add memory

app.py

@@ -8,6 +8,7 @@ from langgraph.prebuilt import ToolNode
 from langgraph.graph import START, StateGraph
 from langgraph.prebuilt import tools_condition
 from langchain.chat_models import init_chat_model
+from langgraph.checkpoint.memory import MemorySaver
 
 from tools import *
 
@@ -16,7 +17,6 @@ if not os.environ.get("GOOGLE_API_KEY"):
 
 # Generate the chat interface, including the tools
 chat = init_chat_model("gemini-2.5-flash", model_provider="google_genai")
-
 tools = [guest_info_tool, weather_info_tool, hub_stats_tool, search_tool]
 chat_with_tools = chat.bind_tools(tools)
 
@@ -32,6 +32,8 @@ def assistant(state: AgentState):
 ## The graph
 builder = StateGraph(AgentState)
 
+memory = MemorySaver()
+
 # Define nodes: these do the work
 builder.add_node("assistant", assistant)
 builder.add_node("tools", ToolNode(tools))
@@ -45,10 +47,18 @@ builder.add_conditional_edges(
     tools_condition,
 )
 builder.add_edge("tools", "assistant")
-alfred = builder.compile()
+alfred = builder.compile(checkpointer=memory)
+
+config = {"configurable": {"thread_id": "1"}}
+# First interaction
+response = alfred.invoke({"messages": [HumanMessage(content="Tell me about 'Lady Ada Lovelace'. What's her background and how is she related to me?")]}, config=config)
+
+print("🎩 Alfred's Response:")
+print(response['messages'][-1].content)
+print()
 
-messages = [HumanMessage(content="Who is Facebook and what's their most popular model?")]
-response = alfred.invoke({"messages": messages})
+# Second interaction (referencing the first)
+response = alfred.invoke({"messages": [HumanMessage(content="What projects is she currently working on?")]}, config=config)
 
 print("🎩 Alfred's Response:")
 print(response['messages'][-1].content)