Fix added tokens config with sensible filter

python/sglang/srt/lora/lora.py

@@ -128,8 +128,8 @@ def _process_weight(self, name: str, loaded_weight: torch.Tensor):
             # added/extra token emb
             self.added_tokens_embeddings[name] = loaded_weight.cpu()
             assert loaded_weight.shape[0] == self.config.lora_added_tokens_size, (
-                f"LoRA adapter {self.uid} has extra_vocab_size {self.config.extra_vocab_size} specified in the config, "
-                f"but the loaded weight has {loaded_weight.shape[0]} extra vocab size"
+                f"LoRA adapter {self.uid} has lora_added_tokens_size {self.config.lora_added_tokens_size} specified in the config, "
+                f"but the loaded weight '{name}' has shape {loaded_weight.shape[0]} in first dimension"
             )
 
     def _normalize_weights(self):

python/sglang/srt/lora/lora_config.py

@@ -13,18 +13,22 @@
 # ==============================================================================
 
 import json
+import logging
 import os
 from typing import Dict, Optional
 
 from huggingface_hub import snapshot_download
 
+logger = logging.getLogger(__name__)
+
 
 class LoRAConfig:
     def __init__(
         self,
         path: Optional[str] = None,
         config_dict: Optional[Dict] = None,
         added_tokens_config: Optional[Dict] = None,
+        base_vocab_size: Optional[int] = None,
     ) -> None:
         self.path = path
 
@@ -38,17 +42,41 @@ def __init__(
         self.target_modules = self.hf_config["target_modules"]
         self.r = self.hf_config["r"]
         self.lora_alpha = self.hf_config["lora_alpha"]
+
+        # Filter fake added tokens: tokens with ID < base_vocab_size are already
+        # part of the base vocabulary and should not be treated as added tokens.
+        # This commonly happens when added_tokens.json is copied from the base
+        # model's tokenizer.
+        if self.added_tokens_config and base_vocab_size is not None:
+            self.added_tokens_config = {
+                token: token_id
+                for token, token_id in self.added_tokens_config.items()
+                if token_id >= base_vocab_size
+            }
+
         self.lora_added_tokens_size = (
             len(self.added_tokens_config) if self.added_tokens_config is not None else 0
         )
 
+        if self.lora_added_tokens_size > 0:
+            raise ValueError(
+                f"LoRA adapter has {self.lora_added_tokens_size} added tokens, "
+                f"but added tokens are not supported yet. "
+                f"Added tokens: {self.added_tokens_config}"
+            )
+
     @classmethod
     def from_dict(
         cls,
         config_dict: Dict,
         added_tokens_config: Optional[Dict] = None,
+        base_vocab_size: Optional[int] = None,
     ) -> "LoRAConfig":
-        return cls(config_dict=config_dict, added_tokens_config=added_tokens_config)
+        return cls(
+            config_dict=config_dict,
+            added_tokens_config=added_tokens_config,
+            base_vocab_size=base_vocab_size,
+        )
 
     def get_lora_config(self, dummy=False):
         if dummy:
@@ -82,9 +110,5 @@ def get_added_tokens_config(self):
             with open(added_tokens_path, "r") as f:
                 return json.load(f)
         except json.JSONDecodeError as e:
-            # Log warning but don't crash if JSON is malformed
-            import logging
-
-            logger = logging.getLogger(__name__)
             logger.warning(f"Failed to parse added_tokens.json: {e}")
             return None

python/sglang/srt/lora/lora_manager.py

@@ -134,7 +134,10 @@ def load_lora_adapter(self, lora_ref: LoRARef) -> LoRAUpdateOutput:
 
         try:
             # load configs
-            new_adapter = LoRAConfig(lora_ref.lora_path)
+            new_adapter = LoRAConfig(
+                lora_ref.lora_path,
+                base_vocab_size=self.base_hf_config.vocab_size,
+            )
             self.validate_new_adapter(new_adapter, lora_ref)
             self.configs[lora_ref.lora_id] = new_adapter
 
@@ -560,7 +563,11 @@ def load_lora_adapter_from_tensors(
         ), f"LoRA adapter with ID {lora_ref.lora_id} is already loaded. This should have been verified before request is sent to the backend."
 
         try:
-            new_adapter = LoRAConfig.from_dict(config_dict, added_tokens_config)
+            new_adapter = LoRAConfig.from_dict(
+                config_dict,
+                added_tokens_config,
+                base_vocab_size=self.base_hf_config.vocab_size,
+            )
             self.validate_new_adapter(new_adapter, lora_ref)
             self.configs[lora_ref.lora_id] = new_adapter