55aafbae9a
- Modified loadChatHistory() to check for active project before fetching all sessions - When active project exists, use project.sessions instead of fetching from API - Added detailed console logging to debug session filtering - This prevents ALL sessions from appearing in every project's sidebar Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
84 lines
2.1 KiB
Python
84 lines
2.1 KiB
Python
# SPDX-License-Identifier: MIT
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# Copyright (C) 2022 Max Bachmann
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from __future__ import annotations
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from collections.abc import Hashable, Sequence
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from typing import Callable, TypeVar, overload
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_UnprocessedType1 = TypeVar("_UnprocessedType1")
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_UnprocessedType2 = TypeVar("_UnprocessedType2")
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@overload
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def distance(
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s1: Sequence[Hashable],
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s2: Sequence[Hashable],
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*,
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prefix_weight: float = 0.1,
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processor: None = None,
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score_cutoff: float | None = 0,
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) -> float: ...
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@overload
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def distance(
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s1: _UnprocessedType1,
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s2: _UnprocessedType2,
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*,
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prefix_weight: float = 0.1,
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processor: Callable[[_UnprocessedType1 | _UnprocessedType2], Sequence[Hashable]],
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score_cutoff: float | None = 0,
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) -> float: ...
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@overload
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def normalized_distance(
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s1: Sequence[Hashable],
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s2: Sequence[Hashable],
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*,
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prefix_weight: float = 0.1,
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processor: None = None,
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score_cutoff: float | None = 0,
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) -> float: ...
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@overload
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def normalized_distance(
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s1: _UnprocessedType1,
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s2: _UnprocessedType2,
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*,
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prefix_weight: float = 0.1,
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processor: Callable[[_UnprocessedType1 | _UnprocessedType2], Sequence[Hashable]],
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score_cutoff: float | None = 0,
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) -> float: ...
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@overload
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def similarity(
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s1: Sequence[Hashable],
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s2: Sequence[Hashable],
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*,
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prefix_weight: float = 0.1,
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processor: None = None,
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score_cutoff: float | None = 0,
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) -> float: ...
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@overload
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def similarity(
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s1: _UnprocessedType1,
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s2: _UnprocessedType2,
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*,
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prefix_weight: float = 0.1,
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processor: Callable[[_UnprocessedType1 | _UnprocessedType2], Sequence[Hashable]],
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score_cutoff: float | None = 0,
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) -> float: ...
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@overload
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def normalized_similarity(
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s1: Sequence[Hashable],
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s2: Sequence[Hashable],
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*,
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prefix_weight: float = 0.1,
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processor: None = None,
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score_cutoff: float | None = 0,
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) -> float: ...
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@overload
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def normalized_similarity(
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s1: _UnprocessedType1,
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s2: _UnprocessedType2,
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*,
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prefix_weight: float = 0.1,
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processor: Callable[[_UnprocessedType1 | _UnprocessedType2], Sequence[Hashable]],
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score_cutoff: float | None = 0,
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) -> float: ...
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