Set Gemma 2 2B MLX as default local model and add --mlx-model flag

README.md

@@ -35,6 +35,7 @@ Useful flags:
 
 ```bash
 ./talk --llm-engine apple             # macOS on-device LLM model (default)
+./talk --mlx-model mlx-community/gemma-2-2b-it-4bit  # specify any local MLX model
 ./talk --llm-engine claude            # Claude Code CLI engine
 ./talk --list-devices                # see microphones and speakers
 ./talk --list-voices                 # see macOS system voices

apple_llm.py

@@ -92,7 +92,7 @@ class MacOSLLM(FrameProcessor):
     def __init__(
         self,
         *,
-        model: str = "mlx-community/Llama-3.2-1B-Instruct-4bit",
+        model: str = "mlx-community/gemma-2-2b-it-4bit",
         system_prompt: str | None = None,
         observer=None,
         **kwargs,
@@ -194,20 +194,20 @@ class MacOSLLM(FrameProcessor):
                 loop = asyncio.get_running_loop()
                 def _gen():
                     from mlx_lm import generate
+                    from mlx_lm.sample_utils import make_sampler
                     # Keep history concise to avoid context drift and repetition
                     recent_history = self._history[-8:]
                     messages = [{"role": "system", "content": self._system_prompt}] + recent_history
                     prompt = self._mlx_tokenizer.apply_chat_template(
                         messages, add_generation_prompt=True, tokenize=False
                     )
+                    sampler = make_sampler(temp=0.7)
                     return generate(
                         self._mlx_model,
                         self._mlx_tokenizer,
                         prompt=prompt,
                         max_tokens=150,
-                        temp=0.7,
-                        repetition_penalty=1.2,
-                        repetition_context_size=30,
+                        sampler=sampler,
                         verbose=False,
                     )
 

bot.py

@@ -157,6 +157,11 @@ def parse_args() -> argparse.Namespace:
         default="apple",
         help="LLM engine to use: apple/macos for native on-device macOS LLM, claude for Claude Code.",
     )
+    parser.add_argument(
+        "--mlx-model",
+        default="mlx-community/gemma-2-2b-it-4bit",
+        help="MLX model repo or path for local macOS execution (e.g. mlx-community/gemma-2-2b-it-4bit).",
+    )
     parser.add_argument(
         "--claude-model",
         default=DEFAULT_CLAUDE_MODEL,
@@ -490,7 +495,7 @@ def build_llm(args: argparse.Namespace, vocabulary=None, brain=None, observer=No
         logger.info(f"LLM: macOS native model ({reason})")
         personality = read_personality(args.cwd) or "You are a helpful macOS voice assistant."
         system_prompt = personality + "\n\n" + VOICE_STYLE
-        return MacOSLLM(system_prompt=system_prompt, observer=observer)
+        return MacOSLLM(model=args.mlx_model, system_prompt=system_prompt, observer=observer)
 
     logger.info("LLM: Claude Code")
     return ClaudeCodeLLM(