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[Fix]fix empty prompt_token_ids,update the parser's triggering condit… (#2891)

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luukunn
2025-07-22 16:13:05 +08:00
committed by GitHub
parent 89a485b69f
commit 920e6b3f60
3 changed files with 28 additions and 9 deletions
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19
fastdeploy/input/text_processor.py
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@@ -239,7 +239,11 @@ class DataProcessor(BaseDataProcessor):
task["enable_thinking"] = kwargs.get("enable_thinking", True)
request.prompt_token_ids = self.messages2ids(task)
else:
raise ValueError(f"The request should have `input_ids`, `text` or `messages`: {request}.")
raise ValueError(
f"The request should have `input_ids`, `text` or `messages`: {request}."
)
if len(request.prompt_token_ids) == 0:
raise ValueError("Invalid input: prompt_token_ids must be a non-empty sequence of token IDs")
if request.get("max_tokens") is None:
request.set(
"max_tokens",
@@ -283,8 +287,11 @@ class DataProcessor(BaseDataProcessor):
raise ValueError("This model does not support chat_template.")
request["prompt_token_ids"] = self.messages2ids(request)
else:
raise ValueError(f"Request must contain 'prompt_token_ids', 'prompt', or 'messages': {request}")
raise ValueError(
f"Request must contain 'prompt_token_ids', 'prompt', or 'messages': {request}"
)
if len(request['prompt_token_ids']) == 0:
raise ValueError("Invalid input: prompt_token_ids must be a non-empty sequence of token IDs")
if request.get("max_tokens") is None:
request["max_tokens"] = max(1, max_model_len - len(request["prompt_token_ids"]))
if request.get("temperature") < _SAMPLING_EPS:
@@ -335,6 +342,7 @@ class DataProcessor(BaseDataProcessor):
Returns:
Dict: response contain text fields
"""
enable_thinking = kwargs.get("enable_thinking")
token_ids = response_dict["outputs"]["token_ids"]
is_end = response_dict["finished"]
req_id = response_dict["request_id"]
@@ -344,8 +352,9 @@ class DataProcessor(BaseDataProcessor):
delta_text, _, previous_texts = self.ids2tokens(token_ids, req_id)
if is_end:
full_text = previous_texts + delta_text
if self.reasoning_parser:
reasoning_content, text = self.reasoning_parser.extract_reasoning_content(full_text, response_dict)
if enable_thinking and self.reasoning_parser:
reasoning_content, text = self.reasoning_parser.extract_reasoning_content(
full_text, response_dict)
response_dict["outputs"]["text"] = text
response_dict["outputs"]["reasoning_content"] = reasoning_content
else: