chore(dgx): snapshot consolidation WIP pour transfert poc DGX

Regroupe le WIP non committé requis pour le clone/runtime DGX (Option A) :
- api_stream.py : préflight replay + smoke santé modèles + handler 403 WP-B
- de-hardcode VLM : vlm_config, gpu/*, vram_orchestrator, ollama_manager
- stream_processor, semantic_matcher, agent_chat (app/planner/intent)
- workflows.db (acquis ; le transfert artifacts le mettra à jour + rewrite chemins)
- docs : plans DGX, benchmarks VLM/grounders, recherche SOTA, coordination 8 juin

Snapshot destiné à la branche poc-dgx poussée sur Gitea pour cloner le DGX.
Scan anti-secret : clean. graphify (repo embarqué) exclu.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

agent_v0/server_v1/stream_processor.py

@@ -2486,30 +2486,25 @@ class StreamProcessor:
             from core.models.workflow_graph import Workflow
 
             count = 0
-            # Charger les workflows du dossier racine (rétrocompatibilité)
-            for wf_file in sorted(workflows_dir.glob("*.json")):
+            workflow_files = sorted(
+                workflows_dir.rglob("*.json"),
+                key=lambda p: (
+                    len(p.relative_to(workflows_dir).parts),
+                    str(p.relative_to(workflows_dir)),
+                ),
+            )
+
+            for wf_file in workflow_files:
                 try:
                     wf = Workflow.load_from_file(wf_file)
+                    rel_parts = wf_file.relative_to(workflows_dir).parts
+                    if len(rel_parts) > 1 and not hasattr(wf, '_machine_id'):
+                        wf._machine_id = rel_parts[0]
                     self._workflows[wf.workflow_id] = wf
                     count += 1
                 except Exception as e:
                     logger.warning(f"Impossible de charger {wf_file.name}: {e}")
 
-            # Charger les workflows des sous-dossiers par machine
-            for machine_dir in sorted(workflows_dir.iterdir()):
-                if not machine_dir.is_dir():
-                    continue
-                for wf_file in sorted(machine_dir.glob("*.json")):
-                    try:
-                        wf = Workflow.load_from_file(wf_file)
-                        # Stocker le machine_id dans les métadonnées du workflow
-                        if not hasattr(wf, '_machine_id'):
-                            wf._machine_id = machine_dir.name
-                        self._workflows[wf.workflow_id] = wf
-                        count += 1
-                    except Exception as e:
-                        logger.warning(f"Impossible de charger {wf_file.name}: {e}")
-
             if count:
                 logger.info(f"{count} workflow(s) chargé(s) depuis {workflows_dir}")
         except ImportError: