* fix(dub): re-dub honors transcript edits — fingerprints canonicalised, preview cache-busted, mux made atomic (#281) Three symptoms, three causes: 1. Edited line, unchanged result: the dubbed preview-video URL was identical across re-dubs, so the WebView kept serving the previous dub. A generation nonce now cache-busts the preview after every completed generation. 2. Preview stuck loading forever: overlapping preview requests ran ffmpeg against the same output path and the mtime cache check saw the half-written file as valid. The mux now runs under a per-path lock, writes to a temp file, and os.replace()s into place. 3. One edit re-dubs all lines: server-side fingerprints were computed from pydantic-parsed segments (defaults filled in) but recomputed client-side from raw dicts (keys omitted), so every segment always looked stale and incremental degraded to a full re-dub. Values are now canonicalised on the backend and the frontend builds generation inputs through one shared helper (utils/segments.js) for both the generate request and the incremental plan. Fixes #281 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * Potential fix for pull request finding 'CodeQL / Uncontrolled data used in path expression' Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com> * fix(dub): realpath containment for job-derived preview paths (CodeQL) Request-supplied job_id/lang flowed into the preview mux output path. Both now pass a realpath containment guard against DUB_DIR (the file's existing per-segment pattern) and lang is allowlist-validated before it lands in a filename. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix(dub): inline the containment guard — CodeQL can't track it through a helper Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> --------- Co-authored-by: Claude Fable 5 <noreply@anthropic.com> Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>
296 lines
10 KiB
Python
296 lines
10 KiB
Python
"""#281 — re-dub must honor transcript edits.
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Root cause: the per-segment fingerprint stored after a generate run was
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computed from the pydantic-parsed request (defaults filled in: `instruct=""`,
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`profile_id=""`, `effect_preset="broadcast"`, `direction` silently dropped),
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while the frontend recomputed it from raw editor state (unset keys omitted,
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`preset:` voices unexpanded). The two representations never hashed the same,
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so after every run EVERY segment was reported "changed" — a 1-line edit
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re-dubbed all N lines, and the incremental plan was useless.
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Covers:
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- fingerprint parity between the server-side (pydantic) view and the
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client-side (raw dict) view of the same logical segment;
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- back-compat: hashes stored by previous builds still match;
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- `DubSegment.direction` is a real schema field (was silently dropped);
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- end-to-end regen with a mocked TTS engine: an edited line produces a
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DIFFERENT cached seg WAV, an untouched line's cached WAV is reused
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byte-for-byte.
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"""
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from __future__ import annotations
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import os
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os.environ.setdefault("OMNIVOICE_DISABLE_FILE_LOG", "1")
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import asyncio
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import hashlib
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import json
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import pytest
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import torch
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from services import incremental
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from schemas.requests import DubRequest, DubSegment
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fp = incremental.segment_fingerprint
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# ── Fingerprint parity (server-side vs client-side payload shapes) ─────────
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def _server_view(seg: DubSegment) -> dict:
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"""What dub_generate hashes: pydantic-parsed segment, defaults filled."""
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return {
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"text": seg.text,
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"target_lang": seg.target_lang,
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"profile_id": seg.profile_id,
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"instruct": seg.instruct,
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"speed": seg.speed,
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"direction": seg.direction,
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"effect_preset": seg.effect_preset,
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}
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def test_parity_minimal_segment():
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"""A segment with only text set must hash identically whether it went
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through pydantic (defaults filled in) or came raw from the editor."""
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server = _server_view(DubSegment(start=0.0, end=1.0, text="Hola"))
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client = {"text": "Hola"} # frontend omits unset keys
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assert fp(server) == fp(client)
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def test_parity_with_null_and_empty_string_defaults():
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server = _server_view(DubSegment(start=0.0, end=1.0, text="Hola"))
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client = {
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"text": "Hola",
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"target_lang": None,
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"profile_id": "",
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"instruct": "",
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"speed": None,
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"direction": None,
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}
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assert fp(server) == fp(client)
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def test_parity_int_vs_float_speed():
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"""JS sends `speed: 1`, pydantic parses `1.0` — same fingerprint."""
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assert fp({"text": "x", "speed": 1}) == fp({"text": "x", "speed": 1.0})
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def test_effect_preset_change_is_still_detected():
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"""Canonicalisation must not erase real preset changes."""
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assert fp({"text": "x", "effect_preset": "cinematic"}) != fp({"text": "x"})
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assert fp({"text": "x", "effect_preset": "broadcast"}) == fp({"text": "x"})
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def test_backcompat_with_hashes_stored_by_previous_builds():
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"""Old builds hashed `{field: value or ""}` with pydantic defaults
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(effect_preset="broadcast"). Stored seg_hashes in existing
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omnivoice_data/ projects must stay valid for unchanged segments."""
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legacy_payload = {
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"text": "Hola", "target_lang": "", "profile_id": "", "instruct": "",
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"speed": "", "direction": "", "effect_preset": "broadcast",
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}
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legacy_hash = hashlib.sha1(
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json.dumps(legacy_payload, sort_keys=True, ensure_ascii=False).encode("utf-8")
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).hexdigest()[:16]
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assert fp({"text": "Hola"}) == legacy_hash
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def test_one_edit_marks_exactly_one_segment_stale():
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"""The #281 scenario: generate stored server-side hashes; the editor
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recomputes with client-side payloads; ONE text edit → ONE stale line."""
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server_segs = [
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DubSegment(start=0.0, end=1.0, text="Line one"),
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DubSegment(start=1.0, end=2.0, text="Line two"),
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DubSegment(start=2.0, end=3.0, text="Line three"),
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]
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stored = {str(i): fp(_server_view(s)) for i, s in enumerate(server_segs)}
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client_segs = [
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{"id": "0", "text": "Line one"},
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{"id": "1", "text": "Line two EDITED"},
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{"id": "2", "text": "Line three"},
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]
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plan = incremental.plan_incremental(client_segs, stored_hashes=stored)
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assert plan["stale"] == ["1"]
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assert plan["fresh"] == ["0", "2"]
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# ── DubSegment.direction (was silently dropped by pydantic) ────────────────
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def test_dubsegment_accepts_direction():
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seg = DubSegment(start=0.0, end=1.0, text="hi", direction="urgent, whispered")
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assert seg.direction == "urgent, whispered"
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# default stays None so old payloads parse unchanged
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assert DubSegment(start=0.0, end=1.0, text="hi").direction is None
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def test_direction_change_flips_fingerprint():
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base = _server_view(DubSegment(start=0.0, end=1.0, text="hi"))
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directed = _server_view(DubSegment(start=0.0, end=1.0, text="hi", direction="urgent"))
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assert fp(base) != fp(directed)
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# ── End-to-end regen with a mocked TTS engine ──────────────────────────────
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class _FakeModel:
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"""Deterministic 'TTS engine': output amplitude depends on the text, so
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a text edit provably changes the rendered audio bytes."""
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sampling_rate = 24000
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def __init__(self):
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self.calls: list[str] = []
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def generate(self, text=None, **kwargs):
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self.calls.append(text)
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h = int(hashlib.sha1(text.encode("utf-8")).hexdigest()[:8], 16)
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val = 0.1 + (h % 1000) / 2000.0
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n = int(0.5 * self.sampling_rate)
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return [torch.full((1, n), val)]
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@pytest.fixture
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def patched_generate(monkeypatch, tmp_path):
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"""Patch api.routers.dub_generate so `_stream` runs hermetically:
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fake model, no DB, no watermark/DSP, WAVs under tmp_path."""
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import api.routers.dub_generate as dg
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model = _FakeModel()
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async def _fake_get_model():
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return model
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job = {
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"duration": 2.0,
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"dubbed_tracks": {},
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"speaker_clones": {},
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}
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job_dir = tmp_path / "jobX"
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job_dir.mkdir()
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monkeypatch.setattr(dg, "get_model", _fake_get_model)
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monkeypatch.setattr(dg, "_get_job", lambda job_id: job)
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monkeypatch.setattr(dg, "_save_job", lambda job_id, j: None)
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monkeypatch.setattr(dg, "DUB_DIR", str(tmp_path))
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monkeypatch.setattr(
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dg, "dub_seg_path",
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lambda job_id, seg_id: str(job_dir / f"seg_{seg_id}.wav"),
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)
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monkeypatch.setattr(dg, "rvc_is_enabled", lambda: False)
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monkeypatch.setattr(dg, "embed_watermark", lambda wav, sr: wav)
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monkeypatch.setattr(dg, "apply_mastering", lambda a, sample_rate=None: a)
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monkeypatch.setattr(dg, "get_effect_chain", lambda preset: None)
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monkeypatch.setattr(dg, "apply_effects_chain", lambda a, **k: a)
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monkeypatch.setattr(dg, "normalize_audio", lambda a, target_dBFS=None: a)
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events: list[str] = []
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class _StubTaskManager:
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def is_cancelled(self, task_id):
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return False
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async def add_task(self, task_id, task_type, func, *args, **kwargs):
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async for evt in func(*args):
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events.append(evt)
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monkeypatch.setattr(dg, "task_manager", _StubTaskManager())
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def run(body: dict) -> list[dict]:
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events.clear()
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req = DubRequest(**body)
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asyncio.run(dg.dub_generate("jobX", req))
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parsed = []
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for e in events:
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line = e.strip()
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if line.startswith("data: "):
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parsed.append(json.loads(line[len("data: "):]))
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return parsed
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return run, model, job, job_dir
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def _body(segments, **extra):
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return {
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"segments": segments,
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"segment_ids": [str(i) for i in range(len(segments))],
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"language": "Auto",
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"language_code": "es",
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"num_step": 4,
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**extra,
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}
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def test_edited_line_produces_different_cached_output(patched_generate):
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run, model, job, job_dir = patched_generate
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segs = [
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{"start": 0.0, "end": 1.0, "text": "Buenos dias"},
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{"start": 1.0, "end": 2.0, "text": "Hasta luego"},
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]
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# ── First full run: both lines rendered, hashes stored ──
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parsed = run(_body(segs))
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done = [p for p in parsed if p.get("type") == "done"]
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assert done, f"no done event in {parsed}"
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seg_hashes = done[0]["seg_hashes"]
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assert set(seg_hashes) == {"0", "1"}
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assert model.calls == ["Buenos dias", "Hasta luego"]
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wav0_v1 = (job_dir / "seg_0.wav").read_bytes()
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wav1_v1 = (job_dir / "seg_1.wav").read_bytes()
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# ── User edits line 0; client-side recompute marks ONLY it stale ──
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edited = [
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{"start": 0.0, "end": 1.0, "text": "Buenas noches"},
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{"start": 1.0, "end": 2.0, "text": "Hasta luego"},
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]
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plan = incremental.plan_incremental(
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[{"id": "0", "text": "Buenas noches"}, {"id": "1", "text": "Hasta luego"}],
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stored_hashes=seg_hashes,
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)
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assert plan["stale"] == ["0"]
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assert plan["fresh"] == ["1"]
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# ── Regen only the stale line ──
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model.calls.clear()
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parsed = run(_body(edited, regen_only=plan["stale"]))
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done = [p for p in parsed if p.get("type") == "done"]
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assert done, f"no done event in {parsed}"
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# TTS ran exactly once, with the edited text
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assert model.calls == ["Buenas noches"]
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wav0_v2 = (job_dir / "seg_0.wav").read_bytes()
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wav1_v2 = (job_dir / "seg_1.wav").read_bytes()
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# the edited line's cached audio changed…
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assert wav0_v2 != wav0_v1
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# …and the untouched line's cached audio was reused as-is
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assert wav1_v2 == wav1_v1
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# stored hash for the edited line was refreshed to the new content
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new_hashes = done[0]["seg_hashes"]
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assert new_hashes["0"] != seg_hashes["0"]
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assert new_hashes["1"] == seg_hashes["1"]
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# the final dubbed track was rebuilt
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assert (job_dir / "dubbed_es.wav").exists()
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def test_full_rerun_rerenders_edited_text(patched_generate):
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"""Plain 'Generate Dub' (no regen_only) must always use the new text."""
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run, model, job, job_dir = patched_generate
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run(_body([{"start": 0.0, "end": 1.0, "text": "primero"}]))
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first = (job_dir / "seg_0.wav").read_bytes()
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run(_body([{"start": 0.0, "end": 1.0, "text": "segundo"}]))
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second = (job_dir / "seg_0.wav").read_bytes()
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assert model.calls == ["primero", "segundo"]
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assert first != second
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