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https://github.com/langchain-ai/langgraph.git
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@@ -29,6 +29,21 @@ async def arun(graph: Pregel, input: dict):
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)
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async def arun_first_event_latency(graph: Pregel, input: dict) -> None:
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"""Latency for the first event.
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Run the graph until the first event is processed and then stop.
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"""
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async for _ in graph.astream(
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input,
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{
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"configurable": {"thread_id": str(uuid4())},
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"recursion_limit": 1000000000,
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},
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):
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break
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def run(graph: Pregel, input: dict):
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len(
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[
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@@ -44,6 +59,21 @@ def run(graph: Pregel, input: dict):
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)
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def run_first_event_latency(graph: Pregel, input: dict) -> None:
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"""Latency for the first event.
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Run the graph until the first event is processed and then stop.
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"""
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for _ in graph.stream(
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input,
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{
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"configurable": {"thread_id": str(uuid4())},
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"recursion_limit": 1000000000,
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},
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):
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break
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benchmarks = (
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(
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"fanout_to_subgraph_10x",
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@@ -330,7 +360,23 @@ benchmarks = (
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r = Runner()
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# Full graph run time
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for name, agraph, graph, input in benchmarks:
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r.bench_async_func(name, arun, agraph, input, loop_factory=new_event_loop)
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if graph is not None:
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r.bench_func(name + "_sync", run, graph, input)
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# First event latency
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for name, agraph, graph, input in benchmarks:
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r.bench_async_func(
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name + "_first_event_latency",
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arun_first_event_latency,
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agraph,
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input,
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loop_factory=new_event_loop,
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)
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if graph is not None:
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r.bench_func(
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name + "_first_event_latency_sync", run_first_event_latency, graph, input
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)
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@@ -4,7 +4,7 @@ from langgraph.graph import MessagesState, StateGraph
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from langgraph.utils.runnable import RunnableCallable
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def create_sequential(number_nodes) -> StateGraph:
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def create_sequential(number_nodes: int) -> StateGraph:
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"""Create a sequential no-op graph consisting of a few hundred nodes."""
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builder = StateGraph(MessagesState)
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