feat(model): Support gemma-2 model (#1675)

dbgpt/model/adapter/base.py

@@ -112,6 +112,31 @@ class LLMModelAdapter(ABC):
         """Load model and tokenizer"""
         raise NotImplementedError
 
+    def parse_max_length(self, model, tokenizer) -> Optional[int]:
+        """Parse the max_length of the model.
+
+        Returns:
+            Optional[int]: The max_length of the model
+        """
+        if not (tokenizer or model):
+            return None
+        try:
+            model_max_length = None
+            if tokenizer and hasattr(tokenizer, "model_max_length"):
+                model_max_length = tokenizer.model_max_length
+            if model_max_length and model_max_length < 100000000:
+                # Can't be too large
+                return model_max_length
+            if model and hasattr(model, "config"):
+                model_config = model.config
+                if hasattr(model_config, "max_sequence_length"):
+                    return model_config.max_sequence_length
+                if hasattr(model_config, "max_position_embeddings"):
+                    return model_config.max_position_embeddings
+            return None
+        except Exception:
+            return None
+
     def load_from_params(self, params):
         """Load the model and tokenizer according to the given parameters"""
         raise NotImplementedError