refactor: models_api.py vira ponto de entrada sobre admin/api/

A ponte JSON do app tinha 1.395 linhas e 37 comandos de oito assuntos
diferentes num arquivo só. Agora models_api.py guarda apenas a referência
dos comandos, a tabela de despacho e o main(); cada assunto virou um módulo
em admin/api/ (models, project, editing, zoom, subtitles, transcription,
voice, review), com a base comum em shared.py.

Nada muda para o app: ele continua chamando admin/models_api.py por caminho,
e os 37 comandos respondem igual — verificado rodando a ponte de verdade.

Duas coisas que a divisão obrigou a arrumar:

- A saída passa por `shared.emit` chamada pelo módulo, não pelo nome
  importado. Isso preserva a propriedade de que trocar `emit` num lugar só
  captura a saída de todos os comandos — que era acidental quando tudo
  morava no mesmo arquivo, e vira intencional agora.
- `_CANCEL` e o lock eram globais compartilhados. O registro de downloads
  foi para models.py, junto de quem o usa, com lock próprio: o antigo
  protegia ao mesmo tempo o dicionário e a escrita em stdout, duas coisas
  sem relação.

Também: admin/test_models_api.py estava fora de `testpaths` e nunca rodava.
Movido para code/tests/ e ligado ao gate — 1441 → 1454 testes
(ver Engine/docs/05_EXPERIENCIAS.md #24).

Lint zerado, 1454 testes passando.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

admin/api/__init__.py

@@ -0,0 +1 @@
+"""Comandos da ponte JSON usada pelo app, agrupados por assunto."""

admin/api/editing.py

@@ -0,0 +1,128 @@
+"""Edições no projeto: silêncio, corte por texto, preenchimento, marcadores.
+
+Extraído de models_api.py — a tabela de comandos segue lá.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import sys
+from pathlib import Path
+
+# code/ is the package root for fcpxml and server modules.
+_CODE_DIR = str(Path(__file__).resolve().parent.parent / "code")
+if _CODE_DIR not in sys.path:
+    sys.path.insert(0, _CODE_DIR)
+
+from fcpxml.model_manager import (
+    load_silence_config,
+    save_silence_config,
+)
+
+from . import shared
+from .shared import (
+    _derived_output,
+    _emit_no_change_or_error,
+)
+
+
+def cmd_remove_silences(args: dict) -> int:
+    """Run the canonical server silence remover into a suffixed copy."""
+    path = str(args.get("path", ""))
+    if not path or not Path(path).exists():
+        shared.emit({"ok": False, "error": "Arquivo de projeto não encontrado."})
+        return 1
+    try:
+        from server import handle_remove_media_silence
+
+        output = _derived_output(path, "_silence_removed", args)
+        contents = asyncio.run(handle_remove_media_silence({**args, "filepath": path, "output_path": output}))
+        message = "\n".join(getattr(content, "text", str(content)) for content in contents)
+        if not Path(output).exists():
+            return _emit_no_change_or_error(path, message)
+        shared.emit({"ok": True, "path": output, "message": message})
+        return 0
+    except Exception as exc:
+        shared.emit({"ok": False, "error": str(exc)})
+        return 1
+
+def cmd_edit_by_transcript(args: dict) -> int:
+    """Cut (or keep only) spoken phrases, using each media's cached transcript."""
+    path = str(args.get("path", ""))
+    phrases = args.get("phrases") or []
+    if not path or not Path(path).exists():
+        shared.emit({"ok": False, "error": "Arquivo de projeto não encontrado."})
+        return 1
+    if not isinstance(phrases, list) or not [p for p in phrases if str(p).strip()]:
+        shared.emit({"ok": False, "error": "Informe ao menos uma frase para cortar."})
+        return 1
+    try:
+        from server import handle_edit_by_transcript
+
+        output = _derived_output(path, "_transcript_edit", args)
+        contents = asyncio.run(handle_edit_by_transcript({**args, "filepath": path, "output_path": output}))
+        message = "\n".join(getattr(content, "text", str(content)) for content in contents)
+        if not Path(output).exists():
+            shared.emit({"ok": False, "error": message})
+            return 1
+        shared.emit({"ok": True, "path": output, "message": message})
+        return 0
+    except Exception as exc:
+        shared.emit({"ok": False, "error": str(exc)})
+        return 1
+
+def cmd_remove_filler_words(args: dict) -> int:
+    """Cut filler words (um, uh, ...) out, using each media's cached transcript."""
+    path = str(args.get("path", ""))
+    if not path or not Path(path).exists():
+        shared.emit({"ok": False, "error": "Arquivo de projeto não encontrado."})
+        return 1
+    try:
+        from server import handle_remove_filler_words
+
+        output = _derived_output(path, "_defillered", args)
+        contents = asyncio.run(handle_remove_filler_words({**args, "filepath": path, "output_path": output}))
+        message = "\n".join(getattr(content, "text", str(content)) for content in contents)
+        if not Path(output).exists():
+            return _emit_no_change_or_error(path, message)
+        shared.emit({"ok": True, "path": output, "message": message})
+        return 0
+    except Exception as exc:
+        shared.emit({"ok": False, "error": str(exc)})
+        return 1
+
+def cmd_transcript_markers(args: dict) -> int:
+    """Add a marker per transcribed segment, using each media's cached transcript."""
+    path = str(args.get("path", ""))
+    if not path or not Path(path).exists():
+        shared.emit({"ok": False, "error": "Arquivo de projeto não encontrado."})
+        return 1
+    try:
+        from server import handle_transcript_markers
+
+        output = _derived_output(path, "_transcript_markers", args)
+        contents = asyncio.run(handle_transcript_markers({**args, "filepath": path, "output_path": output}))
+        message = "\n".join(getattr(content, "text", str(content)) for content in contents)
+        if not Path(output).exists():
+            shared.emit({"ok": False, "error": message})
+            return 1
+        shared.emit({"ok": True, "path": output, "message": message})
+        return 0
+    except Exception as exc:
+        shared.emit({"ok": False, "error": str(exc)})
+        return 1
+
+def cmd_silence_config(args: dict) -> int:
+    """Read the persisted silence thresholds (noise floor, duration, padding)."""
+    shared.emit({"ok": True, **load_silence_config()})
+    return 0
+
+def cmd_set_silence_config(args: dict) -> int:
+    """Persist silence thresholds. Only the given fields change."""
+    config = save_silence_config(
+        noise_db=args.get("noise_db"),
+        min_silence=args.get("min_silence"),
+        padding=args.get("padding"),
+    )
+    shared.emit({"ok": True, **config})
+    return 0

admin/api/models.py

@@ -0,0 +1,145 @@
+"""Catálogo de modelos: listar, baixar, escolher, apagar.
+
+Extraído de models_api.py — a tabela de comandos segue lá.
+"""
+
+from __future__ import annotations
+
+import shutil
+import subprocess
+import sys
+import threading
+from pathlib import Path
+
+# code/ is the package root for fcpxml and server modules.
+_CODE_DIR = str(Path(__file__).resolve().parent.parent / "code")
+if _CODE_DIR not in sys.path:
+    sys.path.insert(0, _CODE_DIR)
+
+from fcpxml.diarize import (
+    diarization_capability,
+)
+from fcpxml.model_manager import (
+    download_model,
+    get_models_dir,
+    is_model_downloaded,
+    list_installed_models,
+    load_catalog,
+    load_hf_token,
+    load_num_speakers,
+    load_selected_model,
+    load_transcript_language,
+    model_cache_dir,
+    save_models_dir,
+    save_selected_model,
+    save_transcript_language,
+)
+
+from . import shared
+from .shared import (
+    RECOMMENDED,
+)
+
+
+# Downloads em andamento, para o comando `cancel` conseguir interrompê-los.
+# Mora aqui, e não no shared, porque só `download` e `cancel` o tocam — e o
+# lock é próprio: ele protege este dicionário, não a saída em stdout.
+_CANCEL: dict[str, threading.Event] = {}
+_CANCEL_LOCK = threading.Lock()
+
+
+def cmd_catalog() -> None:
+    catalog = load_catalog()
+    installed = list_installed_models()
+    diar_ok, diar_msg = diarization_capability(load_hf_token())
+    shared.emit(
+        {
+            "models": catalog,
+            "installed": installed,
+            "selected": load_selected_model(),
+            "language": load_transcript_language(),
+            "models_dir": str(get_models_dir()),
+            "installed_count": len(installed),
+            "recommended": list(RECOMMENDED),
+            "diarization": diar_ok,
+            "diarization_message": diar_msg,
+            "hf_token_set": bool(load_hf_token()),
+            "num_speakers": load_num_speakers(),
+        }
+    )
+
+def cmd_download(args: dict) -> int:
+    model = str(args.get("model", ""))
+    if model not in _model_names():
+        shared.emit({"type": "error", "message": f"Modelo desconhecido: {model}"})
+        return 1
+    ev = threading.Event()
+    with _CANCEL_LOCK:
+        _CANCEL[model] = ev
+    try:
+        download_model(model, progress_cb=lambda f: shared.emit({"type": "progress", "fraction": f}), cancel_event=ev)
+        installed = is_model_downloaded(model)
+        shared.emit({"type": "done", "installed": installed})
+        if installed:
+            save_selected_model(model)
+        return 0 if installed else 1
+    except Exception as exc:
+        shared.emit({"type": "error", "message": str(exc)})
+        return 1
+    finally:
+        with _CANCEL_LOCK:
+            _CANCEL.pop(model, None)
+
+def cmd_cancel(args: dict) -> None:
+    model = str(args.get("model", ""))
+    ev = _CANCEL.get(model)
+    if ev is not None:
+        ev.set()
+    shared.emit({"ok": True})
+
+def cmd_select(args: dict) -> None:
+    model = str(args.get("model", ""))
+    if not is_model_downloaded(model):
+        shared.emit({"ok": False, "error": "Modelo não está instalado."})
+        return
+    save_selected_model(model)
+    shared.emit({"ok": True, "selected": load_selected_model()})
+
+def cmd_set_language(args: dict) -> int:
+    """Persist the transcription language (the default for every transcription)."""
+    lang = str(args.get("language", "auto"))
+    try:
+        saved = save_transcript_language(lang)
+    except ValueError as exc:
+        shared.emit({"ok": False, "error": str(exc)})
+        return 1
+    shared.emit({"ok": True, "language": saved})
+    return 0
+
+def cmd_delete(args: dict) -> None:
+    model = str(args.get("model", ""))
+    try:
+        shutil.rmtree(model_cache_dir(model), ignore_errors=True)
+    except Exception:
+        pass
+    shared.emit({"ok": True})
+
+def cmd_open_finder(args: dict) -> None:
+    target = str(args.get("path") or model_cache_dir(str(args.get("model", ""))))
+    try:
+        subprocess.Popen(["open", target])
+    except OSError:
+        pass
+    shared.emit({"ok": True})
+
+def cmd_set_models_dir(args: dict) -> int:
+    try:
+        d = save_models_dir(str(args.get("dir", "")))
+        shared.emit({"ok": True, "models_dir": d})
+        return 0
+    except ValueError as exc:
+        shared.emit({"ok": False, "error": str(exc)})
+        return 1
+
+def _model_names() -> list[str]:
+    return [m["internal_name"] for m in load_catalog()]

admin/api/project.py

@@ -0,0 +1,75 @@
+"""Projeto: inspecionar o .fcpxml e lembrar a pasta/arquivo em uso.
+
+Extraído de models_api.py — a tabela de comandos segue lá.
+"""
+
+from __future__ import annotations
+
+import sys
+from pathlib import Path
+
+# code/ is the package root for fcpxml and server modules.
+_CODE_DIR = str(Path(__file__).resolve().parent.parent / "code")
+if _CODE_DIR not in sys.path:
+    sys.path.insert(0, _CODE_DIR)
+
+from fcpxml.model_manager import (
+    load_project_config,
+    save_project_config,
+)
+from fcpxml.parser import parse_fcpxml
+
+from . import shared
+
+
+def cmd_inspect(args: dict) -> int:
+    """Validate an FCPXML file and return a summary of its projects/timelines."""
+    path = str(args.get("path", ""))
+    if not path:
+        shared.emit({"ok": False, "error": "Nenhum arquivo informado."})
+        return 1
+    if not Path(path).exists():
+        shared.emit({"ok": False, "error": "Arquivo não encontrado."})
+        return 1
+    try:
+        proj = parse_fcpxml(path)
+    except Exception as exc:
+        shared.emit({"ok": False, "error": f"Erro ao ler o projeto: {exc}"})
+        return 1
+
+    timelines = []
+    for tl in proj.timelines:
+        timelines.append(
+            {
+                "name": tl.name,
+                "duration_seconds": round(tl.duration.seconds, 3),
+                "frame_rate": round(tl.frame_rate, 3),
+                "width": tl.width,
+                "height": tl.height,
+                "clips": tl.total_clips,
+                "cuts": tl.total_cuts,
+                "connected": len(tl.connected_clips),
+                "markers": len(tl.markers),
+            }
+        )
+    shared.emit(
+        {
+            "ok": True,
+            "path": path,
+            "name": proj.name,
+            "fcpxml_version": proj.fcpxml_version,
+            "timelines": timelines,
+        }
+    )
+    return 0
+
+def cmd_project_config(args: dict) -> int:
+    """Read the last project folder/file the app was working on."""
+    shared.emit({"ok": True, **load_project_config()})
+    return 0
+
+def cmd_set_project_config(args: dict) -> int:
+    """Persist the last project folder/file. Only the given fields change."""
+    config = save_project_config(folder=args.get("folder"), file=args.get("file"))
+    shared.emit({"ok": True, **config})
+    return 0

admin/api/review.py

@@ -0,0 +1,97 @@
+"""Revisão de frases: montar a tela de ênfases e salvar o que foi decidido.
+
+Extraído de models_api.py — a tabela de comandos segue lá.
+"""
+
+from __future__ import annotations
+
+import json
+import sys
+from pathlib import Path
+
+# code/ is the package root for fcpxml and server modules.
+_CODE_DIR = str(Path(__file__).resolve().parent.parent / "code")
+if _CODE_DIR not in sys.path:
+    sys.path.insert(0, _CODE_DIR)
+
+
+from . import shared
+
+
+def cmd_build_phrase_review(args: dict) -> int:
+    """Build the reviewable script (phrases + the AI's decisions) for the wizard.
+
+    `voice_timeline` points at the _voice_timeline.json; `actions` carries the
+    decision list the model returned (inline, in any of the shapes the skill
+    emits). The review is always rebuilt from the current analysis, then the
+    decisions saved on a previous visit are laid back over it — reopening the
+    step must show the edits the user left there without freezing the acoustics
+    as they were when they left.
+    """
+    from fcpxml.phrase_review import (
+        build_phrase_review,
+        load_phrase_review,
+        merge_saved_decisions,
+    )
+
+    timeline_path = str(args.get("voice_timeline", ""))
+    if not timeline_path or not Path(timeline_path).exists():
+        shared.emit({"ok": False, "error": "Análise de voz (voice_timeline.json) não encontrada."})
+        return 1
+
+    try:
+        with open(timeline_path, encoding="utf-8") as fh:
+            timeline = json.load(fh)
+    except (OSError, ValueError) as exc:
+        shared.emit({"ok": False, "error": f"Erro ao ler a análise de voz: {exc}"})
+        return 1
+
+    extra = [d for d in (args.get("output_dir"), args.get("media_dir")) if d]
+    review = build_phrase_review(
+        timeline,
+        args.get("actions"),
+        voice_timeline_path=timeline_path,
+        extra_dirs=extra,
+    )
+
+    saved = None if args.get("fresh") else load_phrase_review(timeline_path)
+    review = merge_saved_decisions(review, saved)
+    shared.emit({"ok": True, "reused": saved is not None, **review})
+    return 0
+
+def cmd_save_phrase_review(args: dict) -> int:
+    """Persist the edited review and the actions derived from it."""
+    from fcpxml.phrase_review import save_phrase_review
+
+    timeline_path = str(args.get("voice_timeline", ""))
+    if not timeline_path:
+        shared.emit({"ok": False, "error": "Caminho da análise de voz não informado."})
+        return 1
+
+    phrases = args.get("phrases")
+    if not isinstance(phrases, list):
+        shared.emit({"ok": False, "error": "Nenhuma frase para salvar."})
+        return 1
+
+    review = {
+        "version": args.get("version", "1.0"),
+        "source": args.get("source", ""),
+        "duration": args.get("duration", 0.0),
+        "speakers": args.get("speakers", []),
+        "phrases": phrases,
+        "zooms": args.get("zooms", []),
+    }
+    try:
+        review_path, actions_path = save_phrase_review(timeline_path, review)
+    except OSError as exc:
+        shared.emit({"ok": False, "error": f"Erro ao salvar a revisão: {exc}"})
+        return 1
+
+    shared.emit({
+        "ok": True,
+        "review_path": str(review_path),
+        "actions_path": str(actions_path),
+        "emphasis_count": sum(1 for p in phrases if int(p.get("emphasis", 0) or 0) >= 1),
+        "removed_count": sum(1 for p in phrases if not p.get("active", True)),
+    })
+    return 0

admin/api/shared.py

@@ -0,0 +1,306 @@
+"""Base comum dos comandos da ponte: saída JSON, caminhos derivados e cache.
+
+A saída passa toda por `emit`. Os módulos de comando chamam `shared.emit(...)`
+pelo módulo, e não pelo nome importado, de propósito: assim trocar `emit` num
+lugar só — como a suíte faz para capturar a saída — continua alcançando todos
+os comandos, o que deixaria de valer se cada um tivesse ligado o nome no seu
+próprio import.
+"""
+
+from __future__ import annotations
+
+import json
+import os
+import sys
+import threading
+from pathlib import Path
+from typing import Any
+
+# code/ is the package root for fcpxml and server modules.
+_CODE_DIR = str(Path(__file__).resolve().parent.parent / "code")
+if _CODE_DIR not in sys.path:
+    sys.path.insert(0, _CODE_DIR)
+
+from fcpxml.media_intel import media_src_to_path
+from fcpxml.parser import parse_fcpxml
+from fcpxml.diarize import build_speakers  # noqa: E402
+
+"""JSON bridge between the SwiftUI app and the fcp-mcp-server Python engine.
+
+The SwiftUI app (MacApp/) launches this script as a subprocess with a command
+and optional JSON arguments, then reads a single JSON document (or
+newline-delimited JSON for progress) on stdout.
+
+Commands:
+    catalog
+        -> {"models": [{display_name, internal_name, size, storage,
+                        accuracy, speed}], "installed": [names],
+            "selected": name, "models_dir": path, "installed_count": n,
+            "recommended": [names]}
+
+    download {"model": "small"}
+        -> JSON-lines: {"type":"progress","fraction":0.42}
+                       {"type":"done","installed":true}
+                       {"type":"error","message":"..."}
+
+    cancel {"model": "small"}
+        -> {"ok": true}
+
+    select {"model": "small"}
+        -> {"ok": true, "selected": "small"}
+
+    set_language {"language": "pt"} | "auto"
+        -> {"ok": true, "language": "pt"}
+
+    delete {"model": "small"}
+        -> {"ok": true}
+
+    open_finder {"model": "small"}
+        -> {"ok": true}
+
+    set_models_dir {"dir": "/path"}
+        -> {"ok": true, "models_dir": "/path"}
+
+    inspect {"path": "/path/to/project.fcpxml"}
+        -> {"ok": true, "path": "...", "name": "...", "fcpxml_version": "1.13",
+            "timelines": [{name, duration_seconds, frame_rate, width, height,
+                           clips, cuts, connected, markers}]}
+        or {"ok": false, "error": "..."}
+
+    analyze_voice {"path": "...", "output_dir": "...", "model": "...",
+                   "language": "pt"|"auto"|null, "hf_token": "..."|null,
+                   "num_speakers": ""|null}
+        Build the voice timeline (transcript+diarization+acoustics) for
+        every unique source media — analysis only, writes _voice_timeline.json
+        next to each media, `path` passes through unchanged. Meant as one
+        entry in the batch operations list (see processBatchStep), so
+        `refine_voice_timeline` never has to reopen the audio later.
+        -> {"ok": true, "path": "...", "message": "..."} or {"ok": false, "error": "..."}
+
+    build_phrase_review {"voice_timeline": "..._voice_timeline.json",
+                         "actions": {...}|[...]|null, "fresh": false}
+        The reviewable script for the wizard's emphasis step: every phrase with
+        the AI's decision already applied (active/emphasis/trim). A review saved
+        earlier for the same timeline is returned as-is unless `fresh` is true.
+        -> {"ok": true, "reused": bool, "source", "duration", "speakers",
+            "phrases": [{index, start, end, trim_start, trim_end, text, speaker,
+                         active, emphasis (0-3), track, peak_emphasis,
+                         take_boundary, gap_before, reason, words}],
+            "errors": [...]}
+
+    save_phrase_review {"voice_timeline": "...", "phrases": [...], "source": "...",
+                        "duration": 0.0, "speakers": [...]}
+        Writes _phrase_review.json plus the _phrase_actions.json derived from it.
+        -> {"ok": true, "review_path", "actions_path", "emphasis_count",
+            "removed_count"}
+
+    dynamic_subtitle_config {}
+        -> {"ok": true, "band_height", "block_center_y", "line_gap", "font",
+            "font_size", "emphasis_font", "emphasis_face", "emphasis_size",
+            "active_color", "emphasis_color", "text_scale"}
+
+    set_dynamic_subtitle_config {<any of the fields above>}
+        Persists only the given fields to ~/.fcp-mcp-server/config.json.
+        generate_dynamic_subtitles reads this as its own fallback default.
+        -> {"ok": true, <same shape as dynamic_subtitle_config>}
+
+    silence_config {}
+        -> {"ok": true, "noise_db": -30.0, "min_silence": 0.5, "padding": 0.05}
+
+    set_silence_config {"noise_db": -30.0, "min_silence": 0.5, "padding": 0.05}
+        Persists only the given fields. detect_media_silence and
+        remove_media_silence read this as their own fallback default.
+        -> {"ok": true, <same shape as silence_config>}
+
+    transcribe {"path": "...", "model": "small", "language": "pt"|null,
+                "hf_token": "..."|null, "num_speakers": ""|null}
+        -> JSON-lines:
+            {"type":"progress","fraction":0.5,"stage":"Transcrevendo..."}
+            {"type":"result","transcripts":[{"media","language","words",
+                                             "duration","preview","saved",
+                                             "speakers"}]}
+            {"type":"error","message":"..."}
+
+    edit_by_transcript {"path": "...", "phrases": ["frase um", "frase dois"],
+                        "mode": "remove"|"keep_only", "clip_name": "..."|null,
+                        "padding": 0.0, "model": "small", "language": "pt"|null}
+        -> {"ok": true, "path": "..._transcript_edit.fcpxml", "message": "..."}
+        or {"ok": false, "error": "..."}
+
+    remove_filler_words {"path": "...", "fillers": ["um","uh"]|null,
+                         "clip_name": "..."|null, "padding": 0.02,
+                         "model": "small", "language": "pt"|null}
+        -> {"ok": true, "path": "..._defillered.fcpxml", "message": "..."}
+        or {"ok": false, "error": "..."}
+
+    transcript_markers {"path": "...", "clip_name": "..."|null,
+                        "marker_type": "chapter", "max_label_length": 50,
+                        "model": "small", "language": "pt"|null}
+        -> {"ok": true, "path": "..._transcript_markers.fcpxml", "message": "..."}
+        or {"ok": false, "error": "..."}
+
+    add_zoom {"path": "...", "clip_id": "...", "start": 10.0, "end": 16.0,
+              "scale": 1.3, "ease": 0.3, "position": "0 0"|null}
+        -> {"ok": true, "path": "..._zoom.fcpxml", "message": "..."}
+        or {"ok": false, "error": "..."}
+
+    generate_dynamic_subtitles {"path": "...", "clip_name": "..."|null,
+                                "band_height": 0.22, "block_center_y": -167,
+                                "font": "Helvetica Neue", "font_size": 128,
+                                "emphasis_font": "Playfair Display",
+                                "emphasis_face": "Medium Italic", "emphasis_size": 265,
+                                "active_color": "1 1 1 1", "emphasis_color": "1 1 1 1",
+                                "model": "small", "language": "pt"|null}
+        -> {"ok": true, "path": "..._dynamic_subtitles.fcpxml", "message": "..."}
+        or {"ok": false, "error": "..."}
+
+    rename_speakers {"path": "/to/media_transcript.json",
+                     "speakers": {"SPEAKER_01": "Nome"}}
+        -> {"ok": true, "speakers": [...]}
+
+    set_diarization {"token": "hf_...", "num_speakers": ""}
+        -> {"ok": true, "diarization": bool, "diarization_message": "...",
+            "num_speakers": "..."}
+
+    acoustics_capability
+        Whether librosa (pitch/energy for voice analysis) is installed.
+        -> {"ok": true, "available": bool, "message": "..."}
+
+    voice_analysis
+        -> {"ok": true, "energy_threshold": 0.5, "emphasis_threshold": 0.85,
+            "emphasis_weights": {...}, "emotion_enabled": false,
+            "emotion_sensitivity": 0.5}
+
+    set_voice_analysis {"energy_threshold": 0.6, "emphasis_threshold": 0.9,
+                        "emphasis_weights": {"energy": 0.4}|null,
+                        "emotion_enabled": true, "emotion_sensitivity": 0.5}
+        -> same shape as voice_analysis (only given fields change)
+
+Exit code 0 on success, 1 on error.
+"""
+
+_CODE_DIR = str(Path(__file__).resolve().parent.parent / "code")
+
+if _CODE_DIR not in sys.path:
+    sys.path.insert(0, _CODE_DIR)
+
+RECOMMENDED = ("large-v3", "distil-large-v3", "small", "base")
+
+def _derived_output(path: str, suffix: str, args: dict) -> str:
+    """Resolve a derived XML path, optionally inside the chosen output folder."""
+    output_dir = str(args.get("output_dir", "")).strip()
+    if output_dir:
+        directory = Path(output_dir).expanduser()
+        directory.mkdir(parents=True, exist_ok=True)
+        source = Path(path)
+        extension = ".fcpxmld" if source.is_dir() else source.suffix
+        return str(directory / f"{source.stem}{suffix}{extension}")
+    from server import generate_output_path
+    return generate_output_path(path, suffix)
+
+def _is_no_change_message(message: str) -> bool:
+    """Whether a tool completed cleanly without needing to save a new file."""
+    text = message.lower()
+    return any(
+        token in text
+        for token in (
+            "no cuts to make",
+            "no silence",
+            "file unchanged",
+            "nothing saved",
+        )
+    )
+
+def _emit_no_change_or_error(path: str, message: str) -> int:
+    if _is_no_change_message(message):
+        emit({"ok": True, "path": path, "unchanged": True, "message": message})
+        return 0
+    emit({"ok": False, "error": message})
+    return 1
+
+
+# Serializa a escrita em stdout. A ponte é JSON-lines: dois comandos
+# escrevendo ao mesmo tempo entrelaçariam documentos e o app leria lixo.
+_OUT_LOCK = threading.Lock()
+
+def emit(obj: Any) -> None:
+    sys.stdout.write(json.dumps(obj, ensure_ascii=False) + "\n")
+    sys.stdout.flush()
+
+def _transcript_json_path(media_path: str, output_dir: str = "") -> Path:
+    """Where the ``_transcript.json`` for ``media_path`` lives.
+
+    When ``output_dir`` (the user-selected project folder) is set, the
+    transcript is saved/read there — never next to the source media, which
+    may sit on a read-only volume or a Final Cut Library the user never
+    browses. Falls back to the media's own folder only when no project
+    folder has been chosen (legacy/MCP callers).
+    """
+    p = Path(media_path)
+    if output_dir:
+        directory = Path(output_dir).expanduser()
+        directory.mkdir(parents=True, exist_ok=True)
+        return directory / f"{p.stem}_transcript.json"
+    return p.with_name(p.stem + "_transcript.json")
+
+def _save_json_atomic(path: Path, data: Any) -> None:
+    """Write ``data`` to ``path`` atomically and validate the result on disk.
+
+    Mirrors the reference WHISPERX save path: write a ``.tmp``, ``os.replace``
+    into place, then confirm the file exists, is non-empty, and parses as JSON.
+    """
+    tmp_path = str(path) + ".tmp"
+    with open(tmp_path, "w", encoding="utf-8") as fh:
+        json.dump(data, fh, ensure_ascii=False, indent=2)
+    os.replace(tmp_path, path)
+    if not path.exists() or os.path.getsize(path) == 0:
+        raise RuntimeError("O arquivo salvo está vazio ou não foi encontrado.")
+    with open(path, encoding="utf-8") as fh:
+        json.load(fh)
+
+def _project_media_paths(path: str) -> list[str]:
+    proj = parse_fcpxml(path)
+    tl = proj.primary_timeline or (proj.timelines[0] if proj.timelines else None)
+    media_paths: list[str] = []
+    if tl is not None:
+        for clip in getattr(tl, "clips", []):
+            mp = media_src_to_path(clip.media_path or "")
+            if mp and Path(mp).is_file() and mp not in media_paths:
+                media_paths.append(mp)
+    return media_paths
+
+def _voice_timeline_json_path(media_path: str, output_dir: str = "") -> Path:
+    p = Path(media_path)
+    if output_dir:
+        directory = Path(output_dir).expanduser()
+        directory.mkdir(parents=True, exist_ok=True)
+        return directory / f"{p.stem}_voice_timeline.json"
+    return p.with_name(p.stem + "_voice_timeline.json")
+
+def _load_cached_voice_timeline(json_path: Path, media_path: str) -> dict | None:
+    try:
+        with open(json_path, encoding="utf-8") as fh:
+            data = json.load(fh)
+    except (OSError, json.JSONDecodeError, UnicodeDecodeError):
+        return None
+    if not isinstance(data, dict):
+        return None
+    if data.get("source") != Path(media_path).name:
+        return None
+    if not isinstance(data.get("segments"), list):
+        return None
+    return data
+
+def _load_cached_transcript(json_path: Path) -> dict | None:
+    """Return a valid cached transcript dict, or ``None`` if absent/unreadable."""
+    if not json_path.is_file():
+        return None
+    try:
+        data = json.loads(json_path.read_text(encoding="utf-8"))
+    except (OSError, ValueError):
+        return None
+    if isinstance(data, dict) and isinstance(data.get("words"), list):
+        if "speakers" not in data:
+            data["speakers"] = build_speakers(data.get("segments", []))
+        return data
+    return None

admin/api/subtitles.py

@@ -0,0 +1,240 @@
+"""Legendas: dinâmicas, comuns, SRT e as configurações de estilo.
+
+Extraído de models_api.py — a tabela de comandos segue lá.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import sys
+from pathlib import Path
+
+# code/ is the package root for fcpxml and server modules.
+_CODE_DIR = str(Path(__file__).resolve().parent.parent / "code")
+if _CODE_DIR not in sys.path:
+    sys.path.insert(0, _CODE_DIR)
+
+from fcpxml.media_intel import media_src_to_path
+from fcpxml.model_manager import (
+    load_dynamic_subtitle_config,
+    load_plain_subtitle_config,
+    save_dynamic_subtitle_config,
+    save_plain_subtitle_config,
+)
+from fcpxml.writer import FCPXMLModifier
+
+from . import shared
+from .shared import (
+    _derived_output,
+    _emit_no_change_or_error,
+    _transcript_json_path,
+)
+from .shared import _load_cached_transcript  # noqa: E402
+
+
+def cmd_generate_dynamic_subtitles(args: dict) -> int:
+    """Generate word-by-word ("karaoke") caption compound clips, one per line,
+    using each media's cached transcript."""
+    path = str(args.get("path", ""))
+    if not path or not Path(path).exists():
+        shared.emit({"ok": False, "error": "Arquivo de projeto não encontrado."})
+        return 1
+    try:
+        from server import handle_generate_dynamic_subtitles
+
+        output = _derived_output(path, "_dynamic_subtitles", args)
+        contents = asyncio.run(
+            handle_generate_dynamic_subtitles({**args, "filepath": path, "output_path": output})
+        )
+        message = "\n".join(getattr(content, "text", str(content)) for content in contents)
+        if not Path(output).exists():
+            shared.emit({"ok": False, "error": message})
+            return 1
+        shared.emit({"ok": True, "path": output, "message": message})
+        return 0
+    except Exception as exc:
+        shared.emit({"ok": False, "error": str(exc)})
+        return 1
+
+def cmd_generate_plain_subtitles(args: dict) -> int:
+    """Generate simple static editable subtitle title clips."""
+    path = str(args.get("path", ""))
+    if not path or not Path(path).exists():
+        shared.emit({"ok": False, "error": "Arquivo de projeto não encontrado."})
+        return 1
+    try:
+        from server import handle_generate_plain_subtitles
+
+        output = _derived_output(path, "_plain_subtitles", args)
+        contents = asyncio.run(
+            handle_generate_plain_subtitles({**args, "filepath": path, "output_path": output})
+        )
+        message = "\n".join(getattr(content, "text", str(content)) for content in contents)
+        if not Path(output).exists():
+            return _emit_no_change_or_error(path, message)
+        shared.emit({"ok": True, "path": output, "message": message})
+        return 0
+    except Exception as exc:
+        shared.emit({"ok": False, "error": str(exc)})
+        return 1
+
+def cmd_export_srt(args: dict) -> int:
+    """Write a captions .srt synced to the edited timeline.
+
+    Each transcribed segment is mapped from its SOURCE-media timestamp to its
+    real TIMELINE position (``clip_offset + (seg_start - clip_source_start)``),
+    so captions only cover the frames that remain after cuts/silence removal —
+    not the whole source file. One .srt is produced per media, in timeline order.
+    """
+    path = str(args.get("path", ""))
+    output_dir = str(args.get("output_dir", "")).strip()
+    if not path or not Path(path).exists():
+        shared.emit({"ok": False, "error": "Arquivo de projeto não encontrado."})
+        return 1
+    try:
+        modifier = FCPXMLModifier(path)
+    except Exception as exc:
+        shared.emit({"ok": False, "error": f"Erro ao ler o projeto: {exc}"})
+        return 1
+
+    # Group spine clips by media so each transcript is loaded once.
+    by_media: dict[str, list] = {}
+    for _, el in modifier._iter_spine_clips():
+        src = modifier.resources.get(el.get("ref", ""), {}).get("src", "")
+        mp = media_src_to_path(src)
+        if not mp or not Path(mp).is_file():
+            continue
+        by_media.setdefault(mp, []).append(el)
+
+    # Never emit a caption past the end of the project — Final Cut rejects an
+    # SRT whose last cue overruns the timeline ("subtitle extends beyond project
+    # duration"). Clamp every mapped cue end to this ceiling.
+    timeline_total = modifier._timeline_duration().to_seconds()
+
+    srt_paths: list[str] = []
+    for mp, clips in by_media.items():
+        cached = _load_cached_transcript(_transcript_json_path(mp, output_dir))
+        if cached is None:
+            continue
+        segments = cached.get("segments") or []
+        if not segments:
+            continue
+
+        rows: list[tuple[float, float, str, int]] = []
+        for el in clips:
+            clip_source_start = modifier.source_file_start(el).to_seconds()
+            clip_duration = modifier._parse_time(el.get("duration", "0s")).to_seconds()
+            clip_offset = modifier._parse_time(el.get("offset", "0s")).to_seconds()
+            window_end = clip_source_start + clip_duration
+            for seg_index, seg in enumerate(segments):
+                seg_start = float(seg.get("start", 0.0))
+                seg_end = float(seg.get("end", seg_start))
+                text = seg.get("text", "").strip()
+                if not text or seg_end <= seg_start:
+                    continue
+                # Intersect the complete source segment with this kept clip.
+                # Testing only seg_start loses speech whose first words fall in
+                # a removed range; interval intersection preserves the part
+                # that remains and avoids duplicating a segment wholesale.
+                source_start = max(seg_start, clip_source_start)
+                source_end = min(seg_end, window_end)
+                if source_end <= source_start:
+                    continue
+                tl_start = clip_offset + (source_start - clip_source_start)
+                tl_end = clip_offset + (source_end - clip_source_start)
+                tl_start = max(0.0, min(tl_start, timeline_total))
+                tl_end = max(0.0, min(tl_end, timeline_total))
+                if tl_end > tl_start:
+                    rows.append((tl_start, tl_end, text, seg_index))
+
+        if not rows:
+            continue
+        rows.sort(key=lambda r: (r[0], r[1], r[3]))
+        # Merge only pieces from the same original Whisper segment when their
+        # mapped intervals touch. Never merge unrelated speech or invent time.
+        merged: list[tuple[float, float, str, int]] = []
+        for row in rows:
+            if merged and row[3] == merged[-1][3] and row[0] <= merged[-1][1] + 0.001:
+                prev = merged[-1]
+                merged[-1] = (prev[0], max(prev[1], row[1]), prev[2], prev[3])
+            else:
+                merged.append(row)
+
+        blocks = []
+        for index, (s, e, text, _) in enumerate(merged, 1):
+            start_stamp = srt_stamp(s)
+            end_stamp = srt_stamp(e)
+            # Millisecond SRT precision can collapse a sub-millisecond span;
+            # omit it rather than emit an invalid zero-duration cue.
+            if start_stamp == end_stamp:
+                continue
+            blocks.append(f"{index}\n{start_stamp} --> {end_stamp}\n{text}\n")
+        if not blocks:
+            continue
+
+        out = (
+            Path(output_dir).expanduser() / f"{Path(mp).stem}_captions.srt"
+            if output_dir
+            else Path(mp).with_name(Path(mp).stem + "_captions.srt")
+        )
+        if output_dir:
+            out.parent.mkdir(parents=True, exist_ok=True)
+        try:
+            out.write_text("\n".join(blocks), encoding="utf-8")
+        except OSError as exc:
+            shared.emit({"ok": False, "error": f"Não foi possível salvar a legenda: {exc}"})
+            return 1
+        srt_paths.append(str(out))
+
+    if not srt_paths:
+        shared.emit({"ok": False, "error": "Nenhuma transcrição encontrada. Transcreva o projeto primeiro."})
+        return 1
+
+    shared.emit({"ok": True, "paths": srt_paths, "message": f"{len(srt_paths)} legenda(s) .srt sincronizada(s) com o corte."})
+    return 0
+
+def srt_stamp(seconds: float) -> str:
+    """Format float seconds as ``HH:MM:SS,mmm`` (SRT uses a comma).
+
+    Uses ``floor`` (not ``round``) so a timestamp never rounds up past a frame
+    boundary — an SRT cue ending on the last frame must not overrun the
+    project duration, or Final Cut flags it as extending beyond the project.
+    """
+    ms = int((seconds if seconds > 0 else 0.0) * 1000)
+    h, rem = divmod(ms, 3600000)
+    m, rem = divmod(rem, 60000)
+    s, ms = divmod(rem, 1000)
+    return f"{h:02d}:{m:02d}:{s:02d},{ms:03d}"
+
+def cmd_dynamic_subtitle_config(args: dict) -> int:
+    """Read the persisted dynamic-subtitle style (font, size, color, layout)."""
+    shared.emit({"ok": True, **load_dynamic_subtitle_config()})
+    return 0
+
+def cmd_set_dynamic_subtitle_config(args: dict) -> int:
+    """Persist dynamic-subtitle style fields. Only the given fields change."""
+    config = save_dynamic_subtitle_config(**{
+        k: args.get(k) for k in (
+            "band_height", "block_center_y", "line_gap", "font", "font_size",
+            "emphasis_font", "emphasis_face", "emphasis_size",
+            "active_color", "emphasis_color", "text_scale",
+        )
+    })
+    shared.emit({"ok": True, **config})
+    return 0
+
+def cmd_plain_subtitle_config(args: dict) -> int:
+    """Read the persisted simple subtitle style."""
+    shared.emit({"ok": True, **load_plain_subtitle_config()})
+    return 0
+
+def cmd_set_plain_subtitle_config(args: dict) -> int:
+    """Persist simple subtitle style fields. Only the given fields change."""
+    config = save_plain_subtitle_config(**{
+        k: args.get(k) for k in (
+            "font", "font_size", "font_color", "max_words",
+            "position_y", "uppercase", "keep_punctuation", "text_scale",
+        )
+    })
+    shared.emit({"ok": True, **config})
+    return 0

admin/api/transcription.py

@@ -0,0 +1,191 @@
+"""Transcrição e locutores.
+
+Extraído de models_api.py — a tabela de comandos segue lá.
+"""
+
+from __future__ import annotations
+
+import json
+import sys
+from pathlib import Path
+
+# code/ is the package root for fcpxml and server modules.
+_CODE_DIR = str(Path(__file__).resolve().parent.parent / "code")
+if _CODE_DIR not in sys.path:
+    sys.path.insert(0, _CODE_DIR)
+
+from fcpxml.diarize import (
+    assign_speakers,
+    build_speakers,
+    diarization_capability,
+    diarize,
+)
+from fcpxml.media_intel import media_src_to_path
+from fcpxml.model_manager import (
+    is_model_downloaded,
+    load_hf_token,
+    load_num_speakers,
+    load_selected_model,
+    load_transcript_language,
+    save_hf_token,
+    save_num_speakers,
+)
+from fcpxml.parser import parse_fcpxml
+from fcpxml.transcribe import transcribe
+
+from . import shared
+from .shared import (
+    _save_json_atomic,
+    _transcript_json_path,
+)
+from .shared import _load_cached_transcript  # noqa: E402
+
+
+def cmd_transcribe(args: dict) -> int:
+    proj_path = str(args.get("path", ""))
+    output_dir = str(args.get("output_dir", "")).strip()
+    # Honra o modelo selecionado no programa quando nenhum é passado.
+    model = str(args.get("model", "") or load_selected_model() or "")
+    language = args.get("language")
+    if language is None:
+        language = load_transcript_language()
+    if language == "auto":
+        language = None
+    if not proj_path:
+        shared.emit({"type": "error", "message": "Nenhum projeto selecionado."})
+        return 1
+    if not output_dir:
+        shared.emit({"type": "error", "message": "Selecione a pasta do projeto antes de transcrever."})
+        return 1
+    if not model or not is_model_downloaded(model):
+        shared.emit(
+            {
+                "type": "error",
+                "message": "Nenhum modelo de transcrição instalado. Baixe e selecione um modelo na aba Modelos.",
+            }
+        )
+        return 1
+
+    token = str(args.get("hf_token") or load_hf_token() or "")
+    if args.get("num_speakers") is not None:
+        num_speakers = str(args.get("num_speakers"))
+    else:
+        num_speakers = load_num_speakers()
+
+    # Load project.
+    try:
+        proj = parse_fcpxml(proj_path)
+    except Exception as exc:
+        shared.emit({"type": "error", "message": f"Erro ao ler o projeto: {exc}"})
+        return 1
+    tl = proj.primary_timeline or (proj.timelines[0] if proj.timelines else None)
+    media_paths: list[str] = []
+    if tl is not None:
+        for clip in getattr(tl, "clips", []):
+            mp = media_src_to_path(clip.media_path or "")
+            if mp and Path(mp).is_file() and mp not in media_paths:
+                media_paths.append(mp)
+    if not media_paths:
+        shared.emit({"type": "error", "message": "Nenhum arquivo de mídia acessível encontrado."})
+        return 1
+
+    total = len(media_paths)
+    results: list[dict] = []
+    for i, mp in enumerate(media_paths, 1):
+        stage = f"Transcrevendo {Path(mp).name} ({i}/{total})…"
+        shared.emit({"type": "progress", "fraction": (i - 1) / total, "stage": stage})
+        json_path = _transcript_json_path(mp, output_dir)
+        cached = _load_cached_transcript(json_path)
+        if cached is not None:
+            shared.emit({"type": "progress", "fraction": i / total, "stage": stage})
+            results.append(_result_row(mp, cached))
+            continue
+
+        def _on_progress(file_fraction: float, _i: int = i, _stage: str = stage) -> None:
+            # Blend this file's own progress into the overall fraction so a
+            # single-media project doesn't jump straight to 100% before the
+            # actual (slow) decoding work has even started.
+            overall = (_i - 1 + file_fraction) / total
+            shared.emit({"type": "progress", "fraction": overall, "stage": _stage})
+
+        data = transcribe(mp, model_size=model, language=language, progress_cb=_on_progress)
+        if data is None:
+            shared.emit({"type": "error", "message": f"Não foi possível transcrever: {Path(mp).name}"})
+            return 1
+
+        # Diarização opcional (necessita token HF): assina speaker por segmento/palavra.
+        if token:
+            tracks = diarize(mp, token, num_speakers)
+            segments, words = assign_speakers(
+                data.get("segments", []), data.get("words", []), tracks
+            )
+            data = {**data, "segments": segments, "words": words}
+        data["speakers"] = build_speakers(data.get("segments", []))
+
+        payload = {
+            "schema_version": "1.0",
+            "source": Path(mp).name,
+            "model": model,
+            **data,
+        }
+        try:
+            _save_json_atomic(json_path, payload)
+        except (OSError, RuntimeError, ValueError) as exc:
+            shared.emit({"type": "error", "message": f"Não foi possível salvar o JSON: {exc}"})
+            return 1
+        results.append(_result_row(mp, data))
+
+    shared.emit({"type": "result", "transcripts": results})
+    return 0
+
+
+def cmd_rename_speakers(args: dict) -> int:
+    """Apply real names to speakers already saved in a transcript JSON."""
+    json_path = Path(str(args.get("path", "")))
+    names = args.get("speakers") or {}
+    if not json_path.is_file():
+        shared.emit({"type": "error", "message": "Transcrição não encontrada."})
+        return 1
+    try:
+        data = json.loads(json_path.read_text(encoding="utf-8"))
+    except (OSError, ValueError) as exc:
+        shared.emit({"type": "error", "message": f"Não foi possível ler o JSON: {exc}"})
+        return 1
+    mapping = {str(sid): str(name).strip() for sid, name in (names or {}).items()}
+    for sp in data.get("speakers", []):
+        sid = str(sp.get("id", ""))
+        if mapping.get(sid):
+            sp["name"] = mapping[sid]
+    try:
+        _save_json_atomic(json_path, data)
+    except (OSError, RuntimeError, ValueError) as exc:
+        shared.emit({"type": "error", "message": f"Não foi possível salvar: {exc}"})
+        return 1
+    shared.emit({"ok": True, "speakers": data.get("speakers", [])})
+    return 0
+
+def cmd_set_diarization(args: dict) -> int:
+    """Persist the HuggingFace token and expected speaker count for diarization."""
+    token = args.get("token")
+    num = args.get("num_speakers")
+    if token is not None:
+        save_hf_token(str(token))
+    if num is not None:
+        save_num_speakers(str(num))
+    ok, msg = diarization_capability(load_hf_token())
+    shared.emit({"ok": True, "diarization": ok, "diarization_message": msg, "num_speakers": load_num_speakers()})
+    return 0
+
+def _result_row(mp: str, data: dict) -> dict:
+    words = data.get("words", [])
+    preview = (data.get("text", "") or "")[:160]
+    speakers = data.get("speakers") or []
+    return {
+        "media": Path(mp).name,
+        "language": data.get("language", "?"),
+        "words": len(words),
+        "duration": float(data.get("duration", 0.0)),
+        "preview": preview,
+        "saved": str(_transcript_json_path(mp)),
+        "speakers": [s.get("name", s.get("id", "")) for s in speakers],
+    }

admin/api/voice.py

@@ -0,0 +1,212 @@
+"""Análise de voz e aplicação das decisões de edição.
+
+Extraído de models_api.py — a tabela de comandos segue lá.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import json
+import sys
+from pathlib import Path
+
+# code/ is the package root for fcpxml and server modules.
+_CODE_DIR = str(Path(__file__).resolve().parent.parent / "code")
+if _CODE_DIR not in sys.path:
+    sys.path.insert(0, _CODE_DIR)
+
+from fcpxml.model_manager import (
+    load_hf_token,
+    load_num_speakers,
+    load_selected_model,
+    load_transcript_language,
+    load_voice_analysis_config,
+    save_voice_analysis_config,
+)
+
+from . import shared
+from .shared import (
+    _load_cached_voice_timeline,
+    _project_media_paths,
+    _transcript_json_path,
+    _voice_timeline_json_path,
+)
+from .shared import _load_cached_transcript  # noqa: E402
+
+
+def cmd_analyze_voice(args: dict) -> int:
+    """Build the voice timeline (transcript+diarization+acoustics -> emphasis)
+    for every unique source media in the project, so `refine_voice_timeline`
+    and friends have something to read without ever reopening the audio.
+
+    Analysis only — writes _voice_timeline.json next to each media, doesn't
+    touch the project XML. `path` passes through unchanged so it composes
+    with the other batch steps (silence removal, captions) regardless of
+    where in the list it runs.
+    """
+    path = str(args.get("path", ""))
+    if not path or not Path(path).exists():
+        shared.emit({"ok": False, "error": "Arquivo de projeto não encontrado."})
+        return 1
+
+    model = str(args.get("model", "") or load_selected_model() or "")
+    language = args.get("language")
+    if language is None:
+        language = load_transcript_language()
+    if language == "auto":
+        language = None
+    token = str(args.get("hf_token") or load_hf_token() or "")
+    num_speakers = str(args.get("num_speakers") or load_num_speakers() or "")
+
+    try:
+        media_paths = _project_media_paths(path)
+    except Exception as exc:
+        shared.emit({"ok": False, "error": f"Erro ao ler o projeto: {exc}"})
+        return 1
+    if not media_paths:
+        shared.emit({"ok": False, "error": "Nenhum arquivo de mídia acessível encontrado."})
+        return 1
+
+    from server import handle_build_voice_timeline
+
+    messages: list[str] = []
+    output_dir = str(args.get("output_dir") or "").strip()
+    existing: list[Path] = []
+    for mp in media_paths:
+        timeline_path = _voice_timeline_json_path(mp, output_dir)
+        if _load_cached_voice_timeline(timeline_path, mp) is not None:
+            existing.append(timeline_path)
+    if existing and len(existing) == len(media_paths) and not bool(args.get("force_reprocess", False)):
+        message = "# Voice Timeline Cache\n\n"
+        message += "Reaproveitando análise de voz existente. Nada foi reprocessado.\n\n"
+        for timeline_path in existing:
+            message += f"- **Timeline JSON**: {timeline_path}\n"
+        shared.emit({
+            "ok": True,
+            "path": path,
+            "reused": True,
+            "timelines": [str(p) for p in existing],
+            "message": message,
+        })
+        return 0
+
+    for mp in media_paths:
+        transcript_path = _transcript_json_path(mp, output_dir)
+        reused_prefix = ""
+        if _load_cached_transcript(transcript_path) is not None:
+            reused_prefix = f"# Cache\n\nReaproveitando transcrição existente: `{transcript_path}`\n\n"
+        try:
+            contents = asyncio.run(handle_build_voice_timeline({
+                "media_path": mp, "model": model, "language": language,
+                "hf_token": token, "num_speakers": num_speakers,
+                "output_dir": output_dir,
+            }))
+        except Exception as exc:
+            shared.emit({"ok": False, "error": f"Falha analisando {Path(mp).name}: {exc}"})
+            return 1
+        messages.append(reused_prefix + "\n".join(getattr(c, "text", str(c)) for c in contents))
+
+    shared.emit({"ok": True, "path": path, "message": "\n\n---\n\n".join(messages)})
+    return 0
+
+def cmd_acoustics_capability(args: dict) -> int:
+    """Whether librosa (pitch/energy extraction) is installed in this venv.
+
+    Surfaces `features_capability()` — previously computed but never
+    exposed to the app, so `layers.acoustics: false` in a voice timeline
+    had no explanation the user could act on.
+    """
+    from fcpxml.voice_features import features_capability
+    ok, msg = features_capability()
+    shared.emit({"ok": True, "available": ok, "message": msg})
+    return 0
+
+def cmd_voice_analysis(args: dict) -> int:
+    """Read the persisted voice-analysis settings (energy/emphasis/emotion)."""
+    config = load_voice_analysis_config()
+    shared.emit({"ok": True, **config, "emphasis_threshold": config["emphasis_floor"]})
+    return 0
+
+def cmd_set_voice_analysis(args: dict) -> int:
+    """Persist voice-analysis settings. Only the given fields change."""
+    weights = args.get("emphasis_weights")
+    config = save_voice_analysis_config(
+        energy_threshold=args.get("energy_threshold"),
+        emphasis_weights=weights if isinstance(weights, dict) else None,
+        emphasis_floor=args.get("emphasis_threshold"),
+        emotion_enabled=args.get("emotion_enabled"),
+        emotion_sensitivity=args.get("emotion_sensitivity"),
+        zoom_scale=args.get("zoom_scale"),
+        zoom_mode=args.get("zoom_mode"),
+        zoom_ease_in=args.get("zoom_ease_in"),
+        zoom_ease_out=args.get("zoom_ease_out"),
+    )
+    shared.emit({"ok": True, **config})
+    return 0
+
+def cmd_apply_voice_actions(args: dict) -> int:
+    """Apply a decision list (cuts/zooms/texts/markers) to the project XML.
+
+    The list is produced by a model reading the _voice_timeline.json — this
+    is the step that turns those decisions into an edit, and the one the
+    batch chain was missing: without it the app could measure the voice and
+    caption the result, but never cut by it.
+
+    `actions_path` points at the JSON; either a bare list or the
+    ``{"actions": [...]}`` wrapper the skill emits is accepted. Times stay in
+    ORIGINAL source seconds — the handler resolves cuts first and shifts
+    everything else itself.
+    """
+    path = str(args.get("path", ""))
+    if not path or not Path(path).exists():
+        shared.emit({"ok": False, "error": "Arquivo de projeto não encontrado."})
+        return 1
+
+    actions = args.get("actions")
+    if actions is None:
+        actions_path = str(args.get("actions_path", ""))
+        if not actions_path or not Path(actions_path).exists():
+            shared.emit({"ok": False, "error": "Arquivo de decisões (JSON) não encontrado."})
+            return 1
+        try:
+            with open(actions_path, encoding="utf-8") as fh:
+                loaded = json.load(fh)
+        except (OSError, ValueError) as exc:
+            shared.emit({"ok": False, "error": f"Erro ao ler as decisões: {exc}"})
+            return 1
+        actions = loaded.get("actions") if isinstance(loaded, dict) else loaded
+
+    # The documented output format is {"source": ..., "actions": [...]} —
+    # callers passing that whole object inline (e.g. the wizard pasting the
+    # skill's JSON verbatim) need the same unwrap the actions_path branch
+    # above already does, or a well-formed payload gets rejected as
+    # "malformed" for having one extra layer of nesting.
+    if isinstance(actions, dict):
+        actions = actions.get("actions")
+
+    if not isinstance(actions, list) or not actions:
+        shared.emit({"ok": False, "error": "A lista de decisões está vazia ou malformada."})
+        return 1
+
+    from server import handle_apply_voice_actions
+
+    try:
+        contents = asyncio.run(handle_apply_voice_actions({
+            "filepath": path,
+            "actions": actions,
+            "output_dir": args.get("output_dir"),
+        }))
+    except Exception as exc:
+        shared.emit({"ok": False, "error": f"Falha ao aplicar as decisões: {exc}"})
+        return 1
+
+    message = "\n".join(getattr(c, "text", str(c)) for c in contents)
+    # The handler reports dropped/rejected actions individually; hand the
+    # whole report back so the app can surface them instead of only the count.
+    out_path = path
+    for line in message.splitlines():
+        if line.startswith("- **Saved to**:"):
+            out_path = line.split("`")[1] if "`" in line else path
+            break
+    shared.emit({"ok": True, "path": out_path, "message": message})
+    return 0

admin/api/zoom.py

@@ -0,0 +1,114 @@
+"""Zoom (punch-in): por janela, por clipe e por trecho da transcrição.
+
+Extraído de models_api.py — a tabela de comandos segue lá.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import sys
+from pathlib import Path
+
+# code/ is the package root for fcpxml and server modules.
+_CODE_DIR = str(Path(__file__).resolve().parent.parent / "code")
+if _CODE_DIR not in sys.path:
+    sys.path.insert(0, _CODE_DIR)
+
+
+from . import shared
+from .shared import (
+    _derived_output,
+    _transcript_json_path,
+)
+from .shared import _load_cached_transcript  # noqa: E402
+
+
+def cmd_add_zoom(args: dict) -> int:
+    """Add an ease-in/ease-out punch-in zoom to one clip."""
+    path = str(args.get("path", ""))
+    clip_id = str(args.get("clip_id", "")).strip()
+    if not path or not Path(path).exists():
+        shared.emit({"ok": False, "error": "Arquivo de projeto não encontrado."})
+        return 1
+    if not clip_id:
+        shared.emit({"ok": False, "error": "Informe o nome do clipe."})
+        return 1
+    try:
+        from server import handle_add_zoom
+
+        output = _derived_output(path, "_zoom", args)
+        contents = asyncio.run(handle_add_zoom({**args, "filepath": path, "output_path": output}))
+        message = "\n".join(getattr(content, "text", str(content)) for content in contents)
+        if not Path(output).exists():
+            shared.emit({"ok": False, "error": message})
+            return 1
+        shared.emit({"ok": True, "path": output, "message": message})
+        return 0
+    except Exception as exc:
+        shared.emit({"ok": False, "error": str(exc)})
+        return 1
+
+def cmd_zoom_clips(args: dict) -> int:
+    """Return timeline clips with enough identity for the zoom picker."""
+    path = Path(str(args.get("path", "")))
+    output_dir = str(args.get("output_dir", "")).strip()
+    if not path.exists():
+        shared.emit({"ok": False, "error": "Arquivo de projeto não encontrado."})
+        return 1
+    try:
+        from server import _require_timeline
+
+        _, timeline = _require_timeline(str(path))
+        clips = []
+        for index, clip in enumerate(timeline.clips):
+            media = clip.media_path or ""
+            cached = _load_cached_transcript(_transcript_json_path(media, output_dir)) if media else None
+            clips.append({
+                "id": f"{index}:{clip.start.seconds:.6f}",
+                "index": index,
+                "name": clip.name,
+                "start": clip.start.seconds,
+                "duration": clip.duration_seconds,
+                "media": Path(media).name if media else "",
+                "preview": ((cached or {}).get("text", "") or "")[:180],
+                "has_transcript": cached is not None,
+            })
+        shared.emit({"ok": True, "clips": clips})
+        return 0
+    except Exception as exc:
+        shared.emit({"ok": False, "error": str(exc)})
+        return 1
+
+def cmd_zoom_segments(args: dict) -> int:
+    """Return sentence/word ranges for one timeline clip."""
+    path = Path(str(args.get("path", "")))
+    output_dir = str(args.get("output_dir", "")).strip()
+    try:
+        from server import _require_timeline
+
+        _, timeline = _require_timeline(str(path))
+        index = int(args.get("index", -1))
+        if index < 0 or index >= len(timeline.clips):
+            raise ValueError("Clipe selecionado não existe.")
+        clip = timeline.clips[index]
+        if not clip.media_path:
+            raise ValueError("Este clipe não possui mídia associada.")
+        data = _load_cached_transcript(_transcript_json_path(clip.media_path, output_dir))
+        if data is None:
+            shared.emit({"ok": True, "segments": [], "message": "Transcreva este clipe primeiro."})
+            return 0
+        segments = []
+        for number, segment in enumerate(data.get("segments", [])):
+            text = str(segment.get("text", "")).strip()
+            if text:
+                segments.append({
+                    "id": number,
+                    "start": float(segment.get("start", 0)),
+                    "end": float(segment.get("end", 0)),
+                    "text": text,
+                })
+        shared.emit({"ok": True, "segments": segments})
+        return 0
+    except Exception as exc:
+        shared.emit({"ok": False, "error": str(exc)})
+        return 1

admin/models_gui.py

@@ -20,7 +20,6 @@ import subprocess
 import sys
 import threading
 from pathlib import Path
-from typing import Optional
 
 import flet as ft
 
@@ -29,8 +28,8 @@ _CODE_DIR = str(Path(__file__).resolve().parent.parent / "code")
 if _CODE_DIR not in sys.path:
     sys.path.insert(0, _CODE_DIR)
 
-from fcpxml.media_intel import media_src_to_path  # noqa: E402
-from fcpxml.model_manager import (  # noqa: E402
+from fcpxml.media_intel import media_src_to_path
+from fcpxml.model_manager import (
     download_model,
     get_models_dir,
     is_model_downloaded,
@@ -41,8 +40,8 @@ from fcpxml.model_manager import (  # noqa: E402
     save_models_dir,
     save_selected_model,
 )
-from fcpxml.parser import parse_fcpxml  # noqa: E402
-from fcpxml.transcribe import transcribe  # noqa: E402
+from fcpxml.parser import parse_fcpxml
+from fcpxml.transcribe import transcribe
 
 logger = logging.getLogger(__name__)
 
@@ -101,9 +100,9 @@ class ModelManagerApp:
     def __init__(self, page: ft.Page) -> None:
         self.page = page
         self.selected = load_selected_model()
-        self.downloading: Optional[str] = None
+        self.downloading: str | None = None
         self._cancel_events: dict[str, threading.Event] = {}
-        self._picker: Optional[ft.FilePicker] = None
+        self._picker: ft.FilePicker | None = None
 
     # ── helpers ────────────────────────────────────────────────────────────
 
@@ -121,7 +120,7 @@ class ModelManagerApp:
         self._picker = ft.FilePicker()
         self._picker.on_result = self._on_file_picked
         self.page.overlay.append(self._picker)
-        self._pending_target: Optional[dict] = None
+        self._pending_target: dict | None = None
 
     def _on_file_picked(self, e) -> None:
         if self._pending_target == "project":

code/Engine/docs/05_EXPERIENCIAS.md

@@ -1255,6 +1255,29 @@ o outro; percentil entrega um punhado útil nos dois casos.
 
 ---
 
+## 24 — 2026-08-19 — Teste existia, mas estava fora da suíte
+
+- **Sintoma:** `admin/test_models_api.py` (13 testes) nunca rodava. Não
+  falhava — simplesmente não era coletado, então `models_api.py` figurava
+  como "coberto" sem que uma única asserção fosse executada em nenhum
+  commit.
+- **Causa raiz:** `testpaths = ["tests"]` no `pyproject.toml`, com o pytest
+  rodando de `code/`. O arquivo morava em `admin/`, fora do alcance. Rodá-lo
+  à mão também falhava (`ModuleNotFoundError: admin`), porque a raiz do
+  repositório não entra no `sys.path` — ou seja, o único jeito de executá-lo
+  exigia saber de antemão que ele existia e como.
+- **Solução adotada:** movido para `code/tests/test_models_api.py`, com o
+  insert da raiz do repositório no `sys.path` ao lado do import que precisa
+  dele. Passou a rodar no gate: 1441 → 1454 testes.
+- **Aprendizado:** um teste fora de `testpaths` é pior que teste nenhum — ele
+  dá a sensação de rede sem ser rede. Ao mover ou criar teste fora da pasta
+  padrão, confirme que a contagem total subiu; se não subiu, ele não está
+  rodando. Vale também para o lint: `admin/` ainda não é coberto pelo
+  `run_after_fix.sh`, que roda só dentro de `code/`.
+- **Estado:** `resolvido`
+
+---
+
 ## Resumo rápido (índice)
 
 | # | Data | Problema | Estado |
@@ -1280,5 +1303,6 @@ o outro; percentil entrega um punhado útil nos dois casos.
 | 21 | 2026-08-19 | Teste ainda afirmava o default `zoom scale=1.3` removido do parser (agora vem do `zoom_scale` do usuário) | `resolvido` |
 | 22 | 2026-08-19 | `VideoPlayer` (AVKit) aborta em runtime no app compilado por `swiftc` — etapa 5 fechava o app; trocado por `AVPlayerLayer` | `resolvido` |
 | 23 | 2026-08-19 | Dividir `writer.py` em pacote quebrou `@patch('fcpxml.writer.subprocess')` — a suíte protege comportamento, não localização | `resolvido` |
+| 24 | 2026-08-19 | `admin/test_models_api.py` existia mas estava fora de `testpaths` — 13 testes que nunca rodaram | `resolvido` |
 
 > Mantenha o índice acima sempre sincronizado com as entradas mais recentes.

code/tests/test_models_api.py

@@ -1,12 +1,27 @@
-"""Tests for admin/models_api.py — the SwiftUI JSON bridge commands.
+"""Tests for the SwiftUI JSON bridge commands (admin/api/).
 
-Focused on the transcription-flow changes: atomic save, speaker renaming, and
-the "use the selected model" default plus model-availability guard.
+Focused on the transcription flow: atomic save, speaker renaming, and the
+"use the selected model" default plus the model-availability guard.
+
+Patch targets follow one rule: replace a name **in the module that uses it**.
+`shared.emit` is the exception that proves it — the command modules call it as
+`shared.emit(...)` rather than binding the name locally, precisely so that one
+patch keeps capturing the output of all of them.
 """
 
 import json
+import sys
+from pathlib import Path
 
-import admin.models_api as api
+# `admin/` lives outside `code/`, which is pytest's rootdir — without the repo
+# root on the path this module is invisible and the whole file silently stops
+# being collected. It spent its life outside `testpaths` for exactly that
+# reason, so keep the insert next to the import that needs it.
+_REPO_ROOT = Path(__file__).resolve().parent.parent.parent
+if str(_REPO_ROOT) not in sys.path:
+    sys.path.insert(0, str(_REPO_ROOT))
+
+from admin.api import models, shared, subtitles, transcription  # noqa: E402
 
 
 def _capture(monkeypatch):
@@ -15,13 +30,13 @@ def _capture(monkeypatch):
     def _emit(obj):
         captured.append(obj)
 
-    monkeypatch.setattr(api, "_emit", _emit)
+    monkeypatch.setattr(shared, "emit", _emit)
     return captured
 
 
 def test_save_json_atomic(tmp_path):
     p = tmp_path / "t.json"
-    api._save_json_atomic(p, {"a": [1, 2], "text": "olá"})
+    shared._save_json_atomic(p, {"a": [1, 2], "text": "olá"})
     assert p.exists()
     assert not (tmp_path / "t.json.tmp").exists()
     assert json.loads(p.read_text(encoding="utf-8"))["text"] == "olá"
@@ -41,7 +56,7 @@ def test_rename_speakers(tmp_path, monkeypatch):
         ),
         encoding="utf-8",
     )
-    assert api.cmd_rename_speakers({"path": str(p), "speakers": {"SPEAKER_01": "Erika"}}) == 0
+    assert transcription.cmd_rename_speakers({"path": str(p), "speakers": {"SPEAKER_01": "Erika"}}) == 0
     assert captured[0]["ok"] is True
     saved = json.loads(p.read_text(encoding="utf-8"))
     assert saved["speakers"][0]["name"] == "Speaker 1"
@@ -50,32 +65,32 @@ def test_rename_speakers(tmp_path, monkeypatch):
 
 def test_rename_speakers_missing_file(monkeypatch):
     captured = _capture(monkeypatch)
-    assert api.cmd_rename_speakers({"path": "/nonexistent/x.json"}) == 1
+    assert transcription.cmd_rename_speakers({"path": "/nonexistent/x.json"}) == 1
     assert captured[0]["type"] == "error"
 
 
 def test_transcribe_requires_output_dir(monkeypatch):
     captured = _capture(monkeypatch)
-    monkeypatch.setattr(api, "load_selected_model", lambda: "small")
-    monkeypatch.setattr(api, "is_model_downloaded", lambda m: True)
-    assert api.cmd_transcribe({"path": "/some/project.fcpxml"}) == 1
+    monkeypatch.setattr(transcription, "load_selected_model", lambda: "small")
+    monkeypatch.setattr(transcription, "is_model_downloaded", lambda m: True)
+    assert transcription.cmd_transcribe({"path": "/some/project.fcpxml"}) == 1
     assert captured[0]["type"] == "error"
     assert "pasta do projeto" in captured[0]["message"]
 
 
 def test_transcribe_requires_installed_model(monkeypatch, tmp_path):
     captured = _capture(monkeypatch)
-    monkeypatch.setattr(api, "load_selected_model", lambda: "")
-    monkeypatch.setattr(api, "is_model_downloaded", lambda m: False)
-    assert api.cmd_transcribe({"path": "/some/project.fcpxml", "output_dir": str(tmp_path)}) == 1
+    monkeypatch.setattr(transcription, "load_selected_model", lambda: "")
+    monkeypatch.setattr(transcription, "is_model_downloaded", lambda m: False)
+    assert transcription.cmd_transcribe({"path": "/some/project.fcpxml", "output_dir": str(tmp_path)}) == 1
     assert captured[0]["type"] == "error"
     assert "instalado" in captured[0]["message"]
 
 
 def test_transcribe_defaults_to_selected_model(monkeypatch, tmp_path):
     captured = _capture(monkeypatch)
-    monkeypatch.setattr(api, "load_selected_model", lambda: "small")
-    monkeypatch.setattr(api, "is_model_downloaded", lambda m: m == "small")
+    monkeypatch.setattr(transcription, "load_selected_model", lambda: "small")
+    monkeypatch.setattr(transcription, "is_model_downloaded", lambda m: m == "small")
 
     class FakeTL:
         clips = []
@@ -84,32 +99,32 @@ def test_transcribe_defaults_to_selected_model(monkeypatch, tmp_path):
         primary_timeline = None
         timelines = [FakeTL()]
 
-    monkeypatch.setattr(api, "parse_fcpxml", lambda p: FakeProject())
+    monkeypatch.setattr(transcription, "parse_fcpxml", lambda p: FakeProject())
     # No media accessible -> reaches the media-path check (past model validation).
-    assert api.cmd_transcribe({"path": "/some/project.fcpxml", "output_dir": str(tmp_path)}) == 1
+    assert transcription.cmd_transcribe({"path": "/some/project.fcpxml", "output_dir": str(tmp_path)}) == 1
     assert captured[0]["type"] == "error"
     assert "mídia" in captured[0]["message"]
 
 
 def test_set_language_persists(monkeypatch):
     captured = _capture(monkeypatch)
-    assert api.cmd_set_language({"language": "pt"}) == 0
+    assert models.cmd_set_language({"language": "pt"}) == 0
     assert captured[0]["ok"] is True
     assert captured[0]["language"] == "pt"
-    assert api.load_transcript_language() == "pt"
+    assert models.load_transcript_language() == "pt"
 
 
 def test_set_language_rejects_unknown(monkeypatch):
     captured = _capture(monkeypatch)
-    assert api.cmd_set_language({"language": "xx"}) == 1
+    assert models.cmd_set_language({"language": "xx"}) == 1
     assert captured[0]["ok"] is False
     assert "language" in captured[0]["error"]
 
 
 def test_transcribe_defaults_language_to_persisted(monkeypatch, tmp_path):
-    monkeypatch.setattr(api, "load_selected_model", lambda: "small")
-    monkeypatch.setattr(api, "is_model_downloaded", lambda m: m == "small")
-    monkeypatch.setattr(api, "load_transcript_language", lambda: "pt")
+    monkeypatch.setattr(transcription, "load_selected_model", lambda: "small")
+    monkeypatch.setattr(transcription, "is_model_downloaded", lambda m: m == "small")
+    monkeypatch.setattr(models, "load_transcript_language", lambda: "pt")
 
     media = tmp_path / "clip.mov"
     media.write_bytes(b"fake")
@@ -124,20 +139,21 @@ def test_transcribe_defaults_language_to_persisted(monkeypatch, tmp_path):
         primary_timeline = None
         timelines = [FakeTL()]
 
-    monkeypatch.setattr(api, "parse_fcpxml", lambda p: FakeProject())
-    monkeypatch.setattr(api, "media_src_to_path", lambda mp: str(media))
+    monkeypatch.setattr(transcription, "parse_fcpxml", lambda p: FakeProject())
+    monkeypatch.setattr(transcription, "media_src_to_path", lambda mp: str(media))
     called = {}
     monkeypatch.setattr(
-        api, "transcribe", lambda mp, model_size, language, **kw: called.update(lang=language)
+        transcription, "transcribe",
+        lambda mp, model_size, language, **kw: called.update(lang=language),
     )
-    assert api.cmd_transcribe({"path": "/some/project.fcpxml", "output_dir": str(tmp_path / "out")}) == 1
+    assert transcription.cmd_transcribe({"path": "/some/project.fcpxml", "output_dir": str(tmp_path / "out")}) == 1
     assert called["lang"] == "pt"
 
 
 def test_srt_stamp_format():
-    assert api.srt_stamp(0.0) == "00:00:00,000"
-    assert api.srt_stamp(1.5) == "00:00:01,500"
-    assert api.srt_stamp(3661.234) == "01:01:01,234"
+    assert subtitles.srt_stamp(0.0) == "00:00:00,000"
+    assert subtitles.srt_stamp(1.5) == "00:00:01,500"
+    assert subtitles.srt_stamp(3661.234) == "01:01:01,234"
 
 
 _FCPXML_SAMPLE = """<?xml version="1.0" encoding="UTF-8"?>
@@ -181,12 +197,12 @@ def test_cmd_export_srt_maps_to_edited_timeline(tmp_path, monkeypatch):
             {"start": 50.0, "end": 51.0, "text": "depois do corte"},
         ]
     }
-    tj = api._transcript_json_path(media)
+    tj = shared._transcript_json_path(media)
     tj.parent.mkdir(parents=True, exist_ok=True)
-    api._save_json_atomic(tj, transcript)
-    monkeypatch.setattr(api, "media_src_to_path", lambda src: str(media))
+    shared._save_json_atomic(tj, transcript)
+    monkeypatch.setattr(subtitles, "media_src_to_path", lambda src: str(media))
 
-    assert api.cmd_export_srt({"path": str(project)}) == 0
+    assert subtitles.cmd_export_srt({"path": str(project)}) == 0
     assert captured[0]["ok"] is True
     srt = tmp_path / "clip_captions.srt"
     assert srt.exists()
@@ -205,8 +221,8 @@ def test_cmd_export_srt_no_transcript(tmp_path, monkeypatch):
     project.write_text(_FCPXML_SAMPLE, encoding="utf-8")
     media = tmp_path / "clip.mp4"
     media.write_bytes(b"fake")
-    monkeypatch.setattr(api, "media_src_to_path", lambda src: str(media))
-    assert api.cmd_export_srt({"path": str(project)}) == 1
+    monkeypatch.setattr(subtitles, "media_src_to_path", lambda src: str(media))
+    assert subtitles.cmd_export_srt({"path": str(project)}) == 1
     assert captured[0]["ok"] is False
 
 
@@ -229,12 +245,12 @@ def test_cmd_export_srt_clamps_past_project_duration(tmp_path, monkeypatch):
             {"start": 12.0, "end": 30.0, "text": "longa fala"},
         ]
     }
-    tj = api._transcript_json_path(media)
+    tj = shared._transcript_json_path(media)
     tj.parent.mkdir(parents=True, exist_ok=True)
-    api._save_json_atomic(tj, transcript)
-    monkeypatch.setattr(api, "media_src_to_path", lambda src: str(media))
+    shared._save_json_atomic(tj, transcript)
+    monkeypatch.setattr(subtitles, "media_src_to_path", lambda src: str(media))
 
-    assert api.cmd_export_srt({"path": str(project)}) == 0
+    assert subtitles.cmd_export_srt({"path": str(project)}) == 0
     assert captured[0]["ok"] is True
     srt = tmp_path / "clip_captions.srt"
     text = srt.read_text(encoding="utf-8")