project-architecture

name

project-architecture

description

Orchestration-level architecture of the Owarai GrillMaster pipeline: the resumable stage machine in `workflow/`, project state and path layout in `project.py`, settings/`.env`/ModelSpec in `settings.py`, the Typer CLI in `main.py`, and the supporting services (`services/srt/`, `services/media.py`, `services/ytdlp/`, `services/elevenlabs/`, `services/fixed_glossary/`, `services/progress.py`). Read this before adding/reordering a pipeline stage, changing resumability or cost accounting, adding a setting, adding a source platform, or any task that spans more than one service module. Deep dives live in the sibling skills inference-layer, translate-pipeline, and postprocess-and-packaging.

Owarai GrillMaster — Architecture

A single-user CLI that turns a Japanese variety-show video ID/URL into Traditional Chinese subtitles (SRT + styled ASS), optionally burning them into the video. Everything is local and resumable; there is no server, queue, or database — state lives entirely in projects/<id>/.

Sibling skills own the deep detail — read the one whose files you're touching:

• inference-layer — services/inference/ (backends, schema repair, frame tools)
• translate-pipeline — services/translate/ (pre-pass, chunking, chunk workers, caches)
• postprocess-and-packaging — services/postprocess/, services/finalize/, services/package/

Mental model

The whole program is a linear, idempotent, resumable stage machine. One Project (a Pydantic model persisted as projects/<id>/project.json) carries a boolean per stage. The workflow/ package runs the stages in order; each stage checks its boolean, skips if already done, and on success calls project.mark_progress(...) which flips the boolean and re-saves the JSON. Re-running the same ID resumes exactly where it left off. This is the central invariant — every new stage must preserve it.

The expensive model-driven stages additionally cache their intermediate media and responses under dot-dirs (.asr/, .pre_pass/, .chunks/, …) so that a resume after a crash does not re-extract audio, re-sample frames, or re-call the model for chunks that already succeeded. These caches never self-invalidate; forcing a re-run means deleting the dot-dir.

The pipeline (workflow/)

workflow/__init__.py is the public facade (submit_project, process_project, ProgressStage). workflow/api.py creates/loads the Project, then _process_project_impl runs the stages below in order through WorkflowRunner. Each maps 1:1 to a ProgressStage enum value and a Project.is_* boolean (see "Stage ↔ field sync" invariant). Stage bodies live under workflow/stages/ by subsystem; post-finalize archive/package is in workflow/delivery.py; cover/date background futures are managed by workflow/side_tasks.py.

#	Stage (ProgressStage)	What happens	Module
1	METADATA_FETCHED	get_video_info; for TVer/Abema also fetch cast/talents; resolve_broadcast_date persists Project.broadcast_date (best-effort). Kicks off async broadcast-date research after this stage if enabled and the date is still None	services/ytdlp, services/postprocess/date_research
2	DOWNLOADED	download_video (yt-dlp); also best-effort fetches platform CC subs (ENABLE_OFFICIAL_SUBTITLES). Kicks off async cover gen here if enabled	services/ytdlp, services/postprocess/cover
3	VIDEO_PROCESSED	MediaProcessor.combine_videos (ffmpeg concat) → video.mp4; normalizes downloaded CC → video.official.ja.srt (section runs rebase/filter timestamps)	services/media, services/ytdlp/subtitles
4	AUDIO_PROCESSED	MediaProcessor.extract_audio → .asr/audio.ogg (mono 16 kHz libopus)	services/media
5	ASR_COMPLETED	ElevenLabs Scribe → .asr/asr.json; adds cost	services/elevenlabs
6	SRT_COMPLETED	convert_file ASR JSON → video.ja.srt	services/elevenlabs/srt_builder
7	PREPASS_COMPLETED	One whole-film analysis call → .pre_pass/pre_pass.json	services/translate (pre_pass)
8	CHUNK_TRANSLATED	Concurrent per-chunk translation → video.cht.srt	services/translate (chunk)
9	SRT_REFINED (optional)	Agent polishes TC subtitles → video.cht.refined.srt	services/postprocess/refine
10	GLOSSARY_CHECKED (optional)	Agent checks full-text terminology/facts, may correct pre_pass.json → video.cht.glossary_checked.srt	services/postprocess/glossary_check
11	FINALIZED	Punctuation cleanup → styled video.cht.ass + video.cht.finalized.srt	services/finalize

After FINALIZED (and only if no --break-after): join the async cover and date-research futures, optionally archive() the project dir, then package_project (burn-in + cover copy / remix). Archive and package are post-loop, not stages. Package output is flat: PACKAGE_PATH/{deliverable_name} — YYMMDD_{id}_{name} when broadcast_date is known (announced on-air/publish date, platform-local timezone), plain {id}_{name} otherwise. Archive nests by date instead: ARCHIVED_PATH / Project.archive_subpath = YY/MM/YYMMDD_{id}_{name} when dated, etc/{id}_{name} otherwise; archive() only rmtree's the leaf dir, never the shared YY/MM/etc parents.

Key control-flow details that are easy to break:

• --break-after <stage> stops cleanly after the named stage (works on a fresh or resumed project). When set, cover generation is skipped entirely.
• --start / --to (either or both) process only a section. The full video is still downloaded (yt-dlp's --download-sections is ffmpeg-backed and slow); the video-processing stage combines to video.full.mp4, then stream-copy cuts video.mp4 (keyframe-aligned). Ignored with a warning if the video is already processed.
• Cover generation runs in a background ThreadPoolExecutor started right after download and joined in the finally block — even on pipeline failure, because the Codex subscription cost is already incurred. Don't move the join. The join timeout is the hardcoded _COVER_JOIN_TIMEOUT_SECS in workflow/side_tasks.py. Note is_cover_generated is a Project boolean but not a ProgressStage: it is set directly in the finally block, not via mark_progress.
• Broadcast-date research (ENABLE_BROADCAST_DATE_AGENT_FALLBACK / --date-research, default off) follows the same side-task pattern: started after METADATA_FETCHED when broadcast_date is None, joined in the same finally before archive/package (the deliverable name needs the date). The worker only writes .artifacts/date_research.json (fixed-filename cache; corrupt files count as a miss; delete to re-run); the main thread applies the verdict and sets is_broadcast_date_researched (also not a ProgressStage) — set even on an "unknown" verdict so a resume doesn't re-spend tokens. A completed artifact left by a previous run is applied at kick-off even when the fallback is disabled (the result is already paid for); only the agent dispatch is gated on the flag.
• Optional stages are gated twice: by a settings.enable_* toggle OR a per-run --refine/--glossary-check/--cover/--date-research flag (the flag force-enables).
• Cost accounting: metered stages call project.add_cost(service, amount), which accumulates into project.json. TranslationError carries a partial cost summary so a mid-run failure still records what was spent.
• Stage timing logs: successful main stages go through WorkflowRunner, which logs Stage complete: ... (<elapsed>) after the action and mark_progress finish. Cover/date side tasks use the same elapsed suffix, measured from async dispatch to join.
• Finalize input precedence: glossary-checked SRT → refined SRT → translated SRT (first that exists wins).
• Future architecture direction: the package still keeps the pipeline as an explicit ordered sequence in workflow/api.py. If stage count or branching grows, the next step is a declarative stage registry built on StageSpec and WorkflowRunner, but do not introduce that extra indirection until it removes real branching or repetition.

Project state (project.py)

Project is the single source of truth. It owns:

• Identity: parse_source_str extracts the canonical ID from an ID or URL across Bilibili (BV…), YouTube (stored as v=…), TVer (ep…/sh…), Abema (fallback). source and source_url are derived from the ID's shape — keep these consistent if you add a platform. Abema has two URL kinds: episode IDs contain -/_; pure-alphanumeric IDs are slots (live archives) and rebuild as channels/_/slots/<id> (yt-dlp ignores the channel segment).
• All path properties (video_path, srt_path, pre_pass_path, chunks_cache_dir, …). Never hard-code a project file path elsewhere — add or read a property here so the layout stays in one place.
• Cross-episode seeding: parent_project_path → parent_pre_pass_context() reads a parent project's pre_pass.json to keep names/terms consistent across episodes. It raises early (before any model cost) if the parent is missing.
• Stage ↔ field sync invariant: check_enum_field_sync() runs at import and asserts every ProgressStage value names a real Project.is_* field. If you add a stage you MUST add both the enum value and the boolean field, or import fails fast.

Supporting services

• services/srt/ — SRT primitives: SrtBlock, parse_srt, serialize_srt, timecode math. The shared subtitle data model used everywhere.
• services/media.py — MediaProcessor: ffmpeg wrappers (combine, extract audio, frame sampling, burn-in). FFmpeg must be on PATH. Burn-in runs with -nostdin (headless safety) and validates output duration afterward (BURN_IN_DURATION_TOLERANCE_SECONDS, 2 s): ffmpeg can exit 0 yet silently truncate, so a too-short output raises instead of shipping.
• services/ytdlp/ — download + metadata + TVer/Abema talent scraping + broadcast_date.py (resolves the announced on-air/publish date: YouTube/ BiliBili from yt-dlp timestamps, TVer from broadcastDateLabel month/day + year inferred from the availability start, Abema from program broadcastAt or slot startAt; all best-effort → None) + subtitles.py (platform CC → video.official.ja.srt; single video part only — multi-part is skipped with a warning and the pipeline continues without the reference; same-part language variants prefer exact ja; consumed as ground-truth reference by the translate stages and glossary check — see translate-pipeline / postprocess-and-packaging). Two BiliBili gotchas live in client.py: (1) a temporary monkey-patch falls back from /x/player/wbi/playurl (HTTP 412 on some videos in current yt-dlp) to /x/player/playurl — remove when upstream fixes it; (2) BiliBili inputs are anonymous by default (cookies disabled) because authenticated cookies can lock the format list to 480p; other platforms keep cookies. download.py registers a jpeg-extension fixup PP before the thumbnail convertor (Abema slot thumbnails are JPEG bytes named .png, which breaks the extension-driven image2 demuxer) — keep the convertor out of the opts dict so the fixup stays first.
• services/elevenlabs/ — ASR client + ASR-JSON → SRT builder. Source SRT formatting constants are hard-coded at the top of the builder (maintainer-tuned, intentionally not settings).
• services/fixed_glossary/ — loads fixed_glossary.json / .md (canonical term translations) consumed by pre-pass, glossary-check, and finalize (it is a runtime input for name spacing, not just prompt content).
• services/progress.py — Rich progress reporter (create_progress_reporter, NoopProgressReporter) threaded through chunk translation and packaging.

Settings & configuration (settings.py)

Pydantic-settings, loaded from .env. Notable patterns:

• Per-stage backend selection: pre-pass, chunk, post-process, and the common utility agents (chunk structural fix + broadcast-date research) each pick one spec (agent_prepass_model / agent_chunk_model / agent_postprocess_model / agent_common_model, i.e. AGENT_*_MODEL in .env).
• ModelSpec: *_MODEL is written as "backend/model" or "backend/model/effort" (effort is one of low/medium/high/extra, default high) and parsed into .backend + .model + .reasoning_effort. effort is mapped per client (gemini thinking_level, codex model_reasoning_effort, claude effort); backends without an extra-high value clamp repo-level extra to their highest supported value. The ModelSpecField annotation uses NoDecode so pydantic-settings doesn't JSON-decode the shorthand string — any new spec-shaped field needs the same annotation.
• AGENT_GEMINI_API_KEY is required only when a stage uses gemini-api.
• AGENT_GEMINI_GCP_PROJECT is optional and applies only to gemini-cli (see inference-layer for the env handling).

Prompts are .md files

Every prompt template is a .md under the owning module's prompts/ dir, loaded by a sibling prompts.py. Edit the .md for wording; edit prompts.py only for assembly logic. See translate-pipeline for the audio-conditioned substitution rules guarded by tests.

Testing

uv run --with pytest python -m pytest          # full suite (~350 tests, seconds)
uv run --with pytest python -m pytest tests/test_inference.py        # one file
uv run --with pytest python -m pytest -k chunk_validation            # by keyword

python -m pytest (not bare pytest) is required so the repo root is on sys.path and services/project/workflow import. pytest is not a project dependency — it's pulled in ephemerally via uv run --with pytest. Tests are fast and fully offline (model/network calls are mocked); there is no CI.

Where to make a change (cheat sheet)

• New pipeline stage → add ProgressStage value and Project.is_* field (import-time sync check), add the stage body under workflow/stages/, wire it into workflow/api.py with WorkflowRunner, add path properties on Project.
• New model backend → inference-layer.
• New translate behavior → translate-pipeline (keep chunk-boundary determinism intact).
• Refine/glossary/cover/finalize/packaging → postprocess-and-packaging.
• Prompt wording → the .md, never inline strings.
• New tunable → a settings.py field with a description; read it at the call site, don't thread it through constructors.