Merge pull request #180 from ks6088ts-labs/feature/issue-179_checkpointer

support memory feature to store states

Author: ks6088ts

.gitignore

@@ -168,3 +168,5 @@ generated/
 *.db
 *.wav
 mlartifacts
+*.sqlite
+*.bin

docs/references.md

@@ -17,6 +17,10 @@
 - [Custom UI for Deep Agents](https://github.com/langchain-ai/deep-agents-ui)
 - [How to deploy self-hosted standalone server](https://docs.langchain.com/langgraph-platform/deploy-standalone-server)
 - [「現場で活用するための AI エージェント実践入門」リポジトリ](https://github.com/masamasa59/genai-agent-advanced-book)
+- [Add and manage memory](https://docs.langchain.com/oss/python/langgraph/add-memory)
+- [Persistence](https://langchain-ai.github.io/langgraph/concepts/persistence/)
+- [Chatbot with message summarization & external DB memory](https://github.com/langchain-ai/langchain-academy/blob/main/module-2/chatbot-external-memory.ipynb)
+- [LangGraph の会話履歴を SQLite に保持しよう](https://www.creationline.com/tech-blog/chatgpt-ai/75797)
 
 ### LangChain
 

pyproject.toml

@@ -27,6 +27,7 @@ dependencies = [
     "langchain-text-splitters>=0.3.9",
     "langfuse>=3.6.2",
     "langgraph>=0.6.2",
+    "langgraph-checkpoint-sqlite>=2.0.11",
     "langgraph-supervisor>=0.0.29",
     "mlflow>=3.4.0",
     "openai-whisper>=20250625",

template_langgraph/agents/chat_with_tools_agent/agent.py

@@ -50,9 +50,16 @@ def __call__(self, inputs: dict):
 
 
 class ChatWithToolsAgent:
-    def __init__(self, tools=get_default_tools()):
+    def __init__(
+        self,
+        tools=get_default_tools(),
+        checkpointer=None,
+        store=None,
+    ):
         self.llm = AzureOpenAiWrapper().chat_model
         self.tools = tools
+        self.checkpointer = checkpointer
+        self.store = store
 
     def create_graph(self):
         """Create the main graph for the agent."""
@@ -83,6 +90,8 @@ def create_graph(self):
         # Compile the graph
         return workflow.compile(
             name=ChatWithToolsAgent.__name__,
+            checkpointer=self.checkpointer,
+            store=self.store,
         )
 
     def chat_with_tools(self, state: AgentState) -> AgentState:

template_langgraph/services/streamlits/pages/chat_with_tools_agent.py

@@ -1,5 +1,7 @@
 import os
+import sqlite3
 import tempfile
+import uuid
 from base64 import b64encode
 from dataclasses import dataclass
 
@@ -9,6 +11,8 @@
     StreamlitCallbackHandler,
 )
 from langfuse.langchain import CallbackHandler
+from langgraph.checkpoint.sqlite import SqliteSaver
+from langgraph.store.sqlite import SqliteStore
 
 from template_langgraph.agents.chat_with_tools_agent.agent import (
     AgentState,
@@ -18,6 +22,10 @@
 from template_langgraph.speeches.tts import TtsWrapper
 from template_langgraph.tools.common import get_default_tools
 
+checkpoints_conn = sqlite3.connect("checkpoints.sqlite", check_same_thread=False)
+store_conn = sqlite3.connect("store.sqlite", check_same_thread=False)
+thread_id = str(uuid.uuid4())
+
 
 def image_to_base64(image_bytes: bytes) -> str:
     return b64encode(image_bytes).decode("utf-8")
@@ -68,7 +76,15 @@ def ensure_agent_graph(selected_tools: list) -> None:
     signature = tuple(tool.name for tool in selected_tools)
     graph_signature = st.session_state.get("graph_tools_signature")
     if "graph" not in st.session_state or graph_signature != signature:
-        st.session_state["graph"] = ChatWithToolsAgent(tools=selected_tools).create_graph()
+        st.session_state["graph"] = ChatWithToolsAgent(
+            tools=selected_tools,
+            checkpointer=SqliteSaver(
+                conn=checkpoints_conn,
+            ),
+            store=SqliteStore(
+                conn=store_conn,
+            ),
+        ).create_graph()
         st.session_state["graph_tools_signature"] = signature
 
 
@@ -296,12 +312,18 @@ def build_graph_messages() -> list:
 
 def invoke_agent(graph_messages: list) -> AgentState:
     return st.session_state["graph"].invoke(
-        {"messages": graph_messages},
+        {
+            "messages": graph_messages,
+        },
         {
             "callbacks": [
                 StreamlitCallbackHandler(st.container()),
                 CallbackHandler(),
-            ]
+            ],
+            "configurable": {
+                "thread_id": thread_id,
+                "user_id": "user_1",
+            },
         },
     )