[Feature] add tool parser (#3518)

* [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>

fastdeploy/reasoning/ernie_x1_reasoning_parsers.py

@@ -0,0 +1,162 @@
+# Copyright (c) 2025  PaddlePaddle Authors. All Rights Reserved.
+#
+#
+from collections.abc import Sequence
+from typing import Tuple, Union
+
+from fastdeploy.entrypoints.openai.protocol import ChatCompletionRequest, DeltaMessage
+from fastdeploy.reasoning import ReasoningParser, ReasoningParserManager
+
+#
+#
+# Licensed under the Apache License, Version 2.0 (the "License"
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+@ReasoningParserManager.register_module("ernie_x1")
+class ErnieX1ReasoningParser(ReasoningParser):
+    """
+    Reasoning parser for ernie_x1 model with stricter boundary checking.
+
+    This implementation follows the user's proposed approach:
+    1. For thinking content: waits for \n then checks for </think> tag
+    2. For response content: checks for <response> tag first, then waits for \n
+    3. Handles newlines in content more precisely
+    """
+
+    def __init__(self, tokenizer):
+        super().__init__(tokenizer)
+        self.think_end_token = "</think>"
+        self.response_start_token = "<response>"
+        self.response_end_token = "</response>"
+        self.tool_call_start_token = "<tool_call>"
+        self.tool_call_end_token = "</tool_call>"
+
+        if not self.model_tokenizer:
+            raise ValueError("The model tokenizer must be passed to the ReasoningParser constructor.")
+
+        self.think_end_token_id = self.vocab.get("</think>")
+        if self.think_end_token_id is None:
+            raise RuntimeError("Could not find think end token id in tokenizer vocabulary")
+        self.tool_call_start_token_id = self.vocab.get("<tool_call>")
+
+    def is_reasoning_end(self, input_ids: list[int]) -> bool:
+        return self.tool_call_start_token_id in input_ids
+
+    def extract_reasoning_content_streaming(
+        self,
+        previous_text: str,
+        current_text: str,
+        delta_text: str,
+        previous_token_ids: Sequence[int],
+        current_token_ids: Sequence[int],
+        delta_token_ids: Sequence[int],
+    ) -> Union[DeltaMessage, None]:
+        """
+        根据用户需求实现的流式解析方法:
+        1. 初始内容都视为思考内容，返回delta_text,""
+        2. 当遇到\n时检查后续是否是</think>
+        3. 如果直接遇到</think>也结束思考
+        4. 思考结束后检查是<response>还是<tool_call>
+        5. 对于<response>内容，处理各种边界条件
+        """
+        if len(delta_token_ids) == 1 and delta_token_ids[0] == self.think_end_token_id:
+            return None
+        # 思考阶段处理
+        if not previous_text.endswith(self.think_end_token) and self.think_end_token not in previous_text:
+            # 如果遇到\n，暂时不返回，等待下一个delta_text
+            if delta_text == "\n":
+                return None
+            # 如果前一个是\n且当前是</think>，结束思考
+            elif previous_text.endswith("\n") and delta_text.startswith(self.think_end_token):
+                return None
+            # 如果直接遇到</think>也结束思考
+            elif delta_text.startswith(self.think_end_token):
+                return None
+            # 否则继续返回思考内容
+            return DeltaMessage(reasoning_content=delta_text)
+
+        # 思考结束后检查是tool_call还是response
+        remaining_text = previous_text + delta_text
+        after_think = remaining_text[remaining_text.find(self.think_end_token) + len(self.think_end_token) :]
+        after_think = after_think.lstrip("\n")  # 跳过think后的换行
+
+        # 处理tool_call情况
+        if after_think.startswith(self.tool_call_start_token):
+            return None
+
+        # 处理response情况
+        if after_think.startswith(self.response_start_token):
+            # 遇到<response>标签时不立即返回
+            if delta_text == self.response_start_token:
+                return None
+            # 遇到<response>后的换行符也不立即返回
+            elif delta_text == "\n" and previous_text.endswith(self.response_start_token):
+                return None
+            # 处理回复内容中的换行符
+            if delta_text == "\n":
+                return None
+            # 如果前一个是\n且当前是</response>，结束回复
+            elif previous_text.endswith("\n") and delta_text == self.response_end_token:
+                return None
+            # 如果直接遇到</response>也结束回复
+            elif delta_text == self.response_end_token:
+                return None
+            # 其他情况返回实际内容
+            else:
+                return DeltaMessage(content=delta_text)
+
+        # 默认情况不返回内容
+        return None
+
+    def extract_reasoning_content(self, model_output: str, request: ChatCompletionRequest) -> Tuple[str, str]:
+        """
+        Batch version of the enhanced parser.
+        Modified to preserve newlines in both reasoning and response content,
+        only removing the single newline before closing tags.
+        """
+        reasoning_content = ""
+        response_content = ""
+
+        think_end_pos = model_output.find(self.think_end_token)
+        if think_end_pos != -1:
+            # Extract thinking content - only remove the last newline before </think>
+            reasoning_content = model_output[:think_end_pos]
+            if think_end_pos > 0 and reasoning_content[-1] == "\n":
+                reasoning_content = reasoning_content[:-1]
+
+            remaining = model_output[think_end_pos + len(self.think_end_token) :]
+
+            # Skip newlines after </think>
+            remaining = remaining.lstrip("\n")
+
+            # Check for response or tool_call
+            if remaining.startswith(self.response_start_token):
+                response_pos = len(self.response_start_token)
+                remaining = remaining[response_pos:].lstrip("\n")
+                response_end_pos = remaining.find(self.response_end_token)
+                if response_end_pos != -1:
+                    # Only strip the last newline before </response>, not all
+                    if response_end_pos > 0 and remaining[response_end_pos - 1] == "\n":
+                        response_content = remaining[: response_end_pos - 1]
+                    else:
+                        response_content = remaining[:response_end_pos]
+                else:
+                    # If no </response> found, return the rest as response content
+                    response_content = remaining
+            elif remaining.startswith(self.tool_call_start_token):
+                pass  # No response content
+        else:
+            # No thinking content found, return the whole input as reasoning
+            reasoning_content = model_output
+            response_content = ""
+        return reasoning_content, response_content