From 7ef98d8089d55bb4bd6d987129353b4b236265fe Mon Sep 17 00:00:00 2001
From: Dom <dom@rpa-vision-v3.local>
Date: Fri, 29 May 2026 13:40:15 +0200
Subject: [PATCH] feat(lea): expose competence replay api

---
 agent_v0/server_v1/api_stream.py | 93 ++++++++++++++++++++++++++++++++
 1 file changed, 93 insertions(+)

diff --git a/agent_v0/server_v1/api_stream.py b/agent_v0/server_v1/api_stream.py
index 43d4f021a..050d3ea66 100644
--- a/agent_v0/server_v1/api_stream.py
+++ b/agent_v0/server_v1/api_stream.py
@@ -41,6 +41,16 @@ from .execution_plan_runner import (
     inject_plan_into_queue,
 )
 
+try:
+    from core.competences.catalog import load_competences
+    from core.competences.replay import build_competence_replay_payload, find_competence
+    COMPETENCE_API_AVAILABLE = True
+except Exception:  # pragma: no cover - allows partial deployments
+    load_competences = None
+    build_competence_replay_payload = None
+    find_competence = None
+    COMPETENCE_API_AVAILABLE = False
+
 # Pipeline d'anonymisation PII (OCR + NER côté serveur).
 # Import paresseux : on ne charge pas docTR tant qu'aucune image n'est reçue.
 try:
@@ -688,6 +698,14 @@ class RawReplayRequest(BaseModel):
     params: Optional[Dict[str, Any]] = None
 
 
+class CompetenceReplayRequest(BaseModel):
+    """Requête de test/replay supervisé d'une compétence Léa YAML."""
+    supervised: bool = True
+    start_replay: bool = False
+    session_id: str = ""
+    machine_id: Optional[str] = None
+
+
 class SingleActionRequest(BaseModel):
     """Requête d'exécution d'une seule action (mode Copilot)."""
     action: Dict[str, Any]
@@ -2074,6 +2092,81 @@ async def list_workflows(machine_id: Optional[str] = None):
     return result
 
 
+def _require_competence_api() -> None:
+    if not COMPETENCE_API_AVAILABLE:
+        raise HTTPException(status_code=503, detail="Catalogue compétences Léa indisponible")
+
+
+def _parse_competence_states(state: Optional[str]) -> Optional[List[str]]:
+    if not state:
+        return None
+    states = [part.strip() for part in state.split(",") if part.strip()]
+    return states or None
+
+
+@app.get("/api/v1/lea/competences")
+async def list_lea_competences(state: Optional[str] = None):
+    """Lister les compétences YAML connues par Léa, sans dépendance au VWB."""
+    _require_competence_api()
+    states = _parse_competence_states(state)
+    competences = load_competences(states=states)  # type: ignore[misc]
+    return {
+        "success": True,
+        "competences": [competence.to_dict() for competence in competences],
+        "total": len(competences),
+        "states_filter": states,
+    }
+
+
+@app.get("/api/v1/lea/competences/{competence_id}")
+async def get_lea_competence(competence_id: str):
+    """Retourner une compétence YAML et son plan de test supervisé."""
+    _require_competence_api()
+    try:
+        competence = find_competence(competence_id)  # type: ignore[misc]
+        payload = build_competence_replay_payload(competence_id, supervised=True)  # type: ignore[misc]
+    except KeyError:
+        raise HTTPException(status_code=404, detail=f"Compétence '{competence_id}' introuvable")
+    return {
+        "success": True,
+        "competence": competence.to_dict(),
+        "supervised_replay_preview": payload,
+    }
+
+
+@app.post("/api/v1/lea/competences/{competence_id}/replay")
+async def replay_lea_competence(competence_id: str, request: CompetenceReplayRequest):
+    """Planifier ou lancer le replay supervisé d'une compétence Léa YAML."""
+    _require_competence_api()
+    try:
+        payload = build_competence_replay_payload(  # type: ignore[misc]
+            competence_id,
+            supervised=request.supervised,
+            machine_id=request.machine_id,
+            session_id=request.session_id,
+        )
+    except KeyError:
+        raise HTTPException(status_code=404, detail=f"Compétence '{competence_id}' introuvable")
+
+    if not request.start_replay:
+        return {
+            "success": True,
+            "status": "planned",
+            "competence_id": competence_id,
+            "raw_replay_payload": payload,
+        }
+
+    replay_request = RawReplayRequest(**payload)
+    replay_result = await start_raw_replay(replay_request)
+    return {
+        "success": True,
+        "status": "started",
+        "competence_id": competence_id,
+        "raw_replay_payload": payload,
+        "replay": replay_result,
+    }
+
+
 @app.post("/api/v1/traces/stream/reload-workflows")
 async def reload_workflows():
     """Recharger les workflows depuis le disque.