feat(translation): enforce EN-first pipeline with cue-preserving translations
All translations now derive strictly from the approved English master VTT,
eliminating the cue-count and timestamp drift reported by linguists
(e.g. PL AD = 11 cues vs EN AD = 17 cues).
Key changes:
- Remove video_native translation mode entirely; all languages go through
translate_vtt() which guarantees 1:1 cue alignment with EN master
- Transcreation languages now use translate_vtt(style="transcreate") —
same cue-preserving contract, culturally-adapted instructions
- Post-translation cue alignment validator added (VTTEditor.assert_cue_alignment)
- After ingestion, job moves to PENDING_QC (EN-only) instead of TRANSLATING;
translation pipeline dispatches automatically when EN QC is approved
- New POST /jobs/{id}/retranslate-language endpoint for PM/admin to fix
legacy video_native jobs on demand
- Frontend: origin badge (EN-aligned / transcreated / video-native warning),
EN-first gate banner on target-language cards, Re-translate from EN button
with confirm modal, removed translation mode selector from NewJob
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Vadym Samoilenko
parent
e2af5c0f2f
commit
fddf803b74
13 changed files with 347 additions and 342 deletions
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@ -58,6 +58,7 @@ from ...schemas.job import (
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JobUpdateRequest,
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PromoteToQCRequest,
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RejectJobRequest,
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RetranslateLanguageRequest,
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ReturnToQCRequest,
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UpdateTTSPreferencesRequest,
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UploadCompleteRequest,
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@ -1869,6 +1870,82 @@ async def _trigger_retranslation(job_id: str, job_doc: dict, db, current_user) -
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translate_and_synthesize_task.delay(job_id, languages=target_languages, retranslate=True)
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@router.post("/{job_id}/retranslate-language", response_model=JobResponse)
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async def retranslate_language(
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job_id: str,
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request: RetranslateLanguageRequest,
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http_request: Request = None,
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current_user: User = Depends(require_roles(UserRole.PRODUCTION, UserRole.ADMIN)),
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ctx: MembershipContext = Depends(get_membership_context),
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db: AsyncIOMotorDatabase = Depends(get_database),
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):
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"""Re-translate a single target language from the approved EN master VTT.
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Used by PM/admin to fix drift on existing jobs (e.g. legacy video_native translations).
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EN must be approved before retranslation can be triggered.
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"""
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job_doc = await get_job_or_403(job_id, ctx, db)
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source_language = job_doc["source"].get("language", "en")
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lang = request.language
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if lang == source_language:
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raise HTTPException(status_code=400, detail="Cannot retranslate the source language")
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requested_langs = job_doc.get("requested_outputs", {}).get("languages", [])
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if lang not in requested_langs:
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raise HTTPException(status_code=400, detail=f"Language '{lang}' is not in the job's requested languages")
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# Enforce EN-first gate
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source_qc = (job_doc.get("language_qc") or {}).get(source_language, {})
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if source_qc.get("status") != LanguageQCStatus.APPROVED.value:
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raise HTTPException(
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status_code=409,
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detail=f"Source language '{source_language}' must be approved before retranslation"
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)
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now = datetime.utcnow()
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await db.jobs.update_one(
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{"_id": job_id},
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{
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"$set": {
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"status": JobStatus.TRANSLATING.value,
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f"language_qc.{lang}.status": LanguageQCStatus.PENDING.value,
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f"language_qc.{lang}.approved_by": None,
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f"language_qc.{lang}.approved_at": None,
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"updated_at": now,
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},
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"$push": {
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"review.history": {
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"at": now,
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"status": JobStatus.TRANSLATING.value,
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"by": str(current_user.id),
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"notes": f"Retranslate '{lang}' from EN master. Reason: {request.reason or 'not provided'}",
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}
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},
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},
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)
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await log_job_action(
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AuditAction.VTT_RETRANSLATE, job_id, current_user, http_request,
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details={"language": lang, "reason": request.reason},
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)
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from ...tasks.translate_and_synthesize import translate_and_synthesize_task
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translate_and_synthesize_task.delay(job_id, languages=[lang], retranslate=True)
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result = await db.jobs.find_one({"_id": job_id})
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return JobResponse(
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id=str(result["_id"]),
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title=result["title"],
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status=result["status"],
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source=result["source"],
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requested_outputs=RequestedOutputs(**result["requested_outputs"]),
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review=result.get("review", {"notes": "", "history": []}),
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outputs=result.get("outputs"),
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created_at=result["created_at"].isoformat(),
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updated_at=result["updated_at"].isoformat(),
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)
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@router.post("/{job_id}/vtt/adjust-timing", response_model=JobResponse)
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async def adjust_vtt_timing(
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job_id: str,
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@ -147,6 +147,22 @@ class VTTEditor:
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return VTTParser.build(cues)
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@staticmethod
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def assert_cue_alignment(en_vtt: str, target_vtt: str, lang: str) -> None:
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"""Raise ValueError if target VTT cue count or timestamps diverge from EN master."""
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en_cues = VTTParser.parse(en_vtt)
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tgt_cues = VTTParser.parse(target_vtt)
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if len(tgt_cues) != len(en_cues):
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raise ValueError(
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f"Cue count mismatch for {lang}: EN has {len(en_cues)}, target has {len(tgt_cues)}"
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)
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for i, (en, tgt) in enumerate(zip(en_cues, tgt_cues)):
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if en.start != tgt.start or en.end != tgt.end:
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raise ValueError(
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f"Timestamp mismatch for {lang} cue {i}: "
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f"EN {en.start}-->{en.end}, target {tgt.start}-->{tgt.end}"
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)
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@staticmethod
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def update_cue_text(vtt_content: str, cue_index: int, new_text: str) -> str:
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"""Update text for a specific cue by index"""
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@ -80,7 +80,7 @@ class RequestedOutputs(BaseModel):
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languages: list[str] = []
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transcreation: list[str] = []
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tts_preferences: TTSPreferences | None = None
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translation_mode: Literal["traditional", "video_native"] = "video_native"
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translation_mode: Literal["traditional", "video_native"] = "traditional"
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class PausePointData(BaseModel):
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@ -192,3 +192,8 @@ class UploadCompleteRequest(BaseModel):
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deadline: str | None = None
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initial_linguist_id: str | None = None
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initial_reviewer_id: str | None = None
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class RetranslateLanguageRequest(BaseModel):
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language: str
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reason: str | None = None
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@ -80,7 +80,10 @@ def _celery_fallback(task: str, job_id: str, **extra_args) -> str:
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ingest_and_ai_task.delay(job_id)
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elif task == "translate":
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from ..tasks.translate_and_synthesize import translate_and_synthesize_task
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translate_and_synthesize_task.delay(job_id)
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_langs = extra_args.get("languages")
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if isinstance(_langs, str):
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_langs = [l for l in _langs.split(",") if l]
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translate_and_synthesize_task.delay(job_id, languages=_langs or None)
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elif task == "render":
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from ..tasks.render_accessible_video import render_accessible_video_task
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render_accessible_video_task.delay(job_id, extra_args.get("language", "en"))
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@ -830,6 +830,7 @@ JSON:
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target_language: str,
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source_language: str = "en",
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glossary_block: str | None = None,
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style: str = "literal",
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_cost_ctx: dict | None = None,
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) -> str:
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"""
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@ -839,7 +840,8 @@ JSON:
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1. Send only the text cues (no timestamps) to Gemini as a numbered list
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2. Apply translated texts back onto the original VTT using translate_preserving_timing()
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This avoids any possibility of Gemini drifting or altering timestamps.
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style="literal" — direct translation preserving meaning exactly
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style="transcreate" — culturally adapted but still returns EXACTLY N cues 1:1
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"""
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from ..lib.vtt import VTTEditor, VTTParser
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@ -850,6 +852,13 @@ JSON:
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cue_count = len(source_cues)
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_style_instruction = (
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"- Culturally adapt the text for {tgt} audiences (brand voice, natural phrasing), "
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"while keeping accessibility intent and line length (~32–40 chars)\n"
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if style == "transcreate"
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else ""
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)
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async def _attempt_translation(extra_instruction: str = "") -> list[str]:
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numbered_texts = "\n".join(
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f"{i + 1}. {cue.text.replace(chr(10), ' ')}"
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@ -859,13 +868,14 @@ JSON:
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_tgt_label = locale_lib.get_gemini_label(target_language)
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_glossary_section = self._build_glossary_block(glossary_block)
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_glossary_line = f"\n\n{_glossary_section}" if _glossary_section else ""
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_adapt_line = _style_instruction.format(tgt=_tgt_label) if style == "transcreate" else ""
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prompt = f"""Translate the following {cue_count} numbered text segments from {_src_label} to {_tgt_label}.
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REQUIREMENTS:
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- Return EXACTLY {cue_count} numbered lines, one translation per line
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- Format: "1. translated text", "2. translated text", etc.
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- Preserve speaker labels like [Speaker 1]: unchanged
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- Use natural, idiomatic {_tgt_label}
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- {_adapt_line}Use natural, idiomatic {_tgt_label}
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- Do NOT add any explanation, preamble, or extra lines{extra_instruction}{_glossary_line}
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Segments to translate:
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@ -692,6 +692,41 @@ async def approve_language(
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logger.exception("Failed to send approval emails")
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refreshed = await db[_JOBS].find_one({"_id": job_id})
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# When the source language is approved, dispatch translation for any target
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# languages that don't have VTTs yet (EN-first gate).
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source_lang = (refreshed.get("source") or {}).get("language", "en")
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if lang == source_lang:
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target_langs = [lg for lg in _job_languages(refreshed) if lg != source_lang]
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if target_langs:
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outputs = refreshed.get("outputs") or {}
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untranslated = [lg for lg in target_langs if not (outputs.get(lg) or {}).get("captions_vtt_gcs")]
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if untranslated:
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try:
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from ..services.cloud_run_dispatch import dispatch as _cr_dispatch
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await db[_JOBS].update_one(
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{"_id": job_id},
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{
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"$set": {
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"status": JobStatus.TRANSLATING.value,
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"updated_at": datetime.utcnow(),
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},
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"$push": {
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"review.history": {
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"at": datetime.utcnow(),
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"status": JobStatus.TRANSLATING.value,
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"by": "system",
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"notes": f"EN approved — dispatching translation for {untranslated}",
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}
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},
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},
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)
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await _cr_dispatch("translate", job_id, languages=untranslated)
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logger.info(f"Job {job_id}: EN approved, dispatched translation for {untranslated}")
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return LanguageQCState(**updated_state)
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except Exception as exc:
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logger.error(f"Job {job_id}: failed to dispatch translation after EN approval: {exc}")
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await _maybe_advance_job(db, refreshed)
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return LanguageQCState(**updated_state)
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@ -249,14 +249,14 @@ async def ingest_and_ai_task_impl(job_id: str):
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if transcript_gcs_uri:
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source_lang_output["descriptive_transcript_gcs"] = transcript_gcs_uri
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# Update job with AI results, detected language, and outputs
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# Set status to TRANSLATING to trigger translation pipeline before QC
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# Update job with AI results and move to QC for EN approval.
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# Translation pipeline is triggered only after EN QC is approved.
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await db.jobs.update_one(
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{"_id": job_id},
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{
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"$set": {
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"status": JobStatus.TRANSLATING.value,
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"source.language": source_language, # Update with detected language
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"status": JobStatus.PENDING_QC.value,
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"source.language": source_language,
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"source.detected_language": detected_language,
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"ai.ingestion_json": ai_result,
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"ai.confidence": ai_result["confidence"],
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@ -266,26 +266,21 @@ async def ingest_and_ai_task_impl(job_id: str):
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"$push": {
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"review.history": {
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"at": datetime.utcnow(),
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"status": JobStatus.TRANSLATING.value,
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"status": JobStatus.PENDING_QC.value,
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"by": "system"
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}
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}
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}
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)
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# Broadcast status update
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broadcast_status_update(
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job_id,
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JobStatus.TRANSLATING.value,
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JobStatus.PENDING_QC.value,
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job_title=job_title,
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message=f"{job_title} AI processing complete, starting translation pipeline"
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message=f"{job_title} AI processing complete — awaiting EN approval before translation"
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)
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logger.info(f"AI processing complete for job {job_id}, triggering translation pipeline")
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# Trigger translation and synthesis pipeline via Cloud Run
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from ..services.cloud_run_dispatch import dispatch as _cr_dispatch
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await _cr_dispatch("translate", job_id)
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logger.info(f"AI processing complete for job {job_id}, moved to PENDING_QC for EN review")
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finally:
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# Clean up temp file
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@ -1,7 +1,5 @@
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import asyncio
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import os
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import random
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import tempfile
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from datetime import datetime
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from typing import Any
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@ -20,9 +18,6 @@ from ._websocket_bridge import broadcast_status_update
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logger = get_logger(__name__)
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# Maximum concurrent video-native translations (Gemini API rate limiting)
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MAX_CONCURRENT_VIDEO_NATIVE = 3
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async def retry_with_backoff(func, max_retries=3, base_delay=1):
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"""Retry a function with exponential backoff"""
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@ -166,305 +161,121 @@ async def _async_translate_and_synthesize(job_id: str, languages: list[str] | No
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}
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)
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# Get translation mode (default to "traditional" for backwards compatibility)
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translation_mode = job_doc["requested_outputs"].get("translation_mode", "traditional")
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# Glossary: lazy-loaded per target language during the loop
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from ..services.glossary_service import get_glossary_block_for_job
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logger.info(f"Translation mode for job {job_id}: {translation_mode}")
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sdh_requested = job_doc["requested_outputs"].get("sdh_vtt", False)
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# Get source language VTT content (needed for traditional mode)
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# Source language VTT is the EN master for all translations
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source_outputs = job_doc["outputs"].get(source_language)
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if not source_outputs:
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raise ValueError(f"No outputs found for source language {source_language}")
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# Process each requested language (filtered to specific list when retranslating)
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captions_blob_path = source_outputs["captions_vtt_gcs"].replace(f"gs://{settings.gcs_bucket}/", "")
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ad_blob_path = source_outputs["ad_vtt_gcs"].replace(f"gs://{settings.gcs_bucket}/", "")
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source_captions_vtt = gcs_service.bucket.blob(captions_blob_path).download_as_text()
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source_ad_vtt = gcs_service.bucket.blob(ad_blob_path).download_as_text()
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source_sdh_vtt = None
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if sdh_requested and source_outputs.get("sdh_captions_vtt_gcs"):
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sdh_blob_path = source_outputs["sdh_captions_vtt_gcs"].replace(f"gs://{settings.gcs_bucket}/", "")
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source_sdh_vtt = gcs_service.bucket.blob(sdh_blob_path).download_as_text()
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# Process each requested language (filtered when retranslating a subset)
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requested_languages = job_doc["requested_outputs"]["languages"]
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if languages is not None:
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requested_languages = [l for l in requested_languages if l in languages]
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requested_languages = [lg for lg in requested_languages if lg in languages]
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transcreation_languages = job_doc["requested_outputs"]["transcreation"]
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updated_outputs = job_doc.get("outputs", {})
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# For video_native mode, download source video once before the loop
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video_local_path = None
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source_captions_vtt = None
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source_ad_vtt = None
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if translation_mode == "video_native":
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# Download source video from GCS for re-processing
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source_gcs_uri = job_doc["source"]["gcs_uri"]
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source_blob_path = source_gcs_uri.replace(f"gs://{settings.gcs_bucket}/", "")
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source_blob = gcs_service.bucket.blob(source_blob_path)
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# Create temp file for video
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with tempfile.NamedTemporaryFile(suffix=".mp4", delete=False) as tmp_file:
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source_blob.download_to_filename(tmp_file.name)
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video_local_path = tmp_file.name
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logger.info(f"Downloaded source video for video_native processing: {video_local_path}")
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else:
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# Traditional mode: download source VTT files
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captions_blob_path = source_outputs["captions_vtt_gcs"].replace(f"gs://{settings.gcs_bucket}/", "")
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ad_blob_path = source_outputs["ad_vtt_gcs"].replace(f"gs://{settings.gcs_bucket}/", "")
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captions_blob = gcs_service.bucket.blob(captions_blob_path)
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ad_blob = gcs_service.bucket.blob(ad_blob_path)
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source_captions_vtt = captions_blob.download_as_text()
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source_ad_vtt = ad_blob.download_as_text()
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# Download source SDH VTT for traditional-mode translation
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source_sdh_vtt = None
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if sdh_requested and source_outputs.get("sdh_captions_vtt_gcs"):
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sdh_blob_path = source_outputs["sdh_captions_vtt_gcs"].replace(f"gs://{settings.gcs_bucket}/", "")
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source_sdh_vtt = gcs_service.bucket.blob(sdh_blob_path).download_as_text()
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_source_text_for_glossary = " ".join(filter(None, [source_captions_vtt, source_ad_vtt]))
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try:
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# Get target languages (exclude source)
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target_languages = [lang for lang in requested_languages if lang != source_language]
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if translation_mode == "video_native":
|
||||
# VIDEO NATIVE MODE: Process all languages in parallel with rate limiting
|
||||
# This generates VTTs from scratch with visual context for each language
|
||||
# Note: Transcreation is NOT applicable - video_native replaces it
|
||||
for language in target_languages:
|
||||
_style = "transcreate" if language in transcreation_languages else "literal"
|
||||
logger.info(f"Processing language: {language} (source: {source_language}, style: {_style})")
|
||||
|
||||
semaphore = asyncio.Semaphore(MAX_CONCURRENT_VIDEO_NATIVE)
|
||||
await cost_tracker.aio_preflight(
|
||||
model=gemini_service.model_name,
|
||||
user_external_id=_cost_ctx["user_id"],
|
||||
project_id=_cost_ctx["project_id"],
|
||||
)
|
||||
|
||||
job_brand_context = job_doc.get("brand_context")
|
||||
_job_for_glossary = {**job_doc, "_glossary_source_text": _source_text_for_glossary}
|
||||
_glossary = await get_glossary_block_for_job(_job_for_glossary, language, db)
|
||||
|
||||
async def translate_language_video_native(lang: str) -> tuple[str, str, str, str | None]:
|
||||
"""Process a single language with video-native translation.
|
||||
Returns: (language, captions_gcs_uri, ad_gcs_uri, error_message or None)
|
||||
"""
|
||||
async with semaphore:
|
||||
logger.info(f"Starting video-native translation for {lang} (from source: {source_language})")
|
||||
try:
|
||||
await cost_tracker.aio_preflight(
|
||||
model=gemini_service.model_name,
|
||||
user_external_id=_cost_ctx["user_id"],
|
||||
project_id=_cost_ctx["project_id"],
|
||||
)
|
||||
try:
|
||||
async def translate_captions(_lang=language, _gloss=_glossary, _s=_style):
|
||||
return await gemini_service.translate_vtt(
|
||||
source_captions_vtt, _lang, source_language=source_language,
|
||||
glossary_block=_gloss, style=_s, _cost_ctx=_cost_ctx,
|
||||
)
|
||||
|
||||
# Build glossary block from source VTT for this language
|
||||
_job_for_glossary = {**job_doc, "_glossary_source_text": ""}
|
||||
_glossary = await get_glossary_block_for_job(_job_for_glossary, lang, db)
|
||||
async def translate_ad(_lang=language, _gloss=_glossary, _s=_style):
|
||||
return await gemini_service.translate_vtt(
|
||||
source_ad_vtt, _lang, source_language=source_language,
|
||||
glossary_block=_gloss, style=_s, _cost_ctx=_cost_ctx,
|
||||
)
|
||||
|
||||
async def extract_targeted():
|
||||
return await gemini_service.extract_accessibility_targeted(
|
||||
video_local_path,
|
||||
lang,
|
||||
brand_context=job_brand_context,
|
||||
sdh_requested=sdh_requested,
|
||||
glossary_block=_glossary,
|
||||
_cost_ctx=_cost_ctx,
|
||||
)
|
||||
translated_captions = await retry_with_backoff(translate_captions, max_retries=3)
|
||||
translated_ad = await retry_with_backoff(translate_ad, max_retries=3)
|
||||
|
||||
result = await retry_with_backoff(extract_targeted, max_retries=3)
|
||||
translated_captions = result["captions_vtt"]
|
||||
translated_ad = result["audio_description_vtt"]
|
||||
# Validate cue alignment against EN master
|
||||
from ..lib.vtt import VTTEditor
|
||||
VTTEditor.assert_cue_alignment(source_captions_vtt, translated_captions, language)
|
||||
VTTEditor.assert_cue_alignment(source_ad_vtt, translated_ad, language)
|
||||
|
||||
# Upload translated VTT files
|
||||
captions_gcs_uri = await upload_vtt_to_gcs(
|
||||
translated_captions,
|
||||
gcs_path(job_doc, lang, "captions.vtt")
|
||||
)
|
||||
|
||||
ad_gcs_uri = await upload_vtt_to_gcs(
|
||||
translated_ad,
|
||||
gcs_path(job_doc, lang, "ad.vtt")
|
||||
)
|
||||
|
||||
# Upload SDH VTT if generated
|
||||
sdh_gcs_uri = None
|
||||
if sdh_requested and result.get("sdh_captions_vtt"):
|
||||
sdh_gcs_uri = await upload_vtt_to_gcs(
|
||||
result["sdh_captions_vtt"],
|
||||
gcs_path(job_doc, lang, "sdh_captions.vtt")
|
||||
)
|
||||
|
||||
# Generate descriptive transcript (WCAG 2.1 1.2.1)
|
||||
transcript_gcs_uri = None
|
||||
try:
|
||||
from ..services.descriptive_transcript import (
|
||||
generate_descriptive_transcript,
|
||||
)
|
||||
transcript_text = generate_descriptive_transcript(translated_captions, translated_ad)
|
||||
if transcript_text:
|
||||
transcript_gcs_uri = await upload_vtt_to_gcs(
|
||||
transcript_text,
|
||||
gcs_path(job_doc, lang, "descriptive_transcript.txt")
|
||||
)
|
||||
except Exception as transcript_err:
|
||||
logger.warning(f"Failed to generate descriptive transcript for {lang}: {transcript_err}")
|
||||
|
||||
logger.info(f"Completed video-native translation for {lang}")
|
||||
return (lang, captions_gcs_uri, ad_gcs_uri, sdh_gcs_uri, transcript_gcs_uri, None)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Video-native translation failed for {lang}: {e}")
|
||||
return (lang, None, None, None, None, str(e))
|
||||
|
||||
# Run all translations in parallel (limited by semaphore)
|
||||
if target_languages:
|
||||
logger.info(f"Starting parallel video-native translations for {len(target_languages)} languages: {target_languages}")
|
||||
tasks = [translate_language_video_native(lang) for lang in target_languages]
|
||||
results = await asyncio.gather(*tasks, return_exceptions=True)
|
||||
|
||||
# Process results
|
||||
for i, result in enumerate(results):
|
||||
lang = target_languages[i]
|
||||
if isinstance(result, Exception):
|
||||
# Unexpected exception from gather
|
||||
logger.error(f"Unexpected error for {lang}: {result}")
|
||||
updated_outputs[lang] = {
|
||||
"origin": "video_native",
|
||||
"qa_notes": f"Translation failed: {str(result)}"
|
||||
}
|
||||
else:
|
||||
lang, captions_uri, ad_uri, sdh_uri, transcript_uri, error_msg = result
|
||||
if error_msg:
|
||||
updated_outputs[lang] = {
|
||||
"origin": "video_native",
|
||||
"qa_notes": f"Translation failed: {error_msg}"
|
||||
}
|
||||
else:
|
||||
lang_out = {
|
||||
"captions_vtt_gcs": captions_uri,
|
||||
"ad_vtt_gcs": ad_uri,
|
||||
"origin": "video_native"
|
||||
}
|
||||
if sdh_uri:
|
||||
lang_out["sdh_captions_vtt_gcs"] = sdh_uri
|
||||
if transcript_uri:
|
||||
lang_out["descriptive_transcript_gcs"] = transcript_uri
|
||||
updated_outputs[lang] = lang_out
|
||||
logger.info(f"Successfully processed VTT files for language: {lang} (origin: video_native)")
|
||||
|
||||
else:
|
||||
# Combine source VTTs for glossary term matching
|
||||
_source_text_for_glossary = " ".join(filter(None, [source_captions_vtt, source_ad_vtt]))
|
||||
|
||||
# TRADITIONAL MODE: Process languages sequentially
|
||||
for language in target_languages:
|
||||
logger.info(f"Processing language: {language} (from source: {source_language}, mode: {translation_mode})")
|
||||
|
||||
await cost_tracker.aio_preflight(
|
||||
model=gemini_service.model_name,
|
||||
user_external_id=_cost_ctx["user_id"],
|
||||
project_id=_cost_ctx["project_id"],
|
||||
captions_gcs_uri = await upload_vtt_to_gcs(
|
||||
translated_captions, gcs_path(job_doc, language, "captions.vtt")
|
||||
)
|
||||
ad_gcs_uri = await upload_vtt_to_gcs(
|
||||
translated_ad, gcs_path(job_doc, language, "ad.vtt")
|
||||
)
|
||||
|
||||
# Lookup glossary terms for this target language
|
||||
_job_for_glossary = {**job_doc, "_glossary_source_text": _source_text_for_glossary}
|
||||
_glossary = await get_glossary_block_for_job(_job_for_glossary, language, db)
|
||||
origin = "transcreate" if _style == "transcreate" else "gemini_translate"
|
||||
lang_out: dict = {
|
||||
"captions_vtt_gcs": captions_gcs_uri,
|
||||
"ad_vtt_gcs": ad_gcs_uri,
|
||||
"origin": origin,
|
||||
}
|
||||
|
||||
if sdh_requested and source_sdh_vtt:
|
||||
async def translate_sdh(_lang=language, _gloss=_glossary, _s=_style):
|
||||
return await gemini_service.translate_vtt(
|
||||
source_sdh_vtt, _lang, source_language=source_language,
|
||||
glossary_block=_gloss, style=_s, _cost_ctx=_cost_ctx,
|
||||
)
|
||||
translated_sdh = await retry_with_backoff(translate_sdh, max_retries=3)
|
||||
sdh_gcs_uri = await upload_vtt_to_gcs(
|
||||
translated_sdh, gcs_path(job_doc, language, "sdh_captions.vtt")
|
||||
)
|
||||
lang_out["sdh_captions_vtt_gcs"] = sdh_gcs_uri
|
||||
|
||||
try:
|
||||
if language in transcreation_languages:
|
||||
# TRADITIONAL MODE with transcreation: cultural adaptation
|
||||
async def transcreate(_lang=language, _gloss=_glossary):
|
||||
return await gemini_service.transcreate_content(
|
||||
source_captions_vtt,
|
||||
source_ad_vtt,
|
||||
_lang,
|
||||
brief="Standard accessibility content",
|
||||
glossary_block=_gloss,
|
||||
_cost_ctx=_cost_ctx,
|
||||
)
|
||||
|
||||
result = await retry_with_backoff(transcreate, max_retries=3)
|
||||
translated_captions = result["captions_vtt"]
|
||||
translated_ad = result["audio_description_vtt"]
|
||||
origin = "transcreate"
|
||||
|
||||
else:
|
||||
# TRADITIONAL MODE: Use Gemini translation (6-36x cheaper than Google Translate API)
|
||||
async def translate_captions(_lang=language, _gloss=_glossary):
|
||||
return await gemini_service.translate_vtt(
|
||||
source_captions_vtt, _lang, source_language=source_language,
|
||||
glossary_block=_gloss,
|
||||
_cost_ctx=_cost_ctx,
|
||||
)
|
||||
|
||||
async def translate_ad(_lang=language, _gloss=_glossary):
|
||||
return await gemini_service.translate_vtt(
|
||||
source_ad_vtt, _lang, source_language=source_language,
|
||||
glossary_block=_gloss,
|
||||
_cost_ctx=_cost_ctx,
|
||||
)
|
||||
|
||||
translated_captions = await retry_with_backoff(translate_captions, max_retries=3)
|
||||
translated_ad = await retry_with_backoff(translate_ad, max_retries=3)
|
||||
origin = "gemini_translate"
|
||||
|
||||
# Upload translated VTT files
|
||||
captions_gcs_uri = await upload_vtt_to_gcs(
|
||||
translated_captions,
|
||||
gcs_path(job_doc, language, "captions.vtt")
|
||||
)
|
||||
|
||||
ad_gcs_uri = await upload_vtt_to_gcs(
|
||||
translated_ad,
|
||||
gcs_path(job_doc, language, "ad.vtt")
|
||||
)
|
||||
|
||||
# Translate and upload SDH VTT if requested
|
||||
lang_out: dict = {
|
||||
"captions_vtt_gcs": captions_gcs_uri,
|
||||
"ad_vtt_gcs": ad_gcs_uri,
|
||||
"origin": origin
|
||||
}
|
||||
if sdh_requested and source_sdh_vtt:
|
||||
async def translate_sdh(_lang=language, _gloss=_glossary):
|
||||
return await gemini_service.translate_vtt(
|
||||
source_sdh_vtt, _lang, source_language=source_language,
|
||||
glossary_block=_gloss,
|
||||
_cost_ctx=_cost_ctx,
|
||||
)
|
||||
translated_sdh = await retry_with_backoff(translate_sdh, max_retries=3)
|
||||
sdh_gcs_uri = await upload_vtt_to_gcs(
|
||||
translated_sdh,
|
||||
gcs_path(job_doc, language, "sdh_captions.vtt")
|
||||
from ..services.descriptive_transcript import generate_descriptive_transcript
|
||||
transcript_text = generate_descriptive_transcript(translated_captions, translated_ad)
|
||||
if transcript_text:
|
||||
transcript_gcs_uri = await upload_vtt_to_gcs(
|
||||
transcript_text, gcs_path(job_doc, language, "descriptive_transcript.txt")
|
||||
)
|
||||
lang_out["sdh_captions_vtt_gcs"] = sdh_gcs_uri
|
||||
lang_out["descriptive_transcript_gcs"] = transcript_gcs_uri
|
||||
except Exception as transcript_err:
|
||||
logger.warning(f"Failed to generate descriptive transcript for {language}: {transcript_err}")
|
||||
|
||||
# Generate descriptive transcript (WCAG 2.1 1.2.1)
|
||||
try:
|
||||
from ..services.descriptive_transcript import (
|
||||
generate_descriptive_transcript,
|
||||
)
|
||||
transcript_text = generate_descriptive_transcript(translated_captions, translated_ad)
|
||||
if transcript_text:
|
||||
transcript_gcs_uri = await upload_vtt_to_gcs(
|
||||
transcript_text,
|
||||
gcs_path(job_doc, language, "descriptive_transcript.txt")
|
||||
)
|
||||
lang_out["descriptive_transcript_gcs"] = transcript_gcs_uri
|
||||
except Exception as transcript_err:
|
||||
logger.warning(f"Failed to generate descriptive transcript for {language}: {transcript_err}")
|
||||
updated_outputs[language] = lang_out
|
||||
logger.info(f"Processed language: {language} (origin: {origin})")
|
||||
|
||||
# Store language outputs
|
||||
updated_outputs[language] = lang_out
|
||||
|
||||
logger.info(f"Successfully processed VTT files for language: {language} (origin: {origin})")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to process language {language}: {e}")
|
||||
fallback_origin = "transcreate" if language in transcreation_languages else "gemini_translate"
|
||||
updated_outputs[language] = {
|
||||
"origin": fallback_origin,
|
||||
"qa_notes": f"Translation failed: {str(e)}"
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to process language {language}: {e}")
|
||||
updated_outputs[language] = {
|
||||
"origin": "transcreate" if _style == "transcreate" else "gemini_translate",
|
||||
"qa_notes": f"Translation failed: {str(e)}",
|
||||
}
|
||||
|
||||
finally:
|
||||
# Cleanup temporary video file if created
|
||||
if video_local_path:
|
||||
try:
|
||||
os.unlink(video_local_path)
|
||||
logger.info(f"Cleaned up temporary video file: {video_local_path}")
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to cleanup temp video file: {e}")
|
||||
pass
|
||||
|
||||
# Update status to TTS generating
|
||||
await db.jobs.update_one(
|
||||
|
|
@ -615,7 +426,7 @@ async def _async_translate_and_synthesize(job_id: str, languages: list[str] | No
|
|||
# Broadcast failure status
|
||||
broadcast_status_update(
|
||||
job_id,
|
||||
failure_status,
|
||||
JobStatus.PROCESSING_FAILED.value,
|
||||
job_title=job_title,
|
||||
message=f"Processing failed: {str(e)[:100]}"
|
||||
)
|
||||
|
|
|
|||
|
|
@ -302,6 +302,11 @@ class ApiClient {
|
|||
return response.data;
|
||||
}
|
||||
|
||||
async retranslateLanguage(id: string, language: string, reason?: string): Promise<Job> {
|
||||
const response = await this.client.post(`/jobs/${id}/retranslate-language`, { language, reason });
|
||||
return response.data;
|
||||
}
|
||||
|
||||
async validateJobAssets(id: string): Promise<AssetValidationResponse> {
|
||||
const response = await this.client.get(`/jobs/${id}/validate`);
|
||||
return response.data;
|
||||
|
|
|
|||
|
|
@ -53,8 +53,11 @@ export function QCDetail() {
|
|||
// Get source language from job (default to 'en' for backwards compatibility)
|
||||
const sourceLanguage = job?.source?.language || 'en';
|
||||
|
||||
// Get all available languages from outputs (after workflow change, translations happen before QC)
|
||||
const availableLanguages = job?.outputs ? Object.keys(job.outputs) : [sourceLanguage];
|
||||
// All languages for QC: source always first, then requested targets
|
||||
const availableLanguages = [
|
||||
sourceLanguage,
|
||||
...((job?.requested_outputs?.languages ?? []).filter(l => l !== sourceLanguage)),
|
||||
].filter((l, i, a) => a.indexOf(l) === i);
|
||||
|
||||
// Language selection for QC review
|
||||
const [selectedLanguage, setSelectedLanguage] = useState<string>(sourceLanguage);
|
||||
|
|
@ -115,6 +118,7 @@ export function QCDetail() {
|
|||
refetchInterval: 15_000,
|
||||
});
|
||||
const langQcMap = langQcData?.language_qc ?? {};
|
||||
const isSourceApproved = (langQcMap[sourceLanguage]?.status ?? 'pending') === 'approved';
|
||||
|
||||
// Glossary terms for inline highlighting
|
||||
const clientId = job?.client_id;
|
||||
|
|
@ -155,6 +159,11 @@ export function QCDetail() {
|
|||
const [openCommentLang, setOpenCommentLang] = useState<string | null>(null);
|
||||
const [commentDraft, setCommentDraft] = useState('');
|
||||
|
||||
// Per-language retranslate modal
|
||||
const [retranslateLang, setRetranslateLang] = useState<string | null>(null);
|
||||
const [retranslateReason, setRetranslateReason] = useState('');
|
||||
const [retranslateLoading, setRetranslateLoading] = useState(false);
|
||||
|
||||
const canAssign = authUser?.role === 'project_manager' || authUser?.role === 'production' || authUser?.role === 'admin';
|
||||
const canApproveAll = authUser?.role === 'production' || authUser?.role === 'admin';
|
||||
|
||||
|
|
@ -1080,13 +1089,24 @@ export function QCDetail() {
|
|||
onClick={() => setSelectedLanguage(lang)}
|
||||
className="w-full flex items-center justify-between px-4 py-3 text-left"
|
||||
>
|
||||
<div className="flex items-center gap-2">
|
||||
<div className="flex items-center gap-2 flex-wrap">
|
||||
<span className={`inline-flex items-center justify-center w-5 h-5 text-xs rounded-full ${LANG_QC_BADGE[qcStatus]}`}>
|
||||
{LANG_QC_ICON[qcStatus]}
|
||||
</span>
|
||||
<span className="font-medium text-sm">{lang.toUpperCase()}</span>
|
||||
{lang === sourceLanguage && <span className="text-xs text-gray-400">(source)</span>}
|
||||
<span className={`text-xs px-2 py-0.5 rounded-full ${LANG_QC_BADGE[qcStatus]}`}>{LANG_QC_LABEL[qcStatus]}</span>
|
||||
{lang !== sourceLanguage && (() => {
|
||||
const origin = job?.outputs?.[lang]?.origin;
|
||||
if (!origin) return null;
|
||||
const cfg: Record<string, { cls: string; label: string }> = {
|
||||
gemini_translate: { cls: 'bg-green-100 text-green-700', label: 'EN-aligned' },
|
||||
transcreate: { cls: 'bg-green-100 text-green-700', label: 'transcreated' },
|
||||
video_native: { cls: 'bg-red-100 text-red-700', label: '⚠ video-native' },
|
||||
};
|
||||
const c = cfg[origin] ?? { cls: 'bg-gray-100 text-gray-500', label: origin };
|
||||
return <span className={`text-xs px-2 py-0.5 rounded-full ${c.cls}`}>{c.label}</span>;
|
||||
})()}
|
||||
</div>
|
||||
<span className="text-gray-400 text-xs">{isActive ? '▲' : '▼'}</span>
|
||||
</button>
|
||||
|
|
@ -1139,6 +1159,13 @@ export function QCDetail() {
|
|||
</div>
|
||||
</div>
|
||||
|
||||
{/* EN-first gate banner for target languages */}
|
||||
{lang !== sourceLanguage && !isSourceApproved && (
|
||||
<div className="rounded-lg bg-amber-50 border border-amber-200 px-3 py-2 text-xs text-amber-800">
|
||||
⏳ Waiting for <strong>{sourceLanguage.toUpperCase()}</strong> approval — translation will start automatically once the source language is approved.
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* Workflow action buttons */}
|
||||
<div className="flex flex-wrap gap-2 pt-1">
|
||||
{canStartWork && (
|
||||
|
|
@ -1209,6 +1236,16 @@ export function QCDetail() {
|
|||
Reopen
|
||||
</button>
|
||||
)}
|
||||
{canApproveAll && lang !== sourceLanguage && (
|
||||
<button
|
||||
onClick={() => { setRetranslateLang(lang); setRetranslateReason(''); }}
|
||||
disabled={!isSourceApproved}
|
||||
title={!isSourceApproved ? `${sourceLanguage.toUpperCase()} must be approved first` : 'Re-generate from approved EN master'}
|
||||
className="text-xs px-3 py-1.5 border border-indigo-300 text-indigo-600 rounded-lg hover:bg-indigo-50 disabled:opacity-40 disabled:cursor-not-allowed"
|
||||
>
|
||||
↺ Re-translate from EN
|
||||
</button>
|
||||
)}
|
||||
</div>
|
||||
|
||||
{/* Comments toggle */}
|
||||
|
|
@ -1485,6 +1522,58 @@ export function QCDetail() {
|
|||
</div>
|
||||
)}
|
||||
|
||||
{/* Per-language retranslate confirmation modal */}
|
||||
{retranslateLang && (
|
||||
<div className="fixed inset-0 bg-black/40 flex items-center justify-center z-50">
|
||||
<div className="bg-white rounded-lg shadow-xl p-6 max-w-md w-full mx-4 space-y-4">
|
||||
<h3 className="text-lg font-semibold text-gray-900">Re-translate {retranslateLang.toUpperCase()} from EN master?</h3>
|
||||
<p className="text-sm text-gray-600">
|
||||
This will discard the current <strong>{retranslateLang.toUpperCase()}</strong> translation,
|
||||
reset linguist progress for this language, and regenerate it from the approved English master.
|
||||
</p>
|
||||
<div>
|
||||
<label className="block text-xs font-medium text-gray-500 mb-1">Reason (optional)</label>
|
||||
<textarea
|
||||
rows={2}
|
||||
value={retranslateReason}
|
||||
onChange={e => setRetranslateReason(e.target.value)}
|
||||
placeholder="e.g. legacy video_native drift, cue count mismatch…"
|
||||
className="w-full px-3 py-2 border border-gray-300 rounded-md text-sm focus:outline-none focus:ring-2 focus:ring-indigo-500 resize-none"
|
||||
/>
|
||||
</div>
|
||||
<div className="flex gap-3 justify-end pt-2">
|
||||
<button
|
||||
onClick={() => setRetranslateLang(null)}
|
||||
className="px-4 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-md hover:bg-gray-50"
|
||||
>
|
||||
Cancel
|
||||
</button>
|
||||
<button
|
||||
disabled={retranslateLoading}
|
||||
onClick={async () => {
|
||||
if (!id) return;
|
||||
setRetranslateLoading(true);
|
||||
try {
|
||||
await apiClient.retranslateLanguage(id, retranslateLang, retranslateReason || undefined);
|
||||
toast.toastOnly.success(`Re-translating ${retranslateLang.toUpperCase()} from EN master…`);
|
||||
queryClient.invalidateQueries({ queryKey: ['job', id] });
|
||||
queryClient.invalidateQueries({ queryKey: ['language-qc', id] });
|
||||
setRetranslateLang(null);
|
||||
} catch {
|
||||
toast.toastOnly.error('Failed to trigger retranslation');
|
||||
} finally {
|
||||
setRetranslateLoading(false);
|
||||
}
|
||||
}}
|
||||
className="px-4 py-2 text-sm font-medium text-white bg-indigo-600 rounded-md hover:bg-indigo-700 disabled:opacity-50"
|
||||
>
|
||||
{retranslateLoading ? 'Starting…' : 'Yes, re-translate'}
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* Share link modal */}
|
||||
{showShareModal && (
|
||||
<div className="fixed inset-0 bg-black/40 flex items-center justify-center z-50">
|
||||
|
|
|
|||
|
|
@ -24,7 +24,7 @@ const jobSchema = z.object({
|
|||
accessible_video_mp4: z.boolean(),
|
||||
sdh_vtt: z.boolean(),
|
||||
languages: z.array(z.string()),
|
||||
translation_mode: z.enum(['traditional', 'video_native']),
|
||||
translation_mode: z.enum(['traditional']),
|
||||
});
|
||||
|
||||
type JobFormData = z.infer<typeof jobSchema>;
|
||||
|
|
@ -112,7 +112,7 @@ export function NewJob() {
|
|||
accessible_video_mp4: false,
|
||||
sdh_vtt: false,
|
||||
languages: [],
|
||||
translation_mode: 'video_native',
|
||||
translation_mode: 'traditional',
|
||||
}
|
||||
});
|
||||
|
||||
|
|
@ -192,7 +192,7 @@ export function NewJob() {
|
|||
accessible_video_method: data.accessible_video_mp4 ? accessibleVideoMethod : undefined,
|
||||
languages: data.languages,
|
||||
sdh_vtt: data.sdh_vtt,
|
||||
transcreation: [], // Transcreation replaced by video_native translation mode
|
||||
transcreation: [],
|
||||
tts_preferences: data.audio_description_mp3 ? ttsPreferences : undefined,
|
||||
translation_mode: data.translation_mode,
|
||||
},
|
||||
|
|
@ -286,7 +286,7 @@ export function NewJob() {
|
|||
accessible_video_method: data.accessible_video_mp4 ? accessibleVideoMethod : undefined,
|
||||
languages: data.languages,
|
||||
sdh_vtt: data.sdh_vtt,
|
||||
transcreation: [], // Transcreation replaced by video_native translation mode
|
||||
transcreation: [],
|
||||
tts_preferences: data.audio_description_mp3 ? ttsPreferences : undefined,
|
||||
translation_mode: data.translation_mode,
|
||||
},
|
||||
|
|
@ -369,7 +369,7 @@ export function NewJob() {
|
|||
accessible_video_method: data.accessible_video_mp4 ? accessibleVideoMethod : undefined,
|
||||
languages: data.languages,
|
||||
sdh_vtt: data.sdh_vtt,
|
||||
transcreation: [], // Transcreation replaced by video_native translation mode
|
||||
transcreation: [],
|
||||
tts_preferences: data.audio_description_mp3 ? ttsPreferences : undefined,
|
||||
translation_mode: data.translation_mode,
|
||||
},
|
||||
|
|
@ -797,50 +797,9 @@ export function NewJob() {
|
|||
|
||||
{/* Translation Mode - Only shown when target languages are selected */}
|
||||
{languages.length > 0 && (
|
||||
<div>
|
||||
<label className="block text-sm font-medium text-gray-700 mb-2">
|
||||
Translation Mode
|
||||
</label>
|
||||
<div className="space-y-3">
|
||||
<label className="flex items-start gap-3 p-3 border border-gray-200 rounded-lg cursor-pointer hover:bg-gray-50 transition-colors">
|
||||
<input
|
||||
type="radio"
|
||||
{...register('translation_mode')}
|
||||
value="video_native"
|
||||
className="mt-1"
|
||||
disabled={isUploading}
|
||||
/>
|
||||
<div>
|
||||
<div className="font-medium text-gray-900">
|
||||
Video Native Mode
|
||||
<span className="ml-2 text-xs bg-blue-100 text-blue-800 px-2 py-0.5 rounded">
|
||||
Recommended
|
||||
</span>
|
||||
</div>
|
||||
<p className="text-sm text-gray-500 mt-1">
|
||||
Re-processes the video with AI for each language. Generates captions and audio descriptions
|
||||
directly from visual context, resulting in more natural and culturally appropriate content.
|
||||
</p>
|
||||
</div>
|
||||
</label>
|
||||
|
||||
<label className="flex items-start gap-3 p-3 border border-gray-200 rounded-lg cursor-pointer hover:bg-gray-50 transition-colors">
|
||||
<input
|
||||
type="radio"
|
||||
{...register('translation_mode')}
|
||||
value="traditional"
|
||||
className="mt-1"
|
||||
disabled={isUploading}
|
||||
/>
|
||||
<div>
|
||||
<div className="font-medium text-gray-900">Traditional VTT Translation</div>
|
||||
<p className="text-sm text-gray-500 mt-1">
|
||||
Translates existing English VTT files to target languages. Faster but may lose some
|
||||
visual context nuances.
|
||||
</p>
|
||||
</div>
|
||||
</label>
|
||||
</div>
|
||||
<div className="rounded-lg bg-blue-50 border border-blue-200 px-4 py-3 text-sm text-blue-800">
|
||||
Translations are generated from the approved English master VTT, preserving all cue timings 1:1.
|
||||
Target languages become available for linguist review after English QC is approved.
|
||||
</div>
|
||||
)}
|
||||
|
||||
|
|
|
|||
|
|
@ -48,7 +48,7 @@ export type TTSProvider = "gemini" | "google" | "elevenlabs";
|
|||
export type TTSModel = "flash" | "pro";
|
||||
export type TTSStylePreset = "neutral" | "calm" | "energetic" | "professional" | "warm" | "documentary" | "custom";
|
||||
|
||||
export type TranslationMode = "traditional" | "video_native";
|
||||
export type TranslationMode = "traditional";
|
||||
|
||||
export interface TTSPreferences {
|
||||
provider: TTSProvider;
|
||||
|
|
@ -74,7 +74,7 @@ export interface RequestedOutputs {
|
|||
languages: string[];
|
||||
transcreation: string[];
|
||||
tts_preferences?: TTSPreferences;
|
||||
translation_mode?: TranslationMode; // "video_native" (default) or "traditional"
|
||||
translation_mode?: TranslationMode;
|
||||
}
|
||||
|
||||
export interface VoiceInfo {
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue