feat(vwb): preview lea competence workflows
This commit is contained in:
Dom
105
tests/unit/test_competence_to_vwb_preview.py
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105
tests/unit/test_competence_to_vwb_preview.py
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@@ -0,0 +1,105 @@
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from flask import Flask
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from visual_workflow_builder.backend.services.competence_vwb_preview import (
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competence_yaml_to_vwb_preview,
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competence_yaml_to_vwb_steps,
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)
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def _by_type(preview):
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return [step["action_type"] for step in preview["steps"]]
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def test_competence_to_vwb_preview_key_win_r_steps():
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preview = competence_yaml_to_vwb_preview("key_win_r_wait_explorer_exe")
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assert preview["readonly"] is True
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assert preview["write_back_enabled"] is False
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assert preview["workflow"]["competence_id"] == "key_win_r_wait_explorer_exe"
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assert _by_type(preview) == [
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"pause_for_human",
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"keyboard_shortcut",
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"wait_for_state",
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"pause_for_human",
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]
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def test_keyboard_shortcut_keys_are_preserved():
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steps = competence_yaml_to_vwb_steps("key_win_r_wait_explorer_exe")
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shortcut = steps[1]
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assert shortcut["action_type"] == "keyboard_shortcut"
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assert shortcut["parameters"]["keys"] == ["win", "r"]
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assert shortcut["parameters"]["source"] == (
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"lea_competence:key_win_r_wait_explorer_exe"
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)
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assert shortcut["parameters"]["source_method_id"] == "step_1_key_combo"
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def test_wait_for_state_expected_state_is_preserved():
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steps = competence_yaml_to_vwb_steps("key_win_r_wait_explorer_exe")
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wait_step = steps[2]
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assert wait_step["action_type"] == "wait_for_state"
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params = wait_step["parameters"]
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assert params["expected_state"]["window_title_in"] == ["Ex\u00e9cuter"]
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assert params["expected_state"]["process_active"] == "explorer.exe"
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assert params["timeout_ms"] == 5000
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assert params["poll_interval_ms"] == 250
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assert params["evidence_required"] == "window_or_process"
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def test_pause_for_human_before_and_after_are_supervision_only():
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steps = competence_yaml_to_vwb_steps("key_win_r_wait_explorer_exe")
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before = steps[0]
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after = steps[-1]
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assert before["parameters"]["phase"] == "before"
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assert before["parameters"]["verdict_required"] is False
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assert after["parameters"]["phase"] == "after"
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assert after["parameters"]["verdict_required"] is True
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assert after["parameters"]["write_back_enabled"] is False
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def test_adapter_is_generic_on_methods_not_hardcoded_to_win_r():
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steps = competence_yaml_to_vwb_steps("key_ctrl_s_wait_notepad_exe")
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assert [step["action_type"] for step in steps] == [
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"pause_for_human",
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"keyboard_shortcut",
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"wait_for_state",
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"pause_for_human",
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]
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assert steps[1]["parameters"]["keys"] == ["ctrl", "s"]
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assert steps[2]["parameters"]["expected_state"]["window_title_in"] == [
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"Enregistrer sous"
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]
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assert steps[2]["parameters"]["expected_state"]["process_active"] == "Notepad.exe"
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def test_preview_endpoint_returns_read_only_workflow():
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from visual_workflow_builder.backend.catalog_routes_v2_vlm import (
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competence_preview_bp,
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)
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app = Flask(__name__)
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app.register_blueprint(competence_preview_bp)
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with app.test_client() as client:
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response = client.post(
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"/api/vwb/competences/key_win_r_wait_explorer_exe/preview",
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json={"supervised": True},
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)
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assert response.status_code == 200
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data = response.get_json()
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assert data["success"] is True
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assert data["readonly"] is True
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assert data["write_back_enabled"] is False
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assert data["workflow"]["source"] == "lea_competence_preview"
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assert [step["action_type"] for step in data["steps"]] == [
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"pause_for_human",
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"keyboard_shortcut",
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"wait_for_state",
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"pause_for_human",
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]
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@@ -180,8 +180,9 @@ except ImportError as e:
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# Catalogue VWB - actions VisionOnly
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# V2 avec VLM (Vision Language Model) pour détection intelligente
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try:
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from catalog_routes_v2_vlm import catalog_bp, VLM_MODEL
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from catalog_routes_v2_vlm import catalog_bp, competence_preview_bp, VLM_MODEL
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app.register_blueprint(catalog_bp)
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app.register_blueprint(competence_preview_bp)
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print(f"✅ Blueprint catalog V2 VLM (Ollama {VLM_MODEL}) enregistré")
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except ImportError as e:
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print(f"⚠️ Blueprint catalog V2 VLM désactivé: {e}")
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@@ -1073,6 +1073,11 @@ def find_anchor_multiscale(anchor_image_base64: str, scales: List[float] = None,
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# Créer le blueprint pour les routes catalogue
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catalog_bp = Blueprint('catalog', __name__, url_prefix='/api/vwb/catalog')
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competence_preview_bp = Blueprint(
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'competence_preview',
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__name__,
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url_prefix='/api/vwb/competences',
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)
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# Instance globale du ScreenCapturer (initialisée à la demande)
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_screen_capturer_instance = None
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@@ -1210,6 +1215,44 @@ def _execute_lea_competence_action(
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})
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@competence_preview_bp.route('/<competence_id>/preview', methods=['POST'])
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def preview_lea_competence_workflow(competence_id: str):
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"""Build a read-only VWB preview from a Lea competence YAML."""
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try:
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data = request.get_json(silent=True) or {}
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supervised = bool(data.get('supervised', True))
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from visual_workflow_builder.backend.services.competence_vwb_preview import (
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competence_yaml_to_vwb_preview,
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)
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preview = competence_yaml_to_vwb_preview(
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competence_id,
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supervised=supervised,
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)
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return jsonify({
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"success": True,
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"competence_id": competence_id,
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"preview": preview,
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"workflow": preview["workflow"],
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"steps": preview["steps"],
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"warnings": preview["warnings"],
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"readonly": True,
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"write_back_enabled": False,
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})
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except KeyError:
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return jsonify({
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"success": False,
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"error": f"Competence '{competence_id}' introuvable",
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}), 404
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except Exception as e:
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return jsonify({
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"success": False,
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"error": f"Erreur preview competence: {str(e)}",
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"traceback": traceback.format_exc(),
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}), 500
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def get_screen_capturer():
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"""
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Obtient l'instance du ScreenCapturer (initialisation paresseuse).
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@@ -0,0 +1,254 @@
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"""Build read-only VWB previews from Lea competence YAML files."""
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from __future__ import annotations
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from datetime import datetime, timezone
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from pathlib import Path
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from typing import Any, Dict, Iterable, List, Optional
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from core.competences.catalog import DEFAULT_COMPETENCE_ROOT, CompetenceSummary
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from core.competences.replay import find_competence
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def competence_yaml_to_vwb_preview(
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competence_id: str,
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*,
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root: Path | str = DEFAULT_COMPETENCE_ROOT,
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supervised: bool = True,
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states: Optional[Iterable[str]] = None,
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) -> Dict[str, Any]:
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"""Return a read-only VWB workflow preview for one persisted competence."""
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competence = find_competence(competence_id, root=root, states=states)
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warnings: List[str] = []
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steps: List[Dict[str, Any]] = []
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if supervised:
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steps.append(_pause_step(competence, phase="before", order=len(steps)))
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for method in competence.methods:
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step = _method_to_vwb_step(competence, method, order=len(steps))
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if step is None:
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warnings.append(
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"Methode non supportee en preview VWB: "
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f"{method.get('id') or method.get('kind') or 'unknown'}"
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)
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continue
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steps.append(step)
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if supervised:
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steps.append(_pause_step(competence, phase="after", order=len(steps)))
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_compute_layout(steps)
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workflow = {
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"id": f"preview_competence_{competence.id}",
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"name": f"Lea preview - {competence.id}",
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"description": competence.intent_fr,
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"source": "lea_competence_preview",
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"review_status": "preview",
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"tags": ["lea", "competence", competence.learning_state],
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"competence_id": competence.id,
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"learning_state": competence.learning_state,
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"source_path": competence.source_path,
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"readonly": True,
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"created_at": datetime.now(timezone.utc).isoformat(),
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}
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return {
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"workflow": workflow,
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"steps": steps,
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"warnings": warnings,
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"readonly": True,
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"write_back_enabled": False,
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"db_write": False,
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}
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def competence_yaml_to_vwb_steps(
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competence_id: str,
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*,
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root: Path | str = DEFAULT_COMPETENCE_ROOT,
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supervised: bool = True,
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states: Optional[Iterable[str]] = None,
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) -> List[Dict[str, Any]]:
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"""Compatibility helper returning only VWB steps for a competence."""
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return competence_yaml_to_vwb_preview(
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competence_id,
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root=root,
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supervised=supervised,
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states=states,
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)["steps"]
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def _method_to_vwb_step(
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competence: CompetenceSummary,
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method: Dict[str, Any],
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*,
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order: int,
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) -> Optional[Dict[str, Any]]:
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kind = str(method.get("kind") or method.get("primitive_ref") or "").strip()
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params = method.get("parameters") if isinstance(method.get("parameters"), dict) else {}
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method_id = str(method.get("id") or f"method_{order}")
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source_params = _source_params(competence, method_id)
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metadata = _source_metadata(competence, method, phase="method")
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if kind == "key_combo":
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keys = params.get("keys")
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if not isinstance(keys, list) or not keys:
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return None
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vwb_params = {
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"keys": [str(key) for key in keys],
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"hold_duration_ms": params.get("hold_duration_ms", 50),
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**source_params,
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}
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return _step(
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action_type="keyboard_shortcut",
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order=order,
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label=f"Raccourci : {'+'.join(vwb_params['keys'])}",
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parameters=vwb_params,
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metadata=metadata,
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)
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if kind in {"wait_state", "wait_for_state"}:
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expected_state = params.get("expected_state")
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if not isinstance(expected_state, dict) or not expected_state:
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return None
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vwb_params = {
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"expected_state": expected_state,
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"timeout_ms": int(params.get("timeout_ms", 5000)),
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"poll_interval_ms": int(params.get("poll_interval_ms", 250)),
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"evidence_required": params.get("evidence_required", "window_or_process"),
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**source_params,
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}
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return _step(
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action_type="wait_for_state",
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order=order,
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label="Attendre etat",
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parameters=vwb_params,
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metadata=metadata,
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)
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if kind in {"text_input", "text_input_focused"}:
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text = params.get("text")
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if text is None:
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return None
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return _step(
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action_type="type_text",
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order=order,
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label="Saisir texte",
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parameters={"text": str(text), **source_params},
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metadata=metadata,
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)
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if kind == "click_anchor":
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vwb_params = {
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key: value
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for key, value in params.items()
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if key in {"visual_anchor", "target_text", "target_role", "by_text"}
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}
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return _step(
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action_type="click_anchor",
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order=order,
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label="Clic ancre",
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parameters={**vwb_params, **source_params},
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metadata=metadata,
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)
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return None
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def _pause_step(
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competence: CompetenceSummary,
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*,
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phase: str,
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order: int,
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) -> Dict[str, Any]:
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failure = competence.failure_message_template
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if phase == "before":
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message = (
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f"Prepare le test supervise de la competence '{competence.id}'. "
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f"Intention: {competence.intent_fr}. "
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f"Attendu: {failure.get('attendu', 'etat attendu non renseigne')}."
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)
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verdict_required = False
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else:
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message = (
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f"Valide le resultat de la competence '{competence.id}'. "
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f"Attendu: {failure.get('attendu', 'etat attendu non renseigne')}. "
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"Indique si ce replay peut etre garde comme succes supervise."
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)
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verdict_required = True
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parameters = {
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"message": message,
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"phase": phase,
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"verdict_required": verdict_required,
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"competence_id": competence.id,
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"source": f"lea_competence:{competence.id}",
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"write_back_enabled": False,
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"intention": failure.get("intention", competence.intent_fr),
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"attendu": failure.get("attendu", ""),
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"demande": failure.get("demande", ""),
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}
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return _step(
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action_type="pause_for_human",
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order=order,
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label="Pause supervision" if phase == "before" else "Verdict humain",
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parameters=parameters,
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metadata=_source_metadata(competence, {}, phase=phase),
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)
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def _source_params(competence: CompetenceSummary, method_id: str) -> Dict[str, Any]:
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return {
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"competence_id": competence.id,
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"source": f"lea_competence:{competence.id}",
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"source_method_id": method_id,
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"write_back_enabled": False,
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}
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def _source_metadata(
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competence: CompetenceSummary,
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method: Dict[str, Any],
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*,
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phase: str,
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) -> Dict[str, Any]:
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return {
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"origin": "lea_competence_yaml",
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"competence_id": competence.id,
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"learning_state": competence.learning_state,
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"source_path": competence.source_path,
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"source_method_id": method.get("id"),
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"primitive_ref": method.get("primitive_ref"),
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"method_kind": method.get("kind"),
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"phase": phase,
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}
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def _step(
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*,
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action_type: str,
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order: int,
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label: str,
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parameters: Dict[str, Any],
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metadata: Dict[str, Any],
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) -> Dict[str, Any]:
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return {
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"id": f"preview_step_{order:02d}_{action_type}",
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"action_type": action_type,
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"order": order,
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"position_x": 0,
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"position_y": 0,
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"label": label,
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"parameters": parameters,
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"metadata": metadata,
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}
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def _compute_layout(steps: List[Dict[str, Any]]) -> None:
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for index, step in enumerate(steps):
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step["position_x"] = 80 + index * 300
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step["position_y"] = 120
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