feat(oai refactor): Replace openai_api with entrypoints/openai (#7351)

Co-authored-by: Jin Pan <jpan236@wisc.edu>

python/sglang/srt/entrypoints/engine.py

@@ -37,7 +37,6 @@ setattr(threading, "_register_atexit", lambda *args, **kwargs: None)
 import torch
 import uvloop
 
-from sglang.srt.code_completion_parser import load_completion_template_for_openai_api
 from sglang.srt.entrypoints.EngineBase import EngineBase
 from sglang.srt.managers.data_parallel_controller import (
     run_data_parallel_controller_process,
@@ -58,11 +57,8 @@ from sglang.srt.managers.io_struct import (
     UpdateWeightsFromTensorReqInput,
 )
 from sglang.srt.managers.scheduler import run_scheduler_process
+from sglang.srt.managers.template_manager import TemplateManager
 from sglang.srt.managers.tokenizer_manager import TokenizerManager
-from sglang.srt.openai_api.adapter import (
-    guess_chat_template_name_from_model_path,
-    load_chat_template_for_openai_api,
-)
 from sglang.srt.server_args import PortArgs, ServerArgs
 from sglang.srt.torch_memory_saver_adapter import TorchMemorySaverAdapter
 from sglang.srt.utils import (
@@ -123,12 +119,13 @@ class Engine(EngineBase):
         logger.info(f"{server_args=}")
 
         # Launch subprocesses
-        tokenizer_manager, scheduler_info = _launch_subprocesses(
+        tokenizer_manager, template_manager, scheduler_info = _launch_subprocesses(
             server_args=server_args,
             port_args=port_args,
         )
         self.server_args = server_args
         self.tokenizer_manager = tokenizer_manager
+        self.template_manager = template_manager
         self.scheduler_info = scheduler_info
 
         context = zmq.Context(2)
@@ -647,7 +644,7 @@ def _set_envs_and_config(server_args: ServerArgs):
 
 def _launch_subprocesses(
     server_args: ServerArgs, port_args: Optional[PortArgs] = None
-) -> Tuple[TokenizerManager, Dict]:
+) -> Tuple[TokenizerManager, TemplateManager, Dict]:
     """
     Launch the TokenizerManager in the main process, the Scheduler in a subprocess, and the DetokenizerManager in another subprocess.
     """
@@ -732,7 +729,7 @@ def _launch_subprocesses(
 
         if os.getenv("SGLANG_BLOCK_NONZERO_RANK_CHILDREN") == "0":
             # When using `Engine` as a Python API, we don't want to block here.
-            return None, None
+            return None, None, None
 
         launch_dummy_health_check_server(server_args.host, server_args.port)
 
@@ -741,7 +738,7 @@ def _launch_subprocesses(
             logger.error(
                 f"Scheduler or DataParallelController {proc.pid} terminated with {proc.exitcode}"
             )
-        return None, None
+        return None, None, None
 
     # Launch detokenizer process
     detoken_proc = mp.Process(
@@ -755,15 +752,15 @@ def _launch_subprocesses(
 
     # Launch tokenizer process
     tokenizer_manager = TokenizerManager(server_args, port_args)
-    if server_args.chat_template:
-        load_chat_template_for_openai_api(
-            tokenizer_manager, server_args.chat_template, server_args.model_path
-        )
-    else:
-        guess_chat_template_name_from_model_path(server_args.model_path)
 
-    if server_args.completion_template:
-        load_completion_template_for_openai_api(server_args.completion_template)
+    # Initialize templates
+    template_manager = TemplateManager()
+    template_manager.initialize_templates(
+        tokenizer_manager=tokenizer_manager,
+        model_path=server_args.model_path,
+        chat_template=server_args.chat_template,
+        completion_template=server_args.completion_template,
+    )
 
     # Wait for the model to finish loading
     scheduler_infos = []
@@ -787,4 +784,4 @@ def _launch_subprocesses(
     # Assume all schedulers have the same scheduler_info
     scheduler_info = scheduler_infos[0]
     tokenizer_manager.max_req_input_len = scheduler_info["max_req_input_len"]
-    return tokenizer_manager, scheduler_info
+    return tokenizer_manager, template_manager, scheduler_info