From 13cac7f38b3294c45dffe843ea34cace17ab8dcc Mon Sep 17 00:00:00 2001
From: Nandan Luthra <nandan.luthra9@gmail.com>
Date: Mon, 3 Nov 2025 19:50:47 +0530
Subject: [PATCH] Update imports from langchain to langchain_core

---
 src/oss/langgraph/quickstart.mdx | 20 ++++++++++----------
 1 file changed, 10 insertions(+), 10 deletions(-)

diff --git a/src/oss/langgraph/quickstart.mdx b/src/oss/langgraph/quickstart.mdx
index e36faa6bbe..1286edfdaa 100644
--- a/src/oss/langgraph/quickstart.mdx
+++ b/src/oss/langgraph/quickstart.mdx
@@ -138,7 +138,7 @@ The graph's state is used to store the messages and the number of LLM calls.
 :::python
 
 ```python
-from langchain.messages import AnyMessage
+from langchain_core.messages import AnyMessage
 from typing_extensions import TypedDict, Annotated
 import operator
 
@@ -172,7 +172,7 @@ The model node is used to call the LLM and decide whether to call a tool or not.
 :::python
 
 ```python
-from langchain.messages import SystemMessage
+from langchain_core.messages import SystemMessage
 
 
 def llm_call(state: dict):
@@ -219,7 +219,7 @@ The tool node is used to call the tools and return the results.
 :::python
 
 ```python
-from langchain.messages import ToolMessage
+from langchain_core.messages import ToolMessage
 
 
 def tool_node(state: dict):
@@ -332,7 +332,7 @@ from IPython.display import Image, display
 display(Image(agent.get_graph(xray=True).draw_mermaid_png()))
 
 # Invoke
-from langchain.messages import HumanMessage
+from langchain_core.messages import HumanMessage
 messages = [HumanMessage(content="Add 3 and 4.")]
 messages = agent.invoke({"messages": messages})
 for m in messages["messages"]:
@@ -426,7 +426,7 @@ model_with_tools = model.bind_tools(tools)
 
 # Step 2: Define state
 
-from langchain.messages import AnyMessage
+from langchain_core.messages import AnyMessage
 from typing_extensions import TypedDict, Annotated
 import operator
 
@@ -436,7 +436,7 @@ class MessagesState(TypedDict):
     llm_calls: int
 
 # Step 3: Define model node
-from langchain.messages import SystemMessage
+from langchain_core.messages import SystemMessage
 
 
 def llm_call(state: dict):
@@ -459,7 +459,7 @@ def llm_call(state: dict):
 
 # Step 4: Define tool node
 
-from langchain.messages import ToolMessage
+from langchain_core.messages import ToolMessage
 
 
 def tool_node(state: dict):
@@ -519,7 +519,7 @@ from IPython.display import Image, display
 display(Image(agent.get_graph(xray=True).draw_mermaid_png()))
 
 # Invoke
-from langchain.messages import HumanMessage
+from langchain_core.messages import HumanMessage
 messages = [HumanMessage(content="Add 3 and 4.")]
 messages = agent.invoke({"messages": messages})
 for m in messages["messages"]:
@@ -725,7 +725,7 @@ tools_by_name = {tool.name: tool for tool in tools}
 model_with_tools = model.bind_tools(tools)
 
 from langgraph.graph import add_messages
-from langchain.messages import (
+from langchain_core.messages import (
     SystemMessage,
     HumanMessage,
     ToolCall,
@@ -987,7 +987,7 @@ tools_by_name = {tool.name: tool for tool in tools}
 model_with_tools = model.bind_tools(tools)
 
 from langgraph.graph import add_messages
-from langchain.messages import (
+from langchain_core.messages import (
     SystemMessage,
     HumanMessage,
     ToolCall,