first

speech_to_speech/arguments_classes/language_model_base_arguments.py

@@ -0,0 +1,46 @@
+from dataclasses import dataclass, field
+
+
+@dataclass
+class LanguageModelBaseArguments:
+    model_name: str = field(
+        default="Qwen/Qwen3-4B-Instruct-2507",
+        metadata={"help": "The pretrained language model to use."},
+    )
+    user_role: str = field(
+        default="user",
+        metadata={"help": "Role assigned to the user in the chat context. Default is 'user'."},
+    )
+    init_chat_role: str = field(
+        default="system",
+        metadata={"help": "Initial role for setting up the chat context. Default is 'system'."},
+    )
+    init_chat_prompt: str = field(
+        default="You are a helpful and friendly AI assistant. You are polite, respectful, and aim to provide concise responses of less than 20 words.",
+        metadata={"help": "The initial chat prompt to establish context for the language model."},
+    )
+    chat_size: int = field(
+        default=30,
+        metadata={"help": "Number of interactions assistant-user to keep for the chat."},
+    )
+    stream_batch_sentences: int = field(
+        default=3,
+        metadata={
+            "help": "Number of sentences to accumulate before yielding a batch during streaming. "
+            "Set to 1 for sentence-by-sentence streaming. Default is 3."
+        },
+    )
+    enable_lang_prompt: bool = field(
+        default=False,
+        metadata={
+            "help": "When True, append a user message instructing the model to reply in the detected/selected "
+            "language (e.g. 'Please reply to my message in French.'). Default is False."
+        },
+    )
+    compact_history: bool = field(
+        default=True,
+        metadata={
+            "help": "When True, summarize older turns in the background once the chat exceeds chat_size, "
+            "instead of synchronously evicting them. Adds an extra LLM call per compaction. Default is True."
+        },
+    )