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Code Issues Actions 6 Packages Projects Releases Wiki Activity

Completion add raw_prediction/text_after_process (#3356)

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memoryCoderC
2025-08-12 23:06:45 +08:00
committed by GitHub
parent 2c0d853067
commit 2d1a4cacdf
7 changed files with 51 additions and 15 deletions
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8
fastdeploy/entrypoints/openai/protocol.py
View File

@@ -126,6 +126,8 @@ class ChatMessage(BaseModel):
tool_calls: Optional[List[DeltaToolCall | ToolCall]] = None
prompt_token_ids: Optional[List[int]] = None
completion_token_ids: Optional[List[int]] = None
text_after_process: Optional[str] = None
raw_prediction: Optional[str] = None
class ChatCompletionResponseChoice(BaseModel):
@@ -183,6 +185,8 @@ class DeltaMessage(BaseModel):
completion_token_ids: Optional[List[int]] = None
reasoning_content: Optional[str] = None
tool_calls: Optional[List[DeltaToolCall | ToolCall]] = None
text_after_process: Optional[str] = None
raw_prediction: Optional[str] = None
class ChatCompletionResponseStreamChoice(BaseModel):
@@ -219,6 +223,8 @@ class CompletionResponseChoice(BaseModel):
text: str
prompt_token_ids: Optional[List[int]] = None
completion_token_ids: Optional[List[int]] = None
text_after_process: Optional[str] = None
raw_prediction: Optional[str] = None
arrival_time: Optional[float] = None
logprobs: Optional[CompletionLogprobs] = None
reasoning_content: Optional[str] = None
@@ -261,6 +267,8 @@ class CompletionResponseStreamChoice(BaseModel):
logprobs: Optional[CompletionLogprobs] = None
prompt_token_ids: Optional[List[int]] = None
completion_token_ids: Optional[List[int]] = None
text_after_process: Optional[str] = None
raw_prediction: Optional[str] = None
reasoning_content: Optional[str] = None
finish_reason: Optional[Literal["stop", "length", "tool_calls"]] = None
tool_calls: Optional[List[DeltaToolCall | ToolCall]] = None

17
fastdeploy/entrypoints/openai/serving_chat.py
View File

@@ -83,11 +83,12 @@ class OpenAIServingChat:
else:
request_id = f"chatcmpl-{uuid.uuid4()}"
api_server_logger.info(f"create chat completion request: {request_id}")
text_after_process = None
try:
current_req_dict = request.to_dict_for_infer(request_id)
current_req_dict["arrival_time"] = time.time()
prompt_token_ids = self.engine_client.format_and_add_data(current_req_dict)
text_after_process = current_req_dict.get("text_after_process")
if isinstance(prompt_token_ids, np.ndarray):
prompt_token_ids = prompt_token_ids.tolist()
except Exception as e:
@@ -104,10 +105,14 @@ class OpenAIServingChat:
return ErrorResponse(code=408, message=f"Request queued time exceed {self.max_waiting_time}")
if request.stream:
return self.chat_completion_stream_generator(request, request_id, request.model, prompt_token_ids)
return self.chat_completion_stream_generator(
request, request_id, request.model, prompt_token_ids, text_after_process
)
else:
try:
return await self.chat_completion_full_generator(request, request_id, request.model, prompt_token_ids)
return await self.chat_completion_full_generator(
request, request_id, request.model, prompt_token_ids, text_after_process
)
except Exception as e:
return ErrorResponse(code=400, message=str(e))
@@ -124,6 +129,7 @@ class OpenAIServingChat:
request_id: str,
model_name: str,
prompt_token_ids: list(),
text_after_process: str,
):
"""
Streaming chat completion generator.
@@ -216,6 +222,7 @@ class OpenAIServingChat:
)
if request.return_token_ids:
choice.delta.prompt_token_ids = list(prompt_token_ids)
choice.delta.text_after_process = text_after_process
chunk = ChatCompletionStreamResponse(
id=request_id,
object=chunk_object_type,
@@ -279,6 +286,7 @@ class OpenAIServingChat:
if request.return_token_ids:
choice.delta.completion_token_ids = list(output["token_ids"])
choice.delta.raw_prediction = output.get("raw_prediction")
if include_continuous_usage:
chunk.usage = UsageInfo(
prompt_tokens=num_prompt_tokens,
@@ -329,6 +337,7 @@ class OpenAIServingChat:
request_id: str,
model_name: str,
prompt_token_ids: list(),
text_after_process: str,
):
"""
Full chat completion generator.
@@ -406,6 +415,8 @@ class OpenAIServingChat:
tool_calls=output.get("tool_call_content"),
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,
raw_prediction=output.get("raw_prediction") if request.return_token_ids else None,
)
logprobs_full_res = None
if logprob_contents:

12
fastdeploy/entrypoints/openai/serving_completion.py
View File

@@ -100,6 +100,7 @@ class OpenAIServingCompletion:
api_server_logger.info(f"start inference for request {num_choices}")
prompt_batched_token_ids = []
text_after_process_list = []
try:
for idx, prompt in enumerate(request_prompts):
request_id_idx = f"{request_id}-{idx}"
@@ -109,6 +110,7 @@ class OpenAIServingCompletion:
prompt_token_ids = self.engine_client.format_and_add_data(current_req_dict)
if isinstance(prompt_token_ids, np.ndarray):
prompt_token_ids = prompt_token_ids.tolist()
text_after_process_list.append(current_req_dict.get("text_after_process"))
prompt_batched_token_ids.append(prompt_token_ids)
except Exception as e:
return ErrorResponse(message=str(e), code=400)
@@ -131,6 +133,7 @@ class OpenAIServingCompletion:
created_time=created_time,
model_name=request.model,
prompt_batched_token_ids=prompt_batched_token_ids,
text_after_process_list=text_after_process_list,
)
else:
try:
@@ -141,6 +144,7 @@ class OpenAIServingCompletion:
created_time=created_time,
model_name=request.model,
prompt_batched_token_ids=prompt_batched_token_ids,
text_after_process_list=text_after_process_list,
)
except Exception as e:
return ErrorResponse(code=400, message=str(e))
@@ -156,6 +160,7 @@ class OpenAIServingCompletion:
created_time: int,
model_name: str,
prompt_batched_token_ids: list(),
text_after_process_list: list(),
):
"""
Process the full completion request with multiple choices.
@@ -225,6 +230,7 @@ class OpenAIServingCompletion:
model_name=model_name,
prompt_batched_token_ids=prompt_batched_token_ids,
completion_batched_token_ids=completion_batched_token_ids,
text_after_process_list=text_after_process_list,
)
except Exception as e:
api_server_logger.error(f"Error in completion_full_generator: {e}", exc_info=True)
@@ -251,6 +257,7 @@ class OpenAIServingCompletion:
created_time: int,
model_name: str,
prompt_batched_token_ids: list(),
text_after_process_list: list(),
):
"""
Process the stream completion request.
@@ -309,6 +316,7 @@ class OpenAIServingCompletion:
index=idx,
text="",
prompt_token_ids=list(prompt_batched_token_ids[idx]),
text_after_process=text_after_process_list[idx],
completion_token_ids=None,
)
],
@@ -337,6 +345,7 @@ class OpenAIServingCompletion:
text=output["text"],
prompt_token_ids=None,
completion_token_ids=output.get("token_ids") if request.return_token_ids else None,
raw_prediction=output.get("raw_prediction") if request.return_token_ids else None,
tool_calls=output.get("tool_call_content"),
reasoning_content=output.get("reasoning_content"),
arrival_time=arrival_time,
@@ -398,6 +407,7 @@ class OpenAIServingCompletion:
model_name: str,
prompt_batched_token_ids: list(),
completion_batched_token_ids: list(),
text_after_process_list: list(),
) -> CompletionResponse:
choices: List[CompletionResponseChoice] = []
num_prompt_tokens = 0
@@ -444,6 +454,8 @@ class OpenAIServingCompletion:
text=output_text,
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,
raw_prediction=output.get("raw_prediction") if request.return_token_ids else None,
text_after_process=text_after_process_list[idx] if request.return_token_ids else None,
reasoning_content=output.get("reasoning_content"),
tool_calls=output.get("tool_call_content"),
logprobs=aggregated_logprobs,