feat(p1): persist workflows and semantic learning artifacts
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tests/integration/test_shadow_full_cycle.py
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245
tests/integration/test_shadow_full_cycle.py
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"""Tests integration HTTP — cycle complet Lea-first jusqu'au /persist.
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Specs : docs/POC/SPECS_ENDPOINT_PERSIST_2026-06-01.md
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Le focus est sur l'endpoint /persist : on mocke les phases amont (Shadow
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build) en construisant directement le workflow_ir. Pas de lancement reel
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de session Shadow ici.
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"""
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from __future__ import annotations
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import json
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import sys
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from pathlib import Path
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import pytest
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_ROOT = str(Path(__file__).resolve().parents[2])
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if _ROOT not in sys.path:
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sys.path.insert(0, _ROOT)
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pytestmark = pytest.mark.integration
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_TEST_API_TOKEN = "test_persist_endpoint_token_xyz"
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@pytest.fixture
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def persist_client(monkeypatch, tmp_path):
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"""TestClient FastAPI + redirection des chemins persist vers tmp_path."""
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monkeypatch.setenv("RPA_API_TOKEN", _TEST_API_TOKEN)
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monkeypatch.delenv("RPA_AUTH_DISABLED", raising=False)
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# DB agents isolee pour eviter le guard fleet
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monkeypatch.setenv("RPA_AGENTS_DB_PATH", str(tmp_path / "agents.db"))
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from fastapi.testclient import TestClient
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from agent_v0.server_v1 import api_stream
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from agent_v0.server_v1.agent_registry import AgentRegistry
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from core.competences import persist as P
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monkeypatch.setattr(api_stream, "API_TOKEN", _TEST_API_TOKEN)
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# api_stream peut deja etre importe par un autre test avant que
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# RPA_AGENTS_DB_PATH soit pose. Isoler explicitement le registre global.
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test_registry = AgentRegistry(db_path=str(tmp_path / "agents.db"))
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monkeypatch.setattr(api_stream, "agent_registry", test_registry)
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# Rediriger toutes les ecritures vers tmp_path
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candidate_dir = tmp_path / "competences" / "candidate"
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candidate_dir.mkdir(parents=True, exist_ok=True)
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audit_path = tmp_path / "competences" / "persist_audit.jsonl"
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incomplete_path = tmp_path / "competences" / "incomplete_learnings.jsonl"
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monkeypatch.setattr(P, "COMPETENCES_ROOT", tmp_path / "competences")
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monkeypatch.setattr(P, "CANDIDATE_DIR", candidate_dir)
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monkeypatch.setattr(P, "AUDIT_PATH", audit_path)
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monkeypatch.setattr(P, "INCOMPLETE_PATH", incomplete_path)
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# Reset du rate limiter pour eviter les fuites entre tests
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P.persist_rate_limiter.reset()
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client = TestClient(api_stream.app, raise_server_exceptions=False)
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return client, tmp_path
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def _auth_headers():
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return {"Authorization": f"Bearer {_TEST_API_TOKEN}"}
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def _minimal_workflow_ir():
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return {
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"steps": [
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{
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"kind": "click",
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"primitive_ref": "click",
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"parameters": {"target": "Bouton OK"},
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"description": "Clic sur Bouton OK",
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}
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],
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"preconditions": [],
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"success_marker": {
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"mode": "all_of",
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"timeout_ms": 5000,
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"markers": [],
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},
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}
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class TestPersistEndpointSuccess:
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"""Cas nominal : payload valide -> 201 + YAML cree + audit ecrit."""
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def test_persist_returns_201_and_writes_yaml(self, persist_client):
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client, tmp_path = persist_client
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resp = client.post(
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"/api/v1/lea/competences/candidate/persist",
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json={
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"name": "Test Cycle Complet",
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"machine_id": "machine_test_x",
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"session_id": "sess_xyz",
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"workflow_ir": _minimal_workflow_ir(),
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"parameters": [],
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"annotations_semantiques": {"intent_fr": "tester cycle"},
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"learning_metadata": {"persist_id": "uuid-cycle-1"},
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},
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headers=_auth_headers(),
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)
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assert resp.status_code == 201, resp.text
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body = resp.json()
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assert body["competence_id"] == "test_cycle_complet"
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assert body["learning_state"] == "candidate"
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assert body["persist_id"] == "uuid-cycle-1"
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assert body["audit_entry_id"] >= 1
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# Le YAML doit etre present sur disque (chemin redirige par fixture)
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yaml_file = tmp_path / "competences" / "candidate" / "test_cycle_complet.yaml"
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assert yaml_file.exists()
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# Audit enrichi
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audit = tmp_path / "competences" / "persist_audit.jsonl"
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assert audit.exists()
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lines = audit.read_text(encoding="utf-8").strip().splitlines()
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assert any(json.loads(li).get("persist_id") == "uuid-cycle-1" for li in lines)
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def test_persist_idempotence_returns_previous(self, persist_client):
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client, _ = persist_client
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payload = {
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"name": "Idempotent Test",
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"machine_id": "machine_test_x",
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"workflow_ir": _minimal_workflow_ir(),
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"learning_metadata": {"persist_id": "uuid-idem-1"},
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}
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r1 = client.post(
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"/api/v1/lea/competences/candidate/persist",
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json=payload,
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headers=_auth_headers(),
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)
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assert r1.status_code == 201
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r2 = client.post(
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"/api/v1/lea/competences/candidate/persist",
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json=payload,
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headers=_auth_headers(),
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)
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# Idempotent : 200 ou 201 avec idempotent_replay=True
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assert r2.status_code in (200, 201)
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body2 = r2.json()
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assert body2.get("idempotent_replay") is True
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assert body2["competence_id"] == r1.json()["competence_id"]
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class TestPersistEndpointEdgeCases:
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"""Cas particuliers documentes dans specs §5."""
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def test_partial_true_force_incomplete_state(self, persist_client):
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client, tmp_path = persist_client
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resp = client.post(
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"/api/v1/lea/competences/candidate/persist",
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json={
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"name": "Partial Demo",
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"machine_id": "machine_test_x",
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"workflow_ir": {"steps": []}, # vide accepte si partial
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"learning_metadata": {
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"persist_id": "uuid-partial-1",
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"partial": True,
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"dropout_reason": "utilisateur a abandonne",
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},
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},
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headers=_auth_headers(),
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)
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assert resp.status_code == 201, resp.text
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assert resp.json()["learning_state"] == "incomplete"
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# Double entree : audit principal + incomplete
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incomplete = tmp_path / "competences" / "incomplete_learnings.jsonl"
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assert incomplete.exists()
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def test_empty_workflow_without_partial_returns_400(self, persist_client):
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client, _ = persist_client
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resp = client.post(
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"/api/v1/lea/competences/candidate/persist",
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json={
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"name": "Empty Demo",
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"machine_id": "machine_test_x",
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"workflow_ir": {"steps": []},
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"learning_metadata": {"persist_id": "uuid-empty-1"},
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},
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headers=_auth_headers(),
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)
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assert resp.status_code == 400
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assert resp.json()["detail"]["error"] == "empty_workflow_ir"
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def test_partial_without_dropout_reason_returns_400(self, persist_client):
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client, _ = persist_client
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resp = client.post(
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"/api/v1/lea/competences/candidate/persist",
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json={
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"name": "Partial Sans Raison",
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"machine_id": "machine_test_x",
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"workflow_ir": {"steps": []},
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"learning_metadata": {
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"persist_id": "uuid-partial-noreason",
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"partial": True,
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},
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},
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headers=_auth_headers(),
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)
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assert resp.status_code == 400
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assert resp.json()["detail"]["error"] == "dropout_reason_required"
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def test_stable_request_forced_to_candidate(self, persist_client):
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client, _ = persist_client
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resp = client.post(
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"/api/v1/lea/competences/candidate/persist",
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json={
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"name": "Force Candidate Demo",
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"machine_id": "machine_test_x",
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"workflow_ir": _minimal_workflow_ir(),
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"learning_metadata": {
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"persist_id": "uuid-stable-attempt",
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"learning_state": "stable",
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},
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},
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headers=_auth_headers(),
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)
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assert resp.status_code == 201
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# Regle d'or HDS : jamais stable par persist direct
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assert resp.json()["learning_state"] == "candidate"
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def test_slug_collision_returns_409(self, persist_client):
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client, tmp_path = persist_client
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# Pre-creer un YAML candidate pour declencher la collision
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candidate = tmp_path / "competences" / "candidate" / "collision_demo.yaml"
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candidate.write_text("id: collision_demo\nname: x\n", encoding="utf-8")
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resp = client.post(
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"/api/v1/lea/competences/candidate/persist",
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json={
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"name": "Collision Demo",
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"machine_id": "machine_test_x",
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"workflow_ir": _minimal_workflow_ir(),
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"learning_metadata": {"persist_id": "uuid-coll-1"},
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},
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headers=_auth_headers(),
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)
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assert resp.status_code == 409
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assert resp.json()["detail"]["error"] == "slug_collision"
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