feat: OpenAI-compatible orchestrator + backend auto-routing

- openai_orchestrator.py — new ReAct tool loop engine for any
  OpenAI-compatible endpoint (OpenRouter, Open WebUI, Ollama, LiteLLM);
  model handles both tool loop and final response, no Claude handoff needed
- tools/__init__.py — auto-derive OpenAI JSON Schema from existing Gemini
  FunctionDeclarations so tool definitions have a single source of truth
- routers/orchestrator.py — route to openai_orchestrator when model registry
  "orchestrator" role resolves to a local_openai type host
- routers/chat.py — pass role to _backend_label(); fix fallback_used logic
  (only meaningful for explicit backend overrides, not auto-routing)
- static/app.js — add null/"auto" to backend cycle; fetch local model hint
  without overriding the auto default on page load
- model_registry.py — _normalize() back-fills host_type on old registry files
- requirements.txt — add openai>=1.0.0
- ARCH__BACKENDS.md — document OpenAI-compat backend and routing logic

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

cortex/routers/orchestrator.py

@@ -22,7 +22,9 @@ from auth_utils import get_user_gemini_key
 from config import settings
 from context_loader import load_context
 from persona import set_context, validate as validate_persona
+import model_registry
 import orchestrator_engine
+import openai_orchestrator
 
 logger = logging.getLogger(__name__)
 router = APIRouter(prefix="/orchestrate", tags=["orchestrator"])
@@ -157,13 +159,25 @@ async def _run_job(job_id: str, req: OrchestrateRequest, user: str) -> None:
         history = load_session(session_id)
         session_messages = history or None
 
-        result = await orchestrator_engine.run(
-            task=req.task,
-            system_prompt=system_prompt,
-            session_messages=session_messages,
-            respond_with_claude=req.respond_with_claude,
-            gemini_api_key=get_user_gemini_key(user),
-        )
+        # Choose engine based on the orchestrator role in the model registry
+        orch_model = model_registry.get_model_for_role(user, "orchestrator")
+
+        if orch_model and orch_model.get("type") == "local_openai":
+            result = await openai_orchestrator.run(
+                task=req.task,
+                system_prompt=system_prompt,
+                session_messages=session_messages,
+                model_cfg=orch_model,
+                respond_with_final=req.respond_with_claude,
+            )
+        else:
+            result = await orchestrator_engine.run(
+                task=req.task,
+                system_prompt=system_prompt,
+                session_messages=session_messages,
+                respond_with_claude=req.respond_with_claude,
+                gemini_api_key=get_user_gemini_key(user),
+            )
 
         # Save the turn to the session store so it survives a page refresh
         history.append({"role": "user", "content": req.task})