feat: Léa apprentissage — mode Shadow amélioré (observation + validation)
Aspect 3/4 Léa : Léa montre ce qu'elle comprend pendant l'enregistrement. ShadowObserver (observation temps réel) : - Segmentation incrémentale en UnderstoodStep (changement app, pause, Ctrl+S) - Détection de variables pendant la saisie (typage : date, email, code, texte) - Notifications 4 niveaux : INFO, DECOUVERTE, QUESTION, VARIABLE - Heartbeat périodique, hook gemma4 optionnel (asynchrone) - Thread-safe (RLock), singleton partagé - Performance : 1000 events en < 500ms ShadowValidator (feedback utilisateur) : - 6 actions : validate, correct, undo, cancel, merge_next, split - Reconstruit un WorkflowIR propre avec variables substituées - Historique complet des feedbacks 5 endpoints REST /api/v1/shadow/* : - start, stop, feedback, understanding, build Hook non-bloquant dans stream_event() (try/except, no-op si inactif). Mode optionnel : pas d'impact tant que shadow/start n'est pas appelé. 54 tests (26 observer + 28 validator), 0 régression. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
Dom
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core/workflow/shadow_observer.py
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693
core/workflow/shadow_observer.py
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# core/workflow/shadow_observer.py
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"""
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ShadowObserver — Observation en temps réel de ce que Léa comprend.
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C'est le "mode Shadow amélioré" : pendant que l'utilisateur enregistre
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une démonstration, Léa lui dit ce qu'elle comprend au fur et à mesure.
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Contrairement à l'IRBuilder (qui analyse TOUT à la fin en appelant gemma4),
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le ShadowObserver travaille en incrémental :
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- À chaque événement reçu, il met à jour sa compréhension locale.
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- Il segmente dès qu'un critère de coupure est détecté.
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- Il émet des notifications légères ("Léa a compris : tu viens d'ouvrir le
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Bloc-notes") via un callback.
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- Il détecte les variables (texte saisi) pendant la frappe.
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Le ShadowObserver n'est pas la source de vérité — c'est une couche
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d'observation. La source de vérité reste `live_events.jsonl`.
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Le WorkflowIR final est toujours reconstruit par l'IRBuilder après
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validation, mais la compréhension temps réel accélère la boucle de
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rétroaction avec l'utilisateur.
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Usage :
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def on_notify(event):
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print(f"[{event.niveau}] {event.message}")
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observer = ShadowObserver(notify_callback=on_notify)
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observer.start("sess_abc")
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observer.observe_event(event1)
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observer.observe_event(event2)
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...
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comprehension = observer.get_understanding()
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# → [{"step": 1, "intent": "Ouvrir le Bloc-notes", "confidence": 0.8}, ...]
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observer.stop()
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Contraintes :
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- 100% asynchrone côté performance : la méthode observe_event() ne doit
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jamais bloquer la capture (pas d'appel réseau synchrone).
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- Optionnel : activable via paramètre, ne modifie pas la capture existante.
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- 100% français dans les messages utilisateur.
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"""
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from __future__ import annotations
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import logging
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import threading
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import time
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import uuid
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from dataclasses import dataclass, field
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from enum import Enum
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from typing import Any, Callable, Dict, List, Optional
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logger = logging.getLogger(__name__)
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# =========================================================================
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# Types d'événements observationnels
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# =========================================================================
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class NiveauNotification(str, Enum):
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"""Niveau d'importance d'une notification.
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- INFO : information passive ("Léa observe...")
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- DECOUVERTE : Léa vient de comprendre quelque chose de nouveau
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- QUESTION : Léa aimerait une confirmation (non bloquant)
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- VARIABLE : une variable a été détectée
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"""
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INFO = "info"
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DECOUVERTE = "decouverte"
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QUESTION = "question"
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VARIABLE = "variable"
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@dataclass
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class NotificationShadow:
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"""Notification émise par le ShadowObserver vers la GUI utilisateur."""
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notif_id: str
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niveau: NiveauNotification
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message: str # Texte affichable à l'utilisateur (français)
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session_id: str
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step_index: int = -1 # Index de l'étape concernée, -1 si global
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data: Dict[str, Any] = field(default_factory=dict)
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timestamp: float = 0.0
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def to_dict(self) -> Dict[str, Any]:
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return {
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"notif_id": self.notif_id,
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"niveau": self.niveau.value,
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"message": self.message,
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"session_id": self.session_id,
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"step_index": self.step_index,
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"data": self.data,
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"timestamp": self.timestamp,
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}
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@dataclass
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class UnderstoodStep:
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"""Étape logique comprise en temps réel par le ShadowObserver.
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C'est une version simplifiée de `Step` (core.workflow.workflow_ir),
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optimisée pour la construction incrémentale. Elle sera convertie
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en `Step` final par le ShadowValidator après validation.
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"""
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step_index: int
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intent: str # Intention humaine (ex: "Ouvrir le Bloc-notes")
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intent_provisoire: bool = True # True tant que gemma4 n'a pas confirmé
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confidence: float = 0.5 # Score de confiance (0..1)
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app_name: str = "" # Application principale
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window_title: str = "" # Titre de la fenêtre au début du segment
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events: List[Dict[str, Any]] = field(default_factory=list)
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variables_detectees: List[str] = field(default_factory=list)
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started_at: float = 0.0
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ended_at: float = 0.0
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validated: bool = False # L'utilisateur a validé l'étape
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corrected: bool = False # L'utilisateur a corrigé l'intention
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cancelled: bool = False # L'utilisateur a annulé l'étape
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def to_dict(self) -> Dict[str, Any]:
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return {
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"step_index": self.step_index,
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"intent": self.intent,
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"intent_provisoire": self.intent_provisoire,
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"confidence": round(self.confidence, 3),
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"app_name": self.app_name,
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"window_title": self.window_title,
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"events_count": len(self.events),
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"variables_detectees": list(self.variables_detectees),
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"started_at": self.started_at,
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"ended_at": self.ended_at,
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"validated": self.validated,
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"corrected": self.corrected,
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"cancelled": self.cancelled,
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}
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# =========================================================================
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# Observer
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# =========================================================================
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# Constantes de segmentation (en secondes). On évite de re-déclarer les
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# constantes de l'IRBuilder car l'observation est incrémentale — on peut
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# se permettre des seuils plus courts pour plus de réactivité.
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_SEUIL_PAUSE_LONGUE_S = 4.0
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_SEUIL_CONFIANCE_BASE = 0.5
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_SEUIL_CONFIANCE_APP_CHANGE = 0.8
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# Types d'événements ignorés
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_EVENT_TYPES_IGNORES = {
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"heartbeat",
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"focus_change",
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"action_result",
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"window_focus_change",
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}
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class ShadowObserver:
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"""Observe les événements en temps réel et met à jour la compréhension.
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Thread-safe : peut être appelé depuis plusieurs threads (capture,
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API, worker).
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Le callback `notify_callback` est appelé de manière synchrone mais les
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notifications sont extrêmement légères (juste un dataclass) — elles
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sont destinées à être envoyées via WebSocket/HTTP long-poll depuis la
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couche API.
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"""
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NotifyCallback = Callable[[NotificationShadow], None]
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def __init__(
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self,
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notify_callback: Optional[NotifyCallback] = None,
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*,
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enable_gemma4: bool = False,
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gemma4_callback: Optional[Callable[[UnderstoodStep], None]] = None,
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):
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"""
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Args:
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notify_callback: Fonction appelée à chaque notification
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(doit être rapide, pas d'IO bloquant).
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enable_gemma4: Si True, une tâche asynchrone peut enrichir
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les intentions via gemma4 (non bloquant). En pratique,
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on laisse le caller le brancher via `gemma4_callback`.
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gemma4_callback: Fonction appelée en arrière-plan pour
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enrichir une étape (via gemma4 ou autre LLM). Non bloquant.
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"""
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self._notify_callback = notify_callback
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self._enable_gemma4 = enable_gemma4
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self._gemma4_callback = gemma4_callback
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self._lock = threading.RLock()
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self._sessions: Dict[str, Dict[str, Any]] = {}
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# ----- Cycle de vie --------------------------------------------------
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def start(self, session_id: str) -> None:
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"""Démarrer l'observation d'une session."""
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with self._lock:
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self._sessions[session_id] = {
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"steps": [], # List[UnderstoodStep]
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"current_step": None, # Optional[UnderstoodStep]
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"last_event_ts": 0.0,
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"last_notif_ts": 0.0,
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"total_events": 0,
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"notifications": [], # Historique des notifications
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"started_at": time.time(),
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"stopped_at": 0.0,
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}
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self._notifier(
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session_id,
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NiveauNotification.INFO,
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"Léa t'observe. Fais ta tâche normalement, je vais apprendre.",
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)
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def stop(self, session_id: str) -> None:
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"""Arrêter l'observation et finaliser le segment en cours."""
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with self._lock:
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state = self._sessions.get(session_id)
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if not state:
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return
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current = state.get("current_step")
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if current is not None and current.events:
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current.ended_at = state["last_event_ts"] or time.time()
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state["steps"].append(current)
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state["current_step"] = None
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state["stopped_at"] = time.time()
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nb_steps = len(self.get_understanding(session_id))
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if nb_steps > 0:
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self._notifier(
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session_id,
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NiveauNotification.DECOUVERTE,
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f"J'ai observé {nb_steps} étape(s). Tu veux que je te les "
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f"montre pour validation ?",
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)
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def reset(self, session_id: str) -> None:
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"""Supprimer l'état d'une session (après finalisation)."""
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with self._lock:
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self._sessions.pop(session_id, None)
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# ----- Observation ---------------------------------------------------
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def observe_event(self, session_id: str, event: Dict[str, Any]) -> None:
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"""Observer un nouvel événement pendant la capture.
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Cette méthode est appelée à chaque événement reçu par le serveur.
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Elle doit être RAPIDE (pas d'IO réseau synchrone).
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"""
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evt_type = event.get("type", "")
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if evt_type in _EVENT_TYPES_IGNORES:
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return
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with self._lock:
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state = self._sessions.get(session_id)
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if not state:
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# Auto-start si pas encore démarré (robustesse)
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self.start(session_id)
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state = self._sessions[session_id]
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state["total_events"] += 1
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# 1. Décider si on démarre un nouveau segment
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current = state.get("current_step")
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should_cut, cut_reason = self._should_cut(state, event)
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if should_cut and current is not None:
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current.ended_at = state["last_event_ts"] or time.time()
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state["steps"].append(current)
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self._emit_step_closed(session_id, current, cut_reason)
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current = None
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state["current_step"] = None
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if current is None:
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step_index = len(state["steps"]) + 1
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current = UnderstoodStep(
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step_index=step_index,
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intent=self._initial_intent(event),
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intent_provisoire=True,
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confidence=_SEUIL_CONFIANCE_BASE,
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app_name=self._get_app_name(event),
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window_title=self._get_window_title(event),
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started_at=float(event.get("timestamp", 0)) or time.time(),
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)
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state["current_step"] = current
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# 2. Ajouter l'événement au segment courant
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current.events.append(event)
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ts = float(event.get("timestamp", 0)) or time.time()
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state["last_event_ts"] = ts
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# 3. Rafraîchir l'intent provisoire à partir du contexte accumulé
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current.intent = self._refine_intent(current, event)
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# 4. Détection de variable pendant la frappe
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if evt_type == "text_input":
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self._handle_text_input(session_id, current, event)
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# 5. Émission périodique d'un résumé (toutes les 5s)
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self._maybe_emit_heartbeat(session_id, state)
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# ----- API publique --------------------------------------------------
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def get_understanding(
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self, session_id: str, include_current: bool = True
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) -> List[Dict[str, Any]]:
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"""Récupérer ce que Léa a compris jusqu'ici.
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Returns:
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Liste de dicts au format :
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[{"step": 1, "intent": "Ouvrir le Bloc-notes",
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"confidence": 0.9, "app": "Bloc-notes",
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"events_count": 4, ...}, ...]
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"""
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with self._lock:
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state = self._sessions.get(session_id)
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if not state:
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return []
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steps = list(state["steps"])
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if include_current and state.get("current_step") is not None:
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steps = steps + [state["current_step"]]
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out = []
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for step in steps:
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d = step.to_dict()
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d["step"] = d.pop("step_index")
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out.append(d)
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return out
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def get_notifications(
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self, session_id: str, since_ts: float = 0.0
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) -> List[Dict[str, Any]]:
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"""Récupérer les notifications émises depuis un timestamp."""
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with self._lock:
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state = self._sessions.get(session_id)
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if not state:
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return []
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return [
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n.to_dict() for n in state["notifications"]
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if n.timestamp >= since_ts
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]
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def get_current_step(
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self, session_id: str
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) -> Optional[Dict[str, Any]]:
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"""Retourner l'étape en cours de construction."""
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with self._lock:
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state = self._sessions.get(session_id)
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if not state:
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return None
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current = state.get("current_step")
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if current is None:
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return None
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return current.to_dict()
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def get_steps_internal(
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self, session_id: str, include_current: bool = True
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) -> List[UnderstoodStep]:
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"""Version interne : retourne les objets `UnderstoodStep`.
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Utilisé par le ShadowValidator pour reconstruire un WorkflowIR.
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"""
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with self._lock:
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state = self._sessions.get(session_id)
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if not state:
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return []
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steps = list(state["steps"])
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if include_current and state.get("current_step") is not None:
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steps = steps + [state["current_step"]]
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# Retourner des copies pour éviter les mutations externes
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return [self._copy_step(s) for s in steps]
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def has_session(self, session_id: str) -> bool:
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with self._lock:
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return session_id in self._sessions
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# ----- Internals : segmentation --------------------------------------
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def _should_cut(
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self, state: Dict[str, Any], event: Dict[str, Any]
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) -> tuple:
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"""Décider si l'événement doit démarrer un nouveau segment.
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Returns:
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(should_cut, reason)
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"""
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current = state.get("current_step")
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if current is None or not current.events:
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return (False, "")
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# Coupure : changement d'application
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new_app = self._get_app_name(event)
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if new_app and current.app_name and new_app != current.app_name:
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return (True, "changement_application")
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# Coupure : pause longue entre deux événements
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prev_ts = float(current.events[-1].get("timestamp", 0))
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curr_ts = float(event.get("timestamp", 0))
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if prev_ts > 0 and curr_ts > 0:
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if (curr_ts - prev_ts) > _SEUIL_PAUSE_LONGUE_S:
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return (True, "pause_longue")
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# Coupure : key_combo « lourd » type ctrl+s (sauvegarde) → fin logique
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evt_type = event.get("type", "")
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if evt_type in ("key_combo", "key_press"):
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keys = [str(k).lower() for k in event.get("keys", [])]
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if "ctrl" in keys and any(k in keys for k in ("s", "enter")):
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# On accroche le key_combo à l'étape courante, puis on coupe
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# APRÈS — retourner False ici, la coupure se fera au prochain
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# événement. C'est voulu.
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return (False, "")
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return (False, "")
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def _initial_intent(self, event: Dict[str, Any]) -> str:
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"""Intention provisoire d'un tout nouveau segment."""
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app = self._get_app_name(event) or self._get_window_title(event)
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evt_type = event.get("type", "")
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if evt_type == "mouse_click":
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hint = event.get("vision_info", {}).get("text", "")
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if hint:
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return f"Cliquer sur « {hint} »"
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if app:
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return f"Interagir avec {app}"
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return "Cliquer quelque part"
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if evt_type == "text_input":
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text = event.get("text", "")[:40]
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return f"Saisir du texte" + (f" « {text} »" if text else "")
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if evt_type in ("key_combo", "key_press"):
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keys = event.get("keys", [])
|
||||
return f"Appuyer sur {'+'.join(keys)}" if keys else "Raccourci clavier"
|
||||
return f"Action dans {app}" if app else "Action"
|
||||
|
||||
def _refine_intent(
|
||||
self, step: UnderstoodStep, event: Dict[str, Any]
|
||||
) -> str:
|
||||
"""Raffiner l'intention au fur et à mesure qu'on voit plus d'événements.
|
||||
|
||||
Heuristiques simples — pas de gemma4 ici pour rester rapide.
|
||||
"""
|
||||
types = [e.get("type", "") for e in step.events]
|
||||
has_click = "mouse_click" in types
|
||||
has_type = "text_input" in types
|
||||
has_key = any(t in ("key_combo", "key_press") for t in types)
|
||||
app = step.app_name or self._get_window_title(event)
|
||||
|
||||
# Cas 1 : clic + saisie + entrée → "Rechercher X"
|
||||
if has_click and has_type:
|
||||
texts = [e.get("text", "") for e in step.events if e.get("type") == "text_input"]
|
||||
if texts and any("enter" in [k.lower() for k in e.get("keys", [])]
|
||||
for e in step.events if e.get("type") in ("key_combo", "key_press")):
|
||||
premier_texte = next((t for t in texts if t), "")
|
||||
if premier_texte:
|
||||
step.confidence = min(0.85, step.confidence + 0.05)
|
||||
return f"Rechercher « {premier_texte[:30]} »"
|
||||
|
||||
# Cas 2 : saisie seule → "Écrire du texte"
|
||||
if has_type and not has_click:
|
||||
texts = [e.get("text", "") for e in step.events if e.get("type") == "text_input"]
|
||||
premier_texte = next((t for t in texts if t), "")
|
||||
if premier_texte:
|
||||
return f"Écrire « {premier_texte[:40]} »"
|
||||
return "Écrire du texte"
|
||||
|
||||
# Cas 3 : ctrl+s → "Sauvegarder"
|
||||
if has_key:
|
||||
for e in step.events:
|
||||
if e.get("type") in ("key_combo", "key_press"):
|
||||
keys = [str(k).lower() for k in e.get("keys", [])]
|
||||
if "ctrl" in keys and "s" in keys:
|
||||
step.confidence = min(0.9, step.confidence + 0.1)
|
||||
return f"Sauvegarder{' dans ' + app if app else ''}"
|
||||
if "ctrl" in keys and "c" in keys:
|
||||
return f"Copier{' depuis ' + app if app else ''}"
|
||||
if "ctrl" in keys and "v" in keys:
|
||||
return f"Coller{' dans ' + app if app else ''}"
|
||||
|
||||
# Cas 4 : clic seul + app identifiable
|
||||
if has_click and app:
|
||||
hint = ""
|
||||
for e in step.events:
|
||||
if e.get("type") == "mouse_click":
|
||||
hint = e.get("vision_info", {}).get("text", "")
|
||||
if hint:
|
||||
break
|
||||
if hint:
|
||||
return f"Cliquer sur « {hint} » dans {app}"
|
||||
return f"Interagir avec {app}"
|
||||
|
||||
return step.intent
|
||||
|
||||
def _handle_text_input(
|
||||
self,
|
||||
session_id: str,
|
||||
step: UnderstoodStep,
|
||||
event: Dict[str, Any],
|
||||
) -> None:
|
||||
"""Détecter et notifier une variable lors d'une saisie texte."""
|
||||
text = (event.get("text") or "").strip()
|
||||
if not text or len(text) < 3:
|
||||
return
|
||||
|
||||
# Déduire un nom de variable provisoire
|
||||
var_name = f"texte_{len(step.variables_detectees) + 1}"
|
||||
step.variables_detectees.append(var_name)
|
||||
|
||||
# Heuristique : détecter le type plausible
|
||||
var_type = self._guess_variable_type(text)
|
||||
|
||||
self._notifier(
|
||||
session_id,
|
||||
NiveauNotification.VARIABLE,
|
||||
f"Variable détectée : tu as tapé « {text[:40]} » — c'est {var_type} ?",
|
||||
step_index=step.step_index,
|
||||
data={
|
||||
"variable_name": var_name,
|
||||
"value": text,
|
||||
"variable_type": var_type,
|
||||
},
|
||||
)
|
||||
|
||||
def _guess_variable_type(self, text: str) -> str:
|
||||
"""Deviner le type d'une variable à partir de sa valeur."""
|
||||
t = text.strip()
|
||||
# Date (basique)
|
||||
if len(t) == 10 and t[2] in "/-" and t[5] in "/-":
|
||||
return "une date"
|
||||
if t.isdigit():
|
||||
return "un numéro"
|
||||
if "@" in t and "." in t:
|
||||
return "une adresse e-mail"
|
||||
if len(t) <= 10 and t.replace(" ", "").replace("-", "").isalnum() and not any(c.islower() for c in t):
|
||||
return "un code"
|
||||
if " " in t and len(t) > 10:
|
||||
return "un texte libre"
|
||||
return "un texte"
|
||||
|
||||
# ----- Internals : notifications -------------------------------------
|
||||
|
||||
def _notifier(
|
||||
self,
|
||||
session_id: str,
|
||||
niveau: NiveauNotification,
|
||||
message: str,
|
||||
*,
|
||||
step_index: int = -1,
|
||||
data: Optional[Dict[str, Any]] = None,
|
||||
) -> None:
|
||||
"""Créer et émettre une notification."""
|
||||
notif = NotificationShadow(
|
||||
notif_id=uuid.uuid4().hex[:12],
|
||||
niveau=niveau,
|
||||
message=message,
|
||||
session_id=session_id,
|
||||
step_index=step_index,
|
||||
data=data or {},
|
||||
timestamp=time.time(),
|
||||
)
|
||||
|
||||
with self._lock:
|
||||
state = self._sessions.get(session_id)
|
||||
if state is not None:
|
||||
state["notifications"].append(notif)
|
||||
state["last_notif_ts"] = notif.timestamp
|
||||
|
||||
if self._notify_callback is not None:
|
||||
try:
|
||||
self._notify_callback(notif)
|
||||
except Exception as e:
|
||||
logger.debug(f"ShadowObserver: callback a échoué : {e}")
|
||||
|
||||
def _emit_step_closed(
|
||||
self,
|
||||
session_id: str,
|
||||
step: UnderstoodStep,
|
||||
reason: str,
|
||||
) -> None:
|
||||
"""Émettre une notification quand une étape est fermée."""
|
||||
raison_humaine = {
|
||||
"changement_application": "tu es passé à une autre application",
|
||||
"pause_longue": "tu as fait une pause",
|
||||
}.get(reason, "")
|
||||
|
||||
suffixe = f" ({raison_humaine})" if raison_humaine else ""
|
||||
self._notifier(
|
||||
session_id,
|
||||
NiveauNotification.DECOUVERTE,
|
||||
f"Nouvelle étape comprise : {step.intent}{suffixe}",
|
||||
step_index=step.step_index,
|
||||
data={"step": step.to_dict()},
|
||||
)
|
||||
|
||||
if self._enable_gemma4 and self._gemma4_callback is not None:
|
||||
# Non bloquant : on délègue au caller (qui peut utiliser un thread)
|
||||
try:
|
||||
self._gemma4_callback(self._copy_step(step))
|
||||
except Exception as e:
|
||||
logger.debug(f"ShadowObserver: gemma4_callback a échoué : {e}")
|
||||
|
||||
def _maybe_emit_heartbeat(
|
||||
self,
|
||||
session_id: str,
|
||||
state: Dict[str, Any],
|
||||
) -> None:
|
||||
"""Émettre un résumé périodique (toutes les 5s env.)."""
|
||||
now = time.time()
|
||||
last = state.get("last_notif_ts", 0)
|
||||
if now - last < 5.0:
|
||||
return
|
||||
nb_steps = len(state["steps"])
|
||||
if state.get("current_step") is not None:
|
||||
nb_steps += 1
|
||||
if nb_steps == 0:
|
||||
return
|
||||
self._notifier(
|
||||
session_id,
|
||||
NiveauNotification.INFO,
|
||||
f"J'ai compris {nb_steps} étape(s) jusqu'ici.",
|
||||
data={"steps_count": nb_steps},
|
||||
)
|
||||
|
||||
# ----- Utilitaires ---------------------------------------------------
|
||||
|
||||
@staticmethod
|
||||
def _get_app_name(event: Dict[str, Any]) -> str:
|
||||
"""Extraire le nom d'application depuis un événement."""
|
||||
window = event.get("window") or {}
|
||||
if isinstance(window, dict):
|
||||
title = window.get("title", "")
|
||||
app_name = window.get("app_name", "")
|
||||
else:
|
||||
title = event.get("window_title", "")
|
||||
app_name = ""
|
||||
|
||||
# Préférer app_name si disponible
|
||||
if app_name and app_name != "unknown":
|
||||
return app_name
|
||||
|
||||
# Sinon, extraire depuis le titre
|
||||
for sep in [" – ", " - ", " — "]:
|
||||
if sep in title:
|
||||
return title.split(sep)[-1].strip()
|
||||
return title.strip() if title else ""
|
||||
|
||||
@staticmethod
|
||||
def _get_window_title(event: Dict[str, Any]) -> str:
|
||||
window = event.get("window") or {}
|
||||
if isinstance(window, dict):
|
||||
return window.get("title", "") or ""
|
||||
return event.get("window_title", "") or ""
|
||||
|
||||
@staticmethod
|
||||
def _copy_step(step: UnderstoodStep) -> UnderstoodStep:
|
||||
"""Copie superficielle pour éviter les fuites de mutation."""
|
||||
return UnderstoodStep(
|
||||
step_index=step.step_index,
|
||||
intent=step.intent,
|
||||
intent_provisoire=step.intent_provisoire,
|
||||
confidence=step.confidence,
|
||||
app_name=step.app_name,
|
||||
window_title=step.window_title,
|
||||
events=list(step.events),
|
||||
variables_detectees=list(step.variables_detectees),
|
||||
started_at=step.started_at,
|
||||
ended_at=step.ended_at,
|
||||
validated=step.validated,
|
||||
corrected=step.corrected,
|
||||
cancelled=step.cancelled,
|
||||
)
|
||||
|
||||
|
||||
# =========================================================================
|
||||
# Singleton partagé (optionnel)
|
||||
# =========================================================================
|
||||
|
||||
|
||||
_shared_observer: Optional[ShadowObserver] = None
|
||||
_shared_lock = threading.Lock()
|
||||
|
||||
|
||||
def get_shared_observer() -> ShadowObserver:
|
||||
"""Observer partagé pour l'API (lazy init)."""
|
||||
global _shared_observer
|
||||
with _shared_lock:
|
||||
if _shared_observer is None:
|
||||
_shared_observer = ShadowObserver()
|
||||
return _shared_observer
|
||||
468
core/workflow/shadow_validator.py
Normal file
468
core/workflow/shadow_validator.py
Normal file
@@ -0,0 +1,468 @@
|
||||
# core/workflow/shadow_validator.py
|
||||
"""
|
||||
ShadowValidator — Applique les feedbacks utilisateur et reconstruit un WorkflowIR.
|
||||
|
||||
Le ShadowObserver observe et comprend en temps réel. Le ShadowValidator,
|
||||
lui, prend les décisions de l'utilisateur (valider, corriger, annuler,
|
||||
combiner) et reconstruit un WorkflowIR final « propre » qui sera
|
||||
persisté et exécutable par le runtime.
|
||||
|
||||
Opérations supportées :
|
||||
- validate(step_index) : marquer l'étape comme validée
|
||||
- correct(step_index, new_intent) : corriger l'intention
|
||||
- undo(step_index) : annuler l'étape (elle sera exclue du WorkflowIR)
|
||||
- merge_with_next(step_index) : fusionner avec l'étape suivante
|
||||
- cancel() : annuler tout le workflow
|
||||
- split(step_index, at_event_index) : couper une étape en deux (bonus)
|
||||
|
||||
Le validator ne touche PAS aux événements bruts (events.jsonl) — il
|
||||
travaille sur la liste des `UnderstoodStep` fournie par le ShadowObserver.
|
||||
|
||||
Une fois toutes les actions appliquées, `build_workflow_ir()` produit
|
||||
un WorkflowIR exécutable à partir des étapes validées/corrigées.
|
||||
|
||||
Usage :
|
||||
|
||||
validator = ShadowValidator()
|
||||
validator.set_steps(observer.get_steps_internal(session_id))
|
||||
|
||||
validator.apply_feedback({"action": "validate", "step_index": 1})
|
||||
validator.apply_feedback({
|
||||
"action": "correct",
|
||||
"step_index": 2,
|
||||
"new_intent": "Sauvegarder le document",
|
||||
})
|
||||
validator.apply_feedback({"action": "undo", "step_index": 3})
|
||||
|
||||
ir = validator.build_workflow_ir(
|
||||
session_id="sess_abc",
|
||||
name="Mon workflow",
|
||||
domain="generic",
|
||||
)
|
||||
ir.save("data/workflows/")
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import time
|
||||
from dataclasses import dataclass
|
||||
from typing import Any, Dict, List, Optional, Tuple
|
||||
|
||||
from .shadow_observer import UnderstoodStep
|
||||
from .workflow_ir import Action, Step, Variable, WorkflowIR
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
# Actions supportées par le feedback
|
||||
FEEDBACK_ACTIONS = {
|
||||
"validate",
|
||||
"correct",
|
||||
"undo",
|
||||
"cancel",
|
||||
"merge_next",
|
||||
"split",
|
||||
}
|
||||
|
||||
|
||||
@dataclass
|
||||
class FeedbackResult:
|
||||
"""Résultat d'une opération de feedback."""
|
||||
|
||||
ok: bool
|
||||
action: str
|
||||
step_index: int
|
||||
message: str
|
||||
data: Dict[str, Any]
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
return {
|
||||
"ok": self.ok,
|
||||
"action": self.action,
|
||||
"step_index": self.step_index,
|
||||
"message": self.message,
|
||||
"data": dict(self.data),
|
||||
}
|
||||
|
||||
|
||||
class ShadowValidator:
|
||||
"""Applique les feedbacks utilisateur et produit un WorkflowIR."""
|
||||
|
||||
def __init__(self) -> None:
|
||||
self._steps: List[UnderstoodStep] = []
|
||||
self._cancelled_workflow: bool = False
|
||||
self._history: List[FeedbackResult] = []
|
||||
|
||||
# ----- API -----------------------------------------------------------
|
||||
|
||||
def set_steps(self, steps: List[UnderstoodStep]) -> None:
|
||||
"""Initialiser le validator avec la liste des étapes observées."""
|
||||
self._steps = [self._clone(s) for s in steps]
|
||||
self._cancelled_workflow = False
|
||||
self._history = []
|
||||
|
||||
@property
|
||||
def steps(self) -> List[UnderstoodStep]:
|
||||
"""Vue en lecture des étapes courantes."""
|
||||
return list(self._steps)
|
||||
|
||||
@property
|
||||
def history(self) -> List[FeedbackResult]:
|
||||
"""Historique des feedbacks appliqués."""
|
||||
return list(self._history)
|
||||
|
||||
@property
|
||||
def is_cancelled(self) -> bool:
|
||||
return self._cancelled_workflow
|
||||
|
||||
def apply_feedback(self, feedback: Dict[str, Any]) -> FeedbackResult:
|
||||
"""Appliquer un feedback utilisateur.
|
||||
|
||||
Le `feedback` est un dict au format :
|
||||
{
|
||||
"action": "validate" | "correct" | "undo" | "cancel" | "merge_next" | "split",
|
||||
"step_index": 1, # Index 1-based (comme dans get_understanding)
|
||||
"new_intent": "...", # Pour correct
|
||||
"at_event_index": 3, # Pour split
|
||||
}
|
||||
|
||||
Returns:
|
||||
FeedbackResult
|
||||
"""
|
||||
action = (feedback.get("action") or "").strip()
|
||||
if action not in FEEDBACK_ACTIONS:
|
||||
return self._record(FeedbackResult(
|
||||
ok=False, action=action, step_index=-1,
|
||||
message=f"Action inconnue : « {action} »",
|
||||
data={"supported": sorted(FEEDBACK_ACTIONS)},
|
||||
))
|
||||
|
||||
if action == "cancel":
|
||||
return self._do_cancel()
|
||||
|
||||
step_index = int(feedback.get("step_index", -1))
|
||||
if not self._is_valid_step_index(step_index):
|
||||
return self._record(FeedbackResult(
|
||||
ok=False, action=action, step_index=step_index,
|
||||
message=f"Index d'étape invalide : {step_index}",
|
||||
data={"nb_steps": len(self._steps)},
|
||||
))
|
||||
|
||||
if action == "validate":
|
||||
return self._do_validate(step_index)
|
||||
if action == "correct":
|
||||
return self._do_correct(step_index, feedback.get("new_intent", ""))
|
||||
if action == "undo":
|
||||
return self._do_undo(step_index)
|
||||
if action == "merge_next":
|
||||
return self._do_merge_next(step_index)
|
||||
if action == "split":
|
||||
return self._do_split(
|
||||
step_index, int(feedback.get("at_event_index", -1))
|
||||
)
|
||||
|
||||
return self._record(FeedbackResult(
|
||||
ok=False, action=action, step_index=step_index,
|
||||
message="Action non implémentée", data={},
|
||||
))
|
||||
|
||||
def apply_feedbacks(
|
||||
self, feedbacks: List[Dict[str, Any]]
|
||||
) -> List[FeedbackResult]:
|
||||
"""Appliquer plusieurs feedbacks dans l'ordre."""
|
||||
return [self.apply_feedback(f) for f in feedbacks]
|
||||
|
||||
# ----- Opérations ---------------------------------------------------
|
||||
|
||||
def _do_validate(self, step_index: int) -> FeedbackResult:
|
||||
step = self._get_step(step_index)
|
||||
step.validated = True
|
||||
step.intent_provisoire = False
|
||||
step.confidence = max(step.confidence, 0.95)
|
||||
return self._record(FeedbackResult(
|
||||
ok=True, action="validate", step_index=step_index,
|
||||
message=f"Étape {step_index} validée : {step.intent}",
|
||||
data={"intent": step.intent},
|
||||
))
|
||||
|
||||
def _do_correct(
|
||||
self, step_index: int, new_intent: str
|
||||
) -> FeedbackResult:
|
||||
new_intent = (new_intent or "").strip()
|
||||
if not new_intent:
|
||||
return self._record(FeedbackResult(
|
||||
ok=False, action="correct", step_index=step_index,
|
||||
message="Nouvelle intention vide",
|
||||
data={},
|
||||
))
|
||||
step = self._get_step(step_index)
|
||||
old_intent = step.intent
|
||||
step.intent = new_intent
|
||||
step.corrected = True
|
||||
step.validated = True # Corriger = implicitement valider
|
||||
step.intent_provisoire = False
|
||||
step.confidence = 1.0
|
||||
return self._record(FeedbackResult(
|
||||
ok=True, action="correct", step_index=step_index,
|
||||
message=f"Étape {step_index} corrigée : « {old_intent} » → « {new_intent} »",
|
||||
data={"old_intent": old_intent, "new_intent": new_intent},
|
||||
))
|
||||
|
||||
def _do_undo(self, step_index: int) -> FeedbackResult:
|
||||
step = self._get_step(step_index)
|
||||
step.cancelled = True
|
||||
return self._record(FeedbackResult(
|
||||
ok=True, action="undo", step_index=step_index,
|
||||
message=f"Étape {step_index} annulée : {step.intent}",
|
||||
data={"intent": step.intent},
|
||||
))
|
||||
|
||||
def _do_merge_next(self, step_index: int) -> FeedbackResult:
|
||||
"""Fusionner l'étape avec la suivante."""
|
||||
if step_index >= len(self._steps):
|
||||
return self._record(FeedbackResult(
|
||||
ok=False, action="merge_next", step_index=step_index,
|
||||
message="Aucune étape suivante à fusionner",
|
||||
data={},
|
||||
))
|
||||
step = self._get_step(step_index)
|
||||
next_step = self._get_step(step_index + 1)
|
||||
|
||||
merged = UnderstoodStep(
|
||||
step_index=step.step_index,
|
||||
intent=step.intent if len(step.intent) >= len(next_step.intent) else next_step.intent,
|
||||
intent_provisoire=False,
|
||||
confidence=max(step.confidence, next_step.confidence),
|
||||
app_name=step.app_name or next_step.app_name,
|
||||
window_title=step.window_title or next_step.window_title,
|
||||
events=list(step.events) + list(next_step.events),
|
||||
variables_detectees=list(step.variables_detectees)
|
||||
+ list(next_step.variables_detectees),
|
||||
started_at=step.started_at or next_step.started_at,
|
||||
ended_at=next_step.ended_at or step.ended_at,
|
||||
validated=True,
|
||||
corrected=step.corrected or next_step.corrected,
|
||||
cancelled=False,
|
||||
)
|
||||
|
||||
# Remplacer [step, next_step] par [merged]
|
||||
idx0 = step_index - 1 # 1-based → 0-based
|
||||
self._steps.pop(idx0 + 1) # next_step
|
||||
self._steps[idx0] = merged
|
||||
self._renumber()
|
||||
|
||||
return self._record(FeedbackResult(
|
||||
ok=True, action="merge_next", step_index=step_index,
|
||||
message=f"Étapes {step_index} et {step_index + 1} fusionnées",
|
||||
data={"intent": merged.intent},
|
||||
))
|
||||
|
||||
def _do_split(
|
||||
self, step_index: int, at_event_index: int
|
||||
) -> FeedbackResult:
|
||||
"""Couper une étape en deux au niveau de l'événement at_event_index.
|
||||
|
||||
`at_event_index` est 0-based parmi les events de l'étape.
|
||||
"""
|
||||
step = self._get_step(step_index)
|
||||
if at_event_index <= 0 or at_event_index >= len(step.events):
|
||||
return self._record(FeedbackResult(
|
||||
ok=False, action="split", step_index=step_index,
|
||||
message=f"Index de coupe invalide : {at_event_index}",
|
||||
data={"nb_events": len(step.events)},
|
||||
))
|
||||
|
||||
left_events = step.events[:at_event_index]
|
||||
right_events = step.events[at_event_index:]
|
||||
|
||||
left = UnderstoodStep(
|
||||
step_index=step.step_index,
|
||||
intent=step.intent + " (1/2)",
|
||||
intent_provisoire=True,
|
||||
confidence=step.confidence * 0.9,
|
||||
app_name=step.app_name,
|
||||
window_title=step.window_title,
|
||||
events=left_events,
|
||||
started_at=step.started_at,
|
||||
)
|
||||
right = UnderstoodStep(
|
||||
step_index=step.step_index + 1,
|
||||
intent=step.intent + " (2/2)",
|
||||
intent_provisoire=True,
|
||||
confidence=step.confidence * 0.9,
|
||||
app_name=step.app_name,
|
||||
window_title=step.window_title,
|
||||
events=right_events,
|
||||
started_at=float(right_events[0].get("timestamp", 0))
|
||||
if right_events else step.started_at,
|
||||
ended_at=step.ended_at,
|
||||
)
|
||||
|
||||
idx0 = step_index - 1
|
||||
self._steps[idx0] = left
|
||||
self._steps.insert(idx0 + 1, right)
|
||||
self._renumber()
|
||||
|
||||
return self._record(FeedbackResult(
|
||||
ok=True, action="split", step_index=step_index,
|
||||
message=f"Étape {step_index} coupée en 2",
|
||||
data={"nb_steps": len(self._steps)},
|
||||
))
|
||||
|
||||
def _do_cancel(self) -> FeedbackResult:
|
||||
self._cancelled_workflow = True
|
||||
return self._record(FeedbackResult(
|
||||
ok=True, action="cancel", step_index=-1,
|
||||
message="Workflow annulé",
|
||||
data={},
|
||||
))
|
||||
|
||||
# ----- Construction du WorkflowIR -----------------------------------
|
||||
|
||||
def build_workflow_ir(
|
||||
self,
|
||||
session_id: str = "",
|
||||
name: str = "",
|
||||
domain: str = "generic",
|
||||
*,
|
||||
require_all_validated: bool = False,
|
||||
) -> Optional[WorkflowIR]:
|
||||
"""Construire un WorkflowIR à partir des étapes corrigées.
|
||||
|
||||
Args:
|
||||
session_id: Identifiant de la session source.
|
||||
name: Nom du workflow.
|
||||
domain: Domaine métier.
|
||||
require_all_validated: Si True, lève une erreur si au moins
|
||||
une étape n'a pas été validée explicitement.
|
||||
|
||||
Returns:
|
||||
WorkflowIR ou None si le workflow a été annulé.
|
||||
"""
|
||||
if self._cancelled_workflow:
|
||||
logger.info("ShadowValidator: workflow annulé, pas de build")
|
||||
return None
|
||||
|
||||
ir = WorkflowIR.new(
|
||||
name=name or f"Workflow du {time.strftime('%d/%m/%Y %H:%M')}",
|
||||
domain=domain,
|
||||
learned_from=session_id,
|
||||
)
|
||||
|
||||
variables: List[Variable] = []
|
||||
seen_texts = set()
|
||||
applications: set = set()
|
||||
|
||||
for step in self._steps:
|
||||
if step.cancelled:
|
||||
continue
|
||||
if require_all_validated and not step.validated:
|
||||
raise ValueError(
|
||||
f"Étape {step.step_index} non validée : {step.intent}"
|
||||
)
|
||||
|
||||
if step.app_name:
|
||||
applications.add(step.app_name)
|
||||
|
||||
actions = []
|
||||
for evt in step.events:
|
||||
action = self._event_to_action(evt)
|
||||
if action is None:
|
||||
continue
|
||||
|
||||
# Détection de variable (texte saisi)
|
||||
if action.type == "type" and action.text:
|
||||
text = action.text.strip()
|
||||
if text and text not in seen_texts and len(text) > 2:
|
||||
seen_texts.add(text)
|
||||
var_name = f"texte_{len(variables) + 1}"
|
||||
variables.append(Variable(
|
||||
name=var_name,
|
||||
description=f"Texte saisi : « {text[:50]} »",
|
||||
source="user",
|
||||
default=text,
|
||||
))
|
||||
action.variable = True
|
||||
action.text = "{" + var_name + "}"
|
||||
|
||||
actions.append(action)
|
||||
|
||||
ir_step = Step(
|
||||
step_id=f"s{len(ir.steps) + 1}",
|
||||
intent=step.intent,
|
||||
actions=actions,
|
||||
)
|
||||
ir.steps.append(ir_step)
|
||||
|
||||
ir.variables = variables
|
||||
ir.applications = sorted(applications)
|
||||
ir.updated_at = time.time()
|
||||
|
||||
logger.info(
|
||||
f"ShadowValidator: WorkflowIR construit — {len(ir.steps)} étapes, "
|
||||
f"{len(ir.variables)} variables"
|
||||
)
|
||||
return ir
|
||||
|
||||
# ----- Utilitaires --------------------------------------------------
|
||||
|
||||
def _is_valid_step_index(self, step_index: int) -> bool:
|
||||
return 1 <= step_index <= len(self._steps)
|
||||
|
||||
def _get_step(self, step_index: int) -> UnderstoodStep:
|
||||
return self._steps[step_index - 1]
|
||||
|
||||
def _renumber(self) -> None:
|
||||
for i, s in enumerate(self._steps, start=1):
|
||||
s.step_index = i
|
||||
|
||||
def _record(self, result: FeedbackResult) -> FeedbackResult:
|
||||
self._history.append(result)
|
||||
return result
|
||||
|
||||
@staticmethod
|
||||
def _clone(step: UnderstoodStep) -> UnderstoodStep:
|
||||
return UnderstoodStep(
|
||||
step_index=step.step_index,
|
||||
intent=step.intent,
|
||||
intent_provisoire=step.intent_provisoire,
|
||||
confidence=step.confidence,
|
||||
app_name=step.app_name,
|
||||
window_title=step.window_title,
|
||||
events=list(step.events),
|
||||
variables_detectees=list(step.variables_detectees),
|
||||
started_at=step.started_at,
|
||||
ended_at=step.ended_at,
|
||||
validated=step.validated,
|
||||
corrected=step.corrected,
|
||||
cancelled=step.cancelled,
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def _event_to_action(evt: Dict[str, Any]) -> Optional[Action]:
|
||||
"""Convertir un événement brut en Action (miroir de IRBuilder)."""
|
||||
evt_type = evt.get("type", "")
|
||||
|
||||
if evt_type == "mouse_click":
|
||||
window = evt.get("window") or {}
|
||||
if isinstance(window, dict):
|
||||
target = window.get("title", "")
|
||||
else:
|
||||
target = evt.get("window_title", "")
|
||||
return Action(
|
||||
type="click",
|
||||
target=target or "",
|
||||
anchor_hint=(evt.get("vision_info") or {}).get("text", ""),
|
||||
)
|
||||
if evt_type == "text_input":
|
||||
text = evt.get("text", "")
|
||||
if text:
|
||||
return Action(type="type", text=text)
|
||||
if evt_type in ("key_combo", "key_press"):
|
||||
keys = evt.get("keys", [])
|
||||
if keys:
|
||||
return Action(type="key_combo", keys=list(keys))
|
||||
if evt_type == "scroll":
|
||||
return Action(type="scroll")
|
||||
return None
|
||||
Reference in New Issue
Block a user