Merge pull request #1 from bentoml/rick-0604-pr-chat-template

feat: Use community chat template as the source of truth. Fall back to HF tokenizer template

vllm-chat/bentovllm_openai/utils.py

@@ -88,6 +88,7 @@ def openai_endpoints(
                 if self.chat_template is None and chat_template_model_id is not None:
                     from transformers import AutoTokenizer
 
+                    # If no community chat template is provided, use the tokenizer's chat template
                     _tokenizer = AutoTokenizer.from_pretrained(chat_template_model_id)
                     self.chat_template = _tokenizer.chat_template
 

vllm-chat/service.py

@@ -1,25 +1,30 @@
-import uuid
-import json
-import os
-from typing import AsyncGenerator, Union
-from typing_extensions import Annotated
 import functools
+import json
+import logging
+import os
+import uuid
+from typing import AsyncGenerator, Union
 
 import bentoml
-from annotated_types import Ge, Le
-from bentovllm_openai.utils import openai_endpoints
 import yaml
+from annotated_types import Ge, Le
 from bento_constants import CONSTANT_YAML
-
+from bentovllm_openai.utils import openai_endpoints
+from typing_extensions import Annotated
 
 CONSTANTS = yaml.safe_load(CONSTANT_YAML)
 
 ENGINE_CONFIG = CONSTANTS["engine_config"]
 SERVICE_CONFIG = CONSTANTS["service_config"]
+CHAT_TEMPLATE = CONSTANTS.get("chat_template")
+
+logger = logging.getLogger(__name__)
+logger.setLevel(logging.INFO)
 
 
 @functools.lru_cache(maxsize=1)
 def _get_gen_config(community_chat_template: str) -> dict:
+    logger.info(f"Load community_chat_template: {community_chat_template}")
     chat_template_path = os.path.join(
         os.path.dirname(__file__), "chat_templates", "chat_templates"
     )
@@ -37,17 +42,19 @@ def _get_gen_config(community_chat_template: str) -> dict:
 
 @openai_endpoints(
     served_model_names=[ENGINE_CONFIG["model"]],
+    chat_template=_get_gen_config(CHAT_TEMPLATE)["template"] if CHAT_TEMPLATE else None,
     chat_template_model_id=ENGINE_CONFIG["model"],
 )
 @bentoml.service(**SERVICE_CONFIG)
 class VLLM:
     def __init__(self) -> None:
-        from vllm import AsyncEngineArgs, AsyncLLMEngine
         from transformers import AutoTokenizer
+        from vllm import AsyncEngineArgs, AsyncLLMEngine
 
         ENGINE_ARGS = AsyncEngineArgs(**ENGINE_CONFIG)
         self.engine = AsyncLLMEngine.from_engine_args(ENGINE_ARGS)
         self.tokenizer = AutoTokenizer.from_pretrained(ENGINE_CONFIG["model"])
+        logger.info(f"VLLM service initialized with model: {ENGINE_CONFIG['model']}")
 
     @bentoml.api
     async def generate(
@@ -94,7 +101,7 @@ class VLLM:
         """
         from vllm import SamplingParams
 
-        if CONSTANTS.get("chat_template"):  # community chat template
+        if CHAT_TEMPLATE:  # community chat template
             gen_config = _get_gen_config(CONSTANTS["chat_template"])
             if not stop:
                 if gen_config["stop_str"]: