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https://github.com/langchain-ai/langgraph.git
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more tests
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@@ -237,3 +237,74 @@ def test_diff_channel_unsupported_saver_raises() -> None:
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raw_delta = DiffDelta(delta=[], prev_version=None)
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with pytest.raises(ValueError, match="DiffChannel received a raw DiffDelta"):
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spec.from_checkpoint(raw_delta)
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def test_diff_channel_remove_message_delta_and_replay() -> None:
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"""RemoveMessage stored in a delta must round-trip correctly through the chain."""
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from langchain_core.messages import AIMessage, HumanMessage, RemoveMessage
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from langgraph.checkpoint.base import DiffChainValue, DiffDelta
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from langgraph.channels.diff import DiffChannel
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from langgraph.graph.message import add_messages
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spec = DiffChannel(add_messages)
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ch = spec.from_checkpoint(MISSING)
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ch.after_checkpoint(None)
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# Step 1: add two messages
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ch.update([HumanMessage(content="hi", id="h1")])
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ch.update([AIMessage(content="hello", id="a1")])
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d1 = ch.checkpoint()
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assert isinstance(d1, DiffDelta)
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ch.after_checkpoint("v1")
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assert ch.get() == [
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HumanMessage(content="hi", id="h1"),
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AIMessage(content="hello", id="a1"),
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]
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# Step 2: remove the AI message
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ch.update([RemoveMessage(id="a1")])
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d2 = ch.checkpoint()
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assert isinstance(d2, DiffDelta)
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assert d2.prev_version == "v1"
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assert any(isinstance(w, RemoveMessage) for w in d2.delta)
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ch.after_checkpoint("v2")
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assert ch.get() == [HumanMessage(content="hi", id="h1")]
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# Replay the full chain from scratch — must reproduce the post-remove state
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chain = DiffChainValue(base=None, deltas=[d1.delta, d2.delta])
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ch2 = spec.from_checkpoint(chain)
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assert ch2.get() == [HumanMessage(content="hi", id="h1")]
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def test_diff_channel_update_by_id_delta_and_replay() -> None:
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"""Updating a message by ID stored in a delta must round-trip correctly."""
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from langchain_core.messages import HumanMessage
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from langgraph.checkpoint.base import DiffChainValue, DiffDelta
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from langgraph.channels.diff import DiffChannel
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from langgraph.graph.message import add_messages
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spec = DiffChannel(add_messages)
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ch = spec.from_checkpoint(MISSING)
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ch.after_checkpoint(None)
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# Step 1: add a message
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ch.update([HumanMessage(content="original", id="h1")])
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d1 = ch.checkpoint()
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assert isinstance(d1, DiffDelta)
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ch.after_checkpoint("v1")
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# Step 2: update the same message by ID
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ch.update([HumanMessage(content="updated", id="h1")])
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d2 = ch.checkpoint()
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assert isinstance(d2, DiffDelta)
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assert d2.prev_version == "v1"
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ch.after_checkpoint("v2")
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assert ch.get() == [HumanMessage(content="updated", id="h1")]
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# Replay the full chain — must produce the updated message, not the original
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chain = DiffChainValue(base=None, deltas=[d1.delta, d2.delta])
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ch2 = spec.from_checkpoint(chain)
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assert len(ch2.get()) == 1
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assert ch2.get()[0].content == "updated"
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@@ -9500,3 +9500,90 @@ async def test_diff_channel_time_travel() -> None:
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assert msgs[0].content == "h1"
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assert msgs[1].content == "ai-1"
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assert msgs[2].content == "h3"
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async def test_diff_channel_remove_message_end_to_end() -> None:
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"""RemoveMessage inside a DiffChannel graph must persist and reload correctly."""
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from langchain_core.messages import AIMessage, HumanMessage, RemoveMessage
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from langgraph.checkpoint.memory import InMemorySaver
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from langgraph.channels.diff import DiffChannel
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from langgraph.graph import START, StateGraph
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from langgraph.graph.message import add_messages
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class State(TypedDict):
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messages: Annotated[list, DiffChannel(add_messages)]
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def respond(state: State) -> dict:
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return {"messages": [AIMessage(content="reply", id="ai-1")]}
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def delete_first(state: State) -> dict:
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# removes the first message
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return {"messages": [RemoveMessage(id=state["messages"][0].id)]}
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builder = StateGraph(State)
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builder.add_node("respond", respond)
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builder.add_node("delete_first", delete_first)
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builder.add_edge(START, "respond")
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builder.add_edge("respond", "delete_first")
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graph = builder.compile(checkpointer=InMemorySaver())
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config = {"configurable": {"thread_id": "diff-remove-test"}}
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graph.invoke({"messages": [HumanMessage(content="hello", id="h1")]}, config)
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state = graph.get_state(config)
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msgs = state.values["messages"]
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# h1 was removed, only ai-1 should remain
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assert len(msgs) == 1, f"expected 1 message, got {len(msgs)}: {msgs}"
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assert msgs[0].id == "ai-1"
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# A subsequent turn must reconstruct from the checkpoint correctly
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graph.invoke({"messages": [HumanMessage(content="again", id="h2")]}, config)
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state = graph.get_state(config)
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msgs = state.values["messages"]
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# ai-1 + h2 + ai-1(second reply, same id overwrites) + h2 removed
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# more simply: after second run we expect ai-1 updated + h2 remaining minus deleted h2
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# just assert h1 is still gone
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assert all(m.id != "h1" for m in msgs), (
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"h1 should still be absent after second turn"
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)
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async def test_diff_channel_update_by_id_end_to_end() -> None:
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"""Updating a message by ID via DiffChannel must persist and reload correctly."""
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from langchain_core.messages import HumanMessage
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from langgraph.checkpoint.memory import InMemorySaver
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from langgraph.channels.diff import DiffChannel
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from langgraph.graph import START, StateGraph
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from langgraph.graph.message import add_messages
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class State(TypedDict):
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messages: Annotated[list, DiffChannel(add_messages)]
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def update_msg(state: State) -> dict:
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# re-send h1 with updated content
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return {"messages": [HumanMessage(content="updated", id="h1")]}
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builder = StateGraph(State)
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builder.add_node("update_msg", update_msg)
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builder.add_edge(START, "update_msg")
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graph = builder.compile(checkpointer=InMemorySaver())
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config = {"configurable": {"thread_id": "diff-update-id-test"}}
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graph.invoke({"messages": [HumanMessage(content="original", id="h1")]}, config)
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state = graph.get_state(config)
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msgs = state.values["messages"]
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assert len(msgs) == 1, f"expected 1 message, got {len(msgs)}: {msgs}"
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assert msgs[0].content == "updated"
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assert msgs[0].id == "h1"
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# Second turn: verify the updated state is the base for further accumulation
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graph.invoke({"messages": [HumanMessage(content="new", id="h2")]}, config)
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state = graph.get_state(config)
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msgs = state.values["messages"]
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ids = [m.id for m in msgs]
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assert "h1" in ids # h1 persists (updated, not duplicated)
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assert "h2" in ids
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assert ids.count("h1") == 1, "h1 must not be duplicated"
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