experimental stop when

.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/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

@@ -62,12 +62,7 @@ jobs:
         working-directory: ${{ inputs.working-directory }}
         run: |
           PKG_NAME=$(grep -m 1 "^name = " pyproject.toml | cut -d '"' -f 2)
-          # sdk-py uses dynamic versioning from langgraph_sdk/__init__.py
-          if [ "$PKG_NAME" = "langgraph-sdk" ]; then
-            VERSION=$(grep -m 1 '^__version__' langgraph_sdk/__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/agents/multi-agent.md

@@ -367,13 +367,13 @@ To implement handoffs with `createReactAgent`, you need to:
 
 3.  Define a parent graph that contains individual agents as nodes:
 
-    ```typescript
-    import { StateGraph, MessagesZodState } from "@langchain/langgraph";
-    const multiAgentGraph = new StateGraph(MessagesZodState)
-      .addNode("flight_assistant", flightAssistant)
-      .addNode("hotel_assistant", hotelAssistant)
-      // ...
-    ```
+        ```typescript
+        import { StateGraph, MessagesZodState } from "@langchain/langgraph";
+        const multiAgentGraph = new StateGraph(MessagesZodState)
+          .addNode("flight_assistant", flightAssistant)
+          .addNode("hotel_assistant", hotelAssistant)
+          // ...
+        ```
 
     :::
 
@@ -619,8 +619,7 @@ for await (const chunk of multiAgentGraph.stream({
 3. Name of the agent or node to hand off to.
 4. Take the agent's messages and **add** them to the parent's **state** as part of the handoff. The next agent will see the parent state.
 5. Indicate to LangGraph that we need to navigate to agent node in a **parent** multi-agent graph.
-
-:::
+   :::
 
 !!! Note
 

docs/docs/concepts/mcp.md

@@ -6,14 +6,7 @@
 
 Install the `langchain-mcp-adapters` library to use MCP tools in LangGraph:
 
-:::python
 ```bash
 pip install langchain-mcp-adapters
 ```
-:::
 
-:::js
-```bash
-npm install @langchain/mcp-adapters
-```
-:::

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/docs/how-tos/multi_agent.md

@@ -22,7 +22,6 @@ To set up communication between the agents in a multi-agent system you can use [
 
 To implement handoffs, you can return `Command` objects from your agent nodes or tools:
 
-:::python
 ```python
 from typing import Annotated
 from langchain_core.tools import tool, InjectedToolCallId
@@ -74,109 +73,25 @@ def create_handoff_tool(*, agent_name: str, description: str | None = None):
         commands = [tools_by_name[tool_call["name"]].invoke(tool_call) for tool_call in tool_calls]
         return commands
     ```
-:::
-
-:::js
-```typescript
-import { tool } from "@langchain/core/tools";
-import { Command, MessagesZodState } from "@langchain/langgraph";
-import { z } from "zod";
-
-function createHandoffTool({
-  agentName,
-  description,
-}: {
-  agentName: string;
-  description?: string;
-}) {
-  const name = `transfer_to_${agentName}`;
-  const toolDescription = description || `Transfer to ${agentName}`;
-
-  return tool(
-    async (_, config) => {
-      // (1)!
-      const state = config.state;
-      const toolCallId = config.toolCall.id;
-
-      const toolMessage = {
-        role: "tool" as const,
-        content: `Successfully transferred to ${agentName}`,
-        name: name,
-        tool_call_id: toolCallId,
-      };
-
-      return new Command({
-        // (3)!
-        goto: agentName,
-        // (4)!
-        update: { messages: [...state.messages, toolMessage] },
-        // (5)!
-        graph: Command.PARENT,
-      });
-    },
-    {
-      name,
-      description: toolDescription,
-      schema: z.object({}),
-    }
-  );
-}
-```
-
-1. Access the [state](../concepts/low_level.md#state) of the agent that is calling the handoff tool through the `config` parameter.
-2. The `Command` primitive allows specifying a state update and a node transition as a single operation, making it useful for implementing handoffs.
-3. Name of the agent or node to hand off to.
-4. Take the agent's messages and **add** them to the parent's **state** as part of the handoff. The next agent will see the parent state.
-5. Indicate to LangGraph that we need to navigate to agent node in a **parent** multi-agent graph.
-
-!!! tip
-
-    If you want to use tools that return `Command`, you can either use prebuilt @[`create_react_agent`][create_react_agent] / @[`ToolNode`][ToolNode] components, or implement your own tool-executing node that collects `Command` objects returned by the tools and returns a list of them, e.g.:
-    
-    ```typescript
-    const callTools = async (state) => {
-      // ...
-      const commands = await Promise.all(
-        toolCalls.map(toolCall => toolsByName[toolCall.name].invoke(toolCall))
-      );
-      return commands;
-    };
-    ```
-:::
 
 !!! Important
 
     This handoff implementation assumes that:
     
-    - each agent receives overall message history (across all agents) in the multi-agent system as its input. If you want more control over agent inputs, see [this section](#control-agent-inputs)
-    - each agent outputs its internal messages history to the overall message history of the multi-agent system. If you want more control over **how agent outputs are added**, wrap the agent in a separate node function:
+      - each agent receives overall message history (across all agents) in the multi-agent system as its input. If you want more control over agent inputs, see [this section](#control-agent-inputs)
+      - each agent outputs its internal messages history to the overall message history of the multi-agent system. If you want more control over **how agent outputs are added**, wrap the agent in a separate node function:
 
-      :::python
-      ```python
-      def call_hotel_assistant(state):
-          # return agent's final response,
-          # excluding inner monologue
-          response = hotel_assistant.invoke(state)
-          # highlight-next-line
-          return {"messages": response["messages"][-1]}
-      ```
-      :::
-
-      :::js
-      ```typescript
-      const callHotelAssistant = async (state) => {
-        // return agent's final response,
-        // excluding inner monologue
-        const response = await hotelAssistant.invoke(state);
-        // highlight-next-line
-        return { messages: [response.messages.at(-1)] };
-      };
-      ```
-      :::
+        ```python
+        def call_hotel_assistant(state):
+            # return agent's final response,
+            # excluding inner monologue
+            response = hotel_assistant.invoke(state)
+            # highlight-next-line
+            return {"messages": response["messages"][-1]}
+        ```
 
 ### Control agent inputs
 
-:::python
 You can use the @[`Send()`][Send] primitive to directly send data to the worker agents during the handoff. For example, you can request that the calling agent populate a task description for the next agent:
 
 ```python
@@ -214,63 +129,6 @@ def create_task_description_handoff_tool(
 
     return handoff_tool
 ```
-:::
-
-:::js
-You can use the @[`Send()`][Send] primitive to directly send data to the worker agents during the handoff. For example, you can request that the calling agent populate a task description for the next agent:
-
-```typescript
-import { tool } from "@langchain/core/tools";
-import { Command, Send, MessagesZodState } from "@langchain/langgraph";
-import { z } from "zod";
-
-function createTaskDescriptionHandoffTool({
-  agentName,
-  description,
-}: {
-  agentName: string;
-  description?: string;
-}) {
-  const name = `transfer_to_${agentName}`;
-  const toolDescription = description || `Ask ${agentName} for help.`;
-
-  return tool(
-    async (
-      { taskDescription },
-      config
-    ) => {
-      const state = config.state;
-      
-      const taskDescriptionMessage = {
-        role: "user" as const,
-        content: taskDescription,
-      };
-      const agentInput = {
-        ...state,
-        messages: [taskDescriptionMessage],
-      };
-      
-      return new Command({
-        // highlight-next-line
-        goto: [new Send(agentName, agentInput)],
-        graph: Command.PARENT,
-      });
-    },
-    {
-      name,
-      description: toolDescription,
-      schema: z.object({
-        taskDescription: z
-          .string()
-          .describe(
-            "Description of what the next agent should do, including all of the relevant context."
-          ),
-      }),
-    }
-  );
-}
-```
-:::
 
 See the multi-agent [supervisor](../tutorials/multi_agent/agent_supervisor.md#4-create-delegation-tasks) example for a full example of using @[`Send()`][Send] in handoffs.
 
@@ -278,7 +136,6 @@ See the multi-agent [supervisor](../tutorials/multi_agent/agent_supervisor.md#4-
 
 You can use handoffs in any agents built with LangGraph. We recommend using the prebuilt [agent](../agents/overview.md) or [`ToolNode`](./tool-calling.md#toolnode), as they natively support handoffs tools returning `Command`. Below is an example of how you can implement a multi-agent system for booking travel using handoffs:
 
-:::python
 ```python
 from langgraph.prebuilt import create_react_agent
 from langgraph.graph import StateGraph, START, MessagesState
@@ -319,65 +176,9 @@ multi_agent_graph = (
     .compile()
 )
 ```
-:::
-
-:::js
-```typescript
-import { createReactAgent } from "@langchain/langgraph/prebuilt";
-import { StateGraph, START, MessagesZodState } from "@langchain/langgraph";
-import { z } from "zod";
-
-function createHandoffTool({
-  agentName,
-  description,
-}: {
-  agentName: string;
-  description?: string;
-}) {
-  // same implementation as above
-  // ...
-  return new Command(/* ... */);
-}
-
-// Handoffs
-const transferToHotelAssistant = createHandoffTool({
-  agentName: "hotel_assistant",
-});
-const transferToFlightAssistant = createHandoffTool({
-  agentName: "flight_assistant",
-});
-
-// Define agents
-const flightAssistant = createReactAgent({
-  llm: model,
-  // highlight-next-line
-  tools: [/* ... */, transferToHotelAssistant],
-  // highlight-next-line
-  name: "flight_assistant",
-});
-
-const hotelAssistant = createReactAgent({
-  llm: model,
-  // highlight-next-line
-  tools: [/* ... */, transferToFlightAssistant],
-  // highlight-next-line
-  name: "hotel_assistant",
-});
-
-// Define multi-agent graph
-const multiAgentGraph = new StateGraph(MessagesZodState)
-  // highlight-next-line
-  .addNode("flight_assistant", flightAssistant)
-  // highlight-next-line
-  .addNode("hotel_assistant", hotelAssistant)
-  .addEdge(START, "flight_assistant")
-  .compile();
-```
-:::
 
 ??? example "Full example: Multi-agent system for booking travel"
 
-    :::python
     ```python
     from typing import Annotated
     from langchain_core.messages import convert_to_messages
@@ -522,183 +323,6 @@ const multiAgentGraph = new StateGraph(MessagesZodState)
     3. Name of the agent or node to hand off to.
     4. Take the agent's messages and **add** them to the parent's **state** as part of the handoff. The next agent will see the parent state.
     5. Indicate to LangGraph that we need to navigate to agent node in a **parent** multi-agent graph.
-    :::
-
-    :::js
-    ```typescript
-    import { tool } from "@langchain/core/tools";
-    import { createReactAgent } from "@langchain/langgraph/prebuilt";
-    import { StateGraph, START, MessagesZodState, Command } from "@langchain/langgraph";
-    import { ChatAnthropic } from "@langchain/anthropic";
-    import { isBaseMessage } from "@langchain/core/messages";
-    import { z } from "zod";
-
-    // We'll use a helper to render the streamed agent outputs nicely
-    const prettyPrintMessages = (update: Record<string, any>) => {
-      // Handle tuple case with namespace
-      if (Array.isArray(update)) {
-        const [ns, updateData] = update;
-        // Skip parent graph updates in the printouts
-        if (ns.length === 0) {
-          return;
-        }
-
-        const graphId = ns[ns.length - 1].split(":")[0];
-        console.log(`Update from subgraph ${graphId}:\n`);
-        update = updateData;
-      }
-
-      for (const [nodeName, updateValue] of Object.entries(update)) {
-        console.log(`Update from node ${nodeName}:\n`);
-
-        const messages = updateValue.messages || [];
-        for (const message of messages) {
-          if (isBaseMessage(message)) {
-            const textContent =
-              typeof message.content === "string"
-                ? message.content
-                : JSON.stringify(message.content);
-            console.log(`${message.getType()}: ${textContent}`);
-          }
-        }
-        console.log("\n");
-      }
-    };
-
-    function createHandoffTool({
-      agentName,
-      description,
-    }: {
-      agentName: string;
-      description?: string;
-    }) {
-      const name = `transfer_to_${agentName}`;
-      const toolDescription = description || `Transfer to ${agentName}`;
-
-      return tool(
-        async (_, config) => {
-          // highlight-next-line
-          const state = config.state; // (1)!
-          const toolCallId = config.toolCall.id;
-
-          const toolMessage = {
-            role: "tool" as const,
-            content: `Successfully transferred to ${agentName}`,
-            name: name,
-            tool_call_id: toolCallId,
-          };
-
-          return new Command({
-            // highlight-next-line
-            goto: agentName, // (3)!
-            // highlight-next-line
-            update: { messages: [...state.messages, toolMessage] }, // (4)!
-            // highlight-next-line
-            graph: Command.PARENT, // (5)!
-          });
-        },
-        {
-          name,
-          description: toolDescription,
-          schema: z.object({}),
-        }
-      );
-    }
-
-    // Handoffs
-    const transferToHotelAssistant = createHandoffTool({
-      agentName: "hotel_assistant",
-      description: "Transfer user to the hotel-booking assistant.",
-    });
-
-    const transferToFlightAssistant = createHandoffTool({
-      agentName: "flight_assistant",
-      description: "Transfer user to the flight-booking assistant.",
-    });
-
-    // Simple agent tools
-    const bookHotel = tool(
-      async ({ hotelName }) => {
-        return `Successfully booked a stay at ${hotelName}.`;
-      },
-      {
-        name: "book_hotel",
-        description: "Book a hotel",
-        schema: z.object({
-          hotelName: z.string(),
-        }),
-      }
-    );
-
-    const bookFlight = tool(
-      async ({ fromAirport, toAirport }) => {
-        return `Successfully booked a flight from ${fromAirport} to ${toAirport}.`;
-      },
-      {
-        name: "book_flight",
-        description: "Book a flight",
-        schema: z.object({
-          fromAirport: z.string(),
-          toAirport: z.string(),
-        }),
-      }
-    );
-
-    const model = new ChatAnthropic({
-      model: "claude-3-5-sonnet-latest",
-    });
-
-    // Define agents
-    const flightAssistant = createReactAgent({
-      llm: model,
-      // highlight-next-line
-      tools: [bookFlight, transferToHotelAssistant],
-      prompt: "You are a flight booking assistant",
-      // highlight-next-line
-      name: "flight_assistant",
-    });
-
-    const hotelAssistant = createReactAgent({
-      llm: model,
-      // highlight-next-line
-      tools: [bookHotel, transferToFlightAssistant],
-      prompt: "You are a hotel booking assistant",
-      // highlight-next-line
-      name: "hotel_assistant",
-    });
-
-    // Define multi-agent graph
-    const multiAgentGraph = new StateGraph(MessagesZodState)
-      .addNode("flight_assistant", flightAssistant)
-      .addNode("hotel_assistant", hotelAssistant)
-      .addEdge(START, "flight_assistant")
-      .compile();
-
-    // Run the multi-agent graph
-    const stream = await multiAgentGraph.stream(
-      {
-        messages: [
-          {
-            role: "user",
-            content: "book a flight from BOS to JFK and a stay at McKittrick Hotel",
-          },
-        ],
-      },
-      // highlight-next-line
-      { subgraphs: true }
-    );
-
-    for await (const chunk of stream) {
-      prettyPrintMessages(chunk);
-    }
-    ```
-
-    1. Access agent's state
-    2. The `Command` primitive allows specifying a state update and a node transition as a single operation, making it useful for implementing handoffs.
-    3. Name of the agent or node to hand off to.
-    4. Take the agent's messages and **add** them to the parent's **state** as part of the handoff. The next agent will see the parent state.
-    5. Indicate to LangGraph that we need to navigate to agent node in a **parent** multi-agent graph.
-    :::
 
 ## Multi-turn conversation
 
@@ -709,7 +333,6 @@ The agents can then be implemented as nodes in a graph that executes agent steps
 1. **Wait for user input** to continue the conversation, or  
 2. **Route to another agent** (or back to itself, such as in a loop) via a [handoff](#handoffs)
 
-:::python
 ```python
 def human(state) -> Command[Literal["agent", "another_agent"]]:
     """A node for collecting user input."""
@@ -737,44 +360,6 @@ def agent(state) -> Command[Literal["agent", "another_agent", "human"]]:
     else:
         return Command(goto="human") # Go to human node
 ```
-:::
-
-:::js
-```typescript
-import { interrupt, Command } from "@langchain/langgraph";
-
-function human(state: MessagesState): Command {
-  const userInput: string = interrupt("Ready for user input.");
-
-  // Determine the active agent
-  const activeAgent = /* ... */;
-
-  return new Command({
-    update: {
-      messages: [{
-        role: "human",
-        content: userInput,
-      }]
-    },
-    goto: activeAgent,
-  });
-}
-
-function agent(state: MessagesState): Command {
-  // The condition for routing/halting can be anything, e.g. LLM tool call / structured output, etc.
-  const goto = getNextAgent(/* ... */); // 'agent' / 'anotherAgent'
-
-  if (goto) {
-    return new Command({
-      goto,
-      update: { myStateKey: "myStateValue" }
-    });
-  }
-
-  return new Command({ goto: "human" });
-}
-```
-:::
 
 ??? example "Full example: multi-agent system for travel recommendations"
 
@@ -785,7 +370,6 @@ function agent(state: MessagesState): Command {
     * travel_advisor: can help with travel destination recommendations. Can ask hotel_advisor for help.
     * hotel_advisor: can help with hotel recommendations. Can ask travel_advisor for help.
 
-    :::python
     ```python
     from langchain_anthropic import ChatAnthropic
     from langgraph.graph import MessagesState, StateGraph, START
@@ -987,267 +571,10 @@ function agent(state: MessagesState): Command {
     
     Would you like more specific information about any of these activities or would you like to know about other options in the area?
     ```
-    :::
-
-    :::js
-    ```typescript
-    import { ChatAnthropic } from "@langchain/anthropic";
-    import { StateGraph, START, MessagesZodState, Command, interrupt, MemorySaver } from "@langchain/langgraph";
-    import { createReactAgent } from "@langchain/langgraph/prebuilt";
-    import { tool } from "@langchain/core/tools";
-    import { z } from "zod";
-
-    const model = new ChatAnthropic({ model: "claude-3-5-sonnet-latest" });
-
-    const MultiAgentState = MessagesZodState.extend({
-      lastActiveAgent: z.string().optional(),
-    });
-
-    // Define travel advisor tools
-    const getTravelRecommendations = tool(
-      async () => {
-        // Placeholder implementation
-        return "Based on current trends, I recommend visiting Japan, Portugal, or New Zealand.";
-      },
-      {
-        name: "get_travel_recommendations",
-        description: "Get current travel destination recommendations",
-        schema: z.object({}),
-      }
-    );
-
-    const makeHandoffTool = (agentName: string) => {
-      return tool(
-        async (_, config) => {
-          const state = config.state;
-          const toolCallId = config.toolCall.id;
-
-          const toolMessage = {
-            role: "tool" as const,
-            content: `Successfully transferred to ${agentName}`,
-            name: `transfer_to_${agentName}`,
-            tool_call_id: toolCallId,
-          };
-
-          return new Command({
-            goto: agentName,
-            update: { messages: [...state.messages, toolMessage] },
-            graph: Command.PARENT,
-          });
-        },
-        {
-          name: `transfer_to_${agentName}`,
-          description: `Transfer to ${agentName}`,
-          schema: z.object({}),
-        }
-      );
-    };
-
-    const travelAdvisorTools = [
-      getTravelRecommendations,
-      makeHandoffTool("hotel_advisor"),
-    ];
-
-    const travelAdvisor = createReactAgent({
-      llm: model,
-      tools: travelAdvisorTools,
-      prompt: [
-        "You are a general travel expert that can recommend travel destinations (e.g. countries, cities, etc). ",
-        "If you need hotel recommendations, ask 'hotel_advisor' for help. ",
-        "You MUST include human-readable response before transferring to another agent."
-      ].join("")
-    });
-
-    const callTravelAdvisor = async (
-      state: z.infer<typeof MultiAgentState>
-    ): Promise<Command> => {
-      const response = await travelAdvisor.invoke(state);
-      const update = { ...response, lastActiveAgent: "travel_advisor" };
-      return new Command({ update, goto: "human" });
-    };
-
-    // Define hotel advisor tools
-    const getHotelRecommendations = tool(
-      async () => {
-        // Placeholder implementation
-        return "I recommend the Ritz-Carlton for luxury stays or boutique hotels for unique experiences.";
-      },
-      {
-        name: "get_hotel_recommendations",
-        description: "Get hotel recommendations for destinations",
-        schema: z.object({}),
-      }
-    );
-
-    const hotelAdvisorTools = [
-      getHotelRecommendations,
-      makeHandoffTool("travel_advisor"),
-    ];
-
-    const hotelAdvisor = createReactAgent({
-      llm: model,
-      tools: hotelAdvisorTools,
-      prompt: [
-        "You are a hotel expert that can provide hotel recommendations for a given destination. ",
-        "If you need help picking travel destinations, ask 'travel_advisor' for help.",
-        "You MUST include human-readable response before transferring to another agent."
-      ].join("")
-    });
-
-    const callHotelAdvisor = async (
-      state: z.infer<typeof MultiAgentState>
-    ): Promise<Command> => {
-      const response = await hotelAdvisor.invoke(state);
-      const update = { ...response, lastActiveAgent: "hotel_advisor" };
-      return new Command({ update, goto: "human" });
-    };
-
-    const humanNode = async (
-      state: z.infer<typeof MultiAgentState>
-    ): Promise<Command> => {
-      const userInput: string = interrupt("Ready for user input.");
-      const activeAgent = state.lastActiveAgent || "travel_advisor";
-
-      return new Command({
-        update: {
-          messages: [
-            {
-              role: "human",
-              content: userInput,
-            }
-          ]
-        },
-        goto: activeAgent,
-      });
-    };
-
-    const builder = new StateGraph(MultiAgentState)
-      .addNode("travel_advisor", callTravelAdvisor)
-      .addNode("hotel_advisor", callHotelAdvisor)
-      .addNode("human", humanNode)
-      .addEdge(START, "travel_advisor");
-
-    const checkpointer = new MemorySaver();
-    const graph = builder.compile({ checkpointer });
-    ```
-    
-    Let's test a multi turn conversation with this application.
-
-    ```typescript
-    import { v4 as uuidv4 } from "uuid";
-    import { Command } from "@langchain/langgraph";
-
-    const threadConfig = { configurable: { thread_id: uuidv4() } };
-
-    const inputs = [
-      // 1st round of conversation
-      {
-        messages: [
-          { role: "user", content: "i wanna go somewhere warm in the caribbean" }
-        ]
-      },
-      // Since we're using `interrupt`, we'll need to resume using the Command primitive.
-      // 2nd round of conversation
-      new Command({
-        resume: "could you recommend a nice hotel in one of the areas and tell me which area it is."
-      }),
-      // 3rd round of conversation
-      new Command({
-        resume: "i like the first one. could you recommend something to do near the hotel?"
-      }),
-    ];
-
-    for (const [idx, userInput] of inputs.entries()) {
-      console.log();
-      console.log(`--- Conversation Turn ${idx + 1} ---`);
-      console.log();
-      console.log(`User: ${JSON.stringify(userInput)}`);
-      console.log();
-      
-      for await (const update of await graph.stream(
-        userInput,
-        { ...threadConfig, streamMode: "updates" }
-      )) {
-        for (const [nodeId, value] of Object.entries(update)) {
-          if (value?.messages?.length) {
-            const lastMessage = value.messages.at(-1);
-            if (lastMessage?.getType?.() === "ai") {
-              console.log(`${nodeId}: ${lastMessage.content}`);
-            }
-          }
-        }
-      }
-    }
-    ```
-    
-    ```
-    --- Conversation Turn 1 ---
-    
-    User: {"messages":[{"role":"user","content":"i wanna go somewhere warm in the caribbean"}]}
-    
-    travel_advisor: Based on the recommendations, Aruba would be an excellent choice for your Caribbean getaway! Aruba is known as "One Happy Island" and offers:
-    - Year-round warm weather with consistent temperatures around 82°F (28°C)
-    - Beautiful white sand beaches like Eagle Beach and Palm Beach
-    - Clear turquoise waters perfect for swimming and snorkeling
-    - Minimal rainfall and location outside the hurricane belt
-    - A blend of Caribbean and Dutch culture
-    - Great dining options and nightlife
-    - Various water sports and activities
-    
-    Would you like me to get some specific hotel recommendations in Aruba for your stay? I can transfer you to our hotel advisor who can help with accommodations.
-    
-    --- Conversation Turn 2 ---
-    
-    User: Command { resume: 'could you recommend a nice hotel in one of the areas and tell me which area it is.' }
-    
-    hotel_advisor: Based on the recommendations, I can suggest two excellent options:
-    
-    1. The Ritz-Carlton, Aruba - Located in Palm Beach
-    - This luxury resort is situated in the vibrant Palm Beach area
-    - Known for its exceptional service and amenities
-    - Perfect if you want to be close to dining, shopping, and entertainment
-    - Features multiple restaurants, a casino, and a world-class spa
-    - Located on a pristine stretch of Palm Beach
-    
-    2. Bucuti & Tara Beach Resort - Located in Eagle Beach
-    - An adults-only boutique resort on Eagle Beach
-    - Known for being more intimate and peaceful
-    - Award-winning for its sustainability practices
-    - Perfect for a romantic getaway or peaceful vacation
-    - Located on one of the most beautiful beaches in the Caribbean
-    
-    Would you like more specific information about either of these properties or their locations?
-    
-    --- Conversation Turn 3 ---
-    
-    User: Command { resume: 'i like the first one. could you recommend something to do near the hotel?' }
-    
-    travel_advisor: Near the Ritz-Carlton in Palm Beach, here are some highly recommended activities:
-    
-    1. Visit the Palm Beach Plaza Mall - Just a short walk from the hotel, featuring shopping, dining, and entertainment
-    2. Try your luck at the Stellaris Casino - It's right in the Ritz-Carlton
-    3. Take a sunset sailing cruise - Many depart from the nearby pier
-    4. Visit the California Lighthouse - A scenic landmark just north of Palm Beach
-    5. Enjoy water sports at Palm Beach:
-       - Jet skiing
-       - Parasailing
-       - Snorkeling
-       - Stand-up paddleboarding
-    
-    Would you like more specific information about any of these activities or would you like to know about other options in the area?
-    ```
-    :::
 
 ## Prebuilt implementations
 
 LangGraph comes with prebuilt implementations of two of the most popular multi-agent architectures:
 
-:::python
 - [supervisor](../agents/multi-agent.md#supervisor) — individual agents are coordinated by a central supervisor agent. The supervisor controls all communication flow and task delegation, making decisions about which agent to invoke based on the current context and task requirements. You can use [`langgraph-supervisor`](https://github.com/langchain-ai/langgraph-supervisor-py) library to create a supervisor multi-agent systems.
-- [swarm](../agents/multi-agent.md#supervisor) — agents dynamically hand off control to one another based on their specializations. The system remembers which agent was last active, ensuring that on subsequent interactions, the conversation resumes with that agent. You can use [`langgraph-swarm`](https://github.com/langchain-ai/langgraph-swarm-py) library to create a swarm multi-agent systems.
-:::
-
-:::js
-- [supervisor](../agents/multi-agent.md#supervisor) — individual agents are coordinated by a central supervisor agent. The supervisor controls all communication flow and task delegation, making decisions about which agent to invoke based on the current context and task requirements. You can use [`langgraph-supervisor`](https://github.com/langchain-ai/langgraph-supervisor-js) library to create a supervisor multi-agent systems.
-- [swarm](../agents/multi-agent.md#supervisor) — agents dynamically hand off control to one another based on their specializations. The system remembers which agent was last active, ensuring that on subsequent interactions, the conversation resumes with that agent. You can use [`langgraph-swarm`](https://github.com/langchain-ai/langgraph-swarm-js) library to create a swarm multi-agent systems.
-:::
+- [swarm](../agents/multi-agent.md#supervisor) — agents dynamically hand off control to one another based on their specializations. The system remembers which agent was last active, ensuring that on subsequent interactions, the conversation resumes with that agent. You can use [`langgraph-swarm`](https://github.com/langchain-ai/langgraph-swarm-py) library to create a swarm multi-agent systems. 

docs/docs/how-tos/subgraph.md

@@ -9,20 +9,11 @@ When adding subgraphs, you need to define how the parent graph and the subgraph
 
 ## Setup
 
-:::python
 ```bash
 pip install -U langgraph
 ```
-:::
-
-:::js
-```bash
-npm install @langchain/langgraph
-```
-:::
 
 !!! tip "Set up LangSmith for LangGraph development"
-
     Sign up for [LangSmith](https://smith.langchain.com) to quickly spot issues and improve the performance of your LangGraph projects. LangSmith lets you use trace data to debug, test, and monitor your LLM apps built with LangGraph — read more about how to get started [here](https://docs.smith.langchain.com).
 
 ## Shared state schemas
@@ -31,7 +22,6 @@ A common case is for the parent graph and subgraph to communicate over a shared
 
 If your subgraph shares state keys with the parent graph, you can follow these steps to add it to your graph:
 
-:::python
 1. Define the subgraph workflow (`subgraph_builder` in the example below) and compile it
 2. Pass compiled subgraph to the `.add_node` method when defining the parent graph workflow
 
@@ -59,41 +49,9 @@ builder.add_node("node_1", subgraph)
 builder.add_edge(START, "node_1")
 graph = builder.compile()
 ```
-:::
-
-:::js
-1. Define the subgraph workflow (`subgraphBuilder` in the example below) and compile it
-2. Pass compiled subgraph to the `.addNode` method when defining the parent graph workflow
-
-```typescript
-import { StateGraph, START } from "@langchain/langgraph";
-import { z } from "zod";
-
-const State = z.object({
-  foo: z.string(),
-});
-
-// Subgraph
-const subgraphBuilder = new StateGraph(State)
-  .addNode("subgraphNode1", (state) => {
-    return { foo: "hi! " + state.foo };
-  })
-  .addEdge(START, "subgraphNode1");
-
-const subgraph = subgraphBuilder.compile();
-
-// Parent graph
-const builder = new StateGraph(State)
-  .addNode("node1", subgraph)
-  .addEdge(START, "node1");
-
-const graph = builder.compile();
-```
-:::
 
 ??? example "Full example: shared state schemas"
 
-    :::python
     ```python
     from typing_extensions import TypedDict
     from langgraph.graph.state import StateGraph, START
@@ -143,61 +101,6 @@ const graph = builder.compile();
     {'node_1': {'foo': 'hi! foo'}}
     {'node_2': {'foo': 'hi! foobar'}}
     ```
-    :::
-
-    :::js
-    ```typescript
-    import { StateGraph, START } from "@langchain/langgraph";
-    import { z } from "zod";
-
-    // Define subgraph
-    const SubgraphState = z.object({
-      foo: z.string(),  // (1)! 
-      bar: z.string(),  // (2)!
-    });
-    
-    const subgraphBuilder = new StateGraph(SubgraphState)
-      .addNode("subgraphNode1", (state) => {
-        return { bar: "bar" };
-      })
-      .addNode("subgraphNode2", (state) => {
-        // note that this node is using a state key ('bar') that is only available in the subgraph
-        // and is sending update on the shared state key ('foo')
-        return { foo: state.foo + state.bar };
-      })
-      .addEdge(START, "subgraphNode1")
-      .addEdge("subgraphNode1", "subgraphNode2");
-    
-    const subgraph = subgraphBuilder.compile();
-    
-    // Define parent graph
-    const ParentState = z.object({
-      foo: z.string(),
-    });
-    
-    const builder = new StateGraph(ParentState)
-      .addNode("node1", (state) => {
-        return { foo: "hi! " + state.foo };
-      })
-      .addNode("node2", subgraph)
-      .addEdge(START, "node1")
-      .addEdge("node1", "node2");
-    
-    const graph = builder.compile();
-    
-    for await (const chunk of await graph.stream({ foo: "foo" })) {
-      console.log(chunk);
-    }
-    ```
-
-    3. This key is shared with the parent graph state
-    4. This key is private to the `SubgraphState` and is not visible to the parent graph
-    
-    ```
-    { node1: { foo: 'hi! foo' } }
-    { node2: { foo: 'hi! foobar' } }
-    ```
-    :::
 
 ## Different state schemas
 
@@ -205,7 +108,6 @@ For more complex systems you might want to define subgraphs that have a **comple
 
 If that's the case for your application, you need to define a node **function that invokes the subgraph**. This function needs to transform the input (parent) state to the subgraph state before invoking the subgraph, and transform the results back to the parent state before returning the state update from the node.
 
-:::python
 ```python
 from typing_extensions import TypedDict
 from langgraph.graph.state import StateGraph, START
@@ -240,48 +142,9 @@ graph = builder.compile()
 
 1. Transform the state to the subgraph state
 2. Transform response back to the parent state
-:::
-
-:::js
-```typescript
-import { StateGraph, START } from "@langchain/langgraph";
-import { z } from "zod";
-
-const SubgraphState = z.object({
-  bar: z.string(),
-});
-
-// Subgraph
-const subgraphBuilder = new StateGraph(SubgraphState)
-  .addNode("subgraphNode1", (state) => {
-    return { bar: "hi! " + state.bar };
-  })
-  .addEdge(START, "subgraphNode1");
-
-const subgraph = subgraphBuilder.compile();
-
-// Parent graph
-const State = z.object({
-  foo: z.string(),
-});
-
-const builder = new StateGraph(State)
-  .addNode("node1", async (state) => {
-    const subgraphOutput = await subgraph.invoke({ bar: state.foo }); // (1)!
-    return { foo: subgraphOutput.bar }; // (2)!
-  })
-  .addEdge(START, "node1");
-
-const graph = builder.compile();
-```
-
-1. Transform the state to the subgraph state
-2. Transform response back to the parent state
-:::
 
 ??? example "Full example: different state schemas"
 
-    :::python
     ```python
     from typing_extensions import TypedDict
     from langgraph.graph.state import StateGraph, START
@@ -337,74 +200,11 @@ const graph = builder.compile();
     (('node_2:9c36dd0f-151a-cb42-cbad-fa2f851f9ab7',), {'grandchild_2': {'bar': 'hi! foobaz'}})
     ((), {'node_2': {'foo': 'hi! foobaz'}})
     ```
-    :::
-
-    :::js
-    ```typescript
-    import { StateGraph, START } from "@langchain/langgraph";
-    import { z } from "zod";
-
-    // Define subgraph
-    const SubgraphState = z.object({
-      // note that none of these keys are shared with the parent graph state
-      bar: z.string(),
-      baz: z.string(),
-    });
-    
-    const subgraphBuilder = new StateGraph(SubgraphState)
-      .addNode("subgraphNode1", (state) => {
-        return { baz: "baz" };
-      })
-      .addNode("subgraphNode2", (state) => {
-        return { bar: state.bar + state.baz };
-      })
-      .addEdge(START, "subgraphNode1")
-      .addEdge("subgraphNode1", "subgraphNode2");
-    
-    const subgraph = subgraphBuilder.compile();
-    
-    // Define parent graph
-    const ParentState = z.object({
-      foo: z.string(),
-    });
-    
-    const builder = new StateGraph(ParentState)
-      .addNode("node1", (state) => {
-        return { foo: "hi! " + state.foo };
-      })
-      .addNode("node2", async (state) => {
-        const response = await subgraph.invoke({ bar: state.foo }); // (1)!
-        return { foo: response.bar }; // (2)!
-      })
-      .addEdge(START, "node1")
-      .addEdge("node1", "node2");
-    
-    const graph = builder.compile();
-    
-    for await (const chunk of await graph.stream(
-      { foo: "foo" }, 
-      { subgraphs: true }
-    )) {
-      console.log(chunk);
-    }
-    ```
-
-    3. Transform the state to the subgraph state
-    4. Transform response back to the parent state
-
-    ```
-    [[], { node1: { foo: 'hi! foo' } }]
-    [['node2:9c36dd0f-151a-cb42-cbad-fa2f851f9ab7'], { subgraphNode1: { baz: 'baz' } }]
-    [['node2:9c36dd0f-151a-cb42-cbad-fa2f851f9ab7'], { subgraphNode2: { bar: 'hi! foobaz' } }]
-    [[], { node2: { foo: 'hi! foobaz' } }]
-    ```
-    :::
 
 ??? example "Full example: different state schemas (two levels of subgraphs)"
 
     This is an example with two levels of subgraphs: parent -> child -> grandchild.
 
-    :::python
     ```python
     # Grandchild graph
     from typing_extensions import TypedDict
@@ -488,102 +288,14 @@ const graph = builder.compile();
     ((), {'child': {'my_key': 'hi Bob, how are you today?'}})
     ((), {'parent_2': {'my_key': 'hi Bob, how are you today? bye!'}})
     ```
-    :::
-
-    :::js
-    ```typescript
-    import { StateGraph, START, END } from "@langchain/langgraph";
-    import { z } from "zod";
-
-    // Grandchild graph
-    const GrandChildState = z.object({
-      myGrandchildKey: z.string(),
-    });
-    
-    const grandchild = new StateGraph(GrandChildState)
-      .addNode("grandchild1", (state) => {
-        // NOTE: child or parent keys will not be accessible here
-        return { myGrandchildKey: state.myGrandchildKey + ", how are you" };
-      })
-      .addEdge(START, "grandchild1")
-      .addEdge("grandchild1", END);
-    
-    const grandchildGraph = grandchild.compile();
-    
-    // Child graph
-    const ChildState = z.object({
-      myChildKey: z.string(),
-    });
-    
-    const child = new StateGraph(ChildState)
-      .addNode("child1", async (state) => {
-        // NOTE: parent or grandchild keys won't be accessible here
-        const grandchildGraphInput = { myGrandchildKey: state.myChildKey }; // (1)!
-        const grandchildGraphOutput = await grandchildGraph.invoke(grandchildGraphInput);
-        return { myChildKey: grandchildGraphOutput.myGrandchildKey + " today?" }; // (2)!
-      }) // (3)!
-      .addEdge(START, "child1")
-      .addEdge("child1", END);
-    
-    const childGraph = child.compile();
-    
-    // Parent graph
-    const ParentState = z.object({
-      myKey: z.string(),
-    });
-    
-    const parent = new StateGraph(ParentState)
-      .addNode("parent1", (state) => {
-        // NOTE: child or grandchild keys won't be accessible here
-        return { myKey: "hi " + state.myKey };
-      })
-      .addNode("child", async (state) => {
-        const childGraphInput = { myChildKey: state.myKey }; // (4)!
-        const childGraphOutput = await childGraph.invoke(childGraphInput);
-        return { myKey: childGraphOutput.myChildKey }; // (5)!
-      }) // (6)!
-      .addNode("parent2", (state) => {
-        return { myKey: state.myKey + " bye!" };
-      })
-      .addEdge(START, "parent1")
-      .addEdge("parent1", "child")
-      .addEdge("child", "parent2")
-      .addEdge("parent2", END);
-    
-    const parentGraph = parent.compile();
-    
-    for await (const chunk of await parentGraph.stream(
-      { myKey: "Bob" }, 
-      { subgraphs: true }
-    )) {
-      console.log(chunk);
-    }
-    ```
-
-    7. We're transforming the state from the child state channels (`myChildKey`) to the grandchild state channels (`myGrandchildKey`)
-    8. We're transforming the state from the grandchild state channels (`myGrandchildKey`) back to the child state channels (`myChildKey`)
-    9. We're passing a function here instead of just compiled graph (`grandchildGraph`)
-    10. We're transforming the state from the parent state channels (`myKey`) to the child state channels (`myChildKey`)
-    11. We're transforming the state from the child state channels (`myChildKey`) back to the parent state channels (`myKey`)
-    12. We're passing a function here instead of just a compiled graph (`childGraph`)
-
-    ```
-    [[], { parent1: { myKey: 'hi Bob' } }]
-    [['child:2e26e9ce-602f-862c-aa66-1ea5a4655e3b', 'child1:781bb3b1-3971-84ce-810b-acf819a03f9c'], { grandchild1: { myGrandchildKey: 'hi Bob, how are you' } }]
-    [['child:2e26e9ce-602f-862c-aa66-1ea5a4655e3b'], { child1: { myChildKey: 'hi Bob, how are you today?' } }]
-    [[], { child: { myKey: 'hi Bob, how are you today?' } }]
-    [[], { parent2: { myKey: 'hi Bob, how are you today? bye!' } }]
-    ```
-    :::
 
 ## Add persistence 
 
 You only need to **provide the checkpointer when compiling the parent graph**. LangGraph will automatically propagate the checkpointer to the child subgraphs.
 
-:::python
 ```python
 from langgraph.graph import START, StateGraph
-from langgraph.checkpoint.memory import MemorySaver
+from langgraph.checkpoint.memory import InMemorySaver
 from typing_extensions import TypedDict
 
 class State(TypedDict):
@@ -605,66 +317,20 @@ builder = StateGraph(State)
 builder.add_node("node_1", subgraph)
 builder.add_edge(START, "node_1")
 
-checkpointer = MemorySaver()
+checkpointer = InMemorySaver()
 graph = builder.compile(checkpointer=checkpointer)
 ```    
-:::
 
-:::js
-```typescript
-import { StateGraph, START, MemorySaver } from "@langchain/langgraph";
-import { z } from "zod";
+If you want the subgraph to **have its own memory**, you can compile it `with checkpointer=True`. This is useful in [multi-agent](../concepts/multi_agent.md) systems, if you want agents to keep track of their internal message histories:
 
-const State = z.object({
-  foo: z.string(),
-});
-
-// Subgraph
-const subgraphBuilder = new StateGraph(State)
-  .addNode("subgraphNode1", (state) => {
-    return { foo: state.foo + "bar" };
-  })
-  .addEdge(START, "subgraphNode1");
-
-const subgraph = subgraphBuilder.compile();
-
-// Parent graph
-const builder = new StateGraph(State)
-  .addNode("node1", subgraph)
-  .addEdge(START, "node1");
-
-const checkpointer = new MemorySaver();
-const graph = builder.compile({ checkpointer });
-```    
-:::
-
-If you want the subgraph to **have its own memory**, you can compile it with the appropriate checkpointer option. This is useful in [multi-agent](../concepts/multi_agent.md) systems, if you want agents to keep track of their internal message histories:
-
-:::python
 ```python
 subgraph_builder = StateGraph(...)
 subgraph = subgraph_builder.compile(checkpointer=True)
 ```
-:::
-
-:::js
-```typescript
-const subgraphBuilder = new StateGraph(...)
-const subgraph = subgraphBuilder.compile({ checkpointer: true });
-```
-:::
 
 ## View subgraph state
 
-When you enable [persistence](../concepts/persistence.md), you can [inspect the graph state](../concepts/persistence.md#checkpoints) (checkpoint) via the appropriate method. To view the subgraph state, you can use the subgraphs option.
-
-:::python
-You can inspect the graph state via `graph.get_state(config)`. To view the subgraph state, you can use `graph.get_state(config, subgraphs=True)`.
-:::
-
-:::js
-You can inspect the graph state via `graph.getState(config)`. To view the subgraph state, you can use `graph.getState(config, { subgraphs: true })`.
-:::
+When you enable [persistence](../concepts/persistence.md), you can [inspect the graph state](../concepts/persistence.md#checkpoints) (checkpoint) via `graph.get_state(config)`. To view the subgraph state, you can use `graph.get_state(config, subgraphs=True)`.
 
 !!! important "Available **only** when interrupted"
 
@@ -672,10 +338,9 @@ You can inspect the graph state via `graph.getState(config)`. To view the subgra
 
 ??? example "View interrupted subgraph state"
 
-    :::python
     ```python
     from langgraph.graph import START, StateGraph
-    from langgraph.checkpoint.memory import MemorySaver
+    from langgraph.checkpoint.memory import InMemorySaver
     from langgraph.types import interrupt, Command
     from typing_extensions import TypedDict
     
@@ -700,7 +365,7 @@ You can inspect the graph state via `graph.getState(config)`. To view the subgra
     builder.add_node("node_1", subgraph)
     builder.add_edge(START, "node_1")
     
-    checkpointer = MemorySaver()
+    checkpointer = InMemorySaver()
     graph = builder.compile(checkpointer=checkpointer)
     
     config = {"configurable": {"thread_id": "1"}}
@@ -714,53 +379,11 @@ You can inspect the graph state via `graph.getState(config)`. To view the subgra
     ```
     
     1. This will be available only when the subgraph is interrupted. Once you resume the graph, you won't be able to access the subgraph state.
-    :::
-
-    :::js
-    ```typescript
-    import { StateGraph, START, MemorySaver, interrupt, Command } from "@langchain/langgraph";
-    import { z } from "zod";
-    
-    const State = z.object({
-      foo: z.string(),
-    });
-    
-    // Subgraph
-    const subgraphBuilder = new StateGraph(State)
-      .addNode("subgraphNode1", (state) => {
-        const value = interrupt("Provide value:");
-        return { foo: state.foo + value };
-      })
-      .addEdge(START, "subgraphNode1");
-    
-    const subgraph = subgraphBuilder.compile();
-    
-    // Parent graph
-    const builder = new StateGraph(State)
-      .addNode("node1", subgraph)
-      .addEdge(START, "node1");
-    
-    const checkpointer = new MemorySaver();
-    const graph = builder.compile({ checkpointer });
-    
-    const config = { configurable: { thread_id: "1" } };
-    
-    await graph.invoke({ foo: "" }, config);
-    const parentState = await graph.getState(config);
-    const subgraphState = (await graph.getState(config, { subgraphs: true })).tasks[0].state; // (1)!
-    
-    // resume the subgraph
-    await graph.invoke(new Command({ resume: "bar" }), config);
-    ```
-    
-    2. This will be available only when the subgraph is interrupted. Once you resume the graph, you won't be able to access the subgraph state.
-    :::
 
 ## Stream subgraph outputs
 
-To include outputs from subgraphs in the streamed outputs, you can set the subgraphs option in the stream method of the parent graph. This will stream outputs from both the parent graph and any subgraphs.
+To include outputs from subgraphs in the streamed outputs, you can set `subgraphs=True` in the `.stream()` method of the parent graph. This will stream outputs from both the parent graph and any subgraphs.
 
-:::python
 ```python
 for chunk in graph.stream(
     {"foo": "foo"},
@@ -771,27 +394,9 @@ for chunk in graph.stream(
 ```
 
 1. Set `subgraphs=True` to stream outputs from subgraphs.
-:::
-
-:::js
-```typescript
-for await (const chunk of await graph.stream(
-  { foo: "foo" },
-  {
-    subgraphs: true, // (1)!
-    streamMode: "updates",
-  }
-)) {
-  console.log(chunk);
-}
-```
-
-1. Set `subgraphs: true` to stream outputs from subgraphs.
-:::
 
 ??? example "Stream from subgraphs"
 
-    :::python
     ```python
     from typing_extensions import TypedDict
     from langgraph.graph.state import StateGraph, START
@@ -845,66 +450,4 @@ for await (const chunk of await graph.stream(
     (('node_2:e58e5673-a661-ebb0-70d4-e298a7fc28b7',), {'subgraph_node_1': {'bar': 'bar'}})
     (('node_2:e58e5673-a661-ebb0-70d4-e298a7fc28b7',), {'subgraph_node_2': {'foo': 'hi! foobar'}})
     ((), {'node_2': {'foo': 'hi! foobar'}})
-    ```
-    :::
-
-    :::js
-    ```typescript
-    import { StateGraph, START } from "@langchain/langgraph";
-    import { z } from "zod";
-
-    // Define subgraph
-    const SubgraphState = z.object({
-      foo: z.string(),
-      bar: z.string(),
-    });
-    
-    const subgraphBuilder = new StateGraph(SubgraphState)
-      .addNode("subgraphNode1", (state) => {
-        return { bar: "bar" };
-      })
-      .addNode("subgraphNode2", (state) => {
-        // note that this node is using a state key ('bar') that is only available in the subgraph
-        // and is sending update on the shared state key ('foo')
-        return { foo: state.foo + state.bar };
-      })
-      .addEdge(START, "subgraphNode1")
-      .addEdge("subgraphNode1", "subgraphNode2");
-    
-    const subgraph = subgraphBuilder.compile();
-    
-    // Define parent graph
-    const ParentState = z.object({
-      foo: z.string(),
-    });
-    
-    const builder = new StateGraph(ParentState)
-      .addNode("node1", (state) => {
-        return { foo: "hi! " + state.foo };
-      })
-      .addNode("node2", subgraph)
-      .addEdge(START, "node1")
-      .addEdge("node1", "node2");
-    
-    const graph = builder.compile();
-
-    for await (const chunk of await graph.stream(
-      { foo: "foo" },
-      {
-        streamMode: "updates",
-        subgraphs: true, // (1)!
-      }
-    )) {
-      console.log(chunk);
-    }
-    ```
-  
-    2. Set `subgraphs: true` to stream outputs from subgraphs.
-
-    ```
-    [[], { node1: { foo: 'hi! foo' } }]
-    [['node2:e58e5673-a661-ebb0-70d4-e298a7fc28b7'], { subgraphNode1: { bar: 'bar' } }]
-    [['node2:e58e5673-a661-ebb0-70d4-e298a7fc28b7'], { subgraphNode2: { foo: 'hi! foobar' } }]
-    [[], { node2: { foo: 'hi! foobar' } }]
-    ```
-    :::
+    

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/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 = "0.6.6"
+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/tests/conftest.py

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

libs/langgraph/tests/test_pregel.py

@@ -4805,10 +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]
 
@@ -4824,8 +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(
@@ -4836,19 +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(
@@ -4862,13 +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/prebuilt/langgraph/prebuilt/chat_agent_executor.py

@@ -12,6 +12,7 @@ from typing import (
     cast,
     get_type_hints,
 )
+from operator import add
 from warnings import warn
 
 from langchain_core.language_models import (
@@ -46,7 +47,7 @@ from langgraph.managed import RemainingSteps
 from langgraph.prebuilt.tool_node import ToolNode
 from langgraph.runtime import Runtime
 from langgraph.store.base import BaseStore
-from langgraph.types import Checkpointer, Send
+from langgraph.types import Checkpointer, Command, Send
 from langgraph.typing import ContextT
 from langgraph.warnings import LangGraphDeprecatedSinceV10
 
@@ -66,6 +67,8 @@ class AgentState(TypedDict):
 
     remaining_steps: NotRequired[RemainingSteps]
 
+    model_calls: Annotated[NotRequired[int], add]
+
 
 class AgentStatePydantic(BaseModel):
     """The state of the agent."""
@@ -191,29 +194,6 @@ def _should_bind_tools(
     return False
 
 
-def _get_model(model: LanguageModelLike) -> BaseChatModel:
-    """Get the underlying model from a RunnableBinding or return the model itself."""
-    if isinstance(model, RunnableSequence):
-        model = next(
-            (
-                step
-                for step in model.steps
-                if isinstance(step, (RunnableBinding, BaseChatModel))
-            ),
-            model,
-        )
-
-    if isinstance(model, RunnableBinding):
-        model = model.bound
-
-    if not isinstance(model, BaseChatModel):
-        raise TypeError(
-            f"Expected `model` to be a ChatModel or RunnableBinding (e.g. model.bind_tools(...)), got {type(model)}"
-        )
-
-    return model
-
-
 def _validate_chat_history(
     messages: Sequence[BaseMessage],
 ) -> None:
@@ -245,6 +225,10 @@ def _validate_chat_history(
     raise ValueError(error_message)
 
 
+class StepCountIs(BaseModel):
+    count: int
+
+
 def create_react_agent(
     model: Union[
         str,
@@ -276,6 +260,7 @@ def create_react_agent(
     debug: bool = False,
     version: Literal["v1", "v2"] = "v2",
     name: Optional[str] = None,
+    stop_when: Optional[Callable[[StateSchema], bool]] | StepCountIs = None,
     **deprecated_kwargs: Any,
 ) -> CompiledStateGraph:
     """Creates an agent graph that calls tools in a loop until a stopping condition is met.
@@ -499,13 +484,19 @@ def create_react_agent(
             else AgentState
         )
 
+    structured_output_tools: list[type] = []
     llm_builtin_tools: list[dict] = []
     if isinstance(tools, ToolNode):
         tool_classes = list(tools.tools_by_name.values())
         tool_node = tools
     else:
         llm_builtin_tools = [t for t in tools if isinstance(t, dict)]
-        tool_node = ToolNode([t for t in tools if not isinstance(t, dict)])
+        structured_output_tools = (
+            [response_format] if response_format is not None else []
+        )
+        tool_node = ToolNode(
+            [t for t in [*tools, *structured_output_tools] if not isinstance(t, dict)]
+        )
         tool_classes = list(tool_node.tools_by_name.values())
 
     is_dynamic_model = not isinstance(model, (str, Runnable)) and callable(model)
@@ -527,12 +518,19 @@ def create_react_agent(
 
             model = cast(BaseChatModel, init_chat_model(model))
 
+        # Add structured output tool if response_format is provided
+        structured_output_tools = (
+            [response_format] if response_format is not None else []
+        )
+
         if (
             _should_bind_tools(model, tool_classes, num_builtin=len(llm_builtin_tools))  # type: ignore[arg-type]
             and len(tool_classes + llm_builtin_tools) > 0
         ):
             model = cast(BaseChatModel, model).bind_tools(
-                tool_classes + llm_builtin_tools  # type: ignore[operator]
+                tool_classes + llm_builtin_tools + structured_output_tools,  # type: ignore[operator],
+                tool_choice="any",
+                parallel_tool_calls=False,
             )
 
         static_model: Optional[Runnable] = _get_prompt_runnable(prompt) | model  # type: ignore[operator]
@@ -542,7 +540,11 @@ def create_react_agent(
 
     # If any of the tools are configured to return_directly after running,
     # our graph needs to check if these were called
-    should_return_direct = {t.name for t in tool_classes if t.return_direct}
+    should_return_direct = {
+        t.name for t in tool_classes if getattr(t, "return_direct", False)
+    }
+    if response_format is not None:
+        should_return_direct.add(response_format.__name__)
 
     def _resolve_model(
         state: StateSchema, runtime: Runtime[ContextT]
@@ -608,7 +610,7 @@ def create_react_agent(
     # Define the function that calls the model
     def call_model(
         state: StateSchema, runtime: Runtime[ContextT], config: RunnableConfig
-    ) -> StateSchema:
+    ) -> dict[str, list[AIMessage]] | Command:
         if is_async_dynamic_model:
             msg = (
                 "Async model callable provided but agent invoked synchronously. "
@@ -619,11 +621,25 @@ def create_react_agent(
 
         model_input = _get_model_input_state(state)
 
+        if stop_when is not None:
+            post_model_node = "post_model_hook" if post_model_hook is not None else END
+            if isinstance(stop_when, StepCountIs):
+
+                if (model_calls := _get_state_value(state, "model_calls", 0)) == (stop_when.count - 1):
+                    # set tool_choice to structured output tool if response_format is provided
+                    # though we don't currently expose support for that binding here.
+                    ...
+                elif model_calls == stop_when.count:
+                    return Command(goto=post_model_node)
+            else:
+                if stop_when(state):
+                    return Command(goto=post_model_node)
+
         if is_dynamic_model:
             # Resolve dynamic model at runtime and apply prompt
             dynamic_model = _resolve_model(state, runtime)
             response = cast(AIMessage, dynamic_model.invoke(model_input, config))  # type: ignore[arg-type]
-        else:
+        else:                
             response = cast(AIMessage, static_model.invoke(model_input, config))  # type: ignore[union-attr]
 
         # add agent name to the AIMessage
@@ -638,12 +654,12 @@ def create_react_agent(
                     )
                 ]
             }
-        # We return a list, because this will get added to the existing list
-        return {"messages": [response]}
+
+        return {"messages": [response], "model_calls": 1}
 
     async def acall_model(
         state: StateSchema, runtime: Runtime[ContextT], config: RunnableConfig
-    ) -> StateSchema:
+    ) -> dict[str, list[AIMessage]]:
         model_input = _get_model_input_state(state)
 
         if is_dynamic_model:
@@ -689,49 +705,6 @@ def create_react_agent(
     else:
         input_schema = state_schema
 
-    def generate_structured_response(
-        state: StateSchema, runtime: Runtime[ContextT], config: RunnableConfig
-    ) -> StateSchema:
-        if is_async_dynamic_model:
-            msg = (
-                "Async model callable provided but agent invoked synchronously. "
-                "Use agent.ainvoke() or agent.astream(), or provide a sync model callable."
-            )
-            raise RuntimeError(msg)
-
-        messages = _get_state_value(state, "messages")
-        structured_response_schema = response_format
-        if isinstance(response_format, tuple):
-            system_prompt, structured_response_schema = response_format
-            messages = [SystemMessage(content=system_prompt)] + list(messages)
-
-        resolved_model = _resolve_model(state, runtime)
-        model_with_structured_output = _get_model(
-            resolved_model
-        ).with_structured_output(
-            cast(StructuredResponseSchema, structured_response_schema)
-        )
-        response = model_with_structured_output.invoke(messages, config)
-        return {"structured_response": response}
-
-    async def agenerate_structured_response(
-        state: StateSchema, runtime: Runtime[ContextT], config: RunnableConfig
-    ) -> StateSchema:
-        messages = _get_state_value(state, "messages")
-        structured_response_schema = response_format
-        if isinstance(response_format, tuple):
-            system_prompt, structured_response_schema = response_format
-            messages = [SystemMessage(content=system_prompt)] + list(messages)
-
-        resolved_model = await _aresolve_model(state, runtime)
-        model_with_structured_output = _get_model(
-            resolved_model
-        ).with_structured_output(
-            cast(StructuredResponseSchema, structured_response_schema)
-        )
-        response = await model_with_structured_output.ainvoke(messages, config)
-        return {"structured_response": response}
-
     if not tool_calling_enabled:
         # Define a new graph
         workflow = StateGraph(state_schema=state_schema, context_schema=context_schema)
@@ -753,19 +726,6 @@ def create_react_agent(
             workflow.add_node("post_model_hook", post_model_hook)  # type: ignore[arg-type]
             workflow.add_edge("agent", "post_model_hook")
 
-        if response_format is not None:
-            workflow.add_node(
-                "generate_structured_response",
-                RunnableCallable(
-                    generate_structured_response,
-                    agenerate_structured_response,
-                ),
-            )
-            if post_model_hook is not None:
-                workflow.add_edge("post_model_hook", "generate_structured_response")
-            else:
-                workflow.add_edge("agent", "generate_structured_response")
-
         return workflow.compile(
             checkpointer=checkpointer,
             store=store,
@@ -777,16 +737,14 @@ def create_react_agent(
 
     # Define the function that determines whether to continue or not
     def should_continue(state: StateSchema) -> Union[str, list[Send]]:
+
+        post_model_node = "post_model_hook" if post_model_hook is not None else END
+                
         messages = _get_state_value(state, "messages")
         last_message = messages[-1]
         # If there is no function call, then we finish
         if not isinstance(last_message, AIMessage) or not last_message.tool_calls:
-            if post_model_hook is not None:
-                return "post_model_hook"
-            elif response_format is not None:
-                return "generate_structured_response"
-            else:
-                return END
+            return post_model_node
         # Otherwise if there is, we continue
         else:
             if version == "v1":
@@ -825,45 +783,19 @@ def create_react_agent(
     # Set the entrypoint as `agent`
     # This means that this node is the first one called
     workflow.set_entry_point(entrypoint)
-
     agent_paths = []
-    post_model_hook_paths = [entrypoint, "tools"]
 
     # Add a post model hook node if post_model_hook is provided
     if post_model_hook is not None:
         workflow.add_node("post_model_hook", post_model_hook)  # type: ignore[arg-type]
         agent_paths.append("post_model_hook")
         workflow.add_edge("agent", "post_model_hook")
-    else:
-        agent_paths.append("tools")
-
-    # Add a structured output node if response_format is provided
-    if response_format is not None:
-        workflow.add_node(
-            "generate_structured_response",
-            RunnableCallable(
-                generate_structured_response,
-                agenerate_structured_response,
-            ),
-        )
-        if post_model_hook is not None:
-            post_model_hook_paths.append("generate_structured_response")
-        else:
-            agent_paths.append("generate_structured_response")
-    else:
-        if post_model_hook is not None:
-            post_model_hook_paths.append(END)
-        else:
-            agent_paths.append(END)
-
-    if post_model_hook is not None:
 
         def post_model_hook_router(state: StateSchema) -> Union[str, list[Send]]:
             """Route to the next node after post_model_hook.
 
             Routes to one of:
             * "tools": if there are pending tool calls without a corresponding message.
-            * "generate_structured_response": if no pending tool calls exist and response_format is specified.
             * END: if no pending tool calls exist and no response_format is specified.
             """
 
@@ -886,16 +818,17 @@ def create_react_agent(
                 return [Send("tools", [tool_call]) for tool_call in pending_tool_calls]
             elif isinstance(messages[-1], ToolMessage):
                 return entrypoint
-            elif response_format is not None:
-                return "generate_structured_response"
             else:
                 return END
 
         workflow.add_conditional_edges(
             "post_model_hook",
             post_model_hook_router,
-            path_map=post_model_hook_paths,
+            path_map=[entrypoint, "tools", END],
         )
+    else:
+        agent_paths.append("tools")
+        agent_paths.append(END)
 
     workflow.add_conditional_edges(
         "agent",
@@ -903,7 +836,7 @@ def create_react_agent(
         path_map=agent_paths,
     )
 
-    def route_tool_responses(state: StateSchema) -> str:
+    def route_tool_responses(state: StateSchema) -> str | Command:
         for m in reversed(_get_state_value(state, "messages")):
             if not isinstance(m, ToolMessage):
                 break

libs/prebuilt/langgraph/prebuilt/tool_node.py

@@ -340,11 +340,19 @@ class ToolNode(RunnableCallable):
         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.structured_output_tools: list[str] = []
         self.handle_tool_errors = handle_tool_errors
         self.messages_key = messages_key
         for tool_ in tools:
-            if not isinstance(tool_, BaseTool):
+            if issubclass(tool_, BaseModel):
+                self.tools_by_name[tool_.__name__] = tool_
+                self.tool_to_state_args[tool_.__name__] = {}
+                self.tool_to_store_arg[tool_.__name__] = None
+                self.structured_output_tools.append(tool_.__name__)
+                continue
+            elif 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_)
@@ -437,11 +445,26 @@ class ToolNode(RunnableCallable):
         call: ToolCall,
         input_type: Literal["list", "dict", "tool_calls"],
         config: RunnableConfig,
-    ) -> ToolMessage:
+    ) -> ToolMessage | Command:
         """Run a single tool call synchronously."""
         if invalid_tool_message := self._validate_tool_call(call):
             return invalid_tool_message
         try:
+            if call["name"] in self.structured_output_tools:
+                response_schema = self.tools_by_name[call["name"]]
+                return Command(
+                    update={
+                        "messages": [
+                            ToolMessage(
+                                content="structured output generated",
+                                name="structured_output",
+                                tool_call_id=call["id"],
+                                status="success",
+                            ),
+                        ],
+                        "structured_response": response_schema(**call["args"]),
+                    }
+                )
             call_args = {**call, **{"type": "tool_call"}}
             response = self.tools_by_name[call["name"]].invoke(call_args, config)
 

libs/prebuilt/uv.lock

@@ -316,7 +316,7 @@ wheels = [
 
 [[package]]
 name = "langgraph"
-version = "0.6.6"
+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__ = "0.2.2"
+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/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
@@ -349,72 +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'" },
 ]
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 wheels = [
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-version = "1.2.0"
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 [[package]]
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-version = "2025.8.3"
+version = "2025.7.14"
 source = { registry = "https://pypi.org/simple" }
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 [[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 = [
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