Adding full support for gpt-5 models (#5)

strix/llm/llm.py

@@ -28,6 +28,39 @@ api_key = os.getenv("LLM_API_KEY")
 if api_key:
     litellm.api_key = api_key
 
+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",
+    "grok-4-0709",
+]
+
+REASONING_EFFORT_SUPPORTED_MODELS = [
+    "gpt-5",
+    "gpt-5-mini",
+    "gpt-5-nano",
+    "o1-2024-12-17",
+    "o1",
+    "o3",
+    "o3-2025-04-16",
+    "o3-mini-2025-01-31",
+    "o3-mini",
+    "o4-mini",
+    "o4-mini-2025-04-16",
+    "gemini-2.5-flash",
+    "gemini-2.5-pro",
+]
+
 
 class StepRole(str, Enum):
     AGENT = "agent"
@@ -240,17 +273,48 @@ class LLM:
             "supported": supports_prompt_caching(self.config.model_name),
         }
 
+    def _should_include_stop_param(self) -> bool:
+        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
+        )
+
+    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
+        )
+
     async def _make_request(
         self,
         messages: list[dict[str, Any]],
     ) -> ModelResponse:
-        completion_args = {
+        completion_args: dict[str, Any] = {
             "model": self.config.model_name,
             "messages": messages,
             "temperature": self.config.temperature,
-            "stop": ["</function>"],
         }
 
+        if self._should_include_stop_param():
+            completion_args["stop"] = ["</function>"]
+
+        if self._should_include_reasoning_effort():
+            completion_args["reasoning_effort"] = "medium"
+
         queue = get_global_queue()
         response = await queue.make_request(completion_args)