File size: 1,555 Bytes
1870dee df07284 1870dee df07284 1870dee df07284 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 | from langchain_core.messages import HumanMessage
from .graph import graph
# -> return updates from each Node as it finishes
# for update in graph.stream(
# initial_state,
# stream_mode="updates"
# ):
# print(update)
# stream("updates") → Each Node's State updates.
# stream("values") → Full accumulated State at each step.
def main():
config = {
"configurable": {
"thread_id": "restaurant-test-1"
}
}
# First user message
result = graph.invoke(
{
"messages": [
HumanMessage(
content="Book a table at Olive Garden for 4 people"
)
],
"global_params": {},
"selected_tool": None,
"missing_params": [],
"tool_args": {},
"tool_result": None
},
config=config
)
print("ASSISTANT:", result["messages"][-1].content)
# Second user message
result = graph.invoke(
{
"messages": [
HumanMessage(content="Tomorrow at 7 PM")
]
},
config=config
)
print("SELECTED TOOL:", result["selected_tool"])
print("TOOL ARGS:", result["tool_args"])
print("TOOL RESULT:", result["tool_result"])
print("ASSISTANT:", result["messages"][-1].content)
# Generate Graph image
with open("agent_graph.png", "wb") as f:
f.write(graph.get_graph().draw_mermaid_png())
print("Graph saved to agent_graph.png")
if __name__ == "__main__":
main()
|