refactor: Centralize strix model resolution with separate API and capability names

- Replace fragile prefix matching with explicit STRIX_MODEL_MAP
- Add resolve_strix_model() returning (api_model, canonical_model)
- api_model (openai/ prefix) for API calls to OpenAI-compatible Strix API
- canonical_model (actual provider name) for litellm capability lookups
- Centralize resolution in LLMConfig instead of scattered call sites

strix/llm/llm.py

@@ -14,7 +14,6 @@ from strix.llm.memory_compressor import MemoryCompressor
 from strix.llm.utils import (
     _truncate_to_first_function,
     fix_incomplete_tool_call,
-    get_litellm_model_name,
     parse_tool_invocations,
 )
 from strix.skills import load_skills
@@ -64,7 +63,7 @@ class LLM:
         self.agent_name = agent_name
         self.agent_id: str | None = None
         self._total_stats = RequestStats()
-        self.memory_compressor = MemoryCompressor(model_name=config.model_name)
+        self.memory_compressor = MemoryCompressor(model_name=config.litellm_model)
         self.system_prompt = self._load_system_prompt(agent_name)
 
         reasoning = Config.get("strix_reasoning_effort")
@@ -190,16 +189,12 @@ class LLM:
 
         return messages
 
-    def _get_litellm_model_name(self) -> str:
-        model = self.config.model_name  # Validated non-empty in LLMConfig.__init__
-        return get_litellm_model_name(model) or model  # type: ignore[return-value]
-
     def _build_completion_args(self, messages: list[dict[str, Any]]) -> dict[str, Any]:
         if not self._supports_vision():
             messages = self._strip_images(messages)
 
         args: dict[str, Any] = {
-            "model": self._get_litellm_model_name(),
+            "model": self.config.litellm_model,
             "messages": messages,
             "timeout": self.config.timeout,
             "stream_options": {"include_usage": True},
@@ -264,7 +259,7 @@ class LLM:
             if direct_cost is not None:
                 return float(direct_cost)
         try:
-            return completion_cost(response, model=self._get_litellm_model_name()) or 0.0
+            return completion_cost(response, model=self.config.canonical_model) or 0.0
         except Exception:  # noqa: BLE001
             return 0.0
 
@@ -287,13 +282,13 @@ class LLM:
 
     def _supports_vision(self) -> bool:
         try:
-            return bool(supports_vision(model=self._get_litellm_model_name()))
+            return bool(supports_vision(model=self.config.canonical_model))
         except Exception:  # noqa: BLE001
             return False
 
     def _supports_reasoning(self) -> bool:
         try:
-            return bool(supports_reasoning(model=self._get_litellm_model_name()))
+            return bool(supports_reasoning(model=self.config.canonical_model))
         except Exception:  # noqa: BLE001
             return False
 
@@ -314,7 +309,7 @@ class LLM:
         return result
 
     def _add_cache_control(self, messages: list[dict[str, Any]]) -> list[dict[str, Any]]:
-        if not messages or not supports_prompt_caching(self._get_litellm_model_name()):
+        if not messages or not supports_prompt_caching(self.config.canonical_model):
             return messages
 
         result = list(messages)