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import os
import getpass
from typing import TypedDict, Annotated
from langgraph.graph.message import add_messages
from langchain_core.messages import AnyMessage, HumanMessage, AIMessage
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 *
if not os.environ.get("GOOGLE_API_KEY"):
os.environ["GOOGLE_API_KEY"] = getpass.getpass("Enter API key for Google Gemini: ")
# 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)
# Generate the AgentState and Agent graph
class AgentState(TypedDict):
messages: Annotated[list[AnyMessage], add_messages]
def assistant(state: AgentState):
return {
"messages": [chat_with_tools.invoke(state["messages"])],
}
## The graph
builder = StateGraph(AgentState)
memory = MemorySaver()
# Define nodes: these do the work
builder.add_node("assistant", assistant)
builder.add_node("tools", ToolNode(tools))
# Define edges: these determine how the control flow moves
builder.add_edge(START, "assistant")
builder.add_conditional_edges(
"assistant",
# If the latest message requires a tool, route to tools
# Otherwise, provide a direct response
tools_condition,
)
builder.add_edge("tools", "assistant")
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()
# 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) |