lockfile changes

.github/workflows/_integration_test.yml

@@ -3,9 +3,6 @@ name: CLI integration test
 on:
   workflow_call:
 
-permissions:
-  contents: read
-
 jobs:
   build:
     runs-on: ubuntu-latest

.github/workflows/_lint.yml

@@ -8,9 +8,6 @@ on:
         type: string
         description: "From which folder this pipeline executes"
 
-permissions:
-  contents: read
-
 env:
   # This env var allows us to get inline annotations when ruff has complaints.
   RUFF_OUTPUT_FORMAT: github

.github/workflows/_test.yml

@@ -8,9 +8,6 @@ on:
         type: string
         description: "From which folder this pipeline executes"
 
-permissions:
-  contents: read
-
 jobs:
   build:
     runs-on: ubuntu-latest
@@ -61,3 +58,13 @@ jobs:
           # grep will exit non-zero if the target message isn't found,
           # and `set -e` above will cause the step to fail.
           echo "$STATUS" | grep 'nothing to commit, working tree clean'
+
+      - name: Install min version of deps
+        shell: bash
+        working-directory: ${{ inputs.working-directory }}
+        run: uv sync --no-default-groups --resolution lowest-direct --no-sources --force-reinstall
+
+      - name: Run tests with min version of deps
+        shell: bash
+        working-directory: ${{ inputs.working-directory }}
+        run: make test

.github/workflows/_test_langgraph.yml

@@ -3,9 +3,6 @@ name: test
 on:
   workflow_call:
 
-permissions:
-  contents: read
-
 jobs:
   build:
     runs-on: ubuntu-latest
@@ -56,3 +53,13 @@ jobs:
           # grep will exit non-zero if the target message isn't found,
           # and `set -e` above will cause the step to fail.
           echo "$STATUS" | grep 'nothing to commit, working tree clean'
+
+      - name: Install min version of deps
+        shell: bash
+        working-directory: ${{ inputs.working-directory }}
+        run: uv sync --no-default-groups --resolution lowest-direct --no-sources --force-reinstall
+
+      - name: Run tests with min version of deps
+        shell: bash
+        working-directory: ${{ inputs.working-directory }}
+        run: make test

.github/workflows/baseline.yml

@@ -7,9 +7,6 @@ on:
     paths:
       - "libs/**"
 
-permissions:
-  contents: read
-
 jobs:
   benchmark:
     runs-on: ubuntu-latest

.github/workflows/bench.yml

@@ -5,9 +5,6 @@ on:
     paths:
       - "libs/**"
 
-permissions:
-  contents: read
-
 jobs:
   benchmark:
     runs-on: ubuntu-latest

.github/workflows/ci.yml

@@ -6,9 +6,6 @@ on:
     branches: [main]
   pull_request:
 
-permissions:
-  contents: read
-
 # If another push to the same PR or branch happens while this workflow is still running,
 # cancel the earlier run in favor of the next run.
 #

.github/workflows/link_check.yml

@@ -11,9 +11,6 @@ on:
     - cron: "0 5 * * *"
   workflow_dispatch:
 
-permissions:
-  contents: read
-
 jobs:
   markdown-link-check:
     runs-on: ubuntu-latest

.github/workflows/release.yml

@@ -8,9 +8,6 @@ on:
         type: string
         default: "libs/langgraph"
 
-permissions:
-  contents: read
-
 env:
   PYTHON_VERSION: "3.11"
 

.github/workflows/release_js.yml

@@ -3,9 +3,6 @@ name: JS Release
 on:
   workflow_dispatch:
 
-permissions:
-  contents: read
-
 jobs:
   publish:
     # Disallow publishing from branches that aren't `main`.

.github/workflows/run_notebooks.yml

@@ -11,9 +11,6 @@ on:
   schedule:
     - cron: "0 13 * * *"
 
-permissions:
-  contents: read
-
 defaults:
   run:
     working-directory: docs

docs/docs/cloud/concepts/data_storage_and_privacy.md

@@ -1,54 +0,0 @@
-# Data Storage and Privacy
-
-This document describes how data is processed in the LangGraph CLI and the LangGraph Server for both the in-memory server (`langgraph dev`) and the local Docker server (`langgraph up`). It also describes what data is tracked when interacting with the hosted LangGraph Studio frontend.
-
-## CLI
-
-LangGraph **CLI** is the command-line interface for building and running LangGraph applications; see the [CLI guide](../../concepts/langgraph_cli.md) to learn more.
-
-By default, calls to most CLI commands log a single analytics event upon invocation. This helps us better prioritize improvements to the CLI experience. Each telemetry event contains the calling process's OS, OS version, Python version, the CLI version, the command name (`dev`, `up`, `run`, etc.), and booleans representing whether a flag was passed to the command. You can see the full analytics logic [here](https://github.com/langchain-ai/langgraph/blob/main/libs/cli/langgraph_cli/analytics.py). 
-
-You can disable all CLI telemetry by setting `LANGGRAPH_CLI_NO_ANALYTICS=1`.
-
-## LangGraph Server (in-memory & docker)
-
-The [LangGraph Server](../../concepts/langgraph_server.md) provides a durable execution runtime that relies on persisting checkpoints of your application state, long-term memories, thread metadata, assistants, and similar resources to the local file system or a database. Unless you have deliberately customized the storage location, this information is either written to local disk (for `langgraph dev`) or a PostgreSQL database (for `langgraph up` and in all deployments).
-
-### LangSmith Tracing
-
-When running the LangGraph server (either in-memory or in Docker), LangSmith tracing may be enabled to facilitate faster debugging and offer observability of graph state and LLM prompts in production. You can always disable tracing by setting `LANGSMITH_TRACING=false` in your server's runtime environment.
-
-### In-memory development server (`langgraph dev`)
-
-`langgraph dev` runs an [in-memory development server](../../tutorials/langgraph-platform/local-server.md) as a single Python process, designed for quick development and testing. It saves all checkpointing and memory data to disk within a `.langgraph_api` directory in the current working directory. Apart from the telemetry data described in the [CLI](#cli) section, no data leaves the machine unless you have enabled tracing or your graph code explicitly contacts an external service.
-
-### Standalone Container (`langgraph up`)
-
-`langgraph up` builds your local package into a Docker image and runs the server as a [standalone container](../../concepts/deployment_options.md#standalone-container) consisting of three containers: the API server, a PostgreSQL container, and a Redis container. All persistent data (checkpoints, assistants, etc.) are stored in the PostgreSQL database. Redis is used as a pubsub connection for real-time streaming of events. You can encrypt all checkpoints before saving to the database by setting a valid `LANGGRAPH_AES_KEY` environment variable. You can also specify [TTLs](../../how-tos/ttl/configure_ttl.md) for checkpoints and cross-thread memories in `langgraph.json` to control how long data is stored. All persisted threads, memories, and other data can be deleted via the relevant API endpoints.
-
-Additional API calls are made to confirm that the server has a valid license and to track the number of executed runs and tasks. Periodically, the API server validates the provided license key (or API key).
-
-If you've disabled [tracing](#langsmith-tracing), no user data is persisted externally unless your graph code explicitly contacts an external service.
-
-## Studio
-
-[LangGraph Studio](../../concepts/langgraph_studio.md) is a graphical interface for interacting with your LangGraph server. It does not persist any private data (the data you send to your server is not sent to LangSmith). Though the studio interface is served at [smith.langchain.com](https://smith.langchain.com), it is run in your browser and connects directly to your local LangGraph server so that no data needs to be sent to LangSmith.
-
-If you are logged in, LangSmith does collect some usage analytics to help improve studio's user experience. This includes:
-
-- Page visits and navigation patterns
-- User actions (button clicks)
-- Browser type and version
-- Screen resolution and viewport size
-
-Importantly, no application data or code (or other sensitive configuration details) are collected. All of that is stored in the persistence layer of your LangGraph server. When using Studio anonymously, no account creation is required and usage analytics are not collected.
-
-## Quick reference
-
-In summary, you can opt-out of server-side telemetry by turning off CLI analytics and disabling tracing.
-
-| Variable                       | Purpose                   | Default                          |
-| ------------------------------ | ------------------------- | -------------------------------- |
-| `LANGGRAPH_CLI_NO_ANALYTICS=1` | Disable CLI analytics     | Analytics enabled                |
-| `LANGSMITH_API_KEY`            | Enable LangSmith tracing  | Tracing disabled                 |
-| `LANGSMITH_TRACING=false`      | Disable LangSmith tracing | Depends on environment           |

docs/mkdocs.yml

@@ -215,7 +215,6 @@ nav:
           - how-tos/http/custom_middleware.md
           - how-tos/http/custom_routes.md
       - Data management:
-        - cloud/concepts/data_storage_and_privacy.md
         - Add semantic search: cloud/deployment/semantic_search.md
         - Add TTLs: how-tos/ttl/configure_ttl.md
       - Deployment:

libs/langgraph/langgraph/graph/state.py

@@ -25,8 +25,8 @@ from typing import (
 )
 
 from langchain_core.runnables import Runnable, RunnableConfig
-from pydantic import BaseModel, TypeAdapter
-from typing_extensions import Self, TypeAlias, Unpack, is_typeddict
+from pydantic import BaseModel
+from typing_extensions import Self, TypeAlias, Unpack
 
 from langgraph._typing import UNSET, DeprecatedKwargs
 from langgraph.cache.base import BaseCache
@@ -904,20 +904,18 @@ class CompiledStateGraph(
         self.builder = builder
         self.schema_to_mapper = schema_to_mapper
 
-    def get_input_jsonschema(
-        self, config: RunnableConfig | None = None
-    ) -> dict[str, Any]:
-        return _get_json_schema(
+    def get_input_schema(self, config: RunnableConfig | None = None) -> type[BaseModel]:
+        return _get_schema(
             typ=self.builder.input_schema,
             schemas=self.builder.schemas,
             channels=self.builder.channels,
             name=self.get_name("Input"),
         )
 
-    def get_output_jsonschema(
+    def get_output_schema(
         self, config: RunnableConfig | None = None
-    ) -> dict[str, Any]:
-        return _get_json_schema(
+    ) -> type[BaseModel]:
+        return _get_schema(
             typ=self.builder.output_schema,
             schemas=self.builder.schemas,
             channels=self.builder.channels,
@@ -1384,23 +1382,21 @@ def _is_field_managed_value(name: str, typ: type[Any]) -> ManagedValueSpec | Non
     return None
 
 
-def _get_json_schema(
+def _get_schema(
     typ: type,
     schemas: dict,
     channels: dict,
     name: str,
-) -> dict[str, Any]:
+) -> type[BaseModel]:
     if isclass(typ) and issubclass(typ, BaseModel):
-        return typ.model_json_schema()
-    elif is_typeddict(typ):
-        return TypeAdapter(typ).json_schema()
+        return typ
     else:
         keys = list(schemas[typ].keys())
         if len(keys) == 1 and keys[0] == "__root__":
             return create_model(
                 name,
                 root=(channels[keys[0]].UpdateType, None),
-            ).model_json_schema()
+            )
         else:
             return create_model(
                 name,
@@ -1418,7 +1414,7 @@ def _get_json_schema(
                     for k in schemas[typ]
                     if k in channels and isinstance(channels[k], BaseChannel)
                 },
-            ).model_json_schema()
+            )
 
 
 CHANNEL_BRANCH_TO = "branch:to:{}"

libs/langgraph/langgraph/pregel/__init__.py

@@ -771,7 +771,10 @@ class Pregel(PregelProtocol[StateT, InputT, OutputT], Generic[StateT, InputT, Ou
         self, *, include: Sequence[str] | None = None
     ) -> dict[str, Any]:
         schema = self.config_schema(include=include)
-        return schema.model_json_schema()
+        if hasattr(schema, "model_json_schema"):
+            return schema.model_json_schema()
+        else:
+            return schema.schema()
 
     @property
     def InputType(self) -> Any:
@@ -798,7 +801,10 @@ class Pregel(PregelProtocol[StateT, InputT, OutputT], Generic[StateT, InputT, Ou
         self, config: RunnableConfig | None = None
     ) -> dict[str, Any]:
         schema = self.get_input_schema(config)
-        return schema.model_json_schema()
+        if hasattr(schema, "model_json_schema"):
+            return schema.model_json_schema()
+        else:
+            return schema.schema()
 
     @property
     def OutputType(self) -> Any:
@@ -827,7 +833,10 @@ class Pregel(PregelProtocol[StateT, InputT, OutputT], Generic[StateT, InputT, Ou
         self, config: RunnableConfig | None = None
     ) -> dict[str, Any]:
         schema = self.get_output_schema(config)
-        return schema.model_json_schema()
+        if hasattr(schema, "model_json_schema"):
+            return schema.model_json_schema()
+        else:
+            return schema.schema()
 
     @property
     def stream_channels_list(self) -> Sequence[str]:

libs/langgraph/langgraph/utils/fields.py

@@ -128,8 +128,8 @@ def get_enhanced_type_hints(
 
         # Pydantic models
         try:
-            if hasattr(type, "model_fields") and name in type.model_fields:
-                field = type.model_fields[name]
+            if hasattr(type, "__fields__") and name in type.__fields__:
+                field = type.__fields__[name]
 
                 if hasattr(field, "description") and field.description is not None:
                     description = field.description
@@ -163,7 +163,7 @@ def get_update_as_tuples(input: Any, keys: Sequence[str]) -> list[tuple[str, Any
     """Get Pydantic state update as a list of (key, value) tuples."""
     if isinstance(input, BaseModel):
         keep = input.model_fields_set
-        defaults = {k: v.default for k, v in type(input).model_fields.items()}
+        defaults = {k: v.default for k, v in input.model_fields.items()}
     else:
         keep = None
         defaults = {}

libs/langgraph/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph"
-version = "0.5.1"
+version = "0.5.0"
 description = "Building stateful, multi-actor applications with LLMs"
 authors = []
 requires-python = ">=3.9"
@@ -17,7 +17,8 @@ dependencies = [
     "langgraph-sdk>=0.1.42,<0.2.0",
     "langgraph-prebuilt>=0.5.0,<0.6.0",
     "xxhash>=3.5.0",
-    "pydantic>=2.7.4",
+    "pydantic>=2.7.4; python_version < '3.13'",
+    "pydantic>=2.0.0; python_version >= '3.13'",
 ]
 
 [project.urls]

libs/langgraph/tests/__snapshots__/test_pregel.ambr

@@ -89,10 +89,10 @@
   '''
 # ---
 # name: test_conditional_entrypoint_graph_state
-  '{"properties": {"input": {"title": "Input", "type": "string"}, "output": {"title": "Output", "type": "string"}, "steps": {"items": {"type": "string"}, "title": "Steps", "type": "array"}}, "title": "AgentState", "type": "object"}'
+  '{"properties": {"input": {"default": null, "title": "Input", "type": "string"}, "output": {"default": null, "title": "Output", "type": "string"}, "steps": {"default": null, "items": {"type": "string"}, "title": "Steps", "type": "array"}}, "title": "LangGraphInput", "type": "object"}'
 # ---
 # name: test_conditional_entrypoint_graph_state.1
-  '{"properties": {"input": {"title": "Input", "type": "string"}, "output": {"title": "Output", "type": "string"}, "steps": {"items": {"type": "string"}, "title": "Steps", "type": "array"}}, "title": "AgentState", "type": "object"}'
+  '{"properties": {"input": {"default": null, "title": "Input", "type": "string"}, "output": {"default": null, "title": "Output", "type": "string"}, "steps": {"default": null, "items": {"type": "string"}, "title": "Steps", "type": "array"}}, "title": "LangGraphOutput", "type": "object"}'
 # ---
 # name: test_conditional_entrypoint_graph_state.2
   '''
@@ -178,10 +178,10 @@
   '''
 # ---
 # name: test_conditional_entrypoint_to_multiple_state_graph
-  '{"properties": {"locations": {"items": {"type": "string"}, "title": "Locations", "type": "array"}, "results": {"items": {"type": "string"}, "title": "Results", "type": "array"}}, "required": ["locations", "results"], "title": "OverallState", "type": "object"}'
+  '{"properties": {"locations": {"items": {"type": "string"}, "title": "Locations", "type": "array"}, "results": {"items": {"type": "string"}, "title": "Results", "type": "array"}}, "required": ["locations", "results"], "title": "LangGraphInput", "type": "object"}'
 # ---
 # name: test_conditional_entrypoint_to_multiple_state_graph.1
-  '{"properties": {"locations": {"items": {"type": "string"}, "title": "Locations", "type": "array"}, "results": {"items": {"type": "string"}, "title": "Results", "type": "array"}}, "required": ["locations", "results"], "title": "OverallState", "type": "object"}'
+  '{"properties": {"locations": {"items": {"type": "string"}, "title": "Locations", "type": "array"}, "results": {"items": {"type": "string"}, "title": "Results", "type": "array"}}, "required": ["locations", "results"], "title": "LangGraphOutput", "type": "object"}'
 # ---
 # name: test_conditional_entrypoint_to_multiple_state_graph.2
   '''
@@ -917,10 +917,10 @@
   '{"$defs": {"Config": {"properties": {"tools": {"items": {"type": "string"}, "title": "Tools", "type": "array"}}, "title": "Config", "type": "object"}}, "properties": {"configurable": {"$ref": "#/$defs/Config", "default": null}}, "title": "LangGraphConfig", "type": "object"}'
 # ---
 # name: test_state_graph_w_config_inherited_state_keys.1
-  '{"$defs": {"AgentAction": {"description": "Represents a request to execute an action by an agent.\\n\\nThe action consists of the name of the tool to execute and the input to pass\\nto the tool. The log is used to pass along extra information about the action.", "properties": {"tool": {"title": "Tool", "type": "string"}, "tool_input": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}], "title": "Tool Input"}, "log": {"title": "Log", "type": "string"}, "type": {"const": "AgentAction", "default": "AgentAction", "title": "Type", "type": "string"}}, "required": ["tool", "tool_input", "log"], "title": "AgentAction", "type": "object"}, "AgentFinish": {"description": "Final return value of an ActionAgent.\\n\\nAgents return an AgentFinish when they have reached a stopping condition.", "properties": {"return_values": {"additionalProperties": true, "title": "Return Values", "type": "object"}, "log": {"title": "Log", "type": "string"}, "type": {"const": "AgentFinish", "default": "AgentFinish", "title": "Type", "type": "string"}}, "required": ["return_values", "log"], "title": "AgentFinish", "type": "object"}}, "properties": {"input": {"title": "Input", "type": "string"}, "agent_outcome": {"anyOf": [{"$ref": "#/$defs/AgentAction"}, {"$ref": "#/$defs/AgentFinish"}, {"type": "null"}], "title": "Agent Outcome"}, "intermediate_steps": {"items": {"maxItems": 2, "minItems": 2, "prefixItems": [{"$ref": "#/$defs/AgentAction"}, {"type": "string"}], "type": "array"}, "title": "Intermediate Steps", "type": "array"}}, "required": ["input", "agent_outcome"], "title": "AgentState", "type": "object"}'
+  '{"$defs": {"AgentAction": {"description": "Represents a request to execute an action by an agent.\\n\\nThe action consists of the name of the tool to execute and the input to pass\\nto the tool. The log is used to pass along extra information about the action.", "properties": {"tool": {"title": "Tool", "type": "string"}, "tool_input": {"anyOf": [{"type": "string"}, {"type": "object"}], "title": "Tool Input"}, "log": {"title": "Log", "type": "string"}, "type": {"const": "AgentAction", "default": "AgentAction", "enum": ["AgentAction"], "title": "Type", "type": "string"}}, "required": ["tool", "tool_input", "log"], "title": "AgentAction", "type": "object"}, "AgentFinish": {"description": "Final return value of an ActionAgent.\\n\\nAgents return an AgentFinish when they have reached a stopping condition.", "properties": {"return_values": {"title": "Return Values", "type": "object"}, "log": {"title": "Log", "type": "string"}, "type": {"const": "AgentFinish", "default": "AgentFinish", "enum": ["AgentFinish"], "title": "Type", "type": "string"}}, "required": ["return_values", "log"], "title": "AgentFinish", "type": "object"}}, "properties": {"input": {"title": "Input", "type": "string"}, "agent_outcome": {"anyOf": [{"$ref": "#/$defs/AgentAction"}, {"$ref": "#/$defs/AgentFinish"}, {"type": "null"}], "default": null, "title": "Agent Outcome"}, "intermediate_steps": {"default": null, "items": {"maxItems": 2, "minItems": 2, "prefixItems": [{"$ref": "#/$defs/AgentAction"}, {"type": "string"}], "type": "array"}, "title": "Intermediate Steps", "type": "array"}}, "required": ["input"], "title": "LangGraphInput", "type": "object"}'
 # ---
 # name: test_state_graph_w_config_inherited_state_keys.2
-  '{"$defs": {"AgentAction": {"description": "Represents a request to execute an action by an agent.\\n\\nThe action consists of the name of the tool to execute and the input to pass\\nto the tool. The log is used to pass along extra information about the action.", "properties": {"tool": {"title": "Tool", "type": "string"}, "tool_input": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}], "title": "Tool Input"}, "log": {"title": "Log", "type": "string"}, "type": {"const": "AgentAction", "default": "AgentAction", "title": "Type", "type": "string"}}, "required": ["tool", "tool_input", "log"], "title": "AgentAction", "type": "object"}, "AgentFinish": {"description": "Final return value of an ActionAgent.\\n\\nAgents return an AgentFinish when they have reached a stopping condition.", "properties": {"return_values": {"additionalProperties": true, "title": "Return Values", "type": "object"}, "log": {"title": "Log", "type": "string"}, "type": {"const": "AgentFinish", "default": "AgentFinish", "title": "Type", "type": "string"}}, "required": ["return_values", "log"], "title": "AgentFinish", "type": "object"}}, "properties": {"input": {"title": "Input", "type": "string"}, "agent_outcome": {"anyOf": [{"$ref": "#/$defs/AgentAction"}, {"$ref": "#/$defs/AgentFinish"}, {"type": "null"}], "title": "Agent Outcome"}, "intermediate_steps": {"items": {"maxItems": 2, "minItems": 2, "prefixItems": [{"$ref": "#/$defs/AgentAction"}, {"type": "string"}], "type": "array"}, "title": "Intermediate Steps", "type": "array"}}, "required": ["input", "agent_outcome"], "title": "AgentState", "type": "object"}'
+  '{"$defs": {"AgentAction": {"description": "Represents a request to execute an action by an agent.\\n\\nThe action consists of the name of the tool to execute and the input to pass\\nto the tool. The log is used to pass along extra information about the action.", "properties": {"tool": {"title": "Tool", "type": "string"}, "tool_input": {"anyOf": [{"type": "string"}, {"type": "object"}], "title": "Tool Input"}, "log": {"title": "Log", "type": "string"}, "type": {"const": "AgentAction", "default": "AgentAction", "enum": ["AgentAction"], "title": "Type", "type": "string"}}, "required": ["tool", "tool_input", "log"], "title": "AgentAction", "type": "object"}, "AgentFinish": {"description": "Final return value of an ActionAgent.\\n\\nAgents return an AgentFinish when they have reached a stopping condition.", "properties": {"return_values": {"title": "Return Values", "type": "object"}, "log": {"title": "Log", "type": "string"}, "type": {"const": "AgentFinish", "default": "AgentFinish", "enum": ["AgentFinish"], "title": "Type", "type": "string"}}, "required": ["return_values", "log"], "title": "AgentFinish", "type": "object"}}, "properties": {"input": {"title": "Input", "type": "string"}, "agent_outcome": {"anyOf": [{"$ref": "#/$defs/AgentAction"}, {"$ref": "#/$defs/AgentFinish"}, {"type": "null"}], "default": null, "title": "Agent Outcome"}, "intermediate_steps": {"default": null, "items": {"maxItems": 2, "minItems": 2, "prefixItems": [{"$ref": "#/$defs/AgentAction"}, {"type": "string"}], "type": "array"}, "title": "Intermediate Steps", "type": "array"}}, "required": ["input"], "title": "LangGraphOutput", "type": "object"}'
 # ---
 # name: test_xray_bool
   '''

libs/langgraph/tests/test_large_cases.py

@@ -569,8 +569,8 @@ def test_conditional_state_graph(
     app = workflow.compile()
 
     if isinstance(sync_checkpointer, InMemorySaver):
-        assert json.dumps(app.get_input_jsonschema()) == snapshot
-        assert json.dumps(app.get_output_jsonschema()) == snapshot
+        assert json.dumps(app.get_input_schema().model_json_schema()) == snapshot
+        assert json.dumps(app.get_output_schema().model_json_schema()) == snapshot
         assert json.dumps(app.get_graph().to_json(), indent=2) == snapshot
         assert app.get_graph().draw_mermaid(with_styles=False) == snapshot
 
@@ -1302,8 +1302,8 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
 
     app = create_react_agent(model, tools)
 
-    assert json.dumps(app.get_input_jsonschema()) == snapshot
-    assert json.dumps(app.get_output_jsonschema()) == snapshot
+    assert json.dumps(app.get_input_schema().model_json_schema()) == snapshot
+    assert json.dumps(app.get_output_schema().model_json_schema()) == snapshot
     assert json.dumps(app.get_graph().to_json(), indent=2) == snapshot
     assert app.get_graph().draw_mermaid(with_styles=False) == snapshot
 
@@ -2483,8 +2483,8 @@ def test_message_graph(
     app = workflow.compile()
 
     if isinstance(sync_checkpointer, InMemorySaver):
-        assert json.dumps(app.get_input_jsonschema()) == snapshot
-        assert json.dumps(app.get_output_jsonschema()) == snapshot
+        assert json.dumps(app.get_input_schema().model_json_schema()) == snapshot
+        assert json.dumps(app.get_output_schema().model_json_schema()) == snapshot
         assert json.dumps(app.get_graph().to_json(), indent=2) == snapshot
         assert app.get_graph().draw_mermaid(with_styles=False) == snapshot
 

libs/langgraph/tests/test_pregel.py

@@ -1723,8 +1723,8 @@ def test_conditional_entrypoint_to_multiple_state_graph(
 
     app = workflow.compile()
 
-    assert json.dumps(app.get_input_jsonschema()) == snapshot
-    assert json.dumps(app.get_output_jsonschema()) == snapshot
+    assert json.dumps(app.get_input_schema().model_json_schema()) == snapshot
+    assert json.dumps(app.get_output_schema().model_json_schema()) == snapshot
     assert json.dumps(app.get_graph().to_json(), indent=2) == snapshot
     assert app.get_graph().draw_mermaid(with_styles=False) == snapshot
 
@@ -1848,8 +1848,8 @@ def test_state_graph_w_config_inherited_state_keys(snapshot: SnapshotAssertion)
     app = builder.compile()
 
     assert json.dumps(app.config_schema().model_json_schema()) == snapshot
-    assert json.dumps(app.get_input_jsonschema()) == snapshot
-    assert json.dumps(app.get_output_jsonschema()) == snapshot
+    assert json.dumps(app.get_input_schema().model_json_schema()) == snapshot
+    assert json.dumps(app.get_output_schema().model_json_schema()) == snapshot
 
     assert builder.channels.keys() == {"input", "agent_outcome", "intermediate_steps"}
 
@@ -1912,8 +1912,8 @@ def test_conditional_entrypoint_graph_state(snapshot: SnapshotAssertion) -> None
 
     app = workflow.compile()
 
-    assert json.dumps(app.get_input_jsonschema()) == snapshot
-    assert json.dumps(app.get_output_jsonschema()) == snapshot
+    assert json.dumps(app.get_input_schema().model_json_schema()) == snapshot
+    assert json.dumps(app.get_output_schema().model_json_schema()) == snapshot
     assert json.dumps(app.get_graph().to_json(), indent=2) == snapshot
     assert app.get_graph().draw_mermaid(with_styles=False) == snapshot
 
@@ -2507,8 +2507,8 @@ def test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydantic2(
 
     if isinstance(sync_checkpointer, InMemorySaver):
         assert app.get_graph().draw_mermaid(with_styles=False) == snapshot
-        assert app.get_input_jsonschema() == snapshot
-        assert app.get_output_jsonschema() == snapshot
+        assert app.get_input_schema().model_json_schema() == snapshot
+        assert app.get_output_schema().model_json_schema() == snapshot
 
     with pytest.raises(ValidationError):
         app.invoke({"query": {}})
@@ -6549,7 +6549,7 @@ def test_entrypoint_output_schema_with_return_and_save() -> None:
     def foo2(inputs, *, previous: Any) -> entrypoint.final:
         return entrypoint.final(value="foo", save=1)
 
-    assert foo2.get_output_jsonschema() == {
+    assert foo2.get_output_schema().model_json_schema() == {
         "title": "LangGraphOutput",
     }
 
@@ -6557,7 +6557,7 @@ def test_entrypoint_output_schema_with_return_and_save() -> None:
     def foo(inputs, *, previous: Any) -> entrypoint.final[str, int]:
         return entrypoint.final(value="foo", save=1)
 
-    assert foo.get_output_jsonschema() == {
+    assert foo.get_output_schema().model_json_schema() == {
         "title": "LangGraphOutput",
         "type": "string",
     }
@@ -6584,7 +6584,7 @@ def test_entrypoint_with_return_and_save(
         previous = previous or []
         return entrypoint.final(value=len(previous), save=previous + [msg])
 
-    assert foo.get_output_jsonschema() == {
+    assert foo.get_output_schema().model_json_schema() == {
         "title": "LangGraphOutput",
         "type": "integer",
     }

libs/langgraph/tests/test_pregel_async.py

@@ -4493,8 +4493,8 @@ async def test_in_one_fan_out_state_graph_waiting_edge_custom_state_class_pydant
 
     if isinstance(async_checkpointer, InMemorySaver):
         assert app.get_graph().draw_mermaid(with_styles=False) == snapshot
-        assert app.get_input_jsonschema() == snapshot
-        assert app.get_output_jsonschema() == snapshot
+        assert app.get_input_schema().model_json_schema() == snapshot
+        assert app.get_output_schema().model_json_schema() == snapshot
 
     with pytest.raises(ValidationError):
         await app.ainvoke({"query": {}})

libs/langgraph/tests/test_state.py

@@ -163,12 +163,13 @@ def test_state_schema_optional_values(total_: bool):
         expected_required = set()
         expected_optional = {"val2", "val1"}
     else:
-        expected_required = {"val1", "val2"}
-        expected_optional = set()
+        expected_required = {"val1"}
+
+        expected_optional = {"val2"}
 
     # The others should always have precedence based on the required annotation
-    expected_required |= {"val0a", "val0b", "val3", "val5"}
-    expected_optional |= {"val4", "val6"}
+    expected_required |= {"val0a", "val3", "val5"}
+    expected_optional |= {"val0b", "val4", "val6"}
 
     assert set(json_schema.get("required", set())) == expected_required
     assert (
@@ -181,11 +182,11 @@ def test_state_schema_optional_values(total_: bool):
         expected_required = set()
         expected_optional = {"out_val2", "out_val1"}
     else:
-        expected_required = {"out_val1", "out_val2"}
-        expected_optional = set()
+        expected_required = {"out_val1"}
+        expected_optional = {"out_val2"}
 
-    expected_required |= {"val0a", "val0b", "out_val3", "out_val5"}
-    expected_optional |= {"out_val4", "out_val6"}
+    expected_required |= {"val0a", "out_val3", "out_val5"}
+    expected_optional |= {"val0b", "out_val4", "out_val6"}
 
     assert set(output_schema.get("required", set())) == expected_required
     assert (

libs/langgraph/uv.lock

@@ -1201,7 +1201,7 @@ wheels = [
 
 [[package]]
 name = "langgraph"
-version = "0.5.1"
+version = "0.5.0"
 source = { editable = "." }
 dependencies = [
     { name = "langchain-core" },
@@ -1246,7 +1246,8 @@ requires-dist = [
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
     { name = "langgraph-prebuilt", editable = "../prebuilt" },
     { name = "langgraph-sdk", editable = "../sdk-py" },
-    { name = "pydantic", specifier = ">=2.7.4" },
+    { name = "pydantic", marker = "python_full_version < '3.13'", specifier = ">=2.7.4" },
+    { name = "pydantic", marker = "python_full_version >= '3.13'", specifier = ">=2.0.0" },
     { name = "xxhash", specifier = ">=3.5.0" },
 ]
 
@@ -2166,126 +2167,103 @@ wheels = [
 
 [[package]]
 name = "pydantic"
-version = "2.11.7"
+version = "2.9.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "annotated-types" },
     { name = "pydantic-core" },
     { name = "typing-extensions" },
-    { name = "typing-inspection" },
 ]
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libs/prebuilt/uv.lock

@@ -2,7 +2,8 @@ version = 1
 revision = 2
 requires-python = ">=3.9"
 resolution-markers = [
-    "python_full_version >= '3.12.4'",
+    "python_full_version >= '3.13'",
+    "python_full_version >= '3.12.4' and python_full_version < '3.13'",
     "python_full_version < '3.12.4'",
 ]
 
@@ -320,7 +321,7 @@ wheels = [
 
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-version = "0.5.1"
+version = "0.5.0"
 source = { editable = "../langgraph" }
 dependencies = [
     { name = "langchain-core" },
@@ -337,7 +338,8 @@ requires-dist = [
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     { name = "langgraph-prebuilt", editable = "." },
     { name = "langgraph-sdk", editable = "../sdk-py" },
-    { name = "pydantic", specifier = ">=2.7.4" },
+    { name = "pydantic", marker = "python_full_version < '3.13'", specifier = ">=2.7.4" },
+    { name = "pydantic", marker = "python_full_version >= '3.13'", specifier = ">=2.0.0" },
     { name = "xxhash", specifier = ">=3.5.0" },
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