InMemorySaver

README.md

@@ -60,7 +60,7 @@ from typing import Annotated, Literal, TypedDict
 from langchain_core.messages import HumanMessage
 from langchain_anthropic import ChatAnthropic
 from langchain_core.tools import tool
-from langgraph.checkpoint.memory import MemorySaver
+from langgraph.checkpoint.memory import InMemorySaver
 from langgraph.graph import END, START, StateGraph, MessagesState
 from langgraph.prebuilt import ToolNode
 
@@ -125,7 +125,7 @@ workflow.add_conditional_edges(
 workflow.add_edge("tools", 'agent')
 
 # Initialize memory to persist state between graph runs
-checkpointer = MemorySaver()
+checkpointer = InMemorySaver()
 
 # Finally, we compile it!
 # This compiles it into a LangChain Runnable,
@@ -201,7 +201,7 @@ final_state["messages"][-1].content
     <summary>Compile the graph.</summary>
 
     - When we compile the graph, we turn it into a LangChain [Runnable](https://python.langchain.com/v0.2/docs/concepts/#runnable-interface), which automatically enables calling `.invoke()`, `.stream()` and `.batch()` with your inputs
-    - We can also optionally pass checkpointer object for persisting state between graph runs, and enabling memory, human-in-the-loop workflows, time travel and more. In our case we use `MemorySaver` - a simple in-memory checkpointer
+    - We can also optionally pass checkpointer object for persisting state between graph runs, and enabling memory, human-in-the-loop workflows, time travel and more. In our case we use `InMemorySaver` - a simple in-memory checkpointer
     </details>
 
 6. <details>

docs/docs/cloud/how-tos/langgraph_to_langgraph_cloud.ipynb

@@ -392,7 +392,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "from langgraph.checkpoint.memory import MemorySaver"
+        "from langgraph.checkpoint.memory import InMemorySaver"
       ]
     },
     {
@@ -402,7 +402,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "checkpointer = MemorySaver()\n",
+        "checkpointer = InMemorySaver()\n",
         "graph_with_memory = create_react_agent(model, tools, checkpointer=checkpointer)"
       ]
     },

docs/docs/concepts/memory.md

@@ -148,7 +148,7 @@ LangGraph's [persistence layer](https://langchain-ai.github.io/langgraph/concept
 
 ```python
 # Compile the graph with a checkpointer
-checkpointer = MemorySaver()
+checkpointer = InMemorySaver()
 graph = workflow.compile(checkpointer=checkpointer)
 
 # Invoke the graph with a thread ID

docs/docs/concepts/persistence.md

@@ -26,7 +26,7 @@ Let's see what checkpoints are saved when a simple graph is invoked as follows:
 
 ```python
 from langgraph.graph import StateGraph, START, END
-from langgraph.checkpoint.memory import MemorySaver
+from langgraph.checkpoint.memory import InMemorySaver
 from typing import Annotated
 from typing_extensions import TypedDict
 from operator import add
@@ -49,7 +49,7 @@ workflow.add_edge(START, "node_a")
 workflow.add_edge("node_a", "node_b")
 workflow.add_edge("node_b", END)
 
-checkpointer = MemorySaver()
+checkpointer = InMemorySaver()
 graph = workflow.compile(checkpointer=checkpointer)
 
 config = {"configurable": {"thread_id": "1"}}
@@ -220,7 +220,7 @@ The final thing you can optionally specify when calling `update_state` is `as_no
 
 Under the hood, checkpointing is powered by checkpointer objects that conform to [BaseCheckpointSaver][langgraph.checkpoint.base.BaseCheckpointSaver] interface. LangGraph provides several checkpointer implementations, all implemented via standalone, installable libraries:
 
-* `langgraph-checkpoint`: The base interface for checkpointer savers ([BaseCheckpointSaver][langgraph.checkpoint.base.BaseCheckpointSaver]) and serialization/deserialization interface ([SerializerProtocol][langgraph.checkpoint.serde.base.SerializerProtocol]). Includes in-memory checkpointer implementation ([MemorySaver][langgraph.checkpoint.memory.MemorySaver]) for experimentation. LangGraph comes with `langgraph-checkpoint` included.
+* `langgraph-checkpoint`: The base interface for checkpointer savers ([BaseCheckpointSaver][langgraph.checkpoint.base.BaseCheckpointSaver]) and serialization/deserialization interface ([SerializerProtocol][langgraph.checkpoint.serde.base.SerializerProtocol]). Includes in-memory checkpointer implementation ([InMemorySaver][langgraph.checkpoint.memory.InMemorySaver]) for experimentation. LangGraph comes with `langgraph-checkpoint` included.
 * `langgraph-checkpoint-sqlite`: An implementation of LangGraph checkpointer that uses SQLite database ([SqliteSaver][langgraph.checkpoint.sqlite.SqliteSaver] / [AsyncSqliteSaver][langgraph.checkpoint.sqlite.aio.AsyncSqliteSaver]). Ideal for experimentation and local workflows. Needs to be installed separately.
 * `langgraph-checkpoint-postgres`: An advanced checkpointer that uses Postgres database ([PostgresSaver][langgraph.checkpoint.postgres.PostgresSaver] / [AsyncPostgresSaver][langgraph.checkpoint.postgres.aio.AsyncPostgresSaver]), used in LangGraph Cloud. Ideal for using in production. Needs to be installed separately.
 
@@ -236,7 +236,7 @@ Each checkpointer conforms to [BaseCheckpointSaver][langgraph.checkpoint.base.Ba
 If the checkpointer is used with asynchronous graph execution (i.e. executing the graph via `.ainvoke`, `.astream`, `.abatch`), asynchronous versions of the above methods will be used (`.aput`, `.aput_writes`, `.aget_tuple`, `.alist`).
 
 !!! note Note
-    For running your graph asynchronously, you can use `MemorySaver`, or async versions of Sqlite/Postgres checkpointers -- `AsyncSqliteSaver` / `AsyncPostgresSaver` checkpointers.
+    For running your graph asynchronously, you can use `InMemorySaver`, or async versions of Sqlite/Postgres checkpointers -- `AsyncSqliteSaver` / `AsyncPostgresSaver` checkpointers.
 
 ### Serializer
 

docs/docs/how-tos/create-react-agent-hitl.ipynb

@@ -135,9 +135,9 @@
     "tools = [get_weather]\n",
     "\n",
     "# We need a checkpointer to enable human-in-the-loop patterns\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "\n",
     "# Define the graph\n",
     "\n",

docs/docs/how-tos/create-react-agent-memory.ipynb

@@ -142,9 +142,9 @@
     "\n",
     "# We can add \"chat memory\" to the graph with LangGraph's checkpointer\n",
     "# to retain the chat context between interactions\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "\n",
     "# Define the graph\n",
     "\n",

docs/docs/how-tos/cross-thread-persistence.ipynb

@@ -154,7 +154,7 @@
     "from langchain_anthropic import ChatAnthropic\n",
     "from langchain_core.runnables import RunnableConfig\n",
     "from langgraph.graph import StateGraph, MessagesState, START\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from langgraph.store.base import BaseStore\n",
     "\n",
     "\n",
@@ -187,7 +187,7 @@
     "builder.add_edge(START, \"call_model\")\n",
     "\n",
     "# NOTE: we're passing the store object here when compiling the graph\n",
-    "graph = builder.compile(checkpointer=MemorySaver(), store=in_memory_store)\n",
+    "graph = builder.compile(checkpointer=InMemorySaver(), store=in_memory_store)\n",
     "# If you're using LangGraph Cloud or LangGraph Studio, you don't need to pass the store or checkpointer when compiling the graph, since it's done automatically."
    ]
   },

docs/docs/how-tos/human_in_the_loop/breakpoints.ipynb

@@ -124,7 +124,7 @@
    "source": [
     "from typing_extensions import TypedDict\n",
     "from langgraph.graph import StateGraph, START, END\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from IPython.display import Image, display\n",
     "\n",
     "\n",
@@ -157,7 +157,7 @@
     "builder.add_edge(\"step_3\", END)\n",
     "\n",
     "# Set up memory\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "\n",
     "# Add\n",
     "graph = builder.compile(checkpointer=memory, interrupt_before=[\"step_3\"])\n",
@@ -270,7 +270,7 @@
     "from langgraph.graph import MessagesState, START\n",
     "from langgraph.prebuilt import ToolNode\n",
     "from langgraph.graph import END, StateGraph\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "\n",
     "\n",
     "@tool\n",
@@ -352,7 +352,7 @@
     "workflow.add_edge(\"action\", \"agent\")\n",
     "\n",
     "# Set up memory\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "\n",
     "# Finally, we compile it!\n",
     "# This compiles it into a LangChain Runnable,\n",

docs/docs/how-tos/human_in_the_loop/dynamic_breakpoints.ipynb

@@ -78,7 +78,7 @@
     "from IPython.display import Image, display\n",
     "\n",
     "from langgraph.graph import StateGraph, START, END\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from langgraph.errors import NodeInterrupt\n",
     "\n",
     "\n",
@@ -118,7 +118,7 @@
     "builder.add_edge(\"step_3\", END)\n",
     "\n",
     "# Set up memory\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "\n",
     "# Compile the graph with memory\n",
     "graph = builder.compile(checkpointer=memory)\n",

docs/docs/how-tos/human_in_the_loop/edit-graph-state.ipynb

@@ -126,7 +126,7 @@
    "source": [
     "from typing_extensions import TypedDict\n",
     "from langgraph.graph import StateGraph, START, END\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from IPython.display import Image, display\n",
     "\n",
     "\n",
@@ -159,7 +159,7 @@
     "builder.add_edge(\"step_3\", END)\n",
     "\n",
     "# Set up memory\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "\n",
     "# Add\n",
     "graph = builder.compile(checkpointer=memory, interrupt_before=[\"step_2\"])\n",
@@ -279,7 +279,7 @@
     "from langchain_core.tools import tool\n",
     "from langgraph.graph import MessagesState, START, END, StateGraph\n",
     "from langgraph.prebuilt import ToolNode\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "\n",
     "\n",
     "@tool\n",
@@ -361,7 +361,7 @@
     "workflow.add_edge(\"action\", \"agent\")\n",
     "\n",
     "# Set up memory\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "\n",
     "# Finally, we compile it!\n",
     "# This compiles it into a LangChain Runnable,\n",

docs/docs/how-tos/human_in_the_loop/review-tool-calls.ipynb

@@ -120,7 +120,7 @@
    "source": [
     "from typing_extensions import TypedDict, Literal\n",
     "from langgraph.graph import StateGraph, START, END, MessagesState\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from langchain_anthropic import ChatAnthropic\n",
     "from langchain_core.tools import tool\n",
     "from langchain_core.messages import AIMessage\n",
@@ -195,7 +195,7 @@
     "builder.add_edge(\"run_tool\", \"call_llm\")\n",
     "\n",
     "# Set up memory\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "\n",
     "# Add\n",
     "graph = builder.compile(checkpointer=memory, interrupt_before=[\"human_review_node\"])\n",

docs/docs/how-tos/human_in_the_loop/time-travel.ipynb

@@ -115,7 +115,7 @@
     "from langgraph.graph import MessagesState, START\n",
     "from langgraph.prebuilt import ToolNode\n",
     "from langgraph.graph import END, StateGraph\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "\n",
     "\n",
     "@tool\n",
@@ -201,7 +201,7 @@
     "workflow.add_edge(\"action\", \"agent\")\n",
     "\n",
     "# Set up memory\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "\n",
     "# Finally, we compile it!\n",
     "# This compiles it into a LangChain Runnable,\n",

docs/docs/how-tos/human_in_the_loop/wait-user-input.ipynb

@@ -120,7 +120,7 @@
    "source": [
     "from typing_extensions import TypedDict\n",
     "from langgraph.graph import StateGraph, START, END\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from IPython.display import Image, display\n",
     "\n",
     "\n",
@@ -154,7 +154,7 @@
     "builder.add_edge(\"step_3\", END)\n",
     "\n",
     "# Set up memory\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "\n",
     "# Add\n",
     "graph = builder.compile(checkpointer=memory, interrupt_before=[\"human_feedback\"])\n",
@@ -475,9 +475,9 @@
     "workflow.add_edge(\"ask_human\", \"agent\")\n",
     "\n",
     "# Set up memory\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "\n",
     "# Finally, we compile it!\n",
     "# This compiles it into a LangChain Runnable,\n",

docs/docs/how-tos/memory/add-summary-conversation-history.ipynb

@@ -99,10 +99,10 @@
     "\n",
     "from langchain_anthropic import ChatAnthropic\n",
     "from langchain_core.messages import SystemMessage, RemoveMessage\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from langgraph.graph import MessagesState, StateGraph, START, END\n",
     "\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "\n",
     "\n",
     "# We will add a `summary` attribute (in addition to `messages` key,\n",

docs/docs/how-tos/memory/delete-messages.ipynb

@@ -106,11 +106,11 @@
     "from langchain_anthropic import ChatAnthropic\n",
     "from langchain_core.tools import tool\n",
     "\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from langgraph.graph import MessagesState, StateGraph, START, END\n",
     "from langgraph.prebuilt import ToolNode\n",
     "\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "\n",
     "\n",
     "@tool\n",

docs/docs/how-tos/memory/manage-conversation-history.ipynb

@@ -97,11 +97,11 @@
     "from langchain_anthropic import ChatAnthropic\n",
     "from langchain_core.tools import tool\n",
     "\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from langgraph.graph import MessagesState, StateGraph, START, END\n",
     "from langgraph.prebuilt import ToolNode\n",
     "\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "\n",
     "\n",
     "@tool\n",
@@ -228,11 +228,11 @@
     "from langchain_anthropic import ChatAnthropic\n",
     "from langchain_core.tools import tool\n",
     "\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from langgraph.graph import MessagesState, StateGraph, START\n",
     "from langgraph.prebuilt import ToolNode\n",
     "\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "\n",
     "\n",
     "@tool\n",

docs/docs/how-tos/pass-run-time-values-to-tools.ipynb

@@ -322,7 +322,7 @@
    "source": [
     "from langchain_openai import ChatOpenAI\n",
     "from langgraph.prebuilt import ToolNode, create_react_agent\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "\n",
     "model = ChatOpenAI(model=\"gpt-4o\", temperature=0)\n",
     "tools = [get_context]\n",
@@ -330,7 +330,7 @@
     "# ToolNode will automatically take care of injecting state into tools\n",
     "tool_node = ToolNode(tools)\n",
     "\n",
-    "checkpointer = MemorySaver()\n",
+    "checkpointer = InMemorySaver()\n",
     "graph = create_react_agent(model, tools, state_schema=State, checkpointer=checkpointer)"
    ]
   },
@@ -524,7 +524,7 @@
     "# ToolNode will automatically take care of injecting Store into tools\n",
     "tool_node = ToolNode(tools)\n",
     "\n",
-    "checkpointer = MemorySaver()\n",
+    "checkpointer = InMemorySaver()\n",
     "# NOTE: we need to pass our store to `create_react_agent` to make sure our graph is aware of it\n",
     "graph = create_react_agent(model, tools, checkpointer=checkpointer, store=doc_store)"
    ]

docs/docs/how-tos/persistence.ipynb

@@ -88,7 +88,7 @@
    "metadata": {},
    "outputs": [
     {
-     "name": "stdin",
+     "name": "stdout",
      "output_type": "stream",
      "text": [
       "ANTHROPIC_API_KEY:  ········\n"
@@ -237,9 +237,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "graph = builder.compile(checkpointer=memory)\n",
     "# If you're using LangGraph Cloud or LangGraph Studio, you don't need to pass the checkpointer when compiling the graph, since it's done automatically."
    ]

docs/docs/how-tos/streaming-subgraphs.ipynb

@@ -70,7 +70,7 @@
    "source": [
     "from typing import Optional, Annotated\n",
     "from typing_extensions import TypedDict\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from langgraph.graph import StateGraph, START, END\n",
     "\n",
     "\n",

docs/docs/how-tos/subgraph.ipynb

@@ -104,7 +104,7 @@
    "source": [
     "from typing import Optional, Annotated\n",
     "from typing_extensions import TypedDict\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from langgraph.graph import StateGraph, START, END\n",
     "\n",
     "\n",

docs/docs/how-tos/subgraphs-manage-state.ipynb

@@ -134,10 +134,10 @@
    "source": [
     "from typing import Literal\n",
     "from typing_extensions import TypedDict\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "\n",
     "\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "\n",
     "\n",
     "class RouterState(MessagesState):\n",
@@ -739,10 +739,10 @@
    "source": [
     "from typing import Literal\n",
     "from typing_extensions import TypedDict\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "\n",
     "\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "\n",
     "\n",
     "class RouterState(MessagesState):\n",
@@ -794,9 +794,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "\n",
     "\n",
     "class GrandfatherState(MessagesState):\n",
@@ -823,7 +823,7 @@
     "    \"router_node\", route_after_prediction, [\"graph\", END]\n",
     ")\n",
     "grandparent_graph.add_edge(\"graph\", END)\n",
-    "grandparent_graph = grandparent_graph.compile(checkpointer=MemorySaver())"
+    "grandparent_graph = grandparent_graph.compile(checkpointer=InMemorySaver())"
    ]
   },
   {

docs/docs/tutorials/chatbots/information-gather-prompting.ipynb

@@ -256,7 +256,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from langgraph.graph import StateGraph, START\n",
     "from langgraph.graph.message import add_messages\n",
     "from typing import Annotated\n",
@@ -267,7 +267,7 @@
     "    messages: Annotated[list, add_messages]\n",
     "\n",
     "\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "workflow = StateGraph(State)\n",
     "workflow.add_node(\"info\", info_chain)\n",
     "workflow.add_node(\"prompt\", prompt_gen_chain)\n",

docs/docs/tutorials/customer-support/customer-support.ipynb

@@ -1119,7 +1119,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from langgraph.graph import END, StateGraph, START\n",
     "from langgraph.prebuilt import tools_condition\n",
     "\n",
@@ -1139,7 +1139,7 @@
     "\n",
     "# The checkpointer lets the graph persist its state\n",
     "# this is a complete memory for the entire graph.\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "part_1_graph = builder.compile(checkpointer=memory)"
    ]
   },
@@ -1938,7 +1938,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from langgraph.graph import StateGraph\n",
     "from langgraph.prebuilt import tools_condition\n",
     "\n",
@@ -1962,7 +1962,7 @@
     ")\n",
     "builder.add_edge(\"tools\", \"assistant\")\n",
     "\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "part_2_graph = builder.compile(\n",
     "    checkpointer=memory,\n",
     "    # NEW: The graph will always halt before executing the \"tools\" node.\n",
@@ -2524,7 +2524,7 @@
    "source": [
     "from typing import Literal\n",
     "\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from langgraph.graph import StateGraph\n",
     "from langgraph.prebuilt import tools_condition\n",
     "\n",
@@ -2568,7 +2568,7 @@
     "builder.add_edge(\"safe_tools\", \"assistant\")\n",
     "builder.add_edge(\"sensitive_tools\", \"assistant\")\n",
     "\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "part_3_graph = builder.compile(\n",
     "    checkpointer=memory,\n",
     "    # NEW: The graph will always halt before executing the \"tools\" node.\n",
@@ -3466,7 +3466,7 @@
    "source": [
     "from typing import Literal\n",
     "\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from langgraph.graph import StateGraph\n",
     "from langgraph.prebuilt import tools_condition\n",
     "\n",
@@ -3830,7 +3830,7 @@
     "builder.add_conditional_edges(\"fetch_user_info\", route_to_workflow)\n",
     "\n",
     "# Compile graph\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "part_4_graph = builder.compile(\n",
     "    checkpointer=memory,\n",
     "    # Let the user approve or deny the use of sensitive tools\n",

docs/docs/tutorials/introduction.ipynb

@@ -793,7 +793,7 @@
     "\n",
     "We will see later that **checkpointing** is _much_ more powerful than simple chat memory - it lets you save and resume complex state at any time for error recovery, human-in-the-loop workflows, time travel interactions, and more. But before we get too ahead of ourselves, let's add checkpointing to enable multi-turn conversations.\n",
     "\n",
-    "To get started, create a `MemorySaver` checkpointer."
+    "To get started, create a `InMemorySaver` checkpointer."
    ]
   },
   {
@@ -803,9 +803,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "\n",
-    "memory = MemorySaver()"
+    "memory = InMemorySaver()"
    ]
   },
   {
@@ -1135,7 +1135,7 @@
     "from langchain_core.messages import BaseMessage\n",
     "from typing_extensions import TypedDict\n",
     "\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from langgraph.graph import StateGraph\n",
     "from langgraph.graph.message import add_messages\n",
     "from langgraph.prebuilt import ToolNode\n",
@@ -1203,12 +1203,12 @@
     "from langchain_community.tools.tavily_search import TavilySearchResults\n",
     "from typing_extensions import TypedDict\n",
     "\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from langgraph.graph import StateGraph, START\n",
     "from langgraph.graph.message import add_messages\n",
     "from langgraph.prebuilt import ToolNode, tools_condition\n",
     "\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "\n",
     "\n",
     "class State(TypedDict):\n",
@@ -1456,7 +1456,7 @@
     "from langchain_core.messages import BaseMessage\n",
     "from typing_extensions import TypedDict\n",
     "\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from langgraph.graph import StateGraph\n",
     "from langgraph.graph.message import add_messages\n",
     "from langgraph.prebuilt import ToolNode, tools_condition\n",
@@ -1491,7 +1491,7 @@
     "graph_builder.add_edge(\"tools\", \"chatbot\")\n",
     "graph_builder.set_entry_point(\"chatbot\")\n",
     "\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "graph = graph_builder.compile(\n",
     "    checkpointer=memory,\n",
     "    # This is new!\n",
@@ -1531,7 +1531,7 @@
     "from langchain_community.tools.tavily_search import TavilySearchResults\n",
     "from typing_extensions import TypedDict\n",
     "\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from langgraph.graph import StateGraph, START\n",
     "from langgraph.graph.message import add_messages\n",
     "from langgraph.prebuilt import ToolNode, tools_condition\n",
@@ -1565,7 +1565,7 @@
     ")\n",
     "graph_builder.add_edge(\"tools\", \"chatbot\")\n",
     "graph_builder.add_edge(START, \"chatbot\")\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "graph = graph_builder.compile(\n",
     "    checkpointer=memory,\n",
     "    # This is new!\n",
@@ -2066,7 +2066,7 @@
     "from langchain_community.tools.tavily_search import TavilySearchResults\n",
     "from typing_extensions import TypedDict\n",
     "\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from langgraph.graph import StateGraph, START\n",
     "from langgraph.graph.message import add_messages\n",
     "from langgraph.prebuilt import ToolNode, tools_condition\n",
@@ -2267,7 +2267,7 @@
     "graph_builder.add_edge(\"tools\", \"chatbot\")\n",
     "graph_builder.add_edge(\"human\", \"chatbot\")\n",
     "graph_builder.add_edge(START, \"chatbot\")\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "graph = graph_builder.compile(\n",
     "    checkpointer=memory,\n",
     "    # We interrupt before 'human' here instead.\n",
@@ -2542,7 +2542,7 @@
     "from pydantic import BaseModel\n",
     "from typing_extensions import TypedDict\n",
     "\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from langgraph.graph import StateGraph\n",
     "from langgraph.graph.message import add_messages\n",
     "from langgraph.prebuilt import ToolNode, tools_condition\n",
@@ -2629,7 +2629,7 @@
     "graph_builder.add_edge(\"tools\", \"chatbot\")\n",
     "graph_builder.add_edge(\"human\", \"chatbot\")\n",
     "graph_builder.set_entry_point(\"chatbot\")\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "graph = graph_builder.compile(\n",
     "    checkpointer=memory,\n",
     "    interrupt_before=[\"human\"],\n",
@@ -2674,7 +2674,7 @@
     "from pydantic import BaseModel\n",
     "from typing_extensions import TypedDict\n",
     "\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from langgraph.graph import StateGraph, START\n",
     "from langgraph.graph.message import add_messages\n",
     "from langgraph.prebuilt import ToolNode, tools_condition\n",
@@ -2761,7 +2761,7 @@
     "graph_builder.add_edge(\"tools\", \"chatbot\")\n",
     "graph_builder.add_edge(\"human\", \"chatbot\")\n",
     "graph_builder.add_edge(START, \"chatbot\")\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "graph = graph_builder.compile(\n",
     "    checkpointer=memory,\n",
     "    interrupt_before=[\"human\"],\n",

docs/docs/tutorials/reflection/reflection.ipynb

@@ -322,7 +322,7 @@
     "from typing import Annotated, List, Sequence\n",
     "from langgraph.graph import END, StateGraph, START\n",
     "from langgraph.graph.message import add_messages\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from typing_extensions import TypedDict\n",
     "\n",
     "\n",
@@ -361,7 +361,7 @@
     "\n",
     "builder.add_conditional_edges(\"generate\", should_continue)\n",
     "builder.add_edge(\"reflect\", \"generate\")\n",
-    "memory = MemorySaver()\n",
+    "memory = InMemorySaver()\n",
     "graph = builder.compile(checkpointer=memory)"
    ]
   },

docs/docs/tutorials/storm/storm.ipynb

@@ -1514,7 +1514,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "\n",
     "builder_of_storm = StateGraph(ResearchState)\n",
     "\n",
@@ -1534,7 +1534,7 @@
     "\n",
     "builder_of_storm.add_edge(START, nodes[0][0])\n",
     "builder_of_storm.add_edge(nodes[-1][0], END)\n",
-    "storm = builder_of_storm.compile(checkpointer=MemorySaver())"
+    "storm = builder_of_storm.compile(checkpointer=InMemorySaver())"
    ]
   },
   {

docs/docs/tutorials/usaco/usaco.ipynb

@@ -1029,7 +1029,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from langgraph.graph import END, StateGraph, START\n",
     "\n",
     "builder = StateGraph(State)\n",
@@ -1053,7 +1053,7 @@
     "builder.add_conditional_edges(\"evaluate\", control_edge, {END: END, \"solve\": \"solve\"})\n",
     "\n",
     "\n",
-    "checkpointer = MemorySaver()\n",
+    "checkpointer = InMemorySaver()\n",
     "graph = builder.compile(checkpointer=checkpointer)"
    ]
   },
@@ -1327,7 +1327,7 @@
    "outputs": [],
    "source": [
     "# This is all the same as before\n",
-    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.checkpoint.memory import InMemorySaver\n",
     "from langgraph.graph import END, StateGraph, START\n",
     "\n",
     "builder = StateGraph(State)\n",
@@ -1353,7 +1353,7 @@
     "\n",
     "\n",
     "builder.add_conditional_edges(\"evaluate\", control_edge, {END: END, \"solve\": \"solve\"})\n",
-    "checkpointer = MemorySaver()"
+    "checkpointer = InMemorySaver()"
    ]
   },
   {

examples/code_assistant/langgraph_code_assistant_mistral.ipynb

@@ -154,7 +154,7 @@
    "id": "2dff2209-44c7-4e2c-b607-ba6675f9e45f",
    "metadata": {},
    "outputs": [],
-   "source": ["from langgraph.checkpoint.memory import MemorySaver\nfrom langgraph.graph import END, StateGraph, START\n\nbuilder = StateGraph(GraphState)\n\n# Define the nodes\nbuilder.add_node(\"generate\", generate)  # generation solution\nbuilder.add_node(\"check_code\", code_check)  # check code\n\n# Build graph\nbuilder.add_edge(START, \"generate\")\nbuilder.add_edge(\"generate\", \"check_code\")\nbuilder.add_conditional_edges(\n    \"check_code\",\n    decide_to_finish,\n    {\n        \"end\": END,\n        \"generate\": \"generate\",\n    },\n)\n\nmemory = MemorySaver()\ngraph = builder.compile(checkpointer=memory)"]
+   "source": ["from langgraph.checkpoint.memory import InMemorySaver\nfrom langgraph.graph import END, StateGraph, START\n\nbuilder = StateGraph(GraphState)\n\n# Define the nodes\nbuilder.add_node(\"generate\", generate)  # generation solution\nbuilder.add_node(\"check_code\", code_check)  # check code\n\n# Build graph\nbuilder.add_edge(START, \"generate\")\nbuilder.add_edge(\"generate\", \"check_code\")\nbuilder.add_conditional_edges(\n    \"check_code\",\n    decide_to_finish,\n    {\n        \"end\": END,\n        \"generate\": \"generate\",\n    },\n)\n\nmemory = InMemorySaver()\ngraph = builder.compile(checkpointer=memory)"]
   },
   {
    "cell_type": "code",

libs/checkpoint/README.md

@@ -44,12 +44,12 @@ If the checkpointer will be used with asynchronous graph execution (i.e. executi
 ## Usage
 
 ```python
-from langgraph.checkpoint.memory import MemorySaver
+from langgraph.checkpoint.memory import InMemorySaver
 
 write_config = {"configurable": {"thread_id": "1", "checkpoint_ns": ""}}
 read_config = {"configurable": {"thread_id": "1"}}
 
-checkpointer = MemorySaver()
+checkpointer = InMemorySaver()
 checkpoint = {
     "v": 1,
     "ts": "2024-07-31T20:14:19.804150+00:00",

libs/checkpoint/langgraph/checkpoint/memory/__init__.py

@@ -21,7 +21,7 @@ from langgraph.checkpoint.base import (
 from langgraph.checkpoint.serde.types import TASKS, ChannelProtocol
 
 
-class MemorySaver(
+class InMemorySaver(
     BaseCheckpointSaver[str], AbstractContextManager, AbstractAsyncContextManager
 ):
     """An in-memory checkpoint saver.
@@ -29,7 +29,7 @@ class MemorySaver(
     This checkpoint saver stores checkpoints in memory using a defaultdict.
 
     Note:
-        Only use `MemorySaver` for debugging or testing purposes.
+        Only use `InMemorySaver` for debugging or testing purposes.
         For production use cases we recommend installing [langgraph-checkpoint-postgres](https://pypi.org/project/langgraph-checkpoint-postgres/) and using `PostgresSaver` / `AsyncPostgresSaver`.
 
     Args:
@@ -39,7 +39,7 @@ class MemorySaver(
 
             import asyncio
 
-            from langgraph.checkpoint.memory import MemorySaver
+            from langgraph.checkpoint.memory import InMemorySaver
             from langgraph.graph import StateGraph
 
             builder = StateGraph(int)
@@ -47,7 +47,7 @@ class MemorySaver(
             builder.set_entry_point("add_one")
             builder.set_finish_point("add_one")
 
-            memory = MemorySaver()
+            memory = InMemorySaver()
             graph = builder.compile(checkpointer=memory)
             coro = graph.ainvoke(1, {"configurable": {"thread_id": "thread-1"}})
             asyncio.run(coro)  # Output: 2
@@ -73,7 +73,7 @@ class MemorySaver(
         self.storage = defaultdict(lambda: defaultdict(dict))
         self.writes = defaultdict(dict)
 
-    def __enter__(self) -> "MemorySaver":
+    def __enter__(self) -> "InMemorySaver":
         return self
 
     def __exit__(
@@ -84,7 +84,7 @@ class MemorySaver(
     ) -> Optional[bool]:
         return
 
-    async def __aenter__(self) -> "MemorySaver":
+    async def __aenter__(self) -> "InMemorySaver":
         return self
 
     async def __aexit__(
@@ -135,15 +135,17 @@ class MemorySaver(
                     pending_writes=[
                         (id, c, self.serde.loads_typed(v)) for id, c, v in writes
                     ],
-                    parent_config={
-                        "configurable": {
-                            "thread_id": thread_id,
-                            "checkpoint_ns": checkpoint_ns,
-                            "checkpoint_id": parent_checkpoint_id,
+                    parent_config=(
+                        {
+                            "configurable": {
+                                "thread_id": thread_id,
+                                "checkpoint_ns": checkpoint_ns,
+                                "checkpoint_id": parent_checkpoint_id,
+                            }
                         }
-                    }
-                    if parent_checkpoint_id
-                    else None,
+                        if parent_checkpoint_id
+                        else None
+                    ),
                 )
         else:
             if checkpoints := self.storage[thread_id][checkpoint_ns]:
@@ -176,15 +178,17 @@ class MemorySaver(
                     pending_writes=[
                         (id, c, self.serde.loads_typed(v)) for id, c, v in writes
                     ],
-                    parent_config={
-                        "configurable": {
-                            "thread_id": thread_id,
-                            "checkpoint_ns": checkpoint_ns,
-                            "checkpoint_id": parent_checkpoint_id,
+                    parent_config=(
+                        {
+                            "configurable": {
+                                "thread_id": thread_id,
+                                "checkpoint_ns": checkpoint_ns,
+                                "checkpoint_id": parent_checkpoint_id,
+                            }
                         }
-                    }
-                    if parent_checkpoint_id
-                    else None,
+                        if parent_checkpoint_id
+                        else None
+                    ),
                 )
 
     def list(
@@ -285,15 +289,17 @@ class MemorySaver(
                             "pending_sends": [self.serde.loads_typed(s) for s in sends],
                         },
                         metadata=metadata,
-                        parent_config={
-                            "configurable": {
-                                "thread_id": thread_id,
-                                "checkpoint_ns": checkpoint_ns,
-                                "checkpoint_id": parent_checkpoint_id,
+                        parent_config=(
+                            {
+                                "configurable": {
+                                    "thread_id": thread_id,
+                                    "checkpoint_ns": checkpoint_ns,
+                                    "checkpoint_id": parent_checkpoint_id,
+                                }
                             }
-                        }
-                        if parent_checkpoint_id
-                        else None,
+                            if parent_checkpoint_id
+                            else None
+                        ),
                         pending_writes=[
                             (id, c, self.serde.loads_typed(v)) for id, c, v in writes
                         ],
@@ -474,3 +480,6 @@ class MemorySaver(
         next_v = current_v + 1
         next_h = random.random()
         return f"{next_v:032}.{next_h:016}"
+
+
+MemorySaver = InMemorySaver  # Kept for backwards compatibility

libs/checkpoint/tests/test_memory.py

@@ -9,13 +9,13 @@ from langgraph.checkpoint.base import (
     create_checkpoint,
     empty_checkpoint,
 )
-from langgraph.checkpoint.memory import MemorySaver
+from langgraph.checkpoint.memory import InMemorySaver
 
 
 class TestMemorySaver:
     @pytest.fixture(autouse=True)
     def setup(self) -> None:
-        self.memory_saver = MemorySaver()
+        self.memory_saver = InMemorySaver()
 
         # objects for test setup
         self.config_1: RunnableConfig = {

libs/langgraph/README.md

@@ -60,7 +60,7 @@ from typing import Annotated, Literal, TypedDict
 from langchain_core.messages import HumanMessage
 from langchain_anthropic import ChatAnthropic
 from langchain_core.tools import tool
-from langgraph.checkpoint.memory import MemorySaver
+from langgraph.checkpoint.memory import InMemorySaver
 from langgraph.graph import END, START, StateGraph, MessagesState
 from langgraph.prebuilt import ToolNode
 
@@ -125,7 +125,7 @@ workflow.add_conditional_edges(
 workflow.add_edge("tools", 'agent')
 
 # Initialize memory to persist state between graph runs
-checkpointer = MemorySaver()
+checkpointer = InMemorySaver()
 
 # Finally, we compile it!
 # This compiles it into a LangChain Runnable,
@@ -201,7 +201,7 @@ final_state["messages"][-1].content
     <summary>Compile the graph.</summary>
 
     - When we compile the graph, we turn it into a LangChain [Runnable](https://python.langchain.com/v0.2/docs/concepts/#runnable-interface), which automatically enables calling `.invoke()`, `.stream()` and `.batch()` with your inputs
-    - We can also optionally pass checkpointer object for persisting state between graph runs, and enabling memory, human-in-the-loop workflows, time travel and more. In our case we use `MemorySaver` - a simple in-memory checkpointer
+    - We can also optionally pass checkpointer object for persisting state between graph runs, and enabling memory, human-in-the-loop workflows, time travel and more. In our case we use `InMemorySaver` - a simple in-memory checkpointer
     </details>
 
 6. <details>

libs/langgraph/bench/__main__.py

@@ -8,7 +8,7 @@ from uvloop import new_event_loop
 from bench.fanout_to_subgraph import fanout_to_subgraph, fanout_to_subgraph_sync
 from bench.react_agent import react_agent
 from bench.wide_state import wide_state
-from langgraph.checkpoint.memory import MemorySaver
+from langgraph.checkpoint.memory import InMemorySaver
 from langgraph.pregel import Pregel
 
 
@@ -55,8 +55,8 @@ benchmarks = (
     ),
     (
         "fanout_to_subgraph_10x_checkpoint",
-        fanout_to_subgraph().compile(checkpointer=MemorySaver()),
-        fanout_to_subgraph_sync().compile(checkpointer=MemorySaver()),
+        fanout_to_subgraph().compile(checkpointer=InMemorySaver()),
+        fanout_to_subgraph_sync().compile(checkpointer=InMemorySaver()),
         {
             "subjects": [
                 random.choices("abcdefghijklmnopqrstuvwxyz", k=1000) for _ in range(10)
@@ -75,8 +75,8 @@ benchmarks = (
     ),
     (
         "fanout_to_subgraph_100x_checkpoint",
-        fanout_to_subgraph().compile(checkpointer=MemorySaver()),
-        fanout_to_subgraph_sync().compile(checkpointer=MemorySaver()),
+        fanout_to_subgraph().compile(checkpointer=InMemorySaver()),
+        fanout_to_subgraph_sync().compile(checkpointer=InMemorySaver()),
         {
             "subjects": [
                 random.choices("abcdefghijklmnopqrstuvwxyz", k=1000) for _ in range(100)
@@ -91,8 +91,8 @@ benchmarks = (
     ),
     (
         "react_agent_10x_checkpoint",
-        react_agent(10, checkpointer=MemorySaver()),
-        react_agent(10, checkpointer=MemorySaver()),
+        react_agent(10, checkpointer=InMemorySaver()),
+        react_agent(10, checkpointer=InMemorySaver()),
         {"messages": [HumanMessage("hi?")]},
     ),
     (
@@ -103,8 +103,8 @@ benchmarks = (
     ),
     (
         "react_agent_100x_checkpoint",
-        react_agent(100, checkpointer=MemorySaver()),
-        react_agent(100, checkpointer=MemorySaver()),
+        react_agent(100, checkpointer=InMemorySaver()),
+        react_agent(100, checkpointer=InMemorySaver()),
         {"messages": [HumanMessage("hi?")]},
     ),
     (
@@ -125,8 +125,8 @@ benchmarks = (
     ),
     (
         "wide_state_25x300_checkpoint",
-        wide_state(300).compile(checkpointer=MemorySaver()),
-        wide_state(300).compile(checkpointer=MemorySaver()),
+        wide_state(300).compile(checkpointer=InMemorySaver()),
+        wide_state(300).compile(checkpointer=InMemorySaver()),
         {
             "messages": [
                 {
@@ -157,8 +157,8 @@ benchmarks = (
     ),
     (
         "wide_state_15x600_checkpoint",
-        wide_state(600).compile(checkpointer=MemorySaver()),
-        wide_state(600).compile(checkpointer=MemorySaver()),
+        wide_state(600).compile(checkpointer=InMemorySaver()),
+        wide_state(600).compile(checkpointer=InMemorySaver()),
         {
             "messages": [
                 {
@@ -189,8 +189,8 @@ benchmarks = (
     ),
     (
         "wide_state_9x1200_checkpoint",
-        wide_state(1200).compile(checkpointer=MemorySaver()),
-        wide_state(1200).compile(checkpointer=MemorySaver()),
+        wide_state(1200).compile(checkpointer=InMemorySaver()),
+        wide_state(1200).compile(checkpointer=InMemorySaver()),
         {
             "messages": [
                 {

libs/langgraph/bench/fanout_to_subgraph.py

@@ -107,9 +107,9 @@ if __name__ == "__main__":
 
     import uvloop
 
-    from langgraph.checkpoint.memory import MemorySaver
+    from langgraph.checkpoint.memory import InMemorySaver
 
-    graph = fanout_to_subgraph().compile(checkpointer=MemorySaver())
+    graph = fanout_to_subgraph().compile(checkpointer=InMemorySaver())
     input = {
         "subjects": [
             random.choices("abcdefghijklmnopqrstuvwxyz", k=1000) for _ in range(1000)

libs/langgraph/bench/react_agent.py

@@ -68,9 +68,9 @@ if __name__ == "__main__":
 
     import uvloop
 
-    from langgraph.checkpoint.memory import MemorySaver
+    from langgraph.checkpoint.memory import InMemorySaver
 
-    graph = react_agent(100, checkpointer=MemorySaver())
+    graph = react_agent(100, checkpointer=InMemorySaver())
     input = {"messages": [HumanMessage("hi?")]}
     config = {"configurable": {"thread_id": "1"}, "recursion_limit": 20000000000}
 

libs/langgraph/bench/wide_state.py

@@ -116,9 +116,9 @@ if __name__ == "__main__":
 
     import uvloop
 
-    from langgraph.checkpoint.memory import MemorySaver
+    from langgraph.checkpoint.memory import InMemorySaver
 
-    graph = wide_state(1000).compile(checkpointer=MemorySaver())
+    graph = wide_state(1000).compile(checkpointer=InMemorySaver())
     input = {
         "messages": [
             {

libs/langgraph/langgraph/graph/state.py

@@ -90,7 +90,7 @@ class StateGraph(Graph):
     Examples:
         >>> from langchain_core.runnables import RunnableConfig
         >>> from typing_extensions import Annotated, TypedDict
-        >>> from langgraph.checkpoint.memory import MemorySaver
+        >>> from langgraph.checkpoint.memory import InMemorySaver
         >>> from langgraph.graph import StateGraph
         >>>
         >>> def reducer(a: list, b: int | None) -> list:

libs/langgraph/langgraph/prebuilt/chat_agent_executor.py

@@ -372,8 +372,8 @@ def create_react_agent(
         Add thread-level "chat memory" to the graph:
 
         ```pycon
-        >>> from langgraph.checkpoint.memory import MemorySaver
-        >>> graph = create_react_agent(model, tools, checkpointer=MemorySaver())
+        >>> from langgraph.checkpoint.memory import InMemorySaver
+        >>> graph = create_react_agent(model, tools, checkpointer=InMemorySaver())
         >>> config = {"configurable": {"thread_id": "thread-1"}}
         >>> def print_stream(graph, inputs, config):
         ...     for s in graph.stream(inputs, config, stream_mode="values"):
@@ -408,7 +408,7 @@ def create_react_agent(
 
         ```pycon
         >>> graph = create_react_agent(
-        ...     model, tools, interrupt_before=["tools"], checkpointer=MemorySaver()
+        ...     model, tools, interrupt_before=["tools"], checkpointer=InMemorySaver()
         >>> )
         >>> config = {"configurable": {"thread_id": "thread-1"}}
 
@@ -442,10 +442,10 @@ def create_react_agent(
         ...     system_msg = f"User memories: {', '.join(memories)}"
         ...     return [{"role": "system", "content": system_msg)] + state["messages"]
 
-        >>> from langgraph.checkpoint.memory import MemorySaver
+        >>> from langgraph.checkpoint.memory import InMemorySaver
         >>> from langgraph.store.memory import InMemoryStore
         >>> store = InMemoryStore()
-        >>> graph = create_react_agent(model, [save_memory], state_modifier=prepare_model_inputs, store=store, checkpointer=MemorySaver())
+        >>> graph = create_react_agent(model, [save_memory], state_modifier=prepare_model_inputs, store=store, checkpointer=InMemorySaver())
         >>> config = {"configurable": {"thread_id": "thread-1", "user_id": "1"}}
 
         >>> inputs = {"messages": [("user", "Hey I'm Will, how's it going?")]}

libs/langgraph/tests/memory_assert.py

@@ -12,7 +12,7 @@ from langgraph.checkpoint.base import (
     SerializerProtocol,
     copy_checkpoint,
 )
-from langgraph.checkpoint.memory import MemorySaver
+from langgraph.checkpoint.memory import InMemorySaver
 
 
 class NoopSerializer(SerializerProtocol):
@@ -23,7 +23,7 @@ class NoopSerializer(SerializerProtocol):
         return "type", obj
 
 
-class MemorySaverAssertImmutable(MemorySaver):
+class MemorySaverAssertImmutable(InMemorySaver):
     storage_for_copies: defaultdict[str, dict[str, dict[str, Checkpoint]]]
 
     def __init__(
@@ -64,7 +64,7 @@ class MemorySaverAssertImmutable(MemorySaver):
         return super().put(config, checkpoint, metadata, new_versions)
 
 
-class MemorySaverAssertCheckpointMetadata(MemorySaver):
+class MemorySaverAssertCheckpointMetadata(InMemorySaver):
     """This custom checkpointer is for verifying that a run's configurable
     fields are merged with the previous checkpoint config for each step in
     the run. This is the desired behavior. Because the checkpointer's (a)put()
@@ -119,7 +119,7 @@ class MemorySaverAssertCheckpointMetadata(MemorySaver):
         )
 
 
-class MemorySaverNoPending(MemorySaver):
+class MemorySaverNoPending(InMemorySaver):
     def get_tuple(self, config: RunnableConfig) -> Optional[CheckpointTuple]:
         result = super().get_tuple(config)
         if result:

libs/langgraph/tests/test_pregel.py

@@ -53,7 +53,7 @@ from langgraph.checkpoint.base import (
     CheckpointMetadata,
     CheckpointTuple,
 )
-from langgraph.checkpoint.memory import MemorySaver
+from langgraph.checkpoint.memory import InMemorySaver
 from langgraph.constants import ERROR, PULL, PUSH
 from langgraph.errors import InvalidUpdateError, MultipleSubgraphsError, NodeInterrupt
 from langgraph.graph import END, Graph
@@ -268,11 +268,11 @@ def test_graph_validation() -> None:
 
 
 def test_checkpoint_errors() -> None:
-    class FaultyGetCheckpointer(MemorySaver):
+    class FaultyGetCheckpointer(InMemorySaver):
         def get_tuple(self, config: RunnableConfig) -> Optional[CheckpointTuple]:
             raise ValueError("Faulty get_tuple")
 
-    class FaultyPutCheckpointer(MemorySaver):
+    class FaultyPutCheckpointer(InMemorySaver):
         def put(
             self,
             config: RunnableConfig,
@@ -282,13 +282,13 @@ def test_checkpoint_errors() -> None:
         ) -> RunnableConfig:
             raise ValueError("Faulty put")
 
-    class FaultyPutWritesCheckpointer(MemorySaver):
+    class FaultyPutWritesCheckpointer(InMemorySaver):
         def put_writes(
             self, config: RunnableConfig, writes: List[Tuple[str, Any]], task_id: str
         ) -> RunnableConfig:
             raise ValueError("Faulty put_writes")
 
-    class FaultyVersionCheckpointer(MemorySaver):
+    class FaultyVersionCheckpointer(InMemorySaver):
         def get_next_version(self, current: Optional[int], channel: BaseChannel) -> int:
             raise ValueError("Faulty get_next_version")
 
@@ -11250,7 +11250,7 @@ def test_xray_lance(snapshot: SnapshotAssertion):
     interview_builder.add_conditional_edges("answer_question", route_messages)
 
     # Set up memory
-    memory = MemorySaver()
+    memory = InMemorySaver()
 
     # Interview
     interview_graph = interview_builder.compile(checkpointer=memory).with_config(
@@ -11478,7 +11478,7 @@ def test_subgraph_retries():
     parent.add_edge("parent_node", "child_graph")
     parent.set_entry_point("parent_node")
 
-    checkpointer = MemorySaver()
+    checkpointer = InMemorySaver()
     app = parent.compile(checkpointer=checkpointer)
     with pytest.raises(RandomError):
         app.invoke({"count": 0}, {"configurable": {"thread_id": "foo"}})

libs/langgraph/tests/test_pregel_async.py

@@ -49,7 +49,7 @@ from langgraph.checkpoint.base import (
     CheckpointMetadata,
     CheckpointTuple,
 )
-from langgraph.checkpoint.memory import MemorySaver
+from langgraph.checkpoint.memory import InMemorySaver
 from langgraph.constants import ERROR, PULL, PUSH
 from langgraph.errors import InvalidUpdateError, MultipleSubgraphsError, NodeInterrupt
 from langgraph.graph import END, Graph, StateGraph
@@ -89,11 +89,11 @@ pytestmark = pytest.mark.anyio
 
 
 async def test_checkpoint_errors() -> None:
-    class FaultyGetCheckpointer(MemorySaver):
+    class FaultyGetCheckpointer(InMemorySaver):
         async def aget_tuple(self, config: RunnableConfig) -> Optional[CheckpointTuple]:
             raise ValueError("Faulty get_tuple")
 
-    class FaultyPutCheckpointer(MemorySaver):
+    class FaultyPutCheckpointer(InMemorySaver):
         async def aput(
             self,
             config: RunnableConfig,
@@ -103,13 +103,13 @@ async def test_checkpoint_errors() -> None:
         ) -> RunnableConfig:
             raise ValueError("Faulty put")
 
-    class FaultyPutWritesCheckpointer(MemorySaver):
+    class FaultyPutWritesCheckpointer(InMemorySaver):
         async def aput_writes(
             self, config: RunnableConfig, writes: List[Tuple[str, Any]], task_id: str
         ) -> RunnableConfig:
             raise ValueError("Faulty put_writes")
 
-    class FaultyVersionCheckpointer(MemorySaver):
+    class FaultyVersionCheckpointer(InMemorySaver):
         def get_next_version(self, current: Optional[int], channel: BaseChannel) -> int:
             raise ValueError("Faulty get_next_version")