer_unit_tests/unit_tests/agent.py:graph"}'
 """
         + FORMATTED_CLEANUP_LINES
         + """
-WORKDIR /deps/outer-unit_tests/unit_tests\
+WORKDIR /deps/__outer_unit_tests/unit_tests\
 """
     )
     assert clean_empty_lines(actual_docker_stdin) == expected_docker_stdin
     assert additional_contexts == {
-        "outer-tests": str(pathlib.Path(__file__).parent.parent.absolute()),
+        "__outer_tests": str(pathlib.Path(__file__).parent.parent.absolute()),
     }
 
 
@@ -545,7 +548,7 @@ def test_config_to_docker_pipconfig():
 FROM langchain/langgraph-api:3.11
 ADD pipconfig.txt /pipconfig.txt
 # -- Adding non-package dependency unit_tests --
-ADD . /deps/outer-unit_tests/unit_tests
+ADD . /deps/__outer_unit_tests/unit_tests
 RUN set -ex && \\
     for line in '[project]' \\
                 'name = "unit_tests"' \\
@@ -555,17 +558,17 @@ RUN set -ex && \\
                 '[build-system]' \\
                 'requires = ["setuptools>=61"]' \\
                 'build-backend = "setuptools.build_meta"'; do \\
-        echo "$line" >> /deps/outer-unit_tests/pyproject.toml; \\
+        echo "$line" >> /deps/__outer_unit_tests/pyproject.toml; \\
     done
 # -- End of non-package dependency unit_tests --
 # -- Installing all local dependencies --
-RUN PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+RUN PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e /deps/*
 # -- End of local dependencies install --
-ENV LANGSERVE_GRAPHS='{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}'
+ENV LANGSERVE_GRAPHS='{"agent": "/deps/__outer_unit_tests/unit_tests/agent.py:graph"}'
 """
         + FORMATTED_CLEANUP_LINES
         + """
-WORKDIR /deps/outer-unit_tests/unit_tests\
+WORKDIR /deps/__outer_unit_tests/unit_tests\
 """
     )
     assert clean_empty_lines(actual_docker_stdin) == expected_docker_stdin
@@ -607,7 +610,7 @@ def test_config_to_docker_local_deps():
     expected_docker_stdin = f"""\
 FROM langchain/langgraph-api-custom:3.11
 # -- Adding non-package dependency graphs --
-ADD ./graphs /deps/outer-graphs/src
+ADD ./graphs /deps/__outer_graphs/src
 RUN set -ex && \\
     for line in '[project]' \\
                 'name = "graphs"' \\
@@ -617,13 +620,13 @@ RUN set -ex && \\
                 '[build-system]' \\
                 'requires = ["setuptools>=61"]' \\
                 'build-backend = "setuptools.build_meta"'; do \\
-        echo "$line" >> /deps/outer-graphs/pyproject.toml; \\
+        echo "$line" >> /deps/__outer_graphs/pyproject.toml; \\
     done
 # -- End of non-package dependency graphs --
 # -- Installing all local dependencies --
-RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e /deps/*
 # -- End of local dependencies install --
-ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-graphs/src/agent.py:graph"}}'
+ENV LANGSERVE_GRAPHS='{{"agent": "/deps/__outer_graphs/src/agent.py:graph"}}'
 {FORMATTED_CLEANUP_LINES}\
 """
     assert clean_empty_lines(actual_docker_stdin) == expected_docker_stdin
@@ -657,7 +660,7 @@ dependencies = ["langchain"]"""
 ADD . /deps/unit_tests
 # -- End of local package . --
 # -- Installing all local dependencies --
-RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e /deps/*
 # -- End of local dependencies install --
 ENV LANGSERVE_GRAPHS='{"agent": "/deps/unit_tests/graphs/agent.py:graph"}'
 """
@@ -689,9 +692,9 @@ def test_config_to_docker_end_to_end():
 ARG meow
 ARG foo
 ADD pipconfig.txt /pipconfig.txt
-RUN PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt langchain langchain_openai
+RUN PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt langchain langchain_openai
 # -- Adding non-package dependency graphs --
-ADD ./graphs/ /deps/outer-graphs/src
+ADD ./graphs/ /deps/__outer_graphs/src
 RUN set -ex && \\
     for line in '[project]' \\
                 'name = "graphs"' \\
@@ -701,13 +704,13 @@ RUN set -ex && \\
                 '[build-system]' \\
                 'requires = ["setuptools>=61"]' \\
                 'build-backend = "setuptools.build_meta"'; do \\
-        echo "$line" >> /deps/outer-graphs/pyproject.toml; \\
+        echo "$line" >> /deps/__outer_graphs/pyproject.toml; \\
     done
 # -- End of non-package dependency graphs --
 # -- Installing all local dependencies --
-RUN PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+RUN PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e /deps/*
 # -- End of local dependencies install --
-ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-graphs/src/agent.py:graph"}}'
+ENV LANGSERVE_GRAPHS='{{"agent": "/deps/__outer_graphs/src/agent.py:graph"}}'
 {FORMATTED_CLEANUP_LINES}"""
     assert clean_empty_lines(actual_docker_stdin) == expected_docker_stdin
     assert additional_contexts == {}
@@ -797,7 +800,7 @@ def test_config_to_docker_gen_ui_python():
     expected_docker_stdin = f"""FROM langchain/langgraph-api:3.11
 RUN /storage/install-node.sh
 # -- Adding non-package dependency unit_tests --
-ADD . /deps/outer-unit_tests/unit_tests
+ADD . /deps/__outer_unit_tests/unit_tests
 RUN set -ex && \\
     for line in '[project]' \\
                 'name = "unit_tests"' \\
@@ -807,21 +810,21 @@ RUN set -ex && \\
                 '[build-system]' \\
                 'requires = ["setuptools>=61"]' \\
                 'build-backend = "setuptools.build_meta"'; do \\
-        echo "$line" >> /deps/outer-unit_tests/pyproject.toml; \\
+        echo "$line" >> /deps/__outer_unit_tests/pyproject.toml; \\
     done
 # -- End of non-package dependency unit_tests --
 # -- Installing all local dependencies --
-RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e /deps/*
 # -- End of local dependencies install --
 ENV LANGGRAPH_UI='{{"agent": "./graphs/agent.ui.jsx"}}'
 ENV LANGGRAPH_UI_CONFIG='{{"shared": ["nuqs"]}}'
-ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}}'
+ENV LANGSERVE_GRAPHS='{{"agent": "/deps/__outer_unit_tests/unit_tests/agent.py:graph"}}'
 # -- Installing JS dependencies --
 ENV NODE_VERSION=20
-RUN cd /deps/outer-unit_tests/unit_tests && npm i && tsx /api/langgraph_api/js/build.mts
+RUN cd /deps/__outer_unit_tests/unit_tests && npm i && tsx /api/langgraph_api/js/build.mts
 # -- End of JS dependencies install --
 {FORMATTED_CLEANUP_LINES}
-WORKDIR /deps/outer-unit_tests/unit_tests"""
+WORKDIR /deps/__outer_unit_tests/unit_tests"""
 
     assert clean_empty_lines(actual_docker_stdin) == expected_docker_stdin
     assert additional_contexts == {}
@@ -843,7 +846,7 @@ def test_config_to_docker_multiplatform():
     expected_docker_stdin = f"""FROM langchain/langgraph-api:3.11
 RUN /storage/install-node.sh
 # -- Adding non-package dependency unit_tests --
-ADD . /deps/outer-unit_tests/unit_tests
+ADD . /deps/__outer_unit_tests/unit_tests
 RUN set -ex && \\
     for line in '[project]' \\
                 'name = "unit_tests"' \\
@@ -853,19 +856,19 @@ RUN set -ex && \\
                 '[build-system]' \\
                 'requires = ["setuptools>=61"]' \\
                 'build-backend = "setuptools.build_meta"'; do \\
-        echo "$line" >> /deps/outer-unit_tests/pyproject.toml; \\
+        echo "$line" >> /deps/__outer_unit_tests/pyproject.toml; \\
     done
 # -- End of non-package dependency unit_tests --
 # -- Installing all local dependencies --
-RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e /deps/*
 # -- End of local dependencies install --
-ENV LANGSERVE_GRAPHS='{{"python": "/deps/outer-unit_tests/unit_tests/multiplatform/python.py:graph", "js": "/deps/outer-unit_tests/unit_tests/multiplatform/js.mts:graph"}}'
+ENV LANGSERVE_GRAPHS='{{"python": "/deps/__outer_unit_tests/unit_tests/multiplatform/python.py:graph", "js": "/deps/__outer_unit_tests/unit_tests/multiplatform/js.mts:graph"}}'
 # -- Installing JS dependencies --
 ENV NODE_VERSION=22
-RUN cd /deps/outer-unit_tests/unit_tests && npm i && tsx /api/langgraph_api/js/build.mts
+RUN cd /deps/__outer_unit_tests/unit_tests && npm i && tsx /api/langgraph_api/js/build.mts
 # -- End of JS dependencies install --
 {FORMATTED_CLEANUP_LINES}
-WORKDIR /deps/outer-unit_tests/unit_tests"""
+WORKDIR /deps/__outer_unit_tests/unit_tests"""
 
     assert clean_empty_lines(actual_docker_stdin) == expected_docker_stdin
     assert additional_contexts == {}
@@ -887,7 +890,7 @@ def test_config_to_docker_pip_installer():
     docker_auto, _ = config_to_docker(
         PATH_TO_CONFIG, config_auto, "langchain/langgraph-api:0.2.47"
     )
-    assert "uv pip install --system --prerelease=allow" in docker_auto
+    assert "uv pip install --system" in docker_auto
     assert "rm /usr/bin/uv /usr/bin/uvx" in docker_auto
 
     # Test explicit pip setting
@@ -895,7 +898,7 @@ def test_config_to_docker_pip_installer():
     docker_pip, _ = config_to_docker(
         PATH_TO_CONFIG, config_pip, "langchain/langgraph-api:0.2.47"
     )
-    assert "uv pip install --system --prerelease=allow" not in docker_pip
+    assert "uv pip install --system" not in docker_pip
     assert "pip install" in docker_pip
     assert "rm /usr/bin/uv" not in docker_pip
 
@@ -904,7 +907,7 @@ def test_config_to_docker_pip_installer():
     docker_uv, _ = config_to_docker(
         PATH_TO_CONFIG, config_uv, "langchain/langgraph-api:0.2.47"
     )
-    assert "uv pip install --system --prerelease=allow" in docker_uv
+    assert "uv pip install --system" in docker_uv
     assert "rm /usr/bin/uv /usr/bin/uvx" in docker_uv
 
     # Test auto behavior with older image (should use pip)
@@ -914,7 +917,7 @@ def test_config_to_docker_pip_installer():
     docker_auto_old, _ = config_to_docker(
         PATH_TO_CONFIG, config_auto_old, "langchain/langgraph-api:0.2.46"
     )
-    assert "uv pip install --system --prerelease=allow" not in docker_auto_old
+    assert "uv pip install --system" not in docker_auto_old
     assert "pip install" in docker_auto_old
     assert "rm /usr/bin/uv" not in docker_auto_old
 
@@ -923,7 +926,7 @@ def test_config_to_docker_pip_installer():
     docker_default, _ = config_to_docker(
         PATH_TO_CONFIG, config_default, "langchain/langgraph-api:0.2.47"
     )
-    assert "uv pip install --system --prerelease=allow" in docker_default
+    assert "uv pip install --system" in docker_default
 
 
 def test_config_retain_build_tools():
@@ -984,7 +987,7 @@ def test_config_to_compose_simple_config():
             dockerfile_inline: |
                 FROM langchain/langgraph-api:3.11
                 # -- Adding non-package dependency unit_tests --
-                ADD . /deps/outer-unit_tests/unit_tests
+                ADD . /deps/__outer_unit_tests/unit_tests
                 RUN set -ex && \\
                     for line in '[project]' \\
                                 'name = "unit_tests"' \\
@@ -994,15 +997,15 @@ def test_config_to_compose_simple_config():
                                 '[build-system]' \\
                                 'requires = ["setuptools>=61"]' \\
                                 'build-backend = "setuptools.build_meta"'; do \\
-                        echo "$line" >> /deps/outer-unit_tests/pyproject.toml; \\
+                        echo "$line" >> /deps/__outer_unit_tests/pyproject.toml; \\
                     done
                 # -- End of non-package dependency unit_tests --
                 # -- Installing all local dependencies --
-                RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+                RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e /deps/*
                 # -- End of local dependencies install --
-                ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}}'
+                ENV LANGSERVE_GRAPHS='{{"agent": "/deps/__outer_unit_tests/unit_tests/agent.py:graph"}}'
 {textwrap.indent(textwrap.dedent(FORMATTED_CLEANUP_LINES), "                ")}
-                WORKDIR /deps/outer-unit_tests/unit_tests
+                WORKDIR /deps/__outer_unit_tests/unit_tests
         """
     actual_compose_stdin = config_to_compose(
         PATH_TO_CONFIG,
@@ -1025,7 +1028,7 @@ def test_config_to_compose_env_vars():
             dockerfile_inline: |
                 FROM langchain/langgraph-api-custom:3.11
                 # -- Adding non-package dependency unit_tests --
-                ADD . /deps/outer-unit_tests/unit_tests
+                ADD . /deps/__outer_unit_tests/unit_tests
                 RUN set -ex && \\
                     for line in '[project]' \\
                                 'name = "unit_tests"' \\
@@ -1035,15 +1038,15 @@ def test_config_to_compose_env_vars():
                                 '[build-system]' \\
                                 'requires = ["setuptools>=61"]' \\
                                 'build-backend = "setuptools.build_meta"'; do \\
-                        echo "$line" >> /deps/outer-unit_tests/pyproject.toml; \\
+                        echo "$line" >> /deps/__outer_unit_tests/pyproject.toml; \\
                     done
                 # -- End of non-package dependency unit_tests --
                 # -- Installing all local dependencies --
-                RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+                RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e /deps/*
                 # -- End of local dependencies install --
-                ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}}'
+                ENV LANGSERVE_GRAPHS='{{"agent": "/deps/__outer_unit_tests/unit_tests/agent.py:graph"}}'
 {textwrap.indent(textwrap.dedent(FORMATTED_CLEANUP_LINES), "                ")}
-                WORKDIR /deps/outer-unit_tests/unit_tests
+                WORKDIR /deps/__outer_unit_tests/unit_tests
         """
     openai_api_key = "key"
     actual_compose_stdin = config_to_compose(
@@ -1070,7 +1073,7 @@ def test_config_to_compose_env_file():
             dockerfile_inline: |
                 FROM langchain/langgraph-api:3.11
                 # -- Adding non-package dependency unit_tests --
-                ADD . /deps/outer-unit_tests/unit_tests
+                ADD . /deps/__outer_unit_tests/unit_tests
                 RUN set -ex && \\
                     for line in '[project]' \\
                                 'name = "unit_tests"' \\
@@ -1080,15 +1083,15 @@ def test_config_to_compose_env_file():
                                 '[build-system]' \\
                                 'requires = ["setuptools>=61"]' \\
                                 'build-backend = "setuptools.build_meta"'; do \\
-                        echo "$line" >> /deps/outer-unit_tests/pyproject.toml; \\
+                        echo "$line" >> /deps/__outer_unit_tests/pyproject.toml; \\
                     done
                 # -- End of non-package dependency unit_tests --
                 # -- Installing all local dependencies --
-                RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+                RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e /deps/*
                 # -- End of local dependencies install --
-                ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}}'
+                ENV LANGSERVE_GRAPHS='{{"agent": "/deps/__outer_unit_tests/unit_tests/agent.py:graph"}}'
 {textwrap.indent(textwrap.dedent(FORMATTED_CLEANUP_LINES), "                ")}
-                WORKDIR /deps/outer-unit_tests/unit_tests
+                WORKDIR /deps/__outer_unit_tests/unit_tests
         """
     actual_compose_stdin = config_to_compose(
         PATH_TO_CONFIG,
@@ -1108,7 +1111,7 @@ def test_config_to_compose_watch():
             dockerfile_inline: |
                 FROM langchain/langgraph-api:3.11
                 # -- Adding non-package dependency unit_tests --
-                ADD . /deps/outer-unit_tests/unit_tests
+                ADD . /deps/__outer_unit_tests/unit_tests
                 RUN set -ex && \\
                     for line in '[project]' \\
                                 'name = "unit_tests"' \\
@@ -1118,15 +1121,15 @@ def test_config_to_compose_watch():
                                 '[build-system]' \\
                                 'requires = ["setuptools>=61"]' \\
                                 'build-backend = "setuptools.build_meta"'; do \\
-                        echo "$line" >> /deps/outer-unit_tests/pyproject.toml; \\
+                        echo "$line" >> /deps/__outer_unit_tests/pyproject.toml; \\
                     done
                 # -- End of non-package dependency unit_tests --
                 # -- Installing all local dependencies --
-                RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+                RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e /deps/*
                 # -- End of local dependencies install --
-                ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}}'
+                ENV LANGSERVE_GRAPHS='{{"agent": "/deps/__outer_unit_tests/unit_tests/agent.py:graph"}}'
 {textwrap.indent(textwrap.dedent(FORMATTED_CLEANUP_LINES), "                ")}
-                WORKDIR /deps/outer-unit_tests/unit_tests
+                WORKDIR /deps/__outer_unit_tests/unit_tests
         
         develop:
             watch:
@@ -1155,7 +1158,7 @@ def test_config_to_compose_end_to_end():
             dockerfile_inline: |
                 FROM langchain/langgraph-api:3.11
                 # -- Adding non-package dependency unit_tests --
-                ADD . /deps/outer-unit_tests/unit_tests
+                ADD . /deps/__outer_unit_tests/unit_tests
                 RUN set -ex && \\
                     for line in '[project]' \\
                                 'name = "unit_tests"' \\
@@ -1165,15 +1168,15 @@ def test_config_to_compose_end_to_end():
                                 '[build-system]' \\
                                 'requires = ["setuptools>=61"]' \\
                                 'build-backend = "setuptools.build_meta"'; do \\
-                        echo "$line" >> /deps/outer-unit_tests/pyproject.toml; \\
+                        echo "$line" >> /deps/__outer_unit_tests/pyproject.toml; \\
                     done
                 # -- End of non-package dependency unit_tests --
                 # -- Installing all local dependencies --
-                RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --prerelease=allow --no-cache-dir -c /api/constraints.txt -e /deps/*
+                RUN PYTHONDONTWRITEBYTECODE=1 uv pip install --system --no-cache-dir -c /api/constraints.txt -e /deps/*
                 # -- End of local dependencies install --
-                ENV LANGSERVE_GRAPHS='{{"agent": "/deps/outer-unit_tests/unit_tests/agent.py:graph"}}'
+                ENV LANGSERVE_GRAPHS='{{"agent": "/deps/__outer_unit_tests/unit_tests/agent.py:graph"}}'
 {textwrap.indent(textwrap.dedent(FORMATTED_CLEANUP_LINES), "                ")}
-                WORKDIR /deps/outer-unit_tests/unit_tests
+                WORKDIR /deps/__outer_unit_tests/unit_tests
         
         develop:
             watch:
@@ -1336,22 +1339,19 @@ def test_docker_tag_different_node_versions_with_distro():
         assert tag == expected_tag, f"Failed for Node.js {node_version}"
 
 
-@pytest.mark.parametrize("in_config", [False, True])
-def test_docker_tag_with_api_version(in_config: bool):
+def test_docker_tag_with_api_version():
     """Test docker_tag function with api_version parameter."""
 
     # Test 1: Python config with api_version and default distro
-    version = "0.2.74"
     config = validate_config(
         {
             "python_version": "3.11",
             "dependencies": ["."],
             "graphs": {"agent": "./agent.py:graph"},
-            "api_version": version if in_config else None,
         }
     )
-    tag = docker_tag(config, api_version=version if not in_config else None)
-    assert tag == f"langchain/langgraph-api:{version}-py3.11"
+    tag = docker_tag(config, api_version="0.2.74")
+    assert tag == "langchain/langgraph-api:0.2.74-py3.11"
 
     # Test 2: Python config with api_version and wolfi distro
     config = validate_config(
@@ -1360,22 +1360,20 @@ def test_docker_tag_with_api_version(in_config: bool):
             "dependencies": ["."],
             "graphs": {"agent": "./agent.py:graph"},
             "image_distro": "wolfi",
-            "api_version": version if in_config else None,
         }
     )
-    tag = docker_tag(config, api_version=version if not in_config else None)
-    assert tag == f"langchain/langgraph-api:{version}-py3.12-wolfi"
+    tag = docker_tag(config, api_version="0.2.74")
+    assert tag == "langchain/langgraph-api:0.2.74-py3.12-wolfi"
 
     # Test 3: Node.js config with api_version and default distro
     config = validate_config(
         {
             "node_version": "20",
             "graphs": {"agent": "./agent.js:graph"},
-            "api_version": version if in_config else None,
         }
     )
-    tag = docker_tag(config, api_version=version if not in_config else None)
-    assert tag == f"langchain/langgraphjs-api:{version}-node20"
+    tag = docker_tag(config, api_version="0.2.74")
+    assert tag == "langchain/langgraphjs-api:0.2.74-node20"
 
     # Test 4: Node.js config with api_version and wolfi distro
     config = validate_config(
@@ -1383,11 +1381,10 @@ def test_docker_tag_with_api_version(in_config: bool):
             "node_version": "20",
             "graphs": {"agent": "./agent.js:graph"},
             "image_distro": "wolfi",
-            "api_version": version if in_config else None,
         }
     )
-    tag = docker_tag(config, api_version=version if not in_config else None)
-    assert tag == f"langchain/langgraphjs-api:{version}-node20-wolfi"
+    tag = docker_tag(config, api_version="0.2.74")
+    assert tag == "langchain/langgraphjs-api:0.2.74-node20-wolfi"
 
     # Test 5: Custom base image with api_version
     config = validate_config(
@@ -1396,15 +1393,10 @@ def test_docker_tag_with_api_version(in_config: bool):
             "dependencies": ["."],
             "graphs": {"agent": "./agent.py:graph"},
             "base_image": "my-registry/custom-image",
-            "api_version": version if in_config else None,
         }
     )
-    tag = docker_tag(
-        config,
-        base_image="my-registry/custom-image",
-        api_version=version if not in_config else None,
-    )
-    assert tag == f"my-registry/custom-image:{version}-py3.11"
+    tag = docker_tag(config, base_image="my-registry/custom-image", api_version="1.0.0")
+    assert tag == "my-registry/custom-image:1.0.0-py3.11"
 
     # Test 6: api_version with different Python versions
     for python_version in ["3.11", "3.12", "3.13"]:
@@ -1413,11 +1405,10 @@ def test_docker_tag_with_api_version(in_config: bool):
                 "python_version": python_version,
                 "dependencies": ["."],
                 "graphs": {"agent": "./agent.py:graph"},
-                "api_version": version if in_config else None,
             }
         )
-        tag = docker_tag(config, api_version=version if not in_config else None)
-        assert tag == f"langchain/langgraph-api:{version}-py{python_version}"
+        tag = docker_tag(config, api_version="0.2.74")
+        assert tag == f"langchain/langgraph-api:0.2.74-py{python_version}"
 
     # Test 7: Without api_version should work as before
     config = validate_config(
@@ -1437,11 +1428,10 @@ def test_docker_tag_with_api_version(in_config: bool):
             "node_version": "20",
             "dependencies": ["."],
             "graphs": {"python": "./agent.py:graph", "js": "./agent.js:graph"},
-            "api_version": version if in_config else None,
         }
     )
-    tag = docker_tag(config, api_version=version if not in_config else None)
-    assert tag == f"langchain/langgraph-api:{version}-py3.11"
+    tag = docker_tag(config, api_version="0.2.74")
+    assert tag == "langchain/langgraph-api:0.2.74-py3.11"
 
     # Test 9: api_version with _INTERNAL_docker_tag should ignore api_version
     config = validate_config(
@@ -1461,15 +1451,12 @@ def test_docker_tag_with_api_version(in_config: bool):
             "python_version": "3.11",
             "dependencies": ["."],
             "graphs": {"agent": "./agent.py:graph"},
-            "api_version": version if in_config else None,
         }
     )
     tag = docker_tag(
-        config,
-        base_image="langchain/langgraph-server",
-        api_version=version if not in_config else None,
+        config, base_image="langchain/langgraph-server:0.2", api_version="0.2.74"
     )
-    assert tag == f"langchain/langgraph-server:{version}-py3.11"
+    assert tag == "langchain/langgraph-server:0.2-py3.11"
 
 
 def test_config_to_docker_with_api_version():

libs/cli/uv.lock

@@ -18,16 +18,16 @@ wheels = [
 
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+version = "4.9.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
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     { name = "sniffio", marker = "python_full_version >= '3.11'" },
     { name = "typing-extensions", marker = "python_full_version >= '3.11' and python_full_version < '3.13'" },
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 [[package]]
@@ -53,11 +53,11 @@ wheels = [
 
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+version = "2025.7.14"
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 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/4f/52/34c6cf5bb9285074dc3531c437b3919e825d976fde097a7a73f79e726d03/certifi-2025.7.14-py3-none-any.whl", hash = "sha256:6b31f564a415d79ee77df69d757bb49a5bb53bd9f756cbbe24394ffd6fc1f4b2", size = 162722, upload-time = "2025-07-14T03:29:26.863Z" },
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 [[package]]
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+version = "3.4.2"
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libs/langgraph/.claude/settings.local.json

@@ -5,9 +5,7 @@
       "Bash(python:*)",
       "Bash(grep:*)",
       "Bash(sed:*)",
-      "Bash(awk:*)",
-      "Bash(uv run mypy:*)",
-      "Bash(uv run:*)"
+      "Bash(awk:*)"
     ],
     "deny": []
   }

libs/langgraph/bench/react_agent.py

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

libs/langgraph/channel_versions_explained.md

@@ -1,279 +0,0 @@
-# Understanding `channel_versions` for State Channels in LangGraph
-
-## Overview
-
-While `versions_seen` only tracks trigger channels, `channel_versions` tracks **ALL channels** including state channels like `fieldA` and `fieldB`. This document explains why state channel versions matter.
-
-## The Two Version Tracking Mechanisms
-
-| Mechanism | What it tracks | Purpose |
-|-----------|---------------|---------|
-| `channel_versions` | **All channels** (state + triggers) | Storage, recovery, change tracking |
-| `versions_seen` | **Only triggers** | Scheduling, prevent duplicate execution |
-
----
-
-## Why Track State Channel Versions?
-
-### Purpose 1: Incremental Storage
-
-When saving a checkpoint, LangGraph only serializes channels that have **changed** since the last checkpoint.
-
-```python
-# In checkpointer.put()
-def put(self, config, checkpoint, metadata, new_versions):
-    for k, v in new_versions.items():  # Only changed channels!
-        self.blobs[(thread_id, ns, k, v)] = serialize(values[k])
-```
-
-The `new_versions` parameter is computed by comparing current versions with previous versions:
-
-```python
-def get_new_channel_versions(previous_versions, current_versions):
-    """Get subset of current_versions that are newer than previous_versions."""
-    return {
-        k: v
-        for k, v in current_versions.items()
-        if v > previous_versions.get(k, null_version)
-    }
-```
-
-**Benefit**: If `fieldA` didn't change in a step, it won't be re-serialized!
-
-### Purpose 2: Version-Keyed Storage
-
-Channel values are stored with their version as part of the key:
-
-```python
-# Storage structure in InMemorySaver
-blobs = {
-    (thread_id, ns, "fieldA", v02): b"Hello",         # Step 0
-    (thread_id, ns, "fieldA", v03): b"Hello->A",      # Step 1  
-    (thread_id, ns, "fieldA", v04): b"Hello->A->B",   # Step 2
-    (thread_id, ns, "fieldB", v02): b"World",         # Step 0
-    (thread_id, ns, "fieldB", v03): b"World->A",      # Step 1
-    ...
-}
-```
-
-**Benefit**: Can restore to ANY historical checkpoint - each version's value is stored independently.
-
-### Purpose 3: Precise Recovery
-
-When restoring a checkpoint, use `channel_versions` to load the correct value:
-
-```python
-# Restoring Step 1's checkpoint
-checkpoint["channel_versions"] = {"fieldA": v03, "fieldB": v03}
-
-# Load correct version of each value
-fieldA = blobs[(thread_id, ns, "fieldA", v03)]  # "Hello->A"
-fieldB = blobs[(thread_id, ns, "fieldB", v03)]  # "World->A"
-```
-
----
-
-## Example: Step-by-Step Channel Version Changes
-
-Using the same graph:
-
-```
-        ┌──────────┐
-        │  nodeA   │  (reads fieldA + fieldB)
-        └────┬─────┘
-             │
-      ┌──────┴──────┐
-      ▼             ▼
-┌──────────┐  ┌──────────┐
-│  nodeB   │  │  nodeC   │  (nodeB reads fieldA, nodeC reads fieldB)
-└────┬─────┘  └────┬─────┘
-      │             │
-      └──────┬──────┘
-             ▼
-        ┌──────────┐
-        │  nodeD   │  (reads fieldA + fieldB)
-        └──────────┘
-```
-
-### Step -1: Input
-
-```
-channel_versions:
-    __start__: v01
-
-channel_values:
-    __start__: {'fieldA': 'Hello', 'fieldB': 'World'}
-
-new_versions (to save): {__start__: v01}
-  → Only __start__ is saved
-```
-
-### Step 0: `__start__` executes
-
-```
-channel_versions:
-    __start__:        v02
-    branch:to:nodeA:  v02
-    fieldA:           v02  ← NEW!
-    fieldB:           v02  ← NEW!
-
-channel_values:
-    branch:to:nodeA: None
-    fieldA: Hello
-    fieldB: World
-
-new_versions (to save): {__start__: v02, branch:to:nodeA: v02, fieldA: v02, fieldB: v02}
-  → All changed channels are saved
-```
-
-### Step 1: nodeA executes
-
-```
-channel_versions:
-    __start__:        v02  ← unchanged
-    branch:to:nodeA:  v03  ← updated (consumed)
-    branch:to:nodeB:  v03  ← NEW!
-    branch:to:nodeC:  v03  ← NEW!
-    fieldA:           v03  ← updated!
-    fieldB:           v03  ← updated!
-
-channel_values:
-    branch:to:nodeB: None
-    branch:to:nodeC: None
-    fieldA: Hello->A
-    fieldB: World->A
-
-new_versions (to save): {branch:to:nodeA: v03, branch:to:nodeB: v03, branch:to:nodeC: v03, fieldA: v03, fieldB: v03}
-  → __start__ NOT saved (unchanged at v02)
-```
-
-### Step 2: nodeB and nodeC execute (parallel)
-
-```
-channel_versions:
-    __start__:              v02  ← unchanged
-    branch:to:nodeA:        v03  ← unchanged
-    branch:to:nodeB:        v04  ← updated (consumed)
-    branch:to:nodeC:        v04  ← updated (consumed)
-    fieldA:                 v04  ← updated by nodeB!
-    fieldB:                 v04  ← updated by nodeC!
-    join:nodeB+nodeC:nodeD: v04  ← NEW!
-
-channel_values:
-    fieldA: Hello->A->B
-    fieldB: World->A->C
-    join:nodeB+nodeC:nodeD: {'nodeB', 'nodeC'}
-
-new_versions (to save): {branch:to:nodeB: v04, branch:to:nodeC: v04, fieldA: v04, fieldB: v04, join:...: v04}
-  → Only changed channels saved
-```
-
-### Step 3: nodeD executes
-
-```
-channel_versions:
-    __start__:              v02  ← unchanged since Step 0!
-    branch:to:nodeA:        v03  ← unchanged since Step 1
-    branch:to:nodeB:        v04  ← unchanged
-    branch:to:nodeC:        v04  ← unchanged
-    fieldA:                 v05  ← updated by nodeD!
-    fieldB:                 v05  ← updated by nodeD!
-    join:nodeB+nodeC:nodeD: v05  ← updated (consumed)
-
-channel_values:
-    fieldA: Hello->A->B->D
-    fieldB: World->A->C->D
-    join:nodeB+nodeC:nodeD: set()
-
-new_versions (to save): {fieldA: v05, fieldB: v05, join:...: v05}
-  → Only 3 channels saved, not all 7!
-```
-
----
-
-## Storage Efficiency Visualization
-
-```
-Step 0:  Save [__start__, branch:to:nodeA, fieldA, fieldB]     = 4 channels
-Step 1:  Save [branch:to:nodeA, branch:to:nodeB, branch:to:nodeC, fieldA, fieldB] = 5 channels
-Step 2:  Save [branch:to:nodeB, branch:to:nodeC, fieldA, fieldB, join:...] = 5 channels
-Step 3:  Save [fieldA, fieldB, join:...]                       = 3 channels
-
-Without incremental storage: 7 channels × 4 steps = 28 serializations
-With incremental storage:    4 + 5 + 5 + 3        = 17 serializations
-                                                    = 39% savings!
-```
-
----
-
-## Time Travel: Restoring Any Checkpoint
-
-Because each version is stored separately, you can restore to any point:
-
-```
-Want to restore Step 1?
-  → checkpoint["channel_versions"] = {fieldA: v03, fieldB: v03, ...}
-  → Load blobs[(thread_id, ns, "fieldA", v03)] = "Hello->A"
-  → Load blobs[(thread_id, ns, "fieldB", v03)] = "World->A"
-
-Want to restore Step 2?
-  → checkpoint["channel_versions"] = {fieldA: v04, fieldB: v04, ...}
-  → Load blobs[(thread_id, ns, "fieldA", v04)] = "Hello->A->B"
-  → Load blobs[(thread_id, ns, "fieldB", v04)] = "World->A->C"
-```
-
----
-
-## Summary: State Channel Versions vs Trigger Channel Versions
-
-| Aspect | State Channels (fieldA, fieldB) | Trigger Channels (branch:to:*) |
-|--------|--------------------------------|-------------------------------|
-| In `channel_versions`? | ✅ Yes | ✅ Yes |
-| In `versions_seen`? | ❌ No | ✅ Yes |
-| Version increases when? | Value is updated | Written to OR consumed |
-| Used for scheduling? | ❌ No | ✅ Yes |
-| Used for storage? | ✅ Yes (incremental save) | ✅ Yes |
-| Used for recovery? | ✅ Yes (load correct version) | ✅ Yes |
-
----
-
-## Code Reference
-
-### Where `channel_versions` is updated
-
-```python
-# In apply_writes() - libs/langgraph/langgraph/pregel/_algo.py
-for chan, vals in pending_writes_by_channel.items():
-    if channels[chan].update(vals) and next_version is not None:
-        checkpoint["channel_versions"][chan] = next_version  # ← Update version
-        updated_channels.add(chan)
-```
-
-### Where incremental storage happens
-
-```python
-# In InMemorySaver.put() - libs/checkpoint/langgraph/checkpoint/memory/__init__.py
-def put(self, config, checkpoint, metadata, new_versions):
-    values = checkpoint.pop("channel_values")
-    for k, v in new_versions.items():  # ← Only save changed channels
-        self.blobs[(thread_id, checkpoint_ns, k, v)] = (
-            self.serde.dumps_typed(values[k]) if k in values else ("empty", b"")
-        )
-```
-
----
-
-## Running the Test
-
-To see channel versions in action:
-
-```bash
-cd libs/langgraph
-uv run python test_versions_seen.py
-```
-
-The output shows `channel_versions` for each step, where you can observe:
-1. All channels (state + triggers) are tracked
-2. Versions increment when values change
-3. Some channels stay at the same version across multiple steps (unchanged)
-

libs/langgraph/langgraph/graph/state.py

@@ -25,7 +25,7 @@ from typing import (
 
 from langchain_core.runnables import Runnable, RunnableConfig
 from pydantic import BaseModel, TypeAdapter
-from typing_extensions import NotRequired, Required, Self, Unpack, is_typeddict
+from typing_extensions import Self, Unpack, is_typeddict
 
 from langgraph._internal._constants import (
     INTERRUPT,
@@ -1334,12 +1334,6 @@ def _get_channel(
 def _get_channel(
     name: str, annotation: Any, *, allow_managed: bool = True
 ) -> BaseChannel | ManagedValueSpec:
-    # Strip out Required and NotRequired wrappers
-    if hasattr(annotation, "__origin__") and annotation.__origin__ in (
-        Required,
-        NotRequired,
-    ):
-        annotation = annotation.__args__[0]
     if manager := _is_field_managed_value(name, annotation):
         if allow_managed:
             return manager

libs/langgraph/langgraph/pregel/_algo.py

@@ -194,12 +194,15 @@ def local_read(
         for c, v in task.writes:
             if c in select:
                 updated[c].append(v)
-    if fresh:
+    if fresh and updated:
         # apply writes
         local_channels: dict[str, BaseChannel] = {}
         for k in channels:
-            cc = channels[k].copy()
-            cc.update(updated[k])
+            if k in updated:
+                cc = channels[k].copy()
+                cc.update(updated[k])
+            else:
+                cc = channels[k]
             local_channels[k] = cc
         # read fresh values
         values = read_channels(local_channels, select)

libs/langgraph/langgraph/pregel/remote.py

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

libs/langgraph/langgraph/types.py

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

libs/langgraph/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph"
-version = "0.6.7"
+version = "0.6.4"
 description = "Building stateful, multi-actor applications with LLMs"
 authors = []
 requires-python = ">=3.9"
@@ -14,7 +14,7 @@ license-files = ['LICENSE']
 dependencies = [
     "langchain-core>=0.1",
     "langgraph-checkpoint>=2.1.0,<3.0.0",
-    "langgraph-sdk>=0.2.2,<0.3.0",
+    "langgraph-sdk>=0.2.0,<0.3.0",
     "langgraph-prebuilt>=0.6.0,<0.7.0",
     "xxhash>=3.5.0",
     "pydantic>=2.7.4",

libs/langgraph/test_versions_seen.py

@@ -1,169 +0,0 @@
-"""
-Test script to demonstrate versions_seen in StateGraph
-
-Graph structure:
-    nodeA -> nodeB + nodeC -> nodeD
-
-State:
-    fieldA: str
-    fieldB: str
-"""
-
-from typing import TypedDict
-from langgraph.graph import StateGraph, START, END
-from langgraph.checkpoint.memory import InMemorySaver
-from pprint import pprint
-import json
-
-
-class State(TypedDict):
-    fieldA: str
-    fieldB: str
-
-
-class StateOnlyA(TypedDict):
-    """Input schema for nodeB - only reads fieldA"""
-    fieldA: str
-
-
-class StateOnlyB(TypedDict):
-    """Input schema for nodeC - only reads fieldB"""
-    fieldB: str
-
-
-def nodeA(state: State) -> dict:
-    """Reads fieldA + fieldB"""
-    print(f"  [nodeA] Reading: fieldA='{state['fieldA']}', fieldB='{state['fieldB']}'")
-    return {"fieldA": state["fieldA"] + "->A", "fieldB": state["fieldB"] + "->A"}
-
-
-def nodeB(state: StateOnlyA) -> dict:
-    """Reads only fieldA"""
-    print(f"  [nodeB] Reading: fieldA='{state['fieldA']}'")
-    return {"fieldA": state["fieldA"] + "->B"}
-
-
-def nodeC(state: StateOnlyB) -> dict:
-    """Reads only fieldB"""
-    print(f"  [nodeC] Reading: fieldB='{state['fieldB']}'")
-    return {"fieldB": state["fieldB"] + "->C"}
-
-
-def nodeD(state: State) -> dict:
-    """Reads fieldA + fieldB"""
-    print(f"  [nodeD] Reading: fieldA='{state['fieldA']}', fieldB='{state['fieldB']}'")
-    return {"fieldA": state["fieldA"] + "->D", "fieldB": state["fieldB"] + "->D"}
-
-
-# Build the graph
-graph = StateGraph(State)
-
-graph.add_node("nodeA", nodeA)  # reads fieldA + fieldB (default: full state)
-graph.add_node("nodeB", nodeB, input_schema=StateOnlyA)  # reads only fieldA
-graph.add_node("nodeC", nodeC, input_schema=StateOnlyB)  # reads only fieldB
-graph.add_node("nodeD", nodeD)  # reads fieldA + fieldB (default: full state)
-
-graph.add_edge(START, "nodeA")
-graph.add_edge("nodeA", "nodeB")
-graph.add_edge("nodeA", "nodeC")
-graph.add_edge(["nodeB", "nodeC"], "nodeD")
-graph.add_edge("nodeD", END)
-
-# Compile with checkpointer
-checkpointer = InMemorySaver()
-app = graph.compile(checkpointer=checkpointer)
-
-# Print compiled graph info
-print("=" * 60)
-print("COMPILED GRAPH INFO")
-print("=" * 60)
-print("\nChannels created:")
-for name, channel in app.channels.items():
-    print(f"  - {name}: {type(channel).__name__}")
-
-print("\nNodes with their triggers and channels:")
-for name, node in app.nodes.items():
-    print(f"  - {name}:")
-    print(f"      triggers: {node.triggers}")
-    print(f"      channels: {node.channels}")
-
-# Run the graph
-print("\n" + "=" * 60)
-print("EXECUTION")
-print("=" * 60)
-
-config = {"configurable": {"thread_id": "test-1"}}
-input_state = {"fieldA": "Hello", "fieldB": "World"}
-
-print(f"\nInput: {input_state}\n")
-
-# Run the graph to completion
-result = app.invoke(input_state, config)
-print(f"Final result: {result}\n")
-
-# Now use get_state_history to get all checkpoints in order
-print("=" * 60)
-print("CHECKPOINT HISTORY (using get_state_history)")
-print("=" * 60)
-
-# get_state_history returns checkpoints in reverse order (newest first)
-history = list(app.get_state_history(config))
-history.reverse()  # Reverse to get oldest first
-
-for idx, state_snapshot in enumerate(history):
-    metadata = state_snapshot.metadata
-    
-    print(f"\n{'='*60}")
-    print(f"Step {metadata.get('step', '?')} - Source: {metadata.get('source', '?')}")
-    print(f"{'='*60}")
-    
-    # Show which node(s) wrote this checkpoint
-    if "writes" in metadata and metadata["writes"]:
-        print(f"Writes by: {list(metadata['writes'].keys())}")
-    
-    print(f"\nState values: {state_snapshot.values}")
-    
-    # Access the actual checkpoint data
-    checkpoint_tuple = checkpointer.get_tuple(state_snapshot.config)
-    if checkpoint_tuple:
-        cp = checkpoint_tuple.checkpoint
-        
-        # Helper to simplify version string
-        def simplify_version(ver):
-            return str(ver).split(".")[0][-2:] if "." in str(ver) else str(ver)
-        
-        # Pretty print checkpoint with simplified versions
-        print("\nCheckpoint (raw):")
-        print(f"  v: {cp['v']}")
-        print(f"  id: {cp['id'][:20]}...")
-        print(f"  ts: {cp['ts']}")
-        print(f"  updated_channels: {cp.get('updated_channels')}")
-        
-        print(f"\n  channel_values:")
-        for ch, val in sorted(cp["channel_values"].items()):
-            val_str = str(val)[:50] + "..." if len(str(val)) > 50 else str(val)
-            print(f"    {ch}: {val_str}")
-        
-        print(f"\n  channel_versions:")
-        for ch, ver in sorted(cp["channel_versions"].items()):
-            print(f"    {ch}: v{simplify_version(ver)}")
-        
-        print(f"\n  versions_seen:")
-        for node_name, seen in sorted(cp["versions_seen"].items()):
-            if seen:
-                print(f"    {node_name}:")
-                for ch, ver in sorted(seen.items()):
-                    print(f"        {ch}: v{simplify_version(ver)}")
-            else:
-                print(f"    {node_name}: {{}}")
-
-print("\n" + "=" * 60)
-print("SUMMARY")
-print("=" * 60)
-print("""
-Key observations:
-1. versions_seen only records TRIGGER channels (branch:to:*, join:*)
-2. State channels (fieldA, fieldB) are NEVER in versions_seen
-3. Each node only records the trigger channel that activated it
-""")
-

libs/langgraph/tests/conftest.py

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

libs/langgraph/tests/test_pregel.py

@@ -79,151 +79,9 @@ from tests.messages import (
 
 pytestmark = pytest.mark.anyio
 
-
-def pregel_pretty(data):
-    """Pretty print pregel nodes, channels, or graph with nice formatting."""
-    if not data:
-        return "Empty"
-    
-    # Check if this is a graph object
-    if hasattr(data, 'nodes') and hasattr(data, 'channels'):
-        # This is a graph object, show comprehensive info
-        result = []
-        
-        # Show nodes
-        result.append("="*50)
-        result.append("🔗 GRAPH NODES")
-        result.append("="*50)
-        for name, node in data.nodes.items():
-            node_type = type(node).__name__
-            result.append(f"  📍 {name:<12} → {node_type}")
-        
-        # Show channels
-        result.append("\n" + "="*50)
-        result.append("📡 GRAPH CHANNELS")
-        result.append("="*50)
-        for name, channel in data.channels.items():
-            channel_type = type(channel).__name__
-            if name in ['hello', 'messages']:
-                result.append(f"  🎯 {name:<20} → {channel_type} (user defined)")
-            elif name.startswith('branch:'):
-                result.append(f"  🌿 {name:<20} → {channel_type} (branch)")
-            else:
-                result.append(f"  ⚙️  {name:<20} → {channel_type} (system)")
-        
-        # Show graph structure
-        result.append("\n" + "="*50)
-        result.append("🏗️  GRAPH STRUCTURE")
-        result.append("="*50)
-        try:
-            graph_info = data.get_graph()
-            result.append(f"  Nodes: {len(graph_info.nodes)}")
-            result.append(f"  Edges: {len(graph_info.edges)}")
-            result.append("\n  📊 Execution Flow:")
-            for edge in graph_info.edges:
-                arrow = "  ├─" if edge != graph_info.edges[-1] else "  └─"
-                result.append(f"{arrow} {edge.source} → {edge.target}")
-        except Exception as e:
-            result.append(f"  Could not get graph structure: {e}")
-        
-        result.append("="*50)
-        return "\n".join(result)
-    
-    # Check if this is nodes or channels dict
-    first_key, first_value = next(iter(data.items()))
-    
-    # Detect if this is nodes or channels
-    is_nodes = hasattr(first_value, '__class__') and 'Node' in first_value.__class__.__name__
-    is_channels = hasattr(first_value, '__class__') and ('Channel' in first_value.__class__.__name__ or 
-                                                         'Value' in first_value.__class__.__name__ or
-                                                         'Topic' in first_value.__class__.__name__ or
-                                                         'Aggregate' in first_value.__class__.__name__)
-    
-    result = []
-    
-    if is_nodes:
-        result.append("="*50)
-        result.append("🔗 GRAPH NODES")
-        result.append("="*50)
-        for name, node in data.items():
-            node_type = type(node).__name__
-            result.append(f"  📍 {name:<12} → {node_type}")
-    
-    elif is_channels:
-        result.append("="*50)
-        result.append("📡 GRAPH CHANNELS")
-        result.append("="*50)
-        for name, channel in data.items():
-            channel_type = type(channel).__name__
-            if name in ['hello', 'messages']:
-                result.append(f"  🎯 {name:<20} → {channel_type} (user defined)")
-            elif name.startswith('branch:'):
-                result.append(f"  🌿 {name:<20} → {channel_type} (branch)")
-            else:
-                result.append(f"  ⚙️  {name:<20} → {channel_type} (system)")
-    
-    else:
-        # Fallback for unknown data types
-        result.append("="*50)
-        result.append("🔍 UNKNOWN DATA TYPE")
-        result.append("="*50)
-        for name, item in data.items():
-            item_type = type(item).__name__
-            result.append(f"  ❓ {name:<20} → {item_type}")
-    
-    result.append("="*50)
-    return "\n".join(result)
-
 logger = logging.getLogger(__name__)
 
 
-def test_parallel_nodes() -> None:
-    class State(TypedDict):
-        hello: str
-        messages: Annotated[list[str], add_messages]
-
-    def node_a(state: State) -> State:
-        return {"hello": "world-a", "messages": [_AnyIdHumanMessage(content="hello-a")]}
-
-    def node_b(state: State) -> State:
-        return {"messages": [_AnyIdHumanMessage(content="hello-b")]}
-
-    def node_c(state: State) -> State:
-        return {"messages": [_AnyIdHumanMessage(content="hello-c")]}    
-
-    def node_d(state: State) -> State:
-        return {"hello": "world-d", "messages": [_AnyIdHumanMessage(content="hello-d")]}    
-
-    builder = StateGraph(State)
-    builder.add_node("a", node_a)
-    builder.add_node("b", node_b)
-    builder.add_node("c", node_c)
-    builder.add_node("d", node_d)
-
-    builder.set_entry_point("a")
-    builder.add_edge("a", "b")
-    builder.add_edge("a", "c")
-    builder.add_edge("b", "d")
-    builder.add_edge("c", "d")
-    builder.add_edge("d", END)
-    graph = builder.compile()
-
-    print("\n======COMPLETE GRAPH======\n", pregel_pretty(graph))
-    
-    print(f"\n🔍 CHANNEL CONFIGURATION:")
-    print(f"  📤 output_channels: {graph.output_channels}")
-    print(f"  📡 stream_channels: {graph.stream_channels}")
-    print(f"  📥 input_channels: {graph.input_channels}")
-    print(f"  🌊 stream_channels_asis: {graph.stream_channels_asis}")
-    print(f"  📋 stream_channels_list: {graph.stream_channels_list}")
-
-    result = graph.invoke({"hello": "there"})
-    assert result["hello"] == "world-d"
-    # Only the final message from node_d should be in the result
-    # because each node overwrites the messages field completely
-    assert len(result["messages"]) == 1
-    assert result["messages"][0].content == "hello-d"
-
 def test_graph_validation() -> None:
     class State(TypedDict):
         hello: str
@@ -4947,10 +4805,7 @@ def test_interrupt_subgraph(sync_checkpointer: BaseCheckpointSaver):
     assert graph.invoke(Command(resume="bar"), thread1)
 
 
-@pytest.mark.parametrize("resume_style", ["null", "map"])
-def test_interrupt_multiple(
-    sync_checkpointer: BaseCheckpointSaver, resume_style: Literal["null", "map"]
-):
+def test_interrupt_multiple(sync_checkpointer: BaseCheckpointSaver):
     class State(TypedDict):
         my_key: Annotated[str, operator.add]
 
@@ -4966,8 +4821,7 @@ def test_interrupt_multiple(
     graph = builder.compile(checkpointer=sync_checkpointer)
     thread1 = {"configurable": {"thread_id": "1"}}
 
-    result = [e for e in graph.stream({"my_key": "DE", "market": "DE"}, thread1)]
-    assert result == [
+    assert [e for e in graph.stream({"my_key": "DE", "market": "DE"}, thread1)] == [
         {
             "__interrupt__": (
                 Interrupt(
@@ -4978,19 +4832,12 @@ def test_interrupt_multiple(
         }
     ]
 
-    result = [
+    assert [
         event
         for event in graph.stream(
-            Command(
-                resume="answer 1"
-                if resume_style == "null"
-                else {result[0]["__interrupt__"][0].id: "answer 1"},
-                update={"my_key": " foofoo "},
-            ),
-            thread1,
+            Command(resume="answer 1", update={"my_key": " foofoo "}), thread1
         )
-    ]
-    assert result == [
+    ] == [
         {
             "__interrupt__": (
                 Interrupt(
@@ -5004,13 +4851,7 @@ def test_interrupt_multiple(
     assert [
         event
         for event in graph.stream(
-            Command(
-                resume="answer 2"
-                if resume_style == "null"
-                else {result[0]["__interrupt__"][0].id: "answer 2"}
-            ),
-            thread1,
-            stream_mode="values",
+            Command(resume="answer 2"), thread1, stream_mode="values"
         )
     ] == [
         {"my_key": "DE foofoo "},

libs/langgraph/tests/test_remote_graph.py

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

libs/langgraph/tests/test_state.py

@@ -10,7 +10,6 @@ from langchain_core.runnables import RunnableConfig
 from pydantic import BaseModel
 from typing_extensions import NotRequired, Required, TypedDict
 
-from langgraph.channels.binop import BinaryOperatorAggregate
 from langgraph.graph.state import StateGraph, _get_node_name, _warn_invalid_state_schema
 
 
@@ -138,7 +137,7 @@ def test_state_schema_optional_values(total_: bool):
     class InputState(SomeParentState, total=total_):  # type: ignore
         val1: str
         val2: Optional[str]
-        val3: Required[Annotated[dict, operator.or_]]
+        val3: Required[str]
         val4: NotRequired[dict]
         val5: Annotated[Required[str], "foo"]
         val6: Annotated[NotRequired[str], "bar"]
@@ -160,8 +159,6 @@ def test_state_schema_optional_values(total_: bool):
     graph = builder.compile()
     json_schema = graph.get_input_jsonschema()
 
-    assert isinstance(graph.channels["val3"], BinaryOperatorAggregate)
-
     if total_ is False:
         expected_required = set()
         expected_optional = {"val2", "val1"}

libs/langgraph/versions_seen_explained.md

@@ -1,424 +0,0 @@
-# Understanding `versions_seen` in LangGraph Checkpoints
-
-## Overview
-
-`versions_seen` is a nested dictionary in the checkpoint that tracks which channel versions each node has processed. It's defined in `libs/checkpoint/langgraph/checkpoint/base/__init__.py`:
-
-```python
-versions_seen: dict[str, ChannelVersions]
-"""Map from node ID to map from channel name to version seen.
-This keeps track of the versions of the channels that each node has seen.
-Used to determine which nodes to execute next.
-"""
-```
-
-## Data Structure
-
-```
-versions_seen = {
-    "node_name": {
-        "channel_name": version,
-        ...
-    },
-    ...
-}
-```
-
-## Key Point
-
-**`versions_seen` only records trigger channels, NOT state channels!**
-
-In StateGraph:
-- `triggers` = edge control channels like `branch:to:nodeA`
-- `channels` = state keys like `fieldA`, `fieldB`
-
-So `versions_seen` records `branch:to:*` channels, **NOT** `fieldA` or `fieldB`.
-
----
-
-## Example Graph
-
-```
-        ┌──────────┐
-        │  nodeA   │
-        └────┬─────┘
-             │
-      ┌──────┴──────┐
-      ▼             ▼
-┌──────────┐  ┌──────────┐
-│  nodeB   │  │  nodeC   │
-└────┬─────┘  └────┬─────┘
-      │             │
-      └──────┬──────┘
-             ▼
-        ┌──────────┐
-        │  nodeD   │
-        └──────────┘
-```
-
-### State Definition
-
-```python
-class State(TypedDict):
-    fieldA: str
-    fieldB: str
-
-class StateOnlyA(TypedDict):
-    """Input schema for nodeB - only reads fieldA"""
-    fieldA: str
-
-class StateOnlyB(TypedDict):
-    """Input schema for nodeC - only reads fieldB"""
-    fieldB: str
-```
-
----
-
-## Compiled Graph Structure
-
-### Channels Created
-
-| Channel | Type | Purpose |
-|---------|------|---------|
-| `fieldA` | LastValue | State data |
-| `fieldB` | LastValue | State data |
-| `__start__` | EphemeralValue | Input channel |
-| `branch:to:nodeA` | EphemeralValue | Edge control channel |
-| `branch:to:nodeB` | EphemeralValue | Edge control channel |
-| `branch:to:nodeC` | EphemeralValue | Edge control channel |
-| `branch:to:nodeD` | EphemeralValue | Edge control channel |
-| `join:nodeB+nodeC:nodeD` | NamedBarrierValue | Parallel join channel |
-
-### Nodes Configuration
-
-| Node | triggers | channels | Note |
-|------|----------|----------|------|
-| `__start__` | `["__start__"]` | `"__start__"` | Input node |
-| `nodeA` | `["branch:to:nodeA"]` | `["fieldA", "fieldB"]` | Reads full state |
-| `nodeB` | `["branch:to:nodeB"]` | `["fieldA"]` | Only reads fieldA (via `input_schema=StateOnlyA`) |
-| `nodeC` | `["branch:to:nodeC"]` | `["fieldB"]` | Only reads fieldB (via `input_schema=StateOnlyB`) |
-| `nodeD` | `["branch:to:nodeD", "join:nodeB+nodeC:nodeD"]` | `["fieldA", "fieldB"]` | Reads full state |
-
-**Note**: `triggers` are edge control channels, `channels` are state fields the node reads. Use `input_schema` to control which fields a node reads.
-
----
-
-## Step-by-Step Execution
-
-### Input
-
-```python
-{"fieldA": "Hello", "fieldB": "World"}
-```
-
----
-
-### Step -1: Input Phase (source: input)
-
-```
-State values: {}
-
-channel_versions:
-    __start__: v01
-
-versions_seen:
-    __input__: {}
-```
-
-Initial checkpoint when input is received.
-
----
-
-### Step 0: `__start__` executes (source: loop)
-
-```
-State values: {'fieldA': 'Hello', 'fieldB': 'World'}
-
-channel_versions:
-    __start__:        v02
-    branch:to:nodeA:  v02
-    fieldA:           v02
-    fieldB:           v02
-
-versions_seen:
-    __input__: {}
-    __start__:
-        __start__: v01    ← __start__ node saw __start__ channel
-```
-
-**Note**: `fieldA` and `fieldB` are NOT in `versions_seen`!
-
----
-
-### Step 1: nodeA executes (source: loop)
-
-```
-nodeA reads: fieldA='Hello', fieldB='World'
-State values: {'fieldA': 'Hello->A', 'fieldB': 'World->A'}
-
-channel_versions:
-    __start__:        v02
-    branch:to:nodeA:  v03
-    branch:to:nodeB:  v03
-    branch:to:nodeC:  v03
-    fieldA:           v03
-    fieldB:           v03
-
-versions_seen:
-    __input__: {}
-    __start__:
-        __start__: v01
-    nodeA:
-        branch:to:nodeA: v02    ← nodeA saw its trigger
-```
-
-**Key observation**:
-- `nodeA`'s `versions_seen` only records `branch:to:nodeA`
-- **NO** `fieldA` or `fieldB` because they are NOT triggers!
-
----
-
-### Step 2: nodeB and nodeC execute in parallel (source: loop)
-
-```
-nodeB reads: fieldA='Hello->A'
-nodeC reads: fieldB='World->A'
-State values: {'fieldA': 'Hello->A->B', 'fieldB': 'World->A->C'}
-
-channel_versions:
-    __start__:              v02
-    branch:to:nodeA:        v03
-    branch:to:nodeB:        v04
-    branch:to:nodeC:        v04
-    fieldA:                 v04
-    fieldB:                 v04
-    join:nodeB+nodeC:nodeD: v04
-
-versions_seen:
-    __input__: {}
-    __start__:
-        __start__: v01
-    nodeA:
-        branch:to:nodeA: v02
-    nodeB:
-        branch:to:nodeB: v03    ← nodeB saw its trigger
-    nodeC:
-        branch:to:nodeC: v03    ← nodeC saw its trigger
-```
-
----
-
-### Step 3: nodeD executes (source: loop)
-
-```
-nodeD reads: fieldA='Hello->A->B', fieldB='World->A->C'
-State values: {'fieldA': 'Hello->A->B->D', 'fieldB': 'World->A->C->D'}
-
-channel_versions:
-    __start__:              v02
-    branch:to:nodeA:        v03
-    branch:to:nodeB:        v04
-    branch:to:nodeC:        v04
-    fieldA:                 v05
-    fieldB:                 v05
-    join:nodeB+nodeC:nodeD: v05
-
-versions_seen:
-    __input__: {}
-    __start__:
-        __start__: v01
-    nodeA:
-        branch:to:nodeA: v02
-    nodeB:
-        branch:to:nodeB: v03
-    nodeC:
-        branch:to:nodeC: v03
-    nodeD:
-        join:nodeB+nodeC:nodeD: v04    ← nodeD saw join channel
-```
-
----
-
-## Summary Table
-
-| Node | versions_seen records | Why? |
-|------|----------------------|------|
-| `__start__` | `__start__` | Its trigger is `__start__` |
-| `nodeA` | `branch:to:nodeA` | Its trigger is `branch:to:nodeA` |
-| `nodeB` | `branch:to:nodeB` | Its trigger is `branch:to:nodeB` |
-| `nodeC` | `branch:to:nodeC` | Its trigger is `branch:to:nodeC` |
-| `nodeD` | `join:nodeB+nodeC:nodeD` | One of its triggers (join channel) |
-
----
-
-## Conclusion
-
-- `versions_seen` **only records triggers**
-- `fieldA` and `fieldB` **never appear** in `versions_seen`
-- In StateGraph, triggers are edge control channels (`branch:to:*`), not state fields
-- The purpose of `versions_seen` is to **prevent duplicate triggering**, so it only needs to track trigger channel versions
-
----
-
-## Deep Dive: How `versions_seen` Determines the Last Node
-
-### The Problem
-
-When calling `update_state()` without specifying `as_node`, LangGraph needs to figure out which node "last updated" the state. This is done using `versions_seen`.
-
-### The Algorithm
-
-```python
-last_seen_by_node = sorted(
-    (v, n)
-    for n, seen in checkpoint["versions_seen"].items()
-    if n in self.nodes
-    for v in seen.values()
-)
-```
-
-This creates a sorted list of `(version, node_name)` tuples.
-
-### Key Insight: Version = Superstep
-
-**Nodes that execute in the same superstep (parallel execution) will have the same trigger channel version.**
-
-This is because:
-1. Each superstep increments the version counter
-2. All nodes triggered in the same superstep see the same version
-3. So `version` effectively identifies which superstep a node executed in
-
-### Analysis by Step (Using Our Example)
-
-#### Step 1: After nodeA executes
-
-```
-versions_seen:
-    __start__: { __start__: v01 }
-    nodeA:     { branch:to:nodeA: v02 }
-
-last_seen_by_node = [(v01, "__start__"), (v02, "nodeA")]
-
-Check: last[-1][0] != last[-2][0]?
-       v02 != v01? ✅ YES
-
-Result: as_node = "nodeA" (last node in the latest superstep)
-```
-
-#### Step 2: After nodeB and nodeC execute (parallel)
-
-```
-versions_seen:
-    __start__: { __start__: v01 }
-    nodeA:     { branch:to:nodeA: v02 }
-    nodeB:     { branch:to:nodeB: v03 }  ← same version!
-    nodeC:     { branch:to:nodeC: v03 }  ← same version!
-
-last_seen_by_node = [(v01, "__start__"), (v02, "nodeA"), (v03, "nodeB"), (v03, "nodeC")]
-
-Check: last[-1][0] != last[-2][0]?
-       v03 != v03? ❌ NO (same version = same superstep)
-
-Result: AMBIGUOUS! Multiple nodes executed in the last superstep.
-        → Raises InvalidUpdateError("Ambiguous update, specify as_node")
-```
-
-#### Step 3: After nodeD executes
-
-```
-versions_seen:
-    __start__: { __start__: v01 }
-    nodeA:     { branch:to:nodeA: v02 }
-    nodeB:     { branch:to:nodeB: v03 }
-    nodeC:     { branch:to:nodeC: v03 }
-    nodeD:     { join:nodeB+nodeC:nodeD: v04 }
-
-last_seen_by_node = [(v01, "__start__"), (v02, "nodeA"), (v03, "nodeB"), (v03, "nodeC"), (v04, "nodeD")]
-
-Check: last[-1][0] != last[-2][0]?
-       v04 != v03? ✅ YES
-
-Result: as_node = "nodeD" (only node in the latest superstep)
-```
-
-### Summary Table
-
-| Step | Last Two Versions | Same Superstep? | as_node |
-|------|-------------------|-----------------|---------|
-| Step 1 | v02, v01 | No | ✅ nodeA |
-| Step 2 | v03, v03 | **Yes (parallel!)** | ❌ Ambiguous |
-| Step 3 | v04, v03 | No | ✅ nodeD |
-
-### Visual Representation
-
-```
-Superstep Timeline:
-
-  Superstep 0    Superstep 1    Superstep 2    Superstep 3
-  (v01, v02)        (v03)          (v04)          (v05)
-      │               │              │              │
-      ▼               ▼              ▼              ▼
-  ┌────────┐    ┌──────────┐   ┌─────────┐    ┌────────┐
-  │__start__│    │  nodeA   │   │ nodeB   │    │ nodeD  │
-  └────────┘    └──────────┘   │ nodeC   │    └────────┘
-                               │(parallel)│
-                               └─────────┘
-
-When version[-1] == version[-2]:
-  → Multiple nodes in the same superstep
-  → Cannot determine which one was "last"
-  → Ambiguous!
-```
-
-### The Logic Explained
-
-```python
-if last_seen_by_node:
-    if len(last_seen_by_node) == 1:
-        # Only one node ever executed
-        as_node = last_seen_by_node[0][1]
-    elif last_seen_by_node[-1][0] != last_seen_by_node[-2][0]:
-        # Last two have different versions
-        # → Last superstep had only ONE node
-        # → That node is unambiguously the "last" one
-        as_node = last_seen_by_node[-1][1]
-    # else: versions are equal
-    #     → Multiple nodes in the last superstep
-    #     → Ambiguous, will raise error later
-```
-
----
-
-## How Scheduling Works
-
-```python
-def _triggers(channels, versions, seen, null_version, proc) -> bool:
-    for chan in proc.triggers:  # Only checks triggers!
-        if channels[chan].is_available() and \           # Condition 1: channel has value
-           versions.get(chan, null_version) > seen.get(chan, null_version):  # Condition 2: version updated
-            return True
-    return False
-```
-
-Translation:
-> Trigger the node if ANY trigger channel satisfies **BOTH** conditions:
-> 1. `is_available()` - the channel has a value
-> 2. `current_version > seen_version` - the version is newer than what the node has seen
-
-**Important**: Both conditions must be met! This is why `EphemeralValue` channels (like `branch:to:*`) 
-can have their version increase after being consumed, but won't re-trigger the node because 
-`is_available()` returns `False` after consumption.
-
-Since only triggers are checked, only trigger versions need to be recorded in `versions_seen`.
-
----
-
-## Running the Test
-
-To run the test script yourself:
-
-```bash
-cd libs/langgraph
-uv run python test_versions_seen.py
-```
-

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

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

libs/prebuilt/langgraph/prebuilt/responses.py

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

libs/prebuilt/langgraph/prebuilt/tool_node.py

@@ -31,6 +31,8 @@ Typical Usage:
     ```
 """
 
+from __future__ import annotations
+
 import asyncio
 import inspect
 import json
@@ -68,7 +70,7 @@ from langchain_core.tools.base import (
     TOOL_MESSAGE_BLOCK_TYPES,
     get_all_basemodel_annotations,
 )
-from pydantic import BaseModel
+from pydantic import BaseModel, ValidationError
 from typing_extensions import Annotated, get_args, get_origin
 
 from langgraph._internal._runnable import RunnableCallable
@@ -81,6 +83,8 @@ INVALID_TOOL_NAME_ERROR_TEMPLATE = (
     "Error: {requested_tool} is not a valid tool, try one of [{available_tools}]."
 )
 TOOL_CALL_ERROR_TEMPLATE = "Error: {error}\n Please fix your mistakes."
+TOOL_EXECUTION_ERROR_TEMPLATE = "Error executing tool '{tool_name}' with kwargs {tool_kwargs} with error:\n {error}\n Please fix the error and try again."
+TOOL_INVOCATION_ERROR_TEMPLATE = "Error invoking tool '{tool_name}' with kwargs {tool_kwargs} with error:\n {error}\n Please fix the error and try again."
 
 
 def msg_content_output(output: Any) -> Union[str, list[dict]]:
@@ -122,6 +126,30 @@ def msg_content_output(output: Any) -> Union[str, list[dict]]:
             return str(output)
 
 
+class ToolInvocationError(Exception):
+    """Exception raised when a tool invocation fails due to invalid arguments."""
+
+    def __init__(self, tool_name: str, error: Exception, tool_kwargs: dict[str, Any]):
+        self.message = TOOL_INVOCATION_ERROR_TEMPLATE.format(
+            tool_name=tool_name, tool_kwargs=tool_kwargs, error=error
+        )
+        self.tool_name = tool_name
+        self.tool_kwargs = tool_kwargs
+        self.error = error
+        super().__init__(self.message)
+
+
+def _default_handle_tool_errors(e: Exception) -> str:
+    """Default error handler for tool errors.
+
+    If the tool is a tool invocation error, return its message.
+    Otherwise, raise the error.
+    """
+    if isinstance(e, ToolInvocationError):
+        return e.message
+    raise e
+
+
 def _handle_tool_error(
     e: Exception,
     *,
@@ -129,6 +157,7 @@ def _handle_tool_error(
         bool,
         str,
         Callable[..., str],
+        type[Exception],
         tuple[type[Exception], ...],
     ],
 ) -> str:
@@ -156,12 +185,14 @@ def _handle_tool_error(
         The tuple case is handled by the caller through exception type checking,
         not by this function directly.
     """
-    if isinstance(flag, (bool, tuple)):
+    if isinstance(flag, (bool, tuple)) or (
+        isinstance(flag, type) and issubclass(flag, Exception)
+    ):
         content = TOOL_CALL_ERROR_TEMPLATE.format(error=repr(e))
     elif isinstance(flag, str):
         content = flag
     elif callable(flag):
-        content = flag(e)
+        content = flag(e)  # type: ignore [assignment, call-arg]
     else:
         raise ValueError(
             f"Got unexpected type of `handle_tool_error`. Expected bool, str "
@@ -237,39 +268,69 @@ def _infer_handled_types(handler: Callable[..., str]) -> tuple[type[Exception],
 
 
 class ToolNode(RunnableCallable):
-    """A node that runs the tools called in the last AIMessage.
+    """A node for executing tools in LangGraph workflows.
 
-    It can be used either in StateGraph with a "messages" state key (or a custom key passed via ToolNode's 'messages_key').
-    If multiple tool calls are requested, they will be run in parallel. The output will be
-    a list of ToolMessages, one for each tool call.
+    Handles tool execution patterns including function calls, state injection,
+    persistent storage, and control flow. Manages parallel execution,
+    error handling.
 
-    Tool calls can also be passed directly as a list of `ToolCall` dicts.
+    Input Formats:
+        1. Graph state with `messages` key that has a list of messages:
+           - Common representation for agentic workflows
+           - Supports custom messages key via ``messages_key`` parameter
+
+        2. **Message List**: ``[AIMessage(..., tool_calls=[...])]``
+           - List of messages with tool calls in the last AIMessage
+
+        3. **Direct Tool Calls**: ``[{"name": "tool", "args": {...}, "id": "1", "type": "tool_call"}]``
+           - Bypasses message parsing for direct tool execution
+           - For programmatic tool invocation and testing
+
+    Output Formats:
+        Output format depends on input type and tool behavior:
+
+        **For Regular tools**:
+        - Dict input → ``{"messages": [ToolMessage(...)]}``
+        - List input → ``[ToolMessage(...)]``
+
+        **For Command tools**:
+        - Returns ``[Command(...)]`` or mixed list with regular tool outputs
+        - Commands can update state, trigger navigation, or send messages
 
     Args:
-        tools: A sequence of tools that can be invoked by this node. Tools can be
-            BaseTool instances or plain functions that will be converted to tools.
+        tools: A sequence of tools that can be invoked by this node. Supports:
+            - **BaseTool instances**: Tools with schemas and metadata
+            - **Plain functions**: Automatically converted to tools with inferred schemas
         name: The name identifier for this node in the graph. Used for debugging
             and visualization. Defaults to "tools".
         tags: Optional metadata tags to associate with the node for filtering
             and organization. Defaults to None.
         handle_tool_errors: Configuration for error handling during tool execution.
-            Defaults to True. Supports multiple strategies:
+            Supports multiple strategies:
 
-            - True: Catch all errors and return a ToolMessage with the default
+            - **True**: Catch all errors and return a ToolMessage with the default
               error template containing the exception details.
-            - str: Catch all errors and return a ToolMessage with this custom
+            - **str**: Catch all errors and return a ToolMessage with this custom
               error message string.
-            - tuple[type[Exception], ...]: Only catch exceptions of the specified
+            - **type[Exception]**: Only catch exceptions with the specified type and return the default error message for it.
+            - **tuple[type[Exception], ...]**: Only catch exceptions with the specified
               types and return default error messages for them.
-            - Callable[..., str]: Catch exceptions matching the callable's signature
+            - **Callable[..., str]**: Catch exceptions matching the callable's signature
               and return the string result of calling it with the exception.
-            - False: Disable error handling entirely, allowing exceptions to propagate.
+            - **False**: Disable error handling entirely, allowing exceptions to
+              propagate.
+
+            Defaults to a callable that:
+                - catches tool invocation errors (due to invalid arguments provided by the model) and returns a descriptive error message
+                - ignores tool execution errors (they will be re-raised)
 
         messages_key: The key in the state dictionary that contains the message list.
-            This same key will be used for the output ToolMessages. Defaults to "messages".
+            This same key will be used for the output ToolMessages.
+            Defaults to "messages".
+            Allows custom state schemas with different message field names.
 
-    Example:
-        Basic usage with simple tools:
+    Examples:
+        Basic usage:
 
         ```python
         from langgraph.prebuilt import ToolNode
@@ -283,38 +344,31 @@ class ToolNode(RunnableCallable):
         tool_node = ToolNode([calculator])
         ```
 
-        Custom error handling:
+        State injection:
 
         ```python
-        def handle_math_errors(e: ZeroDivisionError) -> str:
-            return "Cannot divide by zero!"
+        from typing_extensions import Annotated
+        from langgraph.prebuilt import InjectedState
 
-        tool_node = ToolNode([calculator], handle_tool_errors=handle_math_errors)
+        @tool
+        def context_tool(query: str, state: Annotated[dict, InjectedState]) -> str:
+            \"\"\"Some tool that uses state.\"\"\"
+            return f"Query: {query}, Messages: {len(state['messages'])}"
+
+        tool_node = ToolNode([context_tool])
         ```
 
-        Direct tool call execution:
+        Error handling:
 
         ```python
-        tool_calls = [{"name": "calculator", "args": {"a": 5, "b": 3}, "id": "1", "type": "tool_call"}]
-        result = tool_node.invoke(tool_calls)
+        def handle_errors(e: ValueError) -> str:
+            return "Invalid input provided"
+
+        tool_node = ToolNode([my_tool], handle_tool_errors=handle_errors)
         ```
-
-    Note:
-        The ToolNode expects input in one of three formats:
-        1. A dictionary with a messages key containing a list of messages
-        2. A list of messages directly
-        3. A list of tool call dictionaries
-
-        When using message formats, the last message must be an AIMessage with
-        tool_calls populated. The node automatically extracts and processes these
-        tool calls concurrently.
-
-        For advanced use cases involving state injection or store access, tools
-        can be annotated with InjectedState or InjectedStore to receive graph
-        context automatically.
     """
 
-    name: str = "ToolNode"
+    name: str = "tools"
 
     def __init__(
         self,
@@ -323,8 +377,8 @@ class ToolNode(RunnableCallable):
         name: str = "tools",
         tags: Optional[list[str]] = None,
         handle_tool_errors: Union[
-            bool, str, Callable[..., str], tuple[type[Exception], ...]
-        ] = True,
+            bool, str, Callable[..., str], type[Exception], tuple[type[Exception], ...]
+        ] = _default_handle_tool_errors,
         messages_key: str = "messages",
     ) -> None:
         """Initialize the ToolNode with the provided tools and configuration.
@@ -337,17 +391,24 @@ class ToolNode(RunnableCallable):
             messages_key: State key containing messages.
         """
         super().__init__(self._func, self._afunc, name=name, tags=tags, trace=False)
-        self.tools_by_name: dict[str, BaseTool] = {}
-        self.tool_to_state_args: dict[str, dict[str, Optional[str]]] = {}
-        self.tool_to_store_arg: dict[str, Optional[str]] = {}
-        self.handle_tool_errors = handle_tool_errors
-        self.messages_key = messages_key
-        for tool_ in tools:
-            if not isinstance(tool_, BaseTool):
-                tool_ = create_tool(tool_)
-            self.tools_by_name[tool_.name] = tool_
-            self.tool_to_state_args[tool_.name] = _get_state_args(tool_)
-            self.tool_to_store_arg[tool_.name] = _get_store_arg(tool_)
+        self._tools_by_name: dict[str, BaseTool] = {}
+        self._tool_to_state_args: dict[str, dict[str, Optional[str]]] = {}
+        self._tool_to_store_arg: dict[str, Optional[str]] = {}
+        self._handle_tool_errors = handle_tool_errors
+        self._messages_key = messages_key
+        for tool in tools:
+            if not isinstance(tool, BaseTool):
+                tool_ = create_tool(cast(Type[BaseTool], tool))
+            else:
+                tool_ = tool
+            self._tools_by_name[tool_.name] = tool_
+            self._tool_to_state_args[tool_.name] = _get_state_args(tool_)
+            self._tool_to_store_arg[tool_.name] = _get_store_arg(tool_)
+
+    @property
+    def tools_by_name(self) -> dict[str, BaseTool]:
+        """Mapping from tool name to BaseTool instance."""
+        return self._tools_by_name
 
     def _func(
         self,
@@ -390,14 +451,14 @@ class ToolNode(RunnableCallable):
 
     def _combine_tool_outputs(
         self,
-        outputs: list[ToolMessage],
+        outputs: list[Union[ToolMessage, Command]],
         input_type: Literal["list", "dict", "tool_calls"],
     ) -> list[Union[Command, list[ToolMessage], dict[str, list[ToolMessage]]]]:
         # preserve existing behavior for non-command tool outputs for backwards
         # compatibility
         if not any(isinstance(output, Command) for output in outputs):
             # TypedDict, pydantic, dataclass, etc. should all be able to load from dict
-            return outputs if input_type == "list" else {self.messages_key: outputs}
+            return outputs if input_type == "list" else {self._messages_key: outputs}
 
         # LangGraph will automatically handle list of Command and non-command node
         # updates
@@ -425,7 +486,7 @@ class ToolNode(RunnableCallable):
                     combined_outputs.append(output)
             else:
                 combined_outputs.append(
-                    [output] if input_type == "list" else {self.messages_key: [output]}
+                    [output] if input_type == "list" else {self._messages_key: [output]}
                 )
 
         if parent_command:
@@ -437,13 +498,19 @@ class ToolNode(RunnableCallable):
         call: ToolCall,
         input_type: Literal["list", "dict", "tool_calls"],
         config: RunnableConfig,
-    ) -> ToolMessage:
+    ) -> Union[ToolMessage, Command]:
         """Run a single tool call synchronously."""
         if invalid_tool_message := self._validate_tool_call(call):
             return invalid_tool_message
+
         try:
             call_args = {**call, **{"type": "tool_call"}}
-            response = self.tools_by_name[call["name"]].invoke(call_args, config)
+            tool = self.tools_by_name[call["name"]]
+
+            try:
+                response = tool.invoke(call_args, config)
+            except ValidationError as exc:
+                raise ToolInvocationError(call["name"], exc, call["args"])
 
         # GraphInterrupt is a special exception that will always be raised.
         # It can be triggered in the following scenarios,
@@ -455,20 +522,27 @@ class ToolNode(RunnableCallable):
         except GraphBubbleUp as e:
             raise e
         except Exception as e:
-            if isinstance(self.handle_tool_errors, tuple):
-                handled_types: tuple = self.handle_tool_errors
-            elif callable(self.handle_tool_errors):
-                handled_types = _infer_handled_types(self.handle_tool_errors)
+            handled_types: tuple[type[Exception], ...]
+            if isinstance(self._handle_tool_errors, type) and issubclass(
+                self._handle_tool_errors, Exception
+            ):
+                handled_types = (self._handle_tool_errors,)
+            elif isinstance(self._handle_tool_errors, tuple):
+                handled_types = self._handle_tool_errors
+            elif callable(self._handle_tool_errors) and not isinstance(
+                self._handle_tool_errors, type
+            ):
+                handled_types = _infer_handled_types(self._handle_tool_errors)
             else:
                 # default behavior is catching all exceptions
                 handled_types = (Exception,)
 
             # Unhandled
-            if not self.handle_tool_errors or not isinstance(e, handled_types):
+            if not self._handle_tool_errors or not isinstance(e, handled_types):
                 raise e
             # Handled
             else:
-                content = _handle_tool_error(e, flag=self.handle_tool_errors)
+                content = _handle_tool_error(e, flag=self._handle_tool_errors)
             return ToolMessage(
                 content=content,
                 name=call["name"],
@@ -493,14 +567,19 @@ class ToolNode(RunnableCallable):
         call: ToolCall,
         input_type: Literal["list", "dict", "tool_calls"],
         config: RunnableConfig,
-    ) -> ToolMessage:
+    ) -> Union[ToolMessage, Command]:
         """Run a single tool call asynchronously."""
         if invalid_tool_message := self._validate_tool_call(call):
             return invalid_tool_message
 
         try:
             call_args = {**call, **{"type": "tool_call"}}
-            response = await self.tools_by_name[call["name"]].ainvoke(call_args, config)
+            tool = self.tools_by_name[call["name"]]
+
+            try:
+                response = await tool.ainvoke(call_args, config)
+            except ValidationError as exc:
+                raise ToolInvocationError(call["name"], exc, call["args"])
 
         # GraphInterrupt is a special exception that will always be raised.
         # It can be triggered in the following scenarios,
@@ -512,20 +591,27 @@ class ToolNode(RunnableCallable):
         except GraphBubbleUp as e:
             raise e
         except Exception as e:
-            if isinstance(self.handle_tool_errors, tuple):
-                handled_types: tuple = self.handle_tool_errors
-            elif callable(self.handle_tool_errors):
-                handled_types = _infer_handled_types(self.handle_tool_errors)
+            handled_types: tuple[type[Exception], ...]
+            if isinstance(self._handle_tool_errors, type) and issubclass(
+                self._handle_tool_errors, Exception
+            ):
+                handled_types = (self._handle_tool_errors,)
+            elif isinstance(self._handle_tool_errors, tuple):
+                handled_types = self._handle_tool_errors
+            elif callable(self._handle_tool_errors) and not isinstance(
+                self._handle_tool_errors, type
+            ):
+                handled_types = _infer_handled_types(self._handle_tool_errors)
             else:
                 # default behavior is catching all exceptions
                 handled_types = (Exception,)
 
             # Unhandled
-            if not self.handle_tool_errors or not isinstance(e, handled_types):
+            if not self._handle_tool_errors or not isinstance(e, handled_types):
                 raise e
             # Handled
             else:
-                content = _handle_tool_error(e, flag=self.handle_tool_errors)
+                content = _handle_tool_error(e, flag=self._handle_tool_errors)
 
             return ToolMessage(
                 content=content,
@@ -564,9 +650,11 @@ class ToolNode(RunnableCallable):
             else:
                 input_type = "list"
                 messages = input
-        elif isinstance(input, dict) and (messages := input.get(self.messages_key, [])):
+        elif isinstance(input, dict) and (
+            messages := input.get(self._messages_key, [])
+        ):
             input_type = "dict"
-        elif messages := getattr(input, self.messages_key, []):
+        elif messages := getattr(input, self._messages_key, []):
             # Assume dataclass-like state that can coerce from dict
             input_type = "dict"
         else:
@@ -586,10 +674,12 @@ class ToolNode(RunnableCallable):
         return tool_calls, input_type
 
     def _validate_tool_call(self, call: ToolCall) -> Optional[ToolMessage]:
-        if (requested_tool := call["name"]) not in self.tools_by_name:
+        requested_tool = call["name"]
+        if requested_tool not in self.tools_by_name:
+            all_tool_names = list(self.tools_by_name.keys())
             content = INVALID_TOOL_NAME_ERROR_TEMPLATE.format(
                 requested_tool=requested_tool,
-                available_tools=", ".join(self.tools_by_name.keys()),
+                available_tools=", ".join(all_tool_names),
             )
             return ToolMessage(
                 content, name=requested_tool, tool_call_id=call["id"], status="error"
@@ -606,15 +696,15 @@ class ToolNode(RunnableCallable):
             BaseModel,
         ],
     ) -> ToolCall:
-        state_args = self.tool_to_state_args[tool_call["name"]]
+        state_args = self._tool_to_state_args[tool_call["name"]]
         if state_args and isinstance(input, list):
             required_fields = list(state_args.values())
             if (
                 len(required_fields) == 1
-                and required_fields[0] == self.messages_key
+                and required_fields[0] == self._messages_key
                 or required_fields[0] is None
             ):
-                input = {self.messages_key: input}
+                input = {self._messages_key: input}
             else:
                 err_msg = (
                     f"Invalid input to ToolNode. Tool {tool_call['name']} requires "
@@ -645,7 +735,7 @@ class ToolNode(RunnableCallable):
     def _inject_store(
         self, tool_call: ToolCall, store: Optional[BaseStore]
     ) -> ToolCall:
-        store_arg = self.tool_to_store_arg[tool_call["name"]]
+        store_arg = self._tool_to_store_arg[tool_call["name"]]
         if not store_arg:
             return tool_call
 
@@ -722,15 +812,15 @@ class ToolNode(RunnableCallable):
             # input type is dict when ToolNode is invoked with a dict input (e.g. {"messages": [AIMessage(..., tool_calls=[...])]})
             if input_type not in ("dict", "tool_calls"):
                 raise ValueError(
-                    f"Tools can provide a dict in Command.update only when using dict with '{self.messages_key}' key as ToolNode input, "
+                    f"Tools can provide a dict in Command.update only when using dict with '{self._messages_key}' key as ToolNode input, "
                     f"got: {command.update} for tool '{call['name']}'"
                 )
 
             updated_command = deepcopy(command)
             state_update = cast(dict[str, Any], updated_command.update) or {}
-            messages_update = state_update.get(self.messages_key, [])
+            messages_update = state_update.get(self._messages_key, [])
         elif isinstance(command.update, list):
-            # input type is list when ToolNode is invoked with a list input (e.g. [AIMessage(..., tool_calls=[...])])
+            # Input type is list when ToolNode is invoked with a list input (e.g. [AIMessage(..., tool_calls=[...])])
             if input_type != "list":
                 raise ValueError(
                     f"Tools can provide a list of messages in Command.update only when using list of messages as ToolNode input, "

libs/prebuilt/tests/__snapshots__/test_react_agent_graph.ambr

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

libs/prebuilt/tests/model.py

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

libs/prebuilt/tests/specifications/responses.json

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

libs/prebuilt/tests/specifications/return_direct.json

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

libs/prebuilt/tests/test_deprecation.py

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

libs/prebuilt/tests/test_react_agent.py

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

libs/prebuilt/tests/test_react_agent_graph.py

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

libs/prebuilt/tests/test_response_format.py

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

libs/prebuilt/tests/test_responses.py

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

libs/prebuilt/tests/test_responses_spec.py

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

libs/prebuilt/tests/test_return_direct_spec.py

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

libs/prebuilt/tests/test_tool_node.py

@@ -1,25 +1,49 @@
+import dataclasses
+import json
+from functools import partial
 from typing import (
     Annotated,
     Any,
+    List,
+    Type,
+    TypeVar,
     Union,
 )
 
 import pytest
 from langchain_core.messages import (
     AIMessage,
+    AnyMessage,
+    HumanMessage,
     RemoveMessage,
+    ToolCall,
     ToolMessage,
 )
 from langchain_core.tools import BaseTool, ToolException
 from langchain_core.tools import tool as dec_tool
-from pydantic import BaseModel, 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.config import get_stream_writer
 from langgraph.errors import GraphBubbleUp, GraphInterrupt
-from langgraph.graph.message import REMOVE_ALL_MESSAGES
-from langgraph.prebuilt import ToolNode
-from langgraph.prebuilt.tool_node import TOOL_CALL_ERROR_TEMPLATE
+from langgraph.graph import START, MessagesState, StateGraph
+from langgraph.graph.message import REMOVE_ALL_MESSAGES, add_messages
+from langgraph.prebuilt import (
+    ToolNode,
+)
+from langgraph.prebuilt.tool_node import (
+    TOOL_CALL_ERROR_TEMPLATE,
+    InjectedState,
+    InjectedStore,
+    ToolInvocationError,
+    tools_condition,
+)
+from langgraph.store.base import BaseStore
+from langgraph.store.memory import InMemoryStore
 from langgraph.types import Command, Send
+from tests.messages import _AnyIdHumanMessage, _AnyIdToolMessage
+from tests.model import FakeToolCallingModel
 
 pytestmark = pytest.mark.anyio
 
@@ -62,7 +86,8 @@ def tool5(some_val: int):
 tool5.handle_tool_error = "foo"
 
 
-async def test_tool_node():
+async def test_tool_node() -> None:
+    """Test tool node."""
     result = ToolNode([tool1]).invoke(
         {
             "messages": [
@@ -154,7 +179,7 @@ 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",
@@ -195,17 +220,67 @@ async def test_tool_node_tool_call_input():
     ]
 
 
-async def test_tool_node_error_handling():
-    def handle_all(e: Union[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",
+                        },
+                    ],
+                )
+            ]
+        }
+    )
+
+    assert all(m.type == "tool" for m in result["messages"])
+    assert all(m.status == "error" for m in result["messages"])
+    assert (
+        "Error invoking tool 'tool1' with kwargs {'invalid': 0, 'args': 'foo'} with error:\n"
+        in result["messages"][0].content
+    )
+
+
+def test_tool_node_error_handling_default_exception() -> None:
+    tn = ToolNode([tool1])
+    with pytest.raises(ValueError):
+        tn.invoke(
+            {
+                "messages": [
+                    AIMessage(
+                        "hi?",
+                        tool_calls=[
+                            {
+                                "name": "tool1",
+                                "args": {"some_val": 0, "some_other_val": "foo"},
+                                "id": "some id",
+                            },
+                        ],
+                    )
+                ]
+            }
+        )
+
+
+async def test_tool_node_error_handling() -> None:
+    def handle_all(e: Union[ValueError, ToolException, ToolInvocationError]):
         return TOOL_CALL_ERROR_TEMPLATE.format(error=repr(e))
 
     # test catching all exceptions, via:
     # - handle_tool_errors = True
+    # - passing a single exception
     # - passing a tuple of all exceptions
     # - passing a callable with all exceptions in the signature
     for handle_tool_errors in (
         True,
-        (ValueError, ToolException, ValidationError),
+        Exception,
+        (ValueError, ToolException, ToolInvocationError),
         handle_all,
     ):
         result_error = await ToolNode(
@@ -257,7 +332,7 @@ async def test_tool_node_error_handling():
         assert result_error["messages"][2].tool_call_id == "another id"
 
 
-async def test_tool_node_error_handling_callable():
+async def test_tool_node_error_handling_callable() -> None:
     def handle_value_error(e: ValueError):
         return "Value error"
 
@@ -388,7 +463,7 @@ async def test_tool_node_handle_tool_errors_false():
     assert str(exc_info.value) == "Test error"
 
     # test validation errors get raised if handle_tool_errors is False
-    with pytest.raises((ValidationError, ValidationErrorV1)):
+    with pytest.raises((ToolInvocationError)):
         ToolNode([tool1], handle_tool_errors=False).invoke(
             {
                 "messages": [
@@ -1156,3 +1231,304 @@ 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 _InjectedStatePydanticSchema(BaseModelV1):
+    messages: list
+    foo: str
+
+
+class _InjectedStatePydanticV2Schema(BaseModel):
+    messages: list
+    foo: str
+
+
+@dataclasses.dataclass
+class _InjectedStateDataclassSchema:
+    messages: list
+    foo: str
+
+
+T = TypeVar("T")
+
+
+@pytest.mark.parametrize(
+    "schema_",
+    [
+        _InjectStateSchema,
+        _InjectedStatePydanticSchema,
+        _InjectedStatePydanticV2Schema,
+        _InjectedStateDataclassSchema,
+    ],
+)
+def test_tool_node_inject_state(schema_: Type[T]) -> None:
+    def tool1(some_val: int, state: Annotated[T, InjectedState]) -> str:
+        """Tool 1 docstring."""
+        if isinstance(state, dict):
+            return state["foo"]
+        else:
+            return getattr(state, "foo")
+
+    def tool2(some_val: int, state: Annotated[T, InjectedState()]) -> str:
+        """Tool 2 docstring."""
+        if isinstance(state, dict):
+            return state["foo"]
+        else:
+            return getattr(state, "foo")
+
+    def tool3(
+        some_val: int,
+        foo: Annotated[str, InjectedState("foo")],
+        msgs: Annotated[List[AnyMessage], InjectedState("messages")],
+    ) -> str:
+        """Tool 1 docstring."""
+        return foo
+
+    def tool4(
+        some_val: int, msgs: Annotated[List[AnyMessage], InjectedState("messages")]
+    ) -> str:
+        """Tool 1 docstring."""
+        return msgs[0].content
+
+    node = ToolNode([tool1, tool2, tool3, tool4], handle_tool_errors=True)
+    for tool_name in ("tool1", "tool2", "tool3"):
+        tool_call = {
+            "name": tool_name,
+            "args": {"some_val": 1},
+            "id": "some 0",
+            "type": "tool_call",
+        }
+        msg = AIMessage("hi?", tool_calls=[tool_call])
+        result = node.invoke(schema_(**{"messages": [msg], "foo": "bar"}))
+        tool_message = result["messages"][-1]
+        assert tool_message.content == "bar", f"Failed for tool={tool_name}"
+
+        if tool_name == "tool3":
+            failure_input = None
+            try:
+                failure_input = schema_(**{"messages": [msg], "notfoo": "bar"})
+            except Exception:
+                pass
+            if failure_input is not None:
+                with pytest.raises(KeyError):
+                    node.invoke(failure_input)
+
+                with pytest.raises(ValueError):
+                    node.invoke([msg])
+        else:
+            failure_input = None
+            try:
+                failure_input = schema_(**{"messages": [msg], "notfoo": "bar"})
+            except Exception:
+                # We'd get a validation error from pydantic state and wouldn't make it to the node
+                # anyway
+                pass
+            if failure_input is not None:
+                messages_ = node.invoke(failure_input)
+                tool_message = messages_["messages"][-1]
+                assert "KeyError" in tool_message.content
+                tool_message = node.invoke([msg])[-1]
+                assert "KeyError" in tool_message.content
+
+    tool_call = {
+        "name": "tool4",
+        "args": {"some_val": 1},
+        "id": "some 0",
+        "type": "tool_call",
+    }
+    msg = AIMessage("hi?", tool_calls=[tool_call])
+    result = node.invoke(schema_(**{"messages": [msg], "foo": ""}))
+    tool_message = result["messages"][-1]
+    assert tool_message.content == "hi?"
+
+    result = node.invoke([msg])
+    tool_message = result[-1]
+    assert tool_message.content == "hi?"
+
+
+def test_tool_node_inject_store() -> None:
+    store = InMemoryStore()
+    namespace = ("test",)
+
+    def tool1(some_val: int, store: Annotated[BaseStore, InjectedStore()]) -> str:
+        """Tool 1 docstring."""
+        store_val = store.get(namespace, "test_key").value["foo"]
+        return f"Some val: {some_val}, store val: {store_val}"
+
+    def tool2(some_val: int, store: Annotated[BaseStore, InjectedStore()]) -> str:
+        """Tool 2 docstring."""
+        store_val = store.get(namespace, "test_key").value["foo"]
+        return f"Some val: {some_val}, store val: {store_val}"
+
+    def tool3(
+        some_val: int,
+        bar: Annotated[str, InjectedState("bar")],
+        store: Annotated[BaseStore, InjectedStore()],
+    ) -> str:
+        """Tool 3 docstring."""
+        store_val = store.get(namespace, "test_key").value["foo"]
+        return f"Some val: {some_val}, store val: {store_val}, state val: {bar}"
+
+    node = ToolNode([tool1, tool2, tool3], handle_tool_errors=True)
+    store.put(namespace, "test_key", {"foo": "bar"})
+
+    class State(MessagesState):
+        bar: str
+
+    builder = StateGraph(State)
+    builder.add_node("tools", node)
+    builder.add_edge(START, "tools")
+    graph = builder.compile(store=store)
+
+    for tool_name in ("tool1", "tool2"):
+        tool_call = {
+            "name": tool_name,
+            "args": {"some_val": 1},
+            "id": "some 0",
+            "type": "tool_call",
+        }
+        msg = AIMessage("hi?", tool_calls=[tool_call])
+        node_result = node.invoke({"messages": [msg]}, store=store)
+        graph_result = graph.invoke({"messages": [msg]})
+        for result in (node_result, graph_result):
+            result["messages"][-1]
+            tool_message = result["messages"][-1]
+            assert tool_message.content == "Some val: 1, store val: bar", (
+                f"Failed for tool={tool_name}"
+            )
+
+    tool_call = {
+        "name": "tool3",
+        "args": {"some_val": 1},
+        "id": "some 0",
+        "type": "tool_call",
+    }
+    msg = AIMessage("hi?", tool_calls=[tool_call])
+    node_result = node.invoke({"messages": [msg], "bar": "baz"}, store=store)
+    graph_result = graph.invoke({"messages": [msg], "bar": "baz"})
+    for result in (node_result, graph_result):
+        result["messages"][-1]
+        tool_message = result["messages"][-1]
+        assert tool_message.content == "Some val: 1, store val: bar, state val: baz", (
+            f"Failed for tool={tool_name}"
+        )
+
+    # test injected store without passing store to compiled graph
+    failing_graph = builder.compile()
+    with pytest.raises(ValueError):
+        failing_graph.invoke({"messages": [msg], "bar": "baz"})
+
+
+def test_tool_node_ensure_utf8() -> None:
+    @dec_tool
+    def get_day_list(days: list[str]) -> list[str]:
+        """choose days"""
+        return days
+
+    data = ["星期一", "水曜日", "목요일", "Friday"]
+    tools = [get_day_list]
+    tool_calls = [ToolCall(name=get_day_list.name, args={"days": data}, id="test_id")]
+    outputs: list[ToolMessage] = ToolNode(tools).invoke(
+        [AIMessage(content="", tool_calls=tool_calls)]
+    )
+    assert outputs[0].content == json.dumps(data, ensure_ascii=False)
+
+
+def test_tool_node_messages_key() -> None:
+    @dec_tool
+    def add(a: int, b: int):
+        """Adds a and b."""
+        return a + b
+
+    model = FakeToolCallingModel(
+        tool_calls=[[ToolCall(name=add.name, args={"a": 1, "b": 2}, id="test_id")]]
+    )
+
+    class State(TypedDict):
+        subgraph_messages: Annotated[list[AnyMessage], add_messages]
+
+    def call_model(state: State):
+        response = model.invoke(state["subgraph_messages"])
+        model.tool_calls = []
+        return {"subgraph_messages": response}
+
+    builder = StateGraph(State)
+    builder.add_node("agent", call_model)
+    builder.add_node("tools", ToolNode([add], messages_key="subgraph_messages"))
+    builder.add_conditional_edges(
+        "agent", partial(tools_condition, messages_key="subgraph_messages")
+    )
+    builder.add_edge(START, "agent")
+    builder.add_edge("tools", "agent")
+
+    graph = builder.compile()
+    result = graph.invoke({"subgraph_messages": [HumanMessage(content="hi")]})
+    assert result["subgraph_messages"] == [
+        _AnyIdHumanMessage(content="hi"),
+        AIMessage(
+            content="hi",
+            id="0",
+            tool_calls=[ToolCall(name=add.name, args={"a": 1, "b": 2}, id="test_id")],
+        ),
+        _AnyIdToolMessage(content="3", name=add.name, tool_call_id="test_id"),
+        AIMessage(content="hi-hi-3", id="1"),
+    ]
+
+
+def test_tool_node_stream_writer() -> None:
+    @dec_tool
+    def streaming_tool(x: int) -> str:
+        """Do something with writer."""
+        my_writer = get_stream_writer()
+        for value in ["foo", "bar", "baz"]:
+            my_writer({"custom_tool_value": value})
+
+        return x
+
+    tool_node = ToolNode([streaming_tool])
+    graph = (
+        StateGraph(MessagesState)
+        .add_node("tools", tool_node)
+        .add_edge(START, "tools")
+        .compile()
+    )
+
+    tool_call = {
+        "name": "streaming_tool",
+        "args": {"x": 1},
+        "id": "1",
+        "type": "tool_call",
+    }
+    inputs = {
+        "messages": [AIMessage("", tool_calls=[tool_call])],
+    }
+
+    assert list(graph.stream(inputs, stream_mode="custom")) == [
+        {"custom_tool_value": "foo"},
+        {"custom_tool_value": "bar"},
+        {"custom_tool_value": "baz"},
+    ]
+    assert list(graph.stream(inputs, stream_mode=["custom", "updates"])) == [
+        ("custom", {"custom_tool_value": "foo"}),
+        ("custom", {"custom_tool_value": "bar"}),
+        ("custom", {"custom_tool_value": "baz"}),
+        (
+            "updates",
+            {
+                "tools": {
+                    "messages": [
+                        _AnyIdToolMessage(
+                            content="1",
+                            name="streaming_tool",
+                            tool_call_id="1",
+                        ),
+                    ],
+                },
+            },
+        ),
+    ]

libs/prebuilt/tests/utils.py

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

libs/prebuilt/uv.lock

@@ -316,7 +316,7 @@ wheels = [
 
 [[package]]
 name = "langgraph"
-version = "0.6.7"
+version = "0.6.4"
 source = { editable = "../langgraph" }
 dependencies = [
     { name = "langchain-core" },
@@ -509,6 +509,7 @@ dev = [
 
 [[package]]
 name = "langgraph-sdk"
+version = "0.2.0"
 source = { editable = "../sdk-py" }
 dependencies = [
     { name = "httpx" },

libs/sdk-py/Makefile

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

libs/sdk-py/langgraph_sdk/__init__.py

@@ -1,6 +1,11 @@
 from langgraph_sdk.auth import Auth
 from langgraph_sdk.client import get_client, get_sync_client
 
-__version__ = "0.2.6"
+try:
+    from importlib import metadata
+
+    __version__ = metadata.version(__package__)
+except metadata.PackageNotFoundError:
+    __version__ = "unknown"
 
 __all__ = ["Auth", "get_client", "get_sync_client"]

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

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

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

@@ -400,20 +400,6 @@ class AuthContext(BaseAuthContext):
     """
 
 
-class ThreadTTL(typing.TypedDict, total=False):
-    """Time-to-live configuration for a thread.
-
-    Matches the OpenAPI schema where TTL is represented as an object with
-    an optional strategy and a time value in minutes.
-    """
-
-    strategy: typing.Literal["delete"]
-    """TTL strategy. Currently only 'delete' is supported."""
-
-    ttl: int
-    """Time-to-live in minutes from now until the thread should be swept."""
-
-
 class ThreadsCreate(typing.TypedDict, total=False):
     """Parameters for creating a new thread.
 
@@ -436,9 +422,6 @@ class ThreadsCreate(typing.TypedDict, total=False):
     if_exists: OnConflictBehavior
     """Behavior when a thread with the same ID already exists."""
 
-    ttl: ThreadTTL
-    """Optional TTL configuration for the thread."""
-
 
 class ThreadsRead(typing.TypedDict, total=False):
     """Parameters for reading thread state or run information.
@@ -506,9 +489,6 @@ class ThreadsSearch(typing.TypedDict, total=False):
     offset: int
     """Offset for pagination."""
 
-    ids: Sequence[UUID] | None
-    """typing.Optional list of thread IDs to filter by."""
-
     thread_id: UUID | None
     """typing.Optional thread ID to filter by."""
 

libs/sdk-py/langgraph_sdk/schema.py

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

libs/sdk-py/langgraph_sdk/sse.py

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

libs/sdk-py/pyproject.toml

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

libs/sdk-py/tests/test_api_parity.py

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

libs/sdk-py/tests/test_select_fields_sync.py

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

libs/sdk-py/uv.lock

@@ -4,7 +4,7 @@ requires-python = ">=3.9"
 
 [[package]]
 name = "anyio"
-version = "4.10.0"
+version = "4.9.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "exceptiongroup", marker = "python_full_version < '3.11'" },
@@ -12,27 +12,18 @@ dependencies = [
     { name = "sniffio" },
     { name = "typing-extensions", marker = "python_full_version < '3.13'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/f1/b4/636b3b65173d3ce9a38ef5f0522789614e590dab6a8d505340a4efe4c567/anyio-4.10.0.tar.gz", hash = "sha256:3f3fae35c96039744587aa5b8371e7e8e603c0702999535961dd336026973ba6", size = 213252, upload-time = "2025-08-04T08:54:26.451Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/95/7d/4c1bd541d4dffa1b52bd83fb8527089e097a106fc90b467a7313b105f840/anyio-4.9.0.tar.gz", hash = "sha256:673c0c244e15788651a4ff38710fea9675823028a6f08a5eda409e0c9840a028", size = 190949, upload-time = "2025-03-17T00:02:54.77Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/6f/12/e5e0282d673bb9746bacfb6e2dba8719989d3660cdb2ea79aee9a9651afb/anyio-4.10.0-py3-none-any.whl", hash = "sha256:60e474ac86736bbfd6f210f7a61218939c318f43f9972497381f1c5e930ed3d1", size = 107213, upload-time = "2025-08-04T08:54:24.882Z" },
-]
-
-[[package]]
-name = "backports-asyncio-runner"
-version = "1.2.0"
-source = { registry = "https://pypi.org/simple" }
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+    { url = "https://files.pythonhosted.org/packages/a1/ee/48ca1a7c89ffec8b6a0c5d02b89c305671d5ffd8d3c94acf8b8c408575bb/anyio-4.9.0-py3-none-any.whl", hash = "sha256:9f76d541cad6e36af7beb62e978876f3b41e3e04f2c1fbf0884604c0a9c4d93c", size = 100916, upload-time = "2025-03-17T00:02:52.713Z" },
 ]
 
 [[package]]
 name = "certifi"
-version = "2025.8.3"
+version = "2025.7.14"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/dc/67/960ebe6bf230a96cda2e0abcf73af550ec4f090005363542f0765df162e0/certifi-2025.8.3.tar.gz", hash = "sha256:e564105f78ded564e3ae7c923924435e1daa7463faeab5bb932bc53ffae63407", size = 162386, upload-time = "2025-08-03T03:07:47.08Z" }
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 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/4f/52/34c6cf5bb9285074dc3531c437b3919e825d976fde097a7a73f79e726d03/certifi-2025.7.14-py3-none-any.whl", hash = "sha256:6b31f564a415d79ee77df69d757bb49a5bb53bd9f756cbbe24394ffd6fc1f4b2", size = 162722, upload-time = "2025-07-14T03:29:26.863Z" },
 ]
 
 [[package]]
@@ -128,6 +119,7 @@ wheels = [
 
 [[package]]
 name = "langgraph-sdk"
+version = "0.2.0"
 source = { editable = "." }
 dependencies = [
     { name = "httpx" },
@@ -164,7 +156,7 @@ dev = [
 
 [[package]]
 name = "mypy"
-version = "1.17.1"
+version = "1.17.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "mypy-extensions" },
@@ -172,45 +164,39 @@ dependencies = [
     { name = "tomli", marker = "python_full_version < '3.11'" },
     { name = "typing-extensions" },
 ]
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 [[package]]

pregel.learning.md

@@ -1,153 +0,0 @@
-# LangGraph Channel Types Usage Analysis
-
-本文档分析了 LangGraph 中各种通道类型在 StateGraph 中的使用情况，基于对整个仓库的深入分析。
-
-## 通道类型使用总结
-
-### 1. **LastValue** - 最常用的默认通道
-**使用场景：** 普通状态字段的默认通道类型
-**创建方式：** 自动创建（fallback）
-**仓库例子：**
-```python
-class State(TypedDict):
-    hello: str  # 自动创建 LastValue(str) 通道
-    count: int  # 自动创建 LastValue(int) 通道
-```
-
-### 2. **BinaryOperatorAggregate** - 状态聚合通道
-**使用场景：** 使用 reducer 函数进行状态聚合
-**创建方式：** 通过 `Annotated[Type, reducer_function]`
-**仓库例子：**
-```python
-# 例子1: 使用 add_messages
-class State(TypedDict):
-    messages: Annotated[list[str], add_messages]  # 创建 BinaryOperatorAggregate
-
-# 例子2: 使用 operator.add
-StateGraph(Annotated[str, operator.add])  # 整个状态使用聚合
-StateGraph(Annotated[list, operator.add])  # 列表聚合
-
-# 例子3: 使用 operator.or_
-class State(TypedDict):
-    val3: Required[Annotated[dict, operator.or_]]  # 字典合并
-```
-
-### 3. **EphemeralValue** - 临时通道
-**使用场景：** 系统内部使用，节点间的临时通信
-**创建方式：** 系统自动创建
-**仓库例子：**
-```python
-# StateGraph.compile() 中自动创建
-START: EphemeralValue(self.input_schema)  # 输入通道
-
-# CompiledStateGraph.attach_node() 中创建
-EphemeralValue(Any, guard=False)  # 节点分支通道
-```
-
-### 4. **LastValueAfterFinish** - 延迟通道
-**使用场景：** 节点设置了 `defer=True` 时使用
-**创建方式：** 系统根据节点配置自动创建
-**仓库例子：**
-```python
-# CompiledStateGraph.attach_node() 中
-if node.defer:
-    LastValueAfterFinish(Any)  # 延迟节点的分支通道
-```
-
-### 5. **NamedBarrierValue** - 同步屏障通道
-**使用场景：** 多个节点汇聚到一个节点时的同步
-**创建方式：** 系统在处理 waiting_edges 时自动创建
-**仓库例子：**
-```python
-# CompiledStateGraph.attach_edge() 中
-channel_name = f"join:{'+'.join(starts)}:{end}"
-self.channels[channel_name] = NamedBarrierValue(str, set(starts))
-```
-
-### 6. **NamedBarrierValueAfterFinish** - 延迟同步屏障通道
-**使用场景：** 延迟节点的多节点汇聚同步
-**创建方式：** 系统在处理延迟节点的 waiting_edges 时自动创建
-**仓库例子：**
-```python
-# CompiledStateGraph.attach_edge() 中
-if self.builder.nodes[end].defer:
-    self.channels[channel_name] = NamedBarrierValueAfterFinish(str, set(starts))
-```
-
-### 7. **Topic** - 发布订阅通道
-**使用场景：** 仅在直接使用 Pregel 时手动创建，StateGraph 中无实际使用
-**创建方式：** 手动创建或系统内部 TASKS 通道
-**仓库例子：**
-```python
-# Pregel.__init__() 中系统创建
-self.channels[TASKS] = Topic(Send, accumulate=False)
-
-# 直接 Pregel 使用（非 StateGraph）
-app = Pregel(
-    channels={"c": Topic(str, accumulate=True)},  # 手动创建
-    # ...
-)
-```
-
-### 8. **UntrackedValue** - 未追踪通道
-**使用场景：** 在仓库中未找到实际使用例子
-**创建方式：** 需要手动创建
-**状态：** 理论存在但实际未使用
-
-### 9. **AnyValue** - 任意值通道
-**使用场景：** 在仓库中未找到实际使用例子
-**创建方式：** 需要手动创建
-**状态：** 理论存在但实际未使用
-
-## 使用模式总结
-
-### **用户显式创建的通道：**
-1. **BinaryOperatorAggregate** - 通过 `Annotated[Type, reducer]`
-2. **Topic** - 仅在直接 Pregel API 中手动创建
-
-### **系统自动创建的通道：**
-1. **LastValue** - 默认通道类型
-2. **EphemeralValue** - 输入和分支通道
-3. **LastValueAfterFinish** - 延迟节点分支
-4. **NamedBarrierValue** - 多节点汇聚同步
-5. **NamedBarrierValueAfterFinish** - 延迟节点汇聚同步
-
-### **实际使用频率：**
-1. **高频使用：** LastValue, BinaryOperatorAggregate, EphemeralValue
-2. **中频使用：** NamedBarrierValue, LastValueAfterFinish
-3. **低频使用：** Topic（仅系统内部）
-4. **未使用：** UntrackedValue, AnyValue
-
-## 通道创建机制
-
-### 自动创建流程
-1. **StateGraph._add_schema()** - 解析状态类型
-2. **_get_channels()** - 提取类型注解
-3. **_get_channel()** - 判断通道类型：
-   - 检查 Managed Value
-   - 检查 Channel（如 Topic）
-   - 检查 BinaryOperator（如 add_messages）
-   - 默认创建 LastValue
-
-### 编译时创建
-- **START 通道：** `EphemeralValue(input_schema)`
-- **分支通道：** `EphemeralValue(Any, guard=False)` 或 `LastValueAfterFinish(Any)`
-- **汇聚通道：** `NamedBarrierValue` 或 `NamedBarrierValueAfterFinish`
-
-## 设计哲学
-
-**StateGraph 主要关注状态管理，大部分通道类型都是系统自动管理的，用户只需要关心状态结构和聚合逻辑**。只有在需要特殊聚合行为时，用户才需要显式使用 `Annotated` 注解来指定 reducer 函数。
-
-## 关键发现
-
-1. **Topic 通道在 StateGraph 中几乎不使用** - 仓库中没有通过状态 Schema 注解创建 Topic 的实际例子
-2. **BinaryOperatorAggregate 是用户最常显式创建的通道** - 通过 `add_messages` 等 reducer 函数
-3. **大部分通道都是系统内部自动管理** - 用户无需关心底层通道实现
-4. **StateGraph 和直接 Pregel 的使用场景不同** - StateGraph 专注状态管理，Pregel 专注消息传递
-
-## 实际代码位置
-
-- **通道创建逻辑：** `libs/langgraph/langgraph/graph/state.py:1299-1388`
-- **编译时通道管理：** `libs/langgraph/langgraph/graph/state.py:856-894`
-- **节点附加逻辑：** `libs/langgraph/langgraph/graph/state.py:935-1067`
-- **边处理逻辑：** `libs/langgraph/langgraph/graph/state.py:1038-1062`