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[Feature] add tool parser (#3518)

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* [Feature] Pass through the `chat_template_kwargs` to the data processing module (#3421)

* fix chat_template_args

* fix args

* add offline

* add offline

* fix

* fix

* fix default enable_thinking value

* fix default enable_thinking value

* modify condition

* Revert "modify condition"

This reverts commit 26430bdeb1.

* fix unit test

* add Tool Parser (#3272)

* add tool-parser

* add tool-parser

* add tool parser

* add tool parser

* fix

* add offline

* add offline

* fix

* parsers:tool&reasoning

* 修改tool parser名称·

* update

* fix reasoning-parser

* add requirements

* fix finish reason

* fix

* fix reasoning-parser

* fix

* fix

* fix

* fix

* fix

---------

Co-authored-by: zhuzixuan <zhuzixuan@baidu.com>

* [Feature] add tool parser (#3483)

* add tool parser

* add x1 enable_thinking

* restart ci

* fix vl reasoning parser

* modify call style

* modify call style

* add offline enablethinking

* fix completion

* fix

* fix unit test

* fix unit test

* fix unit test

* fix vl reasoning parser

* fix vl reasoning parser

* fix unit test

---------

Co-authored-by: zhuzixuan <zhuzixuan@baidu.com>
This commit is contained in:
luukunn
2025-08-22 11:14:35 +08:00
committed by GitHub
parent d97aab25bc
commit 4a9c04a746
31 changed files with 1289 additions and 70 deletions
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54
fastdeploy/input/ernie_processor.py
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@@ -43,13 +43,14 @@ class ErnieProcessor(BaseDataProcessor):
pad_token_id (int): 存储填充符号的token ID。
"""
def __init__(self, model_name_or_path, reasoning_parser_obj=None):
def __init__(self, model_name_or_path, reasoning_parser_obj=None, tool_parser_obj=None):
self.model_name_or_path = model_name_or_path
data_processor_logger.info(f"model_name_or_path: {model_name_or_path}")
self._init_config()
self.decode_status = dict()
self.tool_parser_dict = dict()
self.thinking_parser_dict = dict()
self._load_tokenizer()
data_processor_logger.info(
@@ -61,6 +62,7 @@ class ErnieProcessor(BaseDataProcessor):
self.eos_token_id_len = len(self.eos_token_ids)
self.pad_token_id = self.get_pad_id()
self.reasoning_parser = None
self.tool_parser_obj = tool_parser_obj
if reasoning_parser_obj:
self.reasoning_parser = reasoning_parser_obj(self.tokenizer)
@@ -133,6 +135,8 @@ class ErnieProcessor(BaseDataProcessor):
request.set("temperature", 1)
if request.get("top_p") < _SAMPLING_EPS:
request.set("top_p", _SAMPLING_EPS)
if self.reasoning_parser and self.reasoning_parser.__class__.__name__ == "ErnieX1ReasoningParser":
request.enable_thinking = True
data_processor_logger.info(f"Processed request {request}")
return request
@@ -194,6 +198,8 @@ class ErnieProcessor(BaseDataProcessor):
request["temperature"] = 1
if request.get("top_p") < _SAMPLING_EPS:
request["top_p"] = _SAMPLING_EPS
if self.reasoning_parser and self.reasoning_parser.__class__.__name__ == "ErnieX1ReasoningParser":
request["enable_thinking"] = True
data_processor_logger.info(f"Processed request {request}")
return request
@@ -221,6 +227,12 @@ class ErnieProcessor(BaseDataProcessor):
response_dict.outputs.reasoning_content = reasoning_content
else:
response_dict.outputs.text = full_text
if self.tool_parser_obj:
tool_parser = self.tool_parser_obj(self.tokenizer)
tool_call_info = tool_parser.extract_tool_calls(full_text, response_dict)
if tool_call_info.tools_called:
response_dict.outputs.tool_calls = tool_call_info.tool_calls
response_dict.outputs.text = tool_call_info.content
data_processor_logger.info(f"req_id:{req_id}, token)ids: {token_ids}")
if response_dict.outputs.text == "" and response_dict.outputs.reasoning_content == "":
return None
@@ -261,12 +273,20 @@ class ErnieProcessor(BaseDataProcessor):
delta_text, _, previous_texts = self.ids2tokens(token_ids, req_id)
if is_end:
full_text = previous_texts + delta_text
if enable_thinking and self.reasoning_parser:
if self.reasoning_parser and (
enable_thinking or self.reasoning_parser.__class__.__name__ == "ErnieX1ReasoningParser"
):
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:
response_dict["outputs"]["text"] = full_text
if self.tool_parser_obj:
tool_parser = self.tool_parser_obj(self.tokenizer)
tool_call_info = tool_parser.extract_tool_calls(full_text, response_dict)
if tool_call_info.tools_called:
response_dict["outputs"]["tool_call"] = tool_call_info.tool_calls
response_dict["outputs"]["text"] = tool_call_info.content
response_dict["outputs"]["raw_prediction"] = full_text
data_processor_logger.info(f"req_id:{req_id}, decode_status: {self.decode_status[req_id]}")
del self.decode_status[req_id]
@@ -292,8 +312,10 @@ class ErnieProcessor(BaseDataProcessor):
token_ids = token_ids[:-1]
delta_text, previous_token_ids, previous_texts = self.ids2tokens(token_ids, req_id)
response_dict["outputs"]["raw_prediction"] = delta_text
if enable_thinking and self.reasoning_parser:
reasoning_content, text = self.reasoning_parser.extract_reasoning_content_streaming(
if self.reasoning_parser and (
enable_thinking or self.reasoning_parser.__class__.__name__ == "ErnieX1ReasoningParser"
):
reasoning_delta_message = self.reasoning_parser.extract_reasoning_content_streaming(
previous_texts,
previous_texts + delta_text,
delta_text,
@@ -301,14 +323,28 @@ class ErnieProcessor(BaseDataProcessor):
previous_token_ids + token_ids,
token_ids,
)
response_dict["outputs"]["text"] = text
response_dict["outputs"]["reasoning_content"] = reasoning_content
else:
response_dict["outputs"]["text"] = delta_text
response_dict["outputs"]["raw_prediction"] = delta_text
response_dict["outputs"]["delta_message"] = reasoning_delta_message
if self.tool_parser_obj:
if req_id not in self.tool_parser_dict:
self.tool_parser_dict[req_id] = self.tool_parser_obj(self.tokenizer)
tool_parser = self.tool_parser_dict[req_id]
tool_call_delta_message = tool_parser.extract_tool_calls_streaming(
previous_texts,
previous_texts + delta_text,
delta_text,
previous_token_ids,
previous_token_ids + token_ids,
token_ids,
response_dict,
)
if tool_call_delta_message is None or tool_call_delta_message.tool_calls:
response_dict["outputs"]["delta_message"] = tool_call_delta_message
response_dict["outputs"]["text"] = delta_text
if is_end:
data_processor_logger.info(f"req_id:{req_id}, decode_status: {self.decode_status[req_id]}")
del self.decode_status[req_id]
if req_id in self.tool_parser_dict:
del self.tool_parser_dict[req_id]
return response_dict
def messages2ids(self, request_or_messages):