ccdc4e4277
- Add users.language_preference (Alembic 0018, default zh); capture at signup/SMS only; expose on auth and profile APIs - Lite English prompts for chat and memoir; localized stage labels and agent names (Life Echo / 岁月知己) - Tencent TTS: language-aware synthesis, ModelType=1 for 501004, English chunking - WebSocket pipeline: emit all AGENT_RESPONSE segments when TTS cancels; INFO logs for tts_this_turn and TTS decisions; on-demand TTS logging - Expo: device language on auth, i18n tiers/agent name, [SPLIT] streaming UX fixes - Tests for migration, prompts, pipeline, router tts_this_turn, reply segments Co-authored-by: Cursor <cursoragent@cursor.com>
100 lines
2.7 KiB
Python
100 lines
2.7 KiB
Python
"""Phase1 批处理 LLM 分块：大量 segment 时拆多次请求并合并 by_id。"""
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from __future__ import annotations
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from types import SimpleNamespace
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from unittest.mock import MagicMock
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import pytest
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from app.agents.memoir.batch_phase1_prep import (
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BatchPhase1SegmentRow,
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run_batch_phase1_prep_chunked,
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)
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from app.agents.state_schema import MemoirStateSchema
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def _state() -> MemoirStateSchema:
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return MemoirStateSchema(
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stage_order=["childhood"],
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current_stage="childhood",
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covered_stages=[],
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slots={},
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)
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def test_run_batch_phase1_prep_chunked_splits_95_into_four_calls(
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monkeypatch: pytest.MonkeyPatch,
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) -> None:
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chunk_lengths: list[int] = []
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def fake_prep(
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segments: list,
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state: MemoirStateSchema,
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llm: object,
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*,
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language: str = "zh",
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) -> dict[str, BatchPhase1SegmentRow]:
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chunk_lengths.append(len(segments))
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return {
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str(s.id): BatchPhase1SegmentRow(
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detected_stage="childhood",
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slots={},
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chapter_category_raw="summary",
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)
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for s in segments
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}
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monkeypatch.setattr(
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"app.agents.memoir.batch_phase1_prep.run_batch_phase1_prep",
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fake_prep,
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)
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segments = [SimpleNamespace(id=f"s{i}", user_input_text="hello") for i in range(95)]
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by_id = run_batch_phase1_prep_chunked(
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segments,
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_state(),
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MagicMock(),
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chunk_size=24,
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)
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assert len(by_id) == 95
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assert chunk_lengths == [24, 24, 24, 23]
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def test_chunked_bisect_on_value_error(monkeypatch: pytest.MonkeyPatch) -> None:
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"""块内失败时二分重试，仍能拼回全量 id。"""
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chunk_lengths: list[int] = []
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def fake_prep(
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segments: list,
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state: MemoirStateSchema,
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llm: object,
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*,
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language: str = "zh",
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) -> dict[str, BatchPhase1SegmentRow]:
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chunk_lengths.append(len(segments))
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if len(segments) == 4:
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raise ValueError("simulate length limit")
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return {
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str(s.id): BatchPhase1SegmentRow(
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detected_stage="childhood",
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slots={},
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chapter_category_raw="summary",
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)
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for s in segments
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}
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monkeypatch.setattr(
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"app.agents.memoir.batch_phase1_prep.run_batch_phase1_prep",
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fake_prep,
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)
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segments = [SimpleNamespace(id=f"b{i}", user_input_text="x") for i in range(4)]
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by_id = run_batch_phase1_prep_chunked(
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segments,
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_state(),
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MagicMock(),
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chunk_size=100,
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)
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assert len(by_id) == 4
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assert chunk_lengths[0] == 4
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assert 2 in chunk_lengths
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