feat(r5): dictée — audio local (faster-whisper) → note → corpus (ADR-004 §5)

Écran Voix R5 (maquetté, jamais construit) implémenté sur décision du référent : open-source et local, pas d'API externe. - apps/ai : faster-whisper (CTranslate2, CPU, MIT) opt-in (AI_TRANSCRIPTION=off|locale|deterministe, défaut off) ; endpoint /internal/transcrire — l'audio ne survit JAMAIS à l'appel (fichier temporaire supprimé quoi qu'il arrive) ; indexer_bilans inclut désormais InterventionReport.note anonymisée (champ existant depuis R2, jamais eu d'écran jusqu'ici) ; 29 pytest. - Contrat (77 opérations) : POST /assistant/transcribe (multipart). - API : proxy multipart vers siop2-ai (WORK_ORDERS.edit — même droit que la saisie du bilan) ; 2 tests e2e (80 tests API au total). - Mobile : expo-audio + expo-file-system, bouton dicter/terminer sur l'écran de clôture, purge locale après transcription, « Joindre la description à l'OT » (corrige un bug latent : enfilerBilan ignorait silencieusement les mises à jour de note). - Docker : siop2-ai embarque le modèle Whisper au build (1,54→2,19 Go), construit et vérifié (transcription réelle en conteneur, non-root). - Vérifié réellement : transcription fidèle (voix de synthèse française) en direct, bout en bout via l'API, dans le conteneur Docker construit, et chaîne corpus complète (note → clôture → réindexation → recherche sémantique). - Base de dev locale réinitialisée avec accord explicite du référent (prisma migrate reset, bloqué par défaut pour un agent IA) après pollution par les tests manuels de la recette terrain précédente. Reste : test tactile sur iPhone physique (bouton dicter) — bloqué par une connexion USB qui ne s'est pas rétablie malgré câble/port/ redémarrage essayés à plusieurs reprises, reporté comme la recette Android. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-08-08 12:41:54 +00:00 · 2026-07-22 11:55:47 +01:00
parent 0730bf9dad
commit 59ed6f3952
28 changed files with 782 additions and 20 deletions
--- a/apps/ai/Dockerfile
+++ b/apps/ai/Dockerfile
@@ -8,29 +8,35 @@
 FROM ghcr.io/astral-sh/uv:python3.11-bookworm-slim AS builder
 WORKDIR /app
 ENV UV_LINK_MODE=copy \
-    FASTEMBED_CACHE_PATH=/opt/fastembed
+    FASTEMBED_CACHE_PATH=/opt/fastembed \
+    HF_HOME=/opt/whisper

 # Manifestes d'abord (cache de couche), puis le code. L'installation du projet
 # reste éditable (.pth → /app/src) : src est donc copié dans l'image finale.
 COPY pyproject.toml uv.lock ./
 RUN uv sync --frozen --no-install-project --no-dev \
-    --extra embeddings --extra generation
+    --extra embeddings --extra generation --extra transcription
 COPY src src
 RUN uv sync --frozen --no-dev \
-    --extra embeddings --extra generation
+    --extra embeddings --extra generation --extra transcription

-# Le modèle d'embeddings est EMBARQUÉ dans l'image : pas de téléchargement au
-# boot (démarrage prévisible, marche sans accès à Hugging Face en production).
+# Les modèles locaux (embeddings + dictée) sont EMBARQUÉS dans l'image : pas
+# de téléchargement au boot (démarrage prévisible, marche sans accès à
+# Hugging Face en production). La dictée reste opt-in (AI_TRANSCRIPTION=off
+# par défaut) — le modèle est prêt si elle est activée un jour, sans rebuild.
 RUN uv run python -c "from siop_ai.embeddings import EmbeddeurLocal; EmbeddeurLocal()"
+RUN uv run python -c "from siop_ai.transcription import TranscripteurLocal; TranscripteurLocal('small')"

 FROM python:3.11-slim-bookworm
 WORKDIR /app
 ENV PATH=/app/.venv/bin:$PATH \
-    FASTEMBED_CACHE_PATH=/opt/fastembed
+    FASTEMBED_CACHE_PATH=/opt/fastembed \
+    HF_HOME=/opt/whisper
 RUN useradd --system --create-home siop
 COPY --from=builder --chown=siop:siop /app/.venv /app/.venv
 COPY --from=builder --chown=siop:siop /app/src /app/src
 COPY --from=builder --chown=siop:siop /opt/fastembed /opt/fastembed
+COPY --from=builder --chown=siop:siop /opt/whisper /opt/whisper
 USER siop
 EXPOSE 8000
 HEALTHCHECK --interval=30s --timeout=5s --start-period=40s --retries=3 \
--- a/apps/ai/pyproject.toml
+++ b/apps/ai/pyproject.toml
@@ -10,6 +10,7 @@ dependencies = [
    "asyncpg>=0.30",
    "pypdf>=5.1",
    "minio>=7.2",
+    "python-multipart>=0.0.20",
 ]

 [project.optional-dependencies]
@@ -17,6 +18,9 @@ dependencies = [
 embeddings = ["fastembed>=0.4"]
 # Génération opt-in (ADR-004 §3) — absente des tests/CI (repli extractif).
 generation = ["anthropic>=0.75"]
+# Transcription opt-in (dictée R5, ADR-004 §5) — absente des tests/CI
+# (transcripteur déterministe). CTranslate2/CPU, licence MIT, local.
+transcription = ["faster-whisper>=1.1"]

 [dependency-groups]
 dev = [
--- a/apps/ai/src/siop_ai/app.py
+++ b/apps/ai/src/siop_ai/app.py
@@ -7,7 +7,7 @@ from contextlib import asynccontextmanager
 from dataclasses import asdict

 import asyncpg
-from fastapi import Depends, FastAPI, Header, HTTPException
+from fastapi import Depends, FastAPI, Header, HTTPException, UploadFile
 from pydantic import BaseModel, Field

 from .assistant import repondre, suggerer_bilan
@@ -16,6 +16,7 @@ from .embeddings import construire_embeddeur
 from .generation import construire_generateur
 from .ingestion import reindexer_tout
 from .recherche import chercher
+from .transcription import construire_transcripteur


@asynccontextmanager
@@ -26,6 +27,9 @@ async def cycle_de_vie(app: FastAPI):
    app.state.generateur = construire_generateur(
        reglages.ai_generation, reglages.ai_api_key, reglages.ai_model
    )
+    app.state.transcripteur = construire_transcripteur(
+        reglages.ai_transcription, reglages.ai_transcription_model
+    )
    app.state.pool = await asyncpg.create_pool(reglages.database_url, min_size=1, max_size=5)
    yield
    await app.state.pool.close()
@@ -50,6 +54,7 @@ async def sante() -> dict:
        "status": "ok",
        "service": "siop2-ai",
        "generation": reglages.ai_generation,  # « off » = extractif — jamais la clé
+        "transcription": reglages.ai_transcription,
    }


@@ -113,3 +118,16 @@ async def suggerer(corps: RequeteSuggestion) -> dict:
            seuil_confiance_forte=app.state.reglages.ai_seuil_confiance_forte,
        )
    return {"suggestions": [asdict(s) for s in suggestions]}
+
+
+@app.post("/internal/transcrire", dependencies=[Depends(verifier_jeton)])
+async def transcrire(fichier: UploadFile) -> dict:
+    """Dictée opt-in (R5 D5, loi 09-08) : l'audio ne persiste JAMAIS — un
+    fichier temporaire le temps de l'inférence, supprimé aussitôt (voir
+    transcription.py). 503 propre si AI_TRANSCRIPTION=off (défaut)."""
+    if app.state.transcripteur is None:
+        raise HTTPException(status_code=503, detail="Transcription non activée (AI_TRANSCRIPTION=off)")
+    audio = await fichier.read()
+    extension = (fichier.filename or "audio.m4a").rsplit(".", 1)[-1]
+    texte = app.state.transcripteur.transcrire(audio, extension)
+    return {"texte": texte}
--- a/apps/ai/src/siop_ai/config.py
+++ b/apps/ai/src/siop_ai/config.py
@@ -29,6 +29,10 @@ class Reglages(BaseSettings):
    ai_seuil_pertinence: float = 0.45
    ai_seuil_suggestion: float = 0.40
    ai_seuil_confiance_forte: float = 0.55
+    # Dictée opt-in (R5 D5, ADR-004 §5) : « off » (défaut — endpoint refuse
+    # proprement), « locale » (faster-whisper, CPU) ou « deterministe » (CI).
+    ai_transcription: str = "off"
+    ai_transcription_model: str = "small"  # tiny|base|small|medium|large-v3

    model_config = {"env_prefix": "", "case_sensitive": False}

@@ -43,4 +47,6 @@ def charger_reglages() -> Reglages:
        raise ValueError("AI_GENERATION doit valoir « off » ou « api »")
    if reglages.ai_generation == "api" and not reglages.ai_api_key:
        raise ValueError("AI_GENERATION=api exige AI_API_KEY (voir ADR-004 §3)")
+    if reglages.ai_transcription not in ("off", "locale", "deterministe"):
+        raise ValueError("AI_TRANSCRIPTION doit valoir « off », « locale » ou « deterministe »")
    return reglages
--- a/apps/ai/src/siop_ai/ingestion.py
+++ b/apps/ai/src/siop_ai/ingestion.py
@@ -119,7 +119,7 @@ async def indexer_bilans(
    await cnx.execute('DELETE FROM "RagChunk" WHERE "sourceType" = \'WORK_ORDER\'')
    bilans = await cnx.fetch(
        '''
-        SELECT wo.id, wo.reference, wo.title, wo."completedAt",
+        SELECT wo.id, wo.reference, wo.title, wo."completedAt", ir.note,
               a.reference AS asset_ref, a.brand, a.model,
               (SELECT json_object_agg(rv.field, rv.label)
                  FROM "InterventionReport" ir2
@@ -137,10 +137,13 @@ async def indexer_bilans(
    for bilan in bilans:
        champs = json.loads(bilan["bilan"]) if bilan["bilan"] else {}
        codes = " ; ".join(f"{champ} : {label}" for champ, label in champs.items())
+        # note (D5) : dictée ou saisie libre relue par l'humain — même pipeline
+        # d'anonymisation que le reste, aucun traitement à part.
+        note = f" Description libre : {bilan['note']}." if bilan["note"] else ""
        contenu = anonymiser(
            f"Intervention {bilan['reference']} — {bilan['title']}. "
            f"Appareil {bilan['asset_ref']} ({bilan['brand']} {bilan['model'] or ''}). "
-            f"Bilan codé : {codes}.",
+            f"Bilan codé : {codes}.{note}",
            noms,
        )
        quand = bilan["completedAt"].date().isoformat() if bilan["completedAt"] else "date inconnue"
--- a/apps/ai/src/siop_ai/transcription.py
+++ b/apps/ai/src/siop_ai/transcription.py
@@ -0,0 +1,54 @@
+"""Transcription audio (dictée R5, ADR-004 §5) : l'audio ne survit JAMAIS à
+cet appel — un fichier temporaire le temps de l'inférence, supprimé aussitôt,
+quoi qu'il arrive (D5, loi 09-08). Seul le texte transcrit est retourné ; la
+relecture humaine reste le seul contenu conservé, dans l'OT (D1).
+"""
+
+import os
+import tempfile
+from typing import Protocol
+
+
+class Transcripteur(Protocol):
+    def transcrire(self, audio: bytes, extension: str) -> str: ...
+
+
+class TranscripteurLocal:
+    """faster-whisper (CTranslate2, CPU, licence MIT) — chargé paresseusement,
+    jamais importé en test. Modèle et langue forcée en français : le mélange
+    français/darija du terrain reste un point de vigilance non calibré (pas
+    de mesure préalable demandée par le référent, 22/07/2026) — à revoir sur
+    échantillons réels si la qualité déçoit en recette."""
+
+    def __init__(self, modele: str) -> None:
+        from faster_whisper import WhisperModel  # import différé (dépendance optionnelle)
+
+        self._modele = WhisperModel(modele, device="cpu", compute_type="int8")
+
+    def transcrire(self, audio: bytes, extension: str) -> str:
+        fd, chemin = tempfile.mkstemp(suffix=f".{extension}")
+        try:
+            with os.fdopen(fd, "wb") as f:
+                f.write(audio)
+            segments, _ = self._modele.transcribe(chemin, language="fr", vad_filter=True)
+            return " ".join(segment.text.strip() for segment in segments).strip()
+        finally:
+            os.remove(chemin)  # D5 — l'audio ne doit JAMAIS survivre à l'appel
+
+
+class TranscripteurDeterministe:
+    """Tests/CI : pas de modèle, pas de dépendance audio réelle — renvoie un
+    texte stable dérivé de la taille du fichier (même interface)."""
+
+    def transcrire(self, audio: bytes, extension: str) -> str:
+        return f"transcription déterministe ({len(audio)} octets, .{extension})"
+
+
+def construire_transcripteur(mode: str, modele: str) -> Transcripteur | None:
+    """None si la dictée n'est pas activée (AI_TRANSCRIPTION=off, défaut) —
+    l'appelant doit alors refuser proprement (503), pas planter."""
+    if mode == "off":
+        return None
+    if mode == "deterministe":
+        return TranscripteurDeterministe()
+    return TranscripteurLocal(modele)
--- a/apps/ai/tests/test_app.py
+++ b/apps/ai/tests/test_app.py
@@ -16,6 +16,33 @@ def test_endpoints_internes_refuses_sans_jeton():
    client = _client_sans_db()
    assert client.post("/internal/reindex").status_code == 401
    assert client.post("/internal/search", json={"question": "couple de serrage ?"}).status_code == 401
+    assert client.post("/internal/transcrire", files={"fichier": ("a.m4a", b"x")}).status_code == 401
+
+
+def test_transcription_off_par_defaut_503():
+    """Dictée pas activée (AI_TRANSCRIPTION=off, défaut) : refus propre,
+    jamais un 500 — même contrat que le service IA éteint côté NestJS."""
+    reponse = _client_sans_db().post(
+        "/internal/transcrire",
+        files={"fichier": ("note.m4a", b"faux-audio")},
+        headers={"X-Service-Token": "dev-only-ai-token"},
+    )
+    assert reponse.status_code == 503
+
+
+def test_transcription_deterministe_retourne_un_texte():
+    from siop_ai.transcription import TranscripteurDeterministe
+
+    client = _client_sans_db()
+    app.state.transcripteur = TranscripteurDeterministe()
+    reponse = client.post(
+        "/internal/transcrire",
+        files={"fichier": ("note.m4a", b"faux-audio")},
+        headers={"X-Service-Token": "dev-only-ai-token"},
+    )
+    assert reponse.status_code == 200
+    assert "10 octets" in reponse.json()["texte"]
+    assert ".m4a" in reponse.json()["texte"]


 def test_question_trop_courte_rejetee_avant_tout():
@@ -32,6 +59,11 @@ def _client_sans_db() -> TestClient:
    modèle d'embeddings) ne tourne pas — on pose l'état minimal. Les tests
    d'intégration DB se font en local (recette), pas en CI (convention R5.1)."""
    from siop_ai.config import charger_reglages
+    from siop_ai.transcription import construire_transcripteur

-    app.state.reglages = charger_reglages()
+    reglages = charger_reglages()
+    app.state.reglages = reglages
+    app.state.transcripteur = construire_transcripteur(
+        reglages.ai_transcription, reglages.ai_transcription_model
+    )
    return TestClient(app, raise_server_exceptions=False)
--- a/apps/ai/tests/test_transcription.py
+++ b/apps/ai/tests/test_transcription.py
@@ -0,0 +1,36 @@
+"""Dictée opt-in (R5 D5, ADR-004 §5) : off par défaut (aucune dépendance
+audio requise), déterministe en CI/tests. Le vrai moteur (faster-whisper)
+se vérifie en recette réelle (convention R5.1 — pas de mesure préalable
+demandée par le référent, 22/07/2026)."""
+
+import pytest
+
+from siop_ai.config import charger_reglages
+from siop_ai.transcription import TranscripteurDeterministe, construire_transcripteur
+
+
+def test_off_par_defaut_ne_construit_rien():
+    assert construire_transcripteur("off", "small") is None
+
+
+def test_deterministe_stable_et_derive_la_taille():
+    transcripteur = construire_transcripteur("deterministe", "small")
+    assert isinstance(transcripteur, TranscripteurDeterministe)
+    texte = transcripteur.transcrire(b"12345", "m4a")
+    assert "5 octets" in texte
+    assert ".m4a" in texte
+    assert transcripteur.transcrire(b"12345", "m4a") == texte  # stable
+
+
+def test_mode_inconnu_refuse_au_boot(monkeypatch):
+    monkeypatch.setenv("AI_TRANSCRIPTION", "toujours")
+    with pytest.raises(ValueError, match="AI_TRANSCRIPTION"):
+        charger_reglages()
+
+
+def test_modele_configurable(monkeypatch):
+    monkeypatch.setenv("AI_TRANSCRIPTION", "deterministe")
+    monkeypatch.setenv("AI_TRANSCRIPTION_MODEL", "medium")
+    reglages = charger_reglages()
+    assert reglages.ai_transcription == "deterministe"
+    assert reglages.ai_transcription_model == "medium"
--- a/apps/ai/uv.lock
+++ b/apps/ai/uv.lock
@@ -149,6 +149,32 @@ wheels = [
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 ]

+[[package]]
+name = "av"
+version = "18.0.0"
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+wheels = [
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