refactor: remove LLM_MODEL env var dependency — config.yaml is sole source of truth

Model selection now comes exclusively from config.yaml (set via
'hermes model' or 'hermes setup'). The LLM_MODEL env var is no longer
read or written anywhere in production code.

Why: env vars are per-process/per-user and would conflict in
multi-agent or multi-tenant setups. Config.yaml is file-based and
can be scoped per-user or eventually per-session.

Changes:
- cli.py: Read model from CLI_CONFIG only, not LLM_MODEL/OPENAI_MODEL
- hermes_cli/auth.py: _save_model_choice() no longer writes LLM_MODEL
  to .env
- hermes_cli/setup.py: Remove 12 save_env_value('LLM_MODEL', ...)
  calls from all provider setup flows
- gateway/run.py: Remove LLM_MODEL fallback (HERMES_MODEL still works
  for gateway process runtime)
- cron/scheduler.py: Same
- agent/auxiliary_client.py: Remove LLM_MODEL from custom endpoint
  model detection

hermes_cli/auth.py

@@ -1671,8 +1671,12 @@ def _prompt_model_selection(model_ids: List[str], current_model: str = "") -> Op
 
 
 def _save_model_choice(model_id: str) -> None:
-    """Save the selected model to config.yaml and .env."""
-    from hermes_cli.config import save_config, load_config, save_env_value
+    """Save the selected model to config.yaml (single source of truth).
+
+    The model is stored in config.yaml only — NOT in .env.  This avoids
+    conflicts in multi-agent setups where env vars would stomp each other.
+    """
+    from hermes_cli.config import save_config, load_config
 
     config = load_config()
     # Always use dict format so provider/base_url can be stored alongside
@@ -1681,7 +1685,6 @@ def _save_model_choice(model_id: str) -> None:
     else:
         config["model"] = {"default": model_id}
     save_config(config)
-    save_env_value("LLM_MODEL", model_id)
 
 
 def login_command(args) -> None:

hermes_cli/setup.py

@@ -681,7 +681,6 @@ def setup_model_provider(config: dict):
             save_env_value("OPENAI_API_KEY", api_key)
         if model_name:
             config['model'] = model_name
-            save_env_value("LLM_MODEL", model_name)
 
         # Save provider and base_url to config.yaml so the gateway and CLI
         # both resolve the correct provider without relying on env-var heuristics.
@@ -913,7 +912,6 @@ def setup_model_provider(config: dict):
             custom = prompt(f"  Model name (Enter to keep '{current_model}')")
             if custom:
                 config['model'] = custom
-                save_env_value("LLM_MODEL", custom)
         elif selected_provider == "openai-codex":
             from hermes_cli.codex_models import get_codex_model_ids
             codex_models = get_codex_model_ids()
@@ -927,12 +925,10 @@ def setup_model_provider(config: dict):
             model_idx = prompt_choice("Select default model:", model_choices, default_codex)
             if model_idx < len(codex_models):
                 config['model'] = codex_models[model_idx]
-                save_env_value("LLM_MODEL", codex_models[model_idx])
             elif model_idx == len(codex_models):
                 custom = prompt("Enter model name")
                 if custom:
                     config['model'] = custom
-                    save_env_value("LLM_MODEL", custom)
             _update_config_for_provider("openai-codex", DEFAULT_CODEX_BASE_URL)
         elif selected_provider == "zai":
             # Coding Plan endpoints don't have GLM-5
@@ -950,12 +946,10 @@ def setup_model_provider(config: dict):
 
             if model_idx < len(zai_models):
                 config['model'] = zai_models[model_idx]
-                save_env_value("LLM_MODEL", zai_models[model_idx])
             elif model_idx == len(zai_models):
                 custom = prompt("Enter model name")
                 if custom:
                     config['model'] = custom
-                    save_env_value("LLM_MODEL", custom)
             # else: keep current
         elif selected_provider == "kimi-coding":
             kimi_models = ["kimi-k2.5", "kimi-k2-thinking", "kimi-k2-turbo-preview"]
@@ -968,12 +962,10 @@ def setup_model_provider(config: dict):
 
             if model_idx < len(kimi_models):
                 config['model'] = kimi_models[model_idx]
-                save_env_value("LLM_MODEL", kimi_models[model_idx])
             elif model_idx == len(kimi_models):
                 custom = prompt("Enter model name")
                 if custom:
                     config['model'] = custom
-                    save_env_value("LLM_MODEL", custom)
             # else: keep current
         elif selected_provider in ("minimax", "minimax-cn"):
             minimax_models = ["MiniMax-M2.5", "MiniMax-M2.5-highspeed", "MiniMax-M2.1"]
@@ -986,12 +978,10 @@ def setup_model_provider(config: dict):
 
             if model_idx < len(minimax_models):
                 config['model'] = minimax_models[model_idx]
-                save_env_value("LLM_MODEL", minimax_models[model_idx])
             elif model_idx == len(minimax_models):
                 custom = prompt("Enter model name")
                 if custom:
                     config['model'] = custom
-                    save_env_value("LLM_MODEL", custom)
             # else: keep current
         else:
             # Static list for OpenRouter / fallback (from canonical list)
@@ -1008,12 +998,10 @@ def setup_model_provider(config: dict):
 
             if model_idx < len(ids):
                 config['model'] = ids[model_idx]
-                save_env_value("LLM_MODEL", ids[model_idx])
             elif model_idx == len(ids):  # Custom
                 custom = prompt("Enter model name (e.g., anthropic/claude-opus-4.6)")
                 if custom:
                     config['model'] = custom
-                    save_env_value("LLM_MODEL", custom)
             # else: Keep current
 
         _final_model = config.get('model', '')