Fix: Update VulkanBackend method signatures to match base class

- Added repeat_penalty, presence_penalty, frequency_penalty params to generate() and generate_stream()
- Changed from **kwargs to explicit parameters to match base class abstract methods

This fixes the TypeError when calling VulkanBackend.generate_stream() with extra params.

codai/backends/vulkan.py

@@ -536,7 +536,10 @@ class VulkanBackend(ModelBackend):
         temperature: float = 0.7,
         top_p: float = 1.0,
         stop: Optional[List[str]] = None,
-        grammar: Optional[str] = None
+        grammar: Optional[str] = None,
+        repeat_penalty: float = 1.0,
+        presence_penalty: float = 0.0,
+        frequency_penalty: float = 0.0
     ) -> str:
         """Generate text non-streaming.
         
@@ -547,6 +550,9 @@ class VulkanBackend(ModelBackend):
             top_p: Top-p sampling
             stop: Stop sequences
             grammar: Optional GBNF grammar string for constrained generation
+            repeat_penalty: Repetition penalty (1.0 = no penalty)
+            presence_penalty: Presence penalty
+            frequency_penalty: Frequency penalty
             
         Returns:
             Generated text
@@ -628,13 +634,27 @@ class VulkanBackend(ModelBackend):
     async def generate_stream(
         self,
         prompt: str,
-        **kwargs
+        max_tokens: Optional[int] = None,
+        temperature: float = 0.7,
+        top_p: float = 1.0,
+        stop: Optional[List[str]] = None,
+        grammar: Optional[str] = None,
+        repeat_penalty: float = 1.0,
+        presence_penalty: float = 0.0,
+        frequency_penalty: float = 0.0
     ) -> AsyncIterator[str]:
         """Generate text with streaming.
         
         Args:
             prompt: Input prompt (or messages for chat)
-            **kwargs: Generation parameters
+            max_tokens: Maximum tokens to generate
+            temperature: Sampling temperature
+            top_p: Top-p sampling
+            stop: Stop sequences
+            grammar: Optional GBNF grammar string
+            repeat_penalty: Repetition penalty (1.0 = no penalty)
+            presence_penalty: Presence penalty
+            frequency_penalty: Frequency penalty
             
         Yields:
             Generated text chunks
@@ -647,15 +667,15 @@ class VulkanBackend(ModelBackend):
             prompt = self._apply_chat_template(prompt, add_generation_prompt=True)
         
         # Set defaults
-        max_tokens = kwargs.get('max_tokens', 256)
-        temperature = kwargs.get('temperature', 0.7)
-        top_p = kwargs.get('top_p', 0.9)
-        top_k = kwargs.get('top_k', 40)
-        repeat_penalty = kwargs.get('repeat_penalty', 1.1)
-        grammar = kwargs.get('grammar', None)
+        max_tokens = max_tokens if max_tokens is not None else 256
+        temperature = temperature if temperature is not None else 0.7
+        top_p = top_p if top_p is not None else 0.9
+        top_k = 40
+        repeat_penalty = repeat_penalty if repeat_penalty is not None else 1.1
+        grammar = grammar
         
         # Get stop strings
-        stop = kwargs.get('stop', None)
+        stop = stop if stop is not None else None
         if stop is None:
             # Get default stop tokens based on template
             stop = get_reasoning_stop_tokens(self.chat_template)