feat: implement robust multi-tier text input architecture and ADB diagnostics

- Android Text Input & IME Normalization:
  - Implement progressive 3-tier input architecture in AndroidAdbDriver and AndroidDeviceController:
    - Tier 1 (Primary): Zero-dependency clipboard injection + KEYCODE_PASTE (immune to IME Pinyin interception, full Unicode/Emoji support, preserves multiline formatting).
    - Tier 2 (Broadcast): Base64 broadcast injection when ADBKeyboard is active.
    - Tier 3 (Fallback): Native ADB physical keyevent fallback.
  - Add literal newline normalization (\r\n, \n, \r) to prevent JSON escape string corruption (e.g. '10086\n' -> '10086、n').
  - Add set_clipboard method to UIAutomatorClient without auxiliary APK requirements.

- Diagnostics & System Probes:
  - Add adb_keys diagnostics probe for ADB key auth checks.
  - Integrate diagnostics into CLI doctor command.

- Admin Console & Showcase UI:
  - Improve model service and system router in admin console.
  - Enhance workspace stream view and session state in showcase UI.

apps/admin_console/services/model_service.py

@@ -17,26 +17,12 @@ from typing import Any
 
 
 class ModelService:
-    """Service handling model profile detection and metadata formatting."""
+    """Service handling agent architecture profile detection and metadata formatting."""
 
     @staticmethod
     def get_active_model_info(profile: str | None = None) -> dict[str, str]:
-        if profile:
-            p_lower = str(profile).lower()
-            if "pro" in p_lower:
-                return {
-                    "name": "Pro",
-                    "id": "gemini-3.7-pro",
-                    "provider": "google",
-                }
-            elif "flash" in p_lower:
-                return {
-                    "name": "Flash",
-                    "id": "gemini-3.7-flash",
-                    "provider": "google",
-                }
-
-        model_name = "Flash"
+        """Return active architecture and underlying LLM model configuration."""
+        # 1. Determine underlying LLM model and provider from config
         model_id = "gemini-3.7-flash"
         provider = "google"
         try:
@@ -44,18 +30,31 @@ class ModelService:
 
             llm_cfg = parse_llm_config()
             if llm_cfg and llm_cfg.operator:
-                op_model = str(llm_cfg.operator.model).lower()
                 provider = str(llm_cfg.operator.provider)
-                model_id = llm_cfg.operator.model
-                if "pro" in op_model:
-                    model_name = "Pro"
-                elif "flash" in op_model:
-                    model_name = "Flash"
-                else:
-                    model_name = llm_cfg.operator.model.capitalize()
+                model_id = str(llm_cfg.operator.model)
+            elif llm_cfg and llm_cfg.default:
+                provider = str(llm_cfg.default.provider)
+                model_id = str(llm_cfg.default.model)
         except Exception:
             pass
-        return {"name": model_name, "id": model_id, "provider": provider}
+
+        # 2. Determine agent architecture name (Flash vs Pro)
+        arch_name = "Flash"
+        if profile:
+            p_lower = str(profile).lower()
+            if "pro" in p_lower:
+                arch_name = "Pro"
+            elif "flash" in p_lower:
+                arch_name = "Flash"
+            else:
+                arch_name = str(profile).capitalize()
+
+        return {
+            "name": arch_name,
+            "id": model_id,
+            "provider": provider,
+            "architecture": f"ARTEMIS {arch_name}",
+        }
 
     @staticmethod
     def resolve_session_profile(
@@ -64,6 +63,7 @@ class ModelService:
         running_profile: str | None = None,
         agent_names: list[str] | None = None,
     ) -> str | None:
+        """Resolve the Artemis agent architecture profile ('flash' or 'pro') for a session."""
         sess_profile = None
         d_info_raw = row_dict.get("device_info")
         if d_info_raw:
@@ -98,7 +98,7 @@ class ModelService:
             if any("flashrunner" in name for name in agent_names_lower):
                 return "flash"
 
-        # Check LLM traces for agent name or model overrides
+        # Check LLM traces for agent name
         if llm_trace_payloads:
             for tr_payload in llm_trace_payloads:
                 if tr_payload:
@@ -115,16 +115,6 @@ class ModelService:
                                 for x in ("planner", "validator", "operator", "checker")
                             ):
                                 return "pro"
-
-                            m_str = str(p_obj.get("model") or p_obj.get("model_name") or "").lower()
-                            if (
-                                "gemini-3.7-pro" in m_str
-                                or "gemini-3.6-pro" in m_str
-                                or "gemini-1.5-pro" in m_str
-                                or "gpt-4" in m_str
-                                or "claude" in m_str
-                            ):
-                                return "pro"
                     except Exception:
                         pass