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https://github.com/hiyouga/LLaMA-Factory.git
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[data] bailing template v2 & openai data converter (#9112)
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wangshaofei
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@ -11,7 +11,7 @@
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import json
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import os
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from abc import abstractmethod
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from dataclasses import dataclass
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@ -227,9 +227,151 @@ class SharegptDatasetConverter(DatasetConverter):
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return output
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@dataclass
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class OpenAIDatasetConverter(DatasetConverter):
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def __call__(self, example: dict[str, Any]) -> dict[str, Any]:
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tag_mapping = {
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self.dataset_attr.user_tag: Role.USER.value,
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self.dataset_attr.assistant_tag: Role.ASSISTANT.value,
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self.dataset_attr.observation_tag: Role.OBSERVATION.value,
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self.dataset_attr.function_tag: Role.FUNCTION.value,
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self.dataset_attr.system_tag: Role.SYSTEM.value,
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}
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messages = example[self.dataset_attr.messages]
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if (
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self.dataset_attr.system_tag
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and len(messages) != 0
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and messages[0][self.dataset_attr.role_tag] == self.dataset_attr.system_tag
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):
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system = messages[0][self.dataset_attr.content_tag]
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messages = messages[1:]
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else:
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system = example.get(self.dataset_attr.system, "") if self.dataset_attr.system else ""
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aligned_messages = []
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tool_responses = []
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broken_data = False
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for turn_idx, message in enumerate(messages):
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role = message[self.dataset_attr.role_tag]
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content = message[self.dataset_attr.content_tag]
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if role in [self.dataset_attr.assistant_tag, self.dataset_attr.function_tag]:
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if "tool_calls" in message and len(message['tool_calls']) > 0:
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tool_calls_list = [tool['function'] for tool in message['tool_calls']]
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content = json.dumps(tool_calls_list, ensure_ascii=False)
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role = self.dataset_attr.function_tag
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if role == self.dataset_attr.observation_tag:
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tool_responses.append(content)
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continue
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elif len(tool_responses) > 0:
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_content = "\n</tool_response>\n<tool_response>\n".join(tool_responses)
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aligned_messages.append(
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{
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"role": Role.OBSERVATION.value,
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"content": _content,
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}
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)
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tool_responses = []
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aligned_messages.append(
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{
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"role": tag_mapping[role],
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"content": content,
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}
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)
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odd_tags = (Role.USER.value, Role.OBSERVATION.value)
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even_tags = (Role.ASSISTANT.value, Role.FUNCTION.value)
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accept_tags = (odd_tags, even_tags)
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for turn_idx, message in enumerate(aligned_messages):
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if message["role"] not in accept_tags[turn_idx % 2]:
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logger.warning_rank0(f"Invalid role tag in {messages}.")
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broken_data = True
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break
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if (not self.dataset_attr.ranking and len(aligned_messages) % 2 != 0) or (
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self.dataset_attr.ranking and len(aligned_messages) % 2 == 0
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):
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logger.warning_rank0(f"Invalid message count in {messages}.")
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broken_data = True
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if broken_data:
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logger.warning_rank0("Skipping this abnormal example.")
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prompt, response = [], []
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elif self.dataset_attr.kto_tag and isinstance(example[self.dataset_attr.kto_tag], bool): # kto example
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prompt = aligned_messages[:-1]
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response = aligned_messages[-1:]
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if example[self.dataset_attr.kto_tag]:
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response = response + [{"role": Role.ASSISTANT.value, "content": ""}]
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else:
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response = [{"role": Role.ASSISTANT.value, "content": ""}] + response
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elif (
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self.dataset_attr.ranking
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and isinstance(example[self.dataset_attr.chosen], dict)
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and isinstance(example[self.dataset_attr.rejected], dict)
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): # pairwise example
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chosen = example[self.dataset_attr.chosen]
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rejected = example[self.dataset_attr.rejected]
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if (
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chosen[self.dataset_attr.role_tag] not in accept_tags[-1]
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or rejected[self.dataset_attr.role_tag] not in accept_tags[-1]
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):
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logger.warning_rank0(f"Invalid role tag in {[chosen, rejected]}.")
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broken_data = True
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prompt = aligned_messages
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response = [
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{
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"role": tag_mapping[chosen[self.dataset_attr.role_tag]],
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"content": chosen[self.dataset_attr.content_tag],
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},
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{
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"role": tag_mapping[rejected[self.dataset_attr.role_tag]],
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"content": rejected[self.dataset_attr.content_tag],
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},
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]
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else: # normal example
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prompt = aligned_messages[:-1]
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response = aligned_messages[-1:]
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tools = example.get(self.dataset_attr.tools, "") if self.dataset_attr.tools else ""
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if isinstance(tools, dict) or isinstance(tools, list):
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tools = json.dumps(tools, ensure_ascii=False)
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short_system_prompt = 'detailed thinking off'
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if not system:
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if not tools:
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system = short_system_prompt
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else:
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pass
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else:
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if not tools:
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if 'detailed thinking on' in system or 'detailed thinking off' in system:
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pass
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else:
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system += '\n' + short_system_prompt
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else:
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system += '\n'
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output = {
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"_prompt": prompt,
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"_response": response,
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"_system": system,
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"_tools": tools,
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"_images": self._find_medias(example[self.dataset_attr.images]) if self.dataset_attr.images else None,
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"_videos": self._find_medias(example[self.dataset_attr.videos]) if self.dataset_attr.videos else None,
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"_audios": self._find_medias(example[self.dataset_attr.audios]) if self.dataset_attr.audios else None,
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}
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return output
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DATASET_CONVERTERS = {
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"alpaca": AlpacaDatasetConverter,
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"sharegpt": SharegptDatasetConverter,
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"openai": OpenAIDatasetConverter,
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}
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@ -679,6 +679,21 @@ register_template(
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)
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register_template(
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name="bailing_v2",
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format_user=StringFormatter(slots=["<role>HUMAN</role>{{content}}<|role_end|><role>ASSISTANT</role>"]),
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format_system=StringFormatter(slots=["<role>SYSTEM</role>{{content}}<|role_end|>"]),
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format_assistant=StringFormatter(slots=["{{content}}<|role_end|>"]),
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format_observation=StringFormatter(
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slots=["<role>OBSERVATION</role>\n<tool_response>\n{{content}}\n</tool_response><|role_end|><role>ASSISTANT</role>"]
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),
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format_function=FunctionFormatter(slots=["{{content}}<|role_end|>"], tool_format="ling"),
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format_tools=ToolFormatter(tool_format="ling"),
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stop_words=["<|endoftext|>"],
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efficient_eos=True,
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)
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register_template(
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name="belle",
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format_user=StringFormatter(slots=["Human: {{content}}\n\nBelle: "]),
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@ -79,6 +79,15 @@ SEED_TOOL_PROMPT = (
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)
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LING_TOOL_PROMPT = (
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"# Tools\n\nYou may call one or more functions to assist with the user query.\n\n"
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"You are provided with function signatures within <tools></tools> XML tags:\n<tools>{tool_text}"
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"\n</tools>\n\nFor each function call, return a json object with function name and arguments within "
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"""<tool_call></tool_call> XML tags:\n<tool_call>\n{{"name": <function-name>, """
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""""arguments": <args-json-object>}}\n</tool_call>"""
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)
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@dataclass
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class ToolUtils(ABC):
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"""Base class for tool utilities."""
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@ -406,6 +415,20 @@ class SeedToolUtils(ToolUtils):
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return results
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class LingToolUtils(QwenToolUtils):
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r"""Ling v2 tool using template."""
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@override
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@staticmethod
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def tool_formatter(tools: list[dict[str, Any]]) -> str:
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tool_text = ""
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for tool in tools:
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wrapped_tool = tool if tool.get("type") == "function" else {"type": "function", "function": tool}
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tool_text += "\n" + json.dumps(wrapped_tool, ensure_ascii=False)
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return LING_TOOL_PROMPT.format(tool_text=tool_text) + "\n" + "detailed thinking off"
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TOOLS = {
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"default": DefaultToolUtils(),
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"glm4": GLM4ToolUtils(),
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@ -414,6 +437,7 @@ TOOLS = {
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"qwen": QwenToolUtils(),
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"glm4_moe": GLM4MOEToolUtils(),
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"seed_oss": SeedToolUtils(),
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"ling": LingToolUtils(),
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}
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