Feat/ext langgraph checkpoint

examples/langgraph-checkpointer/README.md

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+# Dapr For Agents - LangGraph Checkpointer
+
+Supporting Dapr backed Checkpointer for LangGraph based Agents.
+
+## Pre-requisites
+
+- [Dapr CLI and initialized environment](https://docs.dapr.io/getting-started)
+- [Install Python 3.10+](https://www.python.org/downloads/)
+
+## Install Dapr python-SDK
+
+<!-- Our CI/CD pipeline automatically installs the correct version, so we can skip this step in the automation -->
+
+```bash
+pip3 install -r requirements.txt
+```
+
+## Run the example
+
+Export your `OPENAI_API_KEY`:
+
+```bash
+export OPENAI_API_KEY="SK-..."
+```
+
+Run the following command in a terminal/command prompt:
+
+<!-- STEP
+name: Run subscriber
+expected_stdout_lines:
+  - '== APP == Add 3 and 4.'
+  - '== APP == Tool Calls:'
+  - '== APP ==   add'
+  - '== APP ==  Call'
+  - '== APP ==     a: 3'
+  - '== APP ==     b: 4'
+  - '== APP == Name: add'
+  - '== APP == 7'
+  - '== APP == The result of adding 3 and 4 is 7.'
+  - '== APP == Multiply that by 2.'
+  - '== APP ==   Args:'
+  - '== APP ==     a: 7'
+  - '== APP ==     b: 2'
+  - '== APP == ================================= Tool Message ================================='
+  - '== APP == Name: multiply'
+  - '== APP == '
+  - '== APP == 14'
+  - '== APP == ================================== Ai Message =================================='
+  - '== APP == '
+  - '== APP == The result of multiplying 7 by 2 is 14.'
+
+output_match_mode: substring
+background: true
+match_order: none
+sleep: 15
+-->
+
+```bash
+# 1. Run the LangGraph agent
+dapr run --app-id langgraph-checkpointer --app-port 5001 -- python3 agent.py
+```
+
+<!-- END_STEP -->
+
+## Cleanup
+
+Either press CTRL + C to quit the app or run the following command in a new terminal to stop the app:
+
+```bash
+dapr stop --app-id langgraph-checkpointer
+```
+

examples/langgraph-checkpointer/agent.py

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+import os
+
+from dapr.ext.langgraph import DaprCheckpointer
+from langchain_core.messages import HumanMessage, SystemMessage
+from langchain_openai import ChatOpenAI
+from langgraph.graph import START, MessagesState, StateGraph
+from langgraph.prebuilt import ToolNode, tools_condition
+
+
+def add(a: int, b: int) -> int:
+    """Adds a and b.
+
+    Args:
+        a: first int
+        b: second int
+    """
+    return a + b
+
+
+def multiply(a: int, b: int) -> int:
+    """Multiply a and b.
+
+    Args:
+        a: first int
+        b: second int
+    """
+    return a * b
+
+
+tools = [add, multiply]
+llm = ChatOpenAI(model='gpt-4o', api_key=os.environ['OPENAI_API_KEY'])
+llm_with_tools = llm.bind_tools(tools)
+
+sys_msg = SystemMessage(
+    content='You are a helpful assistant tasked with performing arithmetic on a set of inputs.'
+)
+
+
+def assistant(state: MessagesState):
+    return {'messages': [llm_with_tools.invoke([sys_msg] + state['messages'])]}
+
+
+builder = StateGraph(MessagesState)
+
+builder.add_node('assistant', assistant)
+builder.add_node('tools', ToolNode(tools))
+
+builder.add_edge(START, 'assistant')
+builder.add_conditional_edges(
+    'assistant',
+    tools_condition,
+)
+builder.add_edge('tools', 'assistant')
+
+memory = DaprCheckpointer(store_name='statestore', key_prefix='dapr')
+react_graph_memory = builder.compile(checkpointer=memory)
+
+config = {'configurable': {'thread_id': '1'}}
+
+messages = [HumanMessage(content='Add 3 and 4.')]
+messages = react_graph_memory.invoke({'messages': messages}, config)
+for m in messages['messages']:
+    m.pretty_print()
+
+messages = [HumanMessage(content='Multiply that by 2.')]
+messages = react_graph_memory.invoke({'messages': messages}, config)
+for m in messages['messages']:
+    m.pretty_print()

examples/langgraph-checkpointer/requirements.txt

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+langchain-core>=1.0.7
+langchain-openai>=1.0.3
+langgraph>=1.0.3
+dapr-ext-workflow>=1.16.0.dev
+dapr>=1.16.0.dev