【Fix】 remove text_after_process & raw_prediction (#4421)

* remove text_after_process &  raw_prediction

* remove text_after_process &  raw_prediction
This commit is contained in:
LiqinruiG
2025-10-16 19:00:18 +08:00
committed by GitHub
parent 8f77adc381
commit 4251ac5e95
20 changed files with 169 additions and 105 deletions
+10 -14
View File
@@ -118,14 +118,14 @@ class OpenAIServingChat:
else:
request_id = f"chatcmpl-{uuid.uuid4()}"
api_server_logger.info(f"create chat completion request: {request_id}")
text_after_process = None
prompt_tokens = None
try:
current_req_dict = request.to_dict_for_infer(request_id)
if "chat_template" not in current_req_dict:
current_req_dict["chat_template"] = self.chat_template
current_req_dict["arrival_time"] = time.time()
prompt_token_ids = await self.engine_client.format_and_add_data(current_req_dict)
text_after_process = current_req_dict.get("text_after_process")
prompt_tokens = current_req_dict.get("prompt_tokens")
if isinstance(prompt_token_ids, np.ndarray):
prompt_token_ids = prompt_token_ids.tolist()
except ParameterError as e:
@@ -143,12 +143,12 @@ class OpenAIServingChat:
if request.stream:
return self.chat_completion_stream_generator(
request, request_id, request.model, prompt_token_ids, text_after_process
request, request_id, request.model, prompt_token_ids, prompt_tokens
)
else:
try:
return await self.chat_completion_full_generator(
request, request_id, request.model, prompt_token_ids, text_after_process
request, request_id, request.model, prompt_token_ids, prompt_tokens
)
except Exception as e:
error_msg = f"request[{request_id}]full generator error: {str(e)}, {str(traceback.format_exc())}"
@@ -175,7 +175,7 @@ class OpenAIServingChat:
request_id: str,
model_name: str,
prompt_token_ids: list(),
text_after_process: str,
prompt_tokens: str,
):
"""
Streaming chat completion generator.
@@ -289,8 +289,7 @@ class OpenAIServingChat:
if request.return_token_ids:
choice.delta.prompt_token_ids = list(prompt_token_ids)
choice.delta.text_after_process = text_after_process
choice.delta.prompt_tokens = text_after_process
choice.delta.prompt_tokens = prompt_tokens
chunk = ChatCompletionStreamResponse(
id=request_id,
object=chunk_object_type,
@@ -368,8 +367,7 @@ class OpenAIServingChat:
choice.delta.multimodal_content[0]["completion_token_ids"] = list(output["token_ids"])
else:
choice.delta.completion_token_ids = list(output["token_ids"])
choice.delta.raw_prediction = output.get("raw_prediction")
choice.delta.completion_tokens = output.get("raw_prediction")
choice.delta.completion_tokens = output.get("completion_tokens")
if include_continuous_usage:
chunk.usage = UsageInfo(
prompt_tokens=num_prompt_tokens,
@@ -419,7 +417,7 @@ class OpenAIServingChat:
request_id: str,
model_name: str,
prompt_token_ids: list(),
text_after_process: str,
prompt_tokens: str,
):
"""
Full chat completion generator.
@@ -509,10 +507,8 @@ class OpenAIServingChat:
tool_calls=output.get("tool_call"),
prompt_token_ids=prompt_token_ids if request.return_token_ids else None,
completion_token_ids=completion_token_ids if request.return_token_ids else None,
text_after_process=text_after_process if request.return_token_ids else None,
prompt_tokens=text_after_process if request.return_token_ids else None,
raw_prediction=output.get("raw_prediction") if request.return_token_ids else None,
completion_tokens=output.get("raw_prediction") if request.return_token_ids else None,
prompt_tokens=prompt_tokens if request.return_token_ids else None,
completion_tokens=output.get("completion_tokens") if request.return_token_ids else None,
)
if response_processor.enable_multimodal_content():