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https://github.com/bytedance/deer-flow.git
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a4ede80deb
* fix(runtime): reject unsupported run options * fix(runtime): align SDK run compatibility * fix(frontend): avoid unsupported events stream mode --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
48 lines
1.5 KiB
Python
48 lines
1.5 KiB
Python
"""Supported stream modes for the LangGraph-compatible runtime boundary."""
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from __future__ import annotations
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from typing import Literal, get_args
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type RunStreamMode = Literal[
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"values",
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"messages-tuple",
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"updates",
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"debug",
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"tasks",
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"checkpoints",
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"custom",
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]
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SUPPORTED_RUN_STREAM_MODES: frozenset[str] = frozenset(get_args(RunStreamMode.__value__))
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class UnsupportedStreamModeError(ValueError):
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"""Raised when a caller requests a stream mode DeerFlow cannot honor."""
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def __init__(self, modes: list[str]) -> None:
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self.modes = tuple(dict.fromkeys(modes))
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super().__init__(f"Unsupported stream mode(s): {', '.join(self.modes)}")
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def normalize_stream_modes(raw: list[str] | str | None) -> list[str]:
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"""Normalize and validate public run stream modes."""
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if raw is None:
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modes = ["values"]
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elif isinstance(raw, str):
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modes = [raw]
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else:
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modes = raw or ["values"]
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unsupported = [mode if isinstance(mode, str) else type(mode).__name__ for mode in modes if not isinstance(mode, str) or mode not in SUPPORTED_RUN_STREAM_MODES]
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if unsupported:
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raise UnsupportedStreamModeError(unsupported)
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return modes
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def to_langgraph_stream_modes(raw: list[str] | str | None) -> list[str]:
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"""Map public run modes to ``graph.astream`` modes without silent fallback."""
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modes = normalize_stream_modes(raw)
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mapped = ["messages" if mode == "messages-tuple" else mode for mode in modes]
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return list(dict.fromkeys(mapped))
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