feat(llm): enhance model features handling with pattern matching

strix/llm/llm.py

@@ -2,6 +2,7 @@ import logging
 import os
 from dataclasses import dataclass
 from enum import Enum
+from fnmatch import fnmatch
 from pathlib import Path
 from typing import Any
 
@@ -45,27 +46,14 @@ class LLMRequestFailedError(Exception):
         self.details = details
 
 
-MODELS_WITHOUT_STOP_WORDS = [
-    "gpt-5",
-    "gpt-5-mini",
-    "gpt-5-nano",
-    "o1-mini",
-    "o1-preview",
-    "o1",
-    "o1-2024-12-17",
-    "o3",
-    "o3-2025-04-16",
-    "o3-mini-2025-01-31",
-    "o3-mini",
-    "o4-mini",
-    "o4-mini-2025-04-16",
+SUPPORTS_STOP_WORDS_FALSE_PATTERNS: list[str] = [
+    "o1*",
     "grok-4-0709",
+    "grok-code-fast-1",
+    "deepseek-r1-0528*",
 ]
 
-REASONING_EFFORT_SUPPORTED_MODELS = [
-    "gpt-5",
-    "gpt-5-mini",
-    "gpt-5-nano",
+REASONING_EFFORT_PATTERNS: list[str] = [
     "o1-2024-12-17",
     "o1",
     "o3",
@@ -76,9 +64,39 @@ REASONING_EFFORT_SUPPORTED_MODELS = [
     "o4-mini-2025-04-16",
     "gemini-2.5-flash",
     "gemini-2.5-pro",
+    "gpt-5*",
+    "deepseek-r1-0528*",
+    "claude-sonnet-4-5*",
+    "claude-haiku-4-5*",
 ]
 
 
+def normalize_model_name(model: str) -> str:
+    raw = (model or "").strip().lower()
+    if "/" in raw:
+        name = raw.split("/")[-1]
+        if ":" in name:
+            name = name.split(":", 1)[0]
+    else:
+        name = raw
+    if name.endswith("-gguf"):
+        name = name[: -len("-gguf")]
+    return name
+
+
+def model_matches(model: str, patterns: list[str]) -> bool:
+    raw = (model or "").strip().lower()
+    name = normalize_model_name(model)
+    for pat in patterns:
+        pat_l = pat.lower()
+        if "/" in pat_l:
+            if fnmatch(raw, pat_l):
+                return True
+        elif fnmatch(name, pat_l):
+            return True
+    return False
+
+
 class StepRole(str, Enum):
     AGENT = "agent"
     USER = "user"
@@ -332,27 +350,13 @@ class LLM:
         if not self.config.model_name:
             return True
 
-        actual_model_name = self.config.model_name.split("/")[-1].lower()
-        model_name_lower = self.config.model_name.lower()
-
-        return not any(
-            actual_model_name == unsupported_model.lower()
-            or model_name_lower == unsupported_model.lower()
-            for unsupported_model in MODELS_WITHOUT_STOP_WORDS
-        )
+        return not model_matches(self.config.model_name, SUPPORTS_STOP_WORDS_FALSE_PATTERNS)
 
     def _should_include_reasoning_effort(self) -> bool:
         if not self.config.model_name:
             return False
 
-        actual_model_name = self.config.model_name.split("/")[-1].lower()
-        model_name_lower = self.config.model_name.lower()
-
-        return any(
-            actual_model_name == supported_model.lower()
-            or model_name_lower == supported_model.lower()
-            for supported_model in REASONING_EFFORT_SUPPORTED_MODELS
-        )
+        return model_matches(self.config.model_name, REASONING_EFFORT_PATTERNS)
 
     async def _make_request(
         self,
@@ -361,7 +365,6 @@ class LLM:
         completion_args: dict[str, Any] = {
             "model": self.config.model_name,
             "messages": messages,
-            "temperature": self.config.temperature,
             "timeout": self.config.timeout,
         }