feat: chat unifié, GestureCatalog, Copilot, Léa UI, extraction données, vérification replay
Refonte majeure du système Agent Chat et ajout de nombreux modules : - Chat unifié : suppression du dual Workflows/Agent Libre, tout passe par /api/chat avec résolution en 3 niveaux (workflow → geste → "montre-moi") - GestureCatalog : 38 raccourcis clavier universels Windows avec matching sémantique, substitution automatique dans les replays, et endpoint /api/gestures - Mode Copilot : exécution pas-à-pas des workflows avec validation humaine via WebSocket (approve/skip/abort) avant chaque action - Léa UI (agent_v0/lea_ui/) : interface PyQt5 pour Windows avec overlay transparent pour feedback visuel pendant le replay - Data Extraction (core/extraction/) : moteur d'extraction visuelle de données (OCR + VLM → SQLite), avec schémas YAML et export CSV/Excel - ReplayVerifier (agent_v0/server_v1/) : vérification post-action par comparaison de screenshots, avec logique de retry (max 3) - IntentParser durci : meilleur fallback regex, type GREETING, patterns améliorés - Dashboard : nouvelles pages gestures, streaming, extractions - Tests : 63 tests GestureCatalog, 47 tests extraction, corrections tests existants - Dépréciation : /api/agent/plan et /api/agent/execute retournent HTTP 410, suppression du code hardcodé _plan_to_replay_actions Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Dom
@@ -15,5 +15,6 @@ from . import workflow
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from . import capture
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from . import execute
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from . import match # Matching sémantique des workflows
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from . import review # Review/Validation de workflows importés
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__all__ = ['api_v3_bp']
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384
visual_workflow_builder/backend/api_v3/review.py
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384
visual_workflow_builder/backend/api_v3/review.py
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@@ -0,0 +1,384 @@
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"""
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API v3 - Review/Validation de workflows importes depuis le streaming
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Endpoints:
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GET /api/v3/workflows/pending-review -> liste les workflows en attente de review
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GET /api/v3/workflow/<id>/review -> donnees de review (workflow + screenshots)
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POST /api/v3/workflow/<id>/review -> soumettre une decision de review
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POST /api/v3/workflow/import-core -> importer un core Workflow avec review
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"""
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from flask import jsonify, request
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from datetime import datetime
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import logging
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import sys
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import traceback
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from pathlib import Path
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from . import api_v3_bp
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from .workflow import generate_id
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from db.models import db, Workflow, Step
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logger = logging.getLogger(__name__)
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@api_v3_bp.route('/workflows/pending-review', methods=['GET'])
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def list_pending_review():
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"""
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Liste les workflows en attente de validation.
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Filtre par source='graph_to_visual_converter' et review_status='pending_review'.
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Retourne aussi les workflows avec review_status='needs_edit'.
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Response:
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{
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"success": true,
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"workflows": [
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{
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"id": "...",
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"name": "...",
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"description": "...",
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"step_count": 5,
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"source": "graph_to_visual_converter",
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"review_status": "pending_review",
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"created_at": "...",
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"updated_at": "..."
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}
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],
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"total": 2
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}
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"""
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try:
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workflows = Workflow.query.filter(
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Workflow.is_active == True,
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Workflow.review_status.in_(['pending_review', 'needs_edit'])
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).order_by(Workflow.created_at.desc()).all()
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result = []
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for wf in workflows:
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result.append({
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'id': wf.id,
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'name': wf.name,
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'description': wf.description or '',
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'tags': wf.tags or [],
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'step_count': wf.steps.count(),
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'source': wf.source or 'manual',
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'review_status': wf.review_status,
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'review_feedback': wf.review_feedback,
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'created_at': wf.created_at.isoformat() if wf.created_at else None,
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'updated_at': wf.updated_at.isoformat() if wf.updated_at else None,
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})
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return jsonify({
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'success': True,
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'workflows': result,
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'total': len(result)
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})
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except Exception as e:
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logger.error(f"Erreur listing pending review: {e}")
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return jsonify({
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'success': False,
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'error': str(e)
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}), 500
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@api_v3_bp.route('/workflow/<workflow_id>/review', methods=['GET'])
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def get_review_data(workflow_id: str):
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"""
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Retourne les donnees de review pour un workflow.
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Inclut le workflow complet avec ses etapes, les screenshots
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associes (si disponibles via les ancres visuelles), et les
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metadonnees de la source.
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Response:
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{
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"success": true,
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"workflow": { ... },
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"review_info": {
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"source": "graph_to_visual_converter",
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"review_status": "pending_review",
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"review_feedback": null,
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"reviewed_at": null,
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"step_count": 5,
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"steps_with_anchors": 3,
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"steps_without_anchors": 2
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}
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}
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"""
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try:
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workflow = Workflow.query.get(workflow_id)
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if not workflow:
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return jsonify({
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'success': False,
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'error': f"Workflow '{workflow_id}' non trouve"
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}), 404
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# Compter les etapes avec/sans ancres visuelles
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steps = Step.query.filter_by(workflow_id=workflow_id).order_by(Step.order).all()
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steps_with_anchors = sum(1 for s in steps if s.anchor_id)
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steps_without_anchors = len(steps) - steps_with_anchors
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review_info = {
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'source': workflow.source or 'manual',
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'review_status': workflow.review_status,
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'review_feedback': workflow.review_feedback,
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'reviewed_at': workflow.reviewed_at.isoformat() if workflow.reviewed_at else None,
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'step_count': len(steps),
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'steps_with_anchors': steps_with_anchors,
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'steps_without_anchors': steps_without_anchors,
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}
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return jsonify({
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'success': True,
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'workflow': workflow.to_dict(),
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'review_info': review_info,
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})
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except Exception as e:
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logger.error(f"Erreur get review data: {e}")
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return jsonify({
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'success': False,
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'error': str(e)
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}), 500
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@api_v3_bp.route('/workflow/<workflow_id>/review', methods=['POST'])
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def submit_review(workflow_id: str):
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"""
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Soumet une decision de review pour un workflow.
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Request:
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{
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"status": "approved" | "rejected" | "needs_edit",
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"feedback": "Commentaire optionnel..."
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}
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Comportement selon le status:
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- "approved" : le workflow est valide, passe en learning_state COACHING
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- "rejected" : le workflow est marque inactif (is_active=False)
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- "needs_edit": le workflow reste actif, l'utilisateur peut le modifier dans le VWB
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Response:
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{
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"success": true,
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"workflow_id": "...",
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"review_status": "approved",
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"message": "..."
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}
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"""
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try:
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workflow = Workflow.query.get(workflow_id)
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if not workflow:
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return jsonify({
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'success': False,
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'error': f"Workflow '{workflow_id}' non trouve"
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}), 404
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data = request.get_json() or {}
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status = data.get('status')
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if status not in ('approved', 'rejected', 'needs_edit'):
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return jsonify({
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'success': False,
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'error': "Le champ 'status' doit etre 'approved', 'rejected' ou 'needs_edit'"
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}), 400
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feedback = data.get('feedback', '')
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# Mettre a jour le workflow
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workflow.review_status = status
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workflow.review_feedback = feedback
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workflow.reviewed_at = datetime.utcnow()
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workflow.updated_at = datetime.utcnow()
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message = ''
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if status == 'approved':
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# Passer le learning_state du workflow core vers COACHING
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_promote_to_coaching(workflow_id)
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message = f"Workflow '{workflow.name}' approuve. Le systeme peut maintenant suggerer ce workflow."
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elif status == 'rejected':
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# Marquer comme inactif
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workflow.is_active = False
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message = f"Workflow '{workflow.name}' rejete et desactive."
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elif status == 'needs_edit':
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# Laisser actif, l'utilisateur peut modifier
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message = f"Workflow '{workflow.name}' marque pour modification."
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db.session.commit()
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logger.info(f"[Review] Workflow {workflow_id} -> {status} (feedback: {feedback[:50]}...)")
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return jsonify({
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'success': True,
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'workflow_id': workflow_id,
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'review_status': status,
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'message': message,
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})
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except Exception as e:
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db.session.rollback()
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logger.error(f"Erreur submit review: {e}")
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return jsonify({
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'success': False,
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'error': str(e)
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}), 500
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def _promote_to_coaching(workflow_id: str):
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"""
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Passe le learning_state du workflow core vers COACHING.
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Tente de mettre a jour via le LearningManager si disponible.
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Fonctionnement gracieux : si le LearningManager n'est pas disponible,
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on log un warning et on continue.
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"""
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try:
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from services.learning_integration import _get_learning_manager
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manager = _get_learning_manager()
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if manager is None:
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logger.warning(
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f"[Review] LearningManager non disponible, impossible de promouvoir "
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f"le workflow {workflow_id} vers COACHING"
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)
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return
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# Tenter de changer l'etat
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try:
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from core.models.workflow_graph import LearningState
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manager.set_workflow_state(workflow_id, LearningState.COACHING)
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logger.info(f"[Review] Workflow {workflow_id} promu vers COACHING")
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except AttributeError:
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# set_workflow_state n'existe pas, essayer promote
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try:
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manager.promote_workflow(workflow_id)
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logger.info(f"[Review] Workflow {workflow_id} promu via promote_workflow()")
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except Exception as e2:
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logger.warning(f"[Review] Impossible de promouvoir le workflow: {e2}")
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except ImportError as e:
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logger.warning(f"[Review] Import learning_integration impossible: {e}")
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except Exception as e:
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logger.warning(f"[Review] Erreur promotion workflow {workflow_id}: {e}")
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@api_v3_bp.route('/workflow/import-core', methods=['POST'])
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def import_core_workflow_v3():
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"""
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Importe un core Workflow (issu du streaming/GraphBuilder) dans la base v3.
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Convertit via GraphToVisualConverter puis cree un Workflow SQLAlchemy
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avec source='graph_to_visual_converter' et review_status='pending_review'.
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Body: core Workflow JSON dict (tel que produit par Workflow.to_dict())
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Response:
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{
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"success": true,
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"workflow": { ... },
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"warnings": [...],
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"message": "..."
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}
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"""
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try:
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data = request.get_json()
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if not data:
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return jsonify({
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'success': False,
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'error': "Request body (core Workflow JSON) est requis"
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}), 400
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# Ajouter le chemin racine pour les imports core
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core_path = str(Path(__file__).parent.parent.parent.parent)
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if core_path not in sys.path:
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sys.path.insert(0, core_path)
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# Charger le core Workflow
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from core.models.workflow_graph import Workflow as CoreWorkflow
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core_wf = CoreWorkflow.from_dict(data)
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# Convertir vers VisualWorkflow (modele riche)
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from services.graph_to_visual_converter import GraphToVisualConverter
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converter = GraphToVisualConverter()
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visual_wf_rich = converter.convert(core_wf)
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# Creer le workflow SQLAlchemy (v3)
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wf_id = generate_id('wf')
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workflow = Workflow(
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id=wf_id,
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name=visual_wf_rich.name,
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description=visual_wf_rich.description or 'Workflow importe depuis le streaming',
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source='graph_to_visual_converter',
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review_status='pending_review',
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)
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if visual_wf_rich.tags:
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workflow.tags = visual_wf_rich.tags
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db.session.add(workflow)
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# Creer les etapes
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for idx, vnode in enumerate(visual_wf_rich.nodes):
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# Ignorer les nodes start/end purement structurels
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if vnode.type in ('start', 'end'):
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continue
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step = Step(
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id=generate_id('step'),
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workflow_id=wf_id,
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action_type=_visual_type_to_action_type(vnode.type),
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order=idx,
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position_x=vnode.position.x,
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position_y=vnode.position.y,
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label=vnode.label or vnode.type,
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)
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step.parameters = vnode.parameters or {}
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db.session.add(step)
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db.session.commit()
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logger.info(
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f"[Review] Core workflow importe -> {wf_id} "
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f"({workflow.name}, {len(visual_wf_rich.nodes)} nodes)"
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)
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return jsonify({
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'success': True,
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'workflow': workflow.to_dict(),
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'warnings': converter.warnings,
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'message': f"Workflow '{workflow.name}' importe et en attente de validation",
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}), 201
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except Exception as e:
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db.session.rollback()
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traceback.print_exc()
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logger.error(f"[Review] Erreur import core workflow: {e}")
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return jsonify({
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'success': False,
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'error': str(e)
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}), 500
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def _visual_type_to_action_type(visual_type: str) -> str:
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"""Convertit un type visuel VWB vers un action_type v3."""
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mapping = {
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'click': 'click_anchor',
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'type': 'type_text',
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'wait': 'wait_for_anchor',
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'navigate': 'click_anchor',
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'extract': 'extract_text',
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'variable': 'type_text',
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'condition': 'visual_condition',
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'loop': 'loop_visual',
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'validate': 'keyboard_shortcut',
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'scroll': 'scroll_to_anchor',
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'screenshot': 'screenshot_evidence',
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'transform': 'type_text',
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'api': 'click_anchor',
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'database': 'db_save_data',
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}
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return mapping.get(visual_type, 'click_anchor')
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@@ -72,7 +72,9 @@ def get_state():
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'tags': wf.tags or [],
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'trigger_examples': wf.trigger_examples or [],
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'step_count': wf.steps.count(),
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'updated_at': wf.updated_at.isoformat() if wf.updated_at else None
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'updated_at': wf.updated_at.isoformat() if wf.updated_at else None,
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'source': wf.source or 'manual',
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'review_status': wf.review_status,
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})
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return jsonify({
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