feat(model): Proxy model support count token (#996)

dbgpt/model/proxy/llms/chatgpt.py

@@ -92,11 +92,11 @@ def _initialize_openai_v1(params: ProxyModelParameters):
 
 
 def __convert_2_gpt_messages(messages: List[ModelMessage]):
-    chat_round = 0
     gpt_messages = []
     last_usr_message = ""
     system_messages = []
 
+    # TODO: We can't change message order in low level
     for message in messages:
         if message.role == ModelMessageRoleType.HUMAN or message.role == "user":
             last_usr_message = message.content

dbgpt/model/proxy/llms/proxy_model.py

@@ -1,9 +1,36 @@
+from __future__ import annotations
+
+from typing import Union, List, Optional, TYPE_CHECKING
+import logging
 from dbgpt.model.parameter import ProxyModelParameters
+from dbgpt.model.utils.token_utils import ProxyTokenizerWrapper
+
+if TYPE_CHECKING:
+    from dbgpt.core.interface.message import ModelMessage, BaseMessage
+
+logger = logging.getLogger(__name__)
 
 
 class ProxyModel:
     def __init__(self, model_params: ProxyModelParameters) -> None:
         self._model_params = model_params
+        self._tokenizer = ProxyTokenizerWrapper()
 
     def get_params(self) -> ProxyModelParameters:
         return self._model_params
+
+    def count_token(
+        self,
+        messages: Union[str, BaseMessage, ModelMessage, List[ModelMessage]],
+        model_name: Optional[int] = None,
+    ) -> int:
+        """Count token of given messages
+
+        Args:
+            messages (Union[str, BaseMessage, ModelMessage, List[ModelMessage]]): messages to count token
+            model_name (Optional[int], optional): model name. Defaults to None.
+
+        Returns:
+            int: token count, -1 if failed
+        """
+        return self._tokenizer.count_token(messages, model_name)